Biogeochemistry of Marine Dissolved Organic Matter
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Biogeochemistry of Marine Dissolved Organic Matter Edited by
Dennis A. Hansell University of Miami Rosenstiel School of Marine and Atmospheric Science Miami, Florida
Craig A. Carlson University of Californian Santa Barbara Santa Barbara, California
/ ^ ACADEMIC PRESS V — ^ An Elsevier Science Imprint Amsterdam Boston London New York Oxford Paris San Diego San Francisco Singapore Sydney Tokyo
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Copyright © 2002 by Elsevier Science (USA) All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Requests for permission to make copies of any part of the work should be mailed to: Permissions Department, Academic Press, 6277 Sea Harbor Drive, Oriando, Florida 32887-6777 Academic Press An Imprint of Elsevier of Elsevier Science 525 B Street, Suite 1900, San Diego, California 92101-4495, USA http://www.academicpress.com Academic Press 32 Jamestown Road, London NWl 7BY, UK http://www.academicpress.com Library of Congress Catalog Card Number: 2001096950 International Standard Book Number: 0-12-323841-2 PRINTED IN THE UNITED STATES OF AMERICA 02 03 04 05 06 07 MM 9 8 7 6 5 4
3 2 1
For the support and balance that only family can provide we dedicate this hook to our beloved spouses Paula and Alison^ and our children Allison and Rachel, and Matthew and Hayden.
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Contents
Contributors Foreword Preface
xiii xv xxi
Chapter 1
Why Dissolved Organics Matter? John I. Hedges I. 11. III. IV. V. VI. VII.
Introduction 1 DOM Research Pre-1970 2 DOM Research in the 1970s 7 DOM Research in the 1980s 11 "New" DON and DOC 13 Why Dissolved Organics Matter 23 What did we Learn? 25 References 27
Chapter 2
Analytical Methods for Total DOM Pools Jonathan H. Sharp I. II. III. IV.
Introduction 35 Dissolved Organic Carbon Analysis Dissolved Organic Nitrogen Analysis Dissolved Organic Phosphorus Analysis
37 45 49
Contents
V. Multielemental Methods 51 VI. TheLimitsof Elemental Analyses 51 VII. The Need for Continual use of Reference Materials References 54
52
Chapter 3
Chemical Composition and Reactivity Ronald Benner
I. Introduction 59 II. Distribution and Chemical Characteristics of Bulk Marine DOM 64 III. Major Topics of Ongoing and Future Research About the CycUng of DOM 80 References 85 Chapter 4
Production and Removal Processes Craig A. Carlson
I. II. III. IV. V. VI.
Introduction 91 DOM Production Processes 92 DOM Removal Processes 116 DOM LabiUty 123 DOM Accumulation 133 Summary 137 References 139
Chapter 5
Dynamics of DON Deborah A. Bronk
I. II. III. IV. V.
Introduction 153 Concentration and Composition of the DON Pool Sources of DON 186 Sinks for DON 207 DON l\imover Times 226
154
ix
Contents VI. Summary References
227 231
Chapter 6
Dynamics of DOP D. M. Karl and K. M. Bjorkman
I. Introduction 250 II. Terms, Definitions, and Concentration Units 253 III. TheEarly Years of Pelagic Marine P-Cycle Research (1884-1955) 258 IV. The Pelagic Marine P-Cycle: Key Pools and Processes V. Sampling, Incubation, Storage, and Analytical Considerations 266 VI. DOP in the Sea: Variations in Space 280 VII. DOP in the Sea: Variations in Time 294 VIII. DOP Pool Characterization 306 IX. DOP Production, Utilization, and Remineralization X. Conclusions and Prospectus 347 References 348
262
334
Chapter 7
Marine Colloids and Trace Metals Mark L Wells
I. II. III. IV. V. VI. VII. VIII. IX. X.
Introduction 367 Definition of Marine Colloids 369 Analytical Methods 372 Metal Content of Marine Colloidal Matter 380 The Chemical Form of Colloidal Metals 385 Particulate-Based Estimates of Colloidal Metal Concentrations 388 Sources of Metal-Complexing Colloidal Ligands 389 Measurement of Colloid Reaction Rates 390 The Biological Availability of Colloidal Bioactive Metals Summary 396 References 397
395
Contents
Chapter 8
Carbon Isotopic Composition of DOM James E. Bauer
I. Introduction 405 II. Conventions and Definitions for Expressing Isotopic Contents of DOC 407 III. Methods for Extracting DOC from Seawater for Isotopic Analysis 413 rV. Measurements and Distributions of 6^^C and A^'^C in Marine DOC 415 V. Applications of ^^^C and A^^C in Marine DOC Cycling Studies 430 VI. Summary and Future Challenges 443 References 446 Chapter 9
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus Kenneth Mopper and David J. Kieber
I. Introduction 456 II. Photochemical Transformation of Riverine and Marsh-Derived DOM Inputs to the Sea 457 III. Impact of Photochemistry on Elemental Cycles 458 IV. Unresolved Questions and Future Research 476
References Appendix 1 Appendix 2 Appendix 3 Appendix 4
479 490 498 500 503
Chapter 10
Chromophoric DOM in the Coastal Environment Neil V. Blough and Rossana Del Vecchio
I. Introduction 509 II. Optical Properties 513 i n . Distribution 532
xi
Contents IV. Sources and Sinks 534 V. Summary and Future Areas of Research References 540
539
Chapter 11
Chromophoric DOM in the Open Ocean Norman B. Nelson and David A. Siegel I. II. III. IV. V.
Introduction 547 Characterization of CDOM 549 Observed CDOM Dynamics 557 Global CDOM Distribution Patterns 561 Relationship Between DOM and CDOM in the Open Ocean 567 VI. Implications for Photochemistry and Photobiology VII. Needs for Future Advances 571 References 573
568
Chapter 12
DOM in the Coastal Zone Gustave Cauzvet I. II. III. IV.
Introduction 579 River Inputs 580 Estuarine Processes 588 Accumulation of DOM in the Coastal Zone and Export Processes 595 V. Conclusions 600 References 602
Chapter 13
Sediment Pore Waters David J. Burdige I. II. III. IV.
Introduction 612 Dissolved Organic Carbon in Sediment Pore Waters Dissolved Organic Nitrogen (DON) 631 DOM Compositional Data 636
614
Contents
V. The Role of Benthic DOM Fluxes in the Ocean Carbon and Nitrogen Cycles 641 VI. The Role of Pore-Water DOM in Sediment Carbon Preservation 648 VII. Conclusions and Suggestions for Future Research 650 Appendix: A Description of the DOM Advection/Diffusion/ Reaction Model 651 References 653 Chapter 14
DOC in the Arctic Ocean LeifG. Anderson
I. Introduction 665 II. Sources of DOC to the Arctic Ocean 667 III. Composition and Distribution of DOC within the Arctic Ocean 674 IV. Summary of Sources and Sinks 679 References 681
Chapter 15
DOC in the Global Ocean Carbon Cycle Dennis A. Hansell
I. II. III. IV. V. VI.
Introduction 685 Distribution of DOC 687 Net Community Production of DOC 697 Contribution of DOC to the Biological Pump Research Priorities 709 Summary 711 References 711
Chapter 16
Modeling DOM Biogeochemistry James R. Christian and Thomas R. Anderson
I. Introduction 717 II. Ecosystem Modeling Studies
719
702
Contents III. Modeling the Role of DOM in Ocean Biogeochemistry IV. Discussion and Conclusions 743 References 747
Index
734
757
Contributors
Numbers in parentheses indicate page numbers on which the authors contributions begin.
Leif G. Anderson (665), Analytical and Marine Chemistry, Goteborg University Goteborg, Sweden Thomas R. Anderson (717), George Deacon Division, Southampton Oceanography Centre, Southampton United Kingdom James E. Bauer (405), School of Marine Science, College of William and Mary, Gloucester Point, Virginia
xiv
Contributors
Ronald Benner (59), Department of Biological Sciences and Marine Science Program, University of South Carolina, Columbia, South Carolina Neil V. Blough and Rossana Del Vecchio (509), Department of Chemistry and Biochemistry, University of Maryland College Park, Maryland Deborah A. Bronk (153), Virginia Institute of Marine Science, College of WilHam and Mary, Gloucester Point, Virginia David J. Burdige (611), Department of Ocean, Earth, and Atmospheric Sciences, Old Dominion University Norfolk, Virginia Craig A. Carlson (91), University of California, Santa Barbara, Department of Ecology, Evolution and Marine Biology, Santa Barbara, California Gustave Cauwet (579), Laboratoire d'Oceanographie Biologique (UMR CNRS 7621), Observatoire Oceanologique, Banyuls sur mer, France James R. Christian (717), Universities Space Research Association, NASA Goddard Space Flight Center, Code 970.2 Greenbelt, Maryland Dennis A. Hansell (685), University of Miami, Division of Marine and Atmospheric Chemistry, Rosenstiel School of Marine and Atmospheric Science, Miami, Florida John I. Hedges (1), School of Oceanography, University of Washington, Seattle, Washington D. M. Karl and K. M. Bjorkman (249), Department of Oceanography, School of Ocean and Earth Science and Technology, University of Hawaii Honolulu, Hawaii David J. Kieber (455), College of Environmental Science and Forestry Chemistry Department, State University of New York Syracuse, New York Kenneth Mopper (455), Department of Chemistry and Biochemistry, Old Dominion University Norfolk, Virginia Norman B. Nelson and David A. Siegel (547), Institute for Computational Earth System Science, University of California, Santa Barbara, Santa Barbara, California Jonathan H. Sharp (35), Graduate College of Marine Studies, University of Delaware, Lewes, Delaware Mark L. Wells (367), School of Marine Sciences, University of Maine, Orono, Maine
Foreword
Few of us really have intuitive concepts of the differences among ocean ecosystems. Ecosystems on land clearly look different from one another - contrast, for example, the outward appearances of deserts and savannas. Yet oligotrophic gyres and continental shelves, the oceanic analogs of these terrestrial systems, look nearly identical to the unaided eye, and we have to look more deeply (sometimes literally) to perceive the differences. Nearly all terrestrial ecosystems rest, physically and functionally, on an organic-rich soil foundation. Dissolved organic matter (DOM) is the soil of the sea - a large, biochemically resistant reservoir of organic matter providing a substrate for life, and a source for nutrient regeneration, ion exchange capacity, light and heat absorption, and so on. Marine DOM, however, is much less conspicuous than terrestrial soil. It is, in fact, nearly invisible. In this book, Hansen and Carlson and the many contributing authors tell the story of making DOM, the soil of the sea, visible. Recently I was asked to provide a list to the International Geosphere-Biosphere Program (IGBP) of the top accomplishments and failures of the Joint Global Ocean Flux Study (JGOFS). I polled hundreds of scientists and students accessible via US JGOFS' e-mail lists and received numerous opinions about both the program's successes and failures. Interestingly, and as syndicated colunmist Dave Barry would say, "I am not making this up," one topic was on both lists - dissolved organic carbon, DOC! This book attests to the success of DOM studies in JGOFS (including carbon, nitrogen and phosphorus), and throughout ocean biogeochemistry over the past decade. Was it also a story of failure? The question is provocative and I want to explore it here, at least briefly. DOM has a long and distinguished history in marine chemistry and biology, dating to the early controversy as to whether or not this apparently large reservoir of organic matter was an important source of nutrition for marine animals (Krogh, 1934; Jorgensen, 1976). Duursma's (1963) monograph on the seasonal dynamics of DOC in the North Sea and North Atlantic revealed that the pool was an active and variable component of the marine ecosystem. The first radiocarbon dating of XV
xvi
Foreword
DOC by Williams et al. (1969) indicated that the vast majority of this globally significant carbon pool was long-lived and refractory - in both the deep as well as surface oceans. By the late 1980's, as JGOFS began to focus on properties of the ocean carbon system, DOC was perceived as uninteresting -just a large, inert pool without much discemable vertical structure or horizontal gradients. I recall Peter LeB. Williams showing me the DOC analyzer he developed. "Here's the world's best instrument for analyzing the ocean's most boring property!", he said. Added to this was controversy over the best analytical approach to quantify the bulk pool, which went back to Krogh and Keys (1934). Given this backdrop, the seminal paper on DOC analysis by Sugimura and Suzuki (1988) was greeted with great surprise and excitement. In demonstrating a new analytical method and some of its early results, they presented oceanic DOC profiles with surface gradients of several lOO's of /JLM and overall very much higher concentrations than revealed by earlier approaches. These findings made DOC interesting in several ways. Marine chemists seeking improvements to the thermodynamic description of the carbonate system in seawater saw in DOC a potential source of additional protolytes (Bradshaw and Brewer, 1988). Peter Brewer, the new Chair of U.S. JGOFS, was particularly energetic in advancing Suzuki's method and a newly recognized role for DOC in the carbon cycle. Perhaps the greatest push for the new, high DOC levels came from modelers. The 3-dimensional ocean modeling community became very interested in a DOM pool that had a longer lifetime than sedimenting particles and could be transported horizontally for long distances. In this behavior they saw the possible answer to the problem of nutrient trapping in models of the equatorial Pacific Ocean. Ray Najjar modeled DOM export to address the problem in his Ph.D. thesis (Najjar et al., 1992). Robbie Toggweiler discussed other aspects of high DOC levels in a still widely cited paper (Toggweiler, 1989). It was clear that a large and influential segment of the ocean community was prepared to embrace these exciting results. Suzuki's results led to upward revisions of the oceanic DOC inventory, and to an explosion of research on marine DOM, its chemistry, analysis and ecology. Yoshimi Suzuki became an overnight celebrity. He participated in the U.S. JGOFS North Atlantic Bloom Experiment, and measured DOC in May 1989 in close conjunction with Ed Peltzer from Brewer's lab at WHOI, again demonstrating high concentrations and spectacular variations in space and time. Perplexingly, there were no known biological processes to maintain variations in euphotic zone DOC stocks of about 1 mole C as found over scales of a few days or a few km. Yet his analyses made on the same cruise established one of the first direct estimates of DOC utilization by bacteria, and resulted in an influential estimate of bacterial growth efficiency (Kirchman et al., 1991). U.S. JGOFS sponsored two workshops, including a "bake-off" (alluding to high-temperature combustion techniques) to validate Suzuki's method (Williams, 1991). Although large segments of the conmiunity wanted the new results to be true, many marine
Foreword
xvii
chemists remained very skeptical. Reporting on the workshop results, Peter M. Williams reported, "Most strikingly, the ranges of variation in the mean DOC concentrations of the same water samples by the same types of DOC analyzer were almost as great as the entire data set... The DOC data from the different seawater analyses plot along three roughly parallel lines until reaching the high extreme of the measured range... and thus do not vary randomly. One explanation for this pattern is that analyses made by different instruments include blanks of varying magnitude." (Williams, 1991, p. 11).
Williams had it right, as was later demonstrated by Benner and Strom (1993) in the special issue of Marine Chemistry reporting the scientific results of the 1991 bake-off workshop. High-temperature, catalytic oxidation techniques for DOC analysis suffered from high instrument blanks that were not easily evaluated or corrected, leading to variable and high offsets in apparent DOC concentrations. In the meantime, Eiichiro Tanoue measured DOC in the same region of the northwestern Pacific assessed earlier by Sugimura and Suzuki (1988), finding much lower concentrations and less pronounced vertical gradients (Tanoue, 1992). In response to these new findings, Suzuki began a reassessment and reanalysis of his original results. In a statement of extraordinary courage and grace he retracted the results that had caused so much excitement (Suzuki, 1993; see also Hedges et al., 1993). Thus, we see in this series of events a scenario familiar in the history of science. An idea, stimulated by technological innovation, was advanced and tested. Great excitement ensued and the new results suggested new solutions to recognized problems. More scientists saw a subject in a new way. But with increased scrutiny, the method was found wanting and the results were ultimately rejected. I think this is the reason some scientists have tended to regard oceanic DOC measurement as a failure... the initial results didn't hold up. To some, Suzuki is the villain of the story, too quick to accept apparently spectacular results without adequate testing. I view the situation differently. As a result of the excitement generated by the original paper, and by Brewer's and others' strong advocacy of it, many others began to think in new ways about DOM in the sea. They wrote proposals and started new research. The technical aspects of DOC analysis were examined in an unprecedented manner, resulting in new instruments with great precision, capable of resolving 1 /xM differences in DOC concentration. There is today a recognized DOC analytical standard. These developments made possible direct detection of bacterial utilization of the bulk DOC pool, thus allowing us to assess the varying lability of the bulk DOM pool, insights expanded upon the results of Barber (1968) and Ogura (1972) a generation earher. Following the idea pursued t>y Najjar and colleagues, DOC eventually became recognized as an important vector of export production (Copin-Montegut and Avril, 1993; Carlson et al., 1994). Increased precision enabled detection of deep-ocean DOC concentration gradients and basin-scale differences in DOC (Hansell and Carlson, 1998), opening its use
xviii
Foreword
as a new geochemical tracer. Although the NABE study lacked reliable DOC data, all subsequent JGOFS studies had successful DOC research components. Oceanic DOM is now recognized as an important component of the biogeochemical system and possibly a barometer of global change (Church et al., 2002). Most importantly, we can today regard marine DOC as a dynamic component in the global carbon cycle. Success or failure? Read this book and be the judge. Hugh W. Ducklow School of Marine Science The College of William and Mary
REFERENCES Barber, R. T. (1968). Dissolved organic carbon from deep waters resists microbial oxidation. Nature 220,274-5. Benner, R. and Strom, M. (1993). A critical evaluation of the analytical blank associated with DOC measurements by high-temperature catalytic oxidation. Mar. Chem. 41,153-60. Bradshaw, A. L. and Brewer, R G. (1988). High precision measurements of alkalinity and total carbon dioxide in seawater by potentiometric titration. 1. Presence of unknown protolyte(s)? Mar. Chem. 23,69-86. Carlson, C. A., Ducklow, H. W. and Michaels, A. F. (1994). Annual flux of dissolved organic carbon from the euphotic zone in the northwestern Sargasso Sea. Nature 371,405^08. Church, M. J., Ducklow, H. W. and Karl, D. M. (2002). Multi-year increases in dissolved organic matter inventories at Station ALOHA in the North Pacific Subtropical Gyre. Limnol. Oceanogr. 47,1-10. Copin-Montegut, G. and Avril, B. (1993). Vertical distribution and temporal variation of dissolved organic carbon in the northwestern Mediterranean Sea. Deep Sea Res. 40, 1963-1972. Duursma, E. K. (1963). The production of dissolved organic matter in the sea, as related to the primary gross production of organic matter. Netherlands Journal of Sea Research 2, 85-94. Hansen, D. A. and Carlson, C. A. (1998). Deep ocean gradients in dissolved organic carbon concentrations. Nature 395, 263-266. Hedges, J., Lee, C. and Wangersky, P. J. (1993). Conmients from the editors on the Suzuki statement. Mar Chem. 41, 289-290. Krogh, A. (1934). Conditions of life in the ocean. Ecol. Monogr 4,421^29. Krogh, A. and Keys, A. B. (1934). Methods for the determination of dissolved organic carbon and nitrogen in sea water. Biol. Bull. 67,132-144. J0rgensen, C. B. (1976). August Putter, August Krogh and modem ideas on the use of dissolved organic matter in the aquatic environment. Biol. Rev. 51, 291-308. Kirchman, D. L., Suzuki, Y., Garside, C. and Ducklow, H. W. (1991). High turnover rates of dissolved organic carbon during a spring phytoplankton bloom. Nature 352,612-^. Najjar, R. G., Sarmiento, J. L. and Toggweiler, J. R. (1992). Downward transport and fate of organic matter in the ocean: simulations with a general ocean circulation model. Global Biogeochem. Cycles 6,45-76. Ogura, N. (1972). Rate and extent of decomposition of dissolved organic matter in the surface water. Mar. Biol. 13, 89-93. Sugimura, Y. and Suzuki, Y. (1988). A high-temperature catalytic oxidation method of non-volatile dissolved organic carbon in seawater by direct injection of liquid samples. Mar. Chem. 14,105-131.
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Suzuki, Y. (1993). On the measurement of DOC and DON in seawater. Mar. Chem. 41, 287-288. Tanoue, E. (1992). Vertical distribution of dissolved organic carbon in the North Pacific as determined by the high temperature catalytic oxidation method. Earth Planet. Sci. Lett. I l l , 201-216. Toggweiler, J. R. (1989). Is the downward dissolved organic matter (DOM) flux important in carbon transport?, In "Productivity of the oceans: present and past" (W. H. Berger, V. S. Smetacek and G. Wefer, Eds.), pp. 65-83, Wiley. Williams, P. M., Oeschger, H. and Kinney, P. (1969). Natural radiocarbon activity of the dissolved organic carbon in the northeast Pacific Ocean. Nature 224,256-258. Williams, P. M. (1991). Scientists and industry reps attend workshop on measuring DOC in natural waters. US JGOFS News 3(1), 1,5,11.
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Preface
Efforts by the ocean science community to understand the cycHng of the major bioactive elements (C, N, P) in the ocean expanded rapidly in the last decade and continues today. The intensive focus on elemental cycling resulted from society's need to determine the role of the ocean in global cHmate change. By the beginning of the 1990's, the fundamentals of the biological processes involved in the transformations of the major elements were identified. The next phase of research required linking the biological processes to the very large oceanic reservoirs of the major elements. Establishing this linkage between processes and reservoirs falls into the discipline of biogeochemistry. One of the Earth's largest bioactive reservoirs of carbon is dissolved organic matter (DOM) in the ocean. With a stock of 700 Pg C in the global ocean, the pool is approximately equal in size to the stock of carbon resident in atmospheric CO2. Prior to the 1990's, this major pool of carbon was primarily evaluated from a geochemical perspective; resolving the composition of the pool was a central goal. With the onset of an enhanced biogeochemical perspective of nutrient cycling, the scientific questions began to rest broadly on the role of DOM in the oceanic C, N and P cycles. To determine the function of DOM in the elemental cycles, vast intellectual and financial capital was expended throughout the 1990's. Central questions were: can we accurately, with community wide consistency, measure the concentrations of dissolved organic matter in the ocean; what are the distributions of the dissolved organic C/N/P pools and what processes controls these distributions; what are the rates, biogeographical locations and controls on elemental cycling through the pools; what are the biological and physicochemical sources and sinks; what is the composition of the pools and what does this tell us about elemental cycling? Finally, do we understand DOM in elemental cycling well enough to accurately represent the processes in numerical models? In this book, the progress of the last decade in answering these questions is reported and synthesized by key contributors to those advances. The book opens with a chapter by J. Hedges, providing historical perspective for the work of XXI
xxii
Preface
the 1990's, as well as context for the succeeding chapters. An important obstacle that had to be breached before significant biogeochemical advances could be made was coordinated improvement in the methods for determining the bulk DOM pool concentrations. J. Sharp, a leader in those community efforts, reviews methodological advances in Chapter 2. Study of the chemical and isotopic compositions of DOM has provided unique information on elemental cycling. This work is reviewed in chapters by R. Benner and J. Bauer. The biological cycling of the major elements (C, N, P) through DOM is reviewed in chapters by C. Carlson, D. Karl and K. Bjorkman, and D. Bronk. Particular emphasis is placed in these chapters on marine microbes as active agents in the processing of DOM. Colloidal organic matter, with special focus on interactions with metals, is covered by M. Wells. Photochemical reactivity of DOM, and implications for elemental cycling, is discussed by K. Mopper and D. Kieber. The contribution of optically active (chromophoric) DOM in bio-optical processes is covered by N. Blough and R. Del Vecchio for the coastal ocean and by N. Nelson and D. Siegel in the open ocean. The role of DOM in the ocean margins and interfaces (i.e., the coastal realm, the sediments, and the Arctic Ocean) is reviewed in chapters by G. Cauwet, D. Burdige, and L. Anderson, respectively. A review of the global ocean distribution and broad scale transformations of DOM is presented by D. Hansell. The book closes with discussion on the advances for the inclusion of DOM in both ecosystem and global circulation models by J. Christian and T. Anderson. Many scientists in the ocean science conmiunity have developed a strong biogeochemical view of the ocean. This book provides a firm foundation for their forays into the biogeochemistry of marine organic matter. The book maintains a particular focus on DOM in elemental cycling, and therefore does not revisit the many, well-documented advances made in organic geochemistry during the previous decades. Attention is paid largely to the marine environment, with coverage of fresh water systems only at its interface with the marine realm. The book is directed at professional ocean scientists and advanced students of biological and chemical oceanography. Many individuals and organizations must be thanked for support of the science that provided content for this book, as well as to development of the book itself. The U.S. federal agencies supporting much of what has been reported here, including individual research by the chapter authors, are the National Science Foundation, the National Oceanographic and Atmospheric Administration, and the National Aeronautics and Space Administration. The agency program managers who have provided invaluable support to we editors are Neil Anderson, Lisa Dilling, Don Rice, Phil Taylor, and Jim Todd. The U.S. JGOFS program, particularly the Scientific Steering Committee and the Planning Office, provided consistent support to ensure that our understanding of DOM in marine elemental cycles was advanced. Their vision and encouragement was necessary for the many advances reported in this book to be realized. D. A. Hansell and C. A. Carlson
Chapter 1
Why Dissolved Organics Matter John I. Hedges School of Oceanography, University of Washington, Seattle, Washington
I. II. III. IV. V.
Introduction DOM Research Pre-1970 DOM Research in the 1970s DOM Research in the 1980s "New" DON and DOC
VI. Why Dissolved Organics Matter VII. What did we Learn? References
I. INTRODUCTION As this book attests, research on dissolved organic matter (DOM) in seawater has burgeoned in the past decade. This increase in activity is evident not only from the growing number of articles published each year in the scientific literature, but also from the topical breadth and broad integration of present research. The oceanographic community's perception of DOM has evolved from an emphasis on a dilute and largely separate pool of remarkably old and static substances to the current view of a dynamic assemblage of organic molecules that interact with each other, trace metals, and living organisms over a broad continuum of space and time scales. The sparingly reactive components of this molecular continuum that persist and change on time scales sampled by conventional oceanographic surveys represent a small molecular outcrop of a churning mass of molecules through which much of the total primary production of the ocean cycles. To better understand what is to come in this chapter and book, it is useful to keep in mind that investigations of DOM in seawater have followed two fundamentally Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
1
2
John I. Hedges
different strategies. The first is a holistic approach focusing primarily on the total concentration, bulk properties, and collective behavior of the entire mixture of molecules that make up the operationally defined DOM pool. Examples would be measurements of the total dissolved organic carbon (DOC) or dissolved organic nitrogen (DON) concentrations, determinations of bulk spectral or isotopic compositions, and estimates of cumulative oxygen and nutrient changes attending microbial attack of the entire organic mixture. This strategy has the major advantage of yielding characteristics that are representative of the entire DOM pool, but the information obtained is typically limited and highly biased toward the less reactive components of the mixture that accumulate over time. In contrast, the reductionist approach has been to target selected fractions of the total mixture for detailed analyses of specific features that might then be meaningfully extrapolated back to the bulk pool. The most common form of reductionism is the chromatographic analysis of specific biochemical components of seawater DOM. This particular strategy can yield a wealth of information on structural features, stereochemistries, and reaction pathways and dynamics. However, molecular-level analyses are highly selective for individual biochemical classes (or subclasses), which in turn often comprise a tiny, and not necessarily representative, fraction of bulk DOM. Thus, major uncertainties arise in extrapolating from detailed molecular-level information to the whole DOM pool, and especially to its emergent properties. This introductory chapter emphasizes the oceanographic community's perceptions of the entire DOM pool from a bulk chemical perspective, bringing in biochemical and microbiological information primarily as it pertains to the larger view. While this focus on collective properties necessitates that substantial advances at the biochemical level will not be highlighted, it does allow better historic continuity and further development of broad issues pertaining to oceanography in general. This chapter recaps selected experimental and conceptual developments extending from the last century up through the Seattle DOC/DON Workshop Report (Hedges and Lee, 1993) that have led to the modem dynamic view of oceanic DOM presented in the following chapters.
11. DOM RESEARCH PRE-1970 By 1970, study of seawater DOM had already been under way for almost a century (see review by Kalle, 1966). Glass fiber or silver filters available in the mid-20th century had minimal pore sizes of ^0.45-1.0 /xm and became the basis of the operational definition that "dissolved" materials pass such filters whereas "particulate" matter does not (Fig. 1). This definition persists to today, although we now know that seawater contains a continuum of discrete units stretching from the size of whales to that of a water molecule, with no discemable break in abundance in the micrometer range (Sharp, 1973a). The traditional definition can be useful.
W/zy Dissolved Organics Matter mm Meters
I
urn
10-^I III I 10-^ mill III
nm
I
10-5 10-^ IN III nil, lllllilJI
10-^
Partlcuiate
10-8 iiiiiii III
I
I
lo-^ mill I
III
10-^°
Dissolved Colloids
^fel Sand
I [
Viruses
_
|
Macyomolecutes "[
'^rCliyJ Screen Sieves
^^ -^iijfi'lWr,.,L^ Papers f Ultrafilters
Figure 1
Molecular
-^
^-
Sieves
The continuum of sizes and separation methods for organic matter in seawater.
however, because particles smaller than 1/xm are not prone to sink (Duursma, 1961) and all living organisms other than viruses and small bacteria fall into the particulate fraction. Colloidal particles, constituting the upper size range (0.0011.0 jjim) of the DOM continuum, correspond in minimal size to approximately a six-sugar oligosaccharide (Fig. 1). Following several largely unsuccessful early attempts (e.g., Piitter, 1909; Raben, 1910) to quantify the dissolved organic contents of seawater, Krogh and Keys (1934) published comparatively reproducible methods for the determination of both DON and DOC in seawater. The DON method was based on a micro-Kjeldahl (sulfuric acid hydrolysis) procedure, whereas DOC was quantified (after chloride removal) by wet oxidation in aqueous chromic acid. Using these methods, Krogh (1934a) measured the first full water column profiles of DOC and DON in the open ocean off Bermuda. He found uniform concentrations of organic material from the surface down and concluded that seawater DOM is chronologically old, chemically and biochemically inert, and insignificant as a food source for organisms in the deep sea (Krogh, 1934b). The following year, however, Waksman and Carey (1935) demonstrated in a series of culturing experiments that bacteria decompose DOM from surface seawater in a matter of days, with attending increases in inorganic nitrogen and decreases in dissolved oxygen. Kalle (1937) used UV absorption to detect yellow organic substances in the waters of the North Sea and open North Atlantic. Although spectroscopically similar to DOM in rivers, seawater "gelbstoff" was recognized to have a predominant
4
John I. Hedges
marine origin (Kalle, 1949). Kalle (1949) also reported an organic component of seawater DOM that gives a bluefluorescencewhen irradiated with long-wavelength ultraviolet light and appears to have a predominantly terrestrial source. Early attempts to isolate seawater DOM by sorption onto charcoal (Wilson and Armstrong, 1952; Johnston, 1955) or extraction with nonpolar solvents (Slowley et al, 1959; Chanu, 1959) were successful, although subsequent chemical characterizations were primarily limited to demonstrating UV absorbance and the presence of trace amounts of fatty acids (Jeffrey and Hood, 1958). Various laboratory experiments (e.g., Fogg and Boalch, 1958) demonstrated that marine algae (especially phaeophyta) are potential direct sources of seawater DOM. At this time, amino acids and carbohydrates were known to spontaneously condense (although at elevated temperatures) to produce melanoidin polymers (Maillard, 1913) that exhibit many of the spectral qualities of marine DOM (Kalle, 1966). By the early 1960s, DOC was measured at concentrations on the order of 1 mg/L (83.3 /xM) and found to be more concentrated in surface ocean water than at depth (Kay, 1954; Plunkett and Rakestraw, 1955; Duursma, 1961). In addition, a variety of component biochemicals, including simple sugars, low-molecular-weight acids, and vitamin B12, had been detected in seawater (Vallentyne, 1957; Hood, 1970; Duursma, 1965). A wave of pioneering field studies during the 1960s served mainly to strengthen the perception of deep-ocean DOM as a largely static pool. Improved wet chemical oxidation methods for seawater DOM (e.g., the persulfate adaptation of Menzel and Vacarro, 1964) became the basis for extensive surveys of DOC concentrations in various oceans (e.g., Menzel, 1964; Menzel and Ryther, 1968). Menzel's 1964 study of DOC distributions in the western Indian Ocean was by far the most extensive to that time with respect to the number of stations (39) and depths (1-2000 m) sampled. In addition to synoptic temperature and salinity data for each sample, this study included ^"^C-based measurements of primary production under simulated euphotic zone conditions. No apparent correlation between DOC concentration and primary production rates was observed in surface ocean waters. Although DOC concentrations below 200 m ranged geographically between 0.2 and 2 mg/L ('^ 15-170 /xM), these gradients covaried linearly with salinity and thus appeared to result primarily from mixing of different water masses with characteristically different DOC signatures. Menzel (1964) concluded, "carbon in solution and in particulate form in the ocean is extremely stable and subject to limited change by biological activity." Menzel and Ryther (1968) soon published a more detailed study of dissolved and particulate organic carbon (POC) distributions in discrete water samples collected over the entire water column at 14 stations in the southern Atlantic Ocean. In contrast to the Indian Ocean survey, dissolved oxygen was directly measured for each sample, along with temperature and salinity. Relatively constant DOC concentrations (35 ± 5 /xM) were observed at depths greater than 500 m throughout the South Atlantic (Fig. 2). Suspended POC accounted for roughly 1% of
Why Dissolved Organics Matter
DOC, |LiM 0
20
40 I
60 ^1
80
100
Figure 2 Vertical profile of DOC in the southwest Atlantic Ocean (after Menzel and Ryther, 1968). Arrow lengths indicate the range of measured values, with the profile line passing through the mean value for that depth. Values in parentheses represent the total number of multiple analyses at one depth.
DOC below 500 m depth and also was essentially invariant. Dissolved O2 varied linearly versus salinity (Fig. 3) at the core of Antarctic intermediate water in all profiles. This observation of minimal DOC variation (Fig. 2) over a substantial oxygen gradient of > 100 /xM (Fig. 3) supported previous evidence for Httle or no DOC respiration below 500 m (Menzel and Ryther, 1970). By comparison, the theoretical OC/O2 ratio for respiration of "average marine plankton" is 106/138 = 0.77 (Redfield et al, 1963), whereas the best current estimate is near 0.70 (Anderson, 1995). Russian researchers at this time were measuring DOC concentrations by high-temperature combustion of freeze-dried samples. Although this method indicated concentrations that were approximately three times higher than those obtained with persulfate (see review by Starikova, 1970), minimal changes in deep-ocean DOC profiles were nonetheless noted (Skopintsev, 1966). Independent evidence that deep-sea DOM is refractory came from a variety of other sources. Barber (1968) demonstrated that DOM concentrated fivefold from deep-ocean water was not measurably utilized by marine bacteria and argued
John I. Hedges JUU
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Figure 3 Measured dissolved oxygen versus the salinity in excess of 34.000 at the core of the Antarctic intermediate water in the southwest Atlantic Ocean (based on data from Table 1 of Menzel and Ryther, 1968). The equation of the best-fit line (r^ = 0.992) to the 13 data points is O2 = (-439 ± 12) x (S-34) + (374 ± 4).
against previous speculation (Jaanasch, 1967) that seawater DOM might simply be too dilute to serve as a suitable substrate. P. M. Williams (1968b) showed that the stable carbon isotopic composition of DOC is consistent with a predominantly marine origin and essentially constant throughout the water column of the San Diego trough. The definitive experiment of the decade, however, was the demonstration by Williams et al (1969) that the radiocarbon content of dissolved organic matter from the deep Pacific Ocean corresponds to a radiocarbon "age" of roughly 3400 years BR If this radiocarbon "age" is assumed to represent a mean residence time (Williams et al, 1969), it corresponds to a steady-state flux of roughly 0.2 x 10^^ g C/year through the ocean DOC pool (650-700 x 10^^ g C). Critically, this small flux would necessitate that only 0.4% of global primary production enters the marine DOC pool per year. Although a flux of this order could be supported by riverine DOC discharge alone (Williams, 1971; Mantoura and Woodward, 1983), the stable carbon isotopic composition of seawater DOC points toward a marine origin (WilHams, 1968a). WiUiams (1971) concluded that the predominant uncharacterized fraction of seawater DOM is humic-like and thus intrinsically unreactive. At the same time, parallel evidence was accumulating that an appreciable fraction of DOM in surface ocean waters can be physically and biologically reactive under at least some conditions. Natural slicks were observed to form and disperse
Why Dissolved Organics Matter rapidly at the ocean surface (Ewing, 1950; Jarvis, 1967) and to contain a variety of surface-active organic materials (Garrett, 1967, 1970) that could be concentrated by a dipped screen (Garrett, 1965), rotating drum (Harvey, 1966) or, "bubble microtome" (Maclntyre, 1966). In a series of experiments, Sieburth and Jensen (1968, 1969) demonstrated exudation of DOM by phaeophyta (kelp) and associated formation of sea surface slicks (Sieburth and Conover, 1965). Duursma (1961,1963, 1965) observed greater than twofold seasonal variation of DOC in surface waters of the North Sea. This indication of cycling on a monthly time scale suggested the possible use of DOC as an indicator of primary production. In contrast to results for deep water, Barber (1968) found that DOM concentrated from surface seawater exhibited a relatively short half-life (1-2 months) with respect to bacterial remineralization. The list of chromatographically measured biochemicals also increased substantially and the more abundant fatty acids, amino acids, and sugars had been quantified in surface waters and over a few deep-sea profiles (Holm-Hansen et al, 1966; Duursma, 1965; WiUiams, 1971). However, only about 10% of the DOC in surface and subsurface waters could be accounted for as individually measurable biochemical types, even when results from separate studies were added together (Williams, 1971). Although potentially labile biochemicals were evident, their low concentration was taken as additional evidence for a largely refractory pool of bulk DOM. The decade closed with a short conmiunication by Riley and Taylor (1969) describing how fatty acids and humic substances can be recovered from acidified seawater (pH 2) by sorption onto a cross-linked polystyrene resin called Amberlite XAD-1.
III. DOM RESEARCH IN THE 1970s The perception of a labile DOM component in the surface ocean accompanied by largely inert DOM (marine humus) that predominates below ~500 m continued to develop in the 1970s. The decade opened with the report by Williams and Gordon (1970) that the stable isotope composition of DOC at multiple stations in the northeast Pacific Ocean is remarkably uniform (5^^C = -22.6 db 0.6%^ ) and independent of depth and time, as well as dissolved O2 and DOC concentrations. The observation that these values were similar to those of local POC and marine plankton pointed toward a predominant marine origin of oceanic DOM. This inference was supported by a very different 8^^C value of —28.5%o measured for DOM from the Amazon River (Williams, 1968a). Although rivers discharge DOC at a rate sufficient to support the entire marine pool (WiUiams, 1971), the much more ^^C-enriched composition of marine DOC indicates that land-derived DOC must be rapidly removed or profoundly changed in its stable carbon isotopic composition. Minimal changes in the S^^C of marine DOC in depth profiles
7
John I. Hedges Ox
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AOU, ^iM Figure 4 DOC concentration versus AOU in waters of the western North Pacific Ocean (after Ogura, 1970). Different symbols correspond to various isopycnal intervals within the seawaters that were sampled. The line of best fit was by the original author.
characterized by correspondingly large variations in dissolved O2 were interpreted by Williams and Gordon (1970) to suggest that, "dissolved organic matter is stable to biochemical fractionation and oxidation." In a milestone paper that in many ways foreshadowed controversies to come, Ogura (1970) reported a weak overall relationship (Fig. 4) between DOC and apparent oxygen utilization (AOU) in shallow (at < 26.5) waters of the western North Pacific (east of Japan). His DOC measurements, by the standard persulfate method of Menzel and Vaccaro (1964), gave overall concentrations and depth trends similar to those reported by Menzel and Ryther (1968) in the South Atlantic. No relationship between DOC and AOU was apparent in deeper waters (at > 26.5), where AOU increased substantially against a relatively constant background DOC near 40 /xM (Fig. 4). By directly combining DOC and AOU measurements for the first time, Ogura demonstrated that approximately half of the total DOC in shallow waters of the western North Pacific is labile, whereas the other half resembles deepocean DOC in both its concentration and minimal reactivity. An inverse DOC/AOU trend did occur in shallower waters, but at only one-third of the 106/138 molar ratio expected from Redfield stoichiometry (Redfield et al, 1963) for complete remineralization of average marine plankton. Ogura inferred that the organic matter being respired in the upper water column was either compositionally very different from Redfield plankton or that another O2 sink, such as the "particulate organic
Why Dissolved Organics Matter substances" existed throughout the water column. Soon thereafter Craig (1971) reported field evidence for measurable O2 consumption on the time scale of water mass mixing in the deep Pacific Ocean, a result that was supported by later culture experiments (Williams and Carlucci, 1976). Within half a decade, McCave (1975) published a theoretical paper indicating that rare, fast-sinking large particles might compose an as-yet-unsampled source of labile organic matter to the deep ocean which could explain Ogura's and Craig's observations of in situ O2 consumption. Improved methods for DOC analysis were also a main research thrust in the 1970s. New methods for high-temperature combustion of dry samples generated by freeze-drying (Gordon and SutcHffe, 1973) and aspirating (Mackinnon, 1978) seawater were described. Sharp (1973b) reported the first practical adaptation of an earlier Hquid injection method (van Hall et al, 1963) for rapid high-temperature combustion of seawater DOC. These high-temperature combustion methods typically measured greater DOC concentrations than were obtained by prevalent wet chemical methods involving persulfate (Menzel and Vaccaro, 1964) or UV (Williams, 1969a,b) oxidation. This observation supported previous Russian findings based on dry combustion methods that the reservoir of DOC in the ocean might be up to twice as large as previously accepted (Sharp, 1973b). A second major analytical thrust of the 1970s was development of ultrafiltration to separate and characterize colloidal fractions of seawater DOM. Using Millipore and Diaflo membranes with nominal pore sizes of 0.025 and 0.003 /xm. Sharp (1973a) separated roughly 10 and 20% of total DOC, respectively. He noted that colloidal DOC is approximately an order of magnitude more abundant than suspended POC, leading to a monotonic increase in the cumulative fraction of seawater organic matter found in progressively smaller size fractions. Similar molecular size distributions were reported for profiles from the Gulf of Mexico by Maurer (1976), who inferred from colorimetric analyses that proteins and carbohydrates accounted for approximately 15 and 20%, respectively, of colloidal DOM throughout the water column (see also Ogura, 1977). Another advance was the development of improved hydrophobic sorption methods for large-scale isolation and subsequent characterization of milligram amounts of salt-free DOM. Kerr and Quinn (1975), building on the pioneering research of Jeffrey and Hood (1958), isolated seawater DOM by adsorption onto charcoal and demonstrated its lower UV absorbance versus sedimentary and estuarine DOM. The tour de force of this era, however, was the work of Stuermer and Harvey (1974,1977), who carried out the first detailed analysis of seawater DOM isolated from Sargasso Sea and coastal seawater onto XAD-2, a microporous polystyrene resin. This work built on the isolation methodology worked out by Riley and Taylor (1969) and Mantoura and Riley (1975), which on average recovered less than 10% of the total organic carbon in ocean water (Stuermer and Harvey, 1977). Because the tradition at that time was to view structurally uncharacterized materials in soils, sediments, and natural waters as "humic substances," the first paper
9
10
John I. Hedges
in this series (Stuermer and Harvey, 1974) was entitled "Humic Substances from Seawater." The isolated seawater humic substances (SHS) where found to be low in molecular weight (predominantly <700 amu), highly aliphatic (atomic H/C = 1.6), oxygen rich (0/C = 0.55), and nitrogen poor (C/N = 15). The latter value, however, must be considered with caution because all isolates were eluted from XAD-2 with anmionium hydroxide (pH 11.6) solution from which nitrogen may have been added. SHS had 8^^C values near —23%o and, like bulk seawater DOC, appeared to be marine derived. Later ^^C NMR (Stuermer and Payne, 1976) and chemical degradation (Stuermer and Harvey, 1978) studies confirmed the highly aliphatic character of these SHS isolates, although the NMR spectra were noisy. Overall the DOM fractions isolated from seawater were markedly different in their compositional signature from riverine, soil, and sedimentary counterparts (e.g.. Fox, 1983). Nevertheless, the "humic" label stuck and conferred an image of extreme structural alteration and low substrate quality. Following the lead of Garrett (1965,1967) and others, research on the concentration and reactions of organic matter at the air-sea interface blossomed in the 1970s (see reviews by Liss, 1975; Hunter and Liss, 1981). Commonly employed isolation methods involved dipping glass (Harvey and Burzell, 1972) or Teflon (Garrett and Barger, 1974) plates, or plastic funnels (Morris, 1974) through the sea surface microlayer. A particularly creative approach for both collecting and characterizing surface ocean films was sorption onto a germanium prism within which infrared light could be attenuated via multiple internal reflections (Baier, 1972). The resulting IR spectra of most natural films were characterized by the presence of bands at 3400,1650 and 1100 cm~^ that are typical of carbohydrate-like material, as well as bands at 3300 plus 1530 and 1440 cm~^ indicating protein and carboxyl groups, respectively (Baier et al, 1974). Little if any absorbance at 2950 and 2850 cm"^ was observed that would demonstrate the presence of C-H stretching in lipids. Baier et al (1974) concluded that glucoprotein-like substances concentrate at the seaatmosphere interface, although lipids could be observed when slicks are apparent. This conclusion was largely supported by molecular-level analyses that showed major carbohydrate and protein components, and minor lipid concentrations, in sea surface films (Hunter and Liss, 1981). The 1970s also saw increased attention to the reactions of bulk seawater DOM and its biochemical content (see reviews by Williams, 1975; Ogura, 1977). Trace metals, and copper in particular, were observed in complexes with DOM (e.g., Siegel, 1971). Sensitive methods for analysis of amino acids were developed, including means for separating D versus L enantiomers of selected compounds (Lee and Bada, 1975,1977). Observation of elevated D/L aspartic acid ratios in Sargasso Sea waters was one of thefirstdirect indications of a possible bacterial cell wall origin (Bada and Lee, 1977). Decomposition of organic matter dissolved in seawater was observed to advance with selective loss of measurable biochemicals and selective preservation of the high-molecular-weight fraction (Ogura, 1975). By analogy
Why Dissolved Organics Matter
11
with both terrestrial systems (Flaig, 1964) and laboratory simulations (Maillard, 1913; Hodge, 1953), such trends were widely viewed as being indicative of "heteropolycondensation" reactions yielding structurally complex and enzymatically intractable dissolved humic substances (Degens, 1970).
IV. DOM RESEARCH IN THE 1980s Efforts to improve methods for DOM isolation and characterization continued as a major research direction into the 1980s, with a special emphasis on NMR methods. Fu and Pocklington (1983) reported that the sequential passage of acidified seawater onto XAD-2 resin and activated charcoal columns, followed by sequential elutions with methanol and NH4OH, recovered the equivalent of 90-100% of the initial DOC. Little and Jacobs (1985) demonstrated that DOM can be adsorbed from seawater directly onto titanium foil, which could then be pyrolyzed to products that are quite different from those generated by DOM isolated with XAD-2 resin. Wilson et al (1983) pubHshed some of the first high-quality ^H (solution) and ^^C NMR (solution and solids) spectra of coastal seawater DOM isolated by sorption onto XAD-2 resin. These spectra showed evidence for carbohydrate, highly branched alkyl chains, and (to a lesser extent) aromatic carbon as major structural units of seawater DOM and algal exudates. Complementary analysis of the same samples by pyrolysis gas chromatography-mass spectrometry (Wilson et al, 1983; Gillam and Wilson, 1985) indicated phenol- and carbohydrate-based structural units. Harvey et al (1983) published proton NMR spectra of seawater humic and fulvic acids, which were both characterized by resonances of aliphatic structures. They proposed that such macromolecules might be formed by lightcatalyzed, oxidative cross-linking of polyunsaturated fatty acids or glycerides via a free-radical reaction. This pathway, however, did not alone explain the presence nitrogen or the fluorescence of seawater DOM (Laane, 1984). Another major research theme of the 1980s was the study of fluorescent substances dissolved in seawater. Following the lead of Kalle (1949), one line of research involved tracing highlyfluorescentriverineDOM into the coastal ocean. For example, Willey and Atkinson (1982) were able to sensitively trace (~ 1 part in 200 parts seawater) discharges of the Savannah and Ogeechee Rivers (Georgia, U.S.A.) through their respective estuaries and into adjacent coastal waters with salinities greater than 30 ppt. The coastal plain Ogeechee River exhibited approximately twice the fluorescence of the piedmont Savannah River, allowing contributions of these two sources to be distinguished off the Georgia coast. Similar tracer applications were described by Hayase et al (1987) and by Laane (1982) for riverine organic matter discharged into Tokyo Bay and the Ems-DoUart estuary (Netherlands/ Germany), respectively. Donard et al (1989) described a high-sensitivity method based on laser excitation sources for fluorescent DOM in the Mediterranean Sea
12
John I. Hedges
Dark Control \.9^.^..^./....
.•-
Dark Control
k
Sunlight (unsterilized)
Sunlight (sterilized) 20 h 5
10
15
20
25
Days of Treatment Figure 5 Decrease of the natural fluorescence of unsterilized and sterilized coastal seawater during exposure to sunlight. A dark control showed no change in fluorescence over the 20-day experiment (after Kramer, 1979).
and detected different spectral signatures between coastal and offshore waters. The second line of research built on Kramer's (1979) observation that the natural fluorescence of seawater DOM is lowest in the upper water column and is decreased substantially (>50%) during exposure to sunUght over a period of days (Fig. 5). Hayase et al. (1988) later demonstrated that vertical profiles of seawater fluorescence in the North Pacific closely parallel those of dissolved nutrients, suggesting that fluorescent DOM is released as degrading organic substances streaming from sinking particles into ambient seawater. They showed that the fluorescence of deep-sea DOM is also readily bleached by UV light, thereby helping to explain the minimal fluorescence of surface seawater throughout the open ocean. The previous recognition of photobleaching and the photosensitizing properties of seawater (Momzikoff et al, 1983; Zepp et al, 1985) led to a number of studies in the later 1980s on the photochemical reactivity of seawater DOM. For example, Mopper and Stahovec (1986) demonstrated in laboratory andfieldexperiments that low-molecular-weight carbonyl compounds such as formaldehyde, acetone, and glyoxal can be formed by the photolysis of seawater DOM. This process was most pronounced in the surface ocean and in coastal regions where terrigenous DOM prevails (Kieber and Mopper, 1987). The photodegradation products of seawater DOM were rapidly taken up by marine microbes, thereby providing a pathway for the cycling of relatively refractory seawater DOM into planktonic food webs (Kieber ^? a/., 1989).
Why Dissolved Organics Matter
13
Molecular highlights of the 1980s include the application of highly sensitive analytical methods for individual amino acids (Garrasi et al, 1979) and sugars (Mopper et al, 1980) to determine the composition and dynamics of these DOM components in their free and combined (polymeric) forms. For example, Liebezeit et al (1980) found that individual free carbohydrates (<5-650 nmol) and amino acids (
6000 years) of DOC in the deep ocean that was first reported almost two decades before by Williams et al (1969). Williams and Druffel (1987) also demonstrated that the A^^C profiles of DOC and dissolved inorganic carbon (DIC) are remarkably parallel in the Pacific Ocean (Fig. 6) and concluded that the same transport and recycling processes control the radiocarbon distributions of both dissolved carbon pools. However, the approximately 300%o lower A^'^C values of DOC versus coexisting DIC suggested that a fraction of DOC is recycled within the ocean on much longer time scales than for DIC, which largely equilibrates with the atmosphere on a 500- to 1000-year time scale.
V. "NEW DON AND DOC A series of events that was to galvanize the oceanographic community began in the mid-1980s with publication of a paper by Suzuki et al (1985) on the determination of total dissolved nitrogen (TDN) in seawater. The method was based on high-temperature (680 °C) catalytic oxidation (HTCO) of a small (200 /xL)
14
John L Hedges
A^^C, o/oo -600
200
lOOOt
6000 Figure 6 Profiles of the relative radiocarbon contents (A^^C) of dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) in the water column of the central North Pacific Ocean (data from Table 1 of Druffel et al, 1989).
sample of filtered seawater directly injected into a quartz column filled with platinum-impregnated (3 wt%) alumina (AI2O3). High purity O2 acted both as a carrier gas and an oxidizing agent. Injected organic and inorganic nitrogen compounds were all converted to nitrogen dioxide that then combined with a chromogenic reagent, A^-(l-naphthyl)-ethylenediamine dihydrochloric acid, to absorb light at 545 nm. Total organic nitrogen was determined as the difference between total dissolved nitrogen (measured as above) and total inorganic nitrogen (nitrate + nitrite + ammonium). The method description included extensive tests of the effects of combustion column temperature, matrix ions (Cl~, F~, and 804"), and injection sample volume (5 to >200 /xL) on linearity (0-13 mM), precision (<2% for TDN), and analytical error (<2% for TDN). Conversion efficiencies of the analytical system for a variety of inorganic (nitrate) and organic (e.g., caffeine, oxine, and albumin) substances, as well as molecular size fractions of seawater DOM, were found to be >95%. The only exception was sulfathiazole (<65%). TDN measurements of reference materials and natural seawater samples by the HTCO method compared well with those obtained by pyrolytic oxidation of freeze-dried sea salt, whereas nitrate analyses following aqueous persulfate oxidation gave much lower (20-90% recovery) results. This pattern of higher TDN values measured by HTCO versus persulfate was also observed when these two methods
Why Dissolved Organics Matter
15
were compared for water column profiles at two different sites in the western North Pacific (Suzuki et aU 1985). In retrospect, some aspects of the Suzuki et al paper were problematic. For example, all seawater samples were processed through Millipore HA filters that were made of mixed acetate and nitrate esters of cellulose and hence were potential sources of both DOC and TDN. Blank runs for all analyses were made without sample injection and thus were not procedurally representative and would not have picked up contamination derived from filtration or released by injected water from alumina. The Sephadex gel-filtration method (Sugimura and Suzuki, 1983) used to size fractionate DOM in seawater samples indicated that less than 90% of the component nitrogen resides in molecules < 1500 amu. This was a surprising result because previous (Sharp, 1973a; Maurer, 1976) and following studies (Carlson et al, 1985; Benner et al, 1992) indicated that 75% or more of total seawater DOC has a molecular weight less than ^1000 amu. Organic nitrogen would have to be very strongly concentrated in higher-molecular-weight molecules to account for this contrast in DON versus DOC distribution (see later discussion). Most troubling, however, TDN concentrations (30^0 /xM) measured in the surface 100 m at two different sites in the western North Pacific (e.g.. Fig. 7) were much higher than previously reported (e.g., Duursma, 1961; Williams, 1975; Jackson and Williams, 1985). The directly measured large increases in DIN with depth (^40 /zM) produced corresponding decreases in DON concentration (measured as TDN-DIN) on the order of 35 /xM at both sites. The negative correlations between DON and AOU at these two study sites were strong (r^ > 0.95, Fig. 7) and averaged —0.13, compared to a theoretical molar AN/AAOU of —0.12 for the respiration of average marine plankton (Redfield et al, 1963). This result suggests that most of the cumulative respiration evident in the upper 1000 m of each water column was supported by oxidation of DOM, as opposed to sinking organic particles. The second paper in this series focused on a derivative high-temperature catalytic oxidation method for DOC analysis (Sugimura and Suzuki, 1988) and began a cascade of events that carried over into the 1990s and much of the research reported in the following chapters. The DOC paper was similar in many ways to the DON pubHcation of 3 years before. The major differences were that water samples were first passed through a Nuclepore (polycarbonate) membrane filter, acidified with H3PO4, and purged to remove DIC. The same Pt-catalyzed combustion column and procedure were used as for TDN. The generated CO2 was analyzed with a nondispersive infrared detector. The procedural blank was estimated by injecting different volumes of seawater and extrapolating the measured responses back to zero volume. The value of this blank, however, was not reported. Oxidation efficiencies to CO2 were determined for many of the same organic substances (e.g., caffeine, oxine, and albumin) tested in the 1985 paper and again found to be >95%, with the exception of sulfathiazol (<65%). The trend in measured DOC concentration versus combustion temperature was very different for surface versus deep
John I. Hedges
16
Dissolved N, |iM 0
10
20
30
40
50
Figure 7 Representative plots (for the profile taken at 39° 59' N, 144° 02' E) of total dissolved nitrogen (TDN), dissolved inorganic nitrogen (DIN), and dissolved organic nitrogen (DON) concentrations versus AOU (data from Table VII of Suzuki et al, 1985).
waters, with approximately half of the DOM in surface water requiring temperatures in excess of 600°C (versus 500°C for deep-ocean DOM) to obtain complete oxidation. At an optimal temperature of 680°C, the HTCO analyzer reportedly yielded linear responses over the range of 0-2000 //M of DOC (5- to 400 /nL injection volumes) and a precision of ± 2% for glucose and natural seawater. Sugimura and Suzuki (1988) also reported extensive comparisons of their HTCO method to the conventional persulfate procedure (Menzel and Vaccaro, 1964). For surface seawater from the North Pacific (30° N, 147° W) they measured DOC concentrations that were approximately 2.5 times higher than the concentration of 100 fxM obtained by persulfate oxidation and values for deeper waters that averaged almost twice the persulfate-derived concentrations of ~70 fiM. Overall differences between DOC concentrations measured by HTCO and persulfate were even greater (~3x overall) for larger size fractions of a surface seawater, with most of the discrepancies occurring in the higher-molecular-weight (>4000 amu) fractions. These results were supported by the finding that over 60% of the initial DOC (232 IJM by HTCO) in an unspecified seawater sample subjected for 2 h
17
Why Dissolved Organics Matter DU-
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Figure 8 DON versus DOC in surface waters from the North Pacific and East China Sea (data from Table VII of Sugimura and Suzuki, 1988). The five open squares indicate high-DOC waters with a salinity less than 33 that were collected off the mouth of the Changjiang (Yangtze) River. The equation of the best-fit line (r^ = 0.625) to the other 32 data points (sohd squares) is DON = (0.554 ± 0.078) x D O C + (25.9 ±1.5).
to persulfate oxidation still could be measured by HTCO in the residual water. The bulk of the remaining DOC reportedly occurred in the >4000-amu size fractions, indicating again that high-molecular-weight DOC is particularly resistant to persulfate oxidation. In the same paper, Sugimura and Suzuki reported application of the new HTCO method in an extensive survey of surface seawaters and three depth profiles from the western North Pacific. In general, these field results (Fig. 8) strongly reinforced the implications of the previously described laboratory tests. DOC values in the range of 180-490 luM were measured for surface seawaters south of Japan, with values above 275 /xM being limited to five low-salinity (<33) surface waters collected off the mouth of the Changjiang (Yangtze) River in the East China Sea (Fig. 8). In comparison, DOC concentrations previously measured by the conventional persulfate method in surface waters of the open ocean (e.g.. Fig. 2) rarely exceeded 100 fiM (WilHams, 1971, 1975). Commensurately high (-35-45 fiM) DON concentrations were measured for these same surface waters using the Ptcatalyzed HTCO combustion method of Suzuki et al. (1985). The average atomic C/N ratio for all 37 surface seawaters for which DOC and DON data are listed in Table VII of Sugimura and Suzuki (1988) is 7.2 ± 1.6. If the five carbon-rich (C/N = 9.5-12) water samples collected off the Changjiang (Fig. 8) are deleted, the remaining 32 surface waters have an average C/N ratio of 6.6 zb 0.6. This ratio has a very small (< 10%) standard deviation and is the same in value as the atomic C/N of average marine plankton (Redfield et al, 1963).
18
John I. Hedges
However, other patterns in these same data sets were curious. In particular, the previously mentioned strong correlation between DON and DOC values for the 32 open-ocean surface waters generates a best-fit line (r^ = 0.63) with an intercept of 25.9 ± 1.6 /xM of DON at zero DOC (Fig. 8). The slope of this line (0.0554 ± 0.0078) corresponds to an atomic C/N of 18. In contrast, Jackson and Williams (1985) found little correlation between seawater DOC and DON contents measured throughout the ocean by persulfate oxidation and noted that most of their individual samples gave DOC/DON ratios higher than Redfield values. They observed, however, that it is the slope of the DOC/DON correlation line for a sample suite, and not the individual ratios, which indicates the C/N ratio within DOM sample sets. Their seawater samples converged on minimal persulfate-based DOC and DON concentrations near 30 and 1.2 /xM, respectively, indicating a predominant (--80% of DOC) background of "inert" DOM with a C/N near 25 occurring in the deep ocean. The slope of Sugimura and Suzuki's data set for surface waters (Fig. 8) actually indicates DOM components with a much higher C/N ratio than Redfield value (18 vs 7). The intercept obtained by extrapolating this data trend to the DON axis indicates a huge background (^^25 /xM) of additional nitrogenous material deriving systematically from either the water samples or the DON measurement procedure. The close cluster of the measured individual C/N ratios about the Redfield value thus appears highly fortuitous. Elevated C/N values for the five surface waters exhibiting lower salinities would be expected because riverine DOM is typically nitrogen poor with a global average C/N near 25 (Meybeck, 1982). It was the deep ocean profiles of DOC versus DON, DIN, and AOU, however, that appeared to give the greatest evidence that the new Pt-catalyzed HTCO method provided "oceanographically consistent" results. The three profiles (0-2000 m) published by Sugimura and Suzuki (1988) were all very similar in form and extent (e.g.. Fig. 9). All show sharp increases in AOU and DIN with depth to values near 250 and 40 /xM, respectively. DOC and DON profiles were inverse to those for the inorganic species, decreasing from surface values near 300 and 40 /xM, respectively, to concentrations at 2000 m of approximately 50 and 5 /xM. Although no data were tabulated for any of these profiles, the nominal DOC/DON ratios for all samples can be seen to closely approximate Redfield values near 7. Molecular weight analysis by gel filtration of waters from two of the three profiles again indicated that most of the DON and DOC occurred in molecules >4000 amu, which were reported to make up ~90% of surface DON and DOC. The relationship that most captured the attention of the oceanographic community, however, was the reported near-linear inverse relationship between DOC and AOU measurements for all three profiles (Fig. 10). The slope of this trend was very near 1.0, which led the authors to conclude that "the AOU in water can be explained by the in situ decomposition of DOC." Based on such evidence, Sugimura and Suzuki inferred that previous findings of little or no relationship between AOU and DOC
Why Dissolved Organics Matter
19 AOU, DIG, ^iM
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DON, DIN, TDN, |iM Figure 9 DON, DOC, DIN, and AOU depth profiles in the western Pacific Ocean at 19°01' N, 134°00' E (after Fig. 1 la of Sugimura and Suzuki (1988), with TDN determined graphically as DIN + DON).
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Figure 10 DOC versus AOU from all three depth profiles in the western Pacific Ocean published by Sugimura and Suzuki (1988).
20
John L Hedges
(e.g., Figs. 3 and 4) were the result of incomplete persulfate- and UV-based DOC measurements. As has been pointed out (Williams and Druffel, 1988; Farrington, 1992), however, there were reasons to question the Sugimura and Suzuki findings and conclusion. One conceptual problem pertains to the likelihood of a nearly linear relationship of DOC versus AOU at a molar slope near 1 (Fig. 10). This is because the initial concentration of DOC in seawater at the time it sinks from the surface is not physically controlled within a narrow range (Toggweiler, 1989a), as is the initial concentration of oxygen gas (by its solubility). In fact, the DOC concentrations in local surface seawaters reported by Sugimura and Suzuki in the same 1988 paper varied by over 100 /xM (Fig. 8), even when the five high values measured for low salinity samples in the East China Sea are excluded. Moreover, waters collected over the upper 2000 m of the water colunm in the western North Pacific do not all have the same geographic origin or time of sinking and thus also do not represent a common degradation history that would closely couple DOC/AOU trends down the depth profile (Toggweiler, 1989a). Also at issue is whether DOM is likely alone to support respiration throughout the top two kilometers of the western North Pacific Ocean. Large concentrations of dissolved organic phosphorous and nitrogen that should accompany the higher concentrations of DOC measured by Pt-catalyzed HTCO instruments in the surface ocean were not measured by other researchers (Karl et al, 1993; WilUams and Druffel, 1988). Why the "excess" DOM missed by relatively severe wet chemical oxidation should nevertheless be readily utilized by microorganisms in the upper thermocline also was unclear (Toggweiler, 1989b). By this time it had become widely recognized from sediment trap studies that sinking particles are a major sink for O2 and a source of dissolved nutrients, in the interior ocean (Knauer et al, 1979; Martin et al, 1987). Appreciable in situ degradation of sinking particles, however, would decrease the slope of DOC/AOU relationship to values considerably less than one (Fig. 4). In addition, any surface seawater that downwelled containing 40 /xM DON and >300 /xM DOC would have more than enough reducing potential (>380 /xM) in DOM alone to remove all the oxygen it could possibly dissolve (~350 /xM O2, at 0°C and salinity of 35; Broecker and Peng, 1982). Such waters would be highly prone to anoxia if in addition they hosted any in situ respiration of sinking organic particles. Sinking bioactive particles also would be expected to cause a pronounced downward displacement in TDN profiles, which is not evident in Fig. 9. These inconsistencies, however, were difficult to test at the time because the exact composition of the platinized alumina support (Sumitomo Chemical Industry Co. Ltd.), which appeared to be critical to the efficient performance of the Sugimura and Suzuki HTCO DOC and DON analyzers, was proprietary information. Another hurdle for comparative measurements was the authors' report that reliable DOC results could be obtained only when seawater samples were filtered and immediately analyzed
Why Dissolved Organics Matter
21
aboard ship. In addition, neither reference seawater samples nor DOM-free water for blank testing were widely available to the oceanographic community at that time. Not surprisingly, the "revolutionary" (Toggweiller, 1989a)findingsof Sugimura and Suzuki generated a rush by other research groups to acquire and apply Pt-catalyzed HTCO units for DOC and DON analyses. Not only did such instruments appear to measure DOC and DON more efficiently than predecessors employing wet chemical oxidation, they also were faster, easier, more readily automated and required much smaller sample volumes (~ 100 /xL) than were necessary (5 mL) for the standard persulfate method. By 1991, Pt-catalyzed HTCO analyzers for DOC and DON were available from at least six different companies and were in use by more than 20 research groups in the oceanographic community (Hedges et al, 1993). Data both supporting and refuting the "New" DOC/DON hypothesis flooded the oceanographic literature. Theories for why this previously unknown component of seawater DOM was measurable only by Pt-HTCO analyzers proliferated, as did papers attempting to characterize these materials and investigate their biogeochemical importance (see Hedges and Lee, 1993). Unfortunately, the results of these follow-ups were mixed, including two papers (Benner et al, 1992; Ogawa and Ogura, 1992) that cast doubt on most of Suzuki's size distribution and composition findings. Such divergent observations in the early 1990s caused confusion, consternation, and cautious support by national agencies for DOM research. The growing furor led to an NSF/NOAA/DOE-sponsored workshop on the "Measurement of Dissolved Organic Carbon and Nitrogen in Natural Waters" that was held in Seattle in July 1991 (Hedges and Lee, 1993). To assess measurement uniformity within the oceanographic conmiunity, ampoulated samples of surface, mid-depth, and deep-ocean waters collected at the Hawaii ALOHA station (and from a Hawaiian river) were distributed before the workshop to invited participants. A total of 13 independent DON measurements, and 34 independent DOC analyses of the sample suite were made. The results were not encouraging (Hedges et al., 1993). The DON measurements varied by an average of ±30% of the mean value for the samples and were not related to any known aspect of the analyzers or their use. The corresponding DOC concentrations varied by an average of ±40% of the mean values, with HTCO instruments generally measuring higher concentrations than were obtained for the same samples by more conventional wet-chemical techniques (Fig. 11). The DOC differences, however, largely disappeared when the mean value for each analyst's four individual samples was subtracted from the corresponding individual measurements (Hedges et al, 1993). Such a pattern following mean subtraction would be expected if the major sources of difference among DOC concentrations measured by the participating labs were traceable to large background signals intrinsic to each instrument and its method of operation.
22
John I. Hedges 350| 300
" Oj Minimum Zone
250| ^ 200| U Surface Ocean
lOOl 5o| Deep Ocean 0
Means from Each Set of Analyses Figure 11 Trends in measured DOC among reference seawater samples analyzed for the Seattle DOC/DON Workshop (data from Hedges et ai, 1993). Individual data sets are listed in order of decreasing measured concentration for the surface sample. Analyses by wet chemical oxidation methods are indicated by shaded backgrounds.
Supporting evidence for large DOC blanks intrinsic to HTCO-based instruments came from additional workshop reports. In particular, a critical evaluation by Benner and Strom (1993) of the analytical blank associated with DOC measurements using HTCO instruments showed that the platinized-alumina packing used in the combustion columns of almost all of the tested commercially-available analyzers (Shimadzu, Aldrich and Sumitomo) generated large initial blanks equivalent to 50 to >200 /xM of DOC in a 200-/xL injection. A sample of the type of support distributed by Sumitomo and used in the Sugimura and Suzuki HTCO system gave an initial instrument blank value equivalent to 90 /xM of DOC, which could only be reduced to 27 di 5 /xM by 100 sequential injections of reoxidized water. DON measurements (by persulfate or HTCO) approaching the 40 /xM levels routinely reported by Suzuki et al (1985) and Sugimura and Suzuki (1988) were not later measured (e.g. Walsh, 1989; Hansell, 1993; Koike and Tupas, 1993; Karl et al, 1993). Subsequent to these findings, and to a report by Tanoue (1992) of much lower DOC and DON concentrations obtained in the western North Pacific with an improved HTCO analyzer, Suzuki (1993) retracted the data presented in both his 1985 and 1988 papers. The reasons for the unusually high and closely correlated DON and DOC concentrations appearing in the two retracted papers were not completely clear, although inappropriate attention to instrument blanks was apparently a major problem (Suzuki, 1993). Essentially none of the concentration,
Why Dissolved Organics Matter
23
elemental composition or size distribution results published in the two Suzuki papers has been subsequently confirmed.
VI. WHY DISSOLVED ORGANICS MATTER In view of the huge community response to "New" DOC and the subsequent spate of research on DOM that is described in the following chapters, it is interesting to evaluate why this high level of interest and productivity has been sustained through what could have been a discouraging setback brought about by the Suzuki retractions. In the case of DOM research, much of the reason for this continued level of research activity is traceable to major advances in parallel fields. One of these allied developments has been steadily increasing interest in the global carbon cycle, especially as it relates to greenhouse gases such as CO2 and associated climate change. The birth of this movement can be traced to Svante Arrhenius (1896), who pointed out that humans are increasing atmospheric CO2 concentrations by burning fossil fuels. Arrhenius made the remarkable estimate that a doubling of atmospheric CO2 concentration would lead to a 5-6°C increase in the average temperature of the Earth's surface. Over 50 years later, the reality of increasing atmospheric CO2 concentrations was demonstrated by direct measurements (e.g.. Keeling, 1973; Keeling et al, 1995) and the magnitude of the Arrhenius temperature projection was supported by numeric global climate models (Houghton et al, 1996). Both the great size and potential dynamics of the ocean DOM pool have brought it within the focus of global cycle research (Williams and Druffel, 1988; Toggweiler, 1989b, Hedges, 1992). Because the amounts of carbon in oceanic DOM (--700 x 10^^ g) and atmospheric CO2 (^750 x 10^^ g) are similar (Siegenthaler and Sarmiento, 1993), net oxidation of only 1 % of the seawater DOM pool within 1 year would be sufficient to generate a CO2 flux larger than that produced annually by fossil fuel combustion. Concentration differences of this magnitude would be extremely difficult to identify due to the current limits of analytical precision and the heterogeneous distributions of DOC in the ocean. It is not surprising, therefore, that the Sugimura and Suzuki 1988 report of roughly twice as much total DOC in the ocean as was previously measured gained the immediate attention of the oceanographic conmiunity. In addition to greatly raising the global stakes for budgeting actively cycling organic carbon, this report placed three to six times more DOM in the surface ocean where the bulk of this uncharacterized material appeared to be biologically active on time scales of years to decades (Toggweiler, 1989b). This apparent increase in the organic acid component of seawater was also of substantial interest as a potential explanation for the discrepancy between total CO2 measurements in seawater by potentiometric versus manometric methods
24
John I. Hedges
(Bradshaw and Brewer, 1988). Quantitative constraints on organic matter cycling are particularly difficult in the physically and biologically active upper surface ocean (Quay, 1997), where DOC versus POC exports are difficult to distinguish and DOM photodegradation can accompany photosynthesis. Given the susceptibility of DOC to photolysis (Kieber et ai, 1989; Vodacek et al, 1997) and subsequently biodegradation (Benner and Biddanda, 1998), as well as the rapid increases in UV irradiation of the deeply mixed hub for global thermohaline circulation in the Southern Ocean (Solomon, 1999), an assumption that the contemporary oceanic DOM pool is at steady state seems questionable. Another development that has greatly increased interest in DOM distributions and dynamics over the past three decades has been growing recognition that dissolved organic substrates are important intermediates in rapid cycling of bioactive elements within the ocean (Pomeroy, 1974; Azam and Hodson, 1977). This "microbial loop" from DOM to bacteria, to protists and zooplankton became evident from measurements of heterotrophic bacterial production that typically demanded 20-40% of the local average carbon fixation rate (Azam and Fuhrman, 1984). The only means of supplying such a large a flux of nutrients is by rapid cycling of DOM released by a variety of processes including phytoplankton exudation, viral lysis, and protozoan and zooplankton grazing (Jumars et ai, 1989; Nagata, 2000). Given a global net primary production of ~50 x 10^^ g C/year, the microbial loop would appear to pass the DOM equivalent of at least 10-20 x 10^^ g C/year. If applied uniformly throughout the ocean, this respiration flux could turn over the entire marine DOC pool in less than 100 years, compared to its ^"^C-based "age" of thousands of years. The reason for this discrepancy, of course, is that a small fraction of seawater DOC is recycled biologically in the surface ocean at an exceedingly rapid rate. The "survivor" molecules left behind to accumulate in the DOM pool must nevertheless be subjected to continuous and severe bacterial pressure. Thus, any chink in their molecular armor, such as might be imparted by photolysis (Benner and Biddanda, 1998), abiotic chemical oxidation (Sunda and Kieber, 1994), or physical transformation into gels (Chin et ai, 1998) might lead to rapid and efficient remineralization to CO2. Conversely, the chemical and conformational characteristics of those organic substances that can withstand such concerted attacks for thousands of years in the ocean DOM pool may carry the molecular Rosetta stone for deciphering the degradation mechanisms responsible for recycling the other 99.9% of global primary production (Hedges, 1992). Thus, we have much to learn from both the fast- and the slow-cycling components of ocean DOM. There are many other reasons for continued and growing interest in the forms and reactions of seawater DOM. For example, some molecules dissolved in seawater strongly complex trace metal ions, greatly affecting their bioavailability and toxicity (Buffle, 1988; Kozelka and Bruland, 1998). Dissolved organic molecules also can affect the surface properties of minerals (Stumm, 1992), act as aquatic
Why Dissolved Organics Matter
25
telemediators (Gauthier and Aubert, 1981), and change the spectral properties of seawater (Whitehead and Vemet, 2000). Recent demonstrations that the lignin components of seawater vary in composition and concentration with geographic source (Opsahl and Benner, 1997; Opsahl et ai, 1999) and photodegradation history (Opsahl and Benner, 1998) point toward a future where dissolved organic molecules will provide detailed information about the origins and physical histories of their parent waters. Ultimately, however, the biogeochemical usefulness of any class of chemical tracers is limited by its structural diversity (Blumer, 1976) and the range of its sources, input functions, and chemical reactivities (Middelburg, 1989). It is clear, therefore, that the information content of organic molecules, which also carry imbedded stable isotopic signatures and radiochemical clocks, is unsurpassed by any other seawater component. The 10^^ diverse organic molecules dissolved in every milliliter of seawater are the only constituents whose stored information approaches the richness needed to understand where that water has been and what has happened within it over time. The future of oceanographic research belongs in large part to those who can learn to read these molecular messages.
VII. WHAT DID WE LEARN? Setbacks can be useful learning experiences. The following chapters are testimony that the oceanographic community not only persisted through the "New" DOC experience, but also gained substantially from it in numerous ways over the past decade. First of all, HT(C)0 (now often used without oxidation catalyst) analyzers were fundamentally a great idea and are becoming the instruments of choice for analyses of DOC and DON in laboratories and aboard ships. With appropriate attention to blanks and sample handling, the precision and accuracy of DOC analysis by HT(C)0 have improved to the point that meaningful comparisons among deep-ocean waters and within surface ocean time series have become feasible. In addition, the minimal volume requirements of these analyzers have opened the door to multiple analyses of limited volumes of water from such sources as sediments and experimental incubations. It seems feasible that HT(C)0 analyzers will soon be employed for rapid analysis of the stable carbon isotope composition of DOC in individual samples or used in batch mode to obtain sufficient carbon for ^"^C analysis by accelerator mass spectrometry. Second, we (should) also have come to appreciate the immense importance of carefully developing and rigorously testing new analytical methods. Although fresh concepts will continue to be the primary means of advancement in oceanographic research, it is clear from this retrospective that new perceptions almost always ride the back of improved methods for DOM isolation (e.g., dipped prisms, hydrophobic sorption, and tangential-flow ultrafiltration) and characterization (e.g., stable isotopes, NMR and sensitive molecular analyses). Along with the power to make
26
John I. Hedges
such major advances, however, comes the responsibiUty to adequately test and describe new analytical methods, pointing out their weaknesses as well as their advantages. Editors and reviewers of papers describing new analytical methods also carry the burden of protecting the scientific community (and authors) from published oversights that can propagate for years to great disadvantage. Given the reality that it is often the makers of analytical tools, rather than the wielders, who pace modem scientific advances, this rare skill seems underappreciated overall. Many journals covering the aquatic sciences in fact exclude or strongly discourage "analytical papers," even when the research they describe clearly has been developed specifically to attack biogeochemical research problems. Funding agencies and peer reviewers are often reluctant to fund strictly analytical projects or proposals that involve innovative measurement techniques. Analytical chemistry departments in many universities are presently being dismantled or recombined into topical entities that no longer emphasize or adequately train students in the basics of sound analytical methods. Although the current trend by oceanographers toward broad interests and general skills is healthy, a critical mass of analytically oriented investigators with sufficient chemical understanding to imagine the potential pitfalls involved with measurements of trace organic substances in an ocean of salt will always be required. Finally, the Seattle DOC/DON Workshop and subsequent efforts on the part of Jon Sharp and many other oceanographers demonstrated the tremendous logistical advantage of readily available reference samples and the power of communitywide efforts focused on a shared challenge. The crucial demonstration of a problem in DOC and DON analyses in the early 1990s (Fig. 11) came directly from painstaking analyses by the more than 25 different research groups that participated voluntarily in the Seattle Workshop. Fittingly, the diagnostic offsets in this data set also indicated an experimental path toward resolution that proved to be fruitful. The DOC/DON community also is notable as one of the few oceanographic guilds with an organic orientation that successfully has estabhshed a system for providing widely available reference samples (of low-DOC and deep-ocean water) for blank testing and comparisons among (and within) individual labs. Notably, both actions have involved close collaborations in planning and execution within the marine scientific community and their funding organizations. That these combined efforts have borne such extensive scientific fruit over the past decade (see following chapters) bodes well for future research on the fascinating topic of dissolved organic molecules in the ocean.
ACKNOWLEDGMENTS I thank the editors of this book for their encouragement and guidance. This manuscript benefited greatly from reviews by Ron Benner, Ellen Druffel, John Farrington, Michael Peterson, Jon Sharp, and Kenia Whitehead.
Why Dissolved Organics Matter
27
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Hedges, J. L, and Lee, C. (1993). Measurement of dissolved organic carbon and nitrogen in natural waters. Mar. Chem. 41, 1-290. Hodge, J. E. (1953). Chemistry of browning reactions in model systems. Agnc. Food Chem. 1,828-943. Hood, D. W. (1970). "Organic Matter in Natural Waters." Institute of Marine Science, Fairbanks, AK. Holm-Hansen, O., Strickland, J. D. H., and Williams, P. M. (1966). A detailed analysis of biologically important substances in a profile off Southern California. Limnol. Oceanogr. 11, 548-561. Houghton, J. T., Meira Filho, L.G., Callander, B. A., Harris, N., Kattenberg, A., and Maskell, K. (1996). "Climate Change 1995: The Science of Climate Change." Cambridge University Press, New York. Hunter, K. A., and Liss P. S. (1981). Organic sea surface films. In "Marine Organic Chemistry" (E. K. Duursma and R. Dawson, Eds.), pp. 259-298. Elsevier, Amsterdam. Ittekkot, V. (1982). Variations of dissolved organic matter during a plankton bloom: Qualitative aspects based on sugar and amino acid analyses. Mar. Chem. 11,143-158. Ittekkot, v., Brockmann, U., Michaelis, W, and Degens, E. T. (1981). Dissolved free and combined carbohydrates during a phytoplankton bloom in the northern North Sea. Mar Ecol. Prog. Sen 4, 299-305. Jaanasch, H. W (1967). Growth of marine bacteria at limiting concentrations of organic carbon in seawater. Limnol. Oceanogr 12,264-271. Jackson, G. A., and WiUiams, P. M. (1985). Importance of dissolved organic nitrogen and phosphorus to biological nutrient cycling. Deep-Sea Res. 2>1, 223-235. Jarvis, N. L. (1967). Adsorption of surface active material at the air-sea interface. Limnol Oceanogr 12,213-221. Jeffrey, L. M., and Hood, D. W. (1958). Organic matter in seawater; An evaluation of various methods for isolation. /. Mar Res. 17,247-271. Johnston, R. (1955). Biologically active compounds in the sea. /. Mar Biol. Assoc UK 34,185-195. Jumars, P. A., Penry, D. L., Baross, J. A., Perry, M. J., and Frost, B. W (1989). Closing the microbial loop: dissolved carbon pathway to heterotrophic bacteria from incomplete ingestion, digestion and absorption in animals. Deep-Sea Res. 36,483^95. Kalle, K. (1937). Nahrstoff Untersuchungen als hydrographisches Hilfsmittel zur Unterscheiding von Wasserkorpen. Annu. Hydrogr Berlin 65, 276-282. Kalle, K. (1949). Fluoreszenz und Gelbstoff im Bottnischen und Finnischen Meerbusen. Dtsch. Hydrogr Z. 2,111-124. Kalle, K. (1966). The problem of gelbstoff in the sea. Oceanogr Mar Biol. Ann. Rev. 4, 91-104. Karl, D. M., Tien, G., Dore, J., and Winn, C. D. (1993). Total dissolved nitrogen and phosphorus concentration at US-JGOFS Station ALOHA: Redfield reconciliation. Mar Chem. 41, 203-208. Kay, H. (1954). Untersuchungen zur Menge und Verteilung der organischen Substanz im Meerwasser. Keil. Meeresf. 10,202-213. Keeling, C. D. (1973). Industrial production of carbon dioxide from fossil fuels and limestone. Tellus 25,174-198. Keeling, C. D., Whorf, T. R, Whalen, M., and van der PUcht, J. (1995). Interannual extremes in the rate of rise of atmospheric carbon dioxide since 1980. Nature 375, 666-670. Kerr, R. A., and Quinn, J. G. (1975). Chemical studies on the dissolved organic matter in seawater. Isolation and fractionation. Deep-Sea Res. 22,107-116. Kieber, D. J., McDaniel, J., and Mopper, K. (1989). Photochemical source of biological substrates in sea water: Implications for carbon cycling. Nature. 341,637-639. Kieber, D. J., and Mopper, K. (1987). Photochemical formation of glyoxylic and pyruvic acids in seawater. Mar Chem. 21,135-149. Koike, I., and Tupas, L. (1993). Total dissolved nitrogen in the North Pacific assessed by a hightemperature combustion method. Mar Chem. 41,209-214. Knauer, G. A., Martin, J. H., and Bruland, K. W. (1979). Fluxes of particulate carbon, nitrogen and phosphorus in the upper water column of the northeast Pacific. Deep-Sea Res. 26, 97-108.
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Kozelka, P. B., and Bruland, K. W. (1998). Chemical speciation of dissolved Cu, Zn, Cd, Pb, in Narragansett Bay, Rhode Island. Mar. Chem. 60,267-282. Kramer, C. J. M. (1979). Degradation by sunlight of dissolved fluorescing substances in the upper layers of the eastern Atlantic Ocean. Neth. J. Sea Res, 13, 325-329. Krogh, A. (1934a). Conditions of life in the ocean. Ecol. Monogr. 4,421-429. Krogh, A. (1934b). Conditions of Ufe at great depths in the ocean. Ecol. Monogr. 4,430^39. Krogh, A., and Keys, A. (1934). Methods for the determination of dissolved organic carbon and nitrogen in sea water. Biol. Bull. 67, 132-144. Laane, R. W. P. M. (1982). Influence of pH on the fluorescence of dissolved organic matter. Mar Chem. 11,395-401. Laane, R. W. P. M. (1984). Comment on the structure of marine fulvic and humic acids. Mar Chem. 15, 85-87. Lee, C , and Bada, J. L. (1975). Amino acids in Equatorial Pacific Ocean water. Earth Planet. Sci. Lett. 26,61-68. Lee, C , and Bada, J. L. (1977). Dissolved amino acids in the Equatorial Pacific, Sargasso Sea and Biscayne Bay. Limnol. Oceanogr 22, 502-510. Liebezeit, G., Bolter, M., Brown, I. F., and Dawson, R. (1980). Dissolved free amino acids and carbohydrates at pycnocline boundaries in the Sargasso Sea and related microbial activity. Oceanol Acta 3, 357-362. Liss, P. S. (1975). The chemistry of the sea surface microlayer. In "Chemical Oceanography" (J. P. Riley and G. Skirrow, Eds.), Vol. 2, pp. 193-243. Academic Press, London. Little, B., and Jacobs, J. (1985). A comparison of two techniques for the isolation of adsorbed dissolved organic material from seawater. Org. Geochem. 8, 27-33. Maclntyre, F. (1966). Bubbles: A boundary layer microtome for micron-thick samples of a water surface. J. Phys. Chem. 72, 589-592. Mackinnon, M. D. (1978). A dry oxidation method for analysis of the TOC in seawater. Mar Chem. 7, 17-37. Maillard, L. C. (1913). Formation de matieres humiques par action de polypeptides sur sucres. CR Acad. Sci. 156, 148-149. Mantoura, R. F. C , and Riley, J. P. (1975). The analytical concentration of humic substances from natural waters. Anal. Chem. Acta 76, 97-106. Mantoura, R. F. C , and Woodward, E. M. S. (1983). Conservative behavior of riverine dissolved organic carbon in the Severn Estuary: Chemical and geochemical implications. Geochim. Cosmochim. Acta 47,1293-1309. Martin, J. H., Knauer, G. A., Karl, D. M., and Broenkow, W. W. (1987). VERTEX: Carbon cycling in the northeast Pacific. Deep-Sea Res. 34, 267-285. Maurer, L. G. (1976). Organic polymers in seawater: Changes with depth in the Gulf of Mexico. Deep-Sea Res. 23, 1059-1064. McCave, I. N. (1975). Vertical flux of particles in the ocean. Deep-Sea Res. 22,491-502. Menzel, D. W. (1964). The distribution of dissolved organic carbon in the western Indian Ocean. Deep-Sea Res. 11,757-765. Menzel, D. W., and Ryther, J. H. (1968). Organic carbon and the oxygen minimum in the South Atlantic Ocean. Deep-Sea Res. 15, 327-337. Menzel, D. W., and Ryther, J. H. (1970). Distribution and cycling of organic matter in the oceans. In "Organic Matter in Natural Waters" (D. W Hood, Ed.), pp. 31-54. Institute of Marine Science, Alaska. Menzel, D. W, and Vaccaro, R. F (1964). The measurement of dissolved and particulate organic carbon in the sea. Limnol. Oeanogr 9, 138-142. Meybeck, M. (1982). Carbon, nitrogen and phosphorus transport by world rivers. Am. J. Sci. 282, 401^50.
Why Dissolved Organics Matter Meyers-Schulte, K. J., and Hedges, J. I. (1986). Molecular evidence for a terrestrial component of organic matter dissolved in ocean water. Nature 321,61-63. Middelburg, J. J. (1989). A simple rate model for organic matter decomposition in marine sediments. Geochim. Cosmochim. Acta 53, 1577-1581. Momzikoff, A., Santus, R., and Giraud, M. (1983). A study of the photosensitizing properties of seawater. Mar. Chem. 12, 1-14. Mopper, K:, Dawson, R., Liebezeit, G., and Hansen, H-R (1980). Borate complex ion exchange chromatography with fluorimetric detection for determination of saccharides. Anal. Chem. 52, 20182022. Mopper, K., and Stahovec, W. L. (1986). Sources and sinks of low molecular weight organic carbonyl compounds in seawater. Mar Chem. 19, 305-321. Morris, R. J. (1974). Lipid composition of surface films and zooplankton from the eastern Mediterranean. Mar Pollut. Bull. 5, 105-109. Nagata, T. (2000). Production mechanisms of dissolved organic matter. In "Microbial Ecology of the Oceans" (D. L. Kirchman, Ed.), pp. 121-152. Wiley-Liss, New York. Ogawa, H., Fukuda, R., and Koike, I. (1999). Vertical distributions of dissolved organic carbon and nitrogen in the Southern Ocean. Deep-Sea Res. 746, 1809-1826. Ogawa, H., and Ogura, N. (1992). Comparison of two methods for measuring dissolved organic carbon in sea water. Nature 356, 696-698. Ogura, N. (1975). Further studies on decomposition of dissolved organic matter in coastal seawater. Mar Biol. 31, lOl-ni. Ogura, N. (1977). High molecular weight organic matter in seawater. Mar Chem. 5, 535-549. Ogura, N. (1970). The relation between dissolved organic carbon and apparent oxygen utilization in the Western North Pacific. Deep-Sea Res. 17, 221-231. Opsahl, S., and Benner, R. (1997). Distribution and cycling of terrigenous dissolved organic matter in the ocean. Nature 386,480^82. Opsahl, S., and Benner, R. (1998). Photochemical reactivity of dissolved lignin in river and ocean waters. Limnol. Oceanogr 43,1297-1304. Opsahl, S., Benner, R., and Amon, R. M. W. (1999). Major flux of terrigenous dissolved organic matter through the Arctic Ocean. Limnol. Oceanogr 44, 2017-2023. Plunkett, M. A., and Rakestraw, N. W. (1955). Dissolved organic matter in the sea. Deep-Sea Res. 3, 12-14. Pomeroy, L. R. (1974). The ocean's food web, a changing paradigm. Bioscience 24,499-504. Putter, A. (1909). Die Emahrung der Wassertiere und der Stoffhaushalt der Gewasser. Jena, 1909. Quay, P. (1997). Was a carbon balance measured in the equatorial Pacific during JGOFS? Deep-Sea Res. 44,1765-1781. Raben, E. (1910). 1st organischen Kohlenstoff in nennenswerter Menge im Meerwasser gelost vorhanden? Wiss. Meeresunt. Abt. Kiel NF11, 111-117. Redfield, A. C , Ketchum, B. H., and Richards, F. A. (1963). The influence of organisms on the composition of sea water. In "The Sea" (M. N. Hill, Ed.), pp. 26-77. Interscience, New York. Riley, J. P., and Taylor, D. (1969). The analytical concentration of traces of dissolved organic materials from sea water with Amberlite XAD-1 resin. Anal. Chim. Acta 46, 307-309. Sakugawa, H., and Handa, N. (1985). Isolation and chemical characterization of dissolved and particulate polysaccharides in Mikawa Bay. Geochim. Cosmochim. Acta 49, 1185-1193. Sakugawa, H., Handa, N., and Ohta, K. (1985). Isolation and characterization of low molecular weight carbohydrates dissolved in seawater. Mar Chem. 17, 341-362. Sharp, J. H. (1973a). Size classes of organic carbon in seawater. Limnol. Oceanogr 18,441-447. Sharp, J. H. (1973b). Total organic carbon in seawater—Comparison of measurements using persulfate oxidation, and high temperature combustion. Mar Chem. 1, 211-229.
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Vodacek, A., Blough, N. V., DeGrandpre, M. D., Peltzer, E. T., and Nelson, R. K. (1997). Seasonal variation of CDOM and DOC in the Middle Atlantic Bight: Terrestrial inputs and photooxidation. Limnol. Oceanogr. 42, 674-686. Waksman, S. A., and Carey, C. L. (1935). Decomposition of organic matter in sea water by bacteria. /. Bacteriol 29,531-543. Walsh, T. W. (1989). Total dissolved nitrogen in seawater: A new high-temperature combustion method and a comparison with photo-oxidation. Mar. Chem. 26, 295-311. Whitehead, K., and Vemet, M. (2000). Influence of mycosporine-like amino acids (MAAs) on the UV absorption of particulate and dissolved organic matter in La JoUa Bay. Limnol Oceanogr. 45, 1788-1796. Willey, J. D., and Atkinson, L. P. (1982). Natural fluorescence as a tracer for distinguishing between piedmont and coastal plain river water in the nearshore waters of Georgia and North Carolina. Estuarine Coastal Shelf ScL 14,49-59. Wilhams, P. J. le B. (1975). Biological and chemical aspects of dissolved organic matter in sea water. In "Chemical Oceanography" (J. P. Riley and G. Skirrow, Eds.), Vol. 2, pp. 301-363. Academic Press, New York. Wilhams, P. M. (1968a). Organic and inorganic constituents of the Amazon River. Nature 218,937-938. Wilhams, P. M. (1968b). Stable carbon isotopes in the dissolved organic matter of the sea. Nature 219, 152-153. Williams, P. M. (1969a). The wet oxidation of organic matter in seawater. Limnol. Oceanogr 14, 292-297. Williams, P. M. (1969b). The determination of dissolved organic carbon in seawater: A comparison of two methods. Limnol Oceanogr 14, 297-298. Wilhams, P. M. (1971). The distribution and cycling of organic matter in the ocean. In "Organic Compounds in the Aquatic Environment" (S. D. Faust and J. V. Hunter, Eds.), pp. 145-163. Dekker, New York. Williams, P. M., and Carlucci, A. F. (1976). Bacterial utihsation of organic matter in the deep sea. A^fl^Mr^ 262, 810-811. Wilhams, P. M., and Druffel, E. R. M. (1987). Radiocarbon is dissolved organic matter in the central North Pacific Ocean. Nature 339,246-248. Wilhams, P. M., and Druffel, E. R. M. (1988). Dissolved organic matter in the ocean: comments on a controversy. Oceanography 1, 14-17. Williams, P. M., and Gordon, L. I. (1970). Carbon-13:carbon-12 ratios in dissolved and particulate organic matter in the sea. Deep-Sea Res. 17,19-27. Williams, P. M., Oeschger, H., and Kinney, P. (1969). Natural radiocarbon activity of dissolved organic carbon in the Northeast Pacific Ocean. Nature 224, 256-258. Wilson, D. P., and Armstrong, F. A. (1952). Further experiments on biological differences between natural sea waters. /. Mar Biol Assn. UK 31, 335-349. Wilson, M. A., Gillam, A. H., and Collins, P. J. (1983). Analysis of the structure of dissolved marine humic substances and their phytoplanktonic precursors by ^H and ^^C nuclear magnetic resonance. Chem. Geol 40, 187-201. Wilson, M. A., Philp, R. P, Gillam, A. H., Gilbert, T. D., and Tate, K. R. (1983). Comparison of the structures of humic substances from aquatic and terrestrial sources by pyrolysis gas chromatographymass spectrometry. Geochim. Cosmochim. Acta 47,497-502. Zepp, R. G., Schlotzhauer, P. F., and Sink, R. M. (1985). Photosensitized transformations involving electronic energy transfer in natural waters: Role of humic substances. Environ. ScL Technol 19, 74-81.
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Chapter 2
Analytical Methods for Total DOM Pools Jonathan H. Sharp Graduate College of Marine Studies, University of Delaware, Lewes, Delaware I. Introduction II. Dissolved Organic Carbon Analysis A. Historical Perspective B. The Analytical Problem C. Small Group Methods Comparisons D. Broad Community Methods Comparisons III. Dissolved Organic Nitrogen Analysis A. Historical Perspective and the Analytical Problem B. Small Group Methods Comparisons
C. Current and Future Broad Community Methods Comparison IV. Dissolved Organic Phosphorus Analysis A. Historical Perspective and the Analytical Problem B. Small Group Methods Comparisons V. Multielemental Methods VI. The Limits of Elemental Analyses VII. The Need for Continual use of Reference Materials References
I. INTRODUCTION For over a century, there has been interest in quantifying the pool of dissolved organic matter (DOM) in the sea and in other aquatic environments. Some of the early efforts included attempts to quantify "humic substances" and to measure colored material, "gelbstoffe" (Duursma, 1965). Specific organic compounds have been measured and attempts have been made to understand origins and fates of Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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these compounds for decades (Duursma, 1965; Williams, 1975; Menzel, 1974). Analysis of specific compounds and dynamics of organic matter in the sea are discussed in several other chapters of this book. While that type of research is possibly more interesting and fruitful, depending upon the questions asked, more energy has been expended overall to quantify the gross amount of DOM. For much of the past century, the usual currency for quantifying the DOM has been dissolved organic carbon (DOC). A general rule of thumb, not much used today, was that the weight of the total organic matter pool is two times that of the measured organic carbon (Krogh, 1934). Thus, one of the main reasons for measuring DOC has been to quantify the total DOM. Fewer measurements have also been made over the years of dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP). It is unfortunate that sometimes DOC, DON, and DOP are viewed as specific and separate entities. It is probably useful to recognize that these are three subsets of the same DOM. Measurement of them is quantitative, but not really qualitative in terms of characterizing the DOM pool. They take on separate importance when considering the total pools of carbon, nitrogen, and phosphorus in the sea. Measurements of DOC, DON, and DOP have often been performed routinely as minor side parameters in biological or multidisciplinary studies; until recently, these analyses were downplayed or ignored by much of the geochemical community. In this chapter, the focus is on "dissolved" organic matter with the assumption that particles can be removed by filtration through a microporous filter. Such filtration, essential in nearshore waters, is often omitted in oceanic waters where the total organic matter is almost all "dissolved"; e.g., TOC ^ DOC. With the high DOC and DON concentrations reported by Suzuki (Suzuki et al, 1985; Sugimura and Suzuki, 1988), measurements of DOM took on new importance in relation to the global carbon cycle (Toggweiler, 1989). These high concentrations and odd depth distributions also required rethinking of nitrogen and phosphorus cycles as well as carbon cycles (Williams and Druffel, 1988; Jackson, 1988; Toggweiler, 1992). The "controversy" on DOM measurements led to the Seattle workshop (Williams, 1992) that has guided much effort since then (Sharp, 1997). The increased international interest on measurement of DOM makes accurate analyses critical. Prior to this new interest, there were many small "internal" methods checks made to verify accuracy of methods used routinely. As will be discussed below, such efforts have not been very successful; larger, broad-community, methods comparisons ultimately can prove to be more effective in developing community analytical accuracy. Also, discussed below is the opinion of this author that strict continuing use of reference materials is essential for community accuracy. In this chapter, there will be decreasing emphasis from DOC to DON to DOP, reflective of the efforts both in performing routine measurements and in establishing accurate methods. Although routine measurements have been made for decades, the groundswell of interest has propelled DOC analysis into the limelight for the
Analytical Methods for Total DOM Pools past 15 years. Currently, there is more interest in the measurement of DON than in the recent past and an international methods comparison is ongoing through my laboratory. DOP has been more of a poor relative compared to DOC, but some small internal comparisons have been made recently, which will be discussed. Analyses of DOC, DON, and DOP are considered separately below with some historical perspective and discussion of both the small "internal" and the "broadcommunity" methods comparisons. Analytical problems in analysis of DOC are distinctly different from those of DON and DOP; so there is a brief discussion on the analytical problem in each section below.
11. DISSOLVED ORGANIC CARBON ANALYSIS A. HISTORICAL PERSPECTIVE From the earliest published measurements of DOM in seawater (Natterer, 1892), disagreement arose on the accuracy of the quantification and biological significance of the DOM pool. With methods that were soon criticized. Putter reported high concentrations of DOC and suggested that the high concentrations which originated from plankton blooms served as a major food for invertebrates (Putter, 1909). His work was questioned for accuracy of measurement of DOC and DON; ultimately, better methodology discounted his work (Krogh and Keys, 1934). The methods used for the earlier research and all other methods through the 1950s employed some form of wet chemical oxidation (WCO) and colorimetric or gravimetric determination of the resultant oxidation product, CO2. In the late 1950s, Soviet scientists started using high-temperature combustion (HTC) for oxidation of dried samples followed by colorimetric analysis of CO2 (see Skopintsev et al, 1966). The first electronic measure of the CO2 came with the persulfate oxidation (PO) method that culminated in nondispersive infrared analysis (Wilson, 1961). This method was soon popularized as a standard method (Menzel and Vaccaro, 1964). A similar PO method that did not catch on used gas chromatography for the final CO2 determination (Fredericks and Hood, 1965). The PO method with infrared detection became the one most used by the late 1960s. Also in the 1960s, UV oxidation was established as another method for DOC analysis (Armstrong et al, 1966; Williams, 1969); but was never established as a broadly used DOC method.
B. THE ANALYTICAL PROBLEM The quantitative estimate of DOC concentration has almost always been done by conversion of all organic carbon to CO2. Prior to making the conversion.
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Jonathan H. Sharp Acidify sampie and sparge to remove dissolved inorganic carbon.
UV oxidation to convert all DOC to CO2.
Persulfate oxidation to convert all DOC to CO2.
Colorimetric measurement of CO2. All resultant CO2 represents original DOC. Figure 1
High temperature oxidation to convert all DOC to CO2.
Measurement of CO2 in nondispersive infrafed analyzer. All resultant CO2 represents original DOC.
Schematic diagram of procedural steps in commonly used DOC methods.
the dissolved inorganic carbon (DIC) must be removed from the sample, the acid-sparging step (Fig. 1). The procedure used is to acidify the sample, lowering the pH to below 2. This shifts the carbonate equilibrium so that almost all of the DIC is in the form of dissolved CO2. Bubbling this acidified sample with a gas free of CO2 will quickly remove the entire DIC pool. Actually, the removal of CO2 is asymptotic and a tiny amount remains. Experimentation has shown that the residual CO2 can easily be kept below 0.01% of the original (e.g., Sharp, 1977). After removal of the DIC, rapid and complete conversion of the DOC to CO2 requires strong oxidation (Fig. 1). Early DOC methods used exposure to strong acids or other oxidants. There is the inherent error that any easily degraded organic molecules or those that could be made volatile under mildly acidic conditions will be lost in the acid-sparging step. It has always been assumed that the acid-volatile losses are small and it has been demonstrated that the losses are on the order <5% (MacKinnon, 1979). Most methods use an acid-sparging step that does not result in too strong an acidity and does not have sparging for more than 10 min. It is probably important in WCO methods that the acid sparging step be separate from the later oxidation step. It has been suggested that the original persulfate method had an error in not separating these two steps and that DOC concentrations measured were on the order of 20% too low (Sharp, 1997). Most of the WCO methods used relatively large samples for the analysis, on the order of 5 to 100 mL. The more recent HTC methods perform analysis on samples in the 50- to 200-/xL size range. With the larger samples, there was a significant blank problem. With the HTC methods, the contribution of contamination to this problem is made even more serious because of the small sample size. The total
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signal in a 100-/xL sample of oceanic DOC is on the order of 0.1 /xg carbon. This is extremely small and background carbon is a significant problem. A major breakthrough was made in the HTC method with the realization that a very thorough preconditioning was needed to lower the blank in the oxidation tube (Benner and Strom, 1993). In the early years, WCO methods were modified with stronger and stronger oxidants to improve the chances of complete oxidation of all refractory DOC compounds (Duursma, 1961; Menzel and Vaccaro, 1964). HTC methods were introduced as superior to WCO for the same reason of more complete oxidation (van Hall et ah, 1963). With DOC analysis, as well as with DON and DOP analyses, assessment of complete decomposition of all organic matter has been made using representative recalcitrant compounds and natural water samples from the deep ocean and from humic rivers. In all cases, the idea has been to find a method that would be "complete" for all environments so that the same methods could be applied for fresh waters and sea waters ranging from estuarine to deep ocean. Preconceived ideas of expected results have hindered proper assessment of accurate DOC analysis. In the 1960s, extensive DOC analyses gave rise to an expected depth pattern with uniform low deep-water values throughout the ocean. Any data that did notfitthis pattern were suspect. Introduction of stronger oxidants for wet chemical methods in the period of the 1950s to 1960s had given rise to the concept that a method that gave higher DOC was more accurate. Thus, when HTC methods in the 1980s gave higher DOC, the preconceived low deep-water concept was abandoned and it was assumed that the new HTC method was superior. For about 5 years, any DOC analysis that did not show the higher values was suspect. The more manipulations or more steps involved and the smaller the sample, the greater the potential for blank problems. When the high DOC values of the late 1980s were rejected, lower DOC values indicated better control of and correction for blanks. Thus, a bias for level or depth pattern of DOC concentrations appeared to influence acceptance of new or modified methods for several decades. Early high-temperature combustion methods were often abbreviated as HTC. In the late 1980s, there was thought that the exact nature of the catalyst was critical and hence the method often was called high-temperature catalytic oxidation (HTCO). Throughout this chapter, the abbreviation HTC is used to mean any hightemperature combustion method, independent of catalyst.
C. SMALL G R O U P M E T H O D S COMPARISONS
Discussion of DOC methods comparisons has been made recently in an article addressing other methods comparisons (Wangersky, 2000). I will address this subject further here, especially in relation to more recent work. Because blanks
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Jonathan H. Sharp
were usually large and researchers were unable to accurately determine the blanks, almost all DOC measurements prior to the early 1990s required some preconceived idea of "good values" to decide whether or not the method was working well and whether or not values from a specific sample were contaminated. With the extensive work of Menzel and Williams in the 1960s (e.g., Menzel and Ryther, 1970; Williams and Gordon, 1970), the expected pattern of DOC depth distribution was of slightly elevated values at the surface and uniform low values below the surface. The two types of WCO methods that were employed, UV and persulfate oxidation, had been determined to measure similar quantities of DOC by a small comparison done in one laboratory (Williams, 1969). However, careful analyses of data used in this comparison and other data from these same analysts showed how nonuniform the real data were (Sharp, 1997). Other comparisons showed the UV method to measure lower DOC concentrations in seawater than persulfate (Gershey etal, 1979) and reasons for this lower yield have been proposed (Peyton, 1993). In contrast, one study in freshwater showed slightly higher DOC values by UV than by persulfate (Goulden and Brooksbank, 1975). In all of these studies, small data sets were used and it is possible now to consider some of the conclusions to be marred by blank variability. From the late 1960s through the early 1980s, there were claims of DOC concentrations found by wet or dry HTC methods that were higher (up to twofold) than those by WCO methods. Many of these claims were based on indirect comparisons of published numbers (e.g, Gordon and SutcHffe, 1973; MacKinnon, 1978) or based on analyses being done by more than one method by the authors within the same laboratory (e.g.. Sharp, 1973; Gershey etai, 1979). For the most part, claims of the higher values did not create much interest in the global carbon research community. With the enthusiasm of the oceanographic community over claims of higher values and a nonuniform subsurface DOC depth pattern (Sugimura and Suzuki, 1988), there was a large conmiunity response to this higher "new DOC." A number of publications appeared shortly with similar high DOC values, some in which Suzuki did the analyses (e.g., Druffel et al, 1989; Kirchman et al, 1991; Suzuki et al, 1992) and some in which he did not (Kepkay and Wells, 1992; Martin and Fitzwater, 1992; Druffel, 1992; Bauer et aU 1992; WiUiams et al, 1993; Miller et al, 1993a; Peltzer and Brewer, 1993). It should be noted that because of uncertainty on how to determine the absolute blank in the HTC instruments, most of the analyses found high values because of inadequate blank correction. Eventually, Suzuki requested that the data from his papers be withdrawn (Suzuki, 1993). Direct comparisons at that time between persulfate oxidation and HTC methods showed little or no difference between methods when freshwater samples were run (Kaplan, 1992; Benner and Hedges, 1993; Sharp et al, 1993a; McKenna and Doering, 1995). Direct comparisons made with seawater samples did show
Analytical Methods for Total DOM Pools
41
higher yields by HTC (Sharp et al, 1993a; Miller et al, 1993b) but when HTC analysis was done with commercial instruments, the difference was smaller than that determined by Suzuki's instrument. Another direct comparison at that time showed HTC values for oceanic samples that were on the order of 15% higher than that determined by persulfate oxidation (Ogawa and Ogura, 1992). This difference is closer to that shown 20 years earlier (Sharp, 1973). Similarly, comparison of UV oxidation to HTC (WilHams et al, 1993) showed higher values by HTC. These values were not, however, as high as when the HTC analysis was done by Suzuki directly. In all of these cases, the small differences seen could be at least partially due to the large and variable blank in one or both of the methods. With recognition of the blank problem, not only the HTC but also the WCO methods needed reevaluation. With correction using a uniform zero-carbon sample to assess the individual method blank and standardization of a single set of standards in a direct comparison, the persulfate method was shown to give results statistically the same as several HTC instruments (Sharp et al, 1993b). With the "blind analysis" and uniform blank correction discussed below, the persulfate method again gave results similar to those of several HTC instruments (Sharp et al, 1995). Using a uniform carbon-free blank and standards, several HTC methods and persulfate oxidation showed similar results in another small-group comparison (Peltzer et al, 1996). Thus, in a turnabout from earlier conclusions, comparisons in the early 1990s showed that the WCO methods did not give lower concentrations for DOC than HTC methods. These "in-house" comparisons suffer from an unintentional bias in design. Usually, the comparison is the report of an exercise by the author(s) to compare methods. Often, the exercise was spawned by the desire to demonstrate that a method recently developed or modified in a laboratory is comparable to or superior to an established method (e.g.. Sharp, 1973). Another reason for some comparisons is the desire to show that several laboratories or instruments involved with routine measurements are or are not measuring the same thing (e.g.. Sharp et al, 1993b). These exercises are important and perhaps should be viewed as necessary. They can serve to verify comparability with methods that are already accepted as accurate. However, they do not provide the objective independent evaluation of whether or not methods are accurate; and, in some cases, appear to verify inaccurate methods (e.g.. Sharp ^r a/., 1993a).
D . BROAD COMMUNITY M E T H O D S COMPARISONS
The larger community comparison done in conjunction with the Seattle meeting showed lower average DOC values by WCO than HTC (Hedges et al, 1993). It also showed a large range of values for individual samples. However, this comparison was not constrained with a uniform blank control and the participants included
42
Jonathan H. Sharp
some experienced oceanic analysts plus some with new and untried methods. A screening procedure, discussed below would probably have eliminated the most extreme values. If the few highest and lowest values are not included, the range of values for individual samples is not that large. This comparison had the advantage of "blind" analysis. The methods comparison used for the JGOFS Equatorial Pacific field experiment (Sharp et ai, 1995) also used "blind" analysis of the samples; i.e., analyses were done independently with samples that were not identified. Also, due to recognition of the seriousness of the blank problem (Benner and Strom, 1993), this comparison had strict uniform blank subtraction. The exercise showed that the six analysts involved in the program were able to get comparable results for a suite of 50 oceanic samples, ±7.5%. However, this level of agreement was not as good as that desired by most of the analysts involved. Throughout this chapter, comparability among analysts for a suite of samples is assessed with what might be considered "conmiunity precision." For a group of analyses, dividing the standard deviation by the mean for a single sample, a CV (% coefficient of variation) for that sample can be calculated. Averaging the CVs for the suite of samples tells how well that group of analysts agreed on the measurement for the suite of samples and presumably for any similar group of samples. The final exercise in a DOC intercalibration effort (Sharp et al, 2002a) shows a composite analytical capabiHty of ±10% for a suite of 10 samples when the participation was extended to a large group of 53 analysts using high-temperature combustion methods. In that exercise, participation was invited from the broad international community and not limited to a few active oceanic analysts as had been the case in most of the small group comparisons. In the exercise, a prescreening ehminated analytical runs that did not produce accurate values for standards included in the sample set (87% of potential participants were included). Also, the precision quoted was only for the high temperature combustion analysis (not including six sets analyzed by wet chemical methods that gave comparable concentrations but with considerably greater scatter of CVs). Also, apparently contaminated ampoules were removed prior to data analysis (4% of total of 525). Figure 2 shows values for a single deep ocean sample from that 2002 exercise compared to the values from the 1991 Seattle intercomparison. In the figure, the WCO analyses are included along with HTC analyses and the two outliers that were removed for data analyses are put back in the 2002 data set. As was mentioned above, it is very important to recognize that the 2002 comparison had a strict use of a uniform blank, which creates the much smaller range of values than the 1991 data set that permitted each analyst to treat the instrument or methods blank individually (or not accommodate for the blank at all). The later data set indicates a large improvement that is partially due to better blank corrections; it also indicates a larger number of analysts. The later data set includes analyses by wet chemical
43
Analytical Methods for Total DOM Pools
200.0-
-** -^1991 -•-2002
150.0 -
O 100.0 -
o
50.0
0.010
20
30
40
50
60
Number
Figure 2 Comparison of data from deep ocean DOC samples. Data used are from the 1991 DOC exercise for the Seattle workshop (Hedges et at., 1993) and from the latest DOC intercalibration (Sharp et al, 2002a). In each case, a single sample was prepared in ampoules that were sent to all participants. In the 1991 data set, all analysts returned their data with their own calculations and own procedure for handling the instrument or method blank; 7 of the 34 analyses used wet chemical methods (open symbols). In the 2002 data set, raw data were reported for uniform calculations based on individual analysts standards but with a uniform blank included with the sample set. All analyses were used with no removal of outliers; (6 of the 59 analyses used wet chemical methods (open symbols). The number on the jf-axis indicates the number of analyses compared; it does not represent the same analysts or methods for the two data sets.
oxidation methods which are not recommended for modem routine DOC analyses (Sharpera/., 2002a). The difference between an in-house comparison and the more refereed type of comparison can be seen in Fig. 3. Data from a comparison of five analytical runs on four instruments for DOC analysis of JGOFS North Atlantic Bloom Experiment is included in Fitzwater and Martin (1993). These data are shown in Fig. 3a and are contrasted to data from our broad community intercalibration in Fig. 3b from analyses performed by the exact same analysts. In the first case, the analyses were done in 1989 when it was thought that the high DOC values (Sugimura and Suzuki, 1988) were correct. In the second case the analyses were done in the 1994-1995 period when those high values were no longer considered correct (Suzuki, 1993) and analysts had improved their instruments. Figure 3c shows data from a group of five "best" analyses from the broad community intercalibration. The five "best" analyses were arbitrarily selected by considering the six samples in the oceanic depth profile and finding five individual sets that gave an average CV of 4% for the six samples. Considering the community precision concept, the first set of analyses (those reported in Fitzwater and Martin, 1993) had a composite CV of 13.2%, the second group (same analysts in our broad community intercalibration)
44
Jonathan H. Sharp
D O C (^iM)
D O C (^M) 50
100
50
150
100
1000 £
Q.
2000 3000 4000
D O C (^M) 50
100
150
Figure 3 Analysis of oceanic depth profiles of DOC from multiple analysts, (a) Data from 1989 "in-house" analysis of samples from the Atlantic Ocean (data from Fitzwater and Martin, 1993). (b) Pacific Ocean data from the broad community intercalibration (Sharp et ai, 2002a) analyzed in the 1994-1995 period by the same analysts as those involved in (a), (c) Mean values plus 1 SD for the "best" five analysts from the broad community intercalibration; same samples as in (b).
had a composite CV of 10.5%, and the third group (5 "best" analyses in broad community intercalibration) had a composite CV of 4.0%. In this contrast of community precision, note also that the first group reported DOC values that were two to three times higher than the latter. As is indicated in this contrast between one small in-house methods comparison and the broader community comparison, the agreement claimed is not always as good as implied and the absolute values can be even further off from accuracy. If we really wish to compare data collected by various analysts in a large global format with temporal and spatial variability in sample collection, we need to be able to calibrate the conmiunity accuracy with methods that can be thoroughly and openly analyzed. The level of agreement of a group of analysts for analysis of a sample or group of samples has been referred to here as conmiunity precision. If this conmiunity precision is calibrated to a uniformly used reference material, an attempt is being made to measure the "accuracy" of the methods used by the community.
45
Analytical Methods for Total DOM Pools
III. DISSOLVED ORGANIC NITROGEN ANALYSIS A. HISTORICAL PERSPECTIVE AND THE ANALYTICAL PROBLEM As with the DOC analyses, early methods for dissolved organic nitrogen (DON) used wet chemical oxidation as a means to convert all organic nitrogen to the final analyte. Depending upon the method of treatment, the final analyte was either nitrate (NO^) or ammonium (NH^). For both analytical thoroughness and a large data set, the most extensive early method was that of Duursma (1961). The few other earlier papers with DON data had individual methods and there was little uniformity. The UV photooxidation method was proposed in the 1960s (Armstrong et aL, 1966) and soon became the routine one used for seawater analysis of DON. A wet chemical method based on persulfate oxidation was introduced and much used since it did not require the UV lamp (Koroleff, 1976). This method was modified for easier use (D'Elia et al, 1977) and further modified for routine use (Solorzano and Sharp, 1980a). In the latter paper, it was indicated that the persulfate method should be superior to UV oxidation because of indication that the UV method did not completely break down all organic nitrogen compounds. However, direct comparisons of methods were not presented with these persulfate methods papers. Unlike the situation with DOC analysis, the prior removal of inorganic nitrogen is not practical when one measures DON. As a result, with almost all methods used, water samples with no prior treatment undergo conversion of all dissolved nitrogen to a final analyte (Fig. 4). The resultant analyte should then represent the total
Convert TDN to NOaby UV oxidation: to N+5 oxidation state.
Convert TDN to NOaby persulfate oxidation: to N+5 oxidation state.
l\/leasure NO 3 plus NO2colorimetrically to represent TDN.
Convert TDN to NO by high temperature combustion: to N+2 oxidation state.
Measure NO with chemiluminescence detector to represent TDN.
Subtract initially measured total DIN from TDN to calculate DON by difference. Figure 4
Schematic diagram of procedural steps in commonly used DON methods.
46
Jonathan H. Sharp
dissolved nitrogen (TDN) that was originally present in the sample. DON is calculated as the difference between the TDN and the sum of the dissolved inorganic nitrogen (DIN) measured in an aliquot of water prior to the treatment for TDN analysis. The DIN subtracted usually consists of the composite nitrate plus nitrite (NO^ and NO^) and NHj measured separately. In the UV and persulfate oxidation methods, the final analyte of oxidized nitrogen ion is ultimately measured as NO2 after final reduction from NO^, thus measurement of NO^ and NO^ is needed. In the HTC methods, the combustion conditions are maintained to optimally convert all of the TDN to nitric oxide (NO) by pyrolysis (thermodecomposition) rather than by complete oxidation to NO^. A problem in evaluating different DON methods is that the procedure for conversion to the final analyte is not simply one of exhaustive oxidation to the highest oxidation state, i.e., NO^ at the 5 + state. Instead, the UV and persulfate methods convert to NO^ and NO^ with expectation of final reduction to NO^, in the 3 + oxidation state. With the HTC methods, NO is at the 2+ oxidation state and overly strong oxidation conditions will cause the loss of part of the product if it goes to a higher oxidation state.
B. SMALL GROUP METHODS COMPARISONS With the publication of Suzuki's paper (Suzuki et al, 1985), it appeared that the HTC method measured DON values 5-10 times higher in surface waters than the wet chemical methods that were being used. A direct comparison made a few years later indicated essentially identical values for DON by UV, persulfate, and HTC methods (Walsh, 1989). Subsequent comparisons also showed HTC methods giving lower values that were very similar to wet chemical methods (Malta and Yanada, 1990; Hansell, 1993; Karl et al, 1993; Koike and Tupas, 1993; WiUiams et al, 1993) but without direct comparison. There were not many direct comparisons of methods for DON analysis prior to Walsh's paper (1989) and there have not been many since. As an indirect comparison, several papers that included DON data from oceanic surface waters can be compared. At least one of these reports used each of the families of methods: HTC, UV, and persulfate. Subsurface oceanic DON values were found to be in the range of 2-8 /xM N (Hansell and Waterhouse, 1997; Kahler et al, 1997; Wheeler et al, 1997; Ogawa et al, 1999). A range of 6 /xM N does not seem too large in a 40 /xM TDN sample, but it is not good for the resultant DON values. In a recent paper, the persulfate, UV, and HTC methods were directly compared (Bronk et al, 2000). They found that the standard UV method gave lower TDN for both model compounds and field samples while a modified UV method and the PO and HTC methods gave fairly similar results for seawater samples. However, there were small differences for sample types and the authors concluded that each
Analytical Methods for Total DOM Pools
47
method had advantages for certain types of samples. It should be noted that in that comparison, a single surface oceanic sample showed DON variations of 4.4-6.5 MMN. C. CURRENT AND FUTURE BROAD COMMUNITY M E T H O D S COMPARISON
In the Seattle workshop, a broad community comparison was made for DON similar to the one done for DOC (Hedges et al, 1993). Thirteen sets of analyses were performed on four samples for TDN, and DON was computed by subtraction of a single independent determination of DIN for each sample. The samples were surface, mid-depth, and deep samples from oceanic Pacific waters and a river sample. The methods used were primarily HTC but also included sample sets analyzed by UV and persulfate methods. There was large variability in estimates of DON from the 13 analyses. Using the same procedure mentioned above for DOC analysis, it is possible to compute a "community precision" from the 13 analyses on the four samples and the CV is 74%. While the overall agreement is not good, it is important to note that there did not appear to be any systematic differences between methods and this is a comparison based on "blind" analysis. We have just completed a broad-community methods comparison for DON (Sharp etal, 2002b) in which there were 29 analyses of five samples. The samples were all marine and represented deep ocean, surface and deep continental shelf, amended shelf water, and estuarine samples. There was a fairly good distribution of method types in the comparison with 7 using UV, 13 using persulfate, and 9 using HTC methods. As with the DOC comparison, samples were sealed in glass ampoules and stored at room temperature. The two samples that had measurable concentrations of NHj and NO^ were autoclaved to retard further bacterial oxidation after sealing in the ampoules; it was successful and there appeared to be no significant change in any of the nitrogen species for the 6 months over which the comparison was performed. One set of analyses with consistently higher values than all the other analyses was removed for data analysis. The "community precision" for the TDN analysis of the five samples was 14%. There was no difference between the three families of methods. As in the case of the Seattle workshop, a single set of independently analyzed DIN values were used to compute DON. For the same five sets of samples from the 29 analyses, the "community precision" for DON was 32%; the variability of the deep ocean sample was 46%. It should be recognized here that if individually determined DIN values had been used, the variability probably would have been even larger (Sharp et al, 2002b). Figure 5 shows DON results for three of the samples separated by method. By grouping the results by method, significant differences could be seen for the deep
Jonathan H. Sharp
48 25 20 1 15-^ 1
[HTC
]
[persulfate
[uv 1
J •
•
^ •
^
A.
A.
^ ^ •
^
§ 10 Q
1 ••
^ 10
.
. 15 order
.
, 20
25
30
Figure 5 Comparison of DON determination for three samples in the broad conmiunity DON intercalibration (Sharp et ai, 2001b). Analyses are grouped in families of methods. Samples are arbitrarily ordered in increasing concentration by each method for the deep ocean sample (open squares). The other two samples are surface continental shelf (closed circles) and lower estuary (closed triangles).
ocean and coastal samples (t test with 95% confidence interval) with the indication that the HTC methods measured the lowest average value and the UV the highest. This result is surprising and is contradictory to results of previous comparisons, especially the direct comparison of Bronk et al. (2000). It should be cautioned that the scatter was great for each group of methods and that for such large scatter the total n was relatively small. A possible explanation is that some of the UV method applications could overestimate the TDN due to photoreduction leaving a significant part of the final analyte as NO^ that would cause an error when the colorimetric analysis is standardized with NOJ. In addition, there is suspicion that the HTC methods may not completely convert DIN to NO (see Sharp et al. (2002b) for discussion of both of these explanations). This comparison did include a large number of analysts and was based on "blind analysis." It is clear that further evaluation of methods is needed and such activity is underway. The intercalibration effort reported above is continuing. Efforts are being made to better determine what improvements could be made with UV and persulfate methods that could contribute to better agreement. It is apparent from the comparison presented above that one serious problem is in the analysis of the final analyte; both methods produce NO^ and NO^ that is analyzed colorimetrically. The few analysts who also returned results for DIN analysis showed variability for DIN that was as large as that for TDN. It would appear that an effort is needed to better calibrate the community ability to measure the DIN components. In the near future, a smaller group effort will take place for detailed comparison of the HTC methods, both hybrid combinations of TOC analyzers and chemiluminescence detectors and complete TDN instruments. This effort is based on the observation that the various methods used in the methods comparison showed no systematic indication of a problem but did use somewhat different "plumbing," combustion conditions, and postcombustion chemistry.
49
Analytical Methods for Total DOM Pools
IV. DISSOLVED ORGANIC PHOSPHORUS ANALYSIS A. HISTORICAL PERSPECTIVE AND THE ANALYTICAL PROBLEM Some estimates of organic phosphorus in seawater were made from the 1930s on by various wet chemical methods. Probably the first seawater routine methods to measure total dissolved phosphorus (TDP) were the UV (Armstrong etal, 1966) and the persulfate (Menzel and Corwin, 1965) methods. A routine HTC method for dried samples was suggested as an alternative (Solorzano and Sharp, 1980b). A critical step in this HTC method that could cause poor recovery if omitted is the acid hydrolysis to cleave any polyphosphates formed in drying the sample. One reason for introducing the HTC method was that the UV method was shown to give incomplete recovery of specific organic phosphorus compounds. A second reason was that the HTC method was very simple and easily performed on large numbers of samples without any special equipment. All of the DO? methods appear to be similar in basic principle (Fig. 6). A water sample is treated to convert all organic phosphorus compounds to DIP, also called orthophosphate. Unlike with the numerous nitrogen species, there is only one oxidation state in the DIP. Actually due to dissociation of the phosphoric acid, there are three ions but all are measured as the same under the acid conditions of the colorimetric method. The DOP concentration is determined after conversion by
Convert TDP to P04-3 by UV oxidation.
Convert TDP to P04-3 by persuifate oxidation.
Convert TDP to P04"^ by higii temperature combustion.
Measure TDP coiorimetrically.
Subtract previousiy measured P04"^to caiculate DOP by difference. Figure 6 Schematic diagram of procedural steps in commonly used DOP methods.
50
Jonathan H. Sharp
subtracting the DIP from the TDR Most organic phosphorus compounds contain a phosphate ester bond Unking the orthophosphate molecule to an organic molecule which is broken to free the orthophosphate. Checks with specific organophosphorus compounds indicated incomplete recovery of compounds like ATP by the UV method, suggesting that some of the ester bonds may be difficult to break without complete destruction of the organic molecules (Solorzano and Sharp, 1980b). It should be noted that all DOP methods, similar to DON methods, require pre- and postmeasurement of DIP. Thus, the error for DOP analysis is compounded and the accuracy of DOP measurements is weakened if DIP measurements are not accurate.
B. SMALL GROUP METHODS COMPARISONS
In a multiple-laboratory, nutrient performance analysis, samples were also analyzed by some laboratories for total phosphorus (Aminot et al., 1997). In this comparison, less than half of the laboratories showed consistent results for total phosphorus analysis. While this comparison was not strictly one in which different methods were demonstrated, the results do not give confidence that total phosphorus analysis is routine and uniform. There have been several small methods comparisons in recent years for DOP analysis that provide some insight about the methodology. A comparison was run between the UV method, the persulfate method, and a combination UVpersulfate method for a series of about 20 surface and deep samples from the Pacific Ocean (Ridal and Moore, 1992). Compared to the combination method, the UV method measured only 71% and the persulfate method measured only 83%. High-temperature combustion, wet chemical oxidation, and UV methods were compared for five marine samples (Ormaza-Gonzalez and Statham, 1996) with the results that the HTC method gave highest values, the persulfate method lower, and UV method lowest. With several of the samples, the UV method gave essentially zero DOP when the DIP was subtracted from the TDP. In a thorough comparison, Monaghan and Ruttenberg (1999) compared the HTC method to the acid persulfate oxidation. With organic compounds they found that the persulfate method gave poor yields while the HTC method had complete recovery. This was especially true with a phospholipid and phosphonic acid compound. In a comparison with a series of coastal seawater samples, the HTC method gave sUghtly higher TDP concentrations than the persulfate oxidation method. They concluded that the HTC method was equal to or better than the persulfate oxidation one and through experiments rejected earlier claims that the HTC method underestimated TDP. Overall, there is need for more comparison of TDP methodology and, at present, there is reason to suspect that UV methods may not be as effective as HTC and persulfate oxidation ones.
Analytical Methods for Total DOM Pools
51
V. MULTIELEMENTAL METHODS The original UV methodology was offered with the intent of having DOC, DON, and DOP methods that used an identical conversion process (Armstrong and Tibbitts, 1968). However, most of the DOM analyses performed in the past several decades have had separate samples analyzed for only one parameter, even if the same conversion process was used (e.g., UV exposure). Several recent papers have used single samples with dual detectors for DOG and DON (Alvarez-Salgado and Miller, 1998; Ogawa et al, 1999). In both of these cases, the sample is oxidized by HTC and the resultant gas passes through both a nondispersive infrared analyzer and a chemiluminescence detector. These hold great promise for more convenient multiparameter analysis. A recent wet chemical method (persulfate oxidation) has been published with simultaneous measurement of DOC, DON, and DOP (Raimbault etal, 1999). This method was compared to individual analyses for DOC (by HTC), DON, and DOP (both by individual WCO methods) and the comparison is good. However, careful examination of the comparison indicated that the multielement analysis may give results for an individual parameter that is not quite as good as that when the analyses are performed separately. Perhaps more extensive testing is warranted. We must be cautious to not sacrifice accuracy or precision for multiparameter analyses.
VI. THE LIMITS OF ELEMENTAL ANALYSES As indicated in the Introduction, measurement of dissolved organic matter by specific elemental analysis has its limits. The major benefit of such analysis is quantitative information about the size of the total DOM pool. However, other information is often discerned about the dynamics of organic matter in seawater from analyses of specific organic compounds. There has been and continues to be considerable interest in DOC analysis because of its role in the global carbon cycle. Less effort has been expended on more accurate and more frequent measurement of DON and DOP for understanding their global elemental cycles. Perhaps this situation is changing. Due to the paucity of dissolved inorganic forms of these elements in surface ocean waters, it is critical to accurately measure DON and DOP for better understanding of nutrient limitation and cycling in surface oceanic, and probably also coastal, waters. The DOC methodology appears to be fairly well accepted with an apparent high level of accuracy today. DON methodology is currently receiving some attention and should be better evaluated in the next few years. For accurate DOP analysis and to better understand phosphorus dynamics in the surface ocean, the international community should place more attention on DOP methodology.
52
Jonathan H. Sharp
Large analytical performance studies can be revealing for how much they show about lack of good comparability among laboratories. The report by Aminot et al. (1997) is one of several recent studies that indicates poor agreement among laboratories for nutrient analysis. Indeed, part of the problem in our first DON intercalibration (Sharp et al, 2002b) is probably due to poor comparability for nitrate analysis. With any of these parameters, it is necessary to establish and continue the use of reference materials to keep the international community analytical capability at a high level of accuracy.
VII. THE NEED FOR CONTINUAL USE OF REFERENCE MATERIALS DOC reference materials were produced and distributed in 1997 as part of the large community intercalibration exercise. The two references were a zero carbon blank and a deep ocean water sample. The values for the references were determined by averaging results from three analysts who analyzed a combined 24 ampoules of each reference. These expected values for the references plus standard deviations were sent to all analysts along with notes on suggested use of the references. The intent was for analysts to standardize and check their own blanks and then run the two references prior to doing analyses. If expected values for references were not found, subsequent analyses should not be performed and the instrument should be serviced. By recording the value of the references for each day when analyses were run, it is possible to evaluate the performance of that analyst for that period of time. References were sent to all analysts who requested them; some indicated that they had not used them, others that they had used them but not recorded results. A number of analysts, both those who reported results and those who did not, indicated that the availability of the references greatly improved their analytical capability. Data on performance in reference use were received from 14 analysts; results are given in Table I with range, mean, and standard deviation. As can be seen, analysts show different levels of precision by the standard deviation of the repeated use of the references; some with precisions about the same as in the calibration of the references and some with less precision. All analysts show values for the blank that are not significantly different from the expected zero value. Most analysts show a mean value for the deep ocean reference that is not significantly different from the expected value. A few analysts show slightly higher values, but none more than 1 or 2 /xM beyond the expected value plus one standard deviation. If it is assumed that the calibration of the references is accurate, one could conclude that by using the reference materials, the respondent analysts have been able to perform consistently accurate DOC analyses. An analyst with a higher standard deviation for the reference use could not claim the same precision of his analyses as one
53
Analytical Methods for Total DOM Pools Table I Performance with DOC Reference Materials from 14 Analysts Blank
Deep Ocean fZ
Expected 1 2 3 4 5 6 7 8 9 10 11 12 13 14
24 31 31 11 31 16 6 27* 10 55 55 15* 25 9 4
Range
Mean
SD
40.8 to 52.6 44 to 57 42 to 53 40 to 69 39.7 to 47.1 46.2 to 48.3 40.0 to 60.0 34.8 to 50.8 39.1 to 61.3 42.9 to 48.2 38.3 to 75.0 39.7 to 53.4 43.1 to 48.2 47.4 to 49.1
44.0 46.9 49.1 46.9 45.8 42.8 47.2 50.4 44.0 49.2 45.6 55.5 45.6 45.8 48.4
1.5 2.8 3.7 3.9 5.9 2.3 0.7 4.6 4.3 5.2 0.8 11.6 2.9 1.5 0.9
Range -2.8 to 2.4 -ltol7 - 6 to 3 -6.7 to 10.0 -10.2 to 3.9 -2.0 to 1.4 Subtracted -1.5 to 4.5 -8.5 to 9.7 -1.2 to 2.3 Subtracted - 3 . 9 to 3.0 Not reported -0.1 to 0.4
Mean
SD
0.0 -0.2 4.5 -1.3 1.8 -3.2 -0.3
1.5 1.4 4.1 3.1 4.3 3.8 1.3
0.5 -0.5 0.4
2.0 2.8 0.6
0.0
1.7
0.2
0.2
A^o^e. Ranges, means, and standard deviations are given as /xM C. The expected value is that determined by the three laboratories used to calibrate the reference materials (8 random ampoules analyzed by each). Values for the Deep Ocean and Blank references are those calculated by the analyst using the standard curve and home laboratory blank for an individual daily DOC run. The number of times the references were run in the reporting period is given as n. Two laboratories (n indicated with *) had very high Blank values due to method of operation (both used autosamplers); net values for the Deep Ocean minus Blank are listed for those two; Deep Ocean values for others are essentially net since Blank values for them are indistinguishable from zero. Data from Sharp et al, 2002a.
with a smaller one. In my laboratory, we analyzed DOC in a series of very similar samples with some duplicate ampoules of all samples in a period of 6 months. Results for our use on 11 different days was —0.1 ± 1.5 /xM for the blank and 46.1 ± 2.3 /xM for the deep ocean sample. This indicates that we cannot determine DOC in our samples for this period better than about 2.3 /xM. In contrast, analyst 10 from Table I has demonstrated a precision for the period of his analyses of closer to 1 /xM. Both of our analyses could be considered to be accurate (i.e., both have average values similar to the "known" values for the reference materials), again assuming the absolute nature of the reference materials, but his are more precise (i.e., ±0.8 /xM vs ±2.3 /xM). Many analysts can show replicate injections of a sample on their HTC analyzers with precisions on the order of 1 /xM. This does not mean that they can analyze DOC samples with a precision of 1 /xM; that claim could be made only if repeated
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use of a uniform reference can show a day-to-day consistency with a precision of 1 /xM. If that level of precision can be shown through use of a reference material, there is no evidence that the analysis is accurate unless the same reference material is used by other analysts. Unless the international DOC analytical conmiunity uses uniform reference materials and uses them regularly, any claims of accurate DOC analysis are not verifiable. The reference materials sent by my laboratory in 1997 are no longer available. However, Dennis Hansell of the University of Miami has produced and is making available DOC references that should be used by anyone who would like to claim accurate DOC analysis. I recommend that any DOC data produced from this time forward should document use of reference materials to be considered suitable for publication. Calibrated reference materials for DON and DOP are not in use currently, they should be made available and used regularly in the near future.
ACKNOWLEDGMENTS This research was partially supported by NSF Grants OCE 92-00970, 94-02859, 96-33296, and 00-82238. My efforts over the past decade in DOM methods standardization have benefited much from generous cooperation of an international community of close to 100 analysts and their assistance in improving our community analytical capability is much appreciated. I thank John Hedges for data from the 1991 Seattle workshop that was used in Fig. 2 and I thank Ed Peltzer and two anonymous reviewers of an earlier version of this chapter for valuable suggestions.
REFERENCES Alvarez-Salgado, X. A., and Miller, A. E. J. (1998). Simultaneous determination of dissolved organic carbon and total dissolved nitrogen in seawater by high temperature catalytic oxidation: Conditions for precise shipboard measurements. Mar. Chem. 62, 325-333. Aminot, A., Kirkwood, D., and Carlberg, S. (1997). The QUASIMEME laboratory performance studies (1993-1995): Overview of the nutrients section. Mar. Poll. Bull. 35, 2 8 ^ 1 . Armstrong, F. A. J., and Tibbitts, S. (1968). Photochemical combustion of organic matter in sea water, for nitrogen, phosphorus and carbon determination. /. Mar Biol. Assoc. UK 48, 143-152. Armstrong, F. A. J., Williams, P. M., and Strickland, J. D. H. (1966). Photo-oxidation of organic matter in seawater by ultraviolet rediation, analytical and other applications. Nature 211,481-^83. Bauer, J. E., WiUiams, P. M., and Druffel, E. R. M. (1992). 14C activity of dissolved organic carbon fractions in the north central Pacific and Sargasso Sea. Nature 357,667-670. Benner, R., and Hedges, J. I. (1993). A test of the accuracy of freshwater DOC measurements by high-temperature catalytic oxidation and UV-permoted persulfate oxidation. Mar. Chem. 41, 161-166. Benner, R., and Strom, M. (1993). A critical evaluation of the analytical blank associated with DOC measurements by high temperature catalytic oxidation. Mar Chem. 41,153-160. Bronk, D. A., Lomas, M. W., Gilbert, P M., Schukert, K. J., and Sanderson, M. P (2000). Total dissolved nitrogen analysis: Comparisons between the persulfate, UV and high temperature oxidation methods. Mar Chem. 69, 163-178.
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D'Elia, C. E, Steadier, P. A., and Corwin, N. (1977). Determination of total nitrogen in aqueous samples using persulfate digestion. Limnol. Oceanogr. 22,760-764. Druffel, E. R. M., Williams, P. M., Bauer, J. E., and Ertel, J. R. (1992). Cycling of dissolved and particulate organic matter in the open ocean. /. Geophys. Res. 97,15,639-15,659. Druffel, E. R. M., Williams, P.M., and Suzuki, Y. (1989). Concentrations and radiocarbon signatures of dissolved organic matter in the Pacific Ocean. Geophys. Res. Lett. 16,991-994. Duursma, E. K. (1961). Dissolved organic carbon, nitrogen, and phosphorus in the sea. Netherlands J. Sea Res. 1, 1-147. Duursma, E. K. (1965). The dissolved organic constituents of sea water. In "Chemical Oceanography" (J. P. Riley and G. Skirrow, Eds.), Vol. 1, pp. 433^75. Academic Press, London. Fitzwater, S. E., and Martin, J. H. (1993). Notes of the JGOFS North Atlantic Bloom ExperimentDissolved organic carbon intercomparison. Mar. Chem. 41,179-185. Fredericks, A. D., and Hood, D.W. (1965). "A Method for the Determination of Dissolved Organic Carbon in Sea Water by Gas Chromotagraphy," Office of Naval Research Report. Gershey, R. M., Mackinnon, M. D., WilHams, P. J. LeB., and Moore, R. M. (1979). Comparison of three oxidation methods used for the analysis of the dissolved organic carbon in seawater. Mar. Chem. 7, 289-306. Gordon, D. C , and Sutcliffe, W.H. (1973). A new dry combustion method for the simultaneous determination of total organic carbon and nitrogen in seawater. Mar Chem. 1, 231-244. Goulden, P. D., and Brooksbank, P. (1975). Automated determinations of dissolved organic carbon in lake water. Anal. Chem. 47,1943-1946. Hansen, D. A. (1993). Results and observations from measurement of DOC and DON in seawater using a high temperature catalytic oxidation technique. Mar Chem. 41,195-202. Hansen, D. A., and Waterhouse, T. Y. (1997). Controls on the distribution of organic carbon and nitrogen in the eastern Pacific Ocean. Deep Sea Res. 144, 843-857. Hedges, J. I., Bergamaschi, B.A., and Benner, R. (1993). Comparative analyses of DOC and DON in natural waters. Mar Chem. 41,121-134. Jackson, G. A. (1988). Implications of high dissolved organic matter concentrations for oceanic properties and processes. Oceanogr 1, 28-33. Kahler, P., Bjomsen, P. K., Lochte, K., and Antia, A. (1997). Dissolved organic matter and its utilization by bacteria during spring in the Southern Ocean. Deep Sea Res. II44, 341-353. Kaplan, L. A. (1992). Comparison of high-temperature and persulfate oxidation methods for determination of dissolved organic carbon in freshwaters. Limnol. Oceanogr. 37, 1119-1125. Karl, D. M., Tien, G., Dore, J., and Winn, C. D. (1993). Total dissolved nitrogen and phosphorus concentrations at US-JGOFS station ALOHA: Redfield reconcilation. Mar Chem. 41, 203-208. Kepkay, P. E., and Wells, M. L. (1992). Dissolved organic carbon in North Atlantic surface waters. Mar Ecol. Prog. Ser. 80, 275-283. Kirchman, D. L., Suzuki, Y, Garside, C , and Ducklow, H. W. (1991). High turnover rates of dissolved organic carbon during a spring phytoplankton bloom. Nature 352, 612-614. Koike, I., and Tupas, L. (1993). Total dissolved nitrogen in the Northern North Pacific assessed by a high temperature combustion method. Mar Chem. 41,209-214. Koroleff, F. (1976). Total and organic nitrogen. In "Methods of Seawater Analysis" (K. Grasshoff, Ed.), pp. 167-181. Verlag Chemistry, Weinheim. Krogh, A., (1934). Conditions of life in the ocean. Ecol. Monogr 4,421^29. Krogh, A., and Keys, A. B. (1934). Methods for the determination of dissolved organic carbon and nitrogen in sea water. Biol. Bull. 67,132-144. MacKinnon, M. D. (1978). A dry oxidation method for the analysis of TOC in seawater. Mar Chem. 7,17-37. MacKinnon, M. D. (1979). The measurement of the volatile organic fraction of the TOC in seawater. Mar Chem. 8, 143-162.
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Malta, Y., and Yanada, M. (1990). Vertical distribution of total dissolved nitrogen and dissolved organic nitrogen in seawater. Geochem. J. 24,245-254. Martin, J. H., and Fitzwater, S. E. (1992). Dissolved organic carbon in the Atlantic, Southern, and Pacific oceans. Nature 356, 699-700. McKenna, J. H., and Doering, P. H. (1995). Measurement of dissolved organic carbon by wet chemical oxidation with persulfate: Influence of chloride concentration and reagent volume. Mar. Chem. 48, 109-114. Menzel, D. W., (1974). Primary productivity, dissolved and particulate organic matter, and sites of oxidation of organic matter. In "The Sea" (E. D. Goldberg, Ed.), Vol. 5, pp. 659-678. Wiley-Interscience, New York. Menzel, D. W., and Corwin, N. (1965). The measurement of total phosphorus in seawater based on the liberation of organically bound fractions by persulfate oxidation. Limnol Oceanogr. 10, 280-282. Menzel, D. W., and Ryther, J. H. (1970). Distribution and cycling of organic matter in the oceans. In "Organic Matter in Natural Waters" (D. W. Hood, Ed.), pp. 31-54. University of Alaska. Menzel, D. W., and Vaccaro, R. F. (1964). The measurement of dissolved organic and particulate carbon in seawater. Limnol. Oceanogr. 9, 138-142. Miller, A. E. J., Mantoura, R. F. C , and Preston, M. R. (1993a). Shipboard investigation of DOC in the NE Atlantic using platinum-based catalysts in a Shimadzu TOC-500 HTCO analyser. Mar. Chem. 41,215-221. Miller, A. E. J., Mantoura, R. F. C , Suzuki, Y, and Preston, M. R. (1993b). Preliminary study of DOC in the Tamar Estuary, UK, using UV-persulphate and HTCO methods. Mar Chem. 41, 223-228. Monaghan, E. J., and Ruttenberg, K. C. (1999). Dissolved organic phosphorus in the coastal ocean: Reassessment of available methods and seasonal phosphorus profiles from the Eel River shelf. Limnol. Oceanogr 44, 1702-1714. Natterer, K. (1892). Chemische untersuchengen im Oesthchen Mittelmeer. Denkschr Akad. Wiss. Wien. 59,53-116. Ogawa, H., Fukuda, R., and Koike, I. (1999). Vertical distributions of dissolved organic carbon and nitrogen in the Southern Ocean. Deep Sea Res. 146, 1809-1826. Ogawa, H., and Ogura, N. (1992). Comparison of two methods for measuring dissolved organic carbon in sea water. Nature 356, 696-698. Ormaza-Gonzalez, F. I., and. Statham, P. J. (1996). A comparison of methods for the determination of dissolved and particulate phosphorus in natural waters. Water Res. 30, 2739-2747. Peltzer, E. T, and Brewer, P. G. (1993). Some practical aspects of measuring DOC—Sampling artifacts and analytical problems with marine samples. Mar Chem. 41, 243-252. Peltzer, E. T, Fry, B., Doering, PH., McKenna, J.H., Norman, B., and Zweifel, U.L. (1996). A comparison of methods for the measurement of dissolved organic carbon in natural waters. Mar Chem. 54, 85-96. Peyton, G. R. (1993). The free-radical chemistry of persulfate-based total organic carbon analyzers. Mar Chem. 41,91-103. Putter, A. F. R. (1909). "Die Emahrung der Wassertiere und der Stoff haushalt der Gewasser," Fischer, Jena. Raimbauh, P., Pouvesle, W., Diaz, F , Garcia, N., and Sempere, R, (1999). Wet-oxidation and automated cororimetry for simultaneous determination of organic carbon, nitrogen, and phosphorus dissolved in sea water. Mar Chem. 66, 161-169. Ridal, J. J. and. Moore, R. M. (1992). Dissolved organic phosphorus concentrations in the northeast subarctic Pacific Ocean. Limnol. Oceanogr 37,1067-1075. Sharp, J. H. (1973). Total organic carbon in seawater—Comparison of measurements using persulphate oxidation and high temperature combustion. Mar Chem. 1, 211-229.
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Sharp, J. H. (1977). Excretion of organic matter by marine phytoplankton: Do healthy cells do it? Limnol. Ocemogr. 22, 381-399. Sharp, J. H. (1997). Marine dissolved organic carbon: Are the older values correct? Mar. Chem. 56, 265-277. Sharp, J. H., Benner, R., Bennett, L., Carlson, C. A., Dow, R., and Fitzwater, S. E. (1993b). A reevaluation of high temperature combustion and chemical oxidation measurement of dissolved organic carbon in seawater. Limnol. Oceanogr. 38,1774-1782. Sharp, J. H., Benner, R., Bennett, L., Carlson, C.A., Fitzwater, S.E., Peltzer, E.T., and Tupas, L.M. (1995). Analyses of dissolved organic carbon in seawater: The JGOFS EqPac methods comparison. Mar. Chem. 48,91-108. Sharp, J. H., Suzuki, Y., and Munday, W. L. (1993 a). A comparison of dissolved organic carbon in North Atlantic Ocean nearshore waters by high temperature combustion and wet chemical oxidation. Mar Chem. 41, 253-259. Sharp, J. H., Carlson, C. A., Peltzer, E. T., Castle-Ward, D. M., Savidge, K. B., and Rinker, K. R. (2002a). Final dissolved organic carbon broad community interecalibration and preliminary use of DOC reference materials. Mar Chem., in press. Sharp, J. H., et al. (2002b). A prehminary methods comparison for measurement of dissolved organic nitrogen in seawater. Mar Chem., in press. Skopintsev, B. A., Timofeeva, S. N., and Vershinina, O. A. (1966). Organic carbon in the equatorial and southern Atlantic and Mediterranean. Okeanologiya. 6, 201-210. Solorzano, L., and Sharp, J. H. (1980a). Determination of total dissolved nitrogen in natural waters. Limnol. Oceanogr. 25,751-754. Solorzano, L., and Sharp, J. H. (1980b). Determination of total dissolved phosphorus and particulate phosphorus in natural waters. Limnol. Oceanogr. 25,754-758. Sugimura, Y., and Suzuki, Y. (1988). A high temperature catalytic oxidation method for the determination of no-volatile dissolved organic carbon in seawater by direct injection of a liquid sample. Mar C/zem. 41,105-131. Suzuki, Y (1993). On the measurement of DOC and DON in seawater. Mar Chem. 42, 287-288. Suzuki, Y, Sugimura, Y, and Itoh, T. (1985). A catalytic oxidation method for the determination of total nitrogen dissolved in seawater. Mar Chem. 16, 83-97. Suzuki, Y, Tanoue, E., and Ito, H. (1992). A high temperature catalytic oxidation method for determination of dissolved organic carbon in seawater: Analysis and improvement. Deep Sea Res. 39, 185-198. Toggweiler, J. R. (1989). Is the downward dissolved organic matter (DOM) flux important in carbon transport. In "Productivity of the Ocean: Present and Past" (W. H. Berger, V. S. Smetacek, and G. Wefer, Eds.), pp. 65-83. Wiley, Chichester. Toggwieler, J. R. (1992). Bombs and ocean carbon cycles. Nature 347,122-123. Van Hall, C. E., Safranko, J., and Stenger, V. A. (1963). Rapid combustion method for the determination of organic substances in aqueous solutions. Anal. Chem. 35, 315-319 Walsh, T. W. (1989). Total dissolved nitrogen in seawater: A new high-temperature combustion method and a comparison to photo-oxidation. MAT: Chem. 26,295-311. Wangersky, P. J. (2000). Intercomparisons and intercalibrations. "The Handbook of Environmental Chemistry" (P. Wangersky, Ed.), Vol. 5D, pp. 167-191. Springer-Verlag, New York. Wheeler, P. A., Watkins, J. M., and Hansing, R. L. (1997). Nutrients, organic carbon and organic nitrogen in upper water column of the Arctic Ocean: Implications for the sources of dissolved organic carbon. Deep Sea Res. II44,1571-1592. Williams, P. J. LeB. (1975). Biological and chemical aspects of dissolved organic material in sea water. In "Chemical Oceanography" (J. P. Riley and G. Skirrow, Eds.), Vol. 2, pp. 301-363. Academic Press, London.
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Williams, P. M. (1969). Determination of dissolved organic carbon in seawater: A comparison of two methods. Limnol. Oceanogr. 14, 297-298. Williams, P. M. (1992). Measurement of dissolved organic carbon and nitrogen in natural waters. Oceanography 5, 107-116. Williams, P M., Bauer, J. E., Robertson, K. J., Wolgast, D. M., and Occelli, M. L. (1993). Report on DOC and DON measurements made at Scripps Institution of Oceanography, 1988-1991. Mar. C/z^m. 41, 271-281. WiUiams, P. M., and Druffel, E. R. M. (1988). Dissolved organic matter in the ocean: Comments on a controversy. Oceanography 1, 14-17. WiUiams, P. M., and Gordon, L. I. (1970). Carbon-13: carbon-12 ratios in dissolved and particulate organic matter in the sea. Deep Sea Res. 17,19-27. Wilson, R. F. (1961). Measurement of organic carbon in seawater. Limnol Oceanogr 6,259-261.
Chapter 3
Chemical Composition and Reactivity Ronald Benner Department of Biological Sciences and Marine Science Program, University of South Carolina, Columbia, South Carolina
I. Introduction A. Approaches for the Chemical Characterization of DOM B. Size Distribution of DOM II. Distribution and Chemical Characteristics of Bulk Marine DOM A. Bulk Concentration and Composition of DOM B. Molecular Composition of DOM C. Chemical Composition of Isolated Fractions of DOM
III. Major Topics of Ongoing and Future Research about the Cycling of DOM A. Mechanisms of Formation and Removal of Biorefractory DOM B. Bacterial Contributions to DOM C. Fate of Terrigenous DOM in the Ocean References
I. INTRODUCTION The world ocean is one of the largest reservoirs of reactive organic carbon on Earth. Most (>97%) of the organic carbon in seawater resides in the operationally defined dissolved phase. The separation of the particulate and dissolved phases is most commonly accompUshed by the passage of water samples through filters with pore sizes in the 0.2- to 1.0-/im size range. During the past decade, it has become increasingly common to avoid the filtration of open ocean water samples Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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for separation of the particulate and dissolved phases. Filtration is often omitted because particulate organic carbon (POC) is such a small fraction of the total organic carbon, and the extra handling and processing of water samples during filtration aboard ship can lead to contamination. We often refer to the concentrations of organic carbon, nitrogen, and phosphorus in unfiltered water samples as total organic concentrations (e.g., TOC, TON, TOP, respectively). Relatively small volumes (milliliters) of seawater are analyzed for these measurements, and larger particles are not represented in these samples. Thus, the term "total" is somewhat of a misnomer for these analyses. In this chapter the data gathered on the concentrations and chemical composition of marine DOM includes some samples that were not filtered prior to analysis. These samples all come from the open ocean, and the contribution of POM to the reported data is considered to be minimal. In some cases, data for both filtered and unfiltered samples were available and the differences between these samples was often within the error of the measurement. In the first chapter of this book. Hedges (Chapter 1) reviews the importance of DOM in the biogeochemical cycling of bioactive elements in the ocean. During the 1970s and 1980s there was growing recognition of the significance of microbial food webs in the ocean (Pomeroy, 1974; Azam etai, 1983). Heterotrophic bacteria are the major consumers of DOM in seawater (Azam and Hodson, 1977; Williams, 1981), and the quantitative significance of DOM in supporting microbial food webs and carbon and energy flow is now widely apparent to biological oceanographers. Interest in DOM has blossomed, and the search for bioreactive components of DOM has intensified. Many clues about the bioreactivity of DOM are held within its chemical composition, and this chapter will investigate the current information on this topic. Widespread interest in the global carbon cycle during the past two decades has also brought increasing attention to marine DOM. Determining the sources of DOM in seawater and the factors regulating its production and consumption are critical for understanding the ocean carbon cycle. Most DOM resides in the deep ocean and is resistant to biodegradation. Is it by coincidence that the concentrations of DOC in this vast region of the biosphere fall in the narrow range of 35-45 /xM? What is the origin of this organic matter? What regulates the cycHng of DOM in the deep ocean? Varying approaches to these puzzling aspects of marine DOM are needed to address these fundamental questions. We have witnessed extraordinary advances in understanding of the functioning of organisms through fundamental studies of the chemical composition and structure of biomolecules. It appears very likely that when we reach a fundamental understanding of the chemical composition and structure of detrital reservoirs of organic matter, we will have a grasp on answers to central questions concerning the marine and global cycles of major bioactive elements.
Chemical Composition and Reactivity A. APPROACHES FOR THE CHEMICAL CHARACTERIZATION OF
DOM
Two basic approaches have been used for the chemical characterization of DOM: (1) direct analyses of DOM in seawater, (2) analyses of concentrated DOM isolated from seawater. The first of these approaches is ultimately the most desirable, because it avoids potential contamination and artifacts associated with many isolation procedures. However, direct analyses of low concentrations (nanomolar) of organic compounds in aqueous solutions with high salt content are extremely challenging. There have been significant advances in the direct analysis of organic molecules in seawater during the past decade (summarized below), but we are far from characterizing a major fraction of DOM based on this approach. Given the limitations of the direct analysis approach, a variety of methods have been developed for the concentration and isolation of DOM from seawater. The isolation approach opens the door to a variety of powerful analytical methods, such as nuclear magnetic resonance spectroscopy, that require more concentrated samples and the removal of sea salts. A wide variety of concentration and isolation techniques have been applied to natural waters, and the reader is directed to the following reviews for a better appreciation of the breadth of these techniques (Thurman, 1985; Aiken, 1985; Leenheer, 1985). Two techniques, solid-phase extraction and ultrafiltration, have been used most frequently and are briefly described here. Solid-phase extraction techniques rely primarily on chemical properties to partition DOM between the aqueous and sorbent phases. These techniques are therefore chemically selective for specific components of DOM. Ultrafiltration techniques rely primarily on physical properties to separate size fractions of DOM. It appears likely, based on the fundamental differences in the mechanisms of isolation, that compositional differences between DOM isolated using solid-phase extraction and ultrafiltration will exist. 1. Solid-Phase Extraction for DOM Isolation There are numerous solid-phase extraction techniques described in the literature. Most investigators use the term "humic substances" to describe the DOM isolated using these techniques. Humic materials and humic substances are centuriesold terms used to describe colored organic matter extracted from soils using alkali. Colored organic matter isolated from natural waters is also commonly described as humic substances. The techniques used for the isolation of operationally defined fractions of organic matter, such as humic substances, should have a standard protocol so that comparable fractions are isolated. In this chapter, the term humic substances is used to describe DOM sorbed onto a single nonionic macroporous sorbent, either XAD-2 or XAD-8, and eluted with alkali.
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Nonionic macroporous sorbents, specifically the Amberlite XAD resin series, are the most widely used materials for solid-phase extraction of DOM from natural waters (Aiken, 1985; Thurman, 1985). These resins have high adsorption capacities, so relatively large volumes of water can be processed. Water samples are acidified (pH ~2) before solid-phase extraction to protonate organic acids. Acidification increases the efficiency of DOM extraction, because hydrophobic interactions are the primary mechanism for adsorption onto these resins. Alkali (0.1 N NaOH) is commonly used for elution of sorbed DOM. The DOM isolated using this technique undergoes very large changes in pH, and it is unclear to what extent this treatment modifies the structure and composition of the isolated material. Two other potential problems with solid-phase extraction techniques are: (1) contamination of samples due to the release of material from the sorbent, (2) quantitative elution of sorbed organic matter from the sorbent. The fraction of DOC retained during solid-phase extraction is most often reported, rather than the fraction recovered after elution and desalting. Given the chemically selective mechanisms of DOM sorption in solid-phase extraction, it is questionable whether the material retained on the sorbent after elution has the same chemical composition as the material eluted. About 5-25% of seawater DOC is retained on XAD-2 or XAD-8 resins and can be considered humic substances by the definition used in this chapter. Sequential solid-phase extractions through two or more sorbents has been used to increase the total fraction of DOM isolated from seawater (Druffel et ai, 1992; Lara and Thomas, 1994). Combinations of XAD-8 -f XAD-4 and of XAD-2 + XAD-4 retained 30-39% and 23-27%, respectively, of the DOC from surface and deep Pacific waters (Druffel et ai, 1992). The XAD-4 resin retains some of the more hydrophilic components of DOM that are not sorbed by the XAD-8 and XAD-2 resins. Silica-based stationary phases, such as the Cig bonded phase commonly used in liquid chromatography, are now being utilized in a wide variety of soUd-phase extraction applications. As with XAD resins, hydrophobic interactions are the primary mechanism in the sorption of DOM onto silica-based Cig phases. The fraction of seawater DOM that sorbs to Cig material is pH dependent, and maximal sorption occurs at pH values <4 (Amador et ai, 1990; Louchouam et al, 2000). About 35% of coastal seawater DOM is sorbed onto Cig stationary phases (Mills and Quinn 1981; Amador et ai, 1990). Sorbed DOM can be eluted with a variety of organic solvents, with methanol being most commonly recommended. These sorbents have great potential for concentrating and isolating components of DOM from seawater, and they will likely find wider application in the coming years. 2. Tangential-Flow (or Cross-Flow) Ultrafiltration for DOM Isolation Most of the early applications of ultrafiltration in marine science investigated the size distribution of DOM (Sharp, 1973; Ogura, 1974). Stirred cell ultrafiltration
Chemical Composition and Reactivity methods were commonly employed, and numerous difficulties with contamination and adsorption (i.e., polarization) onto membranes were encountered. Improvements in membrane technology, rigorous cleaning, and determination of DOC mass balances led to more reliable estimates of the size distribution of DOM in the ocean (Carlson et al, 1985). Ultrafiltration continues to be a valuable tool for investigating the size distribution of DOM (see Wells, Chapter 7). However, advances in ultrafiltration technology also have led to its application in the concentration and isolation of material from natural water samples. The advent of tangential-flow or cross-flow ultrafiltration techniques opened the door for new applications of ultrafiltration in aquatic sciences. The high flow rates and large membrane surface areas in tangential-flow systems greatly decrease processing times, making it possible to rapidly concentrate and isolate sufficient material for detailed characterization. High flow rates across the surface of ultrafiltration membranes reduce polarization resulting in negligible sorption to membrane surfaces for many applications. Following concentration in tangential-flow systems, marine samples can be rapidly desalted by diafiltration with high-purity water. Tangential-flow ultrafiltration has been used for the concentration and isolation of bacteria, viral particles, and particulate matter (Coffin et al, 1990; Proctor andFuhrman, 1990;Benner, 1991;Benner^^a/., 1997), as well as colloids and dissolved matter (Whitehouse et al, 1990; Benner, 1991; Benner et al, 1992; Moran and Buesseler, 1992). Each application of ultrafiltration has its own requirements. The hardware, membranes, and operating conditions of ultrafiltration systems should be specifically chosen for each application. Variability in the performance of membranes and systems from different manufactures has been observed, as well as variability among results from investigators using similar systems (Kilduff and Weber, 1992; Buesseler ^r a/., 1996; Guo and Santschi, 1996; Dale? a/., 1998). The establishment of defined protocols and careful attention to operating conditions are necessary for the successful application of ultrafiltration techniques.
B. SIZE DISTRIBUTION OF DOM It has been recognized for some time that organic matter in seawater exists in a continuum of sizes (Sharp, 1973). Distinctions among major size classes of organic matter in aquatic systems are primarily based on physical separation by passage through filters and membranes with varying pore sizes. This size-based separation of matter is highly practical given the simplicity of filtration methods and the ability to rapidly process samples in the field. Colloids (0.001- to l-/xm size range) fafl predominantly in the operationally defined DOM size class. Based on this definition, colloidal organic carbon in seawater ranges from 16 to 28 /xM C in surface waters and from 8 to 12 /xM C in deep water (Carlson et al, 1985; Benner et al, 1992, 1997; Ogawa and Ogura, 1992; Guo et al, 1995). However, it has
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been suggested that such a size-based definition is inadequate for understanding the functional role of colloids in the cycling of trace chemicals in aquatic systems (Gustafsson and Gshwend, 1997). Given the common association of the term colloid with its functional implications, colloid is not used further in this paper (see Wells, Chapter 7, for more information on colloids). In this chapter, two operationally defined size classes of DOM are described based on passage through an ultrafiltration membrane with a '^l-nm pore size (1000 Dalton cutoff). High-molecular-weight (HMW) DOM is retained using a 1000-Dalton cutoff membrane, and low-molecular-weight (LMW) DOM is the fraction that passes this membrane. A substantial amount of information about the chemical composition of DOM has been collected during the past decade since the introduction of tangential-flow ultrafiltration as a method for the concentration and isolation of HMW DOM (Benner, 1991; Benner et al, 1992). The size-based distinction between HMW and LMW DOM is quite useful for understanding the sources and transformations of DOM, and these terms are used throughout this chapter. The distribution of carbon along the size continuum of organic matter in seawater is highly skewed to smaller size classes. In the surface ocean, most DOC (60 75%) passes an ultrafiltration membrane with pore sizes of ~ 1 nm (1000 Dalton molecular weight cutoff). In the deep ocean, 75-80% of DOC passes a membrane with a 1000-Dalton cutoff, indicating that most of the organic carbon in seawater exists as LMW DOM. Most LMW DOM in deep water appears to be in combined form, because strong hydrolytic conditions are required to liberate free amino acids and neutral sugars for molecular characterization (Druffel et al, 1992; Borch and Kirchman, 1997; Skoog and Benner, 1997). Monomeric forms of major classes of biomolecules (e.g., sugars, amino acids and fatty acids) typically have molecular weights > 100 Dalton, indicating that combined forms of DOM that pass an ultrafiltration membrane with a 1000-Dalton molecular weight cutoff consist of <10 monomeric subunits. This reference to the size of recognizable biomolecules is intended to provide a relative index of the small size of the bulk of the DOM in the ocean. Only a small fraction of the DOM in seawater has been characterized as recognizable biomolecules.
11. DISTRIBUTION AND CHEMICAL CHARACTERISTICS OF BULK MARINE DOM A. BULK CONCENTRATION AND COMPOSITION OF DOM A summary of the chemical nature of DOM in the surface and deep-ocean is presented in Table I. Data on the concentration and composition of DOM from various ocean basins are summarized, and a range of values is presented for each
65
Chemical Composition and Reactivity Table I Direct Chemical Analyses of DOM in the Surface « 1 0 0 m) and Deep (>1000 m) Ocean Chemical characteristics
Surface ocean
Deep ocean
Reference
Bulk composition DOC (/xM) DON (ixM) DOP iixM) DOC:DON DOC:DOP Carbohydrates (/xM C glucose equivalent)
60-90 3.5-7.5 0.1-0.4 9-18 180-570 10-25
35^5 1.5-3.0 0.02-0.15 9-18 300-600 5-10
1-6,9-10 6-11 6-12 1-12 1-12 13-14
200-800 200-500 42-94 0.2-0.7
20-170 80-160
15-16 17-18 19-20
Molecular composition Total hydrolyzable neutral sugars (nM) Total hydrolyzable amino acids (nM) Total hydrolyzable amino sugars (nM) Lipids (solvent extractable; nM) Total hydrolyzable neutral sugars (% DOC) Total hydrolyzable amino acids (% DOC) Total hydrolyzable amino sugars (% DOC) Solvent extractable lipids (% DOC) Total (% DOC) Total hydrolyzable amino acids (% DON) Total hydrolyzable amino sugars (% DON) Total (% DON)
2-6 1-3
0.4-0.6 0.3-0.9 3.7-10.5 6-12 0.8-1.7 6.8-13.7
4-9 nd
0.5-2.0 0.8-1.8 0.04-0.07
21
nd
1.3-3.9
4-9
0.2-0.4 4.2-9.4
Note. Some measurements are for unfiltered water samples and thus include small (<3%) contributions from suspended particles. Data from high-latitude regions are excluded from the table, nd, not determined. References. 1, Williams and Druffel (1987); 2, Carlson et at. (1994); 3, Sharp et al. (1995); 4, Peltzer and Hayward (1996); 5, Hansell and Carlson (1998); 6, Holm-Hansen et al (1966); 7, Jackson and Williams (1985); 8, Smith et al (1986); 9, Walsh (1989); 10, Abell et al (2000); 11, Loh and Bauer (2000); 12, Ridal and Moore 1992; 13, Pakulski and Benner (1994); 14, Bhosle et al. (1998); 15, Borch and Kirchman (1997); 16, Skoog and Benner (1997); 17, Lee and Bada (1977); 18, Druffel et al (1992); 19, Kaiser and Benner (2000); 20, Benner and Kaiser unpublished; 21, Kennicutt et al (1981).
component. Chemical characteristics of DOM in high-latitude regions are omitted because these systems generally have well mixed water columns, and the characteristic distinctions between surface and deep-ocean DOM are often blurred. Comparisons between surface (<100 m) and deep ocean (>1000 m) waters can provide valuable insights about the compositional characteristics that influence the reactivity of DOM. Most of the production of organic matter occurs in the surface ocean, so surface-ocean DOM includes a greater fraction of freshly produced and reactive DOM than the deep ocean. Deep-ocean DOM is considered very resistant to biological degradation, based on biodegradation studies (Barber, 1968) and its apparent average ^"^C age (Williams and Druffel, 1987; see Bauer, Chapter 8).
66
Ronald Benner
1. C, N, and P Stoichiometry in DOM Concentrations of DOC in surface water of tropical and temperate regions typically range from 60 to 90 /xM (Table I). In these same regions deep water DOC concentrations range from 35 to 45 /xM, with higher values in the deep Atlantic relative to the deep Pacific. These small differences in deep water DOC concentrations could be indicative of DOC remineralization during thermohaline circulation (Hansen and Carlson, 1998). There are fewer measurements of DON and DOP relative to DOC, because these measurements are considerably more time consuming and less precise. Surface water DON values range from 3.5 to 7.5 /xM and surface DOP values range from 0.1 to 0.4 /xM. Based on median values for DOC, DON, and DOP in surface waters (Table I), the following stoichiometric relationships for DOM are calculated: C:N = 13.6, C:P = 300, and C:N:P = 300:22:1 (Fig. 1). These elemental relationships indicate that DOM is depleted in N and P relative to average marine plankton (Redfield et al., 1963). Deep water measurements of DON and DOP include greater error due to the high concentrations of inorganic nutrients in these waters. Deep-water DON values range from 1.5 to 3.0 /xM and DOP values range from 0.02 to 0.15 /xM (Table I). Based on median values for DOC, DON, and DOP in deep waters, the following stoichiometric relationships for DOM are calculated: C:N = 17.8, C:P = 444, and C:N:P = 444:25:1. These elemental relationships indicate that deep-water DOM is even more depleted in N and P than surface water DOM (Fig. 1). It is likely that the depletion of N and P in DOM results, at least in part, due to selective remineralization of N- and P-containing compounds. These "typical" values for the stoichiometric relationships among C, N, and P in DOM can be compared to those for the ultrafiltered (HMW >1000 Dalton) component of DOM isolated from seawater. Analyses of C, N, and P in ultrafiltered DOM does not involve calculating the difference between the total and inorganic component, because the inorganic component (< 1000 Dalton) is removed during diafiltration. Average surface water HMW DOM has the following stoichiometric relationships: C:N = 16.7, C:P = 298, C:N:P = 298:18:1 (Benner et aU 1991 \ Kolowith et al, 2001). Average deep water HMW DOM has the following stoichiometric relationships: C:N = 17.9, C:P = 496, C:N:P = 496:28:1. The C:N:P values for bulk DOM in surface and deep water are very similar to those for the HMW DOM fraction (Fig. 1), indicating that these different size classes of DOM have similar compositions of these major bioactive elements. 2. Colorimetric Analyses of Dissolved Carbohydrates Bulk analyses of carbohydrates using a variety of spectrophotometric methods indicate that this class of compounds is abundant in seawater (Josefsson et al, 1972; Bumey and Sieburth, 1977; Pakulski and Benner 1994; B0rsheim et al, 1999).
67
Chemical Composition and Reactivity •
•
•
1
'
•
1
•
Plankton
-|
Surface DOM
H
Surface HMW DOM H
Deep DOM Deep HMW DOM
•]
C)
5
10
15
2(
C:N
.
.
.
.
.
.
.
.
.
.
.
.
.
.
1
.
.
.
.
Plankton J
Surface DOM
^
Surface HMW DOM
•4
Deep DOM A Deep HMW DOM
.,,••„, 100
.., . , ,
200
300
Jl 400
500
C:P
Figure 1 Molar ratios of C:N and C:P in marine plankton, DOM, and high-molecular-weight (HMW) DOM from the surface (< 100 m) and deep (> 1000 m) ocean.
The various spectrophotometric analyses of carbohydrates share uncertainties about potential interferences and a lack of molecular identification, but have the advantage of including diverse types of carbohydrates in a single analysis. Recent analyses of surface seawater indicate that total (combined and free) carbohydrates typically account for 10-25% of DOC (Pakulski and Benner, 1994; Bhosle et al, 1998; B0rsheim et al, 1999). In deep ocean waters total carbohydrates typically account for 5-10% of DOC. Based on these analyses, carbohydrates are the most abundant, identified component of seawater DOM. Two fractions of total carbohydrates, polysaccharides and monosaccharides, have been distinguished based on spectrophotometric analyses of carbohydrates before and after acid hydrolysis of seawater samples (Bumey and Sieburth, 1977).
68
Ronald Benner
Although this terminology has been widely used in the literature (by this author and others), it has caused some confusion. Following the procedures of Bumey and Sieburth (1977), some combined carbohydrates can react to give a positive response without acid hydrolysis of the sample. Thus, all of the carbohydrates termed "monosaccharides" in this analysis are not necessarily free individual sugars. Oligosaccharides contain 2-10 monosaccharide units joined by glycosidic linkages, whereas polysaccharides contain greater than 10 monosaccharide units (Lehninger, 1975). Using these definitions it is unclear whether the monosaccharides released during acid hydrolysis are derived from oligosaccharides, polysaccaharides, or other forms of combined carbohydrates. Some (5-25%) of the sugar units in oligosaccharides would be measured as "monosaccharide." Given these caveats of nomenclature, investigations of carbohydrates in seawater indicate that most carbohydrates in surface waters exist in combined ("polysaccharide") form. In deep water a significant fraction (25-50 mol%) of the total carbohydrates gives a response without prior acid hydrolysis. It is unlikely that these carbohydrates exist primarily as free "monosaccharide." However, these observations indicate that most carbohydrates in deep water DOM are "exposed" or on the surface of molecular complexes. As discussed earlier, most deep-ocean DOM consists of relatively small molecules with less than 10 monomeric subunits. Concentration gradients of DOM between surface and deep water provide fundamental insights about its sources and reactivity. Concentrations of DOC and DON are often '^2-fold higher in surface water, whereas concentrations of DOP and total carbohydrates are often 3-fold higher in surface water relative to deep water. These concentration gradients indicate that the food web in surface waters is the major source of reactive DOM in the ocean. They also indicate that much of this DOM is rapidly recycled in the upper ocean and that DOM is a major source of regenerated nutrients. Combined carbohydrates, including polysaccharides and oligosaccharides, and DOP appear to be recycled more efficiently in the upper ocean than bulk DOC and DON.
B. MOLECULAR COMPOSITION OF DOM In general, there is a paucity of data on the molecular composition of DOM in the ocean. This limitation results in large part from a lack of suitable chromatographic methods with sufficient sensitivity for the characterization of DOM in seawater. Although methods for the direct analyses of amino acids have been available for 20 years (Lindroth and Mopper, 1979), there are few published profiles of dissolved amino acids in seawater. Data on the concentrations and distributions of biochemicals in the ocean are fundamental for understanding the biogeochemical cycling of bioactive elements, and there is a clear need to establish this as a priority in the near future.
Chemical Composition and Reactivity To the author's knowledge, full-ocean profiles exist for only two major classes of biochemicals: amino acids and carbohydrates. The typical analysis of these biochemicals involves an acid hydrolysis to produce monomeric units from combined (i.e., polymeric) components of DOM. The monomeric units are separated by chromatography, quantified, and collectively referred to as the total hydolyzable yield of the specific class of biochemicals (e.g., total hydrolyzable amino acids or THAA). In Table I, the total concentrations of classes of different biochemicals are presented as well as the percentage of DOC and DON accounted for within each class. A suite of seven neutral sugars, or aldoses (fucose, rhamnose, arabinose, galactose, glucose, mannose, xylose), have been measured in seawater using anion exchange chromatography and amperometric detection (Borch and Kirchman, 1997; Skoog and Benner, 1997). Concentrations of ribose are sometimes reported, but these data are not reliable because ribose is largely destroyed during acid hydrolysis. The most abundant hydrolyzable neutral sugars are glucose, galactose, fucose, mannose, and xylose (Borch and Kirchman, 1997; Skoog and Benner, 1997). The relative abundance of hydrolyzable glucose increases with depth. Concentrations of total hydrolyzable neutral sugars (THNS) in surface water range from 200 to 800 nM and concentrations in deep water range from 20 to 170 nM. It should be noted that the studies reporting these data used different hydrolyses (Borch and Kirchman, 1997; Skoog and Benner, 1997). Surface water THNS concentrations reported in these two studies are similar, but the limited number of deep-water concentrations are quite variable. Subsequent analyses of THNS in my laboratory using a variety of hydrolytic conditions indicate that deep-water concentrations are typically 25-50 nM (unpubhshed data). Neutral sugars account for 2-6% of the DOC in surface water and 0.3-0.9% of the DOC in deep water. Data on the concentrations and distributions of neutral sugars in high latitude marine waters are given in Rich et al, (1997), Kirchman et al. (2001), and Amon et al. (2001). The following 15 common amino acids are typically measured using reversephase liquid chromatography and derivatization with o-phthaldialdehyde: glycine, arginine, alanine, phenylalanine, serine, threonine, aspartic acid, valine, tyrosine, histidine, isoleucine, glutamic acid, lysine, methionine, leucine. In this analysis, the amine groups of glutamine and asparagine are removed during acid hydrolysis, producing glutamic acid and aspartic acid, respectively. Therefore, reported concentrations for glutamic acid equal the combined concentrations of glutamic acid and deaminated glutamine, and aspartic acid concentrations equal the combined concentrations of aspartic acid and deaminated asparagine. The most abundant hydrolyzable amino acids in DOM are glycine, alanine, aspartic acid, serine, and glutamic acid (Hubberton et al, 1995). Profiles of total hydrolyzable amino acids (THAAs) range in concentration from 200 to 500 nM in surface water and 80160 nM in deep water (Table I). Amino acids account for 1-3% of the DOC and 6-12% of the DON in surface water and 0.8-1.8% of the DOC and 4-9% of the
69
70
Ronald Benner
DON in deep water. Data on the concentrations and distributions of amino acids in high-latitude waters are given in Hubberton et al. (1994, 1995). Two amino sugars, glucosamine and galactosamine, have been measured in seawater using anion exchange chromatography and amperometric detection (Kaiser and Benner, 2000, unpublished data). Concentrations of total hydrolyzable amino sugars (THASs) range from 42 to 94 nM in surface water and 4 to 9 nM in deep water (Table I). Amino sugars account for 0.4-0.6% of the DOC and 0.8-1.7% of the DON in surface water and 0.04-0.07% of the DOC and 0.2-0.4% of the DON in deep water. A variety of solvent extractable lipids have been identified and measured by gas chromatography and mass spectrometry (Kennicutt and Jeffrey, 1981). Total concentrations of these lipids in surface waters are less than 1 nM, and they account for < 1 % of the DOC (Table I). A wide variety of other compounds, such as low-molecular-weight organic acids and dimethylsulfide, have been measured in seawater but collectively account for a small fraction of DOC and are not included in Table I. Molecular-level analyses of DOM in the surface ocean account for 4-11% of DOC and 7-14% of DON (Table I; Fig. 2). This bookkeeping exercise indicates that an even smaller fraction of deep water DOM can be characterized at the molecular level. Only 1-3% of the DOC and 4-9% of the DON in deep water has been characterized as recognizable biochemicals (Fig. 2). Most DOM remains uncharacterized at the molecular level, and at the present time we have relatively few molecular clues about the nature of DOM. Carbon- and nitrogen-normalized yields of these biochemicals are reliable relative indicators of the diagenetic state and bioreactivity of organic matter (Cowie and Hedges, 1994; Biersmith and Benner, 1998; Amon et al, 2001). In general, higher C- and N-normaHzed yields of biochemicals are indicative of relatively fresh and bioreactive organic matter, whereas lower yields are indicative of more diagenetically altered and biorefractory material. The C- and N-normalized yields of amino acids, neutral sugars, and amino sugars are higher in surface water relative to deep water (Table I). This indicates that surface water DOM is less diagenetically altered than deep water DOM, which is consistent with the observations that surface water DOM is more bioreactive and has a younger apparent average ^"^C age than deep water DOM (Barber, 1968; Williams and Druffel, 1987). The average percentages of total carbon measurable as chromatographically resolved individual amino acids, neutral sugars, and lipids in net plankton, sinking particles, deep-sea surface sediments, surface water DOM, and deep water DOM are presented in Fig. 3. The percentage of total carbon comprised by these biochemicals decreases from ^^80% in net plankton to ^^20% in surface sediments, indicating that the material becomes increasingly altered as it sinks through the water colunm and accumulates in sediments (Wakeham etai, 1997). Less than 1% of the organic carbon produced in the surface ocean is preserved in deep-sea sediments. About 80% of the organic carbon in deep-sea sediments remains uncharacterized
71
Chemical Composition and Reactivity
• H B n
Neutral sugars Amino sugars Amino acids Uncharacterized
• Amino sugars S Amino acids CI Uncharacterized
Figure 2 The fraction of surface (< 100 m) and deep (> 1000 m) marine DOC and DON identified as specific biomolecules (total hydrolyzable neutral sugars, total hydrolyzable amino sugars, and total hydrolyzable amino acids). The uncharacterized fraction is DOC and DON not accounted for in these specific biomolecules.
at the molecular level. For comparison, the percentage of total carbon comprised by these biochemicals is ^6.6% in surface water DOM and --2.0% in deep water DOM (Table 1). This comparison suggests that DOM in the deep ocean is the most diagenetically altered, as well as abundant, form of organic matter in the sea.
C. CHEMICAL COMPOSITION OF ISOLATED FRACTIONS OF
DOM
The concentration and isolation of DOM from seawater is advantageous for its chemical and isotopic characterization. As discussed in the Introduction, a variety
72
Ronald Benner
Phytoplankton
Sediment trap
U • •
Surface sediment
Surface DOM
Amino acids Lipids Neutral sugars
a
Deep DOM
20
40
60
80
100
Percent characterized organic carbon
Figure 3 Contributions of total hydrolyzable amino acids, total hydrolyzable neutral sugars, and lipids to the organic carbon content of net phytoplankton, sinking particles collected in deep water sediments traps, surface sediments from the deep sea, and DOM from the surface (<100 m) and deep (> 1000 m) ocean. Plankton, sediment trap, and surface sediment data are from Wakeham et al. (1997).
of solid-phase extraction techniques have been used to isolate the operationally defined humic fraction of DOM. Data on the chemical composition of humic substances isolated with the most commonly used sorbents, XAD-2 and XAD-8 resins, are presented in Table II. The bulk C:N ratios for dissolved humic substances isolated from surface and deep water range from 36 to 57, indicating that humic substances comprise a highly N-depleted fraction of DOM. Organic nitrogen is often charged and relatively polar and is therefore depleted in these relatively hydrophobic fractions of DOM. Nuclear magnetic resonance (NMR) spectroscopy is a very useful approach for determining the bulk chemical structure of natural organic matter, and its application to isolated fractions of DOM has provided novel insights about the structural relationships of major bioelements in DOM, including C, H, N, and P. Solid-state ^^C NMR analyses of humic substances from the Pacific Ocean indicate that there is no recognizable compositional difference between surface and deep-water counterparts (Table II). This similarity in structure suggests that humic substances comprise a relatively refractory fraction of DOM. On average.
73
Chemical Composition and Reactivity Table II Average Chemical Characteristics of Dissolved Organic Matter (DOM) Isolated from Surface and Deep Ocean Waters Chemical characteristics
Surface ocean
Deep ocean
Reference
Humic substances (% DOC) Humic substances (C/N atom) Humic substances (% C-C) Humic substances (% C-0, 0-C-O) Humic substances (% C ^ C ) Humic substances (% COO,CNO) Humic substances (% C = 0 ) Total hydrolyzable amino acids (%HS-DOC) Total hydrolyzable amino acids (%HS-DON) HMW DOM (% DOC) HMW DOM (C/N atom) HMW DOM (% C-C) HMW DOM (% C-O, 0-C-O) HMW DOM (% C = C ) HMW DOM (% COO, CNO) HMW DOM (% C = 0 ) Total hydrolyzable neutral sugars (%HMW DOC) Total hydrolyzable amino acids (%HMW DOC) Total hydrolyzable amino sugars (%HMW DOC) Total % DOC Total hydrolyzable amino acids (%HMW DON) Total hydrolyzable amino sugars (%HMW DON) Total % DON
5-25 36-56
15-25 39-57
1-5 3-4 4 4 4 4 4
5-11 25-40 15-18
20-25 18-20
6-13
1.5-2.5
1.3-2.6 10.3-19.6 17-29 3.6-7.1 20.6-36.1
0.5-0.6 5.0-7.1 12-28 1.4-1.9 13.4-29.9
44 19 19 15 3 nd
25 54 5 13 3
3-4
46 17 19 15 3 nd 5-9 30 28 21 16 5
3>-4
6-7
8-10 8,10 8,11 8,11 8,11 8,11 8,11 12-13
12 14
12-13
12 14 12
Note. Humic substances are operationally defined as DOM that is retained on XAD-2 or XAD-8 resins under acidic conditions. High-molecular-weight (HMW) DOM is operationally defined as DOM that is retained by an ultrafiltration membrane with a ~ l - n m pore size and 1000-Dalton molecular weight cutoff. Cross-polarized magic angle spinrung (CPMAS) ^^C nuclear magnetic resonance spectroscopy was used for carbon functional group analyses. References. 1 Gagosian and Stuermer 1977; 2, Harvey et al. (1983); 3, Druffel et al. (1992); 4, Hedges et al. (1992); 5, Ishiwatari (1992); 6, Hubberton et al. (1994); 7, Hubberton et al. (1995); 8, Benner et al (1992); 9, Guo et al. (1995); 10, Benner et al. (1997); 11, McCarthy et al. (1993); 12, McCarthy et al. (1996); 13, Skoog and Benner (1997); 14, Benner and Kaiser unpublished.
humic substances are dominated (^45% of C) by hydrogen-substituted alkyl C, such as methylene groups (Table II; Fig. 4). Oxygen-substituted alkyl C, such as carbohydrate-C, accounts for slightly less than 20% of the C in humic substances. Unsaturated C, such as aromatic-C, accounts for '^20% of the C. About 15% of the C resides in carboxyl and amide groups, although the low
74
Ronald Benner c=o
c=o
coo, CNO
c-c
COO. CNO
c-c
c=c
c=c
C-0, 0-C-O c-0, 0-C-O HMW DOM
Humic substances
Figure 4 The distribution of major functional groups of carbon in high-molecular-weight (HMW) DOM and dissolved humic substances from the surface ocean. The functional group assignments are based on analyses by solid-state cross-polarized magic angle spinning (CPMAS) ^^C NMR.
N content of humic substances indicates that most of this is carboxyl-C (salt and ester). A low percentage (3%) of the C resides in carbonyl compounds (ketones and aldehydes). There have been relatively few molecular-level analyses of conmion biochemicals in dissolved humic substances isolated from seawater. Analyses of amino acids (THAA) indicates that they account for 5-11% of the N in dissolved humic substances (Table II), a value that is similar to the percentage of amino-acid N in DOM (Table I). It is important to recognize that the same common biochemicals found in DOM are often found in dissolved humic substances. Thus, molecularlevel analyses of seawater DOM include biochemicals that reside in the dissolved "humic substances" fraction. As discussed earlier, solid-phase extraction isolates DOM principally on the basis of chemical properties, whereas ultrafiltration isolates DOM principally on the basis of physical properties. Given this fundamental difference in isolation mechanisms, it is particularly interesting to compare the chemical compositions of these fractions of DOM. The C:N ratio of HMW DOM isolated using ultrafiltration ranges from 15 to 20 and is highly enriched in N relative to its humic substances counterpart (Table II). Another striking difference between humic substances and ultrafiltered HMW DOM is in the compositional variability between DOM isolated from surface and deep water. Humic substances are compositionally invariant between the surface and deep ocean, indicating that they are less reactive components of DOM. In contrast, HMW DOM from surface water is highly enriched in oxygen-substituted alkyl C (C-0, 0-C-O) relative to HMW DOM from deep water (Table II). These functional groups are commonly found in carbohydrates, and the C - 0 : 0 - C - 0 ratio falls in the range of 4-5:1 (Benner et ai, 1992), which is
Chemical Composition and Reactivity
75
characteristic of common carbohydrates (i.e., pentoses and hexoses). Slightly over 50% of the C in HMW DOM from surface water is in carbohydrates, whereas only half that percentage is found in HMW DOM from deep water (Table II). Half of all C in surface water HMW DOM is found in carbohydrate-like structures (Fig. 4), indicating that oligo- and polysaccharides are abundant. The large reduction in the percentage of carbohydrate-C in deep-water HMW DOM suggests that oligo- and polysaccharides are reactive components that are largely produced and consumed in the upper ocean. About 25-30% of C in surface and deep DOM resides in substituted alkyl C, which is considerably less than is found in dissolved humic substances (Table II; Fig. 4). Only ~ 5 % of the C in surface DOM resides in unsaturated-C (C=C) structures, whereas ^20% of the C in deep DOM resides in unsaturated-C structures. The major reduction in the fraction of carbohydrate-C between surface and deep HMW DOM is largely compensated by an increase in the fraction of unsaturated-C in deep HMW DOM. Carboxyl-C and amide-C accounted for 13-16% of HMW DOM. The maximum amide-C contribution can be estimated based on the N content if we assume all N is in amide form (McCarthy et al, 1997). Based on an average C:N ratio of 17, a maximum of ^6% of the C in HMW DOM is in amide form, and a minimum of 6-10% of the C is found in carboxyl (salt and ester) structures. A small fraction (3-5%) of the C in HMW DOM resides in aldehyde and ketone structures. The overlap between the C isolated as humic substances and DOM has not been determined, but the present comparison between these fractions indicates substantial compositional differences. Based of the major difference in the carbohydrate-C in surface water humic substances and HMW DOM as indicated by NMR, it appears that the potential overlap is at most --50%. Overlap between these fractions of DOM could be larger in deep water because there was less compositional distinction between these isolated fractions. Molecular-level analyses indicate that neutral sugars (THNS) account for 613% of the C in surface HMW DOM and 1.5-2.5% of the C in deep HMW DOM (Table II). Amino sugars (THAS) account for an additional 1.3-2.6% of the C in surface HMW DOM and 0.5-0.6% of the C in deep HMW DOM (Table II). The NMR analysis of surface and deep HMW DOM samples indicated that carbohydrates accounted for ^50 and '^25% of the C, respectively. Together, neutral and amino sugars account for 15-20% of the carbohydrates in surface HMW DOM and 5-10% of the carbohydrates in deep HMW DOM indicated by NMR. A much larger fraction (50%) of the total carbohydrates in freshly produced HMW DOM from phytoplankton is characterized as neutral sugars (Biersmith and Benner, 1998). The fraction of total carbohydrates identified as neutral sugars appears to decrease with increasing diagenetic alteration of DOM. Carbohydrates are a diverse class of compounds, and only a subset is currently analyzed at the molecular level. Thus, it is possible that the predominant
76
Ronald Benner
carbohydrates in seawater are those that we do not analyze at the molecular level. Variability in susceptibility to hydrolysis is also a problem in carbohydrate analyses at the molecular level. Optimization of hydrolysis is a balance between conditions that are strong enough to release monomers from hydrolysis-resistant matrices and conditions that do not destroy the molecular identity of the monomers. It is also possible that some of the oxygen-substituted carbon identified by NMR does not reside in carbohydrates. We are unsure of the explanation for this important observation, but it demonstrates the usefulness of combining bulk and molecular analyses in attempting to unravel the mysteries concerning the origins and transformations of DOM. Amino acids (THAA) account for a relatively constant 3 ^ % of the C in surface and deep HMW DOM (Table II). A larger fraction (12-29%) of the N in surface and deep HMW DOM is accounted for as amino acids. Amino sugars account for 3.6-7.1% of the N in surface HMW DOM and 1.4-1.9% of the N in deep HMW DOM. Thus, a total of ^ 1 5 % of the C and 28% of the N in surface HMW DOM resides in neutral sugars, amino sugars, and amino acids, whereas ^ 6 % of the C and ~ 2 1 % of the N in deep HMW DOM resides in these common biochemicals. The percentages of total carbon accounted for as neutral sugars, amino sugars, and amino acids in DOM and HMW DOM from surface and deep water are compared in Fig. 5. Two trends in these data are particularly important. The percentages of carbon accounted for in these biochemicals are greater in HMW DOM relative to DOM, and the respective percentages of carbon are greater in surface water relative to deep water. As discussed earlier, the yields of these conmion biochemicals are useful indicators of the diagenetic history of the organic matter. The higher biochemical yields in surface relative to deep DOM and HMW DOM indicate that surface waters contain organic matter of more recent origin that is less altered and potentially more bioreactive than organic matter in deep water. This interpretation of the biochemical data is consistent with the contrasting average apparent ages of surface and deep DOM (Williams and Druffel, 1987) as well as their relative bioreactivity (Barber, 1968). The higher yields of neutral sugars, amino sugars, and amino acids in HMW DOM relative to DOM indicate that the HMW components of DOM are less diagenetically altered and potentially more bioreactive than the LMW components. Direct comparisons of the bioreactivity of the HMW and LMW components of DOM in a variety of marine environments also indicates that the bulk of HMW DOM is more bioreactive than the bulk of LMW DOM (Amon and Benner, 1994, 1996a). These varying lines of evidence lead to the observation that LMW DOM is the most diagenetically altered and least bioreactive fraction of organic matter in seawater. The three groups of biochemicals analyzed in DOM and HMW DOM also appear to have varying susceptibilities to diagenetic alteration. Neutral sugars and amino sugars undergo greater relative losses between surface and deep DOM
u* L 1
77
Chemical Composition and Reactivity
1 — 1 — 1 — 1 — 1 — 1 — 1 —
Surface DOM
Surface HMW DOM
Deep DOM
Deep HMW DOM
L
H B D
10
Amino acids Amino sugars Neutral sugars
15
20
Percent characterized organic carbon
Figure 5 Contributions of total hydrolyzable amino acids, total hydrolyzable neutral sugars, and total hydrolyzable amino sugars to the organic carbon content of DOM and high-molecular-weight (HMW) DOM from the surface (< 100 m) and deep (> 1000 m) ocean.
and HMW DOM than do amino acids, suggesting that most of these combined sugars are more bioreactive than combined amino acids. Seawater HMW DOM has been analyzed by solid state ^^N NMR and ^^P NMR aswellasi^CNMR(Benner^?a/., 1992; McCarthy ^f a/. 1991; Clark etai, 1998), providing a unique perspective on the chemical composition of this fraction of surface and deep HMW DOM (Fig. 6). It is quickly apparent that there is little variability between the ^^N and ^^P spectra of surface and deep HMW DOM, compared to substantial differences between ^^C spectra of surface and deep HMW DOM (as previously discussed). The concentrations of carbon in major functional groups of HMW DOM from surface and deep water are compared in Table III. Assuming the HMW DOM in surface and deep water had similar concentrations and compositions at the time of formation, the difference between the surface and deep HMW DOM compositions is representative of the carbon removed during decomposition. This calculation indicates that 70% of the carbon removed was oxygen-substituted, as occurs in carbohydrates. The C - 0 : 0 - C - 0 ratio of the removed fraction was in the 4-5:1 range expected for common carbohydrates. By this analysis, combined carbohydrates are the most reactive components of HMW DOM.
78
Ronald Benner
l^C-NMR
300
200
100
-100
l^N-NMR
450 " ' " ' * 350 " " ' " 250 '
40
20
«I''''
I'''
0
150
50
r I r y f i » I I I I I ' I '''
-20
-40
Chemical shift (ppm) Figure 6 Solid-state cross-polarized magic angle spinning (CPMAS) ^^C NMR, ^^N NMR, and ^^P NMR spectra of surface and deep high-molecular-weight (HMW) DOM from the surface (< 100 m) and deep (> 1000 m) Pacific ocean. Spectra were taken from Benner et al. (1992), McCarthy et al. (1997), and Kolowith et al. (2001). The asterisks on the ^^N NMR spectra mark the locations of spinning sidebands.
Another interesting feature of the HMW DOM comparison in Table III is the near constant relationship between the C-C and (COO + CNO) functional groups. The C-C:(COO -h CNO) ratio is 1.92,1.87, and 1.97 in surface, deep, and "difference" HMW DOM groups, respectively. Combined amino acids contain all of these functional groups, but comprise a small fraction (3-4%) of the chromatographically
79
Chemical Composition and Reactivity Table III
The Concentrations (/>tM) of Organic carbon and Nitrogen in Surface and Deep High-Molecular-Weight (HMW) DOM and the Concentrations of Organic Carbon Identified in Major Functional Groups by (CPMAS) ^^C Nuclear Magnetic Resonance Spectroscopy HMW DOM
DOC
Surface Deep Difference
21.0 8.1 12.9
DON
ifJLM)
1.25 0.45 0.80
c-c
o-c-o
c=c
COO, CNO
C=0
5.25 2.43 2.82
11.3 2.27 9.03
1.05 1.70 -0.6S
2.73 1.30 1.43
0.63 0.41 0.22
C-0,
Note. The concentrations of DOC and DON are typical values for Pacific Ocean HMW DOM (Benner et al, 1997). The fraction of carbon in major fiinctional groups was taken from Table II.
resolved carbon in surface and deep HMW DOM (Table II). The combined C-C and (COO + CNO) functional groups account for -^40% of the carbon in HMW DOM (Table III). Thus, combined amino acids account for a small fraction of these functional groups in HMW DOM. The molecular "home" of most of these functional groups remains unknown. The^relatively constant ~2:1 ratio of these functional groups in HMW DOM undoubtedly provides clues about its biochemical origin. The constant ratio of these functional groups indicates this material is of average reactivity. The main feature of the ^^N NMR spectra is a resonance centered near a chemical shift of 260 ppm (Fig. 6). This resonance corresponds to the chemical shift for amide nitrogen, which is found in combined amino acids and A/^-acetyl amino sugars (McCarthy et al, 1997). A shoulder is observed on the downfield side of the main resonance at 260 ppm, and this could be indicative of the presence of nitrogen in heterocyclic structures. It is estimated that 75-85% of the nitrogen in HMW DOM is in amide structures. The abundance of amide nitrogen in HMW DOM is perplexing when compared to the amount of measured amino acid (THAA) nitrogen in these samples. Only 8-12% of the amide nitrogen indicated by NMR analyses is identified at the molecular level as hydrolyzable amino acid nitrogen (McCarthy et al, 1997). Proteins and peptides are the most common biopolymers with amide nitrogen. It is possible that a large fraction of the peptide and protein nitrogen in HMW DOM is resistant to hydrolysis, but it is unlikely that hydrolysis-resistant peptides and proteins would be several-fold more abundant than the hydrolyzable fraction that predominates in marine organisms. Biopolymers containing A^-acetyl amino sugars, such as chitin and peptidoglycan, are also abundant in marine plankton. These biopolymers contain amide nitrogen, but analyses of hydrolyzable amino sugars (THAS) in HMW DOM indicate that <10% of the nitrogen resides in these biopolymers (Table II). These combined results are intriguing. Most (>80%) of the amide nitrogen in HMW DOM remains unidentified at
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the molecular level. Most (>80%) of the oxygen-substituted carbon (i.e., carbohydrate) indicated by *^C NMR also remains unidentified at the molecular level. When we resolve these differences we will understand fundamental aspects about the sources and transformations of DOM that remain elusive at the present time. Decomposition processes lead to an increase in the fraction of molecularlyuncharacterized organic matter (Hedges et al, 2000). Thus, the above observations suggest a shared diagenetic history for the major biochemicals in DOM. The ^^P NMR spectra of HMW DOM have resonances centered around chemical shifts of 0 and 25 ppm (Fig. 6). The main resonance at 0 ppm is characteristic of phosphate esters, including monoester and diester phosphates (Clark et al, 1998; Kolowith et al, 2001). About 75% of the phosphorus in surface and deep HMW DOM resides in ester structures. Phosphate esters are found in conmion biopolymers, such as membrane phospholipids, RNA, and DNA. The resonance at 25 ppm is characteristic of phosphonate structures, which contain a carbonphosphorus bond. About 25% of the phosphorus in surface and deep DOM resides in phosphonate structures. Phosphonates are much less abundant in biopolymers than phosphate esters, but they are synthesized in phosphonolipids and phosphonoproteins by a variety of marine organisms (Kolowith et al, 2001). The high relative abundance of phosphonates in HMW DOM is somewhat surprising given their relatively low abundance and apparently limited distribution in marine organisms. Analyses by ^H NMR are supportive of ^^C NMR analyses, indicating that surface water HMW DOM is rich in carbohydrates and depleted in aromatic components (Vemonclark etal, 1995; Aluwihare etal, 1997). These studies also noted the presence of acetyl groups in DOM, and it was speculated that the carbohydrates in DOM were predominantly 0-acetyl oligosaccharides (Aluwihare et al, 1997). However, subsequent analyses of these DOM samples by direct temperatureresolved ammonia chemical ionization mass spectrometry did not detect evidence for 0-acetyl oligosaccharides (Boon et al, 1998). The latter authors found evidence for the presence of A/^-acetyl groups and suggested that the acetyl groups indicated by ^ H NMR reside in A/^-acetyl amino sugars rather than O -acetyl oHgosaccharides. The presence of amino sugars in HMW DOM is confirmed by molecularlevel analyses (Table II). As indicated above, A^-acetyl amino sugar polymers in HMW DOM contribute to the amide signal observed in the ^^N NMR spectra.
III. MAJOR TOPICS OF ONGOING AND FUTURE RESEARCH ABOUT THE CYCLING OF DOM A. MECHANISMS OF FORMATION AND REMOVAL OF BlOREFRACTORY D O M Two important observations about the cycling of DOM in the ocean are readily apparent: (1) most of the DOM produced is rapidly consumed, (2) most of the
Chemical Composition and Reactivity DOM remaining in the ocean is resistant to biological utilization. The first observation is apparent from measurements of the growth and respiration rates of microorganisms in surface waters of the ocean. Heterotrophic bacterial production is a large fraction (0.15-0.20) of primary production in the ocean (Ducklow, 2000). Heterotrophic bacteria are the predominant consumers of DOM, and their growth efficiencies are typically less than 30% (del Giorgio and Cole, 2000). Thus, bacteria utilize over 50% of primary production for growth and respiration in the upper ocean. Production and consumption of DOM in the surface ocean are typically tightly coupled, indicating that most DOM produced in the surface ocean is rapidly consumed. A small fraction of the organic matter produced in the surface ocean escapes remineralization and contributes to the slowly cycling, "biorefractory" DOM reservoir. There are numerous observations indicating that most of the DOM in the ocean is resistant to biological utilization. Most DOM (>70%) resides in the deep ocean, and experimental studies of the bioreactivity of deep water DOM (e.g.. Barber, 1968) as well as oceanic surveys of deep water DOC concentrations (Hansell and Carlson, 1998) indicate that this material is of limited bioavailability and reactivity. Average radiocarbon ages of DOM in the deep ocean are 4000-6000 years (WiUiams and Druffel, 1987; Bauer et al, 1992), a further indication of the slow cycling of this material. So, while most of the DOM produced in the ocean is consumed on time scales of hours to weeks, most of the DOM reservoir in the ocean is resistant to biological utilization. There are two key questions in this carbon cycle conundrum. How is biorefractory DOM formed, and how is it removed? Answers to these questions are central to understanding the global carbon cycle as well as carbon cycling in the ocean. Information about the size distribution and chemical composition of DOM presented earlier in this chapter provides some clues about the formation of biorefractory DOM in the ocean. The fraction of LMW DOM, chemically uncharacterized DOM, and biorefractory DOM all increase with depth in the ocean and appear to be related. Enzymatic and photochemical decomposition processes generally lead to decreases in the size and molecular weight of DOM (Amosti, 1998; Smith et al, 1992; Opsahl and Benner, 1998). Direct comparisons of the biological reactivity of naturally occurring HMW and LMW DOM indicate that HMW DOM is generally more bioreactive (Amon and Benner, 1994,1996a). The yields of hydrolyzable neutral sugars and amino acids decrease with increasing decomposition and diagenetic alteration (Cowie and Hedges, 1994). The depth-related trends in the size, composition, and bioreactivity of DOM in the ocean indicate that most biorefractory DOM in the deep ocean exists as relatively small (<1000 Dalton) molecules of unknown chemical composition. These observations are all consistent with the size-reactivity continuum concept (see Amon and Benner, 1996a) of a degradative sequence from macromolecular material to small molecules that loose their molecular signature and become increasingly resistant to biological utilization.
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There are a variety of potential mechanisms for the formation of biorefractory LMW DOM in the ocean. Some biologically produced organic matter is inherently resistant to biodegradation, but this does not appear to be the primary mechanism of formation of biorefractory LMW DOM in the ocean. The depth-related trends discussed above suggest that biorefractory DOM is formed through degradative processing of macromolecular material rather than direct production by organisms. Photochemical transformations of organic matter occur through free radical reactions that are capable of altering chemical structures to form photoproducts that are resistant to biological utilization and unrecognized by molecular-level analyses of common biochemicals. There is growing evidence that photochemical transformations produce biorefractory DOM in seawater (Benner and Biddanda, 1998; Tranvik and Kokalj, 1998; Obemosterer et al, 1999). Heterotrophic microbial processes also produce biorefractory DOM (Brophy and Carlson, 1989; Heissenberger and Hemdl, 1994; Tranvik, 1993; Ogawa et al, 2001). The mechanisms for the formation of this biorefractory DOM are not understood, but it is possible that nonspecific enzymatic transformations contribute to the formation of biorefractory and chemically unrecognizable DOM (O'Brien and Herschlag, 1999; Williams, 2000; Ogawa et ai, 2001). Based on the average radiocarbon ages of DOM in the deep Atlantic and Pacific oceans of 4000 and 6000 years (Williams and Druffel, 1987, Bauer et al, 1992), Druffel et al. (1992) estimated that 20% of deep water DOM is removed during each mixing cycle ('^lOOO years) of the deep ocean. There is evidence for the slow removal of biorefractory DOM during deep-water circulation (Hansell and Carlson, 1998), but the mechanism of this loss is unknown. It is also possible that biorefractory DOM is removed during its residence in surface waters. The radiocarbon age of DOM exceeds deep ocean mixing times, indicating that on average biorefractory DOM passes through surface waters several times before being removed. During residence in surface waters, biorefractory DOM is susceptible to photochemical transformations that can directly remove carbon as well as increase its susceptibihty to microbial removal (Kieber et al, 1989; Mopper et al, 1991; Miller and Zepp, 1995; Benner and Biddanda, 1998; see Mopper and Kieber, Chapter 9).
B. BACTERIAL CONTRIBUTIONS TO DOM It is widely recognized that autotrophic and heterotrophic bacteria are major contributors to the production and consumption of organic matter in the ocean. Bacteria are the most abundant autotrophs and the most abundant heterotrophs in seawater. They are central components of the ocean food web, and the major mechanisms of DOM production, including direct release, viral lysis, and grazing, all are applicable to bacteria. It is therefore logical to expect bacteria to be a major source of DOM in the ocean. However, this area of research has largely been
Chemical Composition and Reactivity ignored, and relatively little is known about the contributions of bacteria to DOM. Most attention regarding bacteria has been focused on the role of bacteria as DOM consumers. Bacterial utilization of labile radiolabeled substrates (e.g., glucose) and subsequent production of radiolabeled DOM that is resistant to microbial utilization has been demonstrated in several studies (Brophy and Carlson, 1989; Tranvik, 1993; Heissenberger and Hemdl, 1994; Stoderegger and Hemdl, 1998). Although these studies clearly demonstrate the biorefractory nature of DOM and associated radiolabel, the chemical nature of this material is unknown. The radiolabeled substrate could become associated with biorefractory DOM through physical and chemical processes, or it could be utilized by bacteria and released in a different molecular form as newly biosynthesized material. Abiotic control experiments indicate a major role for microbial processes in the production of biorefractory DOM, although it is unclear whether bacteria directly produce DOM that is resistant to degradation. Ogawa et al. (2001) recently conducted similar experiments but used molecular-level chemical analyses to trace the production of biorefractory DOM by marine bacteria. These studies clearly demonstrate that the DOM is bacterially derived and includes such conmion biochemicals as combined neutral sugars, amino acids, and amino sugars that persist for long (>1 year) periods of time. It is interesting that most of the DOM released from bacteria was not characterized at the molecular level and was therefore compositionally similar to DOM in the ocean (Ogawa et al, 2001). It is not known why some bacterially-derived DOM is resistant to biodegradation. Several recent studies have found chemical evidence for the bacterial origin of biorefractory DOM in the ocean. Membrane-derived bacterial proteins (porins) have been identified as ubiquitous components of DOM in seawater (Tanoue et al, 1995). The D-form enantiomers of common amino acids found in the bacterial cell wall polymer, peptidoglycan, have also been reported as important components of DOM in seawater (McCarthy et al, 1998). A variety of methylated sugars and amino sugars that are likely to be of bacterial origin have also been identified in marine DOM (Boon et al, 1998; Kaiser and Benner, 2000). It is difficult to estimate the fraction of DOM of bacterial origin based on these biomarkers, but there is growing evidence that a substantial fraction of biorefractory DOM in the ocean is derived from bacteria. Knowledge of the origins of biorefractory DOM will provide important clues about the mechanisms of formation of this largest reservoir of fixed carbon in the ocean.
C. FATE OF TERRIGENOUS DOM IN THE OCEAN The global annual discharge to the ocean of terrigenous DOC from rivers is quite large (0.25 Pg), yet there is no evidence for a major terrigenous component
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of DOM in the ocean (Hedges et ah, 1997). This is particularly surprising because riverine DOM is generally resistant to biodegradation and has a chemical composition indicating that it is largely soil derived and highly degraded (Benner et al, 1995; Hedges et al, 1994). The stable carbon isotopic composition of DOM in the ocean indicates a predominantly marine, rather than terrestrial, origin and the low concentrations of lignin-derived phenols, unique tracers of terrestrial carbon, are also indicative of a minor terrestrial component (Meyers-Schulte and Hedges, 1986; Druffel et al, 1992; Opsahl and Benner, 1997). Concentrations of Ugnin-derived phenols that are 2.6 times higher in the Atlantic than the Pacific appear to reflect the proportionately higher riverine discharge to the Atlantic (Opsahl and Benner, 1997). In both of these ocean basins the residence time of lignin-derived phenols is relatively short (20-130 years) compared with bulk marine DOM, indicating variability in the predominant mechanisms for removal of these chemically-distinct fractions of DOM. The transport of riverine DOM to the coastal ocean is largely conservative, although losses of specific components due to flocculation can occur at low salinities during mixing (Sholkovitz, 1976; Fox, 1983; Benner and Opsahl, 2001; see Cauwet, Chapter 12). Riverine DOM is slowly degraded by microorganisms, and it appears that microbial degradation of riverine DOM continues in the coastal ocean (Chin-Leo and Benner, 1992). Riverine DOM is generally more photoreactive than marine DOM, and the combination of photochemical and microbial processes is likely to be important for its removal from the ocean (Kieber et ai, 1990; Miller and Zepp, 1995; Amon and Benner, 1996b; Miller and Moran, 1997; Opsahl and Benner, 1998). Additional field and laboratory experiments are needed to understand the mechanisms of removal of terrigenous DOM from the ocean and the factors controlling this process. Studies of the distribution of terrigenous DOM are needed to better define the geographic regions where removal processes are most active. Recent studies of the distribution and composition of terrigenous DOM in the Arctic ocean indicate that physical transport to the north Atiantic is the dominant removal mechanism from these ice-covered waters (Opsahl et al, 1999). Similar regional studies are needed in temperate and tropical environments where terrigenous DOM receives greater exposure to sunlight and warmer temperatures. Molecular evidence of photochemical transformations of terrigenous DOM in the northern Gulf of Mexico near the Mississippi River delta was recently observed (Benner and Opsahl, 2001). Improved and expanded bulk and molecular characterizations are needed to provide a more complete accounting of the components of terrigenous DOM in seawater, because the different chemical components of terrigenous DOM have varying susceptibilities to photochemical and microbial removal mechanisms.
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ACKNOWLEDGMENTS I thank the U.S. National Science Foundation for supporting my research, J. Hedges and S. Wakeham for comments on the manuscript, and the students, postdoctoral associates, and technicians who have passed through my laboratory and contributed to the concepts and research presented in this chapter.
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Chapter 4
Production and Removal Processes Craig A. Carlson^ Bermuda Biological Station for Research, St. Georges GEOl, Bermuda I. Introduction II. DOM Production Processes A. Extracellular Phytoplankton Production B. Grazing-Induced DOM Production C. DOM Production via Cell Lysis D. Solubilization of Particles E. Bacterial DOM: Origination and Transformation of DOM III. DOM Removal Processes A. Biotic Consumption of DOM B. Abiotic Removal Processes IV. DOM Lability A. Biologically Refractory DOM B. Biologically Labile DOM
C. Biologically Semilabile DOM D. Continuum of Biological Lability V. DOM Accumulation A. Abiotic Formation of Biologically Recalcitrant DOM B. Biotic Formation of Recalcitrant DOM C. Limitation of Bacterial Growth and Accumulation of Biodegradable DOM D. Microbial Conmiunity Structure and DOM Utilization VI. Summary References
I. INTRODUCTION Dissolved organic matter (DOM), operationally defined as organic matter that passes a GF/F or a 0.2 /jim filter, represents one of the largest exchangeable carbon reservoirs on earth. The global dissolved organic carbon (DOC) pool is estimated to be 685 Gt C (Hansell and Carlson, 1998a), a value comparable to the mass of ^Present address: Department of Ecology, Evolution and Marine Biology, University of California at Santa Barbara, Santa Barbara, CA 93106-9610. Fax: (805) S93-4124. E-mail: carlson@lifesci. ucsb.edu. Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
91
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Craig A. Carlson
inorganic C in the atmosphere (MacKenzie, 1981; Fasham et al., 2001). Net oceanic uptake of CO2 is approximately 2.1 Gt per year (Quay et al, 1992; Takahashi et al, 1999), a small percentage of the oceanic DOC pool. Small perturbations in the production or sink terms of the oceanic DOC pool could strongly impact the balance between oceanic and atmospheric CO2. Thus, processes that control DOM production, consumption, and distribution are biogeochemically significant with regard to carbon export (Copin-Montegut and Avril, 1993; Carlson et al, 1994; Ducklow et al, 1995; Hansell and Carlson, 1998b, 2001) and carbon storage in the ocean interior (Hansell and Carlson, 1998a; Hansell et al, 2001). DOM also has important ecological significance as a byproduct of biological productivity and as a substrate that supports heterotrophic bacterial growth (Williams, 1970; Pomeroy, 1974; Williams, 1981; Azam et al, 1983; Ducklow and Carlson, 1992). A number of biological processes result in the production of DOM (Fig. 1). A portion of the carbon lost from the planktonic food web as DOC is then salvaged by heterotrophic bacterioplankton, initiating the microbial loop (Azam et al, 1983), and is either repackaged into bacterial particles and passed to higher trophic levels (a trophic link), or remineralized back to its inorganic constituents (a trophic sink; Ducklow et al, 1986). While 50% of carbon fixed by phytoplankton (Ducklow and Carlson, 1992; Williams, 2000) or more (del Giorgio and Cole, 1998) is routed through DOM and processed by bacterioplankton, a fraction of DOM production accumulates in the surface waters and is resistant to rapid microbial attack. Hansell and Carlson (1998b) estimate that 1.2 Gt C year~^ or 17% of global new production escapes rapid microbial utilization, accumulates in the surface waters and is available for export to the ocean's interior. Thus, factors that control the production, removal, and accumulation of DOM in the surface ocean have both ecological and biogeochemical significance. The objectives of this chapter are to (1) review the various mechanisms of DOM production, (2) review the processes of DOM consumption and removal, (3) examine the characteristics of the various pools of DOM in terms of biological lability and their ecological and biogeochemical significance, and (4) review the factors and processes that lead to DOM accumulation. The conceptual model of the various DOM production and removal processes outlined in Fig. 1 will serve as a guide for the first two sections of this review.
11. DOM PRODUCTION PROCESSES The euphotic zone is the principal site of organic matter production in the open ocean. Net production of DOM results from the temporal and spatial uncoupling of in situ biological production and consumption processes (Fig. 1). Net DOM production is most evident in ocean regions that experience annual phytoplankton
Production and Removal Processes
93
Sinking Particles & Aggregates
Figure 1 Schematic representation of the various DOM production and consumption processes in marine systems. The broken arrows associated with viruses represent viral infection and its effect on DOM production via cell lysis. The dark arrow represents dominant biotic removal process. Roman numerals and letters represent the section in the text where the process is discussed.
blooms (Table I). The magnitude and quality of DOM produced during these bloom events varies considerably and is controlled by a number of biological, chemical, and physical parameters. While DOM production is ultimately constrained by the magnitude of primary production (PP), there are several mechanisms responsible for DOM production including (a) extracellular release (ER) by phytoplankton, (b) grazer mediated release and excretion, (c) release via cell lysis (both viral and bacterial), (d) solubilization of particles, and (e) bacterial transformation and release.
Table I Comparison of Maximum Daily 14C Primary Production (PP) Rates and Seasonally Produced DOC, DON, and DOP (ADOC, ADON, and ADOP) Stocks and Concentrationsduring PhytoplanktonBlooms for Selected Marine Sites
Site
DOM deptha (m)
ADOM stock and concentration
PP (mmol m-' day-')
ADOM
type
mmolm-2
pM
548
Arctic Northeast water PolYnYa
&70
11-225
ADOC
35M76Ob
Northeast water PolYnYa
0-70
11-225
ADON
0-27b
04.39
Cornm ents ADOC, change in DOC between May and June; range represents spatial variability ADON, change in DON between May and June; range represents spatial variability; C:N of ADOM > 23
Baltic Sea Bothnian Sea 63" 30'N. 19" 48'E Gulf of Riga 58" 15". 24" 24' E Gulf of Riga 57" 16'N, 24" 23' E
4
ADOC
6G110
3-20
ADOC
70
3-20
ADOC
630
&loo
ADOC
Reference Daly et al., 1999
Daly et al., 1999
Range of maximum DOC from a 2-year time series; ADOC, change in DOC between spring and summer ADOC, change in DOC between spring and summer transect means; coastal input exists ADOC change in DOC between spring and summer transect means; coastal input exists
Zweifel et al., 1993
1-Year time series; ADOC, change in DOC between February and November; range, maximum concentration over 100 m
Copin-MontCgut and Avril, 1993
Zweifel. 1999
Zweifel, 1999
Mediteranean Sea 43" 25' N, 07" 52' E
1233
8-2 1
North Atlantic English Channel 48" 45' N, 3" 57'W
0-30
275
70
ADOC, change in DOC between April and August
Wafar et al., 1984
ADON
3
Wafar et al., 1984
ADOP
0.12
ADON, change in DON between August and September ADOP, change in DOP between August and October 1-Year time series; ADOC, change in DOC between March and June
ADOC
2100'
English Channel 50" 02' N, 4" 22' w
0-70
125
ADOC
1820b
26
English Channel 50" 02' N, 4" 22' w Norwegian Sea 66" N, 2' E
0-70
125
ADON
119'
1.7
0-50
ADOC
165O-418Ob
33-83
5
ADOC
108
45
ADOC
15
ADOC
North Sea 53" Ol'N, 4" 21'E North Sea 58" 55' N, 0" 32' E Bedford Basin, Nova Scotia, Canada
ADOC, change in DON between March and June
Wafar et al., 1984 Banouh and Williams, 1973; PP from Boalch et aL, 1978 Banoub and Williams, 1973
Annual range at for a 3-year time series; no systematic variability with DON 1-Year time series; ADOC, change in DOC between March and April
Bersheim and Myklestad, 1997 Duursma, 1963
21
Measured as dissolved carbohydrates
Ittekkot et al., 1981
40
ADOC, change in DOC between February and April; Coastal hay
Kepkay et al., 1997 (Continues)
Table I (Continued) ADOM stock and concentration
DOM depth'(m)
PP (mmol m-2 day-')
ADOM type
mmolm-2
uM
Sargasso Sea 31" 50'N, 64" 10'W
G250
57-123'
ADOC
500-1400
2 4
Range of maximum DOC from an annual range at for a 5-year time series; no systematic variability with DON
Strait of Georgia
G20
100
ADOC
2500
125
Strait of Georgia
c-20
100
ADON
I-Year time series, ADOC, change between February and August Calculated from mass balance considerations
Site
Southern Ocean Antarctic Polar Front Zone (APFZ) Australian sector 56'45" 24' S Australian sector 56"45O 24' S Atlantic sector 48-52O.5, 2640" w
13
Comments
Reference Carlson et aL, 1994; Hansel1 and Carlson, 2000 Parsons et al., 1970 Williams, 1995; ADON estimates
Surface layer
ADOC
5-15d
Calculated as increase above deep water concentrations;range represents spatial variability
Ogawa et al., 1999
Surface layer
ADON
1.5-7.2d
Calculated as increase above deep water concentrations;range represents spatial variability
Ogawa et aZ., 1999
Calculated from difference max, and minimum concentration in APFZ, Largest accumulationnear southern periphery of A P E
Dafner, 1992
G50
66
ADOC
5ood
Atlantic sector 47-60"s
0-100
Indian Ocean sector 49-63" S
0-100
Antarctic Continental Shelf Systems Bransfield Strait off Palmer Peninsula Prytz Bay 68" 30'S, 77" 50' E Ross Sea 76" 30' S transect line Ross Sea 76" 30's transect line
6-2 1
ADOC
< 1-2od
ADOC
4-16d
0-100
ADOC
>500-1000
15
ADOC
>go00
ADOC
370-1 140
0-150
Surface
80-226e
ADON
0-23
0.1-5.5
Calculated as increase above deep water concentrations; range represents spatial variability Calculated as increase above deep water concentrations; range represents spatial variability
K&kr et al., 1997 Wiebinga and de Baar, 1998 & citations within
Bloom of Phaeocystis sp., Thalassiosira sp., and Corethron sp.
Bolter and Dawson, 1982
Phaeocystis antarctica bloom
Davidson and Marchant, 1992 Carlson et al., 2000
Time series measurement of a composite growing season; ADOM, change between Oct. and Jan. transect means for surface 150 m ADON represent change in surface 150 m; mean C:N ratio of ADOM = 6.2
Carlson et al., 2000
Note. PI' was integrated over the euphotic zone of each site. Blank space means data not available. Table is expanded from Carlson et al. (2000). aDOM depth refers to depth where sample was collected or depth used to integrate DOM stock. bCalculated from integration depth and mean ADOM concentration for given depth horizon. 'Primary production integrated over 140 m. 'Winter and early spring DOM concentrations in Southern Ocean equal deep DOM concentrations (Kahler et al., 1997; Carlson et al., 2000) due to deep mixing and remineralization; thus, during the growing season DOM concentrations in excess of deep water values are assumed to be seasonally produced. 'Primary production estimates from Smith and Gordon (1997) and Smith et al. (2000).
98
Craig A. Carlson
A. EXTRACELLULAR PHYTOPLANKTON PRODUCTION
Over four decades ago, extracellular release of carbohydrates was identified in algal cultures (Lewin, 1956; Guillard and Wangersky, 1958). Since then there has been an explosion of research on extracellular phytoplankton production of carbohydrates, nitrogenous compounds, and organic acids. Several extensive reviews are now available that discuss the rates and potential physiological mechanisms of algal release of DOM in marine systems (Fogg, 1983; Williams, 1990; Baines and Pace, 1991; Nagata, 2000). This topic will be discussed briefly here. Direct measurements of bulk DOM or specific compounds as well as radioisotope techniques have been employed to study ER. Tracing the uptake of ^"^C bicarbonate by phytoplankton and release into DO^'^C is often used as a method for assessing extracellular C production (Fogg, 1966). Methodologically this technique is easy; however, many artifacts associated with this method can bias the interpretation of the data. For example, a lag in DO^^C release can occur because intracellular pools of organic metabolites do not immediately reach isotopic equilibrium; thus, if DOC labeling rates are calculated with a constant tracer release model then actual release rates will be underestimated (Lancelot, 1979; Smith, 1982). In addition, uptake of DO^'^C by heterotrophic microorganisms can result in a decrease in measured DO^'^C release over an incubation (Wiebe and Smith, 1977; Lancelot, 1979), leading to an underestimate of actual DO^'^C release. Alternatively, overloading cells on afilter,rupturing cells during filtration and mishandling of sample can lead to overestimates of ER, especially in oligotrophic systems (Sharp, 1977; Goldman and Dennett, 1985). Finally, the appearance of DOM in incubated seawater samples is difficult to attribute solely to extracellular release due to the presence of a mixed microbial assemblage present and the potential contribution of other DOM production processes within the incubation bottles. Nonetheless, theory (Bj0msen, 1988) as well as field and experimental evidence (Table 11; Mague et ai, 1980; Fogg, 1983; WiUiams, 1990; Baines and Pace, 1991; Karl et al, 1998) suggests that ER of DOC is a normal function of healthy in situ photoautotrophic growth. Extracellular release of dissolved organic nitrogen (DON) has also been assessed, using ^^N tracer techniques (Bronk and Gilbert, 1993; Hu and Smith, 1998; Bronk and Ward, 2000), and is addressed in this book (see Bronk, Chapter 5). Percent extracellular release (PER) is a measure of the ^"^C accumulating in DOC relative to total particulate plus dissolved primary production following incubation. In a review of culture experiments, Nagata (2000) reported that during exponential growth PER values averaged 5% (typical range 2-10%) for a variety of marine phytoplankton isolates. Sharp (1977) criticized PER as a useful indicator in the field, suggesting that procedural artifacts such as inadequate assessment of control blanks and rupturing of cell during processing could lead to artificially high
Production and Removal Processes
99
PER, especially in systems where PP is low. The body of hterature regarding DO^'^C release in nature is large, growing, and often conflicting as to its importance (Sharp, 1977; Fogg, 1983;Bj0msen, 1988; Williams, 1990). Table II demonstrates the wide range in ER rates (0-12 jig C L-^h-^) and PER (0-80%) observed in the field for a variety of coastal and oceanic systems. Several factors, such as community structure, light intensity, nutrient deficiency, and temperature, affect PER in situ. However, for any given controlling factor one can find examples of contrasting effects on PER (Table III), indicating the complex interactions of phytoplankton C production and environmental conditions. Although physiological state, species composition, and local chemical/physical conditions can significantly affect PER, there is little systematic variability of PER across productivity regimes (Baines and Pace, 1991; Nagata, 2000). In a cross-system analysis, Baines and Pace (1991) found that, while the absolute rate of ER varied depending on the nutrient regime of the system, the average PER was 13%. 1. Extracellular Release Models Two models have been proposed to explain extracellular production by photoautotrophs. They are the overflow model (Fogg, 1966, 1983; Wilhams, 1990; Nagata, 2000) and iht passive diffusion model (Fogg, 1966; Bj0msen, 1988). a. Overflow Model Fogg (1966) reasoned that because photosynthesis is largely regulated by irradiance and cellular growth is constrained by the availabihty of inorganic nutrients, a cell's photosynthate may be produced faster than it is incorporated and would therefore be actively released via an "overflow" mechanism. It may be energetically less costly for a cell to discard surplus nonnitrogenous compounds (i.e., capsular material and carbohydrates) than to store it under nutrient-limiting conditions (Wangersky, 1978; Wood and Valen, 1990). According to the overflow model, DOM exudation should (1) correlate to the photosynthetic rate, (2) be absent at night, and (3) be composed of both low-molecular-weight (LMW < 1000 Da) and high-molecular-weight (HMW> 1000 Da) DOM (Fogg, 1966; Bj0msen, 1988; Williams, 1990). Factors such as light intensity and nutrient availabihty potentially control the degree at which the overflow model functions. However, Bratbak and Thingstad (1985) used a modeling exercise to point to a paradoxical situation in which nutrient-stressed phytoplankton appeared to stimulate bacterial production and thus increased competition for nutrients. Bj0msen (1988) argued that active release of extracellular DOC would exacerbate a nutrient limiting scenario and suggested that the release of DOM from phytoplankton was a passive process.
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104
Table III Selected Examples of Conflicting Effects of Light Intensity, Nutrient Limitation, Temperature, and Community Structure on Percent Extracellular Release (PER) of DO^^C Factor Light intensity
Species Natural assemblage Phaeocystis pouchetii (culture) Natural assemblage Natural assemblage Natural assemblage Natural assemblage (diatoms)
Natural assemblage (diatoms and Phaeocystis pouchetii) Natural assemblage
Natural assemblage Chlorella vulgaris, Isochrysis galbana, Synechococcus sp. (cultures) Nutrient concentration
Natural assemblage
Chaetoceros qffinis (culmre)
Diatom dominated assemblage (mesocosm) Chaetoceros affinis (culture)
Phaeocystis sp.-dominated assemblage (mesocosm) Marine diatoms (cultures)
Effect on PER
Citation
Increased PER with high irradiance hicreased PER with high irradiance
Hellebust, 1965
Increased PER with high irradiance Increased PER with high irradiance Increased PER with high irradiance No significant difference between high and low irradiance on PER No significant difference between high and low irradiance on PER No significant difference between high and low irradiance on PER Increased PER with low light intensity Increased PER with low light intensity Increased PER with decreasing nut concentration Increased PER with decreasing nut concentration Increased PER with decreasing nut concentration Increased PER with decreasing nut concentration Increased PER with decreasing nut concentration Increased PER with decreasing nut concentration
Guillard and Hellebust, 1971 Mague et al, 1980 Wood and Valen, 1990 Thomas, 1971 Smith et al, 1977 Lancelot, 1983
Williams and Yentsch, 1976 Fogg, 1966 Zlotnik and Dubinsky, 1989 Fogg, 1966
Myklestad et al., 1989 Norrman et al. 1995 Obemoster and Hemdl, 1995 Smith et al. 1998 Goldman et al., 1992 (Continues)
105
Production and Removal Processes Table III (Continued) Factor
Community structure
Species
Citation
Natural assemblage (diatoms) Natural assemblage (diatoms) Natural assemblage
No relationship between PER and nutrient concentration No relationship between PER and nutrient concentration No relationship between PER and nutrient concentration
Smith et al, 1911 Lancelot, 1983
Phaeocystis pouchetii, diatoms Phaeocystis pouchetii, diatoms
Phaeocystis pouchetii had greater PER than diatoms No difference for PER between natural assemblages of diatoms vs Phaeocystis pouchetii No difference for PER between natural assemblages of diatoms vs Phaeocystis pouchetii
Lancelot, 1983
Phaeocystis antarctica, diatoms
Temperature
Effect on PER
Diatom culture (Leptocylidrus danicus) Chlorella vulgaris, Isochrysis galbana. Synechococcus sp. (cultures)
PER of marine diatom was temperature independent between 5 and 20° C temperatures >30°C increased ER
Williams and Yentsch, 1976
Vemet et at.. 1998
W. 0 . Smith unpublished data Verity, 1981
Zlotnik and Dubinsky, 1989
b. Passive Diffusion Model The passive diffusion model is based on the maintenance of a concentration gradient of LMW photosynthate across the autotrophic cell membrane. Monomers, such as neutral sugars, and nitrogenous compounds, like dissolved free amino acids (DFAAs), would be released via this model (Fogg, 1966). The subsequent uptake of LMW compounds by bacterioplankton and diffusion would maintain the gradient and elicit passive diffusion from phytoplankton cells (Bratbak and Thingstad, 1985; Bj0msen, 1988). Bj0msen (1988) suggested that passive exudation was a process that continued through the night and was correlated to phytoplankton biomass ("property tax") rather than photosynthetic rate. He estimated ER of carbon to be 5% of phytoplankton biomass per day. c. Model Comparison Reports in the literature support both the overflow and the passive diffusion models. For example, observations of ER at night (Mague et al, 1980; Herman and
106
Craig A. Carlson
Kaplan, 1984) and the release of low-molecular-weight compounds (Mague et al, 1980; S0ndergaard and Schierup, 198 l;M0ller-Jensen, 1983; Lee and Rhee, 1997) support the passive diffusion model. However, findings for the release of HMW extracellular products (Guillard and Hellebust, 1971; Lancelot, 1983; Lancelot and Billen, 1984; Lignell, 1990; Biddanda and Benner, 1997), absence of ER at night (Veldhuis and Admiraal, 1985), and enhanced ER during nutrient limitation (Lignell, 1990; Wood and Valen, 1990; Goldman et aL, 1992; Smith et a/., 1998) support the overflow model. In a cross-system analysis of 16 studies, Baines and Pace (1991) found that PP explained 69% of the variance of ER; a finding that supports the overflow model over ih^ passive diffusion model. It is likely that these models are not mutually exclusive and that both models are correct given the right environmental conditions and plankton community structure. The mechanisms controlling ER are still poorly understood and conflicting reports in the literature suggest that specific environmental and growth conditions may control which model is dominant at any given time.
B. GRAZING-INDUCED D O M
PRODUCTION
Jumars et al. (1989) argued that the principal pathway of DOM from phytoplankton to bacteria was via the byproducts of zooplankton ingestion and digestion. The two classes of zooplankton, metazoa (macrozooplankton) and protozoa (microzooplankton), remove significant fractions of phytoplankton production and bacterial production in marine systems. Macrozooplankton and microzooplankton remove 1-77 and 4-60% of phytoplankton production, respectively, depending on the system (Sherr and Sherr, 1988, and citations within). Caron et al. (1991) demonstrated that nanoplanktonic protists are the major consumers of prokaryotes and could remove 54 and 75% of the cyanobacteria and heterotrophic bacteria assemblage each day in field and laboratory experiments. Thus, macro- and microzooplankton grazers can potentially play an active role in transforming particulate carbon back to the dissolved phase via a variety of processes including sloppy feeding, egestion, and excretion (Table IV). The role of grazers in DOM production has been discussed previously (Ducklow and Carlson, 1992; Nagata and Kirchman, 1992; Nagata, 2000) and will be reviewed here. 1. Macrozooplankton Copping and Lorenzen (1980) found that when copepods were fed ^"^C-labeled diatoms, up to 27% of the radiocarbon ingested appeared as DOC. The four main processes by which macrozooplankton could release DOM are excretory release, egestion (release of unassimilated material), breakage of large prey during handling and feeding (sloppy feeding), and release from fecal pellets. Migrating zooplankton
Production and Removal Processes
107
in the Sargasso Sea excrete as much as 2-10% body C day~^and 1-6% of body N day"^ in the form of bulk DOC and DON, respectively (Table IV; Steinberg et ah, 2000; Steinberg et al, submitted). Nitrogen is a dominant excretory product for macrozooplankton. Inorganic nitrogen and urea are continually released by macrozooplankton (Bidigare, 1983) but DFAAs are released in pulses and make up approximately 10-21% of total N excreted (Bidigare, 1983, and citations within). Nagata (2000) speculated that the short burst in DFAA release might be more indicative of egestion than excretion but more data are needed to validate this hypothesis. Lampert (1978) showed that up to 17% of the POC removed by Daphnia pulex was lost as DOC due to cell damage during feeding. Fecal pellets may also be a source of DOM. Jumars et al. (1989) hypothesized that DOC would diffuse from fecal pellets within minutes of release. However, in experiments conducted with ^"^C-labeled fecal pellets Urban-Rich (1999) found that >50% of fresh fecal pellet carbon was released over the course of 48 h, much longer than the minutes hypothesized by Jumars et al. (1989). Lampitt et al. (1990) and Strom et al. (1997) suggested that for DOC release from fecal pellet to be significant the pellets needed to be broken upon reingestion by macrozooplankton. 2. Microzooplankton Microzooplankton grazing, consisting of herbivory and bacterivory, can release varying percentages of C, N, or P depending on prey type (Nagata, 2000). DOM released via herbivory supplies new DOM to the system, whereas bacterivory recycles DOM (Nagata and Kirchman 1992). Microzooplankton release DOM through egestion and possibly diffusion. As food vacuoles fuse with cytoplasmic walls, unassimilated DOM, undigested prey, colloidal material, and enzymes are evacuated (Nagata, 2000). This released DOM is composed of high- and low-molecularweight compounds (Taylor et al, 1985), DFAA, and dissolved combined amino acids (Nagata and Kirchman, 1991) as well as dissolved organic phosphorus (DOP; Caron et al, 1985; Andersen et al., 1986). The production of DOM by microzooplankton is positively correlated with the food concentration, and its release is highest during exponential growth (Nagata and Kirchman, 1992). Hagstrom et al. (1988) hypothesized that DOM release by microzooplankton was the dominant pathway of C flow to bacterioplankton. Nagata (2000) hypothesized that if or when phytoplankton growth is balanced by protozoan grazing, then 10-30% of particulate PP could be transformed to DOC with bacterivory being an additional source of DOM. 3. Biogeochemical Significance Zooplankton grazing has biogeochemical as well as ecological significance. For example, bacterivory increases nutrient regeneration efficiency within the
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112
Craig A. Carlson
microbial food web, increasing the flux of inorganic nutrient to phytoplankton and bacterioplankton and subsequently reducing the passive flux of organic particles from the surface to depth (Michaels and Silver, 1988; Nagata and Kirchman, 1992). Some species of macrozooplankton can contribute to vertical export of carbon by consuming organic particles in the surface at night and respiring it as CO2 below the mixed layer during the day (Longhurst and Harrison, 1989). Steinberg et al. (2000) demonstrated that migrating zooplankton also release large amounts of DOC. They calculated that active export of DOC by migrating zooplankton was comparable to 38 and 71% of particulate organic carbon (POC) flux at 150 and 300 m, respectively, in the northwestern Sargasso Sea. C, DOM
PRODUCTION VIA CELL LYSIS
1. Viral Lysis Virioplankton are ubiquitous in the marine environment (Wonmiack and Colwell, 2000). Typically ranging from 10^ to 10^^ viral particles L " \ they exceed bacterial abundance by 2- to 25-fold (Bergh et al, 1989; Proctor and Fuhrman, 1990; Cochlan et al, 1993). Viral infection can be responsible for 10-50% of bacterial mortality (Proctor and Fuhrman, 1990; Fuhrman, 1992; Steward £^<2/., 1996; Fuhrman, 1999). This process has also been linked to declines of PP and mortality of eukaryotic cells in the water column (Suttle et al, 1990; Bratbak et al, 1992; Gobler et al, 1997). Suttle (1994) estimated that approximately 3% of global PP is lost to viral lysis. Through lytic infection, viruses attached to the host cell produce numerous progeny viruses. The progeny then burst the host cell, releasing viruses, proteins, nucleic acids, monomers, oligomers, polymers, and cell fragments (Fuhrman, 1999). The majority of the DOM released from bacterial lysis is available to bacterioplankton over short time scales (Fuhrman, 1999). Generally, this recycling of DOM by bacteria represents a semiclosed trophic loop with the net effect of inorganic nutrients regeneration and increased DOC flux through bacterioplankton (Fuhrman, 1992; Middelboe et al, 1996). However, viral lysis of prokaryotic and eukaryotic organisms may yield DOM compounds that are resistant to rapid microbial degradation as well. For example, in cultures of the chrysophyte Aurecoccus anophagejferens incubated with active viruses, Gobler et al (1997) reported that 19% of the total cellular C content was released as DOC yet its availability to bacterioplankton was less than that of DOC released from uninfected cultures. While it is unknown whether this process is an important contributor to refractory DOM production it is interesting to note that the cell surface is a site where many refractory compounds are found. Work is needed to quantify this process in the field and to determine if the production of refractory DOM from viral lysis is a general or important phenomenon.
Production and Removal Processes
113
2. Bacterial Lysis Bacterially induced lysis of phytoplankton (Stewart and Brown, 1969; Imai et aly 1993) and other bacteria (Zusheng et al, 1998) is a phenomenon that exists in nature but has received little attention as a potential contributor to DOM production. Stewart and Brown (1969) first observed lysis of cultured algae and Gram-positive and Gram-negative bacteria by Cytophaga sp. isolated from sewage. Later, Imai et al (1993) found that gliding Cytophaga sp. isolated from a marine system had a rather large prey range and were able to lyse or kill at least 10 marine phytoplankton species in culture experiments. Because gliding bacteria need surfaces, Imai et al (1993) speculated that colonization of macroaggregates by gliding bacteria might regulate and or reduce primary productivity and biomass on macroaggregates through bacteria-induced lysis. Bacteria-induced lysis of other bacteria has been show to be associated with the production of external membrane vesicles (MVs) by Gram-negative bacterial. MVs contain high concentrations of peptidoglycan hydrolase, a bacterial cell wall degrading enzyme, used to lyse surrounding dissimilar bacteria (Kadurugamuwa and Beveridge, 1996; Zusheng et al, 1998). The purpose of lysing dissimilar cells would be to increase the flux of nutrients to MV donor cells in addition to reducing competition for existing nutrients. Bacteria-induced lysis can potentially influence the release of labile DOM compounds used to support further microbial growth as well as the release of recalcitrant compound that accumulate in seawater such as bacterial cell wall material (see section V.B.2). The phenomenon of bacterial induced lysis has been observed mostly in experimental cultures and its importance as an in situ DOM production mechanism remains unquantified.
D.
SOLUBILIZATION OF PARTICLES
Bacterial ectoenzymes are of fundamental importance for hydrolysis of polymeric DOM (Hoppe, 1991; Christian and Karl, 1995) and POM (Azam and Cho, 1987; Cho and Azam, 1988; Smith et al, 1992, 1995; Kamer and Hemdl, 1992). In a mesocosm study. Smith et al. (1995) observed a doubling in DOC concentrations immediately following a maximum in protease and chitobiase activity and proposed that a significant fraction of DOM production resulted from enzymatic hydrolysis of phytoplankton surface materials. Smith et al. (1992) demonstrated that bacteria attached to aggregates can express high levels of hydrolytic ectoenzymes, forming an "enzymatic reactor" (Fig. 2) which results in the release of DOM (Table V). They suggested that relative activities of proteases, carbohydrases, and phosphatases suggest the preferential solubilization of DON and DOR Additional particles are subjected to the enzymatic hydrolysis as they are accreted to the aggregate as it descends through the water column. This activity results
Craig A. Carlson
114
Colloids + DOM
DOM
Colloids
POM
Sinking Flux Figure 2 Schematic representation of a sinking organic aggregate functioning as an "enzymatic reactor" adapted from Smith et al (1992). Attached bacteria on the aggregates express high levels of hydrolytic ectoenzymes that mediate the production of DOM and colloidal material from POM.
in the retention of nitrogen and phosphorus in the euphotic zone and is consistent with the observed increase in C:N and C:P of sedimenting material with depth. Smith et al. (1992) calculated integrated release of dissolved combined amino acids (DCAAs) to be 0.5-23.3 mg N m~^ day~^ in the mixed layer of the Southern California Bight. Solubilization of POM to DCAA was uncoupled from bacterial uptake, with 50-98% of the DCAA released escaping rapid utilization by attached bacteria. As such, hydrolysis of structural suprapolymers may produce slowly degraded DOM. Hydrolytic ectoenzyme activity within fecal pellets
Table V Percent of Organic Matter Released as DOM Due to Solubilization of Particles Organic particle
Related units
Reference
DOM
% Released
Larvacean house
DON
8-28
Of aggregate N released as DCAA day-^
Smith ef a/., 1992
Diatom floe
DON
16
Of aggregate N released as DCAA day~^
Srmih etal, 1992
Copepod fecal pellet
DOC
>50
Of fecal pellet carbon released as DO^^C w/in 48 hours
Urban-Rich, 1999
Production and Removal Processes
115
can also play a role in transforming POC to DOC (Table V; Jumars et al, 1989; Urban-Rich, 1999). It is important to note that to date almost all of the data regarding hydrolytic enzymes are derived using methods that measure only exohydrolases. To solubilize particles endohydrolases are also necessary; thus, significant gaps in our understanding of particle hydrolysis in marine systems remain. E. BACTERIAL DOM: ORIGINATION AND TRANSFORMATION OF D O M Bacterioplankton abundance ranges from 10^ to 10^ per liter in most regions of the open ocean, representing the largest living surface area in the world's oceans (Williams, 1981). Heterotrophic bacterioplankton are the dominant consumers of DOM in the ocean, converting it to biomass or inorganic nutrients (Azam and Hodson, 1977; Azam et al, 1983). Photoautotrophic bacteria (cyanobacteria) are major primary producers in some oligotrophic systems (Chisholm et al, 1988; Campbell et al, 1994; Liu et al, 1997). Recent studies have indicated that heterotrophic bacterioplankton can also be a source of organic matter. For example, DOM compounds that have chemical characteristics of bacterial origin have been shown to be distributed ubiquitously in several oceanic basins (Tanoue etal, 1995; McCarthy et al, 1998; see section V.B.2). Bacterioplankton also directly release DOM in the form of hydrolytic enzymes. However, the secondary effect of particle solubilization by attached bacteria is a more important contributor to bacterial DOM production than direct release of DOM (i.e., enzymes; Smith etal, 1992). In addition, compounds of bacterial origin may be more refractory to other bacteria than those of eukaryotic origin Many marine bacteria produce copious amounts of HMW mucous exopolymers (Decho, 1990). These secretions help to maintain a stable microenvironment, house extracellular enzymes, as well as sequester and concentrate nutrients. The release of capsular material is an additional source of DOM (Stoderegger and Hemdl, 1998). Stoderegger and Hemdl (1998) reported a bacterial capsular material release rate of 0.36 fmol C cell~May~^ (Table VI); however, not all bacteria produce capsular material or exopolymers. Bacterioplankton also appear to transform LMW to HMW DOM that is resistant to further bacterial remineralization on the time scale of months (Brophy and Carlson, 1989; Tranvik, 1993; Heissenberger et al, 1996; Ogawa et al, 2001); however, the mechanisms responsible for this "transformation" are poorly understood. The production of recalcitrant DOM via microbial processes, be it origination (i.e., cell wall material) or transformation (converting LMW to HMW compounds), has important biogeochemical implications with regard to organic carbon export and storage in the ocean's interior (see Hansell, Chapter 15).
Craig A. Carlson
116
Table VI Examples of Percent DOC Released from Bacterioplankton Bacterial DOC production process
% Release
Related units
Reference
Production and release of bacterial capsular material
8.6
Of [^'*C] glucose up take was released as capsular material
Stoderegger and Hemdl, 1998
Bacterial production of HMWDOM
6
Of initial [^'^C] leucine concentration was released as HMW (>50 kDa) DOM
Heissenberger etal, 1996
Bacterial transformation ofLMWDOM
5
Of initial \^^C] glucose concentration was released as biologically resistant DOM
Brophy and Carlson, 1989
Bacterial transformation OfLMWDOM
1.4
Of initial [^^C] leucine concentration was released as biologically resistant DOM
Brophy and Carlson, 1989
Bacterial transformation ofLMWDOM
3
Of initial [^^C] glucose concentration was transformed into humic material
Tranvik, 1993
Bacterial transformation of glucose
5
Of amended glucose was converted to DOC that persisted for >1 year
Ogawa^fa/., 2001
Bacterial transformation of glutamate
7
Of glutamate amended to a bacterial culture was converted to DOC that persisted for > 1 year
Ogawa^ffl/., 2001
III. DOM REMOVAL PROCESSES Despite a range of 30 to 8543 mg C m~^ day" ^ (285-fold range in variability) for depth integrated PP in the world ocean (Behrenfeld and Falkowski, 1997), DOM concentrations are maintained in a remarkably narrow range of 40 to 80 /xM C (twofold range in variability) in the surface 1000 m of the open ocean (see Hansell, Chapter 15). Given that DOM production can be a significant fraction of the total PP, this striking offset between the range in PP rates and DOC concentrations indicates that several biotic and abiotic DOM removal processes are at work (Fig. 1). A. BIOTIC CONSUMPTION OF DOM 1. Prokaryotes Free-living heterotrophic bacterioplankton are recognized as the dominant consumers of DOM in the ocean (Azam and Hodson, 1977). Bacterioplankton represent the largest living surface area in the sea and have the ability to directly
Production and Removal Processes
117
transport LMW compounds (500-1000 Da) through their cell membranes via permeases. Some biotic remineralization processes require the necessary enzymes for oxidation to proceed. HMW compounds are also utilized rapidly by bacterioplankton (Amon and Benner, 1994, 1996) after they are hydrolyzed to LMW compounds via hydrolytic enzymes (Hoppe, 1991; Smith et al, 1992; Christian and Karl, 1995). Their ecological role within the microbial loop is to facilitate the transformation of DOM to POM or to remineralize DOM back to its inorganic constituents (Ducklow et al, 1986; Goldman and Dennett, 2000). Bacterial production (BP) is a measure of DOM flux that becomes bacterial biomass, and thus represents the net flux of DOM to bacterioplankton (Ducklow, 2000). Bacterioplankton play an important biogeochemical role in nutrient cycling and in the diagenetic alteration of organic matter (Cowie and Hedges, 1994; Skoog and Benner, 1997). Ultimately, included in what microbial ecologists and biogeochemists wish to know about bacterial processes is how much of the organic matter flows through bacterioplankton. In a cross-system analysis covering a range of geographical locations, extending over seasonal to annual time scales. Cole et al. (1988) concluded that BP averaged 31 % of local PP (note that this is larger than the estimate of 13 % for PER, indicating the importance of other DOC release mechanisms). In evaluating data from several oceanic sites including the oligotrophic Atlantic and Pacific, the Arabian Sea, the subpolar Atlantic, the HNLC region of the Equatorial Pacific and the continental shelf system of the Ross Sea, Ducklow (1999) found that BP ranged from 10 to 20% of local PP (Fig. 3). a. Bacterial Growth Efficiency While the magnitude of BP is usually modest compared to PP one must consider the efficiency at which bacterioplankton convert DOC into bacterial biomass (the bacterial growth efficiency, BGE) to better assess the gross flux of DOC through bacterioplankton. Measuring BGE in natural systems continues to challenge microbial ecologists due to the shortcomings of current experimental designs. In a comprehensive review of BGE del Giorgio and Cole (1998) described the advantages, disadvantages, and associated problems of short- and long-term incubations in determining BGE. They suggested that short-term incubations should be more ecologically relevant; however, it is often not possible to measure changes in natural substrates on time scales of hours. The use of radiolabeled substrates (Williams, 1970, 1981) allows for the detection of substrate changes with high sensitivity and minimizes incubation time, but tends to overestimate BGE due to the use of model compounds. Alternatively, seawater culture techniques that separate bacterioplankton from larger components of the plankton community allow microbial ecologists to assess bacterial dynamics and resolve concentration changes in natural substrates or byproducts (Bj0msen, 1986; Coffin et al, 1993; Kroer, 1993; Zweifel et al, 1993; Biddanda et al, 1994; Hansell et al, 1995; Carlson and
Craig A. Carlson
118
Figure 3 Ratio of bacterial production (BP) to primary production (PP) for various oceanic systems. All sample sites are Joint Global Ocean Rux Study (JGOFS) study sites. Figure adapted with permission from Ducklow (1999); see citation for details.
Ducklow, 1996; Kahler et ai, 1997; Carlson et ai, 1999). These approaches require longer incubations, which can introduce bottle effects such as passage of grazers, wall growth, and community structure shifts. In addition, removal or reduction in grazing activity can also affect bacterial physiology because nutrients are not recycled. For example, Christian (1995) observed shifts in the ratio of enzyme activity in a l-ixm filtrate and suggested that it was related to the absence of N and P recycling by micrograzers. As a result, seawater cultures may indicate bacterial dynamics not entirely representative of in situ dynamics and may lead to a lower BGE when long incubations are conducted (del Giorgio and Cole, 1998). However, del Giorgio and Cole (1998) did notfinda systematic effect of incubation duration on BGE estimates. BGE can be estimated empirically by growing natural assemblages of bacterioplankton on naturally occurring DOM in a closed system and directly measuring changes in bacterial production and DOC consumption or bacterial respiration (BR). BGE can be expressed as BGE = BP/(BP -h BR) ^ BP/ADOC,
[1]
where ADOC is the measured change in DOC concentration during an incubation. BGE varies considerably depending on the system (Table VII); however, the BGE for oceanic systems is generally low (<20%; Carlson and Ducklow 1996; del Giorgio and Cole, 2000, and citations within).
119
Production and Removal Processes Table VII Estimates of Bacterial Growth Efficiency (%) Selected from the Literature, Determined for Natural Assemblages of Marine Bacterioplankton Grown on Naturally Occurring DOM Location
Range
Reference
Method
Mean
AO2 and [^H] TdR
6
Gnmthetal,
AO2 and [^H] TdR
2
Griffith e^fl/., 1990
ADOC and ABacterial
5
2-8
Kirchman er a/., 1991
Sargasso Sea (31°N,64°W)
ADOC and ABacterial
14
7-19
Carlson and Ducklow, 1996
Sargasso Sea (31°N,64°W) Santa Rosa Sound, FL
ATCOz"^ and [^H] TdR AO2 and ABacterial
Santa Rosa Sound, FL Santa Rosa Sound, FL
Atlantic Georgia, USA; nearshore Georgia, USA; shelf North Atlantic (47°N, 18°W)
Baltic Sea Baltic Sea (63°30^N, 19°48'E) Gulf of Riga
Danish Fjord Roskilde Fjord Gulf of Mexico Gulf of Mexico; slope Gulf of Mexico Gulf of Mexico Louisiana shelf (HMW DOM) Louisiana shelf (LMWDOM) Louisiana shelf Mississippi River plume Mississippi River plume
poe
1990
3.8-8.9
Hansen e^fl/., 1995
16
0.4-35
CofSm etal, 1993
ADOC and APOC
30
26-33
Kroer, 1993
ADOC and APOC
22
ADOC and ABacterial POC« ADOC and ABacterial POC^
27
ADOC and APOC
20
11-27
Bj0msen, 1986
AO2 and [^H] Leu
23
19-26
Biddanda^ra/., 1994
AO2 and [^H] Leu ADOC and APOC AO2 and [^H] Leu
8.5 61 25
1-28 61
AO2 and [^H] Leu
42
AO2 and [^H] Leu AO2 and [^H] TdR
45 19
38-55 10-22
AO2 and [^H] Leu
29
9^2
Vom&xoy et al, 1995 Kroer, 1993 Amon and Benner, 1994 Amon and Benner, 1994 Biddandaera/., 1994 Chin-Leo and Benner, 1992 Chin-Leo and Benner, 1992
poe
6.6
11.4
J0rgensen ^r a/., 1994
11-54
6-27
Zweifeleffl/., 1993
Zweifel, 1999
{Continues)
120
Craig A. Carlson Table VII (Continued) Location
Pacific Ocean 34°50'N; 123° 00'W Southern Ocean Antarctic Polar Front Ross Sea Scotia Sea Weddell Sea
Mean
Range
Reference
4
3-5
Cherrier ^r fl/., 1996
ADOC and APOC
28
26-30
KahltretaL, 1997
ADOC, ATCO2/ and APOC ATCO2' and [^H] TdR ATC02^ and [^H] TdR
17
11-43
Carlson era/., 1999
Method ADOC and ABacterial POC^
38 40
Bj0msen and Kuparinen, 1991 Bj0msen and Kuparinen, 1991
Note. Table adapted from Carlson and E>ucklow (1996), Carlson et al. (2000), and del Giorgio and Cole (2000). Methodology for measuring substrate utilization included direct measurements of change in DOC (ADOC) or respiration measurements of O2 (AO2) or total CO2 (ATCO2). ADOC was measured by high temperature combustion. AO2 was measured by high precision Winkler titration. Bacterial production was measured by change in bacterial POC, [^H] thymidine incorporation ([^H] TdR) or [^H] leucine incorporation ([^H] Leu). ^Bacterial POC was estimated from cell abundance and cell volumes. ^Bacterial POC was estimated from cell abundance using carbon conversion factor of 20 fg Cceir^ ^ ATCO2 was measured by liberation of ^^C02. ^ ATCO2 was measured by high precision coulometry.
b. Bacterial Carbon Demand The amount of carbon needed to support BP is called bacterial carbon demand (BCD). BCD represents the gross flux of carbon to bacterioplankton and is estimated with the following formula: BCD = BP/BGE.
[2]
Given this relationship, low BGEs have vast implications for the biogeochemistry of aquatic systems. For example, a lower BGE requires a larger flux of carbon (BCD) to support an observed BP. The lower BGE determined for natural assemblages of bacterioplankton grown on natural substrates can result in calculated BCD exceeding phytoplankton production (Hansell et al, 1995; del Giorgio and Cole, 1998). Thus, BCD can represent a significant fraction of local PP even if BPiPP is low. For example, with a BGE of 14% for the northwestern Sargasso Sea (Carlson and Ducklow, 1996) the euphotic zone integrated BCD averages 67% of the integrated PP (Fig. 4). Ducklow (2000) suggested that BCD approximates the
Production and Removal Processes
111
Figure 4 Ratio of euphotic zone integrated bacterial carbon demand to primary productivity (BCDiPP) in the northwestern Sargasso Sea (31° 50' N, 64° 10' W) from 1990 to 1999. Bacterial carbon demand was estimated by dividing integrated bacterial production estimates by bacterial growth efficiency of 14% (Carlson and Ducklow, 1996). Bacterial C production was estimated with the [^H] thymidine ([^H] TdR) method and converted to carbon units using a TdR conversion factor of 1.63 X 10^^ cells mol-i TdR (Carlson et al, 1996) and a carbon conversion factor of 10 fg C cell (Caron et al, 1995). Primary production was estimated via ^^C dawn-to-dusk incubations and represents the fraction captured on a GF/F filter. Dashed line represents mean BCD:PP value of 0.67 for the data set. Open symbols represent two time points where PP was very low relative to BR Data are from the Bermuda Atlantic Time-Series Study (BATS).
magnitude of local net particulate PP estimated from^^C measurements. However, one must take caution when interpreting BP or BCD data. Due to limited analytical capabilities, there are no direct means of measuring the flux of complex natural DOC compounds to bacterial consumers in situ. BP and BGE estimates are used to derive the flux of carbon through bacterioplankton. Because BP is often estimated by measuring related processes (i.e., incorporation of precursors for nucleic acids or other macromolecules; thymidine or leucine), conversion factors are required to convert measured parameters into carbon units. Considerable variability of both BGE (Jahnke and Craven, 1995; Carlson and Ducklow, 1996; del Giorgio et al, 1997) and the various conversion factors (see Ducklow and Carlson, 1992) are reported in the literature, making BP and hence BCD relatively unconstrained (Anderson and Ducklow, 2001), resulting in estimates of BCD greater than PP, even in oligotrophic regions. Alternatively, BR may is a better measurement to use when calculating carbon flux through bacterioplankton because BR cannot exceed the supply of organic C (Ducklow et al, 2001; Anderson and Ducklow, 2001). However, coherent measurements of both PP and BR are limited, especially in oceanic waters. This section has focused on the role of bacterioplankton in the prokaryotic utilization of DOM. Archaea, too, are likely to be significant consumers of a wide
122
Craig A. Carlson
spectrum of DOM compounds. Traditionally viewed as extremophiles (living in extreme environmental conditions such as high salinity or temperatures) Archaea are beginning to be recognized as potentially important contributors to microbial processes in the oceanic water column (Olsen, 1994; DeLong et ai, 1994; Stein and Simon, 1996). Using molecular probes, Kamer et al. (2001) demonstrated that the contribution of Archaea cell abundance in the North Pacific subtropical gyre was significant between 100 and 1000 m and greater than or equal to bacterial abundance below 1000 m. They suggested that the rRNA hybridization techniques, used to identify Archaea, also identified actively metabolizing cells.If true, this would suggest the possibility that Archaea actively oxidize recalcitrant organic matter found at depth (see below for details on DOM lability). Ouvemey and Fuhrmann (2000) showed that Archaea can contribute to up to 43% of total cell counts in some ocean areas, with 60% of the Archaea comrnunity demonstrating the ability to take up amino acids at in situ concentrations. As Archaea research continues it is likely that we will find Archaea communities to be important contributors to the cycling of C in the world's oceans. 2. Eukaryotes In addition to bacterioplankton, several other marine organisms have the ability to directly take up labile DOM compounds to supplement metabolic needs. "Colloidal DOM," carbohydrates and proteins with molecular weights from 55 to 2000 kDa, can be actively taken up by heterotrophic flagellates (Sherr and Sherr, 1988; Tranvik et al, 1993; Lessard et al, 1995). Marine invertebrates can effectively utilize DOM compounds, such as monosaccharides and DFAAs, as a nutritional source (Manahan and Richardson, 1983; Marchant and Scott, 1993). Based on isotopic composition of several eel leptocephalii, Otake et al. (1993) concluded that DOM could serve as a food source. Photoheterotrophy, the ability of microalgae to take up organic material via phagotrophy or osmotrophy to supplement their autotrophic metabolism, has been demonstrated for a variety of phytoplankton (Rivkin and Putt, 1987; Caron, 2000, and citations within) under light or nutrient limiting conditions. While the process of DOM uptake by marine eukaryotes exists, the magnitude of these removal processes is likely to be small relative to heterotrophic prokaryotic uptake. B. ABIOTIC REMOVAL PROCESSES
1. Phototransformation UV excitation from sunlight impacts DOM removal both directly and indirectly. Direct photochemical mineralization of DOM to CO2 and to a lesser extent CO has been observed in marine systems (Mopper et al, 1991; Moran and Zepp, 1997).
Production and Removal Processes
123
Several studies have demonstrated that photochemical degradation of HMW DOM can lead to the formation of biologically available LMW compounds (Kieber et al, 1989; Mopper et al, 1991; Moran and Zepp, 1997), which facilitates the uptake and remineralization of DOM that would otherwise have extremely long turnover times. Photochemical processes also release labile N and P compounds such as anmionium, amino acids, and phosphate (Moran and Zepp, 2000). In a review of the role of photoreactions Moran and Zepp (1997) estimated the annual loss of DOC via photochemical degradation to be 12-16 x 10^^ g C year"^ or 2-3% of the oceanic DOC pool. This removal rate would suggest extremely high net DOC production rates. However, global estimates of net DOC production are only on the order of 1.2 x 10^^ g C year"^ (Hansell and Carlson 1998b). These data indicate that further research is needed to better constrain photochemical degradation of DOC and net DOC production. See Mopper and Keiber (Chapter 9) for more about photochemical reactions. 2. Sorption of DOM onto Particles Sorption of DOM onto surfaces such as sinking particles has been proposed as an abiotic removal mechanism (Keil and Kirchman, 1994; Druffel etal, 1996; Nagata and Kirchman, 1996; Druffel et al, 1998). Druffel et al (1996) observed a A^^^ gradient in suspended and sinking POC (POCsusp and POCsink. respectively) in the deep northeast Pacific, indicating that the POC at depth was significantly older (A ^"^C values more negative) than POC in the surface waters. Because the source of deep POC is ultimately from the surface, and transit through the water column is on relatively short time scales, Druffel et al (1996) hypothesized that abiotic sorption or biological incorporation of "old" DOC onto POC was a plausible mechanism to explain the older (lower A^^C values) POCsusp observed at depth. Hansell and Carlson (1998a) hypothesized that a portion of the DOC gradient observed in the deep ocean was linked to POC flux. Although, a DOC "stripping" mechanism is a plausible abiotic DOC removal process, the magnitude of its importance in the oceanic carbon cycle is unknown due to insufficient data (Druffel et al, 1998).
IV. DOM LABILITY It is important to avoid the microbiological heresy that asserts that bacteria can defy the laws of chemistry and break down everything! The decomposition of some large molecules requires considerable energy, and the energy balance must in the end be to the organisms advantage. (Floodgate, 1995)
The bulk DOM pool represents a continuum of biological lability, from refractory material turning over on time scales of centuries to millennia (Williams and Druffel, 1987; Bauer et al, 1992) to very labile material turning over on time
Craig A. Carlson
124
scales of minutes to days (Fuhrman, 1986; Keil and Kirchman, 1991; Carlson and Ducklow, 1996; Cherrier et al, 1996; Rich et ah, 1997; Carlson et al, 1999). Ogura (1972) used remineralization experiments to identify a third type of DOC, one that was utilizable by microbes but turned over on time scales of months to years. More recent field studies have shown that a portion of the DOC pool found in excess of deep-water concentrations is resistant to rapid microbial degradation and is termed the "semilabile" DOC pool (see Fig. 5; Kirchman et al, 1993; Carlson and Ducklow, 1995). A conceptual model (Fig. 5 and Table VIII) describing partitioning of the bulk DOM pool into fractions of varying lability allows us to use the vertical structure of the DOM concentrations and its dynamics to gain insight
wir-
500-
: P< • -A
r
•
1000-
'
1500-
ex 1) Q
2000-
2500-
<— Refractory
• : . ' . ; ' \
3000-
1
: K
\
' \
35004000- ' ' ' ' 1 • 0 10
Semi-labi
.;;\. (\
A y
""Labile
• • • 1 • '
20
• • 1 • ' i 1 1 1 it!) • ' 1 ' ' ' ' 1 ' ' ' ' 1 • '
30 40 50 DOC (|iiM C)
60
70
Figure 5 Conceptual cartoon of the various pools of refractory, semilabile, and labile DOC in the open ocean. This figure is based on the mean profile for all DOC data collected at the Bermuda Atlantic Time-series Study (BATS) site in the Northwestern Sargasso Sea. The magnitude and distribution of the various pools of lability will vary depending on the location of the study site and the degree of thermal stratification of the water colunm (see Hansell, Chapter 15). The refractory pool is divided into two broad pools based on the deep ocean gradient observed by Hansell and Carlson (1998a). They observed the lowest concentration of DOC (34 //.M C) in the north Pacific and used this concentration to represent refractory DOC which turns over on time scales of greater than ocean mixing (A, white box). The deep DOC concentrations in excess of the 34 /xM C represents the fraction of the biologically refractory pool that turns over on time scales of ocean mixing (i.e., centuries; B, light gray box).
125
Production and Removal Processes Table VIII
Characteristics of the Three Broad Fractions of DOC Divided by Biological Lability Pool of Lability Biologically labile DOC
Biologically semilabile DOC
Description
Reference
Turnover on time scales of minutes to days
Fuhrman and Ferguson, 1986 Keil and Kirchman, 1999
Composed of HMW and LMW compounds
B&xm&vetal, 1992 Amon and Benner, 1996
Most labile components such as monomers are present in nM concentrations in surface waters
Fuhrman and Ferguson, 1986 Richeffl/., 1997 Keil and Kirchman, 1999 Skoog etal, 1999
Rapid flux of labile compounds supports large portion of heterotrophic bacterial growth
Ducklow and Carlson, 1992 mchetal, 1996 Rich etal, 1997 ^koog etal, 1999
Absence of labile DOC can limit rapid heterotrophic bacterial growth (C limitation)
Kirchman ^/«/., 1990 Kirchman, 1990 Carlson and Ducklow, 1996 ChQuitvetal, 1996
Turnover on time scales of months to years; resists rapid microbial degradation
Ogura, 1972 Kirchman era/., 1993 Carlson and Ducklow, 1995 Cherrier er fl/., 1996 Carlson et al, submitted
Potentially important as an export term because it resists rapid microbial degradation
Copin-Montegut and Avril, 1993 Carlson effl/., 1994 Hansen and Carlson, 2001 Hansen effl/., 2001
Percentage contribution to bulk DOC pool varies spatially, with larger contribution in permanently stratified systems Composed of HMW and LMW compounds
Carlson and Ducklow, 1995 Hansen and Waterhouse, 1997 Carlson et al, 2000 Haiisell, chapter 15
Dominated by carbohydrates
Benner effl/., 1992 Pakulski and Benner, 1994
Composed partially of biosynthetically produced heteropolysaccharides
Biersmith and Benner, 1998 Aluwihare and Repeta, 1999
Contribution of carbohydrates decreases with depth, indicating diagenetically altered material with age
Cowie and Hedges, 1994 Skoog and Benner, 1997
Benner era/., 1992 Amon and Benner, 1996
{Continues)
Craig A. Carlson
126 Table VIII (Continued) Pool of Lability
Biologically refractory DOC
Description
Reference
C:N ratio 6 to >20
WilUams, 1995 Daley era/., 1999 Ogawaera/., 1999 Carlsonef al, 2000 Hansen and Carlson, 2001
Turnover on time scales of centuries to millennia; representative of deep water concentrations
WiUiams and Druffel, 1987 Bauer era/., 1992
Dominated by LMW compounds
Bennerera/., 1992 Amon and Benner, 1996
Resistant to microbial remineralization
Barber, 1968 Ogura, 1972
Most diagenetically altered; low carbohydrate and aldose yield
Cowie and Hedges, 1994 Skoog and Benner, 1997
C:N (molar ratio) 14-20
Ogawaera/., 1999 Carlson et ai, 2000 Hansen and Carlson, 2001
Mean age 4000 years
Bauer era/., 1992
Photochemically active material that can be transformed to biologically labile material
Kieber era/., 1989 Mopper era/., 1991 Moran and Zepp, 1997
Observed gradient in deep ocean DOC between North Atlantic and North Pacific (i.e. 14 fxM C)
Hansen and Carlson, 1998a
Most refractory portion of DOC is composed of approximately 34/LtMC
Hansen and Carlson, 1998a
Portion of deep DOC that turns over on time scale of ocean mixing; varies with location
Hansen and Carlson, 1998a
into the lability of DOM found in the ocean. See Benner (Chapter 3) for extensive review of DOM composition and reactivity.
A. BIOLOGICALLY REFRACTORY DOM The refractory pool is the largest fraction of the bulk DOC. It is dominated by diagenetically altered LMW DOM (Benner et ai, 1992; Amon and Benner, 1996; Skoog and Benner, 1997). This finding would appear contradictory because
Production and Removal Processes
127
bacterioplankton can take up only LMW compounds directly; however, not all LMW compounds are bioavailable. Amon and Benner (1996) proposed a sizereactivity continuum model which suggests that as organic matter is decomposed it become less bioreactive and smaller in size; thus bioreactivity of organic matter decreases as follows: POM - ^ HMW DOM —> LMW DOM, where each size fraction consists of a continuum of composition, reactivities, and diagenetic states (Amon and Benner, 1996). The refractory pool is best represented by the deep ocean DOC stocks (>1000 m), with an apparent mean age of 4000 to 6000 years old in the North Atlantic and the North Central Pacific oceans, respectively (Williams and Druffel, 1987; Bauer et al, 1992). Because the mean age of the deep DOC is much greater than the time scale of thermohaline circulation refractory DOC is reintroduced to the surface waters as it follows the path of ocean circulation. Based on mass balance calculations and natural A^^C estimates, Druffel et al. (1992) suggested that the most refractory component of the bulk DOM pool was uniformly distributed throughout the water column and represents approximately 70% of surface DOC in thermally stratified systems (Carlson and Ducklow, 1995, 1996; Cherrier etal, 1996). In polar systems, the surface contribution of refractory DOM can be even higher due to the absence or reduced concentration of "semilabile" DOM (see below and Hansell, Chapter 15). Although this material is biologically resistant there must be a removal mechanism or DOC would continually accumulate and the apparent age would be much older. While deep DOC is biologically refractory (Barber, 1968), the deep ocean DOC gradient of 14 fjM from the North Atlantic to the North Pacific (Hansell and Carlson, 1998a) indicates that a portion of the deep ocean DOC is removed on time scales of ocean mixing. Rate constants required to account for continuous removal are on the order of 10~^ to 10""* year~\ too slow for continuous microbial decomposition to be likely (Anderson and Wilhams, 1999; WilHams, 2000). Anderson and Williams (1999) proposed a coupled biological-photochemical model in which deep DOC is biologically refractory but photochemically reactive. Once exposed to surface UV irradiation, it is removed via photooxidation or broken into labile compounds and removed via microbial remineralization (Kieber etal, 1989; Mopper et al, 1991). This photochemical mechanism most likely accounts for a portion of refractory DOM loss (Moran and Zepp, 1997); however, as Williams (2000) points out, this process is restricted to the surface ocean and cannot account for the deep DOC gradient observed by Hansell and Carlson (1998a). Williams (2000) proposed a third mode of deep DOC decomposition, in which attached bacteria associated with sinking particles generate short bursts of microbially mediated DOM removal. Such remineralization of refractory DOM by attached bacteria, together with sorption of HMW DOM to sinking particles (Druffel et al, 1996,
128
Craig A. Carlson
1998), may help explain removal of deep refractory DOM as it moves through ocean basins via thermohaline circulation. However, Turley (1993) found that by increasing pressure to 200 atm, incorporation of [^H]leucine and [^H]thymidine (indices of bacterial productivity) was reduced by 94 and 70%, respectively, relative to incorporation rates measured at 1 atm. Based on this experiment, Turley concluded that it was unlikely that bacteria, originating from the surface waters and attached to rapidly sinking particles, play a role in particle remineralization below 1000-2000 m. Thus, further research is needed to fully elucidate refractory DOM removal mechanisms and associated rates.
B. BIOLOGICALLY LABILE DOM The most biologically reactive organic components in seawater include dissolved free compounds such as neutral monosaccharides and DFAAs. Rapid turnover (minutes to hours) maintains these compounds at nanomolar concentrations in the open ocean (Fuhrman and Ferguson, 1986; Rich et al, 1997; Keil and Kirchman, 1999; Skoog et al., 1999). Despite low concentrations, rapid turnover rates suggest that the fluxes of these compounds can be high (Fuhrman and Ferguson, 1986; Rich et ai, 1996; Keil and Kirchman, 1999; Kirchman et al, in press). For example, DFAA uptake has been shown to support 4-41% of bacterial N demand in open ocean environments and up to 100% in coastal studies (Kirchman, 2000). Glucose uptake represented 27-35% of net bacterial production in the equatorial Pacific (Rich et al, 1996) and up to 100% in the Arctic (Rich et al, 1997). In the Gulf of Mexico and the Antarctic, glucose uptake supports < 10% of bacterial production (Skoog et al, 1999; Kirchman et al, in press). Less than 5% of BCD in the Sargasso Sea (Keil and Kirchman, 1999) is supported by glucose. These latter studies indicate that compounds of slower reactivity, such as proteins and other carbohydrates (i.e., polysaccharides), support a significant portion of heterotrophic BCD with turnover on time scales of days. Seawater culture experiments, combined with direct measurements of DOM consumption and bacterial production, are often used to assess the availability of naturally occurring substrates to bacterioplankton (Fig 6; Barber, 1968; Ogura, 1972;Kroer, 1993; Carlson and Ducklow, 1996;Cherrier^^fl/., 1996;Kahler^ra/., 1997; Carlson et al, 1999). The proportion of labile DOM varies spatially with an apparent gradient of decreasing concentrations of labile DOM from coastal to oceanic systems (S0ndergaard and Middelboe, 1995). In some oceanic systems DOM production and consumption processes are so tightly coupled that there is no measurable surplus of labile DOM (on the /xM C scale) available to surface water microbes on time scales of days (Fig. 6b; Carlson and Ducklow, 1996; Cherrier et al, 1996; Carlson et al, in press).
Production and Removal Processes
129
Figure 6 Bacterial carbon production (closed circles) and DOC utilization (open circles) monitored in two seawater culture experiments conducted in the northwestern Sargasso Sea. (a) At the time this experiment was conducted, in situ DOC production and consumption processes were uncoupled, resulting in accumulation of labile DOC above the average mixed layer DOC concentration of 69 /xM C. In the presence of surplus labile DOC, bacterioplankton were able to grow rapidly and consume DOC at an efficiency of approximately 14%. (b) At the time this experiment was conducted, in situ production and consumption processes were tightly coupled preventing accumulation of labile DOC (on the /xM scale). The limited availability of labile DOC at the time water was collected for this experiment prevented rapid microbial growth and DOC degradation. Figure adapted with permission from Carlson and Ducklow (1996).
C
BIOLOGICALLY SEMILABILE D O M
DOM stocks in excess of the deep refractory pool are composed of "labile" and "semilabile" DOM. Because labile DOM concentrations represent a very small fraction of bulk DOM in the open oceans (0-6%), the vertical gradient of the bulk DOM observed in thermally stratified systems is mostly comprised of semilabile DOM (Fig. 5; Carlson and Ducklow, 1995; Cherrier et al, 1996). The semilabile fraction of DOM is biologically reactive only over months to years, allowing it to accumulate in the surface waters. It is this DOM fraction that can be an important export term provided it escapes microbial degradation in the surface waters long enough to be entrained to depth via convective mixing (Copin-Montegut and Avril, 1993; Carlson et al, 1994; Hansell and Carlson, 2001) or advection along isopycnal surfaces (Hansell etal, 2001). For example, in the Sargasso Sea overturn of the water column serves to export DOC that escapes rapid microbial degradation to depths greater than 100 m, with the amount exported dependent on the depth of mixing. Time-series measurements of DOC conducted from 1992-1998 indicated that DOC export ranged from 0.4 to 1.4 mol C m"^ year~^ (Carlson et al, 1994; Hansell and Carlson, 2001). In some years the contribution of organic matter exported out of the euphotic zone in the dissolved phase was greater than that export as POC, as measured by sediment traps (Carlson etal, 1994).
130
Craig A. Carlson
Semilabile DOM is composed of both LMW and HMW compounds of varying lability. HMW compounds can be biologically reactive (Amon and Benner, 1994, 1996), but must be hydrolyzed to monomers via extracellular enzymes prior to bacterial uptake. The time required for microbes to synthesize and release these enzymes decouples DOM production and bacterial remineralization processes (Billen and Fontigny, 1987), resulting in transient DOM accumulation. Dissolved carbohydrates totaling as much as 40% of the surface DOC stocks comprise the largest identifiable fraction of the bulk DOC pool (Bumey et al, 1979; Benner et ai, 1992; Pakulski and Benner, 1994; B0rsheim et al, 1999). Nitrogenous compounds such as amino acids account for a relatively minor component of DOM in the ocean (McCarthy et ai, 1996). The major classes of carbohydrates present in seawater include amino sugars, uronic acids, and neutral sugars (Borch and Kirchman, 1997; Skoog and Benner, 1997; Kirchman et al, 2001, and citations within). Polysaccharides comprise a major fraction of reactive HMW DOM in oceanic surface waters (Benner et ai, 1992; McCarthy et al, 1996) and decrease in concentration with depth.
D. CONTINUUM OF BIOLOGICAL LABILITY In thermally stratified oceanic sites there exists a broad continuum of lability for the semilabile DOM pool, with some fraction of semilabile DOC turning over on seasonal time scales and other fractions persisting for years (Anderson and Williams, 1999; Carlson etal, 2000). Time-series measurements of DOM dynamics can provide insight into turnover rates of various DOM pools. Turnover rates of semilabile DOC for specific depth horizons can be defined as the difference between the maximum and minimum DOM stocks within that depth horizon over an annual cycle. For example, in the Sargasso Sea approximately 4.8 mol m~^ (30%) of bulk DOC measured in the surface 250 m (maximum mixed layer depth for time period) is composed of semilabile DOC yet a maximum of only ^ 1 mol m~^ (20% of semilabile DOC) turns over on a time scale of 1 year or less (Fig. 7; Carlson et al, 1994, 2000; Hansell and Carlson, 2001). The percentage contribution of reactive compounds such as carbohydrates decreases with depth (Benner et al, 1992; Pakulski and Benner, 1994; Skoog and Benner, 1997), indicating that deeper semilabile DOM is more recalcitrant than that found in the surface waters. Because a portion of the semilabile DOM pool present at depth is transported via isopycnal mixing, the ventilation age of water provides insight as to the turnover time of the deeper semilabile DOM. Ventilation ages of water between 250 and 500 m in the Sargasso Sea can range from 1 to > 10 years (Jenkins, 1980) indicating that semilabile DOM advected along isopycnal surfaces to these depths would have turnover rates on the time scale of many years. The continuum of reactivity of the semilabile pool also varies between ocean systems (Carlson et al, 2000). The relative contribution of specific compounds,
131
Production and Removal Processes
iii
• •
Ross Sea
Sargasso Sea
Semi-labile < lyear Semi-labile > lyr Refractory
Mediterranean Sea
Figure 7 Contribution of semilabile DOC to the bulk DOC in the surface 250 m of the Ross Sea and the Sargasso Sea and surface 100 m of the Mediterranean Sea. All stocks were integrated vertically then normalized to integration depth for comparison purposes. Black shaded area of each column represents refractory DOC. DOC concentrations below 1000 m at each study site were used to represent refractory DOC contribution. The sum of the gray areas of each column represents semilabile DOC (i.e., the integrated DOC stock in excess of refractory DOC stocks). The light gray represents the proportion of semilabile DOC that turns over on time scales within 1 year as determined from the difference between the annual maximum and minimum stocks within the depth horizon of each time-series study site. The dark gray area represents the portion of semilabile DOC that is in excess of refractory DOC but does not vary over the time scale of 1 year (i.e., turns over on time scales of > 1 year). Estimates of turnover are based on observed changes in integrated pools from three time series studies. The Ross Sea data were adapted from Carlson et al. (2000); the Sargasso Sea entry was determined from the 1995 spring phytoplankton bloom event (Hansell and Carlson 1998b); the Mediterranean Sea example was adapted from Copin-Montegut and Avril (1993).
such as aldoses, can be used as an index of DOM reactivity (Skoog and Benner, 1997; Biersmith and Benner, 1998). Tlie semilabile DOC pool observed in the Ross Sea, Antarctica, contains a higher percentage of aldoses (up to 50%) than the Arctic, equatorial Pacific, and the Sargasso Sea (Fig. 8; Kirchman et al, 2001). The large contribution of reactive compounds in Ross Sea DOM is consistent with rapid turnover of semilabile DOM observed there (Carlson et al, 2000; Kirchman et al, 2001). Carlson et al (2000) found that nearly the entire semilabile DOC pool present in the Ross Sea in February 1997 (1.14 mol C m"^) was consumed within 2 months. In contrast, only 70 and 20% of the total semilabile DOC pool turned over on the time scales of less than 1 year for the Mediterranean Sea (CopinMontegut and Avril, 1993) and the Sargasso Sea (Carlson et al, 1994; Hansell and Carlson, 2001), respectively (Fig. 7). The inorganic nutrient regime may be an important factor in controlling the stoichiometry of freshly produced DOM and, in turn, its lability (Williams, 1995;
Craig A. Carlson
132 120 c3
u o Q
100 H
80-4
-]
60 H
-^ •S
40J
o
20-
T
1 _L T
jy -j
Arctic
1
^ ^ ^1
, Ross Sea 1 EqPacSl , EqPac S2 1Sargasso Sea1
Ocean Site Figure 8 Dissolved combined aldoses as a fraction of semilabile DOC in surface waters of various oceanic systems. Data from the Equatorial Pacific are from D. Kirchman and N. Borch (unpublished data), the central Arctic from Rich et al. (1997), the Ross Sea from Kirchman et al. (2001), and the Sargasso Sea from C. Carlson and M. Otero (unpublished data). The top, bottom, and line through the middle of each box represent the 75th, 25th, and 50th percentiles, respectively. The lines on the top and bottom of each box extend from the 10th to the 90th percentile of the data. Figure adapted with permission form Kirchman et al. (2001).
Ogawa et al, 1999; Carlson et al, 2000). Carbon-rich DOM (C:N >12 for semilabile DOM) in the North Atlantic was resistant to microbial degradation on seasonal time scales (Williams, 1995; Hansell and Carlson 2001; Kahler and Koeve, 2001), whereas nitrogen-rich DOM (C:N of ^6.7 for semilabile DOM) production in the nutrient replete Ross Sea was utilized on time scale of weeks (Carlson et al, 2000). The variable composition of semilabile DOC within and between ocean sites indicates that applying a single decay constant to calculate turnover of the integrated semilabile DOC pool is inappropriate in most cases. Semilabile DOM turnover is often calculated from integrated DOM stocks and instantaneous BP rates (i.e., semilabile DOM turnover = semilabile stock/(BP/BGE). However, this method of calculating turnover rates probably overestimates the actual rates because instantaneous BP rates (determined from [^H] thymidine or [-^H] leucine incubations) probably do not reflect growth supported by recalcitrant material. Instantaneous BP rates are more likely to be an index of growth supported by the rapid flux of labile DOM rather than semilabile DOM. A^'^C evidence does indicate that
Production and Removal Processes
133
bacterioplankton are able to take up "old" DOM (Cherrier et ah, 1999); however, remineralization of semilabile DOM can be slow and at times undetectable on time scales of days to weeks (Fig. 6b; Carlson and Ducklow, 1996; Cherrier et al, 1996; Carlson et ah, submitted for publication). Thus, one should not assume that semilabile DOM is utilized at a rate comparable to instantaneous BP measurements.
V. DOM ACCUMULATION Why does DOM accumulate? In the open ocean the net production of DOC is ultimately due to the decoupling of biological production and consumption processes. While there are several DOM production mechanisms (see section II), the dominant oxidizers of marine DOM are heterotrophic bacterioplankton (Azam and Hodson, 1977). Thus, factors that prevent rapid microbial utilization of "freshly produced" DOM result in its accumulation. These factors may include: (A) abiotic transformation of labile components to biologically recalcitrant compounds, (B) biological production of recalcitrant DOM, and (C) limitations on heterotrophic bacterial growth.
A. ABIOTIC FORMATION OF BIOLOGICALLY RECALCITRANT DOM Refractory or recalcitrant DOM may be formed from labile compounds by either cross-linking polymerization of LMW DOM (condensation reaction catalyzed by light and metals; Harvey et al, 1983) or modification of LMW labile material (e.g., proteins Hedges, 1988). Keil and Kirchman (1994) demonstrated that labile organic matter could be modified abiotically to a form resistant to rapid microbial oxidation. Condensation reactions, binding of monomers to macromolecular DOM (Carlson et al, 1985), adsorption to colloids (Kirchman et al, 1989; Keil and Kirchman, 1994; Nagata and Kirchman, 1996), and exposure to UV irradiation (Keil and Kirchman, 1994;Naganuma^fa/., \996\ Gohl^v et al, 1997; Benner and Biddanda, 1998; Tranvik and Kokalj, 1998) have all been proposed as mechanisms that physically alter DOM to a molecular structure that impedes DOM degradation. The effects of UV exposure on DOM are complex and seemingly yield both labile (Kieber et al, 1989; Moran and Zepp, 1997) and recalcitrant DOM products (Keil and Kirchman, 1994;Naganuma^ffl/., 1996;Gobler^/(3/., 1997; Benner and Biddanda, 1998; Tranvik and Kokalj, 1998; see Mopper and Keiber, Chapter 9). Benner and Biddanda (1998) found that exposure of euphotic zone DOM to UV irradiation reduced bacterial production by 75% while exposure of deep DOM (150-1000 m) to UV enhanced bacterial production by 40%. They concluded that the chemical composition of DOM dictates whether phototransformations produce
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bioavailable or bioresistant compounds. The exact mechanisms and magnitude of these abiotic transformations remain unknown. Studying abiotic transformation of DOM from labile to recalcitrant forms may provide clues as to the origin of refractory DOM.
B. BiOTic FORMATION OF RECALCITRANT D O M Abiotic processes lead to the restructuring of recognizable labile compounds into complex macromolecules that are not recognized by traditional chemical analysis. These processes appear to "shield" the labile component from biological oxidation (Keil and Kirchman, 1994). Recent studies have also identified unmodified recalcitrant components of DOM, formed by direct biosynthesis, that can contribute a large fraction of the HMW DOM found in the surface waters (Tanoue et ai, 1995; Aluwihare et al, 1997; McCarthy et ai, 1998). Eukaryotic and prokaryotic organisms are both potential sources of biologically recalcitrant DOM. 1. Eukaryotic Sources Extracellular release is a major source of carbon rich carbohydrates in the surface ocean. Polysaccharides contribute a major fraction of the HMW (> 1000 Da) DOM (Benner et al, 1992; McCarthy et ai, 1996; Skoog and Benner, 1997). In a culture experiment with marine diatoms, Lara and Thomas (1995) observed an increase in recalcitrant DOC as POC decreased, indicating that cellular components such as cell wall material may be the source. A compound resembling acyl heteropolysaccharide (APS), a metabolically resistant and dominant polysaccharide in the surface ocean (Aluwihare etal, 1997), has been shown to be released directly by marine diatoms and haptophytes (Aluwihare and Repeta, 1999). This APS-like polysaccharide had a slower degradation rate relative to the total polysaccharide fraction of the phytoplankton exudate. Biersmith and Benner (1998) found similarities between the aldose signature of HMW phytoplankton exudate and HMW DOM isolated from various locations in the surface ocean. Phytoplankton community structure may play an important role in the production of recalcitrant DOM. Aluwihare and Repeta (1999) found that in three species of phytoplankton studied, all produced APS-like polysaccharides. However, the percentage of polysaccharides released as APS varied considerably between species. 2. Prokaryotic Sources Prokaryotes can also be sources of recalcitrant DOM (Table VI). Brophy and Carlson (1989) observed bacterial transformation of ^"^C labeled glucose
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and leucine and subsequent release of recalcitrant HMW (700-1400 Da). Similarly, Tranvik (1993) found that approximately 3% of the initial glucose concentration was transformed into humic-like DOM after a 1-week incubation. Heissenberger et al. (1996) reported ^^C-labeled leucine was transformed into recalcitrant HMW (> 50,000 Da) DOM in a bacterial batch culture. A subsequent study hypothesized that the HMW material produced by microbial growth was capsular material (Stoderegger and Hemdl, 1998). Ogawa et al. (2001) found that when glucose and glutamate were added to bacterial cultures the labile compounds were utilized rapidly; however, the bacterioplankton also produced DOM that resisted further microbial degradation for time scales of more than 1 year. These studies attributed recalcitrant DOM production to bacterial processes, but they were not able to rule out the possibility that viral lysis or grazing contributed to the HMW DOM production. Nonetheless, DOM with bacterial-like biochemical characteristics is ubiquitous in the surface ocean, indicating a bacterial source for some recalcitrant DOM (Tanoue et al, 1995,1996; McCarthy et al, 1998). Tanoue et al. (1995) identified a dissolved protein, homologous to the Gramnegative bacterial membrane porin P, as being common to various ocean basins. Porins are resistant to proteases and rapid microbial degradation (Tanoue et al, 1996 and citations within). Peptidoglycans, the main structural component of bacterial cell walls, have also been proposed as the likely source of enriched D-enantiomer amino acids (D-amino acids) found in two oligotrophic sites (McCarthy et al, 1998). The polysaccharide matrix, with its unusual peptide structures, yields a polymer that is resistant to many common hydrolytic enzymes, rendering it bioresistant (McCarthy et al, 1998). Liposome-Uke particles (aqueous compartments enclosed by a lipid bilayer) released from bacterioplankton via viral lysis or nanoflagellate grazing may be an additional prokaryotic source of recalcitrant DOM (Nagata and Kirchman, 1992; Nagata, 2000). The exact mechanism by which these bacteria-associated compounds enter into the dissolved phase (release from bacteria directly or a byproduct of microzooplankton grazing or viral lysis) are not well understood or quantified. Nonetheless, these bacteria-derived compounds are now becoming recognized as an important source of recalcitrant or refractory DOM. C. LIMITATION OF BACTERIAL GROWTH AND ACCUMULATION OF BIODEGRADABLE
DOM
The accumulation of DOM in surface seawater has been largely attributed to the accumulation of recalcitrant material resistant to microbial degradation (Billen and Fontigny, 1987; Brophy and Carlson, 1989; Legendre and Le Fevre, 1995; Tanoue et al, 1995; Carlson et al, 1998). Based on the assumption that accumulated
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DOM is recalcitrant, one might expect that growth of heterotrophic bacterioplankton is initially limited by the availability of labile DOM (Kirchman et al, 1990; Kirchman, 1990; Keil and Kirchman, 1991; Carlson and Ducklow, 1996; Cherrier et al, 1996; Carlson et al, in press; WilUams, 2000). However, the view of labile DOM limitation of bacterial growth has recently been challenged by the "malfunctioning microbial loop" hypothesis (Thingstad et al, 1997). This hypothesis states that competition for limiting nutrients (Bratbak and Thingstad, 1985; Zweifel et al, 1993; Thingstad and Rassoulzadegan, 1995; Cotner et al, 1997; Rivkin and Anderson, 1997; Thingstad et al, 1998) and grazing pressure (Thingstad and Lignell, 1997; Zweifel, 1999) reduce bacterioplankton growth rate, biomass, and carbon demand to levels that allow accumulation of biodegradable DOC during biologically productive seasons. Low temperatures have also been suggested as a mechanism that inhibits BP (Pomeroy and Deibel, 1986; Pomeroy et al, 1991; Shiah and Ducklow, 1994) and may foster DOM accumulation (Zweifel, 1999). However, Carlson et al (1998) and Ducklow et al (in press), found little evidence to support the hypothesis of temperature regulation on bacterial growth or DOC accumulation in the Ross Sea, Antarctica. However, temperature regulation may be more important in systems that demonstrate large seasonal temperature ranges. According to the "malfunctioning microbial loop" hypothesis, one would expect that by reducing grazing pressure and adding potentially limiting nutrients to dilution cultures, bacterioplankton growth and DOC utilization would be enhanced. The experimental results of Zweifel and Hagstrom (1995), conducted in the Baltic Sea, support this hypothesis by showing enhanced bacterial growth and DOC utilization in cultures amended with inorganic N and P. In contrast to these findings, inorganic amendments had neither an effect on bacterial production nor DOC remineralization in the oceanic eastern North Pacific (Cherrier et al, 1996) or the northwestern Sargasso Sea (Carlson and Ducklow, 1996; Carlson et al, in press). S0ndergaard et al (2000) found that inorganic nutrient amendment had only a marginal effect on DOC degradation. In his review on the controls of microbial growth, Williams (2000) found that the nutrient limitation hypothesis appeared to be more frequently sustained in coastal regions (see his Table IV) and to a lesser extend in oceanic waters. This is not to say that inorganic nutrient limitation of bacterioplankton growth does not occur in oceanic waters. In fact, several studies in the northwestern Sargasso Sea have demonstrated that, at times, bacterioplankton production can respond to amendments of inorganic nutrients (Cotner et al, 1991 \ Rivkin and Anderson, 1997; Caron et al, 2000). However, in studies where DOC consumption was measured directly, no evidence exists to suggest that amending surface water assemblages with inorganic macronutrients further reduces semilabile DOC concentration below the mean mixed layer concentrations of the northwestern Sargasso Sea on the time scales of weeks (Carlson et al, in press).
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Production and Removal Processes D. MICROBIAL COMMUNITY STRUCTURE AND DOM
UTILIZATION
In addition to the inorganic nutrient regime, the structure of the microbial community may play an important role in regulating the accumulation and subsequent remineralization of semilabile DOM. For example, in the northwestern Sargasso Sea DOC stocks accumulate rapidly within the euphotic zone shortly after water column stratification and persist at elevated concentrations throughout the summer into early autumn (Carlson et ai, 1994; Hansell and Carlson, 2001). During seasonal overturn a portion of the seasonally accumulated semilabile DOC can be exported to depths >200 m. Once isolated within the aphotic zone the exported DOC is remineralized relatively quickly on time scales of weeks to months (Carlson et ai, 1994; Hansell and Carlson, 2001). Why does the seasonally produced semilabile DOM escape rapid microbial degradation in the surface but become available to microbial remineralization at depth? While inorganic macronutrients are found at elevated concentrations at depth, simply amending surface water microbial assemblages with inorganic macronutrients did not appear to stimulate DOC removal in experimental cultures conducted in the northwestern Sargasso Sea (Carlson et al, in press). Prokaryotic phylogenetic diversity is greater below the euphotic zone compared to the surface waters (Giovannoni etal, 1996; Gordon and Giovannoni, 1996). Archaea dominate in the mesopelagic regions of some ocean sites (Kamer et al, 2001). Kamer et al. (2001) proposed that the high percentage of Archaea cells containing significant amounts of rRNA suggests that they are metabolically active. Do some Archaea specialize in utilizing diagenetically altered semilabile DOM? Vertical gradients in the availability of nutrients and energy may be responsible for the observed diversification and specialization of microbial communities. These specialized microbial communities may regulate consumption of semilabile DOC transported to depth. Further experimental work is necessary to gain insight and to quantify potential linkages between specialized microbial assemblages and biogeochemical processes, such as utilization of semilabile DOC.
VI. SUMMARY In this chapter, I have outlined our present understanding of the DOM production and removal processes, the characteristics of the general pools of lability of the bulk DOM pool, and factors that lead to DOM accumulation. 1. DOM production mechanisms include direct phytoplankton release, zooplankton-associated processes (i.e., grazing and excretion), virus and bacteriainduced release, solubiHzation of particles, and prokaryotic DOM production.
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Experimental and field evidence suggests that extracellular release of DOM is a normal function of phytoplankton production with typically 13% of PP being released as DOM; however, significant variability exists in the literature (Table II). The magnitude of extracellular release is dependent on a variety of physiological and environmental conditions not fully understood yet. Empiricists (Jumars et al, 1989; Nagata, 2000) and modelers (Anderson and Ducklow, submitted for publication) both suggest that under steady-state conditions the bulk of DOC supply comes from zooplankton processes. Nagata (2000) suggests that as much as 30% of PP is released from protozoan herbivory with an additional contribution from macrozooplankton grazing and bacterivory. Significant study is still required to properly assess the contribution of DOM production via viral impact, solubilization of particles and direct release of organics from prokaryotes. 2. Bacterioplankton (or prokaryotic) oxidation of DOM is considered the main sink for recently produced DOM; however, the role of UV oxidation is now recognized as an important removal process especially for refractory DOM. Sorption of DOM onto sinking particles is also recognized as a potential DOM removal mechanism within the oceans interior. Work continues toward trying to identify and quantify processes that remove refractory DOM. 3. The bulk DOM pool represents a broad continuum of biological lability ranging from material that turns over on time scales of minutes to days (labile DOM), to material that turns over on time scales of weeks to years (semilabile), to material that survives for decades to millennia (refractory DOM). The refractory pool represents the majority of DOC present in the surface waters of thermally stratified waters (^70% in temperate and tropical waters). The labile pool is kept at low concentrations due to high turnover by microbial activity. The majority of the vertical structure in a DOM profile in thermally stratified systems is composed of semilabile DOM, which accumulates in excess of the refractory background DOC stocks. Factors such as biological conmiunity structure and nutrient regime may play a role in the production of semilabile DOM. 4. Accumulation of DOC results from the uncoupling of DOM production and removal processes. The production of biologically resistant compounds via physical processes such as condensation reactions or phototransformation can result in the production of biologically resistant DOM. Unmodified recalcitrant components of DOM, formed by direct biosynthesis, has also been identified for both phytoplankton and bacterioplankton. Inorganic nutrient limitationcontrol of DOM accumulation remains an interesting hypothesis but evidence of its support is ambiguous. Finally spatial variability of microbial conmiunity structure may also play a role in the processing and cycling of recalcitrant compounds.
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ACKNOWLEDGMENTS I particularly express my gratitude to Hugh Ducklow and Dennis Hansell, who have been great collaborators and friends along this path. This chapter benefited greatly from reviews and discussions by and with James Christian, Hugh Ducklow, David Smith, David Kirchman, and Dennis Hansell. Thanks to Walker Smith, David Smith, and Deborah Steinberg for access to unpublished data. I thank Stuart Goldberg and Rachel Parsons for assistance in generating some of the table data used in this chapter. This work has been supported by NSF Grants OCE 9617795, OCE 9619222, MCB-9977918 and OCE-0196305. This is U.S. JGOFS contribution 712.
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Chapter 5
Dynamics of DON Deborah A. Bronk Virginia Institute of Marine Science, College of William and Mary, Gloucester Point, Virginia I. Introduction II. Concentration and Composition of the DON Pool A. Methods for Measuring DON Concentrations B. DON Distributions and Correlative Relationships between DON and Other Parameters C. Chemical Composition of the DON Pool D. Concentration and Composition of the DON Pool: Research Priorities III. Sources of DON A. Biotic Sources of DON in the Water Column B. Methods for Estimating Biotic DON Release Rates C. Literature Values of DON Release
Rates in Aquatic Environments D. Sources of DON: Research Priorities IV. Sinks for DON A. Heterotrophic versus Autotrophic DON Utilization B. Methods for Estimating Biotic DON Uptake C. Literature Values of DON Uptake in Aquatic Environments D. Photochemical Decomposition as a Sink for DON E. Sinks for DON: Research Priorities V. DON Turnover Times VI. Summary References
I. INTRODUCTION Dissolved organic nitrogen (DON) is that subset of the dissolved organic matter (DOM) pool that contains N. From the perspective of a microorganism, this is where the action is—one-stop shopping for N, carbon (C), and energy. Research into DON, however, has lagged far behind that of the larger dissolved organic carbon (DOC) pool as clearly seen by the C:N ratio of chapters in this volume. This situation is primarily the result of the substantial analytical challenges Biogeochemistry of Marine Dissolved Organic Matter Cop)mght 2002, Elsevier Science (USA). All rights reserved.
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inherent in DON research. DON exists in substantially lower concentrations than DOC, multiple chemical analyses are required for a single DON measurement, inorganic N removal is a nightmarish undertaking, and unless you have easy access to a nuclear reactor manufacturing short-lived ^^N, one must be content with labor-intensive stable isotopes rather than the quicker and more sensitive radiotracers. The objectives of this chapter are to review available data specific to DON on the concentration and composition of the pool, to describe recent findings on the sources of DON to aquatic systems, and to survey data on rates and mechanisms of DON uptake and other sinks. An exhaustive review of DON was published by Antia et al (1991). Therefore, this review will focus on work pubUshed largely after 1990 and topics not included in the earlier review. As a subset of the DOM pool, much of the information presented on DOC throughout this volume holds equally true for DON.
11. CONCENTRATION AND COMPOSITION OF THE DON POOL Measurements of DON concentrations have become a routine component of many studies. This section reviews methods for measuring DON and then presents a survey of recent literature values of DON concentrations, relationships between DON and other parameters, data on the chemical composition of the pool, and suggested research priorities for the future. Due to space limitations, DON concentrations in lakes, streams, or groundwater, with some exceptions, are not included. A. METHODS FOR MEASURING DON CONCENTRATIONS Studies of any aspect of DON cycling require first and foremost a reliable method of quantifying DON concentrations with high precision (Bronk et ai, 2000; see Sharp, Chapter 2). To calculate DON concentrations, one must first obtain an accurate total dissolved N (TDN) concentration. The TDN pool consists of an inorganic fraction, composed of ammonium (NH4^), nitrate (NOs"), and nitrite (N02~), and an organic fraction (i.e., DON), the composition of which is largely unknown (see Section II.C). There are presently three methods conmionly used to measure TDN concentrations in aquatic systems: persulfate oxidation (Menzel and Vaccaro, 1964; Sharp, 1973; Valderrama, 1981), ultraviolet oxidation (Armstrong etal, 1966; Armstrong and Tibbitts, 1968), and high-temperature oxidation (Sharp, 1973; Suzuki and Sugimura, 1985). After a TDN concentration has been measured, the sum of the NH4'^ and combined NO3" / NO2" concentrations are subtracted from it, with the residual being defined as DON. This approach is problematic
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because estimates of DON concentrations have the combined analytical error and uncertainty of three analyses: TDN, NH4+, and combined NOs"/ N02~. The first broad community comparison of the three methods used to measure DON was recently completed (Sharp et al, in press; see Sharp, Chapter 2). It consisted of 29 sets of analyses done on five natural samples. The coefficient of variations for the five samples range from 19 to 46%, with the poorest replication observed on deep ocean samples. No one method emerged as clearly superior. B. DON DISTRIBUTIONS AND CORRELATIVE RELATIONSHIPS BETWEEN D O N AND O T H E R PARAMETERS Here DON concentrations are presented and discussed with respect to global distributions, vertical profiles, seasonal variability, and the link between DON and inorganic N distributions. 1. Concentrations of DON in Aquatic Environments In general, the lowest mean concentrations of DON are found in the deep ocean and the highest mean concentrations are found in rivers (Fig. 1 A). Concentrations in Table I for the surface ocean range from 0.8 to 13 JJLM with a mean of 5.8 ± 2.0 /xM. Note that many open ocean studies present data on total organic N (TON), rather than DON. Most researchers working in oligotrophic waters forego the filtration step because the particulate N (PN) pool is generally so small (<10% of TON; Abell et al, 2000) and the risk of contamination and cell breakage during filtration is so high (Libby and Wheeler, 1997; Abell et al, 2000). Concentrations in the deep ocean are lower with most measurements in the 2 to 5 /xM range (Table I); if the very high Tupas and Koike (1990) data are excluded, the mean deep ocean concentration is 3.9 ± 1.8. Concentrations tended to be progressively higher in coastal, then estuarine, and then riverine waters, but the ranges in concentrations are much greater as well (Table I). In all environments, except the deep ocean, the bulk of the TDN pool is organic in form, averaging 60-69% of the TDN pool (Fig. IB). The high NO3" concentrations in the deep ocean, results in the relatively small contribution of DON to the TDN pool in that environment (10 ± 3%, Fig. IB). The C:N ratio of DOM increases from ~14 in the surface ocean along a decreasing salinity gradient to a maximum mean of 26 in riverine systems (Fig. IC; see Karl and Bjorkman, Chapter 6). 2. Global Distributions Our understanding of global distributions of DON is still incomplete. Fortunately, the larger data sets needed to give a more holistic picture of DON
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distributions are becoming more common. In general, the lowest TON concentrations occur right at the equator, with the highest concentrations occurring just to the north and south (--S^N and S; Libby and Wheeler, 1997; Raimbault et al, 1999; Hansen and Waterhouse, 1997). The pattern emerging in the Pacific is that increased biological production of DON occurs near the equator, via a number of release processes, and is fueled by primary production resulting from upwelled NOs" (see Hansell, Chapter 15). The released DON is then exported north or south from the equator in the meridonal Ekman transport to N depleted subtropical waters. The meridonal transport is likely one mechanism for moving organic N to the oligotrophic central gyres where it can fuel autotrophic growth and therefore support export production (Hansell and Waterhouse, 1997; Libby and Wheeler, 1997). Consistent with the picture above, TON concentrations along a transect from 45°N to 10°N in the North Pacific exhibit a gradual decHne, and the TOC.TON ratio increases, as the water is transported northward (Fig. 2; Abell et al, 2000); continuing north (north of ~30°N), the reverse pattern is observed. One intriguing observation is a significant correlation between TON concentrations and apparent oxygen utilization along the four isopycnals surfaces studied (Abell et al, 2000). It was suggested that TON distributions are primarily the result of degradation of organic matter along isopycnal surfaces, although the degradation does not follow Redfield stoichiometry (Abell et al, 2000). In the Atlantic, patterns in surface DON concentrations are similar to those in the Pacific; concentrations are low at the equator and then increase to the north and south, again indicating the possibility of a meridonal flux moving away from the equator (Vidal et al, 1999). Continuing further south, however, DON concentrations reach a minimum of 5 to 7 IJM. Another trend is that concentrations of DON generally increase along ocean margins. This reflects the higher concentrations of DON in estuaries and rivers, which transport DON to the coastal ocean (Table I). From the little data available, it also appears that concentrations of DON tend to decHne beyond the frontal zones to the poles (Table I). 3. Vertical Profiles Vertical profiles of DON (or TON) generally show a surface enrichment relative to concentrations deeper in the water column. This has been observed in a wide number of environments including the equatorial Pacific (Libby and Wheeler, 1997), Monterey Bay and the Bering Sea (Hansell, 1993), the Santa Monica Basin (Hansell et al, 1993), the Mississippi-Atchafalaya river plume (Lopez-Veneroni and Cifuentes, 1992), the Southern Ocean (Ogawa et al, 1999; Kahler et al, 1997), Drake Passage (Sanders and Jickells, 2000), Georges Bank (Hopkinson
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Dynamics of DON Equatorial lition I
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Latitude (deg N) Figure 2 (Top) Concentrations of dissolved inorganic nitrogen (DIN) and total organic N (TON) and (Bottom) the total organic carbon (TOC) to TON ratio along a transect in the North Pacific (modified with permission from Abell et al, 2000).
et al, 1997), the oligotrophic North Pacific (Malta and Yanada, 1990; Harrison et al, 1992; Loh and Bauer, 2000), along a transect from Bermuda to Chesapeake Bay (Bates and Hansell, 1999), the Arctic (Wheeler et al, 1997), the North Pacific (Abell etal, 2000), and the equatorial Atlantic (Vidal etal, 1999). In the Southern California Bight, DON concentrations are generally uniform in the surface layer but become more variable and often increase within the nitracline (Hansell et al, 1993). Elevated DON concentrations at the surface suggest that DON can be exported to depth (Toggweiler, 1989; Hopkinson et al, 1997). DON export, and subsequent ammonification and nitrification, is estimated to supply 19% of remineralized NO3" at depth off Georges Bank (Hopkinson et al, 1997); 15% in the Bering Sea
172
Deborah A. Bronk
(Koike and Tupas, 1993), 10% at various sites in the Pacific (Jackson and Williams, 1985), and 25% in the North Pacific (Malta and Yanada, 1990). Vidal et al (1999) calculated vertical gradient-driven fluxes of DON in the equatorial Atlantic using vertical profiles of DON concentrations and estimates of a vertical eddy diffusion coefficient. They found that surface DON did appear to be transported to depth at times, however, the direction of the dominant flux varied along the north-south transect. The DOC pool is commonly envisioned as being composed of a labile, semilabile, and refractory component based on vertical profile data (Kirchman et al, 1993; Carlson and Ducklow, 1995; see Carlson, Chapter 4). In a similar fashion, the refractory TON pool is estimated at 4 /xM in equatorial Pacific waters, based on TON concentrations in the deep ocean (Libby and Wheeler, 1997). Assuming this recalcitrant fraction is present throughout the water column, refractory TON is -- 60% of the TON in the upper 40 m; the C:N of the refractory TON is 9.9. The semilabile pool in the upper 40 m ranges from 3.4 to 5.8 /xM TON and has a lower C:N ratio (5.1 to 8.5) than the refractory pool. 4. Seasonal Variations The question of whether DON concentrations exhibit a seasonal pattern is an open one. There are areas where no seasonal pattern is indicated, including the Santa Monica Basin (Hansell et al, 1993) and at the Bermuda Atlantic Time Series (BATS) site in the Sargasso Sea (Hansell and Carlson, 2001). In contrast, some studies suggest that DON increases in late spring and summer, including work in the Gulf of Mexico (Lopez-Veneroni and Cifuentes, 1994), Chesapeake Bay (Bronk et al, 1998), North Inlet, SC (Lewitus et al 2000), and a suite of rivers draining into the Baltic Sea (Stepanauskas et al, in press). The most compelling evidence for a seasonal cycle is presented by Butler et al (1979), who conducted an 11-year study of DON concentrations in the English Channel. They documented a steady increase in DON concentrations from January through August and then a steady decline from August to December. The clear seasonal pattern observed by Butler et al (1979) highlights the importance of long-term data sets in defining these types of patterns. In general, oligotrophic environments do not show seasonality in DON, as would be anticipated given the scant supply of N. 5. Link between DON Distributions and Inorganic N There have been a number of observations linking decreases in NOs" or elevations in N2 fixation and accumulations of DON in near surface waters. In the Pacific, an increase in DON/TON concentrations and a concomitant decrease in NOs" concentrations as one moves away from the equator is shown by a number of studies (Libby and Wheeler, 1997; Hansell and Waterhouse, 1997; Raimbault
Dynamics of DON
173
et al, 1999). This pattern suggests that new TON production is fueled by high equatorial new production and subsequent organic N release. An estimated 37 ± 14 and 81 ± 54% of net NO3 ~ depletion accumulates as DON during the movement of upwelled equatorial water to the north and south, respectively (Libby and Wheeler, 1997). In the Ross Sea, approximately 10% of the net NO3" draw down in surface waters accumulates as DON (Carlson et al, 2000). Similar relationships between NOs" consumption or disappearance and TON/DON production have been observed in the English Channel (Butler et al, 1979), in the subarctic Pacific (Malta and Yanada, 1990), in Chesapeake Bay (Bronk et al, 1998), and in a coastal pond {Co\\o% etal, 1996). In the Mississippi River plume, Benner et al (1992a) used 5^^N data to demonstrate the conversion of NO3" to high-molecular-weight (HMW) DON, isolated using a > 1-kDa ultrafiltration unit. The DON produced is likely the result of phytoplankton uptake and subsequent conversion to DON that is then released. The 5^^N of the DOM pool is ~3%o at both the river and Gulf endpoints. At intermediate salinities, however, the 5^^N of the DOM pool increases to ^9%o. The likely cause for this increase is the conversion of NOs" to DON; the NOs" in this region has a ^^^N of -^10%^. In the Pacific, Atlantic, and Gulf of Mexico, the ^^^N of the HMW DON ranges from a mean of 7.9 ± 0.7 in the Pacific to 9.9 ± 0.5%o in the Gulf of Mexico (Benner et al, 1997). There is no relationship between the concentration of HMW DON and the 5 ^^N of the material, suggesting that the isotopic signature reflects the source of the N, not isotopic fractionation during decomposition. The lowest (5^^N values (6.6%o) are observed in the surface waters at the BATS site in the Sargasso Sea, and are likely the result of the use of isotopically light new NOs", which has a 5^^N of ~3.5%o in the region (Altabet, 1988). These low values can also indicate the addition of isotopically depleted N from N2fixation(atmospheric N2 is ~0%o) and then subsequent release of DON from N2fixerssuch as Trichodesmium (see Section III. A.2). In the Pacific, the lightest 5^^N values are measured at the equator where new NOs" is upwelled (Benner, et al, 1997). The 5^^N of DON increases to the north and south of the equator, suggesting that the DOM is being produced biologically during meridonal transport as described above. In the reverse of the NOs" to DON conversion discussed above, Kemer and Spitzy (2001) documented that between 75 and 100% of the LMW DON and NH4+ is consumed and converted to NOs" in the Elbe estuary via nitrification. This is the analogous process that produces the inverse relationship between DON and NOs" concentrations when moving from the surface into the deep ocean (Lara etal, 1993). Finally, there are examples where increases in DON concentrations do not correlate well with decreases in NOs". For example, along the NW African coast, Vidal et al (1999) found that the downward flux of DON exceeds the upward supply of N03~, indicating an additional supply of N from meridonal transport
174
Deborah A. Bronk
(Libby and Wheeler, 1997) or perhaps atmospheric inputs (Cornell et al, 1995). At the station with the highest DON flux, in excess of NOs" influx, there were significant concentrations of Trichodesmium. C. CHEMICAL COMPOSITION OF THE DON
POOL
DON is a heterogeneous mixture of compounds composed of biologically labile moieties, which likely turn over on the order of days to weeks, and refractory components, which persist for months to hundreds of years, and comprise the bulk of the DON measured in the ambient DON pool (see Section V). The more refractory forms are quantitatively dominant with respect to ambient concentrations, but their importance as a potential N source is far exceeded by the smaller, more labile compounds. A large number of compounds have been identified within the DON pool, including urea, dissolved combined amino acids (DCAAs), dissolved free amino acids (DFAA), humic and fulvic substances, and nucleic acids. The remainder of the DON pool is a heterogeneous mixture of unidentified compounds. In this section, individual organic compounds are discussed including measurement techniques and a review of recently measured concentrations, followed by a discussion of recent efforts to chemically characterize the HMW fraction and research priorities for the future. 1. Urea Urea is a low-molecular-weight (LMW) organic compound, which is a product of organic matter decomposition and organismal excretion. The two methods commonly used to measure urea concentrations are the urease method, which involves enzymatic hydrolysis of urea to carbon dioxide and ammonia (McCarthy, 1970), and the direct colorimetric measurement of urea using diacetyl monoxime (Price and Harrison, 1987). Note that urea is occasionally treated as an inorganic N form (Capone, 2000; J0rgensen et al, 1999). The rationale for this practice is that urea is used primarily as a N source and not as a form of energy. Out of solidarity with poor researchers assembling large tables, I suggest this practice be discontinued, because it confuses the calculation of DON concentrations. Urea contains C, as well as N, and so should sit squarely in the DON pool. Urea concentrations range widely from 0 to 13 /xM in the studies surveyed (Table II). In general, urea concentrations in open ocean systems tend to be very low (<0.3 /xM), coastal systems tend to be sUghtly higher (<0.7 /xM, Metzler et al, 2000), and estuarine and riverine systems are higher still (<3 /JM). The highest urea concentrations were measured in polar regions affected by sea ice formation (Conover et al, 1999). In the studies where urea concentrations are presented as part of the total DON pool, urea averages 5.2 =b 3.4% (Table II).
Dynamics of DON
175
2. DCAA The chemical structure of DCAA is largely unknown but can include a suite of bound amino acids including proteins and oligopeptides (Lee and Bada, 1977), amino acids bound to humic or fulvic materials (Lytle and Perdue, 1981; Poutanen and Morris, 1985), and amino acids adsorbed to clays or other materials (Hedges and Hare, 1987). Billen (1991) provided indirect evidence that protein is the dominant form of DCAA in eutrophic waters. Though protein may be a major component of DCAA, abiotic transformations of protein can produce recalcitrant DOM, which is not recognizable as protein in routine chemical analyses, via such processes as glucosylation or the Maillard reaction (Hedges, 1988; see the end of this section). Concentrations of DCAA are typically measured using HPLC after liquid hydrolysis with 6 N HCl at 110°C for 20-24 h (Parsons et aL, 1984). A quicker vapor phase hydrolysis technique was introduced by Tsugita et al. (1987). DCAA concentrations measured with the vapor phase method were found to be 1.5 di 0.4 times higher than those found with the traditional hydrolysis method (Keil and Kirchman, 1991b). Concentrations of DCAA often constitute the largest identifiable pool of DON in the ocean (Sharp, 1983). In the studies surveyed here, DCAA concentrations range from 0.15 to 4.20 /xM and represent 7.2 ± 4.3% of total DON (Table II). DCAA are present in at least three forms (Keil and Kirchman, 1993). First, it can exist as protein similar to that freshly extracted from phytoplankton (<10% of the total DCAA); this material appears to be rapidly assimilated by bacteria with turnover times of hours to days. Second, it can exist as protein kinetically similar to abiotically glucosylated protein (~50% of the DCAA pool); this material appears to turn over much slower. Third, it can exist as nonproteinaceous DCAA that can contribute up to 50% of the DCAA pool; this material is resistant to standard liquid hydrolysis and likely represents bound or sorbed amino acids with an unknown turnover time. Consistent with this scenario, the proportion of DCAA identifiable as protein in the northern Sargasso Sea ranges from 40 to 100% in surface waters but only 20 to 50% in deeper waters (Keil and Kirchman, 1999). Depth profiles suggest that levels of dissolved proteins, measured with tangential flow ultrafiltration and gel electrophoresis, are low in the surface and higher below the euphotic zone; the electrophoretic technique as applied, however, is not quantitative (Tanoue et aL, 1995, 1996). One protein (48 kDa) is present at all depths examined, and the amino acid sequence indicates that it is a homolog of porin P found in Gram-negative bacteria (see Section II.C.6); porin P specifically facilitates P utilization and is induced by P limitation. In general, porins are very resistant to breakdown by proteases (Cowan et aL, 1992), which likely explains why they are so prevalent in the water column. The electrophoretograms of protein dissolved in seawater are very different from the protein in the particulate fraction
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or in bacteria, suggesting that the proteins isolated in seawater do not originate directly from living organisms (Tanoue et aL, 1996). Another important component of the DON pool are the proteolytic enzymes, which are well characterized for a number of bacterial sources (see Chrost, 1991; Hoffman and Decho, 2000). Much less is known about proteolytic enzymes associated with microalgae, though recent work has investigated cell-associated proteases in a number of phytoplankton (Hooper and Hughes, 1992; Berges and Falkowski, 1996) and cyanobacteria (Martinez and Azam, 1993). One interesting area of ongoing research is determining why some organic compounds persist in the ocean for hundreds to thousands of years. Specifically, what is the mechanism that transforms a labile compound to a refractory one (see Section IV.C.3 and Carlson, Chapter 4, and Benner, Chapter 3)? Bacterial assimilation of protein decreases when the protein is aged for as little as 6 h (Keil and Kirchman, 1994). When the protein is aged for 40 days, it degrades fourfold more slowly than unaged protein. No aging affect is observed in organic-free water, indicating that organic-organic interactions produce the refractory protein. Keil and Kirchman (1994) demonstrate that protein comprises 1-10% of the DCAA pool, that glucosylated protein comprises 5-66%, and that glucosylation inhibits bacterial protein degradation. 3. DFAA Concentrations of free amino acids are reported either as DFAA (measured with HPLC; Mopper and Lindroth, 1982) or dissolved primary amines (DPA, estimated fluorometrically; Parsons et ai, 1984); in waters with low NH4"^ concentrations, the two measurements are generally equal (Kirchman et aL, 1989). DFAA concentrations range from 0.001 to 0.70 /xM in the studies surveyed, and represent only 5.9 ib 4.6% of the total DON pool (Table II). Though concentrations of amino acids tend to be very low due to the close coupling between uptake and release (Fuhrman, 1990), this is not always the case. For example, extremely high levels of DPA (up to 17 fiM) were measured during a dinoflagellate bloom in Chesapeake Bay (Sellner and Nealley, 1997). Concentrations of DFAA vary with season, depth, location, and time of day (Mopper and Lindroth, 1982; Williams and Poulet, 1986; Fuhrman, 1987, 1990). A likely source of DFAA are primary producers, many of which have large intracellular pools of amino acids that can be released via a number of processes (see Section III.A; Brown, 1991; Marsot etai, 1991). Laboratory culture experiments indicate that intra- and extracellular amino acids can vary as a function of growth phase (Admiraal et aL, 1986; Marsot et aL, 1991), and thus can be very important indicators of cellular metabolic state in phytoplankton. One area that is receiving attention of late is the analysis of amino acid enantiomeric ratios (McCarthy et aL, 1998; J0rgensen et aL, 1999; see Section IILC.3).
Dynamics of DON
181
The D enantiomers are abundant in bacterial cell walls and are indicative of refractory components, such that they can be used as an indicator of the source and diagenetic state of DOM. During a 10-day decomposition experiment with fresh phytoplankton-derived DOM from an Arctic ice floe, the concentration of the D enantiomer did not change but the D/L ratio increased during the course of the incubation indicating a trend toward the presence of more refractory DOM (Amon et al, 2001). 4. Humic and Fulvic Substances Humic substances are the most hydrophobic component of the DON pool, composed of organic acids (500 to 10,000 MW) and operationally defined based on their retention on hydrophobic resins (Thurman, 1985, Aiken, 1988; see Benner, Chapter 3). Humic substances generally range in color from yellow to dark brown, and can fall into one of three categories: humic acids, which are not soluble in water under acid conditions (
Deborah A. Bronk
182 Table III
Literature Values of Concentrations of N Associated with Humic and Fulvic Acids and Their C:N Ratios Location Humic acids Mangrove swamp Altamaha River, GA Savannah River, GA Crab Cay, Bahamas Gulf Stream
Sampling date
Sampling depth (m)
October 1992
Concentration (MM)
C:N
Reference
Surface
5.3
22.3
Annual means 1996-1998 Annual means 1996-1998 October 1992
Surface
12.33 zb 5.48
Surface
11.65 ±7.14
Surface
1.9
13.4
October 1992
Surface
1.7
14.4
Moran and Hodson, 1994 Bronk et al. unpub. data Bronk et al, unpub. data Moran and Hodson, 1994 Moran and Hodson, 1994 Reviewed in Ishiwatari, 1992 LaiSietaL, 1993 LaiSietaL, 1993 Hubberten et al, 1995 Hubberten et al., 1995 Hubberten et al, 1995 Hubberten et al, 1995 Hubberten et al, 1995 Hubberten et al, 1995 Hubberten et al, 1995 Hubberten et al, 1995
11.1 to 13.3
Marine (6) waters Greenland Sea Greenland Sea Antarctic waters Antarctic waters Antarctic waters Antarctic waters Greenland Sea
June 1991 June 1991 December 1991 December 1991 December 1991 December 1991 June 1991
0 to 3650 0 to 3650 <100
1.00±0.2« 0.77 ± 0.2^ 0.45 ± 0.09^
>100
0.41 ±0.19^
<100
0.67 ±0.12^
>100
0.69 ±0.10^
<100
1.05d=0.23''
Greenland Sea
June 1991
>100
0.86 ± 0.20«
Greenland Sea
June 1991
<100
0.83 ±0.17^
Greenland Sea
June 1991
>100
0.65 ±0.12^ Mean ib std1 15.6 ± 4 . 6
Fulvic acids Sargasso Sea Loch Vale watershed, Colorado
7.8 28.3 to 34.5
Harvey and Boran, 1985 Reviewed in McKnight and Aiken, 1998 {Continues)
183
Dynamics of DON Table III Location
Sampling date
Sampling depth (m)
Pacific Ocean
Concentration (/AM)
C:N
Reference
Reviewed in McKnight and Aiken, 1998 14.0 to 96.0 Reviewed in McKnight and Aiken, 1998 Lara era/., 1993 2.3 ± O.r Meandistd 32.8 ± 19.5 37.0
Lake, rivers, and ponds (14)
Greenland Sea
(Continued)
June 1991
0 to 3650
Note. Data are mean di standard deviation. ^Hydrophobic neutral fraction isolated using XAD-2 (Fu and Pocklington, 1983); represented 56 ± 10% of the total DON pool. ^Hydrophobic acid fraction isolated using XAD-2 (Fu and Pocklington, 1983); represented 25 ± 70% of the total DON pool. ^Hydrophilic fraction isolated using XAD-2 (Fu and Pocklington, 1983); represented 19 ± 4% of the total DON pool.
is associated with the humic substances. Schnitzer (1985) suggested that there are two types of N associations. The first group (~50% of the humic associated N), contains N compounds that have distinct characteristics such as amino acids, amino sugars, ammonium, nucleic acid bases, and purines. The second group includes compounds in which N is an integral part of the humic substance itself. The first group of compounds is the most likely source of the bioavailable N associated with humics (see Sections IV.C.4 and IV.D). 5. Other Organic Compounds There has been a suite of other organic compounds identified in seawater including nucleic acids, purines and pyrimidines, pteridines, methylamines, and creatine (see review by Antia et al, 1991). The nucleic acids include dissolved deoxyribonucleic acids (D-DNA) and dissolved ribonucleic acids (D-RNA). There are a number of methods used to measure nucleic acid concentrations in seawater (reviewed in Karl and Bailiff, 1989). D-DNA is produced by bacteria during growth and can be consumed by bacteria through metabolism and hydrolysis reactions involving cell-surface and extracellular nucleases (Paul et al, 1987). Most DNA is present in the nucleus of the cell, while most RNA is located in ribosomes in the cytoplasm; ribosomes are the sites of protein synthesis. Accordingly, RNA concentrations within a cell are dependent on the cell's growth rate, while DNA
184
Deborah A. Bronk
concentrations are not nearly as variable. In general, D-DNA concentrations are highest in nearshore surface waters, with concentrations decreasing with depth and distance from shore (reviewed by Karl and Bailiff, 1989). In Tokyo Bay, concentrations of both D-DNA and D-RNA decrease from the head to the mouth, and vertical profiles have surface maxima with lower concentrations deeper in the water colunm (Sakano and Kamatani, 1992). Concentrations of particulate DNA and RNA are greater than the dissolved forms, and both D-DNA and total nucleic acids (D-DNA -h RNA) concentrations are correlated with DOP concentrations. Purines and pyrimidines are heterocyclic bases that contain N. The major purine bases found in nucleic acids are adenine and quanine and the major pyrimidine bases are thymine, cytosine, and uracil. Some purines and pteridines are primary excretory products that are the end products of N catabolism (Antia et al, 1991). These compounds have received little attention in the literature. The range of concentrations reported in Antia et al. (1991) is 4-24 x 10"^ to 12.6 /xM. Methylamines are another organic compound that has received attention of late. Methylamines come in mono-, di-, and tri-methyl forms that are primary, secondary, and tertiary methylated homologs of NH3. In the Arabian Sea, concentrations of methylamines are low in oligotrophic open ocean regions and higher in productive coastal areas influenced by upwelling (Gibb et al. (1999). Concentrations of the different forms generally follow the pattern of mono- > di- > tri-methylamines (Table II; Gibb et al, 1999). Overall, methylamines contribute less than 1% of the measured DON pool, and their distributions appear to be biologically controlled with maxima in the mono- and di- forms associated with diatom abundance and microzooplankton grazing. 6. Characteristics of HMW DON The introduction of ultrafiltration techniques has greatly expanded our knowledge of the HMW DON fraction, referred to as ultrafiltered DON (UDON). Ultrafiltration through a nominal 1-kDa ultrafilter routinely isolates approximately 20-40% of total DON (Benner et al., 1992b, 1997; see Benner, Chapter 3). It is unknown how compositionally representative UDON is to the LMW fraction that passes through the ultrafilter, but based on C:N ratios and overall amino acid content, ultrafiltration does not appear to fractionate DOM in terms of major N forms (McCarthy ^r a/., 1997). UDON has a characteristic organic composition that appears to be highly conserved across the ocean basins sampled to date (McCarthy et al, 1996). Chemically, the material appears very different from that of humic substances, phytoplankton, or particles. McCarthy et al. (1997) analyzed ocean samples, with no terrestrial input, and found that retention by a 1-kDa filter ranges from 19% in the deep Pacific to 38% in Pacific surface waters and that the C:N ratio of the HMW fraction ranges from 15.6 to 18.4. By weight, 17-29% of the UDON can be
Dynamics of DON
185
recovered as hydrolyzable amino acids, and this percentage is invariant with depth (McCarthy et al, 1997). McCarthy et al (1997) analyzed the remaining 70-80% of the UDON that was not hydrolyzable using ^^N NMR and found that virtually the entire UDON fraction is amide in form. Amides are conmion linkages in major biomolecules, which do not form abiotically, indicating that the source of the bulk of HMW DON is biological. In the past, the large uncharacterized fraction of the DON pool was assumed to consist predominantly of complex macromolecules produced during biological degradation and spontaneous abiotic condensation reactions (Harvey et al, 1983). The amide fraction could be proteinaceous material that is resistant to conventional hydrolysis and could include hydrolysis-resistant amides produced by some phytoplankton (Derenne et al, 1992), acetylated amino sugars such as chitin (an important structural component of many plankton), or mureins and lipopolysaccharides (found in bacterial cell walls); A^-acetyl amino sugars have been identified as a major component of UDOM by Aluwihare et al (1997). There is also evidence for the presence of small amounts of highly stable indole-like or pyrrole-like N forms in this fraction (McCarthy et al, 1997). These forms may be derived from the bases of DNA, RNA, or the porphyrin ring of photosynthetic pigments. These data are also consistent with the presence of melanoidins, which are the end-products of abiotic sugar and amino acid condensation. UDOM material isolated from surface and deep waters in the central Pacific, Gulf of Mexico, and North Sea shows enrichment in the D enantiomers of four amino acids (McCarthy et al, 1998). These data are interpreted as evidence that peptidoglycan remnants from bacterial cell walls are a major component of the UDON pool. The material could enter the dissolved phase during bactivory by protozoans or viral infection and likely accumulates and persists because the cellwall matrix renders the material resistant to degradation. In another study of HMW material (i.e., UDOM), three phytoplankton species were shown to release HMW DOM rich in polysaccharides (Aluwihare and Repeta, 1999). The HMW DOM produced by Thalassiosira weisflogii has a C:N ratio of 14 early in the culture, but this ratio consistently decreases to a low of 5.6 after ~225 days of decomposition. Surprisingly, this suggests the accumulation of a more N-rich DOM fraction over time. In the same vein, Lara et al (1997) performed a 3-month incubation with a nonaxenic diatom culture to determine the chemical evolution of DOM. During active growth there is a net increase in DON that is largely hydrophilic in nature, and bacterial uptake of DCAA and nonamino DON is observed. In the stationary phase, DON (largely hydrophilic) is consumed but there is an increase in hydrophobic algal exudates. Lara et al (1997) found evidence for the formation of humic substances and suggested that the production of refractory DOM may begin in the hydrophilic fraction because a portion of the particulate amino N pool is transformed into hydrophilic DON during the degradation phase.
186
Deborah A. Bronk
D. CONCENTRATION AND COMPOSITION OF THE DON POOL: RESEARCH PRIORITIES The past decade has been a productive one for research into DON distributions and chemical composition. There are a number of areas, however, where additional research is desperately needed. First, there has just got to be an easier way to measure DON. As long as a DON concentration is determined by taking the difference between TDN and dissolved inorganic nitrogen (DIN) measurements, analytical errors will be a problem and our ability to resolve small but significant changes in DON will be limited. Second, there is a need for large, high-quality data sets of DON concentrations comparable to what is being assembled for DOC (see Hansen, Chapter 15). Third, the information assembled on UDON is impressive, but we must remember that this is a small fraction of the total DON pool. One of the highest research priorities should be to crack the composition of the quantitatively dominant < 1-kDa fraction, a task that will require the development of innovative isolation and concentration technologies.
III. SOURCES OF DON DON in the ocean can originate from a number of sources^both abiotic and biotic. Abiotic sources will be considered only briefly. They include terrestrial inputs, such as DON transport via overland runoff, rivers, streams, and groundwaters (Vahela et al., 1990; Tobias et ai, 2001) and atmospheric inputs (Cornell et al, 1995). Meybeck (1993) estimated that ~70% of the N entering the coastal ocean via rivers is DON (10 x 10^^ gN/year). Galloway etal (1995) predicts that future changes in local precipitation will increase the amount of DON transported to the coastal ocean via this mechanism. Recent data from a wide range of environments indicate that DON is also a substantial fraction of the N in rainwater, representing 2 to 84% of the total N deposited annually (Seitzinger and Sanders, 1999). Bioassay studies indicate that 45 to 75% of this DON is bioavailable on the time scales of days (Seitzinger and Sanders, 1999). This section will focus on biotic sources of DON in the water colunm. Each source will be reviewed, followed by methods for measuring rates of DON release, a summary of available data on release rates, and suggested research priorities for the future.
A. BIOTIC SOURCES OF DON IN THE WATER COLUMN Biotic inputs discussed in this chapter include extracellular phytoplankton production, either through active exudation or passive diffusion of metabolites through
187
Dynamics of DON
Micro/macro zooplankton
Viruses
Figure 3 Conceptual diagram of processes involved in dissolved organic nitrogen (DON) release in aquatic systems including (A) processes that are covered in this chapter and (B) additional processes not discussed.
membranes; bacterial release via active release of exoenzymes, or passive diffusion; micro- and macrozooplankton release via fecal pellet dissolution, excretion, or bactivory or sloppy feeding (i.e., trophic mediated release); and viral release via lysis both of autotrophs and heterotrophs (Fig. 3A). The information on DOC release due to grazing, virus induced lysis, and enzymatic hydrolysis of particles in Carlson (Chapter 4) are all relevant to this discussion.
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Deborah A. Bronk
Additional biotic sources that will not be considered here due to space limitations include release from macroorganismal excretion (Tupas and Koike, 1990), direct release from macroalgae (Mann, 1982; Branch and Griffiths, 1988); detrital particle release via dissolution (see Carlson, Chapter 4); and release from sediments via diagenesis (see Burdige, Chapter 13; Fig. 3B). 1. Phytoplankton When discussing DON release from phytoplankton, it is important to clearly discriminate direct release from phytoplankton, including passive or active release, from mediated release, where the phytoplankton are acted on by other trophic levels. Regarding direct release from phytoplankton, there have been two models proposed: the outflow model (Fogg, 1966) and the passive diffusion model (Fogg, 1966; Bratbak and Thingstad, 1985; Bj0msen, 1988; see Carlson, Chapter 4). Active release (i.e., overflow model) includes release of excess photosynthates that accumulate when C fixation exceeds incorporation into new cellular materials due to nutrient limitation (termed exudation by Fogg, 1983). The overflow model is unlikely to impact DON release significantly because most environments that are lacking in phosphorus (i.e., another Hmiting nutrient), generally do not have an excess of N. Other processes that would be considered direct release are release due to osmostic changes, and release of reduced inorganic or organic N in response to elevations in light (Lomas and Gilbert, 1999). A specialized form of direct release is autolysis—the disruption of cell membranes of an organism by enzymes produced by the same organism. It has been suggested that autolysis in phytoplankton may be a significant death term, and by implication, a significant source of DOM (Agusti et al, 1998). Another specialized form of release that has received little attention is protoplasm lysis during spermatogenesis, which occurs in response to N starvation (Sakshaug and Holm-Hansen, 1977; Collos, 1986). Passive release (i.e., passive diffusion model) includes the permeation of presumably LMW compounds through the cell membrane in response to the large concentration gradient that exists between intracellular and extracellular pools. Passive release would potentially vary depending on such things as physiological stress, exposure to UV radiation, temperature, and Hght levels. Bj0msen (1988) suggested that bacteria act as ectoparasites by continually assimilating extracellular DOM and thus maintaining the concentration gradient between intracellular and extracellular LMW organic pools. Hasegawa et al. (2000a) provided evidence that smaller plankton release DO^^N more efficiently than larger ones. These data support Bj0msen's hypothesis, because smaller cells have a larger surface to volume ratio. Phytoplankton can also be a source of DON when other trophic levels act on them such as during zooplankton sloppy feeding (i.e., grazing; Dagg, 1974; Lampert, 1978), and lysis due to viral infection (Bratbak et al, 1993; Murray, 1995; Gobler etal, 1997; Suttle, 1994; Fuhrman, 1999).
Dynamics of DON
189
Much of what we know about DON release from phytoplankton was learned from culture work done in the 1960s and 1970s (reviewed in Antia et al, 1991). For example, extracellular N as a percentage of total N is highest immediately after transfer of cells from one set of environmental conditions to another (Jones and Stewart, 1969; CoUos et al, 1992; Slawyk and Raimbault, 1995). If these results accurately reflect the phytoplankton's response to changing environmental conditions and are not an artifact of stressing cells during transfer, than the percentage of extracellular release in the turbulent natural environment is likely much higher than longer-term laboratory studies imply. The decline of phytoplankton blooms has also been shown to be a period of significant DOM release from phytoplankton due to such processes as physiological stress or high grazing pressure (Carlson et al, 1994; Jenkinson and Biddanda, 1995). There seems to be a pattern of low rates of release in actively growing cells, such as those found at the beginning of a bloom, and high rates of release when cells are stressed by nutrient limitation, light inhibition, etc., such as at the end of a bloom (Larsson and Hagstrom, 1979). Consistent with this scenario, Flynn and Berry (1999) found that the highest rates of DC AA release occur during stationary phase and that release of DCAA is low during active growth. Other recent work conflicts with this view, however. Biddanda and Benner (1997) found that most of the DOM produced in their cultures is released during nutrient replete conditions. In batch cultures of marine Synechococcus, grown under N-sufficient and N-deficient conditions, DOC release increases under N-deficient conditions, consistent with previous work (Bronk, 1999). Consistent with Biddanda and Benner (1997), however, Bronk (1999) found that the highest rates of DON release, both absolute and as a percentage of gross N uptake, occur during N sufficient growth, and release rates decrease by a factor of 4 to 7 when NH4+ is depleted in the medium. One specialized route of DON release that may be quite important involves vertically migrating mats of Risoselenia (Villareal et al, 1993). The mats migrate into the nitracline and fill large intracellular pools with NO3 ~. Once at the surface, the potential for DON release exists via direct release or during slopping feeding. The magnitude of DON released via this route has yet to be quantified. 2. N2 Fixers N2 fixation by Trichodesmium spp. has been shown to be a significant source of new N to tropical and subtropical marine systems in which they occur (Lipschultz and Owens, 1996; Karl et al, 1991 \ Capone et al, 1991 \ Hansell and Feely, 2000). Trichodesmium contribute to N turnover in oceanic systems both directly, through the release of amino acids, DON, and NH4"^, and indirectly through regeneration of DIN and DON by bacteria and grazers living in association with the colonies (Sellner, 1992).
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Deborah A. Bronk
In natural populations of Trichodesmium from the Atlantic Ocean and Caribbean Sea, up to half of the recently fixed N2 is released directly as DON during growth, primarily as DFAA (Capone et ai, 1994; Gilbert and Bronk, 1994). Data from the subtropical North Pacific station ALOHA also shows enrichment of N pools (NH4+, N03~, DON) within Trichodemsium blooms (Karl et ai, 1992; Letelier and Karl, 1996). In natural populations from the Caribbean Sea and cultured populations of Trichodesmium NIBB1067, lysogenic phages have also been identified that can produce cell lysis and the release of cellular contents (Ohki, 1999). Nausch (1996) estimated that 0.32 to 15 nmol N colony~^h~^ is released by peptidase and b-glucosamidase activity associated with bacteria residing among Trichodesmium colonies in the subtropical Atlantic Ocean. As one of the few known grazers of Trichodesmium spp., Macrosetella gracilis provides an important link in introducing new N from N2 fixation into the food web through sloppy feeding or excretion (O'Neil and Roman, 1992; O'Neil et al, 1996). M. gracilis ingest Trichodesmium at high rates but do not appear to make solid fecal pellets, suggesting that much of the N they release during excretion remains in the dissolved fraction. In a study in the Baltic, Ohlendieck et al. (2000) measured the accumulation of N recently fixed by two other N2fixers,Aphanizomenon and Nodularia. In two experiments in July 1995 and July 1996, they found that 7.7 ± 2.1 and 6.7 ± 2 . 1 % of the recently fixed ^^N was present in the picoplankton, indicating organic release and subsequent reincorporation. 3. Bacteria Bacteria are generally thought of as DON consumers, but they can also be important producers and remineralizers of DON as noted above. Berman et al. (1999) demonstrated that urea (and NH4"^) can be produced from DON by natural bacterial populations or via extracellular enzymes from DON in Lake Kinneret, the Charente Estuary, France, and the French coast of the Atlantic. Addition of guanine, hypoxanthine, and arginine results in significant increases in urea concentrations; the organic compounds were added at environmentally unrealistic levels (40 /JLM), however, which raises questions as to the importance of this process in the environment. Carlsson and GraneU (1993) and Carlsson et al. (1993) also provide evidence that DON is utilized by phytoplankton indirectly through bacterial incorporation of the DON and then release of NH4"^ during bactivory. In another study, J0rgensen et al. (1999) documented urea release in bioassays in the Gulf of Riga. Bacteria are also known to release DON through the mineralization of organic aggregates (Smith et al., 1992). Therkildsen et al. (1997) measured urea production in commercially available cultures of two marine bacteria and found that the highest accumulation occurs during the growth deceleration phase and at the beginning of stationary phase. They argued that internal RNA provides the precursors for the release of urea.
Dynamics of DON
191
During growth, the intracellular RNA pool is dynamic with some portion of it being degraded to urea and NH4+, particularly during exponential growth (Mason and Engli, 1993). 4. Micro- and Macrozooplankton The processes of grazing and bactivory are known to be important in transforming and partitioning C and N within planktonic systems (see reviews by Nagata, 2000; and Strom, 2000). These processes can result in DON release via sloppy feeding (Dagg, 1974; Lampert, 1978) or bactivory, where cells are not ingested whole but are broken, resulting in release of dissolved intracellular materials, via excretion, where DON compounds are released as waste (Miller and Gilbert, 1998; Conover and Gustavson, 1999) or via diffusion away from or the dissolution of fecal pellets (Jumars et al, 1989; Fig. 3A). Microzooplankton tend to ingest whole cells, such that the release of DOM during sloppy feeding is relatively minor, although some workers have found that microzooplankton enhance DOM fluxes as well as influence the composition of the DOM pool (Flynn and Davidson, 1993; Strom et al, 1997). In the studies reviewed in Table IV in Carlson (Chapter 4), 9 di 6% (n = 5) of the N ingested by a number of microzooplankton species is released as DFAA or DFAA and DCAA. Ferrier-Pages et al (1998) measured release of DPA from two flagellates (Strombidium sulcatum, cilitate, and Pseudobodo sp., aplastidic flagellate) grazing on bacteria in culture. They found high rates of DPA release during the exponential phase, when ingestion rates were at a maximum, but lower rates during the other growth phases. In another bactivory study, Alonso et al. (2000) found rates of up to 281 /xg DNA L~^ h~^ in bacterial cultures with the ciliate Uronema sp. and the flagellate Pseudobodo sp. In the Adriatic Sea, concentrations of D-DNA and nanoflagellates were found to covary during a study of diel dynamics, and D-DNA release rates increase sixfold when the nanoflagellate, Ochromonas sp., is present
ilm^etal,
1992).
In contrast to the microzooplankton, it is generally believed that sloppy feeding by macrozooplankton is responsible for the generation of significant amounts of labile DOM (Dagg, 1974; Lampert, 1978; Urban-Rich, 1999). In Table IV in Carlson (Chapter 4), macrozooplankton release 11 ± 12% (n = 11) of their body N as DON, often measured as DFAA, urea, or DCAA. In other studies, 25 ± 12% (n = 6) of the TDN released is organic in form (Table IV in Carlson, Chapter 4). The relative coupling of C and N during this release, however, is poorly known. Daly et al (1999) suggested that C and N release by copepods results in quantitatively different fluxes of DOC and DON, which ultimately results in nonRedfieldian ratios within those pools. Lampert (1978) found that 4 to 17% of particulate organic C (POC) Daphnia pulex ingested was released as DOC as a result of sloppy feeding alone. Release is
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independent of excretory processes or diffusion or dissolution of fecal pellets and is highly dependent on the size and morphology of the phytoplankton prey—^those algae that can be consumed whole release 3.5 to 4.0% of their POC as DOC while those that cannot be consumed whole release 10 to 17% of their POC as DOC. Similar studies have not been done with DON. It has been hypothesized that the majority of DOM diffuses away from fecal pellets within minutes of its release, assuming that the peritrophin membrane surrounding the pellet is permeable (Jumars et al, 1989). The mucus coating of some fecal pellets, however, may restrict this avenue of exchange. Other studies suggest that fecal pellets must be broken up mechanically before a substantial amount of DON is released (Lampitt et al, 1990; Strom et al, 1997). Urban-Rich (1999) measured abiotic and biotic release from copepod fecal pellets using ^"^C tracers in the Greenland Sea and found that 86% of the DOC is utilized or leached from fecal pellets in the first 6 h. Shorter term incubations were not done, however, that could address the issue of time scale raised by Jumars et al (1989). Roy et al (1989) investigated the release of DFAA during sloppy feeding by two copepod species fed a large diatom, known to have large intracellular pools. Although the presence of particulate debris indicates that sloppy feeding occurs, total DFAA concentrations and extracellular composition are not significantly different after copepod grazing. This suggests that the DFAA released are rapidly taken up by bacteria or other cells or that adsorption onto debris produced by the copepods occurs. Fuhrman (1987) found that combinations of copepods and microplankton had a much higher release rate of DFAA than either alone (Table V). He also found that release of DFAA due to sloppy feeding by copepods or excretion can be similar in magnitude to direct release by microzooplankton. In estuarine mesocosms, rates of urea and DPA release from the copepod Acarr/a tonsa tend to be higher during early morning and early evening and are of the same order of magnitude as NH4"^ regeneration (Miller and Gilbert, 1998). Micrograzers are important agents of DON release and bacteria rapidly consume 58 to 103% of the recently released DON in Japanese coastal waters (Hasegawa et al, 2000b). The magnitude of DON release is ~40% of the rate of NH4+ regeneration in the Southern California Bight and Monterey Bay (Bronk and Ward, 1999) and 59% of NH4+ regeneration in Japanese coastal waters (Hasegawa et al, 2000b). A tight positive correlation between rates of DON release and NH4+ regeneration (P<0.00001) has also been observed, suggesting that the same process is likely responsible for both (Ward and Bronk, 2001). 5. Viruses Viruses are unique in that they can be agents of DON release while being a component of the DON pool itself. Viruses are contributors to DON production because in the final stages of viral infection, the phage increase to such numbers
Dynamics of DON
199
within the cell that the cell bursts, releasing its cellular contents. Viruses may influence both the production of DOM, through lysis, as well as the character of DOM by shaping the metabolic characteristics of primary and secondary producer communities (see reviews by Fuhrman, 1999; Wommack and Colwell, 2000; Fuhrman, 2000; see Carlson, Chapter 4). Viruses typically outnumber their potential autotrophic and heterotrophic hosts by at least a factor of 10 making them the most abundant component of the plankton with concentrations ranging from 10^ to 10^^ viral particles L~^ (Wommack and Colwell, 2000). While estimates of virus-mediated mortality exhibit a wide range, studies indicate that 10 to 20% of heterotrophic bacteria and 3-5% of phytoplankton are lysed daily due to viral infection (Suttle, 1994). A conceptual model of the incorporation of viruses and viral lysis into the aquatic food web was offered by Wonmiack and Colwell (2000) that emphasizes the importance of viral lysis in enhancing the flux of autotrophic and heterotrophic biomass into the DOM pool (Fig. 4). Each lysis event releases the entire contents of the host cell into the DOM pool in the form of macromolecules, cell organelles, and viral particles, making viral lysis a highly efficient mechanism for transferring living biomass to the DOM pool. The efficiency of this transfer is large when one considers that only one virus from each lysis event needs to survive to infect another host in order to maintain the lytic cycle (Fuhrman, 1992). The theoretical effect of viral lysis is to divert C and N, fixed by phytoplankton and transformed into bacterial biomass, away from zooplankton consumers into the DOM pool (Fuhrman, 1992; Bratbak et al, 1994; Murray and Eldridge, 1994; Fuhrman and Noble, 1995). Numerous studies have been done to examine the effects of viral lysis on the flux and composition of the DOM pool. In mesocosm experiments it was found that phage lysis products stimulate bacterial growth and metabolic activity, indicating that viral lysis can contribute to a loop in which a portion of available nutrients cycle between the DOM pool and bacterial biomass without contributing to higher trophic levels (Middelboe etal, 1996). In another study, viral lysis of a chrysophyte alga (Aureococcus anophagefferens) was responsible for significant changes in the partitioning of nutrients (i.e., C, N, P, Fe, and S), between dissolved and particulate phases (Gobler et al, 1997). Similarly, Bratbak et al (1998) found that viral lysis of Phaeocystis pouchetii cultures results in a nearly complete conversion of lost algal biomass to bacterial biomass through production of excess DOC. Finally, changes in DOM composition with viral lysis have been demonstrated in mesocosm experiments. Slight (i.e., 2.5-fold) increases in virioplankton concentration results in measurable changes in the chemical characteristics of the DOM compared to unamended controls (Weinbauer and Peduzzi, 1995). These changes are likely due to the increased incidence of viral lysis in virus-enriched mesocosms. As an interesting twist on phytoplankton DOM release, Murray (1995) used a modeling approach to suggest that DOM exudation can be a cost-effective, indirect means of reducing viral infection in phytoplankton. The reasoning is that DOM
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Deborah A. Bronk
Figure 4 Conceptual model of the incorporation of viruses and viral lysis into the microbial loop as presented by Wonmiack and Colwell (2000).
exudation supports bacterial populations that can kill viruses, which the bacteria contact with much greater frequency because of their small size. If DOM exudation leads to a reduction in phytoplankton losses from infection greater than the cost of the exudation, then DOM exudation is a cost-effective strategy.
B. METHODS FOR ESTIMATING BIOTIC DON RELEASE RATES To measure rates of DON release and uptake there are two main methodsmonitoring changes in ambient concentrations and ^^N tracer techniques. In the
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201
first method, samples are collected and the concentration of DON or individual DON components are monitored over time. To measure DON flux rates using ^^N tracer techniques, all of the DIN forms (NH4+, NO3 ~, and NO2 ") must be removed, and the DON pool must be isolated with a high efficiency. At present, there are three basic approaches used to isolate DON—wet chemistry, ion retardation, and dialysis. 1. Wet Chemical Isolation Axler and Rueter (1986) introduced the wet chemical approach, and various permutations have been appHed by later researchers (Slawyk and Raimbault, 1995; Bronk and Ward, 1999). In this approach, NH4"'" is removed by raising the pH slightly, thus effecting a change from soluble protonated NH4"^, to the more volatile NH3 via diffusion in a heated oven (Slawyk and Raimbault, 1995) or vacuum distillation (Bronk and Ward, 1999). Nitrate in the sample is converted to NHswith DeVarda's alloy, with the NH3 again removed through volatilization (Slawyk and Raimbault, 1995; Bronk and Ward, 1999). Both of these techniques can suffer from the artifact of losing labile DON as a result of base hydrolysis (Bronk and Ward, 2000). The problem in the isolation is likely the lengthy diffusion step undertaken to remove NH4+ and N03~/N02~ from solution. My own lab has investigated a suite of other protocols to remove NO3 ~/N02 ~, including vanadium (VIII; Cox, 1980; Garside, 1982), titanium (Tilll, Cresser, 1977; Cox, 1980), and other DeVarda's alloy approaches (Page et al, 1982). The breakdown and loss of DON is a perpetual concern due to the rigorous reducing conditions necessary to effect the loss of N03~. For example, some researchers use diffusion in a heated oven as a way of removing labile DON before isolation of N03~ (Sigman et al, 1997). Potential artifacts during wet chemical DON isolation and the different types of DON release rates and their calculation protocols were recently reviewed by Bronk and Ward (2000) and are not considered here. 2. Ion Retardation The ion retardation method uses a resin (BioRad AG 11 A8) that retards the flow of charged particles. Originally developed for desalting blood samples, the resin can quantitatively remove salts, including NH4"^, N03~, and N02~, allowing DON to be isolated in the eluate (Bronk and Gilbert, 1991, 1993b; Hu and Smith, 1998; Nagao and Miyazaki, 1999). Unfortunately, DOW Chemical, the company that manufactured the resin marketed by BioRad and other distributors, changed the manufacturing process of the resin such that the recently produced resin retains variable amounts of DON. This DON retention is believed to be due to an accumulation of an organicfilmon the resin beads during manufacturing (BioRad, pers. commun.) To overcome this problem, AG 11A8 resin can be manufactured and purified
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Deborah A. Bronk
by buying another resin (Dowex anion exchange resin, BioRad AG1-X8) and then chemically altering it to produce AG 11 A8 as described in Hatch et al. (1957). 3. Dialysis Another technique that has been considered for isolating DON is dialysis. Feuerstein et al. (1997) developed a method to isolate DON in freshwater samples, which uses rotary evaporation to preconcentrate the DON followed by dialysis (100-Da cutoff) to remove DIN; no data on marine samples were presented. Drawbacks of the dialysis approach are that the amount of time it takes to remove DIN (100 h for freshwater; 216 h for marine samples) is excessive, the removal is never absolute, and the risk of bacterial or N contamination is substantial. My own lab has experimented with microdialysis to desalt isolated DON before mass spectrometric analysis, but found that the pores did not maintain their integrity at high ionic strengths.
C. LITERATURE VALUES OF DON RELEASE RATES IN A Q U A T I C ENVIRONMENTS
DON release rates can vary widely within and between systems as reviewed in Tables IV and V. In most cases, these rates were measured using whole water samples, and the specific processes that produced the measured rates are unknown (see Section III.A). 1. Bulk DON The mean rate of DON release is similar for both oceanic and coastal systems at ^40 ng-at N L~^h"^ though the range is large (Table IV), These rates are compared to rates of gross N uptake. Gross N uptake is the total amount of N taken up by cells regardless of whether its ultimate fate was PN production or DON production (Bronk et al, 1994). This is in contrast to a net N uptake rate, which is the rate traditionally measured with ^^N tracer techniques that only includes PN production (Bronk et al, 1994). As a percentage of gross N uptake, DON release appears similar in oceanic and coastal environments with 41 ± 20 and 39 ± 26% of gross N uptake released as DON, respectively (Table IV). Mean rates of release tend to be higher in estuarine environments, ^^72 ng-at N L~^h~\ but again the range is large. Based on the limited data available, the percentage of gross N uptake released as DON in estuarine systems appears to be lower than the other systems at 23 lb 8% (Table IV). Collectively these data suggest that DON release is a significant flux through marine and aquatic systems.
203
Dynamics of DON Table V Summary of Published Release Rates of Individual Organic N Compounds in the Field Location Oceanic Bering Sea Caribbean Sea Southern California Bight Southern California Bight (upper 5 m) Southern California Bight (upper 5 m) Coastal Long Island Sound Long Island Sound Long Island Sound Long Island Sound Long Island Sound Long Island Sound Estuarine Chesapeake Bay Chesapeake Bay Chesapeake Bay Chesapeake Bay mesohaline
Date
Compound released
NP
Release rate (ng-atNL-^h-l)
Method
Reference
Urea
73.8 ± 30.6
i^Nand^^c
Hansen and Goering, 1989
Urea
11.17'^
14c
Cho etal, 1996
September Urea
0.002 to 0.014^
14c
Cho and Azam, 1995
September Urea
0.002 to 0.045^^
14c
Cho and Azam, 1995
November 1988
October 1983 October 1983 October 1983 November 1984 November 1984 November 1984
Alanine
1.3^
[^HJala
Fuhrman, 1987
Alanine
30^
[^HJala
Fuhrman, 1987
Alanine
<0.1^
[^HJala
Fuhrman, 1987
ala, glu, gly, ser ala, glu, gly, ser ala, glu, gly, ser
9.9^
[^HJala
Fuhrman, 1987
17.7^^
[^HJala
Fuhrman, 1987
6.2^
[^HJala
Fuhrman, 1987
Spring
Urea
480 ± 200
l^N or i^N/i^C Lomas et al,
Summer
Urea
670 lb 180
1 5 N or i^N/i^C Lomas et al,
Winter
Urea
1630 ± 820
May 1988
Urea
0 to 377
in press in press iSNor^^N/i^c Lomas et al, in press 15N/14C Bronk et al, 1998 {Continues)
Deborah A. Bronk
204
Table V (Continued) Location Chesapeake Bay, mesohaUne Chesapeake Bay, mesohaline
Date August 1988 October 1988
Compound released
Release rate (ng-atNL~^ h~^)
Method
Reference
Urea
164 to 794
15N/14C
Urea
0 to 1478
15N/14C
Bronk et al, 1998 Bronk et al, 1998
Note. Data was taker\ directly from tables, estimated from graphs, or obtained from the author's directly. Data are presented as mean ± standard deviation. ^ Bacterial release. ^ <202 /xm fraction. ^ <202 Atm fraction + added (125-150) copepods. ^ <0.22 Atm fraction + added (125-150) copepods.
As seen in Table IV, the percentage of gross N uptake that can be released as DON can at times be quiet high (i.e., 90%). Slawyk et al. (2000) contend that such high percentages of release are "impossible," though I disagree with both their assumptions and their calculations. Analogous to the release of DOC as a percentage of primary production, the percentage of release directly from phytoplankton is likely fairly low, as seen in many of the culture studies presented in Table IV. One would expect that this percentage can increase substantially, however, when other trophic levels act on the phytoplankton such as during sloppy feeding and viral infection (see Carlson, Chapter 4). Though these high rates may not be sustainable, they are clearly possible. Rates of DON release that result from either NH4+or N O B " incorporation can be measured using ^^N tracer techniques. Of the studies presented in Table IV, a higher percentage of gross NO3 ~ uptake is released as DON relative to incubations where NH4"^ is the substrate in 7 of 11 cases. Vertical profiles of DON release rates vary. In the Gulf of Lions, DON release is generally higher in surface waters and lower at depth (Diaz and Raimbault, 2000). In Monterey Bay, the percentage of N released as DON increased with depth, suggesting that deeper in the water column, a smaller percentage of the N taken up is incorporated into sinking particles (Bronk and Ward, 1999). The fate of N uptake also appears to change. In Monterey Bay, the primary fate of N uptake is particle production in March but DON production in September (Bronk and Ward, 1999). These data suggest that the DON pool acts as an intermediate between DIN assimilation and the net formation of particles for export and will thus affect C flow in Monterey Bay. In the Choptank River, a subestuary of Chesapeake Bay, rates of total DON release are significantly higher in a <202-/>im fraction relative to the <1.2-/xm plankton likely due to feeding processes associated with the larger size fraction (Bronk and Gilbert, 1993b). Evidence for feeding induced DON release in the
Dynamics of DON
205
<202-/xm fraction includes a low ratio of LMW DON to total DON release, an increase in DON release rates at night when grazing tends to be higher, and a doubling of phaeopigment concentrations during the 36-h experiment, which are an indicator of active grazing. In contrast, rates of LMW DON release in the < 1.2-/xm plankton are not significantly different from rates of total DON release and rates of DON release decrease by over 95% in the dark, suggesting that passive release from autotrophs is a more important release process. In another study in Chesapeake Bay, the average rates of DON release are remarkably constant from season to season, although, within a diel period, there is considerable variability. DON release also often appears to decrease at night, although the difference is not statistically significant (Bronk et al, 1998).
2. Urea Urea has been shown to be excreted by chryptomonads, herbivorous marine zooplankton, oceanic and lake microzooplankton, bivalve muUuscs, marine and freshwater teleost fish, and freshwater crabs (Antia et al, 1991). In the Bering Sea, in situ production of urea is approximately equal to the consumption of urea (Hansell and Goering, 1989). In the central channel of Chesapeake Bay, rates of urea regeneration are generally less than rates of NH4+ regeneration, but, at the highest rates measured, urea regeneration can contribute 100% of the phytoplankton N requirement (Bronk et al, 1998). Lomas et al (in press) reviewed rates of urea regeneration in Chesapeake Bay and found that mean bay wide surface urea regeneration rates are highest but most variable during the fall. In the Southern CaUfomia Bight, urea decomposition is significant deeper in the water column, particularly at the base of the euphotic zone, and the activity is primarily in the bacterial size fraction (Cho and Azam, 1995). These data suggest that urea is an important intermediate between sinking particles and release of NH4+ mediated by bacteria in the mesopelagic.
3. DCAAandDFAA DCAA and DFAA are other important organic release products. In cultures enriched with DIN, extracellular DFAA often accumulate with the highest concentrations generally present during stationary phase (Poulet and Marine-Jezequel, 1983; Myklestad et al, 1989). Diatoms showed the highest rates of DFAA excretion during exponential growth (Myklestad et al, 1989, and references therein). The types of amino acids released from Chaetoceros affinis (diatom) changes during exponential growth relative to stationary growth (Myklestad et al, 1989). In cultures of Phaeodactylum tricomutum, DFAA accumulate extracellularly.
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Deborah A. Bronk
particularly glycine, threonine, and serine, which are all important in cellular respiration or are components of cell walls that are likely resistant to decomposition {MaisotetaL, 1991). Amino acid enantiomeric ratios have also been used to infer DOM release by capitalizing on the fact that eukaryotic organisms release exclusively the L enantiomer. The DCAA in refractory DOM generally has a low L/D ratio of 3 to 4 (Lee and Bada, 1977; McCarthy et al, 1998; II.C.3). Significant phytoplankton release, however, can increase the L/D ratio up to 8, making the ratio a useful indicator of new DOM production. 4. Release of DON Relative to DOC Relatively little is known about the relationship of DOC to DON release. In general, ^5-30% of primary production is directly released as DOM by phytoplankton though the range is very broad (Baines and Pace, 1991; also see Carlson, Chapter 4). In the studies presented here, a mean of 22 to 41 % of gross N uptake is released as DON, but as with DOC, the range is very broad (see Section III.C.l). If phytoplankton maintain a C:N ratio of approximately 6.6, and they are ultimately the primary source for released DOM, then it is reasonable that the C:N of DOM release should be ~6.6 over appropriate space and time scales (see Karl and Bjorkman, Chapter 6). In Chesapeake Bay, combined DOC and DON release rate data indicate that recently released DOM has an approximate C:N ratio of 3.3 in May, 5.0 in August, and 4.7 in October (Bronk et al, 1998). This low C:N ratio is consistent with an apparent accumulation of N-rich DON in the Bay from May to August as observed in the ambient DOC and DON pools. Carlson et aL (2000) reported that DON in excess of background (i.e., winter) concentrations has a C:N ratio of 6.7. S0ndergaard etal. (2000) performed mesocosm experiments to investigate DOC and DON accumulation under a range of conditions over time. Following an 11 -day time lag, the concentration of DON increases linearly (r^ = 0.88-0.89) with time in all treatments (added N, P, glucose, and various combinations of the three). The average DON production rates for all treatments, except for the high N addition treatment, is 0.28 /xM day ~^and the released DOM has a C:N ratio of 11. In the high N addition treatment (5 x the amount added to the rest of the treatments) the rate of DON production increases to 0.74 IJM day~^with a DOCiDON ratio of the released material of 20.
D. SOURCES OF DON: RESEARCH PRIORITIES Clearly there is much work to be done quantifying rates of DON release and, more importantly, systematically defining the mechanisms that produce the
Dynamics of DON
207
measured rates of release. Along these lines, a quick nondestructive means of isolating DON in quantities sufficient for mass spectrometric analysis remains one of the holy grails of marine N research. Such a method could be used to isolate DON in tracer experiments, as well as provide a way to limit analytical error in the measurement of DON concentrations in areas where inorganic N is high, such as the deep ocean. Other areas that should be a high priority for future research are linking DOC with DON release in laboratory growth experiments and in the field, quantifying the role of viruses in DON release, and defining the rates and pathways involving micro- and macrozooplankton in DON release (i.e., sloppy feeding versus excretion versus fecal pellet dissolution). Most of this latter work is fairly straightforward and doable with existing methods. Quantifying virus mediated release, however, will be challenging, particularly in developing appropriate experimental controls.
IV. SINKS FOR DON To date, most studies of N uptake in aquatic systems have focused on DIN, and the studies of DON utilization that have been done have focused on labile LMW DON compounds (i.e., DFAA and urea), which are generally present at very low concentrations. Three main sinks for DON will be considered here—heterotrophic uptake, autotrophic uptake, and abiotic photochemical decomposition (Fig. 5). Here I present the evidence for heterotrophic versus autotrophic use of DON and
Phytoplanldton
Figure 5 Conceptual diagram of processes involved in dissolved organic nitrogen (DON) utilization in aquatic systems.
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Deborah A. Bronk
the role of cell-surface enzymes, discuss a possible link between DON and harmful algal blooms (HABs), review important considerations in measuring DON uptake, and present a survey of recently published estimates of DON uptake rates. The section concludes with a review of photochemical N release and suggested areas for future research.
A. HETEROTROPHIC VERSUS AUTOTROPHIC DON UTILIZATION Heterotrophic bacteria have traditionally been considered the primary users of DON in marine systems. Several aspects of DOM use by bacteria have recently been reviewed in Williams (2000) and Carlson (Chapter 4). Therefore, I will focus the bulk of my review on the emerging role of DON as a source of N for autotrophs. 1. Heterotrophs Studies have shown that bacteria can utilize dissolved proteins and DCAA, and that DFAA can support a large fraction of bacterial growth in freshwater and marine systems (see Carlson, Chapter 4). Most bacteria can take up only inorganic or small organic compounds (Antia et al, 1991). Therefore, extracellular hydrolysis is necessary before the bulk of the water column DON can be used for growth by these organisms (see review by Miinster and De Haan, 1998). Rates of peptide hydrolysis can determine the supply of free amino acids available for uptake or extracellular oxidation. Similarly, rates of amino acid oxidation may be an important control affecting the supply of NH4"*'. A number of methods have been developed to detect proteolytic activity in seawater and sediments, including peptidelike fluorogenic compounds such as leucine-methylcoumarinylamide (Leu-MCA), which have been used to measure aminopeptidase activity (Hoppe, 1983). Additionally, combined hydrolysis and uptake of radiolabeled proteins and peptides have also been measured (Hollibaugh and Azam, 1983; Keil and Kirchman, 1999). A fluorescently labeled peptide was recently synthesized and tested in seawater and sediments (Pantoja et a/., 1997, Pantoja and Lee, 1999). This compound, Lucifer yellow-labeled tetraalanine, has the advantage of allowing one to follow both hydrolysis and product formation; it is specific for peptide hydrolysis as it competes with natural peptides for hydrolysis. 2. Autotrophs It has been argued that if even a small fraction of the large DON pool were utilizable by phytoplankton as a N source, then N-sufficient cells could exist in waters having undetectable DIN concentrations (Jackson and WiUiams, 1985). The role that DON plays as a N source for autotrophs, however, is still under
209
Dynamics of DON
debate, as are the potential mechanisms of utiHzation—^bacterial ammonification and subsequent phytoplankton uptake of the released N or direct incorporation via cell surface enzymes (Fig. 5). Bacterial degradation of DON followed by phytoplankton uptake of the released compounds has been demonstrated by a number of researchers (Berman et al, 1991; Antia et ai, 1991; letswaart et al, 1994; Lisa et al, 1995; Palenik and Hensen, 1997; Berman et al, 1999). When the decomposition results in NH4+ production, the process is known as ammonification. Direct uptake of DON, without bacterial mediation, was considered to be relatively minor. Research over the past decade, however, requires that this assumption be reevaluated. A number of phytoplankton species have been shown to possess cell surface amine oxidases, which can cleave amino groups from amino acids and primary amines (Palenik and Morel, 1990a,b, 1991; Fig. 6). The resulting alpha-keto acids (from amino acids) or aldehydes (from primary amines) are released as potential C sources for bacteria. This scenario illustrates that, though studies with ^"^C-labeled organic compounds result in transfer of the label to the bacterial fraction, these results cannot necessarily be extrapolated to include utilization of the associated amino N. MulhoUand et al. (1998) quantified extracellular amino acid oxidase activity in natural waters from a number of oceanic and estuarine systems using a fluorescent analog of lysine (Pantoja and Lee, 1994). The highest rates of oxidase activity were observed in mesocosms during bloom-like conditions and in samples enriched with Trichodesmium. The resurgence in interest in autotrophic DON utilization has fostered a return to classical culture work (see Antia etal, 1991). One of the common problems with
Amine oxidase Figure 6 Conceptual diagram of phytoplankton amine oxidase activity (adapted from the work of Palenik and Morel, 1991). The enzyme catalyzes the decomposition of an amine at the surface of a phytoplankton cell resulting in the release of ammonium (NH4"'"), a keto acid, and hydrogen peroxide (H2O2). The amine is shown labeled with ^"^C to illustrate that in a tracer experiment, the amine will appear to be used by the bacterial fraction, while the N may actually be utilized by the phytoplankton.
210
Deborah A. Bronk
much of the early cuhure work, however, was that the concentrations of organic N compounds offered to phytoplankton as sole N sources were much higher (at times two to three orders of magnitude higher) than the concentrations of these compounds present in the environment. Though the studies show that a suite of organic N compounds can be a N source for phytoplankton, it is believed that at the very low concentrations of these compounds present in the environment, bacteria, with their superior surface to volume ratio and uptake capabilities, outcompete phytoplankton for their use. For example, John and Flynn (1999) quantified DFAA uptake by the toxic dinoflagellate Alexandrium fundyense and found that, though it can use DFAA as a N source, DFAA cannot support substantial growth at the concentrations found in the environment. This study reinforces the necessity of using environmentally relevant concentrations in cultures. Recent culture studies have shown that Aureococcus and Nannochloris sp. can grow on glutamic acid as its sole N source (Dzurica et al, 1989). A host of organic N compounds, including hypoxanthine, acetamide and formamide, can also support growth in the ubiquitous coccolithophore, Emiliania huxleyi, although the substrates were added at 100 /^M levels (Palenik and Henson, 1997). They suggest that small amides are transported into the cell and then degraded to produce NH4^ through the use of amide-specific enzymes. Results from other studies of E. huxleyi suggest that organic N use might be strain specific. For example, some strains grow well on amino acids (Flynn, 1990) while others do not (lestwaart et al, 1994). Palenik and Koke (1995) found that N starvation in E. huxleyi induces a cell-surface protein (NPRl) that is present when cells are growing on organic N forms (urea and purines) but not when cells are growing on DIN, raising the question of its possible role as an organic N transporter. A number of phytoplankton species from Lake Kinneret, Pediastrum (Chlorophyta), Cyclotella (diatom), and Aphanizomenon ovalisporum (cyanobacteria), also grow well on a number of organic N compounds, including urea, ornithine, lysine, glucosamine, hypoxanthine, and quanine (Berman and Chava, 1999). Again, however, experiments were done with 100 /xM substrate additions such that relating the results to natural waters is questionable. 3. Potential Link between DON and Harmful Algal Blooms Much of the work on DON utilization in the recent past has been tied to DON's potential as a N source to phytoplankton that can form HABs. There is increasing evidence linking DON additions with the increase in harmful algal species (Paerl, 1988; Berg et al, 1997; Carlsson et al, 1998). In general, diatom abundance tends to correlate with high NO3" concentrations (Malone, 1980; Kokkinakis and Wheeler, 1988; Probyn etal, 1990), while low NOs" concentrations and high rates of NH4"^ or DON addition tend to correlate with high microflagellate abundance (Probyn, 1985; Paerl, 1988; Lomas and Gilbert, 1999; Carlsson era/., 1998; Gilbert
Dynamics of DON
211
and Terlizzi, 1999). Dinoflagellates, in particular, are characterized by diverse nutritional strategies (Schnepf and Elbracter, 1992; see review of mixotrophy by Caron, 2000), and a number of dinoflagellate species can use organic nutrients, such as urea and amino acids, both directly (Butler et al, 1979; Berg et al, 1997) and indirectly, via cell-surface enzymes (Palenik and Morel, 1990a,b; Pantoja and Lee, 1994; MulhoUand et al, 1998). Three toxic species that have received considerable attention are the brown tide Aureococcus anophagejferens (a pelegophyte), Gymnodinium breve (a dinoflagellate), and Pfiesteria piscicida. A. anophagejferens has been prevalent along the Northeast Atlantic coast for over 15 years (Bricelj and Lonsdale, 1997). A number of studies have implicated DON in initiating the blooms (Dzurica et al, 1989; Berg et al, 1997; LaRoche et al, 1997) with particular emphasis on urea utilization (Dzurica et al, 1989; Berg et al, 1997). Berg et al (1997) found that organic N comprised 70% of the total N utilized, with the largest portion of N utilization supplied by urea, during an A. anophagejferens bloom off Long Island. In contrast, Gobler and Saiiudo-Wilhelmy (2001) found that urea additions did not increase the relative abundance of A. anophagejferens while glucose additions did. They suggest that DON additions with higher C:N ratios than urea (i.e., amino acids or amino sugars) may be more likely to trigger a brown tide bloom. Brown tides off Long Island are found to commonly occur in drought years when N03~ inputs are reduced and DON concentrations are high relative to DIN (LaRoche et al, 1997). Gilbert and Terlizzi (1999) found that high urea levels (> 1.5 /xM) cooccur with dinoflagellate blooms in aquaculture ponds. G. breve, like other dinoflagellates, can also take up a variety of organic N compounds (e.g., vitamins, amino acids) as N sources for growth (Steidinger et al, 1998). In cultures of G. breve, cell yields increase dramatically when glycine, leucine, and aspartic acid are added (Shimizu et al, 1995). Likewise, the kleptoplastidic (when functional chloroplasts are retained from algal prey) Pfiesteria piscicida can use DIN, urea, and glutamate in culture (Lewitus ^r«/., 1999).
B. METHODS FOR ESTIMATING BIOTIC DON UPTAKE DON is difficult to study as a N source because it is composed of a large number of compounds and the exact composition is unknown (Gardner and Stephens, 1978; Sharp, 1983; Antia et al, 1991). As a result, measurements of DON uptake rates have largely been limited to a few compounds which have commercially available ^^N, ^"^C, or ^H tracers such as amino acids or urea (Fuhrman, 1987; Hansen and Goering, 1989; Wheeler and Kirchman, 1986; Cochlan and Harrison, 1991; Antia et al, 1991). Bronk and Gilbert (1993a) developed a method for manufacturing ^^N-labeled DON produced in situ, which involves incubating a whole water sample with ^^N-labeled NH4+or NO3". The recently released DO^^N
212
Deborah A. Bronk
is then isolated using ion retardation resin (see Section III.B.2) and subsequently used as a tracer to quantify DON uptake rates. Much of the recent work focusing on the bulk DON pool used a bioassay approach, where changes in ambient and added DON are monitored over time (Seitzinger and Sanders, 1997). Bioassay approaches are particularly useful in determining the biological availability of more recalcitrant organic N compounds, such as humic substances (Carlsson and Graneli, 1993; Carlsson et ai, 1995).
C. LITERATURE VALUES OF DON UPTAKE IN A Q U A T I C E N V I R O N M E N T S
Consideration of organic N uptake is slowly becoming a routine part of many field programs. Here, uptake rates of bulk DON (i.e., the total DON pool), urea, DCAA and DFAA, humic substances, and other DON compounds are discussed. 1. Bulk DON Most of the work done on bulk DON utilization has been in freshwater systems using a bioassay approach. This work suggests that 12 to 72% of the DON pool is bioavailable on the order of days to weeks. In the Delaware and Hudson Rivers, 40-72% of the DON is consumed during 10- to 15-day dark bioassays, and DON consumption results in both an increase in PN and the release of DIN (Seitzinger and Sanders, 1997). These data suggest that the bioavailable DON can be utilized within estuaries with residence times on the order of weeks to months. In systems where residence times are shorter, riverine DON will be a source of bioavailable N to coastal waters. Stepanauskas et ai (1999a) measured the concentration and bioavailability of three MW DOM fractions in samples collected seasonally in Swedish wetlands. The percentage of bulk DON represented by the different fractions ranges from a mean of 23 % for the HMW fraction to a low of 6% for LMW DON. They found that bioavailable DON is higher in seawater than in freshwater and that bioavailability does not correlate with the C:N ratio of the DOM. The percentage of the different fractions that are bioavailable in seawater cultures are 12 ± 4, 7 ± 3, 5 ± 4, and 16 ± 8% for bulk, HMW, intermediate, and LMW DON, respectively. In additional studies in wetlands, the addition of natural DON stimulates cell-specific AMPase activity; refractory and humic-rich DOM causes a stronger stimulation than other forms believed to be more labile (Stepanauskas et al, 1999b). AMPase activity is twofold higher in seawater, relative to freshwater, indicating that hydrolysis and turnover of terrestrial DON may increase when it enters the coastal ocean (Stepanauskas ^r (2/., 1999b).
Dynamics of DON
213
In two streams in Sweden, 19-55% of the bulk DON is bioavailable in short-term bioassays (Stepanauskas et ai, 2000). Only 5-18% of the DON is identified as urea, DCAA, or DFAA, suggesting that bacteria also utilize other organic N compounds. Potential DON bioavailability is positively correlated with the concentration of DCAA and the proportion of L-enantiomers in amino acids. In 7- to 8-day bioassay experiments in the Gulf of Riga, an average of 77% (8-136%) of the bacterial N biomass accumulation is a result of DCAA and DFAA uptake, and 13% of the DON is bioavailable during the study (J0rgensen et al, 1999). Bronk and Gilbert (1993a) used ^^N-labeled DON produced in situ in Chesapeake Bay and found that during the decline of the spring bloom, uptake rates of DON are higher than uptake rates of NH4+ and NO3". In August, rates of DON uptake are again higher than uptake rates of NOa", though not higher than NH4"^. 2. Urea In general, phytoplankton are believed to be the primary users of urea in marine systems (Price and Harrison, 1988, Table VI). More recent studies, however, have called this belief into question (Tamminen and Irmisch, 1996). In the Thames Estuary, the addition of a broad procaryotic inhibitor reduces dark uptake rates of amino acids by 49 di 20% and urea by 86 di 25%, suggesting that, contrary to popular belief, autotrophs use a significant fraction of the amino acids and that bacterial uptake of urea is substantial (Middelburg and Niewenhuize, 2000). The whole water microbial conmiunity and the heterotrophic bacterial community alone appear to prefer amino acids, with NH4+ and urea next, and NOs" as the least preferred N substrate. In the bioassay study described in the previous section, J0rgensen et al (1999) also found that urea uptake by bacteria can be as important as DFAA uptake. In the Chesapeake Bay plume, urea contributes 60 to 80% of the N uptake measured throughout most of the year (Gilbert et al, 1991). Lomas et al (in press) reviewed urea uptake rates for over a decade in Chesapeake Bay and found that urea is consistently an important N source for the plankton community, and that the highest mean baywide rates are observed during the sunmier. Illustrating the close coupling between urea uptake and urea regeneration, Hansen and Goering (1989) found that urea uptake rates based on urea disappearance are an average of 140% greater than those based on rates of N accumulation in the Bering Sea. Because urea regeneration is prevalent in their samples, correcting for isotope dilution increases measured uptake rates by an average of 54%. 3. DCAA and DFAA Bacteria are generally considered the primary users of DCAA and DFAA. As noted for urea above, changes in the size of the DFAA pool are generally small even when rates of uptake and release are substantial, indicating that uptake and release
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Deborah A. Bronk
processes are closely coupled (Fuhrman, 1987). In Long Island Sound, DFAA supply >10% of the C and N used to fuel bacterial growth, and DFAA uptake and release rates tend to be highest near noon and lowest at night, suggesting a link to autotrophs (Fuhrman, 1987). The four amino acids measured (glutamic acid, serine, glycine, alanine) can supply 44 to 131% of the calculated bacterial N demand. In other studies, DFAA and DCAA have been shown to supply ^^50% of the bacterial N demand in estuarine and coastal systems (Keil and Kirchman 1991a, 1993; Middelboe et ai, 1995). In the subarctic Pacific and Delaware estuary, DFAAs are used preferentially over DCAAs unless DFAA concentrations are very low (Keil and Kirchman, 1991a). In 14 bioassays performed, 51 ± 45% of the bacterial N demand is met by DFAA, with 18 di 24% met by DON other than DFAA. In the Northern Sargasso Sea, protein is the dominant form of DON fueling bacterial production, supporting 20 to 65% of the estimated bacterial N demand in the surface (Keil and Kirchman, 1999). Middelboe et al (1995) also found that DFAA and DCAA sustains up to 34 and 24% of the bacterial N demand, respectively, during exponential growth. As DFAA and NHU"^ concentrations decrease during stationary phase, the importance of DCAA as both a C and an N source increases. In the Mississippi plume, rapid DFAA turnover occurs coincident with rapid NH4"^ regeneration rates, suggesting that DFAA are important substrates for bacterial NH4"'' regeneration in the plume (Cotner and Gardner, 1993). Similar findings where DFAA turnover exceeds bacterial N demand have been observed in another study in the plume (Gardner et al, 1993), in Chesapeake Bay (Fuhrman, 1990), and in the subarctic Pacific (Kirchman et al, 1989; Keil and Kirchman, 1991a). The role of DFAA as a N source for phytoplankton was reviewed in Flynn and Butler (1986) and Antia et al (1991). Though laboratory studies show that some phytoplankton can grow on DFAA, uptake of DFAA by phytoplankton is considered to be insignificant in the field; as noted above, recent research on cell-surface enzymes suggests that phytoplankton use of DFAA may be greater than previously thought (see Section IV.A.2). In a salt marsh phytoplankton conmiunity, addition of organic N, including glycine, glutamic acid, and an amino acid mixture, results in increased phytoplankton growth (Lewitus et al, 2000). The physiological response of the phytoplankton community to organic N additions, in the presence and absence of antibiotics, suggests that the stimulation caused by organic N additions results directly from uptake of the organic substrates and indirectly through bacterial decomposition. The newly recognized Archaea also appear to use DFAA. In studies in the Mediterranean Sea and the Pacific Ocean near California, ^60% of the Archaea exhibit measurable DFAA uptake at nanomolar levels (Ouvemey and Fuhrman, 2000). There is increasing recognition that the utilization of DCAA and DFAA may be affected by abiotic reactions. Glucosylation and adsorption processes appear to be
Dynamics of DON
111
important in making labile compounds more refractory. Rates of protein utilization decrease when the protein is adsorbed to submicrometer particles (Nagata and Kirchman, 1996). This is potentially a very important mechanism because the surface area of colloids in the surface ocean likely exceeds that of bacteria (Schuster et al, 1998). Accordingly, a given amino acid released from a phytoplankton cell is much more likely to come into contact with colloidal material, rendering it less biologically available, than to come into direct contact with a bacterial cell. These studies suggest that competition between abiotic adsorption onto colloids and bacterial uptake can have large implications for the cycling of DOM, particularly small labile moieties such as amino acids. An estimated ~ 11-55% of the DFAA detectable by HPLC may be adsorbed to colloidal DOM in oceanic surface waters (Schuster et al, 1998). Natural bacterial populations degraded ~92% of dissolved unprotected proteins in 72-90 h in one study (Borch and Kirchman, 1999). Protein adsorbed to or present within liposomes, designed to mimic protein that is adsorbed or trapped within particles similar to those produced by protists, however, has substantially lower degradation rates. The fecal pellets of some flagellates are believed to be similar in structure to liposomes (Nagata and Kirchman, 1992), and viral lysis can also produce liposome-like structures (Shibata et al, 1997). Reduction in the degradation rates of organics associated with liposomelike structures may explain the presence of membrane proteins in the deep ocean DOM pool (Tanoue et al, 1996; McCarthy et al, 1998). On the flip side, adsorption of DFAA can also make refractory organics more bioavailable. Adsorption of DFAA to dextran and phytoplankton-derived colloidal DOM results in approximately three times more efficient utilization of dextran or colloidal DOM by marine bacteria when compared to dextran or DOM without adsorbed DFAA (Schuster et al, 1998). 4. Humic Substances Humic substances constitute a large reservoir of organic C and N in both aquatic and terrestrial systems (Mantoura et al, 1978). Humic substances have long been recognized for their ability to chelate organometallic substances, thereby making trace metals more available to phytoplankton (Prakash, 1971; Prakash et al, 1973) and sequestering toxic heavy metals (Barber, 1973; Toledo et al, 1982). Biologically, humic substances have traditionally been considered unavailable for assimilation due to their HMW and structural complexity. More recent studies of HMW organic compounds, however, have revealed that they are not as refractory as once thought (Moran and Hodson, 1994; Amon and Benner, 1994; Gardner etal, 1996). Despite these advances, the role of marine humic substances remains unclear. It has been postulated that some phytoplankton, specifically the dinoflagellates, may be able to utilize N bound to humic substances (Carlsson and Graneli, 1993).
222
Deborah A. Bronk
Experiments in which natural humic substances, isolated from river water, are added to an assemblage of coastal phytoplankton reveal that growth and biomass formation are stimulated (Carlsson et al, 1993). The hterature suggests that the N associated with humic substances can be removed via one of three mechanisms: through microbial activity (Miiller-Wegener, 1988), via excision by phytoplankton cell-surface enzymes (Palenik and Morel, 1990a; see Section IV.A.2), or through photodegradation to LMW compounds by exposure to UV radiation (Cellar, 1986; Kieber et al, 1990; Mopper et al, 1991; see Section IV.D). 5. Other Organic Compounds Additional studies that measure uptake of other organic N compounds such as purines (Douglas, 1983), pyrimidines (Knutsen, 1972), and amines (Neilson and Larsson, 1980; Wheeler and Hellebust, 1981) show that though phytoplankton and bacteria can utilize these compounds, the uptake rates are quite low (reviewed in Antia etal,l99l). There is still a debate as to whether D-DNA is actually used as a source of N for bacteria; D-DNA is approximately 16% N and so it has the potential to be a N source. Paul et al (1988) found evidence that D-DNA is used as a source of nucleic acids for bacteria and that it is degraded to provide phosphate needed by the cell. J0rgensen et al (1993) measured uptake rates of DCAA, DFAA, and D-DNA in seawater cultures, and found that D-DNA is used primarily as a source of N. When DCAA, DFAA, and D-DNA are combined, they provide 14 to 49% of the net bacterial N uptake measured in that study. Using turnover times of unidentified HMW DON, estimated with 8^^N data, DON concentrations, and rates of primary production, Benner et al (1997) estimated that DON remineraUzation can support 30-50% of daily phytoplankton N demand in the equatorial Pacific region.
D. PHOTOCHEMICAL DECOMPOSITION AS A SINK FOR DON Recent findings in freshwater and marine systems indicate that photochemical processes can effect the release of labile N moieties from DOM (Bushaw et al, 1996). Numerous studies have shown that photochemical reactions occur when DOM from freshwater or marine environments is exposed to natural sunlight. The resulting photoproducts include carbon monoxide, carbon dioxide, various carbonyl compounds, and likely many others (see reviews by Moran and Zepp, 2000, and Mopper and Kieber, Chapter 9). Some of these photoproducts can be lost by direct transfer to the atmosphere, while others can be assimilated rapidly by natural bacterial populations (Kieber et al, 1989; Geller, 1986; Lindell et al, 1995). With respect to N, we know that substances containing organic N can play an important role in the impact of UV radiation on aquatic biogeochemical cycles (de Mora et al, 2000).
Dynamics of DON
223
To date, most of the studies of N photoproduction have focused on fresh or brackish water systems (Table VII). Studies have documented the photoproduction of NH4+, DFAA, DCAA, DPA, and NO2- (Table VII), but the process is not ubiquitous (Bertilsson et ai, 1999; Koopmans and Bronk, in press). DON and isolated humic substances can be a source of labile N when irradiated with sunlight, and wavelengths in the ultraviolet (UV) region (280400 nm) produce the N photoproducts most efficiently (Bushaw et al, 1996). Humic substances are likely important substrates for photoproduction because their aromaticity and color allow them to absorb UV light, making them more photochemically reactive than other classes of marine DOM. Furthermore, an estimated 50 to 75% of the N associated with humic substances exists as DFAA, amino sugars, and other N-rich compounds that are likely sources of the labile N forms produced photochemically (Valiela and Teal, 1979; Rice, 1982; Thurman, 1985; Stevenson, 1994). In a river and bayou in Louisiana, an estimated 9 to 20% of the TON in the photic zone was converted to NH4+ each day (Wang et al, 2000). Koopmans and Bronk (in press) measured N photoproduction from DOM isolated from surficial groundwaters. Photochemical production of NH4"^ was observed in 4 of 5 irradiated estuarine surface water samples, but in only 2 of 13 groundwater samples. In contrast, the photochemically mediated loss of NH4"^ was observed in 7 of 13 groundwater samples, likely due to incorporation into DOM. These data suggest that photochemical reactions may be a sink as well as a source of available N. In a cross-system comparison, photoproduction experiments were performed in parallel with ^^N uptake experiments (Bronk et al, unpublished data). Photochemical ammonification supplied an average of 13,13, and 7% of the NHj taken up in the Eastern Tropical North Pacific, South Atlantic Bight, and two rivers in Georgia, respectively. When photoproduction is detected, it supplies up to 38% of the DPA utihzed and up to 33% of the N02~ taken up. Photochemical ammonification is a relatively minor source of NH4'^ in all three environments with rates being 2 to 6% of biotic NH4+ regeneration rates, measured with the ^^N isotope dilution technique (Gilbert et al, 1982). In a study in Lake Maracaibo, photochemical ammonification rates are ^30% of the total near surface rates of NH4'^ regeneration (Gardner et al, 1998).
E. SINKS FOR DON: RESEARCH PRIORITIES Research on DON utihzation is poised for rapid development. Some specific areas where additional study should prove fruitful would be to address questions of the differential flow of the C and N fractions of DOM in parallel. Combining the new enzymatic approaches with dual labeled substrates (^^C, ^^N, ^^O, etc.)
224
Deborah A. Bronk Table VII
Rates of Photochemical Release from Dissolved Organic Nitrogen (DON) in Whole Water or Various DON Fractions
Substrate
Photoproduction rate (ng-atNL^h-i)
June
Isolated fiilvic acids
370 ± 10
Bushawefa/., 1996
July
Whole water
150 ± 10
Bushaw et ai, 1996
August
Isolated fulvic acids
65 ± 1 0
Bushsiw et al, 1996
Whole water
340 ± 30
Bushaw ef a/., 1996
Isolated fulvic acids
50 ± 1 5
BushsLW etai, 1996
Isolated fulvic acids
320
BushawetaL, 1996
September 1995 Whole water
0 to 220
Gardner et ai, 1998
June-Aug 1996 Whole water
ND
Bertilsson er a/., 1999
June-Aug 1996 Whole water
ND
Bertilsson e/fl/., 1999
July 1994
Whole water
ND
J0rgensen 6^ a/., 1998
< 1000 Dalton DOM < 1000 Dalton DOM
330
Wang era/., 2000
1200 to 1700
Wang era/., 2000
Location Production ofNH4+ Boreal Pond, Manitoba Boreal Pond, Manitoba Boreal Pond, Manitoba Okeefenokee Swamp, GA Satilla River, GA Oyster River, NH Lake Maracaibo, Venezuela River catchments, Sweden Groundwater, Sweden Lake Skarshult, Sweden Pearl River, LA Bayou Trepagnier, LA Bayou Trepagnier, LA Skidaway River, GA Skidaway River, GA Skidaway River, GA Satilla River, GA
Date
August 1997
Reference
January 1999
< 1000 Dalton DOM
1900
Wang et ai, 2000
August 1995
2.8 X Concentrated 2.8 X Concentrated 28 X Concentrated 2.8 X Concentrated
ND
Bushaw-Newton Moran, 1999 Bushaw-Newton Moran, 1999 Bushaw-Newton Moran, 1999 Bushaw-Newton Moran, 1999
February 1996 February 1996 October 1996
humics 7 ±4.9^ humics 60 ±3^^ humics 58 ±3^^ humics
and and and and
(Continues)
225
Dynamics of DON Table VII (Continued) Photoproduction rate (ng-atNL-^h-i)
Reference
Location
Date
Eastern Tropical North Pacific South Atlantic Bight Altamah and Savannah rivers
July 1995
Whole water
5.4 ± 4.4
Bronk et al, unpublished data
March 1999 Mar, July, Oct 1998
Whole water
35.3 ± 39.3
Whole water
10.8 ±15.1
Bronk et al, unpublished data Bronk et al, unpublished data
Substrate
Meanistd 350.0 ib 559.8^ Mean ± std 136.5 ± 139.4^^ Production of dissolved free and combined amino acids Whole water
63
J0rgensen et al. 1998
August 1995 February 1996 February 1996 October 1996 July 1995
2.8 X Concentrated humics 2.8 X Concentrated humics 28 X Concentrated humics 2.28 X Concentrated humics Whole water
ND
41 ±7.1^
Bushaw-Newton and Moran, 1999 Bushaw-Newton and Moran, 1999 Bushaw-Newton and Moran, 1999 Bushaw-Newton and Moran, 1999 Bronk et al. unpublished data
Mar, July, Oct 1998
Whole water
8.7 ± 12
Lake Skarshult, July 1994 Sweden
Production of DPA Skidaway River, GA Skidaway River, GA Skidaway River, GA Satilla River, GA Eastern Tropical North Pacific Altamah and Savannah rivers
ND
Mean ± std Production of NO2Coastal seawater, NC Albermarle sound, NC Marsh, NC Cape Fear Estuary, NC
9 ± 8.5« 6.1 ± 9 . 4
Bronk et al., unpublished data
16.2 ± 16.6
May
Isolated humics
1.4
Kithtx etal, 1999
May
Isolated humics
6.7
Kieberg^(3/., 1999
May May
Isolated humics Isolated humics
1.9 4.9
Ki&hti etal, 1999 Y^thtr etal, 1999 {Continues)
Deborah A. Bronk
226 Table VII (Continued)
Location
Date
Substrate
Photoproduction rate (ng-atNL-^h-i)
Eastern Tropical North Pacific Altamah and Savannah overs
July 1995
Whole water
4.8 ± 4.4
Bronk et al, unpublished data
Mar, July, Oct 1998
Whole water
0.3 ± 0.9
Bronk et al, unpublished data
Reference
Meanistd 3.3 ± 2.5
Note. Data are presented as mean ± standard deviation unless otherwise noted. ND: not detected. ^Standard errors. ^Including all data. ^Excluding the Bayour Trepagnier data.
will likely show that the fate of the separate elements in DOM are different trophic levels (for example, see Fig. 6). It may also show that mixotrophy is more widespread than presently recognized. Along these same lines, quantifying where the DON is going, into autotrophic versus heterotrophic biomass, is extremely important to determining how these flows are modeled. Combining tracer techniques withflowcytometric sorting is one very promising way to discriminate between autotrophic and heterotrophic uptake (Lipschultz, 1995). The increasing availability of flow cytometers and the higher sorting speeds they can reach should make this approach much more widespread in the future. Finally, the long-term goal of bringing molecular techniques to bear on issues of elemental cycling is beginning to pay off. Quantitative PCR-type approaches will continue to be refined, holding out the tantalizing possibility of estimating flux rates without the perturbations inherent in traditional incubation techniques.
V. DON TURNOVER TIMES Considering the heterogeneous nature of the DON pool, interpreting DON turnover times can be difficult. Turnover times for organic N cover a broad range from minutes for DFAA (Fuhrman, 1990) to hundreds of years for the bulk DON pool (Vidal et al, 1999; Table VIII). In the Chesapeake Bay plume, DFAAs cycle rapidly with turnover times of 0.5 to 1.0 h in spring and summer and ^ 3 h in winter (Fuhrman, 1990). When considering the bulk DON pool, Abell et al (2000) estimated turnover times, based on the surface concentrations of bioavailable TON in the mixed layer, to be 18 years when both shallow or
Dynamics of DON
227
deep isopycnal degradation estimates are used. The residence time of DON in the surface waters of the equatorial Atlantic is estimated at 2.5 years (Vidal et al, 1999). Harrison et al. (1992) estimated a maximum DON turnover time of 333 days (0.003 day~^) in the northeastern Pacific by measuring changes in DON concentrations between cruises. Considering the enormous range of turnover times, one tends to wonder whether turnover times for the bulk DON pool really tell us much. One danger in interpreting DON turnover times estimated with ^^N tracers is the convention that the shorter the turnover time, the more labile the compound. For example, Bronk and Ward (1999) found that DON turnover times, estimated with release rates measured in ^^NH4+ incubations, are shorter than those measured in incubations with ^^NOa". These data imply that DON resulting from NH4+ uptake is more labile than that resulting from NOa" uptake. In reality the compounds produced and released are likely the same in both cases because the first step after NO3" is taken up by phytoplankton is the reduction to NH4+. The lability should be the same, regardless of the substrate, because the compounds released should be the same.
VL SUMMARY Traditionally, DON has been viewed as a large refractory pool that is unimportant to microbial nutrition. Research over the past decade has transformed this view, however, and the DON pool is emerging as a dynamic component of the DOM and N cycles. It is increasingly included as a core measurement in field programs and sophisticated chemical analyses are beginning to define its structure, chemical properties, sources, and sinks. I have attempted to describe recent findings in each of these areas, which I summarize below. 1. Concentration and Composition of the DON Pool The lowest DON concentrations are generally found in the deep ocean with the highest observed in rivers (Fig. 1). DON generally accounts for the largest percentage of the TDN pool (~60%) in most systems. Though much work still needs to be done to define the global distributions of DON, the general trends emerging are that upwelling at the equator, in both the Atlantic and Pacific, fuels DON production. The DON produced is then exported to the north and south into the oligotrophic gyres. Concentrations tend to decrease near the poles, though seasonal accumulations in spring are likely, and increase near the continental margins. Vertical profiles of DON generally show a surface enrichment, and DON concentrations tend to be inversely correlated with NOs" concentrations as depth increases. Concentrations of DON and NOa" are also often inversely correlated over time in surface waters. Recent studies estimate that up to 80% of the net NOs" drawdown in a number of
228
Deborah A. Bronk Table VIII Tlimover Time Estimates of Dissolved Organic Nitrogen (DON) and Organic N Compounds Turnover time
Units
Method
DON
0.91
Years
CC
Oct-Nov 1995
DON
0.4tol3.2«
Years
cc
Oct-Nov 1995
DON
12.7 ±26.1''
Years
CC
Vidal et al, 1999
Oct-Nov 1995
DON
2.1to300''
Years
cc
Vidal et al, 1999
November 1988 October 1992
DON
40.7 ± 10.4
Days
15N
DON
11 to 62
Days
15N
July 1990, Feb 1991
Protein
0.38 to 3.42
Days
14c
Northern Sargasso Sea
July 1990
Modified 9.04 to 32.71 protein^
Days
14c
Northern Sargasso Sea
February 1991
Modified 9.04 to 32.71 protein^
Days
14c
Northern Sargasso Sea
July 1990, Feb 1991
DFAA
0.03 to 0.29
Days
3H
Central Arctic
July-Aug 1994
DFAA
-2.72
Days
^H
March 1993
DON
5.0 ± 2.4
Days
15N
September 1993 October 1992
DON
8.2 ± 2.4
Days
15N
DON
24 to 85
Days
15N
February 1991
DFAA
0.013 to 0.073'
Days
3H
Location Oceanic Northeastern Pacific Equatorial Atlantic (15S-25N) Equatorial Atlantic (15S-15N) Equatorial Atlantic (35-15S) Caribbean Sea Southern California Bight Northern Sargasso Sea
Coastal Monterey Bay Monterey Bay Southern California Bight Mississippi River plume
Date NP
Compound considered
Reference Harrison et al, 1992 Vidal et al, 1999
Bronk et al, 1994 Bronk et al, 1994 Keil and Kirchman, 1999 Keil and Kirchman, 1999 Keil and Kirchman, 1999 Keil and Kirchman, 1999 Rich era/., 1997
Bronk and Ward, 1999 Bronk and Ward, 1999 Bronk et al, 1994 Cotner and Gardner, 1993 {Continues)
Dynamics of DON
229 Table VIII {Continued)
Location
Date
Mississippi River plume Santa Rosa Sound, FL Flax Pond, NY
September 1991
Estuarine Chesapeake Bay Chesapeake Bay, mesohaline Chesapeake Bay, mesohaline Chesapeake Bay, mesohaline Chesapeake Bay, mesohaline Choptank River^ Choptank River'^ Chesapeake Bay, mesohaline Chesapeake Bay, mesohaline Chesapeake Bay, mesohaline Thames Estuary
Chesapeake Bay Chesapeake Bay
Turnover time
Units
Method
Reference
DFAA
0.02 to 0.14^
Days
3H
D-DNA
0.2 to 0.43
Days
3H
D-DNA
0.64 to 9.7
Days
3H
Cotner and Gardner, 1993 J0rgensen et al, 1993 J0rgensen et al, 1993
Days
15N
Compound considered
91.0
Bronk et al, 1994 Bronk et al. 1993a
April 1989 DON and 1990 August DON 1991
6.0 to
2.0 to 6.0
Days
15N
May 1988
DON
0.27 ± 0.23
Days
15N
Bronk et al, 1998
August 1988
DON
2.01 ±
1.13
Days
15N
Bronk et al, 1998
October 1988
DON
2.53 it: 2.54
Days
15N
Bronk et al. 1998
August 1990 August 1990 May 1988
DON
33.8
Days
15N
LMWDON
15.9
Days
15N
Urea
0.12 ± 0.03
Days
15N
Bronk et al. 1993b Bronk et al. 1993b Bronk et al, 1998
August 1988
Urea
0.33 ± 0.33
Days
15N
Bronk et al. 1998
October 1988
Urea
1.00 ± 0.30
Days
15N
Bronk et al. 1998
February 1999
Urea
4.2 to
69.0
Days
15N
1973
Urea
3.17 ± 0.63
Days
15N
1988-1997
Urea
1.10 ± 0.71
Days
15N
Middelburg and Nieuwenhuize, 2000 Lomas et al. in press Lomas et al. in press {Continues)
230
Deborah A. Bronk Table Vm (Continued)
Location
Date
Compound considered
Thames Estuary
Turnover time Units Method 0.2 to 1.9 Days
15N
3H
Middelburg and Nieuwenhuize, 2000 Furhman, 1990
Days
3H
Furhman, 1990
Days
3H
Furhman, 1990
Days
3H
Furhman, 1990
Days
3H
Furhman, 1990
1999 Hudson River plume Chesapeake Bay plume Chesapeake Bay plume Chesapeake Bay plume Chesapeake Bay plume
September 1985 February 1985 June 1985 August 1985 April 1986
glu, gly, ala glu, gly, ser, ala glu, gly, ser, ala glu, gly, ser, ala
0.060 to 0.210 0.009 to 0.090 0.017 to 0.170 0.016 to 0.240
Reference
Note. Data are presented as mean ± standard deviation. NP: not presented. ^Estimated with DON concentrations and vertical flux estimates. ^Glucosylated (i.e., aged) protein as in Keil and Kirchman (1993). ^In general, turnover times increased with salinity. ^Subestuary of Chesapeake Bay.
systems accumulates as DON. In the most general sense, a generic DON pool is shaping up to look like this: Identifiable LMW compounds such as urea, DCAA, and DFAA make up --5 to 10% of the total DON pool each. Roughly 30% of the pool is HMW (> 1 kDa). Of that HMW fraction, -20-30% is hydrolyzable amino acids with the remainder being amide in form. This leaves a substantial fraction of the pool yet to be identified 2. Sources of DON With respect to sources of DON, this review focuses on biotic water colunm processes that result in DON production from phytoplankton and N2 fixers (passive diffusion, active release, sloppy feeding, and viral lysis), bacteria (passive diffusion, release of exoenzymes, bactivory, and viral lysis), and micro- and macrozooplankton (fecal pellet dissolution and excretion; Fig. 3). Rates of DON release summarized here suggest that the magnitude of release is similar in oceanic and coastal environments but slightly higher in estuarine systems. The percentage of the rate of gross N uptake released as DON was highest in oceanic systems (—40%) and lowest in estuaries (—23%), though clearly more data are needed before these generalizations can be considered robust. 3. Sinks for DON With respect to DON sinks, this review focuses on heterotrophic uptake, autotrophic uptake, and photochemical N decomposition. Though heterotrophs have been traditionally considered the primary users of DON, there is increasing
Dynamics of DON
231
recognition that DON can be an important source of N for phytoplankton. The recent work on phytoplankton cell surface enzymes has provided a mechanism by which autotrophs can utilize the N associated with DON without developing transport mechanisms for a wide range of compounds. Much of the interest in DON uptake of late has been encouraged by a number of studies that have documented a link between increases in DON concentrations and blooms of harmful algae. Rates of DON utilization vary widely across systems and even within systems. The work summarized here suggests that the large DON pool is more bioavailable than previously thought. Work to date (much of which was done in freshwater systems with dark bioassays) suggests that 12 to 72% of the DON pool is bioavailable on the time scale of days to weeks. Three key substrates within the DON pool are urea, DCAA, and DFAA. In studies where the uptake of these substrates are compared to other N compounds, urea averages 19% of total measured N uptake with 38 and 23% contributed by DCAA and DFAA, respectively. Nitrogen photoproduction has been demonstrated in a number of environments, and it can be an important mechanism for converting DON into labile compounds available for uptake by either phytoplankton or bacteria. Photochemical anmionification has been the most studied with an average rate of 136 ng-at N L~^h~^ with some extremely high rates documented. Rates of DPA and N02~ photoproduction have tended to be lower, though only a small number of studies have been done.
ACKNOWLEDGMENTS I thank N. O. G. J0rgensen for his thought provoking review, S. Seitzinger for editorial advice, two anonymous reviewers for insightful comments, D. Karl for help with DNA/RNA calculations, and C. Carlson and D. Hansell for their patience. This work was supported by Georgia Sea Grant (NA06RG0029) and the National Science Foundation (OCE-0095940). This paper is VIMS Contribution 2400 from the Virginia Institute of Marine Science, College of William and Mary.
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Chapter 6
Dynamics of DOP D. M. Karl and K. M. Bjorkman Department of Oceanography School of Ocean and Earth Science and Technology University of Hawaii Honolulu, Hawaii I. Introduction II. Terms, Definitions, and Concentration Units III. The Early Years of Pelagic Marine P-cycle Research (1884-1955) IV. The Pelagic Marine P-cycle: Key Pools and Processes V. Sampling, Incubation, Storage, and Analytical Considerations A. Sampling B. Use of Isotopic Tracers in P-cycle Research C. Sample Processing, Preservation, and Storage D. Detection of P/ and P-containing Compounds in Seawater E. Analytical Interferences in SRP and TDP Estimation VI. DOP in the Sea: Variations in Space A. Regional and Depth Variations in DOP B. DOP Concentrations in the Deep Sea
Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
C. C:N:P Stoichiometry of Dissolved and Particulate Matter Pools VII. DOP in the Sea: Variations in Time A. English Channel B. North Pacific Subtropical Gyre VIII. DOP Pool Characterization A. Molecular Weight Characterization of the DOP Pool B. DOP Pool Characterization by Enzymatic Characterization C. DOP Pool Characterization by3ipNMR D. DOP Pool Characterization by Partial Photochemical Oxidation E. Direct Measurement of DOP Compounds F. Biologically Available P G. DOP: The "Majority" View IX. DOP Production, Utilization, and Remineralization A. DOP Production and Remineralization
249
250
Karl and Bjorkman B. Direct Utilization of DOP C. Enzymes as P-cycle Facilitators D. DOP Interactions with Light and Suspended Minerals
X. Conclusions and Prospectus References
I. INTRODUCTION Phosphorus (P) is an essential macronutrient for all living organisms; life is truly built around P (deDuve, 1991). In the sea, P exists in both dissolved and particulate pools with inorganic and organic forms. The uptake, remineralization and physical and biological exchanges among these various pools are the essential components of the marine P cycle (Fig. 1). Compared to the much more comprehensive investigations of carbon (C) and nitrogen (N) dynamics in the sea, P pool inventories and fluxes are less well documented though no less important. During cell growth, P is incorporated into a broad spectrum of organic compounds with vital functions including structure, metabolism, and regulation. In time, selected P-containing organic compounds are lost from the cells to the surrounding environment by combined exudation and excretion processes. When cells turn over, whether by death/autolysis, grazing, parasitism, or viral infection, there is an enhanced release of intracellular P-containing compounds as both dissolved and particulate organic matter (DOM and POM, respectively). In this broad view, dissolved organic P (DOP) is simply the intermediate between inorganic P (P/) uptake and Fi regeneration (Fig. 1). For this and other ecological and analytical interdependencies of P/ and DOP, it is impossible to isolate DOP from the remainder of the marine P cycle. It is also imperative to emphasize that the production and cycling of P-containing compounds are inextricably linked to C and N dynamics by virtue of the fact that marine DOM and POM pools include many compounds that contain both C and P (e.g., phospholipids, sugar phosphates and selected vitamins and phosphonates) or C, N, and P (e.g., nucleotides, nucleic acids, and selected phosphonates; see Figs. 2 and 3 and Table I). It is, therefore, inappropriate to consider DOP as separate from dissolved organic C (DOC) and dissolved organic N (DON) or to view the P-cycle in any similar biogeochemical isolation. This review will take a holistic approach to the marine P-cycle with an emphasis on the production and turnover of P-containing and N-and-P-containing dissolved organic matter (i.e., DOC-P and DOC-N-P, hereafter collectively referred to as DOP). By design, this chapter will focus on the pelagic environment, especially the open sea. Investigation of the marine sedimentary P cycle is further complicated by the presence of numerous poorly defined P reservoirs (e.g., Ruttenberg, 1992;
Dynamics ofDOP
251
-ft'-
Atm
/ \ ^ y'v. / I \
Deposition (wet and dry)
circulation processes DOP/
Extreme photolysis
Pi
PH,
DOP
VO,
+
P/
inorganic poly-P/ / tiydroiysis
diffusion, mixing, active transport
Ecto
4r
diffusion, mixing, active transport
Particulate P
\
Low Density Upward Flux
Export Flux (Gravitational and active migrations)
Figure 1 The open-ocean P cycle showing the various sources and sinks of inorganic and organic P, including biotic and abiotic interconversions. The large rectangle in the center represents the upper water column TDP pool composed of Ft, inorganic polyphosphate, and a broad spectrum of largely uncharacterized DOP compounds. Ectoenzymatic activity (Ecto) is critical for microbial assimilation of selected TDP compounds. Particulate P, which includes all viable microorganisms, sustains the P cycle by assimilating and regenerating Pi, producing and hydrolyzing selected non-P/ P, especially DOP compounds, and supporting net particulate matter production and export. Atmospheric deposition, horizontal transport, and the upward flux of low-density organic P compounds are generally poorly constrained processes in most marine habitats. Phosphine (PH3), shown at the right, is the most reduced form of P in the biosphere and is generally negligible except under very unusual, highly reduced conditions. Redrawn from Karl and Bjorkman (2001).
Anderson and Delaney, 2000) which precludes a straightforward determination of P inventories and fluxes. While the majority of P-cycle processes occur throughout the world's oceans, net DOM/POM production is enhanced in the euphotic zone (e.g., the upper 0-100 m of the water column) while net remineralization of DOM/POM generally occurs at greater water depths. This vertical stratification of the marine P cycle (as well as C and N cycles) is an important factor which ultimately controls the distributions and abundances of microbial biomass and rates of global ocean biomass production, and greatly impacts the sources, sinks, and, most likely, chemical composition of marine DOM.
Karl and Bprkman
252 CARBON I CO, "^°^ COi hydrocarbons monosaccharides fatty acids vitD amino acids '
/ PPi " /1 PPPil
hexose-P triose-P RuBP PEP phospholipids
\
PH3\
\
^ selected
nucleotides nucleic acids
amino sugars
teichoic acids
chlorophyll a
selected phosphonates
protein
vit Bi and B12 humic/fuMc adds
\
urea
chitin peptidoglycan
\ NO-
|No; INH; /NgO
lipids polysaccharides cellulose/starch
Figure 2 Bar and shield representation of dissolved matter in seawater showing the intersection of C, N, and P compound classes. For example, dissolved P can exist in a variety of inorganic P forms (outside portion of the shield) or as DOC-P and DOC-N-P compounds. Likewise, C and N have both unique and intersecting pools. Compound symbols include: Fi, orthophosphate; PFi, pyrophosphate (pyro-PO; PPP/, inorganic polyphosphate (poly-P/); PH3, phosphine; RuBP, ribulose bisphosphate; PEP, phosphoenolpyruvate; N2, nitrogen; N02~, nitrite; NOg", nitrate; NH4'^, ammonium; and N2O, nitrous oxide.
We will present selected information on DOP formation, distribution and turnover in the sea building upon several previous, authoritative reviews by Duursma (1960), Armstrong (1965), Comer and Davies (1971), and Benitez-Nelson (2000) on various aspects of the marine P cycle, as well as nearly one century of field and laboratory research on this subject. For reasons already mentioned, it is impossible to discuss DOP in any useful ecological framework without also considering other DOM/POM pools and related biogeochemical processes. Although dissolved inorganic P concentrations (typically reported as soluble reactive phosphorus or SRP) are routinely measured in physical, chemical, and biological studies of the marine environment, estimates of total P (i.e., the sum of reactive and nonreactive forms of dissolved P, also called total dissolved P or TDP) are rare, despite the existence, for over 50 years, of reliable analytical methods. Although TDP was included as a core measurement during the International Geophysical Year (IGY) Atlantic Basin hydrographic survey of 1957-1958 (McGill, 1963), none
Dynamics ofDOP
253
of the "modem" oceanographic sampling programs, including Geochemical Ocean Sections (GEOSECS) and World Ocean Circulation Experiment (WOCE) included TDP as a core measurement. Even the Joint Global Ocean Flux Study (JGOFS) program, which sponsored regional-scale field studies of ocean biogeochemistry, mostly ignored P-cycle processes. Consequently the extant database of high-quality, paired SRP and TDP in the world's oceans is relatively sparse in comparison to the global coverage of SRP.
II. TERMS, DEFINITIONS, AND CONCENTRATION UNITS The total phosphorus (TP) fraction in seawater is divided, unequally, among particulate P (PP) and TDP fractions (TP = PP + TDP); both fractions contain inorganic and organic P derivatives. In most open ocean marine environments, the TDP pool greatly exceeds the PP pool, but it is the biogenic PP pool (i.e., cells or living biomass) that ultimately produces and remineralizes DOP, thereby sustaining the marine P cycle. The inorganic forms of P consist mostly of orthophosphoric acid (in seawater at a salinity of 33%^, 20°C, and pH 8.0 as 1% H2PO4- / 87% HPO/~/12% P04^-; Kester and Pytkowicz, 1967), pyrophosphate (P2O/"; hereafter abbreviated pyro-PO, and other condensed cyclic (metaphosphate) and linear (polyphosphate) polymers of various molecular weights (hereafter abbreviated poly-P/). The condensed phosphates can exist in the dissolved, colloidal and particulate matter fractions of seawater, whereas P/ and pyro-P/ are mostly contained in the truly dissolved fraction or within intracellular pools. Of these various inorganic forms, only P/ is quantitatively detected by the standard molybdenum blue assay procedure (see Section V.D for more information on reaction specificity). Therefore the measurements of pyro-P/ and poly-P/ pools require sample hydrolysis to yield reactive Fi, The organic-P fractions include primarily monomeric and polymeric phosphate esters (C-O-P bonded compounds), phosphonates (C-P bonded compounds), and organic condensed phosphates (Table I and Fig. 3). Among the ester-linked DOP compounds, both phosphomonoesters and phosphodiesters are present (Table I); each compound has unique chemical and physical properties, and each has characteristic phosphohydrolytic enzyme susceptibility. Numerous compound classes (e.g., nucleotides, nucleic acids, phospholipids, phosphoproteins, sugar phosphates, phosphoamides, vitamins) have been detected in seawater and these will be discussed in subsequent sections. Oxidative destruction of the associated organic matter is generally required to convert organic-P to reactive Fi, although certain compound classes are partially hydrolyzed during Fi analysis and thus may contribute to an overestimation of the true Fi concentration. For this reason, the standard molybdenum blue assay measures an operationally defined pool.
BOND TYPE C-O-P (Monoester)
" \ /
Example: Glucose-6-phosphate
HO
C-0-P-O-C (Diester)
NH,
o=p—o-
Example: Ribonucleic acid
H I
f H
O
C-P (Phosphonate)
OH
OH
Example: Phosphonoformic acid OH
C-0-P-O-P-O-P (Polyphosphate monoester) Example: Adenosine-5'-triphosphate
HO
P*^^^^
P*^^-^
OH
OH
OH H I
( H
Dynamics ofDOP
255
soluble reactive P (SRP), and the difference between TDP (i.e., equal to SRP following sample hydrolysis) and the initial SRP value has been termed the soluble nonreactive P (SNP) pool. Although SRP is often equated to P/, in reaUty SRP only sets an upper constraint on P/. Depending upon oxidation/hydrolysis conditions that are used for analysis, the SNP pool includes organic-P, pyro-P/, and poly-P/. Consequentiy, SNP concentration is technically not equal to DOP due to the two independent conditions: SRP>P/ and SNP>DOP. This may have important analytical and ecological implications as discussed in subsequent sections. P in seawater can also be characterized by origin (e.g., biogenic or lithogenic) or by physical characteristics (e.g., molecular weight or photolytic lability). Because many different forms can be used as P sources for marine microorganisms, albeit at variable rates and efficiencies, the most ecologically relevant fraction is biologically available P (BAP) pool. Ideally, BAP consisting of both Ft plus the biolabile fraction of the SNP pool should be measured to constrain oceanic P cyclefluxes,but routine analytical methods do not exist. While it might be argued, a priori, that SRP measurements by the Murphy and Riley (1962) procedure place a lower bound on BAP, because both Fi and acid-labile DOP must be biologically available, this may not always be the case. Fi contained in colloidal associations or adsorbed to nanoparticles would assay as part of the SRP pool but might be unavailable for uptake under ambient conditions. In all likelihood only microbioassay analysis can provide an accurate estimate of BAP (see Section VIII.F). Suffice it to say, we are still lacking a comprehensive chemical description of dissolved P in seawater (see Section VIII). The measurement of TDP is also operationally defined; typically a highintensity ultraviolet (UV) photooxidation (Armstrong et al, 1966) or hightemperature wet chemical oxidation (Menzel and Corwin, 1965) or a combined (Ridal and Moore, 1990) pretreatment is used to convert SNP to Fi for subsequent analysis by the standard molybdenum blue assay. However, it is well known that certain P-containing compounds (e.g., poly-P/, nucleotide di- and triphosphates) are not quantitatively recovered by standard UV photooxidation procedures; neither method quantitatively recovers P from all phosphonate compounds. Depending upon the methods used, the difference between the measurement of TDP and either Fi or SRP can be termed SNP (i.e., SNP = [TDP]-[SRP]) or non-Pf P (non-P/ P = [TDP]-[P/]), where SNP ^ N-Fi F (Thomson-Bulldis and Karl, 1998). As emphasized previously, there is no a priori relationship between these operationally defined pools and the more ecologically relevant BAP pool. Although several SNP compound classes have been reported to exist in seawater, including
Figure 3 Selected structures of representative DOP pool compound classes with specific examples. Not shown here are the less well known classes such as phosphoramidates (N-P-bonded) or phosphorothionates (S-P-bonded) compounds that could also be present in cells and in seawater.
Table I Selected Inorganic and Organic P Compounds Either Known to Be or Likely to Be Present in Seawater Compound Monophosphate esters Ribose-5-phosphoric acid (R-5-P) Phospho(enol)pyruvic acid (PEP) Glyceraldehyde 3-phosphoric acid (G-3-P) Glycerophosphoric acid (Gly-3-P) Creatine phosphoric acid (CP) Glucose-6-phosphoric acid (Glu-6-P) Ribulose-l,5-bisphosphoric acid (RuBP) Fructose-1,6-diphosphoric acid (F-1,6-DP) Phosphoserine (PS) Nucleotides and derivatives Adenosine 5'-triphosphoric acid (ATP) Uridylic acid (UMP) Uridine diphosphate glucose (UDPG) Guanosine 5'-diphosphate 3'-diphosphate or "magic spot" (ppGpp) Pyridoxal 5-monophosphoric acid (PyMP) Nicotinamide adenine dinucleotide phosphate (NADP) Ribonucleic acid (RNA) Deoxyribonucleic acid (DNA) Inositohexaphosphoric acid or phytic acid (PA) Vitamins Thiamine pyrophosphate (vitamin Bi) Riboflavine 5'-phosphate (vitamin B2-P) Cyanocobalamin (vitamin B12)
Chemical formula (molecular weight)
P (% by weight)
Molar C:N:P
CsHiiOgP (230.12) C3H5O6P (168) C3H7O6P (170.1) C3H9O6P (172.1) C4H10N3O5P (211.1) C6H13O9P (260.14) C5H60nP2 (304) C6H14O12P2 (340.1) C3H8NO6P (185.1)
13.5
5:—:1
18.5
3:—:1
18.2
3:—:1
18.0
3:—:1
14.7
4:3:1
11.9
6:—:1
20.4
2.5:—:1
18.2
3:—:1
16.7
3:1:1
18.3
3.3:1.7:1
9.6
9:2:1
10.9
7.5:1:1
20.6
2.5:1.25:1
12.5
8:1:1
9.4
11:3:1
-9.2% -9.5% 28.2
-9.5:4:1 -10:4:1 1:—:1
14.6
6:2:1
6.8
17:4:1
2.3
63:14:1
C10H16N5O13P3 (507.2) C9H13N2O9P (324.19) C15H24N2O17P2 (566.3) C10H17N5O17P4 (603) CgHioNOeP (247.2) C22H28N2O14N6P2 (662) Variable Variable C6H18O24P6 (660.1) C12H19N4O7P2S (425) C17H21N4O9P (456.3) C63H88C0N14O14P (1355.42)
(Continues)
257
Dynamics ofDOP Table I Compound Phosphonates Methylphosphonic acid (MPn) Phosphonoformic acid (FPn) 2-aminoethylphosphonic acid (2-AEPn) Other compounds/compound classes Marine fulvic acid'^ (MFA) Marine humic acid'' (MHA) Phospholipids (PL) Malathion (Mai) "Redfield" plankton
(Continued)
Chemical formula (molecular weight)
P (% by weight)
Molar C:N:P
CH5O3P (96) CO5PH3 (126) C2H8NO4P (141)
32.3
1:—:1
24.6
1:—:1
22.0
2:1:1
0.4-0.8 0.1-0.2 <4 11.6
80-100:—:1 >300:—:1 -40:1:1 9:—:1
1-3
106:16:1
Variable Variable Variable C9H16O5PS (267) Variable
^Marine FA and HA are operationally defined fractions, thus their composition may vary with source. These values are from Nissenbaum (1979).
poly-P/ (Solorzano and Strickland, 1968), nucleotides (Azam and Hodson, 1977; Nawrocki and Karl, 1989), nucleic acids (DeFlaun et al, 1986; Karl and Bailiff, 1989), and monophosphate esters (Strickland and Solorzano, 1966), the SNP pool in seawater remains largely uncharacterized. The earliest reports of P/ and TDP in seawater, prior to approximately 1930, all reported P as milligrams of phosphorus pentoxide (P2O5) per cubic meter of seawater (e.g., Atkins, 1923). Ironically, the chemical form P2O5 decomposes in water; the correct form should be P4O10 (Olson, 1967). Despite a logical recommendation by Atkins (1925) "to convert the conventional P2O5 values into the more rational values for the phosphate ion the factor 1.338, or very approximately 4/3, may be used to multiply the former," the P2O5 equivalence reporting practice continued. In 1933, Cooper (1933) made another plea for the importance of consistency in reporting dissolved nutrient and other elemental data. He suggested the gram-atom (or submultiple thereof, e.g., milligram-atom, microgram-atom) of the element under investigation per cubic meter as the most useful and meaningful concentration unit. This would provide for the direct comparison with other elements, and a relatively straightforward calculation of bioelemental atomic stoichiometry (i.e., C:N:P:Si) for dissolved or particulate matter. Atomic, molecular and ionic ratios would all be numerically identical. Cooper (1933) went on to state, "it is felt that such a radical change in the method of reporting results, before being put into service, requires the concurrence of the majority of oceanographical chemists, as uniformity in practice above all else is desirable." This bold suggestion was not
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Karl and Bjorkman
immediately accepted by the contemporary community of scholars, and even at the present time there is no uniformity of reporting dissolved and particulate matter P concentrations. A variety of units, all interchangeable, have been used to report DOP in seawater. In preparing this review we have converted all of the reported concentration data to either ng-at P L~^ (nM P) or /xg-at P L~^ (/xM P) as appropriate. For organic P pools this refers to P only; so 507 ng L~^ of dissolved adenosine 5'-triphosphate (ATP), for example, would be equal to 1 nM ATP, but 3 nM P because each mole of ATP contains three P atoms. This practice of reporting DOP in P molar equivalents is absolutely necessary because the exact chemical composition remains largely unknown. For quantitative measurements of polymeric compounds such as DNA, RNA, and lipid-P we also report the assumptions that we made regarding the mole percentage of P in the specific polymeric compound. Sometimes molality (mol kg~^ of seawater) rather than molarity (mol L~^ of seawater) is used so that one does not have to calculate changes in volume that occur due to variations in temperature, pressure, or salinity but, for the purposes of this review, we will consider these changes to be negligible.
III. THE EARLY YEARS OF PELAGIC MARINE P-CYCLE RESEARCH (1884-1955) Several pathfinding scientific studies, especially those conducted during the first half of the 20th century, provided a sound foundation for contemporary investigations of the marine P cycle. The creation of the Marine Biological Association of the United Kingdom in 1884 and dedication of their marine laboratory at Plymouth in 1888, and the creation of the Marine Biological Laboratory at Woods Hole, Massachusetts, in 1888 are especially noteworthy because of the major impact these two research centers have had, and continue to have, on the field of marine ecology and biogeochemistry. In 1903, working out of the Plymouth laboratory, Donald J. Matthews began a systematic study of the oceanographic features of the English Channel. His time-series research program that was later continued by Atkins, Cooper, and Harvey, led to a comprehensive understanding of the fundamental links between nutrients, phytoplankton, and fish production in the sea. Matthews (1916, 1917) is also credited with making the first reliable estimations of phosphate in seawater, and with the discovery of oceanic DOP. The colorimetric method that he selected was based on the Pouget and Chouchak reagent (sodium molybdate/strychnine sulfate/nitric acid) which yielded a yellow colored product the intensity of which was proportional to the amount of phosphate in the water sample. Because this method was not very sensitive, Matthews (1917) first had to concentrate the dissolved phosphate by coprecipitation using either anmionia or a mixture of ammonia and an iron salt. The former, a predecessor to the modem
Dynamics ofDOP
259
"MAGIC" technique (Karl and Tien, 1992), removed phosphate by adsorption onto magnesium hydroxide, Mg(OH)2, and the latter as ferric phosphate and ferric hydroxide. Using this laborious but robust method for samples collected near Knap Buoy in the EngUsh Channel, Matthews (1916,1917) made two very important observations: (1) the concentration of phosphate in seawater was approximately 0.85 /xM in December 1915, decreasing systematically to a minimum of <0.1 /xM between late April to late May, increasing again in January 1917 to a similar winter value, and (2) TDP, measured as phosphate following sample oxidation by potassium permanganate, exceeded the initial concentration of phosphate in the untreated sample by up to a factor of two- to threefold. In other words, Matthews documented for the first time the seasonal dynamics of phosphate during the vernal blooming of phytoplankton and, more significant to the topic of this review, the presence of DOP in coastal seawaters. While he was very careful to emphasize that the reported DO? values were not necessarily quantitative, the organic component was highest when the phosphate was at a minimum, suggesting that DOP formation may be coupled to particulate matter production. He concluded this key discovery paper by stating that "the nature and origin of this organic phosphorus is, of course, quite unknown" (Matthews, 1917). The importance of Matthew's research cannot be overstated; however, today, nearly a century after his pioneering contributions, we still lack a comprehensive understanding of DOP dynamics in seawater. Shortly after the completion of these initial studies, Matthews was called into military service and joined the Hydrographic Office of the Navy, where he remained following the end of World War I. A reorganization of research programs at the Plymouth Marine Laboratory led to the formation of a Department of General Physiology and the addition of W. R. G. Atkins and H. W. Harvey to the scientific staff (Southward and Roberts, 1987). Along with L. H. N. Cooper, F. S. Russell, and other staff chemists and plankton biologists at the Plymouth Laboratory, they reestablished in 1921 the monthly time-series sampling program at several key locations in the English Channel. By this time, the phosphate detection system used by Matthews had been replaced by the more sensitive Deniges (1921) method which employed ammonium molybdate, sulfuric acid, and stannous chloride (Atkins and Wilson, 1926). An intense blue color developed in the presence of phosphate. This "molybdenum blue" method, or slight variations thereof, continues to be the method of choice for contemporary studies of the marine P-cycle (see Section V.D). While the seasonal phosphate concentration dynamics using the Deniges-Atkins method revealed trends that were similar to the results published a decade earlier by Matthews, the time-series measurements documented significant interannual variations in both the date of initiation of the spring bloom of phytoplankton and, therefore, the net rate of phosphate uptake (Atkins 1928). There was also significant interannual variation in total phosphate consumed during the spring period, a value that was subsequently related to annual
260
Karl and Bjorkman
variations in the potential production of fish. That is to say, knowledge of the rate of phosphate consumption provided a lower limit constraint on annual phytoplankton production. The seasonal net consumption of phosphate was highly correlated to the removal of both silicate and carbon dioxide, suggesting that diatoms were largely responsible for organic matter production in the English Channel ecosystem (Atkins, 1930). However, by comparison to this deliberate focus on net plankton production for fisheries management, studies of organic matter decomposition and phosphate remineralization were generally ignored. Despite these field successes at Plymouth during the 1920s, research on the nature of the "enigmatic" DOP pools, discovered earlier by Matthews, was placed on hold. Even worse, Atkins considered the observed increase in phosphate following permanganate oxidation to be an analytical artifact due to the presence of arsenite in seawater and concluded that "much of what was formerly considered to be phosphorus in organic combination, in seawater, is in reality arsenic" (Atkins and Wilson, 1927). This inappropriate conclusion from one of the intellectual giants of those times was sufficient to preclude further investigations of DOP at Plymouth or elsewhere, for at least a decade, or more. H. W. Harvey and L. H. N. Cooper, two of Atkins' contemporaries at the Plymouth Marine Laboratory who shared common interests in nutrient and plankton dynamics, began systematic studies of the coupled N and P cycles, including nutrient remineralization. It was reasoned that the inorganic nutrients assimilated into organic compounds by marine plankton must eventually be recycled back to nitrate and phosphate by the combined processes of digestion, decay, and chemical hydrolysis. Consequently both dissolved and particulate organic phosphorus must be considered integral components of the marine P cycle. At about this same time studies on the role of marine bacteria as agents of organic matter decomposition were getting underway at several independent marine laboratories worldwide (e.g., Waksman and Renn, 1936; Renn, 1937; ZoBell and Grant, 1943). Furthermore, considerations of coupled particle sinking and decomposition (Seiwell and Seiwell, 1938) provided the incentive for investigations of the role of biological processes in the distributions of nonconservative properties (e.g., nutrients, oxygen and carbon dioxide) as a function of water depth and distance from land masses. Included in these investigations were studies of the release of phosphate during dark storage of water samples with and without added plankton (Gill, 1927; Cooper, 1935) or specific DOP compounds (Harvey, 1940). It was concluded that much of the total P in the sea, especially in the surface waters, was tied up in physiologically important classes of living and nonliving particulate matter which upon the initial period of decomposition were released as DOP. Only after microbial decomposition was the P released back as free phosphate. From these laboratory experiments came a renewed appreciation for the role of DOP in the marine P cycle and a focused effort on field measurements thereof. Independent, but similar, studies on the N:P stoichiometry of plankton production and decomposition conducted by Redfield et al.
Dynamics ofDOP
261
E 12 1000
Dissolved orthophosphate
H800 700 H600
I
500 "o ® JQ
B "cd
400 x:
Q. CO O
JC
300
Q. CD
200 100
Feb
Apr
June
Aug
Oct
Dec
Figure 4 Annual changes in various living and nonliving P pools and total inventories for the samples collected in the EngUsh Channel. The annual dominance of TDP (>80% of total P) is evident. The most notable seasonal change in the P inventory is the shift from Fi dominance in winter to DOP dominance in late spring-summer. Redrawn with permission from Harvey (1955).
(1937) and Cooper (1938) also accelerated during the 1930s, leading, eventually, to an ecumenical theory of nutrient dynamics in the sea. By the early 1940s, the fundamental role of DOP in the marine P cycle was firmly established (Atkins, 1930;Kreps, 1934; Cooper, 1938;Redfield^^a/., 1937; Newcombe and Brust, 1940). The sustained time series investigations of the EngHsh Channel provided evidence for a seasonally variable pool of DOP, which at the height of the phytoplankton bloom in late spring to early summer was maximal (Harvey, 1950; Armstrong and Harvey, 1950; Fig. 4). Field studies conducted in the epipelagic waters of the Gulf of Maine (Redfield et al, 1937) and in Chesapeake Bay (Newcombe and Brust, 1940) revealed similar results. Confirmation of the presence of a significant pool of DOP in seawaters from diverse habitats further stimulated research to ascertain the sources and sinks of
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Karl and Bjorkman
these potentially diverse, but biologically, relevant, compound classes. Until this time, bacteria had been considered to be the principal agents of DOP remineralization to P/, the preferred substrate for phytoplankton growth. However, careful laboratory experiments conducted by Chu (1946) documented the ability of selected bacteria-free phytoplankton cultures to utilize DOP, thereby providing a novel, alternative pathway in the marine P cycle. Presumably these microorganisms would be selected for during the sunmier months when P/ concentrations were low and DOP/P/ ratios were high which could promote a seasonal succession of phytoplankton species in certain habitats. It seems appropriate to end this section on "The early years of marine P-cycle research" with the pubhcation of Harvey's seminal monograph "The Chemistry and Fertility of Sea Waters" (Harvey, 1955). While his field observations concentrated mainly on the English Channel, the conceptual framework presented in this now classic volume received worldwide attention and provided the incentive for a large portion of the DOP research which followed during the next half-century.
IV. THE PELAGIC MARINE P CYCLE: KEY POOLS AND PROCESSES Compared to the more complex cycles of C, N, and S that are characterized and sustained by redox transformations, the marine P cycle appears rather simple (Fig. 1). With few exceptions, P in the sea is present in the pentavalent state (-1-5) as P04^~, whether as free orthophosphate or as P incorporated into either phosphate ester or phosphonate compounds. The presence of phosphite (P03^~) and phosphine gas (PH3) has been reported in selected anoxic marine habitats where they were formed and, at least in the case of POj^", consumed as part of the marine P cycle (Devai et ai, 1988; Gassmann, 1994; Schink and Friedrich, 2000). These reduced P/ derivatives are not likely to be formed in open ocean habitats. Despite this redox simplicity, P/ is rapidly assimilated to form a diverse spectrum of organic and inorganic derivatives. These compounds have key structural and metabolic functions and, therefore, are continually produced by all living organisms. Cellular P metabolism in the marine environment is complex. The transfer of phosphoryl groups is a fundamental characteristic of intermediary metabolism and is, therefore, crucial for life. Numerous enzymes share the ability to catalyze phosphoryl group transfer including phosphatases, phosphokinases, phosphomutases, nucleotidases, nucleases, phosphodiesterases, phospholipases, and nucleotidyl transferases and cyclases (Knowles, 1980). Of these enzyme classes, the phosphatases (mono- and diesterases), nucleotidases and nucleases have been most frequently studied in the marine environment (Fig. 5). The depolymerization reactions converting high-molecular-weight (HMW) DOP to intermediate- and
Dynamics ofDOP exudation, grazing, death, autolysis, virallysis
263
^ ^
Living Blomass
Pyrophosphatast
PMEase NTPase
3' and 5' Nucleotides
Pyro-P/
C-O-P monomers
t
f
NTPase
nuclease POEase
L
; RNA : : and DNA •
;—I
C-P monomers
1
t
J
PPase
,
C-P tyg^e
C-P Lyase
PMEase
1 .
I
• G-o-P : : polymers ;
i inorganic i I poiy-P/ ;
i
L
c-p
i
I polymers •
DOP POOL
I
hydrolysis, fragmentation, disaggregation
Non-living Particulate Matter
Figure 5 Schematic presentation of the role of selected enzymes (both dissolved and cell/organismassociated) in DOP pool dynamics. The production of detrital P, including both particulate and IMW/HMW dissolved inorganic and organic P pools provides key substrates (open boxes) for the specific enzymes (shaded boxes). The continued supply of monomeric compounds (<1 kDa; open circles) fuels additional enzymatic processes that lead to DOP or ?/ assimilation by living biomass. C-O-P, ester-linked P-compounds; C-P, phosphonates; PPase, inorganic polyphosphatase; PMEase, phosphomonoesterase (including but not limited to APase); 5NDase, 5' nucleotidase; NTPase, nucleotide triphosphatase; PDEase, phosphodiesterase.
low-molecular-weight (IMW and LMW, respectively) DOP are probably slow relative to the hydrolysis and direct uptake of monomeric DOP. Consequently, HMW DOP turnover is probably the "bottleneck" in marine P-cycle dynamics (Fig. 5). Marine microorganisms can assimilate three separate types of P: (1) P/, (2) ester-linked DOP compounds, and (3) phosphonates. Typically, P/ is the preferred substrate so during P/-sufficient growth conditions the synthesis of specific enzymes for phosphate ester and phosphonate utilization are usually repressed (see Section IX.C). Most microorganisms synthesize one or more phosphohydrolytic enzyme in order to degrade selected DOP compounds. For DOP compounds that are not able to be transported into the cell directly, hydrolysis prior to transport is necessary. In bacteria, DOP hydrolysis usually occurs at the outer cell membrane or in the periplasmic space, and under certain conditions enzymes are exported from
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the cell for hydrolytic activity in the surrounding medium. This may be one source of the reported presence of "dissolved" enzymatic activity in the sea. Oftentimes the Fi that is released upon hydrolysis is transported into the cell and assimilated into new biomolecules for metabolism or cell growth. However, depending upon the DOP substrate in question, the P/-free organic molecule may be the preferred target substrate and the newly released ?/ remains behind in the medium. By example, the hydrolysis of glucose-6-P (glu-6-P) most likely provides Fi, whereas the hydrolysis of AMP probably provides a purine base for nucleic acid synthesis with the Fi remaining in the medium. Consequently, the composition of the DOP pool as well as the biosynthetic needs of the microbial assemblage under investigation will largely determine whether cellular phosphohydrolase activity is a mechanism for net Fi regeneration or net Fi sequestration. In either case, however, the enzymatic activity represents a net sink for DOP compounds and effectively sustains DOP pool turnover. The combined processes of excretion, exudation, death, and autolysis, including viral lysis, provide a constant flux into the DOP pool, and the combined processes of hydrolysis (including ectoenzymatic activity, chemical hydrolysis and photolysis) and active microbial uptake comprise the major DOP sinks. The ability to transport and metabolize selected DOP compounds appears to be enhanced during conditions when the preferred growth substrate, P/, is present at limiting concentrations. The regulation of this switch from Fi to DOP assimilation is under complex metabohc control. Suffice it to say that DOP turnover is inextricably linked to Fi supply, and this results in generally negative correlation between Fi and DOP concentrations in the global ocean (see Section VI). For this reason there may be both spatial and temporal decoupling of DOP production and DOP utilization in the marine environment. In coastal regions there can be both point source (e.g., outfalls, rivers, groundwaters) and nonpoint source (e.g., runoff) inputs ofFi, pyro-P/, poly-Pi, and DOP; the chemical composition of the latter may be fundamentally distinct from the autochthonous DOP pool. Atmospheric deposition of P is another potential source term but these fluxes, especially for DOP, are poorly constrained at present. Atmospheric inputs are also likely to be regionally variable with the largest fluxes immediately adjacent to (i.e., downwind) major continental, industrial, or volcanogenic source terms. Active volcanoes may be unique in that they can catalyze the formation of gaseous P (P4O10) by the intense heating of basaltic rocks (Yamagata et aly 1991). The gaseous by-products condense in the volcanogenic steam plume and fallout as pyro-P/ and Fi. Because there is no significant gas phase in the oceanic P cycle, the primary net removal mechanism for P in the open ocean is via gravitational settling of particulate matter, downward diffusion and advection, and, for selected regions of the world's ocean, horizontal transport. However, for most open ocean habitats where concentration gradients are weak or nonexistent, horizontal advection
Dynamics ofDOP
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represents both a source and sink with a near zero net impact on the P budget. Over sufficiently long time scales (decades to centuries) there is a balance between the sources and sinks, which leads to relatively time-invariant pool inventories and fluxes. However, over seasonal-to-decadal time scales, both the concentrations and fluxes can vary in response to changes in local and regional physical forcing and global climate variability. These perturbations can also lead to changes in the relative proportions of P/ to DOP, or DOP, to TDP in selected habitats. The North Pacific Subtropical Gyre case study, presented later in this review, will focus on the P cycle in a climate-forced marine ecosystem. The use of enzymatic biomarkers to assess the P status of natural microbial assemblages has been extensively employed in microbiological oceanography. Constitutive enzymes, those found in cells regardless of nutrient status, inducible enzymes, those produced by an organism when exposed to a specific substrate, and repressible enzymes, those synthesized when the concentration of a specific repressor becomes very low, are the three main classes of enzymes used to efficiently regulate the cell's biodegradation potential. Consequently, the presence or absence of a specific enzyme can be used as an ecological indicator of metabolic readiness (see Section IX). The importance of P in microbial metabolism and, therefore, in ecosystem processes is best demonstrated by the impressive ecophysiological response of bacteria to P/ stress or P/ limitation. Under such conditions, substantial and coordinated changes occur that prepare the cells for competition and survival, including the synthesis of more efficient and specific P/-capture systems, and the ability to utilize a broader range of potential P-containing organic substrates, including phosphonates. In the case of phosphonates, enzymatic hydrolysis of the C-P bond requires either a phosphonatase pathway or a C-P lyase pathway. These independent pathways are distinguishable by their substrate specificities (Wanner, 1993); both pathways are stimulated during periods of P/ limitation (Metcalf and Wanner, 1991). Recently, a comprehensive analysis of protein synthesis during Pi limitation and phosphonate metabolism was conducted for Escherichia coli (VanBogelen et al, 1996). Two-dimensional gel electrophoresis was used to identify 413 separate proteins which exhibited differential synthesis upon P/ limitation About half (208) of the proteins exhibited enhanced synthesis while the other half (205) displayed reduced synthesis. This family of proteins is referred to as the P/ limitation stimulon. Growth on phosphonates as the sole source of P altered the synthesis of 257 proteins; 227 displayed induced synthesis and 30 were repressed. The overlap between the P/ limitation and phosphonate stimulons included 137 proteins, most (>85%) of which displayed induced synthesis. The aggregate mass of proteins responding to P/ limitation or to growth on phosphonates was 30-40% of the total mass of the cell, once again emphasizing the key role of P in cellular metabolism. This impressive laboratory study can be used as a blueprint for bacterial growth
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in the marine environment, at least for the purposes of ecological prediction and hypothesis testing. Another group of enzymes that are an integral part of the Fi limitation stimulon are phosphatases, a general term used to refer to an enzyme that catalyzes the hydrolysis of esters and anhydrides of phosphoric acid. The most common is a class of alkaline phosphomonoesterases, also called alkaline phosphatase (APase; EC 3.1.3.1) which potentially can catalyze the hydrolysis of a broad spectrum of DOP compounds optimally at seawater pH. APase is a relatively nonspecific enzyme that releases P/ from a variety of phosphomonoesters, including di-, tri-, and polyphosphate (e.g., nucleotides) organic derivatives. The ecological advantage is obvious; selected DOP compound classes could serve as reliable growth substrates during periods of Fi depletion. APase enzymes are diverse with variable substrate specificities, physical and kinetic properties, and metal ion requirements. Even within a single species, there may be multiple forms of APase (de Prada et ai, 1996). Some, but not all, APases also possess mononucleotidase activity. Although APase activity has been reported for numerous marine habitats, most ecological studies lack a detailed description of the enzymes under consideration. The relative ecophysiological roles of APase versus 5NDase, ATPase, phosphonate lyase, and other free and cell-associated enzymes will undoubtedly vary with DOP pool composition. Together, these enzymes act primarily on LMW, monomeric substrates and undoubtedly help to keep the ambient pools of LMW DOP at low (10"^ M, or less) levels. We hypothesize that the DOP pool turnover is controlled largely by the production rate of IMW and LMW substrates from the hydrolysis of HMW DOP, rather than by LMW DOP utilization. This would lead to an enhanced ecological role for those enzymes that are capable of hydrolyzing the HMW DOP, especially nucleases (including DNase and RNase), phosphodiesterases (exonuclease), and proteases (Fig. 5). P-cycle closure would ultimately require the coordinated suite of enzymes, but formation of monomers may be the remineralization bottleneck. If this model is correct, then the MW spectrum of DOP in the marine environment would be skewed toward HMW (>10 kDa). At present, there are few open ocean data available to test this ecological prediction.
V. SAMPLING, INCUBATION, STORAGE, AND ANALYTICAL CONSIDERATIONS A, SAMPLING The reliability of any field-collected data set is determined by the methods used for sampling and analysis. Although this chapter focuses on the ecological implications of the field data themselves, it is important to conmient briefly on sampling, experimental design for P flux estimations and laboratory analysis of the respective P pools.
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There are several general concerns that should be mentioned in regard to the methods reviewed in this chapter. First and foremost, P contamination is a major potential problem. Furthermore, sample contamination by toxic trace metals during sampling and subsampling is also a concern for P-flux studies that require sample incubation. It is recommended that all sampling gear, as well as storage and incubation bottles, be thoroughly acid-cleaned (1 M or ^10% HCl) and distilled water rinsed before use, and sample water rinsed before collection of the target seawater. Sampling is one of the most important, but often overlooked, aspects of oceanography. Because of the ease with which a seawater or sediment sample is obtained it is tacitly assumed that sampling is a straightforward and simple task; in reality, it is not (Karl and Dore, 2001). Questions of time and space (Dickey, 1991), minimum size and number of samples, sample replication, contamination, and postcollection treatment of the primary samples are all relevant. Most of our conceptual views of the marine environment and, therefore, the basis for our sampling protocols focus on the vertical structure of the marine environment, despite the fact that the ocean is clearly a "horizontal" habitat (e.g., horizontal-to-vertical scale of the North Pacific Ocean is > 1000:1; Karl and Dore, 2001). In the open sea there is a well-defined vertical zonation of biological communities based on light (in the near surface) and other physical and chemical properties at depths greater than approximately 200 m. In designing a sampling program for P-cycle research it is essential to consider this identifiable zonation as well as the source and other unique characteristics of each of the unique water masses. The investigator should be aware of at least three separate areas where variability can be introduced intofieldmeasurements: replication at the level of sampling (i.e., multiple water samples collected from a common depth), replication at the level of subsampling (i.e., multiple subsamples from a single sample) and analytical replication (i.e., multiple analyses of a single sample extract). Because of the heterogeneous distribution of microbial communities in nature, and therefore of DOP production, variance between sampling bottles is generally the largest source of error. Replication is most meaningful when performed at the highest level, i.e., multiple samples of water from a given environment (Kirchman et aL, 1982). It has also been demonstrated that the overall variance and the precision with which the sample variance can be estimated are functions of the procedure used to subsample the initial sample collection (Venrick, 1971).
B. USE OF ISOTOPIC TRACERS IN P-CYCLE RESEARCH The use of stable and radioisotopic tracers to monitor and quantify the rates of microbial growth, metabolism, and biogeochemical cycling of key elements and compounds has revolutionized the field of microbiological oceanography. For P-cycle research, there are two major categories: (1) the use of naturally occurring,
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cosmogenic radioactive isotopes and (2) the use of exogenously supplied radioactive isotopes. There are two radioisotopic tracers for P, ^^P (^max = 171 MeV, half life = 14.3 days) and ^^P (£niax = 0.25 MeV, half life = 25.3 days), which both exhibit P~ particle decay. The detection and quantification of the cosmogenic radiotracers ^^P and ^^P (Lai and Lee, 1988; Lai et al, 1988) are most useful for long-term (day to week) whole ecosystem studies. Two recent applications in the Sargasso Sea and Gulf of Maine have demonstrated the efficacy of using natural cosmogenic 32p/33p radioisotopes in studies of the marine P cycle (Waser et al, 1996; Benitez-Nelson and Buesseler, 1999). The use of exogenously supplied ^^P and ^^P-labeled inorganic and organic compounds, is best suited for short-term (hour to day) studies of metabolic pathways, nutrient fluxes and organic tissue labeling patterns. Several whole lake (pond) ecosystem studies (Hutchinson and Bowen, 1947,1950; Rigler, 1956) and at least one marine reef flat ^^Vi experiment (Atkinson and Smith, 1987) have been conducted, but direct tracer release has not yet been used in either open ocean patch studies or in mesocosm enclosures. Although P has only a single stable isotope, ^^P, the oxygen atoms that are in association with both inorganic and organic P pools contain three isotopes: ^^O, ^^O, and ^^O. These could, in theory, assist in a quantitative study of the marine P cycle (Longinelli et al, 1976), although no comprehensive study of oxygen isotopes in DOP has yet been published. Phosphate oxygen is tightly bound to P such that under ambient conditions in the sea, exchange of oxygen between P/ and the surrounding water is negligible (Blake et al, 1997). However, it has been hypothesized that biological cycling of P would act to isotopically equilibrate the phosphate-oxygen with ambient water (A. Colman, pers. commun.). Time and space measurements in the 8^^0 of P/ and DOP could thus provide invaluable information on P biogeochemistry. The use of exogenous radioisotopic tracers has become routine for many P-cycle investigations. Often this is the only approach that is sensitive and specific enough to measure the sometimes low fluxes of P that occur in open ocean ecosystems. The details of selected individual methods are discussed elsewhere, however, there are several general considerations regarding the use of ^2p/33p radioactive isotope tracers in studies of microbial ecology that merit attention. These include: (1) the overall reliability of the added element (or compound) as a tracer, including an evaluation of the site of labeling and its uniqueness and stability during cellular metabolism and biosynthesis, (2) isotope discrimination factors, (3) the partitioning of the added tracer into existing exogenous and internal pools of identical atoms, molecules, or compounds and the importance of measuring the specific activity of the incorporated tracer, and (4) the design and implementation of experimental procedures and proper kinetic analysis of the resulting data. The underlying assumption of these methods is that the subsequent incubation conditions do not alter the in situ rates of compound uptake, metabolism, or biosynthesis. This assumption is usually difficult to verify (Karl and Dore, 2001).
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269
In order to ensure that the rates measured during the postcoUection incubation procedure are representative of those occurring in nature, several precautions must be taken. First and foremost, the initial sample must be collected with great care so as to minimize chemical and microbiological contamination. Furthermore, exposure of viable microorganisms to environmental conditions that are substantially different from those at the collection site should be avoided so as to minimize any deleterious effects, ranging from short-term transitions in metabolism to death. A very important but often overlooked principle in the use of radioisotopic tracers in marine ecological studies is the evaluation of the specific activity (radioactivity per unit mass) of the added, incorporated, or metabolized element, molecule, or compound during the incubation/labeling period. The ideal tracer is one that can be added without perturbing the steady-state concentration of the ecosystem as a whole. In ecological studies, an accurate assessment of the specific activity during the incubation/labeling period is further complicated by the dilution of the added tracer with exogenous pools present in the environment and by endogenous pools present in living microbial cells. Without a reliable measurement of the extent of dilution prior to incorporation, tracer uptake data by themselves are of limited use in quantitative microbial ecology (see Section IX.A). Furthermore, isotope-specific activities may change over the course of the labeling period due to the combined effects of depletion (uptake) of the added tracer or isotope dilution by a constant regeneration of the exogenous pools (assuming steady-state conditions). In fact, P/ regeneration rates have been estimated in environmental samples by measuring the extent of isotope dilution during short-term sample incubation periods (Harrison, 1983).
C. SAMPLE PROCESSING, PRESERVATION, AND STORAGE Early investigations made no attempt to preserve seawater samples prior to analysis for P/ or TDP, even during prolonged storage (weeks to months). The regeneration of P/ with time would have resulted in systematic overestimations of P/ and underestimations of DOP, without greatly affecting TDP. Since that time, there has been a great deal of discussion and some acrimonious debate on the issue of seawater sample processing, preservation, and storage prior to analysis for SRP and TDP The first important consideration is whether or not to filter the water sample prior to preservation and long-term storage. The answer to this question is generally site-specific and will depend entirely on the objectives of the study and on the relative proportions of particulate and dissolved P. In most open ocean ecosystems and in all subeuphotic zone habitats PP rarely exceeds 1-5% of the total P in the sample so filtration may not be necessary. However, when sample filtration is desirable,
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then the choice of filter matrix (polycarbonate, cellulose acetate, glass fibers, silver, aluminum oxide), porosity, pressure differential employed, and volume-toarea (i.e., filter loading) are equally relevant concerns. Filtration can also increase SRP and DOP concentrations by cell leakage or breakage (Pilson and Betzer, 1973). No matter what filter is selected, there will be some limitation. For example, glassfiberfilters(Whatman GF/F, or equivalent) that are routinely used in oceanography have two potential problems: (1) the porosity (0.7 /^m nominal) precludes a unique separation of small particles and colloids from the truly dissolved P pools and (2) in certain habitats there is a significant adsorption of dissolved matter onto the GF/F filter matrix. This latter problem is a special concern in oligotrophic ocean environments where DOP concentrations exceed PP by one to two orders of magnitude. Furthermore, the ability of poly-P/ to quantitatively bind to powdered siUca glass (Ault-Riche et aL, 1998) suggests that dissolved poly-P/ in seawater may be underestimated if water samples are first filtered through silica glass fiber filters. The advantage of glass fiber filters is that they can be combusted at 450°C and acid-cleaned before use to thoroughly remove any P contamination. They also have favorable flow characteristics and high loading capacity, which are important for the measurements of certain P pools. If filtration is not employed then PP must also be measured independently to provide the most accurate estimate of DOP (i.e., DOP = TP - [Pi -f- PP]). The use of independent analytical procedures, one for TP (e.g., UV photooxidation) and another for PP (e.g., high temperature ashing followed by acid hydrolysis), has the potential for large systematic errors if, for example, particulate poly-P/ is present. To the extent possible, the oxidation/hydrolysis methods used for TDP and PP should be matched. For decades marine chemists have tested the suitability of various preservation techniques, considering the potential effects of storage container, temperature, chemical additions, and radiation on samples of different water types (Murphy and Riley, 1956; Gilmartin, 1967; Maher and Woo, 1998). The considerable body of literature presents varied and often contradictory opinions on the effectiveness of various preservation methods. The most extreme position is that all P/, SRP, and TDP measurements must be conducted in the field on fresh sample materials. This, of course, is not always possible and sometimes not even desirable even when it is possible. A recent study by Dore et al. (1996) has reevaluated several long-standing criticisms of the seawater sample storage problem. In their hands, immediate freezing (-20°C) of the sample in a high-density polyethylene (HDPE) bottle, stored upright in the dark provides a simple and suitable method for storage of seawater for periods up to one for subsequent analysis of SRP and DOP. Alternatively, preservation with mercuric chloride followed by storage at 4°C in the dark (Kattner, 1999), and acidification to pH 1 followed by storage at 4-5°C (Monaghan and Ruttenberg, 1999) have also been used.
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271
DETECTION OF P / AND P-CONTAINING COMPOUNDS
IN SEAWATER
The analysis of dissolved and particulate P-containing compounds in seawater is neither simple nor straightforward. Olson (1967) has created a glossary for P-containing compounds that includes 75 potential forms of inorganic and organic P that might be found in nature. Strickland and Parsons (1972) have defined eight of the most relevant operational classes of P compounds based on reactivity with the acidic molybdate reagents, ease of hydrolysis, and particle size. These range from "inorganic, soluble and reactive," presumably Pi, through "enzyme hydrolyzable phosphate" (Pi released following treatment with APase), to "inorganic, particulate and unreactive" (presumably P-containing minerals). Some of the operationally defined pools have no convenient analytical method of determination, while others can be estimated only as the difference between two operational classes with partially overlapping specificity. Only a very few specific P-containing compounds or compound classes can be readily detected at the low concentrations typically found in seawater (see Section VIII). Our inability to completely characterize these various dissolved and particulate pools currently limits further progress toward a comprehensive understanding of the marine P cycle. 1. Analysis of Ft The quantitative estimation of DOP (as well as TP, TDP, and PP) relies upon the measurement of P/, both before and after sample oxidation/hydrolysis (see below). Consequently, the precision and accuracy of DOP pool estimation is tied directly to the specificity and reliability of Pi analysis. Although Pi can be measured by any of a number of unrelated analytical techniques (Boltz, 1972), quantitative analysis of Pi in seawater has traditionally relied upon the formation of a 12-molybdophosphoric acid ( 1 2 - M P A ) complex and its subsequent reduction to yield a highly colored blue solution, the extinction of which is measured by absorption spectrophotometry (Osmond, 1887; Deniges 1920, 1921; Atkins, 1923; Fiske and Subbarow, 1925; Murphy and Riley, 1958, 1962). Ironically, molybdate enhances the hydrolysis of selected organic-P compounds and pyro-P/ (Weil-Malherbe and Green, 1951), so the molybdenum blue protocol appears prepositioned for Pi overestimation in natural seawater samples. However, without knowledge of the precise chemical composition of seawater DOP, we cannot predict the magnitude of this interference. The measurement of Pi (i.e., SRP) has a very rich and diverse history which, unfortunately, cannot be fully chronicled here. Over the years, numerous improvements have been introduced to the basic method so that substantial variability now exists in the conditions used for color development, final reduction of the 12-MPA complex, and treatment of potentially interfering compounds; Armstrong (1965), Olson (1967), and Broberg and Petterson (1988) provide comprehensive historical
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accounts of these changes. In 1962, the single "mixed reagent" (sulfuric acid, ammonium molybdate, ascorbic acid, potassium antimonyl tartrate) was introduced and this is the protocol most commonly employed today (Murphy and Riley, 1962). One critical difference between methods is the reducing agent; ascorbic acid in the Murphy-Riley method versus stannous chloride by many other researchers, and the use of antimony (+3) as a reaction catalyst. In addition to being able to mix all required reagents together prior to the single addition of "mixed reagent" to the sample, color development is rapid and relatively stable and salt error, which for the use of stannous chloride is significant (e.g., >15%), is <1% (Murphy and Riley, 1962). Both methods, however, are affected by arsenate reactivity and by the acid-catalyzed hydrolysis of labile organic-P compounds. The consequences of these potential interferences for quantitative determinations of P/, TDP, and, therefore, DOP are discussed below. Although the stepwise chemical procedure for P/ determination is straightforward and fully amenable to automated analysis, there are many complexities, both analytical and conceptual, inherent in measuring and interpreting Pi concentrations in seawater (Tarapchak, 1983). The SRP pool measured by the standard MurphyRiley procedure is not necessarily equivalent to the concentration of Pi, but may also include non-Pi P-containing compounds that are hydrolyzed under the acidic reaction conditions (Fig. 6). Rigler (1956, 1973) was the first to demonstrate that the conventional method of SRP determination in aquatic environments can result in a serious overestimation of Pi, especially when the SNP concentration equals or exceeds the Pi pool. Since then, many investigators have struggled with this problem, and it is still a challenge to obtain a reliable measurement of the Pi concentration in seawater. Drummond and Maher (1995) have recently described an adaptation of the Murphy-Riley (1962) procedure that yields full phosphoantimonyl molybdic acid color development in less than 1 min. Although they did not comment further on this, it is conceivable that this rapid reaction rate might provide a more accurate estimate of Pi by eliminating or at least reducing the time that is available for DOP hydrolysis, similar to the "6-s" assay (Chamberlain and Shapiro, 1969). Significant differences between SRP and Pi have been observed for nearly every natural aquatic ecosystem where more rigorous and specific methods of Pi analysis have been employed (Kuenzler and Ketchum, 1962; Jones and Spencer, 1963; Rigler, 1968; Pettersson, 1979; Karl and Tien, 1997; Thomson-Bulldis and Karl, 1998), and even different SRP methods return unequal estimates of "P/" when tested with common seawater samples (Karl and Tien, 1997). As discussed later in this review, accurate determination of Pi is absolutely essential for the application of artificial ^^Pi or ^^Pi tracer studies if mass flux estimation (Pi uptake or regeneration rates, DOP production rates) is the experimental objective, and for accurate estimation of SNP and DOP, because these pools are difference estimations (i.e., TDP-SRP). Any overestimation of Pi (e.g., by partial DOP hydrolysis) will result in a equimolar underestimation of DOP, and thus will greatly impact the calculated
Dynamics ofDOP
273 SRP (MAGIC)
OH-
Pi
SRAs
labile P compounds
SRP (MR)" labile P compounds SRAs
sugar-P lipld-P nucleotides nucleic acids Poly-P/ phosphonates phosphoprotein vitamins SNAs
h TDP
P/ =s orthophosphate SRP (MR) = soluble reactive P (Murphy & Riley) SRP (MAGIC) = soluble reactive P (by MAGIC) SRAs = soluble reactive As SNAs = soluble non-reactive As [TAs-SRAs] TDP = total dissolved P SNP = soluble non-reactive P [TDP-SRP] Non P/-P = non P / P [TDP-P/ ]
Figure 6 Schematic presentation of the chemically diverse pool of P-containing compounds in the marine environment. Shown on the left is the subset of compounds that are typically detected using the standard Murphy-Riley molybdenum blue spectrophotometric SRP assay including Fi and certain acid (H+) labile P compounds. The dashed Une indicates that the water sample can be pretreated to remove the inhibitory effects of SRAs, but this method is not always employed. Shown at the top is the spectrum of target compounds using the MAGIC-based SRP analysis method and, at right, the TDP procedure which theoretically measures all P-containing compounds. Depending upon the TDP method selected, however, hnear polyphosphates or phosphonates may not be quantitatively recovered. Various operational definitions, given at the bottom, are derived from these analyses but none of these chemical techniques yields an accurate estimate of the biologically available P (BAP) pool, which is the pool of greatest interest in studies of the microbially driven P-cycle.
P//DOP ratio. Although the use of malachite green oxalate for P/ measurements in seawater may reduce, or even ehminate, DOP hydrolysis (Fernandez et al, 1985), this method has not been widely tested under field conditions. According to Strickland and Parsons (1972), the Hmit of P/ detection using the standard Murphy-Riley method is approximately 0.03 /xM P/ and the precision at the 0.3 /xM P/ level is ±0.02/n^-^/xM, where n is number of determinations (e.g., if triplicate samples are prepared, then precision at 0.3 /xM P/ level is 0.012, or 3.8%). For measurements of DOP, which rely upon independent estimates of SRP and TDP, both the detection limit and the precision are degraded. The accuracies of P/, TDP, and DOP estimations, on the other hand, are not easily determined because reliable, certifiable SNP standards do not exist. Furthermore, the P/ concentration
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in many oligotrophic oceanic habitats is below this reported detection limit of 0.03 /xM P, so alternate, high-sensitivity Pi detection methods are sometimes required. Long pathlength spectrophotometry, including Hquid wave guide "total reflection" capillary cells (up to tens of meters in length), have been used to enhance detection sensitivity (see Fuwa etai, 1984). Ormaza-Gonzalez and Statham (1991) reported a P/ detection limit of 1 nM with a relative standard deviation of 6% with a 0.6-m Pyrex capillary system. More recently, Teflon AF-2400 capillary tubing (ID = 280 /xm, length 4.5 m) has been used for seawater absorbance spectroscopy applications (Waterbury et ai, 1997), but not yet for the measurement of Fi. The sensitivity of colorimetric Pi analysis has also been enhanced by thermal lensing and the use of solvents to extract and concentrate the 12-MPA dye, but none of these methods improves the signal:noise (blank) ratio for Pi detection. Karl and Tien (1992) devised the magnesium-induced-coprecipitation (MAGIC) method for Pi analysis that improves both the detection limit and assay precision by concentrating the Pi from seawater prior to the addition of the reagents, thereby enhancing the signal-to-noise ratio. This method has been used to reliably detect subnanomolar concentrations of Pi in seawater (Wu et ai, 2000). More recently, MAGIC has been combined with a novel luminol chemiluminescence technique to provide a convenient, alternative subnanomolar Pi detection system (Zui and Birks, 2000). The MAGIC technique, because it employs an alkaline solution for preconcentration of Pi, rather than an acidic solution, also has the advantage of reducing the potential interference from the hydrolysis of acid-labile DOP compounds during processing if they are not coprecipitated (Karl and Tien, 1992). Although it is conceivable that seawater also contains base-labile DOP which might also be included in the MAGIC-P/ assay (e.g., phosphoproteins), the pH excursion from ambient seawater required for Mg(0H)2 formation is only about 1 to 1.5 pH units (Mg(0H)2 buffers seawater at pH 9.4), so Pi isolation from non-P/ SRP and SNP compounds is possible (Thomson-BuUdis and Karl, 1998). The MAGIC procedure has also been used to separate Pi from DOP, thereby providing a method for the direct determination of DOP (technically, non-P/ TDP) in seawater samples with high P//DOP ratios (Thomson-Bulldis and Karl, 1998). Consequently, this improved method enhances the reliability of both Pi and DOP determinations in seawater. 2. Analysis of TDP The measurement of SNP (and DOP) in seawater requires paired measurements of SRP and TDP, the latter following pretreatment to effect a quantitative conversion of all inorganic and organic, nonreactive P to SRP. The key to successful and accurate SNP (and DOP) estimation is complete oxidation and hydrolysis of the
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combined P. Methods for the breakdown of P-containing organic matter can be classified as: (1) dry combustion with or without subsequent acid hydrolysis of poly-P/, (2) wet combustion with permanganate, persulfate, or perchloric acid as the oxidant, (3) UV photooxidation, or (4) alkali fusion with sodium carbonate or sodium nitrate, followed by acid digestion. Of these, the first three method classes have been used extensively to estimate marine DOP. Two recent and comprehensive reviews of environmental organic-P measurements have recently appeared (Robards et al, 1994; Maher and Woo, 1998), so only a few of the many analytical concerns will be discussed here. The earliest investigators relied on permanganate oxidation (Matthews, 1917), Kjeldahl digestion (Jones and Perkins, 1923), fuming sulfuric acid in a nitric/ hydrochloric acid mixture (Juday et al, 1928), and fuming sulfuric acid plus hydrogen peroxide (Redfield etal, 1937), before a simpler, safer, and generally more convenient method for DOP analysis was eventually devised by Harvey (1948). His method required only the addition of sulfuric acid (0.28 N final concentration) to a whole or filtered seawater sample followed by autoclaving at 135-140°C for 5-6 h. In his hands, this method quantitatively converted nucleic acids, phosphoprotein, and phosphate esters to P/ (Harvey, 1948). An additional advantage is that this procedure could be performed at sea for near real time estimation of DOP (technically SNP) concentrations, if necessary or desirable. Unfortunately, only a few years later Pratt (1950) reported that TP concentrations obtained using the Harvey (1948) method were frequently less than the sum of SRP plus PP, so he concluded that this method was unsatisfactory for seawater analysis; no alternative method was presented. Hansen and Robinson (1953) proposed a method based on initial sample oxidation with perchloric acid, followed by treatment with concentrated hydrochloric acid. Several advantages at that time included a lower blank (compared to sulfuric acid) and more rapid oxidation of organic matter. However, like the earlier methods, the Hansen and Robinson method required time-consuming heating to evaporate the seawater during sample oxidation, not to mention the inherent hazards with the use of perchloric acid. In 1964, Menzel and Vaccaro showed the complete oxidation of carbon from diverse organic compounds using persulfate as an oxidizing agent and a year later an adaptation of this method was described for the quantitative determination of TP and TDP in seawater (Menzel and Corwin, 1965). The method requires only the addition of potassium persulfate (0.7% K2S2O8 final concentration) to a seawater sample followed by autoclaving at 120°C for 30 min, or boiling (100°C) for 1 h. Microwave digestion has also been used (Woo and Maher, 1995). During the procedure, decomposition of persulfate to sulfuric acid results in a drop in pH to about 1.5-1.8, with hydrogen peroxide as another key byproduct. This highly oxidizing, hot acidic environment ensured the complete oxidation of organic matter. Tests with standard P-containing compounds and P mass
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Karl and Bprkman
balance reconciliation with diatom cultures confirmed the efficacy of this procedure (Menzel and Corwin, 1965). It should be mentioned that inorganic poly-P/, if present, would be hydrolyzed to Pi by the Menzel and Corwin (1965) method so its presence would result in a stoichiometric overestimation of DO? if the assumption, TDP-SRP = DOP, is made. Of the various chemical oxidation methods that require evaporation of seawater, only the magnesium sulfate-hydrochloric acid hydrolysis (Solorzano and Sharp, 1980) and the magnesium nitrate oxidation methods (Cembella et al, 1986) have been employed for DOP estimation. These straightforward, efficient, but somewhat laborious methods involve drying a small volume ('^10 mL) sample with exogenous magnesium salt, followed by high-temperature (450-500°C) combustion for 2 h. This decomposes the organic matter and converts some of the DOP to P/. The residue is then treated with hot (80°C) hydrochloric acid to completely hydrolyze any poly-P/ that may be present to reactive P/. The Cembella et al. (1986) magnesium nitrate method targeted hydrolysis of the extremely stable phosphonate compound class and was shown to be very effective. Armstrong et al. (1966) have provided a fundamentally different approach to the same end; namely, photochemical combustion of organic matter by UV radiation. This method, which employs quartz reaction tubes, a 1200-W mercury arc lamp (Hanovia Model 189A, or equivalent), and the addition of only hydrogen peroxide as a source of oxygen, provides an efficient and rapid (1 h) means for the conversion of selected DOP compounds to P/. A comprehensive review of the probable mechanisms of organic matter destruction during UV treatment, including characteristics of the various UV lamps, effects of pH and choice of oxidant(s) has recently been published (Golimowski and Golimoska, 1996). Several advantages include low (effectively, zero) reagent blank and, therefore, higher precision, and the ability to measure both DON (by oxidation to nitrate plus nitrite) and DOP in a single sample. For the phosphate ester (Gly-3-P, ribose-5-P) and phosphonate compounds (2-AEPn) tested, complete hydrolysis to P/ was observed following an irradiation period of approximately 1 h at 60-80°C (the sample tubes were positioned 7 cm from the UV lamp with an incident actinic energy of 200-250 mW cm~^; Armstrong et al, 1966). However, UV photooxidation methods are plagued by aging lamps, hot spots/cold spots in the irradiation apparatus, and the need for adequate temperature control; the use of internal standards and adequate reference materials is highly recommended (see Kerouel and Aminot, 1996). One unique characteristic of the UV photooxidation method, which may be construed as either an analytical advantage or as a disadvantage, is the inability to degrade inorganic and organic polyphosphates. As mentioned above, the persulfate oxidation procedure will overestimate DOP in the presence of inorganic poly-P/. In contrast, inorganic poly-P/ will not interfere in the UV method but DOP will be underestimated if organic poly-P/ compounds, such as ATP, are present. Armstrong and Tibbitts (1968), using a lower intensity 380-W UV mercury arc
Dynamics ofDOP
277
lamp to decrease the hydrolysis reaction rates, suggested that organic poly-P/ esters initially released inorganic poly-P/ that was slowly hydrolyzed with time. They also suggested that TDP concentration, including poly-P/, could be determined by including a postirradiation acid hydrolysis step, a method that could theoretically be used to infer relative contributions of monoester-linked P versus poly-P/. Yanagi et ah (1992) later developed this approach of differential UV-lability into a quantitative assay for the partial characterization of DOP pool (see Section VIII). TDP has also been measured in seawater using hydride generation and gas chromatography (Hashimoto et al, 1987). This method has several advantages over colorimetry, in particular, detection limit and reaction specificity. More importantly, the analytical basis for this method (reduction of all forms of phosphate to phosphine gas by borohydride reduction) is fundamentally different from the colorimetric procedures. The excellent quantitative correspondence between TP and TDP concentrations measured by the P hydride method and persulfate digestion for samples collected from 0 to 9600 m in the Japan Trench provides assurance that there is probably no large, yet undetected DOP pool in seawater. Such a pool was implicitly hypothesized to occur when Suzuki and colleagues reported the existence of substantial, previously undetected pools of DOC and DON (Suzuki et al, 1985; Sugimura and Suzuki, 1988). To achieve a Redfield reconciliation, there would also need to exist a previously undetected pool of DOP, but no such pool has been found (Hashimoto et al, 1987; Karl et al, 1993). With this spectrum of potentially available methods for the measurement of TDP (i.e., SNP and, therefore, DOP) it is only natural that individual researchers might endeavor to compare two or more of these methods before adopting the most reliable one for the seawater samples under consideration. It is conceivable, even likely, that the efficiencies of these methods are site-specific due to regional variations in the chemical composition of the ambient SNP pools. It is important to mention that in presenting the DOP concentration data, later in this review, we make no corrections for variable DOP recovery based on the method selected because, quite frankly, there is no way to estimate this unless multiple TDP protocols were employed—and this situation is rare. Four comprehensive TDP methods comparisons are worthy of mention. Ridal and Moore (1990) compared the persulfate oxidation and UV-irradiation methods against a new method which relies on a sequential UV-persulfate technique. This stepwise UV-acid treatment follows the analytical reconmiendation made originally by Armstrong et al. (1966) for the quantitative recovery of inorganic and organic poly-P/ compounds. Their results for samples collected from a variety of coastal and open ocean marine habitats suggested that, primarily in open ocean ecosystems, the combined method returned values 1.25-1.50 times higher than either method separately (Ridal and Moore, 1990). A subsequent study was conducted in the northeast subarctic Pacific Ocean (Ridal and Moore, 1992). For this habitat, the UV method returned an average concentration that was only 71 zb 9%
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Karl and Bjorkman
and the persulfate method 83 ± 9% of the "DOP" concentration estimated by the combined UV-persulfate technique. They concluded that the "standard" methods of analysis used for most marine studies should be considered minimum estimates of the ambient DOP concentrations; however, without additional information on the presence of inorganic poly-P/ it is not known which DOP estimation is the most accurate. Nedashkowskiy et ah (1995) compared the wet persulfate oxidation and the dry magnesium nitrate combustion methods using seawater collected off Vladivostok and in the Northwestern Bering Sea. For samples containing low concentrations of organic P (<0.5 /xM) the two methods were indistinguishable. However, in productive Bering Sea waters, where organic P exceeded 0.5 /xM, the mean difference approached 20% in favor of the dry combustion method. Ormaza-Gonzalez and Statham (1996) compared five independent methods of TDP analysis. The highest concentrations were obtained by the magnesium nitrate oxidation method while the lowest values were obtained by the UV photooxidation technique. These data suggest that inorganic and organic poly-P/ compounds, that are not detected by the UV method, may comprise a significant percentage of the TDP pool in the North Sea waters used for this comparison. Monaghan and Ruttenberg (1999) compared the dry combustion method, using two separate oxidants (magnesium nitrate and magnesium sulfate), to the wet chemical persulfate oxidation method. This comprehensive study tested the recovery of P/ from a variety of organic-P compounds as well as the estimation of TDP from continental shelf seawaters collected off California. Although quantitative recovery of P/ from selected phosphoUpids and phosphonates was only achieved by dry combustion, TDP concentrations for natural seawater samples were comparable for magnesium sulfate oxidation and persulfate and, on average, 7% lower for the nitrate oxidation method. This indicates a negligible presence in these natural samples, of the known organic-P compounds that are poorly recovered by persulfate oxidation, namely phospholipids and phosphonates (Monaghan and Ruttenberg, 1999). Finally, because many marine biogeochemists seek fundamental information on the coupled N and P pool dynamics in seawater, several methods have been devised to optimize the measurements of DON and DOP or DOC/DON/DOP in a single chemical oxidation treatment. As mentioned above, UV photooxidation can be used to measure both compound classes, though the optimal irradiation time for DOP is 1-2 h, compared to 24 h for DON (Walsh, 1989). A recent comparison of DON estimation using UV photooxidation, persulfate wet chemical oxidation, and high temperature combustion oxidation indicated higher variability and lower recoveries for the UV method (Bronk et al, 2000); however, their inability to recover N H / as N03~ casts some doubt on the efficiency of their UV photooxidation procedures. The fundamental problem with simultaneous wet chemical oxidation of DON and DOP is that organic N requires an alkaline medium while organic P requires an
Dynamics of DOP
279
acidic medium for optimum performance. This problem was solved by F. Koroleff, as reported by Valderrama (1981), using a mixture of potassium persulfate, boric acid, and NaOH which provides for a time-temperature-dependent evolution from alkaline (pH 9.7) to acidic (pH 5-6) conditions during the reaction period. A modification of this procedure which provides for the simultaneous determinations of DOC, DON, and DOP has recently been published (Raimbault et al, 1999).
E. ANALYTICAL INTERFERENCES IN S R P AND T D P ESTIMATION Of the various potential interferences on the accuracy of Vi and TDP estimation, two in particular deserve mention. The first is the potential overestimation of P/ by "reactive" organic-P compounds (Fig. 6). Their ubiquity in marine ecosystems worldwide, especially surface waters, will contribute to the measurement of SRP, and systematically underestimate SNP and DOP. TDP is unaffected by their presence. An equally insidious analytical interference derives from the nearly ubiquitous presence of arsenic (As) in seawater. Arsenate (AsO/~), the most oxidized form of As, reacts with the SRP reagents and forms a blue-colored complex of an equivalent molar absorptivity to that of P/, while arsenite (As03^~) does not react at all. Dissolved As04^" can be reduced to As03^~ with thiosulfate in acidic medium in the presence of excess metabisulfate (von Schouwenburg and Walinga, 1967; Johnson, 1971) to prevent it from interfering with SRP estimation (Fig. 6). As will be reported later in this chapter, the concentration of soluble reactive As (SRAs) sometimes exceeds the concentration of P/ so attention to this potential analytical problem is imperative. Because the time for full color development is prolonged by the addition of thiosulfate required to eliminate As04^~ interference, this procedure is not routinely employed in most automated SRP analyses (Downes, 1978), even though As04^~ may still interfere. For accurate TDP determinations, it is also necessary to correct for As04^~ ^^^ ^^ produced during sample oxidation as a result of the conversion of SNAs to SRAs (e.g., oxidation of organic As), though this is seldom, if ever, done. More than just an analytical nuisance, As has an important biogeochemical cycle that has many features in common with the marine P cycle. In fact, because of the variable redox states commonly found in seawater (As^"^ and As^"^) and the role marine microorganisms have in As oxidation, reduction, and methylation, we can anticipate an active As cycle in most marine habitats. Furthermore, As04^~ is a well studied analog of P/, and it is transported and incorporated by many of the same enzyme systems. It is also a well recognized uncoupler of oxidative and photophosphorylation and, hence, a metabolic poison (Benson, 1984; Francesconi and Edmonds, 1993). When the ambient pool of As04^" ^^ ^^S^' relative to P/, as occurs in many oligotrophic marine habitats (Karl and Tien, 1997), there should be a selection for microorganisms with either high specificity Vi transport systems or high capacity detoxification mechanisms, or both. The former would lead to a
280
Karl and Bjorkman
preponderance of As04^~ and the latter to a preponderance of DOAs. As mentioned above, both SRP (Pi) and TDP measurements need to be cognizant of potential interference from all possible forms of As. Finally, all field data on SRP and TDP concentrations measured using the Deniges-Atkins method and collected prior to about 1940 had an inadvertent analytical error caused by salt interference that required a correction factor of 1.35 (Cooper, 1939a). This correction, when appHed to the data collected for the N:P of plankton and water samples collected off Plymouth, UK, resulted in a revised N:P molar stoichiometry of 15:1, rather than the 20:1 that had been reported previously; this revised ratio was termed the "Cooper ratio" (Cooper, 1938, 1939b).
VI. DOP IN THE SEA: VARIATIONS IN SPACE Biogeochemical cycles of C, N, and P in the sea are ultimately sustained by solar energy via the process of photosynthesis. Consequently, DOP production is highly correlated with the primary formation of organic matter in the euphotic zone. The C:N:P molar stoichiometry of both particulate and dissolved organic matter pools is a key ecological parameter in the sea and will therefore also be considered briefly in this review. However, the primary focus will be on total DOP, which likely contains a broad spectrum of compounds of variable C:P and C:N:P stoichiometry (Fig. 2; Table I). The instantaneous concentration of DOP in seawater is expected to vary geographically, with depth in the water colunm and, for a given location, with time. Consequently, the ambient DOP pool must be viewed as a transient that is largely controlled by the balance between local DOP production and DOP removal processes. The physical, chemical, and biological influences on these key ecosystem processes will be discussed later, as will information on the chemical characterization of the heterogeneous DOP pool. In this section. We present the geographical and depth distributions of oceanic DOP to establish generalized concentration patterns and broad correlations with other relevant parameters, including P/. We have employed two separate data sources: (1) the U.S. National Oceanic and Atmospheric Administration - National Ocean Data Center's (NOAA-NODC) onhne oceanographic profile database (http://www.nodc.noaa.gov/cgi-bin/JOPI/jopi) and (2) our own DOP database collated from the archival literature, which includes many published profiles that are not included in the NOAA-NODC database. The NOAA-NODC global ocean search acquired all SRP/TDP data entries; the full extracted data set included n = 250,694 paired measurements. We then screened these data and removed all entries where the reported SRP exceeded the reported TDP (i.e., "negative" DOP); this decreased the number of measurements ion = 233,118 data pairs. This was our primary Global Ocean DOP data set. We also subsampled the Global Ocean DOP data set to obtain a secondary database for
Dynamics ofDOP
281 Global Open Ocean POP
i5o^wi26''W 9 0 ^ ^«o% !^^—^—dT
&6'y 90'^ 12c 120°E ISCE
180°
Figure 7 Inventory of hydrostations contained in the Global Open Ocean DOP (GOOD) database. These data were obtained from the National Oceanic and Atmospheric Administration-National Oceanic Data Center (NOAA-NODC) via their online World Wide Web-based search and were edited by us, as described in the text. The fully edited GOOD database is available from the senior author upon request.
Stations where the depth of the water column was >200 m (i.e., the pelagic marine environment which is the stated focus of this review). This otherwise unedited Global Open Ocean DOP (or GOOD) database, which includes n = 139,747 measurement pairs is available along with our enhanced DOP summary upon request of the senior author. The GOOD database includes measurements from all major ocean basins but has several large data gaps, most notably the Eastern North Pacific Ocean, the South Pacific Ocean, and the Southern Ocean (Fig. 7). Nevertheless, this n= 139,747 pairs of SRP/TDP measurements greatly exceeded our initial expectation, especially considering the relatively few open ocean DOP profiles that have been published in the refereed literature. A notable exception, that we highlight here, is the extensive survey of the North and South Atlantic Ocean basins conducted as part of the International Geophysical Year (IGY). During this 2-year (1957-1958) investigation, McGill (1963, 1964) compiled what amounts to the most comprehensive study of oceanic DOP yet attempted. This must be considered the exception to the otherwise sparse open ocean database.
A. REGIONAL AND DEPTH VARIATIONS IN DOP There are several general features of the global ocean DOP distributions. First, concentration versus depth profiles in the open ocean almost exclusively reveal
282
Karl and Bjorkman SRP (^iM)
DOP (^iM)
DOP (% TDP)
20
40
60
80
100
Figure 8 SRP, DOP and DOP as a percent of TDP for the Hawaii Ocean Time-series Sta. ALOHA (22°45'N, 158°W). These data are mean values and 95% confidence intervals based on samples collected during 110 research cruises between October 1988 and December 1999.
elevated DOP in the upper 0-100 m of the water column. For example, the 12-year climatology of SRP and DOP at Station ALOHA (22°45'N, 158°W) documents a characteristic inverse depth relationship with high concentrations of DOP in the surface water, decreasing with water depth, and vice versa for SRP concentrations (Fig. 8). The only possible exception to this general pattern might be for highlatitude habitats in winter where deep vertical mixing and low solar irradiance preclude contemporaneous near-surface DOP production via primary production. Despite this predictable depth dependence of total DOP in the open sea, individual DOP compounds or compound classes can have one of three fundamentally different distributions as a function of depth in the water column: (1) local enrichments near the sea surface with decreasing concentrations beneath the euphotic zone (similar to total DOP), (2) near surface depletion with increasing concentrations beneath the euphotic zone, or (3) constant concentration with depth. Dissolved
283
Dynamics ofDOP
nucleotides (e.g., ATP) conform to the first pattern of depth distribution and dissolved vitamins (e.g., vitamin B12) generally conform to the second pattern. These depth distributions are a result of net production/consumption and import/export processes (see Section VIII). At the subtropical location of Sta. ALOHA, DOP in the upper 100 m of the water colunm averages 0.20-0.22 /xM or approximately 70-80% of the TDP pool. Below 100 m, DOP decreases with increasing water depth to values <0.05 /xM; DOP concentrations at depths >300 m are consistently < 10% of the corresponding TDP, indicating a deep water dominance by SRP (Fig. 8). Similar patterns are also observed for both the IGY (North and South Atlantic Oceans) and GOOD data sets (Fig. 9), with the exception of a generally lower percentage of DOP in near surface
DOP (% TDP)
DOP (% TDP) 0
1
1
•
^
1
100
200
300
• • • •
-
400
500 Q. •
Q 600
-
• '•
700
-
• •
.
\
* •
IGY
800 -
900
nnn
•
WORLD OCEAN
- • •
1
1
1
1
Figure 9 Vertical profiles of DOP, expressed as percentage of TDP, for the entire Global Open Ocean DOP (GOOD) database and International Geophysical Year (IGY) subsampled data (see text for more details). The data are presented as mean values and 95% confidence intervals. The data were depth binned, as shown, prior to the determinations of the sunmiary statistics. For the IGY profile, n ranged from 32 (125 m) to 594 (surface) with a median ofn= 130. For the GOOD profile, n ranged from 805 (850 m) to 12,234 (25 m) with a median of n = 2700.
284
Karl and Bjorkman
waters (i.e., 50-60% of the TDP pool compared to 70-80% for the subtropical North Pacific; Fig. 8). For all oceanic DOP profiles, however, both the absolute DOP concentration and the DOP/TDP ratio vary systematically, and therefore predictably, with water depth. It is well known that the concentration of SRP, especially in subthermocline (>600 m) waters, increases as the age of the water mass also increases (Levitus etai, 1993). This is a result of the long-term net remineralization of organic matter. These spatial patterns are clearly evident in the IGY data set (Figs. 10 and 11 [see color plate]). A comparison of two zonal sections, one at 40°N and the other at 24.25°S in the Atlantic Ocean documents the following: (1) a contrast between relatively low TDP/low SRP waters at 40°N compared to high TDP/high SRP in the northward flowing Antarctic Bottom Water in the west (>4000 m) and Antarctic Intermediate Water (^1000 m) seen at 24.25°S; (2) nearly homogeneous concentrations of all forms of P in the relatively "young, well mixed" North Atlantic compared to the South Atlantic, especially for the subeuphotic zone waters; and (3) a general increase in surface water DOP concentrations in the South Atlantic basin, especially in the near-surface water (Figs. 10 and 11). For DOP there also appears to be a significant basin-scale east-to-west gradient, at least at 40°N, with higher DOP concentrations in the western North Atlantic, and minimum DOP concentrations in the deep central waters of both basins. These regional variations are superimposed on the general global DOP distributions described previously and are probably related to circulation patterns and processes. A similar Atlantic Ocean intrabasin gradient in DOP was recently reported by Vidal et ah (1999) for a transect from the Canary Islands to Argentina (22°N to 3 PS). Euphotic zone (0-200 m) DOP concentrations in the western portion of the basin were approximately two to three times greater than they were in the eastern portion of the Atlantic basin (0.2 to 0.3 MM versus <0.1 /xM; Vidal et ai, 1999). If the DOP/TDP ratio of the global ocean remains more or less constant for a given water depth, as the GOOD data set implies (Fig. 9), then one might predict a systematic interocean basin increase in DOP concentration with highest values in the North Pacific and lowest concentrations in the North Atlantic, resulting from the ocean's "conveyor-belt"-like circulation patterns. These interbasin differences in the concentration of DOP, and perhaps in the C:N:P stoichiometry of the DOM pool as well, are anticipated, especially if remineralization processes and long-term accumulation of recalcitrant DOM is an important process. Regional variations within a given ocean basin are also possible. The extant global data set on subeuphotic zone DOP concentrations reveals an approximately constant DOPiTDP ratio which translates to a higher absolute DOP concentration in the North Pacific compared to the North Atlantic based on the higher concentrations of SRP (and hence, TDP) in the Pacific basin (Fig. 9). This reflects the broad conveyor-belt-like features of ocean circulation; the North Atlantic Ocean is the origin and the North Pacific Ocean is the terminus of the global transport system.
Dynamics ofDOP
285
Unfortunately subeuphotic zone DOP measurements, especially where DOP is <10% of the TDP pool, are not very reliable given the nature of the paired analyses of SRP and TDP and estimation of DOP by difference. For this reason, several investigators acknowledge the uncertainty of the deep water DOP pool estimations despite reporting them. The global compilation, with individual estimates based on fairly large sample sizes (n>200), indicates: (1) a detectable pool of DOP at all ocean depths and (2) a decreasing DOP percentage with increasing depth. These features would be consistent with the time dependent remineralization of labile and semilabile DOP. While the global open ocean DOP data sets are poorly positioned to evaluate this biogeochemical prediction rigorously, owing to the inherent inaccuracies of DOP estimation in subeuphotic zone waters (see following section), there does appear to be an increase in DOP along the circulation trajectory (Fig. 12). The global pattern of increasing SRP in deep waters has been previously observed, but we believe this is the first evidence for interbasin variations in near-surface DOP.
North Atlantic
DISSOLVED ORGANIC PHOSPHORUS (^iM) South Atlantic
0|
'
^
1
North Pacific
Or
SOLUBLE REACTIVE PHOSPHORUS (|xM) Or—r
'
•
•
1
0
E 1000
Q 1500
Figure 12 Changes in SRP and TDP pools along the global ocean circulation trajectory from the North Atlantic to the North Pacific oceans. North and South Atlantic measurements are from the NOAANODC Global Ocean DOP dataset, and the North Pacific measurements are from Station ALOHA (22°45'N, 158°W). Values shown are means and 95% confidence intervals for each respective data set.
286
Karl and Bjorkman
This rather robust inverse relationship between SRP and DOP in the surface ocean is a manifestation of ?/ uptake, net biomass production, and the rapid remineraUzation of particulate organic matter. The higher the ratio of recycled-tototal production, the higher the turnover rate of particulate and dissolved organic matter. These processes lead to the eventual, local accumulation of semilabile and refractory DOM compounds, resulting in the broad geographical distributions observed for the global DOP data set. While it is not explicitly demonstrated here, there is likely to be a corresponding gradient in the chemical composition of DOP with a higher percentage of labile phosphate esters in high-latitude regions and, for a given location, in near surface waters. In spite of these broad generalized patterns of DOP in the world ocean, local and regional variations are also evident. DOP is enriched (>0.25 /xM) in most coastal and estuarine habitats that have been investigated (Table II). In the semienclosed Baltic Sea and surrounding coastal regions (Fig. 13 [see color plate]), surface DOP concentrations vary considerably from a minimum, "background" concentration of 0.4 to 0.6 /xM to values >1 /xM in regions that are likely impacted by point source and non-point-source nutrient inputs. In particular, the west coast of the Jutland Peninsula appears to be especially enriched in DOP relative to offshore regions. Even in the open ocean pelagic ecosystem off the west coast of South America, elevated near surface DOP concentrations are apparent (Fig. 14 [see color plate]). Upwelling-induced organic matter production and coupled DOP production, combined with coastal runoff and locally restricted flushing can all contribute to both local and regional elevations in surface DOP.
B. D O P
CONCENTRATIONS IN THE DEEP SEA
The precision of DOP estimation is eroded when SRP is >90% of the TDP pool, for example at all ocean depths greater than approximately 500 m in the global open ocean (Fig. 9), as well as in many high-latitude surface waters. Small relative errors in SRP and TDP determinations translate into large errors in the calculation of DOP. Ketchum etal. (1955) presented a comprehensive assessment of the analytical and statistical considerations for samples collected in the equatorial Atlantic Ocean. From a paired Pi and TDP (using the method of Harvey, 1948) measurement suite that consisted of more than 1000 seawater samples, they concluded that unless the difference (i.e., TDP-P/) exceeded 10% of the TDP value, the DOP (technically, SNP) estimate cannot be considered to be significantly different from zero. For their analyses, 95% of the surface water samples contained significant DOP decreasing through the region of the phosphate-cline where P/ increases and DOP decreases with increasing water depth. At depths greater than 1000 m there was no measurable (statistically significant) DOP present; only 13 out of 259 deep water samples (5%) gave positive differences that exceeded 1 standard deviation
Dynamics ofDOP
287
(Ketchum et al, 1955). It could not be determined whether DOP was present at concentrations below the analytical detection limit, or whether DOP was truly absent. Consequently, few reUable data sets exist for DOP concentrations in the deep mesopelagic and abyssopelagic zones (>1000 m). This is quite unfortunate because the poorly understood, stepwise conversion of PP and DOP to P/ is a key metabolic process in these regions. This analytical uncertainty, for better or for worse, has not prevented ocean researchers from sampling, analyzing, and reporting subeuphotic zone DOP concentrations. The caution we urge here is to be cognizant of the statistical constraints on the methodologies employed, as they will clearly affect the ecological implications of the data obtained. Examination of these data sets documents a fairly broad range in mesopelagic and deep sea DOP concentrations that cannot be easily reconciled with any known oceanic processes. A difference of just 20-50 nM DOP between these determinations, when scaled to dimensions of the deep sea, creates or ehminates a DOP pool that becomes significant for global ocean P budgets. It is imperative that we obtain reliable deep water DOP measurements if we ever hope to understand subeuphotic zone DOP dynamics or marine P cycle as a whole. In theory, one might anticipate a small, butfiniteDOP pool that would represent a balance between local DOP production and utilization processes. The supply of DOP to depth depends to a large extent on the nature of organic matter export processes (e.g., downward diffusion and mixing of DOM versus gravitational settling of POM) and on the pathways and coupling between export and remineralization mechanisms. However, only the process of gravitational settling of particulate matter can export significant amounts of "fresh" organic materials to subthermocline (>500 m) ocean depths. During the 1- to 2-month-long journey to the seabed in the open ocean, these exported particles are disaggregated, hydrolyzed, and otherwise reworked with a continuous, and sometimes variable, loss of organic C, N, and P. Much of this organic matter is remineralized at depth which accounts for the generally increasing concentrations of dissolved inorganic nutrients (see Fig. 8 and 12). For open ocean habitats, the flux of organic P from the euphotic zone (150 m reference depth) is approximately 5 mmol P m~^ year"^ This statistical population of sinking particles is attenuated nearly an order of magnitude by the 1000-m depth horizon and nearly two orders of magnitude at the seabed (5000 m). This attrition of organic P from the sinking particulate pool as a predictable function of depth is the primary starting material for the suspended particulate and dissolved organic matter pools beneath the euphotic zone. Only when a sufficient number of determinations are available can the statistical significance of DOP in the deep sea be assured. Repeated observations of SRP and TDP in a section between Montauk Point, New York, and Bermuda during the period 1958-1961 have demonstrated the appearance, at depth, of a low-salinity subarctic intermediate water mass that covaries with DOP concentration (McGill et al., 1964). For water samples collected
288
Karl and Bjorkman Table II
Selected Marine Dissolved Organic Phosphorus (DOP) Concentrations and DOP as Percentage of Total Dissolved Phosphorus (% of TDP) Reported from a Variety of Geographic Locations Depth (m)
Method^
DOP^ (/xM)
0-1000 0-200
UV UV
0.11-0.29 0.05-0.90
Surface
DA-AH
Surface 10 Surface
PO PO
0.37 ± 0.02 Range 0.04-2.03 («=183) 0.224-0.264 0.318-0.337 0.12-0.17
Surface
PO-AA
0.2-O.6
3 11 16
PO
0.48 ± 0.01 0.63 ± 0.03 0.98 ± 0.05
5 20
UV
0.21 0.22
0-50 75-1300
UV
0.27 to 0.42 -0.15
10 25 75
PO
0.126 0.171 0.120
66 70 56
Orrett and Karl, 1987
10 50 90
UV-PO
0.14 0.39 0.33
29 35 3
Ridal and Moore, 1990
NE continental shelf slope (George Banks)
Surface 200 400-800
UV
0.17 0.06 0.03
Southern NW shelf, Australia Eel River Shelf, N. California (summer values)
<25m
PO
0.06-0.19
33-86
3 10 35
DA-AH
0.40 0.45 0.18
82 76 11
Location Coastal/Estuarine Suruga Bay, Japan Prydz Bay, Antarctica Florida Bay, USA
Sandflord, Norway Mamala Bay, USA Chesapeake Bay, USA Bay of Aarhus, Denmark Continental shelf Southern CaHfomia Bight (off-shore site) Santa CataUna Basin (33° 18.5'N, 118°40'W) NE Pacific off Mexico (15°40'N, 107°30'W) North Atlantic Scotian Shelf
%of TDP
Reference Yanagi^ffl/., 1992 Yanagi^ra/., 1992 Fourqurean er a/., 1993
98-98 90-95 37^3
Thingstad er a/., 1993 Bjorkman and Karl, 1994 Conlty etal, 1995 Thingstad ^^ fl/., 1996
51 42
Anmierman and Azam, 1985 Holm-Hansen et al, 1966
Hopkinson er a/., 1997
Furnas and Mitchell, 1999 Monaghan and Ruttenberg, 1999 {Continues)
Dynamics
289
ofDOP
Location Southern Ocean (6r05^S, 54°8'W) Open ocean North Pacific Subtropical Gyre (~28°30'N, 155°30'W) North Pacific Subtropical Gyre (2r22'N, 155°W) North Pacific Subtropical Gyre (21°22'N, 158°14'W) North Pacific Subtropical Gyre North Pacific Subtropical Gyre (22°45^N, 158°W) Gulf Stream (41°10'N, 64°33'W) NW Mediterranean Sea (42°30'N, 4°22'E) Sargasso Sea (26°N,70°Wto 3r40'N, 64°10^W) Sargasso Sea (3r67'N,64°irto 26°rN,70°W) Southern Ocean (57°35'S, 57°W)
Depth (m) 10 50 150 Surface 100 900 5000 0-200
Table II
(Continued)
Method^
DOP^ (A^M)
UV
0.20 0.16 0.06
Sanders and Jickells, 2000
uv
0.27 0.21 0.12 0.22 0.18
Williams g? a/., 1980
UV
%of TDP
Jackson and Williams, 1985
0-100 900
uv
0.15-0.20 0.03
0-50
uv
0.10-0.35
Surface
PO
0.140-0.285
20 75 125 3600 Surface 125 400 Surface
UV-PO
UV
0.10 0.07 0.01 BDL^ 0.13 0.09 BDL 0.1-0.5
95 50 0 -95-100
Surface
UV
0.074 ± 0.042
-99
Surface 300 500
UV
0.16 0.10 BDL
PO-AA
Reference
57-60 1
Smith etai, 1986
Abellera/., 2000 66-90
Bjorkman et al, 2000
Ridal and Moore, 1990
Raimbmlt et al, 1999
Cavender-Bares et al, 2001
WuetaL,2000
Sanders and Jickells, 2000
^UV, ultraviolet photo-oxidation; PO, wet persulfate oxidation; PO-AA, persulfate oxidation under alkaline-acid conditions; DA-AH, dry ashing, acid hydrolysis; AH-PO, ash hydrolysis and persulfate oxidation; UV-PO, ultraviolet photo-oxidation-persulfate oxidation. ^Data are mean concentrations, mean ± 1 SD or ranges as shown. ^BDL, below detection limit which for the standard paired SRP/TDP assay is <20-30 nM.
Karl and Bjorkman
290
Probability
P Concentration (pM) 1.00
1.10
1.20
1.30
J .40
0.1000
0.0010 0.0100 I 0.0001
Figure 15 Mean SRP (shaded, left) and TDP (shaded, right) concentrations, and respective 95% confidence intervals, for deep water (> 1500 m) samples collected at Sta. S south of Bermuda (32° lO'N, 64°30'W) for the period 1958-1960. Also shown, on the right, are the probabilities that the analyses for SRP and TDP are identical (e.g., a low probability indicates a statistically significant amount of DOP). The TDP analyses were according to the method of Harvey (1948). Redrawn with permission fromMcGillefa/. (1964).
at hydrostation "S" south of Bermuda statistically significant time variable concentrations of DOP (i.e., TDP-SRP) were evident (Fig. 15). It was concluded that these are advective rather than in situ features and provides a constraint on the interpretation of single-point, Eularian design time-series experiments. It is possible that these variations in the DOP concentrations of deep North Atlantic Ocean waters are real. McGill etai (1964) previously reported time-dependent variations of DOP from <0.04 to >0.15 /xM for waters below 1500-m at Station "S" in the Sargasso Sea near Bermuda (Fig. 15). From mass balance considerations, they estimated a net in situ DOP consumption rate of 0.1 /xM year"\ so it is conceivable that interannual variations may exist even in the deep sea. Significant seasonal and interannual variations in particulate matter export at the 1000-m reference level on the order of ±50% of the long-term climatological mean are not unexpected, even in the subtropical gyres of the world ocean. This could easily lead to the changes observed by McGill et al. (1964) for samples collected at Station S. Even if these "temporal" patterns can be reconciled by spatial variability at this site, one would still need to explain the cause(s) of spatial variability in deep-water DOP. Recently a novel method has been devised that can provide more accurate and reliable DOP measurements in the presence of a large SRP pool; deep-sea DOP estimation is a perfect application for the modified MAGIC method (ThomsonBulldis and Karl, 1998). This method provides a separation of SRP from most DOP compounds prior to the direct measurement of DOP following oxidation-hydrolysis to Fi. Application to deep Pacific Ocean seawater has indicated an abyssopelagic DOP concentration of <40 nM values that would have been undetectable by the
Dynamics ofDOP
291 DOP(iLiM) 0
0.1
0 I
I
I
0.2 I
I
0.3 I
1000 M \
^
2000
£ 3000 CL
o
4000 .•
5000
6000 Figure 16 DOP concentration versus depth profiles at several stations in the North Pacific Ocean. ( • ) Data from WiUiams et al (1980) for samples collected in June 1977 at 28°N, 155° W and analyzed using the method of Armstrong et al. (1966); ( • ) data from Loh and Bauer (2000), presented as mean ±1 SD, for samples collected in June 1995 at 34°50'N, 123°W and analyzed using the method of Solorzano and Sharp (1980); (A) data from Thomson-BuUdis and Karl (1998) and K. Bjorkman, unpublished for samples collected in December 1996, January and February 1997, and November 2000 at Sta. ALOHA (22°45'N, 158°W) and analyzed using the MAGIC-persulfate oxidation method.
conventional TDP-SRP difference methodology (Fig. 16). For comparison, we present two other "credible" published profiles for the North Pacific Ocean obtained using different methods for TDP but both based upon the more traditional DOP estimation by difference between SRP and TDP. While there does appear to be a detectable DOP pool in the deep waters of the North Pacific it is uncertain whether it is <40 nM as the MAGIC method implies or more than twice that amount (Fig. 16). An important ecological prediction of this depth-dependent delivery of organic P to the subeuphotic zone waters is the potential selection against DOP utilization
292
Karl and Bjbrkman
by the relatively high and depth-dependent ambient concentrations of Pi. All else being equal, one would predict a relative "preservation" of DOP in the deep sea due to preferential assimilation of P/. Of course, if DOP is utilized for reasons other than Fi acquisition, for example, as a biosynthetic precursor for nucleic acids, then there may be a simultaneous utilization of both Fi and DOP in these otherwise P/sufficient deep sea habitats. To our knowledge this important aspect of microbial ecophysiology has not been systematically investigated. C. C:N:P
STOICHIOMETRY OF DISSOLVED AND
PARTICULATE MATTER POOLS
All known organisms contain a nearly identical suite of biomolecules with common structural and metabolic functions; this biochemical uniformitarianism serves to constrain the bulk elemental composition of life. In a seminal paper, Redfield and his colleagues (Redfield et ai, 1963) summarized much of the earlier research on C, N, and P stoichiometry of dissolved and particulate matter pools in the sea and combined these data sets into an important unifying concept that has served as the basis for many subsequent field and modeling studies in oceanic biogeochemistry. As Paul Falkowski has so eloquently stated "the elemental stoichiometry that we call the Redfield ratio is a result of nested processes that have a molecular foundation but are coupled to biogeochemical processes on large spatial and long temporal scales" (Falkowski, 2000). These biogeochemical characteristics of oceanic habitats involve both macro (N, P) and trace nutrient (e.g., iron) limitation, including DOP pool bioavailability. Despite this perceived uniformity, it is well known that the chemical composition of living organisms can vary considerably as a function of growth rate, energy (including light) availability, and ambient nutrient (including both major and trace elements) concentrations and bioelemental ratios. For example, under conditions of saturating light and limiting N, certain photoautotrophic organisms can store C as lipid or carbohydrate, thereby increasing their C:N and C:P ratios. Likewise, if P is present in excess of cellular demands, it can be taken up and stored as poly-P/, causing a decrease in the bulk C:P and N:P ratios. Conversely, when the bioavailable N:P ratio is greater than what is present in "average" organic matter (i.e., >16N:1P by atoms), selected groups of microorganisms can exhibit a metabolic "P-sparing" effect and produce biomass with C:P and N:P ratios significantly greater than the hypothesized Redfield ratios of 106:1 and 16:1, respectively. Based on theoretical biochemical arguments. Raven (1994) predicted that the C:N:P ratio in microorganisms is nonscalable with decreasing cell size. He concluded that the C:P ratio in small cyanobacteria should be higher than in average eukaryotic phytoplankton cells. Consequently, there does not appear to be a robust constraint on ecological C:N:P stoichiometry in the marine environment.
293
Dynamics ofDOP
Loh and Bauer (2000) have recently assembled one of the most complete biogeochemical data sets, including particulate C, N, P, as well as dissolved C, N, P pool measurements. They used their data from the Eastern North Pacific Ocean to test the hypothesis of preferential remineralization of N relative to P, and of N and P relative to C. Based on C:P and N:P ratios, they concluded that organic P is preferentially remineralized over organic C and N, resulting in increasing C:P and N:P ratios of the DOM pool with increasing water depth. Our inability to provide a comprehensive inventory of DON and DOP compounds has promoted a stoichiometric assessment of the dissolved organic matter pool based on separate measurements of DOC, DON, and DOP. However, this does little to provide a biochemical characterization of the representative compound classes dissolved in seawater. Cavender-Bares et al (2001) have measured near-surface (3 m) dissolved inorganic and organic N and P distributions along a >2500-km transect (sampled in March 1998). Their study area included the eastern North Atlantic subtropical gyre, the Gulf Stream and temperate coastal shelf habitats. Throughout the subtropics, the total dissolved N (TDN) and TDP pools were dominated by organic components (Fig. 17). SRP was very low throughout the southern portion of the
BATS
Gulf Stream
100 ^
I V •^m •Qtf*^#%V*
10
• o
1 26
TDN:TDP DON:DOP 29
32 35 Latitude (°N)
38
Figure 17 Total N and P (TDN and TDP) and organic N and P (DON and DOP) and molar N:P stoichiometry of the respective pools for samples collected along a North Atlantic Ocean transect in March 1998. Vertical striped bars indicate the approximate location of the Bermuda Atlantic Timeseries Study (BATS) and the Gulf Stream. The dotted Hne in the bottom plot shows the Redfield N:P ratio (16:1) as a point of reference. Reprinted with permission from Cavender-Bares et al. (2001).
294
Karl and Bprkman
transect with concentrations between 1 and 10 nM and occasionally below 1 nM (Cavender-Bares et ah, 2001). Only north of the Gulf Stream did the dissolved inorganic constituents represent a significant proportion of the total dissolved nutrient pools. Furthermore, the DON and DOP pools were relatively invariant over a broad geographical range (26-37°N) with mean concentrations of 6.3 /xM N and 0.12-0.13 ^M P, respectively (Fig. 12). The mean molar N:P ratio of the DOM pool averaged 50:1, a value that is three times greater than the canonical Redfield stoichiometry of 16N: IP. North of the Gulf Stream the molar ratio TDN:TDP pool dropped to 16:1 even though the N:P ratio of the DOM pool remained >25 (Fig. 17). The accumulation of N, relative to P, in the marine DOM pool within the subtropical gyre is likely caused by the addition of "extra" N by the metabolic activities of N2 fixing microorganisms that are selected for during periods of low (<16N:1P) dissolved inorganic nutrient availability, especially south of 31 °N (Cavender-Bares et al, 2001). Further implications of this ecological selection process on related aspects of the marine P cycle are discussed in the following section.
VII. DOP IN THE SEA: VARIATIONS IN TIME Long-term ecological studies are predicated on the straightforward assertion that certain processes, such as succession and climate variability, are long-term processes and must be studied as such (Strayer et al, 1986). Indeed there are many examples in the scientific literature where interpretations from short-term ecological studies are at odds with data sets collected over much longer time scales. Because it is difficult to observe slow or abrupt environmental changes directly, much less to understand the fundamental cause-and-effect relations of these changes, Magnuson (1990) has coined the term "the invisible present" to refer to these complex ecological interactions. Most of what we know about the marine DOP pool is locked up in the invisible present and opaque past. As data accumulate in a long-term ecological context, new phenomena will become apparent and new understanding will be derived. Our presentation, above, of the compiled GOOD database implies that DOP pools are constant in time for a given location. This is, most likely, an inaccurate assumption. Because the generally inverse relationship between subeuphotic zone SRP and DOP concentrations is a manifestation of plankton growth in the surface ocean, one might predict a significant but opposite seasonal cycle in the concentrations of SRP and DOP, with DOP maxima following the vernal bloom in temperate ocean habitats (Harvey, 1955; Strickland and Austin, 1960; Butler et al, 1979). During the Research on Antarctic Coastal Ecosystems and Rates (RACER) program, a detailed study of Marguerite Bay from open water to near the fast ice edge revealed a systematic and coherent shift from a SRP-dominated to
Dynamics of DOP
295
a DOP-dominated euphotic zone (Fig. 18). This spatial mosaic was a result of an ice-edge-induced bloom of phytoplankton and the temporal uncoupHng of DOP production and DOP utilization processes (Karl et al, 1992). Similar processes are likely to occur wherever and whenever net planktonic biomass is produced. These seasonally phased near-surface ocean production processes should also drive a seasonal cycle in subeuphotic zone processes via a coupled particulate matter production-export cycle. However, for reasons already presented above, we currently lack the analytical tools to observe small changes in DOP within habitats where the DOP concentrations are <10% of the corresponsponding TDP pools. During the past century, there have been several systematic time-series studies of the marine P cycle; we shall present two case studies in this section. The first is from coastal waters of the English Channel, a study that began in 1916 with the pioneering research of Matthews, Atkins, Cooper, Harvey, and others at the Plymouth Marine Laboratory (see Section III). The second, the Hawaii Ocean Time-series (HOT) study of the subtropical North Pacific Ocean, began in October 1988 and continues to the present. Both research programs have revealed significant time-dependent and climate-driven changes in P biogeochemistry and in the potential role of DOP in ocean productivity.
A. ENGLISH CHANNEL The nearly continuous 60-year data set (1923-1987) for Fi and nitrate concentrations at station El in the English Channel has recently been summarized and interpreted by Joint et al (1997) and Jordan and Joint (1998). Winter maxima in the concentrations of P/ varied considerably with significant interannual and, especially, interdecadal frequencies. Independent analyses of these same data had previously suggested a temporal trend in the chemistry and biology of the Enghsh Channel waters beginning in the 1930s, one that was broadly related to North Atlantic climate variability (Russell et al, 1971; Southward, 1980). During the period 1924-1929, wintertime surface water P/ concentrations averaged 0.67 /xM compared to a mean concentration of 0.48 ^M during 1931-1938. After 1969, P/ returned to the 1920s value of 0.62 /xM. Coincident with these decadal-scale alterations in wintertime P/, there was a significant change in fisheries, including the disappearance of herring after 1930. These ecosystem processes were hypothesized to be linked to climate changes, and to the resultant effects on water movements and associated planktonic assemblages. This has become known as the "Russell Cycle" hypothesis. However, after careful reanalysis, even this heroic data collection effort appears to be inadequate for a rigorous statistical test of this hypothesis (Joint et al, 1997). Changes (improvements) in P/ measurement protocols, uncertain retrospective
SRP (^iM)
0 U J-
^
0.5
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1.5
2
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80
100
i?n 1 DOP (^iM)
0
120
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0.2
0.25
0.3
Dynamics ofDOP
273 SRP (MAGIC)
OH-
Pi
SRAs
labile P compounds
SRP (MR)" labile P compounds SRAs
sugar-P lipld-P nucleotides nucleic acids Poly-P/ phosphonates phosphoprotein vitamins SNAs
h TDP
P/ =s orthophosphate SRP (MR) = soluble reactive P (Murphy & Riley) SRP (MAGIC) = soluble reactive P (by MAGIC) SRAs = soluble reactive As SNAs = soluble non-reactive As [TAs-SRAs] TDP = total dissolved P SNP = soluble non-reactive P [TDP-SRP] Non P/-P = non P / P [TDP-P/ ]
Figure 6 Schematic presentation of the chemically diverse pool of P-containing compounds in the marine environment. Shown on the left is the subset of compounds that are typically detected using the standard Murphy-Riley molybdenum blue spectrophotometric SRP assay including Fi and certain acid (H+) labile P compounds. The dashed Une indicates that the water sample can be pretreated to remove the inhibitory effects of SRAs, but this method is not always employed. Shown at the top is the spectrum of target compounds using the MAGIC-based SRP analysis method and, at right, the TDP procedure which theoretically measures all P-containing compounds. Depending upon the TDP method selected, however, hnear polyphosphates or phosphonates may not be quantitatively recovered. Various operational definitions, given at the bottom, are derived from these analyses but none of these chemical techniques yields an accurate estimate of the biologically available P (BAP) pool, which is the pool of greatest interest in studies of the microbially driven P-cycle.
P//DOP ratio. Although the use of malachite green oxalate for P/ measurements in seawater may reduce, or even ehminate, DOP hydrolysis (Fernandez et al, 1985), this method has not been widely tested under field conditions. According to Strickland and Parsons (1972), the Hmit of P/ detection using the standard Murphy-Riley method is approximately 0.03 /xM P/ and the precision at the 0.3 /xM P/ level is ±0.02/n^-^/xM, where n is number of determinations (e.g., if triplicate samples are prepared, then precision at 0.3 /xM P/ level is 0.012, or 3.8%). For measurements of DOP, which rely upon independent estimates of SRP and TDP, both the detection limit and the precision are degraded. The accuracies of P/, TDP, and DOP estimations, on the other hand, are not easily determined because reliable, certifiable SNP standards do not exist. Furthermore, the P/ concentration
Karl and Bprkman
298
A
M
J
J
Month
A
Figure 19 Seasonal fluctuations in dissolved P {Pi and DOP) and N (nitrate [NO3] and DON) pools in waters of the English Channel, and corresponding N:P molar stoichiometrics of DON:DOP and NOsiPi fractions. The shaded region in the top panel is the mean ± 1 SD for the water column integrated TDNiTDP pool. These data are the monthly climatologies for an 11-year study. Redrawn from Butler era/. (1979).
gyres exhibit substantial physical and biological variability on several time scales from months to decades. There is long standing interest and substantive debate over the nature of nutrient control of primary production in the NPSG and in the world's ocean as a whole. Codispoti (1989) has summarized the key scientific issues, specifically the balance between rates of N2 fixation and denitrification and the bioavailability of P. Extended periods of fixed N-limitation should select for N2-fixing microorganisms and force the ecosystem toward P limitation; P would be the ultimate production rate limiting macronutrient. However, this rather simple conceptual model assumes
Dynamics ofDOP
299
that N2-fixing microorganisms can effectively compete for P and other required trace elements (especially iron) that are required for the activity of nitrogenase, the enzyme responsible for the reduction of N2 to ammonium. Other environmental factors likely to influence N2 fixation are temperature, turbulence, and dissolved oxygen concentration; oxygen inhibits nitrogenase activity. The input of new N into the surface ocean can decouple the otherwise linked regional C-N-P cycles, leading to an altered P-deficient stoichiometry in dissolved and particulate matter pools and a pulsed, net sequestration of atmospheric carbon dioxide. The two most crucial environmental controls on N2 fixation are the bioavailabilities of iron and P, including DOP (Karl et al, 2002). Pioneering research in the NPSG conducted by Perry (1972, 1976) suggested that P might control microbial growth in the near surface waters. Several physiological parameters, including high particulate C:P ratios and high biomass-normalized rates of APase, were indicative of P-deficiency. Nevertheless, analytical and intellectual assets at this time were directed elsewhere. The Plankton Rate Processes in Ohgotrophic Oceans Study (PRPOOS) had a deliberate focus on gross and net rates of primary production in the NPSG, but not on the nutrient controls thereof. In fact, PRPOOS completed its field work on marine production just a few years before the prokaryotic microorganism Prochlorococcus sp. was discovered as the dominant photoautotrophic component of these open ocean habitats (Chisholm et al, 1988), so one might legitimately wonder, "What else didn't we know at that time?" The Vertical Transport and Exchange (VERTEX) program conducted extensive studies of coupled primary production and particulate matter export in the NPSG, but again lacked an explicit focus on the ecophysiological controls thereof. The Asian Dust Inputs to Oligotrophic Seas (ADIOS) project focused on the eolian deposition of trace elements, including iron, but did not systematically evaluate the interrelationships between iron deposition, N2 fixation, and P pool dynamics. In fact, neither of these three major biogeochemical programs included core measurements of DOP; the then unifying concept of new and regenerated production {sensu Dugdale and Goering, 1967), based strictly on nitrate and ammonium pool dynamics, respectively, reigned as biogeochemical dogma. There is presently compelling evidence to suggest that this N-centric view of new and export production in the NPSG is in need of revision to accommodate both N2 fixation and P biodynamics (Karl, 1999, 2000). Since October 1988, a comprehensive suite of ocean measurements including SRP, P/, and TDP determinations have been obtained at the ohgotrophic Sta. ALOHA in the NPSG. Core measurements were selected to provide a data set to evaluate existing C-N-P biogeochemical models and, if necessary, to improve them. The emergent data set from Sta. ALOHA is unique, robust, and rich with previously undocumented phenomena. During the initial investigation period it became evident that the NPSG P cycle was unexpectedly complex. SRP pool dynamics were characterized by both high-frequency (weeks to months) and
Karl and Bjorkman
300 15
E o E E,
10
Q. CC CO
30
E o
I
20 I
§ 10
J A J 0 J A J 0 J A J O J A J O J
1989
1990
1991 1992 Sampling Date
A J 0 .J A J 0
1993
1994
Figure 20 P pool dynamics at Sta. ALOHA for the period 1989-1994. (Top) SRP was measured both by the standard autoanalyzer technique (SRP-AA; data points connected by solid line) and by MAGIC (SRP-M; data points connected by dashed line). (Bottom) DOP was measured by difference (TDP-SRP) following UV treatment. Each data point represents the 0- 100-m depth-integrated inventory of SRP or DOP measured on the cruises, generally from six to seven individual water depths. The model I linear regression fit (bold line) for the SRP-M data set is as follows: SRP-M (nrniol m~^) = 9.95(0.003 X days since 1 January 1989). The model I linear regression fit (bold line) for the DOP data set is as follows: DOP (mmol m'^) = 18.98 + (0.003 x days since 1 January 1989). Redrawn from Karl and Tien (1997).
lower-frequency (years) changes that included aperiodic DOP pool inflation (up to 50%) above the longer term mean (Fig. 20). In these investigations, SRP was measured by both the "standard" autoanalyzer method (SRP-AA) and by MAGIC (SRP-M); significant differences were sometimes, but not always, observed between these two procedures (Fig. 20). Because these two methods target for analysis different subcomponents of the TDP pool (Fig. 5) these differences (e.g., the period May 1991 to August 1992; Fig. 20) imply temporal changes to the bulk chemical composition of the SNP pool. For example, an increase in acid-hydrolyzable DOP (e.g., sugar phosphates) could result in a condition where SRP-AA>SRP-M and, conversely, an increase in base-hydrolyzable DOP (e.g., phosphoprotein)
Dynamics ofDOP
301
could lead to a condition where SRP-M>SRP-AA. Nevertheless, the most impressive result was the systematic and sustained decreasing upper water column (0-100 m) inventory for both SRP-AA and SRP-M from a value of ~10 mmol P m"-^ in January 1989 to ~5 mmol P m~^ in December 1994, and the sustained net accumulation of SNP from ~19 mmol P m"-^ in January 1989 to ~26 mmol P m"-^ in December 1994. This nearly quantitative shift from dissolved "inorganic" to dissolved "organic" P suggested an accumulation of biorefractory materials, a condition that could be a manifestation of enhanced N2 fixation and a switch from N-limitation to P-limitation as first suggested by Karl et al. (1995). At the end of 1994, it was difficult to predict how long these features could persist without fundamentally disrupting new and export production processes in the NPSG. Continued measurements of SRP and DOP have documented further decreases in the SRP inventory to ^2.2 mmol P m~^ by December 1997, but without a concomitant increase in DOP (Karl et al, 2001b; Church et al, 2001). Apparently, the initial DOP pool inflation (Fig. 20) was only a temporary perturbation in the NPSG P-cycle dynamics. In fact, since 1994 DOP has decreased at a rate of approximately 0.37 nmiol P m~^ per annum. This enhanced net utilization of semilabile DOP would be predicted under sustained conditions of P limitation. A shift in bioavailable P, from Fi to DOP, could also promote species selection, thereby affecting overall conmiunity structure and key ecological processes. It is possible that Prochlorococcus competes favorably for the utilization of DOP, either directly or following ectoenzymatic activity. During conditions of sustained DOP dominance, like at Sta. ALOHA (DOP/P/ > 10), Prochlorococcus would be selected for and thus would begin to dominate the photoautotroph assemblage. Karl et al (2001a) have recently hypothesized that the NPSG has selected for Prochlorococcus diwd against eukaryotic algae over the past several decades and the attendant domain shift has caused significant changes in ecosystem structure and nutrient dynamics including P-cycle processes. The stoichiometry of the TDN:TDP pools in the upper 0-100 m of the water colunm (mostly dominated by DON and DOP) also displayed variability on monthly, seasonal, and interannual time scales. For example, monthly observations revealed occasional high frequency changes in the N:P ratio of the total dissolved matter pool between consecutive cruises (e.g., during spring 1989 and spring 1997; Fig. 21). These features were characterized by decreases in the N:P ratio from values that were significantly higher than the Redfield ratio to values approximating it (Fig. 21). When observed, these events always coincided with pulsed inputs of inorganic nutrients as detected by elevated nitrate plus nitrite (N+N) inventories (Karl et al, 2001b). In certain years (e.g., 1991, 1993, 1996) these nutrient injections were either absent or, more likely, missed by the relatively coarse monthly frequency of our sampling program. We also observed several time periods of sustained, systematic change in the N:P ratio; e.g., January 1991 to July 1992, where
302
Karl and Bjorkman 30|
I I I I I I I I I I I I I I I I I I I
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Figure 21 Nitrogen-to-phosphorus (N:P) ratios for the total dissolved matter pools in the upper 0-100 m of the water column at Sta. ALOHA during the 9-year observation period. (A) TDN:TDP versus sampling date. For each cruise, the mean value ±1 SD is presented. As a point for reference, the horizontal dashed hne is the Redfield ratio of 16N:1P. (B) Frequency histogram of TDNiTDP values for the 9-year data set. As a point for reference, the vertical dashed line is the Redfield ratio of 16N: IP. (C) Seasonal variability in TDNiTDP at Sta. ALOHA. Spring, Mar-May; Sunmier, June-August; Fall, September-November; Winter, December-February. The values presented are the mean d=l SD for each data set. (D) Interannual variability in TDN:TDP at Sta. ALOHA. The values presented are die mean ±1 SD for each data set. Redrawn from Karl et al. (2001b).
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the N:P decreased from >20 to values equivalent to the Redfield ratio, followed by an approximately 18-month period during which the N:P ratio slowly increased back to values approaching 25:1 (Fig. 21 A). These features resulted in significant interannual variations in the TDN:TDP ratio (Fig. 21D), with 1993 standing out as a year with an anomalously high mean TDNiTDP ratio of 22.8 (SD = 1.8). The mean TDN:TDP ratio for the complete 9-year data set was 19.6 (SD = 2.6), well above the 16N: IP Redfield ratio. Major differences were also observed for the molar N:P stoichiometrics of the dissolved inorganic nutrient pools (i.e., N+N:SRP) versus the total dissolved nutrient pools (i.e., TDNiTDP; Fig. 22). The greatest differences were observed in the upper 0-400 m of the water column (and, especially in the upper 0-100 m) where dissolved organic nutrients are present as significant fractions of the TDN and TDP pools. Whereas the dissolved inorganic N:P ratios in the upper water column were significantly lower than the Redfield ratio of 16N:1P, the N:P stoichiometry of the total dissolved pool (inorganic plus organic) was significantly greater than the Redfield ratio by as much as 50% (Fig. 22). Furthermore, there were systematic changes in the N:P stoichiometry as a function of water depth; inorganic N:P increased toward a ratio of approximately 14, while total N:P decreased toward the same value (Fig. 22). In both data sets, the greatest rate of change in N:P with depth was in the 100- to 400-m region of the water column. The relatively high TDN:TDP ratios in the near-surface waters are consistent with the hypothesis that P, not N, is the (or one of several) production rate limiting nutrient(s) in this ecosystem. This conclusion assumes that the TDN and TDP pools are fully bioavailable (see Smith, 1984; Jackson and Williams, 1985). However, recent research on dissolved organic matter suggests that near-surface pools are composed of at least two components: one that is locally produced and consumed during microbial metabolism (the labile pool), and one that may be more refractory. Although it is impossible to quantify these subcomponents using existing analytical techniques (and in reality there may be a continuum of bioavailabilities) for the sake of the present discussion we will assume that the mean deep-water (>600 m) DON and DOP pools are refractory. If TDN and TDP are corrected for these nonlabile components, the depth profile of N:P ratios assumes the characteristic "T-shape" (Fanning, 1992), but for a fundamentally different reason than the original author suggested. Rather than being a consequence of analytical uncertainties at low surface ocean concentrations, we hypothesize that the T-shaped profile for the corrected TDN:TDP ratios at Sta. ALOHA is a manifestation of an alternation between periods of N limitation (left-hand portion of the T) and periods of P limitation (right-hand portion of the T). Dinitrogen (N2) fixation is one of two major microbiological processes (the other being denitrification) that can significantly influence oceanic N:P stoichiometry on global scales. Several lines of evidence from Sta. ALOHA suggest that
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20
0
5
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Figure 22 Nitrogen-to-phosphorus (N:P) ratios versus water depth for samples collected at Sta. ALOHA during the period October 1988 to December 1997. (Left) Molar N:P ratios for dissolved inorganic pools calculated as nitrate plus nitrite (N-l-N):soluble reactive phosphorus (SRP). (Center) Molar N:P ratios for the "corrected" total dissolved matter pools (see text for details). (Right) Molar N:P ratios for total dissolved matter pools, including both inorganic and organic compounds, calculated as total dissolved nitrogen (TDN):total dissolved phosphorus (TDP). As a point for reference, the vertical dashed line in each graph is the Redfield molar ratio of 16N:1P. Redrawn from Karl et al. (2001b).
N2 fixation is an important contemporary source of new nitrogen for the pelagic ecosystem of the NPSG. In addition to the observed secular changes in SRP inventories and the N:P ratios already discussed, other independent measurements include: (1) Trichodesmium population abundances and estimates of their potential rates of biological N2fixation,(2) seasonal variations in the natural ^^N abundances of particulate matter exported to the deep sea and collected in bottom-moored sediment traps, and (3) increases in the DON pools during the period of increased rates of N2 fixation (Karl et aU 1997).
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At the beginning of the HOT program in 1988, biogeochemical processes in the gyre were thought to be well understood. New and export production were limited by the supply of nitrate from below the euphotic zone, and rates of primary production were thought to be largely supported by locally regenerated nitrogen. The contemporary view recognizes the gyre as a very different ecosystem (Karl, 1999; Karl et al, 2001a). Based on decade-long data sets, we hypothesize that there has been a fundamental shift from N limitation to P limitation (Karl et al, 1995; Karl and Tien, 1997). The ecological consequences of this hypothesized N2 fixation-forced P/ limitation, especially on DOP pool dynamics, is presented elsewhere (Karl et al, 2001b; see also Fig. 23). Suffice it to say that enhanced P/ cycling rates, shifts in the chemical composition of the DOP pool, and microbial biodiversity changes are all relevant features of these decade-scale ecosystem processes. The fundamental role of nutrient dynamics in biogeochemical processes
1970'S
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t
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i
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N/P = 25
1980
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P-limited Trichodesmium present
Figure 23 Schematic presentation of the NPSG alternating ecosystem state hypothesis. This cartoon depicts the contrasting N and P nutrient cycles during periods of low rates of N2 fixation (e.g., 1970s) and enhanced rates of N2 fixation (1980-present). It is believed that the increased frequency and duration of the El Nino-Southern Oscillation (ENSO) cycle since the early 1980s is a major cause of the N2 fixation rate enhancement (see Karl, 1999; Karl et al, 2001a). The small rectangles and ovals at the top of each panel represent the average N:P ratios in particulate and dissolved matter, respectively, and the upward and downward arrows are the N:P stoichiometry of imported (mostly dissolved) and exported (mostly particulate) matter. N2 fixation (on right) decouples the N;P stoichiometry of the NPSG ecosystem. The center panels depict the inventories of SRP during both phases of the cycle showing a secular decrease in SRP following the selection and growth of N2-fixing microorganisms, such as Trichodesmium. Many of these predictions have been confirmed during the 12-year study at Sta. ALOHA (see text).
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and ecosystem modeling demands that we have a comprehensive, mechanistic understanding of inventories and fluxes. Although the present ongoing ocean timeseries study at Sta. ALOHA has certainly not resolved all of these important matters, it does provide an unprecedented data set to begin the next phase of hypothesis testing.
VIII. DOP POOL CHARACTERIZATION A major analytical challenge in DOP pool characterization is the detection of individual compounds typically present at pM to nM concentrations dissolved in seawater medium containing approximately 35 g L"^ of inorganic salts. Preconcentration and separation using ion exchange resins, ion exclusion or similar chromatographic procedures or even lyophiHzation that have proven useful for the characterization of DOP in soil extracts and freshwater habitats (e.g., Minear, 1972; Hino, 1989; Nanny et ai, 1995; Espinosa et al, 1999) are generally not applicable for the analysis of marine DOP. Because abiotic synthesis of organic P is not likely to occur in the marine environment, both the presence of a detectable DOP pool, as well as its molecular weight spectrum and chemical composition are dependent upon biological, mostly microbiological, processes. If marine DOP is derived from living organisms, as it ultimately must be, then the molecular spectrum of P in living cells or in marine particulate matter should be a first-order inventory of DOP sources. The macromolecular composition (by weight percent) of an "average" bacterial cell is as follows: protein, 52%; polysaccharide, 17%; RNA, 16%; lipid, 9.4%; DNA, 3.2%; other, <3% (Stouthamer, 1977). Of these compound classes, only the nucleic acids and, to a lesser extent, lipids are P-rich. Correll (1965) has measured the percentage distribution of P in natural particulate matter from 11 stations in the sub-Antarctic and Antarctic waters and reported a predominance of RNA-P (15-74%) and lipid P (3-29%) with trace amounts (2-15%) of acid-soluble organic P; these results are consistent with expected subcellular pool distributions. Miyata and Hattori (1986) have also investigated the composition of natural plankton populations (i.e., particulate P) in Tokyo Bay via differential chemical extraction. Their results indicated that nucleic acid P and lipid P were the dominant forms of organic P, together accounting for about 60-70% of the total. A large cellular pool of P/ was also detected. As Waksman and Carey (1935) correctly noted many years ago, the DOM pool in seawater is in a "state of dynamic equilibrium" in which residues and waste products are the source terms and bacterial activity is the sink. The ambient chemical composition of DOM and individual DOP compound concentrations, therefore, reflect the net balance between production and utilization. Nearly 70 years ago, Krogh (1934) first estimated that the amount of DOM present in the sea was nearly
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300 times greater than that contained in all living organisms. He believed that this large reservoir of organic matter, including DOP, must represent "waste products" that cannot be recovered and may even be slowly accumulating. Furthermore, partial degradation, including photo- and chemical alteration processes, can potentially create DOP compounds that are not present in the organisms themselves. Consequently, the chemical composition of DOP in a given habitat can vary significantly as a result of either preferential production or preferential utilization of selected organic-P compounds or compound classes. The marine DOP pool is also expected to vary considerably, ranging from truly dissolved monomeric compounds through polymeric (IMW and HMW) compound classes to small (<0.2 /xm) particles and colloids. Colloidal organic matter is extremely abundant in the marine environment (Koike et al, 1990; Wells and Goldberg, 1991), but remains poorly characterized. The cumulative high surfaceto-volume ratio of marine colloids may facilitate complexation, aggregation, or adsorption interactions with truly dissolved compounds. Furthermore, some colloids may be consumed directly by filter-feeding microorganisms. Colloids appear to have relatively short residence times in the upper ocean, based on ^^^U/^^'^Th disequilibrium measurements (Moran and Buesseler, 1992), so they may play a key role in the interactions between DOM production and removal processes. Fox et al. (1952) may have been the first to study the distribution and chemical composition of marine colloids, which they termed "leptopel." In their field studies, they collected this material by adsorption onto finely powdered metal oxide/hydroxide matrices. The concentrated colloidal materials were then subjected to chemical extraction and analysis by a variety of techniques. Although no direct estimates of the P content of this leptopel were given, they concluded that "organic leptopel was significant to the biogeochemical cycles of C, N and P." More recently, the technique of cross-flow filtration (CFF) has been used to isolate and concentrate colloidal marine materials (e.g., Whitehouse et al., 1990; Buesseler et al., 1996) for subsequent analysis. In the absence of selective adsorption or contamination, TP should behave conservatively in CFF systems. However, in practice, large deviations are observed including an enigmatic production of colloidal P during sample processing (Bauer et al, 1996). A similar production of colloidal P during ultrafiltration processing of freshwater samples has also been reported (Nanny and Minear, 1997), suggesting that some caution is advised in the interpretation of coUoidal-P data sets. For the purposes of this review and except where otherwise noted, colloids are included in the "dissolved" matter fraction. Marine DOP can be characterized by a number of independent techniques including, for example, direct chemical analysis of selected molecules or compound classes, the use of specific hydrolytic enzymes or partial photochemical degradation, chromatographic, and molecular weight fractionation, and ^^P NMR. The combined use of molecular weight separation and specific chemical class
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characterization by, for example, ^^P NMR or enzymatic hydrolysis is beginning to provide a glimpse of complexity of the DOP pool. From an ecological and biogeochemical perspective, the direct measurements of specific P-containing organic compounds are the most useful data sets because their fluxes can be traced to specific sources and sinks. However, the few studies which have been conducted have identified only a minority fraction of the ambient DOP pool, leaving the majority uncharacterized. Below, we present several independent approaches to DOP pool characterization, beginning with the least specific method of physical separation by molecular weight/size and ending with specific methods of single compound or compound class characterization. Example marine DOP data sets will also be presented for each major application. We end this section with some speculation on the possible chemical composition of the uncharacterized majority of the DOP pool.
A. MOLECULAR WEIGHT CHARACTERIZATION OF THE DOP POOL Various techniques have been used to fractionate DOP by molecular weight, size, ionic charge, or ability to adsorb onto specific resins (e.g., nonionic XAD). When combined with chemical detection systems these procedures can be used to characterize the total DOP pool. However, it is uncertain how much ecological information can be obtained by these separation techniques alone because DOP bioavailability is probably not directly correlated with these physical properties. Although the HMW organic fraction has often been considered to be more biorefractory than LMW matter, recent metabolic evidence has shown just the opposite for selected marine habitats (Amon and Benner, 1996). Currently it is impossible to determine how representative this HMW DOP is of either the total DOP or the more ecologically relevant BAP pool. A basic problem in studies of DOP pool characterization is the need for preconcentration of selected compounds prior to analysis. A widely used method in freshwater habitats, but less so in marine ecosystems, is gel chromatography, •isually employing Sephadex gels. This provides for the separation of HMW-P, including colloids, in the "void volume" from IMW and LMW fractions (Broberg and Persson, 1988). Matsuda and Maruyama (1985) used Sephadex G-25 gel chromatography to characterize the DOP pool in coastal waters of Tokyo Bay. Several model DOP compounds were coanalyzed to establish the overall efficacy of this method; HMW DOP compounds (MW >5 kDa) were contained in the void volume, LMW monophosphate esters (e.g., Gly-3-P) eluted prior to P/, and nucleotides eluted after P/. Prior to separation, the TDP was first concentrated 30- to 35-fold by rotary evaporation and salt exclusion, a method which recovered only approximately 50% of the total P. Separate HMW and LMW DOP pools were observed in all
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seawater samples that were analyzed. Both fractions decreased with increasing water depth, suggesting that biochemical lability was independent of molecular weight. In contrast, DOP compounds of IMW (>400 Da but <5 kDa) were relatively constant and, perhaps, biochemically stable (Matsuda and Maruyama, 1985). The IMW DOP fraction also absorbed UV light, consistent with nucleotide bases; no further chemical characterization was given and no ecological implications were discussed. More recently, the method of tangential flow ultrafiltration has been used to isolate and concentrate DOM for subsequent chemical analysis (e.g., see Benner et al, 1992). However, this method is very selective for the IMW and HMW (generally >1 kDa) compounds, which for many aquatic ecosystems may be <35% of the total organic matter pool. In a series of carefully controlled experiments, Nanny et al (1994) evaluated the behavior of ultrafiltration and reverse osmosis for concentration and molecular size fractionation of SNP in freshwater lakes. They evaluated both exogenously supplied standard compounds and the effects of increasing ionic strength by NaCl addition. Their results demonstrated that membrane type, including pore size, ionic strength, specific DOP test compound and volume concentration factor were all key variables that affected model compound—and presumably natural DOP compound—^recovery. Another potential problem with the interpretation of molecular weight separations is the real possibiHty of LMW, monomeric DOP compound, or Fi association with HMW materials. While the exact mechanism is not well understood, adsorption, hydrogen bonding, metal bridging, and even Maillard reaction are all distinct possibilities (Carlson et al, 1985). A novel and significant seawater application of tangential flow ultrafiltration for HMW DOP pool concentration, coupled with ^^P NMR molecular characterization (Clark et al, 1998) is presented in a subsequent section of this review (see Section VIII.C). B. D O P
POOL CHARACTERIZATION BY
ENZYMATIC CHARACTERIZATION
There are at least three separate applications for the use of specific enzymes in ecological studies of the marine P-cycle: (1) the presence and relative activities of specific enzymes in natural microbial assemblages can be used as physiological indicators of Fi stress, deficiency, or other ecological processes; (2) in vitro or in vivo measurements of the rates of specific enzymes in natural assemblages of microorganisms can provide relevant information on DOP turnover rates; and (3) exogenous additions of specific enzymes to whole, filtered, or partially purified seawater samples can be used to help characterize the DOP pool composition and to determine its potential bioavailability. The first two applications are discussed in a subsequent section; the third application is discussed below.
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In theory, selected DOP compounds or compound classes could be estimated by measurements of P/ accumulation in cell-free seawater samples following a timed incubation with an exogenous purified enzyme or multiple enzyme cocktail. This is a straightforward and versatile approach. For example, Herbes et al (1975) used three separate enzyme treatments to characterize both the LMW and HMW DOP fractions from a variety of aquatic habitats. This method could also be used to characterize nascent DOP that is produced during ^^P/ or ^^Vi tracer addition experiments, but to our knowledge this has not yet been attempted. The specificity of the enzyme(s) used will establish the specificity of DOP compound or compound class analysis. In 1966, Strickland and Solorzano described a quantitative assay for total dissolved phosphomonoester P (PME-P) using exogenous APase from E. coli. An adaptation of this method using immobilized E. coli APase has also been described (Shan et al, 1994). This assay monitors the appearance of SRP during timed incubations following APase addition, relative to controls without exogenous enzyme. Conversely, the in situ activity of APase can be estimated by adding excess substrates followed by timed measurements of P/ or other by-products (see Section IX.C.l). Significant PME-P concentrations ranging from 0.05 to 0.45 /xM P were detected in coastal California seawater samples (Strickland and Solorzano, 1966). APase can also release P/ from pyro-P/ and poly-P/ (Rivkin and Swift, 1980), so technically P/ increase from APase treatment only provides an upper constraint on PME-P concentration in seawater. However, independent estimations of pyro-Pi and poly-P/ concentrations could be made to establish limits on this potential source of interference. Technically, though, this should be termed the APase-hydrolyzable P (APHP) pool, rather than PME-P. Taft et al. (1977) applied this assay to samples collected in Chesapeake Bay over 1 full year. PME-P/APHP was > 10% of the total DOP pool in 25 of 61 samples (but typically <20%); PME-P/APHP concentrations covaried with DOP, and both peaked in late summer (Taft et al, 1977). Kobori and Taga (1979) measured PME-P/APHP concentrations, APase activity, bacterial cell number and percentage of isolates that are APase positive, and DOP in a variety of Japan coastal habitats. Ambient concentrations of PME-P/APHP ranged from 19 to 50% of the total DOP but, in general, appeared to be scavenged to low concentrations, presumably because they are readily used by the APase-containing bacteria that dominated these habitats. At depths greater than 100 m in Sagami Bay, PME-P/APHP was undetectable in the environments that were studied. A similar approach to detecting other components of the marine DOP pool has employed DNase and/or RNase treatments of isolated dissolved nucleic acids to estimate the specific enzyme-hydrolyzable components of these macromolecular fractions by measurements of DNA or RNA before and after specific enzyme treatments (DeFlaun et al, 1987; Siuda and Chrost, 2000). Most, but not all, of the extracellular nucleic acid pool appears to be nuclease-hydrolyzable, which implies
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that it is readily assimilated by microorganisms. Direct estimates of [^H]-DNA turnover (Paul et al, 1987) have also supported this conclusion. The "residual" nucleic acid fraction that is not degraded by specific nuclease treatment, could be adsorbed to clay particles or otherwise chemically or physically altered. These semilabile or truly refractory nucleic acid fractions could accumulate over time. McKelvie et al (1995) devised a method using immobilized phytase that was designed to selectively release P/ from phytic acid and related inositol phosphates. However, in practice the phytase system was less specific than anticipated so the defined pool was termed "phytase hydrolysable P" or PHP (McKelvie et al, 1995). PHP was compared to SRP, and for a variety of aquatic environments including several estuarine but no open ocean habitats. PHP was a significant percentage of the "apparent DOR" However, potential problems with the inability to separate P/ from labile DOP in the standard SRP determination could lead to an underestimation of DOP, and overestimation of the percentage of PHP by the methods employed. This analytical limitation is not unique to the phytase assay. In any case, most of the DOP pool in the environments studied appeared to be enzyme hydrolyzable. Suzumura et al (1998) used tangential flow ultrafiltration techniques to isolate LMW and HMW SNP fractions in Tokyo Bay, Japan. These pools were then characterized using two phosphohydrolytic enzymes, APase (as above) and phosphodiesterase (PDEase; EC 3.1.4.1). The former enzyme alone will release P/ from a variety of PME, and the combination of the two enzymes will release P/ from nucleic acids. The molecular weight spectrum revealed a dominance of LMW-SNP (54-76% of the bulk SNP); no further characterization of this fraction was reported. Enzymatic characterization of the HMW-SNP fractions revealed the presence of both phosphomonoesters and diesters, with diester compounds in greatest abundance. However, on average, the majority of the isolated HMW-SNP was resistant to the enzyme treatments (Suzumura et al, 1998). Pretreatment with chloroform, converted a portion of HMW-SNP to an enzymatically labile form and, on this basis, the authors suggested the presence of hydrophobic P-containing compounds, perhaps phospholipids. Presumably, this latter pool of enzymatically resistant compounds is also unavailable for microbial decomposition without prior hydrolysis or other diagenetic alteration.
C. DOP POOL CHARACTERIZATION BY ^^P N M R Nuclear magnetic resonance (NMR) spectroscopy has proven to be a powerful analytical tool for the molecular characterization of marine DOM. The abundant, naturally occurring isotope of P, ^^P, has a magnetic moment that is detectable by dipole resonance in an applied magnetic field. Although resonance is observed that is due solely to the P atom, chemical shifts due to the electron shells of
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the other atoms with which P is associated give the diagnostic NMR spectra. Specifically, mono- and di-P esters are readily distinguishable from phosphonates and can be identified in bulk DOP concentrates. Both solution and solid-state magic angle spinning (MAS) ^^P NMR techniques have been employed in marine ecosystems (Ingall etal, 1990). A major limitation with this method is the detection limit; marine DOP must be concentrated many thousand-fold prior to analysis. During the concentration process, DOP can be selectively eliminated (e.g., by molecular weight) or chemically altered. Detection of Pi in the HMW fraction indicated either postconcentration DOP hydrolysis or desorption of P/ from HMW organic/inorganic matter, or both (Nanny and Minear, 1997). Ironically, the NMR measurement technique itself is "nondestructive." Nanny and Minear (1997) have combined ^^P NMR with selective chemical hydrolysis and other reaction techniques to further characterize the major compound classes of HMW DOP isolated from aquatic ecosystems. For analysis of Crystal Lake, they detected phosphonates in the HMW DOP, but not in the IMW or LMW fractions. Using tangential flow ultrafiltration and solid-state cross-polarized magic angle spinning (CPMAS) ^^P NMR, Clark et al (1998,1999) demonstrated that approximately 75% of the HMW DOP collected at a station in the South Pacific Ocean (12°S, 134°W) was composed of ester-hnked P compounds and the remainder (^25%) were phosphonates (Fig. 24). Both classes could potentially include a broad spectrum of individual compounds with independent sources and sinks and
r-
100
80
1^ 60
40
I -20 -40 20 Chemical Shift (ppm)
-60
-80
-100
Figure 24 ^^P NMR spectra of HMW DOP from several reference depths in the Pacific Ocean (12°S, 135°W). The peak at 0 ppm is indicative of phosphate esters, and the peak at 25 ppm denotes phosphonates. Asterisks indicate spinning sidebands, an artifact of magic angle spinning. Reprinted with permission from Clark e/fl/., (1998).
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variable residence times. Clark et al. (1998) also noted a significant shift in the bulk C:N:P elemental composition of the isolated HMW-DOM with depth (C:N:P molar ratios of 247:15:1, 321:19:1, and 539:30:1 for surface, 375 m, and 4000 m, respectively), indicating a selective remineralization of P from seawater DOM. The relatively high proportion of phosphonates was unexpected and was interpreted to be a result of the selective retention of phosphonates over time, based on the presumption that these compounds are not readily degraded in the sea. Equally intriguing and enigmatic is the fact that despite a sixfold decrease in HMW DOP concentration from 90 nM in the surface to 15 nM at a depth of 4000 m, the ^^P NMR spectra show P-esters and phosphonates at approximately identical proportions, indicating a coupled utilization (Fig. 24). In the absence of a deep water source of P-esters, the hypothesized higher rates of P-ester biodegradation should have resulted in an increasingly lower proportion of P-esters with depth in the water column; this is contrary to what was observed. From the information presented, one is led to conclude: (1) both compound classes are ubiquitous in the marine environment including the South Pacific abyss, (2) both P esters and phosphonates have similar, probably slow, turnover times in the open ocean, and (3) both compound classes are used in proportion to their ambient concentrations. What is still unresolved from the extant data set is the primary source of the high phosphonate to P-ester DOP at all water depths. More recently, Kolowith (nee Clark) et al. (2001) extended their South Pacific Ocean HMW DOP/^^P-NMR measurement program to a station in the North Atlantic subtropical gyre (32°N, 64°W), three stations in the North Pacific Ocean (10°N, 140°W; 18°N, 134°W; 22°N, 130°W), and two stations in the North Sea. The cumulative result from all 16 individual samples shows a remarkable uniformity in composition regardless of water depth or distance from shore; P-esters and phosphonates are present in similar proportions in the HMW DOP throughout the world ocean (Kolowith et al., 2001). For selected sampling sites simultaneous collections of PP (0.1- to 60-/xm fraction) were also obtained, and these were subjected to the same ^^P NMR analysis. Only P-ester compounds were detected in the particulate matter concentrates, reemphasizing an apparent relative enrichment of phosphonates in the DOM pools (Kolowith et al, 2001). D. DOP POOL CHARACTERIZATION BY PARTIAL PHOTOCHEMICAL OXIDATION Karl and Yanagi (1997) used continuous-flow UV photodecomposition to provide a partial characterization of SNP in the subtropical North Pacific Ocean. TDP was reproducibly subdivided into three chemically distinct pools: SRP (presumably dominated by Fi), UV-labile SNP (PUV-L, containing primarily monophosphate esters), and UV-stable SNP (Puv-s» containing primarily nucleotide di- and
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30 E
25
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20
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i c
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-
* ^ *
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4 ^^
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PuV-L Puv-s
::4—====^mlTL^^^ SRP
Q.
1
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Nov
Oct
Dec
1991
Jan
1
Feb 1992
Mar
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Figure 25 Dissolved P pool inventories at Sta. ALOHA (22°45'N, 158°W) for the period September 1991-March 1992. Data shown are the 0- to 100-m depth-integrated P concentrations (mmol m"-^) for each of the pools identified: SRP (A), PUV-L ( • ) . Puv-s ( • ) , and TDP (•); see text for operational definitions. Redrawn from Karl and Yanagi (1997).
triphosphates, nucleic acids, and other compounds that are resistant to the lowintensity UV treatment that was developed for the purpose of organic-P pool characterization). Field application of these procedures to samples collected at Sta. ALOHA (22°45^N, 158°W) during the period September 1991 to March 1992 revealed the presence of all three operationally defined pools with an upper water column (0-100 m) average of 23% SRP, 26% Puv-s, and 51% PUV-L (Karl and Yanagi, 1997). However, the Puv-s pool did vary nearly threefold (4.38 mmol P m~^ in December to 11.07 nmiol P m~^ in March; Fig. 25), suggesting variable production or consumption rates. Depth profiles also revealed near surface enrichments in the Puv-L pool, suggesting a direct coupling with photosynthetic processes (Karl and Yanagi, 1997).
E. DIRECT MEASUREMENT OF D O P COMPOUNDS Despite recent progress in TDP pool characterization, individual compound analyses are difficult and therefore rare. Only a few organic-P compounds or compound classes have been measured in seawater. These individual compounds probably have multiple sources and sinks, and variable residence times in the marine environment. For example, some compounds are probably excreted from living cells (e.g., vitamins and c-AMP), while others are most likely produced only following cell death or lysis (e.g., nucleic acids). Unfortunately, no comprehensive
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study has been conducted to attempt a P mass balance for a given water sample, but it appears that no more than half, and probably less, of the marine DOP pool has been chemically characterized. This uncertainty in SNP pool composition is a major impediment in our attempts to quantify P fluxes in the marine environment. 1. Nucleic Acids None of the five major nucleic acid bases contain P; only the nucleotide derivatives and nucleic acid polymers thereof are part of the DOP pool (Table I). Pioneering research efforts to measure DNA in the sea began in the late 1960s with the quantitative laboratory and field studies of Holm-Hansen and colleagues (Holm-Hansen et al, 1968; Holm-Hansen, 1969). During these initial investigations it was established that a large proportion of particulate DNA was associated with nonliving organic matter (Holm-Hansen, 1969). Subsequent studies confirmed the presence of a large pool of detrital DNA, in both particulate (Karl and Winn, 1984) and dissolved fractions (DeFlaun et al, 1986). Paul et al. (1990) have also detected the intact gene for the enzyme ribulosebisphosphate carboxylase/oxygenase (rbcL) as part of the dissolved DNA (D-DNA) pool indicating that phytoplankton must be considered a probable source for extracellular DNA. Dissolved RNA (D-RNA) has also been detected in seawater (Karl and Bailiff, 1989; Sakano and Kamatani, 1992). Compared to the volume of research focused on D-DNA very Httle is presently known about D-RNA, even though it is sometimes the larger of the two pools in seawater and in cells. If viral lysis is a major control on bacterial and phytoplankton populations in the marine environment, and there is still active debate on this matter, then the production of dissolved nucleic acids in seawater may ultimately be controlled by the viral lytic cycle. The measurement of dissolved nucleic acids requires isolation either by adsorption onto barium sulfate (Pillai and Ganguly, 1972) or hydroxy apatite (Hicks and Riley, 1980), or by precipitation using ethanol (DeFlaun et al, 1986), cetyltrimethylammonium bromide (Karl and Bailiff, 1989), or polyethylene glycol (Maruyama et al, 1993), followed by colorimetric or fluorometric dye detection. Depending on the fluorescent dye selected, either single-stranded DNA or singleplus double-stranded DNA is measured (Sakano and Kamatani, 1992). Some DNA may be bound to histone or similar protein and in this state may be inaccessible to nucleases or to the specific dyes commonly used to quantify nucleic acids. Dissolved nucleic acid can also be measured, indirectly, by high-performance liquid chromatography (HPLC) analysis of the free nucleic acid bases released following polymer hydrolysis (Breter et al, 1977). There are unique advantages and disadvantages of each method (Siuda and Glide, 1996), but a detailed discussion is beyond the scope of this chapter. Research conducted over the past decade has indicated that extracellular DNA has at least three forms: (1) naked, free DNA, (2) DNase-resistant naked
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DNA possibly adsorbed onto small particles or contained within colloids, and (3) protein-DNA complexes, perhaps virus particles. Though less carefully described, D-RNA should have a similar distribution spectrum. Initially, certain researchers thought that much of the dissolved nucleic acid was essentially virus particles (see Wommack and Col well, 2000 for a historical account); this important controversy will not be resolved here. Nevertheless, at least three lines of independent evidence argue against this: (1) the cooccurrence of large concentrations of D-RNA (RNA-containing marine viruses are rare; Steward et al, 1992), (2) the broad D-DNA molecular weight spectrum (<0.1 to >36 k base pairs; DeFlaun et al, 1987), and (3) direct measurements of virus particles and quantitative estimations of their potential contributions to the D-DNA pool. Virus particles, if present, would contribute to the "non-DNase digestible D-DNA" that has been measured for many marine habitats (e.g., Maruyama et al, 1993). During an extensive, time-series investigation in the North Adriatic Sea, Weinbauer et al (1993) reported that virus particles averaged 17.1% (range, 0.788.3%) of the measured D-DNA. Using the method of vortex flow filtration, Paul et al (1991) demonstrated that viral DNA averaged only 3.7% (range 0.9-12.3%) of the D-DNA for a variety of aquatic habitats of different trophic states. Jiang and Paul (1995) used differential centrifugation to separate seawater D-DNA into truly soluble and bound (viral particles, colloids, adsorbed D-DNA) forms; D-DNA pool averaged 50% soluble, 8-15% viral, and 3 5 ^ 2 % other bound D-DNA. Kingdom probing of the isolated D-DNA using 16S rRNA-targeted oligonucleotide probes (universal, eubacterial, and eukaryotic) indicated that D-DNA was a complex domain mixture. However, these results also confirmed a relatively low viral particle contribution to D-DNA in the variety of marine habitats investigated (Jiang and Paul, 1995). Nevertheless, even if the nonliving virus particles did represent a large portion of the dissolved nucleic acid pool in seawater, they would still be "DOM" by our operational definitions and would still need to be considered as part of the dynamic marine P-cycle. The probable fate of free virus particles is to be consumed by protozoan grazers, degraded by cell-associated or free enzymes or adsorption onto sinking particles. Consequently, virus particles are like all other nonliving organic-P pools in the sea from an ecological perspective. The distribution of dissolved DNA follows the general pattern of DOM in the marine environment; namely, highest concentrations in coastal waters, decreasing with distance from shore and with depth in the water colunm (DeFlaun et al, 1987; Fig. 26). For samples collected at an oligotrophic North Pacific station, Karl and Bailiff (1989) reported higher concentrations of D-DNA than particulate DNA (P-DNA), and D-RNA to D-DNA ratios ranging from 3 to 10, similar to particulate RNA:DNA ratios found in growing microorganisms. Although no DOP data were presented, the P content of the D-RNA plus D-DNA fractions could have accounted for approximately 30-40 nM DOP in the euphotic zone of their oligotrophic North
Dynamics ofDOP
317 DNA (nM-P) 5
10
600 Figure 26 Vertical distributions of D-DNA ( • , solid line) and P-DNA ( • , dashed line) for samples collected in the Gulf of Mexico at 26°30'N, 85°W. Redrawn with permission from DeFlaun et al (1987). DNA P was calculated from the reported concentrations (/xg L~^), assuming a P content of 9.5% by weight.
Pacific Station; DOP in this habitat is typically 250-400 nM (Orrett and Karl, 1987). For a series of stations in the English Channel, Hicks and Riley (1980) reported that P contained in the dissolved nucleic acid fraction (RNA plus DNA) accounted for 2 7 ^ 9 % of the total DOP. A similar estimation for samples collected in Tokyo and Sagami Bays yielded a mean dissolved nucleic acid P of 12.9% of the total DOP (Sakano and Kamatani, 1992). The latter authors also documented significant temporal (seasonal?) changes in the concentrations of both D-RNA and D-DNA and especially in the D-RNA/D-DNA ratio (Fig. 27). In another study of D-DNA dynamics in Tampa Bay, Florida, both seasonal and diel concentration variations were observed (Paul etal, 1988; Jiang and Paul, 1994). The mechanism for the significant diel periodicity was not identified, and it is likely to be a result of the balance between production and utilization processes. D-DNA P averaged
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Figure 27 Vertical distributions of D-DNA ( # , solid line) and D-RNA ( • , dashed line) for samples collected in Tokyo Bay (35°08'N, 139°50'E) during Nov 1983 (left) and May 1984 (right). Redrawn with permission from Sakano and Kamatani (1992). Nucleic acid P was calculated from the reported RNA/DNA concentrations {\i% L~^), assuming P contents of 9.2 and 9.5% by weight, respectively, for RNA and DNA.
6.6% of the total DOP, but because D-RNA was not measured, this value should be considered a lower constraint on the contribution of dissolved nucleic acids to marine DOP. A significant research effort has been invested to ascertain extracellular nucleic acid production and utilization processes. Although selected bacterial species produce extracellular DNA during growth, no comparable experimental data are available for D-RNA production. Paul et al (1987) investigated the dynamics of D-DNA (i.e., production and turnover rates) in subtropical coastal and oceanic environments. Daily D-DNA production by heterotrophic bacteria (using [^H] thymidine) was ~ 5 % of the ambient pool. Active consumption of radiolabeled E. coli DNA by cell-associated and extracellular nucleases was also demonstrated. The utilization of D-DNA appears to involve hydrolysis by nonspecific cell-associated nucleases, uptake of individual nucleic acid bases, and salvage pathway biosynthesis back into cellular nucleic acids. Likewise, viral RNA seeded into filtered-sterilized coastal seawater was stable for approximately 1 month compared to only 2 days in paired unfiltered samples (Tsai et ai, 1995), indicating a probable rapid turnover of D-RNA.
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Novitsky (1986) also examined the degradation of ^H-labeled detrital DNA and RNA in sedimentary marine ecosystems. He found that: (1) RNA was degraded faster than DNA, (2) both nucleic acids were ultimately degraded to the same extent, and (3) both dissimilation to ^HaO and assimilation via salvage pathways into new RNA and DNA were evident. The production of extracellular nucleic acids may also be a manifestation of microzooplankton grazing processes or viral-induced cell lysis. The concentrations of D-DNA and nanoflagellates were found to co-vary at a station in the Adriatic Sea (Turk et al, 1992); quantitative estimates indicated that most of the ingested DNA was subsequently released into the environment. The turnover of D-DNA was greater in P-limited than in N-limited habitats (Lorenz and Wackemagel, 1994), suggesting that DNA, a P-enriched macromolecule, may be an important source of P for microbial assemblages. The presence of extracellular nucleic acids and their rapid turnover have important ecological implications. First, RNA and DNA are N- and P-enriched components of the seawater DOM pool (Table I), which could provide nutrients for autotrophic and heterotrophic microorganisms. Second, dissolved nucleic acids could provide a supply of purine and pyrimidine bases for nucleic acid biosynthesis. This would spare the cell the energy that would otherwise be required for de novo synthesis of these invaluable precursors. Third, and perhaps most importantly, free DNA could effect genetic transformation under ecologically permissive conditions. Natural transformation by extracellular DNA is a potential mechanism for lateral gene exchange in natural aquatic habitats. Bacteria are the only organisms known to actively take up DNA and recombine it into their genomes, a process called natural transformation (Redfield et al, 1997), and may have evolved it as a means for bacteria to adapt to changing environments. The presence of gene-sized DNA fragments in seawater prompted DeFlaun and Paul (1989) to look for natural transformation among marine microbial assemblages and, later, Paul et al. (1991) were the first to document transformation in seawater samples under ambient environmental conditions. The D-DNA pool may, therefore, represent the "conmiunity genome" (DeFlaun and Paul, 1989). The ecological implications of horizontal gene transfer are profound; we believe that this is an important contemporary area of research, poised for rapid progress in the next decade. 2. ATP and Related Nucleotides ATP is a biologically labile, but chemically stable, compound, with key functions in cellular energetics, metabolism, and biosynthesis. Its inherent chemical stability predicts that there might exist a detectable dissolved ATP (D-ATP) pool in seawater that would exist as a transient between ATP production and utilization. Azam and Hodson (1977) were thefirstto report the presence of D-ATP in seawater
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CAMP (pM-P)
D-ATP (pM-P) 200
400
600
800
1000
0
1
2
3
4
Figure 28 Dissolved ATP and c-AMP concentration versus depth profiles for samples collected in the North Pacific Ocean. (Left) D-ATP concentrations: ( # , soUd line) at 32°42'N, 117°23'W in the San Diego Trough (redrawn with permission from Azam and Hodson, 1977) and ( • , dashed line) at Sta. ALOHA 22°45'N, 158°W (Bjorkman and Karl, 2001) versus depth. (Right) c-AMP versus depth at a station 41 km offshore in the Southern California Bight (redrawn from Anraierman and Azam, 1981).
and since that time it has been detected in all marine and freshwater environments where measurements have been attempted (e.g., Fig. 28, left). The quantitative determination of D-ATP requires isolation and partial purification (e.g., H2SO4 extraction, adsorption onto activated charcoal, desalting, elution into an ammoniacal ethanol solution, and vacuum evaporation; Hodson et ai, 1976) prior to detection by thefireflyluciferin-luciferase bioluminescence assay. The recovery of D-ATP by this rather labor-intensive procedure is typically around 30% (Karl and Holm-Hansen, 1978; McGrath and Sullivan, 1981), although higher recovery has also been reported (Hodson et ai, 1976). Other adenine and nonadenine nucleotides are also coadsorbed and coconcentrated by the charcoal method. The firefly assay confers a high sensitivity and substrate specificity. Only ATP and, to a lesser extent, guanosine triphosphate (GTP) and uridine triphosphate (UTP) react with crude luciferase enzyme preparations to yield light; however, the presence and relative concentrations of these various substrates can be determined by the kinetics of luciferase light emission (Karl, 1978). More recently, Bjorkman and Karl (2001) have devised an alternative D-ATP concentration technique that is based upon coprecipitation with magnesium hydroxide (i.e., the MAGIC technique; Karl and
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Tien, 1992), followed byfireflybioluminescence. This simple and straightforward technique also routinely yields a high recovery of ATP (>90%) and, if necessary or desired, can yield quantitative recovery. Nonadenine nucleotide triphosphates (e.g., GTP) are also quantitatively coprecipitated. A HPLC technique has also been described (Admiraal and Veldhuis, 1987), but the relatively poor detection limit precludes its use without some preconcentration method. The advantage of HPLC is that all nucleotides and related derivatives can be separated and quantified from a single run. D-ATP is typically highest in surface coastal waters, decreasing substantially with distance from shore and with depth (Azam and Hodson, 1977; Hodson et al, 1981; McGrath and Sullivan, 1981; Figure 28, left); however, ambient near-surface ocean concentrations are not static. For example, the ambient D-ATP pool in the Southern Ocean varied considerably during and following the spring bloom of phytoplankton, with a peak abundance of >2.5 nmol L~^ in December-January and minimum concentrations (<0.004 nmol L~^) in March (Nawrocki and Karl, 1989). At the height of the bloom, D-ATP was approximately 60% of the corresponding particulate ATP (P-ATP), but by March P-ATP was much more dominant. For subeuphotic zone waters off southern California (500 m depth), D-ATP typically exceeds P-ATP, sometimes by an order of magnitude (Azam and Hodson, 1977). However, more recent and, perhaps, more reliable MAGIC-based estimates of subeuphotic zone D-ATP concentrations from the subtropical North Pacific Ocean revealed a much steeper concentration versus depth gradient and much lower deep water concentrations than previously suggested; nevertheless, D-ATP was still detected at a depth of 500 m (Fig. 28, left). This presence of D-ATP in deep seawater argues either for a local source or for a long residence time, or both. While ATP is chemically stable in seawater, with a half-life of approximately 8 years at 21°C (Hulett, 1970), it is microbiologically labile with ambient pool turnover times of hours to days in near-surface temperate waters (Azam and Hodson, 1977; Hodson et al, 1981; McGrath and Sullivan, 1981). D-ATP is used almost exclusively for biosynthesis and less than 2% of the [^"^CJATP tracer was respired (Azam and Hodson, 1977). Marine microorganisms can and do assimilate D-ATP, in part for P and in part for purine salvage and nucleic acid synthesis. Consequently, D-ATP concentration measurements coupled with exogenous radiolabeled (^^P/^^P, ^H, ^"^C) D-ATP uptake measurements can be used to estimate D-ATP and mass flux through marine microbial assemblages (Azam and Hodson, 1977). D-ATP is one of the few organic-P compounds that can be measured at ambient pool concentrations and can be tracked through the microbial food web with specific radioisotopic tracers. In this regard, and especially considering its fundamental role in cellular bioenergetics and biosynthesis, ATP might be considered a "model" compound in studies of the marine P cycle. Because ATP is the primary energy currency in all living cells, the presence of D-ATP, often at concentrations exceeding P-ATP, may seem enigmatic. Why would
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cells leak or otherwise lose such a vital intracellular constituent? The potential mechanisms of D-ATP production, including exudation, inefficient grazing, cell death or viral lysis, are not well constrained. It is possible that the presence of nonATP nucleotides, measured along with D-ATP, might help to identify the major sources. For example, if the grazing of actively growing cells is the main source for D-ATP in seawater, then one might also expect to observe other nucleotide triphosphate compounds that are vital for biosynthesis (e.g., GTP), and a high ratio of ATP relative to total adenylates (sum of ATP + ADP -h AMP). If, on the other hand, D-ATP was a result of viral lysis or programmed death and autolysis, then non-ATP adenine nucleotides (e.g., ADP and AMP) would be expected to dominate the total extracellular nucleotide pool. Nawrocki and Karl (1989) compared the pattern of intracellular and extracellular adenine nucleotides (reported as the adenylate energy charge; ECA = [ATP 4- V2 ADP]/[ATP + ADP + AMP]) for samples collected in Bransfield Strait, Antarctica, as a direct test of the D-ATP source hypothesis. During the early phase of the spring bloom (December), the particulate and dissolved ECA ratios were indistinguishable (D-ECA /P-ECA = 1.01 ib 0.06) at all stations. These results suggested that grazing or excretion could be the primary source of D-ATP in this habitat. A calculation revealed that a loss of approximately 2-3% of the total ATP production by the cells present in the water column would be needed to account for the measured ATP flux. More recently, Bjorkman and Karl (2001) have reported elevated D-GTP concentrations and high D-GTP/D-ATP ratios (approximately 1:1) in near-surface waters (0-100 m) of the subtropical North Pacific gyre. These field results are consistent with a grazing/excretion source. 3. Cyclic AMP Adenosine 3', 5'-cyclic monophosphate (c-AMP) is a ubiquitous cellular compound that is required for the synthesis of a number of inducible catabolic proteins, for bacterial flagellum synthesis, catabolite gene activation, and other key functions (Botsford and Harman, 1992). It is found in both prokaryotes and eukaryotes, including marine bacteria, phytoplankton, and probably Archaea. Intracellular concentrations of c-AMP are carefully regulated by enzymatic synthesis and degradation, as well as by active excretion from the cell. In 1981, Anmierman and Azam documented the existence of c-AMP in coastal seawater. The dissolved c-AMP was extracted from seawater and concentrated using the H2S04-charcoal adsorption technique used previously by Hodson et al (1976) for D-ATP measurements. The isolated c-AMP was quantified by a commercially available radioimmunoassay. At one offshore station in the Southem California Bight, c-AMP was maximal (2-3 pM-P) in the near surface water, decreasing to <1 pM-P at 500 m (see Fig. 28, right). In near-shore seawaters, the
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concentration of dissolved c-AMP was generally higher and varied approximately fourfold with time of day, suggesting a dynamic production and consumption cycle; concentrations peaked at sunset (Ammerman and Azam, 1981). Although c-AMP is stable in filter-sterihzed (0.2 /xm) surface seawater, it is rapidly assimilated by marine microorganisms, especially bacteria (Ammerman and Azam, 1981). Uptake of c-AMP is effected by a high-specificity, high-affinity (Km <10 pM) transport system (Ammerman and Azam, 1982). Evidence from well-designed dual labeled ([•^^P]c-AMP/[2,8--^H]c-AMP) experiments indicated that c-AMP was assimilated intact and that it remained in the cytoplasm rather than being incorporated into biomolecules. This is fully consistent with its role as a regulatory molecule. More recently, Dunlap et al. (1992) has reported growth of the marine luminous bacterium. Vibrio fischeri, on c-AMP as a sole source of C, energy, N, and P (also see Callahan et al, 1995). Growth was effected by a highspecific-activity, narrow-substrate-specificity c-AMP phosphodiesterase located in the periplasm of the cell. Ammerman and Azam (1982) suggested that uptake and release of c-AMP may control intracellular levels and, hence, metabolism for microbes in the marine environment. In their ecosystem model, starved or otherwise metabolically debilitated bacterial cells would take up dissolved c-AMP from seawater to supplement or replace de novo synthesis of c-AMP from cellular ATP; new catabolic enzymatic pathways would be produced and alternate ambient substrates metabolized (Ammerman and Azam, 1987). To our knowledge, this intriguing model has not yet been evaluated under field conditions. 4. Lipids Lipids are major constituents of all living cells. As a class of biomolecules, lipids have enormous structural diversity that, in part, reflects phylogenetic diversity. For example, whereas bacteria contain phospholipids containing ester-linked fatty acids, the membrane phospholipids in Archaea have ether-linked isoprenoid side chains (Tomabene and Langworthy, 1979). At least two different groups of lipids, both cell-membrane-associated, have been detected as constituents of the marine DOP pool: total phospholipid (PL) and lipopolysaccharide (LPS). Despite their billing, certain PL molecules contain as much N as they do P (Table 1), and neither N nor P are in very high relative abundance compared to C (molar C:P ratio is-40:1). Phospholipids are ubiquitous in Bacteria and Eukarya and present to a lesser extent in Archaea; they function primarily as structural components of the membrane. The PL content of cells can be quite large. According to Dobbs and Findlay (1993), PL-P in marine bacteria can account for approximately 15-20% of total cellular P—despite the relatively low percent P content—but the exact amount will vary with nutrient status and growth rate. The turnover time of phospholipids following cell death is rapid (2-10 days), at least in aerobic sedimentary
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habitats, but lipid turnover has not been investigated in the more dilute, pelagic ecosystem. Phospholipids are easily separated from other DOP compounds because of their polar nature; although soluble in organic solvents, they have an associated hydrophilic group at the P-bonded end. Phospholipids can be separated and detected by HPLC or by thin-layer chromatography coupled with flame ionization detection (TLC-FID, Chromarod-Iatroscan system; Parrish and Ackman, 1985). Several different types of phospholipids are present but, most often, "total PL" is reported. However, total PL can be further fractionated by altering hydrolysis conditions into diacyl phospholipids, plasmalogens (vinyl ether containing lipids) and phosphonolipids. The inherent stability of the C-P bond in organic phosphonate compounds has been employed, analytically, to separate phosphate ester-linked lipid compounds from phosphonolipids. Using a stepwise treatment with hydrochloric acid (6 M, 120°C, 2 h) to cleave phosphodiesters, followed by APase to cleave monophosphate esters, only phosphonolipids are expected to remain (Snyder and Law, 1970). Phosphonolipids are produced by eukaryotes, but degraded by prokaryotes. Certain membrane phosphonolipid derivatives of phosphorylethanolamine (e.g., 2-AEP; Table I), detected in relatively high concentrations in certain protozoans (Kennedy and Thompson, 1970), may increase the stability of the surface membranes by resistance to degradation. This would also predict a longer residence time in DOM and could lead to an accumulation relative to more labile DOP compounds. They may have an important physiological and ecological role, especially under low nutrient conditions. Liu et al (1998) used CFF to concentrate the colloidal fraction of DOM (>10 kDa) from phytoplankton cultures and surface seawater collected in Conception Bay, Newfoundland. As expected, colloidal lipids were always present but, on average, lipids were higher in the <10-kDa fraction. Relative to total lipids, the percentage of PL was nearly twice as high in the colloids than in the truly dissolved fraction (Liu et al, 1998). This indicates that colloidal P may be chemically distinct from truly dissolved compounds. Probably the most comprehensive study of PL in the marine environment was that conducted in Bedford Basin, Canada, by C. Parrish and colleagues (Parrish, 1986, 1987; Parrish and Wangersky, 1987). The total lipid fraction was extracted with cold dichloromethane, followed by Chromarod-Iatroscan system detection. Repeat analyses of the major classes of both particulate and dissolved lipids leading up to and following the vernal primary production maximum revealed complex dynamics especially for the dissolved lipid classes (Parrish, 1987). Their results for near surface waters (~5 m) collected during the 1982 spring bloom revealed a phytoplankton conmiunity with peak chl a values of >30 /xg L~^ on Julian day 86; nitrate decreased throughout the bloom period (Fig. 29). Dissolved PL were high
325
Dynamics ofDOP 40 ^ 3 o ^h
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80 Julian day Figure 29 Phospholipid (PL) dynamics during the initiation of the vernal bloom of phytoplankton in Bedford Basin, Canada, during 1982. Shown on the top graph is chlorophyll a (/ig L~^; # , dashed Une) and nitrate concentration (/xM; • , solid line) as a function of time shown in Julian day. Shown on the bottom graph are concentrations of dissolved PL-P (nM P; • , dashed Une) and particulate PL-P (nM P; • , solid line). Redrawn from Parrish (1987). PL (/xM P) was estimated from data on PL {\x% L~^) assuming that PL is 4% P, by weight.
(equivalent to ^50-60 nM-P) prior to the spring bloom, but decreased substantially during the bloom. In contrast, the particulate PL concentration was relatively low (<5 nM-P) before and during the initial stages of the bloom, increasing to ~20 nM-P at the height of the bloom (Fig. 29). Dissolved PL consistently accounted for 15-20% of the total dissolved lipid content of the water column. Similar results, notably the decreased concentrations of dissolved PL at the height of the bloom and a large increase in dissolved PL during the demise phase, were also observed at this location in 1984 (Parrish, 1987). It was suggested that phytoplankton
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in this coastal marine habitat can use PL-Pi as a P source for growth. A postbloom resupply of dissolved PL, hypothesized to be a result of intense grazing pressure, was also observed (Parrish, 1987). 5. Vitamins Vitamins are a class of otherwise unrelated organic compounds that are needed in trace amounts for the normal functioning of all organisms. Both thiamine pyro-P/, the biologically active form of vitamin Bi, and cobalamin (vitamin B12) have been detected in seawater where they contribute to the DOP pool. It is unlikely that vitamins comprise a significant percentage of the total DOP pool, but there is no question that they are important from an ecological perspective. Vitamin B12, in particular, is an obligate growth factor for many marine phytoplankton, so net growth of these organisms requires vitamin B12 uptake from seawater. Vitamin B12 is synthesized exclusively by microorganisms, predominantly bacteria, so there may be an obligate vitamin syntrophy within the marine microbial world (Provasoli and Pintner, 1953). Metabolic relationships between diatoms and heterotrophic bacteria may effectively exchange utilizable organic matter for vitamin B12, thereby maintaining a viable population of B12-requiring phytoplankton during periods of vitamin deficient growth (Haines and Guillard, 1974), as might occur in low nutrient, subtropical gyres. Vitamins Bi and B12 can be measured using rapid and reproducible bioassay procedures based on the incorporation of [^^^C] bicarbonate during growth of specific, vitamin-requiring phytoplankton (Carlucci and Silbemagel, 1966a,b). Application of these extremely sensitive (e.g., detection limits for vitamin B12 <0.05 ng of total vitamin per liter which equates to 4 x 10~^^ mol of P) bioassays have revealed low concentrations (sometimes undetectable) in the surface ocean, especially in open ocean oligotrophic ecosystems, and higher concentrations at depth (Carlucci and Silbemagel, 1966c; Fig. 30). The enigmatic increase at depth may be less a result of local production and more dependent on vitamin B12 import via sinking particles; however, no comprehensive studies have been conducted. An extensive survey of dissolved and particulate vitamins (including Bi and B12) in the Southern Ocean was conducted by Carlucci and Cuhel (1977). At most stations, both vitamins were undetectable in the surface waters (e.g., Fig. 30), and for vitamin Bi it was usually undetectable throughout the entire water column to depths of at least 3000 m. Particulate vitamin Bi and B12 peaked in nearsurface waters and decreased significantly with water depth (Carlucci and Cuhel, 1977). It was concluded that vitamins may limit eukaryotic phytoplankton growth in these high latitude polar habitats. Likewise, for seawater samples collected in the subarctic Pacific Ocean, Natarajan (1970) documented a stimulation of primary production, as measured by light-dependent [^"^C] bicarbonate uptake, by the addition of vitamin Bi, but not B12, especially for samples where the ambient
Dynamics ofDOP
327 POC Oiig/liter) 50
100
150 -T—I—I—r
Dissolved Vitamin B
(p|\/|.p)
Figure 30 Vertical distributions of dissolved vitamin B12 ( • ) and particulate organic carbon (POC; • ) at a station located in the South Indian Ocean (54°S, 115°E). Redrawn with permission from Carlucci and Cuhel (1977). Vitamin B12 P was calculated from the reported vitamin B12 concentrations (ng L~^), assuming a P content of 2.28%, by weight.
Bi concentrations were low. From this data set it was concluded that vitamin Bi may be limiting these natural phytoplankton assemblages. Menzel and Spaeth (1962) documented a seasonal cycle in vitamin B12 concentrations in the Sargasso Sea, with lowest concentrations during the springsummer period. They also showed that vitamin Bi2-requiring phytoplankton species (mostly diatoms) were absent during periods of undetectable vitamin B12 concentration, suggesting a key ecological selection pressure. Finally, it is interesting to note that the subdiscipline of "vitamin ecology" seems to have peaked in the early 1970s without any clear resolution of the role of vitamins in oceanic biogeochemistry. We submit that this is an area ripe for progress in the future. 6. Inorganic Poly-P/ and Pyro-P/ Inorganic poly-P/ are linear polymers of ?/, joined by phosphoanhydride bonds identical to high-energy P-bonds of ATP (Kulaev and Vagabov, 1983). The poly-P/ chain length can vary considerably from n = 2 (pyro-P/) to n>1000. This diversity of form has important implications both for their analysis in seawater and
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for their potential ecological role. While these important cell-derived compounds are obviously not part of the DOP pool per se, they do contribute to the TDP pool and, therefore, to the usual operational definition of "DOP" (i.e., [TDP]-[SRP]). Furthermore, both pyro-P/ and poly-P/ can be formed by enzymatic or photolytic hydrolysis of selected organic-P compounds, so as a courtesy we will include them here as probable constituents of the marine DOP pool. Isolation and partial purification of poly-P/ is difficult because of the variable molecular weight (chain length) and variable chemical properties. For example, laboratory studies have identified at least three poly-P/ fractions: (1) acid-soluble, (2) base-soluble, and (3) other (Clark et ai, 1988). Quantitative estimation is usually by difference measurement based on the relative photochemical stability of poly-P/. This difference approach is inherently unreUable, especially when total poly-P/ is <20% of TDP. Furthermore, it is impossible to separate inorganic poly-P/ from organic poly-P/ by these methods. Solorzano and Strickland (1968) detected poly-P/ in both coastal and open ocean ecosystems. They employed a sequential UV photooxidation followed by hydrochloric acid hydrolysis. The UV-stable, acid-labile P/ was taken as a measure of the sum of organic plus inorganic poly-P/. Concentrations in surface waters ranged from 200 nM P (25% of SNP) in a red tide off Newport Beach to undetectable levels (<50 nM P) in the East-Central Pacific Ocean. Isotope dilution has also been proposed as a method for pyro-P/ and poly-P/ estimation in samples containing other potentially interfering P compounds (Quimby et ai, 1954) but, to our knowledge, this method has not been applied to seawater samples. More recently, poly-P/ has been detected and quantified using a firefly luciferase-based assay for ATP following incubation with exogenous additions of the enzyme polyphosphate kinase and the substrate ADP (Ault-Riche et aly 1998). To our knowledge this sensitive and specific assay for inorganic poly-P/ has not yet been applied to seawater. Poly-P/ is ubiquitous in every cell in nature where it participates in multiple, key functions (Komberg et ai, 1999). Pyro-P/, like poly-P/ and the y- and P'F groups of ATP, is a "high-energy" P compound that is important in cellular bioenergetics; some researchers believe that pyro-P/ was the evolutionary precursor to ATP (e.g., Lipmann, 1965). Extracellular pyro-P/ can also serve as the sole source of energy for the growth of certain aquatic, anaerobic bacteria (Liu et al, 1982; Varma et ai, 1983). Furthermore, the poly-P/ polymer has a clear osmotic advantage over free P/ (i.e., it is osmotically inert), and may also act as a metalion chelator or high-capacity buffering system (Komberg et al, 1999). Perhaps one of the most intriguing potential roles for poly-P/ in marine microorganisms is its role in enabling competence for bacterial transformation by facilitating the cross-membrane transport of extracellular DNA (Reusch and Sadoff, 1988), and perhaps other small and large DOP compounds. Poly-P/, the "molecular fossil," appears to have recently come back to life (Komberg and Fraley, 2000).
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The most important function of poly-P/, however, appears to be regulation of gene expression, especially as it relates to nutritional stresses including P and N limitation. When microorganisms are placed into a P/-deficient medium they are induced to take up large amounts of P/ when it becomes available again. The Fi is converted into poly-P/ and stored until needed for macromolecular biosynthesis (Jensen and Sicko, 1974). In E, coli, poly-P/ transients, accounting for changes of >100-fold in periods of minutes to hours, have been observed during shifts from nutrient-sufficient to minimal growth media (Ault-Riche et al, 1998). Cells deficient in poly-P/ are noncompetitive during periods of nutritional stress, whether acute or chronic (Komberg et al, 1999). For growth in a fluctuating nutrient environment, rapid uptake and storage of P/ would be a key survival strategy. There is also an intracellular transient accumulation of poly-P/ at the onset of Vi depletion which appears to be under control of the Pho regulon discussed below. This process, termed "poly-P/ overplus" (Voelz et al, 1966), is fundamentally distinct from "luxury uptake" of Vi which also results in poly-P/ formation and storage but does not require P/ depletion. Of the two processes, the poly-P/ overplus phenomenon is probably most important in the marine environment and especially so in the open ocean. For example, if near surface ocean microbes are exposed to alternating periods of high and low P/, as they probably are (Karl, 1999), then this could lead to a poly-P/ overplus response and intracellular sequestration of P as poly-P/. Consequently, the current view that poly-P/ would not be expected to exist in low nutrient open ocean seawaters may be terribly incorrect; a focused research effort on this topic should be undertaken.
E BIOLOGICALLY AVAILABLE P Regardless of the rigor and precision with which P-containing compound pools are measured, the ecological significance of these analytical determinations will be incomplete until reliable estimates of the BAP pool are routinely available. In addition to P/, which is generally the preferred substrate for microorganisms, the P contained in a variety of polymeric inorganic compounds, in monomeric and polymeric organic compounds and in selected P containing minerals is available to some or all microorganisms; indeed some microorganisms may prefer esterlinked P sources to free orthophosphate (Tarapchak and Moll, 1990; Cotner and Wetzel, 1992). However, the bioavailability of most organic-P pools depends on ambient P/ pool concentrations and on the expression of specific enzymes that control transport, salvage, and substrate hydrolysis. Because many of these enzymes are induced by low P/, bioavailability may be a variable, time- and habitat condition-dependent parameter, rather than an easily predicted or measured metric. Assessment of the BAP may also depend on the time scale of consideration; for example, substrates that appear to be recalcitrant on short time scales
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(e.g., <1 day) may fuel longer-term (annual to decadal) microbial metabolism, especially as the ambient P/ pool becomes limiting. Theoretically, only a well-designed bioassay procedure can ever be expected to provide reliable data on bioavailable P; chemical assay systems, regardless of design, cannot replicate the metabolism of a living cell. One of the first P bioassay systems, described by Stewart et al. (1970), used P-starved cells of the N2-fixing cyanobsicienum Anabaena, and a response based on acetylene reduction (N2 fixation) to detect bioavailable P in freshwater ecosystems. Bjorkman and Karl (1994) have assessed the short-term bioavailability of seven organic and two inorganic P compounds to natural marine microbial conmiunities by measuring the sparing effect on the uptake of exogenous ^^P/ relative to unamended (negative control) and P/-supplemented (positive control) subsamples, following a procedure described by Berman (1988) for freshwater habitats. These short-term bioavailability surveys indicated that there were marked differences among the compounds tested, but confirmed a strong metabolic preference for P/. Of the compounds tested, nucleotides (ATP, UDP, GDP) were the most available organic-P compounds, followed by poly-P/ and Gly-3-P. Hexose-P compounds had "bioavailability factors" that were consistently <5% those of equimolar additions of P/ (Bjorkman and Karl, 1994). Karl and Bossard (1985) estimated BAP using a y-P labeling technique that they developed for ATP pool turnover. Because the intracellular ATP pool turns over rapidly, the specific radioactivity in the y-P position of the P-ATP pool will reach equilibrium not only with the extracellular P/ pool but with the potentially larger pool of extracellular P that is available to the microbial assemblage at that time, i.e., the BAP pool. Bossard and Karl (1986) successfully applied this ^^P labeling method to a variety of marine and freshwater habitats and reported that BAP was greater than or nearly equal to measured SRP. More recently, Bjorkman et al. (2000) used the y-F ATP labeling method to estimate the BAP pool at two stations in the oligotrophic North Pacific Ocean. In their study BAP was generally greater than P/ or SRP but, as in Bossard and Karl (1986), less than the TDP pool. The BAPiTDP molar ratio averaged 0.24, and generally exceeded the Pr.TDP and SRPrTDP ratios, sometimes by more than a factor of two. These results suggest that there exists some fraction of the ambient DOP that has a bioavailability factor equal to, or greater than, Pi in these open ocean habitats.
G. DOP: THE "MAJORITY'' VIEW Although no comprehensive characterization has been attempted using all possible DOP compound or compound class specific detection capabilities simultaneously, it is probable that less than 50% of the total DOP, and perhaps much less,
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can be identified. That leaves greater than half of the DOP uncharacterized by existing protocols. What is this "majority DOP?" Seawater DOM is marine in origin (Lee and Wakeham, 1988; Hedges et al, 2000); however, it appears to be diagenetically altered and chemically distinct from the source materials. This may account, in large part, for our inability to characterize it. Hedges et al. (2000) have recently reviewed the status of what they term the molecularly uncharacterized component of nonliving organic matter, or simply "MUC". It is generally believed that partial degradation leads to the production of refractory materials that selectively accumulate in seawater. The relatively old mean ^"^C age of the DOM pool (of which DOP is a subcomponent) even in surface ocean implies that much of it may be turned over on time scales of centuries to millennia. However, if we assume that the biorefractory deep water DOM (~40 /xM C, mean age of 6000 years) is also present in surface waters where it represents about 35-50% of the total pool, then the remainder of the surface pool must be zero age (i.e., modem) to reconcile the measured mean surface DOM age estimate of 1500 years. These age estimates may or may not also apply to the P-containing DOM pool because these fractions have never been isolated for direct age determination. The fact is that we simply do not know how the age of the DOM pool scales on mass, class, or other characteristics. Information regarding the age of specific components of the DOP pool would, in our view, be invaluable from an ecological perspective. There are two general processes potentially leading to the formation of MUC (Hedges et al, 2000): (1) heteropolycondensation reactions whereby small reactive organic intermediates combine to from larger and more complex organic compounds (also known as humification) and (2) differential/partial biodegradation of high-molecular-weight organic matter. The starting materials for the latter process would likely be complex compounds like bacterial peptidoglycan-rich cell walls, DNA-histones, or viral particles. While there appears to be an ongoing paradigm shift from process (1) to process (2), few data currently exist for DOP compounds. Humification, the process whereby organic materials that are relatively resistant to microbial and free-enzyme mineralization are polymerized, condensed, and otherwise reworked into a diverse suite of compounds called "humic substances," is widespread in nature (Rashid, 1985). Based on their relative solubilities in acidic or basic solutions, humic substances are further subdivided into humic acids (HA, insoluble in acid, soluble in base), fulvic acids (FA, acid and base soluble), and humins (insoluble in both acid and base). Marine humic substances also have variable molecular weights, ranging from LMW to colloid sized particles, and are isotopically and chemically unique from soil humus. They can adsorb, complex, and chelate most trace metals, and probably adsorb Vi as well. This would be in addition to the actual P content of the compounds themselves.
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Dispersed HA and FA compounds may account for some measurable fraction of the marine DOP pool, but the amount remains uncertain. According to Nissenbaum (1979), sedimentary marine HA and FA fractions contain 0.1-0.2 and 0.4-0.8% P by weight, respectively, with corresponding bulk C:P ratios ranging from 300 to 400 in HA to <100 in FA (Table I). The P-enriched FA fraction is thought to be more recent. Nissenbaum (1979) suggests the following diagentic scheme: plankton -^ DOM ^- FA ^^ HA -^ kerogen. The fact that FA compounds are enriched in P (relative to C) compared to the average C and P contents of plankton (106C:1P) seems enigmatic. This P-enrichment of FA is especially interesting considering the fact that the mean C:P molar ratio of DOM in surface and deep sea water indicates a P depletion (CiPsurface ^^200-400, CiPdeep >800) relative to living biomass. Even many labile DOP compounds have C:P ratios larger than the quoted value of <100 for marine FA (Nissenbaum, 1979). From these analyses we must conclude that the FA fraction of seawater is a probable, but ill-constrained, P trap. Mopper and Schultz (1993) have identified a "humic-type" signature as one of two main fluorescence components of the DOM pool at Sta. ALOHA. While quantitative information on HA/FA abundance is lacking, it is clear that humic substances are present throughout the water column in the global ocean. More careful field work certainly needs to be done to substantiate this claim. Brophy and Carlson (1989) have documented the microbiological formation of biorefractory HMW DOM from bioreactive LMW precursors and suggested that this might be a pathway for local accumulations of organic matter. In similar experiments, labile protein added to seawater and allowed to "age" for 40 days was degraded fourfold more slowly than the non-aged protein (Keil and Kirchman, 1994). The chemical modification was determined to result from abiotic, organicorganic interaction which the authors conclude may be a necessary first step in the formation of biorefractory compounds. It is probable that a fraction of the marine DOP pool is also derived from cell wall-associated compound classes. McCarthy et al. (1997) suggested that degradation-resistant biomolecules, rather than abiotically produced heterocyclic geopolymers, dominate the marine DOM pool. This refractory DOM pool appears to contain a large percentage of bacterial peptidoglycan (McCarthy et a/., 1998). Lipopolysaccharide (LPS) is a component of the cell wall of Gram-negative bacteria including some cyanobacteria (Mayer et al, 1985; Wilkinson, 1996). It is localized in the center portion of the outer membrane, where it contributes to cell integrity. Although LPS is rapidly degraded following cell death and lysis, dissolved LPS (D-LPS) has been detected in aquatic environments and may represent >90% of the total LPS in certain habitats (Karl and Dobbs, 1998). Spontaneous release of LPS has been documented for many bacteria and appears to occur during normal growth (Cadieux et al, 1983). D-LPS may also accumulate as a consequence of protozoan grazing activities or viral lysis.
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Phosphorylation of LPS is a probable mechanism of metabolic regulation in the sea (Ray et al, 1994). A striking feature is the presence of a high level of P (2-6%, by weight) which exists as either ethanolamine-P, ethanolamine-pyro-P/, protein-P, or P/ (Miihlradt et al, 1977). A majority of marine bacteria are Gramnegative and thus may contain LPS-P. Currently it is not known how much P is contained in the D-LPS fraction in seawater (the assay for D-LPS does not measure P content directly), and the P content of individual forms of LPS varies considerably. As discussed above, LPS phosphorylation may serve as a regulatory mechanism in bacteria, so the LPS-P content of seawater could be variable in both space and time. We hypothesize that both LPS and the Gram-positive bacterial cell wall analog compounds teichoic and techuronic acids (which contain Gly-3-P and ribotol-P polymers) may be present as components of the DOP pool because bacterial cell walls are such a significant percentage of total bacterial cell biomass. This prediction, however, awaits direct experimental evaluation. The coordination and regulation of cellular metabolism are key ecological processes. Bacteria, for example, impose regulatory mechanisms on most catabolic and biosynthetic processes to ensure that needs are met, but not exceeded (Saier et al, 1995). Large portions of the bacterial and archaeal genomes appear to be used for regulation, so it is conceivable that regulatory molecules are constantly produced and used by marine microorganisms. These compounds could, in theory, be selectively retained in the DOM pool following exudation or cell death. The phosphorylation and dephosphorylation of proteins is an important metabolic process in living organisms that may be a form of signal transduction and gene regulation (Stock et al, 1989). Both exogenous and endogenous cues can elicit specific adaptive responses that optimize metabolism and maximize survival. The low-temperature dependence of the protein phosphorylation process in certain bacteria (Ray et al, 1994) provides a potential mechanism for a geographical variability in DOP production. The phosphoenolpyruvate: sugar phosphotransferase system (PTS) in bacteria is one of the best characterized examples of phosphoprotein regulation (Saier, 1989); numerous other examples also exist (Bourret et al, 1991). The PTS is used for sugar transport, phosphorylation, and chemoreception; it has been detected in marine bacteria (Hodson and Azam, 1979). Synthesis of polysaccharides (including LPS) from monosaccharides generally relies on a biosynthetic pathway that involves a nucleoside-sugar intermediate (e.g., UDP-glucose, CDP-fructose). To our knowledge these phosphorylated intermediates have not been reported in seawater, though they undoubtedly exist largely for the same reasons as dissolved nucleotides. Also, a family of nucleotide derivatives, including guanosine-3'-diphosphate-5'-diphosphate (ppGpp) has been implicated in the growth rate-dependent regulation of ribosomal RNA and protein synthesis since its discovery more than three decades ago (Cashel and Gallant, 1969). These regulatory processes have unknown but probably key ecological roles and may, therefore, be present in variable intracellular and extracellular
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concentrations in seawater. To our knowledge, they have not yet been detected in seawater. A novel group of phosphoinositol derivatives has recently been reported in very high concentrations (50-350 mM) in the cytoplasm of certain hyperthermophilic bacteria and Archaea (Scholz et al, 1992; Martins et al, 1997; Ramakrishnan et al, 1997). Initially it was thought that they served as thermoprotectors, but it now appears that they have other, yet undiscovered, functions—^perhaps osmolytic (Chen and Roberts, 1998). Inositols are stable to hot hydrochloric acid hydrolysis (6 M, 110°C, 48 h), so it is possible that they have not been quantitatively measured by use of wet chemical oxidation techniques. Inositol isomers have also been detected in marine sediments (White and Miller, 1976; Suzumura and Kamatani, 1995), but not yet in the water column. Another phosphorylated compound, 2,3-diphosphoglycerate, has been shown to be a novel phosphagen in selected Archaea (Kanodia and Roberts, 1983; Matussek et al, 1998). The recent discovery of high concentrations of planktonic Archaea in seawater (DeLong, 1992; Fuhrman et al, 1992; DeLong et al, 1994; Kamer et al, 2001), demands that we also consider them as a potential source for marine DOR Finally, several organic-? compounds have commercial applications; for example, triphenyl phosphate is a plasticizer and tricresyl phosphate is an additive in gasoline. In addition, organophosphorus pesticides (parathion, malathion, ethion, thimet) are in use worldwide. While most of these are eventually degraded, some compounds persist longer than others, especially when present in low concentrations. Atmospheric, riverine, or outfall introduction into the sea may arrest the degradation processes via substrate dilution. This could lead to the selective accumulation of biochemically refractory or otherwise "unwanted" DOP compounds, in spite of a low relative production or delivery rates. In sunmiary, a complete molecular characterization of marine DOP has not yet been possible. This situation may be as much a consequence of lack of effort as it is due to lack of methods. When one considers the combined probable contribution from dissolved nucleic acids, dissolved phospholipids, dissolved proteins, lowmolecular-weight intermediates (including nucleotides, regulatory molecules, and osmolytes), and HA and FA fractions, budget reconciliation may be possible in the near future.
IX. DOP PRODUCTION, UTILIZATION, AND REMINERALIZATION The phosphate regulon (Pho) of E, coli includes at least 31 genes arranged in eight separate operons (Wanner, 1993). These genes are coregulated by environmental P concentrations and, working together, facilitate P/ assimilation. During P/ limitation, selected Pho enzymes are turned on, including: (1) a high-affinity,
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high-specificity periplasmic permease (Pst) to enhance Fi assimilation capacity, (2) a periplasmic alkaline phosphatase to facilitate monophosphate ester-linked DOP hydrolysis, and (3) specific enzymes to facilitate the uptake and hydrolysis of phosphonates. Expression of the ?/ regulon has also been reported for marine bacteria (McCarter and Silverman, 1987), so the much more extensive laboratory studies of E. coli may be an adequate model at least for hypothesis testing in P/-stressed marine habitats. DOP production in the sea typically begins with biological P/ uptake and incorporation into one of the many intracellular P-containing compounds in the cell. For this reason, the environmental controls on rates of P/ uptake and pathways of Pf assimilation into organic-P compounds are critical to our understanding of DOP dynamics. Because P/ concentrations in the surface ocean rarely exceed 3 /xM, one might anticipate the universal presence of the high-specificity, high-sensitivity P/ transport system for many microorganisms in the sea. Most of the P/ that is assimilated by microorganisms is locally regenerated back to Vi to sustain in situ production processes. In the open ocean, typically less than 10% of the total P that is assimilated is exported from the system. As for Pi uptake, accurate Pi regeneration or DOP production estimation requires information on the ambient pool of BAP in the habitat under investigation. When combined with independent methods of DOP pool characterization, the radiotracer experiments described below can also be used to quantify thefluxesof specific DOP compounds or compound classes (e.g., nucleotides). A "pulse-chase" experimental design (i.e., preincubation with ^^P/ or ^^P/ radiotracer followed by the addition a 10-fold excess of ^^Vi) could be employed to follow both net DOP production, during the labeling phase, and DO^^P turnover in the postchase treatments. Dual labeled ^^P//^^P/ pulsed experiments can also be conducted to trace DOP pool dynamics and to estimate DOP pool residence times by models that take advantage of the differential half lives of these independent radiotracers. Finally, the addition of exogenous, ^^P (or ^^P)-radiolabeled DOP compounds (e.g., Glu-6-P, ATP, Gly-3-P) can provide information on the turnover time of individual pools and potentially (if combined with direct measurements of ambient pool concentrations) on mass fluxes (production and utilization rates) through selected organic-P pools. Our present inability to measure any but a very few DOP compounds (a notable exception is ATP, as discussed above), however, limits the field application of this experimental design.
A. DOP PRODUCTION AND REMINERALIZATION The use of ^^P (or ^^P) as a tracer for P/ uptake, DOP production, and Vi regeneration has been extensive in oceanography to measure the growth and metabolic activities of algal and bacterial assemblages (Rigler, 1956; Watt and Hayes, 1963;
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Sorokin and Vyshkvartsev, 1974; Taft et al, 1975; Harrison et al, 1911 \ Perry and Eppley, 1981; Sorokin, 1985; Atkinson, 1987). Certain P radiotracer field experiments have employed either size fractionation treatments (Harrison et al, 1977), metabolic inhibitors (Krempin et al, 1981) or multiple labeled substrates (Cuhel et al, 1983) to separate algal and heterotrophic bacterial activities. Typically, the radiotracer is added as carrier-free ^^P/ (or ^^P/) in order to minimize perturbations that may be caused by P/ pool enrichment. The use of exogenous radiotracers to measure DOP production during timed incubation experiments generally requires a protocol to separate unused or regenerated radiolabeled P/ from the recently produced radiolabeled DOP compounds. This is an analytical challenge in many field studies because most of the radioisotope is generally present as Vi and because of the potential diversity of the individual DOP compounds that are produced. Smith et al (1985) employed the previously described isobutanol extraction technique to separate the ^^P/ (SRP)-molybdenum blue complex from DO^^P in solution. To the extent that SRP exceeds P/, or if any of the DO^^P compounds are soluble in isobutanol, the solvent extraction method will underestimate the net DO^^P production rate. Orrett and Karl (1987) compared the isobutanol technique to the much simpler "Bochner and Ames" (1982) technique; the latter involved a procaine-tungstate-tetraethylammonium-dependent selective precipitation of ^^P/ leaving DO^^P in solution. The mean DO^^P production rate estimates from an open ocean field application of these two methods showed no significant differences (Orrett and Karl, 1987). More recently, Bjorkman et al (2000) have employed the MAGIC technique, described earlier, as an effective means to separate ^^P/ from DO^^P in sample filtrates. Once experimental data are available on ^^P/^^P-labeled DOP accumulation rates (expressed as Bq per volume per time) conversion to the more ecologically meaningful absolute P fluxes requires the assumption/application of a specific P assimilation model to convert P radioactivity to P mass. The key to providing a reliable mass flux is, again, the accurate estimation of the BAP pool. Orrett and Karl (1987) reviewed four independent models that have been used for seawater: (1) SRP (or Vi) model, (2) TDP model, (3) RNA model, and (4) ATP model. Each model differs in the assumptions used for P uptake and assimilation. For example, the SRP model assumes that the exogenous precursor ^^P//^^Pz mixes completely with the SRP pool prior to uptake and incorporation. Consequently the radiolabeled DOP that is produced during the incubation would have a specific radioactivity (radioactive per unit mass) equivalent of that calculated for the SRP pool. However, in most open ocean environments where DOP >P/, it may be more reasonable to acknowledge the possible role of DOP in microbial metabolism. The TDP model, therefore, assumes that both P/ and DOP are bioavailable during these relatively short (<1 day) incubation experiments. In our opinion, this assumption may also be incorrect and would lead to an underestimation of the true precursor specific radioactivity. The remaining two metabolic models rely on direct measurements of
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the specific radioactivity in two independent subcellular constituent pools that are expected to reflect the isotope dilution of the added precursor by all bioavailable extracellular and intracellular P pools (Orrett and Karl, 1987). In the RNA model, the specific radioactivity of nascent RNA is measured directly (using doublelabeled [^H]-adenine and ^^P/ incubations; Karl, 1981) and this value is taken to represent an average for the entire DOP pool. The final method, the ATP model, is analogous to the RNA model but assumes that the terminal phosphate group of ATP (the y-P pool rather than the a-F as in the RNA model) accurately reflects isotope dilution. Two key advantages of the ATP model are the rapid turnover of cellular ATP which leads to rapid isotopic equilibration, and the compelling evidence that the y-P position of ATP is very likely the precursor for the biosynthesis of most P-containing organic compounds (see Section VIII.F). Hudson and Taylor (1996) devised and applied a novel method for the direct measurement of DOP production in planktonic communities. Their procedure requires a preincubation with high specific activity ^^P/ for 17-76 h to label the metabolically active organisms. A subsequent pulse of nonradioactive ^^P/ competitively inhibited further ^^Fi uptake and provided a time zero starting point for the timed appearance of [^^P]DOP from the combined processes of excretion, exudation, grazing and cell lysis. The addition of the ^^P/ pulse is assumed to have no effect on DOP loss by the community of microorganisms. From information on the mean specific radioactivity of the particulate P pool at the beginning of the second incubation, the DOP production (mol P L~^ day~^) can be estimated. To our knowledge, this method has not yet been applied to marine ecosystems. Watt and Hayes (1963) and Johannes (1964) were among the first to demonstrate contemporaneous P/ uptake and DOP production in near surface planktonic assemblages using ^^P/ radiotracer incubations. Johannes (1964) also documented a coupled production of DOP by diatoms and DOP uptake by bacteria. It was also shown that mesozooplankton produced substantial amounts of DOP. According to Satomi and Pomeroy (1965) zooplankton, in general, have low oxygen consumed to P/-released ratios, which suggests that they do not completely oxidize their food; this is consistent with the reported high rates of DOP release. Smith et al. (1985) conducted ^^Fi uptake experiments in coastal and offshore Hawaiian waters. They detected net [^^P]DOP production in all of their incubations, and used both three-component (Fi -> PP ^- DOP) and four-component (Fi -^ PP1/PP2 -^ DOP) steady-state models to evaluate the observed P pools and fluxes. Their results were consistent with a rapid and coupled production and utilization of DOP in these marine habitats. Dolan et al (1995) examined coupled Fi uptake and passage through a simplified planktonic food web as defined by specific particulate matter size fractions in Villefranche Bay, France. Fi uptake was dominated (>50%) by the smallest size fraction (0.2-1 /xm), presumably auto- and heterotrophic bacteria. Fi turnover times were rapid, less than a few hours for most of the 3-month observation period.
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Release of incorporated ^^P from various particulate size-fractions was investigated by incubating with ^^P/ for a 3-h period, followed by the addition of an excess of unlabeled AMP (100 /xM). The addition of AMP, they reasoned, would partially inhibit the assimilation of recently produced [^^P]DOP compound and provide a more accurate estimate of gross DOP fluxes. The measured rates of [^^P]DOP release in these experiments were low, generally < 1 % of the corresponding particulate ^^P activity per hour (Dolan et al, 1995). However, when the concentration of oligotrich ciliates (predators of microorganisms in the 1- to 6-/xm size class) was artificially increased, there was a significant transfer of ^^P from particulate to dissolved pools. These field results confirmed the role of protozoan grazing in nutrient cycling processes (Andersen etal, 1986), including the P/ -^ PP ^- DOP -^ P/ pathway. Thingstad et al (1993) conducted a comprehensive study of microbial transformations of P in P-limited Sandsfjord, western Norway, including the coupling of P/ uptake, DOP production, specific DOP compound hydrolysis, and enzymatic hydrolysis. They focused on the production and turnover of nucleotides, and used ATP as a "model" compound. DOP/P/ concentration ratios in this habitat varied considerably but were generally between 10 and 100:1; P/ (reported as SRP) was <5 nM at selected stations. An averaged flow model was devised to best accommodate the measurements and their underlying assumptions. The most striking result was the presence of a large DOP pool (^200-250 nM) that was dominated (>99% of total DOP pool) by polymeric compounds (presumably RNA and DNA) that turned over very slowly compared to the relatively small but rapidly assimilated nucleotide pool. In this regard, their results are consistent with the nuclease/phosphodiesterase "bottleneck" hypothesis discussed in a previous section of this review (Fig. 5). Orrett and Karl (1987) reported 0-100 m depth-integrated DOP production rates ranging from 0.3-0.8 mmol P m"'^ day"^ (TDP specific activity model) and 0.5-1.2 mmol P m"^ day~^ (RNA-specific activity model) for water samples collected in the NPSG. They reasoned that these DOP production rates could be further extrapolated to organic carbon, if the mean C:P molar ratio was either known or correctly assumed. An upper bound on C:P was taken as the whole cell C:P (106C: IP; Redfield et al, 1963), although it is unlikely that DOP compounds are, on average, this carbon-rich (see Table I). They assigned a value of 3C:1P as the theoretical lower bound on this value, a value identical to the nucleotide triphosphate pool. It is equally unlikely that the DOP pool would be that C poor, relative to P. A ratio of 9.5C: IP, the approximate value for RNA, was taken as the most reasonable estimate; the true C:P ratio for DOP is likely to be closer to the lower bound than to the upper bound. The extrapolated rate of DOC production, 24 mmol C m"-^ day~^ was about 50% of net primary production for this region (Karl et al, 1996,1998). Because this estimate is based on accumulation (net production) of DOP during the incubation period and, therefore, does not include
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contemporaneous [^^P]DOP production and [^^P]DOP utilization, gross DOP fluxes will be even larger. These results suggest an important role for DOP in microbial loop processes in these low-nutrient, open-ocean habitats. At steadystate, DOP production and DOP remineralization rates would be in balance. Consequently, given the DOP pool size and estimates of DOP turnover rates, these organic pools are likely to serve as an important source of P, as well as C and N, for microorganisms. If the compound C:P ratio is less than the whole cell C:P ratio, or if C is derived from additional or alternative sources, then P/ is likely to be released into the medium. These coupled processes most likely sustain the marine P cycle in the euphotic zone of the sea. Finally, Bjorkman et al (2000) measured coupled rates of P/ uptake and DOP production at several stations in the NPSG using ^^P/ as a tracer. Vi uptake rates varied from 3 to 8.2 nM Vi day"^; P/ pool turnover time was 2-40 days. Net DOP production (i.e., accumulation) was 10-40% of the net P/ uptake. The estimated turnover time for the entire DOP pool, assuming compositional singularity with nascent DOP, was 60-300 days. In all likelihood, the recently produced materials are assimilated much more rapidly than this simple calculation would suggest. Vi regeneration from selected, exogenously added DOP compounds was rapid and efficient; highest rates of P/ release were observed for nucleotides (Bjorkman ^r a/., 2000). Although coupled P/ uptake and DOP production is well documented in a variety of marine ecosystems, the actual mechanisms of DOP production remain elusive. Admiraal and Werner (1983) investigated the production of DOP by two coastal marine diatom species in laboratory culture. In addition to total DOP production rates, they concentrated a fraction of the DOP pool, using Sephadex G-10 chromatography, and documented partial reabsorption of the isolated DOP compounds by the same two species during P/-limited growth. The inadvertent diffusive loss of LMW compounds or the active excretion of both LMW and HMW compounds are both feasible; the list of specific compounds that are liberated by growing algae is very large (Fogg, 1966; Hellebust, 1974). Alternatively, DOP release could result from cell autolysis, predator grazing or viral lysis. Each separate pathway might be expected to produce a different spectrum of compounds. Most of the research conducted to date has focused on extracellular production of DOC, not DOP, but suffice it to say that DOP production by healthy microorganisms is probably a universal phenomenon.
B. DIRECT UTILIZATION OF DOP DOP compounds in seawater consist of both labile and refractory compounds. The labile DOP pool includes both transportable and nontransportable organic compounds, either of which can serve as P sources for microbial growth. The
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outer membrane of Gram-negative bacteria allows the transport of molecules up to about 600 Da (Weiss et ai, 1991). Therefore, many DOP compounds can, and probably are, taken up directly without the need for prior hydrolytic alteration. For example, Gly-3-P and AMP can be assimilated intact by certain bacteria (Wanner, 1993; Ruby et ai, 1985), whereas larger DOP compounds must be enzymatically hydrolyzed, either at the cell surface (or in the periplasmic space for bacteria) or in the surrounding medium prior to assimilation. The Pi released is then available for assimilation and biosynthesis. Therefore, the ability of an organism to grow on one or multiple DOP substrates as the sole source of cellular P can be traced to one of two independent properties: the presence of cell membrane or periplasmic bound enzymes that catalyze the DOP compound dephosphorylation and thereby enhance P/ availability or the presence of a DOP compound- or compound-class-specific uptake system. Both pathways are present in marine microorganisms; growth of both prokaryotic and eukaryotic microorganisms on a variety of different DOP compounds is well documented (Kuenzler, 1965; Cembella etai, 1984a,b; Antia etaL, 1991; van Boekel, 1991). Among other functions, the Pho regulon controls the transport of selected, intact DOP compounds into bacterial cells. Several proteins of the outer membrane of many bacteria (termed "porins") are involved in the formation of aqueous pores through which small hydrophilic molecules (<600 Da, including Fi and selected DOP molecules) can pass through the membrane. Fi concentration regulates the synthesis of these proteins; Fi starvation enhances their biosynthesis (Tommassen and Lugtenberg, 1981; Saier, 2000). Tanoue (1995) has reported that porins, specifically porin-P (a protein that is synthesized during P/-limitation) may be a major component of the total dissolved protein pool in seawater. Using sodium dodecylsulfate-polyacrylamide gel electrophoresis, Suzuki et ai (1997) detected several distinct bands with molecular weights 14.3-66 kDa; one frequently observed band (MW = 48 kDa) was identified as bacterial porin P. Consequentiy, it appears that porins may be an ecologically significant potential pathway of P/ and DOP assimilation in low-nutrient, open-ocean habitats. Laboratory studies conducted with E. coli have documented independent and fairly specific transport systems for Gly-3-P and Glu-6-P that are derepressed during Fi limitation. Although both systems also cotransport Fi, they are lowaffinity in this regard, especially when compared to the Pst system that is also active during periods of Fi stress. These specific DOP transport systems appear to be one example of an anion-exchange mechanism in bacteria (Maloney et al, 1990). The uptake of the DOP compound is linked with the export of Fi and may, therefore, integrate into a vital chemiosmotic circuit or H"^ pump; in effect, these DOP transport systems are P/-linked antiporters. Although neither of these specific DOP uptake systems has yet been detected in marine bacteria, it is very likely that they do exist and may have an important ecophysiological role. The two most potentially significant functions of these
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anion-exchange mechanisms are: (1) to catalyze the heterologous exchange of P/ and a selected sugar phosphate (e.g., P/:Gly-3-P and P/:Glu-6-P) and (2) to exchange intracellular AsO/~ for either P/ or for a sugar phosphate. The first function, the asymmetric exchange of Fi for a sugar phosphate, may be part of the cell's mechanism to balance the supply of C and P. Because many DOP compounds have excess P relative to C, compared to whole cell C:P stoichiometry (e.g., the molar C:P ratios for Gly-3-P and Glu-6-P are 3 and 6, respectively, compared to a Redfield stoichiometry of 106; also see Table I) this would provide an efficient system to achieve a physiological C-to-P balance. This control mechanism might be especially important during periods of low growth rate when C demands for maintenance energy generation are high, but biosynthetic demands for P are low, as in the mesopelagic or abyssopelagic zones. The second function, the exchange of AsO/~ for Fi or the exchange of As04^~ for a sugar phosphate may be one of several stratc^gies for As detoxification, especially in open ocean environments where the AsfPi concentration ratio exceeds 10 (Karl and Tien, 1997). Another potential advantage of the direct uptake of DOP, especially nucleotide monophosphates, is the use of these molecules as biosynthetic precursors. This conservation of preexisting phosphate bonds has significant implications for cellular energetics and for the growth efficiency of microorganisms (Rittenberg and Hespell, 1975). The availability of water insoluble or hydrophobic DOP compounds, like membrane phospholipids, may require additional, specific enzymes for assimilation. Lemke et al (1995) evaluated the role of cell surface hydrophobicity, a measurable property of all ifnicrobial cells, on the relative utilization rates of hydrophobic and hydrophilic P compounds. Hydrophilic bacteria grew rapidly on Fi and Gly-3-P, but could not assimilate the hydrophobic substrate, phosphatidic acid (PA) or membrane phospholipids (Lemke et al, 1995). Conversely, bacteria with hydrophobic cell surfaces efficiently utilized PA and lipid P. These cell-specific metabolic capabilities could lead to DOP resource partitioning among otherwise competing microheterotrophs, or to species selection and succession following production or exhaustion of one or more key DOP substrates. An interesting and potentially important study of the effect of fluid motion on the utilization of selected low-molecular-weight DOM (not expHcitly DOP compounds) b> heterotrophic bacteria revealed that uptake rate was enhanced by advective flow, but only at low subsaturating DOM concentrations (Logan and Kirchman, 1991). One prediction of their results is that particle-bound bacteria, especially those sinking through the water column, might be more important for deep-water DOP remineralization than the solitary microorganisms suspended in the water column. Finally, muc;h has been written on the competition between bacteria (chemoheterotrophs) and algae (mostly eukaryotic phototrophs) for Fi and DOP in aquatic environments since the elegant laboratory studies conducted by Rhee (1972).
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These investigations have examined uptake affinities, cell quotas, storage capabilities and other ecophysiological parameters under both P-sufficient and P-limited growth conditions. Despite some contradictory field results, most investigations revealed a tight metabolic coupling between the producer and consumer species and expUcit nutrient resource-based competition, especially at limiting concentrations of ?/. Less well documented is the abiUty to switch from P/-based to DOP-based metabolism or the sequential versus simultaneous utilization of two or more P-containing substrates. In open-ocean environments, the bacterial-algal dichotomy disappears because the "algae" are bacteria (e.g., the picophytoplankton assemblage). Most low nutrient environments are dominated by prokaryotes, e.g., Prochlorococcus or Synechococcus, and may even be supported by mixotrophic growth (e.g., simultaneous utilization of photoautotrophic and chemoheterotrophic metabolic pathways). In any event, all prokaryotes and eukaryotes function as P-traps and ultimately must compete with each other.
C. ENZYMES AS P-CYCLE FACILITATORS
Because P/ starvation causes a significant increase in APase activity it has been suggested that the detection of APase in field collected samples may be an ecophysiological indicator of P/ stress. However, the literature on this topic is confusing and, at times, contradictory. For example, it has also been shown that starvation for nucleic acid bases will induce APase synthesis even under conditions of excess Fi (Wilkins, 1972). Consequently, there may be alternative ecological interpretations for the presence of elevated APase in natural assemblages of microorganisms. APase activity can be measured by colorimetry (using /7ara-nitrophenyl phosphate as the substrate),fluorometry(using either 6>-methyl-fluorescein phosphate or 4-methylumbelliferyl phosphate as the substrate), orfireflybioluminescence (using ATP as the substrate). Substrate selection determines to a large extent measurement sensitivity and assay specificity. For example, para-nitrophenyl phosphate and ATP are both hydrolyzed by APase and the related enzyme nucleotidase, so these assays are not necessarily specific for APase unless combined with other sample treatments (e.g., ?i additions; Karl and Craven, 1980). Furthermore, the use of artificial substrates has the potential to overestimate the in situ rates of enzymatic activity (Cembella et ai, 1984a; Admiraal and Veldhuis, 1987). Only ATP is likely to be a native substrate in natural samples and only the use of ATP provides a detection system that can provide in situ rate estimates. A new insoluble fluorogenic substrate for APase, termed enzyme-labeled fluorescence (ELF), has been used to detect the presence of the enzyme in single microbial cells (Gonzalez-Gil et al, 1998; Dyhrman and Palenik, 1999). Cell detection is by either epifluorescence microscopy or laser-based flow cytometry.
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Laboratory studies of APase in pure cultures of marine bacteria (Hassan and Pratt, 1977) report that APase was completely repressed, partially repressed, or not repressed at all by the presence of 50 mM Fi in the growth medium. This variable response suggested the presence of different APase isozymes, some of which appear to be constitutive. In any case, the relatively high P/ concentrations used in this and other laboratory studies of the Fi repression of APase activity is 10"^ to 10^ times higher than Fi concentrations in most surface ocean waters (open ocean 1-100 nM Fi, coastal ocean <1 /xM), so even "relatively high" seawater concentrations must be considered P/-depleted for the purposes of the microbial APase derepression response. An ecological prediction is that APase should be ubiquitous in seawater. Morita and Howe (1957) may have been the first to measure APase activity in cultures of marine bacteria. Their interests centered on the effects of ambient hydrostatic pressure on the potential efficiency of Fi regeneration in the deep sea. The first published report of APase activity in seawater was for coastal waters near Taiwan (Wai et al, 1960). They detected and quantified APase activity by several procedures including the measurement of Ca^"^ increase following a timed incubation with fish bone powder (calcium phosphate) and by an increase in Fi following a timed incubation with Gly-3-P. APase activity was ubiquitous, but varied with sample location (Wai et al, 1960). Because all living organisms in the sea, from bacteria to marine mammals, can produce APase and other phosphatases it is difficult to determine the exact source of the enzyme activity in most environmental samples. From an ecological perspective it is critical to know which organisms are expressing APase activity under a particular set of environmental conditions. APase activity in the dissolved fraction is also common (Reichardt et al, 1967). Most investigators measure APase activity in either whole water (dissolved plus particulate activity) orfiltered(or filter size-fractionated) subsamples. For example, in Toulon Bay, APase in the >90-/xm fraction accounted for more than 80% of the total activity, whereas in other coastal regions of the Mediterranean APase was restricted to the picoplankton (0.25-5 /xm) fraction (Gambin et al, 1999). Boon (1994) has devised a very clever technique to distinguish between prokaryotic and eukaryotic APase activities. His method relies on a differential inhibition by various physical (e.g., thermal deactivation) and chemical (e.g., Zn^"^ and Cu^+ ion inhibition) treatments. To our knowledge, this technique has not yet been applied to the marine environment. Since the first field report of APase activity in seawater by Wai et al (1960), numerous studies have been conducted using a variety of increasingly more sensitive and specific assay systems. Because APase synthesis is derepressed following Fi limitation and is not induced by the presence of suitable substrates, in vivo enzyme activity under saturated substrate concentrations is not equivalent to P flux. Theoretically, in situ rates of DOP hydrolysis can be estimated only if the concentration of exogenous substrate is comparable to in situ specific DOP compound
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concentrations. Consequently, most APase and other enzyme activity measurements in seawater must be considered "potential" activities. Perry (1972) was the first to document APase activity in an oligotrophic, open ocean ecosystem. The APase activity in the NPSG was greatest for samples collected in the upper 60 m of the water column and decreased with increasing water depth and ambient Pi concentration. Microbial assemblages lacking detectable APase activity at time of sample collection produced APase within 1-2 days when incubated in bottles; the addition of 5 /JM Pi to water samples immediately repressed APase activity (Perry, 1972). Li etal. (1998) measured significant dissolved (<0.2 /xm) and particulate APase activities in the Gulf of Aqaba, northern Red Sea. Dissolved APase activities ranged from 40-70% of the total APase activity; most of the particulate APase activity was attributed to the picoplankton fraction. Cell-free activities were stable in the dark at 4°C for extended periods (up to 40 days) and could lead to variable dissolvediparticulate ratios, for example, as a consequence of transient periods of P/-limitation. In contrast to this open-ocean study, Taga and Kobori (1978) reported a positive, not negative, relationship between APase activity and P/ concentrations for samples collected in Tokyo Bay. As mentioned previously, even the highest P/ concentrations found in marine ecosystems (i.e., 3-4 /xM and generally much lower) are low relative to the Pi concentrations required to repress APase activity in laboratory cultures of bacteria and eukaryotic algae. Consequently, the positive relationship between APase activity and Pi is probably controlled more by seston biomass than by per cell APase activities. In this regard. Smith et al (1992) reported intense APase activity in association with marine aggregates compared to surrounding seawater; volumenormalized enhancements were 10^- to 10^-fold. The interstitial fluids of large dimension suspended and sinking particles may have chemical compositions that are different from the surrounding bulk fluid environments. This could select for, or against, specific enzyme activities. There are at least two ecologically relevant postsynthesis controls on in situ APase activities in seawater: trace metal concentrations and UV-B radiation. Renter (1983) demonstrated that APase activities in phytoplankton cultures, cell-free enzyme preparations and field collected samples are inhibited by free copper ions at concentrations comparable to those found in the marine environment (cupric ion activities of 10"^ to 10~^^ M). This trace metal effect could interfere with or totally block the direct utilization of selected DOP compounds by natural microbial assemblages and therefore alter marine P-cycle dynamics. More recently. Garde and Gustavson (1999) have documented a UV-B radiation (280-320 nm) sensitivity of APase activity in the marine environment. A major implication of this work is that photodegradation of APase activity may limit a cell's ability to obtain Pi from the ambient DOP pool, thereby exacerbating the effects of Pi limitation in well-lighted, near-surface habitats. This UV-B control of APase activity would probably be more important in clear, open-ocean ecosystems than in coastal
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habitats. In more productive coastal-shelf and estuarine habitats there may be a positive photolytic effect that derives from the light-dependent release of APase previously bound (and therefore deactivated) by humic substances (Boavida and Wetzel, 1998; Boavida, 2000). This photodegradation/photoactivation dichotomy may also affect other enzymes in the marine P cycle and, therefore, influence DOP turnover rates. Finally, Hoppe and Ullrich (1999) have presented a comprehensive assessment of APase activities not only in the euphotic zone but to abyssal ocean depths in the Indian Ocean. Contrary to expectation, the measured total APase activities generally increased with increasing depth despite decreased bacterial biomass, increased ambient concentrations of Pi, and a decrease in the activities of other hydrolytic enzymes. Elevated APase activities in the deep ocean (>1000 m) had previously been reported for particulate matter samples collected in the central North Pacific Ocean (Koike and Nagata, 1997) and may be a general feature of marine ecosystems. Hoppe and Ullrich (1999) hypothesized that the elevated deep water APase activities may be a manifestation of an enhanced carbon acquisition system involving bioavailable DOP compounds. The elevated APase would locally regenerate P/ but, more importantly, would capture the DOP compound carbon skeleton which could be respired to provide energy for cell maintenance. If this intriguing deep sea metabolic model is supported by future field research it would be an important lesson regarding our general ignorance of subeuphotic zone ocean processes. Regardless, the report of elevated cell-specific APase activities in P/-sufficient deep sea habitats casts doubt on past interpretations of environmental APase activity as being an indicator of Fi stress only. APase is just one of several potential enzymatic facilitators of DOP turnover in the sea (Fig. 5); we have discussed it at length here as a "case study" because it has been measured extensively in the sea. The enzyme 5NDase is a membranebound protein found in most bacteria (Bengis-Garber and Kushner, 1982) and in eukaryotic algae (Flynn et al, 1986); it is responsible for the hydrolysis of extracellular nucleotides (Fig. 5). In nature the substrate specificity of 5NDase overlaps with other enzymes; for example, ATP is also hydrolyzed by APase as well as by more specific ATPases (EC 3.6.1.4) found in many cells. A major difference seems to be in the regulation of enzyme production, especially the effects of Fi limitation. In contrast to APase, the activity and synthesis of 5NDase in E. coli are not inhibited by P/ and in this respect resemble inorganic pyrophosphatase (Neu, 1967). 5NDase may play a key role in nucleotide pool turnover and biosynthetic salvage pathways. Anmierman and Azam (1985) were the first to detect 5NDase in natural marine microbial assemblages and since that time numerous reports have appeared. Ironically, the assay system most frequently employed releases ^^P/ from [y^^P] ATP. This would integrate the activities of several different classes of phosphohydrolytic enzymes (5NDase, APase, ATPase), thereby overestimating specific 5NDase activity. The addition of 100 /xM of P/ to the assay mixture
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should improve the accuracy of 5NDase detection in collected samples (Cotner and Wetzel, 1991). From an ecological perspective, however, it is not so important which enzyme class is active but rather what the total rate of catalysis is under in situ conditions. Siuda and Glide (1994) found that ATP was hydrolyzed much more rapidly by 5NDase than by APase, whereas the rates of AMP and adenosine 5'-diphosphate (ADP) were comparable. If total extracellular nucleotide production in the ocean is controlled by cell exudation or grazing activities, then ATP may be a large portion of the pool and 5NDase activity would be important. If, on the other hand, hydrolysis of polymeric DNA and RNA supplies most of the dissolved nucleotides in seawater, then both APase and 5NDase would be important to the cells (Fig. 5). In fact, Ammerman (1991) concludes that the major function of 5NDase may be to assist in the coupled recycUng of RNA and DNA by hydrolyzing the riboand deoxyribonucleotides produced by nuclease enzyme activity. As discussed previously, the "bottleneck" in the DOP cycle may be nuclease, rather than 5NDase activity (Fig. 5). Nucleases and related enzymes catalyze the breakdown of nucleic acids by hydrolysis of the phosphodiester bonds. Some nucleases are specific for RNA (RNases), others act only on DNA (DNases), while still others are nonspecific. Furthermore, nucleases can be classified by mode of substrate attack; polynucleotides can be hydrolyzed at many interior locations in the polymer (endonucleases) or stepwise from one end of the chain (exonucleases). Additionally, the exonuclease attack can be directed from either the 3'->5' or the 5^->3'. Therefore the hydrolysis products from nuclease activity in seawater can result in a mixture of oUgonucleotides as well as 3' and 5' mononucleotides (Fig. 5). This is a potentially important point, since 5NDase is specific for 5'-nucleotides and will not hydrolyse 3' compounds (Bengis-Garber and Kushner, 1981). APase, on the other hand, will hydrolyze both 3^- and 5'-nucleotides (Fig. 5). Nuclease activity is also important for control of intracellular RNA concentrations, especially during carbon and energy starvation. In laboratory studies with E. coli, the RNA degradation products—including both 3'- and 5^-nucleotides and oligonucleotides—appear in the medium (Cohen and Kaplan, 1977). Consequently, this may be an important source for DOP production under certain nongrowth conditions (Novitsky and Morita, 1977).
D. DOP INTERACTIONS WITH LIGHT AND SUSPENDED MINERALS The marine DOP pool is known to react with UV light; in fact, this is one of the many techniques used to characterize (Karl and Yanagi, 1997) and quantify it (Armstrong et al, 1966). Less is known about solar-induced DOP photolysis in
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the sea. Francko and Heath (1982) reported the existence of UV-sensitive P (SNP which released SRP following timed exposure to natural UV irradiation) in lake ecosystems and it is probable that similar compound classes also exist in the marine environment (see Kieber etal, 1989). One intriguing implication of photochemical alteration of DOM is the possible cooccurrence of iron photoreduction (reduction of hydrous iron oxides) and P/ desorption from colloidal particles (Tate et ai, 1995). If similar actinic effects occur in the marine P cycle, one might anticipate that they would be restricted to the near surface waters where light fluxes are maximal. Near sea surface enrichments of SRP have recently been reported for samples collected in the North Pacific Ocean (Haury et al, 1994; Karl and Tien, 1997; Haury and Shulenberger, 1998), which could in principle arise via natural DOP photolysis (although other explanations are also possible). The near surface accumulation of lipid-rich, positively buoyant colloidal or particulate material may be important in this hypothesized pathway (i.e., organic matter + light -^ SRP). Finally, metal ion catalysis of phosphate ester hydrolysis in aqueous solutions is well-documented (Dixon et ai, 1982). However, the generally low concentrations of transition metal ions in open ocean habitats may preclude this process. More important in these habitats, phosphate ester hydrolysis may be facilitated by suspended minerals, including amorphous iron and manganese hydroxides (Baldwin et al, 1995). This could lead to an ecologically significant coupling between the atmospheric delivery of bioessential trace metals and the pulsed, abiotic release of P/ from semilabile or biorefractory DOP.
X. CONCLUSIONS AND PROSPECTUS The biogeochemical cycle of P (as well as C and N) in the sea is sustained by energy supplied to the surface ocean by sunlight. Photosynthetic production of organic matter fuels a complex series of trophic interactions and organic matter export (both as DOM and POM) from the euphotic zone that ultimately sustains life throughout most of the world ocean. In pelagic marine ecosystems, the supply rates of both N and P exert primary controls on ecosystem productivity (Smith et al, 1986). Over long time scales, P, rather than N, is probably the biomass- and production-rate-limiting nutrient in the global ocean (Redfield, 1958; Codispoti, 1989), due to P removal in shallow-water, carbonate-dominated ecosystems and due to the role of bacterial N2 fixation as a mechanism for relieving the ecosystem of fixed N limitation. Consequently, field studies of P cycling in the epipelagic zone are of fundamental importance for our understanding of microbial processes in oligotrophic oceanic habitats. Nevertheless, P-cycle investigations conducted beyond the continental shelf are rare, especially by comparison to the relatively large body of knowledge on
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N cycling in oceanic habitats. This situation is due, in part, to technical limitations in the ability to obtain precise and accurate determinations of low concentrations of dissolved P. A more complete chemical characterization of the DOM pools in seawater would be a most welcomed addition to contemporary studies of the marine P cycle. Likewise, a better understanding of the ecosystem processes that are responsible for extracellular accumulation of relevant biomolecules such as ATP, GTP, and nucleic acids will help to constrain DOP sources, sinks and fluxes. Finally, it is imperative that future field studies recognize the P cycle as an integral component of microbiological oceanography and marine biogeochemistry, along with the better studied though no less relevant C and N cycles. As McGill (1963) remarked nearly four decades ago, "The organic portion of the phosphorus cycle will undoubtedly receive much closer scrutiny in the future as its importance becomes more evident to biologists and oceanographers." While prophetic at that time, we still have some unfinished business. We look forward to more pathfinding contributions on marine DOP pool dynamics in the new millennium.
ACKNOWLEDGMENTS We thank the volume coeditors, D. Hansell and C. Carlson, for the invitation to prepare this chapter on marine DOP and, especially, all of the scientists who provided the original ideas, novel methodologies, and oceanic data sets that we summarize herein. A. Colman, K. Ruttenberg, C. BenitezNelson, and J. Ammerman provided invaluable conmients that improved an earlier version of this chapter. The NOAA-NODC online database was indispensable for the preparation of this chapter, as were the many scientists and technicians—both past and present—who have contributed to the HOT core measurement program. L. Lum and L. Fujieki provided invaluable assistance in the preparation of text and figures. Generous support for our investigations of the marine P cycle has been provided by the National Science Foundation (Grants OCE-9617409, OCE99-06820, OCE99-81313, and OPP9632763). This is SOEST publication number 5914 and U.S. JGOFS pubHcation number 769.
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Ammerman, J. W. (1991). Role of ecto-phosphohydrolases in phosphorus regeneration in estuarine and coastal ecosystems. In "Microbial Enzymes in Aquatic Environments" (R. J. Chrost, Ed.), pp. 165-186. Springer-Verlag, New York. Anmierman, J. W., and Azam, F. (1981). Dissolved cyclic adenosine monophosphate (cAMP) in the sea and uptake of cAMP by marine bacteria. Mar. Ecol. Prog. Sen 5, 85-89. Ammerman, J. W., and Azam, F. (1982). Uptake of cyclic AMP by natural populations of marine bacteria. Appl. Environ. Microbiol. 43, 869-876. Anmierman, J. W., and Azam, F. (1985). Bacterial 5'-nucleotidase in aquatic ecosystems: A novel mechanism of phosphorus regeneration. Science 227,1338-1340. Anmierman, J. W., and Azam, F. (1987). Characteristics of cyclic AMP transport by marine bacteria. Appl. Environ. Microbiol. 53,2963-2966. Amon, R. M. W., and Benner, R. (1996). Bacterial utilization of different size classes of dissolved organic matter. Limnol. Oceanogr 41,41-51. Andersen, O. K., Goldman, J. C , Caron, D. A., and Dennett, M. R. (1986). Nutrient cycling in a microflagellate food chain. III. Phosphorus dynamics. Mar. Ecol. Prog. Sen 31,47-55. Anderson, L. D., and Delaney, M. L. (2000). Sequential extraction and analysis of phosphorus in marine sediments: Streamlining of the SEDEX procedure. Limnol. Oceanogr 45,509-515. Antia, N. J., Harrison, P. J., and Oliveira, L. (1991). The role of dissolved organic nitrogen in phytoplankton nutrition, cell biology and ecology. Phycologia 30,1-89. Armstrong, F. A. J. (1965). Phosphorus. In "Chemical Oceanography" (J. P. Riley and G. Skirrow, Eds.), pp. 323-365. Academic Press, New York. Armstrong, F. A. J., and Harvey, H. W.. (1950) The cycle of phosphorus in the waters of the EngHsh Channel. /. Man Biol. Assoc. UK 2% 145-162. Armstrong, F. A. J., and Tibbitts, S. (1968). Photochemical combustion of organic matter in sea water, for nitrogen, phosphorus and carbon determination. /. Mar Biol. Assoc. UK4S, 143-152. Armstrong, F. A., Wilhams, P. M., and Strickland, J. D. H. (1966). Photo-oxidation of organic matter in seawater by ultraviolet radiation, analytical and other applications. Nature 211,481^83. Atkins, W. R. G. (1923). The phosphate content of fresh and salt waters in its relationship to the growth of the algal plankton. /. Mar Biol. Assoc. UK 13, 119-150. Atkins, W. R. G. (1925). Seasonal changes in the phosphate content of sea water in relation to the growth of the algal plankton during 1923 and 1924. /. Mar Biol. Assoc. UK 13,700-720. Atkins, W. R. G. (1928). Seasonal variations in the phosphate and sihcate content of sea water during 1926 and 1927 in relation to the phytoplankton crop. /. Mar Biol. Assoc. UK 15,191-205. Atkins, W. R. G. (1930). Seasonal variations in the phosphate and silicate content of sea-water in relation to the phytoplankton crop. V. November 1927 to April 1929, compared with earlier years from 1923. J. Mar Biol. Assoc. UK 16, 821-852. Atkins, W. R. G., and Wilson, E. G. (1926). The colorimetric estimation of minute amounts of compounds of siHcon, of phosphorus, and of arsenic. Biochem. J. 20,1223-1228. Atkins, W. R. G., and Wilson, E. G. (1927). The phosphorus and arsenic compounds of sea-water. J. Mar Biol. Assoc. UK 14,609-614. Atkinson, M. J. (1987). Rates of phosphate uptake by coral reef flat communities. Limnol. Oceanogr 32,426-435. Atkinson, M. J., and Smith, D. F. (1987). Slow uptake of ^^P over a barrier reef flat. Limnol. Oceanogr 32,436-441. Ault-Riche, D., Fraley, C. D., Tzeng, C.-M., and Komberg, A. (1998). Novel assay reveals multiple pathways regulating stress-induced accumulations of inorganic polyphosphate in Escherichia coli. J. Bacteriol. 18,1841-1847. Azam, F., and Hodson, R. E. (1977). Dissolved ATP in the sea and its utilisation by marine bacteria. Nature 267,696-698.
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Chapter 7
Marine Colloids and Trace Metals Mark L. Wells School of Marine Sciences University of Maine, Orono, Maine I. Introduction II. Definition of Marine Colloids III. Analytical Methods A. Number Concentrations of Marine Colloidal Matter B. Isolation of Colloidal Matter for Bulk Analysis IV. Metal Content of Marine Colloidal Matter V. The Chemical Form of Colloidal Metals
VI. Particulate-Based Estimates of Colloidal Metal Concentrations VII. Sources of Metal-Complexing Colloidal Ligands VIII. Measurement of Colloid Reaction Rates IX. The Biological Availability of Colloidal Bioactive Metals X. Summary References
I. INTRODUCTION A major fraction of organic carbon on the earth's surface exists as dissolved substances in seawater. These materials for the most part constitute the waste products of a dynamic cycling between carbon fixation and consumption in the oceans. They include reactive substances categorized broadly as proteins, polysaccharides, and lipids, as well as biologically resistant heteropolycondensations (humic matter) and degradation products of these primary constituents. Overall, these dissolved substances harbor a myriad of charged sites that can bind trace elements. Because Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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metal availability to microorganisms is in most cases proportional to the free ion concentrations of the metal, organic complexation decreases the immediate availability of nutrient metals. If retained in surface waters, these organic complexes serve to buffer metal ion activities at levels far below the total dissolved metal concentrations and likely also slow the export of essential metals from the photic zone. The cycling and availability of metals to microorganisms therefore is intricately involved with the marine carbon cycle. Metal availability strongly influences the abundance and types of phytoplankton that can flourish in a given location. Low metal availability favors picoplanktonic (0.2-2.0 /xm) algal species over their larger counterparts because higher surface area:volume ratios and narrower diffusional layer thickness make small cells better at acquiring metals. In contrast, higher metal availability is required to sustain rapid growth of nanoplanktonic species (2.0-20 /xm), particularly in the case of iron (e.g., Coale and associates, 1996; Hutchins and Bruland, 1998; Sunda and Huntsman, 1995a; Sunda et al, 1991). The balance struck between pico- and nanoplanktonic algal production strongly affects the export of carbon and nutrients (including metals) from surface waters to the deep. A proportional increase in nitrate export over the long term can raise surface water alkalinity, resulting in lower /7CO2 in surface waters, increased CO2 exchange with the atmosphere, and related consequences on global climate (Sigman and Boyle, 2000). Assessing the effect of dissolved carbon substances on the chemical speciation and transport of metals from surface waters is a key issue for understanding the global carbon cycle. Dissolved organic carbon (DOC) concentrations in coastal and open ocean waters exceed that of bioactive trace metals by several orders of magnitude. But most of the metal-reactive functional sites on these organic constituents interact weakly with trace metals in seawater and instead are occupied by major seawater ions (e.g., Mg^"*", Ca^"^). Organic ligands having high conditional stability constants for metal complexation comprise only a very small fraction of marine DOC. Nonetheless, these strong, effectively metal-specific organic ligands dominate the chemical speciation of most bioactive metals (e.g., Bruland, 1989; Coale and Bruland, 1988; Donat et al, 1994; Gledhill and van den Berg, 1994; Moffett and Brand, 1995; Moffett et al, 1990; Rue and Bruland, 1995; Wu and Luther, 1995). Some phytoplankton and heterotrophic bacteria release metal-complexing ligand molecules in response to metal stress, and grazing also is expected to release metabolites that contribute to metal complexation in seawater. It is anticipated that a tight bidirectional interaction between metal availability and ligand input likely shapes the magnitude and character of phytoplankton production in many coastal and offshore waters. Up until the early 1990s, organic complexation was expected to help retain bioactive metals in surface waters by minimizing the adsorptive loss of dissolved metal ions to sinking particulates. However, there has been a broad recognition over
Marine Colloids and Trace Metals the past decade that colloidal organic matter is extremely abundant in coastal and oceanic waters (e.g., Koikes?a/., 1990;Leppard^^fl/., 1997;Santschi^ra/., 1998; Wells and Goldberg, 1991, 1994). Earlier estuarine studies had demonstrated the importance of colloid aggregation for removing metals and carbon from estuarine waters (e.g., Sholkovitz et al, 1978). But this removal was driven by salt-induced destabilization of mainly lacustrine colloids, and it was not certain at the time whether colloidal cycling would be as important for marine-derived colloidal matter produced in shelf and offshore environments. The immediate fate of colloidal organic carbon phases in ocean waters is a matter of continuing debate. There is direct and indirect evidence that aggregation of colloidal organic matter (and associated metals) can at times be rapid. But colloidal organic phases also are labile with respect to microbial degradation. Aggregations of these organic phases may not only provide a major fuel for sustaining microbial production but might also serve to lock this fuel and microbes together in tight, interactive neighborhoods (Azam, 1998). While the relative importance of these opposing processes in coastal and offshore surface waters remains controversial, the outcome of the debate is significant because it bears upon how ocean systems might respond to perturbations in nutrient inputs associated with climate change. The central goal of this chapter is to summarize how our understanding of colloidal carbonimetal interactions in seawater has evolved over the past decade. During this period the traditional estuarine studies of colloid behavior have been expanded and extended to coastal and open ocean systems. To help set the stage, the definitions of marine colloidal matter and discussion of size separation methods are covered first. A summary is given next on which metals associate with marine colloids in nearshore and offshore waters and to what degree. Evidence is then presented on the chemical nature of the metahcoUoid association along with the sources of these materials. The chapter finishes with a brief discussion of how the marine colloidal phase may influence the biological availability of metals. The key issue that eludes consensus at this time is whether the metal-reactive colloidal matrix is moving toward larger particles via aggregation, or if its immediate fate instead is microbial degradation, leading to the dissemination of metals into the soluble phase of seawaters.
11. DEFINITION OF MARINE COLLOIDS One of the more notable issues in the study of marine colloids over the past decade has been the lack of agreement over what constitutes the marine colloidal phase. Thomas Graham (1861) coined the term "colloid" (meaning glue-like) to describe systems that displayed slow rates of diffusion through porous membranes (typical of glue solutions). Today, it is known that systems exhibiting "colloidal
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characteristics" contain finely divided matter generally sized between ~1 and 1000 nm in diameter (Void and Void, 1983), although these operational boundaries are not rigid. The lower size limit is the smallest dimension at which the internal environment of a substance theoretically can become markedly different from that of the surrounding milieu; hence an interface is established. The existence of an interface introduces the opportunity for other soluble or colloidal chemicals to interact both specifically and nonspecifically at the surface (adsorption), or, depending on the chemical characteristics, partition across the interface into the colloid matrix (absorption). This surface must comprise enough point charges from ionized functional groups to create an electrostatic field sufficient to stabilize the colloidal substance with respect to spontaneous aggregation with other colloidal or (> 1 /xm) particulate matter. The upper size boundary for colloidal matter lies at the juncture where gravity becomes the dominant force acting upon the particle. In essence then, a traditional view of colloids is that they are particles (not dissolved solutes) that do not sink unless they become entangled with other colloidal particles or sorb to sinking particulates. A 1-nm spherical diameter roughly equates with macromolecules of ^^1000 nominal molecular weight (or 1 kDa), a size equivalent to fulvic acids and marine porewater organic macromolecules (Chin and Gschwend, 1992). Organic biogeochemists traditionally categorize these and larger organic macromolecules as high-molecular-weight matter and characterize it in terms of elemental and molecular composition rather than its bulk interface characteristics. As a consequence, studies of the cycling of high-molecular-weight matter focus largely on specific molecular or biologically mediated chemical transformations. Casting the veil of "colloid" over macromolecular constituents does not diminish the importance of these processes but simply adds to them a range of nonspecific surface interactions that also might influence their behavior. In fact, most of the current dispute over the immediate fate of colloidal/high-molecular-weight organic matter lies in whether its short-term behavior is dominated by specific, biologically mediated chemical transformations or by rapid (and likely) nonspecific aggregative processes. By classical definition, the marine colloidal phase encompasses heterotrophic and phototrophic bacteria; termed "biocolloids." However, most oceanographers are dissatisfied with the concept of "biocolloids" so in most cases seawaters are filtered (0.2-0.8 /xm) to arbitrarily separate matter into a "particulate" phase, containing cells and large detritus, and a "dissolved" phase, containing solutes and colloidal particles. Operationally then, marine colloids are a subset of the classical colloid fraction described above. It has been argued recently that the definition of marine colloids instead should be based upon physicochemistry of the intracoUoidal matrix rather than a strict physical dimension (Gustafsson and Gschwend, 1997). In this "chemcentric" approach, the term colloid is applied only to those constituents that provide a molecular environment for the selective escape of chemicals from aqueous solution, by
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0.001 diameter (p.m) Figure 1 A graphical depiction of a chemcentric definition for colloidal matter. Here, the effect of particle dynamic processes on the mass distribution over the various size classes is illustrated. Steady-state particle size distributions (mass-based) are shown for three aquatic regimes having large differences in solids concentrations. The inflection point of each line where the slope changes is the functional distinction between colloids and "gravitoids" (sinking particles). The shaded areas depict the traditional, operational boundaries between soluble, colloidal, and "particulate" fractions. Based on a chemicentric approach, the upper size boundary of colloidal matter shifts in conjunction with the total solids concentrations in the water. Reprinted with permission from Gustafsson and Gschwend (1997).
either partitioning into or onto the colloidal constituent. By this definition, the lower threshold separating solutes from colloids still corresponds to a physical dimension of ~ 1 nm (for the reasons outlined above) but the upper size threshold is constrained by environmental transport conditions rather than by arbitrary size delimitation (Fig. 1). In a refinement of the classical colloid definition, the size boundary between colloids and "gravitoids" is determined by the outcome of kinetic competition between aggregation and sedimentation. Gustafsson and Gschewnd (1997) argue that this size boundary shifts as a function of the total solids concentration, so the upper threshold delimiting colloidal matter will be several micrometers in coastal waters versus several tenths of microns in the deep ocean (Fig. 1). Another significant distinction is that not all substances larger than a nanometer are colloidal. High-molecular-weight polyelectrolye molecules that assume an extended conformation in seawater would not meet the chemcentric criteria for colloids. This aspect is problematic for studying the marine colloidal phase because no methodologies currently exist for measuring the conformation
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of organic molecules in marine water samples. However, a functionally based definition is more adaptable to studying the effect of colloidal processes in natural systems (Gustafsson and Gschwend, 1997). While the past decade has brought more dissention than consensus about what constitutes marine colloids, our understanding of the varied roles that colloids may play in coastal and offshore waters has nonetheless improved despite arbitrary and inconsistent size-based delimitations of the marine colloidal phase. The analytical methods underlying these studies are now considered.
III. ANALYTICAL METHODS The analytical approaches used to study marine colloids lie in two broad categories; determination of the abundance and elemental and molecular composition of marine colloids, and the assessment of colloid reaction rates, primarily with respect to their transfer into particulate phases. The methods used to quantify the abundance of colloidal matter will be considered now while the measurement and implications of colloid reaction rates are covered in section VII.
A. NUMBER CONCENTRATIONS OF MARINE COLLOIDAL MATTER Early studies established that a significant fraction of dissolved organic matter lay in the colloidal size range (e.g., Carlson et al, 1985; Maurer, 1976; Moran and Moore, 1989; Ogura, 1977; Sharp, 1973). These findings catalyzed a burst of interest in marine colloids and their role in carbon and metal cycling. Koike et al. (1990) reported that the abundance of nonliving organic particles sized between 0.38 and 1.0 /xm were ~10^ particles mL~Mn surface waters of the North Pacific. This finding was corroborated for coastal waters off Nova Scotia in a joint project using several different analytical approaches (Longhurst et al, 1992). The concentration of these "Koike" particles decreased by 10x in deep waters, implying that there was active production of colloidal matter in the photic zone. These flexible (difficult to filter) particles were 4-30 x more abundant than marine bacteria. Moreover, Koike et al. (1990) showed that bacteria were not a source of these colloids but that they likely originated with the activity of small flagellates. They estimated that these particles accounted for ~10% of the DOC, in agreement with estimates from earlier bulk separation studies (Sharp, 1973). Number concentrations of marine colloids in seawater were measured for sizes down to ^ 5 nm using a combination of ultracentrifugation and transmission electron microscopy (Wells and Goldberg, 1991, 1992, 1994). Colloid concentrations
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increased logarithmically with decreasing size in coastal California seawaters, with numbers being on the order of 10^ colloids niL~^ Similar abundances were observed in surface and deep waters of the North Atlantic, equatorial Pacific, and the Southern Ocean (Wells and Goldberg, 1994, and unpubHshed data), demonstrating the widespread distribution of marine colloidal matter. At each station, the mean particle size tended to be larger near the base of the thermocline, suggesting a different source or intensity of colloid production in this region. In all cases, the globular-shaped colloidal particles exhibited heterogeneous electron densities, suggesting that they perhaps are aggregates of smaller molecules (Fig. 2). In subsequent studies, resin embedding methods were used to ensure that molecules maintained their configurations upon drying, and stains were applied to improve the visibiHty of the colloidal phase (e.g., Heissenberger and Hemdl, 1994; Leppard et al, 1997). These studies confirmed the presence of the granular colloids noted above and showed that additional, more amorphous colloidal matter also was present. Transmission electron microscopy (TEM) studies also showed the presence of large aggregates of colloidal matter (Leppard et al, 1997; Wells and Goldberg, 1993) that can become incorporated into marine snow aggregates (Leppard ^f fl/., 1996). More recently, Santschi et al (1998) used a combination of TEM and atomic force microscopy to show that fibrillar colloids, 1-3 nm in width and 100-2000 nm in length, comprise a significant fraction of colloidal organic matter in coastal and offshore seawaters. Thesefibrils,rich in polysaccharides (Santschi et al, 1998), are clearly colloidal by the standard size definition but may be noncolloidal based upon a chemcentric view (Gustafsson and Gschwend, 1997). Regardless, these fibrils form aggregates up to several micrometers in size, often incorporating globularshaped colloids (Santschi et al, 1998). Fibrillar "particles" therefore are likely to be important in colloid cycling. Dynamic light scattering (DLS), also known as photon correlation spectroscopy, has been successfully applied recently to the study of colloidal abundance and formation in seawater (Chin et al, 1998). With dynamic Hght scattering, the time dependence offightscattered from a laser-illuminated volume of solution is measured over tenths of a microsecond to milliseconds. These fluctuations are a function of the diffusion rate of molecules and particles within this volume (that is, Brownian motion). The time dependence of scatter therefore can be used to calculate the diffusion coefficient of particles if a number of conditions can be met. In favorable cases there are methods available for treating the time-dependent fluctuations in the scattered light intensity to extract the "hydrodynamic" (or "Stokes radius") colloid size distribution. Chin et al (1998) used this capabiHty to measure shortterm changes in the abundance of colloids a few nanometers to a few micrometers in size (see below). This methodology is certain to be applied more frequently in future studies on marine colloid dynamics.
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10m
300 m
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100 m Figure 2 Transmission electron microscope images of marine colloidal matter from a depth profile in the Sargasso Sea. Colloids were settled directly onto charged TEM grids by ultracentrifugation (see Wells and Goldberg, 1994). Differences in colloid size, morphology, and abundance are readily apparent, with the larger colloids being most prevalent near the base of the photic zone (100 m) and immediately below (3(X) m). These globular colloidal particles as well as more electron-transparent colloidal particles are seen in nearshore waters when embedding and staining methods are employed (Leppard et ai, 1997). Scale bars, 100 nm.
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B. ISOLATION OF COLLOIDAL MATTER FOR BULK ANALYSIS Analysis of the constituents that comprise marine colloidal matter generally requires the separation and preconcentration of colloids from conventionally filtered (e.g., 0.2 /xm) seawater. Although it is possible to analyze elemental compositions of individual particles using TEM/energy dispersive spectroscopy (e.g., Chin etal, 1998), the low sensitivity of the method and nonhomogeneity within and among individual particles strictly limits the quantitative value of this approach (Wells and Goldberg, 1991). The primary method at present for preconcentrating colloidal matter for bulk chemical analysis is cross-flow (or tangential flow) filtration (CFF). This approach is attractive for its operational simplicity and the high concentration factors (>100x) that can be achieved. However, the separation of molecules by pore size exclusion is strongly influenced by molecular conformation, interaction with the membrane and interaction with other soluble and colloidal substances near the membrane surface (Buffle et al, 1992). Aside from conformational and molecular flexibility issues that cloud the accuracy of size exclusion methods, solvent flow through the membrane leads to the accumulation of macromolecular substances near the membrane surface; a process that is countered by back diffusion of molecules from the membrane. This concentration "polarization" can enhance colloid-colloid and colloid-solute interactions. Small solutes that should otherwise pass through the membrane might then become associated with larger colloids that do not, altering the apparent size fractionation. Directing sample flow tangentially across the membrane surface reduces the thickness of the concentration polarization layer, decreasing but likely not entirely eliminating the possibility for self-aggregation (Buffle et al, 1992). The lowering of the osmotic barrier also increases permeate (filtrate) flow rates. In practice, the retentate solution containing the macromolecules is swept from the membrane and recycled through the retentate reservoir. This reservoir usually encompasses the entire starting sample volume, but in a few cases a small retentate reservoir instead is continuously replenished with fresh sample water as CFF proceeds (e.g., Gustafsson et al, 1996). The latter approach, termed sampling mode (Dai et al, 1998), minimizes the exposure of the colloidal constituents to the CFF system and may yield better estimates of the retention coefficient of a molecule. Determination of the colloidal fraction of carbon or metals in conventionally filtered (0.2-0.7/xm) "dissolved" samples typically is done in one of two ways. The more straightforward method is to subtract analyte concentrations in the membrane permeate from those in the starting filtrate solution. But this approach potentially can bias the determinations because any sorption of truly soluble metals or organic molecules to the CFF system is then quantified as being colloidal, thus overestimating the colloid fraction. Conversely, the colloidal fraction could be underestimated if there is low-level carbon or metal contamination of the permeate
376
Mark L Wells
from the CFF system. Nonetheless, once system leaching and sorption problems are verified to be minimal for a given water type, ultrafiltration cartridges can offer a viable straightforward approach for determining colloidal metal concentrations (Nishioka^r^/., 2001) The preferred analytical approach is to determine mass balance for each sample separation to ascertain if there are contamination or sorption problems. In this case, analyte concentrations are measured in the starting filtrate, the membrane permeate, and the membrane retentate fractions. Colloidal metal concentrations are then calculated by subtracting the permeate concentration from the retentate and dividing the result by the concentration factor. Mass balance can then be assessed by comparing the sum of the analyte soluble and colloidal concentrations with that in the conventionally filtered starting solution. While preferable over the simple difference approach, mass balance determinations still are relatively insensitive and could mask significant sorption problems (Gustafsson et ai, 1996). A measured loss of analyte to the CFF system may not be due to sorption. Incomplete flushing while extracting the CFF retentate will leave a large portion of colloidal material in the concentration polarization layer, leading to a low estimate of the colloidal metal concentration (see in Buffle et al, 1992). For example, it is recommended that once CFF processing is complete, the retentate solution should be recirculated for some time with the permeate flow turned off to enhance recovery of the colloidal material (Buesseler et ai, 1996). In practice, any "missing" analyte usually is attributed to incomplete colloid recovery, the identical result as taking the simple difference between permeate and starting solution concentrations. Nonetheless, determining mass balance provides an indication of which results should be interpreted with added caution. The increasing use of CFF in colloid studies during the early 1990s led to an intercomparison study to assess whether different CFF systems provided well-defined and operationally reproducible results (Buesseler et al, 1996). This "colloid cookout" study was conducted using 14 different CFF systems representing five different manufacturers, with the central criterion being the size fractionation of organic carbon with 1-kDa membranes. Large volumes of homogenized surface waters off Woods Hole, Massachusetts, and mid-depth (600 m) waters off the National Energy Laboratory of Hawaii were processed on-site (Buesseler et al, 1996). Although the primary focus was testing the separation of colloidal organic matter, the outcome is sunmiarized here because it has direct significance to the study of colloidal trace metals. There were two primary findings of the intercomparison study. First, extremely long cleaning and flushing times are required to reduce the DOC blanks of new cartridges. Second, the degree of colloid retention by the 1-kDa membranes varied dramatically among manufacturers, but was similar among different groups using the same brand of membrane. Even so, retention efficiencies can vary among CFF membrane batches from a single manufacturer (Dai et al, 1998, P. Santschi,
Marine Colloids and Trace Metals
377
pers. commun.) reflecting the shortcomings of using industrial-based separation technologies outside the limits of their design application. For systems displaying high retention efficiencies of marine colloids (e.g., Amicon), permeate DOC concentrations increased significantly with the concentration factor. In contrast, this "breakthrough" of organic carbon was not apparent in systems equipped with membranes having lower colloidal retention efficiencies. A similar increase in the permeate concentration of trace metals has been observed with Amicon 1-kDa membranes (Guo et al, 2000b; Wen et al, 1996) but not with Filtron 1-kDa membranes (Powell et al, 1996; Wells et al, 2000). Although there is uncertainty about the cause of changing analyte concentrations in the permeate during processing (Buesseler et at., 1996), it may be due to increased membrane transport of soluble (<1 kDa) molecules held in the concentration polarization layer (Guo and Santschi, 1996; Gustafsson et al, 1996). Guo et al (2000b) experimented with standard molecules and showed that >40% of 0.5-kDa rhodamine 6G and 0.6-kDa glutathione are retained by the 1-kDa Amicon SlONl membrane, even at concentration factors of ^50. They suggested that the reverse problem, breakthrough of high-molecular-weight standards, was not significant (but see below). Retention of soluble (<1 kDa) substances would imply that colloidal fractions may be overestimated when large changes occur in permeate analyte concentrations over time. As a result, Guo et al. (2000b) argue that high concentration factors (>40) help to minimize the retention of soluble organic phases, contrary to earlier recommended protocols (e.g., Buesseler et al, 1996). They also showed that diafiltration with deionized water further reduced the retention of their < 1-kDa molecular probes. However, the mechanistic interpretations by Guo et al. (2000b) for the increasing permeate concentrations with higher concentration factors rely on a permeation model for single discrete molecules that assumes that the sorption of molecules to the membrane is neghgible (see in Kilduff and Weber, 1992; Logan and Juany, 1990). But sorption of certain substances can be significant (e.g., Dai et al, 1998; Gustafsson et al, 1996). This simplified model also may not apply equally well to complex mixtures of individual compounds or to colloidal assemblages of discrete molecules, both of which likely comprise the marine colloidal phase. The decreasing ionic strength during diafiltration of the retentate also may alter the conformation of natural colloidal organic molecules enough to affect their retention. For example, decreasing Mg^"^ and Ca^+ activities causes disaggregation of natural colloidal polymers in coastal waters (Chin et al, 1998). The question of the breakthrough of organic molecules during CFF is an issue of continuing debate. Dai et a/. (1998) compared the performance of the Amicon 1-kDa membrane used by Guo et al. (2000b) with the Millipore Prep/Scale 1-kDa membrane with standard molecules as well as nearshore and offshore seawaters. This comparison is particularly useful because the Amicon 1-kDa membrane, a mainstay for marine colloid studies, became no longer commercially available
378
Mark L.Wells
after Amicon merged with Millipore. From these data, Dai et al. (1998) concluded that breakthrough of both high- and low-molecular-weight matter occurs during processing as a consequence of the CFF membrane itself as well as physical/chemical interactions of specific organic constituents with the membrane. Breakthrough varied among the oceanographic sites likely due to differences in molecular composition and concentrations of COC. They attributed the bulk of this breakthrough to high-molecular-weight colloids, in contrast to the findings of Guo et al. (2000b), and reconmiended keeping CFP concentration factors <5 to minimize breakthrough artifacts. It is likely that the same recommendation would apply to the retention of colloidal trace metals, although it is not known whether the minute subset of COC responsible for binding trace metals behaves similarly to the bulk COC. Despite intensive study then, we remain at odds over whether large or small concentration factors improve the accurate retention and isolation of marine colloidal organic matter. The answer, if it is truly one or the other for all marine colloidal constituents, likely will depend in large part upon the molecular architecture of the colloidal organic matter and the degree to which it is structurally rigid or amorphous. Those colloids less susceptible to structural deformation would have a low probability of permeating through the membrane pores while the reverse would be true for more amorphous or even linear structures, such as reported by Santchi et al. (1998). Strict calibration of CFF membranes is useful for assessing membrane characteristics and performance over time, but this "calibration" shifts when standards of equivalent molecular weight but different molecular architectures are used (see in Gustafsson et al, 1996). Combined with the recognition that compositional fractionation of the colloidal retentate will occur as concentration factors increase, it is likely that highly accurate colloidal size separations may never be achieved by CFF. Nonetheless, CFF remains an extremely useful tool for assessing the broad characteristics and abundance of the marine colloidal phase. An alternate method for the size separation of molecules is flow field-flow fractionation (flow FFF), and this technique is only just beginning to be applied in the study of marine colloidal matter (Beckett and Hart, 1993; Beckett et al, 1990; Gustafsson et al., 2001; Hassellov et al., 1996, 1999). In flow FFF, a flow field is applied at right angles to a channel flow in a shallow (~200 /xm) ribbonlike chamber. Soluble fractions are driven through a membrane (1 kDa) at the accumulation wall, while colloidal components are driven toward the membrane surface. The resultant concentration gradient is opposed by diffusion (a function of colloidal size), resulting in colloids of different sizes being retained in different stream laminae (Fig. 3). The smaller the colloids the higher they diffuse into the parabolic velocity profile and thus the faster they elute. The timing at which colloidal matter exits the flow chamber then is in proportion to its size (hydrodynamic diameter). In addition to yielding a soluble phase, the method provides a high-resolution, continuous size spectrum of colloidal matter, contrary to CFF,
379
Marine Colloids and Trace Metals
Inflow (+ sample injection)
Y
X
Outflow (to detector)
Field
Flow FFF Crossflow (in)
M I +I +I I
Frit
Crossflow (out)
Figure 3 The components and theory of FFF separation. (A) The ribbon-hke channel has a breadth of a few centimeters and a thickness of ~ 100 /xm. The outflow is directed to a detector for various optical or metal analyses. (B) The lengthwise cross section of the channel shows the different distributions of arbitrary components X and Y across a parabolic flow profile and the unequal flow velocities that result. The characteristic mean elevations of the X and Y "clouds" are indicated. (C) lUustration of the flow field across the channel in flow FFF. Adapted with permission from Giddings (1993).
which yields only bulk separation of those materials retained by the membrane. A central disadvantage of flow-FFF is that the sample is gready diluted within the channel, decreasing the ability to measure the resultant size fractionation. Sample "focusing," in which a larger volume of sample (e.g., 10 mL) can be preconcentrated within the channel before initiating flow separation (Hassellov et al, 1996), may partially offset this shortcoming but it remains unclear whether this focusing introduces artifacts in the size distribution of the colloidal phase. For
380
Mark L Wells
example, preconcentration of riverine colloids can enhance colloid-colloid and colloid-solute interactions that potentially could alter colloidal size separations by flow-FFF (Lead et ai, 1997), but these aggregation problems have not yet been shown to be significant at the high ionic strength of seawater. Thus while flow-FFF techniques are not be suitable for the bulk isolation of large quantities of marine colloidal matter, they may be ideally suited for studying constituents that can be detected with high sensitivity. Flow FFF also affords an opportunity to perhaps investigate degradation or aggregation process with high definition. For example, the system components can be constructed of "metalfree" polymers suitable for trace metal studies. Hassellov et al (1999) coupled the channel outflow of flow FFF on-line with a low-resolution ICP-MS to determine the colloidal size continuum of >20 elements in stream waters. Unfortunately, the high salt content of seawater precludes this simple approach for all but perhaps estuarine waters, but interfacing flow-FFF with flow injection analytical methods might still provide a similar capability for studying colloidal trace metals in marine waters. While the very limited use offlowFFF in marine waters has prevented close examination of potential methodological artifacts influencing the size separations, these techniques are certain to gamer attention in the future. The differing and imprecise size retention of marine colloids by CFF membranes challenges our ability to quantitatively compare findings among studies from disparate locations and times. While this situation is unfortunate, it is important to remember that these shortcomings are not restricted to CFF systems. Conventional filtration of seawater also suffers major artifacts in size selectivity, even when using etched membrane filters (e.g., Koike et al, 1990; Stockner et al, 1989). Nonetheless, CFF presently remains the only effective method for accumulating enough high-molecular-weight substances from seawater to examine the broad molecular and metal composition of the marine colloidal phase. For that reason, CFF will continue to serve a key role in colloid studies in the foreseeable future.
IV. METAL CONTENT OF MARINE COLLOIDAL MATTER The tremendous increase in study of colloid-associated trace metals over the past decade has considerably expanded the database for estuarine and nearshore waters (Table I). Even so, this database comprises <25 articles with generally only a few samples each. Typically, CFF processing has been conducted with either 1- or 10-kDa molecular weight cutoff membranes. Many early studies either did not determine mass balances or suffered from low metal recoveries. However, the qualitative picture that emerged from this work has been refined with recent improved methods.
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The collective findings establish that a significant component of bioactive, or nutrient, metals (Mn, Fe, Co, Ni, Cu, Zn, Cd) occur in the colloidal phase along with numerous other trace metals. Sigelo and Helz (1981) showed that estuarine colloidal material contained more than 30 elements, while Bertine and VernonClark (1996) found a similarly large range of colloidal elements off the California coast. Postcollection desalting procedures were used in both of these studies, so colloid fractions may have been underestimated if there were significant ionic strength-mediated changes in molecular conformations. But as noted above, Guo et al (2000b) argue that any "losses" during desalting instead result in more accurate colloidal size separations. Despite the different cutoff size and filter types used for conventional filtration and subsequent CFFs, several consistent patterns appear in these estuarine and coastal water data. The most straightforward observation is that the proportion of colloidal to soluble metals tends to decrease from the upper estuary to coastal waters, as has been described previously (e.g., Sholkovitz et al, 1978). Even so, colloid-associated metals constitute a significant fraction of "dissolved" metals in coastal, high-salinity waters (Table I), also consistent with the results of earlier studies (e.g., Mayer, 1982). With respect to nutrient trace metals, a high proportion of dissolved Fe is colloidal in many estuarine waters (e.g., Dai and Martin, 1995; Guieu et al, 1998; Powell et al, 1996; Wen et al, 1996) and coastal embayments (e.g., Benoit et al, 1994; Martin et al, 1995; Wells et al, 1998, 2000; Wen et al, 1999; Whitehouse et al, 1990). Dissolved Cu is only slightly less dependent on the colloidal phase, with 1-90% of dissolved Cu appearing in the various colloidal size fractions in these waters (Table I). Ni and Cd follow, with each being up to ^78% colloidal (Dai and Martin, 1995; Dai et al, 1995; Martin et al, 1995; MuUer, 1998; Powell et al, 1996; Sanudo-Wilhelmy et al, 1996; Wells et al, 1998, 2000; Wen et al, 1996,1999). Wen et al (1999) found that 5-32% of dissolved Co was colloidal in Galveston Bay. Santschi et al (1987) showed that 30-60% of Se, a metal required by some phytoplankton, was colloidal in Narragansett Bay, Rhode Island. In contrast to these metals, dissolved Zn normally is predominantly soluble (Benoit et al, 1994; Sanudo-Wilhelmy et al, 1996; Wells et al, 1998, 2000; Wen et al, 1996). A notable exception is in Galveston Bay, where >85% of dissolved Zn was retained by a 1-kDa (Amicon) membrane (Wen et al, 1999). Dissolved Mn also occurs predominantly as soluble species in seawater (Benoit et al, 1994; Guentzel et al, 1996; Powell et al, 1996; Sanudo-Wilhelmy et al, 1996; Wells et al, 2000; Wen et al, 1996; Whitehouse et al, 1990), the exception being in Venice Lagoon, where ^^50% of dissolved Mn was colloidal (Martin et al, 1995). This unusual result may be related to the very high DOC concentrations in these lagoon waters. The marine colloidal phase also contains nonnutrient trace metals. From 2 to 100% of conventionally filtered Al is colloidal in coastal embayments and
383
Marine Colloids and Trace Metals Table II Compilation of the Percent Colloidal Fraction of Metals in Dissolved (Generally <0.45 /xm) Offshore Waters^ Location Offshore North Atlantic (Moran and Moore, 1989) North Atlantic (Wu and Luther, 1994)fc
Salinity
Cutoff
Al
31-34
1 kDa
1-15
35-36.7
0.2 ^tm
Hawaii—Deep (Reitmeyer etal, 1996; Wen ^ffl/., 1996) Gulf of Maine (Greenamoyer and Moran, 1996)
1 kDa
Ni
Cu
Cd
Pb
9
63
2
9
0-45
34
6-67
20-45
0-11
1 kDa
North Pacific (Nishioka etal, 2001) Equatorial Pacific (Wells, in press)
Fe
13-50
35
1 kDa
10
^ There were no Mn, Co, Zn, As, or Hg data available for offshore waters at the time of this compilation. ^The colloidal size range of 0.2-0.4 /xm is much larger than normally accepted but the results are included here for reference.
nearshore waters (Be^noitetaL, 1994; Sanudo-Wilhelmy ^r«/., 1996). Dissolved Pb shows a similar preference for the colloidal phase (1-100%) in these environments (Benoit et al, 1994; Dai and Martin, 1995; Kozelka et al, 1997; Martin et al, 1995; MuUer, 1998; Wells et al, 1998; Wen et al, 1996, 1999). In addition, a major fraction of dissolved Hg is colloidal in various Texas estuaries and the Ochlockonee estuary in Florida (Powell et al, 1996; Stordal et al, 1996). There are far fewer studies of colloid-associated metals in offshore waters (Table II). Moran and Moore (1989) used some of the first trace metal clean CFF techniques to measure a 1-15% colloidal fraction of Al in North Atlantic surface waters. Similar values were observed in deep (600 m) waters off Hawaii during the colloid intercomparison study (Reitmeyer et al, 1996; Wen et al, 1996). The colloidal fraction of Fe typically is higher, ranging from 10 to 50% in the North Atlantic, North Pacific, and equatorial Pacific (Nishioka et al, 2001; Wells, in press; Wu and Luther, 1994). The colloidal phase comprises a significant portion
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Mark L Wells
of dissolved Ni, Cu, Cd, and Pb in surface waters of the Gulf of Maine and in deep waters off Hawaii (Greenamoyer and Moran, 1996; Reitmeyer et ai, 1996; Wen et al, 1996). Although sparse in comparison to nearshore data, these limited findings suggest that the percentage colloidal component of dissolved metals may not be substantially different between open ocean and coastal environments. Yet these two environments differ greatly in total dissolved metal concentrations. These findings may further suggest that colloids contain chemical species that interact selectively with different metals. The underlying cause for the large differences in percentage colloidal metal measured among similar water types is difficult to assess. This variability is probably attributable partly to the use of different molecular-weight cutoff membranes and variable concentration factors (Gustafsson etal.,l 996). For example Wen et al (1999) found the highest colloidal fraction of Zn to date in a coastal embayment using a membrane brand known to have higher colloid retention efficiencies than other brands (Buesseler et al„ 1996). But a large range in colloidal metal content also is found among environments when uniform sampling methodologies are employed (e.g., Guo et al, 2000a). Moreover, seasonal and depth-related changes in the fraction of colloidal metal have been measured at single sampling sites (Kuma et ai, 2000; Nishioka et al, 2001). For example, Kuma et al. (2000) showed that the change in colloidal fraction of Fe at 2 m over the spring bloom was as large as that from surface to deep (ranging from 6-70%). Thus, while analytical issues can be problematic, they likely overlay fundamental trends in the composition and abundance of the colloidal metal fraction in seawater. In contrast to most studies that analyze volume-based concentrations of colloidal trace metals (e.g., nM), Guo et al. (2000a) characterized metal and carbon contents of diafiltered, freeze-dried CFF colloidal isolates from three marine regions: the Mid Atlantic Bight, the Gulf of Mexico, and Galveston Bay. Their study is the most comprehensive to date on metal colloid associations in different coastal waters. They show that the bioactive metals Cu, Zn, Ni, and Fe have average concentrations > 10 fjig/g colloidal mass while Pb, Al, Mn, V, Ba, and Ti have average concentrations between 1 and 10 fJ^g/g. Concentrations of Cd, Co, and Be were < 1 /jLg/g of colloidal mass. These data have been influenced by a significant loss of colloidal metals during the diafiltration process. In Galveston Bay, metal recoveries from the retentate after diafiltration were ~50% for Cu, ^^36% for Zn, ~32% for Ni, and only ~ 9 % for Pb (Wen et al, 1999). It remains to be determined whether these losses reflect more efficient flushing of low-molecular-weight colloids from the concentration polarization layer (Guo et al., 2000b) or desalting effects on the conformation of colloidal molecules. Despite these uncertainties, the work of Guo et al. (2000b) is important because the identical methodologies employed permit closer examination of the differences in colloidal metal fractions in surface waters of Galveston Bay, the Gulf of Mexico, and the Mid Atlantic Bight. In general, the inshore to offshore concentrations of
Marine Colloids and Trace Metals
385
colloidal metals (/xg Me/gC) either decreased (Cu, Co, Ni, Cd, Fe, Al, Mn, Ba, Ti), or showed no obvious trend (V, Pb, Zn, Cr, Be) in the Gulf of Mexico (Guo et al, 2000b). In contrast, most colloidal metal concentrations iiJiglg) increased from nearshore to offshore in the Mid Atlantic Bight for Fe, Al, Mn, V, Ti, Ba, Co, Ni, Pb, Zn, Cd, Cr, and Be. In almost all cases the average colloid metal concentrations were higher in the Mid Atlantic Bight than in the Gulf of Mexico. This pattern is consistent with the higher terrestrial and aerosol input to North Atlantic waters relative to other open ocean regions (Duce and associates, 1991). These comprehensive data provide clear evidence that colloidal metals are a significant component of the dissolved metal fraction in coastal and open ocean waters. The findings also provide the first quantitative evidence that spatial distribution of colloidal metals in offshore waters is likely coupled to the prevalence of terrestrial dust inputs (e.g., higher in the western North Pacific and equatorial Atlantic surface waters). In contrast, there are no clear indications of the temporal variations in colloidal metals.
V. THE CHEMICAL FORM OF COLLOIDAL METALS One of the more obvious changes in the bulk composition of colloidal matter moving from estuarine to shelf and offshore waters is a progressive decrease in mineralogical content. While clays and metal oxyhydroxides can be abundant colloidal constituents in riverine and estuarine waters (Sigleo and Helz, 1981; Sigleo and Means, 1990), they are only occasionally identified in coastal waters (Wells and Goldberg, 1992, Wells, unpublished data) and are extremely rare in offshore surface and deep environments (Benner et al, 1997; Leppard et al, 1991 \ Wells and Goldberg, 1994). Instead, the colloidal phase is almost exclusively organic matter, the composition of which is discussed in detail by R. Benner (Chapter 3). It is sufficient here to recognize that 10-78% of "dissolved" organic carbon in seawater is colloidal, based upon CFF size fractionation. In most cases then, metals are trace constituents that accompany this bulk carrier phase. Metal associations with organic matter can be characterized by ligand exchange reactions, whereby cations associate with electronegative or negatively charged functional groups of the molecule (or "surface"). These likely include -COOH, -OH, and R-N-R or R-S-R groups distributed within the organic matrix. For example, colloidal organic matter in Galveston Bay and the Gulf of Mexico contains 1.4 meq/g of proton reactive sites, or ^1-10 /xM (Santschi et al, 1995). Taken singly, these sites add hydrophilicity to the molecules but bind trace metals only weakly, if at all, due to competition with the major seawater cations (e.g., Mg^+, Ca^"^). But when two or more of these functional groups occur in close proximity to one another, or along molecules flexible enough to bring them into close proximity, then strong "chelates" might form with trace metal ions depending upon the
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Mark L Wells
architecture of the Ugand site. Unfortunately, measurement of bulk proton reactivity gives no indication of how strongly trace metals will associate with organic matter. Nonetheless, various studies have found positive correlations between colloidal organic carbon (COC) and colloidal metal concentrations. Stordal et al (1996) showed that colloidal Hg in Galveston Bay was strongly related to COC concentrations, perhaps bound to thiol functional sites (Guentzel et al, 1996). Colloidal Cu, Ni, Zn, Co, Cd, and Pb also correlated with COC in Galveston Bay (Guo et al, 2000a; Wen et al, 1999). Colloidal Fe, Ni, and Cu were linearly correlated with COC in the Ochlockonee estuary (Powell et al, 1996). However, in each case the correlations differ distinctly among the metals. On average, colloidal metaliCOC correlations in offshore waters in the Gulf of Mexico and the Middle Atlantic Bight are weaker but still suggested for Cu, Zn, Ni, and Co (Guo et al, 2000a). But these relationships also differed substantially among the three environments (Guo et al, 2000a), making it clear that the colloidal fraction of any given trace metal is not coupled tightly to the abundance of colloidal carbon. It is now widely accepted that the chemical speciation of most bioactive metals in seawater is regulated by strong complexation with natural organic chelators (see in Bruland et al, 1991; Donat and Bruland, 1995). These ligands are present in very low concentrations (nM) but effectively form metal-specific complexes having very high conditional stability constants in seawater, orders of magnitude above that of simple cation sorption to charged surface sites. The cycling of bioactive metals therefore is intrinsic to the behavior of this subset of organic constituents. While it was anticipated that these strong ligands would be of low molecular weight, recent work demonstrates that Cu, Zn, Cd, and Pb complexing ligands are partly colloidal in both Narragansett Bay and estuarine and coastal waters off England and Scotland (Muller, 1996, 1998, 1999; Wells et al, 1998). In Narragansett Bay, there is a distinct separation in the size classes of Cu and Pb ligands, with colloidal Cu ligands being 1-8 kDa and colloidal Pb Ugands being mainly 8 kDa0.2 /xm in size (Wells et al, 1998). These findings indicate that metal-specific reactions control bioactive metalicolloid associations, rather than simple sorption processes. Muller (1998) arrived at the same conclusion for Cu and Pb based upon ligand spatial distributions and comparative ligand/coUoid characteristics in the Firth of Clyde, Scotland. Muller (1999) suggested that colloidal Cu and Pb complexing ligands might form in situ as weakly bound assemblages of soluble metal-specific ligand molecules. A possible mechanism for generating such assemblages is discussed by Chin et al (1998) (see below). Further evidence that metalicolloid interactions are controlled by metal-specific reactions are observations that the conditional stability constants for metal complexation vary with the size of organic ligands. The stronger class of Cucomplexing organic ligands (Li) are more prominent in the soluble phase of Chesapeake Bay (Gordon etal, 1996) and in the coastal waters of southern England (Muller, 1996). But both the strong and weaker classes of Cu-complexing ligands
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appear to be split between the soluble and colloidal phases in Narragansett Bay (Wells et al, 1998). It is not clear if this difference is real or if it simply reflects the different size-separation methodologies used in these studies. In contrast, strong Pb-complexing organic ligands often are predominantly colloidal in these environments (MuUer, 1996,1998; Wells etal, 1998). These findings contribute to the view that the marine colloidal phase is not a uniform substrate for metal associations (Wells et al, 2000). There is some question, though, whether the soluble ligand model is appropriate for colloidal ligand sites. Muller (1998) found that Pb bound to colloidal matter was not in a state of dynamic equilibrium with the solution phase and that "occupied" and "unoccupied" colloidal ligand sites were not equivalent. In other words, Pb association and dissociation kinetics were different when reacting with colloidal matter compared to soluble ligand complexes. Muller suggested that this situation developed with aging of marine colloids in the water column (Muller, 1998). Sunda and Huntsman (1991) showed that a major fraction of "dissolved" Cu in Narragansett Bay surface waters was not released after acidification to pH 2.0 for 19 days but was released 2-8 months later. UV oxidation eliminated this delay, indicating that the organically complexed Cu was not in dynamic equilibrium with the solution phase. The distribution of these kinetically inert complexes closely followed the distribution of colloidal Cu (Wells et al, 2000), indicating that the kinetically inert Cu was bound in colloidal complexes. Slow kinetics of equilibration could arise if soluble metal-complexing ligand molecules incorporate into or onto colloidal organic matrices and then become "internalized" by either hydrophobic partitioning or by the continued sorption of new organic matter. In this case the true conditional stability constant (and specificity) of the metal-ligand complex is unchanged but the ability to readily exchange with solution species becomes restricted. In a dissenting voice, Mackey and Zirino (1994) suggested that observations of organic ligands capable of forming highly specific, strong complexes with trace metals were probably artifacts of the voltammetric methods used. They hypothesized instead that strong ligand signatures arise when weak, metal-binding compounds of low and high molecular weights coalesce, entrapping the weakly bound metals within a colloidal organic matrix (the "onion" hypothesis). They argued that the resultant physically restricted exchange between colloidal metals and the electrode surface would appear as a strong complex. They proposed this model based in large part to puzzlement of how strong chelators could be so specific for a given metal, or why metals and their ligand concentrations should be so closely matched in seawater. But biological systems have evolved highly tuned molecular architectures for the specific complexation of individual bioactive metals (e.g., Crumbliss, 1991; Silva and Williams, 1991), and there now is clear evidence that microbes are a direct source of some metal-specific complexing ligands in seawater (see below). In addition, the "onion" hypothesis requires that the "strength" of metal
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complexation increase with increasing ligand size, which is the opposite of what is measured for Cu, Zn, and Cd in Narragansett Bay (Wells et al, 1998). Even so, colloidal Pb was bound more strongly than by soluble ligands in Narragansett Bay (Wells et al, 1998). It may be then that metal-colloid associations in seawater include both strong, highly specific ligands as well as perhaps less specific and weaker ligands that persist due to their internalization within the colloidal matrix. A progressive intemahzation of either ligand could help explain why the lability of colloidal metals might change with time in the water column (MuUer, 1998; Sunda and Huntsman, 1991).
VI. PARTICULATE-BASED ESTIMATES OF COLLOIDAL METAL CONCENTRATIONS The inherent difficulties in determining colloidal metal concentrations in seawater has spawned early attempts to model colloidal metal content based upon the composition of the particulate phase (e.g., Honeyman and Santschi, 1989; Moran and Buesseler, 1993; Moran et al, 1996). In this approach, a first-order approximation of colloid mass is obtained using projected relationships with the measured particulate mass present in seawater (e.g., Q/Cp = 2 (Moran and Moore, 1989) or Cc= 0.7 • log Cp - 2.6 (Honeyman and Santschi, 1989), where Q and Cp are colloid and particulate masses (mg L~^), respectively). Without going into detail here, these equations have been derived to explain the nonlinear inverse log relationship between the dissolved:particulate partition coefficient {K^) and particulate mass (Cp) at high particle mass concentrations (that is, where colloids and particulate matter compete in the sorption of dissolved metals, e.g., Honeyman and Santschi, 1989). Unfortunately, these relationships remain unverified because colloid mass cannot yet be unequivocally determined in seawater. The resultant colloid mass estimates are combined with assumed colloidimetal partition coefficients (^c) to arrive at first-order predictions for colloidal metal concentrations without a priori knowledge of the processes controlling the colloidal organic phase (e.g., Moran etal, 1996). Preliminary comparisons of these estimates with measured colloidal metal concentrations have not yielded close agreement (Wells et al, 2000), although very few data so far are available for this assessment. There are reasons to expect that bulk methods, while attractive from a methodological approach, will not provide accurate predictions of colloidal metal concentrations anytime in the near future. In addition to the need for stricter characterization of the mechanistic bases underlying any relationship between the particulate and colloidal phases, the selection of values for Kc remains problematic. While it has been generally assumed that A^c ^ ^d for bioactive metals (as appears to be the case for Th (Guo and Santschi, 1997)), measurement of highly specific metal complexation by colloidal matter (e.g., MuUer, 1996; Wells, 1998) would suggest
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that ^ c » ^ d , , assuming that ^d is controlled largely by nonspecific sorption reactions. While this may be true for nearshore waters (Wen et al, 1999), where the particulate phase can be heavily influenced by mineralogical fragments, it may not be as true for offshore seawaters, where living biomass and nonliving cellular fragments comprise much of the particulate phase. In that case, organic particulate matter likely contains remnant (or still functioning) highly specific metal transport sites having high conditional stabiHty constants for bioactive metals. If so, ^d might be expected to vary significantly among water masses, complicating the straightforward application of bulk methods for estimating colloidal metal concentrations. It remains to be seen how effective a sentinel the particulate phase will be for marine colloidal matter.
VII. SOURCES OF METAL-COMPLEXING COLLOIDAL LIGANDS The direct source of strong complexing ligands that control metal speciation in seawater is not well understood. There is clear evidence that Cu-complexing organic ligands can be released by living prokaryotic and eukaryotic phytoplankton in response to Cu stress (Croot et al, 2000; Gonzalez-Davila et al, 1995; Leal et al, 1999; Lombardi and Vieira, 1999; Moffett and Brand, 1995; Maldonado et al, in press). Heterotrophic marine bacteria and fungii also have this capability (Schreiber et al, 1990; Sunda and Gessner, 1989). A handful of marine prokaryotes now are known to release siderophore (Fe-complexing) molecules having conditional stability constants that match the stronger of the two Fe ligand classes measured in seawater (Lewis et al, 1995, Rue and Bruland, unpublished, Rue and Trick, unpublished; Reid and Butler, 1991; Reid et a/., 1993). The direct source of organic chelators specific for other bioactive metals (e.g., Ni, Zn, Co, Cd) remains unknown. Some metal-ligand complexes could be byproducts of intracellular metal detoxification mechanisms (Huges and Poole, 1989; Olafson et al, 1988), although this source likely could be significant only in estuarine and coastal regions impacted by high metal availabilities. It is very unHkely that colloidal ligands are released directly by microbes. The upper size for transport of molecules by bacteria is ~700 Da, although hydrodynamic volume of the molecule is more relevant (Payne, 1980). For example, most siderophore molecules are well below this threshold (Crumbliss, 1991). There is no reason to suspect that the capabilities of marine phytoplankton would be any different. While these actively released compounds presumably are hydrophilic, and thus water soluble, it is conceivable that they could become incorporated into the marine colloidal phase without loss of their metal-complexing functionality. If colloidal metal-specific complexing ligands indeed are sequestered from the soluble phase, then this incorporation should be strongly influenced by the
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character of the colloidal matrix. MuUer (1998) showed that the fraction of strong Cu-binding ligands associated with the colloidal phase increased approximately hnearly with increasing colloid charge density; that is, colloids having low charge densities contained less of the strong Cu chelators. In addition to in situ formation, colloidal metal-complexing ligands may also represent recycled components of cellular metaboUsm (e.g., Koike et al, 1990; Stramski et al, 1992). Inputs related to cell lysis, protozoan excretion, sloppy feeding by grazers, and viral infection all are suspected at this time. For example, molecules of the weaker Fe ligand class in seawater have conditional stability constants similar to the porphyrin complexes (tetrapyroles) that are the most abundant Fe chelators in cellular metaboUsm (Hutchins et al, 1999). A number of metalrequiring metabolites within cells are membrane-bound and so might be expected to appear at least initially associated with higher molecular weight matter upon recycUng. Ja'iry et al. (1999) found the colloidal proportion of Cu increased during a phytoplankton bloom in the river Mame, and similar increased colloidal fractions of bioactive metals have been measured for blooms in upwelling regions (Wells, unpublished data). The breakdown of biogenic detrital particulates might also release metal complexing colloidal phases (Smith etai, 1992). Alternatively, inputs of colloidal ligands from terrestrial and lacustrine sources may be significant in localized regions, as indicated for Pb-binding ligands in the Firth of Clyde (MuUer, 1998).
VIII. MEASUREMENT OF COLLOID REACTION RATES The kinetics of colloid-colloid and coUoid-particulate interactions are likely to strongly influence the residence time of colloidal organic matter in seawater. Based on the findings from estuarine environments, it had been expected that aggregation would be the major fate of marine colloidal matter. Certainly, there is evidence of colloid aggregation in surface and deep ocean waters from transmission electron microscopy (Leppard et al, 1997; Wells and Goldberg, 1993). Two broad morphologies of (globular) colloid aggregates observed at different sites indicate that both very rapid (diffusion-limited) and slower (reaction-limited) aggregation regimes can occur (Wells and Goldberg, 1993). Rapid aggregation, characterized by open, tenuous aggregate architectures (Lin et al, 1989), was only observed in surface waters at primarily nearshore sites (Wells and Goldberg, 1993). Induction of very rapid colloid aggregation is believed to be a critical precursor for formation of marine snow (e.g., Kepkay, 1994; Mopper et al, 1995; Passow and Aldredge, 1995;Passow^ra/., 1994). What effect do these colloid processes have on the transport and fate of trace metals? ^^"^Th has been used widely as a tracer for particle cycling and removal
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Marine Colloids and Trace Metals Dissolved
Particulate
Colloidal
10K-0.2}im
-
xi
^h
>0.2 urn
4
p Th 1
Figure 4 The three-box scavenging model used by Moran and Buesseler (1992, 1993) to calculate the residence times of ^^^Th. in the dissolved, colloidal, and particulate size classes. The variables /th, Cth, and Pth, are the net removal rates of ^^'^Th from the various size classes and X is the ^^"^Th decay constant. In this simplified approach, the processes of ^^"^Th desorption from particulates and colloids and microbial degradation are not considered. Reprinted with permission from Moran and Buesseler (1993).
from surface waters (e.g., Bacon and Anderson, 1982; Coale and Bruland, 1985; Honeyman etal, 1988). Its high affinity for interfaces, short half-Hfe (24 days) and natural in situ radiogenic source (^^^U) make it an excellent tracer for quantifying rates of particle cycling over time scales up to 100 days, which spans that of planktonic processes operating in oceanic systems. These attributes made ^^^Th an ideal starting point for the study of metal scavenging by colloid aggregation in seawater systems (Honeyman and Santschi, 1989). The proportion of dissolved ^^"^Th that is colloidal ranges from 2 to 16% in shelf waters off New England (10 kDa; Moran and Buesseler, 1993), 1 to 47% in surface waters of the Gulf of Maine (1 kDa; Greenamoyer and Moran, 1997), 12% in the northeast Pacific Ocean (10 kDa; Huh and Prahl, 1995), '^10% in the Sargasso Sea (10 kDa; Moran and Buesseler, 1992), and 10 to 78% in the Gulf of Mexico (10 kDa; Baskaran et al, 1992). In most cases, these studies used a three-box scavenging model to estimate the residence times of ^^^Th in the soluble, colloidal and particulate size fractions and then extrapolate to calculate colloid turnover (Fig. 4). By these estimates colloid residence times are on the order of a few hours in nearshore waters and only slightly longer in offshore environments (Baskaran et al, 1992; Moran and Buesseler, 1992,1993). In comparison, residence times for soluble ^^"^Th species ranged from several days to weeks in coastal and offshore waters, respectively (Moran and Buesseler, 1993). Such rapid turnover of colloidal matter implies that colloid cycling could substantially influence the transport and fate of metals even if only a few percent of dissolved metals became associated with the colloidal phase. However, there are several major assumptions in the simplified models used to estimate colloid turnover times. First, the models require a steady-state distribution of tracer among the soluble, colloidal, and particulate size classes, so the effects of changing phytoplankton production on colloid cycling rates cannot be examined
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(e.g., Niven et at., 1995). Second, Th sorption to the colloidal phase is assumed to be irreversible; a condition that is oversimplified for particulate matter (Bacon and Anderson, 1982). Third, these models do not consider direct sorption of soluble ^^"^Th to the particulate phase, making colloid aggregation the only means for transferring Th from the soluble to particulate phase. Improved modeling efforts now account for the direct sorption to particulates and desorption from both particulates and colloidal matter but other necessary parameterizations are still missing (see Burd et al, 2000). A major shortcoming of the ^^"^Th-based colloid cycling models to date is that microbial degradation is not considered. Microbial activity on particulates could release colloidal matter that, in turn, might be degraded to soluble molecules (e.g., Karl et al, 1988; Smith et at., 1992); each step transferring sorbed ^^^Th to smaller size classes. For example, Amon and Benner (1996) showed that while bacterial growth efficiencies on soluble organic matter were consistently higher than sustained by colloidal matter, the utilization rates of colloidal carbon were up to 4x greater. They suggested that the colloidal organic phase is more bioreactive and less diagenetically altered than the bulk of soluble organic matter. This view is supported by carbon isotopic evidence that the colloidal carbon pool as a whole is more recent than the soluble organic phase (Santschi et al., 1995). Benner et al (1997) used extensive data of size-fractionated carbon and nitrogen from the Pacific and Atlantic oceans to argue the "upward" movement of colloidal material into large particulates is less significant than the "downward" size shift from degradation (see Benner, Chapter 3). Metals bound strongly to colloidal ligands, or colloid-associated ligands, presumably also could follow this pathway. A significant degradation pathway is not entirely at odds with ^^"^Th-based modeling of colloid transport. For example, it is feasible that colloidal ^^"^Th could be tracing the decomposition of large biogenic matter; that is, the particle cycling models may be operating in reverse (Moran and Buesseler, 1993). As a further complication, ^^^Th also may not trace bulk colloidal carbon but rather only specific carbon components. Niven et al. (1995) used results from a coastal phytoplankton bloom to argue that ^^^Th associates primarily with the polymer exudates of living phytoplankton, substrates that are thought to be essential precursors for the formation of marine snow (Mopper et al, 1995; Passow and Aldredge, 1995). Because it is unlikely that these carbohydrate polyelectrolytes will form highly stable, metal-specific complexes, ^^"^Th cycling (in either direction) may not be very useful for assessing colloid effects on bioactive metals (Wells et al, 2000). Wen et al. (1997) measured the uptake of ^^Fe, ^^Mn, ^^Zn, ^^Co, ^^^Cd, ^^^Sn, ^^^Ag, and ^^^Ba associated with natural colloidal matter by particulates in estuarine waters of Galveston Bay (5 = 22). They observed two distinct reaction scales, a fast transfer during the first few hours followed by a slower reaction over subsequent days. They suggested that the fast reaction was consistent with a
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r- 4 nm
100
150
250
Time(h) Figure 5 Polymer gel size in seawater as a function of time after conventional filtration (<0.2 /xm). The hydrodynamic diameter of assembling gels was measured by dynamic light scattering (filled circles, solid line) and by flow cytometry (empty squares, dashed line). Poisoning the seawater with 0.02% sodium azide did not alter the outcome of the assembly process (empty circles). A control experiment, where 10 mM EDTA was added to chelate Ca^+ and Mg^+ showed inhibition of polymer assembly (empty triangles), giving an average size of 1-2.5 nm. This inhibition of polymer assembly suggests that aggregates formed by salt bridging among the constituent polymers. Reprinted with permission from Chin ^r a/. (1998).
colloid (Brownian) "pumping" mechanism (Farley and Morel, 1986; Honeyman and Santschi, 1989), while the slower transfer involved trace (colloidal) organic constituents with ligand groups having different trace metal affinities. This view requires the colloidal phase to be nonhomogeneous with respect to metal content, which is supported by later findings (Wells et al, 1998, 2000). Recent evidence adds strong support to the hypothesis that colloid aggregation is prevalent and rapid in ocean waters. Chin et al. (1998) used dynamic light scattering to show that aggregation of soluble and colloidal organic matter quickly forms particulates several micrometers in size once the ambient particulates are removed by conventional filtration (Fig. 5). They went on to demonstrate that these molecule associations were stabilized by salt bridges, as evidenced by aggregate disintegration upon the addition of EDTA to bind Ca^"^ and Mg^+ ions. The pHinduced phase transitions of these particulates were consistent with the tangled network theory of polymer gel formation (Edwards, 1986), indicating that these aggregates were in true equilibrium with soluble and colloidal-sized polymers. If so, thesefindingsturn previous concepts of marine colloid aggregation upside down (Wells, 1998). Rather than colloid aggregation being driven by instability of the
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colloidal phase, it instead would be controlled by an equilibrium-based relationship with particulate gels. Aggregation kinetics then would be a direct function of the rate that particulate gels are lost from surface waters via sinking or perhaps microbial degradation, as indicated by the reformation of microgels after repeated filtrations (Chin et al, 1998). The particulate and colloidal gel phase would remain in pseudo-steady state as long as gel precursors were present in (or added to) the soluble phase. This process will complicate efforts to establish whether the release of organic matter by actively growing phytoplankton assemblages directly alters the dynamics of colloidal trace metal cycling in surface waters (e.g., Kuma et al, 2000; Wells ^r a/., 2000). If microgels formed by this process are more readily intercepted and utilized by heterotrophic bacteria (e.g., Johnson and Kepkay, 1992; Kepkay, 1994; Kepkay and Johnson, 1988), then tangled network theory of polymer gels may provide a novel mechanistic insight to how marine microbes degrade organic matter. By degrading particulate endmembers efficiently, bacteria might facilitate the consumption of reactive soluble and colloidal organic counterparts by drawing these constituents into the particulate phase (Fig. 6). If metal-complexing organic molecules also are incorporated during gel formation, and a significant fraction of these particulate gels are removed by sinking and grazing, then microbial degradation of particulates ironically could indirectly enhance the removal of dissolved bioactive metals from surface waters, which is counter to present expectations.
Geifbrmation
Ca**v "Mg*
Soluble
^
Particulate Microbial degradation
Figure 6 Schematic of the dynamic interplay between marine gel formation via colloid aggregation and the microbial degradation of particulate gels. Thickness of the arrows depicts the expected relative reaction rates. According to polymer gel theory, the particulate gel phase is in equilibrium with the low-molecular-weight gel constituents, so that removal of particulate gels by sinking or microbial degradation results in further aggregation. Reprinted with permission from Wells (1998).
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IX. THE BIOLOGICAL AVAILABILITY OF COLLOIDAL BIOACTIVE METALS A key but largely unanswered question is how metal-colloid associations affect the availability of bioactive metals to prokaryotic and eukaryotic microbes. In most cases, metal uptake by phytoplankton is a function of the free metal ion activity in solution (e.g., Sunda and Guillard, 1976). Complexation by soluble (or colloidal) metal chelators therefore decreases metal availability, in some cases lowering it to levels optimal for organism growth (Sunda and Huntsman, 1995b). (The chemical speciation constraints for Fe (and Co) uptake are considerably more involved; see Nolan etal (1992) and Wells etal (1995).) This complexation also serves to buffer metal ion activity, so that metal is released to the ionic pool in response to biological uptake (Huntsman and Sunda, 1980). It also is expected that complexation slows the rate of metal loss from surface waters by limiting the direct sorption of metals to sinking particulates (Honeyman and Santschi, 1989; Jannasch et al, 1996) (but see above). We now know that some portion of these highly specific, strong chelators of bioactive metals occur in marine colloidal matter (Muller, 1996,1998; Wells et al, 1998). Presumably these colloidal ligands also modulate free metal ion activities and thus influence the availability of bioactive metals (but see Mackey and Zirino, 1994). Wang and Guo (2000) found that addition of marine colloidal matter to cultures of a diatom and dinoflagellate decreased Zn uptake but increased apparent Cr uptake. However, cell surfaces were not washed to remove extracellular metals (e.g., Hudson and Morel, 1989) so it is uncertain whether the enhanced Cr uptake was due to metal assimilation or metal sorption. Nonetheless, decreased Zn uptake is consistent with colloidal complexation of free Zn^"^and the subsequent buffering of its subsequent availability. Nishioka and Takeda (2000) found that the growth of an oceanic Chaetoceros sp. appeared to be fueled by colloidal Fe rather than soluble Fe species in cultures using nutrient-amended offshore seawater. But it is uncertain whether this colloidal Fe existed as colloidal-sized organic complexes or as reactive Fe(III) oxyhydroxides, which can readily dissolve to resupply soluble chemical species taken up by phytoplankton (Rich and Morel, 1990; Wells et al, 1983). While it is unlilkely that phytoplankton and heterotrophic bacteria can take up colloidal matter directly (but see Maranger et al, 1998), the colloidal phase still might be an important direct source of metals to heterotrophic flagellates (Barbeau and Moffet, 2000; Tranvik et al, 1993) and filter-feeding tunicates (Flood et al, 1992) and bivalves (e.g., Roditi et al, 2000, Goldberg and Wells, unpublished data). Much more work is needed before the significance of the colloidal pathway for metal assimilation by animals can be assessed. If the immediate fate of colloidal matrices is microbial degradation, then the associated metals would be recycled to the soluble phase, either as free ions or
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in liberated ligand complexes. The net result would be that colloidal processes act to retain bioactive metals in solution by slowing their sorption to sinking particulates. However, if the metal ligand complexes instead are associated with colloidal constituents that rapidly aggregate, the marine colloidal phase may act to strip bioactive metals from surface waters. The effect of marine colloidal matter on metal availability thus depends upon the balance struck between these opposing fates. The nature of this balance will depend upon the type and quantity of organic matter released by phytoplankton that, in return, may be controlled by nutrient availability and the character of the algal assemblage. It is likely then that the fate of colloidal metals will shift in response to seasonal and short-term episodic perturbations in the biogeochemical cycle.
X. SUMMARY The marine colloidal phase is a major component of DOC in the oceans and contains with it a wide range of metals that affect the growth of marine phytoplankton. Given that this association will alter the biological availability of dissolved metals, colloid-metal interactions almost certainly influence biological production and thus the generation of COC. Advances over the past decade have established this bidirectional coupling but details of the cycling remain obscure. For example, while the ultimate source of COC is marine phytoplankton, it is unclear whether discrete colloidal particles arise primarily from aggregation of soluble organic constituents or by direct release from degradation of living and detrital matter. While the past 10 years has seen a sharp increase in the study of colloidal metals in nearshore and estuarine waters, there have been far fewer studies in the open ocean where the bulk of carbon fixation occurs. Our ability to study the marine colloidal phase has been challenged over the past decade by the limited number of methods available to isolate marine colloids from soluble constituents, and by a lack of consensus over how the colloidal phase should be defined. Recently, novel techniques have been applied to study colloid composition and the kinetics of colloid cycling, and these will undoubtedly attract considerable interest over the next decade. Despite these difficulties, a picture is emerging of the distribution and significance of marine colloids with respect to bioactive (nutrient) metals as well as other geochemically important elements. These colloidal metal associations can be attributed in large part to specific and strong metal complexation rather than nonspecific metal sorption to the bulk colloid interface. This specificity greatly complicates efforts to generate meaningful generalizations and predictions of the colloidal metal contents of different seawaters. Early indications are that globalscale processes such as aerosol transport can influence the concentrations and metal composition of the marine colloidal phase, not by direct deposition but indirectly
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by influencing the biological processes that produce and maintain the pool of marine colloidal organic matter. Perhaps the single greatest unresolved issue is deciphering the predominant fate of marine colloidal matter and its associated metals: aggregation to larger particle sizes, microbial degradation to soluble constituents, or both, depending on the variable influence of other factors. Given the anticipated short residence time of marine colloids in surface waters with respect to either degradation or aggregation, the processes responsible for the outcome almost certainly are highly dynamic. With respect to trace metals, the central challenge facing scientists over the next decade will be to ascertain whether the marine colloidal phase serves primarily to buffer bioactive metals, helping to retain them in surface waters, or instead hastens metal removal from surface waters, thus negatively impacting the marine phytoplankton community.
ACKNOWLEDGMENTS I particularly express my sincere thanks to Ed Goldberg, who rekindled my interest in the marine colloidal phase and has generously provided his guidance and advice to me over the years. I also thank John Hedges, Minhan Dai, and an anonymous reviewer for their helpful suggestions and comments that improved an earlier version of this chapter. This work was supported by NSF Grants OCE-9617719 and OPP-9725345 and ONR Grant NOOO14-00-0304.
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Chapter 8
Carbon Isotopic Composition of DOM James E. Bauer School of Marine Science College of William and Mary Gloucester Point, Virginia
I. Introduction II. Conventions and Definitions for Expressing Isotopic Contents of DOC A. Carbon-13 B. Carbon-14 III. Methods for Extracting DOC from Seawater for Isotopic Analysis A. Sample Processing B. Sample Oxidation IV. Measurements and Distributions of 6^^C and A^^C in Marine DOC A. Distributions of 5l^C and A^4(of DOC in Oceanic Systems
B. Distributions of S^^C and A^^c of DOC in Ocean Margins V. Applications of ^^^C and A^^C in Marine DOC Cycling Studies A. Vertical Mixing and Distribution of A^^C-DOC in the Open Ocean B. Distributions of^i^C and Ai^c of DOC in Ocean Margins C. Sources and Inputs of UDOC to Ocean Margins D. Exchanges of DOC between the Ocean's Margins and Its Interior VI. Summary and Future Challenges References
I. INTRODUCTION The sources, turnover, and fates of dissolved organic carbon (DOC) in the oceans have been studied by a number of techniques and approaches, using both direct measurements and inferred assessments and modeling. Foremost among Biogeochemistty of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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the direct measurement techniques is the use of (a) molecular "fingerprinting," or organic biomarker compound analyses, and (b) natural carbon isotopic measurements. Each of these approaches has specific advantages and disadvantages for its application to studies of DOC biogeochemistry, and yields unique information about the distributions and cycling of both "bulk" (i.e., total) DOC and its constituent organic fractions. Organic biomarkers can be highly sensitive with respect to identifying the contributions of both general sources (e.g., marine vs terrestrial organic matter) as well as specific organisms (e.g., different genera and species of primary and secondary producers) to various organic carbon pools (Killops and Killops, 1993; Wakeham and Lee, 1993), including DOC (Benner, Chapter 3). However, organic compounds may undergo structural modification due to bacterial and photochemical degradation and as a result can rapidly lose their structural specificity (see, for example Moran et al, 1991; Opsahl and Benner, 1998; and Opsahl and Zepp, 2001). In addition, "identifiable" biomarker compound classes and specific compounds typically represent only a small proportion (generally no more than -20-25%) of the total DOC pool (WiUiams and Druffel, 1988; Benner et al, 1992a; Benner, Chapter 3) and as such may or may not be representative of the cycling of the "average" bulk or total pool. The natural isotopes of carbon in DOC provide information that is at once complimentary to and unique from organic biomarker analyses. The use of natural ^"^C and ^^C in DOC, or any other form of organic matter (e.g., particulate organic carbon, or POC), generally provides a lower degree of "specificity" with respect to biological sources than do organic biomarkers. However, carbon isotopic measurements can provide integrated information on the sources, cycling, and turnover times of the average, bulk DOC pool (Williams etal, 1969; Broecker and Peng, 1982; Druffel etal, 1992; Hedges, 1992; Trumbore and Druffel, 1995). In addition, and as a general rule, carbon isotopic signatures of DOC tend to be less affected by degradation and structural modification processes than organic biomarkers (Ostrom and Fry, 1993). As an organic solute, DOC would be predicted to behave nonconservatively over large enough spatial and temporal regimes due to both biotic (e.g., production and consumption) and abiotic (e.g., sorptive/desorptive processes, photochemical oxidation) processes. Indeed, this appears to be the case on global ocean, as well as smaller, scales. Hansell and Carlson (1998) have demonstrated the existence of DOC concentration decreases (—14 /xM) in deep ocean waters along the path of mean deep-water flow (Broecker, 1991). The major conclusion of these findings is that on time scales of deep-water circulation, DOC must be removed by bacterial remineralization, sorption and other biotic and abiotic processes (Stuiver et al, 1983). Earlier attempts to show that deep ocean DOC is nonconservative were made by Craig (1971a) and Craig (1971b) using vertical eddy-diffusion models to evaluate observed oxygen and DOC profiles. The higher concentrations of DOC in nearly all surface ocean waters (the exception to this being vertically destratified conditions) indicate that oceanic DOC has
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its origins in surface ocean primary and secondary production (Hellebust, 1965; Cole et al, 1982; Fogg, 1983; Lancelot, 1984). Yet microbiological investigations have shown that while some of this recently produced DOC is labile over short (days to months) time scales, much of it also becomes refractory to bacterial remineralization over similar time scales (Ogura, 1972; Williams and Yentsch, 1976; Kirchman et al, 1991; Carlson et al, 1994; Cherrier et al, 1996; Carlson, Chapter 4). This is presumably a result of bacterial and photochemical modification of the parent molecules (Zafiriou et al, 1984; Brophy and Carlson, 1989; Miller and Moran, 1997; Ogawa et al, 2001, Mopper and Kieber, Chapter 9). While concentration data alone is useful in this respect, the information provided by natural ^"^C and ^^C measurements can enhance our understanding of the inputs, fates, and conservative vs nonconservative aging of DOC in the open ocean. In this review and synthesis, we will: — assemble the existing global datasets on natural ^^C and ^^C in DOC (including organic component fractions of DOC) both in the open ocean and in ocean margins; — evaluate the application of ^^C as a source tracer and ^"^C as both an age and a source tracer for DOC; and — critically assess the use of ^"^C and ^^C in mass-balance mixing models for describing the vertical and horizontal distributions of these isotopes in DOC in the open and coastal oceans.
11. CONVENTIONS AND DEFINITIONS FOR EXPRESSING ISOTOPIC CONTENTS OF DOC A. CARBON-13 The naturally occurring isotopes of carbon can provide us with several basic kinds of information on seawater DOC specifically and on dissolved organic matter in general. The average natural abundances of the most commonly applied isotopes of carbon, ^^C, ^^C, and ^^C, in various earth reservoirs are approximately 98.89, 1.11, and 10-1°%, respectively (Fritz and Pontes, 1980; Goh, 1991a). Geochemists and biogeochemists are as a rule most familiar with the use of ^^C as a tracer of carbon sources and isotopic fractionation effects. The use of ^^C for such applications was pioneered by Craig (1953). The most common convention for expressing the natural ^^C content of a carbon pool (living or nonliving) is the 6 ("del") convention, where (5 C = [(/^sample/^standard) — 1] X 10
[1]
in %o (per mil), where R = ^^C/^^C, and /^standard is ^^C/^^C of the Pee Dee Belemnite (PDB) standard, or of a secondary standard relative to the PDB. The ^-^C/^^C of
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both natural materials and standards is accomplished through isotope ratio mass spectrometry (for detailed information and references, see Hayes et al, 1978; Hayes, 1983; Boutton, 1991a). The 5^^C signature of marine organic matter is initially set during the photosynthetic fixation of CO2 or bicarbonate by phytoplankton (Sackett, 1989; Boutton, 1991b; Lajtha and Marshall, 1994; Michener and Schell, 1994). This fixation involves fractionations of ^^C (as well as of ^"^C; see Section II.B, below) relative to ^^C at the enzymatic level of ribulose bisphosphate (RuBP) carboxylase that cause reduced organic compounds to be depleted in the two heavier isotopes relative to ^^C (O'Leary, 1981, 1988). Numerous factors have been identified as controlling the degree of isotopic fractionation during inorganic carbon fixation by phytoplankton in seawater, including temperature (Degens et al, 1968; Rau et al, 1982), CO2 partial pressure (Rau et al, 1991, 1992), and phytoplankton community structure (Falkowski, 1991). The fractionation effect of heterotrophic degradation on organic matter is considerably less (~l%o or less for ^^C; Shaffer et al, 1999) and therefore must be correspondingly less for ^"^C (i.e., twice that for ^^C, or ^27oo—see Section II.B, below) than the effects of inorganic carbon fixation. Also like ^"^C (Section II.B), the impact of human activity on ^^C in the surface ocean has been significant and measurable, with the 5^-^ C of surface ocean Die becoming progressively lower as a result of the uptake of ^^C-depleted CO2 derived from fossil fuel burning (Quay et al, 1992; Bacastow et al, 1996). This ^^C depletion must also be manifested in both the DOC and POC derived from phytoplankton carbon, but this factor, and its relevance over different spatial and temporal scales, has not been considered routinely in studies of ocean organic carbon cycHng. The 5^^C signatures of organic matter have traditionally been used to identify sources of carbon and their respective contributions (both relative and absolute) to a given pool or reservoir of organic matter using simple two- or three-end-member mass balance calculations (e.g., see Gearing, 1991; and Ostrom and Fry, 1993; Michener and Schell, 1994, and references therein). This can be achieved only if the 5^^C signatures of the likely sources are (a) sufficiently different from each other and (b) reasonably well constrained for each individual source. In open ocean and most coastal environments, there is often enough overlap and variability in 5^^C within and between discrete general sources (e.g., marine phytoplankton) of organic matter to a given pool, as to make 5^^C-based quantitative estimates of the source contributions to the bulk DOC pool variable or even ambiguous within these systems. Typical 5^^C values for fully marine (i.e., that removed from significant riverine and terrestrial inputs) bulk organic matter (5^^COM» including both DOC and particulate organic carbon, POC) are relatively narrow, spanning a range of perhaps only approximately 10%o (5^^COM ^ - 2 8 to -18%^; Sackett, 1989; Boutton, 1991b; Michener and Schell, 1994) across equatorial, temperate, and polar ocean waters. If lower temperature polar latitude waters are excluded, where
Carbon Isotopic Composition of DOM
409
relatively low 5 ^^CQM values are often observed because of greater photosynthetic CO2 fractionation effects resulting from increased PCO2 (aq) (Rau et al., 1991, 1992), the operational range of (5^^C values for marine bulk organic matter is even more restricted to perhaps as little as ~4-5%o (S^^CQM ^ —23 to —lS%o). As a result, the use of 8^^C for discerning contributions of different forms of marine organic matter is quite limited, due to the relatively high degree of similarity in 5 ^^C of all forms of organic matter produced authochthonously. However, in temperate coastal regions, for example, inputs of terrestrial organic matter to marine waters may allow 5 ^^C to be used more effectively than fully marine waters, due to the generally lower values observed in riverine and terrestrial organic matter ((5^^C ~—30 to —25%o for organic matter produced by terrestrial and riverine C3 plants; Boutton, 1991b; Michener and Schell, 1994) compared to marine organic matter. Overall, however, the relatively narrow dynamic range in (5^^C of bulk DOC and POC in oceanic and coastal waters, and the concomitant high degree of overlap in 5^^C values of both marine and terrestrial sources of bulk organic matter, limit the use of natural abundance ^^C for evaluating—especially in any quantitative sense—sources and transformations of bulk dissolved and particulate organic matter in marine waters. Nonetheless, biogeochemists continue to rely on S^^C in DOC and POC as evidence of their sources in both fully marine as well as coastal waters. Finer-scale identification of the 5^^C values of different potential marine sources (for example, different phytoplankton and zooplankton species, DOC released from healthy vs dead phytoplankton or from "sloppy feeding") to the bulk DOC pool may provide a greater degree of differentiation of the contributions from sources within marine systems.
B. CARBON-14 Conventions for expressing the natural ^"^C content of a carbon pool have changed over the past 10-20 years as a result of changing technologies for the measurement of natural levels of radiocarbon. Historically, natural ^"^C was measured using decay counting of )S particles released during the radioactive decay of ^"^C to ^"^N (Suess, 1954; Goh, 1991a). Although this technique is still used today, its application in the earth and natural sciences is significantly more limited than in the past as a result of (1) the relatively large sample sizes needed (often grams of carbon), (2) the extremely long analysis times (up to days) required for decay counting of a single sample, and (3) the advent of accelerator mass spectrometry (AMS; see reviews by Elmore and Phillips, 1987; and Vogel et al, 1995). In contrast to decay counting, AMS is a direct particle counting technique for measuring the ratio of ^^CI^^C of carbon-containing samples, and requires much smaller sample sizes (as low as 20-100 /xg C) and analysis times (as short as minutes). As a result of AMS technology, the number of natural ^^C analyses being carried out
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James E. Bauer
today has risen dramatically compared to even a decade ago, and the vast majority of analyses of natural ^"^C in all forms of marine organic matter are nowadays performed by AMS. For oceanographic and other geochemical reservoirs of carbon, ^^C content is expressed as (Stuiver and Polach, 1977) A^^C = 8^^C - 2(8^^C + 25.0)(1 + (^^'^C x 10'^))
[2]
in %o (per mil), where ^^'^C is analogous to 8^^C above, except that R = ^"^C/^^C, and the standard is oxalic acid (Stuiver and Polach, 1977;Goh, 1991a). A^'^Cisalso defined as "the %o deviation from the ^"^C activity of 19^*^ century wood" from decay counting, and as a result Eq. [1] contains a correction for isotopic fractionation effects. Theoretical considerations also dictate that ^"^C will fractionate at twice the rate of ^^C due to its higher atomic mass (Stuiver and Polach, 1977). For ease of data reporting, natural A^'^C values are always corrected for fractionation on the basis of the corresponding 8^^C value of a sample (Stuiver and Polach, 1977; Goh, 1991a). The radiocarbon-based equivalent age of carbon-containing materials can also be estimated directly from A^'^C as: ^^C age (in years B.P.) = 8033 In [(1 + (A^^C x lO"^)]"^
[3]
As can be seen from Eq. [3], there is a natural logarithmic relationship between A^'^C and ^"^C age resulting from radioactive decay of ^'^C. Assuming negUgible input and loss rates of carbon from a particular reservoir, we can therefore estimate the mean age of that reservoir, or the mean time elapsed since that reservoir was formed or deposited. However, because geochemical reservoirs (especially of organic matter) are rarely, if ever, static, this assumption is not expected to be valid in the majority of cases, and we must be aware of the complicating factors introduced by either steady-state or non-steady-state inputs of carbon of varying ages from different sources. Such factors can make the application of natural radiocarbon as a simple estimator of age considerably more complicated and ambiguous. A number of factors controls the amount of natural ^^C in a defined reservoir of marine organic matter such as DOC (Fig. 1). Natural ^'^C (ti/2 = 5730 it 30 years; Olsson and Kareen, 1963) is produced in the upper atmosphere by cosmic ray spallation of ^"^N (Suess, 1958, 1968), and elemental ^"^C is rapidly converted to ^"^002 (Libby, 1952). The total atmospheric CO2 pool is turned over approximately every 3 years by air-sea gas exchange with the oceans and by terrestrial biomass production (Schlesinger, 1997), and as a result natural atmospheric ^"^C is rapidly incorporated into these reservoirs as well. The production rate of natural ^^C in the atmosphere itself depends on a variety of factors collectively referred to as "secular" changes in ^"^C. These secular variations are largely due to changes in cosmic ray flux to the upper atmosphere, which in turn govern at any given point
Carbon Isotopic Composition of DOM
411
Cosmogenic ^^C Production
Fossil Fuel Dilution
ATMOSPHERE
B o m b 14C
Air-Sea Exchange y^- ^
SURFACE OCEAN Y
Y
y^
Radiodecay
(Half-Life = 5730 yrs)
Y
DEEP OCEAN
Figure 1 Factors controlling the distribution of ^^C in atmospheric and oceanic carbon reservoirs.
in time the inventory of ^"^C in both the atmosphere and the reservoirs with which it exchanges (Suess, 1953, 1968; Stuiver and Quay, 1980). One of the (if not the) most profound effects on the global inventory of ^^C has taken place over the past ~50 years due to thermonuclear weapons testing. Atmospheric testing of weapons in the 1950s and 1960s increased the A^'^C signature of atmospheric CO2 from its prebomb levels of ^—50 to —40%o in the temperate Atlantic and Pacific regions (Broecker et al, 1960; Linick, 1975), to as high as ~+850-900%o by some estimates (Broecker and Peng, 1982; Nydal and Lovseth, 1983; Broecker et al, 1985; Ostlund et al, 1987; Ostlund and Rooth, 1990; Goh, 1991b; Broecker et al, 1996; Levin and Kromer, 1997) (Fig. 2). This "bomb" ^^C infiltrated various exchangeable global carbon reservoirs, thus providing a transient tracer which has been invaluable for assessing both physical and biogeochemical oceanographic processes occurring on decadal time scales (Siegenthaler, 1989; Broecker and Peng, 1982; Toggweiler, 1990). The magnitude of the bomb spike on oceanic carbon pools was dampened significantly over atmospheric levels due to mixing and dilution of bomb ^^C with non-bomb
James E. Bauer
412
1000 H 800 H
vatmospheric CO.
600 A
u
400 i 200 A 0 -^
temperate surface ocean DIC
-200 H
1950
1960
1970
1980
1990
2000
YEAR Figure 2 The ^"^C ("bomb") transient in northern hemisphere atmospheric CO2 and surface seawater dissolved inorganic carbon (DIC) resulting from thermonuclear weapons testing.
dissolved inorganic carbon (DIC), which elevated the A^'^C signature of the DIC pool to only ~+200%o at the height of weapons testing in the 1960s (Fig. 2). Thus, prior to thermonuclear weapons testing, the production of organic matter by primary and secondary producers in the euphotic zone of the oceans would be expected to be considerably lower in ^"^C (A^'^C < —50%o) than that produced during and after weapons testing (A^'^C > ^—50%o, but <'^+200%o). Both the living and non-living organic matter produced at different times in the upper ocean will therefore reflect the ^"^C content of DIC at the time of fixation. Although, as we will see, the ^"^C content of deep ocean DOC in particular is quite low, at present it is impossible to rule out the prospect that this globally significant reservoir does not contain some component of bomb^^C. The same can be said of any oceanic organic matter reservoir that has received inputs since the 1950s. The possibility that old oceanic carbon reservoirs may contain bomb ^"^C complicates the use of ^"^C as a simple, "one-dimensional" time tracer of organic (or inorganic) carbon turnover. If a given reservoir of marine organic matter contains significant amounts of non-surface ocean-derived carbon (for example from continental margins, hydrocarbon seeps, atmospheric transport, and deposition of the by-products of both fossil fuel and terrestrial biomass burning, etc.) or if different sources have "pre-aged" prior to their input to the oceanic reservoirs, the task of deciphering these different contributions to the average A^'^C values or ages of marine DOC and POC may be formidable indeed.
Carbon Isotopic Composition of DOM
413
Provided the A^'^C signatures of potential sources of carbon to any particular reservoir can be adequately constrained (for example, to the oceanic DOC or POC pools), or even assumed to be negligible, ^"^C, like ^^C, can be used as a source tracer of carbon, in addition to providing some measure of the average age of that reservoir. The range in A ^"^C values of natural organic materials contributing potentially to marine reservoirs of DOC and POC is as low as ~—1000%^ (i.e., "dead" or "fossil" carbon, >50,000 years in age) to as high as approximately +200%o (i.e., "modem" carbon, containing bomb ^^C; see above, this section). In contrast to ^^C, the use of ^"^C may be complicated by it having both natural cosmogenic and "bomb" contributions to global geochemical carbon reservoirs (see Fig. 1). In addition to source information, natural ^"^C, due to its radioactive decay, has the further advantage in DOC studies of providing information on the time elapsed since fixation into reduced organic matter. In this respect at least, bomb-produced ^"^C can serve as a short-term (decadal) tracer of time since fixation, compared to the longer term (up to 50,000 years) time scales that are differentiable using cosmogenically produced ^"^C. It is worth noting that even if the A^'^C signatures of DOC or other forms of organic matter are below levels normally imparted by bomb testing, it is not possible to exclude entirely the possibility that trace amounts of bomb ^"^C are still contained in that organic matter. It is only when A^^C signatures of present day living and recently formed nonliving organic matter are fully bomb in nature (see section V, below) that this assessment is essentially unequivocal. In summary, oceanic ^^C can be used as both a long-term (millennial) as well as a short-term (decadal) tracer of carbon sources and ages. If the sources of organic matter to a specific reservoir (in this case, DOC or POC) can be constrained adequately, ^"^C can provide us not only with information on the average age of the material comprising that reservoir, but with at least qualitative, and possibly semiquantitative, information on the relative magnitudes of the sources comprising that reservoir, much in the same way that natural ^^C is used. In fact, ^^C may potentially be a more sensitive source tracer than ^^C in some applications, due to its much greater dynamic range (^1200%^? for ^"^C in different marine settings vs ~10%o for ^^C). Below, we provide examples of how both ^^C and ^-^C can be applied in studies of seawater DOC cycling.
III. METHODS FOR EXTRACTING DOG FROM SEAWATER FOR ISOTOPIG ANALYSIS A. SAMPLE PROCESSING Sample processing for ^"^C and ^^C analysis of seawater DOC is considerably more challenging than for POC (see Raymond and Bauer, 2001a, for review) owing to a variety of factors, including: (a) the very small concentrations of DOC
414
James E. Bauer
in most open ocean and coastal samples and the very high sample volumes that must consequently be processed; (b) the four to five order-of-magnitude greater amounts of total inorganic salts (~36 g L"^) dissolved in seawater compared to DOC (~1 mg L"^); and (c) the choice of method to "extract" the DOC from the aqueous sample. In freshwater environments, the processing of samples for analysis of A^'^C and S^^C of DOC is typically much simpler than in marine waters, because of the relatively higher DOC concentrations and lower salt contents. For freshwater samples, a given volume of DOC-containing water (anywhere from tens of milliliters to liters) can be dried to remove the water (see, for example. Murphy and Davis, 1989; Murphy etai, 1989; Schiff etaL, 1990, 1997; Arevena and Wassenaar, 1993), using methods such as lyophilization and vacuum centrifugation. Although similar "drying" methods have also been used for seawater samples (see, for example, Fry ^/a/., 1993,1996; Peterson ^r a/., 1994), the exceedingly small amount of total DOC relative to total salts makes it more amenable to S^^C analysis than for A^^C analysis, for which hundreds of micrograms of C are necessary. Ultrafiltration (UF), or cross-flow filtration (CFF), has helped to overcome a number of the difficulties noted above, and has proven to be a highly effective tool for organic geochemical and isotopic studies of DOC (see, for example, Bauer et al, 1996; Buesseler et a/., 1996; Benner, 1991, et aU 1992a, 1997; Guo et aly 1996; Guo and Santschi, 1997; Benner, Chapter 3). By using that fraction of the total DOC that has been extracted using UF methods (the so-called colloidal or ultrafiltered DOC [UDOC], typically representing no more than ^^2030% of marine DOC, but as high as 50-60% of freshwater and estuarine DOC using 1-kDa filters; see Benner, Chapter 3; Wells, Chapter 7), the sample may then be desalted and dried to produce a solid powder that can then be subjected to a number of chemical analyses typically used for solid-phase materials such as POC or sedimentary organic matter (e.g., NMR, CHN, GC-MS, HPLC, sealed tube combustion, etc.; see, e.g., Benner, 1991; Santschi etal, 1995; Benner etal, 1991 \ Bianchi et al, 1997; Guo et al, 1996; Guo and Santschi, 1997; McCarthy et al, 1997; Mitra et aL, 2000; Opsahl and Benner, 1997). Prior to the advent of UF, the method of choice for isolating an operationally defined solid-phase component of DOC was the use of cross-linked polystyrene (XAD) resins for collecting the so-called "humic substances" (see, e.g., Aiken etal, 1979; Thurman and Malcolm, 1981; Ertel^ra/., 1986; Hedges er A/., 1986; Meyers-Schulte and Hedges, 1986). The issue of whether either the UF or the humic fractions are representative of the total DOC has long been questioned (Hedges, 1992, McCarthy et al, 1996; Benner et al, 1997). However, without a means of comparing the organic and isotopic characteristics of these fractions (which in the case of UF does not account for the low-molecular-weight DOC; in the case of humic substances, the more hydrophilic component is underrepresented) to the total DOC, this question will remain an open one.
Carbon Isotopic Composition of DOM
415
B. SAMPLE OXIDATION Following the processing of a sample for total DOC or operationally defined component (e.g., UDOC, humics, etc.), the sample must be converted to CO2 for subsequent isotopic analysis. Several different methods have been used to oxidize DOC for ^"^C and ^^C analyses, with varying degrees of success (Table I). For "solidphase DOC" (e.g., desalted and dried UDOC or humic substances), oxidation may be performed in the same way as for POC samples, that is, by flow-through combustion of the sample followed by IRMS for 8^^C analysis, or by discrete sealed tube combustion for A^'^C analysis by AMS, and/or 8^^C analysis by IRMS. The total DOC in a sample may be oxidized using several methods, each of which has its own inherent advantages and disadvantages. These include high-energy UV irradiation (WilHams, 1968; WilHams etal, 1969; WiUiams and Gordon, 1970; Eadie et al, 1978; WiUiams and Druffel, 1987; Bauer et al, 1992a), high-temperature (^500°C) sealed tube oxidation of the lyophilized DOC/salt mixture (Fry et al, 1993; Peterson et al, 1994; Fry et al, 1996), combined UV-persulfate oxidation (Bauer et al, 1991), and high-temperature flow-through oxidation (Bauer et al, 1992a,b; Clercq et al, 1998). Although none of these methods is considered simple or routine, factors such as quantitative oxidation and recovery, system blanks, and sample: blank ratio, must be considered when deciding on the method to employ for a given sample type. It should be restated that the advent of AMS for natural abundance ^"^C measurements has dramatically enhanced the ability of organic and carbon isotope geochemists to analyze small (as small as 20-50 /xg C) samples of DOC and other materials. The state-of-the-art in natural ^^C analyses presently permits individual chromatographically separated compounds to be analyzed by AMS after they have been separated and collected in quantities as small as tens of micrograms C using methods such as preparative capillary gas chromatography (Eglinton et al, 1996, 1997). However, until very recently (Aluwihare, 1999) these compoundspecific ^^C analyses were limited to samples such as marine sediment, from which relatively large amounts (tens to hundreds of micrograms) of individual organic compounds could be extracted.
IV. MEASUREMENTS AND DISTRIBUTIONS OF 6^^C AND A^^C IN MARINE DOC While ^^C has received a great deal of attention in studies of marine organic matter cycling in general (see Sackett, 1989; Boutton, 1991b; and Michener and Schell, 1994, for recent reviews), there have been far fewer measurements of ^^C in seawater DOC and an even smaller number of measurements of natural abundance ^^C in seawater DOC. The primary reasons for this include the significant analytical
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difficulties imposed by extracting adequate quantities of DOC from saline waters for 8^^C and A^'^C analyses (roughly in a ratio of ^ 3 x 10"^: 1, DOC:total salts in seawater) and the much larger sample sizes that have traditionally been required for natural abundance ^"^C measurements. The total number of studies measuring ^^C and ^'^C in seawater DOC and its components is relatively small. However, the overall patterns of ^^C and ^^C distributions within oceanic and coastal systems are generally consistent with presumed DOC source terms, and with the hydrographic and biogeochemical features characteristic of each type of environment. A. DISTRIBUTIONS OF 6^^C AND A ^ ^ C OF DOC IN O C E A N I C SYSTEMS
Thefirstmeasurements of 5 ^^C in marine DOC were carried out in the late 1960s and early 1970s in the eastern North Pacific (Williams et al., 1969; Williams and Gordon, 1970) and the North Atlantic and Gulf of Mexico (Jeffrey, 1969). All of the earliest methods relied on the processing of very large sample volumes (several hundreds of liters) in order to isolate up to gram quantities of material for isotopic and chemical analysis. Of these early studies, the first to perform natural ^^C analyses on DOC was that of Williams et al. (1969) (see below, this section). Following this pioneering work, the next reported measurements of A^^C-DOC would not be made until almost 20 years later. As mentioned above, in oceanic (i.e., noncoastal) systems, the relative similarity and overlap in ranges of (5^^C signatures of potential autochthonous sources of both living and nonliving organic matter (typically only ^4-5%o for both DOC and POC; see reviews by Sackett (1989), Michener and Schell (1994), and Boutton (1991b) and references therein) to the DOC pool limits its potential for distinguishing the relative contributions of these sources. Indeed, the range in 8^^C values of seawater DOC (both bulk and operationally defined fractions) observed for oceanic systems (Table II) is even smaller (<~4%o across all systems studied, and all methods of DOC extraction) than that of its presumed planktonic and nonliving POC sources. Excluding the Gulf of Mexico values in Table II (and which may have been influenced by either methodological uncertainties, or possibly natural hydrocarbon seepage in this region [Macdonald et al, 1993; PauU et al, 1989; Roberts and Carney, 1997]), the range of 5^^C-D0C values within a given study is only l-2%o for total DOC. The range in 8^^C of humic substances from open-ocean environments is slightly greater by ^l%o than total DOC, with lower values being somewhat more prevalent (Table II). It is typically only in more coastal marine environments that 8^^C signatures of different source materials (e.g., from marine, riverine, estuarine, and terrestrial sources) are adequately distinct to make their appHcation to DOC source differentiation robust (see Sections IV.B and V.B and V.C, below). In no case have 8^^C and A^'^C of DOC for open-ocean waters been
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Figure 3 Map showing the three open-ocean stations at which depth profiles of both A ^"^C-DOC and ^i^C-DOC have been estabhshed. Station coordinates are: Sargasso Sea, 31°50'N, 63°30'W; Southern Ocean, 54°00'N, 176°00'W; central North Pacific, 31°00'N, 159°00'W.
found to correlate, indicating that the two do not co-vary in any meaningful way in these systems. The relative range of A^'^C values for oceanic DOC (^3517oo across all systems studied) is far greater than for 8^^C (Table II). The three main regions of the open ocean for which profiles of A^'^C-DOC are available are the central North Pacific, Sargasso Sea (North Atlantic), and Southern Ocean (Fig. 3). Average profiles of A^^C-DOC for all three regions (Fig. 4a) show three characteristic features: (i) surface maxima, (ii) continuous decreases through the main thermocline, and (iii) lower and near-constant values below the main thermocline. The surface "maxima" in A^'^C-DOC at all three sites, it should be pointed out, are still quite low in absolute terms, and reflect an overall depletion in A^'^C-DOC of the upper water colunm which is not indicative of the majority of this material being derived from contemporary phytoplanktonic carbon. In addition to these general qualitative features, the three profiles, located at varying distances along the path of mean deep-water transport (Stuiver et ah, 1983), also show several distinct differences (Fig. 4a), including: (i) similar values of A^'^C-DOC in surface waters of the Sargasso Sea and central North Pacific; (ii) significantly lower A^'^C-DOC
420
James E. Bauer A^^C of DOC (%o) -550
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Figure 4 Profiles of (a) A^'^C-DOC, (b) DOC concentration, and (c) A^'^C-DOC in the Sargasso Sea (open circles). Southern Ocean (filled triangles), and central North Pacific (filled circles).
values in surface waters of the Southern Ocean, mostly likely as a result of the weaker thermocline there, which allows deeper, A^^C-depleted DOC to mix upward; (iii) below the main thermocline, decreasing mean A^^C-DOC in the order Sargasso Sea (A^'^C = -390 ± 10%^; 3970 years equivalent age) > Southern Ocean (A^'^C = -500 ± 20%o; 5570 years equivalent age) > central North Pacific (A^'^C = -525 ± 20%^; 5980 years equivalent age). As we will describe below more fully, the vertical distributions of A^'^C-DOC in the openocean water column may be used in simple two-box mass balance models to show that DOC above the main thermocline may be described adequately by a combination of (a) ^"^C-depleted, subthermocline DOC that is mixed vertically over time scales of ocean water transport and cycling into the upper water column, and (b) ^^C-enriched DOC that is newly produced by recent biological production. Early work comparing the deep A^'^C-DOC profiles of the central North Pacific (WilUams and Druffel, 1987) with the Sargasso Sea (Bauer et al, 1992a; Druffel et al, 1992) emphasized the near-uniform offset in A^'^C (135%^) and age (2100 years) between these two profiles below the main thermocline. This age difference is close to the approximate 1500-year transport time of deep ocean water between the North Atlantic and North Pacific estimated by Stuiver et al. (1983). This led to the interpretation that deep-ocean DOC is refractory, it ages
421
Carbon Isotopic Composition of DOM
quasi-conservatively during global deep-water transport, and (because of the ages of DOC from both the Sargasso and North Pacific exceeding deep water transport times) it is recycled through the oceans several times prior to being removed. As we shall see, while this overall interpretation may still be valid, new data suggest that the details concerning the transport, aging and utilization of DOC through the deep global ocean may be more complicated than a simple comparison of the Sargasso and North Pacific "end-members" suggests. Although A^'^C-DOC values decrease along the path of mean deep water transport, they do not decrease at the same rate as A^^C of dissolved inorganic carbon (A^'^C-DOC; Fig. 4c), which is generally believed to be a robust measure of deep water mass aging during transport (Stuiver et al, 1983). As can be seen (Fig. 4a), the subthermochne A^'^C-DOC of the Southern Ocean is on average only sHghtly greater (-'25%o) than that of the central North Pacific. In contrast, the A^'^C-DOC in the Southern Ocean is essentially equidistant between the North Atlantic and the North Pacific values and profiles (Fig. 4c). Furthermore, Southern Ocean DOC is very similar in concentration to the Sargasso Sea (Fig. 4b). Therefore, while there is only about a 2 /xM decrease in DOC concentration between the North Atlantic and Southern oceans, the greatest part of the A^'^C-DOC decrease occurs in this same sector. The A^^C-based age differences for both DOC and DIC between these three oceanic regions (Table III) show that the age difference for DOC is about 900 years greater than for DIC in the Atlantic-Southern Ocean sector, whereas the two are much closer in the Southern Ocean-Pacific sector. Furthermore, assuming quasisteady-state rates of change of both A^'^C-DOC and DOC concentration as deep water ages and DOC is degraded, an estimate may be made of a "conservative" rate of change of both of these parameters between the Sargasso and North Pacific (Fig. 5). Taken together, these findings suggest that there may be (a) selective utilization or removal (~2 /xM) of ^"^C-enriched DOC between the Sargasso Sea and Southern Ocean, (b) a selective replacement of average DOC by ^^C-depleted DOC (~3 /xM of A ^^C = -1000%o material, such as petroleum or black carbon) in Southern Ocean waters, or (c) a combination of the two. There exists evidence both for the selective utilization of ^"^C-enriched DOC components by marine bacteria Table III Deep Water Transit Times and DOC Age Differences Sector
Transit time (years) (A^^C-DIC-based)"
DOC age difference (years)
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DOC (|LiM) Figure 5 The relationship between A^"^C-DOC and DOC concentration in deep waters ( > ~ 1000 m depth) of the Sargasso Sea (open triangles). Southern Ocean (filled triangles), and central North Pacific (filled diamonds). The dashed curve represents the expected changes in A ^^C-DOC and DOC assuming a steady rate of change of each during deep water mass transport and aging. Adapted with permission from Druffel and Bauer (2000).
(Cherrier et aL, 1999) as well as for inputs of both ^^C-depleted petroleum carbon (Boehm and Requejo, 1986; Macdonald et al, 1993; Roberts and Carney, 1997) and black carbon (Masiello and Druffel, 1998) to open ocean waters. Whatever the case may be, it is clear from these and other studies (e.g., Hansell and Carlson, 1998) that deep ocean DOC is not completely refractory on time scales of deep water transport, and that both the utilization and input of components of different A^^C signatures may influence the distributions of concentrations and A^'^C of DOC throughout the deep ocean. There has been little work on the A^'^C and/or 5^^C signatures of different components of open ocean DOC. The only organic "components" (operationally defined or otherwise) that have so far been isolated from open-ocean DOC for A^'^C analysis are the humic substances (hydrophobic acids extractable on XAD resins) and the UDOC ( >1 kDa molecular weight) fraction (Table II). The range of A^^C-humic values for the central North Pacific is relatively narrow (—410 to —310%o) compared to that of the total DOC. Conversely, in the Sargasso Sea the range of A^'^C-humic values is greater (-587 to -358%o) compared to that of the total DOC. In both the central North Pacific and Sargasso Sea, A^^C-humic was significantly lower than A^'^C values for total DOC from the same depth (Bauer et ai, 1992a; Druffel et al, 1992). This indicates that this component of the DOC pool must be derived from older, possibly non-marine sources or from hydrophobic marine constituents such as lipids that are fighter in 6^^C (Sackett, 1989) or that it simply ages in situ more extensively than the average DOC.
Carbon Isotonic Composition of DOM
423
In the only known study of open-ocean UDOC in the major open ocean systems, and in contrast to humic substances, Bauer et al. (submitted for pubhcation) demonstrated that the > 1-kDa fraction of DOC (comprising ~40-50% of the total DOC in this study) had A^'^C and 8^^C values that were indistinguishable within analytical error to the total DOC (Table II). This suggests that, isotopically at least, the high-molecular-weight fraction of DOC is representative of the total pool in open-ocean settings. As we shall see, however, there is greater isotopic disparity between the bulk DOC and different molecular-weight components in more coastal settings (see Section IV.B, below). It should be noted that measurement of the isotopic composition of a bulk pool of carbon like DOC, the A^'^C or 8^^C signatures of that bulk pool reflect a weighted average of the isotopic signatures of all the components contributing to it. For example, considering the mean A^'^C-DOC values and corresponding ages for the deep Sargasso Sea (mean A^^^C = -390 ± 10%^; 3970 years B.P.) and central North Pacific (mean A^'^C = -525%^ ± 10%o; 5980 years B.P.), there are a number of possible scenarios for the A^'^C distributions of the entire population of organic molecules in the DOC pool (Figs. 6A-6C). Frequency distributions of A^'^C values of all the components of DOC may have varying degrees of normality as well as varying ranges. For example, frequency distributions of A^^C of different DOC fractions or even molecules may be broad and continuous (Fig. 6A), narrow and continuous (Fig. 6B), or even discrete (Fig. 6C). A number of other potential scenarios may be hypothesized as well. The specific combination of factors that leads to the observed mean weighted A^'^C-DOC values, and the distribution of A^'^C values and ages within the DOC pool is not known, though the advent of compound-class (Wang et al, 1998; Wang and Druffel, 2001) and compound-specific (Eglinton et al, 1996, 1997) A^^C measurements may allow for a greater degree of differentiation of the A^'^C distributions within the bulk DOC pool. The few compound-class A^^C measurements that have been made to date in oceanic DOC (isolated as UDOC) show that, for sugars at least, modem radiocarbon ages predominate, in spite of the old, ^^C-depleted DOC that dominates the average, bulk pool (Aluwihare, 1999). Thus, young, surface ocean-derived components of the DOC pool are transported to the deep ocean where they may fuel deep heterotrophic metabolism (Craig, 1971a,b; Nagata et al, 2000) or where they may become refractory and age (Brophy and Carlson, 1989; Ogawa et al, 2001). B. DISTRIBUTIONS OF ^^^C AND A ^ ^ C OF DOC IN O C E A N M A R G I N S
The distributions of S^^C and A^'^C of DOC and their use as source and age tracers, as well as their comparison to distributions in the open ocean, have only
424
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recently been established in selected ocean margin systems (Table IV). For purposes of this discussion, we will consider ocean margins and coastal environments to be those regions extending from the inner continental shelf, across the continental slope to the continental rise. A detailed description of 5^^C and A^'^C of DOC in areas farther inshore such as estuaries and rivers will not be undertaken here, except insofar as these systems may be important sources of DOC to shelf, slope, and rise waters. For a comprehensive review of 8^^C and A^'^C of DOC in river and estuarine systems, the reader is referred to Raymond and Bauer (2001a).
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The proximity of ocean margins to the continents may allow 5^^C and A^'^C to be used as tracers for identifying the sources and relative inputs of both marine and terrestrial organic matter to seawater DOC in these regions (Hedges, 1992; Hedges et ai, 1997), provided that the isotopic signatures of the major potential source terms can be constrained adequately. Comparing ranges of 5^^C-DOC in ocean margins (Table IV) to oceanic systems (Table II) shows that the range of values in those margin systems studied are much greater than in open ocean waters. Significantly lighter 8^^C values of both total DOC and UDOC may be observed in margins, especially in regions such as the Mid-Atlantic Bight that are directly influenced by significant freshwater inputs (e.g., from Chesapeake and Delaware Bays). The lighter 5 ^^C-DOC values have been found to include not only shelf waters, where low-salinity plumes carrying terrestrial organic constituents predominate (Table II; Santschi et ai, 1995; Guo et al, 1996; Bauer and Druffel 1998; Bauer et al, 2001), but also near-bottom waters of the shelf and slope containing nepheloid material derived from aged terrestrial organic matter stored in shelf and slope sediments (Guo and Santschi, 2000). Anomalously fight 5^^C-D0C values have also been observed in systems such as the Orca Basin (northern Gulf of Mexico, Table IV; Sackett et ai, 1979), where suboxic or anoxic conditions exist, and fermentation and other microbial reactions, or even sources of hydrocarbons, may influence the overall values for total DOC. Like the 5^^C-D0C values, A^'^C-DOC in margin waters also shows a broader range of values than open-ocean counterparts (Table IV), which are both greater and less than values from the Sargasso Sea and central North Pacific (Table II and Fig. 4a). The higher A^'^C-DOC values tend to be associated with lower-salinity plume waters on the shelf, while the lowest A^'^C-DOC values are generally found in waters of the slope and/or nepheloid layer (Guo et al, 1996; Bauer and Druffel, 1998; Bauer et ai, 2001), suggesting that shelf and slope sediments may be a source of ^"^C-depleted ("old") DOC to margin waters. This is emphasized by comparing A^^C-DOC values from the margins with the central basins of the North Atlantic and North Pacific (Figs. 7a and 7b). In both cases A^'^C-DOC is significantly lower in slope and rise waters than in waters of the central basins. The exact sources of this ^"^C-depleted DOC in margins has only been speculated upon, but may include pre-aged marine and terrestrial (on the basis of 5^^C-D0C values) material from shelf and slope sediments (Bauer et al, 1995; Guo et ai, 1996; Guo and Santschi, 2000) as well as aged terrestrial material from rivers (Raymond and Bauer, 2001b). In a detailed study of the western North Atlantic, Bauer et al. (2001) found A^'^C-DOC to be greatest (as high as — 39%o) in lower salinity surface waters of the shelf, decreasing rapidly offshore and with depth, even in relatively shallow (25-50 m depth) shelf waters. The lowest A ^"^C-DOC values were observed in deep slope waters, where they were significantly lower than values measured previously for the deep Sargasso Sea (Fig. 7a). There was also a strong inverse relationship
Carbon Isotonic Composition of DOM
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between A^'^C-DOC and 5^^C-D0C in all shelf and surface slope waters of the western North Atlantic (Fig. 8a), which is likely attributable to varying contributions of young, ^"^C-enriched organic matter of terrestrial and/or riverine origin. This interpretation is further supported by the strong relationships between both A^^c-DOC and salinity (Fig. 8b) and ^^^C-DOC and salinity (Fig. 8c). The more highly ^"^C-depleted DOC in deep slope waters (A^'^C as low as -442%o) was also often observed to contain a correspondingly and somewhat lower 5^^C (as low as -ll.y/oo) component (Fig. 8b); however, this must originate from relic terrestrial material either in the MAB itself or discharged to it from rivers and estuaries. In margins not influenced by major river inputs (e.g., the eastern North Pacific off central California, Table IV) we observe 5^^C-D0C values that are consistent with open ocean values and predominantly marine sources, with little or no discernible terrestrial character such as that seen in river-influenced margins like the western North Atiantic and Mid-Atlantic Bight (Table IV). We do, however, observe consistently ^"^C-depleted DOC values in the eastern, relative to the central, North Pacific (Fig. 7b), again suggesting that margins may be important sources of aged DOC to the oceans in general (Bauer and Druffel, 1998). In addition, the
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Carbon Isotonic Composition of DOM
429
effects of processes such as upwelling on A^'^C-DOC may also be observed in regions such as the eastern North Pacific off California (Fig. 7c). In this case, mean A^'^C-DOC in the upper water column decreases with proximity to the coast, where the effect of upwelling and vertical mixing of deep, ^^C-depleted DOC into surface waters is most pronounced (Bauer et al, 1998b). Several studies have investigated A^'^C and b^^C of the high-molecular-weight UDOC component of DOC in shelf and slope environments (Benner et al, 1992b; Santschi et al, 1995; Guo et al, 1996; Guo and Santschi, 1997; Table IV). In none of these studies was the A^'^C and 5^^C of total bulk DOC also measured, so direct comparisons of the two pools are difficult to make. However, some generalizations may be made about the isotopic composition of UDOC in margin settings. First, the 5^-^C of the >l-kDa fraction has a lower overall range than average bulk DOC measured in other studies (compare values for UDOC with total DOC in Table IV), indicating that it is composed of isotopically lighter material. The A^'^C of the >l-kDa fraction is generally similar to that of the total DOC from the same regions (Table IV), even though direct comparisons have not been made as in the open ocean (Table II, and see Section III.A, above). For >10-kDa UDOC, with the exception of the Mid-Atlantic Bight slope, 5^^C values were overall heavier, and A^^C values were correspondingly enriched, compared to either >l-kDa UDOC or total DOC in the Mid-Atlantic Bight and Gulf of Mexico (Santschi et al, 1995; Guo et al, 1996; Guo and Santschi, 1997; Table IV). One interpretation of these findings (Santschi et al, 1995; Guo et al, 1996) is that the higher molecular weight (> 10-kDa) components of DOC include a disproportionately large contribution from young, ^"^C-enriched marine organic matter compared to either the total or 1- tolO-kDa fractions, which themselves may contain a significant contribution from older, terrigenous inputs. On the very dynamic Mid-Atlantic Bight continental slope, however, the >10-kDa fraction is highly depleted in both A^'^C and ^^^C (Guo et al, 1996; Table IV). In fact, the most depleted A^'^C values in any form of DOC ever observed are found in this fraction in Mid-Atlantic Bight slope waters. Subsequent work by Guo and Santschi (2000) suggests that these anomalously low A^'^C and 5^^C slope values may result from preferential desorption of ^"^C- and ^^C-depleted organic matter during reworking and resuspension of slope sediments. Thus, old ^"^C-depleted DOC and UDOC from slope sediments and benthic nepheloid layers, and possibly including components derived from terrestrial sources, may contribute in part to the old DOC in the open ocean (Bauer and Druffel, 1998). Below we show how simple two- and three-source mass balance models have been applied to A^'^C-DOC and 5^^C-D0C distributions in ocean margins to evaluate (a) the relative contributions of known (in terms of their A^'^C and 5^^C signatures) potential sources of marine and terrestrial DOC to the standing inventory of shelf and slope DOC of selected margin systems and (b) the potential contributions of deep margin (i.e., slope) DOC to the deep open ocean.
430
James E. Bauer
V. APPLICATIONS OF 6^^C AND A^^C IN MARINE DOC CYCLING STUDIES Both (5^^C-D0C and A^'^C-DOC have been used in simple modeling studies of marine organic carbon cycling. The most common application of S^^C has been in evaluating the relative and/or absolute magnitudes of the contributions of different organic matter sources to a given pool or reservoir. 8^^C has been most successfully applied in coastal, estuarine, and other systems where the various potential inputs have measurably different signatures. As discussed above, in openocean water (Table II) the 5^^C of DOC has such a small range (and the factors that are responsible for the limited observed variability are not well-enough established) as to essentially negate its use as a source tracer in these systems. In coastal systems, where contributions of organic matter from nonmarine sources to the DOC pool may be more important and the range of 5^^C-D0C values is greater (Table IV), 8^^C may be used in a semiquantitative manner to establish the relative contributions of different sources. Furthermore, and in contrast to 5 ^^C, A ^"^C-DOC has a greater natural range in both oceanic (Table II) and coastal (Table IV) systems and thus may prove more useful as a potential "source" tracer than 8^^C. It should be noted that when we refer to both isotopes as source tracers, it is in the sense that 8^^C can differentiate between different sources on the basis of fractionation effects (i.e., between different primary producers), while A^^C can differentiate on the basis of source age. Used in conjunction with each other, A^^C and 8^^C may serve as unique source and age tracers in different environments (e.g., in oceanic vs coastal systems) and at times may be used to compliment one another as dual tracers of carbon specifically, and organic matter in general. Natural (cosmogenic) and bomb ^"^C have the added benefit of providing information on the mean weighted age of a given carbon pool. We will now consider some of the major applications of A^'^C and 8^^C as both source and age tracers of organic matter in studies of marine carbon cycling through the DOC pool. A. VERTICAL MIXING AND DISTRIBUTION OF A ^ ^ C - D O C IN THE O P E N O C E A N
Profiles of bulk A^'^C-DOC values and DOC concentrations in all three major open ocean regions studied to date (Figs. 4a and 4b) indicate that there are decreasing inputs to the open ocean water column of excess (i.e., above deep, background A^'^C-DOC values) ^"^C-enriched DOC with increasing depth. Furthermore, the A^'^C-DOC profiles suggest (a) that there must be inputs of the most ^^C-enriched (i.e., "young") material in the shallowest parts of the water column, (b) that these ^"^C-enriched inputs decrease with increasing depth through the main thermocline, and (c) that there are no discernible inputs in ^"^C-enriched DOC below the main thermocline due to the absence of vertical A^'^C-DOC gradients in deep waters
431
Carbon Isotopic Composition of DOM (although this observation alone is not sufficient to rule out such inputs to the deep ocean by other means such as POC dissolution and degradation, lateral inputs, porewater diffusion, etc.). The question, then, is how to interpret the A^'^C-DOC distributions and gradients throughout the open ocean water column. In order to address this, Williams and Druffel (1987), Bauer et al. (1992a), and Druffel et al (1992) invoked a two-component vertical mass balance mixing model that assumed (1) deep-ocean DOC, with its near-constant average concentration and A^'^C signature, is mixed homogeneously throughout both the deep and upper water columns; (2) surfaceocean DOC is composed of a combination of this ^"^C-depleted deep-ocean DOC and ^"^C-enriched DOC derived from contemporary surface-ocean productivity; and (3) the A^'^C values of the contemporary surface-derived DOC are equivalent to the A^'^C of surface ocean DIC from whence the DOC is fixed. Taking the Sargasso Sea as an example (Fig. 9A), and using the above assumptions, Bauer et al. (1992a), and Druffel et al. (1992) predicted that the average mixed layer (ML) DOC (mean [DOC]ML-observed = 66 /^M, mean A^^C-DOCML-observed = —230%o) is composcd of a combination of deep DOC (mean [DOCJdeep-observed = 43 /xM, mean A^'^C-DOCdeep-observed = -390%o) plus DOC assumed to be derived from new contemporary planktonic production (mean [ D O C l n e w estimated = 2 3 / x M [ = 6 6 m i u U S 4 3 / x M ] , m e a n A ^ ^ C - D O C n e w estimated
=
+116%o - the same as Sargasso Sea surface A^'^C-DIC values at the time of this study). Using the following mass-balance calculation, ([DOCIML -observed *A
C-DOCML-calculated)
= ([DOCldeep -observed
A
~r ( [ A - ' ^ ^ l n e w estimated
C-DUL-deep-observed) A
C ~ D U C n e w estimated)?
L^l
the A^'^C for mixed-layer DOC was calculated (A^'^C-DOCML-caicuiated) to be — 214%o, which is close to the average A^^C-DOCjviL-observed value of -230%o (Bauer et al, 1992a; Druffel et al, 1992). In other words, this twocomponent model, whereby old, ^"^C-depleted deep ocean DOC mixes with young ^"^C-enriched DOC from surface production, appears to describe adequately the average, relatively ^"^C-depleted values, of surface-ocean DOC. Performing the same operation for the central North Pacific (Fig. 9B) and using Eq. [4], WilHams and Druffel (1987) and Druffel et al (1992) predicted that the average mixed layer DOC (mean [DOC]ML-observed = 80 /iM, mean A^'^C-DOCML-observed = -153%o) is composcd of a combination of deep DOC ( m e a n [DOCJdeep-observed =
36 /xM, m e a n
A^'^C-DOCdeep-observed =
-525%o)
plus DOC assumed to be derived from new contemporary planktonic (mean [DOCJnewestimated = 4 4 / x M [ = 8 0 m i u U S 3 6 fjM],
m e a n A^"^C-DOCnewestimated
=
-M47%o—the same as central North Pacific surface A^'^C-DOC values at the time of this study). Again using Eq. [4], A^'^C-DOCML-caicuiated is estimated
James E. Bauer
432
MIXED LAYER newly produced DOC
total surface DOC
Assumed: DOC = ~23|LiM Ai4c = ~+116%c
Calculated: DOC = ~66|LiM Ai^C = ~-214%o
Si
DEEPLAYER
Observed: old, DOC = -'43|LiM refractory Ai^C = ~-390%o DOC
Figure 9 Two-component mixing models for evaluating the vertical distributions of A^^C-DOC in (A) the Sargasso Sea and (B) the central North Pacific. See section V.A of text for full description.
to be —155700, which is identical within analytical error (±~6%o) to the A^^C-DOCML-observed of — 153%o. We therefore conclude that in both the north Atlantic and north Pacific central gyres that the DOC in the mixed layer consists to a first approximation of deep ocean DOC that has aged and mixed vertically over time scales of at least deep ocean mixing rates (^1500 years; Stuiver et al, 1983), and of DOC derived from completely modem organic matter synthesized by plankton in the upper ocean. This exercise also demonstrates the extremely refractory nature of the old, deep ocean DOC fraction, the ultimate fate of which is not known. However, surface ocean processes such as photochemical modification (Mopper et al, 1991; Mopper and Kieber, Chapter 9) and/or
433
Carbon Isotopic Composition of DOM MIXED LAYER newly produced DOC
total surface DOC
Assumed: DOC = ~44|xM A14C = ~+147%o
Calculated: DOC = ~80^M A14C = ~-155%o
><
w) B
DEEP LAYER
B
old, Observed: DOC = -36|LiM refractory A14C = -525%c DOC
S
>r Figure 9
(Continued)
bacteria degradation (Kirchman et al, 1991; Carlson and Ducklow, 1996; Carlson, Chapter 4; Cherrier, et al, 1996; 1999) of DOC may be important factors regulating the turnover of this globally significant reservoir of organic matter.
B. DISTRIBUTIONS OF 6^^C AND A ^ ^ C OF DOC IN O C E A N M A R G I N S
The information provided by A^'^C-DOC and 5^^C-D0C may also be used to evaluate the inputs (both qualitative and quantitative) of different sources of organic matter to ocean margin waters. The more highly variable distributions
200
York R. (0 psu)
MAB primary production -[]
100 0
o U
Ches. Bay (5-25 psu)
-100
MAB shelf and shallow slope
-200 -300
SS, > 1,000m
-400 -500 -600 -29
MAB deep slope
MAB nepheloid layer, >10kD
-28
-27
-26
-25
-24
-23
-22
-21
-20
5:13r
8'^Cof DOC(o/oo) b
200
0
o
Q O CJ
MAB primary production
Ches. Bay (5-25 psu)
100
1""
1
1 ^.i^^_^
/
'^^"^^^^-^^^rp.1/'*\'•••••:
-100
^ - ^ ^
-200
Grp. 2 7^^^'^'*''''<1 ^ — ^
-300
/
/
/
• •^^^^i-i '
'• / SS •••• /3-206m
_,^^—"""^ '• MAB nepheloid ^^^^''"^ Grp. 3 •• layer, >10kD^,,,^
-400
1
/
-500 -600 -29
-28
-27
-26
-25
-24
-23
-22
-21
-20
S^^Cof DOG(o/oo) C
200 100 o
0 -100
o
-200
«4—
-300
O CJ <j
-400
MAB Deep Slope Samples \ y
MAB nepheloid layer, >10kD __
SS >1,00'0m
-500 -600 -29
^^^-28
-27
-26
-25
-24
-23
8^3C Of DOC (0/00)
-22
-21
-20
Carbon Isotonic Composition of DOM
435
of A^'^C and 8^^C in the ocean margins (Table IV) compared to the open ocean (Table II) suggest that the origins and sources of margin are concomitantly more diverse in the margins. Several studies have recently attempted to evaluate inputs of multiple sources and ages of organic carbon to the DOC pool of the Mid-Adantic Bight region of the western North Atlantic using A^'^C and 5^^C of both total DOC and of UDOC. The major findings of these studies are summarized here. The A^'^C and 5^^C of total DOC was measured in shelf and slope waters of the Mid-Atiantic Bight by Bauer et al (2001). These data, collected between Nantucket and Cape Hatteras, show a high degree of covariance between A^'^C, (5^^C, and salinity in both shelf and shallow slope waters (Figs. 8a-8c); these relationships, however, were not found to hold for deeper slope waters (>^300 m depth; Fig. 8b), indicating at least two distinct classes of DOC. The paired A^'^C(5^^C distributions for Mid-Atlantic Bight DOC may be evaluated along with the ranges in A^'^C and (5^^C of all of the potential sources of organic matter to the DOC pool that have been measured for this region (Fig. 10a). Since the two classes of measured paired A^'^C-DOC and 5^^C-D0C values He within those of the potential sources, isotopic mass balances can be used to estimate the relative contributions from each of these sources. In simple or well-constrained systems, single isotope linear mixing models are often adequate for first-order approximations of the sources contributing to a sample. However, the number and isotopic variability of autochthonous and allochthonous sources of organic matter in margin and other coastal environments is much greater than in many other aquatic environments. In such systems, the use of multiple natural isotopes may provide a greater degree of differentiation between multiple sources than single isotopes (Williams et al, 1992). Since both A^^C and 5^^C were measured in this study, we may use a dual-isotope approach, which should provide a greater degree of specificity for organic carbon than for organic matter in general. The potential sources of DOC to MAB shelf and slope waters for which paired A^'^C and 5^^C information are available are shown in Table V and plotted in Fig. 10a (means and ranges). These sources include: (a) total freshwater DOC from Chesapeake Bay, as represented by one of its major subestuaries, the
Figure 10 (a) Mean values and ranges in A^^C and 6^^C of potential sources of DOC to MidAtlantic Bight (MAB) shelf and slope waters. Isotope values for potential sources were obtained from the following: York River total DOC—Raymond and Bauer (2001b) and Raymond and Bauer (2001c); Chesapeake Bay > 1-kDa material and MAB > 10-kDa nepheloid layer material—Guo et al. (1996); Sargasso Sea (SS) total DOC—Bauer et al (1992a) and Druffel et al (1992); MAB primary production—based on A^^C and ^^^C values for DIC in Bauer et al (2001). (b) The A^^^C vs ^^^C fields of potential source combinations of DOC to MAB shelf and shallow slope waters only and (c) MAB deep slope waters only. See section V.B. of text for details. Adapted with permission from Bauer e/fl/. (2001).
436
James E. Bauer Table V
Mean A^^C and S^^C Values of Potential DOC Sources Used to Calculate Relative Contributions to DOC in the Mid-Atlantic Bight (Refer to Fig. 10). Potential Source York River freshwater DOC
Mean A^^C (%o)
Mean ^^^C i%o)
200
-28.4
Raymond and Bauer, 2001c
Reference
Chesapeake Bay (5-25 psu) HMW(>lkDa)DOC
-1
-27.8
Guo etal, 1996
Deep MAB VHMW (> 10 kDa) DOC
-580
-26.4
Guo etal, 1996
55
-20^
Bamretal,
-394
-20.8
BmcTetaL, 1992a
-238
-21.2
Dmffe\ et ai, 1992
MAB primary production'' Deep Sargasso DOC Surface Sargasso DOC
2001
Note. Adapted from Bauer et al. (2001). ^ Based on A^^C and ^^^C of DIC (Bauer et al, 2001). ^Assumes fractionation of -19%o during CO2 fixation by marine phytoplankton.
York River estuary (Raymond and Bauer, 2001c), (b) the high molecular weight (> 1 kDa) component of DOC from the mainstem of Chesapeake Bay (Guo et al, 1996), (c) the very high-molecular-weight (VHMW, > 10 kDa) component of MAB near-bottom nepheloid material (Guo et al, 1996), (d) present-day primary production in MAB surface waters, estimated from the A^'^C and 5^^C values of DIC, and (e) previous estimates of fully marine values for the surface and deep Sargasso Sea (Bauer et al, 1992a; Druffel et al, 1992), taken to be representative of open North Atlantic waters in general. It is possible that the two different molecular weight fractions (>1 kDa and >10 kDa) used in this analysis vary isotopically from the bulk DOC from the same ocean margin waters. However, without further comparative isotopic information between the high-molecular-weight components and bulk DOC, we must assume for the present exercise that they are comparable in isotopic content, similar to the observations of Bauer et al (submitted for publication) for open ocean waters (see Table II). Use of the isotopic values of Chesapeake Bay >1 kDa and deep MAB > 10 kDa fractions of DOC (Guo et al, 1996) as terrestrial/riverine end-members is supported by thefindingsof Mitra^fa/. (2000) who showed that both of these components contained elevated amounts of lignin-derived phenols originating from terrestrial plants. The paired A^'^C and 5^-^C distributions of DOC samples measured in this study (Fig. 10a) are consistent with DOC in the MAB being composed of one or more of the indicated potential sources. In addition, A^'^C and 5^^C distributions for DOC from MAB shelf and shallow slope waters lie between different potential
437
Carbon Isotopic Composition of DOM
end-members (i.e., surface Sargasso, Chesapeake BayAfork River and MAB primary production) than does DOC from deeper slope waters (i.e., deep Sargasso and MAB nepheloid layer material). We hypothesize that this is a result of unique sources (and ages) of DOC to these two major water types. It is also possible from Fig. 10a for admixtures of MAB modem primary production and > 10-kDa nepheloid material to give A^'^C and 8^^C values similar to those observed in MAB shelf and shallow slope waters. However, two factors argue against this proposed scenario. First, the > 10-kDa ^"^C-depleted material in deeper waters comprises only 3-6% of the total DOC (Guo et al, 1996) and second, the observations of Guo et al. (1996) indicate that in shallow waters of the MAB, the > 10-kDa fraction was actually similar in both A^'^C and 8^^C to values for MAB primary production (Fig. 10a). Furthermore, as demonstrated by Druffel et al. (1992), Sargasso Sea surface ocean DOC can be adequately described as a combination of old, deep material and young material from primary production. For purposes of the following exercise, we assume that the major inputs to the different shelf and surface slope waters (shown as Groups 1, 2, and 3 in Fig. 10b) can be described reasonably by a combination of (a) surface Sargasso Sea DOC (which itself is composed of deep Sargasso material and recent marine primary production; Bauer et al, 1992a; Druffel et al, 1992), (b) Chesapeake Bay DOC (which must also contain some York River material), and (c) DOC derived from contemporary MAB primary production. In order to establish first-order estimates of the relative contributions of the major presumed sources of DOC to shelf and shallow slope waters, we used three-source isotopic mixing models similar to those of Fry and Sherr (1984) and Kwak and Zedler (1997). The generaUzed mixing equation is ^DOC-MAB = / l ^ D O C - / l + fl^DOC-f2
+ (1 " / l " /2)^DOC-/3.
[5]
where X is the isotopic composition (A^'^C and 8^^C) of DOC from the MAB observed. The value / is the relative contribution of each of the three potential sources to the total DOC in the MAB samples, and/i-|-/2 +/3 = 1.0. Since there are two unknowns (/l and/2) in Eq. (1), the equation must be solved simultaneously using A^'^C and 8^^C. The contribution of the third potential source,/s, is equal to(l-/i-/2).
The results of these calculations (Table VI) indicate that shelf and shallow slope waters are dominated (up to 97%) by DOC that is similar isotopically to that found in the open North Atlantic (Sargasso Sea). However, the DOC from different regions within the MAB contains varying and often significant amounts of material from in situ production and material that must arise from terrestrial, riverine, and/or estuarine (TRE) inputs. For Group 1 (Fig. 10b; Table VI), up to a third of the DOC is TRE material, and sHghtly more (25^3%) is recently derived MAB primary production. Group 2 samples (Fig. 10b) are composed of lower amounts of DOC derived from both TRE (9-25%) as well as MAB primary production (0-12%) (Table VI). Finally, the two anomalous samples (Group 3) that
438
James E. Bauer
Table VI Estimates of Relative Inputs of Different Potential Sources of DOC to the Middle Atlantic Bight, Based on Results of Three-Source Isotopic Mixing Models Relative contribution (%) of: Zone Shelf and shallow slope Group l'^ Group 2" Group 3" Deep slope^
Ches./ York
MAB prim, prod.
Sargasso shallow
Sargasso deep
MAB nepheloid
MAB surf, sediments
19-31 9-25 2-3
25-43 0-12 na
26-52 64-97 77-85
na na na
na na 12-21
na na na
0-3
na
na
74-88
8-25
na
Note. See text for details. Adapted from Bauer et al. (2001). na, not applicable (end-member not used in mass balance). ^ As shown in Fig. 10b. ^ As shown in Fig, 10c. lie outside of the mixing fields that contribute to the majority of shelf and shallow slope samples (Fig. 10b) must have a component that is much older in order to account for the observed values. The only material that has been identified that can fulfill the requirement of a simultaneously ^"^C- and ^-^C-depleted DOC component is the very high-molecular-weight DOC (>10 kDa) from the nepheloid layer (Guo et al, 1996; Guo and Santschi, 2000). When this source is mass-balanced against shallow Sargasso and TRE material, we find that it comprises 12-21% of the total DOC (Table VI), while younger TRE material represents only trace (2-3%) inputs. Following our approach for shelf and shallow slope waters, we assume that MAB deep slope DOC is composed predominantly of a combination of deep Sargasso, >10-kDa nepheloid, and TRE material (Fig. 10c). Similar to the Group 3 DOC samples (Fig. 10b), we find that up to 25% of the deep slope DOC may be composed of a presumably highly aged, ^^C-depleted high-molecular-weight component (Table VI). On the basis of several other recent studies (Druffel and Williams, 1990;Sherrell^M/., 1998;Bianchiert2/., 1998; Bauer and Druffel, 1998; Druffel et al, 1998; Honda et al, 2000), lateral inputs of organic matter from both the nepheloid layer and sediments in continental margins are plausible sources of organic matter not only to slope waters, but to even more oceanic waters. The A ^"^C-POC values in MAB slope waters are even more highly depleted compared to the open North Atlantic (Bauer etal, 2001), suggesting that margins are a source of ^"^C-depleted POC (and by similar reasoning, DOC) to the open ocean water column. The fact that the high-molecular-weight component has substantial terrestrial 8^^C character and is concomitantly so old (Guo et al, 1996; Guo and Santschi, 2000), suggests that slope sediments could represent a temporary "aging
Carbon Isotopic Composition of DOM
439
reservoir" for terrestrial and shelf/slope-derived organic matter. This material, possibly deposited initially in slope and certain shelf sediments as POC or mineralsorbed DOC (Mayer, 1994; Keil et al, 1997), may then undergo partial postdepositional desorption, hydrolysis, and degradation in sediments prior to being re-released to the water column pool of DOC (Burdige and Gardner, 1998; Burdige et al, 1999; Alperin et a/., 1999; Burdige, Chapter 13). If it occurs, this proposed mechanism is significant in that it would result in margin sediments providing a source of "pre-aged" terrestrial and shelf/slope primary production to the deep ocean directly (Bauer et al, 1995). Finally, on the basis of both past and recent evidence (Spiker and Rubin, 1975; Raymond and Bauer, 2001b), we cannot, without further information, rule out the possibility that rivers themselves transport directly a significant amount of aged terrestrial DOC to certain coastal systems. For example, Spiker and Rubin (1975) reported A^'^C values for total DOC in the Rappahannock and Susquehanna Rivers of —91 and —81%o, respectively, while Raymond and Bauer (2001b) have found mean A^'^C-DOC values of -158%o in the freshwater Hudson River.
C. SOURCES AND INPUTS OF U D O C TO OCEAN MARGINS In addition to being used to track sources and inputs of bulk DOC, natural ^"^C and ^^C have also been applied for tracing the origins and ages of UDOC in the Mid-Atlantic Bight and Gulf of Mexico shelf and slope regions. The A^'^C and 8^^C signatures of various molecular weight fractions of UDOC (primarily the > 1 -kDa and > 10-kDa fractions) appear to be more variable than, and differentiable from, bulk DOC from the same environment, and between different environments. Similar to total DOC, Santschi et al. (1995) and Guo et al. (1996) observed inverse correlations between A ^ ^ ^ . U ^ Q C and ^^^C-UDOC in the Gulf of Mexico and Mid-Atlantic Bight margins (Figs. IIA and UB); both A^^C-UDOC and 5^^C-UDOC also correlated inversely with salinity, suggesting a possible application of these relationships for identifying sources of different aged terrestrial and marine (including estuarine and sedimentary UDOM and shelf/slope production) to the UDOC, and hence total DOC, pools. These workers also employed the relationship between the C:N ratios within UDOC (or more appropriately, UDOM, or ultrafiltered dissolved organic matter) to distinguish different end-member "classes" of UDOM and use them to estimate their contributions to the observed A^'^C and C:N values in these two regions (Figs, l i e and IID). In the Gulf of Mexico, UDOM was observed to consist primarily of one of three end-members (deep-water, offshore surface or estuarine; Fig. IIC), with little mixing between the three. In contrast, Mid-Atlantic Bight UDOM appeared to consist to a much larger extent of admixtures between either (a) deep-water and offshore surface UDOM or (b) offshore surface and estuarine
440
James E. Bauer
H 1A +
1
o
Deepwatei colloids
T +
/ /
T
1
— h -
—1
1
Estuarine colloids
o
o
I oo\ 1 /o 1 V/o / '
0
N^V
\——1
"T
-]-
.o y 1 —\—
-200 * C
4-4-
^^ooV
Offshore surface\ water colloids
-1
h
J_
1-
\
-100
(%«)
(%o)
150 L • • • 1 • • ' i • • • 1 • • • 1 • • • 1 • • • J
H
J_B -|-
\
h -—f
H—H
1
b
1
100
i ^
Middle Atlantic Bight (Surface water COM^)
E
50
/ ^
Deep water colloids
T ^m^
4- V-X""**^*
-f -1
1
Estuarine colloids
• •^ 1
-500
h-—1
-400
-300
A" C
\
/ A
o
1 T
" • J Offshore surface 1 -^ water colloids T
-H—
H -200 -100 (%o)
1
1
h
0 -50
1 ^^^"^O i
T
-150
t
-200
f
-100
t
A-^A
]
l
j T
A
A^ i ^ ^^^ ^^"^--^ ^^ I / t
(R=0.71, n=14)
A
+
-250 r • • ' 1 • • • 1 • • • 1 • ' ' 1 ' • ' 1 ' • • 1 -32 -28 -26
5 " C (%c)
Figure 11 Relationships between: (A) C/N and A^'^C of UDOC for the Gulf of Mexico, (B) C/N and A^^^C of UDOC for the Mid-Atlantic Bight, (C) A^^C-UDOC and ^^^C-UDOC for the Gulf of Mexico, and (D) A^^C-UDOC and ^^^C-UDOC for the Mid-Atlantic Bight. COMi refers to >1 kDa UDOM: Adapted with permission from Guo et al. (1996).
UDOM (Fig. 1 ID), but not between deep-water and estuarine UDOM. Thus, lowsalinity sources of both UDOC and total DOC (see Section IV.B, above) appear to be isotopically discernible for a considerable distance from riverine and estuarine sources in ocean margin regions. This further emphasizes that different ocean margin regions may be unique from one another with respect to their sources and inputs of organic matter, depending upon the relative magnitudes of terrestrial and marine fluxes, and with respect to the hydrographic (i.e., mixing) features of a particular ocean margin region. These same workers (Guo et al., 1996) used the A^'^C of > 1 kDa and > 10 kDa and total DOC (based on independent measurements by Bauer et al., 2001) to estimate by mass-balance the relative contributions and A^^C signatures of < 1-kDa, 1- to 10-kDa, and > 10 kDa material to the standing stock of total DOC in the Mid-Atlantic Bight shelf and slope off Cape Hatteras. Results of these mass balance calculations (Table VII) indicate that very low-molecular-weight UDOC (<1 kDa) comprises the majority (65-72%) of UDOC in the Mid-Atlantic Bight, and its A ^"^C signatures were generally less variable (A ^"^C = —487 to -217%) than either the 1- to 10-kDa or > 10-kDa fractions. Furthermore, the < 1-kDa fraction
441
Carbon Isotopic Composition of DOM Table VII Estimates of Relative Inputs and A^'^C Signatures of Different Molecular Weight Fractions of UDOC to the Middle Atlantic Bight, Based on Results of a Mass Balance Mixing Model Relative contribution of
Stn Shelf 10 Slope 1 12 13
Depth (m)
>10kDa
1-10 kDa
%^
Al^C^
%
Ai^C^
%
2 25
-257 -487
66 69
-128 -334
23 27
-6 -132
11 4
2 750 2 2300 2 250 2600
-217 -442 -240 -451 -246 -443 -452
65 70 66 71 66 71 72
-175 -399 -143 -359 -132 -355 -336
30 26 29 26 28 24 25
-160 -427 -9 -558 -8 -611 -709
5 4 5 3 6 5 3
Note. See text for details. Adapted from Guo et al. (1996). ^ C a l c u l a t e d a s A ^ ^ ^ ^ ^ ^ ^ = (Al'^CtotalDOC - ([Al'^Cl-lOkDa X %l-lOkDa] + [A^'^C>iOkDa X Al4C>i0kDa])/%
^Mean error (±1<J) of all A^'^C measuremer\ts was 6%o.
^ C a l c u l a t e d a s %10kDa).
was estimated to always be more depleted in A^'^C than the 1- to 10-kDa fraction, but was both enriched and depleted in A^'^C compared to the >10-kD fraction. Clearly, the different molecular weight fractions of DOC must have a variety of different sources and ages of materials contributing to them in ocean margins regions, in contrast to the high degree of uniformity in the A^'^C signatures in the > 1-kDa fraction and the total DOC in open ocean settings (see Table II, for eastern North Pacific UDOC and total DOC). Thus, size-fractionation of DOC and isotopic analysis of UDOC fractions provides an additional tool for assessing sources and contributions of DOC in ocean margin regions. D. EXCHANGES OF DOC BETWEEN THE OCEAN'S MARGINS AND
ITS INTERIOR
As illustrated in Fig. 7, gradients exist between the A^'^C-DOC signatures of certain ocean margins (e.g., western North Atlantic and eastern North Pacific) and the contiguous open ocean. It has also been shown by Bauer and Druffel (1998) that both of these margins have several micromolar higher average deep DOC concentrations than more remote ocean regions such as the Sargasso Sea and central
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North Pacific. The origin(s) of this old, ^"^C -depleted carbon to continental slope and rise waters is (are) not known, but several possibilities may be considered. In the western North Atlantic, the reintroduction to the water column of old sedimentary organic carbon (initially as both DOC and POC) from weathered shelf and upper slope sediments (Anderson et ai, 1994; Churchill et al, 1994), porewaters (Bauer et ai, 1995; Burdige, Chapter 13), and even submarine hydrocarbon seeps (Boehm and Requejo, 1986; Roberts and Carney, 1997) may contribute to the highly ^"^C-depleted (A^'^C as low as ^—700%o) colloidal and dissolved organic carbon observed in near-bottom waters in the Middle Atlantic Bight (Guo et ai, 1996) as well as to the ^"^C-depleted suspended POC observed in the water column there (Bauer et ai, 2001). The elevated DOC concentrations in slope (in the westem North Atlantic) and rise (in the eastern North Pacific) waters, along with lower A ^"^C-DOC values, indicate that DOC is present in ocean margins that is both older than that in the North Atlantic and Pacific central gyres and potentially available for export to the open ocean (Wollast, 1991, 1998). As a result of these gradients, simple two-source box models have been employed to assess the relative contributions to the deep, interior ocean DOC pools from (a) margin-derived DOC and (b) surface ocean-derived DOC from contemporary production (Bauer and Druffel, 1998). The conceptual framework and the relevant mass-balance relationships used for this assessment are shown in Fig. 12. The presence of positive concentration gradients between the margins and deep open ocean and between the surface and deep open oceans indicate that both
inputs from primary & secondary production
I
A^'^C: greater than deep ocean [DOC]: greater than deep ocean A^'^C: less than deep ocean [DOC]: greater than deep ocean
assumed steady-state deep ocean MASS BALANCE: (A-A i^C-DCX: X A[DOC])^^„,^^^, + (A-A •^C-DOC x A[DOC]),^^,„„p^en, = (A-A i^C-DOC X A[DOC])„id.gy^ = 0 at steady-state
Figure 12 Conceptual model of two-component steady-state inputs of margin-derived and surfaceocean-derived DOC to the deep open ocean. See section V.D of text for details.
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margins and the surface ocean may represent sources of DOC to the deep central gyres (Table VIII). Bauer and Druffel (1998) estimated by ^"^C mass balance the relative potential contributions of each of these sources to the deep North Atlantic and Pacific using the following simplifying assumptions: (a) the deep central North Atlantic and Pacific are in steady state with respect to A^'^C values and concentrations of DOC (Williams and Druffel, 1987; Bauer et al, 1992a; Druffel et al, 1992); (b) the two dominant sources of DOC to the deep central gyres are lateral inputs of ^^C-depleted material derived from the margins and vertical inputs of "modem," ^^C-enriched material derived from surface ocean production (Druffel et al, 1996); and (c) the margin-to-deep open ocean and surface-to-deep open ocean gradients observed in these studies are representative of the North Atlantic and Pacific as a whole. We find that in order to maintain the observed average A^^C-DOC values in the deep central gyres, the input of DOC from the margins is calculated to be as much as 25-100 times that of modem, surface ocean-derived carbon (Table VIII). These estimates of margin and surface ocean contributions to the deep open ocean have two main implications. First, inputs of "aged" DOC from the margins to the deep open ocean may surpass inputs derived from recent surface ocean production. Second, in view of the much larger surfaceto-deep vs margin-to-deep concentration gradients, the vast majority of young, surface-derived material must be degraded, allowing a smaller but more highly refractory margin component to contribute proportionally more to the deep central gyres. Although no a priori assumptions are made in these estimates about the specific mechanisms promoting horizontal exchanges from the margins, transport of ^^C-depleted DOC from ocean margins to the central gyres may be facilitated by isopycnal (i.e., lateral) eddy diffusion, which can be 10^-10^ times greater than vertical eddy diffusive transport (Knauss, 1978). The isotopic signatures of DOC at the coastal/open ocean boundaries (i.e., slope and rise waters) indicate that this carbon has a mainly nonrecent marine origin and is older than organic carbon from the North Atlantic and North Pacific central gyres. If this material propagates seaward, possibly along isopycnal surfaces, it may represent a source of old DOC to intermediate and deep waters of the interior ocean (WoUast, 1991,1998). Alternative mechanisms such as overtuming circulation in regions of intermediate and deep-water formation have been proposed for transporting surface ocean DOC to the deep central gyres and are discussed in detail in Hansell and Carlson (1998), Hansen et al in press) and Hansell (Chapter 15).
VL SUMMARY AND FUTURE CHALLENGES This review and synthesis of the available information on the isotopic (^"^C and ^^C) composition of DOC in open-ocean and ocean-margin environments demonstrates that both of these isotopes can provide useful information on the sources
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and ages of DOC. ^"^C and ^^C constitute powerful tracers of DOC sources and cycling times in both types of environment, especially when used in conjunction with one another, or with other source and age parameters (e.g., salinity, C/N, A^^^C-DIC, etc.). In spite of the invaluable utility of ^"^C and ^^C in studies of ocean DOC cycling, the vast majority of measurements to date have been made on bulk or total pools of DOC, or on operationally defined subfractions such as humic substances or UDOM. There is presently a fundamental need for information in marine organic isotope geochemistry on the sources and ages of DOC to oceanic and coastal waters, and for understanding the internal factors responsible for altering the isotopic and biochemical composition of DOC in marine waters during its transformation and aging. In order to obtain more information on these topics, we propose the following suggested areas of future research on the natural isotopic characterization of DOC in the oceans: (i) Assessing ^"^C and ^^C in autochthonous marine sources of DOC, including, but not limited to, living planktonic biomass, sediment porewaters, and solubilized and degrading sinking POC (e.g., from sediments trap studies). (ii) Evaluating the magnitudes of allochthonous inputs on oceanic distributions of ^"^C and ^^C, including, but not limited to, terrestrial inputs and atmospheric deposition (including the role of black carbon and both natural and anthropogenic hydrocarbons); better characterization of terrestrial, riverine, and estuarine isotopic source signatures; and alterations in the ^"^C and ^^C signatures of terrestrial and riverine DOC in estuaries and the coastal ocean. (iii) Studies of the effects of both biotic and abiotic factors controlling ^"^C and ^^C distributions in DOC. Such factors include changes in ^"^C and ^^C contents during DOC degradation by heterotrophic bacteria due to both preferential utilization of more labile constituents and isotopic fractionation and the potential role of abiotic factors such as sorption, desorption, photolysis, etc. (iv) Evaluating inputs of young, labile DOC to the deep ocean by "shortcircuiting" due to intermediate and deep water formation. (v) Further partitioning and isotopic characterization of the constituents of DOC and UDOC, utilizing compound-class and compound-specific separation techniques and ^^C and ^^C isotopic analyses. Although these techniques have so far been applied successfully to studies of sedimentary organic carbon and POC, they have only recently been extended to studies of marine DOC cycling (Aluwihare, 1999), and it is anticipated that there will be an expansion of such studies in the near future.
ACKNOWLEDGEMENTS I thank numerous individuals for their encouragement, hard work, and coUegiality during the course of this research over the years, foremost among them Drs. Peter M. WilHams and Ellen
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R. M. Druffel. Others in our research groups who made possible our own work in the area of organic isotope geochemistry include Dave Wolgast, Ken Robertson, Sheila Griffin, Pete Raymond, Ai Ning Loh, Jennifer Cherrier, Carrie Masiello, Mark Schrope, and Eva Bailey. Michaele Kashgarian and John Southon of the Center for Accelerator Mass Spectrometry, Lawrence Livermore National Laboratory, were instrumental in making available resources and facilities for AMS A^^C analyses, and Eben Franks performed S^^C analyses. I also thank the captains and crews of a number of UNOLS vessels for helping with the logistics necessary to conduct the fieldwork, including RA^'s Melville, Knorr, New Horizon, Seward Johnson, Endeavor, Columbus Iselin, and others. This work was supported primarily by the Chemical Oceanography Program of the U.S. National Science Foundation and the U.S. Department of Energy's Ocean Margins Program.
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Chapter 9
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus Kenneth M o p p e r
D a v i d J. Kieber
Department of Chemistry and Biochemistry Old Dominion University Norfolk, Virginia
College of Environmental Science and Forestry Chemistry Department State University of New York Syracuse, New York
I. Introduction II. Photochemical Transformation of Riverine and Marsh-Derived DOM Inputs to the Sea III. Impact of Photochemistry on Elemental Cycles A. Carbon B. Sulfur C. Nitrogen and Phosphorus IV. Unresolved Questions and Future Research A. Mechanistic Studies B. Photoproduction and Air-Sea
Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
Exchange of Important Atmospheric Trace Gases C. DOM Photochemistry and Marine Food Web Dynamics D. DOM Photochemical Reactions Involving Trace Elements E. Extrapolating Photochemical Rates to Global Scales References Appendix 1 Appendix 2 Appendix 3 Appendix 4
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I. INTRODUCTION Dissolved organic matter (DOM) plays a dominant role in the absorption of ultraviolet (UV) and visible light in the open ocean (Nelson et al, 1998; Siegel et al, 2002). As DOM absorbance is regulated in part by photobleaching processes (Vodacek et al, 1997; see Blough and Del Vecchio, Chapter 10), hght availability for photosynthesis and the penetration of UV radiation within the marine environment are influenced by photochemical transformations. In addition to its control on UV light fields, DOM photochemistry strongly impacts the biogeochemical cycling of biologically important elements in surface seawater and, via conversion of DOM into volatile species such as carbonyl sulfide, it influences atmospheric chemistry and climate. An example of important light-driven chemical reactions in the photic zone include the reduction of trace metals like iron, manganese, and copper (Blough and Zepp, 1995; see Wells, Chapter 7). The chemistry of these reduced species is quite different from their oxidized counterparts. Photochemical oxidation of DOM also produces a suite of free radicals and other short-lived species including the superoxide anion, carbonate radical, singlet oxygen, hydroxyl radical, dibromide radical anion, and a number of poorly described organic radicals and excited state triplets. These species are much more reactive than their corresponding diamagnetic and ground state species, and are expected to influence biological and chemical processes in sunlit surface waters. Furthermore, DOM photolysis is an important source or sink of a variety of atmospherically important gases that are emitted from the ocean, some of which affect the Earth's radiative balance. Concentrations, and hence emissions, of carbon monoxide (CO), carbon dioxide (CO2), carbonyl sulfide (OCS), and dimethyl sulfide (DMS) are all partly regulated through photochemical processes involving DOM. Photochemical reactions result in the partial remineralization of DOM in the oceans, thereby playing an important role in carbon, nitrogen, sulfur and phosphorus cycling in the photic zone. Photoreactions also alter the bioavailability of refractory DOM. Incomplete oxidation of biologically recalcitrant DOM yields substrates (and nutrients) to marine bacteria, thereby injecting extra "fuel" into the food web. However, this oceanic photochemical/biological couple is poorly constrained, and it is complicated because photoreactions may destroy as well as form biological substrates (Kieber, 2000). Nonetheless, this coupled pathway may be a major sink for riverine DOM and an important control over the geochemical cycling of refractory DOM found in the deep sea (Mopper and Kieber, 2000). Photochemical transformations in seawater are controlled by the absorption of sunlight by DOM, which results in the formation of excited state species. Decay of this absorbed energy occurs through competing photophysical and photochemical pathways, as discussed in numerous reviews (e.g., Blough, 1997; Clark and Zika,
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2000; Whitehead and de Mora, 2000). For most components of DOM, only UV and blue light are energetic enough to promote photochemical transformations; however, most of this absorbed energy is dissipated as heat (Zika, 1981). The efficiency of a photochemical process, known as the quantum yield, is a unitless ratio equal to the number of moles of species formed or photolyzed divided by the moles of photons (Einsteins) absorbed by the chromophore. Often the chromophore giving rise to a phototransient or product is not known, in which case the photoefficiency is related to the total number of photons absorbed by DOM and the term apparent quantum yield is applied. The quantum yield is a fundamental parameter needed to quantify and model photochemical processes in seawater. This is because the rate of a photoreaction is equal to the product of the quantum yield for that reaction and the specific rate of light absorption. The fundamental equations used to describe primary and secondary photochemical reactions, and their application to aquatic systems are described elsewhere (Blough, 1997; Miller, 1998; Faust, 1999; Whitehead and de Mora, 2000) and will not be detailed here. In addition, evaluation of errors associated with quantum yield determinations and with the assumption that quantum yields are constant with photon exposure (i.e., irradiance integrated over time of exposure) is discussed in a recent review (Neale and Kieber, 2000). Understanding and evaluating these errors and assumptions is key to accurately modeling photochemical processes in seawater on a global scale. This review focuses on the impact of photochemistry on the biogeochemical cycles of carbon, sulfur, nitrogen, and phosphorus, highlighting and evaluating recent advances and areas for future work. Although photochemical reactions also impact trace metal cycling in seawater, this topic is discussed in detail elsewhere (Blough and Zepp, 1995; Faust, 1999) and will not be reviewed here. Likewise, analytical techniques (Zafiriou^f^/., 1990; Blough and Zepp, 1995; Miller, 1998), marine optics (Kirk, 1994; Mobley, 1994), and photoinhibition of biological processes (de Mora et ah, 2000), although important, are not covered here because they have been critically evaluated elsewhere.
IL PHOTOCHEMICAL TRANSFORMATION OF RIVERINE AND MARSH-DERIVED DOM INPUTS TO THE SEA Riverine dissolved organic carbon (DOC) shows a generally conservative behavior during estuarine mixing, with flocculation accounting for only a small fraction of its removal (Sholkovitz, 1976; Mantoura and Woodward, 1983; Dister and Zafiriou, 1993; Guo et al, 1995; Amon and Benner, 1996; Opsahl and Benner, 1997; Del Castillo et al, 2000). Thus, in the absence of removal processes, riverine DOC would be expected to accumulate in the sea (Denser, 1988; Hedges et al,
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1992). However, the contribution of riverine DOM to the oceanic DOM pool is negligible (Meyers-Schulte and Hedges, 1986; Druffel et al, 1989; Opsahl and Benner, 1997; Hedges et ai, 1997). Photochemical processes appear to be important in the degradation of riverine DOM in the sea (Kieber et al, 1990; Zuo and Jones, 1995; Zuo et aL, 1998; Amon and Benner, 1996). Riverine DOM has been shown to be photochemically reactive, with high rates of DOC and O2 consumption (Amon and Benner, 1996; Moran et al, 2000), as well as high rates of free radical and singlet oxygen production (Dister and Zafiriou, 1993; HolderSandvik et al, 2000). This photoreactivity results in a loss of chromophores, as evidenced by rapid photobleaching of optical absorbance (Vodacek et al, 1997; Gao and Zepp, 1998; Moran et ai, 2000) and rapid loss and alteration of dissolved lignin phenolic compounds (Opsahl and Benner, 1998; Benner and Opsahl, 2001). Although high rates of photolysis and photobleaching are experimentally observed in marsh-derived andriverinewaters, photodegradation of DOM may be lower than expected within estuaries due to the shallow UV optical depth relative to the depth of the surface mixed layer. Therefore, photochemical effects such as photobleaching may not be observed until the riverine water is sufficiently diluted with the lower DOM-containing and light-absorbing oceanic end member (Kieber et al, 1990; Vodacek et ai, 1997). The main photodegradation products that have been identified in riverine and marsh-derived DOM are CO and CO2 (Miller and Zepp, 1995; Zuo and Jones, 1995; Zuo et al, 1998; Miller and Moran, 1997; Gao and Zepp, 1998), which account for the bulk of the DOC loss. Other products include low-molecular-weight (LMW) carbonyl compounds (Kieber et ai, 1990), nitrogenous compounds (Bushaw et al, 1996; Bushaw-Newton and Moran, 1999; Kieber et ai, 1999a; Gao and Zepp, 1998), and probably LMW carboxylic acids (Bertilsson and Tranvik, 1998). Microbes readily consume many photodegradation products, which increases the rate of removal of riverine and marsh-derived DOM in the sea (Kieber et al, 1990; MormetaL, 1999).
III. IMPACT OF PHOTOCHEMISTRY ON ELEMENTAL CYCLES A. CARBON During the past decade, there has been an exponential increase in the number of studies focusing on the role of DOM photolysis on aquatic carbon cycling. Many of these studies are tabulated in Appendices 1-4. In addition to the main findings, these tables sunmiarize sampling and experimental protocols (e.g., irradiation conditions), which were often widely different and made direct comparison of the results difficult. Two photochemical, oxidation/degradation pathways of
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus DOM have been identified in these studies: an abiotic pathway, involving the direct photochemical production of CO and CO2, and a sequential photochemical/biotic pathway, involving the photodegradation of DOM to LMW substrates followed by microbial uptake and conversion of these substrates into biomass and CO2. Together these two pathways can accelerate both removal of terrestrially derived DOM in coastal waters (Kieber et ai, 1990; Miller and Zepp, 1995; Amon and Benner, 1996; Miller and Moran, 1997; Moran et al, 2000; Mopper and Kieber, 2000; Kieber, 2000) and the geochemical turnover of isotopically old DOM (Mopper et al, 1991; Anderson and Williams, 1999; Mopper and Kieber, 2000). Cherrier et al (1999) reported the presence of isotopically old carbon (}^CI^'^C) in bacteria from open oceanic surface water, and suggested that photoreactions were responsible for increasing the bioavailability and cycling of old, biorefractory DOC. The quantitative importance of coupled biological-photochemical pathways for DOM photoremineralization was demonstrated by Miller and Moran (1997). They determined that the percentage of terrestrially derived DOC in coastal waters utilized by heterotrophs (i.e., incorporated plus respired) as a result of DOM photodegradation was approximately equal to the direct (abiotic) photoproduction of CO and CO2 in those samples. Miller and Zepp (1995) found that the photoproduction of CO and CO2 was approximately 10-15% of DOC in various freshwater and coastal seawater samples. Combining these results suggests that at least 20-30% of terrestrially derived DOC in coastal waters can be rapidly photodegraded and consumed, which underscores the importance of the two DOM photodegradation pathways to carbon cycling in the sea. Further support for this remineralization hypothesis comes from recent lake studies (e.g., Reitner ^?a/., 1997; Bertilsson and Tranvik, 2000; Lindell et al, 2000; Tranvik et al, 2000). The major findings and conclusions from these lake studies are expected to be applicable to marine waters despite the generally higher DOM concentration and turnover in lakes. Therefore, results of lake studies will be mentioned in this chapter when appropriate.
1. Sequential Photochemical-Microbial DOC Degradation Strome and Miller (1978) hypothesized that the degradation of DOM in lakes by solar irradiation could stimulate bacterial growth. This hypothesis was supported by Geller (1986), who performed experiments with extracted and irradiated lacustrine DOM that was inoculated with bacterial isolates. Kieber et al (1989) extended this hypothesis to coastal ocean waters by showing that there was a strong correlation between the photochemical production of pyruvate and its microbial utilization. In addition to providing carbon substrates (e.g., pyruvate), photochemical reactions may enhance microbial activity through a variety of other pathways, for example, by increasing the availability of essential trace metals (e.g..
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iron, copper and manganese) via production or destruction of organic ligands and altering the trace metal redox state/solubility (see Wells, Chapter 7), by release of major nutrients such as nitrogen and phosphorus (Bushaw-Newton and Moran, 1999; Tranvik et ai, 2000), by reactivation of enzymes bound to humic substances (i.e., by photolytic cleavage of humic-enzyme complexes; Wetzel et ai, 1995), by depolymerization of biopolymers such as polysaccharides (Kovac et al, 1998), and by destruction of inhibitory substances such as acrylic acid (Bajt et al, 1997). Thus, photochemical reactions involving DOM can be quite important in food web dynamics, as pointed out in numerous recent reviews (DeHaan, 1992; Crosby, 1994; Moran and Zepp, 1997; Zepp, 1997; Ehrhardt, 1997; Tranvik, 1992, 1998; Zepp etal, 1998; Sulzberger, 2000; Clark and Zika, 2000; Moran and Zepp, 2000; Williams, 2000; Benner and Ziegler, 2000; Miller, 2000; Kieber, 2000; Mopper and Kieber, 2000; Moran and Covert, 2001). Experimental details of individual studies are summarized in Appendices 1-3. Most of these studies have focused on the effects of photochemistry on microbial production (vide infra). Typical experiments to evaluate the sequential photochemical-microbial degradation pathway are performed as follows: a natural water sample is sterile-filtered, transferred to irradiation vessels (usually quartz glass, but for a few studies borosilicate glass or UV-transparent or semitransparent plastic), irradiated for several hours to days in natural or simulated sunlight, inoculated with bacteria (usually isolated from the same sample or from water from a similar depth, but sometimes from other sources such as purified cultures), and incubated in the dark for several hours to several days. Finally, the net effect on microbial activity is measured relative to controls (i.e., samples incubated with nonirradiated water). In related experiments, specific DOM components are added to sterile-filtered water in order to determine the effect of irradiation on microbial utilization of the added component. These components include solid phase-extracted humic substances, size-fractionated DOM, algal extracts/exudates, higher plant leachates (aquatic and terrestrial), and biochemicals (proteins, amino acids, glucose). In these experiments, the controls are usually unamended irradiated samples and dark controls. In a third type of experiment, unfiltered samples are irradiated with the microbial community present to determine the net effect of all light-related processes, in particular direct UV inhibition (e.g., in vivo damage to DNA) and ambient photochemical reactions (e.g., production/destruction of substrates), on microbial activity. However, because of this experimental design, it is not possible to evaluate the contribution of DOM photodegradation to the overall change in biological activity. Various techniques have been employed to evaluate the effects of DOM photochemistry on microbial activity. The most conmion approach is to determine the change in bacterial production based on the uptake of radiolabeled leucine or thymidine. Other approaches include measuring bacterial biomass, bacterial growth (cell number or density), incorporation of specific radiolabeled substrates
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus (e.g., pyruvate, glucose), respiration (O2 consumption and/or DIC production), and DOC loss (due to respiration and biomass formation). A few studies used multiple techniques. These different approaches are summarized in Appendices 1-3, grouped according to whether the study reported positive, negative, or mixed effects of DOM irradiation on microbial activity. Most studies have reported positive effects (Appendix 1), which supports the simple concept that the uptake of photochemically degraded DOM and other photoproducts stimulates bacterial growth. Studies with positive effects can be further separated into two types based on their experimental design. In the most conmion design, humic-rich, terrestrial DOM was photolyzed and the effect on microbial activity was measured directly. In the second type of experiment, a positive effect on microbial growth was inferred from the photochemical formation of specific substrates and, in some cases, simultaneously following their uptake (using radiolabeled substrates). Although the majority of studies have yielded positive effects, several studies (Appendix 2) have suggested that the photochemicalbiological couple is more complicated because photochemistry can destroy as well as form biological substrates. Abiotic cross-linking and humification of labile biomolecules, such as proteins, unsaturated lipids, polysaccharides, fresh algal extracts or exudates, and fresh macrophyte leachates can occur in the dark (Brophy and Carlson, 1989; Tranvik, 1993; Keil and Kirchman, 1994; Thomas and Lara, 1995), but are enhanced by irradiation (see references in Appendix 2) and high concentrations of DOM, as encountered in humic-rich fresh waters, estuarine waters, or adjoining coastal waters. Thus, depending on the net effect of destruction versus formation of substrates, DOM photodegradation can stimulate, inhibit, or have no effect on microbial growth (Appendix 3). Benner and Biddanda (1998) hypothesized that recently produced, algal-derived DOM (which mainly occurs in surface waters) becomes less available, while older, humic-rich DOM (that is dominant in upwelled deep waters) becomes more available to bacteria after photochemical degradation. Therefore, the net effect of photochemistry on microbial growth may depend on the relative proportions of these two DOM types in the irradiated sample. Results of subsequent field and laboratory studies are consistent with this hypothesis (Obemosterer et al, 1999a; Bertilsson, 1999; Benner and Ziegler, 2000; Hemdl et al, 2000; Reitner et al, 2002). The most compelHng evidence in support of this hypothesis comes from a study of over 30 lakes, in which Tranvik et al (2000) and Tranvik and Bertilsson (2001) were able to successfully model the degree of photochemical stimulation or inhibition of microbial activity using the relative proportions of fresh algal-derived DOM (based on Chi a) versus older humic DOM. While changes in the relative importance of substrate photoproduction versus photodestruction were likely responsible for the contrasting results found in a number of studies (Appendies 1-3), other factors may have also been important. These include photochemical production of inhibitory substances such as hydrogen
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peroxide (Gjessing and Kallqvist, 1991; Lund and Hongve, 1994; Mopper et al, 2000; Farjalla et ai, 2001), photolysis of DOM to form substances that are both biologically and photochemically refractory (Kieber, 2000), changes in bacterial growth efficiency (BGE), and differences in carbon/nutrient status among different waters. Based on their results in the Amazon River basin, Amon and Benner (1996) concluded that photoproduction of substrates has a much greater impact on bacteria growing under carbon limited conditions compared to carbon replete conditions. Changes in BGE may be more important than currently recognized (Jahnke and Craven, 1995; del Giorgio and Cole, 2000; WiUiams, 2000; Carlson, Chapter 4). The BGE is usually expressed as the fraction of carbon incorporated relative to total uptake (i.e., incorporated/(incorporated + respired)). In most studies, the impact of photochemistry on bacterial activity was evaluated by measuring only the change in bacterial carbon production, usually by incorporation of radiolabeled thymidine and/or leucine, or by direct counting of bacterial abundance and converting to biomass (Appendices 1-3). However, bacterial production gives an incomplete picture of the amount of total carbon taken up because it accounts for only the fraction that is incorporated into biomass, which is usually a minor fraction of the total photochemically derived carbon uptake. Most of the assimilated carbon is respired to CO2 to provide energy needed for cell maintenance and growth. The percentage respired varies greatly in bacteria, but in the open ocean it is generally about 80-95% and about 60-75% of total carbon uptake in open ocean and coastal waters, respectively (del Giorgio and Cole, 2000). Factors controlling the BGE in marine bacterial assemblages are not well understood, but are likely related to environmental and physiological conditions and to substrate quality (del Giorgio and Cole, 2000; Williams, 2000; Carlson, Chapter 4). For example, DOM photodegradation produces LMW substrates that are more oxidized than the precursor molecules. Oxidized substrates (e.g., LMW organic acids) are utilized less efficiently by bacteria than energy-rich substrates (del Giorgio and Cole, 2000). This factor alone may cause a significant decrease in the BGE, even if no shift in the actively growing bacterial population occurs. However, shifts in BGE can also occur as a result of changes in the bacterial population because the latter is a complex assemblage of microorganisms in varying growth states and with different substrate affinities. Photochemical changes in substrate concentrations and types can potentially cause a shift in the actively growing bacterial population, with a concomitant change in the net BGE (del Giorgio and Cole, 2000). It is likely that both factors (i.e., oxidation state of the substrates and shift in assemblage composition) played a role in the wide range of responses sunmiarized in Appendices 1-3. However, since only bacterial production/biomass was measured in most studies, it is not possible to conclude if the net effect of DOM photodegradation was stimulatory or inhibitory because the BGE was usually not monitored, or simply assumed to be constant (Appendices 1-3). When measured, BGE shifted
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to either higher or lower values in irradiated samples and never remained constant (Appendices 1-3). Decreases in BGE were due to increased respiration relative to incorporation (Vahatalo and Salonen, 1996; Anesio et al, 2000; Farjalla et al, 2001). All irradiation studies that included BGE measurements were conducted with freshwater samples or with isolated DOM components added to deionized water (Appendices 1-3). No studies have been reported for marine samples. We recently carried out experiments at sea to address this complex problem. Microbial production rates were determined from measurements of ^H-thymidine and ^"^C-leucine incorporation, with and without added cold and ^^C-labeled glucose. Respiration (oxygen consumption) was measured in parallel. Results of these preliminary seawater experiments suggest that both carbon limitation and shifts in BGE are important factors in controlling the microbial response to photochemically produced substrates. Incubating coastal seawater with deck-irradiated, sterile-filtered coastal surface water in the dark significantly increased the rate of respiration relative to the dark control (Fig. 1). After the initial time point, the respiration rate for the sample containing irradiated DOM was initially 1.4 times higher than the dark sample, increasing to 1.7 times higher at the end of the incubation. This increase suggests that substrate supply in the dark control decreased at a greater rate than samples containing photodegraded DOM. That is, the latter
Incubation Time (h) 6
12
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o
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-5.0 Figure 1 Microbial respiration in unfiltered surface water during dark incubation with deck irradiated 0.2-)Ltm-filtered surface water (2 parts unfiltered water to 1 part irradiated filtered water) relative to the unirradiated dark control. Both filtered and unfiltered samples were from a depth of 10 m at a site about 2 km off the mouth of the Delaware Bay, June 2000.
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apparently contained sufficient concentrations of new substrates to maintain high respiration rates even after 12 h of growth. Photodegradation of DOM increased respiration rates by 0.15 /xM CO2 h"^ which is comparable to the abiotic CO2 photoproduction rate measured in the same waters (Kieber etai, 2001). Combining abiotic CO2 photoproduction with photochemically enhanced microbial respiration yielded an increase in the rate of carbon cycling of about 3-5 fiM C day~^ at this coastal station. DOC concentrations of 80-100 /xM C at this site yields DOC turnover times of 16-33 days. These results indicate that photochemical degradation can significantly impact carbon cycling in coastal surface waters. This finding is consistent with results from photobleaching studies in the same sampling region (Vodacek et al, 1997) and photoremineralization studies conducted in DOM-rich (and DOM-augmented) fresh waters and estuarine waters (Miller and Zepp, 1995; Miller and Moran, 1997) and modeling studies in oceanic and estuarine waters based on extrapolation of CO photoproduction rates (Stubbins, 2001). While respiration was clearly enhanced in the above coastal study, microbial production (as measured by both leucine and thymidine incorporation methods) decreased by about 20% in irradiated surface samples relative to dark controls (Mopper et ai, unpublished results). Based on the production results alone, one would conclude that photochemistry negatively impacted microbial carbon utilization. However, when the respiration results are also considered, the overall effect was that photochemistry positively impacted bacterial carbon utilization. Our study also demonstrated that BGE is not constant as often assumed (see review by del Giorgio and Cole, 2000). Instead, the BGE shifted to lower values in the irradiated samples due to enhancement of respiration over production, as observed in some freshwater studies (Vahatalo and Salonen, 1996; Anesio etal, 2000; Faijalla etai, 2001). The photochemical effect on bacterial activity is dominated by its effect on respiration, since respiration generally accounts for the largest fraction of bacterial carbon demand (del Giorgio and Cole, 2000; WiUiams, 2000). Given the overall importance of respiration, it is inappropriate to use bacterial production measurements alone to assess the effect of DOM photodegradation on bacterial activity. These findings also suggest that conclusions from many past uptake studies regarding the net photodestruction of substrates or photochemical formation of biologically recalcitrant humic substances from substrates may need to be reevaluated. A further complication with bacterial production measurements was revealed in glucose addition experiments that addressed carbon limitation. Surprisingly, it was often observed that glucose additions had either no effect or caused a significant decrease in leucine and thymidine incorporation (Fig. 2A), even though glucose was clearly taken up (Fig. 2B). A lack of effect of glucose additions on the growth of planktonic bacteria has been previously observed (Kirchman, 1990; Pomeroy etai, 1995; Carlson et ai, 1999). In the case of decreased incorporation, it is possible that the added glucose stimulated the internal production of leucine and thymidine, thereby diluting the radiolabel, which would result in an apparent decrease in
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0.35 -"* 0.30 1 0-25
i ^
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0.15 4 0.10 20
40 60 glucose (nM)
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40 60 "C- glucose (nM)
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Figure 2 (A) Effect of glucose additions on the microbial uptake of radiolabeled thymidine and leucine. Unfiltered samples were from a depth of 10 m at a site about 2 km off the mouth of the Delaware Bay, June 2000. Thymidine and leucine uptake rates were measured according to Smith and Azam (1992) and converted to apparent productivities according to Kirchman (1990) and Kirchman and Rich (1997). (B) Community uptake of uniformly radiolabeled glucose (^"^C) as a function of added glucose (in the same seawater sample as A). The saturation curve describes the uptake kinetics (affinity constant K = 6.49 nM), as given by the equation in the figure.
uptake of radiolabel (P. Falkowski, pers. commun., 2001). A similar effect was found for pyruvate in Antarctic waters (Mopper et al, unpublished results). Since pyruvate is a photochemically produced substrate (Kieber et al, 1989), the question arises as to whether the apparent "inhibition" effects reported in several studies (e.g., decreased microbial production after irradiation; Appendices 2 and 3) may be partly (or totally) due to the photochemical production of substrates that, after being taken up, stimulate the internal production of leucine or thymidine. Clearly, this question needs to be addressed in future studies.
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2. Dissolved Inorganic Carbon Formation and Oxygen Consumption While it has been known for some time that photolysis of DOM yields LMW organic products (see review by Kieber, 2000), it has only recently been shown that the major photoproducts are inorganic species, in particular CO and dissolved inorganic carbon (DIC) (Mopper et ai, 1991; Miller and Zepp, 1995; Bates et al, 1995; Zuo and Jones, 1995; Stubbins, 2001). Photochemical DIC formation may strongly impact carbon cycling in seawater and other natural waters (Miller and Zepp, 1995; Miller and Moran, 1997; Kieber et al, 1999a, 2001; Lindell et al, 2000). In addition, this process may be responsible for a major fraction of abiotic oxygen consumption in irradiated surface waters (Lindell and Rai, 1994). However, photochemical formation pathways of DIC and how they are linked to oxygen consumption are not understood. Evidence supports two main routes for DIC production from DOM: one by oxygen-independent pathways (e.g., direct decarboxylation) and the other by reaction with molecular oxygen and/or reactive oxygen transients (Appendix 4). In support of the latter pathway. Miles and Brezonik (1981) proposed a decarboxylation mechanism that involves the consumption of molecular oxygen, i.e., 1 mol of molecular oxygen consumed per 2 mol of CO2 produced, which is close to the ratio measured in their study. In contrast, Lindell and Rai (1994) and Amon and Benner (1996) found a molar O2 consumption to CO2 evolution ratio close to one for lake waters and river waters, respectively. Despite this close mass balance, it cannot be concluded from these studies that photochemical production of CO2 is dependent on the photoconsumption of molecular O2. Indirect evidence for this dependency comes from Lindell et al (2000), who found no DIC photoproduction from continuously irradiated DOM-rich water samples after reaching 25% or less O2 saturation resulting from photochemical O2 consumption. However, it is not clear whether the drop in DIC production was due mainly to the drop in O2 partial pressure or to the photodestruction (photobleaching) of precursors, as has been demonstrated for CO (Stubbins, 2001). The above studies suggest that molecular oxygen is required for DIC photoproduction. However, this mechanism is not consistent with the finding that DIC photoproduction in sterile filtered coastal seawater either did not change or increased by about 35% after molecular oxygen was removed by exhaustive sparging with oxygen-free helium (Kieber et al, 1999a, 2001). Furthermore, the existing experimental results are not consistent with the amount of O2 required for all purported oxidative processes. For example, about 50 to 100% of all photochemically consumed oxygen is required for the production of H2O2 via dismutation of superoxide (Petasne and Zika, 1987; Blough and Zepp, 1995; Blough and Caron, 1995; Andrews et al, 2000) and for DOM oxidation (Blough and Zepp, 1995). Presumably, this oxygen would not be available for DIC formation. The latter studies suggest that DIC may be photochemically formed from DOM by
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus oxygen-free pathways, e.g., by cleavage of carboxyl groups from DOM molecules (decarboxylation). A variety of decarboxylation pathways have been identified using model compounds (Budac and Wan, 1992). Some potentially important photochemical mechanisms include cleavage of a carboxyl group attached to an aromatic ring via an intramolecular or intermolecular charge transfer reaction (Budac and Wan, 1992); ligand to metal charge transfer excitation of metal complexes (or chelates) followed by cleavage of the carboxyl group (Langford et al, 1973); OH radical-induced decarboxylation of amino acids (Steffen et al, 1991) and organic acids (Zafiriou, 1990); photolysis of aromatic rings followed by decarboxylation of ring cleavage products (Chen et al, 1978; Vahatalo et al, 1999); and photolysis of LMW organic acids (Bockman et al, 1996) such as pyruvate, glyoxylate (Kieber, 1988; Klementova and Wagnerova, 1990) and oxalate (Bertilsson and Tranvik, 1998). The latter mechanism may involve photosensitized oxidation (Klementova and Wagnerova, 1990). If Die photoproduction from DOM occurs mainly by direct decarboxylation (as opposed to oxygen-dependent pathways), one might expect DIC photoproduction to be highly correlated to DOM carboxyl content. However, Mopper et al (2000), in a study of DIC photoproduction by humic substances added to fresh water, found that the only strong correlation was with aromaticity and not with total carboxyl carbon. The correlation of DIC photoproduction with aromaticity suggests that carboxyl groups attached to aromatic rings are preferentially cleaved off the ring to form CO2, which is consistent with studies of model compounds (Budac and Wan, 1992). This mechanism is also consistent with IR spectroscopic results for fulvic acids that showed that the carboxyl signal associated with aromatic groups is preferentially lost during UV irradiation of aqueous solutions, while the aliphatic carboxyl signal increased and the fulvic acids became more oxidized and less aromatic (Chen et al, 1978). Similar results were obtained by solid-phase ^^C and two-dimensional NMR analyses of photolyzed aqueous fulvic and humic substance solutions (Kulovaara et al, 1996; Schmitt-Koplin et al, 1998). Thus, the above studies further support the idea that photochemical DIC production is largely independent of photochemical molecular oxygen consumption. It is clear from these conflicting reports that the major pathways involved in DIC photoproduction, and their relationship to DOM photooxidation and oxygen consumption in seawater and other natural waters, need further study. B, SULFUR Organic sulfur compounds are present in seawater at low concentrations, typically in the 10~^^-10~^ M range, due to close coupling between production and removal processes that include uptake and release by biota, thermal reactions, and photochemical reactions. Photochemical transformations are a key component
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of the sulfur cycle in the upper ocean, and an important factor controlling the volatility and efflux of sulfur from the oceans into the atmosphere. In the atmosphere, reduced sulfur species are oxidized to photochemically stable species including sulfuric acid and methane sulfonic acid, a process that results in the formation of cloud condensation nuclei (CCN), which in turn affect the Earth's radiative balance (Charlson ^r a/., 1987). The principal trace sulfur compounds in seawater are dimethyl sulfide (DMS), dimethylsulfoniopropionate (DMSP), carbonyl sulfide (OCS) and dimethyl sulfoxide (DMSO). Other minor species include hydrogen sulfide (H2S), dimethyl disulfide (DMDS), carbon disulfide (CS2), methane thiol (MeS), cysteine, glutathione, phytochelatins and methionine. Many of these compounds are either formed or degraded in seawater through photochemical transformations involving DOM. However, except for disulfides, none of these sulfur compounds absorb solar radiation in seawater and, therefore, they will either be photochemically stable or will photochemically degrade through secondary photochemical pathways involving photosensitizers and/or reactive transients. Sulfur compounds undergo a variety of secondary photochemical transformations in aqueous media, especially alkyl sulfides, disulfides, and thiols. Known reactants for sulfur include the hydroxyl radical, hydrogen peroxide, and singlet oxygen. However, none of these species is quantitatively important in sulfur phototransformations in seawater, as discussed below. 1. Dimethyl Sulfide Dimethyl sulfide is the predominant volatile sulfur species found in surface seawater (Kettle et al, 1999a). Its atmospheric loss and subsequent photooxidation plays an important role in the formation of CCN in the troposphere (Charlson et al, 1987; Andreae etal, 1995). The primary source of DMS is through enzymatic lysis of DMSP, although it is not clear why algae ly se DMSP (Stefels, 2000; Sunda et al, 2001). While DMSP undergoes enzymatic lysis, it does not photolyze in seawater at ambient concentrations (ca. 10~^ M) (Kieber and Kiene, unpublished results). Atmospheric ventilation was originally proposed to be the primary removal pathway for DMS in seawater, but now it is clear that microbial uptake and photochemical degradation often control the removal of this compound in the photic zone (Kieber et al, 1996; Dacey et al, 1998; Simo and Pedros-Alio, 1999). Dimethyl sulfide does not absorb solar radiation in seawater, and therefore its photochemical degradation must involve other photochemically active components in seawater such as chromophoric DOM. In support of this supposition, the photochemical degradation of DMS is highly correlated to the concentration of DOM (Jiao and Kieber, 1996; Brugger et al, 1998), but the role of DOM in the photochemical breakdown of DMS is not known. The photochemical loss of DMS in seawater is pseudo-first-order with respect to DMS concentration (Brimblecombe and Shooter, 1986; Kieber et al, 1996;
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus Brugger et al, 1998). However, at high concentrations of added DMS, observed reaction kinetics approach zero order with respect to DMS. This saturation-type behavior suggests that the photochemical loss of DMS occurs through a binding (or catalytic) mechanism, presumably involving components of DOM (Jiao and Kieber, 1996) and perhaps reactive species that are generated by DOM. The wavelength dependence for the photochemical loss of DMS determined in the equatorial Pacific showed a distinct maximum in the blue at approximately 450 nm (Kieber^r al, 1996). However, because of the extremely low absorbance of this seawater, it was not possible to calculate apparent quantum yields above 400 nm. The maximum at 450 nm is presumably due to a specific, photoactive component in seawater, probably of biological origin, which is not always present in the seawater. Indeed, further wavelength dependence studies in other oceanic waters did not always show the presence of this peak (Kieber et al, unpublished results). Photochemically generated singlet oxygen (^Oi) can be an important oxidant at micromolar levels of DMS (Brimblecombe and Shooter, 1986). However, it is a relatively minor oxidant at ambient DMS and ^02 concentrations, accounting for about 14% of total DMS photochemical loss, as determined from direct DMSO measurements and sodium azide ^02 quencher studies (Kieber et al, 1996). This finding is consistent with calculations that yield a DMS removal rate (or DMSO production rate) of 2.1 x 1 0 - i i M h - \ given 1 x 10-^MDMS,1 x 1 0 - I 3 M 1 O 2 , and a bimolecular rate constant of 5.8 x 10^ M~^ s~^ (Wilkinson et al, 1995). As with singlet oxygen, hydroxyl radical concentrations (ca. 10~^^M) are also too low to effectively remove DMS from seawater, even though the bimolecular rate constant for this reaction is near the diffusion-controlled limit (k= 1.9 x 10^^ M"^ s~^; Buxton et al, 1988). Dimethyl sulfide also reacts with hydrogen peroxide in seawater (ca. k = 0.14 M~^ s~^; Shooter and Brimblecombe, 1989), but at ambient concentrations of DMS and H2O2 (ca. 10"^ and 10~^ M, respectively), reaction rates are too slow (ca. 0.1 x 10~^^ M h~^) to be a significant removal mechanism for DMS in the photic zone. Appreciable rates are expected only when high concentrations of DMS and/or H2O2 are encountered such as may be observed inside an algal cell (Sunda et al, 2001), or possibly during a rain event (Cooper et al, 1987), or under bloom conditions when relatively high H2O2 and DMS concentrations may occur in the water column. Thus, although it is evident that DOM is involved in the photosensitized loss of DMS in seawater, none of the known reactions can account for the observed DMS loss when considered alone or together. Furthermore, the predominant products have not been identified, as DMSO represents less than 15% of the total DMS lost. 2. Dimethyl Sulfoxide Dimethyl sulfoxide is released into seawater through biological processes (Lee et al., 1999), and is produced in seawater through the reaction of DMS with singlet
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oxygen (Brimblecombe and Shooter, 1986; Kieber etal, 1996). Dimethyl sulfide may also react with other reactive oxygen species such as the carbonate radical, which is known to react with organic sulfides (Huang and Mabury, 2000), to form DMSO. Dimethyl sulfoxide cannot undergo direct photolysis in seawater, since it does not absorb actinic radiation (ca. >290 nm). Therefore, if DMSO photochemical loss is observed, it must occur through secondary photochemical pathways. Reaction of DMSO with the hydroxyl radical is too slow to be quantitatively important. Given a bimolecular rate constant of 6.6 x 10^ M~^ s~^ (Buxton et al, 1988) and ambient seawater concentrations of DMSO and the OH radical of 25 X 10"^ M and 1 X 10"^^ M (Mopper and Zhou, 1990; Vaughan and Blough, 1998), respectively, the rate of DMSO loss in surface seawater is only 6 X 10"^^ M h~K Significant rates are expected only at higher concentrations of reactants, which may be encountered, for example, in a marine algal cell containing high DMSR Inside the cell, DMSO may play a role in alleviating cellular OH radical stress (Lee and de Mora, 1999; Sunda et ai, 2001). Based on rate calculations with known reactants and observations by Brimblecombe and Shooter (1986), it is unlikely that DMSO is photochemically degraded in seawater as suggested by Lee et al (1999). Photochemical studies with ambient levels of radiolabeled DMSO are needed to address this question. While there is some uncertainty regarding the photochemical loss of DMSO, it is likely that this nonvolatile compound will be removed from seawater primarily through its microbial uptake, although experimental evidence to support this removal pathway is limited (Kiene and Gerard, 1995; Lee ^r a/.,'1999). 3. Carbonyl Sulfide Carbonyl sulfide is the most stable, naturally occurring sulfur species that is ventilated from the oceans into the atmosphere. It has a lifetime in the troposphere of more than 1 year (Khalil and Rasmussen, 1984) and diffuses into the lower stratosphere, where it is photooxidized to sulfuric acid, giving rise to the Junge aerosol layer (Crutzen, 1976). In seawater, concentrations of OCS are low compared to those of DMS, DMSO and DMSP, ranging from approximately 0.071.2 X 10"^ M in coastal waters to about 0.03 x 10~^ M in the open ocean. Low seawater concentrations of OCS reflect its low production rate in seawater and rapid turnover in the water column. In particular, although OCS is relatively longlived in the troposphere, it is very reactive in seawater due to its rapid hydrolysis to carbon dioxide and hydrogen sulfide (EUiot et al, 1987,1989; Flock and Andreae, 1996). The half-Hfe of OCS in seawater is approximately 2 days ( k = 3.8 x 10"^ s~^) at 298 K. Photochemical loss of OCS is unlikely to be a major sink as OCS does not undergo primary photolysis in seawater and its reaction with known photochemically formed oxidants is very slow, especially when compared to other organic sulfur compounds.
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus Carbonyl sulfide is produced in the photic zone by both thermal and photochemical pathways. Nonphotochemical (thermal) production of OCS involves DOM (Flock et al, 1997), but the mechanism is poorly described. Nonetheless, thermal formation of OCS is an important source for this compound in seawater, comparable to photochemical production rates (Flock and Andreae, 1996; Ulshofer et al, 1996). Nonphotochemical production is presumably the main source of OCS in deep seawater. Photochemical production is an important source of OCS in sunlit surface waters (Ferek and Andreae, 1984), with rates in the 10"^^ M h~^ range (Flock and Andreae, 1996). Photochemical production of OCS involves DOM both as a photosensitizer and as a source of sulfur (Andreae and Ferek, 1992). Mechanistic studies have shown that oxygen-dependent oxidants such as singlet oxygen and the OH radical are not involved in OCS formation (Zepp and Andreae, 1994). A number of model sulfur compounds can generate OCS photochemically, including cysteine, 3-mercaptopropionic acid, glutathione, thiols, sulfides, and DOM itself, while DMSP, DMSO, and dimethylsulfone produce very little OCS (Zepp and Andreae, 1994; Flock et al, 1997). Production rates increase when DOM is added as a photosensitizer (Flock et al, 1997; Uher and Andreae, 1997). Based on these and other published studies, the mechanism for OCS photoproduction is proposed to involve thiyl or sulfhydryl radicals (Flock etal, 1991 \ Pos etal, 1998). However, the source(s) of these radicals is not known. Gun et al. (2000) studied polysulfide formation in Lake Kinneret, and suggested that OCS formation results from the reaction of polysulfide radicals and carbon monoxide. This mechanism may explain the strong correlation between OCS photoproduction and CO concentrations observed in marine waters (Flock et al, 1991 \ Pos et al, 1998). Perhaps the source of thiyl radicals is the photolysis of metal-sulfide complexes through a ligand to metal charge transfer reaction. These complexes are known to occur in seawater (Luther and Tsamakis, 1989), but their stabiHties, especially with respect to photolysis, are not known. Apparent quantum yields for OCS photoproduction decrease exponentially with increasing wavelength in the UV (Zepp and Andreae, 1994; Weiss et al, 1995), yielding a broad solar response curve between 290 and 400 nm with a maximum response centered at approximately 340 nm (Weiss et al, 1995). This trend is similar to that observed for many photochemically generated species in seawater (see Blough, 1997, for review). However, apparent quantum yields for OCS production (ca. 10~^) are generally much lower than observed for other species (ca. lO""*10~^), such as CO, CO2, and hydrogen peroxide, indicating that specific (and minor) components of DOM are precursors to OCS. Apparent quantum yields for OCS photoproduction were generally much higher in the Zepp and Andreae (1994) study in coastal waters (e.g., 7.0 x 10~^ at 330 nm) than those obtained in open oceanic waters by Weiss et al (1995)(e.g., 1.6 x 10~^ at 336 nm). Other than analytical artifacts, the only way to generate these large differences is to invoke
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large differences in the concentration or type of sulfur precursors present in those samples. If OCS apparent quantum yields vary greatly in seawater, then it may be difficult to model water colunm production rates on a global scale, especially when using remotely sensed data for DOM fluorescence or absorbance (Neale and Kieber, 2000). 4. Minor Suljfur Species Carbon disulfide, methane thiol and hydrogen sulfide, present in seawater at 10~^^ M levels, are all involved in photochemical transformations (vide infra). Other reduced sulfur compounds that may also be involved in photochemical transformations in oxic seawater, but which have not been studied, include cysteine, cystine, glutathione, and polysulfides. Carbon disulfide, which is an atmospherically important trace gas, is photochemically produced in surface waters. Apparent quantum yields for CS2 formation decrease exponentially with increasing wavelength from about 14 x 10~^ at 308 nm to 0.2 x 10~^ at 400 nm (Xie et al, 1998). Apparent quantum yields for CS2 formation are orders-of-magnitude lower than those of hydrogen peroxide or Die and they are approximately 25% of corresponding apparent quantum yields for OCS formation (Weiss et ai, 1995). Both cysteine and cystine are efficient precursors of CS2, and the OH radical is likely an important reactant (Xie et al, 1998). Based on field and laboratory evidence, Xie et al (1998) concluded that the mechanisms for CS2 and OCS formation are similar, and that photoproduction was the primary source of CS2 in seawater. Methane thiol and hydrogen sulfide are both removed from seawater through photochemical transformations. Average methane thiol removal rates in the Northeast Atlantic and Aegean Sea were low, 6,7 and 36 x 10"^^ M h ~ \ respectively (Flock and Andreae, 1996). Although the mechanism is not known, the photochemical loss of methane thiol involves binding to DOM possibly through complexation or formation of a thioketal (Kiene et al, unpublished results). The photochemical degradation of hydrogen sulfide followed first-order kinetics in Biscayne Bay, Rorida seawater, with loss rates of 5.1 and 20.2 x 10~^^ M h"^ Photochemical loss of sulfide was independent of dissolved oxygen and involved DOM and possibly a thiyl radical intermediate (Pos et al, 1997). These investigators observed that the rate of sulfide loss did not decrease exponentially with increasing wavelength as observed for most other species in seawater. Rather HS~ loss showed a maximum in the blue region of the solar spectrum (Pos et al, 1997), which was also observed for DMS (Kieber et al, 1996). It is clear from the above studies that photochemical transformations affect many reduced sulfur compounds in seawater, but there is still much that is not known. In particular, the role of iron and other metals in complexing sulfur compounds, especially hydrogen sulfide and thiols, in seawater is poorly understood. Sulfur
Photochemistry and the Cycling of Carbon, Sulfur, Nitrogen and Phosphorus compounds complex very strongly to type B metals, such as iron and copper, to form very strong complexes. Thus, metallo-sulfur complexes are likely to be important in seawater, both in stabilizing sulfur to thermal oxidation and destabilizing sulfur to photochemical oxidation through ligand to metal charge transfer reactions. Other less-known reactants may also be important in sulfur photodegradation in seawater including the carbonate radical, superoxide anion and organic radicals. Systematic studies are needed to quantify and delineate these sulfur phototransformations.
C. NITROGEN AND PHOSPHORUS In comparison to carbon or sulfur, relatively little is known about photochemical transformations of nitrogen and phosphorus in natural waters, and the available information indicates that these transformations are complex. This complexity is evident from the contradictory results that have been reported to date. Bushaw et at. (1996) irradiated whole water or isolated fulvic acid extracts from a boreal pond and a series of high DOM rivers in Georgia (including the Satilla River), with natural sunlight (or artificial light), and measured high rates of NH4" production, ranging from 40 to 370 x 10~^ M h" ^ Photochemical NHJ production was also observed in irradiated Satilla River water employing specific detection of ammonium by HPLC (Kieber, 2000). Gardner et al (1998) conducted a i^NH+ isotope dilution study infilter-sterilizedlake water and found photoproduction rates for ammonium (ca. 200 x 10~^ M h~^) comparable to those obtained by Bushaw et al. (1996). Additionally, Gardner et al. (1998) were also able to detect variable but consistent photochemical loss of the anmionium (2-130 x 10"^ M h"^) in the same water, presumably due to either incorporation into DOM or loss through a secondary photooxidative pathway. The latter finding is consistent with the results of a laboratory study by Kieber et al. (1997), which demonstrated that ammonium is incorporated into humic extracts during photolysis of filtered seawater. The mechanism for ammonium photoproduction (or loss) was not investigated in these studies, but it may involve either the release of bound ammonium or the photochemical breakdown of DOM to form ammonium (e.g., deamination of peptides or amino acids). Kinetic results support the second hypothesis (Zepp, unpublished results). Although a number of studies have observed net photochemical production of ammonium formation in natural waters, there are many reports that show either no photoproduction or a photoinduced loss of NH^ (e.g., Koopmans and Bronk, 2002). Vahatalo and Salonen (1996), J0rgensen et al. (1998), Bertilsson et al. (1999), and Wiegner and Seitzinger (2001) all observed no change in ammonium concentrations when filter-sterilized fresh water was exposed to sunlight, while J0rgensen etal. (1999) observed a 35-82% loss (or no change) of NHj in irradiated
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Baltic Sea water samples. The reasons for these contrasting results are not known, but may be due to inherent differences in the DOM composition among the different water samples and to differences in the relative importance of photoproduction versus photodestruction pathways for anmionium, as suggested by the work of Gardener et al (1998). Alternatively, the contrasting results may reflect differences and limitations in the analytical methodologies used to quantify NH^, or differences in light exposure history of the DOM (Koopmans and Bronk, 2002). As with ammonium, photochemical results for primary amines and amino acids are not consistent (Koopmans and Bronk, 2002). Using a batch fluorometric technique, Bushaw et al (1996) and Bushaw-Newton and Moran (1999) reported photoproduction of primary amines in DOM isolated from the Skidaway and Satilla River samples. By contrast, Kieber and Miller (unpublished results) found no chromatographic (HPLC) evidence for primary amine or amino acid production in a Satilla River fulvic acid isolate above the detection hmit (ca. 10"^^ M), even after 11 h of solar irradiation. J0rgensen et al (1998) also employed HPLC, but in their study, dissolved free amino acids (DFAA) and carbohydrates increased when water from Lake Skarshult was exposed to sunlight. However, the increases in DFAA were small (13-23%), and no information was given regarding changes in specific amino acids. Increases in DFAA concentrations are likely due to their photochemical release from organically bound DOM. In a follow-up study, J0rgensen et al (1999) observed that in some irradiated samples DFAA concentrations increased, while for other samples there was a net decrease (or no change) in DFAA concentrations. Again, no specific compositional changes in the DFAA pool were reported. In a study assessing the effect of sunlight on protein lability, irradiation of seawater with added protein apparently made the protein less available to microorganisms, possibly due to production of refractory DOM with a concomitant loss of labile proteinaceous nitrogen (Keil and Kirchman, 1994). Thus, photoreactions involving DOM may be both a source and a sink of biologically available nitrogen. In related studies, Amador et al (1989,1991) demonstrated that the photolysis of humic-bound organics such as amino acids and aromatic compounds greatly increases the rate and extent that microorganisms degraded these compounds relative to dark controls. They found that only 20% of the ^"^C-labeled glycine in their humic sample was utilized over a 60-day period in the dark. Most of the glycine (ca. 80%) was bound to intermediate and high-molecular-weight humics (>5000 Da) that could not be utilized by the microbes. Following the exposure of humic acid solutions to sunlight, the percentage of glycine that was mineralized by the heterotrophic bacteria in the dark increased to 40-60% of the total. This increase paralleled the increase in the percentage of glycine associated with the LMW humic acid fraction, and is consistent with the finding that only the photochemically formed LMW fraction is mineralized by the bacteria. However, not all humic-bound organics are biologically labile after exposure to sunlight. They
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attributed this incomplete utilization to the formation of photochemically and biologically resistant iV-heterocycles in the humic acids (Amador et al, 1989, 1991). The lack of agreement in DFAA and NHj results has also been seen for other nitrogen compounds. Photoproduction of urea and nitrite have been observed in natural waters (J0rgensen^r a/., 1998, \999\YAthQv et al, 1999b; Jankowski^ra/., 1999; Koopmans and Bronk, 2002). These compounds have also been shown to remain constant or decrease when filter-sterilized samples are exposed to sunHght (Vahatalo and Salonen, 1996; J0rgensen et al, 1999; Kieber et al, 1999b; Jankowski et al, 1999). For nitrite, these differences are expected because nitrite undergoes primary photolysis in seawater (Zafiriou and True, 1979; Zafiriou and Bonneau, 1987) that competes with its photoproduction. In coastal seawater, the rate of direct photolysis of nitrite was approximately 2.3 x 10~^ M h~^ compared to an average photochemical production rate of 4 x 10~^ M h~^ (Kieber et al, 1999b). Photochemical formation of phosphate was first reported by Francko and Heath (1982), who observed that sunhght exposure of DOM-rich, acidic lake water (pH 5.2-5.8) caused the release of phosphate complexed to high-molecular-weight DOM. The rate of release of bound phosphate was shown to be highly correlated to reduction of Fe (III) to Fe (II). Phosphate photoproduction was also observed in a humic-rich lake (Vahatalo and Salonen, 1996). However, the mechanisms underlying phosphate photoproduction are poorly understood (Francko, 1990), and there appears to be a seasonality in the extent of phosphate release (Cotner and Heath, 1990). Photochemically induced increases in dissolved phosphorus levels have not been observed in other systems, including a culture of the marine diatom A. anophagefferens (Gobler et al, 1997) and a freshwater lake sample (J0rgensen^rfl/., 1998). It is somewhat surprising that DOM shows such a diverse photochemical response in natural waters with respect to nitrogen and phosphorus (i.e., no production, production, and loss). It is difficult to reconcile these differences because the photochemical mechanisms underlying these transformations are not understood, even at the most basic level. For example, what is the effect of dissolved oxygen, pH, and temperature on production rates? Are production rates linearly dependent on the photon exposure? What is the observed reaction order? What are the wavelength-dependent apparent quantum yields? Conflicting results may be due to fundamental differences in the DOM among these waters or to variations in the balance between rates of photoproduction and photodestruction. They may also reflect differences in experimental design and analytical artifacts that result from a lack of understanding of the factors that control nitrogen and phosphorus phototransformations in natural waters. Given the wide range of photochemical results that have been obtained for nitrogen and phosphorus, it is difficult to evaluate the overall importance of photochemical transformations on their biogeochemical
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cycling. This is especially true in oligotrophic seawater where no studies have been performed, almost certainly due to analytical limitations.
IV. UNRESOLVED QUESTIONS AND FUTURE RESEARCH Photochemical reactions undoubtedly have an important impact on a variety of marine processes, and potentially play a significant role in the global biogeochemical cycles of carbon, nitrogen, sulfur, and perhaps phosphorus. However, even though there has been an exponential increase in the number of marine photochemical studies over the past decade, many important questions remain unanswered. We conclude this chapter by indicating future research areas, which include developing a mechanistic understanding of photochemical processes, identifying and quantifying the major photochemical fluxes, and extrapolating/ modeling these fluxes to global scales.
A. MECHANISTIC STUDIES
Despite the importance of photochemistry in the surface ocean, relatively few comprehensive mechanistic studies have been carried out, and those that have been conducted have concentrated on identifying reactive transients and on measuring their steady-state concentrations, rate laws, and production rates in seawater (Blough andZepp, 1995; Blough, 1997; Faust, 1999). Details of most photochemical reaction pathways have not been determined and virtually nothing is known about the major reactive sites (or chromophores) within marine DOM that are responsible for the production of reactive transients in the sea. Progress in this area has been inhibited by the lack of sensitive and selective probes suitable for seawater, as well as a lack of studies that track element mass balances resulting from photochemical transformations. For example, can the photochemical loss of DOC in seawater be accounted for mainly by the production of DIC (and CO)? In order to develop a predictive understanding of the rates and controls of important photochemically produced compounds, it will be necessary to identify the DOM precursors and photosensitizers that affect specific photochemical reactions (i.e., which chromophores are involved?). It will also be important to determine the factors (in chemical, biological and physical domains) that control the photoproduction/ destruction of key species (e.g., DIC, CO, DMS). For example, what is the role of O2 in DOM photodegradation and DIC production; i.e., is molecular oxygen needed as a reactant or does it suppress DIC photoproduction by, for example, quenching reactive triplets, or both? What is the fate of the resultant photooxidized DOM (Blough and Zepp, 1995)? What are the mechanisms and major products formed during the photolysis of DMS in seawater?
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B. PHOTOPRODUCTION AND AIR-SEA EXCHANGE OF IMPORTANT ATMOSPHERIC TRACE GASES Climate models are greatly affected by the degree to which air-sea gas exchanges of CO, C O S , D M S and other cHmatically important gases are influenced by photochemical reactions at the sea surface (Doney et al, 1995; Najar et aL, 1995; Gnanadesikan, 1996; Blough, 1997; Erikson et al, 2000). Future studies are needed to quantify the photoproduction of CO2 and photoproduction/loss of volatile sulfur species in surface seawater and to determine the effect of these processes on their air-sea exchange, as has been done for other reactive species in the sea surface microlayer (Thompson and Zafiriou, 1983). Furthermore, the impact of changes in global UV radiation on air-sea fluxes of important trace gases will need to be assessed. Another major unknown is the role of photochemical processes in the formation and/or destruction of the surface microlayer and its impact upon air-sea gas exchange (Blough, 1997).
C. DOM
PHOTOCHEMISTRY AND MARINE FOOD WEB DYNAMICS
The photochemical processes by which biorefractory DOM is made bioavailable, and by which bioavailable DOM is made unavailable, need to be determined. Identifying these processes would help in developing a predictive understanding of changes in DOM lability due to coupled photochemical-biological transformations. In this context, quantifying the effect of photochemistry on bacterial growth efficiency appears to be essential. In a related area, the role of extracellular release of DOM as a photoprotective mechanism in autotrophs and heterotrophs needs to be examined; i.e., what is the effect of externally (and internally) produced reactive phototransient species (e.g., free radicals) on the growth of autotrophs and heterotrophs?
D. DOM PHOTOCHEMICAL REACTIONS INVOLVING TRACE ELEMENTS Photochemistry can affect trace element speciation (Blough and Zepp, 1995; Faust, 1999). For example, photochemical reactions can alter the concentration and reactivity of organic ligands involved in the complexation/solubilization of trace metals (Moffett, 1995). Photochemical reactions can also result in changes in the oxidation state of trace elements, which in turn can affect their bioavailability. Redox-sensitive trace elements include iron (Voelker et al, 1997; Barbeau and Moffett, 2000), copper (Zafiriou et al, 1998; Voelker et al, 2000), manganese (Sunda and Huntsman, 1994), chromium (Kaczynski and IGeber, 1993),
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mercury (Costa and Liss, 2000; Lalonde et al, 2001) and iodine (Wong and Cheng, 2001). The mechanisms by which these photoredox reactions occur, and the nature of the DOM ligands involved, are not known, and are clearly areas for future research. While DOM photochemistry significantly impacts the chemistry of important trace metals in seawater, the reverse, i.e., the effect of trace metals on the photochemical reactivity and degradation of DOM, is not understood. What is the fate of the oxidized DOM product? Is its complexing capacity increased or decreased relative to the reduced DOM? Does oxidized DOM undergo further reactions leading eventually to decarboxylation, which in turn would contribute to photochemical DIC production?
E. EXTRAPOLATING PHOTOCHEMICAL RATES TO GLOBAL SCALES In order to evaluate the impact of DOM photochemistry on climatic processes and biogeochemical cycling of elements, it will be important to use remotely sensed estimates of chromophoric DOM (CDOM) and available irradiance data to extrapolate photochemical fluxes to global scales (see Blough and Del Vecchio, Chapter 10). However, modeling will require laboratory studies to develop robust parameterizations for apparent quantum yields for important photochemical reactions, including CO2 photoproduction, H2O2 photoproduction, DMS photodestruction, and CDOM photobleaching (Sikorski and Zika, 1993; Kettle et al, 1999b; Vahatalo et al, 2000). As a complement to this laboratory effort, in situ drifter studies need to be conducted in the field to verify global photochemical models (Zafiriou, pers. conmiun.). The advantage of the latter technique is that it does not have some of the inherent uncertainties associated with models based on apparent quantum yield and absorbance data (Neale and Kieber, 2000). The main drawback to this latter approach is that it is time-consuming and expensive. In addition, seasonal and geographic variability in photochemical reaction rates need to be measured. With this information, it should be possible to estimate the importance of marine photochemical reactions on tropospheric budgets of important trace gases (DMS, CO, COS, etc.). These global estimates can then be compared with estimates of other biogeochemically relevant species and for the development of a unified framework for quantifying global fluxes of carbon and sulfur.
ACKNOWLEDGMENTS We thank the National Science Foundation Office of Polar Programs (OPP-9527255 (K. M.) and OPP-9610173 (D. J. K.)) and the Chemical Oceanography Program (OCE-9711206 (K. M.) and OCE-9711174 (D. J. K.)) for financial support of this work. We thank two anonymous reviewers for constructive criticism of the manuscript, and we also acknowledge Dave Seigel and Norm Nelson
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for valuable comments on the Unresolved Questions and Future Research section. We thank Brendon Hofsetz for collection of the respiration data for Fig. 1 and for assistance with preparation of the figures. We thank Yi Zhu for collecting the uptake data for Fig. 2, and Aron Stubbins for conmients on the page proofs.
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Chapter 10
Chromophoric DOM in the Coastal Environment Neil V. Blough and Rossana Del Vecchio Department of Chemistry and Biochemistry University of Maryland College Park, Maryland I. Introduction II. Optical Properties A. Absorption B. Fluorescence III. Distribution IV. Sources and Sinks
A. Sources B. Sinks (or Why Aren't the Oceans Highly Colored?) V. Summary and Future Areas of Research References
I. INTRODUCTION Over the past decade, there has been a renewed interest in the properties and distribution of the major light-absorbing constituent of the dissolved organic matter (DOM) pool in natural waters (the <0.2-/xm fraction). This material, referred to in the past by various names including Gelbstoff, yellow substance, gilvin, and humic substances, has more recently been provided the name chromophoric dissolved organic matter (CDOM). This designation more clearly highlights that this material absorbs not only visible light, but also light in the UV-A (wavelengths from 315 to 400 nm) and UV-B (wavelengths from 280 to 315 nm), which are also part of the surface solar spectrum. By this definition—absorption at wavelengths over the range of surface solar radiation—CDOM represents only a portion of the total DOM pool. Although both "CDOM" and "humic substances" Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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refer to the chemically complex, light-absorbing material produced by the decay of plant and algal matter, our use of "CDOM" is restricted to the material that is present in natural waters, whereas our use of "humic substances" refers to material that is extractable from natural waters. This discrimination is necessary because the extracted materials are not always representative of those found in the original waters (Green and Blough, 1994; Thomas-Smith and Blough, 2001). The recent interest in CDOM has a number of origins. First, it is now recognized that the release of man-made chlorofluorocarbons (CFCs) causes the enhanced destruction of stratospheric ozone in polar regions, leading to increased levels of surface UV-B radiation. These increases have raised concerns over the possible impacts of UV-B (as well as UV-A) radiation on both freshwater and marine ecosystems (Blough and Zepp, 1990; WiUiamson et al, 1996; Hader et al, 1998; Zepp et al, 1998; de Mora et ai, 2000; Neale and Kieber, 2000). Owing to an approximately exponential increase of absorption with decreasing wavelength (see below), CDOM absorbs light strongly in the UV-A and UV-B and is usually the principal constituent within aquatic systems that controls the penetration depth of radiation potentially harmful to organisms (Fig. lA). Thus, the amount of CDOM in surface waters can have a substantial impact on the levels of damaging radiation received by aquatic organisms. Moreover, for estuarine waters and for coastal waters strongly influenced by river inputs, light absorption by CDOM can extend well into the visible wavelengths, often dominating the absorption by phytoplankton in the blue portion of the visible spectrum (Fig. IB). In this situation, the amount and quality of the photosynthetically active radiation available to phytoplankton is reduced, thus decreasing primary productivity and affecting ecosystem structure. Thus CDOM can play a substantial role in the biogeochemistry of natural waters merely through its influence on the aquatic light field (Bidigare et al, 1993; Blough et al, 1993; Arrigo and Brown, 1996; Vodacek et aL, 1995, 1997; DeGrandpre et al, 1996; Schindler et ai, 1996; WiUiamson et al, 1996; Morris and Hargreaves, 1997; Kuhn et al, 1999; West et al, 1999; Conde et al, 2000; de Mora et al, 2000; Gibson et al, 2000; Kuwahara et al, 2000). Second, it has now been firmly established that the absorption of sunlight by CDOM also initiates the formation of a variety photochemical intermediates and products (Helz et al, 1994; Blough and Zepp, 1995; Blough, 1997; Moran and Zepp, 1997; Zepp et al, 1998; Blough, 2001; Mopper and Keiber, Chapter 9). The photochemical reactions producing these species ultimately lead to the destruction of the CDOM and the loss, or bleaching, of its absorption and fluorescence (Fig. 2; Kramer, 1979; Kouassi andZika, 1990,1992; DeHaan, 1993; Skoog etal, 1996; Reche et al, 1999; Whitehead et al, 2000; Moran et al, 2000; Twardowski and Donaghay, 2001). This process can thus act as a feedback to alter the aquatic light field, potentially allowing greater penetration of damaging UV radiation. Light absorption by CDOM can have a number of additional consequences
Chromophoric DOM in the Coastal Environment
511
0.4
300
400
500
600
700
Figure 1 CDOM ( ), particulate detrital material (PDM) ( ) and phytoplankton (P) (• • • • •) absorption spectra along the Southwest Florida shelf during June 2000. (A) Shelf station at 25°35.20^N and 82°23.irW; (B) Mouth of the Lostman River at 25°33.23'N and 8ri2.70'W. (Insets) Same PDM ( ) and P (• • • • •) absorption spectra with expanded vertical scale. The total particulate absorption spectrum is given by the sum of the PDM and P absorption spectra; PDM and P are both retained on GF/F filters following seawater filtration. P is extractable by methanol, whereas PDM is not. The spectrum of P is thus obtained by subtracting the PDM spectrum from the total particulate absorption spectrum.
including: (1) the photooxidative degradation of organic matter through the photochemical production of reactive oxygen species (ROS) such as superoxide (02~), hydrogen peroxide (H2O2), peroxy radicals (RO2), and the hydroxyl radical (OH); (2) changes in metal ion speciation through reactions with the ROS or through direct photochemistry, resulting in the altered biological availability of some metals; (3) the photochemical production of a number of trace gases of importance in the atmosphere, such as CO2, CO, and COS, and the destruction of others such as dimethyl sulfide; (4) the photochemical production of biologically
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235 139 300
350
400
450
500
23
550
0 hrs
600
Wavelength (nm) Figure 2 Time course for the photobleaching of CDOM in the Delaware Bay water. (A) absorption coefficient on linear scale with nonlinear least-squares fit (NLF, continuous lines); (B) absorption coefficient on logarithmic scale. (Inset) Spectral intensity of the irradiation source in units of photons n-2 g-i c-1 ^ jo+15. Before Ught exposure ( ); after 23 h ( ), 139 h (-), and 235 h ( ) of hght exposure at room temperature. The spectral slope, S, obtained using a nonlinear least square fit (NLF) over the range 290-700 nm is also reported at these irradiation times.
available low-molecular-weight (LMW) organic compounds and the release of available forms of nitrogen, thereby fueling the growth of microorganisms from a biologically resistant source material (the CDOM). Recent work thus indicates that photochemistry in concert with microbial action could play an important role in the carbon cycle of the upper ocean and of freshwaters (Kieber et al, 1989; Mopper et al, 1991; Salonen and Vahatalo, 1994; Miller and Zepp, 1995; Wetzel et al, 1995; Amon and Benner, 1996; Bushaw et al, 1996; Graneh et al, 1996; Miller and Moran, 1997; Moran and Zepp, 1997; Benner and Biddanda, 1998; Bertilsson and Tranvik, 1998, 2000; Opsahl and Benner, 1998; Andrews et al, 2000; Kieber, 2000; Moran et al, 2000).
513
Chromophoric DOM in the Coastal Environment Third, the expanding use of satellite ocean color measurements to examine biogeochemical processes over broad spatial and temporal scales has required the development of improved algorithms for determining seawater constituents that are based on more extensive and higher resolution optical measurements. It is now recognized that high levels of CDOM absorption in many coastal and estuarine waters can seriously compromise the determination of phytoplankton biomass from satellite measurements. Thus a great deal of effort has been expended on improving algorithms for the passive remote sensing of phytoplankton biomass and CDOM absorption (e.g., Carder et al, 1991, 1999; Hochman et ah, 1994, 1995; Hoge et aU 1995a, 1999; Garver and Siegel, 1997; O'Reilly et al, 1998; Kahru and Mitchell, 2001), with the ultimate objectives of deriving better regional and global estimates of primary productivity, of tracking the distribution of CDOM throughout the world's oceans, and of possibly determining the magnitude of abiotic photochemical processes over these broad spatial and temporal scales (Nelson and Siegel, Chapter 11).
11. OPTICAL PROPERTIES A previous article (Blough and Green, 1995) reviewed the types of optical measurements that have been employed to characterize CDOM and humic substances and discussed the nature of the information that can be obtained from these measurements. Below, we summarize this past work, including newer information where relevant. A brief overview of more recentfieldworkis provided in Section III. A.
ABSORPTION
CDOM is the principal light-absorbing constituent of the DOM pool in seawater, far exceeding the contributions of discrete dissolved organic or inorganic chromophores. Absorption spectra are broad and unstructured, and typically decrease with increasing wavelength in an exponential fashion. Thus workers have typically fit these spectra to the expression, a{X) = a{Xo)e-'^^-''^\
[1]
where a(X) and a(A,o) are the absorption coefficients at wavelength k and reference wavelength AQ, respectively, and S defines how rapidly the absorption decreases with increasing wavelength (Figs. 1-3) (Bricaud et al, 1981; Zepp and Schlotzhauer, 1981; Carder et al, 1989; Blough et al, 1993; Green and Blough, 1994). Absorption coefficients are calculated from the relation, a(X) = 2.303A(A)/r,
[2]
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Blough and Del Vecchio
600
Wavelength (nm) Figure 3 CDOM absorption spectra obtained along a transect in the MAB during September 1998: (A) on linear scale with nonlinear least-squares fit (NLF); (B) on logarithmic scale with linear leastsquares fit (LF); (C) fl(A) normalized to a{290) with nonlinear least-squares fit (NLF). [1, Delaware River at 39°41.33'N and 75°31.irw ( ); 2, Delaware Bay mouth at 38°48.86'N and 75°4.9rw ( ); 3, MAB at 38°26.42'N and 74°34.01'W ( ); 4, Gulf Stream Western Edge at 37°6.95'N and 72°55.42'W ( )]. The spectral slopes, 5, obtained with a NLF over the range 290-700 nm (A) and with a LF over the range 290 to the instrument detection Umit (0.005 absorbance units) (B) are also reported. (Inset) The residuals were obtained by subtracting thefittedvalues from the actual values. The residuals fall within the photometric accuracy reported by the manufacturer (±0.005 absorbance units, corresponding to ±0.115 m~^ using a 10-cm cell) for this instrument (Hewlett Packard 8452A diode array)]. C clearly illustrates that S increases for offshore waters in the MAB; these absorption curves would be superimposable in the absence of a change in the spectral dependence regardless of the fitting procedure.
Chromophoric DOM in the Coastal Environment
515
where A is the optical density measured across pathlength, r. The fitting of absorption data to Eq. [1] has proved quite useful as a simple means to characterize CDOM spectra rapidly; in most cases, this equation approximates the spectral dependence very well (see below and Fig. 3). The magnitude of CDOM absorption varies substantially across fresh and marine waters, with values of CDOM absorption coefficient at 355 nm, «CDOM(355), ranging from >15 m"^ for some coastal and fresh waters to <0.1 m~^ for surface oligotrophic seawaters (Table I). For coastal waters strongly influenced by river input, CDOM absorption usually dominates the total light absorption, not only in the UV-B and UV-A but also in the blue portion of the visible spectrum where phytoplankton also absorb (Fig. IB). For example, DeGrandpre et al. (1996) found that the <2CDOM(442) was two- to threefold greater than the particulate absorption coefficient, ap(442) (which includes phytoplankton absorption), during August on the shelf of the U.S. Middle Atlantic Bight (MAB); during April, acDOM(442) ranged from ~30 to 100% higher thanflp(442)across the shelf. Only during a fall bloom in November did ap(442) exceedfl!cDOM(442),although even in this instance CDOM absorption represented a substantial portion of the total absorption. Nelson and Guarda (1995) observed even larger differences in the U.S. South Atlantic Bight during high river discharge in the spring, with acDOM(443) being over 10-fold higher than «p(443) between 12 and 50 km offshore. On the western shelf of south Florida during summer, the ratio of CDOM to phytoplankton absorption at 443 nm was observed to vary from 10 for inshore waters to about 1 approximately 100 km offshore (Fig. 1). Employing an integrating cavity absorption meter. Pope et al (2000) reported recently an even larger range in the ratio of CDOM to particulate absorption at 432.5 nm, from 152 to 0.46 for waters of the Gulf of Mexico influenced by the outflow of the Mississippi River. Significant levels of terrestrial CDOM are not confined to the immediate vicinity of the coast, but can extend well offshore for regions experiencing large freshwater inputs. The relatively high levels of CDOM absorption observed in parts of the eastern Caribbean (acDOM(355) ~0.6 m~^) during the high flow period of the Orinoco River represents a particularly striking example (Blough et al, 1993; Del Castillo et al, 1999). Indeed, the input of CDOM from major rivers such as the Orinoco and the Amazon can have a substantial seasonal impact on the optical properties of ocean waters over significant geographical areas (MiillerKaxgcretal, 1988,1989; Blough ^f a/., 1993;Hochman^/fl/., 1994, Del Castillo, 1999). A further example of the injection of terrestrial CDOM into offshore waters has been observed in the U.S. MAB, where riverine CDOM is advected northward from the North Carolina coast along the western boundary of the Gulf Stream (Hoge et al, 1995a,b; Vodacek et al, 1995). Bates and Hansell (1999) estimated that this process could export shelf organic carbon into the North Atlantic basin at a rate of ~3-31 x 10^^ g C year~^ depending on the amount of water advected off the shelf.
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Chromophoric DOM in the Coastal Environment
523
The parameter, S, defines the spectral dependence of the CDOM absorption coefficient, and thus provides information about the "nature" of the CDOM chromophores. Unfortunately, in the past, researchers have not determined this parameter in a consistent fashion. Most investigators have calculated S through a linear least squares regression of the log-transformed absorption data (Table I; Fig.3B;Bricaude?(3/., 1981;Blough^ra/., 1993; Green and Blough, 1994;Nelson and Guarda, 1995; Nelson et al, 1998). However, as pointed out by a number of workers (Stedmon et al, 2000; Boss and Twardowski, private communication), fitting the data to an exponential form using a nonlinear least squares fitting routine represents a better approach, owing to the relatively greater weighting given to the higher, and better measured, absorption values at short wavelengths. In contrast, a linear fit to log-transformed data enhances the relative weights of the low absorption values at long wavelength, and thus biases the value of the slope downward (Fig. 3). This problem becomes particularly acute when workers attempt to fit data over spectral ranges where the absorption is close to the detection limit of the instrument. In contrast, the use of the nonlinear least squares regression allows the complete spectral range of the data to be fit (e.g., from 290 to 700 nm), thus foregoing the indiscriminate use of different spectral ranges to acquire S. A goodness-of-fit statistic, such as x ^» can be reported and used to evaluate whether a simple exponential model provides a sufficient description of the data, or requires the use of a more complicated model such as the sum of two exponentials. However, if the residuals from the single exponential fit fall within the photometric accuracy of the instrument (~0.046-0.115 m~^), the use of a more complicated model is difficult to justify (Fig. 3A, inset). In the past, we have employed a linear least squares regression to obtain S over the range from 290 nm to the wavelength where the detection limit of absorption is reached. A recent analysis in this laboratory has shown that the S values acquired in this fashion are biased toward lower values than those obtained using the nonlinear fitting by ~0.0023 nm~^ (Figs. 3 and 4). However, the values of S obtained in these two ways are well correlated (r^ = 0.857), with the relationship exhibiting a slope very close to one (Fig. 4). These results indicate that although the values of S acquired by the linear least squares analysis may slightly underestimate 5, observed changes in S will be of the same magnitude. Figures 3 A and 3C further illustrate that CDOM absorption spectra measured for waters having substantially different levels of absorption are very well described by an exponential function within the photometric accuracy of the measurements. Because many workers in the past have acquired S using different approaches (linear vs nonlinear) or over different spectral ranges or series of ranges, comparisons among studies can be difficult. Thus, we have annotated the spectral data presented in Table I with information on the method of measurement. S varies with the source of the CDOM (Table I), but also can be altered through the biological and chemical processing of a source material. Values of S for humic
Blough and Del Vecchio
524
0.030 H 31-33
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S (nm-^) (LF) Figure 4 Values of 5 obtained for CDOM absorption spectra for waters in the MAB during September 1998 using a nonlinear least-squares fit to an exponential curve (NLF) and a linear least-squares fit to a semilog plot (LF). The samples were collected along a transect from the Delaware River to ~375 km offshore; theflcDOM(355)ranged from 4 to ~0.1 m " ^
substances and for CDOM from a wide variety of sources range from as low as ^0.01 nm~^ for terrestrial humic acids to as high as 0.02-0.03 nm~^ for CDOM in oligotrophic seawaters (Table I; Fig. 4). For humic substances, the relationship between S and the "molecular" properties of these materials can be summarized as follows (Blough and Green, 1995): (1) S is larger for fulvic acids than for humic acids; (2) S increases with decreasing molecular weight; (3) S increases with decreasing aromatic content. Specific absorption coefficients, a(Xy, for humic substances, obtained by normalizing aiX) to the organic carbon concentration, C, a(X)*[L (mg org. C)"* m"^] = a(X)/C,
[3]
increase with increasing aromatic content (Chin et al, 1994). These results are consistent with the view that humic substances having higher aromatic content, generally those with higher molecular weights, exhibit lower values of S. These lower values arise from enhanced absorption at longer wavelengths (lower energies). This may result from the presence of a distinct suite of chromophores having extended aromatic systems that absorb at lower energies (longer wavelengths). Alternatively, the increased absorption at longer wavelengths could arise from intramolecular charge transfer transitions between (similar) chromophores due to their greater numbers (and thus higher aromaticity) (Power and Langford, 1988; Blough and Green, 1995). Similarly, the increase in a{Xy with increasing aromatic content can be explained as due to a higher percentage of light-absorbing aromatic structures or to an increase in the number of charge transfer interactions.
525
Chromophoric DOM in the Coastal Environment
A number of recent studies have found that the values of S art larger for offshore seawaters (>0.02 nm~^) than for coastal waters influenced by river input (0.013-0.018 nm-i) or for most fresh waters (Table I; Fig. 4; Brown, 1977; Carder et al, 1989; Blough et al, 1993, Green and Blough, 1994; Nelson and Guarda, 1995; Nelson et al, 1998). Despite a few reported exceptions (Stedmon et al, 2000), S is usually observed to increase with decreasing absorption and increasing salinity during transit of the terrestrial CDOM to offshore waters (Fig. 4; Blough et al, 1993), suggesting that this material is being altered or replaced with a marine form. During the summertime in the MAB, the dependence of CDOM absorption on salinity reveals evidence of a significant CDOM sink in surface waters under conditions in which S also increases (Figs. 5 and 6A; Vodacek et al, 1997), consistent with the view that the terrestrial CDOM is being altered (Sections III and IV below). Based on the properties of the humic substances, this increase in S suggests a loss of aromaticity and a decrease in the average molecular weight of the CDOM. Recent laboratory and fieldwork indicates that photochemical bleaching can produce the same effects (Vodacek et al, 1991 \ Schmitte-Kopplin et al, 1998; Moran et al, 2000) and may account in part for the observed gradient in S from in- to offshore waters. However, the in situ production of CDOM having higher
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Blough and Del Vecchio
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Salinity (ppt) Figure 6 (A) Dependence of CDOM spectral slope {S) on salinity for the MAB, in the mixed layer ( • ) and below the mixed layer (O). [The 5 has been calculated with a nonlinear least-squares fit (NFL) over the range 290-700 nm. Similar results have been reported by Blough et al (1993) for the Orinoco River using a linear least fit (LF)]. (B) Dependence of CDOM fluorescence emission maximum on salinity in the Orinoco River ( • ) (Ex. 350 nm) (data from Del Castillo et al, 1999); the Gironde Estuary (V) (Ex. 313 nm) (data from de Souza Sierra et al, 1994, de Souza Sierra et al, 1997); the Continental Shelf (•) (Ex. 313 nm) and the Mediterranean Sea (O) (Ex. 313 nm) (data from de Souza Sierra et al, 1997); the West Horida Shelf (A) (Ex. 285-310 nm) (data from Del Castillo et al, 2000).
values of S presumably could also play a role, especially in oligotrophic waters far from the influence of terrestrial sources (Nelson et al, 1998).
B. FLUORESCENCE Fluorescence measurements of humic substances and CDOM have generally been more common than absorption measurements, due primarily to their greater
Chromophoric DOM in the Coastal Environment
517
sensitivity and simplicity (Donard et al, 1989; Chen and Bada, 1992; Green and Blough, 1994; De Souza Sierra et al, 1994, 1997). Fluorescence is far more amenable to continuous monitoring (Vodacek et al, 1995; Klinkhammer et al, 1997,2000; Chen, 1999; Guay et al, 1999) and remote measurement (Hoge et al, 1995b; Vodacek et al, 1995), and thus potentially allows for the high resolution mapping of CDOM distributions. However, fluorescence provides only an indirect measure of CDOM absorption, and its magnitude and spectral dependence are more sensitive to such factors as pH, ionic strength and the presence of quenchers. Steady-state fluorescence is not representative of the entire population of absorbing species within CDOM, nor of the entire population of emitting species; instead fluorescence spectra will tend to be dominated by those subpopulations exhibiting longer fluorescence lifetimes (Herbelin, 1994; Blough and Green, 1995; Lakowicz, 1983). Thus, to estimate CDOM absorption from fluorescence measurements, a linear relationship between fluorescence and absorption must be established empirically for the geographical region of interest (Section ILB.2). Spectrofluorometry can also be used to acquire additional information about the possible sources and nature of the CDOM through the collection of excitationemission matrix spectra and synchronous scan spectra (Cabaniss and Shuman, 1987; Coble et al, 1990; Green, 1992; Green and Blough, 1994; Blough and Green, 1995; Pullin and Cabaniss, 1997; Section II.B.l), keeping once again in mind that emission spectra tend to be dominated by the longer-lived fluorescent component(s). 1. Fluorescence Excitation and Emission Spectra, Excitation-Emission Matrix Spectra, and Synchronous Spectra The excitation and emission spectra of humic substances and CDOM are very broad and unstructured, with the maxima in the excitation and emission spectra usually falling between 300 and 400 nm and 400 and 500 nm, respectively. The emission maximum shifts continuously to the red and lowers in intensity with increasing excitation wavelength, suggesting the presence of numerous absorbing and emitting centers. Three-dimensional excitation, emission matrix spectra (EEMS) have thus been employed in an attempt to distinguish source-dependent variations in the CDOM. EEMS are obtained by acquiring emission spectra at a series of successively longer excitation wavelengths. These emission spectra are concatenated to generate a plot in whichfluorescenceintensity is displayed as a function of the excitation and emission wavelengths. In contrast, synchronous scan spectra are obtained by scanning the excitation and emission wavelengths simultaneously at a fixed wavelength difference and thus represent a "slice" through the EEMS (Blough and Green, 1995). Although slower to collect, EEMS provide a more complete picture of the CDOM emission properties and can often be used to discriminate among different classes
528
Blough and Del Vecchio Table II Excitation and Emission Maxima for Classes of CDOM Fluorophores Identified by EEMS Type of fluorophore Protein-like Tyrosine Tryptophan Humic-like UV-humic UV-humic Unknown Visible-marine humic Intermediate marine-terrestrial Visible-terrestrial humic Chlorophyll-like Chlorophyll
^ex'^em
Labeled
230, 275/305 230, 275/340
B T
230/430 260/400-460 280/370 290-310/370-410 310/412 320-360/420^60
A N M Intermediate C-M C
398/660
P
Note. Modified from Coble et al, (1998). Table 2, p. 2208.
of fluorophores based on their excitation/emission wavelength maxima, as well as to follow changes incurred by the biological or physical processing of a material. Through the use of EEMS, several broad classes of emitting species have been identified in natural waters, namely the "protein-like," the "humic-like" (CDOM), and the "chlorophyll-like"(Table II; Coble et al, 1990,1998; Mopper and Schultz, 1993; Coble, 1996). The humic-like class has excitation/emission maxima in the range 320-360/420-460 nm, respectively. Offshore waters exhibit excitation and emission maxima for this class that are blue-shifted by ~25 and ^5-30 nm, respectively, relative to coastal and estuarine waters (Fig. 6B; De Souza Sierra etal, 1994, 1997; Coble, 1996). Consistent with the increase in S observed in the absorption spectra (Fig. 6A), these blue-shifts point to a preferential loss of longer-wavelength, lower energy transitions and a decrease in aromaticity, produced possibly by the photochemical and/or microbial processing of the terrestrial CDOM, its mixing or replacement with a less aromatic marine form, or some combination of these effects. The "protein-like" class exhibits excitation maxima at 220 and 270 nm with emission maxima at 305 nm (similar to tyrosine) and at 345 nm (similar to tryptophan). As reported by Mopper and Schultz (1993), the intensity ratio of these excitation peaks is similar to that of proteins reported by Lakowicz (1983), suggesting that these amino acids, either free or within proteins, contribute to the fluorescence signal of some natural waters. These signals have been observed in surface water (Coble et al, 1990; Mopper and Schultz, 1993) and in porewaters (Coble, 1996).
Chromophoric DOM in the Coastal Environment
529
2. Fluorescence Quantum Yield and Fluorescence/Absorption Relation The fluorescence quantum yield is a well-defined photophysical parameter representing the ratio (or percentage) of photons emitted to those absorbed. This parameter can be used to compare the fluorescence efficiencies of CDOM from different locales, thus providing another tool for characterizing the "nature" of the CDOM. A constant quantum yield indicates that the fluorescence intensity of a material will be directly proportional to its absorbance at the excitation wavelength (in the absence of inner filtering; Lakowicz, 1999); the higher the quantum yield, the higher the fluorescence per unit absorbance. Thus fluorescence measurements can also be used to acquire CDOM absorption coefficients, if a linear relationship between a well-calibrated fluorescence signal and absorption can be established (Hoge et al, 1993; Green and Blough, 1994). In earlier work, Green and Blough (1994) showed that the quantum yield for fluorescence obtained with 355 nm excitation (^355) was relatively constant for different humic substances and for CDOM from significantly different geographical areas. 0355 varied by about a factor of five, with the CDOM of most waters having a ^355 of about 1% (see also Vodacek et al, 1995, 1997). Over this range, the highest yields were observed for humic substances isolated from deep marine waters (2.1%), whereas the lowest were observed for terrestrial humic acids and some river waters (~0.4%). The relative invariance of these yields across differing oceanic environments is also mirrored in the linear relationships between CDOM fluorescence and absorption that have been observed by numerous investigators over the past 10 years (Table I; Ferrari and Tassan, 1991; Hoge et al, 1993; Nieke et al, 1991 \ Vodacek et al, 1997; Ferrari and Dowell, 1998; Seritti et al, 1998; Ferrari, 2000). The largest difference in the ratio of absorption to fluorescence obtained from the slope of these relationships (m in Table I) is about a factor of 3 and is observed between the eastern and western coasts of the North Atlantic Ocean (Table I; Section III). However, within a given geographical area, the variation in the ratio is much less, generally no more than ^15-30%. Thus, these fluorescence/absorption relationships have been employed to acquire CDOM absorption coefficients from continuous measurements of m situ fluorescence, as well as from fluorescence measurements acquired by aircraft using NASA's Airborne Oceanographic Lidar (Hoge ^r a/., 1995b; Vodacek ^r a/., 1995, 1997).
3. Relationship of Absorption, Fluorescence to DOC Despite the fact that a significant fraction of the dissolved organic carbon (DOC) is not associated with CDOM, a number of workers have observed correlations between CDOM absorption (orfluorescence)and DOC concentration in the coastal environment (Fig. 7; Laane and Koole, 1982; Vodacek et al, 1995, 1997; Chen,
Blough and Del Vecchio
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1999; Klinkhammer et al, 2000). These correlations usually exhibit a substantial positive intercept on the DOC axis (Fig. 7), implying that the oceanic end-member contains predominantly nonabsorbing DOC and little CDOM. The large intercept and steep slope of this correlation results from the very different content of CDOM and DOC in the freshwater and oceanic end-members; while DOC decreases only by about a factor of four between fresh waters and the surface ocean (~300 fiM vs --70 /xM), CDOM absorption decreases by factors ranging from 40 to 200 (Table I; Fig. 8). This relationship appears to arise primarily from the quasi-conservative mixing of both CDOM and DOC within these regions (e.g., Mantoura and Woodward, 1983), and not through a covariation in the rates of their in situ production and consumption. Under conditions in which CDOM is consumed photochemically (Figs. 5 and 6), this relationship is altered (Fig. 7; Section IV). These results are unlike those observed for the open ocean (Nelson et ai, 1998) or for coastal regions not strongly influenced by river inputs (Ferrari, 2000). In these and other regions such as the northwest Florida shelf (Del Castillo et al, 2000), no (or weaker) correlations have been observed between DOC and CDOM, due to an uncoupling between the sources and sinks of the CDOM and the nonabsorbing DOM in this environment.
Chromophoric DOM in the Coastal Environment
531
Salinity (ppt) Figure 8 Dependence of acDOM(355) on salinity for different geographical areas: (A) Orinoco River on 9/27/88 ( • ) and on 10/9/88 (O) (data from Blough et al, 1993); Gulf of Paria (T) (data from Blough et al, 1993); MAB on April 1994 (V) (data from Vodacek et al, 1997); SAB on August 1992 ( • ) and on April 1993 (D) (data from Nelson and Guarda, 1995); Apalachicola River (•) and Suwanee River (O) (data from Del Castillo et al, 2000); St. Lawrence Estuary (A) (data from Nieke et al, 1997); Amazon River (A) (data from Green and Blough, 1994). (B) North and Baltic Sea ( • ) (data from H0jersley et al, 1996); Baltic Sea (O) (data from Stedmon et al, 2000); Eastern Atlantic Ocean (T) (data from Ferrari, 2000); Tyrrhenian Sea and Amo River (V) (data from Seritti et al, 1998). (Inset) Same Eastern Atlantic Ocean data ( • ) with expanded axis (data from Ferrari (2000)). The «CDOM(355) has been recalculated using theflcDQM(^)and the spectral slope reported for each study.
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III. DISTRIBUTION Field measurements of CDOM optical properties have increased enormously over the past decade. However, because workers have often used different experimental protocols, a direct comparison of the optical properties of CDOM from different waters is often difficult. Nevertheless, we have attempted to compile in Table I a representative list of CDOM optical data obtained in studies over the past ~10 years, and where possible, have converted these data to a common set of parameters so that comparisons could be made (Fig. 8). Although many blackwater rivers such as the Tamiami (southwest Rorida; Green and Blough, 1994), the Surumoni (South America; Battin, 1998), and the Satilla (Georgia; Moran et ai, 2000) can exhibit very high values of «CDOM(355) (> 30 m~ ^), the mouths of the larger rivers and estuaries generally have much lower values, on the order of 5 to 15 m"^ (Fig. 8; Table I). With one notable exception (the outflow of the Orinoco River), acDOM(355) is inversely related to salinity, and for many estuaries and coastal waters appears to behave conservatively, although not in all cases nor in all seasons (Figs. 5 and 8). Nonlinear mixing curves can arise from the in situ production or loss of the CDOM, from the conservative mixing of three or more water masses containing different acDOM(355) end members or from some combination of these factors. Depending on the locale, it is often difficult to distinguish between the in situ production and consumption of CDOM versus the mixing of different water masses. As one example, the dependence of acDOM(355) on salinity for the Orinoco River implies the presence of a large source in the region of the outflow (Fig. 8; Blough et al, 1993). Based on additional evidence, this CDOM does not appear to arise from in situ phytoplankton production, from a sediment source nor through release from particulate matter at higher salinities. An alternative, but as yet untested possibility, is that there are other water masses containing very high levels of CDOM intruding into the Orinoco delta. The nonlinear dependence of CDOM absorption on salinity observed by H0jerslev et al (1996) in the North Sea-Baltic Sea transition zone (Fig. 8) has been interpreted to result from the quasi-conservative mixing of (terrestrial) CDOM from three water masses: (1) North Sea water (high salinity of 35, low CDOM— «CDOM(355) = 0.099 m~^); (2) Baltic Sea water (low salinity of 8, intermediate CDOM—acDOM(355) = 1.36 m"^); (3) German Bight/southern North Sea water (intermediate, high salinity of 31, high CDOM—nflcDOM(355) = 2.13 m"^). At salinities lower than 8, the CDOM increases even further due to the contribution of freshwater inputs from the Bothnian Bay (Fig. 8). Based on their measurements and historical data, these workers concluded that the long-term average concentration of CDOM had not changed significantly over the past 40 years in the Baltic, the North Sea or the Atlantic, suggesting that the (terrestrial) source is in balance
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with a loss pathway. They further concluded that there were only minor seasonal variations in the CDOM levels. However, depending on the spatial and temporal scales examined, workers have come to quite different conclusions concerning the dynamics and seasonal distributions of CDOM. As an example, in the southern Baltic Sea (Ferrari and Dowell, 1998; Kowalczuk, 1999), the magnitude of CDOM absorption was found to vary seasonally depending on the river input to the near-shore bay waters and was inversely related to salinity. In contrast, no correlation of absorption with salinity was observed in offshore waters, possibly due to the numerous river sources contributing to this region. However, a significant correlation was also observed between CDOM absorption and chlorophyll (Chi) concentration in the offshore waters (Kowalczuk, 1999), suggesting that the in situ formation of CDOM from phytoplankton was also playing a role. In general, coastal areas subject to high river inputs exhibit high levels of CDOM absorption, with the magnitude of the absorption depending on the river end member(s) contributing to the region and the seasonal river flow(s). Absorption is inversely related to salinity and exhibits conservative mixing behavior (Fig. 8) in the absence of significant in situ sources and sinks or mixing between multiple water masses. The geographical area impacted varies seasonally, depending on the magnitude of the river flow(s). In contrast, coastal margins not affected by river inputs generally show low values of acDOM(355) (<0.25 m"^), no (or little) correlation between absorption and salinity, and less seasonal variability (Ferrari and Dowell, 1998; Kowalczuk, 1999). Values of 5 observed for river end members from a variety of different geographic regions range from 0.011 to ~0.018 nm~^ (Table I), although some of this variability may result from the differing measurement approaches (Section II.A); more typical values are 0.014 to 0.016 nm~^ Regardless, these values are significantly lower than those observed for offshore and open ocean waters, where values can range as high as 0.030 nm"^, but are more typically ~0.025 nm"^ (Figs. 3,4, and 6; Table I). For terrestrially dominated regions, S changes very little until the salinity reaches fairly high values, ~30, and thereafter increases rapidly (Fig. 6A; see also Blough et al, 1993). This behavior is mirrored in the blue shifts observed in the excitation/emission spectra of the CDOM (Fig. 6B; De Souza Sierra et al, 1994, 1997; Del Castillo et al, 1999, 2000). Emission maxima remain approximately constant with increasing salinity up to ^30 to 33 and then shift sharply to the blue with increasing salinity. These results argue that terrestrial CDOM dominates at the lower salinities and remains largely unaltered. At higher salinity, the increase in S and blue shift in fluorescence both point to the loss of longer-wavelength, lower energy absorption bands, consistent with a loss of aromaticity. This loss of aromaticity could result from a number of factors as discussed in Section II and below (Section IV).
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Unlike these optical parameters, fluorescence quantum yields (0355) show only small changes with increasing salinity or with season, as reflected in the nearly linear relationships between fluorescence and absorption observed by a variety of workers throughout the world. The slope of the absorption to fluorescence relationship (m in Table I), changes by less than threefold for different geographical locales, ranging from as low as ~0.1 for the eastern Atlantic Ocean and the Baltic Sea (Ferrari and Dowell, 1998; Ferrari, 2000) to about 0.25 to 0.3 along the eastem seaboard of the United States (Hoge et al, 1993; Nieke et al, 1997; Vodacek et ai, 1997). Within a geographical region, smaller seasonal and spatial variations of ~30% have also been observed (Vodacek et ai, 1997); although small, these differences do suggest that the CDOM exhibits subtle seasonal and spatial variations within these regions.
IV. SOURCES AND SINKS A. SOURCES The evidence presented above indicates that the CDOM observed in estuaries and coastal waters receiving large river inputs is primarily terrestrial in origin. In these situations, the magnitude of the CDOM absorption varies inversely with saUnity, indicative of a freshwater source (Fig. 8), whereas the values of S and the excitation/emission maxima are usually indistinguishable from those observed for the river end member(s) and do not change greatly over a range of salinities (Fig. 6). Changes in these optical parameters only begin to become evident in higher-salinity, offshore waters, indicative of a transition between terrestrially dominated, inshore regions and more marine-like, offshore regions (Fig. 6). As mentioned in Section II, this transition may result from the (photo)chemical and/or biological processing of the terrestrial CDOM (see below), from the dilution or gradual replacement of the terrestrial CDOM with a marine form, or from some combination of these effects. The geographical extent of the terrestrially dominated regions varies seasonally, depending on the magnitude of the freshwater inputs (Blough et al, 1993; Nelson and Guarda, 1995; Vodacek etaL, 1997). Within these terrestrially dominated regions, unequivocal evidence for a significant contribution from the in situ production of CDOM is lacking. Although mixing curves acquired for some areas such as the Orinoco River outflow are suggestive of an in situ source (Fig. 8), other explanations, such as contributions from other higher end-member sources in the region, are equally probable. Further, in this and other studies (Blough etai, 1993; Nelson and Guarda, 1995; Vodacek etal, 1997), workers have found little or no correlation between the levels of chlorophyll and CDOM in the waters of these regions, thus arguing that phytoplankton
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do not act as di significant, immediate source of CDOM to these waters. Mesocosm studies by Rochelle-Newall et al (1999) support this conclusion. Recently, however, Twardowski and Donaghay (2001) provided evidence for the production of CDOM by phytoplankton within a thin subsurface layer under quiescent conditions. Although these results appear contradictory at first glance, they can be resolved if the level of in situ CDOM production from the phytoplankton source is small with respect to the terrestrial background and, further, is diluted by mixing over some portion of the water column. Thus, the in situ production of CDOM in terrestrially dominated waters may be evident only under a rather unique set of circumstances: a relatively stable water mass containing a high level of phytoplankton, but a relatively low background of terrestrial CDOM (Twardowski and Donaghay, 2001). Unlike the terrestrially dominated margins, coastal regions isolated from freshwater sources exhibit properties more similar to offshore, oligotrophic waters. CDOM absorption in these waters is usually very low (with the possible exception of upwelling regions) and exhibits no clear relationship with salinity or DOC concentration (Ferrari and Dowell, 1998; Obemosterer and Hemdl, 2000). In these regions, as with open-ocean waters, CDOM is presumably created in situ by as yet poorly understood processes. Nelson et al (1998) found at the Bermuda Atlantic Time-Series Study (BATS) site that CDOM absorption did not correlate significantly with chlorophyll concentration. Based on this observation and other evidence, these workers proposed that phytoplankton do not directly produce CDOM (Bricaud et al, 1981), but instead act as a source of material that is transformed to CDOM by the action of heterotrophic bacteria (Tranvik, 1993). In contrast, Kahru and Mitchell (2001) recently found that satelUte-derived estimates of CDOM absorption in the California Current are well correlated with chlorophyll concentrations in the offshore and outer shelf waters, but not well correlated in the inshore waters. They concluded that phytoplankton were the principal source of CDOM in offshore waters but not in the coastal zone. Similar results have been reported for the Baltic Sea (Kowalczuk, 1999). These results, along with reports by other workers of alternative pathways of CDOM formation (Fogg and Boalch, 1958; Yentsch and Reichert, 1961; Harvey et al, 1984; Seritti et al, 1994; Kieber et al, 1997), paint a complicated and, as yet, ill-defined picture of CDOM formation. Clearly, the precise mechanism(s) and rates of CDOM formation within the oceans remain to be determined. Although there is evidence that CDOM is produced within sediments (Skoog et al, 1996) and that high levels of CDOM absorption and fluorescence exist within sediment porewaters (Chen and Bada 1994; Skoog et al, 1996; Seritti et al, 1997), the amount of CDOM contributed to the water column by diffusion from this source has yet to be well quantified. Absorption levels (acDOM(355) from ~5 to 23 m~^) comparable to those of river end members have been reported for some sediments (Seritti et al, 1997). However, the absence of a readily apparent
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source in mixing curves from a variety of geographical regions (Fig. 8), as well as from vertical profiles (Vodacek et ai, 1997) suggests that this input is also small with respect to the terrestrial material delivered by the rivers. However, episodic resuspension events caused by storms could introduce significant pulses of porewater CDOM to shallow coastal waters, as recently reported by Boss et ai (2001). However, further work is clearly needed to better constrain the magnitude of this source. The possible atmospheric input of CDOM to coastal (and offshore) waters through wet and dry deposition has largely been ignored. Although likely to be trivial in coastal waters dominated by freshwater inputs, this source may have some influence on waters receiving little or no river input. Groundwater inputs to coastal regions could also act as a source of CDOM, but to our knowledge, this possibility has yet to be investigated.
B. SINKS (OR WHY AREN'T THE OCEANS HIGHLY COLORED?) In the absence of a sink of terrestrial CDOM, it would take only about 35,000 years for the oceans to reach the average river end member of CDOM absorption («CDOM(355)~5-15 m~^; Fig. 8), assuming the present-day total annualriverflow of about 4 X 10"^ km^ year"^ and ocean volume of about 1.4 x 10^ km^. The existing large gradient between the freshwater (<3CDOM(355)~10 m"^) and "blue water" (acDOM(355)~0.05 m"^) end members (see Fig. 8 and Nelson and Siegel, Chapter 11) implies the presence of a loss mechanism acting over far shorter time scales, on the order of several hundred years or much less, if a substantial amount of CDOM is also created in situ. This rapid loss of terrestrial CDOM is consistent with the near absence of organic biomarkers of terrestrial DOM in the open ocean (Hedges et ai, 1997; Opsahl and Benner, 1997), as well as with estimates of the rate of terrestrial DOM loss via photochemical processes (Kieber et ai, 1990; Mopper et ai, 1991; Miller and Zepp, 1995; Andrews et ai, 2000; see below). Early studies by Sholkovitz (1976) and Sholkovitz et ai (1978) indicated that humic acids were largely removed by flocculation and precipitation at low salinities, thus giving rise to the impression that most terrestrial CDOM was lost by this pathway within estuaries. However, many later field studies have observed conservative (or quasi-conservative) mixing of CDOM absorption with seawaters (Fig. 8), thus indicating that its loss by precipitation is likely to be inconsequential in most estuaries. This conclusion is further supported by studies in which fresh or lower salinity waters have been mixed in various proportions with higher salinity, oUgotrophic seawaters; the levels of CDOM absorption (or fluorescence) in these mixtures agreed with those predicted from simple dilution (Blough et ai, 1993; De Castillo et ai, 1999). Currently, there is no evidence that the optical changes
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occurring at higher salinities (Fig. 6) are a result of the removal of (terrestrial) CDOM by coagulation and precipitation. Unlike the well-defined biomolecules that make up a significant portion of the total DOM, terrestrial CDOM appears to be a complex composite of organic moieties coupled in ways that have yet to be defined. Because of the complexity of this material, bacteria do not seem to have the repertoire of enzymatic activities needed to degrade it readily. Thus, available studies indicate that terrestrial CDOM is largely resistant to direct microbial mineralization; absorption losses attributable to microbial degradation have been found to be very small, even following extended periods of incubation (Moran et al, 2000). However, photochemical reactions, leading to products that can be respired by bacteria (Kieber et al, 1989, 1990; Wetzel et al, 1995), appear to accelerate this process for terrestrial DOM (Miller and Moran, 1997; Moran et al, 2000). In contrast, photochemistry seems to inhibit the microbial degradation of algal-derived DOM (Benner and Biddanda, 1998; Tranvik and Kokalj, 1998; Moran et al, 2000). Regardless of the role of bacteria in metabolizing the photochemical products of CDOM, a now large number of both laboratory and field studies have shown that photochemistry alone can act as a substantial sink of terrestrial CDOM (Mopper and Kieber, Chapter 9), particularly as evidenced by the relatively rapid photochemical loss of its absorption and fluorescence when irradiated with wavelengths in the UV-B and UV-A (Fig. 2). Laboratory experiments on (optically-thin) natural waters have shown absorption losses greater than 50% over irradiation periods of several hundred to one thousand hours using sources approximating the surface solar spectrum. The time scale of these losses, on the order of weeks to months under natural irradiation conditions, is consistent with those observed in field studies (Vodacek et al, 1991 \ Nelson et al, 1998). We have also observed that these treatments produce an increase in S (Fig. 2; Del Vecchio and Blough, accepted for publication), in agreement with some previous laboratory and field studies (Fig. 6A; Vodacek et al, 1997; Moran et al, 2000; Whitehead et al, 2000), but not with all (Miller, 1994; Morris and Hargreaves, 1997; Gao and Zepp, 1998). The precise origin of these differences remains to be resolved, but may be related to the method employed for acquiring the spectral slope (Section II). At early times, fluorescence losses (excitation at 355 nm) generally exceed the absorption, but at later times, both decrease at approximately the same rate; this produces a small, but rapid initial drop in the quantum yield (0355), which then remains constant (Del Vecchio and Blough, accepted for publication). This result would appear to explain in part why only small variations in ^355 are observed for waters experiencing significantly different light histories (Section III; Vodacek et al, 1997). Evidence from field studies also supports a relatively rapid photochemical sink ofCDOM (Morris and Hargreaves, 1997; Vodacek ^r a/.; 1997; Nelsons? a/., 1998; Twardowski and Donaghay, 2001). CDOM absorption is observed to decline significantly in the surface waters of both lakes (Morris and Hargreaves, 1997) and
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the oceans (Nelson et al, 1998) with stratification of the water column over the spring and summer months, and to increase over the fall and winter months with increased vertical mixing and lower solar irradiance. In coastal waters, high (seasonal) river inputs of CDOM and strong vertical mixing can often mask the effects of this photobleaching. Because of the high CDOM absorption in estuarine and near-shore waters, photobleaching is restricted to a very thin surface layer and its effects averaged over a much larger mixed layer (or water column). Only when CDOM absorption is diluted to the point that the average penetration depth of the photochemically active UV-B and UV-A wavelengths becomes comparable to the mixed-layer depth, will the effects of photobleaching become readily apparent (Del Vecchio and Blough, accepted for publication); additional requirements are a stable mixed-layer and reasonably high solar irradiance. These conditions appear to be met for the shelf waters of the U.S. MAB over the late spring and summer; as stratification develops over the summer, the more-dilute CDOM on the shelf is isolated in a increasingly shallower mixed-layer. In this situation, the nonlinear dependence of CDOM absorption (and fluorescence) on salinity indicates the presence of a substantial sink of CDOM in surface waters, but not in the deeper waters below the thermocline where the CDOM is protected from photobleaching (Fig. 5; Vodacek et al., 1997). Further, CDOM in these surface waters shows an increase in S (Fig. 6A) and lower absorption to DOC ratios than those of the deep waters, or of surface waters on the shelf in other seasons when the water column is well mixed (Fig. 7). These results point to a strong photochemical sink of CDOM in the surface waters over the sunmier months and have been used to estimate the extent of the photochemical conversion of DOC to dissolved inorganic carbon in the mixed layer (Vodacek et al, 1997). In contrast, conservative mixing is usually observed in seasons of higher river input and lower solar irradiance and when stratification breaks down (Fig. 5). Results very similar to those acquired for the MAB in summer are also obtained during the high flow period of the Orinoco River (Blough et al, 1993; Del Castillo et ai, 1999). Conservative mixing behavior is seen for the low and intermediate salinity waters (Gulf of Paria, Fig. 8), where S and the excitation/emission maxima of the CDOM remain largely unchanged (Fig. 6A). However, at higher salinities (30-33) in the central eastern Caribbean, S begins to increase (Blough et al, 1993) and the excitation/emission maxima blue-shift (Del Castillo et al, 1999). This seemingly general behavior may simply reflect the fact that river waters must be sufficiently diluted within the surface mixed layer before the effects of photobleaching become readily observable. Although both field and laboratory studies suggest that photochemistry acts as a significant sink of CDOM, it remains to be determined whether photochemistry is the principal sink of the CDOM. Only recently has detailed, spectrally resolved models of CDOM photobleaching become available (Del Vecchio et al, 1998; Miller and Kuhn, 2000; Del Vecchio and Blough, 2001). These models, combined
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with physical mixing models, should provide a much better understanding of the magnitude and time scale of this process.
V. SUMMARY AND FUTURE AREAS OF RESEARCH Substantial amounts of terrestrial CDOM are introduced into the oceans every year, yet on average, the oceans are quite transparent. Photochemistry, perhaps combined with microbial processing, currently appears to be the most viable of the possible mechanisms acting to eliminate the CDOM. A global CDOM "color" budget has yet to be achieved due primarily to our ignorance of the magnitude of the in situ production, in both the water column and the sediments. Currently, we know very little about the mechanisms, time scales, or extent of this production, or how this material compares with the terrestrial material. Further, other than the Orinoco River, and to a much lesser extent the Amazon, we have very little spectroscopic information on the CDOM input by the major river systems of the world. On a more fundamental level, we know almost nothing about the structures of the underlying chromophores giving rise to the unique absorption spectrum of the CDOM. The limited sensitivity of current spectrophotometric methods represents a significant barrier to further progress in field studies, particularly for offshore regions. Although a number of approaches to improving sensitivity have been proposed (D'Sa et al, 1999; Pope et al, 2000), these methods have not yet come into common practice. As pointed out repeatedly in this article, another hindrance is the lack of a common set of protocols for the acquisition and reporting of spectroscopic data. Although this article has focused primarily on the "chromophoric" aspects of CDOM, this material also exhibits a rich tapestry of photochemical reactions (Blough, 2001; Mopper and Kieber, Chapter 9). While the mechanisms and magnitude of these reactions have continued to be slowly unraveled over the past several decades, the importance of abiotic photochemistry to upper ocean biogeochemical processes has only become evident to the general oceanographic community within the past 5 to 10 years. This recent interest should ensure that the role of photochemistry in the element cycles of the upper ocean and in air-sea interaction will continue to be an active area of investigation.
ACKNOWLEDGMENTS We gratefully acknowledge the Office of Naval Research for their continued support of this work. This work was also supported in part by the United States Environmental Protection Agency through the Science to Achieve Results (STAR) program.
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Chapter 11
Chromophoric DOM in the Open Ocean N o r m a n B. N e l s o n and D a v i d A. Siegel Institute for Computational Earth System Science, University of Cahfomia, Santa Barbara, Santa Barbara, Cahfomia I. Introduction A. A Short History of CDOM Research in the Open Ocean II. Characterization of CDOM A. An Operational Definition of CDOM B. Optical Properties of CDOM C. Chemical Composition of CDOM D. Methods for Quantifying CDOM III. Observed CDOM Dynamics A. Impact of CDOM on the Underwater Light Field B. Local Sources and Sinks of CDOM IV. Global CDOM Distribution Patterns
A. Global Distribution of CDM Absorption from SeaWiFS B. Temporal Variability of the Global CDM Distribution C. Controls on the Global CDM Distribution V. Relationship Between DOM and CDOM in the Open Ocean VI. Implications for Photochemistry and Photobiology A. Photochemistry and the Carbon and Sulfur Cycles B. Photoinhibition of Photosynthesis and Microbial Growth VII. Needs for Future Advances References
L INTRODUCTION Recent research has shown that the optically active fraction of dissolved organic matter (chromophoric DOM, or CDOM, also called "gelbstofP' or "gilvin") plays Biogeochemistiy of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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a major role in determining underwater light availability in the open ocean (Siegel etal, 1995; Siegel and Michaels, 1996; Vodacek^ra/., 1997; Nelson ^r a/., 1998; Blough and Del Vecchio, Chapter 10). We define the open ocean as the part of the global ocean where coastal runoff and riverine input are negligible on annual time scales. Furthermore, these aforementioned studies have suggested that significant variability in CDOM concentrations occur on the seasonal to interannual time scales in the upper water colunm. This "picture" of open ocean CDOM differs from the traditional view where light absorption by CDOM was thought to be minor and that CDOM variability was not significant on annual time scales. The change in our perception of CDOM dynamics is important because CDOM can play a direct or indirect role in climate-related biogeochemical cycles, particularly the carbon and sulfur cycles (Mopper and Kieber, Chapter 9). Absorption of light by CDOM controls ultraviolet radiation penetration into the ocean, which has an impact upon phytoplankton and bacterial productivity. CDOM is also a primary reactant in the photoproduction of CO2, CO, H2O2, and OCS and is a photosensitizer in the photolysis of DMS. Because of its impact upon the underwater light field, CDOM can influence the accuracy of global satellite-based measurements of ocean chlorophyll and primary productivity. The purpose of the present chapter is to present recent results of CDOM dynamics in the open sea and to introduce a new synthesis of the factors regulating the global CDOM distribution.
A. A SHORT HISTORY OF CDOM RESEARCH IN THE OPEN OCEAN Optical oceanographers working in the Baltic Sea first related CDOM concentrations to the observed freshwater fraction or salinity of a water mass (e.g., Kalle, 1938; Jerlov, 1953, 1976; H0jerslev, 1982). These observations, as well as recent ones (e.g., Blough et ai, 1993; Vodacek et al, 1997; Del Castillo et al, 1999; Ferrari, 2000), demonstrated that, as the salinity approaches oceanic values, inferences of CDOM concentration decrease to nearly undetectable levels (Blough and Del Vecchio, Chapter 10). This suggests that the source of oceanic CDOM is terrestrial runoff and that oceanic CDOM concentrations can be used as a tracer for terrestrial DOC. On the other hand, organic geochemists have shown that open-ocean DOM contains only small amounts of organic molecular markers for materials of terrestrial origin (cf., Meyers-Schulte and Hedges, 1986; Hedges et al, 1997; Opsahl and Benner, 1997) and that processes in sediments release CDOM into the water column (e.g., Chen, 1999). These results imply that open-ocean concentrations of colored dissolved organic matter are derived from the long-term (multiyear) breakdown products of marine productivity, as has also been proposed (e.g., Kalle, 1966;Bricaud^ra/., 1981; Hedges ^r a/., 1997). Together, these results suggest that CDOM distributions in coastal regions will be strongly affected by land-ocean interactions, whereas in the open ocean, CDOM concentrations will reflect local creation and destruction processes.
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Theoretical and practical use of satellite ocean color data was enhanced by the "bio-optical" assumption which relates upper ocean optical properties to the concentration of the phytoplankton pigment, chlorophyll a (e.g., Smith and Baker, 1978). These studies classified the ocean into "Case I" waters, where optical properties CO-vary with chlorophyll concentrations in a predictable manner (Morel, 1988), and "Case IF' waters, where the influence of CDOM, detrital particulate absorption, and/or particulate scattering destroys this simple correlation. The Case I assumption is useful as it allows the development of simple empirical algorithms relating ocean color and phytoplankton biomass (Morel, 1988; O'Reilly et al, 1998; Morel and Maritorena, 2001). For Case I waters, the contribution of CDOM and detrital absorption is assumed to be small, which has inhibited CDOM research away from coasts and estuaries. Results of recent open-ocean CDOM studies suggest that there is decoupling of the optical signatures of CDOM and phytoplankton biomass (Siegel and Michaels, 1996; Vodacek et a/., 1997, Nelson et al, 1998) on the seasonal scale in the open ocean. These results highlight limitations in simple ocean color algorithms that use chlorophyll concentration as the only index of water optical properties. On the other hand, the lack of correspondence between CDOM and phytoplankton absorption leads to the possibility of using ocean color data to quantify CDOM as well as the chlorophyll concentration (Roesler and Perry, 1995; Garver and Siegel, 1997; Carder et al, 1999; Hoge and Lyon, 1996; Maritorena et al, in press). Efforts to apply these techniques on a global scale with the goal of obtaining a better understanding of the role of CDOM in biogeochemical cycling and ocean ecology are underway (Siegel et al, in press). Other ongoing efforts in CDOM-related research include an assessment of photochemical transformations of DOM on its biological lability and upon carbon cycle in a general sense (e.g., Kieber et al, 1989; Moran and Zepp, 1997; Mopper et al, 1991; Miller and Zepp, 1995; Mopper and Kieber, Chapter 9). These studies have been mostly focused upon the transformations of terrestrial CDOM in estuarine and coastal waters but many of the processes involved are relevant to the open ocean. Only recently have detailed studies investigated the roles of photochemical transformations of DOM on food-web interactions and the open-ocean biogeochemistry.
11. CHARACTERIZATION OF CDOM A. A N OPERATIONAL DEFINITION OF CDOM A complete characterization of open-ocean CDOM is compUcated, as it requires the understanding of the optical and chemical factors that comprise CDOM. Compounding this is the few open-ocean observations of CDOM dynamics. Like all DOM, the definition of CDOM is the manifestation of procedure used to separate a
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water sample into "particulate" and "dissolved" fractions. Hence, the definition of CDOM is strictly operational. Typically, CDOM is defined as organic substances which absorb UV or visible light that have been passed through a submicrometer filter. In some cases combusted GF/F glass fiber filters (effective pore size 0.7 ixm) are used but in most cases preconditioned O.l-fjim polycarbonate Nuclepore filters or mixed-ester Millipore filter cartridges are used to separate the dissolved and particulate fractions. Depending on the method the dissolved fraction may include, for example, viruses and colloids as well as truly dissolved materials (e.g., Shifrin, 1988). Concentration and isolation of CDOM from the bulk pool in fresh or coastal waters has been accomplished by using XAD ion-exchange resins, which take advantage of the hydrophobic and acid nature of humic materials (e.g.. Carder et aL, 1989). These techniques have allowed characterization of the humic and fulvic acids in seawater, but it is unlikely that open ocean CDOM is composed entirely of water-soluble organic acids (Harvey and Boran, 1985). Other techniques used have included C-18 hquid chromatography (Coble et al, 1990) and ultrafiltration (Mopper et al, 1996) but these have not yet been widely used to study CDOM in the open ocean. Therefore, CDOM in oceanic systems is usually assessed by its optical activity; either by its absorption or fluorescence properties.
B. OPTICAL PROPERTIES OF CDOM The absorption of light by water, suspended material (phytoplankton and other particles including nonliving detritus), and CDOM control the propagation of solar radiation through the water column (e.g., Jerlov, 1976; Shifrin, 1988; Kirk, 1994a; Mobley, 1994). Of these four absorbing components, water absorbs visible light primarily in the red and yellow portion of the spectrum and light of these colors is attenuated rapidly within the water colunm. Phytoplankton absorb light mostly in the blue and blue-green regions of the spectrum, with a secondary absorption peak in the red, giving rise to the green to golden color of most phytoplankton. CDOM absorbs primarily ultraviolet and blue light and is also fluorescent. Natural waters containing large amounts of CDOM appear yellowish in color, thus the terms "gelbstofF' (Kalle, 1938), "yellow substance" (Shifrin, 1988), and "gilvin" (Kirk, 1994a). Despite the fact that CDOM is a mixture of chromophores, absorption spectra of CDOM are typically featureless in the visible (400-700 nm) and UV-A (320400 nm) portion of the spectrum, declining exponentially with wavelength (Fig. 1). Because of this, CDOM spectra are usually parameterized as an exponential function with a single slope parameter, 5, (Bricaud et al, 1981), or a^(X) = a^(Xo)e-'^^-^^\
[1]
where a^iX) is the absorption coefficient of CDOM at wavelength X (m~^), XQ is a reference wavelength, and S is the exponential slope parameter (nm~^). At shorter
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350
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450 500 550 Wavelength (nm)
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Figure 1 Absorption spectra of CDOM and particulate matter from the Sargasso Sea, July 1999. Thin solid lines: CDOM absorption spectra from 1, 60, 100, and 200m (see inset for vertical profile of CDOM absorption at 350 nm [o]). Fine dotted lines are extrapolations from exponential curve fits using the 325- to 380-nm range as a basis. Heavy line is the absorption spectrum of particulate material (mostly phytoplankton) from 100 m. The higher exponential slope in the surface CDOM spectrum is visible, as are non-log-linear features in the spectra at wavelengths below 320 nm. (Inset) Vertical profile of CDOM absorption coefficient (O) and particulate matter (A) at 350 nm. Arrows show the depths of collection of the different spectra shown in the main figure.
wavelengths (<320 nm), the CDOM absorption spectrum has features which do not allow the exponential approximation to apply. Values of 5" found in the literature range typically from 0.014 to more than 0.025 nm"^ but these results are difficult to compare because of the various wavelength ranges and curve fitting techniques used to compute S (Bricaud et al, 1981; Carder et ai, 1989; Green and Blough, 1994; Blough and Del Vecchio, Chapter 10). Higher values of 5 are typically found
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where and when CDOM absorption is fairly small. Particulate detrital absorption spectra usually decrease uniformly with wavelength in a manner similar to CDOM (e.g., Roesler etai, 1989; Iturriagaand Siegel, 1989). Typical slope parameters for particulate detrital absorption are noticeably smaller than those found for CDOM. It seems likely that the parameter S reflects relative proportions of the various chromophores found within the CDOM pool. Several investigators have suggested that the value of S can be used as an indicator of the origin or history of a given CDOM water sample. For example, Carder et al (1989) diagnosed variations in the S parameter for CDOM in Gulf of Mexico in terms of the relative proportion of humic and fulvic acids in a water sample. Blough et al (1993), Nelson et al (1998), and Whitehead et al (2000) attributed certain changes in S to selective bleaching of CDOM components by solar radiation. Nelson and coworkers (unpublished data) have also diagnosed S in Sargasso Sea CDOM as reflecting the relative contribution of newly created, biologically semilabile CDOM vs older, more refractory CDOM. Clearly, the interpretation of S parameter variations remains an open question and one that may eventually provide important information about the state and/or history of the CDOM pool.
C. CHEMICAL COMPOSITION OF CDOM The compounds which make up CDOM in the open sea remain largely undefined. The polysaccharides which are known make up much of the total DOM in ocean systems (e.g., Benner et al, 1992; Aluwihare, et al, 1997) are not known to be optically active at visible wavelengths. Thus much of the DOM produced by excretion from phytoplankton or net community production (e.g., Biersmith and Benner, 1998; Hansell and Carlson, 1998; Aluwihare and Repeta, 1999) must be altered before becoming part of the CDOM pool. Terrestrial-origin CDOM which is introduced to the coastal ocean by rivers and runoff is composed largely of humic and fulvic acids (Harvey and Boran, 1985; Carder et al, 1989). These are organic acid polymers derived from the breakdown of higher plant matter (Opsahl and Benner, 1998) by microbes in soil or sediments. These compounds resist degradation by microbes and solar radiation and may make up an unknown portion of the "background" level of CDOM observed in the open sea (e.g.. Nelson et al, 1998). However, terrestrial DOM is thought to make up less than 5% of the total DOM in the open ocean (Opsahl and Benner, 1997). Humic and fulvic acids in the open ocean are distinct from terrestrial humic material and may result from the reaction of fatty acids released by phytoplankton (Harvey and Boran, 1985). Additional contributors to the CDOM pool may include amino acids and peptides, nucleic acids and bases, urea, and other low-molecular-weight compounds. These substances are generally very dilute in concentration in the water column
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as phytoplankton and bacteria readily utilize them. A significant fraction of the high molecular weight (>1000 Da) dissolved organic matter in the open ocean is thought to consist of polysaccharides (Benner et al, 1992). Nitrogen-15 nuclear magnetic resonance (NMR) analyses of dissolved organic nitrogen (DON) from the central North Pacific suggests that amide compounds, proteins or chitinous compounds (from the breakdown of zooplankton exoskeletons), account for the majority of DON in the water column (McCarthy et al, 1997). These ^^N NMR analyses suggest that melanoidins (e.g., compounds formed from peptides and sugars by the Maillard reaction; Kalle, 1966) are a much smaller fraction of the total DON pool. Chitins and melanoidins are also optically active and are probably less readily consumed by bacteria and phytoplankton than the smaller compounds. Direct release of UV-absorbing compounds (mycosporine-like amino acids) into the water column by some phytoplankton has been demonstrated (Vemet and Whitehead, 1996; Whitehead and Vemet, 2000). These compounds may also contribute chromophores to the CDOM pool. Another way to assess the composition of CDOM is in terms of its "lability," or its biological reactivity. This is typically assessed in terms of the ability of the microbial community to consume the DOM in question. "Labile" DOM is consumed rapidly and does not necessarily appear in the water colunm, "refractory" DOM has a long lifetime and is resistant to microbial consumption, while "semilabile" DOM can be consumed but over a longer time period (Carlson et al, 1994; Carlson and Ducklow, 1996). The paradigm describing the formation of refractory humic materials from particulate organic material in the terrestrial environment involves microbial degradation of biopolymers into low-molecular-weight compounds, which subsequently undergo condensation reactions to form more refractory geopolymers (e.g., Rashid, 1985). This process impHes a decrease in lability with an increase in molecular weight. Irradiation of refractory CDOM is thought to yield reactive low-molecular-weight compounds which are more labile, and thus encouraging to microbial growth (e.g., Lindell et al, 1995; Bushaw et al, 1996; Moran and Zepp, 1997; Anderson and WilHams, 1999). On the other hand, some studies have indicated that irradiation of CDOM does not necessarily result in increased lability, and that some lower molecular weight compounds are actually less reactive than their larger precursors (Tranvik and Kokalj, 1998). The impact of solar irradiation on the chemical and biological properties of CDOM in the open sea remains an important ongoing research question. As will be described in more detail below, the time series record at the Bermuda Atlantic Time-Series Study (BATS) shows a near-inverse relationship between CDOM and DOC concentrations (Siegel and Michaels, 1996; Nelson et al, 1998). For example, summertime depletions in DOC concentrations observed in the seasonal thermocline co-occur with local increases in CDOM absorption. A similar lack of correspondence is seen in the summertime mixed layer. This complete lack of correlation between DOC and CDOM indicates that they are regulated by very
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different processes. Further, as large relative changes in CDOM seem to have no impact upon the DOC concentration (cf. Fig. 8), this result suggests on a mass basis that CDOM comprises a small fraction of the total DOM pool (e.g., Siegel and Michaels, 1996). These observations will be further explored later in this chapter.
D. METHODS FOR QUANTIFYING CDOM At this time, CDOM is distinguishable from total DOM only by its optical activity. The standard method for estimating the absorption spectrum of CDOM involves measuring the optical density of filtered seawater samples relative to highly purified fresh water in 10-cm quartz-windowed cuvettes, using a conventional spectrophotometer (Green and Blough, 1994; Vodacek et ai, 1997; Nelson et ai, 1998). There are two drawbacks to this methodology in open-ocean systems: first, many water purification systems do not produce sufficiently CDOM-free water, and second, conventional spectrophotometers do not have sufficient sensitivity to detect the slight absorption which occurs over a 10-cm path of open-ocean water (e.g., Mitchell etai, 2000). High-quality laboratory spectrophotometers can detect CDOM absorption in 10 cm cells down to approximately 0.05 m~^ (range 0.03-0.07 m~^) which is near the average absorption coefficient of CDOM at 400 nm in the Sargasso Sea (Kirk, 1994a; Nelson et al, 1998). Absorption at longer wavelengths can be estimated by extrapolation from valid measurements using the exponential approximation (Eq. [1]), but of course it is difficult to assess the accuracy of this technique. A possible method for overcoming the Umitations of conventional spectrophotometry involves using custom long-path cells (Bricaud et ai, 1981) or capillary optical waveguide cuvettes (D'Sa et ai, 1999) but to date these instruments are not in routine use except in a few laboratories. Even if these advanced techniques were to become popular, a 1-m pathlength will not enable CDOM measurements throughout the visible spectrum in open-ocean seawater unless photometric accuracy also increases dramatically. Thus objective measurements of CDOM light absorption in the open sea will remain difficult to obtain. An in situ method for measuring CDOM absorption was developed by Twardowski et ai (1999) using paired WETLabs AC-9 absorption meters. This instrument is composed of a "shiny tube" absorption instrument (Zaneveld et al, 1992) which measures the total absorption coefficient (i.e., the sum of water, dissolved material, and particulate absorption coefficient) and a transmissometer, which measures the beam attenuation coefficient (sum of absorption and scattering coefficients) at nine discrete visible-light wavelengths in a flow-through 0.25-m tube. CDOM absorption coefficient can be estimated from two AC-9 instruments by placing an in-line filter on the incoming water line of one of the instruments to capture particles larger than 0.2 iim and to subtract off the signal from an
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unfiltered instrument. The principal advantages of this technique over standard laboratory spectrophotometry of discrete samples is that high-resolution profiles can be measured (Twardowski et al, 1999) and the increased sensitivity due to the longer pathlength of the AC-9 optics makes routine measurements to ca. 550 nm in open-ocean waters possible. An unknown fraction of the absorbing chromophores which make up CDOM are also fluorescent (often termed FDOM). In coastal and continental shelf waters, empirical relationships have been developed between FDOM fluorescence and absorption of CDOM using UV excitation and blue emission (e.g., Hoge et al, 1995; Ferrari andTassan 1991; WodaceketaL, 1995; Chen, 1999) but these seem to be specific to the composition of CDOM and are not universal. This limits the utility of FDOM measurements for assessment of CDOM dynamics. Decoupling between CDOM absorption and FDOM fluorescence decrease with salinity was noted by Kalle (1966), who attributed the decoupling to mixing of fresh water CDOM with material of offshore origin, and by Vodacek et al. (1997) who attributed the decoupling to selective bleaching of selected chromophores. On the other hand, deep-ocean profiles of FDOM (measured with single excitation and emission bands) provide clues as to the deep-ocean distribution of CDOM (Chen and Bada, 1992; Hayase and Shinozuka, 1995; Determann et al., 1996; Karabashev, 1999; Section III.B). Patterns of fluorescent chromophore distribution can be elucidated using synchronous fluorescence spectroscopy (Ferrari and Mingazzini, 1995) and excitation-emission matrix spectroscopy (Coble, 1996). To date these techniques have mostly been used in coastal waters and in the coastal transition zone. Fluorescent "fingerprints" have been used to discriminate between terrestrial sources of fluorescent CDOM and between coastal and offshore-origin CDOM, as well as different oceanic water masses (Coble et al, 1990, 1998; Del CastiUo et al, 1999, 2000). These results highlight the diversity of the compounds which make up CDOM. As with absorption spectroscopy, the use of fluorescence spectroscopy to characterize open-ocean CDOM is limited by low ambient concentration. The exponential decrease of absorption with wavelength still limits the amount of information that can be gained from visible wavelengths. Another important set of methods for estimating CDOM light absorption rely on its known impact on the underwater light field. We will refer to these methods hereafter as inversion methods. Inversion methods for CDOM can be based upon determinations of the vertical attenuation of downwelling spectral irradiance or upon the reflected light spectrum. The latter approach may be applied using satellite ocean color data sets enabling global distributions to be assessed. The former method provides a more direct measure of the absorption properties of the water column with fewer corrections for backscattering and geometric issues. Obviously, these inverse methods are not filtering seawater and the operational designation of CDOM from other optically similar absorbing materials cannot be made. The
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difficulty is that the optical properties of detrital particles and CDOM are similar enough that inverse methods can provide a determination only of their combined effects (Carder et al, 1989, 1999; Siegel and Michaels, 1996; Garver and Siegel, 1997). As we will see below, the contribution of detrital particles on a global scale is small. We will refer to the combined absorption due to CDOM and detrital particles as "colored detrital materials" or CDM, which highlights its origin as a recycled material. The decrease of spectral irradiance with depth can be used to compute the diffuse attenuation coefficient spectrum, A'^(A), which is to first order a function of absorption (Kirk, 1994a; Mobley, 1994). In the open ocean, the diffuse attenuation coefficient spectrum is generally computed over depth intervals up to 10 m, thereby overcoming the limited pathlength problem found in the laboratory. Siegel etal (1995) and Siegel and Michaels (1996) partitioned KdQC) determinations into components for water, phytoplankton, and colored dissolved and detrital materials. This partitioning took advantage of the fact that the optical properties of phytoplankton are distinct from those of CDM (Fig. 1). This work assumed fixed values for the spectral CDM slope parameter and the chlorophyll-specific absorption coefficient spectrum for phytoplankton which enabled the time-depth variability of CDM at the BATS site to be assessed (Siegel and Michaels, 1996). A host of investigators have developed semianalytical models to differentiate CDM from chlorophyll absorption using remote sensing reflectance spectra computed from in situ radiometric data (Roesler and Perry, 1996; Garver and Siegel, 1997; Hoge and Lyon, 1996; Carder et aL, 1999; Maritorena et ai, in press). These models can be applied to global ocean color imagery, such as from the SeaWiFS sensor. A globally optimized version of the Garver and Siegel (1997), known as the UCSB (University of California, Santa Barbara) inverse ocean color model, has been used to provide the first assessment of global near-surface CDM distribution (Section IV). The UCSB ocean color model is based upon four basic assumptions: (1) an analytical relationship between the ocean color spectrum and the inherent optical properties (i.e., the absorption and backscattering coefficients) is known, (2) pure seawater optical properties are known, (3) a small number of dissolved and particulate constituents contribute to variations in absorption and backscattering coefficient, and (4) the spectral shapes of these dissolved and/or particulate constituents are assumed to be constant or at least can be parameterized. The application of these assumptions results in an analytical model for ocean color as measured by a remote sensing instrument, with only the magnitudes of the constituent values to be determined. This problem is then solved for the unknown magnitudes (including CDM absorption) by solving the resulting nonlinear least-squares problem. A description of the model may be found in Garver and Siegel (1997) and its global optimization in Maritorena et al. (in press), respectively. Global results of this method appUed to SeaWiFS ocean color imagery are discussed below (from Siegel et al., in press).
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III. OBSERVED CDOM DYNAMICS A. IMPACT OF CDOM ON THE UNDERWATER LIGHT FIELD An analysis of the component light absorption budget provides valuable insights into the relative importance of CDOM to light availability and ocean color. The total absorption coefficient spectrum, a(X), may be partitioned into components due to seawater, ay,{X), phytoplankton, aph(A), CDOM, ag(X), and detrital particles, «det(^), or
a(X) = a^{k) + aph(A,) + ag(X) + adet(^),
[2]
where aw(^) is assumed to be a known constant (Smith and Baker, 1981; Pope and Fry, 1997). As described previously, the spectral shapes of CDOM [ag(X)] and detrital particulate [adetC^.)] absorption are similar. Hence, inverse methods cannot yet differentiate between these two signals. Available spectroscopic observations from the surface waters of many sites from around the world suggest that nonwater absorption is dominated by CDOM. For example, surface layer observations from the Sargasso Sea show that CDOM and detrital particulate absorption comprises 72% (15% SD; n = 143) of the nonwater absorption at 440 nm while detrital particles contribute only 9% (9% SD; n = 143) of this total (Nelson et al, 1998, with additional data). Analyses using a global data set of surface component absorption observations show that on the average 57% (16.4% SD, n = 1365) of the nonwater absorption at 440 nm is due to CDOM and detrital particles while 17.8% (14.0% SD, n = 1365) of this absorption is due to detrital particles (Siegel et al, unpublished data). Further, there is a general trend that as chlorophyll levels increase, the contribution made by CDOM and detritus decreases. At a chlorophyll concentration of ^^0.5 mg m~^ the influence of phytoplankton and CDOM absorption are about the same. A disproportionate fraction of this global data set is coastal (the data set mean chlorophyll concentration is 1.45 mg m~^ compared with mean values from SeaWiFS 0.36 mg m~^). Hence, it is expected that the actual contribution of detrital particles on a global scale will be much smaller than the factors cited previously. In sunmiary, CDOM absorption dominates the total absorption budget over most of the open ocean (chlorophyll concentrations less than 0.5 mg m"-^) and detrital particles will make a small contribution to the CDOM absorption signal determined from inversion methods (Siegel et al, in preparation).
B. LOCAL SOURCES AND SINKS OF CDOM Geochemical evidence demonstrating that terrestrial-origin DOM is a small fraction of total DOM (Meyers-Schulte and Hedges, 1986; Opsahl and Benner, 1998) as well as field results which show large seasonal time-scale variations
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in CDOM highlight the importance of local biological processes on open ocean CDOM. Local sources and sinks in the open sea may include not only production and consumption of CDOM due to biological processes, but also upwelling and convective export. At this point in time, it is clear that much of the open ocean CDOM is cycled by local processes although neither the details of the nature of these processes (i.e, microbial, phytoplankton exudation, photochemical bleaching, etc.) nor their variability in space and time has been established. The first multiyear time series of CDOM measurements in the open sea was made in the subtropical Sargasso Sea near Bermuda at the BATS site (Nelson et ai, 1998). Optical measurements made at BATS by the Bermuda Bio-Optics Project (Siegel et al, 1995) revealed a seasonal pattern in spectral light availability that was interpreted as seasonal variability in CDOM and/or particulate detritus absorption (Siegel and Michaels, 1996). The hypothesized seasonal variability of CDOM was confirmed using spectroscopic data and showed that particulate detritus was a small contributor to the signal (Nelson et al, 1998). A well mixed water column and roughly homogenous distribution of CDOM in the winter months changes each year to a distinct surface minimum-subsurface maximum pattern during the summer (Fig. 2). In fact, the divergence between the surface minimum and subsurface maximum tends to increase over the course of the sunmier while phytoplankton productivity remains low (Nelson et al, 1998). The pattern is repeated on an annual basis as winter mixing homogenizes the water column. This is seen clearly in the relation between mixed layer depth and the depth-time distributions of CDOM (here shown as «g(325)) presented in Fig. 3 (see color plate). The observed seasonal CDOM cycle at BATS suggests a number of possible local sources and sinks. Processes which potentially produce CDOM in situ include release or excretion by organisms and lysis of cells by viruses. In the Sargasso Sea, during the annual spring phytoplankton bloom, there is a sUght increase in CDOM near the surface, which rapidly decreases with the onset of stratification (Fig. 3). This suggests the possibility that phytoplankton release CDOM during active growth, as DOM release by growing phytoplankton is well known and CDOM by growing phytoplankton has been shown to occur in a coastal dinoflagellate (Vemet and Whitehead, 1996; Whitehead and Vemet, 2000). However, the subsurface production of CDOM during the summer occurs mostly between 50 and 100 m (Fig. 2), which is typically shallower than the deep chlorophyll maximum layer (90-120 m) and is not at a depth of either elevated phytoplankton pigment biomass or primary productivity. The 50- to 100-m depth range supports the highest biomass and productivity of bacteria in the upper water column (e.g., Carlson et al, 1996), suggesting that the microbial community may be the source of the "new" summertime CDOM (Nelson ^r a/., 1998). Subsurface maxima in fluorescent CDOM have been observed in the open Pacific over similar depth regions (Chen and Bada, 1992; Hayase and Shinozuka,
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Figure 2 Seasonal averages of light absorption by CDOM (flg) at 325 nm, 1994-1999 (Nelson and Carlson, unpublished data). Horizontal bars are standard deviation/mean. Open circles are winter averages (Dec-Feb) and closed circles are summer averages (Jun-Aug). The winter average profile has features which result from interannual variability in mixed-layer depth. The summer profile reflects the combined effects of sunlight-mediated bleaching of CDOM near the surface and subsurface production of CDOM.
1995). In these studies FDOM concentration was closely related to inorganic nutrient distribution and apparent oxygen utilization, suggesting a link between microbial remineralization and FDOM. The assertion of a link between remineralization and CDOM or FDOM production is strengthened by results of microbial culture experiments using natural populations of bacteria growing in the dark, in seawater amended with organic and inorganic substrates (Nelson et al, 1998; Nelson, Carlson, and Steinberg, unpublished data). In these experiments CDOM light absorption increased in cultures with actively growing bacteria but decreased almost to the initial value over a period of days after the bacterial growth rate went to zero, indicating both production and consumption of CDOM by microbes (Fig. 4). In other experiments (not shown) up to 10% of the CDOM produced during the experiment remained for up to 90 days, indicating that this process does produce CDOM which is refractory enough to resist consumption within the water column.
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Figure 4 Time course of a microbial culture experiment using filtered seawater collected in the Sargasso Sea in late winter-early spring 1996 and incubated in the dark (Nelson and Carlson, unpubhshed data). Asterisks (*) are direct counts of acridine-orange-stained bacteria using fluorescence microscopy (units are 10^ cells L~^). Open circles (O) are absorption coefficient of CDOM at 300 nm (units are m~^). Vertical bars are standard deviation of rephcate samples. In this experiment CDOM was measured for 43 days after the beginning of the experiment; after that time the CDOM absorption coefficient was 0.33 m~^
Mechanisms for CDOM production as a consequence of bacterial production are unclear. The action of microbial extracellular enzymes on DOM is one possibility (e.g., Martinez etal, 1996). Reaction products that are not inmiediately assimilated by the bacteria may rejoin the DOM pool. Some reactions result in optically active products where the reactants are not optically active. The Maillard (1913) reaction between sugars and peptides is an example of such a reaction, although this particular reaction is not known to result from bacterial exoenzyme activity. Release of capsular material or exopoly saccharides by bacteria may also contribute to the CDOM pool. The impact of viral lysis in situ is also difficult to estimate, but it has been proposed that virus abundance is proportional to bacterial cell density (e.g., Guixa-Boixereu et al, 1999). However, culture experiments (e.g.. Fig. 4) suggest that if viral lysis is the process which releases CDOM from bacterial cells, the rate of lysis is proportional to bacterial productivity and not cell density. Disappearance of new CDOM from the dark culture experiments suggests that the majority of newly produced CDOM is labile (i.e., consumable by bacteria) and
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a small portion (ca. 10% or less) is more refractory. Hence, microbial processes are also a sink for CDOM. It is clear, however, that a large sink for CDOM in the open ocean is solar bleaching (Siegel and Michaels, 1996; Nelson et al, 1998; Siegel et al, in press). Sunlight-mediated CDOM bleaching has been well documented in culture and in the field (Mopper et al, 1991; Kouassi and Zika, 1992; Vodacek et al, 1991; Nelson et al, 1998; Andrews et al, 2000; Whitehead et al, 2000). The CDOM surface minimum found in the Sargasso Sea in the summer is thought to be caused by elevated bleaching rates due to CDOM being trapped near the surface during stratification (Siegel and Michaels, 1996; Nelson et al, 1998). The seasonal scale Sargasso Sea CDOM observations (Figs. 2 and 3) have been explained using a simple model of depth-dependent bleaching (decreasing exponentially with depth) and CDOM production proportional to specific bacterial production (Nelson et al, 1998). The model yielded scale estimates for the turnover time of CDOM in the Sargasso Sea due to bleaching of approximately 90 days and turnover time for production of 125-300 days. Estimated bleaching rates were consistent with apparent quantum yields for CDOM bleaching in the published hterature (e.g., Kouassi and Zika, 1992; Whitehead et al, 2000) when diurnal variations in irradiance were taken into account (Nelson unpubl. data). Extrapolation of this estimated bleaching rate over a deepening mixed layer (Nelson et al, 1998) was sufficient to explain the summer-winter decrease in CDOM (e.g.. Fig. 2) if it is assumed that the rate of photobleaching at the surface remains constant. This may not be the case as during the fall, as irradiance decreases and the mixed layer depth deepens. Hence it is possible that both bleaching and microbial consumption play important roles in drawing down CDOM in the Sargasso Sea. In summary, it is clear that CDOM has an important if not dominant role in prescribing light availability in the open ocean. The influence of CDOM will be even more important in the predicting availability of ultraviolet light which is critical for many photochemical reactions. A host of biological and photochemical processes are regulating the concentration of CDOM in the water column. The exact nature of these has yet to be fully documented and this appears to be a very exciting avenue for future research.
IV. GLOBAL CDOM DISTRIBUTION PATTERNS A. GLOBAL DISTRIBUTION OF C D M ABSORPTION FROM SEAWIFS The UCSB inverse model is used with SeaWiFS determinations of water-leaving radiance to provide global fields of CDOM and detrital particles (Fig. 5 [see color
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plate]). Again, the absorption coefficient due to both CDOM and detrital particles is determined using our inverse modeling approach (i.e., CDM) although detrital particulate absorption should be small relative to CDOM in the open ocean (see above). End-to-end errors in the application of the UCSB ocean color model to SeaWiFS water leaving radiance determinations are assessed by comparing satellite-retrieved values of CDM with near-simultaneous (within 4 days) field determinations of CDOM and detrital particulate absorption. This rough match-up data set shows that the satellite retrievals predict 64.3% of the variance (n = 523) in the field-observed CDM determinations with a near-perfect one-to-one line (Siegel et ai, in press). Hence, the preliminary satellite-derived CDM distribution presented here should reflect the actual distribution of CDOM and detrital particles with a rather high degree of fidelity. To first order, the global pattern of CDM absorption estimated from SeaWiFS ocean color imagery mimics the major gyre systems and other large-scale circulation features of the world ocean (Fig. 5; Siegel et al, in press). High values of CDM light absorption are found within regions of persistent large-scale up welling (e.g., subarctic gyres, equatorial divergences, eastern boundary currents, etc.), while low values are observed for regions characterized by largescale downwelling (e.g., subtropical gyres, western equatorial Pacific warm pool). The basin-scale CDM distribution appears similar in many ways to global distributions of chlorophyll concentration or primary production. This suggests that the same local processes that create regions of high phytoplankton biomass are regulating the near-surface CDM distributions. However, a robust statistical relationship is not found between retrieved CDM and chlorophyll concentrations (r^ = 0.34), suggesting that these factors vary independently. When evaluated at high spatial resolution, riverine inputs can be discerned in the CDM distribution although these effects are localized. However, it is apparent that inputs of terrestrial materials are not the first-order controls on the basin-scale CDM distribution (Fig. 5). The fraction of blue light absorption regulated by CDM can be quantified using its contribution of nonwater absorption at 440 nm (which we refer to as %CDM, for percentage contribution of CDM to nonwater absorption coefficient). On a global basis, the mean value of %CDM is 51.1%. This points again to a dominant role for CDOM and detritus in the absorption of blue light. The spatial distribution of %CDM shows a broad minimum in the tropical ocean where %CDM retrievals are approximately 45%. Toward the poles, values of %CDM increase dramatically (Fig. 5). The %CDM contributions also differ among the major ocean basins. Mean determinations of %CDM are higher for the Atlantic and Indian Oceans than for the Pacific Ocean. For example, the mean value of %CDM is 52.5% (SD 10.7%) for the North Atlantic subtropical gyre, whereas it is 45.8% (SD 9.3%) for the North Pacific subtropical gyre. The mean value of %CDM for the tropical Pacific Ocean is smaller than the other basins (mean 43.2%, SD 6.6%). These interbasin
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variations suggest regional differences in the processes that produce mixed layer concentrations of CDOM.
B. TEMPORAL VARIABILITY OF THE GLOBAL C D M DISTRIBUTION Significant temporal changes in CDOM and detritus (CDM) fight absorption and %CDM contribution are also observed in zonally averaged latitude-time distributions of both (determined for 440 nm, Siegel et al, in press). At latitude 30°N, seasonal changes in zonally averaged CDM retrievals vary by more than a factor of five, from ~0.005 m~^ to more than 0.03 m~^ Seasonal cycles are apparent throughout the subtropical gyres as CDM light absorption is reduced in the local summer and increased in the winter. Similar changes, though not as striking, are found throughout the record including the tropics. In general, CDM light absorption estimates are larger for the northern hemisphere subpolar region (north of 45°N) compared with the southern subpolar hemisphere (south of 45°S). The lowest CDM estimates are found in the southern hemisphere mid-latitudes due to the large extent of the South Pacific subtropical gyre. The character of seasonal changes is similar between sites within the North Atlantic and North Pacific subtropical gyres although their amplitudes are very different (Fig. 6). Near Bermuda, CDM estimates increase by more than a factor of two (Fig. 6a), whereas observations from near the Hawaiian Islands show weaker, though still significant seasonal patterns (Fig. 6b). The satellite-observed mean value of %CDM off Bermuda is approximately 55%, which is consistent with the spectrophotometric results presented previously while the %CDM values off Hawaii are considerably lower (approximately 42%). The lower amplitude of the seasonal cycle off Hawaii mirrors lower seasonal changes in primary production and chlorophyll a concentrations observed for this site north of Hawaii compared with the Sargasso Sea off Bermuda (Siegel et aL, 2001). Large intraseasonal changes are also observed. For example, a large pulse in CDM light absorption was observed during the summer of 1998 in the equatorial Pacific Ocean (0° 155°W) in response to the transition from El Nino to La Nina conditions (Fig. 6c). After this transition, retrieved CDM values increased by a factor of roughly 50% compared with the El Nino period before the transition. This result indicates that the onset of equatorial upwelling brings CDOM-rich subsurface waters toward the surface. Sustained equatorial upwelling after this event produces the increased levels of %CDM observed.
C. CONTROLS ON THE GLOBAL CDM DISTRIBUTION If CDOM is a long-lived product of the degradation of organic matter and photobleaching is its primary sink, then it is logical to assume that open-ocean CDOM
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Figure 6 Time series of CDM absorption coefficient (black, left axis) and %CDM (dotted, right axis) for sites in (a) the Sargasso Sea off Bermuda (BATS), (b) the subtropical Pacific ocean near Hawaii (HOT), and (c) the eastern equatorial Pacific ocean (0° 155°W). The time series of sea surface temperature (SST, °C) from the TOGA/TAO mooring at 0° 155°W is shown in (d). In (a) and (b), in situ radiometer observations (symbols) are also plotted (Siegel et al, in press). The field observations were collected and analyzed following the SeaWiFS in situ data protocols (Mueller and Austin, 1995) and the UCSB ocean color algorithm was applied.
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will be consistently depleted in stratified surface waters and enriched below. This pattern of increased CDOM absorption below the mixed layer is observed within the Sargasso Sea during the summer when the water column stability is high (Fig. 3). Increased CDOM values with depth have been also observed from the Arabian Sea and Equatorial Pacific (Pegau, 1996; Del Castillo et ai, 2000) and in vertical distributions of CDOM fluorescence from the world ocean (Chen and Bada, 1992; Hayase and Shinozuka, 1995; Determann et aL, 1996; Karabashev, 1999). Hence, it appears likely that elevated CDOM concentrations will occur at depth and that this pattern may be found throughout the global ocean (although it is apparent that more observations are required). The meridional trend in incident solar irradiance provides additional information about controls on the global CDOM distribution. Rates of CDOM photobleaching should decrease toward the poles in proportion to reduced incident light levels (e.g., Kouassi and Zika, 1992). Further, annual mean mixed layer depths are in general deeper toward the poles. The combination of deep mixed layers and reduced light doses suggest that integrated light doses for photobleaching will be much less in the high-latitude oceans compared with the tropics and subtropics. This should result in CDOM concentrations that increase toward the poles. This pattern is clearly observed in the global CDM distribution, where CDM retrievals increase dramatically toward the poles (Fig. 5). This general meridional trend in the global CDM distribution points to photobleaching as the proximate control on near-surface, open ocean CDOM concentrations (Chen and Bada, 1992). Superimposed on the global-scale meridional CDOM increase with latitude, the global CDM distribution shows patterns spatially consistent with the major ocean gyres and boundary currents (Fig. 5). This indicates that vertical transport of the "deep" reservoir of CDOM within these large-scale current regimes should be a significant external net source of "new" CDOM to the surface ocean. Vertical transports can be due to Ekman pumping driving large-scale vertical motions in the major gyres and equatorial zones of the world ocean, vertical advection created by the presence of a coastal boundary (i.e., coastal or shelf break upwelling), as well as convective and small-scale turbulent mixing, creating diapycnal transports. An excellent example of the role of upwelling can be seen in CDM distribution sampled in the equatorial Pacific during the relaxation of the 1998 El Niiio (Figs. 6c and 6d). Passive (convective) export may also be a sink for surface ocean CDOM in temperate and subtropical areas where there is a large seasonal variation in mixed layer depth. Convective export has been shown to be a significant factor in export of DOM from the surface waters of the Sargasso Sea (Carlson et aL, 1994; Hansell and Carlson, 2001), which would logically return some CDOM to deeper waters as well. This is the case observed off Bermuda (Fig. 3) and is likely to be the dominant process at higher latitudes. At present, it is unclear what the partitioning is between
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"Deep" CDOM Figure 7 Hypothesized interactions regulating mixed layer concentrations of CDOM in the open ocean. Possible sources of CDOM production (excretion by organisms, lysis) contribute to either (or both) the deep CDOM reservoir or the mixed-layer CDOM, where the major sink is photobleaching (as controlled by irradiance and mixed layer depth, or MLD). Production and consumption of CDOM by microbes in the mixed layer is indicated by the double-headed arrow. The dashed line connecting "Net CDOM Production" and "Mixed Layer CDOM" indicates that this flux is presumed but not usually observed, as bleaching can occur quickly.
local (i.e., remineralization) vs terrestrial sources for the deep-ocean reservoir of CDOM. A cartoon illustrating the linkage between CDOM production, photobleaching, and vertical transport processes on near-surface abundances of CDOM is shown in Fig. 7. A host of biological processes have been implicated in the production of CDOM. These include phytoplankton release, products of zooplankton grazing, bacterial release, and viral interactions. Production of CDOM is likely to occur throughout the water column; however, the photobleaching of near-surface CDOM makes it difficult to view this production from a time course of CDOM stocks (hence the dashed arrow in Fig. 7). The net transport of "deep" CDOM into surface layers therefore is the important factor in regulating the global CDOM distribution (Fig. 7). This suggests that the use of CDOM in conjunction with its bleaching rate (on the seasonal time scale) may be an effective tracer for evaluating the residence time for surface water masses, which would be useful for evaluating global circulation models of the ocean.
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V. RELATIONSHIP BETWEEN DOM AND CDOM IN THE OPEN OCEAN Because a significant fraction of terrestrial-origin DOM appears to be optically active humic material, instances of correlation between DOC concentration and CDOM light absorption is expected. Estimates of the mass ratio of CDOM carbon to DOC based on these assumptions range from 0.1 to 4% (Shifrin, 1988). At first glance it would also appear that, as there often is in coastal regions (e.g., Vodacek et al, 1995; Ferrari, 2000), there should be a strong relationship between DOC concentration and CDOM absorption coefficient in the open sea. This stems from the supposition that new CDOM production results from either phytoplankton productivity or microbial reprocessing of DOM, which is also a by-product of phytoplankton growth. This presumed correlation turns out not to be present, possibly in part due to the temporal decoupling of the different processes and in part due to the differences in the processes which regulate CDOM and DOM. In the subtropical Sargasso Sea, no correlation exists between DOC and CDOM in the upper water column (Fig. 8; Nelson et al, 1998). This appears to be a result
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DOC (^moir^) Figure 8 Scatter plot comparison of DOC concentration (ixmol L~^) with CDOM absorption [ag(325 nm), m~^] from samples taken on BATS cruises in the Sargasso Sea (e.g., Fig. 3) from spring of 1994 through the end of 2000. DOC and CDOM samples were taken on the same or adjacent days. (*) 0- to 40-m samples, (0) 60- to 120-m samples, (A) 140- to 250-m samples.
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of the summertime bleaching of the surface CDOM (Fig. 2), which does not have a noticeable impact upon the concentration of DOC (Fig. 3). Thus, most openocean surface DOM appears to be colorless and thus not subject to bleaching (e.g., Siegel and Michaels, 1996). Further, microbial activity and convective export is relatively low in the tropics and central gyres; the concentration of DOC increases as one travels away from the source areas (Hansell et ai, 1997). This leads to the curious postulate that CDOM absorption and DOC concentrations in the open sea will vary inversely over large spatial scales. This is in direct conflict with coastal regions where CDOM is removed with distance from the coast, leading to a positive correlation with DOC. This unusual inverse pattern is consistent with the present synthesis of global DOC concentrations as prepared by Hansell and coworkers (Fig. 5C, Hansell et ai, 1997; Hansell, Chapter 15). The global DOC distribution shows neither global-scale meridional patterns nor gyre-scale patterns consistent with the CDM distribution (Fig. 5). This suggests that the basic mechanisms driving the surface DOC distribution are fundamentally different from those driving the CDOM distribution (i.e., the net vertical transport of subsurface CDOM).
VL IMPLICATIONS FOR PHOTOCHEMISTRY AND PHOTOBIOLOGY Many marine processes require CDOM as a reactant or use CDOM as protection from harmful UV radiation. Hence, open-ocean CDOM concentrations have an important role in marine photochemical and photobilogical processes. For example, the photochemical production of dissolved inorganic carbon (DIC) from DOM is thought to occur primarily through the cleaving of organic acids found in CDOM (Miller and Zepp, 1995). Globally integrated DOM to DIC conversion rate estimates are highly uncertain, ranging from 0.1 to 12 Tg C per year (D. Siegel, UCSB, unpublished results; S. Johannesen, Dalhousie University unpubl. data). The upper end of these global rate estimates is many times greater than the global air-sea flux of CO2 and nearly equal to the new production rate (Takahashi et al, 1997; Falkowski et ai, 1998). Similarly, it is important to understand the role of UV radiation on phytoplankton photosynthesis. Hence, it is imperative to improve our ability to estimate photochemical and photobiological rates on a global scale. It is clear from the field and remote sensing evidence presented here that open ocean CDOM distributions vary significantly in both space and time. These factors must be taken into account when estimating the rates of many processes involving the interaction between solar energy and the ocean environment (Mopper and Kieber, Chapter 9).
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A. PHOTOCHEMISTRY AND THE CARBON AND SULFUR CYCLES
Photochemical decomposition of CDOM by sunlight results in the production of various atmospheric trace gases, including carbon dioxide, carbon monoxide, and carbonyl sulfide (e.g., Valentine and Zepp, 1993; Erickson, 1989; Miller and Zepp, 1995). CDOM is also implicated in the cycling of organic sulfur compounds including the photolysis of dimethyl sulfide (Shooter and Brimblecombe, 1989; Kieber etal,\ 996) and the photoproduction of carbonyl sulfide (Doney etal, \995\ Preiswerk and Najjar, 2000). Details of the major photochemical reactions related to CDOM and their biogeochemical implications have been reviewed elsewhere (Blough, 1997; Mopper and Kieber, Chapter 9). We here discuss some aspects of the problem which are specifically related to the properties of CDOM, particularly in the open ocean. Quantum yield spectra for photochemical reactions tend to decline exponentially with wavelength, as do CDOM absorption spectra. Irradiance spectra, conversely, increase dramatically with wavelength in the UV (Kirk, 1994a,b), which typically leads to a peak in the production spectrum in the UV-A (320-400 nm) range. In this waveband CDOM dominates absorption of light in the open sea (Kirk, 1994a,b; Siegel et al, 1995; Nelson et al, 1998; Siegel et al, in preparation. Fig. 5B). Available light in the water column at a temperate or subtropical site varies about 50% over the course of a year (Siegel et al, 1995), tropical sites much less and high-latitude sites much greater (Kirk, 1994a). Temporal variability in CDOM concentration in many open ocean areas around the globe is proportionally similar or greater than that of the light field (Nelson et al, 1998; Fig. 2; Fig. 3). Thus, available light energy for photochemical reactions is a function of astronomical and meteorological factors (e.g., latitude, day length, and clouds) and of the amount of CDOM in the water column (Kirk, 1994a,b) in which light availability and CDOM concentration play approximately an equal part. CDOM has a compound effect on photochemical reaction rates: first by being a reactant or intermediary in the photochemical reaction, and second by being a major light-absorbing component. Increasing the amount of CDOM will not only increase the absorbed quanta (assuming the incident irradiance is similar), but will shift the depth distribution of production closer to the surface. For example, model estimates of CO production rate profiles in the Sargasso Sea have an ^-folding depth of approximately 14 m in the spring, and 25 m in the suromer (N. Nelson, O. Zafiriou, H. Xie, and R. Najjar, unpublished data). This is significant in terms of the overall biogeochemical cycling of species in which air-sea gas exchange plays an important part (e.g., Doney etal, 1995; Preiswerk and Najjar, 2000). The quantum yield itself may be a function of the chemical composition (or "quality") of the CDOM, and may be different for "fresh" or "aged" CDOM, and different still for CDOM of terrestrial origin. For example, there appears to be
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significant differences between CO quantum yields calculated for US estuarine, coastal, and open-ocean sites (Valentine and Zepp 1983,0. Zafiriou and W. Wang, pers. commun. 2000, L. Ziolkowski, pers. commun. 2001). However, for the open ocean, the impact of CDOM quality on photochemical quantum yields may be small. Measurements of spectral quantum yields for CO production made on a long gyre-to-gyre transect across the equatorial Pacific (thereby sampling bleached, "aged" CDOM and freshly upwelled CDOM) suggest that such variability may be small (O. Zafiriou and W. Wang, pers. commun. 2000). Nevertheless, it is clear that the variability of CDOM light absorption over ocean basins and in time is significant in terms of global photochemical reaction rates. B. PHOTOINHIBITION OF PHOTOSYNTHESIS AND MICROBIAL G R O W T H
Light absorption by CDOM is the major factor controlling the penetration of ultraviolet radiation (both UV-A and UV-B) into the open ocean (e.g., Fig. 1). This in turn impHes that CDOM concentration controls the amount of UV-mediated inhibition of biological production and growth. UV radiation is implicated in photoinhibition of photosynthesis (Smith ^r a/., 1980,1992;Cullen^^^/., 1992; Smith and Cullen, 1995) and in inhibition of microbial growth (Hemdl et al, 1993). Like photochemical quantum yield spectra, "biological weighting functions" for photoinhibition and microbial mortality typically decline exponentially with wavelength (Smith and Baker, 1979; Cullen et al, 1992; Boucher and Prezelin, 1996). Unlike photochemical reactions, however, these biological processes are complicated by factors such as dynamic repair of damaged cells (Lesser et al, 1994), turbulent mixing in a steep light gradient, altering exposure (Scully et al, 1998), and relatively long time constants for the onset of photoinhibition (Neale and Richerson, 1987). It is less certain that CDOM concentration will be clearly inversely related to photoinhibition processes. On the other hand, measured photosynthetic rates (Smith et«/., 1980) and microbial cell counts (Carlson and Ducklow, 1996) in stratified (hence bleached) ocean waters do show surface minima, as if photoinhibitory processes are acting on the populations. This pattern is less often observed in mixed (possibly more CDOM-rich) waters (Arrigo and Brown, 1996). Smith and Baker (1979) demonstrated that the vertical attenuation of the DNAdamage dose (convolution of downwelling irradiance with the action spectrum of Setlow (1974)) was approximated by the diffuse attenuation coefficient for irradiance at 305 nm. At this wavelength, light absorption (and therefore the diffuse attenuation coefficient) is dominated by CDOM, therefore a change in CDOM will have a nearly proportional impact upon the biologically effective dose. This may explain the release of UV-A-absorbing compounds by some phytoplankton (Vemet and Whitehead, 1996; Whitehead and Vemet, 2000). Estimates of the
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global distribution of CDOM in this context will add to our understanding of the global impact of UV radiation on primary productivity, microbial populations, and DOM cycling, especially in the context of ozone depletion.
VIL NEEDS FOR FUTURE ADVANCES Many of the problems faced in the study of CDOM in the open ocean are common to the study of the larger DOM pool. Sources, sinks, reactivity, and chemical composition are only starting to become known. An additional complication is that only a small fraction of the total DOM is optically active, and a technique for separating the two has not been developed. Yet CDOM is the largest factor controlling the penetration of UV and (blue) visible light into the water column, and there is compelling evidence that CDOM plays an important role in biogeochemical carbon and sulfur cycles and in microbial ecology. Hence increased understanding of the properties and dynamics of CDOM is in order. Some broad areas of study include: • • • • • • •
origin and chemical composition of CDOM, relationship between biological lability and photolability, rates of formation of CDOM and its global distribution, determination of the lability of CDOM and its relation to DOM lability, impact of bleaching on CDOM labiHty and photochemical reactivity, role of chemical composition of CDOM on photochemical reactions, the ultimate role of CDOM in biogeochemical cycles.
The origin of open-ocean CDOM has not been clarified by recent investigations. It has been clearly demonstrated that local sources and sinks can account for annual fluctuations but the flux terms are not well enough constrained to rule out the possibility that the "background" or deep-ocean CDOM may have a significant terrestrial component. To determine the contribution of terrestrial components to the CDOM pool requires that terrestrial biomarkers be quantified in CDOM separately from the entire DOM pool. As mentioned previously, the chemical makeup of open ocean CDOM is less-well understood than terrestrial CDOM, as are the processes which give rise to it. It may well be that the paradigm for terrestrial humic matter formation (microbial digestion and alteration of biopolymers, followed by biological or abiological condensation reactions) does not apply to marine CDOM. This remains to be explored. Variations in the composition of CDOM can influence its reactivity (both in terms of photochemical and biological lability) and by this its role in biogeochemistry and ecology. But at present no feasible method exists of assessing the CDOM separately from the bulk pool of DOM without making limiting assumptions about the chemical nature of the open-ocean CDOM.
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The process by which "refractory" CDOM accumulates in the deep ocean also may have interesting oceanographic applications. The annual pattern of CDOM distribution in the Sargasso Sea is superimposed upon a background of CDOM "concentration"(as absorption coefficient) which makes up 50-100% of the total (Nelson et al, 1998). In fact this background CDOM appears to have significant changes in concentration in the Sargasso Sea on the multiyear time scale (Nelson unpubl. data) which may suggest that it can be used as a tracer of intermediate water masses outcropping at the surface. This in turn would be useful for assessing the rate of subsurface water mass renewal. It is by no means certain that this "background" CDOM is the same material that is produced and destroyed on an annual basis in the upper water column, as it can be spectroscopically distinct from newly produced CDOM (Nelson and Carlson, unpubl. data). Some of this background material may also be attributable to "residual" terrestrial-origin DOM, as the ratio of land endmember absorption coefficient (e.g., Blough and Del Vecchio, Chapter 10) to openocean "background" end-member absorption coefficient (e.g.. Fig. 2) is similar to the range of estimates for the fractional contribution of terrestrial biomarkers to open-ocean DOM (ca. 5%, Meyers-Schulte and Hedges, 1986; Opsahl and Benner, 1997). On the other hand, clear evidence exists for the production of FDOM as a consequence of microbial remineralization in the thermocline (Chen and Bada, 1992; Hayase and Shinozuka, 1995), which could also account for the deep reservoir of CDOM. Understanding the formation of refractory CDOM and its properties seems to be an important, if far-off, goal. Along those lines, assessing the biological and photochemical properties of different "types" of CDOM is also in order. The A background CDOM found in intermediate or deep water masses may be more or less labile than newly produced CDOM or material that has been bleached in surface waters. The possible difference in lability may have an impact upon the growth of the microbial conmiunity. The photochemical reactivity of the different pools of CDOM may also differ. The issue of "quality" of CDOM remains an open question. The role of CDOM in biogeochemical cycles relevant to the climate is also a relatively untouched field. To date no ecosystem GCM models have incorporated marine-boundary-layer photochemistry, although by some estimates thesefluxesof inorganic carbon and sulfur gases may be climatically significant. This may prove worthy of research as global assessments of photochemical reaction rates become available for incorporation (e.g., Erickson, 1989; Doney et al., 1995; Preiswerk and Najjar, 2000).
ACKNOWLEDGMENTS The authors express our appreciation for the continued support and assistance of the NASA Ocean Biogeochemistry program, the NSF Cheniical Oceanography program, and the research staffs of the Bermuda Bio-Optics Project and the US JGOFS Bermuda Atlantic Time-Series Study.
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Hayase, K., and Shinozuka, N. (1995). Vertical distribution of fluorescent organic matter along with AOU and nutrients in the equatorial Central Pacific. Man Chem. 48, 283-290. Hedges, J. I., Keil, R. G., and Benner, R. (1997). What happens to terrestrial organic matter in the ocean? Organ. Geochem. 27,195-212. Hemdl, G. J., MuUer-Niklas, G., and Frick, J. (1993). Major role of ultraviolet-B in controlling bacterioplankton growth in the surface layer of the ocean. Nature 361, 717-719. Hoge, F. E., and Lyon, R E. (1996). Satellite retrieval of inherent optical properties by Unear matrix inversion of oceanic radiance models—An analysis of model and radiance measurement errors. /. Geophys. Res. 101,16,631-16,648. Hoge, F. E., WiUiams, M. E., Swift, R. N., Yungel, J. K., and Vodacek, A. (1995). Satellite retrieval of the absorption coefficient of chromophoric dissolved organic matter in continental margins. /. Geophys. Res. 102, 24,847-24,854. H0jerslev, N. (1982). Yellow substance in the sea. In "The Role of Solar Ultraviolet Radiation in Marine Ecosystems." (J. Calkins, Ed.), pp. 263-281. Plenum Press, New York. Iturriaga, R., and Siegel, D. A. (1989). Microphotometric characterization of phytoplankton and detrital absorption properties in the Sargasso Sea. Limnol. Oceanogr. 34,1706-1726. Jerlov, N. G. (1953). Influence of suspended and dissolved matter on the transparency of sea water. Tellus 5, 59-65. Jerlov, N. G. (1976), "Marine Optics," 2nd ed. Elsevier, New York. Kalle, K. (1938). Zum problem der meerwasserfarbe. Ann. Hydrol. Mar mitteilungen 66,1-13. Kalle, K. (1966). The problem of the gelbstoff in the sea. Oceanogr Mar Biol. Ann. Rev. 4,91-104. Karabashev, G. S. (1999). On the origin of the subsurface maxima of DOM fluorescence in the active layer of the open ocean. Oceanology 39,155-166. [translated from Russian] Kieber, D. J., Jiao, J. R, Kiene, R. P, and Bates, T. S. (1996). Impact of dimethylsulfide photochemistry on methyl sulfur cycling in the equatorial Pacific Ocean / Geophys. Res. 101, 37153722. Kieber, D. J., McDaniel, J., and Mopper, K. (1989). Photochemical source of biological substrates in sea water—Implications for carbon cycling. Nature 341, 637-639. Kirk, J. T. O. (1994a). "Light and Photosynthesis in Aquatic Ecosystems," 2nd ed. Cambridge University Press, Cambridge. Kirk, J. T. O. (1994b). Optics of UV-B radiation in natural waters. Arch. Hydrobiol. Beih Ergeb. Limnol. 43,1-16. Kouassi, A. M., and Zika, R. G. (1992). Light-induced destruction of the absorbance property of dissolved organic matter in seawater. Toxicol. Environ. Chem. 35,195-211. Lesser, M. P., CuUen, J. J., and Neale, P. J. (1994). Carbon uptake in a marine diatom during acute exposure to ultraviolet-B radiation—Relative importance of damage and repair. /. Phycol. 30, 183-192. Lindell, M. J., Graneli, W., and Tranvik, L. J. (1995). Enhanced bacterial growth in response to photochemical transformation of dissolved organic matter. Limnol. Oceanogr 40, 195-199. Maillard, L. C. (1913). Formation des matieres humiques par action de polypeptides sur les sucres. C. R. Acad. Sci. Paris 156,1159-1160. McCarthy, M., Pratum, T, Hedges, J., and Benner, R. (1997). Chemical composition of dissolved organic nitrogen in the ocean. Nature 390,150-154. Maritorena, S., Siegel, D. A., and Peterson, A. R. Optimization of a semi-analytical ocean color model for global scale applications. Applied Optics, in press. Martinez, J., Smith, D. C , Steward, G. R, and Azam, R (1996). Variability in ectohydrolytic enzyme activities of pelagic marine bacteria and its significance for substrate processing in the sea. Aquat. Microb. Ecol. 10,223-230. Meyers-Schulte, K. J., and Hedges, J. I. (1986). Molecular evidence for a terrestrial component of organic matter dissolved in ocean water. Nature 321, 61-63.
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Miller, W. L., and Zepp, R. G. (1995). Photochemical production of dissolved inorganic carbon from terrestrial organic matter: Significance to the oceanic organic carbon cycle. Geophys. Res. Lett. 22, 417^20. Mitchell, B. G., and others (2000). Determination of spectral absorption coefficients of particles, dissolved material, and phytoplankton for discrete water samples. In "Ocean Optics Protocols for Satellite Ocean Color Sensor Validation" (G. S. Fargion and J. L. Mueller, Eds.), revision 2, NASA TM—2000—209966. Available from SIMBIOS Project, Goddard Space Flight Center, Greenbelt, MD 20771. Mobley, C. D. (1994). "Light and Water: Radiative Transfer in Natural Waters." Academic Press, New York. Mopper, K., Feng, Z. M., Bentjen, S. B., and Chen, R. F. (1996). Effects of cross-flow filtration on the absorption and fluorescence properties of seawater. Mar. Chem. 55,53-74. Mopper, K., and Kieber, D. J. (2001). Photochemistry and Cycling of Carbon, Sulfur, Nitrogen and Phosphorus. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. Hansell and C. A. Carlson, Eds.), pp. 455-507. Academic Press, San Diego. Mopper, K., Zhou, X. L., Kieber, R. J., Kieber, D. J., Sikorski, R. J., and Jones, R. D. (1991). Photochemical degradation of dissolved organic carbon and its impact on the oceanic carbon cycle. Nature 353,60-62. Moran, M. A., and Zepp, R. G. (1997). Role of photoreactions in the formation of biologically labile compounds from dissolved organic matter. Limnol. Oceanogr 42,1307-1316. Morel, A. (1988). Optical modeUng of the upper ocean in relation to its biogenous matter content (case I waters). J. Geophys. Res. 93, 10,749-10,768. Morel, A., and Maritorena, S. (2001). Bio-optical properties of oceanic waters: a reappraisal. / Geophys. /?^5., 106,7163-7180. Neale, P. J., and Richerson, P. J. (1987). Photoinhibition and the diurnal variation of phytoplankton photosynthesis. 1. Development of a photosynthesis-irradiance model from studies of in situ responses. J. Plankton Res. 9, 167-193. Nelson, N. B., Siegel, D. A., and Michaels, A. R (1998). Seasonal dynamics of colored dissolved material in the Sargasso Sea. Deep-Sea Res. 145,931-957. Opsahl, S., and Benner, R. (1997). Distribution and cycling of terrigenous dissolved organic matter in the ocean. Nature 386,480-482. Opsahl, S., and Benner, R. (1998). Photochemical reactivity of dissolved hgnin in river and ocean waters. Limnol. Oceanogr 43, 1297-1304. O'Reilly, J. E., Maritorena, S., Mitchell, B. G., Siegel, D. A., Carder, K. L., Garver, S. A., Kahru, M., and McClain, C. (1998). Ocean color chlorophyll algorithms for SeaWiFS. /. Geophys. Res. 103, 24,937-24,953 Pegau, W S. (1996). Distribution of colored dissolved organic matter (CDOM) in the equatorial Pacific. Ocean Optics XIII, Proc. SPIE 2963, 508-513. Pope, R. M., and Fry, E. S. (1997). Absorption spectrum (380-700 nm) of pure water. 2. Integrating cavity measurements. Appl. Opt. 36, 8710-8723. Preiswerk, D., and Najjar, R. G. (2000). A global, open-ocean model of carbonyl sulfide and its air-sea flux. Global Biogeochem. Cycles 14,585-598. Rashid, M. A. (1985). "Geochemistry of marine humic compounds." Springer-Verlag, New York. Roesler, C. S., and Perry, M. J. (1995). In situ phytoplankton absorption, fluorescence emission, and particulate backscatter spectra determined from reflectance. J. Geophys. Res. 100, 13,27913,294. Roesler, C. S., Perry, M. J., and Carder, K. L. (1989). Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters. Limnol. Oceanogr 34,1510-1523. Scully, N. M., Vincent, W F , Lean, D. R. S., and Maclntyre, S. (1998). Hydrogen peroxide as a natural tracer of mixing in surface layers. Aquat. Sci. 60,169-186.
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Setlow, R. B. (1974). The wavelengths in sunlight effective in producing skin cancer: a theoretical analysis. Proc. Mat. Acad. Set USA 71, 3363-3366. Shifrin, K. S. (1988). "Physical Optics of Ocean Water" (D. Oliver, translator). American Institute of Physics, New York. Shooter, D., and Brimblecombe, P. (1989). Dimethylsulfide oxidation in the ocean. Deep-Sea Res. I 36, 577-585. Siegel, D. A., and Michaels, A. F. (1996). Quantification of non-algal Ught attenuation in the Sargasso Sea: Implications for biogeochemistry and remote sensing. Deep-Sea Res. II 43, 321345. Siegel, D. A., Michaels, A. R, Sorensen, J., O'Brien, M. C , and Hanmier, M. A. (1995). Seasonal variability of light availability and its utilization in the Sargasso Sea. /. Geophys. Res. 100, 86958713. Siegel, D. A., Karl, D. M., and Michaels, A. F. (2001). Interpretations of biogeochemical processes from the US JGOFS Bermuda and Hawaii time-series sites. Deep Sea Res. II48, 14031404. Siegel, D. A., Maritorena, S., Nelson, N. B., Hansell, D. A., and Lorenzi-Kayser, M. Global distribution and dynamics of colored dissolved organic materials. /. Geophys. Res., in press. Smith, R. C. (1982). Assessment of the influence of enhanced UV-B on marine primary productivity. In "The Role of Solar Ultraviolet Radiation in Marine Ecosystems" (J. Calkins, Ed.). Plenum, New York. Smith, R. C , and Baker, K. S. (1978). Optical classification of natural waters. Limnol. Oceanogr. 23, 260-267. Smith, R. C , and Baker, K. S. (1979). Penetration of UV-B and biologically effective dose-rates in natural waters. Photochem. PhotobioL 29,311-323. Smith, R. C , and Baker, K. S. (1981). Optical properties of the clearest natural waters. Appl. Opt. 20, 177-184. Smith R. C , Baker, K. S., Holm-Hansen, O., and Olson, R. (1980). Photoinhibition of photosynthesis in natural waters. Photochem. PhotobioL 31, 585-592. Smith, R. C , and CuUen, J. J. (1995). Effect of UV radiation on phytoplankton. Rev. Geophys. 33, 1211-1223. Smith R. C , Prezelin, B. B., Baker, K. S., Bidigare, R. R., Boucher, N. P., Coley, T., Karentz, D., Macintyre, S., Matlick, H. A., Menzies, D. Ondrusek, M., Wan, Z., and Waters, K. J. (1992). Ozone depletion-ultraviolet radiation and phytoplankton biology in Antarctic waters. Science 255, 952-959. Takahashi, T, Feely, R. A., Weiss, R. R, Wanninkhof, R., Chipman, D. W, Sutheriand, S C , and Takahashi, T. T. (1997). Global air-sea flux of CO2: An estimate based on measurements of air-sea pCOi difference. Proc. Nat. Acad. Sci. USA 94, 8292-8299. Tranvik, L., and Kokalj, S. (1998). Decreased biodegradability of algal DOC due to interactive effects of UV radiation and humic matter. Aquat. Microb. Ecol. 14, 301-307. Twardowski, M. S., Sullivan, J. M., Donaghay, P. L., and Zaneveld, J. R. V. (1999). Microscale quantification of the absorption by dissolved and particulate material in coastal waters with an ac-9. / Atmos. Ocean Tech. 16, 691-707. Valentine, R. L., and Zepp, R. G. (1993). Formation of carbon monoxide from the photodegradation of terrestrial dissolved organic carbon in natural waters. Environ. Sci. Technol. 27, 409412. Vemet, M., and Whitehead, K. (1996). Release of ultraviolet-absorbing compounds by the red-tide dinoflagellate, Lingulodinium polyedra. Mar Biol. Ill, 35-44. Vodacek, A., Blough, N.V., DeGrandpre, M. D., Peltzer, E. T, and Nelson, R. K. (1997). Seasonal variation of CDOM and DOC in the Middle Atlantic Bight: Terrestrial inputs and photooxidation. Limnol. Oceanogr 42, 674-686.
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Vodacek, A., Hoge, R E., Swift, R. N., Yungel, J. K., Peltzer, E. T., and Blough, N. V. (1995). The use of in situ and airborne fluorescence measurements to determine absorption coefficients and DOC concentrations in surface waters. Limnol Oceanogr. 40,411-415. Whitehead, K., and Vemet, M. (2000). Influence of mycosporine-like amino acids (MAAs) on UV absorption by particulate and dissolved organic matter in La JoUa Bay. Limnol. Oceanogr. 45, 1788-1796. Whitehead, R. R, de Mora, S., Demers, S., Gosselin, M., Monfort, R, and Mostajir, B. (2000). Interactions of ultraviolet-B radiation, mixing, and biological activity on photobleaching of natural chromophoric dissolved organic matter: A mesocosm study. Limnol. Oceanogr., 45,278-291. Zaneveld, J. R. V., Kitchen, J. C , Bricaud, A., and Moore, C. (1992). Analysis of in situ spectral absorption meter data. Ocean Opt. XI Proc. SPIE1750,187-200.
Chapter 12
DOM in the Coastal Zone Gustave Cauwet Laboratoire d'Oceanographie Biologique (UMR CNRS 7621), Observatoire Oceanologique, Banyuls sur mer, France
I. Introduction II. River Inputs A. Estimates of River Discharge B. Biodegradability of Riverine DOM III. Estuarine Processes A. Physical Processes B. Degradation of DOM During Estuarine Mixing
IV. Accumulation of DOM in the Coastal Zone and Export Processes A. Mechanism of Accumulation B. Export of DOM from the Coastal Zone V. Conclusions References
I. INTRODUCTION The river inputs to the coastal zone, together with the intense physical and biological activity in coastal waters, make that part of the marine realm one of the most dynamic in terms of dissolved organic matter (DOM). Globally, riverine inputs of DOM represent about 0.25 Gt C per year. Despite its refractory character, recognized by many authors, a relatively large fraction of that DOM is degraded after mixing with seawater, with turnover times ranging from days to years. DOM behavior is also modified by the physical-chemical processes occurring in the mixing zone, particularly flocculation and photooxidation. These processes affect the structure and the biodegradability of organic matter, thereby influencing the fate of DOM in the coastal zone. In addition to riverine inputs, seasonal autochthonous production contributes to a large amount of DOM present in the coastal zone. In this chapter, I review processes occurring in rivers and estuaries that are important Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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to marine DOM. The chapter closes with discussion on the mechanisms of DOM accumulation and export from coastal realms.
11. RIVER INPUTS A. ESTIMATES OF RIVER DISCHARGE World rivers play a major role in the global water cycle and consequently they contribute to enrich the coastal seawater with many dissolved compounds. After the successive symposia on transport of carbon and minerals in major world rivers and the series of volumes issued from these meetings (Degens, 1982; Degens et ah, 1983, 1985, 1987, 1988), the most recent reference that tried to collect all existing data and knowledge about organic matter in rivers was the volume on biogeochemistry of world rivers (Degens etal, 1991a). During the past decade, the effort was largely on the study of processes but several works on a few large rivers produced new data, completing and revising the previously published estimates. The total water discharge to the ocean by major world rivers was estimated to be about35 X lO^km^year"^ (BaumgartnerandReichel, 1975; Degens ^f a/., 1991b). Individual average flows ranged from a few m^ s~^ for small rivers to more than 200,000 m^ s~^ for the Amazon River, by far the most important river (Table I). This estimate does not include Australian rivers and many small rivers, and is probably an underestimate. The underestimate, that could be 20% or more, is also the result of an incomplete assessment of dramatic floods that cannot be precisely estimated. For many rivers it is not realistic to expect a very high frequency of sampling, allowing a precise view of daily water discharge, so good estimations can be obtained only from several-year averages because of a sometimes high interannual variability. River discharge has an influence on the dissolved content, which is quite variable when we compare low and high water periods. The content of dissolved compounds is highly dependent on the type of watershed and the regime of the river (Meybeck, 1988). Hard eruptive rocks are much less eroded than soft soils and the slope of the river course is also an important parameter for erosion. It generally influences directly the contribution to suspended matter and indirectly to the dissolved content. Other important factors include the position of sampling stations, type of sampling devices and depth of sampling. The content in organic matter depends on the nature of soils and the land use in the watershed, resulting in occasional large differences between rivers of different types in different climatic regions. The range and the mean DOC concentration from major morphoclimatic zones have been estimated by Thurman (1985) and Spitzy and Leenheer (1991) in order to calculate the DOC export from zones representing about 37.7% of estimated global discharge (Table II). Some of these estimates should be corrected using more recent data for some rivers. For the
Table I Drainage Area, Total Discharge Volume, and Carbon Fluxes in Major World Rivers River South America Amazon (Obidos) Orinoco Parana Uruguay Magdalena Sao Francisco Estimate of total continental North America Mississippi Columbia St Lawrence Mackenzie Yukon Other US rivers W coast Other US rivers E coast and Gulf of Mexico Estimate of total continental Africa Zaire Niger Senegal Nile (Assiut) Zambezi Orange Estimate of total continental Asia Ob Yenisei Lena Yana Indigirka Huanghe (Yellow River) Changjiang (Yang Tse) Jiulong Zhujiang (Pearl River) Mekong
Area (xlO^km^)
4.69
1.0 2.8 0.24 0.26 0.63
3.22 0.67 1.15 1.81 0.84
DOC (xlO^t/year)
900 150 80 11
19.1^^ 4.5^ 5.9^ 0.5^
2,220
6.0
nd nd
11,039
1,927
44.2
410 182 413 249 210 33
296 14 5.1 nd nd
3.5^ 0.4^ 1.55^ 1.3^ 0.9^^
0.8*^ 0.25^ 0.31*^ 1.8^ 0.3^
0.12/
0.02/
179
nd
0.51/
1.5/
1,831
33.8
14.6
48
10.15^ 0.53^ nd 0.19^ nd 0.03^ 24.7
2.8^ 0.66^ 0.015^ 0.38^ nd 0.01^ 8.3
nd nd 900
2.98^ 3.00^^ 3.6^> nd nd 0.076^"
1.2^ 1.7^ 1.8^> nd nd 4.5^'
486
1.8^'
5.0/
5,780 1,100
470 145 215 120
5,840
3.5 1.2
1,300
1.0
152 10 38 75 11
29.8
3,409
1.9 2.0 20 0.7 211
433 555 505
13.4 14.5 11.7
0.27
3.0 0.54
2.99 2.50 2.44 0.358 0.75
POC (xlO^t/year)
TSS (xlO^t/year)
Volume (km^/year)
27.3 47.5 34.2
25.4
13.0« 2.0^ 1.3^ 0.1^ nd nd 24.1
1.95
925
0.015 0.35
222
nd nd
nd 1.1^
nd nd
0.79
666
nd
nd
nd
14.7
(Continues)
582
Gustave Cauwet Table I (Continued) River
Irrawady Ganges + Brahmaputra Indus Estimate of total continental Europe Wolga Don Dniepr Danube Po Tiber Rhone Loire Seine Garonne Rhine Elbe Vistula Northern Dvina Pechora Estimate of total continental Estimate of total (excl. Australia)
POC (xlO^t/year)
Area (xlO^km^)
Volume (km"^/year)
TSS (xlO^t/year)
DOC (xlO^t/year)
0.43 1.48
428 971
265 1,670
nd 3.6'
nd 32'
1.17 44.1
238 12,205
100 11,172
0.75' 94
nd 128
1.46 0.43 0.53 0.82 0.067 0.017 0.099 0.121 0.079 0.085 0.224 0.146 0.199 0.365 0.330 10
243 29.3 52.3 198 46.4 7.2 59.9 27.0 15.8 21.4 69.4 23.7 34.7 112 128 2,826
27.4 6.4 2.12 83 9.0 nd 11 7.8 3.54 1.3 3.4 0.84 nd 1.54 1.44 158
nd nd nd 0.59^" 0.12" nd 0.18^ O.llP nd 0.075P nd nd nd nd
nd nd nd 0.356'" 0.14" nd 0.09^ 0.04P nd 0.035P 0.37^? nd nd nd nd
126
35,300
4,625
250
176
Note. Modified with permission from Degens et al, 1991. ^Richey(1991). ^Depetris and Paolini (1991). ^Telangera/. (1991). ^Prahl and Coble (1994). ^Hopkinson^ra/. (1998). /Leenheer (1982). ^Martins and Probst (1991). ^Olsson and Anderson (1997). ^Cauwet and Sidorov (1996). ^Cauwet and Mackenzie (1993). ^Cauwet, impubUshed data. 'Spitzy and Leenheer (1991). ^Cauwet et al. (in press). "PettineeM/. (1998). ^Cauwet ^r a/. (1990). ^'Kempeera/. (1991). '^Eismaera/. (1982). ^Laraera/. (1998).
583
DOM in the Coastal Zone
Table II DOC and Water Export from Major Morphoclimatic Zones Based on Discharge and Typical DOC Concentration Data After Meybeck (1988) and Spitzy and Leenheer (1991). Water discharge
DOC export
Morphoclimatic zone
Typical DOC concentration (mg/L)
km^/year
% of total
Tundra Taiga Temperate Wet tropic Dry tropic Semiarid
2 7 4 8 3 1
1,122 4,376 10,285 19,186 2,169 262
3 11.7 27.5 51.3 5.8 0.7
2.2 30.6 41.1 153.5 6.5 0.3
1 13 17.6 65.6 2.8 0.1
37,400
100
243.2
100
Total
10^ t/year
% of total
Amazon River, the most recent data (Hedges et al, 1994) shows 300-400 /xM DOC in the lower main stem of the river, with high values in some black water tributaries (Rio Negro, 800 JJM). For Arctic Siberian rivers, we now have reliable DOC measurements (Cauwet and Sidorov, 1996; Lara et aL, 1998) that can replace the old TOC data used in the Spitzy and Leenheer budget. The mean DOC concentration in the lower Lena River is probably close to 600 /JM from June to September, a period that represents about 85% of the total annual discharge. The resulting annual DOC flux is about 3.6 x 10^ t C. For a more detailed study of carbon inputs to the Arctic Ocean, see Olsson (Olsson and Anderson, 1997; Anderson, Chapter 14). For the main Chinese rivers (Yangtze, Huanghe, and Pearl Rivers) more data have been recently collected, and a large correction to estimated fluxes has to be done. The mean DOC concentration for the Huanghe River (Yellow River) was greatly overestimated at 1000 /xM and is probably closer to 250 /xM (Zhang et aL, 1992; Cauwet and Mackenzie, 1993). In addition, the discharge of the Yellow River has decreased over the past 20 years due to damming and irrigation. Flow is now probably less than 600 m^ s~^ while it was estimated around 1300 m^ s~^ in previous studies. Consequently, the annual DOC flux of the Huanghe River previously proposed (0.54 x 10^ t year"^) has to be divided by almost 8 (0.076 x 10^ t year~^). DOC concentrations were also overestimated for the Yangtze River. It was recently estimated in the range 250-400 /xM (Cai et aL, 1992; Cauwet and Mackenzie, 1993), much less than the 1100 /xM (13.4 mg C L~^) cited by Spitzy and Leenheer (1991). For the Pearl River there are only infrequent and recent DOC data (Cauwet, unpublished). The estimated DOC concentration is around 600-800 /xM C. These values were measured on only a few samples collected in an estuarine environment and could be influenced by human activity, leading to an overestimation of the natural concentration in
584
Gustave Cauwet
the river, but contributing partly to the total input to the coastal sea. Some recent studies on the Mississippi River (Gardner et al, 1996; Kelley et al, 1998) also give estimates of DOC concentration but the new data do not change significantly the earlier carbon budget. If we reassess the global DOC input from rivers to oceans, we need to modify the amount (0.11-0.25 10^ t year"^) estimated by Degens and Ittekkot (1985). An estimate made by Degens et al. (1991b) and reproduced by Meybeck (1993) proposed a total DOC input of 0.2 x 10^ t C year~^ but without European rivers and without any data on the Ganges, Brahmaputra, Irrawady (no data exist for that large river), Mekong, Lena, Ob, and lenissei in Asia, Zambezi and Senegal, in Africa, or Rio Magdalena in South America. If one considers that these rivers contribute about 14% of total freshwater discharge to the global ocean and include some of the large rivers having the highest DOC concentrations (the Siberian rivers), we can reasonably estimate that the total DOC input to the global ocean is about 0.25 x 10^ t year"^ or 0.25 x lO^^g C year"^ (0.25 Gt C year"^). This estimation is comparable to that made recently by Hedges et al. (1997). This annual input represents only about 0.0004 times the DOC content of the ocean (estimated at 685 Gt C; Hansell and Carlson, 1998a), but sufficient alone to sustain the 6000-year estimated turnover of DOC of the ocean (WiUiams and Druffel, 1987). This riverine input remains low compared to the annual production of the whole ocean (about 50 Gt C year~^).
B . BlODEGRADABILITY OF RiVERINE D O M Though the yearly DOC discharged by rivers represent only 0.03% of total marine DOC pool, the impact of DOC inputs on the coastal zone is far from negligible. Furthermore, it is unknown how much is rapidly degraded or persists in the marine environment. Hedges et al. (1997) have documented the recent studies on the topic and discussed the fate of terrestrial organic matter in the ocean. They compiled all data (bulk composition, isotopic characteristics, molecular tracers approach) that were used to differentiate terrestrial from marine organic matter, mostly on particulate matter and coastal sediments but sometimes on the dissolved fraction. They concluded that either our global budgets and distribution estimates are greatly in error, or both dissolved and particulate organic matter of terrestrial origin suffer rapid and remarkably extensive remineralization at sea. The first approach utilized to evaluate the possible biodegradability of dissolved or particulate organic matter was the analysis of the probable most degradable fractions: proteins and carbohydrates. In an early work, Ittekkot and coworkers collected all data on carbohydrates and amino acids in the world's rivers (Ittekkot et al., 1982). These authors estimated that carbohydrates and amino acids mainly represent the aquatic life and present a high degradable character, in contrast to
585
DOM in the Coastal Zone
4
3] (0
2
O
1 3
4
5
9
6
10
11
Months
1200
900 800 700 S 3 O Q
1000 800
600 500 400 300 200
5" - =^
<0 (/)
600 400 200
100 0
E
<
0 5
6 Months
7
10
11
-DOC -Aminoacid -sugars
Figure 1 Yearly variability of water discharge (a) and DOC (^tM), amino acid (/xg L ^), and carbohydrate (/xg L~^) concentrations (b) in the River Ganges (after SafiuUah et al, 1987).
organic matter from soils or terrestrial plant litter, usually considered to be more refractory to further degradation. There has been no recent review paper but several works were published dealing with biodegradability or biodegradation processes in several estuaries of the world. A good example of the variability of concentration of labile compounds can be seen in a survey of the Ganges River in 1984 (Safiullah et ah, 1987). The water discharge started to increase in May, reaching a maximum value in July and August and decreased afterward to reach again a minimum value in November (Fig. la). DOC concentration, slightly increasing from January (267 /xM) to April (317 /xM), decreased in May-June, only to increase sharply in July (reaching 783 /xM) before decreasing rapidly later (Fig. lb). When the water flow increases, it provokes the soil leaching and the solubilization of organic matter, increasing the DOC content. One can expect that the DOC concentration increases linearly with the water flow but too many different situations were observed to be able to propose a common rule for all situations in all rivers. In a recent publication (Sempere et al, 2000) it is clearly shown that the good Hnear relationship obtained {R^ = 0.70 and 0.90, respectively) when plotting log TSM (total suspended matter) or log POC (particulate organic carbon) versus
586
Gustave Cauwet
log Q (water discharge; m^ s~^) is less clear when plotting log DOC versus log Q(R^ = 0.53). It seems that DOC is highly variable, perhaps reflecting the sum of several sources. It was several times observed that DOC increased rapidly at the beginning of a flood to stabilize after, as if the first leaching solubilized the DOM that had accumulated in soils, everything being then diluted by the increasing water discharge. This scenario is not what was observed in the Ganges River, exhibiting a slight DOC decrease before the maximum concentration, coinciding with the maximum flow. Plotting DOC, amino acid, and carbohydrate concentrations versus Q produces different correlations, but never clearly linear (Fig. 2). DOC (Fig. 2a) is distributed like on a partial hysteresis loop while amino acid concentration is almost linear (Fig. 2b) and carbohydrate concentration randomly distributed (Fig. 2c). These differences correspond to the discrepancy existing between DOC and biomolecule concentrations rising, suggesting multiple sources for DOM. A more recent and complete study of organic matter composition in coarse particles, fine particles and ultrafiltered (dissolved) fraction in the Amazon basin (Hedges et al, 1994) has shown that only the fine particulate fraction is rich in nitrogen (C:N = 9), while the dissolved one is of an acidic character, very poor in amino acids, and has a high C:N ratio (27-52). On such a basis we can hardly consider riverine DOC as an easily degradable fraction that could contribute to biological processes in the coastal zone. However, we must consider that that study dealt with ultrafiltered DOC, excluding the colloidal fraction that could be more degradable. It must be noticed also that 70% of riverine DOM is HMW (>1000 Da) while this HMW portion is only 30% in surface ocean and 22% in deep ocean (Hedges et al, 1994). Ogawa (1999) also mentioned that the structure of HMW DOM is similar to biomolecules while the LMW fraction seems more complex in terms of structure and poorly determined. Looking at the literature, it is rather difficult to have a precise idea of the nature of dissolved organic matter discharged by rivers. There are several reasons for that, the main one being that information is sometimes for dissolved, sometimes for particulate fractions, and sometimes for the total organic matter. For instance, cellulose (and relative structures) and lignin are major constituents of terrestrial plants, but these compounds are not known to be very soluble and they are mostly transported as detritus. To get soluble fractions there must be degradation by microorganisms in the soils or in the water. Consequently, the DOM from soils is discharged when soil leaching occurs, generally during rainy seasons and high discharge periods. This is what occurs with the increase in DOC concentration during floods in many rivers. However, it is not that simple; heavy rains bringing large quantities of water that dilute the leachate, and what is often observed is an increase in DOC at the beginning of the flood and a decrease, due to dilution, in the second part of the flood (see Fig. 1). In fact, the DOM in rivers is mainly composed of humic matter, bringing with it the degraded characteristics of lignin
587
DOM in the Coastal Zone 1000 g* 800 3 600
g
Q
400 ]
200 -{ 0 1
2
3
Q(10^xmV) ^^ 700 O) 600 3 500 ^ 400 ] o 300 -]
2 200
c 100 E 0 < 0 Q{10^xmV')
3
(0
1200 n 1000 800 -
&
600 -
o
400 -
•o
•s (0 O
200 n U i
0
•
t 1
2
3
4
Q(10^xmV) Figure 2 Relationship between water discharge (Q) and DOC (a), amino acid (b), and carbohydrate (c) concentrations in the River Ganges.
and cellulose, but also a minor fraction originating in the riverine production. This does not exclude direct human influence, particularly in estuaries surrounded by regions of dense population, where organic matter issued from pollution can be an important and rapidly mobilizable fraction. Nevertheless, most authors point out the difficulty in giving a precise estimation of the real flux of DOM issued from
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Gustave Cauwet
rivers, even with high frequency sampHng. A perfectly representative sampling of flood events is almost impossible in terms of the relationship between discharge and concentration. This is essentially due to the high variability observed in the river water at a space scale (the sampling strategy can be improved for large rivers) and at different time scales (daily, annual, and interannual). A good example can be cited with a 2-year (13 cruises) survey of the Chesapeake Bay (Fisher et al, 1998), where DOC concentration varied in the river from 129 to 316 /xM (mean value 232) and was measured in the estuarine zone from 144 to 374 jiM. No clear relation can be shown between DOC concentrations in the river or the estuary with the Susquehanna River discharge; there is little seasonal variation. Such a detailed survey aptly describes the processes occurring in the mixing zone, especially identifying the internal sources. Nevertheless, the authors point out that the interpretation of mixing diagrams must be done with caution, due to the variability of the end-members that can create a nonlinear behavior under conservative mixing. This was already mentioned by other authors (Loder and Reichart, 1981; Cifuentes et al, 1990) in the past and recently. In conclusion, most of the recently published works in estuaries and the coastal zone show that the most important source of dynamics for carbon is probably linked to the equilibrium (or disequilibrium) existing between production and consumption of organic matter in the mixing zone. Now that we are more in confidence with most analytical data, the challenge is to identify the mechanisms transforming or oxidizing the allochthonous riverine DOM to explain the general observation that terrestrial organic matter is in low concentration in seawater and marine sediments (Hedges et al, 1997). The study of estuarine processes can certainly help to find the pathways of DOM from rivers to the sea, including the identification of internal sources and consumption mechanisms.
III. ESTUARINE PROCESSES A. PHYSICAL PROCESSES Due to high concentrations of DOM and particles and to the rapid change in salinity occurring in estuaries, a strong influence is expected of chemical-physical processes like adsorption, desorption, aggregation, flocculation, and deflocculation on the behavior of DOM. The earliest work describing flocculation processes in estuaries is probably that of Sholkovitz and coworkers (Sholkovitz, 1976; Sholkovitz et al, 1978). In these works, the authors described an important flocculation of dissolved humic substances (60-80% of the humic material was removed along the salinity gradient) and suggested that this humic fraction represented only 3-6% of riverine DOM. Nourredin and Courtot (1989) estimated that humic matter represents up to 60% of DOM and behave conservatively. In the estuarine flocculation
DOM in the Coastal Zone
589
literature it appears that each author has seen what he expected, relative to his own field. Specialists in clay focused on the particle size and the clay composition to explain fast deposition of sediment in estuarine environments (ICranck, 1981). Others pointed out that iron also participates in the flocculation and probably is the initiator of the mechanism (Sholkovitz et al, 1978; Fox, 1983, 1984). Others suggested that temperature is possibly an important factor (Droppo et al, 1998). Most of the time, especially when the results came from laboratory experiments, the authors did not take into account the water dynamics and the probable role it played. In fact, it seems that flocculation and deflocculation can occur at different stages of the estuarine mixing, in relation to mixing process (mixed or stratified estuaries) and the level of energy of turbulence (Eisma, 1986). It was sometimes shown that besides the turbidity maximum due to resuspension another turbidity peak could be attributed to a flocculation mechanism (Biggs et al, 1983). In well-mixed estuaries, it is difficult to differentiate these mechanisms; the rapid mixing and the presence of a turbidity maximum due to sediment resuspension completely mask the minor processes. In partly mixed estuaries, it is sometimes possible to observe this coupled mechanism showing exchanges between particulate and dissolved organic matter (Cauwet, 1985; Cauwet and Meybeck, 1987); but this occurs mostly in the freshwater portion of the estuary under tidal influence, as a consequence of variation in turbulence, not because of salinity increase. In well stratified estuaries (generally microtidal estuaries) it is easier to observe some flocculation processes occurring at the surface of the salt wedge (Cauwet, 1991; Lipiatou et al, 1991; Lipiatou and Saliot, 1992). The main reason is more probably the increase of the residence time of riverine colloids with low turbulence at the interface, rather than a drastic change in environmental conditions. It was observed that some molecular characteristics of riverine dissolved organic matter that are absent in particles brought by the river and in the river plume are again observed in particles found in the bottom nepheloid layer below the plume (Lipiatou et al, 1991). This finding suggests that some flocculation mechanism, involving dissolved or colloidal organic matter, occurs at the freshwater-saltwater interface and the newly formed floes are transported along the salt wedge toward bottom water in the estuary. One prominent character of riverine DOM that can influence the flocculation is the high concentration of colloids (Whitehouse et al, 1989; Filella and Buffle, 1993; Filella et al, 1993; Dai et al, 1995; Kim et al, 1995; Sempere and Cauwet, 1995; Gustafsson and Gschwend, 1997). Up to 50% of "dissolved" organic carbon (passing through GF/F glass fiber filters) is in the form of colloids and does not pass through 10-kDa membranes (Newman et al, 1994; Dai et al, 1995; Cauwet and Sidorov, 1996; Patel et al, 1999; Wells, Chapter 7). In many cases, the colloid concentration decreases rapidly with increasing salinity (Fig. 3). However, it has not been possible to demonstrate that a decrease in colloidal carbon corresponds quantitatively with a decrease in DOC or an increase in POC. Obviously, the exchange processes between the three fractions (true
590
Gustave Cauwet r-
80
7 5 Q 40 .•2^5
i
5^20 o
O
n 2 Salinity
Figure 3 Concentration of organic colloids along the salinity gradient at low salinity in the Lena River mixing zone.
dissolved, colloidal, and particulate) are more complex than sometimes supposed and the disappearance of colloids can enrich particulate matter or return back to dissolved phase. Fragile particulate flocculants can turn to colloidal or dissolved organic matter. These colloids, while accumulating at the freshwater-saltwater interface, have more time to coagulate and form aggregates. Several observations in estuarine environments have demonstrated that large flocculants (3-4 mm) are easily destroyed by turbulence while small flocculants (<125 /xm) are more stable and can survive for a longer time and be transported offshore, where they are decomposed by bacteria (Eisma, 1986; Eisma et ai, 1991; Eisma and Li, 1993). The difference between small and large flocculants is not in the quantity of solid material, but more in the density of the flocculants, as regulated by the water content. In fact, small flocculants are more condensed, which explains their stability connected with more cohesion. The possible flocculation of organic matter at the continent-ocean interface and the stabilization of flocculants of a certain size can be a significant form of transport for river DOM, to the open sea and to sediment. The existence of a bottom nepheloid layer widely distributed over continental shelves (Naudin and Cauwet, 1997) can be an important way of transfering from coast to shelf and from shelf to slope. The relative importance of this phenomenon as an export mechanism to the open sea is not known.
B. DEGRADATION OF D O M
DURING ESTUARINE MIXING
One of the questions challenging scientists concerning riverine organic matter is the extent that it is degraded or it accumulates in the marine environment and the most important processes in the degradation. We have seen above that the nature of riverine dissolved organic matter is complex, with a major fraction comprising lignin or cellulose polymers. Several authors (Mantoura and Woodward, 1983; Prahl and Coble, 1994; Alvarez-Salgado and Miller, 1998) have observed a
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DOM in the Coastal Zone
conservative mixing behavior of DOC concentration with saUnity, and considered that it is a general trend in all estuaries. Comparing the DOC distribution in several very different estuaries, different behavior can be observed, from conservative behavior to a deficit or excess in DOC. Even an apparent conservative behavior of total DOC can mask an internal variabihty. Sharp et al (1984) have shown that the apparent general conservative picture of DOC is sometimes contrasted by strikingly nonconservative natures of two of its components. It can be variable in the same estuary according to seasons and the intensity of biological processes. A good example of conservative behavior is described for the Ouse-Humber estuary (Alvarez-Salgado and Miller, 1998) at different seasons. In this example, more than 96% of the variability in the DOC profiles are simply explained by conservative mixing of the two end members. It is observed that there is a higher variability of DOC concentration at very low salinity. The authors consider that this is due to a difference between the most landward station in River Ouse and the zero salinity station in the Humber estuary where there is a turbidity maximum. This explanation is realistic if remobilization of DOC from suspended sediment is considered, but the variability of the riverine end members that can cause interesting deviations in any apparent conservative picture must be also mentioned (Sharp et al, 1986; Cifuentes ^? a/., 1990). The conservative nature of DOC is often based on only one or few samples in freshwater or at low salinity (Fig. 4), while the DOC concentration in the freshwater body or at very low (<5) salinity can have great variability. The results observed for colloids in the Lena delta (Fig. 3) demonstrate that some important mechanisms can occur at salinity below 5, but biological processes are generally not the cause. This finding also demonstrates that at salinity over 5 mixing dominates, as long as sampling is in the plume of the river and not during a high biological activity period. Cauwet and Mackenzie (1993) found that DOC is generally conservative in winter but not in spring or summer when estuarine biological processes are intense. Recently, Cifuentes and Eldridge (1998) tried to model DOC behavior during estuarine mixing. They computed that conservative profiles were 190 170 i • g- 150 3 130 O110Q 90 70 c^n -
0
..,• y = -2.0884x +159.95 R' = 0.9285
10
20
30
40
Salinity igure 4 Conservative behavior of DOC in the Rhone estuary in November 1994
592
Gustave Cauwet y = -0.1595x +7.2182 R' = 0.9411
20 Salinity Figure 5 DOC concentrations vs salinity in the Lena River mixing zone.
obtained when time scales (half life, turnover time) associated with sources and sinks were significantly greater than estuarine mixing times, but that DOC was not conservative when more than 10% of riverine DOC was labile. This last result is in agreement with most of the data published for estuaries; DOC generally exhibits a nonconservative behavior in stratified estuaries where the mixing time is longer than in well-mixed estuaries and also when there is an extra source of DOC or a high flux of labile DOC due to a high aquatic production. Their results also fit well with the conservative character observed in winter (when there is a very low content of labile organic matter) and the more complex situation observed during warmer periods. They showed that in a well-mixed estuary, even with Unear DOC profiles, most of the DOC was from autochthonous primary production. Another example of misleading conservative mixing interpretation can be given with a carbon-rich, colloids-rich river, the Lena,flowingfrom Siberia to the Laptev Sea and the Arctic Ocean (Fig. 5). The good correlation coefficient (R^ = 0.94, n = 32) does not mask the fact that the conservative mixing is effective only from salinity 2-3 upward, not at very low salinity. As was shown above (Fig. 3), between salinity zero and two there is a disappearance (flocculation?) of colloidal organic carbon but the high variability of the freshwater end member frequently hampers any quantitative evaluation. A third example of DOC behavior in estuarine mixing is represented by what can be observed in the mixing zone of the Danube River in NW Black Sea. At any season (winter, spring, summer), the DOC concentration is relatively constant along the salinity gradient, while the "marine" values, encountered in nonsurface offshore waters, are lower (Fig. 6). This distribution is the most surprising one because we could expect a conservative mixing or the evidence of a consumption mechanism (DOC curve below the theoretical mixing line) or a production process (DOC curve above the theoretical mixing line). A similar DOC distribution was observed in turbid Chinese estuaries (Cauwet and Mackenzie, 1993) in summer and is not something exceptional but previously, there was no precise and simple explanation for this observation. It seems to be the consequence of the superposition
593
DOM in the Coastal Zone 350 a 250 250 0 q
,°°n5 ^o ••
4D4^1
O 200 Q 150 100 10
15
Salinity
20
25
• late winter JDsummer o early spring
Figure 6 DOC concentration in coastal and open seawater of the Black Sea in July 1995, April 1997, and May 1995.
of several mechanisms balancing the DOC concentration. In the case of the Danube mixing zone, it was observed that DOC concentrations were constant during winter, around 200 /xM in all the Black Sea, but increased gradually from spring to summer (up to 300 /iM) in the mixing zone, while remaining at 200 /xM in deep offshore waters (Fig. 6). The changes in river inputs alone cannot explain this increase along the saHnity gradient; estuarine processes also influence the concentration in DOC. In this case, there are several mechanisms that overlap each other to explain such a distribution. In spring and summer, there is a high production in the river, bringing freshwater diatoms to the sea. The freshwater cells die and are lysed when reaching a salinity of 3-4, producing a flux of very labile organic matter (Ragueneau et al, 2002). The microbial loop is active in this area, regenerating nitrogen as NO3 but utilizing a proportion of the phosphorus brought by the river (Becquevort et al, 2002). The phosphorus depletion observed at higher salinity provokes a stress for phytoplankton cells that start to produce carbohydrates. The lack of phosphorus (and somewhat later of nitrogen) explains DOC preservation, bacteria being unable to use it in such a situation. This mechanism is a general one we will describe later. The apparent different DOC behaviors in various estuaries do not indicate a high utilization of riverine DOM during mixing, and cannot explain why the terrestrial organic matter disappears rapidly when passing from coastal to open sea. Amon and Benner (1996) in an experiment with Amazon waters (black and white waters) have measured low bacterial activity in terms of DOC and oxygen consumption, especially in Rio Negro black waters. More interesting, they described a high photoinduced oxidation of DOC (4 /xM C h~^). They estimated that up to 20% of the riverine DOM could be oxidized in about 7 days when the river plume extended along the shelf. It is also important to remember that the surface microlayer of the sea is enriched in DOM, up to 1000-fold (Liu and Dickhut, 1998), and this organic matter is exposed to sunlight. Several other works also pointed out the
594
Gustave Cauwet
relatively high photoreactivity of riverine DOM (Miller and Zepp, 1995). Most interesting are studies on the relationship between photochemical and bacterial processes (Lindell et al, 1995; Bushaw et ai, 1996; Miller and Moran, 1997; Moran and Zepp, 1997; Bushaw-Newton and Moran, 1999), even if some works on seawater DOM give questionable results (Benner and Biddanda, 1998). According to Moran and Zepp (1997), photodegradation of DOM stimulates the growth and activity of microorganisms by 1.6- to 6-fold. In the coastal zone, they estimated that degradation products during one summer day can satisfy more than 20% of the bacterial carbon demand and 30% of the nitrogen demand. This fraction of DOM being more easily metabolized increases the potential bioavailabihty of riverine or marine DOM. Again, the difference between well-mixed and stratified estuaries is important. In the second type, river water remains at the surface longer while losing most of the suspended sediment and becomes more subject to sunlight. In a recent paper, Opsahl and Benner (1998) demonstrated that lignin derivatives were destroyed by light in a short time. This was confirmed in the Mississippi plume by the same authors (Benner and Opsahl, submitted for pubUcation) who found a rapid decrease in lignin phenols along the salinity gradient. There are many recent studies (Chin Leo and Benner, 1992; Findlay et al, 1992; Boyd and Carlucci, 1993; Koepfler et al, 1993; Baross et al, 1994; Feliatra and Bianchi, 1994; Benner et al, 1995; Pakulski et al, 1995; Carlson and Ducklow, 1996; Carlson et al, 1996; Gardner et al, 1996; Saliot et al, 1996; Creach et al, 1997; Seitzinger and Sanders, 1997; Moran ^M/., 1999;Stepanauskas^ra/., 1999; Pakulski ^f a/., 2000) dealing with bacterial activity in estuaries and the coastal zone, and its relation to riverine or marine DOM consumption. It is difficult to sunmiarize this abundant literature (though see Carlson, Chapter 4) since the parameters studied, the field or experimental conditions, and the focus of the authors varied. Also, it is difficult to reconcile the seemingly contradictory results of different reports. For example, it has been shown that bacteria can be carbon-limited in oligotrophic environments and rapidly metabolize glucose added to the water (Carlson and Ducklow, 1996). In contrast, it has been shown that phosphorus-limited bacteria let polysaccharides or even glucose accumulate in artificial blooms produced in mesocosms (Fajon et al, 1999; S0ndergaard et al, 2000). Some studies focus on DOC availabihty or lability to explain the utilization of DOM in aquatic environments without taking into account the complex relationship existing between DOC, nutrients, planktonic (phyto- and bacterio-) population, and water dynamics. It is difficult to demonstrate carbon, phosphorus, or nitrogen limitation to explain bacterial activity. In conclusion, we must consider that only a small fraction of riverine DOC is labile enough to be degraded during the estuarine mixing. However, this is not the case if the residence time is increasing, for instance if coastal dynamics is trapping fresh-brackish water at the coast for some time. It is also incorrect to
DOM in the Coastal Zone
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conclude that nitrogen and phosphorus cannot be limiting in mixing zones due to the proximity of the river mouth and the richness of the water. Focusing on estuaries and river plumes to evaluate the degradability of terrestrial organic matter is too limiting for understanding and explaining the low terrestrial budget in the sea. For such a purpose we must include the whole coastal zone and study all processes influencing the carbon cycle, as well as of other bioelements like nitrogen and phosphorus.
IV. ACCUMULATION OF DOM IN THE COASTAL ZONE AND EXPORT PROCESSES A. MECHANISM OF ACCUMULATION The study of pelagic production of DOM and the evaluation of various sources (remobilization from sediment) in the coastal zone are considered in other chapters of this volume and will not be developed in detail here (see Chapters 3,4, 5,6, 8, 13, and 15). The coastal zone is one of the most productive areas in the world ocean and its contribution to the release of DOM should be also significant in the global budget. The main pathways for DOM to be released can be natural excretion from living cells, death and lysis of planktonic cells under grazing pressure or salinity stress, and rapid release of accumulated substances (reserve substances?) from generally senescent cells under nutrient depletion stress. Considering the different conditions under which DOM can be released, one can imagine that the nature and the fate of this DOM can also be different. It can be continuously recycled at low rate while being produced but in special circumstances it accumulates for weeks or months. This seasonal accumulation was pointed out by Williams (1995), revisiting previously published data on DOC and DON. In that publication, the author explained the accumulation by an increase in DOM release from spring to summer, correlative to a low bacterial uptake during the same period. He also mentioned that this is mainly true for DOC, not DON, which implies that the accumulated organic matter is carbon-rich and that it provokes a decoupling of the C and N cycles. This seasonal accumulation of DOM in marine waters was also shown more recently (Zweifel et al, 1995; Borsheim and Myklestad, 1997; Borsheim et al, 1999; Zweifel, 1999), with emphasis on the richness in polysaccharides (Gomez-Moreno ^?fl/., 1997; Biersmith and Benner, 1998, Borsheim ^r a/., 1999; FsLJon etal., 1999). The net annual accumulation of DOC in the euphotic zone has been calculated by several authors for different marine areas (see Hansell, Chapter 15). In the Sargasso Sea, it was estimated at 0.7-1.4 mol C m~^ (Carlson etai, 1994; Hansell and Carlson, 2001), in the western Mediterranean Sea it was 1.23 mol C m~^
596
Gustave Cauzvet
(Copin-Montegut and Avril, 1993), and in North Atlantic waters up to 1.654.18 mol C m-2 (Borsheim and Myklestad, 1997). The discovery that DOC accumulates during summer and that it is mainly made of carbohydrates is relatively recent and the explanations proposed by different authors depend on their own research field and sensitivity. In the case of mucilage that accumulates dramatically in the northern Adriatic Sea, the explanation proposed for this high organic matter production and accumulation was successively the role of benthic diatoms (Welker and Nichetto, 1996), the role of bacteria releasing mucus (Serratore et ai, 1995), the role of phytoplankton cells destroyed by viral lysis (Baldi et al, 1997), the lack of grazing (Malej and Harris, 1993), the role of pollutants discharged by rivers (Monti et al, 1996), the role of nutrient limitation (Degobbis et al, 1995; Obemosterer and Hemdl, 1995), etc. One of the ways to understand the seasonal accumulation of DOC is to design laboratory (or mesocosms) experiments in which several key parameters are controlled and their influence on DOC release and accumulation measured. During the past few years, several of these experiments were conducted. Though they differed by several points, they all exhibited a high production and the accumulation of DOC. Introducing a rich nutrient mixture to a seawater sample produces a strong bloom, generally favoring large cells like diatoms (Norrman et a/., 1995). During a series of experiments which were conducted with Adriatic Sea water, the same result was observed—a strong bloom more favorable to diatoms—^but different results in terms of DOC production when conducting the experiments at different periods of the year with different initial conditions in terms of plankton population and nutrient concentration (Mozetic et al., 1997, 1998; Cauwet et al., 1999; Fajon et al, 1999; Malej et al, 1999). Samples taken in June, depleted in nutrients (phosphorus as well as nitrogen) and rich in flagellates, gave a bloom in answer to the enrichment in nutrients, with some limited increase of the diatom population but no visible accumulation of DOC. On the contrary, populations in samples collected in April, already dominated by diatoms, and limited in both phosphorus and nitrogen or in phosphorus alone, gave a high production of DOC (mainly carbohydrates) as soon as nutrients were again limited (Fig. 7) or were accumulating particulate polysaccharides during several days before releasing them in the dissolved form (Fig. 8). In both cases it is obvious that after the exponential growth phase, as soon as nutrients were limited, diatoms cells were fixing CO2 but could produce only polysaccharides (organic molecules without nitrogen or phosphorus). It is difficult to explain why in one case polysaccharides are first accumulated in cells before being released 2-3 days later, while they are released immediately when synthesized in the other case. The only difference between the two experiments was in the initial sample, richer in diatoms and depleted in both nutrients when DOC was immediately released. The recent nutritive history of phytoplankton (if the population was already under nutrient stress or not, for instance) can influence the reaction of cells and the result of the experiment. In
597
DOM in the Coastal Zone — • - DCHO - • - P04 - A - N03
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Figure 7 Release of dissolved polysaccharides correlated with nitrogen and phosphorus depletion during a mesocosm experiment in the Adriatic Sea.
these examples, the methodology was to increase suddenly the concentration in nutrients in previously depleted samples, trying to reproduce what happens in the coastal zone when rivers are suddenly flooding, after short storms with heavy raining, as is frequently observed in coastal zones under the Mediterranean climate. The change is not always so rapid in most coastal areas and even less in open seawater. In differently designed experiments, with limited daily additions of nu-
1200 1000 V 800 O 600 o» 400 200 0
1 J•
b
-^POC -•- PTCHO
f
? ^ 6 Days
10
12
Figure 8 Distribution of carbohydrates during a mesocosm experiment (a) and comparison of POC and particulate carbohydrate increase (b). PTCHO, particulate total carbohydrates; DTCHO, dissolved total carbohydrates; DPCHO, dissolved polysaccharides; DMCHO, dissolved monosaccharides.
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Gustave Cauwet
trients, S0ndergaard and coworkers (S0ndergaard et al, 2000) also observed the constant accumulation of DOM. They showed that the production of new DOC preceded new DON by about 1 week and that polysaccharides accounted for 50-70% of the new DOC. They also demonstrated that carbon partitioning in favor of C-rich DOM can take place during an active diatom bloom and not only during the decay of the bloom. That last observation is important since it gives to the release of carbon-rich DOM a general character. It can occur everywhere during blooms or during their decay. Nevertheless, nutrient limitation seems a favorable situation that can influence the quality of DOM. In such a situation, phytoplankton cells continue to synthesize organic matter by photosynthesis, but in the absence of nitrogen and possibly phosphorus they produce mainly polysaccharides that are more or less rapidly released in the aquatic environment. Because of the low phosphorus and nitrogen content, bacteria are temporarily unable to metabolize this carbon-rich DOM which accumulates in the dissolved or colloidal forms. At a later time, when nutrients are again available, bacteria can use this substrate more easily and the labile DOM disappears in a few weeks. This phenomenon generally occurs in late autumn when sunmier stratification disappears and nutrient-rich deep water can upwell and be mixed with nutrient-poor surface waters. From studies made recently in estuarine environments (Pakulski et al, 1995; Naudin et ah, 1991 \ Benner and Opsahl, submitted for publication, Cauwet et ai, 2002), it appears that the high concentration of nutrients measured in the rivers can decrease rapidly in the mixing zones down to very low values, by dilution and utilization, when reaching a salinity of 15 to 25. This finding means that the nutrient impoverished coastal waters are favorable for a high, C-rich DOM release. The fast change, on a short space and time scale, from highly productive to nutrient-limited condition, creates the perfect situation for DOC accumulation: a diatom bloom rapidly growing and a sudden limitation in nutrients, especially in phosphorus. DOC is seasonally accumulating in surface seawater, with more extension in coastal mixing zones.
B. EXPORT OF DOM FROM THE COASTAL ZONE Since excess DOM can remain in surface waters for several months, it is interesting to evaluate lateral or vertical transport of this accumulated DOC. Although known for a long time that DOC concentration is higher in surface waters than in deep ocean, it is only recently that some authors mentioned the possibility of a nonnegligible vertical transfer (Copin-Montegut and Avril, 1993; see Hansell, Chapter 14). With evidence that DOC accumulation in surface waters is a general phenomenon, this hypothesis must be considered more seriously. The general stratification observed in summer is not favorable for vertical transfer in the dis-
DOM in the Coastal Zone
599
solved form (diffusion). However, two other ways can be important: the mixing of surface water with deep water occurring in autumn and the association of surface DOM with particles that can sink rapidly. Calculating how much surface DOC can be transferred to deep waters by winter mixing is not easy because of the difficulty in determining the relative water volumes involved and how the deep layer is influenced by mixing. It is possible that the surface layer enriched in DOC mixes with the first 10- to 100-m layer below the nitracline. This is enough to enhance the mineralization of the excess DOC, contributing to the oxygen minimum. However, it should not enrich the deeper layers (>200 m) unless there is a strong downwelling. More realistic can be the transfer through the association with particles. The observation that flocculants can form from dissolved (or, more probably, colloidal) organic matter is not recent but if applied to surface waters enriched with polysaccharides it becomes a possible transfer of important quantities of carbon. The example of the mucilage formed in the Adriatic Sea from DOM, though being an extreme case, describes the possible mechanism. The richness of marine snow in carbohydrates has been mentioned and the bacterial activity associated with these aggregates has been well described (Azam et al, 1993). Recently, a study of the composition of surface and deep water particles has shown that polysaccharides associated with deep-sea particles have a composition close to polysaccharides in surface-water DOM, but different from dissolved sugars found in deep-sea water (Aluwihare and Repeta, 2000). This also suggests that there is an aggregation or adsorption onto particles of recently released carbohydrates in surface water, and that these particles sink rapidly, transferring their signal to deep waters. Another way of DOC transfer has been shown recently (Alldredge, 2000) in the form of interstitial water within marine aggregates. The author found as much as 10-140 mg C L~^ of aggregate, representing one to two orders of magnitude more than in surrounding water. Nevertheless, this "interstitial" carbon represented less than 2.5% of DOC in the water column, which would not change very much the total vertical flux. There is also a high probability that a large fraction of this interstitial DOC comes from the hydrolysis of particulate matter by bacteria in the aggregate and not from DOM from surface water. As far as deep water is concerned, the possibility of surface DOC being aggregated or adsorbed on particles to participate in a rapid vertical flux is probably the most realistic and quantitatively important mechanism of DOC transfer. Considering that seasonal accumulation of DOC in surface waters can increase the DOC concentration by 20 to 200 /xM, with probably a mean increase of 40-50 /xM (about 50 ^lg L"^), (Kepkay et aU 1993; Zweifel et al, 1995; Thingstad et al, 1997; Zweifel, 1999; S0ndergaard etal, 2000; Cauwet etal, 2002) the total DOC increase for the world ocean would be enormous. Considering the different values calculated for yearly DOC accumulation in different oceans (Copin-Montegut and Avril, 1993; Carlson et al, 1994; Borsheim and Myklestad, 1997; see Hansell,
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Chapter 15, for global estimates), 1.2 mol C nT'^ would be an acceptable average value. If only 10% of this excess is transferred to deep water it would represent an annual flux of 1.4 g C m~^ year~^ This flux is not very important compared to total primary production but not so different compared to the flux of detrital carbon and will enrich deep waters with labile or semilabile organic carbon. If it is not recycled, it will constitute an additional sink for carbon; if it is recycled it will increase the consumption of oxygen and will influence the cycle of nutrients. The mineralization of DOM generally recycles nutrients (N and P) but if this DOM is mainly composed with carbon-rich molecules (polysaccharides) it will consume more than recycle nutrients, especially phosphorus. This flux is more important in the coastal ocean than in the open ocean due to shallow waters and it will constitute a complementary input of food for some benthic organisms. The lateral export of DOM from the coastal zone to the open ocean should also be considered. Probably because blooms are larger in the coastal zone, the DOC accumulation is more important here than in the open sea. A fraction of this excess DOC can be transported to the slope and the open sea if the dynamics are favorable for such a rapid transfer. The evidence of a filament of carbonrich shelf water abutting the Gulf Stream (Bates and Hansell, 1999) led the authors to calculate that this mechanism could export to the Atlantic as much as 2.7 X 10^^ g C year"^ They also suggest that this DOC originates mainly from riverine sources. It seems far from negligible compared to the estimate of global DOC inputs by world rivers (250 x 10^^ g C year"^). It is difficult to imagine that the Chesapeake Bay exports more than 14% of total DOC exported by the Amazon River (19 x 10^^ g C year"^). It is also surprising that the authors attribute this DOM to the river inputs while the C:N ratio of DOM ranges from 10 to 14, a low value for terrestrial organic matter. Nevertheless, it demonstrates that rapid DOC export from the coastal zone can be an important transfer mechanism.
V. CONCLUSIONS From river inputs to export of DOM, this chapter covers a broad topic and demonstrates in itself the complexity, but also the importance, of the coastal zone. Compared to the open ocean, the nearshore ocean is more complex because of variable inputs from continents, remobilization processes and a succession of several recycling steps. In the coastal ocean, mixing of organic matter of various origins and of different diagenetic histories is the norm. In terms of riverine inputs, most global estimates are more than 10 years old. There is also very little work on the nature of riverine organic matter and its variability. Usually, the viewpoint in the Hterature is that terrestrial organic matter originates from higher plants, forgetting that there is an intense aquatic life in
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freshwater bodies. Some isotopic studies on organic matter exported by estuaries or salt marshes have shown that the terrestrial signature is not always dominant and the aquatic contribution can modify the 8^^C of DOM (Fry et al, 1992). It could explain why some studies on isotopic composition in coastal zone and estuaries give sometimes results difficult to interpret. What is probably true for POC is not certainly true for DOC. The paradox several times mentioned that terrestrial organic matter brought by the rivers is highly refractory to degradation but is rapidly disappearing when progressing toward open sea is not clearly explained. The isotopic measurements made by Kelley et al. (1998) are quite demonstrative of the complexity of coastal systems. These authors found 5^^C values of —20/—25 in particulate organic matter from Mississippi plume to the Gulf of Mexico, -19.6/-24.7 in DOM of the Gulf of Mexico, and - 3 3 in bacteria of the coastal zone, suggesting they are mainly living on terrestrial dissolved organic matter. More recently, Raymond and Bauer (2001) have shown the variable age (from modem to 1300 years) of DOM transported by several rivers of the eastern coast of the United States, compared to the generally old POC (700 to 4700 years). They also demonstrated that the most labile fraction is also the youngest one. The main consequence is the strong influence of the degradation processes occurring in the river, the estuary or the coastal zone on the apparent age of the exported DOM, the youngest one disappearing rapidly while the oldest one can accumulate in the water column or in sediment. Concerning the biogeochemical processes in mixing zones of estuaries, we slowly discover, while progressing in our knowledge that things are much more complex than we thought before and that supposed rich (in terms of nutrients) areas function from time to time like oligotrophic environments. The complex relationship existing between different nutrients and between phytoplankton and bacterioplankton makes interpretation of field results sometimes very difficult. Coupling of fieldwork and experimental approaches will be more and more necessary if we want to understand processes and quantify them. In the future, we must organize new multidisciplinary programs. Studies focusing on a few parameters may be necessary to enrich the data bank but they are too limited for understanding the complex biogeochemical mechanisms occurring in the coastal zone. Until now, for the coastal zone, the water dynamics aspect was somewhat neglected while it could sometimes bring key information. This is particularly true if we consider that one of the most—or maybe the most—important parameter controlling the biogeochemistry of estuarine and coastal zones could be the residence time. The time scale seems to be our bigger problem for explaining the mechanisms. Finally, joining some other authors (Bauer and Druffel, 1998), we must now acknowledge that the coastal zone must be considered seriously as an important contributor to carbon export toward the open and deep sea. To know if it can contribute to a significant carbon sink from the atmosphere to the deep ocean, or even more to the sediment, is another story.
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ACKNOWLEDGMENTS I thank three anonymous reviewers for their useful comments and criticisms, with a special mention for Dr. Jon Sharp, who did extensive editing of my English while also proposing relevant improvements to the manuscript.
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Meybeck, M. (1993). C, N, P and S in rivers: From sources to global inputs. In "Interactions of C, N, P and S Biogeochemical Cycles and Global Change" (R. WoUast, F. T. Mackenzie, L. Chou, Eds.), NATO ASI Series, pp. 163-193. Springer-Verlag, Berlin. Miller, W. L., and Moran, M. A. (1997). Interaction of photochemical and microbial processes in the degradation of refractory dissolved organic matter from a coastal marine environment. Limnol. Oceanogr. 42,1317-1324. Miller, W. L., and Zepp, R. G. (1995). Photochemical production of dissolved inorganic carbon from terrestrial organic matter: Significance to the oceanic organic carbon cycle. Geophys. Res. Lett. 22, 417-420. Monti, M., Welker, C , and Fonda-Umani, S. (1996). Effects of synthetic zeolite "A" and polycarboxylates on quality and quantity of diatom mucous exudates. Chemosphere 32,1741-1754. Moran, M. A., Sheldon, W. M. J., and Sheldon, J. E. (1999). Biodegradation of riverine dissolved organic carbon in five estuaries of the southeastern United States. Estuaries 22,55-64. Moran, M. A., and Zepp, R. G. (1997). Role of photoreactions in the formation of biologically labile compounds from dissolved organic matter. Limnol. Oceanogr. 42,1307-1316. Mozetic, P., Turk, V., and Malej, A. (1998). Nutrient enrichment effect on plankton composition. Ann. Istran Mediterr. Stud. {Slovenia) 13/98, 31-42. Mozetic, P., Turk, V., Malej, A., Tezic, S., Ahel, M., and Cauwet, G. (1997). Coastal plankton response to nutrient enrichment: An experimental system. In "Water Pollution. IV. Modelling, Measuring and Prediction" (R. Rajar and C. A. Brebbia, Eds.), pp. 151-160. Computational Mechanics, Southampton, Boston. Naudin, J. J., and Cauwet, G. (1997). Transfer mechanisms and biogeochemical processes at the bottom nepheloid layer. Case study of the coastal zone off the Rhone River (France). Deep-Sea Res. I, 44, 769-779. Naudin, J. J., Cauwet, G., Chretiennot Dinet, M. J., Deniaux, B., Devenon, J. L., and Pauc, H. (1997). River discharge and wind influence upon particulate transfer at the land ocean interaction: Case study of the Rhone River plume. Estuarine Coastal Shelf Sci. 45,303-316. Newman, M. E., FileUa, M., Chen, Y., Negre, J. C , Perret, D., and Buffle, J. (1994). Submicron particles in the Rhine River II. Comparison of field observations and model predictions. Water Res. 28,107-118. Norrman, B., Zweifel, U. L., Hopkinson, C. S., Jr., and Fry, B. (1995). Production and utilisation of dissolved organic carbon during an experimental diatom bloom. Limnol. Oceanogr 40, 898-907. Nourredin, S., and Courtot, P. (1989). Conservative behaviour of humic substances (DHS) in a macrotidal estuary. Composition of particulate and dissolved phases. Oceanol. Acta 12, 381-391. Obemosterer, I., and Hemdl, G. J. (1995). Phytoplankton extracellular release and bacterial growth: Dependence on the inorganic N/P ratio. Mar Ecol. Prog. Ser 116, 247-257. Ogawa, H. (1999). Microbial utilization of dissolved organic matter in sea water: The latest trend of the research from biogeochemical viewpoints. Bull. Plankton Soc. Jpn. 46, ?>A-A2. Olsson, K., and Anderson, L. G. (1997). Input and biogeochemical transformation of dissolved carbon in the Siberian shelf seas. Cont. Shelf Res. 17, 819-833. Opsahl, S., and Benner, R. (1998). Photochemical reactivity of dissolved lignin in river and ocean water. Limnol. Oceanogr 43,1297-1304. Pakulski, J. D., Benner, R., Amon, R. M. W., Eadie, B., and Whitledge, T. (1995). Conmiunity metabolism and nutrient cycling in the Mississippi River plume: Evidence for intense nitrification at intermediate salinities. Mar Ecol. Prog. Ser 117,207-218. Pakulski, J. D., Benner, R., Whitledge, T., Amon, R., Eadie, B., Cifuentes, L., Ammerman, J., and Stockwell, D. (2000). Microbial metabolism and nutrient cycling in the Mississippi and Atchafalaya River plumes. Estuarine Coastal Shelf Sci. 50,173-184. Patel, N., Mounier, S., Guyot, J. L., Benamou, C , and Benaim, J. Y. (1999). Fluxes of dissolved and colloidal organic carbon, along the Purus and Amazonas rivers (Brazil). Sci. Total Environ. 229, 53-64.
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Pettine, M., Patrolecco, L., Camusso, M., and Crescenzio, S. (1998). Transport of carbon and nitrogen to the Northern Adriatic Sea by the Po River. Estuarine Coastal Shelf Sci. 46,127-142. Prahl, F. G., and Coble, P. G. (1994). Input and behavior of dissolved organic carbon in the Columbia River estuary. In "Changes in Fluxes in Estuaries: Implications from Science to Management," pp. 451-457. Olsen and Olsen, Fredensborg. Ragueneau, O., Lancelot, C , Egorov, V., Vervlinmieren, J., Daoud, N., Rousseau, V., Popovitchev, v., Cauwet, G., and Deliat, G. (2(X)2). Present day biogeochemical transformations of inorganic nutrients in the Danube-north western Black Sea mixing zone. Estuarine Coastal Shelf Set, in press. Raymond, P. A., and Bauer, J. E. (2002). Bacterial consumption of DOC during transport through a temporate estuary. A^war. Microb. Ecol 22, 1-12. Richey, J. E. (1991). The biogeochemistry of a major river system: the Amazon case study. In "Biogeochemistry of Major World Rivers" (E. Degens, S. Kempe, and J. E. Richey, Eds.), pp. 57-74. Wiley, Chichester. Safmllah, S., Mofizuddin, M., Iqbal Ah, S. M., and Enalul Kabir, S. (1987). Biogeochemical cycles of carbon in the rivers of Bangladesh. In "Transport of Carbon and Minerals in Major World Rivers" (E. T. Degens, S. Kempe, and W. Gan, Eds.), part 4, pp. 435-442. Mitteilungen Der GeologischPalaontologischen Institutes der Universitat Hamburg. Saliot, A., Cauwet, G., Cahet, G., Mazaudier, D., and Daumas, R. (1996). Microbial activities in the Lena River delta and Laptev Sea. Mar. Chem. 53, 247-254. Seitzinger, S. P., and Sanders, R. W. (1997). Contribution of dissolved organic nitrogen from rivers to estuarine eutrophication. Mar. Ecol. Prog. Sen, 159, 1-12. Sempere, R., and Cauwet, G. (1995). Occurrence of organic colloids in the stratified estuary of the Krka River (Croatia). Estuarine Coastal Shelf Sci. 40,105-114. Sempere, R., Charriere, B., Van Wambeke, F , and Cauwet, G. (20(X)). Carbon inputs of the Rhone River to the Mediterranean sea: Biogeochemical implications. Global Biogeochem. Cycles 14,669-681. Serratore, P., Rinaldi, A., Montanari, G., Ghetti, A., Ferrari, C. R., and VoUenweider, R. A. (1995). Some observation about bacterial presence in seawater related to mucilaginous aggregates in the Northern Adriatic Sea. Sci. Total Environ. 165, 185-192. Sharp, J. H., Cifuentes, L. A., Coffin, R. B., Pennock, J. R., and Wong, K. C. (1986). The influence of river variability on the circulation, chemistry and microbiology of the Delaware Estuary. Estuaries 9, 261-269. Sharp, J. H., Pennock, J. R., Church, T. M., Tramontano, J. M., and Cifuentes, L. A. (1984). The estuarine interaction of nutrients, organics and metals: A case study in the Delaware Estuary. In "The Estuary as a Filter" (V. S. Kennedy, Ed.), pp. 241-258. Academic Press, Orlando. Sholkovitz, E. R. (1976). Rocculation of dissolved organic and inorganic matter during the mixing of river water and seawater. Geochim. Cosmochim. Acta 40, 831-845. Sholkovitz, E. R., Boyle, E. A., and Price, N. B. (1978). The removal of dissolved humic acids and iron during estuarine mixing. Earth Planet. Sci. Lett. 40, 130-136. S0ndergaard, M., WiUiams, P. J. 1., Cauwet, G., Riemann, B., Robinson, C , Terzic, S., Woodward, M., and Worm, J. (2000). Organic carbon partitionning and DOC accumulation in marine plankton conmiunities: Controls, flux and fate of DOC in a mesocosm experiment. Limnol. Oceanogr. 45, 1097-1111. Spitzy, A., and Leenheer, J. (1991). Dissolved organic carbon in rivers. In "Biogeochemistry of Major Worid Rivers" (E. Degens, S. Kempe, and J. E. Richey, Eds.), pp. 213-232. Wiley, Chichester. Stepanauskas, R., Leonardson, L., and Tranvik, L. J. (1999). Bioavailability of wetland-derived DON to freshwater and marine bacterioplankton. Limnol. Oceanogr 44,1477-1485. Telang, S. A., Pocklington, R., Naidu, A. S., Romankevitch, E. A., Gitelson, I. I., and Gladyshev, M. I. (1991). Carbon and minerals transport in major North American, Russian Arctic and Siberian Rivers: The St Lawrence, the Mackenzie, the Yukon, the arctic Alaskan Rivers, the arctic basin
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rivers in the Soviet Union and the Yenisei. In "Biogeochemistry of Major World Rivers, SCOPE Report 42" (E. T. Degens, S. Kempe, and J. E. Richey, Eds.), pp. 75-104. Wiley, Chichester. Thingstad, T. R, Hagstrom, A., and Rassoulzadegan, F. (1997). Accumulation of degradable DOC in surface waters: Is it caused by a malfunctioning microbial loop? Limnol Oceanogr. 42, 398-404. Thurman, E. M. (1985). "Organic Geochemistry of Natural Waters." Martinus Nijhoff/Dr W. Junk, Boston. Welker, C , and Nichetto, R (1996). The influence of mucous aggregates on the microphytobenthic community in the northern Adriatic Sea. RS.Z.N.I. Mar. Ecol 17,473^89. Wells, M. L. (2002). Marine colloids and metals. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. HanseU and C. A. Carlson, Eds.), pp. 367^04. Academic Press, San Diego. Whitehouse, B. G., MacDonald, R. W, Iseki, K., Yunker, M. B., and McLaughlin, F. A. (1989). Organic carbon and colloids in the Mackenzie River and Beaufort Sea. Mar. Chem. 26, 371-378. Williams, P. J. L. (1995). Evidence for the seasonal accumulation of carbon-rich dissolved organic material, its scale in comparison with changes in particulate material and the consequential effect on net C/N assimilation ratios. Mar. Chem. 51,17-29. WiUiams, P. M., and Druffel, E. R. M. (1987). Radiocarbon in dissolved organic matter in the central North Pacific Ocean. Nature 330,246-248. Zhang, S., Gan, W. B., and Ittekkot, V. (1992). Organic matter in large turbid rivers: The Huanghe and its estuary. Mar. Chem. 38, 53-68. Zweifel, U. L. (1999). Factors controlling accumulation of labile dissolved organic carbon in the Gulf of Riga. Estuarine 48,357-370. Zweifel, U. L., Wikner, J., Hagstroem, A., Lundberg, E., andNorrman, B. (1995). Dynamics of dissolved organic carbon in a coastal ecosystem. Limnol. Oceanogr 40, 299-305.
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Chapter 13
Sediment Pore Waters D a v i d J. Burdige Department of Ocean, Earth, and Atmospheric Sciences Old Dominion University Norfolk, Virginia I. Introduction A. Scientific Background II. Dissolved Organic Carbon (DOC) in Sediment Pore Waters A. General Observations B. An Advection/Diffusion/ Reaction Model for Sediment DOC Cycling Controls on DOC Concentrations with Depth in Surficial ("Shallow") Sediments D. Pore Water DOC Profiles in Deep Sediment Cores III. Dissolved Organic Nitrogen (DON) IV. Dissolved Organic Matter (DOM) Compositional Data A. Volatile Fatty Acids (VFAs) B. Amino Acids C. Carbohydrates V. The Role of Benthic DOM Fluxes in the Ocean Carbon and Nitrogen Cycles
Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
A. Benthic DOC Fluxes B. Benthic DON Fluxes C. The Extent to Which Benthic DOM Fluxes Affect the Composition and Reactivity of Deep-Water DOM VI. The Role of Pore-Water DOM in Sediment Carbon Preservation VII. Conclusions and Suggestions for Future Research Acknowledgments Appendix: A Description of the DOM Advection/Diffusion/ Reaction Model Anoxic, Nonbioturbated Sediments (ANS Model) Bioturbated and/ or Bioirrigated Sediments (BBS model) References
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I. INTRODUCTION Dissolved organic matter (DOM) in marine sediment pore waters plays an important role in sediment carbon remineralization and may also be involved in sediment carbon preservation (see discussions in Krom and Westrich, 1981; Hedges, 1992, Henrichs, 1992, 1993; Hedges and Keil, 1995). It is also important in oceanic and sediment nutrient (N and P) cycling (e.g., Burdige and Zheng, 1998). Finally, DOM in sediment pore waters plays a role in pore water metal complexation and therefore affects dissolved metal and metal-complexing ligand fluxes from sediments (Elderfield, 1981; Skrabal et aL, 1997, 2000). Of the articles cited above that discuss the role of DOM in sediment carbon remineralization and preservation, only Krom and Westrich (1981) summarizes the known information on the concentrations and composition of pore water DOM (also see Thurman, 1985, for similar discussions). In spite of the 15- to 20-year gap since the presentation of such sunmiaries, the goal here is not, however, to simply update these inventories. Rather, I wish to specifically examine DOM in sediment pore waters with reference to several specific questions: 1. What do we know about the composition and reactivity of pore-water DOM, with particular reference to its role in sediment organic matter remineralization? 2. What do we know about the controls on pore-water DOM concentrations? 3. What is the role of benthic DOM fluxes in the global ocean cycles of carbon and nitrogen? 4. What is the role of pore-water DOM in sediment carbon preservation? The discussion in this chapter will focus on examining these questions in estuarine and continental margin sediments, in part because much of the detailed work in recent years on sediment DOM cycling has occurred in these sediments. Since the vast majority of carbon preservation and remineralization in all marine sediments occurs in estuarine and continental margin sediments (Hedges, 1992; Hedges and Keil, 1995; Middelburg etal, 1997), there is also important scientific justification for taking this approach. A.
SCIENTIFIC B A C K G R O U N D
To begin this discussion I start with the general observation that DOM in sediment pore waters is a heterogeneous collection of organic compounds, ranging in size from relatively large macromolecules (e.g., dissolved proteins or humic substances) to smaller molecules such as individual amino acids or short-chain organic acids (e.g., Krom and Westrich, 1981; Burdige and Martens, 1990; Henrichs, 1992). Concentrations of DOM in pore waters (both dissolved organic carbon [DOC] and dissolved organic nitrogen [DON]) are generally elevated over bottom-water
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values (up to an order of magnitude), implying that there is net production of this material in sediments as a result of remineralization processes. Much of the total pore water DOC and DON is of relatively low molecular weight (<3 kDa; see below) and appears to be refractory, at least in a bulk sense. Such observations are consistent with the results of water column studies showing that high-molecularweight DOC represents a more reactive and less diagenetically altered fraction of the total DOC than the more abundant, and presumably more refractory, lowmolecular-weight DOC (Benner et al, 1992; Amon and Benner, 1994; Santschi et al, 1995; Guo et al, 1996; Guo and Santschi, 1997; Benner, Chapter 3). To help further explain the cycling (i.e., production and consumption) of DOM in sediment pore waters, Burdige and Gardner (1998) proposed the pore water size/reactivity (PWSR) model, a model that in part is conceptually based on traditional models for carbon cycling in anoxic sediments. In this model we think of the degradation of sediment particulate organic matter (POM) to inorganic nutrients as occurring by a series of hydrolytic (or oxidative), fermentative, and eventually respiratory processes that produce and consume pore-water DOM intermediates with increasingly smaller molecular weights. Although this process likely leads to a continuum of DOM compounds (in terms of molecular weights), the model assumes that there is an initial class of high-molecular-weight DOM (HMW DOM) that contains biological polymers such as dissolved proteins and polysaccharides resulting from the initial hydrolysis or oxidative cleavage (depolymerization) of sediment POM (Laanbroek and Veldkamp, 1982; Capone and Kiene, 1988; Henrichs, 1992; Alperin et al, 1994; Amosti et al, 1994; Burdige et al, 2000). Most HMW DOM is further hydrolyzed and fermented to monomeric lowmolecular-weight DOM compounds (mLMW DOM) such as acetate, other small organic acids, and individual amino acids, that are then utilized in terminal respiratory processes in sediments such as denitrification or sulfate reduction. It is also assumed in this model that a small fraction of the HMW DOM is broken down to a group of polymeric low-molecular-weight compounds (pLMW DOM) that are proposed to be much less reactive than HMW DOM. This assumption does not exclude the possibility of geopolymerization reactions forming pLMW DOM from mLMW DOM compounds, through reactions such as the melanoidin or "browning" reaction (an abiotic sugar-amino acid condensation reaction; Hedges, 1988), or through complexation reactions such as those that have been described for short-chain organic acids such as acetate (Christensen and Blackburn, 1982; Michelson et al, 1989). However, if these reactions do occur on early diagenetic time scales, their products apparently still have relatively low molecular weights (i.e., less than ~ 3 kDa; Burdige and Gardner, 1998). The existence of these different DOM pools (with different reactivities) is consistent with DOM molecular weight studies showing that the vast majority of the DOC and DON in sediment pore waters has a molecular weight less than ^ 3 kDa (~80-90% in estuarine sediments and ^60-70% in continental margin
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sediments; Burdige et ai, 1996; Burdige and Gardner, 1998; Burdige and Zheng, 1998). Since total DOM generally increases with sediment depth (see Sections II.A and III), this low-molecular-weight material (also referred to as DOC3) also accumulates with sediment depth and burial. Therefore, the accumulation of pore water DOM with depth in sediments results from the net production of refractory low (and not high)-molecular-weight DOM, since both HMW DOM and mLMW DOM represent reactive DOM pools that turn over rapidly. From one perspective this accumulation of DOM in sediment pore waters is somewhat similar to that which is observed for inorganic nutrients in pore waters (e.g., Krom and Westrich, 1981). However, because many components of the DOM pool are intermediates in the remineralization process (as opposed inorganic nutrients, which are remineralization end products) the dynamics of DOM cycling in sediments is likely to be different than those of inorganic nutrients. Several lines of evidence suggest that the DOM accumulating in sediments is indeed refractory. The first is simply that relatively high concentrations of this material can be found in sediments and that DOM accumulates with depth in sediments as rates of POM remineralization and the reactivity of sediment POM both decrease (Westrich and Bemer, 1984; Middelburg, 1989; Burdige, 1991a). If the majority of the pore-water DOM had a high degree of reactivity, then one would expect its concentration to eventually decrease with depth on early diagenetic time scales. Second, in many coastal marine sediments, pore-water DOM "humic"-like fluorescence is strongly correlated with total DOC concentrations (Chen et al, 1993; Skoog et aL, 1996; Burdige et al, 2002). Given that the vast majority of the DOC in sediment pore waters is of low-molecular-weight (less than ~ 3 kDa), and that the properties of this low-molecular-weight DOC appear to be consistent with what is referred to as pLMW DOC (see Burdige and Gardner, 1998, for further details), these DOM fluorescence observations support the notion that pLMW DOM is likely what is referred to as dissolved humic substances. This observation is also consistent with the rethinking in recent years by some workers of just what humic substances represent and how they form (see discussions above and in Hatcher and Spiker, 1988; Amon and Benner, 1996).
II. DISSOLVED ORGANIC CARBON IN SEDIMENT PORE WATERS A. GENERAL OBSERVATIONS
In the past two decades there have been numerous pore-water DOC profiles published from a wide range of surficial marine sediments (upper ~1 m), in environments ranging from the deep sea to shallow-water estuaries, salt marshes, and sea grasses (Suess et ai, 1980; Devol and Ahmed, 1981; Elderfield, 1981; Orem
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and Gaudette, 1984; Sholkovitz and Mann, 1984; Howes et al, 1985; Heggie et al, 1987; Henrichs and Farrington, 1987; Alperin et al, 1992, 1994, 1999; Burdige et aU 1992, 1999, 2000; Chen et al, 1993; Koepfler et al, 1993; Martin and McCorkle, 1993; Burdige and Homstead, 1994; Bauer et al, 1995; Holmer and Nielsen, 1997; Hulth et al, 1991 \ Landen-Hillmeyr, 1998; Lomstein et al, 1998; Otto and Balzer, 1998; Lahajnar et al, 2000; Burdige, 2001; Holcombe et al, 2001; and others; also Krom and Westrich, 1981, for a review of the earlier literature). In an attempt to describe some of the general controls on pore-water DOC depth profiles Starikova (1970) and Krom and Sholkovitz (1977) noted that these profiles tend to fall into two general categories. In anoxic sediments, where sulfate reduction dominates and benthic macrofaunal processes (i.e., bioturbation and/or bioirrigation) are insignificant, pore-water DOC concentrations generally increase with depth, often approaching "asymptotic" concentrations with depth (Fig. 1). In contrast, in what these authors term "oxic" or "oxidizing" sediments, DOC concentrations are elevated above bottom-water values but are also much more constant with depth in the upper portions of the sediments (Fig. 2). While many of these sediments are oxic in character, it may actually be more appropriate to recognize that such sediments are often bioturbated and/or bioirrigated and have mixed (or oscillating) redox conditions (as defined by Aller, 1994). The threedimensional, heterogeneous geometry in such sediments then leads to a situation
DOC (|iM) 400
800 1200 1600
DOC (^iM) 1200
s a^
Figure 1 Pore water DOC concentrations versus depth in anoxic marine sediments. Symbols on the upper jc-axes represent concentrations in bottom-water samples obtained by hydrocasts. (Left) Cores collected at site M3 in the mesohaUne Chespapeake Bay in 7/95 ( • ) and 10/95 ( • ) . Data from Burdige and Zheng (1998). (Right) Replicate cores collected in Santa Monica Basin in 3/94 (Burdige et al, unpubhshed data). Also see Jahnke (1990), Shaw et al (1990), and McManus et al (1997) for general information on the geochemistry of these sediments. See Fig. 8 for additional DOC profiles in anoxic sediments.
David J. Burdige
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Figure 2 Pore-water DOC concentrations versus depth in bioturbated and/or bioimgated (i.e., mixed redox) marine sediments. Symbols on the upper jc-axes represent concentrations in bottom water samples obtained by hydrocasts. (Left) Cores collected at site S3 in the southern Chespapeake Bay in 10/96 ( • ) and 8/97 ( • ) . Data from Burdige and Zheng (1998) and Burdige (2001). (Middle) Replicate cores collected at a site (95 m water depth) in Monterey Bay (Burdige et ai, unpubHshed data). Also see Burdige et al (1999) and Berelson et al. (in preparation) for general information on the geochemistry of these sediments. (Right) A core collected at station N on the California continental rise (4100 m water depth) at the base of the Monterey deep sea fan (DOC data from Bauer et al., 1995). Also see Cai et al. (1995) for general information on the geochemistry of the sediments at this site.
in which organic matter remineraUzation may (at least partially) be thought of as oscillating between oxic and suboxic/anoxic processes. The factors controlling DOC profiles in these two types of sediments will be discussed in the next two sections. It is also important to note here that if one were to go into the literature and examine these published DOC depth profiles, one would find that some profiles do not appear to be consistent with the discussions presented here. Clearly, it is possible (and highly likely) that our incomplete understanding of DOC cycling in sediments is the cause of these differences. At the same time though, several studies have discussed potential sampling artifacts that can affect pore water DOM analyses (Howes etal, 1985; Hines etai, 1994; Chin and Gschwend, 1991; Martin and McCorkle, 1993; Burdige and Gardner, 1998; Otto and Balzer, 1998; Alperin^ra/., 1999; Holcombe et ai, 2001), suggesting another possible explanation for these differences. In particular, in sediments containing abundant benthic macrofaunal populations pore-water collection via sediment centrifugation can lead to elevated DOC concentrations as compared to concentrations in pore waters collected by more "gentle" techniques (e.g., by using sediment sippers; Burdige and Gardner, 1998; Alperin et al, 1999; Holcombe et al, 2001). It has been suggested that these differences are due to animal rupture or simple DOM release by benthic organisms
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during core processing (Martin and McCorkle, 1993; Alperin et al, 1999). Such possible artifacts may also affect concentrations of individual components of the DOC pool as well as total DOC concentrations (J0rgensen et al, 1981; Burdige and Martens, 1990). Recently, however, Holcombe et al. (2001) observed similar differences in pore-water DOC concentrations as a function of sample collection techniques (i.e., centrifugation versus sediment sipping) in cores collected in anoxic continental margin sediments off Mexico that are devoid of benthic macrofauna. They argue that these differences, along with analogous differences in bioturbated/bioirrigated sediments, are not methodological artifacts (as described above) but are more general mechanistic responses possibly associated with pore-water DOM-sediment mineral surface interactions. As they note, more detailed chemical analyses of the pore-water DOM collected by these various methods will be needed to test this suggestion. More detailed comparative studies in other anoxic (nonbioturbated/ bioirrigated) sediments will also be needed to verify the generality of the Holcombe etal. (2001) results.
B. A N ADVECTION/DIFFUSION/REACTION M O D E L FOR SEDIMENT D O C
CYCLING
To examine the controls on DOC cycling in the different sediment types discussed above, I will use an advection/diffusion/reaction model based on one originally described by Burdige and Martens (1990) for the cycling of dissolved, free amino acids in anoxic sediment pore waters. The model is illustrated in Fig. 3. In this model, it is assumed that the utilization of sediment POM (producing reactive DOC intermediates) decreases exponentially from a value of RQ at the sediment surface to some low, constant value, ROQ, at depth (Burdige and Martens, 1990). Assuming that HMW DOC (H) represents the first set of DOC intermediates produced during remineralization, and that its consumption is first order with respect to its concentration, the steady-state diagenetic equation for HMW DOC can be
y
mLMW-DOM
=(i-a)kHH y sediment POM
» HMW-DOM • (H) =kHH
=akHH '
— (fast)
pLMW-DOM (P)
Figure 3 A schematic model of DOM remineralization in sediments based on the PWSR model. See the text for the definitions of these symbols.
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written as A ^
- CO— + ARe-^^ -hRoo- kuH = 0,
[1]
where D^ is the bulk sediment diffusion coefficient, co is the sedimentation rate, X is the attenuation constant for the rate of sediment POM utiHzation (=HMW DOC production), k^ is the rate constant for HMW DOC consumption, x is depth, and AR equals RQ — ROQ. Based on arguments presented in Burdige (2001) it is assumed that HMW DOC consumption then occurs by two pathways, through either pLMW DOC or mLMW DOC intermediates. Since mLMW DOC compounds are presumed to be a relatively small fraction of the total DOC pool that are rapidly oxidized to CO2, I have chosen to not model their depth distribution here. This then leads to the following steady-state diagenetic equation for pLMW DOC: d^P dP Ds-r^ - CO— + akuH - k^P = 0, dx^ dx
[2]
where P is the concentration of pLMW DOC, a is the fraction of HMW DOC consumption that goes through the pLMW DOC pool, and kp is first-order rate constant for pLMW DOC consumption. The solutions to these equations are described in the Appendix, as is the development and solution to modified forms of these equations that include the benthic macrofaunal processes bioturbation and bioirrigation. 1. Application to Anoxic Sediments Model profiles obtained using the ANS model are similar in shape to those seen for sediment pore-water profiles of total DOC in anoxic, nonbioturbated, and nonbioirrigated sediments (e.g., compare Figs. 1 and 4). Furthermore, model-derived profiles of pLMW DOC are consistent with pore water profiles of humic-like fluorescence, based on the assumption that humic-like fluorescence is a tracer for refractory pLMW DOC (see Burdige, 2001; Burdige et ai, 2002, for further details). Interestingly, in spite of the fact that model-predicted concentrations of HMW DOC were substantially lower than those of pLMW DOC, their pore water gradients near the sediment surface were much more similar in magnitude (see the insert to Fig. 4). These model results also indicate that net production rates of HMW DOC and pLMW DOC have different depth distributions. Net production of HMW DOC was highest at the sediment surface and decreased very rapidly with depth in an exponential-like fashion. In contrast, net production rates of pLMW DOC were at least initially lower than those of HMW DOC, reached their maximum value just below the sediment surface and then decreased more slowly with depth. These observations will be discussed in further detail in section V.C.
619
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1
^0
Figure 4 Model results obtained using the anoxic, nonbioturbated (ANS) DOM model described in the text and Appendix. (Left) Pore-water profiles for HMW DOM, pLMW DOM, and total DOM (= pLMW DOM + HMW DOM) predicted by the model equations. Shown as an insert are the pLMW DOM and HMW DOM curves on an expanded scale, indicating the similarity in concentration gradients for both types of DOM near the sediment-water interface. (Middle) The pore water profile for HLMW DOM shown on the left on expanded depth and concentration scales. (Right) Net production rates of HMW DOM and pLMW DOM versus depth in these model calculations. Note the scale break for HMW DOM production in the upper ~ 1 cm, and the fact that there is a small amount of net HMW DOM consumption between ~ 1 and 12 cm. The net production rate of HMW DOM is defined as (ARe-^^ + Roo) -kuH (see Eq. [1] for further details), while that for pLMW DOM is aknH-k^P (see Eq. [2] for further details). The parameters used in these model calculations are: RQ = 610 mM year •,Roo= 40mMyear-i; ^H = lOOOyear"^; ^p = 1.2 year'^; a = 0.1; X = 0.82 cm'^-w = 1 cm year" ; Ds = 52.5 cm^/year; ^ ° = 5 /xM; P° = 145 /xM.
2. Application to Bioturbated and Bioirrigated Sediments Equations [1] and [2] can be modified to include the benthic macrofaunal processes of bioturbation and bioirrigation. These modified equations and their solutions (the BBS model) are discussed in the Appendix. The approach used here builds on observations discussed in Burdige (2001) in which a box model version of these equations (and Fig. 3) was used to compare sediment DOM cycling in anoxic versus mixed redox (bioturbated and/or bioirrigated) sediments. Relevant to the discussion here, these results show that changes in sediment redox conditions alter the pathways of carbon flow through DOM intermediates and lead to the buildup of refractory pLMW DOM ( « total DOC) under anoxic conditions. This appears to occur as a result of some combination of either enhanced consumption of pLMW DOM or preferential carbon flow through mLMW DOM intermediates under mixed redox conditions. In the context of the model discussed here this would imply that either k^ or (l-a) is smaller under anoxic vs mixed redox conditions (see Burdige, 2001, for further details). However,
620
David J.Burdige
in the discussion below I will simply use the former assumption in the model that is presented here (i.e., that k^ is smaller under anoxic versus mixed redox conditions.) Model profiles obtained using the BBS model are shown in Fig. 5. To keep these profiles geochemically "honest" I have used a and DB values based on pubHshed results (AUer, 1982; Boudreau, 1997; Nie et al, 2001). Given a Ds value of 53 cm^/year for an average DOC molecule (Burdige et al, 1992), this then implies that a value of Dj/Ds equal to ^ 3 is likely a reasonable upper limit of this ratio. Although I am unable to similarly constrain k^ using field observations, in these calculations I have simply set k^ equal to 10 (note that kj = kp^B^kp^N and is thus the ratio of the rate constant for pLMW DOC consumption in bioturbated/bioirrigated versus anoxic sediments). The effect that varying kr has on these pore water DOM profiles will also be examined below. In a general sense, the effects of bioturbation and bioirrigation on total pore water DOC profiles are similar to those seen for inorganic pore water constituents (e.g., Aller, 1982). Bioturbation tends to minimize pore-water DOC concentrations that would otherwise build up with depth in nonbioturbated sediments. The inclusion of bioirrigation in model calculations yields similar results, although here the balance between sediment remineralization processes, diffusion and DOC loss by irrigation results in slightly more pronounced mid-depth minima in the zone of burrowed sediments. Concentration profiles for HMW DOC show much smaller changes as a result of sediment mixing or pore-water irrigation as compared to those observed for total DOC depth profiles. Presumably, the rates of HMW DOC cycling near the sediment-water interface are sufficiently rapid, relative to either macrofaunal transport processes or enhanced pLMW DOC oxidation, and therefore minimize the effects of these processes on depth profiles of reactive HMW DOC intermediates. An examination of the profiles in Fig. 5 indicates that there are three aspects of mixed redox conditions in sediments that can affect pore-water DOC concentrations: physical mixing of the sediments by bioturbation, bioirrigation of the sediments, changes in the kinetics of sediment DOM cycling (i.e., enhanced pLMW DOC consumption). The significance of these parameters on sediment DOC dynamics has been further examined using sensitivity plots that examine the effects of the following quantities on average DOC concentrations in the sediment mixed (or burrowed) layer: the ratio Dj/Ds, the bioirrigation exchange coefficient a, the rate constant k^. The values of Dj/Ds and a used here are those used in Fig. 5, and kj; has been varied from 1 (where redox conditions have no effect on pLMW-DOC consumption) to values where redox conditions do have a significant effect (kr >10). The results of this sensitivity analysis are shown in Fig. 6. For all but modest rates of bioirrigation (small a values) and small values ofk^, average DOC concentrations are essentially independent of both parameters and are significantly lower than those in anoxic, nonbioirrigated sediments (Figs. 6A and 6B). Average DOC
total DOC (mM) (= pLMW-DOC)
HMW- DOC (|lM) 0
200
400
a OH
(U
Q
400
S Q
Figure 5 Model-derived profiles for HMW DOC and total DOC (^ pLMW DOC) obtained using the BSS model, examining the effects of bioturbation (top panels) and bioirrigation (bottom panels) on DOC concentrations (note the different depth and concentration scales for the two types of DOC). In these calculations it was assumed that there was a 10-cm-thick mixed or burrowed sediment layer, with bioturbation constants or bioirrigation rates in this layer defined in the figure legends. In this upper layer it was also assumed that the value of ^p was 10 times greater than it was in the lower, anoxic sediments (i.e., k^ = 10). All other parameters used in these calculations are defined in the legend to Fig. 4. Also note that the curves defined here as "anoxic" are those shown in Fig. 4.
t
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-
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Sediment Pore Waters
623
concentrations also decrease slightly as a function of Dj/Ds (Fig. 6C), although here DOC concentrations are a stronger function of k^ values (i.e., the curves in Fig. 6C do not converge on one another as Dj/Ds values increase as they do in Fig. 6A for increasing a values). This can also be seen in comparing Figs. 6B and 6D, where much "steeper" curves are seen for the bioturbated (Dj/Ds > 1) sediments in Fig. 6D versus the bioirrigated (a > 0 year~^) sediments in Fig. 6B. At the same time, though, while changes in a, Dj/Ds or kj; have similar effects on DOC pore-water concentrations in the surface mixed or burrowed layer, their effects on benthic DOC fluxes are quite different. As expected, increasing bioturbation or bioirrigation (at a constant kr value) leads to increases in the benthic DOC flux (Table I) in spite of observed decreases in the DOC pore-water gradient at the sediment-water interface (e.g., see Fig. 5). In contrast, enhanced DOC oxidation in mixed redox sediments (i.e., increasing k^ at fixed a or Dj/Ds values) decreases benthic DOC fluxes as a result of more effective utilization of DOC produced in situ during sediment remineralization. However, in this discussion I have assumed that both k^ and either a or Dj/Ds are affected by the occurrence of bioturbation or bioirrigation (the former as a result of associated changes in sediment redox conditions). Therefore, for a fixed input of reactive carbon to sediments (i.e., constant RQ and Roo values) these two opposing phenomena partially cancel one another out and lead to a slight enhancement in the benthic DOC flux as a result of their combined effects (Table I). In its present format, this model does not incorporate the effects of bioturbation or bioirrigation on the depth-dependence of HMW DOM production due to, e.g., mixing of reactive particulate matter deeper into the sediments (e.g., Aller, 1982; Smith et al, 1993; Hammond et al, 1996). Although such processes are likely to have additional effects on sediment DOC profiles, the results shown here indicate some of the ways that macrofaunal transport processes such as bioturbation or bioirrigation and accompanying changes in sediment redox conditions affect sediment DOC concentrations, cycling, and benthic fluxes.
C. CONTROLS ON DOC CONCENTRATIONS WITH DEPTH IN SuRFiciAL ( " S H A L L O W " ) S E D I M E N T S
DOC (and DON) accumulate with depth in sediment pore waters due to a slight imbalance between production and consumption (Burdige and Gardner, 1998;
Figure 6 Sensitivity plots examining average model-derived DOC concentrations in the upper 10 cm of sediment as a function of a (A), k^ (B and D), and D j / A (C). Note that kx = \,a =0 year~^ and Z>r/Ds = 1 define conditions in completely anoxic sediments (i.e., Fig. 4). All other parameters used in these calculations are defined in the captions to Figs. 4 and 5.
624
David J. Burdige Table I The Effects of Bioturbation, Bioirrigation, and Redox-Associated Changes in Sediment DOC Cycling on Model-Derived Benthic DOC Fluxes^ Benthic DOC flux^ ^r
a(year ^)
I>T/DS
mmol/m^/day
%of' "Anoxic''flux'^
HMW DOC flux'^ (% of DOC flux)
Bioturbation 1 1 10 25
0 0 0 0
1 3 3 3
4.28 6.22 5.27 4.86
100 146 123 114
60 67 79 86
Bioirrigation 1 1 10 25
0 60 60 60
1 1 1 1
4.28 6.49 5.83 5.06
100 152 136 118
60 58 65 75
^ All other parameters used in these model calculations are listed in the caption to Fig. 4. ^Benthic DOC fluxes were determined from the sum of the diffusive/bioturbation flux and the bioirrigation flux. Each of these fluxes was calculated individually for the HMW DOC and pLMW DOC fractions and then summed to yield the total DOCfluxesshown here. Diffusive/bioturbation benthic fluxes were determined using the equation -0Z>r(dC/dj:);c=oThe gradient at the sediment-water interface ([dC/djc];c=o) was estimated as AC/Ax using numerical results obtained with the BBS model. Here AC is the difference between the concentration in the overlying waters and at the first model grid point (at x = 0.05 cm), and AJC is therefore 0.05 cm. The bioirrigation flux was determined using the equation -/a(C-Co) dx (Boudreau, 1997). This integration was performed numerically (using trapezoidal approximations) over the depth of burrowed sediment using the results of the BBS model. ^Benthicfluxesof HMW DOC were calculated as discussed above for total DOC using calculated HMW DOC pore water profiles. They are reported here as a percentage of the benthic flux of total DOC shown in the fourth column. ^''Anoxic'' sediments are nonbioturbated and nonbioirrigated sediments (i.e., kr = 1, a = 0 year"^ Dj/Ds = 1). The results for anoxic sediments are shown in the first row of each section in this table. Alperin et aL, 1999). In surficial anoxic sediments these profiles generally approach asymptotic concentrations with depth (Fig. 1; again note that here surficial is defined as being less than ^ 1 m and is often on the order of the upper ~20-30 cm of sediment). This accumulation occurs predominantly in the form of refractory pLMW DOM (see Fig. 4), since both HMW DOM and mLMW DOM represent reactive DOM pools that turn over rapidly. As shown in Fig. 7 there is a positive relationship between maximum pore-water DOC concentrations ([DOC]oo) in anoxic surficial sediments and depth-integrated sediment carbon oxidation rates (Cox). Bioturbated/bioirrigated sediments do not appear to fall on the trend line for
Sediment Pore Waters
625
[m ( D)Calif. Borderland 10 \F T ( V ) Central Calif, margin [ [ L
u
1 SB
O mid-Atl shelf/slope break O Ches. Bay sta. S3 # Ches. Bay sta. M3 A ( A ) Other sites
•^
CLB
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anoxic sediments
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bioturbated/bioirrigated sediments
10
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Sediment Carbon Oxidation Rate (mmol m" d" ) Figure 7 The maximum DOC concentration in the upper ~20-30 cm of sediment versus the depthintegrated sediment carbon oxidation rate. Open symbols represent bioturbated/bioirrigated sediments while closed symbols represent more strict anoxic sediments. The two lines "through" these data sets are not meant to imply any functional relationships, but are simply presented here to show the different general trends in the data sets. Data sources: Chesapeake Bay sites M3 and S3—Burdige and Homstead (1994), Burdige and Zheng (1998), and Burdige (2001); California Borderlands and central California margin sites—Berelson et al. (1996) and Burdige et al (1999, unpubHshed data); midAtlantic-shelf/slope break (site WC4)—Burdige et al. (1996, 2000, unpublished data); Cape Lookout Bight, NC (CLB)—Martens et al. (1992) and Alperin et al. (1994); Skan Bay (SB), Alaska—Alperin et al. (1992); station N (see Fig. 2)—Bauer et al. (1995).
anoxic sediments, consistent with the discussion in the previous section regarding the role of macrofaunal processes in affecting pore-water DOC concentrations. At least two possibilities may explain these observation in anoxic sediments. The first is that a balance occurs at depth between DOC production (from sediment POM) and DOC consumption (Alperin et al, 1994; Burdige and Gardner, 1998). This explanation is implicitly incorporated into the ANS model since in Eq. [A-2] the concentration of pLMW DOC at depth (which is essentially [DOC]oo) equals the parameter Qs (= aR^/kp). Based on the model in Fig. 3 Qs is the steady-state concentration of pLMW DOC at depth that is achieved when consumption and production are balanced. If a and kp are roughly constant in these sediments (see Section II.D for further details), then Q^ is proportional to Roo and the observations in Fig. 7 are consistent with this explanation if /?oois positively correlated with Cox (which does not appear to be an unreasonable assumption). Interestingly, Alperin et al. (1999) used a very different modeling approach to examine sediment DOC
626
David]. Burdige
cycling and obtained the following proportionality: [DOCloc oc CoxZ*,
[3]
where z*is the ^-folding depth for sediment organic matter remineralization. Assuming that z* is roughly constant in all of these sediments this equation is also consistent with the observations in Fig. 7. A second explanation for asymptotic DOC concentrations with depth is that DOC production rates go to zero with depth and biotic or abiotic changes in the composition of the refractory pore water DOC pool (^pLMW DOC) continually decreases its reactivity. This would eventually lead to a situation in which pore water DOC found at depth is effectively nonreactive on early diagenetic time scales and is therefore selectively preserved. In this case, one might think of this DOC at depth much like one thinks of "inert" inorganic nutrient end products such as phosphate, ammonium, or X!C^2, which also show similar exponential-like profiles in anoxic sediments (e.g., Bemer, 1980). This analogy would predict that greater amounts of DOC accumulate with depth in sediment pore waters as rates of sediment carbon oxidation increase (e.g., Krom and Westrich, 1981), as is seen in Fig. 7. Additional insights into this possible explanation will be discussed in the next section. Finally, recent studies have shown that sorption of DOC to sediment particles can affect pore-water DOC concentrations (Hedges and Keil, 1995; Henrichs, 1995), and that pore water DOC concentrations may be "buffered" by reversibly sorbed DOC in equilibrium with the pore waters (Thimsen and Keil, 1998). While it is not inmiediately apparent how these processes could explain the results in Fig. 7 they could possibly affect DOC concentrations at depth depending on the intrinsic reactivity of pore water DOC and that which is adsorbed to sediment particles (Lee, 1994; Mayer, 1994b; Henrichs, 1995), the relative sizes of the pore water and sorbed DOC pools (Thimsen and Keil, 1998), and the extent to which sorption sites on particles deposited in a marine sediment are "saturated" by DOC-particle interactions in the water colunm. However, Alperin et al. (1999) recently concluded that the buffering of pore-water DOC concentrations by reversible sorption is not an important controlling factor in explaining pore-water DOC concentrations in these North Carolina continental slope sediments (see Section VI for further details).
D. PORE WATER DOC PROFILES IN DEEP SEDIMENT CORES In contrast to the numerous DOC profiles that have been collected in "shallow" surficial sediments (see Section I.A), far fewer studies have examined porewater DOC concentrations over larger depth and time scales (Starikova, 1970; Nissenbaum et al, 1972; MichaeHs et al, 1982; Chen et al, 1993; Alperin et al.
627
Sediment Pore Waters DOC (mM) 0
1
2
DOC (mM)
DOC (mM) 3
2
4
4
6
8
12
1
^
1 • x
1 L
•
I fit to entire data set
sta. M3, Chsapeake Bay (CH XVII, 8/96)
sta. C, North Carolina continental slope
\*
• •
!
•
fit to upper 115m
1 | •
ODP site 1082, Walvis Basin
Figure 8 Pore-water DOC concentrations versus depth from three contrasting anoxic marine sediments fit to Eq. [4]. The resulting best fit parameters are Hsted in Table II, along with the references to the sources of the data used in these calculations. Note the factor of 4 difference in concentration scales and factor of > 1000 difference in depth scales as one moves from the estuarine Chesapeake Bay sediments to the deep sediment (ODP) cores collected in Walvis Basin. The different symbols for the Chesapeake Bay plot (left) represent replicate cores collected on this date at this site. At site C on the North Carolina continental slope (middle) the data were fit to Eq. [4] starting at a sediment depth of 25 cm based on the observation that the upper portion of these sediments are extensively bioturbated (AlpQTinetaL, 1999). Therefore the term yx inEq. [4] was replaced here with y(x-25) and CQ (at 25 cm) was used as an adjustable fitting parameter. The resulting best value of Co was 1.42 mM versus the measured value of 1.50 mM. Finally, for the Walvis Basin sediments (right) both the entire data set and the upper 115 m of sediment were both fit to Eq. [4]. Although there are factor of ~2 differences in each of the resulting fitting parameters (see Table II), both sets of results are consistent with the general trends discussed in the text regarding the comparison of the fitting parameters from all three sediments.
1999). Interestingly, however, when such profiles are compared with results from shallow sediments (Fig. 8), one observes a general similarity in the exponentiallike shape of the profiles, in spite of significant differences in both the depth and concentration scales for the profiles. Examining these observations in the context of the proportionality between [DOCJooand Cox in Eq. [3] leads to the conclusion that the increasing depth scale over which organic matter remineralization occurs in these sediments (e.g., z*) likely plays a major role in explaining these observations. This point is further reinforced by the fact that at least between site M3 in Chesapeake Bay and site C on the North Carolina continental slope Cox values decrease (~20 vs ~5 mmol m~^ day~^) as [DOC]oo values increase (Fig. 8); Burdige and Zheng, 1998; Alperin et al, 1999). The results from these cores can be used to further examine suggestions posed in the previous section regarding the controls on pore-water DOC concentrations with depth. To do this I initially attempted to "fit" the data from these different
628
David J. Burdige
cores to Eq. [A-2]. However, taking this approach led to the observation that the fit of these data to this equation was insensitive to several of the model fitting parameters (e.g., R^, A, and A:H). In part this occurs because all but one of the exponential terms in Eq. [A-2] decay rapidly with depth, and therefore their actual values have a minimal impact on the overall fit of the data to this equation (see Burdige and Martens, 1990, for a discussion of a similar problem encountered in fitting dissolved free amino acid pore water profiles to an analogous equation). I am currently working to more tightly constrain the parameters in the ANS model with other measured quantities that define sediment carbon remineralization, and therefore limit the number of adjustable, fitting parameters in the model (e.g., see similar discussions in Alperin et al, 1999). Given these observations, Eq. [A-2] can be rewritten by simply removing these terms, yielding [DOC] = (Co - 25)^"^" + 25,
[4]
and since the parameters a and R^o cannot be separated from one another in the equation for Qs (Eq. [A-8]), Eq. [4] actually has only two fitting parameters (A:p [in Eq. [A-9] for y], and the combined parameter aRoo), assuming Co can be fixed with the bottom water value. Equation [4] is very similar to an analogous equation derived by Alperin et al. (1999), although here by explicitly defining the kinetics of sediment DOC production and consumption I am also able to estimate the rate constant for total DOC consumption, which is also essentially the rate constant for the consumption of pLMW DOC. The results of fitting the data from these three sites to Eq. [4] are shown in Fig. 8, where it can be seen that this modified equation does a reasonably good job of fitting data from these very different marine sediments. The resulting rate parameters from these fitting efforts are listed in Table II. As a first observation, I note that the k^ value for Chesapeake Bay sediments is ^ 2 to more than 3000 times smaller than analogous first-order rate constants for the decomposition of monomeric dissolved organic compounds such as acetate or individual amino acids (see Henrichs, 1993, for a summary of these results). This observation is consistent with previous discussions that the bulk of the porewater DOC pool (^pLMW DOC) represents relatively refractory material that turns over much more slowly than components of the mLMW DOC pool. At the same time, the Chesapeake Bay rate constant is of the same order of magnitude as those determined in degradation studies in Alaska coastal sediments of synthetic glutamic acid and alanine melanoidins (0.2-0.7 and <0.09 yr~\ respectively; Henrichs and Doyle, 1986). Since melanoidins have been discussed in the literature as models for refractory marine humic materials (Nissenbaum et al, 1972; Krom and Sholkovitz, 1977; Hedges, 1988) this observation is not surprising. Perhaps more interesting, however, is the six-order-of-magnitude decrease in k^ values as one moves from surficial Chesapeake Bay sediments to deep Walvis
629
Sediment Pore Waters Table II
Best Fit Rate Parameters for DOC Cycling in Contrasting Marine Sediments^ Depth interval offit
POC range {%f
kp (year-^)
aRpo (mM/year)
0-25 cm
4-8 to 3 ^
6.4 ± 2 . 1
1.3 ± 0 . 4
North Carolina continental slope (site C)^
25-225 cm
3 to 2-2.5
1.7 ± 0.7 x 10"^
1.1 ± 0.3 x 10"^
Southwest African Margin (Walvis Basin, site 1082/
1.5-115 m 1.5-370 m
3-6 to 3 ^ 3-6 to 1-3
5.2 ± 1.9 x 10"^ 14 ± 5 x lO'^
4.6 ± 1.2 x 10"^ 9.3 ± 2.9 x 10"^
Site Chesapeake Bay (site M3)^
^See Fig. 8 for the best-fit profiles. ^Surface POC value and value at depth. '^Core collected 8/96. Data from Burdige and Zheng (1998). "DOC data and other model input parameters from Alperin et al. (1999). ^DOC data from Burdige et al. (unpublished data), other model input parameters from Wefer etal.(199S).
Basin sediments. To further examine the significance of this observation I first note that there is a similar large decrease in the parameter a/^oo in these sediments. This decrease is almost certainly due to a decrease in the overall reactivity of the source POM since sulfate reduction dominates organic matter remineralization at all three sites, the amounts of sediment POM at all three sites are comparable (Table II), and it is unlikely that the parameter a undergoes a multiple-order-of-magnitude decrease in its size. This decrease in POM reactivity is not surprising in the context of models for sediment POM remineralization such as the multi-G model or power model (Westrich and Bemer, 1984; Middelburg, 1989), since remineralization of sediment POM continually fractionates this material by preferentially using the most reactive material that is available and continually decreasing the overall reactivity of the remaining material (also see Burdige, 1991a). At first glance then, the observations in Table II might be interpreted as implying that the remineralization of increasingly refractory sediment POM leads to the net production of increasingly refractory pore-water DOC. While this is certainly a possibility, I suggest that these results can equally be interpreted using the scheme shown in Fig. 9. In this explanation I have assumed that within a given time window the bulk of the pLMW DOC produced is ultimately remineralized (i.e., production ^ consumption as discussed above), although a small amount also undergoes internal transformations that lead to a decrease in its reactivity. In part for ease of explanation, I show this as a series of three pLMW DOC pools of decreasing reactivity that are produced from one another (recognizing at the same time that this model and other DOC and POC models that attempt to "quantize"
630
David J. Burdige Pathways ofpLMW-DOC remineralization
^
I
• • • • • • • • • I 'TifmeH^ifOH'S^HHHiHHJI "Time Window 1" • • • • • I Time WinOow r
P O C WB^
HMW-DOCI
"1
pLMW-DOC, m ^
'•"'kp'.'
pLMW-DOC, — ^
I
pLMW-DOCj
\~\^
\"K.
mLMW-DOC
• p Increasing Time, Increasing [pLMW-DOCj] — and Decreasing pLMW-DOMj reactivity (l^i)
Figure 9 A reexamination of the model shown in Fig. 3 in which the reactivity of the pLMW DOM pool is viewed in terms of different subcomponents with decreasing reactivities. In any given time window the majority of the pLMW DOM can be thought of as accumulating in only one of these pools, with pLMW DOM loss then occurring predominantly from remineralization of matrial in this pool. As a result, the k^ value for this pool defines the apparent rate constant for the entire pLMW DOM pool in this time window. At the same time, it is proposed here that during remineralization a small amount of the pLMW DOM in a given pool undergoes internal transformations that decrease its reactivity. Therefore, the overall reactivity of the pLMW DOM pool decreases with time.
or compartmentalize the continuum of these materials and their reactivities are almost certainly oversimplifications). In this formalism then, we would think of pLMW DOC reminerahzation in Chesapeake Bay sediments occurring almost exclusively from this first pool, since reactions transforming pLMW DOCi to pLMW DOC2 would be too slow to be observed to any appreciable extent within the time scale of biogeochemical processes in these estuarine sediments. At the other extreme, in the deep Walvis Basin sediments the remineralization of the more "reactive" pLMW DOCi and pLMW DOC2 would be fast in comparison to the overall time scale of diagenetic processes in these sediments. Therefore, pLMW DOC would accumulate here in the pLMW DOC3 pool. Furthermore, as discussed above (also see Eq. [3]) the significantly longer time scales over which processes in Walvis Basin sediment occur would also lead to the accumulation of higher concentrations of this more refractory DOC. In some sense this observation is analogous to those made by other workers about sediment POC dynamics, namely that the POC degradation rates one observes are strongly dependent on the observational time scales (e.g., Emerson and Hedges, 1988; Middelburg, 1989). In summary, this explanation supports the general observation that a balance between production and consumption roughly controls DOC concentrations at depth. However, it also suggests that a second but equally important aspect of sediment DOC cycling is that with time there are also changes in the pLMW DOC pool (e.g., in its composition and/or structure) that lead to an overall decrease in its
Sediment Pore Waters
631
bulk reactivity. This latter process allows this material to continually accumulate with depth on long (geological) time scales, and may play a role in overall sediment carbon preservation.
III. DISSOLVED ORGANIC NITROGEN (DON) Much of what has been said about DOC in sediment pore waters applies equally well to pore-water DON, in that DON is also a heterogeneous class of organic compounds that range from well-defined biochemicals such as urea or amino acids, to larger dissolved proteins and peptides to more complex (and poorly characterized) N-containing humic and fulvic acids (e.g., Walsh, 1989; Antia et al, 1991; Bronk, Chapter 5). Nitrogen found in DOM can have several types of functionality, although in the water column much of this functionality appears to be in the amide form (-NH2; McCarthy et al, 1997). This issue has not yet been examined in sediment pore waters. In contrast, a much higher proportion of heterocyclic nitrogen functionality (i.e., nitrogen in aromatic rings such as five-member pyrrole-like or six-member pyridine-like structures) has been observed in sediment organic matter (Patience et al, 1992). The occurrence of this material may be due to either selective utilization of amino nitrogen compounds (i.e., selective preservation of heterocyclic nitrogen compounds) or the occurrence of in situ rearrangement (i.e., condensation) reactions that produce new heterocyclic "compounds" from amino-nitrogen compounds. Patience et al. (1992) suggest that the latter suggestion is more likely, based on mass balance considerations, although this issue remains unresolved. The fact that recent sediments contain levels of heterocyclic nitrogen that are comparable to amino nitrogen (Patience et al, 1992) implies that if such rearrangement reactions do occur then they may begin during the early diagenesis of sedimentary organic matter. Based on arguments presented here, this could occur through DON intermediates, although this problem has not been extensively studied (e.g., see discussions in Rubinsztain et al, 1984). The simultaneous determination of DOC and DON in pore waters allows one to examine the C/N ratio of pore-water DOM (= C/NpDOM). gaining further insights into the composition and reactivity of pore-water DOM. Pore-water profiles of DON and C/NpDOMfrom selected marine sediments are shown in Fig. 10, and Table III contains a more detailed sunmiary of C/NpooMvalues and depth trends from a wide range of marine sediments. At least four general conclusions can be made from these observations. Although not directly shown here, the first of these is that when C/NpDOM values in estuarine Chesapeake Bay sediments are compared with the C/N ratio of DOM benthic fluxes, we observe that DOM accumulating in sediment pore waters is depleted in nitrogen compared to that which escapes the sediments as a benthic
DON (|iM) 0
0 I—r-
20
C/N,pDOM
40
60
5
10
15
20
15
20
10
15
20
10
15
20
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20
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20
40
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5
Patton Escarpment
Sediment Pore Waters
633
flux (Burdige and Zheng, 1998; Burdige, 2001). This observation will be discussed in further detail in section V.C. A second observation is that in sediments where there is a significant input of terrestrial organic matter, C/NpDOM values tend to be higher (e.g., site N3 in the Chesapeake Bay and ODP core 1075 from the Southwest African Margin). Such observations are consistent with the fact that terrestrially derived organic matter is generally depleted in nitrogen as compared to marine organic matter (C/N values of ~20-80 vs - 6 - 8 ; e.g., Emerson and Hedges, 1988; Meyers, 1997). A third observation is that in oxic or mixed redox sediments C/NpDOM values tend to be relatively low as compared to more strict anoxic sediments. This can be seen at site S3 in the Chesapeake Bay, in the Patton Escarpment sediments, and in oxic, pelagic sediments in the southwest Pacific. In past work we suggested that this may occur as a result of benthic macrofaunal processes that produce specific low C/N ratio organic compounds. Urea (C/N = 0.5) is one such compound (Lomstein et al, 1989; Burdige and Zheng, 1998), although at site S3 in Chesapeake Bay our recent results suggest that urea is not a significant component of the DOM pool in these sediment pore waters (Burdige, 2001). In addition to macrofaunal sources of low C/N ratio pore-water DOM compounds, another possibility is bacterial sources. Bacteria have C/N ratios that range from ~ 3 to 5 (Saunders et al, 1983; Fenchel et al, 1998) and grazing of bacteria by higher organisms (Kemp, 1990; Lee, 1992) could lead to the production of DOM with a low C/N ratio in either oxic or mixed redox sediments. The absence of such bacterial grazing in anoxic sediments would then preclude the production of low C/N ratio bacterial DOM. Much of this low C/N ratio material is likely amino acids (see discussions in Burdige, 2001), although evidence for this in pore water amino acid data from strictly anoxic versus bioturbated/bioirrigated sediments is equivocal at best (see Section IV.B for further details). The final observation based on the results in Table III is that in most of the continental margin sediments examined to date, C/NpDOMvalues increase with depth (also see the San Clemente Basin profiles in Fig. 10). Since there is evidence for the occurrence of terrestrially derived organic matter in these sediments (Steinberg
Figure 10 Pore-water DON concentrations (left) and C/NpooM (right), both versus depth in marine sediments. Symbols on the upper x-axes represent concentrations in bottom-water samples obtained by hydrocasts. (First row) Cores collected at site S3 in the southern Chespapeake Bay in 10/96 ( • ) and 8/97 ( • ) . Data from Burdige and Zheng (1998) and Burdige (2001). (Second row) Cores collected at site M3 in the mesohaline Chespapeake Bay in 7/95 ( • ) and 10/95 ( • ) . Data from Burdige and Zheng (1998). (Third row) Replicate cores collected in San Clemente Basin in 3/94 (Burdige et al, unpublished data). (Fourth row) Replicate cores collected at the Patton Escarpments in 3/94 (Burdige et al, unpublished data). See Burdige et al (1999), McManus et al (1997), and Shaw et al (1990) for general information on the geochemistry of the San Clemente Basin and Patton Escarpment sediments. Note that DOC data from these Chesapeake Bay site M3 cores are shown in Fig. 1, and those from the site S3 cores are shown in Fig. 2.
Table III C/NpDOM Values in Marine Sediments
Site
Maximum sediment depth
Coastal, estuarine sediments Chesapeake Bay 30 cm site MS*^
C/NpDOM
C/NpDOM
(range)
(depth variations)
-12-18
Depth variations less important than seasonal variations (that are out of phase with temperature and sediment remineralization rates) No coherent depth trends
Chesapeake Bay site SS"
30 cm
-8-14
Chesapeake Bay site N^"
30 cm
-10-30
Increase with depth
5 cm
-10-20
20-21 (upper 1 cm), constant below this depth ( = - 1 0 - 1 1 )
Danish coastal sediments^
Continental margin and deep sea sediments Mid-Atlantic shelf/ 30 cm -7-17 slope break (400-750 m water depths)^
Santa Monica Basin (California Borderlands; 900 m water depth)^ San Clemente Basin (California Borderlands; ~2000 m water depth)'^
Increase with depth in most cores
30 cm
-7-18
Increase with depth (7-12 near sediment surface, 7-18 at depth)
30 cm
-7-17
Increase with depth (7-10 near sediment surface, —17 at depth)
Sediment characteristics Anoxic, nonbioturbated; sulfate reduction and methanogenesis dominate organic matter remineralization
Mixed redox conditions; sediments are bioturbated and bioirrigated Sediment organic matter largely terrestrially derived; some bioturbation in upper —5 cm of sediment Shallow water depth (4 m); upper —10 cm of sediment bioturbated Suboxic sediments with minimal bioturbation in the upper 20-30 cm of sediments; nitrate goes to zero in the upper 1-4 cm of sediment; linear sulfate gradients in the upper 25 cm of sediment Anoxic, sulfidic sediments with no bioturbation or bioirrigation
Suboxic sediments; pore water O2 depleted in the upper 1 cm of sediment, nitrate depleted by —2-5 cm sediment depth (Continues)
635
Sediment Pore Waters Table III (Continued)
Site
Maximum sediment depth
C/NpDOM
C/NpDOM
(range)
(depth variations)
Patton Escarpment (eastern North Pacific; ~3700 m water depth)'^
30 cm
-5-15
Minimum value observed—1-2 cm below the sediment surface; increase with depth below
Hatteras continental rise (northwest Atlantic; ~4200 m water depth)^
30 cm
-6-11
No obvious depth trends
-2-7
No obvious depth trends
Southwest Pacific pelagic sediments (~2800-5400 m water depths)^
30-50 cm
"Deep" (ODP) sediment cores (southwest African Margin)^ Lower Congo Basin 60 m 20 ± 7 No consistent depth (core 1075; trends ~3000m water depth)
Walvis Basin (core 1082;-1300 m water depth)
360 m
11.3 ± 3 . 2 No consistent depth trends
Sediment characteristics Pore water O2 depleted at a sediment depth of —2.5 cm, nitrate depleted by —4-10 cm sediment depth; some sediment bioturbation and bioirrigation Suboxic sediments; nitrate depleted by —8 cm sediment depth after an initial increase in the upper 1-2 cm of sediment Oxic sediments; nitrate increases with depth in an exponential-like fashion
Anoxic sediments; sulfate goes to zero by —30 m sediment depth; marine and terrestrial organic matter sources Anoxic sediments; sulfate goes to zero by —20 m sediment depth; predominant marine organic matter sources
^ Data from Burdige and Zheng (1998) and Burdige (2001). ^Data from Lomsteki et al. (1998). '^Data from Burdige and Gardner (1998) and Burdige et al (2000, unpublished data). ^DOC and DON data from Burdige et al. (1999, unpublished data). Other data from Shaw et al. (1990), Berelson et al. (1996), and W. Berelson (pers. commun). ^Data from Heggie et al. (1987). /Data from Suess et al. (1980). ^DOC and DON data from Burdige et al. (unpublished data). Other data from Wefer et al. (1998).
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David J. Burdige
et al, 1987; Eganhouse and Venkatesan, 1993; Harvey, 1994) one explanation of these C/NpDOM values is that the increased remineralization of terrestrially derived POM becomes increasingly important with depth, leading to the production of DOM with an increasing C/N ratio. Implicit in this assumption (from the standpoint of any of the sediment organic matter remineralization models discussed above) is that N-depleted, terrestrially derived organic matter deposited in these sediments is less reactive than marine-derived POM (e.g., see discussions in Burdige, 1991a). At the same time, decomposition studies with Chesapeake Bay sediments suggest that there is terrestrially derived POM that undergoes remineralization with depth (Burdige, 1991a), yet similar trends in C/NpooMvalues are not observed in these estuarine sediments (Burdige and Zheng, 1998). The reasons for these differences are not well understood, although as discussed in Burdige and Zheng (1998), they suggest that there may not be a tight coupling between the C/N ratio of the sediment organic matter undergoing remineralization and that of its DOM intermediates (or its refractory "end products," e.g., pLMW DOM). Kristensen and Blackburn (1987) observed that the C/N ratio of sediment organic matter undergoing remineralization is not always a good indicator of its reactivity, a fact that could also explain these differences.
IV. DOM COMPOSITIONAL DATA Much of the biologically produced organic matter can (at least operationally) be categorized as carbohydrates, proteins (amino acids), and lipids. In the water column, however, such an approach accounts for less than 15% of the measured DOC (e.g., Williams and Druffel, 1988; Bauer et ai, 1992; Benner, Chapter 3). Much of the DOC in pore waters too is uncharacterized at the molecular or even compound-class level (e.g., total carbohydrates, lipids, etc.; see Burdige, 2001, for further details). Recently, Lomstein et al. (1998) were able to quantify ^40% of the DON in Danish coastal sediment pore waters as dissolved free and combined amino acids, although the details about what these combined amino acids actually represent is still uncertain (see Section IV.B for further details). In 1981, Krom and Westrich observed that "few attempts have been made to identify individual biochemically important compounds in marine pore waters." Here, much has clearly changed in the past 20 years. Looking at these studies characterizing pore-water DOM in the context of the PWSR model, I note that most efforts have focused on examining concentrations and cycling of compounds that fall into the mLMW DOM category (see the discussion below and also see Henrichs, 1993, for a sunmiary). While some work has been carried out examining the dynamics of the HMW DOM pool (Mayer, 1989; Mayer and Rice, 1992; Amosti etai, 1994;Boschker^r«/., 1995; Pantoja and Lee, 1999; Amosti, 2000), less work has been carried out examining its chemical composition.
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A. VOLATILE FATTY ACIDS ( V F A S ) Interest in the study of VFAs in marine sediments stems from the observation that acetate and other short-chain VFAs are important in situ substrates for both sulfate reducing and methanogenic bacteria in anoxic sediments (S0rensen et ah, 1981; Sansone and Martens, 1982; King et al, 1983; Christensen, 1984; Parkes et al, 1989; Wellsbury and Parkes, 1995). Rephrasing this in the context of the PWSR model, this suggests that VFAs represent major components of the mLMW DOC pool through which much of the carbon flow ultimately occurs in anoxic sediments (e.g., see Fig. 3). In most anoxic sediments acetate concentrations range from <1 to up to ~100 /xM (Ansbaek and Blackburn, 1980; Barcelona, 1980; Christensen and Blackburn, 1982; Parkes and Taylor, 1983; Shaw et al, 1984; Crill and Martens, 1986;Novelli^ra/., 1988;Michelson^^a/., 1989; Shaw and Mcintosh, 1990; King, 1991; Mines et al, 1994; Wellsbury and Parkes, 1995; Albert and Martens, 1997). These concentrations increase with depth (in the upper 20-30 cm of sediment) in most of these sediments. In many of these studies total DOC concentrations were generally not determined along with acetate, although where both measurements were made (or where DOC values can be obtained from other published studies) I estimate that acetate accounts for ~ 5 % (at most) of the total pore-water DOC and often times less than 1% of the DOC. Concentrations of other VFAs such as formate or propionate have generally not been determined as frequently as acetate, although based on the available literature, concentrations of these other VFAs can be comparable to those of acetate (e.g., Barcelona, 1980; Albert and Martens, 1997). Many of the studies discussed above have also concluded that much of the acetate and other VFAs that can be chemically measured may not be biologically available (see Henrichs, 1993, for a sunmiary of these studies). This observation further reinforces the notion that material in the mLMW DOM pool represents a small fraction of the total sediment pore-water DOM pool whose concentration is held at relatively low levels due to rapid bacterial turnover. There are two interesting sedimentary environments where pore water acetate concentrations do not follow these general trends. The first is in the anoxic sediments of Cape Lookout Bight, NC, in the transition zone between where sulfate reduction and methanogenesis predominate (Sansone and Martens, 1982). Here it is observed that during the warm summer months a distinct subsurface maximum in acetate develops at the sediment depths where sulfate concentrations go to zero. At these depths acetate concentrations are as high as ^ 2 mM and account for -^25% of the total DOC (Crill and Martens, 1986; Alperin et al, 1994; Albert and Martens, 1997). Pooling of acetate in this sediment transition zone appears to occur as seasonal temperatures rise, rates of sulfate reduction increase, and the zero sulfate horizon in the sediments moves upward toward the sediment surface. As a result of these changes, acetate consumption by sulfate-reducing bacteria
638
David]. Burdige
apparently decreases at the base of the sulfate reduction zone, and a lag in the development of a methanogenic population in this portion of the sediments that can consume this acetate leads to this transient subsurface acetate maximum (Alperin et al, 1994). The extent to which this phenomena occurs in other organic-rich, anoxic sediments has not been determined. A second sedimentary environment where significantly elevated acetate concentrations have been observed are deeply buried marine sediments (the so-called deep marine biosphere; Parkes et ai, 1994). In sediments on the Blake Ridge in the Atlantic Ocean, temperatures increase from deep-sea values (~2-3°C) to ~20-30°C within several hundred meters of sediment burial, and this apparently stimulates microbial activity in the sediments and also leads to a significant increase in the reactivity of the sediment organic matter found at depth. These depth changes results in pore-water acetate concentrations increasing with sediment depth below ^300 m, such that by 700 m acetate concentrations are as high as 15 mM (Wellsbury et al, 1997). The significance of this process in terms of the overall dynamics of the deep marine biosphere will require further study.
B. AMINO ACIDS Amino acids represent significant amounts of the carbon and nitrogen that are remineralized in marine sediments (Henrichs and Farrington, 1987; Burdige and Martens, 1988; Cowie and Hedges, 1992b), and pore water dissolved amino acids are likely important intermediates in this process (see references cited below). Amino acids in pore waters have been examined in a wide range of marine sediments including salt marsh, estuarine, and coastal sediments (Gardner and Hanson, 1979; Henrichs and Farrington, 1979; J0rgensen et ai, 1981; Caughey, 1982; Henrichs and Farrington, 1987; Burdige and Martens, 1990; Colombo etal, 1998; Landen and Hall, 1998; Lomstein et ai, 1998) and continental margin and deepsea sediments (Henrichs and Farrington, 1980; Henrichs et ai, 1984; Haberstroh and Karl, 1989; Landen and Hall, 2000). Several of these studies have also examined amino acid adsorption to marine sediments as well as dissolved amino acid turnover rates in sediments (also see Rosenfeld, 1979; Christensen and Blackburn, 1980; Sugai and Henrichs, 1992; Henrichs and Sugai, 1993). In most sediments, concentrations of total dissolved free amino acids (TDFAAs) decrease with sediment depth, with surface pore water concentrations generally ranging from ^20 to 200 /xM and concentrations below 10-20 cm being less than 5-10 /xM. In the few studies where total DOC and DON have been examined along with amino acids, TDFAAs represent 1-13% of the DON and <4% of the DOC (Henrichs and Farrington, 1987; Lomstein etai, 1998; Landen and Hall, 2000). The predominant amino acids in the DFAA pool include glutamic acid, alanine, glycine.
Sediment Pore Waters
639
aspartic acid, and, in some sediments, the nonprotein amino-acid ^-aminoglutaric acid ()S-aga), an isomer of glutamic acid (see the next paragraph for further details). For the protein amino acids the DFAA pool is generally enriched in glutamic acid relative to the sediment hydrolyzable amino acid pool. Other nonprotein amino acids in addition to )S-aga can also be enriched in pore waters relative to the sediments (e.g., )S-alanine). These (and other) compositional differences between pore water and sediment amino acids are likely related to both biological and physical (e.g., adsorption) processes that affect pore water amino acids as they undergo remineralization (see discussions in Henrichs and Farrington, 1987; Burdige and Martens, 1990). The nonprotein amino acid ^-aga was first observed in pore waters by Henrichs and Farrington (1979). In anoxic sediments they noted that the mole percentage of )S-aga generally increases with depth (upper ^30 cm), often becoming the predominant DFAA (>~40 mol %; also see Henrichs and Farrington, 1980,1987; Henrichs et al., 1984; Burdige and Martens, 1990). In contrast, ^S-aga appears to be a much less important component of the pore water DFAA pool in sediments that are described as either "oxic" or, more likely, are bioturbated and/or bioirrigated (Henrichs and Farrington, 1980; Caughey, 1982; Landen and Hall, 1998, 2000). The source(s) of ^^-aga in anoxic sediment pore waters is not well characterized (Henrichs and Cuhel, 1985; Burdige, 1989), although its relative accumulation with depth in these sediments may occur because it is more refractory than other amino acids (Henrichs and Farrington, 1979). The observed differences in relative concentrations of j6-aga in anoxic versus oxic/mixed redox sediments suggests that the proposed refractory nature of )S-aga could also be a function of sediment redox conditions, similar to that which has been observed for other refractory components of pore water DOM (Burdige, 2001). Along the same lines, the observations in Section III suggest that there could be broader compositional differences in the dissolved amino acid pools in anoxic versus oxic/mixed redox sediments that might help explain the low C/NpDOM values in these latter sediments. Focusing on the amino acid glycine (C/N = 2), my examination of the pore water amino acid data in the references cited above suggests that glycine may be preferentially enriched in the pore-water amino-acid pool of mixed redox sediments versus more strict anoxic sediments. Unfortunately, however, given the way some of these data are presented in the literature, this conclusion should be viewed as tentative. Furthermore, glycine is an abundant amino acid in many benthic invertebrates (Awapara, 1962; Henrichs, 1980), and the possibility exists that these elevated glycine levels might simply result from release of this amino acid by benthic organisms during core collection and/or pore water processing (J0rgensen et al, 1981; Burdige and Martens, 1990). Nevertheless, these glycine results appear to be consistent with the C/NpDOM values discussed in Section III and would therefore appear to warrant further examination (also see discussions in Burdige, 2001).
640
David J. Burdige
Finally, another pool of dissolved amino acids that has been given little study is that of dissolved combined amino acids (DCAAs). These represent amino acids that are either found in dissolved peptides/proteins or incorporated into abiotic (humic?) compounds. In the few studies of DCAAs in marine sediment pore waters (Caughey, 1982; Colombo et al, 1998; Lomstein et al, 1998; Pantoja and Lee, 1999); Burdige, unpub. data) concentrations of total DCAAs appear to be ^l.5-A times that of total DFAAs. Given the small data set on pore-water DCAAs it is difficult to determine whether the DCAA pool compositionally looks more like DFAAs or hydrolyzable sediment amino acids. Such information could be important in determining the extent to which the DCAA pool represents dissolved peptides or proteins (i.e., "reactive" high-molecular-weight intermediates of sediment organic matter remineralization) or abiotic condensation products of, e.g., melanoidin-type reactions. In the former case, the DCAA pool might be expected to be more similar to that of sediment amino acids, while in the latter case DCAAs might be expected to look more like DFAAs. At the same time nonprotein amino acids such as )S-alanine and y-aminobutyric acid are often times enriched in the free amino acid pool of many sediment pore waters, and become increasingly important in the sediment organic matter pool as this material becomes increasing diagenetically altered (Whelan, 1977; Cowie and Hedges, 1994; Cowie etal, 1995; Hedges etal, 1999). Thus, information on a possible linkage between the occurrence of these amino acids in different pore water pools (DFAAs vs DCAAs) and their preservation in sediments could be important in understanding carbon preservation in sediments in general.
C. CARBOHYDRATES Carbohydrates represent a significant component of the pools of living and nonliving organic matter in the marine environment. In marine sediments, particulate carbohydrates (PCHOs) account for 10-20% of the total sediment POC, and a similar percentage of the sediment POC undergoing remineralization (see recent discussions in Burdige et al, 2000). Despite the apparent biological lability of carbohydrates, some fraction of the chemically recognizable carbohydrates deposited in marine sediments escape remineralization and are "preserved" on time scales of decades to >1 million years (Cowie and Hedges, 1992a; Martens et al, 1992; Whelan and Emeis, 1992; Cowie et al, 1995; Burdige et al, 2000). Interest in the study of pore-water carbohydrates therefore stems from a desire to better understand their role in carbohydrate remineralization and carbohydrate (and perhaps total carbon) preservation. Total dissolved carbohydrates (DCHOs) have been determined in a limited number of coastal and continental margin sediments, with concentrations that
Sediment Pore Waters
641
generally range from ~10 to 400 /xM C (Lyons et al, 1979; Amosti and Holmer, 1999; Burdige et al, 2000). In most cases DCHO concentrations increase with sediment depth (upper '^20-30 cm) and represent ^10-40% of the total DOC. Higher percentages have been observed just below the sediment-water interface in Cape Lookout Bight, North Carolina, sediments (Amosti and Holmer, 1999) and in some Bermuda carbonate sediments (Lyons et al, 1979). Relative DCHO concentrations generally decrease with sediment depth (again upper ^^20-30 cm), although the magnitude of these decreases vary among the few sites that have been examined to date (see discussions in Burdige et al, 2000, for further details). Concentrations of dissolved carbohydrates in sediment pore waters are uncoupled from particulate (sediment) carbohydrate concentrations, and DCHO concentrations appear to be more strongly controlled by sediment remineralization processes (Burdige et al, 2000). Evidence-to-date also suggests that DCHOs may be preferentially found in the high-molecular-weight (HMW) pore-water DOC pool and therefore likely represent some of the initial HMW intermediates produced and consumed during sediment POC remineralization (Amosti and Holmer, 1999; Burdige ^r a/., 2000). Burdige etal (2000) determined individual aldoses (monomeric neutral sugars) in selected pore-water samples from Chesapeake Bay and mid-Atlantic shelf/slope break sediments. We observed that ~30 to 50% of the DCHOs in these pore waters could be identified as individual aldoses, and that total aldose yields (total individual aldose concentrations as a percentage of DOC) were higher in the continental margin sediment pore waters {^9%) than they were in the estuarine sediment pore waters (<5%). Dissolved glucose was the predominant aldose (28%), with the following order of abundance for the remaining aldoses: xylose (16%); fucose, rhamnose, and galactose (each average value between 12 and 14%); mannose (10%); arabinose (7%). These aldose distributions are different than those observed in the water column (e.g., Skoog and Benner, 1998), consistent with the suggestion that pore-water DCHO concentrations are controlled by sediment remineralization processes.
V. THE ROLE OF BENTHIC DOM FLUXES IN THE OCEAN CARBON AND NITROGEN CYCLES A. BENTHIC DOC FLUXES The fact that concentrations of both DOC and DON in sediment pore waters are elevated over bottom waters implies that sediments could be a potential source of DOM to overlying waters. Prior to the early 1990s the possible occurrence of these processes was discussed in the literature (Emerson and Dymond, 1984; Heggie et al, 1987; Bender et al, 1989), and in these and other works (Williams
642
David J. Burdige
and Druffel, 1987; Mopper et al, 1991; Hedges, 1992) it was suggested that sediments might represent a significant source of DOC to the deep ocean. In these works it was also proposed that benthic DOC fluxes might provide an explanation for the apparent discrepancy between the "old" (^^6000 ybp) ^^C age of deepwater DOC, the average oceanic mixing time (^^1000 years), and other chemical properties of deep-water DOC (i.e., 5^^C and lignin concentrations) that suggest that this material is primarily of marine origin. It was not until recent years that direct measurements of these fluxes were undertaken using either core incubation techniques or in situ benthic landers or chambers (Hall et ai, 1990; Burdige et al, 1992, 1999; Burdige and Homstead, 1994;Hulth^ra/., 1997; Burdige and Zheng, 1998; Alperin^ra/., 1999; Holcombe et ai, 2001). To date, benthic DOC fluxes have been determined in this manner in a number of estuarine, coastal and continental margin sediments, with values that range from ^0.1 to 3 mmol m~^ day"^ Recently, we compiled these results and observed that there was a positive, but nonhnear, relationship between benthic DOC fluxes (BDF) and depth-integrated sediment carbon oxidation rates (Cox) expressed as BDF = 0.36Cox^-^^
[5]
(BDF and Cox both expressed here as nmiol m"^ day~^; Burdige et al, 1999). The relationship between BDF and Cox impUes that the ratio of BDF to Cox decreases with increasing Cox (also see Table IV). With these results we were able to estimate the global significance of benthic DOC fluxes in oceanic and sediment carbon cycUng (Table IV). This calculation suggests that the integrated DOC flux from coastal and continental margin sediments (0-2000 m water depth) is ^^190 Tg C year"^ This quantity is larger than (though of roughly similar magnitude) a similar estimate by Alperin et al. (1999), who used a subset of the data we used and also assumed that benthic DOC fluxes were a constant fraction (1.6 ih 0.2%) of sediment carbon oxidation rates. Their approach yields an integrated DOC flux of ^^40 Tg C year~^ from this same portion of all marine sediments. The implications of our results are several-fold. First, it can be seen that DOC fluxes from coastal and margin sediments are generally less than ^10% of sediment carbon oxidation rates. Thus, sediments appear to be quite efficient in retaining (oxidizing) DOM produced during remineralization processes, consistent with past discussions here. Similar trends also appear to be the case for sediment DON cycling (see next section) and both observations imply that net sediment DOM production is small in comparison to gross sediment DOM production. This occurs because under steady-state conditions the former (net DOM production) is balanced by, or equals, the benthic DOM flux (e.g., see general discussions in Bemer, 1980), and the latter (gross DOM production) is approximately equal to gross DOM consumption or inorganic nutrient production (which results in
643
Sediment Pore Waters Table IV Benthic DOC Fluxes from Coastal and Continental Margin Sediments"
Sediment regime^
Benthic DOC flux Sediment carbon oxidation (Cox) Integraiea^ Average^ Integrated*^ Average*^ (Tg C/year) (mmol/m'^/day) (mmol/m^/day) Tg C/year %ofCox^
"Coastal" Sediments (0-200 m; 9%)
1630 (52%)
14.7
0.91
88 ± 3 0
5.4
"Margin" Sediments (200-2,000 m; 7%)
940 (30%)
6.6
0.65
89 ± 2 5
9.5
177 ± 56
6.9
Coastal plus Margin Sediments (0-2000 m)
2570 (82%)
Note. Note that Tg C/year = 10^^ g C/year. ^ Adapted from Burdige et al (1999). ^The percentage of all marine sediments found in each sediment regime is listed in parentheses. ^ Taken from Midddelburg et al (1997), who estimated globally integrated rates of sediment processes in these regimes using an extensive database of published rates of sediment biogeochemical processes. Listed in parentheses in this column is the integrated Cox in each region as a percentage of the integrated Cox for all marine sediments (= 3130 Tg C/year). ^Obtained by dividing the integrated Cox in each region by the sediment surface area in the region. ^Obtained using the average Cox in each region and Eq. [5] in the text. ^Obtained by multiplying the average benthic DOC flux in each region by the sediment surface area in the region. ^The average benthic DOC flux as a percentage of the average Cox in each sediment regime.
inorganic nutrient benthic fluxes). These trends are consistent with discussions in Section LA regarding carbon and nitrogen flow through DOM intermediates during sediment POM remineralization and the role of DOM as an intermediate in the remineralization process. A second implication of the results in Table IV is that the integrated benthic DOC flux reported here is comparable to estimates of the organic carbon burial rate in all marine sediments (~160 Tg C year"^; Hedges and Keil, 1995) and the riverine DOC input (200 Tg C year"^ Meybeck, 1982). Thus, as has been noted previously (Burdige et al, 1992; Burdige and Homstead, 1994) marine sediments may be an important net source of DOC to the oceans. However, the actual impact these fluxes have on the oceanic carbon cycle ultimately depends on the extent to which sediment-derived DOM is reactive or refractory in the water column. This point will be discussed in greater detail in Section V.C. Finally, Burdige et al. (1999) noted that there might be additional significance to the fact that integrated benthic DOC fluxes and sediment carbon burial rates
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David J. Burdige
are of comparable magnitude. Since pore-water DOC cycling may play a role in sediment carbon preservation (see Section VI), these observations suggest a linkage between benthic DOCfluxesand sediment carbon preservation "mediated" by pore water DOC concentrations and cycling. Changes in the factors controlling benthic DOC fluxes (and/or the cycling of DOC in sediments) may then affect or control sediment carbon preservation (also see similar discussions in Hedges and Keil, 1995; Henrichs, 1995). The exact details of the relationship between benthic DOC fluxes and sediment carbon preservation await further studies.
B. BENTHIC DON FLUXES Interest in benthic DON fluxes and their role in the marine nitrogen cycle is similar to that discussed above for benthic DOC fluxes and the marine carbon cycle. However, because nitrogen can be a limiting nutrient in marine ecosystems (Carpenter and Capone, 1983), and because marine phytoplankton can use DON as their nitrogen source (Jackson and Williams, 1985; Antia et al, 1991; Bronk, Chapter 5), there has additional interest in understanding the role of sediments as a source of DON to the water column. Several studies have examined benthic DON fluxes from coastal and estuarine sediments (Hartwig, 1976; Nixon et ai, 1976; Boynton et ai, 1980; Nixon, 1981; Nixon and Pilson, 1983; Hopkinson, 1987; Teague et al, 1988; Doflar et aL, 1991; Enoksson, 1993; Cowan and Boynton, 1996; Burdige and Zheng, 1998), and two studies have also examined these fluxes from high-latitude continental margin sediments (Blackburn et ai, 1996; LandenHillmeyr, 1998). Benthic DON fluxes show quite a tremendous range both in absolute magnitude and direction (into and out of the sediments). However, at estuarine or coastal sites where repeated (or seasonal) studies have been carried out, mean or annual averages generally suggest that these fluxes are small, usually out of the sediments, and only a small percentage of the benthic DIN flux (see Burdige and Zheng, 1998, for more details; DIN, dissolved inorganic nitrogen, i.e., ammonium plus nitrate+nitrite). For example, in Chesapeake Bay sediments benthic DON fluxes range from ^^0.08 to 0.2 mmol m~^ day~^ in the anoxic sediments at site M3 and essentially zero to 0.4 mmol m"-^ day~^ in the bioturbated and bioirrigated sediments at site S3 (Burdige and Zheng, 1998; Burdige, 2001). However, at both sites benthic DON fluxes were only ^3-4% of benthic DIN fluxes. Interest in benthic DON fluxes also stems from a desire to better understand the relative importance of these fluxes in sediment nitrogen budgets relative to sediment denitrification rates (Nixon, 1981; Boynton and Kemp, 1985; Bender et ai, 1989; Kemp et ai, 1990; Devol and Christensen, 1993; Blackburn et al, 1996; Landen-Hillmeyr, 1998). This problem is of some significance in continental
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margin sediments since here denitrification is generally thought to be an important (and perhaps the major) sink for combined nitrogen in the entire marine environment (see, e.g., Codispoti, 1995, and references therein). However, until recently, sediment denitrification rates were generally determined indirectly and used to balance sediment nitrogen budgets by implicitly assuming that benthic DON fluxes were of minor significance. At site M3 in Chesapeake Bay we were able to examine this problem in a slightly different fashion, using data on sediment nitrogen deposition and burial, DIN and DON benthic fluxes, and several independent estimates of sediment denitrification rates to develop a sediment nitrogen budget (Burdige and Zheng, 1998). This approach led us to conclude that here benthic DON fluxes are less than ^20% of sediment denitrification, based on an integrated annual average benthic DON flux of 0.18 ± 0.07 mmol m"-^ day~^ and estimates of sediment denitrification that range from 0.8 to 2.4 mmol m"^ day"^ (Burdige and Zheng, 1998). In contrast, in Arctic sediments (water depths 170 to 2600 m) Blackburn et al. (1996) observed benthic DON fluxes (0.93 mmol m~^ day"^) that were substantially larger than either benthic DIN fluxes (0.1 mmol m"-^ day~^) or sediment denitrification rates (0.03 nmiol m~^ day~^). However, these workers also suggested that these large DON fluxes may have been a temporary phenomena associated with the recent sedimentation of fresh detrital material. At the same time, in sediments of the Skagerrak (a continental margin region of the North Sea), Landen-Hillmeyr (1998) reported benthic DON fluxes that range from ^0.3 to 1.4 mmol m'^day"^ and were again substantially larger than benthic DIN fluxes. The ratio of benthic DON fluxes to denitrification rates ranged from 0.3 to 17.5 at the five sites they studied, although without the high value of 17.5, this ratio was ^^1.5. In all but one of these sites denitrification rates were determined indirectly from benthic DIN fluxes and integrated sediment ammonium production rates, although at the one site where denitrification rates were directly determined, the ratio of benthic DON fluxes to denitrification rates was 1.2. The reasons why these very different results were obtained in anoxic Chesapeake Bay sediments versus these high-latitude continental margin sediments is unclear at the present time. Whether this is due to differences in sediment setting (estuarine versus continental margin), geography (temperate versus high latitude sites), or sediment redox conditions (anoxic versus more mixed redox) will require further study. Interestingly, results from irrigated Washington state continental margin sediments suggest that benthic DON fluxes are not an important component of nitrogen cycling in these sediments (Devol and Christensen, 1993). These workers were able to essentially balance sediment nitrogen budgets at these sites using only inorganic nitrogen benthic fluxes and measured denitrification rates (determined with benthic lander N2 measurements). However, given the fact that benthic DON fluxes do appear to be significant relative to sediment
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denitrification rates in at least some continental margin sediments suggests that this problem should be further examined to more conclusively resolve the reasons for these differences. C. THE EXTENT TO WHICH BENTHIC D O M
FLUXES AFFECT
THE COMPOSITION AND REACTIVITY OF DEEP-WATER
DOM
Interest in DOM fluxes from marine sediments stems in part from a recognition of the need to better understand the sources and sinks of DOM in the oceans (Hedges, 1992; Carlson, Chapter 4; Cauwet, Chapter 12; Hansell, Chapter 15; Hedges, Chapter 1; also see Section V. A). Although benthic DOC fluxes appear to be of similar magnitude as other DOC inputs such as riverine inputs (Burdige et al, 1999) the impact of these fluxes on water-column DOC concentrations and properties depends on the reactivity of sediment-derived DOC in the water colunm. If this material is sufficiently refractory, then these fluxes could represent an important source of DOC to deep waters and might help explain some of the observations about deep-water DOC discussed in Section V. A. Conversely, if sediment-derived DOC is reactive in the water column (i.e., it undergoes remineralization on time scales shorter than deep-water residence times) then it will have minimal impacts on deep-water DOC properties (Alperin et aL, 1999). Several lines of evidence from contrasting marine sediment suggest that not all of the sediment-derived DOM (i.e., from benthic fluxes) is refractory and that it does have the potential to be reactive in the water column. In estuarine Chesapeake Bay sediments a comparison of measured benthic DOM fluxes versus calculated, diffusive DOM fluxes suggests that there is enhanced production of N-rich DOM at or near the sediment-water interface (Burdige, 2001). This is consistent with the observation that DOM accumulating in these sediment pore waters is carbon-rich (C/NpDOM > 10) relative to the more N-rich DOM that escapes the sediments as a benthic flux (which has a C/N ratio of ~4-6 at site M3 and ^^2-4 at site S3; Burdige and Zheng, 1998). Similar trends in DOM elemental ratios have been observed in other sediments (Blackburn et aL, 1996; Landen-Hillmeyr, 1998), and were explained as being due to diffusional loss of low C/N ratio DOM produced during the initial hydrolysis of fresh (i.e., low C/N ratio) detrital organic matter near the sediment surface. This explanation is consistent with our Chesapeake Bay observations discussed above and discussions in Burdige and Gardner (1998), regarding the spatial separation in sediments between processes that produce the initial high-molecular-weight intermediates of sediment POM remineralization, and processes responsible for the production of refractory DOM in sediment pore waters (i.e., pLMW DOM). This spatial separation of HMW DOM and pLMW DOM net remineraUzation rates can also be inferred from the model results in Fig. 4. Based on these results the
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uncoupling between DOM that escapes as a benthic flux and that which accumulates in pore waters can be explained if one assumes that the C/N ratio of humic-like, pLMW DOM is greater (i.e., more carbon-rich) than that of this reactive HMW DOM, which appears to be a reasonable assumption (see Burdige, 2001, for further details). Results in Fig. 4 also show that in spite of the fact that model-derived concentrations of HMW DOC were significantly lower than those of pLMW DOC, their pore water gradients near the sediment surface were similar in magnitude. This observation is further quantified in Table I where it can be seen that calculated HMW DOC benthic fluxes are --50-80% of the total benthic DOC flux. Thus, in both anoxic and mixed redox sediments, model results suggest that fluxes of both refractory and reactive DOM can be similar in magnitude. In another approach to this problem, Bauer et al. (1995) examined the stable carbon and radiocarbon content of pore water DOM from the upper ~5 cm of two contrasting eastern North Pacific sediments (in Santa Monica Basin and at a 4100 m water depth site on the continental rise at the base of the Monterey deep-sea fan). At both sites the 8^^C values of the pore-water DOC had values consistent with a predominant marine source (—21 to —22 %o) and the pore-water DOC was greatly enriched in ^"^C as compared to bottom-water DOC (approx. —150 to —250 %oin the pore waters versus approx. —500 %o in the water column). While pore-water DOC profiles at both site predict diffusive, benthic DOC fluxes that are near-equal to the sediment carbon oxidation rate, this sediment DOC source does not appear to have a significant impact on bottom-water DOC radiocarbon values. To explain this latter observation, Bauer et al. (1995) suggested that either ^"^C-enriched pore water DOC is not released from the sediments in significant quantities (i.e., they have overestimated the benthic DOC flux in their simple benthic flux calculation) or that this radiocarbon-enriched, sediment-derived DOC "does not persist in the water colunm" (i.e., it is sufficiently reactive that it is rapidly remineralized). Consistent with the first suggestion is the fact that benthic DOC fluxes at these sites that I estimate using reported sediment carbon oxidation rates and Eq. [5] are seven to eight times smaller than those calculated by Bauer et al. (1995). At the same time though, the model results discussed earlier in this section (and shown in Fig. 4) suggest that benthic DOC fluxes may contain both refractory and reactive DOM components, which are likely to have different radiocarbon ages (e.g., see Eglinton et a/., 1997, for a discussion of analogous studies of radiocarbon ages of biomarker compounds in sediment POC). This would imply that the radiocarbon values determined by Bauer et al. (1995) could result from refractory (radiocarbon-depleted) and reactive (radiocarbon-enriched) components. This reactive sediment-derived DOC would likely undergo remineralization in the bottom waters, thus further minimizing the importance of sediment pore waters as a source or refractory DOC to the deep ocean.
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While the discussion here shows that benthic DOC fluxes may not be as important a source of refractory DOC to the water colunm as once suggested, recent results suggest another way that sediment pore-water DOC dynamics could play a role in explaining the ^"^C age of deep-water DOC. In recent studies, Guo and Santschi (2000) observed that simple desorption of colloidal (>1 kDa) organic matter from continental margin sediments yields DOC that is substantially older than the bulk sediment organic matter (^3000 years vs 700 years, respectively). Desorption of this material from sediments in continental margin benthic nepheloid layers, coupled with transport of this material to the deep ocean (e.g., Bauer and Druffel, 1998), could then play an important role in explaining the age of deepocean DOC. Assuming that this old, desorbed DOC is in some kind of reversible equilibrium with the sediment pore waters while in the sediments, the relatively refractory nature of the bulk pore water DOC pool (^pLMW DOC) would then aid in the aging process of this sorbed organic matter while it is resides in the sediments.
VI. THE ROLE OF PORE-WATER DOM IN SEDIMENT CARBON PRESERVATION As was discussed at the beginning of this chapter, two common models for sediment carbon preservation, the geopolymerization model (Nissenbaum et ai, 1972; Tissot and Welte, 1978; Krom and Westrich, 1981) and the mesopore protection model (Mayer, 1994a,b; Hedges et ai, 1999), suggest that DOM in sediment pore waters may play an important role in the preservation process. A third model for carbon preservation, the selective preservation of refractory biomacromolecules (Hatcher and Spiker, 1988; de Leeuw and Largeau, 1993) is generally thought to not involve DOM intermediates. In its simplest sense, the geopolymerization model involves condensation reactions in which low-molecular-weight dissolved organic compounds (such as amino acids or simple sugars; i.e., mLMW DOM compounds in the PWSR model) react to form higher-molecular-weight dissolved humic substances. The continued condensation of these dissolved humics is thought to eventually lead to the formation of particulate material such as humin or kerogen, and to the preservation of this organic matter in sediments. Although there have been numerous studies of these condensation reactions in the lab, there is little direct evidence for their occurrence in nature (Hedges, 1988; Henrichs, 1992). Furthermore, based on our molecularweight data (Burdige and Gardner, 1998), we noted that if these reactions do occur on early diagenetic time scales their products still have relatively low molecular weights (i.e., less than 3 kDa). In the mesopore protection model, DOM sorption is proposed to occur in small mesopores on mineral surfaces, where the sorbed DOM is physically protected
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from attack by microbial enzymes (Mayer, 1994a,b, 1999; Hedges and Keil, 1995). The mesopore protection model, however, is not mutually exclusive of the occurrence of geopolymerization reactions, since rates of abiotic condensation reactions may be accelerated in mesopore sites, by either steric- or concentration-related phenomena, thus further enhancing the preservation of sorbed DOM (Mayer, 1994b; Collins et al, 1995; Hedges and Keil, 1995). This latter point is of some interest, since under most natural conditions aqueous phase (i.e., pore water) geopolymerization reactions are thought to be quite slow (Hedges, 1988; Alperin et al, 1994). Since mesopore size places some constraint on the upper limit of the size/molecular weight of DOM molecules that can be taken up in mesopores (Mayer, 1994b), the relatively small size (<3 kDa) of most pore-water DOM would appear to aid in its possible interaction with these adsorption sites. Similarly, the refractory nature of the bulk pore-water DOM pool may also enhance its preservation, if these sorption processes are reversible to any significant extent (see discussions in (Lee, 1994; Mayer, 1994b; Henrichs, 1995). At the same time, however, if this process does play a role in controlling carbon preservation, then the nature of the sorption process and the composition of the DOM molecules involved in sorption (and ultimately carbon preservation) are likely more complicated than that which can be described by bulk DOC concentrations and simple sorption processes and coefficients (Henrichs, 1995; Mayer, 1995; Alperin et al, 1999). Finally, these observations can be used to briefly examine questions related to the relationship between anoxia and sediment carbon preservation (compare, e.g., discussions in Pedersen and Calvert, 1990; Canfield, 1994, and references therein; also see Aller, 1994; Hedges and Keil, 1995; Hedges etal, 1999). In general, field observations, experimental studies, and model calculations (Burdige, 2001) show that pore-water DOC concentrations are generally higher under anoxic conditions (also see sections II.A and II.B). Burdige (2001) also shows that changes in sediment redox conditions alter the pathways of sediment DOM remineralization, leading to the enhanced relative accumulation of refractory DOC (i.e., pLMW DOC) under anoxic conditions. Such elevated DOC concentrations in anoxic sediments could therefore enhance sediment carbon preservation in both the "conventional" geopolymerization model and the surface area adsorption/mesopore protection model (the caveats/concerns at the end of the last paragraph notwithstanding). Furthermore, given the importance of DOC as an intermediate in sediment POM remineralization these observations may help explain how oxygen exposure time apparently enhances sediment POM remineralization (Hedges and Keil, 1995; Hartnett et al, 1998; Hedges et al, 1999). Overall, then, these arguments suggest that some amount of enhanced carbon preservation may indeed occur in anoxic sediments, in spite of the fact that anoxia and sediment carbon preservation may not necessarily be causally linked.
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VII. CONCLUSIONS AND SUGGESTIONS FOR FUTURE RESEARCH Throughout this chapter I have attempted to summarize and synthesize the existing data on DOM in marine sediment pore waters and present explanations that (at least to me) appear to best explain the observations. I have also attempted to avoid repeatedly reminding the reader that "more work is clearly needed to examine these problems " although it should be apparent that this is indeed the case in most of these instances. The fact that much of the DOM in sediment pore waters appears to be refractory and is not well characterized to date (at least in terms of known biochemicals) suggests that "structural" approaches, similar to those used in water-colunm DOM studies (e.g., Aluwihare et al, 1997; McCarthy et ai, 1997; Boon et al, 1998), may prove useful here as well. Further studies linking DOM composition and reactivity will also be required to examine many of the problems discussed here. It is interesting to note that many of these questions could be addressed in carefully conducted sediment incubation experiments (S0rensen et ai, 1981; Burdige, 1991a,b). The work discussed here has focused on dissolved organic carbon and nitrogen, both in terms of bulk compositions and depth distributions and in specific compositional studies of the DOM pool. To date, little work has focused on dissolved organic phosphorus or sulfur in sediment pore waters, although it seems highly likely that such studies could be important in understanding the sedimentary and oceanic cycles of these elements as well. Such studies might also be of relevance in better understanding sediment carbon preservation depending on how (or if) natural vulcanization reactions affect carbon preservation (Tegelaar et al., 1989; de Leeuw and Largeau, 1993). As discussed throughout this chapter, DOM compounds are important intermediates in sediment carbon remineralization and perhaps sediment carbon preservation as well. Therefore, differences in DOM composition and reactivity due to differences in sediment redox conditions might play a role in how sediment redox conditions affect overall sediment carbon preservation in these different sediment types. Again, however, future studies will be needed to examine how (or even if) this occurs.
ACKNOWLEDGMENTS Preparation of this chapter was supported by grants from the Office of Naval Research (Harbor Processes Program and Coastal Benthic Optical Properties Program). My work on pore-water DOM has also been supported by grants from the National Science Foundation. I thank Will Berelson,
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Yo Chin, Marc Alperin, Juli Homstead, Mark Hines, Jack Middelburg, Annelie Skoog, Bob Haddad, and Paul Kepkay for discussions over the years that helped me clarify many of the thoughts and ideas that now appear here. Special thanks go to Chris Martens for first getting me involved in studies of porewater DOM sometime in the past century. I also thank Rick Keil and an anonymous reviewer for their comments on an earlier version of this chapter. Finally, musical inspiration while preparing this chapter came from two great FM stations that now broadcast over the Internet, KPIG (Freedom, CA) and WFUV (Bronx, NY).
APPENDIX: A DESCRIPTION OF THE DOM ADVECTION/DIFFUSION/REACTION MODEL ANOXIC, NONBIOTURBATED SEDIMENTS ( A N S MODEL) Equations [1] and [2] are solved using the boundary conditions H = H° and P = P° at X = 0 and dH/dx = 0 and dP/dx = 0 as x -^ cx), yielding H = We-^"" + G2(l - e-^"") + Qxie-^"" - e'^"")
[A-1]
where Qi =
—
T
k}{ — Xo) — DgA^
Qi = Roo/ku
[A-3] [A-4]
2A
kp — Q)X — A ^
^ =
Qs = aRoo/kp
[A-8]
-co + y/(o^ + 4Dskp m
f^-'^
652
David J. Burdige
BioTURBATED
AND/OR BIOIRRIGATED SEDIMENTS
(BBS
MODEL)
The equations developed here are general equations for sediment systems in which bioturbation and bioirrigation can both occur. In these equations it is assumed that there is a surficial bioturbated zone in which bioturbation is modeled as a random, diffusion-like process with a bioturbation coefficient D^ (Boudreau, 1997). This then leads to Dj = Ds + DB in the "mixed" layer and Dj = D^ below the mixed layer. The bioturbation coeffiecient DB can either be a constant value (leading to Dj being a step function across the mixed layer boundary) or any other function of depth. Bioirrigation is modeled as a nonlocal advective process of the form a(C - C")
[A-10]
(e.g., Boudreau, 1997), where a is the bioirrigation exchange coefficient and C° is the bottom-water concentration. Again, a can be either a constant in the "irrigated" zone or a function of depth. Given these formulations for these biological transport processes, Eqs. [1] and [2] can be rewritten as. — ( • T - ^ I - co-^ - a(H - H') -h ARe-^^ + Roc - k^H = 0 dx \ dx I dx
[A-11]
or 72
dx^
dx dx
dx
[A-12]
and dP d_ / „ dP\ DT— - CO—- - a(P - P°) + akuH - Ux)P dx J dx dx \
=0
[A-13]
or Dj^
dx"^
+^ ^ - c o ^ - a { P - P ' ) dx dx dx
+ aknH - k^(x)P = 0,
[A-14]
where kp is now written as kp(x) to indicate that its value is likely higher in the upper portions of the sediments that are bioturbated and/or bioirrigated (Burdige, 2001). The boundary conditions for these equations are the same as those for the equations described above for the ANS model. To keep the depth-dependence of DT (i.e., DB), a, and k^ as general as possible, Eqs. [A-12] and [A-14] have been solved by numerical techniques. This involves using the Crank-Nicolson implicit centered-differencing scheme to
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Sediment Pore Waters
approximate the first and second derivatives of P and H (Crank, 1975; Dhakar and Burdige, 1996; Boudreau, 1997). Here the sediment column is divided into n depth intervals of equal size AJC and after numerically approximating the concentration derivatives, one is left with n equation of the form -at C,_i + bi d + Ci G+i = di
[A-15]
for both P and H. In these equations C/ is the concentration of either P ox H at depth interval /* Ax, and at, bf, c,, and df are based on the values of the other parameters in Eqs. [A-12] and [A-14]. Depending on the depth-dependence of DB, the first derivative of Dj can be either determined analytically at each depth interval, or numerically approximated as described above. In solving these equations the first and last equation in each set of equations (i.e., for either P or H) is rewritten based on the boundary equations (see Dhakar and Burdige, 1996, for further details). Each set of equations can then be expressed in the form of a tridiagonal matrix and solved by Gaussian elimination (Boudreau, 1997). Although the equations for P and H are coupled, the coupling is such that the set of equations for H can first be independently solved for H versus depth. This solution is then used to solve for P versus depth. This systems of equations can be solved in an Excel spread sheet (a copy of which is available from the author). The validity of this numerical scheme was verified several ways. In the first case, bioturbation and bioirrigation were "turned off' and numerical solutions were compared with analytical solutions to the equations developed above for anoxic, nonbioturbated sediments. In the second case, analytical solutions to a simple two-layer bioturbation model (AUer, 1982) were compared with numerical solutions to the same equations. In all of these comparisons, exact agreement between the two solutions was observed. Finally, it was observed that varying the value of Ax by a factor of two did not affect the solution of model calculations that included a range of bioturbation and bioirrigation coefficients. This insensitivity of numerical solutions to the grid size is a further indication of a stable numerical solution (see discussions in Alperin, 1989).
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Bemer, R. A. (1980). "Early Diagenesis: A Theoretical Approach." Princeton University Press, Princeton, NJ. Blackburn, T. H., Hall, R O. J., Hulth, S., and Landen, A. (1996). Organic-N loss by efflux and burial associated with a low efflux of inorganic N and with nitrate assimilation in Arctic sediments (Svalbard, Norway). Mar. Ecol Prog. Sen 141, 283-293. Boon, J. J., Klap, V., and Eglinton, T. (1998). Molecular characterization of microgram amounts of colloidal dissolved organic matter (UDOM) in ocean water samples by direct temperature resolved anmionia chemical ionization mass spectrometry. Org. Geochem. 29,1051-1062. Boschker, H. T. S., Bertilsson, S. A., Dekkers, E. M. J., and Cappenberg, T. E. (1995). An inhibitorbased method to measure initial decomposition of naturally occurring polysaccharides in sediments. Appl. Environ. Microbiol. 61,2186-2192. Boudreau, B. P. (1997). "Diagenetic Models and Their Implementation." Springer-Verlag, Amsterdam. Boynton, W. R., and Kemp, W. M. (1985). Nutrient regeneration and oxygen consumption by sediments along an estuarine salinity gradient. Mar. Ecol. Prog. Sen 23,45-55. Boynton, W. R., Kemp, W. M., and Osborne, C. G. (1980). Nutrient fluxes across the sediment-water interface in the turbid zone of a coastal plain estuary. In "Estuarine Perspectives" (V. S. Kennedy, Ed.), pp. 93-109. Academic Press, San Diego. Bronk, D. A. (2002). Dynamics of DON. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. Hansen and C. A. Carlson, Eds.), pp. 153-247. Academic Press, San Diego. Burdige, D. J. (1989). The effects of sediment slurrying on microbial processes, and the role of amino acids as substrates for sulfate reduction in anoxic marine sediments. Biogeochemistry 8,1-23. Burdige, D. J. (1991a). The kinetics of organic matter mineralization in anoxic marine sediments. J. Mar Res. 49,121-161. Burdige, D. J. (1991b). Microbial processes affecting alanine and glutamic acid in anoxic marine sediments. FEMS Microbiol. Ecology 85, 211-231. Burdige, D. J. (2001). Dissolved organic matter in Chesapeake Bay sediment pore waters. Org. Geochem. 32,487-505. Burdige, D. J., Alperin, M. J., Homstead, J., and Martens, C. S. (1992). The role of benthic fluxes of dissolved organic carbon in oceanic and sedimentary carbon cycling. Geophys. Res. Lett. 19, 1851-1854. Burdige, D. J., Berelson, W. M., Coale, K. H., McManus, J., and Johnson, K. S. (1999). Fluxes of dissolved organic carbon from California continental margin sediments. Geochim. Cosmochim. Ac^fl 63,1507-1515. Burdige, D. J., Chen, W., and Kline, S. W. (2002). The cycling of fluorescent dissolved organic matter in contrasting marine sediments, ms in prep, for Mar Chem. Burdige, D. J., and Gardner, K. G. (1998). Molecular weight distribution of dissolved organic carbon in marine sediment pore waters. Mar Chem. 62,45-64. Burdige, D. J., Gardner, K. G., and Skoog, A. (2000). Dissolved and particulate carbohydrates in contrasting marine sediments. Geochim. Cosmochim. Acta 64,1029-1041. Burdige, D. J., Gardner, K. G., and Zheng, S. (1996). The molecular weight distribution of dissolved organic matter (DOM) in marine sediment pore waters. EOS 76 (3), OSl IK (abstr.). Burdige, D. J., and Homstead, J. (1994). Fluxes of dissolved organic carbon from Chesapeake Bay sediments. Geochim. Cosmochim. Acta 58, 3407-3424. Burdige, D. J., and Martens, C. S. (1988). Biogeochemical cycling in an organic-rich marine basin 10. The role of amino acids in sedimentary carbon and nitrogen cycling. Geochim. Cosmochim. Acta 52,1571-1584. Burdige, D. J., and Martens, C. S. (1990). Biogeochemical cycling in an organic-rich marine basin. 11. The sedimentary cycling of dissolved free amino acids. Geochim. Cosmochim. Acta 54, 30333052.
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Shaw, D. G., and Mcintosh, D. J. (1990). Acetate in recent anoxic sediments: direct and indirect measuraients of concentration and turnover rates. Estuarine Coastal Shelf Sci. 31,775-788. Shaw, T. J., Gieskes, J. M., and Jahnke, R. A. (1990). Early diagenesis in differing depositional environments: The response of transition metals in pore waters. Geochim. Cosmochim. Acta 54, 1233-1246. Sholkovitz, E. R., and Mann, D. R. (1984). The pore water chemistry of ^^^'^"^^Pu and ^^^Cs in sediments of Buzzards Bay, Massachusetts. Geochim. Cosmochim. Acta 48, 1107-1114. Skoog, A., and Benner, R. (1998). Aldoses in various size fractions of marine organic matter: Implications ofr carbon cycling. Limnol. Oceanogr. 42, 1803-1813. Skoog, A., Hall, R O. J., Hukth, S., Paxeus, N., and Rutgers van der Loef, M. (1996). Early diagenetic production and sediment-water exchange of fluorescent dissolved organic matter in the coastal environment. Geochim. Cosmochim. Acta 60, 3619-3629. Skrabal, S. A., Donat, J. R., and Burdige, D. J. (1997). Fluxes of copper-complexing ligands from estuarine sediments. Limnol. Oceanogr. 42,992-996. Skrabal, S. A., Donat, J. R., and Burdige, D. J. (2000). pore water distributions of dissolved copper and copper-complexing ligands in esmarine and coastal marine sediments. Geochim. Cosmochim. Ac/fl 64,1843-1857. Smith, C. R., Pope, R. H., DeMaster, D. J., and Magaard, L. (1993). Age-dependent mixing in deep-sea sediments. Geochim. Cosmochim. Acta 57, 1473-1488. S0rensen, J., Christensen, D., and J0rgensen, B. B. (1981). Volatile fatty acids and hydrogen as substrates for sulfate-reducing bacteria in anaerobic marine sediments. Appl. Environ. Microbiol. 42, 5-11. Starikova, N. D. (1970). Vertical distribution patterns of dissolved organic carbon in sea water and interstitial solutions. Oceanology 10,796-807. Steinberg, S. M., Venkatesan, M. I., and Kaplan, I. R. (1987). Organic geochemistry of sediments from the coninental margin off southern New England, U.S.A. I. Amino acids, carbohydrates and Hgnin. Mar. Chem. 21, 249-265. Suess, E., MuUer, P. J., and Reimers, C. E. (1980). A closer look at nitrification in pelagic sediments. Geochem. J. 14, 129-137. Sugai, S. P., and Henrichs, S. M. (1992). Rates of amino acid uptake and remineralization in Resurrection Bay (Alaska) sediments. Mar. Ecol. Prog. Sen 88, 129-141. Teague, K. G., Madden, C. J., and Day, J. J., Jr. (1988). Sediment-water oxygen and nutrient fluxes in a river-dominated estuary. Estuaries 11, 1-9. Tegelaar, E. W., Leeuw, J. W. de, Derenne, S., and Largeau, C. (1989). A reappraisal of kerogen formation. Geochim. Cosmochim. Acta 53, 3103-3106. Thimsen, C. A., and Keil, R. G. (1998). Potential interactions between sedimentary dissolved organic matter and mineral surfaces. Mar Chem. 62,65-76. Thurman, E. M. (1985). "Organic Geochemistry of Natural Waters." Martinus Nijhoff/Junk, The Hagve. Tissot, B., and Welte, D. H. (1978). "Petroleum Occurrence and Formation." Springer-Verlag, Amsterdam. Walsh, T. W. (1989). Total dissolved nitrogen in seawater: A new high-temperature combustion method and a comparison with photo-oxidation. Mar Chem. 26, 295-311. Wefer, G., Berger, W H., Richter, €., etal. (1998). "Proceedings of the Ocean Drilling Program, Initial Reports," Vol. 175. College Station, TX. Wellsbury, P, Goodman, K., Barth, T, Cragg, B. A., Barnes, S. P, and Parkes, R. J. (1997). Deep marine biosphere fuelled by increasing organic matter availability during burial and heating. Nature 388, 573-576. Wellsbury, P., and Parkes, R. J. (1995). Acetate bioavailability and turnover in an estuarine sediment. FEMS Microbiol. Ecol. 17, 85-94, Westrich, J. T, and Bemer, R. A. (1984). The role of sedimentary organic matter in bacterial sulfate reduction: The G model tested. Limnol. Oceanogr 29, 236-249.
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Whelan, J. K. (1977). Amino acids in a surface sediment core of the Atlantic abyssal plain. Geochim. Cosmochim. Acta 41, 803-810. Whelan, J. K., and Emeis, K.-C. (1992). Sedimentation and preservation of amino compounds and carbohydrates in marine sediments. In "Productivity, Accumulation, and Preservation of Organic Matter in Recent and Ancient Sediments" (J. K. Whelan and J. W Farrington, Eds.), pp. 176-200. Columbia Univ. Press, New York. WilHams, P., and Druffel, E. (1988). Dissolved organic matter in the ocean: Comments on a controversy. Oceanogr. Mag. 1,14-17. Williams, P M., and Druffel, E. R. M. (1987). Radiocarbon in dissolved organic matter in the central North Pacific Ocean. Nature 330,246-248.
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Chapter 14
DOC in the Arctic Ocean Leif G. Anderson Analytical and Marine Chemistry Goteborg University Goteborg, Sweden I. Introduction A. Water Masses and Circulation II. Sources of DOC to the Arctic Ocean A. River Runoff Sources B. Seawater Sources C. Biological Sources within the Arctic Ocean III. Composition and Distribution of DOC within the Arctic Ocean
A. Lignin Oxidation Products and Stable Carbon Isotopes B. C/N Molar Ratios C. Distribution IV. Summary of Sources and Sinks References
I. INTRODUCTION The objective of this chapter is to summarize the present knowledge on the input of terrigenous dissolved organic matter (DOM) to the Arctic Ocean, the input of marine DOM in water masses flowing into the Arctic from the Pacific and Atlantic oceans, and the distribution of terrigenous and marine-origin DOM within the Arctic Ocean. The Arctic Ocean is, together with the Greenland, Iceland, and Labrador seas, a major area of deep-water formation in the Northern Hemisphere (Anderson et al, 1999). As this deep water contributes to the global thermohaline circulation and thus adds to the deep waters of all global oceans, it is of global interest to evaluate the vertical flux of DOM within the Arctic Ocean (and the other deep-water formation sites). In order to address the above aspects of DOM it is essential to consider the water mass formation and circulation within the area. Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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LeifG. Anderson
Several rivers draining large areas of Siberia and North America flow into the Arctic Ocean. The four dominating are the Ob, Yenisey, and Lena from Siberia and the Mackenzie from North America. In addition, much of the runoff from the Yukon River reaches the Arctic Ocean after entering the Bering Sea and flowing north through the Bering Strait. Consequently, the Arctic Ocean receives much freshwater, about 10% of the global runoff (Aagaard and Carmack, 1989), while constituting only about 1% of the global ocean volume (Menard and Smith, 1966). Theserivers,with the major fractions supplied by Siberian rivers, add large amounts of terrigenous DOM to the Arctic Basins (e.g. Gordeev et ai, 1996). A significant fraction of this DOM is dissolved organic carbon (DOC), which is the focus of this review. The large terrestrial component of DOM distinguishes the Arctic Ocean from the Southern Ocean. A. WATER MASSES AND CIRCULATION
Ocean water from the Pacific enters the Arctic Ocean through the Bering Strait and from the Atlantic, through the eastern Fram Strait and the Barents Sea (Fig. 1). Fresh water, in the form of runoff and sea ice meltwater mixes with ocean water in the upper Arctic Ocean and exits the Arctic Basin mostly through the Canadian
5 Russia
Figure 1 Map with geographic information and schematic circulation of surface water (gray arrows) and intermediate water (black arrows). The straight arrows indicate the mouths of the rivers included in Table I.
DOC in the Arctic Ocean
667
Archipelago and western Fram Strait (Jones et al, 1998). Some of the upper waters are entrained and transported to deeper regions. Intermediate-depth water largely follows the topography, resulting in several large loops within the deep central Arctic Ocean (Rudels et al, 1994). Deep water both enters and exits the Arctic Ocean through Fram Strait over a sill at a depth of about 2200 m. The inflowing Pacific water is relatively fresh and contributes significantly only to the upper water masses. However, a small amount of high-salinity water formed during sea ice production penetrates to the deepest parts of the Canadian Basin (Jone5 et al, 1995). The Adantic water, on the other hand, has a saHnity of close to 35 when entering the Fram Strait and the Barents Sea, but the temperature is high enough (around 4°C) for this water to stay at the surface. However, during the transit over the Barents Sea, heat is lost to the atmosphere and, together with brine release from sea-ice production, the density increases to form waters that penetrate to intermediate depths of the Arctic Ocean (e.g., Swift et al, 1983; Schauer et al, 1997). Most of this high-density water enters the Arctic Ocean through the St. Anna Trough, though some water of Atlantic origin passes through the Kara Sea into the Laptev Sea, with a fraction continuing into the East Siberian Sea before meeting water of Pacific origin (Jone5" et al, 1998). The Atlantic water that flows through Fram Strait meets sea ice and the upper part of this warm water melts the sea ice, forming an approximately 100-m-thick surface water layer of low salinity (5 ~34.2) and with temperatures close to the freezing point (Rudels et al, 1996). This constitutes the formation of the lower halocline water (LHW) and prevents deep-water formation within the central Arctic Ocean. In addition, the LHW hampers the penetration of heat from the Adantic Layer water to the overlying sea-ice cover. The Pacific water, and to some extent the Atlantic water, transports significant amounts of nutrients into the Arctic Ocean shelf seas. The high nutrient supply and hydrographic conditions stabilizing the water column result in primary production rates that are high even in a global perspective. In the Bering-Chukchi Sea region, new production has been estimated to be 288 g C m~^ year"^ (Hansell et al, 1993). New productivity in the Barents Sea is also considered high, being stifl higher within the marginal ice zone (Sakshaug and Skjoldal, 1989). Because of the patchy productivity it is difficult to estimate a mean productivity rate, but the vertical carbon flux at 75 m, as simulated by a 3-D model, generally varied between 10 and 40 g C m~^ year"\ depending on forcing conditions (Slagstad and Wassmann, 1996).
11. SOURCES OF DOC TO THE ARCTIC OCEAN The highest concentrations of DOC in source waters to the Arctic Ocean are found in river runoff, with a mean of more than 500 JJM (e.g., Gordeev et al, 1996; Lobbes et al, 2000). This concentration is about an order of magnitude higher than
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LeifG. Anderson
in the inflowing Atlantic water, but the volume flux of the latter is about 50 times larger than that of the continental runoff. Nevertheless, there is a clear signature of terrigenous DOC in the surface water over the central Arctic Ocean (Opsahl et al, 1999). Many of the investigations of organic carbon in the Arctic Ocean have reported data on unfiltered samples and are therefore total organic carbon (TOC) concentrations. However, often the waters of the Arctic Ocean are very low in particles, which makes the difference between DOC and TOC very little. This is not the case for samples collected during high primary productivity or in turbulent coastal waters.
A. RIVER RUNOFF SOURCES Numerous rivers enter the Arctic Ocean. They drain enormous areas (total drainage basin area > 10 x 10^ km^) with variable vegetation and soil conditions. Consequently, DOC concentrations vary significantly between rivers (Table I). There are also significant seasonal differences in river TOC concentration, as reported for the Lena River by Cauwet and Sidorov (1996). The maximum concentration (980 ^M) was found during the maximum water discharge in early summer, followed by a lower concentration (700 /xM) in the summer and autumn, and the lowest concentration (310 /xM) during winter. The mean annual, discharge-weighted, concentration was 830 jiM. It should be noted that several investigations were performed after maximum water discharge in summer, and not always is the date of sampling given in the literature. To get average discharge weighted concentrations, DOC concentrations were multiplied by each river discharge and divided by the total annual discharge (Table II). Another uncertainty is that around one-third of the discharge to the Arctic Ocean takes place through smaller rivers and creeks that are not included in Table I. An alternative approach for estimating an average discharge weighted concentration for the rivers entering a given area is to sample the estuary and the surrounding sea and make a DOC versus salinity plot (Fig. 2). Assuming that DOC behaves conservatively, the intercept at 5 = 0 corresponds to a discharge weighted mean of the rivers entering the area investigated. This estimate includes the seasonal variability, as the residence time of the runoff on the Eurasian shelves has been estimated to ^ 3 years (Schlosser et al, 1994). This approach is not suitable for the Beaufort Sea area, where the Mackenzie River discharges, as the residence time of the surface water on the shelf in summer is short (Macdonald et al, 1989). The Mackenzie River dominates the discharge from North America into the Arctic Ocean and it is thus more straightforward to evaluate the DOC concentration in the runoff from this continent, than from the Eurasian. The regression lines of Figs. 2C and 2D (from the Laptev Sea region) are in excellent agreement with an intercept of 579 and 580 /xM. The data of Fig. 2B fall
669
DOC in the Arctic Ocean Table I Reported Concentrations of DOC and TOC in Arctic Rivers No.
River
1 2 3 4 5 6 7 8 9 10 11 B.S.
Pechora Ob Pyr Yenisey Katanga Olenek Lena Yana Indigirka Kolyma Mackenzie Yukon
DOC {^iM)
111 850 538 to 558 232 to 264 404 387 375 to 863 357 to 733
TOC (^lM)
References
Shelf seas
1083 592 to 733 558 617 525 600 792 to 842 558 to 611 642 to 754 389 to 675 642 to 1050 476 to 833
d d,g d d,e,g d d,e a, c, d, e, g c, d, e, g c,d,g c,d,g b,dj,g
Barents Kara Kara Kara Laptev Laptev Laptev Laptev East Siberian East Siberian Beaufort Bering
b,f,g
Note. The Yukon river enters the Bering Sea (B.S.), outside the range of Figure 1, but most of its w^ater enters the Arctic Ocean through Bering Strait. "Cauvet and Sidorov (1996). ^Degens et al. (1991). ^Fitznar (1999). '^Gordeev et al (1996). ^Lobbesetfl/. (2000). ^Pocklington (1987). ^Telang et al (1991).
Table II DOC Flux from Major Rivers into the Arctic Ocean (Lobbes et al, 2000) River Mezen
Ob Yenisey delta Olenek Lena delta Yana Indigirka Kolyma Mackenzie Total
Discharge (km"^ year~^)
Drainage basin area (km^ 10^)
DOC flux D O C (jLtM)
(lO^gCyear-i)
56
1006
2,990 2,440
1,805
735 711 850 538 232 404 387 640
248 3,690 4,860 323 3,380 85 241 458 1,917
10,994
636^^
15,200
21 419 569 32 524 31 50 98 249
2,430
1,993
198 244 305 526
"The mean concentration is computed as (DOC flux)/(discharge) x (12).
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around the same regression line, but without data in the salinity interval 1 to 28 it is not meaningful to make a linear regression calculation. The data West of 115°E in Fig. 2A also falls along the same regression line, but with too few low-salinity data to make a linear regression calculation. Hence, it is not possible to draw any conclusion with regard to the DOC concentration in the runoff entering the Kara Sea relative to that entering the Laptev Sea. A striking feature in Fig. 2A is the large scatter in data east of IIS'^E and the low DOC concentrations in the lowsalinity waters. Three possible explanations for the scatter can be considered. First, these samples were not filtered prior to analysis, which might both result in higher concentration and larger scatter. Second, these samples were analyzed on board the ship, using a Shimadzu TOC 5000, which is sensitive to vibrations, and thus also likely to contributes to scatter. Finally, the low-salinity samples were mainly collected in the East Siberian Sea, where sea-ice melt contributed significantly to the freshwater (Olsson and Anderson, 1997). Since sea ice can have highly variable TOC concentrations depending on biological activity in and under the ice, this can add to the scatter. The consequence of all these uncertainties is that it is difficult to evaluate any mean runoff DOC (or TOC) concentration for the East Siberian Sea, using the available data. Guay et al. (1999) used a UV fluorometer on the SCICEX-97 cruise to record a continuous in situ record of fluorescence at excitation 320 nm and emission 420 nm along the submarine track, at a depth of about 50 m. The fluorescence measurements can be used to estimate the concentrations of the humic-rich terrestrial component of DOM. The measured fluorescence detector response (V) gave a linear correlation to the TOC concentrations (TOC = 94.8 x V, r^ = 0.84, n = 186), the latter measured by high-temperature combustion on samples collected roughly every hour during the cruise. Also particulate organic carbon was determined on some samples and that accounted for less than 4.2% of the measured TOC, leading the authors to conclude that DOC ^ TOC. The DOC and salinity data collected along the continental slope of the Makarov and Amundsen Basins, show a linear correlation of DOC = -18.5 x 5 + 705 /xM (r^ = 0.76, n = 4914). This is interpreted as data from a region with high DOC Eurasian runoff mixing with waters of Atlantic origin with low DOC. The resulting runoff concentration of 705 /xM is higher than that found from measurements in the Laptev Sea. However, there might be temporal variability in the runoff DOC concentration and also the data reported by Guay et al. (1999) covered a salinity range of about 32 to 34, making the computed intercept at 5' = 0 somewhat uncertain. These data help identify regions with runoff from the shelf seas to the deep central Arctic Ocean.
B.
SEAWATER SOURCES
The reported DOC concentrations in the inflowing water from the Atlantic vary between 52 and 75 JJLM (Wheeler et al, 1997; B0rsheim and Mycklestad, 1997;
672
LeifG. Anderson
Opsahl et al, 1999; Fransson et al, 2001). Some of this variation might be a result of analytical errors, but in addition different water masses were sampled, and they were not sampled at the same time. Inflowing water from the Atlantic includes surface water flowing through Fram Strait and the Barents Sea, as well as deeper water flowing through Fram Strait. Deeper Atlantic water is modified between the Greenland-Scotland Ridge and the Arctic Ocean. The Norwegian Sea deep water, flowing north through Fram Strait, is a mixture of Eurasian Basin deep water and Greenland Sea deep water (Swift et ai, 1983). Some of the Eurasian Basin deep water that exits through Fram Strait flows around the Greenland Sea and mixes with the Greenland Sea deep water before it reenters the deep Arctic Ocean. It is difficult to assign a specific DOC concentration to the water flowing in through Bering Strait as the inflow consists of several different water masses and considerable modifications take place during the transit through the Bering Sea. The Arctic Ocean Section expedition in 1994 showed a TOG concentration span of 50 to 110 /JLM in the waters with Pacific-derived characteristics (Wheeler et al, 1997). When the particulate carbon fraction was subtracted the DOC concentrations had a span of 20 to 100 /xM (their Fig. 8). The mean concentration computed for the samples at the slope stations equals ~70 ± 1 5 /xM. Using a Lagrangian model, Walsh et al. (1997) computed a monthly depth average DOC concentration of between 67 and 134 fiM at positions over the 80-m isobath of the northwestern Chukchi Sea. The annual average of the monthly values is ^^90 /iM, which is in fairly good agreement with the Wheeler et al. (1997) mean DOC measurements of the slope stations north of the Chukchi Sea.
C. BIOLOGICAL SOURCES WITHIN THE ARCTIC OCEAN
An additional source of DOM in the Arctic Ocean is through biological processes within the Arctic Ocean and its shelves. Primary productivity over the continental shelves is substantial and results in a significant seasonal production of marine DOM. This seasonal signal can be observed in surface waters. The outflow from the Barents Sea into the central Arctic Ocean through the St. Anna Trough (containing insignificant fraction of river runoff) showed elevated surface DOC concentrations relative to waters below 150 m (Fransson et al, 2001). At depths shallower than 150 m, the nutrient distribution indicated that primary production occurred in the surface water during the transit over the Barents Sea. Subtracting the deep-water DOC concentration (average of 52 /xM) from surface DOC values estimates the labile, i.e., freshly produced, part of the DOC (cf. Hansell and Carlson, 1998). The labile DOC amounts to 1.4 mol C m"^ integrated over the top 150 m (Fransson et al., 2001), which will be exported to the central Arctic Ocean. The Chukchi Sea also has a high biological productivity. In analogy with the above estimate of exported DOC, the difference between the highest (134 /xM)
DOC in the Arctic Ocean
673
and lowest (67 /xM) monthly depth average, DOC concentrations at the continental break of the northwestern Chukchi Sea (Walsh et al, 1997) should reflect the marine DOC exported into the central Arctic Ocean from this area. The productivity of the central Arctic Ocean is small compared to the shelf seas. Based on the computed deficit of phosphate in surface waters, Anderson et al. (2000) estimated an average export production of 0.04 mol m~^ year~^ over the central Arctic Ocean. In contrast an in situ DOC production of over 0.5 mol m~^ year~^ (assuming a 120-day productive season) was computed for the central Arctic Ocean in 1994 (Wheeler et al, 1997). If this DOC production is distributed over the top 50 m, it will result in a concentration increase of 10 /xM. In order to sustain such an annual DOC production over the residence time of the Arctic Ocean surface water, 5-10 years, an unrealistic DOC concentration would follow, indicating extensive recycling. Hence, it is essential to consider the seasonal production and degradation of marine DOC in the Arctic Ocean. Data are unfortunately not available to make such an evaluation, not even in the shelf seas. From extensive measurements, DOC in sea ice has been attributed to ice algae production (e.g.. Smith et al, 1997). In shelf seas receiving much runoff, the sea ice produced will include some terrigenous DOC. In the spring (beginning of April to end of May) when the sea ice algae develops, Smith et al. (1997) found a good correlation between chlorophyll a and DOC in the bottom ice of Resolute Passage in the Canadian Archipelago. DOC concentrations were much higher in ice than in underlying water, especially in ice covered with only a thin snow layer. The highest DOC concentration (>3000 /xM) was measured in the bulk of the bottom ice on May 14 (Smith et al, 1997). However, the volume with this high concentration is small and thus the integrated contribution of DOC from ice to the underlying water mass is small. Measurements of DOC release rates by ice algae were performed by Gosselin et al (1997) along the track of the Arctic Ocean section in 1994. The release rate varied from less than 25 /xmol m~^ day~^ to 1600 lb 1500 /xmol m~^ day~^ with the highest rates in the Chukchi Sea. Thomas et al (1995) collected three ice cores of more than 2 m length in the Fram Strait. In two of these the DOC concentration was mostly below 100 /xM all through the core. In the third the concentration was close to 100 /xM in the top ^1.8 m, and increased to a maximum of ~700 /xM some 10 cm from the bottom. This increase was explained by a combination of DOM excretion by biota and decomposition of organisms (Thomas et al, 1995). The mean bulk concentration of DOC in sea ice from the central Arctic Ocean is 316 ± 99 /xM (Melnikov, 1997). If 1 m of ice melts annually, the concentration in the top 50 m (typical winter surface mixed layer (Rudels et al, 1996)) would increase by just over 6 /xM. A further source of DOC from biological processes is release from the sediment surface caused by decomposition of particulate organic material. Hulth et al (1996) measured DOC concentrations in the range of 500 to 8000 /xM in pore
674
LeifG. Anderson
water in the Svalbard area. The lowest concentrations were found at stations east of Svalbard, where also a significant inverse linear correlation (r^ = 0.849) of DOC concentrations with a sediment reactivity index (defined as sediment oxygen consumption rate normalized to the organic content) was found. This suggests a coupling between reactivity of organic matter in sediment and DOC lability in pore water. In a study of the eastern Eurasian Basin and adjacent shelves (Hulthe and Hall, 1997), DOC fluxes out of the sediment were evaluated to be in the range from close to zero to 3.6 mmol m"-^ day~^. The highest fluxes were found on the shelves and the lowest in the deep basins and on the slopes. A positive correlation of the DOC and dissolved inorganic carbon fluxes was observed, with DOC constituting up to 50% of the total benthic carbon flux at stations with the highest total benthic carbon fluxes. This indicates that the fraction of DOC that is oxidized to inorganic carbon is decreasing with increasing decomposition rates.
III. COMPOSITION AND DISTRIBUTION OF DOC WITHIN THE ARCTIC OCEAN Before the transport of DOC to and from of the Arctic Ocean is discussed, the quality of the terrigenous DOM has to be considered. Does it flow with the water as a biogeochemically stable solute or is it available to diagenetic alteration or photochemical decomposition? Several investigations have studied the composition of DOM in rivers entering the Arctic Ocean (e.g., Gordeev et al, 1996; Cauwet and Sidorov, 1996; Lara et al, 1998; Lobbes et ai, 2000) as well as in the Arctic Ocean itself (e.g., Wheeler ^r a/., l991;OpsahletaL, 1999; Kattner^r^/., 1999). One general conclusion is the stability of terrigenous DOC in the surface waters of the Arctic Ocean. Except for the Unear mixing line of runoff and seawater in a DOC vs salinity plot, the fairly constant composition of the DOM in all of the Arctic Ocean supports this conclusion.
A. LiGNiN OXIDATION PRODUCTS AND STABLE CARBON ISOTOPES The most useful quantitative tracers of terrestrial organic matter are lignin oxidation products, which have been determined in runoff to the Arctic Ocean (Opsahl et ai, 1999; Lobbes et al, 2000) and in the surface waters of the Arctic Ocean (Opsahl et al, 1999; Kattner et al, 1999). Kattner et al (1999) determined lignin in the "humic" fraction of DOM and used this as a tracer for terrigenous influence, with the result that the riverine-derived freshwater contribution to the Laptev Sea is 8 to 30%. Combining this proportion with DOC concentrations in the Lena River and Laptev Sea indicates that about 60% of the DOC in the surface layer of the Laptev Sea and adjacent Eurasian Basin would be of terrigenous
675
DOC in the Arctic Ocean
origin. In contrast, terrigenous dissolved organic nitrogen (DON) only accounted for 20 to 30% of the total DON (Kattner et al, 1999). However, as stressed by the authors, the distribution of DON is generally more influenced by biological processes, making this last estimate more uncertain. The fraction of terrigenous DOM in surface waters of the central Arctic Ocean was estimated from the carbon-normalized yields of lignin oxidation products (Ae) and (5^^C in ultrafiltered dissolved organic matter (UDOM) (Opsahl et al, 1999), resulting in 5-22% and 16-33%, respectively. The UDOM represents the highmolecular-weight fraction of DOM (>1 kDa), which is about 20-30% of total DOM. In Fig. 3 the mean values (ibvariability) of samples from the Kara Sea (low (5^^C), the polar surface water (medium 5^^C), and deep Fram Strait and Greenland Sea (high <5^^C) (Opsahl et al, 1999) are plotted versus A6. The polar surface water (32.04<5'<34.49) samples in this investigation were collected from submarines at depths of 38 to 165 m, within the SICEX program. Hence, these data do not include low-salinity surface waters. The relative contribution of terrigenous DOM in the polar surface water was computed from the mixing line of Fig. 3 to 15 ± 6%, where the error represents the extreme variability of the data. This computation is based on the same hypothesis as the estimate by Opsahl et al (1999), that the deep Fram Strait and Greenland Sea data represents marine-derived organic matter and the Kara Sea data represents terrigenous-derived organic matter. If A6 and 8^^C are conservative, the data would fall along a straight line, and the estimates of Opsahl et al (1999) and that from Fig. 3 would be equal.
-20 , Deep Fram Strait -21 -Pt.. and Greenland Sea -22 «
^-23. O S -24
P -25.
:
*
•
Polar Surface Water Kara Sea
-26-1 -27 H -28 0.0
—I—
0.2
—I—
0.4
—I—
0.6
— 1 —
0.8
1.0
AeCmg/IOOmgOC) Figure 3 The mean values (± standard deviation) of carbon normalized yields of lignin oxidation products (A6) versus stable carbon isotopic composition (5^^C) of DOM samples from the Kara Sea, the polar surface water and deep Fram Strait and Greenland Sea. The open circle indicates value from one sea ice sample. All data from Opsahl et al. (1999).
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Leif G.Anderson
Syringyl and vanillyl phenols are two of the oxidation products from lignin. The ratio of syringyl and vanillyl (SA^) has been shown to be an indicator of oxidative changes. Investigations suggest that the SA^ ratio is reduced by diagenetic alterations in the Atlantic and Pacific oceans (Opsahl and Benner, 1997). Likewise, photochemical degradation can selectively alter SA^ of terrigenous DOM oceans (Opsahl and Benner, 1998). Lobbes et aL (2000) showed that the S/V ratio also is a biomarker to distinguish between DOM originating from angiosperm plants (high SA^ ratios) and gymnosperms (low SA^ ratios) in Russian rivers entering the Arctic Ocean. Opsahl et al. (1999) determined the SA/^ ratio in UDOM for different regions of the Arctic Ocean, showing ratios not too different in the Kara Sea (0.3-0.5; n = 9) and central Arctic Ocean (0.12-0.31; n= 13) samples. Consequently, the relatively constant S A'^ ratio within the Arctic Ocean indicates a limited alteration of terrigenous DOM in this region.
B. C/N MOLAR RATIOS The molar ratio of C/N is the most studied property of DOM and can be used as a tracer for the origin of DOM. The C/N ratio is generally high in terrigenous DOM and low in marine DOM. An average C/N ratio of 20.5 ± 2.6 was reported for seven Siberian rivers (Gordeev et al, 1996, recalculated by Wheeler et al, 1997). Cauwet and Sidorov (1996) found a similar value (22) for the Lena river, while significantly higher ratios (30 to 58) were reported by Lara et al. (1998) for different locations along the Lena River. Lobbes et al. (2000) reported data from several rivers, where the mean C/N ratio for Yenisey, Olenek, Lena, Yana, and Indigirka was 47 ib 10. The variabiHty in the reported ratios is mainly a result of variable DON concentrations. The high C/N ratios of DOM in the runoff are characteristic of riverine fulvic acids (Thurman, 1985). The C/N ratio of marine DOM is dependent on biological activity in the investigated water mass. When the C/N ratio is plotted versus salinity for samples collected in the outer Laptev Sea, at the continental margin and in the eastern part of the Eurasian Basin, two regimes can be identified (Fig. 4). At salinities below 34.5 (depth <100 m), the C/N ratio increases with decreasing salinity (o in Fig. 4) and at saUnities above 34.5 (depth >100 m), the ratio varies from 12 to 30 (x in Fig. 4). The signature at 5'<34.5 is mainly a result of water of Atlantic origin mixing with runoff, supported by the intercept 49.7 at 5 = 0 of the fitted line. No trend but a large C/N span can be seen in the waters of iS'>34.5, which likely is a result of these samples being deep waters and thus have a signal affected by decay of sinking organic particulate matter. A large variability in the C/N ratio of DOM, ranging from 10 to 40 with a peak around 15, was also observed in the Fram Strait (Lara et al, 1998). The variable C/N ratio in marine dominated waters is a result of variable DON concentrations. This makes the C/N ratio less useful for
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DOC in the Arctic Ocean
30-
C/N = -0.943*S + 49.7 F^= 0.2799
25 H
,
O Q
o o o
I 20. c3
X
o
o o
15H
X X
o^o
X
10-
I
28
I
29
30
—r32 Salinity
31
33
"~T—
34
35
Figure 4 C/N ratio in dissolved organic matter (DOC/DON) in the eastern Eurasian Basin. Open circles represent S <34.5, crosses represent S >34.5. The linear regression line is fitted to the open circles. Data are from Fitznar (1999).
quantitative computations, but it is valuable as a qualitative tracer of terrigenous DOM.
C. DISTRIBUTION Too few DOC data are available from the central Arctic Ocean surface waters to produce a map of the concentration distribution. Several processes considerably influence the distribution by producing and consuming DOC. The relative importance of these processes can be seen in a DOC versus salinity plot of the surface waters with 5<34.5 (Fig. 5). A line representing the conservative mixing of Atlantic water (S = 34.926 and DOC = 60 /xM) and runoff (S = 0 and DOC = 550 jjM) is included as reference. Data with 5'>34 (Anderson et al, 1994; Opsahl et al, 1999) are spread around the mixing line, showing that consumption and production of DOC balance. At saHnities around 33, the Opsahl et al. (1999) data are below the mixing line, while the Anderson et al. (1994) data are above the mixing line. The latter is likely caused by biological activity as shown by Wheeler et al. (1997). Their data from the Arctic Ocean section 1994 show a similar trend (see Fig. 5 in Wheeler et al, 1997), but with fewer data above the mixing line.
LeifG. Anderson
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Salinity Figure 5 DOC versus salinity for the samples from the central Arctic Ocean with 5 <34.5. The open circles are data from the Oden 91 cruise (Anderson et al, 1994), while the square illustrates the range of data from Opsahl et al. (1999). A line representing the conservative mixing of Atlantic water {S = 34.926 and DOC = 60 /LIM) and river runoff (5 = 0 and DOC = 555 /AM) is included as a reference.
However, sea-ice meltwater also lowers the salinity, and the DOC concentration (316 ± 99 /xM; Melnikov, 1997) is lower in sea-ice meltwater than in the runoff. Nevertheless, the DOC concentration in the surface waters of the central Arctic Ocean is negatively correlated with salinity to a large degree. The DOC concentrations in Arctic Ocean deep waters are lower than in the inflowing Atlantic water (Opsahl et ai, 1999; Bussmann and Kattner, 2000). Opsahl et al. (1999) found 61 /xM in the inflowing Atlantic water of Fram Strait and 65 /xM in that recirculating in Fram Strait, while Bussmann and Kattner (2000) found 59 /xM (n = 37) in the Atlantic layer of the central Arctic Ocean. The mean deep-water concentration was 50 /xM in the Nansen Basin (n = 53), 54 /xM in the Amundsen Basin (n = 67), and 56 /xM in the Makarov Basin (Bussmann and Kattner, 2000). These values agree well with the observations in the outflowing deep waters from the Canadian and Eurasian Basins, 53 and 49 /xM, respectively (Opsahl et al, 1999). The difference in DOC concentration between the inflowing Atlantic water and the Arctic Ocean deep waters is in the order of 10 /xM, which is not much above the analytical range of accuracy. However, it is realistic to expect a higher DOC concentration in the Atlantic water relative to the Arctic Ocean deep waters as the former has been exposed to a larger flux of particulate organic matter from above. Furthermore, the Arctic Ocean deep waters have a long residence time (>100 years), with a limited flux of particulate organic matter from above,
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resulting in a DOC decomposition rate that could be larger than the production rate by decay of particulate organic matter. The lower DOC concentrations in the Arctic Ocean deep waters do not exclude an export of terrigenous DOM to the deep waters, as this is a function of sources and sinks. However, both the low concentration of lignin oxidation products and the predominance of a marine 8^^C signature indicate that terrigenous DOM is a minor contribution to the DOC of the deep waters of the Arctic Ocean (Opsahl et al, 1999).
IV. SUMMARY OF SOURCES AND SINKS A budget of the fluxes to and from the Arctic Ocean is given in Table III, based on measured concentrations of DOC and reported volume fluxes of the different waters. This budget does not distinguish between terrigenous and marine DOC. Generally the terrigenous DOC is high in the surface waters and low in the deep waters (Opsahl et al, 1999; Fitznar, 1999). It should be noted that the DOC budget of Table III is around 15% lower than that reported by Anderson et al (1998), a result of much new high-quality data being collected during the past few years, as referred to in Section III. The uncertainties given in Table III are based on the variability in reported DOC concentrations for the different water masses. No considerations of uncertainties in volume fluxes are included. Fortunately, the largest uncertainties are in the Atlantic and deep-water volumefluxesand these waters have a fairly constant DOC concentration. Consequently, an error in the volume influx has to be compensated by a comparable error in the volume outflux and hence have a small impact on the net DOC flux out of the Arctic Ocean. Adding the in- and outfluxes of Table III gives —5 ± 9x 10^^ g C year~\ indicating that the Arctic Ocean is neither a sink nor a source of DOC considering the uncertainty in the estimate. The in situ production of marine DOC within the central Arctic Ocean has been estimated to 6.1 g C m"-^ year~^ and the in situ respiration to 8.8 g C m~^ year~^ (Wheeler et al, 1997). Combining these numbers with the area of the deep central Arctic Ocean (5.8 x 10^^ m^) gives a total m^to production of 35 x lO^^gCyear"^ and a total in situ respiration of 51 x 10^^ g C year~^ These numbers are based on one summer investigation in a limited area and the uncertainties must be significant when applying them to a whole year and the whole central Arctic Ocean. Nevertheless, it is interesting to note that the in situ respiration of DOC exceeds that of in situ production of marine DOC, while the latter is of the same order as the added terrigenous DOC (35 x 10^^ g C year~^ relative to 23 x 10^^ g C year~^). These results indicate that the in situ respiration of DOC in the central Arctic Ocean will quantitatively consume all marine DOC produced in the central Arctic Ocean and some of that added by river runoff. This estimate does not include the DOC produced by the biota on the shelves.
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LeifG. Anderson Table III A Budget of the DOC Fluxes to and from the Arctic Ocean Water mass
Volume flux (Sv)
DOC (AtM)
Atlantic water Deep water Pacific water Runoff
2.5 0.58 0.83 0.11
58 ±5^^ 53 ± 5 ^ 71 ± 20^ 555 ± 50^
Total in
4.02
Organic carbon transport, (1012• g C year-i)
In
Out Sea ice From EB:
From CB:
Total out Net outflow
- Surface mixed layer - Halocline - Atlantic layer - Deep water - Surface mixed layer - Halocline - Atlantic layer - Deep water
0.11 0.165 0.25 0.9 0.42 0.362 0.54 0.698 0.575 4.02
55 12 22 23
±5 ±1 ±6 ±2
112 ± 8 316 ±50^ 82 ± 15/ 70 ± 6 / 58 ± 4 / 51 ± 5 ^ 100 ± 10/
75 ± nf 53d=4/ 55 lb 5^
13 ± 2 5±1 1± 1 20 ± 1 8±1 14 ± 1 15 ± 2 14 ± 1 12 ± 1 107 ± 4 -5
±9
Note. The volume fluxes of the water masses are from Anderson et al (1998), while the DOC concentrations are means of literature values. The river runoff includes all continental freshwater input, and outflows are from the Eurasian Basin (EB) and Canadian Basin (CB), respectively. As discussed in the text, errors in the organic carbon transport figures do not include errors in the volume fluxes. ^Mean of Wheeler et al (1997), Opsahl et al (1999), and (Bussmann and Kattner, 2000). ^Data in the Greenland Sea at 1800 m (Opsahl et al, 1999). ^Mean of Walsh et al (1997), Wheeler et al (1997), and Guay et al (1999). ^The mean of the regression lines at S = 0 of Figures 2B-D. ^Melnikov (1997). /Wheeler effl/. (1997). ^Mean of Opsahl et al (1999) and Bussmann and Kattner (2000).
Even if the Arctic Ocean itself is neither a sink nor a source of DOC there is a significant export of DOC to the North Atlantic. This flux (29 x 10^^ g C year"^) is a combined result of inflow from the Pacific Ocean (22 x 10^^ g C year"^), river runoff (23 x 10^^ g C year~^), and the difference between in situ production (35 X 10^^ g C year"^) and respiration (51 x 10^^ g C year"^) within the Arctic Ocean. The above arguments together with the balanced budget support the idea that terrigenous DOC is relatively stable within the Arctic Ocean.
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The finding that the outflowing deep water DOC concentrations are lower than (or very similar to) the inflowing water concentrations indicate (/) that little terrigenous DOM is exported to deep layers (as was also concluded by Opsahl et al, (1999) on the basis of lignin analysis) and (//) that little net export of marine DOM occurs to deep layers. The latter statement is supported by the arguments above that most marine DOC produced in the central Arctic Ocean is respired in the surface layers. The fact that little terrigenous DOC is exported to the deep waters of the Arctic Ocean through dense plumes originating on the shelves, where they are initiated by brine drainage from sea ice production, is an important finding as it put constraints on the global DOC budget. With regard to the total carbon budget in and out of the Arctic Ocean, the DOC fluxes are about 5% of the total carbon fluxes, calculated as the sum of inorganic and organic carbon. However, while the dissolved inorganic carbon concentration largely has a positive correlation with salinity, the DOC concentration has a negative one. Consequently, in situ production and respiration of DOC plays a relatively more important role for the carbon cycle in the low-salinity surface waters, relative to deeper layers, and it is the surface water that is in contact with the atmosphere linking the marine carbon cycle to climate.
ACKNOWLEDGMENTS Gerhard Kattner, Annelie Skoog, and Robert Benner gave valuable comments that helped improve the present manuscript. Financial support from the Swedish Research Council is greatly acknowledged.
REFERENCES Aagaard, K., and Carmack, E. C. (1989). The role of sea ice and other fresh water in the Arctic circulation. /. Geophys. Res. 94,14,485-14,498. Anderson, L. G., Bjork, G., Holby, O., Kattner, G., Koltermann, R K., Jones, E. P., Liljeblad, B., Lindegren, R., Rudels, B., and Swift, J. H. (1994). Water masses and circulation in the Eurasian Basin: Results from the Oden 91 North Pole Expedition. J. Geophys. Res. 99, 3273-3283. Anderson, L. G., Jones, E. P., and Rudels, B. (1999). Ventilation of the Arctic Ocean estimated by a plume entrainment model constrained by CFCs. /. Geophys. Res. 104,13,423-13,429. Anderson, L. G., Jones, E. P., and Swift, J. H. (2000). Export production in the central Arctic Ocean as evaluated from phosphate deficit. Submitted for publication. Anderson, L. G., Olsson, K., and Chierici, M. (1998). A carbon budget for the Arctic Ocean. Global Biogeochem. Cycles. 12,455^65. B0rsheim, K. Y., and Myklestad, S. M. (1997). Dynamics of DOC in the Norwegian Sea inferred from monthly profiles collected during 3 years at 66°N, 2°E. Deep-Sea Res. 44, 593-601. Bussmann, I., and Kattner, G. (2000). Distribution of dissolved organic carbon in the central Arctic Ocean: The influence of physical and biological properties. /. Mar. Sys. 27,209-219.
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Cauwet, G., and Sidorov, I. (1996). The biogeochemistry of Lena River: Organic carbon and nutrients distribution. Mar. Chem. 53, 211-227. Degens, E. T., Kempe, S., and Richey, J. E. (1991). Summary: Biogeochemistry of major world rivers. In "Biogeochemistry of Major World Rivers" (E. T. Degens, S. Kempe, and J. E Richey, Ed.), pp. 323-347. Wiley, New York. Fitznar, H. R (1999). D-Amino acids as tracers for biogeochemical processes in the river-shelf-oceansystem of the Arctic. Ber. Polarforsch. 334, [in German]. Fransson, A., Chierici, M., Anderson, L. G., Bussman, I., Kattner, G., Jones, E. P., and Swift, J. H. (2001). The importance of shelf processes for the modification of chemical constituents in the waters of the eastern Arctic Ocean. Com. Shelf Res. 21, 225-242. Gosselin, M., Levasseur, M., Wheeler, P. A., Homer, R. A., and Booth, B. C. (1997). New measurements of phytoplankton and ice algal production in the Arctic Ocean, Deep-Sea Res. II44, 1623-1644. Gordeev, V. V., Martin, J. M., Sidorov, I. S., and Sidorova, M. V. (1996). A reassessment of the Eurasian river input of water, sediment, major elements, and nutrients to the Arctic Ocean. /. Am. Sci. 296, 664-691. Guay, C. K., Klinghammer, G. P, Falkner, K. K., Benner, R., Coble, P G., Whitledge, T. E., Black, B., Bussel, F. J., and Wagner, T. A. (1999). High-resolution measurements of dissolved organic carbon in the Arctic Ocean by in situ fiber-optic spectrometer. Geophys. Res. Lett. 26,1007-1010. Hansen, D. A., and Carlson, C. A. (1998). Net community production of dissolved organic carbon. Global Biogeochem. Cycles. 12,443^53. Hansen, D. A., Whitledge, T. E., and Goering, J. J. (1993). Patterns of nitrate utilization and new production over the Bering-Chukchi shelf. Cont. Shelf Res. 13,601-628. Hulth, S., Hall, P O. J., Blackburn, T. H., and Landen, A. (1996). Arctic sediments (Svalbard): Pore water and solid phase distributions of C, N, P and Si. Polar Biol. 16,447^62. Hulthe, G., and Hall, P. (1997). Benthic carbon fluxes—DOC versus ECO2 in shelf, slope and deep-sea environments, and relation to oxygen fluxes. Rep. Polar Res. 22^, 115-116. Jones, E. P., Anderson, L. G., and Swift, J. H. (1998). Distribution of Atlantic and Pacific waters in the upper Arctic Ocean: Implications for circulation. Geophys. Res. Lett. 25,765-768. Jones, E. P., Rudels, B., and Anderson, L. G. (1995). Deep waters of the Arctic Ocean: Origin and circulation. Deep-Sea Res. 42,131-160. Kattner, G., Lobbes, J. M., Fitznar, H. P, Engbrodt, R., Nothig, E.-M., and Lara, R. J. (1999). Tracing dissolved organic substances and nutrients from the Lena River through Laptev Sea (Arctic). Mar Chem. 65, 25-39. Lara, R. J., Rachold, V., Kattner, G., Hubberten, H. W, Guggenberger, G., Skoog, A., and Thomas, D. N. (1998). Dissolved organic matter and nutrients in the Lena River, Siberian Arctic: Characteristics and distribution. Mar Chem. 59, 301-309. Lobbes, J. M., Fitznar, H. P., and Kattner, G. (2000). Biogeochemical characteristics of dissolved and particulate organic matter in Russian rivers entering the Arctic Ocean. Geochim. Cosmochim. Acta. 64, 2973-2983. Macdonald, R. W, Carmack, E. C , McLaughlin, F. A., Iseki, K., Macdonald, D. M., and O'Brien, M. C. (1989). Composition and modification of water masses in the Mackenzie shelf estuary. J. Geophys. Res. 94,18,057-18,070. Melnikov, I. A. (1997). "The Arctic Ice Ecosystem." Gordon and Breach Science Pubhsher, The Netherlands. Menard, H. W., and Smith, S. M. (1966). Hypsometry of ocean basin provinces. /. Geophys. Res. 71, 4305^325. Olsson, K., and Anderson, L. G. (1997). Input and biogeochemical transformation of dissolved carbon in the Siberian shelf seas. Cont. Shelf Res. 17, 819-833. Opsahl, S., and Benner, R. (1997). Distribution and cycling of terrigenous dissolved organic matter in the ocean. Nature. 386,480-482.
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Opsahl, S., and Benner, R. (1998). Photochemical reactivity of dissolved lignin in river and ocean waters. Limnol. Oceanogr. 43,1297-1304. Opsahl, S., Benner, R., and Amon, R. M. W. (1999). Major flux of terrigenous dissolved organic matter through the Arctic Ocean. Limnol Oceanogr. 44,2017-2023. Pocklington, R., (1987). "Arctic rivers and their discharge," Vol. 64, pp 261-268. Mitt. Geol.-Palaontol. Inst. Univ., Hamburg. Rudels, B., Anderson, L. G., and Jones, E. P. (1996). Formation and evolution of the surface mixed layer and halocline of the Arctic Ocean. /. Geophys. Res. 101, 8807-8821. Rudels, B., Jones, E. P., Anderson, L. G., and Kattner (1994). On the intermediate depth waters of the Arctic Ocean. In "The Polar Oceans and Their Role in Shaping the Global Environment" (O. M. Johannessen, R. D. Muench, and J. E. Overland, Eds.), pp. 3 3 ^ 6 . American Geophysical Union, Washington, DC. Sakshaug, E., and Skjoldal, H. R. (1989). Life at the ice edge. Ambio. 18,60-67. Schauer, U., Muench, R., Rudels, B., and Timokhov, L. (1997). The impact of eastern Arctic shelf waters on the Nansen Basin intermediate layers. J. Geophys. Res. 102, 3371-3382. Schlosser, P., Bauch, D., Fairbanks, R., and Bonisch, G. (1994). Arctic river-runoff: mean residence time on the shelves and in the halocline. Deep-Sea Res. 41,1053-1068. Slagstad, D., and Wassmann, P. (1996). Climate change and carbon flux in the Barents Sea: 3-D simulations of ice-distribution, primary production and vertical export of particulate organic carbon. Mem. Nat. Inst. Polar Res. 51,119-141. Smith, R. E. H., Gosselin, M., Kudoh, S., Robineau, B., and Taguchi, S. (1997). DOC and its relationship to algae in bottom ice conununities. /. Mar. Syst. 11,71-80. Swift, J. H., Takahashi, T, and Livingstone, H. D. (1983). The contribution of the Greenland and Barents Seas to the deep water of the Arctic Ocean. /. Geophys. Res. 88, 5981-5986. Telang, S. A., Pocklington, R., Naidu, A. S., Romankevich, E. A., Gitelson, L I., and Gladyshev, M. L (1991). Carbon and Mineral Transport in Major North American, Russian Arctic, and Siberian Rivers: The St. Lawrence, the Mackenzie, the Yukon, the Arctic Alaskan Rivers, the Arctic Basin Rivers in the Soviet Union, and the Yenisey. In "Biogeochemistry of Major World Rivers" (E. T. Degens, S. Kempe, and J. E. Richey, Eds.), pp. 75-104. Wiley, New York. Thomas, D. N., Lara, R. J., Eicken, H., Kattner, G., and Skoog, A. (1995). Dissolved organic matter in Arctic multi-year sea ice during winter: Major components and relationship to ice characteristics. Polar Biol. 15,417-4S3. Thurman, E. M. (1985). Aquatic humic substances. In "Organic Geochemistry of Natural Waters," pp. 273-361. Nijhoff/Junk PubHshers, Dordrecht. Walsh, J. J., Dieterle, D. A., MuUer-Karger, F. E., Aagaard, K., Roach, A. T, Whitledge, T. E., and Stockwell, D. (1997). CO2 cycling in the coastal ocean. II. Seasonal organic loading of the Arctic Ocean from source waters in the Bering Sea. Cont. Shelf Res. 17,1-36. Wheeler, P. A., Watkins, J. M., and Hansing, R. L. (1997). Nutrients, organic carbon and organic nitrogen in the upper water column of the Arctic Ocean: Implications for the sources of dissolved organic carbon. Deep-Sea Res. II44,1571-1592.
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Chapter 15
DOC in the Global Ocean Carbon Cycle Dennis A. Hansell^ Bermuda Biological Station for Research, Inc., St. Georges Bermuda
I. Introduction II. Distribution of DOC A. Spatial Variability at the Basin Scale B. Temporal Variability III. Net Community Production of DOC A. Evidence for Net Production of DOC B. Regional and Global Estimates for Net Production of DOC
C. Nutrient Depletion and Net Production of DOC IV. Contribution of DOC to the Biological pump A. Evidence for DOC Export B. Exportable DOC V. Research priorities VI. Summary References
L INTRODUCTION Dissolved organic carbon (DOC) makes up the second largest of the bioreactive pools of carbon in the ocean (680-700 Pg C; WilHams and Druffel, 1987; Hansell and Carlson, 1998a), second to the very large pool of dissolved inorganic carbon (38,000 Pg C). The size of the reservoir, as well as its positions as a sink for autotrophically fixed carbon and as a source of substrate to microbial heterotrophs, ^ Present address: University of Miami, Rosenstiel School of Marine and Atmospheric Science, 4600 Rickenbacker Causeway, Miami, FL 33149. Biogeochemistiy of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
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indicates that DOC plays a central role in the ocean carbon cycle. But what is this role, how is it realized, and what are its mechanisms and controls. The fundamentals of these questions have remained unchanged over the past 40 years (Duursma, 1962) and continue to challenge the ocean carbon research community today. A considerable amount of financial and intellectual capital has been expended and significant progress has been made over the past decade. DOC concentrations in the ocean range from a deep-ocean low of 34 JJLM to surface-ocean highs of >90 jxM (Section II). Biological processes set up this vertical gradient (net production at the surface and net consumption at depth), while certain physical conditions (high vertical stability) are required to maintain the gradient (Section II.A). The bulk DOC in the ocean can be resolved into at least three fractions, each qualitatively characterized by its biological lability (see Carlson, Chapter 4). All ocean depths contain (1) the very old, biologically recalcitrant DOC (see Bauer, Chapter 8). Its distribution is thought to be fairly uniform in the ocean, largely comprising the DOC of the deep ocean. Built upon the recalcitrant DOC at intermediate and upper layer depths is (2) material of intermediate (or semi-) lability (months to years). It is this material that is produced in the surface ocean and then mixed into the main thermocline, thereby reducing the vertical concentration gradient and contributing to carbon export (Section IV). Concentrations of this fraction can be 10-30 /xM in the upper ocean, and near zero in the deep ocean. The surface ocean alone contains (3) the highly biologically labile fraction of DOC, with lifetimes of days to months and concentrations of just a few to tens of micromolar of C. This latter material is most important for supporting the microbial heterotrophic processes in the ocean (see Carlson, Chapter 4) and shows high variability seasonally. In this chapter, the role of DOC in the ocean carbon cycle is considered in its broadest temporal and spatial scales. The chapter begins with an evaluation of the spatial distribution of DOC at the regional and basin scales, in both the surface and deep ocean. In this context, the distribution of DOC relative to the distribution and timing of marine productivity is evaluated. The older data sets reporting DOC distributions are appraised here as well. The next Section evaluates temporal variability, with consideration of how DOC varies seasonally from high to low latitudes. Following the assessment of variability, the net community production of DOC is examined. The focus is on DOC that accumulates for durations with biogeochemical relevance. This Section is followed by an evaluation of the contribution of DOC to the biological pump. We examine the mechanisms and locations of DOC export, and thus develop an understanding of the controls on export. The chapter concludes with priorities for present and future research, as well as a brief synthesis of the findings reported. Note that organic carbon in the ocean is distributed between the dissolved and particulate (POC) fractions. Summed, these fractions are referred to as total organic carbon (TOC). It is common to measure TOC directly in the water column
DOC in the Global Ocean Carbon Cycle (analysis of unfiltered water), even when DOC is the pool of interest, when the POC concentrations are very low relative to the DOC concentrations. This situation is common at ocean depths well below the surface layer (at depths >200 m), as well as in some surface ocean regions where POC concentrations are normally a few micromolar. The latter conditions are found in the oligotrophic ocean and in highlatitude systems during winter. In these situations (deep water and low-POC surface water), TOC serves as a very close approximation to the DOC concentrations. A primary reason for measuring TOC in these waters, rather than measuring DOC directly, is to avoid contamination by handling (filtering, transfers, etc.) the sample. The term DOC is used in this chapter both for true DOC analyses, and when TOC was measured in deep or POC-impoverished surface waters. The term TOC is reserved for use when DOC and POC, measured separately, are sunmied.
11. DISTRIBUTION OF DOC A. SPATIAL VARIABILITY AT THE BASIN SCALE During the decades leading up to the 1990s, DOC data were relatively sparse because relatively few laboratories made the measurements. An early body of work that stands as providing some of the greatest spatial coverage of an ocean region is that by Duursma (1962). He conducted extensive DOC surveys in the northern reaches of the Gulf Stream and its offshoots south of Greenland, finding the spatial variability associated with hydrographic features that we would likely find today. Since his early work, the few additional ocean sections occupied in the decades leading to the 1990s produced data of uncertain quality (see discussion by Wangersky, 1978, and below). Consequently, our sense for the distribution of DOC in the ocean has been highly uncertain. In this discussion, findings from recently occupied sections in various ocean basins will be discussed (locations identified in Fig. 1) and some of the older sections evaluated. 1. Upper Ocean Distributions Meridional sections from the eastern and western South Pacific and the central Indian Ocean show that the highest upper ocean DOC concentrations are typically found in the low to mid latitudes (Fig. 2 [see color plate]). Concentrations decrease into colder water, whether as a horizontal gradient along the surface from low to high latitudes or vertically with increasing depth. Vertical stability provided by the main thermocline of the open ocean supports the accumulation of DOC in the surface waters. Where vertical stability is strong, DOC concentrations are relatively high; where stability is weak, DOC concentrations can remain at low levels (Fig. 2c). The cold, deep waters have the lowest concentrations, and where
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Figure 1 Map depicting locations in the global ocean from which data are shown in this chapter. The solid Unes (gray) represent ocean sections; the triangles are the sites of the time-series stations near Bermuda and Hawaii; the filled circles and the triangles are the sites of the deep-water DOC analyses in addition to the time series sites.
these waters ventilate at high latitudes, similarly low DOC values are present (Figs. 2b and 2c). Where low-DOC, subsurface water mixes to the surface its impact is felt in the surface DOC concentrations. Upwelling sites, both in coastal regions and along the equator, normally have relatively low DOC values at the surface where upwelling is strongest. In the central Equatorial Pacific, DOC is depressed at the surface because of upwelling (note the upward doming of the subsurface DOC contours at the equator; Figs. 2b and 2c). In the central Indian Ocean, where equatorial upwelling is weak, DOC is rather uniform from the subtropical gyre to across the equator (Fig. 2a). DOC along the equator in the Pacific shows the controls by hydrography and biology (Fig. 3 [see color plate]). The Equatorial Undercurrent, near 200 m west of the dateline, has a DOC concentration of ~55 /xM (Hansell et al, 1997b). This water is transported to the east, shoaUng to near surface in the central and eastern Equatorial Pacific, bringing with it low-DOC water. The return flow of surface water to the west undergoes an increase in DOC (to ~65 /xM) due to biological activity. The highest DOC concentrations in Fig. 3 (>70 /xM C; largely west of 165° W in the surface 100-120 m) are associated with the Western
DOC in the Global Ocean Carbon Cycle Pacific Warm Pool (Hansell et al, 1997b; Hansell and Feely, 2000). The front separating the DOC-enriched Warm Pool to the west and the recently upwelled water to the east varies with the ENSO state, being found further to the west during La Nina conditions (Dunne et al, 2000). The impact of upwelling on equatorial DOC concentrations exists at coastal upwelling sites as well. Along the coast of Oman in the Arabian Sea, strong upwelling occurs during the Southwest Monsoon. Low surface DOC concentrations are present in coastal water during such periods although productivity can be quite high (Hansell and Peltzer, 1998). UpwelUng along the northwest margin of the African continent similarly forces a shoaling of the DOC isolines (Postma and Rommets, 1979). Similarly, Doval et al (1997) reported a decrease in subsurface DOC in northwest Spain due to upwelling. Ocean margins influenced more by riverine inputs than by upwelling tend to show increases in DOC concentrations. Rivers introduce water with high DOC concentrations (see Cauwet, Chapter 12), thus raising concentrations along the coast. One example is in the Chesapeake Bay outfall, where DOC concentrations increase from 70 ^xM in the surface Sargasso Sea to >200 JJM in the Chesapeake Bay mouth (Bates and Hansell, 1999). Guo et al (1994) reported onshore DOC concentrations of 131 /xM off Galveston, Texas, and moderate concentrations of 83 /xM offshore in the Gulf of Mexico. Property/property plots of DOC and salinity show the conservative nature of riverine DOC as it mixes with oceanic water. In general, the strength and direction of concentration gradients between the surface open ocean and the coastal ocean depend on the degree of upwelling of low-DOC water from below or invasion of DOC-enriched freshwater from the continent. Comparing two zonal sections in the North Atiantic provides further evidence for the control physical properties of the water column play on DOC distributions (Fig. 4 [see color plate]). A Section at 24°N shows strongly enhanced DOC concentrations in the upper 200 m (up to 80 /xM C), reflecting the strong stratification present in the subtropical gyre. In a more northerly Section, surface DOC is lower (>60 jjM C) and the concentration contours are pushed deeper into the water column. Note, for example, the 55 /xM DOC contour at 200-300 m along 24°N, but at 200-600 m on the northern Section. This change in contour depths reflects the weaker stratification at higher latitudes, and subsequent downward mixing of the surface produced DOC. 2. Deep-Ocean Distributions Reports on the distribution and variability of DOC in the deep ocean have been conflicting. Measurements from the 1960s (discussed below) suggested strong, horizontal gradients in DOC. More recently, Druffel et al (1992) reported a modest 5 /xM concentration difference between the deep waters near Bermuda and Hawaii. Martin and Fitzwater (1992), in contrast, reported the complete absence of DOC
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gradients in the deep ocean. Hansell and Carlson (1998a), in an effort to narrow the uncertainty, surveyed representative sites in the deep ocean (Fig. 1). They found a 29% decrease in DOC concentration from the northern North Atlantic (48 /xM in the Greenland Sea) to the northern North Pacific (34 /JM in the Gulf of Alaska) (Fig. 5, top). The gradient reflects the export of DOC-enriched (formerly subtropical) water during North Atlantic deep water (NADW) formation (Fig. 5, bottom) and the decrease in DOC (by mineralization and mixing) along the path of deep ocean circulation away from the North Atlantic. The formation of Antarctic bottom water (AABW) does not introduce additional DOC to the deep ocean (see Section IV), so the concentrations remain low near those sites. The small increase in DOC concentrations from the Southern Ocean into the deep South Pacific and Indian oceans is enigmatic and the source unidentified (Hansell and Carlson, 1998a). Possible causes include inputs from marginal seas (Red Sea, Arabian Sea, and Bay of Bengal for the Indian Ocean), inputs due to dissolution of sinking biogenic particles, non-steady-state conditions in the deep-ocean concentration gradients of DOC, and, of course, unidentified processes. The highest deep-water DOC concentrations may be those in the deep Eurasian Basin of the Arctic Ocean (see Anderson, Chapter 14), where concentrations >50 /j^M C have been reported (Anderson et aL, 1994). The sources of this material must be terrestrial runoff and Arctic continental shelf produced DOC (Opsahl et aL, 1999; Wheeler etai, 1997). It is interesting to speculate as to the mechanisms responsible for DOC concentration decreases in the deep ocean. Certainly microbial mineralization and mixing contribute, but, based on our present knowledge, these mechanisms appear to be inadequate. The DOC concentration decreases by 14 /xM over the length of the deep limb of the "global conveyor belt," but would the marine microbes we are most familiar with today be satisified with such meager rations over the half millennium required for transport over that distance? The apparent rate of oxidation (^30 nM year"^ over ^500 years), and the amount of energy derived over these several centuries, is miniscule. Perhaps the poorly understood Archaea, now known to inhabit the deep ocean, are designed to catabolize recalcitrant DOC at such low rates. Perhaps microbes play only a secondary role, and DOC is removed primarily by coagulation and formation of sinking particles, or it is stripped from the water column by particles passing through the water colunm. The true mechanisms for DOC loss need to be resolved. 3. Relation to Productivity Given the surface DOC distributions described here (Fig. 5), of low DOC near sites of upwelling or deep mixing and high values in stratified water, a general observation can be made: upper ocean DOC concentrations are relatively high in oligotrophic waters where regenerated production dominates, and low in systems
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DOC in the Global Ocean Carbon Cycle 50
Pacific/Indian Sector
Indian
32' 80°N
40"N
80°S
40"S
40°S
40°N
80"N
Latitude
Atlantic Sector
Pacific/Indian Sectors
av^ace NPOH^//
AABW
North
Circumpolar water
South
CDW North
Figure 5 (Top) Distribution of DOC in the deep-ocean. The x-axis is viewed in the context of the deepocean circulation, with fonnation in the North Atlantic, circulation around the Southern Ocean, and flow northward into the Indian and Pacific oceans. Station locations in Fig. 1. (Bottom) The general patterns of ocean circulation driving the deep ocean DOC signal. DOC-enriched surface water is introduced to the deep ocean in the North Atlantic. This water moves south as North Atlantic deep water (NADW), to the circumpolar waters of the Southern Hemisphere. DOC-impoverished Circumpolar deep water (CDW) flows north into the Pacific and Indian oceans. Deep return flow to the North Atlantic is via Antarctic bottom water (AABW) and to Antarctica via North Pacific (NPDW) and Indian Ocean deep waters (lODW).
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where new nutrients are introduced to the surface. Such a meridional gradient has been reported for the Equatorial Pacific (Tanoue, 1993), the South Pacific (Hansell and Waterhouse, 1997; Doval and Hansell, 2000) and the North Atlantic (Duursma, 1962; Kahler and Koeve, 2001) and is evident in Fig. 2. The regenerated vs new production nature of these systems is a reflection of the conmiunity compositions within them. The mechanisms by which conununity composition controls DOC concentrations are not understood (see Carlson, Chapter 4). DOC concentrations are also controlled by the vertical stability of the water colunm. The highest DOC concentrations in the open ocean are normally found where stratification of the water column is highest (Hansell and Waterhouse, 1997; Hansell and Feely, 2000). This finding suggests that stability facilitates the retention of DOC in the upper ocean. The lowest DOC concentrations, to the contrary, exist where DOC-depleted subsurface water is introduced to the surface, either by vertical mixing or upwelling. These high nutrient sites can experience large but brief seasonal increases in DOC concentrations, however (see below). Because of the role of ocean stratification in controlling DOC concentrations, a positive correlation between DOC concentrations and primary productivity (an oft predicted relationship) is absent in much of the oligotrophic, open ocean. Menzel and Ryther (1970) reported the absence of this correlation early and evidence for the generality will be given using data from the Sargasso Sea later in the chapter (Section II.B.2). In fact, in the highly stratified portions of the open ocean, DOC broadly correlates positively with temperature (Hansell and Waterhouse, 1997; Doval and Hansell, 2000), another sign of the importance of physical control on concentrations. At higher latitudes, however, where DOC concentrations are depressed during the winter, elevated DOC values indeed follow springtime elevation of primary productivity (Borsheim and Myklestad, 1997; Chen et al, 1996; Carlson et al, 2000). This positive relationship between primary production and DOC was reported early by Duursma (1963) and has been discussed elsewhere (Williams, 1995). In high-latitude systems, increased water colunm stability favors both phytoplankton growth and DOC accumulation in the upper ocean. The data indicate that low-latitude, highly stratified environments behave very differently than high-latitude environments in terms of the coupling between DOC dynamics and primary production. So, while their observations are in apparent conflict, both Menzel and Ryther (1970) and Duursma (1963) were correct about the relationship between DOC and productivity; but they were correct specifically for the hydrographic systems they were evaluating. 4. Historical Data With the onset of discussions surrounding the use of the high-temperature combustion (HTC) systems for DOC analysis (Sugimura and Suzuki, 1988), much attention has been paid to whether or not the earlier data are accurate and, therefore,
DOC in the Global Ocean Carbon Cycle of value (Sharp, 1997). A comparison of what we find in the ocean today with that reported in earlier decades shows some older data and findings to have serious flaws. A comparison of historical and recent data from the surface ocean cannot be easily made because of the wide natural variability in those waters (see below). The most useful comparisons between historical and recent data are made in the intermediate and deep ocean, where significant changes in concentration over a few decades (the sampling interval) are unlikely. Menzel (1964) reported DOC concentrations in the intermediate depths (400800 m) of the Arabian Sea and western Indian Ocean to range from 0.4 to 1.6 mg/L (30 to 130 /xM DOC). This wide range is not reproducible anywhere in the intermediate or deep ocean using modem techniques, nor was it evident during the US Joint Global Ocean Flux (US JGOFS) program in the Arabian Sea during 1995 (Hansen and Peltzer, 1998). Menzel and Ryther (1970) also reported a very unlikely DOC concentration doubling at all depths > 1000 m between the waters northeast and southeast of South America. Romankevich and Ljutsarev (1990), reviewing investigations conducted by the Soviet Union, reported DOC off Peru at 500-1000 m to be an unlikely 1 mg/L (^83 /xM). Soviet measurements in the deep Bay of Bengal exceeded 1 mg/L as well. These latter DOC concentrations are probably high by a factor of two. Williams et al (1980) reported DOC concentrations in the central North Pacific a few meters off bottom (5650 m) that were elevated by twofold relative to the values at 2000-5000 m. Such a strong DOC gradient, indicative of sedimentary input of DOC to the bottom layer, has not been confirmed using modem techniques and extensive near-bottom surveys. Recent data, using modem HTC techniques, should be viewed with caution as well. Dileep Kumar et al. (1990) reported a strong DOC concentration gradient from the central Arabian Sea to the westem Indian Ocean, increasing from 100 to 300 /zM at 2500 m. The high DOC concentrations and wide range reported are unlikely to be accurate representations of that system.
B. TEMPORAL VARIABILITY The temporal variability of DOC concentrations in the surface ocean has been noted since the earliest days of the measurement. Duursma (1963) reported a twofold increase in DOC concentrations in the North Sea, from winter lows of 0.8 mg/L (~66 jiM) to spring and early summer highs of 1.8 mg/L (~150 /xM). The increase in DOC concentrations started some weeks after the spring phytoplankton bloom. Holmes et al. (1967) reported large spikes in DOC concentrations, from a baseline of 1 mg/L up to 4-5 mg/L (330-415 /xM), during several red water dinoflagellate blooms off La JoUa Bay, Califomia. Here, too, the DOC peaks followed the decline of the blooms. Williams (1995) evaluated the seasonal accumulation of DOC using data from Parsons et al. (1970), Banoub and WiUiams (1973),
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and Duursma (1963), suggesting that the accumulation of C-rich dissolved organic matter resulted from nitrogen limitation. The possible role of nutrient depletion in the generation of DOC is discussed below. (See Carlson, Chapter 4, for a more complete listing of publications reporting temporal variability of DOC.) 1. High Latitudes Strong seasonal increases in DOC concentrations associated with phytoplankton blooms appear to be characteristic of systems that receive high input of new nutrients over the winter periods. The waters of the Ross Sea polynya, for example, undergo deep mixing over the winter such that nitrate concentrations exceed 30 fiM prior to the spring bloom (Bates et ai, 1998). DOC concentrations increase in the surface layer from winter lows of 42 /xM to summer highs of 65-70 /xM (Carlson etai, 1998). High southern latitude systems can experience large increases in DOC concentrations (tens of micromolar C), with the wintertime baseline concentration as low as the much deeper waters (Carlson et aL, 2000; Wiebinga and de Baar, 1998; Kahler et aL, 1997). The Ross Sea undergoes DOC concentration increases of 15-30 /xM where the Phaeocystis and diatom blooms are particularly strong (Carlson etal, 2000). Where the blooms are small because of various controls on plant growth (deep mixing, iron limitation, etc.), the DOC concentrations remain low (e.g., over the Ross Sea shelf break, with a gain of <5 JJLM relative to winter) (Sweeney et aL, 2000). The North Sea (Duursma, 1963), as well as other highlatitude/strong-bloom regions (e.g., the Norwegian Sea, Borsheim and Myklestad, 1997), likely behaves similarly to the Ross Sea. In Trondheimsfjord, Borsheim et aL (1999) reported a >2x increase in DOC concentrations during the summer. It is apparent, though, that the winter lows of DOC concentrations in the high northern latitudes are not as low as the local deep-water values (in contrast to the conditions found in the Southern Ocean). This finding holds true along 20°E in the North Atlantic, where Kortzinger et aL (2001) reported the winter low DOC to be 53 fiM C, well above the deep-ocean values in the region. The more physically stratified nature of the northern systems prevents full water column overturn and homogenization of the DOC each winter. 2. Mid-latitudes The more oligotrophic, mid-latitude zones of the ocean do not show the same seasonality (in either strength or direction) as the high latitudes or other nutrientrich areas. In the Sargasso Sea, where convective overturn during the winter introduces small amounts of new nutrients to the euphotic zone and phytoplankton blooms follow (Michaels and Knap, 1996), the seasonality of DOC in the surface ocean contrasts that found at high latitudes (Carlson et aL, 1998; Hansell and Carlson, 2001a). Overturn of the water column coincides with the spring bloom
DOC in the Global Ocean Carbon Cycle there because adequate light is present at these mid latitudes. The effect is to mix low DOC subsurface water upward, thereby reducing the DOC concentrations during the periods of highest primary productivity. Once stratification reasserts itself with warming of the surface ocean, and the bloom terminates, DOC concentrations rebuild to normal summer levels (Fig. 6 [see color plate]). The concentration change from the annual low to the annual high is only 3-6 /xM, a very small range compared to high-latitude systems. The lowest winter concentrations remain well above the deep-water values. While the DOC concentrations in the Sargasso Sea are lowest during the winter overturn/spring bloom period, the same cannot be said for the integrated DOC stocks. Relatively deep convective overturn maintains the low surface DOC concentrations but the bloom still supports the net production of as much as 1-1.5 mol m"^ of DOC over the upper 250 m (Fig. 7; Carlson et al, 1994; Hansen and Carlson, 2001a [see color plate]). This increase in DOC stock is as large as that seen in the much more productive Ross Sea (Carlson et al, 2000). DOC and bloom dynamics in the Arabian Sea during the NE Monsoon are similar to that in the Sargasso Sea. Convective overturn in the Arabian Sea, forced by cool dry winds off the Tibetan plateau, mixes moderate amounts of nutrient into the euphotic zone. There, too, DOC concentration changes are not large during the bloom, but the increase in DOC stock can be 1.5-2 mol C m~^ (Hansell and Peltzer, 1998). It is interesting that while the seasonal range for DOC in the western Sargasso Sea (at ~31°N) is only 3-6 luM, the seasonal range at the same latitude in the eastern North Atlantic can reach 10-20 /xM (Kortzinger et al, 2001). The western North Atlantic is generally warmer and more stratified than in the east, suggesting differing community composition and productivity between the sites. This follows from the gyre circulation patterns: the northward flow of water in the west, from the warm equatorial region to higher latitudes, lends itself to high vertical stability and highly oligotrophic conditions; the southern flow in the east, carrying cooler water from the north, would lend itself to less stability and less oligotrophic conditions. It may be that the more stable system in the west experiences less primary productivity and net DOC production than the system in the east. Physical characteristics of the systems and the biological regimes they support are centrally important in controlling DOC dynamics. 3. Low Latitudes Low-latitude systems that do not undergo winter freshening of the surface layer do not show seasonality in DOC concentrations. The waters at Station ALOHA, north of Hawaii at 23°N, represent such a system. There, variability in DOC occurs at interannual time scales, but there is no recurring trend with seasons (Fig. 6). Church et al (2001) reported a net accumulation from 1993 to 1999 of a DOM
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pool that was enriched in C and N, relative to P. These long-term changes may be a manifestation of the broad, ecosystem-wide shift from N to P limitation described by Karl (1999). No such shifts have been noted in the Sargasso Sea, hence the near constancy in summer time DOC highs from year to year. Note that the surface DOC concentrations at ALOHA are much higher than the highs at BATS (Fig. 6) and higher than any values found along 24°N in the North Atlantic (Fig. 4). Why this difference exists between these similarly low latitude zones of the North Atlantic and North Pacific is unknown. Community composition may be key, but an evaluation has not been conducted. 4. Deep Ocean Whether or not there is measurable temporal variability of DOC in the deep ocean remains debatable. Hansell and Carlson (2001a) did not resolve DOC variability in the deep Sargasso Sea over 6 years of time series measurements. Similarly, Hansell and Peltzer (1998) found no variability in the deep Arabian Sea over a single year, even through periods of very high sinking particle flux. Bauer et al (1998), in contrast, reported significant (8 /xM) long-term (2-year) changes in DOC in the deep eastern North Pacific. They tied these variations to natural variability ("patchiness") and exchanges with sinking POC. Why there may be variability at this site and not at the others studied needs to be resolved. 5. Short-Term Biological Events Further variabiUty in DOC concentrations can be expected to occur with biological "events." Examples are blooms of red tide organisms described by Holmes et al (1967) and of diazotrophs. Onset of enhanced nitrogen fixation rates in openocean systems can increase DOM stocks considerably. Karl et al. (1997) reported organic nitrogen concentration increases of several micromolar which should coincide with several tens of micromolar increase in DOC. A case in point is the western tropical South Pacific, where relatively high DOC is present under the zone of the atmospheric South Pacific Convergence Zone. Hansell and Feely (2000) suggested that the excess precipitation in this system increased vertical stability, thereby favoring nitrogen fixers and in turn increasing concentrations of DON and DOC. Near the continental margins, DOC concentrations will vary with the strength of DOC-enriched riverine inputs or coastal upwelling, both of which vary seasonally (Cauwet, Chapter 12; Hansell and Peltzer, 1998). High riverine input may result in high-DOC concentrations; strong upwelling reduces the DOC concentrations. Zones of equatorial upwelling similarly exhibit the lowest DOC concentrations during strong upwelling (e.g., La Nina), and the highest values during reduced upwelling (e.g.. El Nino; Peltzer and Hayward, 1996). In this way, physical stability plays a major role in controlling DOC concentrations both along the margins, in
DOC in the Global Ocean Carbon Cycle the open ocean and in equatorial upwelling systems (Carlson and Ducklow, 1995; Hansen and Waterhouse, 1997; Tanoue, 1993). 6. Summary Our present understanding of seasonal variability in DOC can be summarized here: At high latitudes, where spring blooms are intense, we expect to see large DOC concentration changes. Because the winter DOC concentrations are low in these high-latitude systems, the highest concentrations during sunmier may be no higher than the summer highs in the low-latitude gyre systems, but the concentration change between seasons may be large. However, the large increases in concentration do not necessarily translate into large accumulations of DOC stock (vertically integrated loads of DOC) because of the normally shallow euphotic zones in these highly productive systems (high concentrations but over little depth). In mid-latitude open-ocean regions, such as the Sargasso and Arabian Seas, where convective overturn introduces moderate nutrient loads, DOC concentration ranges between seasons can be relatively small, though the change in integrated stocks can be a relatively large signal (comparable to the change in DOC stock in the Ross Sea). The overturning water column mixes the DOC too deeply for a strong surface accumulation to occur, as found in blooms occurring in more stratified systems but the small concentration change over large depths results in significant increase in stock. At mid-latitude coastal sites with significant winter recharge of surface nutrients, DOC seasonality will be strong. Upwelling reduces the DOC concentrations while high riverine inputs increase them. At low-latitude sites where spring blooms are absent, no seasonality is evident; but, as with all ocean regions, interannual variability exists. The DOC that accumulates each year at mid-latitudes has a lifetime exceeding the season in which it was produced, so it can be transported elsewhere with surface currents, or be available for export during the subsequent winter overturn events. At higher latitudes, the seasonally produced DOC is seen to have a lifetime shorter than that of the season of production; thus it undergoes net consumption by microbes once primary production is reduced with the onset of Fall conditions. This material is not as available for export (see Section IV.A).
III. NET COMMUNITY PRODUCTION OF DOC DOC is produced on a daily basis as part of the primary and secondary production systems in the surface ocean. Most of the DOC released is mineralized on the time scale of hours to days. For DOC to play a role in the ocean carbon cycle beyond serving as substrate for surface ocean microbes, it must act as a reservoir for carbon on the time scales of ocean circulation. This it does, given that the
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ET-^ Deep and Bottom water m High density mode water • I Low density and Subtropical mode water —— Subtropical gyre circulation
Figure 8 Distribution of sites of water column overturn (from Talley, 1999), general patterns of surface circulation in the subtropical gyres, and proposed distribution of exportable DOC. Overlap in the distribution of exportable DOC (background field of white) and sites of ocean ventilation (sites colored by gray scale) favors DOC export; a lack of overlap precludes export. The waters of the Southern Ocean (slanted stripes) are without exportable DOC present, so where these waters overlap sites of ventilation, little export is expected.
production and accumulation of DOC in the surface ocean has been demonstrated (Figs. 2-8). The rates of, and controls on, the net production of DOC, topics not well understood at this time, are the focus of this section. Because so few DOC data exist, particularly from ocean systems for which accumulation has been evaluated, it is useful to normalize estimates of DOC accumulation to a more broadly available and easily measured variable. DOC accumulation as a function of net community production (NCP) has proven useful in this way (Hansell and Carlson, 1998b; Kortzinger et aL, 2001). NCP occurs when autotrophic production exceeds heterotrophic consumption, such as during a spring bloom. It is a process that largely results in the export of carbon and new nitrogen from the euphotic zone as sinking biogenic particles and in this way is analogous to new production (Dugdale and Goering, 1967). If DOC accumulates, then DOC too is a sink for NCP. NCP is estimated most directly by measuring the biological drawdown of the reactants (dissolved inorganic carbon and/or nitrate) or as the flux of the products (i.e., accumulation of DOC, suspended POC, export of sinking biogenic particles.
DOC in the Global Ocean Carbon Cycle and contributions by migrating zooplankton). The Section above on temporal variability of DOC sheds light on the net production of DOC. As a rule, oceanic regions showing seasonality of DOC concentrations are experiencing some transfer of NCP into the DOC pool.
A. EVIDENCE FOR NET PRODUCTION OF DOC Seasonal increases of DOC stocks in the Ross Sea indicate that 8-20% of NCP in the polynya system accumulates each growing season as DOC (Bates et al, 1998; Carlson et al, 2000; Hansell and Carison, 1998b; Sweeney et aU 2000). The balance of NCP is lost to the deep ocean as sinking biogenic particles, mostly Phaeocystis and diatoms. Annual rates of NCP in the Ross Sea polynya are 6-14 mol C m"^, so net DOC production of 1.2-2 mol C m"^ occurs over the growing season (Bates et al, 1998; Carlson et al, 2000; Sweeney et al, 2000). The net production of DOC in the Ross Sea is about that in the Sargasso Sea (1-2 mol C m~^; see above), but the Sargasso Sea has a much lower annual rate of net commiunity production. The rate of DOC production in the Ross Sea, normahzed to NCP, is similar to that found in the Equatorial Pacific. Estimates of net DOC production as a percentage of NCP in the central Equatorial Pacific range from 6 to 40%, with most estimates near the 20% level (Archer et al, 1997; Hansell et al, 1997a,b; Zhang and Quay, 1997). These values from the Equatorial Pacific are similar to the Equatorial Atlantic (20%; Thomas et al, 1995), but significantly lower than prior estimates in the Equatorial Pacific by Murray et al (1994), Feely et al (1995), and Peltzer and Hay ward (1996). Those latter authors estimated net DOC production closer to 75% of NCP, but those findings have been challenged (Hansell et al, 1997b; Zhang and Quay, 1997). Noji et al (1999) suggested that more than half of NCP in the Greenland Sea accumulated as DOC, high compared to findings from other nutrient-rich sites. Alvarez-Salgado et al (2001) reported that 20% of net ecosystem production accumulated as DOC in a coastal upwelling environment along the Iberian margin in the North Atlantic. This rate is very similar to that reported for the Equatorial Pacific and the Ross Sea. Net DOC production in the Ross Sea, the Equatorial Pacific and the Iberian margin takes place when the conditions are right for net autotrophy. In the Ross Sea, this occurs when vertical stability and light are available, while in the Equatorial Pacific and the coast of Spain light becomes available following upwelling. At these three sites, vertical stability is relatively strong during the periods of net production. The Sargasso Sea contrasts those systems. Light is generally available year round but nutrients are not, so a reduction in vertical stability (convective overturn of the water column and entrainment of nutrients) is required for net autotrophy. A representative year (July 1994 to July 1995) for DOC in the Sargasso
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Sea is useful for demonstrating net DOC production (Fig. 7). Winter overturn and mixing of the water column was both the cause of concentration reductions and the trigger for net DOC production each year following nutrient entrainment and subsequent new production (Carlson et aL, 1994; Hansell and Carlson, 2001a). The net production of DOC at the BATS site varies interannually as a function of the maximum in the winter mixed layer depth. The greater the vertical mixing (and nutrient entrainment) in the Sargasso Sea, the greater the net production of DOC (Hansell and Carlson, 2001a). In winter 1995 (Fig. 7), the DOC stock increased by 1.4 mol C m~^in response to maximum mixing depths of 260 m (note the net production of DOC in the upper 250 m of the water colunm; Fig. 7b). In subsequent years experiencing shallower maxima in mixed layer depth (<220 m), DOC stocks increased <0.7 mol C m~^ during the overturn event (Hansell and Carlson, 2001a). For the 1995 spring bloom, net DOC production was estimated to be 59-70% of the NCP (Hansell and Carlson, 1998b). This high rate does not hold for the entire year though. Much of the DOC produced during overturn and then mixed into the subsurface layers is remineralized upon restratification (note the rise and fall in integrated stocks of DOC at 100-250 m; Fig. 7b). Indeed, NCP continues throughout the summer and fall periods (Steinberg et ai, 2001), while DOC concentrations remain relatively static (no net production of DOC). As such, net DOC production reduces to ^ 8 % of NCP on an annual basis. Left unanswered is why so much of the NCP during the bloom accumulates as DOC, compared to the much lower NCP-normalized accumulation of DOC in the Ross Sea and the Equatorial Atlantic and Pacific. Community compositions and their responses to physical dynamics vary between these systems, and the answer likely lies in those variables (Carlson etai, 1998; Hansell and Carlson, 1998b). B. REGIONAL AND GLOBAL ESTIMATES FOR N E T PRODUCTION OF
DOC
As mentioned in the introduction to this Section, the value of normalizing the DOC accumulation rates to NCP is that NCP is a variable for which there is high data density. We can use the findings developed here on net DOC production, along with existing estimates for new (nitrate-based) production in various ocean regions (Chavez and Toggweiler, 1995), to estimate annual rates of DOC accumulation (Table I). The ratio of net DOC production to new production for each ocean region was assigned given what is known for the few systems (reviewed above) in which data exist. As would be expected, the regions of highest new production, such as tropical and coastal upwelling areas, contribute most to net DOC production globally. The weakest sites for the entrainment of nitrate to the
DOC in the Global Ocean Carbon Cycle
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Table I Estimates of Annual Net DOC Production Based on Regional Estimates of New Production (Chavez and Toggweiler, 1995) Region Tropical open ocean Upwelling Turbulent Mixing Southern ocean Subarctic gyres Coastal upwelling Monsoonal Subtropical gyre Continental margins Western boundary currents Estuarine influenced shelves Total
Net DOC production (pg C year~^ )
New production (pg C year"^)
ADOCiNP
1.5 (21%) 0.7 (9.5%) 1.1 (15.5%) 0.3 (4%) 0.8(11%) 0.4 (5.5%) 0.5 (7%)
0.2 0.1 0.12 0.15 0.2 0.2 0.1
0.3 (24.6%) 0.07 (5.7%) 0.13(10.8%) 0.04(3.7%) 0.16(13.1%) 0.08 (6.6%) 0.05 (4.1%)
0.7(9.5%) 1.2(17%) 7.2
0.2 0.2
0.14(11.5%) 0.24 (19.7%) 1.2 (17% of total NP)
Note. Values in parentheses represent percentages of the global estimate. Adapted with permission from Hansell and Carlson (1998b).
surface (such as the subtropical gyres) are the weakest in DOC net production. Net DOC production, based on this analysis, is the sink for about 17% of global new (nitrate based) production each year. A recent estimate for global new production is ^1 Pg C year-i (Chavez and Toggweiler, 1995; Fung et al, 2000; Lee, 2001), so net DOC production in the global ocean could be ^ 1.2 Pg C year~^. This estimate is for nitrate-based new production, thus excluding other forms of new production such as nitrogen fixation. We do not at present know the fraction of carbon fixed by active diazotrophs accumulating as DOC.
C. NUTRIENT DEPLETION AND NET PRODUCTION OF DOC One apparent axiom of net DOC production has been that nutrient depletion drives high rates of DOC production. This perception was based on numerous batch phytoplankton culture experiments where nutrients were allowed to run to very low values. When nutrients were present, and the plants were in the exponential growth phase, DOC release was very small; when nutrients were depleted and the plants went into stationary phase, carbon fixation exceeded the N stocks available to support biomass growth, so C-rich DOC was released (e.g., Goldman et al, 1992). Because of these results, it has been assumed that nutrient depletion forces high levels of DOC production everywhere in the ocean. It would follow
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that high levels of DOC in oligotrophic systems were expected because of nutrient limitation. Such arguments can be tested for relatively oligotrophic systems using the time-series data from the Sargasso Sea (Fig. 6). As outlined above, net DOC production took place largely while rates of primary production were highest (the spring bloom period). During the summers, when nutrients were most depleted, there was no further accumulation of DOC; nor was there a major enhancement in bacterial respiration rates relative to primary productivity to indicate high release of labile DOC (Carlson et ai, 1996). The data from the Sargasso Sea indicate that nutrient depletion alone does not drive high rates of DOC production. Indeed, Parsons et al. (1970) reported DOC accumulation during the sunamer in the Strait of Georgia, but without depletion of the macronutrients (nitrate went as low as 7 /xM only). Where the culture experiments fail to reflect nature is in their inability to support reasonable changes in community composition. In nature, new assemblages of autotrophs will develop given changes in the nutrient forcing, and the stress of nutrient depletion on the sunmier population will be dissimilar to that felt by the spring bloom population. It is apparent that nutrient depletion alone is not adequate to force significant net production of DOC in the open ocean.
IV. CONTRIBUTION OF DOC TO THE BIOLOGICAL PUMP A. EVIDENCE FOR DOC EXPORT DOC plays perhaps its most important role in the biogeochemistry of the ocean carbon cycle when it contributes to the biological pump (Copin-Montegut and Avril, 1993; Carlson et ai, 1994; Ducklow et ai, 1995). The export of sinking biogenic particles has long been understood to drive respiration in the ocean interior and to help maintain the ocean's strong vertical gradient of inorganic carbon. The contribution of DOC to the biological pump has been debated for several decades, and is only now being resolved. Menzel (1970) stated that deep-ocean changes in oxygen and nutrients could not be attributed to the long-term in situ decomposition of dissolved organic matter. He acknowledged that some published data suggested that 15% of the total oxygen consumption was due to oxidation of DOC, but he thought this value to be unreaUstic. Craig (1971), in a direct counter to these findings, suggested that one-third of the oxygen consumption in recently formed North Atlantic Deep Water could be due to DOC oxidation. While he did not have faith in the accuracy of the DOC data available at the time, and he used calculations that he described as "brute force," he was satisfied that deep DOC oxidation was substantive. Ogura (1970) took a refined approach to the question. He evaluated property/property plots of DOC and apparent oxygen utilization (AOU) along
DOC in the Global Ocean Carbon Cycle isopycnal surfaces in the western North Pacific, reporting that one-third of the AOU was due to DOC consumption. He noted that the contribution was restricted to the upper ocean (<500 m); DOC oxidation was not resolvable in the deep waters. Kahler and Koeve (2001) argued that DOC is unlikely to be substantial in the export of biogenic material to the deep sea; otherwise the deep-ocean C:N ratios should deviate from Redfield stoichiometry as required by the input of C-enriched dissolved organic matter. The export of DOC in the ocean is a consequence of its accumulation in the surface ocean (Fig. 2), redistribution with the wind-driven circulation, and eventual transport to depth with overturning (thermohaline) circulation at high latitudes and subduction in the subtropical gyres. Thermohaline circulation refers to the vertical movement of water that takes place when its density increases by a significant change of temperature or salinity. The most important sites for ventilation of the intermediate and deep ocean are located in the North Atlantic (Labrador Sea Intermediate Water and North Atlantic Deep Water formation sites), the North Pacific (site of North Pacific Intermediate Water formation), the area around Drake Passage (Antarctic Intermediate Water formation), and around Antarctica (Antarctic Bottom Water formation) (Fig. 8). Water mass formation at these sites occurs primarily during winter. Subduction occurs year round in subtropical gyres due to Ekman pumping of the surface layer. The upper thermocline ventilates by this process. Because the mixed layer density and depth reach their local maxima at late winter, the water subducted into the permanent thermocline has properties that are strongly biased toward the late winter values (Stommel, 1979). As a rule, DOC export with ventilation of the ocean occurs if there is a vertical DOC concentration gradient at the onset of overturn. In such a situation, DOC accumulated at the surface undergoes net transport downward. Where vertical DOC gradients are weak or absent, there is little net downward movement of DOC with overturn and subduction. 1. Export into the Upper Pycnocline The main thermoclines of the major ocean basins ventilate following buoyancy loss (via cooling) in DOC-enriched warm water previously transported poleward in the western boundary currents. Equatorward subduction beneath the less dense surface waters results in the export of DOC along isopycnal surfaces, a process evaluated by Ogura (1970), Doval and Hansell (2000), and Abell et at. (2000). Establishing the contribution of DOC to export is perhaps best examined by normalizing the gradients in DOC concentrations to the gradients in AOU. AOU derives from the mineralization of sinking biogenic particles and subducted DOC and so reflects the total oxidation of biogenic carbon along specified surfaces. A representative isopycnal surface along 170°W in the western South Pacific is that of (7^26-26.5 (Doval and Hansell, 2000). DOC concentrations along that isopycnal decreased away from the sea surface commensurate with an increase in AOU,
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such that oxidation of DOC drove ^40% of the AOU. Mineralization of sinking biogenic particles formed overhead in the euphotic zone drove the balance of the AOU. In the isopycnal surfaces lying between aelS.S and 27.0 along 170°W, 21-47% of the AOU was driven by DOC oxidation (Doval and Hansell, 2000). Like Ogura's (1970) findings in the North Pacific, DOC oxidation along 170°W was restricted to the upper 500 m; at greater depths, only biologically refractory DOC remained in the water colunm so sinking particles alone drove additional AOU development. Guo et al. (1994) similarly found that 20-30% of AOU may be due to DOC mineralization in the Gulf of Mexico. Subtropical mode water formation is a strong form of subduction ventilating the upper thermocline primarily during winter at mid-latitudes. Such a process is important to ventilation of the western North Atlantic in the north Sargasso Sea. The waters of the Sargasso Sea near Bermuda are strongly stratified through much of the year. During the fall and winter months, regular storm fronts deliver cold, dry winds that cool the surface water, causing a deepening of the mixed layer by convective overturn. Overturn of the water colunm, when deep enough (~250 m), ventilates Worthington's (1976) 18° Mode Water. DOC near Bermuda is present at its highest concentrations during the long warm (summer) periods (Fig. 7). At overturn, DOC concentrations and stocks at depths >100 m increase (Fig. 7), reflecting the downward mixing of the carbon; its disappearance with time at those depths reflects net microbial mineralization and removal by horizontal advection and mixing into mode water. During the overturn periods of 1992-1998, DOC export near Bermuda ranged from 0.4 to 1.4 mol C m"-^, rates representing 15 to 41% of the total biogenic carbon mineralized annually in the upper 400 m of the water colunm (Carlson et al, 1994; Hansell and Carlson, 2001a). 2. Export into the Deep Pycnocline Ventilation of the deep pycnocline occurs with the formation of intermediate water masses. At present few data exist for evaluating DOC export during this process. An exception is DOC export with North Pacific intermediate water (NPIW) formation (Hansell et al, 2002). NPIW forms by brine rejection in the Sea of Okhotsk north of Japan. It is delivered to intermediate depths (400-1000 m and bounded by cr6i26.6-27.4) of the subtropical North Pacific as a mixture of recently ventilated, relatively fresh subpolar (Oyashio) water and older, more saline subtropical (Kuroshio) water of the same density range. New NPIW is transported eastward from the site of subduction east of Japan as a low-salinity tongue, with eventual circulation into the intermediate layers of the subpolar and subtropical gyres, thus replenishing those systems (Talley, 1997). Data collected at 1000 m (^27.4 ae), between 10 and 45°N along 1527158°W (Fig. 1), demonstrate the export of DOC-enriched subpolar water and its impact on DOC distribution in the NPIW of the subtropical gyre (Fig. 9). The samples were from deep in the
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Figure 9 Evidence for the export of DOC with formation of new North Pacific intermediate water, (a) Salinity contours in the upper 2000 m along 152°/158°W in the North Pacific, overlain (bold) by cr^ surfaces (26.6 and 27.4) indicating the upper and lower bounds of NPIW. Filled circles indicate sample locations for DOC (b) along the section. Note the freshening of the water column to the north, where the influence of new NPIW is strongest.
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NPIW, across a salinity gradient of high subpolar (fresh) water influence in the north and high subtropical (sahne) water influence in the south (Fig. 9a). Samples comprising subtropical water (south of 25°N and salinity >34.4) had a mean DOC concentration of 38.7 ±0.7 /xM (Fig. 9b). Waters to the north, with a greater subpolar contribution (salinity <34.4), had a mean of 44.7 ±0.6 /iM, for a 15% enrichment. The evidence for DOC export with NPIW formation is clear. 3. Export to the Deep Ocean Removal of carbon from exchange with the atmosphere is greatest with DOC export associated with deep- and bottom-water formation. Evidence for the export of DOC with NADW formation is the strong meridional gradient in deep-water DOC, along the proximal path of the deep western boundary current (Fig. 5; Hansell and Carlson, 1998a). Data from 75°N in the deep Greenland Sea are presently our best representation for concentrations of DOC in the source water for NADW formation (48 /xM). NADW overrides and entrains northward-flowing Antarctic bottom water (AABW), of a largely Weddell Sea source and with a DOC concentration of 41 /xM (Fig. 5). Mixing of these two source waters, along with microbial degradation, results in a DOC concentration gradient in the Atlantic Ocean. AABW forms in the cyclonic gyres that develop south of the Antarctic Circumpolar Current system, particularly the Weddell and Ross Sea gyres. The contribution of AABW formation to DOC export appears to be very small. The best studied of the high-latitude cyclonic gyre systems with regard to DOC distributions is the Ross Sea (Carlson et al, 1998, 2000). During the 1997 austral summer season in the Ross Sea, DOC concentrations in the surface 50 m reached >20 ^M above background in certain areas. By the time of winter overturn in fall, biological mineralization of the DOC reduced the concentrations to a mean of <5 /xM above background. The vertical export of this material, if still remnant at the time of complete overturn, would contribute to only 2% of the annual export of particulate plus dissolved organic carbon in the Ross Sea (Sweeney et al, 2000). Mineralization of the DOC prior to overturn prevented it from making a major contribution to export in this system. Evaluating horizontal gradients of DOC in the deep layers between the Ross Sea and the circumpolar deep water is a second test for DOC export with AABW formation. Because DOC exported with NADW formation demonstrated a strong gradient along the path of advection, so too should a gradient be present from the sites of AABW formation to the deep circumpolar waters if export is significant. The deep Ross Sea (data from 76°S in the Pacific sector of Fig. 5) has a DOC concentration (42 /xM) that is indistinguishable from the concentration in the circumpolar water to the north at 60°S (Fig. 5). The lack of a gradient suggests the absence of DOC export.
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B. EXPORTABLE DOC We see from the analyses presented here that the export of DOC contributes in a significant way at some, but not all, sites of water mass formation. The water masses formed in the Northern Hemisphere, as well as those formed in the low- to mid-latitudes of the Southern Hemisphere, carry with them significant DOC loads for export. NADW, formed in the region of 60-70°N of the North Atlantic, exports DOC at ^32 Tg C year"^ and contributes to 40-50% of AOU in the deep northern North Atlantic (Hansell and Carlson, 1998b; Hansell et al, 2002). NPIW, formed at 40°N in the western North Pacific, exports ?^13 Tg C year"\ driving 30% of oxygen utilization near the site of formation (Ogura, 1970; Hansell et al, 2002). Overturn at 32°N in the Sargasso Sea exports DOC adequate to drive 15-40% of AOU in the underlying waters (Hansell and Carlson, 2001a). Similarly, ventilation of the South Pacific and Indian Ocean main thermoclines delivers DOC adequate to drive 20-45% of AOU (Doval and Hansell, 2000). In contrast, DOC export does not take place with AABW formation. Export with Antarctic intermediate water formation, a poorly resolved process, is likely low as well. In order for DOC export to occur its concentration must be elevated at the surface relative to the deeper water into which mixing takes place. This excess DOC at the surface must be present at the onset of overturn. Exportable DOC is the term used here to refer to DOC present at overturn that is in excess of the DOC concentrations at the depth to which vertical mixing takes place. It is the fraction of DOC whose lifetime exceeds the season of production and is therefore transportable to sites of water mass formation by surface currents. (So as to avoid confusion, some comments about the terminology used here and in the Introduction must be made. The exportable DOC introduced here is approximately the same fraction of DOC as the "semilabile" pool given in the Introduction. In this Section, though, the DOC pool is resolved into fractions that describe their export functionality. Terms such as "semilabile" DOC highhght the functional nature of DOC relative to microbial turnover of the various fractions.) Significant amounts of exportable DOC appear to be absent at high latitudes in the Southern Ocean. Sharp fronts in a variety of properties separate the Antarctic Circumpolar Current System (ACCS) from the DOC-enriched subtropical gyres, as evidenced by the abrupt shifts in DOC concentrations south of the gyres (Fig. 2). It is likely to be in the gyres that exportable DOC is stored. Certainly it is in these waters that this fraction is resident year round (Fig. 6). The primary hydrographic front separating the subtropical and subantarctic water masses in the Southern Ocean is the Subtropical Front (also known as the Subtropical Convergence). Where subtropical gyre waters serve as precursors for water mass formation, we expect DOC export to be important. Where high-density waters of the Southern Ocean are the primary source for water mass formation (such as for AABW formation), DOC export appears to be negligible. Kahler et al (1997), Wiebinga and
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de Baar (1998), and Carlson et al (1998, 2000) noted the apparent lack of DOC export in the Southern Ocean. Kahler et al (1997) highlighted the absence of the greater-than-seasonal fraction of DOC, a fraction they described as being of intermediate stability and one that is defined here as making up the exportable fraction of DOC. The distribution of the world ocean's primary sites for water mass formation (Talley, 1999), when overlain by the proposed global distribution of exportable DOC, indicates where DOC export is likely to be of consequence (Fig. 8). Excluded from this map are the zones of subduction in the subtropical gyres, which will force a relatively shallow (<500 m) export of DOC. Hansell and Carlson (2002 b) hypothesize that the primary sites of formation for exportable DOC are the subtropical gyres and the equatorial/coastal upwelling regions. It is in the gyres that exportable DOC is present year round, that this fraction has ample residence time in the euphotic zone to accumulate, and from which surface water is exported to higher latitudes as precursor for water mass formation. Further evidence for this hypothesis is that the exportable fraction is absent at high southern latitudes missing inputs of subtropical water (i.e., the Southern Ocean). Given this, high-latitude regions replenished by subtropical gyre waters via western boundary currents, such as the northern North Pacific and northern North Atlantic, will have exportable DOC present at the time of overturn. High-density water masses formed in high northern latitudes (NADW, NPIW, and likely Labrador Sea intermediate water), but fed by subtropical water, will export DOC. In contrast, DOC export in high-density water masses formed in the high-latitudes of the Southern Hemisphere will not contribute to the total export of biogenic carbon. The presence of the strong frontal systems in the ACCS prevents the DOC-enriched subtropical water from serving as source water during convection. The absence, as well, of locally produced exportable DOC at high southern latitudes precludes the process. Formation of Antarctic intermediate water (AAIW) should support a more variable export of DOC, dependent on the ratio of highlatitude and subtropical waters serving as precursor to this widely distributed water mass. Much more work is required to quantify DOC export with AAIW formation. Hansell and Carlson (2002 b) have estimated the global, annual export of DOC. Export with intermediate, deep, and bottom water was estimated at ^9.8x10^^ mol C year~\ or ^10% of the total export (oxygen utilization) to depths >500 m. The contribution of DOC to exported C oxidized at depths <500 m is elevated relative to the deep ocean. DOC contributes 15 to 41% of oxygen utilization at the BATS site in the Sargasso Sea (Hansell and Carlson, 2001a) and 25 to 45% in the main thermoclines of the South Pacific and Indian Oceans (Doval and Hansell, 2000). The global contribution of DOC to export must lie between the ~10% value of the deep ocean and the ~30% value of the main thermocline. The contribution of DOC to global export in the open ocean, then, must fall in the range of 20 =b 10%.
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As referenced above, 7 Pg C year" ^ is the recent estimate for global new production, so total DOC export is 1.4 ± 0.7 Pg C year~^ DOC export to depths >500 m is only 0.13 Pg C year~\ so most of the global export of DOC takes place through the many paths of shallow subduction. This rate of export is about the same as the earlier estimate of global net production of DOC (1.2 Pg C year"^), suggesting that most of the annual net production of DOC is exported. The sites of production are spatially distinct from the sites of export; surface currents provide the essential connectivity.
V. RESEARCH PRIORITIES In this chapter, a holistic picture of DOC in the ocean carbon cycle was developed. DOC was evaluated in the context of its wide-scale distribution (i.e., spatial and temporal variability), net production, and export. Evaluating DOC in this way was possible through collection of high quality data at key ocean sites. Unfortunately, our data density remains far too small to generate a higher resolution picture of the system. Many of the details await discovery and, the conceptual models and hypotheses, critical testing. The major constraint on improving data density in the past has been that most of the DOC data generated by the international community were not referenced against common materials. Data from within a laboratory could be used to quantify, for example, wide-scale spatial variability, but data could not be combined from several laboratories for a similar analysis. The analytical differences between laboratories often exceeded the natural variability assessed, thus precluding such data compilations. The solution is increasing dedicated use of standardized reference materials for DOC analysis, now available to the ocean science community through funding by the U.S. National Science Foundation. One important issue not covered in this chapter is the oceanic transport of carbon as DOC with surface currents. We evaluated DOC production and export, but we did not physically connect the processes with an evaluation of transport. What is required is a strong analysis of DOC transport with the surface-ocean, wind-driven circulation. The data now in existence are inadequate for extensive analyses of transport. Some efforts can be made in the North Atlantic where zonal sections have been completed (Fig. 4). The distribution of DOC, with highest concentrations in the low to mid-latitude gyres, suggests that the subtropical gyres and low to mid-latitude upwelling systems are important sources of DOC for export at higher latitude sites of ocean ventilation. The strong western boundary currents carry the warm, saline subtropical water to higher latitudes, where cooling drives overturn of the water column. The subtropical waters are DOC-enriched, so the boundary currents must be important for the net transport of DOC as well. Little fieldwork or data analysis exists
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to understand or quantify this process for the various ocean basins. The assessment made here that much of the net DOC production occurs in coastal and equatorial upwelling sites in turn suggests that the gyres must serve as a reservoir for that DOC produced. From these ocean systems, the DOC is transported to the high latitudes for export. This model will be evaluated over the next decade. Changes in the circulation and net DOC production patterns with ocean climate change will modify the importance of the system described. One form of DOC export not considered in this chapter is vertical diffusive mixing into the water colunm. This process is likely important on a global scale but it has not been adequately evaluated. Loh and Bauer (2000), Emerson et al (1997), Guo et al (1995), Christian et al (1997), and Vidal et al (1999) provide recent calculations for downward diffusive flux of DOC. One major uncertainty with this method is the choice of the vertical diffusion coefficient, which may be uncertain by an order of magnitude. Also, it is difficult to test the vertical diffusive flux calculations independently. Confidence in rate estimates comes with independent evaluations. Clearly, this mechanism of export needs a good deal more analysis. Modeling efforts may prove the most useful test of the reported findings. Other issues requiring high-priority effort include understanding controls on the variability in surface DOC concentrations between the various major subtropical gyres. DOC in the subtropical North Pacific, for example, may be elevated relative to the North Atlantic (Fig. 6), but we do not know why. Will the size of the marine reservoir of organic carbon vary with climate-induced changes in the unknown controls on the reservoir? Further, we do not know the factors controlUng the NCP-normaUzed net production of DOC, such that the rate is high in the Sargasso Sea and lower in the areas with higher nutrient loads. In the deep ocean, we do not understand the processes causing the variability seen in Fig. 5. What are the mechanisms for removal of DOC along the entire path, and what are the mechanisms for introducing DOC in the low-latitude southern hemisphere? We also need to identify the truly important mechanisms of DOC production. Many times in publications a "laundry list" of mechanisms is presented (phytoplankton exudation, sloppy feeding, viral lysis, particle dissolution, etc.), but in truth we do not know which are significant and when. We know just as little about the processes involved in DOC decomposition. Progress is required here. While a great deal of field work is still needed, certainly we can make more significant headway by modeling DOC dynamics, particularly when performed in the context of ocean physics. Advances in understanding processes such as DOC export will be made whole when models are employed to expand our understanding of how the system works. Meanwhile, it is important to collect high-quality data and to interpret these in the context of the biological and physical conditions present at collection.
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VL SUMMARY In this chapter an understanding for the role of DOC in the ocean carbon cycle was developed. Net DOC production is a function of net community production in the ocean, so where NCP is highest, net DOC production is high as well (Table I). The coastal and equatorial upwelling environments are particularly important in this regard. DOC produced at mid-latitudes, given sufficient lifetime, converges by surface currents into the subtropical gyres. The gyres, as the recipients of the DOC enriched waters and as sites of strong vertical stability, have the highest year-round concentrations and stocks of DOC in the global ocean. Subduction in the gyres carries DOC into the upper pycnocHne. The western boundary currents are important in the transport of the DOC from the gyres to higher latitudes, where DOC export occurs at sites of deep-water mass ventilation. Where the western boundary currents reach high latitudes, both intermediate and deep water formation carries exported DOC. Where western boundary currents are impeded from reaching high latitudes by frontal systems, such as in the Southern Ocean, DOC export is minimal. Annually, net DOC production represents about ~20% of net community production and ~20% of export production. Surface currents connect the sites of net production and export.
ACKNOWLEDGMENTS An understanding for the role DOC plays in the ocean carbon cycle is developed only with great support from many individuals and institutions. I thank the U.S. National Science Foundation (Ocean Chemistry) and the U.S. National Oceanographic and Atmospheric Administration (Office of Global Programs) for their continued support of this work. Numerous individuals have suffered many hours over hot instrumentation to generate the thousands of DOC values required for the analyses reported. Rachel Parsons did the lion's share of the DOC analyses; I owe her a great debt of gratitude. Also important are Dr. Wenhao Chen, Paula Hansell, Tye Waterhouse, Susan Becker, Amy Ritchie, and Bemie CuUen; each spent many hours in the laboratory and at sea. Finally, I thank Craig Carlson for being a good friend and collaborator.
REFERENCES Abell, J., Emerson, S., and Renaud, R (2000). Distributions of TOP, TON, and TOC in the North Pacific subtropical gyre: Implications for nutrient supply in the surface ocean and remineralization in the upper thermocline. J. Mar. Res. 58, 203-222. Alvarez-Salgado, X. A., Gago, J., Miguez, B. M., and Perez, F. F. (2001). Net ecosystem production of dissolved organic carbon in a coastal upwelling system: The Ria de Vio, Iberian margin of the North Atlantic. Limnol. Oceanogr. 46,135-147. Anderson, L. G. (2002). The Arctic Ocean. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. Hansell and C. A. Carlson, Eds.), pp. 665-715. Academic Press, San Diego.
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Anderson, L. G., Olsson, K., and Skoog, A. (1994). Distribution of dissolved inorganic and organic carbon in the Eurasian Basin of the Arctic Ocean, In "The Polar Oceans and Their Role in Shaping the Global Environment" (O.M. Johannessen, R. D. Muench, and J. E. Overiand, Eds.), pp. 255-262. Geophysical Monograph Series, American Geophysical Union, Washington, DC. Archer, D., Peltzer, E. T., and Kirchman, D. L. (1997). A timescale of DOC production in equatorial Pacific surface waters. Global Biogeochem. Cycles 11,435-452. Banoub, M. W., and Williams, P. J. leB (1973). Seasonal changes in the organic forms of carbon, nitrogen and phosphorus in the EngUsh Channel in 1968. J. Mar. Biol. Assoc. UK 53,695-703. Bates, N., and Hansell, D. A. (1999). Hydrographic and biogeochemical signals in the surface ocean between Chesapeake Bay and Bermuda. Mar. Chem. 67,1-16. Bates, N. R., Hansell, D. A., Carlson, C. A., and Gordon, L. I. (1998). Distribution of CO2 species, estimates of net conmiunity production and air-sea CO2 exchange in the Ross Sea polynya. J. Geophys. Res. 103,2883-2896. Bauer, J. E. (2002). Carbon isotopic composition of DOM. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. Hansell and C. A. Carlson, Eds.), pp. 405^53. Academic Press, San Diego. Bauer, J. E., Druffel, E. R. M., WilUams, P M., Wolgast, D. M., and Griffin, S. (1998). Temporal variability in dissolved organic carbon and radiocarbon in the eastern North Pacific Ocean. J. Geophys. Res. 103, 2867-2881. Borsheim, K. Y., and Myklestad, S. M. (1997). Dynamics of DOC in the Norwegian Sea inferred from monthly profiles collected during 3 years at 66°N, 2°E. Deep-Sea Res. I 36,497-507. Borsheim, K. Y., Myklestad, S. M., and SneU, J. A. (1999). Monthly profiles of DOC, mono- and polysaccharides at two locations in the TrondheimsQord (Norway) during two years. Mar. Chem. 63,255-272. Carlson, C. A. (2002). Production and removal processes. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. Hansell and C. A. Carlson, Eds.), pp. 91-151. Academic Press, San Diego. Carlson, C. A., and Ducklow, H.W. (1995). Dissolved organic carbon in the upper ocean of the central equatorial Pacific Ocean, 1992: Daily and finescale vertical variations. Deep-Sea Res. II42,639656. Carlson, C. A., Ducklow, H. W, Hansell, D. A., and Smith, W O., Jr. (1998). Organic carbon partitioning during spring phytoplankton blooms in the Ross Sea polynya and the Sargasso Sea. Limnol. Oceanogr. 43, 375-386. Carlson C. A., Ducklow, H. W, and Michaels, A. F. (1994). Annual flux of dissolved organic carbon from the euphotic zone in the northwestern Sargasso Sea. Nature 371,405-408. Carlson, C. A., Ducklow, H. W, and Sleeter, T. D. (1996). Stocks and dynamics of bacterioplankton in the northwestern Sargasso Sea. Deep-Sea Res. II43,491-515. Carlson, C. A., Hansell, D. A., Peltzer, E. T, and Smith, W. O., Jr. (2000). Stocks and dynamics of dissolved and particulate organic matter in the southern Ross Sea, Antarctica. Deep-Sea Res. II47, 3201-3225. Cauwet, G. (2002). DOM in the coastal zone. In "Biogeochemistry of Marine Dissolved Organic Matter" (D. A. Hansell and C. A. Carlson, Eds.), pp. 579-609. Academic Press, San Diego. Chavez, F. P., and Toggweiler, J. R. (1995). Physical estimates of global new production: The upwelling contribution. In "Upwelling in the Ocean: Modem Processes and Ancient Records" (C. P. Summerhayes et al., Eds.), pp. 313-320. Wiley, New York. Chen, R. F , Fry, B., Hopkinson, C. S., Repeta, D. J., and Peltzer, E. T. (1996). Dissolved organic carbon on Georges Bank. Cont. Shelf Res. 16,409-420. Christian, J. R., Lewis, M. R., and Karl, D. M. (1997). Verticalfluxesof carbon, nitrogen, and phosphorus in the North Pacific Subtropical Gyre near Hawaii. J. Geophys. Res. 102,15,667-15,677. Church, M. J., Ducklow, H. W., and Karl, D. M. (2002). Decade-scale secular increase in dissolved organic carbon and nitrogen inventories in the North Pacific subtropical gyre. Limnol. Oceanogr. 47,1-10.
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Copin-Montegut, G., and Avril, B. (1993). Vertical distribution and temporal variation of dissolved organic carbon in the Northwestern Mediterranean Sea. Deep-Sea Res. 740,1963-1972. Craig, H. (1971). The deep metaboHsm: Oxygen consumption in abyssal ocean water. J. Geophys. Res. 76, 5078-5086. Dileep Kumar, M., Rajendran, A., Somasundar, K., Haake, B., Jenisch, A., Shuo, Z., Ittekkot, V., and Desai, B. N. (1990). Dynamics of dissolved organic carbon in the northwestern Indian Ocean. Mar. Chem. 31,299-316. Doval, M. D., Alvarez-Salgado, X. A., and Perez, F. F. (1997). Dissolved organic matter in a temperate embayment affected by coastal upwelling. Mar. Ecol. Prog. Ser. 157, 21-37. Doval, M., and Hansell, D. A. (2000). Organic carbon and apparent oxygen utilization in the western South Pacific and central Indian Oceans. Mar. Chem. 68, 249-264. Druffel, E. R. M., WiUiams, P. M., Bauer, J. E., and Ertel, J. R. (1992). Cycling of dissolved and particulate organic matter in the open ocean. J. Geophy. Res. 97,15639-15659. Ducklow, H. W., Carlson, C. A., Bates, N. R., Knap, A. H., and Michaels, A. F (1995). Dissolved organic carbon as a component of the biological pump in the North Atlantic Ocean. Phil. Trans. R. Soc. London B 348,161-167. Dugdale, R. C , and Goering, J. J. (1967). Uptake of new and regenerated forms of nitrogen in primary productivity. Limnol. Oceangr. 12,196-207. Dunne, J. P., Murray, J. W., Rodier, M., and Hansell, D. A. (2000). Export production in the western and central equatorial Pacific using ^^^Th calibrated sediment traps and TOC accumulation. Deep-Sea Res. I 47,901-936. Duursma, E. K. (1962). Dissolved organic carbon, nitrogen and phosphorus in the sea. Neth. J. Sea Res. 1, 1-148. Duursma, E. K. (1963). The production of dissolved organic matter in the sea, as related to the primary gross production of organic matter. Neth. J. Sea Res. 2, 85-94. Emerson, S., Quay, P., Karl, D. M., Winn, C , Tupas, L., and Landry, M. (1997) Experimental determination of the organic carbon flux from open-ocean surface waters. Nature 389, 951-954. Feely, R. A., Wanninkhof, R., Cosca, C. E., Murphy, R R, Lamb, M. F , and Steckley, M. D. (1995). CO2 distributions in the equatorial Pacific during the 1991-1992 ENSO event. Deep-Sea Res. II 42, 365-386. Fung, I. Y, Meyn, S. K., Tegen, I., Doney, S. C , John, J. G., and Bishop, J. K. B. (2000). Iron supply and demand in the upper ocean. Global Biogeochem. Cycles 14, 281-295. Goldman, J. C , Hansell, D. A., and Dennett, M. R. (1992). Chemical characteristics of two large chain-forming oceanic diatoms: Impact on water column chemistry. Mar Ecol. Progn Ser. 88, 257-270. Guo, L., Coleman, C. H., Jr., and Santschi, P. H. (1994). The distribution of colloidal and dissolved organic carbon in the Gulf of Mexico. Mar Chem. 45,105-119. Guo, L., Santschi, P. H., and Wamken, K. W. (1995). Dynamics of dissolved organic carbon (DOC) in oceanic environments. Limnol. Oceanogr 40,1392-1403. Hansell, D. A., Bates, N. R., and Carlson, C. A. (1997a). Predominantly vertical losses of carbon from the surface layer of the Equatorial Pacific Ocean. Nature 386, 59-61. Hansell, D. A., and Carlson, C. A. (1998a). Deep ocean gradients in dissolved organic carbon concentrations. Nature 395, 263-266. Hansell, D. A., and Carlson, C. A. (1998b). Net community production of dissolved organic carbon. Global Biogeochem. Cycles 12,443-453. Hansell, D. A., and Carlson, C. A. (2001a). Biogeochemistry of total organic carbon and nitrogen in the Sargasso Sea: Control by convective overturn. Deep-Sea Res. II48,1649-1667. Hansell, D. A., and Carlson, C. A. (2002 b). Dissolved organic carbon export by ocean circulation and mixing. Submitted for publication. Hansell, D. A., Carlson, C. A., Bates, N. R., and Poisson, A. (1997b). Horizontal and vertical removal
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of organic carbon in the equatorial Pacific Ocean: A mass balance assessment. Deep-Sea Res. II 44,2115-2130. Hansell, D. A., Carlson, C. A., and Suzuki, S. (2002). Dissolved organic carbon export with North Pacific Intermediate Water formation. Global Biogeochem. Cycles, in press. Hansell, D. A., and Feely, R. A. (2000). Atmospheric intertropical convergences impact surface ocean carbon and nitrogen biogeochemistry in the tropical Pacific Ocean. Geophys. Res. Lett. 27,10131016. Hansell, D. A., and Peltzer, E. T. (1998). Spatial and temporal variations of total organic carbon in the Arabian Sea. Deep-Sea Res. II45,2171-2193. Hansell, D. A., and Waterhouse, T. Y. (1997). Controls on the distribution of organic carbon and nitrogen in the eastern Pacific Ocean. Deep-Sea Res. 144, 843-857. Holmes, R. W., Williams, P M., and Eppley, R. W. (1967). Red water in La JoUa Bay, 1964-1966. Limnol. Oceanogr. 12,503-512. Kahler, P., Bjomsen, P. K., Lochte, K., and Anita, A. (1997). Dissolved organic matter and its utiUzation by bacteria during spring in the Southern Ocean. Deep-Sea Res. II 44, 341353. Kahler, P., and Koeve, W. (2001). Dissolved organic matter in the sea: Can its C:N ratio explain carbon overconsumption? Deep-Sea Res. I 48,49-62. Karl, D. M. (1999). A sea of change: Biogeochemical variability in the North Pacific subtropical gyre. Ecosystems 2,181-214. Karl, D. M., Letelier, R., Tupas, L., Dore, J., Christian, J., and Hebel, D. (1997). The role of nitrogen fixation in biogeochemical cycling in the subtropical North Pacific Ocean. Nature 388, 533-538. Kortzinger, A., Koeve, W, Kahler, P., Mintrop, L. (2001). C:N ratios in the mixed layer during the productive season in the northeast Atlantic Ocean. Deep-Sea Res. I 48,661-688. Lee, K. (2001). Global net conmiunity production estimated from the annual cycle of surface water total dissolved inorganic carbon. Limnol. Oceanogr. 46,1287-1297. Loh, A. N., and Bauer, J. E. (2000). Distribution, partitioning and fluxes of dissolved and particulate organic C, N and P in the eastern North Pacific and Southern Oceans. Deep-Sea Res. I 47, 2287-2316. Martin, J. H., and Fitzwater, S. E. (1992). Dissolved organic carbon in the Atlantic, Southern and Pacific oceans. Nature 356,699-700. Menzel, D. W. (1964). The distribution of dissolved organic carbon in the Western Indian Ocean. Deep-Sea Res. 11,757-765. Menzel, D. W. (1970). The role of in situ decomposition of organic matter on the concentration of non-conservative properties in the sea. Deep-Sea Res. 17,751-764. Menzel, D. W, and Ryther, J. H. (1970). Distribution and cycling of organic matter in the oceans. In "Organic Matter in Natural Waters" (D. W. Hood, Ed.), Institute of Marine Science Occasional Publication 1, pp. 31-54. Univ. of Alaska, Fairbanks, AK. Michaels, A. F , and Knap, A. H. (1996). Overview of the U.S. JGOFS Bermuda Adantic Time-series Study and the Hydrostation S program. Deep-Sea Res. II43,157-198. Murray, J. W., Barber, R. T., Roman, M. R., Bacon, M. P., and Feely, R. A. (1994). Physical and biological controls on carbon cycling in the Equatorial Pacific. Science 266,58-65. Noji, T. T., Rey, F , Miller, L. A., Borsheim, K. Y., and Urban-Rich, J. (1999). Fate of biogenic carbon in the upper 200 m of the central Greenland Sea. Deep-Sea Res. II46,1497-1509. Ogura, N. (1970). The relation between dissolved organic carbon and apparent oxygen utilization in the western North Pacific. Deep-Sea Res. 17,221-231. Opsahl, S., Benner, R., and Amon, R. M. W. (1999). Major flux of terrigenous dissolved organic matter through the Arctic Ocean. Limnol. Oceanogr. 44,2017-2023. Parsons, T. R., LeBrasseur, R. J., and Barraclough, W E. (1970). Levels of production in the pelagic
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environment of the Strait of Georgia, British Columbia: A review. /. Fish. Res. Bd. Can. 27, 1251-1263. Peltzer, E. T., and Hayward, N. A. (1996). Spatial and temporal variabiHty of total organic carbon along 140°W in the equatorial Pacific Ocean in 1992. Deep-Sea Res. II43,1155-1180. Postma, H., and Rommets, J. W. (1979). Dissolved and particulate organic carbon in the north Equatorial Current of the Atlantic Ocean, Neth. J. Sea Res. 12, 85-98. Romankevich, E. A., and Ljutsarev, S. V. (1990). Dissolved organic carbon in the ocean. Mar. Chem. 30,161-178. Sharp, J. H. (1997). Marine dissolved organic matter: Are the older values correct? Mar. Chem. 56, 265-277. Steinberg, D. K., Carlson, C. A., Bates, N. R., Johnson, R. J., Michaels, A. E, and Knap, A. H. (2001). Overview of the US JGOFS Bermuda Atlantic Time-series Study (BATS): A decade-scale look at ocean biology and biogeochemistry. Deep-Sea Res. II48,1405-1447. Stommel, H. M. (1979). Determination of water mass properties of water pumped down from the Ekman layer to the geostrophic flow below. Proc. Natl. Acad. Sci. USA 76, 3051-3055. Sugimura, Y., and Suzuki, Y. (1988). A high-temperature catalytic oxidation method for the determination of non-volatile dissolved organic carbon in seawater by direct injection of liquid sample. Mar. Chem. 24,105-131. Sweeney, C , Hansell, D. A., Millero, F. J., Takahashi, T, Gordon, L. I., Carlson, C. A., Codispoti, L. A., Smith, W. O., Jr., and Marra, J. (2000). Biogeochemical regimes, net conmiunity production and carbon export in the Ross Sea, Antarctica. Deep-Sea Res. II47, 3369-3394. Talley, L. D. (1997). North Pacific Intermediate Water transports in the Mixed Water Region. /. Phys. Oceanogr. 27,1795-1803. Talley, L. D. (1999). Some aspects of ocean heat transport by the shallow, intermediate and deep overturning circulations. Geophys. Monogr. Sen 112,1-22. Tanoue, E. (1993). Distributional characteristics of DOC in the central Equatorial Pacific. /. Oceanogr. 49,625-639. Thomas, C , Cauwet, G., and Minster, J.-F. (1995). Dissolved organic carbon in the equatorial Atlantic Ocean. Mar Chem. 49,155-169. Vidal, M., Duarte, C. M., and Agusti, S. (1999) Dissolved organic nitrogen and phosphorus pools and fluxes in the central Atlantic Ocean. Limnol. Oceanogr 44,106-115. Wangersky, P. J. (1978). Production of dissolved organic matter. Mar Ecol. 4,115-220. Wheeler, P. A., Watkins, J. M., and Hansing, R. L. (1997). Nutrients, organic carbon and organic nitrogen in the upper water column of the Arctic Ocean: implications for the sources of dissolved organic carbon. Deep-Sea Res. II44,1571-1592. Wiebinga, C. J., and de Baar, H. J. W. (1998). Determination of the distribution of dissolved organic carbon in the Indian sector of the Southern Ocean. Mar Chem. 61,185-201. Williams, P. J. le B. (1995). Evidence for the seasonal accumulation of carbon-rich dissolved organic material, its scale in comparison with changes in particulate material and the consequential effect on net C/N assimilation ratios. Mar Chem. 51,17-29. Williams, P. M., Carlucci, A. E, and Olson, R. (1980). A deep profile of some biologically important properties in the central North Pacific. Oceanol. Acta 3,471-476. WiUiams, P. M., and Druffel, E. R. M. (1987). Radiocarbon in dissolved organic carbon in the central north Pacific Ocean. Nature 330,246 -248. Worthington, L. V. (1976) "On the North Atlantic Circulation," Vol. 6. The Johns Hopkins Oceanographic Studies, Baltimore, MD. Zhang, J., and Quay, P. D. (1997) The total organic carbon export rate based on ^^C and ^^C of DIC budgets in the equatorial Pacific region. Deep-Sea Res. II44,2163-2190.
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Chapter 16
Modeling DOM Biogeochemistry James R. Christian^
Thomas R. Anderson
Universities Space Research Association NASA Goddard Space Flight Center, Code 970.2 Greenbelt, Maryland
George Deacon Division Southampton Oceanography Centre, Southampton United Kingdom
I. Introduction II. Ecosystem Modeling Studies A. Compartments and Currencies B. Modeling Production of DOM C. Modeling Utilization and Remineralization of DOM III. Modeling the Role of DOM in Ocean Biogeochemistry A. Major Classes of Ocean Models B. Early Results: Equatorial Nutrient-Trapping C. DOM Turnover Times
D. DOM and Atmospheric CO2 E. Diagnostic Models of the North Atlantic F. Basin-to-Global Scale Ecosystem Modeling G. Inverse Models of Flows within Food Webs H. Coastal and Estuarine Systems I. Small-Scale Spatial Structure IV. Discussion and Conclusions References
I. INTRODUCTION In the 1970s and 1980s it was realized that planktonic food webs were far more complex than had previously been appreciated, and that microorganisms ^ Present address: Earth System Science InterdiscipHnary Center, University of Maryland, College Park, MD 20742. Biogeochemistry of Marine Dissolved Organic Matter Copyright 2002, Elsevier Science (USA). All rights reserved.
717
718
Christian and Anderson
constitute the majority of biomass and respiration in most planktonic systems (Pomeroy, 1974; Williams, 1981; Azam et al, 1983). This new paradigm of the "microbial loop" developed contemporaneously with a heightened interest in the ocean's role in the global carbon cycle, following the realization that changes in ocean biogeochemistry may have forced changes in atmospheric CO2 during glacial periods (Broecker, 1982) and that a large "missing sink" for atmospheric CO2 existed, in which the ocean biota might play a role (Wong, 1978; Walsh etal, 1981). Although the literature of ocean biogeochemical modeling has sometimes been concerned with one or the other of these developments without explicitly linking the two (i.e., the microbial food web is highly parameterized in some ocean biogeochemical models, and some microbial food web models are concerned primarily with organismal interactions rather than biogeochemical cycles), at least some investigators drew the connection quite early on (e.g., Pace etal, 1984). These developments predated the "discovery" of dissolved organic carbon (DOC) measured by high-temperature catalytic oxidation (HTCO) but not detected by other methods, in the late 1980s (Sugimura and Suzuki, 1988). This development heightened interest in DOC in the biogeochemical modeling community and led to the first global-scale simulations of oceanic DOC. While the original results of Sugimura and Suzuki (1988) are now considered erroneous (Suzuki, 1993), they opened the door to a different view of dissolved organic matter (DOM). In particular, it is now known that there is a substantial pool of DOM with a turnover time much less than the ocean overturning time scale (~1000 years), but long enough to allow carbon and nutrients to be remineralized far from where they were incorporated into organic matter. After elevated levels of DOC and dissolved organic nitrogen (DON) were reported using HTCO methods (Suzuki et al, 1985; Sugimura and Suzuki, 1988), a number of modeling experiments were undertaken to assess the implications of these observations for the global carbon cycle (e.g., Bacastow and Maier-Reimer, 1991; Najjar et al, 1992; Paillard et al, 1993). These experiments are of considerable interest in terms of understanding the evolution of the field, although their contemporary relevance is somewhat diminished by new information that calls into question some the assumptions employed. Most importantly, these authors took the concentration estimates of Suzuki and coworkers to be substantially accurate, and assumed that a "Redfield equivalent" pool of dissolved organic phosphorus (DOP) would eventually be observed as well. Neither of these assumptions remained tenable for long. By 1993, it had become clear that the HTCO-DOC estimates of Sugimura and Suzuki (1988) were excessive, although a pool of DOC not measured by other methods does exist (Suzuki, 1993; Hedges and Lee, 1993). Furthermore, the DON estimates of Suzuki et al (1985) were shown to be erroneous, and no clear evidence for either DON or DOP not measurable by non-HTCO methods exists (Hansen, Chapter 15).
Modeling DOM Biogeochetnistry
719
The conclusions drawn in the early global modeling experiments must therefore be reconsidered in light of an HTCO-DOC pool that is (a) considerably smaller than originally assumed, although not negligible and with similar vertical distribution, and (b) considerably out of Redfield ratio, i.e., strongly enriched in C relative to N and P. More recently, it has been shown that the equatorial nutrient-trapping and anoxicity that Bacastow and Maier-Reimer (1991) and Najjar et al. (1992) attempted to remedy by adding a DOM component to their models may be largely an artifact of the coarse resolution of the ocean circulation models employed, and can be eliminated simply by increasing resolution with no modification to the biogeochemical model (Aumont et al, 1999). Matear and Holloway (1995) also showed that these artifacts could be remedied by changing circulation fields without including any DOM component in the biogeochemical model. However, the basic conclusion of Toggweiler (1989), that advection of DOM will substantially alter the distribution of nutrients, oxygen and dissolved inorganic carbon (DIC) relative to an ocean model with only sedimentation of particulate organic matter (POM), remains sound and relevant. The need for prognostic, mechanistic models of the processes that create and consume this pool is acute, and the fact that its elemental composition deviates from Redfield ratio underscores the need for a more sophisticated treatment of variable stoichiometry in biogeochemical models.
11. ECOSYSTEM MODELING STUDIES A. COMPARTMENTS AND CURRENCIES The bulk DOM pool is still largely uncharacterized (Benner, Chapter 3) and cycling of elements through DOM is poorly understood from a mechanistic perspective (Kirchman etai, 1993a; Azam, 1998). Reducing the complexity of DOM biogeochemistry to representative and quantifiable structures in models is therefore difficult, and a diversity of approaches and model structures have been utilized (Table I). Early ecosystem modeling studies examined the role of the microbial loop in recycling of nutrients and as a pathway for carbon transfer to higher trophic levels. The models of Fasham et al. (1990) and Taylor and Joint (1990) included labile DOM and heterotrophic bacteria (HBAC) as state variables, but no slowturnover DOM pools. More recently, interest has focused on the biogeochemical role of longer-lived pools of DOM and, in particular, their contributions to export from the euphotic zone. Despite its heterogeneous nature, modelers have endeavored to categorize DOM into different classes to distinguish material that turns over rapidly from that which accumulates and can potentially be exported. Highmolecular-weight organic matter requires enzymatic hydrolysis in order to provide the simple monomers that can be taken up by bacteria (Chrost, 1990), and so in principle should be utilized more slowly than monomers. The "HSB" model developed
720
Christian and Anderson Table I Model Characteristics POM DOM
Reference
Type
State variables
Fashamefa/., 1990
OD
NPZDB
L
N
N
Billen and Becquevort, 1991
OD
B
L,S
C
C
Connolly and Coffin, 1995
OD
ZDB
L,S
C
C
Kawamiyaera/., 1995
ID
NPZD
S
N
N
Six and Maier-Reimer, 1996
3D
NPZD
S
P(C)
C
Anderson and Williams, 1998
OD
NPZDB
L,S
N(C)
N,C
LcwyetaL, 1998
ID
NPZDB
L,S
N
N
Anderson and Williams, 1999
ID
B
L,S,R
C
C
BissetX etai, 1999
ID
NPZDB
L,R
N(C)
N,C
Waish etai, 1999
3D
NPZDB
L,S
N(C)
C
Tianera/., 2000
ID
NPZDB
L
N(C)
c
Vallino, 2000
OD
NPZDB
US
N,C
N,C
DOM pools
Note. State variables: nutrient (N), phytoplankton (P), zooplankton (Z), detritus (D), and bacteria (B) are listed if present. Others not listed. DOM pools: labile (L, turnover rate hours to days), semilabile (S, weeks to months), refractory (R, decades and longer); terminology may differ in original texts. Currencies: parentheses indicate fixed C / N or C/P ratios.
by the Brussels group (Billen, 1990; Billen and Becquevort, 1991; Lancelot etai, 1991) exploited this principle by including two polymeric pools, with fast and slow rates of hydrolysis by bacterial ectoenzymes, which are converted to a common monomeric pool which is consumed rapidly by bacteria. However, the correlation between molecular weight and lability is surprisingly weak in natural DOM (Benner, Chapter 3). High-molecular-weight material can be highly bioreactive, while conversely the bulk of oceanic DOM comprises small molecules that cycle slowly or are relatively unavailable to microorganisms (Amon and Benner, 1994, 1996; Kepkay, 2000). The simplest distinction between different DOM pools can be made simply on the basis of turnover rates, without necessarily invoking underlying causes. The early work of Ogura (1975) indicated that DOM decomposition in coastal seawater occurred in two distinct phases with rates of 0.1-1 and 0.007 day"^ with a third fraction remaining unutilized. Experiments with DOM derived from phytoplankton in the laboratory also suggest a relatively small number of fractions, although the rate coefficients are quite variable (Pett, 1989; Chen and Wangersky, 1996). The bulk DOM pool can be usefully categorized into labile, semilabile, and
Modeling DOM Biogeochemistry
721 DOC (mmol m-^)
0
10
20
30
40
0 •
50
60
70
jQsemi-labil^/Q^
80
90
JQ^ 1
Qf/om
200-
(Se)
/MO
# 1 **
400-
j
# T3
600-
i
QefractorJ)
o
800-
1000- " " " " " ^ ^ ^ ^ " H P " ^ ^ ^
0
10
20
o
> •
p
1
30-9-91^ 40
o
1 50
60r
1
1
1
70
80
90
Figure 1 Vertical profile of DOC as simulated by the model of Anderson and Williams (1999), split into its component parts: labile, semilabile, and refractory. Data are for various profiles in the Atlantic (solid points) and Pacific oceans (open points) (see Anderson and Williams, 1999, for details).
refractory fractions (Kirchman etal, 1993a; Carlson and Ducklow, 1995; Cherrier et al, 1996) on the basis of turnover rates. Labile material is consumed rapidly, on time scales of hours to days, semilabile material degrades on seasonal time scales, while refractory material degrades very slowly and may be biologically inert. Anderson and Williams (1999) modeled vertical profiles of DOC in the ocean using a model based on these three fractions (Fig. 1). Many other models have employed two pools representing labile and semilabile compounds without necessarily assuming that this distinction is exactly analogous to, for example, monomers vs polymers (e.g., Connolly and Coffin, 1995; Anderson and Williams, 1998; Levy et al, 1998; Walsh et al, 1999; Vallino, 2000). The terminology regarding different fractions has been variously applied in the literature, e.g., the semilabile pool as defined above has been described as both labile (e.g.. Six and Maier-Reimer, 1996) and refractory (e.g., Walsh and Dieterle, 1994; Levy et al, 1998). Few models contain long-lived refractory pools (Anderson and WiUiams, 1999; Bissett etal, 1999a).
722
Christian and Anderson
Phytoplankton production is often limited by nutrient elements such as N or P, so one of these is usually employed as a model currency. Nitrogen is in some cases the only model currency (e.g., Fasham et al, 1990; Kawamiya et al., 1995; Levy et al, 1998). However, the growth of heterotrophic bacteria may be carbon- or energy-Umited (Kirchman, 1990; Carlson and Ducklow, 1996). Fasham et al. (1990) derived a relationship to balance the uptake of DON and ammonium based on assumed C/N ratios of bacteria and DOM of 5 and 8, respectively. Flows of carbon in multielement models are often calculated by assuming fixed C/N (or C/P) ratios for state variables. Ratios in zooplankton and bacteria are commonly different (lower) than those in phytoplankton and DOM. Elemental ratios in zooplankton and bacteria, and to a lesser extent phytoplankton, are relatively constant, whereas ratios in DOM are more variable, for example having highest C/N ratios during accumulation in spring (Williams, 1995). It is therefore necessary to stoichiometrically balance N cycling with DOC uptake and respiration by bacteria (e.g., Anderson, 1992; Goldman and Dennett, 2000). Two approaches have been used to overcome difficulties with variable DOC/DON: DOC can be included in models without associated DON, or DOC and DON can be included as separate state variables permitting varying C/N. DOC and DON are, of course, inextricably Hnked; although N-free DOC exists, organic compounds contain C and so there is no DON without DOC. The first approach is useful for modeling accumulation and turnover of DOC, but neglects the role of DON in recycling of nutrients. This approach does not permit nitrogen to enter slow-turnover DON pools, and may therefore result in overestimation of remineralization rates. Bacterial growth is assumed to be limited by DOC, and nitrogen requirements are taken from the inorganic pool (Fig. 2). The second approach is to have separate state variables for DOC and DON, giving rise to a dynamic C/N. Models of this type (e.g., Moloney and Field, 1991; Anderson and Williams, 1998; ValUno, 2000) permit a detailed examination of the roles of DOM in nutrient
CO.
co^ / I bacteria
I-co.
,.i-l phytoplankton
1 ^ m'- I ^ ^ 1
I
^ J__, U ^
-I I
DOC
zooplankton
iLr J - , 'I I I I I
U I
Figure 2 Ecosystem model structure which includes DOC but not DON. Solid lines, N or P flows; dashed lines, C flows.
723
Modeling DOM Biogeochemistry
cycling and accumulation and export of DOC and DON, but parameterization of the interactions between C and N is far from simple.
B. MODELING PRODUCTION OF DOM DOM is produced from a variety of sources, so ecosystem models need to be complex if production processes are to be fully addressed. Most ecosystem models contain phytoplankton, zooplankton, and detritus, thus providing the potential for sources to be adequately defined. Models which do not include a full ecosystem, but do contain HBAC and DOM as state variables, have been used to study DOM cycling. Billen and Becquevort (1991) modeled bacterial production in Antarctic coastal waters using observed phytoplankton biomass to estimate production of DOC. Anderson and WiUiams (1999) defined DOC production rate in the euphotic zone as afixedfraction of primary production and examined the fate of the organic carbon in a deep-water column. Some modeling studies that do include a full ecosystem include external as well as internal sources of DOM. Parsons and Kessler (1986) included a riverine source of DOC in an estuarine model. Walsh and Dieterle (1994) included a sedimentary source in their shallow-water model. Bissett et al (1999a) included a source from dinitrogen fixation without having an explicit population of N2-fixers. There are a large number of processes by which DOM is produced (Fig. 3), most of which are poorly understood. As a first approximation, these processes can be
photo-oxidation I
A
lysis
DOCI
semi-labileT
bacteria
labile
solubilization^^
detritus
A
JI.-*
exudation
phytoplankton
refractory
lysis \ s osolubilization ]
grazer-associated losses
pellets
zooplankton Figure 3 Idealized food web illustrating the four main DOC production terms (phytoplankton exudation, grazer-associated losses, lysis, detrital solubilization) and the two principal loss routes (bacterial uptake, photo-oxidation).
724
Christian and Anderson Table U Sources of DOM in Models That Include an Ecosystem Phytoplankton
Zooplankton
Lysis
Detritus
Fasham et ai, 1990
0.05pp
0.025Z
—
0.05D
Connolly and Coffin, 1995''
0.15pp
{0.07-0.14}g
—
{0.1-0.3}D
Kawamiya etai, 1995
0.135pp
—
—
0.5(0.03+ 0.0693T)D^
Six and MaierReimer, 1996
0.03(P-0.01)
0.06(Z-0.01)
Anderson and Williams, 1998
(0.05 + 0.34)pp^
0.23g
0.04B + 0.015P
0.05D
L&yy etai, 1998
0.05pp
{0.005-0.025}Z
Bissett et ai, 1999
0.05P
{0.33-0.46}g
—
Walsh et ai, 1999
0.04pp
0.5g
0.0075P
{0.02-0.04}?
0.4g
Reference
Tian et ai, 2000 Vallino, 2000
0.564pp
{0.008-0.075}D
0.132D d
—
49.6D^
Note. P, phytoplankton; Z, zooplankton; B, bacteria; D, detritus; T, temperature; pp, primary production; g, grazing rate. All rates are per day. Brackets indicate a range of values; parentheses have their standard meaning in mathematical expressions. "Includes only partial ecosystem (input observed pp). ^An equivalent amount is remineralized directly to DIN. '^First term (0.05) leakage (C, N), second term exudation (C only). ^Includes breakdown of large (sinking) to small (nonsinking) particles. ^Final value after optimization from a first guess of 0.1 day~^ with a range of 0-50, indicating that this parameter was essentially unconstrained by the data.
divided into four categories: phytoplankton exudation, grazer-associated losses, lysis, and detrital turnover. Different models have included different combinations of these terms, and parameterized them in different ways (Table II). 1. Phytoplankton Exudation Phytoplankton exudation may involve both passive "leakage" and active release. Leakage results from the permeability of the plasma membrane to low-molecularweight compounds (Bj0msen, 1988). Metabolic instabilities in algae may cause "extra" carbon to be actively exuded as DOC (Williams, 1990). High release rates
Modeling DOM Biogeochemistry
725
may be a common feature of oligotrophic waters, possibly a result of continued use of photosynthetic machinery after nutrient exhaustion (Norrman et al., 1995; Obemosterer and Hemdl, 1995). Exuded polymers may serve a number of functions, few if any of which are well understood (Decho, 1989; Hoagland et aly 1993). Literature estimates of percentage extracellular release (PER) of DOC have a mean of about 13% of primary production, although considerably higher estimates exist (Baines and Pace, 1991; Nagata, 2000). There is significant uncertainty about a mean value due to both methodological considerations and adequacy of data coverage; oceanic environments are underrepresented (Baines and Pace, 1991; Nagata, 2000). The balance of the data seem to suggest that passive leakage is not the dominant mechanism, i.e., that exudation is more closely related to primary production rather than to phytoplankton biomass (Baines and Pace, 1991), although some studies suggest the opposite (e.g., Fuhrman et al, 1980). Bj0msen (1988) argued for the representation of exudation as a "property tax" (some fraction of biomass per unit time) rather than an "income tax" (a fraction of photosynthesis) and estimated the rate as about 5% of carbon biomass per day. Models have variously used both approaches (Table II). Rates of production may differ for carbon and nitrogen. A range of compounds including simple sugars and amino acids may be leaked from cells, containing both C and N, whereas exudation due to an overflow of photosynthate might be expected to be dominated by nonnitrogenous compounds. Anderson and Williams (1998) distinguished in their model between leakage, which occurred in the C/N ratio of the phytoplankton, and exudation which was only carbon. The Bissett et al (1999a) exudation term supplied only DOC. Vallino (2000) optimized model parameters to fit mesocosm data and found that a very high C/N in phytoplankton exudate (43200), as well as an exuded fraction of greater than 50% of photosynthesis, achieved the best results. Anderson and Williams (1998) adjusted the exuded fraction in their model in order to simulate the seasonal accumulation of DOC at a station in the English Channel and similarly found that a high DOC exudation rate (PER of 29%) was required. A few models have treated exudation rate as being inversely related to photosynthetic or phytoplankton growth rate (e.g.. Pace et al, 1984; Bratbak and Thingstad, 1985), but this approach has not been favored in the more recent literature and does not appear to be supported by the available data (Baines and Pace, 1991). Anderson and Williams (1998) compared two formulations of exudation—a constant fraction of photosynthesis, or a fraction of the difference between nutrient-limited and nutrient-saturated growth rates (cf. Bratbak and Thingstad, 1985). They were unable to assert that either of these parameterizations was more useful than the other. 2. Grazer-Associated DOM Production There are several mechanisms of grazer-associated DOM production, including so-called "sloppy feeding" (release of dissolved compounds when prey cells are
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Christian and Anderson
broken by mouthparts of crustacean zooplankton), direct exudation of DOM, and egestion and dissolution of fecal material. Sloppy feeding losses are negligible if prey can be ingested whole and are likely restricted to metazoa (Nagata, 2000). Rapid pellet dissolution may provide an important mechanism of DOC production (Jumars et ai, 1989). Strom et al (1997) estimated that between 16 and 37% of algal C is released as DOC during grazing by phagotrophic protozoa. The most common modeling approach is to direct a fixed fraction of grazed material to DOM. Values assigned in this manner typically range between 0.2 and 0.4 (Table II), giving rise to large fluxes of DOM via zooplankton. Another approach has been to direct a fraction of zooplankton losses (excretion, mortality) to DOM. Several models do not have any explicit term for production of DOM by zooplankton, but direct losses to "particulate" detritus which is subsequently solubilized to DOM. Including this lag may cause small differences in the dynamic behavior of models, but it is unlikely that these differences are meaningful given the overall uncertainty regarding definitions of particulate and dissolved. Most modelers will likely continue to assign losses to "DOM" or "detritus" depending on assumptions about the size of the grazers that dominate in a particular ecosystem; in open ocean ecosystems, aflowthat is predominantly directly to DOM is appropriate (Nagata, 2000). 3. Lysis Planktonic microorganisms may be lysed by a variety of agents including viruses, bacteria, and under certain circumstances their own intrinsic hydrolytic enzymes (autolysis). Lytic processes potentially explain a great deal of DOM production, especially the more refractory fractions, as cell walls and membranes are sources of important components of DOM (Tanoue et al, 1995; McCarthy et al, 1998). There have been relatively few attempts to model the details of these processes. Models of viral infection have been developed (e.g., Murray and Jackson, 1992), although these have not yet been incorporated into biogeochemical models that fully account for the fate of the DOM produced in this process, with the exception of the very comprehensive treatment by Blackburn et al (1996). These authors modeled four biochemical pools: protein, carbohydrate, nucleic acid, and phospholipid. The DOM released during viral lysis was divided about equally between protein and nucleic acid with only minor contributions from carbohydrate and phosphoUpid, which were largely retained in "ghost" cells. Thingstad (2000) modeled multiple bacterial strains with a common protozoan predator but host-specific viruses, and showed that the overall rate of viral infection and the importance of lysis in biogeochemical cycles depends strongly on the diversity of the bacterial conmiunity. Plankton models often include a nonspecific mortality term to account for phytoplankton loss processes other than grazing and sedimentation. This term may be
Modeling DOM Biogeochemistry
727
directed to POM, DOM, or inorganic nutrients. The first models to have assigned some of this loss term to DOM appear to have been Taylor and Joint (1990), who applied a first-order loss term to all of their biota groups and assigned some fraction of this to DOC, and Moloney and Field (1991), who defined a population of "senescent" cells that were then subject to lysis to DOC. More recent models that assign some of the loss to lysis to DOC include Anderson and Williams (1998) and Walsh et al, (1999). More commonly, this term is applied to particulate organic carbon (POC), which is subsequently subject to solubilization and/or remineralization.
4. Solubilization of Particles It has been observed that the rate of solubilization of particles by hydrolytic enzyme activity may be orders of magnitude greater than the rate at which the DOM produced is respired (Smith et al, 1992), implying that most particle mass enters the dissolved phase as DOM. Particle turnover is therefore often passed directly to DOM in models (e.g., Fasham et al, 1990; Anderson and Williams, 1998; Levy et al., 1998; ValHno, 2000), although other models recycle it at least in part directly to inorganic nutrients (e.g., Bissett et al, 1999a). Fluxes are modeled as first-order rate processes in many models. Modeling the underlying mechanisms of this process is in its infancy. A basic theory exists for fragmentation of aggregates by turbulence, although there are a number of ill-constrained parameters involved (Hill, 1996). The importance of turbulence in the fragmentation process is in dispute, however, because the turbulent energy required exceeds that normally found in the ocean by several orders of magnitude (Alldredge et al, 1990; Hill, 1998). Solubilization of POM to DOM is in general a biological process, for which few quantitative models exist. Vetter et al. (1998) determined the steady-state distribution of a freely released extracellular enzyme and its hydrolysate in an idealized aggregate with a single bacterium at its center. This simple model provides little quantitative information about rates of solubilization, but can be used to estimate the ratio of hydrolysate respired by attached bacteria to that lost to the environment as DOM, which was one to two orders of magnitude greater. The flux of hydrolysate to the cell depends strongly on the diffusivity of the enzyme, with smaller enzymes producing less benefit because hydrolysis occurs, on average, further from the cell. Within the range of diffusivities and partition (between solid and liquid phase) coefficients considered, the flux of hydrolysate increased linearly with increasing release of enzyme, i.e., there was no optimal rate of release. This simple model demonstrates that it is possible for bacteria in porous aggregates to survive by releasing hydrolytic enzymes and that literature estimates of "uncoupled solubilization" from field experiments are reasonable.
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5. Lability of DOM Produced In models with multiple DOM pools, production of DOM must be allocated between the various pools. Phytoplankton exudation is usually assumed to consist solely of labile molecules (e.g., Billen and Becquevort, 1991; Anderson and Williams, 1998; Walsh et ai, 1999). However, there is marked variability between models in how other fluxes are allocated. Billen and Becquevort (1991) assumed that DOC produced by lysis and sloppy feeding was partitioned equally between their two polymeric fractions. Walsh et al (1999) allocated 40% of DOCrelated grazing losses to the labile pool, with the remainder to semilabile. Connolly and Coffin (1995) assumed that both bacteria and phytoplankton biomass contain 15% labile and 20% semilabile C, part of which is released as DOC during zooplankton grazing. Various modeling studies have adjusted the allocation of organic fluxes to different pools in order to achieve acceptable fits to data. Anderson and Williams (1998) were able to simulate the seasonal DOC increase in the English Channel (34 /xmol L~^) by partitioning 90% of DOM produced by various processes (lysis, sloppy feeding, detrital turnover) to the semilabile pool (with the remainder labile). Lowering this fraction required unrealistically high phytoplankton exudation rates in order to generate sufficient DOC to match observations. In a mesocosm experiment, Vallino (20(X)) found the best fit to data when 67% of detrital turnover went to the semilabile pool. By contrast, in the Mediterranean Sea, Levy et al (1998) found that only 15% of DOC fluxes needed to be allocated to the semilabile pool. Processes contributing to the production of refractory DOM are poorly understood and have not been extensively modeled. Anderson and Williams (1999) allocated a small fraction of the turnover of labile and semilabile pools to the refractory pool; a value of 0.35% led to a balance between production and ultraviolet (UV) photooxidation (see Section II.C.3). Bissett etal (1999a) assumed that 4.0 % of DOC consumption was released as refractory material.
C. MODELING UTILIZATION AND REMINERALIZATION OF DOM The primary loss mechanism for DOM is uptake by heterotrophic bacteria. Measurements of bacterial production and growth efficiency show that bacterial respiration accounts for a large fraction of primary production in most oceanic ecosystems (Ducklow, 1999). Some eukaryotic microorganisms (Sherr, 1988; Marchant and Scott, 1993) and metazoa (Wright and Manahan, 1989) can take up dissolved or colloidal organic matter, but it is not known how widespread or quantitatively significant this process is, and it has not to our knowledge been explicitly incorporated into models. The other sink is abiotic photooxidation by solar ultraviolet radiation. Direct photooxidation of DOC to DIC (photomineralization) may be as great as photolysis to monomers and subsequent respiration by bacteria (Miller
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and Zepp 1995; Miller and Moran 1997), although it is not known how quantitatively important this process is in the open ocean. Photochemical effects have been incorporated into several ecosystem models (Bissett et al, 1999a; Anderson and WilHams, 1999). 1. Turnover of Semilabile DOM Semilabile material is variously defined in different models, so it is unsurprising that parameterizations of its turnover vary. Connolly and Coffin (1995, p. 682) describe it as compounds that are "readily used, but are less optimal for bacterial growth." They assumed that semilabile material was utilized only after exhaustion of labile substrates and with a lower growth efficiency. Another definition is "molecules whose eventual assimilation by the bacteria requires ectoenzyme hydrolysis to the labile pool" (Anderson and Williams, 1998). Many models therefore employ Michaelis-Menten kinetics to describe turnover, which is usually passed to labile pools (Table III). However, estimates of the kinetic parameters are rare. Billen (1990) estimated parameter values from degradation of DOM derived from an algal culture; Walsh and Dieterle (1994) used these parameters in their model. Lamy et al (1999)fitthe HSB model directly to time-series data from experimental microcosms using nonlinear regression. Connolly et al (1992) and Connolly and Coffin (1995) derived values for a variety of coastal and freshwater environments; values from Santa Rosa Sound were applied to the English Channel by Anderson and Williams (1998). 2. Bacterial Utilization of Labile DOM The predominant model of uptake of dissolved organics by bacteria is a hyperbolic form similar to Michaelis-Menten kinetics, which has been widely used in ecosystem models (Davidson, 1996). Monod (1942) showed that the relationship of growth rate of bacteria in culture to substrate concentration has the form J W ^ Ks + S'
[1]
where S is the substrate concentration, /Xmax is the maximal growth rate, and ^ s is the substrate concentration at which /x=/Xinax/2. Monod's formulation has been widely adopted by the modeling community, although it lacks a strong theoretical basis (Button, 1998) and there is evidence that other hyperboHc functions give a better fit to observed growth rates (Bader, 1982). Monod's result was derived for cultures grown on simple monomers such as glucose, which some early models assumed to be the predominant form of substrate (e.g., Bratbak and Thingstad, 1985). As models have come to consider other forms of substrate the basic formulation has been retained, although experimental evidence of its applicability is limited.
730
Christian and Anderson Table III Models of DOM Cycling and l\imover Model
Bacterial model
Parameters
Fasham et al, 1990
FDM (see text)
v^ = 2.0 day"^ A:=0.5AtMN
Billen and Becquevort, 1991
Monod fn DOC
coQ = 0 . 3 v^ = 4.3 day~^ K=0.%ixMC
Connolly and Coffin, 1995
Monod fn DOC VB = 5.0 day-i
Semilabile turnover
Parameters
—
—
Monod fn DOC
z;s = 6 day~^ K=20S^iMC
Monod fn DOC
coc = 0.2 i^s = 10 day~^
UV
—
^=20.8A6MC
Kawamiya et al, 1995 Six and MaierReimer, 1996
—
Anderson and Williams, 1998
CN stoichiometry
Levy et al, 1998
FDM
Temperature dependent rate
0.03 day-i at 0°C
Monod fn phosphate
vs = 0.025 day-^ K=0.5fiMP
coc = 0.27 UB = 3.6 day~^ /i:=25/iMC
Monod fn DOC
Vs = 4.0 day~^ K=411 fiMC
= 2.0 day~^ K=0.5 fiMN
fixed rate
vs = 1.0 year~^
—
VB
Bissett et al, 1999
Min[C, N terms], C:Monod, N:after FDM
UB = 2.0 day-i /s:=130/xMC
Walsh et al, 1999
Monod fn DOC
a>C = 0.5 VB = 1.6day~^
Tian et al, 2000
Monod fn DOC
Vallino, 2000
CN stoichiometry
—
— Y
Monod fn DOC
Vs = 0.6 day~^ /s:=0.83/iMC
Y
= 0.5 day~^ K=l2.5fiMC
VB
Fixed rate coc = 0.804 VB = 40.0 day-^ ^ = 48.8AtMC
0.128 day-i
Note."\JW" ir\dicates models that include photolysis a n d / o r photomineralization. coc, carbon gross growrth efficiency; VQ, maximum bacterial growth rate (in some cases may be the product of maximum uptake rate and gross grow^th efficiency); vs, maximum semilabile uptake rate; K, half-saturation constant.
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Modeling DOM Biogeochemistry
The basic formulation of Monod has been extended in ecosystem models to address the simultaneous use of organic and inorganic nitrogen (Fasham et al, 1990; Ducklow, 1994). The N-based model of Fasham et al (1990) defines a ratio of inorganic to organic nitrogen uptake for balanced growth, given by ^=
<^c^0M
;
T— - 1,
r^i
[2]
where cOx is the growth efficiency for carbon or nitrogen, and ^DOM ^^'^ ^B are C/N ratios of DOM and bacteria, respectively. This model assumes that if there is sufficient NH4'^, dissolved inorganic nitrogen (DIN) and DON are taken up in fixed ratio (^ = 0.6). If not, DIN and DON jointly limit the bacterial growth rate. This model does not include carbon and does not consider the dependence of NH4"^ excretion on substrate C/N; excretion occurs at a constant biomass-specific rate (0.05 day-i). Excretion of nitrogen by bacteria is thought to decrease at high substrate C/N ratio (Goldman et al, 1987) as N is conserved for growth and respiration costs are met using C-rich substrates. Net nitrogen excretion, £^B, can be described by the following expression (Goldman et al, 1987; Anderson, 1992; Goldman and Dennett, 2000):
E. = uJ-^-'^),
[3]
where Uc is DOC uptake. A negative E^ requires ammonium uptake to supplement DOC as a growth substrate. Net excretion occurs only at low C/N, and supplementation of DON by anmionium occurs only if there is insufficient DON to meet N demand. If sufficient C is available then no net excretion of N occurs. Depending on the C/N of DOM, either C or N is predicted to limit growth; above a threshold C/N ratio OB/COC, N is Hmiting. At high C/N there may be insufficient NH4^ to permit full utilization of DOC for growth, and DOC can accumulate (Anderson and WiUiams, 1998; see also Thingstad et al, 1997). Net regeneration of NH4"^ is predicted to occur only when nonnitrogenous C sources are scarce and N-rich DOM is being utilized. Simple relationships between regeneration of ammonium by bacteria and respiration may not occur (Ducklow, 1994). Values of co vary considerably among models (Table III), typically between 0.25 and 0.50. A recent review of bacterial growth efficiency in the open ocean indicates a mean value of 0.15 for carbon (del Giorgio and Cole, 2000). The model of Vallino et al (1996) provides a more mechanistic basis for modeling bacterial respiration and growth efficiency, but ecosystem models to date have not generally moved beyond assuming constant values. Blackburn et al (1996) used a two-component model of bacterial respiration, with a constant fraction of DOC
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Christian and Anderson
uptake respired in addition to a constant mass-specific basal metabolism. Values of the half saturation constant for labile DOC uptake also show marked differences between models. Moreover, there is evidence that bacteria physiologically adapt to changing substrate levels, e.g., by altering the maximal uptake rate (Kirchman et al, 1993b, 1995), a phenomenon not currently considered in models. A mathematical treatment of the mechanisms underlying such adaptation is given by Button (1998). A slightly different approach to dual element modeling was taken by Bissett et al (1999a). The equations of Fasham et al (1990) were used to define rates of DON and NH4^ uptake, except that the value of ^DOM (and therefore r]) was variable, and a separate Monod function was defined for DOC. The rate of carbon uptake was then set to be the minimum of the carbon- and nitrogen-limited rates of carbon uptake. If the former, nitrogen uptake was adjusted downward to achieve balanced growth. DIN uptake was reduced first, and if DON uptake was in excess once DIN uptake was eliminated, the "excess" N was transformed into NH4'^, permitting remineralization of N when the ambient substrate pool was N rich. The model of Thingstad et al (1997, 1999) indicates that labile DOC may not be consumed rapidly by bacteria because of a "malfunctioning microbial loop." These models contain a steady-state representation of the bacteria-phytoplanktonphosphate-flagellate system, which is subject to external grazing pressure from ciliates and higher predators. Biomass of HBAC can be limited by a combination of nutrient stress and predation so that an increase in the total nutrient content (and therefore phytoplankton biomass and production) of the system can result in accumulation of labile DOC (Thingstad et al, 1997). Lags between peaks of primary and secondary (bacterial) production during blooms can be explained even if the DOM is labile (Thingstad et al, 1999). This work provided a theoretical and experimental demonstration of how a combination of predation and mineral nutrient limitation, rather than the availability of organic substrates, may control bacterial production and thus consumption of labile DOM. 3. Photochemical Effects The photochemistry of DOM has been an area of increasing interest in recent years, although most models do not contain such processes. The basic equations of aquatic photochemistry have been reviewed by Miller (1998) and Mopper and Kieber (Chapter 9) and will not be repeated here. The absorption spectrum of absorbing or "colored" DOM (CDOM) has a negative exponential shape, increasing monotonically toward shorter wavelengths. Most of the photochemical reactivity is in the ultraviolet B range (UVB, approximately 280-320 nm). A number of models exist that describe photochemical production of various compounds from DOM (e.g., Sikorski and Zika, 1993; Gnanadesikan, 1996; Preiswerk
Modeling DOM Biogeochemistry
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and Najjar, 2000), but are not discussed here as they do not explicitly model the DOM pool itself. For a general treatment of the theory of modeling meteorological and solar forcing of photochemistry in the upper ocean see Doney etal (1995). Anderson and WilHams (1999) included refractory DOM (RDOM) as one of three fractions in their model. This RDOM was not subject to direct bacterial oxidation, but was photooxidized to labile DOM which was available to bacteria. Using a photochemical breakdown rate at the ocean surface (ofo) of 0.0015 day~^ and an attenuation coefficient for UVB (A:uv) of 0.33 m ~ \ they found that a steady state was attained with an RDOM production rate of 0.35% of labile and semilabile DOM utilization by bacteria. The depth-integrated rate of photooxidation in this one-dimensional model can be approximated as aoRo/K^ (their Eq. [7]), where Ro is the concentration of RDOM at the ocean surface. This model suggested that a 10% increase in UV radiation at the ocean surface would decrease the global ocean stockof RDOM by less than 1% over 200 years. Klepperetal (1994) estimated that increased UV-induced DOM photolysis would decrease ocean carbon storage in 2070 by more than 25% relative to their baseline simulation of no change in ocean circulation or biogeochemistry with CO2-induced climate change. This effect was the largest of the seven "feedback" terms that they quantified, but was considered the most uncertain. Few details about the model are given, so it is difficult to evaluate these conclusions. The model incorporates in at least rudimentary form the ocean's overturning circulation, which is impossible in the type of model employed by Anderson and Williams (1999), and is highly relevant to the question of global DOM photooxidation rates. Bissett et al. (1999b) coupled a complete ecosystem model to a spectral model of inherent and apparent optical properties, by specifying a certain fraction of the DOC produced within the ecosystem model as "colored" and subject to photochemical reactions. Estimating these fractions is difficult, and their values in nature are largely unknown (Nelson and Siegel, Chapter 11). Bissett et al. (1999b) had observations of spectral attenuation coefficients with which to compare the model output, although their model is very complex and difficult to constrain. Modeled values of CDOM absorption in the Sargasso Sea were maximal at 60-80 m depth in autumn, which is consistent with observations (Siegel and Michaels, 1996). Ratios of the downwelling attenuation coefficients at 412 and 487 nm, which is an approximate index of attenuation due to CDOM relative to phytoplankton (Siegel and Michaels, 1996) were in the range of 1-1.2 and were generally lower than observed values except at the surface in summer. This may imply low rates of photooxidation or it may be the modeled seasonal cycle of DOC itself that is in error, rather than the photochemical model. This model was also the first to our knowledge to consider direct photomineralization to CO2.
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Christian and Anderson
III. MODELING THE ROLE OF DOM IN OCEAN BIOGEOCHEMISTRY A. MAJOR CLASSES OF OCEAN MODELS At basin to global scale, ocean models generally belong to one of two classes: ocean general circulation models (OGCMs) and box-diffusion models. The former represent the integration of the equations of motion, or a partially linearized approximation, on a grid whose resolution is generally on the order of 1-3° for basin- to global-scale models. The latter divide the ocean up into a number of boxes that exchange heat and chemical tracers according to specified rates of advective exchange and mixing coefficients ("eddy diffusivities"). The processes that are represented by these coefficients are also relevant to OGCMs, as the grid is too coarse to represent mixing processes explicitly, and the results are frequently highly sensitive to how these "sub-grid-scale" processes are represented (e.g., Danabasoglu et ai, 1994; McWilliams, 1996). An important innovation in box-diffusion models has been the inclusion of an "outcrop" box in the high latitudes that extends from the surface to greater depths than the surface boxes in lower latitudes (e.g., Siegenthaler and Joos, 1992). This permits rapid exchange of oxygen and carbon between the atmosphere and the low-latitude deep ocean via the high latitudes, as these fluxes occur in the ocean primarily along isopycnal surfaces. B. EARLY RESULTS: EQUATORIAL NUTRIENT-TRAPPING Experiments with both OGCMs and box-diffusion models were conducted in the wake of the "discovery" of HTCO-DOC to assess the effects of DOC production on the large-scale distribution of nutrients, oxygen, and DIG (e.g., Bacastow and Maier-Reimer, 1991; Najjar et al, 1992; Paillard et ai, 1993). It is important to note that not all of these simulations employed prognostic biological models: in many cases they simply estimated "new production" (NP, which is actually net community production) either by restoration of the model nutrient fields to climatological values as these are altered by upwelling and advection (Najjar et al, 1992) or as a function of nutrient concentration (Paillard et al, 1993) or nutrient concentration and irradiance (Bacastow and Maier-Reimer, 1991; Matear and Holloway, 1995). This NP is then redistributed downward to simulate sedimentation, usually according to the hyperbolic expression of Martin et al (1987). Early experiments with DOM assigned some fraction of NP to the DOM pool rather than to the sedimentation flux, allowing it to be mixed and advected in the same fashion as dissolved inorganic nutrients. Bacastow and Maier-Reimer (1991) assigned a decay rate for DOM of 0.02 year~^ (turnover time, r = 5 0 years). Najjar et al (1992) did not specify
Modeling DOM Biogeochemistry
735
r, but their model gives values of the same order. This results in a significant penetration of DOM into the mesopelagic and alters the vertical distribution of nutrients and oxygen relative to particle-only simulations. An important component to these experiments was the search for solutions to the equatorial "nutrient-trapping" problem. It had been found that sedimentation-only biogeochemical models produced large accumulations of (inorganic) nutrients and depletions of oxygen in the equatorial thermocline that were not consistent with observations (Toggweiler, 1989). Assigning some of the NP to DOM rather than to the sedimentation scheme (which results in remineralization directly below the point at which the particles are formed) seemed to remedy this problem, resulting in nutrient maxima that were deeper, weaker, and less restricted to the equatorial region (Toggweiler, 1989; Bacastow and Maier-Reimer, 1991; Najjar et al, 1992). These simulations employed OGCMs with horizontal resolution on the order of 3 ^ ° , which is inadequate for accurate simulation of the equatorial current system. These early results have been called into question on the grounds that artificialities in the circulation fields are as likely an explanation for the nutrienttrapping problem as the use of particle-only biogeochemical models. Matear and HoUoway (1995) used a simple POM-based biogeochemical model similar to that used by Bacastow and Maier-Reimer (1991) and an adjoint technique that allows particular model parameters or fields to vary in order to force selected fields closer to observations or other a priori constraints. By retaining the circulationfieldsof the basic model but allowing the new production rate at a given nutrient concentration and remineralization length scale (RLS) for sinking particles to vary, they found that an increased RLS and reduced NP could alleviate nutrient-trapping without an explicit DOM component, but not with reaHstic values of these terms. By retaining the base values of the biogeochemical parameters but allowing the circulation fields to vary, they found that small changes in circulation could achieve the same result and concluded that uncertainties about the modeled circulation were too large for definitive conclusions to be drawn regarding the relative roles of DOM and POM. More recent experiments by Aumont et al. (1999) have shown that increasing the resolution of the circulation model largely eliminates nutrient trapping without any change in the biogeochemical model. Note that the authors of the original studies appear to have been well aware that this might prove to be the case (Toggweiler, 1989; Najjar and Toggweiler, 1993). A more extensive discussion of the effects of advection schemes and grid resolution on biogeochemical models is given by Oschlies (2000).
C. D O M TURNOVER TIMES The decay rates employed in the early simulations of Bacastow and MaierReimer (1991) and Najjar et al. (1992) were called into question by Archer et al.
736
Christian and Anderson
(1997) and Yamanaka and Tajika (1997), using HTCO-DOC data not available at the time of the earUer experiments. Using a steady-state model of DOC production and consumption and an OGCM simulation of the tropical Pacific circulation, Archer et al (1997) defined a "grow in" time scale for semilabile DOC. This model reduced the production and remineralization rates to a single value (based on the observed differences between surface and deep concentrations), assuming that oligotrophic surface waters with the highest observed DOC concentrations are near steady-state with respect to production and consumption of DOC, while recently upwelled waters are not. This simple model generated optimal values of r between 30 and 120 days, suggesting that the bulk of semilabile DOC is not nearly as refractory as assumed in earlier studies. Yamanaka and Tajika (1997) used a slightly more complex model to estimate the ratio of DOC to POC produced ("production ratio") and the decay rate of semilabile DOC. They found that r's of 0.3-1 year, and production ratios of 1-2 were the most consistent with observed surface concentrations and penetration depths of semilabile DOC. These values increase and decrease, respectively, by about a factor of 2 if POM solubilization produces labile rather than semilabile DOM. An innovative aspect of this analysis is that while either the observed surface concentrations or penetration depths generate a range of approximately equivalent solutions, the two sets of observations provide orthogonal constraints (in terms of positive or negative correlation between turnover time and production ratio for statistically equivalent solutions). Only a narrow range of solutions are consistent with both. The authors note, however, that estimates of the penetration depth are imprecise, and that more observations in the 1(X) to 4(X) m depth range would make these solutions more robust. These estimates of the mean Ufetime of semilabile DOM are also consistent with the ID model results of Anderson and Williams (1999); these authors found the poorest fit to data in the 200 to 400 m depth range. It has also been shown that alleviation of nutrient trapping is possible with turnover times in this lower range (Anderson and Sarmiento, 1995), using the same circulation fields employed by Najjar ^rtz/. (1992).
D.
DOM
AND ATMOSPHERIC
CO2
There are several examples of global ocean box models applied to questions about atmospheric CO2. Models of ocean-atmosphere CO2 exchange on glacialinterglacial time scales tend to underestimate the glacial-interglacial difference (ACO2, ~100 ppm). Paillard et al. (1993) attempted to determine whether including DOM in the ocean model would alleviate this, but found that it actually increased the discrepancy (decreased ACO2 in the model) because it reduced the overall geochemical stratification of the model ocean, i.e., less transport of carbon to the deep ocean. Decreasing the turnover time of the DOM would bring ACO2
Modeling DOM Biogeochemistry
737
more in line with the particle-only model, while increasing it tends to further "smooth out" the glacial-interglacial cycle. The biogeochemical model resembles those of Bacastow and Maier-Reimer (1991) and Najjar et al (1992) in that DOM was assumed to have Redfield C/N/P ratios and a Ufetime of order 100 years. Keller and Goldstein (1995) used a variant of the model of Siegenthaler and Joos (1992) to assess the long-term consequences of a pulse of CO2 into the atmosphere or an injection into the oceanic thermocline. They found that at steady state (the simulations ran for 1500 years) a negUgible fraction (0.21%) of the "excess" carbon was found in the DOC pool. Sensitivity studies showed that an increased upwelling velocity caused a significant increase in the total DOC, due to increased input of nutrients to the surface layer. They assumed Redfield stoichiometry for DOM and modeled remineralization as a first-order process with a turnover time that appears to have been on the order of 100 years. Klepper et al (1994) used a box-diffusion model to analyze biogeochemical feedbacks to rising atmospheric CO2, but provide so few details that it is difficult to determine what if any effect DOM had on their results.
E. DIAGNOSTIC MODELS OF THE NORTH ATLANTIC
Schlitzer (1989) constructed a simple model of the North Atlantic Ocean and estimated values of new production, particle flux, and air-sea exchange of CO2 in each box by fitting the model to historical observations of nutrients, oxygen, DIG, and alkalinity. He then attempted to add a DOC component to the model based on the very Hmited data available at the time, by (1) using pre-HTGO values, (2) using values derived from the Sugimura and Suzuki (1988) Pacific data, with their surface concentrations in the first model layer {GQ < 25.5) and their deep concentrations in the other layers, and (3) calculating DOC from apparent oxygen utilization based on the correlation reported by Sugimura and Suzuki (1988). The result of this experiment was that with the pre-HTGO DOG concentrations, solutions could be derived that were consistent with the range of data constraints available, whereas when the results of Sugimura and Suzuki (1988) were used this was not possible. In experiment (2), the distributions of total G, N, and P were "incompatible with the circulation pattern of the model and with [North Adantic Deep Water] formation rates greater than 5 Sv" (Schlitzer, 1989, p. 12,791). The method used allows the circulation to change to give the best fit of the model to biogeochemical fields, but the changes required in this case were outside acceptable bounds. In experiment (3), the optimal solution was better but still unacceptable; new production was much less than the smallest literature values, and diapycnal mixing coefficients were negative in some places. Note that this experiment was conducted considerably before Suzuki's (1993) retraction of his early results. As a cautionary note, however, like other early modeling efforts in the
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"post-HTCO" era, Schlitzer (1989) appears to have assumed large pools of DON and DOP as well as DOC. Walsh et al (1992) also attempted to estimate meridional fluxes of DOM in the North Atlantic from a handful of early (and probably erroneous) HTCO-DOC estimates, using zonally integrated transport estimates for various depth strata (cf. Rintoul and Wunsch, 1991). They too found mass-balance difficulties, such as ratios of carbon and oxygen flux that were far out of Redfield ratio. The concentration estimates are generally high, but if this is attributed largely to blank-correction problems (Suzuki, 1993) the net meridional transport estimates may not be entirely fanciful. They estimated the net (southward) flux of DOC as about \~^ X 10^^ mol year~^ which would imply that DON could not balance the apparent poleward transport of DIN estimated by Rintoul and Wunsch (1991) with reasonable C/N ratios.
E BASIN-TO-GLOBAL SCALE ECOSYSTEM MODELING None of the studies discussed above employed prognostic biological models (e.g., state variables for phytoplankton and zooplankton). Prognostic ecosystem models including a DOM component have been coupled to OGCMs in the North Atlantic (Fasham etal, 1993; Sarmiento etal, 1993), the North Pacific (Kawamiya et al.y 2000), the equatorial Pacific (Toggweiler and Carson, 1995), the Arabian Sea (Ryabchenko et al, 1998), and, in only one case that we are aware of, globally (Six and Maier-Reimer, 1996). Not all of these models included an explicit population of heterotrophic bacteria; Six and Maier-Reimer (1996) and Kawamiya et al. (2000) used concentration-dependent rate equations for remineralization of DOM. In the simulations of Fasham et al (1993) and Sarmiento et al (1993), DON constituted a small fraction of total N in the North Atlantic (~0.01 /xM N, much less than particulate detritus or plankton biomass), reflecting the fact that the ecosystem model employed (Fasham et al, 1990) simulates only labile DON. Fasham et al (1993) noted that at both Bermuda (subtropical) and Ocean Weather Station "India" (OWSI, subarctic) about half of the annual supply of DON came from breakdown of detritus. Although this result is sensitive to parameter choices, it was not anticipated by the authors of the model. This source was most dominant below about 40 m depth. Convective overturning was the dominant process for removal of DON from the euphotic zone (more than an order of magnitude greater than vertical mixing or downwelling when averaged over the model grid), consistent with observations collected near Bermuda (Carlson et al, 1994; Hansell and Carlson, 2001). Convective losses were much greater at Bermuda than at OWSI, although annual mean surface concentrations were quite similar. This may reflect the lack of production in winter in the subarctic and periodic restratification in
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winter in the subtropics, but caution is required in interpreting these results as the OGCM may overestimate the vertical exchange of nitrogen by wintertime convection (McGillicuddy et al, 1998). Kawamiya et al. (2000) simulated realistic concentrations of DON (6-8 /xM) in the tropical Pacific Ocean. Their model included a prognostic phytoplankton and zooplankton model; DON consumption was parameterized by a first-order remineralization term. Their model equations indicate a temperature-dependence of this rate, but the temperature-dependence parameter was assigned a value of zero, implying a constant specific remineralization rate of 0.01 day~^. Solubilization of particulate organic nitrogen (PON) was temperature-dependent with a base rate of 0.05 day~^ and rates of ~0.3 day~^ at the temperatures characteristic of the tropics. A simple calculation gives the steady-state concentration of DON as a function of temperature, PON concentration, and the rate of production of DON by processes other than solubilization; the modeled values of 6-8 /xM are consistent with values of these expected for tropical-subtropical surface waters. The specific rate of PON solubilization is consistent with measurements of ectoenzyme activities on particles (Smith et al, 1992), and calculations based on fluxes of particles collected in sediment traps (Christian et al, 1997) or on thorium disequilibria (Mumane, 1994). Kawamiya^f al. (2000) compared their modeled DON distributions with data collected by Libby and Wheeler (1997) between 10°S and 10°N and about 95-140°W, noting the model's reproduction of a minimum at the equator and a zonal gradient (increasing westward) north of the equator, which they attributed to greater mixed layer depths in the central tropical Pacific. Six and Maier-Reimer (1996), like Kawamiya et al. (2000), employed prognostic phytoplankton and zooplankton models, but did not model bacteria and used first-order remineraHzation of DOC, with a maximal rate of 0.025 day"^. The actual rate was a function of inorganic nutrient concentration; i.e., it was assumed that nutrient limitation of HBAC would reduce the rate of remineralization (see also Thingstad et al, 1997). They did not include solubilization of POC as a source of DOC. Like Kawamiya et al. (2000), their simulated DOC concentrations were within the range of observed values (15-40 /xM at the surface, not counting the refractory "background" fraction). The highest concentrations were in the summer hemisphere, with strong enrichments to ~60° latitude in the sunmier months and maximal concentrations around 20°. DOC dominated the poleward transport of organic matter that balances equatorward transport of mineral nutrient; these transports were maximal at 10-15°N or S. These simulations showed little seasonality of surface DOM concentrations at latitudes less than about 20°, while at higher latitudes most of the surface-layer DOM appears to be turned over on annual time scales. These results could be highly sensitive to the choice of temperature or nutrients as the factor determining the remineralization rate, as these are negatively correlated in surface waters at large space and time scales.
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G. INVERSE MODELS OF FLOWS WITHIN FOOD WEBS An "inverse method" is a statistical method for fitting a model to data, and can be applied to both diagnostic (e.g., Vezina and Piatt, 1988; Jackson and Eldridge, 1992) and prognostic (e.g., Matear and Holloway, 1995; Spitz etaly 1998; Fasham etaly 1999; Vallino, 20(K)) models. Fitting of a Hnear, steady-state model of aplanktonic food web was described by Vezina and Piatt (1988), and applied to data sets collected in the English Channel and the Celtic Sea. This model estimates the flows of matter and energy among the model compartments (e.g., phytoplankton, zooplankton, heterotrophic bacteria) that best fit the data in a least-squares sense, subject to specified constraints (e.g., an upper limit to the fraction of gross photosynthesis that can be exuded as DOC), but does not specify the mathematical form of relationships among these compartments. This methodology has since been applied to data collected in various regions of the ocean (e.g., Jackson and Eldridge, 1992; Donali et ai, 1999; Vezina et al, 2000), as well as freshwater (Vezina and Pace, 1994) and sea ice (Vezina et ai, 1997) ecosystems. The solutions derived by Vezina and Piatt (1988) suggest that a majority of DOC (~65%) came from heterotrophs (DON was assumed to come only from heterotrophs). A substantial fraction (11-19%) of DOC came from the heterotrophic bacteria. There were no a priori constraints placed on this flow (whereas other groups had upper limits set on the fraction of energy intake lost to DOC), so it is not surprising that in the optimal solutions this flow would have a positive value, and little can be concluded with certainty from it. The upper limit to detrital dissolution was set at 1% day"^ Jackson and Eldridge (1992), applying the method to data collected in the Southern California Bight, discarded this constraint and found that this rate was about 6% day~^ for their data set. The flux of carbon to bacteria from DOM in the solutions of Vezina and Piatt (1988) was 16.2 nmiol C m"^ day~^ in the English Channel and 17.5 mmol C m~^ day~^ in the Celtic Sea. In the English Channel this is equivalent to 0.56% of the total DOC pool each day, or 36-40% of net primary production. In the Celtic Sea, the estimatedfluxof carbon to bacteria exceeded measured bacterial production by a factor of 21, implying a very low growth efficiency. In both systems, the calculated C/N molar ratio of the DOM consumed by bacteria was 14, and uptake rates of DON and NH4"'" were similar. In the Gulf of Riga, Donali et al. (1999) found that bacterial carbon demand significantly exceeded DOC supply in spring and autunm. Because the calculation takes account only of the mean flows during the period of the field observations, such imbalances do not violate mass balance constraints, but imply that a large amount of DOC (which was not measured) was present in the water prior to the cruises. These authors attributed this DOM to phytoplankton production rather than terrestrial input. In the subarctic Pacific, Vezina and Savenkoff (1999) calculated flows for cruises in September, February, and May. In May, steady-state solutions could not be derived, i.e., changes in the mass of some compartments over the
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course of the cruise were necessary. They calculated a net DOC accumulation on the order of 100 mg m~^ day~^ which would imply a seasonal accumulation of ~10 fjM. As with the data sets employed by Vezina and Piatt (1988), heterotrophs dominated DOC production in all seasons, with the highest autotrophic input in spring. Heterotrophs also dominated DOC production in the Gulf of St. Lawrence, which was approximately half of gross primary production during winter-spring, with protozoa accounting for the largest fraction (Vezina et al, 2000).
H. COASTAL AND ESTUARINE SYSTEMS Coastal systems are not our area of expertise, and we have not attempted to cover exhaustively work in this area, especially that which is primarily concerned with anthropogenic DOM (e.g., Yassuda etal, 2000). The principles of modeling DOM in coastal systems are essentially the same as in pelagic systems, except that one must consider allocthonous (e.g., fluvial) sources of DOM, and exchange of organic matter at the water-sediment interface. Some ecosystem models take account of the DOM flux from sediments in some fashion (e.g., Walsh and Dieterle, 1994). Decomposition of fluvial DOM has been modeled using a variety of approaches, few of which take explicit account of the biochemical composition of this material. Hopkinson et al. (1998) defined equations relating measurable quantities such as elemental composition and molecular weight to the chemical composition (e.g., aromaticity) and degree of carbon reduction of terrestrially derived DOM, which are expected to be correlated with bacterial growth rate and efficiency (Vallino etal, 1996). An important issue in oceanography is the lateral transport of autocthonously produced (plankton source) DOM, as well as inorganic nutrients and DIC, from coastal regions to the open ocean (e.g.. Pace et al, 1984; Walsh et al, 1997; Tusseau-Vuillemin et al, 1998). Walsh et al (1997) used a Lagrangian model to estimate fluxes from the coastal zone to the open ocean, concluding that there are substantial fluxes of DOM from the Bering and Chukchi seas to the Pacific and Arctic oceans. Tusseau-Vuillemin et al. (1998) found that the continental shelf of the Gulf of Lions was a source of nitrate to the open Mediterranean in winter but a sink for oceanic DIN for much of the rest of the year. The shelf sink for DIN in sunmier may imply an export of DON, and this model could in principle be used to quantify fluxes of DOM (including fluvial DOM) from the margin to the open ocean. The magnitude of this flux, however, depends on exchanges at the sediment-water interface that the authors describe as "roughly parameterized." Cifuentes and Eldridge (1998) developed a simple model of DOC dynamics along estuarine salinity gradients, which they used to identify additional allocthonous (e.g., wetlands) and autocthonous (e.g., phytoplankton) sources of DOC
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when the model deviated from patterns expected for the central processes of mixing, advection and decomposition of fluvial DOM. These authors provide a useful analysis of the relationship between DOC decomposition time scales and estuarine mixing and advection time scales, noting that the behavior of DOC in strongly mixed estuaries will be quite different than in those where advection dominates. Accurate identification of nonfluvial sources will likely improve with improved models of mixing and DOC decomposition.
I. SMALL-SCALE SPATIAL STRUCTURE Virtually all of the models cited thus far treat the plankton conmiunity as homogeneous in space on scales ranging from a few meters to hundreds of kilometers. The interaction between bacteria and their substrates takes place on viscous scales orders of magnitude smaller. The basic concepts for understanding how organisms function on these scales have been reviewed by Jackson (1987) and Jumars et al (1993). Significant results from these studies are that (a) oceanic turbulence does not enhance the flux of substrate to cells in the bacterial size range over that resulting from molecular diffusion alone, (b) motile bacteria "swim" along a biased random walk trajectory rather than a consistently up or down gradient path, and (c) the minimum size of phytoplankton cells that can be "found" by chemotactic bacteria is 2-5 /xm. Several investigators have addressed the question of whether bacteria can gain energetic advantage from chemotactic "clustering" around phytoplankton cells "leaking" DOM. Jackson (1989) addressed this question in relation to laminar sinking of phytoplankton cells, concluding that only in conditions where cells were large, abundant, and leaky did chemotaxis appear to confer significant energetic advantage for nonattached bacteria, with the caveat that the effects of turbulent fluid motion needed to be assessed before this question could be resolved. Bowen et al (1993) showed that there is a small but significant gain from chemotaxis under reahstic conditions of oceanic turbulence. Individual cells do not remain in a particular cell's halo for long except under the most quiescent conditions, and the fraction of cells found within enriched microzones is small, but chemotactic cells spend enough time within these microzones on average to derive a significant energetic advantage. Blackburn et al (1997) addressed the question of chemotaxis with a microbial food web model that was spatially structured (70 x 70 grid cells) but purely viscous (molecular diffusion only). Rather than exudation, they treated "events" of protozoan predation or cell lysis as the source of DOM. A chemically homogeneous and presumably labile pool of DOM was employed, whose concentration remained low (much less than plankton biomass). DOM concentration varied by more than two orders of magnitude in both time and space, although the total
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volume simulated was less than 1 mL. This experiment provides an additional qualitative confirmation of the value of chemotaxis and shows that the aggregate behavior of the spatially structured model differs significantly from that of a homogeneous version of the same food web model. The spatial scales and diffusivities employed are at (or perhaps beyond) the limits of the viscous assumption, so the results should be taken as an illustration and not at as a realistic simulation of the "invisible world." An important aspect of the Blackburn et al. (1997) study is that they addressed temporal as well as spatial variability of DOM production, whereas Jackson (1989) and Bowen et al. (1993) treated the phytoplankton cell as a continuous point source of DOM. In all of these experiments it is assumed that autotroph or micrograzer cells from which DOM is generated are much larger than bacteria (e.g., 20 /xm). The "encounter rate" of bacteria with the enriched "microzones" scales linearly with the number of such microzones but with the third power of their diameter (Jumars et al, 1993), so results calculated for a relatively small number of large microzones can not necessarily be extrapolated to oligotrophic waters with a larger number of smaller ones.
IV. DISCUSSION AND CONCLUSIONS Over the past two decades there have been considerable advances in the methodologies of both seawater chemistry and numerical ocean modeling. The relatively small number of high-quality observations, as well as the fundamental weakness of our understanding of interactions within microbial conmiunities (Nagata, 2000) and of the physiology of heterotrophic bacteria (Kirchman, 2000), limit what can be achieved with numerical models. For example, few estimates of the kinetic parameters defining degradation of semilabile DOM are available, and it is questionable how reliably it is possible to simulate this process in models. Estimates of the decay time scale of semilabile DOM in early models (e.g., Bacastow and Maier-Reimer, 1991; Najjar et al, 1992) are much longer than those in more recent studies (e.g.. Archer et al, 1997; Yamanaka and Tajika, 1997). The rate of attenuation of DOM concentration with depth is important for biogeochemical cycling and model validation; more observations in the thermocline and mesopelagic zone (e.g., 100-500 m) would be useful. The question of what are the optimal biological structures for use in large-scale biogeochemical modeling studies is a subtle one. The one component which appears to be required is a semilabile DOM fraction, which provides a significant contribution to export flux in many areas. But what about labile and refractory fractions and indeed heterotrophic bacteria? One important argument for the inclusion of heterotrophic bacteria and the whole microbial loop is that these organisms provide the enzymes for hydrolysis of macromolecular and even monomeric
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DOM. Without explicit treatment of bacteria it is necessary to resort to empiricism to model DOM turnover. However, this apparent advantage must be weighted against the reliability with which bacteria can be simulated, as well as our ability to mechanistically parameterize semilabile DOM turnover. Other reasons for explicit treatment of the microbial loop in models are that it may provide a link between the microbial and metazoan food webs and that bacteria compete with phytoplankton for inorganic nutrients (e.g., Bratbak and Thingstad, 1985). The question of whether to include refractory DOM in models would appear to be a matter of time scales. Anderson and Williams (1999) examined the response of this pool to increased UV and concluded that it was so slow that it may not be necessary to include refractory material dynamically in models for examining climate change within the next 200 years. Processes by which DOM is created are represented in models in varying ways. In models that do not include explicit DOM state variables, terms representing exudation, respiration, and lysis and other forms of nongrazing mortality can have essentially identical mathematical form, although the choice of processes considered and terminology used to describe them varies. Here we have shown the wide diversity that exists in the ways models that consider DOM explicitly represent cycling of organic matter. One can speculate on various causes of this variabihty— differences between systems, varying objectives, or a lack of consensus on the importance of representing different processes in models. We suggest that the last of these causes is likely to be a significant source of model variability, highlighting the need for further process studies and improved models. Determining model sensitivities to choices of processes and parameters is a necessary first step, which requires data relative to which the models' sensitivities can be adequately assessed (e.g., relatively complete seasonal cycles of DOC concentration, direct measurement of rate processes such as exudation). Ultimately, evaluation of different model formulations' performance relative to common data sets will be required. One of the earhest marine ecosystem models to consider DOM assumed that all organisms produce DOM (Pace et ai, 1984). Since then there have been both models that assumed just one or two processes were responsible, and models that specified a variety of different processes (Table II). The recent models of Anderson and Williams (1998), Walsh et al (1999), and Tian et al (2000) have incorporated a broad spectrum of processes. The mathematical formulation of these terms remains tentative and speculative, and the sensitivity of the models with respect to the formulation of these various sources need to be assessed carefully. Analysis of carbon flows within food webs seems to confirm that heterotrophs, not autotrophs, account for the largest fraction of DOC production. This conclusion needs to be examined for biases resulting from the structure of the food web models and the data to which they are fitted, but is consistent with other results and should be taken seriously by developers of ecosystem models.
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Differences in terminology between studies also confound model comparison. The distinction between what is dissolved and what is particulate is not necessarily clear (Sharp, 1973). From a biogeochemical modeling perspective, the distinction between dissolved material and suspended particles with neghgible sinking velocities is not necessarily meaningful, although the mechanisms and rates of utilization by bacteria may differ (Joint and Morris, 1982; Kepkay, 2000). Bissettetal. (1999a) gave three of their four fecal pellet fractions zero sinking velocity, but treated these differently than DOM and did not make them available to HBAC. Tian et al (2000) considered only a single "dissolved" organic fraction and two of "particulate" detritus, but the smaller of these did not sink. The inclusion of additional fractions may stem from a desire to include a reasonably complete representation of the range of microbial processes. Vertical transport is a key issue in biogeochemical cycling, so more complete tests of these various formulations' performance are desirable. There has been progress on the "demand" side (modeling the utilization of DOM by HBAC), for example, the models of Anderson and Williams (1998), Bissett et al (1999a), and VaUino (2000) allow for both C- and N-limited growth and net uptake or remineralization of DIN. Spitz et al (2001) found that the fit of their model (based on that of Fasham et al, 1990) to data from the Bermuda Atlantic Time-Series station was significantly improved by including these processes. Nevertheless, the assumptions underpinning these models need further validation. A major weakness of most models is that the biochemical composition of DOM is not explicitly considered. The composition of the mixture of substrates utilized in nature is not well known, and the variable energy content of different biochemicals with similar stoichiometry is not accounted for in models (VaUino et al, 1996; Weber, 2000). An important challenge for the near future will be to model the full C/N/P stoichiometry of bacterial growth. The biochemistry and biogeochemistry of N and P are quite different (Kirchman, 2000; Karl and Bjorkman, Chapter 6), and few models have addressed these differences. Furthermore, bacteria in aquatic ecosystems are a diverse group of organisms, and so care has to be exercised when using, for example, stoichiometric models. The physiological capacities of dominant bacterial groups can vary seasonally (Pinhassi and Hagstrom, 2000). Nutrient additions may stimulate particular types of bacteria, changing overall community composition (Fuchs et al, 2000). Only a few models have addressed the significance of UV radiation in DOM cycling, and those have focused on increases in lability resulting from photooxidation of refractory material. While exposing refractory DOM to UV radiation can increase its lability, there is also evidence that photochemical reactions can render labile DOM less available for bacterial consumption (Keil and Kirchman. 1994; Benner and Biddanda, 1998; Obemosterer et al, 1999). Simulating the balance between these opposing effects of UV radiation on DOM labiUty presents a significant future challenge for modelers.
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Among the most promising recent developments is the use of optimization techniques for statistical fitting of prognostic models to data (Spitz et al, 1998, 2001; Fasham et al, 1999; Lamy et al, 1999; Vallino, 2000). These experiments have employed physical frameworks such as a mesocosm (Vallino, 2000) and a Lagrangian, drifter-tracking cruise (Fasham et al, 1999) to minimize advective effects and make use of zero-dimensional models viable. The limited information available from these experiments results from the mismatch of model complexity and the available observational data, that is, the available analytical methodologies may not be adequate to place strong constraints on many of the terms in the models. ValUno (2000) applied a variety of parameter-estimation techniques to a model of a mesocosm experiment with four experimental treatments (control, -hDOM, +DIN, and -hDOM-hDIN). The results are somewhat disconcerting: despite the extraordinary effort expended in finding the most statistically probable solutions for the model parameters, these solutions could not be generalized from one experimental treatment to another. It is therefore unlikely that the model accurately represented the mechanisms regulating the response of the microbial community to the different experimental treatments. It is simple to find fault with particular aspects of the model or the experimental treatments; it is quite another matter to demonstrate that these artificialities and not a fundamental lack of understanding of the underlying biology are responsible for the weakness of the solutions derived. There are many areas in which biogeochemical models have not yet addressed the underlying biological mechanisms. For example, the results of Thingstad (2000) suggest that the diversity of the bacterial community may represent an important control on biogeochemical cycles. Even for a single species, a more mechanistic treatment of bacterial growth is clearly possible (Vallino et al, 1996; Button, 1998). Nonetheless, the development of modeling in the study of dissolved organic matter in the oceans has advanced rapidly over the past decade. While there are many remaining uncertainties, and many of the results cited are quite tentative, a fair amount of progress has been made. A variety of sophisticated new models, have been developed in a simplified (OD or ID) physical context, and their ability to simulate spatial and temporal variability of DOM and its effects on large-scale ocean biogeochemistry will hopefully be evaluated in the near future. There is a continuing need for improved parameterizations of the underlying processes, and coupling of these to contemporary models of the ocean circulation (cf. Doney, 1999). All of the global and most of the regional simulation experiments to date have employed fairly coarse-resolution models, and conclusions regarding biogeochemistry must be received cautiously until more realistic circulation fields are employed. Equatorial nutrient-trapping and anoxicity can be eliminated in particleonly models and may be an artifact of poor simulation of the equatorial circulation (Matear and HoUoway, 1995; Aumont etal, 1999). However, the "negative result" that DOM is not needed to eliminate these artifacts cannot be taken to imply that DOM plays a minor role in ocean biogeochemistry.
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Inclusion of DOM in models can alter the biogeochemical stratification of the ocean and the partitioning of carbon between ocean and atmosphere, decouple the C, N, and P cycles, and change the structure of food webs and the grazing pressures on phytoplankton. Quantifying these effects is difficult due to lack of data and uncertainty about model structure. Early experiments in large-scale modeling were clustered at opposite extremes, i.e., biogeochemical models with highly parameterized biology and long DOM lifetimes, and microbial food web models with a single, labile DOM pool. Both the long lifetimes assumed by the former and the low concentrations generated by the latter are probably erroneous. Proper simulation of the role of DOM in biogeochemistry would appear to require at the least that the semilabile pool be simulated, and that its lifetime is on the order of 1 year. Some recent experiments have included a single pool with a first-order remineralization rate in the semilabile range, and generated realistic concentrations and spatial and seasonal variations (Six and Maier-Reimer, 1996; Kawamiya et al, 2000). Dependence of these remineralization rates on temperature and inorganic nutrient concentration needs to be better understood, assuming that such dependence even exists. Rigorous evaluation of competing formulations against observations, combined with development more mechanistic models of the remineralization process (e.g., Vallino et al, 1996) could potentially identify weaknesses in empirical formulations and also identify situations in which they are adequate to the task at hand. Models with both a semilabile pool and an explicit HBAC population have generated realistic depth profiles (Anderson and Williams, 1999), but need to be more extensively tested with regard to temporal variations. To understand biogeochemical fluxes on interannual to interdecadal time scales, more data in the mesopelagic zone are required, along with a better understanding of why some models fit the observations poorly in this region. Fluxes between the coastal zone and the open ocean are also poorly characterized; improved models of exchanges at the sediment-water interface and of decomposition of terrestrially derived DOM need to be explored.
ACKNOWLEDGMENTS The authors acknowledge support from the NSF Biological Oceanography program, the NASA Ocean Biogeochemistry program, and the Natural Environment Research Council, UK. Hugh Ducklow, Alain Vezina, Ray Najjar, and two anonymous reviewers made helpful comments on an earlier draft of this chapter. US-JGOFS Contribution 669.
REFERENCES Alldredge, A. L., Granata, T. C , Gotschalk, C. C , and Dickey, T. D. (1990). The physical strength of marine snow and its implications for particle disaggregation in the ocean. Limnol Oceanogr. 35, 1415-1428.
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Index
AABW, see Antarctic bottom water Abiotic formation of biologically recalcitrant DOM, 133-134 removal processes, 122-123 phototransformation, 122-123 sorption of DOM onto particles, 123 Absorption of light, 513-526 CDOM as principle, 513-515 magnitude of, 515 Absorption of UV light, role of DOM in, 456-457 Absorption/fluorescence, relationship to DOC, 529-531 Accumulation of DOM, 133-137 abiotic formation of biologically recalcitrant DOM, 133-134 biotic formation of recalcitrant DOM, 134-135 limitation of bacterial growth and accumulation of biodegradable DOM, 135-136 microbial community structure and DOM utiUzation, 137 Accumulation of DOM in coastal zone and export processes export of DOM from coastal zone, 598-600 mechanism of accumulation, 595-598 Adenosine 3^ 5'-cyclic monophosphate (c-AMP), 322-323 Advection/diffusion/reaction model for DOM, description of, 65\-65%app) anoxic, nonbioturbated sediments (ANS) model, 651
bioturbated and/or bioirrigated sediments (BBS) model, 652-653 Advection/diffusion/reaction model for sediment DOC cycling, 617-623 application to anoxic sediments, 618-619 application to bioturbated and bioirrigated sediments, 619-623 Air-sea exchange of important atmospheric trace gases, photo production and, 495 Air-sea surface, organic matter at, 10 Algal blooms, harmful, potential link between DON and, 210-211 Amberlite XAD resin series, 62 Amino acids, 638-640 common, in seawater, 69-70, 72, 76-77 Ammonium formation in natural waters, 473-474 Anabaena, 330 Analytical interferences in SRP and TDP estimation, 279-280 Analytical methods for total DOM pools broad community methods comparisons, 41^4 historical perspective, 37 problem, 37-39 small group methods comparisons, 39^1 Antarctic bottom water (AABW) decrease of DOC in, 690 forms in cyclonic gyres, 706 Anoxia and sediment carbon preservation, relationship between, 649 Anoxic nonbioturbated sediments (ANS) model, 651 (app)
757
758 Anoxic sediments acetate concentration range, 637-638 application to, 618-619 APase activity, 342, 343, 344 Aquatic environments, concentrations of DON in, 155 Arabian Sea, DOC and bloom dynamics of, 695 Arachaea, 137, 220 Arctic Ocean, DOC in composition and distribution of DOC within, 674-679 C/N molar ratios, 676-677 distribution, 677-679 lignin oxidations products and stable carbon isotopes, 674-676 sources of DOC to Arctic Ocean, 667-674 biological sources with Arctic Ocean, 672-674 river runoff sources, 668-671 seawater sources, 671-672 summary of sources and sinks, 679-681 water masses and circulation, 665-667 Arctic Ocean, productivity of central, 673 Arctic Ocean waters, DOC concentrations of deep, 678 Arsenic (As) in seawater, 279 Atlantic Ocean, and, 562-563 Atmospheric CO2, DOM and, 736-737 Atmospheric trace gases, important, photo production and air-sea exchange, 495 Atmospheric ventilation, 468 ATP and related nucleotides, 319-322 Autotrophic versus heterotrophic DON utilization, 208-211 Autotrophs, 208-210 B Bacteria as DON consumer, 190-191 role in metabolizing photochemical products ofCDOM,537 Bacterial carbon demand, 120-122 Bacterial contributions to DOM, research on, 82-83,113,134-135 Bacterial DOM growth and accumulation of biodegradable DOM, limitation of, 135-136 origination and transformation of, 115-116
Index Bacterial growth efficiency, 117-120 selected from literature, 119-120 changes in, 480 Bacterial lysis, 113 Bacterial utilization of labile DOM, 116-117, 729-732 of labile radiolabeled substrates, 83 Bacterioplankton, examples of DOM released from, 116 Baltic Sea, optical oceanographers working in, 548-549 Basin scale, spatial variabihty at, 687-693 Basin-to-global scale ecosystems modehng, 738-739 Benthic DOC fluxes (BDF), 642, 643-644 Benthic DOM fluxes in ocean carbon and nitrogen cycles, role of benthic DOC fluxes, 641-644 benthic DON fluxes, 644-646 extent to which benthic DOM fluxes affect composition and reactivity of deep-water DOM, 646-648 Bermuda Atlantic Times-Series Study (BATS), 553-554 Bioactive metals in seawater, chemical speciation of, 386 Bioassay procedure, 330 Biodegradability of riverine DOM, 584-588 Biological labihty of DOM, continuum of, 130-133 Biological pump, contribution of DOC to evidence for DOC export, 702-706 exportable DOC, 707-709 Biological sources of DOC within Arctic Ocean, 672-674 Biologically available P, 329-330 Biologically labile DOM, 128-129 Biologically refractory DOM, 126-128 Biologically semilable DOM, 129-130 Biomolecules, well-defined, 537 Bioreactive pools of carbon in ocean, 123-133, 685-687 Biorefractory DOM mechanisms of formation and removal of, 80-82 reservoir, 81 Biorefractory LMW DOM in ocean, 82 Biotic consumption of DOM, 116-122 eukaryotes, 122
Index prokaryotes, 116-122 bacterial carbon demand, 120-122 ^ bacterial growth efficiency, 117-120 Bidtic DON release rate, methods for estimating, 200-202 uptake, methods for estimating, 211-212 Biotic formation of recalcitrant DOM eukaryotic sources, 134 prokWyotic sources, 134-135 Biotic sources of DON in water column, 186-200 Bioturbated and/or bioirrigated sediments (BBS) model, 652-653 (app) application to, 619-623, 624 Blackwatenrivers, distribution of CDOM of, 532 Blank problem, recognition of, 41 Blue Hght absorption, fraction of, 562 Blue shifts, observation of in excitation/emission spectra of CDOM, 533 Bomb ^^C, old oceanic carbon reservoirs, 412 Broad community methods comparison current and future, 47-48 for total DOM pools, 4 1 ^ 4 Budget of DOC fluxes to and from Arctic Ocean, 680 Bulk DON, 202 Bulk marine DOM, distribution and chemical characteristics of bulk concentration and composition, 64-68 chemical composition of isolated fractions of, 71-80 molecular composition, 68-71 Bulk seawater DOM and biochemical content, 10-11
C/N molar ratios, 676-677 C:N ratio within UDOC, 439 C:N:P stoichiometry of dissolved and particulate matter pools, 292-294 Carbohydrates, 640-641 during mesocosm, distribution of, 597 Carbon, distribution of along size continuum of organic matter in seawater, 64 Carbon and sulfur cycles, photochemistry and, 569-570 Carbon dioxide (CO2), 456 Carbon isotopic composition of DOM application of ^^^C and A^^^C of DOC in ocean margins, 430-443
759 distributions of DOC in ocean margins, 433-439 exchanges of DOC between ocean's margins and interior, 441-443 sources and inputs of UDOC to ocean margins, 439^41 vertical mixing and distribution of A^^^C-DOC in open ocean, 430-433 conventions and definitions for expressing isotopic contents carbon 13, 407-^09 carbon 14, 409-413 future challenges, 445 measurements and distributions of 8^C and A^^C of DOC in oceanic systems, 415-429 distribution of in ocean margins, 423-429 distribution of in oceanic systems, 417-423 methods used for extraction, 416 methods for extracting DOC from seawater for isotopic analysis sample oxidation, 414 sample processing, 413^14 studies, 405-407 summary, 443-445 Carbon monoxide (CO), 456 Carbon 13 isotopic contents, conventions and definitions for expressing, 407^09 signatures of organic matter, 408 Carbon 14, isotopic contents, conventions and definitions for expressing, 409^13 content of carbon pool, 409 expression of, 410 Carbon 14 PP rates, daily, and seasonally produced DOC, DON, and DOP stocks and concentrations during phytoplankton blooms for marine sites, 94-97 Carbon-oxygen mass balances and absorbence changes, photochemical DOM degradation in relation to, 503-507 Carbonyl sulfide (OCS), 456,468-472 CDOM composition, assessing, 553 Cell lysis, DOM production via, 112-113 bacterial lysis, 113 viral lysis, 112 Cell-wall-associated compound classes, 332 Cellular metabolism, coordination and regulation of, 333
760 Cellular P metabolism, 262-263 CFF colloid studies, use of, 376 Characterization by ^^P NMR, 311-313 Chemical characterization of DOM, 61-63 soHd-phase extraction for DOM isolation, 61-62 tangential-flow (or cross-flow) ultrafiltration for DOM isolation, 62-63 Chemical composition and reactivity chemical characterization of DOM, 59-64 approaches for chemical characterization, 61-63 size distribution of, 63-64 distribution and chemical characteristics of bulk marine DOM bulk concentration and composition, 64-68 chemical composition of isolated fractions of, 71-80 molecular composition, 68-71 major topics on research on cycling of DOM, ongoing and future fate of terrigenous DOM in ocean, 83-84 mechanisms of formation and removal of biorefractory DOM, 80-82 Chemical composition of DOM, 552-554 Chemical composition of DON pool, 174-185 Chemical form of colloidal metals, 385-388 Chemocentric definition for colloidal matter, 371 Chesapeake Bay sediments, 628 anoxic, 645 remineralization, 630 Chlorophyll absorption, CDOM from, 556 Chromophores, absorbing, 555 Chromophoric DOM in coastal environment distribution, 532-534 fiiture areas of research, 539 interest in, 509-510 optical properties, 513-531 absorption, 513-526 fluorescence, 526-531 sources and sinks sinks, 536-539 sources, 534-536 sunmiary, 539 Chromophoric DOM in open ocean characterization of DOM chemical composition, 552-554
Index methods for quantifying, 554-556 operational definition, 549-550 optical properties, 550-552 future advances, needs for, 571-572 global CDOM distribution controls on global CDOM distribution, 563-566 global distribution of CDOM absorption from sea WiFS, 561-563 temporal variability of global CDOM distribution, 563 implications for photochemistry and photobiology, 568-571 photochemistry and carbon and sulfur cycles, 569-570 photoinhibition of photosynthesis and microbial growth, 570-571 observed DOM dynamics impact of CDOM on underwater light field, 557 local sources and sinks of CDOM, 557-561 recent research, 547-548 short history, 548-549 relationship between DOM and CDOM in open ocean, 567-568 Cloud condensation nuclei (CCN), 486 Coastal and estuarine systems, 741-742 Coastal zone, DOM in accumulation of DOM in coastal zone and export processes, 595-600 export of DOM from coastal zone, 598-600 mechanism of accumulation, 595-598 conclusions, 600-601 estuarine processes, 588-595 degradation of DOM during estuarine mixing, 590-595 physical processes, 588-590 river inputs in, 579-588 biodegradability of riverine DOM, 584-588 estimates of discharge from river, 580-584 Colloid, definition of, 64 Colloid cycHng models, 392 Colloid-associated metals in offshore waters, studies of, 383-384 Colloidal bioactive metals, biological availability of, 395-396
Index Colloidal ligands, sources of metal-complexing, 389-390 Colloidal matter isolation of for bulk analysis, 375-380 reaction rates, 390-394 Colloidal metals, chemical form of, 385-388 Community precision for TDN analysis, 47 Composition and concentration of DON pool, 154^186 Composition and distribution of DOC within, 674-679 C/N molar ratios, 676-677 distribution, 677-679 lignin oxidation products and stable carbon isotopes, 674-676 Concentration and composition of bulk marine DOM, 64-68 C, N, and P stoichiometry in DOM, 66 colormetric analyses of dissolved carbohydrates, 66-68 Concentration and composition of DON pool, 154-186 chemical composition of DON pool, 174-185 DON distributions and correlative relationships between DON and other parameters, 155-174 methods for measuring DON concentrates, 154-155 research priorities, 186 Concentration gradients of DOM between surface and deep water, 68 Consumption processes of DOM, see Production and consumption processes of DOM Contrasting marine sediments, best fit rate parameters for DOC cycling in, 629 Controls on DOC concentrations with depth in surficial sediments, 623-626 Controls on global CDOM distribution, 563-566 Cross flow filtration (CFF), 307, 375 Cross flow ultrafiltration for DOM isolation, 62-63 Cross-linked polystyrene (XAD) resins, 414 Cyclic AMP, DOP in, 322-323 D D-DNA, 183-184 DCAA chemical structure of, 175 and DFAA, 205, 206, 213, 220-221
761 Deep ocean, concentrations in, 286-292 distributions of DOC, 689-690 DOC samples, data from, 43 DOM, extent to which benthic DOM fluxes affect composition and reactivity of, 646-648 DOM samples refractory, 5-6 as static pool, 4 exportable DOC to, 706 and surface DOC, 599 temporal variability of DOC in, 696 transit times and DOC age differences, 421 Deep pycnocline, exportable DOC into, 704, 706 Deep sediment cores, pore water DOC profiles in, 626-631 Degradation of DOM during estuarine mixing, 590-595 S^^C and A^^C of DOC in ocean margins, 430-443 distributions of DOC in ocean margins, 433-^39 exchanges of DOC between ocean's margins and interior, 441-^43 sources and inputs of UDOC to ocean margins, 439^41 vertical mixing and distribution of A^^^C-DOC in open ocean, 430-433 Denges-Atkins method of seasonal phosphate concentration dynamics, 259-260 Depth variations in DOP, 281-286 Derivative high-temperature catalytic oxidation method for DOC analysis, 15 DFAA chemical structure of, 180-181 and DCAA, 205, 206, 213, 220-221 Dialysis, 202 Dimethyl sulfide (DMS), 456, 468-469 Dimethyl sulfoxide, 469 Dinitrogen (N2) fixation, 303-304 Direct measurement of DOP compounds, 314-329 ATP and related nucleotides, 319-322 cyclic AMP, 322-323 inorganic poly-P/ and pyro Fi, 327-329 lipids, 323-326 nucleic acids, 315-319 vitamins, 326-327
762 Direct utilization of DOP, 339-342 Discharge from river, estimates of, 580-584 Dispersed HA and FA compounds, 332 Dissolved inorganic carbon (DIC), removal of, 37-38 Dissolved organic carbon (DOC) advection/diffusion/reaction model for sediment DOC cycling, 617-623 analysis, improved methods for, 9 benthic carbon fluxes, 641-646 controls on DOC concentrations with depth in surficial sediments, 623-626 deep ocean profiles of versus DON, 18 examples of light intensity, nutrient limitation, temperamre, and community structure on PER of, 104-105 general observations, 614-617 in seawater, 3 large blanks intrinsic to HTCO-based instruments, 22 measurements of concentrates, 2 pore water DOC profiles in deep sediment cores, 626-631 release rates and PER for natural assemblages of marine origin, 100-103 Dissolved organic matter (DOM) global carbon cycle and, 23 importance of, 23-25 learning experiences, 25-26 measurement of DOC and DON concentrates, 2 new DON and DOC, 13-23 operational definition of, 549-550 quantifying DOM, 36 research on, 1, 2-13 pre-1970's, 2-7 inl970's,7-ll in 1980's, 11-13 UV-based, 20 Dissolved organic matter (DOM) compositional data, 636-Ml amino acids, 638-640 carbohydrates, 640-641 volatile fatty acids (VFAs), 637-638 Dissolved organic nitrogen (DON), 631-636 analysis current and future broad community methods comparison, 47-48 benthic fluxes, 644-646 concentrates deep ocean profiles versus DON, 18
Index definition of, 153-154 dynamics concentration and composition of DON pool, 154-186 chemical composition of DON pool, 174-185 DON distributions and correlative relationships between DON and other parameters, 155-174 methods for measuring DON concentrates, 154-155 research priorities, 186 historical perspective and analytical problem, 45^6 in seawater, 2-3 sinks for DON, 207-226 heterotrophic versus autotrophic DON utilization, 208-211 literature values of DON uptake in aquatic environments, 212-222 methods for estimating biotic DON uptake, 211-212 photochemical decomposition as sink for DON, 222-223 research priorities, 223-226 small group methods comparisons, 46-47 sources of, 186-213 biotic sources of DON in water column, 186-200 literature values of DON release rates in aquatic environments, 202-212 research priorities, 206-207 methods for estimating biotic DON release rate, 200-202 summary, 227-231 turnover times for DON, 226-227 values in marine sediments, 634-635 Dissolved organic phosphorus (DOP) analysis historical perspective and analytical problem, 49-50 small group methods comparison, 50 Dissolved organic phosphorus (DOP), dynamics of conclusions and prospecms, 347-348 early years of pelagic marine P-cycle research, 258-262 pelagic marine P cycle, key pools and processes, 262-266 phosphorus (P), as essential nutrient for living organisms, 250-253
763
Index pool characterization, 306-334 biologically available P, 329-330 characterization by enzymatic characterization, 309-311 characterization by ^^P NMR, 311-313 direct measurement of DOP compounds, 314-329 majority view of DOP, 330-334 molecular weight characterization of DOP pool, 308-309 by partial photochemical oxidation, 313-314 production, utilization and remineralization, 334-347 direct utilization of DOP, 339-342 DOP interactions with light and suspended minerals, 346-347 DOP production and remineralization, 335-339 enzymes as P-cycle facilitators, 342-346 sampling, incubations, storage, and analytical considerations analytical interferences in SRP and TDP estimation, 279-280 detection of Fi and P-containing compounds in seawater, 271-279 isotopic tracers, use of in P-cycle research, 267-268 sample processing, preservation and storage, 269-270 sampling, 266-267 in sea, variation in space, 280-294 C:N:P stoichiometry of dissolved and particulate matter pools, 292-294 in deep sea, concentrations in, 286-292 regional and depth variations in DOP, 281-286 in sea, variation in time, 294-306 English Channel, 295-297 North Pacific Subtropical Gyre (NPSG), 297-306 terms, definitions and concentration units, 253-258 Dissolved polysaccharides, release of, 597 Distribution of DOC spatial variabiUty at basin scale, 687-693 temporal variability, 693-697 DOC, see Dissolved organic carbon DOC/DON Workshop, 26 DOM, see Dissolved organic matter
DON, see Dissolved organic nitrogen DOP, see Dissolved organic phosphorus Dynamic light scattering (DLS), 373
Ecological significance of DOM, 92 Ecosystem model coupled to spectral model, 733 model structure, 722 sources of DOM that include, 724 Ecosystem modeling studies, 719-743 coastal and estuarine systems, 741-742 compartments and currencies, 719-723 diagnostic models of North Atlantic, 737-738 inverse models of flows within food webs, 740-741 modeling production of DOM, 723-728 modeling utilization and remineralization of DOM, 728-733 small-scale spatial structure, 742-743 Elemental analyses, limits of, 51-52 Elemental cycles, impact of photochemistry on carbon, 458, 460-467 nitrogen and phosphorus, 473 sulfur, 467-473 English Channel DOP in, 295-297 DOP samples, 259 Enzymatic characterization of P, 309-311 Enzymes as P-cycle facilitators, 342-346 schematic presentation of role of selected, 263 Equatorial nutrient-trapping, early results, 734-735 Equatorial Pacific, DOC production in, 699 Escherichia coli, 265, 340 Estuarine and coastal systems, 741-742 Estuarine processes of DOM degradation of during mixing, 590-595 physical processes, 588-590 Eukaryotes, 122, 134 Excitation and emission spectra, 527-528 Excitation-emission matrix spectra, 527-528 Exogenous radioisotopic tracers, use of, 268 Exogenous radiotracers, 336 Export of DOM from coastal zone, 598-600 Exportable DOC, 702-709 to deep ocean, 706 into deep pycnocline, 704, 706 into upper pycnocline, 703-704
764 Extracellular phytoplankton production, 98-106 release models, 99-105 model comparison, 105-106 overflow model, 99 passive diffusion model, 105
Fate colloidal organic carbon phases in ocean waters, 369 Flow-field fractionation (flow FFF), 378-380 components and theory of FFF separation, 379 techniques, 380 Flows within food webs, inverse models of, 740 Ruorescence measurements of humic substances and CDOM, 526-531 fluorescence quantum yield and fluorescence/absorption relation, 529 fluorescent-excitation and emission spectra, 527-528 relationship of absorption/fluorescence to DOC, 529-531 Fluorescent chromophore distribution, 555 Ruorescent substances dissolved in seawater, 11 Food webs idealized, 723 inverse models of flows within, 740-741 plankton, complexity of, 717-718 Fractions of DOC, characteristics of divided by biological labiHty, 125-126 Fulvic and humic substances, 181-183
Gel formation via colloid aggregation, 394 Geopolymerization model for sediment preservation, 648 Global carbon reserves, factors controlling distribution of ^^C in, 411 Global carbon cycle importance of, 23 interest in, 60 Global CDOM distribution controls on global CDOM distribution, 563-566 global distribution of CDOM absorption from sea WiFS, 561-563 temporal variability of global CDOM distribution, 563 Global distributions of DON, 155-157 Global ocean carbon cycle, DOC in
Index bioreactive pools of carbon in ocean, 685-687 contribution of DOC to biological pump evidence for DOC export, 702-706 exportable DOC, 707-709 distribution of DOC spatial variability at basin scale, 687-693 temporal variability, 693-697 net community production of, 697-702 evidence for net production of DOC, 699-700 nutrient depletion and net production of DOC, 701-702 regional and global estimates for net production of DOC, 700-701 research priorities, 709-710 sunmiary, 711 Global open ocean DOP, 280, 281 Global pattern of CDOM absorption, 562 Global scales, extrapolating photochemical rates to, 478 Global-scale meridonial CDOM increase, 565 Grazer-associated DOM production, 725-726 Grazing-induced DOM production, 106-112 biogeochemical significance, 107, 112 macrozooplankton, 106-107 macrozooplankton, 107 GulfofMexico,DON, 173 Gulf of Riga, DOC in, 740-741
H Heterotrophic bacteria, 395 Heterotrophic versus autotrophic DON utilization, 208-211 Heterotrophs, 208 High latitudes regions, chemical characteristics of DOM in, 65 temporal variability of DOC in, 694 High-temperature catalytic oxidation (HTCO), 718 HMWDOM,613 HMWDON characteristics of, 184-185 mucous exopolymers, 115 HT(C)0, use of with oxidation, 25 method, 16, 17 HTCO-based instruments, large DOC blanks intrinsic to, 22 Humic substances, 221-222 and fulvic substances, 181, 183
765
Index Humic-bound organics, photolysis of, 492 Humification, 331 Hydrogen sulfide, photochemical degradation of, 472 Hypothesized interactions regulating mixed layer concentrations, 566
Iberian margin, DOC production in, 699 Ice in sea, DOC in, 673 In-house comparison and refereed type of comparison, differences between, 43 small, 44 Indian Ocean, and %CDOM contributions, 562-563 Individual organic N compounds and bulk DON pool, published rates of, 214-219 release rates of in field, 203 Inorganic carbon formation, photochemical dissolved, 484-485 Inorganic forms of P, 253, 256-257 Inorganic N, link between DON and, 172-174 Inorganic poly-P/ and pyro Fi, DO? in, 327-329 Intercalibration effort, 48 Inverse models of flows within food webs, 740-741 Ion retardation, 201-202 Isolated fractions of chemical composition of DOM, 71-80 amino acids analyses (THAA), 74, 75 average, 73 hydrolysis, variability in susceptibility to, 76 NMR spectroscopy, 72-73 Isotope dilution, 328 Isotopes of carbon in DOC, natural, 406 Isotopic analysis, methods for extracting DOC from seawater for, 413-414 Isotopic contents, conventions and definitions for expressing carbon 13,407-409 carbon 14, 409-413 Isotopic tracers, use of in P-cycle research, 267-268
K Key pools and processes, 262-266
Labile DOM component in surface ocean, perception, 7 Lability of DOM, 123-133 biologically labile DOM, 128-129 biologically refractory DOM, 126-128 biologically semilable DOM, 129-130 continuum of biological lability, 130-133 produced, 728 Light absorption of CDOM, methods for estimating, 555-555 Light and suspended minerals, DOP interactions with, 346-347 Lignan-derived phenols, concentrations of, 84 Lignin oxidation products and stable carbon isotopes, 674-676 Lipids, DOP in, 323-326 Literature values of DON concentrations of DOC in aquatic systems, 176-178 concentrations of N associated with humic and fulvic acids, 182 concentrations of TDN and DON, 158-170 release rates in aquatic environments, 202-206 uptake in aquatic environments, 206-222 Low latitudes, temporal variabihty of DOC in, 695-696 Low-DOC subsurface water mixes, 688 Low-molecular-weight (LMW) organic compounds, 512 Lysis, 726-727
M Macro- and macrozooplankton, 191, 198 selected examples of PER DOM release by, 106-107,108-111 Magnesium sulfate-hydrochloric acid hydrolysis, 276 Magnesium-induced-coprecipitation (MAGIC) method for Fi analysis, 274 Majority view of DOP, 330-334 Malfunctioning microbial loop hypothesis, 136 Marine colloids and trace metals analytical methods, 372-380 isolation of colloidal matter for bulk analysis, 375-380
766 Marine colloids and trace metals (continued) number concentrations of marine colloidal matter, 372-374 biological availability of colloidal bioactive metals, 395-396 chemical form of colloidal metals, 385-388 definition of, 369-372 dissolved organic carbon concentrations, 367-369 fate of colloidal organic carbon phases in ocean waters, 369 metal availability, 368 metal content of marine colloidal matter, 380-385 measurement of colloid reaction rates, 390-394 particulate-based estimates of colloidal metal concentrations, 388-389 sources of metal-complexing colloidal ligands, 389-390 sunmiary, 396-397 Marine DOP concentrations, selected, 288-289 Marine food web dynamics, DOM photochemistry and, 477 Marine microorganisms, 263 Marine sediments carbon/nitrogen values in, 634-635 sediments, values in, 634-635 Mass-balance calculation, 431 Measurement of Dissolved Organic Carbon and Nitrogen in Natural Waters, workshop on, 21 Measurements and distributions ofS^^C and A^'^C of DOC in oceanic systems, 415^29 distribution of in ocean margins, 423-429 distribution of in oceanic systems, 417-423 Measuring DON concentrates, methods for, 154-155 Mechanistic studies of DOM, 476 Meridonial fluxes of DOM in North Atlantic, 738 Meridonial trend in incident solar irradiance, 565 Mesopore protection model, 648-649 Metal content of marine colloidal matter, 380-385 availability, 368 Metal/colloidal interactions, control of by metal-specific reactions, 386-387
Index Metal-complexing colloidal ligands, sources of, 389-390 Methane thiol, 472 Micro- and macrozooplankton, 191, 198 selected examples of PER DOM release by, 107,108-111 Microbial conmiunity structure and DOM utilization, 137 Microbial growth, photoinhibition of photosynthesis and, 570-571 Microbial loop, 24, 92 Microgels, 394 Mid-latitudes, temporal variability of DOC in, 694-695 Millipore HA filters, 15 Minor sulfur species, 490-491 Mississippi plume, 220 Mississippi river DON, 173 Mixed redox sediments, 633 Mixed or no effects of photochemical DOM alteration on microbial DOM utilization, 500-502 Model comparisons of extracellular phytoplankton, 105-106 Modeling DOM chemistry ecosystem modeling studies, 719-743 basin-to-global scale ecosystems modeling, 738-739 coastal and estuarine systems, 741-742 compartments and currencies, 719-723 diagnostic models of North Atlantic, 737-738 inverse models of flows within food webs, 740-741 modeling production of DOM, 723-728 modeling utilization and remineralization of DOM, 728-733 small-scale spatial structure, 742-743 modeling role of DOM in ocean biogeochemistry, 734-737 DOM and atmospheric CO2, 736-737 DOM turnover times, 735-736 early results, equatorial nutrient-trapping, 734-735 major classes of ocean models, 734 planktonic food webs, complexity of, 717-718 Molar stoichiometrics of dissolved inorganic nutrient pools, 303 Molecular composition of DOM, 68-71 Molecular highlights of 1980's, 13
Index Molecular weight characterization of DOP pool, 308-309 Molecular-level analyses of DOM in surface ocean, 70 Monod, basic formulation of, 731 Morphoclimactic zones, water exports from, 583 Multi elemental methods of DOM pools analysis, 51
N N compounds, other organic, 222 N2 fixer, 189-190 NCP, estimate of, 698-699 Negative effects of photochemical DOM alteration on microbial DOM utilization, studies showing, 498-499 Neutral sugars, measured in seawater, 69 Nitrogen and phosphorus, impact of photochemistry on, 473 Nitrogen-to-phosphorus (N:P) ratios for total dissolved matter, 301, 302, 304 NOAA-NODC global ocean search, 280-281 Nonionic macro porous sorbents, 62 Nonlinear dependence of CDOM absorption on salinity, 532-533 Nonprotein amino acid beta-aga, observation of, 639 North Adriatic Sea, investigation in, 316 North Atlantic deep water, oxygen consumption in, 702-703 diagnostic models of, 737-738 Meridonial fluxes of DOM in, 738 North Pacific Ocean, DOC concentrates in, 8 North Pacific Subtropical Gyre (NPSG), DOP in, 297-306 NPSG alternating ecosystem state hypothesis, schematic presentation of, 305 Nucleases and related enzymes, 346 Nucleic acids, DOP in, 315-319 Number concentrations of marine colloidal matter, 372-374 Nutrient depletion and net production of DOC, 701-702 Nutrient trace metals, 382
O Observed DOM dynamics impact of CDOM on underwater light field, 557 local sources and sinks of CDOM, 557-561
767 Ocean, open, see Open ocean Ocean biogeochemistry, modeling role of DOM in, 734-737 DOM and atmospheric CO2, 736-737 DOM turnover times, 735-736 early results, equatorial nutrient-trapping, 734-735 major classes of models, 734 Ocean carbon and nitrogen cycles, role of benthic DOM fluxes in, 641-648 Ocean margins distributions of DOC in, 423^29, 433^39 and interior, exchanges of DOC between, 441^43 sources and inputs of UDOC to, 439-441 Oceanic depth profiles of DOC, analysis of, 44 Oceanic systems, distribution of A^^C and 8^^C from oceanic systems, 417^23 OCGMs with horizontal resolution, 735 OCS, photochemical production of, 471 Open ocean P cycle, 251 vertical mixing and distribution of A^^C-DOC in, 430-433 Open ocean, chromophoric DOM in characterization of DOM chemical composition, 552-554 methods for quantifying, 554-556 operational definition, 549-550 optical properties, 550-552 future advances, needs for, 571-572 global CDOM distribution controls on global CDM distribution, 563-566 global distribution of CDM absorption from SeaWiFS, 561-563 temporal variability of global CDOM distribution, 563 implications for photochemistry and photobiology, 568-571 photochemistry and carbon and sulfur cycles, 569-570 photoinhibition of photosynthesis and microbial growth, 570-571 observed DOM dynamics impact of CDOM on underwater light field, 557 local sources and sinks of CDOM, 557-561 recent research, 547-548 short history, 548-549
768 Open ocean (continued) relationship between DOM and CDOM in open ocean, 567-568 Optical properties of CDOM absorption, 513-526 for different geographic areas, 516-522 fluorescence, 526-531 Optical properties of DOM, 550-552 Organic matter released as DOM due to solubilization of particles, 114-115 Organic molecules during CFF, breakthrough of, 377-378 Organic N compounds, turnover time estimates of DON and, 228-230 Organic P fractions, 253-254, 256-257 Organic solute DOC, 406 Organic sulfur compounds, 467^73 Overflow model of extracellular phytoplankton production, 99 Oxic or mixed redox sediments, 633 Oxidation, sample, 414 Oxygen consumption, photochemical dissolved, 466-467
Pacific Ocean, and %CDOM contributions, 562-563 Pacific water, inflowing, 667 Parameter S, 523 Partial photochemical oxidation, DOP pool characterization by, 313-314 Particles, solubilization of, 727 Particulate carbohydrates (PCHOs), 640 Particulate organic carbon (POC) distributions in discrete water samples, 4-5, 8-9 Particulate-based estimates of colloidal metal concentrations, 388-389 Passive diffusion model of extracellular phytoplankton production, 105 Pee Dee Belemnite (PDB) standard, 407-408 Pelagic marine P-cycle key pools and processes, 262-266 research, early years of, 258-262 Pelagic production of DOM, study of, 595 Percent extracellular release (PER), 98-99 Permanganate oxidation, 275 Permeate, changing analyte concentrations in during processing, 377 Pho regulon, 340
Index Phosphate, photochemical formation of, 493 Phosphoinositol derivatives, 334 Phospholipids, 323-324, 325 Phosphorus and nitrogen, impact of photochemistry on, 473 Phosphorus (P), as essential nutrient for living organisms, 250-253 Phosphorylation of LPS, 333 Photobleaching and photosensitizing properties of seawater, 12 Photochemical and cycling of carbon, sulfur, nitrogen and phosphorus impact of photochemistry on elemental cycles carbon, 458, 460-467 nitrogen and phosphorus, 491 sulfur, 467^73 photochemical transformation of riverine and marsh-derived DOM inputs to sea, 457-458 role of in absorption of UV Hght, 456-457 unresolved questions and future research, 476-478 DOM photochemical reactions involving trace elements, 477^78 DOM photochemistry and marine food web dynamics, 477 extrapolating photochemical rates to global scales, 478 mechanistic studies, 476 photo production and air-sea exchange of important atmospheric trace gases, 477 Photochemical decomposition decompensation of CDOM, 569 Die photo production from DOM, 485, see also Dissolved inorganic carbon as sink for DON, 222-223 Photochemical effects of DOM, 732-733 Photochemical release from DON in whole water, rates of, 224-226 Photochemistry, impact on carbon, 458, 460-467 photochemical dissolved inorganic carbon formation and oxygen consumption, 466-467 sequential photochemical-microbial DOC degradation, 459, 460-475 Photochemistry and photobiology, implications for, 568-571 photochemistry and carbon and sulfur cycles, 569-570
Index photoinhibition of photosynthesis and microbial growth, 570-571 Photodegradation products, main, 458 Photoinhibition of photosynthesis and microbial growth, 570-571 Photolysis of humic-bound organics, 492 Photon correlation spectroscopy, 373 Photoplankton, 722 Phototransformation of recalcitrant DOM, 122-123 Phytoplankton, 188-189 and colloid phase, 395 exudation, 724-725 and zooplankton models, 739 P/ and P-containing compounds in seawater, detection of, 271-279 analysis of P/, 271-274 analysis of TDP, 274-279 Planktonic food webs, complexity of, 717-718 Polymer gel size in seawater as function of time after conventional filtration, 393 Polymeric low-molecular-weight compounds (pLMWDOM),613 Polysaccharides, synthesis of, 333 Pool characterization, 306-334 biologically available P, 329-330 characterization by enzymatic characterization, 309-311 characterization by ^^P NMR, 311-313 direct measurement of DOP compounds, 314-329 majority view of DOP, 330-334 molecular weight characterization of DOP pool, 308-309 by partial photochemical oxidation, 313-314 pools and processes, key, 262-266 Pore water DOC profiles in deep sediment cores, 626-631 DOM in sediment carbon preservation, role of, 648-649 DON concentrations, 632-633 size/reactivity (PWSR) model, 613 Positive effects of photochemical DOM alteration on microbial DOM utilization, studies showing, 490-497 (app) Potentiometric versus manometric methods of measuring seawater, 23-24
769 Process of production of DOM bacterial DOM, origination and transformation of, 115-116 DOM production via cell lysis, 112-113 extracellular phytoplankton production, 98-106 grazing-induced DOM production, 106-112 solubilization of particles, 113-115 Prochlorococcus species, 299, 301 Production, utilization and remineralization of DOP, 334-347 direct utiUzation of DOP, 339-342 DOP interactions with light and suspended minerals, 346-347 DOP production and remineralization, 335-339 enzymes as P-cycle facilitators, 342-346 Production and consumption processes of DOM accumulation of DOM, 133-137 abiotic formation of biologically recalcitrant DOM, 133-134 biotic formation of recalcitrant DOM, 134-135 limitation of bacterial growth and accumulation of biodegradable DOM, 135-136 microbial community structure and DOM utilization, ecological significance of DOM, 92 lability of DOM, 123-133 biologically labile DOM, 128-129 biologically refractory DOM, 126-128 biologically semilable DOM, 129-130 continuum of biological lability, 130-133 production process, 92-116 bacterial DOM, origination and transformation of, 115-116 DOM production via cell lysis, 112-113 extracellular phytoplankton production, 98-106 grazing-induced DOM production, 106-112 solubilization of particles, 113-115 removal process of DOM, 116-123 abiotic removal processes, 122-123 biotic consumption of DOM, 116-122 Production of DOC, net community, 697-702 evidence for net production of DOC, 699-700 nutrient depletion and net production of DOC, 701-702
770 Production of DOC, net community (continued) regional and global estimates for net production of DOC, 700-701 Production of DOM, modeling, 723-728 grazer-associated DOM production, 725-726 lability of DOM produced, 728 lysis, 726-727 phytoplankton exudation, 724-725 solubilization of particles, 727 Prokaryotes, 116-122, 134-135 bacterial carbon demand, 120-122 bacterial growth efficiency, 117-120 Protein-like class, 528 Pt-catalyzed combustion column and procedure, 15 HTCO units for DOC and DON analyses, 21 Published rates of DON release rates of individual organic N compounds in field, 203 summary of, 192-197 Pycnocline, exportable DOC into deep pycnocline, 704, 706 upper Pycnocline, 703-704
Quantifying DOM, methods for, 554-556 Quantifying pool of DOM in sea and other aquatic environments analysis broad community methods comparisons, 41-^W historical perspective, 37 problem, 37-39 small group methods comparisons, 3 9 ^ 1 dissolved organic nitrogen analysis current and future broad community methods comparison, 47-48 historical perspective and analytical problem, 45-^6 small group methods comparisons, 46-47 dissolved organic phosphorus analysis historical perspective and analytical problem, 49-50 small group methods comparison, 50 interest in, 35-37 limits of elemental analyses, 51-52 methods, diagram of, 38 multielemental methods, 51 reference materials, need for continual, 52-54
Index Quantitative assay for total dissolved phosphomonoester P, 310 Quantitative constraints on organic matter cycHng, 24 Quantitative determination of D-ATP, 320 Quantitative estimation of DOP, 271 Quantitative importance of coupled biological-photochemical pathways for photoremineralization of DOM, 459 Quantitative tracers of terrestrial organic matter, use of, 674-675 Quantum yield spectra for photochemical reactions, 569 Quantum yields for OCS photo production, apparent, 471
Radiocarbon ages of DOM in deep Atlantic and Pacific oceans, 82 Radiocarbon-based equivalent age of carbon-containing materials, estimation of, 410 Rapid cycling of bioactive elements with ocean, 24 Recalcitrant DOM, biotic formation of, 134-135 Reference materials for total DOM pools, need for continual, 52-54 Refractory CDOM, 572 Refractory DOM (RDOM), 733 Regional and depth variations in DOP, 281-286 Regional and global estimates for net production of DOC, 700-701 Remineralization of DOP, 335-339 and modeling utiUzation of DOM, 728-733 bacterial utilization of labile DOM, 729-732 models of DOM cycling and turnover, 730 photochemical effects, 732-733 turnover of semilabile DOM, 729 Removal process of DOM, 116-123 abiotic removal processes, 122-123 biotic consumption of DOM, 116-122 Research priorities, 709-710 for DON, 186, 206-207, 223-226 River inputs to coastal zone, 579-588 biodegradabiUty of riverine DOM, 584-588
Index estimates of discharge from river, 580-584 River runoff sources of DOC, 668-671 Riverine DOC, 457-458 DOM, biodegradability of, 584-588 and marsh-derived DOM inputs to sea, photochemical transformation of, 457^58 Rivers in Arctic concentrations of DOC and TOC in, 669 flux of DOC from into Arctic Ocean, 669 Ross Sea, rate of DOC production of, 699
S, parameter, 523-524 value of, 524 S, slope parameter, 550-511 S, values of observed for river end members, 533 Sample processing, preservation and storage, of DOP, 269-270 Sampling DOP, 266-267 Sargasso Sea CDOM observations, 563 seasonal scale, 561 DOC concentrations in, 694-695, 700 western, 695 Sea, DOP in, variation in space, 280-294 C:N:P stoichiometry of dissolved and particulate matter pools, 292-294 in deep sea, concentrations in, 286-292 regional and depth variations in DOP, 281-286 variation in time, 294-306 English Channel, 295-297 North Pacific Subtropical Gyre (NPSG), 297-306 Sea ice, DOC in, 673 SeaWiFS, global distribution of CDOM absorption from, 561-563 Seasonal dependence of CDOM fluorescence, 530 Seasonal variations of DON, 172 Seawater bar and shield representation of dissolved matter in, 252 DOM, origin of, 331
771 methods for extracting DOC from for isotopic analysis sample oxidation, 414 sample processing, 413^14 photochemical loss of DMS in, 468^69 sources of DOC, 671-672 Seawater HMW DOM, analysis of by solid state, 77 Seawater humic substances (SHS), 10 Sediment carbon oxidation rate, 625 Sediment pore waters appendix: description of DOM advection/diffusion/reaction model, 651-653 benthic DOM fluxes in ocean carbon and nitrogen cycles, role of benthic DOC fluxes, 641-644 benthic DON fluxes, 644-646 extent to which benthic DOM fluxes affect composition and reactivity of deep-water DOM, 646-648 conclusions and suggestions for future research, 650 Dissolved organic carbon in sediment pore waters (DOC) advection/diffusion/reaction model for sediment DOC cycling, 617-623 controls on DOC concentrations with depth in surficial sediments, 623-626 general observations, 614-617 pore water DOC profiles in deep sediment cores, 626-631 DOM compositional data, 636-641 amino acids, 638-640 carbohydrates, 640-641 volatile fatty acids (VFAs), 637-638 dissolved organic nitrogen (DON), 631-636 values in marine sediments, 634-635 pore-water DOM in sediment carbon preservation, role of, 648-649 scientific background, 612-614 Semilabile DOM, turnover of, 729 Sephadex-gel-filtration method, 15 Sequential photochemical-microbial DOC degradation, 459, 460-465 evaluating, 460 Shallow sediments, see Surficial sediments Short-term biological events, 696-697
772 Siberian Shelf Seas, DOC concentration versus salinity in, 670 Sinks and sources of CDOM, local, 557-561 and sources, summary of, 679-681 of terrestrial CDOM, 536-539 Sinks for DON, 207-226 heterotrophic versus autotrophic DON utilization, 208-211 literature values of DON uptake in aquatic environments, 212-222 methods for estimating biotic DON uptake, 211-212 photochemical decomposition as sink for DON, 222-223 research priorities, 223-226 Size distribution of DOM, 63-64 Small group methods comparisons, 46-47 of total DOM pools, 3 9 ^ 1 of DOP analysis, 50 Small-scale spatial structure, 742-743 Solar irradiance, incident, 565 Solid-phase extraction for DOM isolation, 61-62 Solid-state cross-polarized magic angle spinning (CPMAS), 78 SolubiUzation of DOM particles, 113-115, 727 Soluble ligand model, 387 Sorption of DOM onto particles, 123 Sources and sinks, 534-536 ofCDOM, local, 557-561 Sources of DOC to Arctic Ocean, 667-674 biological sources within Arctic Ocean, 672-674 and links, summary of, 679-681 river runoff sources, 668-671 seawater sources, 671-672 Space, DOP variations in, 280-294 Spatial and temporal scales, examination of, 533 Spatial variability at basin scale, 687-693 deep-ocean distributions, 689-690 historical data, 692-693 relation to productivity, 690-692 upper ocean distributions, 687-689 Spectral irradiance, decrease, 556 Spectral model coupled to ecosystem model, 733 Stable carbon isotopes and lignin oxidation products, 674-676
Index Stratification in ocean, role in controlling DOC concentrations, 692 Subeuphotic zone DOP measurements, 285 Subsurface maxima in fluorescent CDOM, 558-559 Subtropical mode water formation, 704 Sugars, neutral, measured in seawater, 69, 76-77 Sulfur and carbon cycles, photochemistry and, 569-570 impact of photochemistry on, 467-473 carbonyl sulfide, 468-472 dimethyl sulfide, 468-469 dimethyl sulfoxide, 469 minor sulfur species, 472-473 Surface water and DOC transfer, 599 map with geographic information and schematic circulation of, 666 Surficial sediments, controls on DOC concentrations with depth in, 623-626 Synchronous spectra, 527-528 Syringyl and vanillyl phenols, 676
Tangential-flow or cross-flow ultrafiltration for DOM isolation, 62-63 ultrafiltration and solid-state-cross-polarized magic angle spinning (CPMAS), 312-313 TDP analysis of, 274-279 measurement of, 255 methods, comprehensive, 277-278 Temporal variability of DOC, 693-697 deep ocean, 696 high latitudes, 694 low latitudes, 695-696 mid-latitudes, 694-695 short-term biological events, 696-697 summary, 697 Temporal variability of global CDOM distribution, 563 Terrestrially dominated regions, 534-535 Terrigenous dissolved organic matter (DOM) input of to Arctic Ocean, 665-666, 675 in ocean, fate of, 83-84 mechanisms of removal of, 84
773
Index Thermoclines of major ocean basins, main, 703-704 Three-box scavenging model, 391 Three-dimensional excitation, 527-528 Three-source isotopic mixing models, 437 results, 438 Time, DOP variations in, 294-306 Time series of CDOM absorption coefficient, 564 Total dissolved carbohydrates (DCHOs), 640-641 Total dissolved free amino acids (TDFAAs), 638-639 Total dissolved nitrogen (TDN) in seawater, 13-14 Trace elements DOM photochemical reactions involving, 477-^78 atmospheric trace gases, atmospheric, 477 Trace metals and marine colloids analytical methods, 372-380 biological availability of colloidal bioactive metals, 395-396 chemical form of colloidal metals, 385-388 definition of, 369-372 dissolved organic carbon concentrations, 367-369 measurement of colloid reaction rates, 390-394 particulate-based estimates of colloidal metal concentrations, 388-389 sources of metal-complexing colloidal Ugands, 389-390 sunmiary, 396-397 Transmission electron microscope images of marine colloidal matter from depth profile, 374 Trichodesmium, 190 population, 304 Turnover times DOM, 735-736 estimates of DON and organic N compounds, 228-230 Two- and three-source mass balance models, 429, 432^33 calculations, 429, 437 Two-component steady-state inputs of margin-derived and surface-ocean-derived DOC to deep open ocean, 442
U UDOC, sources and inputs to ocean margins, 439-441 Ultrafiltration (UF), or cross-flow filtration (CFF), 414 Ultraviolet (UV) absorption to detect yellow organic substances, 3 ^ fluorometer, use of, 671 photooxidation, 255, 276-277 UV-based DOC measurements, 20 Underwater light field, impact of CDOM on, 557 Upper ocean distributions of DOC, 687-689 Upper pycnocline, exportable DOC into, 703-704 Urea, 174, 205, 219 Utilization and remineralization of DOM, modeling, 728-733
Vanillyl and syringyl phenols, 676 Ventilation of deep pycnocline, 704, 706 Vertical diffusive mixing into water column, 710 Vertical distributions of D-DNA, 317, 318 Vertical mixing and distribution of A^^C-DOC in open ocean, 430-433 Vertical profiles of DON, 157, 171-172 Vertical Transport and Exchange (VERTEX) program, 299 Viral lysis, 112 Viruses, 198-200 Vitamins, DOP in, 326-327 Volatile fatty acids (VFAs), 637-638 Volume-based concentrations of colloidal trace metals, 84
W Water, deep, see Deep water Water column overturn, distribution of sites of, 698 Water discharge and DOC, relationship between, 586-588 Water insoluble or hydrophobic DOP compounds, 341 Water masses and circulation, 665-667
Index
774 Wavelength dependence for photochemical loss ofDMS,469 WCO, see Wet chemical oxidation Wet chemical isolation, 201, 204 Wet chemical oxidation (WCO), 21 method, 37, 38-39, 45, 51 World rivers drainage area, total discharge volume and carbon fluxes in, 581-582 major role of in global water cycle, 580
X XAD ion, exchange resins, 550 resins, 414 XAD-2, 9 retaining seawater on, 62 XAD-8 resins, 62 Zooplankton and phytoplankton models, 739
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Surface DOP 70 N
65N
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Figure 13 Compilation of near surface ocean DOP concentrations (|LLM P ) for samples collected in the Baltic Sea and surrounding coastal regions. These data were obtained from the NOAA-NODC using their World Wide Web-based online search program and are neither time-averaged nor contemporaneous measurements. Stations are indicated by white circles.
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Figure 14 As in Figure 13, except for samples collected off the west coast of South America.
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Longitude E Figure 5 Global distribution of (A) absorption coefficient of CDM at 443 nm (ensemble mean estimates using data from Sep. 1997 to Jun. 2000), (B) the % contribution of CDM to total non-water light absorption based on SeaWiFS observations of ocean color spectra (Siegel et al, in press), and (C) global surface ocean DOC distribution (^mol I'l) inferred from global surveys of DOC and empirical relationships between DOC and sea surface temperature (D. Hansell, pers. commun. 2000, Siegel et al, in press). Central gyre regions where DOC accumulates are typically regions of lower CDM concentration (Fig. 5), as increased stratification leads to increased bleaching of CDM. (Panel C courtesy of D. Hansell and C. Pequignet.)
60°S
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Figure 2 Meridional sections of DOC in the Southern Hemisphere. (A) the central Indian Ocean nominally along 80°E; (B) the western South Pacific along 170°W; and (C) the eastern South Pacific along 1057110°W. Note the uplifting of contours in the Equatorial Pacific and surface accumulations in the subtropical gyres. See Fig. 1 for locations of sections. Labels on the figures indicate ocean section designations by the World Ocean Circulation Experiment (WOCE). In the section from the eastem South Pacific (C), the location of the Equatorial Undercurrent and its contribution to equatorial upwelling and downwelling is indicated. The approximate position of the main thermocline is indicated by the dashed line, and the general circulation patterns are shown by the arrows [low DOC Circumpolar Deep Water (CDW) upwells to the surface; Antarctic Intermediate Water (AAIW) subducts toward the equator; convergence in the gyres leads to downwelling of DOC enriched surface waters].
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Figure 6 Time-series of DOC in the western Sargasso Sea near Bermuda (top) and the North Pacific near Hawaii (bottom). Note the differences in DOC contour scales. SeasonaHty in the Sargasso Sea is evident both in the DOC and temperature contours (shallow contour is 24°C; deeper contour is 20°C), while DOC seasonahty is absent near Hawaii. Data from the Bermuda Atiantic Time-series Study (BATS) and Hawaiian Ocean Time-series (HOT) programs, respectively.
Figure 3 Zonal section of DOC along the equator in the Pacific Ocean. The data are a compilation collected in Autumn 1992 (Peltzer and Hayward, 1996; 110°W to 140°W) and in Autumn 1994 (Hansen etal, 1997b; 150°Wto 170°E), during similar ENSO states. Note the shoaling of low DOC, Equatorial Undercurrent (EUC) to the east. The high concentrations west of the dateline are associated with the Western Pacific Warm Pool (WPWP). The dashed lines serve to delineate the various water masses described. Figure 4 Zonal sections of DOC in the North Atlantic Ocean, along 43°-49°N (top) and 24°N (bottom). Labels on the figures indicate ocean section designations by WOCE.
400 Juiy94
Oct.94
Jan.95
Apr.95
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U o Ho O
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8
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Figure 7 Top: DOC, overlain by isotherms, during 12 months (July 1994-July 1995) in the Sargasso Sea at the BATS site. Note the seasonal overturn of the water column, the downward mixing of DOC, and the summer maximum in DOC associated with high water column stability. Bottom: DOC stocks (moles m-^) during the period. Note the increase in DOC stock during the period of overturn, both over the upper 250 m (reflecting total net DOC production) and at 100-250 m (reflecting export of DOC to those depths).
