ENCYCLOPEDIA OF
OCEAN SCIENCES SECOND EDITION
Editor-in-chief
JOHN H. STEELE
Editors
STEVE A. THORPE KARL K. TUREKIAN
Boston • Heidelberg • London • New York • Oxford Paris • San Diego • San Francisco • Singapore • Sydney • Tokyo Academic Press is an imprint of Elsevier
(c) 2011 Elsevier Inc. All Rights Reserved.
ENCYCLOPEDIA OF
OCEAN SCIENCES SECOND EDITION
(c) 2011 Elsevier Inc. All Rights Reserved.
Subject Area Volumes from the Second Edition Climate & Oceans edited by Karl K. Turekian Elements of Physical Oceanography edited by Steve A. Thorpe Marine Biology edited by John H. Steele Marine Chemistry & Geochemistry edited by Karl K. Turekian Marine Ecological Processes edited by John H. Steele Marine Geology & Geophysics edited by Karl K. Turekian Marine Policy & Economics guest edited by Porter Hoagland, Marine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts Measurement Techniques, Sensors & Platforms edited by Steve A. Thorpe Ocean Currents edited by Steve A. Thorpe The Coastal Ocean edited by Karl K. Turekian The Upper Ocean edited by Steve A. Thorpe
(c) 2011 Elsevier Inc. All Rights Reserved.
ENCYCLOPEDIA OF
OCEAN SCIENCES SECOND EDITION Volume 2: D - F Editor-in-chief
JOHN H. STEELE
Editors
STEVE A. THORPE KARL K. TUREKIAN
Boston • Heidelberg • London • New York • Oxford Paris • San Diego • San Francisco • Singapore • Sydney • Tokyo Academic Press is an imprint of Elsevier
(c) 2011 Elsevier Inc. All Rights Reserved.
Academic Press is an imprint of Elsevier 32 Jamestown Road, London NW1 7BY, UK 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA Copyright ^ 2009 Elsevier Ltd. All rights reserved
The following articles are US government works in the public domain and are not subject to copyright: Fish Predation and Mortality; International Organizations; Large Marine Ecosystems; Ocean Circulation: Meridional Overturning Circulation; Salt Marsh Vegetation; Satellite Passive-Microwave Measurements of Sea Ice; Satellite Oceanography, History and Introductory Concepts; Satellite Remote Sensing: Ocean Color; Science of Ocean Climate Models; Wind- and Buoyancy-Forced Upper Ocean. Fish Migration, Horizontal Crown Copyright 2001 Turbulence Sensors Canadian Crown Copyright 2001 No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher
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ISBN: 978-0-12-375044-0
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Editors
Editor-in-chief John H. Steele Marine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA
Editors Steve A. Thorpe National Oceanography Centre, University of Southampton Southampton, UK School of Ocean Sciences, University of Bangor, Menai Bridge, Anglesey, UK Karl K. Turekian Yale University, Department of Geology and Geophysics, New Haven, Connecticut, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
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Editorial Advisory Board John H. S. Blaxter Scottish Association for Marine Science Dunstaffnage Marine Laboratory Oban Argyll, UK Quentin Bone The Marine Biological Association of the United Kingdom Plymouth, UK Kenneth H. Brink Woods Hole Oceanographic Institution Woods Hole MA, USA Harry L. Bryden School of Ocean and Earth Science James Rennell Division University of Southampton Empress Dock Southampton, UK Robert Clark University of Newcastle upon Tyne Marine Sciences and Coastal Management Newcastle upon Tyne, UK J. Kirk Cochran State University of New York at Stony Brook Marine Sciences Research Center Stony Brook NY, USA Jeremy S. Collie Coastal Institute Graduate School of Oceanography University of Rhode Island South Ferry Road Narragansett RI, USA
Paul G. Falkowski Departments of Geological Sciences & Marine & Coastal Sciences Institute of Marine & Coastal Sciences School of Environmental & Biological Sciences Rutgers University New Brunswick NJ, USA Mike Fashamw Southampton Oceanography Centre University of Southampton Southampton UK John G. Field MArine REsearch (MA-RE) Institute University of Cape Town Rondebosch South Africa Michael Fogarty NOAA, National Marine Fisheries Service Woods Hole MA, USA Wilford D. Gardner Department of Oceanography Texas A&M University College Station TX, USA Ann Gargett Old Dominion University Center for Coastal Physical Oceanography Crittenton Hall Norfolk VA, USA
Peter J. Cook Australian Petroleum Cooperative Research Centre Canberra, Australia
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Robert A. Duce Departments of Oceanography and Atmospheric Sciences Texas A&M University College Station TX, USA
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deceased
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Editorial Advisory Board
Christopher Garrett University of Victoria Department of Physics Victoria British Columbia, Canada
Lindsay Lairdw Aberdeen University Zoology Department Aberdeen UK
W. John Gould Southampton Oceanography Centre University of Southampton Southampton UK
Peter S. Liss University of East Anglia School of Environmental Sciences Norwich, UK
John S. Grayw Institute of Marine Biology and Limnology University of Oslo Blindern Oslo, Norway
Ken Macdonald University of California Department of Geological Sciences Santa Barbara CA, USA
Gwyn Griffiths Southampton Oceanography Centre University of Southampton Southampton UK
Dennis McGillicuddy Woods Hole Oceanographic Institution Woods Hole MA, USA Alasdair McIntyre University of Aberdeen Department of Zoology Aberdeen UK
Stephen J. Hall World Fish Center Penang Malaysia Roger Harris Plymouth Marine Laboratory West Hoe Plymouth, UK Porter Hoagland Woods Hole Oceanographic Institution Woods Hole MA, USA George L. Hunt Jr. University of California, Irvine Department of Ecology and Evolutionary Biology Irvine CA, USA William J. Jenkins Woods Hole Oceanographic Institution Woods Hole MA, USA
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deceased
W. Kendall Melville Scripps Institution of Oceanography UC San Diego La Jolla CA, USA John Milliman College of William and Mary School of Marine Sciences Gloucester Point VA, USA James N. Moum College of Oceanic and Atmospheric Sciences Oregon State University Corvallis OR, USA Michael M. Mullinw Scripps Institution of Oceanography Marine Life Research Group University of California San Diego La Jolla CA, USA
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Editorial Advisory Board
Yoshiyuki Nozakiw University of Tokyo The Ocean Research Institute Nakano-ku Tokyo Japan
Ellen Thomas Yale University Department of Geology and Geophysics New Haven CT, USA
John Orcutt Scripps Institution of Oceanography Institute of Geophysics and Planetary Physics La Jolla CA, USA Richard F. Pittenger Woods Hole Oceanographic Institution Woods Hole MA, USA Gerold Siedler Universita¨t Kiel Institut fua¨r Meereskunde Kiel Germany
Peter L. Tyack Woods Hole Oceanographic Institution Woods Hole MA, USA Bruce A. Warren Woods Hole Oceanographic Institution Woods Hole MA, USA Wilford F. Weeks University of Alaska Fairbanks Department of Geology and Geophysics Fairbanks AK, USA
Robert C. Spindel University of Washington Applied Physics Laboratory Seattle WA, USA
Robert A. Weller Woods Hole Oceanographic Institution Woods Hole MA, USA
Colin P. Summerhayes Scientific Committee on Antarctic Research (SCAR) Scott Polar Institute Cambridge, UK
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Stewart Turner Australian National University Research School of Earth Sciences Canberra Australia
James A. Yoder Woods Hole Oceanographic Institution Woods Hole MA, USA
deceased
(c) 2011 Elsevier Inc. All Rights Reserved.
Preface to Second Print Edition The first edition of the Encyclopedia of Ocean Sciences, published in print form in 2001, has proven to be a valuable asset for the marine science community – and more generally. The continuing rapid increase in electronic access to academic material led us initially to publish the second edition electronically. We have now added this print version of the second edition because of a demonstrated need for such a product. The encyclopedia can now be accessed in print or electronic format according to the preferences and needs of individuals and institutions. In this edition there are 54 new articles, 67 revisions of previous articles, and a completely revised and improved index. We are grateful to the members of the Editorial Advisory Board, nearly all of whom have stayed with us during the lengthy process of going electronic. The transition from Academic Press to Elsevier occurred between the two editions. We thank Dr. Debbie Tranter of Elsevier for her efforts to see this edition through its final stages.
Preface to First Edition In 1942, a monumental volume was published on The Oceans by H. U. Sverdrup, M. W. Johnson, and R. H. Fleming. It was comprehensive and covered the knowledge at that time of the scientific study of the oceans. This seminal book helped to initiate the tremendous burgeoning of marine research that occurred during the following decades. The Encyclopedia of Ocean Sciences aims to embody the great growth of knowledge in a major new reference work. There have been remarkable new approaches to the study of the oceans that blur the distinctions between the physical, chemical, biological, and geological disciplines. New theories and technologies have expanded our knowledge of ocean processes. For example, plate tectonics has revolutionized our view not only of the geology and geophysics of the seafloor but also of ocean chemistry and biology. Satellite remote sensing provides a global vision as well as detailed understanding of the close coupling of ocean physics and biology at local and regional scales. Exploration, fishing, warfare, and the impact of storms have driven the past study of the seas, but we now have a great public awareness of and concern with broader social and economic issues affecting the oceans. For this reason, we have invited articles explicitly on marine policy and environmental topics, as well as encouraged authors to address these aspects of their particular subjects. We believe the encyclopedia should be of use to those involved with policy and management as well as to students and researchers. Over 400 scientists have contributed to this description of what we now know about the oceans. They are distinguished researchers who have generously shared their knowledge of this ever-growing body of science. We are extremely grateful to all these authors, whose ability to write concisely on complex subjects has generated a perspective on our science that we, as editors, believe will enhance the appreciation of the oceans, their uses, and the research ahead. It has been a major challenge for the members of the Editorial Advisory Board to cover such a heterogeneous subject. Their knowledge of the diverse areas of research has guaranteed comprehensive coverage of the ocean sciences. The Board contributed significantly by suggesting topics, persuading authors to contribute, and reviewing drafts. Many of them wrote Overviews that give broad descriptions of major parts of the ocean sciences. Clearly, it was the dedicated involvement of the Editorial Advisory Board that made this venture successful. Such a massive enterprise as a multivolume encyclopedia would not be possible without the long-term commitment of the staff of the Major Reference Works team at Academic Press. In particular, we are very grateful for the consistent support of our Senior Developmental Editor, Colin McNeil, who has worked so well with us throughout the whole process. Also, we are very pleased that new technology permits enhanced search and retrieval through the Internet. We believe this will make the encyclopedia much more accessible to individual researchers and students.
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Preface to Second Print Edition
In Memoriam During the creation of the Encyclopedia of Ocean Sciences and also in several cases prior to the publication of the electronic Second Edition, several Associate Editors or designated Associate Editors died. We specifically acknowledge their role in making this work an effective publication. They are Mike Fasham, John S. Gray, Lindsay Laird, Michael Mullin and Yoshiyuki Nozaki. J. H. Steele, S. A. Thorpe, and K. K. Turekian Editors
(c) 2011 Elsevier Inc. All Rights Reserved.
Guide to Use of the Encyclopedia
Introductory Points In devising the vision and structure for the Encyclopedia, the Editors have striven to unite and interrelate all current knowledge that can be designated ‘‘Ocean Sciences’’. To aid users of the Encyclopedia, this new reference work offers intuitive searching and extensive cross-linking of content. These features are explained in more detail below.
Structure of the Encyclopedia The material in the Encyclopedia is arranged as a series of articles in alphabetical order. To help you realize the full potential of the material in the Encyclopedia we have provided three features to help you find the topic of your choice.
1. Contents Lists Your first point of reference will probably be the contents list. The contents list appearing in each volume will provide you with the page number of the article. Alternatively you may choose to browse through a volume using the alphabetical order of the articles as your guide. To assist you in identifying your location within the Encyclopedia a running headline indicates the current article.
2. Cross References All of the articles in the encyclopedia have heen extensively cross referenced. The cross references, which appear at the end of each article, have heen provided at three levels: i. To indicate if a topic is discussed in greater detail elsewhere.
ACOUSTICS, ARCTIC See also: Acoustics in Marine Sediments. Acoustic Noise. Acoustics, Shallow Water. Arctic Ocean Circulation. Bioacoustics. Ice–ocean interaction. Nepheloid Layers. North Atlantic Oscillation (NAO). Ocean Circulation: Meridional Overturning Circulation. Platforms: Autonomous Underwater Vehicles. Satellite Passive-Microwave Measurements of Sea Ice. Sea Ice. Sea Ice: Overview. Seals. Seismic Structure. Tomography. Under-Ice Boundary Layer. Water Types and Water Masses.
ii. To draw the reader’s attention to parallel discussions in other articles. ACOUSTICS, ARCTIC See also: Acoustics in Marine Sediments. Acoustic Noise. Acoustics, Shallow Water. Arctic Ocean Circulation. Bioacoustics. Ice–ocean interaction. Nepheloid Layers. North Atlantic Oscillation (NAO). Ocean Circulation: Meridional Overturning Circulation. Platforms: Autonomous Underwater Vehicles. Satellite Passive-Microwave Measurements of Sea Ice. Sea Ice. Sea Ice: Overview. Seals. Seismic Structure. Tomography. Under-Ice Boundary Layer. Water Types and Water Masses.
(c) 2011 Elsevier Inc. All Rights Reserved.
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Guide to Use of the Encyclopedia
iii. To indicate material that broadens the discussion.
ACOUSTICS, ARCTIC See also: Acoustics in Marine Sediments. Acoustic Noise. Acoustics, Shallow Water. Arctic Ocean Circulation. Bioacoustics. Ice–ocean interaction. Nepheloid Layers. North Atlantic Oscillation (NAO). Ocean Circulation: Meridional Overturning Circulation. Platforms: Autonomous Underwater Vehicles. Satellite Passive-Microwave Measurements of Sea Ice. Sea Ice. Sea Ice: Overview. Seals. Seismic Structure. Tomography. Under-Ice Boundary Layer. Water Types and Water Masses.
3. Index The index will provide you with the volume and page number where the material is to be located, and the index entries differentiate between material that is a whole article, is part of an article or is data presented in a table or figure. On the opening page of the index detailed notes are provided.
4. Appendices In addition to the articles that form the main body of the encyclopedia, there are a number of appendices which provide bathymetric charts and lists of data used throughout the encyclopedia. The appendices are located in volume 6, before the index.
5. Contributors A full list of contributors appears at the beginning of volume 1.
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors Volume 1 E E Adams
N Caputi
Massachusetts Institute of Technology, Cambridge, MA, USA
Fisheries WA Research Division, North Beach, WA, Australia
T Akal
C A Carlson
NATO SACLANT Undersea Research Centre, La Spezia, Italy
University of California, Santa Barbara, CA, USA H Chamley
R Arimoto New Mexico State University, Carlsbad, NM, USA
Universite´ de Lille 1, Villeneuve d’Ascq, France R Chester
J L Bannister The Western Australian Museum, Perth, Western Australia
Liverpool University, Liverpool, Merseyside, UK V Christensen University of British Columbia, Vancouver, BC, Canada
E D Barton University of Wales, Bangor, UK
J W Dacey
N R Bates Bermuda Biological Station for Research, St George’s, Bermuda, USA
Woods Hole Oceanographic Institution, Woods Hole, MA, USA R A Duce
A Beckmann
Texas A&M University, College Station, TX, USA
Alfred-Wegener-Institut fu¨r Polar und Meeresforschung, Bremerhaven, Germany
H W Ducklow
P S Bell
The College of William and Mary, Gloucester Point, VA, USA
Proudman Oceanographic Laboratory, Liverpool, UK I Dyer G Birnbaum
Marblehead, MA, USA
Alfred-Wegener-Institut fu¨r Polar und Meeresforschung, Bremerhaven, Germany
D W Dyrssen Gothenburg University, Go¨teborg, Sweden
B O Blanton The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA E A Boyle Massachusetts Institute of Technology, Cambridge, MA, USA
S M Evans Newcastle University, Newcastle, UK I Everson Anglia Ruskin University, Cambridge, UK
P Boyle
J W Farrington
University of Aberdeen, Aberdeen, UK
Woods Hole Oceanographic Institution, MA, USA
D M Bush
M Fieux
State University of West Georgia, Carrollton, GA, USA
Universite´ Pierre et Marie Curie, Paris, France
K Caldeira
R A Fine
Stanford University, Stanford, CA, USA
University of Miami, Miami, FL, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contributors
K G Foote Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA L Franc¸ois University of Lie`ge, Lie`ge, Belgium M A M Friedrichs Old Dominion University, Norfolk, VA, USA T Gaston National Wildlife Research Centre, Quebec, Canada J Gemmrich University of Victoria, Victoria, BC, Canada Y Godde´ris University of Lie`ge, Lie`ge, Belgium D R Godschalk University of North Carolina, Chapel Hill, NC, USA A J Gooday Southampton Oceanography Centre, Southampton, UK A L Gordon Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA D A Hansell University of Miami, Miami FL, USA L W Harding Jr University of Maryland, College Park, MD, USA R Harris Plymouth Marine Laboratory, Plymouth, UK P J Herring Southampton Oceanography Centre, Southampton, UK B M Hickey University of Washington, Seattle, WA, USA M A Hixon Oregon State University, Corvallis, OR, USA E E Hofmann Old Dominion University, Norfolk, VA, USA S Honjo Woods Hole Oceanographic Institution, Woods Hole, MA, USA D J Howell Newcastle University, Newcastle, UK J M Huthnance CCMS Proudman Oceanographic Laboratory, Wirral, UK B Ja¨hne University of Heidelberg, Heidelberg, Germany F B Jensen SACLANT Undersea Research Centre, La Spezia, Italy A John Sir Alister Hardy Foundation for Ocean Science, Plymouth, UK
C D Jones University of Washington, Seattle, WA, USA P F Kingston Heriot-Watt University, Edinburgh, UK W Krauss Institut fu¨r Meereskunde an der Universita¨t Kiel, Kiel, Germany W A Kuperman Scripps Institution of Oceanography, University of California, San Diego, CA, USA D Lal Scripps Institute of Oceanography, University of California San Diego, La Jolla, CA, USA C S Law Plymouth Marine Laboratory, The Hoe, Plymouth, UK W J Lindberg University of Florida, Gainesville, FL, USA J R E Lutjeharms University of Cape Town, Rondebosch, South Africa P Malanotte-Rizzoli Massachusetts Institute of Technology, Cambridge, MA, USA W R Martin Woods Hole Oceanographic Institution, Woods Hole, MA, USA R P Matano Oregon State University, Corvallis, OR, USA J W McManus University of Miami, Miami, FL, USA G M McMurtry University of Hawaii at Manoa, Honolulu, HI, USA R Melville-Smith Fisheries WA Research Division, North Beach, WA, Australia P N Mikhalevsky Science Applications International Corporation, McLean, VA, USA W D Miller University of Maryland, College Park, MD, USA D Monahan University of New Hampshire, Durham, NH, USA J C Moore University of California at Santa Cruz, Santa Cruz, CA, USA A Morel Universite´ Pierre et Marie Curie, Villefranche-sur-Mer, France R Narayanaswamy The University of Manchester, Manchester, UK
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors W J Neal Grand Valley State University, Allendale, MI, USA D Pauly University of British Columbia, Vancouver, BC, Canada J W Penn Fisheries WA Research Division, North Beach, WA, Australia L C Peterson University of Miami, Miami, FL, USA S G Philander Princeton University, Princeton, NJ, USA N J Pilcher Universiti Malaysia Sarawak, Sarawak, Malaysia O H Pilkey Duke University, Durham, NC, USA
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D H Shull Western Washington University, Bellingham, WA, USA D K Steinberg College of William and Mary, Gloucester Pt, VA, USA L Stramma University of Kiel, Kiel, Germany R N Swift NASA Goddard Space Flight Center, Wallops Island, VA, USA T Takahashi Lamont Doherty Earth Observatory, Columbia University, Palisades, NY, USA P D Thorne Proudman Oceanographic Laboratory, Liverpool, UK
A R Piola Universidad de Buenos Aires, Buenos Aires, Argentina J M Prospero University of Miami, Miami, FL, USA S Rahmstorf Potsdam Institute for Climate Impact Research, Potsdam, Germany P C Reid SAHFOS, Plymouth, UK G Reverdin LEGOS, Toulouse Cedex, France S R Rintoul CSIRO Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, TAS, Australia J M Roberts Scottish Association for Marine Science, Oban, UK P A Rona Rutgers University, New Brunswick, NJ, USA T C Royer Old Dominion University, Norfolk, VA, USA B Rudels Finnish Institute of Marine Research, Helsinki, Finland
P L Tyack Woods Hole Oceanographic Institution, Woods Hole, USA T Tyrrell National Oceanography Centre, Southampton, UK F E Werner The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA E A Widder Harbor Branch Oceanographic Institution, Fort Pierce, FL, USA D J Wildish Fisheries and Oceans Canada, St. Andrews, NB, Canada A J Williams, III Woods Hole Oceanographic Institution, Woods Hole, MA, USA D K Woolf Southampton Oceanography Centre, Southampton, UK
W Seaman University of Florida, Gainesville, FL, USA
C W Wright NASA Goddard Space Flight Center, Wallops Island, VA, USA
F Sevilla, III, University of Santo Tomas, Manila,The Philippines
J D Wright Rutgers University, Piscataway, NJ, USA
L V Shannon University of Cape Town, Cape Town, South Africa
J R Young The Natural History Museum, London, UK
G I Shapiro University of Plymouth, Plymouth, UK
H J Zemmelink University of Groningen, Haren, The Netherlands
A D Short University of Sydney, Sydney, Australia
W Zenk Universita¨t Kiel, Kiel, Germany
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contributors
Volume 2 G P Arnold Centre for Environment, Fisheries & Aquaculture Science, Suffolk, UK
K Dyer University of Plymouth, Plymouth, UK
K M Bailey Alaska Fisheries Science Center, Seattle, WA, USA
M Elliott Institute of Estuarine and Coastal Studies, University of Hull, Hull, UK
J G Baldauf Texas A&M University, College Station, TX, USA
D M Farmer Institute of Ocean Sciences, Sidney, BC, Canada
J Bascompte CSIC, Seville, Spain
A V Fedorov Yale University, New Haven, CT, USA
A Belgrano Institute of Marine Research, Lysekil, Sweden
M J Fogarty Northeast Fisheries Science Center, National Marine Fisheries Service, Woods Hole, MA, USA
O A Bergstad Institute of Marine Research, Flødevigen His, Norway J H S Blaxter Scottish Association for Marine Science, Argyll, UK
R Fonteyne Agricultural Research Centre, Ghent, Oostende, Belgium
Q Bone The Marine Biological Association of the United Kingdom, Plymouth, UK
D J Fornari Woods Hole Oceanographic Institution, Woods Hole, USA
I Boyd University of St. Andrews, St. Andrews, UK
A E Gargett Old Dominion University, Norfolk, VA, USA
K M Brander DTU Aqua, Charlottenlund, Denmark and International Council for the Exploration of the Sea (ICES), Copenhagen, Denmark
C H Gibson University of California, San Diego, La Jolla, CA, USA
J N Brown Yale University, New Haven, CT, USA T K Chereskin University of California San Diego, La Jolla, CA, USA J S Collie Danish Institute for Fisheries Research, Charlottenlund, Denmark and University of Rhode Island, Narragansett, RI, USA G Cresswell CSIRO Marine Research, Tasmania, Australia
J D M Gordon Scottish Association for Marine Science, Argyll, UK J F Grassle Rutgers University, New Brunswick, New Jersey, USA S J Hall Flinders University, Adelaide, SA, Australia N Hanson University of St. Andrews, St. Andrews, UK P J B Hart University of Leicester, Leicester, UK
J Davenport University College Cork, Cork, Ireland
K R Helfrich Woods Hole Oceanographic Institution, Woods Hole, MA, USA
R H Douglas City University, London, UK
D M Higgs University of Windsor, Windsor, ON, Canada
S Draxler Karl-Franzens-Universita¨t Graz, Graz, Austria
N G Hogg Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J T Duffy-Anderson Alaska Fisheries Science Center, Seattle, WA, USA J A Dunne Santa Fe Institute, Santa Fe, NM, USA and Pacific Ecoinformatics and Computational Ecology Lab, Berkely, CA, USA
E D Houde University of Maryland, Solomons, MD, USA V N de Jonge Department of Marine Biology, Groningen University, Haren, The Netherlands
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors K Katsaros Atlantic Oceanographic and Meteorological Laboratory, NOAA, Miami, FL, USA J M Klymak University of Victoria, Victoria, BC, Canada M Kucera Eberhard Karls Universita¨t Tu¨bingen, Tu¨bingen, Germany R S Lampitt University of Southampton, Southampton, UK J R N Lazier Bedford Institute of Oceanography, NS, Canada J R Ledwell Woods Hole Oceanographic Institution, Woods Hole, MA, USA P F J Lermusiaux Harvard University, Cambridge, MA, USA M E Lippitsch Karl-Franzens-Universita¨t Graz, Graz, Austria
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T J Pitcher University of British Columbia, Vancouver, Canada A N Popper University of Maryland, College Park, MD, USA J F Price Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA R D Prien Southampton Oceanography Centre, Southampton, UK A-L Reysenbach Portland State University, Portland, OR, USA P L Richardson Woods Hole Oceanographic Institution, Woods Hole, MA, USA A R Robinson Harvard University, Cambridge, MA, USA M D J Sayer Dunstaffnage Marine Laboratory, Oban, Argyll, UK
B J McCay Rutgers University, New Brunswick, NJ, USA
R W Schmitt Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J D McCleave University of Maine, Orono, ME, USA
J Scott DERA Winfrith, Dorchester, Dorset, UK
D Minchin Marine Organism Investigations, Killaloe, Republic of Ireland
M P Sissenwine Northeast Fisheries Science Center, Woods Hole, MA, USA
C M Moore University of Essex, Colchester, UK K Moran University of Rhode Island, Narragansett, RI, USA G R Munro University of British Columbia, Vancouver, BC, Canada J D Nash Oregon State University, Corvallis, Oregon, OR, USA A C Naveira Garabato University of Southampton, Southampton, UK
T P Smith Northeast Fisheries Science Center, Woods Hole, MA, USA P V R Snelgrove Memorial University of Newfoundland, St John’s, NL, Canada M A Spall Woods Hole Oceanographic Institution, Woods Hole, MA, USA A Stigebrandt University of Gothenburg, Gothenburg, Sweden D A V Stow University of Southampton, Southampton, UK
J D Neilson Department of Fisheries and Oceans, New Brunswick, Canada
D J Suggett University of Essex, Colchester, UK
Y Nozakiw University of Tokyo, Tokyo, Japan
U R Sumaila University of British Columbia, Vancouver, BC, Canada
R I Perry Department of Fisheries and Oceans, British Columbia, Canada S G Philander Princeton University, Princeton, NJ, USA w
Deceased.
K S Tande Norwegian College of Fishery Science, Tromsø, Norway S A Thorpe National Oceanography Centre, Southampton, UK R S J Tol Economic and Social Research Institute, Dublin, Republic of Ireland
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contributors
K E Trenberth National Center for Atmospheric Research, Boulder, CO, USA J J Videler Groningen University, Haren, The Netherlands
R S Wells Chicago Zoological Society, Sarasota, FL, USA D C Wilson Institute for Fisheries Management and Coastal Community Development, Hirtshals, Denmark
Volume 3 S Ali Plymouth Marine Laboratory, Plymouth, UK
K H Coale Moss Landing Marine Laboratories, CA, USA
J T Andrews University of Colorado, Boulder, CO, USA
M F Coffins University of Texas at Austin, Austin, TX, USA
M A de Angelis Humboldt State University, Arcata, CA, USA
P J Corkeron James Cook University, Townsville, Australia
A J Arp Romberg Tiburon Center for Environment Studies, Tiburon, CA, USA
B C Coull University of South Carolina, Columbia, SC, USA
T Askew Harbor Branch Oceanographic Institute, Ft Pierce, FL, USA
R Cowen University of Miami, Miami, FL, USA
R D Ballard Institute for Exploration, Mystic, CT, USA
G Cresswell CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia
G Barnabe´ Universite´ de Montpellier II, France
D S Cronan Royal School of Mines, London, UK
R S K Barnes University of Cambridge, Cambridge, UK
J Csirke Food and Agriculture Organization of the United Nations, Rome, Italy
E D Barton University of Wales, Bangor, Menai Bridge, Anglesey, UK
G A Cutter Old Dominion University, Norfolk, VA, USA
D Bhattacharya University of Iowa, Iowa City, IA, USA
D J DeMaster North Carolina State University, Raleigh, NC, USA
F von Blanckenburg Universita¨t Bern, Bern, Switzerland
T D Dickey University of California, Santa Barbara, CA, USA
D R Bohnenstiehl North Carolina State University, Raleigh, NC, USA
D Diemand Coriolis, Shoreham, VT, USA
H L Bryden University of Southampton, Southampton, UK J Burger Rutgers University, Piscataway, NJ, USA S M Carbotte Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA G T Chandler University of South Carolina, Columbia, SC, USA M A Charette Woods Hole Oceanographic Institution, Woods Hole, MA, USA
C S M Doake British Antarctic Survey, Cambridge, UK C M Domingues CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia C J Donlon Space Applications Institute, Ispra, Italy F Doumenge Muse´e Oce´anographique de Monaco, Monaco R A Dunn University of Hawaii at Manoa, Honolulu, HI, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors R P Dziak Oregon State University/National Oceanic and Atmospheric Administration, Hatfield Marine Science Center, Newport, OR, USA O Eldholm University of Oslo, Oslo, Norway
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S K Hooker University of St. Andrews, St. Andrews, UK H Hotta Japan Marine Science & Technology Center, Japan G R Ierley University of California San Diego, La Jolla, CA, USA
A E Ellis Marine Laboratory, Aberdeen, Scotland, UK C R Engle University of Arkansas at Pine Bluff, Pine Bluff, AR, USA C C Eriksen University of Washington, Seattle, WA, USA V Ettwein University College London, London, UK S Farrow Carnegie Mellon University, Pittsburgh, PA, USA M Fieux Universite´ Pierre et Marie Curie, Paris Cedex, France N Forteath Inspection Head Wharf, TAS, Australia J D Gage Scottish Association for Marine Science, Oban, UK S M Garcia Food and Agriculture Organization of the United Nations, Rome, Italy
G Ito University of Hawaii at Manoa, Honolulu, HI, USA J Jacoby Woods Hole Oceanographic Institution, Woods Hole, MA, USA M J Kaiser Bangor University, Bangor, UK A E S Kemp University of Southampton, Southampton Oceanography Centre, Southampton, UK W M Kemp University of Maryland Center for Environmental Science, Cambridge, MD, USA V S Kennedy University of Maryland, Cambridge, MD, USA P F Kingston Heriot-Watt University, Edinburgh, UK G L Kooyman University of California San Diego, CA, USA
C Garrett University of Victoria, VIC, Canada
W Krijgsman University of Utrecht, Utrecht, The Netherlands
R N Gibson Scottish Association for Marine Science, Argyll, Scotland
J B Kristoffersen University of Bergen, Bergen, Norway
M Gochfeld Environmental and Community Medicine, Piscataway, NJ, USA
K Lambeck Australian National University, Canberra, ACT, Australia
H O Halvorson University of Massachusetts Boston, Boston, MA, USA
R S Lampitt University of Southampton, Southampton, UK
B U Haq Vendome Court, Bethesda, MD, USA
M Landry University of Hawaii at Manoa, Department of Oceanography, Honolulu, HI, USA
G R Harbison Woods Hole Oceanographic Institution, Woods Hole, MA, USA
C G Langereis University of Utrecht, Utrecht, The Netherlands A Lascaratos University of Athens, Athens, Greece
R M Haymon University of California, CA, USA
S Leibovich Cornell University, Ithaca, NY, USA
D L Hebert University of Rhode Island, RI, USA J E Heyning The Natural History Museum of Los Angeles County, Los Angeles, CA, USA P Hoagland Woods Hole Oceanographic Institution, Woods Hole, MA, USA
W G Leslie Harvard University, Cambridge, MA, USA C Llewellyn Plymouth Marine Laboratory, Plymouth, UK R A Lutz Rutgers University, New Brunswick, NJ, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
xx
Contributors
K C Macdonald Department of Geological Sciences and Marine Sciences Institute, University of California, Santa Barbara, CA, USA F T Mackenzie University of Hawaii, Honolulu, HI, USA L P Madin Woods Hole Oceanographic Institution, Woods Hole, MA, USA M Maslin University College London, London, UK G A Maul Florida Institute of Technology, Melbourne, FL, USA M McNutt MBARI, Moss Landing, CA, USA M G McPhee McPhee Research Company, Naches, WA, USA A D Mclntyre University of Aberdeen, Aberdeen, UK J Mienert University of Tromsø, Tromsø, Norway G E Millward University of Plymouth, Plymouth, UK H Momma Japan Marine Science & Technology Center, Japan J H Morison University of Washington, Seattle, WA, USA A E Mulligan Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J E Petersen Oberlin College, Oberlin, OH, USA M Phillips Network of Aquaculture Centres in Asia-Pacific (NACA), Bangkok, Thailand B Qiu University of Hawaii at Manoa, Hawaii, USA F Quezada Biotechnology Center of Excellence Corporation, Waltham, MA, USA N N Rabalais Louisiana Universities Marine Consortium, Chauvin, LA, USA R D Ray NASA Goddard Space Flight Center, Greenbelt, MD, USA M R Reeve National Science Foundation, Arlington VA, USA R R Reeves Okapi Wildlife Associates, QC, Canada A Reyes-Prieto University of Iowa, Iowa City, IA, USA P B Rhines University of Washington,Seattle, WA, USA A R Robinson Harvard University, Cambridge, MA, USA H T Rossby University of Rhode Island, Kingston, RI, USA H M Rozwadowski Georgia Institute of Technology, Atlanta, Georgia, USA
W Munk University of California San Diego, La Jolla, CA, USA
A G V Salvanes University of Bergen, Bergen, Norway
E J Murphy British Antarctic Survey, Marine Life Sciences Division, Cambridge, UK
R Schlitzer Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany
P D Naidu National Institute of Oceanography, Dona Paula, India
M E Schumacher Woods Hole Oceanographic Institution, Woods Hole, MA, USA
N Niitsuma Shizuoka University, Shizuoka, Japan
M I Scranton State University of New York, Stony Brook, NY, USA
D B Olson University of Miami, Miami, FL, USA G-A Paffenho¨fer Skidaway Institute of Oceanography, Savannah, GA, USA C Paris University of Miami, Miami, FL, USA M R Perfit Department of Geological Sciences, University of Florida, Gainsville, FL, USA
K Sherman Narragansett Laboratory, Narragansett, RI, USA M D Spalding UNEP World Conservation Monitoring Centre and Cambridge Coastal Research Unit, Cambridge, UK J Sprintall University of California San Diego, La Jolla, CA, USA J H Steele Woods Hole Oceanographic Institution, MA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors C A Stein University of Illinois at Chicago, Chicago, IL, USA
S M Van Parijs Norwegian Polar Institute, Tromsø, Norway
C Stickley University College London, London, UK
L M Ver University of Hawaii, Honolulu, HI, USA
U R Sumaila University of British Columbia, Vancouver, BC, Canada
F J Vine University of East Anglia, Norwich, UK
S Takagawa Japan Marine Science & Technology Center, Japan
K L Von Damm University of New Hampshire, Durham, NH, USA
P K Taylor Southampton Oceanography Centre, Southampton, UK
R P Von Herzen Woods Hole Oceanographic Institution, Woods Hole, MA, USA
A Theocharis National Centre for Marine Research (NCMR), Hellinikon, Athens, Greece
xxi
D Wartzok Florida International University, Miami, FL, USA
P C Ticco Massachusetts Maritime Academy, Buzzards Bay, MA, USA R P Trask Woods Hole Oceanographic Institution, Woods Hole, MA, USA
W F Weeks Portland, OR, USA R A Weller Woods Hole Oceanographic Institution, Woods Hole, MA, USA
A W Trites University of British Columbia, British Columbia, Canada
J A Whitehead Woods Hole Oceanographic Institution, Woods Hole, MA, USA
A Turner University of Plymouth, Plymouth, UK
J C Wiltshire University of Hawaii, Manoa, Honolulu, HA, USA
P L Tyack Woods Hole Oceanographic Institution, Woods Hole, MA, USA
C Woodroffe University of Wollongong, Wollongong, NSW, Australia
G J C Underwood University of Essex, Colchester, UK
C Wunsch Massachusetts Institute of Technology, Cambridge, MA, USA
C L Van Dover The College of William and Mary, Williamsburg, VA, USA
H S Yoon University of Iowa, Iowa City, IA, USA
Volume 4 A Alldredge University of California, Santa Barbara, CA, USA D M Anderson Woods Hole Oceanographic Institution, Woods Hole, MA, USA O R Anderson Columbia University, Palisades, NY, USA
J M Bewers Bedford Institute of Oceanography, Dartmouth, NS, Canada N V Blough University of Maryland, College Park, MD, USA W Bonne
P G Baines CSIRO Atmospheric Research, Aspendale, VIC, Australia
Federal Public Service Health, Food Chain Safety and Environment, Brussels, Belgium
J M Baker Clock Cottage, Shrewsbury, UK
University of Cape Town, Cape Town, Republic of South Africa
J G Bellingham Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA
R D Brodeur
G M Branch
Northwest Fisheries Science Center, Newport, OR, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
xxii
Contributors
H Burchard Baltic Sea Research Institute Warnemu¨nde, Warnemu¨nde, Germany P H Burkill Plymouth Marine Laboratory, West Hoe, Plymouth, UK Francois Carlotti C.N.R.S./Universite´ Bordeaux 1, Arachon, France K L Casciotti Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J S Grayw University of Oslo, Oslo, Norway A G Grottoli University of Pennsylvania, Philadelphia, PA, USA N Gruber Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, Switzerland K C Hamer University of Durham, Durham, UK D Hammond University of Southern California, Los Angeles, CA, USA
A Clarke British Antarctic Survey, Cambridge, UK
W W Hay Christian-Albrechts University, Kiel, Germany
M B Collins National Oceanography Centre, Southampton, UK
J W Heath Coastal Fisheries Institute, CCEER Louisiana State University, Baton Rouge, LA, USA
J J Cullen Department of Oceanography, Halifax, NS, Canada D H Cushing Lowestoft, Suffolk, UK
D Hedgecock University of Southern California, Los Angeles, CA, USA C Hemleben Tu¨bingen University, Tu¨bingen, Germany
K L Denman University of Victoria, Victoria, BC, Canada S C Doney Woods Hole Oceanographic Institution, Woods Hole, MA, USA
T D Herbert Brown University, Providence, RI, USA I Hewson University of California Santa Cruz, Santa Cruz, CA, USA
J F Dower University of British Columbia, Vancouver, BC, Canada
Richard Hey University of Hawaii at Manoa, Honolulu, HI, USA
K Dysthe University of Bergen, Bergen, Norway
P Hoagland Woods Hole Oceanographic Institution, Woods Hole, MA, USA
H N Edmonds University of Texas at Austin, Port Aransas, TX, USA
N Hoepffner Institute for Environment and Sustainability, Ispra, Italy
L Føyn Institute of Marine Research, Bergen, Norway
M Hood Intergovernmental Oceanographic Commission, Paris, France
J Fuhrman University of Southern California, Los Angeles, CA, USA
M J Howarth Proudman Oceanographic Laboratory, Wirral, UK
C P Gallienne Plymouth Marine Laboratory, West Hoe, Plymouth, UK
M Huber Purdue University, West Lafayette, IN, USA
E Garel CIACOMAR, Algarve University, Faro, Portugal
J W Hurrell National Center for Atmospheric Research, Boulder, CO, USA
D M Glover Woods Hole Oceanographic Institution, Woods Hole, MA, USA S L Goodbred Jr State University of New York, Stony Brook, NY, USA J D M Gordon Scottish Association for Marine Science, Oban, Argyll, UK
D R Jackett CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia R A Jahnke Skidaway Institute of Oceanography, Savannah, GA, USA w
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors
xxiii
A Jarre University of Cape Town, Cape Town, South Africa
A F Michaels University of Southern California, Los Angeles, CA, USA
J Joseph La Jolla, CA, USA
J D Milliman College of William and Mary, Gloucester, VA, USA
D M Karl University of Hawaii at Manoa, Honolulu, HI, USA
C D Mobley Sequoia Scientific, Inc., WA, USA
K L Karsh Princeton University, Princeton, NJ, USA
M M Mullinw Scripps Institution of Oceanography, La Jolla, CA, USA
J Karstensen Universita¨t Kiel (IFM-GEOMAR), Kiel, Germany
P Mu¨ller University of Hawaii, Honolulu, HI, USA
R M Key Princeton University, Princeton, NJ, USA
L A Murray The Centre for Environment, Fisheries and Aquaculture Sciences, Lowestoft, UK
P D Killworth Southampton Oceanography Centre, Southampton, UK B Klinger Center for Ocean-Land-Atmosphere Studies (COLA), Calverton, MD, USA H E Krogstad NTNU, Trondheim, Norway I Laing Centre for Environment Fisheries and Aquaculture Science, Weymouth, UK
T Nagai Tokyo University of Marine Science and Technology, Tokyo, Japan K H Nisancioglu Bjerknes Centre for Climate Research, University of Bergen, Bergen, Norway Y Nozakiw University of Tokyo, Tokyo, Japan
G F Lane-Serff University of Manchester, Manchester, UK
K J Orians The University of British Columbia, Vancouver, BC, Canada
A Longhurst Place de I’Eglise, Cajarc, France
C A Paulson Oregon State University, Corvallis, OR, USA
R Lukas University of Hawaii at Manoa, Hawaii, USA
W G Pearcy Oregon State University, Corvallis, OR, USA
M Lynch University of California Santa Barbara, Santa Barbara, CA, USA
W S Pegau Oregon State University, Corvallis, OR, USA
M Macleod World Wildlife Fund, Washington, DC, USA E Maran˜o´n University of Vigo, Vigo, Spain S Martin University of Washington, Seattle, WA, USA S M Masutani University of Hawaii at Manoa, Honolulu, HI, USA I N McCave University of Cambridge, Cambridge, UK T J McDougall CSIRO Marine and Atmospheric Research, Hobart, TAS, Australia C L Merrin The University of British Columbia, Vancouver, BC, Canada
T Platt Dalhousie University, NS, Canada J J Polovina National Marine Fisheries Service, Honolulu, HI, USA D Quadfasel Niels Bohr Institute, Copenhagen, Denmark J A Raven Biological Sciences, University of Dundee, Dundee, UK G E Ravizza Woods Hole Oceanographic Institution, Woods Hole, MA, USA A J Richardson University of Queensland, St. Lucia, QLD, Australia M Rubega University of Connecticut, Storrs, CT, USA w
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
xxiv
Contributors
K C Ruttenberg Woods Hole Oceanographic Institution, Woods Hole, MA, USA
K K Turekian Yale University, New Haven, CT, USA T Tyrrell University of Southampton, Southampton, UK
A G V Salvanes University of Bergen, Bergen, Norway
O Ulloa Universidad de Concepcio´n, Concepcio´n, Chile
S Sathyendranath Dalhousie University, NS, Canada
C M G Vivian The Centre for Environment, Fisheries and Aquaculture Sciences, Lowestoft, UK
R Schiebel Tu¨bingen University, Tu¨bingen, Germany F B Schwing NOAA Fisheries Service, Pacific Grove, CA, USA
J J Walsh University of South Florida, St. Petersburg, FL, USA
M P Seki National Marine Fisheries Service, Honolulu, HI, USA
R M Warwick Plymouth Marine Laboratory, Plymouth, UK
L J Shannon Marine and Coastal Management, Cape Town, South Africa
N C Wells Southampton Oceanography Centre, Southampton, UK
K Shepherd Institute of Ocean Sciences, Sidney, BC, Canada
J A Whitehead Woods Hole Oceanographic Institution, Woods Hole, MA, USA
D Siegel-Causey Harvard University, Cambridge MA, USA D M Sigman Princeton University, Princeton, NJ, USA A Soloviev Nova Southeastern University, FL, USA J H Steele Woods Hole Oceanographic Institution, MA, USA P K Takahashi University of Hawaii at Manoa, Honolulu, HI, USA L D Talley Scripps Institution of Oceanography, La Jolla, CA, USA E Thomas Yale University, New Haven, CT, USA J R Toggweiler NOAA, Princeton, NJ, USA
M Wilkinson Heriot-Watt University, Edinburgh, UK R G Williams University of Liverpool, Oceanography Laboratories, Liverpool, UK C A Wilson III Department of Oceanography and Coastal Sciences, and Coastal Fisheries Institute, CCEER Louisiana State University, Baton Rouge, LA, USA H Yamazaki Tokyo University of Marine Science and Technology, Tokyo, Japan B deYoung Memorial University, St. John’s, NL, Canada G Zibordi Institute for Environment and Sustainability, Ispra, Italy
Volume 5 D G Ainley H.T. Harvey Associates, San Jose CA, USA W Alpers University of Hamburg, Hamburg, Germany J R Apelw Global Ocean Associates, Silver Spring, MD, USA w
Deceased.
A B Baggeroer Massachusetts Institute of Technology, Cambridge, MA, USA L T Balance NOAA-NMFS, La Jolla, CA, USA R Batiza Ocean Sciences, National Science Foundation, VA, USA W H Berger Scripps Institution of Oceanography, La Jolla, CA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors J L Bodkin US Geological Survey, AK, USA
I Everson British Antarctic Survey Cambridge, UK
I L Boyd Natural Environment Research Council, Cambridge, UK
I Fer University of Bergen, Bergen, Norway
A C Brown University of Cape Town, Cape Town, Republic of South Africa
M Fieux Universite´-Pierre et Marie Curie, Paris, France
xxv
J Burger Rutgers University, Piscataway, NJ, USA
R A Flather Proudman Oceanographic Laboratory, Bidston Hill, Prenton, UK
C J Camphuysen Netherlands Institute for Sea Research, Texel, The Netherlands
G S Giese Woods Hole Oceanographic Institution, Woods Hole, MA, USA
D C Chapman Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J M Gregory Hadley Centre, Berkshire, UK
R E Cheney Laboratory for Satellite Altimetry, Silver Spring, Maryland, USA T Chopin University of New Brunswick, Saint John, NB, Canada J A Church Antarctic CRC and CSIRO Marine Research, TAS, Australia J K Cochran State University of New York, Stony Brook, NY, USA P Collar Southampton Oceanography Centre, Southampton, UK R J Cuthbert University of Otago, Dunedin, New Zealand L S Davis University of Otago, Dunedin, New Zealand K L Denman University of Victoria, Victoria BC, Canada R P Dinsmore Woods Hole Oceanographic Institution, Woods Hole, MA, USA G J Divoky University of Alaska, Fairbanks, AK, USA
S M Griffies NOAA/GFDL, Princeton, NJ, USA G Griffiths Southampton Oceanography Centre, Southampton, UK A Harding University of California, San Diego, CA, USA W S Holbrook University of Wyoming, Laramie, WY, USA G L Hunt, Jr University of Washington, Seattle, WA, USA and University of California, Irvine, CA, USA P Hutchinson North Atlantic Salmon Conservation Organization, Edinburgh, UK K B Katsaros Atlantic Oceanographic and Meteorological Laboratory, NOAA, Miami, FL, USA H L Kite-Powell Woods Hole Oceanographic Institution, Woods Hole, MA, USA M A Kominz Western Michigan University, Kalamazoo, MI, USA
L M Dorman University of California, San Diego, La Jolla, CA, USA
R G Kope Northwest Fisheries Science Center, Seattle, WA, USA
J F Dower University of British Columbia, Vancouver, BC, Canada
G S E Lagerloef Earth and Space Research, Seattle, WA, USA
J B Edson Woods Hole Oceanographic Institution, Woods Hole, MA, USA
L M Lairdw Aberdeen University, Aberdeen, UK
T I Eglinton Woods Hole Oceanographic Institution, Woods Hole, MA, USA
M Leppa¨ranta University of Helsinki, Helsinki, Finland w
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
xxvi
Contributors
E J Lindstrom NASA Science Mission Directorate, Washington, DC, USA
C T Roman University of Rhode Island, Narragansett, RI, USA
A K Liu NASA Goddard Space Flight Center, Greenbelt, MD, USA
M Sawhney University of New Brunswick, Saint John, NB, Canada
C R McClain NASA Goddard Space Flight Center, Greenbelt, MD, USA
G Shanmugam The University of Texas at Arlington, Arlington, TX, USA
D J McGillicuddy Jr Woods Hole Oceanographic Institution, Woods Hole, MA, USA
J Sharples Proudman Oceanographic Laboratory, Liverpool, UK
W K Melville Scripps Institution of Oceanography, La Jolla CA, USA
J H Simpson Bangor University, Bangor, UK R K Smedbol Dalhousie University, Halifax, NS, Canada
D Mills Atlantic Salmon Trust, UK
L B Spear H.T. Harvey Associates, San Jose, CA, USA
P J Minnett University of Miami, Miami, FL, USA W A Montevecchi Memorial University of Newfoundland, NL, Canada W S Moore University of South Carolina, Columbia, SC, USA S J Morreale Cornell University, Ithaca, NY, USA K W Nicholls British Antarctic Survey, Cambridge, UK T J O’Shea Midcontinent Ecological Science Center, Fort Collins, CO, USA T E Osterkamp University of Alaska, Alaska, AK, USA F V Paladino Indiana-Purdue University at Fort Wayne, Fort Wayne, IN, USA C L Parkinson NASA Goddard Space Flight Center, Greenbelt, MD, USA A Pearson Woods Hole Oceanographic Institution, Woods Hole, MA, USA J T Potemra SOEST/IPRC, University of Hawaii, Honolulu, HI, USA J A Powell Florida Marine Research Institute, St Petersburg, FL, USA T Qu SOEST/IPRC, University of Hawaii, Honolulu, HI, USA
R L Stephenson St. Andrews Biological Station, St. Andrews, NB, Canada J M Teal Woods Hole Oceanographic Institution, Rochester, MA, USA K K Turekian Yale University, New Haven, CT, USA P Wadhams University of Cambridge, Cambridge, UK W F Weeks Portland, OR, USA G Wefer Universita¨t Bremen, Bremen, Germany W S Wilson NOAA/NESDIS, Silver Spring, MD, USA M Windsor, North Atlantic Salmon Conservation Organization, Edinburgh, UK S Y Wu NASA Goddard Space Flight Center, Greenbelt, MD, USA L Yu Woods Hole Oceanographic Institution, Woods Hole, MA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contributors
xxvii
Volume 6 A V Babanin Swinburne University of Technology, Melbourne, VIC, Australia
S E Humphris Woods Hole Oceanographic Institution, Woods Hole, MA, USA
R T Barber Duke University Marine Laboratory, Beaufort, NC, USA
W J Jenkins University of Southampton, Southampton, UK
J Bartram World Health Organization, Geneva, Switzerland
D R B Kraemer The Johns Hopkins University, Baltimore, MD, USA
A Beckmann Alfred-Wegener-Institut fu¨r Polar- und Meeresforschung, Bremerhaven, Germany M C Benfield Louisiana State University, Baton Rouge, LA, USA P S Bogden Maine State Planning Office, Augusta, ME, USA J A T Bye The University of Melbourne, Melbourne, VIC, Australia M F Cronin NOAA Pacific Marine Environmental Laboratory, Seattle, WA, USA A R J David Bere Alston, Devon, UK W Deuser Woods Hole Oceanographic Institution, Woods Hole, MA, USA J Donat Old Dominion University, Norfolk, VA, USA C Dryden Old Dominion University, Norfolk, VA, USA A Dufour United States Environmental Protection Agency, OH, USA C A Edwards University of Connecticut, Groton, CT, USA W J Emery University of Colorado, Boulder, CO, USA E Fahrbach Alfred-Wegener-Institut fu¨r Polar- und Meeresforschung, Bremerhaven, Germany
S Krishnaswami Physical Research Laboratory, Ahmedabad, India E L Kunze University of Washington, Seattle, WA, USA T E L Langford University of Southampton, Southampton, UK J R Ledwell Woods Hole Oceanographic Institution, Woods Hole, MA, USA P L-F Liu Cornell University, Ithaca, NY, USA M M R van der Loeff Alfred-Wegener-Institut fu¨r Polar und Meereforschung Bremerhaven, Germany R Lueck University of Victoria, Victoria, BC, Canada J E Lupton Hatfield Marine Science Center, Newport, OR, USA L P Madin Woods Hole Oceanographic Institution, Woods Hole, MA, USA M E McCormick The Johns Hopkins University, Baltimore, MD, USA M G McPhee McPhee Research Company, Naches, WA, USA J H Middleton The University of New South Wales, Sydney, NSW, Australia P J Minnett University of Miami, Miami, FL, USA E C Monahan University of Connecticut at Avery Point, Groton, CT, USA
A M Gorlov Northeastern University, Boston, Massachusetts, USA
C Moore WET Labs Inc., Philomath, OR, USA
I Helmond CSIRO Marine Research, TAS, Australia
J H Morison University of Washington, Seattle, WA, USA
R A Holman Oregon State University, Corvallis, OR, USA
J N Moum Oregon State University, Corvallis, OR, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
xxviii
Contributors
N S Oakey Bedford Institute of Oceanography, Dartmouth, NS, Canada D T Pugh University of Southampton, Southampton, UK D L Rudnick University of California, San Diego, CA, USA H Salas CEPIS/HEP/Pan American Health Organization, Lima, Peru L K Shay University of Miami, Miami, FL, USA W D Smyth Oregon State University, Corvallis, OR, USA J Sprintall University of California San Diego, La Jolla, CA, USA
L St. Laurrent University of Victoria, Victoria, BC, Canada W G Sunda National Ocean Service, NOAA, Beaufort, NC, USA M Tomczak Flinders University of South Australia, Adelaide, SA, Australia A J Watson University of East Anglia, Norwich, UK P H Wiebe Woods Hole Oceanographic Institution, Woods Hole, MA, USA P F Worcester University of California at San Diego, La Jolla, CA, USA
(c) 2011 Elsevier Inc. All Rights Reserved.
Contents Volume 1 Abrupt Climate Change
S Rahmstorf
1
Absorbance Spectroscopy for Chemical Sensors Abyssal Currents
R Narayanaswamy, F Sevilla, III
W Zenk
Accretionary Prisms
15
J C Moore
31
Acoustic Measurement of Near-Bed Sediment Transport Processes Acoustic Noise
Acoustic Scintillation Thermography Acoustics In Marine Sediments
K G Foote
62
P A Rona, C D Jones
71
T Akal
75
P N Mikhalevsky
Acoustics, Deep Ocean
92
W A Kuperman
101
F B Jensen
112
Acoustics, Shallow Water R Chester
Agulhas Current
120
J R E Lutjeharms
Aircraft Remote Sensing
128
L W Harding Jr, W D Miller, R N Swift, C W Wright
Air–Sea Gas Exchange
38 52
Acoustic Scattering by Marine Organisms
Aeolian Inputs
P D Thorne, P S Bell
I Dyer
Acoustics, Arctic
7
B Ja¨hne
138 147
Air–Sea Transfer: Dimethyl Sulfide, COS, CS2, NH4, Non-Methane Hydrocarbons, Organo-Halogens J W Dacey, H J Zemmelink
157
Air–Sea Transfer: N2O, NO, CH4, CO
163
Alcidae
C S Law
T Gaston
171
Antarctic Circumpolar Current Antarctic Fishes
S R Rintoul
I Everson
191
Anthropogenic Trace Elements in the Ocean Antifouling Materials
E A Boyle
211
W Seaman, W J Lindberg
234
R A Duce
Atmospheric Transport and Deposition of Particulate Material to the Oceans R Arimoto Authigenic Deposits
226
S G Philander
Atmospheric Input of Pollutants
Baleen Whales
203
B Rudels
Atlantic Ocean Equatorial Currents
Bacterioplankton
195
D J Howell, S M Evans
Arctic Ocean Circulation Artificial Reefs
178
G M McMurtry H W Ducklow
J L Bannister
238 J M Prospero, 248 258 269 276
(c) 2011 Elsevier Inc. All Rights Reserved.
xxix
xxx
Contents
Baltic Sea Circulation Bathymetry
W Krauss
288
D Monahan
297
Beaches, Physical Processes Affecting Benguela Current
Benthic Foraminifera
316 D J Wildish
328
A J Gooday
Benthic Organisms Overview
336
P F Kingston
348
P L Tyack
357
Biogeochemical Data Assimilation
E E Hofmann, M A M Friedrichs
Biological Pump and Particle Fluxes Bioluminescence
Bioturbation
S Honjo
376
A Morel
385
D H Shull
Black Sea Circulation
395
G I Shapiro
Bottom Water Formation
401
A L Gordon
415
Brazil and Falklands (Malvinas) Currents
A R Piola, R P Matano
Breaking Waves and Near-Surface Turbulence
J Gemmrich
D K Woolf
Calcium Carbonates
L C Peterson
E D Barton
Carbon Dioxide (CO2) Cycle
467
T Takahashi
Cenozoic Climate – Oxygen Isotope Evidence Cenozoic Oceans – Carbon Cycle Models
J D Wright L Franc¸ois, Y Godde´ris
R A Fine W R Martin
J W Farrington
Coastal Zone Management
514
539 551 563
F E Werner, B O Blanton
Coastal Topography, Human Impact on Coastal Trapped Waves
502
531
H Chamley
Coastal Circulation Models
495
524
Chemical Processes in Estuarine Sediments
Coccolithophores
E E Adams, K Caldeira
P Boyle
Chlorinated Hydrocarbons
477 487
Carbon Sequestration via Direct Injection into the Ocean
Clay Mineralogy
455
C A Carlson, N R Bates, D A Hansell, D K Steinberg
CFCs in the Ocean
431
445
B M Hickey, T C Royer
Canary and Portugal Currents
Cephalopods
422
439
California and Alaska Currents
Carbon Cycle
364 371
P J Herring, E A Widder
Bio-Optical Models
Bubbles
305
L V Shannon
Benthic Boundary Layer Effects
Bioacoustics
A D Short
D M Bush, O H Pilkey, W J Neal
J M Huthnance D R Godschalk
T Tyrrell, J R Young
(c) 2011 Elsevier Inc. All Rights Reserved.
572 581 591 599 606
Contents
Cold-Water Coral Reefs Conservative Elements
J M Roberts
615
D W Dyrssen
626
Continuous Plankton Recorders Copepods
A John, P C Reid
R Harris
Coral Reefs
630 640
Coral Reef and Other Tropical Fisheries Coral Reef Fishes
xxxi
V Christensen, D Pauly
M A Hixon
655
J W McManus
660
Corals and Human Disturbance Cosmogenic Isotopes
N J Pilcher
671
D Lal
678
Coupled Sea Ice–Ocean Models Crustacean Fisheries
651
A Beckmann, G Birnbaum
688
J W Penn, N Caputi, R Melville-Smith
699
CTD (Conductivity, Temperature, Depth) Profiler Current Systems in the Atlantic Ocean Current Systems in the Indian Ocean
A J Williams, III
L Stramma M Fieux, G Reverdin
Current Systems in the Southern Ocean
A L Gordon
Current Systems in the Mediterranean Sea
P Malanotte-Rizzoli
708 718 728 735 744
Volume 2 Data Assimilation in Models Deep Convection
A R Robinson, P F J Lermusiaux
J R N Lazier
Deep Submergence, Science of
13 D J Fornari
22
K Moran
37
Deep-Sea Drilling Methodology Deep-Sea Drilling Results
1
J G Baldauf
45
Deep-Sea Fauna
P V R Snelgrove, J F Grassle
55
Deep-Sea Fishes
J D M Gordon
67
Deep-Sea Ridges, Microbiology
A-L Reysenbach
73
Deep-Sea Sediment Drifts
D A V Stow
80
Demersal Species Fisheries
K Brander
90
Determination of Past Sea Surface Temperatures Differential Diffusion
A E Gargett
Dispersion from Hydrothermal Vents Diversity of Marine Species Dolphins and Porpoises
R W Schmitt, J R Ledwell
K R Helfrich
P V R Snelgrove R S Wells
Double-Diffusive Convection
98 114
Dispersion and Diffusion in the Deep Ocean
Drifters and Floats
M Kucera
R W Schmitt
P L Richardson
(c) 2011 Elsevier Inc. All Rights Reserved.
122 130 139 149 162 171
xxxii
Contents
Dynamics of Exploited Marine Fish Populations East Australian Current
M J Fogarty
G Cresswell
179 187
Economics of Sea Level Rise
R S J Tol
197
Ecosystem Effects of Fishing
S J Hall
201
Eels
J D McCleave
208
Effects of Climate Change on Marine Mammals Ekman Transport and Pumping
T K Chereskin, J F Price
El Nin˜o Southern Oscillation (ENSO)
Electrical Properties of Sea Water
Energetics of Ocean Mixing
228
S G Philander
R D Prien
Elemental Distribution: Overview
Y Nozaki
255
A C Naveira Garabato
261
Eutrophication
271
J M Klymak, J D Nash
Estuarine Circulation
288
K Dyer
299
V N de Jonge, M Elliott
Evaporation and Humidity
Fiord Circulation
306
K Katsaros
Exotic Species, Introduction of Expendable Sensors
241 247
w
A V Fedorov, J N Brown
Estimates of Mixing
218 222
K E Trenberth
El Nin˜o Southern Oscillation (ENSO) Models
Equatorial Waves
I Boyd, N Hanson
324
D Minchin
332
J Scott
345
A Stigebrandt
353
Fiordic Ecosystems
K S Tande
359
Fish Ecophysiology
J Davenport
367
Fish Feeding and Foraging Fish Larvae
P J B Hart
E D Houde
Fish Locomotion
381
J J Videler
Fish Migration, Horizontal Fish Migration, Vertical
Fish Reproduction
Fish Vision
392
G P Arnold
402
J D Neilson, R I Perry
Fish Predation and Mortality
Fish Schooling
374
411
K M Bailey, J T Duffy-Anderson
J H S Blaxter
425
T J Pitcher
432
R H Douglas
445
Fish: Demersal Fish (Life Histories, Behavior, Adaptations) Fish: General Review
O A Bergstad
Q Bone
458 467
Fish: Hearing, Lateral Lines (Mechanisms, Role in Behavior, Adaptations to Life Underwater) A N Popper, D M Higgs w
417
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
476
Contents
Fisheries and Climate
K M Brander
Fisheries Economics
483
U R Sumaila, G R Munro
Fisheries Overview
491
M J Fogarty, J S Collie
Fisheries: Multispecies Dynamics Fishery Management
499
J S Collie
505
T P Smith, M P Sissenwine
Fishery Management, Human Dimension
513
D C Wilson, B J McCay
Fishery Manipulation through Stock Enhancement or Restoration Fishing Methods and Fishing Fleets Floc Layers
xxxiii
M D J Sayer
R Fonteyne
522 528 535
R S Lampitt
548
Florida Current, Gulf Stream, and Labrador Current Flow through Deep Ocean Passages Flows in Straits and Channels
P L Richardson
N G Hogg
554 564
D M Farmer
572
Fluid Dynamics, Introduction, and Laboratory Experiments
S A Thorpe
578
Fluorometry for Biological Sensing
D J Suggett, C M Moore
581
Fluorometry for Chemical Sensing
S Draxler, M E Lippitsch
589
Food Webs
A Belgrano, J A Dunne, J Bascompte
Forward Problem in Numerical Models Fossil Turbulence
596
M A Spall
604
C H Gibson
612
Volume 3 Gas Exchange in Estuaries
M I Scranton, M A de Angelis
Gelatinous Zooplankton
L P Madin, G R Harbison
General Circulation Models
Geomorphology
20
C G Langereis, W Krijgsman
C Woodroffe
Geophysical Heat Flow
C A Stein, R P Von Herzen
40 K Lambeck
C C Eriksen A D Mclntyre
Grabs for Shelf Benthic Sampling
67
P F Kingston
70
M McNutt
80
Groundwater Flow to the Coastal Ocean Habitat Modification
49 59
Global Marine Pollution
Gravity
25 33
Glacial Crustal Rebound, Sea Levels, and Shorelines Gliders
9
G R Ierley
Geomagnetic Polarity Timescale
1
A E Mulligan, M A Charette
M J Kaiser
Heat and Momentum Fluxes at the Sea Surface Heat Transport and Climate History of Ocean Sciences
88 99
P K Taylor
H L Bryden H M Rozwadowski
(c) 2011 Elsevier Inc. All Rights Reserved.
105 114 121
xxxiv
Contents
Holocene Climate Variability Hydrothermal Vent Biota
M Maslin, C Stickley, V Ettwein R A Lutz
125 133
Hydrothermal Vent Deposits
R M Haymon
144
Hydrothermal Vent Ecology
C L Van Dover
151
Hydrothermal Vent Fauna, Physiology of
A J Arp
159
Hydrothermal Vent Fluids, Chemistry of
K L Von Damm
164
Hypoxia
N N Rabalais
172
Icebergs
D Diemand
181
Ice-Induced Gouging of the Seafloor Ice–Ocean Interaction
W F Weeks
J H Morison, M G McPhee
191 198
Ice Shelf Stability
C S M Doake
209
Igneous Provinces
M F Coffins, O Eldholm
218
Indian Ocean Equatorial Currents Indonesian Throughflow
M Fieux
J Sprintall
237
Inherent Optical Properties and Irradiance Internal Tidal Mixing Internal Tides
T D Dickey
W Munk
258
C Garrett
266
International Organizations Intertidal Fishes
M R Reeve
274
R N Gibson
Intra-Americas Sea
244 254
R D Ray
Internal Waves
Intrusions
226
280
G A Maul
286
D L Hebert
295
Inverse Modeling of Tracers and Nutrients
R Schlitzer
300
Inverse Models
C Wunsch
312
IR Radiometers
C J Donlon
319
K H Coale
331
Iron Fertilization Island Wakes Krill
E D Barton
343
E J Murphy
349
Kuroshio and Oyashio Currents
B Qiu
Laboratory Studies of Turbulent Mixing Lagoons
358 J A Whitehead
R S K Barnes
Lagrangian Biological Models Land–Sea Global Transfers
377 D B Olson, C Paris, R Cowen F T Mackenzie, L M Ver
Langmuir Circulation and Instability Large Marine Ecosystems
S Leibovich
K Sherman
Laridae, Sternidae, and Rynchopidae Law of the Sea
371
389 394 404 413
J Burger, M Gochfeld
P Hoagland, J Jacoby, M E Schumacher (c) 2011 Elsevier Inc. All Rights Reserved.
420 432
Contents
Leeuwin Current
G Cresswell, C M Domingues
Long-Term Tracer Changes Macrobenthos Magnetics
444
F von Blanckenburg
455
J D Gage
467
F J Vine
478
Manganese Nodules Mangroves
xxxv
D S Cronan
488
M D Spalding
496
Manned Submersibles, Deep Water
H Hotta, H Momma, S Takagawa
Manned Submersibles, Shallow Water
T Askew
505 513
Mariculture Diseases and Health
A E Ellis
519
Mariculture of Aquarium Fishes
N Forteath
524
Mariculture of Mediterranean Species Mariculture Overview
G Barnabe´, F Doumenge
M Phillips
537
Mariculture, Economic and Social Impacts Marine Algal Genomics and Evolution Marine Biotechnology
532
C R Engle
545
A Reyes-Prieto, H S Yoon, D Bhattacharya
H O Halvorson, F Quezada
552 560
Marine Chemical and Medicine Resources
S Ali, C Llewellyn
567
Marine Fishery Resources, Global State of
J Csirke, S M Garcia
576
Marine Mammal Diving Physiology
G L Kooyman
Marine Mammal Evolution and Taxonomy
J E Heyning
Marine Mammal Migrations and Movement Patterns Marine Mammal Overview
582
P J Corkeron, S M Van Parijs
P L Tyack
Marine Mammal Trophic Levels and Interactions Marine Mammals and Ocean Noise
A W Trites
Marine Policy Overview Marine Protected Areas Marine Silica Cycle
635 643
654 G-A Paffenho¨fer
656
P Hoagland, P C Ticco
664
P Hoagland, U R Sumaila, S Farrow D J DeMaster
R S Lampitt
Maritime Archaeology
622
651
J H Steele
Marine Plankton Communities
Mediterranean Sea Circulation
672 678 686
R D Ballard
Meddies and Sub-Surface Eddies
Meiobenthos
S K Hooker
A E S Kemp
Marine Mesocosms
615
628
R R Reeves
Marine Mammals: Sperm Whales and Beaked Whales
Marine Snow
P L Tyack
D Wartzok
Marine Mammals, History of Exploitation
596 605
Marine Mammal Social Organization and Communication
Marine Mats
589
H T Rossby A R Robinson, W G Leslie, A Theocharis, A Lascaratos
B C Coull, G T Chandler (c) 2011 Elsevier Inc. All Rights Reserved.
695 702 710 726
xxxvi
Contents
Mesocosms: Enclosed Experimental Ecosystems in Ocean Science Mesopelagic Fishes
J E Petersen, W M Kemp
A G V Salvanes, J B Kristoffersen
Mesoscale Eddies
748
P B Rhines
Metal Pollution
755
G E Millward, A Turner
Metalloids and Oxyanions
732
768
G A Cutter
776
Methane Hydrates and Climatic Effects
B U Haq
784
Methane Hydrate and Submarine Slides
J Mienert
790
Microbial Loops
M Landry
Microphytobenthos
799
G J C Underwood
807
Mid-Ocean Ridge Geochemistry and Petrology Mid-Ocean Ridge Seismic Structure Mid-Ocean Ridge Seismicity
M R Perfit
815
S M Carbotte
826
D R Bohnenstiehl, R P Dziak
Mid-Ocean Ridge Tectonics, Volcanism, and Geomorphology
837 K C Macdonald
Mid-Ocean Ridges: Mantle Convection and Formation of the Lithosphere Millennial-Scale Climate Variability
J T Andrews
Mineral Extraction, Authigenic Minerals Molluskan Fisheries Monsoons, History of Moorings
G Ito, R A Dunn
852 867 881
J C Wiltshire
890
V S Kennedy
899
N Niitsuma, P D Naidu
910
R P Trask, R A Weller
919
Volume 4 Nekton
W G Pearcy, R D Brodeur
Nepheloid Layers
1
I N McCave
Network Analysis of Food Webs
8 J H Steele
Neutral Surfaces and the Equation of State Nitrogen Cycle
19 T J McDougall, D R Jackett
D M Karl, A F Michaels
Nitrogen Isotopes in the Ocean Noble Gases and the Cryosphere Non-Rotating Gravity Currents North Atlantic Oscillation (NAO) North Sea Circulation
25 32
D M Sigman, K L Karsh, K L Casciotti
40
M Hood
55
P G Baines
59
J W Hurrell
65
M J Howarth
73
Nuclear Fuel Reprocessing and Related Discharges
H N Edmonds
82
Ocean Biogeochemistry and Ecology, Modeling of
N Gruber, S C Doney
89
Ocean Carbon System, Modeling of Ocean Circulation
S C Doney, D M Glover
N C Wells
105 115
Ocean Circulation: Meridional Overturning Circulation
J R Toggweiler
(c) 2011 Elsevier Inc. All Rights Reserved.
126
Contents
Ocean Gyre Ecosystems
M P Seki, J J Polovina
Ocean Margin Sediments Ocean Ranching
132
S L Goodbred Jr
138
A G V Salvanes
146
R G Williams
156
Ocean Subduction
Ocean Thermal Energy Conversion (OTEC) Ocean Zoning
S M Masutani, P K Takahashi
M Macleod, M Lynch, P Hoagland
Offshore Sand and Gravel Mining Oil Pollution
Okhotsk Sea Circulation
E Garel, W Bonne, M B Collins
200
H Yamazaki, H Burchard, K Denman, T Nagai
Open Ocean Convection
A Soloviev, B Klinger
Open Ocean Fisheries for Deep-Water Species
Optical Particle Characterization
P H Burkill, C P Gallienne
265 272 274
R Lukas
287
E Thomas
295 W W Hay
Paleoceanography: Orbitally Tuned Timescales Paleoceanography: the Greenhouse World Particle Aggregation Dynamics Past Climate from Corals
T D Herbert
M Huber, E Thomas
A Alldredge
A G Grottoli
K L Denman, J F Dower
Pelagic Biogeography
A Longhurst
D H Cushing
Pelecaniformes
Peru–Chile Current System
C A Paulson, W S Pegau
J Karstensen, O Ulloa
319 330 338 348 356
379 385 393
K C Ruttenberg
Photochemical Processes
311
370
M Rubega
Phosphorus Cycle
303
364
D Siegel-Causey
Penetrating Shortwave Radiation
252 261
I Laing
Paleoceanography, Climate Models in
Phytobenthos
R A Jahnke
K K Turekian
Pacific Ocean Equatorial Currents
Phalaropes
243
G F Lane-Serff
Oysters – Shellfish Farming
Pelagic Fishes
234
K K Turekian
Oxygen Isotopes in the Ocean
Paleoceanography
226
J Joseph
Organic Carbon Cycling in Continental Margin Environments
Overflows and Cascades
208 218
J D M Gordon
Open Ocean Fisheries for Large Pelagic Species
Origin of the Oceans
182 191
L D Talley
One-Dimensional Models
167 174
J M Baker
Patch Dynamics
xxxvii
N V Blough
M Wilkinson
401 414 425
(c) 2011 Elsevier Inc. All Rights Reserved.
xxxviii
Contents
Phytoplankton Blooms
D M Anderson
Phytoplankton Size Structure Plankton
M M Mullin
Plankton and Climate Plankton Viruses
432
E Maran˜o´n
445
w
453
A J Richardson
455
J Fuhrman, I Hewson
465
Platforms: Autonomous Underwater Vehicles Platforms: Benthic Flux Landers
J G Bellingham
R A Jahnke
485
Platinum Group Elements and their Isotopes in the Ocean
G E Ravizza
Plio-Pleistocene Glacial Cycles and Milankovitch Variability Polar Ecosystems
K H Nisancioglu
A Clarke
Pollution, Solids
494 504 514
C M G Vivian, L A Murray
Pollution: Approaches to Pollution Control Pollution: Effects on Marine Communities Polynyas
473
519
J S Grayw, J M Bewers R M Warwick
526 533
S Martin
540
Population Dynamics Models
Francois Carlotti
Population Genetics of Marine Organisms Pore Water Chemistry
546
D Hedgecock
556
D Hammond
Primary Production Distribution
563
S Sathyendranath, T Platt
572
Primary Production Methods
J J Cullen
578
Primary Production Processes
J A Raven
585
Procellariiformes
K C Hamer
590
Propagating Rifts and Microplates
Richard Hey
597
Protozoa, Planktonic Foraminifera
R Schiebel, C Hemleben
606
Protozoa, Radiolarians
O R Anderson
Radiative Transfer in the Ocean Radioactive Wastes Radiocarbon
C D Mobley
619
L Føyn
629
R M Key
637
Rare Earth Elements and their Isotopes in the Ocean Red Sea Circulation Redfield Ratio Refractory Metals
Y Nozaki
w
D Quadfasel
677
K J Orians, C L Merrin
Regime Shifts, Physical Forcing Regime Shifts: Methods of Analysis
653 666
T Tyrrell
Regime Shifts, Ecological Aspects
w
613
L J Shannon, A Jarre, F B Schwing F B Schwing B deYoung, A Jarre
Deceased.
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687 699 709 717
Contents
Regional and Shelf Sea Models
J J Walsh
Remote Sensing of Coastal Waters
Rigs and offshore Structures River Inputs
722
N Hoepffner, G Zibordi
Remotely Operated Vehicles (ROVs)
xxxix
732
K Shepherd
742
C A Wilson III, J W Heath
748
J D Milliman
754
Rocky Shores
G M Branch
762
Rogue Waves
K Dysthe, H E Krogstad, P Mu¨ller
770
Rossby Waves
P D Killworth
Rotating Gravity Currents
781
J A Whitehead
790
Volume 5 Salmon Fisheries, Atlantic
P Hutchinson, M Windsor
Salmon Fisheries, Pacific Salmonid Farming Salmonids
1
R G Kope
L M Laird
12
w
23
D Mills
29
Salt Marsh Vegetation
C T Roman
Salt Marshes and Mud Flats Sandy Beaches, Biology of Satellite Altimetry
39
J M Teal
43
A C Brown
49
R E Cheney
58
Satellite Oceanography, History, and Introductory Concepts J R Apel w
W S Wilson, E J Lindstrom, 65
Satellite Passive-Microwave Measurements of Sea Ice
C L Parkinson
80
Satellite Remote Sensing of Sea Surface Temperatures
P J Minnett
91
Satellite Remote Sensing SAR
A K Liu, S Y Wu
Satellite Remote Sensing: Ocean Color
C R McClain
Satellite Remote Sensing: Salinity Measurements Science of Ocean Climate Models Sea Ice
103
G S E Lagerloef
S M Griffies
P Wadhams
114 127 133 141
Sea Ice Dynamics
M Leppa¨ranta
159
Sea Ice: Overview
W F Weeks
170
Sea Level Change
J A Church, J M Gregory
179
Sea Level Variations Over Geologic Time Sea Otters
w
M A Kominz
J L Bodkin
185 194
Deceased.
(c) 2011 Elsevier Inc. All Rights Reserved.
xl
Contents
Sea Surface Exchanges of Momentum, Heat, and Fresh Water Determined by Satellite Remote Sensing L Yu
202
Sea Turtles
212
F V Paladino, S J Morreale
Seabird Conservation
J Burger
Seabird Foraging Ecology Seabird Migration
220
L T Balance, D G Ainley, G L Hunt Jr
L B Spear
227 236
Seabird Population Dynamics
G L Hunt Jr
247
Seabird Reproductive Ecology
L S Davis, R J Cuthbert
251
Seabird Responses to Climate Change Seabirds and Fisheries Interactions
David G Ainley, G J Divoky C J Camphuysen
Seabirds as Indicators of Ocean Pollution Seabirds: An Overview Seals
265
W A Montevecchi
274
G L Hunt, Jr
279
I L Boyd
285
Seamounts and Off-Ridge Volcanism Seas of Southeast Asia
R Batiza
292
J T Potemra, T Qu
Seaweeds and their Mariculture Sediment Chronologies
305
T Chopin, M Sawhney
317
J K Cochran
327
Sedimentary Record, Reconstruction of Productivity from the Seiches
Seismic Structure
I Fer, W S Holbrook
L M Dorman
367
K B Katsaros
375
Sensors for Micrometeorological and Flux Measurements Shelf Sea and Shelf Slope Fronts
J B Edson
J Sharples, J H Simpson
H L Kite-Powell
Single Point Current Meters
T I Eglinton, A Pearson
P Collar, G Griffiths
436
Slides, Slumps, Debris Flows, and Turbidity Currents Small Pelagic Species Fisheries Small-Scale Patchiness, Models of
419 428
T J O’Shea, J A Powell G Shanmugam
R L Stephenson, R K Smedbol D J McGillicuddy Jr
Small-Scale Physical Processes and Plankton Biology
J F Dower, K L Denman
M Fieux
447 468 474 488 494
A B Baggeroer
Southern Ocean Fisheries
391
409
Single Compound Radiocarbon Measurements
Sonar Systems
382
401
R P Dinsmore
Somali Current
351 361
Sensors for Mean Meteorology
Shipping and Ports
333 344
A Harding
Seismology Sensors
Sirenians
G Wefer, W H Berger
D C Chapman, G S Giese
Seismic Reflection Methods for Study of the Water Column
Ships
257
504
I Everson
(c) 2011 Elsevier Inc. All Rights Reserved.
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Contents
Sphenisciformes
L S Davis
520
Stable Carbon Isotope Variations in the Ocean Storm Surges
K K Turekian
529
R A Flather
530
Sub Ice-Shelf Circulation and Processes Submarine Groundwater Discharge Sub-Sea Permafrost Surface Films
xli
K W Nicholls
541
W S Moore
551
T E Osterkamp
559
W Alpers
570
Surface Gravity and Capillary Waves
W K Melville
573
Volume 6 Temporal Variability of Particle Flux Thermal Discharges and Pollution
W Deuser
1
T E L Langford
10
Three-Dimensional (3D) Turbulence Tidal Energy Tides
W D Smyth, J N Moum
A M Gorlov
26
D T Pugh
Tomography
32
P F Worcester
Topographic Eddies Towed Vehicles
40
J H Middleton
57
I Helmond
Trace Element Nutrients
65
W G Sunda
Tracer Release Experiments
75
A J Watson, J R Ledwell
Tracers of Ocean Productivity
Transmissometry and Nephelometry Tritium–Helium Dating
87
W J Jenkins
93
Transition Metals and Heavy Metal Speciation
Tsunami
18
J Donat, C Dryden
100
C Moore
109
W J Jenkins
119
P L-F Liu
127
Turbulence in the Benthic Boundary Layer Turbulence Sensors
R Lueck, L St. Laurrent, J N Moum
N S Oakey
Under-Ice Boundary Layer
148
M G McPhee, J H Morison
Upper Ocean Heat and Freshwater Budgets Upper Ocean Mean Horizontal Structure Upper Ocean Mixing Processes
155
P J Minnett
163
M Tomczak
175
J N Moum, W D Smyth
185
Upper Ocean Structure: Responses to Strong Atmospheric Forcing Events Upper Ocean Time and Space Variability Upper Ocean Vertical Structure Upwelling Ecosystems
141
L K Shay
192
D L Rudnick
211
J Sprintall, M F Cronin
217
R T Barber
Uranium-Thorium Decay Series in the Oceans: Overview
225 M M R van der Loeff
(c) 2011 Elsevier Inc. All Rights Reserved.
233
xlii
Contents
Uranium-Thorium Series Isotopes in Ocean Profiles Vehicles for Deep Sea Exploration
S E Humphris
Viral and Bacterial Contamination of Beaches Volcanic Helium
J Bartram, H Salas, A Dufour
285
Water Types and Water Masses
W J Emery
291
M E McCormick, D R B Kraemer
Waves on Beaches
267 277
E L Kunze
Wave Generation by Wind
244 255
J E Lupton
Vortical Modes
Wave Energy
S Krishnaswami
300
J A T Bye, A V Babanin
304
R A Holman
310
Weddell Sea Circulation
E Fahrbach, A Beckmann
318
Wet Chemical Analyzers
A R J David
326
Whitecaps and Foam
E C Monahan
Wind- and Buoyancy-Forced Upper Ocean Wind Driven Circulation
331 M F Cronin, J Sprintall
P S Bogden, C A Edwards
Zooplankton Sampling with Nets and Trawls
337 346
P H Wiebe, M C Benfield
355
Appendix 1. SI Units and Some Equivalences
373
Appendix 2. Useful Values
376
Appendix 3. Periodic Table of the Elements
377
Appendix 4. The Geologic Time Scale
378
Appendix 5. Properties of Seawater
379
Appendix 6. The Beaufort Wind Scale and Seastate
384
Appendix 7. Estimated Mean Oceanic Concentrations of the Elements
386
Appendix 8. Abbreviations
389
Appendix 9. Taxonomic Outline Of Marine Organisms
L P Madin
401
Appendix 10. Bathymetric Charts of the Oceans
412
Index
421
(c) 2011 Elsevier Inc. All Rights Reserved.
DATA ASSIMILATION IN MODELS A. R. Robinson and P. F. J. Lermusiaux, Harvard University, Cambridge, MA, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 623–634, & 2001, Elsevier Ltd.
Introduction Data assimilation is a novel, versatile methodology for estimating oceanic variables. The estimation of a quantity of interest via data assimilation involves the combination of observational data with the underlying dynamical principles governing the system under observation. The melding of data and dynamics is a powerful methodology which makes possible efficient, accurate, and realistic estimations otherwise not feasible. It is providing rapid advances in important aspects of both basic ocean science and applied marine technology and operations. The following sections introduce concepts, describe purposes, present applications to regional dynamics and forecasting, overview formalism and methods, and provide a selected range of examples.
Field and Parameter Estimation Ocean science, and marine technology and operations, require a knowledge of the distribution and evolution in space and time of the properties of the sea. The functions of space and time, or state variables, which characterize the state of the sea under observation are classically designated as fields. The determination of state variables poses problems of state estimation or field estimation in three or four dimensions. The fundamental problem of ocean science may be simply stated as follows: given the state of the ocean at one time, what is the state of the ocean at a later time? It is the dynamics, i.e., the basic laws and principles of oceanic physics, biology, and chemistry, that evolve the state variables forward in time. Thus, predicting the present and future state of oceanic variables for practical applications is intimately linked to fundamental ocean science. A dynamical model to approximate nature consists of a set of coupled nonlinear prognostic field equations for each state variable of interest. The fundamental properties of the system appear in the field equations as parameters (e.g., viscosities, diffusivities, representations of body forces, rates of earth rotation, grazing, mortality, etc.). The initial and boundary
conditions necessary for integration of the equations may also be regarded as parameters by data assimilation methods. In principle the parameters of the system can be estimated directly from measurements. In practice, directly measuring the parameters of the interdisciplinary (physical-acoustical-optical-biological-chemical-sedimentological) ocean system is difficult because of sampling, technical, and resource requirements. However, data assimilation provides a powerful methodology for parameter estimation via the melding of data and dynamics. The physical state variables are usually the velocity components, pressure, density, temperature, and salinity. Examples of biological and chemical state variables are concentration fields of nutrients, plankton, dissolved and particulate matter, etc. Important complexities are associated with the vast range of phenomena, the multitude of concurrent and interactive scales in space and time, and the very large number of possible biological state variables. This complexity has two essential consequences. First, state variable definitions relevant to phenomena and scales of interest need to be developed from the basic definitions. Second, approximate dynamics which govern the evolution of the scale-restricted state variables, and their interaction with other scales, must be developed from the basic dynamical model equations. A familiar example consists of decomposing the basic ocean fields into slower and faster time scales, and shorter and longer space scales, and averaging over the faster and shorter scales. The resulting equations can be adapted to govern synoptic/mesoscale resolution state variables over a large-scale oceanic domain, with faster and smaller scale phenomena represented as parameterized fluctuation correlations (Reynolds stresses). There is, of course, a great variety of other scalerestricted state variables and approximate dynamics of vital interest in ocean science. We refer to scalerestricted state variables and approximate dynamics simply as ‘state variables’ and ‘dynamics’. The use of dynamics is of fundamental importance for efficient and accurate field and parameter estimation. Today and in the foreseeable future, data acquisition in the ocean is sufficiently difficult and costly so as to make field and parameter estimates by direct measurements, on a substantial and sustained basis, essentially prohibitive. However, data acquisition for field and parameter estimates via data assimilation is feasible, but substantial resources must be applied to obtain adequate observations.
(c) 2011 Elsevier Inc. All Rights Reserved.
1
2
DATA ASSIMILATION IN MODELS
The general process of state and parameter estimation is schematized in Figure 1. Measurement models link the state variables of the dynamical model to the sensor data. Dynamics interpolates and extrapolates the data. Dynamical linkages among state variables and parameters allow all of them to be estimated from measurements of some of them, i.e., those more accessible to existing techniques and prevailing conditions. Error estimation and error models play a crucial role. The data and dynamics are melded with weights inversely related to their relative errors. The final estimates should agree with the observations and measurements within data error bounds and should satisfy the dynamical model
Adaptive sampling
Observational network Sampling scheme Sensor data and data errors
UPl
Model improvements
LS
USVj
DE
MPk
M
OSVi
ION SCH E
_ DYNA M
DELS _ A MO SS L A
T ILA IM
IC
Measurement models and error models
_ ERROR M O ES
State and parameter estimates and errors SV SV: P: O: M: U: E: :
SVE
P
PE
State Variable Parameter Observed Measured Unobserved or Unmeasured Error Dynamical linkages
Figure 1 Data assimilation system schematic. Arrows represent the most common direction for the flows of information. The arrows between the measurement models and dynamical models double because measurement models can include operators that map state variables and parameters to the sensor data (e.g. interpolations, derivatives or integrals of state variables/parameters) and operators that transform sensor data into data appropriate for the model scales and processes (e.g. filtering, extrapolations or integrals of sensor data). The legend at the bottom explains abbreviations.
within model error bounds. Thus the melded estimate does not degrade the reliable information of the observational data, but rather enhances that information content. There are many important feedbacks in the generally nonlinear data assimilation system or ocean observing and prediction system (OOPS) schematized in Figure 1, which illustrates the system concept and two feedbacks. Prediction provides the opportunity for efficient sampling adapted to real time structures, events, and errors. Data collected for assimilation also used for ongoing verification can identify model deficiencies and lead to model improvements. A data assimilation system consists of three components: a set of observations, a dynamical model, and a data assimilation scheme or melding scheme. Modern interdisciplinary OOPS generally have compatible nested grids for both models and sampling. An efficient mix of platforms and sensors is selected for specific purposes. Central to the concept of data assimilation is the concept of errors, error estimation, and error modeling. The observations have errors arising from various sources: e.g., instrumental noise, environmental noise, sampling, and the interpretation of sensor measurements. All oceanic dynamical models are imperfect, with errors arising from the approximate explicit and parameterized dynamics and the discretization of continuum dynamics into a computational model. A rigorous quantitative establishment of the accuracy of the melded field and parameter estimates, or verification, is highly desirable but may be difficult to achieve because of the quantity and quality of the data required. Such verification involves all subcomponents: the dynamical model, the observational network, the associated error models, and the melding scheme. The concept of validation is the establishment of the general adequacy of the system and its components to deal with the phenomena of interest. As simple examples, a barotropic model should not be used to describe baroclinic phenomena, and data from an instrument whose threshold is higher than the accuracy of the required measurement are not suitable. In reality, validation issues can be much more subtle. Calibration involves the tuning of system parameters to the phenomena and regional characteristics of interest. Final verification requires dedicated experiments with oversampling. At this point it is useful to classify types of estimates with respect to the time interval of the data input to the estimate for time t. If only past and present data are utilized, the estimation is a filtering process. After the entire time series of data is available for (0,T), the estimate for any time 0 r t r T is
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best based on the whole data set and the estimation is a smoothing process.
Goals and Purposes The specific uses of data assimilation depend upon the relative quality of data sets and models, and the desired purposes of the field and parameter estimates. These uses include the control of errors for state estimates, the estimation of parameters, the elucidation of real ocean dynamical processes, the design of experimental networks, and ocean monitoring and prediction. First consider ocean prediction for scientific and practical purposes, which is the analog of numerical weather prediction. In the best case scenario, the dynamical model correctly represents both the internal dynamical processes and the responses to external forcings. Also, the observational network provides initialization data of desired accuracy. The phenomenon of loss of predictability nonetheless inhibits accurate forecasts beyond the predictability limit for the region and system. This limit for the global atmosphere is 1–2 weeks and for the mid-ocean eddy field of the north-west Atlantic on the order of weeks to months. The phenomenon is associated with the nonlinear scale transfer and growth of initial errors. The early forecasts will accurately track the state of the real ocean, but longer forecasts, although representing plausible and realistic synoptical dynamical events, will not agree with contemporary nature. However, this predictability error can be controlled by the continual assimilation of data, and this is a major use of data assimilation today. Next, consider the case of a field estimate with adequate data but a somewhat deficient dynamical model. Assimilated data can compensate for the imperfect physics so as to provide estimates in agreement with nature. This is possible if dynamical model errors are treated adequately. For instance, if a barotropic model is considered perfect, and baroclinic real ocean data are assimilated, the field estimate will remain barotropic. Even though melded estimates with deficient models can be useful, it is of course important to attempt to correct the model dynamics. Parameter estimation via data assimilation is making an increasingly significant impact on ocean science via the determination of both internal and external parameter values. Regional field estimates can be substantially improved by boundary condition estimation. Biological modelers have been hampered by the inability to directly measure in situ rates, e.g., grazing and mortality. Thus, for interdisciplinary studies, internal parameter estimation is particularly promising. For example, measurements
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of concentration fields of plankton together with a realistic interdisciplinary model can be used for in situ rate estimation. Data-driven simulations can provide four-dimensional time series of dynamically adjusted fields which are realistic. These fields, regarded as (numerical) experimental data, can thus serve as high resolution and complete data sets for dynamical studies. Balance of terms in dynamical equations and overall budgets can be carried out to determine fluxes and rates for energy, vorticity, productivity, grazing, carbon flux, etc. Case studies can be carried out, and statistics and general processes can be inferred for simulations of sufficient duration. Of particular importance are observation system simulation experiments (OSSEs), which first entered meteorology almost 30 years ago. By subsampling the simulated ‘true’ ocean, future experimental networks and monitoring arrays can be designed to provide efficient field estimates of requisite accuracies. Data assimilation and OSSEs develop the concepts of data, theory, and their relationship beyond those of the classical scientific methodology. For a period of almost 300 years, scientific methodology was powerfully established on the basis of two essential elements: experiments/observations and theory/ models. Today, due to powerful computers, science is based on three fundamental concepts: experiment, theory, and simulation. Since our best field and parameter estimates today are based on data assimilation, our very perception and conceptions of nature and reality require philosophical development. It is apparent from the above discussion that marine operations and ocean management must depend on data assimilation methods. Data-driven simulations should be coupled to multipurpose management models for risk assessments and for the design of operational procedures. Regional multiscale ocean prediction and monitoring systems, designed by OSSEs, are being established to provide ongoing nowcasts and forecasts with predictability error controlled by updating. Both simple and sophisticated versions of such systems are possible and relevant.
Regional Forecasting and Dynamics In this section, the issues and concepts introduced in the preceding sections are illustrated in the context of real-time predictions carried out in 1996 for NATO naval operations in the Strait of Sicily and for interdisciplinary multiscale research in 1998 in Massachusetts Bay. The Harvard Ocean Prediction System (HOPS) with its primitive equation dynamical model was utilized in both cases. In the Strait of Sicily (Figure 2), the observational network with platforms
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Figure 2 Strait of Sicily. (A) Schematic of circulation features and dominant variabilities. (B) Forecast of the surface temperature for 25 August 1996, overlaid with surface velocity vectors (scale arrow is 0.25 m s1). (C) Objectively analyzed surface standard error deviation associated with the aircraft sampling on 18 September 1996 (normalized from 0 to 1). (D) Surface values of the first nondimensional temperature variability mode. (E) Satellite SST distributions for 25 August 1996. (F) Main LIW pathways, features, and mixing on deep potential density anomaly iso-surface (sY ¼ 29.05), over bottom topography (for more details, see Lermusiaux, 1999, and Lermusiaux and Robinson, 2001).
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consisting of satellites, ships, aircraft, and Lagrangian drifters, was managed by the NATO SACLANT Undersea Research Centre. In Massachusetts Bay (Figure 3), the observational network with platforms consisting of ships, satellites, and autonomous underwater vehicles, was provided by the Littoral Ocean Observing and Prediction System (LOOPS) project within the US National Ocean Partnership Program. The data assimilation methods used in both cases were the HOPS OI and ESSE schemes (see Estimation Theory below). In both cases the purposes of data assimilation were to provide a predictive capability, to control loss of predictability, and to infer basic underlying dynamical processes. The dominant regional variabilities determined from these exercises and studies are schematized in Figures 2A and 3A. The dominant near surface flow in the strait is the Atlantic Ionian Stream, AIS (black lines for the stream; smooth and meandering dashed lines for the common locations of fronts and wave patterns, respectively) and dominant variabilities include the location and shapes of the Adventure Bank Vortex (ABV), Maltese Channel Crest (MCC), Ionian Shelfbreak Vortex (ISV), and Messian Rise Vortex (MRV) with shifts and deformations 0(10–100 km) occurring in 0(3–5 days). The variability of the Massachusetts Bay circulation is more dramatic. The buoyancy flow-through current which enters the Bay in the north from the Gulf of Maine may have one, two or three branches, and together with associated vortices (which may or may not be present), can reverse directions within the bay. Storm events shift the pattern of the features which persist inertially between storms. Actual real-time forecast fields are depicted in Figures 2B and 3B. The existence of forecasts allows adaptive sampling, i.e., sampling efficiently related to existing structures and events. Adaptive sampling can be determined subjectively by experience or objectively by a quantitative metric. The sampling pattern associated with the temperature objective analysis error map (Figure 2C) reflects the flight pattern of an aircraft dropping subsurface temperature probes (AXBTs). The data were assimilated into a forecast in support of naval operations centered near the ISV (Figure 2A). The sampling extends to the surrounding meanders of the AIS, which will affect the current’s thermal front in the operational region. The multiscale sampling of the Massachusetts Bay experiment is exemplified in Figure 3C by ship tracks adapted to the interactive submesoscales, mesoscales, bay-scales, and large-scales. Note that the tracks of Figure 3D are superimposed on a forecast of the total temperature forecast error standard deviation. The shorter track is objectively located around an error
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maximum. The longer track is for reduction of velocity error (not shown). Eigendecomposition of variability fields helps dynamical interpretations. This eigen-decomposition estimates and orders the directions of largest variability variance (eigenmodes) and the corresponding amplitudes (eigenvalues). The first temperature variability eigenmodes for the strait and the bay are depicted in Figures 2D and 3E respectively. The former is associated with the dominant ABV variability and the latter with the location, direction, and strength of the inflow to the bay of the buoyancy current from the Gulf of Maine. A qualitative skill score for the prediction of dominant variations of the ABV, MCC, and ISV indicated correct 2- to 3-day predictions of surface temperature 75% of the time. The scores were obtained by validation against new data for assimilation and independent satellite sea surface temperature data as shown in Figure 2E for the forecast of Figure 2B. An important kinematical and dynamical interconnection between the eastern and western Mediterranean is the deep flow of salty Levantine Intermediate Water (LIW), which was not directly measured but was inferred from data assimilative simulations (Figure 2F). The scientific focus of the Massachusetts Bay experiment was plankton patchiness, in particular the spatial variability of zooplankton and its relationship to physical and phytoplankton variabilities (Figure 3B, G). The smallest scale measurements in the bay were turbulence measurements from an AUV (Figure 3F), which were also used to research the assimilation in real time of subgridscale data in the primitive equation model.
Concepts and Methods By definition (see Introduction), data assimilation in ocean sciences is an estimation problem for the ocean state, model parameters, or both. The schemes for solving this problem often relate to estimation or control theories (see below), but some approaches like direct minimization, stochastic, and hybrid methods (see below) can be used in both frameworks. Several schemes are theoretically optimal, while others are approximate or suboptimal. Although optimal schemes are preferred, suboptimal methods are generally the ones in operational use today. Most schemes are related in some fashion to least-squares criteria which have had great success. Other criteria, such as the maximum likelihood, minimax criterion or associated variations might be more appropriate when data are very noisy and sparse, and when probability density functions are multimodal (see Stochastic and hybrid models below). Parameters are assumed from here on to be
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Figure 3 Massachusetts Bay. (A) Schematic of circulation features and dominant variabilities. (B) Chlorophyll-a (mg m3) at 10 m, with overlying velocity vectors. (C) Sampling pattern for the bay scales and external large-scales in the Gulf of Maine. (D) Forecast of the standard error deviation for the surface temperature (from 01C in dark blue to a maximum of 0.71C in red), with tracks for adaptive sampling. (E) 20 m values of the temperature component of the first nondimensional physical variability mode. (F) AUV turbulence data (Naval Underwater Warfare Center (NUWC)). (G) Vertical section of zooplankton (mM m3) along the entrance of Massachusetts Bay (for more details, see Robinson and the LOOPS group, 1999, and Lermusiaux, 2001).
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included in the vector of state variables. For more detailed discussions, the reader is referred to the article published by Robinson et al. in 1998 (see Further Reading section).
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data and forecast. Conditions for convergence to the Kalman filter have been derived, but in practice only a few iterations are usually performed. Frequently, the scales or processes of interest are corrected one after the other, e.g., large-scale first, then mesoscale.
Estimation Theory
Estimation theory computes the state of a system by combining all available reliable knowledge of the system including measurements and theoretical models. The a priori hypotheses and melding or estimation criterion are crucial since they determine the influence of dynamics and data onto the state estimate. At the heart of estimation theory is the Kalman filter, derived in 1960. It is the sequential, unbiased, minimum error variance estimate based upon a linear combination of all past measurements and dynamics. Its two steps are: (1) the forecast of the state vector and of its error covariance, and (2) the dataforecast melding and error update, which include the linear combination of the dynamical forecast with the difference between the data and model predicted values for those data (i.e., data residuals). The Kalman smoother uses the data available before and after the time of interest. The smoothing is often carried out by propagating the future data information backward in time, correcting an initial Kalman filter estimate using the error covariances and adjoint dynamical transition matrices, which is usually demanding on computational resources. In a large part because of the linear hypothesis and costs of these two optimal approaches, a series of approximate or suboptimal schemes have been employed for ocean applications. They are now described, from simple to complex. Direct insertion consists of replacing forecast values at all data points by the observed data which are assumed to be exact. The blending estimate is a scalar linear combination, with user-assigned weights, of the forecast and data values at all data points. The nudging or Newtonian relaxation scheme ‘relaxes’ the dynamical model towards the observations. The coefficients in the relaxation can vary in time but, to avoid disruptions, cannot be too large. They should be related to dynamical scales and a priori estimates of model and data errors. In optimal interpolation (OI), the matrix weighting the data residuals, or gain matrix, is empirically assigned. If the assigned OI gain is diagonal, OI and nudging schemes can be equivalent. However, the OI gain is usually not diagonal, but a function of empirical correlation and error matrices. The method of successive corrections performs multiple but simplified linear combination of the
Control Theory
All control theory or variational approaches perform a global time-space adjustment of the model solution to all observations and thus solve a smoothing problem. The goal is to minimize a cost function penalizing misfits between the data and ocean fields, with the constraints of the model equations and their parameters. The misfits are interpreted as part of the unknown controls of the ocean system. Similar to estimation theory, control theory results depend on a priori assumptions for the control weights. The dynamical model can be either considered as a strong or weak constraint. Strong constraints correspond to the choice of infinite weights for the model equations; the only free variables are the initial conditions, boundary conditions and/or model parameters. A rational choice for the cost function is important. A logical selection corresponds to dynamical model (data) weights inversely proportional to a priori specified model (data) errors. In an ‘adjoint method’, the dynamical model is a strong constraint. One penalty in the cost function weights the uncertainties in the initial conditions, boundary conditions, and parameters with their respective a priori error covariances. The other is the sum over time of data-model misfits, weighted by measurement error covariances. A classical approach to solve this constrained optimization is to use Lagrange multipliers. This yields Euler-Lagrange equations, one of which is the so-called adjoint equation. An iterative algorithm for solving these equations has often been termed the adjoint method. It consists of integrating the forward and adjoint equations successively. Minimization of the gradient of the cost function at the end of each iteration leads to new initial, boundary, and parameter values. Another iteration can then be started, and so on, until the gradient is small enough. Expanding classic inverse problems to the weak constraint fit of both data and dynamics leads to generalized inverse problems. The cost function is usually as in adjoint methods, except that a third term now consists of dynamical model uncertainties weighted by a priori model error covariances. In the Euler-Lagrange equations, the dynamical model uncertainties thus couple the state evolution with the adjoint evolution. The representer method is an algorithm for solving such problems.
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Direct Minimization Methods
Examples
Such methods directly minimize cost functions similar to those of generalized inverse problems, but often without using the Euler-Lagrange equations. Descent methods iteratively determine directions locally ‘descending’ along the cost function surface. At each iteration, a minimization is performed along the current direction and a new direction is found. Classic methods to do so are the steepest descent, conjugate-gradient, Newton, and quasi-Newton methods. A drawback for descent methods is that they are initialization sensitive. For sufficiently nonlinear cost functions, they are restarted to avoid local minima. Simulated annealing schemes are based on an analogy to the way slowly cooling solids arrange themselves into a perfect crystal, with a minimum global energy. To simulate this relatively random process, a sequence of states is generated such that new states with lower energy (lower cost) are always accepted, while new states with higher energy (higher cost) are accepted with a certain probability. Genetic algorithms are based upon searches generated in analogy to the genetic evolution of natural organisms. They evolve a population of solutions mimicking genetic transformations such that the likelihood of producing better data-fitted generations increases. Genetic algorithms allow nonlocal searches, but convergence to the global minimum is not assured due to the lack of theoretical base.
This section presents a series of recent results that serve as a small but representative sample of the wide range of research carried out as data assimilation was established in physical oceanography.
Stochastic and Hybrid Methods
Stochastic methods are based on nonlinear stochastic dynamical models and stochastic optimal control. Instead of using brute force like descent algorithms, they try to solve the conditional probability density equation associated with ocean models. Minimum error variance, maximum likelihood or minimax estimates can then be determined from this probability density. No assumptions are required, but for large systems, parallel machines are usually employed to carry out Monte Carlo ensemble calculations. Hybrid methods are combinations of previously discussed schemes, for both state and parameter estimation; for example, error subspace statistical estimation (ESSE) schemes. The main assumption of such schemes is that the error space in most ocean applications can be efficiently reduced to its essential components. Smoothing problems based on Kalman ideas, but with nonlinear stochastic models and using Monte Carlo calculations, can then be solved. Combinations of variational and direct minimization methods are other examples of hybrid schemes.
General Circulation from Inverse Methods
The central idea is to combine the equations governing the oceanic motion and relevant oceanic tracers with all available noisy observations, so as to estimate the large-scale steady-state total velocities and related internal properties and their respective errors. The work of Martel and Wunsch in 1993 exemplifies the problem. The three-dimensional circulation of the North Atlantic (Figure 4A) was studied for the period 1980–85. The observations available consisted of objective analyses of temperature, salinity, oxygen, and nutrients data; climatological ocean–atmosphere fluxes of heat, water vapor, and momentum; climatological river runoffs; and current meter and float records. These data were obtained with various sensors and platforms, on various resolutions, as illustrated by Figure 4B. A set of steady-state equations were assumed to hold a priori, up to small unknown noise terms. The tracers were advected and diffused. The advection velocities were assumed in geostrophic thermal–wind balance, except in the top layer where Ekman transport was added. Hydrostatic balance and mass continuity were assumed. The problem is inverse because the tracers and thermal wind velocities are known; the unknowns are the fields of reference level velocities, vertical velocity, and tracer mixing coefficients. Discrete finite-difference equations were integrated over a set of nested grids of increasing resolutions (Figure 4A). The flows and fluxes at the boundaries of these ocean subdivisions were computed from the data (at 11 resolution). The resulting discrete system contained c. 29 000 unknowns and 9000 equations. It was solved using a tapered (normalized) least-squares method with a sparse conjugate-gradient algorithm. The estimates of the total flow field and of its standard error are plotted on Figure 1C and D. The Gulf Stream, several recirculation cells and the Labrador current are present. In 1993, such a rigorous large-scale, dense, and eclectic inversion was an important achievement. Global versus Local Data Assimilation via Nudging
Malanotte-Rizzoli and Young in 1994 investigated the effectiveness of various data sets to correct and control errors. They used two data sets of different types and resolutions in time and space in the Gulf
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Figure 4 (A) Domain of the model used in the inverse computations. Weak dynamical constraints were imposed on the flow and tracers, and integrated over a set of nested grids, from the full domain (heavy solid lines) to an ensemble of successive divisions (e.g., dashed lines) reaching at the smallest scales the size of the boxes labeled by numbers. (B) Locations of the stations where the hydrographic and chemical component of the data set were collected (model grid superposed). (C) Inverse estimate of the absolute sea surface topography in centimeters (contour interval is 10 cm). (D) Inverse estimate of the standard error deviation (in cm) of the sea surface topography shown in (C). (Reproduced with permission from Martel and Wunsch, 1993.).
Stream region, at mesoscale resolution and for periods of the order of 3 months, over a large-scale domain referred to as global scale. One objective was to assimilate data of high quality, but collected at localized mooring arrays, and to investigate the effectiveness of such data in improving the realistic attributes of the simulated ocean fields. If successful, such estimates allow for dynamical and process studies. The global data consisted of biweekly fields of sea surface dynamic
height, and of temperature and salinity in three dimensions, over the entire region, as provided by the Optimal Thermal Interpolation Scheme (OTIS) of the US Navy Fleet Numerical Oceanography Center. The local data were daily current velocities from two mooring arrays. The dynamical model consisted of primitive equations (Rutgers), with a suboptimal nudging scheme for the assimilation. The global and local data were first assimilated alone, and then together. The ‘gentle’ assimilation of
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Cross-over points
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Figure 5 (A) TOPEX/POSEIDON crossover points and subsampling. Representers were calculated only for the windowed subset of 986 satellite crossover points (large filled dots), but differences from all 6355 crossover points (small dots and large filled dots) were included in the data-misfit penalty. (B) Generalized inverse estimate of the amplitude and phase of the M2 tidal constituent. The phase isolines are plotted in white over color-filled contours of the amplitude. Contour interval is 10 cm for amplitude and 301 for phase. (Reproduced with permission from Egbert et al. 1994.).
the spatially dense global OTIS data was necessary for the model to remain on track during the 3-month period. The ‘strong’ assimilation of the daily but local data from the Synoptic Ocean Prediction SYNOP was required to achieve local dynamical accuracies, especially for the velocities. Small-scale Convection and Data Assimilation
In 1994, Miller et al. addressed the use of variational or control theory approaches (see earlier) to assimilate data into dynamical models with highly
nonlinear convection. Because of limited data and computer requirements, most practical ocean models cannot resolve motions that result from static instabilities of the water column; these motions and effects are therefore parameterized. A common parameterization is the so-called convective adjustment. This consists of assigning infinite mixing coefficients (e.g., heat and salt conductivities) to the water at a given level that has higher density than the water just below. This is carried out by setting the densities of the two parcels to a unique value in such a way that heat and mass are conserved. In a
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numerical model, at every time step, water points are checked and all statically unstable profiles replaced by stable ones. The main issues of using such convective schemes with variational data assimilation are that: (1) the dynamics is no longer governed by smooth equations, which often prevents the simple definition of adjoint equations; (2) the optimal ocean fields may evolve through ‘nonphysical’ states of static instability; and (3), the optimization is nonlinear, even if the dynamics are linear. Ideally, the optimal fields should be statically stable. This introduces a set of inequality constraints to satisfy. An idealized problem was studied so as to provide guidance for realistic situations. A simple variational formulation had several minima and at times produced evolutions with unphysical behavior. Modifications that led to more meaningful solutions and suggestions for algorithms for realistic models were discussed. One option is the ‘weak’ static stability constraint: a penalty that ensures approximate static stability is added to the cost function with a very small error or large weight. In that case, static stability can be violated, but in a limited fashion. Another option is the ‘strong constraint’ form of static stability which can be enforced via Lagrange multipliers. Convex programming methods which explicitly account for inequality constraints could also be utilized.
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size of the problem was reduced by winnowing out the full set of 6350 crossovers to an evenly spaced subset of 986 points (see Figure 5A). The resulting representer matrix was then reduced by singular value decomposition. The amplitude and phase estimates for the M2 constituent are shown in Figure 5B. The M2 fields are qualitatively similar to previous results and amphidromes are consistent. However, when compared with previous tidal model estimates, the inversion result is noticeably smoother and in better agreement with altimetric and ground truth data.
Conclusions The melding of data and dynamics is a powerful, novel, and versatile methodology for parameter and field estimation. Data assimilation must be anticipated both to accelerate research progress in complex, modern multiscale interdisciplinary ocean science, and to enable marine technology and maritime operations that would otherwise not be possible.
Acknowledgments We thank Ms. G. Sweetland and Ms. M. Armstrong for help in preparing the manuscript, and the ONR for partial support.
Global Ocean Tides Estimated from Generalized Inverse Methods
In 1994, Egbert et al. estimated global ocean tides using a generalized inverse scheme with the intent of removing these tides from the data collected by the TOPEX/POSEIDON satellite and thus allowing the study of subtidal ocean dynamics. A scheme for the inversion of the satellite crossover data for multiple tidal constituents was applied to 38 cycles of the data, leading to global estimates of the four principal tidal constituents (M2, S2, K1 and O1) at about 11 resolution. The dynamical model was the linearized, barotropic shallow water equations, corrected for the effects of ocean self-attraction and tidal loading, the state variables being the horizontal velocity and sea surface height fields. The data sets were linked to measurement models and comprehensive error models were derived. The generalized inverse tidal problem was solved by the representer method. Representer functions are related to Green’s functions: they link a given datum to all values of the state variables over the period considered. These representers were computed by solving the Euler-Lagrange equations in parallel. The
See also Open Ocean Convection. Biogeochemical Data Assimilation. Coastal Circulation Models. Current Systems in the Mediterranean Sea. CTD (Conductivity, Temperature, Depth) Profiler. Elemental Distribution: Overview. Expendable Sensors. Florida Current, Gulf Stream and Labrador Current. Forward Problem in Numerical Models. Inverse Models. Mesoscale Eddies. Ocean Circulation. Patch Dynamics. Regional and Shelf Sea Models. Tides. Upper Ocean Time and Space Variability.
Further Reading Anderson D and Willebrand J (eds.) (1989) Oceanic Circulation ModelsC: ombining Data and Dynamics. Dordrecht: Kluwer Academic. Bennett AF (1992) Inverse Methods in Physical Oceanography. Cambridge Monographs on Mechanics and Applied Mathematics. Cambridge: Cambridge University Press.
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Brasseur P and Nihoul JCJ (eds.) (1994) Data assimilationt: ools for modelling the ocean in a global change perspective. Series IG: lobal Environmental Change, 19. Berlin: Springer-Verlag. NATO ASI Series. Egbert GD, Bennett AF, and Foreman MGG (1994) TOPEX/POSEIDON tides estimated using a global inverse model. Journal of Geophysical Research 24: 821--824 852. Haidvogel DB and Robinson AR (eds) (1989) Special issue on data assimilation. Dynamics of Atmospheres and Oceans 13: 171–517. Lermusiaux PFJ (1999) Estimation and study of mesoscale variability in the Strait of Sicily. Dynamics of Atmospheres and Oceans 29: 255--303. Lermusiaux PFJ (2001) Evolving the subspace of the threedimensional multiscale ocean variability: Massachusetts Bay. Journal of Marine Systems. In press. Lermusiaux PFJ and Robinson AR (1999) Data assimilation via error subspace statistical estimation, Part IT: heory and schemes. Monthly Weather Review 7: 1385--1407. Lermusiaux PFJ and Robinson AR (2001) Features of dominant mesoscale variability, circulation patterns and dynamics in the Strait of Sicily. Deep Sea Research, Part I. In press. Malanotte-Rizzoli P and Young RE (1995) Assimilation of global versus local data sets into a regional model of the Gulf Stream system: I. Data effectiveness. Journal of Geophysical Research 24: 773--796. Malanotte-Rizzoli P (ed.) (1996) Modern Approaches to Data Assimilation in Ocean Modeling, Elsevier
Oceanography Series. The Netherlands: Elsevier Science. Martel F and Wunsch C (1993) The North Atlantic circulation in the early 1980s – an estimate from inversion of a finite-difference model. Journal of Physical Oceanography 23: 898--924. Miller RN, Zaron EO, and Bennett AF (1994) Data assimilation in models with convective adjustment. Monthly Weather Review 122: 2607--2613. Robinson AR, Lermusiaux PFJ, and Sloan NQ III (1998) Data assimilation. In: Brink KH and Robinson AR (eds.) The SeaT: he Global Coastal Ocean I, Processes and Methods, 10. New York: John Wiley and Sons. Robinson AR (1999) Forecasting and simulating coastal ocean processes and variabilities with the Harvard Ocean Prediction System. In: Mooers CNK (ed.) Coastal Ocean Prediction, AGU Coastal and Estuarine Study Series, pp. 77--100. Washington: AGU Press. Robinson AR and the LOOPS group (1999) Real-time forecasting of the multidisciplinary coastal ocean with the Littoral Ocean Observing and Predicting System (LOOPS). Third Conference on Coastal Atomspheric and Oceanic Prediction and Processes. New Orleans, LA: American Meterological Society, 30*35. (3-5 Nov 1999). Robinson AR and Sellschopp J (2000) Rapid assessment of the coastal ocean environment. In: Pinardi N and Woods JD (eds.) Ocean ForecastingC: onceptual Basis and Applications. London: Springer-Verlag. Wunsch C (1996) The Ocean Circulation Inverse Problem. Cambridge: Cambridge University Press.
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DEEP CONVECTION J. R. N. Lazier, Bedford Institute of Oceanography, NS, Canada Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 634–643, & 2001, Elsevier Ltd.
Introduction Density of ocean water generally increases with depth except at the surface where stirring by waves and convection creates a well-mixed homogeneous layer. Breaking waves alone can mix the upper 5–10 m, but convection, forced by an increase in density at the surface via heat loss or evaporation, can greatly increase the mixed layer depth. During winter, heat loss from the surface of the ocean is high and convectively mixed surface layers are the norm in the extratropical oceans. The deepest (4 1500 m) are found in the Labrador Sea, the Greenland Sea, and the Golfe du Lion in the Mediterranean Sea, because of two special features. First, they are near land where cold continental air flows over the water to create the necessary high heat loss. Second, the circulation in each is weakly cyclonic which helps to maintain the convecting water where the high heat loss occurs. The combination of these features provides the persistent heat loss from the same body of water that is needed to force convection to reach great depths. The example of a deepening convection layer in Figure 1 shows profiles of s1.5 (s1.5 þ 1000 ¼ potential density in kg m 3 referenced to 1500 decibars; 1 decibar corresponds to about 1 m) versus depth, on February 25 and March 8, 1997, in the Labrador Sea. The convecting layer is the approximately homogenous layer next to the surface about 750 m deep with a s1.5 of 34.65 kg m 3 on February 25 (Station 1) and 1150 m deep and 34.67 kg m 3 11 days later (Station 2). The buoyancy that was removed between the two profiles is proportional to the area between them, i.e. buoyancy ¼ ðg=r0 Þ
Z Drdz
where g (10 m s 2) is the acceleration due to gravity, r0(E1034 kg m 3) is the reference density, z is the depth and Dr is the difference in density between Stations 1 and 2. For the two stations illustrated this calculation yields a buoyancy loss of 0.17 m2 s 2. By
ignoring the small effect of evaporation, precipitation, and any advection, this buoyancy loss can be assumed to be due solely to heat loss from the surface. The loss is converted to joules by dividing by ga/r0c where g and r0 are as before and a (about 10 4 1C 1) is the thermal expansion of water and c (4.2 kJ kg 1 1C 1) is the specific heat of sea water at constant pressure. The conversion suggests that a heat loss of about 0.68 109 J m 2 was required to remove the buoyancy between the two dates. Over the 11 days between the observations this heat loss is equivalent to an average rate of heat loss of 715 W m 2. By a similar calculation, the heat loss required to increase the depth of convection to 2000 m would have been about 1.2 109 J m 2 or 460 W m 2 over a month. If the profiles in Figure 1 had been obtained during an era of mild winters rather than during one of abnormally severe winters they probably would have exhibited a markedly lower density in the upper layers. This might occur because of abnormally large freshwater flows into the surface layers due to increased outflows from the Arctic, warmer summers or a multiyear period of restratification following a vigorous period of convection. As the lower density represents ‘extra’ buoyancy to be removed before convection can proceed to greater depths, the ultimate depth of the convecting layer will be less in this situation, for a given heat loss, than in the illustrated one. Thus the ultimate depth of the convecting layer during a winter depends on the total amount of buoyancy lost from the sea surface and the distribution of that buoyancy with depth. The distribution of the newly convected water in two dimensions is illustrated in the contour plot of salinity across the Labrador Sea in Figure 2. These data were obtained in July following the exceptionally cold winter of 1992–93. The water mass resulting from convection is the large volume of nearly homogeneous water lying between 360 and 800 km on the horizontal scale and between 500 and 2300 m in the vertical. Because of its large volume, unique properties, and the fact that it spreads beyond its region of formation, this water is known as Labrador Sea Water. The upper layer (0–500 m) in the central part of the section is clearly not as well mixed as the layer between 500 and 2300 m. This is because the observations were obtained in July about 3 months after deep convection ceased at the end of the cooling season, about April 1. Since that time the surface layer has been flooded with fresh water derived from melting ice and river runoff. Also, the layer below this
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DEEP CONVECTION
1.5 (kg m–3) 34.64 0
34.66
34.68
Sta 1
34.70
34.72
Sta 2
400
Depth (m)
800
1200
1600
2000
Figure 1 Vertical distribution of s1.5 obtained from R/V Knorr at 56.81N, 54.21W in the Labrador Sea on February 25 (Station 1) and March 8, 1997 (Station 2).
1
5
10
15
20
25
0 34.93 34.92 34.91 34.90 34.89 34.88 34.87 34.86 34.85 34.84 34.83 34.82 34.81 34.80 34.75 34.70 34.60 34.40 34.20 34.00 33.50 33.00 32.00
Depth (m)
1000
2000
3000
100
300
500
700
900
Distance (km) Figure 2 Salinity distribution across the Labrador Sea between 53.01N, 55.51W and 60.61N, 49.31W obtained between June 19 and 23, 1993. The water between 500 m and 2200 m in the central part of the section is unusually homogeneous because of deep convective mixing during the severe winter of 1992–93. The CTD station positions are indicated by numbered triangles along the surface.
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DEEP CONVECTION
low salinity surface layer, to about 500 m, has been invaded by higher salinity water from the right (northeast) and to a lesser extent the left (south-west). The newly formed Labrador Sea Water is a mixture of all the water down to 2300 m including the water in contact with the atmosphere at the surface. In these uppermost layers the concentration of gases such as oxygen, carbon dioxide, tritium, and chlorofluorocarbons (CFCs) are at or near equilibrium with the atmosphere. By transporting these gases down from the upper layers of the ocean to intermediate depths, convection provides a mechanism to ventilate the deeper layers, which is one of the most important consequences of deep convection. Dissolved oxygen, for example, is slowly used up in the deep ocean by biological processes and would eventually vanish without the renewal via convection. Also most of the carbon dioxide ever put in the atmosphere by volcanoes since the formation of the Earth became dissolved in the ocean and is now contained in sediments in the bottom of the ocean. As combustion of fossil fuels over the earth raises the carbon dioxide content of the atmosphere it is important to understand the rate at which this gas is entering the deeper layers of the ocean through processes such as deep convection. Subsequent to formation, Labrador Sea Water spreads to other regions of the ocean at intermediate depths. Knowledge of the speed of this flow and its influence increased during the 1990s due to the widespread high quality observations of temperature, salinity, and CFCs across the North Atlantic obtained under the international World Ocean Circulation Experiment. The newly ventilated water formed in the Labrador Sea during the severe winters of the early 1990s moved across the North Atlantic at about 2 cm s 1. This speed is about three to four times greater than the previous estimate, leading to the conclusion that the intermediate flows are much faster than previously thought. A comparison of six decades of data from the Labrador Sea and from the subtropical waters near Bermuda suggest that the products of deep convection in the Labrador Sea impact the waters off Bermuda after about 6 years.
Plumes – the Mixing Agent Convection begins to increase the depth of the mixed layer in the Labrador Sea near the end of September when the surface net buoyancy flux from the surface turns from positive to negative. Deepening continues until about the end of March when the buoyancy flux again becomes positive. When convection is active, water at the surface becomes denser than the underlying water and descends in plumes. This water
15
is replaced by slightly lighter water rising toward the surface. The physical features of the convecting water including the plumes and the water between have been the subject of a number of investigations; most notably by the group of scientists at Kiel working in the Golfe du Lion in the Mediterranean Sea with moored acoustic Doppler current profilers (ADCP) and current meters. The cartoon in Figure 3 summarizes some of the main features of plumes and the mixing layer. At the surface is the thermal boundary layer where the water is losing heat/buoyancy to the atmosphere. Water in this layer is, on average, slightly denser than in the mixed layer beneath and descends into the mixing layer within plumes which have a horizontal dimension of about 1 km, approximately equal to that vertical extent, i.e. an aspect ratio of E 1. The average rate of descent within the plumes is about 0.02 m s 1 while the maximum is E0.13 m s 1. Rotation of the plumes, due to the horizontal component of the Coriolis force, is expected because water must converge into the plume at its top and presumably diverge out of it near the bottom. However, this effect has not yet been conclusively observed in the field although it has been observed in laboratory experiments and in numerical simulations. Another effect that has not been observed is an increasing horizontal dimension with depth which is expected if water is entrained into the plumes as they descend, or if they decelerate as they go deeper. Observations also indicate that there is no net vertical mass flux within a convecting region or patch. This appears to have solved the long-standing puzzle of whether the descending water was replaced by rising water between the plumes or by converging flow in the upper layer and diverging flow in the deep layer. Finally, on average, the plumes are not penetrative, i.e. the plumes do not have enough energy to descend into water that is denser than the water within the plume. One consequence of this is illustrated in Figure 1 by the fact that the bottom of the mixing layer at Station 2 lies on the s1.5 versus depth curve observed earlier on February 25. If convection was penetrative the bottom of the mixed layer on March 8 would lie below this curve and the s1.5 versus depth gradient at the bottom of the mixing layer would be greater than when it was observed earlier. The plumes in the cartoon suggest that there should be a high correlation between fluctuations in temperature and vertical velocity. However, recent measurements from drifting floats indicate this correlation to be weak, thus making the cartoon a rather simplified view of the true situation. In reality the plumes are probably not vertical over the full depth
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DEEP CONVECTION
Figure 3 A schematic diagram of a E 1000 m convecting layer indicating approximate values for features of individual plumes including the horizontal scale, vertical downward velocity, rotation, and entrainment. Across the patch of convecting water there is no net vertical mass flux and no significant penetration into the layers of denser water beneath the convecting layer. Buoyancy (B0) lost from the surface creates the thermal boundary layer in the upper E 100 m where the denser water is formed which sinks within the plumes. The wiggly up arrow indicates the (slow) upward flow that replaces the (relatively fast) downward flow within the plumes. Note that the horizontal scale in the figure is E 50 times the vertical scale.
of the convecting layer but contorted by the largerscale flows. A direct view of the motion within convecting plumes has recently been obtained from freely drifting floats. When one of these is launched it immediately sinks to a predetermined depth below the convecting layer where it remains for typically 7 days while its buoyancy adjusts. At the end of this period its buoyancy is decreased slightly and the float rises into the convecting layer. A large attached drogue then causes the float to moved up and down with the vertical motions of convection. In the Labrador Sea over 25 days in February and March 1997 the maximum vertical velocity observed by a set of these floats was downward at 0.2 m s 1 with a rms value for all the observations of 0.02 m s 1. This is equivalent to a round trip of the convecting layer of 1 day for the average water parcel. On a number of
occasions the floats were seen to penetrate below the average bottom of the mixing layer. Contrary to the conclusions mentioned above that the convection is not penetrative, this suggests that a certain amount of plume penetration into denser layers does occur.
Temperature and Salinity Variability Year-long time-series records of temperature and salinity obtained in the middle of the Labrador Sea indicate that there is a marked increase in temperature and salinity variability during and following convection. This is evident in the temperature record in Figure 4 obtained at 510 m in 1994–95. Between June and the middle of February the temperature sensor is below the mixed layer and the temperature slowly increases by about 0.21C. In mid-February the temperature drops by about 0.41C as the deepening
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DEEP CONVECTION
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3.4
Potential temperature (°C)
3.2
3.0
2.8
2.6
2.4 June
Aug
Oct
Dec
Feb
Apr
June
Months, 1994 – 95 Figure 4 A 1 year record of temperature at 510 m in the central Labrador Sea illustrating the increase in variance during and after the mixed layer reaches the depth of the instrument in early February 1995 plus the sudden upward shift in temperature near April 1 associated with the end of convection.
convecting layer reaches the depth of the sensor. At this time the magnitude of the variations in temperature suddenly increase and continue at a high level for a number of weeks. Spectra calculated from 85-day pieces of this record before and after the arrival of the convection layer show a broadband fourfold increase in the spectral energy of the variability after the sensor is immersed in the mixed layer. Time-series of the energy show a peak in February shortly after the mixed layer arrives followed by a decline to 1/30th of the peak value by the end of the record in June. Similar fluctuations occur in salinity and are largely in phase with those in temperature. Figure 5 shows temperature versus salinity plots at four depths during 21 days in March 1995 when convection was proceeding to about E 2000 m. During this time period density at each of these levels was relatively constant in time. In the figure the hourly observations at each depth show the extent of the fluctuations in temperature and salinity and the fact that they are largely parallel to the constant density surfaces; the T–S fluctuations tend to be parallel to the isopycnals. The most probable explanation for the fluctuations is that they are horizontal variations in temperature and salinity being swept past the mooring by the current. One suggestion is that these variations reflect horizontal variability in the depth of convection. However, recent work in the mixed
layer of the tropical Pacific demonstrates that compensating horizontal variations in temperature and salinity may be ubiquitous features of the mixed layer whether it is convecting or not. These results lead to the alternative suggestion that the compensating temperature and salinity variations exist in the windmixed surface layer before deep convection begins and are propagated downward by the convection. When convection stops, the vertical density stratification is reestablished in the surface layers and the horizontal variations that appeared during convection are no longer renewed. Those variations existing when convection ends are then slowly mixed away by turbulent eddies leading to the decay in the amplitude of the fluctuations as observed in the timeseries. Assuming a horizontal scale L of 100 km for the region of convection with its small-scale horizontal variations, the timescale of eddy mixing will be about L2/KH where KH, the horizontal eddy diffusivity, is about 103 m2 s 1. This gives a timescale for the horizontal mixing of about 4 months, which is about the decay time observed in the records.
Restratification At the end of the cooling season, vertical mixing due to convection ceases and its dominant influence on mid-depth water properties ends. This also marks the beginning of the restratification process during which
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DEEP CONVECTION
260 m 3.0
510 m
3.0
2
4.6
Potential temperature (°C)
2.9
1.5
=3
2.9
2.8
2.8
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2.7 2.6
2.6 .72
2.5 34.78
34
34.80
34.82
34.84
2.5 34.86
34.78
34.80
Potential temperature (°C)
3.0
2.9
2.9
2.8
2.8
2.7
2.7
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2.6
34.80
34.82
34.84
34.86
34.84
34.86
1510 m
1010 m 3.0
2.5 34.78
34.82
34.84
34.86
2.5 34.78
Salinity
34.80
34.82 Salinity
Figure 5 Temperature versus salinity diagrams based on data obtained at 260, 510, 1010, and 1510 m in the central Labrador Sea, between March 12 and April 2, 1995, during the final stage of convection when the density at these depths remained relatively constant.
the vertical stratification existing prior to the homogenization begins to be reestablished. Two timescales seem to be involved. At the end of convection a rapid restratification occurs which is indicated by sudden shifts of variables such as temperature. One example is indicated in Figure 4 by the increase of 0.21C near April 1 following roughly 6 weeks of convective activity at this depth. It is not clear if this increase indicates an end to convection over a large area, or the advection of a stratified nonconvecting water column to the observation site. The first option, however, seems more likely as the end of convection appears in other records as a rapid increase in stratification especially in the upper layers. For example, a tomographic array in the Golfe du Lion observed a roughly 40 day restratification period following convection. This seems to be the only observation of restratification over a large area. Another example is the record from a PALACE
(profiling autonomous Lagrangian circulation explorer) in the Labrador Sea which shows, during 2 consecutive years, a sudden transition between the low stratification associated with convection and a stratified water column. This record is admittedly like a mooring, from a single point, but it does give a consistent picture in the 2 years. A recent numerical model of the restratification process may describe this rapid phase. It has a homogeneous cylinder of water floating in an ocean of constant stratification. The density gradient between the cylinder and the surrounding ocean gives rise to a narrow cyclonic current which breaks up via baroclinic instability into baroclinic eddies. These mix the homogeneous water horizontally with the stratified waters and so dissipate the homogeneous cylinder in timescale t. For the special case where the stratification in the water surrounding the homogeneous cylinder is concentrated in the upper
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DEEP CONVECTION
layer h:
19
Restratification over a number of years is illustrated in the time series of s1.5 through the 1990s in Figure 7. In the early years of the decade the water produced by the convection, indicated by the layer of low vertical gradient, lies within the 34.64 and 34.70 kg m 3 surfaces. Between 1990 and 1994 the volume of this waterremains roughly constant but the value of s1.5 at the core increases from 34.67 to 34.69 kg m 3 as the winters became more severe and the convecting layer continued to deepen into the stratified layer below. In the years following 1995, convection was limited to 1000–1500 m. The deep reservoir of ‘homogeneous’ water was thereby isolated below the convecting layer and slowly decreased in volume with each passing year as it drained away. This decrease in volume was balanced by an increase in the volume of lighter more stratified water in the upper layers from the boundaries. The large interannual variation in the volume of the Labrador Sea Water illustrated in this figure is a well known property of the water mass; however, its effects on the large-scale ocean currents and processes are not yet well understood.
tE56 r=ðhDbÞ1=2 where r is the radius of the homogeneous cylinder, h is the depth of the upper stratified water bounding the homogeneous cylinder and Db is the difference in density between the homogeneous water and the surrounding water in buoyancy units (i.e. Db ¼ gDr/r0). For the Labrador Sea where h E 500 m, Db E 2 10 3 m s 2 and r E 100 km; t E 65 days. This result, being of the same order as the observed rapid changes in stratification, suggests that the model may be appropriate to explain the observations. The long timescale of restratification has now been observed in the Labrador Sea. Observations have been made continuously over one summer and intermittently over a few successive years. Changes over the summer of 1996 are illustrated in Figure 6 by the depths of four of the isopycnals within the upper 1000 m. At stations between 400 and 600 km the isopycnal depths increase significantly between May and October while the 27.72 and 27.74 kg m 3, surfaces between 650 and 790 km, show a decrease in depth. These changes suggest that lighter water, from beyond the region of deepest convection (400– 600 km), moves into the upper water column in the region of deepest convection while denser water in the region of deepest convection moves outward toward the boundaries at mid-depth.
Discussion While the focus of this article has been on the Labrador Sea, numerous aspects of the convective processes discussed here also apply to the other two locations of open-ocean convection in the North
Distance (km) 200
300
400
500
600
700
800
900
0 27.64 200
Depth (m)
27.68
400 27.72 May 600 October 27.74 800
1000 Figure 6 Four surfaces of constant s0 (potential density anomaly relative to 0 m) across the Labrador Sea based on CTD data collected in May 1996 (solid lines) and October 1996 (dotted lines).
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DEEP CONVECTION
0
1.5 = 34.56
500 34.60
Depth (m)
1000 34.64 1500
34.68
2000
2500 1990
1992
1994
1996
1998
2000
Years Figure 7 Depths of s1.5 surfaces in the middle of the Labrador Sea through the 1990s based on CTD data collected in May or June of each year.
Atlantic: the Greenland Sea and the Mediterranean Sea. But as there are common threads to the overturning in these seas there are also significant regional differences. The Greenland Sea is unique in that ice plays a significant role in the preconditioning phase. The deepest convective overturning occurs in late winter just after the ice-free ‘Nord Bukta’ region opens up. In the Mediterranean the winds are more localized than in the other two regions. This clearly influences the convection, as the region of deepest mixed layers generally lies in the path of the Mistral winds. Furthermore, these winds are rarely coldenough to cause convection during daylight hours, so the Mediterranean has a daily cycle of overturning that is not present in the other two seas. Also, the impact of the basin-scale NorthAtlantic Oscillation wind pattern influences the Labrador and Greenland Seas to a much greater extent than the Mediterranean. Finally, the dimensions of the convection zones and convected water masses differ greatly. In the Mediterranean, the convecting patch is of order 50 km wide; in the Greenland Sea it is of order 100 km wide, and in the Labrador Sea the zone of convection approaches 500 km in width, and includes the boundary currents. Convection at each of these three Atlantic sites contributes to the global meridional overturn circulation, although the quantitative measures are not yet known. In the Greenland Sea particularly, the deep convection into the cyclonic gyre seems rather isolated from the processes that produce the dense
overflows. Mediterranean Water and Labrador Sea Water both make an obvious contribution to the Upper North Atlantic Deep Water, respectively, as high and low salinity endpoints. Distant identification of Labrador Sea Water is through its low salinity; potential vorticity; low nutrient concentration; high dissolved oxygen, tritium, and CFCs. Along the western boundary velocity and CFC maxima associated with Labrador Sea Water have been observed near Abaco, nearly 5000 km south. For the era ending in 1977 a dilution of the tritium maxima of the deep western boundary currents by factors of order 10 was observed, from the subpolar gyre to the Blake-Bahama Outer Ridge. This suggested dilution and delay (recirculation) mechanisms en route. Model studies suggest that when convection is initiated or increased at the high-latitude source, a pressure wave propagates south along the western boundary, as a topographic Rossby wave, well before the arrival of tracer-tainted, identifiable water mass. Such model studies point out that sloping topography acts as a wave guide, and rather gently leads dense water masses equatorward from high latitude, as they slowly sink. Thus, ‘sinking’ is minimal in the near-field of the convection, but occurs downstream. Production of kinetic energy of theoverturning circulation by potential energy created by buoyancy forcing requires that dense water sink and less dense water rise, but the sites of sinking and rising are, at least in modestudies, often distant from the
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DEEP CONVECTION
convection. In a diapycnal/epipycnal coordinate system, however, convection is more locally associated with time-averaged diapycnal transport (‘watermass conversion’). Such analyses are beginning to be carried out with models and are an insightful way to approach the link between convection, sinking, and global meridional overturning. Thus we are still seeking to quantify production rates of the constituent water masses of the global meridional overturning. Outward transport of Labrador Sea Water is even difficult todefine, because of extensive recirculation within the subpolar gyre, and entrainment once the water mass has left the subpolar gyre. Estimates have ranged from o1 Sv to 410 Sv. Much alsremains unknown about the detailed geography of deep convection and circulation. In the Labrador Sea, both interior and boundary currents are known to participate in the deep convection (estimates of 1–2 Sv of boundary current production). However, the boundary current, is shielded from deep convection by low salinity shelf waters at some sites. Where the circulation crosses from Greenland to Labrador, the boundary currents broaden and slow down, andare generally exposed to some of the most intense air–sea heat flux in the sea; there and over the wide continental slope near Labrador, convection may be particularly deep. Direct velocity and transport measurements are needed to augment water mass observations. Unfortunately the Lagrangian movement of water masses is difficult to observe even with modern ‘quasi-Lagrangian’ floats and drifters. A recent description of the Labrador/Irminger Sea circulation from PALACE floats notes that ‘no floats travelled southward to the subtropical gyre in the deep western boundary current, the putative main pathway of dense
21
water in the meridional overturning circulation’. If the boundary current is concentrated to a narrow width, for example at the Flemish Cap, then these profiling floats may have difficulty staying within it; tracer observations assure us that the transport does in fact take place.
See also Carbon Cycle. Current Systems in the Mediterranean Sea. Mediterranean Sea Circulation. Rossby Waves. Sub-sea Permafrost.
Further Reading Lazier JR, Pickart RS, and Rhines PB (2001) Deep convection. In: Ocean Circulation and Climate – Observing and Modelling the Global Ocean. London: Academic Press. Lilly J, Rhines P, Visbeck M, et al. (1999) Observing deep convection in the Labrador Sea during winter 1994– 1995. Journal of Physical Oceanography 29: 2065--2098. Marshall J and Schott F (1999) Open-ocean convection observations, theory and models. Reviews of Geophysics 37: 1--64. Schott R, Visbeck M, and Send U (1994) Open ocean deep convection, Mediterranean and Greenland Seas. In: Malanotte-Rizzoli P and Robinson AR (eds.) Ocean Processes on Climate Dynamics: Global and Mediterranean Examples, pp. 203--225. Dordrecht: Kluwer Academic Publishers. Lab Sea Group (1998) The Labrador Sea Deep Convection Experiment. Bulletin of the American Meteorological Society 79: 2033--2058.
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DEEP SUBMERGENCE, SCIENCE OF D. J. Fornari, Woods Hole Oceanographic Institution, Woods Hole, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 643–658, & 2001, Elsevier Ltd.
Introduction The past half-century of oceanographic research has demonstrated that the oceans and seafloor hold the keys to understanding many of the processes responsible for shaping our planet. The Earth’s ocean floor contains the most accurate (and complete) record of geologic and tectonic history for the past 200 million years that is available for a planet in our solar system. For the past 30 years, the exploration and study of seafloor terrain throughout the world’s oceans using ship-based survey systems and deep submergence platforms has resulted in unraveling plate boundary processes within the paradigm of sea floor spreading; this research has revolutionized the Earth and Oceanographic sciences. This new view of how the Earth works has provided a quantitative context for mineral exploration, land utilization, and earthquake hazard assessment, and provided conceptual models which planetary scientists have used to understand the structure and morphology of other planets in our solar system. Much of this new knowledge stems from studying the seafloor – its morphology, geophysical structure, and characteristics, and the chemical composition of rocks collected from the ocean floor. Similarly, the discoveries in the late 1970s of deep sea ‘black smoker’ hydrothermal vents at the midocean ridge (MOR) crest (Figure 1) and the chemosyntheticbased animal communities that inhabit the vents have changed the biological sciences, provided a quantitative context for understanding global ocean chemical balances, and suggest modern analogs for the origin of life on Earth and extraterrestrial life processes. Intimately tied to these research themes is the study of the physical oceanography of the global ocean water masses and their chemistry and dynamics, which has resulted in unprecedented perspectives on the processes which drive climate and climate change on our planet. These are but a few of the many examples of how deep submergence research has revolutionized our understanding of our Earth and ocean history, and provide a glimpse at the diversity of scientific frontiers that await exploration in the years to come.
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Enabling Deep Submergence Technologies The events that enabled these breakthroughs was the intensive exploration that typified oceanographic expeditions in the 1950s to 1970s, and focused development of oceanographic technology and instrumentation that facilitated discoveries on many disciplinary levels. Significant among the enabling technologies were satellite communication and global positioning, microchip technology and the widespread development of computers that could be taken into the field, and increasingly sophisticated geophysical and acoustic modeling and imaging techniques. The other key enabling technologies which supplanted traditional mid-twentieth century methods for imaging and sampling the seafloor from the beach to the abyss were submersible vehicles of various types, remote-sensing instruments, and sophisticated acoustic systems designed to resolve a wide spatial and temporal range of ocean floor and oceanographic processes. Oceanographic science is by nature multidisciplinary. Science carried out using deep submergence vehicles of all types has traditionally involved a wide range of research components because of the time and expense involved with conducting field research on the seafloor using human occupied submersibles or remotely operated vehicles (ROVs), and most recently autonomous underwater vehicles (AUVs) (Figures 2–6). Through the use of all these vehicle systems, and most recently with the advent of seafloor observatories, deep submergence science is poised to enter a new millennium where scientists will gain a more detailed understanding of the complex linkages between physical, chemical, biological, and geological processes occurring at and beneath the seafloor in various tectonic settings. Understanding the temporal dimension of seafloor and sub-seafloor processes will require continued use of deep ocean submersibles and utilization of newly developed ROVs and AUVs for conducting timeseries and observatory-based research in the deep ocean and at the seafloor. These approaches will provide new insights into intriguing problems concerning the interrelated processes of crustal generation, evolution, and transport of geochemical fluids in the crust and into the oceans, and origins and proliferation of life both on Earth and beyond. Since the early twentieth century, people have been venturing into the ocean in a wide range of diving vehicles from bathyscapes to deep diving submersibles.
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DEEP SUBMERGENCE, SCIENCE OF
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(D)
(C)
Figure 1 Hydrothermal vents on the southern East Pacific Rise axis at depths of 2500–2800 m. (A) Titanium fluid sampling bottles aligned along the front rail of Alvin’s basket in preparation for fluid sampling. (B) Alvin’s manipulator claw preparing to sample the hydrothermal sulfide chimney. (C) View from inside Alvin’s forward-looking view port of the temperature probe being inserted into a vent orifice to measure the fluid temperature. (D) Hydrothermal vent after a small chimney was sampled which opened up the orifice through which the fluids are exiting the seafloor. Photos courtesy of Woods Hole Oceanographic Institution – Alvin Group, D. J. Fornari, K. Von Damm, and M. Lilley.
Even in ancient times, there was written and graphic evidence of the human spirit seeking the mysteries of the ocean and seafloor. There is unquestionably the continuing need to take the unique human visual and cognitive abilities into the ocean and to the seafloor to make observations and facilitate measurements. For about the past 40 years submersible vehicles of various types have been developed largely to support strategic naval operations of various countries. As a result of that effort, the US deep-diving submersible Alvin was constructed. Alvin is part of the National Deep Submergence Facility (NDSF) of the University National Oceanographic Laboratories System (UNOLS) operated by the Woods Hole Oceanographic Institution (Figure 7). Alvin provides routine scientific and engineering access to depths as great as 4500 m. The
US academic research community also has routine, observational access to the deep ocean and seafloor down to 6000 m depth using the ROV and tethered vehicles of the NDSF (Figure 7). These vehicle systems of the NDSF include the ROV Jason, and the tethered optical/acoustic mapping systems Argo II and DSL120 sonar (a 120 kHz split-beam sonar system capable of providing 1–2 m pixel resolution back-scatter imagery of the seafloor and phase-bathymetric maps with B4 m pixel resolution (Figure 7). These fiberopticbased ROV and mapping systems can work at depths as great as 6000 m. Alvin has completed over 3600 dives (more than any other submersible of its type), and has participated in making key discoveries such as: imaging, mapping, and sampling the volcanic seafloor on
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DEEP SUBMERGENCE, SCIENCE OF
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Figure 3 (A) The ROV Jason being lifted off the stern of a research vessel at the start of a dive. (B) ROV Jason recovering amphora on the floor of the Mediterranean Sea. Photos courtesy of Woods Hole Oceanographic Institution – Alvin Group and R. Ballard.
(B)
Figure 2 (A) The submersible Alvin being lifted onto the stern of R/V Atlantis, its support ship. (B) Alvin descending to the seafloor. Photos courtesy of Woods Hole Oceanographic Institution – Alvin Group and R. Catanach.
the MOR crest; structural, petrological, and geochemical studies of transforms faults; structural studies of portions of deep-sea trenches off Central America; petrological and geochemical studies of volcanoes in back-arc basins in the western Pacific Ocean; sedimentary and structural studies of submarine canyons, discovering MOR hydrothermal vents; and collecting samples and making time series measurements of biological communities at hydrothermal vents in many MOR settings in the Atlantic
and Pacific Oceans. In 1991, scientists in Alvin were also the first to witness the vast biological repercussions of submarine eruptions at the MOR axis, which provided the first hint that a vast subsurface biosphere exists in the crust of the Earth on the ocean floor (Figure 7).
Deep Submergence Science Topics Some of the recent achievements in various fields of deep submergence science include the following. 1. Discoveries of deep ocean hydrothermal communities and hot (43501C) metal-rich vents on
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DEEP SUBMERGENCE, SCIENCE OF
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Figure 4 Photographs taken from the ROV Jason at hydrothermal vents on the Mid-Atlantic Ridge near 371N on the summit of Lucky Strike Seamount at a depth of 1700 m. All photographs are of a vent named ‘Marker d4.’ (A) Overall view of vent looking North. White areas are anhydrite and barite deposits, yellowish areas are covered with clumps of vent mussels. (B) Close-up of the side of the vent; Jason’s sampling basket is in the foreground. (C) Close-up view of mussels on the side of the hydrothermal chimney; the hydrothermal vent where hot fluids are exiting the mound is at the upper right, where the image is blurry because of the shimmering effect of the hot water. Nozzles of a titanium sampling bottle are at the middle-right edge. (D) Inserting a self-recording temperature probe into a beehive chimney. (E) Titanium fluid sampling bottles being held by Jason’s manipulator during sampling. (F) Close-up of nozzles of sampling bottle inserted into vent orifice during sampling. Photos (D)–(F) are frame grabs of Jason video data. Photos courtesy of Woods Hole Oceanographic Institution – ROV Group, D. J. Fornari, S. Humphris, and T. Shank.
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DEEP SUBMERGENCE, SCIENCE OF
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(B)
Figure 5 (A) ROV Tiburon of the Monterey Bay Aquarium Research Institute (MBARI) in the hanger of its support ship R/V Western Flyer. This electric-powered ROV can dive to 4000 m. A steel-armored, electro-optical cable connects Tiburon to the R/V Western Flyer and delivers power to the vehicle. Electric thrusters allow fine maneuvering while minimizing underwater noise and vehicle disturbance. A variable buoyancy control system, together with the syntactic foam pack, enables Tiburon to hover inches above the seafloor without creating turbulence, to pick up a rock sample, or maneuver quickly to follow an animal. (B) ROV Ventana of the MBARI being launched from its support ship R/V Pt. Lobos. This ROV gives researchers the opportunity to make remote observations of the seafloor to depths of 1850 m. The vehicle has two manipulator arms – a seven-function arm with five spatially correspondent joints and another sevenfunction robot arm with six spatially correspondent joints. Both arms can use a variety of end effectors to suit the type of work being done. Ventana is also equipped with a conductivity, temperature, and density (CTD) package including a dissolvedoxygen sensor and a transmissometer. Photos courtesy of MBARI.
many segments of the global mid-ocean ridge (MOR); 2. Documentation of the immediate after-effects of submarine eruptions on the northern East Pacific Rise, Axial Seamount, Gorda Ridge and CoAxial Segment of the Juan de Fuca Ridge;
Figure 6 The autonomous underwater vehicle (AUV) ABE (Autonomous Benthic Explorer) of the Woods Hole Oceanographic Institution’s Deep Submergence Laboratory, which can survey the seafloor completely autonomously to depths up to 4000 m and is especially well suited to working in rugged terrain such as is found on the Mid Ocean Ridge. Photo courtesy of Woods Hole Oceanographic Institution.
3. Utilization of Ocean Drilling Program bore holes and specialized vehicle systems (e.g. Scripps Institution’s Re-Entry Vehicle) (Figure 8) and instrument suites (e.g. CORKs) (Figure 9) for a wide range of physical properties, fluid flow and seismological experiments; 4. Discoveries of extensive fluid flow and vent-based biological communities along continental margins and subduction zones; 5. Initial deployment of ocean floor observatories of various types which enable the monitoring and sampling of geological, physical, biological and chemical processes at and beneath the seafloor (Figures 10 and 11). These studies have revolutionized our concepts of deep ocean processes and highlighted the need
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DEEP SUBMERGENCE, SCIENCE OF
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Figure 7 (A) Summary of the US National Deep Submergence Facility (NDSF) vehicles operated for the University National Oceanographic Laboratories System (UNOLS) by the Woods Hole Oceanographic Institution (WHOI). (B) Montage of the NDSF vehicles showing examples of the various types of data they collect. The figure also shows the nested quality of the surveys conducted by the various vehicles which allows scientists to explore and map features with dimensions of tens of kilometers (top right multibeam sonar map), to detailed sonar back scatter and bathymetry swaths which have a pixel resolution of 1–2 m (DSL-120 sonar), which are then further explored with the Argo II imaging system, or sampled using Alvin or ROV Jason. Graphics by P. Oberlander, WHOI; photos courtesy of WHOI – Alvin and ROV Group.
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DEEP SUBMERGENCE, SCIENCE OF
_ 1500 _ 2000 _ 2500
37˚ 05′ N
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1 km DSV Alvin
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Figure 7 (Continued)
for more detailed, time-series, multidisciplinary research. Within the field of biological oceanography, major recent advances have come from the study of the new life forms and chemoautotrophic
processes discovered at hydrothermal vents (Figure 10). These advances have fundamentally altered biological classification schemes, extended the known thermal and chemical limits of life, and have pushed the search for origins of life on Earth
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DEEP SUBMERGENCE, SCIENCE OF
(A)
Figure 8 (A) The Scripps Institution of Oceanography’s Control Vehicle is a specialized ROV that can place instrument strings inside deep-sea boreholes, using a conventional oceanographic vessel capable of dynamic positioning and equipped with a winch carrying 17.3 mm (0.68 in) electromechanical cable with a single coax (RG8-type). The control vehicle is 3.5 m tall and weighs about 500 kg in water (1000 kg in air). It consists of a stainlesssteel frame that contains two orthogonal horizontal hydraulic thrusters, a compass, a Paroscientific pressure gauge, four 250 W lights, a video camera, sonar systems, electronic interfaces to electrical releases and to a logging probe, and electronics to control all these sensors and handle data telemetry to and from the ship. Telemetry on the tow cable’s single coax is achieved by analog frequency division multiplexing over a frequency band extending from 20 kHz to about 800 kHz. The sonars include a 325 kHz sector-scanning sonar, a 23.5 kHz narrow beam acoustic altimeter, and a 12 kHz sonar for long baseline acoustic navigation. This system was used successfully in the 1998 Ocean Seismic Network Pilot Experiment at ODP Hole 843B, 225 km south-west of the island of Oahu, Hawaii. In 1999, the control vehicle’s analog telemetry module was converted into a digital system using fiberoptic technology thus providing bandwidth capabilities in excess of 100 Mbaud. (B) Cartoon showing the configuration of the control vehicle deployed from a research ship as it enters an Ocean Drilling Program bore hole to insert an instrument string. Photo and drawing courtesy of Scripps Institution of Oceanography – Marine Physical Laboratory, F. Spiess, and C. de Moustier.
29
as well as for new life forms on other planetary bodies. Recent marine biological studies show that: (1) the biodiversity of every marine community is vastly greater than previously recognized; (2) both sampling statistics and molecular tools indicate that the large majority of marine species have not been described; (3) the complexity of biological communities is far greater than previously realized; and (4) the response of various communities to both natural and anthropogenic forcing is far more complex than had been understood even a decade ago. Focused studies over long time periods will be required to characterize these communities fully. The field of marine biology is heading toward a more global time-series approach as a function of recent discoveries largely in the photic zone of the oceans and in the deep ocean at MOR hydrothermal vents. The marine biological, chemical, and physical oceanographic research which will be carried out in the next decade and beyond will certainly have a profound impact on our understanding of the complex food webs in the ocean which control productivity at every level and have direct implications for commercial harvesting of a wide range of resources from the ocean. Meeting the challenge of deciphering the various chemical, biological, and physical influences on these phenomena will require a better understanding and resolution of the causes and consequences of change on scales from hours to millennia. Understanding ocean ecosystems and their constituents will improve dramatically in response to emerging molecular, chemical, optical, and acoustical technologies. Given the relative paucity of information on deep-sea fauna in general, and especially the relatively recent discovery of chemosynthetic ecosystems at MOR hydrothermal vents, this will continue to be a focus for deep ocean biological research in the coming decade and beyond. Time-series and observatory-based research and sampling techniques will be required to answer the myriad of questions regarding the evolution and physiology of these unique biological systems (Figures 10 and 11). Present and future foci for deep submergence science is MOR crests, hydrothermal systems, and the volcano–tectonic processes that create the architecture of the Earth’s crust. Geochemists from the marine geology and geophysics community have emphasized the need for studies of: (1) the flux-frequency distribution for ridge-crest hydrothermal activity (heat, fluid, chemistry); (2) the role played by fluid flow in gas hydrate accumulation and determination of how important hydrates are to climate change; (3) slope
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DEEP SUBMERGENCE, SCIENCE OF
Soft tether and Multiconductor cable 0.68″ Control vehicle
Tow cable
300 m
Probe
Acoustic transponder
Cone
(B) Figure 8b (Continued)
stability; and (4) determination of how much of a role the microbial community plays in subsurface chemical and physical transformations. Another focus involves subduction zone processes, including: an assessment of the fluxes of fluids and solids through the seismogenic zone; long-term monitoring of changes in seismicity, strain, and fluid flux in the seismogenic zone; and determining the nature of materials in the seismogenic zone. To answer these types of questions, the marine geology and geophysics community requires systematic studies of temporal evolution of diverse areas
on the ocean floor through research that includes mapping, dating, sampling, geophysical investigations, and drilling arrays of crustal holes (Figures 8, 9 and 11). The researchers in this field stress that the creation of true seafloor observatories at sites with different tectonic variables, with continuous monitoring of geological, hydrothermal, chemical, and biological activity will be necessary. Whereas traditional geological and geophysical tools will continue to provide some means to address aspects of these problems, it is clear that an array of deep submergence vehicles, in situ sensors, and ocean floor
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DEEP SUBMERGENCE, SCIENCE OF
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Figure 9 (A) Diagram of the upper portion of an Ocean Drilling Program (ODP) borehole with a Circulation Obviation Retrofit Kit (CORK) assembly. These units serve the same purpose as a ‘cork’ which seals a bottle; in the deep-sea case, the bottle is the sea floor which contains fluids that are circulating in the ocean crust. The CORK allows scientists to access the circulating fluids and make controlled hydrologic measurements of the pressures and physical properties of the fluids. (B) A CORK observatory on the ocean floor in ODP hole 858G off the Pacific north-west coast. (C) A CORK with instruments installed to measure sub-seafloor fluid circulation processes. Diagram courtesy of Woods Hole Oceanographic Institution and J. Doucette; photo courtesy of K. Becker and E. Davis.
observatory systems will be required to address these topics and unravel the variations in the processes that occur over short (seconds/minutes) to decadal timescales. The infrastructural requirements, facility, and
development needs required to support the research questions to be asked include: a capability for longterm seafloor monitoring; effective detection and response capability for a variety of seafloor events
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DEEP SUBMERGENCE, SCIENCE OF
(A)
(B)
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(D) (G)
(E) Figure 10 Time-series sequence of photographs taken of the same area of seafloor from the submersible Alvin of a hydrothermal vent site on the East Pacific Rise axis near 9149.80 N at a depth of 2500 m. (A) ‘Snow blower’ vent spewing white bacterial by-product during the 1991 eruption. (B) Same field of view as (A) about 9 months later. Diffuse venting is still occurring as is bacterial production. White areas in the crevices
of the lava flow are juvenile tube worms. (C) Patches of Riftia tube worms colonizing the vent area B18 months after the March 1991 eruption. (D) Tube worm community has continued to develop, and the venting continues over 5 years after the eruption. (E) Close-up photograph of zoarcid vent fish (middleleft), tube worms, mussels (yellowish oblong individuals) and bathyurid crab (center). (F) A time-series temperature probe (with black and yellow tape), deployed at a hydrothermal vent (Tube worm pillar) on the East Pacific Rise crest near 9149.60 N at a depth of 2495 m. The vent is surrounded by a large community of tube worms. (G) Seafloor markers along the Bio-Geo Transect, a series of 210 markers placed on the seafloor in 1992 to monitor the changes in hydrothermal vent biology and seafloor geology over a 1.4 km long section of the East Pacific Rise axis that have occurred after the 1991 volcanic eruption at this site. Photographs courtesy of T. Shank, Woods Hole Oceanographic Institution and R. Lutz, Rutgers University, D. J. Fornari and Woods Hole Oceanographic Institution – Alvin Group.
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DEEP SUBMERGENCE, SCIENCE OF
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(A) Figure 11 (A) Diagram of the deployment of the Hawaii-2 Observatory (H2O) one of the first long-term, deep seafloor observatories deployed in the past few years. Scientists used the ROV Jason to splice an abandoned submarine telephone cable into a termination frame which acts as an undersea telephone jack. Attached by an umbilical is a junction box, which serves as an electrical outlet for up to six scientific instruments. An ocean bottom seismometer and hydrophone are now functioning at this observatory. (B) The H2O junction box as deployed on the seafloor and photographed by ROV Jason. Drawing courtesy of Jayne Doucette, Woods Hole Oceanographic Institution (WHOI), A. Chave, and WHOI–ROV group.
(volcanic, seismic, chemical); adequately supported, state-of-the-art seafloor sampling and observational facilities (e.g. submersible, ROVs, and AUVs), and accurate navigation systems, software, and support for shipboard integration of data from mutiscalar and nested surveys (Figures 7B, 11 and 12). As discussed above, the disciplines involved in deep-submergence science are varied and the scales of investigation range many orders of magnitude from molecules and micrometer-sized bacteria to segment-scales of the MOR system (10s to 100s of kilometers long) at depths that range from 1500 m to
6000 m and greater in the deepest trenches. Clearly, the spectrum of scientific problems and environments where they must be investigated require access to the deep ocean floor with a range of safe, reliable, multifaceted, high-resolution vehicles, sensors, and samplers, operated from support ships that have global reach and good station-keeping capabilities in rough weather. Providing the right complement of deep-submergence vehicles and versatile support ships from which they can operate, and the funding to operate those facilities cost-effectively, is both a requirement and a challenge for satisfying the
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DEEP SUBMERGENCE, SCIENCE OF
(B) Figure 11 (Continued).
objectives of deep-sea research in the coming decade and into the twenty-first century. To meet present and future research and engineering objectives, particularly with a multidisciplinary approach, deep submergence science will require a mix of vehicle systems and infrastructures. As deep submergence science investigations extend into previously unexplored portions of the global seafloor, it is critical that scientists have access to sufficient vehicles with the capability to sample, observe and make timeseries measurements in these environments. Submersibles, which provide the cognitive presence of humans and heavy payload capabilities will be critical to future observational, time-series and observatorybased research in the coming decades. Fiberopticbased ROVs and tethered systems, especially when used in closely timed, nested investigations offer unparalleled maneuverability, mapping and sampling capabilities with long bottom times and without the limitation of human/vehicle endurance. AUVs of various designs will provide unprecedented access to the global ocean, deep ocean and seafloor without dedicated support from a surface ship. AUVs represent vanguard technology that will revolutionize seafloor and oceanographic measurements and observations in the decades to come. Over approximately the past 5 years scientists at several universities and private laboratories have made enormous advances in the capabilities and fieldreadiness of AUV systems. One such system is the Autonomous Benthic Explorer (ABE) developed by engineers and scientists at the Woods Hole Oceanographic Institution (Figure 6). ABE can survey the seafloor completely autonomously and is especially well suited to working in rugged terrain such as is found on the MOR. ABE maps the seafloor and the water column near the bottom without any guidance
from human operators. It follows programmed track-lines precisely and follows the bottom at heights from 5 to 30 m, depending on the type of survey conducted. ABE’s unusual shape allows it to maintain control over a wide range of speeds. Although ABE spends most of its survey time driving forward at constant speed, ABE can slow down or even stop to avoid hitting the seafloor. In practice, ABE has surveyed areas in and around steep scarps and cliffs, and not only survived encounters with the extreme terrain, but also obtained good sensor data throughout the mission. Recently ABE has been used for several geological and geophysical research programs on the MOR in the north-east and south Pacific which have further proved its reliability as a seafloor survey vehicle, and pointed to its unique characteristics to collect detailed, near-bottom geological and geophysical data, and to ground-truth a wide range of seafloor terrains (Figure 12). These new perspectives on seafloor geology and insights into the geophysical properties of the ocean crust have greatly improved our ability to image the deep ocean and seafloor and have already fostered a paradigm shift in field techniques and measurements which will surely result in new perspectives for Earth and oceanographic processes in the coming decades.
Conclusions One of the most outstanding scientific revelations of the twentieth century is the realization that ocean processes and the creation of the Earth’s crust within the oceans may determine the livability of our planet in terms of climate, resources, and hazards. Our discoveries may even enable us to determine how life itself began on Earth and whether it exists on other worlds. The next step is toward discovering the linkages between various phenomena and processes in the oceans and in exploring the interdependencies of these through time. Marine scientists recognize that technological advances in oceanographic sensors and vehicle capabilities are escalating at a increasingly rapid pace, and have created enormous opportunities to achieve a scope of understanding unprecedented even a decade ago. This new knowledge will build on the discoveries in marine sciences over the last several decades, many of which have been made possible only through advances in vehicle and sensor technology. With the rapidly escalating advances in technology, marine scientists agree that the time is ripe to focus efforts on understanding the connections in terms of interdependency of phenomena at work in the world oceans and their variability through time.
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DEEP SUBMERGENCE, SCIENCE OF
_ _ 2 _ 2 46 4 24 5 0 40 0
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Figure 12 (A) Bathymetry map (contour interval 10 m) showing location of the 1993 CoAxial lava eruption (gray) on the Juan de Fuca Ridge off the coast of Washington, and ABE tracklines (each color is a separate dive). (B) Magnetic field map based on ABE tracklines showing strong magnetic field over new lava flow. (C) Computed lava flow thickness assuming an average lava magnetization of 60 A/m compared with (D) lava flow thickness determined from differential swath bathymetry. Figure courtesy of M. Tivey, Woods Hole Oceanographic Institution.
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See also Cephalopods. Deep-Sea Ridges, Microbiology. Hydrothermal Vent Fluids, Chemistry of. Manned Submersibles, Deep Water. Mid-Ocean Ridge Geochemistry and Petrology. Platforms: Autonomous Underwater Vehicles. Remotely Operated Vehicles (ROVs). Seamounts and Off-Ridge Volcanism.
Further Reading Becker K and Davis EE (2000) Plugging the seafloor with CORKs. Oceanus 42(1): 14--16. Chadwick WW, Embley RW, and Fox C (1995) Seabeam depth changes associated with recent lava flows, coaxial segment, Juan de Fuca Ridge: evidence for multiple eruptions between 1981–1993. Geophysical Research Letters 22: 167--170. Chave AD, Duennebier F, and Butler R (2000) Putting H2O in the ocean. Oceanus 42(1): 6--9. de Moustier C, Spiess FN, Jabson D, et al. (2000) Deep-sea borehole re-entry with fiber optic wire line technology. Proceedings 2000 of the International Symposium on Underwater Technology. pp. 23–26. Embley RW and Baker E (1999) Interdisciplinary group explores seafloor eruption with remotely operated vehicle. Eos Transactions of the American Geophysical Union 80(19): 213--219 222. Fornari DJ, Shank T, Von Damm KL, et al. (1998) Timeseries temperature measurements at high-temperature hydrothermal vents, East Pacific Rise 91490 –510 N: monitoring a crustal cracking event. Earth and Planetary Science Letters 160: 419--431.
Haymon RH, Fornari DJ, Von Damm KL, et al. (1993) Direct submersible observation of a volcanic eruption on the Mid-Ocean Ridge: 1991 eruption of the East Pacific Rise crest at 91450 –520 N. Earth and Planetary Science Letters 119: 85--101. Humphris SE, Zierenberg RA, Mullineaux L, and Thomson R (1995) Seafloor Hydrothermal systems: Physical, Chemical, Biological, and Geological Interactions. American Geophysical Union Monograph, vol. 91, 466 pp. Ryan WBF (chair) et al., (Committee on seafloor observatories: challenges and opportunities) (2000) Illuminating the Hidden Planet, the Future of Seafloor Observatory Science. Washington, DC: Ocean Studies Board, National Research Council, National Academy Press. Shank TM, Fornari DJ, Von Damm KL, et al. (1998) Temporal and spatial patterns of biological community development at nascent deep-sea hydrothermal vents along the East Pacific Rise, 9149.60 N–9150.40 N. Deep Sea Research, II 45: 465--515. Tivey MA, Johnson HP, Bradley A, and Yoerger D (1998) Thickness measurements of submarine lava flows determined from near-bottom magnetic field mapping by autonomous underwater vehicle. Geophysical Research Letters 25: 805--808. UNOLS (University National Laboratory System) (1994) The Global Abyss: An Assessment of Deep Submergence Science in the United States. Narragansett, RI: UNOLS Office, University of Rhode Island. Von Damm KL (2000) Chemistry of hydrothermal vent fluids from 9–101N, East Pacific Rise: ‘Time zero’ the immediate post-eruptive period. Journal of Geophysical Research 105: 11203--11222.
(c) 2011 Elsevier Inc. All Rights Reserved.
DEEP-SEA DRILLING METHODOLOGY K. Moran, University of Rhode Island, Narragansett, RI, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction The technology developed and used in past scientific drilling programs, the Deep Sea Drilling Project and the Ocean Drilling Program, has now been expanded in the current Integrated Ocean Drilling Program (IODP). These technologies include innovative drilling methods, sampling tools and procedures, in situ measurement tools, and seafloor observatories. This new IODP technology will be used to drill deeper into the seafloor than was possible in the previous scientific programs. The first drilling target of the IODP using the new technology is the seismogenic zone offshore Japan, a location deep in the Earth (7–14 km) where earthquakes are generated.
ship’s motion from the drill pipe; and a pump that flushes sea water through the drill pipe. Open hole methods are successfully used in all of the Earth’s oceans (Figure 2). Scientific ocean-drilling achievements include drilling in very deep water (6 km) and to 42 km below the seafloor (Table 1). Although there have been many achievements using these methods, there are also limitations. Although the exact depth limit of open-hole drilling method is not yet known, it is likely limited to 2–4 km below the seafloor. This limitation exists because the drill fluid must be modified to a lower density so that the deep cuttings can be lifted from the bit and flushed out of the hole when drilling deep into the seafloor. Another
Drilling Technology The Deep Sea Drilling Project and the Ocean Drilling Program used the same basic drilling technology, the open hole method. Today, the IODP has extended this capability to include closed hole methods, known as riser drilling. Open Hole or Nonriser Drilling
Drilling is the process of establishing a borehole. The open hole method uses a single drill pipe that hangs from the drill ship’s derrick, a tall framework positioned over the drill hole used to support the drill pipe. The drill pipe is rotated using drilling systems, specifically a hydraulically powered top drive located above the drill floor of the ship. Surface sea water is flushed through the center of the pipe to lubricate the rotating bit that cuts the rock and then flushes sediment and rock cuttings away to the seafloor (Figure 1). Open hole refers to the resulting borehole which remains open to the ocean during drilling. This method is also called a riserless drilling system. Important parts of the deep-water drilling system are a drilling derrick that is large and strong enough to hang a long length of drill pipe reaching deep ocean and subseafloor depths (up to 8 km); a system that rotates the drill pipe; a motion compensator that isolates the
Drill pipe
Drilling fluid is pumped down through drill pipe
Cuttings
Drilling fluid and cuttings flow into ocean
Seafloor Surface casing
Second casing
Uncased hole
Drilling fluid and cuttings flow up between the drill pipe and the borehole or casing
Drill bit
Figure 1 Diagram of a nonriser drilling system.
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(c) 2011 Elsevier Inc. All Rights Reserved.
Figure 2 Map of all sites drilled by the Deep Sea Drilling Project (DSDP), the Ocean Drilling Program (ODP), and the IODP.
DEEP-SEA DRILLING METHODOLOGY
Table 1
39
Fact sheet about the JOIDES Resolution, the research vessel used by the Ocean Drilling Program
Total number of days in port Total number of days at sea Total distance traveled Total number of holes drilled Deepest water level drilled Deepest hole drilled
Leg 129 Leg 148, Hole 504B (South-eastern Pacific Ocean, off coast of Ecuador)
Total amount of core Most core recovered on single Northern-most site drilled
Leg 175 – Benguela (15 Aug.–10 Oct. 1997) Leg 113, site 911
Southern-most site drilled
Leg 151, site 693
Year and place of constitution
1978
Laboratories and other scientific equipment installed Gross tonnage Net tonnage Engines/generators
1984
Length Beam Derrick Speed Crusing range Scientific and technical party Ship’s Crew Laboratory space Drill string
limitation of the open hole method is that drilling must be restricted to locations where hydrocarbons are unlikely to be encountered. In an open hole, there is no way to control the drilling fluid pressure. In locations where oil and gas may exist, the formations are frequently overpressured (similar to a champagne bottle). If these formations would be punctured with an open hole system, the drill pipe would act like a straw that connects this overpressured zone in the rock to the ocean and the ship. This type of puncture is called a ‘blow-out’ and is a serious drilling hazard. The explosion as gases are vented through the straw to the ship’s drill floor could cause serious damage, or worse yet, the change in the density of the seawater as the gas bubbles are released into the overlying ocean could cause the ship to sink. Without a system to control the pressure in the borehole, there is no way to prevent a blow-out. Closed Hole or Riser Drilling
The new deep-sea drilling technology used in IODP is a closed system, also known as riser drilling. This
445 days 4751 days 507 420 km 1445 holes 5980 m 2111 m
180 880 m 8003 m Latitude 80.47441 N Longitude 8.22731 E Latitude 70.83151 S Longitude 14.57351 W Halifax, Nova Scotia, Canada Pascagoula, Mississippi 9719 tons 2915 tons Seven 16 cyl index Diesel 5@2100 kW (2815 hp) 2@15500 kW (2010 hp) 143 m 21 m 62 m 11 knots 120 days 50 people 65 people 1115 m2 8838 m
technology has been used, in shallow to intermediate water depths, by the offshore oil industry to explore for, and produce oil and gas. Riser drilling uses two pipes: a drill pipe similar to that used for open hole drilling and a wider diameter riser pipe that surrounds the drill pipe and is cemented into the seafloor (Figure 3). The system is closed because drill fluid (seawater and additives) is pumped down the drillpipe (to lubricate the bit and flush rock cuttings away from the bit) and then returned to the ship via the riser. With riser drilling, the drill fluid density can be varied and borehole pressure can be monitored and controlled, thus overcoming the two limitations of open hole drilling. The single limitation of riser drilling is water depth. The current water depth limit of riser technology is approximately 3 km. This water depth limit occurs because the riser, filled with drill fluid and cuttings, puts a large amount of pressure on the rock. This pressure is greater than the strength of the rock; thus, the rock breaks apart under the riser pressure, causing the drilling system to fail.
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DEEP-SEA DRILLING METHODOLOGY
Cuttings returned to ship
Riser Drill pipe
Drilling fluid is pumped down through drill pipe
Drilling fluid and cuttings flow up between the drill pipe and the riser
Seafloor Surface casing
Second casing
Uncased hole
Drilling fluid and cuttings flow up between the drill pipe and the borehole or casing
Drill bit
Figure 3 Diagram of a riser drilling system.
Deep-Sea Sampling Scientific ocean drilling not only requires a borehole, but – more importantly – the recovery of highquality core samples taken as continuously as possible. Recovering sediment and rock samples from below the seafloor in deep water requires the use of wireline tools. Wireline tools are pumped down the center of the drill pipe to the bottom (called the bottom hole assembly) where they are mechanically latched into place near the drill bit in preparation for sampling. Different types of tools are advanced into the geological formation and take a core sample in different ways, depending on the type of sediment or rock. After the tool samples the rock formation, it is unlatched from the bottom hole assembly with a mechanical device, called an overshot, that is sent down the pipe on a wire. The overshot is used to
unlatch the wireline tool, return it to the ship, and recover the core sample. In scientific ocean drilling, three standard wireline core sampling tools are used: the advanced piston corer, the extended core barrel, and the rotary core barrel. The piston corer is advanced into the sediment ahead of the drill bit using pressure applied by shipboard pumps through the drill pipe (Figure 4(a)). The drill fluid pressure in the pipe is increased until the corer shoots into the sediment. After the corer is shot 10 m ahead of the bit, it is recovered using the wireline overshot. The drill pipe and bit are then advanced by rotary drilling another 10 m, in preparation for taking another core sample. The piston corer is designed to recover undisturbed core samples of soft ooze and sediments up to 250 m below the seafloor. In soft to hard sediments, the piston corer can achieve 100% recovery. However, because the cores are taken sequentially, sediment between consecutive cores may not be recovered. To ensure that a continuous sedimentary section is recovered, particularly for paleoclimate studies, the IODP drills a minimum of three boreholes at one site. The positions of the breaks between consecutive core samples are staggered in each borehole so that if sediment is not sampled in one borehole at a core break depth, it will be recovered in the second or third borehole. The extended core barrel is a modification of the oil industry’s rotary corer and is designed to recover core samples of sedimentary rock formation (Figure 4(b)). Typically, the extended core barrel is deployed at depths below the seafloor at which the sediment is too hard for sampling by the piston corer. The extended corer uses the rotation of the drill string to deepen the borehole and cut the core sample. The cutting action is done with a small bit attached to the core barrel. An innovation of this tool is an internal spring that allows the core barrel’s smaller bit to extend ahead of the drill bit in softer formations. In hard formations, where greater cutting action is needed, the spring is compressed and the small core bit rotates with the main drill bit. The rotary core barrel is a direct descendant of the rotary coring system used in the oil industry and is similar to the extended core barrel in its retracted mode. The rotary corer is designed to recover core samples from medium to very hard formations, including igneous rock. The corer uses the rotation of the drill string and the main drill bit to deepen the hole and cut the core sample (Figure 4(c)). In all drilling operations, there are times when the drill pipe must be recovered to the ship, for example, to change a worn bit or to install different bottom hole equipment. Before pulling the pipe out of the
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Figure 4 Diagrams of the Ocean Drilling Program’s coring tools: (a) advanced piston corer; (b) extended core barrel; and (c) rotary core barrel.
borehole, a re-entry cone (Figure 5) is dropped down the outside of the drill pipe where it free-falls to the seafloor. The cone is used as a guide to re-enter the borehole with a new bit or equipment. The cone is a very small target in deep water (1–6 km) and ancillary tools are needed to locate it for re-entry into the borehole. The cone is first located acoustically, using seafloor transponders. To precisely pinpoint the cone, a video camera is lowered with the drill pipe to visually pinpoint the location and drop the drill pipe back into the borehole. Special corers are used to sample unusual and difficult formations. For example, gas hydrates, ice-like material that is stable under high pressure and low temperature, commonly occur in deep water below the seafloor and require special samplers. Gas hydrates have generated much public interest since they can contain methane gas trapped within their structure, which is thought to be a potential future energy
source. However, when gas hydrate is sampled, it must be kept at in situ pressure conditions to maintain the integrity of the core. Thus, a pressure core sampler is used to sample hydrates. The sampler is similar to the extended corer in that it has its own bit, but it has an internal valve that closes before the sampler is removed from the formation. The closed valve maintains the sample at in situ pressure conditions.
Drilling Measurements Once sampling is completed, logging tools are lowered into the borehole to measure the in situ geophysical and chemical properties of the formation. In IODP, logging tools, developed for use in the oil industry, are most commonly leased from Schlumberger. The origins of logging go back to 1911 when the science of geophysics was new and was just beginning to be used
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Drill pipe connection Removable line wiper Derrick
Side-entry port for logging tools and wireline Float valve
Moon pool 23′ 4–3/8′′ O.A.L.
Thrusters
Logging tool Drill pipe
5.7 mi
Drill pipe connection Figure 6 Diagram of the side-entry sub technology.
Re-entry cone
Acoustic beacon
Sediment
Hard rock Not to scale
Figure 5 Diagram of the ship, drill pipe, and re-entry cone used in the drilling process.
to explore the internal structure of the Earth. Conrad and Marcel Schlumberger, the founders of Schlumberger, conceived the idea that electrical measurements could be used to detect ore (precious minerals). Working at first alone and then with a number of
associates, they extended the electrical prospecting technique from the surface to the oil well. Now, the use of electric prospecting, called logging, is widely accepted as a standard method in oil exploration. Logging tools are lowered into the borehole using a cable that also transmits the data, in real time, to the ship. The term logging refers to the type of data collected. For example, a borehole log is a record or ledger of the sediment and rock encountered while drilling. Logs are geophysical and chemical records of the borehole. The logging tools typically comprise transmitters and sensors or a sensor alone encased in a robust stainless steel tube. Examples of tool measurements include electrical resistivity, gamma ray attenuation, natural gamma, acoustic velocity, and magnetic susceptibility. Log data provide an almost continuous record of the sediment and rock formation along length of the borehole. Log data are of high quality when collected in the open hole, outside of the drill pipe. The most common method for deploying logging tools is to deploy a device that releases the drill bit from the drill pipe once all drilling and sampling operations are completed. The drill bit falls to the bottom of the borehole and is left there. The drill pipe is retracted and only 75–100 m of pipe is left at the top of the borehole to keep the upper, loose part of the borehole stable. Logging tools are lowered through the drill pipe to the bottom of the borehole. Log data are acquired by slowly raising the tool up the borehole at
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a constant speed. When boreholes are unstable and the walls are collapsing into the open hole, another method is used, unique to scientific ocean drilling. In unstable conditions, the drill pipe cannot be retracted to within 75 m of the seafloor without borehole walls collapsing and blocking or bridging the hole. In these situations, after the bit is released, the logging tools are lowered inside the drill pipe to the bottom of the hole. The drill pipe is retracted only enough to expose the logging tools to the open hole, while protecting the remainder of the borehole walls. Then, drill pipe is retracted at the same speed as logging tools are pulled up through the borehole. The technology developed that allows for this unique operation is called the side-entry sub (Figure 6). When inserted as a part of the drill string, the cable, to which the tools are attached, exits the drill pipe at
the side-entry sub, positioned well below the ship. In the way, the logging cable does not interfere with removal of drill pipe. Data in the borehole are also collected using wireline-deployed tools. Sediment temperature is measured with a temperature sensor mounted inside the cutting edge of the piston corer. In addition, other tools are deployed that do not recover a sample. They are pushed into the sediment ahead of the drill bit, left in place for 10–15 min to record temperature, and then pulled back to the ship, where the data are downloaded and analyzed. Special wireline tools have also been used to measure pressure and fluid flow properties of sediment and rock. IODP also uses an oil industry-developed method for logging sediment and igneous rocks – loggingwhile-drilling or LWD. In this method, some of the
Data logger
Re-entry cone
Hydraulic feed through Packer Thermistor string Zone I
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Zone II
Optional osmosampler Sinker bar Optional bridge plug screen
Figure 7 Diagram of the advanced CORK system used to seal instruments in the borehole.
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same wireline logging sensors are repackaged and attached to the drill string, immediately behind the drill bit. The sensors log the geophysical properties of the sediment and rock as drilling proceeds, thus eliminating problems associated with borehole collapse.
Deep Seafloor Observatories The circulation obviation retrofit kit (CORK) is a seafloor observatory that measures pressure, temperature, and fluid composition – important parameters for the study of the dynamics of deep-sea hydrologic systems. CORKs are installed by the IODP for measurements over long periods of time (months to years). Since 1991, observatories have been installed on the deep seafloor in different settings, for example, at mid-ocean ridge hydrothermal systems and at active margins. The CORKs are installed by the drill ship. After a borehole is drilled, a CORK is installed to seal instruments in the borehole away from the overlying ocean (Figure 7). The CORK has two major parts: the CORK body that provides the seal and an instrument cable, for measuring fluid pressures, and temperatures that hangs from the CORK into the borehole. A data recorder is included with the instrument cable. The data recorders have sufficient battery power and memory for up to 5 years of operation. Data are recovered from CORKs using manned submersibles or remotely operated vehicles. The instruments in the CORK measure pressure and temperature spaced along a cable that extends into the sealed borehole. The CORK also includes a valve above the seal where borehole fluids can be sampled. Advanced CORKs are also used to isolate specific and measure the properties of different sediment or rock zones. The IODP installs another type of long-term seafloor observatory for earthquake studies. Seismic monitoring instruments are installed in deep boreholes located in seismically active regions, for example, off the coast of Japan. These data are used to help established predictive measures to prevent loss of life and damage to cities during large earthquakes. Deep-sea seismic observatories contain a strainmeter, two seismometers, a tilmeter, and a temperature sensor. The observatories have replaceable data-recording devices and batteries like CORKs, and are serviced by remotely operated vehicles. Eventually, real-time power supply and data retrieval will be possible when some of the observatories are connected to nearby deep-sea fiber-optic cables.
Summary Deep-sea scientific drilling applies innovative sampling, instrument, and observatory technologies to the study of Earth system science. These range from the study of Earth’s past ocean and climate conditions using high-quality sediment cores, to the study of earthquakes and tectonic processes using logging tools and seafloor observatories, to exploring gas hydrates (a potential future energy source) using specialized sampling tools. In 2004, the IODP succeeded two earlier scientific programs, Deep Sea Drilling and Ocean Drilling. The IODP operates two ships: the D/V JOIDES Resolution and the D/V Chikyu and leases ships for special operations in shallow water and ice-covered seas. The IODP is supported by the US, Japan, and Europe.
See also Deep Submergence, Science of. Deep-Sea Drilling Results. Manned Submersibles, Deep Water. Remotely Operated Vehicles (ROVs).
Further Reading DSDP (1969–86) Initial Reports of the Deep Sea Drilling Project. Washington, DC: US Government Printing Office. http://www.deepseadrilling.org/i_reports.htm (accessed Mar. 2008). Integrated Ocean Drilling Program (2001) Earth, Oceans and Life: Scientific Investigation of the Earth System Using Multiple Drilling Platforms and New Technologies, Integrated Ocean Drilling Program, Initial Science Plan, 2003–2013. Joint Oceanographic Institutions (1996) Understanding Our Dynamic Earth: Ocean Drilling Program Long Range Plan. Washington, DC: Joint Oceanographic Institutions. Oceanography Society (2006) Special Issue: The Impact of the Ocean Drilling Program. Oceanography 19(4). ODP (1985–present) Proceedings of the Ocean Drilling Program, Initial Reports, vols. 101–210. College Station, TX: ODP. http://www-odp.tamu.edu/publications (accessed Mar. 2008). ODP (1985–present) Proceedings of the Ocean Drilling Program, Scientific Results, vols. 101–210. College Station, TX: ODP. http://www-odp.tamu.edu/publications (accessed Mar. 2008). ODP (2004–present) Proceedings of the Integrated Ocean Drilling Program, vols. 300–. College Station, TX: Integrated Ocean Drilling Program. WHOI (1993–94) Oceanus: 25 Years of Ocean Drilling, vol. 36, no. 4. Woods Hole, MA: Woods Hole Oceanographic Institution.
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DEEP-SEA DRILLING RESULTS J. G. Baldauf, Texas A&M University, College Station, TX, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 666–676, & 2001, Elsevier Ltd.
Introduction Modern scientific ocean drilling commenced over forty years ago with the inception of Project Mohole. This project was named for its goal of coring a 5– 6 km borehole through thin oceanic crust, continuing through the Mohorovicic Discontinuity and into the earth’s mantle. Project Mohole was active from 1957 through 1966. Although it did not achieve its objective, the Project demonstrated the means for coring in the oceans for scientific purposes and in doing so planted the seed for future decades of scientific ocean drilling.
The current era of scientific coring commenced with the creation of the Joint Oceanographic Institutions for Deep Earth Sampling (JOIDES) in 1964. In 1965, JOIDES completed its first scientific drilling program on the Blake Plateau using the drilling vessel Caldrill. This initial experiment led to the development of the Deep Sea Drilling Project (DSDP) managed by Scripps Institution of Oceanography, California. The scientific objective of DSDP was expanded, compared to that of Project Mohole, and included the recovery of sediments and rocks from throughout the World Ocean to improve the understanding of the natural processes active on this planet. Central to DSDP was the scientific research vessel Glomar Challenger (Figure 1) operated by Global Marine Inc. During the 15 years (1968–1983) of operations, DSDP advanced the scientific frontier by completing 96 scientific expeditions throughout the World Ocean (Figure 2). These expeditions contributed to
Figure 1 Scientific Research Vessel Glomar Challenger operated by Global Marine Inc. for the Deep Sea Drilling Project from 1968 to 1983.
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advancement of the earth sciences. For example, DSDP confirmed Alfred Wegner’s theory of continental drift, and provided fundamental evidence in support of plate tectonics, established the timing of northern and southern hemisphere glaciations, documented the desiccation of the Mediterranean Sea, documented the northward migration of India and its collision with Asia, determined the history of the major oceanic gateways and their impact on ocean circulation, and improved the understanding of oceanic crust formation and subduction processes. The overwhelming success of DSDP and the numerous scientific questions still remaining provided the framework for the current scientific drilling program, the Ocean Drilling Program (ODP). This new program, established in 1984, continues to explore the history of the earth as recorded in the rocks and sediments beneath the World Ocean. The centerpiece of ODP is the scientific research vessel
JOIDES Resolution (Figure 3) operated by Transocean SedcoForex for Texas AM University. To date 92 scientific expeditions have been completed by ODP (Figure 4).
Science Initiatives The earth system is complex and dynamic with numerous variables and a multitude of forcing and response mechanisms. The sediments preserved beneath the World Ocean record the tempo and variation of the climate system at annual to millennial scales. Likewise, oceanic crust records the environment at the time of its formation. The understanding of these variables and the naturally occurring process active in the Earth’s environment and in the Earth’s interior continue to evolve based on results from scientific ocean drilling. The
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DSDP Legs 1_ 96, Sites 1_ 624 Figure 2 Geographic location of the sites occupied during scientific expeditions of the Deep Sea Drilling Project from 1968 to 1983.
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Figure 3 Scientific Research Vessel JOIDES Resolution operated by Transocean SedcoForex for the Ocean Drilling Program 1984 to present.
partitioning of the Earth’s processes into these two themes is in part arbitrary as the external environment is closely linked to that of the Earth’s interior.
Dynamics of the Earth’s Environment The Earth’s climate system consists of processes active in and between five regimes, space, atmosphere, ocean, cryosphere, and crust (Figure 5). For example, variation in incoming solar radiation influences the atmosphere-ocean coupling through changes in precipitation, evaporation and heat exchange. In addition, ice-sheets (and in turn sea level), sea ice, albedo, and terrestrial and oceanic biomass also respond to solar radiation changes. Similarly, variations in the dimensions and shape of the ocean basins, through crust formation on destruction or the opening or closing of oceanic gateways, influence oceanic circulation, as well as the
salinity and temperature of specific water masses. These changes subsequently impact the distribution of nutrients, regional climates, and the Earth’s biomass. The complexity of the climate system is only now beginning to be realized, in part through the ground truthing of climatic models and the historical perspective at various (annual to millennial) scales provide through ocean drilling. ODP’s contributions to understanding the Earth’s environment are extensive. For example, coring off northern Florida provided evidence to support the Cretaceous/Tertiary Boundary meteorite impact theory and its causal impact on widespread extinction of the Earth’s biota. Numerous other cruises have provided insight as to the complexity of the climate system, investigating scientific themes such as the desertification of Africa, implications on climate of the uplift of Tibet plateau, refinement of the glacial history of both hemispheres, including the climate periodicity in icehouse and
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Figure 4 Geographic locations of the 91 scientific expeditions currently completed by ODP from 1984 to the present. Legs indicated in black were completed in 1990 and 1991.
SPACE
Space dust
Aerosol atmosphere _ land coupling
CLOUDS
ATMOSPHERE
Precipitation Heat exchange
e.g., CO2 BIOMASS
Changes in solar radiation Terrestrial radiation Evaporation
Wind stress
ODP SEA-ICE
LAND
Changes of atmospheric composition
Atmosphere _ ocean coupling Changes of land features, orography vegetation, albedo, etc.
Atmosphere _ ice coupling
OCEAN
Ice-ocean coupling Sedimentary record is an integrated signal
ICE SHEETS Changes of ocean basin, shape, salinity, temperature, etc.
EARTH
Figure 5 Schematic representation of the major components of the earth’s climatic system. (Adapted from Crowley and North (1992) and the ODP long-range plan (1996).)
greenhouse worlds, and understanding of the history of sea level. In addition, ODP continues to investigate the extent of the biosphere based on evidence of organisms
deep within Earth’s crust. The discovery of organisms in volcanic crust is significant as it extends the depth of the biosphere and indicates that life is possible in extreme environments.
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Three scientific themes associated with the dynamics of the Earth’s environment continue to be explored by ODP. These themes include understanding the Earth’s changing climate, the causes and effects of sea level change, and fluids and bacteria as agents of change. Dynamics of the Earth’s Interior
The global cycling of mass and energy in the Earth’s interior and the extrusion of this material into the Earth’s exterior environment impacts global geochemical budgets (Figure 6). For example, the formation of oceanic crust at the mid-ocean spreading centers plays an important role in mantle dynamics, geochemical fluxes, and heat exchange within and between the Earth’s internal and external environments. Similarly, the subduction of a lithospheric plate at a convergent margin results in the melting of the plate, which in turn contributes to the composition and circulation dynamics of the mantle. Associated with subduction zones are volcanic systems through which magma and gases are extruded to Earth’s exterior, contributing to the chemical fluxes of the oceans and atmosphere. Understanding of the processes associated with crustal formation and plate subduction has been enhanced through the recovery of crustal rocks from beneath the oceans. For example, ODP has improved the understanding of the chemical flux by coring within subduction zones to understand the processes
VOLCANIC ARC
associated with subduction, including chemical and mass balances and fluid flow associated with the interface between the two plates, referred to the Decollement zone. Coring of large igneous provinces (LIPs) such as the Kerguelen Plateau and the Ontong Java Plateau has also provided insight into the mantle dynamics and chemical fluxes. These LIPs formed from the injection of magma through volcanic hotspots. Obtaining crustal samples from these regions enhances the understanding of chemical composition and fluxes, mantle dynamics, and the impact of the formation of these features on oceanic and atmospheric chemistry. ODP has also recovered over 500 m of gabbro from a single hole on the South-west Indian Ridge. This sequence represents the most continuous stratigraphic sequence of lower crust from oceanic basement, allowing insight into the chemical composition and structure of oceanic crust. Two other areas of interest for ODP have been the processes associated with the formation of ore bodies and the formation of gas hydrates – frozen methane crystallized with water. Of particular interest is the origin and history of such deposits and their potential influence on global chemical fluxes. Two scientific themes remain central to ODP investigations: exploring the transfer of heat and material to and from earth’s interior and investigating deformation of the lithosphere and earthquake processes.
OCEANIC SEDIMENTS
Formation of ore bodies
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IGNEOUS OCEAN CRUST
MID-OCEAN SPREADING CENTER Sulfide deposit formed at spreading center
Fate of sediment Assimilation Metasomatism
COLD LITHOSPHERIC PLATE
Melting Melting or dewatering
Metamorphism, dewatering of oceanic crust
Intraplate volcanism
MAGMA Partial melting
High temperature hydrothermal circulation
Fate of subducted ore bodies Metal addition Fate of subducted plate
Figure 6 Schematic representation of the major components of the earth’s tectonic cycle. (Adapted from the ODP long-range plan 1996.)
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Technological Advances Scientific advances made through ocean drilling are closely linked to advances in technology. New tools such as the development of seafloor observatories, enhanced coring and logging prototypes, seafloor equipment, and state-of-the-art laboratory equipment have provided new opportunities to advance the scientific frontier.
Seafloor Observatories
A reentry cone seal, also referred to as CORK, has been developed and used to seal an ODP hole, thus preventing flow into or out of the borehole. The CORK provides a means for monitoring borehole temperature and pressure as well as recovery of borehole fluid samples. A typical CORK configuration (Figure 7A and B) is characterized by the thermistor string used for the collection of pressure and temperature data, a borehole fluid sampler for collection of borehole fluids, and a data logger for the recording and storage of data from the thermistor string until it can be downloaded via a submersible. The next-generation borehole seals, known as the ACORK, are currently being developed. The ACORK will allow subdivision of the borehole into
isolated segments, allowing monitoring of fluid flow for given horizons or intervals. Coring and Logging Tools
Advanced piston corer (APC) This is a hydraulically actuated piston corer designed to recover undistributed core samples from soft sediments with enhanced core quality and core recovery. Initially developed during the latter phases of DSDP and enhanced during ODP, the APC has become the mainstay for the recovery of highresolution sedimentary records for paleoceanographic and climate studies. Pressure core sampler (PCS) The PCS was developed for the retrieval of core samples from the ocean floor while maintaining near in situ pressures up to 10 000 psi (69 MPa). This tool continues to be critical for investigating gas-bearing sediments, such as gas hydrates, for the analysis of biogeochemical cycling. Formation microscanner (FMS) Adapted from industry, this logging tool provides an oriented, two-dimensional, high-resolution image of the variations in microresistivity around the borehole
Data logger download access Data logger Data logger latch Borehole fluid sampling window
Submersible/ROV platform Reentry cone Seafloor
11¾" casing hanger Cork seals 16" casing hanger 11¾" casing Thermistor string Open borehole (A)
(B)
Figure 7 (A) Schematic of a reentry cone seal, also referred to as a CORK. The tool provides a means for monitoring borehole temperature and pressure as well as recovery of borehole fluid samples. (B) Underwater view of the CORK landed in a reentry cone.
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wall. Collected data allow the correlation of coring and logging depth, orientation of cores and location of the cored sections when recovery is less than 100%, mapping of sedimentary structures, and interpretation of depositional environments.
Seafloor Equipment Seafloor equipment such as a reentry cone and the hard rock guide base have been developed and implemented to achieve scientific objectives at specific sites. The reentry cone is a permanent seafloor installation, which serves as a conduit for reentry of the borehole and a platform for supporting various casing strings. Often the drill pipe is pulled from the hole to replace coring bits or to change coring tools. A temporary reentry cone referred to as a ‘free fall funnel’ is also used to allow bit changes. The hard rock guide base (HRGB) was developed to focus the direction of the drill bit into hard, irregular seafloor surfaces that are otherwise undrillable. The difficulty in drilling is both the inability to spud or start a hole as insufficient weight could be applied to the bit and the tendency of the bit to ‘walk’ downhill when trying to start a hole on a sloping surface. The HRGB, when placed on the seafloor, provides support for the drill string to start a hole. Recent technological development of the Hard Rock Reentry System (HRRS) allows a cased reentry hole to be established in bare hard rock without the use of the HRGB.
Laboratory Equipment Mutisensor track (MST)
The MST allows measurements of cores at centimeter scales for examination of changes in physical parameters resulting from changes in lithology, composition, porosity, density, and magnetic susceptibility of the sediment collected. Changes in these properties result from changing oceanographic Table 1 183)
conditions at the time of deposition or from postdeposition processes. The high-resolution records obtained with the MST also allow correlation of data sets from offset holes to ensure completeness of the geological record. In addition, the high-resolution data collected (100–1000 y) can be correlated to data collected through the logging of the borehole to allow direct correlation of laboratory measurements with those from the borehole.
Facilities The scientific research vessel JOIDES Resolution is a dynamically positioned drilling vessel capable of maintaining position over specific locations while coring in water depths down to 8200 m. The vessel was built in Halifax, Nova Scotia, Canada in 1978 and has a length of 143 m, a breadth of 21 m, a gross tonnage of 7539, and a derrick that towers 61.5 m above the water line. A computer-controlled automated dynamic positioning system regulates 12 thrusters in addition to the main propulsion system to maintain the position of the vessel directly over the drill site. JOIDES Resolution was originally operated as an oil exploration vessel. In 1984, ODP converted the vessel into a scientific research vessel by removing the shipboard riser system and adding scientific laboratories. Operating statistics of the JOIDES Resolution are shown in Table 1. Unique to this vessel is the 7-story laboratory structure housing state-of-the-art scientific equipment for use in the studies of geochemistry, microbiology, paleomagnetism, paleontology, petrology, physical properties, sedimentology, downhole measurements, and marine geophysics. This structure also includes support facilities for electronic repair, computers, photography, database management, communications, and conference facilities. Cores and data collected during each scientific cruise are stored at shore-based facilities for future research by members of the international scientific community. ODP maintains four core repositories,
Significant operational highlights of the JOIDES Resolution from 1985 to 1999 (Leg 100–
Deepest hole penetrated Shallowest operational water depth Deepest operational water depth Most core recovered during a single expedition Total number of sites visited Total number of holes cored Total core cored Total core recovered
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2111 m below the seafloor – Holes 504B completed during Leg 148, eastern Pacific. 37.5 m – Leg 143, north-west Pacific. 5980 m – Leg 129, western Pacific. 8003 m – Leg 175, south-east Atlantic. 535 – ODP Legs 100–183. 1417 – ODP Legs 100–183. 251 017 m – ODP Leg 100 through Leg 183. 170 770 m – ODP Leg 100 through Leg 183.
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three in North America and one in Europe. The North American repositories include the East Coast Repository (ECR) at Lamont Doherty Earth Observatory (LDEO), which stores cores from the Atlantic Ocean through Leg 150; the Gulf Coast Repository (GCR) at Texas A&M University (TAMU), Texas, which houses cores from the Pacific and Indian Oceans, and the West Coast Repository (WCR) at Scripps Institution of Oceanography, California, which houses cores from the Pacific and Indian Ocean collected during the Deep Sea Drilling Project. The Bremen Core Repository at the University Bremen, Germany, houses cores obtained from the Atlantic since Leg 151. Data collected during each cruise are stored in one of two locations. Downhole measurement (logging) and site survey data are housed at LDEO. All other data collected during a cruise are housed at TAMU.
Scientific Expeditions Using the JOIDES Resolution, ODP recovers sediments or rocks from beneath the World Ocean. Typically two types of coring tools, the Rotary Core Barrel (RCB) and the Advanced Piston Corer (APC), are used to cut the oceanic sediments and rocks. The RCB, typical of the petroleum industry, is used for penetration of hard rocks or sediment, while the APC is used in the less-indurated, softer sediment. The APC tool is typically used to recover the upper several hundred meters of the sediment sequence, with the subsequent sequence cored using the RCB. Once collected, the cores are returned to the ship via a wireline. Once on board the 9.5 m cores are sectioned into 1.5 m lengths for ease of handling within the shipboard laboratories. Following coring operations, the borehole is often logged using standard industrial tools. Logging provides data on the variation in the physical and chemical properties of the sediments and rocks directly from the walls of the borehole. Seafloor laboratories may also be established by instrumenting a borehole with thermistors, water samplers, or seismometers for long term, multiyear monitoring. Each cruise addresses a specific scientific theme based on a rigorous review of proposals submitted by members of the international science community. The duration of a leg depends on the specific objective. Generally each leg is two months in duration. The ship crew consists of about 106 individuals of whom 51 are members of the scientific party. The remaining contingent supports ship and coring operations. The scientific party consists of international
scientists from participating member countries and a technical support staff from TAMU.
International Partnership Eight international members representing 22 countries currently provide funding for the Ocean Drilling Program. The budget for the program is about US$46 million annually with the US National Science Foundation contributing about 66% of the required funds. The remaining funds are provided by five additional full members, each contributing about US$3 million annually, and two associate members each contributing between US$0.5 and 2 million annually. Full members of the program are the Australia/ Canada/Korea/Chinese Taipei Consortium for Ocean Drilling, the European Science Foundation Consortium for Ocean Drilling (Belgium, Denmark, Finland, Iceland, Ireland, Italy, Norway, Portugal, Spain, Sweden, Switzerland, and The Netherlands), Germany, Japan, the United Kingdom, and the United States. Associate members include France and the People’s Republic of China.
Management Structure The ODP management team consists of the Prime Contractor, Joint Oceanographic Institution (JOI), the Science Operator at Texas A&M University, and the Wireline Operator at Lamont Doherty Earth Observatory (Figure 8). As the prime contractor from the National Science Foundation, JOI is responsible for overall management of the program, including scientific planning, operations, and
International funding sources
National Science Foundation ODP Prime Contractor JOI
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Science Advisory Structure _ JOIDES
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Figure 8 ODP management structure including the National Science Foundation, Joint Oceanographic Institutes (JOI), Texas A&M University (TAMU) and Lamont Doherty Earth Observatory (LDEO). Science advice is provided to JOI through the Joint Oceanographic Institutes for Deep Earth Sampling (JOIDES) panels.
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DEEP-SEA DRILLING RESULTS
responding to recommendations from the science advisory structure. Texas A&M University is subcontracted through JOI to implement the scientific program developed by the science advisory structure. As Science Operator, TAMU is responsible for shipboard operations, including cruise staffing, maintenance and support of shipboard laboratories, data acquisition, engineering development, publication, core curation, and shipboard logistic (clearance, safety review, etc.) Lamont Doherty Earth Observatory is subcontracted through JOI to implement the wirelinelogging program for each scientific cruise. As Wireline Operator, LDEO is responsible for standard logging, specialized logging, and log analysis support services and database. LDEO is also responsible for the ODP Site Survey Data Bank at LDEO, which archives and distributes site survey data for ODP.
Advisory Structure The ODP advisory structure (Figure 9) provides advice on the scientific program and on logistical activity and program facilities. Scientific guidance is provided by two JOIDES advisory panels, one focused on the Earth’s environment and the second focused on Earth’s interior. The remaining advisory panels provide guidance for shipboard operations and logistics, such as shipboard laboratories, pollution prevention and safety, and site locations. Scientific Guidance
The success of ODP is in the bottom-up approach when it comes to determining the scientific programs JOI EXCOM SCICOM SSEP Environment
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Program Planning & Detailed Planning Groups Figure 9 JOIDES Advisory structure consisting of two science panels (SSEP) and four additional panels technology TEDCOM, Site Survey (SSP), pollution prevention and safety (PPSP) and shipboard measurements (SCIMP) providing guidance and advice to the SCICOM committee (SCICOM) and the Operations subcommittee (OPCOM). Recommendations of SCICOM are forwarded to the Executive committee (EXCOM) for endorsement and to JOI for implementation.
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most likely to advance the scientific frontier. Individuals or groups of scientists in the international community submit a proposal to answer specific scientific questions. Each proposal is reviewed by the Science Advisory Panels (SSPS) and recommendations are made to the Science Committee (SCICOM), which is responsible for ranking each proposal based on the overall contribution the proposed program would make to understanding Earth history. SCICOM forwards to the Operations Subcommittee (OPCOM), the highest-ranked proposals for scheduling consideration, taking into account available budget, weather constraints, and efficiency of scheduling when comparing days on site versus days in transit between sites. OPCOM sends back to SCICOM a proposed schedule, which is then ratified by SCICOM and forward to the Executive Committee (EXCOM) for approval. Upon approval, EXCOM forwards the schedule to JOI and subsequently to the TAMU and LDEO for implementation. Logistics/Infrastructure
In addition to science planning, the JOIDES Advisory structure provides recommendations on site locations, pollution prevention and safety, shipboard measurements and technological developments. The Site Survey Panel (SSP) is responsible for reviewing all site location data and forwarding recommendations to OPCOM concerning the state of readiness of proposals under consideration for implementation. Similarly, the Pollution Prevention and Safety panel reviews each proposal for safety concerns. This panel is focused on reducing risks associated with the potential occurrence of hydrocarbons to an acceptable level. Both SSP and PPSP make recommendations to OPCOM for consideration when considering proposals for scheduling. The Scientific Measurements Panel (SCIMP) provides advice and guidance on the shipboard laboratories, primarily pertaining to data acquisition, database storage, and data retrieval. In addition, this panel provides recommendations on publications and databases. The Technology Committee (TEDCOM) works closely with the Engineering development teams at TAMU and LDEO to provide guidance on technological developments.
Future Directions Like the Deep Sea Drilling Project before it, the present ODP has a defined duration, with the present program ending 30 September 2003. Although the
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program as currently configured will end, the need for continued scientific research through ocean drilling remains great. Recognizing this continued demand, the international partners are actively planning for a new program of scientific ocean drilling. The future program is envisioned to utilize multiple platforms, with both Japan and United States providing platforms for the Integrated Ocean Drilling Program (IODP). Japan will provide a new raiser vessel capable of completing deep (43 km) stratigraphic holes. The United States will provide a nonriser vessel to continue work similar to that currently completed by the JOIDES Resolution. In addition to these two platforms, additional alternate platforms will be included for operating in regions not accessible by the other two vessels, such as the Arctic Ocean, shallow water continental margins, and coral reefs, among others. It is envisioned that this new era of scientific ocean drilling will commence in late 2003.
See also Deep Submergence, Science of. Deep-Sea Drilling Methodology. Manned Submersibles, Deep Water. Remotely Operated Vehicles (ROVs).
Further Reading Bleil U and Thiede J (1988) Geological History of the Polar Oceans: Arctic versus Antarctic. NATO Series C, Mathematical and Physical Sciences, vol. 308. Dordrecht: Kluwer Academic.
Coffin MF and Eldholm O (1994) Large igneous provinces: crustal structure, dimensions, and external consequences. Reviews of Geophysics 32: 1--36. Cullen V (1993/94) 25 years of Ocean Drilling. Oceanus 36(4). Dickens GR, Paull CK, Wallace P and the Leg 164 Science party (1997) Direct measurement of in situ methane quantities in a large gas hydrate reservoir. Nature 385: 426–428 Lomask M (1976) Project Mohole and JOIDES, A Minor Miracle, An Informal History of the National Science Foundation, National Science Foundation. Washington, DC: pp. 167–197. Hsu KJ (1992) Challenger at Sea, a Ship that Revolutionized Earth Science. Princeton, NJ: Princeton University Press. Kastner M, Elderfield H, and Martin JB (1991) Fluids in convergent margins: what do we know about their composition, origin, role in diagenesis and importance of oceanic chemical fluxes? Philosophical Transactions of the Royal Society(London) 335: 275--288. Kennett JP and Ingram BL (1995) A 20,000 year record of ocean circulation and climate change from Santa Barbara basin. Nature 377: 510--513. Parkes RJ, Cragg SJ, Bale JM, et al. (1994) Deep bacterial biosphere in Pacific Ocean sediments. Nature 371: 410--413. Summerhayes CP, Prell WL, and Emeis KC (1992) Upwelling Systems: Evolution since the Early Miocene. Geological Society Special Publication, 64. London: Geological Society of London. Summerhayes CP and Shackleton NJ (1986) North Atlantic Paleoceanography. Geological Society Special Publication 21. London: Blackwell Scientific. Warme JE, Douglad RG, and Winterer EL (1981) The Deep Sea Drilling Project: a Decade of Progress, Special Publication 32. Tulsa, OK: Society of Economic Paleontologists and Mineralogists.
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DEEP-SEA FAUNA P. V. R. Snelgrove, Memorial University of Newfoundland, St John’s, NL, Canada J. F. Grassle, Rutgers University, New Brunswick, New Jersey, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 676–687, & 2001, Elsevier Ltd.
Overview The deep sea covers more of the Earth’s surface than any other habitat, but because of its remoteness and the difficulty in sampling such great depths, our sampling coverage and understanding of the environment have been limited. There has been a common misperception that the deep sea is species poor, and a commonly used ‘desert’ analogy is hardly surprising given that early sampling found few organisms, and the first deep-sea photographs revealed large plains of rolling hills covered in sediment with little obvious life (Figure 1). Indeed, all lines of evidence suggested that the deep sea is a very inhospitable environment. Temperatures are low (B41C), ambient pressure is extremely high (hundreds of times greater than on land), light is completely absent, and food is generally in very low abundance. But within the last few decades, quantitative samples have revealed what primitive sampling gear and photographs could not – that sediments in the deep sea are teeming with a rich diversity of tiny invertebrates only a few millimeters in size or smaller. These benthic (bottom-dwelling) organisms may reside just above the bottom but closely associated with it (hyperbenthos), on the sediment surface (epifauna), or among the sediment grains (infauna). The change in perception regarding the species richness of the deep sea has continued to evolve; we now know that, on the basis of the combination of species richness per unit area and total size, the deep sea is the most species-rich habitat in the oceans and among the richest on earth. A similar change in perception has occurred with two other generalizations about the deep sea. First, the deep sea is generally thought of as a food-limited environment, where biomass of individuals and communities as a whole are extremely low. Although this generalization usually holds, the surprising discovery of hydrothermal vent communities in the late 1970s, with meter-long tube worms and biomass that rivaled even the most productive shallow-water areas,
proved that clear exceptions exist. A second generalization is that the deep sea has been considered to be an extraordinarily stable habitat, where variables such as salinity, temperature, and food supply are constant, and light and photosynthesis are uniformly absent. Again, this generalization holds in some respects, in that temperature and salinity are often invariant and light is indeed absent. Studies in the last two decades, however, have indicated that smallscale patchiness is common, seasonal variation in phytoplankton production in surface waters can be directly reflected in the material that reaches deepsea sediments, and some deep-sea areas are very dynamic in terms of currents and sediment movement. The recent discoveries in the deep sea raise several interesting questions. First, how can a seemingly inhospitable and physically homogeneous habitat such as the deep sea support a rich diversity of organisms? Second, how can hydrothermal vents support such a high biomass of organisms relative to most deep-sea environments? We now have a firm understanding of the latter question and some definite ideas on the former.
Defining the Habitats Some deep-sea biologists define deep-sea habitats somewhat arbitrarily as those greater than 1000 m in depth. For this review, the deep sea is defined as all benthic habitats beyond the edge of the continental shelf, including the continental slope, continental rise, abyssal plains, ocean ridges (including hydrothermal vents), and deep-ocean trenches. Thus, ocean bottom from B200 to 10 000 m falls within this definition. Most of these regions share the features described above, including low temperature, dependence on organic production 1000s of meters above, high pressure and a sedimentary bottom, but each has unique characteristics as well (Figure 2). The continental slope, because it is adjacent to the continental shelf, generally receives a higher level of organic input than abyssal areas and, with its B31 slope, it is the steepest of the deep-sea environments other than trenches and seamounts and is subsequently subject to occasional sediment slides (called turbidity currents) that may move large volumes of sediment down the slope to the rise and abyssal plains. The continental slope is largely covered in sediments, which often derive from terrestrial and riverine runoff but may also come from marine
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Figure 1 Photograph of a typical deep-sea landscape. This photo is from 750 m near St Croix, US Virgin Islands. Infaunal burrows (B), a sea cucumber (C) and a sea whip (W) are visible.
biological production. The continental rise occurs at the base of the slope and can exhibit elevated organic matter relative to lower slope areas because material moving down the slope may accumulate at the rise. By far, the abyssal plains cover the largest portion of the deep sea (B40% of the Earth’s surface), but they also represent the most benign of the deep-sea habitats. Because they are removed from land influence and very deep (h4000 m), the amount of organic matter reaching the bottom is generally quite small, even in comparison with the slope and rise.
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The deepest ocean habitats are trenches, which form in subduction areas and are characterized by relatively steep sides, poor circulation, and occasional mud slumping. The poor circulation and slumping make trenches particularly inhospitable to most organisms. The sedimentary environment is vertically structured in terms of geochemistry and living organisms. Sediments have limited permeability and oxygen normally penetrates only a few millimeters by diffusion alone. Greater oxygen penetration occurs when bottom currents mix sediments or when organisms move pore water and sediments around (bioturbation). Sediments with active bioturbation are usually oxygenated within the top few centimeters, although strong bioturbation can lead to deeper pockets of penetration. Because light is absent from the deep sea, most productivity is provided by phytoplankton detritus and fecal pellets sinking from surface waters above, or closer to coastal habitats, from organic material transported seaward (e.g. kelps, seagrass etc.). Most of the available organic matter is concentrated near the sediment surface, although some species are capable of ‘caching’ food deeper in the sediment for later use. The combination of limited food and oxygen penetration at depth in sediments results in the vast majority of organisms being confined to the upper few centimeters of
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Figure 2 Schematic representation of the deep ocean environments and their sedimentary makeup. The horizontal axis has been greatly compressed, and the vertical axis is subsequently exaggerated. (Modified from Wright JE (ed.) (1977). Introduction to the Oceans. Milton Keynes, UK: The Open University.).
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sediment near the sediment–water interface. Smaller organisms that can tolerate anoxia and larger organisms that maintain a burrow or appendage to the surface can live deeper, but even then distributions are usually only a few centimeters deeper. Historically, the deep sea was perceived to be aseasonal because temperature is largely invariant at deep-sea depths, the absence of any light negates any day-length signal, and the habitat is so far removed from surface waters that it was thought that any signal from surface production would be completely dampened. Evidence in the last two decades has indicated that seasonality is a factor in many deep-sea environments. Samples from a number of different areas around the world and at a full range of depths have shown that the organic content of sediment does change seasonally. The strength of the seasonal signal, not surprisingly, varies with latitude and location; areas with very strong spring blooms are more likely to result in pulses of phytodetritus that sink to the seafloor than areas with weak production cycles. Where pulses are strong, the benthic fauna has been shown to respond quickly to organic input in terms of activity and biomass. Experimental patches of organic enrichment also generate a response by colonizing species. The deep-sea floor lacks the large-scale physical heterogeneity of habitats such as forests and coral reefs, but it is nonetheless far from uniform. Biologically generated features such as burrows and feeding mounds create small-scale heterogeneity that persists for longer periods of time than in shallow water because physical redistribution of sediments by waves does not occur in the deep sea. As organic matter such as phytodetritus sinks to the seafloor and is carried horizontally by currents, small-scale bottom topography creates spatial variation in how that material settles. Depressions on the sea floor, for example, trap phytodetritus. Sessile species such as sea whips, glass sponges and protozoans called xenophyophores co-occur with mobile groups such as sea spiders and sea cucumbers, whose movements across the sediment can create tracks and topography. All of this small-scale heterogeneity acts in concert to create a mosaic of microhabitats for different organisms.
Seamounts Seamounts, like volcanic islands, are mountains that are formed above the ocean floor near spreading centers, and they subsequently break up the landscape of abyssal plains. Because they are generally steep-sided, much of the substrate is volcanic rock,
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but sedimentary environments occur where sides are not steeply sloped or if the top of the seamount is flattened to form a guyot. Because seamounts can extend large distances above the bottom (thousands of meters), the fauna is often different from that found on the surrounding abyssal plains. The hard substrate, of course, supports very different species from sedimentary environments, and the relatively high flows that can occur over seamounts can support a higher proportion of organisms that feed on suspended particles than most deep-sea environments. In some cases the seamount may extend through the oxygen minimum layer of the Pacific Ocean; these low oxygen conditions favor a very different set of species than areas where oxygen is not limited.
Hydrothermal Vents Hydrothermal vents represent a very specialized and unusual deep-sea environment, and prior to their discovery in 1977, the deep sea was thought to support very low densities of small invertebrates. There had been some debate until that time as to whether high pressure and low temperature constrain the size of benthic organisms, or whether deepsea environments were simply food limited. The discovery of vents quickly answered that question, as researchers discovered dense concentrations of large organisms such as tube worms, clams, and crabs (Figure 3). Compared to the surrounding deep-sea environment, the vents supported extraordinary biomass of large organisms, and led to early analogies of ‘oases in the desert’. From a biomass perspective this is an appropriate analogy, but from a species diversity perspective it is not. Vents occur where tectonic spreading and subduction create fissures in the Earth’s crust, allowing sea water to percolate through the crust and become heated by the mantle (Figure 4). When this water percolates out through the crust again, it is rich in minerals and reduced compounds such as hydrogen sulfide. Water temperature is extremely high (200– 4001C), and is prevented from boiling by the extreme pressure. It cools quickly, however, as it mixes with the ambient sea water that is typically B41C. The mixture of sedimentary and hard substrate habitats that are characteristic of vent fields often support a large biomass of a very specialized fauna. The key to the high productivity of hydrothermal vents are chemoautotrophic bacteria that live freely or form symbioses within specialized tube worms, clams, and mussels. These bacteria utilize hydrogen sulfide to synthesize organic compounds, which in
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Figure 3 Photograph of tube worms (A), clams (B), and polychaete worms (C) from a hydrothermal vent.
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Subduction zone Figure 4 Hydrothermal vents occur where plate tectonic spreading and subduction occur. Water percolates through cracks that plate motion creates in the crust and is superheated in the mantle. The high temperatures cause chemical reactions, changing the chemistry of the sea water, and creating a fluid rich in hydrogen sulfide and various compounds.
the latter case may be passed on to the symbiont hosts. Not surprisingly, the hosts are characterized by reduced guts and little or no feeding structures. For both members of the symbiotic partnership, there are clear advantages. The host provides a physically stable habitat in the immediate proximity of hydrogen sulfide and the bacteria provide a rich food supply to the host. But relatively few species can utilize this symbiotic relationship. The extreme temperature gradients and toxic concentrations of hydrogen sulfide create a habitat that few organisms can tolerate. Moreover, the transient nature of vent environments, which generally persist for time scales of only decades, means that organisms must be able to colonize, grow quickly, and reproduce before vent flow ceases.
Defining the Organisms Deep-sea biologists, like other benthic researchers, divide organisms based on size groupings. These groupings are not absolute in that the larval or juvenile stages of one group may be similar in size to adults from a smaller group, but this division is necessary because the sampling logistics that are appropriate for large organisms are inappropriate for small ones. Organisms that can be readily identified in bottom photographs, such as seastars and crabs, are commonly called megafauna (Figure 5A–C). Included here are characteristic deep-sea fish such as grenadiers, which cruise around near the bottom feeding on any falling carcass or disturbing the sediment and creating feeding pits as they feed on
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Figure 5 Deep-sea organisms, including megafauna (A, rattail fish; B, sea spider; C, brittle star), macrofauna (D, cumacean; E, tanaid; F, polychaete annelid) and meiofauna (G, ostracod; H, nematode). All taxa are from the northwest Atlantic except nematode from San Diego Trough (kindly provided by PJD Lambshead and D Thistle; G Hampson kindly provided photographs D, E, and G).
bottom invertebrates. Some of these taxa migrate up into the water column, providing an additional means by which energy may be cycled between the water column and the benthos. Macrofauna are organisms living on or in the sediments that are retained on a 300-mm sieve; this cutoff is in contrast to the coarser sieves used by shallow-water benthic researchers because the smaller size of deep-sea animals requires a finer sieve. This size grouping includes polychaete annelids, crustaceans, bivalves and many other phyla (Figure 5D–F). Meiofauna are organisms between 40 and 300 mm, and include nematodes, foraminiferans, tiny crustaceans, and many others (Figure 5G–H). Microorganisms pass through a 40-mm sieve and include bacteria and protists. Within any one of these groups, the taxonomic challenges are considerable in that few individuals are trained in taxonomy of deep-sea organisms and many species have yet to be described (see below). Not surprisingly, syntheses across groups are therefore rare in a single study. Feeding modes in deep-sea sediments include omnivores, predators, scavengers and parasites. Most species are deposit feeders that ingest sediment grains and the organic particles and bacteria associated with them; through their feeding activity, these organisms are particularly important bioturbators.
In some areas, suspension feeders filter particles out of the water column above the bottom, but because they rely on suspended particles they are most abundant in energetic environments such as seamounts. As bottom depth increases, both biomass and densities of organisms decrease (Figure 6). Because food resources become scarcer and scarcer as distance from surface water and primary producers increases, this pattern is not unexpected. What is less intuitive, however, is that as food becomes more limiting and densities of organisms decrease, species diversity does not decline.
Sampling the Fauna Early efforts to sample the deep ocean floor used crude trawls towed from surface ships that were ineffective, and undoubtedly contributed to the idea that the environment is species poor. Modern trawls are now used in deep-sea fisheries, and some of these are effective for sampling megafauna living above the sediment or on bedrock. For smaller organisms, Howard Sanders and Robert Hessler, in their important work in the 1960s, used a semiquantitative device called an epibenthic sled comprising a metal frame surrounding a mesh bag. The sled is lowered
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to the bottom and towed behind a ship, where it skims off the surface sediment and associated fauna (Figure 7C). For hyperbenthos, this is still an instrument of choice, but for infauna it is only semiquantitative and has been replaced by quantitative samplers. In the late 1960s, biologists began using a large metal device called a spade or box corer that is commonly used today to sample macrofaunal organisms. Box corers range in size but typically sample B 0.25 m 0.25 m of ocean bottom. A metal frame surrounds a metal box that is lowered into the sediment from a surface ship (Figure 7A). After the box, which is often subdivided by a grid of metal subcores, enters the sediment, the spade swings down and slices beneath the box, locks in place, and seals the sediment within the corer for the return trip to the surface ship. Although the box corer is effective for sampling macrofauna, it must be handled carefully to avoid a bow wave as it approaches the
sediment. For meiofauna and microbes living right at the sediment surface, even a slight bow wave is a problem because it can blow away the lightest sediments and organisms at the sediment–water interface. To circumvent this problem, a device called a multicorer was developed by the Scottish Marine Biological Association (now the Scottish Association of Marine Sciences). With this sampler, a frame is gently lowered onto the seafloor from a surface ship and individual acrylic cores slowly enter the sediment. Individual cores are typically B 6 cm in diameter and a corer can have 4–12 individual cores or more. Sampling gear that is deployed from surface ships has a distinct disadvantage; although the samples are quantitative, they are largely collected blindly, meaning that there is no frame of reference for the area where the sample was collected. Thus, the corer could land on or near some anomalous feature on the seafloor, and the investigating scientist could have trouble interpreting why the fauna was unusual. The development of research submersibles, such as ALVIN (Figure 7B) or the Johnson Sealink (Figure 7D) allows scientists to actually visit deep-sea environments and watch as their samples are collected at precisely the locations they request. To achieve this, a device called an ALVIN box corer, which is effectively a miniaturized box corer, has been developed. The manipulator arm of the submersible pushes the corer (typically 15 cm 15 cm) into the sediment and then trips the doors that seal-in the sample, much as the spade does for the larger box corer. On board ship, individual subcores are processed over a sieve and then preserved in buffered 4% formaldehyde. Samples are kept in formaldehyde for at least 48 hours and then transferred to 70% ethanol. Hard substrate environments present a different challenge in terms of quantitative sampling. Quantitative removal of hard substrate fauna is near impossible except where the substratum itself may be removed (e.g. manganese nodules). For these environments, visually based surveys, achieved through submersibles, remotely operated vehicles (ROVs), or towed cameras provide the most common means of evaluating fauna. These same approaches are also used for some megafaunal studies in sedimentary environments. The instruments described above are the bases for evaluating faunal abundance, but studies of deep-sea fauna do not always focus on species composition. Physiologists have developed special respiration chambers to study metabolic processes, and ecologists have developed baited traps, colonization trays, and settlement tiles to study species response to
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Figure 7 (A) The box corer is one of the basic sampling tools for deep-sea sediments. The corer is lowered from a surface vessel on a wire, and when the box penetrates into the sediment, the spade swings down and slices through the sediment, sealing the sample in the box. Fred Grassle is shown directing the deployment of the corer. (B) ALVIN was one of the first submersibles to be used for deepsea research and played a vital role in the early characterization of hydrothermal vents. (C) An epibenthic sled, developed for deepsea sampling in the 1960s, is towed so that it skims along the seafloor and samples sediments and near-bottom fauna. (D) The Johnson Sealink is a submersible that allows scientists to descend, with a pilot, to the deep-sea floor. ALVIN corers and colonization trays, seen on the front of the submersible, were to be deployed on this dive along with other gear.
resource availability. Most of these instruments are most effectively deployed by submersibles but other approaches have also been used, including free vehicles that are dropped to the bottom from surface ships, and later float to the surface when a release mechanism is triggered.
Patterns of Diversity Although a few scientists before the turn of the century recognized that the deep sea was indeed a species-rich environment, general recognition of this fact did not occur until a series of papers were published by Howard Sanders and Robert Hessler. They collected a series of samples using an epibenthic sled; although this sampling approach is now known to significantly undersample, it represented a marked
improvement over previous gear. Comparison of the data with data from other environments (Figure 8) indicated that the deep sea was among the most diverse of marine sedimentary habitats. From data collected along a transect running from Martha’s Vineyard, Massachusetts to Bermuda, they demonstrated that diversity in deep-sea sediments exceeded that in most shallow areas and rivaled that observed in shallow tropical areas. At the time, this finding represented a startling contrast to current thinking, and even now the desert analogy still persists in some textbooks. More recent work using a box corer (Figure 7A), has shown that the deep sea is not only species rich, but it may also rival tropical rain forests in terms of total species present. Several studies have looked at broad scale pattern in the deep sea, and found that diversity is not
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uniform with depth, location, or latitude. Michael Rex analyzed patterns with depth in gastropods and other taxa, and found a parabolic pattern, with a peak in diversity between 2000 and 3000 m on the continental slope. Diversity in shallow-water sedimentary habitats, such as in estuaries and tidal flats, is relatively low, then increases somewhat on the continental shelf, peaks along the mid to lower slope and then declines to abyssal plains. A similar pattern has been noted by other researchers, although the slope depth of the diversity peak varies among studies. There have been exceptions noted to this pattern. The abyssal Pacific, for example, has higher diversity than shallower areas, and work in Australia suggests that some coastal environments are extremely diverse, perhaps even exceeding that observed in the deep sea. Studies have examined latitudinal patterns and suggest that diversity in the deep sea may decrease with latitude, at least in the North Atlantic. This work has focused on North Atlantic macrofauna, but other studies on meiofaunal nematodes in the Atlantic and isopod crustaceans from the South Pacific do not support such a trend.
How Many Species Are There? At higher taxonomic levels, the marine environment is inarguably more diverse than any other habitat on Earth, and most of the phyla and classes of organisms that are unique to the marine environment occur in sedimentary environments. Some 90% of all animal families and 28 of 29 nonsymbiont animal phyla occur in marine environments, and of these 29, 13 occur only in marine habitats. Only one animal phylum, the Onychophora, has no living representatives in marine habitats, but even then there are marine fossil forms now known. A number of estimates have been made regarding the possible number of species in the oceans (Figure 9) and considerable debate has arisen from these estimates; much of this controversy arises from the general acceptance that the deep sea has many undescribed species but disagreement over how many. Of particular uncertainty is the validity of assumptions that have gone into various estimates. One approach has been to survey taxonomic specialists who work on different groups, and determine what proportion of their taxon remains undescribed (left panel in Figure 9). The famous tropical rainforest estimate by Terry Erwin (central panel in Figure 9) of 10 million insect species was generated by looking at numbers of beetle species associated with a given species of rainforest tree, estimating what portion of
insects comprises beetles, and then multiplying by estimated numbers of tropical tree species. Based on the rate at which species were added with increased area sampled along a 176-km long depth contour off the eastern United States, Grassle and Maciolek extrapolated to the total area of the deep sea and estimated that there are 10 million deep-sea macrofaunal species. Robert May suggested that because about half of Grassle and Maciolek’s species were previously undescribed, one could extrapolate from the presently described 250 000 marine species to arrive at a projection of B 500 000 total species. Data from the Pacific suggests that only 1 in 20 species has been described; using this estimate, May’s approach would yield B 5 million species. John Lambshead, a nematode ecologist, has noted that meiofaunal nematodes are more abundant and species rich in individual core samples than macrofauna, and his estimate for total nematodes in the deep sea is 100 million species. At present we know little about how widely distributed nematode species may be, making extrapolation even more tenuous than for macrofauna. Species richness comparisons across different environments are complex. Within any given environment, estimating the total numbers of species present is difficult because it is impossible to fully sample the environment. The deep sea is particularly problematic. It has been estimated that of the B 3.25 108 km2 of seafloor that is part of the deep sea, only about 2 km2 has been sampled for macrofauna and 5 m2 has been sampled for meiofauna. Sampling coverage for microbes is poorer still. In addition to the huge area involved, ship time and sample processing are expensive, and relatively few taxonomic specialists know the deep-sea fauna.
Polychaete and bivalve species
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Tropical shallow Deep sea slope
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Outer shelf 50 Tropical shallow Tropical estuary
25
Boreal shallow
Boreal estuary 2000 1000 Number of individuals
3000
Figure 8 Comparison of deep-sea communities to other marine sedimentary communities based on plotting numbers of species versus numbers of individuals. (From Sanders HL (1969) Marine benthic diversity and the stability-time hypothesis. Brookhaven Symposium on Biology 22: 71–80.)
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0
Soils and sediments (all taxa)
Tropical insects
Poore and Wilson (1993)
Grassle and Maciolek (1992) May (1992)
Thorson (1971)
Erwin (1982)
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Terrestrial
Terrestrial (described)
Freshwater
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Marine (described) 9 3 10 bacteria? Marine 9 10 nematodes?
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Number of species (× 10 )
Global biodiversity estimates
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Figure 9 Various estimates of total species richness in marine sediments in comparison with estimates for other environments. Numbered sources in the left panel are: 1Palmer MA, Covich AP, Finlay BJ et al. (1997) Biodiversity and ecosystem processes in freshwater sediments. Ambio 26: 571–577; 2Brussaard L, Behan-Pelletier VM, Bignell DE et al. (1997) Biodiversity and ecosystem functioning in soil. Ambio 26: 563–570; 3Snelgrove PVR, Blackburn TH, Hutchings PA et al. (1997). The importance of marine sedimentary biodiversity in ecosystem processes. Ambio 26: 578–583. For each of these sources, the numbers of described and projected species are given. The arrow in Snelgrove et al. indicates estimates if bacteria (1012?) or nematodes (109?) are included; data on which estimates for these groups are based are very limited. Values in other panels are projected numbers of species. Numbers for marine systems are solid bars. Freshwater and terrestrial refer to species number for all global components of those environments pooled, although estimates for bacteria are not included in these numbers. Additional data sources are Thorson G (1971). Life in the Sea. New York; McGraw-Hill and Erwin TL (1982) Tropical forests: their richness in Coleoptera and other Arthropod species. Coleopterists’ Bulletin 36: 74–75.
Thus, current conclusions on pattern and numbers are based on very limited spatial coverage. Most of the data on species number and pattern has been based on data from the North Atlantic. Clearly the variability in patterns described above suggests that a wider database is needed to effectively test the generality of these concepts. Areas such as the southern oceans that have been poorly sampled in the past offer key pieces to the puzzle of deep-sea pattern. Another shortcoming with large-scale comparisons is that most focus on just one of the size groupings of organisms. Thus, between-group differences in pattern are difficult to attribute to differences in areas sampled or to real differences between the groups. In short, we need deep-sea studies that are broader in geographic coverage and taxonomic coverage before these questions can be resolved definitively.
Low Diversity Environments Not all deep-sea communities are species rich. As described earlier, the hydrogen sulfide and heavy metals emitted at vents are toxic to most species, and species diversity is quite low. Moreover, the short life span of most individual vents makes them among the most unpredictable environments in the deep sea. Like the hard substrate environment around vents, the sediments that occur in hydrothermal vent areas
are inhospitable because of high concentrations of metals, sulfide, and hydrocarbons. There are, nonetheless, often mats of bacteria over these sediments that utilize the hydrogen sulfide as an energy source. Not surprisingly, an increase in hydrothermal flux can quickly ‘cook’ the bacteria, whereas a decrease in flux can starve them to death. A number of other specialized deep-sea environments are species depauperate. Deep-sea trenches are subject to mud slumping and poor circulation as a result of the steep trench sides, and species diversity is very low. Sediments beneath upwelling regions and other highly productive areas, such as the upper slope off Cape Hatteras, are also generally low in diversity because large amounts of organic matter accumulate on the ocean floor and decompose, resulting in hypoxic (low oxygen) conditions that few organisms can tolerate. A few deep-sea areas, such as the ‘HEBBLE’ site on the continental slope off Nova Scotia, are subject to intensive ‘storms’, where currents become intense and sediment resuspension occurs. Evidence suggests that macrofaunal diversity is depressed in such areas, but surprisingly meiofaunal diversity is not. Presumably, the meiofauna are able to cope with the disturbance more effectively than the macrofauna. Although ecological processes are undoubtedly important in the deep sea, evolutionary time scales and processes are also important. Defaunation of
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some deep-sea areas such as the Norwegian Sea over recent geological time scales is thought to have contributed to low diversity. Glaciation defaunated the area by blocking sunlight and reducing circulation, and the shallow sills that surround the basin have likely resulted in very slow reestablishment of deep-sea communities from adjacent basins.
Theories One of the driving questions in deep-sea ecology since the 1960s is how an environment that appears so physically homogeneous is able to support a speciesrich fauna. When Sanders documented the high diversity of deep-sea systems in the late 1960s, he proposed the stability–time hypothesis, in which the high level of stability afforded by the deep sea over evolutionary time has resulted in greater specialization and niche diversification in deep-sea fauna. Certainly the relative stability of deep-sea environments has contributed to the numbers of species present, but if stability were the lone explanation then it is inconsistent with observations of lower diversity on abyssal plains than on adjacent slope habitats. An additional problem is that most species are thought to be relatively nonselective deposit feeders, which is inconsistent with niche specialization. In the early 1970s, several alternative theories were proposed. Predators could prevent competitive equilibria from being attained by infauna by cropping back individuals. But most deep-sea predators appear to be nonselective, and infauna are characterized by slow growth, late reproductive maturity and dominance by older age classes; none of these characteristics would be expected in a predatorcontrolled system. Evidence from shallow-water sediments suggests that at small scales at least, predators decrease sedimentary diversity, but the role that predators may play in maintaining deep-sea diversity remains largely unanswered at this point. The increasing evidence for small-scale spatial and temporal heterogeneity in deep-sea systems has led to speculation that small-scale patches may be important. The patch mosaic model proposes that small patches create disequilibria habitats that promote different species and thus promote coexistence. Studies have tested the patch mosaic model by sampling natural patches or creating experimental patches; both types of study have found that species that occur in most patch types are usually rare or absent from nonpatch sediments. This pattern is consistent with the patch mosaic model, but experiments so far have demonstrated that patches promote only a modest number of species and the overall species
richness in a given patch tends to be lower than in nonpatch areas. It is unclear whether we need to sample more patch types or invoke an altogether different explanation for high diversity. Island biogeography has shown that larger areas tend to support more species, and it has been argued that the large area of the deep sea may be the primary reason for its species richness. To some extent this areal relationship must be a contributing factor, but if area were the only issue then abyssal plains would consistently exceed all other habitats in diversity. Moreover, the deep sea does not appear to add habitat heterogeneity with area as most habitats do; vast areas of sedimentary bottom may sometimes exhibit changes in sediment composition, but even compared to shallow areas the habitat heterogeneity is quite small. Intermediate disturbance has been touted in a number of ecological systems as being important for high diversity. High levels of disturbance can eliminate sensitive species and invariant habitats may allow superior competitors to outcompete weaker species; both scenarios result in reduced diversity. Intermediate disturbance prevents competitive dominants from taking over but is not severe enough to eliminate sensitive species, resulting in high diversity. The strongest evidence for this hypothesis in the deep sea is the mid-slope peak in diversity described earlier, and the reduced diversity observed in disturbed deep-sea habitats such as hydrothermal vents, low oxygen areas, environments with benthic storms, and slumping areas. In summary, we still lack a definitive explanation for which factors are most important in promoting diversity in deep-sea ecosystems. In all likelihood, no single explanation is correct and multiple factors will prove to be important. Efforts are currently underway to try to clarify this question using experimental approaches such as predator exclusion experiments and creation of artificial food patches, along with analytical approaches that analyze pattern with respect to environmental variables. As the available data increase, many of the questions about pattern and cause may become clearer, but there is considerable work to be done.
Threats and Benefits The deep-sea environment has attributes that render it vulnerable to human disturbance, but impacts have nonetheless been modest compared to most marine habitats because of the distance from land, large size, and great depth. Pollutants and nutrients that have created severe problems in coastal areas via land
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DEEP-SEA FAUNA
runoff, river runoff or aerosol transport, are usually sufficiently diluted by the time they reach the open ocean that impacts are modest. There is biochemical evidence, however, that pollutants may occur in deep-sea organisms at low concentrations. Fishing, and the habitat destruction it causes, is less widespread in the deep sea than in shallow water because it is expensive and time consuming to fish at great depths. Moreover, the densities of organisms that are present are often insufficient to support commercial fishing. Having said that, there are a number of deepsea fisheries, many of which utilize trawls and dredges that damage the integrity of the benthic habitat, injure organisms, and remove many nontarget species as by-catch. The vulnerability of deepsea species to human activities is well exemplified by fisheries such as that for the Australian orange roughy. Like many deep-sea fisheries, fishing effort has outpaced the capacity of the population to recover, raising the distinct possibility that a sustainable deep-sea fishery may represent an oxymoron. This same vulnerability presumably applies to nontarget species that are removed as by-catch or injured by fishing gear. A third human impact is through waste disposal. Materials ranging from sewage sludge to radioactive waste have been dumped in the deep ocean, largely justified on the basis that the currents are weak so containment is more likely, food chains are far removed from most human harvesting activities, and the large area of the deep sea reduces the likelihood of a major impact. There is also a feeling among some that even if an impact occurs, the organisms that would be affected have little or no obvious economic value to humans. A final potential threat to deep-sea communities is deep-sea mining. There has been some interest in the mining of manganese nodules, small softball-sized nodules that are rich in manganese, nickel and other metals. These nodules occur on the seabed in abyssal plain areas of the oceans, but because of the depths involved, deep-sea mining is not commercially viable at present. Metals such as manganese are, however, of great strategic importance because many countries presently rely on foreign suppliers. Thus, there is a very real chance that deep-sea mining may someday occur. Different mining strategies will, of course, have different types of impact but habitat destruction is likely to be the greatest problem. Because many deep-sea organisms grow very slowly, reproduce at an older age than their shallowwater counterparts, and produce very few offspring per individual, they are thought to be extremely vulnerable to disturbance and habitat damage. In the past it has been assumed, however, that many deepsea species are broadly distributed because there are
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few barriers to dispersal and little obvious habitat heterogeneity. If this assumption holds, then their vulnerability to extinction might be reduced. At present, our understanding of how quickly species turn over spatially is very limited, particularly for some of the groups like nematodes that have been least studied. With emerging molecular approaches, it is also becoming clear that species that have been treated as cosmopolitan may, in some instances, be species complexes. Given that many deep-sea environments support species that are either of no commercial fishing interest or are not sustainable, is there any reason to exercise caution in how humans impact the deep sea? There are, in fact, several compelling reasons to be concerned. First, the deep sea represents one of the few remaining pristine habitats on Earth. We can say, with only a few exceptions, that deep-sea communities have not been compromised by human development. This attribute makes them one of the last natural laboratories on Earth where the ‘chemicals’ have not been tainted. Because it is so very diverse, the deep sea can provide a natural and uncompromised laboratory in which to test ideas on regulation of biodiversity. A second reason to exercise caution is that the deep sea may represent one of the largest species pools on Earth. From an ethical and esthetic perspective, it could be argued that this characteristic alone is sufficient motivation to limit human disturbance. But from an economic perspective, there is great interest among pharmaceutical companies in organisms with unusual physiologies; the thermophilic bacteria that live at hydrothermal vents, for example, have generated tremendous interest for their bioactive compounds. A third concern is with respect to remediation. Although material dumped in the deep sea may be out of sight and mind, any decision at a later time to remediate (e.g. leaking radioactive waste) would be prohibitively expensive, if it was possible at all. In summary, the deep sea is a vast and relatively undisturbed habitat that may be very vulnerable to human disturbances. Our current understanding of the deep sea and its immense diversity is very limited, but is nonetheless advancing steadily. A precautionary approach will ensure that the unusual attributes of the deep sea, including its rich biodiversity, will not be inadvertently destroyed by ignorance.
See also Benthic Boundary Layer Effects. Benthic Foraminifera. Benthic Organisms Overview. Demersal Species Fisheries. Macrobenthos. Meiobenthos. Ocean Margin Sediments. Pelagic Biogeography
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Further Reading Gage JD and Tyler PA (1991) Deep-Sea Biology. A Natural History of Organisms at the Deep-Sea Floor. Cambridge: Cambridge University Press. Grassle JF and Maciolek NJ (1992) Deep-sea species richness: regional and local diversity estimates from quantitative bottom samples. American Naturalist 139: 313--341. Gray J, Poore G, and Ugland K (1992) Coastal and deepsea benthic diversities compared. Marine Ecology Progress Series 159: 97--103. Lambshead PJD (1993) Recent developments in marine benthic biodiversity research. Oceanis 19: 5--24. May R (1992) Bottoms up for the oceans. Nature 357: 278--279.
Merrett NR and Haedrich RL (1997) Deep-sea demersal fish and fisheries. London: Chapman Hall. Poore GBC and Wilson GDF (1993) Marine species richness. Nature 361: 597--598. Rex MA (1983) Geographic patterns of species diversity in the deep-sea benthos. In: Rowe GT (ed.) The Sea: DeepSea Biology, vol. 8, pp. 453--472. New York: John Wiley. Rex MA, Stuart CT, and Hessler RR (1993) Global-scale latitudinal patterns of species diversity in the deep-sea benthos. Nature 365: 636--639. Sanders HL and Hessler RR (1969) Ecology of the deep-sea benthos. Science 163: 1419--1424.
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DEEP-SEA FISHES J. D. M. Gordon, Scottish Association for Marine Science, Argyll, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 687–693, & 2001, Elsevier Ltd.
Introduction For the purpose of this article a deep-sea fish is one that lives, at least for most of its life, at depths greater than 400 m. The fishes of the continental shelves are usually classified as either pelagic or demersal. These categories are often further subdivided in the deep sea. The pelagic component is comprised of the mesopelagic and bathypelagic fishes that live entirely in the water column and are generally of small adult size. Mesopelagic fishes, e.g. lantern fishes (family Myctophidae) and cyclothonids (family Gonostomatidae), live beneath the photic zone to a depth of approximately 1000 m. Bathypelagic fishes live below 1000 m and are usually highly adapted to life in a food-poor environment. Examples are the deep-water angler fishes (family Ceratidae) and the gulper eels (family Eurypharyngidae). Although the term demersal, referring to fishes living on or close to the bottom, is equally appropriate to the deep sea it has become customary to divide these fish into benthic and benthopelagic species. There is also a trend to refer to these as ‘deep-water’ rather than ‘deep-sea’ fish, thus avoiding the nautical use of deep-sea meaning distance from land. Benthic fishes are those that spend most of their time on the bottom and include the rays (family Rajidae), the flatfishes (e.g. family Pleuronectidae) and the tripod fishes (family Chlorophthalmidae). The benthopelagic fishes are those that swim freely and habitually near the ocean floor and examples include the squalid sharks (family Squalidae), the macrourid fishes (family Macrouridae) and the smoothheads (family Alepocephalidae) (see Figure 1). The long-held belief that deep-sea fish belonged to old (in evolutionary terms) and archaic groups is no longer tenable. The deep sea has been invaded many times and there is little doubt that the specialized pelagic fauna have undergone much of their evolution in the deep sea. On the other hand, the demersal fishes probably evolved mainly in the shallower waters and secondarily invaded the deep sea and therefore, although well-adapted for life at
depth, their special morphological features are usually less well-developed than those found in the meso- and bathy-pelagic fishes. In some areas, such as the deep Norwegian Sea, the colonization by demersal fishes appears to be of fairly recent origin. Although there are very marked regional differences in the deep-water demersal fish faunas there is also a degree of global similarity, and certain families such as the macrourids and smoothheads are dominant. Some species such as several deep-water sharks and the orange roughy (Hoplostethus atlanticus) are widely distributed on continental slopes. Many abyssal species, of which the armed grenadier (Coryphaenoides armatus), the blue hake (Antimora rostrato), and the lizardfishes (Bathysaurus spp.) are good examples, are cosmopolitan in their distribution. Our knowledge of the deep-water demersal fishes ultimately depends on the sampling techniques. The bottom trawl, beam or otter, has been the most widely used sampling method. Each design of trawl is selective for a particular spectrum of fishes, and on the upper continental slope – especially in areas where there is commercial exploitation – a wide range of trawls have been used that has resulted in a better understanding of the fish assemblages. On the lower slope and at abyssal depths fewer, more specialized sampling gears have been utilized, and the assemblages may not be adequately described. Where the seabed is unsuitable for bottom trawling, sampling by longlines and traps has been successful. Advances in submersible technology continue to provide information on the distribution and behavior of deep-water fishes.
Depth-related Changes in Abundance and Biomass The abundance, biomass, and usually the number of species, decreases with increasing depth. This in turn is related to the food supply which, with the exception of a very small contribution of probably o1% from chemosynthesis, is ultimately derived from photosynthesis at the surface, see Figure 2. Surface production is not uniform throughout the world’s oceans, as it depends on the factors necessary for photosynthesis such as light, temperature, and nutrients. In general, it tends to be greatest at higher latitudes where there is strong winter mixing and in areas of upwelling. On the basis of this production,
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100 cm
Aphanopus carbo
Phycis blennoides
Bathypterois dubius
Hoplostethus atlanticus
Coryphaenoides rupestris
Bathysaurus ferox
Sebastes mentella
Synaphobranchus kaupi
Figure 1 Some deep-water species to show different morphologies.
the upper layer of the world’s oceans can be divided into a series of fairly well-defined faunal provinces, which extend into the mesopelagic. These provinces have been well-defined for some groups such as the
myctophid fishes. Since the demersal fishes ultimately depend on the same energy supply it is not unreasonable to suppose that such faunal provinces exist also for the demersal fishes, but with a few
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0m Surface production
Vertical migration
Deep scattering layer
Rain of dead organisms
Continental shelf
Mesopelagic Horizontal and vertical impingement of mesopelagic food
1000 m
Bathypelagic
Overlapping food chains
2000 m
3000 m
Benthopelagic Food fall
4000 m
Figure 2 A diagram showing some of the pathways by which food reaches the deep-sea fish. Vertical migration is probably an important food source for bottom fish at around 1000 m and could account for the increased biomass at this depth.
exceptions the level of sampling has been insufficient to identify their presence. An indication that such faunal provinces may exist and that they might be directly related to surface production comes from some work on the deep-water, abyssal fishes of the north-eastern Atlantic. The investigations were carried out in three main areas, the Porcupine Abyssal Plain (c. 481N; 161W), the Madeiran Abyssal Plain (c. 311N; 251W) and off the west African coast (201N). All the stations were at depths between about 4000 and 5550 m. Striking differences in species composition, morphology, maximum fish size, feeding pattern, and reproductive strategies were demonstrated between the fish catches of these areas. In the area of the Madeiran Abyssal Plain, where there is a well-established seasonal thermocline and surface productivity is relatively low, the abyssal fish fauna is most diverse. The individual fish tend to be of small body size and adapted to life where the food supply is dispersed and limited. The stations off the African coast have a distinct fauna, which is probably attributable to higher productivity caused by upwelling along the continental margin. Further north, where there is a marked seasonal cycle of productivity, the fauna is less diverse and the individual fish have larger body sizes and are adapted to exploiting food sources that tend to be patchily
distributed. There appears to be a general trend for decreasing diversity and increasing body size from low to high latitudes. Overall, the biomass at abyssal depths is low compared with the continental slope and shelf. Another trend that has been reported in the Pacific is for a decrease in fish biomass with increasing distance from the continental land mass. This probably results from increased surface productivity attributable to terrestrial inputs. The abyssal fishes are dependent on the ‘rain’ of detritus and associated bacteria and occasional large food falls for their food supply and as these decrease exponentially from the surface to the seabed, the low biomass is easy to explain. However, at depths of around 1000 m on the continental slopes or around seamounts there is often an increase in demersal fish abundance and biomass. It is this increase in biomass that forms the basis of the developing deep-water fisheries. Most of the fishes at this depth are benthopelagic and studies of their diets (see below) have shown that pelagic and benthopelagic organisms dominate their diet. Many of the prey organisms are vertical migrators, ascending towards the surface at night to feed and descending to a depth of about 1000 m during the day, where they form a deepscattering layer. Where this scattering layer impinges either vertically or horizontally onto the slope, it
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provides a rich source of food for the benthopelagic fishes.
The Diet of Deep-water Demersal Fishes In situ investigations in the deep sea are difficult and inevitably this means that much of our knowledge on feeding is derived from stomach content analysis. This has many inherent difficulties, such as the very high percentage of empty or everted stomachs due to the expansion of the gas during recovery from depth in those species that have gas-filled swim bladders. Very often all that remains are hard parts such as vertebrae, squid beaks, and crustacean appendages that become trapped in the lining of the stomach and which can lead to an overestimation of these prey types. The problem of identifying food items, often from fragments, can lead to bias especially when some prey taxa are poorly known, as is often the case in the deep sea. Indeed in some studies, the contents of the fish stomachs have been considered as yet another method of sampling the deep-sea fauna. For example, a significant part of the mesopelagic fauna of Madeira was described from the stomachs of deep-water species such as the black scabbardfish (Aphanopus carbo) landed by the commercial fishery. Net feeding is also considered to be a problem because of the long time the fish spend in the net after initial capture. In some fishes, such as the Alepocephalidae, there is often a high percentage of unidentified soft tissue that may result from feeding on gelatinous plankton. The gelatinous plankton is poorly sampled by nets but the deployment of cameras has shown that it can be abundant and therefore it should not be neglected as a potentially significant food source. Indirect evidence of feeding modes can be obtained from parasite loadings, presence of sediment in the gut, the morphology of the fish, and its associated sensory systems. Stable isotope ratios are beginning to be used to determine the level of the different fishes in the food chain. Direct observation from manned submersibles, remotely operated vehicles, and baited camera systems is a useful tool for understanding feeding behavior. The feeding strategies of the deep-sea fishes cover as wide a range as their shelf counterparts and, as one might expect, reflect the habitat differences (e.g. depth, bottom topography). The piscivorous fishes can broadly be divided into those that adopt a sitand-wait strategy, such as the lizardfish (Bathysaurus) and those that are active predators such as some deep-water sharks and the black scabbardfish. Many deep-water species, including the macrourids,
feed on a mixed diet of the larger pelagic and benthopelagic crustaceans, cephalopods, and small fishes. Others feed on a mixed diet of the smaller benthopelagic organisms and epifauna including amphipods, mysids, and copepods. Again this group can be divided into those that actively forage, such as some of the smaller macrourid fishes, and those that sit and wait, such as the tripod fish (Bathypterois spp.). Feeding directly on the benthos, whether it is browsing at the surface, sifting the sediment for infauna, cropping or even scavenging is relatively unimportant and reflects the relatively low amount of energy that reaches the deep-sea floor.
Sensory Systems Olfaction is well developed in some groups such as the Gadiformes (families Macrouridae and Moridae), some of the sharks, and the synaphobranchid eels. It is probably mostly used for the detection of food, but because it can be sexually dimorphic in some species it may also be used for mate recognition. For example, many male macrourids have larger nostrils than the female. In general the eyes of the benthopelagic fishes do not have the wide range of adaptations to life in the deep sea that are found in the meso- and bathy-pelagic fishes. The eyes tend to remain large and functional and are probably used mainly to detect bioluminescence. Relatively few of the benthopelagic fishes have photophores. Some families have adaptations to maximize the incoming light. In the Alepocephalidae there is a large aphakic space which allows more light to reach the retina from around the edge of the lens, even if it is less focussed. In the squalid sharks and in some teleosts there is a reflective tapetum behind the retina which maximizes the stimulation resulting from the light entering the eye. Some species such as the tripod fish and the forkbeards (Phycis spp.) have developed long fin rays that are sensitive to touch and are used for detecting prey. As may be expected in a dark environment, the lateral line system for detecting movements is particularly well developed in deepwater species and in some species it is particularly elaborate and extends onto the head as a series of canals. The elongate body form of many species is probably an adaptation to increase the sensitivity of the lateral line. In some deep-water species, including many macrourids and gadids of the slope, the males have drumming muscles on their swim bladders for producing sound. This adaptation is absent in the abyssal species.
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Buoyancy Fishes in general have evolved many different methods of reducing the energy required to maintain them in the water column and deep-water fishes are no exception. Gas-filled swim bladders are widely used by the benthopelagic fishes of the continental slopes and also in some abyssal fishes, such as the macrourid fishes, where it has been shown that there is a direct relationship between the length of the retia mirabila (the blood supply to the gas gland) and the depth of occurrence. In some species the swim bladder has become filled with low-density lipid, such as wax esters as in the orange roughy. Some gasfilled swim bladders also have considerable amounts of phospholipid and/or cholesterol, although their role in buoyancy control is uncertain. Reduction in body density can be achieved by having lipids distributed throughout the body. The orange roughy has wax esters in a layer beneath the skin and in vacuoles on the head. Density can also be decreased by reducing the ossification of the skeleton and by having a high water content in the tissues, such as in the alepocephalid fishes. The deep-water sharks have very large livers and also generate hydrodynamic lift by their pectoral fins during swimming, as in their shallow-water counterparts.
Longevity The otoliths (earbones) of most deep-water fishes have well defined opaque and transparent zones typical of those found in shallow water where, at least in temperate latitudes, they correspond to seasonal changes in growth and hence can be used to age the fish (Figure 3). In shallow water the broader opaque zones are associated with faster summer growth, but it is not so obvious why fish living in the aseasonal deep sea should have changes in growth rate, unless they are linked to seasonal changes in food availability and/or quality. Although otoliths, and sometimes scales, have been used to estimate age of deepwater species on the assumption that the rings are laid down annually it has seldom been possible to directly validate these age estimates except in juvenile specimens. Radiometric aging, although controversial, has tended to confirm the generally held view that many deep-water species are long-lived. The commercially exploited grenadiers (Macrouridae) can live to about 50 years and the orange roughy in New Zealand waters lives to more than 100 years.
Reproduction The benthopelagic fishes have relatively few of the more extreme reproductive adaptations, such as
Figure 3 An otolith (ear bone) of an abyssal macrourid (Coryphaenoides rupestris) showing growth zones similar to the annual rings in shallow-water fish. If these rings are annual then this fish will be 6 years old.
parasitic males and hermaphroditism that are more frequently found in the meso- and bathy-pelagic fishes. However, hermaphroditism does occur in some groups such as the tripod fishes and live-bearing occurs in the Scorpaenidae (e.g., Sebastes spp.) and in the deep-water squalid sharks. It was a long held belief that the lack of seasonality in the deep sea would result in year-round reproduction. However, it has become increasingly apparent that many of the deep-water species of the continental slopes, especially in areas of the oceans where there are marked seasonal cycles of production at the surface, have well-defined spawning seasons. At greater depths year-round spawning or asynchronous spawning is more common. It is also possible that some abyssal species, such as the armed grenadier, are semelparous (spawn once in a lifetime). Many shallow-water fishes begin spawning before they reach full adult size, however there is some evidence that some deepwater fishes may not mature until they reach adult size, thus partitioning the energy supply first for somatic growth and then for reproduction. There is a lack of information on the egg and larval stages of many of the benthopelagic fish species. For example, the eggs and larvae of the commercially important black scabbardfish are unknown and the eggs of the roundnose grenadier (Coryphaenoides rupestris) another widespread and exploited species in the Atlantic, have only been described from the Skagerrak. On the other hand, the abundance of eggs of the orange roughy in the South Pacific has been used for stock assessments. It is probable that the eggs of most species are pelagic, but although there has been speculation about the eggs rising and hatching in the food-rich waters
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associated with the thermocline, there is little evidence to substantiate this. Indeed, recent investigations suggest that the ornamentation of the surface of the eggs of some macrourid species might be an adaptation to restrict the ascent of the eggs through the water column and avoid too wide a dispersal.
See also Bioluminescence. Deep-Sea Fishes. Demersal Species Fisheries. Fish Migration, Vertical. Fish Reproduction. Fish Schooling. Mesopelagic Fishes. Open Ocean Fisheries for Deep-Water Species. Upwelling Ecosystems.
Life Histories The relatively low level of sampling in the deep sea, its restriction to a small number of areas and/or depths, and a general lack of seasonal sampling have all resulted in incomplete life history information. Except where there are special physical features, such as extreme temperature changes with depth (e.g. Norwegian Sea), there is little evidence of zonation in the deep-sea fishes. Instead each species has a depth range which can extend over several thousand meters, as in the cut-throat eel (Synaphobranchus kaupi) or over a few hundred meters, as in the tripod fish (Bathypterois dubius) (both examples from the north-east Atlantic). The ‘bigger-deeper’ phenomenon is a common feature among the deep-water demersal fishes, although it might be more correctly referred to as ‘smaller-shallower’. The juveniles of many of the demersal fishes of the continental slopes live at shallower depths than the adults. While in some regions the horizontal distribution of a species can be well documented there is little information on stock discrimination. With present technology it is difficult to tag, release, and recapture deep-water fishes and therefore there is very little information on the movements of deep-water fishes. Some of the commercial deep-water fisheries exist because they often target spawning aggregations, such as orange roughy in the South Pacific and blue ling (Molva dypterygia) in the North Atlantic. Some of the shark species are often found in single sex shoals, and in the exploited leafscale gulper shark (Centrophorus squamosus) of the North Atlantic the gravid females have never been found. The juveniles of many demersal species have never been found in trawl surveys, which suggests that there are separate nursery grounds or that they occur higher in the water column and are not sampled by bottom trawls.
Further Reading Garter JV Jr, Crabtree RE, and Sulak KJ (1997) Feeding at depth. In: Randall DJ and Farrell AP (eds.) Deep-sea Fishes, pp. 115--193. San Diego: Academic Press. Gordon JDM and Duncan JAR (1985) The ecology of the deep-sea benthic and benthopelagic fish on the slopes of the Rockall Trough, northeastern Atlantic. Progress in Oceanography 15: 37--69. Gordon JDM, Merrett NR, and Haedrich RL (1995) Environmental and biological aspects of slope-dwelling fishes of the North Atlantic Slope. In: Hopper AG (ed.) Deep-water Fisheries of the North Atlantic Oceanic Slope, pp. 1--26. Dordrecht: Kluwer Academic Publishers. Haedrich RL (1997) Distribution and population ecology. In: Randall DJ and Farrell AP (eds.) Deep-sea Fishes, pp. 79--114. San Diego: Academic Press. Marshall NB (1979) Developments in deep-sea biology. Poole: Blandford Press. Mauchline J and Gordon JDM (1991) Oceanic pelagic prey of benthopelagic fish in the benthic boundary layer of a marginal oceanic region. Marine Ecology Progress Series 74: 109--115. Merrett NR (1987) A zone of faunal change in assemblages of abyssal demersal fish in the eastern North Atlantic; a response to seasonality in production? Biological Oceanography 5: 137--151. Merrett NR and Haedrich RL (1997) Deep-sea Demersal Fish and Fisheries. London: Chapman and Hall. Montgomery J and Pankhurst N (1997) Sensory physiology. In: Randall DJ and Farrell AP (eds.) Deepsea Fishes, pp. 325--349. San Diego: Academic Press. Pelster B (1997) Buoyancy at depth. In: Randall DJ and Farrell AP (eds.) Deep-sea Fishes, pp. 195--237. San Diego: Academic Press. Randall DJ and Farrell AP (eds.) (1997) Deep-sea Fishes. San Diego: Academic Press.
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DEEP-SEA RIDGES, MICROBIOLOGY A.-L. Reysenbach, Portland State University, Portland, OR, USA Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 693–700, & 2001, Elsevier Ltd.
Introduction Microbes are central to deep-sea ridge ecosystems. Here, in the absence of light energy, the geochemical energy is the primary energy source for microbial growth. These microbes gain energy from oxidation of inorganic compounds such as sulfide and are referred to as chemolithotrophs. Chemolithotrophy or chemosynthesis is the basis of the primary productivity at deep-sea hydrothermal vents, and its discovery challenged our traditional view that all ecosystems were driven by light energy and photosynthesis. The chemolithotrophic microbes are found free-living as well as associated as symbionts with the invertebrates. Additionally, heterotrophic microbes are present that utilize the abundant organic carbon available as a result of the high productivity of these ecosystems. Many of the microbiological discoveries of ocean ridges were gleaned through studying microbial processes or trying to grow novel microbes from these environments. More recently, however, a much more comprehensive picture of the diversity of deep-sea vent microbes is emerging owing to culture-independent diversity assessments. This article will indicate how these different approaches have provided a complementary approach to understanding the dynamics of microbes in deep ocean ridge ecosystems.
Geological Setting Hydrothermal venting occurs both in the terrestrial and marine environments, primarily as a direct result of plate tectonic movement. Divergent boundaries (spreading centers) and convergent margins that produce island arcs are two areas where heat release occurs from the ocean crust, generating high-temperature water activity. At spreading centers, as the tectonic plates are pulled apart, hot molten rock deep within the earth will rise up and fill the gap. Additionally, fissures develop in the crust, and sea water percolates into the crust, reacts with the surrounding rocks, and is heated. This chemically altered sea water will eventually be forced back convectively to the ocean floor as superheated, highly reduced,
hydrothermal fluid rich in gases and minerals (Figure 1) – primary energy sources for microbial growth. Back-arc basins form along active plate margins when old ocean crust is subducted beneath the continental plate. Water can move with the sinking oceanic crust and react with the mantle. As the hydrothermal fluid chemistry is a record of its path within the earth’s crust, these back-arc spreading centers produce heterogeneous hydrothermal fluid chemistry relative to the more stable mid-ocean ridge chemistries. A third basic type of tectonic activity that results in hydrothermal activity comprises ‘hot spots’ and seamounts. Hotspots are places where plumes of hot molten rock may begin deep within the mantle and rise up through the entire mantle and crust. Figure 2 identifies some of the hydrothermal areas that have been studied. Back-arc basins and seamounts are of particular interest for vent biologists as they represent examples of possible island biogeography for vent-related species. The differences in chemistries of these different systems may result in selecting for different physiological types of microbes, but few ecological studies have been addressed to explore such microbial ecological questions in marine vent environments.
Microbial Habitats Deep-sea hydrothermal vents represent one of the most chemically diverse habitats for microbial growth. The geochemical and thermal gradients provide a wide range of possible niches for microbes, with a continuum from oxic to anoxic, pH 3.5 to 8.0, 41C to 4001C, and chemical gradients that mirror the physical gradients (Figure 1). These gradients provide a geochemical disequilibrium, which in turn provides chemical energy for microbial growth. Therefore, there are a multitude of different combinations of electron donors and acceptors and carbon sources for microbial growth. The microbes can be psychrophilic (able to grow best below 151C), mesophilic (growing best between 25 and 401C), or thermophilic (growing best above 451C). Hyperthermophiles are thermophiles that grow best at temperatures above 801C. The mesophilic microbes can be free-living, growing in the cold nutrient-rich sea water surrounding deep-sea vents in areas such as the buoyant plume that results as the hydrothermal fluid rises into the water column and disperses laterally or microbial mats covering sediments and
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Plume Microbes H2 oxidation → CH4 oxidation → Mn oxidation
Thermophilic chemolithotrophs and heterotrophs Epibionts and symbionts
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Figure 1 Diagrammatic cross-section of a seafloor spreading center. The vertical is not to scale. The arrows indicate direction of fluid flow.
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Figure 2 World map depicting some of the known marine hydrothermal vent sites.
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rocks. Other mesophilic microbes at vents include epibionts that attach to the invertebrates colonizing the vents, or endosymbionts found in specialized intracellular compartments in the invertebrates. Thermophilic microbes are restricted to areas where there is close contact with the high-temperature hydrothermal fluid. This may be in the porous sulfidic rocks or chimney structures, in the mineral sediments covering diffuse flow areas, or perhaps in the subsurface environment. Consider, for example, a cross-section through a porous hydrothermal chimney (Figure 3). From fluid flow and geochemical models one can predict the potential physiological types that can inhabit this thermal environment. However, by far the more abundant niches for microbial growth at deep-sea vents are in the aerobic zone surrounding the high-temperature venting, and it has been estimated that microbial processes other than sulfide oxidation may account for as little as 4% of the total microbial productivity (in terms of energy yield) of the vent ecosystem.
Microbial Diversity at Deep-sea Vents Measures of Diversity
Traditionally, microbial diversity was measured by what could be grown and identified in the laboratory. This approach is heavily biased toward how
Mesophilic heterotrophs H2S oxidizers Methanogens Fe oxidizers Mn oxidizers
successfully we are able to understand the conditions that support growth of deep-sea microbes. However, the use of nucleotide sequence comparisons of the small subunit rRNA (16S rRNA in Archaea and Bacteria), has provided an evolutionary molecule by which all life can be compared. With this emerged the ‘Universal Tree of Life,’ in which all life is placed within a phylogenetic framework of three domains, the Archaea, the Bacteria (both prokaryotic lacking a cell nucleus), and the Eukarya (all eukaryotes). Since the 16S rRNA molecule is present in all Bacteria and Archaea, one can extract DNA from an environmental sample, amplify the gene that encodes for the 16S rRNA using the polymerase chain reaction (PCR), sort the different genes from the different microbes by cloning, and sequence the individual genes that represent the ‘fingerprints’ of each phylogenetically distinct microbe in the environment. These sequences can be placed in the phylogenetic framework of a tree, and the diversity of the microbes in the environment can then be identified without the reliance on trying to grow them in the laboratory. This molecular phylogenetic approach to identifying microbes that have previously resisted cultivation has revolutionized our perception of the microbial world. For example, many symbionts cannot grow without their hosts. All of the endosymbionts of deep-sea hydrothermal invertebrates were identified using these molecular phylogenetic approaches.
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Endosymbionts
The initial discovery of deep-sea hydrothermal vents more than 20 years ago was accompanied by the discovery of a deep-sea oasis for invertebrate life. The invertebrates included large bivalves and giant tubeworms (Riftia pachyptila), and later it was shown that many of the invertebrates also harbored endosymbionts. The high productivity of these deep-sea oases has been linked to the successful associations between the chemoautotrophic endosymbionts and their macroinvertebrate hosts. Most of the endosymbionts are chemolithotrophic sulfur-oxidizing gamma Proteobacteria. Riftia pachyptila, the giant tubeworm, houses its symbionts in a specialized structure called the trophosome. The worm is mouthless and gutless and the densities of the endosymbionts can be up to B3.7 109 cells per gram of trophosome. The endosymbionts require sulfide, oxygen, and carbon dioxide. Sulfide oxidation provides the energy for carbon dioxide fixation. The host supplies the microbes with these gases, whereas the symbiont provides the host with a continuous supply of organic carbon. The host transports high concentrations of oxygen and hydrogen sulfide, in the less toxic HS form, via an unusual hemoglobin. These gases are taken directly via the host’s vascular system to the endosymbionts. Carbon dioxide is transported freely as CO2 or HCO3 in the host’s blood without the aid of hemoglobin. The sulfur-oxidizing endosymbionts associated with many of the deep-sea vent invertebrates highlighted the importance of chemoautotrophy in the overall productivity of hydrothermal ecosystems. In areas where methane is prevalent, another endosymbiotic relationship between a microbe and invertebrate also exists, namely between a giant bathymodiolid mussel and methylotrophic (methaneoxidizing) endosymbionts. The symbionts in this methane-based symbiosis are housed in the gill tissues and the symbionts have the stacked internal membrane structures diagnostic of methylotrophs. In some cases where methane and sulfide are in abundance, such as at the Mid-Atlantic Ridge (Snake Pit), the mussels have two different symbionts in their gills, the sulfur-oxidizing symbionts and the methylotrophs. Clearly this provides the mussels with the metabolic versatility to capitalize on the different potential energy sources that may be available any given time at a vent environment. Using molecular techniques, it has been shown that the symbionts of the bivalves such as the giant clams and mussels are transferred vertically, viz. from adults to offspring via the ovarian tissue and oocytes. In tubeworms, however, there is no evidence
to support the transmission of symbionts from the adult through the eggs and larvae. In this case, it is thought that the tubeworm has to acquire its symbionts from the environment, and the larval tubeworms probably do so by ingestion of free-living forms of the symbionts. So how did the symbiotic relationships evolve in the bivalves? There is evidence from molecular phylogenetic comparisons of host phylogenies and the symbiont phylogenies that in the vesicomyid clam (another symbiotic invertebrate from deep-sea vents) the symbiont and host have coevolved and cospeciated. As additional molecular phylogenetic studies are completed for other host–symbiont relationships, more insight into the population genetics and cospeciation of vent invertebrates will no doubt be gleaned. Epibionts
Several studies have explored the diversity of epibionts associated with hydrothermal invertebrates. Initial microscopic observations of invertebrates, such as with the polychaete Alvinella pompejana and the vent shrimp Rimicaris exoculata, revealed dense colonization of microbiota associated with dorsal integuments (Figure 4) and mouth parts, respectively. In both cases, the identity of these epibionts was determined using culture-independent approaches and 16S rRNA phylogenetic analysis. These epibionts belong to the epsilon Proteobacteria, a group that appears to be prevalent both as epibionts and as
Figure 4 An Alvinella pompejana on a petri plate. Note the white microbial filaments covering the parapodia; these have been identified using 16S rRNA techniques and belong to the epsilon Proteobacteria.
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free-living microbes in the hydrothermal vent environment. The role these epibionts have in relation to their hosts is unclear; however, they may have some nutritional benefit for their host. The dominant epibiont associated with Alvinella pompejana showed some interesting variation between the populations colonizing the anterior and posterior parts of the worm. This small variation in 16S rRNA sequence was not enough to designate the two different population types as different species, but the variation may represent a variation in ecological niche. Recently it was proposed that microbiologists take on a ‘natural concept’ for microbial species, in which environmental gradients provide different ecological niches and cause environmentally induced genetic variation resulting in different ecotypes or ecospecies.
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Figure 5 An extensive microbial mat surrounding a clump of Riftia pachypitila in Guaymas Basin, Mexico. The sampling basket and arm of submersible Alvin are in the foreground. (Photograph by A.-L. Reysenbach, S. Cary, and G.W. Luther.)
Free-living Microbial Diversity
Mesophiles The rising particle- and nutrient-rich hydrothermal fluid forms the hydrothermal plume that can be detected many kilometers away from the actual vent site. This buoyant plume is enriched in reduced compounds and provides ecological niches for a succession of different metabolic types, laterally and further from the site of venting. Initial rapid hydrogen oxidation takes place, then methane oxidation, and finally manganese oxidation. The shifts in the microbial community laterally along the hydrothermal source are being investigated. Immediately surrounding the deep-sea vents is a very diverse and dense (up to 109 cells per ml) community of microbes that range from obligate chemolithotrophs to heterotrophs. Much of the initial research on these communities focused on the sulfur-oxdizers that form visible microbial mats such as those seen at Guaymas Basin (Figure 5). These communities are dominated by large filaments belonging to the genera Beggiatoa and Thiothrix. Like its close relatives Thiomargarita and Thioplaca, Beggiatoa, has very large cells, much of which is devoid of cytoplasm. The vacuolar space is where nitrate can accumulate. These organisms can couple anoxic oxidation of H2S with nitrate reduction, so they can occupy the anoxic–oxic water interface. Several new surprises emerged using a molecular phylogenetic approach to assess the microbial diversity in a mat associated with the active deep-sea hydrothermal system at Pele’s vents (Loihi Seamount, Hawaii). Not only did the epsilon proteobacteria (similar to the epibiont described above) predominate in these mats, but also a wide diversity of Archaea were detected, closely related to Archaea from the marine planktonic environment and coastal
sediments. This study further supported the growing evidence that archaea are ubiquitous and not restricted to extreme environments. Perhaps one of the most significant discoveries made regarding mesophilic microbial activity at deep-sea hydrothermal vents was the discovery of microbes that produce copious amounts of inorganic filaments of sulfur. Arcobacter-related isolates are able to produce filamentous sulfur at the sulfide– oxygen interface of a gradient and are probably responsible for the white flocculent material (floc) that covers fresh basalt within weeks following an eruption. These microbes may also proliferate in the shallow subsurface and produce the sulfur filaments in areas where hydrothermal fluid is mixing with oxygenated sea water. If an eruption occurs, this flocculent material is then dispersed onto the ocean floor (Figure 6). Thermophiles An emerging theme with studies of microbial diversity at deep-sea hydrothermal vents is that the thermophiles that have been obtained in cultures are only a very minor component of the diversity of thermophiles at deep-sea vents. Many of the enrichment cultures have focused on microbes that grow best above 801C (hyperthermophiles). Most of these organisms fall within the Archaea, and include over 20 different reports of new members of the heterotrophic and sulfur-reducing Thermococcales. Other archaea that have been isolated include thermophilic methanogens such as Methanococcus jannaschii (whose genome was recently fully sequenced) and Methanopyrus, and sulfate-reducing archaea of the order Archaeoglobales. Other Archaeal
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the epsilon Proteobacteria also thrived in this chamber, raising the question whether these prevalent types are perhaps thermophilic inhabitants of deep-sea vents. Additionally, novel archaeal lineages were detected that were related to known iron oxidizers and thermoacidophiles (acid- and heat-loving organisms). In an independent study that explored the archaeal diversity of deep-sea vent chimneys, many novel very deeply diverging lineages were identified. Molecular-based inventories of deep-sea microbial diversity provide the baseline database for rigorous microecological studies at vents. Additionally, these assessments provide guidance for enrichment culturing strategies. Figure 6 Biogenic flocculent material (floc) in the water column surrounding a newly erupted vent field at 91N on the East Pacific rise. (Photograph by R. Haymon and D. Fornari, courtesy T. Shank.)
isolates obtained from deep-sea vents are the facultatively aerobic obligate chemolithoautotroph Pyrolobus fumarii that was obtained from a hydrothermal chimney sample and grows up to 1131C, the highest temperature recorded for a microbe growing in laboratory culture. Surprisingly few thermophilic Bacteria have been obtained from deep-sea vents; however, culture-independent approaches may change this perception. Thermophilic Bacillus and Thermus species have been reported from deep-sea vents, as have members of sheathed thermophilic heterotrophs, the Thermotogales. More recently, and perhaps more significantly, representatives of two new lineages never previously reported from vents have been isolated. One, named Desulfurobacterium, is the only sulfurreducing obligate chemolithotrophic thermophile in the domain Bacteria. Additional isolates of this group have confirmed that it may represent a new order. A second lineage, relatively closely related to the deeply branching Aquificales lineage, has also been isolated and is a microaerophilic hydrogen oxidizer. Interestingly, this Aquificales lineage was first recognized as existing at deep-sea vents by analyzing the diversity associated with the deployment of an in situ growth chamber using a culture-independent approach. This chamber is placed on top of a hydrothermal vent for a predetermined time. The fluid flows through the chamber, and microbes can colonize surfaces that are placed in the chamber. Upon retrieval, the chamber is brought back to the surface and the diversity of organisms that are present in the chamber is analyzed using DNA-based techniques. Several interesting surprises emerged from one such study. Not only were there novel bacterial lineages prevalent in this environment, but
Subsurface Biosphere It has been estimated that the subsurface is the major biosphere for microbes. Deep-sea hydrothermal vents may represent surface manifestations of this biosphere, and offer ‘windows’ into the Earth’s interior ecosystem. The challenges now are to explore the extent of this biosphere. These include ocean drilling of hydrothermal environments, but also monitoring of microbial, geochemical, and biological changes that occur after new eruptions on the ocean floor. Perhaps one of the most spectacular examples of indirect evidence for an extensive subsurface biosphere at deep-sea vents is the initial biogenic sulfur flocs that are seen being emitted from eruptions (Figure 6). As described above, this flocculant material is produced by a mesophilic vibriod microbe that produces strands of filamentous sulfur at the sulfide–oxygen interface.
Deep-sea Hydrothermal Vents and the Origins of Life As the early Earth accreted more than 4.0 billion years ago, it had a hot volcanic environment and a surface bombarded by asteroids. As the Earth started to cool, hydrothermal activity was extensive, and it is estimated that there was three times more heat flow due to hydrothermal activity in the Archaean Earth, than there is today. Some of the first evidence for life dates back to 3.8 Ga and some of the first microfossils date to about 3.5 Ga when there is no evidence for oxygen in the environment. Additionally, the deepest branching lineages within the tree of life are all represented by thermophilic microbes. These microbes may represent modern day analogues of their thermophilic ancestors. If life did originate in a hot hydrothermal environment, it is likely that the rich CO2 environment and geochemical disequilibrium
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DEEP-SEA RIDGES, MICROBIOLOGY
associated with the hydrothermal venting was an excellent energy source for the evolution of chemolithotrophs. Prior to the evolution of life, it is also possible that some of the first molecules may have evolved in this environment. A patent attorney and chemist, Gunter Wa¨chterha¨user has proposed an elegant theory of how some of life’s precursor molecules could have assembled on positively charged surfaces such as pyrite, an abundant mineral in hydrothermal systems.
Conclusion Deep-sea hydrothermal ecosystems represent a frontier in science. Microbiologists have only begun to explore this new frontier. With the use of molecular techniques, rapid genomic sequencing, and better methods for sampling microbial niches at ridge ecosystems we will gain a much more comprehensive insight into the roles that microbes play in these ecosystems. Furthermore, understanding how these organisms thrive in this hostile deep environment, how they may influence the precipitation of minerals, and how they may become fossilized into the rock has implications in our search for the evidence of life (past or present) on other planets.
See also
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Vent Fauna, Physiology of. Mid-Ocean Ridge Seismic Structure.
Further Reading Bock GR and Goode JA (eds.) (1996) Evolution of Hydrothermal Ecosystems on Earth (and Mars?). New York: Wiley. Jeanthon C (2000) Molecular ecology of hydrothermal vent microbial communities. Antonie van Leeuwenhoek 77: 117--133. Karl DM (ed.) (1995) The Microbiology of Deep-sea Hydrothermal Vents. Boca Raton, FL: CRC Press. McCollom TM and Shock EL (1997) Geochemical constraints on chemolithoautotrophic metabolism by microorganisms in seafloor hydrothermal systems. Geochimica et Cosmochimices Acta 61: 4375--4391. Van Dover CL (2000) The Ecology of Deep-sea Hydrothermal Vents. Princeton, NJ: Princeton University Press. Wa¨chterha¨user G (1988) Before enzymes and templates. Theory of surface metabolism. Microbiological Reviews 52: 452--484. Ward DM, Ferris MJ, Nold SC, and Bateson MM (1998) A natural view of the microbial biodiversity within hot spring cyanobacterial mat communities. Microbiology and Molecular Biology Reviews 62: 1353--1370. Whitman WB, Coleman DC, and Wiebe WJ (1998) Prokaryotes: the unseen majority. Proceedings of the National Academy of Sciences of the USA 95: 6578--6583.
Hydrothermal Vent Biota. Hydrothermal Vent Deposits. Hydrothermal Vent Ecology. Hydrothermal
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DEEP-SEA SEDIMENT DRIFTS D. A. V. Stow, University of Southampton, Southampton, UK Copyright & 2001 Elsevier Ltd. This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 700–709, & 2001, Elsevier Ltd.
variation in deep-sea paleocirculation. As this is closely linked to climate, the drift successions of ocean basins hold one of the best records of past climate change. This clear environmental significance, together with the recognition that sandy contourites are potential reservoirs for deep-sea oil and gas, has spurred much current research in the field.
Introduction The recognition that sediment flux in the deep ocean basins might be influenced by bottom currents driven by thermohaline circulation was first proposed by the German physical oceanographer George Wust in 1936. His, however, was a lone voice, decried by other physical oceanographers and unheard by most geologists. It was not until the 1960s, following pioneering work by the American team of Bruce Heezen and Charlie Hollister, that the concept once more came before a critical scientific community, but this time with combined geological and oceanographic evidence that was irrefutable. A seminal paper of 1966 demonstrated the very significant effects of contour-following bottom currents (also known as contour currents) in shaping sedimentation on the deep continental rise off eastern North America. The deposits of these currents soon became known as contourites, and the very large, elongate sediment bodies made up largely of contourites were termed sediment drifts. Both were the result of semipermanent alongslope processes rather than downslope event processes. The ensuing decade saw a profusion of research on contourites and bottom currents in and beneath the present-day oceans, coupled with their inaccurate identification in ancient rocks exposed on land. By the late 1970s and early 1980s, the present author had helped establish the standard facies models for contourites, and demonstrated the direct link between bottom current strength and nature of the contourite facies, especially grain size. Discrimination was made between contourites and other deep-sea facies, such as turbidites deposited by catastrophic downslope flows and hemipelagites that result from continuous vertical settling in the open ocean. Since then, much progress has been made on the types and distribution of sediment drifts, the nature and variability of bottom currents, and the correct identification of fossil contourites. Of particular importance has been the work at Cambridge University in decoding the often very subtle signatures captured in contourites in terms of
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Bottom Currents At the present day, deep-ocean bottom water is formed by the cooling and sinking of surface water at high latitudes and the deep slow thermohaline circulation of these polar water masses throughout the world’s ocean (Figure 1 and 2). Antarctic Bottom Water (AABW), the coldest, densest, and hence deepest water in the oceans, forms close to and beneath floating ice shelves around Antarctica, with localized areas of major generation such as the Weddell Sea. Once formed at the surface, partly by cooling and partly as freezing sea water leaves behind water of greater salinity, AABW rapidly descends the continental slope, circulates eastwards around the continent and then flows northwards through deep-ocean gateways into the Pacific, Atlantic and Indian Oceans. Arctic Bottom Water (ABW) forms in the vicinity of the subpolar surface water gyre in the Norwegian and Greenland Seas and then overflows intermittently to the south through narrow gateways across the Scotland–Iceland–Greenland topographic barrier. It mixes with cold deep Labrador Sea water as it flows south along the Greenland–North American continental margin. Above these bottom waters, the ocean basins are compartmentalized into water masses with different temperature, salinity, and density characteristics. Bottom waters generally move very slowly (1–2 cm s1) throughout the ocean basins, but are significantly affected by the Coriolis Force, which results from the Earth’s spin, and by topography. The Coriolis effect is to constrain water masses against the continental slopes on the western margins of basins, where they become restricted and intensified forming distinct Western Boundary Undercurrents that commonly attain velocities of 10–20 cm s1 and exceed 100 cm s1 where the flow is particularly restricted. Topographic flow constriction is greater on steeper slopes as well as through narrow passages or gateways on the deep seafloor. Bottom currents are a semipermanent part of the thermohaline circulation pattern, and sufficiently
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Figure 1 Global pattern of abyssal circulation. Shaded areas are regions of production of bottom waters. (After Stowet al., 1996).
competent in parts to erode, transport and deposit sediment. They are also highly variable in velocity, direction, and location. Mean flow velocity generally decreases from the core to the margins of the current, where large eddies peel off and move at high angles or in a reverse direction to the main flow. Tidal, seasonal, and less regular periodicities have been recorded during long-term measurements, and complete flow reversals are common. Variation in kinetic energy at the seafloor results in the alternation of short (days to weeks) episodes of high velocity known as benthic storms, and longer periods (weeks to months) of lower velocity. Benthic storms lead to sediment erosion and the resuspension of large volumes of sediment into the bottom nepheloid layer. They appear to correspond to episodes of high surface kinetic energy due to local storms. Deep and intermediate depth water is also formed from relatively warm surface waters that are subject to excessive evaporation at low latitudes, and hence to an increase in relative density. This process is generally most effective in semi-enclosed marginal seas and basins. The Mediterranean Sea is currently the principal source of warm, highly saline, intermediate water, that flows out through the Strait of Gibraltar and then northwards along the Iberian and north European margin. At different periods of Earth history warm saline bottom waters will have been equally or more important than cold water masses.
Contourite Drifts Contourite accumulations can be grouped into five main classes on the basis of their overall
morphology: (I) contourite sheet drifts; (II) elongate mounded drifts; (III) channel-related drifts; (IV) confined drifts; and (V) modified drift–turbidite systems (Table 1, Figure 3). It is important to note, however, that these distinctive morphologies are simply type members within a continuous spectrum, so that all hybrid types may also occur. They are also found at all depths within the oceans, including all deep-water (42000 m) and mid-water (300–2000 m) settings. Those current-controlled sediment bodies that occur in shallower water (50–300 m) on the outer shelf or uppermost slope are not considered contourite drifts sensu stricto. The occurrence and geometry of these different types is controlled principally by five interrelated factors: the morphological context or bathymetric framework; the current velocity and variability; the amount and type of sediment available; the length of time over which the bottom current processes have operated; and modification by interaction with downslope processes and their deposits. Contourite Sheet Drifts
These form extensive very low-relief accumulations, either as part of the fill of basin plains or plastered against the continental margin. They comprise a layer of more or less constant thickness (up to a few hundred meters) that covers a large area, but that demonstrates a very slight decrease in thickness towards its margins, i.e., having a very broad lowmounded geometry. The internal seismofacies is typically one of low amplitude, discontinuous reflectors or, in some parts, is more or less transparent. They may be covered by large fields of sediment waves, as in the case of the South Brazilian and
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DEEP-SEA SEDIMENT DRIFTS
Greenland Iceland Europe
Indian Ocean
Africa
STC AC
AD
P
0 Antarctic
Depth (m)
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6000 40˚ 20˚ 0˚ 60˚ N ABW : Arctic bottom water AABW : Antarctic bottom water AAIW : Antarctic intermediate water AIW : Arctic intermediate water CW : Central water DW : Deep Atlantic water UDW : Upper Atlantic water MDW : Middle deep water LDW : Lower deep water
20˚
40˚
60˚
80˚
S Med : Water from the Mediterranean : Regions of upwelling AC : Antarctic convergence AD : Antarctic divergence STC : Subtropical convergence P : Arctic polar front : Minimum oxygen levels
Figure 2 Bottom water masses in the North Atlantic Ocean (Reproduced from Stow et al., 1996).
Argentinian basins where they are also capped in the central region by giant elongate bifurcated drifts. The different hydrological and morphological contexts define either abyssal sheets or slope sheets (also known as plastered drifts). The former carpet the floors of abyssal plains and other deep-water basins including those of the South Atlantic and the central Rockall trough in the north-east Atlantic. The basin margin relief partially traps the bottom currents and determines a very complex gyratory circulation. Slope sheets occur near the foot of slopes where outwelling or downwelling bottom currents exist, such as in the Gulf of Cadiz as a result of the deep Mediterranean Sea Water outwelling at an intermediate water level into the Atlantic, or around the Antarctic margins as a result of the formation and downwelling of cold AABW. They are also found plastered against the slope at any level, particularly
where gentle relief and smooth topography favors a broad nonfocused bottom current, such as along the Hebrides margin and Scotian margin. Abyssal sheet drifts typically comprise fine-grained contourite facies, including silts and muds, biogenicrich pelagic material, or manganiferous red clay, interbedded with other basin plain facies. Accumulation rates are generally low – around 2–4 cm ky1. Slope sheets are more varied in grain size, composition and rates of accumulation. Thick sandy contourites have been recovered from base-of-slope sheets in the Gulf of Cadiz, and rates of over 20 cm ky1 (1000 years) are found in sandy–muddy contourite sheets on the Hebridean slope. Elongate Mounded Drifts
This type of contourite accumulation is distinctly mounded and elongate in shape with variable
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DEEP-SEA SEDIMENT DRIFTS
Table 1
Drift morphology, classification and dimensions
Drift type
Subdivisions
Size (km2)
Examples
Contourite sheet drift
Abyssal sheet
105–106
Slope (plastered sheet)
103–104
Argentine basin; Gloria Drift Gulf of Cadiz; Campos margin
Slope (patch) sheets
103
Detached drift
103–105
Eirek drift; Blake drift
Separated drift
103–104
Feni drift; Faro drift
Patch-drift
10–103
North-east Rockall trough
Contourite-fan
103–105
Vema Channel exit Sumba drift; East Chatham rise
Elongated mounded drift
Channelrelated drift
Confined drift
103–105
Modified Extended drift–turbidite turbidite bodies systems
103–104
Sculptured 103–104 turbidite bodies Intercalated Can be very turbidite– extensive contourite bodies
Columbia levee South Brazil Basin; Hikurangi fandrift South-east Weddell Sea Hatteras rise
dimensions: lengths from a few tens of kilometers to over 1000 km, length to width ratios of 2 : 1 to 10 : 1, and thicknesses up to 2 km. They may occur anywhere from the outer shelf/upper slope, such as those east of New Zealand to the abyssal plains, depending on the depth at which the bottom current flows. They are very common throughout the North Atlantic, but also occur in all the other ocean basins and some marginal seas. One or both lateral margins are generally flanked by distinct moats along which the flow axis occurs and which experience intermittent erosion and nondeposition. Elongate drifts associated with channels or confined basins are classified separately. Both the elongation trend and direction of progradation are dependent on an interaction between the local topography, the current system and intensity, and the Coriolis Force. Elongation is generally parallel or subparallel to the margin, with both detached and separated types recognized, but progradation can lead to parts of the drift being elongated almost perpendicular to the margin. Internal seismic character
83
reflects the individual style of progradation, typically with lenticular, convex-upward depositional units overlying a major erosional discontinuity. Fields of migrating sediment waves are common. Sedimentation rates depend very much on the amount and supply of material to the bottom currents. On average, rates are greater than for sheet drifts, being between 2 and 10 cm ky1, but may range from o2 cm ky1 for open ocean pelagic biogenic-rich drifts, to 460 cm ky1, for some marginal drifts (e.g., along the Hebridean margin). The sediment type also varies according to input, including biogenic, volcaniclastic, and terrigenous types. Grain size varies from muddy to sandy as a result of longterm fluctuations in bottom current strength. Channel-related Drifts
This type of contourite deposit is related to deep channels, passageways or gateways through which the bottom circulation is constrained so that flow velocities are markedly increased (e.g., Vema Channel, Kane Gap, Samoan Passage, Almirante Passage, Faroe-Shetland Channel etc.). Gateways are very important narrow conduits that cut across the sills between ocean basins and thereby allow the exchange of deep and intermediate water masses. In addition to significant erosion and scouring of the passage floor, irregular discontinuous sediment bodies are deposited on the floor and flanks of the channel, as axial and lateral patch drifts, and at the downcurrent exit of the channel, as a contourite fan. Patch drifts are typically small (a few tens of square kilometers in area, 10–150 m thick) and either irregular in shape or elongate in the direction of flow. They can be reflector-free or with a more chaotic seismic facies, and may have either a sheet or mounded geometry. Contourite fans are much larger cone-shaped deposits, up to 100 km or more in width and radius and 300 m in thickness (e.g., the Vema contourite fan). Channel floor deposits include patches of coarsegrained (sand and gravel) lag contourites, mud–clast contourites and associated hiatuses that result from substrate erosion, as well as patch drifts of finergrained muddy and silty contourites where current velocities are locally reduced. Manganiferous mud contourites and nodules are also typical in places. Accumulation rates range from very low, due to nondeposition and erosion, to as much as 10 cm ky1 in some patch drifts and contourite fans. Confined Drifts
Relatively few examples are currently known of drifts confined within small basins. These typically
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DEEP-SEA SEDIMENT DRIFTS
TYPE I Contourite sheets Drift sheet
Plastered drift
TYPE II Elongate drifts
Detached drift
Separated drift
TYPE III Channel-related drifts Contourite 'fan'
Lateral and axial patch drifts
TYPE IV Confined drift
TYPE V Modified fan-drift
Figure 3 Contourite drift models. (Modified from Faugeres et al., 1999.)
occur in tectonically active areas, such as the Sumba drift in the Sumba forearc basin of the Indonesian arc system, the Meiji drift in the Aleutian trench and an unnamed drift in the Falkland Trough. Apart from their topographic confinement, the gross seismic character appears similar to mounded elongate drifts with distinct moats along both margins. Sediment type and grain size depend very much on the nature of input to the bottom current system. Modified Drift-turbidite Systems: Process Interaction
The interaction of downslope and alongslope processes and deposits at all scales is the normal
condition on the margins as well as within the central parts of present ocean basins. Interaction with slow pelagic and hemipelagic accumulation is also the norm, but these deposits do not substantially affect the drift type or morphology. Over a relatively long timescale, there has been an alternation of periods during which either downslope or alongslope processes have dominated as a result of variations in climate, sealevel and bottom circulation coupled with basin morphology and margin topography. This has been particularly true since the late Eocene onset of the current period of intense thermohaline circulation, and with the marked alternation of depositional style reflecting glacial–interglacial episodes during the past 2 My (million years). At the scale of the drift deposit, this interaction can have different expressions as exemplified in the following examples. 1. Scotian Margin: regular interbedding of thin muddy contourite sheets deposited during interglacial periods and fine-grained turbidites dominant during glacials; marked asymmetry of channel levees on the Laurentian Fan, with the larger levees and extended tail in the direction of the dominant bottom current flow. 2. Cape Hatteras Margin: complex imbrication of downslope and alongslope deposits on the lower continental rise, that has been referred to as a companion drift-fan. 3. The Chatham–Kermadec Margin: the deep western boundary current in this region scours and erodes the Bounty Fan south of the Chatham Rise and directly incorporates fine-grained material from turbidity currents that have traveled down the Hikurangi Channel. This material, together with hemipelagic material, is swept north from the downstream end of the turbidity current channel to form a fan-drift deposit. 4. West Antarctic Peninsula Margin: eight large sediment mounds, elongated perpendicular to the margin and separated by turbidity current channels, have an asymmetry that indicates construction by entrainment of the suspended load of down-channel turbidity currents within the ambient south-westerly directed bottom currents and their deposition downcurrent. 5. Hebridean Margin: complex pattern of intercalation of downslope (slides, debrites, and turbidites), alongslope contourites and glaciomarine hemipelagites in both time and space; the alongslope distribution of these mixed facies types by the northward-directed slope current has led to the term composite slope-front fan for the Barra Fan.
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DEEP-SEA SEDIMENT DRIFTS
concentrations of coarser material. They have a siltyclay grain size, poor sorting, and a mixed terrigenous (or volcaniclastic)–biogenic composition. The components are in part local, including a pelagic contribution, and in part far-traveled.
Erosional Discontinuities
The architecture of deposits within a drift is complex, stressing variations of the processes and accumulation rates linked to changes in current activity. In many cases, the history of contourite drift construction is marked by an alternation of periods of sedimentation and erosion or nondeposition, the latter corresponding to a greater instability of and/or a drastic change in current regime. The result is the superposition of depositional units whose general geometry is lenticular and whose limits correspond to major discontinuities, that are more or less strongly erosive. These discontinuities can be traced at the scale of the accumulation as a whole and are marked by a strong-amplitude continuous reflector, commonly marking a change in seisomofacies linked to variation in current strength. Such extensive and synchronous discontinuities are typical of most drifts. The principal characteristics of drifts evident in seismic records are shown in Figure 4.
Silty Contourites
These, which are also referred to as mottled silty contourites commonly show bioturbational mottling to indistinct discontinuous lamination, and are gradationally interbedded with both muddy and sandy contourite facies. Sharp to irregular tops and bases of silty layers are common, together with thin lenses of coarser material. They have a poorly sorted clayey-sandy silt size and a mixed composition. Sandy Contourites
These occur as both thin irregular layers and as much thicker units within the finer-grained facies and are generally thoroughly bioturbated throughout. In some cases, rare primary horizontal and crosslamination is preserved (though partially destroyed by bioturbation), together with irregular erosional contacts and coarser concentrations or lags. The mean grain size is normally no greater than fine sand, and sorting is mostly poor due to bioturbational mixing, but more rarely clean and well-sorted sands occur. Both positive and negative grading may be present. A mixed terrigenous–biogenic composition is typical, with evidence of abrasion, fragmented bioclasts and iron oxide staining.
Contourite Sediment Facies Several different contourite facies can be recognized on the basis of variations in grain size and composition. These are listed and briefly described below and illustrated in Figure 5 and 6.
• • • • • •
Siliciclastic contourites (muddy, silty, sandy and gravel-rich variation) Shale-clast/shale-chip contourites (all compositions possible) Volcaniclastic contourites (muddy–silty–sandy variations) Calcareous biogenic contourites (calcilutite, -siltite, -arenite variations) Siliceous biogenic contourites (mainly sand grade) Manganiferous muddy contourites ( þ manganiferous nodules/pavements)
Gravel-rich Contourites
These are common in drifts at high latitudes as a result of input from ice-rafted material. Under relatively lowvelocity currents, the gravel and coarse sandy material remains as a passive input into the contourite sequence and is not subsequently reworked to any great extent by bottom currents. Gravel lags indicative of more extensive winnowing have been noted from both glacigenic contourites and from shallow straits, narrow moats, and passageways, where gravel pavements are
Muddy Contourites
These are homogeneous, poorly bedded and highly biouturbated, with rare primary lamination (partly destroyed by bioturbation), and irregular winnowed
ED Debris Flow
NQ
TWT 400 ms
P
SW
MRD
NQ
TWT 400 ms
P
SSF SWa
85
North-east Rockall Trough SSF BSD
ED
M MRD
Wyville-Thomson ridge NE
NQ P 10 km
BES 85 / 05-4
Figure 4 Seismic profiles of actual drift systems.
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TWT 1000 MS
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DEEP-SEA SEDIMENT DRIFTS
(A) Clastic contourites Muddy bioturbated trace lamination
(F) Biogenic contourites
(B)
(G)
Carbonate sand ± clean, laminated ± bioturbated
Silica sand ± clean, laminated ± bioturbated
Silty-muddy mottled irreg. layers bioturbated (C)
(H) Sandy bioturbated trace lamination
Biogenic mud/silt bioturbated trace lamination
(I) Chemogenic contourites
(D) Micro-brecciated shale-chip layer in muddy contourite
(E) Gravel-lag irregular, poorly-sorted reverse-graded ±muddy ±Fe Mn crust
Fe Mn-muddy contourites ± micronodules ± Fe Mn lamination ± Fe Mn pavements (J) 'Shallow-water' contourites Clastic +/or biogenic laminated and bioturbated. Gradational grainsize variation
Figure 5 Contourite facies models for clastic, biogenic, chemogenic, and ‘shallow-water’ contourites. (Reproduced from Stow et al., 1996.)
locally developed in response to high-velocity bottom current activity Shale-clast or Shale-chip Layers
These have been recognized in both muddy and sandy contourites from relatively few locations. They result from substrate erosion under relatively strong bottom currents, where erosion has led to a firmer substrate and in some cases burrowing on the omission surface has helped to break up the semi-firm muds. Calcareous and Siliceous Biogenic Contourites
These occur in regions of dominant pelagic biogenic input, including open ocean sites and beneath areas of upwelling. In most cases bedding is indistinct, but may be enhanced by cyclic variations in composition, and primary sedimentary structures are poorly developed or absent, in part due to thorough bioturbation as in siliciclastic contourites. In rare cases, the primary lamination appears to have been well preserved. The mean grain size is most commonly silty clay, clayey silt or muddy-sandy, poorly sorted and with a distinct sand-size fraction representing
the coarser biogenic particles that have not been too fragmented during transport. The composition is typically pelagic to hemipelagic, with nannofossils and foraminifera as dominant elements in the calcareous contourites and radiolaria or diatoms dominant in the siliceous facies. Many of the biogenic particles are fragmented and stained with either iron oxides or manganese dioxde. There is a variable admixture of terrigenous or volcaniclastic material. Manganiferous Contourites
These manganiferous or ferromanganiferous-rich horizons are common. This metal enrichment may occur as very fine dispersed particles, as a coating on individual particles of the background sediment, as fine encrusted horizons or laminae, or as micronodules. It has been observed in both muddy and biogenic contourites from several drifts. Bottom-current Influence
It is important to recognize that bottom currents will influence, to a greater or lesser extent, other deepwater sediments, particularly pelagic, hemipelagic,
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DEEP-SEA SEDIMENT DRIFTS
Figure 6 Photographs of contourite facies from cores drilled through existing drift systems. Vertical scales labelled in cm.
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DEEP-SEA SEDIMENT DRIFTS
turbiditic, and glacigenic, both during and after deposition. Where the influence is marked and deposition occurs in a drift, then the sediment is termed contourite. Where the influence is less severe, so that features of the original deposit type remain dominant, then the sediment is said to have been influenced by bottom currents, as in bottom-current reworked turbidites. Some more-laminated facies, as well as the thin, clean, cross-laminated sands originally described from the north-east American margin, are most likely of this type.
Contourite Sequences and Current Velocity Muddy, silty, and sandy contourites, of siliciclastic, volcaniclastic, or mixed composition, commonly Lithology and structure
occur in composite sequences or partial sequences a few decimeters in thickness. The ideal or complete sequence shows overall negative grading from muddy through silty to sandy contourites and then positive grading back through silty to muddy contourite facies (Figure 7). Such sequences of grain size and facies variation are now widely recognized, although not always fully developed, and are most probably related to long-term fluctuations in the mean current velocity. Not enough data exist to be certain of the timescale of these cycles, though some evidence points towards 5000–20 000 cycles for certain marginal drifts. The occurrence of widespread hiatuses in the deepocean sediment record is best related to episodes of particularly intense bottom currents. More locally,
Mean grain size 4 8 16 32 64 μm
Silt mottles and lenses irregular Horizontal alignment Bioturbated
Mottled silt and mud
Massive irregular sandy pockets Bioturbated Contacts sharp to gradational
Sandy silt
Silt mottles, lenses and irregular layers Bioturbated Contacts variable
Mottled silt and mud 10 (cm)
ease decr city Velo
Cross-laminated bioturbated
Silt
Maximum velocity
Bottom Velocit current y incre ase
Laminated
Positively graded
Bioturbated
Mud
Negatively graded
88
Bioturbated
Mud
0
Bioturbation Discontinuous silt lenses Gradational contact Sharp (irregular) contact Figure 7 Composite contourite facies model showing grain size variation through a mud–silt–sand contourite sequence. (Modified from Stow et al., 1996.)
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DEEP-SEA SEDIMENT DRIFTS
such strong currents result in significant sediment winnowing and the accumulation of sand, gravel, and shale-clast contourites. Thick units of sandy contourites together with sandy turbidites reworked by the bottom current are potentially important as hydrocarbon reservoirs where suitably buried in association with source rocks. Biogenic contourites typically occur in similar sequences of a decimetric scale that show distinct variation in biogenic/terrigenous ratio, generally linked to the grain size variation. This cyclic facies pattern has a longer timescale, in the few examples from which there is good dating, and is closely analogous to the Milankovitch cyclicity recognized in many pelagic and hemipelagic successions. It is, therefore, believed to be driven by the same mechanism of orbital forcing superimposed on changes in bottom-current velocity. The link between contourite sequences and changes in paleoclimate and paleocirculation is an extremely important one. Where such sequences can be correctly decoded then a more accurate understanding of the paleo-ocean and its environment can be built up.
See also Bottom Water Formation. Nepheloid Layers. Ocean Margin Sediments. Sea Level Change.
89
Further Reading Faugeres JC, Stow DAV, Imbert P, Viana A, and Wynn RB (1999) Seismic features diagnostic of contourite drifts. Marine Geology , 162: 1--38. Heezen BC, Hollister CD, and Ruddiman WF (1966) Shaping the continental rise by deep geostrophic contour currents. Science 152: 502--508. McCave IN, Manighetti B, and Robinson SG (1995) Sortable silt and fine sediment size/composition slicing: parameters for paleocurrent speed and paleoceanography. Paleoceanography 10: 593--610. Nowell ARM and Hollister CD (eds.) (1985) Deep ocean sediment transport – preliminary results of the high energy benthic boundary layer experiment. Marine Geology 66. Pickering KT, Hiscott RN, and Hein FJ (1989) DeepMarine Environments: Clastic Sedimentation and Tectonics. London: Unwin Hyman. Stow DAV and Faugeres JC (eds.) (1993) Contourites and Bottom Currents, Sedimentary Geology, Special Volume 82, 1--310. Stow DAV, Reading HG, Collinson J (1996) Deep seas. In: Reading HG (ed.) Sedimentary Environments and Facies. 3rd edn, pp. 380–442. Blackwell Science Publishers. Stow DAV and Faugeres JC (eds.) (1998) Contourites, turbidites and process interaction. Sedimentary Geology Special Issue 115. Stow DAV and Mayall M (eds.) (2000) Deep-water sedimentary systems: new models for the 21st century. Marine and Petroleum Geology, Special Volume 17.
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DEMERSAL SPECIES FISHERIES
This article is reproduced from the 1st edition of Encyclopedia of Ocean Sciences, volume 2, pp 718–725, & 2001, Elsevier Ltd.
Introduction Demersal fisheries use a wide variety of fishing methods to catch fish and shellfish on or close to the sea bed. Demersal fisheries are defined by the type of fishing activity, the gear used and the varieties of fish and shellfish which are caught. Catches from demersal fisheries make up a large proportion of the marine harvest used for human consumption and are the most valuable component of fisheries on continental shelves throughout the world. Demersal fisheries have been a major source of human nutrition and commerce for thousands of years. Models of papyrus pair trawlers were found in Egyptian graves dating back 3000 years. The intensity of fishing activity throughout the world, including demersal fisheries, has increased rapidly over the past century, with more fishing vessels, greater engine power, better fishing gear and improved navigational and fish finding aids. Many demersal fisheries are now overexploited and all are in need of careful assessment and management if they are to provide a sustainable harvest. Demersal fisheries are often contrasted with pelagic fisheries, which use different methods to catch fish in midwater and close to the water surface. Demersal species are also contrasted with pelagic species (see relevant sections), but the distinction between them is not always clear. Demersal species frequently occur in mid-water and pelagic species occur close to the seabed, so that ‘demersal’ species are frequently caught in ‘pelagic’ fisheries and ‘pelagic’ species in demersal fisheries. For example Atlantic cod (Gadus morhua), a typical ‘demersal’ species, occurs close to the seabed, but also throughout the water column and in some areas is caught equally in ‘demersal’ and ‘pelagic’ fishing gear. Atlantic herring (Clupea harengus), a typical pelagic species, is frequently caught on the seabed, when it forms large spawning concentrations as it lays its eggs on gravel banks. Total marine production rose steadily from less than 20 million tonnes (Mt) in 1950 to around 100 Mt during the late 1990s (Figure 1). The demersal
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100 80
Million tonnes
Copyright & 2001 Elsevier Ltd.
fish catch rose from just over 5 Mt in 1950 to around 20 Mt by the early 1970s and has since fluctuated around that level (Figure 2). The proportion of demersal fish in this total has therefore declined over the period 1970–1998. The products of demersal fisheries are mainly used for human consumption. The species caught tend to be relatively large and of high value compared with typical pelagic species, but there are exceptions to such generalizations. For example the industrial (fishmeal) fisheries of the North Sea, which take over
60 40 20
0
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19
60
90
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70
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19
19
19
Year Demersal fish
Pelagic fish
Molluscs
Crustaceans
Other fish Aquatic plants
Figure 1 Total marine landings.
20
Million tonnes
K. Brander, International Council for the Exploration of the Sea (ICES), Copenhagen, Denmark
15 10 5 0
50
19
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19
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19
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Year Other demersal Blue whiting
Argentine hake Atlantic cod
Figure 2 Total demersal fish landings.
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Sand eels Alaska pollock
DEMERSAL SPECIES FISHERIES
half of the total fish catch, are principally based on low-value demersal species which live in or close to the seabed (sand eels, small gadoids). Demersal fisheries are also often known as groundfish fisheries, but the terms are not exact equivalents because ‘groundfish’ excludes shellfish, which can properly be considered a part of the demersal catch. Shellfish such as shrimps and lobsters constitute the most valuable component of the demersal trawl catch in some areas.
Principal Species Caught in Demersal Fisheries For statistical, population dynamics and fisheries management purposes the catch of each species (or group of species) is recorded separately by FAO (UN Food and Agriculture Organization). The FAO definitions of species, categories and areas are used here. FAO groups the major commercial species into a number of categories, of which, the flatfish (flounders, halibuts, soles) and the shrimps and prawns are entirely demersal. The gadiforms (cods, hakes, haddocks) include some species which are entirely demersal (haddock) and others which are not (blue whiting). The lobsters are demersal, but most species are caught in special fisheries using traps. An exception is the Norway lobster, which is caught in directed trawl fisheries or as a by-catch, as well as being caught in traps.
Table 1
91
The five demersal marine fish with the highest average catches over the decade 1989–98 are Alaska (walleye) pollock, Atlantic cod, sand eels, blue whiting and Argentine hake. These species all spend a considerable proportion of their time in mid-water. Sand eels spend most of their lives on or in the seabed, but might not be regarded as a typical demersal species, being small, relatively short-lived and of low value. Sand eels and eight of the other 20 top ‘species’ in fact consist of more than one biological species, which are not identified separately in the FAO classification (Table 1). The vast majority of demersal fisheries take place on the continental shelves, at depths of less than 200 m. Fisheries for deep-sea species, down to several thousand meters, have only been undertaken for the past few decades, as the technology to do so developed and it became profitable to exploit other species. The species caught in demersal fisheries are often contrasted with pelagic species in textbooks and described as large, long-lived, high-value fish species, with relatively slow growth rates, low variability in recruitment and low mortality. There are so many exceptions to such generalizations that they are likely to be misleading. For example tuna and salmon are large, high-value pelagic species. Three of the main pelagic species in the North Atlantic (herring, mackerel and horse mackerel) are longer lived, have lower mortality rates and lower variability of recruitment than most demersal stocks in that area (Table 2).
Total world catch of 20 top demersal fish species (averaged from 1989–1998)
Common name
Scientific name
Tonnes
Alaska pollock Atlantic cod Sand eels Blue whiting Argentine hake Croakers, drums nei Pacific cod Saithe (Pollock) Sharks, rays, skates, etc. nei Atlantic redfishes nei Norway pout Flatfishes nei Haddock Cape hakes Blue grenadier Sea catfishes nei Atka mackerel Filefishes Patagonian grenadier South Pacific hake Threadfin breams nei
Theragra chalcogramma Gadus morhua Ammodytes spp. Micromesistius poutassou Merluccius hubbsi Sciaenidae Gadus macrocephalus Pollachius virens Elasmobranchii Sebastes spp. Trisopterus esmarkii Pleuronectiformes Melanogrammus aeglefinus Merluccius capensis, M. paradox Macruronus novaezelandiae Ariidae Pleurogrammus azonus Cantherhines ( ¼ Navodon) spp. Macruronus magellanicus Merluccius gayi Nemipterus spp.
3 182 645 2 317 261 1 003 343 628 918 526 573 492 528 425 467 385 227 337 819 318 383 299 145 289 551 273 459 266 854 255 421 242 815 237 843 234 446 230 221 197 911 186 201
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DEMERSAL SPECIES FISHERIES
Table 2 The intensity of fishing is expressed as the average (1988–1997) probability of being caught during the next year. The interannual variability in number of young fish is expressed as the coefficient of variation of recruitment. Species shown are some of the principal demersal and pelagic fish caught in the north-east Atlantic Probability of being Coefficient of variation caught during of recruitment next year Demersal species Cod Haddock Hake Plaice Saithe Sole Whiting
33–64% 19–52% 27% 32–48% 29–42% 28–37% 47–56%
38–65% 70–151% 33% 35–56% 45–56% 15–94% 41–61%
Pelagic species Herring Horse mackerel Mackerel
12–40% 16% 21%
56–63% 40% 41%
Fishing Gears and Fishing Operations A very wide range of fishing gear is used in demersal fisheries (see also Fishing Methods and Fishing Fleets), the main ones being bottom trawls of different kinds, which are dragged along the seabed behind a trawler. Other methods include seine nets, trammel nets, gill nets, set nets, baited lines and longlines, temporary or permanent traps and barriers. Some fisheries and fishermen concentrate exclusively on demersal fishing operations, but many alternate seasonally, or even within a single day’s fishing activity, between different methods. Fishing vessels may be designed specifically for demersal or pelagic fishing or may be multipurpose.
Effects of Demersal Fisheries on the Species They Exploit Most types of demersal fishing operation are nonselective in the sense that they catch a variety of different sizes and species, many of which are of no commercial value and are discarded. Stones, sponges, corals and other epibenthic organisms are frequently caught by bottom trawls and the action of the fishing gear also disturbs the seabed and the benthic community on and within it. Thus in addition to the intended catch, there is unintended disruption or destruction of marine life (see also Ecosystem Effects of Fishing)
The fact that demersal fishing methods are nonselective has important consequences when trying to limit their impact on marine life. There are direct impacts, when organisms are killed or disturbed by fishing, and indirect impacts, when the prey or predators of an organism are removed or its habitat is changed. The resilience or vulnerability of marine organisms to demersal fishing depends on their life history. In areas where intensive demersal fisheries have been operating for decades to centuries the more vulnerable species will have declined a long time ago, often before there were adequate records of their occurrence. For example, demersal fisheries caused a decline in the population of common skate (Raia batis) in the north-east Atlantic and barndoor skate (Raia laevis) in the north-west Atlantic, to the point where they are locally extinct in areas where they were previously common. These large species of elasmobranch have life histories which, in some respects, resemble marine mammals more than they do teleost fish. They do not mature until 11 years old, and lay only a small number of eggs each year. They are vulnerable to most kinds of demersal fishery, including trawls, seines, lines, and shrimp fisheries in shallow water. The selective (evolutionary) pressure exerted by fisheries favors the survival of species which are resilient and abundant. It is difficult to protect species with vulnerable life histories from demersal fisheries and they may be an inevitable casualty of fishing. Some gear modifications, such as separator panels may help and it may be possible to create refuges for vulnerable species through the use of large-scale marine protected areas. Until recently fisheries management ignored such vulnerable species and concentrated on the assessment and management of a few major commercial species. In areas with intensive demersal fisheries the probability that commercial-sized fish will be caught within one year is often greater than 50% and the fisheries therefore have a very great effect on the level and variability in abundance (Table 2). The effect of fishing explains much of the change in abundance of commercial species which has been observed during the few decades for which information is available and the effects of the environment, which are more difficult to estimate, are regarded as introducing ‘noise’, particularly in the survival of young fish. As the length of the observational time series increases and information about the effects of the environment on fish accumulates, it is becoming possible to turn more of the ‘noise’ into signal. It is no longer credible or sensible to ignore environmental effects when evaluating fluctuations in demersal fisheries, but a
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DEMERSAL SPECIES FISHERIES
Effects of the Environment on Demersal Fisheries
Rate (growth, reproduction)
The term ‘environment’ is used to include all the physical, chemical and biological factors external to the fish, which influence it. Temperature is one of the main environmental factors affecting marine species. Because fish and shellfish are ectotherms, the temperature of the water surrounding them (ambient temperature) governs the rates of their molecular, physiological and behavioral processes. The relationship between temperature and many of these rates processes (growth, reproductive output,
0
15 10 Temperature (˚C)
5
20
25
Landings in thousand tonnes
Figure 3 The relationship between temperature and many rate processes (growth, reproductive output, mortality) is domed. The optimum temperature is species and size specific.
mortality) is domed, with an optimum temperature, which is species and size specific (Figure 3). The effects of variability in temperature are therefore most easily detected at the extremes and apply to populations and fisheries as well as to processes within a single organism. Temperature change may cause particular species to become more or less abundant in the demersal fisheries of an area, without necessarily affecting the aggregate total yield. The cod (Gadus morhua) at Greenland is at the cold limit of its thermal range and provides a good example of the effects of the environment on a demersal fishery; the changes in the fishery for it during the twentieth century are mainly a consequence of changes in temperature (Figure 4). Cod were present only around the southern tip of Greenland until 1917, when a prolonged period of warming resulted in the poleward expansion of the range by about 1000 km during the 1920s and 1930s. Many other boreal marine species also extended their range at the same time and subsequently retreated during the late 1960s, when colder conditions returned. Changes in wind also affect demersal fish in many different ways. Increased wind speed causes mixing of the water column which alters plankton production. The probability of encounter between fish larvae and their prey is altered as turbulence increases. Changes in wind speed and direction affect the transport of water masses and hence of the planktonic stages of fish (eggs and larvae). For example, in some years a large proportion of the fish larvae on Georges Bank are transported into the Mid-Atlantic Bight instead of remaining on the Bank. In some areas, such as the Baltic, the salinity and oxygen levels are very dependent on inflow of oceanic water, which is largely wind driven. Salinity
500
3.0
400
2.5
300
2.0
200
1.5
100
1.0
0 1900
1920
1940
1960
1980
Temperature (˚C)
considerable scientific effort is still needed in order to include such information effectively.
93
0.5 2000
Figure 4 Cod catch and water temperature at West Greenland. Temperature is the running five-year mean of upper layer (0–40 m) values. , local catch 20; —— international catch; – – –, temperature.
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DEMERSAL SPECIES FISHERIES
and oxygen in turn affect the survival of cod eggs and larvae, with major consequences for the biomass of cod in the area. These environmental effects on the early life stages of demersal fish affect their survival and hence the numbers which recruit to the adult population.
World Catches from Demersal Fisheries and the Limits Demersal fisheries occur mainly on the continental shelves (i.e., at depths less than 200 m). This is because shelf areas are much more productive than the open oceans, but also because it is easier to fish at shallower depths, nearer to the coast. The average catch of demersal fish per unit area on northern hemisphere temperate shelves is twice as high as on southern hemisphere temperate shelves and more than five times higher than on tropical shelves (Figure 5). The difference is probably due to nutrient supply. The effects of differences in productive capacity of the biological system on potential yield from demersal fisheries are dealt with elsewhere (see also Ecosystem Effects of Fishing). Demersal fisheries provide the bulk of fish and shellfish for direct human consumption. The steady increase in the world catch of demersal fish species ended in the early 1970s and has fluctuated around 20 Mt since then (Figure 2). Many of the fisheries are overexploited and yields from them are declining. In a few cases it would seem that the decline has been arrested and the goal of managing for a sustainable harvest may be closer. 2.5
A recent analysis classified the top 200 marine fish species, accounting for 77% of world marine fish production, into four groups – undeveloped, developing, mature and declining (senescent). The proportional change in these groups over the second half of the twentieth century (Figure 6) shows how fishing has intensified, so that by 1994 35% of the fish stocks were in the declining phase, compared with 25% mature and 40% developing. Other analyses reach similar conclusions – that roughly twothirds of marine fish stocks are fully exploited or overexploited and that effective management is needed to stabilize current catch levels. Fish farming (aquaculture) is regarded as one of the principal means of increasing world fish production, but one should recall that a considerable proportion of the diet of farmed fish is supplied by demersal fisheries on species such as sand eel and Norway pout. Fishmeal is also used to feed terrestrial farmed animals.
Management of Demersal Fisheries The purposes of managing demersal fisheries can be categorized as biological, economic and social. Biological goals used to be set in terms of maximum sustainable yield of a few main species, but a broader and more cautious approach is now being introduced, which includes consideration of the ecosystem within which these species are produced and which takes account of the uncertainty in our assessment of the consequences of our activities. The formulation of biological goals is evolving, but even the most basic, such as avoiding extinction of species, are not being
Northern temperate
2.0 Southern temperate
t/km2
1.5
1.0
Tropical (and Mediterranean)
0.5
0.0 E E W W l. N tl. N c. N c. N A Pa Pa
At
W SE W l. S ac. c. S a P P
At
S C C C EC .E W IO IO. . + B c. E c. W l. W Atl. a a d P P e M
At
Figure 5 Demersal fish landings per unit area of continental shelf o200 m deep for the main temperate and tropical areas. The boxes show the spread between the upper and lower quartiles of annual landings and the whiskers show the highest and lowest annual landings 1950–1998. Atl, Atlantic; Pac, Pacific; IO, Indian Ocean; Med, Mediterranean; BS, Black Sea.
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DEMERSAL SPECIES FISHERIES
95
100 Phase IV _ Senescent
90
Percentage of resources
80 70
Phase III _ Mature
60 50 40
Phase II _ Developing
30 20
Phase I _ Undeveloped
1991
1993
1989
1987
1985
1981
1983
1977
1979
1975
1971
1973
1969
1967
1963
1965
1961
1957
1959
1953
1955
0
1951
10
Figure 6 Temporal change in the level of exploitation of the top 200 marine fish species, showing the progression from mainly undeveloped or developing in 1951 to mainly fully exploited or overexploited in 1994.
achieved in many cases. At a global level it is evident that economic goals are not being achieved, because the capital and operating costs of marine fisheries are about 1.8 times higher than the gross revenue. There are innumerable examples of adverse social impacts of changes in fisheries, often caused by the effects of larger, industrial fishing operations on the quality of life and standard of living of small-scale fishing communities. Clearly there is scope for improvement in fisheries management. From this rather pessimistic analysis of where fisheries management has got us to date, it follows that a description of existing management regimes is a record of current practice rather than a record of successful practice. Biological management of demersal fisheries has developed mainly from a single species ‘yield-perrecruit’ model of fish stocks. The output (yield) is controlled by adjusting the mortality and size of fish that are caught. Instruments for limiting fishing mortality are catch quotas (TAC, total allowable catch) and limits on fishing effort. Since it is much easier to define and measure catch than effort, the former is more widely used. In many shared, international fisheries, such as those governed by the European Union, the annual allocation of catch quotas is the main instrument of fisheries management. This requires costly annual assessment of many fish stocks, which must be added to the operating costs when looking at the economic balance for a fishery. Because annual assessments are costly, only
the most important species, which tend to be less vulnerable, are assessed. For example the US National Marine Fisheries Service estimate that the status of 64% of the stocks in their area of responsibility is unknown. The instruments for limiting the size of fish caught are mesh sizes, minimum landing sizes and various kinds of escape panels in the fishing gear. These instruments can be quite effective, particularly where catches are dominated by a single species. In multispecies fisheries, which catch species with different growth patterns, they are less effective because the optimal mesh size for one species is not optimal for all. There are two classes of economic instruments for fisheries management: (1) property rights and (2) corrective taxes and subsidies. The former demands less detailed information than the latter and may also lead to greater stakeholder participation in the management process, because it fosters a sense of ownership. The management of demersal fisheries will always be a complex problem, because the marine ecosystem is complicated and subject to change as the global environment changes. Management will always be based on incomplete information and understanding and imperfect management tools. A critical step towards better management would be to monitor performance in relation to the target objectives and provide feedback in order to improve the system. One of the changes which has taken place over the past few years is the adoption of the precautionary
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DEMERSAL SPECIES FISHERIES
approach. This seeks to evaluate the quality of the evidence, so that a cautious strategy is adopted when the evidence is weak. Whereas in the past such balance of evidence arguments were sometimes applied in order to avoid taking management action unless the evidence was strong (in order to avoid possible unnecessary disruption to the fishing industry), the presumption now is that in case of doubt it is the fish stocks rather than the short-term interests of the fishing industry which should be protected. This is a very significant change in attitude, which gives some grounds for optimism in the continuing struggle to achieve sustainable fisheries and healthy ecosystems.
Demersal Fisheries by Region The demersal fisheries of the world vary greatly in their history, fishing methods, principal species and management regimes and it is not possible to review all of these here. Instead one heavily exploited area with a long history (New England) and one less heavily exploited area with a short history (the south-west Atlantic) will be described.
continued. Most groundfish species remain at low levels and, even with management measures intended to rebuild the stocks, are likely to take more than a decade to recover. The changes in abundance of ‘traditional’ groundfish stocks (cod, haddock, redfish, winter flounder, yellowtail flounder) have to some extent been offset by increases in other species, including some elasmobranchs (sharks and rays). However, prolonged high levels of fishing have resulted in severe declines in the less resilient species of both elasmobranchs (e.g. barndoor skate) and teleosts (halibut, redfish). This is covered more fully elsewhere (see Ecosystem Effects of Fishing). The second half of the twentieth century saw major changes in the species composition of the US demersal fisheries. By the last decade of the century catches of the two top fish species during the decade 1950–59, redfish and haddock, had declined to 0.6% and 2.3% of their previous levels, respectively. Shellfish had become the main element of the demersal catch (Table 3).
New England Demersal Fisheries
Demersal Fisheries of the South-West Atlantic (FAO Statistical Area 41)
The groundfish resources of New England have been exploited for over 400 years and made an enormous contribution to the economic and cultural development of the USA since the time of the first European settlements. Until the early twentieth century, large fleets of schooners sailed from New England ports to fish, mainly for cod, from Cape Cod to the Grand Banks. The first steam-powered otter trawlers started to operate in 1906 and the introduction of better handling, preservation and distribution changed the market for fish and the species composition of the catch. Haddock became the principal target and their landings increased to over 100 000 t by the late 1920s. The advent of steam trawling raised concern about discarding and about the damage to the seabed and to benthic organisms. From the early 1960s fishing fleets from European and Asian countries began to take an increasing share of the groundfish resources off New England. The total groundfish landings rose from 200 000 t to 760 000 t between 1960 and 1965. This resulted in a steep decline in groundfish abundance and in 1970 a quota management scheme was introduced under the International Commission for Northwest Atlantic Fisheries (ICNAF). Extended jurisdiction ended the activities of distant water fleets, but was quickly followed by an expansion of the US fleet, so that although the period 1974–78 saw an increase in groundfish abundance, the decline subsequently
The catch from demersal fisheries in the SW Atlantic increased steadily from under 90 000 tonnes in 1950 to over 1.2 Mt in 1998 (Figure 7). The demersal catch consists mainly of fish species, of which Argentine hake has been predominant throughout the 50-year record. The catch of shrimps, prawns, lobsters and crabs is almost 100 000 t per year and they have a relatively high market value. Thirty countries have taken part in demersal fisheries in this area, the principal ones being Argentina, Brazil, and Uruguay, with a substantial and continuing component of East European effort. A three year ‘pulse’ of trawling by the USSR fleet resulted in a catch over 500 000 t of Argentine hake and over 100 000 t of demersal percomorphs in 1967. The fisheries in this area are mostly industrialized and long range. As the stocks on the continental shelf have become fully exploited, the fisheries have extended into deeper water, where they take pink cusk eel and Patagonian toothfish. The main coastal demersal species are whitemouth croaker, Argentine croaker and weakfishes. The Argentine hake fishery extends over most of the Patagonian shelf. It is now fully exploited and possibly even overexploited. Southern blue whiting and Patagonian grenadier are also close to full exploitation. Hake and other demersal species are regulated by annual TAC and minimum mesh size regulations.
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DEMERSAL SPECIES FISHERIES
Table 3
Average US catch from the north-west Atlantic region
Species
Scientific name
Atlantic redfishes nei Haddock Silver hake Atlantic cod Scup Saithe (Pollock) Yellowtail flounder Winter flounder Dogfish sharks nei Raja rays nei American angler American sea scallop Northern quahog (Hard clam) Atlantic surf clam Blue crab American lobster Sand gaper Ocean quahog
Average catch (t)
Sebastes spp Melanogrammus aeglefinus Merluccius bilinearis Gadus morhua Stenotomus chrysops Pollachius virens Limanda ferruginea Pseudopleuronectes americanus Squalidae Raja spp. Lophius americanus Placopecten magellanicus Mercenaria mercenaria Spisula solidissima Callinectes sapidus Homarus americanus Mya arenaria Arctica islandica
1950–59
1989–98
77 923 64 489 47 770 18 748 17 904 11 127 9103 7849 502 73 41 77 650 52 038 43 923 28 285 12 325 12 324 1139
518 1487 16 469 24 112 3846 6059 5085 5700 17 655 10 304 19 136 81 320 25 607 160 795 57 955 29 829 7739 179 312
then the catches from some stocks have declined, due to overfishing, while other previously underexploited stocks have increased their yields. The limits of biological production have probably been reached in many areas and careful management is needed in order to maintain the fisheries and to protect the ecosystems which support them.
1.4 1.2 1.0
Million tonnes
97
0.8 0.6 0.4
See also
0.2 0.0
50
19
60
19
70 19 Year
80
19
90
Ecosystem Effects of Fishing. Fishing Methods and Fishing Fleets.
19
Other demersal
Weakfishes nei
Patagonian grenadier
Whitemouth croaker
Southern blue whiting
Argentine hake
Figure 7 Total demersal fish landings from the south-west Atlantic (FAO Statistical area 41).
Conclusions Demersal fisheries have been a major source of protein for people all over the world for thousands of years. World catches increased rapidly during the first three-quarters of the twentieth century. Since
Further Reading Cochrane KL (2000) Reconciling sustainability, economic efficiency and equity in fisheries: the one that got away? Fish and Fisheries 1: 3--21. Cushing DH (1996) Towards a Science of Recruitment in Fish Populations. Ecology Institute, D-21385 Oldendorf/ Luhe, Germany. Gulland JA (1988) Fish Population Dynamics: The Implications for Management, 2nd edn Chichester: John Wiley. Kurlansky M (1997) Cod. A Biography of the Fish That Changed the World. London: Jonathan Cape.
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES M. Kucera, Eberhard Karls Universita¨t Tu¨bingen, Tu¨bingen, Germany & 2009 Elsevier Ltd. All rights reserved.
by the CLIMAP (Climate: Long Range Investigation Mapping and Prediction) group (Figure 1), the recognition of the pattern, rate, and magnitude of ocean cooling and warming during glacial cycles, and the determination of tropical and polar temperatures during supergreenhouse climates of the Mesozoic and early Cenozoic.
Introduction Temperature is one of the most striking aspects of the climate system. Its distribution on the surface of the Earth determines regional climate and habitability and its changes through time mirror the climatic evolution of our planet. The surface ocean represents the main reservoir of latent heat with ocean currents being the major means of heat redistribution at the Earth’s surface. In addition to the position of currents, sea surface temperature also reflects vertical mixing in the ocean, where upwelling brings deep cold waters to the surface. Clearly, knowledge of past variations in sea surface temperature (SST) and its spatial distribution is essential for the assessment of current warming trends as well as for the general understanding of the dynamic processes in the ocean and their links with global climate. Importantly, quantitative data on spatial and temporal distribution of past SST are instrumental for validation of numerical climate models. Unfortunately, direct instrumental measurements of SST are only available for the last two centuries. This time window is too short to assess the nature of natural variability and understand how the ocean and atmosphere systems behave under different climatic regimes. To know when, why, by how much, and how fast SST changes, scientists need long, continuous records spanning centuries to millions of years. Fortunately, SST affects a range of metabolic and thermodynamic processes that leave a distinct signature in biological materials. Some of these materials are preserved in the geological record and the signals locked in them can be decoded to estimate SST variation in the past. Unsurprisingly, reconstructing the temperature history of the surface ocean became one of the major tasks in geosciences and the last 50 years have seen the establishment of quantitative paleothermometry as the backbone of paleoceanography and paleoclimatology. Among the main achievements of SST paleothermometry are the reconstruction of the ocean surface during the Last Glacial Maximum
98
Characteristics of Sea Surface Temperature Before explaining the various paleothermometry methods, it is important to understand what is actually meant by SST. The surface ocean derives its temperature from solar insolation, whereas the temperature of the deep waters is relatively constant, preserving the SST signature at the place of their origin. At present, deep waters in the oceans are formed chiefly in polar and subpolar regions and their temperatures range between 0 and 4 1C. The resulting thermal gradient (Figure 2) implies that only a relatively shallow upper layer of the ocean retains the temperature of the ocean’s surface. The ‘mixed layer’ is homogenized by wave action and turbulence. Its depth is typically 50–100 m (Figure 3), although in summer during calm weather and due to intense heating, it can be only a few meters thin. Importantly, the mixed layer can be taken to roughly correspond to the photic zone, which means that phytoplankton and photosymbiotic organisms like corals and some planktonic foraminifera are likely to record the SST, whereas some zooplankton may live below the mixed layer, recording the temperature of the thermocline rather than the surface ocean (Figure 2). Due to the high thermal capacity of water, the range of surface ocean temperature is smaller than that of the atmosphere. At present, the coldest surface waters in polar oceans reach the freezing point of seawater at –1.7 1C while the highest surface temperatures of 32 1C are recorded in the Western Pacific Warm Pool. Seasonal variations in SST are also relatively muted, which makes the SST a good recorder of the mean state of the climate system. However, the magnitude of the seasonal signal (Figure 3) exceeds the precision of most methods for past SST determination and the difficulty in seasonal attribution of SST reconstructions is one of the main caveats in paleothermometry.
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
99
Sea ice 75° N Land ice
Sea ice (seasonal)
50° 25° 0 25° 50°
Sea ice 75° S
Land ice 150° W
100°
50°
−7.5
50°
0
−5.0
−2.5
0.0
100°
150° E
2.5
Temperature change (°C) Figure 1 The CLIMAP reconstruction of SST during the Last Glacial Maximum (c. 21 000 years ago), expressed as the difference between present-day and glacial values. The map represents one of the milestones of paleoceanography. It was derived from abundances of microfossil species in sediment cores using the transfer function method. Reproduced from Mix A, Bard E, and Schneider R (2001) Environmental processes of the ice age: Land, oceans, glaciers (EPILOG). Quaternary Science Reviews 20: 627–657, with permission from Elsevier. Data from CLIMAP Project Members (1976) The surface of the ice-age Earth. Science 191: 1131–1137.
Recorders of SST signature
Idealized SST profile
Coral reefs
∼∼ ∼∼
25 °C
100 m 150 m ∼∼ ∼∼ Zooplankton
Geological archives of past sea surface temperature
15
Mixed layer
50 m Phytoplankton
Photic zone
Hermatypic corals
5
Thermocline
∼∼ ∼∼ ∼∼ ∼∼
2000 m 3000 m 4000 m
Deep-sea sediments Figure 2 An idealized scheme of the habitats of SST signal carriers and the occurrence of geological archives of SST. Hermatypic corals and phytoplankton grow only in the photic zone, which normally overlaps with the mixed layer. Some zooplankton species live below the photic zone and record thermocline temperatures rather than SST.
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100
DETERMINATION OF PAST SEA SURFACE TEMPERATURES
Average yearly SST variation off Puerto Rico 29.0 0m 28.5
10 m 20 m 30 m
28.0
50 m SST (°C)
75 m 27.5
27.0
26.5
26.0
25.5 Jan.
Feb.
Mar.
Apr.
May
Jun.
Jul.
Aug.
Sep.
Oct.
Nov.
Dec.
Month of year Figure 3 A typical tropical mean annual SST record for different depths. The temperature of the Caribbean Sea off Puerto Rico varies by 42 1C throughout the year; the thickness of the mixed layer varies between 450 m in winter and c. 30 m in summer. Data from the Comprehensive Ocean–Atmosphere Data Set (COADS).
Methods for Determination of Past Sea Surface Temperatures Nature of the Sea Surface Temperature Signal in Geological Materials
Many properties of marine organisms are affected by their chemical and physical environment. For SST reconstructions, the most significant are kinetic processes that alter the rate of incorporation of trace elements and isotopes into biominerals, metabolic regulation of the composition of cellular membranes, and temperature-driven changes in species abundance (Table 1). These various signals locked in fossil materials are not directly related to individual environmental parameters. Therefore, a whole branch of paleoceanography has been established to develop and test proxies – recipes and algorithms describing ways of how to relate measurements and observations made on fossils and other geological material to past environmental variables. Paleothermometry is the branch of paleoceanography devoted to the development of proxies for the reconstruction of past ocean temperatures. At present, only two archives have the capacity to provide long and continuous records of past SST: marine sediments and coral colonies (Figure 2). Deep-
sea sediments are particularly suitable as SST archives because they are often undisturbed and accumulate continuously for millions of years. Marine sediments are sampled by coring or drilling and SST signals are extracted from mineral or organic remains of planktonic microorganisms that lived in the surface ocean above the site of deposition. Strictly speaking, the SST signal is not in situ, because the plankton remains were transported to the seafloor by sinking through several kilometers of overlaying water. The degree of potential lateral displacement of the signal depends on the size of the signal carrier: small organic-walled microfossils and organic compounds are more easily transported than shells of planktonic foraminifera (Figure 4) or microfossils carried down in fecal pellets. SST records in marine sediments have typically centennial and rarely decadal resolution. The skeletons of hermatypic corals grow by accretion and like tree rings they record with high resolution the conditions of the surface ocean. Hermatypic corals are restricted to the tropical oceans with normal salinity where water temperature exceeds 25 1C. The vast majority of reef-building corals (such as the genus Porites) harbor photosymbiotic algae and are thus limited to the photic zone (Figure 2). Individual coral records recovered from cores drilled into living or fossil submerged coral heads are typically only a few
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
Table 1
101
Parameters of the main methods used to determine past sea surface temperatures
Method
Substrate
SST rangea
Typical standard error ( 1C)
Temporal applicability
Regional applicability
Oxygen isotopes in planktonic foraminifera Mg/Ca in planktonic foraminifera
Foraminiferal calcite
2 1C to no upper limit B5 1C to no upper limit
0.5b
0–120 Myc
All oceans
1
0–120 Myd
Mostly tropical waters, no upper limit Best performance between 5 and 27 1C 0–28 1C 428 1Ch
0.5b
0–130 ky
All oceans, best performance in Tropics Mainly Tropics
1.5
0–5 Mye
2
0–120 Myf
5–30 1C
1–1.5
0–500 kyg
Radiolaria
0–30 1C
1–1.5
0–500 kyg
Diatoms
2 to 18 1C
1–1.5
0–500 kyg
Dinoflagellate cysts
2 to 22 1C
1.5–2
0–500 kyg
Foraminiferal calcite
Oxygen isotopes and Sr/ Ca in corals
Sclearctinian aragonite
Alkenone unsaturation k0 ) (U37
Haptophyte alkenones in sediments Crenarchaeotal membrane lipids in sediments Planktonic foraminifera
Tetraether index (TEX86)
Transfer functions
All oceans except those of polar regions All oceans, possibly also lakes All oceans except those of polar regions All oceans except those of polar regions Polar to transitional waters All oceans except those of deep oligotrophic basins
a
Mean annual SST. Provided the isotopic and trace element composition of seawater is known. c In sediments older than c. 25 My in pristine preservation only. d In sediments older than c. 5 My, unknown species offsets and Mg content of the ocean may cause significant bias. e Ecology of pre-Quaternary alkenone-producing haptophytes is unknown. f Possibly older, if well-preserved lipids are found. g Estimate based on the age of the modern planktonic foraminifer fauna; older applications are problematic. h Several alternative calibrations are used for SST 4 28 1C b
centuries long. However, depending on the growth rate, they can provide yearly or even monthly resolution and data from several heads can be stacked to develop longer, regional records.
Paleothermometers Based on Chemical Signals in Biominerals
Oxygen isotopes in planktonic foraminifera Measurement of oxygen isotopic composition of marine biogenic carbonates provided geoscientists and paleoceanographers with the first quantitative paleothermometer. The method is based on the discovery by the American physicist and Nobel Prize laureate Harold Urey that during precipitation of calcite from seawater, a thermodynamic fractionation occurs between the two main stable isotopes of oxygen, 16O and 18O, and that this fractionation is a logarithmic function of temperature. The technique was originally calibrated on mollusk shells, but since
the pioneering work of Cesare Emiliani in the 1950s, planktonic foraminifera (Figure 4) became the prime target for oxygen isotope paleothermometry in oceanic sediments. The oxygen isotopic composition of foraminiferal shells is determined by mass spectrometry of CO2 evolved by acid digestion of foraminiferal calcite. Although modern analytical methods allow measurements of oxygen isotopes in single shells, a standard analysis requires about 10–20 specimens, in order to obtain a representative average of the conditions integrated in a fossil sample. The oxygen isotopic composition of foraminiferal calcite is expressed as a deviation, in per mille, from a standard (normally V-PDB): 2 6 d18 O ¼ 4
18
3 O=16 O 18 O=16 O standard 7 sample 5 103 18 O=16 O
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standard
½1
102
DETERMINATION OF PAST SEA SURFACE TEMPERATURES
Figure 4 Shells of planktonic foraminifera from a Caribbean surface sediment sample. Foraminifera are the main substrate for geochemical and transfer function paleothermometry. The shells have been extracted by washing and sieving of the sediments through a 0.15-mm mesh. The image is 4 mm across.
The determination of past SST from oxygen isotopes requires a priori knowledge of the isotopic composition of ambient seawater. When this is known, empirical calibrations from culture experiments or surface sediments can be used to derive paleotemperature equations for different species and SST ranges. These equations usually take on a secondorder polynomial form; the Shackleton calibration is perhaps the most commonly used: Tcalcification ½1C ¼ 16:9 4:38 d18 Ocalcite d18 Oseawater 2 þ 0:1 d18 Ocalcite d18 Oseawater ½2 Given the high analytical precision of oxygen isotope measurements (o0.1%), the method allows SST reconstruction with the precision of 0.5–1 1C. However, the biomineralization of calcite by foraminifera is affected by a range of secondary factors and the d18O composition of seawater in the past must be estimated from a number of assumptions.
The two main factors influencing d18Oseawater are the global ice volume and the local precipitation/ evaporation (P/E) balance. Due to fractionation during water phase transitions, continental ice is depleted in the heavy isotope, leaving the seawater isotopically heavy. Similarly, during evaporation, the light isotope preferentially enters the gaseous phase, making water vapor and precipitation isotopically light. The P/E effect is also known as the salinity effect, because seawater salinity is affected by the P/E balance in a similar way as its oxygen isotopic composition. The combined effect of ice volume and P/E balance on d18O in foraminifera can be substantially larger than that of SST, making paleotemperature reconstructions from foraminiferal d18O rather difficult. In fact, the d18O method is now used predominantly to reconstruct the isotopic composition of seawater and, if available, other paleothermometers are preferred. Planktonic foraminifera are heterotrophic zooplankton and their habitat is not limited to the surface mixed layer (Figure 2). Each species calcifies at specific depths, often below the mixed layer, and
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
Mg/Ca in planktonic foraminifera The amount of trace elements incorporated into inorganically precipitated calcite depends chiefly on their concentration in the solution from which the mineral grows. However, the rate of cation substitution in calcite also depends on temperature. This latter effect is particularly pronounced for magnesium and forms the basis of the Mg/Ca paleothermometer. The substitution of magnesium for calcium in calcite is endothermic and both thermodynamic calculations and experimental data confirm that Mg/Ca of inorganically precipitated calcite increases by 3% per 1C. A similar phenomenon is observed in biologically precipitated calcite produced by a range of organisms, although the actual relationship between Mg/Ca and SST is often offset from the thermodynamic prediction. In oceanic sediments, shells of planktonic foraminifera offer the best source of calcite for Mg/Ca paleothermometry. Planktonic foraminiferal shells are composed of low-magnesium calcite and contain several times less magnesium (o1% Mg) compared to inorganic calcite precipitated at the same conditions. The response of foraminiferal Mg/Ca to increasing SST is 9% per 1C, that is, 3 times larger than the thermodynamic prediction. The reason for the latter effect is not known, although it is likely to be related to the lower Mg/Ca content of foraminiferal calcite. No matter what its cause, the larger response of foraminiferal Mg/Ca to SST change is extremely important for paleothermometry as it increases the sensitivity of the method and reduces the uncertainty of Mg/Ca-derived SST reconstructions.
Following the thermodynamic prediction, the relationship between Mg/Ca in foraminiferal calcite and calcification temperature is expressed as an exponential function: h i Mg=Ca mmol mol1 ¼ b emTcalcification ½1C
½3
After a rigorous cleaning to remove Mg from adhering sediment, organic matter, and secondary precipitates, the magnesium content of foraminiferal shells is routinely determined by inductively coupled plasma mass spectrometry (ICP-MS) or atomic emission spectrometry (ICP-AES). Both techniques provide a precision of Mg/Ca ratio measurements of the order 0.5%. Data from laboratory cultures as well as calibrations from sediments and watercolumn samples converge on the value of m being between 10.7% and 8.8%. The pre-exponential term b appears more variable, ranging between 0.30 and 0.53. The parameters of the equation vary depending on which species is analyzed and how the calcification temperature is determined. An extensive calibration based on foraminifera from sediment traps (Figure 5) yielded the following conversion 6
5 Mg/Ca (mmol/mol)
maximum production occurs at specific times of the year. In addition, the presence of symbiotic algae in some species offsets the d18O signal, as do changes in growth rate, addition of gametogenic calcite at depth, carbonate ion concentration in seawater, and various other ‘vital effects’. Dissolution appears to increase d18O in foraminifera by about 0.2% per kilometer water depth, but this effect is relatively easy to contain. On geological scales, foraminiferal calcite is gradually recrystallized during burial in the sediment and the secondary calcite assumes the isotopic composition of inorganic precipitate from pore water fluid. Foraminiferal d18O paleothermometry in Cretaceous and Paleogene sediments appears only feasible on pristinely preserved shells recovered from clay-rich sediments. Although the method is no longer seen as the prime SST paleothermometer, the development of independent methods based on the same signal carrier (Mg/Ca, transfer functions) provides an exciting opportunity to subtract the SST contribution to foraminiferal d18O and reconstruct more precisely than before the d18O of seawater.
103
4
3
G. truncatulinoides G. trilobus G. sacculifer G. ruber (white) G. ruber (pink) P. obliquiloculata G. inflata G. hirsuta N. dutertrei G. crassaformis G. conglobatus
2
1 10
15
20 Temperature (°C)
25
30
Figure 5 The relationship between calcification temperature (inferred from oxygen isotopes) and Mg/Ca in a range of planktonic foraminifera species from a Bermuda sediment trap. For most species, the global calibration expressed in eqn [4] can be used, yielding a standard error of 1.5 1C. Modified from Barker S, Cacho I, Benway HM, and Tachikawa K (2005) Planktonic foraminiferal Mg/Ca as a proxy for past oceanic temperatures: A methodological overview and data compilation for the Last Glacial Maximum. Quaternary Science Reviews 24: 821–834. Data from Anand P, Elderfield H, and Conte MH (2003) Calibration of Mg/Ca thermometry in planktonic foraminifera from a sediment trap time series. Paleoceanography 18: 1050, with permission from Elsevier.
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
equation, which appears to be applicable globally and across a range of species: Tcalcification ½1C ¼
1 0:09
h i1 Mg=Ca mmol mol1 A ½4 ln@ 0:38 0
The standard error of foraminiferal Mg/Ca calibrations is typically around 1 1C. Because of the exponential nature of the conversion equations, the sensitivity of the Mg/Ca paleothermometer decreases with temperature. The method is thus less suitable for SST reconstructions in subpolar and polar waters, whereas its sensitivity is higher in the Tropics where it ought to yield robust reconstructions even when past tropical SST was higher than today. As discussed in the previous section, planktonic foraminifera migrate through the water column during life and different parts of the shell calcify at different depths, often within or even below the thermocline. In order to circumvent this problem, Mg/Ca paleothermometry generally focuses on surface-dwelling species, which spend most of their life within the mixed layer: Globigerinoides ruber, Globigerinoides sacculifer, and Globigerina bulloides. The sedimentary Mg/Ca signal is typically derived by a pooled analysis of 10–50 shells and is therefore biased toward the season of highest production of the analyzed species. The effect of salinity on foraminiferal Mg/Ca (for the range of normal marine conditions) is believed to correspond to 0.6–0.8 1C per psu; the effect of surface ocean pH is c. –0.6 1C per 0.1 pH units. Both these effects are relatively small and affect Mg/Ca SST reconstructions only in extreme environments or on geological timescales. On these timescales, the possibility of changes in oceanic Mg/Ca must be considered as well. By far the largest secondary effect on Mg in foraminiferal shells is that of carbonate dissolution. Mg is preferentially removed from calcite during dissolution, and in foraminifera sinking through the water column and on the seafloor, this effect translates to about 0.4–0.6 1C loss per km or 2.8 1C loss per km of lysocline shift. With some effort, the influence of carbonate dissolution on Mg/Ca SST reconstructions can be quantified and it is generally assumed that in normal marine sediments, the maximum bias on the three commonly used species is of the order of 0.5 1C. Foraminiferal Mg/Ca paleothermometry is analytically relatively straightforward and offers the possibility to determine past SST from the same
phase as oxygen isotopes. This provides a powerful means for subtracting the temperature signal obtained from Mg/Ca measurements from the d18O signal in foraminifera, allowing reconstructions of past seawater isotopic composition and assessment of phase relationships between SST and ice sheet dynamics in the past. The greatest advantage of the Mg/Ca method is its high sensitivity at warm SST with no upper limit to reconstructed SST values. Therefore, Mg/Ca in planktonic foraminifera is currently considered the best paleothermometer for the Tropics. Sr/Ca and oxygen isotopes in hermatypic corals Skeletons of hermatypic corals also offer a possibility to obtain long continuous records of past SST variability. Unlike planktonic foraminifera, scleractinian corals produce aragonite, which is the rhombohedric variety of calcium carbonate. Elemental and isotopic substitutions in aragonite are also controlled by temperature and both the d18O and Sr/Ca of coral skeletons record SST. The d18O signal in scleractinian aragonite follows the slope of the relationship derived from inorganic precipitation experiments, but the curve is offset from equilibrium. The offset is presumably due to biological ‘vital effects’ such as growth rate or symbiont activity, and it appears to vary even within individual coral colonies. In order to convert coral d18O to past SST, the d18O of seawater must be known. The combined influence of the vital effect and uncertainties in the determination of seawater d18O make the coral d18O signal very difficult to deconvolve and the signal is thus often interpreted as a generalized ‘climate’ record, rather than SST. The Sr content of inorganically precipitated aragonite is an exponential function of temperature, but the exponential constant is small (–0.45% per 1C), and within the range of marine tropical SST, the relationship is often described as a linear function. The substitution reaction is exothermic, favoring Sr substitution at lower SST. Coralline Sr/Ca is determined by atomic absorption spectrophotometry (AAS) and the standard error of empirical calibrations is around 0.5 1C. However, recent studies indicate that the Sr content of coralline aragonite also responds to a number of secondary effects including symbiont activity, and the slope of empirical calibrations shows a large variability. In addition, the Sr/Ca paleothermometer may be affected on glacial/interglacial and longer timescales by secular changes of the Sr content of seawater. In comparison with calcite, aragonite is much more susceptible to dissolution and alteration, especially when exposed to meteoric waters. Both the
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
d18O and Sr/Ca signals are heavily altered during this process and the applicability of coral paleothermometry on uplifted reefs is severely reduced. The best coral climatic records are therefore derived from submerged corals. Coral paleothermometry is obviously limited to the Tropics, where hermatypic corals occur, and it provides an important means of studying tropical climate variability. Due to the high resolution of the records, climate data extracted from corals have provided fascinating insights into decadal dynamics of tropical oceans. It is, however, not always possible to separate the SST component in the d18O and Sr/Ca signals in coral skeletons and the method is therefore more useful when seen as recording the combined effect of SST, P/E balance, and seawater chemistry. Paleothermometers Based on Organic Biomarkers in Sediments 0
k Alkenone unsaturation (U37 ) The alkenone k0 (Uk standing for ‘unsatuunsaturation index U37 rated ketones’) is the main organic biomarker proxy for SST. It is based on the measurement of the relative abundance in marine sediments of unbranched long-chained methyl ketones with 37 carbon atoms (C37) and a variable number of double bonds. C37 alkenones, together with C38 and C39 alkenones, their fatty acid methyl esters (alkenoates), and alkenes, are specific for certain species of haptophyte algae, including one of the main primary producers in the oceans, the bloomforming Emiliania huxleyi (Figure 6). These molecules are chemically inert and survive transport throughout the water column as well as burial in marine sediments, where they are known to persist for millions of years, in concentrations ranging
105
typically between 0.1 and 10 ppm. The abundance of the individual compounds is determined from total lipid extracts or purified lipid fractions by high-temperature elution gas chromatography. Each analysis requires between 1 and 10 g of dry sediment. Current technology allows determination of the unsaturation index in all marine sediments, except where virtually no organic matter is preserved. The function of the long-chained alkenones is not fully understood. The high abundance of these compounds in the haptophyte algae (up to 10% of cellular carbon) indicates that they play a significant role in the cellular structure. It has been suggested that alkenones may serve as storage molecules or that they may be incorporated into the cellular membrane where they act as fluidity regulators. The latter hypothesis links alkenone unsaturation directly with growth temperature and provides a mechanistic explanation for the striking relationship between the degree of unsaturation and temperature, observed in C37 alkenone extracts from surface sediment samples and from laboratory cultures. The degree of unsaturation has been originally expressed as a ratio between the quantities of the di- (C37:2), tri- (C37:3), and tetra- (C37:4) unsaturated C37 alkenones: k U37 ¼
½C37:2 C37:4 ½C37:2 þ C37:3 þ C37:4
½5
It was later shown that there is no benefit in including the C37:4 alkenone and the currently used version of the index is marked by a prime: 0
k ¼ U37
½C37:2 ½C37:2 þ C37:3
½6
O
C37:2 heptatriaconta-15E,22E-dien-2-one O C37:3 heptatriaconta-8E,15E,22E-trien-2-one O 2 µm
C37:4 heptatriaconta-8E,15E,22E,29E-tetraen-2-one
Figure 6 Scanning electron micrograph (SEM; in false color) of a single cell of the alkenone-producing haptophyte alga Emiliania huxleyi. The cell is covered by a mineral skeleton (coccosphere), consisting of isolated interlocking plates (coccoliths). The structures k0 paleotemperature index are shown to the of the three unsaturated alkenones produced by this species and used to calculate the U37 right. SEM image courtesy of Dr. Marcus Geisen and Dr. Claudia Sprengel, Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany.
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
1.0 0.9 0.8 0.7
K′ U37
0.6 Atlantic
0.5
Indian
0.4 Pacific
0.3 0.2
Atlantic Ocean Indian Ocean Pacific Ocean
0.1 0.0 0
5
10 15 20 25 Annual mean SST, 0 m (°C)
30
Figure 7 Empirical calibration of mean annual SST at 0-m k0 determined in 149 depth and the alkenone unsaturation index U37 globally distributed surface sediment samples. Thick line shows the global regression as expressed in eqn [7]; standard error of the regression is 1.5 1C. Reproduced from Mu¨ller PJ, Kirst G, Ruhland G, von Storch I, and Rosell-Mele´ A (1998) Calibration of k0 based on core-tops the alkenone paleotemperature index U37 from the eastern South Atlantic and the global ocean (601 N– 601 S). Geochimica et Cosmochimica Acta 62: 1757–1772, with permission from Elsevier.
This modified index shows a strong and consistent linear relationship with SST (Figure 7). Empirical calibrations in surface sediment samples yielded the following conversion equation between the unsaturation index and annual mean SST at 0-m depth: 0 k 0:044 =0:033 SST0 m ½1C ¼ U37
½7
The form of this equation has been confirmed by laboratory culture studies as well as measurements of particulate organic matter in the water column. The standard error of the empirical calibration is about 1.5 1C and the method appears to work best in the SST range between 5 and 27 1C. The alkenone content of marine sediments is the result of many years of integration of alkenone production over the site of deposition. Therefore, the signal should be biased toward the preferred depth and season of growth of the haptophyte algae. It has been repeatedly demonstrated that the alkenone unsaturation index measured in surface sediments shows a stronger correlation with annual mean SST at 0-m depth than for any other depth and season. Consequently, past SST reconstructions based on alkenone unsaturation in fossil sediments are
interpreted as reflecting annual mean values at the ocean surface. Like all other algae, haptophytes are dependent on photosynthesis and their growth occurs within the photic zone (Figure 2). Therefore, the alkenone unsaturation signal records the conditions within or near the mixed layer and this conjecture ought to remain valid for as long as the haptophytes were the sole producers of the alkenones. The main production of haptophyte algae occurs in spring or in autumn. The temperature of these seasons is comparable to the annual average, explaining the best fit of sedimentary unsaturation values with mean annual SST. However, in the absence of information on the ecology of the alkenone producers in the past, interpretations of alkenone unsaturation values in fossil sediments as reflecting past SST for a specific season remain speculative. The modern alkenoneproducing species evolved during the late Quaternary (within the last 1 My) and ecological shifts could be significant for the interpretation of older alkenone signals, particularly at high latitudes where seasonal differences in SST are large. Apart from changes to vertical and seasonal production of the alkenones, the unsaturation signal appears robust to the usual sources of bias. Alkenones are recalcitrant to diagenesis and reworking of older alkenones has been found significant only in rare circumstances, such as in the polar waters where the primary production by the haptophytes was low, particularly during glacial times. Similarly, there is little evidence that the signal is affected by other environmental parameters such as productivity or salinity (within the range of normal oceanic values). To conclude, the fortuitous discovery by the Bristol organic geochemistry group in 1986 of the strong relationship between alkenone unsaturation and SST has survived extensive scrutiny and the unsaturation index remains one of the most robust means for determination of past SST in marine sediments. Crenarchaeotal membrane lipids (TEX86) The relatively novel biomarker paleothermometer TEX86 is based on the abundance of different types of crenarchaeotal membrane lipids called glycerol dialkyl glycerol tetraethers (GDGTs) in sediments. The presence of cyclopentane rings in the GDGT lipids of hyperthermophilic Crenarchaeota increases the thermal transition point of the membrane (the temperature beyond which the membrane loses its biological functionality) and the number of such rings in crenarchaeotal GDGT is known from laboratory cultures to increase with temperature. The kingdom Crenarchaeota of the domain Archaea
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
was long believed to include exclusively hyperthermophilic organisms, but recent studies showed that one group of Crenarchaeota is abundant in the upper water column of the oceans, where it may make up a significant portion of the picoplankton. Oceanic crenarchaeota also synthesize GDGT lipids
107
and the proportions of four types of GDGT molecules with 86 carbon atoms and different numbers of cyclopentane rings correlates with SST (Figure 8). Empirical calibration of GDGT abundance in surface sediments led to the definition of the TEX86
HO O O O
O
OH
I HO O O
O
O OH
II HO O O
O
O III
OH
0.90 0.80
TEX86
0.70 0.60 0.50 0.40 0.30 0.20
0
5
10
15 20 Annual mean SST (°C)
25
30
Figure 8 Empirical calibration of mean annual SST at 0 m depth and the crenarchaeotal membrane lipid index TEX86 determined in 40 globally distributed surface sediment samples. The thick lines show the linear regression expressed in eqn [9]; the standard error is 2 1C. The structure of the GDGTs is shown; roman numerals refer to the number of cyclopentane rings. The structure of the GDGTIV is not yet known. Modified from Schouten S, Hopmans EC, SchefuX E, and Sinninghe Damste´ JS (2002) Distributional variations in marine crenarchaeotal membrane lipids: A new tool for reconstructing ancient sea water temperatures? Earth and Planetary Science Letters 204: 265–274, with permission from Elsevier.
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
‘tetraether index of lipids with 86 carbon atoms’: TEX86 ¼
ð½GDGTII þ ½GDGTIII þ ½GDGTIV0 Þ ð½GDGTI þ ½GDGTII þ ½GDGTIII þ ½GDGTIV0 Þ ½8
This index is highly correlated with annual mean SST at 0-m depth and for SST range 0–28 1C the following conversion can be used: SST0 m ½1C ¼ ðTEX86 0:28Þ=0:015
½9
The abundance of the different GDGT types (Figure 8) is determined from total lipid extracts by highperformance liquid chromatography/atmospheric pressure positive ion chemical ionization mass spectrometry (HPLC/APCI-MS). The combined uncertainty in TEX86 SST reconstructions due to the standard error of the calibration and the analytical error is less than 2 1C. The TEX86 technique was first described in 2002 and there are many aspects of the method that require further investigation. The effects of secondary parameters like salinity and productivity are not known and it is not clear why the index correlates best with annual mean SST at 0-m depth, when the GDGT producing Crenarchaeota are known to inhabit the top 500 m of the water column. The abundance of marine Crenarchaeota is negatively correlated with that of algal phytoplankton and the GDGT lipids deposited on the seafloor should represent different seasons than those when algal blooms occur. On the other hand, the application of the TEX86 technique is not restricted to the oceanic environments. First results indicate that a similar relationship between SST and GDGT abundance also holds for lake sediments. Like alkenones, the TEX86 proxy can be used in carbonate-free sediments, and it additionally offers the possibility of reconstructing SST in very old sediments. The GDGT-producing Crenarchaeota are most likely ancient and measurable amounts of the GDGT lipids have been found in sediments older than 100 My. Paleothermometers Based on the Composition of Fossil Assemblages
Principles of transfer functions Temperature is one of the most important factors controlling the distribution and abundance of species of marine phyto- and zooplankton (Figure 9). Assemblage composition in those groups of plankton that leave a fossil record can therefore be used as a means to reconstruct past SST variation. In order to obtain quantitative, calibrated
reconstructions of past SST, microfossil assemblages are extracted from surface sediments, abundance of individual species is determined, and the data are linked to a long-term average SST above the site of their deposition. The relationship between the assemblage composition and SST is described in the form of the so-called transfer functions. Transfer functions are empirically calibrated mathematical formulas or algorithms that serve to optimally extract the general relationship between microfossil assemblage composition in sediment samples and environmental conditions in the surface ocean. Assuming that SST changes in the past were manifested mainly through zonal redistribution of microfossil assemblages, a transfer function derived from modern sediments can then be used to convert assemblage composition data from fossil samples to SST reconstructions (Figure 10). Unfortunately, this assumption is not always met and many fossil samples yield microfossil assemblages without analogs in the modern ocean. Such assemblages may reflect secondary alteration or reworking as well as no-analog oceanographic conditions in the past. No-analog assemblages are typically easy to recognize, but their use for SST reconstructions is always problematic. The potential of the transfer function technique in providing calibrated paleoenvironmental reconstructions has been realized in 1976 by the CLIMAP project in the seminal paper on SSTs of the Last Glacial Maximum. Ever since, transfer functions have become a standard method in paleothermometry, applicable in virtually all marine sediments and extendable to variables other than SST. The calibration of a transfer function requires a large database of census counts from surface sediments, including typically 100–1000 samples with counts of 20–50 species. The data set may be global or regional. Like any other empirical calibration, transfer functions rely on a number of assumptions (Figure 10). Unlike geochemical paleothermometers, transfer functions are robust to mild diagenesis, require no cleaning or chemical extraction, and can be relatively cheap and fast. However, they rely on the exact knowledge of species ecology and their use is thus limited to the late Quaternary (B0.1–0.5 My). Theoretically, transfer functions can be calibrated to SST representing any depth and season. In most cases, a temperature characteristic of the mean annual conditions in the mixed layer is used, as well as the winter and summer seasonal averages. However, a simultaneous reconstruction of summer and winter SST by the transfer function method does not equate to the reconstruction of a seasonal contrast in the past. The simultaneous reconstruction of several SST representations is only possible because all SST
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
109
90 G. ruber 80
Relative abundance (%)
70
60
T. quinqueloba
50
40
30
20
10
0 0
4
8
12
16
20
24
28
Annual average sea surface temperature (°C)
Figure 9 Relative abundance of two species of planktonic foraminifera (Turborotalita quinqueloba and Globigerinoides ruber) vs. mean annual SST at 10-m depth in 863 surface sediment samples from the North Atlantic (101 S to 901 N). Thick lines show average abundance per 1 1C increment. Note the strong and distinctly different SST response of the two species. Scanning electron micrographs of the two species are not to scale. Data from the MARGO database (http://www.pangaea.de).
representations in the present-day ocean are extremely highly correlated to each other. Transfer functions can only produce reliable SST reconstructions within the limits of the calibration range. The method is therefore most sensitive in the middle of the SST range and weaker at the SST extremes. Prediction errors are estimated by validation where a portion of the calibration database is held back, the transfer function is then applied on this validation data set, and the SST ‘reconstructions’ are compared with the actual values. If the calibration data set is small, the leaving-one-out method may be used where one sample is held back at a time and a new transfer function is produced. The prediction error is then calculated as the average of the prediction errors for the individual samples. The form of the transfer function may vary considerably. A simple linear relationship is expressed by the weighted average method, where past SST is calculated as the weighted average of the abundances of n species: , n n X X ðpi SSTi Þ pi ½10 SST ¼ i¼1
i¼1
where pi is the proportion of species i and SSTi is the ‘optimal temperature’ for species i determined empirically from the calibration data set. The performance of the weighted average method has been improved by including partial least squares regression. The classical method by Imbrie and Kipp is mathematically related. It involves transformation of the census counts into a number of artificial ‘assemblages’ by means of factor analysis, followed by a multiple regression of the assemblage scores (and their cross products and squares) onto SST. The modern analog technique (MAT) is a variant of the k-nearest neighbor regression. This method searches the calibration data set for samples with assemblages that most resemble the fossil assemblage. To identify the best analogs in the calibration data set, the square chord distance measure is used: dij ¼
p h i2 X ðxik Þ1=2 ðxjk Þ1=2
½11
k¼1
where dij is the dissimilarity coefficient between sample i and sample j, xk is the percentage of species k in a sample, and p is the total number of species in
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
Empirically determined
SST
Long-term average of instrumental measurements
1 Empirical calibration
Census counts in surface sediments
Modern fauna /flora
Transfer function
2 3
Census counts in fossil samples
Fossil fauna /flora
Reconstructed
Mathematically derived
4
5
Past SST
Assumptions of paleotemperature transfer functions: 1 2 3 4 5
Species abundances in the calibration data set are systematically related to sea surface temperature (SST). SST is a significant determinant in the ecological system represented by the calibration data set or is at least strongly correlated to such a determinant. The mathematical method used to derive the transfer function provides an adequate model of the ecological system and yields a calibration with sufficient predictive power. Species in fossil samples all have modern counterparts and their ecological responses to SST have not changed significantly. The joint distribution of SST with other environmental parameters acting on the ecological system in the calibration data set is the same as in the fossil sample.
Figure 10 The principles of the transfer function paleothermometer, showing the five main assumptions on which the method is based.
the calibration data set. Past SST is then reconstructed from the physical properties recorded in the best modern analog samples:
SST ¼
m X
, ðsi SSTi Þ
i¼1
m X
si
½12
i¼1
where SSTi is the SST value in ith of the m best analog samples and si is a similarity coefficient between the fossil sample and the ith best analog sample:
sij ¼
p X pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi xik xjk
½13
k¼1
The MAT approach has been further modified in the SIMMAX technique which weighs the best analogs additionally by their geographical distance from the fossil sample. The revised analog method (RAM) expands the calibration data set by interpolation in the space of the reconstructed environmental parameters. It also includes an algorithm for flexible selection of the number of best analogs.
Increasingly more complex mathematical methods are being used to extract the relationship between species counts and SST, including artificial intelligence algorithms and Bayesian techniques. The main issue in further development of transfer functions is how to avoid overfitting and extract the general signal. A useful approach appears to be that of comparison of the differences among SST reconstructions derived by different mathematical methods. Microfossil groups used for transfer functions Four microfossil groups are commonly used for transfer function paleothermometry. By far the most commonly used are planktonic foraminifera (Figure 4). The foraminifera are isolated from marine sediments by washing and sieving and the determination of foraminiferal assemblage census typically involves counting under a binocular microscope of 300–500 specimens in random splits of the 40.150 mm fraction. Foraminiferal transfer functions are applicable in all marine sediments deposited above the calcite lysocline, apart from polar waters where the dominance of a single species (Neogloboquadrina pachyderma) causes lack of resolution (Figure 11).
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
111
Artificial neural network transfer function for North Atlantic planktonic foraminifera 30
Reconstructed mean annual SST10 m (°C)
25
20
15
10
5 R 2 = 0.99 RMSEP = 0.96 °C N = 863
0
−5 −5
0
5
10
15
20
25
30
Observed mean annual SST10 m (°C) Figure 11 Comparison of actual SST values with transfer function estimates for a calibration of census counts of 26 foraminiferal species in 863 North Atlantic (101 S to 901 N) surface sediment samples. The transfer function was derived by training of backpropagation artificial neural networks. The root mean square error of prediction of the calibration is 1 1C; the calibration breaks down in polar samples (SSTo3 1C) due to the dominance of a single species. Modified from Kucera M, Weinelt M, Kiefer T, et al. (2005) Reconstruction of sea-surface temperatures from assemblages of planktonic foraminifera: Multi-technique approach based on geographically constrained calibration datasets and its application to glacial Atlantic and Pacific Oceans. Quaternary Science Reviews 24: 951–998. Data from the MARGO database (http://www.pangaea.de).
Typically, annual, summer, and winter SST are reconstructed simultaneously. Both regional and global calibrations exist, all showing prediction error estimates in the range of 1–1.5 1C. The approach has been successfully used throughout the last 0.5 My; applications to sediments as old as the mid-Pliocene exist, but must be viewed with utmost caution due to evolutionary modifications of species ecology. In sediments affected by carbonate dissolution, in the tropical Pacific and in polar oceans, the siliceous skeletons of diatoms (Chrysophyceae) and radiolarians are the prime target for transfer functions. The siliceous skeletons of diatoms and radiolarians are concentrated using chemical maceration of the sediment. The residue is mounted on glass slides and typically 300–500 specimens are counted under light microscope. Radiolaria are eurybathyal heterotrophic protists and their production maximum occurs in tropical and subpolar/transitional waters. The
maximum production of the diatom algae is in polar waters and high-productivity upwelling regions. Diatoms are particularly suitable for SST reconstruction in polar waters of the Southern Hemisphere. As light-dependent phytoplankton, their production during polar winter ceases and diatom transfer functions are therefore commonly used to reconstruct summer SST only. Unlike foraminifera, diatoms are diverse even in the coldest waters and can be used to reconstruct SST up to the freezing point of seawater. In fact, diatom transfer functions can be even used to reconstruct the extent of permanent sea ice. The prediction error of diatom transfer functions are estimated to be around 1 1C; slightly higher values are reported for radiolarians. Both groups have been used for paleothermometry only in the late Quaternary (last 0.5 My). Cysts of dinoflagellate algae are made of resistant biopolymers and can be extracted from sediments by
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
chemical maceration involving hydrofluoric acid. The residue is mounted on glass slides and preferably 300, but sometimes less, specimens are counted. Dinoflagellates are normally phototrophic, although some species are mixotrophic or heterotrophic. Cystproducing forms live typically in coastal waters and the use of dinocyst transfer functions in open-ocean settings is therefore somewhat limited. Large calibration data sets exist only for the Northern Hemisphere and dinocyst transfer functions are particularly useful in the high latitudes. Like diatoms, dinoflagellates can be used to reconstruct SST up to the freezing point of seawater and even to detect the presence of permanent sea ice. The prediction error of dinocyst transfer functions are estimated at 1.5–2 1C and the method has been used only in the late Quaternary (last 0.5 My). Apart from the four microfossil groups mentioned above, coccolithophore algae have been used for transfer functions in the past, but due to taxonomic uncertainties, this method has been largely abandoned. The transfer function approach has seen a recent revival, fueled mainly by the development and application of advanced computational techniques. Despite its caveats and limitation, the method is less sensitive to shifts in production season of the microfossils, is taphonomically more robust, and offers a methodologically independent validation of geochemical paleothermometers.
Conclusion The methods used to reconstruct past SST depend on analytical instrumental precision and computational power and their development has accelerated in the past few decades hand in hand with the technological progress. After the first attempts to quantify the magnitude of past SST change, the science is now focusing on the reduction of uncertainties in SST reconstructions, on a better understanding of the origin of the SST signal and on the search for new types of SST signatures. Existing methods are being tested on new substrates, such as oxygen isotopes in diatom opal and trace elements in monospecific isolates of coccolithophore calcite. Modern instrumentation is opening up new chemical and isotopic systems and the analysis of calcium isotopes in planktonic foraminifera appears a promising avenue of research. Finally, physical properties of microfossils other than assemblage composition are being studied and it appears that size of planktonic foraminifera and morphology of coccoliths (such as Gephyrocapsa oceanica) could be used to reconstruct past SST.
See also Calcium Carbonates. Land–Sea Global Transfers. Past Climate from Corals. Plankton and Climate. Protozoa, Planktonic Foraminifera. Radiative Transfer in the Ocean. Satellite Remote Sensing of Sea Surface Temperatures. Sediment Chronologies. Sedimentary Record, Reconstruction of Productivity from the.
Further Reading Anand P, Elderfield H, and Conte MH (2003) Calibration of Mg/Ca thermometry in planktonic foraminifera from a sediment trap time series. Paleoceanography 18: 1050. Bard E (2001) Comparison of alkenone estimates with other paleotemperature proxies. Geochemistry Geophysics Geosystems 2 (doi:10.1029/2000GC000050). Barker S, Cacho I, Benway HM, and Tachikawa K (2005) Planktonic foraminiferal Mg/Ca as a proxy for past oceanic temperatures: A methodological overview and data compilation for the Last Glacial Maximum. Quaternary Science Reviews 24: 821--834. Bemis BE, Spero HJ, Bijma J, and Lea DW (1998) Reevaluation of the oxygen isotopic composition of planktonic foraminifera: Experimental results and revised paleotemperature equations. Paleoceanography 13: 150--160. Birks HJB (1995) Quantitative palaeoenvironmental reconstructions. In: Maddy D and Brew JS (eds.) Technical Guide 5: Statistical Modelling of Quaternary Science Data, pp. 161--254. Cambridge, MA: Quaternary Research Association. CLIMAP, Project Members (1976) The surface of the iceage Earth. Science 191: 1131--1137. de Vernal A, Eynaud F, Henry M, et al. (2005) Reconstruction of sea-surface conditions at middle to high latitudes of the Northern Hemisphere during the Last Glacial Maximum (LGM) based on dinoflagellate cyst assemblages. Quaternary Science Reviews 24: 897--924. Gagan MK, Ayliffe LK, Beck JW, et al. (2000) New views of tropical paleoclimates from corals. Quaternary Science Reviews 19: 45--64. Gersonde R, Crosta X, Abelmann A, and Armand L (2005) Sea surface temperature and sea ice distribution of the Southern Ocean at the EPILOG Last Glacial Maximum – a circum-Antarctic view based on siliceous microfossil records. Quaternary Science Reviews 24: 869--896. Herbert TD (2006) Alkenone paleotemperature determinations. In: Elderfield H (ed.) Treatise on Geochemistry, Vol. 6: The Oceans and Marine Geochemistry, pp. 391--432. Oxford, UK: Elsevier. Kucera M, Weinelt M, Kiefer T, et al. (2005) Reconstruction of sea-surface temperatures from assemblages of planktonic foraminifera: Multi-technique approach based on geographically constrained calibration datasets and its
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DETERMINATION OF PAST SEA SURFACE TEMPERATURES
application to glacial Atlantic and Pacific Oceans. Quaternary Science Reviews 24: 951--998. Lea DW (2006) Elemental and isotopic proxies of past ocean temperatures. In: Elderfield H (ed.) Treatise on Geochemistry, Vol. 6: The Oceans and Marine Geochemistry, pp. 365--390. Oxford, UK: Elsevier. Mix A, Bard E, and Schneider R (2001) Environmental processes of the ice age: Land, oceans, glaciers (EPILOG). Quaternary Science Reviews 20: 627--657. Mu¨ller PJ, Kirst G, Ruhland G, von Storch I, and RosellMele´ A (1998) Calibration of the alkenone paleotempek0 rature index U37 based on core-tops from the eastern South Atlantic and the global ocean (601 N–601 S). Geochimica et Cosmochimica Acta 62: 1757--1772. Schouten S, Hopmans EC, SchefuX E, and Sinninghe Damste´ JS (2002) Distributional variations in marine crenarchaeotal membrane lipids: A new tool for
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reconstructing ancient sea water temperatures? Earth and Planetary Science Letters 204: 265--274. Waelbroeck C, Mulitza S, Spero H, Dokken T, Kiefer T, and Cortijo E (2005) A global compilation of late Holocene planktonic foraminiferal d18O: Relationship between surface water temperature and d18O. Quaternary Science Reviews 24: 853--868.
Relevant Website http://margo.pangaea.de – MARGO at PANGAEA; the MARGO project houses a database of geochemical and microfossil proxy results for the Last Glacial Maximum, numerous calibration data sets, software tools, and publications.
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DIFFERENTIAL DIFFUSION A. E. Gargett, Old Dominion University, Norfolk, VA, USA & 2009 Elsevier Ltd. All rights reserved.
Introduction Because three-dimensional turbulence normally occurs on time and space scales much smaller than those resolved by numerical ocean models, its effects must generally be parametrized in these models. A particularly important quantity is r0 w0 , the averaged (overbar) vertical flux of density associated with small-scale turbulence, in which r0 and w0 are turbulent fluctuations of density and vertical velocity. By analogy with molecular diffusive fluxes, this turbulent flux is routinely parametrized as r0 w0 ¼ Kr r¯ z , that is, as proportional to r¯ z , the vertical gradient of mean density with a proportionality constant, the turbulent eddy diffusivity Kr, that is assumed to be much larger than the molecular diffusivity of density Dr (see Three-Dimensional (3D) Turbulence). In addition, present ocean general circulation models (OGCMs) normally assume that the same diffusivity can be used to parametrize the vertical turbulent flux of all other scalars in terms of their mean gradients. This assumption underlies use of the same eddy diffusivity in separate equations for temperature (T) and salinity (S), the two properties that (with pressure) determine the density of seawater. Finally, frequent usage of constant Kr in OGCMs implicitly assumes that Kr will not change if mean ocean conditions such as stratification change over time. Details of parametrizations of small-scale turbulence would be a matter of relatively minor import were OGCM predictions insensitive to them, but this is not the case. Different constant values of Kr are known to produce large changes in important features of predicted steady-state circulations: for example, heat flux carried by the oceanic meridional overturning circulation, a climatically important variable, is particularly sensitive to the value chosen for Kr. OGCM sensitivity to Kr results from linkages among the vertical turbulent flux of density, the mean vertical density structure, and horizontal circulation. Since density in the ocean is a highly nonlinear function of the two scalar variables T and S, differences in their vertical fluxes will lead to changes in these modeled linkages, hence to potential changes in modeled circulation.
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Differential vertical transfers of T and S have long been recognized in double diffusive processes (see Double-Diffusive Convection), which can occur in regions of the ocean where the mean vertical gradient of either T or S is destabilizing. However, even where mean gradients of T and S are both stabilizing, ordinary turbulent processes may be associated with what has come to be called differential diffusion, the preferential vertical turbulent transfer of T relative to S.
What Is Differential Diffusion? Differential diffusion results from the larger molecular diffusivity of T relative to that of S, by a mechanism whose cartoon is shown in Figure 1. Figure 1(a) shows a box filled with a light layer of warm (W) and fresh (F) water atop a denser layer of cold (C) and salty (S) water: both T and S components contribute to static stability of the system. Figure 1(b) depicts a blob of lower layer fluid that has been displaced into the upper layer: the blob becomes warmer relatively quickly as heat is rapidly communicated by molecular diffusion from its warmer surroundings. However, because the molecular diffusivity of salt (DS) is 100 times smaller than that of temperature (DT), very little salt escapes from the blob during the time it takes for its temperature to equilibrate. This leaves (Figure 1(c)) a blob that is still denser than its surroundings due to the excess salt, hence falls back to an equilibrium position (Figure 1(d)) between the two original layers. In this final state, temperature has been transferred vertically, but very little salt has accompanied it. In the case of actual turbulence, a simplified conceptual picture is that of a locally overturning turbulent eddy that stirs an embedded scalar field. The decay timescale te of the eddy is influenced by the turbulent Reynolds number Re uc/n (where u and c are characteristic turbulent velocity and length scales
(a)
(b) WF WF
CS T
CS
(d)
(c) T T CS
WF WS
WF WS
CS
CS
Figure 1 Cartoon of the process of differential diffusion of T and S, which has its roots in the much larger molecular diffusivity of temperature than salt in seawater, where DT C 100 DS.
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DIFFERENTIAL DIFFUSION
Laboratory Evidence for Differential Diffusion Differential diffusion was first demonstrated in the laboratory, where J.S. Turner used T and S in turn to produce a two-layer density stratification that was subsequently mixed away by grid-generated turbulence. Figure 2 shows (normalized) entrainment velocity ue, which quantifies the vertical transport of density, as a function of a Richardson number Ri0 g(Dr/r)c/u2 defined in terms of turbulent velocity (u) and length (c) scales and the density difference Dr between the two layers. At high values of Ri0, the entrainment velocity is consistently higher when Dr is produced by T than when the same density difference was produced by S. Effects similar to those observed in Turner’s singly stratified experiments were subsequently demonstrated in laboratory experiments where T and S made simultaneous and equal contributions to the stability of either a density step or linear density stratification. In all of these laboratory settings, the oceanically important scalars T and S, characterized by DTC100 DScDS, exhibit differential diffusion in the sense of enhanced vertical flux of T relative to
Limit at zero Ri0 1.0 5×10−1 2×10−1 10−1 ue /u
and n is fluid kinematic viscosity), which determines the range of scales present in the flow, hence the time required to transfer turbulent kinetic energy to the small spatial scales at which velocity variance is dissipated. Turbulent stirring also transfers variance of an embedded scalar to a scalar dissipation scale that varies as D1/2, where D is the scalar molecular diffusivity (see Three-Dimensional (3D) Turbulence). Important oceanic scalars such as T, S, dissolved oxygen, and chemical nutrients are all characterized by scalar Schmidt number Sc n/D41, hence by scalar variance dissipation scales that are smaller than velocity variance dissipation scales (see ThreeDimensional (3D) Turbulence). Straining scalar variance to a smaller scalar dissipation scale requires additional time, and this added time increases as Sc increases. As a result, the amount of scalar variance that is dissipated during te depends upon Sc. For ScB1, scalar variance can be entirely erased within the decay timescale of the velocity field, while effectively nondiffusive scalars (Scc1) will experience almost no transfer of variance to their much smaller diffusive scales within the same period of time. Since irreversible scalar mixing is rooted in the elimination of scalar variance by intermingling at the molecular level, these differences can result in differential vertical diffusion of scalars which have different molecular diffusivities.
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5×10−2 2×10−2 10−2 5×10−3 2×10−3 1.0
2
5
10 Ri0
20 l Δ =g u2
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Figure 2 Comparison between directly measured entrainment velocity (equivalent to vertical flux) resulting from grid-stirring on one side of a density interface produced respectively by T (filled circles) and S (open circles). Mean stratification increases with Richardson number Ri0 , here calculated with turbulent length c and velocity u scales characteristic of the grid turbulence. Reproduced from Turner JS (1973) Buoyancy Effects in Fluids. Cambridge, UK: Cambridge University Press, with permission from Cambridge University Press.
that of S, that is, greater vertical diffusion of the scalar with the larger molecular diffusivity. In the doubly stratified experiments, where vertical gradients of T and S simultaneously make equal contributions to stability, the differential fluxes can be directly interpreted as KT4KS, that is, a larger turbulent diffusivity for T than for S.
Numerical Simulation of Differential Diffusion Much of what is known about the mechanism of differential diffusion in double stably stratified systems has come from direct numerical simulation (DNS), in which dependence of the process on molecular properties of scalars is provided by explicit resolution of the necessary dissipative scales. Even with modern computers, however, computational limitations do not presently allow three-dimensional
