ADVANCES IN AGRONOMY Advisory Board
PAUL M. BERTSCH
RONALD L. PHILLIPS
University of Kentucky
University of Minnesota
KATE M. SCOW
LARRY P. WILDING
University of California, Davis
Texas A&M University
Emeritus Advisory Board Members
JOHN S. BOYER
KENNETH J. FREY
University of Delaware
Iowa State University
EUGENE J. KAMPRATH
MARTIN ALEXANDER
North Carolina State University
Cornell University
Prepared in cooperation with the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America Book and Multimedia Publishing Committee DAVID D. BALTENSPERGER, CHAIR LISA K. AL-AMOODI
CRAIG A. ROBERTS
WARREN A. DICK
MARY C. SAVIN
HARI B. KRISHNAN
APRIL L. ULERY
SALLY D. LOGSDON
Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 32 Jamestown Road, London, NW1 7BY, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2010 Copyright # 2010 Elsevier Inc. All rights reserved. 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 Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email:
[email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-381031-1 ISSN: 0065-2113 (series) For information on all Academic Press publications visit our website at elsevierdirect.com Printed and bound in USA 10 11 12 10 9 8 7 6 5 4 3 2 1
CONTRIBUTORS
Numbers in Parentheses indicate the pages on which the authors’ contributions begin.
Yoav Bashan (77) The Bashan Foundation, Corvallis, Oregon, USA, and Environmental Microbiology Group, Northwestern Center for Biological Research (CIBNOR), Colonia Playa Palo de Santa Rita, La Paz, B.C.S., Mexico R. Budd (1) California Department of Pesticide Regulation, Sacramento, California, USA R. A. Dahlgren (1) Department of Land, Air and Water Resources, University of California, Davis, California, USA Luz E. de-Bashan (77) The Bashan Foundation, Corvallis, Oregon, USA, and Environmental Microbiology Group, Northwestern Center for Biological Research (CIBNOR), Colonia Playa Palo de Santa Rita, La Paz, B.C.S., Mexico J. Gan (1) Department of Environmental Sciences, University of California, Riverside, California, USA B. Mohan Kumar (237) College of Forestry, Kerala Agricultural University, Thrissur, Kerala, India Bekunda Mateete (183) Kampala International University,Nairobi Centre,Kenya J. J. Maynard (1) Department of Land, Air and Water Resources, University of California, Davis, California, USA Vimala D. Nair (237) Soil and Water Science Department, University of Florida, Gainesville, Florida, USA Sanginga Nteranya (183) Tropical Soil Biology Institute of the International Centre for Tropical Agriculture, Nairobi, Kenya
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Contributors
A. T. O’Geen (1) Department of Land, Air and Water Resources, University of California, Davis, California, USA Bo Pan (137) Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China, and Department of Plant, Soil and Insect Sciences, University of Massachusetts, Amherst, Massachusetts, USA S. J. Parikh (1) Department of Land, Air and Water Resources, University of California, Davis, California, USA P. K. Ramachandran Nair (237) Center for Subtropical Agroforestry, School of Forest Resources and Conservation, University of Florida, Gainesville, Florida, USA Julia M. Showalter (237) Soil and Water Science Department, University of Florida, Gainesville, Florida, USA Woomer Paul L. (183) Forum for Organic Resource Management and Agricultural Technology, Nairobi, Kenya Baoshan Xing (137) Department of Plant, Soil and Insect Sciences, University of Massachusetts, Amherst, Massachusetts, USA
PREFACE
Volume 108 contains five outstanding reviews from an international group of authors that deal with some of the great challenges of our time— environmental quality, food production, and carbon sequestration. Chapter 1 discusses the important role that constructed and managed wetlands have in mitigating nonpoint pollution in agriculture from nutrients, microbes, patho gens, pesticides, and trace metals. Chapter 2 is a critical review on how the plant growth promoting bacterium, Azospirillum, promotes plant growth. Chapter 3 is a timely review on nanoparticles, with emphasis on manufactured nanopar tices and the role they play in sorption of organic chemicals. Chapter 4 is concerned with developments in enhancing and restoring the fertility of soils in sub Saharan Africa, a critical factor in increasing food production. Chapter 5 is a comprehensive review on carbon sequestration in agroforestry systems. Topics such as measurement, mechanisms, and management of carbon seques tration are covered. I am grateful to the authors for their outstanding contributions. DONALD L. SPARKS Newark, Delaware, USA
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C H A P T E R
O N E
Mitigating Nonpoint Source Pollution in Agriculture with Constructed and Restored Wetlands A. T. O’Geen,* R. Budd,† J. Gan,‡ J. J. Maynard,* S. J. Parikh,* and R. A. Dahlgren* Contents 1. Mitigating Pollution with Wetlands 1.1. Types of anthropogenic wetlands 1.2. Governing factors influencing CWs 1.3. Contaminant removal processes 1.4. Vegetation 2. Suspended Sediment 3. Pesticides 3.1. Herbicides 3.2. Organophosphate insecticides 3.3. Pyrethroid insecticides 3.4. Pesticide removal 4. Nitrogen (N) 4.1. Environmental impacts 4.2. N cycling in CWs 4.3. N removal efficiency 5. Phosphorus (P) 5.1. Environmental impacts 5.2. Phosphorus forms in CWs 5.3. P transformations 5.4. Removal efficiencies of P fractions 5.5. Wetland management strategies to improve P removal 6. Dissolved Organic Matter 6.1. DOM sources 6.2. DOM sinks 6.3. DOM input–output budgets from agricultural wetlands
3 4 6 7 9 10 12 12 15 16 20 24 24 25 28 32 32 33 34 37 38 38 39 40 41
* Department of Land, Air and Water Resources, University of California, Davis, California, USA California Department of Pesticide Regulation, Sacramento, California, USA Department of Environmental Sciences, University of California, Riverside, California, USA
{ {
Advances in Agronomy, Volume 108 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)08001-6
#
2010 Elsevier Inc. All rights reserved.
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7. Trace Metals 7.1. Sources of trace metals to agricultural soils 7.2. Trace metal fate and transport in agricultural soils 7.3. Trace metals in saturated soils and wetlands 8. Pathogens 8.1. Pathogen removal 8.2. Case study: Agricultural wetlands treatment of irrigation tailwaters 9. Other Water-Quality Constituents 9.1. Salinity 9.2. Biological oxygen demand 10. Design and Management 10.1. Hydrology 10.2. Dimensions and design 10.3. Placement 10.4. Managing vegetation 10.5. Design features for mosquito control 11. Summary References
43 44 45 45 48 48 50 51 51 52 52 53 55 57 58 59 59 60
Abstract Nonpoint source pollution (NPSP) from agricultural runoff threatens drinking water quality, aquatic habitats, and a variety of other beneficial uses of water resources. Agricultural runoff often contains a suite of water-quality contaminants, such as nutrients, pesticides, pathogens, sediment, salts, trace metals, and substances, contributing to biological oxygen demand. Increasingly, growers who discharge agricultural runoff must comply with water-quality regulations and implement management practices to reduce NPSP. Constructed and restored wetlands are one of many best management practices that growers can employ to address this problem. This review focuses on the ability of constructed and restored wetlands to mitigate a variety of water-quality contaminants common to most agricultural landscapes. We found that constructed and restored wetlands remove or retain many water-quality contaminants in agricultural runoff if carefully designed and managed. Contaminant removal efficiency generally exceeded 50% for sediment, nitrate, microbial pathogens, particulate phosphorus, hydrophobic pesticides, and selected trace elements when wetlands were placed in the correct settings. There are some potentially adverse effects of constructed and restored wetlands that must be considered, including accumulation of mercury and selenium, increased salinity, mosquito habitat, and greenhouse gas emissions. Proper wetland management and design features are discussed in order to reduce these adverse effects, while optimizing contaminant removal.
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1. Mitigating Pollution with Wetlands An emerging challenge for agriculture is to feed the world without adversely affecting the environment. Global demand for food is growing at an alarming rate. According to FAO predictions, food production must increase 40% by 2030 and 70% by 2050 to sustain the planet’s population growth (OECD FAO, 2009). Today, roughly 1.4 billion hectares of cropland are in production across the planet, yet to sustain this emerging global demand, cropland area would have to more than double (OECD FAO, 2009). At the same time, prime farmland is being lost to urbanization and other land uses. The loss of this productive farmland has displaced farming into marginal lands that are more erosive and require more inputs than those required for prime farmland (Charbonneau and Kondolf, 1993). Thus, soil and water resources will be subjected to added pressures in the future requiring cost effective, best management practices (BMPs) to ensure environmental protection. Nonpoint source pollution (NPSP) is a global problem affecting the safety of our drinking water supply and aquatic habitats. According to the 2000 National Water Quality Inventory, agriculturally derived NPSP is the leading cause of water quality degradation in surface waters (US EPA, 2002). Pollutants originating from agricultural runoff include sediment, nutri ents (N and P), pesticides, pathogens, salts, trace elements, dissolved organic carbon (DOC), and substances that contribute to biological oxygen demand (BOD). For example, discharge of nutrients into aquatic ecosystems has lead to dramatic shifts in trophic relationships (Boesch et al., 2001) including hypoxia/ anoxia induced ‘‘dead zones’’ in more than 400 locations worldwide (Diaz and Rosenberg, 2008). Thus, new and effective management practices for agri culture must be identified, tested, and monitored in order to reduce the impacts of agriculture on the sustainability of water resources. Wetlands are widely advertised as critical components of our planet providing a wide variety of ecosystem services: kidneys of the hydrologic cycle by removing pollutants, biodiversity hot spots, habitats of rare and endangered species, ground water recharge zones, localized areas for flood protection, carbon sinks, and aesthetic value (Zedler, 2003). Upon settle ment of the United States, the lack of understanding for the role of wetlands and drive for agricultural production resulted in a loss of over 53% of the nation’s wetlands (Dahl, 1990). California and Texas, two states leading agricultural production in the United States, have lost more than a com bined 5 million hectares of wetlands. Much of this loss was as result of programs in the United States such as Swamp Buster, which encouraged the conversion of marginal land (e.g., wetlands) into agricultural production. Coincident with this landscape conversion was the rise in use of agricultural chemicals. As a result, the filtration effect of wetlands has been uncoupled from riparian environments resulting in severe degradation of the nation’s
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(and the planet’s) water resources. Only in the last few decades have wet lands been recognized for their potential role to ameliorate NPSP. Traditionally, constructed and restored wetlands have been developed in agricultural settings to improve wildlife habitat, mainly through the U.S. Conservation Reserve Program and the Wetlands Reserve Program (WRP). The WRP is an outreach effort administered through the Natural Resource Conservation Service (NRCS) and its partners. It is designed to provide financial and technical assistance to landowners to restore, enhance, and protect wetlands and surrounding surface waters. As of 1999, there were a total of 785,000 ha of marginal farmland that have been enrolled in the WRP (Mitsch and Gosselink, 2000). The conversion of floodplain agro ecosystems to wetlands is becoming a popular land use practice nationwide (Fig. 1), yet little information exists to document how these wetlands filter water quality contaminants in runoff from agricultural fields.
1.1. Types of anthropogenic wetlands There are many different definitions of wetlands from a variety of federal agencies and stakeholders. Mitsch and Gosselink (2000) present a definition by NRC (1995) as one of the most comprehensive descriptions of a wetland:
Figure 1 Restored wetland in the San Joaquin Valley, CA. This CW receives irrigation tailwater for approximately 6 months during the growing season. A natural wetland in this setting would be inundated with water during the winter and early spring months.
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‘‘A wetland is an ecosystem that depends on constant or recurrent, shallow inundation or saturation at or near the surface of the substrate. The mini mum essential characteristics of a wetland are recurrent, sustained inunda tion or saturation at or near the surface and the presence of physical, chemical, and biological features reflective of recurrent, sustained inunda tions or saturation. Common diagnostic features of wetlands are hydric soils and hydrophytic vegetation. These features will be present except where specific physiochemical, biotic, or anthropogenic factors have removed them or prevented their development.’’
This review will address the ability of two types of wetlands, constructed and restored wetlands (termed CW herein), to improve water quality in agricultural landscapes. Constructed wetlands, also referred to as created wet lands, are developed in areas where natural wetlands did not previously exist. Restored wetlands are enhanced and/or developed wetlands in areas where wetlands were drained or disturbed in some manner (Mitsch, 1992; Van de Valk and Jolly, 1992). There are two main types of CWs, surface flow and subsurface flow (both vertical and horizontal). Subsurface flow wetlands are not common in agricultural settings because of the high maintenance costs asso ciated with the clogging of porous media. Therefore, this review primarily focused on surface flow CWs, where agricultural runoff (surface and/or sub surface) is delivered to and passes through a wetland system ultimately destined for adjacent surface water bodies such as rivers, streams, lakes, and estuaries. This review addresses the application of CWs to mitigate NPSP in agricultural settings, primarily from field runoff and subsurface drainage. CWs are one of several BMPs for mitigating NPSP. There is a tremendous body of literature on treatment wetlands, which we define as wetlands designed to filter and treat municipal waste water (but also storm runoff, mine waste, and animal waste). Despite the tremendous depth of knowledge on treatment wetlands (e.g., Kadlec and Knight, 1996), there is a paucity of published information addressing the efficacy of CWs for controlling NPSP (Baker, 1992; Woltemade, 2000). Moreover, CWs in agricultural settings differ greatly from treatment wetlands, and direct comparisons between treatment wetlands, which have relatively constant input flows, are not always reliable (Poe et al., 2003; Tanner et al., 2005). Most treatment wetlands that receive municipal or animal waste experience continuous water flow and uniform input loads of waste. For example, in a study of water quality in 244 sewage treatment facilities across the nation, standard deviations of mean values for nutrients were around 10% (Gakstatter et al., 1978). In contrast, the relative standard deviation for irrigation tailwaters in the San Joaquin Valley of California often exceeded 50% for several water quality parameters (Brauer et al., 2009). Before the early 1990s, most water quality research on wetlands in agricultural settings has focused on runoff from confined animal operations (Cronk, 1996; Mitsch and Gosselink, 2000; Tanner et al., 1995, 2005). The composition of nitrogen (N) and phosphorus (P)
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differs between waste water effluent and agricultural cropland runoff. Relative comparisons of the two indicate that wastewater is N limited with a mean N:P ratio of 2.4:1 while agricultural runoff tends to be P limited with a mean N:P ratio of 31:1 (Baker, 1992). Nutrients in treatment wetlands are often immobilized in organic/particulate forms, where as in agriculture, these constituents are commonly in inorganic/dissolved forms making the process of plant uptake more relevant (Baker, 1992). The goal of this review is to summarize the current state of knowledge regarding the use of CWs in agricultural settings to improve water quality. In this effort we considered benefits of implementing CWs, and discussed dominant wetland processes, contaminant removal efficiencies, wetland management practices, and design and placement considerations. This review focuses on surface flow through wetlands and does not directly address evaporation ponds, vertical seepage wetlands, treatment wetlands, or natural wetlands. CWs in agricultural settings receive a broad suite of water quality contaminants, and therefore the potential amplification of some constituents resulting in adverse effects will also be addressed.
1.2. Governing factors influencing CWs 1.2.1. Climate Temperature is a controlling variable for biogeochemical reaction rates, thus the coincidence of agricultural runoff with seasonal temperatures is a key factor in contaminant removal. Irrigated agriculture represents the best case scenario, where CWs receive inflows from tailwaters during the warmest times of the year. However, many CWs are placed in farmscapes to inter cept storm water runoff. These systems often receive highest inflows during winter rains or spring snowmelts, often during the coldest times of the year (Werker et al., 2002). Solar radiation drives wetland energy balance and ultimately governs all wetland processes. Solar radiation directly affects primary productivity, temperature, and evapotranspiration (Kadlec, 1999). It also contributes to photodegradation of organic compounds. Solar radiation and wind govern evapotranspiration and water loss affecting removal efficiencies calculated on a concentration basis. 1.2.2. Inflow CWs receiving agricultural runoff witness event based fluxes of water and materials that correspond with hydrological patterns, irrigation and cultiva tion practices, and biogeochemical cycles, all of which are governed to a large extent by climate. As such, CWs in these settings experience a high degree of variability (Brauer et al., 2009; Woltemade, 2000). Variability in hydrologic loading depends on wetland design and the origin of source water (e.g., irrigation runoff, tile drainage, surface runoff, stream flow
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diversion, or in stream flow). Seasonal patterns in contaminant flux and dilution occur as a result of land use, storm events or snow melt, discharge from tile drainage, and/or irrigation runoff. Concentration pulses may reflect runoff events, fertilization timing, mineralization of soil organic matter, and/or application of soil amendments. Pesticide concentrations vary as a function of application timing, crop rotation, crop mix, and drift patterns. When evaluating the efficacy of CWs for water quality purposes, or when comparing CWs across regions, it is important to consider the nature of source waters and the timing of their delivery. CWs receiving irrigation runoff experience seasonal variability governed by the length of the growing season and cropping patterns. In California’s Central Valley, it was shown that wetland input water concentrations of nutrients, sediment, and salinity originating from tailwaters were highly variable and showed no relationship with flow when the contributing area was relatively small (<1500 ha) (Brauer et al., 2009). Water quality con taminant concentrations were less variable, however, in large contributing areas, which supplied constantly high input loads. Contaminant concentra tions tend to be more variable when the size of the contributing area is small because pulses are linked to the timing of biogeochemical processes, irriga tion, fertilization, and cultivation. Large contributing areas integrate all factors that result in contaminant flux, the end result being a more constant contaminant concentration within input waters (Brauer et al., 2009).
1.3. Contaminant removal processes In agricultural settings, wetlands serve as filters, sinks, and transformers of water quality constituents ( Jordan et al., 2003). The retention and/or removal of water quality contaminants in CWs are/is governed by three general processes: additions, transformations, and translocations. Input loading affects the rate and pathway of removal mechanisms. Transformations lead to a change in phase and reactivity of constituents, while translocation processes render contaminants inactive and/or inert, often through burial. In many instances, transformations and translocations work in concert, resulting in a constituent loss. Some specific processes lead to a permanent loss from the system, such as the transformation of nitrate to N2O and N2 gas and its diffusion into the atmosphere. Others result in the transfer of contaminants from one compartment of the system (water column) to another (sediment), the latter rendering the contaminant less reactive in the environment. There are several mechanisms acting in CWs that contribute to the removal of contaminants, including: (1) sedimentation and burial (phos phorus, pesticides, particulate organic carbon, pathogens); (2) biogeochem ical transformations (denitrification, methanogenesis, dimethylselinide production); (3) biotic uptake of nutrients and salts; (4) microbial degrada tion of pesticides and organic matter; (5) redox transformations affecting
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solubility, sorption, and toxicity (e.g., As, Se, methyl Hg); (6) predation of pathogens; and (7) photodegradation of pesticides and organic matter. As a result of these processes, it is commonly considered that wetlands have a predominantly beneficial effect on water quality (Jordan et al., 2003; Zedler, 2003). Important factors controlling water purification capacity of wetlands include rate of contaminant inflows, residence time of water in the wetland, availability of organic matter and other substrates for growth of microbes, light intensity and penetration, temperature, and nutrient uptake by plants (Phipps and Crumpton, 1994; Woltemade, 2000). 1.3.1. Redox processes Redox status of wetland soils dictates many important constituent transfor mations affecting the chemical phase (aqueous, solid, or gas), mobility of some contaminants, and the reactivity of sorption sites. Reducing condi tions arise as soils become saturated. Oxygen rapidly becomes limited in submerged soils because the oxygen diffusion rate is orders of magnitude slower in saturated soil compared with well drained soils. Anaerobic con ditions develop in the absence of O2, and as a result, other electron acceptors are utilized for microbial respiration. In the presence of oxygen, redox potentials are generally in the range of 400–600 mV. Following oxygen depletion, nitrate is reduced to N2O and N2 gas at a threshold redox potential around 250 mV (Mitsch and Gosselink, 2000). Once nitrate (NO3) is consumed, constituents that affect P cycling are reduced, such as manganese and iron (hydr)oxides, at redox thresholds around 225 and 100 mV, respectively. At low redox potentials, sulfate is reduced to sulfide ( 100 mV) and CO2 is reduced to methane ( 200 mV). Wetland soils are not completely reduced. A thin oxidative layer exists at the soil surface, which ranges in thickness from a few millimeters to several centimeters. This layer forms as a result of mixing between the atmosphere, water column, and soil. Its thickness is mediated by temperature, rate of diffusion, plant and microorganism respiration rates, oxygen production via photosynthesis by aquatic vegetation, and mixing in the water column (Mitsch and Gosselink, 2000). Since some water quality constituents become less mobile under oxidizing conditions (Mn and Fe), this thin oxidized layer can act as a barrier for translocations from sediment pore water to the water column. Moreover, it also serves as an important area where aerobic bio chemical reactions occur, such as mineralization and methane oxidation. 1.3.2. Sedimentation Sedimentation is the physical process of solid particles settling in water. The rate of sedimentation is governed by particle size, particle density, water velocity and turbulence, salinity, temperature, and water column depth. In wetlands, sedimentation results in many ecosystem benefits. The most dramatic effect is an increase in water clarity, which is important to downstream
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fish habitat and the aesthetic value of connected water bodies. Sedimentation also contributes to water quality improvements through the settling of reactive particles that serve as sorption sites for other contaminants such as pesticides, trace metals, phosphorus, ammonium, and pathogens. Carbon sequestration is partially facilitated through sedimentation, where settled particulate organic carbon and carbon associated with sediment is buried and preserved in anaer obic soil environments where decomposition is very slow (Smith et al., 2001, 2002). Removal of particulate organic matter also reduces the BOD, which reduces the potential for hypoxia in aquatic ecosystems. 1.3.3. Sorption The process where contaminants in the water column are removed from solution and retained on surfaces of solid particles is termed sorption. Sorption leads to contaminant removal by rendering the contaminant less reactive or by removing it from the system through sedimentation and burial. Sorption is limited by the amount of sorptive surfaces and the chemical and mineralogical nature of the particles. The nature of water quality contaminants is also important to consider. Cations, for example, will be attracted by negatively charged colloids of clay or organic matter via cation exchange reactions. Sorption to particulates coupled with sedimen tation and burial is also an important removal process for pathogens and pesticides (Knox et al., 2008; Streets and Holden, 2003). An important process that facilitates phosphorus removal occurs through sorption via inner and outer sphere complexes to crystalline and poorly crystalline oxides or clay crystal edges and subsequent sedimentation. 1.3.4. Photochemical processes Photochemical processes can cause direct or indirect transformation of water quality contaminants (Miller and Chin, 2005). Organic chemicals and constituents such as pesticides, herbicides, pharmaceuticals, pathogens, and DOC can be remediated in wetlands by photodegradation. While most pathogens can be destroyed directly by UV light, many pesticides decom pose as a result of indirect photolysis (Miller and Chin, 2005). For example, humic substances when exposed to photons can yield reactive oxygen species and the photochemically excited states of dissolved organic matter (DOM) may enhance photolysis of organic contaminants. Nitrate has also been shown to be an important photosensitizer in wetlands, producing hydroxyl radicals (OH) when photolyzed (Zepp et al., 1987).
1.4. Vegetation Vegetation plays an important role in filtration of contaminants in wetlands. Assimilation of pollutants including metals and nutrients is an important translocation and transformation mechanism, but is not considered a removal
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process unless vegetation is harvested and removed or burned in the case of nitrogen. There are, however, a variety of indirect contributions of vegetation toward contaminant removal. Stems and leaves within the water column impede water flow promoting particle settling and preventing sediment resus pension. Wetland vegetation also increases the surface area of substrate for microbial attachment and biofilm communities that are responsible for many transformation processes (Brix, 1997). As plants die and decay organic carbon is supplied, which is needed for many microbial transformations such as denitri fication. Organic materials are also important in the sorption of pesticides in CWs. Central to nitrogen transformations (ammonium and organic N), wet land vegetation facilitates the existence of the soil aerobic zone by transferring oxygen from the atmosphere to the rhizosphere via aerenchymous tissues facilitating mineralization, nitrification, and methane oxidation. Another function of plants is to decrease the hydrologic load leaving CWs through transpiration (Carty et al., 2008). The shading effect of an emergent canopy can have positive and negative impacts on contaminant removal. Canopy interception of solar radiation reduces UV light penetration in the water column, which reduces pathogen attenuation and photodegradation processes. However, light interception results in less phytoplankton algae that could cause high BOD and hypoxia downstream. Wetland vegetation has been shown to uptake considerable amounts of nutrients. For example, Schoenoplectus tabernaemontani was found to uptake 190–390 g N m 2 yr 1 (Tanner et al., 1998) and Scirpus, Phragmites, and Typha were found to assimilate 90–130 g N m 2 yr 1 (Debusk et al., 1995; Kadlec, 1999). The effects of plant uptake in a CW are counteracted by litter deposition and mineralization of detritus, and thus, vegetation must be harvested and disposed of annually to facilitate long term nutrient removal.
2. Suspended Sediment Out of all the pollutants from irrigated agriculture, CWs are most effective at removing suspended sediment. Sediment adversely affects surface water bodies by decreasing water clarity, and destruction of benthic commu nities and spawning beds in rivers and streams. Sediment can also be considered indirectly toxic since pollutants (metals, pesticides, pathogens, and nutrients) are often sorbed to particulates. The forms of suspended sediment are organic and mineral. Mineral fractions may include microaggregates, sand, silt, or clay. The dominant process of suspended solids removal is sedimentation. As high energy input flows are dispersed across the CW environment, the velocity is reduced, resulting in settling of the suspended load. The energy needed to support suspended particles is dissipated by the increase in cross sectional area
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and in part by vegetation, which reduces turbulence and decreases water velocity (Barko et al., 1991; Schmid et al., 2005). Several studies, however, have disputed the claim that vegetation directly affects sedimentation (Brueske and Barrett, 1994; Leonard et al., 2002). Instead, it is thought that vegetation reduces resuspension resulting in increased net sediment retention (Braskerud, 2001; Brueske and Barrett, 1994). Other factors in the CW environment that affect sedimentation are degree of particle flocculation, particle diameter, particle density, water temperature, turbulence, and residence time. The amount of vegetative cover has been shown to affect sediment resuspension. For example, Braskerud (2001) found that a 30% increase in vegetative cover from less than 20% reduced sediment resuspension from 40% to near zero. Wetland depth may also indirectly affect sediment retention. Water levels should be deep enough to reduce water velocity on the soil surface, however, if too deep, vegetation cannot establish resulting in significant resuspension of sediment. Water depths between 20 and 50 cm optimize plant establishment, decrease water velocities, anchor soil, and provide the added benefit of short particle settling distance (Braskerud, 2002a). Some studies contradict this statement, finding higher sedimentation rates in deeper open water environments (Brueske and Barrett, 1994; Fennessy et al., 1994). Preferential flow through unvegetated areas may be responsible for higher sedimentation rates witnessed in these studies, by distributing more material to open areas. Maynard et al. (2009) found that fine sediments (silts and clay) were transported along preferential pathways through wetlands with low HRT resulting in a decrease in the retention efficiency for particle bound P. This may also apply to particle associated pesticides, metals, pathogens, and other chemicals. Sediment accumulation rates are highly variable when comparing differ ent wetlands. In a review of several freshwater wetlands in the eastern half of the United States, Johnston (1991) found mass sediment accumulation rates to range from 39 to 5200 g m 2 yr 1 and in some instances no sedimentation occurred. Out of about 39 different wetlands, the average sediment mass accumulation rate among mineral soil wetlands was 1680 g m 2 yr 1. Wet lands with the highest accumulation rates received agricultural field runoff (Cooper et al., 1987) or sediment rich stream and river waters, many of which drained agricultural areas (Johnston, 1991). In a review of nine wet lands receiving stream or river water, Phillips (1989) showed that on average 62% of suspended sediment was retained ranging from 23% to 93%. Sediment removal by CWs can become a problem for wetland managers. Sediment accumulation eventually reaches a point where CWs need to be dredged or regraded to maintain proper hydrologic functioning. In agricultural settings, sediment traps often need to be cleared 1–2 times per year. The costs associated with removal and disposal of accumulated sediment can be substantial. Moreover, the risks associated with the use of potentially contaminated sedi ment (e.g., pesticides and trace elements) are unknown.
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3. Pesticides Pesticides have been detected in most surface water systems throughout the United States. One or more pesticides have been found in 95% of samples collected from about 1600 streams within the United States (Gilliom et al., 1999). Due to the potential deleterious effects on aquatic organisms, there is a growing need to reduce pesticide contamination in receiving waterways. CWs may cause the removal of contaminants via physical, chemical, and biological processes. The use of CWs as a mitigation strategy is gaining in popularity; however, at the present time, there exist only a small number of studies in the literature on the use of CWs in mitigating pesticide contamina tion. A total of 26 studies representing 18 different wetland systems were found (Table 1). All wetlands in the following reviewed studies were con structed with the purpose of evaluating their effect on water quality. Pesticides are a diverse group of chemicals with various physiochemical properties that influence their transport and transformation potentials after being applied in the field. There are several classes of pesticides depending on the target organism, including herbicides, insecticides, fungicides, and nematicides. The majority of research evaluating pesticides in CWs has considered herbicides and organophosphate and pyrethroid insecticides. Owing to their different properties, each class of pesticide presents a unique challenge in the development of mitigation measures.
3.1. Herbicides Herbicides are an extremely heterogeneous class of chemicals with variable physiochemical properties. The reported octanol–water partition coeffi cient (log) Kow values range from 0.16 for dicamba to over 5.0 for flurox ypyr, making any generalization on their partitioning behavior impossible. Most herbicides are fairly water soluble, with solubilities reaching the 103 ppm range. Some, however, such as the popular trazine herbicide simazine, are relatively insoluble at 5 mg l 1. Runes et al. (2003) evaluated atrazine retention under various frequency and intensity of runoff events in a wetland consisting of five 40 m linked cells. Retention varied between 76% and 84% under the five flow regimes. A sixth experiment resulted in 100% of the applied atrazine recovered at the wetland outlet. The authors noted that treatment was most likely compro mised due to internal loading from runoff from adjacent fields (Runes et al., 2003). Atrazine retention was also evaluated by Moore et al. (2000). The authors estimated a necessary wetland length of 281 m for effectively mitigating input effluent of 147 g l 1. Effective removal of another triazine herbicide was noted by Stearman et al. (2003), who observed a mean
Table 1
Selected characteristics of constructed wetlands reviewed
Reference
Class*
System characteristics
Rose et al. (2006)
H, OC
2 sequential cells, mixed
Sherrard et al. (2004) Blankenberg et al. (2006) Blankenberg et al. (2006), Braskerud and Haarstad (2003), Haarstad and Braskerud (2005) Budd et al. (2009)
F, OP H, F H, F
Flow regime b
Size (m)a 2
2
Flow (m3 h 1)
HRT (d) R (%)
Ponded
14
Ponded
100 , 200
0–55 (H), 15–39 (OC) 98 3–47 25–67 (yr. 1), 11–19 (yr. 2)
Closed system mesocosm 8 parallel cells Stepped sections in expanded stream
Ponded S.F. S.F.
1.85 0.63 40 24 100 8.4
Ponded 45 28–63
3 n.r. n.r.
OP, P
Sediment basin, 1o, 2o cells
S.F.
450 long
252
Budd et al. (2009)
OP, P
Sediment basin, 1o cells
S.F.
720 long
72
Kohler et al. (2004)
Interconnected basins on golf course Sediment basin, 1o, 2o cells
S.F.
0.34–1.24 ha 1.8–19.4
Moore et al. (2007a,b, 2009), Bouldin et al. (2007) Moore et al. (2002), Schulz and Peall (2001), Schulz et al. (2003a) Moore et al. (2000, 2002)
H, OC, OP OP, P
0.04 (1o) 52–90 (P), 22–61 (OP) 0.75 64–94 (P), 52–82 (OP) n.r. n.r.
S.F.
180 22
n.r.
n.r.
95c (P)
OP
Single cell, mixed
S.F.
134 36
97–1152
n.r.
77–100c
H
4 single cells
S.F.
66 10
45.4
0.38
Moore et al. (2006), Schulz et al. (2003a,b)
OP
2 single cells
S.F.
50 10
31.8
n.r.
66–82c (H), 83 (OP) 100c (continued)
Table 1
(continued) Flow (m3 h 1)
HRT (d) R (%)
15–30
n.r.
0–84
3.6
7.4
n.r.
S.F.
40 3 (each) 27 12, 24 12 70 12
24.5
2.3
52 (OP)
Single cell—mixed Twin small
S.F. V/R
1 ha 11
4.2 0.01
30 n.r.
H
7 subsurface flow cells
S.S.
0.03–0.12
H
4 parallel cells
S.S.
4.9 1.2, 4.9 2.4 24 1
> 79 100 (OP), 0–36 (H) 2.3–20.6 59–95
0.2–0.03
3.8
Reference
Class*
System characteristics
Flow regime
Runes et al. (2003)
H
5 sequential cells
S.F.
Hunt et al. (2008)
2 sequential cells
S.F.
1 cell with 4 inlets
Matamoros et al. (2008) Cheng et al. (2002a,b)
OC, OP, P OC, OP, P H OP, H
Stearman et al. (2003) Borges et al. (2009)
Hunt et al. (2008)
Size (m)a
39
* H, herbicide; F, fungicide; OC, organochlorine; OP, organophosphate; P, pyrethroid; S.F., surface flow; S.S., subsurface flow; V/R, vertical/reverse flow; HRT, hydraulic residence time; R, removal efficiency; n.r., not reported. a Size in meters unless otherwise noted. b Mixed sections of open water and vegetated. c %R estimated from reported input/outputs.
Mitigating Nonpoint Source Pollution
15
removal of 65–96% for simazine, and 59–96% for the aniline herbicide metolachlor in vegetated cells over a 2 year period. Other herbicides have proven more recalcitrant to mitigation measures. Only 39% of ametryn was removed within 24 1 m subsurface flow CW that had a 3.8 day hydraulic retention time (Borges et al., 2009). The retention of certain chemicals varied substantially between studies. In one study, MCPA and mecoprop were effectively treated (>79% removal) over a 2 year period within a 1 ha wetland receiving effluent from a wastewater treatment plant. Removal of terbutylazine was inconsistent, with only 1% removal in the first year, but reaching 80% in the second year of monitoring (Matamoros et al., 2008). Cheng et al. (2002a) found that MCPA concentrations decreased by only 36% in another subsurface wetland, while removal of dicamba was negligi ble. The discrepancy in MCPA removal was most likely due to system variances, as the latter CW was only 1 m2 in size.
3.2. Organophosphate insecticides Organophosphates are comprised of two main groups, thionate triesters (P¼S) and oxonates (P¼O) (Stangroom et al., 2000a). All organophosphates are acetocholinesterase inhibitors and have toxicity to mammalian species. Although heralded as a better choice than their organochlorine predecessors due to their relatively short half lives, their acute toxicity to human and aquatic organisms is a serious environmental concern that has contributed to the restricted use of some organophosphate products (Bondarenko and Gan, 2004; Ragnarsdottir, 2000). Organophosphates are generally more soluble than pyrethroids, and therefore partition into the aqueous phase more readily. As with pyrethroids, there is generally a positive correlation between pH and rate of hydrolysis. However, photolytic degradation is much more prevalent for organophosphates in natural water systems (Stangroom et al., 2000b). Chlorpyrifos and diazinon are often detected in watersheds with agri cultural inputs at levels of ecological concern. Concentrations of diazinon in agricultural storm water runoff draining into the San Joaquin River Basin were found to be toxic to some fish and invertebrate species (Werner et al., 2004). A survey study of streams within the Central Valley of California found both diazinon and chlorpyrifos present at levels above those set for water quality standards in over 80% of samples analyzed (Bailey et al., 2000). Most research concerning organophosphate insecticides in CWs has focused on chlorpyrifos, diazinon, and methyl parathion. CWs have proven to be an effective mitigation strategy for reducing chlorpyrifos concentration in the water column. One study conducted in the Central Valley of California showed reductions in chlorpyrifos concentrations between 52% and 61% for two separate systems monitored over the course of a 4 month irrigation season (Budd et al., 2009). Two separate studies evaluated chlorpyrifos
16
A. T. O’Geen et al.
concentrations within a wetland located along the Lourens River in South Africa. In the first study, inlet chlorpyrifos concentrations reached a maxi mum of 1.3 g l 1 during a storm event, but were reduced to 0.03 g l 1 at the outlet (Moore et al., 2002). The inlet concentrations of 0.02 g l 1 after a second storm were reduced to below the detection limit at the outlet (Schulz and Peall, 2001). Chlorpyrifos concentrations in suspended sediment were detected at levels reaching 89.4 mg kg 1 at inlets, but decreased to below the detection limit at the wetland outlet in both studies. Studies have also demonstrated the potential of CWs for removing other organophosphates. Methyl parathion transport was evaluated within vege tated and nonvegetated wetland cells located at the University of Mississippi Field Station. Two studies evaluating simulated runoff events showed the vegetated cells to be 100% efficient at removing methyl parathion within 40 m (Moore et al., 2006; Schulz et al., 2003a). Azinphos methyl retention was also evaluated in the Lourens River wetland. Reductions in concentra tions ranged from 77% to 93% after a storm event, and 90% on average after five independent spray drift trials (Schulz and Peall, 2001; Schulz et al., 2003b). Parathion and omethoate were completely removed from the water column within the dual 1 m2 flow wetland chamber that was previously noted to be ineffective at removing MCPA (Cheng et al., 2002a). Diazinon, another heavily used organophosphate, appears to be more resilient to translocation and transformation processes within wetlands. Moore et al. (2007a) conducted a simulated runoff study in a three cell wetland located in the Beasley Lake watershed in Mississippi, USA. Less than 41% of the total diazinon mass was retained within the sediment retention basin or primary wetland cell. Although measurements were not reported for the outlet, low retention within the first two cells indicated that there was little mitigation of diazinon within the CW. Budd et al. (2009) observed similar behavior for diazinon within two CWs located in the Central Valley of California. Diazinon was only detected on four of the eight sampling dates. During one sampling period, diazinon was detected orders of magnitude higher at the outlet than the corresponding inlet. The authors hypothesized an external loading source to the wetland, but average seasonal removal efficiencies (68% and 92%) suggested less mitigation of diazinon compared to chlorpyrifos and pyrethroids (98–100%) within the same system (Budd et al., 2009). Lower removal efficiency of diazinon may be due to its relatively low hydrophobicity as compared to chlorpyrifos and pyrethroids (Table 2).
3.3. Pyrethroid insecticides Most pyrethroid insecticides on the market today are second generation or chemically stable derivatives of pyrethrins, the insecticidal ingredients derived from the chrysanthemum flower. Table 2 lists selected physicochemical
Table 2
Reported pesticide properties and removal efficiency (%R) rangesa
Chemical
Class*
log Kow
Solubility (mg L1)
%R
Reference
Ametryn Atrazine Bentazone Dicamba Dichlorprop Fenpropimorph Fluroxypyr Linuron MCPA
H H H H H H H H H
2.63 2.5 0.46 1.88 1.77 4.2 1.24 3 0.71
200 33 570 6100 350 4.3 91 63.8 273.9
39 0–84b 2 0–3 35 10–50 0 3–56 27–93
Mecoprop Metalaxyl Metalochlor Metamitron Metribuzin Propachlor Propiconazole Simazine Terbutylazine Azinphos methyl Chlopyrifos Diazinon
H H H H H H H H H OP OP OP
0.10 1.75 2.9 0.83 1.58 1.4–2.3 3.72 2.1 3.21 2.96 4.7 3.3
734 8400 1700 488 1050 580 100 6.2 8.5 28 1.4 60
23–91 0–41 57–97 7–58 11–40 14–67 13–25 59–96 1–80 90–100 52–100 0
Borges et al. (2009) Moore et al. (2000), Runes et al. (2003) Braskerud and Haarstad (2003) Braskerud and Haarstad (2003), Cheng et al. (2002a,b) Braskerud and Haarstad (2003) Blankenberg et al. (2007), Braskerud and Haarstad (2003) Braskerud and Haarstad (2003) Blankenberg et al. (2007), Braskerud and Haarstad (2003) Braskerud and Haarstad (2003), Cheng et al. (2002a,b), Matamoros et al. (2008) Braskerud and Haarstad (2003), Matamoros et al. (2008) Blankenberg et al. (2007), Braskerud and Haarstad (2003) Stearman et al. (2003) Blankenberg et al. (2007), Braskerud and Haarstad (2003) Blankenberg et al. (2007), Braskerud and Haarstad (2003) Blankenberg et al. (2007), Braskerud and Haarstad (2003) Braskerud and Haarstad (2003) Stearman et al. (2003) Matamoros et al. (2008) Schulz and Peall (2001), Schulz et al. (2003b) Budd et al. (2009) Budd et al. (2009) (continued)
Table 2
(continued)
Chemical
Class*
log Kow
Solubility (mg L1)
%R
Reference
Methyl parathion Omethoate Parathion Prothiofos Bifenthrin Cyhalothrin Cypermethrin Esfenvalerate Permethrin
OP OP OP OP P P P P P
3 0.74 3.83 5.67 >6 6.9 6.6 6.22 6.1
55 Miscible 11 0.7 < 0.001 0.005 0.004 0.002 0.006
100 100 100 100 69–84 71–90 52–64 77–87 90–94
Moore et al. (2006), Schulz et al. (2003a) Cheng et al. (2002a,b) Cheng et al. (2002a,b) Schulz and Peall (2001) Budd et al. (2009) Budd et al. (2009) Budd et al. (2009) Budd et al. (2009) Budd et al. (2009)
a
Physiochemical properties taken from Tomlin (2000). The lack of mitigation during one test likely due to external loading, average %R for first five tests * OP, Organophosphate; P, pyrethroid; H, herbicide.
b
81%, solubility in mg l
1
.
Mitigating Nonpoint Source Pollution
19
properties of some pesticides of interest (Laskowski, 2002). As evident from the water solubility and Koc values, pyrethroids are extremely hydrophobic and tend to bind to organic matter, including DOM (Bondarenko et al., 2006; Stangroom et al., 2000a; Zhou et al., 1995). Photolysis has been shown to be a potential degradation pathway for several pyrethroids including esfenvalerate, deltamethrin, and fenpropathrin (Stangroom et al., 2000b). In natural systems, however, binding to DOM will limit photolytic degradation. Hydrolytic degradation will most likely be the primary route of abiotic degradation for pyrethroids in wetland systems. The rate of hydrolysis generally increases with increasing pH, resulting in more polar products (Stangroom et al., 2000b). Sediment toxicity or bioavailability is usually estimated from the organic carbon based sediment concentration, as evident in application of the Equi librium Partitioning Theory (Di Toro et al., 1991). Although pyrethroids are fairly nontoxic to mammalian species, they display acute toxicity to aquatic organisms, especially invertebrates, at very low levels. The OC normalized LC50 values for the amphipod Hyalella azteca have been reported for l cyhalothrin (0.45 g g 1 OC), bifenthrin (0.52 g g 1 OC), deltamethrin (0.79 g g 1 OC), cyfluthrin, (1.08 g g 1 OC), esfenvalerate (1.54 g g 1 OC), and permethrin (10.83 g g 1 OC) (Weston et al., 2005). Several monitoring studies have attributed observed aquatic toxicity of benthic invertebrates to sediment contamination by pyrethroids (Amweg et al., 2006; Bay et al., 2004; Werner et al., 2004). Residue concentrations of pyrethroids in sediments have been detected in watersheds throughout the United States, especially in California (Budd et al., 2007; Kimbrough and Litke, 1996). Agricultural fields are a well documented source of pyrethroids in downstream sediment beds. Weston et al. (2004) detected pyrethroids in 75% of sediment samples collected within the agriculture dominated Central Valley of California (Weston et al., 2004). Pyrethroid residues have been frequently detected in the sediment from a number of urban streams in northern California (Amweg et al., 2006; Bacey et al., 2005; Weston et al., 2005). A few studies have considered the potential of wetlands for removing pyrethroid insecticides from the water column. Due to the hydrophobic nature of this class of chemicals, the studies have consistently shown the high efficiency for wetlands to remove pyrethroids from input waters. Seasonal average reductions in water concentrations for five pyrethroids ranged from 52% to 94% in one study (Budd et al., 2009). Moore et al. (2009) observed l cyhalothrin and cyfluthrin concentrations in a three cell wetland for a 55 day period following a simulated runoff event. While input concentrations were 17 and 64 g l 1, outlet concentrations peaked at 0.77 and 3.77 g l 1 for l cyhalothrin and cyfluthrin, respectively (Moore et al., 2009). In a small on farm system, Hunt et al. (2008) observed that pyre throid concentrations decreased by >60% at the outlet.
20
A. T. O’Geen et al.
3.4. Pesticide removal 3.4.1. Pesticide characteristics affecting removal Pesticide removal by wetlands may be influenced by both properties of the pesticides and the characteristics of the wetlands. Figure 2A is a plot of a pesticide octanol–water partition coefficients (Kow) against the reported removal efficiency. One of the difficulties in the correlation analysis was that there are often several reported chemical Kow values for the same compound in the literature. To reduce uncertainties, all log Kow values in Fig. 2 were derived from two sources. Only studies with calculated reductions in concentrations between two lateral points within the system (e.g., inlet and A % Reduction in concentration
100 80 60 40 20 0 0
1
2
3
4
5
6
7
8
log Kow B % Reduction in concentration
100
80
60
40
20
0 –6
–4
–2
0
2
4
6
8
10
12
log (Kow /sol.)
Figure 2 Wetland efficacy in reducing pesticide concentrations (% reduction) in relation to (A) octanol water partition coefficient (log Kow) and (B) log (Kow/solubility).
Mitigating Nonpoint Source Pollution
21
outlet) were included. Also, multiple year results were separated and used independently. This resulted in several reduction values (%R) for the same chemical. Negative values were replaced with zero, signifying a lack of mitigation. Although a clear linearity was not observed, a general trend of improved removal was noted with increasing Kow values (Fig. 2A). With one exception, log Kow values >4.2 resulted in >50% reduction in pesticide concentrations, indicating that for highly hydrophobic chemicals, sorption is the primary driving force of removal. Between log Kow values of 1 and 4, there were large variations in the %R values, indicating that chemicals in this range have the potential for removal by wetlands, but the performance likely depends on system characteristics. Miscible chemicals (log Kow <1) generally had lower %R. This trend was even more pronounced when the Kow was divided by water solubility (Fig. 2B). This suggests that pesticides having high water solubility are not effectively mitigated by wetlands as the primary strategy, independent of system characteristics. Overall, CWs have shown tremendous promise as a mitigation option for removing insecticides. We found 27 individual %R values reported for 12 organophosphate and pyrethroid insecticides (Table 2). With the excep tion of diazinon, all %R values were >52%, with several of these com pounds completely removed from the water column at the outlet. In comparison, removal of herbicides appears to be much more variable. In some cases, pesticides passed through the system uninhibited, while in others concentrations were effectively reduced. In addition to the inherent properties of pesticides, the behavior of pesticides in a given wetland is controlled by many environmental variables. Conditions such as hydraulics and hydrology of the wetland are primary external forces affecting pesticide retention and removal. Other important factors include vegetation type and density, availability of organic matter and other substrates for microbial growth, and nutrient uptake demand by plants (Phipps and Crumpton, 1994; Woltemade, 2000). To achieve maximal contaminant removal, it is important to increase retention time within the CW and decrease the persistence of the retained contaminants by providing optimum conditions for biotic and abiotic transformations. Physical removal may be a result of pesticide adsorption by soil and plants, and elimination of the pesticide associated with the suspended particles due to sedimentation and burial, plant filtration, and other physical trapping mechanisms. 3.4.2. Effect of vegetation Studies have shown a positive correlation between vegetation density and pesticide removal due to increased sorption to macrophytes and organic matter, physical trapping of pesticide laden particles by plants, or a reduction in hydraulic conductivity (Moore et al., 2002; Schulz et al., 2003c). Sorption to plants has been shown to be the primary sink in highly vegetated agricultural ditches (Bennett et al., 2005). Only a few studies were designed with the intent
22
A. T. O’Geen et al.
to directly evaluate the role of vegetation in pesticide removal. Stearman et al. (2003) observed herbicide removal over a 2 year period in wetland systems, where half of the cells contained Scirpus validus (600 stems m 2) and the other half were absent of vegetation. In the absence of vegetation, average removal efficiencies for metolochlor and simazine were 63% and 64%, respectively. Removal increased to 82% and 77% for metolachlor and simazine, respec tively, in vegetated cells. In a similar study, methyl parathion removal was evaluated in the presence and absence of vegetation. The vegetated cells were planted with both Juncus effuses (256 ramets m 2) and Leersia oryzoides (43 ramets m 2). Concentrations were below detection limits in semipermeable membrane devices (SPMD) deployed at the outlet of the vegetated cells 96 h postexposure of a simulated storm runoff event. The mean concentration in the SPMD at the outlet of the nonvegetated cells was 8.83 g g 1, indicating downstream transport of methyl parathion was minimized in the presence of vegetation (Moore et al., 2006). Rose et al. (2006) did not observe a difference in pesticide removal for diuron, aldicarb, or fluometuron between vegetated and open water cells of a CW draining a cotton field during the first monitoring season. During the second season, however, fluometuron removal was 17% higher in the vegetated portion in the beginning of the season, but lower at the end of the season once an algal bloom occurred in the open water section. Other research has provided indirect evidence for the positive correlation between vegetation and pesticide removal. Moore et al. (2002, 2007a, 2009) evaluated phase partitioning of several organophosphate and pyrethroid insec ticides in wetland systems after simulated rainfall events. The total chemical mass associated with plants was considerable for chlorpyrifos (25%), diazinon (43%), l cyhalothrin (49%), and cyfluthrin (76%) after the events. Budd et al. (2009) attributed inefficient mitigation of pyrethroids and organophosphates within a portion of a monitored wetland to a lack of vegetation and subsequent channeling within that section. These studies together indicate the importance of vegetation within a wetland to provide sorption sites and slow down water flow allowing deposition of sorbed pesticides. 3.4.3. Hydrology and hydraulics The hydrologic and hydraulic properties of a wetland have a dramatic effect on transport of pesticides through CWs (Braskerud and Haarstad, 2003). Pesticide removal efficiency has been shown to decrease considerably with increasing flow (Stearman et al., 2003). Thus, characteristics that control residence time of pesticides in CWs affect attenuation. The rate of sedimen tation is often a critical process for pesticide removal from the water column. Sedimentation is dependent on hydrologic residence time, sediment particle size and texture, flocculation of suspended particles, and vegetation (Fennessy et al., 1994). Unfortunately, few studies reported flow rates or estimated residence time of the test systems, making comparative analysis impossible. A comparison of simazine and metolachlor removal in cells with varying
Mitigating Nonpoint Source Pollution
23
hydraulic residence times (HRT) demonstrated removal efficiencies up to >90% for vegetated cells with HRT >10 days, while for those with HRT <4 days, removal was <70% on average for both herbicides. The HRT increased by an average of 30% in cells planted with common bulrush (600 stems m 2) as compared to unvegetated cells (Stearman et al., 2003). A HRT of approximately 18 h was found to be sufficient for reducing the concentra tion of several pyrethroids by 64–94% (Budd et al., 2009). The HRT of a system should be maximized as much as possible to assure the greatest attenuation due to sorption and degradation. However, in prac tice, this is often a challenge. Obtaining enough land to achieve long resi dence time is often economically infeasible. Also, conditions of a particular wetland often change over time as vegetation biomass varies both spatially and temporally, and input flow also changes with time. Dense vegetation has been shown to influence both the flow rate and sedimentation patterns within wetlands (Fennessy et al., 1994). In addition, erosion over time can lead to changes in flow patterns, which can influence HRT. Newly constructed wetlands with a lack of established vegetation are prone to channeling, thereby decreasing the HRT and increasing the potential for downstream transport of pesticides (Budd et al., 2009). In determining an optimal HRT for a system, wetland managers must consider many variables, such as the pesticides of primary interest, the level of desired mitigation, and the range of potential input concentrations. For instance, estimated residence time necessary to achieve a final atrazine concentration of 20 mg l 1 increased from 30–39 days for cells with an initial concentration of 73 mg l 1 to 133–143 days for cells with an initial concentration of 147 mg l 1 (Moore et al., 2000). Maintaining effective mitigation performance to account for varying environmental conditions will be a challenge for wetland managers. 3.4.4. Pesticide sorption and degradation Pesticide sorption and transformation are important considerations when evaluating wetland performance. Adsorption potential of a pesticide is known to depend on the properties of both the pesticide and the sorbent phase, such as soil or sediment. For hydrophobic chemicals, sorption to soil or sediment is influenced not only by the quantity of organic matter, but also by the binding characteristics of the organic matter (Ahmad et al., 2004; Lee et al., 2003). In addition, pesticides have been shown to become less available to microbial degradation with longer contact time, a concept known as ‘‘aging’’ (Ahmad et al., 2004). The Kd values of several organo phosphates were shown to increase dramatically after only 1 month of aging (Bondarenko and Gan, 2004). It is likely to detect higher concentrations associated with sediment further downstream, a phenomenon known as enrichment, because silt and clay settling times are longer and their binding capacity is higher (Gan et al., 2005).
24
A. T. O’Geen et al.
A wetland may be more chemically reactive, due to the presence of favorable conditions, such as pH, temperature, and redox conditions, that can lead to enhanced transformations of the pesticide. Redox potential of a system has been shown to have a dramatic effect on persistence and degrada tion rates of pesticides in wetlands (Seybold et al., 2001). For example, the persistence of chlorpyrifos in sediments increased significantly under anaero bic conditions (t1/2 ¼ 125–746 days) in comparison to aerobic soils (t1/2 ¼ 1.8–4.9 days) (Bondarenko and Gan, 2004). The biotic degradation pathway is dependent on several factors including microbial population, temperature, and the contaminant bioavailability. It is possible that repetitive exposure to the same pesticides over time may cause induction and adaptation of microbes, leading to establishment of organisms capable of rapidly degrad ing the pesticides in the wetland (Felsot et al., 1981; Racke and Coats, 1988). On the other hand, although pesticide degrading microbes may become enriched in a wetland, the strong binding capacity of hydrophobic chemicals, such as pyrethroids, has been found to hinder microbial degradation (Lee et al., 2004). The aging of sediment has also been shown to increase the sequestration of hydrophobic chemicals, which further decreases the micro bial degradability of sorbed pesticides (Ahmad et al., 2004). 3.4.5. Summary of pesticide removal in CWs To summarize, CWs are expected to be large sinks for pesticides due to enhanced sediment deposition, plant sorption and uptake, and microbial degradation. A number of studies have demonstrated the potential for CWs to remove pesticides in input flows; however, conditions of CWs as well as pesticide types studied so far are highly variable, preventing a meaningful statistical comparison. In general, pesticide removal efficiencies were shown to vary between chemical, design, hydrology, and vegetation characteristics. Increasing the wetland HRT and maximizing vegetation density help optimize wetland performance. However, there exists a need for more research quantifying the relationship between CW size, HRT, flow, vege tation density, and pesticide removal with chemicals of varying physio chemical properties. This information will be vital to managers for optimizing the performance of CWs within the confines of each system.
4. Nitrogen (N) 4.1. Environmental impacts Constructed wetlands have become a popular BMP for treatment of nitrate in waste waters. Nitrate contamination of surface water and groundwater resources is prolific in agricultural regions. Excess nitrogen causes eutrophi cation in surface waters and is the limiting nutrient responsible for dead
Mitigating Nonpoint Source Pollution
25
zones in estuaries and oceans (Boesch et al., 2001). In agricultural regions, nitrate is a major water quality constituent of concern in groundwater (Nielsen and Lee, 1987). Nitrate is a human health risk when present in drinking water due to its potential for causing methemoglobinemia in infants. Approximately one third of the total N loading in the planet’s rivers is anthropogenic, originating from agriculture, sewage, urban runoff, and atmospheric deposition (Meybeck, 1982).
4.2. N cycling in CWs Forms of nitrogen in irrigated agricultural runoff include nitrate, ammo nium, and organic N (dissolved and particulate). The type of N in input waters is important because wetlands are not as effective at removing organic N and ammonium, as they are for nitrate (Phipps and Crumpton, 1994). Nitrogen inputs to CWs in cropland settings come from field and surface water runoff, agricultural return flows and tile drains, but can also result from biological fixation, and wet and dry atmospheric deposition (Fig. 3). Unlike treatment wetlands that receive wastewater with high levels of dissolved organic N and ammonium, the dominant form of N in CWs that receive agricultural runoff is nitrate (Baker, 1998). The relative amounts of organic N and ammonium depend on organic matter minerali zation rates, soil properties, and agricultural practices such as the use of manures. The dominant N removal mechanism in CWs is respiratory denitrifica tion, the microbially mediated transformation of nitrate to N2O and N2 gasses in the absence of oxygen (Kadlec and Knight, 1996). The low redox potentials in CW soils result in the perfect environment for denitrification. This process is mediated by heterotrophic microbes at redox potentials around 250 mV. Other N removal mechanisms, which account for a fraction of N removal in CWs include: plant assimilation, sedimentation and burial of particulate N (organic N and N adsorbed to particles), and ammonia volatilization (Fig. 3; Tanner et al., 2002). Nitrate leaching can also be considered a removal mechanism, although it clearly does not result in an environmental improvement unless nitrate is denitrified in groundwater. There are many published studies that have documented denitrification as the primary NO3 removal mechanism in wetlands (Kadlec and Knight, 1996). Only a handful of studies have directly measured denitrification process in CWs receiving NPSP from agriculture (Hernandez and Mitsch, 2007; Poe et al., 2003; Xue et al., 1999). Comparisons of denitrification rates among studies in CWs is difficult because values vary widely depending on climate, vegetation, source water chemistry, hydrology, and methods used (Seitzinger, 1993). The dominant controlling variables on denitrification rates are dissolved oxygen concentration, nitrate levels, sediment organic
Inputs: Influent NO3 > organic N > NH4, > N sorbed to particles Wet and dry deposition Biotic and abiotic fixation Litter deposition
Volatilization
Inputs
Water column
NH4 + NO3
Assimilation
Export
Algae
Sedimentation and mineralization
Organic N Aerobic soil zone Mineralization
NH4
Nitrification
NO3
Plant and microbial assimilation
Anaerobic soil zone NO3
Denitrification
Leaching
Figure 3
Schematic of the nitrogen cycle in CWs.
N2O, NxO, N2
Mitigating Nonpoint Source Pollution
27
matter concentration and quality, temperature, and macrophyte cover (Poe et al., 2003). In surface flow wetlands, the rate of denitrification is also controlled by the degree of mixing between the water column and anoxic soil. Thus, water exchange and nitrate diffusion are important factors. Studies that have used 15N tracer methods and the acetylene inhibition technique to measure denitrification in CWs in agricultural settings have demonstrated similar findings with rates ranging from 0.02 to 11.8 mg N m 2 h 1 and average rates around 2 mg N m 2 h 1 (Fleischer et al., 1994; Poe et al., 2003; Smith et al., 2000; Xue et al., 1999). The range in values represents seasonal temperature effects, differences in nitrate loading, and microbially labile carbon concentrations. Significant correlation between nitrate/nitrite and denitrification rate (P < 0.01; r2 ¼ 0.98) have been demonstrated, where pulses in nitrate after storm events stimulated denitrification (Poe et al., 2003). Studies commonly show maximum rates in the summer and minimum rates when temperatures decrease (Poe et al., 2003; Xue et al., 1999). The optimum temperature range for denitrification is 20–25 C, and the rate decreases below 15 C as diffusion rates and microbial activity decrease (Beutel et al., 2009; Spieles and Mitsch, 2000). Wetland soil denitrification rates were shown to increase by as much as two orders of magnitude with a 21 C increase from 4 C (Sirivedhin and Gray, 2006). Thus, the ability of CWs to transform nitrate from agricultural runoff is compromised in areas where peak runoff and N loadings occur during the cold seasons. In settings where CWs receive input waters from streams or rivers, high N loads are common in fall, winter, and early spring runoff. However, N removal can still occur if a bulk of the N is organic N due to removal by settling and burial (Braskerud, 2002b). The availability of organic carbon for microbes is an important factor regulating denitrification rates (Beauchamp et al., 1989). Vegetation is the primary carbon source in many CWs and vegetation type affects the avail ability of carbon, serving as the ‘‘parent material’’ that is used by heterotrophic denitrifiers. Hernandez and Mitsch (2007) observed differences in denitrifica tion potential (DNP) within experimental wetlands that corresponded to differences in vegetation and hydrologic environment. DNP was highest ( 0.065 mg N h 1 kg 1) in zones where emergent macrophyte commu nities were dominant and soils were continuously submerged. DNP was lower, around 0.02 mg N h 1 kg 1, in open water communities and the forested edge of the wetland. Organic matter quality, as measured by cold water extraction, had a positive linear relationship with DNP. Typha spp. was the dominant emergent macrophyte, where labile carbon forms (high levels of cold water extractable C) and DNP rates were highest. Environments with plants that decompose more readily to labile forms of organic matter result in higher denitrification rates (Hernandez and Mitsch, 2007). Denitrification is low in open water bodies where water levels are too high for emergent macrophyte establishment or where woody species are the dominant carbon
28
A. T. O’Geen et al.
source (DeLaune et al., 1996; Kadlec, 2005; Westerman and Ahring, 1987). In agricultural settings, there is often large inputs of organic matter from the eroded topsoil or from algae blooms (Maynard, 2009). A potential adverse effect of nitrogen removal by denitrification in CWs is the production of N2O. N2O is a greenhouse gas several times more potent than CO2. It can be argued, however, that once NO3 has entered the hydrologic cycle, its ultimate fate is to be denitrified. Thus, the location where denitrification occurs is inconsequential assuming the conversion ratio of nitrate to N2O is similar in wetlands compared to other large NO3 sinks (Mitsch et al., 2001). In settings where organic N or NH4 are the dominant forms in input waters, such as systems that receive animal waste, mineralization and nitrifi cation must first occur in order to facilitate significant N removal. Nitrifi cation occurs where oxygen is present. In CWs, oxygen is present in the water column and in the soil aerobic zone, a thin interface between the water column and the anaerobic root zone (Fig. 3; Reddy et al., 1989). Since oxygen diffusion rates into flooded soil are very low, the movement of oxygen through aerenchymous tissue of wetland plants into the root zone is an important process that maintains this aerobic layer. In this soil envi ronment, transformations of organic N and NH4 to nitrate occur in the rhizosphere. Other factors that influence N transformations to NO3 include chemical oxygen demand, available carbon source, pH, and temperature. NH4 is a component in many fertilizers applied to fields, commonly as anhydrous ammonia, ammonium nitrate, or ammonium sulfate. Ammonium can be oxidized via nitrification to NO3 in agricultural soils. Ammonium can be transported from fields since it is adsorbed to cation exchange sites of soil colloids and fixed by vermiculite clay minerals. However, ammonium tends to build up in anaerobic soil horizons where large soil organic matter pools slowly decompose. Wetland mineralization rates are variable ranging from 4 and 357 mg N m 2 day 1 with a mean of 111 124 mg N m 2 day 1 (Martin and Reddy, 1997). A diffusion gradient for NH4 exists in wetland soils because nitrification occurs in the aerobic zone (Fig. 3). The rate of diffusion of NH4 into the overlying aerobic soil horizon is very slow, much slower than NO3. Thus, in settings where NH4 and organic N dominate, removal rates are first limited by sedimentation and then by mineralization and diffusion into aerobic zones where nitrification can occur followed by translocation of nitrate to anaerobic zones where denitrification occurs.
4.3. N removal efficiency Studies of CWs for waste water treatment have found that NO3 removal efficiency decreases with increasing hydraulic load and as wetland surface area decreases (Kadlec and Knight, 1996; Knight et al., 2000; Tanner et al., 1998). Mitsch and Gosselink (2000) have summarized nitrate removal from
Mitigating Nonpoint Source Pollution
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agricultural runoff as a function of nitrate loading from two wetlands in the Midwest, USA, receiving dilute NO3 input concentrations. They found that nitrate removal, calculated on an aerial basis (g N m 2 yr 1) increased with NO3 loading. However, when calculated on a mass or concentration basis, NO3 removal decreased with increased N loading. While mass removal increases with greater N loading calculated on an aerial basis, differences in concentration between input and outputs may be insignificant at high loading rates (Kadlec, 2005). Mitsch and Gosselink (2000) suggest that the tradeoff between percent NO3 removal and NO3 export load occurs at input loads of 50 g NO3–N m 2 yr 1 in Midwestern climates. N loading comparisons are difficult to extrapolate among CWs across the nation or globe because in agricultural settings, flow and nitrogen load vary across a wide range of temporal scales (Table 3). Wetland characteristics (shape, size, depth, age, sediment characteristics, and vegetation) also vary widely. Most studies of CWs receiving NPSP from agriculture report NO3 removal efficiencies ranging from 30% to as high as 99% (Table 3). Similar studies of NO3 removal in cold environments, which also tend to have short HRTs, range from being a NO3 source to up to 15% removal (Table 3; Bastviken et al., 2009; Braskerud, 2002b; Koskiaho et al., 2003). Studies have demonstrated that NO3 removal responds to N pulses (Phipps and Crumpton, 1994; Poe et al., 2003). This response to N pulses was induced after episodes of little or no nitrate influx suggesting that denitrification in these settings was N limited. Nitrogen in NPSP is highly variable in agricultural settings. In CWs where contaminants are supplied by runoff from streams, seasonal patterns in total N load exist. High total nitrogen (TN) loading is often associated with high flows in spring and fall runoff. Low TN loads are observed during summer at low stream flow where N removal processes have more time to occur (Hill, 1996). Seasonal trends in N form also affect N removal rates. In a study of CWs in Illinois, Phipps and Crumpton (1994) found that N removal rates were high when nitrate was the dominant form of TN. These wetlands became sources of N in summer months when organic N was the dominant form of TN. In settings where CWs are supplied by tailwaters, the relationship with flow is less clear, and variability in TN and NO3 is a result of the catchment size, variety of crops grown, timing of fertilization, and crop rotations (Brauer et al., 2009). In irrigated agriculture, where high runoff events are less frequent, a design that accommodates low to moderate flows is needed. Nitrate removal is greatest in settings where NO3 makes up a majority of the TN load. In CWs receiving input water from agricultural streams, N removal efficiency was greatest (up to 93%) in seasons when NO3 comprised most of the TN input load (Phipps and Crumpton, 1994). In contrast, N removal was low (8%) and some CWs were sources of N ( 22% to 33%) during seasons where organic N comprised most of the TN load.
30
Table 3
Reported nitrate removal efficiencies relative to select wetland characteristics
Project
Location
HRT (d)
Area (ha)
Depth (m)
Input (mg l 1)
Rem. Eff. (%)
Hey et al. (1994)
Illinois
–
2–3.5
1–1.5
1.22
85.5–98
Mustafa et al. (1996) Phipps and Crumpton (1994)
Florida Illinois
– –
49 1.9–2.4
– 0.6–0.7
1.69 –
26 78–95
Comin et al. (1997)
NE Spain
–
–
0.1–0.5
–
50–98
Hunt et al. (1999)
North Carolina
1–111
3.3
0.3–2
6.6
51
Larson et al. (2000) Kovacic et al. (2000)
Illinois Illinois
– 11–21
0.60–0.78 0.3–0.8
– 0.4–0.9
0.1–52 –
37–65 34–44
Woltemade (2000) Borin et al. (2001)
Midwest NE, Italy
– –
0.03–3.7 0.32
– –
– –
20–80 1
Braskerud (2002b)
Norway
–
0.035–0.09
0.2–0.8
0.75–2.8
1 to 9
Koskiaho et al. (2003)
Finland
0.25–1.6
0.48–0.6
0.9–2
2.4–7.9
0–36
Jordan et al. (2003)
Maryland
12–19
1.3
>1
0–2
52
Notes
River water, agricultural watersheds; data from 1991, April–October River water; Total N only Same site as Hey et al., 1994. Data from 1991 season, April–November Rice field runoff over growing season In stream wetland; removal was a load reduction Vertical seepage study Spring flow, tile drainage; Removal was lowest in lowest HRT Comparison of case studies Crop runoff with waste water applied In stream wetlands, agricultural watersheds Removal increased with increase in HRT, no removal at HRT of 0.25 day Year round storm runoff from agriculture
Tanner et al. (2005)
New Zealand
1.5–51
0.026
0.3
11
11–46
Kovacic et al. (2006) Moreno et al. (2007) Mustafa et al. (2009)
Illinois NE Spain Ireland
7–12 1–4 –
0.16–0.4 0.005–0.05 0.12–0.24
0.4–0.5 0.1 1–1.5
1.5–8.9 5.8–20.7 3.81
16–43 24–43a 74
Bastviken et al. (2009)
Sweeden
1–3
0.002
0.4
–
3–15
Beutel et al. (2009)
Washington
8
0.7–0.8
0.6
1.3–1.4
90–93
Moreno et al. (2010)
NE Spain
2–15
0.005–0.5
0.1
–
34–87
HRT, hydraulic residence time. a Removal was calculated from total N.
Seasonal mass removal rates from dairy pasture runoff Tile drain input water – Dairy farm effluent; very little outflow Compared emergent versus submersed vegetation types Runoff during growing season 10–22 C Received runoff during growing season. Compared size and HRT
31
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A. T. O’Geen et al.
For CWs receiving storm runoff from agricultural fields, the wetland to watershed area is an important consideration. Generally speaking, N removal is highest in larger wetlands (> 0.5 ha) where HRTs are around one day or more (Table 3). Most studies agree that N removal efficiencies increase as hydraulic loading rate decreases and HRT increases (Jordan et al., 2003). Some of the highest removal rates reported in the literature for CWs receiv ing agricultural NPSP are 90%. These sites have in common warm tem peratures during runoff, large area, and HRTs 1 day (Table 3; Beutel et al., 2009; Borin and Tocchetto, 2007; Comin et al., 1997; Hey et al., 1994; Moreno et al., 2007, 2010; Phipps and Crumpton, 1994). Nitrogen removal is lowest in cold climates and/or where wetland area is small relative to its contributing area (Table 3; Bastviken et al., 2009; Braskerud, 2002b; Koskiaho et al., 2003; Mustafa et al., 2009). In such settings, longer water retention times are needed (Kadlec, 2005). The wide range in removal efficiencies observed among CWs in similar environments may also be a result of variability in input flow (Carleton et al., 2001; Jordan et al., 2003).
5. Phosphorus (P) 5.1. Environmental impacts In many agricultural systems, nutrient management strategies maximize nitrogen availability and uptake, often resulting in phosphorus (P) applica tion rates that exceed crop requirements (Whalen and Chang, 2001). As a result, many agricultural areas have experienced a buildup of soil P above that required for plant growth, with reported excess application rates of 1–9 kg P ha 1 yr 1 in the United States (Slaton et al., 2004) and 20 kg P ha 1 yr 1 in Europe (Edwards and Withers, 1998). Phosphorus is relatively immobile in most soils, and generally remains close to the point of applica tion. Consequently, decades of fertilization have resulted in high soil P concentrations, which can be transported from fields primarily as erosion during storm and irrigation events. The discharge of agricultural runoff into surface water bodies has resulted in dramatic shifts in trophic relationships (Jeppesen et al., 2000), resulting in part from elevated P concentrations due to its limiting status in many freshwater ecosystems. CWs have become a popular management practice to remove P from agricultural runoff (Jordan et al., 2003; Raisin and Mitchel, 1995; Reinelt and Horner, 1995). However, due to the conservative nature of P in wetlands (i.e., no significant gaseous loss pathway), sustainable long term P removal has proven to be particularly challenging given that wetland soils provide the only long term P sink (DeBusk and DeBusk, 2000, DeBusk et al., 2005). Although there has been a tremendous amount of work conducted on the fate of P in freshwater aquatic systems (Reddy et al.,
Mitigating Nonpoint Source Pollution
33
1999; Sharpley, 1999), there is much less known with regards to the mechanisms of P retention in CWs receiving agricultural runoff.
5.2. Phosphorus forms in CWs In agricultural watersheds, phosphorus entering wetlands is typically present in both organic and inorganic forms that are either dissolved (<0.45 mm) or particulate (>0.45 mm). In most agricultural soils, 50–75% of P is inorganic, with 60–90% of P transported from cultivated fields in the particulate form (Sharpley, 1999). While dissolved inorganic P (DIP) is, for the most part, immediately available for biological uptake, particulate forms of P (PP) must first be transformed before biological utilization can occur. The extent to which the PP fraction becomes bioavailable is dependent upon a range of chemical, physical, and biological processes (Uusitalo and Elknom, 2003), and thus, PP represents a variable but long term source of P for aquatic biota. Different fractions of inorganic PP and the relative bioavailability of each fraction are operationally defined based on a chemical extraction scheme, typically consisting of four sequential extractions of increasing recalcitrance (Cooke, 1992; Hieltjes and Lijklema, 1980; Psenner et al., 1988; Reddy et al., 1998). These fractions include: (i) exchangeable P, (ii) Fe and Al bound P, (iii) Ca and Mg bound P, and (iv) residual P. The bioavailable fraction of PP (i.e., exchangeable P) has been reported to range between 5% and 30% for agricultural runoff (DePinto et al., 1981; Dorich et al., 1985; Maynard et al., 2009; Uusitalo et al., 2000) and 15–32% in CWs (Maynard et al., 2009). In general, wetlands possess conditions conducive for PP transformations to occur including: shallow water depths, short settling times for suspended sediment, anaerobic soils, and fluctuating hydroperiods. Wetlands have been shown to be effective sinks of PP through the retention of sediment and particulate organic material (Braskerud, 2002a; Johnston, 1991; Richardson, 1999), however, deposition of PP may result in its transforma tion to soluble forms via Eh/pH driven reactions (e.g., iron oxide dissolu tion) and kinetic processes (e.g., desorption and organic P mineralization) (James et al., 2002). When accounting for these potential transformations, the fraction of PP that is potentially bioavailable has been reported to range from 50% to 70% of PP (Dorich et al., 1985; James et al., 2002; Maynard et al., 2008; Pionke and Kunishi, 1992). Additionally, wetlands are known for their ability to transform inorganic P into organic forms (e.g., plant and microbial assimilation), thus minimizing the immediate impact of P inflows (Brix, 1997; Ga¨chter and Meyer, 1993). Biogeochemical cycling of P in wetlands is complex; therefore, to better assess the efficacy of CWs to attenuate P loads, it is critical to evaluate the mechanisms by which these systems transform and remove different forms of P, with particular emphasis on the bioavailable fractions.
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A. T. O’Geen et al.
5.3. P transformations Phosphorus retention in CWs is controlled by a range of physical, chemical, and biological processes, including sedimentation, filtration, chemical sorp tion and precipitation, redox processes, microbial interactions, and uptake by vegetation (Reddy and DeLaune, 2008). The three dominant retention mechanisms include: storage in biomass (biological), sorption to soil (chemical), and formation and accretion of new mineral and organic soils (physical) (Fig. 4; Kadlec, 1997; Reddy and DeLaune, 2008). Phosphorus that enters the wetland water column is quickly taken up by bacteria, periphyton, and aquatic plants. However, studies using P radio isotopes have shown that wetland biota provide a small and typically short term sink for P, while wetland soils serve as larger long term sinks (Davis, 1982; Richardson and Marshall, 1986). In one study it was found that of the total 32P added to the Everglades water column, macrophytes contained less than 10%, periphyton around 20%, and soils around 60% of P added (Davis, 1982). In a Michigan mesocosm study, 80–90% of added P was located in the soil compartment after 1–2 weeks (Richardson and Marshall, 1986). When wetland plants and microbes decompose, most of the P contained in cellular materials is mineralized and made available for further cycling, while a smaller fraction is stored within refractory organic compounds that con tribute to the accretion of new soil (Fig. 4). The chemical processes of adsorption to particles and settling is consid ered one of the most important long term P sequestration mechanisms (Reddy et al., 1995; Richardson, 1985), although rates of P removal by this process can vary significantly due to differences in biogeochemical conditions. Wetland systems with the highest P adsorption capacity are typically neutral to acidic mineral soils with high levels of Fe and Al (hydr)oxides (Richardson, 1985; Sah and Mikkelsen, 1986) or alkaline mineral soils with high concentrations of Ca (Litaor et al., 2003). Iron and aluminum (hydr)oxides occur in soils as mixtures ranging widely in their degree of crystallinity, particle size, surface area, and reactivity (Jones and Bowser, 1978; Schwertmann, 1988). It is widely recognized that poorly crystalline oxides exhibit higher P sorption capacity compared with more crystalline phases, due to their larger surface area per unit volume (Parfitt, 1989; Parfitt and Childs, 1988). The P sorption capacity of wetland soils is strongly influenced by redox processes involving iron and its potential interaction with sulfur. Phosphorus solubility in wetland soils is directly affected by changes in redox potential (Patrick, 1964). At low Eh values (i.e., 100 to 250 mV) P solubility increases resulting in high P concentration in soil pore water (Ann et al., 2000). The dominant processes controlling phosphorus solubility in anaerobic systems are thought to be the reduction and dissolution of iron and its reprecipitation as ferrous minerals (Reddy and DeLaune, 2008). In many wetland systems, the
Inputs: PIP > DIP > POP > DOP Litter deposition Inorganic P
Inputs Water column
DIP
Assimilation
Aerobic soil zone DOP + POP Mineralization
Export
Algae
Sedimentation and mineralization
Organic P
DIP PIP Sedimentation
Plant and microbial assimilation
DIP Anaerobic soil zone
DIP POP Peat accretion
a)
PO43–+ Fe3+
Fe(OH)3–PO4
Adsorbed P PIP (Fe, Al or Ca bound P)
Aerobic Anaerobic
Leaching upon saturation of soil sorption sites
Fe(OH)3–PO4 SO42–
SRB
H2S
H2S + Fe(OH)3–PO4
FeRB PO43–+ Fe2+
FeS
Figure 4 Schematic of phosphorus cycle in constructed wetlands. Phosphorus fractions include particulate inorganic P (PIP), dissolved inorganic P (DIP), particulate organic P (POP), and dissolved organic P (DOP). Magnified insert (A) shows the effects of sulfate reduction on iron phosphate complexes. SRB, sulfate-reducing bacteria; FeRB, Fe(III)-reducing bacteria; Fe(OH)3, amorphous Fe(III) oxide. Fe(OH)3 PO4 complexes can be reduced biotically via FeRB or abiotically via H2S.
36
A. T. O’Geen et al.
presence of a thin oxidized layer at the soil–water column interface is important in regulating P flux between the soil and water column (Chambers and Odum, 1990; Scudlark and Church, 1989). The reduction and dissolution of crystalline Fe and its reformation as poorly crystalline Fe within this oxidized layer provides an important trap for P due to its high P sorption properties (Fig. 4; Chambers and Odum, 1990; Patrick and Henderson, 1981; Richardson, 1985; Scudlark and Church, 1989). In many agricultural areas, the leaching of SO4 from fields has been linked to eutrophication in freshwater wetlands due to its effect on P mobility (Bostrom et al., 1982; Caraco et al., 1989; Lamers et al., 1998; Lucassen et al., 2004). In CWs, sulfide produced during sulfate reduction reacts rapidly with dissolved Fe(II) in pore water or Fe(II) sorbed to mineral surfaces (Bostrom et al., 1982; Heijs et al., 1999; Moore and Reddy, 1994; Patrick and Kahlid, 1974; Roden and Edmonds, 1997; Rozan et al., 2002). As dissolved iron availability decreases, sulfide reacts with organic and mineral bound iron complexes. This can result in the release of P associated with redox sensitive iron pools and organo mineral complexes (Fig. 4; Kleeberg and Dudel, 1997; Lamers et al., 1998; Roden and Edmonds, 1997; Rozan et al., 2002). The removal of bioavailable P fractions (e.g., DIP and labile PP) via sorption processes is an important mechanism for limiting eutrophication of surface waters. However, the P sorption capacity of wetlands receiving con tinued exposure to elevated P inputs has been shown to diminish as sorption sites become saturated (Richardson, 1985). For example, high initial rates of P removal were reported in 10 freshwater wetlands in Maryland, followed by large exports of P after a few years, thus suggesting a potential limitation of wetlands to remove P over the long term in watersheds receiving high P loads (Richardson, 1985). In systems that experience high sedimentation rates, however, the influx of new surface material with new sorption sites may prevent P saturation (i.e., saturation of P adsorption sites) in CW soils (Maynard et al., 2009). The accumulation of new soil, via deposition of exogenous mineral and organic sediments and endogenous organic matter, is the dominant process responsible for sustained long term P retention (Richardson, 1999), and has been shown to operate over a wide range of climatic and geographic conditions (Craft and Richardson, 1993; Faulkner and Richardson, 1989; Mitsch, 1992). Annual P accumulation rates for selected wetlands with both mineral and organic soils were summarized by Johnston (1991), wherein wetlands with mineral soils accumulated 0.1–8.2 g P m 2 yr 1 (average ¼ 1.46 g m 2 yr 1), compared to 0.04–1.1 g P m 2 yr 1 (average ¼ 0.26 g m 2 yr 1) in wetlands with organic soils. Although the accumulation of P associated with organic and inorganic matter is a relatively slow process, it represents a major sink for P in CWs. Conse quently, it is important to understand the composition and stability of newly
Mitigating Nonpoint Source Pollution
37
accreted materials to determine the long term efficacy of P retention in wetland systems (Reddy and DeLaune, 2008). Additionally, the microen vironmental factors at the soil–water column interface (e.g., redox potential, availability of electron acceptors, pH) and the chemical composition of both water and soil (e.g., iron, aluminum, calcium, and sulfur content) dictate how effectively P associated with settling particles is retained in wetland soils (Richardson, 1999).
5.4. Removal efficiencies of P fractions There have been numerous studies evaluating the potential of wetlands to retain P, however, the majority of these have examined systems that receive regulated flows from municipal or other waste water sources. Additionally, most studies have focused on inflow and outflow characteristics of water, with very limited information on the internal processes regulating P cycling and retention. Although CWs are capable of removing large quantities of P from inflowing water, the concentration of P in outflow water is dependent upon the mass P loading. Using the North American Wetland Database, Richardson and Qian (1999) developed a statistical model that established a threshold mass P loading value of 1 g m 2 yr 1 for optimum P removal efficiency with minimal ecosystem change. Additionally, Debusk et al. (2005) conducted a review of wetlands from around the world that were used for removing P from agricultural runoff. They concluded that low outflow P concentrations (15–20 g l 1) were only attainable at low mass P loading rates (<1–2 g m 2 yr 1). However, reported mass P loads for CWs treating agricultural runoff vary widely, ranging from 1 to over 100 g m 2 yr 1 (Debusk et al., 2005). Thus, meeting low targeted outflow P concentrations is challenging given the high wetland area requirements per unit mass of P removed. Newly constructed wetlands are thought to be more effective at remov ing P than older wetlands due to rapid vegetation growth and associated P uptake, and high availability of P sorption sites (Debusk et al., 2005). In general, an increase in mass P loading will result in an increase in outflow P concentrations, while a decrease in mass P loading will tend to decrease outflow P. However, in older wetlands that experience variable P loading conditions, load reductions do not always result in a decrease in outflow P concentration (Debusk et al., 2005; Jordan et al., 2003). This is due to the release of existing P retained in the soil, also termed ‘‘phosphorus memory’’ or ‘‘phosphorus buffering,’’ during periods of low P loading (Reddy and DeLaune, 2008). This was demonstrated in a restored wetland in Maryland, where in the first year of the study 59% of TP was retained, while in the second year there was no significant net removal (Jordan et al., 2003). This was attributed to a decrease in inflow TP concentration in the second year resulting in a release of P stored in wetland sediment.
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5.5. Wetland management strategies to improve P removal Some of the key design parameters effecting wetland P removal include: water flow velocity, water depth, hydraulic retention time, length to width ratio, vegetation type and cover, and soil physiochemical properties (Reddy and DeLaune, 2008). Since the dominant form of P transported in agricul tural runoff is PP, the design and management of wetlands to maximize retention of suspended sediment is essential in effectively removing P. Wetland vegetation increases sedimentation and trapping of PP by slowing water velocities, providing a substrate for particles to adhere to, and preventing resuspension (Braskerud, 2001). Additionally, designing CWs with optimal length to width ratios or flowpaths can dramatically increase hydraulic retention times (Persson et al., 1999). In addition to initial wetland design features, a number of management techniques have been evaluated for improving long term P removal perfor mance by CWs, including routine vegetation harvesting, removal of accu mulated sediment, and chemical immobilization of P in sediment using amendments (Debusk et al., 2005). While microbial and plant uptake are generally considered short term transient P pools (De Groot and Fabre, 1993; Richardson and Marshall, 1986), the harvesting of plant biomass may lead to the removal of considerable amounts of P, ranging from 4 to 15 kg P ha 1 yr 1 (Hoffman et al., 2006; Richardson and Marshall, 1986). Additionally, the removal of accumulated sediment was shown to be effec tive in reducing P concentration in the overlying water column in a Florida wetland (Debusk et al., 2005). In this study, sediment removal decreased water column P concentrations from 130 mg l 1 before removal, to 62 mg l 1 after sediment removal. However, sediment removal from several shallow lakes was shown to be less successful in reducing TP concentrations (Moss et al., 1996; Ruley and Rusch, 2002). Inorganic chemical amend ments, typically alum (aluminum sulfate) and FeCl3 (ferric chloride), have been used effectively to reduce excess dissolved phosphorus from the wetland water column and soil pore water (Reddy and DeLaune, 2008). While these management practices have been shown to work in pilot scale systems, their technical and economic feasibility for full scale use remains to be demonstrated.
6. Dissolved Organic Matter The fate and transport of DOM through wetlands is of great concern due its importance in a multitude of biogeochemical reactions. DOM can be an important component of the microbial food web (Findlay and Sinsabaugh, 2003) and contribute to BOD and hypoxia (Volkmar and
Mitigating Nonpoint Source Pollution
39
Dahlgren, 2006). Complexation of metals by DOM can contribute to transport and ecological availability of metals (Hirose, 2007) and to enhanced rates of toxic methyl mercury production (Ravichandran, 2004). Similarly, due to the hydrophobic nature of DOM, it may adsorb pesticides and facilitate their transport (Muller et al., 2007). DOM is of particular concern in waters used as a source of drinking water because it is a precursor for disinfection byproducts (DBPs), such as trihalomethanes, haloacetic acids, and haloacetonitriles (Chow et al., 2005; Richardson et al., 2003; Xie, 2004). Some of these DBPs are suspected to be mutagens, carcinogens, or developmental toxicants if ingested over extended periods of time (Ahmed et al., 2005; Muellner et al., 2007; Villanueva et al., 2004). Among the different sources of DOM within watersheds, wetlands are recognized as one of the most important, contributing a disproportionate amount of DOM relative to their land surface area (Mladenov et al., 2007; Rostad et al., 2000). Wetlands are highly productive and tend to increase DOM concentrations and change its chemical characteristics through inter nal processing and loading (Pinney et al., 2000). As a result, some studies have found a positive correlation between downstream DOM concentra tion, expressed by DOC, and the extent of wetland area (Chow et al., 2007; Daley, 2002; Gergel et al., 1999). In any case, wetland performance with respect to DOM dynamics will depend on several wetland design and management factors, such as hydraulic and pollutant loading rate, HRT, vegetation characteristics, nature of sediment, and input water characteristics.
6.1. DOM sources A major source of DOM in wetlands receiving agricultural runoff is the import of DOM from surrounding croplands (Maynard, 2009). The DOM can consist of readily solubilized materials leaching from plant residues or DOM released from humic substances. These contrasting sources would be expected to have strongly contrasting chemical properties and persistence in the environment. In a study of six wetlands receiving waters from agricul tural runoff (primarily irrigation tailwaters) in the Central Valley of California, DOC concentrations in input waters ranged from 1.3 to 12.5 mg l 1 (Diaz et al., 2008, 2009). Input waters to wetlands in the Sacramento Valley had significantly higher DOC concentrations (mean ¼ 6.9 mg l 1) compared to those in the San Joaquin Valley (mean ¼ 3.8 mg l 1). DOC concentrations in agricultural drainage waters entering wetlands in the Midwestern USA (surface and tile drain sources) ranged from 2.1 to 3.6 mg l 1 in Illinois (Kovacic et al., 2000, 2006) to 18.0 mg l 1 in Iowa (Davis et al., 1981). These differences may be attributable to several factors including cropping patterns, tillage and irrigation practices, type of runoff (tile drainage vs. surface runoff) and contrasting soil types and
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drainage water properties (e.g., ionic strength, pH) (Chow et al., 2006). Thus, DOM inputs appear to be highly variable in time and space. Within wetlands, DOM can be leached from plants and soils with DOM leaching resulting from a combination of abiotic solubility of plant/sedi ment organic carbon compounds and microbial degradation of plant resi dues (Mladenov et al., 2007; Pinney et al., 2000). Therefore, wetlands accumulating high levels of plant biomass and detrital materials in their soils will have a greater potential for internal generation of DOM. Since DOM solubility is a function of water chemistry, factors such as pH, specific conductivity, and divalent versus monovalent cation concentration can strongly affect DOM solubility (Chow et al., 2006). In addition, longer HRTs should result in more DOM leaching due to the longer period for leaching to occur. Wetting and drying cycles have also been shown to enhance DOM production from organic rich soils (Chow et al., 2006). Reductive dissolution of iron oxides may further contribute to DOM release due to the strong sorption of DOM by iron (hydr)oxides (Reddy and DeLaune, 2008). DOM in wetlands is also subject to concentration by evaporation and dilution due to rainfall events. These factors will largely be determined by the combination of climate (rainfall vs. evapotranspiration), vegetation, and hydrologic characteristics (e.g., HRT). In wetlands having an appreciable infiltration capacity, DOM may be removed from wetland water during subsurface transport. This will result in a decrease in the DOM load leaving the wetland due to the loss of water flux; however, it will not affect the DOM concentration in output waters.
6.2. DOM sinks Within the wetland environment, DOM can be removed or chemically altered by microbial and photochemical degradation (Engelhaupt et al., 2003; Obernosterer and Benner, 2004; Vahatalo and Wetzel, 2004). Labo ratory incubation studies of agricultural drainage waters and wetland waters from the Central Valley, CA, indicate low microbial degradation ranging from less than detection to 8% during 10–14 day incubation periods (Diaz et al., 2008; Engelage et al., 2009). These same studies indicated small changes in the aromatic content of the DOM (as measured by specific ultraviolet absorption at 254 nm) during incubation, which ranged from an increase of 5% to a decrease of 11%. The high molecular weight DOC, which usually comprises the chromophoric DOC fraction, is relatively recalcitrant to bacterial utilization (Engelhaupt et al., 2003; Vahatalo and Wetzel, 2004). Thus, UVA did not significantly change, even though some organic carbon may be utilized by the microorganisms. These studies suggest that the DOM of input and wetland waters is relatively refractory with respect to DOM degradation and alteration by microbial processing.
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Photochemical degradation by solar radiation may oxidize DOM to CO2 or breakdown large molecules into lower molecular weight compounds. Short term (6–14 days) sun exposure of wetland waters has been shown to decrease UVA by 25–47%, while having a lesser effect on DOM concentra tion (Diaz et al., 2008; Waiser and Robarts, 2004). These results are consistent with previous studies that showed solar radiation was more effective at converting aromatic carbon into CO2 and lower molecular weight organic compounds than microbial mineralization (Obernosterer and Benner, 2004; Vahatalo et al., 1999). Other studies suggest that photochemical degradation is the most important mechanism for loss of terrestrially derived humic DOM, while microbial degradation is most important for nonhumic (e.g., algal biomass and plant leachates) and microbially derived, soil humic DOM (Amado et al., 2006; Miller et al., 2009). The effectiveness of photochemical degradation will strongly depend on attenuation of solar radiation by the vegetation canopy and turbidity within the water column. Thus, photochem ical degradation would be expected to be highest in open water wetlands having low water column turbidity and long hydrologic residence times. Sorption of DOM to sediments may result in the loss of DOM from the water column. It is common for a subsurface layer (1–2 cm depth) of poorly crystalline Fe (hydr)oxides to form at the interface between the anoxic and oxic sediments (Reddy and DeLaune, 2008). These poorly crystalline Fe (hydr)oxides have a high surface area and high affinity for DOM sorption.
6.3. DOM input–output budgets from agricultural wetlands Studies examining wetland DOM/DOC dynamics in a variety of agricul tural settings have shown variable results. Illinois wetlands receiving surface and tile drainage showed overall DOC mass retention of 2% (3 year period) (Kovacic et al., 2000) and 9% (21 month period) (Kovacic et al., 2006). In the former study, overall retention was positive in fall, winter, and summer, but negative during the spring (Kovacic et al., 2000). These results contrast with those for an Iowa prairie pothole wetland receiving surface and subsurface drainage from maize/soybean agriculture in which DOC outputs exceeded inputs by 71% (Davis et al., 1981). The large DOC production in the pothole wetland was attributed to very high biomass production as well as pulse flows following a period of drought. Input–output studies of wetlands in the Central Valley of California indicate a range from net retention to net production of DOC as a result of wetland processing (Diaz et al., 2008, 2009; Maynard, 2009). There was a small reduction ( 12%) of DOC load between inflow (6437 kg) and outflow (5642 kg) of a sparsely vegetated wetland receiving irrigation tailwaters during the irrigation season (Maynard, 2009). Most studies of DOC dynamics in California agricultural wetlands have examined input and output concentra tions rather than loads. Agricultural wetland drainage in California typically
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has DOC concentrations more than two times higher than agricultural drains and rivers suggesting that some CWs are an appreciable source of DOC (Engelage et al., 2009). Studies by Diaz et al. (2008, 2009) have demonstrated that HRT and vegetation density were important factors regulating DOC concentrations. CWs with short HRTs (<2 days) did not produce significant changes in DOC concentration with respect to the irrigation return flow input to CWs. In contrast, CWs with long HRTs (>10 days) increased DOC concentrations by an average factor of 2.4. The increase in DOC was largely attributable to evapoconcentration ( 80% on average) as the electrical con ductivity increased by an average factor of 2.0. The remaining DOC con centration increase (20% on average) is presumably due to leaching from plants, algae, bacteria, and soil organic materials within the wetlands. Longer HRTs should also allow for higher DOC leaching from organic materials due to the longer contact time between the water and organic materials. In a comparison of four wetlands with contrasting HRTs, DOC concentration consistently increased with increasing HRT with average DOC increases of 0.03, 0.8, 5.2, and 8.8 mg l 1 for wetlands with HRTs of 0.9, 1.6, 11.6, and 15–20 days, respectively (Diaz et al., 2009). Importantly, the DOC increase due to evapoconcentration will not impact the DOC load discharged into the rivers as the volume of water will be reduced by a proportional amount. In contrast, the DOC increase related to leaching of organic materials will increase the DOC load to the river. Thus, the higher DOC concentrations found in wetland drainage by Engelage et al. (2009), which was a very large CW, may result from evapoconcentration of DOC and may therefore have little effect on DOC load. CW treatment did not appreciably affect DOC quality (e.g., aromaticity) as assessed by specific ultraviolet absorbance (Diaz et al., 2008, 2009; Engelage et al., 2009). DBP formation potentials were increased in output waters relative to input waters due to the higher DOC concentrations, but the propensity of a given carbon atom to form DBPs was not changed by wetland treatment. The speciation of trihalomethanes in output waters was similar to the input waters (Diaz et al., 2008). Microcosm studies (14 day incubations) examining microbial degrada tion (Escherichia coli spiked) and photodegradation (natural sun exposure) of wetland waters from the Central Valley of California did not detect signifi cant changes in DOC concentration due to treatment (Diaz et al., 2008). However, there was more than a 25% decrease in UVA254 after exposure to sunlight, whereas there was no significant change following the microbial degradation treatment. In terms of trihalomethane formation potential, solar radiation and microbial degradation reduced formation potentials by 24% and 10%, respectively. In contrast, biodegradation studies by Engelage and coworkers for California agricultural wetland drainage waters demon strated an 8% decrease in DOC and 5% increase in aromatic carbon (as measured by SUVA254), but no change in the propensity of DOC to
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form trihalomethanes in wetland drainage. This suggests that the fraction of DOC most resistant to biodegradation is also the most significant contribu tor to trihalomethane production in wetland drainage. Based on these studies, we conclude that photodegradation and microbial degradation have variable effects on DBP formation potentials in wetland waters and factors, such as DOM source, HRT, vegetation shading, water temperature, nutrients, etc., will greatly affect the magnitude of their effects.
7. Trace Metals Trace metals are naturally occurring and are found at low levels in soil and water. They are typically defined as elements required for life, but can be toxic at elevated concentrations. The United States Environmental Protec tion Agency (U.S. EPA) has included 13 trace metals on their priority pollutants list. From this list, 10 of them are of concern for agricultural runoff As, Cd, Cr, Cu, Hg, Ni, Pb, Se, V, and Zn; the other three on the list are Ag, Sb, and Tl. The term trace metal is often interchanged with micronutrients, microelements, and heavy metals; although not all trace metals are heavy metals. The terms will be used interchangeably in this review. The principle factor distinguishing heavy metals from other potential agricultural contaminants, such as nitrogen, phosphorus, pesticides, and pathogens, is the fact they are much less mobile and do not degrade. Annual inputs of trace metals to soil are cumulative and concentrations can increase incrementally each year. The various collective inputs over long time periods should be considered when evaluating trace metals in soils and agricultural runoff. A study modeling the risk of trace element (As, Cd, Cu, Pb, Zn, Se) accumulation in Canadian soils accounting for various inputs (e.g., fertilizers, atmospheric deposition, manures, and biosolids) estimates that trace elements (with the exception of the volatile Se) will be up to threefold higher than present background levels in 100 years (Sheppard et al., 2009). Elevation of trace metals in soils at this level would prove extremely detrimental to agricultural systems and environmental quality. This projection highlights the importance of understanding the mechanisms of trace metal accumulation and transport and should serve as a reminder for the need to develop management strategies to mitigate future trace element additions to soil. Moreover, trace metal buildup is likely to be amplified in CWs, which receive eroded soil from surrounding landscapes. Due to the strong binding of most trace metals to soil constituents, and their limited transport, trace metals have long residence time in soils (Hesterberg, 1998) and concentrations can become elevated above back ground levels and threaten plant, animal, and environmental health. Although leaching of metals to groundwater is typically minimal, erosion
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of metal rich soil particles via surface runoff can threaten surface water quality, contaminate river sediment, and lead to long range transport of associated trace metals (He et al., 2004; Quinton and Catt, 2007; Zhang et al., 2003). The presence of elevated trace metal concentrations in soil and water is problematic as they bioaccumulate in the food chain and are resistant to degradation. Plants grown in contaminated soils can uptake metals which are then fed to livestock or directly consumed by humans.
7.1. Sources of trace metals to agricultural soils Atmospheric deposition and the application of fertilizers, agrochemicals, sewage sludge, soil parent material, irrigation water, and soil amendments with low levels of trace metals can lead to accumulation of a wide range of trace metals in agricultural soils. Of the various inputs by which trace metals enter soils, fertilizers and sewage sludge are considered to be the greatest source for metals to enter agricultural systems (Adriano, 2001). Phosphate rock (PR) used in the production of inorganic fertilizers is a major source of heavy metals. While the location where PR is mined contributes to its specific composition, heavy metals commonly found in PR include As, Cd, Cr, Pb, Hg, Mo, Ni, and V (Franklin et al., 2005; Mortvedt, 1996; Nziguheba and Smolders, 2008). Of these metals, Cd concentrations are typically of the most concern as Cd is easily incorporated into plant biomass (Basta et al., 2005; McLaughlin et al., 1996) and is potentially the most harmful to human health (Mortvedt, 1996). Average concentrations of trace metals in phosphate fertilizers are given in Table 4. Model simulations examining the risk of As and Cd accumulation in soils from addition of chemical fertilizers reveal that As concentrations will not significantly increase; however, Cd levels could increase over time and pose a risk of transfer to the food chain (Chen et al., 2007). Historical use of pesticides and application of biosolids, including sewage sludge and animal manures, has increased trace metal content in agricultural soils. The levels of trace metals in sewage sludge are typically higher than animal manures and can vary greatly depending on the source and treatment Table 4 Mean trace element concentrations (ppm) in various phosphate fertilizers (raw and N–P–K blends) Phosphate fertilizer a
USA (Franklin et al., 2005) Europeb (Nziguheba and Smolders, 2008) a b
n n
16. 196, Cu and V not measured.
As
Cd
Cr
Cu
Ni
Pb
V
Zn
12.5 37.1 101 36.1 28.3 178 175 235 7.6 7.4 89.5 – 14.8 2.9 – 166
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method. Heavy metals of interest in sewage biosolids include As (1–230 mg kg 1), Cd (1–3410 mg kg 1), Cr (10–99,000 mg kg 1), Cu (84–17,000 mg kg 1), Pb (13–26,000 mg kg 1), Hg (1–56 mg kg 1), Mo (1–214 mg kg 1), Ni (2–5300 mg kg 1), Se (2–17 mg kg 1), and Zn (101–49,000 mg kg 1) (Chaney, 1983). Currently, the application of metal containing pesticides is not common. Notable exceptions include the foliar application of Cu to prevent disease (e.g., viticulture and citrus industries) (Koma´rek et al., 2010; Paradelo et al., 2008).
7.2. Trace metal fate and transport in agricultural soils The fate and toxicity of trace metals in soils is dictated by the chemical form in which they are present within soils. These general forms include water soluble metals (i.e., free ions, inorganic or organic complexes), exchange able metals, metals precipitated as inorganic compounds, metals complexed with humic materials, metals bound to hydrous oxides and layer silicate minerals, metals precipitated as insoluble sulfides, and metals bound within the structure of primary minerals (Gambrell, 1994). The two most impor tant factors controlling trace metal speciation in soils, sediments, and wet lands are redox potential and pH (Basta et al., 2005; Du Laing et al., 2009; Gambrell, 1994; Olivie Lauquet et al., 2001; Schulz Zunkel and Krueger, 2009). Typically, solubility of trace metals increases under reducing condi tions or low pH. In a study examining influence of agricultural practices on trace element distribution, redox conditions were shown to be the most important factor controlling the movement of Co (Cr, Ni, and Zn influ enced to a lesser degree) within the soil profile, primarily due to the reductive dissolution of Fe and Mn oxides (Montagne et al., 2007). Salinity also plays an important role in trace metal transport (Du Laing et al., 2009; Speelmans et al., 2007). High salinity increases heavy metal mobility through complexation with Cl ions (Paalman et al., 1994) and cation exchange (Tam and Wong, 1999). Additionally increasing salinity leads to greater bioavailability of heavy metals (Basta et al., 2005; Speelmans et al., 2007). This is particularly important for semiarid and arid regions, such as the San Joaquin Valley (California), where drainage water, the main water supply for CWs, is often saline and enriched in trace metals, including Se, As, Cu, Mo, and Zn (Herbel et al., 1997). Of these trace metals, the high concentrations of Se have garnered the most attention due to its toxicity to fish and wildlife, most notably waterfowl (Gao et al., 2007; Lemly, 1994; Lemly et al., 1993).
7.3. Trace metals in saturated soils and wetlands Seasonally submerged soils of CWs fluctuate between oxic and anoxic conditions. Under aerobic conditions, trace metals are typically sorbed or precipitated onto soil constituents including clay minerals, iron, aluminum,
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and manganese oxides, organic matter, phosphates, and carbonates. Soils saturated for prolonged periods result in reduction of trace metals and Fe and Mn oxides to which trace metals are bound (Du Laing et al., 2009; Montagne et al., 2007). Alternatively, the presence of strongly reducing conditions can result in sulfate reduction and heavy metal (e.g., Cd, Cu, Zn) coprecipitation with sulfide minerals facilitating retention in CW soils (Du Laing et al., 2008; O’Sullivan et al., 2004). Wetland soils are generally characterized as having reducing conditions and high levels of organic matter; serving as a source of ligands to bind trace metals. These two conditions exert a large influence on chemical speciation and transport processes of trace metals in wetlands. Sedimentation is recog nized as the primary process responsible for the removal of metals from the aqueous phase in natural and constructed wetlands (Sheoran and Sheoran, 2006). Sedimentation requires aggregation and sorption (including precipita tion) to occur for metals to settle and become sequestered in soils. Trace metals readily bind to a wide range of clay minerals, metal (hydr)oxides, and organic matter fractions. Precipitation and sorption of trace metals in wetlands depend on the pH, redox potential, solubility product (Ksp) of the metal, trace metal concentration, ionic strength, and background electrolyte composition (Fox and Doner, 2003; O’Sullivan et al., 2004; Sheoran and Sheoran, 2006). The redox status of wetlands can strongly influence the mobility of trace metals, although prediction of mobility is not always straight forward. While increased transport of many metal species is observed under reducing condi tions (Du Laing et al., 2009; Montagne et al., 2007), there are cases where strongly reducing conditions lead to increased sediment retention of trace metals. For example, As, Mo, and V accumulation in sediment was highest under more reducing conditions and lowest under more oxidizing conditions (Fox and Doner, 2003). Under moderately reducing conditions both As and V can become mobilized, possibly due to a sequence of simultaneous pro cesses including dissolution, desorption, precipitation, and adsorption. Upon drying of sediments, 73% of Mo became water soluble, having strong impli cations for the effect of drying wetlands on Mo mobility. Sorption of trace metals to dissolved and solid phase organic matter is an important mechanism for metal removal in wetlands, particularly for Cu, Ni, and U (Sobolewski, 1996). Ionizable functional groups within organic matter fractions, such as carboxyl and phenolic moieties, serve as sites for metal binding (Tipping and Hurley, 1992). Once bound to organic matter metals can be sequestered in aggregated forms or on mineral bound organic matter; alternatively binding to soluble, low molecular weight organic matter can promote transport in the aqueous phase. The release of trace metals within wetlands occurs primarily via organic matter decomposition or microbially catalyzed reduction of Mn and Fe oxides (Tarutis and Unz, 1995). Microbial driven redox processes play an important role in the speciation of trace metals in soils and aquatic environments. A study examining the
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influence of wetland seasonal variability on trace element release revealed that the initiation of trace element release occurs simultaneously with increasing water temperature, a decline of redox potential, and increase in organic carbon content (Olivie Lauquet et al., 2001). The research hypothesized that Fe and Mn reducing soil microorganisms catalyze this change in redox potential and subsequent increase of DOC as microorganisms degrade trace element rich organic compounds. The increased DOC serves as a source of organic ligands for transport of trace elements (Olivie Lauquet et al., 2001). Another example of how microorganisms influence metal concentrations in wetlands is by examining the unique way in which sulfate reducing bacteria (SRB) contrib ute to metal sequestration in wetlands. In anaerobic environments, SRB generate H2S initiating the precipitation of metals from the aqueous phases as metal sulfides (Amacher et al., 1993; Webb et al., 1998). While reduced aqueous concentrations of trace metals in wetlands is observed, due largely to binding to sediment and organic matter, removal of trace metals from wetlands requires an anthropogenic influence such as harvesting of metal accumulating wetland plants. The use of hyperaccumu lating plants (e.g., Typha latifolia, Phragmites australis, Glyceria fluitans, Eriophorum angustifolium) has been demonstrated as an effective method for removing a range of metals (e.g., Cd, Cu, Pb, Zn, Hg, Se) from wetland ecosystems (Cheng et al., 2002b; LeDuc and Terry, 2005; Liu et al., 2007; Matthews et al., 2005; Rai, 2009; Williams, 2002). A number of strategies have been explored to manage CWs containing trace metals. The acidification of evaporation ponds has been proposed to discourage habitation by water fowl and other animals (Herbel et al., 1996, 1997). Acidifica tion of treatment ponds is effective on reducing concentrations of As, Mo, and Se with an increase in Fe and Mn concentrations; however, the high cost for initial acidification limits the implementation of this management strategy (Herbel et al., 1996). Treatment options currently employed include a series of drainage ponds with algal–bacterial selenium removal (ABSR) (Quinn et al., 2000), the use of flow through wetlands to bind Se to sediment (Gao et al., 2000, 2003a,b), and the use of wetland plants (e.g., Eichornia crassipes, Typha angusfolia, Polypogon monspeliensis) to phytoaccumulate Se (Rai, 2009; Thompson et al., 2003). Anaerobic bacteria in CW soils facilitate the conversion of inorganic mercury into methylmercury, which is a strong neurotoxin. The existence of low redox potentials and labile organic carbon are CW characteristics that support this transformation. Moreover, DOC is thought to play an impor tant role in the mobility of mercury in wetlands. Hall et al. (2008) found that the aromatic reactive fraction of DOC was positively correlated with total mercury and methylmercury in wetland water samples. Relatively low levels of inorganic mercury can bioaccumulate in tissues of organisms that reside in CWs, especially those at the top of the food chain (Ackerman et al., 2010; Hall et al., 2008). A study of invertebrates in wetlands and rice fields in California demonstrated that mercury bioaccumulation was
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greater in wetlands that were permanently saturated compared to seasonally saturated rice fields. Since mercury bioaccumulates through the food chain, translocation mechanisms within CWs and its biota are extremely complex and are exceedingly difficult to identify. CWs should be closely monitored if developed in regions with high background levels of mercury, such as those surrounding coal fired energy plants, waste incineration facilities, and gold mining/extraction sites (Ackerman et al., 2010; Hall et al., 2008). Trace metals in agriculture will likely become of increasing concern as concentrations continue to slowly increase, threatening food safety, water quality, and human health. To date the use of constructed wetlands for remediation of agricultural drainage water is not prevalent. However, engineered approaches, in conjunction with phytoremediation strategies, may be necessary to protect our agricultural soils, water supplies, and ensure increased production of crops for human and animal consumption.
8. Pathogens Microbial pathogens are considered one of the leading causes of water quality impairment in agricultural watersheds worldwide (Collins, 2004; Cooley et al., 2007; Rosen, 2000; United Nations Environment Programme, 2004; Wilkes et al., 2009). Microbial pathogens of particular concern for public health include protozoa such as Cryptosporidium parvum and Giardia duodenalis, as well as bacteria such as Salmonella and E. coli O157:H7. Watershed sources of these pathogens are diverse as they are shed in the feces of wildlife, humans, livestock, and pets (Simpson et al., 2002). With improvements in wastewater treatment technologies in recent decades, nonpoint sources have become the primary source of microbial pathogens in waterways, with agricultural activities being the single largest contributor. In addition to drinking water and recrea tional body contact concerns, the use of surface waters for irrigation of fresh produce and vegetables leads to food safety concerns for pathogen contamina tion (e.g., E. coli O157:H7 on spinach) (Cooley et al., 2007).
8.1. Pathogen removal The use of constructed wetlands as a management practice to reduce microbial contaminant loads represents a potentially effective mechanism to economically treat agricultural runoff prior to discharge into waterways (Rosen, 2000). Retentions of 80–99% have been seen for pathogen indi cators such as E. coli and fecal coliforms in surface flow CWs treating municipal and livestock wastewater (Gerba et al., 1999; Hill, 2003; Quinonez Diaz et al., 2001). In contrast to the large literature base available for wastewater treatment wetlands, very few studies have addressed
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microbial pathogen treatment of agricultural runoff using wetlands (Kadlec and Knight, 1996). Given several differences between agricultural and wastewater treatment wetlands (e.g., pulsed flow, pollutant loading levels, low hydrologic residence times), it is difficult to extrapolate the microbial pathogen retention efficiencies between these wetland types. A range of physical, chemical, and biological removal mechanisms affect microbial pathogen fate during wetland treatment (Stottmeister et al., 2003). Physical removal mechanisms include filtration, sedimentation, soil and bio film adsorption, and aggregation. Biological elimination mechanisms include predation (protozoan and/or viral), bacteriophage activity, lytic bacteria, release of antibiotics by plants and other microbes, and natural death. Chemical elimination mechanisms include oxidative damage, UV irradiation, and toxins excreted by other bacteria and plants. Environmental factors such as pH, sunlight, temperature, vegetation type and density, and redox potential play a role in pathogen survival and elimination (Kristian Stevik et al., 2004). The effectiveness of microbial pathogen removal is also coupled to the HRT with removal modeled by first order kinetics (Vymazal, 2005). Differences in performance observed within a given CW in time (diur nally, seasonally, or degree of maturation) or between wetlands (distinct in location) cannot be adequately understood without regard to their dynamic living components (Werker et al., 2002). Since wetlands can take a number of years to achieve a fully developed vegetation community and root zone, the manner in which these systems are allowed to mature may be critical to their long term performance. The presence of plants has been observed to exhibit highly variable effects on the removal of microbial contaminants in CWs with the type of vegetation often having a large impact on removal efficiency (Stottmeister et al., 2003). Several studies have shown that plants provide for higher rates of pathogen removal when compared to unplanted beds (Decamp and Warren, 2000; Hatano et al., 1993; Soto et al., 1999). Wetland plants and their associated biofilm communities can enhance filtration, adsorption, and inactivation by competition with other microorganisms. In subsurface flow wetlands, the roots of plants are of particular importance and may enhance bacterial inactivation by increasing the variety of micro organisms present in the wetland environment and therefore creating more competition and bacterial reduction (Hench et al., 2003; Werker et al., 2002). In contrast, shading of the water column in surface flow wetlands can significantly reduce E. coli retention (MacIntyre et al., 2006). Maximum removal of E. coli occurs under high solar radiation and high temperature (Boutilier et al., 2009; Chapra, 1997; Crane and Moore, 1986; Whitman et al., 2004; Zdragas et al., 2002). Thus, shading by vegetation can greatly reduce UV radiation and maximum water temperatures leading to lower removal efficiencies. While vegetation may provide favorable attachment sites for E. coli, dense canopies can hinder free exchange of oxygen between the water column and the atmosphere. This vegetative induced barrier limits
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dissolved oxygen levels and decreases predator zooplankton populations, which decreases microbial pathogen retention (MacIntyre et al., 2006). The reduction of E. coli by sedimentation is dependent on whether the bacteria are ‘‘free floating’’ or associated with particles (Boutilier et al., 2009). Microbial contaminants associated with particles, especially dense inorganic particles, settle out of the water column faster than those in the free floating form (Characklis et al., 2005). Quinonez Diaz et al. (2001) found a strong correlation between Giardia cyst removal and turbidity suggesting that cysts and turbidity (suspended sediments) were removed simultaneously in wetland systems, possibly due to cyst–particle association. Bacteria have also been shown to survive longer within sediments than within the water column (Howell et al., 1996), and therefore, microbial partitioning between the sediment and water column will affect bacteria fate, transport, and inactiva tion (Characklis et al., 2005). High water flow pulses into wetlands or channelization may result in resuspension and entrainment of sediment that could mobilize previously retained microbial pollutants during high flow events (Collins, 2004; Jamieson et al., 2005; Wilkes et al., 2009). A negative collateral effect of constructed wetlands is that they often become an attractive wildlife habitat for possible disease vectors, such as birds, livestock, deer, pigs, rodents, etc. These animals can increase the presence of pathogens in the water by depositing their excreta within the wetland, thus replacing pathogens removed by wetland treatment (Collins, 2004; Cooley et al., 2007).
8.2. Case study: Agricultural wetlands treatment of irrigation tailwaters There are few studies addressing the fate of pathogens in CWs that focus on field runoff. Therefore, the following case study is presented to document the performance of wetlands treating tailwaters from flood and furrow irrigation from croplands in California to highlight microbial dynamics in agricultural wetland systems. Four constructed surface flow through wet lands located in the San Joaquin Valley, California and discharging into the San Joaquin River were monitored for their effectiveness in removing E. coli from irrigation tailwaters. Characteristics of the wetlands including design, age, catchment area, vegetation coverage, and hydrologic residence time can be found in Diaz et al. (2009). The main crops in the study area were tomatoes, alfalfa, melons, nuts, and stone fruits. All wetlands were continuous flow through wetlands with HRTs ranging from about 0.9 to 11.6 days. Due to the expense and technical challenges in the measurement of human pathogenic organisms, an indicator of pathogen removal, E. coli, was monitored (Dufour, 1977; World Health Organization, 2003). Approximately 47% of water samples collected from irrigation return flows exceeded the E. coli standard of 126 cfu per 100 ml (range: 13–1400 cfu
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per 100 ml). In contrast, E. coli concentration in wetland outflows ranged from 0 to 300 cfu per 100 ml. Based on paired input–output concentrations in the four wetlands, mean E. coli concentrations were reduced from 69% to 95%. Removal efficiencies in terms of E. coli load were even higher, 98–99%, due to water losses (seepage and evapotranspiration) within the wetland. Following wetland treatment, 93% of wetland outflows met the California water quality standard for E. coli (126 cfu per 100 ml). E. coli concentration was strongly correlated with total suspended solids, suggesting sedimentation of suspended sediments as a potential mechanism for E. coli removal. In spite of several differences among the four wetlands, HRT was a good predictor of E. coli removal efficiencies. Mean removal efficiency was 69%, 79%, 82%, and 95% for wetlands having mean HRTs of 0.9, 1.6, 2.5, and 11.6 days, respectively. The importance of HRT was explained by the fact that longer HRTs increase bacteria exposure to removal processes, such as sedimenta tion, adsorption, predation, impact of toxins from microorganisms or plants, and UV radiation (Stottmeister et al., 2003). Hourly sampling of E. coli concentrations in wetland inputs and outputs showed no consistent diel patterns. On an hourly time scale (during a 24 h period on three different days), E. coli fluctuation at the input sites varied from 120 to 792 cfu per 100 ml, while at the output locations ranged from 17 to 60 cfu per 100 ml. Results from this study indicate that passing irrigation tailwaters through wetlands can significantly reduce E. coli con centration and load. Of all the parameters considered, HRT appeared to be the factor having the greatest effect on the efficiency of E. coli removal. Remarkably, a HRT of less than a day can achieve considerable E. coli retention (70%), which allows for relatively small wetland areas being able to treat runoff from large agricultural areas (up to 360 ha of contributing farmland runoff per 1 ha of wetland in this study).
9. Other Water-Quality Constituents 9.1. Salinity Salinity is a common water quality concern affecting freshwater resources, especially in the western United States. In many arid and semiarid regions, the combination of soil parent materials rich in salts, high evapotranspiration rates, and incomplete deep percolation has resulted in saline agricultural drainage waters. There are no wetland processes that can reduce salinity levels in CWs except blending of input waters with higher quality waters. In most CWs, salinity tends to increase through evapoconcentration if HRTs are long enough. For example, in California, electrical conductivity in output waters increased by a factor of 2 compared to input waters in CWs with residence times >10 days (Diaz et al., 2008, 2009). The intolerance for salinity by most
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freshwater aquatic life and the need to preserve water quality for downstream users have resulted in the establishment of salinity Total Daily Maximum Loads (TMDL) in surface water bodies throughout the west and southwestern United States. In these settings, using CWs as BMPs to address nutrients and pesticides may be in conflict with established salinity TMDLs.
9.2. Biological oxygen demand BOD is a water quality parameter that can be a problem in agriculture discharge (Volkmar and Dahlgren, 2006). Substances such as DOM, algae, and ammonium consume dissolved oxygen through biogeochemical reac tions. BOD is an important water quality parameter because high BOD results in low dissolved oxygen in water, which can kill aquatic life or serve as a barrier for migrating fish. Wetlands have the potential to become either a sink or source of BOD. Studies of treatment wetlands have shown that these systems can reduce BOD; however, there are few studies that focus on CWs in agricultural settings, which tend to receive higher quality runoff compared to treatment wetlands (Stringfellow et al., 2008; Sundaravadivel and Vigneswaran, 2001). While CWs have effectively decreased volatile sus pended solids (i.e., organic matter) in output waters (O’Geen et al., 2006) some wetlands receiving agricultural drainage have been identified as a source of BOD (Stringfellow et al., 2008). The component of BOD from these wetlands was mainly organic carbon, with algae being a major contributor. CWs have the potential to serve as bioreactors for algae when HRTs are long and nutrient levels are high, and can serve as a seed source for algae growth in downstream environments. Maynard (2009) observed a decrease in chloro phyll a concentration (a bioindicator of algae) in CW output waters with a corresponding increase in emergent canopy of macrophytes. It was suggested that the reduction in algae production was caused by canopy interception of sunlight causing a light limitation in the water column. Conversely, wetlands with a large amount of vegetation and long residence times could be a source of organic carbon contributing to BOD. More research is needed to understand the origin of constituents contributing to BOD in wetlands, especially between organic carbon supplied by algae versus vegetation residue.
10. Design and Management CWs can be designed for a variety of ecosystem services that contrib ute to biological habitat and diversity, hydrologic buffering, and water filtration. The placement of CWs for water quality improvement of agri cultural runoff involves many considerations including the nature of runoff (hydrologic loading, constituent loading, and temporal patterns), soil
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properties, location within a watershed, the amount of space available, and landscape and infrastructure constraints on its development. Ideally, CWs should be developed for multiple ecosystem services and their design should have input from many disciplines including engineers, biologists, ecologists, soil scientists, biogeochemists, and hydrologists. Design considerations for CWs should include: (1) low maintenance of biota, hydrology, and struc tures; (2) a hydrological infrastructure that utilizes the potential energy of source waters; (3) a system compatible with the surrounding landscape; and (4) a system with multiple environmental objectives (e.g., pollution control, biodiversity, flood prevention) (Mitsch, 1992).
10.1. Hydrology Hydrology is the most important design parameter for successful removal of water quality contaminants. The efficiency of treatment is largely controlled by the extent to which water is evenly distributed across the wetland area. CW treatment capacity is diminished by designs that result in stagnant zones, which reduce the effective treatment area, or short circuit flowpaths that decrease water residence time (Kadlec, 2005). It is difficult to optimize hydrologic characteristics of CWs receiving agricultural runoff because flows are not continuous and they can originate from many sources, such as surface runoff, stream and river runoff, tile drainage, or irrigation return flows. Thus, consideration of the seasonality, velocity, volume, and duration of flow is important and will differ greatly among agricultural watersheds. Some key considerations largely instigated from the treatment wetland literature are hydroperiod, hydraulic loading rate, residence time, flowpath design and CW dimensions and morphology (Mitsch and Gosselink, 2000). 10.1.1. Hydroperiod The temporal pattern of water depth and saturation describes wetland hydro period (Mitsch and Gosselink, 2000). Hydroperiod is governed by inflow, ouflow, and storage capacity and is one of the most important hydrologic design considerations because hydroperieod affects wetland surface area, vegetation, particle settling and resuspension, biodiversity, soil redox status, soil mineralogy, and ultimately, pollutant removal. CWs that receive water from irrigated agriculture often have stable hydroperiods during the growing season, but highly variable in the off season due to flooding or dry down. In contrast, CWs that receive water via surface runoff or tile drainage have hydroperiods dependent on rainfall distribution. Those that receive pumped water from adjacent streams or rivers may experience pulse events. CWs with highly variable hydroperiods experience fluctuations in wetted surface area and depth, which facilitates a diversity of biological and biogeo chemical conditions that optimize wetland function (Mitsch and Gosselink, 2000). Episodes of flooding and drying have been linked to improved
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nutrient removal efficiency. Fluctuating hydroperiod facilitates aerobic and anaerobic conditions and the coupling of nutrient removal processes such as nitrification with denitrification (Wijler and Delwiche, 1954) and poorly crystalline (hydr)oxide formation with P sorption (Busnardo et al., 1992; Maynard et al., 2008, 2009). For example, a comparison of a CW experien cing different hydroperiods over 2 years, one year being consistently wet and the consecutive year having a dry period showed that TN, TP, and organic carbon removal efficiencies were significantly higher when dry down occurred (Jordan et al., 2003). An evaluation of mesocosms subjected to different hydroperiods showed that P removal efficiency was more responsive to fluctuating hydroperiods compared to N (Busnardo et al., 1992). Similar to hydroperiod, water depth affects plant habitat, light penetration, particle settling, and resuspension. Studies suggest that depth should range from 15 to 50 cm. If shallower, the wetland floor becomes more susceptible to sediment resuspension, channelization, and recruitment of less desirable plants (Braskerud, 2002a; Carty et al., 2008). CWs commonly have deeper depths than the above (Table 3). Deeper depths discourage emergent macrophyte establishment (Kadlec, 2005). Although, localized areas of deeper water pro mote greater habitat diversity and cooler water temperatures (Knight, 1992). 10.1.2. Hydraulic residence time HRT is widely recognized as an important design consideration for max imizing pollutant removal. Many wetland studies have identified HRT as one of the main factors affecting contaminant removal efficiency (Blahnik and Day, 2000; Greenway and Woolley, 1999; Jordan et al., 2003; Knox et al., 2008; Toet et al., 2005). HRT can be estimated by dividing the wetland volume by the flow rate or tracer addition studies. Variability in agricultural runoff received by CWs makes it difficult to maintain constant HRT (Woltemade, 2000). Inefficient pollutant removal by CWs is often a result of short HRT due to high hydraulic loading rates or insufficient storage capacity. Since HRT is most often calculated using the wetland volume, values can be somewhat misleading because of wetland depth. For example, a small, deep wetland may have a HRT similar to a larger but shallow system. For most pollutants, removal efficiencies will be higher for shallower systems despite similar HRT because more wetland surface area is available, and more plant and microbial biomass is present. Thus, studies suggest that aerial loading rate is a more accurate design criterion. Designing large wetland areas is the best way to maintain long HRT in agricultural settings, where input flows may be highly variable. Alternatively, HRT can also be managed by decreasing input or output flow, but this process can be costly or impractical to implement. Overly long HRT can have adverse effects by increasing the export of DOC and associated DBPs or by increasing salinity via evapoconcentration effects in semiarid regions (Diaz et al., 2008).
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Most studies demonstrate that HRT of 2 days or more is necessary for significant nitrate removal (Beutel et al., 2009; Hey et al., 1994; Kovacic et al., 2000, 2006; Moreno et al., 2007; Phipps and Crumpton, 1994). 10.1.3. Hydrologic loading rate Hydrologic loading rate, calculated by dividing the flow rate by the wetland surface area, is a way to size a CW relative to its input water flow. Treatment wetland literature suggests that hydrologic loading rates should be between 0.025 and 0.05 m day 1 (Mitsch and Gosselink, 2000). Hydrologic loading rate is difficult to design for in agricultural environments, which can receive highly variable inflows originating from expansive land areas. In most agricultural settings, loading rate is partly predetermined by the input flow rate, and therefore, design considerations should manipulate wetland area to optimize hydrologic loading rate. A general rule of thumb is that CWs size should be from 3% to 6% of its contributing watershed area although this depends on the climate and nature of runoff. If the wetland is too small, excessive loading rates will limit the HRT. If the CW is too big, the hydroperiod may be overly variable resulting in expansive dry regions. This guideline may be difficult to implement in irrigated areas, where flows can vary from year to year as a result of crop rotations, changes in technology, and availability of irrigation water. If surface runoff is the main water supply, hydrologic loading rate can be estimated by watershed modeling with knowledge of the drainage area, climate, and the runoff curve number (Millhollon et al., 2009; USDA NRCS, 2008). Hydrologic loading rate can also be managed if input waters are pumped into the CW. Braskerud (2002b) reported low removal rates (< 15%) in CWs with hydraulic loads ranging from 0.7 to 1.8 m day 1. It was reported that a 2 day residence time was necessary for significant annual N removal in CWs with hydrologic loading rates ranging from 0.26 to 6.8 m day 1 (Arheimer and Wittgren, 2002).
10.2. Dimensions and design Efficient CWs can have a variety of shapes and sizes. In general, the larger the wetland, the greater the potential for contaminant removal. CWs should be wide enough to allow sufficient trapping of sediment and other particu late materials, and long enough to generate adequate residence time for nutrient removal. However, some investigators suggest that long narrow wetlands are less efficient at removing contaminants compared to square or round CWs (Carty et al., 2008; Scholz et al., 2007), most researchers agree that the CW surface area should be as large as possible in order to maximize HRT and storage capacity.
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10.2.1. Hydraulic efficiency The evenness of dispersion of water across the wetland, termed hydraulic efficiency, is largely defined by wetland dimensions and relative position of input and output locations. High hydraulic efficiency maximizes contami nant removal. Hammer (1992) reported the optimum design should have a 3–5:1 length to width ratio in order to avoid excessive contaminant load ing near the input, even though designs with this ratio may not have optimum hydraulic efficiencies (Persson et al., 1999). CW designs with good hydraulic efficiency have shapes and/or barriers to facilitate complete mixing throughout the wetland without the persis tence of stagnant zones. All CW designs with good hydraulic efficiency have input and output locations positioned on opposite ends of the wetland. Some examples of efficient CW designs include: (1) CWs with multiple input locations across the width of the wetland, (2) upland barriers con structed to create a sinous path across the length of the wetland, (3) an island obstructing and diverting input flow to both sides of the CW, (4) a submerged berm across the width of the CW near the input to encourage vertical mixing, and (5) very long and narrow design (Braskerud, 2002a; Persson et al., 1999). Designs with multiple inlets and outlets are needed for large wetlands to encourage parallel flowpaths to minimize stagnant zones (Fig. 5; Kadlec, 2005). 10.2.2. Sediment traps Sediment traps are an important design feature in settings where input waters have high levels of suspended solids (Knight, 1992). Sediment traps consist of small swales or ponds positioned between the input and the main 1.
4.
Input
Output
Input
Input
Output
Output
2.
5. Input
Output
3. Input
Output
Figure 5 Theoretical designs to optimize hydraulic efficiency in CWs. Examples 2 and 3 depict micro-uplands that expand the active flowpath across the wetland. Example 4 depicts a submerged berm to encourage water mixing. Figure was redrawn in part from Persson et al., 1999.
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wetland to promote coarse particle settling before water is distributed across the wetland. Sediment traps should be located at easily accessible positions where sediment can be removed on a regular basis. This design feature decreases sedimentation within the wetland, which lengthens the time between dredging, prevents burial of germinating seedlings, and helps limit channelization and short circuiting of flowpaths. CWs often require time to mature in order to reach peak removal efficiency. The time needed ranges from 1 to 3 years depending on the rate of vegetative and microbial establishment. Most CWs have a fixed lifespan depending on sedimentation rates. In agricultural settings, sedimen tation rates are highly variable and can be as high as 85 kg m 2 yr 1 (Maynard et al., 2009). Therefore, to maximize CW lifetime, design speci fications should consider sedimentation rates when designing sediment traps, heights of water control structures, and dikes (Hammer, 1992).
10.3. Placement There are two general options to reduce NPSP from agriculture: (1) manage ment practices implemented on site that limit application and losses from farmlands and (2) off site practices that intercept NPSP before reaching major water supplies. CWs can be used within a farmscape as an on site farm practice or as an off site tool where downstream flood plains are converted to wetlands to mitigate NPSP at watershed scales (Van de Valk and Jolly, 1992). 10.3.1. Watershed to wetland area ratio Placement of a CW is ultimately a site specific consideration addressing contaminants of concern, nature of input flows, and desired community goals. The size of the contributing area, hence placement within a water shed, should be considered with the goal of having a low watershed to wetland area ratio (Kovacic et al., 2000). This is especially important for CWs that receive field runoff or stream flow. To maximize particle trapping, Braskerud (2002a) suggests that the placement of CWs should be near the sediment source in low order watersheds. This minimizes travel distance and increases the likelihood for the CW to receive intact aggre gates, which have greater settling velocities than smaller particles. Braskerud (2002a) suggested that a CW area of at least 0.1% of the watershed area for optimum sediment trapping, however, this study was conducted at wetland sites that received high particulate loads. To realize effective N and P removal, studies in the Midwestern United States suggested that the water shed to wetland area ratios should be around 15–20:1, which corresponded to 3–6% of the watershed area (Kovacic et al., 2000). In irrigated agriculture, the size of the contributing area is indirectly relevant, and it is more important to consider placement of the CW relative to the magnitude of inflow volume and its variability.
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10.3.2. Sociopolitical considerations There are scientific, social, political, and economic issues that require con sideration in order to implement CWs with the intent of having a watershed scale effect on water quality. For example, locating a CW in downstream sites near the watershed output (off site practices) may be considered an efficient way to implement BMPs at the watershed scale. This approach, however, requires the conversion of a large land area to accommodate the hydrologic load and has the potential to be overwhelmed during extreme events (Knight, 1992). The technological investment needed to develop large CWs capable of handling outflows from an entire watershed is much higher than what would be needed if CWs are distributed throughout the watershed. Distributing CWs within headwater environments (on site prac tices), however, can lead to more sporadic inflows and prolonged dry periods, and potentially less efficient systems. More importantly, it requires participation by all (or most) dischargers in order to realize a watershed effect. Other factors to consider for the placement of CWs include the value of land being converted, support of neighboring land owners, the long term avail ability of water, presence of adjacent CWs, and the partners that may be financially involved ( Jia and Luo, 2009; Van de Valk and Jolly, 1992). 10.3.3. Cost It is also important to consider the costs associated with CWs. Maintenance costs are mainly associated with sediment removal, vegetation harvest, and/ or control and management of water control structures. Development costs are primarily associated with grading, dike construction, and flow distribu tion, much of which can be subsidized by government programs, such as USDA EQIP and WRP. Knight (1992) estimated project costs for con struction of CWs over 100 ha at $10,000 per ha, whereas for smaller CWs, costs can be as high as $50,000 per ha (Knight, 1992). Larger wetlands tend to be more cost effective on an area basis because most costs are associated with the development of berms and input–output structures. It may be important to consider the visual appeal of CWs to gain support of local stakeholders. Wetlands with a more natural appearance tend to be more attractive and those CWs with sinuous or wavy lines, and level embankments, tend to be most pleasing to the eye. Adding microtopography to create islands or peninsulas for establishment of trees and deeper water areas may also be a good idea to promote texture and biodiversity (Carty et al., 2008).
10.4. Managing vegetation When choosing vegetation for CWs, the suitability of plants for specific site conditions, including hydrology, climate, food for wildlife, and water quality, should be considered. Ideally the vegetation should have a high pollutant tolerance and assimilation capacity (Scholz and Lee, 2005). In agricultural
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settings, planting native species can often fail due to the large seedbank of exotic species within input waters, thus planting with native species is often not supported by the Wetland Reserve Program (Kovacic et al., 2006). Vegetation provides a variety of benefits but can also become a problem. Vegetation should be encouraged in a way that there is enough biomass for nutrient uptake, sorptive surface area, and plant residue supply. It also needs to be managed to promote light penetration for photodegradative processes and to limit residue accumulation to avoid DOC export. One way to promote this balance is to create areas of deeper water to limit emergent macrophyte establishment intermixed with shallow zones that encourage plant establishment.
10.5. Design features for mosquito control Mosquitoes are undesirable pests and can be vectors for disease. Design features that promote water quality improvements are often at odds with mosquito control measures. A variety of mosquito abatement methods can be used including: (1) chemical treatments; (2) biological treatments, such as Bacillus thuringiensis variety israelensis (Bti) and Bacillus sphaericus (Bs); (3) larvi vorous fish such as Gambusia affinis; and (4) CW design features that discour age habitat and/or facilitate access by predators. Mosquitoes proliferate in densely vegetated wet areas, a CW condition that is preferred for optimizing many contaminant removal processes. Dense stands of vegetation protect mosquito larvae from predators and inhibit biological control efforts (Knight et al., 2003). CW design features to control mosquito larvae attempt to discourage vegetation by preventing stagnant areas, and encourage mos quito fish habitat (Thullen et al., 2002). These include creation of steep walled basin margins, maintaining episodes of water depths greater than 80–150 cm to discourage establishment of emergent macrophytes and creation of deeper areas for fish with access to shallow areas where larvae proliferate.
11. Summary NPSP from agricultural activities is a global problem affecting the quality of our waters for drinking, recreation, and aquatic ecosystems. The agricultural community requires cost effective and practical options to attenuate NPSP. CWs are an appealing option because they are effective contaminant removal systems that are relatively inexpensive to develop and maintain (Hammer, 1992; Larson et al., 2000). NPSP pollutants from agriculture have the potential to be successfully mitigated if CWs are carefully designed and managed. Differences in per formance observed within a given CW in time (diurnally, seasonally, or degree of maturation) or between wetlands (distinct in location) result from
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complex interactions between wetland design (e.g., watershed contributing area to wetland area, placement in watershed, hydrologic efficiency) and management (e.g., hydrologic residence time, hydrologic and pollutant loading rates, vegetation characteristics). CWs efficiently remove (generally >50% removal efficiency) sediment, nitrate, microbial pathogens, particu late phosphorus, hydrophobic pesticides, and selected trace elements when designed appropriately and placed in the correct settings. Additional eco logical services provided by CWs include wildlife habitat and biodiversity, hydrologic buffering of surface waters, ground water recharge zones, and aesthetic value. Many CW systems sequester eroded carbon and endoge nous carbon demonstrating that CWs have potential as a climate change mitigation strategy for agriculture (Maynard, 2009). There are some potentially adverse effects of CWs that must be consid ered in certain regions. Areas with high background levels of mercury or selenium are of concern due to bioaccumulation and biomagnification of toxic metals within the food chain. CWs may also be a source of DOC that acts as precursors for formation of carcinogenic disinfection by products during drinking water purification. CWs with long HRTs can increase salinity in output waters due to evapoconcentration of salts and should be designed with short HRTS (1 day) in areas with high salinity. CWs have the potential to emit potent greenhouse gasses, such as methane and N2O, thus contributing to global climate change. CWs may also provide breeding grounds for disease carrying mosquitoes. Proper wetland management can greatly reduce these potentially adverse effects. However, additional site specific studies are necessary to determine optimum management strategies to maximize contaminant removal and minimize adverse effects across a variety of environmental conditions (i.e., climate, soil, cropping practices). CWs can be employed as on site or off site BMPs to filter agricultural runoff. To realize optimal water quality improvements at the watershed scale, CWs should be included as part of a combination of management techniques, such as conservation tillage, improved irrigation and fertiliza tion techniques, and vegetated filter strips. Further research evaluating the effects of wetland design and management options on NPSP water quality concerns will continue to lead to enhanced wetland performance. When considering all of the ecological services provided by wetlands, CWs should be promoted as an integral component of the farmscape.
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C H A P T E R
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How the Plant Growth-Promoting Bacterium Azospirillum Promotes Plant Growth—A Critical Assessment Yoav Bashan*,† and Luz E. de-Bashan*,† Contents 1. Introduction 2. Major Mechanisms 2.1. Production of phytohormones 2.2. Nitrogen fixation 2.3. General improvement of root growth and enhanced uptake of minerals and water 2.4. Phosphate solubilization and mobilization and rock weathering 2.5. Mitigation of stresses 3. Other Proposed Mechanisms 3.1. Biological control 3.2. Nitric oxide 3.3. Nitrite 3.4. Signal molecules and enhanced proton extrusion from roots 3.5. Azospirillum nitrate reductase 3.6. Additive hypothesis 4. Concluding Remarks and a Proposal Acknowledgments References
78 80 80 101 106 107 108 113 113 116 117 117 119 119 120 122 122
* The Bashan Foundation, Corvallis, Oregon, USA Environmental Microbiology Group, Northwestern Center for Biological Research (CIBNOR), Colonia Playa Palo de Santa Rita, La Paz, B.C.S., Mexico
{
This review is dedicated to the memory of Dr. Wolfgang Zimmer (1958 2002) from Fraunhofer-Institute of Atmosphere Research in Garmisch-Partenkirchen, Germany. He intensively studied mechanisms of action by Azospirillum in the 1980s and 1990s. Advances in Agronomy, Volume 108 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)08002-8
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2010 Elsevier Inc. All rights reserved.
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Yoav Bashan and Luz E. de-Bashan
Abstract During the last 35 years of studies of Azospirillum–plant interaction, over 20 proposals were suggested for the mechanism of action by which Azospirillum spp., the most intensively studied plant growth-promoting bacteria, enhances plant growth. The proposals include a single phytohormone activity, multiple phytohormones, nitrogen fixation, assortments of small-sized molecules and enzymes, enhanced membrane activity, proliferation of the root system, enhanced water and mineral uptake, mobilization of minerals, mitigation of environmental stressors of plants, and direct and indirect biological control of numerous phytopathogens. By volume, the largest number of published information involves hormonal activities, nitrogen fixation, and root proliferation. After analyzing the accumulated knowledge, it was concluded that this versatile genus possesses a large array of potential mechanisms by which it can effect plant growth. Consequently, this review proposes the ‘‘Multiple Mechanisms Theory,’’ based on the assumption that there is no single mechanism involved in promotion of plant growth by Azospirillum, but a combination of a few or many mechanisms in each case of inoculation. These may vary according to the plant species, the Azospirillum strain, and environmental conditions when the interaction occurred. The effect can be cumulative, an ‘‘additive hypothesis’’ (proposed before), where the effects of small mechanisms operating at the same time or consecutively create a larger final effect on plant. Additionally, the observed effect on plant growth can be the result of a tandem or a cascade of mechanisms in which one mechanism stimulates another, yielding enhanced plant growth, such as the plausible relations among phytohormones, nitric oxide, membrane activities, and proliferation of roots. Finally, the growth promotion can also be a combination of unrelated mechanisms that operate under environmental or agricultural conditions needed by the crop at particular locations, such as mitigating stress (salt, drought, toxic compounds, adverse environment), and the need for biological control of or reducing pathogenic microflora.
1. Introduction Since the rediscovery in the mid 1970s of the genus Azospirillum as a plant associated bacteria by the late Johana Do¨bereiner and her collaborators in Brazil and its definition as a plant growth promoting bacteria (PGPB; Do¨bereiner and Day, 1976), two main characteristics defined the genus; it fixes atmospheric nitrogen and produces phytohormones (Tien et al., 1979). Consequently, these two features were considered, from the onset of plant–bacteria studies, as the cornerstone of the effect of this genus on plant growth and yield. Because Azospirillum is the most studied PGPB, excluding rhizobia, and reached commercialization in several countries, including Argentina, Mexico, India, Italy, and France (Dı´az Zorita and
How the Plant Growth-Promoting Bacterium Azospirillum Promotes
79
Ferna´ndez Canigia, 2009; Hartmann and Bashan, 2009), considerable knowledge has been accumulated during the last three decades, showing more and different facets of this interaction. Despite intensive studies of the physiology and molecular biology of this genus, mostly as an easy to handle laboratory model of a rhizosphere bacterium, the exact mode of action of the bacteria on plants is not much clearer than it was decades ago (Bashan and Holguin, 1997; Bashan and Levanony, 1990; Bashan et al., 2004). There are three facts that are beyond dispute, each with a reservation: (1) Most Azospirillum strains can fix nitrogen but only a fraction of it, if any at all, is transferred to the plant; (2) Many strains, but not all, produce several phytohormones in vitro and also a few in association with plants, but transfer of hormones is probably limited and was not always detected and only assumed to occur; (3) A general positive growth response in numerous plant species is evident in the majority of cases of inoculation, but the effect is not always apparent in terms of economic productivity (Dı´az Zorita and Ferna´ndez Canigia, 2009; Okon and Labandera Gonzalez, 1994). These concerns accelerate the research into alternative mechanisms. The most apparent outcomes of most inoculations with Azospirillum are the major changes in plant root architecture. Inoculation can promote root elongation (Dobbelaere et al., 1999; Levanony and Bashan, 1989), develop ment of lateral and adventitious roots (Creus et al., 2005; Fallik et al., 1994; Molina Favero et al., 2008), root hairs (Hadas and Okon, 1987; Okon and Kapulnik, 1986), and branching of root hairs ( Jain and Patriquin, 1985), some of which occurred in many plant species, consequently significantly increasing and improving their root system. It is generally accepted that these developmental responses in root morphology are triggered by phyto hormones, possibly aided by their associated molecules. The fundamental question is: one hormone or several or a fine tuned combination among several hormones?—all of which were produced by the bacterium, but mainly in vitro. Inoculated plants absorbed more minerals and water, and in many cases, were more vigorous and greener, and showed enhanced plant growth. Several possible mechanisms were suggested to explain these phenomena, some with more experimental data than others. Yet, there is no definite agreement on exactly how the bacteria can effect plant growth. Is this a result of an input by the bacteria and can we manipulate it? Naturally, a multitude of proposed mechanisms claim to the lead mechanism responsible for the observed effects on plant growth, and specifically, on plant yield, that in most case, is the desired outcome and the main reason for inoculation. These questions are the driving force in Azospirillum research today, because if we have a clearer idea how the bacterium interacts with its host, we may envision ways to improve the interaction.
80
Yoav Bashan and Luz E. de-Bashan
The aims of this chapter are to critically assess the large amount of knowledge on the possible plant promoting mechanisms of Azospirillum (Table 1, Fig. 1) and to present potential avenues for clarifications of this open question or at least some starting points for future research.
2. Major Mechanisms 2.1. Production of phytohormones The ability to form plant hormones is a major property of many micro organisms and PGPB in general and specifically, species of Azospirillum that stimulate and facilitate plant growth (Tsavkelova et al., 2006). This is believed to be part of the mutualistic relationships developed between plants and their associate bacteria. Azospirillum spp. are known for their ability to produce plant hormones, as well as polyamines and amino acids in culture media (Hartmann and Zimmer, 1994; Thuler et al., 2003). Among these hormones, indoles, mainly indole 3 acetic acid (IAA; Spaepen et al., 2007a), and gibberellins (GAs) of several kinds (Bottini et al., 2004) may play a larger role. These phytohormones alter metabolism and morphology of plants, leading to better absorption of minerals and water, consequently larger and healthier plants. In the unicellular microalga Chlorella vulgaris, phytohormones lead to larger cell populations (de Bashan et al., 2008a). Thus far, hormonal effects are the mode of action for the largest volume of experimental data, and it is presented, justifiably or not, as the major (and sometimes as the sole) contribution of Azospirillum to plant growth. The topic of IAA in PGPB in general and Azospirillum in particular and specifically the genes involved in synthesis of IAA were intensively, contin uously, and excellently reviewed during the last decade (Costacurta and Vanderleyden, 1995; Dobbelaere et al., 2003; Patten and Glick, 1996; Spaepen et al., 2007a,b; Steenhoudt and Vanderleyden, 2000; Vande Brock and Vanderleyden, 1995), and therefore, this review will present only a few key points for and against their proposal. 2.1.1. Indole-3-acetic acid IAA is a heterocyclic compound containing a carboxymethyl group (acetic acid) that belongs to the auxin phytohormone family. It is the best char acterized and the most studied phytohormone and involved in numerous mechanisms in plant physiology. Auxins are responsible for division, exten sion, and differentiation of plant cells and tissues. Phytohormones of this group increase the rate of xylem and root formation; control processes of vegetative growth, tropism, florescence, and fructification of plants; and also affect photosynthesis, pigment formation, biosynthesis of various metabo lites, and resistance to biotic stress factors. In microorganisms, in general, the
Table 1
General evaluation of proposals for mode of action on plants by Azospirillum
Proposal
Year proposed and significance with current knowledgea Description
Phytohormones
1979 present (þþþ)
IAA
1979 present (þþþ)
Evidence for
Arguments against and/ or lack of evidence for
References (examples)b
Costacurta and Azospirillum can produce in vitro several phytohormones. External Vanderleyden (1995), application of synthetic hormones or hormones purified from Spaepen et al. bacterial culture imitated the positive effects of Azospirillum on root (2007a), Steenhoudt development and Vanderleyden (2000), Vande Brock and Vanderleyden (1995) 1. Only several cases of Baca et al. (1994), IAA is produced by 1. Most strains of Barbieri and Galli direct involvement Azospirillum the bacterium (1993), Bothe et al. of IAA in growth produce IAA in vitro in large (1992), de Bashan promotion of plants in vitro quantities and et al. (2008a), are known 2. In several cases, is attributed to Dobbelaere et al. 2. There are no IAA IAA attenuated affect numerous (1999), El Khawas deficient mutants mutants were alterations in plant and Adachi (1999), 3. Most demonstrated ineffective functions yielding Fallik et al. (1989), cases are indirect or compared to their eventually growth Gonzalez and Bashan circumstantial wild type parental promotion. (2000), Hartmann 4. IAA is produced by strains Significant et al. (1983), Malhotra plant cells and IAA knowledge about 3. Application of IAA and Srivastava (2008), detected in the plants mimics IAA metabolism Molla et al. (2001), were only indirectly Azospirillum and molecular Omay et al. (1993), induced, but not inoculation on (continued)
82
Table 1
(continued)
Proposal
Year proposed and significance with current knowledgea Description
mechanism in the bacterium is known
Evidence for
root morphology and growth promotion of plants and single cell algae 4. IAA is involved in numerous functions in the plant cells and therefore might be a part of a cascade employing other mechanisms 5. Elevated IAA was detected in inoculated plants 6. IAA overproducing mutants showed stronger effect on plants
Arguments against and/ or lack of evidence for
5.
6.
7.
8. 9.
directly produced by the bacterium Direct transfer of bacterial IAA into plant cells and its functional consequences are still lacking Production of bacterial IAA in the plant was not demonstrated Cases of no evidence of correlation between capacity of IAA biosynthesis and root growth promotion Is additional IAA in planta better? Studies showing that Azospirillum IAA biosynthesis alone cannot account for the overall growth promotion observed
References (examples)b
Remans et al. (2008), Spaepen et al. (2007b, 2008), Zimmer et al. (1991)
Insufficient evidence for Bottini et al. (1989, 1. GAs are GA affecting plant 2004), Cassan et al. involvement of synthesized and development in (2009a,b), Fulchieri bacterial GA in metabolized by similar manner like et al. (1993), Piccoli promoting growth Azospirillum in vitro auxins with several and Bottini (1994a,b), 2. GA are produced differences. GA Piccoli et al. (1997, in planta by promotes cell 1999), Perrig et al. Azospirillum division and (2007) elongation and are 3. Inoculation of GA deficient involved in mutant dwarf rice breaking dormancy mutants with Azospirillum GA producer reversed dwarfism No direct evidence in Cacciari et al. (1989), Cytokinins were 1979 (UN) Cytokinins are Horemans et al. plants. Insufficient produced by involved in cell (1986), Strzelczyk data. Azospirillum in vitro enlargement and et al. (1994), Tien division, shoot and et al. (1979) root morphogenesis and senescence Insufficient evidence for Cohen et al. (2008, 2007 present (UN) ABA is involved in 1. This compound 2009), Perrig et al. involvement of was found in vitro response to (2007) bacterial ABA in in several strains environmental growth promotion stress such as heat, 2. Interaction between GA and water, and salt ABA in water stress mitigation of plants
Gibberellins (GA) 1989 present (þþ)
Cytokinins
Abscisic acid (ABA)
83
(continued)
84
Table 1
(continued)
Proposal
Year proposed and significance with current knowledgea Description
Evidence for
Arguments against and/ or lack of evidence for
References (examples)b
Holguin and Glick Too few cases of Ethylene plays a role 1. Ethylene was (2001, 2003), Perrig ethylene involvement found in culture in breaking et al. (2007), Prigent in Azospirillum, to filtrate of dormancy of seeds. Combaret et al. compare with other A. brasilense Its main effect is in (2008), Ribaudo et al. PGPB, where it is a senescence of the 2. Growth (2006) major mechanism promotion was plant associated with low ethylene levels in tomato 3. Insertion gene of ACC deaminase in Azospirillum improve plant growth Cassan et al. (2009a), 1. These compounds Limited data 2003 present (UK) Unclear function. Polyamines: Perrig et al. (2007), were found in vitro Can act as growth cadaverine, Thuler et al. (2003) 2. Application of regulating putrescine, cadaverine compounds spermine, and mitigated osmotic spermidine stress in rice Bashan et al. (1990), 1. Most data is 1979 present Inoculation caused a 1. Enhanced root Enhanced root Jain and Patriquin descriptive and does system is the most (þþþ) more developed growth (1984), Kapulnik et al. not show whether common root system that combined with (1981, 1985b), Lin the improvements allows better uptake phenotypical effect enhanced et al. (1983), are the cause or the of inoculation with
Ethylene
2006 present (þ)
mineral and water uptake
Nitrogen fixation 1975 present (þþ)
85
Morgenstern and results of other Azospirillum in Okon (1987), Murty mechanisms most plant species and Ladha (1988), 2. Enhanced mineral 2. The wide range of Ogut and Er (2006), enzymes related to and water uptake Sarig et al. (1988, these phenomena by plants follow 1992) was only slightly inoculation studied 3. Despite the large volume of information, relatively few strains were evaluated Baldani and Baldani Many studies showed Nitrogen fixation is a 1. Following (2005), Bashan et al. little or minimal inoculation common feature of (1989b, 2004), contribution of fixed significant increase most Azospirillum Choudhury and nitrogen in the plant. in total N in shoots species. Kennedy (2004), Some systems showed and grain Christiansen none 2. Many greenhouse Weniger (1992), and field Garcia de Salamone experiments et al. (1997), indicate some Katupitiya et al. contribution of (1995a,b), Kennedy fixed N in the and Islam (2001), plant Kennedy et al. (2004), 3. Inoculation Mirza et al. (2000), commonly Rodrigues et al. reduced the level (2008), Saubidet and of N fertilization Barneix (1998), needed for many Sriskandarajah et al. plant species of water and minerals
(continued)
86 Table 1
(continued)
Proposal
Year proposed and significance with current knowledgea Description
Nitric oxide (NO)
2005 present (þ)
Nitrite production
1992 (UN)
NO is a free radical which participates in metabolic, signaling, defense, and developmental pathways in plants Azospirillum can produce nitrite as part of its normal metabolism
Evidence for
Arguments against and/ or lack of evidence for
4. Enhanced nitrogenase activity in inoculated plants 5. The contribution of fixed N was apparent in many para nodule systems Limited data 1. Azospirillum can produce NO in vitro by different pathways 2. NO can modify root architecture 1. Nitrite participated Limited data in plant growth promotion 2. Nitrite can cause sharp decrease in formation of lateral roots
References (examples)b
(1993), Van Dommelen et al. (2009)
Creus et al. (2005), Molina Favero et al. (2007, 2008)
Bothe et al. (1992), Zimmer et al. (1988)
Limited data 1. NR activity of An explanation for wheat leaves was accumulating decreased by nitrogen following inoculation with Azospirillum some Azospirillum inoculation strains 2. Increase in nitrate assimilation Limited data Several strains can 1998 present (UN) Solubilization of solubilize several rock nonsoluble P and minerals especially other minerals from P making them rocks and stones available for the plant
Nitrate reductase 1987 (UN) (NR)
Phosphate solubilization and mineral weathering
Effect on plant membranes and enhanced proton extrusion
1989 present (UN) Inoculation induces root cell membranes to release protons
87
1. Short exposure of roots to A. brasilense significantly enhanced the proton efflux of the root 2. Inoculation significantly reduced the membrane potential in every root part
Boddey and Do¨bereiner (1988), Ferreira et al. (1987)
Carrillo et al. (2002), Chang and Li (1998), Kamnev et al. (1999a, 2002b), Puente et al. (2004a,b, 2006), Rodriguez et al. (2004), Seshadri et al. (2000) 1. Signal molecules in Alen’kina et al. (2006), Amooaghaie et al. bacteria that might (2002), Antonyuk affect membranes et al. (1993, 1995), were not identified Bashan (1990, 1991), 2. Mobilization of ions Bashan and Levanony via the affected (1991), Bashan et al. membranes was not (1989a, 1992), studied Carrillo et al. (2002), Nikitina et al. (2004)
(continued)
Table 1 (continued) 88 Proposal
Year proposed and significance with current knowledgea Description
1988 present Mitigation of environmental stress Salinity
Evidence for
Arguments against and/ or lack of evidence for
3. Inoculation changed the phospholipid content in plant membranes 4. Azospirillum produces lectins. Some can cause change in growing cells mitosis 5. Wheat germ agglutinin from plants enhanced several metabolic pathways in Azospirillum Best effects of inoculation occurred when plants are grown under suboptimal conditions
1997 present (þþ) Inoculated plant under saline condition grow better
References (examples)b
Bashan and Holguin (1997), Bashan and Levanony (1990), Bashan et al. (2004) Missing information on: Bacilio et al. (2004), 1. Inoculation Barassi et al. (2006), 1. Relation between improved Creus et al. (1997), salt tolerance of the germination, plant Hamdia and bacterium and those development of the plant
Drought
Metal toxicity
2. Increases in content of water, chlorophyll, essential minerals, proteins, amino acids, enhanced uptake of K and Ca, NR, and nitrogenase 3. Restricted Na uptake Inoculation improved 1988 present (þþ) Inoculated plant plant growth, under drought or reduce grain loss, osmotic stress are improve water growing better content, increased turgor pressure, positive effect on cell wall elasticity, higher Mg, K, and Ca in grains, and improve fatty acid distribution profile 2000 present (þ) Reduction in toxicity 1. The bacterium to plants tolerates medium levels of metals
2. What are the physiological mechanisms involved? 3. How do the bacteria induce these effects?
El Komy (1997), Hamdia et al. (2004)
Too little data about the Alvarez et al. (1996), Creus et al. (1998, physiological 2004), El Komy et al. mechanisms involved (2003), Pereyra et al. (2006), Sarig et al. (1990)
Inoculation does not provide full protection against metal toxicity
Belimov and Dietz (2000), Belimov et al. (2004), Kamnev et al.
89
(continued)
90
Table 1
(continued)
Proposal
Year proposed and significance with current knowledgea Description
Humic acid toxicity
2003 (UN)
pH and tryptophan in aquatic environment High light intensity
2005 present (þ)
2006 present
Evidence for
Arguments against and/ or lack of evidence for
2. Inoculation allows plants to grow in metal contaminated soils and in mine tailings Inoculation does not Reduction in toxicity 1. Improved provide full to plants germination and protection against plant growth at toxicity elevated humic acids 2. Consumption of humic acid by the bacterium Inoculated microalgae Unknown Inoculation allows microalgae to grow can grow in high pH and toxic levels under unfavorable of tryptophan aquatic conditions 1. Inoculated wheat Unknown Inoculation allows plants produced plants to grow photoprotective under high light photosynthetic intensity pigments
References (examples)b
(2005, 2007), Lyubun et al. (2006)
Bacilio et al. (2003)
de Bashan and Bashan (2008), de Bashan et al. (2005) Bashan et al. (2006), de Bashan et al. (2008b)
2. Inoculation allowed microalgae to grow under extreme light intensities Unknown Feng and Kennedy Herbicide 1997 (UN) Reduction in toxicity Cotton plants were (1997) to plants partially protected from the herbicide 24D Bashan and de Bashan 1. Most studies are 1. Azospirillum Biological control 1990 present (þþ) Indirect effects on (2002a), Dadon et al. descriptive produces a variety of pathogens plant growth (2004), Gonc¸alves 2. Almost all of inhibitory reducing the and de Oliveira mechanisms were substances deleterious effects (1998), Kavitha et al. not studied or are in 2. Inhibits of pathogens (2003), Khan and initial stage germination and Kounsar (2000), development of Romero et al. (2003), parasitic weeds Sudhakar et al. (2000) 3. Can compete with phytopathogens 4. Inhibits development of microfauna and insects 5. Inhibits foliar bacterial diseases and soil borne fungal pathogens 91
(continued)
Table 1 (continued)
Proposal
a b
Year proposed and significance with current knowledgea Description
Additive hypothesis
1990 present
Multiple mechanisms
2010
Evidence for
Arguments against and/ or lack of evidence for
The effects of small mechanisms operating at the same time or consecutively create a larger final effect on plant
References (examples)b
Bashan and Dubrovsky (1996), Bashan and Levanony (1990) A combination of a few or many mechanisms in each case of inoculation This essay
þþþ, possibly major mechanism; þþ, possibly moderate; þ, possibly minor; UN, unknown. More comprehensive literature are listed in the text.
93
How the Plant Growth-Promoting Bacterium Azospirillum Promotes
Azospirillum
? Enhanced mineral
Effect on root architecture
and water uptake
Phytohormones+ accessory molecules
IAA
GA
Ethyl
Salinity
No
Cyto
P and m neral so ub lizat on
Po y amines
Nitrite
Drought
pH Herb Com
ABA
Tox Ex Li
IAA; Indol-3-acetic acid GA; Gibberellins ABA; Abscisic acid Ex-Li; Excessive light Herb; Herbicide Com; Compost Tox; Toxic substances Ethyl; Ethylene Cyto; Cytokinins NO; Nitric oxide NR; Nitrate reductase
NR
?
? ? Reduced environmental stress
? Effects on membranes
Additive hypothesis
Lectins
Nitrogen fixation Multiple biological control mechanisms
Multiple mechanisms hypothesis
?
Figure 1 Mechanisms by which Azospirillum spp. may enhance plant growth and their possible interactions grouped as biological processes. Circles represent processes containing experimental data. Squares represent theories. Size of a circle represents its relative importance according to current data. Solid arrow: mechanism(s) that can fully create the observed growth promotion; dash arrow: mechanism(s) that can only partially explain the observed growth promotion. Simple arrows: proven interactions among different mechanisms; double-line arrow: direct production of molecules or processes by the bacterium cell; ?: unproven as yet, or partially proven pathway.
three known pathways of IAA biosynthesis are related to tryptophan metabolism (amino acid frequently found in plant exudates; Costacurta and Vanderleyden, 1995; Patten and Glick, 1996). Omission of tryptophan from the culture medium decreases the level of IAA synthesis by the culture’s microorganisms. Addition of exogenous tryptophan (or, more rarely, tryptamine) may augment auxin biosynthesis by an order of magni tude or even greater. The known routes of IAA biosynthesis includes: (1) IAA formation via indole 3 pyruvic acid (IPyA) and indole 3 acetalde hyde; (2) Conversion of tryptophan into indole 3 acetaldoxyme and indole 3 acetonitrile (IAN); and (3) IAA biosynthesis via indole 3 acet amide formation (IAM; Zakharova et al., 1999). It has been reported that a tryptophan independent pathway, more common in plants, was also found in azospirilla (Carren˜o Lopez et al., 2000; Prinsen et al., 1993). However, the contribution of this pathway to IAA biosynthesis is questionable, and the mechanisms are largely unknown.
94
Yoav Bashan and Luz E. de-Bashan
Involvement of tryptophan in IAA production by Azospirillum has been known for a long time (Reynders and Vlassak, 1979). A key gene ipdC encodes for indole pyruvate decarboxylase. This is a key enzyme in the IAA synthesis pathway by A. brasilense that mediates conversion of IPyA into indole 3 acetaldehyde; its presence presented conclusive evidence for the IPyA pathway in this bacterium (Costacurta et al., 1994). Zimmer et al. (1998) isolated the ipdC gene from strain Sp7 of A. brasilense and showed tryptophan dependent stimulation of gene expression in this bacterium. These two findings were later confirmed by IAA production by several strains of Azospirillum where production depended on the type of culture media and availability of tryptophan as a precursor (e.g., El Khawas and Adachi, 1999; Malhotra and Srivastava, 2006, 2008). The pH of the culture medium has a significant effect on the amount of IAA produced (Ona et al., 2003). Release of large amounts of IAA by Azospirillum spp. cultures is probably controlled by the stationary phase of the bacteria cells after deple tion of the carbon source in the medium used in batch culture. Depletion of the carbon source reduces growth (Ona et al., 2003, 2005). Assessment of possible precursors (indole, anthranilic acid, and tryptophan) for IAA for mation in A. brasilense Sp245 revealed a high motive force for tryptophan synthesis from chorismic acid and for IAA synthesis from tryptophan (Zakharova et al., 1999). Vitamins may also play a role in the regulation of IAA synthesis in A. brasilense. Very low levels of B vitamins, especially pyridoxine and nicotinic acid, increased production of IAA in A. brasilense (Zakharova et al., 2000). To demonstrate direct involvement of IAA produced by A. brasilense on plant growth, it would be preferable, if not essential, to use IAA deficient mutants. It is relatively straightforward to obtain IAA overproducing mutants (Hartmann et al., 1983) but, so far, almost impossible to obtain IAA deficient mutants. This occurs because of the different pathways that Azospirillum spp. has to produce IAA (Spaepen et al., 2007a; Zakharova et al., 1999). For example, in most mutants, the unstable indole pyruvic acid spontaneously breaks down and produces some IAA (Steenhoudt and Vanderleyden, 2000). These IAA attenuated mutants produce 0.2–10% of the level of IAA produced by the wild type, sometimes even more. Quite a few of these strains were found or constructed and used. A strain of A. irakense released about 10 times less IAA into the medium than A. brasilense Sp7 (Zimmer et al., 1991). Two mutants of A. brasilense pro duced 2–5% of the IAA produced by the parental strains (Prinsen et al., 1993, Vande Broek et al., 1999). Mutants of A. brasilense and A. lipoferum that were modified to include the gfp (green fluorescent protein) gene produced less than 0.25% IAA of their parental strains (Bacilio et al., 2004; Rodriguez et al., 2006) and mutant of A. brasilense Sp6, carrying another Tn5 insertion in the ipdC gene, produced less than half the IAA of its parental strain (Barbieri and Galli, 1993). Recently, an ipdC knockout mutant was found to produce
How the Plant Growth-Promoting Bacterium Azospirillum Promotes
95
only 10% of the wild type IAA production level (Spaepen et al., 2007b). Furthermore, when the endogenous promoter of the ipdC gene was replaced by either a constitutive or a plant inducible promoter and both constructs were introduced into the wild type strain, the introduction of these recom binant ipdC constructs improved the growth promoting effect of A. brasilense (Spaepen et al., 2008). IAA is produced during all stages of culture growth and well after the stationary phase (Malhotra and Srivastava, 2009). This feature makes the bacterium especially qualified for plant growth promotion when the effect last weeks or months after inoculation. Consequently, IAA production by Azospirillum sp. was proposed to play a major role in growth promotion and even more auxin type molecules were detected in Azospirillum, such as indole butyric acid (IBA; Fallik et al., 1989), indole lactic acid (Crozier et al., 1988), indole acetamide (Hartmann et al., 1983), indole acetaldehyde (Costacurta et al., 1994), indole ethanol and indole methanol (Crozier et al., 1988), and phenyl acetic acid (Somers et al., 2005). Nonetheless, when compared to the large base of knowledge on IAA production by the bacterium cell, a far smaller volume of indirect and direct evidence regard ing the effect of IAA of bacterial origin in plants has been published. In general, morphological changes in roots, following Azospirillum inoc ulation, were mimicked by applying a combination of plant growth sub stances, which point to involvement of an auxin produced by Azospirillum for root proliferation and consequent plant growth promotion (for reviews, see Bashan and Holguin, 1997; Bashan et al., 2004). Specific evidence for the involvement of auxins in promoting plant growth includes elevated IAA and IBA in Azospirillum inoculated maize plants (Fallik et al., 1989). Addi tion of filter sterilized culture supernatants to rice roots grown in hydro ponic tanks increased root elongation, root surface area, root dry matter, and development of lateral roots and root hairs, compared with untreated roots. Higher concentrations of the supernatant strongly inhibited root elongation, lateral root development, and caused nodule like tumors on the roots (El Khawas and Adachi, 1999). Similarly, a cell free supernatant of A. brasilense Cd applied to soybean plants induced many roots and increased root length (Molla et al., 2001). Inoculation of wheat with wild strains of A. brasilense Sp245 and Sp7 led to an exceptional decrease in root length and increase in root hair formation, as is common with such inoculations. The effect on root morphology was further enhanced by adding tryptophan; this could be mimicked by replacing Azospirillum cells with IAA (Dobbelaere et al., 1999). Exogenous application of IAA to bean roots resembled responses of these plants to inoculation with Azospirillum (Remans et al., 2008). Similarly, application of IAA directly to growing cells of the fresh water microalgae C. vulgaris mimicked cell proliferation induced by Azospirillum (Gonzalez and Bashan, 2000). More direct evidence for the importance of IAA was provided when several IAA attenuated mutants
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were compared with their parental wild types for their effect on the growth of this microalga, when only the wild types were capable of promoting growth. Yet, adding culture filtrate of these wild types to cultures of IAA attenuated mutants, incapable of inducing microlagal growth, restored their effect on microalgal growth (de Bashan et al., 2008a). A mutant of A. brasilense with low production of phytohormones, but high N2 fixation activity, did not enhance root growth over uninoculated controls. In contrast, a mutant with increased phytohormone production significantly affected root morphology. In general, increased plant biomass and N2 fixation were recorded in strains having increased production of indole compounds (Kundu et al., 1997). Further study of the contribution of auxin biosynthesis by A. brasilense in altering root morphology and root proliferation showed that inoculation of wheat seedlings with an A. brasilense Sp245 strain, carrying a mutation in the ipdC gene, which did not cause shorter roots or stimulate root hair formation, in contrast to inoculation with the wild type (Dobbelaere et al., 1999). The insertion of the heterologous IAM pathway, consisting of the iaaM and iaaH genes into A. brasilense SM increased IAA levels by threefold and the engi neered strain showed a superior effect on the lateral branching of sorghum roots, as well as its dry weight when compared with the wild type strain (Malhotra and Srivastava, 2006). Several studies showed no evidence of correlation between the capacity for IAA synthesis by A. brasilense and the effects on observed root growth promotion (Bothe et al., 1992; Harari et al., 1988; Kapulnik et al., 1985a). Additionally, several studies showed that Azospirillum IAA biosynthesis alone cannot account for the overall growth stimulatory effect observed (for a review, see Spaepen et al., 2007a). In summary, although evidence of IAA production in Azospirillum spp. is the most comprehensive and documented from all hormones or suggested mechanisms, the direct evidence of involvement of this hormone as the sole mechanism by which the bacteria affect plant growth is, in our opinion, unproven, although it is very likely that IAA is involved in many of the interactions of this genus. It is feasible though to consider a hormonal effect in very early stages of germination. Most stains of Azospirillum, when fermented as an inoculant, are capable of producing IAA and other growth regulators at a concentration sufficient to produce morphological and phys iological change in young seed tissues. Such initial ‘‘phytohormonal shock’’ would be the first contact between the bacterial inoculant and the seed and would not necessarily depend on the presence of bacteria. However, the presence of live bacteria may contribute to in situ phytohormone produc tion over a longer term. According to this concept, bacterial phytostimula tion would be crucial in early developmental stages (germination and initial seedling growth) and will be complementary to other mechanisms operating at later stages of Azospirillum interaction with plants (Cassan et al., 2009b), as summarized in Section 3.6.
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2.1.2. Gibberellins and abscisic acid GAs, diterpenoid acids that are synthesized by the terpenoid pathway, are hormones (over 120 types have been found in plants, fungi, and bacteria) that control growth and a wide variety of other plant developmental processes similar to auxins. Primarily, they promote cell division and elongation, but without inhibitory effects presented by some auxins. Additionally, GAs are involved in the natural process of breaking dor mancy during seed germination. GAs in the seed embryo signal starch hydrolysis by inducing the synthesis of the enzyme a amylase in the aleurone cells. This enzyme hydrolyzes starch into glucose; the glucose is used for energy by the seed embryo. GAs cause higher levels of transcription of the gene coding for the a amylase enzyme to stimulate the enzyme synthesis (Richards et al., 2001). Despite this major role and the fact that A. brasilense is known to enhance germination of wheat and soybean seeds (Bacilio et al., 2003; Cassan et al., 2009b), GAs, so far, were not directly linked to this phenomenon. It was only shown that improved seed germination coincides with high GA production in cultures by this bacterium (Cassan et al., 2009b). Azospirillum has the capacity to synthesize and metabolize GAs in vitro (Bottini et al., 1989; Piccoli and Bottini, 1994a,b; Piccoli et al., 1996, 1997) and in planta (Bottini et al., 2004; Cassan et al., 2001a,b, and references cited therein). A growth promotion effect of Azospirillum spp. on plants has been suggested to be partially caused by the production of GAs by the bacterium as has occurred with other PGPB (for a review, see Bottini et al., 2004). Several studies support this proposal. When a GA producing strain of A. lipoferum was cultured in the presence of glucosyl ester or glucoside of GA A20, both conjugates were hydrolyzed. These in vitro results support the hypothesis that growth promotion in plants induced by inoculation with Azospirillum results from a combination of GA production and GA gluco side/glucosyl ester deconjugation by the bacterium (Piccoli et al., 1997). The effect of water potential or concentration of O2 on growth and GA A3 (the main GA identified in Azospirillum) production in A. lipoferum showed that this GA produced by each culture was reduced severely at high water potentials or low O2 concentrations. At the highest water potential concen tration, GA A3 was reduced by 50%, despite a 90% reduction in cell numbers. This indicates an increase in the amount of GA A3 produced per cell with increasing water potential (Piccoli et al., 1999). Involvement of GA A3 produced by Azospirillum spp. in promoting growth of maize was also suggested (Lucangeli and Bottini, 1997). A. brasilense Cd and A. lipoferum USA 5b promoted elongation of root sheaths with two single genes in GA deficient dwarf rice mutants, dy and dx, when the inoculated seedlings were supplied with [17, 17 2H2] GA A20 glucosyl ester. This growth resulted from GA metabolism by the bacteria in the dx mutant and by the rice plant
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and microorganism in the dy mutant. In the dy mutant, inoculation by both bacterial strains reversed dwarfism in seedlings incubated with [17, 17 2H2] GA A20, forming [17, 17 2H2] GA A1. It is possible that the bacterial enzyme responsible for these phenomena is 2 oxoglutarate dependent dioxygenase, similar to those of plants (Cassan et al., 2009a,b). Initial studies on the effect of Azospirillum spp. on plants linked GAs and bacteria produced abscisic acid (ABA), a common isoprenoid phytohor mone usually synthesized in all plant parts. ABA is ubiquitous and produced by higher plants, algae, and fungi (Zeevaart, 1999) and as a by product of chemically defined cultures of A. brasilense Sp245 (Cohen et al., 2008). ABA originated from its role in the abscission of leaves of only a few plant species but its main role in plants is as a response phytohormone to environmental stress, such as decreased soil water potential and heat, water, and salt stresses. ABA produced in roots is then translocated by transpiration in the xylem to the leaves, where it rapidly alters the osmotic potential of stomata guard cells, causing them to shrink and stomata to close. The ABA induced closure of stomata reduces transpiration, preventing further water loss in times of low water availability (Bartels and Sunkar, 2005). In this stress mitigation process, ABA–GAs were investigated with Azospirillum inocula tion even though ABA and GAs have antagonistic roles in many processes of plant growth (Achard et al., 2006; Nemhauser et al., 2006). The effects of A. lipoferum in maize plants, in which ABA and GA synthesis were diminished by inhibitors of their own biosynthetic pathways (ABA by fluridone and GA by Ca prohexadione) and subjected or not to drought stress, were measured. Application of fluridone diminished growth of well watered plants similar to the effect of drought and A. lipoferum inoculation completely reversed this effect. The relative water content of the fluridone treated and drought stressed plants was significantly lower, and this effect was completely neutralized by A. lipoferum. The results suggest that ABA produced by the bacterium may account, at least partially, for the amelioration of growth parameters in drought stressed and fluri done treated plants. Similarly, growth was diminished in plants subjected to drought and treated with Ca prohexadione, alone or combined with flur idone, even though ABA levels were higher. The results suggest that ABA and GAs participate in alleviating water stress of plants by the presence of A. lipoferum (Cohen et al., 2009). So far, the results indicate that, among the mechanisms involved in water stress alleviation of plants by Azospirillum, is the production of stress type hormones such as ABA (Cohen et al., 2008) along with growth promoters, such as auxins (Costacurta and Vanderleyden, 1995) and GAs (Bottini et al., 2004). Similar to the studies on IAA, there is far more information about GA metabolism in the bacterium that the effect of bacterial produced GA in plants where the information about the involve ment of ABA is still at an embryonic stage.
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2.1.3. Polyamines The newest compound involved in promoting growth by Azospirillum spp. is the polyamine cadaverine synthesized from lysine. Polyamines are low molecular weight organic compounds having two or more primary amino groups (–NH2). Polyamines are known to be synthesized in cells via highly regulated pathways, yet, their actual function is not entirely clear. If cellular polyamine synthesis is inhibited, usually cell growth is stopped or severely inhibited. Application of exogenous polyamines restores the growth of these cells. Most eukaryotic cells have a polyamine transporter system on their cell membranes that facilitates internalization of exogenous polya mines. Polyamines serve as growth regulating compounds (Kuznetsov et al., 2006); among them, cadaverine has been correlated with root growth promotion in pine and soybean (Gamarnik and Frydman, 1991; Niemi et al., 2001), response to osmotic stress in turnip (Aziz et al., 1997), and controlling stomata activity in Vicia faba beans (Liu et al., 2000). A. brasilense strain Az39, which is a widely used as a wheat and maize inoculant in Argentina, is known to produce polyamines such as spermidine and sper mine (Perrig et al., 2007), and putrescine (Thuler et al., 2003) in culture, and also produce cadaverine in chemically defined medium supplemented with the precursor L lysine and in rice plants inoculated with this strain. Appli cation of cadaverine mitigated osmotic stress in rice seedlings, based on improved water status and decreased production of ABA in inoculated seedlings (Cassan et al., 2009a). Cadaverine was proposed as a contributing factor to the whole plant response to Azospirillum inoculation, summarized in Section 3.6 (Bashan et al., 2004). 2.1.4. Cytokinins Cytokinins are a class of purine type phytohormones that promote cell division, shoot and root morphogenesis, chloroplast maturation, cell enlargement, auxiliary bud release, and senescence. The ratio of auxin to cytokinin is crucial during cell division and differentiation of plant tissues. Auxin is known to regulate the biosynthesis of cytokinin. The adenine type cytokinins represented by kinetin, zeatin, and 6 benzylaminopurine occur in plants. Cytokinins are produced in defined culture medium by many rhizo sphere bacteria (Barea et al., 1976), including Azospirillum (Cacciari et al., 1989; Horemans et al., 1986; Strzelczyk et al., 1994; Tien et al., 1979). Cytokinins from bacteria might affect plant growth positively or negatively. Apart from initial results of plants inoculated with Azospirillum, it is ques tionable if cytokinins, on their own, modified the root morphology observed in many Azospirillum inoculation models or if it is the levels of combination with auxin and GAs that induced the observed effect. It is hypothesized (F. Cassa´n, personal communication) that the contribution of
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cytokinins is of some, yet undefined, importance when Azospirillum is combined with Bradyrhizobium for inoculation of soybeans. Recently, nod factors in soybean were shown as not essential for nodulation and that some strains of Bradyrhizobium use purines (cytokinins) as an alternative option for nodulation (Giraud et al., 2007). Azospirillum as a potential producer of cytokinins might support this type of nodulation. It is commonly observed that inoculation with Azospirillum increased nodulation (Schmidt et al., 1988; Yahalom et al., 1990). Yet, this hypothesis is still an open proposal for future research. 2.1.5. Ethylene During most phases of plant growth, ethylene production is minimal. Ethylene plays a major role in germination by breaking the dormancy of seeds; however, a high level of ethylene concentration inhibits subsequent root elongation. High levels of ethylene may be synthesized as a response to biological or environmental stresses, causing wilting and senescence (Glick et al., 1999). Controlling ethylene levels, often by lowering them, prevents significant economic losses in agriculture. One of the precursors of ethylene synthesis is the enzyme 1 aminocyclopropane 1 carboxylic acid (ACC) deaminase. ACC deaminase is a key enzyme, commonly found in many soil microorganisms and PGPBs and capable of degrading ACC. Thus, lowering ethylene levels in plants can be considered as having potential for promoting growth (Glick et al., 1999). Wild strains of Azospirillum spp. do not have ACC deaminase; nevertheless, some strains can produce eth ylene (Perrig et al., 2007). A single exception to this role is A. lipoferum strain 4B that possesses the ACC deaminase structural (acdS) gene (Prigent Combaret et al., 2008). This gene of the PGPB Enterobacter cloacae UW4 was inserted in A. brasilense Cd and Sp245. Roots of canola and tomato seedlings, plants sensitive to ethylene, were significantly longer in plants inoculated with the A. brasilense transformants than plants inoculated with nontransformed strains of the same bacterium (Holguin and Glick, 2001). In a further study, they speculated that a construct with the ACC deaminase gene under control of a constitutive promoter weaker than the lac promoter, might impose less metabolic load on Azospirillum. The acdS gene was cloned under the control of a tetracycline resistance gene promoter: A. brasilense Cd transformants holding acdS fused to the Tetr gene promoter showed lower ACC deaminase activity than transformants with acdS controlled by the lac promoter. However, acdS controlled by the Tetr gene promoter exerted less metabolic load on A. brasilense Cd transformants than acdS controlled by the lac gene, resulting in increased IAA synthesis, growth rate, and survival of tomato leaf surfaces and ability to promote growth of seedlings (Holguin and Glick, 2003). A proposal that growth promotion triggered by inoculation with A. brasilense involves a signaling pathway that has ethylene as a central, positive regulator was published. The evidence is
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based on higher levels of IAA and ethylene in inoculated plants. Exoge nously supplied ethylene mimicked the effect of inoculation, and the addition of an inhibitor of its synthesis or of its physiological activity completely blocked promotion of growth by A. brasilense (Ribaudo et al., 2006). Taken together, all of this may show that the involvement of ethylene in promoting growth by Azospirillum is probably small.
2.2. Nitrogen fixation Since nitrogen fixation was the original proposed major mechanism by which Azospirillum affected plant growth (Okon et al., 1983), considerable information has been published on this mechanism (for reviews, see Baldani and Baldani, 2005; Bashan and Holguin, 1997; Bashan and Levanony, 1990; Bashan et al., 2004; Choudhury and Kennedy, 2004; Kennedy and Islam, 2001; Kennedy et al., 2004, and references therein). The reason is that, following inoculation, there is a significant increase in the total N in shoots and grains of inoculated plants (Kapulnik et al., 1981 and references in the above reviews). Incorporation of atmospheric nitrogen into the host plant by Azospirillum was evaluated initially by the acetylene reduction assay. However, conclusive proof that plants derive some of their N from the atmosphere came from the use of isotopic 15N2 and 15N dilution techni ques. The original seven species of this genus are diazotrophs (Bashan et al., 2004). Most new species, but not all, are defined as nitrogen fixers, either as free living bacteria or in association with plants and participate in several transformations in the nitrogen cycle (Doroshenko et al., 2007; Eckert et al., 2001; Mehnaz et al., 2007a,b; Peng et al., 2006). Subsequently, a very large volume of information on nitrogen fixation mechanism in the association was published (for a review, see above). Taken together, the evidence collected during the last three decades concerning this mechanism has generated a substantial controversy. On one hand stands the numerous greenhouse and field experiments that repeatedly demon strate some contribution of fixed nitrogen (measured as transfer of 15N2). This was combined with more common observations that inoculation, commonly and significantly, reduced the required doses of nitrogen fertili zation for cultivation of many plant species. Evidence that nitrogen fixation contributes to the N balance of plants is based on the common observation of an increase in nitrogenase activity within inoculated roots, a microbial enzyme that does not exist in plants. This well documented enzymatic activity in Azospirillum is of sufficient magnitude to account for the increase in total N yield of inoculated plants if all the fixed N is incorporated into the plants (Kennedy et al., 1997; for earlier studies Bashan and Holguin, 1997 and references therein). On the other hand, many studies show that the contribution of nitrogen fixation by Azospirillum to the plant is minimal and ranged, at best, from 5% to 18% of the total N increase in the plant. In many
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of those studies, the contribution was smaller than 5% or null. Hence, it is an open debate to this day (Bashan and Holguin, 1997; Bashan and Levanony, 1990; Bashan et al., 2004). These findings almost caused an abandonment of nitrogen fixation aspects of Azospirillum, except for continuing pure genetic studies. Several confirmatory reports about the contribution of fixed nitrogen by Azospirillum to plants, similar in nature to reports of earlier years, illustrate the controversy. The 15N isotope dilution technique indicated that there were significant biological N2 fixation contributions to two genotypes of maize that showed similar increases in grain yield when they were inocu lated with a mixture of Azospirillum strains or fertilized with the equivalent of 100 kg N ha 1. These plant genotypes had a large increase in total N. This suggests that the yield response resulted from increased acquisition of nitrogen, but not from bacterial nitrate reductase (NR); NR mutants generally caused plant responses similar to those of the parent strains (Garcia de Salamone et al., 1997). The ability of the bacteria to transfer fixed nitrogen from the atmosphere to wheat plants was tested using a 15N2 enriched atmosphere. Labeled fixed nitrogen was detected in plant growth media and roots and shoots of wheat grown for 26 days in a 15N2 enriched atmosphere, but the highest levels of 15N were detected in wheat shoots. Ammonia or nitrate supplied to plants did not repress 15N2 fixation (Ruppel and Merbach, 1997). Relationships of 12 A. brasilense strains with roots of a wheat cultivar were studied. They were compared for responses in root colonization, growth stimulation, and nitrogen supply to the plant. All strains colonized the root surface and interior. Most strains stimulated plant growth, but to different degrees. Some strains increased the total nitrogen in roots and leaves up to 80% over noninoculated plants, while others pro duced no effect on nitrogen content. Inoculation of five wheat cultivars with the most efficient strain for nitrogen fixation resulted in increased growth and nitrogen content, but the effects varied among the cultivars. These results suggest that a potential exists for A. brasilense to supply considerable nitrogen to wheat plants, probably dependent on specific bacteria–cultivar interaction (Saubidet and Barneix, 1998). Apparently, dismissal of nitrogen fixation as a possible mechanism for promoting plant growth by Azospirillum in the 1990s was premature and additional greenhouse studies in the last decade showed significant and direct contribution of nitrogen fixation. Measurement of nitrogen fixation after inoculation with A. lipoferum and A. brasilense in rice showed that the N derived from the atmosphere were 20.0% (A. lipoferum) and 19.9% (A. brasilense) in basmati rice and 58.9% (A. lipoferum) and 47.1% (A. brasilense) in super basmati rice (Mirza et al., 2000). Using an in vitro model (A. brasilense and wheat) within 70 h after inoculation, insignificant amounts of newly fixed N were transferred from an ammonia excreting strain of A. brasilense to the shoot tissue of wheat. Adding malate (a preferred
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carbon source for Azospirillum), transfer of nitrogen to the shoots increased 48 fold, which indicates that 20% of nitrogen in the shoot was derived from nitrogen fixation. Apparently, the inability of the host plant to release sufficient carbon into the rhizosphere is a significant constraint on the development of the A. brasilense–wheat association. Perhaps wheat with an increased release of photosynthate to the rhizosphere should be a priority for improving effectiveness of the association (Wood et al., 2001). Inocula tion of strains of A. amazonense on rice increased grain dry matter and nitrogen accumulation at maturation. Contributions from nitrogen fixation were up to 27% of the contribution to the plant. Promotion of growth by A. amazonense for these rice plants was primarily a response to nitrogen fixation (Rodrigues et al., 2008). Finally, winter wheat inoculated with A. brasilense having a point mutation in the ammonium binding site of gluta mine synthetase showed the importance of its nitrogen contribution to the plant. The glutamine synthetase is one of the main ammonium assimilating enzymes; mutations in this enzyme generally result in the release of ammo nium from the bacterium to the environment. The ammonium excreting mutant performed better than the wild type A. brasilense strain for wheat growth parameters and yield (Van Dommelen et al., 2009). An innovative approach to enhance nitrogen fixation to plants by Azospirillum was the creation of a specialized site for nitrogen fixation, a para nodule. This root structure externally resembles a legume nodule and can be induced by adding low concentrations of the auxin herbicide 2,4 D to roots (Tchan et al., 1991). Because Azospirillum does not secrete signifi cant amounts of ammonium and sometimes provides the plant only small amounts of nitrogen, spontaneous mutants of A. brasilense were selected that excrete substantial amounts of NH4þ and the bacteria were established inside para nodules. When plants were grown on a nitrogen free medium, these mutants were responsible for significant increases in organic matter (root and shoot dry matter and total plant nitrogen), compared with plants treated with wild type Azospirillum or plants that were not inoculated. Analysis of 15N2 in these plants showed that the mutants were able to transfer more nitrogen to the host plants than the wild type strain (Christiansen Weniger and van Veen, 1991). Para nodules induced in rice seedlings were the preferential sites for colonization by a NH4þ excreting A. brasilense mutant. Nitrogenase activity in para nodules structures inhabited by bacteria significantly increased, compared with untreated control plants (Christiansen Weniger, 1997). It is probable that within para nodules, bacterial nitrogenase is less sensitive to increased oxygen tension in the roots, as confirmed by Deaker and Kennedy (2001). Host plants benefit from enhanced nitrogen fixation in their roots with para nodules because fixed nitrogen is incorporated into the host plant. Host plants probably stimulate nitrogenase activity of endophytic Azospirillum spp. by providing a carbon source as energy (Christiansen Weniger, 1998).
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These results show that the Gramineae are capable of establishing an association with diazotrophic bacteria in which ammonium excreting bac teria provide the host plants with nitrogen. Para nodule on wheat seedling roots was further developed by the researchers who invented it (Katupitiya et al., 1995b; Sriskandarajah et al., 1993) and specifically and consistently showed that nitrogenase activity in para nodules was higher than in inocu lated roots without para nodules (Tchan et al., 1991; Yu et al., 1993; Zeman et al., 1992). Similar results were obtained with maize (Saikia et al., 2004, 2007). Para nodules add a new dimension to research on biological nitrogen fixation, even if extensive developmental and biochemical modification of the para nodule system is required before effective nitrogen fixation can be achieved. The options are intriguing (Christiansen Weniger, 1994; Kennedy, 1994; Kennedy and Tchan, 1992). In the last decade, perhaps as a response to the controversy mentioned earlier, studies have focused on the nitrogen cycle within cells of bacteria and on many details of molecular mechanisms and the genes involved that proliferate as Azospirillum was developed as a general model to study nitrogen fixation in nonsymbiotic bacteria. This is not a topic of this review (see e.g., Araujo et al., 2004a,b; Huergo et al., 2006a,b, 2009; Klassen et al., 2005). The full genetic sequences of A. brasilense and A. lipoferum have been accomplished and they will be accessible at the Genoscope sites (France) and of A. brasilense at the Oak Ridge National Laboratory site (USA) (I. Kennedy, personal communication). Meanwhile, the complete nucleotide sequence of the A. brasilense fixA, fixB, fixC, and fixX genes were reported, as well as several other genes (Sperotto et al., 2004). Mutants of the common A. brasilense strains Sp7 and Sp245 (defective in flocculation, differentiation into cyst like forms, and colonizing of roots) had a higher nitrogenase expression than wild strains in association with wheat. Appar ently, the ability of Sp7 and Sp245 mutants to remain in vegetative forms (spirillum and rods) improved their ability to express exceptionally high rates of nitrogenase activity. Restoring cyst formation and a normal colo nizing pattern to the spontaneous mutant Sp7S reduced nitrogenase activity to the level of the wild Sp7. This suggests that bacterial cells in the vegeta tive state provides faster metabolism, which directly affects nitrogen fixation (Pereg Gerk et al., 2000). A. brasilense carrying gfp genes expressed pleiotro pic physiological effects caused by disruption of the clpX gene encoding for heat shock protein. One of the consequences of inserting the gfp gene is a threefold increase in nitrogen fixation (Rodriguez et al., 2006). This phe nomenon was confirmed in other A. brasilense strains (de Campos et al., 2006). Apparently, higher expression of the clpX gene may be involved with creation of the Nif phenotype of the A. brasilense mutants by unknown mechanisms (Castellen et al., 2009). Efficiency of nitrogen fixation and denitrification in A. lipoferum can be regulated by varying the concentration
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of oxygen, nitrate, and molybdenum. The maximum growth rate in two strains was observed under microaerobic conditions, minimal nitrate, and the maximum concentration of molybdenum. These conditions were also conducive for obtaining maximum efficiency of denitrification (nitrate reduction to molecular N2; Furina et al., 1999). Microaerobic conditions favor nitrogen fixation. Low dissolved oxygen was also a limiting factor when ammonium concentrations limit growth of A. lipoferum (Tsagou et al., 2003). In A. brasilense, cytochrome c oxidase is required under microaerobic conditions when a high respiration rate is needed. However, under nitro gen fixing conditions, respiration rates do not seem to be a growth limiting factor. Evidence for this was provided when a wild type A. brasilense was compared with a cytN mutant A. brasilense. Under aerobic conditions, growth during the log phase was similar between the two types. Under microaerobic conditions (with NH4þ supplied; no nitrogen fixation), low respiration of A. brasilense cytN decreased its growth rate compared with the growth rate of the wild type A. brasilense. Under nitrogen fixing conditions (without NH4þ supplied), growth and respiration rates of the wild type bacterium were significantly diminished and the differences in growth and respiration rates between the wild and mutant forms were smaller. Yet, the nitrogen fixing capacity of the mutant was still approximately 80% of the wild type (Marchal et al., 1998). Out of 40 thermo tolerant mutants devel oped from a mesophilic A. lipoferum, only 14 could grow and fix nitrogen at 45 C. These mutants excrete ammonia only as very old cultures (maximum production after 12 days under stationary conditions; Steenhoudt et al., 2001). Nitrogen fixation by aerobic bacteria is a very energy demanding process, requiring efficient oxidative phosphorylation, since O2 is toxic to the nitrogenase complex. Azospirillum spp. and other well known nitrogen fixing soil bacteria have evolved a variety of strategies to deal with and overcome the apparent ‘‘O2 paradox.’’ The question is whether the specific environmental adaptations of azospirilla are sufficient to allow optimal proliferation and nitrogen fixation in their natural habitat. Could improving O2 tolerance of the nitrogen fixing process contribute to the development of more efficient strains for inoculation of plants (Marchal and Vanderleyden, 2000)? This remains a future research objective. In evaluating the overwhelming data accumulated over the last 35 years on nitrogen fixation by Azospirillum, ignoring nitrogen fixation as a mechanism for Azospirillum, is premature. In several systems of inoculation, clear demonstration of significant increases of fixed nitrogen for plant growth was demonstrated, while it did not occur in others tests. It is also feasible that in systems where the contribution is small, the quantity of nitrogen provided by the nitrogen fixing process is accumulative, with other mechanisms to produce the final growth promotion effect (see Section 3.6).
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2.3. General improvement of root growth and enhanced uptake of minerals and water Enhanced root systems, including root hairs, are the most common pheno typic phenomena observed following Azospirillum inoculation in most species. Consequently, improved root growth and function leading to improved water and mineral uptake was proposed in the late 1970s. Enhanced mineral uptake was a popular explanation for the inoculation effects in the 1980–1990s (for reviews, see Bashan and Holguin, 1997; Bashan and Levanony, 1990). Increased mineral uptake in plants has been suggested due to a general increase in volume of the root system and not to any specific metabolic enhancement of the normal ion uptake mechanism (Morgenstern and Okon, 1987; Murty and Ladha, 1988) and that this is related to secretion of phytohormones by the bacteria. Other studies suggested a more active involvement in acquisition of minerals. Inoculation may promote availabil ity of ions in the soil by helping the plant scavenge limiting nutrients (Lin et al., 1983), which may explain the common accumulation of N com pounds in the plant without any apparent N2 fixation. Thus, the plant may absorb N more efficiently from the limited supply in the soil, resulting in a less N fertilization to attain a desired yield. By volume of information this is one of the largest parts of the Azospirillum literature, although the physio logical, biochemical, and molecular details were left unsearched and only analyses of specific variables was presented. As a result, the available infor mation about this mechanism is largely descriptive. Several examples, out of many, illustrate the mechanism. In hydroponic systems in greenhouses, inoculation with A. brasilense increased the number and length of adventitious roots of Sorghum bicolor by 33–40% over non inoculated controls, such as a higher rate of growth, earlier root appearance, and a greater elongation rate of individual roots (Sarig et al., 1992). In addition to increasing (Kapulnik et al., 1981, 1985b) or decreasing (Kucey, 1988) many root parameters, inoculation affected many foliage parameters. These changes were directly attributed to positive bacterial effects on mineral uptake by the plant. Enhancement in uptake of NO3 , NH4þ, PO42 Kþ, Rbþ, and Fe2þ and several micronutrients by Azospirillum (Barton et al., 1986; Jain and Patriquin, 1984; Kapulnik et al., 1985a; Lin et al., 1983; Morgenstern and Okon, 1987; Murty and Ladha, 1988; Sarig et al., 1988) was proposed to cause an increase in foliar dry matter and accumulation of minerals in stems and leaves. During the reproductive period, these minerals could have been transferred to the panicles and spikes and result in higher yield and higher mineral content (Ogut and Er, 2006). Supporting evidence for increased mineral uptake by inoculated roots is provided by enhancement in proton efflux activity of wheat roots inocu lated with Azospirillum (Bashan, 1990; Bashan et al., 1989a). It is well known
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that proton efflux activity is directly related to the balance of ions in plant roots (described below). Although some studies showed accumulation of N and minerals in the inoculated plants, others showed that enhanced growth of wheat and soybeans was not necessarily because of a general enhancement of mineral uptake (Bashan et al., 1990). In addition to improved mineral uptake, inoculation improved water status in stressed sorghum plants. Inoculated plants were less stressed, having more water in their foliage, higher leaf water potential, and lower canopy temperature than noninoculated plants. Soil moisture extraction by Azospirillum inoculated plants was greater and water was extracted from deeper layers in the soil. Therefore, increased sorghum yield was primarily attrib uted to improved utilization of soil moisture (Sarig et al., 1988; see Section 2.5 for more details.) It is likely that improved mineral and water uptake occur in the Azospirillum–plant association. However, the descriptive data presented so far have not shown whether these improvements are the cause or the result of other mechanisms, such as changes in the balance of plant hormones or enhanced proton extrusion. Furthermore, the wide range of enzymatic activities related to these phenomena were poorly studied and no apparent evaluation of Azospirillum mutants deficient in induction of mineral and water uptake by plants has been made. Finally, it should be noted that very few strains have been studied and it is doubtful if all Azospirillum strains possess these abilities. There is evidence that some strains of A. brasilense failed to improve uptake of several ions, but nevertheless improved plant growth (Bashan et al., 1990).
2.4. Phosphate solubilization and mobilization and rock weathering Despite the reservations listed above, improved mineral uptake by plants was suggested as a major contribution of Azospirillum inoculation, therefore, azospirilla weathering of minerals in general and phosphorus in particular were studied. This has received attention because of the related larger field of phosphate solubilization that involves other bacterial genera. A. halopraeferens, a bacterium that does not use glucose, and consequently does not produce acid, can solubilize insoluble inorganic phosphate in vitro by unknown mechanisms (Seshadri et al., 2000). Two strains of A. brasilense and one strain of A. lipoferum were capable of producing gluconic acid, thereby leading to solubilization of insoluble phosphate in rocks (Puente et al., 2004a; Rodriguez et al., 2004). Sugars, like glucose, are part of the root exudates of pea plants grown in P deficient substrates and enhanced the capacity of Azospirillum spp. to solubilize normally insoluble Ca3(PO4)2. The relative proportion of glucose in pea exudates decreased under P deficiency, while the content of galactose, ribose, xylose, and fucose increased. Azospirillum spp. can metabolize all these sugars. Therefore, the shift in sugars under
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P deficiency increased the capability of Azospirillum spp. to mobilize phos phate (Deubel et al., 2000). Similarly, inoculation of cardon (a giant cactus) with A. brasilense Cd enhanced phosphate solubilization and enhanced plant growth (Carrillo et al., 2002). These observations can partly be explained by acidification of the nutri ent medium by protons and organic acids. Azospirillum spp. can produce different organic acids that assist in P solubilization, depending on the sugar in the root exudates. Yet, Azospirillum can solubilize P by itself without adding root exudates. For example, three Azospirillum strains were isolated from the ectomycorrhizal sporocarps (Rhizopogon vinicolor) that colonized Douglas fir trees. In vitro, they were able to degrade limestone, marble, and calcium phosphate (Chang and Li, 1998). These observations were con firmed using other strains of Azospirillum (Puente et al., 2004a,b, 2006). Uptake by A. brasilense cells of the essential elements Mg, Ca, Mn, and Fe and trace elements V, Co, Ni, Cu, Zn, and Pb (which do not essentially suppress growth of bacterial cultures) present in weathered rock fragments and are accumulated by the cells was shown. Zn and Cu were accumulated in the bacterial biomass in relatively significant amounts, but uptake of Co and Ni was much less, and Pb and V were apparently not assimilated by azospirilla. In particular, Cu cations were effectively absorbed by the bacte rium and this increased the rate of uptake of other metals; however, the process takes time. Short exposures have only a limited effect on absorption of Cu (Ignatov et al., 2001; Kamnev et al., 1997a). Additionally, these bacteria are capable of producing structural modifications of the magne sium ammonium orthophosphate molecule when added to the medium (Kamnev et al., 1999a). Fourier transform infrared spectroscopy is a power ful tool for nondestructive identification and characterization of cell com ponents; it was applied to studies of molecular structures in A. brasilense, its essential element content (Kamnev et al., 1997b, 2001), heavy metal induced metabolic changes in the cells (Kamnev et al., 2002), and mem brane composition and structure (Kamnev et al., 1999b). These capabilities notwithstanding, it has not been demonstrated so far that these elements, obtained from the environment, were transferred to the plant. The research field of mineral solubilization and mobilization in Azospirillum is potentially useful for studying interactions and survival of the bacteria in the soil. Although the literature treated this proposal as an individual entity, it should be considered as a subfield of enhanced mineral uptake mentioned earlier.
2.5. Mitigation of stresses From the earliest field experiments with Azospirillum in the 1980s, the best effects on plant growth and yield were obtained when the growth conditions were suboptimal. A common explanation for the effects of Azospirillum on
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plant growth was reduction in environmental stresses by the bacteria, providing the plant a more favorable environment to grow in an otherwise limiting environment. Sometimes inoculation permits plant growth in soils that normally did not allow growth. None of these theories can explain enhanced growth of inoculated plants under favorable plant growth condi tions that also occurred and were regularly reported. Environmental stressors varied and included mitigation of drought (Sarig et al., 1990), salinity (Creus et al., 1997), heavy metals (Belimov and Dietz, 2000), toxicity of other substances (de Bashan and Bashan, 2008), extreme pH (de Bashan et al., 2005), toxic humic substances (Bacilio et al., 2003), and suboptimal levels of nitrogen (discussed earlier). 2.5.1. Salinity stress Numerous cultivated soils worldwide are becoming more saline, mainly from the use of marginal irrigation water, from excess fertilization, and various desertification processes. Inoculation with Azospirillum sp. under saline stress conditions is therefore commonplace. Prior findings (for a review, see Bashan and Holguin, 1997) showed that common agricultural Azospirillum strains tolerated high salinity (2%). Salt resistance among species increased from A. amazonense (lowest) to A. halopraeferans (highest), the latter tolerating over 3% NaCl (seawater salinity). Azospirillum inoculation of maize at NaCl concentrations up to –1.2 MPa significantly increased chlorophyll, K, Ca, soluble saccharides, and protein contents, compared with control maize growing without NaCl (Hamdia and El Komy, 1997). Alleviation of salt stress in maize involved several changes that probably were related to different operating mechan isms: proline concentration declined significantly, the concentration of most amino acids increased on exposure to NaCl, as well as when inoculated with Azospirillum. Azospirillum apparently restricted Naþ uptake and enhanced the uptake of Kþ and Ca2þ. Finally, inoculation stimulated nitrate reductase and nitrogenase activity in shoots and roots (Hamdia et al., 2004). Inoculat ing wheat seedlings with A. brasilense exposed to severe salt (NaCl) or osmotic (polyethylene glycol) stress significantly reversed part of the nega tive effects; both stresses reduced the relative elongation rate of shoots. Fresh weight, fresh weight/dry weight ratio, water content, and relative water content were higher in shoots from inoculated plants than in stressed controls (Creus et al., 1997). Similarly, under high NaCl concentration, inoculation of wheat with A. lipoferum reduced some of the deleterious effects of NaCl (Bacilio et al., 2004). Finally, Azospirillum inoculated lettuce seeds had better germination and vegetative growth than noninoculated controls after being exposed to NaCl (Barassi et al., 2006). The most fundamental omissions in current knowledge are (1) uncer tainty about whether improved salt tolerance of the bacterium is needed to enhance the bacterium’s effect on plants or if existing salt tolerance in plants
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is adequate to ensure positive growth promotion by inoculation; (2) what are the mechanisms that are triggered and are responsible for enhanced saline resistance after inoculation; and (3) what is the microbial mechanism that provides resistance in plants. 2.5.2. Water stress Apparently, inoculation with Azospirillum improved growth under water stress conditions as was initially demonstrated in the 1980s (for a review, see Bashan and Levanony, 1990). Subjecting inoculated S. bicolor plants to osmotic stress in hydroponic systems diminished the adverse effects caused by osmotic stress, such as reduction of leaf senescence (Sarig et al., 1990). Coleoptile height and fresh and dry weight of wheat seedlings inoculated with A. brasilense Sp245 were enhanced, despite the water stress (Alvarez et al., 1996). Inoculation with Azospirillum alleviated the stress on wheat plants grown under drought conditions (El Komy et al., 2003). Turgor pressure at low water potential was higher in inoculated seedlings in two wheat cultivars under osmotic stress. This could result from better water uptake as a response to inoculation that, in turn, is reflected by faster shoot growth in inoculated seedlings exposed to these stresses. They showed better water status and effects on cell wall elasticity or apoplastic water (Creus et al., 1998). To assess the contribution of A. brasilense Sp245 during drought when flowers open (anthesis), inoculated wheat seeds were sub jected to drought. Even though all the plants underwent osmotic stress, significantly higher water content, relative water content, water potential, apoplastic water fraction, and lower cell wall modulus of elasticity values were obtained in inoculated plants. Grain yield loss to drought in inoculated plants was significantly reduced and significantly higher Mg, K, and Ca in grains were detected. Probably, inoculation improved water status and an additional ‘‘elastic adjustment’’ in plants (Creus et al., 2004). Recently, inoculation with A. brasilense contributed to protection of wheat seedlings under water stress through changes in the fatty acid distribution profiles of phosphatidylcholine and phosphatidylethanolamine, major root phospholi pids (Pereyra et al., 2006). Transformed A. brasilense that could produce trehalose, an osmotic regulating sugar, was more salt resistant than the wild type and significantly enhanced the survival of maize growing under drought stress. It also significantly increased biomass and leaf and root length of the plants (Rodrı´guez Salazar et al., 2009). The limitations in our know ledge regarding the effect of inoculation under saline stress are valid for osmotic stress, as well. 2.5.3. Herbicides Cotton plants could be partly protected from harmful effects of the herbi cide 2,4 D by inoculation with A. brasilense. The degrading plasmid of 2,4 D was transferred into A. brasilense Sp7. Trans conjugants degraded
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2,4 D in pure culture via cometabolism. However, when the trans conjugants were inoculated on cotton seeds, the plants were resistant only to low levels of the herbicide, which is not sufficient for protection of cotton. Plants growing in soils with this concentration of herbicide and inoculated with wild type strains died (Feng and Kennedy, 1997). 2.5.4. Toxic metals Another possible mechanism for producing a healthier plant is reduction of metal toxicity in contaminated soils and mine tailings that, under normal conditions, almost completely inhibits plant growth. Although the bacte rium tolerate only moderate levels of metals and other toxic compounds (see previous reviews Bashan and Holguin, 1997; Bashan and Levanony, 1990; Bashan et al., 2004; also Kamnev et al., 2005, 2007), it apparently contributed mechanisms allowing plants to grow in mine tailings or con taminated soils. Cadmium causes severe inhibition of growth and nutrient uptake in barley. In the presence of CdCl2, inoculation with A. lipoferum partly decreased Cd toxicity, possibly through the improvement of mineral uptake. Additionally, inoculation slightly enhanced root length and biomass of barley seedling treated with Cd and the amount of nutrients absorbed by the inoculated plants increased significantly. There was only some protec tion against Cd toxicity, but no uptake of Cd, since Cd content in the inoculated plants was unchanged (Belimov and Dietz, 2000; Belimov et al., 2004). A. brasilense Sp245 associated with wheat changes the speciation, bioavailability, and plant uptake of arsenic. Plants inoculated with Azospirillum accumulated less arsenic than did uninoculated plants (Lyubun et al., 2006). Inoculation of the wild desert shrub quailbush (Atriplex lentiformis) growing in extremely stressed environment with A. brasilense strains Sp6 and Cd, such as acidic mine tailings having high metal content, resulted in a significant increase in production of plant biomass (L.E. de Bashan et al., unpublished data). Similar results were obtained when wild yellow palo verde desert trees (Parkinsonia microphylla) were inoculated with A. brasilense Cd in rock phosphate tailings (Bashan et al., unpublished data). 2.5.5. Compost and humic substances Some compost may be toxic to plants because of elevated humic acids or inappropriate preparation. Inoculation of wheat seeds with A. brasilense or A. lipoferum prior to sowing in soil that was amended with two types of compost improved seed germination and plant development. The bacteria possibly changed or consumed the humic acids because both bacterial species can survive and grow in high humic acid solution as the sole source of carbon; thus, modify the composition of the compost during in vitro tests (Bacilio et al., 2003).
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2.5.6. pH and toxic substances in aquatic environments Apart from terrestrial applications, Azospirillum is being used as an inoculant in aquatic environments mainly to promote the growth and metabolism of microalgae of the genus Chlorella that is used in wastewater treatment (de Bashan et al., 2004; Gonzalez and Bashan, 2000; Hernandez et al., 2006). Under aquatic conditions, the pH, available dissolved nutrients, and toxic molecules to the microalgae have significant impact on the process of mass production. High pH of the medium interferes with the microalgal cell cycle and decreases microalgal population. Coculturing of the micro algae with A. brasilense eliminated this negative effect (de Bashan et al., 2005). Similarly, high levels of the amino acid tryptophan reduced multi plication of C. vulgaris where coculturing with A. brasilense significantly reduced the inhibition probably by converting it to IAA that enhances the growth of the microalgae (de Bashan and Bashan, 2008). 2.5.7. Protection from relative high light intensities Inoculation of plants sometimes occurs under light intensity that is stressful and has an inhibiting effect on specific crops. Inoculation of wheat seedlings with A. brasilense Cd significantly increased the quantity of the photosyn thetic pigments chlorophyll a and b, but also the auxiliary photoprotective pigments violaxanthin, zeaxanthin, antheroxanthin, lutein, neoxanthin, and b carotene that help the plant to sustain photosynthesis under unfavorable light conditions. This outcome yielded greener plants with no apparent visible stress. The greatest difference in the quantity of all pigments between inoculated and noninoculated plants occurred in the first week of growth (Bashan et al., 2006). Similarly, although the microalgae C. sorokiniana is capable of growing at high light intensities, coculturing with A. brasilense enhanced this capacity and the microalgae could tolerate extreme light intensities as high as 2500 mmol m 2 s 1 (de Bashan et al., 2008b). Taking all these phenomena together, it appears that a multitude and remotely related or unrelated mechanisms are operating in these complex interactions of Azospirillum with plants. All these accumulating findings yielded a recent proposal to include Azospirillum in the group of other rhizosphere PGPB that regulated homeostasis of plants under conditions of abiotic stress. This group was designated ‘‘Plant Stress Homeo regulat ing Bacteria’’ (PSHB; Cassan et al., 2009b; Sgroy et al., 2009). These types of bacteria, Azospirillum included, may use an assortment of mechanisms, such as biosynthesis of phytohormones, growth regulators, osmoregulator molecules, expression of specific regulatory and metabolic enzymes, and immobilization or catabolism of various toxic molecules for plants to assist plant growth. This proposal forms a part of the initial theory of Section 3.6.
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3. Other Proposed Mechanisms 3.1. Biological control Azospirillum is not yet known as a typical biocontrol agent of soil borne plant pathogens because many strains lack direct suppressive chemicals or hydrolytic enzymes likely to affect plant pathogens. However, reports are accumulating that this mechanism has been overlooked. Some possible mechanisms used by Azospirillum to reduce damage from pathogens have been demonstrated as environmental competition and displacement of pathogens, inhibition of seed germination of parasitic weeds, general enhancement of plants to resist patho gen infection, and possible inhibition of fungal growth via production (at least in vitro) of microbial toxic substances. 3.1.1. Toxic substances When iron was withheld, A. lipoferum strain M produced catechol type side rophores under iron starvation that exhibited antimicrobial activity against various bacterial and fungal isolates (Shah et al., 1992). Although some strains from Brazil produce cyanide (HCN) in vitro (Gonc¸alves and de Oliveira, 1998), this feature is uncommon in strains from other geographic locations. Some Azospirillum isolates produced bacteriocins that inhibited growth of several indicator bacteria (Tapia Hernandez et al., 1990). An antimicrobial auxin like molecule, phenylacetic acid was isolated from an A. brasilense culture (Somers et al., 2005). A. brasilense cells contain a low molecular weight compound that inhibits germination and growth of the radicle of Egyptian broomrape seeds (Orobanche aegyptiaca), a specific weed parasite of sunflower (Dadon et al., 2004). Azospirillum spp. inhibited germination of the parasitic striga weed (witchweed) seeds (Striga hermonthica) that infest fields of tropical sorghum, thereby promoting growth of sorghum (Bouillant et al., 1997). Azospirillum cells suspended in a synthetic germination stimulant did not inhibit germination of striga weed seeds, but blocked radicle elongation. These radicles had abnormal morphology and contained no vacuolated cells in the root elongation zone. Lipophilic compounds extracted from the medium of bacteria prevented germination of striga seeds (Miche´ et al., 2000). So far, Azospirillum has not been reported to induce any negative effect on healthy plants (Bashan, 1998). If this is the case, these toxic compounds are either in vitro artifacts or are induced only in the presence of pathogens. 3.1.2. Competition The effect of A. brasilense on crown gall formation in Dicotyledoneae was studied after inoculation with virulent strains of Agrobacterium tumefaciens. When wounded tissues of grapevines and carrot disks were inoculated with live cells of A. brasilense strains 94 3 or Sp7, development of the typical
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bacterial galls was inhibited and the protective effect of Azospirillum lasted over a 24 h period (Bakanchikova et al., 1993). When A. brasilense Cd was added to a culture with the pathogenic mangrove rhizosphere bacterium Staphyloccus spp., the population of the latter was significantly reduced (Holguin and Bashan, 1996). To assess displacement of pathogens by inoculation with Azospirillum, the tomato leaf pathogen Pseudomonas syringae pv. tomato (PST, bacterial speck) and A. brasilense were inoculated onto tomato plants, as a mixed culture or consecutively. Inoculation of seeds with a mixed culture resulted in reduction of the pathogenic population in the rhizosphere, increased the population of A. brasilense, prevented development of PST, and improved plant growth. PST did not survive in the rhizosphere in the presence of A. brasilense. Inoculation of leaves with the mixed bacterial culture under mist conditions significantly reduced the population of PST and signifi cantly decreased the severity of the disease. Challenge with PST after A. brasilense was established in the leaves further reduced PST and severity of the disease and significantly enhanced plant development. Selective enhancement of the population of A. brasilense on leaves occurred by applying malic acid (favorable for A. brasilense, but not for PST), decreased PST to almost undetectable levels, almost eliminated disease development, and improved plant growth to the level of uninoculated healthy controls (Bashan and de Bashan, 2002a). Seeds inoculated with A. brasilense Sp7 and later challenged by two foliar bacterial pathogens of tomato (Clavibacter michiganensis spp. michiganensis [bacterial canker] and Xanthomonas campestris pv. vesicatoria [XCV, bacterial spot]) delayed leaf and plant death compared with untreated controls, but canker severity was not affected. Unfortu nately, inoculation with Azospirillum increased the severity of XCV on cherry tomatos (Romero et al., 2003). Several isolated bacterial strains showed antagonism toward the fungus Aspergillus flavus that produces afla toxin (the most potent carcinogenic mycotoxin produced by some fungi), and were capable of degrading the toxin in vitro. Since identification of the microorganism was based on morphological characteristics, it is uncertain whether the identification of the strains as Azospirillum is valid (Cho et al., 2000). A strain of A. brasilense with increased capacity for N2 fixation was tested in vitro against the soil borne plant pathogens, Fusarium oxysporum f. sp. lycopersici, Rhizoctonia solani, and Pythium sp. that infect cucumbers. The bacteria reduced the dry weight of Fusarium mycelium by 90–96%, of Rhizoctonia by 72–94%, of Pythium by 71–95%, and completely eliminated Sclerotinia mycelium (Hassouna et al., 1998). 3.1.3. Production of a ‘‘healthier plant’’ by unknown mechanisms Many examples of possible ‘‘biological control’’ are reported without spe cifying the mechanisms. It is assumed that inoculation produce healthier plants by deterring pathogenic infections (Tilak et al., 2005). This is a
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possibility especially when the effect recorded is against microfauna and insects and not against microorganisms, as is expected. For example, inoculation with A. lipoferum of mung bean (Vigna radiata) infected with root knot nematode (Meloidogyne incognita) led to fewer root galls and egg masses per root system. After inoculation with A. lipoferum, plants infected with the nematode had significantly greater growth and biomass, probably related to a greater number of functional nodules on roots that had been infected (Khan and Kounsar, 2000). When inoculated with A. brasilense, okra (Abelmoschus esculentus) showed enhanced plant characteristics and pod yield. At the same time, there was a significant reduction in root knot nematodes egg masses, eggs per egg mass, and total nematode population (Ramakrishnan et al., 1997). Similar results in sun flower were obtained with a commercial inoculant of A. brasilense (Ismail and Hasabo, 2000). Maize that was inoculated with a combination of mycorrhizal fungi, Glomus fasciculatum, Azospirillum sp., and phosphate solubilizing bacteria reduced the population of the Pratylenchus zeae nema tode and induced very high cob yield (Babu et al., 1998). When A. lipoferum was inoculated onto wheat plants, it reduced Heterodera avenae nematode infection (Bansal et al., 1999). Inoculation of sorghum with A. brasilense to control the sorghum shoot fly Atherigona soccata that causes dead heart in sorghum resulted in a 10 fold reduction of the disease and increased grain yield (Kishore, 1998). A. brasilense was applied as a foliar spray against foliar fungal and bacterial diseases of mulberry, such as powdery mildew caused by Phyllactinia corylea, black leaf spot caused by Pseudocercospora mori, black leaf rust caused by Cerotelium fici, and bacterial leaf blight caused by P. mori. Inoculation reduced fungal pathogens and excelled as a treatment against bacterial blight (Sudhakar et al., 2000). The addition of Rhizobium, Azospirillum, or Azotobacter inocula as a combined seed and soil treatment in cultivation of pearl millet (Pennisetum glaucum) reduced downy mildew (Sclerospora graminicola) in the leaves (Gupta and Singh, 1999). Inoculation with arbuscular mycor rhizal (AM) fungi and Azospirillum spp. suppressed damping off disease in chili (Capsicum sp.) caused by Pythium aphanidermatum (Kavitha et al., 2003). Combinations of several ineffective management tactics (spraying Cu and streptomycin combined with Azospirillum seed inoculation and seed disin fections, individually ineffective against PST, significantly reduced occur rence and severity caused by PST and also improved plant growth. Additionally, the combined treatment significantly reduced the amount of chemical pesticides required to protect tomato plants from PST (Bashan and de Bashan, 2002b). The mechanisms by which this happens in all the described cases remain unknown. So far, Azospirillum is not commonly reported to induce systemic resis tance in plants. However, inoculation of rice plant with the endophyte Azospirillum sp. B510 induced disease resistance against diseases caused by
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the virulent rice blast fungus Magnaporthe oryzae and bacterial pathogen Xanthomonas oryzae, apparently by activating a novel type of resistance mechanism independent of salicylic acid mediated defense that does not signal accumulation or expression of pathogenesis related genes (Yasuda et al., 2009). At this time, these reports do not provide conclusive evidence that Azospirillum is a true biological control agent, although significant biological control activity can be attributed to this genus.
3.2. Nitric oxide Nitric oxide (NO) is a volatile, lipophilic free radical which participates in metabolic, signaling, defense, and developmental pathways in plants (Cohen et al., 2010; Lamattina and Polacco, 2007; Lamattina et al., 2003). As its major role, NO participates in the IAA signaling pathways. This participation leads to lateral and adventitious root formation where the exact role of NO is as an intermediary in IAA induced root development (Correa Aragunde et al., 2004, 2006; Pagnussat et al., 2002, 2003). One wild type A. brasilense Sp245 can produce NO in vitro, under anoxic and oxic (or aerobic) conditions (Creus et al., 2005). The latter can be achieved by possible different pathways, such as aerobic denitrification and heterotrophic nitrification. NO is produced during the middle and late logarithmic phases of growth (Molina Favero et al., 2007, 2008). An NO dependent promoting activity in A. brasilense Sp245 induces morphological changes in tomato roots regardless of the full bacterial capacity for IAA synthesis. An IAA attenuated mutant of this strain, producing up to 10% of the IAA level compared with the wild type strain (Dobbelaere et al., 1999) had the same physiological characteristics and slightly less effect on root development. When the NO was removed, using a chemical NO scaven ger, both types of root formation were inhibited. This demonstrates that NO mediated Azospirillum induced branching of roots. These results pro vide further evidence of an NO dependent promoting activity of tomato root branching, regardless of the bacterium’s capacity for synthesizing IAA (Molina Favero et al., 2008), a phenomenon that occurs in other inocula tion systems lacking IAA activity (see above). It is commonly argued that denitrification in agriculture is considered, in general, and specifically in plant inoculations, as an undesirable feature of PGPB because it reduces availability of N (Zimmer et al., 1984) for the plant. Yet, the capacity of A. brasilense to reduce nitrate aerobically to NO, which in turn, could promote growth of tomato roots is a point for reconsideration. Several studies demonstrate the continuous relation between NO and IAA on root development (Huang et al., 2007; Lombardo et al., 2006; Tewari et al., 2007). It is possible that a connection, not proven so far, exists in Azospirillum–plant systems. However, the way that IAA and NO
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are acting together, if acting, on plant cells triggering the branching of roots is still an open question for research. Nonetheless, the relationship between NO and A. brasilense showed that, in addition to the well established connection between NO production and defense responses to pathogenic microorganisms (Modolo et al., 2005; Zeidler et al., 2004), it seems that NO metabolism also plays a role in the positive close association of PGPB with roots.
3.3. Nitrite Nitrite (NO2 ), either directly added or excreted by A. brasilense during nitrate respiration may participate in growth promotion effects. It causes a sharp increase in the formation of lateral roots (Zimmer et al., 1988). Nitrite is produced under anaerobic or microaerobic conditions by the dissimila tory nitrate reduction pathway, in addition to NO and nitrous oxide (N2O; Hartmann and Zimmer, 1994). Nitrite could have promoting effects when reacting with ascorbate (Bothe et al., 1992; Zimmer et al., 1988). This avenue has not been investigated further.
3.4. Signal molecules and enhanced proton extrusion from roots Whatever the operating mechanism, Azospirillum affects plant cell metabo lism from outside the cell (without entering the intact plant cells) and this suggests that these bacteria are capable of excreting and transmitting a signal (s) that crosses the plant cell wall and is recognized by the plant membranes. This interaction can initiate a chain of events resulting in altered metabolism of the inoculated plant and proliferation of roots. Since plant membranes are extremely sensitive to any change, their response may serve as a precise indicator of Azospirillum activity at the cellular level. Improving plant growth by affecting proton and organic acid extrusion (proton pump) mechanisms in plants by inoculation with Azospirillum spp. was proposed two decades ago. A proton pump is an integral membrane protein that is capable of moving protons (Hþ) across the membrane of a cell, mitochondrion, or other subcellular compartment. In cell respiration, the pumps move protons from the space enclosed by the two membranes within the organelle and release the protons into the intermembrane space. The confined protons create a gradient in both pH and electrical charge across the plasma mem brane that acts as a reservoir of stored energy for the cell. For plants to react to their constantly changing environments and simultaneously maintain optimal metabolic conditions, the expression, activity, and interplay of the pumps generating these Hþ gradients have to be tightly regulated (Gaxiola et al., 2007; Schumacher, 2006). Additional functions, such as opening and
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closing of stomata, cell growth, and intracellular pH homeostasis, have been proposed (Duby and Boutry, 2009). Short exposure of wheat roots to live A. brasilense Cd significantly enhanced the proton efflux of the root at 5 h after inoculation. Bacteria in the logarithmic phase are required for this enhancement, which is a triggering nature (Bashan, 1990; Bashan et al., 1989a). Inoculation of soybean seedlings with the same Azospirillum strain significantly reduced the membrane potential in every root part and this was greatest in the root elongation zone (Bashan, 1991; Bashan and Levanony, 1991). Inoculation of soybeans and cowpeas with this strain increased proton efflux from their roots and changed the phospholipid content in membranes of cowpeas (Bashan et al., 1992). Although the nature of the released signal molecule is still unknown, Azospirillum probably targets plant membranes on plant roots. This phenomenon also occurs in cardon cactus. Lowering the pH of the rhizosphere increases the availability of phosphorus and iron to plants, especially in arid lands with high calcium content and soil pH (Carrillo et al., 2002). A confirmatory study of the proton extrusion phenomenon in wheat showed that inoculation enhanced proton efflux and elongation of the roots. Although the evidence is circumstantial, perhaps these two phenomena are related. This effect was directly dependent on the bacterial strain–plant combination, suggesting that compatible strains are necessary to induce this activity (Amooaghaie et al., 2002). This kind of investigation has not been pursued in recent years. It is possible that a receptor in A. brasilense is involved in the binding of wheat germ agglutinin (WGA; one of the most studied plant lectins; Antonyuk et al., 1993). This binding induced changes in the cellular metabolism of A. brasilense Sp245 and promoted nitrogen fixation, excre tion of ammonium ions, and synthesis of IAA (Antonyuk and Evseeva, 2006; Antonyuk et al., 1993, 1995). WGA changed the relative proportion of acidic phospholipids of the membrane. It is possible that acidic phospho lipids participate in trans membrane communication. WGA may function as a signal molecule in the Azospirillum–plant association (Antonyuk et al., 1995). Some Azospirillum strains are known to produce several lectins in vitro (Castellanos et al., 1998). Two cell surface lectins isolated from A. brasilense Sp7 and from a mutant (defective in hem agglutinating activity), A. brasilense Sp7.2.3, affected activities of a glucosidase, b glucosidase, and b galactosidase in the membrane and apoplast fractions of roots of wheat seedlings (Alen’kina et al., 2006). Other lectins induced changes in the mitotic state of growing onion plant cells (Nikitina et al., 2004). In general, effects on proton extrusion merit further investigation because the changes in the metabolism of the roots may induce enhanced mineral and water uptake even without proliferation of roots that are induced by phytohormones. This may provide further support to the theory of enhanced mineral uptake in cases when hormonal activity is not detected.
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3.5. Azospirillum nitrate reductase An alternative to nitrogen fixation as an explanation for N accumulation after inoculation of wheat plants by Azospirillum is the bacterial NR theory. NR activity in wheat leaves was decreased by inoculation with some Azospirillum strains. Inoculation with NR mutants resulted in a small response, concomitant with an increase in leaf NR, compared with inocu lation with the parental NRþ strain (Ferreira et al., 1987). Inoculation of field grown plants with A. brasilense Sp245 and its NR mutant confirmed that the mutant was significantly less effective in increasing yield than the parental strain (Boddey and Do¨bereiner, 1988). This phenomenon indicates that the effect of some Azospirillum strains on wheat plants is not solely via nitrogen fixation (both the parental and the mutant strains have this ability), but rather results from an increase in assimilating nitrate. The parental strain aided reduction of nitrate in the roots and thus decreased translocation of nitrate to the leaves, while inoculation with the NR mutant caused direct translocation and reduction of nitrate in the foliage. This theory might explain, in part, the observation of increased N accumulation in shoots because the unaffected ability to fix nitrogen may also contribute N to the plants in addition to NR activity. It also might be a part of a larger theory of enhanced mineral uptake by Azospirillum inoculation (described earlier). This line of research has not been pursued further.
3.6. Additive hypothesis Several recent studies on modes of action in Azospirillum gave new momen tum to the additive hypothesis that was suggested 20 years ago. The hypothesis considers multiple mechanisms rather than one mechanism participating in the association of Azospirillum with plants. These mechan isms operate simultaneously or in succession, the contribution of an indi vidual mechanism being less significant when evaluated separately. The sum of activities under appropriate environmental conditions results in the observed changes in plant growth (Bashan and Levanony, 1990). For example are the cases where nitrogen fixation contributes less than 5% of the observed effect of Azospirillum on the plant. As such low levels, it is not sufficient and does not fully explain increases in yield. When combined with other small mechanisms, this may be a significant contribution. With a general mechanism unknown, or more likely, does not exist after 30 years of intensive research, it would be more practical to look at the effects of Azospirillum spp. on the whole plant as an outcome of multiple mechanisms rather than a single mechanism operating at the organ, tissue, cellular, or molecular levels. Support for this notion is provided by an analysis of literature of many of the known cases of the effect of inoculation on the root to shoot (S/R) ratio that shows that the general effect of Azospirillum
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spp. on the entire plant was largely overlooked. From the changes the bacteria produce in the S/R ratio, it appears that it also participates in the partitioning of carbon compounds within the plant, a phenomenon that is well recognized as multiparametric. The analysis provides supportive exper imental data (although collected from many diverse studies) that indicate that the mode of action of Azospirillum spp. is probably composed of multiple mechanisms (Bashan and Dubrovsky, 1996). Additional supportive experimental data are provided by recent studies on polyamines (Cassan et al., 2009a) and nitrogen fixation (Van Dommelen et al., 2009) that were presented earlier.
4. Concluding Remarks and a Proposal Today, the prevailing explanation for the effect of Azospirillum on plants is the production of an assortment of phytohormones, mainly IAA, altering the metabolism and morphology of the roots, yielding better mineral and water absorption, hence, higher yields. The contribution of nitrogen fixation is more controversial and, despite the increasing large volume of literature on other possible mechanisms, these are largely ignored by reviews on the topic of plant growth promotion, mostly evaluating PGPB in general. In a comprehensive analysis of the knowledge about physiology, metabolic pathways, and molecular biology mechanisms of Azospirillum and their possi ble mode of action, it is apparent that phytohormones, especially IAA working in synchronization with other phytohormones produced by the bacterium, play a major role in various aspects of metabolism for growth. However, to attribute extremely complex phenomena for nonspecific causes of growth promotion in numerous plant species inoculated with many strains of Azospirillum having great differences in physiological traits, to one or a few substance (s) produced in abundance, mainly in vitro, is an oversimplification. Yet, it is, useful research tool for probing the mode of action of these bacteria. There was, and still is, a disproportion between the large amount of knowledge on the bacterium cell and less knowledge about its interaction with the plants. In many aspects of interaction, such as mitigation of stresses or biological control, our knowledge about the mode of action is close to nil. Unfortunately but frequently, the knowledge about bacterial metabo lisms per se is extrapolated to explain possible effects on plants without providing solid evidence that such activity do exist in planta. Mutants that are defective in several traits are used in this field of research, but are employed on a smaller scale than in the related fields such as biological control of plant pathogens. For a more accurate determi nation of the role of phytohormones in promoting growth in general, and
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IAA in particular, there is a need to obtain a mutant that is totally deficient in IAA production, but otherwise identical to the parent strain. Although several IAA attenuated mutants were constructed, this goal has not yet been achieved. The same is true for other phytohormones. Additionally, to clearly state whether hormones are the main mechanism for promoting growth, we need to demonstrate that other proposed mechanisms have a minor role. Yet, there is much evidence to the contrary. These include the importance of nitrogen fixation under specific circumstances, including the postpara nodule colonization (presented earlier) and new data collected under greenhouse and field conditions (Rodrigues et al., 2008; Van Dommelen et al., 2009). The overall accumulated evidence that nitrogen fixation plays a role in the association reconfirms that dismissal of nitrogen fixation, as a mechanism for plant growth reported in several reviews in recent years, is premature, and that nitrogen fixation should be reconsidered as a plausible comechanism. Additionally, the importance of signal mole cules in initiating the cascade of events that induce a plant response, should be considered, perhaps in relation to root membranes (the main subcellular units responsible for mineral uptake detected in numerous associations of plant with Azospirillum). Many cases of mitigation of environmental stresses, possibly by mechanisms not envisioned so far or by a combination of several proposed mechanisms, as well as the possibly of limited biological control of plant pathogens, deserve critical evaluation and reconsideration. The multitude of options for enhancing plant growth by inoculation with Azospirillum led us to propose the ‘‘Multiple Mechanisms Theory,’’ based on the assumption that there is no single mechanism involved in promoting plant growth with Azospirillum, but rather a combination of a few or many mechanisms in each specific case of inoculation. The mechan isms may vary with the plant species, the strain of Azospirillum, and envi ronmental conditions prevailing during the interaction. The effect can be cumulative, as proposed earlier by the ‘‘additive hypothesis’’ (Bashan and Levanony, 1990), where the effects of small mechanisms, operating at the same time or consecutively, create a larger final effect on the plant. The effect on plant growth can also be a result from tandem or cascading mechanisms in which one mechanism stimulates the other, which finally yields enhanced plant growth (such as the plausible relations among plant hormones, NO, membrane activities, and proliferation of root). Finally, promoting growth can be the result of a combination of unrelated mechan isms that operate according to environmental or agricultural conditions in a certain location. These include stress mitigation (salt, drought, toxic com pounds) and biological control of pathogenic microflora. This inclusive kind of theory may close the gaps between competing theories and might lead to new insights about overlapping and cooperation among seemingly different mechanisms that affect plant growth than have been studied so far.
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ACKNOWLEDGMENTS Yoav Bashan participated in this essay in memory of the late Avner Bashan of Israel. We thank the following scientists for critical reading and insightful suggestions during manuscript preparation: Fabricio Cassan, University of Rio Cuarto, Argentina (phytohormones), Ivan Kennedy, Nitrogen Fixation Center, University of Sydney, Australia (N2 fixation), Cecilia Creus, University de Mar del Plata, Argentina and Michael Cohen, Sonoma State Univer sity, California (NO). Juan Pablo Hernandez at CIBNOR, Mexico prepared the drawing. This review was mainly supported by The Bashan Foundation USA and partly by Consejo Nacional de Ciencia y Tecnologı´a (CONACYT Investigacion Cientifica Basica 2005 50560 Z), and Secretaria de Medio Ambiente y Recursos Naturales of Mexico (SEMAR NAT 23510).
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C H A P T E R
T H R E E
Manufactured Nanoparticles and their Sorption of Organic Chemicals Bo Pan*,† and Baoshan Xing† Contents 1. Introduction 1.1. Nanoparticles and their sources 1.2. Toxicity of nanoparticles 1.3. Environmental behavior of organic chemicals regulated by nanoparitcles 2. Occurrence, Characterizations, Structures, Properties of Manufactured Nanoparticles 2.1. Occurrence of manufactured nanoparticles in the environment 2.2. Manufactured nanoparticle characterization and quantification 2.3. Pathways of manufactured nanoparticles to enter the environment 3. Colloidal Behaviors of Manufactured Nanoparticles 3.1. Colloidal behavior of manufactured nanoparticles and their mobility 3.2. Colloidal behavior as affected by ionic strength and pH 3.3. Colloidal behavior as affected by surface functional groups 4. Adsorption Mechanism of Organic Chemicals on Manufactured Nanoparticles 4.1. Carbon-based nanoparticles 4.2. Inorganic manufactured nanoparticles 4.3. Natural nanoparticles 4.4. Simultaneous functioning of various mechanisms 5. Manufactured Nanoparticle Sorption Properties as Affected by NOM 5.1. NOM coating 5.2. Three-phase system 5.3. Dispersion of manufactured nanoparticles
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* Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China Department of Plant, Soil and Insect Sciences, University of Massachusetts, Amherst, Massachusetts, USA
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Advances in Agronomy, Volume 108 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)08003-X
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2010 Elsevier Inc. All rights reserved.
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6. Environmental Mobility of Organic Chemicals and Manufactured Nanoparticles as Affected by Adsorption 6.1. Leaching of manufactured nanoparticles as affected by adsorption of organic chemicals 6.2. Transport of organic chemicals after adsorbed by manufactured nanoparticles 7. Environmental Exposure and Risk of Organic Chemicals and Manufactured Nanoparticles as Affected by Adsorption 7.1. Uptake and toxicity of manufactured nanoparticles to organisms and the effect of organic chemical adsorption 7.2. Release, bioavailability and toxicity of organic chemicals after adsorption on manufactured nanoparticles 8. Summary and Perspectives 8.1. Main points 8.2. Future directions Acknowledgments References
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Abstract With the rapid development and application of nanotechnology, increasing concern has been raised on the environmental risks of manufactured nanoparticles (MNPs) because they will find their way into the environment during their production, purification, application, and disposal. The interactions between organic chemicals and MNPs will alter the environmental behavior of both organic chemicals and MNPs. Therefore, understanding organic chemical– MNP adsorption mechanisms as well as the consequent influences on organic chemical and MNP environmental behavior is fundamental to assessing their environmental exposure and risks. Thus, current research progress and knowledge gaps regarding adsorption mechanisms of organic chemicals on MNPs are the main focus of this review. In addition, MNP application, general properties, occurrence, and entry pathways to the environment are summarized. MNP colloidal behaviors, which are their unique properties in comparison to other adsorbents, are discussed. The mobility and toxicity of both organic chemicals and MNPs after adsorption are also addressed. Finally, future research directions are presented.
1. Introduction Nanoparticles (NPs) are fine particles with one dimension smaller than 100 nm. In comparison to bulk particles, the atoms in NPs have the following two features: (1) less coordination number and (2) more exposed reactive species in the surrounding circumstances ( Jones and Grainger, 2009). Surface atom percentage increases with decreasing particle size
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(Auffan et al., 2009). For microparticles, less than 1% of the atoms locate on particle surface (Nel et al., 2006). But 10% of atoms occupy the surfaces for particles with a diameter of 10 nm. If the particle size is further decreased to 2 nm, 60% of the atoms are located on the surface and are in contact with the environment. Thus, as particle size decreases, the reactivity of the surface atoms could increase dramatically. These unique properties make nano sized particles valuable engineering materials because of their extraor dinary strength, chemical reactivity, electrical conductivity, or other characteristics that the same material does not possess at the micro or macroscales. The novel technologies developed based on these unique properties of NPs are called nanotechnologies (EPA, 2007). The application of nanotechnology could greatly improve the efficiency of industrial pro cesses and facilitate human daily life. Therefore, human started to synthesize NPs since 1970s. Nanotechnology has become one of the most promising new technologies of the twenty first century and will have dramatic impacts across the fields of physics, chemistry, biology, medicine, material science, engineering, and environmental sciences. Up to November 2009, the Project on Emerging Nanotechnologies (http://www.nanotechproject. org) listed over 1000 nanotechnology products closely related with our daily life, covering the categories of automotive, electronics, food/bever age, household tools, toys, clothing, and personal care products. The potential market value for nanotechnology related products in 2011–2015 will be up to $ 1 trillion per annum (NSF, 2001; Wiesner et al., 2006). Although reliable detection and analytical techniques are still lacking, the presence of natural NPs (NNPs) in the environment is believed to be very high. However, because these particles are naturally derived and they have been in the environment with the evolution of organisms, their environmental risk has been lessened and showed very good compatibility with the environment. Therefore, their environmental risks are not the main concern of current studies. On the other hand, manufactured NPs (MNPs) are emerging materials and the ecological system has not developed adaptive mechanisms. During the synthesis, purification, application, and disposal, MNPs will inevitably enter the environment. Because of the recent appearance of MNPs, the organisms have not developed the resistance to these new materials. Especially, because the properties of MNPs are intentionally strengthened during synthesis for their applications, their environmental risks are much higher than NNPs. Therefore, the environmental risks of MNPs are attracting increasing attention from both the public and scientific communities. The toxicity of MNPs has been widely reported (Nel et al., 2006). Therefore, the vast production and application of MNPs surely bring along the public concern of their health risk. To ensure the safe application and sustainable development of nanotechnology, we need to systematically investigate the environmental risks of MNPs (Maynard et al., 2006). Because of their large surface area, MNPs are reported to strongly interact
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with heavy metals (Rao et al., 2007) and organic contaminants (Pan and Xing, 2008). Specifically, the interaction between MNPs and organic chemicals would control the environmental behavior and toxicity of both MNPs and organic chemicals. In addition, this interaction could show distinct effect on ecological systems. Therefore, this review will give emphasis on the interaction mechanisms between MNPs and organic chemicals. The particle sizes of MNPs are in the range of colloids and thus the concepts in colloidal chemistry could be applied to study MNPs. MNP colloidal behavior will alter their adsorption properties with organic chemicals. Therefore, this review will summarize MNP colloidal behavior in a separate section. The toxicity and environmental behavior of MNPs and organic chemicals as affected by their interaction will also be discussed and summarized. Several important types of NNPs, such as soot and humin, which have very strong interactions with organic chemicals, will also be presented for comparison with MNPs.
1.1. Nanoparticles and their sources NPs could be classified according to different criteria, such as sources, bulk materials, and sizes. Because this chapter focuses on MNPs, the first level of NP classification will be based on their sources. To facilitate the detailed discussion on adsorption mechanisms, the bulk material will be a second level of NP classification (Fig. 1). Depending on their sources, NPs could be
Natural
NPs
Biogenic
Humic/fulvic acids, polysaccharides, and peptidoglycan
Geogenic
Soot/black carbon, clay, carbon nanotubes and fullerene
Atomospheric
Aerosol, ocean salt, organic acids, soot
Accidental
Electricity generation, diesel burning, and welding
Anthropogenic
Carbon-based
Carbon nanotubes and fullerene
Metal-based
Gold, silver, zero valence iron
Oxide-based
Titanium oxide, zinc oxide, silicon oxide
Polymer-based
Polyethyleneglycol, latex
Manufactured
Figure 1 Classification of nanoparticles (NPs). Natural NPs are classified as biogenic, geogenic (including burning of geogenic sources), and atmospheric NPs which present in the environment for a long period of time. Anthropogenic NPs contains two categories, namely accidental NPs and manufactured NPs. Manufactured NPs are of the major concern of this study (gray background).
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divided into NNPs and anthropogenic NPs (ANPs). MNPs are the major constituent of ANPs. According to their matrix materials, MNPs could be divided into the following groups: carbon based NPs (such as carbon nanotubes (CNTs) and fullerene), metal based NPs (such as nanogold and nano zero valent iron), oxide based NPs (such as nano silver oxide, nano titanium oxide, nano zinc oxide, and silicon oxide), and polymer based NPs (such as polyethyleneglycol). During manufacturing and human daily activ ities, such as cooking, electricity generation, industrial boiling, diesel burning, and welding, NPs may be accidentally produced and discharged into the environment (Murr et al., 2004). This type of NPs is known as accidental NPs. 1.1.1. Natural nanoparticles NNPs have been present in the environment for millions of years, such as organic colloids (including dissolved organic matter, polysaccharides, humic materials, and peptidoglycan), soot/black carbon, and inorganic particles (including clay and ocean salt) (Nowack and Bucheli, 2007). Black carbon is produced during incomplete combustion of fossil fuels, biofuel, and biomass and could exist in soils/sediments in NP size range (Maurice and Hochella, 2008). Black carbon derived from biomass burning was estimated to be 0.05–0.27 Gt/year (Kuhlbusch and Crutzen, 1995), and that produced from fossil fuel combustion was 0.012–0.024 Gt/year (Penner et al., 1993). The increased biomass burning and fossil fuel consumption in recent years have drastically increased the input of black carbon to the environment. Soot is a production of incomplete combustion of fossil fuels and vegetation. Soot belongs to black carbon and has the dimension in the range of NPs. Black carbon/soot is also viewed as accidental ANPs because they are also by products from human activities, such as diesel burning and cooking. Biogenically derived NPs are mostly organic colloids, such as polysacchar ides, proteins, organisms of nano size (e.g., viruses), and humic/fulvic acids. These particles are actively involved in biological processes. Researchers even detected CNTs and fullerene in ice core formed 10,000 years ago (Murr et al., 2004). The formation of fullerene and CNTs in the environment was attributed to metamorphosis of PAHs at 300–500 C in the presence of sulfur (Heymann et al., 2003) or natural combustion. 1.1.2. Manufactured nanoparticles MNPs could be easily classified according to their bulk materials. The easily controlled size, surface charge, morphology, and composition of polymers enable the synthesis of polymeric NPs. Polymeric NPs attracted many applications in drug delivery because this type of NPs could pass through cell membranes and cross the blood–brain barrier (Koziara et al., 2003). Carbon based NPs are mostly synthesized using the following methods: (1) Arc-discharge – Carbon based NPs were initially found in soot produced
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in arc discharge with catalytic metals such as Fe, Ni, and Co. This method was then modified and reacted in a controlled condition to produce CNTs and fullerene. (2) Laser ablation – Carbon based NPs are produced by pulsed YAG laser ablation of graphite target in a furnace at 1200 C. (3) Chemical vapor deposition – Using this method, carbon based NPs are grown from nucleation sites of a catalyst in carbon based gas environments (such as ethylene, methane, and propane) at elevated temperatures (600–1000 C). The production and type of carbon based NPs are dependent on catalyst material, gas, temperature, flow rate, and reaction time. Inorganic NPs include a wide range of NPs. Up to now, the most widely used MNPs is elemental silver NPs which accounted for more than 25% of nanoproducts (http://www.nanotechproject.org). Silver has been used for medical application for over 100 years because of its antibacterial and antifungal properties (Morones et al., 2005). Nano sized silver particles have an extremely large specific surface area and thus their contact with and effectiveness to target organisms are maximized. The most important benefit of nano sized silver particles is that they can be embedded in/with or coated on other materials. Thus, the antibacterial activities could be applied in various products, such as cooking tools, cloth, personal care products, and sports instruments. Because of their inert properties, TiO2 NPs are used in paints, paper, plastics, sunscreens, and even food (e.g., confectioneries, white colored sauces and dressings, nondairy creamers, and mozzarella and cottage cheeses) (Nohynek et al., 2007). The estimated human daily intake of TiO2 NPs exceeds 5.4 mg/day (Lomer et al., 2000). TiO2 NPs are highly efficient catalyst and are used in photocatalytic processes such as water treatment. They are commercially available in the form of dry powder, cream, or aqueous suspension. Current TiO2 NP production is estimated be 40,000 MT/year in the United States alone and predicted to reach more than 2,000,000 MT/year at 2025 (Robichaud et al., 2009). Aluminum NPs are currently used in a number of applications, such as energetics, alloys, coatings, incendiary devices, and sensors. Reduced Al particle size could greatly reduce the ignition time and enhance the burn rate because of the increased surface area (Meda et al., 2006). This property suggests promising applications in aerosolization of Al NPs. Thus, the deposition of Al NPs in a large area is expected. The physical properties of gold are changed distinctively when its particle size is reduced. In bulk scale, gold, known as a shiny, yellow metal that does not tarnish, is nonmagnetic and melts at 1336 K. However, gold NPs could be used as a very efficient catalyst and exhibit strong magnetism. The melting temperature decreases dramatically as size goes down, reaching around 400 K. In nanoscale, gold is not even golden any more. It appears green, red, blue, yellow, and other colors. The most widely accepted application of nanotechnology in environ mental remediation is zero valent iron (ZVI) NPs used in groundwater
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remediation (Zhang, 2003). ZVI particles are a powerful reductant and ZVI NPs are much more reactive than granular ZVI. Thus, ZVI NPs have the potential to quickly react with many environmental contaminants. In addi tion, nano sized particles make the injection in the soil pores much easier than coarse particles. Therefore, ZVI NPs could be readily delivered and are used as a permeable reactive barrier.
1.2. Toxicity of nanoparticles Strong evidence has been reported to show the toxicity of NPs to plants, fish, rats, and cells. The toxicity of MNPs is quite different from larger particles. They could enter different types of cells by nonendocytic and actin indepen dent mechanisms (Mayhew et al., 2009). The mechanisms of the toxic effect of MNPs on organisms could be summarized as follows: (1) NPs could generate reactive oxygen species because of their redox activity and thus pose oxidative stress to organism. (2) NPs could be adsorbed on cell mem brane, disturbing its permeation properties, puncturing cell membrane, and interfering with physiological activities. (3) NPs could retain electrons and thus disturb electron transfer in organisms, such as phosphorylation and energy transfer. (4) NPs could interact with proteins and thus disturb the transfer of biosignals or even gene information (Chen and von Mikecz, 2005; Linse et al., 2007; Oberdorster, 2004). All the aforementioned mechanisms are based on the studies on plants and animals, thus may not be applicable to humans. However, on August 19, 2009, Reuters reported a disease or even death case because of longtime contact with NPs (Reuters, 2009). The toxicity and the mechanisms of NP toxic effect are all dependent on their properties. This viewpoint could be firstly understood from the bulk materials. However, for a same material, different types of NPs may manifest different toxic effects. For example, single walled CNTs could be accumu lated on the surface of fish gills, and thus disorder fish respiration system (Smith et al., 2007). This mechanism belongs to the second toxic mecha nism. On the other hand, because of their small size and lipophilicity, fullerene could pass through the external cellular membrane and be loca lized to the mitochondria, the cytoplasm, lysosomes, and cell nuclei (Porter et al., 2007). Fullerene thus poses peroxide stress to fish (Zhu et al., 2006), which belongs to the first mechanism. Up to date, various toxic effects have been reported, sometimes with controversial results. The results from different studies could be hardly com pared. For example, nano TiO2 was reported to stimulate the growth of spinach when applied to the seeds or sprayed onto the leaves (Gao et al., 2006; Hong et al., 2005; Yang et al., 2006a; Zheng et al., 2005). The benefited spinach growth was attributed to the increased activity of several enzymes, promoted nitrate adsorption, and enhanced efficiency of transforming inor ganic nitrogen to organic nitrogen. However, the toxicity of nano TiO2 was
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reported to algae and daphnids (Hund Rinke and Simon, 2006). One of the main reasons for these various or even controversial results is lack of a general standard procedure of toxicity experiments for NPs. Thus, the comparison between the results from different toxicity experiments is not quite appropriate. The factors to be considered for procedure standardization include the preparation of NPs, the selection of organism species, the endpoints of toxicity experiments, and the environmental conditions in the experimental system. The readers are suggested to refer to the review by (Handy et al., 2008) for a more complete presentation on MNP ecotoxicity.
1.3. Environmental behavior of organic chemicals regulated by nanoparitcles The environmental fate of organic chemicals has been a hot topic for several decades. The basic framework of this line of research is to study the interactions between organic chemicals and environmental components, and then sum marize all the processes in a complex model to provide a general view on organic chemical environmental behavior. This work is essential in under standing the environmental risks of organic chemicals and will provide funda mental information of their risk assessment. The presence of emerging material in the environment will inevitably raise new environmental concerns. How to understand the environmental risk of MNPs is a new challenge to environ mentalists. CNTs possess a strong hydrophobic surface, and thus their interac tion with organic chemicals attracted the greatest attention in comparison with other MNPs. In addition to the aforementioned influence on organic chemical fate, the importance of understanding organic chemical–CNT interactions could be further viewed from the following two points: (1) the strong interac tion showed potential application of CNTs as effective adsorbents for organic chemicals in environmental analysis and water treatment and (2) the structures of CNTs are well defined and their surfaces are relatively uniform in contrast with activated carbons (ACs). Therefore, CNTs are considered to be a good choice to study adsorption mechanisms. For these reasons, understanding of organic chemical–CNT interactions will provide important information on assessing the environmental risks of both organic chemicals and CNTs and exploring CNT applications.
2. Occurrence, Characterizations, Structures, Properties of Manufactured Nanoparticles To understand the effects of MNPs on organic chemical environmen tal behavior, it is fundamental to know MNP properties and their occur rence in the environment. A summary on this research area will provide a
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basis for environmental relevance of MNP research. In addition, it is important to learn the disadvantages of current technologies used in MNP characterization and quantification. Thus, their limitations will also be summarized in this section.
2.1. Occurrence of manufactured nanoparticles in the environment Lack of identification and quantification techniques of MNPs hinder our knowledge on the occurrence of MNPs in the environment. Currently, investigators applied simple algorithms to predict the discharge of MNPs to the environment. Very high concentrations of Latex, ZnO, and TiO2 are expected in soil and water (Boxall et al., 2008; Fig. 2). It seems that a distribution parameter (i.e., 41.9 L/kg as indicated in Fig. 2) was applied to describe the distribution of MNPs between soil and water, which is only an estimation. Gottschalk et al. (2009) also calculated environmental con centrations of MNPs in different environmental media based on a probabi listic material flow analysis. The most frequent values for fullerenes, CNTs, TiO2 NPs, ZnO NPs, and Ag NPs are two to four orders of magnitude higher in sewage treatment effluents than in surface water, indicating current MNP risks to aquatic organisms are mostly in the region affected by sewage treatment effluents. Kiser et al. (2009) investigated the behavior of TiO2 NPs and larger sized TiO2. They observed that TiO2 particles
10,000 ZnO Latex
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Figure 2 Predicted MNP concentrations in water and soil (modified from Boxall et al., 2008). The expected MNP concentrations in soil are 40 times higher than those in water. The highest concentrations for MNP are Latex, ZnO, and TiO2, because of their wide applications.
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larger than 0.7 mm were well removed by wastewater treatment plant processes. The detected Ti in the effluents was mostly in the particles <0.7 mm with the concentration of 5–15 mg/L. Most of Ti accumulated in the settled solid with concentrations of 1000—6000 mg/g. The TiO2 NPs discharged with the effluent and field applied sludge will bring TiO2 NPs to the environment and lead to environmental exposure and risk. More accurate estimation is still unavailable because of the absence of proper quantitative methods.
2.2. Manufactured nanoparticle characterization and quantification In order to understand the environmental risks of MNPs, characterization and quantification are of the fundamental importance. Methods tradition ally used in organic colloid analysis could be borrowed in MNP characteri zation and quantification. For example, microscopic methods (TEM, SEM, and AFM), size fractionation (ultrafiltration, ultracentrifuge, cross flow filtration, and field flow fractionation), chromatography (size exclusive chromatography, gel permeation chromatography), and size distribution analysis (zetasizer) could all be applied to characterize MNPs (Tiede et al., 2009). Microscopic methods are often used in characterizing MNPs. How ever, only a very small fraction of the sample was used to obtain the image and thus the result may be sometimes subjective and incomplete. To get a representative sample is very difficult. In addition, during the procedure of preparing the samples for microscopic analysis, the structure of the NPs can be altered (Burleson et al., 2003). Field flow fractionation (FFF) is successfully used to determine the particle size distribution of MNPs (Carpino et al., 2005). In comparison to common liquid chromatography containing mobile and stationary phases, FFF achieves the separation within the mobile phase alone. Particles inter acting less strongly with the field are eluted more quickly than those interacting more strongly. The application of this method could be extended by connecting inline with other quantification devices, such as UV–vis and HPLC–MS. Size exclusion chromatography (SEC) is an effective, nondestructive method for purification and size separation using a stationary phase with defined pore sizes. This method is known as gel filtration chromatography if the particular samples are transported by aqueous phase, or gel permeation chromatography if the aqueous phase is organic solvent. SEC is widely used to purify and analyze synthetic and biological polymers, such as proteins, polysaccharides, and nucleic acids. This method was successfully used to characterize CdSe quantum dots (Krueger et al., 2005) and CNTs (Duesberg et al., 1998).
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In the framework of MNP characterization, MNPs should be distinguished from NNPs. There is no discussion on distinguishing these two classes of NPs. The aforementioned methods are mostly dependent on the physical shape and size of MNPs, and thus could not identify the chemical composition of MNPs. Therefore, only nano sized particles are observed without recognizing their origin and chemical properties. Energy dispersive X ray (EDX) is applied in association with imaging techniques and the chemical composition in a specific small region could be identified. Therefore, it is a very powerful way for MNP environmental behavior analysis. However, this method is relatively expensive and could not be widely applied in research. In addition, as other imaging techniques, EDX provide information only about a very limited area or amount, and the overall information may not be provided. The methodology applied in black carbon studies may provide valuable ideas in developing new method for MNP characterization, especially for carbon based NPs. Systematic evaluation of black carbon/soot quantifica tion methods in environmental samples is summarized in the paper by Cornelissen et al. (2005). Two quantification methods are widely used in the analysis of black carbon, namely thermal and chemical methods. Both methods could be viewed as two steps. Non black carbon organic matter is selectively removed using thermal or chemical method, then the remaining carbonaceous materials are BC. These residue particles are then character ized using different methods, such as microscopic methods, titration, coulometry, NMR, or elemental analysis (Nowack and Bucheli, 2007). Explicit quantification method is available only for fullerene. Fullerene is usually quantified using UV–vis spectrometer at 336, 407, 540, and 595 nm. But the method is only applicable for high concentrations, mostly in laboratory systems. HPLC is more reliable method of quantifying fullerene at low con centrations (Fortner et al., 2005). HPLC method is also reported to be efficient in analyzing fullerene from environmental samples (Chijiwa et al., 1999). UV–vis spectrometer is also used to quantify CNTs at very high con centrations at 253, 266, 350 nm or 800 nm. However, this method is only applicable in simple systems, for example laboratory simulated systems. For the samples from the environment, pretreatment of the samples, such as extraction from the environmental matrices, separation from interfering materials, and concentrating to a higher concentration, is needed. However, these pretreatment methods are not available for CNTs, yet.
2.3. Pathways of manufactured nanoparticles to enter the environment MNPs could enter the environment in various forms through different path ways (Fig. 3). During their synthesis, application, and disposal, MNPs may enter the environment directly. For example, TiO2 NPs were detected in soil and water around the place where TiO2 NP containing paints were applied
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NPs
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Figure 3 Environmental fate of NPs. Both accidentally generated and manufactured NPs may enter wastewater treatment system or directly discharged into the environment. All types of NPs will eventually find their way into the environment, and pose toxic effect to organisms and ecosystems.
(Kaegi et al., 2008). During environmental remediation, MNPs were directly applied in open environments, and inevitably, these particles will transport in environmental media. MNPs related with daily activities were discharged into sewage system. If MNPs were removed during water treatment procedure, these particles will mostly be precipitated into sewage sludge. During sludge burial or application of sewage sludge on land, MNPs enter the environment and may be transported and spread out by water and wind. If MNPs were not removed during water treatment, these particles will be discharged with the effluent into surface water and groundwater, or even drinking water system. Therefore, during their life cycle, MNPs could find their way into the environment and transport in air, water, and soil systems.
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Understanding the pattern that MNPs enter the environment is a funda mental requirement to study MNP environmental fate and consequently their risks. For traditional chemicals, the physiochemical parameters are applied as inputs in multimedia modeling, such as octane–water distribution coefficient, saturation vapor pressure, and adsorption coefficient. These parameters are readily available from literature or through simple experiment measurements. However, this modeling concept is not applicable to MNPs because all these parameters are not applicable to MNPs. The first attempt to quantitatively describe MNP environmental fate was provided by Mueller and Nowack (2008). They developed a conceptual model and compared the environmental transport and exposure of silver, TiO2, and carbon NPs. In this model, the authors systematically incorporated global production, appli cation, recycling, and disposal of MNPs. In all the procedures, the pathways and amount that MNPs could enter the environment are estimated. The possible concentrations that MNPs may be present in environmental media were compared with the concentrations that pose no toxic effect. Thus, MNP environmental risks were evaluated. Their results showed that the environmental behavior and risks were distinctly different for different MNPs. In addition, the current modeling results and predicted risks will be changed soon with more development and application of nanotechnology (Nowack, 2009). However, because the environmental concentration of MNPs could not be detected properly up to now, the accuracy and reliability of the model could not be tested. Further, explicit quantification of MNP behavior instead of the conceptual mass calculation is needed. Most of the NPs are embedded in nanotechnology products. The release of NPs from these final products is dependent on the technology that these products are synthesized, the surface coating as well as the application and disposal of these products. The only available information is on silver NPs releasing from socks (Benn and Westerhoff, 2008). Systematic examination of NP release from different final products is still not available.
3. Colloidal Behaviors of Manufactured Nanoparticles The adsorption of organic chemicals on MNPs is dependent on their properties, such as particle size, size distribution, shape, surface and core chemistry, agglomeration state, crystallinity, purity, surface charge, and poros ity. These properties could also control and/or are affected by MNP colloidal behaviors, namely aggregation and dispersion. For example, MNPs tend to form big aggregates in water because of the attractive interaction (mostly London–Van der Waals force) between particles of nanoscale (Nowack and Bucheli, 2007). These interactions could be well described using DLVO (Derjaguin, Landau, Verwey and Overbeek) theory. It is easy to understand
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that aggregated MNPs could precipitate and hardly be transported by water. Consequently, the ability of MNPs to adsorb and carry organic chemicals will be decreased. Higher degree of MNP oxidation (Templeton et al., 2006) and lower ionic strength of the aqueous system (Li et al., 2009; Saleh et al., 2008; Wiesner et al., 2008) usually result in better suspension.
3.1. Colloidal behavior of manufactured nanoparticles and their mobility The mobility of iron NPs is discussed by several studies because of their application in underground water remediation. The stability and transport of iron NPs were influenced by their electrostatic and magnetic interactions. Iron NPs with less magnetism could elute more easily from soil column and more stable in water than highly magnetic particles (Hong et al., 2009). In addition, hydrophilic carbon and poly(acrylic acid) supported iron NPs form very stable colloidal suspensions and settle very slowly in comparison to unsupported iron NPs (Schrick et al., 2004). Thus, the anionic surface of the supported NPs facilitated their transport and consequently enabled these particles to reach polluted underground water. The deposition of MNPs in porous media could be viewed as two processes: (1) If the pores are too small for the colloids to pass through, straining occurs. This process plays an important role when the ratio of particle to collector grain diameters is greater than 0.05 (Sakthivadivel, 1969), or even as low as 0.003 (Braddord et al., 2007). The shape of MNPs, for example, the large aspect ratio, the variability of their length, and bundled state also play a significant role in straining (Jaisi et al., 2008). (2) Physico chemical filtration. Jaisi et al. (2008) observed significant increase of CNT deposition with ionic strength higher than 3 mM and this observation is consistent with conventional colloid deposition theory. The authors stated that physicochemical filtration is the dominant mechanism for the column to retain CNTs. They also connected three columns and the eluted solution was used as an influent of the subsequent column. They observed decreased deposition as the colloidal solution successively pass through the three col umns. This result indicated that the column selectively retained long and more bundled Single walled CNTs (SWCNTs) in the first column and more mobile SWCNT fractions were leached out. Consequently, the extent of SWCNT deposition decreased in the subsequent runs. The properties of the stationary matrix are also important. For example, the transport of Al NPs through soil column was much slower than that through sand column (Darlington et al., 2009). Various factors should be combined to understand this difference, for example, the electrostatic interactions between the particles and the matrix, the dynamic pore size of the matrix over time, and the specific surface area. At the very beginning stage of MNP environmental transport study, all these parameters are still under investigation.
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3.2. Colloidal behavior as affected by ionic strength and pH Ionic strength and pH control MNP surface charge and thus determine their colloidal behavior. One of the most important properties of colloids is their point of zero charge (pHzpc). This parameter is a pH value at which the colloid surface exhibits zero net charge. Generally, colloids at this pH show minimum stability or maximum coagulation/aggregation rate. For example, the stability of TiO2 colloids is mainly governed by solution pH (Guzman et al., 2006; Kallay and Zalac, 2002). At pH around pHzpc (6.2 for TiO2), TiO2 NPs were highly aggregated. But at other pHs (either higher or lower), over 80% of TiO2 NPs were mobile (Guzman et al., 2006). pHzpc for iron NPs is lower than 6, which is why iron NPs are more negatively charged at pH 9 than at pH 6, and thus iron NPs eluted to a greater extent at pH 9 (Hong et al., 2009). At neutral pH, the zeta potential of nC60 (fullerene suspension) is about 50 mV. Therefore, once C60 are dispersed in water, they could be stable for months. In the aqueous condition with cations of Ca and Mg in the range of 0.01–10 mM, nC60 remain negatively charged (Brant et al., 2005). The increased Ca or Mg concentration could neutralize the surface charges of nC60. As the ionic strength increased to 100 mM, the zeta potential reached zero and thus the electrostatic repulsion is minimized, which consequently result in larger aggregates. Investigators observed that MNP dispersion decreased with increased ionic strength (Wiesner et al., 2006). Divalent cations are more effective in reducing the stability of colloidal particles than monovalent cations, even at a same total ionic strength (Jaisi et al., 2008; Lin et al., 2009). However, Li et al. (2009) observed higher solubility of C60 in 1 mM Ca2þ (13.9 mg/L) than that in 0.1 mM NaCl (5.9 mg/L). But the authors did not discuss about the reason that Ca2þ could increase the stability of C60 in their study. It is well known that the presence of natural organic matter (NOM) could enhance the dispersion of MNPs. The presence of ions could neutralize and shrink NOM molecules adsorbed on MNP surface and thus the electrostatic repulsion between NOM molecules, then steric hindrance of the adsorbed NOM molecules are decreased (Li et al., 2009). As a result, the suspension of MNPs by NOM could be decreased because of the presence of ions. More discussion regarding MNP dispersion by NOM could be found in Section 5.
3.3. Colloidal behavior as affected by surface functional groups Surface functional groups may alter the surface charge or the steric interac tions between NPs. Untreated CNTs usually have pHzpc around pH 7. The acid treatment introduced oxygen containing functional groups on CNT surface and thus CNTs are negatively charged at pH 7 with a zeta potential from 30 to 70 mV (Hu et al., 2005), which is one of the
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reasons that surface modified CNTs could be easily dispersed in comparison to the original ones. In addition, the surface functional groups on CNTs made them more polar than their original counterparts (Zhang et al., 2009). Therefore, these functional groups have a positive effect on CNT dispersi bility in water. The solubility of C60 in water is reported to be very low. For example, after mixing with 10 mM NaN3 for 2 weeks, the concentration of C60 in ultrapure water was 0.23 mg/L. When the mixing time extended to 11 months, C60 solubility increased slightly to 0.26 mg/L (Dhawan et al., 2006). However, fullerene could be easily dispersed after derivatized with ionizable or hydrophilic groups (Wudl, 2002). C60 could be chemically modified in ozone (Fortner et al., 2007), in organic amines (Li and Liang, 2007), and by sunlight and thus the dispersion was increased. C60 dispersion was observed to be further accelerated by sunlight in the presence of NOM. The reason is that NOM could act as photosensitizers under sunlight. In addition, NOM could produce highly reactive species, such as singlet oxygen, hydroxyl radicals, organic peroxy radicals, and triplet state of NOM (Schwarzenbach et al., 2003; Stumm and Morgan, 1996). Al NPs are often positively charged. Thus, these particles could be retained by the negatively charged soil particles (Darlington et al., 2009). However, phosphate could be tightly bound with aluminum surface. When phosphate is coated on Al NP surface, the surface charge is reversed. After this surface modification, Al NPs and soil particles may repel each other because of electrostatic repulsion, and then the phosphate coated Al NPs could be easily transported. This result indicated that electrostatic interac tions are important in the transport of MNPs and surface properties should also be incorporated in the consideration of MNP environmental behavior. The authors (Darlington et al., 2009) also observed that the uncoated NPs were increasingly retained in the column during the leaching. This result could not be explained by the electrostatic interactions because the retained positively charged NPs may pose repulsion to the particle in the flow through the column and consequently increased transport of Al NPs should be observed. The authors hypothesized that uncoated Al NPs may form aggregates with time and the larger particles could be more easily settled.
4. Adsorption Mechanism of Organic Chemicals on Manufactured Nanoparticles Studying the interactions between organic chemicals and MNPs not only provide important information to understand their environmental behavior and risks, but also promote the application of MNPs in various fields, such as in water treatment, environmental analysis, as well as drug
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delivery. This section summarizes our current understanding on the adsorp tion mechanisms of organic chemicals on MNPs. To facilitate the discus sion, subsections will be entitled with different types of MNPs.
4.1. Carbon-based nanoparticles Carbon based NPs could be viewed as graphite sheet(s) rolling up into different shapes, such as CNTs and fullerene. Their surfaces form systematic benzene ring structures and have very high hydrophobicity. Thus, the adsorption of organic chemicals on CNTs is expected to be very high. However, if compared from adsorption capacity, CNTs did not show significant higher adsorption than AC. It should be noted that the specific surface areas of AC (around 1000 m2/g) are several times higher than those of CNTs (generally in the range of 100–300 m2/g). If the adsorption capacity is normalized by specific surface area, the resulted adsorption capacity of a unit surface area (QSSA) is much higher for CNTs than that of ACs. Because CNTs normally exist as aggregates, the higher QSSA for CNTs indicates that CNTs have very high adsorption potential. If technol ogies to disperse CNTs are applied, CNT surface area will increase, and possibly their adsorption capacities increase as well. Studies have indicated that CNTs with a higher degree of oxidation could be easily suspended by ultrasonic (Templeton et al., 2006). More adsorption sites will be available after CNT dispersion and the adsorption capacity may be increased. On the other hand, CNT aggregation will remarkably decrease their surface area and their adsorption (Zhang et al., 2009). Up to now, various techniques have been proposed to disperse CNTs, such as ultrasonic (Templeton et al., 2006), surfactants coating (Moore et al., 2003; Tan and Resasco, 2005), and NOM adsorption (Chen and Elimelech, 2007; Hyung et al., 2007; Yang et al., 2009). However, these methods usually alter the surface properties of CNTs and these changes may not always enhance their adsorption capacity. For example, ultrasonic could disperse CNT aggregates and at the same time may oxidize CNT surface (Templeton et al., 2006). The enhanced surface oxidation was reported to decrease the adsorption for organic chemicals (Cho et al., 2008). The reasons could be understood from the following two aspects: (1) The hydration shell of oxygen containing functional groups is much thicker than that of the plain CNT surface, and thus the adsorption of organic chemicals is inhibited. Zhang et al. (2009) observed decreased adsorption of phenanthrene, biphenyl, and 2 phenylphe nol on CNTs after surface oxidation. The authors also reported that the surface oxygen contents measured by XPS were higher than those measured using elemental analyzer. Similar data were also reported by Lin and Xing (2008a). This phenomenon indicated that the oxidation mostly occurs on the outer surface of CNT aggregates. Water clusters formed at the outer surface and thus the adsorption of the hydrophobic organic chemicals decreased.
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(2) The oxidation of CNTs could increase the polarity of CNT surface. Hence, for some polar compounds, CNT oxidation may increase their adsorption capacity, such as organic chemicals whose adsorption processes are controlled by hydrogen bond or electron donor–acceptor (EDA) systems (Lu et al., 2006; Piao et al., 2008). Obviously, the effects of CNT oxidation on their adsorption capacities are highly dependent on the properties of organic chemicals. Therefore, proper classification is needed in order to accurately interpret the interaction mechanisms between organic chemicals and CNTs. Regarding to desorption hysteresis, different investigators have different points of view. Some of the results showed no obvious desorption hystere sis, such as the data for polyaromatic hydrocarbons (Yang and Xing, 2007), butane (Hilding et al., 2001), and atrazine (Yan et al., 2008). But another group of researchers observed significant desorption hysteresis from small organic molecules (such as methane, ethylene, and benzene) to polymers (Chen et al., 2002; Pan et al., 2008b). The strongly adsorbed organic chemicals could not be released as washed by organic solvents (Wang et al., 2002), buffering solution (Chen et al., 2003), or water (Shim et al., 2002). This strong interaction was also confirmed using SEM and AFM (Shim et al., 2002; Wang et al., 2002). The resistant desorption was attrib uted to the following two reasons: (1) CNT aggregates were rearranged after the adsorption and thus the desorption pathway is different from the adsorption one. For example, fullerene aggregates were reorganized after adsorption of PAHs, and significant desorption resistance was observed (Yang and Xing, 2007). (2) The strong and exothermic interaction between CNT surface and organic chemicals results in retarded desorption. The desorption is not possible without energy input. For example, the adsorp tion of bisphenol A and 17a ethinyl estradiol on CNTs is through EDA system and significant desorption resistance was observed (Pan et al., 2007a). The strong EDA interaction may also cause rearrangement of CNT aggre gates. Thus, the two mechanisms for resistant desorption may not be explicitly separated.
4.2. Inorganic manufactured nanoparticles In comparison with CNTs, the adsorption of organic chemicals on other NPs was studied in a much lesser extent. Because of their hydrophilic surface, metal oxide NPs were believed to have low adsorption of nonpolar organic chemicals from water. The adsorption of pyrene on MNPs (Al2O3, ZnO, and TiO2 NPs, Wang et al., 2008b) is more than one order of magnitude lower than pyrene adsorption on multiwalled CNTs with diam eter of 15 nm (MWCNT 15, Yang et al., 2006b). Wang et al. (2008b) discussed that a layer of water molecules was chemically adsorbed on mineral particle surface which prevented hydrophobic chemicals from approaching and interacting with oxide surfaces. This is also the reason
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that although surface roughness is expected for oxide particles, a linear adsorption of pyrene was observed. Pyrene adsorption on inorganic MNPs is at least one order of magnitude higher than regular particles. Surprisingly, Fang et al. (2008) observed very high adsorption of ZVI NPs for phenanthrene with Kd values in the range of 84.4–278 L/kg at equili brated aqueous concentrations of 20–800 mg/L. These values are compara ble to the adsorption of phenanthrene on MWCNT 15 (Kd values in the range of 99–822 L/kg at the same equilibrated aqueous concentration range, Yang et al., 2006b). ZVI NPs even showed much lower surface area than CNTs (11.2 m2/g vs. 174 m2/g). The authors did not make this comparison and thus explanation was not provided. But they did compare the adsorption of phenanthrene between different inorganic NPs. They observed linear and reversible adsorption on SiO2 NPs which was attributed to their hydrophilic properties. In the contrast, phenanthrene adsorption on ZVI and zerovalent copper (ZVC) NPs was nonlinear and irreversible because of their significantly heterogeneous surface energy distribution patterns. Based on the evidence of pH dependent adsorption, the authors proposed that hydrophobic effect and dipole interactions were important mechanisms for phenanthrene adsorption on ZVI, ZVC, and SiO2 NPs. For polar or amphiphilic molecules (such as DOM), the adsorption on these inorganic NPs was relatively strong (Iorio et al., 2008; Yang et al., 2009). The adsorption of NOM on metal oxide NPs is controlled by the properties of these particles. NPs of aluminum oxide, titanium oxide, and zinc oxide showed significant adsorption with NOM, but the adsorption of NOM on silicate oxide NPs could be neglected (Yang et al., 2009). The adsorption of NOM on metal oxide NPs is mostly controlled by electro static interaction and ligand exchange (Yang et al., 2009). NOM is a complex mixture of small and macromolecule and the adsorption may result in fractionation of chemical fractions and conformation change of their physical organizations (Hur and Schlautman, 2004). The selective adsorp tion is also observed for NOM adsorption on metal oxide NPs. Phenol groups tend to be adsorbed on titanium oxide NPs, but carboxyl groups tend to be adsorbed on zinc oxide NPs (Yang et al., 2009). Various studies have demonstrated that MNPs could enter organisms through skin, respiratory system, or gastrointestinal tract. The adsorption of enzymes and proteins on MNPs (such as TiO2, Fe3O4, and silica) and the consequent inhibition of enzyme activity can be the major mechanisms of MNP toxicity (Sun et al., 2009; Wang et al., 2009b). The adsorption mechanisms of enzymes on MNPs include electrostatic interaction, van der Waals force, hydrogen bonds, and possible ligand exchange. The inhibition of enzyme activity was mostly attributed to the conformational change of enzyme macromolecules after adsorbed on NPs (Kathiravan et al., 2009). Human serum albumin (HSA) fluorescence was attributed to the presence of tyrosine, tryptophan, and phenylalanine residues. Kathiravan et al. (2009)
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observed significant blue shift of HSA fluorescence spectra, indicating that HSA conformation was altered to a more polar and less hydrophobic environment around tyrosine residues. A loss in a helix content of chicken egg lysozyme structure was observed after adsorption on silica NPs (Vertegel et al., 2004). The fraction of activity lost correlates well with the decrease in a helix content.
4.3. Natural nanoparticles NNPs include vastly different types of NPs. This section will selectively discuss the ones that have strong interactions with organic chemicals. The strong nonlinear adsorption and sequestration of organic chemicals on black carbon and soot have been long recognized. This strong interaction leads to the nonideal adsorption between organic chemicals and soils/sediments (Cornelissen et al., 2005; Koelmans et al., 2006). However, naturally derived organic particles also show nonideal interactions with organic chemicals. The purified HA showed very strong nonlinear adsorption (Kang and Xing, 2005; Pan et al., 2007b). Kerogen, which is one of the most condensed organic matter in soils/sediments, has very high adsorption affinity with organic chemicals (Ran et al., 2007). The interaction between dissolved organic matter and organic contami nants is believed to be linear partitioning. However, studies have reported strong evidence that the interaction between NOM and hydrophobic organic chemicals is nonideal as indicated by two stage desorption kinetics (Akkanen et al., 2005; Schlebaum et al., 1998), apparent nonlinear interac tion (Eriksson and Skyllberg, 2001), competition with other chemicals and desorption hysteresis (Pan et al., 2007a) for polar and even nonpolar com pounds. Since hydrophobic interaction is the main interaction mechanism for nonpolar NOM interactions, the investigators proposed that discrete hydrophobic microenvironment in NOM may provide adsorption regions with different adsorption energy. Then, adsorption exhibits nonlinear iso therms because of the unevenly distributed hydrophobic regions in terms of interaction energy (Pan et al., 2007a).
4.4. Simultaneous functioning of various mechanisms Various mechanisms have been proposed to be important for organic pollutant adsorption on CNTs. Hydrophobic interaction seems unable to totally explain the adsorption. For example, Chen et al. (2007a) reported poor correlations between the adsorption affinity and hydrophobicity of several aromatic derivatives. Pan et al. (2007a) also indicated that KHW normalized adsorption coefficient varied more than 1000 times for several organic pollutants on CNT. A correlation study between adsorption coef ficient and organic chemical properties failed to establish a satisfied
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relationship (Pan and Xing, 2008). Obviously, various mechanisms need to be considered. For PAHs, hydrophobic interaction (simply because of CNT hydrophobic surface property) and p–p bond (because of the benzene ring structure of both PAHs and CNTs) are of the major importance (Yang et al., 2006b). For ionizable organic chemical adsorption on CNTs, the involved mechanisms could be diverse. Besides hydrophobic and p–p interactions, electrostatic interaction (because of the charged surface of both organic chemicals and CNTs) and hydrogen bond (because of the functional groups on both organic chemicals and CNTs) would all operate. The discussion on adsorption mechanisms should also compare the adsorption systems at different pHs because pKa of organic chemicals and pHzpc of MNPs can affect the magnitude of adsorption. Different adsorp tion mechanisms may contribute at different pHs as presented in Fig. 4. This figure only discuss the system with pKa of organic chemical < pHzpc π–π bond H bond Hydrophobic effect Cation exchange
Electrostatic attraction
Electrostatic repulsion
Adsorption coefficient K
Electrostatic repulsion
pKa of the adsorbate
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Figure 4 The contribution of different adsorption mechanisms at different pHs. The schematic figure highlights the adsorbent with a specific pHzpc and adsorbate pKa < adsorbent pHzpc. At pH > pHzpc or pH < pKa, electrostatic repulsion may be the dominant interaction mechanisms. H-bond and p p interaction are also possible interaction mechanisms. At pKa < pH < pHzpc, the interaction is much more complicated and may be a combination of electrostatic interactions, cation exchange, hydrophobic effect, H-bond as well as p p interaction. (Reprinted from Zhang et al. (2010) with permission of the American Chemical Society).
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of MNPs. At pH > pHzpc or pH < pKa, the electrostatic repulsion decreases the adsorption as pH increases (when pH > pHzpc) or pH decreases (when pH < pKa). But at pKa < pH < pHzpc, electrostatic attraction is an important interaction mechanism. In addition, in this pH range, cation exchange, hydrophobic interaction, hydrogen bond, p–p interaction, and EDA system could all contribute to the overall adsorption. Hydrogen bond is considered as an attractive force between a hydrogen atom and an electronegative atom, for example nitrogen, oxygen, or fluo rine. At pHs higher than pKa of organic chemicals and pHzpc of MNPs, both organic chemicals and MNPs are deprotonated, and thus hydrogen bond is negligible. Therefore, lack of pH dependent adsorption is an evidence of minimal contribution of hydrogen bond (Chen et al., 2007). It should be noted that there may not be much exchangeable cations on CNTs because of their hydrophobic surface; hence, cation exchange may not be an important interaction mechanism. If a dominant adsorption mechanism was not identified, a complete wrong conclusion may be obtained. For example, if the adsorption is controlled by hydrophobic interaction, CNT oxidation will decrease the adsorption. However, if the adsorption is controlled by hydrogen bond, CNT oxidation will increase the adsorption in the pH range where both organic chemicals and CNTs are not dehydrogenated. Therefore, it is of essential importance to identify the contribution of different adsorption mechanisms at a given environmental condition. However, up to now, the studies only indicate the possible mechanisms. No good methods have been proposed and developed to study and separate the contribution of different mechanisms. Normalization of sorption coefficient by KOW or KHW could screen off hydrophobic effect, and thus investigators could focus on the factors other than hydrophobicity (Chen et al., 2007). More directly, sorption experiments could be conducted in organic solvents. For the adsorption of organic chemicals on geosorbents (such as soil and sediment), a fraction of the adsorbent may be dissolvable in organic solvents. Thus, the experiment with organic solvents is not applicable for mechanistic study in those systems, and the data need to be analyzed carefully to exclude the hydrophobic effect (Borisover and Graber, 2002). However, the major portion of CNTs is well defined and the structure is explicit. Moreover, CNTs do not dramatically dissolve in organic solvent because of their rigid structure. Another benefit for the adsorption experiment with organic solvents is to ensure reliable detection by keeping the adsorbate concentration well above the detection limit due to high solubility in organic solvent. Therefore, the comparison of organic pol lutant adsorption on CNTs between aqueous system and organic solvent system (such as in hexadecane) will provide important information for quantifying the relative contribution of hydrophobic interaction and other mechanisms.
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Another useful method to investigate the adsorption mechanism of organic pollutants on CNTs is to conduct adsorption experiments on CNTs with various functional groups. For example, hydrophobic interac tion may be depressed and H bond may be enhanced after CNT oxidation. Comparison of organic pollutant adsorption on CNTs with different extents of oxidation or different types of functional groups would reveal the importance of individual mechanisms. Molecular dynamic simulations were applied to investigate the adsorp tion of organic molecules on CNTs (Star et al., 2001; Woods et al., 2007; Zhao et al., 2003). These methods seem promising in studying the explicit contribution of different mechanisms. However, theoretical simulations often use vacuum conditions, which is different from real environments. The modeling concept should be improved to integrate various environ mental conditions.
5. Manufactured Nanoparticle Sorption Properties as Affected by NOM NOM is the decomposition compounds of the residuals of organisms (including animals and plants). These ubiquitous compounds will inevitably interact with MNPs and consequently alter MNP adsorption properties, environmental behavior, as well as their risks. Therefore, this line of study has attracted great research interest. Surface coating, three phase interac tion, and MNP dispersion as affected by NOM will be discussed in this section. The similar effects are also applicable to surfactants and polymers. Therefore, in the following discussion, information regarding surfactants and polymers will also be incorporated.
5.1. NOM coating The interaction between NOM and organic chemicals could alter organic chemical environmental behavior and bioavailability. This research direc tion has been the focus of environmental scientists for more than three decades. In a typical soil–water system, NOM presents as two main forms. (1) NOM presents as solid phase such as precipitated humic acid and organomineral complex (humin). The adsorption of organic chemicals on these NOMs could decrease the mobility and bioavailability of organic chemicals. (2) NOM exists as dissolved organic matter in aqueous phase. The interaction between organic chemicals and dissolved NOM could enhance the solubility of organic chemicals, decrease their adsorption on solid particles, and possibly increase their environmental risk (Chiou et al., 1986; Pan et al., 2007a; Pan et al., 2008a). In MNP–water system, NOM
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may have the similar functions. Generally speaking, NOM coated on MNPs could adsorb organic chemicals on solid phase, while dissolved NOM could increase the solubility of organic chemicals in aqueous phase. However, for different types of MNPs, the apparent adsorption as affected by NOM could be quite different. Carbon based NPs usually have very strong adsorption with organic chemicals (Pan and Xing, 2008). Thus, the adsorption of NOM on MNP surface may compete with organic chemicals. These interactions result in decreased adsorption of organic chemicals on MNPs (Chen et al., 2008; Wang et al., 2009a). According to relevant studies on activated and black carbon adsorption as affected by NOM coating, adsorp tion of organic chemicals were decreased through the mechanisms of molecular sieving, pore blockage and the competition between NOM and organic chemicals on the adsorption sites (Kilduff and Wigton, 1999; Kwon and Pignatello, 2005; Pignatello et al., 2006). But for metal oxides, their surface is hydrophilic and the adsorption of organic chemicals is very low. The MNP adsorbed NOM may adsorb organic chemical more strongly than MNPs themselves. Thus, the resulted apparent adsorption increased in comparison with pure MNPs (Iorio et al., 2008; Li et al., 2008; Yang and Xing, 2009). Li et al. (2008) observed significantly increased adsorption of diethyl phthalate (DEP) on both nano and micro alumina after NOM coating. The enhancement was more significant for nano sized alumina. In addition, the adsorption was faster on coated nano sized particles. These differences were attributed to the smaller size and higher surface area of NPs. NOM is complex with different chemical components. The molecular weight ranged from thousands to millions Daltons (Schnitzer and Khan, 1978). The adsorption properties on MNPs of different components are different. Thus, fractionation is expected during NOM adsorption on MNPs. In addition, because the interactions between NOM fractions and organic chemicals are different, fractionation could result in significant dif ferent adsorption properties of coated NOM on MNPs and aqueous residual NOM (Yang and Xing, 2009). In these studies on NOM fractionation after adsorption on the particles of microscale, arguments exist regarding the fractions that will be selectively adsorbed. For example, aliphatic fraction was reported to be preferentially adsorbed by kaolinite and montmorillonite, while aromatic fraction left in the solution (Wang and Xing, 2005). On the other hand, a priority sorption of aromatic carbons on kaolinite and goethite was presented (Namjesnik Dejanovic et al., 2000). Different selectivities of NOM fractions on different types of mineral particles were observed in a single study. Polymethylene groups were prevalent at the surface of kaolinite, while aromatic groups on montmorillonite as shown with HR MAS NMR (Feng et al., 2006). As one can see, the selectivity of NOM fractions is dependent on the properties of mineral particles, such as surface area, func tional groups, and charges. This line of study on NOM adsorption on MNPs
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is just the beginning. However, the same research framework needs to be carried out for MNPs and the difference between nano sized and micro sized particles may provide valuable information to understand the interaction mechanisms between MNPs and NOM. NOM may interact with MNPs through hydroxyl and carboxyl groups, and thus the physical conformation will be reorganized after coating on MNP surface (Yang and Xing, 2009). MNP coated NOM showed more condensed structure than original NOM and thus stronger nonlinear inter action is expected (Yang and Xing, 2009). The reconformation of NOM on microscale particles results in a membrane like structure with a hydropho bic interface between NOM and mineral particles (Wershaw, 1993) or a more condensed structure at low NOM loading (Gunasekara and Xing, 2003). Limited evidence is available to validate if these hypotheses are application in NOM adsorption on MNPs.
5.2. Three-phase system Current studies regarding the effect of NOM on MNP–organic chemical interactions mostly focus on the coating of NOM on MNP particles. The interaction between aqueous NOM and organic chemicals has not been well investigated in current studies. As indicated in Fig. 5, at low NOM
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Figure 5 The role of dissolved organic matter (DOM) and surfactants in suspending MNPs and their adsorption for organic chemicals. Surface coated DOM/surfactant may decrease the zeta potential of MNPs (C) and thus facilitate the dispersion of MNP aggregates (B). The aggregate size may be decreased after surface coating. The availability of adsorption sites may be increased because of MNP dispersion. However, because of the interaction between DOM/surfactant and organic chemicals in aqueous phase, the adsorption on solid particles may decrease as DOM/surfactant concentration increase.
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concentrations, the adsorption of organic chemicals on MNPs may be increased because of the dispersion (for both CNTs and inorganic NPs) or NOM coating (for inorganic NPs). However, as NOM concentration further increases, the adsorption of NOM on MNPs reaches saturation. In this case, the significant interaction between aqueous NOM and organic chemicals could result in decreased adsorption. Current studies applied limited NOM concentrations in the experimental design, and often reported a decreased adsorption of organic chemicals on CNTs ( Ji et al., 2009; Wang et al., 2009a) or increased adsorption on oxide NPs (Iorio et al., 2008) with the addition of NOM. No study was conducted to investigate the possible nonmonotonic influences of DOM on MNP adsorption characteristics. Nonideal interactions between organic chemical–NOM, NOM–solid particles, and organic chemical–solid particles are a widely recognized phenomenon. These nonideal interactions result in nonlinear adsorption, competitive adsorption, and desorption hysteresis. Incorporation of these processes in organic chemical fate modeling could greatly increase the complexity and uncertainty of the model. Therefore, no study has attempted to completely consider all the processes.
5.3. Dispersion of manufactured nanoparticles MNP aggregation could markedly decrease their available surface area and the convenience (or ease) for engineering processing. Therefore, various methods are proposed and practiced to disperse MNP aggregates. Coating with organic molecules is of the major concern. The practiced organic coatings include surfactants ( Jiang et al., 2003), biopolymers, such as alginic acid (Liu et al., 2006), starch (Star et al., 2002), proteins (Karajanagi et al., 2006), phospholipids (Wu et al., 2006) as well as NOM (Hyung et al., 2007; Lin and Xing, 2008b; Lou et al., 2004; Petrov et al., 2003). Because NOM is ubiquitous in the environment, the discussion on NOM dispersing MNPs has generated tremendous research interest. Although ionic strength is another important environmental parameter, the ionic strength is normally less than 0.005 M in soil solution (Black and Campbell, 1982), at which MNP colloidal stability is hardly affected. Therefore, NOM may be a major controlling factor in addition to pH. Two main dispersion mechanisms were proposed based on the studies on CNT dispersion by surfactants (Han et al., 2008; Moore et al., 2003; Tan and Resasco, 2005). One group of researchers stated that CNTs could be solubilized inside columnar micelles in aqueous solution as a result of energetic sonication of the mixture (O’Connell et al., 2002). Another group of researchers believe that CNTs could not be dissolved in micelles, but the adsorption of surfactant molecules on CNT surface form one layer coating and thus CNT aggregates could be separated (Matarredona et al., 2003).
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The main evidence for this mechanism is that CNTs could not be dispersed unless violent disturbance is involved (such as ultrasonic) (Matarredona et al., 2003; Yu et al., 2007). Though exact suspension processes still remain unclear, the ‘‘unzippering’’ type of mechanism of dispersion has been proposed and widely adopted (Bandyopadhyaya et al., 2002; Strano et al., 2003). It is postulated to form gaps or spaces at the bundle ends in the high shear environment of ultrasonicating solution. Surfactant adsorption and diffusion then propagate this space along the bundle length, thereby separ ating the individual CNTs. After the adsorption on NOM on MNPs, the zeta potential could decrease and the repulsion between MNPs could increase. Thus, MNP aggregates could be more easily dispersed (Chen and Elimelech, 2007; Hyung et al., 2007; Yang et al., 2009). The presence of NOM at environmentally related concentrations could increase C60 dispersion. After 10 days of mixing, C60 solubility increased to a few to tens of milligrams per liter (Li et al., 2009). The dispersion mechanism was attributed to steric hindrance effect of the adsorbed NOM and the reduced surface hydrophobicity after NOM adsorption. It is also worth noticing that the extent of MNP suspension is dependent on the properties of NOM. Better dispersion performance of NOM on MNPs was observed for NOM with higher content of surfactant related component. While carbohydrate dominated NOM showed much lower dispersion performance on MNPs (Chappell et al., 2009). The properties of NOM to stabilize or destabilize MNP colloids include molecular size, charge, and rigidity of various functional groups (Wilkinson et al., 1997). Up to now, limited study was conducted to relate the ability of NOM to disperse MNPs and NOM properties. Extended work is needed in this direction and the comparison between suspension performances of NOM with different properties may provide important information to understand suspension mechanisms. Interestingly, NOM may promote the aggregation of MNPs at certain environmental conditions, and the aggregation is also controlled by NOM properties. For example, the coagulation rate of montmorillonite colloids is increased by aquagenic biopolymers, while the addition of fulvic acid could stabilize the colloids (Wilkinson et al., 1997). NOM may disperse MNPs at neutral and alkaline pHs. But at acid pHs, MNPs may be aggregated (Ghosh et al., 2008). At acid pHs, long chain NOM molecules could form cross linking structure, then capture MNPs and aggregate them. Short chain NOM molecules could neutralize the surface charge of MNPs and promote the aggregation (at acid pH, NOM molecules are negatively charged while MNPs are positively charged). In the system with the presence of cations, MNP aggregation could be further promoted. Cations may decrease the repulsion between coated NOM molecules and thus promote aggregation of MNPs. In addition, cations could bridge NOM molecules and cause aggregation of NOM molecules. This enhanced cross linking of NOM
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molecules resulted in bigger network of NOM molecules and their ability to capture MNPs is enhanced (Chen et al., 2006). Therefore, if environ mental condition is to be considered, MNP dispersion by NOM becomes more complicated. MNP dispersion may release more adsorption sites and increase the adsorption with organic chemicals (Carrillo Carrion et al., 2007; Gotovac et al., 2006; Wang et al., 2008a). Although the dispersion of MNPs by NOM has been widely reported, the adsorption characteristics could not be easily investigated using traditional adsorption experimental design. One of the major reasons is that aqueous/solid separation could not be achieved using centrifugation or normal filtering methods. One possible method for this goal is to apply ultrafiltration (Hyung and Kim, 2008) or dialysis equilibrium system (Pan et al., 2007a) to separate suspended MNPs and the aqueous phase.
6. Environmental Mobility of Organic Chemicals and Manufactured Nanoparticles as Affected by Adsorption As discussed earlier, MNP environmental behavior is substantially controlled by their surface properties. The adsorption of organic chemicals could remarkably alter MNP surface properties and thus their mobility. Further, the environmental behavior and risks of organic chemicals will be strikingly changed by MNP adsorption. Therefore, understanding the change of the environmental behaviors of both MNPs and organic chemi cals after the adsorption is vital to assess their exposure and risks.
6.1. Leaching of manufactured nanoparticles as affected by adsorption of organic chemicals Many studies have been conducted to obtain stable MNP suspensions for industrial applications. However, there is very limited information available for MNP dispersion/aggregation behaviors in natural environments, such as in soil and water. Because MNPs tend to aggregate and deposit in water, it may be reasonably expected that MNPs have limited mobility and transport in natural system after their release, hence having low exposure and risk. However, as has been discussed earlier in Section 5, MNPs may be dispersed through various ways in the environment. Dispersed MNPs could be stable in soil suspension for weeks to months without any change in particle size distribution (Gimbert et al., 2007), and thus pose much higher environmen tal risks in comparison with aggregated MNPs. For example, the adsorption of ciprofloxacin could stabilize CNTs for over 1 month (Kumar and Wang, 2009). The presence of dissolved organic carbon and clay content in soil
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solution could facilitate suspending of TiO2 NPs (Fang et al., 2009). In soil column containing relatively large particles and low solution ionic strength, 18.8–83.0% of the added TiO2 NPs could pass through the soil columns. The authors estimated that TiO2 NPs could transport as much as 41.3– 370 cm in soil. NOM could decrease the deposition of MNPs in porous media by increasing electrostatic repulsion (Franchi and O’Melia, 2003) and steric repulsion ( Jaisi et al., 2008). The dispersed MNPs may be transported to longer distances, have longer persistence, and potentially facilitate contaminant movement (Sen and Khilar, 2006; Zhuang et al., 2003). In addition, application of MNPs in environmental remediation results in intensive dispersion of MNPs. For example, nano ZVI particles are now used for groundwater remediation. The efficiency of these particles is restricted because of their aggregation. Therefore, many studies were devoted to investigate effective methods to disperse nano ZVI. Water soluble starch (He and Zhao, 2005), hydrophilic carbon or polyacrylic acid delivery vehicles (Schrick et al., 2004), sodium carboxymethyl cellulose (He et al., 2007), and polymers (Saleh et al., 2007) are all used as organic coating to disperse nano ZVI. The transport of these suspended MNPs is of great research attention for both engineering application and risk assessment of MNPs. Although most of the studies considered a certain transport distance of MNPs in soil column, the limited MNP transport distance does not mean a zero risk of the retained particles. Even deionized water could rinse out the deposited MNPs (Jaisi et al., 2008). Therefore, the retained particles can be released with the change of pH, ionic strength, DOM concentration, temperature, and flow rate. The redispersion and transport of the retained MNPs in soil column should be investigated in future studies.
6.2. Transport of organic chemicals after adsorbed by manufactured nanoparticles Natural colloid facilitated transport of organic contaminants has been well studied. This line of research is summarized in several valuable reviews (de Jonge et al., 2004; Sen and Khilar, 2006). Although quantitative descrip tion of this process is still under investigation, the methodology applied in natural colloids can be used to study organic chemical transport carried by MNPs. MNPs, especially CNTs, could strongly adsorb organic chemicals and directly affect their environmental concentration and behavior. For example, breakthrough of PCB was not observed after 120 pore volume of leaching. However, in the mixture of PCB and fullerene, breakthrough was observed after seven pore volume. Importantly, the leaching curves overlapped for PCB and fullerene. This experiment provided clear evidence that fullerene could enhance the mobility of PCB (Tomson, 2007). One of the most important factors controlling the transport of organic chemicals as affected by MNPs is the rate of desorption. For example, if the
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desorption reaches equilibrium much faster in comparison to MNP trans port, the effect of MNPs on organic chemical transportation could be minimal. However, if the desorption rate is very slow, or negligible in comparison to MNP transport, MNPs may markedly enhance organic chemical transport (Hofmann and von der Kammer, 2009). Although the adsorption of organic chemicals on MNPs is being studied widely, few studies examine desorption, especially desorption kinetics. Lack of extensive information on desorption hinders our understanding on the effect of MNPs on organic chemical transport. Various parameters should be considered in predicting the environmental behavior of organic chemicals in the presence of MNPs. However, because of the limited data from literature, current transport modeling is based on many simplifications, including some important processes. For example, MNPs were assumed to have no interaction with the stationary phase when assessing MNP relevance to organic chemical transport (Hofmann and von der Kammer, 2009). Clearly, this assumption is not valid in most of the environmental conditions, because MNPs could be significantly retained in the matrix through which they pass (Darlington et al., 2009).
7. Environmental Exposure and Risk of Organic Chemicals and Manufactured Nanoparticles as Affected by Adsorption The adsorption of organic chemicals on MNPs can change the speci ation and mobility of organic chemicals in environmental matrixes, and the surface properties and the aggregation state of MNPs. These changes will directly affect the environmental risks of both organic chemicals and MNPs. Therefore, toxicity and exposure studies of MNPs should consider the presence of organic chemicals.
7.1. Uptake and toxicity of manufactured nanoparticles to organisms and the effect of organic chemical adsorption MNP dispersion by organic chemicals could decrease their aggregate size or even to individual particles, which may increase the penetration of MNPs through bio–nonbio interface. Thus, MNP toxicity may be increased. In addition, the surface properties of MNPs (such as redox reactivity) may be significantly changed after organic chemical coating. Thus, the attachment of MNPs on cell membrane and the electrons retaining by MNPs could all be decreased. All these processes could directly affect the toxicity of MNPs (Dong et al., 2007). On the other hand, the suspension stability was reported to be affected by biological activities. SWCNTs could be well suspended
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after being coated with lysophosphatidylcholine (LPC) (Roberts et al., 2007). Daphnia activity decreased LPC–SWCNT concentration, indicating a strong effect of Daphnia on the solubility of LPC–SWCNTs. The authors proposed that Daphnia could ingest the water containing LPC–SWCNTs and utilize the lipid coating as their food source. After being subjected to digestive enzymes in the gut tract, LPC molecules were removed from SWCNT surface and thus, the uncovered SWCNTs may form big aggre gates. The aggregated SWCNTs are not able to be taken up by Daphnia and dark precipitation was observed in the experiment, which is probably why the authors did not discuss about the toxicity of SWCNTs through uptake, but the accumulation of SWCNTs on the external surface of Daphnia. Similarly, other organisms (including grazing and filter feeding aqueous organisms) as well as biofilms may facilitate the removal of surface coating and cause precipitation of suspended MNPs. This biologically facilitated precipitation could decrease MNP toxicity (Fig. 6). Organisms may also react with MNPs and increase MNP dispersion or dissolution. For example, bacterial activity may promote the dissolution of ions from MNPs and increase the bioavailability of toxic elements (Ha et al., 2006). In this case, the risk from the released ions instead of MNPs
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Figure 6 Biological process may increase or decrease MNP toxicity. Biologically derived macromolecules could form organic coatings on MNP aggregates. The organic coating may facilitate the dispersion of MNPs and thus increase their mobility, which may consequently increase MNP environmental exposure and risk. On the other hand, the coated organic molecules may screen off MNP toxic effects. Organisms may also digest the organic molecules. The bioactivities may strip the organic coating. MNPs could reaggregate and settle down, which eliminate their toxic effects. However, organisms may also react with MNP surface and promote the release of some toxic ions.
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themselves increased. But natural organic coatings (environment derived macromolecules) may protect MNPs from biological activities and thus extend the existence of MNPs in the environment. Then, the risk of MNPs could be increased. The fate of MNPs in actual environments such as soil and water requires direct field experiments.
7.2. Release, bioavailability and toxicity of organic chemicals after adsorption on manufactured nanoparticles The bioavailability of organic chemicals usually decreased because of their adsorption on solid particles. For example, the toxicity of organic chemicals decreased significantly when they were adsorbed by black carbon (Knauer et al., 2007; Koelmans et al., 2006). However, because MNPs could be absorbed by organisms, various influences should be considered. If MNPs were aggregated and could not be taken up by organisms, the adsorption of organic chemicals on these particles would decrease the bioavailability of organic chemicals. However, if MNPs could be absorbed by organisms, the adsorption of organic chemicals on MNPs may increase the bioavailability. Further, the toxicity of organic chemicals is also dependent on the revers ibility of the adsorption. If desorption hysteresis is observed, the adsorbed organic chemicals may show limited toxic effect to organisms. However, if the adsorption is reversible, the concentrated organic chemicals may release in high quantity. Then, MNPs act like a concentrator/collector of organic chemicals (Trojan horse effect) and the environmental risk of organic chemicals could be enhanced distinctively (Yang et al., 2006b). The effects of MNPs on the toxicity of organic chemicals are dependent on the chemical properties. For example, the bioaccumulation of phenan threne increased with the addition of fullerene. However, the toxicity of pentachlorophenol decreased with the addition of fullerene. For other chemicals, such as atrazine and methyl parathion, the effect of fullerene on their toxicity was not significant (Baun et al., 2008). Therefore, the effect of fullerene on the toxicity of organic chemicals was not solely controlled by fullerene–pollutant interactions, but also dependent on the mechanisms of toxicity and the physiology of the tested organisms. Another important implication of this study is that the interaction mechanisms between organic chemicals and MNPs need to be incorporated into this type of toxic studies. As we have discussed in previous text, the adsorption/desorption hysteresis is the key process controlling the fraction of the bioavailable chemicals. The four chemicals may bind with MNPs with different strengths and the release behavior from MNPs could be varied substantially. This process could control the toxicity of the chemicals. However, extended discussion could not be presented from the limited information on this topic. It is interesting to note that uncoated alumina NPs could slightly decrease root elongation but phenanthrene coated alumina NPs did not
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(Yang and Watts, 2005). The authors excluded the possibility that changed NP aggregation size after phenanthrene loading contributed to the decreased toxic effect. Combining evidence from FTIR analysis and DMSO scavenging free hydroxyl radicals, the authors suggested that the loaded phenanthrene could change the surface characteristics of alumina NPs and decrease their toxicity. Therefore, in this study, the toxicity of both phenanthrene and Al NPs was decreased after adsorption. It is not unreasonable to speculate that the toxic effect may be strengthened in the presence of a secondary contaminant, which consequently results in synergistic effect between organic chemicals and MNPs. No evidence on this synergistic effect has been reported, yet.
8. Summary and Perspectives 8.1. Main points With the fast development and application of nanotechnology, MNP produc tion and discharge are increasing dramatically. From the discussion on MNP classification, application, and occurrence, it is expected that during their life cycle, MNPs can always find their way into the environment and transport in air, water, and soil systems. The interactions between organic chemicals and MNPs control greatly the environmental mobility, exposure, and toxicity and risk of both organic chemicals and MNPs. Among different types of MNPs, carbon based NPs show the strongest interaction with organic chemicals. Various mechanisms operate simultaneously, including hydrophobic interac tions, p–p bonds, hydrogen bonds, electrostatic interactions, and cation exchange. Accurate prediction of organic chemical adsorption on MNPs depends on quantitative measurements of the contribution from individual mechanisms to the overall adsorption. The latter clearly merit more investigations. MNP colloidal behavior describes their aggregation status and regulates their adsorption properties. Higher density of MNP surface hydrophilic func tional groups (mostly oxygen containing functional groups), lower ionic strength, and organic coating may facilitate MNP suspension. The suspended MNPs could transport farther than the aggregated ones and thus carry organic chemicals to a longer distance. NOM will interact with MNPs upon contact, thus rendering the MNP colloidal stability, adsorption properties, environ mental fate and transport, as well as their exposure and risks. NOM influences should be incorporated in the environmental risk assessment of MNPs. Adsorption of organic chemicals could suspend MNPs, decrease their aggregate size, increase their mobility, and the possibility of penetrating through biomembranes. On the other hand, the colloidal behaviors of MNPs also determine the leaching and risks of organic chemicals associated with MNPs. Therefore, the adsorption characteristics (with emphasizing on
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the contributions of individual mechanisms) and affecting parameters (such as pH, ionic strength, and temperature) should be outlined for organic chemical– MNP interaction in order to properly assess MNP environmental risks. This line of study is an opportunity and a challenge as well to environmental scientists.
8.2. Future directions If we need to accurately assess the environmental risk of this newly emerging material, MNPs, two lines of studies are suggested as displayed in Fig. 7. Firstly, systematic work needs to investigate MNP properties. This type of work focuses on obtaining MNP property parameters and their apparent toxic effect as well as toxicity mechanisms. Another line of study will be the macroscale environmental behavior, including environmental concentrations and distribution in different compartments. The goal of this
Source analysis and investigation Occurrence/distribution in the environment Environmental process and transport Quantitative environmental fate modeling Risk control Risk assessment
Sustainable green nanotechnology
Exposure route identification and simulation Toxicology study and risk simulations Simulation of environmental fate Characterization and quantification methods
Figure 7 Overall outlook on environmental exposure and risk assessment of MNPs. Two lines of study are suggested. The status of MNPs in the environment needs to be systematically studied for their source, pathways they enter the environment, occurrence, and distribution in environmental compartments. MNP transport among environmental media has to be quantitatively described for a quantitative environmental fate modeling. Another line of study is to develop proper MNP characterization methods (quantitative and qualitative). The mechanisms of MNP interacting with other pollutants as well as their colloidal behavior need to be examined based simulation experiments with different scales. Toxicity study and exposure experiments are fundamental to understand MNP negative effects on ecosystems and the public health. The above mentioned two lines of study should be integrated to comprehensively assess MNP environmental risks and thus the regulatory strategies and policies for sustainable green nanotechnology could be proposed. The interactions between MNPs and organic chemicals are involved in all these processes.
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type of study is to quantitatively describe MNP involved environmental processes. The knowledge of interactions between MNPs and organic chemicals and their environmental implications will facilitate or is advanced by the progresses of all the lines of research outlined in Fig. 7. For example, the development of MNP characterization technologies could improve our understanding on MNP properties, which consequently provide valuable information to explain adsorption data. On the other hand, the adsorption of organic chemicals on MNPs may change MNP surface properties (such as surface charge, surface smoothness and fractal dimension, redox potential, aggregate size, and dispersion) and consequently their environmental expo sure and risks. The information on the occurrence and fate of MNPs in the environment help us understand the extent and pattern that MNPs control organic chemical behavior, whereas organic chemical (including NOM) adsorption is an important process determining MNP colloidal behavior and transport. Therefore, studies on organic chemical–MNP interactions are fundamental for the whole framework and several urgently needed studies are discussed in the following paragraphs. To estimate the environmental behavior and adsorption characteristics of MNPs, it is essential to quantitatively describe their environmental occurrence and physical/chemical properties. Understanding the pathways that MNPs enter the environment during production, storage, application, and disposal (i.e., life cycle) is the very first step. However, because of the lack of reliable MNP quantification techniques and methods, this type of study is at its infancy. Up to date, we do not have enough information to make any accurate estimation of their environmental occurrence and distri bution. Several investigators tried to use mass balance calculation and simple distribution process to predict the source and behavior of MNPs (Gottschalk et al., 2009; Mueller and Nowack, 2008). These trials are the only possible method at this stage of research. What makes this line of study more difficult is that the properties of MNPs are diverse, such as particle size distribution, solubility, elemental composition, morphological and crystal structure, surface area, surface charge, impurities, and surface coatings. In addition, MNPs may undergo dispersion–reaggregation, redox reactions and other transformations. All these MNP properties and processes cause uncertainties in recognizing and determining MNP environmental behav ior (Isaacson et al., 2009; Tiede et al., 2009). A general perplexity in understanding organic chemical–MNP interac tion is the simultaneous operating of various mechanisms. Because different mechanisms may respond differently to a change in environmental condi tions, accurate prediction of organic chemical adsorption on MNPs is not possible without knowing the exact contribution of individual mechanisms to the overall adsorption. This review suggested several ideas to separately measure the contribution of different mechanisms, for example, normal izing adsorption coefficients with KHW or KOW, performing experiments in
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inert organic solvent, investigating adsorption as affected by pH and MNP functional groups, and conducting molecular dynamic simulations. It is accepted that MNP colloidal behaviors are controlled by NOM coating. Although several studies has been conducted in this direction, it is still unclear what NOM properties affect their coating on MNPs, and how and in what extent NOM coating decrease or increase organic chemical adsorption. Limited information is available on NOM fractionation in aqueous and solid phases after their adsorption on MNPs. Consequently, to comprehensively determine the distribution of a given organic chemical in aqueous residual NOM and MNP adsorbed NOM is difficult if not impossible. The extent of organic chemicals on controlling MNP mobility is deter mined by their ability to suspend MNPs, which is examined in several engineering applications, such as macromolecules to suspend ZVI (He et al., 2007; Saleh et al., 2007), but not from the point of environmental risk. The transport of organic chemicals by MNPs was evaluated borrowing the concept and techniques of organic chemical transport by colloids. How ever, a few important processes were ignored, such as the interaction between MNPs and stationary phase, kinetic desorption from MNPs, MNP reaggregation and resuspension. Carefully designed experiments emphasizing the difference between MNPs and traditional colloids are demanded. MNP dispersion affects their toxicity and most of the studies focus on this aspect. However, on the other hand, biological process may also change MNP aggregation state. Few studies recognize the importance of this topic. Thus, more studies are needed to examine the effect of biological processes on MNP surface properties and the change of their adsorption character istics, and to elucidate how MNP aggregation promoted by biological process is related with organism defense systems to these emerging pollutants. It is important to emphasize that the study on MNP environmental behavior and risk is not to restrict the development and application of nanotechnology. On the contrary, the goal is to build a guiding system for MNP risk control and promote the development of sustainable green nanotechnology. For this ultimate goal, many blanks are left to be filled. It could be very dangerous without knowing the flip side of MNPs before their wide application and disposal.
ACKNOWLEDGMENTS This research was supported by the USDA Hatch program (MAS00978) and NSF (CMMI 0531171), the National Scientific Foundation of China (40803034 and 40973081), and the Research Fund for Future Talent of Yunnan Province.
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C H A P T E R
F O U R
Restoring Soil Fertility in Sub-Sahara Africa Bekunda Mateete,* Sanginga Nteranya,† and Woomer Paul L.‡ Contents 184 186 188 192 192 193 211 220 221 222 225 226 228
1. 2. 3. 4.
Introduction Fertility Status of SSA Soils Impact of Smallholder Farming on Soil Fertility Technologies for Mitigating Soil Fertility Degradation 4.1. Diagnosis of soil fertility status 4.2. Soil fertility restorative technologies 4.3. Optimizing biophysical control measures 5. Continuing Concerns: External Controlling Factors 5.1. Participatory involvement 5.2. Driven by markets 5.3. Policy interventions 6. Lessons Learned and Way Forward References
Abstract Sub-Sahara Africa can overcome the soil fertility depletion that has resulted from decades of nutrient mining by small-scale farmers and threatens the region’s food security. Nutrient restoration is now technically feasible because its mechanisms are understood and the rural development community is alerted to this need. Rapid and inexpensive approaches of diagnosing soil fertility limitations are also becoming available and information generated is becoming systematically applied. For example, the recently initiated Africa Soil Information Service project aims at evaluating, mapping, and monitoring Africa’s soil qualities for better targeting of soil fertility management technologies to improve crop yields while enhancing the environment. Practical knowledge is available on nutrient management in small-scale farming systems that combines increased biological nitrogen fixation, utilizes agromineral resources such as phosphate rock, better uses organic resources, and more efficiently * Kampala International University, Nairobi Centre, Kenya Tropical Soil Biology Institute of the International Centre for Tropical Agriculture, Nairobi, Kenya Forum for Organic Resource Management and Agricultural Technology, Nairobi, Kenya
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Advances in Agronomy, Volume 108 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)08004-1
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2010 Elsevier Inc. All rights reserved.
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applies mineral fertilizers. The new approach to managing soil nutrients, recognized as integrated soil fertility management, aims to increase food production through strategic combination of traditional and new technologies and is being stimulated through increased availability and more profitable use of mineral fertilizers by Africa’s poorer farmers. This is building on already existing sparks of hope for restoring soil fertility in sub-Saharan Africa derived from such examples as the increasing adoption of the zaı¨-type of pitting system originated in drier parts of West Africa which exemplifies the beneficial effects of integrating harvesting of water and applying nutrient sources at each planting station so as to increase yield in a region where both necessities are key limiting factors. Nitrogen fixation by indigenous and introduced legumes combined with improved agronomic practices has shown potential for kick-starting selfmultiplying improvements in soil productivity. Such successes will be accelerated by broader initiatives which improve rural infrastructure, increase accessibility of inputs, improve marketing facilities, and make reinvestment into farming more productive and sustainable. Indeed, experience indicates that investments in farming and, by inference, soil fertility conservation are made when economic returns from smallholder production are sufficient to do so. So, while technical advances leading to improvements in farming practice must continue, policymakers must also recognize that agriculture ultimately forms the basis for economic recovery and act upon past promises to invest in agriculture, including the restoration of nutrient-depleted soils. Investments must address factors that have impacts both on the broad reforms for provision of services such as marketing and trade, as well as those directly constraining the poor farmers such as capacity to access and efficiently apply fertilizers.
1. Introduction Failure by smallholder farmers to intensify agricultural production in a manner that maintains soil productivity is the main cause of land degrada tion in sub Saharan Africa (SSA). This decline is not out of their own volition, but rather the consequence of striving for household well being under difficult circumstances. The social syndrome where diminishing availability of lands, inherent low fertility, continuous soil erosion, and continuous nutrient removal without replenishment results in a spiraling decay in productive capacity and a diminished resilience of the soil system to provide a suitable medium for crop growth (Woomer and Muchena, 1995). The magnitude and threats of the decline have been highlighted in a series of publications quantifying nutrient depletion, identification of most limit ing nutrients, changes in soil chemical properties, and lowering crop yields (Buresh et al., 1997; Smaling, 1998). In the case of Western and Central Africa, for example, IFAD (2002) reports indicate that land degradation from extensive agriculture, deforestation, and overgrazing has reached
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alarming levels; about 50% of the farmland suffer soil erosion and up to 80% of rangelands are degraded. The major threat is on the economic and social stability of the already impoverished countries in the region; less food is grown, production of cash crops and incomes are endangered, and land conflicts emerge (FAO, 2001). As a result of these consequences, it is now more widely appreciated that protecting and improving the soil makes economic and social sense. In 2001, at the founding of the African Union’s New Partnership for Africa’s Development (NEPAD), African heads of state declared that improved agricultural performance is a prerequisite of economic development on the continent. NEPAD’s (2003) Comprehen sive Africa Agriculture Development Programme (CAADP) is a framework of goals, principles, and investment priorities that were developed to guide agricultural development. CAADP is premised on the judgment that agri culture led development is fundamental to cutting hunger, reducing poverty, generating economic growth, and reducing the burden of food imports. In order to achieve these, one of its areas of primary action is ‘‘building up soil fertility and the moisture holding capacity of agricultural soils . . . so as to provide farmers with opportunities to raise output on a sustainable basis and contribute to the reliability of food supplies.’’ The recommendation of the Africa Fertilizer Summit (2006) ‘‘to increase the fertilizer use from the current 8 to 50 kg ha 1 nutrients by 2015’’ reinforces the role of fertilizer as a key entry point for increasing crop productivity and attaining food security and rural well being in SSA. Hartemink (2006b) defined soil fertility decline to include nutrient depletion (greater removal than addition of nutrients), nutrient mining (removal of nutrients without inputs), acidification (decline in soil pH), the loss of soil organic matter (SOM), and an increase in toxic elements such as aluminum. Soil fertility depletion and nutrient mining (Smaling et al., 1997) are the terms that have been most debated in Africa over several decades, culminating in the above mentioned Abuja Declaration by the Sub Saharan Africa Heads of State (Africa Fertilizer Summit, 2006). This declaration was a long overdue policy reversal from the Structural Adjust ment Programs that caused subsidizing of fertilizer imports to be abolished, and the consequent uncontrolled increase in fertilizer prices that placed them beyond the reach of most farmers. It is also a realization that the rapid population growth in Africa requires extra food which cannot be supported by conversion of new lands to agriculture, as in the past, but rather through agricultural intensification in current croplands. Smallholder farmers are at the center of the soil fertility restoration processes (Fig. 1). Their decisions (A) to utilize technologies (B) to improve soil fertility are guided by the overall benefits that will accrue from produc tion. The technologies must be adapted to the biophysical factors (C) that control yield and nutrient cycles, and informed by the socioeconomic (D) realities so as to be able to cause positive development. Given the extent
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B. Soil fertility restoration implementation (use of fertilizers and agrominerals, organic resource management, resource integration) C. Biophysical factors (sound agronomic practices, soil and water conservation)
Iterative process
D. External controlling factors (market developments, enabling policy, outreach services)
A. Farmer decision-making (monitoring performance, analysis and planning)
Figure 1 Conceptual diagram of the soil fertility restoration process and the controlling factors.
of nutrient depletion in SSA (Smaling et al., 1997), an increase in plant nutrients of 50 kg ha 1 yr 1 is unlikely to restore decades of nutrient mining. An alternative is to focus more on the efficient application of farmer available input resources to supply nutrients where and when they are needed, and this requires knowledge about the soils and its technological application. These issues form the basis of this review; we provide back ground to issues related to soil fertility degradation with focus on nutrient depletion, highlight different strategies that have been developed and deployed to overcome nutrient limitations, identify challenges that farmers face adopting these strategies and suggest options that could serve to make these strategies more effective in restoring soil fertility.
2. Fertility Status of SSA Soils Most of Africa’s ability to produce food is determined by access to inherently fertile soils because more intensive forms of managing fertility, particularly regular nutrient replacement with mineral fertilizers, are too seldom practiced (Buresh et al., 1997). About 15 years ago, African soils with little or no soil constraints to production comprised 34% of croplands
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(Woomer and Muchena, 1995), but this proportion has likely declined due to continuous mismanagement. According to Eswaran et al. (1997) 55% of the land area in Africa is unsuitable for sustainable agriculture but even those lands with high (16%) to medium (13%) quality soils offer limited opportu nity for highly productive commercial farming due to population growth and competition with other land uses. The remaining 16% low quality soils are a result of inherently poor soil properties and human induced land degradation. These soils require rehabilitation and sustainable maintenance; otherwise the percentage of low quality soils will continue increasing. The differences in the inherent quality of soils are determined by age, parent material, physiography, and climatic conditions. The continent has some of the oldest soils resulting from intense cycles of weathering, erosion, and leaching. Entisols (FAO equivalent: Arenosols) and Alfisols (Lixisols) are the main soils in semiarid Africa (Table 1). Entisols have low water holding capacity and nutrient content, are weakly structured, and are prone to erosion. Alfisols have a clay accumulation horizon, low capacity to store plant nutrients, and tend to acidify under continuous cultivation. Vertisols have a high content of swelling clays and low phosphorus (P) availability. The mean carbon (C) stock in the top meter of African soils is estimated at between 64,000 and 67,000 kg C ha 1 (Smaling and Dixon, 2006), compared to the global mean stock of between 109,000 and 116,000 kg C ha 1, another indication of the low fertility in the highly weathered soils. Soils in semiarid Africa are generally low in organic carbon (C stock range ¼ 42,000–45,000 kg C ha 1) and total
Table 1 Major soil orders in the different agroecological zones of sub-Saharan Africa and their nutrient-related constraints (adapted from Sanginga and Woomer, 2009) Agroecological % of Major soil orders zone area (FAO) Major nutrient constraints
Arenosols, Lithososls, Regosols Lixisols, Ferralsols Ferralsols, Acrisols
Low available soil P, soil acidity, low water holding capacity
7
Ferralsols, Nitisols
Soil acidity, low available soil N and P
7
Ferralsols, Andosols
Soil acidity, low available soil P
Lowland dry savanna
36
Lowland moist savanna Lowland humid forest Mid altitude moist savanna Highland moist forests
17 15
S, Zn deficiency under intensive cultivation, low available N and P Soil acidity, low available soil P
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nitrogen (N) because of low biomass production and a high rate of decompo sition (Mokwunye et al., 1996). These characteristics indicate how nutrient management could be approached, for example, the P requirement for maxi mum yield on soils in the semiarid areas is often low (Mokwunye, 1979) because they contain low activity clays and consequently low capacity to occlude added P. These soils’ weak, often sandy structure presents problems of efficient use of applied N because of high rates of loss through leaching. In subhumid and humid SSA, the dominant soils are Alfisols, Ultisols (Niti sols), and Oxisols (Ferralsols). Ultisols and Oxisols have little or no weath erable minerals and a clay fraction containing kaolinite as well as iron and aluminum oxides and hydroxides. They have high P sorption and low cation exchange capacity, factors which require balanced fertilization with several nutrients. Bationo et al. (2006) suggested that the different dominant soils within agroecological zones of SSA demonstrate representative trends in moisture and nutrient storage capacity, organic matter content and nutrient depletion. Sanginga and Woomer (2009) expanded upon these trends (Table 1) but also highlighted the spatial heterogeneity occurring within local catchments and farms.
3. Impact of Smallholder Farming on Soil Fertility Stakeholders engaged in the process of restoring soil fertility must have a set of agronomic, socioeconomic and environmental goals to guide the alloca tion and recycling of nutrient inputs. Too often, smallholder farmers in SSA do not benefit from proven agricultural technologies primarily because their field practices are driven by subsistence rather than market oriented agriculture, and they rely upon locally collected rather than purchased farm inputs. Therefore, few ‘‘modern’’ soil management technologies have been adopted by the smallholder farmers, in part because of their high cost relative to crop price, and economic returns to farming have remained low (Woomer, 2007). The traditional farming practices of shifting cultivation and fallowing that allowed for adequate restoration of fertility during the resting phase have become less feasible with increasing populations and this has driven encroachment on forests and other marginal lands as a means of producing more food (Hauser et al., 2006). These forces exacerbate continued depletion of soil fertility even after it is recognized as an ominous threat to the food security of SSA. The impacts of smallholder induced nutrient depletion express them selves in form of continued declines in crop yields, which can be abrupt or gradual depending on soil type (Fig. 2). For example, in West Africa, only 3–4 years of cropping sandy soils without nutrient inputs were required for yield to decline to 50% (Bekunda et al., 1997). The same was observed over
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4.5 4.0
Maize yield, E. Africa
3.5
Yield (kg ha–1)
3.0 2.5 2.0
Sorghum yield, W. Africa
1.5 1.0 0.5 0.0 1950
1960
1970 1980 Experiment year
1990
2000
Figure 2 Crop grain yield following continuous cropping on same pieces of land. (Source: Bekunda et al., 1997.)
8 years on clayey soils in East Africa. The rate and proportion of nutrients lost is normally greater in sandy soils largely because SOM particles are less protected from microbial decomposition in sandier soils than in loamy or clayey soils (Woomer and Swift, 1994). Consequently, approaches to nutri ent restoration must be tailored to meet these variations in soil properties and management conditions. Overall, there has been a continuous decline in soil nutrient reserves and productivity over time across all African sub regions, with most pronounced decline in Ethiopia, Kenya, Malawi, and Rwanda due to extensive hillside cultivation (Smaling et al., 1997). A special conference on Soil Fertility Management in Sub-Saharan Africa held in Nairobi, Kenya in 1997, resulted in a treatise on nutrient balances as an indicator of crop and livestock productivity in SSA agriculture (Agricultural Ecosystems & Environment, Vol. 71, 1998). It is a summary of research work in Africa over the 1980s and 1990s utilizing the concept of budgeting as a means of identifying nutrient balances resulting from inflows and out flows. While some inherent uncertainties in the methodology were acknowledged, the results were still disquieting, suggesting average annual depletion rates of 22 kg nitrogen per hectare, 2.5 kg phosphorus per hectare, and 15 kg potassium per hectare at continental level. Intensively cultivated highlands in East Africa lose an estimated 36 kg N ha 1 yr 1, 5 kg P ha 1 yr 1, and 25 kg K ha 1 yr 1 while croplands in the Sahel decline by 10, 2, and 8 kg ha 1, respectively. In Rwanda and Malawi,
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nutrient depletion rates were more than three times the continental average values. Furthermore, continental rates are four times higher than the aver age 8 kg ha 1 yr 1 consumption of mineral fertilizers (Africa Fertilizer Summit, 2006). Figure 3 provides an indication of how nitrogen balances may vary within various land uses and the underlying causes of net losses (Van den Bosch et al., 1998). This figure also serves as an indication of required investment in soil management; note that more fertilizer nitrogen inputs were applied to cash crops (tea and coffee) compared to traditional staples (maize and beans). Napier grass fodder and pasture systems support livestock operations with greater potential for both income generation and nitrogen recycling through manures. Nutrient balances provide a meaning ful context within which to organize what is known about a system’s biogeochemical cycles, put nutrient pools and fluxes into perspective (Hartemink, 2006a,b) and help guide soil fertility management research and land manager decision making (Gachene and Kimaru, 2003). Nutrient depletion rates are largely regulated by site specific field con ditions. Smallholders typically produce several different food and cash crops on small plots that are managed according to available input and labor resources (Tittonell et al., 2005; Vanlauwe et al., 2006a,b), as well as prevailing socioeconomic environments (Walker et al., 2002), that eventu ally result in localized soil fertility and crop productivity gradients. Between farms, differences arise from diversity in household resource endowment with greater soil fertility on farms of wealthier farmers (Crowley and Carter, 2000; Shepherd and Soule, 1998). Several other factors also differentiate resource endowment with land degradation, including farm size, level of education, farming experience, land tenure, distance to markets, off farm income, access to credit, and technical knowledge (Browder et al., 2004). Ominous consequences of nutrient depletion include biodiversity losses, sedimentation within watersheds, and pollution of water bodies (Sanginga and Woomer, 2009). There is also the link between decreased agricultural productivity resulting in lower on farm employment driving rural to urban migration. These migrants too often find themselves in poorly paid, menial jobs surrounded by urban ills and would willingly work closer to home if greater opportunity existed in rural areas (Woomer et al., 1998). The foregoing discussion is evidence that concern over soil degradation within smallholder farming systems in SSA is justified. Over the last half century, attempts were made to generate and put into practice knowledge on the management of these soils. However, the impact is still very limited. It is still considered that the most important on site effects of smallholder agriculture are the loss of organic matter and reduced nutrient stock and buffering capacity. The next section describes the strategies that researchers, promoters, and practitioners of soil fertility management have employed over time, and how the lessons learned provide a platform for potential success in restoring Africa’s soil fertility.
250
IN 1: Chemical fertilizer IN 2: Residues and manure Immissions FI 3: Residues/napier
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FI 4: Grazing FI 5: Animal manure FI 6: Home consumption Out 1: Products
50 kg ha–1 yr–1
Emissions
0
–88
Balance
–31
–50 –70 –88
Immissions: • Atmospheric deposition • N-fixation
–90 –126
–150
Emissions: • Leaching • Gaseous losses • Erosion
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–250 n = 13
n = 11
n = 14
n = 33
n = 13
n = 11
Tea
Coffee
Maize
Maize/beans
Napier
Pasture
–350
Figure 3 Nitrogen flows and balances for six crop systems in East Africa. Number of field observations are denoted by n. (After Van den Bosch et al., 1998.)
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4. Technologies for Mitigating Soil Fertility Degradation 4.1. Diagnosis of soil fertility status The starting point in the process of restoring and managing soil fertility is assessing the nutrient status based upon the hierarchy of limiting nutrients, the expected crop response to applying the limiting nutrients and the expected economic returns from the management interventions (Sanginga and Woomer, 2009). Traditional laboratory methods of soil testing were adapted to African conditions to provide commercial farmers and extension agents with information on nutrient needs and other limitations such as soil acidity and salinity (Okalebo et al., 2002). However, the analytical services in SSA are usually not adequate; they are offered by few institutions, being mainly research centers and universities that sometimes have limited manpower, equipment and reagent supplies. Moreover, the vast majority smallholders requiring these services have no capacity to pay for them, and even if they could the complexity of farming operations confounds representative sam pling. In response to this challenge, cheaper, more rapid and mobile approaches using soil test kits have been developed for use by farmers or extension agents. One distinct advantage with this approach is that the extension agent actively engages the farmer in the assessment of the fertility status and in the discussion of the available management options where necessary. The kits have been used as determinants of indicators of technical knowledge in the process of integration with ethnopedology to form an expanded ‘‘shared’’ knowledge on soils and their management (Barrios et al., 2006). The use of infrared spectroscopy for rapid analysis of soil quality and organic resources has been a major breakthrough in field diagnostics (Shepherd and Walsh, 2002; Shepherd et al., 2003). The technology can be combined with GPS and GIS tools to predict quickly and inexpensively how improved crop varieties will respond to fertilizer at a given location. Impacts are expected from application of these new quantitative methods through better understanding of the complexity and diversity of local soils and also serving as tools for monitoring soil quality for environmental protection and supplying the information necessary for making policy decisions that will help the rural poor manage soils better, boost crop productivity, achieve food security, and protect the environment better. Visual deficiency symptoms expressed on plants are also used to evaluate soil fertility. They appear when the metabolic roles relating to the deficient nutrient are not satisfied (Sanginga and Woomer, 2009). While this is a rapid diagnostic method, it has certain limitations: first is that symptoms can be confounded with conditions like moisture stress, water logging and plant diseases which can lead to misdiagnosis, second is that by the time the visual
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symptoms are expressed, physiological damage has already occurred, and third is that it is difficult to formulate recommendations based on visual symptoms alone. However, research into the comparison of plant leaves to color charts to determine nitrogen needs free of the above limitations is being pursued in cereals (Shukla et al., 2004) and may in future be found suitable for application across the different agroecosystems in Africa. Indeed, timing nitrogen topdressing to the slightest paling of crops, particularly after heavy rains is a powerful field skill required by smallholders seeking to produce crop surpluses. Field tests reveal that the most limiting nutrients in SSA are N and P (Bekunda et al., 1997; Woomer and Muchena, 1996). For example, in a series of fertilizer trials conducted throughout the Kenyan highlands, N and P deficiencies were reported in 57% and 26% of the cases, respectively (Kenya Agricultural Research Institute, 1994). However, K, Ca, Mg, S, and micro nutrients may also require attention once N and P requirements are met. Responses to K fertilization are common in sandy savanna soils (Ssali et al., 1986). Kumwenda et al. (1995) demonstrated that Zn and S supplementation targeted to deficient soils improved N fertilizer efficiency and increased maize yields by 40% over standard N and P recommendations alone. Before market liberalization, all compound fertilizers in Zimbabwe were required by law to contain S, Zn, and B to deal with inherent soil deficiencies. To a limited extent, the response of soils to agricultural activities has also been diagnosed by monitoring changes in soil chemical properties over time or comparing them to those of adjacent land under a different land use system (Ekanade, 1988; Hartemink, 2006a,b). Soils with largest nutrient contents before land clearing tend to have proportionately larger losses when subjected to permanent cropping (Kotto Same et al., 1997).
4.2. Soil fertility restorative technologies There are several technical solutions to soil fertility restoration, many with similar fundamental principles, but their successes depend upon practical relevance, efficiency of application, and acceptance by the farmer. During the mid 1990s, a conceptual approach to increasing food security and poverty alleviation in humid and subhumid Africa, the replenishment of soil fertility as an investment in natural resource capital, was proposed (Sanchez et al., 1997). The underlying principles were that (i) enhancement of long term food security requires offsetting nutrient losses suffered by the smallholders, (ii) nutrient depletion is reversible through use of diverse nutrient resources available, and (iii) combinations of P fertilizers and organic inputs can replenish soil N and P nutrient stocks. The success on N replenishment was dependent upon biological nitrogen fixation (N from the air) and utilization of available organic materials, and P replenishment dependent upon fertilizer resources, targeting the ample phosphate rock (PR) resources
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(P from the rock) applied directly or after processing (Van Straaten, 2002). Supplementation with mineral fertilizers for these and other nutrient ele ments (others as needed from the bag) would be applied as strategic interven tions since smallholder farmers lacked the capital and access to credit for investing in their use. No tested guidelines for this approach were devel oped but the basic principles behind the different proposed amendments have been utilized in soil management in several other ways. 4.2.1. N from the air The importance of BNF in Africa is reflected in its annual contribution to the reactive N on the continent, amounting to about 27.7 Tg during the 1990s (Galloway et al., 2004), and being more than 80% of the total N introduced. Although only 1.8 Tg N yr 1 were fixed during cultivation, it is about half as much as that introduced from fertilizer importation and manufacturing, and proportionally higher in the SSA region where fertilizer use is much lower. The most important N2 fixing agents in agricultural systems are the symbiotic associations between crop and forage/fodder legumes with the microsymbiont rhizobia but other agents exist, including Azolla cyanobacteria, cereal associative and endophytic bacteria, and free living bacteria (Giller, 2001). Smallholder farmers traditionally practiced agroforestry and included legumes in rotation or intercropping, but these stopped being adequate for soil productivity maintenance as the demands for food grew. Much research has, therefore, been directed toward identi fying means of intensifying legume cultivation so as to enhance the benefits from N2 fixation as well as improve soil physical conditions, increase organic inputs, and conserve nutrients. In a conference of the African Network (AfNet) for Soil Biology and Fertility held in Yaounde, Cameroon on integrated soil fertility manage ment (ISFM) (Bationo et al., 2007), 41% of the papers presented under that theme represented research findings, many with promising messages, on the following systems: (i) improved fallow where selected nitrogen fixing woody or herbaceous plants are purposefully grown on cropland to allow faster system regeneration, recycling of nutrients, and addition of nitrogen; (ii) intercropping systems where nitrogen fixing plants are integrated with crops in both time and space; (iii) relay systems where the nitrogen fixing plant shares space with the other crops but usually planted to allow their primary growth periods to differ; (iv) dual purpose legumes that are grown in intercrop or rotation with cereals both for production of grain and provision of BNF benefits; and (v) biomass transfer where the organic material is transported from its ex situ site to the cropping area. Over 40 legume provenances were studied in several African countries with major staple cereals, maize, sor ghum, and millet, employed as the main test crops. Outreach in legume technologies was presented in 8 out of 22 papers while legumes were a main
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subject in 3 out of the 9 cross cutting chapters. A total of 105 papers were presented. Grain legumes in Africa seasonally fix about 15–210 kg N ha 1 (Dakora and Keya, 1997) and, according to Giller (2001), net soil N accrual from effectively recycled legume residue can be as much as 140 kg ha 1. But the increased yield of crops grown as intercrops or in sequence with legumes at research level (Table 2) shows different degrees of the beneficial effects of legumes. The average grain yield response was only about 50% of the already low crop yields. On the poor soils, the legumes themselves may not attain their biological production potentials. The prospects for legume intensification by smallholders are therefore likely to depend more on improving their ability to reach their genetic potential and integrating them with other approaches to soil fertility restoration. Nitrogen fixation by legumes results from a stepwise sequence of events that, if properly characterized, can permit reliable forecasting of where and when it will occur (Fig. 4). BNF is first driven by the symbiotic plant’s demand for nitrogen as a growth requirement. For example, soybean requires approxi mately 100–300 kg of N per hectare to achieve maximum yields (Giller, 2001), nitrogen may be obtained from the soil, as fertilizer or as products of nitrogen fixation. In general, applications of more than 25 kg N ha 1 directly to the legume crop suppress BNF but starter nitrogen at rates of 10–20 kg N ha 1 may promote early root growth and photosynthate supply resulting in increased nodulation. In some cases, even small amounts of applied N appear deleterious to BNF. Thus, the availability of mineral nitrogen represents an initial condition that may either preclude or promote the demand for BNF depending upon soil fertility and fertilizer management. Three situations can be identified when introduction of rhizobia is necessary to establish nodulation and effective nitrogen fixation in legumes: (1) where compatible rhizobia are lacking; (2) where the population of compatible rhizobia is insufficient to initiate rapid nodulation; and (3) where the indigenous rhizobia are ineffective or less effective than elite inoculant strains. Simply observing ‘‘poor’’ nodulation on a field grown legume is not clear evidence that these conditions apply because of the environmental constraints which can interfere with nodulation, and the difficulties of recovering nodules on deeper roots. Benefits from inoculation are better understood by conducting need to inoculate trials in the field in which noninoculated plots, inoculated plots, and plots fertilized with sub stantial amounts of N are compared (Date, 1977), keeping in mind that if legume performance is not improved by N fertilizer, then other factors are limiting and inoculation is unlikely to improve yield unless corrected. The likelihood of responses to inoculation can also be inferred by enumerating the population of rhizobia in the soil using an appropriate trap host (Thompson and Vincent, 1967; Woomer et al., 1990). If there is a small population of effective rhizobia (<20–50 cells per gram of soil) then it
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Table 2
Grain yields from controls and relative yield gain or loss resulting from different legume management treatments Control Yield (t ha 1)
t ha 1
Percent
3.7 1.7 2.2 0.93 1.52 1.57 1.50 0.78 3.7 2.0 1.2
308 142 183 48 80 82 79 41 132a 71a 43a
4.0 2.3 1.8
143a 82a 64a
0.45 0.73 2.65 0.83 0.14
0.51 0.31 0.10 1.16 0.94
113b 42b 4b 141 671
2.55
0.67 1.46
26 57
Site
Legume
Management
Domboshawa, Zimbabwe
Sesbania sesban Acacia angustissian Cajanus cajan Crotalaria sp. (n ¼ 2) Canavalia ensiformis Mucuna pruriens Lablab purpureus Tephrosia vogelii Tephrosia vogelii
2 year improved fallow
1.2
6 months green manure
1.9
9 months fallow Intercrop Relayed intercrop (45 days) 9 months fallow Intercrop Relayed intercrop (45 days) Rotation
2.8
Mubende, Uganda
Bambui, Cameroon
Crotalaria juncea
Fashola, Nigeria Shika, Nigeria Davie, Togo Farako, Burkina Faso Sadore, Niger
Vigna unguiculata
Nyabeda, Kenya
Mucuna pruriens Soybean
Rotation, millet test crop Rotation
Yield response
Farako, Burkina Faso Kirinyaga, Kenya
Samanko, Mali
Muheza, Tanzania
Western Kenya
Arachis hypogea Mucuna pruriens Crotalaria ochroleuca Lablab purpureus Indigofera astragalia Crotaralia sp. Tephrosia vogelli Tephrosia candida Sesbania sesban Cassia sieberiana Cajanus cajan Gliricidia sepium Casuarina junghuniana Faidherbia albida Lablab purpureus Crotalaria sp.
Green manure
0.83 0.75
Short duration fallows (one season), sorghum test crop 2 year fallow, sorghum test crop
0.54
Intercrop: coppicing/ pollarding
1.44
Relay (n ¼ 63) Fallow (n ¼ 73)
1.48 (n ¼ 70)
Unless stated otherwise, maize was the test crop. (Compiled from different chapters in Bationo et al., 2007.) a Mean for two sites. b Mean for eight genotypes. c Mean for 2 years. d Mean for three sites. e Mean for three seasons.
0.57
0.90 0.40 0.05 0.20 0.47 0.34 0.36
108c 51d 6 26 87 62 67
0.80 1.54 0.50 0.68 0.66 0.55 0.67 0.45 0.79
140 270 88 119 45e 37e 46e 30e 41e
197
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Nitrogen
Rhizobia
Crop development
Available soil nitrogen
Indigenous rhizobia
Abiotic growth conditions
Crop demand for nitrogen
Infection and nodulation
Symbiotic N demand
Applied nitrogen
Inoculant rhizobia
Symbiotic N fixation
Biotic stress conditions
Figure 4 The stepwise sequence of factors that determine symbiotic nitrogen fixation in the field.
400
Yield increase (%)
300
Larger inoculant dose More competitive strains
200
More soil nitrogen Nitrogen less limiting 100
0 0
10
100
1000
Rhizobia per g soil
Figure 5 The relationship between indigenous rhizobia and inoculation response (based upon Thies et al., 1991).
is likely that a yield response to inoculation will be found (Singleton and Tavares, 1986; Thies et al., 1991). A simple approach was developed to predict the likelihood of inoculation responses based on the soil N and initial number of indigenous rhizobia (Fig. 5). If compatible rhizobia are absent, nodulation and BNF are likely to increase in proportion to the
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number of rhizobia applied in the inoculum (Brockwell et al., 1989). The characteristics of indigenous rhizobia and the delivery of inoculants also affect the host symbiotic response (Singleton et al., 1992). To counter this competition from indigenous rhizobia and unfavorable soil conditions, land managers must deliver a minimum dose of inoculant rhizobia. A few hundred cells per seed is sufficient to result in infection by inoculant strains under favorable conditions with small background indigenous populations of rhizobia, but it is possible to greatly exceed this dose (to many thousand cells) based upon the amount and population density of inoculants applied to the seed (FAO, 1985). On the other hand, the presence of a large indigenous population of compatible rhizobia does not necessarily preclude response to inoculation if competitive and highly effective strains are intro duced in high quality inoculants. A good example is observed in Brazil, where responses to reinoculation resulting in yield increases are observed even in soils with 1 billion cells per gram (Hungria et al., 2005, 2006). Infection by rhizobia and subsequent early nodulation are important physiological stages, but they do not assure BNF because the crop must continue to grow in a manner that permits a steady flow of assimilates to the nodules. Both abiotic and biotic constraints to crop growth may reduce BNF (Fig. 5). If N is not the limiting factor to crop growth, rather some other essential nutrient is in least supply, or if toxicities or physical constraints (such as drought) occur, then BNF becomes greatly reduced. Furthermore, the crop must remain healthy. Plants infested with insects or disease have few surplus assimilates available to support nodule function. Some pests and disease specifically target nodules (nodule feeding beetles) and their resident bacteroids (phage virus). A preliminary assessment of rhizobia in soils of East and Southern Africa (Table 3) suggests that their population sizes vary between ecological zones and land use but often occur below the threshold that precludes legume response to inoculation (Woomer et al., 1997a). Furthermore, while Bradyrhizobium sp. has widespread distribution, those that nodulate soyabean are rare and few. B. japonicum population sizes fell far below the threshold of 50 cells per gram of soil in 94% of the locations examined. This observation is based upon the findings of the Rhizobium Network for East and Southern Africa (RENEASA) network assessment of indigenous rhizobia at 47 loca tions across eight countries using plant infection counts. Assuming that nitrogen is the limiting constraint to crop growth at these sites, it is likely that a response to inoculation would be widespread. In some locations with a history of inoculated soyabean cultivation, however, large populations of B. japonicum were observed, suggesting that introduced rhizobia can colonize cultivated soils. If promiscuously nodulated soyabean were cultivated, those that nodulate readily with indigenous bradyrhizobia, a response to inocula tion likely be observed at slightly more than half of these sites.
Table 3
Indigenous rhizobia present in soils of different African countries and climates (Woomer et al., 1997a) B. japonicum
Climate Country
Moisture
Elevation
Sites n
Bradyrhizobium sp. (Cells per gram of soil)
Cells per gram of soil
Frequency
Ethiopia Kenya Kenya Kenya Kenya Mozambique Rwanda Tanzania Uganda Zambia Zimbabwe
Subhumid Semihumid Semiarid Subhumid Humid Semiarid Humid Subhumid Humid Semihumid Semiarid
Highland Lowland Midland Uplands Highlands Lowland Highlands Midlands Midlands Midlands Uplands
2 1 6 3 5 4 2 6 9 4 4
74 4 23 3370 15 10 6 27 1627 177 4368
0 0 4 5 <1 0 0 0 2 5 681
0 0 0.16 0.33 0.40 0 0 0 0.11 1.00 0.80
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Legume hosts differ in the range of partners with which they form symbioses. At one end of this range are legumes such as chickpea (Cicer arietinum) which nodulate with a restricted number of rhizobial strains and are thus considered to be specific in their nodulation requirement. At the other end is cowpea (Vigna unguiculata) which is extremely promiscuous (or nonspecific), nodulating with diverse rhizobia. Indeed, tropical rhizobia constitute a highly diverse group of both fast and slow growing types with a wide range of symbiotic specificities (Giller, 2001) and legumes with more specific requirement for rhizobia, such as soybean and chickpea, more often require inoculation. This can be achieved using commercially available rhizobial inoculants already tested in African conditions. However, inoculant use in smallholder farming systems of SSA is generally low due to the poor presence of inoculant infrastructure and expertise in the region. Commercial inoculant production does occur, however, in Kenya, South Africa, and Zimbabwe and efforts are underway to better target smallholder farmers as clients for market expansion. In many African farming systems, less than 5% of farm area is planted to legumes (Giller et al., 2006; Ojiem, 2006; Ojiem et al., 2006). This paucity is largely the result of weak marketing infrastructure and low market prices for legumes, conditions that are being addressed through numerous rural development initiatives. When incentives for increased legume production are in place, each incremental increase of the farm area planted with legumes will significantly increase the amount of nitrogen inputs into the farming systems. In combination with efforts to select grain legumes for BNF, and improvement in inoculant delivery systems, it is projected that inputs from BNF can increase from approximately 35 kg N ha 1 to over 90 kg ha 1 resulting in increased total amounts of N per farm from approximately 8–30 kg N yr 1 across the whole area of SSA. 4.2.2. P from the rocks Apart from nitrogen which can be obtained from atmospheric N2 through BNF or the Haber Bosch chemical processes, all other agro nutrients are from rocks. Africa has about 4.5 billion tons of PR in deposits distributed across the continent (Fig. 6), some of which are reactive enough to constitute a direct application P source (van Straaten, 2002). This is a potentially cheaper form of replenishing soil P by smallholders with limited resources. The PR deposits are igneous, sedimentary or biogenic in nature and with different P contents and agronomic effectiveness. The degree of agronomic effectiveness can be used as a guide to PR use in direct application. For example, van Straaten (2002) proposes that PRs with a high neutral ammonium citrate (NAC) solubility of >5.9 are suitable for most annual and perennial crops growing on soils with pH < 5.5, those with medium NAC solubility of 3.4–5.9 are suitable for low P demanding crops (including many legumes), while those with NAC solu bility of <3.4 are mainly suitable for perennial crops. Knowledge on their
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Tunisia
o
cc
ro
Mo
Algeria
Egypt
Libya
Mauritania
Mali Niger
Senegal
Nigeria
da Democratic Republic of the Congo
Somalia Republic
Kenya
an
Togo Equatorial Guinea
Ethiopia Central African Republic
Ug
Liberia
Ivory Coast
Ga bo Cam n er oo Rep n the ublic Con of go
Guinea
Sierra Leone
Djibouti Sudan
Chad
Benin
na rki Buaso E
Gha na
Gambia GuineaBissau
Sedimentary
Tanzania
Igneous
Rwanda Burundi Malawi
Angola
dag Ma
M
Botswana
asc
biq am
Zimbabwe
oz
Namibia
ar
ue
Zambia
Swaziland South Africa
Lesotho
Figure 6 Sedimentary and igneous deposits of phosphate rock (after van Kauwenbergh, 2006).
mineralogical, chemical, and textural characteristics, the properties of soil to which the PR is applied, crop species, climatic conditions, and management practices have been taken into consideration in developing a Phosphate Rock Decision Support System (Smalberger et al., 2006). In general, biogenic PRs are most effective in releasing P for crop uptake on direct application but are limited in reserves, while igneous PRs are the least effective. The Tilemsi PR in Mali, Matam PR in Senegal, and Minjingu PR in Tanzania are the few known to have greater potential for direct use. But research results also show that a one time large application of PR can have positive residual effects on crop yields during several consecutive cropping seasons, which justifies the use of PRs in restoring soil P status (Buresh et al., 1997). PRs can have agronomic values beyond supplying P. Some provide secondary nutrients such as calcium, magnesium, zinc, and molybdenum while those containing calcite and dolomite have a liming effect and can reduce aluminum saturation in acid soils.
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The limited success in the use of the less reactive PR for direct applica tion has lead to several studies being conducted on applying mechanical, biological, and chemical processing techniques to modify the PRs so as to improve their agronomic effectiveness. Van Straaten (2002) has described such methods including partial acidulation, thermal treatment, blending with water soluble phosphates, mechanical activation, organic solubiliza tion, phosphocomposting, application with green manure, and cogranulat ing ground PR and ground sulfur to produce ‘‘biosuper.’’ All these approaches show promise, the degree of which may vary based on the factors that diminish the PR’s effectiveness. Elsewhere, studies have shown improvement of PR effectiveness in the presence of phosphorus enhancing microorganisms such as mycorrhizae (Barea et al., 2005). Most of these approaches have been conducted at experimental level and need to be screened for their suitability and acceptance by the smallholder farmers. Compelling evidence for the use of rock P in East Africa is provided by Woomer et al. (1997b). A comparison between Tanzanian Minjingu rock P (MRP) and imported TSP revealed that MRP at that time cost $50 a ton and was transported for about $0.08 km 1 t 1. Thus, MRP was available to severely P deficient areas in west Kenya for $115 per ton where TSP at the time cost $480 per ton. MRP was 65% as effective as TSP on an equal P basis and contains 69% as much P on a unit basis, therefore MRP was 45% as effective at only 24% of the cost. One approach to P replenishment (45 kg P in 400 kg of MRP per hectare) improved maize yield in the first year by 1 ton, resulting in an agronomic efficiency of 23% (Okalebo et al., 2006). Nonetheless, making better use of MRP in East Africa presents a challenge to rural development specialists. The Minjingu mine contains 6.6 million tons of P reserves, and has a processing capacity of 100,000 t yr 1, but over the past several years only 2000 t yr 1 were delivered for use in severely P deficient soils of neighboring Kenya. In 2008, further restrictions on export of MPR were imposed by the Tanzanian Government as a means of stimulating domestic consumption at the expense of subregional promo tion. This distorted policy was quickly reversed, although the sales price has increased to levels similar to processed P fertilizers (Sanginga and Woomer, 2009). Greater effort must continue to be sought to assess the economic benefits from utilizing PR in restoring soil fertility, to better process and distribute (e.g., through mass distribution in areas with known widespread P deficiency) PR products for use by smallholder farmers, and to develop awareness of the potential use of dolomite and gypsum deposits for correct ing soil acidity and S and micronutrient deficiencies. 4.2.3. Nutrients from the bag Conventional wisdom is that synthetic fertilizers are the principal sources for restoring nutrients in depleted soils of low productive capacity. The push to use synthetic fertilizers started becoming important in SSA during
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the 1960s when, in its implementation of the ‘‘Freedom from Hunger Campaign (FFHC),’’ the FAO agreed to prioritize fertilizer projects to demonstrate the impacts of modern technology on agricultural production. The FFHC was replaced in the late 1970s by the FAO’s Fertilizer Program which ended in the 1990s (FAO, 2004). Other widespread field testing and demonstration programs for fertilizers on the major food crops were con ducted under the Sasakawa Global (SG) 2000 projects (Quifiones et al., 1997) in selected countries. Later studies focused on new arguments to justify the need for using synthetic fertilizers in SSA, especially using the nutrient balances as a tool to evaluate widespread soil fertility decline and nutrient mining (Smaling et al., 1997). In SG 2000 project countries, yields in fertilizer demonstrations were typically two to three fold greater than traditional farmers’ fields (Quifiones et al., 1997). Analysis of the extensive FAO data shows that strong trends in yield are evident from fertilizer responses across different soils and environments. Figure 7A illustrates that maize yield response to low levels of P application is generally similar in three soils irrespective of their initial fertility status. A typical response curve to nitrogen application was generated from data obtained from different sites in SSA but on the same Lixisol. These data show that the responses can be negative (below the 1:1 ratio), equal to or higher than the control (Fig. 7A), and highly variable (Fig. 7B). It is this variability that calls for the need to address the challenges of applying fertilizers in right amounts to the right soil at the right time and developing more site specific soil management practices. It also partly explains failure in the adoption of fertilizer recommendations that were often based on overgeneralized blanket recommendations. Where these factors are addressed, fertilizers can be applied continuously for several years with consistent positive yield responses, a potential recognized by large scale farmers sustaining relatively high yields of maize (Kenya, Zambia, and Zimbabwe), tobacco (Nicotiana tabacum L.; Malawi and Zimbabwe), and coffee (Coffea arabica L.; Kenya) for periods of up to 30 years or more (Bekunda et al., 1997). Some smallholder farmers in SSA do use fertilizers but often in limited quantities. For example, Manyong et al. (2001) reported up to 90% of 200 surveyed farmers in the northern savanna of Nigeria applied fertilizers to their fields but only 81% of the fields received less than half of the recommended rate. Limited use of the fertilizers is determined by a variety of reasons including high costs, especially after market reforms removed subsidies, inefficient marketing systems, and restricted markets for outputs that constrain investment opportunities. Farmers, especially in the Sahel, reverted to strate gic application of the limited fertilizer amounts to individual planting holes (point placement) as a means of maximizing the economic returns from the applied fertilizer. Yields of millet and sorghum were increased by 43% over those obtained from broadcast applications (Tabo et al., 2007).
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Restoring Soil Fertility in Sub-Sahara Africa
A
10,000
Yield at 60 kg ha−1 P2O5
8000
6000
4000
Ferralsol Leptosol Nitosol
2000
0
0
2000
6000
4000
8000
10,000
–1)
Control yield (kg ha B
10,000
Yield (kg ha–1)
8000
6000
4000
2000
0
0
50
100
150
200
N rate (kg ha–1)
Figure 7 (A) Scatter plot of a 60 kg ha 1 P2O5 treatment yield against control yield of a maize crop on Ferralsol, Leptosol, and Nitosol. The solid line represents where treatment and control yields are the same. (B) Scatter plot of maize yield against different N application rates on a Lixisol. The solid curve is a plot against the mean values for each N rate. Symbols denote different fields. (Data source: FAO’s FERTIBASE.)
The application of small and moderate quantities of soluble P fertilizer (10–30 kg P ha 1) to maize by either mixing in the planting hole or by broadcast and incorporation was found to be economically attractive on moderate P fixing, P deficient soil (Jama et al., 1997). Some fertilizer place ment approaches such as banding and point placement (Christianson and Vlek, 1991) are being refined to create fertile hot spots while split application
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(Arora and Juo, 1982; Mughogho et al., 1990; Uyovbisere and Lombin, 1991) with more accurate timing (Woomer et al., 2004) during peak nutrient demand by crops have been practiced as a means of improving fertilizer use efficiency. Periodic microdozing can gradually build up nutrients and SOM as a result of improved crop productivity and residue recycling (Bationo, 2008). Long term experiments have shown that crop yields from treatments consisting of mineral fertilizers without accompanying organic inputs can decline over time (Bekunda et al., 1997) as a result of (i) soil acidification, (ii) rapid depletion of nonapplied nutrients, (iii) increased loss of nutrients through leaching, and (iv) decline of SOM. The depletion of other nutri ents not contained within fertilizers to deficiency levels in the soil is a plausible explanation for declining yields in many cases. The same long term experiments showed that the benefits of mineral fertilizers are much more enhanced when applied in combination with organic materials (Bekunda et al., 1997) because nutrients are better retained and buffered and their use efficiency is improved (Woomer and Swift, 1994). 4.2.4. Nutrients from organic resources Apart from the BNF systems described earlier, nutrients can be added on farm in form of (i) livestock manures directly deposited by grazing animals or after collection, treatment and systematically applying on land, (ii) crop residues utilized in situ or transferred from other production areas, and (iii) compost which is a value added product of a collection of a range of organic compounds that have been incubated for a period to allow for their decomposition. These have been the most important nutrient input sources for many smallholder farmers in SSA. Contribution of organics to farming extends beyond nutrient provision and includes increase in the SOM pool which maintains the physical and physicochemical components of soil fertility such as cation exchange capacity, reduction of phosphorus sorption capacity and improved soil structure. Farmers manage organic materials in a holistic manner (Bekunda and Woomer, 1996; Nzuma et al., 1998); plant residues are used as cattle feed, bedding materials in kraals, composted, applied as surface mulch or ploughed into the soil, and applied in combina tion with livestock manures or synthetic fertilizers. In many cases, organic resources available to the farmers are relocated between enterprises. The nutrient concentrations and other chemical characteristics in the organic resources vary widely (Table 4), even within each category (Palm et al., 2001), are low particularly in residues from food crops, and determine the impact of the applied resources on soil fertility. The organic resource database developed at the Tropical Soil Biology and Fertility Institute (Palm et al., 2001) contains information on chemical characteristics of over 300 plant species residues including nitrogen, lignin, and polyphenols that were used to formulate a decision tool for managing the resources (Fig. 8). This tool distinguishes four types of organic resources, suggesting how each can
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Restoring Soil Fertility in Sub-Sahara Africa
Table 4 Average nutrient contents on a dry matter basis for selected plant materials and livestock manures (adapted from Sanginga and Woomer, 2009)
Material
Zea mays (maize) stover Phaseolus vulgaris (bean) stover Glycine max (soybean) prunings Vigna unguiculata (cowpea) prunings Coffea robusta (coffee) husks Crotalaria spp. leaf Mucuna pruriens Leucaena spp. prunings Sesbania sesban leaf Tithonia diversifolia leaf Poultry manure Cattle manure (dry)
N (kg t 1)
P (kg t 1)
K (kg t 1)
Lignin (kg t 1)
Polyphenols (kg t 1)
8.3
0.8
13
88.2
7.4
9.9
1.1
19
108.2
3.4
27
1.9
22
85.3
17.7
24
3.1
11
127
11.1
17
1.3
29
39.6
13.8
42
1.9
14
66.9
15.9
29 30
2.3 1.8
15 16
78.6 164.7
88.1 71.6
35
2.1
14
5.7
58.9
38
3.8
46
116.6
34.6
29 10
18 2
16 9
119.3 84.8
– 1.7
be managed for short term nutrient release within cropping systems (Vanlauwe et al., 2006a,b). For example, materials with less nitrogen and higher lignin and polyphenol contents are expected to release less nutrients due to microbial immobilization and chemical binding, and thus they require supplementary fertilizer or higher quality organic resources to release nutrients at levels useful to land managers. When this concept was tested under field conditions in East, Southern, and West Africa, the results indicated that (i) the N content of organic resources is an important factor affecting maize production, (ii) organic resources with a relatively high polyphenol content result in relatively lower maize yields for the same level of N applied, and (iii) fertilizer equivalency values of some organic inputs can equal or even exceed those applied from synthetic sources (Sanginga and Woomer, 2009). This diagnostic approach was later trans lated into a more farmer friendly version using criteria that do not require chemical analysis (Fig. 8). These characteristics include color (green versus
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A
Characteristics of organic resource
N > 2.5% Yes
No
Lignin < 15% Polyphenols < 4% Yes
Lignin < 15%
Yes
No
No
Incorporate directly with annual crops
Mix with fertilizer or high-quality organic matter
Mix with fertilizer or add to compost
Surface apply for erosion and water control
Class 1
Class 2
Class 3
Class 4
B
Leaf color Green Leaves fibrous (do not crush) Highly astringent taste (makes your tongue dry)
Yellow Leaves crushed to powder when dry
Yes No
No
Yes
Incorporate directly with annual crops
Mix with fertilizer or high-quality organic matter
Mix with fertilizer or add to compost
Surface apply for erosion and water control
Class 1
Class 2
Class 3
Class 4
Figure 8 A decision tree to assist management of organic resources in agriculture: (A) is based on Palm et al. (2001), (B) is a farmer-friendly version of the same framework developed by Giller (2000).
brown), taste (mild versus astringent), and physical integrity (crumbly versus fibrous or solid). This approach provides land managers with the necessary knowledge to evaluate the potential use of organic resources in the field. On farm studies suggest that a majority of plant resources available to land managers belong to Class 2 but several Class 1 materials exist that are considered to be as useful as fertilizer (Gachengo et al., 1999). Using this field diagnostic approach, farmers can confirm for themselves that the different organic materials have a predictable impact on soil fertility and crop yields, and use them within their farms accordingly.
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Livestock are inextricably linked to cropping in most agroecosystems of SSA. Crop residues are vital livestock feeds during dry seasons while natural forages from range and fallow lands become external nutrient sources to croplands through manure. In relatively few cases, additional nutrients may also be introduced in the form of purchased feed concentrates and forages. Through digestion, livestock improve the quality of the organic resource making it subject to less nutrient immobilization when applied to soils. However, the quality of the manure depends on the feed quality and the livestock management practices, and Lekasi et al. (1998) established that there was scope for the development of decision tools to predict manure–compost quality from at least some manure characteristics. Elsewhere, such data have been used to develop software, the Manure Management Planner ( Joern and Hess, 2005), to calculate manure application rates for use in crop production. Quantitative availability of organic materials to farmers for application to their fields is the primary limiting factor to their use in SSA. During the assessment of the low external input technologies (LEIA management) in East Africa (De Jager et al., 2004) mulch, manure, and compost amounts ranging from 8.5 to 150 t ha 1 were applied on farmers’ fields. While significant increases in yield and economic returns were realized with relatively high application levels, availability of material then became the limiting factor because sources of the inputs were largely concentrated (redistributed) from within the farms. In reality, far much less amounts of organic materials than would be recommended for replenishing nutrients are available to the farmers, as low as 1.3 t ha 1 of millet stover, 450–1600 kg ha 1 of manure in the Sahel, and 1–1.5 t per animal per year in Kenya (Palm et al., 2001). Secondly, accumulation of nutrients in organic resources is greater in fertile soils, so degraded soils of SSA are not expected to produce high quality crop residues. Legumes provide higher quality organic inputs but mainly in terms of N. In order to benefit from the resources with such limitations, smallholders have concentrated their appli cation nearer to homesteads and inadvertently created gradients, with decreasing soil fertility as one progresses away from the homestead (Rowe et al., 2006). Others have taken fuller advantage of the limited resources by utilizing them expediently such as through microdosing. These smallholder intricacies should be considered as opportunities for engaging them in devising appropriate soil fertility management programs and interventions. 4.2.5. Integrating use of resources Synthetic fertilizers and organic inputs in most cases fulfill different func tions in soil fertility restoration. Given that neither of them is widely available to smallholder farmers, it makes more practical sense to advocate for their combined use. In an attempt to resist soil fertility depletion, smallholder farmers have always practiced a range of soil fertility manage ment strategies, with farmer available organic resources as the driving factor
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(Bekunda and Woomer, 1996; Place et al., 2003), and moving between them as the conditions warranted. The idea is to maximize benefits from both the available natural resource inputs and the more expensive external fertilizer inputs. Benefits from combined application of crop residues of different quality can sometimes be similar to those between crop residues and synthetic fertilizers. The ISFM paradigm shares common concepts with the smallholder strategies, but advocates for the use of synthetic fertilizers as an entry point in an environment that permits farmer investment in soil fertility management. ISFM is defined as ‘‘the application of soil fertility management practices, and the knowledge to adapt these to local condi tions, which maximise fertilizer and organic resource use efficiency and crop productivity. These practices necessarily include appropriate fertilizer and organic input management in combination with the utilization of improved germplasm’’ (Sanginga and Woomer, 2009). One of the benefits of the integrated use of input resources is a direct result of more nutrients being added from the two or more resources combined than applied singly. Synthetic fertilizers have the advantage of being less bulky and easy to manipulate but their constitution hardly includes the essential minor elements and organics meet this requirement. Interac tions result more from the impact on mechanisms of nutrient release from the resources and uptake by the plant. The C:N ratio, for example, determines the rate of mineralization of an organic resource added to soil, and when synthetic N is applied to the soil together with an organic resource with a wide C:N ratio, it will be immobilized and released at a slower rate, thus minimizing its loss and making it available to the plant at a rate likely similar with uptake. At Kabete, Kenya, Kapkiyai (1996) reported a 29% loss of total soil N in the top 15 cm when maize and beans were grown in rotation for 18 years without nutrient inputs and with crop residues removed. The same loss took place in plots with the recommended fertilizer applications but no residues returned. When fertilizers and manures were added and the maize stover was retained, the decline in total topsoil N was reduced by one half. It was concluded that organic inputs and/or the recycling of crop residues could have provided the soluble C necessary to reduce N depletion in this fertile soil. While a similar process may occur with P, the major impact of organic residues are more likely important in soils with high P fixing capacity, where the release of organic acids block sites for P fixation and increase P availability to the plant (Iyamuremye and Dick, 1996). An extra benefit from this process is stimulated root growth and increased exploration of the soils for more nutrients. Several studies already show the benefits of combining different types of resources (Table 5). The additive or synergistic effects may not be as pronounced in the first crop after application of the resources (columns 2–4) as those including yields of subsequent crops that benefitted from the residual effects of the resources (column 5). Column 6 shows that where
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Table 5 Maize grain yield (kg ha 1) response to combined synthetic and organic nutrient sources Study sites
a b c d e
Treatment
Sadore, Nigera
Zimbabwe (three sites)b
Magadu Tanzaniac
Western Kenyad
Western Kenyae
Control Manure (M) Fertilizer (F) MþF
0.55 1.01 1.15 1.30
0.92 1.59 1.27 1.74
1.11 2.01 2.16 2.51
2.7 6.5 3.5 8.6
0.4 1.6 1.1 0.9
Bationo (2008). Manure fertilizer N; three season average of maize yield. Dhliwayo (1998). Manure fertilizer P; three sites average of groundnut kernel yield. Ikerra et al. (2007). Green manure fertilizer P; two season average maize. Gachengo et al. (1999). Green manure fertilizer P; three season cumulative yield including two residuals Jama et al. (1997). Green manure fertilizers N and P at equal total rates; two season average maize yield.
materials are added at same nutrient rates, organics alone offer a better input choice. Organics also improve agronomic efficiency through better nutrient retention and improved nutrient release patterns, which is related to improved soil physical and biological properties.
4.3. Optimizing biophysical control measures 4.3.1. Fertilizer forms and formulations Synthetic fertilizers are marketed in different forms and in various nutrient combinations. Nitrogen fertilizers are usually in the form of urea, the least expensive and therefore most widely applied straight N fertilizer, with a nitrogen content of 46.2%. Other common N fertilizer forms are ammo nium nitrate and calcium ammonium nitrate (CAN). Triple superphosphate (TSP) is the most commonly used phosphorus fertilizer form. Other forms common on markets in SSA are diammonium phosphate and single superphosphate. Potassium is commonly applied as muriate of potash. Compound fertilizers result from intentional mixing of two or more nutrients in various percentages, the most common ones being the NþP and NþPþK blends. Choice of use of different formulations should be guided by plant growth response and quality, the type of soil as a growth medium, the potential for losses and environmental pollution, and economic consideration. The nitrogen in NH4þ based fertilizers, for example, has to be converted to NO3 2 by microorganisms before most plants can absorb it, and this conversion depends on the soil and environmental compositions that favor the performance of the microorganisms. Low levels of organic matter and aerobic bacteria, low temperature, low pH, and high moisture all reduce the
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rate of nitrification. But NH4þ carries a positive charge that helps make it more resistant to leaching than the negatively charged NO3 2. Fertilizers may be formulated for more efficient use, usually by coating with low molecular weight polyethylene wax and a tackifying resin that allow nutrient release over an extended period of time, but with the disadvantage of higher initial cost. 4.3.2. Improving the quality of organics Organic resources may be either gathered and deployed or collected and stored for use in a manner that is better timed to cropping seasons and plant nutrient demands. Examples of direct deployment include the establishment of trash lines and mulches from crop residues (Kanyanjua et al., 2000) and cutting and incorporation of green manures (Mureithi et al., 2002). Alternatively, organic materials may be gathered, bulked, and stored, practices well suited to crop residues and animal manures (Sanginga and Woomer, 2009). Examples of organic resource storage and use include piling crop residues as livestock feed during the dry season, heaping manures, and the production of compost. It is important to protect stored organic materials from the elements. This goal may be achieved by covering organic piles with tarpaulins or putting them in sheds (Kanyanjua et al., 2000). In many cases, organic materials must be well dried in the field and well aerated during storage to prevent further decomposition. One of the more expedient applications of organic resources is to apply them during land preparation. This strategy combines organic inputs with field operations such as tillage and fertilizer application (Sanginga and Woomer, 2009). In the case of green manure, management precedes soil tillage by several weeks because vegetative cover must be chopped or grazed in order to reduce its bulk, particularly if tillage is to be undertaken by hand or animal traction. Caution must be exercised in applying low quality materials, even in conjunction with mineral fertilizers. Organic inputs extremely low in nutrients and high in lignin and polyphenols must not be incorporated into the soil as these inputs will likely result in immobilization of soil nutrients and applied fertilizers. Rather these materials are best applied as surface mulches. Surface mulching is a useful field practice in terms of soil surface protec tion and water use efficiency, but is difficult to achieve at a field scale (Giller et al., 2009; Sanginga and Woomer, 2009). Crop residues have competing uses and may undergo rapid loss by termites and other soil fauna, and surface mulches subjected to rapid removal and comminution do not provide their intended purpose. Another source of mulch is prunings cut from boundary areas and nearby natural vegetation (Maundu and Tenga¨s, 2005) but this operation is labor consuming and the prunings are best applied to higher value crops, within animal feeds or as ingredients for compost making. On the other hand, near permanent soil cover is one of the foundations of Conser vation Agriculture (Derpsch, 2008) and practitioners must find a means to gain access to sufficient organic materials. Establishment of trailing legumes as
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a relay intercrop is one means of producing live mulch that will survive into the following dry season and provide surface mulch (Mureithi et al., 2002). Composting is a means of bulking organic resources and concentrating their nutrients. The composting process must be controlled, particularly through the choices of substrate, moisture content, and aeration. It is characterized by a period of rapid decomposition and temperature accumu lation followed by cooler, slower decay of the remaining organic substrate (De Bertoldi et al., 1985). The rate of decomposition can be increased by stacking the materials in a pile to a height of 1–1.5 m but higher stacks must be more regularly turned to facilitate rapid decomposition and prevent the formation of accumulated anaerobic by products (Savala et al., 2003). The most important physical properties to composting are particle size and moisture content (Lekasi et al., 2003a). Particle size affects oxygen movement into and within the pile, as well as microbial and enzymatic access to the substrate. Proper balance in the particle size should be main tained. If too large, the organic materials should be chopped into smaller pieces. On the other hand, if too small, the organic materials should be mixed with a bulking agent such as wood chips or bagasse. The optimum moisture content for composting is 40–60% as excess water interferes with oxygen accessibility, slowing the rate of composting. Too little water hinders diffusion of soluble molecules and microbial activity. The relative quality and quantity of the organic residues determines the rates of composting and the characteristics of the finished products (Table 6). When the carbon to nitrogen ratio (C/N) of the organic matter is approxi mately 25, transformation of the organic material proceeds rapidly with a high degree of efficiency of N assimilation into the microbial biomass. A narrower C/N ratio may lead to loss of N from compost through volatilization and greater C/N ratios (>40) promote immobilization of available N, slowing the rate of decomposition. Therefore, addition of mineral N (and P) can enhance more rapid decomposition and enrichment of the low quality residues. Low quality organic materials such as maize stover or wheat straw with a wide C/N ratio are suitable for preparing fortified compost (Ndung’u et al., 2003).
Table 6 Chemical characteristics of some compost samples submitted for analysis by farmers in Kenya (Lekasi et al., 2003b)
Source
N (kg t
K.W. Kamau C. Othiambo M.K. Ouma P.S. Watua
12 16 20 26
P 1 ) (kg t
K 1 ) (kg t
Ca 1 ) (kg t
Mg 1 ) (kg t
3 11 6 7
20 11 2 24
38 35 18 16
5 19 3 7
C 1 ) (kg t
350 410 320 550
Poly Lignin phenol 1 ) (kg t 1) (kg t 1)
107 84 131 222
42 32 6 38
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An alternative approach to composting involves epigeic earthworms that live within and consume plant debris (Savala et al., 2003). These worms consume a wide variety of organic materials to produce vermicompost that is rich in plant nutrients and has excellent physical properties. Useful vermicom posting species include the tiger worm (Eisenia foetida) and African night crawler (Eudrilus eugeniae). The tiger worm is the most commonly utilized species in commercial vermiculture and waste reduction (Haimi and Huhta, 1990). Vermicompost is best used as the main ingredient in a seedling or potting medium after passing it through a 5–10 mm mesh. A typical nutrient content from a manure based vermicompost using E. foetida is 1.93% N, 0.26% P, and 2.64% K (Savala et al., 2003). 4.3.3. Appropriate agronomic practices Agronomy is the science of managing growing crops at an extensive scale and is, therefore, complementary to soil fertility management. Appropriate agro nomic practices can make positive impact on soil fertility restoration provided they also result in positive returns to investment. Successful agronomic practices begin with assessing improved varieties and matching them with management practices of seedbed preparation, early sowing, optimum plant ing densities and row spacing, pest and weed control, and rotations that maximize crop residues and reduce the carryover of pests and disease. Most of these practices act to balance the plants’ needs with available soil moisture, so supplemental irrigation can be an important agronomic practice in drought prone areas. In Mali, it was demonstrated that applying fertilizer P as part of a package that included planting at the right time and at the correct plant density could raise the yield of maize by more than three times (Bationo et al., 1997). Soil fertility restoration can itself positively contribute to the reduction of some pest problems related to low soil fertility. Oswald et al. (1996) observed that fallows of Sesbania, a nitrogen fixing shrub, encouraged suicidal germination of the parasitic weed striga (Striga hermonthica (Del.) Benth.) in western Kenya, reducing its seed pool by one half. Another agronomic practice that has shown promise is fertilizer place ment (Poulton et al., 2006). ICRISAT (2006) showed that farmers could increase their average yields by 50–100% by applying as little as 9 kg N ha 1 directly to the base of the plant. In Malawi, recommendations for improving maize yield include top dressing with fertilizer N and band application of both basal and top dress fertilizers (Kumwenda et al., 1995). Several agro nomic success stories drawn from East, Sahelian, Southern, and West Africa follow. 4.3.3.1. Soybean rotation in Nigeria Identification and release of high yielding promiscuous varieties from the breeding program at IITA led to their widespread use by farmers in Nigeria. Uptake of the new promiscuous varieties was initially slow but gained rapid momentum as they became
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more widely known to farmers so that the new varieties were being grown by 75% of male farmers and 62% of women farmers after 10 years (Sanginga et al., 1999). Varieties developed subsequently contained traits more widely appreciated by farmers and experienced more rapid adoption (Sanginga et al., 2001). Earlier field studies performed in Nigeria showed that soybean derived about 60% of its N from fixation with a contribution to the N balance in the cropping system ranging from 8 to 43 kg N ha 1 depending on the soybean cultivars. In a rotational maize and soybean system where legume residues are retained and mineral fertilizer applied (15 kg P ha 1 to soybean and 45 kg N ha 1 to maize), soybean yields were 2.5 ton of grain per hectare with N fixation contributing about 50 kg N ha 1. The maize following soybean had 75% greater yield than maize following maize (Sanginga et al., 2001). 4.3.3.2. Fertilizer microdosing in West Africa In an effort to economize on fertilizer use, farmers experiment with fertilizers at different rates and methods of application. In West Africa, for example, farmers have adopted the ‘‘microdose’’ technology that involves strategic application of small amounts of fertilizer (4 kg P ha 1) and seed (Tabo et al., 2005). This fertilizer application is only one third of the recommended rates for the area. Small amounts of fertilizers are more affordable for farmers, give an economically optimum (though not biologically maximum) response, and if placed in the root zone of these widely spaced crops rather than uniformly distributed, result in more efficient uptake (Bationo and Buerkert, 2001). Generally, in the West African countries (Burkina Faso, Mali, and Niger), yields of millet and sorghum have been observed to be between 43% and 120% higher when using fertilizer ‘‘microdosing’’ than with the earlier recommended fertilizer broadcasting rates and farmers’ practices (Table 7). In addition, crops under microdosing have been observed to perform better under drought conditions because the crops’ larger root systems are more efficient at finding water, and because fertilizer hastens crop maturity, avoiding late season drought. Table 7 Effect of microdose on millet grain yield in the Sahel (Tabo et al., 2007) Treatments
Millet grain yield (kg ha 1)
1. Farmers’ practices 2. NPK HP 3. DAP HP 4. PRT þ NPK HP
487 1030 924 1325
NPK, 15-15-15 compound fertilizers; DAP, diammonium phosphate; HP, hill placement at 4 kg P ha 1; PRT, Tahona phosphate rock broadcast at 13 kg P ha 1.
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In Niger, the adoption of the microdosing technologies was rapid such that in just 3 years, a total of about 5000 farm households in 20 pilot sites started using better natural resource management technologies (i.e., fertil izer microdosing), were able to produce 100% more food, and had increased farm incomes by over 50% on average (Tabo et al., 2007). In view of the demonstrated potential of microdosing, ICRISAT initiated a program to scale up and out the technology. The recently completed USAID TAR GET project, building on FAO’s initiative, expanded testing of microdos ing to reach over 12,000 farmers in Burkina Faso, Mali, and Niger over 4 years. Over the years the number of farmers adopting the microdose technology has continued to grow increasing the potential for meeting the food needs of the population in the Sahel. The potential of microdosing is enormous. Even if it had been employed by just a quarter of Niger’s farmers in 2005, it is estimated an additional 275,000 tons of millet grain would have been produced—enough to eliminate the 2005 shortfall. 4.3.3.3. Staggered intercropping in East Africa Large benefits can accrue from simple agronomic interventions and then open the way for further, more complex technologies. For example, staggered row arrangement in maize–legume intercropping permits African smallholders to grow a wider range of food legumes with maize. Maize is planted at its recommended population, but every other row is shifted by 25 cm, providing a wider inter row to the legume. This approach permits intercropping with groundnut green gram, soyabean, and other higher value food legumes that are not normally intercropped with maize. It was developed through an on farm research and development process in west Kenya where traditional maize– bean intercropping resulted in poor yields (1450 kg maize and 240 kg beans per hectare) and low household incomes ($195 yr 1). Results from farmer managed trials over four seasons indicated that staggered intercropping with out fertilizer improved maize yields by 24%. The resulting recommended practice of maize–groundnut planted with 35 kg N and 10 kg P resulted in yields of 3204 kg maize and 472 kg groundnut per hectare, offering additional net returns of $434 per hectare (Woomer et al., 2004). Five years after its development, staggered intercropping was practiced by 16% of 250 randomly selected households. Not only did staggered intercropping result in improved farm yields but it served as an entry point for several ‘‘better management practices’’ relating to soil fertility management. These practices included increased symbiotic biological nitrogen fixation, substitution of preplant mineral fertilizers with composted manure, and better timing of top dressed mineral nitrogen, each of which further increased the benefits from staggered intercropping. In addition, requirement for new legume seed, particularly disease resistant groundnuts and soyabean, stimulated community based and commercial seed production, illustrating how a simple, low cost intervention can achieve multiple impacts.
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4.3.3.4. Pigeon pea intercropping in Southern Africa Intercropping maize with dual purpose pigeon pea, combined with adjusted agronomic practices and judicious fertilizer use, has successfully improved land produc tivity in Southern Africa. Both crops are planted at the same time, but early development of pigeon pea is slow, and maize is harvested before the long duration pigeon pea begins to form substantial biomass. After the maize is harvested, pigeon pea grows for several more months on residual soil moisture, produces a complete canopy cover and yields of up to 1.5 t ha 1 of grains. Maize is planted at the same spacing as in the mono crop, and yields of maize planted as an intercrop are similar to those of sole maize. Combining pigeon pea and maize reduces N and P fertilizer needs in subsequent years (Sogbedji et al., 2006). Inputs of N through fallen pigeon pea leaves contributes 75–90 kg N ha 1 which substantially benefits a following maize crop (Sakala et al., 2000). Pigeon pea is also capable of accessing scarce soil soluble P and can efficiently utilize residual P remaining in the soil from fertilizer applied to maize (Bahl and Pasricha, 1998). In addition, intercropping pigeon pea leads to significant reductions in pest and disease damage (Chabi Olaye et al., 2005; Sileshi and Mafongoya, 2003). Pigeon pea–maize intercropping is a common farmers’ practice in southern Malawi and parts of Mozambique and Tanzania but is possible only where some rains occur during the extended dry season. Pigeon pea is also used in intercropping in the derived savanna of West Africa, particularly in Benin and southern Nigeria. 4.3.3.5. Striga management and soil fertility improvement Over 120 million people living in Africa are affected by striga (witchweed), a parasitic weed infesting cereal, resulting in food insecurity and rural poverty. Maize is particularly susceptible to Striga which has colonized about 2.4 million hecatare of maize cropland resulting in the annual loss of 1.6 million tons of grain with an economic value of US $383 million (Woomer et al., 2008). Soil borne striga seeds germinate and attach to host plant root systems, causing plant toxicity, yield reduction, and even death of the host plant. Striga infestation is aggravated by low soil fertility and mostly affects resource poor farmers. For several decades, small scale farmers sought to control striga by hand weeding, but this practice failed because striga causes damage before emerging aboveground. Two new technologies offer greater control of striga, imazapyr seed coating of herbicide resistant maize seeds, and intercropping or rotation of maize with field legumes that suppress striga. On farm evaluation of integrated striga management technologies in west Kenya resulted in yield improvement of 1022 kg maize grain per hectare, reduced striga expression by 81% and increased economic returns by $143 per hectare (Woomer et al., 2008). Striga infestation and its reduction through crop management are important, and often overlooked, determinants of soil health. Striga suppression technologies cannot work
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Table 8 Some common ISFM field practices and their possible impact upon striga (Woomer et al., 2008) ISFM field practice
Possible striga management impact
Replace nutrient losses regularly Healthier cereals resist striga parasitism Apply nitrogen topdressing as urea striga is unable to metabolize reduced N forms Replenish long term phosphorus Legume roots better stimulate abortive loss germination Practice patch amelioration Treats striga invasion at its earliest outbreak Combine mineral and organic N forms become less available to striga inputs parasite Legume intercropping or rotation Legumes suppress striga through several mechanisms Cover crops and green manures Legumes suppress striga through several mechanisms Establish trash lines along contour Spread of striga seeds is reduced Improve urine and manure Fresh urine and manures suppress striga recovery handling expression Stubble and tether grazing Livestock suppress late emerging striga
alone rather they must be combined with improved soil fertility manage ment in order to substantially increase crop productivity. Many relatively simple field practices options also have suppressive effects on striga (Table 8). 4.3.3.6. Conservation agriculture Investment in conservation agriculture is somewhat risky for smallholder farming but offers potentially huge future returns by reversing degrading land quality and securing greater return from investments in mineral fertilizer. Conservation agriculture was first developed through mechanized approaches and it requires translation into the context of African farming in ways that do not expect too much from the poor farmer. Some of this translation requires that field operations be retooled for drilling into the soil rather than cutting across it. Implements used in such operations, like hand and oxen drawn planting and fertilizer microdose drills, would have to be designed and commercialized. The greatest challenge rests in weed management as conservation agriculture relies heavily upon herbicides and smallholders lack the capacity to acquire them and the necessary knowledge and applicators for these operations. The challenge is to distribute relatively expensive conservation agriculture products to a sufficient number of house holds to achieve significant impacts on land management, and to break even in terms of project costs and farmer economic benefits. Benefits of conservation agriculture include erosion control, water con servation, improved nutrient cycling and use efficiency, C sequestration,
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and more stable crop yields. The following CA techniques have been evaluated and actively promoted in East and Southern Africa since the 1980s (Rockstrom et al., 2009): no till tied ridging, mulch ripping, no till strip cropping, clean ripping, hand hoeing or zero till, tied furrows (for semiarid regions) and open plough furrow planting followed by mid season tied ridging. These have frequently been promoted in combination with fertilizer treatments and/or with mechanical structures such as: graded contour ridges, dead level contour ridges with cross ties (mainly for semiarid regions); infiltration pits dug at intervals along contour ridge channels; fanya juus (for water retention in semiarid regions); vetiver strips and broad based contour ridges (mainly used on commercial farms). 4.3.4. Soil and water conservation Soil erosion control and water conservation technologies are necessary for keeping the nutrient capital in place. On a slope of as low as 3%, Van Bodegom (1995) found increased soil and P loss by erosion when a natural uncultivated fallow was replaced with a planted sesbania fallow in order to replenish N fertility on an Eutrudox in western Kenya. Increased erosion in the sesbania fallow was attributed at least partly to reduced ground cover resulting from removal of weeds during establishment and early growth of sesbania. This observation highlights the importance of maintaining soil ground cover and surface roughness when restoring fertility of erosive soils. Physical conservation structures tend to have high initial construction costs, but there exist biological methods of erosion control such as planting legume hedges or vegetative strips along contours (Garrity and Mercado, 1994), with additional soil restorative capacities through nitrogen fixation and improved chances of adoption if they can provide useful by products like fodder and fuelwood. In the drylands, restoring soil fertility can be better optimized using support technologies that target water capture. In most occasions, micro dose is practiced in conjunction with other technologies such as the zaı¨ pits, use of manure, crop residue and household waste for composting, and straw treatment with urea for better intake and digestibility by animals. The use of planting pits, stone bounds and ridges in the drylands have been observed to conserve water and increase crop production (Table 9). The zaı¨ pits are often filled with organic matter so that moisture can be trapped and stored more easily. The pits are then planted with annual crops such as millet or sorghum. The zaı¨ pits extend the favorable conditions for soil infiltration after runoff events, and the pits are beneficial during storms, when there is too much water. The compost and organic matter in the pits absorb excess water and act as a form of water storage for the planted crops. The success of zaı¨ planting pits has been documented all over the Sahel region. In 1989– 1990, a project implemented by the Djenne´ Agricultural Systems (SAD) showed that agricultural yields increased by over 1000 kg ha 1 compared to
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Table 9 Effect of planting pits (zaı¨) and nutrient application on sorghum grain yield (Tabo et al., 2007)
Technology
Only planting pits Zai þ cattle manure Zai þ mineral fertilizers Zai þ cattle manure and fertilizers
Sorghum yield (kg ha 1)
Yield increase (%)
200 700 1400 1700
– 250 600 750
traditionally ploughed control plots. In Niger, Hassane et al. (2000) and Hassane (1996) observed average cereal yields of 125 kg ha 1 on untreated fields and 513 kg ha 1 in pitted fields with a minimum of 297 kg ha 1 for 1992 and a maximum of 969 kg ha 1 for 1994. Reij and Thiombiano (2003) have also reported higher sorghum grain yields when the planting pits were amended with organic and/or inorganic nutrient sources indicating the importance of nutrient management in improving the performance of the zaı¨ technology. Other studies have also demonstrated improved water and nutrient use efficiencies from the combination of water harvesting and nutrient application thus giving a win–win situation (Bationo, 2008).
5. Continuing Concerns: External Controlling Factors Soil fertility management research and outreach programs have been conducted in the SSA countries by several institutions, generating several knowledge intensive technologies that have proven themselves successful for managing soil fertility. Proven technical innovations are but one com ponent of land restoration and must be accompanied by mitigating actions to achieve their full impacts. The socioeconomic environment (e.g., enhanced marketing pathways and policy), land tenure systems (e.g., land fragmentation), and community specific characteristics (e.g., ability to con form to bylaws) play roles in farmer decisions to adopt soil fertility restora tion innovations. Small scale farmers in central Uganda mentioned environmental changes, labor, financial capital, transportation, markets, and information as major constraints to adopt and sustain agricultural technologies and practices (Mazur and Onzere, 2009). When such con straints are not addressed, then the technologies will be given limited adoption priority. The challenge is to develop farming enterprises that offer both food security and economic incentives to the farmers and
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consequently lead to the appreciation and adoption of management mea sures that better manage and restore soil fertility.
5.1. Participatory involvement In the past, project implementations in SSA were commonly focused upon short term measures of success. They did not involve all stakeholders in deciding the justification, course of technology development and implemen tation, and realistic expectations. In many cases, therefore, farmers became cynical of projects they considered as transient (did not allow deepening use of new knowledge), disconnected from their daily priorities and disproportion ately serving researcher interests (Ramisch, 2004). Too often, project cycles do not consider feedback from their intended beneficiaries to assure that real and lasting impacts were achieved upon target communities. And so, agricultural success resulting from this type of research was limited. Reece and Sumberg (2003) argued that both resource poor farmers and the formal research system have important but different parts to play and that the contribution of each may be optimized if the task of developing new technology is passed on to farmers at the earliest stage. In line with this, agricultural research to transform SSA has gone through a series of methodological outreach procedures including farm ing systems research which gave way to participatory and farmer first approaches and then to broader livelihoods and knowledge systems approaches at household, community, and meso levels (Matlon, 2009). Each successive procedure expanded the unit of intervention by acknowledging the nonlinear and iterative nature of the change process, and introduced a larger scale and set of economic, sociocultural, institutional, and political factors to understanding and directing the drivers of technological change. The current procedure, the innovations systems approach, seeks to make greater contribution to enhancing agricultural productivity by stimulating synergy between the various potential partners in agricultural innovation. It more fully involves farmers in decision making about ways forward, in both research and practice, and adds knowledge to their capacities to innovate and adapt both new and older technologies. One experience of this approach, the Farmer Field Schools (FFS), assessed for its appropriateness in effecting innova tion in soil fertility management in eastern and central Kenya, came up with profound results (de Jager et al., 2009). FFS members gained more knowledge on, became aware of more types and adopted more and wider variety of the nontraditional soil fertility management practices than non FFS members over a 3 year period (Table 10). More than 90% of the FFS households reported higher yields and financial returns as a result of adopting new soil fertility management practices, but also through the synergy achieved through strengthening farmer organization, linking the farmers to markets and empow ering them to engage in experiential learning. Clearly, strengthening long term relationships between farmers, researchers, and other service providers who
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Table 10 Adoption of soil fertility management practices after 3 years of participation or nonparticipation in farmer field schools in Kenya (percentage of households mentioning type of management practice; average of four FFS) (adapted from de Jager et al., 2009)
Soil fertility management practices
FFS participants (n ¼ 80)
Non-FFS participants (n ¼ 31)
Rhizobium inoculant Manure Fertilizer Tithonia Manure/fertilizer combination Crop residues Mulching Ridges Terraces Compost Double digging Soil and water conservation Napier grass strips Agroforestry Crop rotation Planting method
41 51 58 35 13 10 14 1 15 26 43 4 13 4 6 3
– 55 58 – 13 – 3 9 29 13 13 3 – – – –
lend support such as in marketing, processing, cooperatives, and microfinance management is necessary for effective farmer led agricultural innovation processes.
5.2. Driven by markets The bulk of the smallholder agriculture is not yet efficient enough for integration into the global input, financial and produce market systems. In fact, markets have always bypassed smallholder farmers with little monetary income given their low productivity and weak institutional status to help out. Yet market integration is a major exit route from smallholder’s poverty and adoption of soil restoration practice assures that the crop surpluses needed for market are sustainable. There are experiences in Africa to show that access to profitable markets can lead smallholders to adapt, innovate, and increase agricultural production. In Ghana, an increase in the free on board (FOB) price of cocoa from 40% to 70% led to a doubling of cocoa production (Rolling, 2009). In Nigeria, farmers were willing and able to produce grain for the market and purchase the necessary fertilizer
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when they did not have to compete with subsidized grains. Vanilla became known as ‘‘green gold’’ in Uganda after cyclone Hudah destroyed Mada gascar’s vanilla crop in 2003, which accounted for 75% of the vanilla sold on the world market. Prices shot up and vanilla growing expanded rapidly with limited assistance from the national extension systems. Marketing opportu nities that have included soil fertility management schemes have been designed and practiced successfully around commercial crop enterprises. Across Africa, large scale growers of ‘‘cash’’ crops like tea, sugarcane, cotton, and tobacco have provided contract and out grower farmers with packages of services, inputs and credit that have allowed smallholders to benefit from export markets. Bingen et al. (2003) consider that more market success can be achieved after investment in human capital to enable effective participation since the skills in marketing often determine the ability of a community to access inputs and information, and to market produce. Lessons learned from the Maize Marketing Movement of Western Kenya (Woomer, 2002) were that smallholders were economically viable as maize and legume producers; they quickly organized for collective action after basic training in cereal proces sing and being provided a convenient collection point (cereal banks) to deposit their crop surpluses. The grain they produced met the quality standards of top end buyers. A similar program in Zimbabwe offered training to farmers on the use of rhizobial inoculants, a soil fertility restora tion technology, and processing of soybean for a variety of uses. It then assisted them in accessing seed of improved soybean varieties, and linked them to markets led to an expansion of participating farmers from 50 in 1996 to over 10,000 3 years later (Mpepereki et al., 2000). In the Nigerian soybean case study reported in Section 4.3.3, extension efforts for creating awareness and home utilization techniques and stimulating small income generating businesses resulted in the improved well being of millions of people in both urban and rural areas. The presence of small industries for soybean processing provided a ready market for crop surpluses, and redir ected demand toward new soybean products. Partnerships were formed with government, social, agencies, and NGOs to incorporate soybean utilization into their activities. Hospitals were also involved and several child weaning foods were made from soybean. Similarly, success of the pigeon pea intercropping in Southern Africa (see Section 4.3.3.4) is related to an efficient extension program linking diverse stakeholders, from farmers and researchers to potential buyers and input suppliers (Snapp, 2004). A collaborative team approach across industry, NGOs and government ser vices facilitated farmer access to inputs, new cultivars and training in improved crop management and postharvest techniques. As a result of the technologies and dissemination approaches, intercropping maize and pigeon pea is becoming a common farmers’ practice in Southern Africa. This system also offers opportunity for accessing better markets and prices
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( Jones et al., 2002), including export opportunities to Europe and India, the world’s largest consumers of pigeon pea. Through linkage to millers and guaranteed good grain quality, the export market grew rapidly with 40,000 tons of pigeon pea shipped from central Tanzania in 2002. These examples explain how a strategic alliance of all important stakeholders, training and capacity building as well as awareness creation can catalyzed the whole process of restoring soil fertility in SSA. Input markets are equally important. Most smallholder farmers in Africa appreciate the value of fertilizers, but they are seldom able to apply them at the recommended rates and at the appropriate time because of high cost, lack of credit, delivery delays, and low and variable returns (Sanchez et al., 1997). Most farm inputs into African farming, including fertilizers, are imported. As inputs travel from the sea ports along to the hinterland, their retail sales prices increase due in part to the cost of transportation but other factors may also result in price distortion that cause too many products to be unaffordable to small scale farmers. A farm input pipeline survey along a 1800 km distance from the port of Mombasa, Kenya, to Goma in the Democratic Republic of Congo (Bekunda et al., 2005) showed that (i) as fertilizers move down the supply pipeline, their price increased at an average of $0.10 km 1 t 1 (Table 11), (ii) the most widely distributed fertilizer along the pipeline was DAP which contains the two nutrients, N and P, for which field observations suggest are limiting in most of the soils, and (iii) the number of farm input shops as well as farm input types decreased, reflecting the weak demand along the pipeline. It is now recognized that advances in utilizing external nutrient inputs for soil fertility restoration and manage ment will be realized at farm and community levels by promoting and empowering marketing by agro dealers. This has been equated to a mar ket led extension approach (Kelly et al., 2003) because it has the advantage of linking input provision to output and financial markets in a way that provide farmers with incentives to further invest in soil fertility manage ment. Given the large number of smallholder farmers who use fertilizers at low rates, improvement of accessibility of fertilizers is now focusing mainly Table 11 Availability and price of fertilizer as it moves through the supply pipeline from Mombasa, Kenya, to Goma, DR Congo (Bekunda et al., 2005) Location
Distance Fertilizers (km) (no. sold)
DAP (US$ kg
CAN ) (US$ kg
Nairobi Kampala Kabale Kisoro
484 1167 1605 1701
5 6 3 2
0.45 0.52 0.59 0.54
0.37 0.45 n.a. n.a
0.42 0.52 0.59 n.a.
0.45 0.51 0.59 0.54
Ruhengeri 1738 Goma 1807
3 0
0.58
n.a.
0.53
0.57
1
Urea ) (US$ kg
1
Triple 17 ) US$ kg 1)
1
Other (US$ kg
1
)
SSP at 0.36 SSP at 0.51 25-5-5 at 0.54
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on packaging them into small packets to increase affordability, and net working of rural agro dealers who provide extension advice to farmers.
5.3. Policy interventions The review so far has given examples of existing sparks of hope for restoring soil fertility in sub Saharan Africa, but the problem is that these sparks have taken long to ignite a sustainable restorative process, and the answers seem to be mainly policy related. Djurfeldt et al. (2006) give a chronology of policy progress in SSA and argue that it is possible, by means of policy measures on the part of African governments and the international community, to cause a green revolution in SSA. Until the mid 1970s most SSA countries were self sufficient in food crop production and virgin lands were still available, so that the pressure to change established ways of production and accompanying social institutions was minimal. A series of internal shocks during the 1970s, including episodic droughts and famine, led African governments to commit themselves to agriculture’s key role in national development. Public invest ment in the agricultural sector was generally high, the state provided credit and assumed responsibility for supplying inputs and handling produce through state led cooperatives and marketing boards. Crop research programs were initiated and new high yielding cereal varieties were released. Govern ments regulated prices and provided inputs such as seed and fertilizer at subsidized prices to smallholders who then had access to external resources as well as markets. But the regulated prices reduced the margin between cost of production and revenue from sale of produce for both smallholders and traders, thereby reducing the incentive to produce a marketable surplus and consequently manage the natural resources adequately. Parastatal organiza tions and marketing boards operated at a loss, subsidy costs mushroomed and this policy became economically unsustainable. From the mid 1980s to the mid 1990s SSA governments adopted Structural Adjustment Policies that aimed at reducing the role of the state and enhancing that of the private sector. It was presumed that this would spur agricultural intensification and more general development. But the results have not matched expectations because the policies were not small holder based. On the whole, farms in SSA remain small and most small holders cannot afford to purchase fertilizer. Fields are mainly worked by family members using simple hand tools. Production and yields of food crops are low although there are variations both regionally and within the same localities; a few farmers obtain yields substantially higher than the majority of farmers. These few are from wealthier households who have access to resources and the financial security that make it possible to improve yields, diversify and raise production and market the majority of their harvests. These yield gaps show that potential for agricultural growth exists in SSA, but also that it must be policy driven.
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In the recent times, some African governments have turned away from market based policies in favor of bringing the state back into supporting agriculture. Malawi is one such a country. Malawi’s soils, like those across SSA are highly depleted and many of its farmers are too poor to afford fertilizer at market prices. In 2006, in response to disastrously low agricul tural harvests, Malawi began a program of fertilizer subsidies that were designed to reenergize the land and boost crop production. This program was, championed by the country’s president, is radically improving Mala wi’s agriculture, and causing Malawi to become a net exporter of food to nearby countries (Dugger, 2007). This is crucial evidence of how invest ment in smallholder farming can alleviate hunger, poverty, and also con tribute to environmental rehabilitation. African governments recognized the great disparity between budgetary allocations to the agricultural sector (6.2% on average for 34 countries during 2004) that contributes 27% to the national GDP and, at the Second Ordinary Assembly of the African Union in July 2003 in Maputo, the African Heads of State and Government endorsed the ‘‘Maputo Declaration on Agriculture and Food Security in Africa’’ within which was the ‘‘commitment to the allocation of at least 10% of national budgetary resources to agriculture and rural development policy implementation within five years’’ (African Union, 2005). By 2005, six countries had already achieved the target. It is considered that the circum stances surrounding the policy reversal are more favorable today than they have been hitherto. Population growth, the limited land for extensive agricultural production and the reduced external aid to agriculture now calls for governments to better utilize the continent’s internal resources for intensification. It may also require policy change at global level, especially at international trade level, to assist SSA be party to global sustainable development.
6. Lessons Learned and Way Forward Soil degradation is just but one of the constraints to food crop pro duction in SSA smallholder agriculture but a root cause of persistent cycles of rural poverty. Where there is a limited use of external farm inputs because of low capacity to invest in farm improvement, continuous cultivation results in low and declining crop yields and an inability to attend to other farm production constraints, and eventually to food deficits, low incomes and perpetuated poverty. Because of the complex causes of low crop yields among these small scale farmers, and their far reaching effects, no simple intervention is likely to overcome yield limitations, uplift households and restore soil fertility; rather an integrated approach involving access to farm
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inputs, technologies to ensure their efficient use, land conservation mea sures and improved socioeconomic support is required. Issues of soil degradation in SSA and the urgent need to reverse this ominous processes have been addressed at different levels, ranging from global to project programs. In 2005, the United Nations Millennium Project released recommendations on how to attain the Millennium Devel opment Goals by 2015 (UNDP, 2005) among which was one focusing on soil health, small scale water management, and use of superior seeds as entry points for drastically increasing agricultural productivity in SSA. Conse quent actions supported by the Millennium Promise seek to demonstrate that the end of extreme poverty can be achieved by working with the poorest of the poor, village by village throughout Africa, in partnership with governments and other committed stakeholders. This approach requires affordable and science based solutions to help people lift themselves out of the poverty. In the same year, the United Nations World Summit endorsed the launching of the African Green Revolution called forth by the then UN Secretary General, Kofi Annan on July 5, 2004 in Addis Ababa at the high level event on ‘‘Innovative approaches to meeting the hunger millennium development goal in Africa.’’ In his own words, a successful revolution is where ‘‘we would see soil health restored, through agroforestry techniques and organic and mineral fertilizers,’’ among other solutions. At the June 2006 Abuja Fertilizer Summit, African heads of state and government added practical momentum to the African Green Revolution by identifying spe cific operational targets for 2007 through 2015, after declaring ‘‘fertilizer, from both inorganic and organic sources, a strategic commodity without borders.’’ In 2007, the Alliance for a Green Revolution in Africa was launched, including major programs in improved seeds and soil health. The overall vision is the elimination of hunger and absolute poverty in SSA. These activities have spilled over to country levels which agreed to subject themselves to a global monitoring framework by which progress on development goals could be measured. Despite these grand intentions very little has changed at the farm level, particularly among the poorest households. These stakeholders were bypassed during colonial times and early independence as unable to con tribute to larger economic goals, and lost to the first Green Revolution because the infrastructure and incentives necessary to adopt modern agri culture were not in place, particularly toward the use of sufficient fertilizer (Okigbo, 1990). Farming Systems Research and Development and its early participatory approaches were more sensitive to the plight of smallholders, and resulted in isolated successes in managing locally available agricultural resources (Chambers et al., 1989), but in the end were rejected because it served more to document rural household conditions than to empower farmers to solve production and marketing problems. The same could be said of Sustainable Agriculture which focused more upon environmental
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integrity rather than household well being (Dumanski et al., 1991) and assumed that good things must happen to those who take better care of the land. Focus upon soil nutrient depletion in Africa quantified its losses and raised awareness of an ominous future (Smaling et al., 1997) but the calls for large scale nutrient replenishment as an investment in agricultural resource capital never materialized (Sanchez et al., 1997). Indeed, the succession of paradigms reflect a learning process among rural development specialists, and better direct applied research, but it appears that the applica tion of new knowledge has failed to keep pace with environmental decline and spiraling poverty in SSA, and this has led to the new directions involving an African Green Revolution (Conway and Toenniessen, 2003) that embrace market led research, smart policy intervention, and agricul tural value chain enhancement (Sanginga and Woomer, 2009). Certainly, the direction and scope of many recently awarded research and develop ment thrusts in the areas of seed systems, ISFM, rural microfinance and training of local agro dealers signal that important lessons have been learned but do not guarantee that poorer households will not be bypassed yet again. For this reason it is advisable to always include the lower cost denominator in rural development programs such as community based versus commer cial seed production, local agromineral exploitation versus massive fertilizer importation or biological nitrogen fixation versus mineral nitrogen addition (Dakora and Keya, 1997; Smaling and Dixon, 2006; Woomer et al., 1997b). We also note with concern that 4 years into the targets set by the African Fertilizer Summit, modest improvements in nutrient inputs have not kept pace and that corrective actions are necessary to guide the continent’s pathway toward nutrient balance and food security.
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Carbon Sequestration in Agroforestry Systems P. K. Ramachandran Nair,* Vimala D. Nair,† B. Mohan Kumar,‡ and Julia M. Showalter† Contents 1. Introduction 2. Agroforestry 2.1. Historical development 2.2. System diversity 2.3. Ecological sustainability 2.4. Area under agroforestry 3. Carbon Sequestration in Agroforestry Systems: Concepts and Mechanisms 3.1. Definition and concepts 3.2. Aboveground (vegetation) carbon sequestration 3.3. Belowground (soil) carbon sequestration 3.4. Mechanisms of soil carbon sequestration 4. Carbon Sequestration in Agroforestry Systems: Measurements 4.1. Aboveground (vegetation) 4.2. Belowground (soil) 4.3. Soil carbon in agroforestry compared with other land-use systems 5. Carbon Sequestration in Agroforestry Systems: Management Considerations 5.1. Silvicultural practices 5.2. Choice of species and species admixture 5.3. Agroforestry practices and tree rotation cycles 5.4. Silvicultural carbon emissions 5.5. Animals in agroforestry
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* Center for Subtropical Agroforestry, School of Forest Resources and Conservation, University of Florida, Gainesville, Florida, USA Soil and Water Science Department, University of Florida, Gainesville, Florida, USA { College of Forestry, Kerala Agricultural University, Thrissur, Kerala, India {
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5.6. Soil management 5.7. Carbon sequestration programs and rural livelihood security 6. Concluding Remarks References
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Abstract Agroforestry—the practice of growing trees and crops in interacting combinations—is recognized worldwide as an integrated approach to sustainable landuse. It is estimated to be practiced over 1 billion hectares in developing countries, and to a lesser extent in the industrialized countries. Agroforestry systems (AFSs) are believed to have a higher potential to sequester carbon (C) because of their perceived ability for greater capture and utilization of growth resources (light, nutrients, and water) than single-species crop or pasture systems. The estimates of C stored in AFSs range from 0.29 to 15.21 Mg ha 1 yr 1 aboveground, and 30 to 300 Mg C ha 1 up to 1-m depth in the soil. Recent studies under various AFSs in diverse ecological conditions showed that tree-based agricultural systems, compared to treeless systems, stored more C in deeper soil layers near the tree than away from the tree; higher soil organic carbon content was associated with higher species richness and tree density; and C3 plants (trees) contributed to more C in the silt- þ claysized (<53 mm diameter) fractions—that constitute more stable C—than C4 plants in deeper soil profiles. The extent of C sequestered in AFSs depends to a great extent on environmental conditions and system management. Trading of the sequestered C is a viable opportunity for economic benefit to agroforestry practitioners, who are mostly resource-poor farmers in developing countries. However, more rigorous research results are required for AFSs to be used in global agendas of C sequestration.
1. Introduction Climate change is an important environmental issue that has captured the world’s attention during the recent past. Hardly a day passes without something related to it hitting the headlines. Enormous efforts (conferences and discussions, research activities, action plans, etc.) have been and con tinue to be made around the world at various levels and scales of magnitude to understand the complexities and severity of human induced climate change, ways to adapt to the changes, and mitigate the adverse effects. Thus, global climate change, commonly referred to as global warming, is a serious environmental issue affecting human lives and planet Earth today. Global warming is a highly debated term. As the term indicates, it refers to the increase in temperature of the earth’s near surface air and oceans in recent decades. In order to deal with the problem, an Intergovernmental Panel on Climate Change (IPCC) was established in 1988 under the
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auspices of the United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO) for the purpose of assessing ‘‘the scientific, technical and socioeconomic information relevant for the understanding of the risk of human induced climate change.’’ The IPCC does not conduct any research nor does it monitor climate related data or parameters. Thousands of scientists from all over the world contribute to the work of the IPCC on a voluntary basis. The IPCC bases its assessment mainly on published and peer reviewed scientific technical literature (www.ipcc.ch). The First Assessment Report of the IPCC published in 1990 as well as a supplemental report prepared in 1992 supported the establishment of the United Nations Framework Convention on Climate Change (UNFCCC) at the United Nations Conference on Environment and Development (commonly known as ‘‘The Earth Summit’’) held in Rio de Janeiro, Brazil, in 1992. The UNFCCC treaty, which the United States has signed, is the first major international agreement to combat global warming, and it forms the foundation of international political efforts in this direction. The IPCC reports were also influential at the first Conference of the Parties (COP) to the Climate Convention held in Berlin, Germany, in 1995. The 15th COP held in Copenhagen, Denmark, in December 2009 (often referred to as the Copenhagen Climate Convention) was the most recent in the series of COPs. Each IPCC Assessment Report and deliberations of each COP involve massive volumes of work and synthesis reports, and are available on the Internet and as various print versions. It is fair to say that these Assessment Reports represent a thorough, carefully explained view of the state of climate change science. The IPCC’s Second Assessment in 1996, along with additional special materials, provided key input to the negotiations that led to the adoption of the Kyoto Protocol to the UNFCCC in 1997. The Kyoto Protocol, ratified by 190 countries as of December 2009 (UNFCCC, 2010), is an international agreement that establishes binding targets for reducing the heat trapping emissions of the so called greenhouse gases (GHGs) from industrialized countries. Among the GHGs, CO2 is believed to be the most prominent one (other significant gases are methane, CH4, and nitrous oxide, N2O) causing global warming (Lorenz and Lal, 2010). Atmospheric concentration of CO2 has increased from the preindustrial level of about 280 ppm to the current level of approximately 380 ppm, and is estimated to be increasing at the rate of 2 ppm annually (Tans, 2009). Thus, reducing global warming entails reducing the atmospheric concentrations of GHGs, particularly CO2. Such reductions are brought about by carbon sequestra tion (CS), the process of removing carbon (C) from the atmosphere and depositing it in a reservoir, or the transfer of atmospheric CO2 to secure storage in other long lived pools (UNFCCC, 2007). Land Use, Land Use Change and Forestry (LULUCF), an approach that became popular in the context of the Kyoto Protocol, allows afforestation
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and reforestation (A & R) as GHG offset activities. Forest , crop , and grazing land management, and revegetation were added to the detailed list of LULUCF activities in 2001 as an important means to capture and store atmospheric CO2 in vegetation, soils, and biomass products. Consequently, agroforestry became recognized as a CS activity under the A & R activities, and agroforestry systems (AFSs) attracted attention as a CS strategy from both industrialized and developing countries (Albrecht and Kandji, 2003; Haile et al., 2008; Makundi and Sathaye, 2004; Nair and Nair, 2003; Nair et al., 2009a; Sharrow and Ismail, 2004; Takimoto et al., 2008a,b). Since the Clean Development Mechanism (CDM) under the Kyoto Protocol allows industrialized countries with a GHG reduction commitment to invest in mitigation projects in developing countries, there is an attractive opportu nity for subsistence farmers in developing countries, who are the major practitioners of agroforestry, to benefit economically from their agroforestry practices. Thus, the role of agroforestry as a CS strategy has raised consider able expectations. Since soils are a major reservoir of C (Section 3.3), an understanding about C storage in soils under AFSs is particularly important. It is also relevant from the soil fertility point—the traditional role of C in land use. The objective of this review is to assess the realistic potential of agroforestry as a biological approach to CS in the light of available scientific results, and examine the management approaches to realizing this seemingly underexploited potential of agroforestry. To set the stage, we will first present a brief account of the status of the science and practice of agroforestry.
2. Agroforestry Agroforestry has been defined in various ways. The World Agrofor estry Centre (www.icraf.cgiar.org) defines it as ‘‘a dynamic, ecologically based, natural resources management system that, through the integration of trees on farms and in the agricultural landscape, diversifies and sustains production for increased social, economic and environmental benefits for land users at all levels.’’ The Association for Temperate Agroforestry, AFTA (www.aftaweb.org) defines it as ‘‘an intensive land management system that optimizes the benefits from the biological interactions created when trees and/or shrubs are deliberately combined with crops and/or livestock.’’ Several other definitions are also available (Nair, 1993). In essence, they all refer to the practice of the purposeful growing of trees and crops, and/or animals, in interacting combinations, for a variety of benefits and services (Nair et al., 2008, 2009a).
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2.1. Historical development The practice of growing trees and crops together has been prevalent for many centuries in different parts of the world, especially under subsistence farming conditions. Homegardening, a major agroforestry practice today and one of the oldest forms of agriculture in Southeast Asia (Kumar and Nair, 2006), is reported to have been associated with fishing communities living in the moist tropical region about 13,000–9000 BC (Wiersum, 2004). Agroforestry in Europe is reported to have started around 4000 BC, when domestic animals were introduced in forests for feeding. The dehesa (animal grazing under trees) system of Spain is reportedly 4500 years old. It has been only during the past three decades, however, that these indigenous forms of growing trees and crops/animals together have been brought under the realm of modern, scientific land use scenarios (Nair et al., 2008). The motivations for taking a new look at the old practices were several. In the tropics, the Green Revolution of the 1970s (Evenson and Gollin, 2003) largely did not reach the poor farmers and those in less productive agroecological environments. In addition, defective land management practices resulted in increased tropical deforestation, fuelwood shortage, soil degradation, and biodiversity decline. The search for strategies to address these problems focused the attention on the age old practice of combining production of trees, crops, and livestock on the same land unit and an appreciation of their inherent advantages, and led to the establish ment of an international center, ICRAF, in 1977 (Steppler and Nair, 1987). The center, now known as the World Agroforestry Centre (www. worldagroforestry.org), one of the CGIAR—Consultative Group of Inter national Agricultural Research—institutions, was initially called the Inter national Council—and subsequently Centre—for Research in Agroforestry (ICRAF). Agroforestry thus began to be recognized and incorporated into national agricultural and forestry research agendas in many developing countries during the 1980s and 1990s (Nair, 1989, 1993). In temperate regions, ‘‘modern’’ agroforestry had a slower evolution than in the tropics. It started with an increased perception on the part of the general public about the environmental consequences of high input agri culture and forestry. The single species emphasis of food and wood pro duction in commercial systems has caused considerable decline of biological (including genetic) diversity: compare the diversity of corn (Zea mays L.), soybean (Glycine max (L.) Merr.) or pine (Pinus spp.) production systems with the approximate 100 species found in an oak (Quercus spp.)—hickory (Carya spp.) forest (Gordon et al., 2009). When the entire American food system, from field to table, is considered, 42 kJ of energy input is estimated to be required for each kilojoule consumed (Brown, 2004; www.earth policy.org; accessed June 2010). The land use and land cover changes
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associated with the removal and fragmentation of natural vegetation for establishment of agricultural and forestry enterprises and real estate devel opment are responsible, to a large extent, for the decline in biodiversity, invasion of exotic species, and alterations to nutrient, energy, and water flows, resulting in soil erosion, water quality deterioration, and environ mental pollution (Brown, 2004). Public demand for environmental accountability and application of ecologically compatible management practices increased when the problems associated with row crop agriculture became clearer. Consequently, the concept of agroforestry gained accep tance as an approach to addressing some of these problems. That led to the development of agroforestry applications in North America and other temperate zones such as Australia and New Zealand, Europe, and China, demonstrating the range of conditions under which agroforestry can be successfully applied (Garrett, 2009; Nair et al., 2008).
2.2. System diversity Today, agroforestry is recognized as an integrated applied science that has the potential for addressing many of the land management and environ mental problems found in both developing and industrialized nations. Numerous and diverse AFSs can be found in the tropics, partly because of their favorable climatic conditions, and partly because of the socioeconomic factors such as human population pressure, higher labor availability, smaller land holding size, complex land tenure, and closer proximity to markets (Nair, 2007; Nair et al., 2008). Table 1 presents a list of the major tropical practices. Local adaptations and manifestations of these (and other) practices exist as innumerable AFSs with site specific characteristics in different parts of the tropics and subtropics (Nair, 1989, 1993). The AFTA has recognized five major agroforestry practices in North America: alley cropping, forest farming, riparian buffer strips, silvopasture, and windbreaks (Fig. 1). Other temperate zone AFSs include the ancient tree based agriculture involving a large number of multipurpose trees (MPTs) such as chestnuts (Castanea spp.), oaks (Quercus spp.), carob (Ceratonia siliqua L.), olive (Olea europa L.), and figs (Ficus spp.) in the Mediterranean region (Nair et al., 2008; Rigueiro Rodriguez et al., 2008). The dehesa system, grazing under oak trees with strong linkages to recurrent cereal cropping in rangelands, is also a very old European practice (Howlett, 2009; Rigueiro Rodriguez et al., 2008).
2.3. Ecological sustainability The concept of agroforestry stems from the expected role of on farm and off farm tree production in supporting sustainable land use and natural resource management. This concept is based on the premise that land use
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Table 1
243
Major agroforestry practices in the tropics
Agroforestry practice
Brief description
Alley cropping (hedgerow intercropping)
Fast growing, preferably leguminous, woody species grown in crop fields as a hedgerow with close ( 0.5 m) in row spacing and wide (4 m or more) between row spacing; the woody species pruned periodically at low height (< 1.0 m) to reduce shading of crops; the prunings applied as mulch into the alleys as a source of organic matter and nutrients, or used as animal fodder. Intimate multistory combinations of a several trees— especially fruit and nut producing species—and crops in homesteads; livestock may or may not be present; the size of the garden is small (< 1 ha) and the garden is managed intensively usually by family labor. Fast growing, preferably leguminous, woody species planted and left to grow during short fallow phases— not exceeding 3 years—between cropping years; woody species contributes to site improvement and may yield economic products. Fruit trees and other multipurpose trees scattered or planted in some systematic arrangements in crop or animal production fields; trees provide products such as fruits, fuelwood, fodder, and timber. Integrating trees in animal production systems: Cattle grazing on pasture under widely spaced or scattered trees. Stall feeding of animals with fodder from trees grown in blocks on farms.
Homegardens
Improved fallow
Multipurpose trees (MPTs) on farms and rangelands Silvopasture:
Grazing systems Cut and carry
system (Protein banks) Shaded perennial crop systems
Shelterbelts and windbreaks Taungya
Growing shade tolerant species such as cacao (Theobroma cacao L.) and coffee (Coffea sp.) under or in between overstory shade , timber , or other commercial tree crops. Use of trees to protect fields from wind damage, sea encroachment, floods, etc. Growing agricultural crops during the early stages of establishment of forestry (timber) plantations; cropping is done for 2 or 3 years depending on the rate of tree canopy development (causing shading of crops) and soil fertility.
Source: Modified from Nair et al. (2008); copyright Elsevier.
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Agroforestry practices in North America Trees planted in single or multiple rows with agricultural or horticultural crops cultivated in the alleyways between the tree rows.
Alley cropping
Forest farming
Strips of permanent vegetation consisting of trees, shrubs, and grasses planted and managed together in between agricultural lands and water bodies.
Riparian buffer strips
Silvopasture
Windbreaks
Cultivation of shade-tolerant, high-value, specialty crops under the protection of a modified and managed forest-overstory.
Combining trees with forage (pasture or hay) and livestock production.
Row trees around farms and fields, managed as part of crop or livestock operation to protect crops, animals, and soil from wind hazards.
Figure 1 Agroforestry practices in North America. Source: Adapted from Nair et al. (2008) and Gold and Garrett (2009).
systems that are structurally and functionally more complex than either crop or tree monocultures result in greater efficiency of resource (nutrient, light, and water) capture and utilization, and greater structural diversity that entails tighter nutrient cycles. While the above and belowground diversity provides more system stability and resilience at the site level, the systems provide connectivity with forests and other landscape features at the land scape and watershed levels (Nair et al., 2008). The forced integration of trees into agricultural production systems adds considerable interspecific interac tion, especially competition, to whatever existing intraspecific competition for water, nutrients, light, and CO2, thereby creating a more complex agroecosystem (Rao et al., 1998). Both positive (e.g., enhanced productiv ity, cycling of nutrients, soil fertility, and microclimate) and negative (e.g., allelopathic, pest, and disease vectors) may be created, and ironically, single management activities undertaken in AFSs may change both negative and positive interactions simultaneously (Gordon et al., 2009; Jose et al., 2009). An important hypothesis of agroforestry is resource complementarity of the components of the system; AFSs include more species than single species systems and therefore more resource uptake strategies (‘‘niche complemen tarity hypothesis’’; Harper, 1977). Ecologically, combining ability underlies
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the process of selecting combinations of species with divergent growth char acteristics to ensure better complementarity in resource utilization (Menalled et al., 1998) and provide better ecosystem services such as water quality amelioration (Jose, 2009; Michel et al., 2007; Nair et al., 2007a). Growth characteristics of trees vary considerably among species, for example, shade tolerant versus shade intolerant, evergreen versus deciduous, rapid versus slow juvenile height growth, and deep versus shallow rooting. The greater range of traits extant in diverse assemblages probably ensures complementarity and positive species interactions (Menalled et al., 1998). The multitude of ways in which trees may be incorporated into agricul tural production systems—intercropping as opposed to silvopastoralism, for example—could be problematic in terms of conceptualizing all AFSs in one standardized system model. Nonetheless, there is great merit in doing so because it allows comparison with natural forested or agroecosystems as to the relative extent that ecological properties are maintained or relinquished by AFSs. For example, compared with the net primary productivity (NPP) of 2–6 Mg dry matter (biomass) per hectare per year for temperate conifer ous forest plantations, some AFSs in the tropics such as the multistrata (vertically stratified) homegardens and shaded perennial systems can exhibit in excess of 15 Mg ha 1 yr 1 (Kumar and Nair, 2006). Indeed, the ecological indices for species similarity, diversity, and richness (Sorenson’s, Shannon–Wiener, and Margalef, respectively) of multispecies homegardens are similar to those of nearby primary forests (Mohan et al., 2007). These similarities with natural ecosystems are strong indicators of ecological sus tainability of AFSs—assuming, of course, that natural ecosystems are eco logically sustainable.
2.4. Area under agroforestry One of the difficulties in planning for capitalizing on the potential benefits of agroforestry has been the lack of availability of an unambiguous estimate of the area under the system at a given period of time. For example, Montagnini and Nair (2004) noted that with no reliable estimates on the extent of area and the gross variability expected in terms of tree species and soil attributes, it is an ‘‘almost insurmountable’’ task to estimate C stocks in agroforestry. A major difficulty in estimating the area under agroforestry is lack of proper procedures for delineating the area influenced by trees in a mixed stand of trees and crops. In simultaneous systems, the entire area occupied by multistrata systems such as homegardens and shaded perennial systems and intensive tree intercropping situations can be listed as agrofor estry. However, most of the AFSs are rather extensive, where the compo nents, especially trees, are not planted at regular spacing or density; for example, the parkland system and extensive silvopastures (Nair, 1993, 1989). The problem is more difficult in the case of practices such as
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windbreaks and boundary planting where although the trees are planted at wide distances between rows (windbreaks) or around agricultural or pastoral parcels (boundary planting), the influence of trees extends over larger than easily perceivable extent of areas. The problem has a different dimension of difficulty when it comes to sequential systems such as improved fallows and shifting cultivation. In such situations, the beneficial effect of trees and other woody vegetation (in the fallow phase) on the crops that follow them (in the cropping phase) is believed to last for a variable length of time (years). Some attempts have, however, been made to estimate the area and C stocks under agroforestry in the world. Based on available information and informed assumptions, Nair et al. (2009a) estimated the total area under agroforestry in the world as 1023 million hectares. Almost simultaneously, through geospatial analysis of remote sensing derived global datasets at 1 km resolution, the World Agroforestry Centre and collaborators (Zomer et al., 2009) reported that agroforestry is practiced on about 1 billion hectares of agricultural lands worldwide, servicing about 1.5 billion farmers, primarily smallholders, in developing countries. This projection is, of course, tenta tive. It does not include areas that could potentially be brought under agroforestry, such as the vast areas of degraded forestland. For example, IPCC (2000) estimated that 630 million hectares of unproductive croplands and grasslands could be converted to agroforestry worldwide. In summary, as Nair et al. (2008) observed, agriculture and forestry are too often treated separately, yet these two sectors are often interwoven on the landscape and share many common goals and ecological foundations. The multitude of AFSs, be they practiced in the tropics or temperate regions, are firmly grounded on strong ecological principles, and through provision of many basic needs and ecosystem services, they contribute to attainment of many regional developmental goals. Thirty years ago, agro forestry began to attract the attention of the international development and scientific community, primarily as a means for sustaining agricultural pro duction in marginal lands and remote areas of the tropics that were not benefited by the Green Revolution. Today, thanks to input from modest research, agroforestry has been recognized as having the potential to offer much more toward ensuring not only food security in poor countries, but also environmental integrity in poor and rich nations alike.
3. Carbon Sequestration in Agroforestry Systems: Concepts and Mechanisms The concept of CS is the same across different land use systems. While the underlying mechanisms too are similar, they may manifest themselves differently in different systems depending on system specific characteristics.
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After discussing the general definition and concepts of CS, we will present the CS mechanisms under AFSs in this section.
3.1. Definition and concepts Carbon sequestration is the process of removing C from the atmosphere and depositing it in a reservoir. It entails the transfer of atmospheric C, especially CO2, and its secure storage in long lived pools (UNFCCC, 2007). The long term global C cycle, which describes the biogeochemical cycling of C among surface systems consisting of oceans, the atmosphere, biosphere, and soil, controls the atmospheric CO2 concentration over geological time scales of more than 100,000 years (Berner, 2003). The short term C cycle over decades and centuries is of greater importance than the long term cycle in forest, AFSs, and agricultural ecosystems. The important processes of this cycle are the fixation of atmospheric CO2 in plants through photosynthesis and return of part of that C to the atmosphere through plant, animal, and microbial respiration as CO2 under aerobic and CH4 under anaerobic conditions. Vegetation fires, and burning and land clearing for cultivation for agricultural and forestry purposes, can also release significant quantities of CO2 (and CH4) to the atmosphere; but much of this C is recaptured in subsequent regrowth of vegetation (Lorenz and Lal, 2010; Nair et al., 2010). Carbon pools in such terrestrial systems include the aboveground plant biomass, durable products derived from biomass such as timber, and below ground biomass such as roots, soil microorganisms, and the relatively stable forms of organic and inorganic C in soils and deeper subsurface environ ments. Thus, from the agroforestry point of view, CS involves primarily the uptake of atmospheric CO2 during photosynthesis and transfer of fixed C into vegetation, detritus, and soil pools for ‘‘secure’’ storage. The Soil Science Society of America (SSSA) recognizes that C is seques tered in soils in two ways: direct and indirect (SSSA, 2001). Direct soil CS occurs by inorganic chemical reactions that convert CO2 into soil inorganic C compounds such as calcium and magnesium carbonates. Indirect plant CS occurs as plants photosynthesize atmospheric CO2 into plant biomass. Some of this plant biomass is then sequestered as soil organic carbon (SOC) during decomposition processes. The amount of soil C sequestered at a site reflects the long term balance between C uptake and release mechanisms. Because those flux rates are large, changes such as shifts in land cover and/or land use practices that affect pools and fluxes of SOC have large implications for the C cycle and the earth’s climate system. It is clear from the above that CS occurs in two major segments of the agroforestry ecosystem: aboveground and belowground. Each can be parti tioned into subsegments: the former into specific plant parts (stem, leaves, etc. of trees and herbaceous components), and the latter into living biomass such as roots and other belowground plant parts, soil organisms and C stored
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in various soil horizons. The total amount sequestered in each part differs greatly depending on a number of factors, including the region, the type of system (and the nature of components and age of perennials such as trees), site quality, and previous land use. On average, the soil and aboveground parts are estimated to hold major portions, roughly 60% and 30%, respec tively, of the total C stored in tree based land use systems (Lal, 2005, 2008). Based on the notion that tree incorporation in croplands and pastures would result in greater net C storage above and belowground (Haile et al., 2008; Palm et al., 2004), AFSs are believed to have a higher potential to sequester C than pastures or field crops (Kirby and Potvin, 2007; Roshetko et al., 2002).
3.2. Aboveground (vegetation) carbon sequestration Aboveground C storage is the incorporation of C into plant matter either in the harvested product, or in the parts remaining on site in a living form. The amount of biomass, and subsequently C, that is stored depend to a great deal—apart from the nature of plant itself—on the properties of the soil on which it grows, with higher concentrations of organic matter (OM), nutri ents, and good soil structure, leading to greater biomass production. The aboveground biomass (AGB) that is not removed from the site is eventually reincorporated into the soil as plant residues and OM. Estimates of above ground CS potential (CSP) are based on the assumption that 45–50% of branch and 30% of foliage dry weight constitute C (Schroth et al., 2002; Shepherd and Montagnini, 2001). A summary of aboveground CS rates in some major AFSs around the world (Table 2) presented by Nair et al. (2009a) shows that the estimates of CSP in AFSs are highly variable, ranging from 0.29 to 15.21 Mg ha 1 yr 1. As can be expected, these values are a direct manifestation of the ecological production potential of the system, depending on a number of factors, including site characteristics, land use types, species involved, stand age, and management practices. Moreover, biomass production—based upon which these data seem to have been derived—may not represent the UNFCCC stipulated measure of CS (‘‘secure storage in long lived pools’’). Notwithstanding the above limita tions, in general, AFSs on the arid, semiarid, and degraded sites have a lower CSP than those on fertile humid sites; and the temperate AFSs have relatively lower CSP compared with tropical systems. Considering that aboveground CS estimates are direct manifestations of AGB production, the basic mechanism of the two functions (CS and AGB production) is the same: uptake of atmospheric CO2 during photosynthesis and transfer of fixed C into vegetation (sequestration involves the additional step of ‘‘secure storage’’ of such fixed C). A large number of ecological and management factors influence the rate at which this fundamental process proceeds. Lorenz and Lal (2010) have recently described the effect of such
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Table 2 Reported values of carbon sequestration in the vegetation (above- and belowground) of some agroforestry systems
Age (year)
Fodder bank, Se´gou, Mali, West African Sahel (Gliricidia sepium (Jacq.) Kunth ex Walp., Pterocarpus lucens Willd. and P. erinaceus Poir.) Tree based intercropping, Canada: hybrid poplar þ barley (Hordeum vulgare L.) Parklands, Se´gou, Mali, West African Sahel Agroforest, Western Oregon, USA [Pseudotsuga menziesii (Mirb) Franco þ Trifolium subterraneum L.] Agrisilviculture, Chhattisgarh, Central India Silvopasture, Kerala, India
7.5
0.29
Takimoto et al. (2008a)
13
0.83
Peichl et al. (2006)
35
1.09
11
1.11
Takimoto et al. (2008a) Sharrow and Ismail (2004)
5
1.26
Swamy and Puri (2005)
5
6.55
23.2
4.29
13
6.31
Kumar et al. (1998a, 1998b) Kirby and Potvin (2007) Dossa et al. (2008)
13.4
8.00
26
5.85
5
10.34
Beer et al. (1990)
10
11.08
Beer et al. (1990)
4
12.04
Parrotta (1999)
Home and outfield gardens Shaded coffee, Southwestern Togo Indonesian homegardens, Sumatra Cacao (Theobroma cacao L.) agroforests, Mekoe, Cameroon Cacao agroforests, Turrialba, Costa Rica Cacao agroforests, Turrialba, Costa Rica Woodlots, Puerto Rico a
Mean vegetation Ca (Mg ha 1 yr 1)
Agroforestry/land-use system and location
References
Roshetko et al. (2002) Duguma et al. (2001)
Values for similar systems (in terms of location and age) were pooled wherever possible regardless of species. Source: Adapted from Nair et al. (2009a); copyright Wiley InterScience.
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ecological factors on CS in forest ecosystems. The influence of management factors that are particularly relevant to AFSs is considered in some detail in Section 5. Belowground CS is influenced by inherent soil properties and processes, some of which are not influenced by management practices. Moreover, as stated above, roughly two thirds of the total CS occur belowground. Therefore, belowground (especially soil related) mechan isms and processes are considered in more detail than aboveground mechan isms and processes in subsequent sections of this chapter.
3.3. Belowground (soil) carbon sequestration Soils play a vital role in the global C cycle. The soil C pool comprises SOC estimated at 1550 Pg and soil inorganic C about 750 Pg both to 1 m depth (Batjes, 1996). This total soil C pool of 2300 Pg is three times the atmo spheric pool of 770 Pg and 3.8 times the vegetation pool of 610 Pg. Thus, any change in the soil C pool would have a significant effect on the global C budget. The historical amount of CO2–C emitted into the atmosphere from the terrestrial ecosystems is estimated to be about 136 55 Pg, of which soils account for about 78 12 Pg (Lal, 2008). Loss of organic C from tropical soils not only increases the atmospheric CO2 content, but also reduces the fertility of those soils that are generally nutrient poor. Soil organic matter (SOM) contains more reactive organic C than any other single terrestrial pool. Consequently, SOM plays a major role in determin ing C storage in ecosystems and in regulating atmospheric CO2 concentra tions. A reduction in the soil C pool by 1 Pg is equivalent to an atmospheric enrichment of CO2 by 0.47 ppm (Lal, 2001). Thus, soil C that traditionally has been a sustainability indicator of agricultural systems has now acquired the additional role as an indicator of environmental health. The literature on soil carbon sequestration (SCS) potential of AFSs is scanty, although rather plentiful reports are available on the potential role of agricultural soils to sequester C. Reviewing the available information on SCS in AFSs worldwide, summarized in Table 3, Nair et al. (2009a) reported that the estimates varied greatly across systems, ecological regions, and soil types. The study revealed a general trend of increasing SCS in agroforestry compared to other land use practices (with the exception of forests); overall, the land use systems were ranked in terms of their SOC content in the order: forests > agroforests > tree plantations > arable crops. [Agroforests are complex multistrata systems, similar to homegardens in structural complexity, but larger in size (Nair et al., 2009a).] The authors noted that the estimated values of SCS in AFSs varied greatly and were a reflection of several factors including biophysical and socioeconomic char acteristics of the system parameters as well as the lack of uniformity in study procedures.
Table 3
Some reported values of soil organic carbon (SOC) stock in agroforestry systemsa
Agroforestry system/species
Location
Age (year)
Soil depth (cm)
Soil C (Mg ha 1)
References
Mixed stands, Eucalyptus þ Casuarina (C), C þ Leucaena (L), Eucalyptus þ L Agroforest [Pseudotsuga menziesii (Mirb) Franco þ Trifolium subterraneum L.] Agrisilviculture (Gmelina arborea Roxb. þ eight field crops) Tree based intercropping: hybrid poplar þ barley Silvopastoral system: Acacia mangium Willd. þ Arachis pintoi Krapov. & W. C. Gregg Alley cropping Leucaena 4 m wide rows Alley cropping: hybrid poplar þ wheat, soybeans, and maize rotation Alley cropping system: Erythrina poeppigiana (Walp.) O. F. Cook þ maize and bean (Phaseolus vulgaris L.) Gliricidia sepium þ maize
Puerto Rico
4
0–40
61.9, 56.6, and 61.7
Parrotta (1999)
Western Oregon, USA
11
0–45
95.9
Sharrow and Ismail (2004)
Chhattisgarh, Central India Ontario, Canada
5
0–60
27.4
13
0–20
78.5
Swamy and Puri (2005) Peichl et al. (2005)
Pocora, Atlantic coast, Costa Rica
10–16
0–100
173
Ame´zquita et al. (2005)
Western Nigeria
5
0–10
13.6
Lal (2005)
Southern Canada
13
0–40
125
Oelbermann et al. (2006)
Costa Rica
19
0–40
162
Oelbermann et al. (2006)
Zomba, Malawi
10
0–200
123
Makumba et al. (2007) (continued)
Table 3 (continued)
a
Soil depth (cm)
Soil C (Mg ha 1)
References
0–40
45.0
13
0–40
97.3
Kirby and Potvin (2007) Dossa et al. (2008)
Florida, USA
8–40
0–125
6.9–24.2
Haile et al. (2008)
Se´gou, Mali
35
0–100
33.3
Se´gou, Mali
8
0–100
24
Takimoto et al. (2008a) Takimoto et al. (2008a)
Se´gou, Mali
6–9
0–100
33.4
Kerala, India Central Spain Bahia, Brazil
35þ 30þ 30
0–100 0–100 0–100
101–126 27–50 302
Agroforestry system/species
Location
Agroforest (home and outfield gardens) Shaded coffee, Coffea robusta L. Linden þ Albizia spp. Sivopasture: slash pine (Pinus elliottii Engelm.) þ bahiagrass (Paspalum notatum Flu¨gge) Faidherbia albida (Delile) A. Chev. parkland Live fence (Acacia nilotica (L.) Willd., Acacia Senegal (L.) Willd., Bauhinia rufescens L., Lawsonia inermis L., and Ziziphus mauritiana Lam.) Fodder bank (See Table 2 for species list) Homegardens Dehesa system Shaded cacao systems
Ipetı´ Embera, Panama Southwestern Togo
Age (year)
Takimoto et al. (2008a) Saha et al. (2009) Howlett (2009) Gama Rodrigues et al. (2010)
Values for similar systems (in terms of location and age) were pooled wherever possible regardless of species. Source: Some values are adapted from Nair et al. (2009a); copyright Wiley InterScience.
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The impact of any AFS on SCS depends largely on the amount and quality of biomass input provided by tree and nontree components of the system, and on properties of the soils, such as soil structure and their aggregations. For example, in the establishment of silvopastoral systems, some functional consequences are inevitable when trees are allowed to grow in grass dominated land such as an open pasture. These include alterations in above and belowground total productivity, modifications to rooting depth and distribution, and changes in the quantity and quality of litter inputs (Connin et al., 1997; Jackson et al., 2000; Jobbagy and Jackson, 2000). Such changes in vegetation component, litter, and soil characteristics modify the C dynamics and storage in the ecosystem (Ojima et al., 1991; Schlesinger et al., 1990). Thus, SCS in AFSs—indeed in any land use system—is dependent on a large number of factors, ranging from agroeco logical conditions to management practices. Our understanding on these factors and mechanisms of SCS will be examined in more detail here.
3.4. Mechanisms of soil carbon sequestration Decomposition of plant residues and other organic materials in the soil is a source of C and nutrients for new growth of microbial communities and plants. Much of this C is released back into the atmosphere as CO2 during respiration, or is incorporated into living biomass. However, about one third of SOM breaks down much more slowly and could still be present in the soil after 1 year (Angers and Chenu, 1997). This SOM represents a significant carbon store and can remain in the soil for extended periods as a part of soil aggregates. The fraction of SOM that is so ‘‘protected’’ from further rapid decomposition is very important from the point of view of SCS. 3.4.1. Types of soil organic matter protection Soil organic matter is protected in the soil by three main processes: bio chemical recalcitrance, chemical stabilization, and physical protection (Christensen, 1996; von Luetzow et al., 2008). Biochemical recalcitrance occurs when the chemical makeup of SOM involves aromatic polymers and other structures that are difficult for microbes to break down (Christensen, 1996). A common example is lignin, one of the main components of woody plants. However, recent studies suggest that this factor alone does not lead to long term soil C recalcitrance as was previously thought (Flessa et al., 2008; Mikutta et al., 2006). Flessa et al. (2008) found that all individual organic compounds had turnover rates shorter than that of the bulk SOC (<53 yr). It is now believed that biochemical recalcitrance must work in conjunction with other factors such as physical protection and organomineral stabiliza tion to stabilize SOC (Flessa et al., 2008; Marschner et al., 2008). Physical protection is the binding of SOM in soil aggregates, separating it from microbial populations and preventing its degradation. Fractions of
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SOM that would otherwise be labile are not exposed to microbial activity and can remain in the soil for much longer periods of time (Six et al., 2000). However, the eventual shifting and breaking of aggregates leads to the exposure and subsequent breakdown of this protected SOM. Organomineral stabilization is the conversion and binding of SOM with minerals to form organomineral complexes that can remain in the soil for extended periods. In conjunction with physical protection and biochemical recalcitrance, it helps to create stable SOC. The majority of recalcitrant SOM is bound in organomineral complexes; Mikutta et al. (2006) found that at least 86% of SOM was mineral protected in forest subsoils. However, the forma tion of these complexes takes time to occur (Six et al., 2000). Physical protection and biochemical recalcitrance can allow SOM to remain in the soil longer, giving time for organomineral complexes to form. Thus, the recalcitrance of SOM is a combination of these short and long term processes. 3.4.2. Soil aggregates Soil aggregates and size fractions are known to have an important effect on the retention of C in soil (Six et al., 2004). Aggregates are secondary particles formed through the combination of mineral particles with organic and inorganic substances (Bronick and Lal, 2005; Jastrow and Miller, 1997). They range in size from microns to millimeters and are often classified according to their ability to resist slaking in water. Depending on their diameter, they are classified into various size classes (Oades and Waters, 1991; Tisdall and Oades, 1982). Although there have been some differences between designations of size classes, most studies now follow the following divisions. The smallest size fractions among the microaggregates (smaller than 53 mm in diameter, usually referred to as the silt þ clay fraction) are composed of recalcitrant organomineral complexes. These are often bound together in larger microaggregates that range from 53 to 250 mm in diameter and are held together with polysaccharides and humic materials that are also fairly persistent due to biochemical recalcitrance and physical protection. These materials are often bound together in macroaggregates by roots, hyphae, and organic materials that readily decompose or change but are physically protected within the aggregate. Macroaggregates are greater than 250 mm in diameter. These three size classes occur in what is referred to as an aggregate hierarchy. The largest aggregates, the macroaggregates, are least stable and break up most easily when exposed to slaking. These are followed by the intermediate sized microaggregates, which are slightly stronger than the macroaggregates and, finally, the smallest microaggregates which are the most stable (Tisdall and Oades, 1982). The age and amount of C in each size class also follows this aggregate hierarchy: the highest concentration of C is in the macroaggregates. This C is also, on average, the youngest. The lowest concentrations of C and the oldest C are in the smallest fraction or microaggregates. Different procedures are available to
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divide SOM into several fractions based on the degree of physical protection and occlusion within aggregates (Cambardella and Elliott, 1994; Golchin et al., 1994; Sollins et al., 1996; Swanston et al., 2002). Elliott (1986) fractionated SOM into decomposable and recalcitrant fractions on the basis of its location within aggregates of different sizes. Aggregates physically protect SOM by (1) forming a physical barrier between microorganisms, microbial enzymes, and their substrates; (2) controlling food web interactions; and (3) influencing microbial turn over (Six et al., 2000). It has been established that, in many soil types, the inclusion of organic materials within soil aggregates reduces their decomposition rate (Elliott and Coleman, 1988; Oades, 1984). Increases in aggregation concomitant with increases in organic C have been observed in no till systems (Paustian et al., 2000; Six et al., 2000). Tisdall and Oades (1982) found greater concentrations of organic C in macroaggregates than in microaggregates and suggested that the presence of decomposing roots and hyphae within macroaggregates not only increased C concentrations but also contributed to their stabilization. However, this may not be true for Oxisols, in which oxides are the main binding agents, rather than SOM (Oades and Waters, 1991; Zotarelli et al., 2005, 2007). 3.4.2.1. Aggregate formation and stabilization Aggregates are stabilized when large macroaggregates form from a combination of older microag gregates and fresh SOM (Fig. 2). Many of the compounds in fresh SOM are physically protected within the macroaggregate, but readily decompose if exposed. If the macroaggregate remains intact, over time, this fresh OM is converted through a combination of microbial activity and abiotic factors to recalcitrant organomineral complexes. This eventually leads to an increase in concentration of recalcitrant microaggregates within macroaggregates, increasing the amount of C sequestered in the soil. Macroaggregates only have a life span of years compared to decades for microaggregates, but stability for this period is closely linked with the conversion of fresh SOM into recalcitrant microaggregates (Puget et al., 2000). Thus, in the process of CS, the formation of microaggregates (<250 mm), where the oldest most recalcitrant SOC is found, hinges on the formation and stability of macro aggregates and the availability of fresh SOM. The ‘‘glue’’ that holds macroaggregates together results from biological activity surrounding fresh SOM, which consists of plant residues that still have a recognizable cell structure and are referred to as coarse intra aggregate particulate organic matter (iPOM) (Kogel Knabner et al., 2008). Soil aggre gates are often formed by microbial activity centered around coarse iPOM (Golchin et al., 1994; Oades and Waters, 1991). In the process of breaking down iPOM, microbes deposit polysaccharides and other chemicals that act as binding agents in the soil. These binding agents stick mineral particles and microaggregates together, giving structural integrity to the macroaggregate.
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Fresh residue
t1
Coarse iPOM Fine iPOM Macroaggregate
Aggregate formation
CO2
t2 Old microaggregate New microaggregate CO2
t3 Reduced microbial activity t4
Free microaggregates POM (new and old)
Figure 2 A schematic drawing of the formation and hierarchy of soil aggregates. iPOM ¼ intra-aggregate particulate organic matter; POM ¼ particulate organic matter; t ¼ time. Modified from Six et al. (2000); copyright Elsevier.
This also reduces air and water movement, creating anoxic conditions and slowing down microbial activity and decomposition of SOM within the macroaggregate. In addition, roots and hyphae grow around the iPOM, further physically protecting and stabilizing the macroaggregate (Oades and Waters, 1991). Hyphal exudates from arbuscular mycorrhizal fungi such as glomalin are closely linked with aggregate stabilization (Wright and Upadhyaya, 1998). They are found in high concentrations in the soil, have high recalcitrance, and often they form coatings on soil aggregates even after hyphae have senesced. Exudates produced by roots can also help in the physical and chemical binding of smaller microaggregates into larger macroaggregates. Plants with higher root densities were found to have higher aggregate
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stability, SOC, and microbial biomass in a greenhouse study (Haynes and Beare, 1997). Macroaggregate formation is dependent on a combination of products of these microbial communities, roots, and hyphae. The rate of aggregation is also dependent on the type of OM and its ability to support microbial populations (Angers and Chenu, 1997). Carbon to nitrogen (C/N) ratios in SOM affect biochemical recalcitrance against microbial activity and, subsequently, rates of decomposition. Furthermore, OM high in lignin and other large molecules made of complex aromatic amorphic carbon structures are difficult for microbes to break down and can remain intact in the soil for longer periods of time. In the short term, materials high in sugars and proteins are broken down more quickly. Thus, biochemical recalcitrance can allow SOM to remain longer, giving it a chance to form organomineral complexes. This means that over time, coarse iPOM is broken down into fine iPOM. Coarse iPOM is much more susceptible to decomposition while fine iPOM binds with mineral particles and microbial products and forms more recalcitrant SOC (Six et al., 2000). Thus, manage ment practices that favor the building and maintaining of soil macroaggre gates are important to the recalcitrance of iPOM and its incorporation into microaggregates. The recalcitrance of microaggregates is due to a combination of different properties. The fine iPOM that they are composed of is a collection of organomineral complexes that display hydrophobic qualities. This creates a physical barrier to microorganisms that would otherwise break down the OM. In addition, OM fills micropores in these aggregates, leaving only very small mesopores (2–50 nm). Bacteria and even enzymes cannot penetrate the mesopores to attack OM in the interior of the microaggregate (Bachmann et al., 2008). Because microaggregates are mostly comprised of organomineral complexes, they also have lower levels of N, P, and organic C than macroaggregates, which are comprised of more recent organic C (Elliott, 1986). 3.4.2.2. Factors affecting soil-aggregate formation Soil type, climate, landscape position, ecology, and anthropogenic factors all play a major role in aggregate formation and SCS (Christensen, 1996). In the context of discussion on the impacts of agroforestry on CS, it is important to understand the role of these environmental factors in soil aggregate forma tion. In addition, the variability in results from site specific studies can be better understood and their broader implications ascertained in light of the effect of these environmental factors.
3.4.2.2.1. Soil texture Soil texture plays a large role in the number and kind of primary organomineral complexes that are formed (Christensen, 1996).
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Clays form the majority of complexes with organic C, and can greatly enhance aggregation and the stability of those aggregates. In addition, clay has been found to be closely positively correlated with physical protection of SOM (Hassink and Whitmore, 1997). Overall, clay is positively correlated with SOC in the soil (Jobbagy and Jackson, 2000). The importance of clay in SOC content in soil increases with soil depth, playing a larger role than climate in deeper horizons (Jobbagy and Jackson, 2000). In addition, clayey soils tend to aggregate due to wet–dry cycles as a function of the mineral properties (Horn and Smucker, 2005). Therefore, soils that have high clay content exhibit strong aggregate formation and stability and follow classical models of aggregate hierarchy (Fig. 2). For example, Oades and Waters (1991) found that Mollisols and Alfisols have a strong soil aggregate hierarchy. John et al. (2005) also found that Alfisols displayed aggregate hierarchy and that this hierarchy was greatly affected by land use. On the other hand, sands do not form organomineral complexes, and must rely on physical binding of roots, hyphae, and related OM for aggregate formation. Thus, the aggregates that are formed in sandy soils such as Spodosols are typically weak although they do still exhibit aggregate hierarchy (Sarkhot et al., 2007). The movement of SOC down in the soil profile to the Bh horizon also occurs in Spodosols, and C is sequestered deeper in the soil profile (Sarkhot et al., 2007). In addition to texture, other factors that are important to aggregate formation and stability are similar to those that determine soil quality, including a combination of aeration, soil moisture, flora and fauna, climate, and OM inputs. For example, Chen et al. (1997) found that Mollisols were good at forming stable, long lasting soil aggregates due to a combination of these soil quality determining factors. 3.4.2.2.2. Reactive properties Reactive properties of the minerals making up the soil can also play an important role in aggregate formation. When the key binding factors are oxides instead of OM, such as in Oxisols, soil aggregation is dictated by completely different physical and chemical processes. Unlike most other soil groups, Oxisols do not display the same hierarchy of soil aggregate formation and structure (Oades and Waters, 1991). Other soils have higher levels of SOC in macroaggregates than in microaggregates because microaggregates are bound together by OM in the macroaggregate. However, since oxides are the major binding agent in Oxisols, they do not display this same framework of OM build up. In a review, SOC was found to have poor correlation with soil aggregates in tropical soils compared to temperate soils (Six et al., 2002). In Brazil, two Oxisols had higher levels of macroaggregates and higher levels of organic C, but these factors were not well correlated (Zotarelli et al., 2005). Similar to clays, ferric and aluminum oxides can form complexes with SOM that are hydrophobic, repelling decomposing organisms (Bachmann et al., 2008).
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Although Oxisols make up a great deal of tropical soils, the structure and movement of SOC through these soils has not been studied in detail. 3.4.2.2.3. Climate Climatic factors such as temperature and humidity greatly affect the activity of microbial communities and the breakdown of OM in soil aggregates (Carter, 1996). Cold or dry climates slow down processes leading to slower aggregate formation and breakdown. On the other hand, moist and/or warm climates have very high microbial activity leading to a fast turnover of OM in the soil. Although moist climates have higher microbial activity, very wet climates can have anoxic (anaerobic) soil conditions, leading to little OM breakdown. Thus, cooler and wetter climates have greater potential to sequester carbon (Lal, 2006). On the other hand, dry and hot climates have less potential. This is due to the amount of organic C inputs as well as the rates of C cycling. While hot climates have rapid C cycling, dry climates have low C inputs. Also, wetting and drying cycles can greatly increase aggregation of soils especially if they are high in clays (Horn and Smucker, 2005). In addition, freeze thaw cycles in temperate climates can also be important to aggregate formation (Chen et al., 1997). 3.4.2.2.4. Plant species Species of plants can have a great impact on the type of OM introduced to the soil, which can affect aggregate formation and recalcitrance (Jasinska et al., 2006). Nitrogen fixation and mycorrhizal associations can increase nutrient availability, boosting microbial popula tions and resulting in higher levels of SOC and aggregate stability (Haynes and Beare, 1997). Moreover, different plant species produce different types and amounts of plant residues affecting the total amount of SOM as well as the type and the ability of microorganisms to break it down. The properties of different SOM on a molecular scale can have a great impact on its resistance in microaggregates to microbial attack (Bachmann et al., 2008). In addition, plants with greater root density have been found to have higher levels of SOC and aggregation (Haynes and Beare, 1997). Woody, deep rooted plants can increase the amount of SOM and microbial activity deep within the soil profile compared to shallow rooted grasses (Haile et al., 2008; Jobbagy and Jackson, 2000; Liao et al., 2006). Percent total SOC at different depths differed substantially among plant types with levels in the top 20 cm of 50%, 33%, and 42% between forests, shrublands, and grass lands, respectively (Jobbagy and Jackson, 2000). Liao et al. (2006) also found increased aggregate stability and increases of 100–150% in SOC of wood land succession over grasslands compared to the remnant grassland in the Rio Grande Plains of Texas. John et al. (2005) found that SOC was much higher in a spruce (Picea abies (L.) H. Karst) stand than grassland, wheat (Triticum aestivum L.), or maize fields, primarily due to high surface inputs. Similarly, Wick et al. (2009) found higher concentrations of C on
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shrublands than grasslands growing on semiarid reclaimed mine sites in Wyoming. Clearly, soil aggregates and size fractions have an important effect on the retention of C in soil, and environmental factors play a major role in aggregate formation. However, information on aggregate formation under AFSs is scanty. Udawatta et al. (2008) reported that in an Alfisol in Missouri, USA, the agroforestry buffer treatment had more water stable aggregates than the grass buffer and row crop treatments at 0–40 cm soil depth. In recent studies conducted on different AFSs in different ecological regions by the Center for Subtropical Agroforestry (CSTAF), University of Florida, Gainesville, FL, USA (described in Section 4.3), wide variations in the distribution of size fractions (<53, 53–250, 250–2000 mm diameter classes) were found in different soils (Table 4). With the knowledge of the mecha nism of aggregation and the environmental factors that affect it, manage ment practices can be tailored to optimize conditions for CS. For example, if the soil is sandy but has a deeper clay horizon, species that are deep rooted could be selected to increase aggregation and carbon storage deeper in the horizon. These and other management practices that affect soil aggregation in light of the above mechanisms and environmental factors of aggregate formation are discussed in Section 5.
4. Carbon Sequestration in Agroforestry Systems: Measurements This section presents a review of the various methods employed and the results obtained in measuring/estimating CS in AFSs, both above and belowground. The aboveground measurements are mostly direct deriva tives of biomass measurements/estimates, and are relatively straightforward compared to belowground measurements. Therefore, the major emphasis of the section is on belowground measurements.
4.1. Aboveground (vegetation) Aboveground measurement of CS involves summing up the amount of harvested and standing biomass. Estimation of tree biomass by whole tree harvesting is an old approach. Nair (1979) used that procedure for estima tion of coconut (Cocos nucifera L.) biomass: cutting down sample trees, separating various parts (stem, leaves, inflorescence, etc.), digging out and washing the roots, determining their dry weights from samples of each part, and adding them up to get the total biomass. Parrotta (1999) followed a similar procedure for estimation of tree biomass and C content in Panama. After dividing up the harvested representative trees into their various
Table 4
Distribution of different soil size-fractions under some agroforestry systemsa Percent (by weight) distribution of size fractions (mm)
System; soil order; location
Silvopasture; Spodosols; Florida, USA
Shaded cacao; Oxisols; Bahia, Brazil
Homegardens; Inceptisols; Kerala, India
Parkland system; Alfisols; Se´gou, Mali, West Africa a
Soil depth (cm)
0–5 5–15 15–30 30–50 50–75 75–100 0–10 10–30 30–60 60–100 0–20 20–50 50–80 80–100 0–10 10–40 40–100
< 53 (silt þ clay)
1.8 2.3 2.5 2.5 2.1 2.4 4.4 6.0 7.1 7.3 15.7 16.5 18.5 17.8 49.5 46.6 45.1
See Table 6 for description of various systems and their locations.
53 250 (microaggregates)
58.7 60.4 62.1 61.5 64.0 63.7 13.0 18.0 21.0 20.0 35.4 35.5 36.5 35.0 37.4 37.5 40.2
250 2000 (macroaggregates)
36.7 35.9 32.8 33.6 30.4 31.3 80.0 72.0 70.0 72.0 49.0 48.0 45.0 47.2 12.9 15.8 14.6
References
Haile et al. (2010)
Gama Rodrigues et al. (2010) Saha et al. (2010)
Takimoto et al. (2009)
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components (branchlets, branches, dead branches, leaves, roots and fine roots), C content in each component was measured by combustion of the samples. The whole tree biomass and carbon content so derived were then used to develop a regression curve. Such whole tree harvest procedures are extremely time and labor intensive. Takimoto et al. (2008a) used allome tric equations for estimating standing tree biomass in the parkland AFSs in the Sahel. However, species specific allometric equations were not available for all tree species in that study region; therefore, the general equations from FAO (1997) were used for parkland trees, as recommended by UNFCCC (2006). In other cases, more simple analyses were used for large scale estimations. Dixon et al. (1993) made estimations by measuring the volume of stem wood and multiplying it with species specific wood density; that number was then multiplied by 1.6 to get an estimation of whole tree biomass. Carbon content was assumed to be 50% of the estimated whole tree biomass, and root biomass was excluded. This rough estimation was then used for more extensive estimations of global forest biomass. Besides the concerns about the accuracy of these estimates, such deter minations of biomass and C content can be difficult for smallholder agro forestry plots that comprise much of the agroforestry in developing countries. As described in Section 2.2, agroforestry in many developing countries involves a multitude of plants of varying growth habits yielding diverse economic products. The species are planted and their products harvested, mostly for household consumption, throughout the year, with no defined planting and harvesting schedules. Variations in tree manage ment can be another issue: trees in AFSs may be pruned depending on management practices or may have different growth forms due to differ ences in spacing compared to natural (forest) systems. Furthermore, no two agroforestry plots are similar: each may be unique in terms of plant compo sition, planting arrangements, and stand densities. Thus, determination of biomass production from indigenous AFSs is a challenging task, and makes extrapolation from one system to others very difficult.
4.2. Belowground (soil) The determination of belowground organic carbon dynamics in AFSs is crucial for understanding the impact of the system on CS, but it is difficult. Organic C occurs in soils in a number of different forms, including living root and hyphal biomass, microbial biomass, and as SOM in labile and more recalcitrant forms. The complex interactions of these different forms make measurement, estimation, and prediction of SCS a daunting task. Methods that have been used for assessing the content and attributes of SOC will therefore be briefly reviewed here.
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4.2.1. Measurement and estimation Soil organic carbon is often measured on a whole soil basis. The Walkley– Black procedure was employed extensively in the past. It involves digestion of OM in the sample through oxidation with potassium dichromate. The digestion is incomplete, ranging from 60% to 87% depending on the sample (Walkley, 1947); therefore, an average correction factor of 1.33 is applied. This could lead to over or underestimations depending on the soil. More over, the use of potassium dichromate makes the technique less environ mentally friendly. Because of these concerns, the procedure has since been abandoned (Kimble et al., 2001). Currently, many studies measure SOC by quantifying the amount of CO2 produced through heating in a furnace. Other studies measure the change in weight of the sample after heating. However, the temperature used can vary; it needs to be standardized for accurate comparison of different studies. The presence of carbonates and charcoal in the soil can also skew results (Kimble et al., 2001). These measurements of C on a whole soil basis give information about total concentrations, but other analytical procedures are needed to determine details of the form and recalcitrance of the stored C as well as where it is stored. In order to gain a better understanding of these details of CS in soils, attention has focused on the study of soil aggregates. 4.2.1.1. Soil aggregates As explained in Section 3.4.2, study of soil aggregates is critical to SCS determinations. Most soil aggregation studies use some adaptation of the wet sieve method. This involves putting soil in the top of a nest of sieves and lowering and raising the sieves in water to simulate natural wetting of the soil (Yoder, 1936). The different aggregate classes then break down and are caught in different levels of the sieve. This technique has been widely used and is easy to replicate. The wet sieve method has been carried out for a range of soil types, including Alfisols, Inceptisols, Mollisols, Oxisols, Spodosols, and Ultisols (Filho et al., 2002; Haile et al., 2008; Oades and Waters, 1991; Six et al., 1998; Williams and Petticrew, 2009). Usually the recovery rate of the sum of aggregates com pared to the whole soil is high. For instance, Haile et al. (2008) had a recovery rate of 97.5% suggesting minimal loss caused by methodology on aggregate size fractions. Measurement of the number of soil microaggregates within macroaggregates can give important information about the quality of the macroaggregate and the amount of SOM it is protecting. The technique developed by Six et al. (2000) is the commonly used one. It aims at breaking up the macroaggregates while minimizing disruption of microaggregates. Macroaggregates are shaken on a 250 mm mesh sieve with glass beads immersed in water; water is run through the system and microaggregates are flushed through to a 53 mm mesh, minimizing the amount that may have
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been broken up by the glass beads. Sieving on the 53 mm mesh ensures that only water stable microaggregates of 53–250 mm diameter remain. The weight of the sand that is the same size as the aggregates is then corrected for (sand is usually not part of the aggregate, so its weight should be removed from the aggregate weight totals). Six et al. (1998) also derived a method to isolate particulate organic matter (POM) in the whole soil and within aggregates. This is a valuable measurement for determining the amount of fresh OM in the soil and within aggregates. The procedure involves isolating the POM that is not occluded, and then breaking up aggregates to find the iPOM. The aggre gates are flocculated and run through a nest of sieves, with any particulate matter that is larger than sand silt or clay isolated. This is also a way of separating measurements of mineral associated SOM from iPOM. Because iPOM can comprise a large fraction of the OM in an aggregate, this is an important way to get better estimates of the more recalcitrant forms of broken down and mineral associated SOM. Sand corrections have also become an important addition to making accurate C and N measurements of aggregates (Elliott et al., 1991). Because sand grains do not have any OM, they must be excluded from the measurements of OM in that size class. The amount of OM found in each aggregate size class can be found using sonication (Cambardella and Elliott, 1993a). The vibrations produced by the ultrasonic probe disrupt the bonds that hold the aggregate together. However, this technique has not been standardized, and using too high energy levels can lead to measurement of an increased concentration of SOC in microaggregates, skewing results (Roscoe et al., 2000). This hap pens because the larger pieces of OM can be broken up and associated with microaggregates, as in Oxisols, where soil macroaggregates can have very high strength. Roscoe et al. (2000) found that a threshold strength of 260– 275 J mL 1 was needed for breaking up unstable aggregates while leaving stable aggregates in an Oxisol. Due to vastly different levels of cohesion, various soils have different dispersive energies. For example, Sarkhot et al. (2007) only needed an energy level of 17–113 J mL 1 for dispersion of Florida Spodosols, while Cambardella and Elliott (1994) used a dispersive energy of 22.5 J mL 1 for a Mollisol. The problem with using different dispersive energies is that with an increase in energy, more OM becomes associated with smaller aggregate fractions. This would skew results depend ing on the type of soil. Another method recently developed to determine soil quality on areas with different tillage regimes is stratification ratio (SR; Sa and Lal, 2009). The SR is used as an indicator of soil quality and can be an index of SCS. It was developed to compare conventionally tilled areas and areas that have been converted to no till. Conventional tillage homogenizes SOM in the top 20 cm, breaking soil aggregates and leading to loss of CO2. No till leads to the gradual increase in stratification of SOM, with higher concentrations
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near the surface from plant residue inputs, and lower concentrations deeper in the soil profile. The SR can be used to determine where in the process of stratification a soil is, and can indicate the soil’s quality. This could be used to look at other areas as well to determine the rates of C incorporation from surface inputs, and thus help to gauge rates of CS. Since the majority of organic carbon in the soil is found in soil aggre gates, we can have a better understanding of how carbon is entering, moving through, and leaving the soil by understanding the structure and cycling of these aggregates. Previously, many studies have looked at SOC on a whole soil basis. Although this is valuable and gives us a general understanding of the amount of carbon being sequestered and its residence time in the soil, understanding aggregates will give us the ability to predict future levels based on inputs and current conditions. By knowing what factors are likely to influence aggregate formation and stability, we can predict what factors to take into consideration. We will thus be able to better develop and adopt new agricultural and land management practices to optimize CS both immediately and for the long term. 4.2.1.2. Measuring belowground living biomass In addition to SOM, belowground NPP (biomass) is a major C pool (Nadelhoffer and Raich, 1992). However, belowground biomass is difficult to measure. The root to shoot ratio is therefore commonly used to estimate belowground living biomass. The ratios differ considerably among species and across ecological regions. These difficulties pose a serious problem in our understanding of belowground CS in living biomass. Living microbial biomass can be an important indicator of OM decom position and turnover. There are myriad procedures for gaining a detailed understanding of the makeup of microbial populations, but they are often complicated and give more detail than is needed for basic understanding of microbial activity and biomass. Common measurements for microbial bio mass and activity include chloroform fumigation or adenosine triphosphate (ATP) assays. Chloroform fumigation involves fumigation of a soil sample with chloroform, which lyses the majority of microbial cells (Vance et al., 1987). The small fraction of microbes that remain metabolize the C released by the dead cells and produce CO2; the sample is left for a period of time, and the amount of CO2 produced is measured. A common method is to place an alkali in the container along with the fumigated sample and later titrate it against an acid to determine the amount of CO2. The ATP luciferin–luciferase assay is based on the premise that the cells are broken up and then mixed with luciferin–luciferase, the enzyme in fireflies that make them glow. The ATP binds with the luciferase and creates light; the more the ATP present, the more the intensity of light produced by the sample. This assay can be used to compare microbial populations in relation to aggregate stability (Williams and Petticrew, 2009). However, ATP can
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vary widely from sample to sample and determining statistically different results is difficult. In spite of these limitations, these microbial assays are valuable tools to understand the vital role that microbes play in CS though their breakdown or tying up of C and their relationship to soil aggregates. 4.2.1.3. Isotope measurements and carbon dating Numerous studies (Accoe et al., 2002; Bernoux et al., 1998; Ehleringer et al., 2000; Swap et al., 2004) have used stable C isotope ratio analysis to trace the source of SOC to plants that follow C3 and C4 photosynthetic pathways. The reported d13C values range from 19% to 9% for C4 plants and 35% to 20% for C3 plants (Biedenbender et al., 2004; Staddon, 2004). When a C4 plant is introduced to a system that had previously been under a C3 plant or vice versa, the relative contribution of new versus old soil organic C can be quantified using the mass balance of stable isotope contents based on the change in 13C signature of SOM (Dawson et al., 2002; Del Galdo et al., 2003). In a combined tree þ grass land use system, C3 inputs are dominated by either woody shrubs or trees and C4 inputs are dominated by grass (McClaran and McPherson, 1995). The d13C isotope technique requires comparison between a site where the photosynthetic pathway of the dominant vegetation (C3 or C4) has been changed and a reference site where the photosynthetic pathway of the vegetation remains unchanged. Haile et al. (2010) used that technique in silvopasture systems of the southeastern USA, composed of slash pine (Pinus elliottii Engelm), a C3 plant, d13C 29.5%, with bahiagrass (Paspalum notatum Flu¨gge), a C4 plant, d13C 13.3%, as the understory species (Section 4.3.2). Com bining SOM fractionation techniques with the 13C natural abundance technique offers a compelling approach to investigating small shifts in soil C stores that would be significant in the long term but might not be detected by conventional methods. Carbon 14 (14C) dating can be used to determine the age of SOM. When a plant incorporates carbon from CO2 in the atmosphere, it takes in a proportional amount of 14C to the amount in the atmosphere. However, once the organism dies, the amount of 14C slowly decreases at a fixed rate due to radioactive decay. Ages of carbon in the soil can thus be determined (Kaiser et al., 2002). The contribution of fossil carbon compared to OM in soil aggregates can also be determined using 14C dating (Flessa et al., 2008; Rethemeyer et al., 2004). Flessa et al. (2008) used it to determine the rate of decomposition of SOM compared to fossil carbon. Carbon dating can also be used to track the recalcitrance of different SOM fractions. Due to nuclear weapons testing, there was a sharp increase in atmospheric 14C starting in 1954 and spiking in 1963. This spike, referred to as bomb 14C, can be used as a bench marker for measuring the age of SOC (Rethemeyer et al., 2005). However, in order to use bomb 14C, information of the inputs and losses of 14 C up until 1954 is needed. Other studies have used 14C labeling of plant
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roots or other OM inputs to determine the mechanisms and location of OM incorporation into soil aggregates (Gale et al., 2000). This can be carried out by labeling the plant roots with 14C. Measurements of 14C in different aggregate fractions can then be used to track the decomposition and incor poration of the roots. An on going study using 14C in agroforestry combi nations of Eucalyptus spp. with fodder grass (Panicum spp.) or rice (Oryza sativa) as understory species in the Oxisols of Minas Gerais state, Brazil showed that, at 50–100 cm soil depth, the silt þ clay fraction (<53 mm) had higher (negative) values of d14C than the 53–250 and 250–2000 mm frac tions (range of d14C values: 348.3 to 257.2). The d14C values were positive in the surface 0–10 cm soil, indicating that the OM in the surface soil was of recent formation, and that the mean residence time of SOC was greater at the lower depth and in the most stable fraction (<53 mm) of this AFS (Tonucci, 2010). 4.2.1.4. Modeling In order to understand global carbon cycling, models that incorporate rates of terrestrial carbon cycling are used. These models are based on a collection of assumptions that are formed from our understand ing of ecological processes including tree growth, and decomposition pro cesses in the soil. The CENTURY and RothC models are the most widely used soil carbon models. The former, originally developed for grassland soils by Parton et al. (1987), predicts long term soil C cycling and SOM decompo sition for forest and agricultural lands. It models the cycling of C and other elements (phosphorus, nitrogen, and sulfur) and their interactions, focusing specifically on the effects of species type and management practices such as tillage to model agricultural systems. It accounts for agricultural systems, forests, or savannah but does not model for integrated tree–crop systems such as agroforestry. This could be an interesting and important addition to this model in order to improve CS estimates in global soils. The Rothamsted model (RothC model) takes into consideration organic pools in terms of how labile they are. The model was developed for agricultural, forest, and grassland systems and takes climate, manage ment, and soil type into consideration, and soil samples are used for calibra tion (Jenkinson, 1990). This model was based on the long term experiments studying OM on the Rothamsted sites in England. Although the parameters of the model are comparatively simple, they are surprisingly good at mod eling the breakdown of OM at the site. With slight modification to the decomposition rate of the resistant plant material pool and the humic pool, the model was accurate when compared to measured field data in Australia (Skjemstad et al., 2004). However, the model may not be as appropriate for predictions of tropical agroforestry sites; for example, decomposition rates were greatly underestimated when RothC was applied to an AFS in Nigeria (Diels et al., 2004).
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The G’DAY is an ecological model based on the CENTURY model that is used to predict the effects of elevated CO2 and raised temperature on ecosystems. By using this model, Medlyn et al. (2000) determined that soils play a more important role in long term NPP than aboveground plant growth. The APSIM (Agricultural Production Systems Simulator) model is also used commonly, although it is more focused on crop production and yields in terms of soil conditions (McCown et al., 1996). In order to get ecosystem estimates, these soil carbon models must be incorporated into larger ecosystem models. However, in order to do that, the information required for the model must be easily attainable, and the model must run at the same time step as the other aspects of the ecosystem level model. An ecosystem level model used for alternative management practices that estimate total CS is the CO2FIX (Masera et al., 2003). It is applicable to temperate and tropical systems that take into account forest stands, products, dead wood, and soil carbon. It is used for estimation of uneven aged or multicohort systems such as selectively cut forests or AFSs. It is a synthesis of various preexisting models that cover each of the para meters and the model used for the soils aspect is YASSO. This model differs from CENTURY and RothC because it only takes into consideration very recalcitrant soil C or labile C, without any intermediate forms, because the time step of this model is 1 year, within which period these intermediate forms do not make a difference. Another model that though not focused on CS per se could be a valuable tool is the yield SAFE model, developed to assess the environmental and economic impact of agroforestry in Europe (Werf et al., 2007). It involves input of only basic parameters such as temperature, precipitation, soil type, and species selection and spacing. It gives information about yields, and effects on erosion and other environmental factors. Because it was designed for use in AFSs, it differs from other described models that were developed for forests or agricultural land, and it could be a valuable tool to integrate into carbon modeling for AFSs. 4.2.2. Methodological difficulties Although several methods have been developed to determine or estimate SCS as described above, these methods have, unfortunately, not been perfected for universal application. They sometimes differ from experiment to experiment, making it difficult to compare or synthesize results. For example, size of soil aggregates has not been standardized; macroaggregates have been described in the range of 4000–250 mm in different studies (Jastrow, 1996; John et al., 2005; Madari et al., 2005; Williams and Petticrew, 2009). Obviously, this can greatly affect the conclusions made when comparing the differences under different management practices, soils, and environments.
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A major issue that lacks uniformity is soil sampling depth. Most soil studies are limited to the surface soils to 20 or 30 cm depth. The importance of sampling beyond the surface soil cannot be overemphasized while study ing tree based systems such as agroforestry, not only because tree roots extend to deeper soil horizons, but also because of the role of subsoil in long term stabilization of C. The lack of uniformity in breaking points between soil horizon depths is another procedural problem: results of a C study in the 0–5 cm surface horizon cannot realistically be compared with those of 0–50 cm study. Thus, it is likely that the reported values of CSP in agroforestry and other tree based systems (Table 5) are inaccurate and often times may not be comparable. Modeling of AFSs also faces issues of accuracy and standardization. The models described above were developed for natural ecosystems or agricul tural systems and there is some debate about the best for modeling of AFSs. In addition, they all rely on different assumptions and are often hard to incorporate into larger ecosystem models, and they require different levels of input. Obviously, more studies are needed on these aspects to produce accurate results. As mentioned in Section 4.2.1.2, estimations of belowground living biomass based on aboveground production can be misleading due to differ ences in growth form of agroforestry trees and management practices that can lead to underestimations of root biomass. Furthermore, AFSs can demonstrate high levels of spatial heterogeneity and extrapolation between one AFS and another or even from one area of an agroforestry plot to another can be misleading. Thus, the lack of standard procedures of mea surement or estimation is a serious issue in CS studies in agroforestry. The uncertainties arising from the lack of uniform methods for describ ing area under agroforestry (Section 2.4) is another difficulty in gauging the Table 5 Indicative values of soil carbon sequestration potential (SCSP) under major agroforestry systems in the tropics
Agroforestry systems
Shaded perennial systems Alley cropping Homegardens Tree intercropping Silvopasture (semiarid grazing systems)
System characteristics
SCSP to 1 m soil depth (Mg C ha 1)
Time frame (year)
New/young, < 5 year old New/young, < 5 year old > 750 trees ha 1 50 trees ha 1 < 10 year old; 50 trees ha 1
100–200
10
30–120
> 10
100–180 70–120 30–50
> 20 > 20 > 25
Source: Adapted from Nair et al. (2009b); copyright Elsevier.
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importance of agroforestry in CS. Although some studies carry out chron osequences to see the change in C, these are few and not well standardized. Since changes in C stock are unlikely to be linear through time, under standing the nature of the curve of C storage over time is important to understand the periods when most C is being sequestered. In addition, it is difficult to know if the residence time of C that is sequestered initially in a system differs from that of C that is sequestered later. Are the cycles that the initial C and later C additions go through the same? A large number of many such questions need to be answered for realistically assessing the impact of agroforestry and other management practices on CS.
4.3. Soil carbon in agroforestry compared with other land-use systems Agroforestry systems are perceived to have higher potential for sequestering carbon, especially under soils, compared with cropping or grazing systems under similar ecological conditions (Section 3.1); however, field studies comparing such systems have been very few. Following an analysis of the reported values in literature and field experiences, Nair et al. (2009b) prepared some ‘‘best bet estimates’’ of the ranges of SCS under different AFSs in the major agroecological regions of the tropics. The suggested values ranged from 5 to 10 kg C ha 1 in about 25 years in extensive tree intercropping systems of arid and semiarid lands to 100–250 kg C ha 1 in about 10 years in species intensive multistrata shaded perennial systems and homegardens of humid tropics (Table 6). Considering the importance of information of this nature, some such studies undertaken in the recent past by CSTAF at the University of Florida, Gainesville, FL, USA, referred to in Section 3.4.2.2 are summarized below. 4.3.1. Study locations and procedures The study involved six different locations in five continents and included several agroforestry and other land use systems (Table 6; Fig. 3). At all sites, soils were sampled up to at least 1 m depth in multiple depth classes and fractionated into three size classes (250–2000, 53–250, and <53 mm), and the C content in each determined. Stable isotope ratio was used (Section 4.2.1.3) to determine, wherever applicable, the relative contribution of trees and grasses to soil C. The experimental details for each study are described in the respective publications listed in Table 6. 4.3.2. Significant findings SOC content in AFSs in different locations in comparison with other relevant land use systems in the same locations is presented in Fig. 4A–D. A summary of the difference between AFS and comparable non AFS, expressed as percentage of C store in AFS at different locations is given in
Table 6 Site and system details of the University of Florida, Center for Subtropical Agroforestry research sites for carbon sequestration studies at different locations Sites Location; coordinates
Climate (m.a.p., mm; mean temp. range, C)
Soil order
Agroforestry systems
References
Silvopasture: slash pine (Pinus elliottii Engelm.) þ bahiagrass (Paspalum notatum Flu¨gge); 12–14 year ‘‘old’’ (i.e., since establishment) Dehesa oak silvopasture (Quercus suber L.); > 80 year old
Haile et al. (2008, 2010)
1. Florida, USA; 28–29 N; 81–83 W
Humid subtropical; 1330; 3 to 28
Spodosols
2. Central Spain; 39o590 N; 6o60 W
Alfisols
3. Kerala, India; 10 320 N; 76 140 E
Subhumid Mediterranean; 600; 8–26 Humid tropical; 2700; 27–32
4. Se´gou, Mali; 13 200 N; 6 100 W
Semiarid tropical; 500–700; 29–36
Alfisols
5. Bahia, Brazil; 14 00 S; 39 20 W
Humid tropical; 1500; 25–32
Oxisols
6. Minas Gerais, Brazil; 17 360 S; 46 420 W
Cerrado: Subhumid tropical; 1350; 20–30
Oxisols
Inceptisols
Homegardens: Intensive multispecies mixtures of trees, shrubs, and herbs in small (< 0.5 ha) holdings; > 40 year old Intercropping under scattered trees, > 30 year old; and 9 year old plantings of live fences and fodder banks Cacao (Theobroma cacao L.) under thinned natural forest (cabruca) or planted shade trees; 30 year old Silvopasture: Eucalyptus spp. with understory of Brachiaria spp. (fodder grass); 40 year old
Howlett (2009) Saha et al. (2010)
Takimoto et al. (2008a, 2009)
Gama Rodrigues et al. (2010) Tonucci (2010)
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2
1
Silvopasture Florida, USA
3
Dehesa Northern Spain
Homegardens Kerala, India
2 1
4
3
6
4
5 6
Silvopasture MG, Brazil
Shaded cacao Bahia, Brazil
Parklands Ségou, Mali
Figure 3 Various agroforestry systems at different research locations in the University of Florida, Center for Subtropical Agroforestry study on soil carbon sequestration in agroforestry systems. See Table 6 for location details and brief system descriptions.
Fig. 5. The results of these investigations have been reported in various publications (Gama Rodrigues et al., 2010; Haile et al., 2008, 2010; How lett, 2009; Nair et al., 2007b; Saha et al., 2009, 2010; Tonucci, 2010). The salient results of this multilocation study showed that:
The amount of C stored in soils depends on soil qualities, especially, silt þ clay content (Haile et al., 2010; Takimoto et al., 2009). Tree based agricultural systems, compared to treeless systems, store more C in deeper soil layers under comparable conditions (Fig. 4A). Long term AFSs (e.g., shaded perennials and homegardens) store similar or more amounts of SOC in upper soil layers compared with adjacent natural forests (Fig. 4B). Higher SOC content is associated with higher species richness and tree density (Saha et al., 2009). Soil near the tree, compared to away from the tree, stores more C (Howlett, 2009; Takimoto et al., 2009). C3 plants (trees) contribute to more C in the silt þ clay sized (<53 mm) fractions than C4 plants in deeper soil profiles (Haile et al., 2010).
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A
C3 contribution to soil organic carbon, % 0
20
40
80
60
100
120
0
20
Soil depth, cm
40
60
80
100 Silvopasture (53–250 μm)
Silvopasture (250–2000 μm)
Treeless pasture (250–2000 μm) Silvopasture (<0.53 μm) Treeless pasture (53–250 μm) Treeless pasture (<53 μm)
120
B
SOC (Mg ha–1 cm–1) 0
0
0.5
1
1.5 b b b
b
2
2.5
ab
a
3
20 Depth (cm)
c
b
40
a
b b
b
60
d
c
a
b
b b
80 d
c
b
b
a
b 100 Forest
Cocounut
HGL
HGS
Figure 4 (Continued)
Rubber
Rice paddy
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C
b a
0–10
b b a
10–30 cm
c a b b
30–60
b
60–100
ab a
0
2
4
6
SOC, Mg ha–1 (in 1cm of soil) Cabruca
Cacao with erythrina
D
Natural forest
Mg C ha–1 0
60
40
20
a ab
0–25
Soil depth, cm
b a a a
25–50
50–75
a a a
75–100
a a a
2m 5m 15 m
Figure 4 (A) Tree (C3) contribution to soil organic carbon with depth at silvopasture and treeless pasture locations at an Ultisol site in Florida, USA. Source: Nair et al. (2007b); with permission from Scientia Agricola. (B) Depth-wise mean soil organic carbon (SOC) stock in the whole soil up to 1 m depth in six different land-use systems in Thrissur district, Kerala, India. Lower case letters indicate differences (at the 0.05 probability level) in SOC among land-use systems compared within 1 m soil depth. HGL ¼ Large Homegarden (>0.4 ha); HGS ¼ Small Homegarden (< 0.4 ha). Source: Saha et al. (2010), with permission from Springer. (C) SOC storage at different depths in three land-use systems in Bahia, Brazil. Values followed by the same letter(s) within each depth are not significantly different according to the Tukey test (p ¼ 0.05). Source: Gama-Rodrigues et al. (2010), with permission from Springer. (D) Soil carbon storage in the whole soil in different soil depths up to 100 cm as it varies from distance to Quercus suber L. in the whole soil at the St Esteban Farm, Extremadura, Spain. At each depth, means that differ statistically (p < 0.05) are labeled with different lower case letters. Source: Howlett (2009), with permission of the author.
275
ΔAF (%)
Carbon Sequestration and Agroforestry Systems
100 90 80 70 60 50 40 30 20 10 0 –10 –20 –30 –40 –50 –60 –70
262.5
Agroforestry versus Agricultural System
1
2
Near tree versus Far from tree
3
4
Agroforestry versus forest
5
6
7
8
Land-use types 0–50 cm
50–100 cm
ΔAF (%) = [(AF-Non-AF)/Non-AF] ⫻100
Number Systems
Location
Soil order Ulfisols
1
Pine + pasture versus treeless pasture
Florida, USA
2
Pasture under birch trees versus treeless pasture
Northern Spain
Inceptisols
3
Homegardens versus rice paddy
Kerala, India
Inceptisols
4
Under tree versus away from trees (Dehesa)
Northern Spain
Alfisols
5
Under tree versus away from trees in parkland system Ségou, Mali
Alfisols
6
Homegardens versus forest
Kerala, India
Inceptisols Oxisols
7
Cacao under shade versus forest
Bahia, Brazil
8
Brachiaria + Eucalyptus versus forest
Minas Gerais, Brazil Oxisols
Figure 5 Differences in soil carbon stock to 1 m depth between comparable AF and agricultural systems, near the trees and away from trees in AFSs, and AF and natural forests, expressed as percent of non-AFS values, at different locations. See Table 6 for additional site- and system details.
In summary, available results—in spite of their methodological difficul ties—indicate that AFSs store higher amounts of carbon, compared to single species cropping and grazing systems, in both aboveground and belowground compartments of the system. The CSP of AFSs seems espe cially significant in the soil, particularly in soil depths below 50 cm. The extent of CS will, obviously, depend on a number of site specific factors as well as system management. This latter aspect is considered in detail in the following section.
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5. Carbon Sequestration in Agroforestry Systems: Management Considerations As discussed in Section 3.1, agroforestry vis a` vis climate change is grounded on the belief that AFSs have higher potential to sequester C than pastures or field crops. Most discussions on CS also emphasize the impor tance of management practices on CS, especially in soils (Lal, 2004). It is not clearly understood, however, how the management of integrated tree and crop production systems such as agroforestry would alter the rate and magnitude of CS. If agroforestry is to be used in global agendas of CS such as the CDM, rigorous datasets are required on various aspects of this process. Most of the available information on the topic originates from reports on CS in tree plantations, and in all such reports, CS is also considered synonymous to C stock (Nair et al., 2009a,b). This section looks at how tree component management impacts the CSP above and belowground in AFSs.
5.1. Silvicultural practices Clearly, aboveground CS in trees is directly related to the production of AGB. Silvicultural practices ranging from site preparation to stand manage ment operations can alter tree growth and productivity and, by extension, improve above and belowground CS, but sometimes can also contribute to C emissions. The effects of silvicultural practices are thus complex (Fig. 6), and have been studied only scarcely (Hiroshima, 2004). Broadly, such practices fall under two groups: those favorable to CS (e.g., tree and stand management, choice of species, site quality, rotation length) and unfavor able to CS (e.g., harvesting, burning). Depending on the magnitude and intensity, the factors that foster CS also may have þ, , or 0 (neutral) effects. Practices such as weed control and fertilization may increase stand growth and promote CS (Johnsen et al., 2001), but may also emit CO2 (Section 5.4), making the picture further complicated. If agroforests are to be managed for CS, systems that maximize C gain must be developed. 5.1.1. Stand-density management The control of growing stock (density) has a tremendous impact on the stand structure (Long, 1985). Indeed, the way trees grow is dependent on stand density. Therefore, designing appropriate regimes of density to meet specific objectives is an important aspect of sound stand density manage ment (Kumar et al., 1995). In such situations, we can maximize either the individual tree size or total volume, or we can compromise one for the other, influencing the C pools. In general, higher stocking levels of trees
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Carbon Sequestration and Agroforestry Systems
Drivers Stand density regulation
Pruning
Processes
Effects
Biomass production Litter fall and decay Vegetation carbon sequestration
Fertilization/ manuring Fine root dynamics Harvesting and burning
Organic matter turnover
Agroforestry carbon sequestration Soil carbon sequestration
Choice of species Rhizodeposition
Rotation length
Site quality
Formation of soil aggregates and organo-mineral complexes
Species diversity
Figure 6 Drivers, processes, and effects of silvicultural practices on carbon sequestration potential of agroforestry.
(denser stands) enhance the vegetation C pools (Table 7). However, this may create conflicts with other stand management objectives (e.g., under story production). Although denser stands generally promote CS, exces sively high stand densities may adversely affect tree growth and productivity through competitive effects, resulting in lower vegetation C pools. Like wise, thinning improves the growth of stands and thus leads to more C assimilation, but produces a net release of C if the removed woods and slash are burnt or otherwise decomposed (Lavigne, 1991; Schroeder, 1991). Stand management practices as described above would alter litter fall fluxes, which in turn influences the SCS too (Kumar, 2008). Kunhamu et al. (2009) reported that annual litter fall of 9 year old Acacia mangium Willd. stands in southern India ranged from 5.73 Mg ha 1 in a thinned stand (remnant population density: 533 trees per hectare) to 11.18 Mg ha 1 in an unthinned stand (1600 trees per hectare), with a significant (p < 0.0001) linear relationship between stand basal area and litter fall (Fig. 7). Other
Table 7
Effect of tree spacing on C stock of 9-year-old Ailanthus triphysa (Dennst.) Alston woodlots in Kerala, India Stem wood
Spacing (m)
3 2 3 3
1 2 2 3
Density (plants ha 1)
3333 2500 1667 1111
Branch wood
Foliage
Aboveground
Roots
Total Mean annual C stock (C Mg ha 1 yr 1)
1
(C Mg ha
48.4a 47.9a 28.7b 21.1b
)
7.5a 7.0a 4.6b 3.5a
3.4a 3.8a 2.3b 2.1a
Means within a column followed by different superscripts are significantly different. Source: Adapted from Shujauddin and Kumar (2003); copyright Elsevier.
59.3a 58.6a 35.6b 26.6b
8.3a 7.3a 4.9b 2.6c
67.6a 65.9a 40.5b 29.7b
6.8a 6.7a 4.1b 3.1b
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Carbon Sequestration and Agroforestry Systems
y = 0.455x + 4.818 R2 = 0.887
Litter fall (Mg ha–1 yr–1)
14 12 10 8 6 4 2 0
5
10
15
20
Stand basal area (m2 ha–1)
Figure 7 Litter fall and stand basal area relationships in a 9-year-old Acacia mangium Wild stand in central Kerala, India (17 29 months post-thinning). Source: Kunhamu et al. (2009), with permission from Can. J. For. Res.
researchers also reported that stand thinning decreased litter fall with con comitant reductions in nutrient and OM inputs to the soil (Blanco et al., 2006; Caldentey et al., 2001; Chertov et al., 1999; Huebschmann et al., 1999). Thinning/pruning of trees also brings about changes in understory light, air/soil temperature, and soil moisture regimes and accelerate detritus turnover rates, further reducing SCS. For instance, in the above cited study of Kunhamu et al. (2009), high thinning intensities of 9 year old A. mangium Willd. stands resulted in accelerated litter decay rates. The highest soil organic C concentrations (0–15 cm soil layer) were also noted in the unthinned stands, reflecting the potential of high tree densities in promoting C retention in soil. Nevertheless, the microclimatic modifica tions associated with tree management practices such as thinning normally would promote understory production, offsetting such reductions in SCS to some extent. Thus, the effects of thinning on SCS appear to be complex. 5.1.2. Pruning Although wider tree spacing offers greater opportunities for understory cropping, spreading crowns could pose a problem in widely spaced tree stands. This will necessitate the adoption of tree management practices such as tree canopy pruning in AFSs. Crown pruning (green) generally favors stem development (Beadle et al., 2007; Kerr and Morgan, 2006; Kunhamu et al., 2010) and thus promotes CS in the stem wood, besides promoting understory production. Tree pruning operations are also customarily car ried out in the traditional tree þ crop land use systems during the cropping season, to meet the green leaf manure requirement of field crops and/or to
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facilitate greater understory light availability (Bayala et al., 2008). Pruning, however, can reduce litter fall and/or alter its periodicity, albeit temporarily (George and Kumar, 1998). Despite such short term reductions in litter fall, tree canopy pruning provides substantial quantities of green leaf manure and/or firewood.
5.2. Choice of species and species admixture Carbon sequestration potentials of tropical taxa are highly variable. Sum marizing the C stocks of several AFSs (Table 2), Nair et al. (2009b) suggested that tree growth and CSP are dependent on species, age/rotation length, site quality, and tree management. Growth differences among tree species and the ‘‘native versus exotic’’ species controversy are among widely debated but not yet resolved biological issues related to CS in AFSs. Recent reports indicating the extent of variability in aboveground and belowground CSP of native and exotic species are summarized below:
In a study of nine native and exotic taxa in the humid tropics of peninsular India, the aboveground C stock ranged from 9.9 to 172 Mg C ha 1, with the highest for exotic species such as Acacia auriculiformis A. Cunn ex. Benth., followed by Paraserianthes falcataria (L.) I. C. Nielsen (Kumar et al., 1998a). Native forest plantations (9–14 year old) in Costa Rica sequestered on an average 12.4–91.0 Mg C ha 1 aboveground (Redondo Brenes, 2007). This led to an increase in the number of native tree plantations in the Payments for Environmental Services (PES) Program during the 1990s, especially on small and medium sized farms in rural areas (Ortiz and Kellenberg, 2002). In an evaluation of 20 year old plantations of three exotic species with native forest and farmland in the southwestern highlands of Ethiopia, the average total SOC to 50 cm depth was in the range 101.2– 180.4 Mg ha 1. Total SOC stored under farmland and Pinus patula Schiede ex Schltdl. & Cham. was significantly lower than those under native forest, Cupressus lusitanica Mill. and Eucalyptus grandis W. Hill ex Maiden (Lemma et al., 2006). Comparing four neotropical tree plantations established on a degraded pasture of the Caribbean lowlands of Costa Rica, Jime´nez et al. (2007) noted that the highest SOC pool was under the native species Hieronyma alchorneoides Allemao followed by Vochysia guatemalensis Smith (132 and 119 Mg C ha 1, respectively). Furthermore, variations in growth and CSP within a particular group (exotic vs. native) are profound, but comprehensive databases describing these are lacking. From the point of view of CS, it is therefore unclear whether native species, because of their supposedly better adaptability to local conditions, would be superior to exotic ones for use in plantations
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(Nair et al., 2009a,b). Thus, it is clear that the choice of species for agrofor estry may be based on a rigorous species site matching. A key criterion when choosing appropriate tree species for agroforestry is its leafing phenology. Woody species fall into four phenological groups (Williams et al., 1997): (1) evergreen, retaining a full canopy throughout the year with continuous turnover; (2) brevi deciduous, exhibiting brief reduc tions in canopy size which never exceed 50% and do not occur every year; (3) semideciduous, showing reductions in canopy density of at least 50% every year; and (4) deciduous, which are leafless for at least 1 month every year (Eamus and Prichard, 1998). The frequency, at which trees replace their leaves, and the timing within the annual cycle when they do so, may vary depending on species and the nature and severity of internal and environmental stress factors and other stimuli. As Lott et al. (2000) pointed out, the challenge in AFSs is how to retain the positive effects of tree species while limiting the negative effects of competition with crops. Deciduous (e.g., Paulownia fortunei (Seem.) Hemsl.) and semideciduous (e.g., Alnus acuminata Kunth) trees are thought to be less competitive with crops than evergreen species (e.g., Grevillea robusta A. Cunn. Ex R. Br.) due to their divergent leafing phenology (Muthuri et al., 2005). Trees which are leafless during the active growth phase of understory crops are particularly pre ferred. For example, poplar (Populus deltoides W. Bartram ex Marshall), a fast growing deciduous tree is less competitive with wheat (Puri and Nair, 2004), as they are leafless during winter when wheat is grown. ‘‘Reverse phenology,’’ as exemplified by the African tree Faidherbia albida (Delile) A. Chev, which sheds the leaves during the rainy season and retains it during the dry months, is yet another phenomenon of relevance in this respect. Another aspect of uncertainty is in the differences in wood quality of species vis a` vis their C accumulation rates. Fast growing species may accumulate more C before they are 10 years old than slower growing species; however, the slower growing species accumulate more C in the long term (Redondo Brenes, 2007). The wood of slower growing species also possesses higher specific gravity, which further increases the CSP in the long term (Baker et al., 2004; Balvanera et al., 2005; Bunker et al., 2005; Redondo Brenes and Montagnini, 2006). The more valuable, high specific gravity wood also constitutes a longer term sink for fixed C (e.g., construc tion timber, furniture, wood crafts) than low specific gravity wood used for short lived purposes such as packaging cases and poles. Nitrogen fixing trees constitute yet another group of important tropical trees in agroforestry. Although the growth rates and CSP of N2 fixing trees are presumably not different from those of other taxa (Kumar et al., 1998a), they are highly valued in AFSs for their potential to improve soil fertility through N2 fixation and therefore promote the growth and productivity of associated species. Consistent with this, mixed plantings involving N2 fixing tropical species have been reported to produce more AGB or volume production
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compared to their monoculture stands (Bauhus et al., 2004; Forrester et al., 2006; Kumar et al., 1998b). Pure and mixed species stands that include N2 fixers appear to be an option for SCS too. For example, all comparisons of N2 fixers and non N2 fixers have found 20–100% more soil C under N2 fixers (Binkley and Sollins, 1990; Cole et al., 1995; Johnson, 1992; Kaye et al., 2000; Resh et al., 2002; Rhoades et al., 1998). Many of the studies on encroachment of woody plant species, mainly N2 fixing tree legumes, into natural grass systems also showed significant increases in SOC (Pugnaire et al., 1996; Stock et al., 1995). These increases are attributed to greater inputs of N to N limited ecosystems such that N limitation of plants and microbes is reduced leading to greater plant productivity (Wardle, 1992). Major differences in organic C inputs from tree prunings of N2 fixing trees are, however, possible. In a 19 year study, Oelbermann et al. (2006) noted profound differences in OM inputs between alley cropped Gliricidia sepium (Jacq.) Kunth ex Walp and Erythrina poeppigiana (Walp.) O. F. Cook in Costa Rica, implying the need for proper choice of N2 fixing species to augment SOC. Although the impact of N2 fixing tropical species on atmospheric con centration of GHGs other than CO2 such as nitrous oxides (N2O) is also frequently mentioned (Firestone and Davidson, 1989; Sharkey and Loreto, 1993), a solid body of research data is not yet available (Hall and Asner, 2007). The arguments presented above clearly show that the effects on vegetation and SOC accretion may be positive, negative, and neutral, and it is possible to influence biomass and SCS by selecting appropriate tree species. Many AFSs use MPT species that are fast growing, have high biomass productivity, and have N2 fixing properties to enhance soil nutri ent cycling and increase levels of SOC (Nair et al., 1999; Oelbermann et al., 2006) and as such are expected to have high CSP. The long standing debate on the pros and cons of adopting mono or polycultures when establishing forest plantations (Ball et al., 1995; FAO, 1992) is also worth mentioning here. Several benefits are attributed to a mix of species. These include more efficient resource use, site quality improve ments, reduced risk of catastrophic damage such as mechanical injury and pest outbreaks, diversified production and reduced economic risk against market failures, and higher ecological integrity (Hartley, 2002). Mixed stands also provide a better risk management strategy through compensatory biomass and nutrient production gains and offer a better basket of options for tree products (industrial timber, firewood, stakes for climbing crops, and light construction wood), reducing soil erosion on sloping land (Stanley and Montagnini, 1999), and site fertility improvement through biological N2 fixation (Montagnini et al., 2005). A recent review based on a meta analysis of more than 50 field experiments that contrasted pure stand versus mixed stand of the same tree species demonstrated a significant increase in insect pest damage in single species stands ( Jactel et al., 2005), which again makes mixtures inherently more productive than single species stands.
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5.3. Agroforestry practices and tree rotation cycles Agroforestry practices (Table 1, Fig. 1) differ considerably in their CSP depending on a number of site specific factors such as ecology, species composition, and management as indicated in Tables 3 and 5. Considerable variation exists within each practice depending on rotation lengths, cultiva tion intensity, organic versus chemical agriculture, and others (Christensen and Johnston, 1997; Lal and Kimble, 1997). As discussed later (Sec tion 5.6.1), there is a negative relationship between SOC and cultivation intensity. The general consensus is that organic agriculture can lead to higher SOM storage than conventional agriculture (L es and gaard, 1997; Stolze et al., 2000), due to the recirculation of animal manures and crop residues (Foereid and H gh Jensen, 2004). However, crop production in organic agriculture could be lower than in conventional (commercial) agriculture because of nutrient limitations (Halberg and Kristensen, 1997). Among the tropical agroforestry practices (Table 1), improved fallows (Buresh and Cooper, 1999) have been found to increase SOC levels compared to conventional cropping. In the humid lowlands of Nigeria, fallows were found to greatly increase the stability and cohesiveness of soil aggregates (Salako et al., 1999). Comparing improved fallows, traditional fallows, and continuous maize in Zimbabwe, Nyamadzawo et al. (2009) found that the improved fallows had higher levels of carbon in macroag gregates, and more microbial carbon than other treatments. Based on a simulation study, Markewitz (2006) concluded that longer tree rotations would increase the stored C stock (partly as wood in use) and would reduce C emissions from harvesting and processing operations per unit of wood harvested. Thus, the largest amount and most permanent form of C may be sequestered by increasing the rotation age of trees and/or shrubs and by manufacturing durable products from them upon harvesting. Although longer rotation lengths are generally preferred for agroforestry too, there may be conflicts between CS and other stand management objectives. In certain cases, productivity (a surrogate for CSP) also has been linked to site quality, for example higher productivity for species mixtures on nutrient poor sites (Binkley, 1992; Montagnini et al., 1995).
5.4. Silvicultural carbon emissions Fossil fuels utilized for silvicultural activities such as fertilization and site preparation, intended to increase CS, may emit CO2 and can play a signifi cant negative role in the C balance of forestry and AFSs. The impacts of burning, fertilization, and herbicide use on components of the C budget in forests have been investigated (Echeverria et al., 2004; Johnson and Curtis, 2001; Knoepp and Swank, 1997; Markewitz, 2006). Major silvicultural practices that contribute to C emissions are summarized below.
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Although addition of inorganic fertilizers may accelerate both above ground and soil CSP, fertilizer manufacture is an energy intensive process. For example, applying 100 kg ha 1 yr 1 of diammonium phosphate would produce approximately 0.009 Mg C (0.45 Mg C over 50 years) from manufacture, assuming a factor of 0.58 moles of CO2–C per mole N produced (Schlesinger, 1999). This rises to 0.022 Mg C (1.1 Mg C over 50 years) if energy for storage, transport, and application were factored into the calculation (Schlesinger, 1999). In addition, nitrogenous fertili zers may also contribute to the emissions of other GHGs such as N2O, exacerbating global warming (Prasad, 2009). Carbon emissions occur due to fossil fuel combustion in operating heavy equipment in forestry activities (Lorenz and Lal, 2010; White et al., 2005). However, as mentioned earlier, this has not been studied in an agrofor estry context, presumably because agroforestry is often practiced by the smallholders, who seldom use heavy equipment. Carbon emissions related to increased activities such as use of herbicides or energy for water pumping in irrigated systems also may counter balance any potential gains in CS (Schlesinger, 2000). Although herbicides and other agrochemicals may promote tree growth and aboveground CS especially by suppressing competitors, parasites and predators, the effects are seemingly more complex. The associated gains in aboveground CS may be offset by emissions on account of the fossil energy consumption in the manufacture and application of such chemicals. Burning (Vose and Swank, 1993) and harvesting (Harmon, 2001; Harmon et al., 2009; Morrison et al., 1994) are management practices, which cause removal of considerable woody biomass from the site and thus would probably release substantial C. Although forest burning reduces C stored in AGB in the short term, the early effects on soils are quite variable with both increase and decrease being reported (Markewitz, 2006). The issue of whether potential gains in CS by the use of inorganic fertilizers and other chemical inputs exceed the resultant C emissions is important in management decisions relating to CS process (Markewitz, 2006), and it is considered in more detail in Section 5.6.2.
5.5. Animals in agroforestry Another important issue in this context is the role of animals in AFS in the context of their GHG emission potential. The Food and Agriculture Orga nization (FAO) of the United Nations’ so called LLS (Livestock’s Long Shadow) report (FAO, 2006) states that 18% (7100 Tg CO2 equivalents per year) of anthropogenic GHGs are directly or indirectly related to the world’s livestock. [Note: CO2 equivalents (CO2 eq) represent the total impact (radiative forcing) of GHG in the atmosphere, and it is used as a
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measure to compare the climate change impact of one GHG versus another.] While this figure is not universally applicable, the fact remains that livestock production contributes substantially to global climate change, though at varying extents in different geographical regions (Pitesky et al., 2009). The authors (Pitesky et al., 2009) argue that the contribution of livestock production to a country’s overall GHG portfolio could be rela tively small in developed countries (where other sectors such as transporta tion, energy, and other industries are the leading GHG contributors), the trend could be reverse in the developing countries. The LLS report attributes almost half of the climate change impact associated with livestock to the changes in land use patterns such as conver sion of forested land to animal production. Animals constitute a major component of several AFSs. For example, silvopasture (trees in support of animal production, Table 1; Fig. 1) is the most prominent AFS in North America (Garrett, 2009), and tree fodder is the mainstay of animal feed in the tropics too (Nair, 1993). However, the impact of animal production in AFSs on global climate change has not been investigated. Indeed, if sustain able silvopastoral systems could be developed as viable alternatives to con version of forest lands to support animal production, the above stated high levels of ‘‘carbon footprint’’ of animal production in developing countries could be reduced considerably.
5.6. Soil management Management practices are one of the key factors affecting soil aggregate formation and stability. By having an impact on the mechanisms described in Section 3, management can influence aggregate formation, stability, and degradation. The three main anthropogenic factors that influence SCS are (1) disturbance of the soil, such as tilling; (2) amendments, such as fertiliza tion or irrigation; and (3) incorporation of OM (Jarecki and Lal, 2003). These are discussed in some detail below. Although most of the studies reported here are for agricultural systems, the information is relevant to the discussion, given that agroforestry is considered as one of the management alternatives in the context of conversion of degraded lands for cultivation of biofuel crops (Nair et al., 2010) as well as the recent REDD (Reduced Emission from Deforestation and Forest Degradation) initiative (http:// unfccc.int/methods science/redd/items/4531.php; Section 5.6). 5.6.1. Soil tillage A number of studies have shown that conventional tillage practices decrease CS in agricultural soils (Alvaro Fuentes et al., 2009; Cambardella and Elliott, 1993b; Elliott, 1986; Madari et al., 2005; Six et al., 2000, 2002). This decrease is related to the rate of microaggregate production in till versus no till systems. Although both systems may have similar rates of
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macroaggregate formation, the level of microaggregates within macroag gregates of no till systems was found to be higher. The authors attributed it to tillage that caused breakup of up soil aggregates, exposing iPOM in macroaggregates and hastening their break down (Six et al., 2000). No till, on the other hand, allowed macroaggregates to persist for longer allowing iPOM to break down slowly into more recalcitrant microaggre gates. Thus, although levels of light fraction OM are no different between tillage and no tillage and coarse iPOM only differs slightly, the incorpora tion of these materials into fine iPOM and microaggregates is greatly affected by break up of macroaggregates by conventional tillage (Six et al., 1998). No till practices are reported to have a positive effect on SOC concentrations of Oxisols too (Filho et al., 2002; Madari et al., 2005). Most, if not all, of such studies on the effect of tillage on soil are in agricultural systems and are confined to surface soils. Alvaro Fuentes et al. (2009) found that no till increased the number of macro and microaggre gates in the top 5 cm of soil in the Mediterranean. They found, however, that levels of C in the aggregates only sometimes increased in the no till system and that the type of C rather than the quantity may be more important to aggregate formation. Other field studies on the impact of tillage on C storage have yielded contrasting results in various parts of the world. A recent study (Poirier et al., 2009) showed that while no till practices enhanced the SOC content in the soil surface layer, moldboard plowing resulted in greater SOC content near the bottom of the plow layer in a clayey loam soil. Hence, when the entire soil profile (0–60 cm) was considered, both effects compensated each other, resulting in statistically equivalent SOC stocks for both tillage practices. An explanation of the high intersite variability of the influence of no till on soil C storage will require that we understand the impacts of no till on SOC sequestration for various soil and climatic conditions. In any case, the extent of tillage operations in AFSs is considerably less than in conventional agricultural systems. 5.6.2. Use of fertilizers and other agrochemicals Although fertilization of agricultural crops and forest stands is a well established management practice and it generally increases C storage in the short term (Markewitz, 2006), fertilization experiments on most tropical trees are scarce. Furthermore, published reports involving continuous or repeated application of inorganic nutrients, especially N, to forest stands have given mixed results. While many workers have proposed a positive effect of N fertilization on many temperate trees (Allen et al., 2001; Prescott et al., 1995a,b; Weetman et al., 1995), others have advocated that balanced nutrient application including other nutrient elements is central to the sustainability of plantations (Clarholm and Rosengren Brinck, 1995; Kumar, 2005; Tiedemann et al., 1998). Some reports indicate negative effects of N addition (Becker et al., 1992; Jobidon, 1993; Luxmoore et al.,
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2008; Stanturf and Stone, 1994; Woods et al., 1992) and yet others report neutral effects (Kim, 2008; Shujauddin and Kumar, 2003). Fertilizer addi tions to pine plantations in the Georgia piedmont, USA, did not signifi cantly increase soil carbon (Sartori et al., 2007). On the whole, effects of inorganic fertilization on tree plantations may be positive, negative, or neutral depending on a number of local factors (site fertility, species, fertilizer dose, stage of stand development, etc.). This calls for long term studies and analyses to ascertain whether fertilization can induce a change in C dynamics and to better understand the processes involved. Evaluating the effects of long term organic manure addition in the Indian Himalayas, Kundu et al. (2007) reported that SOC concentration increased 40% and 70% in the NPK þ FYM treated plots (10 Mg ha 1 FYM; 0–45 cm soil depth) as compared to NPK (43.1 Mg C ha 1) and unfertilized control plots (35.5 Mg C ha 1), respectively. By extension, use of organic manures in agroforestry for tree and herbaceous crop manage ment, besides incorporation of crop residues and pruned materials and detritus from the trees, may promote SOC sequestration. Consistent with this, Farage et al. (2007) showed the negative effects of inorganic fertilizer on soil C when organic additions were completely substituted by chemical fertilizers. Fertilization can also influence the formation and stability of soil aggre gates. The effect of fertilization practices on SOC can be dependent on the nature of the fertilizer as well as the climate and other site specific factors. Tripathi et al. (2008) found that nitrogen fertilizer inputs increased the formation of macroaggregates and associated microbial biomass nitrogen in dry tropical forests in India, but caused a decrease in savanna. Nitrogen in the form of inorganic fertilizer on maize (Z. mays) fields in Ghana also lead to a decrease in soil aggregation (Fonte et al., 2009). Amendments with high C/N ratios compared to low C/N ratios were found to lead to higher levels of SOC and greater aggregate stability in a dryland ecosystem in India (Singh et al., 2009). Similarly, when inorganic fertilizers are used in combi nation with carbon additions, there is an increase in SOC and aggregate stability as well as nutrient levels in the soil. Inorganic fertilizers by them selves did not have this effect (Xiang et al., 2009). In an experiment comparing an organic farm and conventional farm in England, the main factor effecting aggregate stability was SOM input. Organic versus inorganic fertilizers were not significantly different but there was a trend toward less stable aggregates when using the inorganic fertilizers (Williams and Petticrew, 2009). It is also important to keep in mind the cost of manufacturing inorganic fertilizer when weighing its impact as a CS tool. It is costly in fossil fuels to produce and these costs can counteract the positive impacts it may have on CS (Markewitz, 2006). The differences found in aggregate formation with inorganic fertilizer use compared to nutrient additions from OM
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amendments support agroforestry having a positive impact on aggregate formation. Agroforestry practices often involve using nitrogen fixing trees and high OM inputs. The OM input in conjunction with the increase in nitrogen in the soil instead of inorganic fertilizer could improve aggregate formation. If harvested wood is utilized for structural wood products (i.e., lumber, oriented strand board, etc.) and/or meeting the energy require ments, it would probably result in a positive C balance (Hiroshima, 2004). Overall, it seems that abandonment of environmentally sustainable land management practices and replacement by actions such as heavy tillage, tree felling, or switching from manures to inorganic fertilizers would favor net C loss from the soil (Farage et al., 2007). Herbicides can affect the formation of soil aggregates by having a direct impact on the amount of OM introduced to the soil, or by effecting microbial populations. Roberson et al. (1991) found that orchards with a ground cover crop had better macroaggregation compared to herbicided areas. Heavy fraction carbonates were correlated with aggregate stability, though total C levels were not. A pine plantation on a Florida Spodosol that was intensely managed with herbicide also had lower levels of OM in macroaggregates (Sarkhot et al., 2007). Another study examining the use of herbicides in the Georgia piedmont found that there was a decrease in soil C with herbicide application depleting levels by 5 Mg C ha 1 (Sartori et al., 2007); soil aggregates, however, were not measured in that study. On the other hand, a study in California found that herbicide had no effect on soil C pools on most sites but that sites where there was strong understory compe tition, herbicide increased soil C pools. This was due to an increase in litter production by trees that compensated the reduction in understory litter production (McFarlane et al., 2009). However, again, only total C pools were studied, not soil aggregates. These studies suggest that herbicides can affect, either positively or negatively, the amount of litter input to the soil, changing carbon inputs and aggregate formation. It is also possible that herbicides and pesticides can affect soil ecology, disrupting the processes that lead to the formation of soil macroaggregates. Soil flora and fauna are key to the formation of soil aggregates and pesticides and herbicides can have an impact on these communities, shifting their composition (Sylvia et al., 2005). In addition, the roots of understory plants can play an important role in aggregate formation, especially in sandy soils such as Spodosols where physical protection is the main driver of aggregate formation. Herbicides not only limit plant residue inputs from the surface, but root inputs as well (Sarkhot et al., 2007). As a result, SOM is not physically protected and it breaks down more quickly. There is little information about possible effects of pesticides on soil aggregation or CS.
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5.6.3. Management improvements: possibilities and limitations Overall, the type of land use is an important factor controlling OM storage in soils since it affects the amount and quality of litter input, the litter decomposition rates, and the processes of OM stabilization in soils ( John et al., 2005; Shepherd et al., 2001; Six et al., 1999, 2002). Land use and soil cultivation can change the total amount of SOM stabilized but they may also change the relative importance of the SOM protecting processes (Martens et al., 2003). As described in Section 4.3.2, Saha et al. (2009) reported that the soil C stock was directly related to plant diversity: in homegardens of Kerala, India, smaller sized gardens that had higher tree density and plant species density had more soil C to 1 m depth (119.3 Mg ha 1) than larger sized ones (108.2 Mg ha 1). The above review points out the possibilities for improvement of management practices to optimize CS. Comparative studies of managed areas and adjacent natural ecosystems have shown large differences in the amounts of SOC in the two systems (Cambardella and Elliott, 1993b; Madari et al., 2005; Tapia Coral et al., 2005). Even when best management practices (BMPs) are being implemented, native systems often have higher total carbon levels and rates of sequestration. In Minas Gerais, Brazil, Tapia Coral et al. (2005) found that degraded lands that are regenerating naturally into secondary forest had higher levels of CS than the adjacent agroforestry plots. However, C:N ratios were much lower in the agroforestry plots, indicating higher levels of nutrient cycling. In the long term, this may lead to improved growth and aggregate formation leading to higher CS over time compared to the natural regeneration. Madari et al. (2005) found SOC concentrations of 25 g kg 1 on no till plots compared to 443 g kg 1 in adjacent forest soil on an Oxisol in southern Brazil. This observation on lower soil C levels in managed systems compared to natural systems, however, is not universally valid; the magnitude of difference will depend on the type of systems being compared. For example, Gama Rodrigues et al. (2010) found in an Oxisol of Bahia, Brazil, that 30 year old shaded cacao (Theobroma cacao L.) systems under natural shade (cabruca system) or planted shade trees had similar or more SOC up to 1 m soil depth compared to adjacent natural forest. The high amount of litter fall (10 Mg ha 1 yr 1) from cacao and little or no soil tillage under cacao stands were stated as the likely factors promoting this situation. Overall, however, soil C levels are lower even in areas implementing BMPs compared to natural ecosystems, and this indicates scope for better manipulation management practices enhanc ing CS levels in managed systems comparable to those of natural systems. Although management practices can influence the formation and stabil ity of soil aggregates, and thus the amount of CS, anthropogenic impacts can only go so far. There is a limit of C that can enter the soil, and a certain point that C additions to the soil will not be incorporated into microaggregates,
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but only into more labile macroaggregates that will be decomposed. This results in C being lost as quickly as it is added (Gulde et al., 2008). The authors found that SCS did not increase when manure applications were increased from 120 to 180 Mg ha 1 yr 1. They also found that macroaggregates were the only aggregate size class that increased in C across all manure application levels and that this was due to an increase in iPOM concentration. This suggests that rates of manure application cannot speed up the rate of CS. However, as discussed in Section 4, such results are site specific. Adoption of recommended management practices (RMPs) may allow steady incorporation of SOC for long periods of time before reaching equilibrium. Rates of CS in a prairie soil would reach a predicted equilib rium only after 384 years while macroaggregates were much faster to reach equilibrium in a predicted 10.5 years ( Jastrow, 1996). In addition, the impact of management practices on other carbon pools should be taken into con sideration. Management practices can also produce differing amounts of AGB and alternate energy sources and materials. All of these factors should be viewed in conjunction with the amount of belowground carbon being sequestered to gain a better perspective of anthropogenic impacts.
5.7. Carbon sequestration programs and rural livelihood security The CDM under Article 12 of the Kyoto Protocol offers an economic opportunity for subsistence farmers in developing countries for selling the C sequestered through agroforestry activities (Rosa et al., 2003; UNEP, 2004). It is now widely recognized that sink related CDM projects can promote sustainable development and resilience of the smallholder production sys tems (UNFCCC, 2004). In Mexico, for instance, a CDM project assisted farmers to switch from swidden agriculture to agroforestry, either by com bining crops and timber trees or by enriching fallow lands (Nelson and de Jong, 2003). Using a simulation model designed to assess the value of terrace and agroforestry investments, Antle et al. (2007) showed that participation in C contracts could increase adoption of terraces and agroforestry practices. According to these authors, there are two potential benefits for the farmers to enter into contracts to sequester C. First, they could sell the C seques tered in agroforestry (and other) systems in C credit markets, and thus would be compensated for the C they sequester, based on the quantity of C sequestered and the market price of C. Second, farmers would benefit from any gains in productivity associated with the adoption of C sequester ing practices. Consistent with this, Verchot et al. (2007) argued that the tree component in mixed species systems may buffer against income risks asso ciated with climatic variability, especially during ‘‘stress’’ years, and thus agroforestry options may provide a means for increasing the ‘‘sustainability’’
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(reduced vulnerability of the agricultural sector to climate change) of smallholder farming systems. Sink related CDM projects could also represent financial inflows espe cially for developing countries (Nair et al., 2009a). In particular, it augments the credit facilities to smallholders. Takimoto et al. (2008b), based on a cost benefit analysis of CS in two improved AFSs (live fence and fodder bank) and the traditional parkland AFSs in semiarid Mali in the West African Sahel region, suggested that C credit sale was likely to contribute to economic development of the subsistence farmers in the region. This ‘‘carbon money’’ may help such farmers start up new enterprises such as bee keeping, goat rearing, and poultry farming. In spite of all the perceived merits of agroforestry projects (income genera tion, poverty reduction, and environmental preservation, sustainability, etc.), the profitability of land use related CDM projects will largely depend on the price of C in the international market, additional income from the project like the sale of timber, and the cost related to C monitoring (Nair et al., 2009a). Estimates of future C prices, however, are highly uncertain. High transaction costs constitute yet another crucial problem in smallholder CS projects (Lipper and Cavatassi, 2004). At the international level, efforts to reduce transaction costs include developing simplified methods for small scale CS projects to come under the CDM (Pfaff et al., 2007). Building institutional capacity to facilitate successful implementation of CS projects is another hitch (Jindal et al., 2008). To further illustrate this, the Kyoto Protocol requires each developing country to establish a Designated National Authority (DNA) that serves as the point of contact between international investors and local service providers. A mecha nism for coherent, justifiable, and transparent assessment of carbon projects and to generate enough revenue through these assessments to finance itself, how ever, is nonexistent in many developing countries, especially in Africa (Jindal et al., 2008). Protocols and methods for developing and implementing new interventions such as REDD are also seemingly very complex (IPCC, 2007; Kanninen et al., 2007). Though REDD has been described as a potential poverty alleviation tool, whether and how REDD benefits are to reach forest dependent communities is still unknown ( Jindal et al., 2008). In most Asia Pacific countries, it is very unclear what REDD benefits will be and to whom they will flow (www.redd net.org; accessed 16 February 2010). Lower levels of demand, higher levels of supply, or significant price reductions for nonperma nence may further exacerbate the problem and depress the opportunities for suppliers of CS through land use change (Lipper and Cavatassi, 2004). In spite of the uncertainties surrounding carbon offsets, many carbon offset projects have been developed ( Jindal et al., 2008). Globally, CS projects are now worth millions of dollars (www.ecosystemmarketplace. com; accessed June 2010). The Ecosystem Marketplace estimates that over the last decade, more than 880,000 ha of forest and agricultural lands have been brought under CS, yielding carbon offsets or credits worth US$ 92
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million ( Jindal et al., 2008). The Biocarbon Fund (www.biocarbonfund. org; accessed 15 February 2010) established by the World Bank, is a prominent source of funds for such projects. Thus, agroforestry based CDM projects have the potential not only to sequester significant amounts of C but also improve rural livelihoods by turning unproductive land into productive land that can generate income. The extent of this potential has not been rigorously assessed. Simple estimations obtained by multiplying the estimates of area under AFSs (current and potential) with an average CSP value (Mg ha 1 yr 1) lack credibility. Payments for CS appear attractive for local incomes and for ecosystem services. Carbon trading is also rapidly expanding, now that the World Bank and other multilateral institutions have established funds to facilitate the establishment of CDM projects. Although there are tradeoffs between C stored and profit, and ‘‘there are no win–win (high C and high profit) land uses, there are certainly some ‘no regrets options’ with medium to high profit and medium C stocks’’ (Verchot et al., 2007), of which agroforestry practices are prominent.
6. Concluding Remarks The multitude of AFSs, be they practiced in the tropics or temperate regions, are firmly grounded on strong ecological principles. Through provision of many basic needs and ecosystem services, they contribute to attainment of many regional developmental goals. Although ignored or bypassed in the research and development paradigms of the Green Revolu tion era, the potential of AFSs to develop into a set of major land use options is now gradually being recognized, thanks to three decades of modest research efforts. One of the underexploited attributes of AFSs is their CSP. The under lying premise is that tree incorporation in croplands and pastures would result in greater net aboveground as well as belowground CS. Although some estimates of CSP of AFSs are available, these are mostly estimates of C stocks and, overall, the data are not rigorous. Methodological difficulties in estimating C stock of biomass especially belowground and the extent of soil C storage under varying conditions are serious limitations in exploiting this low cost environmental benefit of agroforestry. However, the limited research results that are available on the increase in C storage under AFSs compared with non AFSs under similar ecological conditions show the extent of this potential, especially in soils, and the importance of the nature and properties of soils in the magnitude of their CSP. Overall, these results provide clear indications of the role of AFSs in climate change mitigation. Agroforestry is estimated to be practiced on 1 billion hectares of agricultural lands worldwide, servicing about 1.5 billion farmers, primarily smallholders, in
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developing countries; it is also a potentially important land use activity in the industrialized nations. Since subsistence farmers in developing countries are the major practitioners of AF, there is an added and attractive opportunity for them to benefit economically from agroforestry when the C sequestered through AF is sold to developed countries according to CDM stipulations. Admittedly, there could be ideological arguments against encouraging devel oping countries to adopt land use practices with the objective of ‘‘benefitting’’ the industrialized countries. That is not the case here. AFSs have been practiced in the developing countries since time immemorial, and they are a part of the culture and livelihood of the people in many societies. It is a question of recognizing the hitherto underexploited potential of these time tested prac tices. Furthermore, traditional AFSs with diverse and structurally complex shade canopies are among the agricultural land uses that are most likely to conserve a significant portion of the original forest biodiversity, an issue that though very important has not been discussed in this chapter. The current debate on land use and carbon mitigation is focused more on economics and accounting, and not enough on science. Clearly, it is time that in the poverty alleviation–conservation–environmental protection paradigms, we pay more attention to these ignored or bypassed integrated land use systems that are practiced on small farms by millions of farmers around the world, and the underlying science of the practice.
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Index
A a Amylase, 97 Aboveground carbon sequestration, 249 coconut biomass, 260, 262 tree management variations, 262 whole-tree biomass, 262 Abscisic acid (ABA), 98 Acetylene inhibition technique, 27 Additive hypothesis, 119 120, 121 Agricultural production systems simulator (APSIM) model, 268 Agroforestry. See also Carbon sequestration, agroforestry aboveground carbon sequestration, 249 coconut biomass, 260, 262 tree management variations, 262 whole-tree biomass, 262 area under agroforestry, 245 246 belowground carbon sequestration agricultural production systems simulator model, 268 belowground living biomass, 265 266 carbon dating, 266 267 ecosystem-level model, 268 G’DAY model, 268 isotope measurements, 266 267 methodological difficulties, 268 270 Rothamsted model (RothC model), 267 soil aggregates, 263 265 yield-SAFE model, 268 definition, 240 ecological sustainability, 242, 244 245 historical development, 241 242 North America, 244 silvicultural practices carbon emissions, 283 284 pruning, 279 280 stand-density management, 276 279 soil carbon vs. land-use systems research locations, University of Florida, 270 275 study locations and procedures, 270 soil management best management practices (BMPs), 289 fertilizers, 286 287 herbicides, 288 managed areas vs. adjacent natural ecosystems, 289
pesticides, 288 recommended management practices, 290 soil aggregates, 289 290 soil tillage, 285 286 system diversity, 242, 243 Agronomic practices, Sub-Sahara Africa conservation agriculture, 218 219 fertilizer microdosing, 215 216 pigeon pea intercropping, 217 soybean rotation, 214 215 staggered intercropping, 216 striga management, 217 218 Aluminum nanoparticle, 142 1-Aminocyclopropane-1-carboxylic acid (ACC)-deaminase structural (acdS) gene, 100 Anthropogenic nanoparticle (ANPs), 140, 141, 148. See also Manufactured nanoparticles (MNPs) Association for Temperate Agroforestry (AFTA), 240, 242 Azospirillum, plant growth additive hypothesis, 119 120 biological control competition, 113 114 healthier plant production, 114 116 toxic substances, 113 laboratory model, 79 mechanisms, 93 minerals and water uptake foliage parameters, 106 proton efflux activity, 106 107 reproductive period, 106 sorghum plants, 107 mode of action, 81 92 nitrate reductase, 119 nitric oxide (NO), 116 117 nitrite, 117 nitrogen fixation 15 N isotope dilution technique, 102 ammonia-excreting strain, 102 103 denitrification, 104 105 gene sequence, 104 nitrogenase activity, 101 102 oxygen, nitrate, and molybdenum, 105 para-nodule system, 103 104 phosphate solubilization and mobilization, 107 108 phytohormones
309
310
Index
Azospirillum, plant growth (cont.) cytokinins, 99 100 ethylene, 100 101 IAA, 80, 93 96 polyamines, 99 root growth, 106 107 root morphology, 79 signal molecules and proton extrusion, 117 118 stress compost and humic substances, 111 herbicides, 110 111 pH and toxic substances, 112 plant protection, high light intensity, 112 salinity, 109 110 toxic metals, 111 water, 110 B Belowground carbon sequestration, 249 agricultural production systems simulator model, 268 belowground living biomass, 265 266 carbon dating, 266 267 ecosystem-level model, 268 G’DAY model, 268 isotope measurements, 266 267 methodological difficulties, 268 270 Rothamsted model (RothC model), 267 soil aggregates, 263 265 yield-SAFE model, 268 Biochemical recalcitrance, 253 Biological nitrogen fixation. See Nitrogen Biological oxygen demand (BOD), 52 Biomass transfer, 194 Black carbon, 141 C Carbon-based nanotubes (CNTs), 153 154 adsorption mechanisms different pH range, 157 158 functional groups, 159 hydrophobic interaction, 156 157 molecular dynamic simulations, 159 organic solvents, 158 desorption hysteresis, 154 dispersion and adsorption capacity, 153 154 synthesis arc-discharge, 141 142 chemical vapor deposition, 142 laser ablation, 142 unit surface area (QSSA), 153 Carbon sequestration, agroforestry. See also Agroforestry; Soil carbon sequestration (SCS) aboveground (vegetation), 248 250 coconut biomass, 260, 262
tree management variations, 262 whole-tree biomass, 262 agroforestry practices, 283 animals, 284 285 belowground (soil), 250 253 agricultural production systems simulator model, 268 belowground living biomass, 265 266 carbon dating, 266 267 ecosystem-level model, 268 G’DAY model, 268 isotope measurements, 266 267 methodological difficulties, 268 270 Rothamsted model (RothC model), 267 soil aggregates, 263 265 yield-SAFE model, 268 direct and indirect, 247 silvicultural practices carbon emissions, 283 284 pruning, 279 280 stand-density management, 276 279 soil management best management practices (BMPs), 289 fertilizers, 286 287 herbicides, 288 pesticides, 288 recommended management practices, 290 soil aggregates, 289 290 soil tillage, 285 286 species and species admixture above and belowground CSP, variability, 280 benefits, 282 C accumulation rates, 281 nitrogen-fixing trees, 281 282 nitrous oxides (N2O), 282 woody species, 281 tree rotation cycles, 283 Clean development mechanism (CDM), 240 Compost, 206, 209 chemical characteristics, 213 control, 213 epigeic earthworms, 214 physical properties, 213 vermicompost, 214 Comprehensive Africa Agriculture Development Programme (CAADP), 185 Conference of the Parties (COP), 239 Conservation agriculture, 218 219 Constructed wetlands climate, 6 contaminant removal process photochemical process, 9 redox status, 8 sedimentation, 8 9 sorption, 9 design and management cost, 58
311
Index
hydraulic efficiency, 56 hydrology, 52 55 mosquito control, 59 sediment traps, 56 57 sociopolitical considerations, 58 vegetation, 58 59 watersheds, 57 dissolved organic matter (DOM) input output studies, 41 43 sources, 39 40 inflow, 6 7 municipal waste water, 5 6 nitrogen cycling, 25 28 environmental impacts, 24 25 removal effciency, 28 32 pathogens biological elimination, 49 chemical removal, 49 E. coli reduction, 50 microbial pathogen retention reduction, 49 50 negative collateral effect, 50 physical removal, 49 retentions, 48 49 pesticides herbicides, 12, 15 organophosphate insecticides, 15 16 pyrethroid insecticides, 16 19 removal, 20 24 phosphorus accumulated sediment removal, 38 chemical immobilization, 38 environmental impacts, 32 33 organic and inorganic forms, 33 P transformations, 34 37 routine vegetation harvesting, 38 wetland design features, 38 subsurface flow, 5 surface flow, 5 suspended sediment, 10 11 tailwater treatment, 50 51 trace metals fate and transport, 45 saturated soils and wetlands, 45 48 sources, 44 45 vegetation, 9 10 water-quality parameter biological oxygen demand (BOD), 52 salinity, 51 52 Cytokinins, 99 100 D Denitrification potential (DNP), 27 Designated National Authority (DNA), 291 Dissolved organic matter (DOM) agricultural runoff, 39 40 input output studies
California, 41 42 HRT and vegetation density, 42 Illinois wetlands, 41 input and output waters, 42 microcosm studies, 42 43 pothole wetlands, 41 leaching, 40 microbial degradation, 40 photochemical degradation, 41 solubility, 40 sorption, 41 sources, 39 40 E Ecosystem-level model, 268 Energy dispersive X-ray (EDX), 147 Ethylene, 100 101 F Fertilizer microdosing, 215 216 Field-flow fractionation (FFF), 146 Food security crop productivity, 185 nutrient balance, 228 smallholder farming, 188 soil fertility management, 220 restorative technologies, 193 status diagnosis, 192 Fullerene, 143 desorption resistance, 154 dispersion, 152 PCB mobility, 165 pentachlorophenol toxicity, 168 quantification, 147 G G’DAY model, 268 Gibberellins (GA), 97 98 Gold nanoparticle, 142 Greenhouse gases (GHGs) atmospheric CO2, 239 Kyoto protocol, 239 240 Livestock’s Long Shadow (LLS), 284 285 N2-fixing tropical species, 282 nitrogenous fertilizers, 284 H Herbicides, 12, 15 Azospirillum, plant growth, 110 111 carbon sequestration, agroforestry, 288 Hydrology hydraulic residence time (HRT), 54 55 hydroperiods, 53 54 loading rate, 55
312
Index I
Indole-3-acetic acid (IAA) bacterium cell, 95 biosynthesis, 80, 93 functions, 80 mutants, A. brasilense, 94 95 phytohormonal shock, 96 roots, morphological changes, 95 96 tryptophan, 94 Indole pyruvate decarboxylase (ipd) gene, 94 Inorganic manufactured nanoparticles enzymes and proteins, 155 156 nano-sized silver particles, 142 polar/amphiphilic molecules, 155 pyrene adsorption, 154 155 Integrated nutrient resources maize grain yield, 210 211 organic resources, 209 210 synthetic fertilizer, 210 Integrated soil fertility management (ISFM), 194 195, 210 Intercropping pigeon pea, 217 relay, 194, 213 (see also Legumes) staggered, 216 system, 194 Intergovernmental Panel on Climate Change (IPCC), 238 239 International Council-Research in Agroforestry (ICRAF), 241 Intra-aggregate particulate organic matter (iPOM), 255 257 L Land Use, Land Use Change and Forestry (LULUCF), 239 240 Legumes beneficial effects, 195 197 dual purpose, 194 erosion control, 219 increased nitrogen input, 201 maize legume intercropping, 216 nitrogen fixation, 195, 198 quality organic inputs, 209 relay intercrop, 212 213 rhizobia infection, 199 nodulation, 195 population sizes, 199 200 vs. inoculation response, 198 199 striga management, 217 symbioses, 201 M Manufactured nanoparticles (MNPs) carbon-based nanoparticles (see Carbon-based nanotubes (CNTs))
characterization energy dispersive X-ray (EDX), 147 field-flow fractionation (FFF), 146 size-exclusion chromatography (SEC), 146 colloidal behavior, 169 170 adsorption, 169 170 aggregation, 169 ionic strength and pH, 151 mobility, 150 surface functional groups, 151 152 environment fate, 147 149 environmental exposure and risk assessment, 170 fullerene, 143 desorption resistance, 154 dispersion, 152 PCB mobility, 165 pentachlorophenol toxicity, 168 quantification, 147 future aspects, 170 172 inorganic manufactured nanoparticles enzymes and proteins, 155 156 nano-sized silver particles, 142 polar/amphiphilic molecules, 155 pyrene adsorption, 154 155 natural organic matter (see also Natural organic matter (NOM)) coating, 159 161 MNP dispersion, 162 164 three-phase system, 161 162 occurrence, 145 146 organic chemicals carbon-based nanoparticles, 153 154 inorganic manufactured nanoparticles, 154 156 natural nanoparticles, 156 oxide-based NPs (see Oxide-based nanoparticle) polymer-based NPs, 141 quantification methods, 147 toxic effect controversial results, 143 144 mechanisms, 143 Metal-based nanoparticles nanogold, 141, 142 zero-valent iron (ZVI), NPs environmental remediation, 142 143 groundwater remediation, 165 MNP, organic chemicals, 172 phenanthrene adsorption, 155 Minjingu rock P (MRP), 203 MNP. See Manufactured nanoparticles (MNPs) Mosquito control, 59 Multiple mechanisms theory, 121 N Nanoparticles (NPs) classification, 140 141
313
Index manufactured, 141 143 (see also Manufactured nanoparticles (MNPs)) natural nanoparticles (NNPs), 140 141 organic chemicals, regulation, 144 sources, 140 141 surface atom, 138 139 toxicity, 143 144 Nanotechnology, 139 Natural nanoparticles (NNPs), 140 141 Natural organic matter (NOM) coating, 159 161 MNP colloidal behaviors, 172 MNP dispersion, 151 adsorption sites, 164 aggregation, 163 164 C60 dispersion, 163 ionic strength, 162 mechanism, 162 163 suspension performance, 163 three-phase system, 161 162 NOM concentration, 161 162 nonideal interactions, 162 Net primary productivity (NPP), 245 Neutral ammonium citrate (NAC), 201 New Partnership for Africa’s Development (NEPAD), 185 Nitric oxide (NO), 116 117 Nitrite, 117 Nitrogen cycling, denitrification acetylene inhibition technique, 27 controlling variables, 25, 27 mechanism, 25 N2O production, 28 15 N tracer methods, 27 organic carbon, 27 28 organic N and NH4, 28 schematics, 26 surface flow wetlands, 27 environmental impacts, 24 25 fixation, 194 ammonia-excreting strain, 102 103 denitrification, 104 105 gene sequence, 104 ISFM, 194 195 legumes (see Legumes) 15 N isotope dilution technique, 102 nitrogenase activity, 101 102 oxygen, nitrate, and molybdenum, 105 para-nodule system, 103 104 removal efficiency N loading, 29 nitrate removal efficiency, 30 31 storm runoff, 32 total nitrogen loads, 29 NOM. See Natural organic matter (NOM) Nonpoint source pollution (NPS)
constructed wetlands climate, 6 contaminant removal process, 7 9 inflow, 6 7 municipal waste water, 5 6 subsurface flow, 5 surface flow, 5 vegetation, 9 10 pollutants, 3 Wetlands Reserve Program (WRP), 4 15 N tracer methods, 27 Nutrients mineral fertilizers, 206 organic resources availability, 209 composting, 213 214 contents and chemical characteristics, 206 207 decision tool, 206 208 forms, 206 green manure, 212 livestock manure, 209 surface mulching, 212 213 recommended fertilizer, 204 206 synthetic fertilizer, 203 205 O Organic chemicals, adsorption. See also Natural organic matter (NOM) bioavailability, 168 environmental exposure and risk, 166 169 MNP leaching dispersion/aggregation, 164 165 nano-ZVI particles, 165 retained MNPs, 165 toxicity, 168 169 transport desorption rate, 165 166 natural colloids, 165 uptake and toxicity, MNP bacterial activity, 167 168 biological process, 167 natural organic coatings, 168 surface properties, 166 SWCNTs, 166 167 Organic farming, 206 209 Organomineral stabilization, 254 Organophosphate insecticides, 15 16 Oxide-based nanoparticle silver, 142, 149 SiO2, 145, 155 titanium dioxide, 146, 155 applications, 142 colloidal behavior, 151 in environment, 145 146 leaching, 165
314
Index
Oxide-based nanoparticle (cont.) pyrene adsorption, 154 toxic effects, 143 ZnO, 145, 154 P Para-nodule system, 103 104 Pathogens biological elimination, 49 chemical removal, 49 E. coli reduction, 50 microbial pathogen retention reduction, 49 50 negative collateral effect, 50 physical removal, 49 retentions, 48 49 Pesticides carbon sequestration, agroforestry, 288 herbicides, 12, 15 organophosphate insecticides, 15 16 pyrethroid insecticides, 16 19 removal hydrologic and hydraulic properties, 22 23 octanol water partition coefficients (Kow), 20 21 %R values, 21 retention time, 21 sorption and degradation, 23 24 vegetation effect, 21 22 Phosphate rocks (PR) deposits, 201, 202 direct use, 202 effectiveness, 203 MRP vs. TSP, 203 NAC solubility, 201 Phosphate solubilization and mobilization, 107 108 Phosphorus accumulated sediment removal, 38 chemical immobilization, 38 environmental impacts, 32 33 organic and inorganic forms, 33 P transformations cycling, 34, 35 mineral and organic, 36 37 new mineral and organic soils, 36 37 P sorption properties, 34, 36 P storage, 34 SO4 leaching, 36 removal efficiencies, 37 routine vegetation harvesting, 38 wetland design features, 38 Phytohormone production, Azospirillum abscisic acid (ABA), 98 cytokinins, 99 100 ethylene, 100 101 gibberellins (GA), 97 98 indole-3-acetic acid (IAA) bacterium cell, 95
biosynthesis, 80, 93 functions, 80 mutants, A. brasilense, 94 95 phytohormonal shock, 96 roots, morphological changes, 95 96 tryptophan, 94 polyamines, 99 Pigeon pea intercropping, 217 Plant growth-promoting bacteria (PGPB), 78 Polyamines, 99 Polymer-based nanoparticle, 141 Pruning, 279 280 Pyrethroid insecticides, 16 19 R Recommended management practices (RMPs), 290 Rhizobium Network for East and Southern Africa (RENEASA), 199 Rothamsted model (RothC model), 267 S Salinity, 109 110 Sediment traps, 56 57 Semipermeable membrane devices (SPMD), 22 Silver nanoparticle, 142 Silvicultural practices, carbon sequestration drivers, processes, and effects, 277 pruning, 279 280 stand-density management C pools, tree size, 276 278 litter fall fluxes, 277, 279 thinning/pruning, 279 Single-walled CNTs (SWCNTs), 150 Size-exclusion chromatography (SEC), 146 Soil carbon sequestration (SCS). See also Carbon sequestration, agroforestry soil aggregates climate, 259 formation and stabilization, 255 257 macroaggregates, 254 microaggregates, 254 plant species, 259 260 reactive properties, 258 259 sizes, 254 255 soil texture, 257 258 SOM, physically protection, 254 255 soil organic matter protection biochemical recalcitrance, 253 organomineral stabilization, 254 physical protection, 253 254 Soil fertility, Sub-Sahara Africa agronomic practices conservation agriculture, 218 219 fertilizer microdosing, 215 216 pigeon pea intercropping, 217 soybean rotation, 214 215 staggered intercropping, 216
315
Index
striga management, 217 218 CAADP, 185 economic and social stability, 184 185 external controlling factors, 220 221 market, 222 225 participatory involvement, 221 222 policy interventions, 225 226 fertilizer forms and formulations, 211 212 organic resources quality, 212 214 restoration integrated resources, 209 211 nitrogen fixation, 194 201 nutrients, 203 209 phosphate rocks, 201 203 principles, 193 194 process, 185 186 smallholder farming agricultural technology, 188 nitrogen balance, 189 191 nutrient depletion, 188 190 soil and water conservation, 219 220 status field tests, 193 inherent soil quality, 186 187 laboratory method, 192 soil order, 187 188 visual symptom, 192 193 Soil organic carbon (SOC) belowground carbon sequestration agroforestry systems, 251 252 land-use systems, 250 belowground (soil) sequestration isotope measurements and carbon dating, 266, 267 measurement and estimation, 263 microaggregates, 264 vs. land-use systems, 270, 272 274 nitrogen-fixing trees, 282 soil carbon sequestration aggregate formation and stabilization, 255, 257 organomineral stabilization, 254 plant species, 259 reactive properties, 258 259 soil texture, 258 SOM protection, 253 soil management fertilization practices, 287 long-term organic manure addition, 287 managed areas vs. adjacent natural ecosystems, 289 recommended management practices, 290 soil tillage, 286 Soil organic matter (SOM) belowground carbon sequestration, 250 isotope measurements and carbon dating, 266
modeling, 267 soil aggregates, 263, 264 fertilization, 287 land-use and soil cultivation, 289 organic agriculture, 283 pesticides, 288 soil carbon sequestration biochemical recalcitrance, 253 climate, 259 formation and stabilization, 255 257 macroaggregates, 254 microaggregates, 254 organomineral stabilization, 254 physical protection, 253 254 plant species, 259 260 reactive properties, 258 259 sizes, 254 255 soil texture, 257 258 SOM, physically protection, 254 255 Soil Science Society of America (SSSA), 247 SOM. See Soil organic matter (SOM) Soybean rotation, 214 215 Staggered intercropping, 216 Striga management, 217 218 T Titanium dioxide (TiO2) nanoparticle applications, 142 colloidal behavior, 151 in environment, 145 146 leaching, 165 pyrene adsorption, 154 toxic effects, 143 Total daily maximum loads (TMDL), 52 Total nitrogen (TN) loads, 29 Triple superphosphate (TSP), 203, 211 U United Nations Framework Convention on Climate Change (UNFCCC), 239 W Water stress, 110 Y Yield-SAFE model, 268 Z Zero-valent iron (ZVI) nanoparticle environmental remediation, 142 143 groundwater remediation, 165 MNP, organic chemicals, 172 phenanthrene adsorption, 155
