Advances in Agronomy, Volume 93

Agronomy

D VA N C E S I N

VOLUME 93

Advisory Board Paul M. Bertsch University of Georgia

Ronald L. Phillips University of Minnesota

Kate M. Scow University of California, Davis

Larry P. Wilding Texas A&M University

Emeritus Advisory Board Members John S. Boyer University of Delaware

Kenneth J. Frey Iowa State University

Eugene J. Kamprath North Carolina State University

Martin Alexander 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 Kenneth A. Barbarick

Hari B. Krishnan Sally D. Logsdon Michel D. Ransom

Craig A. Roberts April L. Ulery

Agronomy D VA N C E S I N

VOLUME 93 Edited by

Donald L. Sparks Department of Plant and Soil Sciences University of Delaware Newark, Delaware

AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier

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Contents CONTRIBUTORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ix xi

AGRICULTURAL CONTRIBUTIONS OF ANTIMICROBIALS AND HORMONES ON SOIL AND WATER QUALITY Linda S. Lee, Nadia Carmosini, Stephen A. Sassman, Heather M. Dion and Maria S. Sepu´lveda I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Use and Occurrence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Antimicrobials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Hormones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Sorption by Soils and Sediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Antimicrobials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Hormones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Degradation in Soil, Manure, and Aqueous Environments . . . . . . . . A. Antimicrobial Degradation in Manure and Soil . . . . . . . . . . . . . . B. Antimicrobial Degradation in Aqueous Environments . . . . . . . . . C. Hormone Stability in Manure, Urine, and Composted Manure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Hormone Stability in Soils and Manure-Amended Soils. . . . . . . . V. Transport Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. DOM-Faciliated Transport of Antimicrobials . . . . . . . . . . . . . . . B. RunoV Versus Drainage of Antimicrobials . . . . . . . . . . . . . . . . . . C. Hormone Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Ecological and Human Health EVects . . . . . . . . . . . . . . . . . . . . . . . . A. Antimicrobial Toxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Development of Antimicrobial-Resistant Bacteria . . . . . . . . . . . . C. Hormone-Induced Endocrine Disruption . . . . . . . . . . . . . . . . . . . VII. Analytical Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Method Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Antimicrobials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Hormones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII. Summary and Future Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

v

2 5 5 7 13 13 16 19 19 20 20 21 23 23 25 26 28 28 29 31 36 36 38 46 50 53 53

vi

CONTENTS

ANTHROPOGENIC INFLUENCES ON WORLD SOILS AND IMPLICATIONS TO GLOBAL FOOD SECURITY Rattan Lal I. II. III. IV. V.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Land Area of Natural Ecosystems Converted to Agriculture. . . . . . . Consequences of Agricultural Expansion and Intensification . . . . . . . Water Consumption and Change in the Hydrologic Cycle . . . . . . . . Anthropogenic Impact on Biogeochemical Cycles of Principal Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. The Carbon Cycle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. The Nitrogen Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. The Phosphorus Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Food Demands for the World’s Growing Population . . . . . . . . . . . . VII. Stewardship of Soil and Water Resources . . . . . . . . . . . . . . . . . . . . . VIII. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

70 71 74 75 80 80 82 83 83 86 90 91

MITIGATION AND CURRENT MANAGEMENT ATTEMPTS TO LIMIT PATHOGEN SURVIVAL AND MOVEMENT WITHIN FARMED GRASSLAND David M. Oliver, A. Louise Heathwaite, Chris J. Hodgson and David R. Chadwick I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Sources of Pathogens in the Farm Environment . . . . . . . . . . . . . . . . A. Manures Spread to Land . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Grazing Animals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Manure Spreading Versus Grazing as a Source . . . . . . . . . . . . . . D. Farmyards and Animal Feeding Operations . . . . . . . . . . . . . . . . . III. Reducing Pathogen Numbers via Manure Management . . . . . . . . . . A. Solid Manures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Liquid Manures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Livestock Welfare . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Land Management Strategies to Limit Pathogen Transfer from Land to Water. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Measures to Reduce Pathogen Mobilization from Land . . . . . . . B. Measures to Reduce Pathogen Delivery to Water . . . . . . . . . . . . V. Synthesis and Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . A. Conceptualizing Microbial Mitigation . . . . . . . . . . . . . . . . . . . . .

96 97 100 102 104 106 107 107 111 120 122 123 127 138 138

CONTENTS B. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vii 139 140 140

WEED MANAGEMENT IN DIRECT-SEEDED RICE A. N. Rao, D. E. Johnson, B. Sivaprasad, J. K. Ladha and A. M. Mortimer I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Direct-Seeding of Rice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Yield Loss Due to Weeds in Direct-Seeded Rice . . . . . . . . . . . . . II. Weeds, Weed Competition, and Ecology in Direct-Seeded Rice . . . . A. Occurrence of Major Weeds in DiVerent Methods of Direct-Seeding Across the World . . . . . . . . . . . . . . . . . . . . . . . . . B. Crop–Weed Competition in Direct-Seeded Rice . . . . . . . . . . . . . . C. Weed Species Shifts and Weed Population Dynamics Due to Changes in the Methods of Rice Establishment . . . . . . . . . . . . III. Integrating Weed Management Practices in Direct-Seeded Rice . . . . A. Preventive Methods of Weed Control . . . . . . . . . . . . . . . . . . . . . . B. Intervention Methods of Weed Control . . . . . . . . . . . . . . . . . . . . C. Developing Weed Management for Direct-Seeded Rice . . . . . . . . IV. Future Research Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

154 156 160 164 164 180 182 190 192 198 211 225 228 229

ECOREGIONAL RESEARCH FOR DEVELOPMENT J. Bouma, J. J. Stoorvogel, R. Quiroz, S. Staal, M. Herrero, W. Immerzeel, R. P. Roetter, H. van den Bosch, G. Sterk, R. Rabbinge and S. Chater I. II. III. IV.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changing Concepts of Development . . . . . . . . . . . . . . . . . . . . . . . . . Research in Relation to the Policy Cycle . . . . . . . . . . . . . . . . . . . . . . Examples from the Projects of the Fund . . . . . . . . . . . . . . . . . . . . . . A. Developing the Kenyan Highlands . . . . . . . . . . . . . . . . . . . . . . . . B. Reacting to Trade Liberalization . . . . . . . . . . . . . . . . . . . . . . . . . C. Signaling Constraints in Sustainable Use of Water Resources on the Tibetan Plateau. . . . . . . . . . . . . . . . . . . . . . . . . D. Multiple Goals for Land Use in Southeast Asia . . . . . . . . . . . . . . E. From Environment to Human Health . . . . . . . . . . . . . . . . . . . . . F. Really Dealing with Soil Erosion . . . . . . . . . . . . . . . . . . . . . . . . .

258 260 262 266 266 273 283 290 295 298

viii

CONTENTS G. Reestablishing Farmers’ Credit in the Highveld

Region, South Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Where Do We Stand Now and Where to Go? . . . . . . . . . . . . . . . . . . A. Showing New Ways of Conducting Research . . . . . . . . . . . . . . . . B. Showing New Ways of Presenting Results . . . . . . . . . . . . . . . . . . C. Presenting New Messages to Policymakers and Land Users . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

301 303 303 306 307 308 308

INFLUENCE OF HIGH TEMPERATURE AND BREEDING FOR HEAT TOLERANCE IN COTTON: A REVIEW Rishi P. Singh, P. V. Vara Prasad, K. Sunita, S. N. Giri and K. Raja Reddy I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. EVects of High Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Morphological and Yield Traits . . . . . . . . . . . . . . . . . . . . . . . . . . B. Physiological and Biochemical Traits . . . . . . . . . . . . . . . . . . . . . . III. Heat Stress and Heat Tolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Definition and Levels of Heat Stress . . . . . . . . . . . . . . . . . . . . . . B. Heat Tolerance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Screening for Heat-Tolerance Traits . . . . . . . . . . . . . . . . . . . . . . . . . A. Physiological and/or Biochemical Traits . . . . . . . . . . . . . . . . . . . . B. Ecophysiological Traits. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Association Among Ecophysiological, Morphological, and Yield Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Breeding for High-Temperature Tolerance . . . . . . . . . . . . . . . . . . . . . A. Trait Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Correlated Response of Selected Trait . . . . . . . . . . . . . . . . . . . . . C. Isogenic Lines to Study Individual Trait Performance . . . . . . . . . D. Genetic Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Inheritance Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. Impact of Heat-Tolerant Genes . . . . . . . . . . . . . . . . . . . . . . . . . . G. Breeding for High-Temperature Tolerance . . . . . . . . . . . . . . . . . . H. Practical Achievements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Summary and Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

314 316 317 324 329 329 329 330 331 336

INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

387

340 344 344 347 350 352 355 357 358 364 367 369 369

Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

H. van den Bosch (257), Wageningen University and Research Centre, Wageningen, The Netherlands J. Bouma (257), Wageningen University and Research Centre, Wageningen, The Netherlands Nadia Carmosini (1), Department of Agronomy, Purdue University, West Lafayette, Indiana 47907 David R. Chadwick (95), Manures and Farm Resources Team, Institute of Grassland and Environmental Research, North Wyke Research Station, Okehampton, Devon EX20 2SB, United Kingdom S. Chater (257), Green Ink Ltd., Devon, United Kingdom Heather M. Dion (1), Nuclear Nonproliferation Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 S. N. Giri (313), Birsa Agriculture University, Hazaribagh, Jharkhand 835006, India A. Louise Heathwaite (95), Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom M. Herrero (257), International Livestock Research Institute, Nairobi, Kenya Chris J. Hodgson (95), Manures and Farm Resources Team, Institute of Grassland and Environmental Research, North Wyke Research Station, Okehampton, Devon EX20 2SB, United Kingdom W. Immerzeel (257), FutureWater, Wageningen, The Netherlands D. E. Johnson (153), International Rice Research Institute (IRRI), Crop, Soil, and Water Sciences Division, Metro Manila, Philippines J. K. Ladha (153), International Rice Research Institute (IRRI), IRRI-India OYce, National Agriculture Science Center (NASC) Complex, New Delhi 110012, India Rattan Lal (69), Carbon Management and Sequestration Center, The Ohio State University, Columbus, Ohio 43210 Linda S. Lee (1), Department of Agronomy, Purdue University, West Lafayette, Indiana 47907 A. M. Mortimer (153), Integrative Biology Research Division, School of Biological Sciences, The University of Liverpool, Liverpool L69 3BX, United Kingdom David M. Oliver (95), Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom P. V. Vara Prasad (313), Department of Agronomy, Kansas State University, Manhattan, Kansas 66506 ix

x

CONTRIBUTORS

R. Quiroz (257), International Potato Centre, Lima, Peru R. Rabbinge (257), Wageningen University and Research Centre, Wageningen, The Netherlands A. N. Rao (153), International Rice Research Institute (IRRI), IRRI-India OYce, National Agriculture Science Center (NASC) Complex, New Delhi 110012, India K. Raja Reddy (313), Department of Plant and Soil Sciences, Mississippi State University, Mississippi 39762 R. P. Roetter (257), Wageningen University and Research Centre, Wageningen, The Netherlands Stephen A. Sassman (1), Department of Agronomy, Purdue University, West Lafayette, Indiana 47907 Maria S. Sepu´lveda (1), Department of Forestry and Natural Resources and School of Civil Engineering, Purdue University,West Lafayette, Indiana 47907 Rishi P. Singh (313), Division of Genetics, Indian Agricultural Research Institute, New Delhi 110012, India B. Sivaprasad (153), International Rice Research Institute (IRRI), IRRI-India OYce, National Agriculture Science Center (NASC) Complex, New Delhi 110012, India S. Staal (257), International Livestock Research Institute, Nairobi, Kenya G. Sterk (257), Wageningen University and Research Centre, Wageningen, The Netherlands J. J. Stoorvogel (257), Wageningen University and Research Centre, Wageningen, The Netherlands K. Sunita (313), Division of Genetics, Indian Agricultural Research Institute, New Delhi 110012, India

Preface Volume 93 contains six timely and comprehensive reviews dealing with plant, soil, and environmental sciences. Chapter 1 deals with antimicrobials and hormones from agricultural sources and their impacts on soil and water qualities. A topic that is of much interest worldwide, the review covers reaction processes including sorption, degradation, and transport, ecological and human health effects, and analytical methods. Chapter 2 discusses anthropogenic influences on soils worldwide and effects on global food security. Impacts related to land development, water consumption, and biogeochemical cycles are discussed. Chapter 3 covers ways to mitigate and minimize pathogen survival and movement in agricultural settings. Sources of pathogens and effective management strategies are discussed. Chapter 4 is a comprehensive review on weed management in direct-seeded rice. Topics that are discussed include weed competition and ecology and integrated weed management practices. Chapter 5 is a thought-provoking discussion of ecoregional research for development. It blends science with policy and contains a number of case studies as well as ways to more effectively convey research results and needs to policymakers and land users. Chapter 6 reviews efforts to enhance heat tolerance in cotton. Topics that are covered include effects of high temperature, heat stress and heat tolerance, screening for heat-tolerance traits, and breeding for high-temperature tolerance. I am grateful to the authors for their first-rate contributions. DONALD L. SPARKS University of Delaware Newark, Delaware

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AGRICULTURAL CONTRIBUTIONS OF ANTIMICROBIALS AND HORMONES ON SOIL AND WATER QUALITY Linda S. Lee,1 Nadia Carmosini,1 Stephen A. Sassman,1 Heather M. Dion2 and Maria S. Sepu´lveda3 1

Department of Agronomy, Purdue University, West Lafayette, Indiana 47907 2 Nuclear Nonproliferation Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 3 Department of Forestry and Natural Resources and School of Civil Engineering, Purdue University, West Lafayette, Indiana 47907

I. Introduction II. Use and Occurrence A. Antimicrobials B. Hormones III. Sorption by Soils and Sediments A. Antimicrobials B. Hormones IV. Degradation in Soil, Manure, and Aqueous Environments A. Antimicrobial Degradation in Manure and Soil B. Antimicrobial Degradation in Aqueous Environments C. Hormone Stability in Manure, Urine, and Composted Manure D. Hormone Stability in Soils and Manure‐Amended Soils V. Transport Processes A. DOM‐Faciliated Transport of Antimicrobials B. RunoV Versus Drainage of Antimicrobials C. Hormone Transport VI. Ecological and Human Health EVects A. Antimicrobial Toxicity B. Development of Antimicrobial‐Resistant Bacteria C. Hormone‐Induced Endocrine Disruption VII. Analytical Methods A. Method Development B. Antimicrobials C. Hormones VIII. Summary and Future Needs Acknowledgments References

1 Advances in Agronomy, Volume 93 Copyright 2007, Elsevier Inc. All rights reserved. 0065-2113/07 $35.00 DOI: 10.1016/S0065-2113(06)93001-6

2

L. S. LEE ET AL. Detection of many emerging chemicals of concern, including antimicrobials and steroid hormones, in the environment has increased in the past decade with the advancement of analytical techniques. There are several potential sources of these inputs, including municipal wastewater discharge, municipal biosolids, pharmaceutical production, and agriculture‐related activities. However, the heavy use of antibiotics in the livestock industry and the dramatic shift in recent years toward more highly concentrated animal feeding operations (CAFOs), thus a concomitant increase in the volume of animal wastes per unit of land, has drawn attention to the role of animal waste‐borne antimicrobials, antibiotic‐ resistant bacteria, and steroid hormones on ecosystem and human health. Antimicrobials, although frequently detected, are typically present in water at concentrations in orders of magnitude below what would be considered inhibitory to most biota. Most antibiotics have a high aYnity for soil and sediment, thus residual soil concentrations are usually much higher than noted in water but still often below concentrations of concern. The focal point with antibiotic use in animal production is the development of antibiotic‐resistant bacteria. Although there is a growing body of evidence of the presence of numerous antibiotic‐resistant genes in animal wastes, in soils where wastes are land applied, and in water bodies receiving runoV from manure‐amended fields or discharges from aquacultures, conclusive evidence of animal‐derived antibiotic‐ resistant pathogens compromising human health is lacking. In contrast to antibiotics, hormones and related chemicals can cause significant biological responses at very low concentrations. CAFO discharges will include a variety of estrogens, natural and synthetic androgens and progesterones, and phytoestrogens associated with animal feed. Measurable concentrations of many of these hormones have been detected in soil, and ground and surface waters receiving runoV from fields fertilized with animal manure and downstream from farm animal operations. Overall, hormones appear to be moderately to highly sorbed and to dissipate quickly in an aerobic soil environment, but quantitative information on hormone persistence in manure‐applied fields and subsequent eVects of hormone loads from CAFOs to the aquatic environment is lacking. Research directed toward evaluating the facilitated transport processes with regards to antimicrobial and hormone inputs from manure‐amended fields is in its infancy. With the advances in analytical techniques and what has already been learned with regards to transport of nutrients (nitrogen, phosphorus, and carbon) and pesticides from agricultural fields, a reasonable evaluation of CAFOs and associated activities (land application of animal wastes) should be forthcoming in the next decade. Meanwhile, implementation of management practices that optimize reduction in already regulated nutrient releases from CAFOs should also help to minimize the release of antimicrobials and hormones. # 2007, Elsevier Inc.

I. INTRODUCTION The role of steroid hormones and antimicrobial agents on soil and water quality is receiving increasingly more attention as rapid advances in analytical capabilities lower the limits of detection for these compounds in

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

3

complex environmental matrices. Agriculture and other anthropogenic activities (e.g., municipal wastewater discharge, pharmaceutical production) may act as point and nonpoint sources for both steroid hormones and antimicrobials in soils, water, and sediment systems (Larsen et al., 2001; Williams, 2005). A comprehensive survey by the United State Geological Survey (USGS) in 36 states reported 22 antimicrobials in more than 50% of samples and 11 reproductive hormones in more than 40% of samples (Kolpin et al., 2002). Over the past two decades, the livestock industry has shifted toward more highly intensive and concentrated production facilities, termed concentrated animal feeding operations (CAFOs). Current EPA rulings define a CAFO as an animal‐feeding operation, which either exceeds a certain animal‐specific size threshold of the number of animals confined, exhibits certain water discharge characteristics, or is designated by a regulatory oYcial as contributing significantly to surface‐water pollution (http://cfpub.epa.gov/npdes/afo/ cafofinalrule.cfm). CAFOs generate a large volume of wastes in a relatively small area, and thus, can pose a number of potential risks to ecosystem and human health. To date, concerns have focused on nutrient, particle, and pathogen emissions as well as odor control. More recently, there has been an increasing interest in the contribution of CAFOs to antibiotic and hormone loads to the environment as well as antibiotic‐resistant bacteria. The quantity of antimicrobials used in large‐scale animal husbandry is estimated to consume roughly 80% of all antibiotics, coccidiostats, and parasiticides produced annually in the United States (Mellon et al., 2001). About 60–80% of commercial livestock are administered antimicrobials as therapeutic, prophylactic, and growth‐promoting agents during their productive life span (USEPA, 2000), and much of the ingested dose is excreted either unchanged or as active metabolites (Addison, 1984). The widespread use of antimicrobials in animal husbandry has drawn particular attention for its potential contribution in promoting the evolution of antimicrobial‐ resistant bacteria and compromising the eYcacy of important human medicines. In addition, although environmental concentrations of antimicrobials are typically below acute‐toxicity levels for routinely tested organisms, little is known about the risks associated with chronic low‐level exposure or how the eVects of a toxicant may be modulated or intensified by concurrent exposure to other anthropogenic or natural stressors (Relyea, 2003; Sandland and Carmosini, 2006). Hormones are also used for growth promotion and reproductive control, but the majority of hormones excreted are produced naturally. On the basis of approximate levels of natural hormones excreted and the volume of feces produced daily by cattle, pigs, sheep, and chickens, Lange et al. (2002) estimated that 49 t of reproductive hormones are excreted annually by farm animals in the United States with the majority being from pregnant cattle. Changes in environmental concentrations of hormones have been suspected

4

L. S. LEE ET AL.

of being responsible for the decline in certain species and change of sex in fish (Orlando et al., 2004). Common types of hormones include synthetic estrogens (e.g., used in birth control pills, steroid replacement therapy) and anabolic agents (e.g., used in animal production), as well as natural estrogens and androgens (Richardson, 2002). Estrogen, androgen, and progestin agonistic and antagonistic activities have also been associated with eZuents from animal‐feeding operations (Durhan et al., 2006; Soto et al., 2004). Approximately 130 billion pounds of manure are produced annually in the United States, most of which is land applied (USEPA, 2000). This represents a potential concentrated source of both antimicrobials and hormones, and an entryway into the terrestrial ecosystem and receiving waters. CAFOs typically store animal waste products in some type of reservoir prior to land disposal. For example, about 23% of swine sites store wastes in an outdoor lagoon with another 57% using below ground slurry storage (deep pit) while the remaining 20% use other waste storage systems that result in manure piles that are spread, hauled away, or composted (USDA, 2002b). For manure solids and slurries, application to land varies with size and region in which the site is located. For example, swine waste‐derived lagoon eZuent is used as irrigation water in nearly 80% of the larger farms (>10,000 head) in the southern regions of the United States. In the northern, west central, and east central regions of the United States, broadcast/solid spreaders, and surface application or subsurface injection of slurries are primarily used. In all cases, the majority of producers apply manure wastes to meet nutrient demands (USDA, 2002b). The potential impact of animal husbandry‐derived antimicrobials and hormones in the environment is a function of the quantity excreted, which is dependent on species, gender, reproductive stage, feed type and amendment levels, treatment of manure and manure‐laden bedding, type of land application, and amount applied. After the release of these compounds into the environment, the magnitude of their eVect is determined by a number of compound‐specific properties such as hydrophobicity, ionization potential, sorption, and degradability along with a variety of environmental factors including local hydrology, soil characteristics, light intensity, temperature, and microbial activity. Much of the current research relevant to assessing the impact of antimicrobials and hormones from animal husbandry on soil and water quality has focused on source quantification, characterization of sorption and persistence, ecotoxicological studies, analytical techniques for detecting trace levels (ppb and ppt levels) in environmental matrices, and field‐monitoring studies attempting to link land application of manure with the presence of veterinary pharmaceuticals in surface waters. Several reviews have been published in the past 5 years summarizing much of this information,

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

5

especially for veterinary pharmaceuticals. Kumar et al. (2005) wrote a comprehensive summary of the pertinent information on antibiotic use in agriculture including amounts excreted, the factors aVecting the fate of antimicrobials in the terrestrial environment, and ecotoxicological impacts. This chapter is preceded by articles from Tolls (2001) who reviewed sorption data in soils and Thiele‐Bruhn (2003) who summarized properties, analytical methods, occurrence, and fate for veterinary antibiotics. The environmental fate and potential impact of sex hormones specifically originating from diVerent livestock production systems were highlighted by Lange et al. (2002). Hanselman et al. (2003) summarized estrogen levels as a function of reproductive stage in various types of dairy, swine, and poultry wastes as well as estrogen occurrence in manure‐impacted waters. In this chapter, we provide additional information relevant to occurrence, environmental fate, and ecological impacts with a focus on the most recent findings. We also summarize the rapidly growing analytical procedures used to extract and quantify the major classes of veterinary antimicrobials and hormones from environmental matrices.

II.

USE AND OCCURRENCE A. ANTIMICROBIALS

Several estimates of total annual antimicrobial use in the United States have been published. The USEPA estimated that in 1998, 13.7 million kg of antimicrobials were used in the United States (USEPA, 2003). The Union of Concerned Scientists (UCS) reported similar values for antimicrobial use in 1998 based on the total number of animals and usage data from the various cattle, swine, and poultry industries: 1.7, 4.7, and 4.7 million kg, respectively, in addition to the 1.4 million kg that were used in human medicine (Mellon et al., 2001). A survey by the Animal Health Institute (AHI) in 1998 reported that only 8.1 million kg of antimicrobials were used in veterinary medicine with 6.7 million kg going toward the treatment and prevention of disease and only 1.4 million kg for growth promotion (Barlam, 2001). These estimates by the AHI are lower and diVer from the UCS’ conclusion that the vast majority of antimicrobials used in animal husbandry are for nontherapeutic purposes. Although the AHI survey data was obtained directly from the industry, it relied on self‐reporting by farmers with no means of verification and with 20% of the industry not included in the data collection.

6

L. S. LEE ET AL.

Regardless of the actual amounts of antimicrobials used, it is generally accepted that the primary consumers of these compounds are the swine and poultry industries (Benbrook, 2001). In swine production, the most commonly used antimicrobials are chlortetracycline, oxytetracycline, bacitracin, tylosin, sulfathiazole, sulfamethazine, penicillin, carbadox, and lincomycin (USDA, 2002a). In the poultry industry, monensin, roxarsone, bacitracin, amprolium, salinomycin, lasalocid, zoalene, and erythromycin are among the most frequently used (Mellon et al., 2001). Major antimicrobials used in cattle production include chlortetracycline, oxytetracycline, tylosin, sulfamethazine, monensin, and lasalocid. Refer to Tables III–V in Kumar et al. (2005) for animal‐specific use details. Approximately 55% of the drugs used in veterinary medicine are also used in humans, especially chlortetracycline, bacitracin, oxytetracycline, sulfathiazole, sulfamethazine, and penicillin, although alternatives exist for most of these drugs (Benbrook, 2001). Because many antimicrobials are poorly absorbed in the digestive tract of animals, these compounds are often present in livestock wastes in significant concentrations. Tetracyclines, sulfonamides, b‐lactams, macrolides, and ionophores are examples of antimicrobial classes that are frequently detected in manure wastes (Kumar et al., 2005; Meyer et al., 1999). In a study of a number of poultry and swine production facilities, antimicrobials were found in all swine storage lagoon samples (Campagnolo et al., 2002). Total antimicrobial residues in a given sample approached 1 mg liter
1, with the tetracyclines present in the highest concentration followed by sulfonamides and lincomycin. Antimicrobials were also found in 31% of surface and groundwater samples collected proximal to the swine farms and in 67% of surface and groundwater samples proximal to poultry farms (Campagnolo et al., 2002). In another recent study, monensin was detected in beef lagoon samples at 40 mg liter
1 in the filtered aqueous portion and 2000 mg kg
1 in the suspended solids portion (S. A. Sassman and L. S. Lee, unpublished data). In a nearby drainage ditch that received eZuent from several tile drained fields, monensin was detected at not more than 100 ng liter
1 in the aqueous fraction and at <1 ng kg
1 in the sediment from the bottom of the ditch (S. A. Sassman and L. S. Lee, unpublished data). A compilation of some antimicrobial concentration data for diVerent manures can be found in Table IX of Kumar et al. (2005). Antimicrobials were detected in dust originating from swine production farms. Hamscher et al. (2003) analyzed dust collected from a pig‐finishing unit at 1.5 m above the floor (typical breathing height of a human) annually for a period of 2 weeks to 1 month during the 1981–2000 time frame. Antimicrobials were routinely detected (18 of 20 samples) including tylosin, various tetracyclines, sulfamethazine, and chloramphenicol in total amounts ranging from 0.2 to 12.5 mg kg
1.

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

7

Aquaculture is another important source of antimicrobials in the environment. Estimates of antimicrobials used annually in the aquaculture industry in the United States vary from 93 to 196 thousand kg, which include primarily oxytetracycline, sulfamerazine, sulfadimethoxine, ormetoprim, and formalin (Benbrook, 2002). Although the quantity of antimicrobials used in aquaculture is small compared to other areas of animal husbandry, a direct comparison cannot be made because of the very diVerent environments (land based vs aqueous based) where the use occurs. Antimicrobials used in aquaculture are often released directly into aVected waters by leaching from food pellets. Rates of antimicrobial release from pellets vary, but losses of more than 50% within minutes (e.g., <15 min) have been reported (Inglis, 1996). In addition, food not eaten by fish and drugs excreted with feces settle at the bottom of net pens. Coyne et al. (1994) detected oxytetracycline in sediment under a marine salmon farm at levels as high as 10.9 mg kg
1. It is estimated that 70–80% of antimicrobial drugs used in aquaculture end up in the environment (Boxall et al., 2003).

B. HORMONES The detection of natural and synthetic estrogens and androgens in surface waters has sparked an interest in the research community and the general public because of their potential to invoke adverse ecological eVects at low concentrations. Table I lists several hormones of interest, including a few related compounds known to be endocrine disrupting chemicals (EDCs), along with selected characteristics for reference. Exposure to environmental estrogens has been linked to decreased sperm counts, increased testicular, prostate, and breast cancer, and reproductive disorders in human males (Peterson et al., 2000). The term environmental estrogens is commonly used to describe environmental agents, such as persistent organochlorines, plasticizers, pharmaceuticals, and natural and synthetic hormones, that alter the endocrine system (thus also referred to as EDCs for endocrine disrupting chemicals) (McLachlan, 2001). The large amounts of animal wastes and municipal biosolids that may contain hormones have been proposed to be a primary source of estrogens in the environment (Shore and Shemesh, 2003). However, hormones originating from CAFOs have yet to be causally linked to a significant eVect on the human endocrine system. The types of sex hormones excreted as well as the ratios of free to conjugated forms vary depending on the animal species, gender, and reproductive stage. For instance, cattle excrete over 90% of estrogens as 17a‐estradiol, estrone, and estriol, with most of it being composed of the 17a‐estradiol epimer. Conversely, 17a‐estradiol rarely occurs in the excreta of swine or

8

L. S. LEE ET AL.

Table I List of Hormones and EDCs from FDA 2004 Green Book, CAS Number, Molecular Weight (MW), and log Kow Calculated from the EPA Program KOWWIN Version 1.66 Unless Otherwise Noted Analyte 17a‐Ethinyl estradiol 17b‐Estradiol Bisphenol A Diethylstilbestrol Estriol Estrone Fluoxymesterone Hexestrol Levonorgestrel Melengestrol acetate Mestranol Methandrostenolone Methyl testosterone Nonylphenol ethoxylate Norethindrone Nortestosterone Octylphenol ethoxylate Progesterone Stanozolol Taleranol Testosterone Trenbolone Zearalanone Zeranol a

Class/comment Synthetic steroidal estrogen/human use Reproductive hormone Nonsteroidal estrogen from plastics Synthetic nonsteroidal estrogen/human use banned Reproductive hormone metabolite Reproductive hormone metabolite Synthetic anabolic steroid/human use Synthetic nonsteroidal estrogen/banned Synthetic steroidal estrogen/human use Synthetic steroidal estrogen/animal use Synthetic steroidal estrogen/human use Synthetic anabolic steroid/banned Synthetic anabolic steroid/human use Nonsteroidal estrogen from surfactants Synthetic steroidal estrogen/human use Anabolic steroid/synthetic form banned Nonsteroidal estrogen from surfactants Reproductive hormone Synthetic anabolic steroid/ human and animal use Nonsteroidal estrogen/ veterinary drug Reproductive hormone Synthetic anabolic steroid/ animal use Nonsteroidal estrogen/mycotoxin Nonsteroidal estrogen/ veterinary drug

Calculated using Chemaxon’s Marvinsketch# application.

CAS

MW

Log Kow

57‐63‐6

296.41

4.12

50‐28‐2 80‐05‐7

272.39 228.29

3.94 3.64

56‐53‐1

268.36

5.64

50‐27‐1

288.39

2.81

53‐16‐7

270.37

3.43

76‐43‐7

336.45

2.49

5635‐50‐7

270.37

5.6

797‐63‐7

312.46

3.48

5633‐18‐1

354.48

2.69a

72‐33‐3

310.44

4.68

72‐63‐9 58‐18‐4

300.44 302.46

3.51 3.72

25154‐52‐3

220.36

5.99

68‐22‐4

298.43

2.99

434‐22‐0

274.41

2.82

27193‐28‐8

206.33

5.5

57‐83‐0 10418‐03‐8

314.47 328.5

3.67 4.42 4.78a

58‐22‐0 10161‐33‐8

288.43 270.37

3.27 2.53a

17924‐92‐4 26538‐44‐3

318.37 322.4

3.58 5.37

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

9

poultry (Hanselman et al., 2003). The relative amount of total hormones in feces versus urine varies with animal species. For example, for cattle and sheep, nearly 70% of the total estrogens are excreted via feces, whereas for pigs, almost 90% of the total estrogens are excreted via urine (Lange et al., 2002). Irrespective of species, all steroids excreted in feces are in their free form, whereas the majority of steroids found in urine are water‐soluble conjugated glucoronide or sulfate forms (HoVmann et al., 1997; Lange et al., 2002). Currently, the environmental significance of conjugated versus unconjugated steroids is unknown. In terms of reproductive condition, during pregnancy, the placenta is a significant source of estrogens, and excretion of these estrogenic steroids usually increases with length of gestation (HoVmann et al., 1997; Lange et al., 2002). Other natural sex steroids commonly released to the environment by CAFOs include androgens (mostly 17a‐ or b‐testosterone, androstenedione, and related conjugates) and progestagens (progesterone and its metabolites 5a‐ or b‐pregnanediones, pregnenolones, and pregnenediols) (Lange et al., 2002). In addition to naturally produced hormones, cattle are implanted with hormone supplements to increase growth rates. A USDA survey indicates that more than 97% of cattle are routinely implanted with hormones (Balter, 1999; USDA, 2000). The primary growth promoters used in the United States include the androgens, testosterone and trenbolone acetate (TBA); the estrogens, 17b‐estradiol and zeranol; and the progestins, progesterone and melengestrol acetate (MGA) (Lange et al., 2001). Estrogen‐containing implants were first used in the 1950s with the synthetic anabolic agent TBA entering the United States market in 1987. These anabolics are used for various positive eVects including improved daily weight gains, feed conversion, dressing percentage, and increase dry matter intake (Song and Choi, 2001). Progestins are also used for estrus synchronization and/or induction in cattle (SchiVer et al., 2001). Except for MGA, hormones are administered to cattle via a subcutaneous ear implant either alone or in combination such as TBA and 17b‐estradiol, estradiol benzoate and progesterone, or estradiol benzoate and testosterone (Arcand‐Hoy et al., 1998; Stenquist, 1990). When TBA is administered to cattle, it is released to the blood where it is later hydrolyzed to produce the active form 17b‐trenbolone. 17b‐Trenbolone is later epimerized to form 17a‐trenbolone. Both isomers are excreted by the treated animals, but the a form predominates over the b form by a ratio of about 10:1 (SchiVer et al., 2001). TBA has been shown to be 8–10 times more eVective at growth promotion compared to the natural androgen testosterone. MGA is an orally active progestin (synthetic progestagen) used for estrus synchronization or induction in cattle. It is also marketed as a feed additive for feedlot heifers to improve feed eYciency and rate of weight gain (SchiVer et al., 2001). TBA and MGA are likely the most important

10

L. S. LEE ET AL.

nondietary source of hormones in animal manures because of their resistance to degradation and their ubiquitous use as growth promoters in the United States and Canada (Lorenzen et al., 2004; USEPA, 2003).

1. Hormone Occurrence in Animal Wastes Regardless of the strategies and techniques used to quantify the hormones excreted from livestock, the highest levels appear to be consistently measured for estrogens in swine wastes. For swine farrowing and finishing waste on a dry weight (dwt) mean basis, concentrations for estrone ranged from 200 to 5000 mg kg
1, 17a‐estradiol from 400 to 890 mg kg
1, and 17b‐estradiol from 160 to 1200 mg kg
1 (Hanselman et al., 2003; Raman et al., 2004). Mean concentrations of these three hormones tend to be lower in dairy cattle wastes (estrone: 203–800 mg kg
1, 17a‐estradiol: 139–603 mg kg
1, and 17b‐estradiol: below detection to 239 mg kg
1) and poultry litter (estrone: below detection, 17a‐estradiol: below detection, and 17b‐estradiol: 14–904 mg kg
1). The same trends have been reported for measurements of estrogen receptor gene‐transcription activity (Lorenzen et al., 2004). Mean estrogen activity in liquid swine manure ranged from 3000 to 6000 mg kg
1 dwt for adult sows and finishing pigs and from just under 2000 to 2500 mg kg
1 dwt for weaned pigs less than 1‐year old. Estrogen activity in dairy cow manure was slightly lower, ranging from 22 to 5000 mg kg
1 dwt. In poultry litter, mean estrogen activity ranged from 55 to 400 mg kg
1 dwt. We recently monitored hormones in manures excreted by cattle implanted with Ravoler‐S (140 mg TBA and 28 mg estradiol). Manure from these implanted cows was collected in the pit below their stalls and flushed every 2 weeks into a lagoon system consisting of two consecutive cells. Manure pits were sampled after mixing immediately prior to flushing, and the lagoons were sampled every 2 weeks starting with the fourth week after implanting. Trenbolone exhibited the highest concentration of the hormones in both the manure (3 mg liter
1 for the sum of a and b) and the lagoon samples with concentrations more than an order of magnitude lower in the lagoon cell 1. Hormone concentrations in cell 2 at 4 weeks after implants were generally below 0.03 mg liter
1 except for trendione (0.14 mg liter
1). Pit flush water is a mix of fresh and eZuent from cell 2. Of the estrogens, estriol levels were the highest but never exceeded 0.23 mg liter
1 (B. Khan, S. A. Sassman, and L. S. Lee, unpublished data). None of these studies observed statistically significant diVerences in manure estrogen levels between animals that were pregnant or lactating versus those that were not, or between egg‐laying chickens versus broilers. However, higher androgen receptor gene‐transcription activity was detected

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

11

in manure from pregnant, nonlactating cows (1700 mg kg
1 dwt) compared to lactating, early gestation cows (not detectable) (Lorenzen et al., 2004). In addition, only breeder layer flocks of chickens consistently produced litter with androgen activity, although levels were generally less than 30 mg kg
1 dwt (Lorenzen et al., 2004). The way that animal manures are stored and managed can also aVect hormone concentrations in certain cases. Swine finishing hoop systems, which utilize bedding material to collect and store animal waste in a dry state for a 6‐month period, had the highest mean 17b‐estradiol concentrations (40 mg kg
1). Mean estrone concentrations (54 mg kg
1) were second only to swine‐farrowing pits (57 mg kg
1), which store high solids, high‐ strength manure slurries in a completely anaerobic state for a period of about 6 months (Raman et al., 2004). However, for dairy cows, the type of manure storage did not consistently change either the estrogen or the androgen hormone equivalent activities. Instead, the type of diet fed to the animals did. Estrogen receptor gene‐transcription activity was significantly higher for manure from farms using feed containing soy (2000–3050 mg kg
1 dwt) compared to those that did not use such feed (<800 mg kg
1 dwt) (Lorenzen et al., 2004). Soy‐based foods have been shown to contain substantial amounts of phytoestrogens (Axelson et al., 1984). The presence of phytoestrogens in manure, water, and soil may be one reason why measures of estrogenic activity are frequently higher than reported hormone concentrations. Other reasons include interferences such as the presence of dissolved organic matter (DOM) and quantitative analysis of only a select few of actual hormones and associated metabolites present. Compared to dairy cows, beef cattle manure had relatively low levels of estrogen or androgen activity, even when the animals were treated with commercial estrogen and TBA implants. The highest levels of estrogen and androgen gene‐transcription activity (20 mg kg
1 dwt) were measured for heifers that had been treated with hormone implants, and levels decreased with time since the last implant. Interestingly, steers treated with estrogen (14 mg) and TBA (140 mg) had very low estrogen‐ and androgen‐activity levels (<2.5 mg kg
1 dwt and nondetectable, respectively) (Lorenzen et al., 2004). Heifers implanted with TE‐H (140 mg TBA and 14 mg 17b‐estradiol) or SYNOVEXÒ PLUS™ (200 mg TBA and 20 mg 17b‐estradiol benzoate) had fecal pats with the highest levels of estrogen and androgen receptor gene‐transcription activities compared to those implanted at earlier times. However, the hormone equivalent values were very low compared to manures from other farm animals (Lorenzen et al., 2004). Although manure and eZuent may be field applied in response to reducing waste volume, application is usually based on crop‐nutrient requirements, and thus, information exclusively on hormone concentrations on a dwt basis

L. S. LEE ET AL.

12

is not suYcient for predicting hormone‐loading rates. Raman et al. (2004) showed that although mean 17b‐estradiol concentrations on a dwt basis were three times higher in swine‐farrowing pits compared to lagoons, the mean 17b‐estradiol to nitrogen (N) ratio in the pit waste (13.75 ppt ppm
1) was about half of that in the lagoon (27 ppt ppm
1). Therefore, meeting N‐fertilizer needs with lagoon waste would contribute twice the amount of 17b‐estradiol compared to the pit waste. However, if P‐fertilizer requirements were limiting manure application rates, 17b‐estradiol concentrations would be the same for pit and lagoon wastes, but the former would contribute higher concentrations of estrone because mean estrone:P ratios in pits (222 ppt ppm
1) are much higher than in lagoons (89 ppt ppm
1). In contrast to swine, hormone to macronutrient ratios among diVerent dairy waste handling systems were not as variable and were generally lower than ratios observed for swine. However, mean feces production for cattle (10–40 kg day
1) is substantially greater than for swine (2 kg day
1) (Lange et al., 2002).

2.

Hormone Occurrence in Aqueous Environments

Over the past few decades, the availability of data on the occurrence of hormones in groundwater and surface waters has grown rapidly. Surveys as early as 1977 reported detection of estradiol in springs and wells used for drinking water, but levels were all below 1 ng liter
1 (Rurainski et al., 1977). In the first nationwide reconnaissance stream survey of pharmaceutical occurrence in the United States, reproductive hormones or their metabolites were detected in 3–21% of the streams assayed (number of samples tested 70) (Kolpin et al., 2002). For waters in which hormones were detected, the highest concentration in ng liter
1 reported are as follows with the median value given in parentheses: 93 (9) for 17b‐estradiol, 117 (27) for estrone, 51 (19) for estriol, 74 (30) for 17a‐estradiol, 214 (116) for testosterone, and 199 (111) for progesterone. Soto et al. (2004) and Durhan et al. (2006) investigated the presence of trenbolone and metabolites in waters associated with feedlots in Nebraska and Ohio, respectively. Hormonally active substances were noted in the feedlot eZuents with trenbolone and its primary metabolites contributing not more than 1.1% of the total androgenic activity (Soto et al., 2004). Durhan et al. (2006) detected 17a‐trenbolone more frequently and at higher concentrations (10–120 ng liter
1) than 17b‐ trenbolone (10–20 ng liter
1) at the point of discharge. Only small to negligible amounts of both isomers were detected in upstream and downstream samples. Fine et al. (2003) measured estrogen levels in swine lagoons from farrowing sow, nursery, and finishing operations. Estrogen concentrations were highest in lagoons with farrowing sow waste where estrone

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

13

concentrations ranged from 9600 to 24,900 ng liter
1 followed by estriol at 5000–10,400 ng liter
1 and 17b‐estradiol at 2200–3000 ng liter
1. One exception to the trend was a high estrone concentration of 74,700 ng liter
1 observed in a finishing facility lagoon. Reasons for this apparent anomaly are not known; however, this lagoon did contain much higher suspended material than the others. Estrogen levels were not detected or quantifiable in groundwater below the sow and nursery sites except for one sample that contained 4.5 ng liter
1 estrone.

III. SORPTION BY SOILS AND SEDIMENTS The potential adverse impacts of antimicrobials and hormones generated from agricultural activities will be directly aVected by their persistence and mobility in manure as well as in the aqueous and soil environment. Compound‐ specific properties including hydrophobicity, ionization potential, sorption, and degradability, along with a variety of environmental factors such as local hydrology, soil characteristics, and climate conditions, will all contribute to their ultimate fate and potential to reach nontarget biota. Predicting the magnitude of sorption to soils and sediment, and identifying the domains that control sorption can be important in assessing the risks to the aquatic ecosystem associated with antimicrobials and reproductive hormones from agricultural activities.

A. ANTIMICROBIALS Several studies have quantified sorption isotherms for some of the most commonly used antimicrobials. Partition coeYcients (Kd, liter kg
1), which express the ratio of the solute concentration sorbed to the soil phase (Cs, mg kg
1) to that freely dissolved in the aqueous phase (Cw, mg liter
1), range from less than 1 liter kg
1 to more than 350,000 liter kg
1 (Kumar et al., 2005; Sassman and Lee, 2005a; Tolls, 2001). Unlike previously studied organic soil contaminants that were primarily neutral and hydrophobic, antimicrobials are moderately polar to polar and often posses functional groups (e.g., –C¼O, –NO2, –NH2, –OH, –CN, –OH, –COOH) that contribute to moderately high aqueous solubility, while simultaneously promoting sorption to charged soil surfaces. Coexisting pH‐dependent species (i.e., cation, anion, zwitterion) will interact to varying degrees with the sorptive components of soil (e.g., aluminosilicate clays, organic matter, oxides, and

14

L. S. LEE ET AL.

oxyhydroxides) through cation exchange, cation bridging, complexation, and H‐bonding. As a result, the variability among Kd values for a particular antimicrobial sorbed to diVerent soils is not reduced by normalization to soil organic carbon (OC) content (Tolls, 2001). Among high‐use veterinary antimicrobials, members of the tetracycline and quinolone groups sorb strongly to soil (Kd: 70–353,000 liter kg
1), followed by the macrolids (Kd: 8–6100 liter kg
1), ionophores (Kd: 0.5–280 liter kg
1), and the sulfonamides and nitroimidazoles (Kd: 0.2–2 liter kg
1) (Oliviera et al., 2002; Sassman and Lee, 2005a,b; Tolls, 2001). Binding by cation exchange has been shown to be an important sorption mechanism for compounds possessing a positive charge. Indeed, research on other basic organic contaminants has demonstrated that when cation exchange governs contaminant binding to soils, Kd can be normalized with the soil’s cation exchange capacity (CEC) as follows:
1 ) is the CEC‐normalized distribuKCEC ¼ Kd =CEC where KCEC (liter cmol(þ) tion coeYcient (Lee et al., 1997; Zachara et al., 1986). Sassman and Lee (2005a) showed that this concept is also applicable to the sorption of tetracyclines by soils with a wide range of properties. The range of pKa values associated with the dimethylammonium group and –OH groups (3.3–9.3) in tetracyclines results in large shifts in the predominance of the cation (þ00), zwitterion (þ
0), or anionic species (þ

) over the range of typical soil pH values. A sorption model in which species‐specific sorption coeYcients normalized to þ00 þ
0 þ

; KCEC ; KCEC Þ and weighted by the pH‐dependent pH‐dependent CEC ðKCEC fraction of each species ð fþ00 ; fþ
0 ; fþ

Þ fit the data well across all soils, except for a soil rich in gibbsite and high in anion exchange capacity. The  , liter cmol
1) was expressed as: overall distribution coeYcient (KCEC þ00 þ
0 þ

 KCEC ¼ KCEC  fþ00 þ KCEC  fþ
0 þ KCEC  fþ

. This approach was used by Figueroa et al. (2004) to describe tetracycline sorption to isolated clay minerals. The exchange concept is also consistent with studies on tetracyclines and sulfonamides that reported decreases in Kd values with increasing soil pH (Jones et al., 2005; Kulshrestha et al., 2004). In addition, Sassman and Lee (2005a) observed changes in sorption with electrolyte composition that generally followed: 0.001 N CaCl2 > 0.01 N KCl > 0.01 N CaCl2 after accounting for induced pH shifts, which is consistent with a cation‐exchange mechanism. Cation bridging with divalent and trivalent cations present in soils has also emerged as an important sorption mechanism for zwitterionic antimicrobials possessing negatively charged functional groups. This was demonstrated in work on ciprofloxacin sorption to Al‐ and Fe‐hydrous oxides (Gu and Karthikeyan, 2005). Ciprofloxacin is a human medicine, but it is also the primary metabolite of enrofloxacin, a veterinary antimicrobial that diVers structurally from ciprofloxacin by a single ethyl group. Ciprofloxacin sorption was highly pH‐dependent between pH 4 and 10, particularly for the Fe‐hydrous oxides. Overall KCEC values increased with increasing pH up to approximately pH 7, but with further decreases in pH, both the sorbate and

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

15

sorbent became increasingly more negatively charged, and sorption decreased. Interestingly, the sorption capacity for the Fe‐hydrous oxide was higher than the Al‐hydrous oxide. Analysis by Fourier transform infrared spectroscopy (FTIR) indicated that this was attributable to the formation of a strong bidentate complex between an Fe atom and the keto‐O and deprotonated O of the carboxylate group. In contrast, ciprofloxacin formed only a monodentate complex between the deprotonated carboxylate group and an Al atom. This spectroscopic evidence for cation bridging supports results from previous studies that found sorption of fluoroquinolones and tetracyclines could be explained by the formation of complexes with Ca2þ, Al3þ, and Fe3þ (Sithole and Guy, 1987). Compared to other commonly used antimicrobials, relatively little attention has been directed toward understanding the interactions with soils for antimicrobials that are not concurrently used in human medicine such as ionophores and carbadox. Monensin and lasalocid are both carboxylic ionophores produced by Streptomyces and used to treat coccidiosis. Monensin was classified as having a high priority for a detailed risk assessment based on toxicity and usage profiles and the potential to reach the environment (Capleton et al., 2006). The sorption by soils with diverse properties was reported for monensin and lasalosid (Sassman and Lee, 2005b). Monensin Kd values ranged from a low of 0.5 liter kg
1 for a soil with low CEC (4.3 cmol(þ) kg
1) and low organic matter content (0.64% organic C), to 50 and 65 liter kg
1 for two soils of relatively low pH (4.2 and 5.5, respectively) that possessed some anion exchange capacity (0.03 and 0.42 cmol(
) kg
1). The same trends were observed for lasalocid with Kd values ranging from 9 to 280 liter kg
1. The higher Kd values for lasalocid reflect this compound’s greater hydrophobicity compared to monensin, which is consistent with their estimated Kow values (Sassman and Lee, 2005b). Carbadox (methyl 3‐[2‐quinoxalinylmethylene]carbazate N1, N4 dioxide) is a chemotherapeutic growth promoter and antibacterial drug added to feed for starter pigs to prevent dysentery and improve feed eYciency. Carbadox has been shown to be rapidly metabolized in the pig’s liver and kidneys, producing both mono‐N1 and mono‐N2 oxides, bis‐desoxycarbadox, and quinoxaline‐2‐carboxylic acid. Both carbadox and bis‐desoxycarbadox have been shown to be potential mutagens (Freedom of Information Summary, 1998), thus much research has been done to assess their stability and residence time in edible swine tissue as well as transport and transformation through the pig’s gastrointestinal tract (references [1–12] cited in Strock et al., 2005). However, available literature about sorption of compounds containing aromatic N‐oxides is sparse. Strock et al. (2005) measured sorption of carbadox, bis‐desoxycarbadox, and two N‐oxide‐reduced metabolites by soils, sediment, and homoionic smectite and kalonite clays with CaCl2 or KCl solutions. Sorption appeared well correlated to OC for the soils,

16

L. S. LEE ET AL.

for example, log[Koc, liter kg
1 OC] ¼ 3.96 þ 0.18 for carbadox. However, sorption was enhanced in the presence of Kþ, competitive sorption by the metabolites was observed, and sorption by clay minerals was large (105 liter kg
1 for SWy‐1 montmorillinite) and inversely correlated to surface charge density. In fact, the 2000 Feed Additive Compendum cautions against adding carbadox to feed containing bentonite clays, which is often used as a pellet‐ binding agent in feed, indicating reduction in the antibiotic eYcacy of carbadox (Animal Health Institute, 2000). In the absence of a clay surface, hydrophobic‐ type forces dominated as evidenced by increasing Kow values and reverse‐phase chromatographic retention times with the loss of oxygen from the aromatic nitrogens. Therefore, although sorption was generally well described by OC, specific interactions with clays can contribute significantly to sorption of carbadox and related metabolites.

B. HORMONES Sorption of reproductive hormones by soils and sediments will impact their degradation and transport into aquatic systems. Lee et al. (2003) and Khan et al. (2005) examined the simultaneous sorption and dissipation of three reproductive hormones (testosterone, 17b‐estradiol, and 17a‐ethynyl estradiol) and one androgen (17b‐trenbolone), respectively, in several Midwestern US soils. Sorption isotherms were generated by measuring aqueous concentrations and extracting the sorbed parent chemical or transformation products (e.g., estrone from 17b‐estradiol, androstenedione from testosterone, and trendione from 17b‐trenbolone). Sorption isotherms for the parent hormones and their principal transformation products were generally linear and near equilibrium appeared to be reached within a few hours. Average OC‐normalized sorption coeYcients (Koc) resulted in standard deviations of less than 0.3 log units (Table II) and were consistent with reported aqueous solubilities and octanol–water partition coeYcients, indicating hydrophobic partitioning as the dominant sorption mechanism. Lai et al. (2000) also reported a high positive correlation between sorption and OC for 17b‐estradiol, estrone, estriol, 17a‐ethynyl estradiol, and mestranol on five sediments ranging in OC from 0.3% to 2.2%. In addition, they noted significant sorption to an iron oxide; however, sorption was measured by diVerence, thus loss of mass from solution may have occurred through oxide‐catalyzed transformations rather than sorption. SchiVer et al. (2004) measured sorption of 17b‐trenbolone and MGA by the surface and subsurface horizons of an agricultural soil with OC contents of 1.6% and 0.3%, respectively. Sorption was positively correlated to soil OC and was generally linear with the exception of trenbolone which exhibited substantial nonlinear sorption on the surface horizon (Freundlich N value of 0.59). Estimated log Koc values (Table II) were high relative to values reported for same or similar

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

17

Table II Properties of Selected Estrogens and Androgens

Hormone

Molecular weight (g mol
1)

Water solubility (mg liter
1)

a Log Kow

Log Kow

Deg range in t½ (day)

17b‐Estradiol

272.4

13a

4.01f 3.10a 3.94a 4.01n

3.34  0.18h

0.8–9.7h 0.4–2j 0.3–0.5k

Estrone

270.4

13a

3.43a 3.13a,f 3.38c 2.45f 4.54n

3.20  0.02h

0.7–4.8j 0.6–1.7k

Estriol

288.4

32d

2.81a 2.6a 2.55c 3.24n

NAg

NAg

17a‐Ethynyl estradiol

296.4

4.8

3.67a 4.15a 4.02n

2.99  0.07h

3.1–9.6h 1.9–6.9l

Testosterone

288.4

18–25b

3.22c 3.84n

3.32  0.18h

0.3–7.3h 2–14j

Androstenedione

286.4

37–41e

4.36n

3.72  0.05h

0.7–3.2j

(continued)

18

L. S. LEE ET AL. Table II (continued )

Hormone

Molecular weight (g mol
1)

Water solubility (mg liter
1)

a Log Kow

Log Kow

Deg range in t½ (day)

17b‐Trenbolone

270.4

20m

2.53n

3.26  0.15i 4.28  0.03m

0.2–0.5i

Trendione

268.4

NA

3.06n

3.60  0.27i

3–5i

Melengestrol acetate

396.5

0.1m

4.01n

4.40  0.43m

NAg

a

Cited by Lai et al. (2000). Sugaya et al. (2002). c Calculated by Nuez and Yalkowsky (1997). d Solubility from a control tablet comprising estriol and a‐cyclodextrin (1988). e Measured at 37  C (Lee et al., 1985). f Suzuki et al. (2001). g Not available. h Lee et al. (2003). i Khan et al. (2005). j Das et al. (2003). k Colucci et al. (2001a). l Colucci et al. (2001b). m Estimated from data reported by SchiVer et al. (2004). n Calculated using Marvinsketch# from www.chemaxon.com. b

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

19

hormones. Sorption was estimated by loss from solution and degradation of 17b‐trenbolone was noted, thus contributing to artificially high Koc values.

IV.

DEGRADATION IN SOIL, MANURE, AND AQUEOUS ENVIRONMENTS

A.

ANTIMICROBIAL DEGRADATION

IN

MANURE AND SOIL

Studies evaluating the degradation of antimicrobials in manure and aqueous soil environments are limited and usually only consider loss of the parent compound. Since antimicrobials are typically large compounds with multiple functional groups, transformation of the parent may involve the change of a single functional group, which may or may not alter the potential adverse eVects of the compound on the ecosystem. Much of the published literature on antimicrobial degradation was tabulated by Kumar et al. (2005). Half‐lives (strictly loss of the parent compound) ranged from a few days to over a year depending on the specific antimicrobial and associated environmental conditions. Longer half‐lives were typically associated with anaerobic environments. Degradation data not noted in the Kumar et al. (2005) are highlighted in the following discussion. For monensin, concentrations declined from 4.5 to 2.6 mg kg
1 after 10 weeks in fresh feces from monensin‐fed cattle incubated at 37  C (Donoho, 1984). In a 2‐week old manure land pile, monensin concentrations decreased from 4.7 to 2.8 mg kg
1 in a 3‐week period, and subsequently to 0.7 mg kg
1 in the following 6 weeks. When monensin was incorporated into soil at 1 mg kg
1 with and without manure, all monensin degraded within 1 month. In another study with monensin and lasalocid, degradation in moist aerobic soil microcosms was rapid with half‐lives (t1/2) ranging from 2.2 to 3.3 days (Sassman and Lee, 2005b). These data indicate that while monensin and related antimicrobials may degrade slowly in a fresh manure anaerobic environment, the parent compounds will be short‐lived once they are introduced to an aerobic land scenario. Oliveria et al. (2002) and Strock (2004) examined the fate of tylosin, carbadox, and chlortetracycline in bench‐scale‐simulated manure microcosms incubated at room temperature with manure collected from swine fed a single antimicrobial at the recommended dose (50 mg kg
1). Only desoxycarbadox (the di‐N‐oxide‐reduced metabolite of carbadox) was detectable in fresh manure at concentrations ranging from 0.25 to 0.75 mg g
1. Desoxycarbadox concentrations diminished in the manure microcosms over the next 40 days with an estimated half‐life of 9 days (Strock, 2004). For pigs fed Tylan, tylosin A (17 mg g
1 dwt), tylosin D (251 mg g
1 dwt), and the

20

L. S. LEE ET AL.

metabolite O‐mycaminosyltylonolide (5.27 mg g
1 dwt) were found to be the primary forms of tylosin present in 1‐day‐old manure samples, with most of the antimicrobial present in the feces. The estimated t1/2 of the active ingredient, tylosin A, was about 1 week (Oliveria et al., 2002). The initial concentration of chlortetracycline in the manure was 5 mg kg
1, and its t1/2 value was estimated at about 3 weeks (Oliveria et al., 2002). In another study where calves were treated with oxytetracycline and tylosin at recommended levels, tylosin was found to degrade rapidly in the manure while OTC was more persistent (De Liguoro et al., 2003). The t1/2 of OTC in manure was 30 days, and after 5 months the concentration had decreased to 0.82 mg kg
1.

B. ANTIMICROBIAL DEGRADATION

IN

AQUEOUS ENVIRONMENTS

A large portion (70–80%) of the antimicrobials used extensively for treatment of infectious disease in aquaculture appear to end up in the environment mostly due to the deposition of feed pellets and fish feces (Samuelsen et al., 1992). Bjorklund et al. (1991) found oxytetracycline concentrations of 0.8–6.3 mg kg
1 in sediment under medicated fish pens, while Coyne et al. (1994) measured concentrations as high as 10.9 mg kg
1 under a marine salmon farm. Oxolinic acid, flumequine, oxytetracycline, sulfadiazine, and sulfadimethoxine were stable for 180 days in artificial aquaculture sediment under lab conditions (Samuelsen et al., 1994). However, Coyne et al. (1994) measured a t1/2 for oxytetracycline of 13–16 days in sediments under a marine salmon farm. Bjorklund et al. (1990) found that the t1/2 of OTC in sediments was 9 days on one farm, but 419 days on another where sediment conditions appeared more stagnant, thus potentially under more anoxic conditions. Microbial assays indicated oxolinic acid, flumequine, sulfadiazine, and sulfadimethoxine were stable with only a 20% decrease in 180 days whereas ormethoprim and trimethoprim could not be detected after 1 and 2 months, respectively (Samuelsen et al., 1994). In addition to concerns about the persistence of antimicrobials in sediments under fish farms, the presence and fate of antimicrobials in the farm eZuent where they are directly bioavailable are of greater concern. Samuelsen (1989) found that the t1/2 of oxytetracycline in seawater varied from 128 to 390 h depending on amount of light. Oxytetracycline residues were detected in wild fish for up to 13 days after treatment in a fish farm (Bjorklund et al., 1990).

C. HORMONE STABILITY IN MANURE, URINE, AND COMPOSTED MANURE The number of studies assessing the occurrence of hormones in manures has increased in the last 5 years; however, research on the degradation of hormones in manure during storage and after being land applied is still sparse

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

21

and limited. In bovine urine samples, Van der Merwe and Pieterse (1994) noted zeranol and taleranol appeared stable when frozen and under direct sunlight (up to 50  C), whereas trenbolone degraded significantly. However, in a cattle manure canal, which was likely anaerobic, 17a‐trenbolone and 17b‐ trenbolone appeared relatively persistent with estimated t1/2 of about 267 and 257 days, respectively. Trendione, the primary metabolite for trenbolone, was detected in fresh manure and concentrations did not decline over time. In solid dung hills, which would likely be aerobic for the most part, trenbolone and metabolite dissipation appeared to be more rapid, which likely included both microbial degradation and leaching (SchiVer et al., 2001). MGA was also tracked in the solid dung hills. Although initial MGA concentrations varied with sampling position within the hill, upper levels of MGA did not change much over the storage period (4.5 months). One management option for reducing hormone levels is composting. Hakk et al. (2005) monitored levels of water‐soluble hormones using immunoassay kits of 17b‐estradiol and testosterone in organic‐amended poultry manure. The manure was amended with hay, leaves, and straw to achieve an initial C:N ratio of 30 followed by weekly turning to enhance aeration. Water‐soluble concentrations were determined from an aqueous batch extraction and were assumed to be a representative index of leaching by rain water. Decreases in the amount of water‐soluble 17b‐estradiol and testosterone followed first‐order kinetics with loss rate constants of 0.01 and 0.015 per day, respectively. However, hormones could still be detected in water extracts after 4.6 months of composting. Total hormone concentrations of the amended manure over time were not clearly reported, thus, the total hormone mass available for water desorption after composting was not clear. In addition, there was no control data with regards to what the water‐extractable hormone levels were in the manure prior to composting and how they changed with time in the absence of composting. Therefore, although composting may hold promise, further research is needed to optimize and assess composting strategies with regards to hormone dissipation.

D. HORMONE STABILITY

IN

SOILS AND MANURE‐AMENDED SOILS

Currently, most studies on hormone degradation involve hormones added directly to soils without incorporating a manure matrix. In moist soil microcosms with three agricultural soils from Ontario, Colucci et al. (2001a,b) reported dissipation constants between 0.1 and 3 per day for 17b‐ estradiol and 17a‐ethynyl estradiol, which corresponds to t1/2 values between 0.2 and 7 days. 17b‐Estradiol was oxidized to estrone in both autoclaved and nonsterile soils, respectively whereas 17a‐ethynyl estradiol and estrone appeared stable in autoclaved soils. However, based on radiolabeled material,

22

L. S. LEE ET AL.

both estradiol and its primary metabolite, estrone, formed nonextractable residues (56–91% in a few days), but only in nonsterile systems. Complete mineralization was slow, with not more than 15% of the estrogens mineralized after 61 days (Colucci et al., 2001a). Lee et al. (2003) observed similar t1/2 values for 17b‐estradiol, 17a‐ethynyl estradiol, and testosterone in aerobic soil–water slurries assuming a pseudo‐first‐order degradation process (Table II). Likewise, the synthetic androgen, 17b‐trenbolone, degraded to trendione under aerobic conditions in both saturated soil slurries and unsaturated moist soil microcosms with t1/2 values less than 1 day. However, subsequent degradation of trendione was much slower with half‐lives between 3 and 5 days. Therefore, although trenbolone appears to be persistent in manure pits (SchiVer et al., 2001), which are likely to be anaerobic, once applied to an aerobic soil environment, degradation of the parent compound appears to occur rapidly. Das et al. (2003) estimated degradation coeYcients of testosterone and 17b‐ estradiol and their multiple metabolites during flow‐interruption periods in column studies involving a surface soil, fresh‐water sediment, and two sands. Estimated degradation rate coeYcients (k) in the agricultural surface soil and the freshwater sediment ranged from 0.002 to 0.41 h
1 (t1/2 ¼ 0.07–14 days) (Table II) with k values for the two primary metabolites being larger than those for the parent hormones. Estimated k values decreased with column life, most likely as a result of nutrient depletion; addition of NHþ 4 increased the rate of degradation. Estimated sorption mass‐transfer constants estimated during flow were at least an order of magnitude larger than degradation rate coeYcients. Therefore, although sorption by soils of the parent and metabolites was substantial (4–80 liter kg
1), sorption did not hinder degradation and near‐ equilibrium sorption conditions could be assumed within a short timeframe as was previously indicated in batch studies by Lee et al. (2003). In similar continuous flow column studies, SchiVer et al. (2004) observed conversion of 17b‐trenbolone to 17a‐trenbolone. 17b‐Trenbolone was still predominant in the column eZuent, but the percentage present as metabolites was higher in the surface (Ap) horizon (37%) compared to the Bt subsurface horizon (12%). Soil properties can aVect abiotic transformation as well as microbial transformation. The Bt soil had a higher clay content (31% vs 14%), but the Ap horizon had higher amounts of OC (1.6% vs 0.3%) and a higher pH (6.8 vs 5.9); therefore, diVerences are likely due to higher fertility, thus higher microbial activity in the Ap horizon in agreement with observations reported by Das et al. (2003). Incubation of moist soils amended with 10% swine‐manure in laboratory microcosms showed increased conversion to metabolites of 17b‐estradiol and testosterone over time (Jacobsen et al., 2005). However, complete mineralization (to CO2) was decreased by the amendments as monitored using radio‐labeled 17b‐estradiol and testosterone. These results indicate that manure‐borne microbes may be better acclimated at transforming

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

23

hormones to their metabolites with typically lower endocrine disruption potential, although soil microbes may enhance complete mineralization.

V. TRANSPORT PROCESSES Strong sorption of most antimicrobials and short half‐lives for steroid hormones suggest that leaching from soils will be limited, which seems contradictory to their frequent detection in surface and groundwater. However, previous work on other strongly sorbing organic compounds has shown that desorption, surface runoV, preferential transport through soil macropores to groundwater or tile drains, and DOM‐facilitated transport can enhance contaminant mobility (Haws, 2003; Hoorman et al., 2004; Huang and Lee, 2001; Kung et al., 2000). Rapid transport to tile drains regardless of solute reactivity, especially following the first rainfall event after application, has been well documented (Kladivko et al., 2001). Haws (2003) conducted water and solute transport studies on two subsurface‐drained agricultural fields using multiple nonretarded (chloride and bromide) and reactive (atrazine and alachlor) tracers to identify if only chemicals applied immediately above the tile drain were vulnerable to rapid transport. Tracers were surface‐ applied at diVerent horizontal distances above a tile drain that was located 1 m below the surface. Peak concentration for both chloride and atrazine applied 0–1 m from the tile drain preceded the water peak, indicating that drainage is primarily event water and interactions with the soil were minimal. Furthermore, bromide and alachlor placed 5 m from the tile drain arrived in the tile drain simultaneously, clearly exemplifying the spatial extent of preferential networks. Laboratory column studies with intact cores from the site suggested that a primary network of large macropores (possibly root channels and earthworm burrows) serves as preferential flow paths when soils were near or at saturation. As the soil saturation level decreases, transport occurs through a primary network of smaller macropores (Haws et al., 2004). Preferential flow of liquid animal manure as evident by the appearance of manure in tile drains upon subsurface injection in a field where soil was already at its water‐holding capacity has been observed (Hoorman et al., 2004). Research directed toward evaluating these transport processes with regards to antimicrobial and hormone inputs from agricultural practices is in its infancy.

A. DOM‐FACILIATED TRANSPORT OF ANTIMICROBIALS Since many antimicrobials are highly persistent in the environment, soils contaminated with antimicrobial‐laden manure may act as a reservoir from which the compounds desorb into the aqueous phase over time

24

L. S. LEE ET AL.

(Carlson and Mabury, 2006; Kumar et al., 2005). For example, it has been shown that oxytetracycline concentrations between 0.6 and 3.3 mg g
1 dwt sediment were easily desorbed from the sediments of two Maryland rivers impacted by sewage treatment plants and poultry agriculture (Simon, 2005). Aqueous concentrations of antimicrobials may also be enhanced through associations with DOM from manure or lagoon eZuent. Antimicrobials may bind to DOM by cation exchange and cation bridging, with the dominant sorption mechanism depending on the properties of the contaminant (e.g., polarity, charge) and the DOM (e.g., composition, acidity). Subsequently, the DOM can act as a carrier and facilitate transport through a soil profile. Recent work which examined the sorption of oxytetracycline and several fluoroquinolones by solutions of Aldrich humic acid provides evidence supporting this hypothesis. For oxytetracycline, DOM binding coeYcients (KDOM) measured with a dialysis membrane technique ranged from 5500 to 250,000 liter kg
1, and increased with the addition of polyvalent metal cations (e.g., Al3þ, Fe3þ) that promoted the formation of ternary complexes between oxytetracycline and humic acid ligand groups (MacKay and Canterbury, 2005). In contrast, additions of Ca2þ reduced KDOM values from 5500 to 2980 liter kg
1, indicating that Ca2þ competed with oxytetracycline for cation‐exchange sites on the humic acid. Binding coeYcients for fluoroquinolones fell within the same range (3000–200,000 liter kg
1), and in some cases showed a pronounced pH dependence (Holten Lu¨tzhøft et al., 2000). For example, KDOM values for flumequin and oxolinic acid increased between pH 3 and 6, and remained constant at higher pH levels despite the increase in electrostatic repulsion between the negatively charged antimicrobial and humic acid. These results are consistent with a cation‐bridging mechanism since both antimicrobials posses a single pKa associated with a carboxylic acid group (flumequin: 6.4, oxolinic acid: 6.9). In contrast, binding of sarafloxacin, which has a basic amine group (pKa: 8.6) in addition to the carboxylic acid group, was higher than either flumequin or oxolinic acid under acidic conditions and remained relatively constant between pH 3 and 8. This behavior suggests that compounds with positive and negative functional groups may bind to DOM by both cation exchange and cation‐bridging mechanisms depending upon the pH and availability of complexing polyvalent metals. However, a shortcoming of the two studies conducted to date is the use of Aldrich humic acid, which is a poor surrogate for soil‐, water‐, or waste‐ derived humic material (Malcolm and MacCarthy, 1986). Known diVerences in the proportion of aliphatic versus aromatic components, and hydrophobic versus hydrophilic components can be expected to impact the degree to which antimicrobials and DOM will interact, making the extrapolation of binding constants among types of DOM tenuous. Among waste‐derived organic materials, the hydrophilic fraction can range from less than 10% to

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

25

60% depending on whether anaerobic or aerobic conditions were maintained (Gigliotti et al., 2002). To date, two studies have examined the eVect of DOM on the mobility or aqueous concentration of antimicrobials, and results have been inconsistent. A soil column study showed that the presence of manure slurry did not aVect the mobility of sulfachloropyridazine and oxytetracycline (Kay et al., 2005b). In contrast, a batch equilibrium study on five diVerent sulfonamides found that DOM from swine manure increased the antimicrobials’ aqueous concentrations (Thiele‐Bruhn and Aust, 2004). The roots of these inconsistencies are unknown since no study has yet directly measured binding constants for antimicrobials on soil‐ or waste‐derived DOM. We recently examined the sorption of enrofloxacin and ciprofloxacin to Aldrich humic acid and DOM isolated from swine manure. Similar to findings by MacKay and Canterbury (2005) and Holten Lu¨tzhøft et al. (2000), both antibiotics sorbed strongly to Aldrich humic acid (KDOM 4.5–5.1) (N. Carmosini and L. S. Lee, unpublished data). In contrast, however, preliminary experiments indicate that the antibiotics have no aYnity for the swine‐derived DOM, highlighting the importance of evaluating eVects on contaminant solubility and transport with environmentally relevant DOM.

B. RUNOFF VERSUS DRAINAGE

OF

ANTIMICROBIALS

A handful of recent studies have evaluated the relative contributions that drainage and overland flow (runoV) make toward the loss of antimicrobials from soils. In field studies where soils were amended with contaminated swine manure, peak concentrations of sulfachloropyridazine and oxytetracycline were 613 and 36 mg liter
1 in drain flow (Kay et al., 2004) and 703 and 72 mg liter
1 in runoV (Kay et al., 2005a). Tylosin was not detected in any samples, reflecting its tendency to sorb strongly to soil and degrade rapidly (Loke et al., 2000, 2002; Oliveira et al., 2002; Rabolle and Spliid, 2000). In a similar study, concentrations of three sulfonamides in runoV from manured soil ranged from 330 to 360 mg liter
1 (Kreuzig et al., 2005). In general, aqueous phase transport accounted for the majority of antimicrobial loss (78% to >99%), even though suspended sediment levels were in the order of hundreds of mg liter
1 (Kay et al., 2005a). However, sediment transport made the greatest contribution toward the transport of oxytetracycline (22%) compared to sulfachloropyridazine (1%). This reflects the tendency for tetracyclines to sorb strongly to soils relative to sulfonamides. The significance of sediment transport for strongly sorbing antimicrobials is also demonstrated by a study that found that the oxytetracycline concentration in eZuent from a land‐based fish farm was significantly reduced or completely eliminated when filtration or sedimentation traps were used (Smith et al., 1994).

L. S. LEE ET AL.

26

C.

HORMONE TRANSPORT

Das et al. (2003) examined the fate and transport of testosterone and 17b‐estradiol in a series of fast‐flow‐velocity transport experiments under pulse‐type and flow‐interruption boundary conditions in columns packed with a surface soil, fresh‐water sediment, and two sands. Sorption of both the parent hormones and the metabolites was proportional to soil OC with log KOC values (2.77–3.69) similar to what was observed by Lee et al. (2003) in batch equilibration studies. Larsen et al. (2001) evaluated sorption and mobility of 17b‐estradiol and testosterone in two soils, a Glyndon silt loam (a Mollisol with 2–3% organic carbon) and a sand. Consistent with hydrophobic processes dominating sorption, neither hormone was eluted from the silt loam column after leaching with more than 10 pore volumes of water. Of the applied testosterone and 17b‐estradiol, 80% and 96% respectively, were retained within the top 5 cm. In contrast, the sand column eluted 90% of both compounds within two pore volumes. Contrary to what others have observed, Casey et al. (2003) reported a high correlation between 17b‐estradiol sorption and soil surface area and CEC. Although 17b‐estradiol has an ionizable phenolic group, its pKa is well above environmentally relevant pH values (pKa ¼ 10.71) and when ionized (pH > 8.7) it will be present as an organic anion. Therefore, neither the neutral nor the charged species is amenable to cation exchange. The apparent correlation to CEC may be due to the positive relationship between CEC and organic matter. Casey et al. (2003) also reported similar sorption coeYcients for 17b‐estradiol on pure bentonite clay and a 7.5% organic matter loam soil. Sorption was measured by diVerence with long contact times (48–168 h), thus loss of chemical due to microbial degradation or surface‐ induced abiotic transformation may have also caused artifacts confounding data interpretation. SchiVer et al. (2004) investigated the transport of trenbolone and MGA in laboratory columns packed with either the Ap or Bt horizons of an aggregated agricultural Luvisol soil. Both MGA and 17b‐trenbolone exhibited very high aYnity to the soil organic matter leading to high retardation within the upper layers of the soil columns. However, small amounts of both compounds passed through the columns within one pore volume as detected by an enzyme immunoassay, and additional breakthrough occurred earlier than predicted from sorption isotherm data. The latter was likely due to physical nonequilibrium processes (i.e., mobile–immobile regions within aggregated soil as indicated by early and skewed chloride breakthrough), and possibly DOM‐facilitated transport. Substantial amounts of DOC did breakthrough in the first few pore volumes. Sorption coeYcients of selected estrogenic compounds (17b‐estradiol, 17a‐ethynyl estradiol, estriol, p‐nonylphenol, p‐tert‐octyl‐phenol, and

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

27

dibutylthalate) for a variety of surrogate DOMs have been reported (Yamamoto et al., 2003). The lowest average log KDOM values were measured with polysaccharides, alginic acid, and dextran (2.76–3.75). Average log Koc values for well‐characterized humic and fulvic acids ranged from 4.55 to 4.99. The highest log KDOM values were measured for tannic acid (4.84–5.32). No significant correlation between log KDOM and log Kow has been observed, which diVers from results for more strongly hydrophobic neutral compounds. Instead, log KDOM values were better correlated to the phenolic group concentration of the DOM and UV absorptivity at 272 nm, which reflects the aromaticity of DOM. The authors concluded that rather than simple hydrophobic partitioning, these results indicate that the sorption is driven by H‐bonding and interactions between p‐electrons of the estrogenic compounds and the DOM. Shore et al. (2004) monitored 15 sites for two consecutive rain seasons in the Upper Jordan Valley, which included small farms, cattle pasture, and fish ponds. Concentrations were highest after the first and heavy rain event following an unseasonably low 3‐year rainfall period. Testosterone was detected first at concentrations as high as 6 ng liter
1 followed by estrogen at similar levels, which gradually decreased over a 3‐month period to nondetectable levels (<0.3 ng liter
1). These concentrations were attributed to runoV from cattle pastures and fish pond eZuent. Later peaks consisted of only testosterone and were attributed to leaching from soil and baseline flow. Shore et al. (1997) monitored five wells located in the Chesapeake Bay Watershed under a farm with extensive animal husbandry and fields where chicken and pig manures were routinely applied in which only small amounts of testosterone (1 ng liter
1) and no estrogen (<0.1 ng liter
1) were observed. Likewise in an earlier study, only testosterone appeared to leach with aqueous solutions from a heavy soil while estradiol remained bound in the upper soil layer (Shore et al., 1993). Therefore, although testosterone appears to have a similar reversible equilibrium sorption coeYcient as estradiol (Table II), estradiol appears to undergo irreversible sorption or transformation processes to a much greater extent or faster rate than testosterone, possibly due to specific interactions (e.g., H‐bonding, ligand exchange) with the phenolic group on estradiol. Most field‐monitoring studies, attempting to link land application of manure with the presence of veterinary pharmaceuticals in surface waters, have focused on measuring concentrations of either or both estradiol and testosterone in runoV from agricultural fields that have received applications of poultry litter (Finlay‐Moore et al., 2000; Nichols et al., 1997, 1998; Shore et al., 1995). In all these studies, significant amounts of 17b‐estradiol and/or testosterone were observed in runoV or drainage waters. Finlay‐Moore et al. (2000) used an enzyme‐linked immunosorbent assay (ELISA) to estimate 17b‐estradiol and testosterone concentrations in both runoV water and soil

L. S. LEE ET AL.

28

from a cattle‐grazed grassland amended with poultry litter. RunoV concentrations of estradiol and testosterone ranged from 20 to 2330 ng liter
1 and from 10 to 1830 ng liter
1, respectively. Soil concentrations of estradiol and testosterone after poultry litter application were as high as 675 and 165 ng kg
1, respectively, with soil levels of testosterone in fields with grazing cattle being higher compared to control fields (Finlay‐Moore et al., 2000). In both the Finlay‐Moore et al. (2000) and Nichols et al. (1997) studies, runoV concentrations appeared strongly dependent on the litter application rates and time elapsed after application. Amending poultry litter with alum, reduced concentrations and mass loss of 17b‐estradiol, which was hypothesized to be due to alum‐induced decreases in pH and soluble organic compounds (Nichols et al., 1997).

VI.

ECOLOGICAL AND HUMAN HEALTH EFFECTS A. ANTIMICROBIAL TOXICITY

In the past few years, several studies have examined whether antimicrobial residues in the environment have the potential to negatively impact nontarget organisms or promote the emergence of resistant bacteria. With the exception of monensin, ivermectin, and doramectin, the highest antimicrobial concentrations measured in wastewater treatment plant eZuent, surface waters, soils, or even animal manure and lagoon eZuent (typically in the mg liter
1 or mg kg
1 range) are more than an order of magnitude lower than the lowest observable adverse eVect levels (LOAEL) for routinely tested organisms (Boxall et al., 2002; De Liguoro et al., 2003; Halling‐Sørensen et al., 2005; Kinney et al., 2006; Kolpin et al., 2002; Miao et al., 2004; Pierini et al., 2004; Sengeløva et al., 2003). However, a few aquatic and terrestrial organisms have been identified that may potentially be aVected by certain antimicrobials under worst‐case scenarios such as direct exposure to manure, lagoon eZuent, or highly contaminated soil pore water. Several studies have found that bacteria are typically the organisms most aVected by antimicrobials (Halling‐Sørensen et al., 2000, 2002; Holten Lu¨tzhøft et al., 1999; Kumar et al., 2005). Robinson et al. (2005) reported low EC50 values (effective concentration halfway between baseline and maximum that provokes a response) for the cyanobacteria Microcystis aeruginosa (0.017– 1.96 mg liter
1) exposed to fluoroquinolones. Microbially mediated processes (e.g., soil dehydrogenase and phosphatase activity, nitrification, organic matter decomposition) have also responded negatively to antimicrobial exposure (Boleas et al., 2005; Halling‐Sørensen, 2001; Klaver and Matthews, 1994; Sommer and Bibby, 2002). In contrast to these findings, Isidori et al. (2005) found that relatively high antimicrobial concentrations were required to aVect the luminescence of

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

29

Vibrio fischeri bacteria (EC50: 23.3 to >100 mg liter
1), or to achieve mutagenic eVects in Salmonella typhimurium (0.31 to >100 mg liter
1) or genotoxic eVects in Escherichia coli (6.25 to >100 mg liter
1). The most sensitive species identified by Isidori et al. (2005) was the freshwater green alga Pseudokirchneriella subcapitata (EC50: 0.002–1.44 mg liter
1), whereas tests on this species over the same time frame (72 h) by Robinson et al. (2005) yielded EC50 values that were substantially higher (1.1–22.7 mg liter
1). Both studies used standard test procedures although methods diVered. Thus, it is unclear as to whether apparent discrepancies between results are due to varying species sensitivities to diVerent antimicrobials or experimental artifacts. Other potentially sensitive organisms that were identified were Lemna minor (duckweed; EC50: 0.051–2.47 mg liter
1), Brachionus calyciflorus (rotifer; EC50: 0.68–12.21 mg liter
1), and Ceriodaphnia dubia (crustacean cladocera; EC50: 0.18–8.16 mg liter
1). Multispecies studies conducted on soil organisms, such as earthworms, springtails, and plant seedlings, also show that LOAEL are typically higher than environmental concentrations (Baguer et al., 2000; Boleas et al., 2005). However, undesirable eVects at relatively low concentrations have been reported for some plants. Boleas et al. (2005) examined plant growth responses (biomass production and stem elongation) in the presence of sulfachloropyridazine and found that at a concentration of 0.01 mg kg
1 reduced elongation of Triticum aestivum, and 1 mg kg
1 reduced biomass production of Vicia sativa. The ability of plants to take up antimicrobials and potentially transfer residues to higher trophic levels has also been demonstrated (Boxall et al., 2006). Lettuce and carrots grown in antimicrobial contaminated soil accumulated small quantities of florfenicol, trimethoprim, and enrofloxacin. However, the estimated potential daily intake for a human consuming these plants was in the order of mg day
1, which is not expected to pose a health threat.

B. DEVELOPMENT

OF

ANTIMICROBIAL‐RESISTANT BACTERIA

In addition to apprehensions over potential detrimental eVects to susceptible nontarget organisms, the development of resistant human pathogens is of significant concern. Bacterial resistance toward antimicrobials can develop through either genetic mutation (spontaneous change in genome) or more commonly through the transfer of genetic material from donor bacteria to acceptor bacteria through protein tunnel‐mediated transfer by conjugative plasmids or transposons. There is considerable evidence that the use of antimicrobials in large‐scale livestock agriculture and aquaculture operations selects for resistant strains such as zoonotic enteropathogens (e.g., Salmonella spp.) and commensal bacteria (enterococci) (McEwen and Fedorka‐Cray, 2002; Wegener, 2003). Usually, these bacteria are also resistant to important human

30

L. S. LEE ET AL.

medicines, since antimicrobials used in food animals are often the same as or closely related to those used as human drugs. This has raised concerns over the transfer of resistance vectors to human bacterial pathogens, which would compromise our ability to treat human infections. Opinions diverge over whether the evidence supporting the potential for transmission to human pathogens is established. A review of this ongoing and vigorous scientific debate is beyond the scope of this article (Phillips et al., 2004; Turnidge, 2004). Here, we will focus on the most recent findings regarding the role that antimicrobial residues in the environment may have toward fostering resistant bacteria. A handful of studies have evaluated the amplification and persistence of antimicrobial‐resistant genetic elements in soils at the laboratory and field scale (Burgos et al., 2005; Rysz and Alvarez, 2004; Sengeløva et al., 2003). Results show that current manure‐management practices add resistant intestinal bacteria to soil. For example, a study that isolated enteric bacteria in soils collected from dairy farm corrals found these bacteria to be multidrug resistant (Burgos et al., 2005). Minimal inhibitory concentrations (MICs) ranged from 6 to >50 mg liter
1 for chloramphenicol, 2–8 mg liter
1 for nalidixic acid, 25 to >300 mg liter
1 for penicillin G, and 1 to >80 mg liter
1 for tetracycline. Similar findings were reported in a study that monitored resistance to tetracycline, macrolides, and streptomycin in bacteria from farmland treated with pig manure slurry (Sengeløva et al., 2003). Only tetracycline‐resistant bacteria were elevated after manure amendment, with higher manure loads yielding higher frequencies of resistance. However, the occurrence of resistance vectors declined to control levels during the 8‐month study period. Since the tetracycline concentrations in the soils (42–698 mg liter
1) were substantially lower than the MIC range (4–12.5 mg liter
1), the soil presented no selective pressure in favor of resistant organisms. A laboratory column study by Rysz and Alvarez (2004) also showed that although exposure to tetracycline (50 mg liter
1) increased the frequency of resistance in soil bacteria, control levels were resumed 1 month after tetracycline exposure was terminated. Therefore, although resistance vectors are released into agricultural soils by manure additions, the processes of dilution, sorption, and degradation substantially reduce the concentrations of antimicrobial residues so that resistance appears to attenuate naturally. Several studies have reported positive correlations between antimicrobial use at inland fish farms and bacterial resistance levels in and around these farms (Bjorklund et al., 1991; DePaola et al., 1988; Guardabassi et al., 2000; McPhearson et al., 1991; Schmidt et al., 2000; Spanggaard et al., 1993). For example, Chelossi et al. (2003) found significantly higher incidence of bacterial resistance in sediments under a fish farm relative to controls. Husevaag et al. (1991) found higher levels of oxytetracycline‐resistant bacteria in the sediments at abandoned fish farms compared to sediment samples taken

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

31

200–250 m away from the aquaculture sites. Pathogenic bacteria resistant to oxytetracycline have also been isolated from the intestines of treated fish and fish farm sediments (Bjorklund et al., 1991) as well as the intestines of wild fish (Bjorklund et al., 1990). At an integrated fish farm in southeast Asia, analyses of the intestinal bacteria of fish collected from ponds receiving chicken and pig manure revealed significantly higher resistance to chloramphenicol, ciprofloxacin, erythromycin, oxytetracycline, streptomycin, and sulfamethoxazole compared to those that were sampled from ponds isolated from animal production (Petersen and Dalsgaard, 2003). An investigation of the susceptibility of a number of aquatic bacterial isolates, including two species of major fish pathogens, taken from the inlets, outlets, and pond water of four Danish rainbow trout Oncorhynchus mykiss farms showed that increased resistance to certain antimicrobials, particularly oxytetracycline, had developed in some bacteria isolates from the outlets and pond waters (Schmidt et al., 2000). The high incidence of resistance to oxytetracycline was not expected since its use at fish farms in the area had dropped considerably during the few years prior to the study. There was no clear relationship between resistance levels and periods of antimicrobial treatment, suggesting that the resistance traits persisted during periods of nontreatment (Schmidt et al., 2000). Research has shown that bacteria can possess a wide range of resistance mechanisms in the absence of an anthropogenically introduced selective pressure. Work on fecal coliforms, enterococci, and pseudomonads collected from wastewater treatment plants and groundwater wells found that Pseudomonads from nonpolluted groundwater were among the most resistant isolates (Gallert et al., 2005). Additional evidence was provided by a study on 480 spore‐forming microbial isolated from soils (D’Costa et al., 2006). Every isolate examined was resistant to at least six to eight antimicrobial agents, and several resistance mechanisms had never been characterized before.

C.

HORMONE‐INDUCED ENDOCRINE DISRUPTION

Alterations in reproductive physiology and endocrinology have been extensively documented in aquatic organisms exposed to EDCs. The list of chemicals that are known to aVect the endocrine and reproductive systems of invertebrate and vertebrate animals is extensive and includes heavy metals, pesticides, persistent halogenated pollutants, and synthetic and natural steroids found in complex eZuents released from sewage treatment plants (see Gross et al., 2002; Sumpter, 2005; and Falconer et al., 2006 for reviews on this topic). Comprehensive chemical analyses of these eZuents have identified several estrogenically active compounds including naturally occurring

32

L. S. LEE ET AL.

(estrone, 17b‐estradiol, estriol) and very potent synthetic steroidal estrogens (17a‐ethynyl estradiol) released by women using birth control. In contrast, relatively little is known about the environmental impact of hormone‐containing discharges (eZuents and manures) released from CAFOs. This is despite the fact that it has been known for quite some time that animal wastes may be significant sources of naturally occurring and synthetic sex steroids. However, from information gained from other waste streams containing EDCs, it follows that exposure to animal wastes has the potential to elicit significant reproductive eVects. The following will focus on eVects reported in aquatic organisms, mostly fish, in response to exposure to hormones known to be present in wastes from CAFOs. Unless noted, the eVects reported in Sections VI.C.1–3 were derived from laboratory‐controlled exposures.

1.

Estrogens

As already discussed, animal wastes contain appreciable amounts of natural steroidal estrogen hormones, particularly 17b‐estradiol and estrone. 17b‐Estradiol contamination of waterways is a concern because low part per trillion (10–100 ng liter
1) concentrations of these chemicals can adversely aVect the reproductive biology of aquatic fish and wildlife (Oberdorster and Cheek, 2001). Indeed, estrogens are among the most potent EDCs found in the environment, with estrogenic potencies typically three orders of magnitude higher than most other EDCs (Miyamoto and Klein, 1998). To our knowledge, only one field study has examined the relationship between manure‐borne estrogens from CAFOs and adverse eVects on aquatic organisms. Irwin et al. (2001) found an increase in concentrations of vitellogenin (an egg yolk precursor protein that is normally produced only by adult females) in female painted turtles (Chrysemys picta) sampled from ponds receiving runoV from beef cattle pastures. Concentrations of free 17b‐ estradiol in these ponds ranged from 0.05 to 1.8 ng liter
1 as measured by radioimmunoassay (RIA). No measurable increases of vitellogenin were observed in males. The authors speculated that additional vitellogenin production in female turtles may shift energy allocations away from growth and survival requirements in this species. There is an extensive literature collection on the eVects of estrogens on fish reproduction. EVects include induction of female‐specific genes and proteins, altered gonad development and expression of secondary sex characteristics, behavioral changes, and decreased spawning success. Literature on the eVects of estrogens on fish reproduction has been reviewed by Lai et al. (2002) so only a few examples will be presented here.

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

33

Induction of vitellogenin in male fish is considered a sensitive and quantitative measure of estrogen exposures, and dose–response relationships have been developed for fish exposed to estrone and 17b‐estradiol. For instance, concentrations of estrone or 17b‐estradiol in water as low as 30 ng liter
1 for 21 days can induce vitellogenin synthesis and abnormal testicular growth in male fathead minnows (Pimephales promelas) (Panter et al., 1998, 2000) and other fish species (Snyder et al., 2001; Thorpe et al., 2003). In another study, male eelpout (Zoarces viviparous) responded with an increase in vitellogenin production when injected with 17b‐estradiol (10–100 mg g
1) (Tyler et al., 1998). Induction of vitellogenin in male fish has been associated with reduced testicular growth and size (Jobling et al., 1996; Tyler et al., 1998; Van den Belt et al., 2001, 2002). Abnormal development of both ovary and testes has also been reported after exposure to estrogens. Exposure of EDCs during the period of sex diVerentiation can result in irreversible structural changes leading to altered reproductive output and permanent (irreversible) masculinisation or feminization. However, if exposures occur after gonads have been diVerentiated, these changes are usually reversible. For instance, eVects on sexual diVerentiation leading to partial feminization have been reported in fish larvae exposed to waterborne 17b‐estradiol concentrations ranging from 25 to 1000 ng liter
1, whereas complete sex reversals have been reported in fish larvae‐fed diets containing between 5 and 60 mg kg
1 of 17b‐estradiol (Bla´zquez et al., 1998; Gorshkov et al., 2004; Pandian and Sheela, 1995). In contrast, a similar exposure to sexually diVerentiated adult fish resulted in only transitory eVects on secondary sex characteristics and gonad histology (Bla´zquez et al., 1998; Miles‐Richardson et al., 1999). Exposure to estrogens can also lead to lower breeding success and altered spawning and fry development. Mature male goldfish (Carassius auratus) exposed to 17b‐estradiol via ingestion (1–100 mg g
1 food) and water (1–10 mg liter
1) for 28–74 days responded with severe reproductive changes such as altered sexual behavior and spawning (Bjerselius et al., 2001). Survival and growth of embryos of mummichog (Fundulus heteroclitus) were significantly reduced when reared in seawater containing 10
10 to 10
6 M 17b‐estradiol (Urushitani et al., 2002). In addition, bone malformations and skewed sex ratios were observed after hatching in these 17b‐estradiol‐ treated fry. In terms of synthetic estrogens, zeranol (or a‐zearalanol) is a b‐resorcylic acid lactone derived from the myco‐estrogen zearalanone that is used as an anabolic growth promoter in beef production (LeVers et al., 2001). The parent compound, zearalenone, is produced by fungi of the genus Fusarium, and it is known to have strong estrogenic eVects, leading to fertility disorders, and altered spermatogenesis, ovulation, and implantation in cattle and pigs (Conkova et al., 2003; Minervini et al., 2001). In rats, zeranol has

34

L. S. LEE ET AL.

also been associated with severe declines in ovarian function (Yuri et al., 2004). The estrogenic potency of zearalenone and its derivatives was compared to that of other estrogens through in vitro studies, using estrogen‐ dependent human breast cancer (MCF‐7) cells (Malekinejad et al., 2005). These studies found that the estrogenic potency of these compounds ranked in the following order: a‐zearalenol > a‐zearalanol > zearalenone > b‐zearalenol. Almost nothing is known about the in vivo toxicity of zeranol in fishes. However, from in vitro studies, it is known that zeranol is capable of binding to the estrogen receptors of rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) (Arukwe et al., 1999; Le Guevel and Pakdel, 2001). In addition to natural and synthetic estrogens, metabolites of phytoestrogens (e.g., formononetin, daidzein, and equol) have also been found in the urine of several farm animals (Axelson et al., 1984). It is well known that phytoestrogens can act as EDCs in fish, although with a much weaker potency compared to synthetic and natural estrogens (Burnison et al., 2003). An interesting note relates to the bioavailability of synthetic versus natural steroids. It is estimated that 98% of endogenous 17b‐estradiol is bound to proteins, especially serum hormone binding globulin (SBHG), resulting in only a small percentage being available to cells (Ben‐Rafael et al., 1986). However, zeranol and other exogenous growth‐promoting hormones exhibit limited or no binding to carrier proteins (Mastri et al., 1985; Nagel et al., 1998; Shrimanker et al., 1985). This is of great toxicological importance because it means that their potential potency is much larger than that suggested by their actual concentrations (up to 50 times).

2.

Androgens

Trenbolone acetate, which is administered to cattle via implants, releases the acetate form of this steroid into the bloodstream where it is hydrolyzed to produce the active form, 17b‐trenbolone. 17b‐Trenbolone is later epimerized to form 17a‐trenbolone. Both isomers are excreted by the treated animals, but the a form predominates over the b form by a ratio of about 10:1 (SchiVer et al., 2001). It is well known that 17b‐trenbolone acts as a potent agonist of mammalian androgen receptors, with a binding aYnity to the human androgen receptor comparable to dihydrotestosterone, and 20‐fold greater than 17a‐trenbolone (Bauer et al., 2000; Pottier et al., 1981; Wilson et al., 2002). 17b‐Trenbolone also binds in vivo to the androgen receptor of the fathead minnow with greater aYnity than testosterone (Ankley et al., 2003). In contrast to most androgens that are aromatized (i.e., converted to estrogens by cytochrome‐P450 aromatase enzymes or CYP19), 17b‐trenbolone is not aromatizable and thus has pure androgen

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

35

like qualities. Interestingly, 17b‐trenbolone is also capable of binding to fish estrogen receptors and inducing vitellogenin production in males (Ankley et al., 2003; Le Guevel and Pakdel, 2001). The mechanism by which trenbolone aVects vitellogenin synthesis is not clear, but it suggests significant cross talk between estrogen and androgen‐regulated gene expression mechanisms. Studies evaluating the toxicological eVects of TBA metabolites in aquatic organisms are limited. In aquaculture, TBA administered at pharmacological doses (25 mg kg
1) has been used to revert sexes and produce 100% phenotypic male populations (Arslan and Phelps, 2004; Bart et al., 2003; Davis et al., 2000; Galbreath and Stocks, 1999; Galvez et al., 1996). Interference with normal development of reproductive tract and overall reproduction has also been reported in mammals treated with TBA (Moran et al., 1990). Adult fathead minnow females exposed to 17b‐trenbolone (>0.027 mg liter
1) for 21 days developed male secondary sex characteristics (dorsal nuptial tubercules) and had decreased fecundity, plasma vitellogenin, and sex steroid concentrations (Ankley et al., 2003). No eVects on fry or juvenile fish were reported at the concentrations tested. These reproductive eVects were later fitted into a predictive population model and used to determine projected population alterations (Miller and Ankley, 2004). The model predicted that continuous exposure of fathead minnow populations to 17b‐trenbolone concentrations 0.027 mg liter
1 would induce large population losses within 2 years leading to population extinction. In another study, a 28‐day exposure of mosquitofish (Gambusia aYnis) fry to 17b‐ trenbolone (1–10 mg liter
1) induced premature diVerentiation of spermatozoa in the testes and formation of ovotestis in females (Sone et al., 2005). In addition, much lower doses of 17b‐trenbolone (0.3 mg liter
1) resulted in the formation of male secondary sex characteristics (gonopodium‐like structure) in female fry. Exposure of zebrafish (Danio rerio) and Japanese medaka (Oryzias latipes) from 1 to 60 days posthatch to 50 ng liter
1 17b‐trenbolone ¨ rn et al., resulted in significant decreases in vitellogenin concentrations (O 2006). Masculinization was only observed in zebrafish, and both species responded with an increase in the percentage of testes occupied with mature spermatozoa. Data from competitive binding assays using mammalian androgen receptors suggest that 17a‐trenbolone would be expected to be about an order of magnitude less potent than the b isomers (Bauer et al., 2000). However, a study with fathead minnows reported similar potencies for eVects on fecundity and masculinization of adult females for 17a‐trenbolone compared to the b form with an EC50 for fecundity inhibition of 0.011 mg liter
1 versus 0.018 mg liter
1 for the a and b forms, respectively (Jensen et al., 2006). Overall, eVects of a‐trenbolone on the reproductive system of the fish were qualitatively and quantitatively quite similar to those caused by b‐trenbolone. This similarity might arise in part from the fact that a substantial amount of

36

L. S. LEE ET AL.

a‐trenbolone appeared to be converted to b‐trenbolone by the fish; although the authors hypothesized that they acted via similar toxic mode(s) of action. Currently, a single field study has been conducted on the potential androgenic eVects of CAFO eZuents (Orlando et al., 2004). These authors found that wild fathead minnows collected below a cattle feedlot exhibited altered reproductive biology, including decreased testosterone synthesis and testis size in males, and decreased 17b‐estradiol–testosterone ratios in females. The chemical(s) responsible for these changes were not elucidated, but the authors hypothesized that androgenic substances were at least in part responsible due to potent androgenic responses observed in their transfected human androgen receptor in vitro assays (Orlando et al., 2004). 3.

Progestagens

Progesterone, the only natural progestagen, is naturally occurring in the body and produced from cholesterol (Hancock et al., 1991; Lange et al., 2002). Progesterone metabolizes to testosterone (Hancock et al., 1991), thus it is often used in combination with estradiol in cattle growth implants. Melengestrol acetate is an orally active progestin (synthetic progestagen) used for estrus synchronization and/or induction in cattle. It is also marketed as a feed additive for feedlot heifers to improve feed eYciency and rate of weight gain (SchiVer et al., 2001). MGA exerts both progestional and glucocorticoid activity. Its progestional activity is about 125 times greater than that of progesterone as measured by estrus cycle inhibition in cattle, and its anabolic action is assumed to be due to stimulation of endogenous 17b‐estradiol (Hageleit et al., 2000; SchiVer et al., 2001). Medroxyprogesterone is another progestin used in veterinary medicine as an estrus regulator (Cavestany et al., 2003). There are no published studies on the eVects of synthetic progestins on fish or other aquatic organisms.

VII. ANALYTICAL METHODS A. METHOD DEVELOPMENT Testing for very low residual concentrations of antimicrobials and hormones in exceedingly complex environmental samples is a complicated endeavor. Animal excrement combined with other waste products (e.g., bedding and feed) may contain ammonium, acetate, bicarbonate, fatty acids, phenols, metal ions, straw, sawdust, and wood shavings. These compounds may result in multiple interfering coextractants that make direct quantification diYcult to impossible for environmental samples (Ferguson et al., 1998). It is essential

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

37

that extraction and cleanup methods eliminate potential interferences as much as possible. Therefore, up to two‐thirds of the time spent obtaining concentration data for antimicrobials and hormones is devoted to sample extraction and preparation. This step is crucial in developing reproducible methods that optimize time, resources, and reduce detection errors (Stolker et al., 1996). After extraction and clean up, samples are typically concentrated prior to the final steps in quantifying analyte concentrations. For both liquid and solid samples, the contaminant of interest is typically extracted from an environmental matrix with a solvent. The solvent should be chosen so that it suYciently extracts the analyte, while reducing the amount of coextracted material. The choice of solvent also depends on the sample matrix and the analytical technique used for detection. Compounding the problem is the fact that it is unlikely that any one extraction method will be successful for all analytes of interest. Selecting an extraction solvent or process requires knowledge of various properties of the target analyte such as aqueous solubility, hydrophobicity, and pKa, as well as the nature of the sample matrix. For solid samples, traditional methods include Soxhlet extraction, batch solvent extraction, and ultrasonic‐assisted extraction. Advanced extraction techniques such as accelerated solvent extraction (ASE) and supercritical fluid extraction (SFE) have been investigated as a way to increase eYciency and minimize time spent on sample preparation. In ASE, the extraction solvent is pressurized and heated before being cycled through an extraction cell in either a static or dynamic mode. In SFE, CO2 is pressurized and heated to the point where the phase transition for supercritical state is reached. SFE cycles supercritical CO2 through the sample cell and deposits the extracted compounds either on an adsorbent or into solvent. SFE is best suited for hydrophobic analytes and has been investigated as a means of extracting analytes from matrices without using solvent. For liquid samples, solid phase extraction (SPE) or liquid–liquid extraction are the preferred methods (Baronti et al., 2000; Gomes et al., 2005; Lagana et al., 2001). Samples containing large amounts of suspended particles are typically centrifuged prior to extraction, and the particulates and liquid portions extracted separately. Liquid and liquid–solid slurries can also be extracted with a water immiscible solvent provided that the analyte partitions into the solvent phase. After extraction of the analyte, a cleanup step may be necessary to remove coextracted material that can interfere with chromatographic separation or suppress or enhance signal detection. Sample cleanup is usually done using some type of sorbent material that either retains the desired analyte while other unwanted compounds are allowed to pass through (after which the analyte is washed from the sorbent using an appropriate solvent) or sorbs the unwanted material while the desired analyte is allowed to pass through.

38

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After sample cleanup, a concentration step is often employed where the solvent containing the sample is evaporated to a small volume. Sample concentration for aqueous samples is often performed simultaneously with sample cleanup by using a sorbent material to separate the analyte from a large volume of aqueous sample after which the analyte is eluted from the sorbent with a small amount of solvent. Upon completion of these steps, the sample is ready for analysis. Analysis of organic compounds such as hormones and antimicrobials in environmental samples typically involves gas or liquid chromatographic (GC, LC) separation coupled to a detector with the detector of choice being a mass spectrometer (MS). Class‐specific ELISA kits are another common detection method for the determination of hormones in environmental samples (Huang and Sedlak, 2001; Nunes et al., 1998) and for detection of tetracyclines (Aga et al., 2003).

B. ANTIMICROBIALS The extraction, analyte clean up or isolation, and detection of several major classes of antimicrobials used heavily in livestock production are briefly summarized in this section. Specific details on selected examples of extractants, clean up methods, and analytical details for several pharmaceutical classes in environmental and food samples have been tabulated by Thiele‐Bruhn (2003).

1.

Tetracyclines

Tetracyclines, including oxytetracycline, chlortetracycline, and tetracycline, are amphoteric, with a partially conjugated four‐ring structure and a carboxyamide functional group. They are soluble in polar and moderately polar solvents, and form strong complexes with multivalent cations. Using a variety of solvents and solvent–buVer combinations, tetracyclines have been successfully extracted from many diverse matrices, including milk, animal organs, egg, meat, water, soil, sludge, and manure (see Table III for specific citations). The addition of ethylenediaminetetraacetic acid (EDTA) to the extraction solvent prevents these antimicrobials from chelating metal ions in solutions and from sorbing irreversibly to glassware (Blackwell et al., 2004a,b; Croubles et al., 1997; Fedeniuk and Shand, 1998; Hamscher et al., 2002; Hirsch et al., 1999; Sczesny et al., 2003; Zhu et al., 2001). Metal chelate aYnity chromatography has also been used to purify tetracyclines from extracts, relying on the strong aYnity of tetracyclines for metals (Croubles et al., 1997). Extraction of tetracyclines from solid matrices has been accomplished using a variety of methods: sodium succinate buVer (pH 4.0) and methanol

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

39

Table III Citations to Extraction and Analysis of Common Human and Animal Antimicrobials and the Matrices from Which They Have Been Extracted Analytes Chlortetracycline

Doxycycline

Methacycline Minocycline Oxytetracycline

Tetracycline

Penicillin, cloxacillin Sulfachloropyridazine

Citation Carlson and Mabury (2006); Croubles et al. (1997); Furusawa (2002); Hamscher et al. (2002); Hirsch et al. (1999); Jacobsen et al. (2004); Kamel et al. (1999); Lindsey et al. (2001); Reverte et al. (2003); Sassman et al. (2005a); Sczesny et al. (2003); Zhu et al. (2001) Croubles et al. (1997); Fernandez et al. (2004); Furusawa (2002); Hirsch et al. (1999); Lindsey et al. (2001); Reverte et al. (2003) Kamel et al. (1999) Kamel et al. (1999); Lindsey et al. (2001) Blackwell et al. (2004a,b); Croubles et al. (1997); Furusawa (2002); Halling‐Sørensen et al. (2003); Hamscher et al. (2002); Hirsch et al. (1999); Jacobsen et al. (2004); Kamel et al. (1999); Lindsey et al. (2001); Reverte et al. (2003); Sassman et al. (2005a); Sczesny et al. (2003); Zhu et al. (2001) Croubles et al. (1997); Furusawa (2002); Hamscher et al. (2002); Hirsch et al. (1999); Kamel et al. (1999); Lindsey et al. (2001); Reverte et al. (2003); Sassman et al. (2005); Sczesny et al. (2003); Zhu et al. (2001) Hirsch et al. (1999) Blackwell et al. (2004a,b); Cavaliere et al. (2003); Lindsey et al. (2001)

Matrix Milk, egg, meat, soil, water, wastewater, manure

Milk, egg, meat, manure, water, wastewater

Water Water Milk, egg, meat, soil, water, manure, wastewater

Milk, egg, meat, soil, water, wastewater, manure

Water Milk, egg, water, manure, soil

(continued)

40

L. S. LEE ET AL. Table III (continued)

Analytes Sulfadiazine

Sulfadimethoxine

Sulfaguanidine Sulfamerazine Sulfameter Sulfamethazine

Sulfamethizole Sulfamethoxazole

Sulfamethoxypyridazine, sulfamonomethoxine, sulfanilamide Sulfapyridine (often used as IS) Sulfathiazole

Trimethoprim

Alklomide, nitromide, zoalene

Citation Cavaliere et al. (2003); Haller et al. (2002); Jacobsen et al. (2004); Kim and Lee (2002); Kreuzig and Holtge (2005); LoZer and Ternes (2003); Wolters and SteVens (2005) Cavaliere et al. (2003); Haller et al. (2002); Kim and Lee (2002); Wang and Yates (2006) Cavaliere et al. (2003); Haller et al. (2002) Cavaliere et al. (2003); Lindsey et al. (2001) Cavaliere et al. (2003) Cavaliere et al. (2003); Haller et al. (2002); Hirsch et al. (1999); Kim and Lee (2002); Lindsey et al. (2001); LoZer and Ternes (2003); Renew and Huang (2004) Cavaliere et al. (2003); Kim and Lee (2002) Cavaliere et al. (2003); Haller et al. (2002); Hirsch et al. (1999); Lindsey et al. (2001); LoZer and Ternes (2003); Renew and Huang (2004) Cavaliere et al. (2003)

Cavaliere et al. (2003); Kim and Lee (2002); LoZer and Ternes (2003) Cavaliere et al. (2003); Haller et al. (2002); Kim and Lee (2002); Lindsey et al. (2001) Haller et al. (2002); Hirsch et al. (1999); LoZer and Ternes (2003); Renew and Huang (2004) Parks et al. (1995)

Matrix Milk, egg, sediments, manure, soil, meat

Milk, egg, manure, meat, soil

Milk, egg, manure Milk, egg, water Milk, egg Milk, egg, sediments, manure, wastewater, water, meat Milk, egg, meat Milk, egg, sediments, manure, wastewater, water Milk, egg

Milk, egg, sediments, meat Milk, egg, manure, water, meat

Sediment, manure, wastewater, water Liver

(continued)

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

41

Table III (continued) Analytes Erythromycin

Roxithromycin Tylosin

Albendazole, cambendazole, fenbendazole, flubendazole, mebendazole, netobimin, oxfendazole, oxibendazole, thiabendazole, triclabendazole Cinoxacin Ciprofloxacin

Danofloxacin

Enoxacin Enrofloxacin

Flumequine

Levofloxacin Marbofloxacin Nalidixic acid

Citation Dehouck et al. (2003); Hirsch et al. (1999); Jacobsen et al. (2004); LoZer and Ternes (2003); Yang and Carlson (2004) Schluesener et al. (2006); Yang and Carlson (2004) Blackwell et al. (2004a,b); Carlson and Mabury (2006); Hamscher et al. (2002); Jacobsen et al. (2004); Yang and Carlson (2004) Danaher et al. (2003)

McCourt et al. (2003); van Vyncht et al. (2002) Golet et al. (2002, 2003); Johnston et al. (2002); McCourt et al. (2003); Morales‐Munoz et al. (2004); Neckel et al. (2002); Renew and Huang (2004); Reverte et al. (2003); van Vyncht et al. (2002) Johnston et al. (2002); McCourt et al. (2003); van Vyncht et al. (2002) McCourt et al. (2003); van Vyncht et al. (2002) Johnston et al. (2002); McCourt et al. (2003); Renew and Huang (2004); Reverte et al. (2003); van Vyncht et al. (2002) Johnston et al. (2002); Lutzhoft et al. (2000); McCourt et al. (2003); van Vyncht et al. (2002) Neckel et al. (2002) McCourt et al. (2003); van Vyncht et al. (2002) van Vyncht et al. (2002)

Matrix Sediment, soil, wastewater, water

Wastewater, swine manure Soil, water, wastewater, manure

Liver

Kidney, water Plasma, kidney, fish, sewage sludge, soil, wastewater, water

Kidney, fish, water

Kidney, water Kidney, fish, wastewater, water

Kidney, fish, water

Plasma Kidney, water Kidney (continued)

42

L. S. LEE ET AL. Table III (continued)

Analytes Norfloxacin

Ofloxacin

Orbifloxacin Oxolinic acid

Piromidic acid Sarafloxacin Monensin Salinomycin, tiamulin

Citation Golet et al. (2002, 2003); McCourt et al. (2003); Morales‐Munoz et al. (2004); Renew and Huang (2004); van Vyncht et al. (2002) McCourt et al. (2003); Renew and Huang (2004); van Vyncht et al. (2002) Johnston et al. (2002) Johnston et al. (2002); Lutzhoft et al. (2000); van Vyncht et al. (2002) Johnston et al. (2002) Johnston et al. (2002); Lutzhoft et al. (2000) Carlson and Mabury (2006) Schluesener et al. (2006)

Matrix Kidney, sewage sludge, soil, wastewater, water Kidney, wastewater, water Fish Kidney, fish, water

Fish Fish, water Soil Swine manure

(Croubles et al., 1997); oxalic acid–sodium chloride in ethanol–water (Sassman and Lee, 2005a); citrate buVer and acetonitrile (pH 5) (Sczesny et al., 2003); citrate buVer and ethyl acetate (Hamscher et al., 2002); McIlvaine buVer, methanol, and EDTA (Blackwell et al., 2004a,b). In addition, ASE has been employed using citrate buVer and methanol at 1500 psi (Jacobsen et al., 2004). Several types of SPE materials have been used to isolate and concentrate tetracyclines, including traditional hydrophobic phases such as C8 and C18 (Furusawa, 2002; Zhu et al., 2001) and styrene divinylbenzene (SDB) (Hamscher et al., 2002). However, isolation techniques based on hydrophobic interactions tend to give low recoveries for tetracyclines due to irreversible sorption to exposed silanol groups (Croubles et al., 1997; Lindsey et al., 2001). Solid phase extraction conditions for C8, C18, and SDB cartridges or disks include preconditioning and elution with water only (Furusawa, 2002), preconditioning with a methanol–citric acid buVer and elution with methanol (Hamscher et al., 2002), and preconditioning with sodium phosphate dibasic– citric acid buVer–EDTA disodium and elution with oxalic acid–methanol (Zhu et al., 2001). Another option for the isolation of tetracyclines involves exploiting the ability of tetracyclines to form ion–ion and ion–dipole interactions by using ion exchange cartridges or disks. These phases include strong cation exchange (e.g., IsoluteÒ SCX, Biotage AB, Uppsala, Sweden) (Diaz‐Cruz et al., 2003) and strong anion exchange (e.g., IsoluteÒ ENVþ, Biotage AB, Uppsala, Sweden) (Blackwell et al., 2004a). In addition, a combination of

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

43

SAX and OasisÒ hydrophilic–lipophilic balance (HLB) cartridges consisting of a poly(divinylbenzene‐co‐N‐pyrrolidone) sorbent (Waters, Milford, MA) used in sequence eliminates interferences by retaining coextractants on the anion exchange phase while retaining the analytes of interest on the OasisÒ HLB phase (Blackwell et al., 2004a; Jacobsen et al., 2004). Preconditioning and elution solvents are similar to those used in C8, C18, or SDB and consist primarily of methanol, phosphate buVers, and EDTA. Tetracyclines undergo a reversible epimerization in the pH range of 2–6 to form 4‐epi‐tetracyclines (McCormick et al., 1957). Epimerization is promoted by the presence of anions such as formate, acetate, citrate, oxalate, and phosphate. The 4‐epi‐tetracyclines have been reported to exhibit greater water solubility and decreased antibacterial activity (Halling‐Sørensen et al., 2002). Most procedures for extraction and analysis of tetracyclines do not attempt to separately quantify tetracyclines and 4‐epi‐tetracyclines. This is because for eYcient extraction of tetracyclines from environmental matrices, solutions that promote epimer conversion must be used. However, some work attempting to deal with isomerization and degradation of tetracyclines in various matrices has been done. Halling‐Sørensen et al. (2003) examined the abiotic degradation pathways of oxytetracyclines in soil interstitial water. Because no extraction was necessary, and no salts were used in the LC/MS mobile phase, the possibility of epimer conversion was minimized. Analysis of tetracyclines using this kind of mobile phase has only become possible with the recent development of chromatographic columns manufactured using ultra high purity silica, polar‐embedded functionality, and polymeric sorbents. In the past, it was always necessary to use a chelating agent such as EDTA to block the strong interaction of tetracyclines with metal impurities present in the column. Tetracyclines are usually separated using a reverse phase column (either C8 or C18) and detected with either UV‐Vis/fluorescence (Blackwell et al., 2004a,b; Croubles et al., 1997; Furusawa, 2002; Reverte et al., 2003; Sassman and Lee, 2005a) or LC/MS as documented in several published methods (Halling‐Sørensen et al., 2003; Hamscher et al., 2002; Hirsch et al., 1999; Jacobsen et al., 2004; Kamel et al., 1999; Kennedy et al., 1998; Lindsey et al., 2001; Sczesny et al., 2003; Zhu et al., 2001). Ionization for LC/MS systems is generally achieved with positive mode electrospray ionization (ESI). Coupling of LC and MS has several advantages over traditional high performance LC (HPLC) detectors, including lower detection limits and enhanced compound specificity to eliminate interferences from coextractants. In addition, the growing popularity of LC/MS/MS systems allows for even more precise identification of unknown analytes. Detection limits for tetracyclines using the above methods tend to be in the low ppb range. Actual recoveries of tetracyclines vary greatly from matrix to matrix, with matrices that are abundant in clay and organic material yielding

44

L. S. LEE ET AL.

lower recoveries. The most commonly reported problem in the analysis of tetracyclines in environmental samples is matrix complexity, which make external calibration diYcult (Lindsey et al., 2001). For this reason, the use of an internal standard is often implemented. Typical internal standards for tetracycline analysis include other members of the tetracycline family, which are not likely to be found in environmental samples such as methacycline and minocycline. Aga et al. (2003) used a tetracycline ELISA kit (R‐Biopharm GmbH, Darmstadt, Germany) to screen for tetracyclines in manure samples from hog lagoons and cattle feedlots, track the decline of tetracyclines over a 28‐ day period, and evaluate column eZuent samples in a tetracycline leaching study. The ELISA test was able to detect the epimers of tetracylines and the corresponding hydration by‐products. LC/MS confirmation analysis was performed on one swine manure slurry in which tetracycline concentrations were high and a more dilute lagoon water sample. LC/MS analysis resulted in substantially lower concentrations of total tetracylines in the manure slurry compared to that estimated by ELISAs (6700 ppb vs 20,000 ppb), whereas comparable results were obtained for waste lagoon samples (11 ppb for LC/MS vs 9 ppb for ELISA). Although ELISA tests are much less labor intensive than sample preparation for LC/MS, interferences such as dissolved organic matter, which was likely high in the manure slurry, can yield artifactually high values.

2.

Sulfonamides

Several members of the sulfonamide family of antimicrobials are registered for veterinary use in the United States. Of these, sulfamethazine is the most prevalent. All sulfonamide antimicrobials contain a sulfur dioxide and nitrogen functional group directly linked to a benzene ring. Sulfonamides are negatively charged at neutral pH with pKa1 values ranging from 5.4 to 7.5 and pKa2 values around 2.5, which tend to make them relatively water soluble (Lindsey et al., 2001). Sulfonamides have been extracted from meat, eggs, manures, soil, sediment, water, and wastewater (Table III). Extraction methods for sulfonamides primarily involve some type of sequential solvent extraction with methanol, acetone, and ethyl acetate (LoZer and Ternes, 2003); increasing the pH to 9 and adding sodium chloride/ethyl acetate (Haller et al., 2002); combinations of multiple extraction solvents such as methanol, EDTA, and McIlvaine buVer (pH 7) to eliminate interferences from other analytes of interest (Blackwell et al., 2004a,b); and acetonitrile/sodium phosphate (Kim and Lee, 2002). Modern extraction techniques such as ASE and SFE have also been utilized (Jacobsen et al., 2004; Stolker et al., 1996). Sulfonamides are often purified after extraction with SPE

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

45

cartridges or disks containing a variety of phases such as LiChrolute EN (LoZer and Ternes, 2003), OasisÒ HLB (Blackwell et al., 2004a,b; Lindsey et al., 2001; Renew and Huang, 2004), C18 (Blackwell et al., 2004a,b), SAX (Blackwell et al., 2004a,b), and SAX‐HLB (Blackwell et al., 2004a,b; Jacobsen et al., 2004). Separation and detection methods for sulphonimides are similar to those cited for tetracyclines and generally involve either a C8 (Lindsey et al., 2001) or C18 column with UV/Vis or fluorescence detection using fluorescamine as a derivatization agent (Blackwell et al., 2004a,b) or MS detection (Ashton et al., 2004; Blackwell et al., 2004a,b; Cavaliere et al., 2003; Haller et al., 2002; Hirsch et al., 1999; Jacobsen et al., 2004; Kim and Lee, 2002; LoZer and Ternes, 2003; Renew and Huang, 2004). LC/MS coupled methods are typically performed using positive mode ESI. However, some compounds, such as sulfadimethoxine and sulfamethoxazole, are better detected in the negative mode (Haller et al., 2002). In addition, Kim and Lee (2002) reported atmospheric pressure chemical ionization (APCI) as a more eVective ionization source than ESI with respect to separation eYciency and detection sensitivity. In general, the detection limits for the methods above are in the low ppb range, with higher detection limits for more complex matrices (e.g., egg, milk, manure) and when more than one analyte class is being evaluated (Blackwell et al., 2004a,b; Cavaliere et al., 2003).

3. Quinolones/Fluoroquinolones Quinolones and the newer fluoroquinolones, including enrofloxacin and sarafloxacin, contain a central benzene ring connected to a nitrated phenol, and have pKa1 values between 5.6 and 6.6 and pKa2 values from 7.7 to 8.6 (except for flumequine and cinoxacin) (McCourt et al., 2003). Van Vyncht et al. (2002) investigated the application of several SPE solid‐phases for the extraction and clean up of 11 quinolones. However, due to diVerences in the pKa values of the analytes, no single solid‐phase could be employed to quantitatively recover all 11. Extraction of quinolones from solid matrices (Table III), including kidney, fish and seafood, sediments, soil, and sludge, have been accomplished mainly through solvent extraction. However, other extraction techniques exist such as ASE and microwave‐assisted extraction. In ASE, acetonitrile and acetic acid were used as the extracting solvent under 100  C and 100 bar (Golet et al., 2002, 2003). Microwave‐assisted extraction was performed using water (Morales‐Munoz et al., 2004). Sample clean up using SPE cartridges has included mixed phase cation exchange cartridges (e.g., SDB‐RPS and MPC‐SD, 3M Empore, St. Paul, MN) (van Vyncht et al., 2002; Golet et al., 2002); anion exchange

46

L. S. LEE ET AL.

(e.g., Sep‐Pack, Waters, Milford, MA) (van Vyncht et al., 2002); Supelclean ENVI Chrom P cartridge (Supelco, Bellefonte, PA) followed by AG MP‐1 resin (Bio‐Rad, Hercules, CA) (Johnston et al., 2002); OasisÒ HLB (Golet et al., 2001; Reverte et al., 2003); and a strong anion exchange cartridge (IsoluteÒ SCX, Biotage AB, Uppsala, Sweden) with OasisÒ HLB (Renew and Huang, 2004). In an examination of several SPE phases, the mixed mode C8/cation exchange phase SDB‐RPS resulted in the best recoveries for the 11 fluoroquinolones (van Vyncht et al., 2002). Detection of quinolones is accomplished using HPLC with a C18 column and either fluorescence detection (Golet et al., 2003; Neckel et al., 2002) or MS detection. Ionization of quinolones has been studied using both APCI and ESI (van Vyncht et al., 2002), but positive mode ESI remains the preferred method (Johnston et al., 2002; Renew and Huang, 2004; Reverte et al., 2003). Johnston et al. (2002) found that quinolones manufactured earlier were well retained on a C18 column, but newer fluoroquinolones were eluted too quickly and resulted in some overlap in the chromatography. Newer methods such as capillary electrophoresis (CE)/ESI/MS have also been successful depending on the initial sample matrix (McCourt et al., 2003).

C. HORMONES A summary of citations for extraction, analyte isolation, and detection methods for several hormones and a few structurally related endocrine disrupting compounds is presented in Table IV along with the matrices from which they have been extracted. Methanol is the most commonly used solvent for hormone extraction from solid animal wastes and soils, although other solvents including acetone, ethyl acetate, toluene, tert‐ butylmethyl ether, and hexane have also been used (Gomes et al., 2004; Hanselman et al., 2006; Korner et al., 2000; Lagana et al., 2000; Ternes et al., 2002; Lorenzen et al., 2004). Examples of more advanced extraction technologies that have been successful include ASE for estrone, 17b‐estradiol, estriol, and progesterone from sediment samples using an acetone:methanol mixture at 75  C and 1500 psi (Cespedes et al., 2004), and SFE for trenbolone, testosterone, zeranol, teranol, or zearalanone (Launay et al., 2004; Stolker et al., 1996, 2003). In all cases, following the extraction phase, samples were passed through a reverse‐phase SPE cartridge as a cleanup step (see below). Other applications of SFE include testing meat for the anabolic steroid stanozolol (Stolker et al., 2003) and for in‐line extraction/ detection of estrone, hexestrol, methyltestosterone, norestrosterone, stanozolol, testosterone, and zeranol from water (Ramsey et al., 1997; Simmons and Stewart, 1997).

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47

Table IV Citations to Extraction and Analysis of Estrogenic and Androgenic Compounds and the Matrices from Which They Have Been Extracted Analyte

Citation a

17a‐Ethinyl estradiol

17b‐Estradiol

Bisphenol Aa

Diethylstilbestrola

Estriol

Estrone

Fluoxymesteronea Hexestrola Levonorgestrela Melengestrol

Mestranola Methandrostenolonea Methyltestosteronea

Belfroid et al. (1999); Benijts et al. (2004a,b); Hanselman et al. (2003); Lee et al. (2003); Lerch and Zinn (2003); Ternes et al. (2002); Raman et al. (2004) Belfroid et al. (1999); Benijts et al. (2004a); Benijts et al. (2004b); Fine et al. (2003); Hanselman et al. (2003); Lagana et al. (2000); Lee et al. (2003); Raman et al. (2004); Ternes et al. (2002) Benijts et al. (2004); Benijts et al. (2004); Lerch and Zinn (2003) Benijts et al. (2004); Benijts et al. (2004); Cespedes et al. (2004) Benijts et al. (2004); Benijts et al. (2004); Cespedes et al. (2004); Lagana et al. (2000); Lerch and Zinn (2003) Belfroid et al. (1999); Benijts et al. (2004); Cespedes et al. (2004); Hanselman et al. (2003); Lagana et al. (2000); Lee et al. (2003); Lerch and Zinn (2003); Raman et al. (2004); Ramsey et al. (1997); Ternes et al. (2002) Cespedes et al. (2004); Lagana et al. (2000) Simmons and Stewart (1997) Ramsey et al. (1997) Chichila et al. (1989); Marchand et al. (2000); Neidert et al. (1990) Cespedes et al. (2004) Ternes et al. (2002) Simmons and Stewart (1997)

Matrix Sediment, sludge, water, wastewater

Soil, water, wastewater, lagoon eZuent

Water

Sediment, water

Sediment, water, wastewater, lagoon eZuent Soil, sediment, sludge, water, wastewater, lagoon eZuent

Water Water Sediment Animal tissues

Sediment, sludge Water Liver, food, meat, water (continued)

48

L. S. LEE ET AL. Table IV (continued)

Analyte Nonylphenol ethoxylatea

Norethindronea Nortestosteronea Octylphenol ethoxylatea

Progesterone Stanozolol Taleranol

Testosterone Trenbolone

Zearalanonea Zeranol a

Citation Parks et al. (1995); Simmons and Stewart (1997); Stolker et al. (1996) Cespedes et al. (2004) Cespedes et al. (2004) Parks et al. (1995); Simmons and Stewart (1997); Stolker et al. (1996) Cespedes et al. (2004) Cespedes et al. (2004) Launay et al. (2004); Simmons and Stewart (1997); Stolker et al. (2003) Lee et al. (2003); Stolker et al. (1996) Parks et al. (1995); Simmons and Stewart (1997); Stolker et al. (1996) Stolker et al. (1996); Launay et al. (2004) Stolker et al. (1996); Launay et al. (2004)

Matrix Sediment

Sediment Liver, food, meat, water Sediment

Sediment Meat, water Food, meat, bovine urine

Liver, food, meat, water, soil Meat

Food, meat, bovine urine Food, meat, water, bovine urine

Not used in agriculture.

After extraction, a cleanup step is usually required and has been achieved at varying levels of success with SPE cartridges consisting of normal phase materials such as silica gel and florisil, reverse‐phase materials such as C18, and polymeric phases such as OasisÒ HLB and SDB, as well as graphitized carbon‐based sorbents such as ENVI‐CARB (Supelco, Bellefonte, PA) (Lagana et al., 2000), or Carbograph (Alltech, Inc., Deerfield, IL) (Andreolini et al., 1987; D’Ascenzo et al., 2003), ion exchange materials like strong cation exchange (Diaz‐Cruz et al., 2003), and weak anion exchange (e.g., DEAE, Macherey‐Nagel, Easton, PA; Reddy et al., 2005). Hormones can also be isolated from extracts using gel permeation chromatography where high‐ molecular weight compounds (>1000 amu) are retained by the solid phase whereas the smaller analytes pass through unretained (Gomes et al., 2004). Determination of hormone concentrations is complicated by the presence of sulfate and glucuronide conjugates. These conjugates are much more hydrophilic than the parent compounds. Thus, they are expected to be

ANTIMICROBIALS AND HORMONES FROM AGRICULTURE

49

more prevalent in animal urine and the aqueous portion of filtered mixed wastes. Liquid samples containing hormone conjugates are usually cleaned up using a material with ion exchange properties such as a weak ion exchange resin (Reddy et al., 2005) or graphitized black carbon (Andreolini et al., 1987; D’Ascenzo et al., 2003). Given the diVerences in the polarity of the parent hormones and the hormone conjugates, a single clean up method usually will not yield optimal recovery of both compound groups. Detection and quantification of hormones are most often performed using coupled chromatographic–MS detection systems, although UV‐Vis spectroscopic detection has been used for methyltestosterone, stanozolol, testosterone, methandrostenolone, and zeranol (Simmons and Stewart, 1997). Both GC and LC methods have been used for the separation of hormones. The use of GC requires a derivatization step to permit the volatilization of hormones without thermal decomposition. Lerch and Zinn (2003) examined a series of derivatization agents for eVectiveness in terms of reaction percent and by‐products formed. If estrogen conjugate concentrations are to be determined by GC, the conjugates must be converted to the parent compounds prior to derivatization. This is done by acid or enzymatic hydrolysis. Electron impact (EI) and chemical ionization (CI) mass spectrometry are the most commonly used detection techniques used for gas chromatographic detection of hormones. Fine et al. (2003) quantified 17b‐estradiol, estrone, and estriol in groundwater and swine lagoon samples by derivatizing with pentafluorobenzyl bromide and N‐trimethylsilylimidazole followed by analysis with GC–MS in the negative CI mode. Limits of quantitation reported were 1 and 40 ng liter
1 for groundwater and swine lagoon samples, respectively. A linear regression of the peak ratios of the targeted estrogen relative to a deuterated spike of the same estrogen was used. Formaldehyde was used to prevent conversion of estradiol to estrone in the swine lagoon samples. LC methods have largely replaced GC methods for analysis of hormones because they are amenable to the analysis of nonvolatile compounds, including underivatized estrogens and their conjugates. Most commonly, a C18 column is used with either positive or negative mode ESI–MS. Analytes that are more amenable to negative mode ESI include estradiol, estrone, and estriol while testosterone, androstenedione, trenbolone, progesterone, and stanozolol respond better in positive ion mode. Benijts et al. (2004a) compared ESI to APCI and found signal suppression due to matrix eVects in both ionization sources. APCI tends to be influenced by analyte precipitation or coprecipitation with other nonvolatile matrix components whereas ESI signal suppression tended to be due to competition between matrix components and analytes. Detection limits for hormone analytes using coupled chromatographic–MS techniques are strongly influenced by the sample matrix, sample size, and extent of sample cleanup and concentration.

50

L. S. LEE ET AL.

Detection limits typically range from the low ppt range for aqueous samples to the low ppb range for solid samples. Commercial ELISA kits are also readily available, easy to use, portable, and can achieve ng liter
1 detection limits (Huang and Sedlak, 2001; Nunes et al., 1998). In this method, an antigen is adsorbed onto the surface of a test tube or microtiter well. An aliquot of antiserum is then reacted with the adsorbed antigen, and unreacted molecules are washed away. Next, an enzyme‐linked anti‐immunoglobulin is added. The analyte is then added, and the concentration is determined by the amount of color developed. A number of variations of this technique have been described (Benjamini and Leskowitz, 1991; Hage et al., 1993; Meulenberg et al., 1995). ELISA has been used for the analysis of 17b‐estradiol, 17a‐ethynyl estradiol, estrone, estriol, testosterone, melengestrol acetate, and trenbolone in various environmental matrices (Hakk et al., 2005; Hanselman et al., 2003; Huang and Sedlak, 2001; SchiVer et al., 2001; Shore et al., 2004). Although ELISA techniques are easy, sensitive, and relatively inexpensive, matrix interferences including cross‐reactivity with nontarget hormones, and matrix eVects caused by humic substances, endogenous enzymes, and protein binding can aVect the quality of the data obtained (Hanselman et al., 2003; Huang and Sedlak, 2001; Nunes et al., 1998). For this reason, confirmation of selected samples by coupled chromatographic–MS techniques is often required (Huang and Sedlak, 2001). For many environmental samples, including animal wastes and soil, the need for extensive sample cleanup can negate the advantages of using immunoassay tests.

VIII. SUMMARY AND FUTURE NEEDS The frequency of detection in soil and water of antimicrobials and steroid hormones has increased in the past decade with the advancement of analytical techniques that allow quantitation of contaminants in complex environmental matrices to ppb and ppt levels. Although there are several sources of these agents to the environment, the heavy use of antibiotics in the livestock industry and the dramatic shift in recent years toward more highly concentrated production units have brought attention to the role of animal waste‐borne antimicrobials, antibiotic‐resistant bacteria, and steroid hormones on ecosystem and human health. Antimicrobials, although frequently detected, are typically present in water at concentrations orders of magnitude below what would be considered inhibitory to most biota. Most antibiotics have a high aYnity for soil and sediment, thus residual concentrations found in soil are usually much higher than noted in water, but still often below concentrations of concern.

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The focal point with antibiotic use in animal production is the development of antibiotic‐resistant bacteria. Although the actual percentage is in much dispute, the majority of antibiotics used in animal production are given at subtherapeutic levels (levels assumed to be too low to eVectively eradicate targeted bacterial populations) solely to increase the rate of weight gain and feed eYciency. These antibiotics are fed to animals at low levels for extended periods, which may facilitate the evolution of bacteria toward antibiotic resistance. Indeed, there is a growing body of evidence of the presence of numerous antibiotic‐resistant genes in animal wastes and soils where waste are land applied and in water receiving runoV from these fields or discharges from aquaculture facilities. The World Health Organization recently suggested that the use of antimicrobials for growth promotion can be discontinued without significantly harming animal health or farmer income. After a ban on antimicrobial use for the purpose of growth promotion in Denmark, antimicrobial usage decreased 54% from its peak in 1994. Drug‐resistant strains in animals and meat fell dramatically in 2001. Farmers did have to increase the use of antimicrobials by approximately one‐third to treat sick animals after the ban. Overall, farmer costs increased 1% while profits from pork production rose. It was also noted that bacterial resistance in the human digestive tract was also reduced after the ban (Ferber, 2003). However, little is known about the actual contribution of animal manure‐borne antibiotic‐resistant bacteria to the development of resistant human pathogens. This issue is still under much debate, because evidence of animal‐derived antibiotic‐resistant pathogens compromising human health has yet to be conclusive (Phillips et al., 2004). In contrast to antibiotics, there is a growing body of evidence indicating that significant biological responses can occur at very low hormone concentrations (Oberdorster and Cheek, 2001), although research on the ecotoxicological eVects of hormones originating from CAFOs in its infancy. Much is known about the physiological eVects to fish exposed to natural estrogens such as 17b‐estradiol whereas research on the eVects of synthetic steroids (17b‐trenbolone, zeranol, and MGA) lags significantly behind. In addition, little is known about the toxicological eVects after in vivo exposures to a combination of hormonally active agents, which for animal manures includes a variety of estrogens, natural and synthetic androgens and progesterones as well as phytoestrogens associated with animal feed. In the last few years, there have been some studies assessing how hormones behave in soil and hormone levels initially present in poultry, swine, beef, and dairy manures; however, there is still little known on hormone persistence in manure‐applied fields and how it relates to hormone release from CAFOs. Overall, hormones appear to be moderately to highly sorbed and to dissipate quickly in an aerobic soil environment; therefore, in the absence of preferential or DOM‐ facilitated transport (e.g., to a tile drain) or surface flow (runoV), the potential

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to contaminate water adjacent to animal production units would seem low. Nevertheless, measurable concentrations of these hormones have been detected in soil, ground, and surface waters receiving runoV from fields fertilized with animal manure, and downstream from farm animal operations (Finlay‐Moore et al., 2000; Hanselman et al., 2003; Kolodziej et al., 2004; Lange et al., 2002; Soto et al., 2004). To better assess the real contribution of animal production and associated agricultural practices on steroid hormone inputs into the aquatic environment, systematic studies are needed to address: (1) hormone persistence in the field after being land applied; (2) the relative contribution of runoV events, tile drainage, and leaching on the actual quantities of hormones released to water sources, which will vary with region and time after land application; and (3) correlation between time after application and rainfall events on hormone loadings to aquatic systems. Also research is needed to understand how application methods and timing of applications aVect potential hormone loadings to aquatic systems as well as how manure storage or composting parameters can be optimized toward reducing manure‐borne hormone concentrations prior to land application. Currently, there is no cost‐eVective way to pretreat most animal wastes except for poultry litter for which composting and treatment is less cost prohibitive (Lorenzen et al., 2004; Shore and Shemesh, 2003). However, as noted, further research is needed to optimize and assess composting strategies with regards to hormone and antimicrobial dissipation, but composting is unlikely to reduce the presence of manure‐borne antibiotic‐resistance bacteria. Small changes in how manure is stored or treated (e.g., aeration) prior to land application may serve to reduce hormone and antibiotic concentrations. The use of buVer strips as is currently recommended to reduce pesticide and phosphate loadings to aquatic systems should also reduce the amounts of both antimicrobials and hormones entering waterways from runoV. Hoorman et al. (2004) also recommended minimizing manure application to fields that are prone to flooding. To reduce direct manure discharge through tile drains, Hoorman et al. (2004) make several logical recommendations such as not applying manure when tile drains are flowing, limiting manure applications to the water‐holding capacity of the top 8 in. of soil, using multiple smaller liquid manure applications instead of a single large volume application, and monitoring tile drains during manure application. For aquaculture operations, filtration and/or sedimentation traps can be useful for reducing or completely eliminating the level of eZuent contamination in land‐based fish farms (Smith et al., 1994). Treatment and reuse of water in fish ponds are also being considered to minimize water demand in regions where water is limited, and reduce environmental contamination driven primarily by reducing N, P, and carbon discharges. Currently, some aquaculture units are investigating the use of aquaculture water discharge

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for growing hydroponic plants that need N, P, and C nutrients, which allows simultaneous reuse and treatment. Whether water reuse from aquaculture facilities will gain momentum in the future will depend on overall impacts on profit margins with the largest costs associated with monitoring and energy.

ACKNOWLEDGMENTS This eVort and the recent research cited to the authors of this book chapter were funded in part by the Purdue Research Foundation; School of Agriculture, Purdue University; US Environmental Protection Agency National Risk Management Research Laboratory (Cincinnati, OH) under Cooperative Agreement No. 82811901‐0; and the Savanna River Ecology Laboratory, University of Georgia.

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Panter, G. H., Thompson, R. S., and Sumpter, J. P. (1998). Adverse reproductive eVects in male fathead minnows (Pimephales promelas) exposed to environmentally relevant concentrations of the natural oestrogens, oestradiol and oestrone. Aquat. Toxicol. 42, 243–253. Panter, G. H., Thompson, R. S., and Sumpter, J. P. (2000). Intermittent exposure of fish to estradiol. Environ. Sci. Technol. 34, 2756–2760. Parks, O. W., Lightfield, A. R., and Maxwell, R. J. (1995). EVect of sample matrix dehydration during supercritical fluid extraction on the recoveries of drug residues from fortified chicken liver. J. Chromatogr. Sci. 33, 654–657. Petersen, A., and Dalsgaard, A. (2003). Antimicrobial resistance of intestinal Aeromonas spp. and Enterococcus spp. in fish cultured in integrated broiler‐fish farms in Thailand. Aquaculture 219, 71–82. Peterson, E. W., Davis, R. K., and OrndorV, H. A. (2000). 17b‐Estradiol as an indicator of animal waste contamination in mantled karst aquifers. J. Environ. Qual. 29, 826–834. Phillips, I., Casewell, M., Cox, T., De Groot, B., Friis, C., Jones, R., Nightingale, C., Preston, R., and Waddell, J. (2004). Does the use of antimicrobials in food animals pose a risk to human health? A critical review of published data. J. Antimicrob. Chemother. 53, 28–52. Pierini, E., Famiglini, G., Mangani, F., and Cappiello, A. (2004). Fate of enrofloxacin in swine sewage. J. Agric. Food Chem. 52, 3473–3477. Pottier, J., Cousty, C., Heitzman, R. J., and Reynolds, I. P. (1981). DiVerences in the biotransformation of a 17b‐hydroxylated steroid, trenbolone acetate, in rat and cow. Xenobiotica 11, 489–500. Rabolle, M., and Spliid, N. H. (2000). Sorption and mobility of metronidazole, olaquindox, oxytetracycline and tylosin in soil. Chemosphere 40, 715–722. Raman, D. R., Williams, E. L., Layton, A. C., Burns, R. T., Easter, J. P., Daugherty, A. S., Mullen, M. D., and Sayler, G. S. (2004). Estrogen content of dairy and swine waste. Environ. Sci. Technol. 38, 3567–3573. Ramsey, E. D., Minty, B., and Rees, A. T. (1997). Drugs in water: Analysis at the part‐per‐ billion level using direct supercritical fluid extraction of aqueous samples coupled online with ultraviolet‐visible diode‐array liquid chromatography‐mass spectrometry. Anal. Commun. 34, 261–264. Reddy, S., Iden, C. R., and Brownawell, B. J. (2005). Analysis of steroid conjugates in sewage influent and eZuent by liquid chromatography‐tandem mass spectrometry. Anal. Chem. 77, 7032–7038. Relyea, R. A. (2003). Predator cues and pesticides: A double dose of danger for amphibians. Ecol. Appl. 13, 1515–1521. Renew, J. E., and Huang, C.‐H. (2004). Simultaneous determination of fluoroquinolone, sulfonamide, and trimethoprim antimicrobials in wastewater using tandem solid phase extraction and liquid chromatography‐electrospray mass spectrometry. J. Chromatogr. A 1042, 113–121. Reverte, S., Borrull, F., Pocurull, E., and Marce, R. M. (2003). Determination of antimicrobial compounds in water by solid‐phase extraction‐high performance liquid chromatography‐ (electrospray) mass spectrometry. J. Chromatogr. A 1010, 225–232. Richardson, S. D. (2002). Environmental mass spectrometry: Emerging contaminants and current issues. Anal. Chem. 74, 2719–2741. Robinson, A. A., Belden, J. B., and Lydy, M. J. (2005). Toxicity of fluoroquinolone antimicrobials to aquatic organisms. Environ. Toxicol. Chem. 24, 423–430. Rurainski, R. D., Theiss, H. J., and Zimmermann, W. (1977). Existence of natural and synthetic estrogens in drinking water. GWF, Wasser/Abwasser 118, 288–291. Rysz, M., and Alvarez, P. J. J. (2004). Amplification and attenuation of tetracycline resistance in soil bacteria: Aquifer column experiments. Water Res. 38, 3705–3712.

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ANTHROPOGENIC INFLUENCES ON WORLD SOILS AND IMPLICATIONS TO GLOBAL FOOD SECURITY Rattan Lal Carbon Management and Sequestration Center, The Ohio State University, Columbus, Ohio 43210

I. II. III. IV. V.

Introduction Land Area of Natural Ecosystems Converted to Agriculture Consequences of Agricultural Expansion and Intensification Water Consumption and Change in the Hydrologic Cycle Anthropogenic Impact on Biogeochemical Cycles of Principal Elements A. The Carbon Cycle B. The Nitrogen Cycle C. The Phosphorus Cycle VI. Food Demands for the World’s Growing Population VII. Stewardship of Soil and Water Resources VIII. Conclusions References

The world population has increased from 2–10 million at the dawn of settled agriculture about 10–12 millennium ago to 6.5 billion in 2006, and may stabilize at 10–12 billion by 2100. Most of the future increase in world population will occur in developing countries where the natural resources are already under great stress, and where most of world’s food‐insecure population lives. Rapid increase in population, especially between 1700 and 2000, caused large scale conversion of natural ecosystems to agricultural land uses. The land‐use change involved conversion of 1135 million hectares (Mha) of forest and woodland, and 669 Mha of savanna, grassland, and steppe. Similarly, the area under grazing land increased from 530 Mha to 3300 Mha. Agricultural expansion and its intensification, by plowing and irrigation along with use of chemicals: (1) exacerbated the problems of soil degradation that reportedly aVects 1966 Mha worldwide of which the large fraction is caused by water and wind erosion, (2) increased irrigated land area to about 280 Mha or 19% of the total cropland area consuming 18,200 km3 for evapotranspiration or 26% of the total terrestrial evapotranspiration, (3) disrupted global biogeochemical cycling of carbon leading to increase in atmospheric abundance of CO2 by 37.5% from 280 ppm in
1750 to 385 ppm 69 Advances in Agronomy, Volume 93 Copyright 2007, Elsevier Inc. All rights reserved. 0065-2113/07 $35.00 DOI: 10.1016/S0065-2113(06)93002-8

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RATTAN LAL in 2006, (4) accentuated the use of fertilizers and pesticides to increase food production, and (5) caused mass extinction of plant and animal species. Drastic increase in crop yields during the second half of the twentieth century led to increase in per capita global food production despite the increase in world population. However, the global cereal demand (rice, wheat, maize) will increase at the rate of 1.3% per year between 2000 and 2025 necessitating increase in the mean grain yield of these cereals especially in the developing countries. The required cereal grain yield in developing countries will have to be increased from 2.6 Mg ha1 in 2000 to 3.60 Mg ha1 by 2025 and 4.30 Mg ha1 by 2050 even if the food habit of population in emerging economies (e.g., China, India) remains the same. Therefore, a judicious and scientific management of soil and water resources is essential. Degraded soils and ecosystems must be ameliorated, and the depleted organic carbon pool restored so that soils can respond to the use of yield‐enhancing input (e.g., fertilizers, improved varieties). Restoring soil quality through improvements in soil organic carbon pool is essential to increasing agronomic yields especially in sub‐Saharan Africa (SSA), South Asia, and elsewhere in the tropics with harsh climate, fragile soils, and resource‐poor farmers. This strategy requires the adoption of a holistic approach based on sound scientific principles of managing the soil and water resources in accord with social, economic, and political realities of the region. # 2007, Elsevier Inc.

I. INTRODUCTION The world population was probably 2–10 million when agriculture began about 10–12 thousand years ago. It was estimated to be 200–400 million by 1 AD and 1 billion by 1850. The population increased drastically during the twentieth century. It was 2 billion in 1930, 3 billion in 1960, 4 billion in 1975, 5 billion in 1987, and 6 billion in 1998. The human population has increased by 152% from 2.5 billion in 1950 to about 6.3 billion in 2004 (Rees, 2004). The population is presently increasing at the rate of about 1.3% per year, and is expected to reach 7 billion by 2010, 8 billion by 2025, and stabilize at 10–12 billion by 2100 (Cohen, 2003). Most of the future projected increase in population will occur in developing countries, especially in Asia and sub‐ Saharan Africa (SSA). These regions, characterized as the population hot spots of the world, are also home to food‐insecure population and to those prone to hidden hunger and malnutrition. Chronically food‐insecure people in the world were estimated at 960 million in 1970, 938 million in 1980, 831 million in 1990, 790 million in 2000, 730 million in 2005, and will be 680 million by 2010 (Rosegrant and Cline, 2003). It is widely feared that the UN Millennium Development Goals will not be met. Of the 730 million food‐ insecure persons in 2005, 175 million were children under 5 and 510 million were women. Yet, 70% of the food in food‐deficient countries is produced by

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women. Most of the food‐insecure people live in South Asia and Africa. In SSA, there are 200 million food‐insecure people or one‐third of the total population of the region (Sanchez, 2002). Food grains and roots and tubers, which form staple of these persons, are either grown on degraded soils or with extractive farming practices with little or no input of essential fertilizers or organic amendments. In their quest to increase food production to meet the demands of growing population, humans have brought about drastic changes in terrestrial and aquatic ecosystems. This chapter addresses human‐induced changes in terrestrial ecosystems beginning with the dawn of settled agriculture about 10–12 millennium ago. The principal focus is on agricultural activities rather than industrial activities with particular reference to changes in terrestrial and aquatic ecosystems, and disruptions in cycles of H2O, C, N, and P. It also outlines strategies for sustainable management of soil and water resources to enhance food production in SSA.

II.

LAND AREA OF NATURAL ECOSYSTEMS CONVERTED TO AGRICULTURE

Increase in population necessitated conversion of natural ecosystems to croplands and grazing lands. World cropland area increased rapidly with the onset of industrialization, especially after World War II. The cropland area was estimated at 265 million hectares (Mha) in 1700, 537 Mha in 1850, 913 Mha in 1920, 1170 Mha in 1950, 1500 Mha in 1980, and 1360 Mha in 2000 (FAO, 2004; Myers, 1996; Richards, 1990). Deforestation has been a major factor in conversion of forested ecosystems to cropland (William, 1994). The data in Table I show that between 1700 and 1992 (292 years) the conversion of natural ecosystems to croplands comprised 1135 Mha of forest and woodland at an average rate of 3.9 Mha year1, and 669 Mha of savanna, grassland, and steppe at an average rate of 2.3 Mha year1. Of the 1135 Mha of forest converted to agricultural land use, 422 Mha were from tropical forest, 451 from temperate forest, 222 Mha from deciduous/ evergreen forest and woodland, and 40 Mha from the Boreal forest (Table II). Regions with more drastic increase in cropland were North America, Latin America, Southeast Asia, and USSR (Table III). A strong decline in per capita cropland, especially in countries with rapidly increasing population, will necessitate additional deforestation such as in Indonesia (Sumatra), Western and Central Africa, and South America. The cropland area of 1.5 Bha in 2000 is projected to increase to 1.66 Bha by 2020 and 1.89 Bha by 2050 (Tilman et al., 2001).

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Table I Estimates of Changes in Vegetation Types Due to Land Use Change for Conversion to Cropland (Recalculated from Ramankutty and Foley, 1999)

Vegetation type Forest and woodland Savanna, grassland, and steppe Tundra and polar deserts Total

Actual land area (106 ha)

Prehistoric area (106 ha)

1700

5527 3336

5277 3232

4992 3136

4392 2667

1135 669

3.9 2.3

2357

2352

2347

2331

26

0.09

13,008

12,604

12,187

10,983

2025

6.93

1850

1992

Total change (106 ha)

Average rate of change (106 ha year1)

Table II Estimates of Changes in World Forest Resources for Conversion to Cropland (Recalculated from Ramankutty and Foley, 1999) Actual land area (106 ha)

Prehistoric area (106 ha)

1700

1850

Forest and woodland Temperate forest Boreal forest Evergreen, deciduous forest, and woodland

2259 957 818 1493

2150 864 812 1451

Total

5527

5277

Forest type

1992

Total change (106 ha)

Average rate of change (106 ha year1)

2098 703 802 1389

1837 506 778 1271

422 451 40 222

1.45 1.54 0.14 0.76

4992

4392

1135

3.90

Managed grazing occupies more than 3300 Mha worldwide or 25% of the global land surface (Asner et al., 2004). Grazing lands have increased more than 600% in geographic extent from about 530 Mha in 1700 to 3300 Mha in 2000. There are more than 1.5 billion animal units (AU) grazing on these lands (WRI, 1990). The AU is defined as: AU ¼ n (cows þ buValoes) þ 0.2n (sheep þ goats) þ 1.2n (horses þ camels). The distribution of managed‐grazing lands in diVerent ecosystems shows that most of the grazing land exists in savanna, grassland/steppe, dense shrubland, and open shrubland (Table IV). Of the total area of 3300 Mha, the continental distribution of improved pasture includes the following: 780 Mha in Africa, 640 Mha in Asia, 460 Mha in South America, 450 Mha in Oceania,

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Table III Trends in Agricultural Land Use Between 1700 and 2000 over 300 Years (Recalculated from Richards, 1990) Cropland (106 ha) Continent Sub‐Saharan Africa North Africa and Middle East North America Latin America China South Asia Southeast Asia Europe USSR Pacific Total

Grassland and pasture (106 ha)

1700 1850 1920 1950 1980 1700

1850

1920

1950

1980

44 20

57 27

88 43

136 66

222 1052 107 1123

1061 1119

1091 1112

1130 1097

1158 1060

3 7 29 53 4 67 33 5

50 18 75 71 7 132 94 6

179 45 95 98 21 147 178 19

206 87 108 136 35 152 216 28

203 915 142 608 134 951 210 189 55 125 137 190 233 1068 58 639

914 621 944 189 123 150 1078 638

811 646 941 190 114 139 1074 630

789 700 938 190 105 136 1070 625

790 767 923 187 92 138 1065 608

265

537

913

1170 1501 6860

6837

6748

6780

6788

Table IV Distribution of Managed‐Grazing Land in DiVerent Biomes (Recalculated from Asner et al., 2004) Biome Savanna Grassland/steppe Open shrubland Dense shrubland Desert Tropical evergreen forest/woodland Temperate deciduous Evergreen/deciduous forest/woodland Topical deciduous forest/woodland Temperate needle leaf evergreen forest/woodland Temperate broad leaf/ evergreen/forest/woodlands Tundra Boreal evergreen forest/woodland Boreal deciduous forest/woodland Total

Area grazed (106 ha)

Grazed percentage

1931 1422 1209 601 1545 1743

948 768 398 273 197 172

49.1 54.0 32.9 45.4 12.8 9.9

510 1568

149 126

29.1 8.0

596

120

20.2

362

76

20.9

126

71

56.0

732 636 218

17 8 2

2.3 1.2 1.1

13,199

3325

25.2

Total area (106 ha)

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360 Mha in North and Central America, 370 Mha in former USSR, and 80 Mha in Europe (Graetz, 1994). Similar to the projected increase in cropland area, the pasture/grazing land area is projected to increase from 3.47 Bha in 2000 to 3.67 Bha in 2020 and 4.01 Bha in 2050 (Tilman et al., 2001).

III.

CONSEQUENCES OF AGRICULTURAL EXPANSION AND INTENSIFICATION

Conversion of vast areas of natural to agricultural ecosystems was facilitated by the invention of the ‘‘ard’’ or ancient plow which evolved from a digging stick to the Roman plow whose description was vividly provided by Vergil around 1 AD (White, 1967). The Roman plow evolved into the iron‐made soil‐inverting plow around fifth to tenth century AD. The use of the horse‐driven moldboard plow was instrumental in the expansion of agriculture in the Western United States during the eighteenth and nineteenth centuries. The basic equipment, called the prairie breaker, was a horse‐pulled moldboard plow designed by Thomas JeVerson in 1784 and patented by Charles Newfold in 1796. The plow was marketed in the 1830s as a cast iron plow by a blacksmith named ‘‘John Deere.’’ Further expansion of cropland worldwide was facilitated by the invention of the ‘‘steam horse’’ or the steam‐powered tractor in 1910. Soil perturbation by deforestation and plowing exacerbated the global problem of soil degradation. Oldeman (1994) estimated that total land area aVected by soil degradation worldwide at 1966 Mha comprising 1094 Mha by water erosion, 549 by wind erosion, 249 Mha by chemical degradation, and 83 Mha by physical degradation. There is some overlap and duplication in estimates of land area aVected by soil erosion by water and wind. The severity of degradation is high in croplands and grazing lands, and in tropical regions characterized by harsh climate and sloping lands. Of the total degraded area of 1966 Mha, 579 Mha is attributed to deforestation, 679 Mha to overgrazing, 552 Mha to agricultural activities, 133 Mha to overexploitation, and 23 Mha to bioindustrial activities (Oldeman, 1994; Table V). The ‘‘Dust Bowl’’ of the 1930s in the United States was an example of soil degradation and desertification caused by overexploitation and severe disturbance of the soil by plowing and excessive grazing. A cloud of dust rising up to 4500 m high obscured the Sun in May 1934 from the Texas Plains up through the Dakotas and from Montana to the Ohio Valley. On 12 May 1934, the dust sifted through the windows of the White House and covered President Roosevelt’s desk. It was this event that inspired Hugh Hammond Bennett to promote creation of the US Soil Conservation Service (SCS), now called the Natural Resource Conservation Service of USDA (NRCS).

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Table V Extent of Soil Degradation for Agricultural and Forestry Land Uses in DiVerent Continents (Modified from Oldeman, 1994) Cropland (106 ha)

Pasture land (106 ha)

Forest and woodland (106 ha)

Total

Africa Asia South America Central America North America Europe Oceania

120 206 64 28 63 72 8

243 197 68 10 29 54 84

130 344 112 25 4 92 12

494 747 244 63 96 218 104

Total

561

685

719

1966

Continent

IV. WATER CONSUMPTION AND CHANGE IN THE HYDROLOGIC CYCLE Irrigated agriculture started some 9500–8800 BC. Irrigation was widely used by 4000 BC by Sumerians, Babylonians, and other ancient civilizations in the valleys of the Nile, Indus, and Yangtze Rivers (Hillel, 1994). These civilizations have appropriately been called ‘‘hydric civilizations.’’ Increase in cropland area during the nineteenth and twentieth centuries, especially in arid and semiarid regions, was accompanied by expansion in irrigated land area. Thus, cropland area under irrigation increased drastically during the nineteenth and twentieth centuries. The land area under irrigated agriculture was 8 Mha in 1800, 40 Mha in 1900, 100 Mha in 1950, 185 Mha in 1975, 255 Mha in 1995, and 270 Mha in 2000 (FAO, 2004; Field, 1990; Framji and Mahajan, 1969; Gleick, 2003a,b; Postel, 1999). Presumably, the rate of growth in irrigated agriculture is decreasing because of the lack of readily available water resources. Scherr and Yadav (1999) predicted that the projected land area under irrigated agriculture will be about 300 Mha by 2020 and most of the future expansion in irrigation will occur in South Asia, especially India (Table VI). Tilman et al. (2001) projected that irrigated land area in the world will increase from 280 Mha in 2000 to 367 Mha by 2020 and 529 Mha by 2050. Agriculture is the largest consumer of anthropogenic water use, estimated at 85% of the total human consumptive use (Gleick, 2003a,b). Postel et al. (1996) estimated that evapotranspiration appropriated by human land uses includes 5500 km3 by cropland, 5800 km3 by grazing land, 6800 km3 by forest land, and 100 km3 by urban land uses (e.g., lawns, parks, golf courses, and so on). Thus, human‐managed ecosystems consume a total of 18,200 km3 of evapotranspiration or 26% of the total

76

RATTAN LAL Table VI Land Area Under Irrigation (Adapted from Scherr and Yadav, 1999) Region Sub‐Saharan Africa Latin America South Asia India China World

1993 (106 ha)

2000 (106 ha)

4.9 17.1 74.7 50.1 49.9

7.4 18.7 97.8 68.6 53.1

253.0

296.0

(18,200 km3 out of the total 69,000 km3 terrestrial evapotranspiration). Irrigated agriculture produces 40% of the total production (Gleick, 2003a,b; Postel, 1999). Humans now use 26% of total terrestrial evapotranspiration and 54% of the total runoV that is geographically and temporally accessible (Postel et al., 1996). The use of total runoV may increase by 10% by 2025 compared to 1995. There are numerous factors which aVect the global water use (Table VII). Some of the anthropogenic activities, such as deforestation and agricultural use of soil and water, have a positive feedback. Increase in temperature due to global warming may increase evaporation and consumptive water use (Vo¨ro¨smarty et al., 2005; Table VII). Consequently, the sustainable water supply will decrease with increase in human population (Table VIII). With world population increasing from 4.98 to 8.0 billion between 1985 and 2025, global sustainable water supply is projected to decrease from 39,399 km3 in 1985 to 37,100 km3 in 2025 (Table VIII). Most drastic decline in global sustainable water supply will occur in Africa and South America. The population of Africa will increase by 265%, and that of South America by 170% over the same period. Yet, the demand for water is continuing to increase with the increase in world population (Table IX). Estimates of total water consumption are highly variable because of diVerent methods used and other uncertainties. Whereas the estimates listed in Table X diVer than those in Table IX, allocation of scarce water resources to agriculture will face increasing competition from industry and urbanization. Share of agricultural water use from the global consumption decreased from 81.4% in 1900 to 56.7% in 2000 (Table X). Similar to the decline in per capita cropland area (Brown, 2004), there is also a serious decline in per capita renewable fresh water supply. Gardner‐ Outlaw and Engelman (1997) projected that more than a billion people will be prone to water scarcity and as much as 3 billion people to water stress at the medium population projection by 2025. Johnson et al. (2001) estimated that in the year 2000, 2.3 billion people lived in river basins with water stress or per capita annual water availability of <1700 m3. Of these, 1.7 billion

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77

Table VII Anthropogenic Activities AVecting Global Water Budget (Adapted from Vo¨ro¨smarty et al., 2005) Process

Anthropogenic activities responsible

Global climate change a. Rise in temperature and evaporation b. Increase in frequency of extreme events c. Change in runoV Change in hydrologic cycle at the scale of river basins River flow regulation Erosion and sedimentation

Pollution, eutrophication, and hypoxia Contamination of water Decline and/or changes in biodiversity

Fossil fuel combustion, tropical deforestation, soil cultivation, and land‐use conversion

Deforestation, wetland drainage, irrigation, high evaporation from reservoirs, and interbasin water transfer Interbasin transfer, dams, stream channelization, leveeing, and human settlement of flood plains Land‐use conversion including deforestation, biomass burning, soil cultivation, excessive and uncontrolled grazing, changes in sediment flux due to dams, and reduced river discharge Nonpoint source pollution; point source pollution from industry, mining, feed lots, and urban centers; hypoxia of coastal waters Increase in fecal contamination from unplanned urbanization and animal husbandry Changes in flora and fauna, including those in soils, due to pollution by agriculture, mining, grazing, and urbanization; thermal pollution; introduction of new species from globalization; fragmentation of waterways and change in flood patterns

Table VIII Sustainable Water Supply and the Corresponding Population in 1985 and 2025 (Adapted from Vo¨ro¨smarty et al., 2005) Population (106)

Sustainable water supply (km3 year1)

Continent

1985

2025

1985

2025

Africa Asia Australia/Oceania Europe North America South America

543 2930 22 667 395 267

1440 4800 33 682 601 454

4520 13,700 714 2770 5890 11,700

4100 13,300 692 2790 5870 10,400

World total

4830

8010

39,300

37,100

78

RATTAN LAL Table IX Global Water Withdrawal and Consumption (Gleick, 2003a) Year

Withdrawal (km3)

Consumption (km3)

1900 1940 1950 1960 1970 1980 1990 1995 2000 2010 2025

579 1065 1366 1989 2573 3214 3590 3765 3927 4323 5137

415 704 887 1243 1536 1918 2192 2265 2329 2501 2818

Table X Competition for Global Agricultural Water Consumption from Industry and Urbanization During Twentieth Century (Modified from Kondratyev et al., 2003) Agricultural use (109 m3 year1) Urban use Industrial use Total Year (109 m3 year1) (109 m3 year1) (109 m3 year1)

Net

1900 1940 1950 1960 1970 1975 1985 1995 2000

350 660 860 1510 1930 2100 2400 2760 3400

430 870 1190 1990 2630 3080 3970 4750 6000

20 40 60 80 120 150 250 320 440

30 120 190 310 510 630 1100 1560 1900

Percentage of total 81.4 75.9 72.3 75.9 73.4 68.2 60.5 58.1 56.7

people resided in highly stressed river basins where water availability falls below 1000 m3 per capita annually. By the year 2025, 3.5 billion or 48% of the world population will live in water‐stressed river basins. Numerous inland water bodies (e.g., Aral sea, Lake Chad) are considerably diminished and rapidly shrinking. Indeed, aquatic ecosystems have been altered more than even the terrestrial ecosystems. In many cases, even the fossil or nonrenewable water is being depleted. India uses 200 km3 of ground water for irrigation annually. This water use is three times the annual flow of China’s Yellow River. Excessive water use is for rice production in arid

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79

Punjab and Haryana states. It is a matter of the highest priority to diversify crops and identify economically viable alternatives to the rice–wheat system practiced on 15 Mha of land area in the Indo‐Gangetic region. The uncertainty about the available water resources is heightened by the projected climate change and its eVects on the world water balance. Ragab and Prudhomme (2002) observed that by 2050, North Africa and some parts of Egypt, Saudi Arabia, Iran, Syria, Jordan, and Israel are expected to have reduced rainfall amounts of 20–25% less than the present mean values (Table XI). The decrease in rainfall accompanied by an increase in temperatures between 2 and 2.75  C will have strong adverse impact on available water resources. In southern Africa, there will be an increase in temperature between 1.5 and 2.5  C in the south to between 2.5 and 3  C in the north accompanied by an average annual decrease in rainfall by about 10%. In the Thar Desert, the average annual temperature will increase by 1.5–2.5  C along with decrease in annual precipitation of 5–25% (Ragab and Prudhomme, 2002). The increasing scarcity of fresh water supply will be confounded by the widespread problems of water contamination, pollution, and eutrophication. The risks of contamination of water by pesticides used in agriculture are progressively increasing. The global pesticide used in 1990s was 2.6 million Mg of active ingredients. The amount of pesticides used in the world was 3.75 million Mg in 2000 and is projected to increase to 15.6 million Mg by 2020 and 25.1 million Mg by 2050 (Tilman et al., 2001). As much as 85% of all pesticides are used in agriculture. Pesticide use is increasing very rapidly in

Table XI EVect of Projected Climate Change on Precipitation and Temperature of DiVerent Regions (Adapted from Ragab and Prudhomme, 2002) Projected change in Region North Africa, Egypt, Saudi Arabia, Iran, Syria, Israel, and Jordan Sahara Southern Africa Taklimakan region, China Thar Desert (South Asia) Aral Sea Basin Australia

Temperature ( C)

Season

Rainfall (%)

(i) Summer

20 to 25

þ2 to þ2.75

(ii) Winter Winter (i) Summer (ii) Winter Summer Summer Summer (i) South (ii) North

10 to 15 þ25 5 to 15 þ5 to þ20 þ5 to þ20 5 to 25 þ5 to þ10 20 to 25 5 to 10

þ1.75 to þ2.5 þ1.5 to þ3.0 þ1.75 to þ2.5 þ2.0 to þ2.5 þ2.0 to þ2.75 þ1.0 to þ1.5 þ2.0 to þ2.75

80

RATTAN LAL

developing countries where regulatory standards and protocols are not in place. Chemical industry produces 100 million ton of chemicals every year, representing 70,000 diVerent compounds, and about 1000 new compounds are added annually. Some of the compounds (e.g., DDT, Aldrin, PCBs, CFCs, HCFCs) have a very long residence time and severe environmental impact. The problem of water pollution is extremely acute in developing countries (e.g., India, China, SSA). The fresh water requirements are also expected to increase because of the change in food habits of people in the developing countries due to change in the household income and preference of meat and poultry over grains and vegetables. Consumptive water use per kilogram of edible product is considerably more for animal‐based food products than crop/grain‐based food. The water requirement per kilogram of product is 900–2000 liter for wheat, 1900–5000 liter for rice, 1100–1800 liter for sorghum, and 1100–2000 liter for soybean, compared with 3500–5700 liter for chicken, 15,000–70,000 liter for beef, and 1000–300,000 for shrimp (Clay, 2004). The change in food habits of large populations of China and India from primarily vegetarian diet to animal products will create additional stress on the scarce water resources.

V.

ANTHROPOGENIC IMPACT ON BIOGEOCHEMICAL CYCLES OF PRINCIPAL ELEMENTS

Drastic anthropogenic perturbations of natural ecosystems have disrupted cycles of principal elements. Most important among these with strong impact on the environments are the cycles of C, N, and P.

A. THE CARBON CYCLE There are five major or global C pools. These pools are interconnected, and C circulates among them (Fig. 1). These pools are: (1) the oceanic with C stock of 38,000 Pg, (2) the geologic with 5000 Pg, (3) the pedologic with 2500 Pg to 1‐m depth, (4) the atmospheric with 760 Pg, and (5) the biotic with 560 Pg. The atmospheric pool has been increasing steadily since about 10,000 years ago with the dawn of settled agriculture which necessitated deforestation and biomass burning. The increase in atmospheric C pool involved increase in concentration of CO2 and CH4. The latter was associated with the cultivation of rice paddies which began about 5000 years ago in South and Southeast Asia (Ruddiman, 2003, 2005). While the emission of C from perturbation of the terrestrial ecosystems for agriculture activities has been gradual, combustion of fossil fuel with the onset of industrial revolution in 1750 increased emissions and caused a drastic increase in atmospheric concentration of CO2 from

WORLD SOILS AND THE ENVIRONMENT

1.

Biotic pool 560 Pg (+2 Pg year−1)

8 Pg

−1

81

Geologic pool 5000 Pg

ye

r ea gy P 7

−1

ar

Atmospheric pool 760 Pg (+3.3 Pg year−1)

Pedologic pool 2500 Pg 1.14

Pg C

per y

per year

ear

Oceanic pool 38,000 Pg (+2.2 Pg year−1)

Figure 1 Human‐induced changes in global carbon pools and fluxes.

280 ppm around 1850 to 377 ppm in 2004, an increase of 35%. It is presently increasing at the rate of 1.8 ppm or 0.47% per year (WMO, 2006). Global CO2– C emissions from fossil fuel consumption were 1.6 Pg in 1950, 6.3 Pg in 2000 (Table XII), and 7 Pg in 2004 (WMO, 2006). The principal sources of CO2 are fossil fuel combustion at 7 Pg C per year and tropical deforestation at 1.8 Pg C per year (IPCC, 2001; WMO, 2006). Of the total annual anthropogenic source of 8.6 Pg, 3.3 Pg is absorbed by the atmosphere, 2.2 Pg by the ocean, and the fate of remainder of the C emitted is rather uncertain. It is often argued that the so‐called fugitive CO2 is absorbed by a large terrestrial sink probably somewhere in North America. With business as usual, the atmospheric concentration of CO2 may double by the end of the twenty‐first century with an attendant increase in temperature of 2–6 C (IPCC, 2001; Karl and Trenbath, 2003). These changes are causing a drastic impact on earth’s climate (Flannery, 2005). Conversion of natural to agricultural ecosystems, through deforestation and biomass burning followed by repeated plowing and other tillage operations, have drastically altered the soil C pool. The latter comprises two components: soil organic carbon (SOC) pool and soil inorganic carbon (SIC) pool. The SOC pool is estimated at 1550 Pg and the SIC pool at 950 Pg, both to 1‐m depth (Batjes, 1996; Eswaran et al., 2000). The SOC pool is more drastically perturbed by agricultural activities than the SIC pool. Lal (1999) estimated the historic loss of SOC pool due to agricultural activities at 66–90 Pg, of which 12–39 Pg is due to accelerated soil erosion. The loss of SOC pool leads to decline in soil quality in relation to agronomic productivity and environment‐moderation capacity (e.g., filtering and denaturing contaminants). In contrast, restoration of degraded soils and ecosystems can enhance SOC pool through the

82

RATTAN LAL Table XII Global CO2–C Emissions from Fossil Fuel Combustion (Adapted from Kondratyev et al., 2003; Marland et al., 2001) Year

Emissions (Tg C per year)

1751 1800 1850 1860 1880 1900 1920 1940 1960 1980 1990 1995 2000 2004

3 8 54 91 236 534 932 1299 2535 5155 5931 6190 6299 7000

process of soil C sequestration. The C sink capacity of world soils, through restoration of degraded soils and adoption of recommended management practices (RMPs), is 0.6–1.2 Pg C per year for 25–50 years. Realization of this C sink capacity can oVset fossil fuel emissions by 10–15% (Lal, 2004b). The C cycle is closely linked to the water cycle, and accelerated soil erosion strongly impacts the soil C pool. Soil C transported with the sediments may be a source of atmospheric enrichment of CO2 (Lal, 2005).

B. THE NITROGEN CYCLE Similar to the link between H2O and C cycles, there is also a strong link between C and N cycles. Anthropogenic activities have altered the N cycle primarily through manufacture of N fertilizer. Changes in N fertilizer use shown in Table XIII indicate drastic increase since 1960s. Use of N fertilizer, important to enhancing agricultural production, increased from <10 million Mg in 1950 to 87 million Mg in 2000 and is projected to increase to 135 million Mg in 2020 and 236 million Mg in 2050 (Table XIII). In contrast to synthetic N fixation, the biological N fixation by legumes is estimated at 40 million Mg year1 (Vitousek et al., 1997). The disruption in the cycle of N has numerous adverse environmental impacts such as acid rain, increase in NO3 concentrations in surface and ground waters, and transport in major world rivers (Caraco and Cole, 1999). The hidden C costs, in terms of CO2 emitted into the atmosphere, is another environmental concern.

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Table XIII World Fertilizer Consumption Since 1960s (IFDC, 2004; Tilman et al., 2001) Year 1951–1952 1961–1962 1970–1971 1980–1981 1990–1991 2000–2001 2002–2003 2020–2021 2050–2051

N (106 Mg)

P (106 Mg)

K (106 Mg)

Total (106 Mg)

<10.0 11.6 31.8 60.8 77.2 80.9 84.7 135.0 236.0

NA 10.9 21.1 31.7 36.3 32.5 33.6 47.6 83.7

NA 8.7 16.4 24.2 4.5 21.8 23.2 NA NA

NA 31.2 73.3 116.7 138.0 135.2 141.6 NA NA

NA: Data not available.

The Haber‐Bosch process for the production of ammonia indicates an emission of 0.375 moles of C per mole of N produced (Schlesinger, 1999): 3CH4 þ 6H2 O ! 3CO2 þ 12H2 12H2 þ 4N2 ! 8NH3 The CO2 released during the production of N fertilizer has high hidden C costs. Indeed, 1 kg of N fertilizer leads to emission of 0.86–1.3 kg of CO2–C in production, packaging, transport, and application (Lal, 2004a).

C. THE PHOSPHORUS CYCLE Several anthropogenic activities have impacted the P cycle (Bennett et al., 2001; Howarth et al., 1995; Tiessen, 1995). Important among these are fertilizers manufactured from P‐bearing rocks and other geological formations, and concentration in animal feeds, agricultural products, and animal and human wastes. These activities have a strong impact on the global P cycle (Schlesinger, 1997; Smil, 1990). Bennett et al. (2001) analyzed the impact of anthropogenic perturbations on the global P cycle. The data in Table XIV show drastic increase in P storage in world soils and water bodies, primarily due to fertilizer use.

VI.

FOOD DEMANDS FOR THE WORLD’S GROWING POPULATION

The adoption of Green Revolution technologies since 1960s led to increase in agricultural production at a rate higher than that of the population growth (Alexandratos, 1995). There have been drastic increases in grain yields of

84

RATTAN LAL Table XIV Anthropogenic Influences on the Global P Cycle (Recalculated from Bennett et al., 2001)

Activity/process Rock weathering Mining Change in storage in soils and water Atmospheric output Fluvial drainage

Preindustrial (106 Mg)

Year 2000 (106 Mg)

10–15 0 1–6 1 8

15–20 18.5 10.5–15.5 1 22

corn (120%), rice (109%), and wheat (152%) during the last four decades of the twentieth century (Table XV). Consequently, per capita food production increased despite the rapid increase in population (Table XVI). However, the per capita production peaked in 1990 at 335 kg and has progressively decreased during 1990s. Per capita grain production was 324 kg in 1996, 316 kg in 1998, and 303 kg in 2000. The future increase in population, however, is projected to occur mostly in developing countries where natural resources (soil and water) are already under great stress. Cassman et al. (2003) estimated that global cereal demand (rice, wheat, and maize) will increase from 1657 million Mg in 1995 to 2436 million Mg in 2025 at the mean rate of 1.29% per year. To meet this demand, the mean grain yield of these cereals will have to be increased from 3.21 Mg ha1 in 1995 to 4.38 Mg ha1 in 2025 at the mean rate of 0.98% per year. The projected rate of increase takes into account the possibility of increase in the area under cereal cultivation from 506 Mha in 1995 to 556 Mha in 2025, with an annual rate of increase of 0.31% per year (Cassman et al., 2003). Despite the gains in global mean average crop yields (Table XV), grain yields of cereals in developing countries are still low. The data in Table XVII show the range of yield of wheat from 0.8 Mg ha1 in Kazakhstan to 7.8 Mg ha1 in the United Kingdom. Similarly, the yield of corn (maize) ranges from 1.3 Mg ha1 in Nigeria to 9.4 Mg ha1 in Italy. There are indeed many countries in which there is a large gap between the ecologically attainable yield and actual yield (Table XVIII). Indeed the actual grain yield of wheat is closer to the attainable grain yield in only three EU countries (Denmark, United Kingdom, and France). Thus, there is a large potential of increasing production by narrowing the yield gap through alleviation of specific constraints. Ecologically attainable crop yield is determined by solar radiation, temperature, genotype, and crop canopy. The diVerence between the actual and attainable yields (i.e., the yield gap) is determined by two factors (Cassman et al., 2003). Gap 1, of a lower magnitude, depends on the water supply through irrigation and rainfall. Gap 2, of a larger magnitude, depends on other limiting factors such as water,

WORLD SOILS AND THE ENVIRONMENT

85

Table XV Trends in Global Mean Yield of Principal Crops (Modified from Clay, 2004) Mean yield (Mg ha1) Crop

1961

1970

1980

1990

2000

Percentage increase from 1961 to 2000

Corn Rice Sorghum Soybean Sugarcane Wheat

1.94 1.87 0.89 1.13 50.3 1.09

2.35 2.38 1.13 1.48 54.8 1.49

3.16 2.75 1.20 1.60 55.3 1.86

3.68 3.54 1.37 1.90 61.6 2.56

4.27 3.90 1.38 2.18 64.1 2.74

120 109 55 93 28 152

Table XVI Total and per Capita Grain Production in the World Between 1950 and 2000 (Modified from Kondratyev et al., 2003) Year

Total grain production (106 Mg)

Per capita grain production (kg)

1950 1960 1970 1980 1990 2000

631 824 1177 1430 1769 1840

247 271 311 321 335 303

nutrients, weeds, pests, and so on. The data on actual and attainable yields of wheat and rice in India are shown in Table XIX. In comparison with the mean national yield in 1993–1995, the potential to increase yield is 61% in wheat and 91% in rice. Therefore, adoption of RMPs can narrow the yield gap and increase food production drastically. Wild (2003) observed that in the developing countries the attainable yield of cereals is 4.0 Mg ha1 compared to actual yield of 2.5 Mg ha1 (1993–1995) in wheat and 5.40 Mg ha1 compared with 2.86 Mg ha1 in rice (Table XX). Bridging this yield gap can be important especially in large countries such as China, India, Brazil, and so on. The data in Table XX also show that the actual yield of cereals in 2000 of 2.64 Mg ha1 will have to be increased to 3.60 Mg ha1 by 2025 and 4.30 Mg ha1 by 2050 assuming that food habits of the population do not change. The required cereal grain yield will be 4.40 Mg ha1 by 2025 and 6.0 Mg ha1 by 2050 if there is a strong shift in food habits involving animal‐based products (Table XX). Such a strong increase in crop yield (agronomic productivity) necessitates

86

RATTAN LAL

Table XVII DiVerences in Average Yields (Between 1996 and 2000) of Wheat and Corn in Developed and Developing Countries (Recalculated from Bruinsma, 2003) Wheat Country United Kingdom Germany Denmark France Egypt Hungary Poland Italy China United States Spain India Romania Ukraine Argentina Canada Pakistan Turkey Australia Iran Russia Kazakhstan

Corn 1

Yield (Mg ha )

Country

Yield (Mg ha1)

7.8 7.3 7.1 7.0 6.0 3.9 3.4 3.2 3.1 2.7 2.6 2.6 2.6 2.5 2.4 2.4 2.2 2.1 2.0 1.6 1.4 0.8

Italy Spain France United States Canada Egypt Hungary Argentina Yugoslavia China Thailand Romania Brazil Indonesia South Africa India Philippines Nigeria

9.4 9.1 8.6 8.2 7.4 7.3 6.0 5.0 4.0 3.8 3.5 3.0 2.6 2.6 2.5 1.7 1.6 1.3

a judicious management of soil and water resources, and widespread adoption of RMPs in all developing countries.

VII. STEWARDSHIP OF SOIL AND WATER RESOURCES There is a strong need for stewardship of soil resources (Leopold, 1963). Not only between one‐third and one‐half of the land surface has been transformed by anthropogenic activities (Vitousek et al., 1997), humans appropriate 10–55% of all terrestrial photosynthesis products (Rojstaczer et al., 2001). Therefore, the rate of extinction of species is drastically increased by the continuous increase in human demands as natural resources and net primary productivity. Vitousek et al. (1997) estimated that rates of species extinction are now on the order of 100–1000 times those of the prehistoric era. At present, 11% of the remaining birds, 18% of the mammals, 5% of fish,

WORLD SOILS AND THE ENVIRONMENT

87

Table XVIII Actual and Agroecologically Attainable Yield of Wheat (Average of 1996–2000) in Some Selected Countries (Recalculated from Bruinsma, 2003) Country

Ecologically attainable yield (Mg ha1)

Actual yield (Mg ha1)

7.60 7.03 7.00 6.73 6.70 6.50 6.41 6.30 6.25 5.84 4.84 4.50 4.50 4.20 4.20

7.25 3.40 7.25 7.83 7.30 3.30 3.83 2.50 2.40 2.83 2.10 1.25 2.50 2.20 2.00

Germany Poland Denmarka United Kingdoma Francea Italy Hungary Romania Ukraine United States Turkey Russia Canada Argentina Australia

a Actual grain yields of wheat in Denmark, United Kingdom, and France are either close to or even higher than the attainable yields under rainfed high input farming.

Table XIX Actual and Attainable Yields of Wheat and Rice in India (Modified from Bruinsma, 2003) Year 1972–1974 1984–1986 1993–1995 Attainablea

Wheat yield (Mg ha1)

Rice yield (Mg ha1)

1.26 1.95 2.48 4.00

1.63 2.21 2.83 5.40

a Attainable yield is weighted average of irrigated and rainfed conditions.

and 8% of plant species are threatened with extinction (Vitousek et al., 1997). The magnitude of agriculturally driven environmental change (Schlesinger et al., 2001) must be minimized through using recent advances in agropedology (Lin et al., 2005), adopting RMPs, using input judiciously, and restoring value of world’s degraded lands (Dailey, 1995). Therefore, a judicious and scientific management of soil resources is essential both to attaining a food‐secure world and to increasing biodiversity. A food‐ secure world is the one in which every person is assured of access at all times to the food required to lead a healthy and productive life. The basic strategy to achieve food security is to manage constraints to supplies of production

88

RATTAN LAL Table XX Average Yield of Cereals Required in Developing Countriesa by 2025 and 2050 to Meet the Required Production with No Increase in Area (Adapted from Wild, 2003)

Parameter Present (2000) Required a. 2025 (i) þ35%b (ii) þ62% b. 2050 (i) þ58%c (ii) þ121%

Cereal grain yield (Mg ha1)

Cereal production (106 Mg year1)

2.64

1267

3.60 4.40

1706 2045

4.30 6.00

1995 2786

a

Africa, Asia, South America, and Asia (excluding Japan). Thirty‐five percent and sixty‐two percent increase above the present level in 2025 estimated to account for increase in population and change in food habits. c Fifty‐eight percent and one hundred twenty‐one percent increase above the present level in 2050 and estimated to account for increase in population and change in food habits. b

inputs, so that the yield gap can be narrowed. The goal is to deliver nutrients, water, and oxygen directly to plant roots at the most critical stage of growth through precision farming and agricultural intensification. Similarly, the global hot spots of biodiversity must be protected and degraded land restored for nature conservancy to reduce the risk of extinction of endangered species. The basic strategy to increase biodiversity is to alleviate the environmental consequences of anthropogenic use of soil and water resources. The urgent need for judicious management of soil and water resources is nowhere more than in SSA. The roots of agrarian stagnation in SSA and the attendant food deficit must be addressed. Soil nutrient depletion, an apparent cause of low crop yields (Sanchez et al., 1997; Smaling et al., 1997), is only one of the factors responsible for low agronomic productivity. While the use of chemical fertilizers is important to increasing production (Quinones et al., 1997), the eVectiveness of fertilizer use can only be achieved through water conservation and improvements in soil quality. Otherwise, the Green Revolution, if at all occurs, will either be limiting (Holme´n, 2005a) or short‐lived indeed. Soil degradation, especially biological degradation caused by severe depletion in SOC pool, is a principal cause of soil degradation and must be addressed. Crop residues and animal dung, systematically removed for use of fodder and household fuel, must be returned to soil as amendments. Identifying alternative sources of fodder and clear cooking fuel is a high priority of South Asia and SSA. Agricultural intensification in Africa will have to be based on a holistic approach involving restoration of soil quality through adoption of conservation‐eVective measures, enhancement of available soil water in the root zone through in situ moisture conservation and supplemental irrigation;

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increase in SOC pool by return of crop residues as mulch through conversion of traditional tillage to no‐till farming along with application of compost, manures, and other organic amendments; and use of integrated nutrient management options to achieve a positive‐nutrient balance in soils. Over and above these measures, adoption of input‐responsive varieties, resistant to pests and drought, is also essential. In this regard, analyses of factors (e.g., social, economic, political) are essential to understanding the barriers to agricultural intensification in SSA (Holme´n, 2005a,b). Lal (2006) reported that increasing SOC pool is essential to improving agronomic yields. The data in Table XXI show that improving SOC pool can advance food security in SSA by enhancing production of grains by 3.3–5.4 million Mg year1 and that of roots and tubers by 3.0–6.2 million Mg year1. Total potential increase in food production, through improvement in soil quality by increasing SOC pool, of 6.3–11.6 million Mg year1 is enough to meet the current and projected food deficit in SSA. While there are numerous uncertainties in achieving these production gains, the adverse impacts of drought and nutrient deficit can be strongly minimized through improvements in soil quality brought about by increase in quantity and quality of the SOC pool. Table XXI Increase in Grain and Root/Tuber Production in Africa Through Increase in SOC Pool in the Root Zone by 1 Mg C per hectare per year (Adapted from FAO, 2005; Lal, 2006)

Area (Mha)

Current yield (kg ha1)

Increase in yield with increase in SOC pool (kg ha1 year1)

Total increase in production (106 Mg year1)

(a) Grains Corn Rice Sorghum Millet Beans Soybeans Total

26.6 7.8 21.6 20.1 3.1 0.9 80.1

1677 2211 862 670 668 973 7061

30–50 10–30 80–120 30–50 40–60 20–30 210–340

0.8–1.30 0.08–0.23 1.7–2.6 0.6–1.0 0.1–0.2 0.02–0.03 3.3–5.4

(b) Roots and tubers Cassava Yam Sweet potato Taro Total

12.3 4.3 2.5 1.6 20.7

9000 8900 4500 5000 27,400

200–400 100–200 50–100 60–120 410–820

2.4–5.0 0.4–0.8 0.1–0.2 0.1–0.2 3.0–6.2

100.8

34,461

620–1160

6.3–11.6

Crop

Grand Total

Data of increase in crop yield with increase in SOC pool are gross estimates. There are few if any studies relating crop yields to SOC pool in the root zone for soils of SSA. Such data are especially lacking for roots and tubers and are a researchable priority.

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VIII. CONCLUSIONS Humans have impacted soils and ecosystems significantly and in some cases irreversibly. Major impact has been on transformation of natural into managed ecosystems leading to conversion of large areas of forest, savannas, and grass/prairies into agricultural and plantation type land uses. Human activities have caused extinction of numerous animal and plant species. Irrigated agriculture is a principal user of the world fresh water resources. There have been major disruptions in cycling of water, C, N, P, and other elements. Long‐term use of extractive farming practices has caused severe and widespread problems of soil degradation by erosion and nutrient depletion along with salinization and biological degradation. Widespread deforestation and soil cultivation for 10–12 thousand years, along with fossil fuel combustion since the onset of industrial revolution, have drastically impacted the atmospheric concentration of CO2 and other greenhouse gases, with long‐term adverse impacts on quality of soil and water resources. However, the demand for food production has to be met even with shrinking arable land area and diminishing water resources. Similar to population, increase in future food demand is also projected to be more in developing countries of Asia, Africa, South and Central America, and the Caribbean. These are also the regions where soil and water resources are already under great stress, and the resource‐poor farmers are neither able to aVord nor sure of the eVectiveness of prohibitively expensive and energy‐ intensive input (e.g., fertilizers, pesticides, irrigation). Yet, there are no viable alternatives to agricultural intensification. The latter involves restoration and enhancement of soil quality through adopting conservation‐ eVective measures, recycling of crop residues, and land application of other biosolids, creating positive‐nutrient balance, improving activity and species diversity of soil fauna, and enhancing plant‐available water in the root zone through in situ conservation of rain and supplemental irrigation. Although fears about the adequacy of soil resources to feed human population go back to Malthus’s essay on population in 1798, supporters of Malthusian concept will always be proven wrong provided that soil resources are restored, improved, and used rather than taken for granted. Sustainable use of soil resources does not depend solely on the use of fertilizers, irrigation, improved varieties, and even no‐till and mulch farming systems. It depends on the adoption of a holistic approach, in which all recommended components are combined in synergism. Judicious use of soil and water resources, based on soil‐specific recommended technologies, is the guiding principle. Such technologies must be validated under local biophysical and socioeconomic conditions. Humans must avoid the trap of adopting ‘‘technologies without wisdom.’’

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MITIGATION AND CURRENT MANAGEMENT ATTEMPTS TO LIMIT PATHOGEN SURVIVAL AND MOVEMENT WITHIN FARMED GRASSLAND David M. Oliver,1 A. Louise Heathwaite,1 Chris J. Hodgson2 and David R. Chadwick2 1

Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom 2 Manures and Farm Resources Team, Institute of Grassland and Environmental Research, North Wyke Research Station, Okehampton, Devon EX20 2SB, United Kingdom

I. Introduction II. Sources of Pathogens in the Farm Environment A. Manures Spread to Land B. Grazing Animals C. Manure Spreading Versus Grazing as a Source D. Farmyards and Animal Feeding Operations III. Reducing Pathogen Numbers via Manure Management A. Solid Manures B. Liquid Manures C. Livestock Welfare IV. Land Management Strategies to Limit Pathogen Transfer from Land to Water A. Measures to Reduce Pathogen Mobilization from Land B. Measures to Reduce Pathogen Delivery to Water V. Synthesis and Concluding Remarks A. Conceptualizing Microbial Mitigation B. Conclusions Acknowledgments References

To successfully curb microbial contamination of surface waters we need to understand, and holistically evaluate, the range of mitigation strategies that have been designed to protect watercourses from nonpoint agricultural sources, so as to use them to best eVect. A cost‐eVective and pragmatic approach is to improve knowledge of farm management operations capable of (1) reducing potential pathogen numbers in livestock manures and (2) reducing subsequent 95 Advances in Agronomy, Volume 93 Copyright 2007, Elsevier Inc. All rights reserved. 0065-2113/07 $35.00 DOI: 10.1016/S0065-2113(06)93003-X

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D. M. OLIVER ET AL. transfer (through the environment) of fecal microorganisms derived from livestock manures that are recycled to land. This will prove important for supporting farmer decision making, devising policy, and implementing mitigation practices to limit fecal microorganism delivery from land to water. In this chapter, we consider a diverse suite of manure, animal, and land management options that range from simple manure‐composting techniques and the use of slurry additives, through to land management engineering approaches and the design of constructed wetlands to protect watercourses from microbial contamination. The choice as to which strategy to use, if any, is ultimately made by the farmer and is likely to be influenced by a complex range of factors which may include, for example, tradition, convenience, and farm economics. We conclude that the inherent complexity associated with heterogeneous landscapes confounds the likelihood that a single management strategy will provide complete protection of receiving waters from microbial contamination. Instead, the coupling of diVerent strategies alongside improved education and considerable vigilance by farmers and landowners is needed for a more sustainable approach to limiting diVuse microbial (and, crucially, other contaminant) pollution from agriculture. # 2007, Elsevier Inc.

I. INTRODUCTION In agricultural catchments, the export of microbial contaminants from diVuse sources occurs when bacteria, protozoa, and viruses are mobilized from locations within or on soil and then transported to watercourses. This potential for microbial pollution of surface waters is exacerbated within farmed catchments (Crowther et al., 2001, 2002, 2003; Kay et al., 1999; Pickup et al., 2005; Wither et al., 2005) largely as a result of the recycling of livestock excreta to land either by grazing animals or applications of organic manures. The ramifications are that agricultural practices have the potential to contaminate surface waters with enteric microorganisms, a proportion of which may be pathogenic to humans. Thus, water‐borne illness and the associated ease of transmission of a variety of pathogenic microorganisms via watercourses remain of significant importance despite the potential risks associated with land applied livestock manures having been recognized for more than 100 years (Gerba and Smith, 2005). In Europe, legislation such as the Bathing Waters Directive (76/160/EEC) (Anon, 1976) has acted to drive improvements in sewage treatment, sewerage infrastructure, and compliance with mandatory bathing water quality regulations. Similarly, in the United States, the microbiological quality of beach water is required to be of a safe standard as established by the USEPA. Unfortunately, noncompliance with microbial guidelines can still occur at designated bathing sites, particularly after high rainfall, and this has been attributed, in part, to diVuse sources contributed from agricultural land (Crowther et al., 2002).

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In winter months or for significant summer storms, heavy rainfall primarily drives high water‐flow conditions, and so the transport of fecally derived microbes through catchments can be of a highly episodic nature (Wilkinson et al., 2006), which adds to the complexity of tackling catchment scale microbial pollution of watercourses. DiVuse pollutants sourced from farmed areas are likely to come under increased scrutiny following the implementation of both the EU Water Framework Directive (2000/60/EC) (Anon, 2000) and cross‐ compliance associated with Common Agricultural Policy (CAP) reform. Furthermore, in the case of European legislation, the Bathing Waters Directive is soon to be updated, with microbial standards set to get tougher and compliance at bathing beaches predicted to fall as a result (Jones, 2002). In a move to curb the potential increase in designated bathing waters failing to meet future mandatory standards, a cost‐eVective and pragmatic approach is required to improve understanding of farm management operations capable of (1) reducing potential pathogen numbers in livestock excreta and manures and (2) reducing subsequent transfer (through the environment) of fecal microorganisms derived from livestock excreta that are recycled to land. This will prove important for supporting farmer decision making, devising policy, and implementing mitigation practices to limit fecal microorganism delivery from land to water. Figure 1 synthesizes these points in a basic conceptual framework. The aims of this chapter are twofold. First, to assess current measures (available to farmers and landowners) capable of limiting and reducing fecal microorganism numbers within manures, which accumulate on farms (i.e., targeting the source of pathogens). Second, to assess proactive land management options capable of limiting microbial movement from grassland soils to watercourses. As an initial strategy, mitigation eVorts can attempt to limit the mobilization of fecally derived contaminants once they are received by land, and a secondary option is to focus eVorts on limiting the delivery of manure‐borne microbes to a watercourse through ‘‘disconnecting’’ hydrological connectivity. Mitigation eVorts can therefore focus on source, mobilization, and delivery aspects of pathogen cycling through the environment, and each of these components is dealt with in this chapter in accordance with a ‘‘source‐mobilization‐delivery’’ concept (Fig. 2). The conceptual model shown in Fig. 2 has been adopted for many types of contaminants and is as equally applicable for microbial pollutants.

II. SOURCES OF PATHOGENS IN THE FARM ENVIRONMENT Within this chapter, the term manure will be used when describing both solid and liquid animal manures, slurry will refer specifically to liquid manures, and the term solid manure will be used generically to describe

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Farmer decision-making D Farm C

Livestock manure treatment

Livestock manure treatment

B Land and animal management

A Land and animal management

Watercourse

Farmer decision-making Figure 1 Approaches available to limit delivery of potential pathogens to receiving waters. Route A represents no vigilance on the part of the farmer, any reduction is a result of environmental and microbial processes. Route B suggests that land management techniques are employed such as fencing oV watercourses from grazing animals or applying manures at acceptable times via appropriate application methods. Some farms may choose route C and compost or process animal manures to the detriment of microbial populations. Farms showing a willingness to protect the environment are likely to combine benefits of both land and animal manure management for maximum eVect (route D). An overarching influence is the decision‐making process embedded within individual farmers. The weight of the line associated with each route denotes a simple level of relative risk of potential contamination of adjacent watercourses.

cattle and pig farmyard manure (FYM) and poultry manure. A common misdemeanor is to perceive and refer to such animal by‐products as animal wastes. This is misleading and instead we should recognize manures to be a farm resource (Burton and Turner, 2003). Although a valuable farm resource, excretions from livestock can be a substantial source of pathogens to the environment; a study in the United Kingdom has suggested that over 30% of livestock manures (derived from cattle, pigs, sheep, and poultry) contain at least one form of microbial pathogen (Hutchison et al., 2004a). The survival of fecally derived microorganisms within farm manures has been reviewed previously by Oliver et al. (2005a). Consequently, the following evaluation focuses on sources of potential pathogens commonly found within farm environments and agricultural land.

MITIGATION TO LIMIT PATHOGENS IN GRASSLANDS

Pathogen status en-route from source to end-point receptor

1. Source For example, manure applied to land or animals grazing

99

Potential mitigation option

Storage/batch storage Composting Thermal processing (drying) Animal health Dietary supplementation Anaerobic digestion Oligolytic treatment Slurry additives Reduce pathogen numbers in source

2. Mobilization For example, runoff facilitated transfer via soil channel

3. Delivery For example, hydrological connectivity to watercourse

Manure application techniques Farmer vigilence

Limit movement of pathogens once applied to land

Filter strips, riparian buffers, and grassed waterways Land management engineering Fenced waterways Constructed wetlands Farm ponds Limit pathogens reaching a watercourse

Figure 2 Conceptual model of pathogen stage‐transition through the environment via source, mobilization, and delivery. Mitigation eVorts for preventing pathogen contamination of watercourses will target one or more of the three components of the source–mobilization– delivery model.

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A. MANURES SPREAD

TO

LAND

1. Slurry (Liquid Manure) Slurry is a relatively uniform mix of excrement and urine produced by housed livestock and collected in a liquid form (Chadwick and Chen, 2002) with a typical dry matter content ranging between 1% and 10% (Pain and Menzi, 2003). Slurry may also contain parlor washings, dilution water, and secretions from the animal’s nose, throat, blood, mammary gland, skin, and placenta (Pell, 1997). It flows under gravity and can be collected via slatted floor systems within animal housing, which empty into reception pits. This liquid manure is then spread to land to provide replenishment of nutrients for plant growth. Intensification of livestock agriculture in the United Kingdom has favored the production of slurry over solid manure because of the reduced use of bedding materials (Strauch and Ballarini, 1994). All European member states prevent the spreading of slurries within nitrate vulnerable zones (NVZs) during an autumn closed period in an attempt to protect watercourses. In the United States, animal feeding operations (AFOs) are regulated in accordance with farm size (based on ‘‘animal units’’), with larger AFOs constrained by greater regulation, based on the assumption that larger operations pose a greater pollution risk (Risse et al., 2005). Slurries contain a host of microbes that are derived from the gut of farm animals and accommodate a more uniform microbial distribution when compared with solid manure because of the greater mobility of microorganisms in this liquid material (Chadwick and Chen, 2002). There is noted to be seasonal variability in pathogen numbers found in slurries. As an example, higher counts of Camplyobacter have been recorded in cooler winter months within stored dairy slurry on farms in Lancashire, United Kingdom (Stanley et al., 1998). In the United Kingdom, slurry storage often consists of above ground cylindrical tanks (made either of steel or concrete) or slurry lagoons and is often a mixture of old material and newly deposited manure. Storage capacity varies with farming activity, financial investment, and the amount of rain water that is able to access the store. Covered slurry stores are advantageous because less precipitation is able to contribute to the accumulation of the liquid fraction of the slurry, limiting both the amount of manure required for recycling back to land and the potential for overflowing. Improper sealing of all valves or a crack developing in the store wall could potentially lead to water and soil contamination of extensive proportions. An alternative system to slurry storage tanks are lagoons. These comprise a pit in the ground and can be either lined with concrete or be earth walled. Similarly, lagoons are generally open to rainfall.

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Solid Manure (Farmyard Manure)

In contrast to slurry, solid manure cannot flow under gravity. However due to its solid form it is easily stacked. Specifically, FYM is made up of livestock excretions combined with a bedding material (generally straw). It is common practice for broiler chickens to be bedded on woodshavings, thus generating broiler litter. In the short term, solid manure is generally piled into heaps that accumulate within the farmyard though Nicholson et al. (1999) suggested that only 21% of solid manure is stored permanently on concrete in United Kingdom and Wales. More often, solid manure is transferred to a field and stored as a field heap until spread to land. Within United Kingdom and Wales, the practice of leaving uncovered manure heaps in fields until a more appropriate time for application (Fig. 3A) is common, and this method accounts for 79% of solid manure storage (Nicholson et al., 1999). This acts to free up space within farmyards and can improve the convenience of spreading manure at a later date. However, high‐intensity rainfall that occurs prior to spreading may provide the driving force to facilitate the transfer of microbes from uncovered manure heaps to nearby watercourses. Consequently, careful thought needs to be given as to where to best situate field heaps in order to minimize the risk of water pollution. The solid fraction of the manure heap [Fig. 3A (i)] can generate a liqueur that seeps out of the bottom of the manure pile [Fig. 3A (ii)], and this may either infiltrate slowly through the soil profile and provide a vehicle for vertical microbe transfer or transfer over the surface of sloping land. A large liquid

A

B

(i)

(i)

(ii)

(ii)

Figure 3 Typical examples of temporary field stores on farms in North Devon, United Kingdom. Photo (A) shows (i) an uncovered manure heap with (ii) resulting manure liquor drainage, and photo (B) shows a dirty water soak‐away [(i) solid and (ii) liquid fraction] (photograph A taken by D. Oliver, photograph B taken by C. Hodgson).

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fraction can be generated when manure heaps are left uncovered outside, and so good agricultural practice would require that such heaps are not located above field drains or within 10 m of a watercourse (MAFF, 1998).

3.

Dirty Water

Any form of water that has been contaminated with feces or urine may be termed dirty water and is generally of a dry matter consistency of less than 3%. Dirty water can accumulate following the washing down of agricultural machinery, parlor floors, and concrete yards areas but also following the generation of runoV across hard‐standings used by livestock. In particular, large quantities of dirty water can accumulate on dairy farms in areas of high rainfall (Smith et al., 2001). Additionally, seepage from slurry, FYM, and silage stores often drains to dirty water stores on farms. Weeping wall lagoons can be used to fractionate oV a liquid component of slurries and solid manures, and this liquid fraction, containing greater nutrient and organic matter concentrations than dirty water, is then often pumped from a collection tank to a sprinkler system that distributes this liquid to land. Pathogens, such as Escherichia coli O157, Campylobacter, and Salmonella, have been reported to survive for up to 3 months in stored dirty water (Nicholson et al., 2005) highlighting that even though this is a more dilute form of farm manure, it can represent an additional source of pathogens and fecally derived microbes to agricultural land. Codes of good agricultural practice (CoGAP) stipulate that pollution to surface water caused by dirty water can be minimized if facilities are in place to store and manage this farming by‐product and if warning devices and automatic cut‐oVs for sprinkler devices are checked and maintained (MAFF, 1998). Although sprinkler systems are a common method of distributing dirty water to land, an alternative approach adopted by some farmers is to accommodate a dirty water soak‐ away within the farm (Fig. 3B). In doing so, dirty water is collected and then pumped from a holding lagoon to another field and left to soak‐away through the natural filter of the soil matrix. The solid [Fig. 3B (i)] and liquid [Fig. 3B (ii)] components of the dirty water are separated during the soak‐ away process. Clearly, if combined with heavy rainfall, and if situated in a location whereby surface runoV could facilitate transfer, poorly designed soak‐aways represent a significant risk to surface water quality.

B. GRAZING ANIMALS All grazing animals defecate onto pasture, and their deposited feces contain large quantities of enteric bacteria and potentially a number of

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pathogenic microbes. The volume of excreta deposited to pasture varies with animal type, size, and age. Typical volumes of excreta voided by a 550‐kg dairy cow, 500‐kg beef cow, 180‐kg beef bullock, 65‐kg mature sheep, and 35‐kg lamb are estimated to be 53, 32, 13, 4.1, and 1.1 liters day
1, respectively (MAFF, 1998). Pasture that becomes contaminated with feces from grazing animals may facilitate the spread of a pathogen throughout uninfected animals should other grazers ingest microbes from the sward (Judge et al., 2005). Thelin and GiVord (1983) and Avery et al. (2004b) have suggested that fecal deposits appear to provide a protective niche for the long‐term survival of indigenous bacteria, and the physical crusting of feces can contribute to the lengthy persistence of some bacteria outside the animal gut. Grazing‐rejection patches which result from a higher sward height around deposited dung on grazing fields (Bao et al., 1998; Norman and Green, 1958) can increase the shade surrounding feces and may bring some relief from the detrimental eVects of UV radiation to potentially prolong bacterial survival on pasture (Meays et al., 2005). While cattle, both dairy and beef, are considered important reservoirs of pathogenic E. coli, a comparative study identified that for fresh manures from cattle and sheep, E. coli O157 had an incidence of 13.2% and 20.9% within bovine and ovine manure, respectively (Hutchison et al., 2004b). The same study identified that within fresh manures, sheep were found to accommodate a higher incidence of Salmonella, Campylobacter, Cryptosporidium parvum, and Giardia intestinalis than cattle (Hutchison et al., 2004b). In sheep, Cryptosporidium has been identified as having an increasingly important role in neonatal diarrhea syndrome and is currently associated with high morbidity rates for these animals (de Graaf et al., 1999). While farmers can take steps to limit this occurrence by using prelambing vaccinations, this may lead to diVerent risks associated with contamination associated with veterinary medicines reaching water bodies or contaminating soils. A study in Spain found that the most frequent etiologic agent involved in outbreaks of diarrhea in lambs was C. parvum (65% of outbreaks and 45% of the individuals) (Munoz‐Fernandez et al., 1996), and Xiao et al. (1993) suggested that ewes were an important source of infection for lambs following an outbreak of diarrhea in neonatal lambs in northern Ohio where 100% of newborn lambs were aVected. Similarly, colonized neonatal lambs have been reported to have excreted in excess of 6.5  107 viable Cryptosporidium oocysts per gram of feces in the first 10 days of birth (Svoboda et al., 1997). In contrast, a study has questioned the role of sheep as important zoonotic reservoirs for Cryptosporidium and Giardia (Ryan et al., 2005) following findings that around 98% and 76% of Cryptosporidium and Giardia isolates respectively, isolated in a study, were not known to infect humans. However, a limitation of the Ryan et al. (2005) research was that preweaned lambs were excluded from the study, yet it is acknowledged that C. parvum

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may be the most prevalent species in preweaned lambs. As a final comment, it should be recognized that livestock markets can facilitate contact between infected herds, and the subsequent transportation of animals suggests that widespread dissemination of microbes is feasible (Fe`vre et al., 2006).

C.

MANURE SPREADING VERSUS GRAZING

AS A

SOURCE

In comparing sources of fecal microbes derived from manure spreading and animal‐grazing periods, Fig. 4 shows a conceptual model that contrasts the input and decline of E. coli, on pasture, for a single broadcast slurry application versus a single grazing season. The profile of E. coli decline within each livestock manure type is simplified but based on literature (Oliver et al., 2005b, 2006). The initial number of E. coli on pasture is shown to be high for slurry (Fig. 4; Scenario A) because the livestock manure is applied to a greater area of pasture than that covered by fecal deposits at time zero (i.e., the beginning of the grazing season). By contrast, the grazing season (Fig. 4; Scenario B) is shown to provide an accumulating E. coli input to pasture via sporadic fecal deposition over a greater time‐period than a single slurry application. Numbers of E. coli on pasture then decline following the removal of grazing cattle at the end of the grazing season. Clearly the ‘‘risk window’’ available for surface‐water contamination is more limited for a one‐oV manure application to pasture than for the grazing season. In addition, the loading of land with E. coli derived from slurry is likely to be considerably lower if batch‐stored, as opposed to fresh slurry is applied to land (Hutchison et al., 2005a) (see Section III.B.1). The increased ‘‘risk window’’ for potential bacterial contamination of surface waters associated with grazing is also likely to coincide with the bathing season (May 15 to September 30) in Europe. Therefore, a summer storm that occurs several months into a grazing period may have considerable impact on bacteriological quality of bathing water located near agricultural land at a time of critical importance with respect to water‐quality monitoring. A drained clay loam plot experiment in Scotland found that the risk of E. coli loss from land grazed by sheep exceeded that associated with slurry applications during autumn/spring and wet summer conditions (Vinten et al., 2004a). Complementary findings have been reported by Soupir et al. (2006), whereby feces deposited on pasture by grazing livestock had a greater potential to contribute high bacterial concentrations to watercourses than the application of liquid dairy manure. However, factors such as stocking density, grazing‐season duration, and manure‐application rates will all play a role in determining the overall microbial‐pollution potential to nearby receiving waters. The conceptual model shown in Fig. 4, along with the two studies described here, highlight that it is essential to focus mitigation

Change in number of E. coli on pasture

A Low High B

End of grazing season

Low

Increasing number of days since slurry applied to pasture/ cattle introduced to graze pasture

Potential for E. coli transfer to surface waters given appropriate hydrological drivers High

Low

Figure 4 Conceptual diagram highlighting potential change in E. coli numbers within slurry applied (A) and fresh feces deposited (B) to pasture. The change in the potential for bacterial contamination of surface waters, given appropriate hydrological drivers (e.g., a storm event), is shown. The black lines depict generalized die‐oV curves.

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eVorts on losses from grazing animals in addition to losses attributed to manure spreading.

D.

FARMYARDS

AND

ANIMAL FEEDING OPERATIONS

A survey in United Kingdom and Wales of 471 dairy farmers and 515 beef farmers indicated that in general dairy farms generate manures in the form of 65% slurry and 35% FYM compared with 80% FYM and 20% slurry on beef farms (Smith et al., 2001). Farmyards may constitute a significant source of microbial pathogens, largely because they are often the hub of farming activity and accommodate retention systems for holding the manures that are deposited within the farmyard. This is particularly pertinent for dairy farms whereby a single dairy cow (550 kg) is likely to produce 9.7 m3 of liquid manure over a 6‐month housing period compared with 5.8 m3 from a single 500‐kg beef cow (Burton and Turner, 2003). Farmyards can accommodate milking parlors, housed animals, and manure storage facilities, and these tend to be structured on hard‐standings of concrete or a nonporous material that can result in runoV of contaminated water at a rapid rate following storm events (Edwards and Merrilees, 2003). The farmyard will often be host to animal movements or act to confine animals in limited space, and can be used to allow daily exercise for dairy cows, which often need to be kept close to the milking parlor (Lewis et al., 2005). Stressful conditions associated with movement and limited space may result in high quantities of manures being deposited by animals (Friend, 1991). Farmyards are always drained to some extent, and this may allow for direct hydrological connectivity from the farmyard to a nearby watercourse. Goss et al. (1994) claimed that in Canada, NH3 and bacteria contributions to watercourses are of lesser concern than phosphorus (P) because their release from storage facilities could be controlled by appropriate management practices. Clearly then, poor management of stored manures and animals confined within the farmyard will result in a more substantial threat of environmental pollution. In the United States, AFOs are a significant potential source of microbial pathogens, generating around 100 more waste than wastewater treatment plants (Gerba and Smith, 2005), and that does not include the manure produced by grazing animals. Leaking septic tanks are often regarded as potential point sources of pollution, and they can represent an additional source of fecal microbes that originate close to the farmyard. Direct evidence has shown, using biochemical fingerprinting of fecal indicator bacteria, that septic systems can at times fail and then act as a potential source of pathogens to surface waters (Ahmed et al., 2005). Septic tank leakages are not specific to farms though, as many rural homes would also accommodate such domestic waste

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systems. Additionally, within catchments, other contributions to microbial loadings of watercourses are likely to arise from human sewage discharges and wildlife and urban drainage.

III.

REDUCING PATHOGEN NUMBERS VIA MANURE MANAGEMENT

Manure that undergoes a thorough treatment process prior to land application can be an eVective and safe organic fertilizer, whereas those manures that are not treated represent a potential microbial hazard if combined with hydrological connectivity to a watercourse. An evaluation of current methods used to promote pathogen and fecal microbe die‐oV in livestock manures revealed a varied selection of approaches, each with associated costs and benefits. Techniques range from simple and cheap pragmatic approaches of manure management through to complex techniques that require high capital and running costs and which, in some cases, would require external contractors, rather than a solitary farm, to deal with livestock manures. Briefly, the methods addressed in Section III.A include manure storage, aeration techniques (liquid and solid composting), liming and the use of other slurry additives, oligolytic (or electrolytic) methods, pasteurization, anaerobic digestion techniques, and dietary supplementation. The choice as to which treatment to use, if any, is ultimately made by the farmer and is likely to be influenced by a complex range of factors which may include, for example, tradition, convenience, and farm economics.

A. SOLID MANURES 1.

Solid Manure Storage

In the United Kingdom, guidance is provided for the handling and storage of livestock manures via the Department for Environment, Food, and Rural AVairs CoGAP for protection of water (MAFF, 1998). In the United Kingdom, solid farm manures are typically stored for period of 3–6 months prior to land application (Smith et al., 2000). Storage is commonplace primarily because much manure is produced over winter while animals are housed and pasture is unavailable for grazing but also because collected manures cannot be recycled to land in one application in order to achieve the greatest benefit for the farmer and the land. Additionally, compliance with CoGAP would prevent the spreading of livestock manure to land under certain circumstances, for example, during or following heavy rainfall

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(MAFF, 1998)—though this does not necessarily mean such practices are strictly adhered to by all farmers because it is often diYcult to gauge the unpredictable nature of weather. Thus, storage of livestock manure on some farms is a necessity, and at the same time, manures can undergo an improvement in their microbiological quality through potential reduction of fecal microorganism numbers as a function of time. For those farms that are unable to store manures due to limited storage capacity, the alternative and sometimes more convenient option is that they are forced to spread straight to land (Smith et al., 2001). In doing so, the farmer bypasses a microbe‐ reduction period (related to time) and spreads fresh manure (containing higher concentrations of fecal microbes) onto pasture. The observed decline in pathogen numbers in stored solid manure over time is dependent on management and storage conditions (Nicholson et al., 2005), but it is generally understood that the microbial population in excreta experiences considerable change during storage. Factors influencing microbial fluctuations in solid manure include, for example, temperature (Himathongkham et al., 1999; Hutchison et al., 2005b), aeration (Forshell and Ekesbo, 1993), and competing microbes (Jones et al., 1977). Storage of solid livestock manures can result in heat‐generating composting processes, whereas, in contrast, untreated slurries stored in tanks or lagoons are likely to remain at ambient temperature. However, even at low temperatures, time will result in a general decline of microbes (Maule, 1999). Storage of solid manure heaps in locations exposed to UV radiation (Fig. 3A), such as in fields or farmyards without any protective covering, are also likely to experience a more rapid decline in the numbers of microbes because of the detrimental impact of sunlight. However, manure heaps may become saturated if exposed to rainfall, and this can result in poor conditions for facilitating eVective composting of solid manure (see Section III.A.2). Provided there is enough bedding material to allow good airflow then extended storage is not required for FYM, and in any case, manure heaps are often left in excess of 90 days due to normal farming practice, and this should be suYcient for significant pathogen reduction.

2.

Composting

Composting is an exothermic process that involves the decomposition of organic wastes within a warm, moist, aerobic environment via a suite of microorganisms (Forshell and Ekesbo, 1993) and which provides numerous advantages to manures. These can include: reduced odor (Hobbs et al., 2004) and biological oxygen demand (BOD) and reductions in manure volume (Burton and Turner, 2003) and nitrogen (N) control (Michel et al., 2004) alongside the potential for fecal microorganism reduction. Simple solid manure

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storage should result in composting, but by using manure management techniques, the eYciency of this process can be enhanced. The eYciency of any composting system is related to a number of variables, including, for example, straw content, moisture content, and the frequency of manure turning (Nicholson et al., 2000), and so not all composting is successful in (1) attaining high temperatures (55  C) and therefore (2) reducing fecal microbe numbers eVectively. The inactivation of pathogens is promoted when composting reactors are used, equipped with adequate insulation so that walls also reach high temperatures and prevent the formation of areas of low temperature (Vinneras et al., 2003). Composting is limited by oxygen presence, and so an adequate air supply is a prerequisite for microbes to decompress mass and avoid anaerobic conditions (Mohaibes and Heinonen‐ Tanski, 2004). Agitation of solid manure assists in supplying oxygen to the heap to promote successful composting. A common composting technique is termed static pile composting and involves a heap of manure being placed on a porous layer of straw or woodchips in order to maximize air distribution within the manure heap. To avoid forced aeration via manual turning of manure heaps, it has been suggested that the use of a minimum of 2.5 kg of straw per cow (and day) must be used to provide a manure that can self‐ compost (Forshell and Ekesbo, 1993). Thermal insulation may then be achieved using a covering layer of mature compost or by using an amount of material large enough to achieve self‐insulation (Finstein, 2004). An alternative to static pile composting is windrow composting whereby long rows of solid manure (approximately 3‐m wide and 1.5‐m high, but can vary) are periodically turned to provide aerobic conditions. A historical perspective of the evolution of composting technology is available (Fitzpatrick et al., 2005). Solids composting is able to generate much more heat than liquid composting because the exothermic processes lose less heat through dissipation within the solid livestock manure. Temperatures as high as 75  C have been reported during solids composting (Svoboda, 2003). The composting of green waste (garden and park waste), for 3 days at a temperature of 55  C, has been suggested to be eYcient for pathogen removal (Jones and Martin, 2003). Tiquia et al. (1998) provide an account of windrow composting of pig manure and sawdust; the pathogen Salmonella was successfully eradicated after temperatures of 64–67  C were reached and maintained for 2–3 weeks. Similarly, windrow composting of beef cattle feedlot manure bedded with either cereal, straw or wood chips was found to reduce total coliforms (TC) and E. coli by over 99.9% in only 7 days after temperatures of up to 42  C were attained (Larney et al., 2003). The bedding type did not aVect bacterial elimination, and although temperature was clearly a key determinant in coliform kill, the authors speculated that the observed decline may also be a function of antagonism from aerobic heterotrophic bacterial populations.

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Other work has reported that thermophilic windrow composting at temperatures in excess of 55  C for a period of 15 days is suYcient to result in a significant decline of Cryptosporidium and Giardia (oo)cysts (Van Herk et al., 2004). Solid manures of high moisture content will not compost as eYciently as dry manures (Finstein, 2004; Nicholson et al., 2000). Seasonal fluctuations in temperature are therefore likely to aVect composting eYciency and hence manure heaps composted over winter months have the potential to harbor disease‐causing microbes for longer periods. Manure composting using laboratory‐stored heaps (at 20 and 37  C) facilitated a log10 reduction in E. coli O157 numbers within 13.5 and 3.6 days, respectively (Himathongkham et al., 1999). Another study, at ambient temperatures, was able to isolate E. coli O157 from small aerated bovine FYM heaps for up to 47 days and for up to 4 months from small aerated ovine FYM heaps (Kudva et al., 1998). However, because it is diYcult to ascertain the heat distribution throughout concentrated slurry and manure, it is advised that safety margins for time be used if composting is used to destroy pathogens (Mohaibes and Heinonen‐ Tanski, 2004). Nicholson et al. (2005) reported that most pathogen types were eliminated in less than 1 week within solid manure heaps under composting conditions that reached over 55  C. Others have reported that the movement of livestock bedding manure heaps from pens to a storage location, where temperatures are likely to rise, can prove eVective for reduction of pathogen numbers (Hutchison et al., 2005b). This is a simple and cheap method for lowering pathogen levels in solid manure and one which reflects routine agricultural practice. Not only direct eVects of increased temperature contribute to the decline of potential pathogens. In addition, the composting of a material containing a high N supply is likely to result in the release of free NH3, which is detrimental to microorganism persistence (Finstein, 2004; Svoboda, 2003). Solid manure composting represents a viable approach to implement on farms in the United Kingdom and abroad due to its simplicity and low running costs and capital expenditure. Even turning a manure heap only once can encourage aeration of the heap and can lead to large reductions in fecal microbe numbers.

3. Thermal Processing (Drying) Successful thermal processing of solid manure should result in moisture removal from, and volume reduction of, manures (Pain and Menzi, 2003). Part of the natural drying process involves draining of ‘‘manure tea’’ (which can contain fecal bacteria) as the heap becomes compressed under its own weight. Sterilization of manure can be achieved if conditions allow the process

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to work at optimal eYciency, and the technique has been found to be more reliable for manures of a higher dry matter content (e.g., poultry manure). At present, it is not a widely adopted approach based on the grounds of cost to dry FYM (Hutchison, personal communication).

B. LIQUID MANURES 1.

Slurry Storage

The survival of enteric microbes and potential pathogens has been extensively detailed using studies at a variety of scales. The impact of storage time of slurry on generic and pathogenic E. coli populations has been shown via batch experimentation by Oliver et al. (2006) and Himathongkham et al. (1999), respectively. However, when scaling up to the farm management level, slurry tanks are often filled over a timecourse and, as a consequence, the reduction eVects of storage are negated due to introduction of fresh slurry to the store, which inoculates the liquid livestock manure with a new supply of viable microorganisms. This suggests that ideally a farm needs more than one slurry store to prevent recontamination of stored slurry and facilitate batch storage. It is therefore worrying that a risk‐assessment study of 117 farms carried out in two river catchments in south west Scotland identified that 21% of farmers had less storage than 1 month of the farm’s manure production (Aitken, 2003). Only 29% had more than 5 months’ storage and over 50% of the farms were found to have inadequate or unsatisfactory manure storage facilities in terms of risk of water pollution incidents (Aitken, 2003). A survey of United Kingdom and Wales likewise identified that 23% of beef and dairy farms combined had no or minimal slurry storage suggesting these farms may pose an increased risk of storage overflow (Smith et al., 2001). The extent of reduction via storage varies between studies. A batch experiment using five diVerent cattle slurries demonstrated that for all slurries, E. coli O157 declined steadily, though at significantly diVerent rates, but after 64 days, in most cases, E. coli O157 was still detectable (Avery et al., 2005). Avery et al. (2005) conducted the experiments at 10  C to reflect the mean annual air and soil temperature as experienced in North Wales. Work reported by Oliver et al. (2006) showed that generic E. coli declined to undetectable levels (<130 CFU ml
1) as early as day 42, representing a 6 log10 CFU reduction, when stored in slurry at 15  C. While it is accepted that generic E. coli, as an indicator of potential pathogen presence, must survive at least as long as pathogenic strains, it is likely that the more rapid decline observed by Oliver et al. (2006) in comparison with Avery et al. (2005) is governed, in part, by the higher experimental temperature used. Early work of Jones (1976) highlighted

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a rapid reduction in Salmonella dublin in cattle slurry during the first month of storage, and the rate of decline corresponded with increasing temperature. During the months of June–December and at temperatures of generally less than 20  C, E. coli O157, Salmonella spp., and Campylobacter spp. have been shown to survive for up to 3 months (Nicholson et al., 2005). Another study evaluated the survival times of E. coli and Salmonella in slurry. These were reported to be a maximum of 1 and 28 weeks, respectively (Kovacs and Tamasi, 1979). Under these experimental conditions, Salmonella was observed to persist seven times longer at 20  C than at 4  C. This again highlighted the role of temperature‐dependent destruction kinetics; however, the more lengthy persistence in this study was associated with a higher temperature treatment, which is contradictory to much of the other published research. It was speculated in a review by Oliver et al. (2005a) that the lower temperatures may have induced a viable but nonculturable (VBNC) state in the Salmonella spp. and so may have allowed for Salmonella cells to avoid detection. The VBNC state means that the microbes remain metabolically active but are no longer able to grow and divide on conventional media and thus do not produce colonies. As a result the Salmonella count at the low temperature may have been an underestimate. In a comparison of bacterial and protozoan pathogen die‐oV within slurry, the protozoa C. parvum was found to be much more robust than bacterial cells (Hutchison et al., 2005a). This research found that after inoculation of pathogens into 35,000 liter volumes of fresh livestock manure, the decimal reduction time (D‐values; time for a 1 log10 drop) for bacterial pathogens ranged between 6 and 44 days, whereas C. parvum had a maximum D‐value of 345 days. No distinct eVect of seasonality on decline of microorganisms under storage was observed (Hutchison et al., 2005a). Generally, it is found that batch storage of livestock manures provides a useful and simple strategy for reducing the enteric microorganism content, but it is considerably more expensive than standard storage because of the extra batch storage capacity needed (Chambers, 2003). Storage is also beneficial because it means that manures can be spread to land when the risk of surface runoV is less. However, some researchers believe that long‐term storage is not the answer for complete destruction of pathogenic E. coli within manure (Avery et al., 2005). Others have suggested that livestock manures, if contaminated with bacterial pathogens, should undergo storage duration of 6 months to reduce pathogen levels, though alternative strategies should be explored to reduce viable levels of protozoan pathogens (Hutchison et al., 2005a). The results of a report similarly concluded that an extensive length of storage (6 months or greater) is required to reduce bacteria numbers by 99% (Svoboda, 2003). Unfortunately, storage of slurry for long periods can result in anaerobic conditions that will usually give rise to oVensive odors in farming environments

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and release methane and NH3 to the atmosphere (Zanardini et al., 2002). In fact, stored livestock manure derived from cattle accounts for significant (around 10% of total) NH3 emissions from UK agriculture (Misselbrook et al., 2000, 2005). Furthermore, it has been estimated that the cost of slurry storage may not justify fecal bacteria reduction by such means (Svoboda, 2003). The requirement to obtain more storage space may also incur additional disadvantages. Those farms deemed to have inadequate storage would need to increase their storage capacity, which in turn creates a greater exposed surface area of liquid livestock manure and hence allows for increased rainfall collection. As a result, this would increase the cost of slurry disposal for the farmer. Finally, a worry would be that farmers could become complacent with their storage space; this may result in situations where stores overflow onto land not suited for manure application (Svoboda, 2003).

2.

Aeration

This particular manure‐treatment strategy is primarily used to control odors released from slurries, but it can also assist in the reduction of fecally derived microorganisms (Svoboda, 2003). Oxygen must be dissolved into slurry to provide an aerobic environment in replacement of an anaerobic system if successful aeration of liquid livestock manure is to occur (Burton, 1998). The technique is also capable of stabilizing organic matter and converting available organic N to ammonia N. The main methods of aerating slurry are through the use of: surface aerators, bubblers, air injectors, plunging jets, sparger aerators, and venture (suction) aerators, and these can vary in investment cost, aeration capacity, and reliability (Burton and Turner, 2003). The process of aeration in slurry tanks should result in a temperature rise, but the accompanying rise in pH during aeration may also play a role in reducing potential pathogen numbers. Others have commented that protozoa are aerobic microbes, and the aeration process may therefore promote protozoan predation of bacterial pathogens (Heinonen‐Tanski et al., 1998a). A variety of studies have examined the impact of aeration on microbial populations within slurries, both in the laboratory and within farm scale slurry tanks. Thermophilic aeration of cattle slurry has been shown to result in a high standard of hygienic quality of livestock slurry, with temperatures of up to 70  C resulting after 19 days’ aeration at ambient temperatures of around freezing. Combining cattle slurry with whey and fruit‐jam waste was found to be optimal for composting (Heinonen‐Tanski et al., 2005). A period of 2–5 weeks brought about a >99% reduction (and in some cases levels dropped below detection limits) of the initial Salmonella population within

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cattle slurries at the farm scale, following aeration processes (Heinonen‐ Tanski et al., 1998a). In addition, numbers of fecal coliforms (FC) and fecal streptococci (FS) were reduced, though the impact was greater for FC. In another study, it was concluded that aeration of liquid slurry in farm tanks at low temperatures eVectively reduced levels of Yersinia, Listeria, enterococci, and coliphages by over 90% of the original inoculum (Heinonen‐Tanski et al., 1998b). Others have stated that aeration always results in a more rapid decline of bacteria within slurry (Munch et al., 1987). In terms of eliminating protozoan pathogens, aerated cattle slurry has been reported to contain significantly reduced numbers of C. parvum in contrast to unaerated slurry (Svoboda et al., 1997). Similar research has investigated the impact of aeration on viruses in slurry and determined the rate of inactivation of enterovirus to be increased with aeration. A log10 unit drop was observed within 2–4 days at 20  C in contrast to the same level of virus reduction within 300 days at 5  C (Lund and Nissen, 1983). The technique can only be eVective provided that no fresh slurry is introduced to aerated batches. Trouble free and eVective aeration of cattle slurries may first require both dilution and mechanical separation of the manure (Haygarth et al., 2004). Also, the conditions of the final composted product may allow for the growth of some potential pathogens, such as E. coli O157 and Salmonella, if the composting process has been ineYcient and organic matter remains poorly stabilized (Jones and Martin, 2003). Other disadvantages of the approach include the production of foam, and further details have been published on aeration oxygen transfer, mixing and foam control, and aerator performance (Cumby, 1987a,b,c). This aside, aeration is a relatively simple concept and can prove an eVective approach, but, depending on the system used, running costs and capital investment from the farmer can be expensive when compared to other potential manure management strategies (e.g., intensive aeration can require very high capital costs).

3.

Anaerobic Digestion

Anaerobic digestion is a natural process that operates in the absence of oxygen and which facilitates the decomposition and decay of organic matter. Liquid manures will undergo anaerobic digestion unless artificially aerated. A more comprehensive evaluation of anaerobic digestion is provided by Monnet (2003), but a short description is provided in the following. Briefly, microorganisms are used to decompose organic matter within livestock manures within a confined digester, and this will result in the emission of methane and CO2, hence biogas recovery systems are sometimes known as anaerobic digesters. The resulting digestion can increase reactor

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temperatures into mesophilic or thermophilic ranges, equivalent to 20–45  C and 55–70  C, respectively. Thermophilic anaerobic digestion will provide a higher gas yield in comparison with its mesophilic counterpart, but in turn it requires increased capital investment (Nicholson et al., 2000). Anaerobic digestion has a variety of benefits, and under controlled conditions it can manage odor, reduce pathogen numbers, improve nutrient manageability, breakdown organic mass, and be a competitive alternative to lagoon systems (Moser et al., 1998). Subsequently, it has been described as a holistic manure treatment solution (Wilkie et al., 2004). Unfortunately, the system is relatively complex, and it has been reported that such treatment systems are generally only used by enthusiastic farmers, primarily because of the associated high capital costs (Nicholson et al., 2000) and intensive management required; this is reflected in the low number of United Kingdom anaerobic systems adopted (Svoboda, 2003). Nicholson et al. (2000) estimated that the total capital investment required for anaerobic digestion of cattle slurry for the whole of the United Kingdom would be in the region of £1300 million and as such, this is not a realistic option for farms because of the costs involved. It has been reported that the anaerobic digestion process can result in over a 2 log10 decline of pathogen numbers (Moser et al., 1998). Mesophilic fermentation at 30  C for a period of 14 days has been suggested to be suYcient to reduce pathogen content of slurries significantly (Burton and Turner, 2003), though digestion at thermophilic temperatures will prove more efficient in reducing microbe numbers (Martens et al., 1998). Research investigating specifically bacterial pathogens (Salmonella typhimurium, E. coli, and Shigella dysenteriae) determined that laboratory scale anaerobic batch digesters eliminated all of these bacteria within 5–10 days at temperatures of 35  C. A fecal bacterium, indicative of potential pathogen presence (Streptococcus fecalis), was more robust, surviving for up to 15 days at 35  C. At lower temperatures (18–25  C) all of the bacteria were able to persist for longer periods; 35 days in the case of S. fecalis, 20 days for E. coli and S. typhimurium, and 10 days for S. dysenteriae (Kumar et al., 1999). Increasing the temperature into a thermophilic regime is reported to impact further on fecal bacteria destruction times during anaerobic digestion (El‐Mashad et al., 2003). At a temperature of 53  C, E. coli and S. fecalis numbers have been found to decline by 90% within 0.4 and 1.0 h, respectively (Olsen and Larsen, 1987). In contrast, a laboratory scale digester experiment using mesophilic anaerobic digestion was found to initially reduce E. coli, S. typhimurium, Y. enterocolitica, and L. monocytogenes numbers rapidly, but a 90% reduction for these bacteria ranged between 0.7 and 0.9 days during batch digestion (Kearney et al., 1993). Others have highlighted the ineVective role of anaerobic digestion of liquid fractions of flushed dairy manures due to the highly diluted nature

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of the waste material. This is reflected in the greater wealth of research literature for solid rather than liquid manures. For example, there is a wide selection of work describing the impact of anaerobic digestion on fecal microorganism numbers within biosolids (De Leon and Jenkins, 2002; Horan et al., 2004; Kato et al., 2003; Nielsen and Petersen, 2000; Sahlstrom, 2003). As a solution, researchers at the University of Florida developed a fixed film anaerobic digestion procedure, which represented a high‐rate anaerobic digestion technology (Wilkie et al., 2004). Briefly, the method allows for the digestion of the liquid portion of the livestock manure at ambient temperatures. The term ‘‘fixed film’’ was derived from the use of inert media, which was packed into a tank; a consortia of bacteria were able to attach to this and then grow as a biofilm. As liquid manure was passed through the system, the anaerobic layer of biomass broke down organic matter as previously described.

4.

Pasteurization

Pasteurization involves a heat treatment of livestock slurry that partially sterilizes the content. The temperature of the slurry is raised considerably but is below boiling point and generally below the temperature required to denature protein. It is considered a highly eVective technique to eradicate potential pathogens from livestock manures and the method involves maintaining the manure at temperatures as high as 70  C for 30 min or longer. This increase of temperature will also cause the volatilization of odorous slurry compounds. Widespread implementation of this technique in the United Kingdom is unlikely due to associated expenses in terms of both capital and running costs (Svoboda, 2003).

5.

Oligolytic Treatment

Literature describing the eVectiveness of oligolytic treatment impact on fecal microbes in livestock manures is limited. In brief, oligolysis is an electrolytic approach that is principally used to reduce the odor of stored slurry (Zanardini et al., 2002), particularly that derived from piggeries (Feddes et al., 1998; Ranalli et al., 1996; Yu et al., 1991). However, it has been suggested to have other beneficial eVects, one being pathogen removal, because of the bacteriostatic eVect of copper ions. Using this approach, small quantities of metal ions, in particular copper, are dissolved in slurry via electrolysis resulting in sterilization of some microbes. Oligolysis methods take place within storage tanks and can last several months.

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This electrolytic technique works by first reducing the fermentation and/ or respiratory activities of microbes present in slurry through the use of copper ions. The fermentation and respiratory activities of cells within slurry are limited because of an electric current that impacts on cellular membrane mechanisms and adenosine 5‐triphosphate (ATP) synthesis (Skjelhaugen and Donantoni, 1998). A potential on‐farm set‐up for electrolytic treatment of slurry (Fig. 5) would require a secondary slurry store to allow for the oligolysis phase. The provision of a secondary store will in itself be expensive, as discussed earlier when evaluating the benefits of manure storage. Some research has shown that oligolytic treatment can result in a 2 log10 decline of FC and FS bacteria, but this represented only a small reduction of total numbers and left over 104 cells liter
1 within both pig and cattle slurry (Sorliny et al., 1990). Other research has suggested that electrolytic treatment ensures an eVective pathogen kill (Skjelhaugen and Donantoni, 1998). However, in this study, the electrolytic treatment followed on from an initial aeration procedure, and this may have been influential in the reduction of pathogen numbers, though the authors do comment that the electrolytic treatment reduced microbial content very quickly. Conversely, other reports have concluded that the approach provided unconvincing results in the

Housed livestock

Slurry reception pit

Primary slurry storage tank

Electrolytic treatment

Secondary slurry storage tank

Typical example of slurry management on a farm

Supplementary treatment stage: Requirement of second batch slurry store

Cu electrodes Figure 5 Schematic on‐farm design of electrolytic treatment for liquid livestock manure.

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reduction of fecal indicator organisms (FIOs) when compared with other methods of potential pathogen control in livestock manures (Svoboda, 2003). Complementary findings were reported in another laboratory‐based experiment investigating the oligolytic treatment of pig slurry. Oligolysis lasting for 91 days did not result in a significant reduction of pathogenic indicators (Colanbeen and Neukermans, 1992). Oligolysis requires a high amount of initial capital to set up a farm scale system as shown in the schematic diagram of Fig. 5. However, a basic system requires low investment, and its simplicity has meant that the approach has benefited from continued interest (Burton and Turner, 2003). Currently, this potential strategy for pathogen control still appears to be underresearched in the literature, and this was echoed in a recent expert panel survey conducted for the RELU project RES‐224‐25‐0086 that found that out of 16 experts in the fields of microbiology, manure management, and contaminant transfer, only 3 were aware of its use as a mitigation option for reducing pathogen numbers in manures (unpublished data).

6.

Slurry Additives and Disinfectants

Slurry additives are not, at present time, widely used in United Kingdom and Wales (Nicholson et al., 2000) and evidence of their eVectiveness is scarce (Burton and Turner, 2003). However, if it can be shown that a range of microbiological benefits can arise from additions to slurries at cost eVective rates, then it would be advantageous to administer livestock manure additives on a grander scale. Potential additives include strong acids, base precipitating salts, and disinfectants. Those substances likely to alter slurry pH can be expected to be eVective for pathogen reduction. Additionally, disinfection of liquid livestock manures may be achieved via the inclusion of chlorate ions to stores; nitrate reductases are known to reduce chlorate ions to form chlorite ions, which would impose a bactericidal eVect on potential bacterial‐pathogen populations (Tamasi and Lantos, 1983). Commercially available manure odor control agents have been investigated with respect to their ability to simultaneously impact on E. coli numbers in animal manures because some of these products claim to reduce pathogens present in swine slurry. One study evaluated 10 odor control agents; none were eVective at inhibiting or destroying E. coli when supplemented at manufacturer recommended rates (Johnston et al., 2002). On mixing the agents with slurry at a tenfold higher rate, one odor control product (ENVIROPUR) was able to reduce E. coli numbers to levels below detection, even at temperatures as low as 4  C, and several other products reduced viable E. coli levels within the slurry following 8 days’ incubation (Johnston et al., 2002). Generally, it has been suggested that proprietary

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additives will have little impact on pathogen survival in slurries (McCrory and Hobbs, 2001). Lime treatment of slurry can reduce the number of fecal bacteria and potential pathogens through a simple procedure while simultaneously providing the added value of a liming agent to livestock manures. Calcium oxide (CaO) and calcium hydroxide [Ca(OH)2] are the most commonly used alkaline additives (Svoboda, 2003) and are capable of increasing pH up to levels of 11.5 and greater. It is reported that achieving a pH of 12, for a minimum of 2 h, is suYcient to result in an eVective pathogen decline (Department of the Environment, 1996). Alkaline conditions may prove detrimental for fecal bacteria because under such circumstances there exists increased potential for the binding of heavy metals to cell membranes, which may inhibit the intracellular transfer of a variety of metabolites. The addition of lime will also result in a rise in temperature of the livestock manure, which in itself is detrimental for fecal bacteria survival. Such a temperature rise will also release some odorous slurry compounds. Provided there is an adequate mixing of the lime agent with slurry, fecal microbes can be successfully reduced in number. However, an important point to bear in mind is that the use of lime as a reduction technique is only valid if the land to which slurry is to be applied has a suYciently low pH and suitable buVering capabilities to accommodate the lime. Similarly, acidification of slurry can reduce bacterial numbers, though E. coli O157 has been reported to be more acid tolerant than other potential pathogens (Benjamin and Datta, 1995; Russel and Jarvis, 2001). Acidic conditions help reduce bacterial numbers because of the combined eVects of promoting hydrogen ion absorption to cell walls, the inhibition of cation replacement within cells, and the potential increase in leakage of compounds essential to normal cell function. The on‐farm practicalities associated with acid treatment, such as management requirements, safety precautions, and potential corrosion of steel and concrete stores, mean that in reality only a specialist contractor would be able to facilitate this management option (Chambers, 2003). The use of sheep dips in the form of synthetic pyrethroid (SP) insecticides within UK agriculture replaced organophosphate (OP) insecticides after health risks to farmers were associated with the latter. As a result, SPs are now the most commonly used sheep dips within the United Kingdom (Semple et al., 2000). However, SPs are considerably more toxic than OPs for aquatic life‐forms (Virtue and Clayton, 1997), and thus sheep dip contamination of watercourses can have detrimental eVects on aquatic ecosystems (Hooda et al., 2000). Consequently, a standard disposal strategy is to dilute the sheep dip with animal slurry. In doing so, Semple et al. (2000) found that when high concentrations of sheep dip were diluted with the slurry a significant increase in the FC group, in addition to other bacteria,

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was observed. Lower concentrations (0.002–0.02%) in contrast had little eVect on microbial populations. This led the authors to speculate that sheep dip may be detrimental for protozoa survival thus limiting protozoan grazing on bacteria. A follow up study was able to confirm that the presence of sheep dip formulations in liquid livestock manures was able to reduce the number and diversity of protozoa (Boucard et al., 2004). This highlights the potential for some slurry additives to increase the risk of bacterial contamination of water and land associated with the spreading of liquid livestock manure to pastures.

C.

LIVESTOCK WELFARE 1.

Animal Health

Most of the pathogens discussed thus far are harmful to humans and not to the livestock themselves. Therefore, although animals may be carriers of these bacteria and protozoa, they do not necessarily show any clinical signs of illness (except in the case of neonatal diarrhea). This makes it diYcult to detect livestock that are carriers of human pathogens. Nonetheless, general livestock health can impact on the microbial composition of livestock feces. Understanding when livestock are susceptible for excreting the highest pathogen loads would clearly aid on‐farm pathogen control. The age, species, diet, and management of livestock can aVect pathogen levels found in animal manures (Burton and Turner, 2003). Animals that are exposed to stressful conditions are known to shed higher concentrations of bacteria in their excrement (Grau et al., 1969; Jones, 2001; Mechie et al., 1997). When animals are overstressed, their immune system is inhibited from responding to infection in an eYcient and eVective manner (de Passille and Rushen, 2005). Inadequate animal housing whereby, for example, large numbers of livestock are confined in small areas, is also likely to enhance the potential for animal‐to‐animal transfer and pose new health and environmental concerns (Fitzgerald et al., 2003). In general, high stocking densities typical of intensive animal husbandry are likely to increase animal stress levels, which may in turn increase the shedding of pathogens and rate of reinfection. As an example, a study concluded that high stocking density increased E. coli O157 shedding in beef feedlots (Sargeant et al., 2004). Enhancement of animal welfare through improvements in housing could help limit disease transmission through lower microbial shedding (de Passille and Rushen, 2005). Heat stress may also aVect fecal‐shedding rates. In the United States, dairy farms that have moved into more warm regions have subjected more cattle to higher temperatures for longer durations (Fitzgerald et al., 2003).

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Others have claimed that a lack of animal preconditioning combined with long haul transport increased fecal shedding of both generic and pathogenic E. coli by calves on, and shortly after, arrival at feedlots (Bach et al., 2004). Similar studies have identified that transportation acted to stress cattle and led to an increase in Salmonella spp. shed in feces (Barham et al., 2002). Shorter transit times and preconditioning may potentially prove eVective as management strategies for minimizing pathogen shedding by calves.

2.

Dietary Supplementation

Perhaps a more complex management option is to manipulate the pathogen content of livestock excrement before it is produced. This can be achieved by manipulation of animal diet because of the subsequent alteration of the structure and functions of the gastrointestinal tract (Buddington and Weiher, 1999). There is evidence that pathogen numbers within excrement can be reduced via the supplementation of livestock diet (Braden et al., 2004; Schamberger et al., 2004). For example, animals fed prior to harvest with an Ascophyllum nodosum dietary supplementation experienced a lower prevalence of enterohemorrhagic E. coli O157 (Braden et al., 2004). A review provides a comprehensive account of options available for control of enterohemorrhagic E. coli in ruminants and discusses the use of antibodies, probiotics, fasting, and farm management practices (Stevens et al., 2002). However, in conclusion the authors suggest that it is debatable as to whether such strategies can impact on the shedding rates of enterohemorrhagic E. coli suYciently in order to minimize the risk to human health because of the low dose required to cause infection in humans. It has been proposed that the introduction of novel forages into agricultural swards can reduce potential pathogen numbers in the animal gut by releasing antimicrobial products on ingestion (Davies et al., 2001). The use of sodium chlorate as a supplement to cattle diet is claimed to reduce E. coli O157 populations in cattle and be a viable strategy to limit pathogen input to land and livestock manure stores (Callaway et al., 2002). The authors highlight that such a supplementation also reduced generic E. coli numbers, and in the case of their study, E. coli declined by two orders of magnitude in the rumen. By supplementing drinking water with sodium chlorate for 24 h all strains of E. coli O157 were reduced by 2 log10 cells in the rumen and 3 log10 cells in feces. The reduction in cell numbers occurred because facultative anaerobic bacteria, such as E. coli, which are able to anaerobically respire on nitrate through reduction to nitrite, also cometabolically reduce chlorate to cytotoxic chlorite when exposed to chlorate. Chlorate is only bactericidal against nitrate reductase‐positive bacteria (Callaway et al., 2002) and thus represents a potential strategy to curtail E. coli populations

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in livestock prior to excretion. Olson et al. (1998) reported that allicin‐based products administered to neonatal calves infected with C. parvum did not alter the duration of C. parvum induced diarrhea shedding. However, intensive prophylactic administration of the same product was proposed as being able to delay diarrhea in calves exposed to C. parvum which is also the most frequent etiologic agent involved in outbreaks of diarrhea in lambs (Munoz‐ Fernandez et al., 1996). Colicinogenic E. coli additions to cattle feed are an alternative strategy for reducing fecally shed E. coli O157 (Schamberger et al., 2004). Colicins are antimicrobial proteins and so these bacteria are used as a probiotic. Schamberger et al. (2004) found that feed supplementation of this type resulted in a reduction of 1.1 log10 CFU g
1 feces and that a daily administration of 108 CFU of colicin E7 producing E. coli to every gram of feed had the potential to limit fecal shedding of this pathogenic E. coli strain. Other studies have investigated the survival of E. coli O157 in slurry from cattle fed diVerent diets. As an example, over a 10‐week slurry storage period, E. coli O157 was observed to decline in number by 3.5 and 5.5 log10 CFU within slurry derived from cattle fed a silage and silage plus concentrate diet, respectively (McGee et al., 2001). Furthermore, a change of diet from grain‐ to hay‐based diet has been proposed as an option to lower the number (and acid resistance) of E. coli within cattle (Diez‐Gonzalez et al., 1998). This is important because acid tolerant E. coli are more likely to survive in the human stomach; if the strain is pathogenic then it may lead to an increased potential of infection of the human host if the bacteria can withstand the acid environment (Couzin, 1998). However, in the long term, probiotic or dietary ways of controlling potential pathogens may not prove to be consistent, and it is likely that farm/land management may also be required to complement such measures. The reason for this is that survival studies in soil, water, and manures consistently suggest that outside the host animal, fecal microbes do not survive well. Land/farm management strategies could focus on (1) making the outside environment as unconducive as possible to survival or (2) prolonging the residence time of those microbes in the environment that exist in the farm.

IV. LAND MANAGEMENT STRATEGIES TO LIMIT PATHOGEN TRANSFER FROM LAND TO WATER Pathogen transfers from land to water can occur through a range of soil hydrological pathways (Oliver et al., 2005a). A key factor governing the transport of microbes from land is high‐intensity rainfall (Oliver et al., 2005b), but clearly human activity is unable to regulate this driver.

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In response, there are a variety of methods aimed at limiting microorganism movement and delivery to watercourses, and these are evaluated on a case‐ by‐case basis in the following. It is critical, however, to emphasize that for optimal mitigation of microbial contamination of watercourses there is a need to develop a holistic and integrated catchment management approach to support sustainable solutions by using strategies that complement one another.

A. MEASURES TO REDUCE PATHOGEN MOBILIZATION

FROM

LAND

1. Manure Application Techniques The discussion in Section II identified that spreading of livestock manures to pasture could introduce a source of pathogens to land, which may subsequently be transferred through and across the soil when coupled with hydrological drivers such as rainfall. For consideration of how to eVectively limit any potential movement in an attempt to protect watercourses from microbial delivery following manure application, attention must be given to the timing and rates of application and to the variety of manure application methods at the farmer’s disposal. In the United Kingdom, Defra funded the production of a series of summary booklets for managing livestock manures, one of which provided valuable information with respect to spreading systems for slurries and solid manures (Chambers et al., 2001). Application methods for liquid manures include broadcast (splash plate), band, trailing hose, and injection techniques. Briefly, broadcast spreading uses pressure to force slurry from the tanker onto an inclined ‘‘splash plate’’ resulting in a widely distributed topical application of manure to land. Band spreading provides close application to land in the form of narrow bands via a series of hoses connected to a boom at the rear of a slurry tanker. The trailing shoe option is similar to band spreading, except that the shoe attached to each hose facilitates slurry deposition under the sward canopy. Finally, injection methods literally inject slurry under the soil surface— either by means of a shallow or deep injection. For grassland, shallow injectors are used that are able to incorporate slurry to a depth of less than 0.1 m from the soil surface (Rodhe and Etana, 2005). The most common solid manure spreading techniques are side discharge spreading and rear discharge spreading. Plowing land following manure spreading eVectively incorporates the manure into the soil and can be adopted when reseeding grassland. Rapid, or incidental, transfers of contaminants can occur following rainfall coupled with ill‐timed manure applications (Preedy et al., 2001), and this can represent a significant source of bacterial pollution for surface waters

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(Ramos et al., 2006). Manures (and associated microbes) applied via broadcast techniques without incorporation are likely to be more readily mobilized by surface runoV than those injected or plowed into the soil because they are less well protected from detachment mechanisms associated with (1) impacting rain drops and (2) resulting surface runoV processes (Quinton et al., 2003). While the shallow injection and trailing shoe techniques deliver liquid manures in bands under the sward cover and therefore protect the slurry components from rainfall, some studies have found that there is an increased risk of bacteriological contamination of tile drains following injection rather than broadcast spreading (Dean and Foran, 1992; Foran and Dean, 1993; King et al., 1994). The advice provided to farmers in terms of the best preventative spreading methods to limit microbial contamination is complicated further because of impacts on microbe survival associated with these diVerent spreading methods. Deep injection and plowing of manures into the soil may be seen as a strategy to aid the protection of watercourses from rapid overland transfers of manures and manure‐associated bacteria and protozoa through prohibiting lateral movement, but a direct consequence of incorporation with the soil is that the microbes, such as E. coli O157, persist for longer periods than they would on the soil surface (Avery et al., 2004a). Similarly, Hutchison et al. (2004b) showed that the rate of pathogen decline was governed by the amount of time contaminated manures remained on the soil surface and that microbe viability increased when incorporated with the soil. This may have arisen because the surface‐injected/plowed cells were protected from desiccation eVects associated with UV radiation, known to be eVective for pathogen kill (Hijnen et al., 2006; Meays et al., 2005). But additionally, the soil environment can provide protective microniches for microbes (England et al., 1993). However, the incorporated location within the soil does not guarantee that the microbe will stay on land. Water movement through soil may then facilitate a slower vertical microbial transfer through the soil matrix or rapid passage through bypass pathways (macropores), which may potentially deliver the cells to a watercourse, providing the microbes are not filtered and trapped within the soil profile. So as a counter argument it may be construed that broadcast spreading is the preferred option to protect watercourses from microbial pollution because it allows for a more rapid elimination of microbes through desiccation and UV radiation, eVectively removing the pathogen source and preventing microbial contamination. However, it would be imperative that the manure application be well timed to avoid an immediate rainfall event following application; this is dependent on the vigilance of the farmer (see Section IV.A.2). As a final consideration, there must be appreciation that microbial contaminants are not the only environmental concern associated with spreading manures to land. Incorporation techniques are seen as eYcient methods to

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reduce NH3 emissions and nuisance odors following spreading periods (Malgeryd, 1998; Misselbrook et al., 2002; Moseley et al., 1998). Broadcast applications may allow for rapid microbial die‐oV but do not necessarily benefit other pollution issues, and if coupled with a rainfall event, broadcast spreading can be disastrous for water quality if a watercourse is in proximity to the land to which the manure has been applied.

2.

Farmer Environmental Stewardship

Farmer vigilance can undoubtedly complement even the most eVective mitigation eVorts. There are a variety of simple options that can be adopted that are proven to oVer some means of watercourse protection from contaminants derived from livestock manures. The key to such vigilance essentially lies in the maintenance of fields and farmyards. Simple and often cheap measures can include grazing fields located away from watercourses, separation and diversion of clean water from roofs away from dirty areas of the farmyard, the repair of guttering to facilitate such separation, and the relocation of gateways to avoid likely runoV pathways. Interestingly, a simulation study for the River Irvine catchment in Scotland identified that catchment mitigation approaches may be more beneficial for the microbial quality of bathing water at Irvine Beach than simply reducing stocking density of animals (Vinten et al., 2004b). However, reduced stocking densities will result in less excreta per unit area, and this has to be considered as a potential strategy to limit fecal loading of pasture, though in balance it is also associated with additional economic costs because the farmer will be required to either increase the area of farmed land or reduce animal numbers. Removal of animals from pasture prior to rainfall events is probably of little benefit to water quality because pasture will have already been contaminated with excrement, and work has reported the importance of the legacy of fecal material on pasture in terms of microbial impact on receiving waters even after the removal of cattle (Oliver et al., 2005b). In addition, the relocation of cattle may impact pasture by creating rapid overland flow pathways from the continually trampled and poached ground as livestock are herded from field‐to‐field thus eliminating any benefit of moving the cattle in the first instance. Knowing that bacterial transfer from land to water occurs, an alternative strategy is to remove livestock from susceptible and vulnerable areas of pasture. By mapping such vulnerable areas of pasture (see Section IV.B.4) there may exist the potential to limit microbial loading of receiving waters by (1) avoiding overland flow pathways and steep slopes and (2) including natural vegetation buVers or constructed wetlands as complementary mitigation strategies.

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A crucial aspect to consider in relation to manure spreading rather than animal management is the timing of manure applications to land—which, if done carefully and according to CoGAP (MAFF, 1998), can be extremely eVective. This is because there is an increased likelihood for bacterial contamination of receiving waters if a rain event occurs soon after slurry application (Ramos et al., 2006). The farmer decision‐making process ultimately determines when manures are spread to land at particular times throughout the agricultural calendar. Limiting the impacts of a manure application on water quality can be addressed by vigilance on the part of the farmer. However, the practicalities are not always straightforward if storage space is insuYcient and farmers are forced to apply manure to land (Aitken, 2003). Earlier in the chapter, Section II suggested that batch storage of manure is beneficial for the microbial composition of slurry and solid manure, but it does not prove convenient if storage space is limited. In fact, limited storage space can in some cases dictate application timings. A proportion (up to 16%) of dairy farms in the United Kingdom have insuYcient (less than 1 month) storage capacity, and therefore the spreading of manure to land almost 365 days a year becomes a necessity (Smith et al., 2001). Other factors may also govern farmer’s decisions, such as family tradition and the firmness of the ground to be able to take farm machinery onto pasture in the first instance. In considering farmyard management strategies, McGechan and Wu (1998) raise an interesting modeling scenario when discussing slurry storage options for impacts on the environment and farm economics. They adopt two slurry store size options for their simulations, each reflecting a diVering farmer attitude to the manure. It follows that a farmer who opts for a small slurry store may consider the slurry to be an embarrassing ‘‘waste’’ requiring disposal, which will often take place when the store has reached capacity and on fields in closest proximity to the store. In contrast, the authors state that farmers opting for larger slurry stores may represent farmers who consider slurry to be a beneficial ‘‘resource’’ that can be exploited for their economical gain. The logic behind this is that the slurry can be stored and spread at the optimum time for nutrient uptake by crops, therefore increased storage provides increased flexibility for land application. A final farmyard management strategy is associated with roof and gutter maintenance. Roofing can constitute a source of nonpoint water pollution, and this will vary with the roofing material, age, and slope (Chang et al., 2004). Clean water can transfer from roofing and mix with farmyard washings thus increasing the volume of dirty water sourced from the hard standings. Separation of clean roof water (via guttering) from farmyard areas contaminated with feces will help in reducing dirty water runoV from farmyard areas. ‘‘The 4 point plan’’ (4 point plan, 2004) published in

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Scotland is an example of literature distributed to farmers that is aimed, in part, at increasing awareness of how to minimize dirty water accumulation around farmyards via straightforward advice.

B. MEASURES

TO

REDUCE PATHOGEN DELIVERY TO WATER

1. Restricting Livestock Access to Streams Establishing a minimum distance from a watercourse at which animals can graze and thus fencing oV such areas is a potential strategy designed to limit runoV of excrement from nearby pasture and prevent direct cattle access to streams. Fencing oV of watercourses can therefore prevent the direct deposition of fecal material into a stream. However, fencing alone cannot guarantee a reduction in pollutant loading to the stream because even fenced fields pose a risk of contributing contamination from overland flow and subsurface drainage contributions to water (Byers et al., 2005; Oliver et al., 2005b; Signor et al., 2005). Any grazed fields that are fenced oV from watercourses must then be coupled with the provision of an alternative water source for livestock to drink. It has been reported that it is increasingly unlikely that there will be direct impact on microbial pollution of watercourses caused by animal defecation into surface waters because of farmers attempting to provide animals with drinking water away from rivers and streams (SheYeld et al., 1997). These authors found that the provision of water troughs away from a stream drew cattle away from the watercourse for drinking 92% of the time, therefore reducing FC concentrations in receiving streams by up to 51%. While this has been shown to reduce E. coli contamination of watercourses (Byers et al., 2005), other argue that the eVect of an oV‐stream water source does not satisfactorily prove eVective at reducing pollutant loads to water (Line, 2003) presumably because excrement can be deposited in high concentrations around oV‐stream drinking areas (White et al., 2001), and this may be mobilized following rainfall. Additionally, cattle will often use streams for loafing in warm weather, and so the stream does not only represent a source of drinking water but also a cooling agent during summer months, and this will act to further complicate widespread uptake of fenced waterways. Clearly, allowing cattle to drink from a stream is cheaper for the farmer than having to provide alternative water sources, shaded areas and fencing, but it is less sustainable for microbial water quality. The provision of small bridges to allow animal crossings from field‐to‐field rather than through streams will also restrict cattle loafing in watercourses but again requires monetary input from a farmer in contrast to cost‐free stream fording.

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2.

Vegetated Buffer Strips

Vegetated buVer strips (VBS) are designed to reduce surface flow, and their use is widely recognized as a management option to protect watercourses from sediment and particulate P derived from agricultural land (Abu‐Zreig, 2001; Abu‐Zreig et al., 2003, 2004; Ferguson et al., 2003; Hickey and Doran, 2004; Magette et al., 1989). VBS may also prove eVective for removing unwanted bacteria from surface runoV, prior to their delivery to receiving waters from both land receiving manures and grazed pasture. In the United Kingdom, CoGAP recommends that a 10‐m buVer be used between manure spreading and a watercourse (MAFF, 1998). However, such an approach is only eVective when subsurface pathways of microbial transfer, such as tile drainage, are unimportant. A basic model of the microbial eYciency of VBS is given in Eq. (1): Tr ¼

Mi
M o Mi

(1)

where Tr is the trapping eYciency of the VBS and Mi and Mo are the total number of fecal microorganisms in the inflow and outflow, respectively. A number of studies have reported the varying capacity of VBS to trap microbes in runoV, and in general successful filter strips are required to promote infiltration, dilution, and sedimentation. Typically, VBS oVer optimal eYciency when runoV depth is shallow. A simplified summary of VBS eYciency is shown in Fig. 6. Protozoan pathogen attenuation via VBS has been evaluated by Atwill et al. (2002) and Tate et al. (2004) among others. BuVers constructed with silty clay or loam or at lower bulk densities were most successful at filtering the oocysts, in contrast to sandy loams and higher bulk density soils. It was proposed that under certain rainfall and slope conditions, 1 m of VBS can produce a 0.9–2.0 log10 mean reduction in C. Parvum oocyst flux relative to the total oocyst load applied in a fecal matrix (Tate et al., 2004). Atwill et al. (2002) concluded that VBS of slope <20%, soil bulk density of 0.6–1.7 g cm
3, and of 3‐m width should result in a 3 log10 reduction of C. parvum oocysts from overland flow that is generated from rainfall events of <4 cm h
1. In another study, a comparison of vegetated and nonvegetated surfaces was made to evaluate the impact on overland and near surface transport of C. parvum using tilted soil chambers with bare ground and in contrast with brome vegetation (Trask et al., 2004). Similar to other researches, vegetation was found to eVectively filter protozoa from surface runoV. Under high‐ intensity rainfall (63.5 mm h
1), up to 59% of oocysts were recovered in surface runoV from the bare soil surface in contrast to a maximum of 27% from the vegetated surface. In conclusion, vegetation was proposed as a viable

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Scenario

Description

Rainfall event (i) of intensity ⫻ mm h-1 falls onto fecally contaminated pasture generating overland flow of A mm depth

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Rainfall event (ii) of intensity 2 ⫻ mm h-1 falls onto fecally contaminated pasture generating overland flowof 2A mm depth

1 No buffer in place

No buffer is used to Fecal microorganisms protect watercourse detected in watercourse from wash-in of fecal bacteria applied or deposited onto pasture of slope angle Z °

Increased number of fecal microorganisms detected in watercourse relative to rainfall event (i)

Buffer strip of y meters is used to protect watercourse adjacent to pasture of slope angle Z°

Reduced number of fecal microorganisms are detected in watercourse relative to Scenario 1

Increased number of fecal microorganisms detected in watercourse relative to rainfall event (i)

Buffer strip of (2 * y) meters is used to protect watercourse adjacent to pasture of slope angle Z °

Reduced number of fecal microorganisms are detected relative to Scenario 2

Increased number of fecal microorganisms detected in watercourse relative to rainfall event (i)

Buffer strip of y meters is used to protect watercourse adjacent to pasture of slope angle (1.5 * Z )°

Increased number of fecal microorganisms are detected relative to Scenario 2

Increased number of fecal microorganisms detected in watercourse relative to rainfall event (i)

2 Buffer strip y

3 Buffer strip 2 * y

4 Buffer strip y

Figure 6 Basic matrix to illustrate buVer strip eYciency for reducing fecal microbe delivery to watercourses.

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management strategy to reduce pathogenic protozoa being delivered to surface waters because of oocyst entrapment within vegetation, adsorption to plant material, and infiltration into the soil profile (Trask et al., 2004). Research which evaluated the impact of the distance of bovine manure from a collection point to demonstrate the eYcacy of VBS in reducing FC bacteria within overland flow found that a vegetated strip of 0.61 m between feces and stream would reduce the number of FC entering the stream by 83% in contrast to direct deposition of the fecal matter into the water (Larsen et al., 1994). Increasing the vegetated strip to 2.1 m increased this reduction of FC by a further 12%. Tate et al. (2006) observed similar findings of increased cell attenuation associated with increased buVer width. They reported that, relative to a 0.1‐m buVer, each additional meter of vegetative buVer can result in a 0.3–3.1 log10 reduction of E. coli discharge for the range of slope, rainfall, and runoV conditions investigated. Similarities in FC and P transfer through short VBS under saturated conditions have been found, leading some to believe that there is potential to evaluate buVer strip performance based on the more substantive volume of literature associated with P mitigation using vegetated strips (Stout et al., 2005). A small‐scale plot experiment (2.4 m  30.5 m), whereby the upper 12.2 m of each plot received manure application, and the lower 18.3 m acted as a VBS was undertaken by Lim et al. (1998). RunoV water was sampled at various filter lengths and concentrations of FC bacteria were reduced from 2  105 FC ml
1 to undetectable levels following runoV passage through 6.1 m of filter strip (Lim et al., 1998). Field experimentation in New Zealand has found that sloping (8 ) grass buVer strips (5‐m long, 2‐m wide) provided minimal entrapment of E. coli and Campylobacter under high flow events, but that under low water application rates entrapment could exceed 95% of the applied cells (Collins et al., 2004). It was proposed that during large runoV events, a 5‐m length of buVer strip would be required to significantly limit delivery of fecal bacteria to receiving waters. Others have found that the eVect of buVer width on E. coli discharge was partly dependent on total runoV volumes (Tate et al., 2006). Interestingly, remobilization of trapped microbes was also investigated using a subsequent rainfall event after a 5‐day interlude and cells were observed to be washed out in the order of two to three times lower than recorded at the end of the experiment. IneVectiveness of VBS with respect to limiting fecal bacteria transfer has also been reported (Coyne et al., 1995) leading to debate over the usefulness of such abatement strategies. While 99% of sediment in runoV was retained by 9‐m long grass filter strips, only 74% and 43% of FC were trapped in the two plots studied. Coyne et al. (1995) commented that this was an inadequate filtering eYciency for the protection of receiving waters in accordance with US primary water contact standards, especially following heavy rain and surface runoV. Similarly, Fajardo et al. (2001) concluded that VBS were ineVective at coliform

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reduction in surface runoV despite other published work supporting significant attenuation of fecal cells in vegetative buVers (Tate et al., 2006). There are some concerns that VBS may only function eVectively for a limited period and that they may even become a source of agricultural contaminants as opposed to functioning as sinks all year round (Osborne and Kovacic, 1993). In response, some researchers have stated that prudent management of vegetation within buVer systems is required, in addition to careful installation and design, to achieve optimal benefits for both the environment and public health (Atwill et al., 2002; Barling and Moore, 1994; Tate et al., 2006).

3.

Riparian Buffer Strips

Riparian buVer strips (RBS) are seen as a crucial link between agricultural land and the river corridor (Anbumozhi et al., 2005). In some situations, the reduction of diVuse agricultural pollutants being delivered to receiving waters, carried by surface runoV, can be attributed to RBS because of the natural filtering capability of the dense vegetation, which can trap fecal matter and reduce the momentum of surface runoV. This management technique is often recommended as a tool for removing diVuse pollutants from agricultural areas (Anbumozhi et al., 2005; Lee et al., 2003). As an example, to protect shellfisheries from fecal bacteria in North Carolina, riparian buVer restoration was recommended as a viable management strategy to implement alongside wetlands and improved education (White et al., 2000). Modeled scenario analysis was employed to suggest a potential reduction (in the range of 3–82%; median 35%) of E. coli concentrations in stream waters of the Upper Managaotama catchment, Whatawhata, following the restriction of cattle access to the stream and riparian retirement (Collins and Rutherford, 2004). In Georgia, on a grassed area of Tifton loamy sand with an adjacent riparian forest of slash pine on a loamy sand, riparian filter strips (30‐m long) composed of 10‐m grass and 20‐m forest prevented a surface‐flow wastewater pulse moving beyond 7.5 m in dry seasons, but in wet weather the surface‐flow pulse was able to reach 30 m (Entry et al., 2000a). Stream bank engineering within the Lake Champlain Basin Program opted to include riparian restoration as part of the devised management strategy to reduce P, sediment, and bacterial loads entering the water. As part of a combined mitigation eVort (buffers were coupled with riparian fencing and protected stream crossings) a significant decline in bacterial counts in the watershed was observed (Meals, 2001). Vegetation in RBS has also been investigated with respect to coliform bacteria survival (Entry et al., 2000b). Following application of animal manure to the RBS, coliform bacteria declined to background levels

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after 3–4 months, though the bacteria declined tenfold every 1–2 weeks, irrespective of seasonality eVects. In general, higher numbers of FC remained in the upper soil profile (0–5 cm). Given that shade can facilitate improved survival of bacteria contained within fecal deposits it is possible that riparian zones allow bacteria, such as E. coli, to survive longer than if feces is deposited on open grassland (Meays et al., 2005). It is therefore important to fence oV riparian areas not only to prevent cattle poaching, but also to restrict feces being deposited in the riparian area where it remains protected from UV radiation and available for wash oV into adjacent water. If we also consider that the habitat of a riparian zone is likely to be home to a variety of wildlife that can contribute feces and associated bacteria to the vegetation and soil, then even with fencing to protect the riparian zone, wild animals can potentially contaminate the area that is intended to protect the watercourse from fecally derived bacteria. Ecological engineering aspects of riparian buVer design are discussed by Anbumozhi et al. (2005). Briefly, they note that a time lag will occur between the planting of riparian zone trees and the mature functioning of this buVer for pollutant removal. Clearly, combining a riparian buVer with grass filter stretches and shrubs will allow for additional filtering until trees are fully grown. Other factors, such as maintenance and bank stabilization, are also crucial aspects to consider in the design of eVective riparian buVers. The topography of the land surrounding RBS clearly needs to be accounted for because steep slopes dropping to buVers are less likely to function eYciently. Alongside maintenance there still remains the issue of practicality; in many instances farmed land is a valuable asset and the use of land to provide a 20‐m riparian buVer may be met with some opposition on economic grounds from farmers. As concluded by Collins and Rutherford (2004), the extent of the eYciency of such a management tool for protecting neighboring watercourses remains highly uncertain, and this can be attributed, in part, to our incomplete understanding of how fecal microbes actually transfer (freely suspended or particulate associated) through the environment once released from fecal matter. It has also been suggested that it is not wise to focus primarily on RBS as an ‘‘end‐of‐the‐line’’ strategy for limiting microbial loading of watercourses (Edwards and Merrilees, 2003) and instead the coupling of several mitigation approaches within an integrated catchment management strategy may oVer improved protection.

4.

Land Management Engineering and Vulnerability Mapping

A variety of studies have identified that overland flow can facilitate the transfer of microorganisms from land to water (Collins et al., 2005). In response, limiting overland flow may act to reduce (though not eliminate)

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200 m

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N

Figure 7 ArcGIS hillshade image of a farm in the United Kingdom, which can assist the identification of topography and likely flow paths for overland flow. It can be combined with other datasets to help screen for land considered more ‘‘risky’’ for contributing contaminants from land to water. Solid black line represents the farm boundary.

the delivery of fecal microbes to receiving waters. While there exist a range of methods to reduce such transfers, many of which are evaluated in this chapter, there is also an option to engineer the land in a way that benefits both the environment and its users, in a form of proactive intervention (Quinn and Hewett, 2003). The advent of geographic information systems (GIS) and recent technological developments have accelerated and dramatically improved visual modeling approaches to land management. Hydrological flow paths in agricultural environments can now be mapped with the aid of computer programs linked with digital elevation and digital terrain models (DEMs and DTMs). Consequently, high resolution digital terrain analysis can be used to highlight zones likely to generate runoV within farmed landscapes. Figure 7 shows the ArcGIS hillshade output of a 5‐m DTM (NextMap Britain) for a small area of the Taw catchment in North Devon, United Kingdom. A farm boundary is shown on the map via a solid black line. Even with a basic output as shown in Fig. 7, it is possible to make sensible predictions of where overland flow may potentially develop within this example farm environment following rainfall. An example of a software tool developed for studying runoV processes at the farm scale is TopManage, which is basically a hydrological/topographical

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toolkit (Hewett and Quinn, 2003). Briefly, TopManage allows for the representation of local microtopography to provide visualization of likely runoV zones and enable a simulation of how man‐made features such as tire tracks from machinery, hedgerows, and concrete roads, may accelerate or decelerate farm runoV. This can then allow the user to make an informed assessment on the likely impact of such features on water flow from farmed land. TopManage can therefore be used as an integral part of a runoV management plan. Heathwaite et al. (2005) have discussed modeling and managing critical source areas (CSAs) using flow‐connectivity simulation through combining CSAs and flow accumulation models. This helped to identify the importance of tramlines, tracks, and field drains in concentrating flow toward receiving waters. Lane et al. (2004) discussed flow‐connectivity modeling in terms of a network index approach. They suggested that for hydrological connectivity from a saturated zone to a watercourse to occur, all DEM cells between that saturated zone and the drainage network must become saturated. Within such models assumptions can be made with respect to flow direction of runoV based on contours derived from the base DEM. If a contaminant of concern is known to be transported by surface runoV processes, then being able to predict the location of surface generated flow can be an important landscape‐screening tool. Discussions relating to the importance of DEM spatial resolution in generating model outputs are provided by Abedini et al. (2006) and Brazier et al. (2005). An appreciation that complete field characterization cannot be facilitated through GIS modeling alone is essential. To obtain a more representative understanding we require a combination of field visits, farmer interviews, and nationally available datasets at diVerent spatial resolutions to allow for spatially distributed assessments of the risk of surface runoV in the environment. If these options are coupled with the assumption that surface water flows will also act as a carrier for microbial contaminants, the risk of land contributing microbes to water can be gauged in relative terms thus allowing prioritization of sites for land management (Lane et al., 2006). DEMs are clearly important tools, and when coupled with hydrological knowledge and agronomic information (often obtained from farmers), they oVer a valuable insight into potential eVective management and control of runoV from land. If such landscape engineering can be employed to disconnect flow, then the implications are that entrained contaminants will also be disconnected from surface waters. 5.

Constructed Wetlands

A constructed wetland is a biological system engineered to imitate the conditions of a natural wetland and used in the amelioration of wastewater (Nuttall et al., 1997). Constructed wetlands, or reed beds, are an eVective,

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environmentally passive way to treat eZuents and wastewaters of various degrees of potency with relatively low capital and operating costs and minimal maintenance (Collings and Phillips, 2001). They are seen as part of the sustainable development approach to waste management, oVering both a low environmental impact and an appropriate ecological option (Hodgson et al., 2002). Constructed wetlands are categorized into two main groups—free water surface treatment wetlands (FWS) and subsurface flow treatment wetlands (SSF). In the FWS system the wetland has a water depth up to 0.6 m with the water surface open to the air. Vegetation and microorganisms grow in the wetland and act to ameliorate the wastewater, which is often delivered as a constant stream. In this type of reed bed, eZuent passes over the support medium, between the macrophyte stems and through any surface litter. In the SSF system the reed bed resembles a percolating filter except it accommodates aquatic plants. The wastewater is introduced in such a way as to cover the surface of the bed and percolate down through the plant rhizospheres and supporting media. By intermittent dosing of the wastewater on to the reed bed suYcient aeration of the support media is maintained to avoid anoxic conditions. Constructed wetlands are now considered as fundamental requirements in the design of nonmains sewage treatment systems (Grant et al., 2000). The application of diVerent plant species, alongside various designs of macrophyte systems, has been the focus of research, with the parameters that constitute the consent standards [biological oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), and nitrates and phosphates] receiving most attention (Hunt et al., 2002; McNevin et al., 2000; Nuttall et al., 1997; Perkins and Hunter, 2000; Turner, 1995). Where studies on constructed wetlands have been conducted there is often a lack of information regarding the frequency of sampling and the period of study (Chendorian et al., 1998; Quinonez‐Diaz et al., 2001; Thurston et al., 2001). Perkins and Hunter (2000) undertook a study on the FWS macrophyte system, they concluded that on average an order of magnitude reduction in concentration of FC and FS was observed between the inflow and outflow of the FWS system, equating to mean removal eYciencies of 86–94% for FC bacteria and 83–90% for FS bacteria. Stenstro¨m and Carlander (2001) reported a 99.9% removal of fecal enterococci as compared to 97.5% removal for FC, via constructed wetlands, in their Swedish study. Similarly, Kay et al. (2005) reported reductions of over 97% in the flux and concentration of FIOs to marine recreational waters by a natural wetland. Kern et al. (2000) reported removal rates for FC bacteria of 99.3% in the summer and 95.8% in the winter in a constructed wetland treating dairy farm wastewaters. The mechanisms associated with the removal of bacterial indicators are attributable to both biotic and abiotic factors. The biotic factors include

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predation, die‐oV, and addition from transient and resident animals (water voles, coots, pied wagtails, and so on), while the abiotic factors include sedimentation, filtration, adsorption, eZuent flow, and temperature (Perkins and Hunter, 2000; Reed et al., 1995). Clearly, eZuent flow has a strong influence on bacterial removal, as borne out by the strong negative correlation observed between bacterial removal and eZuent flow (Hodgson et al., 2004), and so at times of high flow, bacterial removal eYciency declines (Green et al., 1997). An explanation for this is that an essential design criterion for wetland systems is to provide conditions conducive to the settlement of particulate‐associated pollutants. This is achieved through the presence of vegetation which impedes flow, thus allowing the more eVective sedimentation of fine particulates (<2 mm in size), which have a slower settling velocity (Davies et al., 2003). Recording the time that samples have been taken may have a significant outcome on the reported removal eYciency of a wetland. Hodgson et al. (2004) identified a diurnal trough, in terms of removal eYciency, during normal flow conditions. This is perhaps typical of a sewage treatment system dealing predominately with domestic wastewater. This may in part go some way in explaining why so many authors report such high removal eYciencies for constructed wetlands (Decamp and Warren, 2001; Kern et al., 2000; Pundsack et al., 2001; Quinonez‐Diaz et al., 2001; Thurston et al., 2001; Wood and McAtamney, 1994). In each case removal eYciencies in excess of 98.5% are reported; however, no mention of sampling time is indicated. The type of planting medium (gravel or soil) can also influence the eVectiveness of SSF wetlands in reducing coliform numbers. Decamp and Warren (2000) exemplified both of these cases in a combined microcosm and pilot‐scale experiment and found that most E. coli removal takes place within the first one‐third of a system and that E. coli did not decline as quickly within unplanted soil bed when compared with gravel bed systems. The relationship between E. coli concentration and distance along the bed followed an exponential decline. When scaling up from a microcosm (1.25 m  0.3 m  0.25 m) to pilot (6.0 m  2.8 m  0.6 m) study, the average E. coli removal increased by at least 24%. This may be attributed to the less eYcient communities developed within the microcosms (Decamp and Warren, 2000).

6.

Farm Ponds

Farm ponds may be considered as a viable mitigation measure in providing a sink for contaminants mobilized within surface runoV from pasture (Hawkins and Scholefield, 2003; Heathwaite et al., 2005; Quinn et al., 2004).

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In contrast, others believe that ponds are a contaminant source within farm environments because of their susceptibility to receive and harbor contaminated surface runoV and fecal droppings (Malaney et al., 1962). In a similar fashion to VBS, RBS, and constructed wetlands, farm ponds rely on retention as a mechanism to attenuate fecal microbes. Some work have shown that grazing livestock on land above farm ponds can be advantageous in reducing the rate and number of fecal bacteria entering watercourses (Fisher et al., 2000). In one study, stream water quality was protected because the ponds intercepted TC, E. coli and enterococci bacteria leaving the grazed watershed. It was found that the outflow of microbes from the pond was of similar magnitude to those in surface waters draining a wooded catchment (Fisher et al., 2000). Larger protozoan pathogens can be removed by ponds largely because of sedimentation processes; bacteria in contrast are eliminated more by the processes of UV, high pH, and predation within the pond environment. Pond depth can therefore prove important as it impacts directly on the penetration of UV radiation through the water and also influences dissolved oxygen concentrations (Von Sperling, 2005). In particular, specifically designed waste stabilization ponds are considered to be eVective at removing pathogenic bacteria (Von Sperling, 2005). Others oppose the value of farm ponds as mitigation options because they argue that ponds simply create another problem while trying to minimize the diVuse pollution issue they are intended to alleviate. This may then have to be dealt with in terms of regulation of farm ponds in the future, yet another form of regulation for farmers to adhere to. Jones (2005) has stated that farm ponds are actually a rich source of pathogens for livestock, which can eVectively lead to a continuous cycle of shedding and ingestion within the farm environment. Perhaps more worryingly, ponds also provide birds with potentially pathogen contaminated water for consumption and bathing. Ingestion of microbes by birds may then allow for the transfer of fecally derived bacteria and protozoa beyond the farm boundary. A study has warned that migratory species could even serve to disperse bacteria between widely separated locations (Cole et al., 2005). This study also speculates that opportunities exist for new health problems in wildlife populations to emerge because birds use farm ponds and waste lagoons and graze on pastures inhabited by cattle and other livestock. Birds do not only pose a threat around farm ponds. Their known potential for excretion of a range of human pathogens in droppings means that congregations of birds represent a source of environmental pollution whatever their immediate surroundings (Jones, 2005). This can further complicate our assessment of the contribution of agriculture to fecal loading of surface waters.

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V.

SYNTHESIS AND CONCLUDING REMARKS A. CONCEPTUALIZING MICROBIAL MITIGATION

The risk of microbial contamination of watercourses varies with the extent to which a source of pathogens (e.g., manure) is combined with a transfer mechanism (e.g., rainfall and slope) and a delivery component (e.g., hydrological connectivity) to form a continuum, which facilitates successful microbial export from land to water. Should a pathogen source be coupled with both a means of transfer and successful delivery to a watercourse, then a potential source becomes an actual risk (Edwards and Merrilees, 2003). Conversely, without a source of microbial contaminants, it does not matter if runoV is generated and hydrological connectivity to a stream exists because no microbes will be carried in the water flow and no microbial contamination of water will result. Similarly, if manure high in pathogen numbers is applied to land, but is located in a field where runoV risk is low and hydrological connectivity to a watercourse is indirect and negligible (i.e., no field drains present and the field is located far from a watercourse) then again, the risk of water contamination is significantly reduced. In summary, integrated mitigation strategies should be able to successfully limit microbial contamination of watercourses by attempting to remove, or significantly reduce source, transfer, or delivery components from a potentially risky agricultural scenario (as summarized in Fig. 8), so that large source areas of fecally derived microbes do not coincide with areas prone to the generation of surface runoV or other transfer processes. In more general terms, a mitigation option should aim to remove the contribution of CSAs specific to the contaminant of concern. However, at the same time there is a need to make a holistic assessment of any proposed mitigation strategy. This chapter has dealt primarily with microbial contaminants but there remains a diYcult ‘‘balancing act’’ for farmers and land managers if they are to embrace successful stewardship of farmed land. The diversity of physical, biological, and chemical characteristics associated with the growing suite of agricultural pollutants means that while certain practices may assist in limiting microbial delivery to watercourses, they may in turn accelerate pollution of the environment with other agriculturally derived contaminants (‘‘pollution swapping’’). This is highlighted with strategies designed to alleviate N and P diVuse pollution. Both contaminants have diVering chemistry and flow pathways meaning that mitigation options are often in conflict and liable to compromise water quality remediation (Sharpley et al., 1998). Risk‐assessment strategies should be considered to assess the benefits of ‘‘pollution swapping’’ to limit environmental impacts from grassland farming and aid design of holistic frameworks for designing mitigation strategies for agricultural pollutants.

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Limited transfer. Risk of water contamination minimized

Spread manure on field with low runoff risk

Manure

Successful composting

Transfer

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Connectivity

Potential risk of water contamination converted into actual risk

Buffer strip Limited connectivity. Risk of water contamination minimized

No source. Risk of water contamination cannot be realized

Figure 8 A conceptual flow chart depicting source, transfer, and delivery stages of pathogen cycling through the environment. Examples of potential mitigation measures are highlighted as breaking the continuum that would otherwise allow for a potential risk to become an actual risk.

B. CONCLUSIONS Agronomic perturbations arising from grassland management and human activities can alter the rural landscape and contribute to temporal and spatial variability in pollutant loading of streams. The inherent complexity associated with heterogeneous landscapes confounds the likelihood that a single management strategy will provide complete protection of receiving waters from microbial contamination. Appreciation that a solitary mitigation option cannot deliver 100% eVective mitigation for diVuse microbial pollution needs to remain completely transparent for land managers, and it is only with the coupling of diVerent strategies alongside improved education and considerable vigilance by farmers that a more sustainable approach to limiting diVuse microbial (and, crucially, other contaminant) pollution from agriculture can be practiced. Awareness that small farms can adopt simple measures and that larger, more economically stable farms can accommodate more comprehensive multistage strategies of mitigation is a fundamental foundation for designing suitable land and manure management plans.

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Advances in manure management strategies continue to address the potential problem of diVuse bacterial pollution from an ‘‘upstream’’ perspective, prior to land application, and undoubtedly further improvements in technology will make for more eYcient strategies of manure ‘‘cleansing’’ in the future. However, no matter how eVective the strategy, some microbes of concern are likely to remain available for transfer from land to water. Furthermore, we should also question whether it is acceptable for manure particles to enter receiving waters even if fecal pathogens have been removed—the answer is probably not because in reality we do not want to come into contact with fecal matter, sterile or not, in potable water. This means that land management will, and must, remain a key tool in minimizing the hydrologically driven transfer of fecal matter from farmed grassland to adjacent watercourses, and this continues to be a challenging area of catchment science, largely because of the complexity of addressing the mitigation of sporadic episodes of overland flow. Essentially, the quality of our approach to land management should be reflected in the quality of our watercourses. However, this means that cost‐eVective strategies and land management options need to be widely adopted throughout farmed catchments in order to prevent other neighboring farms jeopardizing the microbial water quality at the expense of the eVort of others. While management options can prove valuable, equally important is the need to transfer such information to the farming community, so that management strategies can be adopted at the farm management level in order to improve the bacteriological quality of water that drains catchments and so that results of scientific studies are not wasted.

ACKNOWLEDGMENTS This work was funded as part of project RES‐224‐25‐0086 by the Rural Economy and Land Use (RELU) program, which receives financial support from the Biotechnology and Biological Sciences Research Council (BBSRC), the Natural Environment Research Council (NERC), the Economic and Social Research Council (ESRC), the Department for Environment, Food and Rural AVairs (Defra), and the Scottish OYce.

REFERENCES Abedini, M. J., Dickinson, W. T., and Rudra, R. P. (2006). On depressional storages: The eVect of DEM spatial resolution. J. Hydrol. 318, 138–150.

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WEED MANAGEMENT IN DIRECT‐SEEDED RICE A. N. Rao,1 D. E. Johnson,2 B. Sivaprasad,1 J. K. Ladha1 and A. M. Mortimer3 1 International Rice Research Institute (IRRI), IRRI‐India Office, National Agriculture Science Center (NASC) Complex, New Delhi 110012, India 2 International Rice Research Institute (IRRI), Crop, Soil, and Water Sciences Division, Metro Manila, Philippines 3 Integrative Biology Research Division, School of Biological Sciences, The University of Liverpool, Liverpool L69 3BX, United Kingdom

I. Introduction A. Direct‐Seeding of Rice B. Yield Loss Due to Weeds in Direct‐Seeded Rice II. Weeds, Weed Competition, and Ecology in Direct‐Seeded Rice A. Occurrence of Major Weeds in DiVerent Methods of Direct‐Seeding Across the World B. Crop–Weed Competition in Direct‐Seeded Rice C. Weed Species Shifts and Weed Population Dynamics Due to Changes in the Methods of Rice Establishment III. Integrating Weed Management Practices in Direct‐Seeded Rice A. Preventive Methods of Weed Control B. Intervention Methods of Weed Control C. Developing Weed Management for Direct‐Seeded Rice IV. Future Research Needs Acknowledgments References

Rice (Oryza sativa L.) is a principal source of food for more than half of the world population, especially in South and Southeast Asia and Latin America. Elsewhere, it represents a high‐value commodity crop. Change in the method of crop establishment from traditional manual transplanting of seedlings to direct‐seeding has occurred in many Asian countries in the last two decades in response to rising production costs, especially for labor and water. Direct‐seeding of rice (DSR) may involve sowing pregerminated seed onto a puddled soil surface (wet‐seeding) or into shallow standing water (water‐ seeding), or dry seed into a prepared seedbed (dry‐seeding). In Europe, Australia, and the United States, direct‐seeding is highly mechanized. The risk of crop yield loss due to competition from weeds by all seeding methods is higher than for transplanted rice because of the absence of the size diVerential 153 Advances in Agronomy, Volume 93 Copyright 2007, Elsevier Inc. All rights reserved. 0065-2113/07 $35.00 DOI: 10.1016/S0065-2113(06)93004-1

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A. N. RAO ET AL. between the crop and weeds and the suppressive eVect of standing water on weed growth at crop establishment. Of 1800 species reported as weeds of rice, those of the Cyperaceae and Poaceae are predominant. The adoption of direct‐seeding has resulted in a change in the relative abundance of weed species in rice crops. In particular, Echinochloa spp., Ischaemum rugosum, Cyperus diVormis, and Fimbristylis miliacea are widely adapted to conditions of DSR. Species exhibit variability in germination and establishment response to the water regime postsowing, which is a major factor in interspecifically selecting constituents of the weed flora. The relatively rapid emergence of ‘‘weedy’’ (red) rice, rice phenotypically similar to cultivars but exhibiting undesirable agronomic traits, has been observed in several Asian countries practicing DSR, and this poses a severe threat to the sustainability of the production system. Stale seedbeds, tillage practices for land leveling, choice of competitive rice cultivars, mechanical weeders, herbicides, and associated water management are component technologies essential to the control of weeds in DSR. Herbicides in particular are an important tool of weed management, but hand weeding is either partially or extensively practiced in countries of Asia, Africa, and Latin America. Though yet to be globally commercialized, transgenic rice varieties engineered for herbicide resistance are a potential means of weed control. The release of herbicide‐resistant rice for red rice control in the United States has indicated the need to critically examine mitigation methods for the control of gene flow. Integrating preventive and interventional methods of weed control remains essential in managing weed communities in DSR, both to prohibit the evolution of herbicide resistance and to maximize the relative contributions of individual components where herbicides are not widely used. There remains a need to further develop understanding of the mechanisms and dynamics of rice weed competition and of the community dynamics of weed populations in DSR to underpin sustainable weed management practices. # 2007, Elsevier Inc.

I. INTRODUCTION Over 1800 plant species have been reported as weeds of rice in South and Southeast Asia (Moody, 1989), and there is an enormous diversity of taxa considered to be weeds of rice (Soerjani et al., 1987). There are two major reasons for this. The first is that rice is grown over a range of agroecosystems, characterized by the presence or absence of water (from dry land to fully flooded land) for all or parts of its growing season, which generates highly diverse weed floras. The second is that, in many developing countries, rice farming relies on manual labor, and removal of weeds is ineYcient, leading to their persistence. Reviews of rice yield loss due to the presence of weeds equally indicate considerable variability and, in part for the same underlying

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reasons, a diversity of weed species across diVerent ecosystems (Karim et al., 2004; Oerke and Dehne, 2004; Oerke et al., 1994; Sanint et al., 1998; Widawsky and O’Toole, 1996; Yaduraju and Mishra, 2004). It is widely accepted that, in the absence of chemical weed control, rice that is transplanted into standing water that is subsequently maintained for much of the growing season will suVer less competition from weeds and consequentially have less yield loss than rice established by other ways. The underlying ecological reason for this is the inherent size and growth advantage of rice, which derives from transplanting seedlings into standing water under which weed species must initially germinate, establish, and subsequently compete for limiting resources (principally light) during growth in a dense crop monoculture. Where geographically large flood plains exist (e.g., the Mekong Delta), transplanting rice has been time honored, and labor for crop establishment and subsequent manual weeding has been one mainstay of the sustainability of the system. Contrastingly, before the advent of the Green Revolution and adoption of irrigation, rainfed rice was often broadcast into moist soil (Pandey and Velasco, 2002, 2005) and yields were low, variable, and highly prone to weed competition, as is still experienced today, particularly in upland rice (Roder et al., 2001). There is now evidence that water scarcity prevails in rice‐growing areas (Tuong et al., 2005), and societal demands for water from the urban and commercial sectors will continue to increase. Direct‐seeding of rice, in place of transplanting, provides opportunities for water savings but at the expense of the absence of the suppressive eVects of standing water on weed growth. Hence, the direct‐seeding of rice (DSR) crop faces severe challenges from weeds, and eVective weed management is essential for cropping of DSR. Weed management in DSR grown in both tropical and temperate regions has been assessed previously by many authors (De Datta, 1986; De Datta et al., 1989; Hill et al., 1994; Ho, 1996; Moody, 1981, 1983, 1993, 1995; Moody and Cordova, 1985; Sankaran and De Datta, 1985). However, given the anticipated shortages of labor and water, there will likely be a continuing shift from transplanting to direct‐seeding and greater reliance will be placed on direct‐seeded systems for food security. This chapter reviews the management of weeds in DSR from the background of three perspectives. First, rice is a principal source of food for more than half of the world’s population, and rice cultivation underpins the livelihoods of hundreds of millions of households around the globe. Moreover, several countries of Asia and Africa are highly dependent on rice as a source of foreign exchange and government revenue (www.fao.org/rice2004/en/world.htm). Rice is planted on
153 million hectares annually, of which 134 million hectares are planted in Asia. Whereas rice production increased at 3.0% and 2.5% per annum during the 1970s and 1980s, respectively, to meet demographic demand, the increase

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was only 1.5% during the 1990s (Dawe and Dobermann, 1999). Globally, rice production must increase by 36% by 2025 to feed an estimated 4 billion rice consumers (Pinstrup‐Anderson et al., 1997). Reducing yield losses due to weed competition will contribute to that increase. Second, the global area planted to rice is declining because of pressure of urbanization and industrialization through land loss, and water and labor shortages (Nelson‐Smith, 1995). As Khush (2005) and others have argued, new technologies to increase rice productivity will be needed to meet the challenge of enhancing rice production under such constraints. Improved weed management, particularly in DSR, will contribute in this respect. The final perspective is one of sustainability. Historically, in weed management, overreliance on a single management technology has resulted in both ecological and evolutionary responses in the target weed flora. Successful weed management is concerned with minimizing the impacts of weeds in the short term and simultaneously ensuring that yield losses will not increase in the long term as a result of practices that are implemented. In this chapter, we (1) assess the current status of direct‐seeded rice, including the extent of yield losses due to weeds, (2) examine changes in weed species composition, (3) document and critically evaluate the available weed management options, and (4) discuss future research needs and strategies to continue to manage weeds eVectively and economically, in a sustainable manner.

A. DIRECT‐SEEDING 1.

OF

RICE

Methods of Direct‐Seeding

Direct‐seeding refers to the process of establishing a rice crop from seeds sown in the field rather than by transplanting. Once germination and seedling establishment are complete, the crop can then be sequentially flooded and water regimes maintained as for transplanted rice. Alternatively, the crop can remain rainfed, the upper surface soil layers fluctuating from aerobic to nonaerobic conditions. Direct‐seeding is the oldest method of rice establishment and, prior to the late 1950s, direct‐seeding was the major method used in developing countries (Grigg, 1974; Pandey and Velasco, 2005). DSR systems are classified into (1) dry‐seeded rice, (2) wet‐seeded rice, and (3) water‐seeded rice based on the physical condition of the seedbed and the seed/seedling environment at germination and establishment (Table I). Dry‐seeded rice is a traditional practice developed by farmers to suit the agroecological conditions in systems ranging from shifting cultivation in the humid forest zones to intensive cultivation in the rainfed lowlands (Fujisaka et al., 1993; Johnson et al., 1991; My et al., 1995; Roder, 2001;

Table I Direct‐Seeded Rice Systems of the World

Dry‐seeded rice

Wet‐seeded rice

Seedbed condition

Land preparation procedure

Dry (un‐saturated)/ Plowing and moist soil harrowing once suYcient soil moisture is present

Puddled soil

Plowed, flooded, puddled and leveled

Lithao (manual or animal drawn): 15 cm

Random: hand broadcasting

Mechanized seed drill: 8–10 cm Harrowed seed bed: 5 –11 cm Planking by power tiller: 4–12 cm

Rows: drilled or manually sown 1. Broadcast by hand or motorized blower onto a puddled soil surface; after drainage

Typical seed germination environment Dry seed buried (2–5 cm) in aerobic soil

Aerobic wet seeding: pregerminated seed onto a saturated mostly aerobic soil surface

Typical water regimes 0–14 days after sowing

Agricultural system/ region where method is practiced

(i) Rainfed upland or dry land, (ii) some areas of rainfed lowland and deep‐water agricultural systems of Asia, Africa, Latin America, and the Caribbean Agricultural systems with controlled irrigation systems in America, Europe, and Australia Initially a saturated Irrigated and favorable rainfed agricultural soil with 0–0.3 cm systems in Asia, Africa, surface water Latin America, and the Caribbean No standing water until rice has reached about the 3‐leaf stage

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Direct‐seeding method

Soil microtopography in relation to land preparation and leveling method, data are standard Methods and deviations (cm)a pattern of seeding

(continued)

157

158

Table I (continued )

Direct‐seeding method

Seedbed condition

Leveling may be soil Mechanized bucket and movement by scraper: 4–7 cm tractor‐mounted bucket and scraper, by ‘‘planking’’: Laser leveled drawing a flat (Asia): 3–5 cm plank behind a tractor or power tiller or by laser leveling with precision‐grading mechanical operations As for wet‐seeded Soil ridged before rice flooding to prevent aggregation of settled seed; laser‐leveled (USA): 1–2 cm

a Data from IRRI (unpublished); Fujii and Cho (1996). Developed from Balasubramanian and Hill (2002).

Typical seed germination environment

2. Row seeded by a Anaerobic wet seeding: drum‐seeder pregerminated either hand seed sown into drawn or the surface attached to layers (5–10 cm power tiller of a saturated soil). Seed may be coated with oxygenating agents (e.g., calcium peroxide). Anaerobic Broadcast into standing water manually, by motorized blower or from the air

Typical water regimes 0–14 days after sowing

Agricultural system/ region where method is practiced

Irrigation applied to ensure soil surface does not crack Drainage as needed to prohibit premature flooding Sequential irrigation to a depth of 3–5 cm depending on rate of rice shoot elongation Standing water Irrigated of 5–10 cm agricultural systems of Malaysia, America, Asia, Australia, and Europe

A. N. RAO ET AL.

Water‐seeded On puddled or rice unpuddled soil in standing water to a depth of 3–5 cm

Land preparation procedure

Soil microtopography in relation to land preparation and leveling method, data are standard Methods and deviations (cm)a pattern of seeding

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

159

Watters, 1971) in Asia, Africa, and Central and South America. Dry seed is sown at the beginning of the rainy season after either minimum or zero tillage in the shifting cultivation systems or into prepared seedbeds in more intensive systems. Hand broadcasting or dibbling seeds into furrows or drill‐seeding in rows by machine is used for seeding at shallow depths into moist, aerobic soil (Hill et al., 1991). Subsequently, rice is raised as a dryland crop or the field is kept flooded during much of the season depending on the soil and climatic conditions. In the United States, Europe, and Australia, to some extent rice is drilled in rows and then irrigated. In contrast, wet‐seeding involves sowing pregerminated seed, with a radicle varying in size from 1 to 3 cm, on or into puddled soil. Where motorized broadcasting is used, the pregermination period is shortened to ensure short radicles for ease of handling and to minimize damage, as is the case when drum‐seeders for row‐seeding are employed (Balasubramanian and Hill, 2002). Land preparation is critical to successful crop establishment under wet‐seeding since seedbeds need to be leveled to prohibit premature seedling death by flooding and to ensure that pregerminated seeds remain at or near the surface of the soil. Where seeds sink into the upper layers of the soil surface, anaerobic conditions prevail during seedling establishment and seed coatings to improve oxygenation in the immediate vicinity of the developing seedling may be employed. Achieving precision leveling requires considerable land preparation and maintenance, and variability is always likely to occur not least because of machinery passage on small fields but also due to biotic factors, including wading birds. Kawasaki (1989) argued that a standard deviation of 2 cm in soil surface height across a field was acceptable as this rarely led to large gaps in DSR and modern laser‐leveling techniques can achieve greater precision. Simple leveling of a field by drawing a plank behind a power tiller or tractor in contrast imparts much greater variability (Table I). The significance of this variability is that it generates spatial variation in water regimes in the field that in turn influences weed seed germination and recruitment into the weed flora. Water‐seeded rice can be established by traditional means where pregerminated seeds are sown into standing water that may recede with time. Seeds must be heavy enough to sink below standing water to enable anchorage at the soil surface. Traditionally in Asia, water‐seeding is resorted to only when early flooding occurs, and water cannot be drained from the field. Only a few traditional rice varieties are used for this method of water‐seeding in Thailand, Indonesia, and Vietnam. Modern techniques of water‐seeding include aerial sowing using aircraft in the United States and Australia, seed broadcasting using tractor‐mounted seeders in Italy, or broadcasting using motorized blowers in Malaysia. Aerial water‐seeding is the most common seeding method used in temperate rice zones (Hill et al., 1991).

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160

2.

Global Distribution of Direct‐Seeded Rice

Rice cropping varies widely across countries and regions. Table II summarizes the extent of global direct‐seeding of rice. Currently,
23% of the rice is direct‐seeded in the world. Rice is planted either in a dry‐seeded or water‐seeded system in the United States (Gianessi et al., 2002), Australia (Pratley et al., 2004), and Europe (Ferrero and Nguyen, 2004; Gianessi et al., 2003; Ntanos, 2001). The vast majority of Australian rice (more than 90%) is aerially sown into water (Pratley et al., 2004). Pandey and Velasco (2002) noted that direct‐seeding was increasing rapidly in Asia, with 21–22% of the total rice area being dry‐ or wet‐seeded. Broadcasting and dibbling are common seeding practices for upland rice in Africa (Ampong‐Nyarko, 1996) and, on dry soils in Latin American countries, drill‐seeding is used. However, direct‐seeding on saturated soil has been widely adopted in southern Brazil, Chile, Venezuela, Cuba, some Caribbean countries, and in certain areas of Colombia (Fischer and Antigua, 1996). In India, dry‐seeding is extensively practiced in rainfed lowlands, uplands, and flood‐prone areas, while wet‐seeding remains a common practice in irrigated areas (Misra et al., 2005). In southern Vietnam, especially in the Mekong Delta, rice is wet‐seeded by broadcasting (Luat, 2000). Kim et al. (2001) reported that 11% of the total rice area in Korea was under direct‐ seeding, dry‐seeding being 6.4% and wet‐seeding 4.7%. In the northern provinces of Cambodia, in a typical wet season, 80–90% of rice fields are dry‐seeded, whereas, in the southern provinces, both wet‐ and water‐seeding occur (CIAP, 1998). In the Philippines, both dry‐ and wet‐seeding are used, with wet‐seeding being the most common practice and dry‐seeding again occurring in areas with higher elevation and slope, non‐irrigated flat lands and irrigated lowlands with medium‐ to light‐textured soils (de Dios et al., 2005). In Thailand, the majority of rainfed rice area is dry‐seeded, whereas, under irrigation in the Central Plain, rice is predominantly wet‐seeded (Azmi et al., 2005). In Malaysia, wet‐seeding is favored but is encouraged only where eVective water management is possible (Azmi et al., 2005). Rice, seeded directly into aerobic nonpuddled and nonflooded soils (‘‘aerobic rice’’) in China, is mainly distributed in the northern and northeastern regions, with 80,000 and 60,000 ha, respectively (Xie et al., 2005).

B. YIELD LOSS DUE

TO

WEEDS IN DIRECT‐SEEDED RICE

Weeds are a major yield‐limiting factor in rice production (Bastiaans et al., 1997), and the literature reporting yield losses is numerous. Globally, actual rice yield losses due to pests have been estimated at 40%, of which weeds have the highest loss potential (32%). The worldwide estimated loss in

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161

Table II Estimated Direct‐Seeded Rice (DSR) Area in DiVerent Rice‐Growing Countries

Continent/country Asia Bangladesh Cambodia China India Indonesia Iran Japan Korea Laos Malaysia Myanmar Nepal Pakistan Philippines Sri Lanka Thailand Turkey Vietnam South America Argentina Bolivia Brazil Colombia Ecuador Guyana Paraguay Peru Uruguay Venezuela North and Central America Cuba Dominican Republic Mexico Nicaragua United States Africa Burkina Faso Chad Congo Democratic Republic Coˆte d’Ivoire Egypt Ghana Guinea

Total rice areaa (000 ha)

Estimated DSR area (000 ha)

DSR area (% of total area)

134,544 11,000 2300 29,420 42,500 11,753 570 1650 990 820 670 6000 1550 2210 4000 756 9800 80 7400 5799 172 142 3732 517 350 130 28 318 190 135 2026 205 107 51 94 1349 10,220 51 80 415 510 630 125 525

27,186 2090 230 1471–2648 11,900 2116 28 0 89 271 476 540 0 0 1680 582 3332 72 2309–3478 3176 155 128 1866 465 70 117 25 57 171 122 1628 144 43 36 56 1349 2226 1 4 332 357 126–158 6 52

20.2 19b 10b 5–9b 28b 18b 5c 0b 9b 33b 71b 9b 0b 0b 42b 77b 34b 90–100c 39–47b 55 90–100c 90–100c 50c 90–100c 20c 90–100c 90–100c 18c 90–100c 90–100c 80 70c 40c 70c 60c 100c 22 2c 5c 80c 70c 20–25d 5c 10c (continued)

162

A. N. RAO ET AL. Table II (continued)

Continent/country

Total rice areaa (000 ha)

Guinea Bissau Liberia Madagascar Mauritania Mozambique Nigeria Senegal Sierra Leone Tanzania Europe France Greece Italy Portugal Russian Federation Spain Oceania Australia World

65 120 1219 17 179 4900 88 200 330 594 21 22 215 26 143 121 73 65 153,257

Estimated DSR area (000 ha) 6 12 244 9 13 980 26 20 33 534 19 20 194 23 109 109 73 65 34,823

DSR area (% of total area) 10c 10c 20c 50c 7c 20c 30c 10c 10c 90c 90–100c 90–100c 90–100c 90–100c 90–100c 90–100c 100c 100c 22.7

a

Source: FAO (2005). Pandey and Velasco (2002). c Based on FAO (2002), Ampong‐Nyarko (1996), and other papers quoted in this chapter. d Hassan and Rao (1996). Note: When a range was given in the source, minimum percent area was taken for the continent/ country estimate. b

rice yield from weeds is around 10% of the total production (Oerke and Dehne, 2004). However, accurate estimates of yield loss are limited, and much of the information on yield loss is often derived from basic trials assessing pesticide eYcacy, which tend to overestimate yield loss and do not take into account the natural variation and extremes that occur in farmers’ fields. A superficial extension of this observation is that variability in rice yield losses due to weeds might be greater in rainfed environments than in irrigated environments because of the lack of a managed water supply that suppresses weeds. In a detailed analysis of the injury profiles (due to pathogens, insects, and weeds) of lowland rice in farmers’ fields, Savary et al. (2000a,b) argued that specific injury profiles could be associated with particular cropping patterns, distinguishing those of intensive transplanted rice from direct‐seeded rice–rice rotations. In both, however, weed infestations were a common constraint and, whether weed species at maturity grew above or below average rice canopy height, yield losses due solely to weeds were about 20% of attainable yield.

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

163

Country

Figures 1–3 illustrate the scales of yield loss reported for DSR in the last decade. Ranges for yield loss by country (Fig. 1) indicate considerable variability and are a reflection of both site‐specific conditions and the methodologies used in estimation. However, they do serve to reinforce the severity of losses that may occur due to a variety of potential, and often additive, consequences of weed infestations. These include (1) the diversity of the weed flora as a consequence of crop establishment practices, (2) water management during the life of the crop, (3) associated pests and diseases whose abundance may be influenced by companion weeds of rice, and (4) the impact on harvest and postharvest operations, including grain cleaning and drying (Hill et al., 1994; Smith and Hill, 1990). Widawsky and O’Toole (1996) estimated that weeds in eastern India were the second largest damaging constraints in both rainfed lowlands and uplands, although the magnitude of yield losses in upland rice was greater than in lowland environments (Fig. 2). Weeding was considered as inadequate in both environments for a number of socioeconomic and technical reasons. Of greater importance is a measure and understanding of the scale of yield loss that is experienced at the farm level. Figure 3 illustrates the variability of loss in transplanted rice and DSR. Where rainfed DSR is grown on terraced land, the weed flora may diVer substantially because of the position on the toposequence (Pane et al., 2005). Nevertheless, the range of yield losses due to weeds may be similar (Fig. 3) and diVer little from that

West Africa Vietnam USA Thailand Sri Lanka Malaysia Korea India Europe Egypt Australia 0

10

20

30 40 50 60 70 Range of yield loss (%)

80

90

100

Figure 1 Reported range of yield loss in direct‐seeded rice due to weed competition in the absence of any control measures [Sources: Australia, Pratley et al. (2004); Egypt, Hassan and Rao (1993, 1996); Europe, Oerke et al. (1994); Gianessi et al. (2003); India, Yaduraju and Mishra (2004); Korea, Kim and Ha (2005); Malaysia, Karim et al. (2004); Sri Lanka, Herath Banda et al. (1998); Abeysekera (2001); Thailand, Meenakanit and Vongsaroj (1997); Tomita et al. (2003a); USA, Hill et al. (1994); Vietnam, Chin et al. (2000a); West Africa, Akobundu and Fagade (1978); Ampong‐Nyarko (1996); Fofana and Rauber (2000)].

A. N. RAO ET AL.

164 200

Yield loss due to weeds (kg ha−1)

180 160 140 120 100 80 60 40 20 0 RUR (DRSR)

RLR (DRSR)

RL (TPR)

IWS (TPR) IDS (TPR)

Eastern India

Agricultural system Figure 2 Estimated yield losses due to weeds in diVerent rice‐growing environments of eastern India. (RUR, rainfed upland ecosystem; RLR, rainfed lowland ecosystem; RL, rainfed deepwater ecosystem; IWS, irrigated ecosystem, wet season; IDS, irrigated ecosystem, dry season; DRSR, dry‐seeded rice; TPR, transplanted rice) [Source: Widawsky and O’Toole (1996)].

experienced by farmers under transplanted conditions. In all instances, distributions of loss tend to be skewed, with the highest variability being evident in drill‐seeded rice. Understanding the causes of this variation and determining points and means of interventions in the context of whole‐farm economics and farmer livelihoods are discussed in Section II.

II. WEEDS, WEED COMPETITION, AND ECOLOGY IN DIRECT‐SEEDED RICE A. OCCURRENCE OF MAJOR WEEDS IN DIFFERENT METHODS DIRECT‐SEEDING ACROSS THE WORLD

OF

Globally, weed communities of DSR are floristically diverse because they (1) span temperate and tropical regions, (2) reflect diVerent agroecosystems in a region, (3) may vary in relation to seasonal crop management patterns at the farm level, and (4) may diVer because of spatial heterogeneity that is

WEED MANAGEMENT IN DIRECT‐SEEDED RICE 0.8

165

A

B

C

D

E

F

0.6

Proportion

0.4 0.2 0.0 0.8 0.6 0.4 0.2 0.0 0

2

4

60

2 Yield loss (ton

4

60

2

4

6

ha−1)

Figure 3 Distribution of yield loss due to weeds under farm management practices, data being derived by paired plot comparisons in on‐farm and researcher‐managed trials of the impact of additional weeding on farmers’ current weeding practices. (A) Bangladesh—dry‐seeded, upper toposequence position; (B) Bangladesh—dry‐seeded, mid toposequence position; (C) Bangladesh— dry‐seeded, low toposequence position; (D) Bangladesh—transplanted irrigated rice; (E) India— wet‐seeded rice; (F) India—dry‐seeded rice. For all distributions, n > 50, data being collected post 2000 [Sources: Mazid et al. (2001); Singh et al. (2001)].

often linked to patterns of flooding and drainage and soil nutrition at the field level (Moody, 1995; Mortimer and Johnson, 2005). They can vary further in relation to the eYcacy of weed management practices. Some weed species, however, show a ubiquity of distribution that elevates them to the status of ‘‘the world’s worst weeds’’ (Holm et al., 1977) and particular sedge (Terry, 2001) and grass (Mortimer, 2001) species feature prominently in DSR, including Cyperus rotundus, Echinochloa crus‐galli, Echinochloa colona, and Sorghum halepense. Table III summarizes the weed species that have been reported as the most common in DSR and that are considered to be of economic importance— Africa (Ampong‐Nyarko, 1996; Johnson, 1997), Asia (Caton et al., 2004; Galinato et al., 1999), Bangladesh (Sarkar et al., 2002), Bhutan (Parker, 1992), Brazil (Anon, 1997), Cambodia (John et al., 1996), China (Wang, 1990), Egypt (Hassan and Rao, 1993, 1996), Greece (Ntanos, 2001), India (Singh, 2005; Tadulingam et al., 1955), Indonesia (Pane et al., 2000), Italy (Bocchi et al., 2005), Japan (Morita, 1997), Korea (Kim and Ha, 2005), Latin America and the Caribbean (Fischer and Antigua, 1996), Malaysia (Ho, 1996; Itoh, 1991), Myanmar (Morris and Waterhouse, 2001), Pakistan

166

Table III Weed Species Reported to be Most Commonly Associated with Direct‐Seeded Rice in DiVerent Countriesa Type of direct‐seedingb Weed species

Family

DRSR c

Fabaceae Fabaceae

Aeschynomene rudis Benth. Aeschynomene virginica (L.) Britton, Sterns & Poggenby Aeschynomene denticulata Rudd Ageratum conyzoides L.

Fabaceae Fabaceae

IND, THA, IDO, NEP, PHI, SRI, VIE BAN, BRA, CAM, CHI, IND, JPN, KOR, LAO, LAC, MAL, MYA, NEP, PAK, PHI, SRI, THA, USA (ARK), VIE BRA, USA (ARK) LAC, USA (MSO, ARK), NEP

Fabaceae

BRA

Asteraceae

AFR, BAN, BHU, CHI, COT, IND, IDO, JPN, PHI, LAO, MAL, MYA, NEP, NGR, SRI, THA, VIE, CHI, LAC, MAL

Alisma lanceolatum Withering Alisma plantago‐ aquatica L. Alternanthera philoxeroides (Mart.) Griseb. Alternanthera sessilis (L.) R. Br. ex DC. Amaranthus retroflexus L. Amaranthus spinosus L.

Alismataceae

WRSR

MAL MAL, PHI, SRI, THA

USA (ARK, LOU, MIS)

LAC, IND

USA (ARK, LOU, MIS, MSO)

SRI

ITL, AUS

Alismataceae

IND

JPN

ITL, EUR, TUR, AUS

Amaranthaceae

CHI, USA (TX, FLO), IND, IDO, JPN, THA, BAN, LAO, MYA

THA

USA (ARK, LOU, MIS, TX)

Amaranthaceae

AFR, BAN, BHU, CAM, CHI, IND, IDO, LAO, MAL, MYA, NEP, PHI, SRI, THA, VIE USA (FLO), CHI, MYA

BAN, IND, PHI, THA, VIE

Amaranthaceae Amaranthaceae

AFR, BAN, BHU, CHI, IND, IDO, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE

A. N. RAO ET AL.

Aeschynomene aspera L. Aeschynomene indica L.

WTSR

IND

Lythraceae

COT, IND, IDO, JPN, PHI, SRI, THA, VIE, AFR, BHU, MAL, MYA, PAK AFR, IDO, IND, SRI, THA, VIE, BAN, LAO CAM, MYA, NEP, PAK USA

Ammannia baccifera L. Ammannia coccinea Rottb. Bacopa rotundifolia (Michx.) Wettst. Bolboschoenus maritimus (L.) Palla ¼ Scirpus maritimus L. Brachiaria plantaginea (Link) Brachiaria platyphylla (Munro ex C. Wright) Nash Butomus umbellatus L. Caesulia axillaris Roxb. Caperonia palustris (L.) St. Hil. Celosia argentea L. Chara sp. (algae) Chloris pilosa Schumach. Commelina benghalensis L.

Lythraceae

JPN, PHI

USA

Scrophulariaceae

USA (ARK), IND, JPN, SRI, IDO

JPN, MAL

USA (ARK, CAL, LOU, MIS)

Cyperaceae

ITL

AFR

ITL, EUR

Poaceae

BRA, LAC

Poaceae

BRA, JPN, USA

IND

Butomaceae Asteraceae Euphorbiaceae

IND IND, BAN, SRI, NEP USA (FLO, MSO, TX)

JPN IND, PAK

Amaranthaceae

BAN, IND, IDO, LAO, MYA, PHI, SRI, THA, VIE, NEP

Commelina communis L. Commelina diVusa Burm. f.

Commelinaceae

Corchorus aestuans L.

Tiliaceae

Characeae Poaceae Commelinaceae

Commelinaceae

IND, BAN, NEP, SRI

TUR, ITL USA (MSO, TX, ARK, LOU, MIS)

SRI

USA (CAL)

COT, AFR AFR, BAN, BHU, IND, IDO, KOR, LAO, MYA, NEP, NGR, PAK, PHI, SRI, THA, VIE IND, JPN, USA (ARK)

IND, SRI

AFR, BAN, BHU, BRA, IND, IDO, JPN, KOR, LAC, LAO, MAL, MYA, NEP, PHI, SRI, THA, USA, VIE BAN, IND, PHI, SRI, THA

AFR, IND, PHI, SRI

USA (ARK, LOU)

IND

167

Amaranthaceae

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Amaranthus viridis L.

(continued)

168

Table III (continued ) Type of direct‐seedingb Weed species

Family

DRSR

WTSR

AFR, BAN, BHU, CAM, CHI, CHL, IND, IDO, JPN, LAO, MYA, NEP, PAK, PHI, SRI, THA, VIE CAM, IND, IDO, LAO, MYA, NEP, PHI, SRI, THA, VIE,

IND, PHI, SRI

Cyperaceae

AFR, AUS, BAN, BRA, CAM, IND, IDO, KOR, LAC, LAO, MAL, NGR, PAK, PHI, SRI, THA, VIE, NEP

Cyperus esculentus L.

Cyperaceae

Cyperus ferax Rich. ¼ Diclidium ferax (Rich.) Schrad. ex Nees Cyperus haspan L.

Cyperaceae

AFR, BRA, IND, IDO, JPN, LAC, MAL, NEP, NGR, SRI, THA, USA (ARK, FLO, MIS) BRA, LAC

AFR, BAN, BHU, CHI, EGY, IND, JPN, NGR, POR, LAC, MAL, MYA, NEP, PHI, SRI, THA, VIE IND, LAC, SRI

Cyperaceae

Cyperus iria L.

Cyperaceae

Cyperus laetus J. Presl and C. Presl Cyperus odoratus L. ¼ Diclidium odoratum (L.) Schrad. ex Nees

Cyperaceae

Poaceae

Cyperaceae

Cyperaceae

AFR, BAN, CHL, IDO, IND, PHI, SRI, VIE, CAM, LAO, MYA, NEP, PAK, THA AFR, BAN, BHU, BRA, CAM, CHI, IND, IDO, KOR, LAO, LAC, MAL, MXC, MYA, NEP, PAK, PHI, SRI, THA, USA, VIE BRA USA (ARK), BAN, CAM, IND, LAO, MAL, MYA, PHI, SRI, THA, VIE

SRI, VIE

CHI, IDO, IND, MAL, SRI, VIE CHI, EGY, IDO, IND, LAC, MAL, MYA, PHI, SRI, THA, VIE

AUS, ITL, TUR, USA (CAL)

USA (ARK)

USA (ARK, LOU, MIS)

USA (ARK)

A. N. RAO ET AL.

Cynodon dactylon (L.) Pers. Cyperus brevifolius (Rottb.) Endl. ex Hassk. Cyperus diVormis L.

WRSR

AFR, BAN, BHU, CHI, COT, IDO, IND, JPN, KOR, LAO, LAC, MAL, MXC, MYA, NEP, NGR, PAK, PHI, SRI, THA, VIE KOR, ITL, BAN, CAM, LAO, MAL, MYA, NEP, PAK, SRI, THA, VIE

BAN, IND, PHI, SRI, THA

AFR, BAN, CHI, IND, IDO, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE AUS

IND, PHI

AFR, BAN, BHU, BRA, CAM, CHI, IND, IDO, JPN, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE AFR, BRA, COT, NGR

MAL, PHI, SRI

IND

USA (ARK)

AFR, BAN, EGY, IND, IDO, LAC, MAL, MYA, PHI, SRI, THA, VIE

ITL, TUR, USA (TX)

AFR, BAN, CHI, EGY, IND, JPN, KOR, LAC, MAL, MYA, NEP, PHI, SRI, THA, VIE

AUS, ITL, KOR, TUR, USA (ARK, LOU, MIS, MSO, TX, CAL)

Poaceae

AFR, BAN, BHU, IND, IDO, ITL, KOR, LAC, MAL, MYA, NGR, PHI, THA, USA (ARK) AFR, BAN, BHU, BRA, CAM, CHI, COT, IDO, IND, JPN, KOR, LAC, LAO, MAL, MYA, MXC, NEP, NGR, PAK, PHI, SRI, THA, USA (FLO, TX), VIE AUS, BAN, BHU, BRA, CAM, CHI, CUB, IDO, IND, JPN, KOR, LAC, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, USA (CAL, FLO, ARK, MIS, MSO, TX), VIE CAM, LAO, NEP, PAK, PHI

Poaceae

MAL, MYA, NEP, PAK, SRI, THA

PHI

TUR, USA (CAL)

Poaceae

MYA, NEP, VIE

MAL, VIE

ITL, USA (CAL)

Poaceae

MYA, THA,

MAL, PHI

Cyperus serotinus Rottb. ¼ Juncellus serotinus (Rottb.) C. B. Clarke Dactyloctenium aegyptium (L.) Willd.

Cyperaceae

Damasonium minus (R. Br.) Buch. Digitaria ciliaris (Retz.) Koel.

Alismataceae

Digitaria horizontalis Willd. ¼ Digitaria sanguinalis var. horizontalis (Willd.) Rendle Digitaria sanguinalis (L.) Scop.

Poaceae

Echinochloa colona (L.) Link

Poaceae

Echinochloa crus‐galli (L.) P. Beauv.

Poaceae

Echinochloa glabrescens Munro ex Hook. F. Echinochloa oryzoides (Ard.) Fritsch Echinochloa phyllopogon (Stapf) Stapf ex Koss Echinochloa picta (J. Konig) P.W. Michael

Poaceae

Poaceae

Poaceae

JPN, KOR

KOR

AUS

IND, PHI, SRI

169

Cyperaceae

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Cyperus rotundus L.

(continued)

170

Table III (continued ) Type of direct‐seedingb Weed species

Family

DRSR

WTSR

WRSR

Poaceae Poaceae

RUS, ITL, USA BAN, IND, MYA, NEP, PHI, SRI, THA

PHI, MAL, THA, VIE MAL, PHI, SRI

ITL, TUR, EUR, USA

Asteraceae

AFR, IND, MAL, PHI, SRI, THA, VIE

USA (ARK, LOU, MIS)

Eichhornia crassipes (Mart.) Solms Eleocharis acuta R. Br. Eleocharis kuroguwai Ohwi Eleusine indica (L.) Gaertn.

Pontederiaceae

Euphorbia heterophylla L.

Euphorbiaceae

Fimbristylis annua (All.) Roem & Schult. Fimbristylis dichotoma (L.) Vahl Fimbristylis miliacea (L.) Vahl

Cyperaceae

AFR, BAN, BHU, BRA, CAM, CHI, CHL, IND, IDO, JPN, LAC, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, USA (ARK), VIE BAN, CAM, IND, LAO, MYA, NEP, THA, VIE AUS JPN, KOR AFR, BAN, BHU, CAM, CHI, COT, IND, IDO, KOR, LAC, LAO, MAL, MYA, NEP, NGR, PAK, PHI, SRI, THA, VIE AFR, BHU, IND, IDO, COT, PHI, SRI, THA, VIE LAC

BAN, IND, JPN, LAC, MYA, PHI, SRI, THA, VIE AFR, BAN, CHI, GUY, IND, IDO, JPN, LAC, MAL, MYA, NEP, PHI, SRI, THA, VIE

LAC

Cyperaceae Cyperaceae Poaceae

Cyperaceae

Heliotropium indicum L.

Boraginaceae

Heteranthera limosa (Sw.) Willd. Heteranthera reniformis Ruiz & Pav.

Pontederiaceae

BAN, CHI, IND, IDO, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE AFR, BAN, BHU, BRA, CAM, CHI, GUY, IND, IDO, JPN, KOR, LAC, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE BAN, IND, IDO, LAO, MYA, PHI, SRI, THA, VIE IND, JPN, USA (ARK, MIS)

Pontederiaceae

BRA, IND

Cyperaceae

CHI, IND, MAL, SRI

JPN, KOR IND, PHI

KOR

LAC

LAC

ITL, USA (ARK, LOU, MIS, CAL) ITL

A. N. RAO ET AL.

Echinochloa spp. Echinochloa stagnina (Retz.) P. Beauv. Eclipta prostrata (L.) L.

Poaceae

BAN, IDO, IND, THA

Poaceae

Ipomoea grandifolia (Dammer) O’Donell Ipomoea lacunose L. Ipomoea wrightii A.Gray Ischaemum rugosum Salisb.

Convolvulaceae

AFR, BAN, BHU, CHI, IND, IDO, JPN, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE BRA, SRI

Convolvulaceae Convolvulaceae Poaceae

Leersia hexandra Sw.

Poaceae

Leersia japonica (Makino ex Honda) Honda Leersia oryzoides (L.) Sw. Leptochloa chinensis (L.) Nees

Poaceae

USA (ARK, LOU, MIS) GUY, IND, JPN, LAC, MAL, PHI, THA, VIE, SRI AFR, BAN, CHI, MAL, MYA, PHI, VIE CHI

KOR

Poaceae

ITL, JPN, MAL, THA CAM, CHI, IND, IDO, JPN, KOR, LAO, MAL, PHI, SRI, THA, VIE, BAN, PAK, IND, LAO NGR

POR, ITL

Poaceae

USA (MSO, TX)

USA (MSO, TX)

Poaceae

CUB, IND, ITL, USA

USA

Poaceae

AUS, USA (ARK, MIS)

AUS, USA (ARK, LOU, MIS, MSO, TX)

Poaceae

USA (ARK, MIS, TX)

Poaceae

CHI, LAO, MAL, SRI, USA (ARK, MSO, TX), VIE USA

Butomaceae

JPN, LAO, MAL, MYA, VIE, SRI

IND, MAL, MYA, PHI, SRI, THA, VIE AFR

IND

USA (ARK, LOU, MIS, MSO, TX)

BAN, JPN, LAC, MAL, MYA, SRI, THA, VIE

171

Leptochloa caerulescens Steud. Leptochloa dubia (Kunth) Nees Leptochloa fascicularis (Lam.) A. Gray. Leptochloa fusca subsp. fascicularis (Lam.) N. W. Snow Leptochloa panicea (Retz.) Ohwi Leptochloa panicoides (J. Presl) Hitchc. Limnocharis flava (L.) Buchenau

Poaceae Poaceae

JPN, USA (MIS) USA (ARK, LOU, MIS) AFR, BAN, BRA, CAM, CUB, GUY, IND, IDO, JPN, KOR, LAC, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE AFR, BAN, CAM, BRA, IND, LAO, MAL, NEP, PAK, SRI, THA, VIE

MAL, MYA

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Hymenachne acutigluma (Steud.) Gilliland Imperata cylindrica (L.) Raeuschel

(continued)

172

Table III (continued ) Type of direct‐seedingb Weed species

DRSR

WTSR

Scrophulariaceae

IND, IDO, MAL, SRI, THA, VIE

Scrophulariaceae

BAN, BHU, CHI, IDO, IND, SRI, THA, VIE

PHI

Scrophulariaceae

IND

Scrophulariaceae Scrophulariaceae

BAN, CAM, IND, IDO, LAO, MYA, NEP, PHI, SRI, THA, VIE JPN, USA (ARK) BAN, BHU, IDO, JPN, KOR, PAK, VIE

Onagraceae

BAN, CAM, IDO, IND, LAO, NEP, THA, VIE

Onagraceae

BAN, CAM, CHI, IDO, LAO, MAL, THA

Onagraceae

AFR, CHI, IND, MAL, MYA, PHI, THA, VIE AFR, MAL, PHI, SRI, MYA, THA AFR, BAN, IND, MAL, MYA, PHI, SRI, THA, VIE IND, MYA, PHI, SRI

Ludwigia prostrata Roxb.

Onagraceae

AFR, BAN, CAM, IDO, LAO, MAL, MYA, NEP, PHI, SRI, THA, VIE BAN, CAM, IND, LAO, MAL, MYA, NEP, PAK, SRI CAM, CHI, KOR, NEP, SRI, VIE

Luziola subintegra Swallen Luziola peruviana Juss. ex J. F. Gmel. Malachra fasciata Jacq. Marsilea minuta L.

Poaceae Poaceae

BRA

Malvaceae Marsileaceae

MXC, PHI BAN, CAM, LAO, MAL, PAK, SRI, THA, VIE

Marsilea quadrifolia L.

Marsileaceae

CAM, IDO, IND, LAO, MAL, NEP, PAK, PHI

Onagraceae

JPN BHU, JPN, KOR, SRI, VIE

KOR, BAN, IND, MAL, NEP, SRI LAC

AFR, BAN, BHU, IND, IDO, MAL, MYA, PHI, THA, VIE BAN, CHI, IND, JPN, MYA, NEP, SRI, VIE

WRSR

USA (ARK, LOU, MIS) KOR

KOR

A. N. RAO ET AL.

Limnophila aromatica (Lam.) Merr. Lindernia antipoda (L.) Alston Lindernia ciliata (Colsm.) Pennell Lindernia dubia (L.) Pennell Lindernia procumbens (Krock.) Borbas Ludwigia adscendens (L.) H. Hara Ludwigia hyssopifolia (G. Don) Exell Ludwigia octovalvis (Jacq.) P. H. Raven Ludwigia perennis L.

Family

Sterculiaceae

AFR, BAN, CAM, IND, IDO, MAL, NEP, PHI, THA, VIE CHI, IDO, IND, JPN, KOR, PHI, THA, VIE, LAO, NEP, PAK

IND, MAL, PHI, THA

Monochoria vaginalis (Burm. f.) C. Presl

Pontederiaceae

Murdannia keisak (Hassk.) Hand.‐Mass. Murdannia nudiflora (L.) Brenan Oryza longistaminata A. Chev & Roehr. Oryza sativa L. (weedy rice, red rice)

Commelinaceae

IDO, JPN, KOR, MAL

BAN, BHU, CHI, IDO, IND, JPN, KOR, MAL, MYA, NEP, NGR, PHI, SRI, THA, VIE KOR

Commelinaceae

BAN, LAC, IND, IDO, PHI, THA, VIE

BAN, SRI

Poaceae

AFR, MAL

AFR, SRI

Poaceae

AFR, BRA, EUR, GUY, IND, JPN, KOR, LAC, MYA, USA (ARK, MIS, MSO, TX)

Panicum repens L.

Poaceae

Paspalum distichum L.

Poaceae

Paspalum modestum Mez Paspalum scrobiculatum L.

Poaceae Poaceae

Phaseolus lathyroides L. ¼ Macroptilium lathyroides (L.) Urb. Phyllanthus fraternus G. L. Webster Physalis angulata L. Pistia stratiotes L.

Fabaceae

AFR, BAN, BRA, CAM, CHI, IND, IDO, ITL, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, USA (ARK), VIE BAN, BHU, CHI, IND, IDO, JPN, KOR, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE BRA AFR, BAN, CAM, CHI, IND, IDO, KOR LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE CAM, IDO, LAC, LAO, MAL, PHI, SRI, VIE

AFR, GUY, IND, JPN, LAC, MAL, MYA, KOR, SRI, THA, VIE IND, BAN, MAL, MYA, PHI, SRI

Euphorbiaceae

IDO, IND, NEP, PHI, THA, VIE, NEP

Solanaceae Araceae

BRA, USA (ARK) BAN, CAM, LAO, NEP, THA, VIE

BAN, CHI, IND, MYA, PHI, SRI, VIE

KOR, USA (CAL)

EUR, ITL, POR, USA (ARK, LOU, MIS, TX) USA (ARK, LOU, MIS)

ITL

USA (LOU) PHI

PHI

IND, PHI USA (ARK, LOU, MIS)

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Melochia corchorifolia L.

AFR, CHI, IND, MAL, MYA, PHI, SRI

173

(continued)

174

Table III (continued ) Type of direct‐seedingb Weed species

Family

DRSR

WTSR

Polygonaceae

BAN, BHU, BRA, CHI, IND, IDO, KOR, LAC, MAL, NEP, THA

KOR

Polygonaceae

ITL, USA (ARK)

SRI

Portulacaceae

IND, PHI, SRI,

Rotala indica (Willd.) Koehne Rottboellia cochinchinensis (Lour.) Clayton

Lythraceae

Sagittaria guayanensis Kunth Sagittaria longiloba Engelm. ex J.G. Sm. Sagittaria montevidensis Cham. & Schltd. ¼ Sagittaria pugioniformis var. montevidensis (Cham. & Schultz) Kuntze Sagittaria pygmaea Miq.

Alismataceae

AFR, BAN, BHU, CHI, COT, IND, IDO, JPN, KOR, MAL, MYA, NGR, PAK, PHI, SRI, THA, VIE AFR, BAN, CAM, CHI, IDO, IND, KOR, LAO, MYA, NEP, PAK, PHI, SRI, THA, VIE AFR, CHI, IND, IDO, JPN, KOR, LAO, LAC, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE BRA, CAM, GUY, IDO, LAO, MYA, NEP, PAK, SRI

Sagittaria trifolia L.

Alismataceae

Poaceae

WRSR

USA (ARK, LOU, MIS)

A. N. RAO ET AL.

Polygonum hydropiperoides Michx. ¼ Persicaria hydropiperoides (Michx.) Small Polygonum spp. (incl. P. pennsylvanicum L.) Portulaca oleracea L.

CHI, KOR, MAL, SRI, THA, VIE

GUY, LAC, MAL, THA, VIE

Alismataceae

USA (CAL)

Alismataceae

BRA, AUS

Alismataceae

CAM, CHI, IND, LAO, MAL, MYA, THA, VIE BAN, CAM, IDO, IND, LAO, MAL, MYA, NEP, PAK

AUS, USA (CAL)

CHI, JPN, KOR BAN, JPN, KOR, IND, NEP, SRI, THA, VIE

KOR

Spilanthes filicaulis (Schumach. & Thonn.) C. D. Adams Stenotaphrum secundatum (Walter) Kuntze Striga asiatica L. Kuntze Striga aspera (Willd.) Benth.

USA (CAL)

Cyperaceae

BAN, BHU, CAM, IND, LAO, NEP, PAK, SRI, THA

Cyperaceae

CAM, IND, ITL, JPN, LAO, MYA, NEP, PAK, PHI, SRI

Cyperaceae

MXC

Fabaceae

AFR, IND, LAC, MYA, PHI, VIE

Fabaceae

BAN, VIE

Fabaceae

IND, JPN, USA, LAC

Fabaceae

USA (ARK, MSO)

Poaceae Poaceae Poaceae

IND, BAN, JPN, NEP, SRI IND, KOR, PHI, VIE NGR

Poaceae

IND, ITL, JPN, PHI, USA

Campanulaceae

Asteraceae

AFR, BAN, CAM, IND, IDO, JPN, LAO, MAL, MYA, NEP, NGR, PAK, PHI, SRI, THA, USA (ARK), VIE AFR, COT, MYA

Poaceae

LAC

Scrophulariaceae Scrophulariaceae

AFR AFR

BAN, BHU, CHI, EGY, IND, KOR, MYA, MAL, NEP, SRI, THA IND, JPN, MAL, VIE

KOR

EUR, ITL, TKY, USA (CAL)

LAC USA (ARK, LOU, MIS, MSO) IND, SRI IND

USA (ARK, LOU, MIS) AFR, BAN, IND, JPN, KOR, LAC, MAL, MYA, NEP, NGR, PHI, SRI, THA, VIE

USA (ARK, LOU, MIS)

175

Cyperaceae

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Scirpus fluviatilis (Torr.) A. Gray. Scirpus juncoides Roxb. ¼ Schoenoplectus juncoides (Roxb.) Palla Scirpus mucronatus L. ¼ Schoenoplectus mucronatus (L.) Palla Scleria setuloso‐ ciliata Boeck. Senna obtusifolia (L.) H. S. Irwin & Barneby Sesbania bispinosa (Jacq.) W. Wight Sesbania exaltata (Raf.) Cory Sesbania herbacea (Mill.) McVaugh Setaria glauca (L.) P. Beauv Setaria viridis (L.) P. Beauv. Sorghum aethiopicum (Hack.) Rupr. ex Stapf. Sorghum halepense (L.) Pers. Sphenoclea zeylanica Gaertn.

(continued)

176

Table III (continued ) Type of direct‐seedingb Weed species

Family Aizoaceae

Urochloa platyphylla (Munro ex C. Wright) R. D. Webster Xanthium strumarium L.

Poaceae

a

Asteraceae

AFR, BAN, CAM, COT, IDO, IND, LAO, MAL, MYA, NEP, PAK, PHI, SRI, THA, VIE USA (ARK, MSO, MIS, TX)

BHU, IND, JPN, MYA, PAK, THA, USA (ARK, LOU, MIS)

WTSR

WRSR

IND

USA (ARK, LOU, MIS, MSO, TX) USA (ARK)

Based on the large number of references cited in this review and personal communications. DRSR, dry‐seeded rice; WTSR, wet‐seeded rice; WRSR, water‐seeded rice. c AFR, Africa; AUS, Australia; BAN, Bangladesh; BHU, Bhutan; BRA, Brazil; CAM, Cambodia; CHI, China; CHL, Chile; COT, Coˆte d’Ivoire; CUB, Cuba; EGY, Egypt; EUR, Europe; GUY, Guyana; IDO, Indonesia, IND, India; ITL, Italy; JPN, Japan, KOR, Korean peninsula; LAC, Latin America and Caribbean; LAO, Lao PDR; MAL, Malaysia; MYA, Myanmar; MXC, Mexico; NEP, Nepal; NGR, Nigeria; PAK, Pakistan; PHI, Philippines; POR, Portugal; RUS, Russia; SRI, Sri Lanka; THA, Thailand; TUR, Turkey; USA, United States of America (ARK, Arkansas; CAL, California; FLO, Florida; LOU, Louisiana; MIS, Mississippi; MSO, Missouri, TX, Texas); VIE, Vietnam. b

A. N. RAO ET AL.

Trianthema portulacastrum L.

DRSR

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

177

(Khalid, 1995), Philippines (De Datta and Baltazar, 1996; Rao and Moody, 1994), South Asia (Malik and Moorthy, 1996), Sri Lanka (Abeysekera, 1999; Haigh, 1951; Sangakkara et al., 2004), Thailand (Noda et al., 1984; Tomita et al., 2003a,b; Vongsaroj, 1995); the United States (Gianessi et al., 2002; Hill et al., 1994), and Vietnam (Chin et al., 2002; Koo et al., 2005; Mai et al., 2000; Tan et al., 2000). Tables such as this, arising out of weed surveys, commonly lead to the assertion that, even though a large number of species are known to be weeds of rice (Galinato et al., 1999; Moody, 1989), it is often only a small number of species that are considered to be economically important within a country. Such species are considered major as (1) they are competitive with rice and individually may cause severe yield loss (Ampong‐ Nyarko, 1996; Chin et al., 2002; Hassan and Rao, 1996; Kim and Ha, 2005; Tomita et al., 2003a,b), (2) they are usually abundant (Caton et al., 2004; Galinato et al., 1999), (3) they exhibit high colonization rates (Bocchi et al., 2005; Tan et al., 2000), and (4) they are resilient to current and past control measures. Table III includes over 140 species covering 27 families in which members of the Cyperaceae and Poaceae are the most dominant. Equally, the species listed present a diversity of life forms and life histories, including obligate aquatic and terrestrial species and ‘‘semi‐aquatics,’’ with some species being recorded under all three methods of direct‐seeding. Such lists need to be considered cautiously when asserting the importance of an individual species. Ranking the comparative damage done by a single species is fraught with diYculty given the interaction of factors and processes in weed–crop interference in the field that ultimately leads to yield loss in the crop or economic damage in general. Cousens and Mokhtari (1998) and Jasieniuk et al. (2001) in examining competitiveness and yield loss in selected weed species concluded that there was little correlation of competitiveness across seasons, and yield losses in response to weed density varied considerably. However, such lists reflect the persistence of a species under the suite of crop and weed management practices practiced in the recent past.

1.

Dry‐Seeded Rice

More than 50 weed species infest irrigated DSR and cause major yield losses in the United States (Dilday et al., 2000). Dry drill‐seeded, flush‐ irrigated rice in the southern states of the United States is infested with dryland weeds (e.g., Urochloa platyphylla) early in the season, followed by aquatic weeds (e.g., Heteranthera limosa) after the permanent flood. Red rice (O. sativa L.) remains the most troublesome weed in rice production of Louisiana, Arkansas, and Missouri (Gianessi et al., 2002) but is excluded from California. Echinochloa spp. constitute the major weed species in all

178

A. N. RAO ET AL.

rice‐growing areas of the United States (Echinochloa crus‐galli, in Mississippi and Texas and Echinochloa crus‐galli, Echinochloa phyllopogon, and Echinochloa oryzoides in California). Similarly, in Italian rice production, predominantly terrestrial weeds are recruited into the flora initially and followed by semi‐aquatic and aquatic species. Bocchi et al. (2005) recorded that species emerging in the initial dry phase prior to flooding were Echinochloa spp., Panicum dichotomiflorum (L.) Michx, Cyperus serotinus, Bidens spp., Digitaria sanguinalis, Sorghum halepense, and Polygonum spp., with a second less competitive group of weeds emerging later (Bolboschoenus maritimus, Schoenoplectus mucronatus, and Leersia oryzoides). In the Krasnodar region (Russia), aquatic perennial weeds B. maritimus and Bolboschoenus compactus (HoVm.) Drobow, wild rice varieties (O. sativa var. ferruquinoza), and Echinochloa spp. were recorded as strong competitors with rice (Dobermann, 1992). A total of 351 weed species were identified in diVerent rice‐growing areas of Cuba, with the largest yield reduction occurring with Echinochloa crus‐galli (Antigua, 1993). In Asia, lowland DSR fields have a more species‐rich vegetation and greater diversity in the weed flora than transplanted rice (Tomita et al., 2003a). Ludwigia hyssopifolia (G. Don) Exell and F. miliacea L. have been observed season long in both DSR fields and transplanted fields, irrespective of water level (Tomita et al., 2003a,b). Cynodon dactylon (L.) Pers., Panicum repens L., Paspalum scrobiculatum L., Melochia corchorifolia L., and Digitaria elongata Trin Spreng. infested DSR fields, whereas Ludwigia adscendens (L.) Hara was mainly observed in transplanted fields. Panicum repens L., Paspalum scrobiculatum L., and Digitaria elongata especially grew under poor‐ (flooding for 0–60 days) and medium‐water (flooded for 60–120 days) conditions (Tomita et al., 2003a,b). In Indonesia, 56 weed species covering 18 families were recorded in dry‐seeded bunded rice, which is raised on sloping lands (Pane et al., 2000). Weed communities remaining after farmer weeding at upper‐ and mid‐positions of the toposequence were similar in species composition (Lindernia spp., Echinochloa colona, F. miliacea, and Murdannia nudiflora). These diVered from those at the base of the toposequence, which was dominated by Ammannia baccifera, Echinochloa colona, F. miliacea, and Leptochloa chinensis. Weedy rice (O. sativa) ecotypes have become a major cause of yield loss in irrigated DSR in Malaysia (Azmi et al., 2003), Thailand, and Vietnam, particularly under dry‐seeding conditions (Chin, 1997). Kim and Ha (2005) also recorded weedy rice along with annual grasses, such as Echinochloa crus‐galli, Digitaria ciliaris, Leptochloa chinensis, and Setaria viridis, as the most predominant weeds of dry‐seeded rice in Korea. In Coˆte d’Ivoire, West Africa, weed species in upland rice diVered between forest and savannah zones, with Chromolaena odorata (L.) R. M. King and Robinson being common in the former and Platosoma africanum

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

179

P. Beauv. and Mariscus cylindristachus in the latter (Kent et al., 2001). These authors also observed that Bacopa decumbens, Fimbristylis littoralis, Sphenoclea zeylanica, and Echinochloa colona were common in both forest and savannah lowlands, whereas the sedges Cyperus diVormis and Cyperus iria were particularly abundant in the savannah. Echinochloa spp. were the most common weeds in fully irrigated systems, and Panicum laxum Sw. was more common in imperfectly irrigated fields (Becker and Johnson, 1999). Roder et al. (1997) recorded the major weed species of upland dry‐seeded rice of Laos in terms of cover and frequency in farmers’ fields. They were Chromolaena odorata, Ageratum conyzoides, Commelina spp., Lygodium flexuosum, Panicum trichoides, Corchorus spp., Pueraria thomsonii, Panicum cambogiense, and Imperata cylindrica. Although C. odorata was the most abundant weed, farmers generally did not consider it as a serious weed because of ease of control, reflecting a belief in zero opportunity cost of manual weeding. In Vietnam, the major weeds in farmers’ dry‐seeded rice fields were Echinochloa crus‐galli, Echinochloa glabrescens, and F. miliacea (My et al., 1995). Weed infestations of upland rice are one of the main issues confronting the sustainability of cropping systems in North Vietnam. Stevoux et al. (2002) recorded Ageratum conyzoides, Crassocephalum crepidioides, Paspalum conjugatum, Eleusine indica, and Imperata cylindrica together with adventive species from forest area (Lygodium flexuosum, Trema angustifolia, and Melastoma sp.). In dry‐seeded bunded rice in Indonesia, weed species commonly observed after farm weeding were Eclipta alba, Echinochloa crus‐galli, Echinochloa colona, F. miliacea, Cyperus diVormis, and C. rotundus (Pane et al., 2000). The existence of grass weeds such as Echinochloa crus‐galli, Leptochloa chinensis, and I. rugosum, and of Cyperus diVormis clearly poses a significant threat to rice intensification and underlines the importance of eVective weed control.

2.

Wet‐ and Water‐Seeded Rice

Wet‐ and water‐seeding provide an aquatic environment for the germination of weed species adapted to germinate in an anaerobic and partially anaerobic environment. As a consequence, there is a tendency for annual aquatic weeds to predominate. Water‐seeded rice in Australia tends to be infested with Cyperus diVormis, Damasonium minus, Sagittaria montevidensis, Alisma plantago‐aquatica, and Alisma lanceolatum (Skinner and Taylor, 2002). Alisma plantago‐aquatica and Scirpus mucronatus have been identified as troublesome weed species in rice of Europe (Weber and Gut, 2005). Water‐seeded rice in California has experienced an increase in the importance of Echinochloa oryzoides and Echinochloa phyllopogon with the adoption of continuous flooding to suppress Echinochloa crus‐galli. Echinochloa

180

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oryzoides and Echinochloa phyllopogon in dense infestations continue to cause yield loss (Fischer et al., 2000b). Leptochloa spp. have also been recorded in water‐seeded rice (Hill et al., 1994). A recent survey of the occurrence of weeds in water‐seeded rice in the Red River Delta of Vietnam recorded 60 weed species from 19 families, the most important families again being the Poaceae and Cyperaceae. The most widespread species, occurring at >50% sites in spring and summer, was Rotala indica, followed by Echinochloa crus‐galli and Cyperus diVormis (Tan et al., 2000). The dominant weeds of wet‐seeded rice in the Mekong Delta of Vietnam included the latter two species and Leptochloa chinensis, F. miliacea, and C. iria (Chin and Mortimer, 2002). Kim and Ha (2005) concluded that Echinochloa crus‐galli, Murdannia keisak (Aneilema keisak), Ludwigia prostrata, and Leersia japonica were the dominant weeds of wet‐seeded rice in Korea.

B. CROP–WEED COMPETITION IN DIRECT‐SEEDED RICE The outcome of the process of interspecific competition among plant species is the diVerential acquisition of resources for growth and yield. At the population level, resource acquisition is density dependent and it is only when there is spatial and or temporal niche diVerentiation that two species can coexist. In plant species, the most important competition is usually preemptive competition that occurs among seedlings, since it is almost impossible for a seedling of one species to outcompete an established adult of another species. The inherent size diVerence between rice seedlings and emerging weed species that confers a competitive advantage to transplanted rice is removed when direct‐seeding is practiced. Relative outcomes of competition between a weed species and direct‐seeded rice are, however, influenced by weed species and rice cultivar, weed and crop density, and competition duration as governed by the selective removal of the weed species, along with associated agronomic and cultural management factors. Although rice is sown at a seed rate to ensure an optimal dense plant stand, infestations of weed species may result in a near total loss of yield. Gibson et al. (2001) recorded a grain yield reduction of up to 99% with a mixed infestation of Echinochloa oryzoides and Echinochloa phyllopogon in wet‐seeded rice. Ferrero and Nguyen (2004) reported similar findings for European rice weeds. The literature contains numerous examples of yield losses in response to the density of individual weed species (Marambe, 2002; Mishra, 2000; Smith, 1988), but interspecific comparisons of their impact provide little value in assessing relative competitiveness. This is because studies are usually conducted over too narrow a density range and rarely carried out concurrently under the same experimental conditions. Nevertheless,

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this has not reduced the desire to develop weed management tools based on the concepts of critical periods of crop competition and economic thresholds. Cousens (1987) argued that the use of short‐term economic thresholds as a within‐season management tool has little value for two reasons: (1) wide variation is seen in yield response to the same weed density when intersite comparisons are made and (2) it is diYcult to accurately anticipate the future market value of the crop. Long‐term economic thresholds that take into account how weed control in one year aVects future weed infestation densities and how financial decisions made in the present year impact on future expenditures for weed control appear to oVer a more sound basis on which to develop a weed management plan. To be eVective, these decisions require a detailed understanding of the population dynamics of the weed species under control measures (Wallinga, 1998). However, Jones and Medd (2000) have suggested that the integration of control tactics using dynamic optimal decision rules with a long‐term planning horizon can both maximize farm returns and lead to the exhaustion of weed seed banks and that this is superior to the use of long‐term economic thresholds. Such approaches, however, necessarily focus on a single weed species, which merits attention because of diYculty to control. The concept of a critical period of crop–weed competition (the crop‐ growth period measured empirically during which yield is reduced by weed competition, Zimdahl, 1999), introduced by Nieto et al. (1968), holds an attraction in that it draws attention to the critical time period when weeding should occur. It suVers criticism, however, for many of the same reasons that may be leveled at the use of thresholds, and its methodological empiricism underlines its limitations. The weed flora in toto is presumed to be injurious, and no distinction is made between the nature of competitive processes that may be occurring. For instance, in DSR, preemptive (exploitative) competition for light initially may be most important but give way later to interference competition for other resources. While Gibson et al. (2001) showed that complete suppression of Echinochloa phyllopogon occurred if emergence was delayed for 30 days after rice seeding (DAS) or longer, the shape of the yield loss curve resulting from periods of earlier introduced competition diVered among seasons. Similarly, in field trials of dry‐seeded irrigated rice, 95% of a weed‐free rice yield was obtained by controlling weeds until 32 DAS in the wet season and until 83 DAS in the dry season in the Senegal River delta (Johnson et al., 2004). The authors argued that the occurrence of diVerent weed species and lower growth temperatures in the early dry season accounted for the diVerences in the critical period for competition. The time after which weeding may be suspended often coincides with periods of maximum tillering of the crop and consequent canopy closure, which may well explain the maximum days in the ranges reported in dry‐ (15–45 DAS; Singh et al., 1999;

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Yaduraju and Mishra, 2004) and wet‐seeded (15–30 DAS; Azmi, 1991) rice. However, there is evidence that both above‐ and below‐ground competition plays a major role in governing competitive outcomes in rice–weed mixtures and that it may be that the seasonal variation seen in many studies is a reflection of temperature‐mediated diVerential resource responses. Such observations have led to several authors emphasizing the importance of mechanistic modeling of rice–weed interactions (Caton et al., 1999a; KropV and Lotz, 1993; KropV et al., 1993; Lindquist and KropV, 1996). The general conclusion that emerges from studies of rice–weed competition for DSR is that competitive processes occur earlier in the life of the crop and reemphasize the oft‐quoted need for early weed control. This also underlines the importance of land preparation for seedbeds and the use of early postemergence chemical weed control.

C. WEED SPECIES SHIFTS AND WEED POPULATION DYNAMICS DUE CHANGES IN THE METHODS OF RICE ESTABLISHMENT

TO

1. Weed Species Shifts Preadaptation, evolution, and alien immigration are the three principal, but not mutually exclusive, means by which weeds species become incorporated into a weed flora (Mortimer, 1990). While natural selection giving rise to herbicide resistance (Maxwell and Mortimer, 1994) and evolution by crop mimicry (Hirosue et al., 2000) together with alien immigration often through seed importation (Hodkinson and Thompson, 1997; Rao and Moody, 1990; Yan and Yin, 1994) have led to new or resurgent weed infestations in many ecosystems, preadaptation is perhaps the most common means. Preadapted weed species are those that are resident in an agroecosytem within dispersal distance of a crop and come to predominate through a change in management practice. The soil seed banks of irrigated and rainfed rice fields may exhibit high floristic diversity for two reasons: (1) in Asia, seasonal switching between a diverse terrestrial vegetation in dry‐season crops and a much altered aquatic and semi‐aquatic flora in the wet season on the same area of land is common practice (Moody, 1983) and (2) additionally, the landscape of rice agriculture is fragmented within a season since it simultaneously oVers terrestrial (bunds), aquatic (irrigation channels), and semiaquatic (drainage channels) habitats for weed growth. Moreover, typically high seed densities (in excess of 107 propagules per m3) have been reported (Sahid et al., 1995) in rice field soils. The weed species shift evidenced with the switch from transplanting to direct‐seeding is a prime example of preadaptation.

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Table IV DiVerences in Weed Flora in Relation to Crop Establishment Method Method of establishment and year Weed flora Number of species Number of genera Number of families

Transplanted (1979)

Dry‐seeded (1987)

21 18 13

Major weed species (ranked by density) Monochoria vaginalis Ludwigia hyssopifolia Fimbristylis miliacea Cyperus diVormis Limnocharis flava

50 38 22 Echinochloa crus‐galli Echinochloa colona Leptochloa chinensis Scirpus grossus Fimbristylis miliacea

Wet‐seeded (1989) 57 44 28 Echinochloa crus‐galli Leptochloa chinensis Fimbristylis miliacea Marsilea crenata Monochoria vaginalis

Source: Ho (1991) for the MUDA area in Malaysia.

Ho (1991) reported on changes in the weed flora of Malaysian rice with the use of direct‐seeding as a result of the adoption of double cropping of rice in the late 1970s. Double cropping for food security was made feasible with the introduction of irrigation and drainage schemes and with increased use of mechanization for land leveling. Adoption of both dry and wet direct‐ seeding in place of transplanting resulted in an increase in floristic diversity and a change in the relative dominance of the major weed species (Table IV). In a longer and more detailed study covering the transition from transplanting to direct‐seeding and the continued use of direct‐seeding in Malaysia, Azmi and Mashor (1995) and Azmi (personal communication) assessed the dominance structure of the weed flora present at 60 DAS/days after transplanting (DAT) in fields after farm weeding had been completed. Figure 4 illustrates the changes in the weed flora from 1989 to 2001 when two rice crops were grown in a year. A total of 46 species were present in transplanted rice in 1989, logarithmically distributed in terms of abundance, with the flora being dominated by Sagittaria guayenensis, Monochoria vaginalis, Limnocharis flava, and F. miliacea. After a further six seasons of cropping and substantive adoption of wet‐seeding, this dominance had changed, with the principal weeds being graminaceous, including Echinochloa spp., Ischaemum rugosum, and Leersia hexandra, and 21 new species being added to the flora. By 2001, ‘‘weedy’’ rice was the most dominant weed, followed by Echinochloa spp., Leptochloa chinensis, and Ischaemum rugosum. A species that persisted throughout this study period was F. miliacea. Although diVerences in weed management practices were not recorded at the field level, variation in herbicide use among farmers has been reported (Azmi and Baki, 1995). The shift in dominance of weed species from dicotyledonous

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Rank order 100.00 1

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Sagittaria guayanensis Monochoria vaginalis Limnocharis flava Fimbristylis miliacea

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Fimbristylis miliacea Sagittaria guayanensis Echinochloa crus-galli var. crus-galli

Echinochloa crus-galli

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Oryza rufipogon Weedy rice Echinochloa spp. Leptochloa chinensis

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Rank order Figure 4 Changes in weed species composition in response to direct‐seeding. Species are ranked in order of proportional abundance based on area coverage per m2. Data from Azmi and Mashor (1995), Mortimer and Hill (1999).

and sedge species in transplanted rice to competitive grassy weeds in DSR has been related by several authors to the continuous use of herbicides in weed‐control operations since all rice farmers who practiced direct‐seeding adopted chemical weed control (Azmi and Baki, 1995; Ho, 1998). Azmi and Baki (1995) observed that Echinochloa crus‐galli was dominant in the plots

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repeatedly sprayed with 2,4‐D, whereas M. vaginalis became dominant with the repeated use of molinate/propanil, thiobenacarb/propanil, pretilachlor, quinclorac, propanil, and fenoxaprop‐ethyl. Molinate use suppressed Echinochloa crus‐galli but caused an increased infestation of Leptochloa chinensis and I. rugosum (Azmi and Mashor, 1995). In wet‐seeded rice, when serial applications of bensulfuron and 2,4‐D were applied, Scirpus grossus and Echinochloa crus‐galli, respectively, predominated (Azmi and Mortimer, 2002). In Malaysia, Azmi and Baki (2003) reported that Limnophila erecta Benth. and Bacopa rotundifolia Wettst. had become dominant weeds in areas where sulfonylurea herbicides were used continuously. Changes in rankings of dominant weeds were observed by Singh et al. (2005a) in response to both dry‐ and wet‐seeding of rice in the Indo‐Gangetic plains (Fig. 5). After four seasons of rice cropping, at 56 days after planting, Ischaemum rugosum and F. miliacea were the dominant species of unweeded wet‐seeded plots and Echinochloa colona and Commelina diVusa of dry‐ seeded plots in comparison with Cyperus iria and Echinochloa colona in transplanted rice. Manual weeding 30 days after sowing led to increased importance of Cyperus rotundus in wet‐seeded rice and Ischaemum rugosum in dry‐seeded rice. Yaduraju and Mishra (2005) reported that sedges such as Cyperus iria and Cyperus diVormis were common under both wet‐ and dry‐seeded conditions, whereas C. rotundus and Fimbristylis dichotoma (L.) Vahl were dominant in rainfed uplands where dry‐seeding was practiced. In Jiangsu and Zhejiang provinces in eastern China, the long‐term use of butachlor and molinate in rice has led to the elimination of Echinochloa crus‐ galli, with an associated increase in other species, including Leptochloa chinensis, Sagittaria montevidensis, Alternanthera philoxeroides (Mart.) Griseb., Juncellus serotinus, and Scirpus planiculmis (Zhang, 2003). Similarly, in Sri Lanka, usage of alternate herbicides for controlling propanil‐resistant Echinochloa crus‐galli has resulted in a shift in dominance to Ischaemum rugosum with continuous use of quinclorac and to Leptochloa chinensis with continuous use of bispyribac‐sodium (Marambe, 2002).

2.

Weed Population Dynamics

Understanding the processes governing the persistence of a weed species or the underlying reasons for an increase with a change in management requires a reductionist approach examining the comparative population dynamics of individual species under alternative management regimes. Figure 6A shows the flux in population size of Echinochloa crus‐galli in wet‐seeded rice and emphasizes the species’ ability to compensate for losses

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186 A Dry biomass (g m−2)

10

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Echinochloa Cyperus iria colona Ischaemum Echinochloa colona rugosum Cyperus iria Caesulia axillaris Caesulia axillaris Cyperus difformis

Leptochloa chinensis

Leptochloa chinensis 0.1

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Fimbristylis miliacea 10

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Cyperus difformis Caesulia Cyperus rotundus axillaris Echinochloa crus-galli Ischaemum rugosum Commelina diffusa Cyperus rotundus Cyperus iria Fimbristylis miliacea Echinochloa colona

0.1

C

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Commelina diffusa Echinochloa Cyperus rotundus Cyperus iria 10 colona Ischaemum Fimbristylis Caesulia axillaris miliacea rugosum Ischaemum rugosum 1 Cyperus rotundus Echinochloa crus-galli Leptochloa chinensis Caesulia axillaris 0.1

Figure 5 Abundance (dry biomass) of weeds at 56 days after establishment in: (A) transplanted rice, (B) wet‐seeded rice, and (C) dry‐seeded rice. All plots were maintained under saturated soil conditions 30 days after planting. The upper curve in each pair is from unweeded plots, the lower from plots manually weeded, 30 days after establishment [Source: Singh et al. (2005a)].

during the seedling recruitment phase due to early flooding and in the fallow periods between cropping seasons through both adult plant fecundity and the existence of a persistent seed bank in the soil. Seed dormancy ensures a persistent seed bank (Fig. 6B), which at a 15‐cm soil depth may exhibit a half‐life of more than 3 years, from which seedling recruitment may occur as a result of land preparation. An isolated plant of

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Echinochloa crus‐galli may produce more than 6000 caryopses. The likelihood of successful plant establishment into a developing canopy is governed in part by the speed of attainment of autotrophy after germination. This in turn is dependent on the water profile (depth and duration of flooding events) and light regimes experienced in early seedling growth, particularly in wet‐seeded rice. In Echinochloa crus‐galli, carbohydrate mobilization and subsequent partitioning to developing biomass may result in the onset of autotrophy before leaf emergence above the water surface in an illuminated water column (Fig. 6C). In contrast, in total darkness (as a model of deep, turbid water), there is a maximum shoot height that can be achieved before the exhaustion of reserves. Mortimer et al. (2005) reported that this height was 80 mm for one accession of Echinochloa crus‐galli, with evidence of enhanced height extension rate when seedlings were under water. Once the plant is committed by germination to growth, the ability to photosynthesize under water at lowered light intensities and to mobilize resources to develop photosynthetic structures out of water, together with adaptations to hypoxia, are key traits influencing plant survivorship. Figure 7 contrasts the dynamics of weed seedling recruitment in wet‐seeded and transplanted rice and highlights that the net recruitment of weed seedlings was confined to the first 14 DAT in flooded transplanted rice and only extended beyond that date in graminaceous species in plots that were initially wet‐seeded and subsequently flooded to a shallow (<50 mm) depth. Late‐emerging cohorts of grass species predominantly comprised the large‐seeded species Ischaemum rugosum, Echinochloa crus‐galli, and Echinochloa glabrescens. In dry‐seeded rice, similar patterns of early recruitment of weeds have been observed (J. D. Janiya, personal communication). The preceding discussion identifies key processes in the regulation of weed seedling recruitment in relation to direct‐seeding in which seed size is an important attribute and in some species is ecologically correlated with seed dormancy traits. Seed size in rice weeds varies on a logarithmic range from about 10 mg (Sphenoclea zeylanica and Cyperus diVormis) to greater than 104 mg (Rottboellia cochinchinensis). In small‐seeded species, the absence of oxygen (M. vaginalis) or lowered oxygen concentration (Zinzania aquatica), fluctuating diurnal temperatures (Najas graminea), and diVerential responses to spectral light ratios (Sphenoclea zeylanica) have all been shown to be cues involved in response mechanisms that govern seed germination rates under water. Phytochrome‐mediated switches in response to red/far‐red light ratios provide another probable mechanism governing germination, although there has been little detailed work on the features of photocontrol of germination of many small‐seeded rice weeds (Sanders, 1994). Gap‐detection mechanisms are moreover likely to confer fitness advantages in a rice–weed community that will experience largely uniform canopy

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188 A

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Figure 6 (A) Flux in population size (log scale) of Echinochloa crus‐galli from an initial infestation of 1000 seeds over two cropping seasons of wet‐seeded rice in the Philippines. Early flooding (4 DAS, open circles) as opposed to late flooding (12 DAS, closed circles) causes death in 50% of seedlings (dry season) and prohibits recruitment of successive seedling cohorts (wet season). The population suVers 97% loss (by seed removal in harvesting and in fallow germination), accounting for the reduction in seedling population size at the start of the wet season, but surviving plants compensate by increased seed production to return the Echinochloa crus‐galli seed population to high densities again. From Mortimer (1998). (B) Seed bank dynamics over two seasons. Seed populations were buried in open mesh bags at depths of 5 or 15 cm, exhumed at regular intervals and tested for viability. From Mortimer (1998). (C) Seedling growth responses (biomass and shoot height) in response to flooding. Germinated seeds were placed in water columns containing nutrient solution to a depth of 50 mm and either illuminated (light/dark) on a 12 h cycle (PAR 450 mE m2 s1) or maintained in total darkness at a temperature of 30/20  C day/night. From Mortimer et al. (2005). (Source: International Rice Research Institute.)

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closure, often within 30–40 days. Equally evident is the fact that small‐seeded species such as Cyperus diVormis exhibit polymorphisms in germination response to flooding, providing ‘‘bet‐hedging’’ tactics against unpredictable flooding events. Conversely, some species (F. miliacea, Echinochloa colona) exhibit little or no innate or induced dormancy and germinate rapidly on the surface of saturated soils but not under water (Kim and Moody, 1989). As with temperate terrestrial weed species (Cousens and Mortimer, 1995), there also appears to be no statistical relationship between seed fecundity and seed weight when considering a range of weed species across several taxa, although seed size and number vary over similar orders of magnitude (Fig. 8).

1000

Broadleaf - shallow Broadleaf - deep Grass - shallow Grass - deep Sedges - shallow Sedges - deep

Wet-seeded rice

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Plants m−2 (log scale)

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Days after transplanting Figure 7 Changes in size of weed communities (grouped into grasses, sedges and dicotyledonous weeds during a cropping season in transplanted or direct‐seeded rice). Plots were either flooded to a depth of at least 10 cm (deep) or less than 5 cm (shallow) from 7 DAS/DAT for the duration of a direct‐seeded or transplanted crop. No weeding was done. Data from Hill et al. (2001). (Source: International Rice Research Institute.)

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190 6

Ludwigia octovalvis

Ludwigia hyssopifolia

Celosia argentea Scirpus grossus Dactyloctenium aegyptium Eleusine indica

Fecundity seed per plant (log scale)

5

Leptochloa chinensis Eclipta alba Portulaca oleracea Fimbristylis miliacea Panicum maximum Cyperus iria Echinochloa crus-galli Monochoria vaginalis Ischaemum rugosum Rotala indica Rottboelia cochinchinensis Cyperus rotundus Echinochloa Commelina benghalensis colona Tridax procumbens

Cyperus difformis 4

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Leersia hexandra Cyanotis axillaris 2

1 0

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Seed biomass, µg (log scale)

Figure 8 Seed size fecundity relationships in selected seed‐producing weed species [Sources: Kim and Moody (1989); Sanders (1994)].

III.

INTEGRATING WEED MANAGEMENT PRACTICES IN DIRECT‐SEEDED RICE

The traditional practice of puddling soil to kill existing weeds and aid water retention, transplanting rice seedlings into standing water to achieve an optimum stand density, and maintaining standing water to suppress weeds, followed by one or several periods of manual weeding, is a well‐ established example of integrated weed management (IWM). It is integrated in the sense that it involves preventive actions followed by precise interventions as a response to the consequences of suites of preventive measures. There is, to our knowledge, no definitive rigorous experimental disassembling of this entire process because the experimentation involved would be considerable. However, inference and prevailing farmer practice are suYcient

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to groundtruth much of the assertion but not to quantify the magnitude of the individual components. Tillage and puddling soil constitute a preventive process which provides the multiple functions of vegetation clearance, soil mixing, and reduction of water loss by downward percolation. In the absence of tillage, a young transplanted crop is placed in a resource‐poor habitat characterized by early intense weed competition. A second preventive component is standing water above which a crop canopy matures, resulting in a systematic light reduction, with canopy development conferring resource‐advantage to the crop. Poor choice of initial stand density and variable density of planting together with variability in water depth combine to selectively alter niche dimensions for weed germination and establishment, as discussed above. Manual weeding constitutes an intervention as a consequence of the selective failure of preventive measures. Classifying weed control measures as either preventive or interventionist provides a way of evaluating control procedures in the context of both their contribution to IWM and to the biology and ecology of target species. Most definitions of IWM have two features in common: (1) the use of multiple control tactics and (2) the integration of knowledge of weed biology into the management systems (Davis and Ngouajio, 2005). Liebman and Gallandt (1997) have described IWM as the choice and application of weed management practices as ‘‘many little hammers,’’ which in combination provide crop protection from weed competition and suppress weed communities. Long‐term management of weed communities without excessive reliance on a single method is a key feature of the strategy of IWM. Rice crop establishment, whether by wet‐ or dry‐seeding, represents a major change in the habitat template that interspecifically governs the recruitment of weed species. It is this phase which removes the preventive eVects of standing water on weed recruitment, dramatically reduces the seedling age diVerence between the crop and weeds, and places a premium on early interventionist selective control that is achieved with chemical control. This is not, however, to argue that preventive tactics do not play a role in weed management in DSR. An integrated approach involving cultural practices, crop rotation, stale seedbed practices, selection of suitable competitive varieties, and the use of herbicide mixtures is essential in responding to changes in weed community structure in DSR (Sharma, 1997; Yaduraju and Mishra, 2004). As discussed by many authors (Hassan and Rao, 1996; Radosevich et al., 1997; Zimdahl, 1999), cultural methods of weed control are preventive in nature since they function to enhance crop growth by precision agronomy and in so doing maximize crop competitiveness against weeds. In this chapter, we consider land preparation, water management, and choice of cultivar in the context of preventive weed control practices before considering the use of herbicides and manual weeding in the context of interventions.

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A. PREVENTIVE METHODS OF WEED CONTROL 1.

Land Preparation

Land preparation through tillage operations such as plowing, disking, harrowing, soil puddling, and land leveling contributes to reduced weed growth by providing weed‐free conditions at planting in addition to the suppression of growth of certain perennial weeds (De Datta and Baltazar, 1996). These practices in a cumulative way cause cryptic seed and seedling mortality at depths within the soil profile and influence the dormancy status of buried seed populations through exposure to altered temperature (Forcella et al., 1993), gaseous (Corbineau and Coˆme, 1995; Pons and Schroder, 1986) and water regimes (Dekker, 1999). As a consequence, the frequency, depth, and timing of cultivation operations are important in governing the emerging weed flora both in the seedbed and in designing tillage operations to maximize the value of stale seedbeds. In Asia, conventional farm tillage practice for double‐cropped DSR often involves a sequence of land cultivation between rice crops. Typically, this is dry tillage after harvest followed by cycles of wet tillage, and subsequent land leveling, before wet‐seeding of rice (Azmi and Mortimer, 1999). Earlier work (Ho, 1996; Ho and Itoh, 1990) showed that populations of the perennial grass Echinochloa stagnina may be considerably reduced by flooding and puddling the field twice in contrast to a single round of dry rotovation prior to seeding. In this case, the improved control was due to suppression of regrowth from stolons in standing water. Hach et al. (2000) confirmed that wet tillage in contrast to dry tillage reduced the density of weed seedling populations in wet‐seeded rice to the greatest extent but noted increased infestations of Echinochloa crus‐galli and Paspalum distichum in the absence of tillage. Azmi and Mortimer (1999) noted that M. vaginalis achieved greater abundance in the developing crop after wet tillage prior to establishment, in contrast to sedges, in particular F. miliacea, under dry tillage. They hypothesized that two cycles of wet tillage before crop establishment were suYcient to break seed dormancy in M. vaginalis, which requires exposure to anaerobic conditions to promote germination (Yamasue and Ueki, 1983). Dry tillage enforced the dormancy of F. miliacea through lack of soil moisture, prohibiting seed losses that would normally occur under wet tillage. As with wet‐seeded rice, it has been shown that increasing the number of tillage operations before dry‐sowing of rainfed rice reduces weed infestation and contributes to rice yield gain (Sharma, 1997). Bhagat et al. (1999) reported that two plowings at the time of land preparation significantly reduced broadleaf weed density compared with one plowing but further increasing tillage frequency did not aVect groups of weed species significantly.

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Dry land tillage is the most common method of land preparation for much dry‐seeded rice in the United States, southern Australia, most of Latin America and West Africa, parts of tropical Asia, and most of Europe (De Datta and Baltazar, 1996). It usually involves one to two plowings or disking 10‐ to 20‐cm deep followed by 2–3 harrowings with a spike‐tooth or disk harrow and sometimes a roller‐packer to break up big clods and then land leveling (Anon, 1990). Comparison of the change in weed flora with the adoption of zero or reduced tillage techniques provides an indication of the preventive control measures arising from conventional tillage practices, given similar water regimes subsequently. Ipomoea wrightii Gray is one species that was suppressed by conventional tillage but increased with zero tillage (Gealy, 1998). Weed species shifts have been reported to occur with the adoption of dry‐seeding and zero tillage, with annual grass weeds in particular increasing in density (Tuong et al., 2005). Singh et al. (2005) examined the weed flora of drill‐seeded rice after conventional and zero tillage following shallow (1–3 cm) flooding up to 30 DAS. Under zero tillage, Commelina diVusa and Cyperus rotundus became dominant weed species, whereas Ischaemum rugosum, Leptochloa chinensis, and Eragrostis japonica predominated after conventional tillage while the abundance of Paspalum spp. and Cyperus rotundus decreased. Smith et al. (1993) reported reduced infestation of aquatic weeds (e.g., H. limosa) under zero or minimum tillage. In a comparison of a range of tillage regimes, Piggin et al. (2001) reported that the abundance of F. miliacea and Leptochloa chinensis was not influenced by tillage practices, whereas Echinochloa colona and Ludwigia octovalvis increased in abundance on zero‐till and dry‐seeded plots. Tillage method was also found not to aVect the incidence of R. cochinchinensis (Janiya et al., 2001). Stale seedbeds, also named the false seeding technique, refer to a cultural method of weed control commonly applied in rice monoculture (Ferrero, 2003). After seedbed preparation, the land is left unsown to allow weed emergence. The rice is then sown after weed removal by either mechanical (harrows) or chemical (nonselective herbicides) means. The technique reduces both the size of the soil seedbank and the emergent weed infestation. The success of this technology depends as much on the eYcacy of practices promoting weed germination as it does on nonselective mortality of emerged weed seedlings. Kartaatmadja et al. (2004) observed that paraquat applied to minimum tillage in irrigated lowland rice (1) eVectively controlled broadleaves and annual grasses such as Leptochloa chinensis and Echinochloa crus‐ galli, (2) had an eYcacy of 80% against sedges such as F. littoralis and Cyperus diVormis, and (3) had only 20% eYcacy against perennial weeds such as P. distichum. Minimum tillage results in a higher percentage of germination of the weed seeds that are present in the upper soil layer, compared with moldboard plowing (Ferrero and Vidotto, 1999), and in

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Rio Grande do Sul, Brazil, about 250,000 ha are cropped using this technique (Noldin and Cobucci, 1999). Renu et al. (2000) observed that the use of paraquat in a stale seedbed was more eVective than mechanical weeding in dry‐seeded rice. Application of glyphosate before planting rice can reduce labor input for weeding by 30–60% (Roder et al., 2001). In Louisiana (USA), typically, water‐seeded rice fields are mechanically tilled after flooding to destroy existing weed vegetation and create a uniform seedbed. This cultural practice is generally referred to as ‘‘mudding in’’ (Bollich and Feagley, 1995). Public perceptions and increasing legislation concerning water quality have resulted in a shift of some of the water‐seeded rice area to varying levels of conservation tillage. Since 1998, no‐till and stale seedbed conservation tillage area has fluctuated between 7% and 15% of the water‐seeded rice (Anon, 1998, 2004). Leon (2005) examined imazethapyr use in a water‐seeded system receiving no tillage or tilled in the water before seeding and observed that (1) imazethapyr provides producers the option to use conservation tillage in a water‐seeded rice production system and (2) the benefits of reducing soil erosion and surface water contamination from muddy‐water discharge at seedling establishment can be obtained in a stale seedbed system without experiencing a decrease in weed control or rice yield.

2.

Water Management

Water management is arguably the most important cultural practice in DSR (Caton et al., 2002). Floodwater management aVects the density, vigor, and uniformity of rice stands; the severity of weed competition; and the eVectiveness of herbicides (Kim et al., 2001). The main reason that prompted rice farmers in California to convert entirely from dry‐seeding to water‐ seeding in the early part of the twentieth century was primarily to manage Echinochloa crus‐galli (Hill et al., 2001). Water depth alone exerts a dominant eVect on the structure of weed communities and the fate of weeds recruited into the growing crop (Janiya et al., 1999). Early flooding, 4–5 DAS in contrast to 12 DAS, to a 5‐cm depth reduced the density of Echinochloa crus‐galli (Dizon et al., 1999) as well as other species (Chin et al., 2002; Hach et al., 1998). Bhagat et al. (1999) concluded that, irrespective of herbicide application, continuous shallow water ponding throughout the life of a wet‐seeded rice crop, as well as up to panicle initiation, was eVective in reducing weed diversity, number, density, and biomass compared with saturated soil maintained throughout. Balasubramanian and Krishnarajan (2001) similarly recorded lower weed growth with continuous submergence in wet‐seeded rice. Flooding depth, however, has a diVerential eVect on the survival and growth of weed species. Kent and Johnson (2001) reported that, compared

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to saturated soil conditions, flooding to 2–8 cm increased the density of Sphenoclea zeylanica and Heteranthera callifolia Rchb. ex. Kunth. and decreased that of Echinochloa colona and E. crus‐pavonis, with no eVect on F. miliacea. Where flooding of 4‐ or 8‐cm depth was maintained for 2 or 4 days out of 7 days, there were greater densities of Ammannia prieuriana Guill. & Perr. than in soil maintained in a saturated condition at the same intervals. Increased flood duration from either 2 or 4 days out of 7 days to continuous flooding increased the density of H. callifolia, had no eVect on Sphenoclea zeylanica, but decreased plant numbers in Spilanthes filicaulis, Echinochloa colona, and E. crus‐pavonis (Kent and Johnson, 2001). Gealy (1998) observed that cultural practices such as deep‐flooding in both dry‐ seeded and water‐seeded rice may reduce morning‐glory (Ipomoea lacunosa L. and I. wrightii Gray) infestations. This cultural practice suppresses the germination and establishment of Echinochloa crus‐galli but promotes aquatic weeds such as Cyperus diVormis, Damasonium minus, Sagittaria montevidensis, and Alisma plantago‐aquatica (Seal et al., 2004). Smith et al. (1977) observed that seed of H. limosa (Sw.) Willd. germinated only in saturated or flooded soils due to low oxygen levels required for germination (Marler, 1969). Baskin et al. (2003) have suggested that it may be possible to reduce H. limosa infestation by exploiting the temperature response of the species by (1) flooding fields during the winter to decrease dormancy break and (2) sowing rice as early as possible before daytime temperatures reach 30–35  C as very few seeds of H. limosa, flooded during winter, gain the ability to germinate even under flooded conditions at 25/15  C. Cohort recruitment of weeds in dry‐seeded rice may extend over a longer period than in wet‐seeded rice, depending on the time of initiation and depth of flooding. In dry‐seeded rice of temperate regions, it is recommended that the permanent flood be applied as soon as possible in order to suppress weed seed germination. Typically, the permanent flood is applied 3–6 weeks after planting (Rainbolt and Bennett, 2005).

3.

Rice Cultivars

a. Weed Competitiveness. Interest in crop competitiveness as a weed management tool in DSR has stemmed in part from the evolution of weed resistance to herbicides and the lack of alternative control options (Gibson et al., 2003), and also because many rice farmers have limited cash and labor resources and are unable to invest in herbicides (Johnson et al., 1998). Sanint et al. (1998) estimated that enhancing crop competitiveness against weeds could reduce weed control costs by 30%.

196

A. N. RAO ET AL.

The significance of crop interference with weed growth is historically well established and variation in competitive ability has been established in many crops (Berkowitz, 1998; Callaway, 1992). Caton et al. (2001) argued that, even with this observation, breeding for crop competitiveness was rare because (1) there was a lack of understanding about which traits conferred competitiveness; (2) competitive processes are intrinsically dynamic and changes in crop management, environment, and season markedly influence outcomes; and (3) alternative weed management technologies oVered both greater and more cost‐eVective weed control. Crop competitiveness may be judged by either crop tolerance (the ability to maintain shoot or grain biomass in the presence of weeds) or weed suppression (the ability to reduce weed biomass or reproductive propagules) or both (Jannick et al., 2000). The literature reflects arguments for and against (Callaway, 1992; Jordan, 1993) the use of these measures which stem in part from the hypothesis that a trade‐oV exists between the two (Jennings and Aquino, 1968; Kawano et al., 1974). Subsequent analysis (KropV et al., 1993) and studies (Fischer et al., 1997; Gealy et al., 2000; Johnson et al., 1998) have led to the conclusion that trade‐oVs are not inherent and the extent to which the abilities of tolerance or weed suppression are linked is as yet unresolved (Pester et al., 1999). Harnessing competitiveness as a preventive weed control measure for DSR may be achieved by focusing on both early vigor as well as traits influencing competitiveness throughout the growth cycle. DiVerences between rice cultivars in their competitiveness with weeds have been reported from Asia (Caton et al., 2003; Garrity et al., 1992; Zhao et al., 2006), Latin America (Fischer et al., 1997; Kawano et al., 1974), the United States (Gealy et al., 2005b), and Africa (Fofana and Rauber, 2000), and between O. sativa and Oryza glaberrima rice (Johnson et al., 1998). Zhao et al. (2006) reported that vegetative vigor scored at 2 weeks after seeding and weed‐free yield accounted for 87% of the variation in yield between cultivars in competition for weeds and that these two traits could be eYcient means of indirect selection for improving rice yield in competition with weeds. Competitive ability in rice is often associated with traits related to light interception and is correlated with height and leaf area index (Garrity et al., 1992), droopy leaves, tiller production (Estorninos et al., 2002, 2005; Fischer et al., 1997; Fofana and Rauber, 2000), higher specific leaf area, earlier tiller production (Dingkuhn et al., 1999; Johnson et al., 1998), root length density (Fofana and Rauber, 2000), and biomass of roots and stems (Gealy et al., 2005b). Most studies have related to rice grown under upland conditions, though Haefele et al. (2004) found that height, tiller density, specific leaf area, leaf area index, and growth duration were negatively related to yield loss under lowland conditions. After studying the competitive relationships in a number of crops, including rice, KropV et al. (1993) concluded that it was the morphological

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traits that contributed to early ground cover and height that were the most important traits for competitiveness. Further, they suggested that ecophysiological models may help to understand the integration of component traits. After studying a range of O. sativa and O. glaberrima rice cultivars, Dingkuhn et al. (1999) suggested that specific leaf area and tillering ability, as major components of vegetative vigor, were predictive of competitiveness. In addition, Asch et al. (1999) reported that the superior competitiveness of O. glaberrima is partly due to the early onset of autotrophic growth, higher partitioning coeYcients to laminae, and high specific leaf area. After studying the growth of rice cultivars with and without competition from weeds, Caton et al. (2003) reported that early vigor was highly repeatable and that it could be used to discriminate between more and less competitive cultivars even in monoculture. The use of more competitive cultivars has been proposed as a tool to improve weed control in water‐seeded rice (Dingkuhn et al., 1999; Fischer et al., 1997; Gibson et al., 2001). It is well known (from early work, Kira et al., 1953) that the asymptotic response of yield to sowing density is resource dependent and that the competitiveness of a crop is inherently related to stand density (Rainbolt and Bennett, 2005). Tropical rice systems under precision resource management, high tillering rate, and consequent rapid canopy closure (Peng et al., 1994) can allow wet‐seeded rice farmers to use low seeding rates (50–80 kg ha1), especially where seed costs are high (Luat et al., 1998). However, in the Philippines and Vietnam, high seed rates (150 and 250 kg ha1) are used in wet‐seeded rice to suppress weeds in early growth (Balasubramanian and Hill, 2002). While this may contribute to weed management of some species, Gibson et al. (2001) found no significant eVect of rice‐seeding rate in reducing Echinochloa growth in water‐seeded rice. Some authors (e.g., Labrada, 2002) have argued that the use of high seed density for weed management should be reconsidered in DSR, within the context of integrated crop management. However, in resource‐poor environments such as dryland rice, this may not prove to be a viable option because it often leads to low and patchy stand establishment. b. Submergence Tolerance. There has been renewed interest in the potential for selecting rice germplasm that is tolerant of very early flooding (48 h after germination) for use in direct‐seeding (Yamauchi et al., 1993), particularly to control problematic grasses and sedges in wet‐ and water‐ seeding (Hill et al., 2001). Rice can germinate and develop a coleoptile in the absence of oxygen, and there are genotypic diVerences in the rates of coleoptile, root, and leaf development at low oxygen concentrations (Turner et al., 1981). In anaerobic conditions, rapid coleoptile elongation hastens the shoot emergence from soil or water, leading to rapid oxygen transport to the apical meristem

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(Yamauchi et al., 1995). Tolerance of early flooding, where rapid coleoptile growth is considered important, therefore contrasts with tolerance of flooding at the later stages of growth, when submergence injury is exacerbated by rapid leaf extension and consumption of assimilates (Das et al., 2005; Jackson and Ram, 2003). Cultivars with a superior ability to germinate under anaerobic conditions have been identified, and these have developed coleoptiles that are longer and elongate faster than others (Yamauchi and Biswas, 1997). Anaerobic germinability and flooding tolerance are complex traits, and it seems that they are regulated by several genes (Fukao et al., 2003). Combining the ability to germinate in anaerobic conditions with other key agronomic traits will enable greater use of floodwater in IWM.

B.

INTERVENTION METHODS

OF

WEED CONTROL

It can be argued that both chemical and manual means of weed control are preventive in that they aim to prohibit weed increase in the long term. However, the decision to intervene in the management of a crop and commit expenditure to the application of a herbicide or to labor for mechanical or hand weeding is a proximal one as, not least, it is seasonally dependent. Although indirect (preventive) methods aim mainly to reduce the number of weeds emerging in a crop, direct (intervention) methods also aim to increase crop competitive ability against weeds (Barbery, 2003).

1.

Manual and Mechanical Methods of Weed Control

In spite of the increasing herbicide use in weed control in DSR, hand weeding is either partially or extensively practiced in countries of Asia, Latin America, and Africa (Ahmed et al., 2001; Chin, 2001; Chin and Mortimer, 2002; de Dios et al., 2005; Fischer and Antigua, 1996; Islam et al., 2004; Jashim et al., 2004; Makara et al., 2001; Noldin et al., 2004; Oteng and Sant’Anna, 1999; Son and Rutto, 2002; Yaduraju and Mishra, 2004; Zhang, 2003). In dry‐seeded rice in Africa, farmers normally rely on family labor for weeding, which usually starts at 15–30 DAS and continues over many days (Oteng and Sant’Anna, 1999). Similarly, in Cambodia manual weeding is practiced at least twice and commonly three times (Makara et al., 2001) as is done in flood‐prone areas of Bangladesh (Jashim et al., 2004). Weed control in slash‐and‐burn rice production in northern Laos requires about 140–190 days ha1 or 40–50% of the total labor input (Roder et al., 1997) and probably represents one example of the maximum time allocated to a

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199

practice of crop protection. In these situations, manual weeding of rice is done by hand or, if weeds are small, with simple tools. In wet‐seeded rice in Vietnam, Chin et al. (2000a) considered that hand weeding twice was the most eVective treatment in terms of both controlling weeds and crop safety but noted that the labor cost was high and often prohibitive. Manual weeding can be implemented only when weeds have reached a suYcient size to be pulled, and it has an inherent opportunity cost. Manual weeding is therefore often practiced late as evidenced by yield loss comparisons of the eVects of manual weeding at 21–30 DAS with those from the use of early postemergence herbicides (Singh et al., 2005a). Labor scarcity, high labor cost, poor weather conditions, and the presence of perennial weeds that fragment on pulling may all lead to lowered eYcacy in weeding. Mechanical weed control with the use of simple implements remains a practical and economic method for many small and marginal farmers of Asia and Africa. Mechanical weeding is almost universally practiced on row‐ seeded rice since interrow cultivation with either hand tools or animal traction equipment reduces time in weeding and minimizes crop damage. An exception to this is the practice of beushening in which dry‐seeded broadcast rice is flattened by ‘‘planking’’ (drawing of a heavy flat wooden object over the crop) after crop tillering has commenced. The process kills weed species with single main stems, whereas rice is able to retiller from basal nodes on stems pressed to the ground in addition to those at the plant base. Comparisons of traditional and mechanically modernized weeding equipment suggest the value of these technologies in resource‐limited farming communities. Sarma and Gogoi (1996) reported that in rainfed upland rice in India a manually operated peg‐type dryland weeder and a twin wheel hoe were eVective in weed control when used twice at 20 and 30 days after emergence. Another dryland weeder (with a straight‐line peg arrangement) has also shown excellent performance across a range of soil types with varying soil moisture levels and weed intensity providing a labor saving of
57% compared with hand weeding (127 person‐days ha1) (Subudhi, 2004). Similar observations have been made elsewhere in identifying the practical eYcacy of mechanical weeders and economies in labor use. EVective weed control has been demonstrated in Gambia, with a donkey‐drawn implement (the Super‐Eco seeder), cultivating twice (21 and 42 DAS) with the animal‐drawn hoe followed by selective hand pulling (Remington and Posner, 2000). In Bangladesh, farmers’ principal weed management practices in transplanted rice remain hand weeding and the use of a push weeder (Ahmed et al., 2001). A rake‐type weeder developed in Bangladesh has been shown to work in light and heavy soils and has a capacity of 0.04 ha h1 (Islam et al., 2004). Power‐operated rotary weeders have improved weeding eYciency (Victor and Verma, 2003). In northeast Thailand, a mechanized dry

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200

DSR management system has been advocated, which includes weeding with a soil cultivator involving tillage between rows of rice twice at 2 and 4 weeks after seeding (Kabaki et al., 2003). In wet (row)‐seeded rice, an improved and modified IRRI conoweeder (Parida, 2002) gave a weeding eYciency of 80% during the first weeding, with a field capacity of 0.02 ha h1. With labor scarcity, mechanical weed control methods may be more eYcient and suitable in DSR as they help save labor. Hence, eVorts to improve the eVectiveness of existing weeding tools and implements are desirable, especially for developing countries.

2.

Chemical Method of Weed Control

Labor unavailability, increasing labor costs, and the pressing need to raise yields and maintain profit on a progressively limited land base have been major drivers for farmers to seek alternatives to manual weeding. Herbicides are one such alternative. EVective weed management practices are an important prerequisite in DSR culture, with herbicide application seemingly indispensable (Azmi et al., 2005). The trend for an increase in herbicide use has been reinforced by the spread of DSR (Naylor, 1994). In Asia, herbicide use grew dramatically from 1980 to 1995, with more than a threefold increase in herbicide sales amounting to more than US$900 million per annum (Naylor, 1996). In the Americas, Australia, Europe, and East Asia, over 90% of DSR areas are treated with herbicides (De Datta and Baltazar, 1996). Parts of South and Southeast Asia and Latin America have seen moderate but fast expansion in herbicide use. In Asia, more herbicide is used in irrigated DSR than in rainfed DSR, with much less use in upland rice in tropical Asia and Africa. From 1996 to 2003, however, there was a decline in the value of sales at annual growth rates of –5.8% in North America, –3.6% in Latin America, and –2.4% in Asia (Cropnosis, personal communication). This has been partly due to the changes in the pricing structure of the herbicide market and also the influx of generic products from China and India. Declines in sales of herbicide volumes may, however, be a misleading indicator of herbicide use as there has been a shift to low‐volume, sulfonylurea‐based products in many countries in Asia, excluding Japan. Herbicide options for weed control in DSR diVer according to method of crop establishment because the performance of herbicides varies in relation to water regimes. Extensive research has been conducted over the years by many researchers to find out the optimum rate, time, type, and method of herbicide application. This information is summarized in Table V. a. Dry‐Seeded Rice. In irrigated dry‐seeded systems, 4–6 weeks may elapse between planting and permanent flood establishment and controlling

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201

weeds during this period is critical to optimize grain yield. Thus, for dry‐ seeded rice, in general, two herbicide applications are recommended: one at the dry period either just before or after rice emergence and the other at the flood period (Kim and Ha, 2005). Pendimethalin, quinclorac, and thiobencarb have residual activity and control annual grasses and some broadleaf weeds (Jordan et al., 1998b; Smith and Hill, 1990). Pendimethalin and thiobencarb can be applied after rice has imbibed water for germination but before rice and weeds emerge (Jordan et al., 1998b). Quinclorac can be applied preemergence, delayed preemergence, or postemergence. Although these herbicides can provide season‐long barnyardgrass control in silt loam soils (Helms et al., 1995), they generally do not provide control for an entire season on alluvial clay soils (Jordan, 1997). The capacity of these soils to change in volume by swelling and shrinkage allows exposure of nontreated soil to conditions that promote weed germination and emergence from soil below the zone treated with herbicide. Subsequent weed flushes are generally controlled with postemergence herbicides (Jordan et al., 1998b) or manual weeding. Failure to apply postemergence herbicide treatment may reduce irrigated dry‐seeded rice yield by 9–60% (McCauley et al., 2005). Examples of postemergence herbicides are acifluorfen, bensulfuron, bentazon, bispyribac, carfentrazone, clomazone, cyhalofop, 2,4‐D, fenoxaprop, halosulfuron, molinate, propanil, quinclorac, and triclopyr. Bentazon, acifluorfen, bensulfuron, 2,4‐D, and triclopyr target broadleaf species. DiYculties in achieving grass and sedge weed control have led to a continued call for new graminicides. Clomazone and halosulfuron are relatively recent introductions. Clomazone provided the most consistent residual barnyardgrass control over a range of environmental conditions and water management practices (Jordan and Kendig, 1998). Halosulfuron provides protection against Cyperus spp., including Cyperus rotundus, with activity on broadleaf weeds also (Table V). The diverse weed flora (terrestrial and aquatic) in dry‐seeded rice fields usually necessitated the use of two or more herbicides for wide‐spectrum weed control (Gianessi et al., 2002) and determining compatability of herbicides is important in developing management strategies (Jordan, 1995). In Arkansas, propanil, molinate, clomazone, quinclorac, glyphosate, triclopyr, pendimethalin, 2,4‐D, acifluorfen, and holosulfuron are used in order of decreasing percentage area applied for dry‐seeded rice (Gianessi et al., 2002) and, in Mississippi, clomazone, propanil, quinclorac, 2,4‐D, glyphosate, molinate, halosulfuron, and acifluorfen are used. Chemical control in dry‐seeded rice has been inconsistent from site‐to‐site and from year‐to‐year at the same site because of diverse interacting factors such as varying weed species, weed populations, and soil and climatic conditions (Ho, 1996). Therefore, flexibility in herbicide usage to suit conditions is critical to the acceptance of herbicides (Moody, 1981; Sankaran and De Datta, 1985). Chemical weed control is widely used in rice agriculture in Korea. Recommendations for use (Kim and Ha, 2005; Kim et al., 2001) include (1) early

202

Table V Herbicides and Their Combinations Reported to be EVective in Controlling Weeds in Direct‐Seeded Rice Class of (i) Application timec weeds Dry‐seeded Wet‐seeded Water‐seeded controlledb (ii) Water regimed Type of rice direct‐seeding

Herbicide

Mode of action, chemical groupa

Referencese

Inhibition of acetyl CoA carboxylase (ACCase), aryloxyphenoxy‐propionates (FOPs)

þ

þ

þ

G, B, CS

Fenoxaprop‐p‐ ethyl

As above

þ

þ

þ

G, CB, C

Quizalofop‐p‐ ethyl Clefoxydim

As above

þ

G

þ

þ

G

þ

þ þ

G BSR G, CB, CS (i) PPI fb POST (in IT rice) (ii) FARF (PPI)

Ferrero et al. (2002) Pellerin and Webster (2004); UOA (2005)

þ

G, B

Anon (2003); Chin et al. (2000a); Fischer et al. (2004); Rainbolt and Bennett (2005); Risi et al. (2004); UOA (2005)

þ

G, CB, CS (i) POST

Clethodim Imazethapyr

Bispyribac‐ sodium

Pyribenzoxium

Inhibition of acetyl CoA carboxylase (ACCase), cyclohexanediones, lipid biosynthesis inhibitor (DIMs) As above Inhibition of acetolactate synthase (ALS) (acetohydroxyacid synthase, AHAS), imidazolinones Inhibition of acetolactate synthase (ALS), (acetohydroxyacid synthase, AHAS), pyrimidinylthio‐ benzoates As above

þ

(i) EPOE, POST Bocchi et al. (2005); Esqueda and (ii) WDRA (EPOE), Tosquy (2004); Ferrero et al. ESMC (POST) (2002); Ntanos et al. (2000); Saini and Angiras (2002); Subbaiah and Sreedevi (2000); UOA (2005) (i) EPOE, POST Azmi and Mortimer (2002); (ii) WDRA (EPOE), Karim et al. (2004); Saini and ESMC (POST) Angiras (2002); UOA (2005); Yang et al. (2004) (i) BSR Eleftherohorinos and Dhima (2002) (i) BSR, POST Anon (2003); Tabacchi and Romani (2002)

(i) EPOE

Baron (2005); Dasanayaka (2003)

A. N. RAO ET AL.

Cyhalofop‐butyl

þ

þ

þ

G, S

(i) EPOE, POST

þ

þ

þ

B, S

(i) EPOE, POST (ii) HWAP

Chlorimuronþ metsulfuron Cinosulfuron

As above

þ

þ

G, B

(i) EPOE, POST

As above

þ

þ

þ

S, B

(i) EPOE, POST

Ethoxysulfuron

As above

þ

þ

þ

B, S

(i) EPOE, POST

Halosulfuron‐ methyl Imazosulfuron

As above

þ

þ

B, S

As above

þ

Metsulfuron

As above

þ

G, B

(i) POST (ii) DAFL (i) PPI, EPOE, POST (i) POST

Pyrazosulfuron‐ ethyl

As above

G, S, B

(i) PRE, POST

Metosulam

Inhibition of acetolactate synthase (ALS), (acetohydroxyacid synthase (AHAS), triazolopyrimidines As above Inhibition of photosynthesis at photosystem II‐amides

þ

B, S

(i) POST

þ

G, S, B G, CB, S

(i) EPOE POST

Bensulfuron‐ methyl

Penoxsulam Propanil

þ

þ

þ

þ

þ þ

Anon (2003); Bocchi et al. (2005); Ferrero et al. (2002); Kim et al. (2001); Tabacchi and Romani (2002) Azmi and Mortimer (2002); Clampett and Stevens (2002); Peterson et al. (1990); Pratley et al. (2004) Singh et al. (2006); Yaduraju and Mishra (2004) Azmi and Supad (1990); Bocchi et al. (2005); Dasanayaka (2003); Ferrero et al. (2002); Son and Rutto (2002) Bocchi et al. (2005); Ferrero et al. (2002); Kolhe (1999); Moorthy and Saha (2002); Saini and Angiras (2002a); Singh et al. (2006) Rainbolt and Bennett (2005); Suarez et al. (2004); UOA (2005) Kim et al. (2001); Ottis et al. (2004). Anon (2003); Bocchi et al. (2005); Peterson et al. (1990) Anon (2003); Kim et al. (2001); Moorthy (2002); Ooi (1988); Yaduraju and Mishra (2004) Bocchi et al. (2005)

(continued )

203

Lam et al. (2005) Ampong‐Nyarko (1996); Bocchi et al. (2005); Fischer and Antigua (1996); Hill and Fischer (1999); Lo and Cheong (1995); Navarez et al. (1979)

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Inhibition of acetolactate synthase (ALS) (acetohydroxy‐acid synthase, AHAS), sulfonylureas As above

Azimsulfuron

Table V (continued )

204

Class of (i) Application timec weeds Dry‐seeded Wet‐seeded Water‐seeded controlledb (ii) Water regimed Type of rice direct‐seeding

Herbicide

Mode of action, chemical groupa Inhibition of photosynthesis at photosystem II‐benzothiadiazinones

Paraquat

Photosystem‐I‐ electron diversion: bipyridiliums Protoporphyrinogen oxidase (PPO) inhibitors, diphenylethers (chlorophyll synthesis inhibitor) As above

Acifluorfen

Oxyfluorfen

Oxadiargyl Oxadiazon

Inhibition of protoporphyrinogen oxidase (PPO): oxadiazoles As above

Carfentrazone‐ethyl Inhibition of protoporphyrinogen oxidase (PPO), triazolinone Benzofenap

Clomazone

Glyphosate

Bleaching: inhibition of 4‐hydroxyphenyl‐pyruvate‐ dioxynase (4‐HPPD), pyrazoles (chlorophyll synthesis inhibitor) Bleaching: inhibition of carotenoid biosynthesis (unknown target), isoxazolidinones Inhibition of EPSB synthase, glycines (aromatic amino acid biosynthesis inhibitor)

þ

þ

þ

B, S

þ

G, B, S

þ

B

(i) POST

þ

B, G

(i) PRE

þ

G

(i) PRE

þ

þ

(i) POST (ii) PALW

(i) BSR

þ

þ

þ

G, B

(i) BSR, PRE (ii) MWAT

þ

þ

þ

B, S

þ

B, S

(i) PRE FLOOD/POST (ii). FFEW (i) BSR to EPOE (ii) AWMF

þ

þ

G, B

(i) BSR, EPOE (ii) WMBA

þ

þ

G, B

(i) BSR

Anon (2003); Bocchi et al. (2005); Ferrero et al. (2002); Fischer and Antigua (1996); Rainbolt and Bennett (2005); Taylor (2004) Eleftherohorinos and Dhima (2002); Lacy and Stevens (2005) Smith and Hill (1990); UOA (2005)

Anon (2003); Biswas et al. (1991); Fischer and Antigua (1996); Vongsaroj (1995) Chin et al. (2000a); Gnanasambandan and Murthy (2002) Adigun et al. (2003); Ampong‐Nyarko (1996); Antigua (1993); Bhagat et al. (1977); Bocchi et al. (2005); Fischer and Antigua (1996); Hassan and Rao (1996); Lim (1988) Dasanayaka (2003); Rainbolt and Bennett (2005); UOA (2005) Clampett and Stevens (2002); Pratley et al. (2004); Skinner and Taylor (2002) Anon (2003); Jordan et al. (1998); Lacy and Stevens (2005); Pegg et al. (2002); UOA (2005) Anon (2003); Eleftherohorinos and Dhima (2002); Ferrero et al. (2002)

A. N. RAO ET AL.

Bentazon

Referencese

G, B

(i) BSR

þ

G, B, S

PRE

G, CB

(i) BSR, EPOE (ii) AFSF

Microtubule assembly inhibition, pyridines (cell division inhibitor) Inhibition of cell division (inhibition of very long fatty acids), chloroacetamides As above As above

þ

G, B

(i) PRE

þ

þ

Butachlor þ safener Metolachlor Pretilachlor

As above

þ

þ

As above As above

þ

þ

þ þ

G G, S, CB

(i) BSR (i) BSR, POST

Pretilachlor þ safener

As above

þ

þ

þ

G, CB

(i) PRE

Anilofos

Inhibition of cell division (inhibition of very long chain fatty acids), others Inhibition of lipid synthesis, not ACCase inhibition: chloro‐carbonic‐acids Inhibition of lipid synthesis: not ACCase inhibition‐ thiocarbamates

þ

þ

G, CB

G

(i) BSR, PRE, EPOE (II) ESWA (i) BSR

G

(i) EPOE

Dinitramine

Pendimethalin

Dithiopyr Acetochlor

Alachlor Butachlor

Dalapon

Dimerpiperate

þ

þ

þ

þ

þ

(i) BSR

G G, CB

(i) BSR (i) PRE (ii) ESWA (i) PRE

þ

þ

Ferrero et al. (2002); Lanclos et al. (2003) Bhagat et al. (1977)

Ampong‐Nyarko (1996); Anon (2003); Rainbolt and Bennett (2005); Valverde et al. (2001); Vongsaroj (1995); Yaduraju and Mishra (2004) Hassan and Rao (1996); Malik et al. (2002) Eleftherohorinos and Dhima (2002)

Eleftherohorinos and Dhima (2002) Ampong‐Nyarko (1996); De Datta and Bernasor (1973); Yaduraju and Mishra (2004) Moorthy and Saha (2002); Piggin et al. (2001) Eleftherohorinos and Dhima (2002) Angiras and Rana (1998); Bocchi et al. (2005); Karim et al. (2004) Kyau and Win (2000); Moorthy and Saha (1999); Ooi and Chong (1988); Yaduraju and Mishra (2004) Tamilselvan and Budhar (2001); Yaduraju and Mishra (2004) Ferrero et al. (2002)

Bocchi et al. (2005); Ferrero et al. (2002)

205

þ

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

Inhibition of glutamine synthetase, phosphinic acids Microtubule assembly inhibition, dinitroaniline (cell division inhibitor) As above

Glufosinate

(continued )

Table V (continued )

206

Class of (i) Application timec weeds Dry‐seeded Wet‐seeded Water‐seeded controlledb (ii) Water regimed Type of rice direct‐seeding

Mode of action, chemical groupa

Herbicide As above

þ

þ

þ

G, B

(i) PPI, POST

Thiobencarb

As above

þ

þ

þ

G, CB

(i) BSR, PRE, EPOE, POST (ii) ESMC, FARF

2,4‐D

Synthetic auxins (action like indole acetic acid), phenoxy‐carboxylic acids

þ

þ

þ

B, S

(i) POE

MCPA sodium salt

As above

þ

þ

B, S

(i) POST (ii) PALW

Triclopyr

Synthetic auxins (action like indole acetic acid), pyridine carboxylic acids

þ

B, S

(i) POST (ii) FDAA

Quinclorac

Synthetic auxins (action like indole acetic acid), quinoline carboxylic acids

þ

G, CB

(i) PRE, EPOE, POST (ii) DWPF

a

þ

þ

Herbicide classification by mode of action, 2003 Weed Science.org and Tomlin (1997).

Bocchi et al. (2005); Ferrero et al. (2002); Fischer and Antigua (1996); Hill and Fischer (1999); Ho and Zuki (1988); Lo and Cheong (1995) Antigua (1993); Clampett and Stevens (2002); De Datta and Bernasor (1973); Fischer and Antigua (1996); Hassan and Rao (1996); Hill and Fischer (1999); Okafor (1986); Singh (2005) Anon (2003); Antigua (1993); Azmi and Mortimer (2002); Fischer and Antigua (1996); Kim et al. (2001); Singh (2005); UOA (2005) Ampong‐Nyarko (1996); Clampett and Stevens (2002); Pratley et al. (2004) Ferrero et al. (2002); Jordan et al. (1998a); Lo and Cheong (1995); Singh et al. (2006); UOA (2005); Valverde et al. (2001) Abeysekera and Wickrama (2005); Anon (2003); Bocchi et al. (2005); Chang (1988); Fischer and Antigua (1996); Valverde et al. (2001)

A. N. RAO ET AL.

Molinate

Referencese

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207

application (0–10 days after flooding) of soil‐applied herbicides for grass weeds such as butachlor, thiobencarb, dithiopyr, anilofos, molinate, esprocarb, pyrazolynate, pentoxazone, and several mixtures of these with bensulfuron‐methyl, pyrazosulfuron‐methyl, and imazosulfuron; (2) an intermediate application (15–25 days after flooding) of sulfonylurea mixtures for controlling annual grasses and perennial sedges; and (3) late application (30–40 days after flooding) of primarily foliar‐applied herbicide mixtures using bispyribac‐sodium, cyhalofop‐butyl, fenoxaprop‐ethyl, pyribenzoxim with propanil, bentazon, azimsulfuron, and ethoxysulfuron. Drill dry‐seeding of rice using resource conservation technologies (RCTs) such as the furrow‐irrigated raised‐bed planting system (FIRBS) is more eYcient in irrigation water use than transplanted rice on puddled soil (Balasubramanian et al., 2003). Singh et al. (2006) reported that, in the FIRBS (1) ethoxysulfuron at 18 g a.i. ha1 applied at 21 DAS was eVective for controlling broadleaf weeds and (2) fenoxaprop‐p‐ethyl þ ethoxysulfuron at 50 þ 18 g a.i. ha1, applied at 21 DAS, and pendimethalin followed by chlorimuron þ metsulfuron at 1000 fb 4 g a.i. ha1 applied at 3 DAS followed by 21 DAS gave broad‐spectrum weed control. Remington and Posner (2000) observed eVective control of within‐row weeds by broadcasting oxadiazon at 0.75 kg a.i. ha1 at 1 DAS or by banding b G, grasses; CG, certain grasses; B, broadleaf weeds; CB, certain broadleaf weeds; S, sedges; CS, certain sedges. c PPI, preplant incorporation; BSR, before seeding rice; PRE, preemergence (0–3 DAS); EPOE, early postemergence (4–20 DAS); POE, postemergence (20 DAS and later). d AFGC, apply to flooded field and maintain flood until grass is controlled; AFSF, apply after the first flushing and ensure that the soil surface is sealed by flushing or rainfall before application. Apply a second flush or permanent water after 2 days but not later than 5 days after application; AWMF, apply within 10 days of commencement of flooding. Water movement to and within bays should cease 12 hours before application and for 5 days after application, but maintaining permanent flood; DAFL, do not apply into flood; DWPF, in dry‐seeded rice, if weeds emerge after preemergence application, rainfall or flushing may be required for activation and reactivation; ESMC, excellent soil moisture is critical for good activity; ESWA, ensure suYcient moisture at the time of application; FARF, flush for activation if rainfall does not occur within a few days of planting. Repeat flushing as needed to keep soil‐applied treatment active; FDAA, flood should be delayed 3 days after application; FFEW, postflood/POST to exposed weeds: apply to rice and weeds after permanent flood and when 80% of the foliage of the weeds is exposed; FLEW, the flood water must be lowered to expose small weeds for foliar absorption of the herbicide; HWAP, as it is highly water soluble, avoid pumping water for 7 days after treatment; MWAT, maintain water after treatment for 14 days; PALW, prior to application, lower water levels to expose more than two‐third of the weed growth to direct contact with the spray; WDRA, works by direct contact with weeds. Re‐flood after 2 hours and fill as soon as possible to limit germination of new weeds; WMBA, water movement must cease before application and for 3 days after to ensure suYcient water to maintain permanent flood. e References are given here as examples.

208

A. N. RAO ET AL.

thiobencarb and propanil at 0.72 and 1.30 kg a.i. ha1 over the row at 21 DAS. Seed treatment with cinosulfuron at 0.2–0.6 g l1 and optimal N management have been reported to delay Striga emergence (Adagba et al., 2002a,b). The following treatments were eVective in controlling weeds in dry‐seeded rice: pendimethalin or pretilachlor as preemergence application followed by hand weeding in India (Singh, 2005); oxadiazon followed by one hand weeding in Bangladesh (Mazid et al., 2005); oxadiazon, butachlor/2,4‐D, and thiobencarb/propanil in Indonesia (Pane and Mortimer, 2002); 2,4‐D and propanil in Laos (Roder et al., 2001); oxadiazon, butachlor, thiobencarb, propanil, butachlor, bentazone, and oxadiazon or their combinations; quinclorac; pretilachlor followed by bensulfuron‐methyl þ thiobencarb; pretilachlor followed by bensulfuron þ quinclorac; pretilachlor þ fenclorim; cyhalofop; fenoxaprop‐p‐ethyl; oxaziclomefone; fentrazamide; thiobencarb þ bensulfuron; pretilachlor þ bensulfuron; pendimethalin þ bensulfuron; and bispyribac‐sodium in China (Guan et al., 2004; He et al., 2000; Wang et al., 2000). Bispyribac‐sodium when applied with thiobencarb or fenoxaprop‐p‐ethyl was eVective against L. chinensis (Wang et al., 2000). Pretilachlor þ bensulfuron‐methyl applied at 0 or 4 DAS was very eVective against Echinochloa crus‐galli and L. chinensis (He et al., 2000). In Mexico, clomozone controlled Echinochloa colona and partially controlled Scleria setuloso‐ciliata but had no eVect on Cyperus iria and Cyperus rotundus (Esqueda, 2000). A mixture of clomazone þ 2,4‐D þ propanil controlled all weeds. b. Wet‐Seeded Rice. Herbicides are considered indispensable for cost‐ eYcient weed control in wet‐seeded rice (De Datta et al., 1989). In general, the choice of herbicide for wet‐seeding, where soil may be saturated or there is standing water, is relatively narrow compared with dry‐seeding because modes of action cannot necessarily rely on adsorption to soil particles or uptake in an aqueous environment. For early applications (10–20 DAS), molinate, dimepiperate, dymron, fenclorim, pyrazolate, mefenacet, cyhalofop‐ butyl, and pyriminobac‐methyl, applied singly or in a mixture with sulfonylurea herbicide, are recommended. Subsequent application of herbicides at 30–40 DAS depends on the composition of surving weed flora (Kim and Ha, 2005). For late application, foliar‐applied herbicide mixtures are recommended using bispyribac‐sodium, cyhalofop‐butyl, fenoxaprop‐ethyl, and pyribenzoxim with propanil, bentazon, azimsulfuron, or ethoxysulfuron (Kim and Ha, 2005; Kim et al., 2001). Mixtures combining graminicide with a herbicide for sedges and broadleaf weed control such as quinclorac þ bensulfuron, molinate þ bensulfuron, molinate þ 2,4‐D, and thiobencarb þ pyrazosulfuron are commonly recommended (Karim et al., 2004). In India, cyhalofop‐butyl followed

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

209

by 2,4‐D was found eVective against mixed weed populations (Angiras and Attri, 2002). The success of weed control with herbicide is closely linked to water management because of the precise chemical requirements for achieving specificity in weed control and minimizing the risk of phytotoxicity to rice (Hill et al., 2001). Foliar‐active herbicides (e.g., bentazon, 2,4‐D, triclopyr) require spray contact with the leaf and require draining the field to completely expose weeds to herbicide. Molinate needs to be applied into water as application into drained paddies would result in its loss by volatility. Sulfonylureas work best when applied into flooding water, with floodwater acting as a carrier for their even distribution. Hach et al. (1997) concluded that increased flooding depth enhanced the eYcacy of early postemergence pyrazosulfuron‐ethyl (20 g a.i. ha1), a synergy not exhibited by butachlor and thiobencarb. Metsulfuron methyl is being used by farmers to control Marsilea minuta (Chin and Mortimer, 2002). The combination of presowing treatment of pretilachlor at 0.6 kg a.i. ha1 in flooded conditions, drainage before sowing, and seed treatment with fenclorim (as safener) is eVective in controlling weedy rice (Azmi et al., 2003), which is becoming a major weed of wet‐seeded rice. Maneechote et al. (2004) reported that quizalofop‐p‐tefuryl at 50 g a.i. ha1 induced sterility of wild rice when applied at either flowering or booting stage, thereby increasing rice yield. In the Philippines, butachlor þ safener at 0.75 kg a.i. ha1 and pretilachlor þ safener at 0.3 kg a.i. ha1 applied at 3 DAS eVectively controlled weeds in the farmers’ practice (Tuong et al., 2000) and with controlled irrigation (de Dios et al., 2005). The rate of pretilachlor þ safener can be reduced from the recommended rate and still achieve adequate control of weeds by flooding the field continuously with 2 cm of water (Janiya and Johnson, 2005). Chemical weed control is practiced by 90% of the rice farmers in Sri Lanka (Abeysekera, 1999) and 82% of the farmers in South Vietnam (Chin et al., 2000a). Propanil, quinclorac, bispyribac‐sodium, and fenoxaprop‐ethyl are most commonly used by farmers as per a survey in Sri Lanka (Sangakkara et al., 2004). The use of a wider spectrum of chemical modes of action may also help delay the development of herbicide resistance (De Datta and Baltazar, 1996). Mohankumar et al. (1996) reported that in wet‐seeded rice EC formulations of preemergence herbicides could be eVectively applied by mixing with sand instead of spray. Splash application is a new method of herbicide treatment that uses a relatively small amount of water, 5–10 liters ha1 (Lojo et al., 2001). The splash technique was reported to be simple, easy to use, and fast, and it requires no spray equipment and improves farmers’ eYciency and applicator safety.

210

A. N. RAO ET AL.

c. Water‐Seeded Rice. Water‐seeding rice into continuously flooded fields was developed as a cultural control for severe infestation of barnyardgrass and herbicides have become an integrated component of these rice‐ cropping systems (Hill et al., 1994). Herbicides are necessary to achieve levels of weed control suYcient to maintain economic viability (Hill, 2000). EVective control of weeds is dependent on herbicide rate, environmental conditions, and growth stage at the time of application (Scherder et al., 2004). Matching water management to the translocation characteristics of the herbicide used is extremely important to the success of the application (Hill and Fischer, 1999). For example, for triclopyr, a translocated herbicide, only 70% of the foliage need to be exposed. Most of the postemergence herbicides need to be applied to partially or fully drained fields to ensure full coverage of weeds with herbicides. Fischer et al. (2004) observed synergism on late watergrass (Echinochloa phyllopogon) in the field when 10 g a.i. ha1 bispyribac‐sodium was mixed with 1120–2240 g a.i. ha1 thiobencarb. This synergism can have multiple benefits. The eYciency of control can be enhanced using lower herbicide rates. Propanil plus molinate and bentazone were more compatible with fenoxaprop at 0.075 kg ha1 for control of barnyardgrass, whereas bensulfuron, carfentrazone, halosulfuron, and triclopyr can antagonize fenoxaprop activity on barnyardgrass (Zhang et al., 2005). In water‐seeded systems of Arkansas, Louisiana, and Mississippi in the United States, thiobencarb or molinate is applied before seeding to suppress aquatic weeds and grasses. After water‐seeding, propanil, propanil þ molinate and quinclorac are used to control grasses and broadleaf weeds. These herbicides are often supplemented with broadleaf weed‐controlling herbicides (Shipp, 2005). In California, where 95% of the rice area is water‐seeded, propanil, molinate, thiobencarb, triclopyr, bensulfuron, fenoxaprop, 2,4‐D, MCPA, and pendimethalin are used in order of decreasing percentage of area applied (Gianessi et al., 2002). In water‐seeded rice in California, Williams et al. (1990) evaluated the interaction of water depth from 5 to 20 cm, and the control of Echinochloa spp. improved from 16% to 77%. Cyperus diVormis was also suppressed by deeper water. Although all flooding depth treatments were improved by the application of herbicides, shallow water treatments were much more dependent on the herbicides to achieve high yields (Hill et al., 2001). Common postemergence herbicides used in Europe are propanil, pretilachor, thiobencarb, molinate, cyhalofop, fenoxaprop, azimsulfuron, quinclorac, bentazon, bensulfuron, cinosulfuron, propanil, and 2,4‐D (Bocchi et al., 2005; Gianessi et al., 2003; Su¨rek, 2000). Pendimethalin, thiobencarb, and molinate are used as preemergence herbicides. In fields where propanil‐resistant barnyardgrass exists, an alternative strategy is to apply molinate as preemergence followed by a postemergence application of

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

211

quinclorac þ azimsulfuron or cyhalofop (Gianessi et al., 2003). The farmers in Turkey sometimes apply herbicides late or in high dosage. Some of them try to control broadleaf or sedge weeds with propanil and inappropriate herbicide application makes them apply herbicides two or more times (Su¨rek, 2000). In Australia, thiobencarb for controlling barnyardgrass and benzofenap for controlling Cyperus diVormis, Damasonium minus, Sagittaria montevidensis, A. lanceolatum, and Alisma plantago‐aquatica are recommended (Clampett and Stevens, 2002). Bensulfuron‐methyl has been applied to more than 90% of the New South Wales rice crop, most often in combination with molinate (Skinner and Taylor, 2002). The herbicides used in Australian rice are bensulfuron, benzofenap, clomazone, molinate, thiobencarb, dicamba, MCPA sodium, glyphosate, paraquat, pendimethalin, and propanil (Taylor, 2004).

C. DEVELOPING WEED MANAGEMENT

FOR

DIRECT‐SEEDED RICE

In spite of eVorts in developing and disseminating eVective management strategies for crop protection from competition by weeds, weeds remain of major importance in DSR. In this section, we discuss a range of issues that are important in developing weed management for DSR both in terms of the response of the flora and in the development of new and existing technologies.

1. Grass Weed Control Section II outlined the responses in the weed flora that arose with the change to direct‐seeding in Asia, and many authors have highlighted the need to focus on grass weed control, particularly for Echinochloa spp. and weedy rice. a. Echinochloa spp. The genus Echinochloa consists of
50 species that exhibit polyploidy and ecotypic race diVerentiation and comprise both annual and perennial species (Kim, 1994; Michael, 1983; Yabuno, 1983). It has long been recognized as a contributor of weeds in both tropical and temperate rice. Echinochloa crus‐galli (and closely related species) is more competitive in direct‐seeded than in transplanted rice (Rao and Moody, 1987, 1992) in Asia and is well known as a serious weed in a range of crops elsewhere (Barrett, 1983; Norris, 1992). Despite possessing a C4 photosynthetic pathway, Echinochloa crus‐galli has evolved cold temperature adaptations and is native to

212

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Europe, North America (Potvin and Simon, 1989; Robert et al., 1983), and China (Zhang, 2003). Range expansion to West Africa has been reported (Danquah et al., 2002). Despite its worldwide distribution and economic importance, little is known about the population genetic structure of members of the genus (Lopez‐Martinez et al., 1999). The closely related species Echinochloa phyllopogon and Echinochloa oryzoides constitute the main grass weed species in California and Echinochloa phyllopogon has developed resistance to most herbicides currently used by farmers (Fischer et al., 2000a,b), indicative of genetic diversity. Resistance to butachlor has been reported in China (Huang and Gressel, 1997) and resistance to propanil in Sri Lanka (Marambe et al., 1997). Ecological amplitude (Mortimer, 2001), however, is characteristic of members of this genus (Gibson et al., 2004), and several authors have argued that there is a need to recognize the genetic structure and likely phenotypic variability of target populations in developing appropriate management strategies (Danquah et al., 2002). Gibson et al. (2002, 2003) and Gibson and Fischer (2001, 2004) have pointed to the importance of natural resource management that favors resource acquisition by the crop at the expense of the weed in this respect. Analysis of the reasons why an individual species continues to renew populations under weed management and persists in the face of control measures can only come through understanding the population dynamics of the species as argued earlier. Understanding the factors that govern seedling recruitment from the soil seed bank and cohort establishment within the rice crop in relation in particular to the water regime prior to germination and during early establishment is an important research issue in developing Echinochloa management in wet‐seeded rice. Equally, such understanding may explain the diVering abundance of Echinochloa spp. Echinochloa colona co‐occurs with Echinochloa crus‐galli in rice agroecosystems but tends to dominate in rainfed agriculture. It is a plausible hypothesis that the water profile (depth, duration, and frequency of flooding) immediately after land preparation and sowing interspecifically selects species. Pons (1982) commented that seed burial in saturated soil conditions prohibited Echinochloa colona germination, and Sahid and Hossain (1995) showed that early flooding increased seedling mortality. A similar mechanistic explanation can be advanced to explain the spatial distribution of Leptochloa chinensis in rice fields, where dense infestations are more often observed on land that has remained saturated but has not been flooded early (21–30 DAS) after crop sowing. Pane and Mansoor (1994) have experimentally indicated the subtlety of the interactions of plant size at time of flooding and depth in determining seedling survivorship. b. Weedy and Red Rice. Rice (O. sativa or other species) that is grown unintentionally in and around cultivated rice‐growing areas is regarded as a

WEED MANAGEMENT IN DIRECT‐SEEDED RICE

213

weed (Vaughan and Morishima, 2003). Generally, the term ‘‘weedy rice’’ refers to populations of Oryza spp. that diminish farmers’ income both quantitatively through yield reduction and qualitatively through lowered commodity value at harvest (Baki et al., 2000). Weedy rice poses perhaps the greatest threat to DSR because of the close similarity between weedy forms and the cultivated crop. Watanabe et al. (1997) recorded a yield loss of 60–74% in DSR, with an
35% weedy rice infestation. Weedy rice phenotypes occur in more than 50 countries in Africa, Asia, and Latin America (Valverde, 2005). Weedy rice infestations are reported for 40–75% of the rice area in European countries (Ferrero, 2003), 55% in Senegal (Diallo, 1999), 80% in Cuba (Garcia and Rivero, 1999), 60% in Costa Rica (Fletes, 1999), and 0.5–35.2% in southern Korea (Kim and Ha, 2005). In Latin America (Noldin, 2000), weedy rice is a much older problem than in Asia where it has been recorded at damaging infestation levels in Vietnam (Mai et al., 2000), Malaysia (Azmi et al., 2003), the Philippines (Fajardo and Moody, 1995; Moody, 1994; Rao and Moody, 1994), Sri Lanka (DA, 1997), Korea (Choi et al., 1995; Kim and Ha, 2005), and Thailand (Azmi et al., 2005). In Thailand, wild rice (Oryza rufipogon GriV.), a close relative of cultivated rice, is a noxious weed in fields of the central region (Maneechote et al., 2004). Invasion in some fields has been so severe that the crop has had to be abandoned occasionally. Similarly, a weedy form of rice (O. sativa Luolijing) has been reported to seriously interfere with cultivated rice in Liaoning Province of China (Yu et al., 2005). Historically, perhaps the most well‐known form of weedy rice is red rice, O. sativa possessing a caryopsis with a pigmented pericarp, which was identified as a weed as early as 1846 (Craigmiles, 1978). The name red rice is derived from the red color of pericarp, which, during milling, causes contamination of commercial rice grain. Red rice has been reported to contribute to lower grain quality in Greece (Eleftherohorinos and Dhima, 2002; Eleftherohorinos et al., 2002), Turkey, (Su¨rek, 2000), and Portugal (da Silva and Rodrigues, 2000). It is a common weed in most irrigated rice production areas in the Americas: Bolivia, Brazil, Chile, Colombia, Guyana, Italy, the United States, and Venezuela (Ferrero and Vidotto, 2002; Noldin, 2000). The status of red rice and its management in the United States were reviewed by Noldin (2000) and Sadohara et al. (2000). Rice growers in Louisiana (USA) have considered red rice of special importance since no selective herbicides were available prior to the advent of herbicide‐resistant rice (Williams et al., 2001). Gealy et al. (2000) reviewed the scale of red rice infestations in the southern rice belt of the United States and estimated that severe economic infestations occurred in 65% of the rice area in Louisiana, 25% in Arkansas, Texas, and Missouri, and 15% in Mississippi. The only areas where red rice is not considered a major problem

214

A. N. RAO ET AL.

are California and Uruguay. In California, water‐seeding and the use of certified seed have prohibited the ingress of weedy rice (Hill et al., 1994). Until recently, red rice was considered to be taxonomically identical to commercial rice. Genetic studies have shown that this classification is inadequate and that there are at least three distinct types of red rice (Vaughan et al., 2001). Red rice accessions have varying degrees of relatedness with cultivated rice (O. sativa subsp. indica and O. sativa subsp. japonica), and wild rice spp. Oryza nivara and O. rufipogon (Vaughan et al., 2001). O. sativa has a tendency to become weedy in areas where wild and cultivated rice grow sympatrically. In such regions hybrids that compete with cultivated rice and reduce yield may occur (Oka, 1988). However, weedy rice had also arisen in areas without native wild rice populations (Vaughan and Morishima, 2003). Weedy rice is postulated to be derived from (1) hybridization between diVerent cultivars and between cultivars, and wild species, (2) through the selection of weedy traits present in cultivars, and (3) by segregation from land races. Microsatellite marker analysis (Gealy et al., 2002) comparing the genetic relationships between populations of cultivars and weedy rice has provided insights into their origin in DSR‐growing areas. A global workshop on red and weedy rice control (FAO, 1999) recommended integrated approaches that combine preventive, cultural, and chemical methods. A key control measure is the use of clean and certified seeds. In the United States, the commercial availability of imidazolinone‐tolerant (IT) rice cultivars oVered the opportunity for selective chemical control of red rice as well as other weed species (Ottis et al., 2004). However, rapid gene introgression into rice (Burgos, 2005, personal communication) has now constrained the utility of this germplasm. Weedy rice has infested several rice‐growing areas in Malaysia, in particular in the MUDA region for the last decade, and rice farmers have resorted to practicing manual weeding for control (Azmi et al., 2003). Water‐seeding and control strategies combining preventive and cultural measures have also been shown to be eVective (Azmi et al., 2003; Chin et al., 2000b). However, designing and implementing strategies, particularly integrated weed control tactics, are a real challenge as the biological characteristics of weedy rice are similar to those of cultivated rice (Valverde, 2005). Vaughan et al. (2001) have emphasized that, since red rice is much more diverse than previously assumed, this diversity must be considered when developing management strategies. 2. Weed Management Technologies a. Improving Herbicide Use. Direct‐seeding systems are less robust than transplanting as the control of elements of soil moisture, irrigation, drainage, and weed control are more critical in DSR for successful crop

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establishment and growth. With management playing a more decisive role in crop establishment and weed control, direct‐seeding can be described as a ‘‘knowledge‐intensive’’ practice (Johnson and Mortimer, 2005). The transition from traditional transplanting to direct‐seeding renders ineVective the experience of traditional rice production systems with their reliance on indigenous knowledge and manual inputs. Instead, substantial information is required to enable farmers to judge the best technological options, especially during the transition from transplanting to direct‐seeding. In DSR, the timing and rate of application of herbicides need to be more precise than in the transplanted system. Improving farmers’ knowledge can substantially raise productivity, as was shown in the Sahel, where farmers were able to improve yields by 1.0 ton ha1 by combining appropriate timing and dose of herbicide application (Haefele et al., 2000). Such changes had a benefit‐to‐ cost ratio of more than 4, but they did require the acquisition and understanding of appropriate knowledge of both weed and crop management. The challenge for researchers is to analyze the existing knowledge gap, synthesize available knowledge, develop location‐specific practical solutions, and make them available to users. Rice varieties display diVerential sensitivities to a number of herbicides in relation to the soil environment and water regimes postapplication (Jordan et al., 1998a). For example, clomazone has been identified for weed control in dry‐seeded rice in the southern United States (Zhang et al., 2004) and is currently used in both dry‐seeded and water‐seeded rice (Scherder et al., 2004). Although rice has shown acceptable tolerance of clomazone (Mitchell and Gage, 1999), substantial injury can occur (Bollich et al., 2000; Jordan et al., 1998) especially on soils low in clay content. While not causing mortality, high doses of oxadiargyl (150 g a.i. ha1) can cause crop injury and presowing application of oxadiargyl with subsequent flooding may reduce selectivity in wet‐seeding (Gitsopoulos and Froud‐Williams, 2004). Butachlor at 1.5 kg ha1 without a safener may damage wet‐seeded rice seedlings when applied at 2 or 7 DAS, and toxicity is significant at the later application time (Angiras and Rana, 1998). Similarly, anilofos þ 2,4‐D ethyl ester at 0.40 þ 0.53 kg ha1 applied at 5 DAS may damage wet‐seeded rice (Behera and Jena, 1997; Choudhary and Thakuria, 1998). In wet‐seeded rice, phytotoxicity has also been observed with oxyfluorfen at 0.17 kg a.i. ha1 (Natarajan and Kuppuswamy, 1997), butachlor at 1, 1.5, and 2 kg a.i. ha1 (Angiras and Rana, 1998; Mathew and Jagadeeshkumar, 1999), and anilofos at 0.3–0.4 kg a.i. ha1 applied at 3 DAS (Mathew and Jagadeeshkumar, 1999; Sreedevi et al., 2001) and 8 DAS (Madhavi and Reddy, 2002). Informing farmers of the phytotoxic eVects of herbicides and the potential for rice recovery is of special relevance as direct‐seeding is adopted.

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b. Herbicide Resistance in Weeds and Its Management in Direct‐Seeded Rice. The evolution of herbicide resistance is now a common and undesirable feature of most cropping systems—313 herbicide‐resistant biotypes across 183 weed species have been reported at the time of writing (www.weedscience.org/ in.asp). Weed species resistant to herbicides have been reported in countries with high herbicide adoption rates, including the Philippines (Migo et al., 1986), Malaysia (Azmi and Baki, 2003; Kone et al., 2001), Japan (Itoh et al., 1999), Sri Lanka (Marambe et al., 1997; Sangakkara et al., 2004), Thailand (Maneechote et al., 2005), Korea (Kim and Ha, 2005; Kim et al., 2001), Colombia and Costa Rica (Rubin, 1997), Italy, Portugal, Spain, France, and Greece (Bocchi et al., 2005; Ferrero and Nguyen, 2004; Ntanos, 2001), North and Central America (Fischer et al., 2000b; Heap, 1997), and Australia (Graham et al., 1996; Pratley et al., 2001, 2004). Weeds of DSR that are resistant to herbicides in diVerent countries are summarized in Table VI. While herbicides remain inexpensive and eVective options, sustainable use requires a prudent mix of agronomic practices and the rotation of herbicides (Kone et al., 2001), and the use of herbicide mixtures with diVerent modes of action (Schmidt, 1997). The theory behind the evolution of herbicide resistance is well understood (Cousens and Mortimer, 1995; Gressel and Segel, 1990). However, resistance prevention ultimately depends on knowledge dissemination by a diversity of routes, and not least the product supply chain. In turn mitigating measures, when herbicide resistance has occurred, are essential. For example, in managing propanil‐resistant Echinochloa colona, pendimethalin has been considered an excellent partner for propanil to prevent propanil resistance evolution and as an alternative product when propanil resistance has already evolved (Riches et al., 1997). Table VII illustrates options for controlling herbicide‐resistant weeds.

c. Herbicide‐Resistant Transgenic Rice and Weed Management in Direct‐ Seeded Rice. Rice containing transgenes that impart resistance to postemergence, nonselective herbicides such as glyphosate and glufosinate allow farmers use of reduced‐ or no‐tillage cultural practices, and may potentially reduce the intensity of herbicide application while controlling nearly the entire spectrum of weed species (Duke, 1999). Three herbicide‐tolerance systems are being developed in rice: Clearfield (nontransgenic technology, providing tolerance of imidazolinones; Stidham and Singh, 1991), Liberty Link (transgenic technology with resistance to glufosinate) and, to a lesser extent, Roundup Ready rice (transgenic technology with resistance to glyphosate) (Williams et al., 2002). However, no transgenic rice cultivar has yet been approved for commercial cultivation anywhere in the world. Clearfield rice was registered in 2001 and fully

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Table VI Herbicide Resistance Among Major Weeds of Rice in DiVerent Countries Weed species

Resistance to the herbicide

Alisma plantago‐ aquatica Alisma plantago‐ aquatica Ammannia coccinea Bacopa rotundifolia Bacopa rotundifolia

Bensulfuron‐methyl and cinosulfuron Bensulfuron‐methyl

Bidens pilosa Cyperus diVormis Cyperus diVormis Cyperus diVormis Cyperus diVormis

Damasonium minus Echinochloa colona

Echinochloa colona Echinochloa colona Echinochloa colona Echinochloa crus‐galli Echinochloa crus‐galli Echinochloa crus‐galli Echinochloa crus‐galli

Echinochloa crus‐galli Echinochloa crus‐galli

Echinochloa crus‐galli

Bensulfuron‐methyl Bensulfuron‐methyl Bensulfuron‐methyl, metsulfuron‐methyl, and pyrazosulfuron‐ethyl Metsulfuron‐methyl Bensulfuron‐methyl Cyclosulfamuron and pyrazosulfuron‐ethyl Azimsulfuron, bensulfuron‐ methyl, and cinosulfuron Azimsulfuron, bensulfuron‐ methyl, cinosulfuron, cyclosulfamuron, ethoxysulfuron, halosulfuron‐methyl, imazosulfuron, and pyrazosulfuron‐ethyl Bensulfuron‐methyl Propanil

Quinclorac Azimsulfuron, fenoxaprop‐ p‐ethyl and propanil Fenoxaprop‐p‐ethyl Quinclorac Butachlor Thiobencarb Propanil

Butachlor and propanil Cyhalofop‐butyl, fenoxaprop‐p‐ethyl and quizalofop‐p‐tefuryl Propanil and quinclorac

Country (year of report) Italy (1994) Portugal (1995), Spain (2000) USA (2000) Malaysia (2000) Malaysia (2001)

China (1999) USA (1993), Australia (1994), Spain (2000) Brazil (2000) Italy (1999) South Korea (2002)

Australia (1994) Colombia (1988), Costa Rica (1987), El Salvador (1999), Guatemala (1999), Honduras (1999), Panama (1999), Venezuela (2000) Colombia (2000) Costa Rica (1998) Nicaragua (2000) Brazil (1999), USA (1998) China (1993) China (1993) Greece (1986), Italy (2000), Sri Lanka (1997), USA (1990) Thailand (1998) Thailand (2001)

USA (1999) (continued)

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Weed species

Resistance to the herbicide

Echinochloa crus‐galli

Cyhalofop‐butyl, fenoxaprop‐p‐ethyl, molinate, and thiobencarb Thiobencarb Fenoxaprop‐p‐ethyl Bispyribac‐sodium Cyhalofop‐butyl, fenoxaprop‐p‐ethyl, molinate, and thiobencarb Pyrazosulfuron‐ethyl 2,4‐D Fenoxaprop‐p‐ethyl Clefoxydim, fenoxaprop‐p‐ ethyl, and quizalofop‐p‐ ethyl 2,4‐D 2,4‐D and bensulfuron‐ methyl 2,4‐D, bensulfuron‐methyl, cinosulfuron Bensulfuron‐methyl and pyrazosulfuron‐ethyl Azimsulfuron, bensulfuron‐ methyl, cinosulfuron, cyclosulfamuron, ethoxysulfuron, halosulfuron‐methyl, imazosulfuron, and pyrazosulfuron‐ethyl Bensulfuron‐methyl, and pyrazosulfuron‐ethyl Bensulfuron‐methyl Bensulfuron‐methyl Imazosulfuron Bensulfuron‐methyl Bensulfuron‐methyl

Echinochloa phyllopogon Echinochloa phyllopogon Echinochloa phyllopogon Echinochloa oryzicola

Fimbristylis miliacea Fimbristylis miliacea Ischaemum rugosum Leptochloa chinensis

Limnocharis flava Limnocharis flava Limnophila erecta Lindernia dubia Lindernia dubia

Lindernia procumbens Monochoria vaginalis Rotala indica Rotala indica Sagittaria guayanensis Sagittaria montevidensis Sagittaria montevidensis

Sagittaria pygmaea Scirpus juncoides Scirpus juncoides

Bispyribac‐Na, cyclosulfamuron, ethoxysulfuron, metsulfuron‐methyl, and pyrazosulfuron‐ethyl Sulfonyl urea herbicides Bensulfuron‐methyl Azimsulfuron, bensulfuron‐ methyl, and pyrazosulfuron‐ethyl

Country (year of report) USA (2000)

USA (1998) USA (1998) USA (2000) USA (2000)

Brazil (2001) Malaysia (1989) Colombia (2000) Thailand (2002)

Indonesia (1995) Malaysia (1998) Malaysia 2003) Japan (1996) South Korea (2000)

Japan (1997) South Korea (1999) Japan (1998) South Korea (2002) Malaysia (2000) Australia (1994), USA (1993) Brazil (1999)

South Korea (2005) Japan (1998) South Korea (2001)

(continued)

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Table VI (continued) Weed species

Resistance to the herbicide

Scirpus mucronatus

Azimsulfuron, bensulfuron‐ methyl, cinosulfuron, and ethoxysulfuron Bensulfuron‐methyl Sulfonyl urea herbicides Metsulfuron‐methyl

Italy (1994)

2,4‐D

Malaysia (1995), Philippines (1983), Thailand (2000)

Scirpus mucronatus Scirpus planiculmis Solanum phoreinocarpum Sphenoclea zeylanica

Country (year of report)

USA (1997) South Korea (2004) China (1999)

Source: References cited in the review and www.weedscience.org/in.asp

released by BASF in 2002. So far, Newpath (imazethapyr) is the only imadazolinone herbicide registered in the Clearfield system. i. Imidazolinone‐tolerant rice. Rice tolerance of imidazolinone herbicides was developed from a single plant that survived a chemically induced mutation trial in 1993 (Sanders et al., 1998). This rice line is considered nontransgenic because it was developed through seed mutagenesis and not through gene transfer. Imazethapyr is a broad‐spectrum herbicide that controls many annual and perennial grass and broadleaf weeds preemergence or postemergence in drill‐ and water‐seeded rice (Kent et al., 1991; Williams et al., 2002). In both systems, imazethapyr eVectively controlled Echinochloa crus‐galli (91–98% mortality) with 70 or 87 g ha1 soil applied followed by 70 or 53 g ha1 early postemergence or late postemergence application (Pellerin and Webster, 2004). Pellerin et al. (2004) concluded that, in drill‐seeded rice, a preemergence application of imazethapyr followed by a postemergence herbicide mixture of imazethapyr plus bentazon plus acifluorfen, carfentrazone, halosulfuron, or propanil plus molinate would provide total weed control for grass (including red rice) and broadleaf weeds. Because of the possibility of outcrossing between IT rice and red rice, Ottis et al. (2004) argued the need to apply the maximum allowable imazethapyr rate of 70 g a.i. ha1 in two separate applications to ensure complete control of red rice, even on coarse‐ textured soils. As mentioned earlier, widespread outcrossing of imazethapyr resistance has now been detected in red rice (Shivrain et al., 2007). ii. Glufosinate‐resistant rice. The rice varieties Gulfmont and Koshihikari possess the bialaphos resistance (BAR) gene for glufosinate resistance through genetic engineering (Agracetus, Inc., 1991), and if glufosinate‐ resistant rice is released, it is anticipated that lines will be developed from medium‐grain variety BNGL‐62 (Lanclos et al., 2003; Webster et al., 2003). Glufosinate is a nonselective herbicide that controls many grass and broadleaf

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Table VII Alternative Herbicides Identified for Managing Herbicide‐Resistant Weeds Herbicides Oxadiazon, thiobencarb, fentrazamide, oxadiargyl, butachlor; simetryn, carfentrazon‐ethyl, pyriminobac‐methyl, bezobicyclon Bispyribac‐sodium

Bentazon/MCPA

Quinclorac, bispyribac‐ sodium Imazethapyr

Quinclorac þ propanil Pendimethalin

Benzofenap Piperophos and anilofos

Weeds controlled

Country

References

Sulfonylurea‐ resistant weeds

South Korea

Kim and Ha (2005)

Thiobencarb, molinate and fenoxaprop‐ethyl‐ resistant Echinochloa crus‐ galli and Echinochloa phyllopogon 2,4‐D and sulfonylurea‐ resistant weeds Propanil‐resistant Echinochloa crus‐ galli Propanil‐resistant Echinochloa crus‐ galli and Urochloa platyphylla Propanil‐resistant Echinochloa colona Propanil‐resistant Echinochloa colona

USA

De Witt et al. (2002)

Malaysia

Azmi (2003)

Sri Lanka

USA

Marambe and Amarasinghe (2002) Scherder et al. (2001)

Costa Rica

Valverde et al. (2001)

Costa Rica

Bensulfuron‐ resistant weeds Propanil‐resistant Echinochloa colona

Australia

Riches et al. (1997); Valverde et al. (2001) Pratley et al. (2001, 2004) Valverde et al. (1997, 1999)

Costa Rica

weeds (Ahrens, 1994). It has been evaluated extensively for weed control in rice (Braverman and Linscombe, 1994; Hatzois, 1998; Lanclos et al., 2002). Postemergence application of glufosinate provides eVective control of most weeds, including red rice, with little injury to glufosinate‐resistant rice (Lanclos et al., 2003). In glufosinate‐resistant rice, glufosinate at 0.6 kg ha1 controlled red rice (Sankula et al., 1997) and at 0.42 kg ha1 controlled barnyardgrass and broadleaf signalgrass [Brachiaria platyphylla (Griseb.)] Nash (Lanclos et al., 2002). Control increased with the addition of propanil (Lanclos et al., 2002;

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Sankula et al., 1997), acifluorfen at 0.6 kg ha1 (Sankula et al., 1997) or propanil plus molinate (Lanclos et al., 2002). Antagonism was observed for control of barnyardgrass with mixtures of glufosinate at 0.42 kg ha1 with bensulfuron, halosulfuron, and quinclorac (Lanclos et al., 2002). d. Gene Flow and Its Implications in Weed Management. The use of herbicide‐resistant GM crops poses the risk of gene flow via pollen and seed, resulting in (1) contamination of nearby non‐GM crops with the transgene, (2) establishment of herbicide‐resistant volunteer weeds in the crop field and nearby non‐cropland, and (3) unintended and unanticipated eVects on closely related species (Cohen et al., 1999; Kwon et al., 2001). Although rice is primarily a self‐pollinated crop, cultivars in farmers’ fields are rarely isogenic at all loci and cross‐pollination occurs at a suYcient frequency to cause hybrids. Moreover, wild rice occurs sympatrically with cultivated rice and each is sexually compatible (Song et al., 2003). Weedy rice in particular often grows within cultivated rice fields (Messeguer et al., 2004). Experimentally, Song et al. (2003) demonstrated that gene flow from cultivated rice to the wild species O. rufipogon occurred at a considerable rate (around 3%) and at a distance up to 43 m. In China, Lu et al. (2002) and Chen et al. (2004) confirmed that cultivated rice and its wild relative O. rufipogon had a sympatric distribution and overlapping flowering time, which met the spatial and temporal conditions necessary for transgene escape from cultivated rice to wild relatives, and that most of the AA genome wild Oryza spp. had relatively close biosystemic relationships and could cross with cultivated rice, particularly O. rufipogon, O. nivara, and O. spontanea (weedy rice). However, other studies have reported a lower rate of gene flow from transgenic rice to red rice (Zhang et al., 2003) and conventional rice (Messeguer et al., 2004). Transgene escape may become a much more serious problem where weedy rice is abundant because its life cycle within the cropping system is closely aligned with the crop. Because weedy rice is a global constraint to rice production, the merit of transferring herbicide‐resistance genes into modern rice varieties needs careful evaluation. Recognizing this threat, Valverde and Gressel (2005) have called for genetic mitigation constructs in developing new lines of herbicide‐resistant rice. Certainly, one of the possible and immediate risks is herbicide‐resistant GM crops becoming volunteer weeds (Kwon and Kim, 2001). Dry direct‐ seeded rice is one of the most likely crops in this respect. In the event of commercialization of glufosinate‐resistant rice, IWM programs would therefore need to be adopted to control gene transfer (Sankula et al., 1998). Control strategies such as tillage, competitive crops in rotation and the use of herbicides with diVerent modes of action represent mainstays in this regard and emphasize the ‘‘knowledge‐intensive’’ nature of this technology.

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3.

Potential Weed Control Methods

a. Allelopathy. Perusal of the literature on weed management in rice indicates that there has been a long interest in the potential role of allelopathy in weed management. Rice cultivars with allelopathic ability, that is, producing root exudates that target competing species, have long been hypothesized to occur. Extensive evaluation of the allelopathic potential of rice germplasm in drill‐seeded systems began in the early 1980s, and rice cultivars were reported to suppress H. limosa and partially suppress Echinochloa crus‐galli in the United States (Dilday et al., 1998, 2001; Gealy et al., 2003, 2005a) and Asia (Olofsdotter et al., 2002). Allelopathy has been a contentious area of ecological research since its inception, and Harper (1977) made the point that allelopathy in the field has proved extraordinarily diYcult to illustrate, and stated that ‘‘it is logically impossible to prove that it does not happen and perhaps nearly impossible to prove absolutely that it does.’’ He went on to point out that almost any plant species could, by appropriate digestion, extraction, and concentration, be persuaded to yield a product that was toxic to one species or another. Common laboratory screening of rice cultivars for allelopathy uses a ‘‘relay seeding technique’’ the results of which are correlated with field studies of rice competitiveness against selected weed species (Olofsdotter, 2001). Numerous studies on allelopathy have continued, and rice accessions with putative allelopathic potential have been identified (Ahn et al., 2005; Dilday et al., 1994; Gealy et al., 2003, 2005a; Olofsdotter et al., 2002). Much of this work ignores the findings of Stowe (1979), who concluded that the results from bioassay methods were highly variable and that incidence of autotoxicity was as high as allotoxicity. As a consequence, it is likely that allelopathy as measured in bioassays does not occur in the field. Further, he concluded that ‘‘bioassays never adequately simulate natural conditions, and the investigator can neither demonstrate allelopathy if the results are positive, nor discount them if they are negative.’’ Further complications arise from the diYculties of separating the individual eVects of plant interactions. It can be hypothesized that an allelopathic trait may have evolved in response to resource (light, water, nutrients, space) competition. Is competition required, however, for allelopathic ability to be expressed and, if so, can researchers distinguish between the outcome of resource competition and allelochemical interactions? Williamson (1990) argued that the application of Koch’s postulates was required to establish proof of allelopathy. In this test, the putative chemicals would be added on a rate release basis and, to remove all alternative interactions, the allelopathic plant would be absent. Until such critical experiments are undertaken, the significance of allelopathy in the field can only be inferred and remains conjecture. This, however, has not halted discussion of the potential value of allelopathic rice cultivars as a component of IWM

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(Duke et al., 2000, 2002; Jensen et al., 2001; Kim and Shin, 2005; Ni and Zhang, 2005; Olofsdotter, 2001). b. Bioherbicides. Biological control can be divided into the ‘‘classical’’ and ‘‘bioherbicide’’ approaches (Hallett, 2005). The classical approach involving the use of exotic predators or pathogens has not been implemented in rice. However, there has been greater research interest in the development of bioherbicides. This technology commonly seeks to exploit the use of a naturally occurring coevolved plant pathogen which is applied at inundative levels in a simple formulation. The status of bioherbicides has been reviewed by a number of authors (Charudattan, 2001; Hallett, 2005; Li et al., 2003), and some eVective biocontrol agents are listed in Table VIII. Although a substantial number of pathogens for target species have been identified, relatively few have been commercialized. Colletotrichum gloeosporiodes (Penz.) Penz. & Sacc. aeschynomene (Collegot) was registered in 1982 for the control of northern jointvetch [Aeschynomene virginica (L.) B.S.P.] in rice in the United States. Puccinia canaliculata (Biosedget) was shown to control Cyperus esculentus L. and limit new tuber formation by 66% (Boyetchko, 1997), though it has yet to be commercialized (Li et al., 2003). Damasonium minus (R. Br.) Buch is an important native plant species considered to be the most important weed in rice‐growing areas of Australia. Rhynchosporium alismatis (Oudem.) J. J. Davis is a coevolved pathogen of both these species and others in the Alismataceae (Jahromi et al., 2004), and leaf necrosis occurs on leaves of Damasonium minus, Sagittaria guyanensis H.B.K., Alisma lanceolatum L., and Alisma plantago‐aquatica L. (Cother et al., 2002). Farzad et al. (2001) concluded that R. alismatis had characteristics to be a successful mycoherbicide as it can be readily multiplied in artificial culture. It has also been reported to have a synergistic eVect with bensulfuron‐methyl (Cother et al., 2002). Good control of Sphenoclea zeylanica with Alternanthera alternate (Fr.) Keissler f. sp. sphenocleae has been reported (Mabbayad and Watson, 1995; Masangkay et al., 1999) for specific humidity and temperature regimes. Similarly, foliar application of conidial suspensions of Curvularia tuberculata Jain and Cyperus oryzae Bugnicourt killed seedlings of Cyperus diVormis, C. iria, and F. miliacea (Luna et al., 2002a,b). Exserohilum monoceras and Cochliobolus lunatus have been reported to kill Echinochloa sp. after 14 days leaving rice unaVected (Chin, 2001). Spraying of the fungus Setosphaeria rostrata on Leptochloa chinensis resulted in almost complete leaf death (Thi et al., 1999). Synergism has also been reported between Setosphaeria rostrata and pyrazosulfuron ethyl for L. chinensis control (Chin et al., 2002). Drechslera monoceras has been tested on Echinochloa crus‐galli in rice; better control being observed under low (25/15  C, day/night) temperatures (Hirase et al., 2004).

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Table VIII Potential Biocontrol Agents Reported to be EVective in Controlling Weed Species Associated with Rice

Weed species

Potential biocontrol agent

Country

References

Australia

Cother et al. (2002)

Alternanthera philoxeroides Cyperus diVormis Cyperus diVormis Cyperus esculentus

Rhynchosporium alismatis Fusarium sp.

China

Tan et al. (2002).

Curvularia tuberculata Curvularia oryzae Dactylaria higginsii

Cyperus globulosus

Dactylaria higginsii

Cyperus iria

Dactylaria higginsii

Cyperus iria Cyperus iria Cyperus rotundus

Curvularia tuberculata Curvularia oryzae Dactylaria higginsii

Damasonium minus

Rhynchosporium alismatis

Echinochloa crus‐galli Echinochloa crus‐galli Echinochloa crus‐galli Echinochloa crus‐galli Echinochloa crus‐galli Echinochloa glabrescens Echinochloa spp. Eichhornia crassipes

Exserohilum monoceras Drechslera monoceras Exserohilum monoceras Cochliobolus lunatus Exserohilum monoceras Exserohilum monoceras

Philippines Luna et al. (2002a,b) Philippines Luna et al. (2002a,b) USA Kadir and Charudattan (2000) USA Kadir and Charudattan (2000) USA Kadir and Charudattan (2000) Philippines Luna et al. (2002a,b) Philippines Luna et al. (2002a,b) USA Kadir and Charudattan (2000) Australia Cother et al. (2002); Jahromi et al. (2001, 2004) China Huang et al. (2001) China Huang et al. (2001) Vietnam Chin (2001) Vietnam Chin (2001) Philippines Zhang and Watson (1997) Philippines Zhang and Watson (1997)

Drechslera monoceras Fusarium pallidoroseum

Japan India

Alismataceae weeds

Eichhornia crassipes Fimbristylis miliacea Fimbristylis miliacea Hydrilla verticillata Kyllinga brevifolia Leptochloa chinensis Sagittaria trifolia Sphenoclea zeylanica Sphenoclea zeylanica

Hirase et al. (2004, 2004a) Praveena and Naseema (2003) Myrothecium advena India Praveena and Naseema (2003) Curvularia tuberculata Philippines Luna et al. (2002a,b) Curvularia oryzae Philippines Luna et al. (2002a,b) Plectosporium tabacinum USA Smither‐Kopperl et al. (1998) Dactylaria higginsii USA Kadir and Charudattan (2000) Setosphaeria rostrata Vietnam Chin et al. (2003); Thi et al. (1999) Plectosporium tabacinum Korea Chung et al. (1998) Colletotrichum Philippines Bayot et al. (1994) gleosporiodes Alternanthera alternata Philippines Mabbayad and Watson (1995); Masangkay et al. (1999)

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Despite the demonstrated eYcacy of some bioherbicides under laboratory test conditions, adoption has been rare. An intrinsic constraint of inundative bioherbicides is that they most commonly target a single weed species in a weed community and moreover that species itself will have coevolved with the pathogen. In consequence genetic variability in resistance to the bioherbicide is to be expected and evolution of resistance may be an expected response. Hallett (2005) concluded that the current status of bioherbicide applications does not promise to make significant advances unless the performance of bioherbicides themselves can be reliably enhanced. With more eVort devoted to developing techniques for the cultural and genetic enhancement of bioherbicidal organisms, they may have a role in future weed management systems.

IV.

FUTURE RESEARCH NEEDS

Weed infestation is a major threat to yield and further expansion of DSR throughout the world. In most developed nations, direct‐seeding is the sole method of rice establishment and is reliant on mechanization and close attention to weed management. While shortage of labor in Asian agriculture is encouraging the adoption of direct‐seeding, so too is the need to improve water productivity (Tuong et al., 2005). ‘‘Aerobic’’ rice (Bouman, 2003) may reduce water consumption by up to 50% (Yang Xiaoguang et al., 2002). Sustainable rice production by direct‐seeding therefore will critically depend on ensuring that on‐farm weed management technologies are implemented in the absence of a historical free public good—standing water for weed suppression. This represents a paradigm shift in the application of weed control measures for rice farmers that have solely transplanted in the past. At the research and extension level, it places a premium on the design of integrated management measures to respond to weed species shifts arising from changes in crop establishment and/or the evolution of herbicide resistance. Some future research needs focusing on this issue are highlighted below, in addition to those discussed earlier. 1. Characterizing scales of yield loss: Knowledge of the yield losses at farm level in developing countries due to imperfect weed control remains incomplete, as too, do the underlying reasons for them. Adoption of DSR is likely to increase the variance in these yield losses since it is likely that knowledge transfer for successful cropping may be incomplete. Information on farmers’ resource base and knowledge will be needed to successfully implement suitable weed management practices. In the first instance, studies may best be conducted in selected agroecosystems

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in order to provide broad‐based understanding on which location‐specific options can be based. 2. Understanding the role of water management on weed population dynamics: Water management plays an important role in weed control in direct‐ seeded rice, yet greater understanding is still required to be able to maximize the role of water in weed management in itself and in combination with herbicides. For example, alternate wetting and drying by controlled irrigation has water‐saving potential (B. A. M. Bouman, personal communication), yet at the same time, this procedure will have considerable impact on the germination and establishment of weeds. Relevant research in this area includes (1) understanding the relationship between water depth/drainage and weed recruitment and (2) identifying rice germplasm and practices to improve rice‐seedling survival and emergence under flooding (Jackson and Ram, 2003). The corollary at the extension level includes perfecting decision tools to target particular weeds species and improving infrastructure at the field level to allow for precision flooding, uniform water depths, and drainage. 3. Developing cultivars with competitive ability: Improved competitive ability of rice cultivars, as a component of IWM, is yet to be exploited fully. Vigorous, early vegetative growth has been identified as the key characteristic (Asch et al., 1999), but there remains much to be learnt about the characteristics that impart competitiveness, the component traits of vegetative vigor, possible trade‐oVs, and the relative importance of these in diVerent cropping environments and management systems (Caton, 2002). Unraveling these relationships requires mechanistic process‐based modeling coupled with detailed experimentation as emphasized by many authors (Bastiaans et al., 1997; Caton et al., 1999a,b; Weigelt and JolliVe, 2003). Several studies (Assemat et al., 1981; Gibson et al., 1999; Perera et al., 1992) have suggested that root competition plays a major role in the interaction between rice and Echinochloa spp. Gibson et al. (1999) found that the primary mechanism by which water‐seeded rice reduced watergrass growth was through competition for nitrogen. Gibson and Fischer (2001) opined that for substantial Echinochloa oryzoides control, early nutrient deprivation by rice roots may be as relevant as improving rice ability to intercept light. Rice cultivars can diVer in root growth and morphology (Slaton et al., 1990) and nutrient‐uptake rates (Teo et al., 1995). The relationship between rice root growth, competitive ability of rice for resources against weeds, and rice yields deserves more attention. 4. Identifying crop rotations and management practices for reducing weed infestations: Rotation of crops with diVerent planting dates and growth periods, contrasting competitive characteristics, and dissimilar management practices are well known to arrest the development of weed

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communities. Knowledge‐intensive RCTs including zero tillage, the FIRBS, and rotary tillage have been developed for the rice–wheat system in the Indo‐Gangetic plains (Singh et al., 2006). Singh et al. (2005a) have shown that diVering tillage practices in wheat selectively alter the relative abundance of grass and sedge weeds in the succeeding rice crop. The extent to which rotation of DSR methods (dry and wet) has an impact on rice weed communities remain unclear as does the influence of dry season nonrice‐cropping practices. Further understanding will arise from long‐ term studies of weed communities coupled with autecological examination of selected target species. 5. Evolving eVective herbicides and IWM: The use of herbicides will increase with the expansion of DSR and the decreasing availability of irrigation water, and with the development and adoption of reduced‐tillage systems. There is an urgent need to optimize their use not only as a response to regulations and the public concern about pesticide residues in food and water, and to minimize possible adverse eVects on the environment, but also to ensure that herbicides will remain an eVective and valuable tool to farmers of DSR in the future. EVective, safe herbicides and mixtures are required to enable farmers to use them as components of IWM. Continuous monitoring to identify the emergence of new and diYcult‐to‐control weed problems such as weedy rice and the evolution of herbicide‐resistant weed biotypes is necessary if farmers are to be provided with timely alternatives. The challenge for weed management research in DSR is to develop control strategies that sustain and enhance farm profits while safeguarding the environment and human health. The key to the success of DSR is the availability of eYcient weed control techniques to use as components of IWM. Due attention is needed to identify, streamline, and adopt the ways and means to increase farmers’ participation in developing ecologically and economically viable IWM systems for DSR. 6. Molecular biology: Molecular methods are vital to providing a better understanding of the potential for gene flow that might result from the introduction of GM crops, such as herbicide‐tolerant rice varieties, in addition to elucidating the genesis of weedy rice as discussed earlier. Taxonomic uncertainty among certain weed species (e.g., the Echinochloa spp. complex) remains an additional constraint in understanding the reasons for resilience to control and improved understanding of the genetic structure of grass populations and their evolutionary responses to control will underpin the development of improved weed management practices. 7. Improving decision making: Direct‐seeded rice is by nature knowledge intensive, and ensuring that relevant, beneficial, and cost‐eVective decisions are made at the farm level is prerequisite for both farm profitability and sustainable weed management. Decision making at strategic (long term), tactical (seasonal), and operational levels in the field (short term)

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ensures appropriate responses to a variable weed flora, safe use of chemical weed control in areas where water has a multiplictity of uses (domestic and agricultural) and prohibition of herbicide resistance evolution. In many instances, understanding of farmer decision making in these contexts is scant, particularly in developing countries, and there is considerable scope for research into eVective transfer and utilization of knowledge (Orr, 2003). 8. Understanding the impact of global climate change: Rapid and simultaneous changes in temperature, precipitation, and the atmospheric concentration of CO2 are predicted to occur over the next century (IPCC, 2001). As discussed in an earlier section, competitive grass weeds with a C4 pathway (e.g., Echinochloa spp., Paspalum spp.) are expected to increase with the adoption of DSR. Competitiveness could be enhanced in a C3 crop (rice) relative to a C4 weed (Echinochloa glabrescens) with elevated CO2 alone, but that simultaneous increases in CO2 and temperature could still favor a C4 species (Alberto et al., 1996). It is generally thought that global warming will favor C4 species relative to C3 species, and indeed the distribution of many tropical and subtropical C3 and C4 weeds appears to be limited by low temperature although some C4 weeds are highly successful in northern latitudes (e.g., Amaranthus spp., Echinochloa crus‐galli). Temperature sensitivity to growth may limit poleward range expansion of some rice weeds, for example, R. cochinchinensis (Patterson, 1993), but increased CO2 may in itself allow such extension. Elevated CO2 has been found to increase tolerance to low temperatures in several weed species (Potvin and Strain, 1985). Relatively little is known about patterns of phenological development, flowering time, and seed production in rice weed species in relation to changes in temperature and CO2. Flowering can be faster, slower, or unchanged at elevated CO2 depending on species (Patterson, 1995), and more rapid emergence of weed seedlings at elevated CO2 has been documented under field conditions (Ziska and Bunce, 1993), tending to occur in small‐seeded species. Weed scientists have as much a duty to future generations to assess the likelihood of range expansion and altered crop competitive pressure in weed species as do crop scientists in evaluating crop performance in monoculture in response to climate change.

ACKNOWLEDGMENTS The authors are grateful to Cropnosis Limited for providing data on herbicide sales; Drs. Y. Singh, M. M. Kyu, H. Pane, and A. Abeysekera for their advice on the distribution of weed species; Professor Robert E. L. Naylor,

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University of Aberdeen, UK; Drs. N. T. Yaduraju and H. Pathak, Indian Agricultural Research Institute, India for providing critical and constructive comments on the chapter; and Dr. Bill Hardy, Senior editor, IRRI for editing the chapter.

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ECOREGIONAL RESEARCH FOR DEVELOPMENT J. Bouma,1 J. J. Stoorvogel,1 R. Quiroz,2 S. Staal,3 M. Herrero,3 W. Immerzeel,4 R. P. Roetter,1 H. van den Bosch,1 G. Sterk, 1 R. Rabbinge1 and S. Chater5 1

Wageningen University and Research Centre, Wageningen, The Netherlands 2 International Potato Centre, Lima, Peru 3 International Livestock Research Institute, Nairobi, Kenya 4 FutureWater, Wageningen, The Netherlands 5 Green Ink Ltd., Devon, United Kingdom

I. II. III. IV.

Introduction Changing Concepts of Development Research in Relation to the Policy Cycle Examples from the Projects of the Fund A. Developing the Kenyan Highlands B. Reacting to Trade Liberalization C. Signaling Constraints in Sustainable Use of Water Resources on the Tibetan Plateau D. Multiple Goals for Land Use in Southeast Asia E. From Environment to Human Health F. Really Dealing with Soil Erosion G. Reestablishing Farmers’ Credit in the Highveld Region, South Africa V. Where Do We Stand Now and Where to Go? A. Showing New Ways of Conducting Research B. Showing New Ways of Presenting Results C. Presenting New Messages to Policymakers and Land Users Acknowledgments References

ABBREVIATIONS ACED ARC-GCI

Assessment of Current Erosion Damage Agricultural Research Council-Grain Crop Institute (South Africa) 257 Advances in Agronomy, Volume 93 Copyright 2007, Elsevier Inc. All rights reserved. 0065-2113/07 $35.00 DOI: 10.1016/S0065-2113(06)93005-3

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CGIAR CIMMYT CIP CLRRI CLUE GIS ICIMOD IDIAP ILRI IMPACT IPM IRRI KARI LUPAS MARDI MIDA NUTMON SWAT SYSNET

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Consultative Group on International Agricultural Research Centro Internacional de Mejoramiento de Maı´z y Trigo (International Wheat and Maize Improvement Center), Mexico Centro Internacional de la Papa (International Potato Center), Peru Cuu Long Delta Rice Research Institute (Vietnam) Conversion of Land Use and its EVects Geographical Information Systems International Centre for Integrated Mountain Development Instituto de Investigacio´n Agropecuaria de Panama´ International Livestock Research Institute (Kenya) Integrated Modeling Platform for Mixed Crop-Animal Systems Integrated Pest Management International Rice Research Institute (Philippines) Kenya Agricultural Research Institute Land Use Planning and Analysis System Malaysian Agricultural Research and Development Institute Panama’s Ministry of Agriculture and Development Nutrient Modeling for Tropical Farming Systems Soil and Water Assessment Tool Systems Research Network for Ecoregional Land Use Planning in Support of Natural Resource Management in Tropical Asia

I. INTRODUCTION The character of international agricultural research has changed profoundly in the last decades of the twentieth century. This can be well illustrated by developments within the Consultative Group on International Agricultural Research (CGIAR) as reviewed by Rabbinge (1997). The following successive phases may be distinguished since the 1960s: (1) crop improvement through better use of genetic material, with particular emphasis on wheat [CIMMYT, i.e., Centro Internacional de Mejoramiento de Maı´z y Trigo (International Wheat and Maize Improvement Center), Mexico] and rice (IRRI, i.e., International Rice Research Institute, Philippines); (2) improved agronomic technologies, such as soil management, including soil fertility and tillage, irrigation,

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and crop protection; (3) farming systems research tailored to farmers’ socioeconomic needs; (4) awareness of environmental side eVects of agricultural practices, particularly in fragile regions, such as land degradation, erosion, excessive leaching of agrochemicals, salinization and biodiversity loss, calling for improved resource management; and (5) a comprehensive systems’ analysis focusing on basic, applied, and strategic research in a participatory mode and tailored toward ecoregions. Thus, supply-oriented research gave way to demand orientation. Technology push was replaced by technology pull and the linear knowledge model became obsolete and was replaced by a participatory cyclic knowledge model. Exclusive emphasis on crop research broadened to investigating production systems on farm and regional levels emphasizing sustainable development including socioeconomic and environmental considerations. Not only farmers became involved in research but also other land users and stakeholders as well as policymakers and planners, although addressing the latter category was and remains challenging. The problems to be studied are highly complex and diYcult. Computer simulation models, performing a comprehensive systems’ analysis, appear to be indispensable research tools, as has been demonstrated in comparable econometric and exploratory studies of national planning bureaus. However, before the 1990s, methodologies for making a comprehensive systems’ analysis of sustainable agricultural production systems were hardly available. The need for a further support of comprehensive systems’ analysis of the CGIAR agenda required new research and the development agencies of the Dutch and Swiss governments initiated, therefore, the Ecoregional Methodology Fund in 1995 as part of its development-oriented activities. Despite all rhetoric suggesting otherwise, most agricultural research activities in the tropics were still focused on plot, field, or farm level and were primarily addressed to farmers advising them on production issues. This was less relevant for decision makers and opinion leaders on regional, national, and international levels without a broader context. The Fund was charged to: support the development of new methodological tools for research that is ecoregional in scope with the intention of promoting new approaches to natural resource management and rural development in ecoregions. This chapter summarizes and discusses what the Fund has accomplished and which future challenges remain. In doing so, the following items are discussed: (1) a sketch of the changing social and political environment in which the work has been done, ranging from the UN Millennium Development Goals (MDGs) to the strategy of the CGIAR Science Council and the Gleneagle summit, (2) the changing role of research vis a vis the policy cycle, (3) illustrations for the policy cycle from projects of the Fund, and (4) implications for research, including new forms of interaction, design of operational tools, and new forms of education and communication.

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II. CHANGING CONCEPTS OF DEVELOPMENT In the early years of the Fund, the eVectiveness of development cooperation was increasingly questioned by international donors. Even though substantial amounts of money were spent on a wide range of development projects, many very poor countries were unable to accelerate their development with the eVect that the gap between rich and poor, North and South, continued to widen significantly. Corruption and ineVective governance next to poor planning led to waste and lack of promising results. In this period several studies by the World Bank were influential. For example, Dollar (1998) showed that aid was correlated with economic growth in poor countries but only under conditions of good governance, which was defined somewhat loosely as abiding by the rules of law, human rights, and democracy in a stable institutional framework. The suggestion was to restrict aid to countries with good governance and to require these countries to write Poverty Reduction Strategy Papers in which they specifically formulated their plans. This has worked well to a certain extent but the nagging question remained what to do about the many countries that did not meet the northern-imposed criteria for good governance? Increasingly, the feeling prevailed that no matter what, development processes in the world cannot be sustained when more than 800 million of its inhabitants are hungry and 1.2 billion earn less than one dollar a day. Poverty reduction seemed to be the key to a more or less harmonious pattern of global development. Increased concern about the inadequacy of so many lofty plans that did not materialize, led in the year 2000 to the UN Millennium project which formulated 8 goals and 18 specific targets to combat world poverty (www. unmillenniumproject.org). In 2005, 13 task forces reported on possible measures to be taken to reach the Millennium Goals. In the same year, the Fund was foreseen to end its activities. It would, of course, not be wise to ignore the Millennium Goals when evaluating the work of the Fund, goals which so clearly reflect an international consensus. Results will therefore also be reported in relation to the eight Millennium Goals. Of particular relevance are Goal 1 (eradicates extreme poverty and hunger), Goal 7 (ensures environmental sustainability), and Goal 8 (develops a global partnership for development). This selection indicates that the Fund and agricultural research in general can, of course, only cover part of what are seen as key problems of development. Still, as agriculture in most developing countries employs more than 80% of the people, emphasis on improving land productivity and land use can be seen as a core activity and as a logical starting point in trying to reach the Millennium goals. Aside from the task-force reports, the year 2005 also saw the results of the Gleneagle conference of the G8 where promised aid to Africa was doubled.

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Within the CGIAR system, the Science Council has in this context defined five separate research priority areas for CGIAR, specified by 23 subpriorities (www.sciencecouncil.cgiar.org): 1. Sustaining biodiversity 2. Producing more food at lower costs through genetic improvement 3. Creating wealth among the rural poor through high-value commodities and products 4. Combining poverty alleviation and sustainable management of water, land, and forest resources 5. Improving policies and facilitating institutional innovation to support sustainable reduction of poverty and hunger Area (5) is particularly relevant for the ecoregonial work where the primary focus is not on individual farmers but on policymakers, politicians, and planners and their plans as they aVect farmers and other land users. Illustrating the urgency of taking a fresh look at the role of research in development, the World Bank has launched a new assessment to look at the role of agricultural science, knowledge, and technology for development (IAASTD, 2005). Are scientists prepared to make major contributions toward reaching the Millennium Goals or the objectives of the CGIAR priority areas? One cannot be sure. International agricultural research is now in a permanent discussion on its future course. There is a tendency to go back to the former linear knowledge model (mode-1) and pleas for more strategic research. There is, however, also clear interest to further develop the character of research emphasizing a more demand-driven approach using a participatory knowledge model (mode-2). This corresponds with a general trend in science where a focus on society and relevant policy issues is receiving increasing attention, emphasizing the need for interdisciplinary research and interactivity of researchers with various stakeholders (Ravetz and Funtowicz, 1999). Gibbons et al. (1994) speak about (mode-1) science which is academic, disciplinary, homogeneous, hierarchic, stable, and subject to academic quality control and accountability. ‘‘Mode-2’’ research, on the contrary, is application-oriented, transdisciplinary (also involving stakeholders), heterogeneous, nonhierarchic, and variable, while quality is measured on a wider set of criteria (Royal Netherlands Academy of Arts and Sciences, 2005) and accountability is to society as well. This broader focus is also clearly indicated in the strategic plan for the period 2006–2010 of the ICSU (International Council of Science, 2005). In their vision, they speak of: where science is used for the benefit of all . . . and where scientific knowledge is eVectively linked to policymaking. Their goal is to: strengthen the international science for the benefit of society. Also the recent reports of the InterAcademy Council (2004a,b) and the taskforce on Science, Technology, and Innovation

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of the Millennium project emphasize the need for interdisciplinarity and interaction with stakeholders and policymakers. Not only the international agencies were making plans. The Kenyan government, for example, published a Strategy for Revitalizing Agriculture in 2004 (Ministries of Agriculture and Livestock and Fisheries, 2004). The National Planning Commission of the Nepalese government published a Poverty Reduction Strategy Paper (National Planning Commission, 2003) and a South African report to the OYce of the Executive Deputy President and the Inter-Ministerial Committee for Poverty and Inequality also addressed the need for development research (Wilkens, 1998). The projects of the Ecoregional Methodology Fund clearly reflect the demand-driven approach, mentioned above, using a participatory knowledge model. Moreover, as the projects of the Fund have proceeded from 1996 onward, it became increasingly clear that the relation between the research community and its stakeholders, be it farmers, land users, or policymakers, was clearly changing. So rather than only defining tools and methods for ecoregional research (which was and is the prime objective of the Fund) major attention was also paid to the manner as to how these tools and methods are being used and can be used by whom and when. More broadly the question will be addressed in various case studies funded by the Ecoregional Methodology Fund, as to how environmental and agricultural sciences should adapt its procedures to the new challenges of the information age and to progressing globalization. By addressing the regional level, the projects of the Fund fill a particular niche. The Millennium goals and many reports with a global scope address global issues in a by necessity generic manner. On the other hand, much agricultural research still focuses on the farm level and research at the intermediate regional level has so far been somewhat neglected. This level, defining specific local conditions, is particularly relevant for local stakeholders and national policymakers and they were the primary partners in the various projects of the Fund.

III. RESEARCH IN RELATION TO THE POLICY CYCLE The objectives for research under the auspices of the Fund focused on natural resource management and rural development. This strongly defines its character and not only implies emphasis on the regional and higher spatial levels, rather than on the field and farm level, but also requires nontraditional research. In the standard research procedure, a problem is defined and a hypothesis is formulated that has the potential of ‘‘solving’’ the problem.

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Next, a research process is initiated that produces results within a given time and budget frame that, ideally, allows acceptance of the hypothesis and can be used to ‘‘solve’’ the problem. Consideration of natural resource management and rural development presents a rather diVerent picture. DiVerent stakeholders usually have quite contrasting ideas about management and development. There is not a single ‘‘truth’’! Also, their perception of current and desirable conditions in future varies widely, as they are often inspired by ideological or commercial motivations. There is not a well-defined problem nor one single ‘‘magic’’ solution. The manner in which science should deal with such problems, which are characteristic for all problems of society and certainly not limited to dealing with natural resources, has been studied extensively in the last decades (Bouma, 2005; Castells, 2000; Funtowicz and Ravetz, 1993; Giddens, 1991; Ravetz and Funtowicz, 1999; Van Ittersum et al., 2004; Wenger et al., 2002). There is no question as to the relevance of science in this confusing context: ‘‘true’’ information and an objective evaluation of issues raised are essential in discussions where emotions can run high and where particular interest groups may unduly dominate and monopolize discussions. The general concept of sustainable development is most useful in this context: whatever is being proposed as a way to deal with a given problem, it should balance economic, social, and environmental interests in a manner, acceptable to all or, at least, to a majority of those involved. Defining a series of options that might solve a problem, rather than a single ‘‘magic’’ solution, has turned out to be a profitable way of dealing with the question of solving problems of natural resource management or rural development. Next, a selection has to be made by policymakers in dialogue with stakeholders, from all options presented. This approach is, of course, not new. Scenario analyses have been made by many agencies in the past (e.g., the SHELL oil company in the eighties). As time went by in this project, we have increasingly returned to this approach of defining sustainable options for land use and natural resource management whereby emphasis was paid to defining story lines to make such options more accessible to various users. The Fund contributed to two important elements: (1) Options were geographically defined and visualized by using Geographic Information Systems (GIS). Rather than producing generic tables with data, illustrating eVects of diVerent land-use options, we focused on defining what might happen where and when. This turned out to be particularly interesting for policymakers, planners, and stakeholders alike as it oVered opportunities to introduce spatial diVerentiation when fine-tuning policy measures. (2) Interaction with stakeholders received much emphasis during the entire policy circle, and not only during parts of it. We try to be involved during the entire policy cycle, which includes the following:

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1. The signaling phase in which problems are identified, preferably based on a characterization of current conditions. 2. The design phase in which options for possible corrective action are defined based on research using existing and newly acquired information. 3. The decision phase in which a selection is made by policymakers of options being presented. Here, negotiation processes play an important role. 4. The implementation phase in which the selected option is being realized. 5. The evaluation phase in which the entire process is analyzed in terms of a learning experience. This may have to include new monitoring activities to document achievements. Rather than have a short period of interaction between researchers and stakeholders at some point during the research process (usually during the design phase), we intended to introduce a long, joint-learning process in our projects for the five phases mentioned above, in which tacit knowledge and experience of stakeholders played an important role next to scientific data and information being injected into the debate by scientists. Such data and information are quite diVerent in the various phases: (1) Scientists have a particularly important role in the signaling phase: all ideas should be welcomed but some degree of screening may be needed. This is also the phase where scientists are called on to introduce long-term visions and where there is time for having dreams. (2) When designing diVerent options to solve a given problem, scientists have a major responsibility to make sure that for any option, a primary focus on sustainable development is being maintained. In other words, economic, social, and environmental aspects should always be considered for any option. This is essential for making realistic trade-oVs later between contrasting demands. Action groups, NGOs, and policymakers with particular political signatures often emphasize only one of the three basic aspects of sustainability when defining their favorite option. Scientists, who are neutral, in principle, in terms of their personal preferences, have an important function in keeping track of the overall context of any given problem. (3) Scientists have no role in decision making. They can, however, facilitate the political negotiation process by providing additional information or clarification at the right time and place. (4) Problems always occur when a given plan has to be implemented. Again, scientists have a limited role here to make sure that implementation stays on track by making sure that the original objectives are not forgotten and mistakes or errors are promptly communicated to and openly discussed with the members of the team. The time of interesting, new ideas is over when implementing a plan that has been widely discussed and agreed upon. Of course, conditions can change, but suggestions for continued change of plans may also be suspected

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and may reflect hidden agenda’s of particular participants. More general, it is in the interest of science that at least some shining examples are generated of well executed and successful plans that have followed the policy cycle and that illustrate what science can accomplish. The role of scientists is now often terminated after the decision phase and this is unfortunate because a lot can be learned from implementation and making this part of an overall evaluation process is attractive as part of a learning process that can make research more eVective in future. The schematized policy cycle, as presented here, suggests a rigid sequence of successive phases. This is, of course, not realistic as the various phases may interact while the sequence may occasionally change over time. The cycle is, however, a good metaphor to illustrate diVerent functions that have to be distinguished no matter what in the overall decision-making process: thinking about what should or might be done, defining possible options to solve problems, wondering about who decides what, deciding about implementation plans, and learning from evaluating the processes involved. When dealing with natural resource management and rural development, eVective contact and interaction between governmental agencies, users of the land, and other stakeholders are crucial. If land users are not involved when governmental agencies define new land-use policies or desired forms of management and corresponding rules and regulations, those users are unlikely to implement measures as they are seen as having been imposed from above. On the other hand, policymakers cannot only base their designs, rules, and regulations exclusively on opinions of the land users because broader issues that are beyond scope and expertise of the land users may be important from a national or international policy point of view and have therefore to be taken into account, however unpopular they may be at the time. This is the particular responsibility of policymakers and they have to find ways by which this can be communicated convincingly to the land users. Interaction between land users and policymakers is therefore crucial and here scientists can make unique contributions as mediators and facilitators while at the same time continuously feeding scientific information into the debate. This is, in our view, more fruitful than scientists having exclusive contacts with either land users or policymakers which is often seen in practice. In Section IV, projects of the Fund will be discussed, following the various phases mentioned above. We will describe examples according to the policy cycle, allowing us to illustrate the quite diVerent circumstances that we have encountered in all four continents where projects have been executed. As stated above, only a main story line will be presented here. Detailed reports are presented on the project website (www.ecoregionalfund.com).

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EXAMPLES FROM THE PROJECTS OF THE FUND A. DEVELOPING

THE

KENYAN HIGHLANDS

Hunger and poverty in sub-Saharan Africa have received huge media attention in the 1980s. More recently, they have been emphasized in the formulation of the millennium goals. Although attention was focused on dramatic soil degradation processes—like water erosion and salinization— and extensive droughts, increasingly soil fertility decline was mentioned as one of the key drivers behind the stagnating agricultural production in this part of the world. After studying the low levels of fertilizer use and the declining productivity, FAO commissioned a study to quantify soil nutrient balances for sub-Sahara Africa in 1989. The results showed that soil nutrient losses were significant especially in East Africa with annual per hectare losses exceeding 40 kg N, 7 kg P, and 20 kg K (Stoorvogel and Smaling, 1990; Stoorvogel et al., 1993). It became clear that soil fertility decline may be just as important as some of the other factors of soil degradation. More detailed studies that followed the initial study confirmed the earlier results at more detailed scale levels (De Jager et al., 1998; Smaling et al., 1993). The signal function of these studies was clear, but at the same time the studies did not provide a solution to the problem. Key question that remained was how to deal with the problem? Where do we start and how to intervene? Since the early study, soil nutrient depletion has gained international attention and is often considered to be one of the key causes for stagnating or declining productivity. It is therefore not surprising that it is emphasized in Kenya’s Strategy for Revitalizing Agriculture of 2004. The document provides us, among others, with two possible directions how to intervene: (1) stimulates nutrient inputs through mineral fertilizer and (2) promotes eYcient livestock production systems. The document is, however, not very specific as to how this can be implemented. Although technical solutions at the field level may contribute, it is clear that solutions to this wide scale problem need also to be addressed at higher scale levels. Three diVerent projects supported by the Fund dealt with three diVerent issues: (1) Where do we expect major changes in agricultural land use under diVerent policy scenarios or so-called story lines? (2) What changes in agriculture can we expect under diVerent policy scenarios or technological innovations? and (3) Are the modeled changes realistic options if we evaluate them at the farm level in combination with the specific constraints and objectives of the farmer? Here we will provide an overview on the approaches that have been followed to answer each of these questions. The analysis was focused on the smallholder mixed crop-livestock producers in the Kenyan highlands.

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1.

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Detecting Hot Spots for Change

The Trajectory of Change (TOC) program (see: www.trajectories.org), coordinated by the International Livestock Research Institute, Kenya (ILRI) focused on the determination of hot spots for change. Where do we expect that major changes in land use will take place? The project followed a two-step approach. Intensive stakeholder consultation resulted in the development of various story lines for agricultural development in the Kenyan Highlands. These story lines were next translated into various scenarios representing pathways for development in terms of population density, education, extension services, and specific policy interventions. Two examples are the baseline scenario and the scenario of equitable growth. The baseline scenario mimics the policy, government, and investment environment that has characterized Kenyan agriculture during the 1980s and 1990s. Key features include poorly functioning public institutions for supporting agriculture and market development; market barriers internally and externally, and poor market infrastructure; a policy environment that stifles innovation in both rural and urban economies. The equitable growth scenario mimics the plans put forth in the government’s Economic Recovery Strategy. Key features include well-functioning public institutions for supporting agriculture and market development; reduced market barriers and improved infrastructure, both internally and externally; and a policy environment that facilitates innovation in both rural and urban economies. These two scenarios represent diVerent pathways for development. Under the baseline scenario about 20% of land use in the area is likely to change between 2004 and 2024. Of this change, 9% of the farming systems are projected to turn into less intensified farming systems and 80% of the farming systems will turn into more intensified farming systems of which 53% will shift into export-oriented farming. Under the equitable growth scenario 25% of the area is likely to change in the same period. Only 5% of the farming systems are now projected to turn into less intensified farming systems, and most of the others are likely to change into more intensified systems of which 66% will change into export-oriented farming. The TOC project used the Conversion of Land Use and its EVects (CLUE) model (Verburg et al., 2001) to subsequently analyze where these changes in farming systems are likely to take place. The CLUE model was applied to the Kenyan highlands showing actual land-use patterns and changing patterns that might result from the diVerent scenarios. The CLUE model can do this because it defines critical ‘‘drivers’’ of land-use change which can be used to answer the central question: ‘‘what might happen if?’’ Thus, ‘‘hot spots’’ and ‘‘cold spots’’ of change could be identified for the various scenarios. Figure 1 shows three maps indicating which areas are likely to be subject to change under the two scenarios. A good

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A Kenyan highlands Current situation

B Kenyan highlands Baseline scenario

Legend Subsistence farmers with no dairy Farmers with dairy activities Intensified farmers with no dairy Export-oriented farmers with no dairy Export-oriented farmers with dairy activities

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Towns

Figure 1 Projected land-use change in the Kenyan highlands with the CLUE model: (A) current situation, (B) baseline scenario, and (C) equitable growth scenario.

example of a hot spot is the Machakos district (southeastern corner of the study area). Under the Baseline scenario many intensified farmers are going back to subsistence farming whereas under the equitable growth scenario many farmers that are currently subsistence will intensify their farming system. In other parts of the Kenyan highlands changes are less pronounced. The procedures that were followed in the TOC project were very attractive to get the message out. First, the results were visualized using the linkage

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with a GIS model allowing users to see the spatial patterns in the outcomes. Second, the story lines were jointly defined with the various stakeholders. Recognition of story lines and the user-friendly visualization allow for eVective communication to the various stakeholders. On the other hand, we have to realize that the farming systems as they have been defined in the analysis are not static and even farming systems staying in the same category will undergo changes. The consequences of the two story lines on, for example, soil degradation and poverty alleviation require, therefore, more detailed studies.

2.

Trade-offs in Agricultural Development

The CLUE model results show that under the two story lines Machakos is expected to undergo significant land-use changes. The Machakos district is famous for land-use changes through the publication of TiVen et al. (1994): ‘‘More People, Less Erosion.’’ They present Machakos as the miracle case where, despite increasing population density, soil erosion has been stopped through massive introduction of terraces. Today the future of Machakos agriculture is less bright as soil fertility decline seriously threatens the sustainability of the systems; a reason for some researchers to revisit the study by TiVen et al. (Siedenburg, 2006). The CLUE analysis in the TOC program indicates the Machakos study area as a hot spot for land-use change where under the various scenarios farming systems are likely to develop into producing export cash crops with limited dairy activities. Interesting enough, there has already been a significant expansion of zero-grazing units in the area; although many farmers lost their dairy cattle during the recent drought. The Machakos district is well studied in the past. In the last decade various surveys have been carried out to describe farm management and to assess the dynamics in soil fertility (De Jager et al., 1998, 2001). The Trade-oV Analysis (TOA) project funded by the Fund in combination with the Soil Management Collaborative Research Support Program of US-AID and headed by Wageningen University and Montana State University took up the challenge to carry out an integrated assessment of the farming systems in Machakos using available survey data from the various Nutrient Modeling for Tropical Farming Systems (NUTMON) studies. Through econometric estimation techniques the land-use decision process of the farmers was modeled where land-use decisions are a function of expected productivities, price distributions, and resource availability. The TOA system (Stoorvogel et al., 2004a,b) uses these models for a quantitative assessment of various interventions in terms of mutual ‘‘trade-oVs’’ between economic, social, and environmental indicators. The analysis allows for an ex ante evaluation of technology and policy interventions.

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Although a plethora of diVerent scenarios can be presented, we will have a more detailed look at the eVect of the two interventions proposed in Kenya’s strategy to reduce poverty through improved soil nutrient management. First of all, they propose the reduction of fertilizer prizes. Currently, farm gate prices of fertilizer are far above the world market prices due to transaction costs (import tariVs, transportation costs, and retailer). These high prices are commonly perceived to be one of the key reasons behind low fertilizer use by farmers (De Jager et al., 2001; Salasya, 2005). Fertilizer prices can be reduced through various interventions including the development of eYcient marketing chains or packaging smaller quantities. A second example is the intensification of the livestock production which should improve the nutrient eYciency through better recycling of nutrients on the farm. This can be done through, for example, improved zero-grazing units on farms and an increase in manure use. Figure 2 shows the main eVects of these two scenarios on the two key indicators for the Machakos district: soil nitrogen depletion and poverty, that is, the number of people below the poverty line of US$1 per person per day. The reduction of fertilizer prices clearly is a win–win situation (although at the cost of the investments needed to reduce these prices!). Both the poverty index as well as the nitrogen depletion rate are going down. On the other hand, we see that increasing manure production negatively influences the soil nitrogen balance. This may seem rather counterintuitive. The reason for this change are the underlying processes that link manure availability and manure use to the production of maize. In other words, if we stimulate manure use, we will also stimulate the cultivation of maize. Maize is one of the more depleting

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ECOREGIONAL RESEARCH FOR DEVELOPMENT Change in poverty (%) −63 to −54 −54 to −46 −46 to −36 −38 to −29 −29 to −21 −21 to −13 −13 to −4 −4 to 4 4 to 13 No data

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Figure 3 Changes in soil nutrient depletion (in kg ha
1 year
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crops and, as a result, an increase in maize results in a more negative soil nutrient balance. Machakos district is a highly variable region with a wide range in diVerent agroecological conditions. As a result one can wonder whether these conclusions are actually valid throughout Machakos district. The maps presented in Fig. 3 show the impact of the manure scenario on the poverty index and the soil nutrient balance (under the observed fertilizer price regime). The maps show that the impact of the scenario is also highly variable within the district and this underlines the need for the georeferenced analysis and presentation of the scenario results.

3.

Verifying the Feasibility

The Kenyan Highlands story is completed by the Integrated Modeling Platform for Mixed Crop-Animal Systems (IMPACT) model (Herrero et al., 2005) that models individual farming systems. CLUE simulations tell us where agricultural land use is going to change and model simulations make selections among various discrete farming systems, each with a dynamic character. In a more detailed analysis we see the TOA system modeling the various management decisions at the farm level. By modeling the various decisions at the farm level one can wonder whether the simulated system is realistic and whether all the boundary conditions in terms of, for example, feed availability are met. It is therefore extremely useful to take the assumptions for the various simulation

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runs as well as the simulation results to an analysis at the farm level. The IMPACT model is used to check whether the various options for farming systems by CLUE are realistic. At the same time IMPACT is used to check whether results of the TOA can be applied to farming systems in the area and if not, how they can be modified. In Sections IV.A.1 and IV.A.2, we looked at the potential changes in farming systems in the African highlands. We identified the Machakos region as one in which we can expect significant changes. Two alternative scenarios were subsequently analyzed representing commonly believed perceptions that fertilizer prices have to be lowered for farmers to make adequate use of this essential input and more intensive livestock management is required to streamline nutrient flows within the farm through eVective nutrient recycling. The farming systems in Machakos are highly complex with numerous crops grown on a single field, among them, fodder crops, and with significant interactions between the various farm components, that is, the cropped fields, livestock, zero-grazing units, stocks, and the household. The IMPACT model enabled us to analyze these complex interactions and to put the model results in perspective. Increased fertilizer use may not resolve the soil nutrient balance directly but the increased production of crop residues that may be fed to the animals (leading to increased manure production) or incorporated in the soil may support a more sustainable use of the soil resource. These IMPACT studies help us to interpret the results that we obtain with the TOA system, but it also helps us to define specific scenarios that are realistic and in line with farmers objectives. The highly detailed surveys for the IMPACT model, where few farms are monitored for a longer period, also provide insight in the core objectives and constraints of the farmer managing his enterprise. These objectives and constraints form the basis for looking for alternative management practices and the most eVective policy interventions. Subsequently, these practices and interventions can be evaluated again using the TOA model to assess the impact at another scale level.

4.

In Retrospect

All in all, we see three models operating at three spatial scales and interacting in defining most promising agricultural land-use systems in future. In doing so, there are intensive contacts with both policymakers and farmers to generate the most appropriate options, trade-oVs, and farming systems. Local research institutes, such as Kenya Agricultural Research Institute (KARI), guide research and are assisted by ILRI and Wageningen and Montana Universities. Courses are organized to transfer and discuss technologies. This arrangement comes close to what the Fund was intended to do.

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The case study clearly shows the added value of the research chain where diVerent research methods are used in combination to answer the complex questions by policymakers and to streamline research activities. CLUE helped us to identify regions where changes are likely to take place and to focus data-intensive methods like the TOA. The IMPACT model allows for the definition of various scenarios to be analyzed with the TOA and to interpret and check the subsequent results. The Kenyan Highlands project is still in the design phase. Policy decisions have not yet been made and implementation is not yet relevant, except for educational programs familiarizing farmers, policymakers, and local researchers with the new tools in a joint-learning mode.

B. REACTING TO TRADE LIBERALIZATION The explosion of free trade agreements (FTAs) has marked the last decade. This seems to be the norm for a country to have a full membership in a globalized world, in spite of the criticisms from grassroots organizations and environmentalists, among others. Small countries like Panama receive a lot of pressure to sign FTAs with more powerful nations, oftentimes putting their food security at stake.

1.

Signaling Phase

Sprouted by an invited conference given by the International Potato Center (CIP) in September 2000 at the occasion of the 25th anniversary of the Panamanian Institute for Agriculture and Livestock Research (IDIAP), the minister of Agriculture invited CIP again in January 2002, through IDIAP, to become familiar with the advances in ecoregional research. After the exchange, the minister highlighted the new challenges faced by the agricultural sector under the FTAs the Panamanian Government was negotiating and their possible impacts on farmers. His plan was to get funding from the Central Government for IDIAP to start using the tools and methods available, with backstopping from CIP and partners. The key question was ‘‘What can the Panamanian government do to help farmers to compete under the new rules of globalized markets?’’ Even though money was set aside by the Central Government and CIP’s DG traveled to Panama to agree on terms and conditions, a new minister was appointed and the funding was assigned elsewhere. In spite of the lack of Government funding, Panamanian institutions— IDIAP, ministries, particularly agriculture and health, cooperatives,

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the private sector, and NGOs—complemented the seed funds provided by the Ecoregional Fund to initiate the research in a pilot site. One of the most important watersheds in the country, the Chiriquı´ Viejo, was selected. The upper watershed is encroached in a natural park containing the main forest reserve to produce clean water for the province of Chiriquı´. The first part of the signaling phase was completed. The problems to be addressed were identified. On the one hand, there are international pressures to sign FTAs, notwithstanding the unpreparedness of the sector involved, in this particular case the agricultural. On the other hand, environmentalists defend the role the upper watershed plays as clean water provider. Stakeholders from diVerent sectors agreed to work together and use the experience as a hands-on learning process. The characterization of the current conditions was taken as the next challenge. The experience gained by CIP and the University of British Columbia, in a comparative watershed analysis between the Andes and the Himalayas, was instrumental. Ten hypermedia CD-ROMs from these studies were presented and made available to all stakeholders. The friendliness of the format and the richness of the contents caught the attention of all the participants. Seeing how much can be accomplished when data is shared and how all the participating institutions can claim ownership of the product was appealing. The way geospatial data is combined with table, texts, numbers, and pictures was highlighted as a key attribute of the products. The experience gained in Phase 1 of The Fund was also shared; the Ecuadorian CDROM contained the findings of Phase 1 in El Carchi, Ecuador. The first few versions of the Chiriquı´ Viejo Watershed CD-ROM were assembled with the data provided by those who wanted to share plus the maps belonging to the public domain, processed under CIP’s leadership. The advances were presented at the coordination meetings, led by IDIAP and the private sector. Those institutions reluctant to share at the beginning soon realized that it was better to have their logo included as participating institution than being left out in the process. Soil fertility layers were constructed for the Chiriquı´ Viejo Watershed. Samples analyzed by IDIAP from the last 30 years were georeferenced and used to interpolate the attributes into the following thematic maps: texture, organic matter, pH, CEC (cation exchange capacity), Al saturation, P, K, Ca, Mg, Zn, Cu, Fe, and Mn. The results were combined with other thematic attributes such as topographic variables, accessibility to markets, and climatic variables. Principal component analysis was used to reduce the redundancy of information in the variables, followed by a clustering procedure using the maximum likelihood rule. Six agroecological zones (AEZ) were defined (Fig. 4). AEZ 1 is a coastal area with potential for intensive agriculture (e.g., banana, sugar cane, and beef cattle). AEZ 2 is also in the lowlands and suitable for maize, rice,

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Figure 4 Agroecological zones in the Chiriquı´ Viejo Watershed, Panama.

sorghum, tropical fruits, and livestock production. AEZs 3 and 4 are located at intermediate altitudes. The most striking diVerences between these two zones are the rainfall and the topography. AEZ 3 presents rainfall above 5000 mm year
1 and beef cattle and some dairy cattle are feasible. AEZ 4 is suitable for bean production, some maize, and beef cattle. AEZ 5 is a special niche for gourmet coVee and AEZ 6 is the horticultural area. AEZs 3, 5, and 6 are the water towers of the province of Chiriquı´, the most important agricultural area of the country. During the last 40 years, the forests were drastically reduced from 78% to less than 40% of the total cover,

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and substituted by horticultural crops and pastures. Large, nonarable areas have been planted making the zone and the water towers highly vulnerable.

2.

Design Phase

The agricultural sector is greatly concerned with the FTA trade implications, particularly those aVecting resource-poor farmers. The project helped local partners to identify hotspots, assess the vulnerability of the farming systems in the project area, and systematize research results into simulation models to ex ante assess the impact of technology adoption on the competitiveness of three selected commodities in a liberalized market. The analysis was complemented with the assessment of the environmental cost in term of soil erosion and water quality, both under actual practices and future scenarios. Crop and livestock process-based models were used to systematize historical research findings prior to the upscaling of results to the watershed level. A strong component of the project was the training of local professionals in the use of systems analysis and ecoregional methods. For the last 40 years, the Government of Panama has invested in pasture and livestock research. The project focused on systematizing research findings into the LIFE-SIM models (Leo´n-Velarde et al., 2006) to calibrate them and teaching local researchers how to use these tools to complement their research. The models proved robust in predicting beef and dairy production by grazing and stalled animals and combined feeding strategies (Fig. 5). Simulated experiments were run to assess alternative feeding strategies, the incorporation of legumes into grasslands, determination of optimal stocking rates, and so on. Response surface designs were used to find optimal combination of management strategies (Leo´n-Velarde and Quiroz, 1999) simulating FTA scenarios. Although the process-based models used adequately simulated results from field research, the scaling up of the scenarios for the entire watershed was still a challenge. To model livestock production, time series of vegetation indexes were converted into available green dry matter (Jongschaap and Quiroz, 2000; Quiroz et al., 2000). The quality of the pasture and grasslands was already determined by IDIAP. A geospatial version of the LIFE-SIM (simulating pixel by pixel) was used to estimate beef or milk production from the pasture lands in the watershed. The analysis produced by the animal scientists with the newly adopted simulation tools indicated that with the adoption of IDIAP’s technology, particularly the utilization of mixed grass–legume pastures, farmers can produce beef at a cost nearing US$0.80 kg
1 and an internal rate of return of near 25%. In short, the Chiriquı´ Viejo Watershed can produce beef at

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competitive prices in a globalized market, not only for the national but for the export markets as well. The lowlands do not seem to be competitive in milk production, but the upper watershed, if reconverted to a grazing-based grasslegume pasture can compete to retain the national market. Actual production cost per kilogram of milk is around US$0.24. Farmers are profiting since they currently receive up to US$0.31 kg
1 of liquid milk. Prices in countries that have already signed an FTA, such as Chile, have fallen as low as US$0.15 kg
1. Production costs per kilogram of milk under grazing conditions could fall to less than US$0.10. The reconversion, due to costly equipment, elite breeds, and high-tech milking parlors, would be costly. Simulating livestock production and calculating gross margin at the expected prices under an FTA scenario highlighted the areas in the watershed where the livestock sector could compete under an FTA with the United States or other countries. Gross margins ($ ha
1) ranged from 1100 to 1300 and from 1400 to 1900 for dairy and beef production, respectively. CIP has supported potato research in Panama since the research program started. Varieties released by IDIAP come from genetic material originated at CIP. Potato models calibrated for CIP materials (Bowen et al., 1999) were used to assess management strategies under FTA scenarios (Fig. 2). For the spatial simulation, soil and climate data are required on a pixel by pixel basis. The fertility data came from the interpolated maps described above. For the temperature, split windows algorithm using remotely sensed data (Pozo Va´squez et al., 1997) are used. Rainfall data using traditional geospatial methods (Immerzeel et al., 2005) did not provide the accuracy needed. A new method developed within the project was used. Daily rainfall data from local weather stations were jointly analyzed with a dataset containing 197 ten-day composite normalized diVerence vegetation index (NDVI) images derived from the SPOT-4 and -5 VEGETATION instruments. The periodical behavior of the two signals (frequency, periodicity, and amplitude) was performed using the Fourier transform [F( f )]: Z Fð f Þ ¼

1
1

f ðtÞe
i2pft dt;

where f(t) is the signal and t the time when data was collected. The ratio of the mean value of the two signals or characteristic amplitude was used to bring both signals to the same scale. The lag between the phases of the two signals was also determined and corrected. As a result, a signal with similar scale and phases was obtained. This new signal was processed with the wavelet transform [Wf(l, u)] of the signal f(t):

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Z Wf ðl; uÞ ¼

279

1 t
u f ðtÞ pffiffiffi c dudt l l
1 1

where cl,t(u) is the mother wavelet, l represents the scale factor which is related to the frequency, and u represents the translation associated with time. Both signals (rainfall and NDVI), measured at the pixel corresponding to the weather station, were decomposed twice (second level decomposition) using the Wavelet Symmlet2, a high frequency filter. The two spectra obtained for each signal—low frequency (base) and high frequency (noise)—were used in the reconstruction. The ‘‘base’’ signals, for each pixel diVerent from the ones where the weather stations were located, were combined with the ‘‘noise’’ extracted from the rainfall signal from the respective weather station, to reconstruct the daily rainfall for each pixel in the target area. The validation of this method produced coeYcients of determination (R2) ranging from 0.71 to 0.85. This fit is higher than the ones reported in the literature for daily rainfall (Immerzeel et al., 2005). A modified LINTUL-potato model coupled to GIS software was then used to simulate potato production. Local researchers and the private sector determined—based on their research findings and modeling alternative scenarios—that to retain the national potato market, farmers must produce at least 35 ton ha
1 at a maximum cost of US$0.16 kg
1. The agroecological conditions are mainly suitable during the dry season. During the rainy season, the presence of pests and diseases increases not only the cost but also the negative eVect on the environment. In the past, IDIAP evaluated CIP materials tolerant to late blight, but farmers did not like them because they produced too much foliage and were long-cycle (late) cultivars. Could it be that the new rules of the game will provide room for these types of materials that minimize the use of chemicals? Overall, potato/horticulture farmers do not seem to be competitive without tariVs given the size of operation and the excessive presence of pests and diseases, typical of tropical highlands. 3.

What Is the Cost?

In Section IV.B.2, we described how research combined with decision support tools could be used to ex ante assess competitiveness of key commodities under FTA scenarios. We also indicated—based on simple economic analysis—that with the adoption of the technologies promoted by IDIAP and MIDA the beef and dairy small farmers could profit even if prices decrease due to FTAs. On the other hand, potato farmers would have more diYculty under such conditions; they require some protection from the central government. According to a recent oYcial presentation, potato and other horticultural crops are classified as sensitive commodities. It is highly likely to get a grace period with tariV protection.

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The analysis in the upper watershed of Rı´o Chiriquı´ Viejo went beyond the cost–benefit analysis. An attempt was made to quantify some of the ecological costs of maintaining the ‘‘status quo.’’ Horticultural production poses two potential environmental problems: soil erosion and chemical leaching. Most of the erosion comes from the areas nonsuitable for cropping such as steep slopes. The Soil and Water Assessment Tool (SWAT), developed by USDA, was calibrated with field data and used to assess alternative land uses. By converting the hillsides into pasture for milk production or practicing conservation agriculture, the level of erosion in the entire upper watershed can be reduced to tolerable levels (Fig. 6). This is a nonattractive business for farmers because they can make around US$2000 ha
1 year
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1 year
1 in horticulture, at actual prices. This reconversion could be suitable under a no-tariV FTA scenario because expected revenues from horticulture are calculated to decrease to less than US$3000 ha
1 year
1. An additional possibility is for farmers to receive a premium for producing clean water. This might be an issue of importance in the near future since the government is interested in increasing the number of hydropower plants in the country and river has been selected as a good candidate. The second environmental issue presented for horticultural production is carbofuran leaching. The levels estimated at the outlet of each subbasin are, by EPA standards, above the permissible levels. Integrated Pest Management (IPM) can reduce substantially the levels of carbofuran in the river. Additional reductions can be obtained by reconverting the hillsides into pasture (Fig. 7). Several policy scenarios were analyzed using the minimum data TOA model (Antle and Valdivia, 2006), for example, giving a premium price for IPM products. Even though this type of policy showed to be attractive in terms of expected adoption with minor increments in premium prices, local decision makers do not see this as a feasible policy under an FTA environment. The analysis was then centered on the production of environmental services. The trade-oV curves shown in Fig. 5 illustrate that small incentives to farmers per kilogram of active ingredient reduced could induce adoption of IPM and reconversion of hillsides into pasture thus producing a substantial reduction in carbofuran in the river. Expected adoption rates seem to be high. One partner in the alliance made a study on water consumers’ perceptions and their willingness to pay for water services. Users are willing to pay additional US$0.04–$0.08 month
1 to guarantee a good quality of drinking water.

4. Lessons Learned Several lessons were learned in this experience. The first one was how diYcult it is to engage decision makers in countries with high political turnover rates. Second, it is better to work with more permanent professionals

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in spite of the fact that they are not at the top of the decision-making pyramid: the message gets across and remains within the institution. Third, having something to show for at the onset of the project, based on previous experience, makes the diVerence and allows the proactive approach followed by CIP. Hypermedia CD-ROMs provide user-friendly interfaces to promote ecoregional tools and methods. Fourth, robust process-based models capable of predicting research results are good entry points to attract researchers’ attention and, once validated, constitute a solid base for geospatial analyses. Fifth, presenting land-use alternatives and the expected impact on income and environment seems to be attractive for policymakers, but it also imposes a higher demand on quantitative thinking to define scenarios and to interpret a large set of options. These tools are seen as a threat to a few conventional policymakers and even advisors using traditional methods. A continuous eVort is needed to demonstrate the eVective use of these techniques. Sixth, the process is outstanding to build permanent R&D partnerships. The process has now reached the decision phase where input by research is limited and restricted to further explaining the various scenarios and their implications. Once decisions have been made, research has again a function during implementation because unexpected developments are likely to take place requiring additional analyses but now in a defined context. The eVective partnership between CIP and IDIAP, based on a concerted mutual eVort, forms an excellent basis for further activities by IDIAP. The Ministry of Agriculture has already assigned funds to IDIAP to conduct similar analyses in five important watersheds in the country. The Panama Canal Authority is holding meetings with IDIAP to conduct a similar study in the Panama Canal Watershed. FAO is interested in cofinancing CIP’s and Montana State University’s backstopping to IDIAP to look into options for payment for environmental services in the canal watershed.

C. SIGNALING CONSTRAINTS IN SUSTAINABLE USE OF WATER RESOURCES ON THE TIBETAN PLATEAU 1.

The Tibetan Plateau

The Tibetan plateau is located in the southwestern part of China and covers an area of 1.2 million km2. The elevation ranges from 400 m above sea level (m.a.s.l.) to the summit of Mt. Everest (8848 m.a.s.l) with an average altitude of over 4000 m (Fig. 8). Tibet is considered the water tower of Asia and rivers originating in Tibet flow into various regions in Asia. The Mekong, the Yellow river, the Yangtze, the Brahmaputra, the Indus, and the Karnali all originate on the Tibetan plateau and support hundreds of millions of people downstream.

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Since Asia is monsoon dominated, with precipitation concentrated in just a few months, the perennial flow of the rivers largely relies on the constant flux of the glaciers in Tibet. As the pressure on Tibet’s water resources is mounting because of rapid economic development, its conservation becomes ever more important. Population growth, increased incomes, and urbanization have joined forces and agriculture cannot keep up with the increasing demands of this emerging, new society (Ecoregional Fund, 2005). Yields are restricted by a short growing season, large diurnal temperature ranges, and above all a shortage of water. Annual precipitation is only 600 mm and is concentrated in the monsoon months July and August (Immerzeel, 2005). The proportion of arable land is only 0.3% of the total land area and more than 60% of this land is arid and has a low productivity. Gaps between actual and potential yields of the main crops barley and wheat are very large and this is caused by a poorly developed irrigation infrastructure (Tashi et al., 2002). Increasing the irrigated acreage and promoting new technologies, such as greenhouse horticulture, are the only answer to sustain the increased demand for more and diverse products (Immerzeel, 2005). Climate change is another major threat to the future of Tibet’s water resources. Widespread accelerated glacier retreat and shifts in stream flow timing, from spring to winter, are likely to be associated with climate change (Houghton et al., 2001). There are serious concerns about the alarming rate of retreat of Himalayan glaciers. It has been predicted that the coverage of glaciers in western China, accounting for up to 70% of the Himalayan glaciers, will decrease by 27% by 2050 (Qin, 2002). In the short run, the glacier melt may increase water availability but also major waterborne disasters are likely. Rapid accumulation of water in glacial lakes can lead to a sudden breaching of the unstable ‘‘dam’’ behind which they have formed. The resultant discharges of huge amounts of water and debris—a glacial lake outburst flood (GLOF)—often have catastrophic eVects to people, both upstream and downstream. In the long term fresh water shortages could cause severe problems for the livelihoods of the mountain people. Changes in timing and available volume of water available for irrigation will threaten agricultural productivity (Houghton et al., 2001) and will impact heavily on the economy of the region (Matthews et al., 1995). The ability to feed the growing population, a significant number of which already undernourished at this time, is being threatened (FAO, 1999; UNICEF, 1999).

2.

Research in Mountainous Areas

Mountainous regions globally are considered ‘‘the blackest of black boxes in the hydrological cycle’’ with respect to data availability and understanding (Klemes, 1988). The Ecoregional Fund has acknowledged the importance of

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applied research in mountain ecosystems by funding the development of a comprehensive geospatial database on natural resources in six Himalayan countries by the International Centre for Integrated Mountain Development (ICIMOD, 2003). The Fund decided on a follow-up activity to harness the potential of this approach in a Tibet case study. Ecoregional analysis, which aims at linking multiple scientific disciplines with the policymaking process, is a pristine area in Tibet. A traditional, highly hierarchical scientific structure, lack of data, known and unknown political sensitivities, and the sheer physical inaccessibility of the area led to a challenging starting point. Tibet, however, is also the ultimate laboratory to show what role science can play in signaling potentially large problems to policymakers, using modern technologies to overcome insurmountable obstacles that would be found when traditional technologies, based on field surveys only, would be available.

3.

The Case Study

The case study operated on two scales. First, the Tibetan plateau as a whole was studied. Lack of data on local precipitation, which is essential to assess agricultural potential, required the development of a new technique to derive such data from available remote sensing satellite data. A relationship was quantified between precipitation and the NDVI (Tucker, 1979) derived from satellite imagery. In data scarce environments time series analysis of remotely sensed NDVI data can provide valuable information when assessing spatially defined linkages between climate properties, vegetative phenological cycles, and rain fed land use. The Tibetan plateau is characterized by harsh climatic conditions, and food production is mainly depending on fragile rangelands and (irrigated) crop production systems. Annual rainfall and temperature are the dominant determinants in ensuring food security in this sensitive landscape. Only local data are available at this time and only for short periods (Tashi et al., 2002). The high temporal resolution and the up to date character of the NDVI imagery enables and facilitates prediction and spatial interpolation of climate parameters. The research provided insight into the complexity of relating NDVI-derived parameters (NDVI increments between consecutive 10-day periods) to precipitation and land use. Harmonic analysis (the Fast Fourier transform) was applied to correct the NDVI time series for noise. Regression analysis with 15 meteorological stations has shown that the total amount of precipitation during the growing season exhibits a strong relationship with NDVI-derived parameters (R2 = 0.72). Interannual NDVI variation based on Fourier transformed time series was studied and when linked to food production it can provide a robust early warning system, since very early in the season the expected weather conditions of the upcoming

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season can already be predicted. It was concluded that harmonic analysis clearly has added value over the analysis of original NDVI time series which are disturbed by atmospheric noise, sensor instability, or orbit deviations (Immerzeel et al., 2005). This study clearly demonstrates how modern techniques, such as remote sensing by satellites, can rapidly fill critical data gaps that could never be filled with traditional monitoring studies which would be far too costly and would take far too long to implement. The study also shows that cutting-edge research, publishable in the international literature, can be based on questions raised in the context of developmentoriented work. When used in a broader policy analysis, as was done here, the value of such data is much higher than when it is published as a technical study as such. The second part of the project focused on a specific watershed. The hydrological model SWAT (Neitsch et al., 2001) can be used to quantify eVects of land-use change and specifically eVects of intensification of agriculture, on water resources downstream. The selected site was a small watershed about 40 km northwest of the capital city Lhasa (Fig. 8). SWAT applies a process-based approach to hydrological modeling and is designed to predict the impact of diVerent land management practices on water quality and quantity over long periods in large complex watersheds with highly variable conditions. Using public domain data and limited locally available data on elevation, land use, soils, meteorology, and farming practices a base model was built for the watershed. The steep slopes, shallow and sandy soils and a short growing season resulted in low yields for the main crops cultivated (0.7–1.7 ton ha
1). Surprisingly at first sight, the analyses show that increasing irrigation did not result in significantly higher yields because the physical conditions do not allow water to be retained in the root zone of the soils and is therefore not available to plants for evaporation (Immerzeel, 2005). Figure 9 shows the average annual water balance of the watershed from 2000 to 2003. The watershed receives an average amount of 617 mm of precipitation and 28 mm of irrigation. The amount of irrigation water in the watershed water balance is relatively small since only a proportion of the watershed is arable. Of this 645 mm of water that enters the watershed only 390 mm evapotranspires, a small amount considering a potential evapotranspiration of nearly 1000 mm year
1. Due to the steep slopes in the watershed a considerable amount of precipitation is lost due to runoV (97 mm). Only if significant soil conservation measures would be introduced (e.g., terracing, strip cropping, contour tillage), the runoV can be reduced and made available to plants for transpiration. At the same time the sandy and shallow soils with high hydraulic conductivities result in a low water retention capacity of the soil. The result on the water balance is evident; percolation to the shallow aquifer is 110 mm, of which 99 mm is diverted back to the river as return

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Figure 9 Average annual water balance based on data from 2000 to 2003 derived with the SWAT model with data from 2000 to 2003. (P, precipitation; I, irrigation; ET, actual evapotranspiration; R, surface runoV; IN, infiltration; CR, capillary rise; PC, percolation; QL, subsurface flow; RF, return flow; RC, recharge to deep aquifer; DS, change in storage.)

flow, and subsurface flow to the river is 49 mm. In other words, the steep slopes, sandy and shallow soils, and high potential evaporation result in unfavorable conditions for cost-eVectively increasing agricultural yields. Since many similar watersheds are found across the plateau, it could mean that the overall potential for irrigation improvement in Tibet might very well be much lower than planners and developers think. This is a highly significant and new insight at this time, with profound policy implications. Investments in irrigation will only pay oV in a few high potential areas. In other areas investments are likely to be wasted. On the basis of this type of exploratory research, the potential for both crop and livestock production should be explored through further research in other areas. Only such work will provide a rational basis for a regional dialogue as to how regional development and

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the associated water use can be fine-tuned to allow agricultural development in potentially successful areas only, avoiding unproductive water losses elsewhere and allowing downstream users to maintain access to clean water resources in future.

4.

Discussion and Conclusions

The objective of the project was to acquire insight into the issues related to the water tower function of Tibet and to signal these issues to policymakers. The case study did not completely succeed in the latter objective for several reasons. First, the site selected for field research turned out to have been chosen more for its accessibility from the capital city than for its representativeness. Tibet’s most productive agriculture is located not to the northwest of Lhasa but well to its west, on the plains near the plateau’s two other major cities, Shigatse and Ghyamtse (Fig. 8). Soils here are deep and relatively fertile, so the potential for irrigation and eYcient water use is much higher there. The reported study provides the data to support this diVerent focus. A second, and related, limitation was that the study did not succeed in meeting its major aim of attracting the attention of policymakers. Partly because the location is not recognized as strategically important, but there are also cultural and political factors at work here. Issue-driven applied science is not yet valued highly as a basis for decision making in China. Researchers are not used yet to engage policymakers in their work by showing their results and its implications which are rather dramatic in this particular case. In time, also here a more proactive attitude by researchers is required but at this time this is contrary to the established hierarchical customs. Further complicating factors are Tibet’s status as an outlying region, remote from the center of power, and its limited capacity for local research. Local scientists who are well educated and proficient in English tend to climb the career ladder quickly, escaping the relative tranquility of Lhasa for a more challenging position elsewhere. There could also be a deeper reason why policymakers showed so little interest in the study. China is intent on harnessing Tibet’s water for its own uses and might not welcome a reminder that these resources should be shared with other countries—or that environmental concerns should curb its headlong rush for development. China’s flag should not be the only one on the water tower, but its government may be reluctant to acknowledge this. Despite these limitations, the Tibet study successfully demonstrated the potential of modeling tools to ‘‘open windows’’ onto prospects not previously viewed by policymakers. The future of Tibet’s water tower is a new issue on which almost no research has yet been done. Although this project did not draw an immediate response from policymakers, it aVorded a glimpse of a problem

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that is bound to clamor for increased attention in years to come. In short, it was good signaling, even if no one is yet heeding the signals.

D. MULTIPLE GOALS 1.

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Using Systems Analysis to Study Pressing Land-Use Problems

During the early 1990s, post-Green Revolution issues, such as stagnating crop yields in Haryana and Punjab in India and environmental degradation in Haryana, Ilocos Norte in the Philippines, and Can Tho in Vietnam, were seen as major problems by Local Government Units (LGUs) and National Agricultural Research Systems (NARS) in the various regions of the humid and semihumid (sub)tropics. Environmental degradation was mainly the result of crop diversification and excessive use of irrigation and agrochemicals in rice-based cropping systems. NARS scientists realized the need for interdisciplinary approaches to allow the necessary integrative studies on agricultural development and land use. They were, however, not equipped to perform such studies and contacts were established with the IRRI, asking for support. In response, the Systems Research Network for Ecoregional Land Use Planning in Support of Natural Resource Management in Tropical Asia (SYSNET) program was established in 1996, the first project to be funded by the Ecoregional Methodology Fund and, in retrospect, one of the very successful ones (see also ISNAR, 2004). Issues at stake in rice-based ecosystems of the (sub)humid tropics of Asia are complex. Increased yields do not necessarily imply higher farm income, which is the primary driver for rural development. Intensification of agricultural practices may have quite adverse eVects on environmental quality and these have to be considered when defining alternative land management practices. To make such complex issues more transparent and to allow generation of quantitative trade-oVs between economic, social, and environmental considerations at the regional level, SYSNET developed the Land Use Planning and Analysis System (LUPAS) (Hoanh et al., 1998). LUPAS was applied and evaluated in four regions of Southeast Asia: Haryana State (India), Ilocos Norte Province (Philippines), Kedah-Perlis Region (Malaysia), and Can Tho Province (Vietnam). LUPAS is a modeling framework using interactive multiple goal linear programing as the integrative component to generate potential land uses in a given region that correspond with best solutions for certain political scenarios, each one considering a characteristic mix of economic, social, and environmental aspects as well as technological developments (Roetter et al., 2005). LUPAS shows potential land-use patterns and is not based on current land use, there by allowing a fresh look at possibilities. LUPAS presents land-use maps with geographically defined results of diVerent politically inspired scenarios.

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Thus, LUPAS can deliver important input into all phases of the policy debate. While the strength of LUPAS lies particularly in supporting the signaling and design phase (Van Ittersum et al., 2004), it is also very useful in the decision phase. Using modern (web based) technology, it allows rapid generation of maps in response to stakeholders’ assumptions once the underlying database is available. Also, now that LUPAS is available on the web, accessibility of the methodology is no longer a problem. An illustration of the methodology will now be presented for a province in the Philippines.

2.

An Illustration for Ilocos Norte Province, The Philippines

The LUPAS model for exploratory land-use scenario analysis developed for Ilocos Norte Province maximizes a selection of development goals subject to constraints on land, water and labor resources, agricultural technology, and local demand for agricultural products. Data on resource availability and local demand have been assembled and adapted from a number of secondary sources. The total area available for agriculture for the year 2010 was estimated at 119,850 ha (assuming an overall land-use conversion rate of 7% from agriculture to nonagricultural uses) (Roetter et al., 2000). This area was divided into a total of 200 relatively uniform land units by overlaying biophysical characteristics (irrigated areas, annual rainfall and distribution, slope, and soil texture) and administrative units, comprising 22 municipalities and 1 township. Provincial demand for agricultural products was assessed on the basis of information on per capita demand and projected population from the Provincial Planning OYce. The demand for rice was estimated at 112,610 ton. Labor force and irrigation water were quantified per month and per land unit and month, respectively, based on census data and hydrological data (rainfall, ground, and surface water) from the province and trend projections. Details on the procedures applied to assess resource availability and constraints have been described by Roetter et al. (2000, 2005). The cropping systems or so-called land-use types (LUTs) are selected on the basis of farm surveys and composed of (1) single cropping: root crops, sugarcane, and rice followed by fallow; (2) double cropping: two rice crops, rice in rotation with (yellow or white) corn, garlic, mungbean, peanuts, tomato, tobacco, cotton, potato, onion, sweet pepper, eggplant, and vegetables; and (3) triple cropping: three rice crops, rice in rotation with garlic and mungbean, with (white or yellow) corn and mungbean, and with water melon and mungbean. The basic scenarios analyzed, based on intensive consultations and discussions with stakeholders (Roetter et al., 2000) and after having explored the biophysical potential of the province, were: (1) emphasis on increasing

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farmers’ income, while meeting minimum demands for rice and some selected other crops, and taking into account current water and labor constraints, (2) emphasis on rice production meeting minimum demands for rice and some selected other crops, and taking into account current resource constraints. In further stakeholder discussions it became obvious that most interest groups do not regard rice production (though important) a promising future perspective for Ilocos Norte but rather a variety of other agricultural and tourism activities. These discussions led to examine the possible impact of R&D targeted at knowledge-intensive technologies. For this, 3 variants (or subscenarios) to scenario 1 were analyzed (Table I). The aim was to look at the likely eVect on maximum income if all farmers could choose between diVerent production technologies. For each LUT three technologies were defined, as follows: technology 1: ‘‘average farmer practice,’’ technology 2: ‘‘high yield/ high input,’’ and technology 3: ‘‘high yield/improved practice.’’ The relevant input–output coeYcients for technologies 1 and 2 were derived from farm surveys in Ilocos Norte Province, while technology 3 (SSNM, site-specific nutrient management) was generated based on quantitative relationships between yield and soil conditions and fertilizer management practices These quantitative relationships (established using the QUEFTS procedure, i.e., the quantitative estimation of the fertility of tropical soils system) were derived from comprehensive experimental data sets from diVerent locations in Asia. For the Ilocos Norte case, technology 1 involves average values for all farms (after data cleaning). Technology 2 depicts the land use of a group of survey farmers obtaining higher than average output through intensive use of inputs. For yields, the mean of the values with a yield level between the 90th and 95th percentile of the survey data was reported. Fertilizer and pesticide use were assumed 100% higher and labor 70% higher, other inputs remaining identical to those in the average practice. For the ‘‘improved

Table I Results of the Regional Explorations (Year 2010) Maximize farmers’ income Variable Income Rice Employment Biocide N fertilizer Land used

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practice’’ or SSNM variant (technology 3), the same, high, yields as in technology 2 were assumed, but biocide inputs were reduced by 20% compared to those in ‘‘average farmers’’ practice. We, moreover, assumed higher fertilizer use eYciency than in the first two technologies. For defining realistic improvements in fertilizer eYciency, we screened data from fertilizer experiments in the Philippines and other Southeast Asian countries. Results for scenario 1 show, among others, that if all farmers in Ilocos Norte would apply technology 2, their income would be considerably higher than with technology 1. However, this would be achieved at the cost of high use of agrochemicals. If all farmers would apply technology 3, even higher income levels than with technology 2 could be achieved at about 30% lower inputs of fertilizers and pesticides. For all technologies, in scenario 1, total rice production would exceed the current production levels. Site-specific and more balanced nutrient and pest management practices could lead to considerably higher incomes at reduced environmental costs, while still satisfying local demand for the main food crops: a clear win–win situation (at least, as predicted by this exploratory analysis at the provincial level). This does, of course, not imply that all farmers will adopt these technologies; however, the methodology illustrates specifically what might happen if they did, and as such, it presents motivation for change. To study the farmers’ perspective in more depth, a PhD study and a followup project were launched to supplement the regional results with farm household analysis in Batac (Laborte, 2006) and Dingras municipalities (www.irmla. alterra.nl). Aside from scenarios 1 and 2, mentioned above, a large number of additional scenarios have been analyzed for Ilocos Norte Province by SYSNET following interaction with user groups and policymakers. These are available on CD-ROM. One major concern deals with use of irrigation water. Figure 10 illustrates, for example, the shifts to be expected in land-use allocations for rice cropping systems under the assumption of the possibility to share water among the irrigation systems of the province, making water use more eYcient. Associated calculations indicate that rice production could increase by 40% and farmers’ income by 16%, partly because sharing water implies that the triple-rice cropping systems could be more widely applied, be it only in certain areas! This example illustrates how a relatively abstract concept of increasing water-use eYciency can be ‘‘translated’’ into specific financial terms for a region and into associated land-use patterns that land users and policymakers can identify with. Application of LUPAS has ‘‘lubricated’’ discussions in the diVerent countries by showing what the consequences might be for a given region of major departures from current land use and agricultural practices. Of course, each region has a characteristic ‘‘window of opportunities’’ and LUPAS is

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particularly suitable to provide a sketch for that window. Rather than making an obvious statement such as: ‘‘anything’’ cannot be done ‘‘anywhere,’’ LUPAS allows statements as to what ‘‘might’’ be done ‘‘where’’ under certain, well defined, conditions. With that kind of information regional development objectives and targets can be generated for policy objectives. This is combined with considering interventions at the farm level, making sure that scenarios at regional level are realistic, while at the same time providing specific stimuli for local farmers when the potential benefits of certain changes on a regional level can be made visible for the farm level as well. This joint eVect on policy and farm level has been analyzed for Ilocos Norte Province in the Philippines (Laborte, 2006) and Pujiang county in China (www.irmla.alterra.nl).

3. What It Takes to Apply the Methodology in Practice In order to integrate use of LUPAS into the practice of land-use planning, during the period 2001–2005, it has been applied independently to several provinces of Vietnam by local teams from Cuu Long Delta Rice Research

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Institute (CLRRI) in the Mekong Delta and by the National Institute of Soils and Fertilizers (NISF) in North Vietnam. Studies have been performed in close consultation with local governments and stakeholder platforms established during the SYSNET research process (Roetter et al., 2000; Van Paassen et al., 2006). In Malaysia, independent applications have not been reported due to ‘‘brain drain’’ of IT and computer specialists at Malaysian Agricultural Research and Development Institute (MARDI). The SYSNET team in India has applied modules of the LUPAS system, such as the technical coeYcient generator (TCG), in a number of policy-relevant land-use studies and has expanded the TCG to include calculation of greenhouse gas emissions. The Philippine team, supported by IRRI, finally, has continued to look concurrently at the adoption of knowledge-intensive technologies and supportive policies on sustainable agricultural development in Northern Luzon. Similarly, iterative multi-scale analyses of technology and policy options have been performed in follow-up projects to SYSNET such as in the IRMLA project between Zhejiang University and local government organizations, for example, the Agricultural Bureau in China (www.irmla.alterra.nl). Changes in land management practices and policies that can be attributed to SYSNET and its follow-up projects include, for instance, abandonment of heavy agrochemical use in dry season crops in Ilocos Norte, Philippines, increased investments and special R&D programs for participatory development and dissemination of IPM and site-specific nutrient management practices in Ilocos Norte (Philippines), Can Tho Province in the Mekong Delta and Tam duong district in the Red River Delta (Vietnam) and in Pujiang county (China). Through results from scenario analyses the awareness of excessive nitrogen and pesticide use in rice-based systems has been clearly raised, and policy objectives to achieve this have been introduced in policy documents of local governments (in particular in the Mekong Delta, Vietnam, and in Zhejiang Province, China) (Van Paassen et al., 2006). Several follow-up R&D projects have been realized in Southeast Asia and this has been made possible by substantial investments in institutional capacity building made by SYSNET project (ISNAR, 2004; Van Paassen et al., 2006).

E. FROM ENVIRONMENT

TO

HUMAN HEALTH

The DME-NOR project from the first phase of the Fund is one of the few projects that, in combination with significant leverage funding and follow-up projects, has covered the entire policy cycle. Although the commercial farmers of the Carchi region in Northern Ecuador are probably some of the better endowed in the rural communities of the Andes, it became increasingly apparent that the use of pesticides in intensive potato production was not only a blessing but a curse as well. In the early 1990s, researchers, farmers, and

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NGOs paid increasing attention to the negative eVects of the intensive use of pesticides. The farmers in the Carchi region were very much dependent on these pesticides to control pernicious pests and blight. Intensive on-farm research revealed some of the major health and environmental impacts associated with these pesticides. The intensive use of highly toxic pesticides resulted in significant neurobehavioral eVects on farmers and pesticides were detected in ground water as well as streams that serve irrigation and domestic use downstream. A broad signaling phase with large groups of stakeholders, however, also drew the attention to soil erosion. Many fields revealed the light-colored subsoil on the upper parts of the fields and the common perception was that water erosion was the main cause. However, research showed that water erosion was not responsible for the erosion of the topsoil due to low rainfall intensities in combination with a high infiltration capacity of the volcanic ash soils. The steep fields cultivated with potatoes require intensive tillage. All tillage and harvest operations transport topsoil material down the slope. On fields tilled with tractors the situation is even more serious. As slopes are too steep for contour plowing, tractors plow downslope. Rather than water erosion, tillage erosion was in this case the main cause for the observed erosion processes. This example clearly shows the importance of stakeholder input but also the impact of scientists in the signaling phase, avoiding misperceptions that could easily have led to irrelevant routine research on water erosion. After signaling and quantifying the key sustainability factors, that is, human health and environmental impacts of pesticide use and tillage erosion, the question that remained was how to intervene. Clearly, the reduction of pesticides also pesticide handling issues were the two elements to focus on to reduce the environmental and health impacts of pesticides. To reduce the impact of tillage erosion, very few technical solutions were available. The potato crop requires intensive tillage and any tillage practice on these steep slopes automatically results in soil erosion. The only practice that significantly reduces tillage erosion is based on the little-known pre-Columbian limited tillage/cover potato system Wachu rozado that is still being practiced in Northern Ecuador. In this system seed potatoes are placed on top of the pasture and the grass mat is folded over the potatoes. In the DME-NOR project the TOA methodology has been developed that was also applied in the Kenya research (see Section IV.A). A 2-year dynamic farm survey provided insight in the management decisions of the farmers in the Carchi region. This resulted in an economic simulation model allowing for the ex ante evaluation of alternative policy and management scenarios (Crissman et al., 1998; Stoorvogel et al., 2004a). The TOA methodology addresses two key elements: first, it provides an organizational structure around which to design successful interdisciplinary research that assesses the sustainability of production systems; second, it provides a

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successful means to communicate research findings to policymakers and the public. Farmers are the Andes’ most numerous and most important soil resource managers. Agricultural technology ranges from traditional, extensive, lowinput, low-output systems to modern, intensive, high-input, high-output systems. The traditional systems have to be maintained within their ecological constraints and, as a result, are generally perceived as environmentally friendly and sustainable. However, due in part to shrinking farm size, traditional systems have proven to be economically and socially nonsustainable. With a closed agricultural frontier in most parts of the Andes, the fundamental option for Andean farmers is to increase the physical and financial output from the existing farm. This inexorable pressure provides a strong incentive to shift to the higher output modern systems. The basic quest of agricultural and environmental research for sustainable farming systems is to match the environmental friendliness of traditional farming systems while reaching the higher outputs and, thus, the economic and social sustainability found in modern farming systems. Figure 11 shows an example of the type of answer one can expect from the TOA system. The trade-oV curves between net returns and carbofuran (one of the most commonly applied highly toxic insecticides) leaching are constructed by varying the potato prices. In the base scenario the current management system is evaluated. The trade-oV curve shows that with increasing potato prices, the net returns of the systems increase coinciding with an increase in carbofuran leaching. The latter is due to an increase in the potato area but also due to a more intensive management of the potatoes.

Carbofuran Ieaching (g ha−1)

800

Base scenario (trend) Base scenario IPM scenario (trend) IPM scenario Tillage erosion (trend) Tillage erosion

700 600 500 400 300 200 100 0 0

1000 2000 Net returns (sucres ha−1)

3000

Figure 11 The eVect of IPM and tillage erosion on net returns and carbofuran leaching in the Carchi region in Northern Ecuador.

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Two alternative scenarios have been evaluated: the eVect of tillage erosion and the eVect of the introduction and adoption of IPM. Due to tillage erosion we see that carbofuran leaching increases. This can be explained by the removal of the organic matter-rich topsoil that fixes carbofuran. IPM shows an opposite eVect where the trade-oV curve is moving down. Less carbofuran is being applied and as a result leaching is going down. However, the reduction of IPM comes at a cost. Alternative management practices are required to control the pest requiring farm labor. As a result net returns are slightly decreasing. The TOA provided information on possible interventions both at the political level as well as at the farm level. In various follow-up projects the policy cycle has been closed. While pesticides have not been eliminated from the Carchi communities, they are now generally used more cautiously. There is also momentum at a policy level for reducing pesticide dependence. In 1999, all stakeholders were brought together to discuss pesticides and health. This meeting resulted in the Carchi declaration demanding the elimination of the highly toxic products, the inclusion of IPM in university level agriculture training, and a wider dissemination of information on the eVects of pesticides. In addition, farmer field schools have been set up in which farmers and the research community developed IPM technologies but also pesticide handling measures to reduce the impact of pesticides. The eVects of various management changes, as part of IPM, on these farmer field schools are striking. The number of pesticide applications was reduced from 12 in conventional plots to 7 in plots with IPM. Even more important, the overall amount of pesticides applied dropped dramatically. The amount of fungicides decreased by 50% while insecticide quantities dropped between 40% and 75%. The Carchi story is illustrative for a combined eVort in which farm surveys, advanced simulation modeling, GIS techniques, IPM research, stakeholder meetings, and farmer field schools led to a strong reduction of pesticide use in the Carchi study area. It illustrates the strength of the research chain rather than a single method and/or project. The project was successful in designing innovative production systems for potatoes that were environmentally friendly while protecting the health of farmers. Political decisions were made about environmental and health regulations and they were implemented, so far only at the regional level. Educational programs for farmers were initiated during this research projects and are continued up to this day.

F. REALLY DEALING WITH SOIL EROSION Widespread soil erosion—one of the most studied topics in agricultural research—and the associated land degradation are caused by overexploitation of natural resources due to an increasing demand for food, fiber, and

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fodder by growing human and livestock populations without the economic means to sustain the resource base. Exploitative land-use practices include deforestation for expansion of cultivation, excessive grazing, and removal of fuel wood and timber. This reduces the protective plant cover, thereby exposing the soil surface to the destructive impact of high-intensity rainfall. Land degradation can be reversed by soil and water conservation (SWC) practices that have been developed during many decades of research but results in the field have so far been quite disappointing. Often, farmers are blamed for this low success rate. They are accused of being ignorant, uncooperative, and conservative. This, however, is increasingly seen as an unfair judgment. Poor planning of SWC research rather than unwilling farmers, appears to be the core issue. Too much top-down research has been done without consulting farmers in the process, resulting in recommendations that did not match the priorities of the farmers who tend to focus on productivity loss rather than on soil loss as such. The question as to how farmers can be more involved in a meaningful manner in soil erosion research is therefore still relevant. Another aspect to be considered in erosion research is the need to look at larger areas than only single farms as local management practices may aVect conditions elsewhere in the area through patterns of water movement. The so-called ‘‘catchment approach’’ looks at an entire natural geographic area which drains all rainfall within the area to a single outlet. Unfortunately, so far research methods for the catchment scale are not well available and this was a main reason to start a project to develop an improved method for SWC planning at catchment scale in the East African highlands (EROAHI). As discussed by Van den Bosch and Sterk (2005), experiences elsewhere with the catchment approach had been mixed so far at best. Involvement of communities of land users turned out to be diYcult. Also, oV-farm conservation work often not considered as emphasis was still on farms. To overcome the problems of nonparticipation and ineVectivity, new scientific tools and procedures were developed in the EROAHI project to tap the active and creative input of farmers and their communities in developing innovative and eVective SWC measures on catchment level. Research followed a number of steps: (1) a review of farmer’s perceptions on erosion and SWC measures. Emphasis on this first step led to serious farmer’s involvement right from the start and to insights into their perceptions; (2) identification and calibration of indicators of erosion. This step was essential to nail down perceptions outlined in step (1). Without this step, discussions would have remained unfocused; (3) construction of a tool for participatory soil erosion mapping. Having jointly defined the indicators, now a map is made of the entire catchment requiring active participation of all farmers and providing a platform for discussion and information exchange (Okoba, 2005); (4) surveys and modeling. Having defined the eVects of erosion as seen by farmers, scientific procedures to study these

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eVects are applied and tested. Note that this more traditional form of research enters the discourse only in step (4). Three procedures were used here. The first was the internationally established method for Assessment of Current Erosion Damage (ACED). The second was the Morgan, Morgan, and Finney (MMF) model, an easy to understand empirical model with a physical base and a low data demand. The third was the LISEM model, based on physical—chemical laws and requiring many detailed data. This model is particularly suitable to estimate eVects of a single rainfall event and was calibrated and validated by measuring outflow from the studied catchments; (5) comparison of the farmers map with the ACED survey and modeling results. Although there were expected discrepancies between farmers observations and ACED results, the predictions of the farmers were often closer to the ACED results than the model predictions (Fig. 12). Use of farmer’s indicators for infield erosion assessment in combination with the ACED approach and MMF modeling provides a good basis for productive, joint work of researchers, extensionists, and farmers (Vigiak, 2005). The LISEM model has not only a prohibitively high data demand but it also needs intensive calibration after which it can predict total runoV from a particular catchment after a given rainfall event. However, erosion patterns over the catchment are not well predicted nor is the model suitable to predict average annual erosion rates (Hessel, 2006); (6) once overall erosion has been predicted, attention is focused on eVects of particular SWC measures,

A

B

N

Field boundaries Legend Strongly underpredicted Underpredicted Correct Overpredicted Strongly overpredicted

EROAHI project 0

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Figure 12 Map of the Gikuuri catchment showing the diVerence between farmers’ estimates and ACED field survey (A) and the diVerence between LISEM and the ACED field survey (B).

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where field research provides specific data in the defining context described by procedures (1)–(5). Having this context makes such experiments much more valuable than having only isolated experiments. Here, hillside ditches turned out to be more eVective than bench terraces and grass strips; (7) the financial eVectiveness of SWC measures and construction of a practical tool for participatory financial analysis (Tenge, 2005). This aspect is very important for farmers and policymakers alike in the context of cost–benefit analyses that often form the ultimate criteria for success or failure; and finally (8) the project tested the developed tools under field circumstances. The tools developed in Kenya were tested in Tanzania and the Tanzania tools were tested in Kenya. Results indicated the general applicability of the developed tools and procedures (www.ecoregionalfund.com; van den Bosch and Sterk, 2005). This project illustrates a particular form of signaling. The importance of soil degradation and erosion hardly needs signaling. Libraries are filled with data reflecting a century of research. Interestingly, signaling here was focused on the SWC profession itself, questioning basic premises of previous work. By starting with farmers’ expertise and by introducing scientific survey and modeling techniques later, the design process was innovative and resulted in a true interactive process between farmers and researchers. The high-tech LISEM model, used routinely in many erosion studies, was shown to have serious limitations. The decision process focused on farmers and by providing jointly developed tools for both the technical and financial evaluation, their commitment was earned. Implementation was tested in the field in both Kenya and Tanzania and results, though necessarily of a preliminary nature, are promising. Evaluation in the end provides a clear message for the research community—rather than the usual technology push, time has come to move toward true interactivity with the land user which may be time consuming at first sight but which results in real eVects in the field as a result of fine-tuned technology infusion into the social interaction processes occurring in catchment areas. Such messages, showing clear results, are a good starting point for renewed interaction with policymakers who have become unreceptive to generic complaints about soil erosion which they have heard so many times before.

G.

REESTABLISHING FARMERS’ CREDIT IN SOUTH AFRICA

THE

HIGHVELD REGION,

The primary staple foods of southern Africa are grain crops. Large areas in southern Africa, which are classified as arid to semi-arid with irregular rainfall patterns, are planted under maize, sorghum, and millet. Due to climatic conditions, yields are irregular and unpredictable. The oYce of the ‘‘Agricultural Research Council-Grain Crops Institutes’’ (ARC-GCI) in Potchefstroom (South Africa) is responsible for research in the Highveld

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region. The Highveld region, located within South Africa, is representative for most of the environmental and economic risks which are experienced within the other southern and eastern African countries. In the Highveld region 70% of the arable area is planted to maize. Up to 90% of the country’s maize is produced in this region. As the main staple food, maize production plays an important role in the livelihoods of the rural communities. Questions to be answered by ARC-CGI were not raised by scientists. Key questions were asked by banks, industry, government, and farmers: Can we assess the likelihood of crop failure in any given year? Is this land providing enough income to support farmers with credit? What is the expected regional maize production in the current growing season? and What are the expected eVects of climate change on maize production in the Highveld region? Uncertainty about these issues had resulted in lack of credit and insurance facilities for farmers, as bankers considered risks involved to be commercially unacceptable. This created an emergency situation for the region. ARC-GCI considers crop growth simulation models to be one of the key instruments to investigate the various problems surrounding the cultivation of the main crop. Questions being raised could not be answered with existing more traditional agronomic expertise and tools. Use of models resulted in various questions to the research community at ARC-GCI. For example: What are the genetic coeYcients for the local maize varieties to be used in the crop growth simulation models? Are various existing crop growth simulation models providing us with reliable estimates? and Can we extrapolate weather conditions observed locally in a few weather stations both in space and time to the entire area? The ARC-GCI project developed specific modeling tools and focused on generating the required input data. They used the models and tools to provide specific answers to the questions of farmers, policymakers, industry representatives, and bankers. The work was done in close interaction with these four groups of stakeholders, making sure that every step in the procedure was discussed, explained, and, if necessary, modified. Many of the tools currently being used by the research community are not geared to answering these practical questions. Significant changes were therefore required and specific utilities had to be developed to obtain an operational system. And all this had to be achieved with limited resources and time. In the end, researchers showed convincingly that the models were useful tools to answer the various questions but only after a significant investment in calibration and development of specific tools for the region. By developing the work in close consultation with farmers and bankers, results were readily and successfully adopted. In this project signaling by farmers and bankers was followed by a research-initiated design phase with a high participatory character. Results were such that bankers and insurers decided to embrace the system and provide again credit and insurance to farmers. The project of the Fund was terminated in 2002 and as far as we

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know, the system still operates to full satisfaction of participants. Implementation of the modeling approach has led to many questions along the way which are still being addressed by the researchers of ARC. This successful project has covered the entire policy chain.

V. WHERE DO WE STAND NOW AND WHERE TO GO? When dealing with science in support of natural resource management and rural development in developing countries—the charge for the Fund—we have to look beyond the individual farm, realizing, however, that what does or does not happen on the farm will have a major impact on the region and country in which the farms occur. That is why up- and downscaling are so crucial. In other words, how can changes at farm level aVect regional development and—a more dominant consideration—how do regional, national, and international developments aVect the farm level? And what is and can be the role of research in all of this? In their ‘‘Strategy for Revitalizing Agriculture’’ the Kenyan Government (2004) lists five critical areas requiring attention. One of them is ‘‘promotion of research and technology development.’’ Our premise is that innovative approaches are needed for research at the regional level in future for it to be eVective in promoting better natural resource management, contributing to rural development. The problems we deal with are immense and baZing but with due recognition of the limitations of a single project and of all the good work being done elsewhere, we like to propose that our work has contributed in three ways.

A. SHOWING NEW WAYS OF CONDUCTING RESEARCH 1.

Up- and Downscaling by Using Sequences of Models

Rather than study only isolated problems, a comprehensive analysis of the land-use system is needed, starting at regional and higher-scale level, with functional links to the local level. Computer simulation modeling is by now an indispensable tool, as has been demonstrated in the various case studies discussed here. User-friendly approaches and accessibility on the web allow use at even the most inaccessible locations. A sequence of models to be used has been demonstrated in the various projects of the Fund (e.g., LUPAS–CLUE–TRADE-OFF–IMPACT). Downscaling moves from left to right and upscaling from right to left. Rather than being defined as an abstract concept, scaling can thus be associated with and translated into specific questions, data demands and answers that are associated with various models, each one characteristic for a given scale level and focused on

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questions that are unique for that particular level. The sequence CLUE– TRADE-OFF–IMPACT, including up- and downscaling was most clearly demonstrated in Section IV.A (African Highlands) and Section IV.B (Panama). For erosion, diVerent sets of interconnected models were used for the farm and watershed level in Section IV.F (Kenya/Tanzania). This comprehensive systems analysis provides lots of opportunities for basic research as demonstrated by published papers for each of the case studies in Section IV.

2.

Covering the Entire Policy Cycle

Research should preferably cover the entire policy cycle from signaling problems to implementation of possible solutions. The traditional restriction of research to the design phase does not mobilize the available research potential (interestingly, in their strategy document the Kenyan Government does not speak of the policy cycle but of ‘‘five steps of logical thinking’’). Demands on research are diVerent when signaling a problem, when designing options for solving the problem, when advising policymakers to make decisions, or when helping to implement selected measures, rules, or regulations (Bouma, 2005). Due to time limitations, many of the more recent projects of the Fund have not moved beyond the design phase. Most experiences obtained referred therefore to the signaling phase. But some of the earlier projects, as described in Sections IV.D (Southeast Asia), IV.E (Peru), and IV.G (South Africa), have covered the entire cycle. Significantly, signaling never followed the stereotype sequence of a project being formulated by a governmental agency or by researchers, followed by research ending with the delivery of a report. DiVerent approaches were evident in the studies of the Fund. 1. Governmental initiatives. The Kenyan government was instrumental in putting agricultural development on the agenda (Section IV.A), but this was immediately picked up by local researchers of KARI and external researchers (the latter category includes researchers associated with CGIAR Centers and those associated with northern Universities) into a joint design process; 2. Initiatives by external researchers. The FTA study (Section IV.B) was initiated by CIP at an IDIAP conference, demonstrating eVective communication of the possibilities of modern techniques studying land use. After that, the government joined external and increasingly local researchers into a highly interactive process of design. The innovative exploratory work in Tibet (Section IV.C) could not yet connect with local researchers let alone with policymakers. Still, indications are that

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slowly policymakers are being convinced that modern land-use studies can assist their cause and local researchers may follow but only after extensive training. Studies in Southeast Asia (Section IV.D) were also initiated by external researchers who strongly involved local researchers, which, in turn, attracted governmental attention resulting in a truly jointlearning process in the design phase. Because this program has been proceeding since 1997, policy decisions have been made and there is clear evidence of implementation. The soil erosion studies of Section IV.F were initiated by external researchers who took a much-needed fresh look at available studies on erosion. They are involving local researchers and face the task to communicate their findings and recommendations to governmental agencies that have received abundant erosion advice over the years, leading to no significant advances in combating eVects of erosion. There is clearly a certain degree of skepticism to be overcome. 3. Initiatives by local researchers. The foremost example of this is the farmers’ credit study in South Africa (Section IV.G). Local researchers quickly picked up the signals of farmers and bankers, signaling the problem. They designed solutions in close interaction with farmers and bankers and made sure that the developed information systems were implemented. External researchers had limited but essential input in providing simulation models and climate expertise. A second example is reported for Ecuador in Section IV.E. Here, local researchers and stakeholders were worried about erosion of potato fields. External researchers showed that erosion was less a problem than toxic eVects of biocides, used for the potato crop. An extensive education program was set up by external and local researchers while the latter group is now a prime actor in implementation of remediative action. For researchers, the implications of this diversity in approach have as yet been largely unexplored and represent a new challenge to find the appropriate mix of initiatives and activities for each new project. It requires in any case an extended project period of at least 10 years to allow organic development of such projects and this is in stark contrast to the type of shortduration projects we see now. The evaluation aspect in the end is particularly valuable. It allows a learning experience based on an analysis of mistakes made and successes achieved, with the potential to improve the research process next time around. 3. True Interaction Requires a Long-Time Engagement Covering the entire policy cycle requires intensive and long-term interaction not only with policymakers but also with a wide variety of land users. Case studies in Section IV illustrate this well. To be eVective, this cannot be

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an ad hoc activity but requires a structural arrangement, which, so far, has not often been realized in practice. As any situation is diVerent it is diYcult to formulate general rules, except for researchers to be engaged and open to dialogue without sacrificing their scientific virility. Researchers are most eVective when they focus on a key element of democratic society, which is the necessary interaction and eVective communication between citizens and their government. This is more eVective than exclusive interaction of researchers with either governmental agencies or stakeholder groups, which is not uncommon at this time. EVective interaction results from injection of the right knowledge or expertise into the debate at the right time (including recognition of tacit knowledge of stakeholders as an essential ingredient) but also from being prepared to play the role of mediators. Two aspects need emphasis here: (1) as relatively neutral outsiders with no direct stake in the way resources are used in a particular region, scientists can be particularly eVective in safeguarding sustainable development which requires a delicate balance between economic, environmental, and social requirements, and (2) the need for training and capacity building by initiating workshops with emphasis on joint learning rather than on technology transfer. Cases presented in Section IV provide examples of both aspects.

B. SHOWING NEW WAYS OF PRESENTING RESULTS A key element of work of the Fund is the systematic use of GIS which visualize diVerent land-use patterns, ranging from actual conditions to possible patterns following certain land-use options. Good examples were provided in Sections IV.A, IV.B, IV.C, and IV.D. Too many reports present their statements in texts and tables, making them diYcult and tiring to read, understand, and interpret. Reports with long ‘‘Shopping lists’’ defining problems and other lists with possible solutions (without any indication as to how those solutions could possibly be attained) are all too familiar and discourage rather than stimulate the reader. Visualization is a powerful tool of communication and GIS maps form only a relatively simple mode. Accessibility of the programs on the Web makes them much more easy to use. In addition, modern 3D visualization techniques are widely used in the information and communication industry, for example, for gaming purposes. Initial plans to incorporate these techniques in our work could not be realized. We still feel, however, that such techniques should be more widely applied in land-use studies as users of information are usually quite susceptible to impulses in terms of ‘‘what’’ might happen ‘‘where’’ and ‘‘when.’’ The Kenyan Highland study (Section IV.A) was a good example of showing ‘‘hot’’ and ‘‘cold’’ spots of possible future developments including the possible eVects of better marketing and improved

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functioning of institutions, which are some of the critical areas defined by the Strategy for Revitalizing Agriculture in Kenya (2004). Communication is not only an art but also a science. Involvement of science writer Simon Chater from Green Ink Ltd. (United Kingdom), who wrote two bulletins with the challenging title: ‘‘(More) Method in our Madness,’’ was essential, we found, in communicating our message to a broader audience than the usual one being addressed in scientific circles (Ecoregional Fund, 2005; www.ecoregionalfund.com; ISNAR, 2004).

C.

PRESENTING NEW MESSAGES

TO

POLICYMAKERS

AND

LAND USERS

The new message is that we would like to join in a permanent partnership with policymakers and land users in order to increase the eVectivity of our research. We acknowledge similar considerations being made elsewhere, for example, at the Millennium Institute in Arlington, Virginia, United States (www.millennium-institute.org). Obviously, research cannot on its own define ‘‘ideal’’ solutions to complicated environmental problems and rural development. Rather than have ad hoc joint activities with policymakers and land users for (parts of) separate projects, we would prefer a structural arrangement where joint learning (including scientists) would be the overall objective. This arrangement has been called a Community of Practice (CoP) (Wenger et al., 2002). Responsibilities of all parties involved, which are not only policymakers and land users but also possibly NGOs and representatives from industry, should be well defined. Researchers taking part in CoPs have their own responsibilities and should be keen to preserve their academic independence. They should listen well to other participants and try to learn from their experiences. At the same time, however, they have their own scientific input in the debate, not only on the basis of existing expertise which can now easily be tapped from the internet, but also on the basis of new research to be initiated because the CoP considers this to be necessary. Being part of a CoP does not necessarily imply that scientists glorify the input of other members of the CoP (which sometimes happened in farming system research where farmers’ expertise was uncritically embraced by some) but that they critically examine all input. Forming an eVective CoP also requires discipline from the other team members: paying for a project does, for example, not necessarily imply that the answer should comply with preconceived ideas of the financier. EVectively acting within a CoP puts a strain on the scientific community because demands on researchers are quite diVerent than the traditional ones. Bouma (2005) therefore advocates next to a CoP, formation of Communities of Scientific Practice (CSP) within which the scientific community tries to get its act together. A group of workers from within the scientific community

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interacts with diVerent groups of stakeholders, policymakers, NGOs, and so on in a broader issue-oriented CoP. Each CoP requires a diVerent CSP. Within a CSP there should be ample opportunity for interaction between basic, strategic and applied researchers in diVerent fields, including the legal one, and communication experts. All projects of the Fund—and many others outside the Fund—show that CSPs are being formed now in which external and local researchers not only work well together but in which local researchers increasingly become leaders and initiators. This is an excellent development for the future.

ACKNOWLEDGMENTS The Directorate General of International Cooperation of the Dutch Foreign Ministry has provided the funding for this project, which was also supported in its first phase by the Swiss Development Ministry. We thank Hans Wessels and Theo van der Sande for their support and Caroline Wiedenhof for her helpful comments on a draft of this paper. Administrative support was provided by ISNAR during the first phase and we thank Stein Bie and Gigi Manicad for their input. Price Waterhouse Coopers supported the second phase and we thank Joep Meerman and Pauline Rauwerda for their highly dedicated contributions. We are deeply grateful to all of our collaborators in the various countries.

REFERENCES Antle, J. M., and Valdivia, R. O. (2006). Modelling the supply of ecosystem services from agriculture: A minimum‐data approach. Aust. J. Agric. Res. Eco. 50(1), 1–15. Bouma, J. (2005). Soil scientists in a changing world. Adv. Agron. 88, 67–97. Bowen, W., Cabrera, H., Barrera, V., and Baigorria, G. (1999). Simulating the response of potato to applied nitrogen. In ‘‘Impact on a Changing World. Program Report 1997– 1998,’’ pp. 381–386. International Potato Center, Lima, Peru. Castells, M. (2000). ‘‘The Rise of the Network Society. The Information Age: Economy, Society and Culture,’’ Vol. 1, Blackwell Publishing, Oxford. Crissman, C. C., Antle, J. M., and Capalbo, S. M. (Eds.) (1998). ‘‘Economic, Environmental, and Health Tradeoffs in Agriculture: Pesticides and the Sustainability of Andean Potato Production.’’ Kluwer Academic Publishers, Boston, USA. De Jager, A., Kariuku, I., Matiri, F. M., Odendo, M., and Wanyama, J. M. (1998). Monitoring nutrient flows and economic performance in African farming systems (NUTMON): IV. Linking nutrient balances and economic performance in three districts in Kenya. Agric. Ecosyst. Environ. 71, 81–92.

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INFLUENCE OF HIGH TEMPERATURE AND BREEDING FOR HEAT TOLERANCE IN COTTON: A REVIEW Rishi P. Singh,1 P. V. Vara Prasad,2 K. Sunita,1 S. N. Giri3 and K. Raja Reddy4 1

Division of Genetics, Indian Agricultural Research Institute, New Delhi 110012, India 2 Department of Agronomy, Kansas State University, Manhattan, Kansas 66506 3 Birsa Agriculture University, Hazaribagh, Jharkhand 835006, India 4 Department of Plant and Soil Sciences, Mississippi State University, Mississippi 39762

I. Introduction II. EVects of High Temperature A. Morphological and Yield Traits B. Physiological and Biochemical Traits III. Heat Stress and Heat Tolerance A. Definition and Levels of Heat Stress B. Heat Tolerance IV. Screening for Heat‐Tolerance Traits A. Physiological and/or Biochemical Traits B. Ecophysiological Traits C. Association Among Ecophysiological, Morphological, and Yield Traits V. Breeding for High‐Temperature Tolerance A. Trait Selection B. Correlated Response of Selected Trait C. Isogenic Lines to Study Individual Trait Performance D. Genetic Variability E. Inheritance Studies F. Impact of Heat‐Tolerant Genes G. Breeding for High‐Temperature Tolerance H. Practical Achievements VI. Summary and Conclusions Acknowledgments References

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R. P. SINGH ET AL. Cotton (Gossypium spp.) is an important crop in several parts of the world, which is highly sensitive to environmental stresses. In the last century, carbon dioxide concentration [CO2] has risen rapidly from about 350 mmol mol
1 in 1980 to about 378 mmol mol
1 at present. At the current rate of gas emissions and population increase, it is predicted that CO2 will double by end of this century. These changes in CO2 and other greenhouse gases are predicted to increase surface mean temperature in the range of 1.4–5.8  C. In addition, studies also show that future climates will have more frequent short episodes of high temperature (heat). Most crops are highly sensitive to heat stress and often result in progressively decreasing yields at temperatures above the optimum. In most of the cotton‐producing regions, current temperatures are already close to or above the optimum temperature for its growth and yield, particularly during flowering and boll growth period. Therefore, any increase in mean temperature or episodes of heat stress will further decrease yields. One of the most important and economic ways to overcome negative eVects of heat stress is to identify and/or develop heat‐tolerant cultivars. At present, the major constraint for identifying heat‐tolerant cultivars is the lack of reliable screening tool. Better understanding of the possible impact of high‐temperature stress on physiological, morphological, and yield processes would not only help in mitigating the adverse eVects of high‐temperature stress but also in developing reliable field‐screening tools. This chapter reviews eVects of high temperature on the cotton plant as a whole, including important physiological, growth and yield processes, and fiber properties. In addition, various new screening techniques based on physiological, ecophysiological, and morphological traits to identify tolerant germplasm are discussed in detail. Finally, the genetic, biotechnological, and breeding approaches are discussed herewith to improve understanding of heat tolerance in cotton. # 2007, Elsevier Inc.

I. INTRODUCTION Cotton (Gossypium spp.) is produced in about 76 countries, covering more than 32 million ha across a wide range of environmental conditions. World cotton commerce is about US$20 billion annually (Saranga et al., 2001). As the world’s leading textile fiber plant, cotton forms a vital part of global agriculture and is a mainstay of the economy of many developed and developing countries. Cotton is the main source of employment for millions engaged in production, processing, ginning, textile, and trade‐related activities, and contributes to a significant portion of the gross national product of many countries, including India, China, Pakistan, Uzbekistan, Australia, and Greece (FAO, 2005). About 65% of world cotton production is between 30 N and 37 N latitudes, which includes United States, parts of the former Soviet Union, and China. Approximately 25% of the total production comes from the northern tropics up to 30 N. Small cotton‐production areas in Greece,

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Bulgaria, Romania, China (45 N), and parts of the former Soviet Union are farther north (Lee, 1984). Similarly, small quantities of cotton are grown 40 N in Bulgaria, Russia, and Korea, but the summers are short and only suitable for varieties which mature very quickly (Munro, 1987). The farthest north the crop seems to be Hungary at 46 N and Ukraine at 47 N (Wendel et al., 1992). Today, upland cotton is being grown globally across both tropical and temperate latitudes. The Egyptian crop is grown near sea level or a little higher, while those in East Africa are mostly grown at altitudes over 900 m in Rhodesia, and those of the higher plains of Texas (United States) are probably the highest lying commercial cotton crops in the world. The Sea Island cotton crop of West Indies is grown under fairly high humidity levels. Perennial cottons in parts of Sierra Leone receive annual rainfall of 3300 mm, and perennial cottons under the Himalayas may receive several meters of rainfall in the year (Prentice, 1972). Cotton is generally regarded as a crop of the hot, semi‐arid regions of the world, but is also an important crop in arid‐irrigated regions and extends to semi‐humid tropics. The area under rainfed cotton varies among countries, but at the global level, cotton area under water‐limited conditions is estimated to be around 47% (Hearn, 1994). Outside the tropical belt, temperature rather than rainfall determines the cropping cycle and the crops 30 N can only be grown in the summer months maturing in September–November. The wild cottons generally occur in the tropics and subtropics, that is, in frost‐free areas. Wild species of Gossypium occur in habitats where maximum temperatures are often very high, especially in the arid regions where insolation rates are very high (Fryxell, 1986). Daytime maximum temperatures in excess of 43 C and high‐ minimum‐nighttime temperatures (27 C or more) are characteristics at low elevations (<450 m) in Arizona (Feaster and Turcotte, 1985). In the United States, Pima cotton (Gossypium barbadense L.) is grown primarily in the arid southwest, an area where air temperatures >40 C are common throughout the growing season (Radin, 1992). Similar extremes may occur in areas of the Arabian Peninsula and the deserts of southwestern Africa, where other species of cotton are grown. In the US Cotton Belt, temperature variation is quite large with seasonal variation exceeding 20 C and with greater diurnal variation (Reddy et al., 1995a,b). High temperature had a strong negative correlation with lint yields, with yields decreasing about 110 kg ha
1 for each 1 C increase in maximum day temperature. Lobell and Asner (2003) estimated that there was as much as 17% decrease in yields of corn and soybean for each degree centigrade increase in average growing season temperature above the optimum in the United States. High temperature rarely occurs alone and is often accompanied by high solar irradiance, drought, and wind, all of which exacerbate plant injury from high temperature (Paulsen, 1994). Saranga et al. (2001) stressed the coexistence of water and heat stress under arid region field conditions. They

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emphasized the need for a balance between tolerance of heat and drought, and the need for changing crop water use to improve crop productivity under arid conditions. This need is further strengthened by the fact that changes in cotton germplasm over the past 30 years may have resulted in reduced tolerance of modern cultivars to environmental stresses (Brown et al., 2003; Lewis et al., 2000). Polley (2002) stressed that understanding the interactive eVects of rising [CO2] and temperature for crop yields and water economy is among the major challenges confronting research. The detrimental eVects of high diurnal temperature on various physiological processes impacting crop yields are complex. These complicated eVects support the need to merge physiological and genetic approaches to address the problem in a systematic manner and to improve the tolerance to heat stress. It is imperative that more heat‐tolerant germplasm be identified (Brown and Zeiher, 1998). In this chapter, the eVects of high temperature on cotton plant as a whole, including important physiological, growth and yield processes, and fiber properties, are reviewed. The various ecomorpho‐ physiological screening techniques to identify the tolerant germplasm are discussed in detail. Finally, the genetic, biotechnological, and breeding approaches to improve understanding of heat tolerance in cotton are also discussed.

II. EFFECTS OF HIGH TEMPERATURE High‐temperature stress is among the least understood of the adversities that aVect plants (Paulsen, 1994). However, significant progress has been made in the last decade on better understanding of high‐temperature stress in several crops, including cotton. Furthermore, in recent years, due to the importance of, and concern about climate change there is a renewed interest in better understanding high‐temperature stress and its association with other climate‐change factors such as elevated CO2, UV‐B radiation, ozone, and drought. Numerous experiments have been conducted in the last two decades to determine the eVect of high temperature at diVerent plant growth stages individually and collectively on yield. A better understanding of plant responses to high temperatures is essential for developing cultivars for production in many hostile environments. Knowledge of high‐temperature eVects will also help to predict the agronomic consequences of global warming associated with greenhouse gases and to ensure the sustainability of agriculture (Paulsen, 1994; Reddy and Hodges, 2000). The eVects of high temperatures at seedling, vegetative, and reproductive stages, including yield and fiber quality of cotton, are summarized in this section.

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A. MORPHOLOGICAL 1.

AND

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YIELD TRAITS

Seedling and Root Growth

Optimum temperatures for seed germination and seedling development of cotton range from 28 to 30 C. The base temperature for seed germination is near 12 C, while that for growth is about 15.5 C. Cool temperatures during germination and initial growth are a problem in several locations in the United States particularly across the Mississippi Delta region. Genotypic diVerences for germination and root development under cool soil temperatures have been observed (Mills et al., 2005). The optimum range of temperature (day/night) for cotton root growth is 30/22–35/27 C, and high temperatures (40/32 C) altered the distribution of roots, causing shallower roots, even under optimum water and nutrient conditions (Reddy et al., 1997b,c). Burke (2001) reported that seedling heat tolerance is essential in most dryland cotton production areas because producers plant cotton when moisture becomes available. Similarly in North India, the soil temperature and wind velocity at sowing time are very high, resulting in rapid loss of soil moisture (Lather et al., 2001). Under these conditions, emerging cotton seedlings have poorly developed root system, with a primary tap root and the beginnings of lateral root development. Burke (2001) observed that when seedling temperature increases above optimal levels, acquired thermotolerance system is induced. Maximum protection levels are induced when plant temperature reaches 37.7–40 C, but at higher temperatures protection levels decline rapidly. Root temperature stress alters hydraulic conductivity and nutrient uptake, and regulates hormone synthesis and transport (Burke and Upchurch, 1995; Clarke and Reinhard, 1991). The impact of soil temperatures on the rate of downward extension of the cotton root system has been documented in controlled environments (Bland, 1993). From this study, increase in rooting depth appears predictive for much of the crop lifecycle, because of the temperature‐ dependent growth responses of seedling roots. Taylor and Klepper (1978) found that cotton roots extend deeper in the soil profile with gradual soil drying. In locations where drip irrigation or shallow wetting of the soil surface occurs, root growth may be restricted to the upper soil layers, with plants becoming prone to drying conditions in a shorter period. McMichael and Burke (1994) found that the diVerences in the temperature optima appear to be associated with dynamic changes in seedling development, which may be related to changes in stored seed reserves. Cotton has a strong tap root that can penetrate to more than 3 m, but low pH, compact soil layers, and low [O2], which can result from water logging, may limit root growth to only 0.45 m (Hearn, 1980). Cotton roots can penetrate at rates up to

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90 mm day
1 in a rhizotron (Taylor and RatliV, 1969). In the field on coarse soil, the maximum rate recorded was 50 mm day
1, but was decreased to 8 mm day
1 in cool soil temperatures (Bassett et al., 1970). Taylor and Klepper (1974) found that roots continued to grow in drying soil until the water content was 6–7% (
0.1 MPa). However, moisture stress can increase root growth (Brouwer and de Wit, 1969). Numerous functions of roots, including uptake of nutrients and water, assimilation and synthesis of metabolites, and translocation, are very sensitive to temperature. Root temperature may be more critical than shoot temperatures for plant growth because roots have a lower temperature optimum and are less adaptable to extreme fluctuations (Nielsen, 1974). Synthesis of cytokinins which originate predominantly in roots is among the most sensitive processes (Paulsen, 1994).

2.

Vegetative Growth

Leaf area development is highly sensitive to temperature. Optimum temperature for leaf area development is 26 C (Reddy et al., 1992a,b). Leaf expansion in cotton occurs at a greater rate in the dark than in the light (Krieg, 1981). At 20 days after emergence (DAE) the leaf area of plants grown at 28 C was found to be six times more than that of plants grown at 21 C (Reddy et al., 1997b,c). Reddy et al. (1992a) reported that in upland cotton main stem elongation, leaf area expansion, and biomass accumulation rates were very sensitive to temperature at about 21 DAE. The temperature optimum for stem elongation, leaf area expansion, and biomass accumulation was 30/22  C. Development rates, as depicted by number of main stem nodes produced, number of fruiting branches and fruiting branch nodes were not as sensitive to temperatures above 30/22  C as were growth rates. The length of fruiting branches increased as temperature increased to 30/22  C and then decreased about 25% among plants grown at the two higher temperatures (35/27 and 40/32  C), due to shortening of branch internodes. Growth of fruiting branch length responded to temperature in a similar fashion to main stem elongation and to fruiting branches produced when temperature treatments were imposed at first flower (Reddy et al., 1990). The total length of vegetative branches increased rapidly as temperature increased from 20/12 to 25/17  C. But with further increase in temperature, vegetative branch length declined linearly to near zero at 40/32  C. The leaf area per plant increased rapidly between 28 and 56 DAE at all temperatures. Nearly eight times more leaf area was produced at 30/22  C than at 20/12  C. About 50% more leaf area was produced at 40/32  C than at 30/22  C. Leaf growth rates were 20% and 50% smaller at cooler (20/12 C) and higher (40/30 C) temperatures, respectively, when compared to growth rates at 30/22  C.

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Heitholt (1994) speculated that extremely high air temperatures from 31 to 44 days after planting, which reached 34  C or greater each day, reduced canopy growth. In other studies, Reddy et al. (1991b, 1992a,b) observed that both upland and Pima cotton main stem elongation rates and node development rates responded significantly to temperature. While in Pima cotton (Reddy et al., 1992b), the main stem elongation rates were very sensitive to temperature after about 21 DAE. Before that time, the diVerences were small. Main stem node addition rate increased as temperature increased from 20/12 to 40/32  C (Reddy et al., 1992a). The temperature optimum for fruiting branch growth, square and boll production, and retention was 30/22  C. Above 30/22  C, average fruiting branch length was less and square initiation was completely inhibited at 40/32  C, while vegetative branch length kept increasing up to 40/22  C (Reddy et al., 1992a,c). In India, Sikka and Dastur (1960) gave the optimum range for vegetative growth of Asiatic cotton as 21–27  C and cool nights are needed for the best results, but given good moisture conditions the plant can stand temperatures even as high as 43–46  C.

3.

Flower Production and Fruit Set

Flowering intervals on vertical and horizontal branches are influenced by temperature (Munro and Farbrother, 1969; Reddy et al., 1997c). Mauney (1966) found similar relationships between temperature and flowering interval. Farbrother (1961) found that the horizontal flowering interval was approximately 11 days in Uganda, where temperatures in the field are fairly uniform throughout the year. Ehlig and LeMert (1973) observed that the number of flowers per meter of row declined approximately 3 weeks after periods when the maximum temperature exceeded 42  C. Heat stress during flowering resulted in square and flower drop when day temperatures exceeded 30  C (Reddy et al., 1992c). At day temperatures above 40  C, all the squares and flowers were aborted and dropped in several upland cotton cultivars (Reddy et al., 1991a). Pima cotton was more sensitive to high temperature than upland cotton and some of the Pima cotton varieties failed to produce fruiting branches and reproductive sites when the average daily temperature was 36  C (Reddy et al., 1995a, 1997c, 2004, 2005). Although upland type cotton did produce fruiting branches and formed squares at high temperature, it did not successfully produce bolls (Reddy et al., 1991b, 1992a). High‐temperature stress prior to and during flowering significantly influences several reproductive processes leading to decreased fruit set in cotton. Oosterhuis (1999) observed that high temperature could lead to decreased pollen viability and fertilization and this eVect usually occurred

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approximately 17 days before flowering. Similar observations were previously reported (McDonald and Stith, 1972; Meyer, 1969; Powell, 1969; Sarvella, 1966). High temperature of 32  C at 15–17 days before anthesis caused pollen sterility in temperature‐sensitive male sterile lines. Even fertile lines begin to show sterile anthers when temperatures were above 38  C (Meyer, 1969). The exact stage of development at which the sensitivity occurs is not known; however, based on the timescale of Sarvella (1964) or Quintanilha et al. (1962) it occurs after, rather than during, meiosis. If the plant is able to sustain the flower, high temperatures during anthesis influences pollination and processes leading to fertilization (pollen shed, pollen germination, pollen tube growth, and fertilization). Cotton flowers typically open in the morning between 0700 and 1100 h depending upon the environmental conditions (Pundir, 1972). Once pollen is shed it germinates within 30 min, but actual fertilization occurs between 12 and 24 h after the release of pollen (Pundir, 1972). In west Punjab of Pakistan, the occurrence of nondehiscent anthers and abnormal pollen was observed during the hot months of June, July, and August (Taha et al., 1981). Pollen germination is highly sensitive to temperature, and Burke et al. (2004) reported optimal temperature of 28  C for pollen germination. Suy (1979) found that the rate of pollen tube elongation was near zero below 19  C and above 45  C, and the rate of pollen tube growth was linearly related to temperature up to 37  C, but pollen tube growth declined rapidly above that temperature. Kakani et al. (2005) estimated cardinal temperatures for 12 cultivars and reported as 15.0, 31.8, and 43.3  C (T minimum, T optimum, and T maximum, respectively) for pollen germination and 11.9, 28.6, and 42.9  C for pollen tube length. Weaver and Timm (1988) suggested that pollen is more sensitive to high temperature than other reproductive organs, which could account for a lack of fertilization under high‐temperature stress. The position of the flower on plant canopy can also aVect pollen viability. Burke (2001) demonstrated that pollen harvested in the afternoon from flowers within the canopy had normal pollen viability, while pollen harvested from flowers at the top of the canopy showed a drastic reduction in pollen viability. This diVerential response may be related to lower temperature in the microenvironment due to lower radiation levels. Under controlled experiment, Zeiher et al. (1995) demonstrated that the poor boll set was associated with elevated night temperature. In contrast, night temperature appears to specifically aVect square development either by suppressing the development of the reproductive meristem or by increased abortion of young squares. Hesketh and Low (1968) observed that the late‐maturing varieties were more susceptible to fruit shedding when grown in temperatures above 30  C day and 25  C night. Powell (1969) reported that plants grown at a constant temperature of 29.4  C did not produce viable pollen. Furthermore,

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plants grown at 32.2  C did not set fruit even when pollinated with viable pollen, and it was concluded that night temperature had a more pronounced eVect on fruit set and boll development.

4.

Fruit Growth

Rawson (1992) and Ziska et al. (1997) demonstrated that higher temperatures could accelerate crop development and reduce the time during which carbon (dry matter) is gained. Hodges et al. (1993) observed that most of the shortening of development time occurs during the boll growth period, resulting in smaller bolls, lower yields, and poor quality lint. At high temperature, crop developmental rate will proceed at much faster rate. Accordingly, the time required to produce squares, flowers, and mature fruits was reduced by an average of 1.6, 3.1, and 6.9 day  C
1 of increased temperature, respectively (Reddy et al., 1997c). Furthermore, assuming that temperature increase will be equally distributed throughout the growing season, a 5  C increase in average global temperature should speed development from emergence to maturity by 35 days (Reddy et al., 1997a,b). High temperatures can have a detrimental eVect on boll development. Stockton and Walhood (1960) found that boll size and fiber length decreased with increasing temperatures. Plants exposed to 40  C for 12 h during the fruiting period had less than 1% of the plant mass as bolls (Reddy et al., 1991a). Reddy et al. (1992c) observed that boll weight was greatest at 30/32  C and was less at both higher and lower temperatures; moreover, boll growth was more temperature sensitive than vegetative growth. Reddy et al. (1992a,b,c) reported that above‐optimum temperatures caused considerable problems with boll retention. Furthermore, it was observed that only about 50% of the squares and fruit produced were retained when the average daily temperature was 33  C, and none were retained when the average daily temperature was 36  C. Morris (1964) demonstrated that high temperature shortened the boll maturation period. High temperatures induced square and boll shedding and decreased boll size leading to lower cotton yield (Brown et al., 1995; Reddy et al., 1991a; Zeiher et al., 1995). In the conventional commercial varieties grown in Pakistan, heat‐induced sterility was observed when cotton was sown during May or early June. These crops shed almost all their early bolls and they developed excessive vegetative growth due to loss of fruit (Taha et al., 1981). Gipson and Joham (1968a) observed that low night temperature was negatively correlated with the boll maturation period. High night temperature (25  C) delayed flowering in upland cotton regardless of day temperature (Mauney, 1966). Furthermore, it was observed that both maximum and

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minimum temperatures influenced the first fruiting branch; higher night temperature progressively delayed the appearance of the first fruiting branch. Night temperature generally exerts more impact than day temperature in controlling flowering (Gipson and Ray, 1969).

5. Yield and Fiber Components Brown et al. (2003) proposed that environmental stresses, particularly water deficit, and temperature stress were mainly responsible for year‐to‐year variability in cotton yield (Lewis, 2000). Oosterhuis (2002) observed that high temperature during day, followed by high night temperatures, might exacerbate this detrimental eVect and provide an important cause of yield variability. Temperature eVects on yield are complex; crop responses to changes in temperature depend on the temperature optima for photosynthesis, growth, and yield processes and these optimal values are all diVerent (Conroy et al., 1994; Polley, 2002). When temperature is below the optimum for net photosynthesis, a small increase in temperature can stimulate crop growth. The converse is true when temperature is near the maximum for yield. A small increase in temperature can dramatically reduce yield. Johnson and Wadleigh (1939) reported increases in yields with increases in July average maximum temperature up to 35  C and decreases in yields as the July average maximum temperature exceeded 35  C. All these findings support the concept that there is an optimum temperature for cotton growth and development and growth decreased at temperatures above and below this optimum. However, the optimum temperature was not well defined and may be a characteristic of cultivar diVerences. There was a strong negative correlation between high temperature and cotton yield in Arkansas (Oosterhuis, 2002). Under field conditions, cotton foliage in monsoon (rainy season) nights can be warmer by 4–5  C than foliage during nights of drier times (summer season), which significantly decreases vegetative dry matter production, fruit retention, and lint yield (Brown et al., 1995). Bibi et al. (2003) observed that average maximum temperatures during boll development in the Mississippi Delta are always well above the optimum range (20–30  C). Oosterhuis (1999) reported that there was no sharp threshold, but rather a gradual decline to more than a 50% decrease in boll development at about 32  C. Furthermore, he reported that the overall result of high temperature was insuYcient carbohydrate production to satisfy the plant’s needs. This insuYciency can be reflected in increased boll shedding, malformed bolls (e.g., parrot beak), smaller boll size decreased lint percent, and lower yield. Cotton fiber is made predominantly of carbohydrate, therefore, decreased availability of carbohydrate can also be manifested in less fiber and lower ginning turnout. Excessively

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Table I Correlation of Fiber Quality Parameters with Temperature Fiber trait

Correlation

Fiber length

Negative

Fiber strength

Positive

Fiber strength

Positive

Secondary wall deposition (fiber maturity) Fiber fineness (micronaire increase)

Positive

Positive

Temperature condition

References

DiVerence between maximum and minimum temperature Maximum or mean maximum temperature Heat unit accumulation during boll development Temperature/heat unit accumulation

Hanson et al. (1956)

Heat unit accumulation

Johnson et al. (1997), Bradow et al. (1997)

Hanson et al. (1956)

Snipes and Baskin (1994)

Johnson et al. (1997), Bradow et al. (1996)

high temperature can also decrease seed size, fibers per seed, and fiber length. Oosterhuis (1999) concluded that the end result of high temperature and decreased carbohydrate is fewer seeds, lower fibers per seed, and smaller bolls. The same situation was evident in Arkansas (United States) in 1995 and 1998. The correlations between fiber quality traits and temperatures are given in Table I. Haigler et al. (2005) reported that in central and south Texas, high temperature coupled with water stress during boll filling resulted in relatively short fibers with high micronaire (increase roughness). Bradow et al. (2001) demonstrated that temperature (as cumulative heat units or degree) altered the rates of fiber wall deposition and fiber cross‐sectioned growth and micronaire. The heat units accumulated in the first 50 days after planting had the most significant eVect on micronaire at harvest. The rates of fiber elongation and secondary wall thickening were both influenced by temperature. In experiments with constant growth conditions, Grant et al. (1966) found that the shortest period between flowering and boll opening (41 days) was at 29.5  C. Since secondary wall development in fibers and other epidermal cells of the same cotton seed are synchronous (Berlin, 1977), the temperature‐dependent rate of cellulose synthesis is probably only a part of more general temperature dependence at the level of the cotton boll. Higher temperatures shorten the boll maturation period while incomplete boll maturation is due to low minimum night temperatures (Yfoulis and Fasoulas, 1978).

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Gipson and Joham (1969) and Gipson and Ray (1969) demonstrated that initial stages of fiber elongation were highly sensitive to high night temperatures, whereas the later stages appeared to be less sensitive to temperature. Smutzer and Berlin (1975) confirmed that in upland cotton, var. Dunn, fiber elongation was optimal at 15  C. Night temperatures below 22  C increased the time required for fibers to reach the genetic potential for length of fiber (Gipson and Joham, 1969; Gipson and Ray, 1969). The maximum length of fiber was obtained when night temperatures were between 15 and 21  C, and reduction in length occurred above and below this temperature range (Gipson and Joham, 1968b). Lint index, lint percentage, and lint per boll were decreased by either high (37  C) or low (13  C) night temperatures (Gipson and Ray, 1976). Hesketh and Low (1968) found that among fiber characters the greatest eVect was an increase in fiber strength with increased temperature, along with reduced ginning percentage; however, changes in fiber length and micronaire were less consistent. Seed N content was linearly related with night temperature (Gipson and Ray, 1970; Gipson et al., 1969) and the percent oil tended to respond hyperbolically, with the optimum being near 20  C. 6. Growth Traits It is evident from literature that growth of cotton is highly influenced by temperature. Studies by Jackson (1967) in Sudan (Northeast Africa) revealed that relative growth rate (RGR) and net assimilation rate (NAR) increased with increasing temperature during August through mid‐October, but subsequent decrease in temperature decreased NAR. Rajan et al. (1973) studied the impact of temperature on growth components at the seedling stage within the range of 10–35  C and showed that NAR, leaf area index (LAI), and leaf area ratio (LAR) increased with increasing temperature. Studies by Singh et al. (1987) showed that increasing temperature decreased crop growth rate (CGR) and mean LAI, but improved NAR, specific leaf weight (SLW), and leaf weight ratio (LWR). LAR was, however, not influenced by change in temperature. It appears that if temperature regimes(s) experienced by the crop were supraoptimal it decreased leaf area and biomass production.

B. PHYSIOLOGICAL

AND

BIOCHEMICAL TRAITS

Temperatures that routinely occur in many cotton‐producing regions strongly limit various physiological, biochemical, and growth processes (Reddy et al., 1997a,b,c, 2004, 2005). The most commonly influenced processes include membrane disruption, gas exchange (photosynthesis, photorespiration, stomatal conductance, and transpiration), and translocation.

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Table II EVect on Important Physiological Processes and/or Their Association with High Temperature in Cotton No.

Physiological processes

Impact/Association

1

Crop growth rate (CGR) and maximum and minimum temperature Photosynthetically active radiation (PAR) and maximum and minimum temperature CGR and mean temperature Canopy temperature depression (CTD) and leaf conductance Mean leaf area index and maximum and minimum temperatures Fraction of PAR absorbed (Fp) and maximum and minimum temperatures Photosynthesis (PSII) and high temperature Photorespiration and high temperature Dark respiration and high temperature Stomatal conductance and transpiration

Negative

Bhardwaj and Singh (1991)

Negative

Bhardwaj and Singh (1991)

Positive Positive

Pettigrew and Meredith (1994) Amani et al. (1996)

Negative

Bhardwaj and Singh (1991)

Negative

Bhardwaj and Singh (1991)

Negative

Schrader et al. (2004)

Positive

Krieg (1986) Perry et al. (1983) Guinn (1974); Ludwig et al. (1965) Kolb and Robberecht (1996)

2

3 4 5

6

7 8 9 10

Positive Positive

References

The physiological processes aVecting the overall performance of cotton and their associations with high temperature are presented in Table II. Although most examples discussed are taken from cotton, at places where such information in cotton is not available, the processes are discussed generally and should be put in perspective of cotton. 1.

Membrane Disruption

The plasmalemma and membrane of cell organelles play vital roles in the functioning of cells. Temperature stress on the membranes leads to disruption (Chaisompongopan et al., 1990; Hall, 1993). Horvath et al. (1998) and Orvar et al. (2000) demonstrated that temperature‐induced change in membrane fluidity is one of the immediate consequences during temperature stresses in plants and might represent a potential site of injury. Furthermore, they concluded that membrane fluidity plays a central role in sensing both

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high‐ and low‐temperature conditions. Research on ultra structural eVects of high temperature has focused on chloroplasts because of the extreme sensitivity of many photosynthetic reactions (Paulsen, 1994). Increased thylakoid membrane ionic conductance and ribulose‐1,5‐bisphosphate carboxylase/ oxygenase (Rubisco) deactivation have been suggested as the primary cause that inhibits photosynthesis. Schrader et al. (2004) demonstrated that in dark‐ adapted cotton leaves, heating caused an increase in thylakoid permeability at 36  C. The increased permeability did not cause a decline in adenosine 5‐triphosphate (ATP) levels during steady state or transient heating. Rapid heating caused a transient decline in ribulose‐1, 5‐bisphosphate without a decrease in Rubisco activation. However, sustained heating caused a decline in Rubisco activation and also oxidized the stroma as judged by NADP‐ MDH activation and this is hypothesized to result from increased cyclic photophosphorylation, explaining the maintenance of ATP content in the face of increased thylakoid membrane ion leakiness.

2.

Gas Exchange

Reddy et al. (1995b) observed that net photosynthesis in cotton was less at both higher and lower temperatures than at optimum (28  C). Net photosynthesis decreases with increasing temperature, while dark respiration increases exponentially with increasing temperatures (Bednarz and van Iersal, 2001). Heat stress inhibited CO2‐exchange rate (CER) primarily by decreasing the activation state of Rubisco via inhibition of Rubisco activase (Law and Crafts‐Brander, 1999). Although Rubisco activation was more closely correlated with CER than the maximum quantum yield of photochemistry of photosystem II (PSII), both processes could be acclimated to heat stress by gradually increasing the leaf temperature. High temperature also increases rates of photorespiration (Krieg, 1986), thus reduces net carbon gain in C3 species. Perry et al. (1983) observed that in cotton a linear increase in photorespiration was recorded as air temperature increases from 22 to 40  C at saturating photon flux density. At 22  C photorespiration was less than 15% of net photosynthesis and was comparable to the dark respiration rate. At 40  C, photorespiration represented about 50% of the net photosynthesis. This indicates that temperature is the major factor influencing the ratio of photorespiration to photosynthesis. Arevalo et al. (2004) demonstrated that rates of respiration in the dark were significantly increased in cotton plants grown in elevated night temperatures, and the photosynthetic activity was decreased when measured the next day. Pima cotton was bred for irrigated production in high‐temperature environments. Stomatal conductance in cotton varies genetically over a wide

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temperature range and has increased with each release of new higher yielding cultivars (Radin et al., 1994). In the high‐yielding lines such as Pima S‐6, net photosynthesis was constant between 24 and 36  C. Stomatal conductance, on the other hand, increased linearly with temperature in that temperature range from about 0.55 to about 0.8 mmol m
2 s
1. Since the increase in stomatal conductance at higher temperatures did not result in higher photosynthetic rates, there was no apparent advantage for higher conductance in the advanced lines in terms of carbon gain (Lu and Zeiger, 1994). However, increased stomatal conductance or transpirational cooling is an important trait by which some plants keep their canopy cool and thus potentially avoid heat stress. Therefore, it is important to consider measuring and using tissue temperatures wherever possible. With the emphasis shifted to plant temperature rather than air temperature, all factors that limit evaporative cooling must also be considered important (Radin et al., 1994), particularly water supply and humidity. Diurnal trends of canopy conductance and transpiration were measured at four temperatures (20/12, 25/17, 30/22, and 35/27  C) (Reddy et al., 1995c, 1997a, 2005). Conductance and transpiration rate closely followed the diurnal trend in photosynthetic photon flux density on a cloud‐free day at all temperatures. Canopy conductance and transpiration increased with increasing temperatures from 20/12 to 35/27  C. Canopy water‐use eYciency declined with increased temperature due to increased water loss. Similar observations were observed on leaf‐level stomatal conductance and transpiration rates (Reddy et al., 1998). Leaf stomatal conductance increased as temperature increased from 26/18 to 31/23  C and thereafter further increase to 36/28  C did not influence leaf level stomatal conductance. However, leaf transpiration rates increased linearly with increasing temperatures from 26/18 to 36/28  C. Wright et al. (1993) reported that the genotypes with high transpiration eYciency (TE) had higher assimilation (A). Moreover, the genotypes with thicker leaves (low SLA) had significantly higher nitrogen content, indicative of higher photosynthetic capacity. Similarly, Subbarao et al. (1995) while discussing the basis of variation in TE through SLA (i.e., leaf thickness) pointed out that it might result from a diVerence in photosynthetic capacity on a unit leaf area basis.

3.

Heat‐Shock Proteins

Synthesis and accumulation of proteins during a rapid heat stress is one of the established phenomena. These proteins are designated as heat‐shock proteins (HSPs). It has been reported that increased production of these

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proteins also occurs when plants experience a gradual increase in temperature more typical of that experienced in a natural environment (Abrol and Ingram, 1996). In arid and semi‐arid drylands, crop may synthesize and accumulate substantial levels of HSP in response to elevated leaf temperatures. The induction temperature for synthesis and accumulation of HSPs in laboratory‐grown cotton ranged from 38 to 41  C (Burke et al., 1985). In genetic studies it was observed that HSP expression was cosegregating with heat tolerance (Abrol and Ingram, 1996). Genetic variability in the synthesis of HSP in cereal plants was reported by Ougham and Stoddart (1986), Zivy (1987), and Nguyen et al. (1989). These reports indicate the possibility of using physiological and genetic approaches in studying the role of HSP genes in plants. Plant cells respond to heat stress by rapidly accumulating HSPs. However, there is only correlative evidence for HSPs protecting cells from high‐ temperature stress. There are three main classes of proteins as distinguished by molecular weight of HSP, namely HSP90, HSP70, and low molecular weight (LMW) proteins of 15–30 kDa. The proportions of the three classes diVer among species. Under maximum heat stress conditions, HSP70 and HSP90 mRNAs can increase 10‐fold and LMW proteins increase as much as 200‐fold. Certain proteins, mainly of 15–30, 70, and 90 kDa, are induced in plants at all stages of development by sudden exposure to high temperature. These HSPs are implicated in acquired thermotolerance, maintenance of cell integrity, prevention of protein denaturation, and protection of PSII, but neither these roles nor any involvement in inheritance of high‐temperature hardiness have been documented (Vierling, 1991). Attempts have been made with some success to modify plant thermotolerance by over expressing HSP– protein fusions. Lee et al. (1995) and Hinderhofer et al. (1998) have demonstrated that the basal thermotolerance of Arabidopsis can be increased when HSP‐reporter fusion genes are introduced into plants. The appearance of plant HSP is strongly correlated with the development of stress conditions and acquired thermo‐tolerance (Burke, 2001). The acquired thermo‐tolerance is a complex physiological phenomenon that has been shown to involve some HSPs (Vierling, 1991). Nover et al. (2001) reported that the multiplicity and diversity of heat‐shock factors in plants is greater than in other organisms. Law and Craft‐Brandner (2001) suggested that in response to high temperature, de novo protein synthesis rapidly shifted from mainly expression of Rubisco large and small subunits to the major HSPs. The rigidification of thylakoid membrane, but not the plasma membrane, appears to invoke altered expression profiles of heat‐shock genes suggesting that the temperature‐sensing mechanism could reside in the thylakoid membrane (Horvath et al., 1998). Although varying in magnitude among plant cultivars, most vegetative tissues exhibit an inducible heat‐ shock response. Germinating pollen, however, has not been found to exhibit

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the HSP induction pattern upon exposure to elevated sublethal temperatures, and concomitantly exhibits rapid losses in viability upon heat exposure (Hopf et al., 1992). According to Burke et al. (2004), this may explain Boyer’s observation that those crops with economically valuable reproductive structures show the greatest discrepancy between average and record yields (Boyer, 1982).

III.

HEAT STRESS AND HEAT TOLERANCE A. DEFINITION

AND

LEVELS

OF

HEAT STRESS

Brown (2001) reported that heat stress conditions typically develop during monsoon (rainy) season when high air temperatures combined with rising humidity, thus forcing the canopy temperatures to rise above the optimal range for proper fruit development. Brown (2002) defined two levels of heat stress. Level 1 heat stress develops when crop temperature averages between 28 and 30  C for the 24‐h day. Periods of level 1 stress commonly generate light to moderate fruit shed and smaller bolls. Fruit shed usually subsides rather quickly when the stress is relieved. The impact of level 1 stress on cotton reproductive development is often variable. Possible reasons for this variable response include: relative heat tolerance of varieties, field microclimates (e.g., topography and canopy development), crop condition (e.g., fruit retention and crop vigor), and errors associated with estimating crop temperature. Level 2 heat stress develops when average crop temperature is in excess of 30  C for the 24‐h day. Level 2 stress is the more severe stress and typically produces heavier fruit shed as well as malformed and/or smaller bolls. Fruit shed generally subsides once the stress is alleviated, but level 2 stress also impacts the viability of young (14 days prebloom) squares and thus can produce a second, delayed fruit shed nearly two weeks after the stress episode.

B. HEAT TOLERANCE Hall (2004) defined heat tolerance as where a genotype is more productive than another genotype in environments where heat stress occurs. Heat tolerance can also be defined as the relative performance of a plant or plant process under heat compared with performance under optimal temperature. Resistance to heat is more relevant to the needs of farmers than heat tolerance, whereas heat tolerance often is of interest to scientists studying mechanisms of adaptation. However, there may only be a little or no

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possibility of complete resistance to high temperatures. Heat tolerance is generally associated with cellular mechanisms that facilitate the maintenance of essential plant structures and functions when the tissues are heated to supraoptimal temperatures (Blum, 1988). Fischer and Maurer (1978) partitioned stress eVects on yield (Y) into parameters measuring susceptibility to stress (S), the extent of the stress (D), and yield potential (YP). Y ¼ YPð1
S  DÞ where D ¼ (1
X/XP), and X and XP are the mean yields of all cultivars under stressed and optimal conditions, respectively. With D being a constant for a particular trial, it can be shown that:   Y ðYP
Y Þ ¼ S ¼ 1
YP YP where S is the yield decrease due to stress relative to the potential yield with a low value of S being desirable. Thus S is the inverse of heat tolerance. Greater heat tolerance is defined as a specific plant process being damaged less by high tissue temperature and can involve constitutive eVects or require acclimation (Hall, 2004). According to Paulsen (1994), numerous characteristics that are associated with resistance of plants to high temperature indicate that thermo‐tolerance is highly complex. Stress tolerance to temperature extremes involves complex traits dependent on many attributes. The ability to survive a temperature stress that otherwise would be lethal can be conferred by exposure to a mild nonlethal temperature stress. This induced ability to survive a normally lethal stress is known as acquired thermo‐tolerance (Sung et al., 2003). A heat‐resistant cultivar is defined as one that has higher productivity than other cultivars when grown in environments where heat stress occurs. High tissue temperature may be either an advantage or a disadvantage depending on whether the canopy temperature is above or below optimum temperature (Reddy et al., 1991a,b, 1992a,b).

IV. SCREENING FOR HEAT‐TOLERANCE TRAITS Increases in season‐long average temperature and periodic episodes of heat stress exacerbate the eVect on many aspects of crop growth and development, thereby reducing grain/seed numbers, yield, and fiber content and quality (Reddy et al., 1996). As discussed earlier, diVerent physiological mechanisms may contribute to heat tolerance. In any crop‐improvement

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program, the first and foremost requirement is to identify the suitable stock(s) to be used in breeding. Therefore, it is imperative to use cost‐ eYcient and reliable techniques to screen the available germplasm for various ecophysiological, morphological, and reproductive traits to assist their utilization in crop‐breeding programs. Breeding programs may measure such traits to assist in the selection of heat‐tolerant parents, segregating generations or advanced lines (Reynolds et al., 2001). A brief description of some new emerging ecological, morphological, and physiological techniques, which are being used in many crop improvement programs particularly at various international crop improvement centers (mainly CIMMYT and IRRI) and other national research centers, are discussed in this section. Several methods in both field and controlled‐environment facilities are commonly being used for screening heat tolerance. Field studies are more advantageous than controlled environment as they represent the true nature of the farmer’s and breeder’s field conditions. However, the major limitation is the lack of control of the environment, which makes the screening process diYcult. Multilocation tests to obtain variable temperature environment should be used for field evaluation of the genotypes for tolerance. Keeping in view the limitations of field studies, several studies are conducted in controlled environment, mainly greenhouses and growth chambers for evaluation of heat tolerance. In such conditions, it is recommended to use a natural soil profile rather than doing pot studies. According to Hall (2004), when plants growing in pots are subjected to high air temperatures, both the shoot and the roots are subjected to hot conditions. In contrast, when plants growing in the field are subjected to high air temperatures, the shoot is subjected to more extreme temperatures than the root system. In field conditions, temperature of the soil below 10 cm is buVered and does not warm as much or cool as much as the air. Consequently, using plants in pots, when studying eVects of heat stress can subject roots to unnaturally high temperatures and generate artifacts. However, these controlled environments can be used for preliminary screening but it will be important to also test the performance of the genotypes identified under controlled condition in field conditions before they are used extensively in the breeding programs.

A. PHYSIOLOGICAL 1.

AND/OR

BIOCHEMICAL TRAITS

Cellular Membrane Thermostability

High temperature modifies membrane composition and structure and can cause leakage of ions. Membrane disruption also causes the inhibition of processes such as photosynthesis and respiration. Alexandrov (1964) concluded that thermostability is determined by the ability of plants to harden in

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response to high temperature and resist injurious metabolic changes at moderately high temperature, resistance of protoplasmic proteins to denaturation at extremely high temperature, and reparatory capacity of cells after injury. Stability of proteins and other macromolecules may be conveyed by very minor changes in amino acid residues, hydrogen bonds, hydrophobic interactions, addition of glycolic unit, and net free energy of stabilization (Brock, 1985). Sullivan (1972) developed a heat‐tolerant test that determines cellular membrane thermostability (CMT) through measuring the amount of electrolyte leakage from leaf disks bathed in deionized water after exposure to heat treatment. Later modification to this method has also been proposed for specific crops. Blum and Ebercon (1981) used this technique to measure both heat and drought tolerance in wheat. Electrical conductivity of exudates from tissues disks, which is usually expressed as the ratio of values at experimental and lethal temperatures, measures the CMT to stress (Blum and Ebercon, 1981). Some studies showed that these results were similar and associated with field performance (Saadalla et al., 1990a). The method might be less applicable to plants at younger stages than at mature stages; however, cell membranes are less sensitive than thylakoid activities to high temperature in young plants, whereas their liability increases during maturation (Paulsen, 1994). Bibi et al. (2003) demonstrated that membrane leakage was the most sensitive technique for quantifying temperature tolerance in cotton under field conditions. Cell membrane thermal stability has been used as a measure of heat tolerance in several other crops, including rice (Tripathy et al., 2000), soybean (Martineau et al., 1979), potato and tomato (Chen et al., 1982), and cotton (Kakani et al. (2005). CMT in rice was used as a major selection index of drought tolerance in cereals (Tripathy et al., 2000). The use of CMT to measure heat tolerance has been successful in cowpea (Hall, 2004). Genetic experiments conducted by Thiaw and Hall (2004) confirmed that leaf‐electrolyte‐leakage (LEL) under heat stress was negatively correlated with heat tolerance for pod set in cowpea. The LEL protocol (Thiaw, 2003) consisted of subjecting leaf disks to 46  C for 6 h in aerated water, then measuring electrical conductivity of the solution followed by boiling the leaf disks, and then measuring the electrical conductivity of the solution again. The percent leakage during heat stress was calculated from the two measurements. Blum (1988) and others have proposed that plants should be heat‐hardened prior to sampling the tissue, and four measurements of electrolyte leakage should be used in calculating CMT. An advantage of the LEL method used by Thiaw (2003) over the CMT method used by Blum et al. (2001) is that samples for the LEL method can be taken from plants growing in any field nursery or glasshouse without the need for acclimated plants. Also, only two measurements of electrolyte leakage are needed with the LEL method, so more plants can be evaluated than with the CMT method which requires four measurements.

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The LEL protocol (Thiaw and Hall, 2004) has an advantage over direct selection that it can be conducted in the oV season with plants grown in moderate temperatures. Thiaw and Hall (2004) proposed an improved method for breeding heat‐resistant cowpeas. This method consists of direct selection for abundant flowering and pod set in very hot summer field nurseries or glasshouses, followed by indirect selection using slow LEL in the fall and winter with plants grown under moderate temperatures in greenhouses. However, some studies did not show strong correlation between CMT with reproductive traits such as pollen viability and seed set in several cultivars of peanut (Kakani et al., 2002), cotton (Kakani et al., 2005), and rice (Prasad et al., 2006). Recent studies on cotton showed that CMT was positively and significantly correlated with biomass and yield under stress conditions but not with biomass or yield under nonstress conditions (Rahman et al., 2004). Blum et al. (2001) observed that the associations between CMT and yield under heat stress were reasonably strong and significant but not perfect. Furthermore, they reported that other factors besides CMT may support yield under heat stress, and that CMT alone cannot be used as the criterion in the ‘‘final breeding stage’’ or as a rough selection tool to reduce a large population into the most likely heat‐tolerant core at the early stages of the breeding program.

2.

Chlorophyll Content

Reynolds et al. (1994) exhibited physiological evidence indicating that loss of chlorophyll during grain filling was associated with reduced yield in the field of wheat. Wardlaw et al. (1980) and Blum (1986) demonstrated the presence of genetic variability under controlled environmental conditions among wheat cultivars when exposed to high temperature. Similarly, Al‐Khatib and Paulsen (1984) and Harding et al. (1990) detected similar diVerences in photosynthesis under heat stress that were associated with a loss of chlorophyll and changes in the ratio of chlorophyll a to b. Pettigrew et al. (1993) showed that the higher assimilation in cotton cultivars with ‘‘okra’’ shaped leaves to had a high SLW (g m
2 leaf area) and higher leaf chlorophyll concentration compared with ‘‘normal’’ leaf cultivars. They postulated that the genotypic diVerences in assimilation were due to a higher concentration of the photosynthetic apparatus per leaf caused by increased leaf thickness. In drought experiments, it was reported that the cotton lines having the highest carbon isotope discrimination values also had the lowest chlorophyll a and b contents (Cohen, 2001; Saranga et al., 2004). High seed cotton‐producing lines were characterized by low canopy temperature and high chlorophyll a. There were strong correlations between chlorophyll a and dry matter production under both

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water‐limited and well‐watered treatments of cotton (Saranga et al., 2004). Reynolds et al. (2000) observed high leaf chlorophyll content in the Mexican wheat landrace collection where the best genotypes showed substantially greater leaf chlorophyll concentration than the standard check. They also established that while high chlorophyll content does not guarantee heat tolerance. However, stay‐green trait has been associated with heat tolerance in wheat and similarly high chlorophyll content was associated with heat tolerance of sister lines in some wheat crosses (Reynolds et al., 1997).

3.

Chlorophyll Fluorescence

Chlorophyll fluorescence emission kinetics from plants provides an indicator of plant photosynthetic performance (Kaustsky et al., 1960). Siebke et al. (1997) demonstrated that fluorescence parameters were related directly to the photosynthetic CO2 assimilation rate of leaves. The sensitivity of chlorophyll fluorescence to perturbations, in metabolism coupled with the ease and speed of measuring chlorophyll fluorescence, makes fluorescence a potentially useful for noninvasive screening to identify metabolic disturbances in leaves. The ratio of variable to maximum fluorescence (Fv:Fm) of PSII measures the eYciency of excitation energy captured by PSII. Decrease in Fv:Fm indicates an increase in the nonphotochemical quenching of PSII excitation energy, and Fv:Fm can be used to monitor responses to environmental stress (Warner and Burke, 1993). The main drawback in part to use chlorophyll fluorescence has been the small sampling area of commercially available fluorimeters that use fiber optics for collecting fluorescence emissions. Recently, the development of chlorophyll fluorescence imaging systems that can image fluorescence parameters from areas in excess of 100 cm2 has allowed the application of the technique for the screening of many plants simultaneously. Fv:Fm estimates the maximum quantum eYciency of PSII photochemistry (Butler, 1978). As Fv:Fm is a widely used parameter that estimates the maximum quantum eYciency of PSII photochemistry and can be determined in less than a second, Barbagallo et al. (2003) suggested that this should be the preferred parameter for screening where possible. They also demonstrated that a strong correlation exists between Fv: Fm and the leaf area exhibiting chlorophyll fluorescence. Hall (2004) suggested that for crops where the limiting eVect of heat stress involves damage to photosynthesis, there is some merit in trying measurements of chlorophyll fluorescence as an indicator of damage to PSII. Equipment is available that permits rapid field measurement of the Fv:Fm parameter which provides an estimate of the damage to PSII. For this approach, also, key tests have not yet been reported for any species that demonstrate whether selection based on chlorophyll fluorescence is eVective in enhancing heat tolerance.

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It should be noted that when determining whether a selection method is eVective it is also necessary to determine the eYciency of the method: the costs of the selection procedure in relation to the gains that are compared with other selection procedures. Bibi et al. (2003) showed significant diVerences between the obsolete and modern cultivars only at 30.5  C for chlorophyll fluorescence. This technique showed some sensitivity for quantifying temperature tolerance in that it is a much easier technique for field use. MoVat et al. (1990) suggested that chlorophyll fluorescence may be more promising as a screening trait, given that association between plant tolerance and lower fluorescence signals have been reported in a number of crops, including wheat. Images of fluorescence parameter (Fv:Fm) have been widely used to detect stress in plants (Maxwell and Johnson, 2000). Jiang and Huang (2000) demonstrated that under the combined drought and heat stresses, the reduction in Fv:Fm was correlated with that of net photosynthesis. The interaction of drought and heat caused more rapid and severe damage to the photochemical eYciency of PSII than either stress alone, similar to the eVects on net photosynthesis.

4.

Carbon Isotope Discrimination

There are two naturally occurring stable isotopes of carbon, 12C and 13C (Farquhar et al., 1989). Most of the carbon is 12C (98.9%), with 1.1% being 13 C. The overall abundance of 13C relative to 12C in plant tissue is commonly less than in the carbon of atmospheric CO2, indicating that carbon isotope discrimination occurs during the incorporation of CO2 into plant biomass. This fractionation between 13C and 12C is caused by diVerences in the diVusivities in air between the heavier and lighter isotope and by the initial carboxylating enzyme (Rubisco) which discriminates against heavier isotope. Carbon isotope analysis integrates the ratio of stable isotopes of carbon (13C:12C) across the life of plant tissue being analyzed. There are strong negative correlations between carbon isotope discrimination (D) and water‐use eYciency in several plant species (Craufurd et al., 1999; Farquhar and Richards, 1984; Farquhar et al., 1989; Wright et al., 1993). The underlying principle of negative relationship is related to stomatal conductance (Farquhar et al., 1989). As water becomes limiting, stomatal closure occurs, therefore, discrimination against 13C decreases as water stress increases because the ratio of 13C:12C increases in stressed leaves of C3 plants, and Rubisco has less opportunity to discriminate (Farquhar et al., 1989). The carbon isotope discrimination has not been used to study the eVects of high temperature alone or in combination with water stress, despite the fact that heat stress is an important component of drought stress (Williams and Boote, 1995).

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Stable carbon isotope discrimination diVerences among cultivated Pima cotton lines were positively associated with degree of selection for lint yield and heat resistance (Lu et al., 1996). Similarly, Saranga et al. (2001) demonstrated that the relatively large quantitative trait loci (QTL) associated with carbon isotope discrimination may help to identify the important physiological traits that contribute to stomatal conductance/photosynthetic capacity relationships under heat and other abiotic stresses.

B. ECOPHYSIOLOGICAL TRAITS 1.

Aerodynamic Resistance

Aerodynamic resistance of a crop plays a major role in determining the relative importance of stomatal conductance to TE. If the canopy resistance to heat and water vapor diVusion is large, an increase in stomatal conductance would tend to cool and humidify the air in the boundary layer, thus lowering the leaf‐air vapor pressure deficit (VPD); TE would then increase (Farquhar et al., 1989; Reddy et al., 1991b). Thus, cultivars with greater stomatal conductance could assimilate more at the same level of TE (Cowan and Farquhar, 1977; Farquhar et al., 1988). Under field conditions, the boundary layer that forms over crop canopies could cause gas exchange to be less dependent on stomatal conductance, and is thus one of the important factors aVecting TE (Jarvis and McNaughton, 1982). A plant with high TE may be able to decrease the aerodynamic conductance of its canopy boundary layer through greater rigidity of the canopy, while maintaining a high stomatal conductance (Walker and Lance, 1991). Boundary layer resistance at the canopy level depends on canopy architecture, which is determined by leaf size, leaf arrangement, growth habit (i.e., prostrate vs erect), and height of the canopy. With a low canopy conductance, leaf water equilibrates with adjacent airspace of higher humidity than the bulk atmosphere (Walker and Lance, 1991). O’Toole and Real (1986) have shown that aerodynamic resistance and canopy resistance to water vapor transfer can be determined from the linear relationship of diVerence between canopy and air temperature (Tc
Ta) and VPD. Change in either aerodynamic resistance or stomatal resistance among cultivars would influence canopy temperature through an eVect on either sensible or latent heat exchanges. Cultivars with warmer canopy temperature, given that all other conditions are equal, will have decreased evapotranspiration (Hatfield et al., 1987). They reported that consistent canopy temperature diVerences occurred among cotton varieties grown in the irrigated plots even though the environmental conditions varied. In the dryland plots, canopy temperature showed significant cultivar‐by‐day interaction suggesting that

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some varieties use available soil water faster than other varieties. Those varieties, which had warmer canopies in the irrigated plots, had the larger biomass in the dryland plots. Hatfield et al. (1987) reported that leaf conductance was positively correlated with leaf water potential (c), which indicates that leaf conductance diVerences among the varieties were influenced by the leaf water status and by factors causing increased canopy temperature and decreased leaf conductance that may have a positive eVect on growth. Canopies that were warmer had lower leaf conductance, which would result in decreased transpiration, for example, 10% reduction in evapotranspiration induces a canopy with a temperature 1.5  C warmer than another (Hatfield et al., 1987). They observed maximum potential diVerences in evapotranspiration rates of 13%. The decreased transpiration rate in the warmer environment should decrease the rate of water uptake from the profile and increase the period of water availability to the plant.

2.

Quantification of Stress Index Using Canopy Temperature

Leaf, foliage, and canopy temperatures have excited plant physiologists and atmospheric physicists alike for more than 100 years (Jackson, 1982). Tanner (1963) stated that plant temperature might be a valuable qualitative index to diVerences in plant water regimes. In the last 25 years, there has been rapid development in the use of foliage temperature to quantify plant stress. Several indices have been developed based on the comparison of midday foliage and air temperature and their diVerential. a. Canopy Temperature Depression. The diVerence between air and foliage temperature is referred to canopy temperature depression (CTD). The ability of the plant to decrease temperature through transpirational cooling will keep the plant cool and benefits plants at above optimal stress conditions. As much as 10  C diVerence between air and leaf temperatures have been reported in cotton (Burke and Upchurch, 1989). Hatfield et al. (1987) demonstrated that canopy temperature of field‐grown cotton tracked air temperature at night and became cooler than air temperature each morning when the leaf temperature approached 27.5  C. This temperature was approximately midpoint of an identified thermal kinetic window (TKW) (Burke and Upchurch, 1989). Mahan et al. (1995) reported that various factors including leaf area, root to leaf ratio, leaf orientation, size and shape, surface characteristics (e.g., pubescence), leaf thickness and size, and distribution of stomata are known to aVect transpiration. Nobel (1999) reported that the sun tracking of leaves could reduce their temperature by

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up to 6  C. Accordingly, small leaf has thinner boundary layer that is more conducive to sensible and latent heat transfers and as a consequence is often cooler than bigger leaves in similar environments. CTD has been used to quantify stress within a given species (Idso et al., 1981; Jackson et al., 1981). In cotton, the relationships among canopy temperature, VPD, and stress have allowed the development of crop stress indices. Amani et al. (1996) reported that for a given genotype, CTD is a function of a number of environmental factors, principally soil water status, air temperature, relative humidity, and incident radiation. Moreover, they have also demonstrated that the trait is best expressed at high VPD conditions associated with low relative humidity and warm air temperature. The relative importance of the characteristic of individual leaves decreases as the plant canopy becomes denser. Under these conditions the aerodynamic characteristics of the canopy play a major role in the energy transfer between the plant and environment. Ham et al. (1991) and Mateos et al. (1991) studied the eVect of canopy closure on the energy balance of plants and concluded that rapid closure of the canopy will reduce the occurrence of high leaf temperature. b. Crop Water Stress Index. Initially stress degree day (SDD) was defined as the diVerence in foliage and air temperature (Idso et al., 1977; Jackson et al., 1977) to account water stress of crops. Later, Idso et al. (1981) incorporated VPD to account for diVerences among environments and the concept of crop water stress index (CWSI) was refined to include this parameter. Ehrler (1973) concluded that using leaf‐air temperature diVerences for scheduling irrigations in cotton was useful. Ehrler et al. (1978) demonstrated that the diVerence in leaf and air temperature of well‐irrigated cotton and wheat was linearly related to VPD of the atmosphere 1 m above the crop canopy. Idso et al. (1981) and Idso (1982) confirmed this observation at four diVerent locations in the United States and further illustrated that a unique linear relationship between canopy‐air temperature (Tc
Ta) and VPD could be found for 26 agricultural crop species. The relationship between canopy temperature, air temperature, and transpiration is not simple and involves atmospheric conditions (VPD, air temperature, and wind velocity), soil (soil moisture), and plant morphophysiological characteristics (canopy size, canopy architecture, and leaf adjustment to water deficit). These variables are considered when canopy temperature is used to develop the CWSI. The CWSI is a measure of the relative transpiration rate occurring from a plant at the time of measurement using a measure of plant temperature and VPD (refers to dryness of the air). Jackson et al. (1981) presented the theory behind the energy balance that separates net radiation from the sun into sensible heat that heats the air, and latent heat that is used for transpiration. The CWSI incorporates midday values of net radiation, canopy

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and air temperature, VPD, aerodynamic resistance, and canopy resistance into an energy balance for a crop surface. The CWSI has been related to yield in cotton (Burke et al., 1990). When a plant is transpiring fully the leaf temperature is 1–4  C below the air temperature and CWSI is zero. As the transpiration decreases, the leaf temperature rises and can reach to 4–6  C above the air temperature. When the plant is no longer transpiring the CWSI is 1. However, O’Toole and Hatfield (1983) found that wind speed influenced the canopy to air temperature diVerence. Some researchers (Hatfield, 1985; Wanjura et al., 1984) demonstrated that the unstressed baseline of cotton for the CWSI varies slightly from those initially defined by Idso et al. (1981). Keener and Kircher (1983) studied the eVectiveness of SDD, water stress index, and CWSI which were developed for arid or semi‐arid regions. It was demonstrated by these authors that CWSI would be of limited utility under humid conditions. Jackson et al. (1981) also acknowledge the potential problems in humid environments and pointed out that the occurrence of leaf temperature warmer than air temperature presents a limitation of any of the current canopy temperature‐based stress indices. c. Thermal Stress Index. The CWSI method often exhibits values below 0 and above 1 in areas with VPD below 1.0 kPa. This eVect is due to the limitations in resolving diVerences in Tc and Ta in regions of high humidity as reported by Burke et al. (1990). These authors stressed that the impact of changing air temperature on plant growth and performance can be understood only when the temperature providing optimum enzyme function is known. Burke et al. (1988) reported that the temperature range for which the value of the apparent Km remained within 200% of the minimum observed value was defined as the TKW for optimum enzyme function. For crop plants, the TKW is generally established as a result of thermally induced lipid phase, changes in Rubisco activity, and the starch synthesis pathway in leaves and reproductive organs. The temperature response curves for recovery of PSII fluorescence following illumination compare favorably with the TKW in several crop species (Burke, 1990). Overall, the TKW is useful in defining the bounds of thermal stress in plants and exploring the genetic improvement of heat tolerance using a molecular approach (Nguyen, 1994). Burke and Upchurch (1989) found the TKW for cotton is 23.5–32  C through the relationship between leaf and air temperatures and plant water use. Burke et al. (1988) demonstrated that canopies of both wheat and cotton were only within their TKW for approximately 30% of the growing season in west Texas. The length of time the plant temperature was within the TKW was related to biomass production. Furthermore, Burke et al. (1990) suggested the potential use of the crop‐specific biochemical temperature optimum (the midpoint temperature 27.5  C of the TKW for cotton)

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as baseline temperature for a TSI. The formula for TSI suggested by the author is TSI ¼

ðTf > Tb Þ Tb

where Tf is foliage temperature and Tb is the biochemically determined base line temperature of 27.5  C. The values of TSI range from zero to some positive limit and are restricted to a thermal stress resulting from an inability of the plant to cool either because of soil water deficit or because of physical limitation to cooling resulting from high humidity levels. The biochemical‐ based TSI and the physically based CWSI were highly correlated (r2 ¼ 0.92) for cotton across a range of environmental conditions.

C. ASSOCIATION AMONG ECOPHYSIOLOGICAL, MORPHOLOGICAL, AND YIELD TRAITS In any breeding program the knowledge of association among diVerent traits is of paramount importance. The information generated from character association studies can be utilized to determine the correlated response (if any) and to decide the breeding methodology/strategy for the successful incorporation of useful traits in optimum combination. The association among various ecophysiological, morphological, and yield components reported elsewhere is summarized in this section and presented in Table III. Feaster and Turcotte (1985) reported a highly significant negative correlation (r2 ¼ 0.79) between fruiting height and yield. Empirically the first fruiting nodes number has been associated with earliness of a particular genotype. Again earliness has been found to be negatively correlated with yield in Pima cotton. Temperature is an important factor modulating the interrelationship(s) of the above parameters. Bhardwaj and Singh (1991) demonstrated that CGR is positively correlated with photosynthetically active radiation (PAR) (absorbed), fraction of photosynthetically active radiation absorbed (Fp), and mean LAI but negatively with maximum and minimum temperatures. On the other hand, PAR absorbed is correlated positively with Fp and LAI but negatively with maximum and minimum temperatures. Furthermore, LAI and Fp also had negative correlation with temperature (maximum and minimum), and Fp was correlated negatively with SLW. Pettigrew and Meredith (1994) reported that CER was positively correlated with N fertilization (r ¼ 0.768) and SLW (r ¼ 0.568). CGR was correlated positively with light utilization eYciency (LUE) along with LAI, mean temperature, and SLW. CGR possesses a positive correlation with

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Table III The Association Among Eco‐Morpho‐Physiological Parameters and Yield

No.

Parameters

Association with yield

1

Cell membrane thermostability (CMT)

Positive

2

Canopy temperature depression (CTD) Leaf and stomatal conductance Crop water stress index (CWSI) Thermal stress index Carbon isotopes discrimination diVerences Leaf chlorophyll content

Positive

8 9 10

Stay‐green eVect Chlorophyll fluorescence Dark respiration

Positive Positive Negative

11

Photosynthesis

Positive

3 4 5 6 7

References

Positive

Bibi et al. (2003), Rahman et al. (2004), Reynolds et al. (2001), Saadalla et al. (1990b) Idso and Reginato (1982), Reynolds et al. (1998) Amani et al. (1996), Lu et al. (1994) Burke et al. (1990)

Positive Positive

Burke et al. (1990) Lu et al. (1996)

Positive

Reynolds et al. (2001), Saranga et al. (2004) Reynolds et al. (2001) Bibi et al. (2003) Oosterhuis et al. (2002), Hodges et al. (1991) Lu et al. (1994), Reynolds et al. (2001)

Positive

LUE and mean LAI (Bhardwaj and Singh, 1991). They speculated that the crop follows the same strategy to combat higher temperatures. When temperatures approach 41/30  C (maximum and minimum, respectively) leaf area growth ceases and is followed by no crop growth (i.e., zero CGR) at 42/31  C. Photosynthesis is evenly balanced by respiratory activity (i.e., compensation point). PAR was not absorbed by the crop at 43/32  C whereas light interception ceases at 46/34  C. At this stage the crop would register negative growth owing to stoppage of photosynthesis but continuation of photo and dark respirations. Abrol and Ingram (1996) reported that correlation between synthesis and accumulation of HSPs and heat tolerance suggests, but does not prove that the two are causally related. Cell membrane thermostability was found to be highly correlated to heat stress at the seedling and anthesis stages in cotton (Saadalla et al., 1990b). However, it was observed that there is no correlation between CMT and tolerance during anthesis particularly related to pollen germination and tube growth of cultivars which had higher temperature optima and greater pollen germination (Kakani et al., 2005). It was shown that in cotton, heat tolerance does not correlate with degree of lipid

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saturation (Rikin et al., 1993). Similar observations in genotypes of other crops species in relation to heat tolerance and membrane lipid were reported (Kee and Nobel, 1985). Idso et al. (1984) established a strong correlation of CTD with yield. Similarly, Reynolds et al. (1998) observed that CTD had high genetic correlation with yield and high values of proportion of direct response to selection indicating that the traits are heritable and therefore, amenable to early generation selection. Since CTD is directly or indirectly aVected by a number of physiological processes, it is a good indicator of genotype fitness in a given environment. CTD and leaf conductance show an association with each other and with yield (Amani et al., 1996). The possibility of coupling selection for both traits is attractive. Reynolds et al. (2001) suggested that CTD could be used to select among early generation bulks that are heterogeneous and may still be segregating. CTD also seems to be aVected by the ability of a genotype to partition assimilation to yield and is indicated by the fact that CTD frequently shows a better association with yield (Reynolds et al., 2001). Radin et al. (1994) reported a positive relationship between photosynthetic rate and stomatal conductance in the low range of conductance values up to about 0.4 mmol m
2 s
1, but apparent relation at higher conductance values, and therefore, failed to support the hypothesis that the observed variation in stomatal conductance was mediated by variation in photosynthetic rates. There is a strong correlation between assimilation and stomatal conductance over a wide range of cultivar of plant species and under a diversity of environmental conditions (Wong et al., 1979). Reynolds et al. (1994) demonstrated that loss of chlorophyll during grain filling is associated with reduced yield of wheat. The diVerence in photosynthesis under heat stress has been shown to be associated with a loss of chlorophyll and a change in the chlorophyll a:b ratio due to premature leaf senescence (Al‐Khatib and Paulsen, 1984; Harding et al., 1990). The CTD which is a function of stomatal conductance (Amani et al., 1996) is a mechanism of heat escape in cotton (Cornish et al., 1991). Under high‐temperature conditions the respiration costs are higher, leading eventually to carbon starvation because assimilation cannot keep pace with respiratory losses (Levitt, 1980). This process would seem unavoidable, as evidenced by the positive association recorded between dark respiration at high temperature and heat tolerance in sorghum lines (Gerik and Eastin, 1985). On the other hand, high rates of respiration may be severely detrimental to yield in wheat (Wardlaw et al., 1989) and cotton (Hodges et al., 1991; Oosterhuis et al., 2002). Reynolds et al. (1998) demonstrated that there is positive association between heat tolerance and both leaf respiration and CMT; thereby indicating that nonphotosynthetic cellular metabolism is

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associated with sensitivity to warmer environments in wheat. Significant positive genetic correlations between wheat yield and CTD, CMT and leaf chlorophyll during grain filling, leaf conductance and photosynthesis have been reported under heat stress conditions (Reynolds et al., 2001). A strong positive correlation has been observed between carbon isotope discrimination and specific leaf area among groundnut genotypes (Rao and Wright, 1994). This is consistent with the hypothesis that high TE genotypes have higher assimilation. Indeed, the genotypes with thicker leaves (low SLA) had significantly higher leaf nitrogen contents, again indicative of higher photosynthetic capacity. The significant application of these observations is that breeders could use the inexpensively measured specific leaf area in lieu of carbon isotope discrimination, to screen for high TE among genotypes within a specific environment (Craufurd et al., 1999; Wright et al., 1993). Correlated traits such as specific leaf area, which has been shown to be related with carbon isotope discrimination, could thus be used as a surrogate to 13C discrimination analysis (Craufurd et al., 1999; Subbarao et al., 1995). El‐Sharkawy et al. (1965) found a negative correlation between leaf thickness and CER among several cotton species. Reddy et al. (1992c) observed that flower retention was negatively associated with the number of hours per day the plants were exposed to 40  C. Ehlers and Hall (1996) reported the association present between reproductive‐ stage heat tolerance and extreme earliness. Ahmed et al. (1993) speculated that this association may be due to heat susceptibility being caused by certain phytochromes that also cause late flowering. This association between extreme earliness and heat tolerance has been observed in other species. McDonald and Stith (1972) had seen simple correlations between maximum temperature at 17 days preanthesis and sterility. Fisher (1973) did not find significant correlations between boll set and maximum temperature, though he observed highly significant negative correlations between boll set and minimum night temperature. Yfoulis and Fasoulas (1973) observed a negative correlation between the 24‐h cycle mean temperature and boll period and genetic responses to temperature changes. Oosterhuis (1997) observed a strong negative correlation between yield and temperature in August when boll development occurs. Cotton canopy architecture, particularly with respect to plant height and branch formation, is modified temperature (Hanson et al., 1956; Reddy et al., 1990, 1997c). Higher temperature can have significant negative impact on photosynthesis, reduced photosynthetic rates, and the modulation of other metabolic factors, in association with lower light intensities, may result in lower micronaire, fiber strength, and yield (Pettigrew, 1996). The micronaire reading of fiber produced in the warmest environment was highest (Quisenberry and Kohel, 1975).

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V. BREEDING FOR HIGH‐TEMPERATURE TOLERANCE A. TRAIT SELECTION Nasyrov (2004) emphasized that the selection of plants on a physiological and genetic basis will make it possible to get varieties and hybrids with high photosynthetic eYciency and a balanced ratio between source and sink that will provide the maximum expression of yield potential. This task cannot be solved by geneticists alone because it is necessary to overcome the accursed negative correlation between yield and plant resistance. Tolerance to high soil temperatures during seed germination would appear to require constitutive genetic eVects; although the mother‐plant environment during seed development and maturation can influence the heat tolerance of seed during germination. Tolerance to high tissue temperatures during plant emergence and early seedling growth involves both constitutive and acclimation eVects. Seedlings subjected to moderately high temperatures synthesize a novel set of proteins that have been called HSPs, and the plants become more tolerant, in terms of plant survival, to more extreme temperatures (Vierling, 1991). These proteins are thought to enable cells to survive the harmful eVects of heat by two general mechanisms: as molecular chaperones and by targeting proteins for degradation. As an example of chaperone activity, it has been shown that a specific small HSP cooperates with other HSPs to reactivate a heat‐denatured protein (Lee and Vierling, 2000). HSPs do not appear to be the only mechanism whereby plants diVer in heat tolerance (Hall, 2004). In cotton, Rahman et al. (2004) reported that CMT could be a useful technique for diVerentiating heat‐tolerant and heat‐susceptible cottons; however, they cautioned regarding its indirect selection on the basis of seed cotton yield under non‐heat‐stressed environments. While working on the development of heat‐tolerant Pima cotton cultivars in the late 1950s in Arizona, several indices were developed to select the heat‐ tolerant Pima cotton genotypes (visual index in 1962, and phenotypic index and fruit‐height response index in 1964). Feaster and Turcotte (1985) concluded that fruiting‐height response at low elevation in Arizona was an eVective indicator of heat tolerance. The lower fruiting genotypes have greater heat tolerance since they are capable of fruiting well during July and August when minimum night temperatures are high. Faver et al. (1996) suggested that a genetic base may exist for improving the photosynthetic capacity, and genetic diVerences have been reported in the rate of carbon assimilation in cotton. Light distribution can be aVected by the species of cotton (Sassenrath‐Cole, 1995). Upland cotton exhibited regular leaf shapes throughout the growing season and was diaheliotropic. Pima cotton leaves were large and fairly flat early in the season, but progressively

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became more cupped at increasing main stem positions and showed no heliotropic response. As a result of the solar‐tracking response and leaf shape, the canopy light environment diVered for two species. Genotypic diVerences in CER could be due to a greater concentration of photosynthetic apparatus per unit leaf area caused by leaf thickness diVerences. Genetic diVerences in photosynthetic capacity may be detected indirectly by selecting for leaves that have more dry weight per unit leaf area, because they usually have higher levels of photosynthetic enzymes and photosystem components per unit leaf area (Hall, 2001). The functional relationship between smaller leaf areas and higher yield potential and heat resistance is also of interest. Boundary layer resistance and heat transfer are markedly dependent on leaf dimensions (Nobel, 1991). Use of the energy balance model to stimulate the eVect of leaf width on leaf temperature at high irradiance and high stomatal conductance showed that leaf temperature decreases with width (Lu et al., 1992) thus, the smaller leaf area of the advanced Pima lines might contribute to their enhanced heat resistance (avoidance). It is of interest that leaves from the more productive upland cotton are smaller than leaves from Pima S‐7, the commercial Pima line currently in use. In contrast, the stomatal conductance, which was uniformly high in all elite lines. This observation suggests that selection pressures for higher stomatal conductance have been stronger than those for leaf area. Lu et al. (1997) suggested that higher stomatal conductance and photosynthetic rate and smaller leaf areas are functionally important for the attainment of higher heat tolerance and yields. Pettigrew et al. (1993) suggested that photosynthetic rate could be a selection criterion for plant breeders especially if lines with superior photosynthesis could be identified and coupled with those lines with suitable partitioning of photosynthates between reproductive and vegetative growth. Establishing why certain lines may diVer in photosynthetic rate could provide more tools for selection. Plant breeders can use photosynthetic rate as a selection criterion for improved lines. These improved lines in turn could be crossed with other lines that possess suitable partitioning of photosynthates between reproductive and vegetative growth (Pettigrew and Meredith, 1994). Significant negative correlation has been shown between photosynthetic capacity and specific leaf area (DornhoV and Shibles, 1976). According to Subbarao et al. (1995), this evidence suggests indirectly that basis of variation in TE through specific leaf area (i.e., leaf thickness) may result from diVerence in photosynthetic capacity on a unit leaf area basis. El‐Sharkawy et al. (1965) reported the presence of significant genetic diVerences in photosynthetic rate in cotton and suggested the possibility of diVerences in ratio of photosynthesis to photorespiration. The extent to which respiration can be increased through selecting for leaf traits that influence photosynthesis is controversial (Evans, 1983). However,

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some studies reported that increasing productivity of wheat, cotton, and soybean was positively associated with stomatal conductance and photosynthetic rate (Condon and Hall, 1997; Fischer et al., 1998; Lu et al., 1998; Morrison et al., 1999). Lu et al. (1996, 1998) concluded decisively that independent selection pressure exists independent of photosynthetic rates for higher stomatal conductance and for a relationship between stomatal conductance and yield. Radin et al. (1994) emphasized that one cycle of selection solely for conductance from a segregating population led to decreased leaf temperature and enhanced yield. Furthermore, they reported that the stomatal component of heat resistance was apparently dependent upon evaporative cooling. This represents a ‘‘heat avoidance strategy’’ in that leaf temperature decrease without necessarily increasing tissue tolerance to thermal stress. The genetic variability for an avoidance of heat resistance has been reported. Lu et al. (1994) and Radin et al. (1994) in follow‐up studies under field and laboratory conditions have demonstrated that independent selection processes for higher net photosynthesis and stomatal conductance. The stomatal response to temperature is as a key stomatal property altered by selection for higher yields and heat tolerance (Lu and Zeiger, 1994). Ulloa et al. (2000) worked on the hypothesis that selection for high yields had imposed indirect selection pressure for elevated stomatal conductance at supraoptimal temperature under irrigated environments. This increased conductance may reduce leaf temperature and confer tolerance (or avoidance) to high temperatures especially during critical fruiting periods. Lu and Zeiger (1994) reported that the selection pressure for higher stomatal conductance cannot be explained by an adaptive advantage of enhanced carbon gain. Saranga et al. (2004) suggested that there are important opportunities for developing polyploid crop genotypes that retain commercial levels of quality and productivity. DiVerent cotton species have evolved diVerent alleles related to physiological responses for improved adaptation to abiotic stress. Furthermore, the discovery in several cases of complementary favorable alleles on homologous chromosome showed that by assembling interspecific hybrid genotypes both Gossypium hirsutum and G. barbadense could be improved relative to their native state. This exemplifies the unique opportunities to evolve favorable new traits that accrue as a result of polyploid formation; the evolution of the genus Gossypium has included a very successful experiment in polyploid formation. The merger of two genomes A and D with diVerent evolutionary histories in a common nucleus appears to oVer unique avenues for phenotypic response to selection (Jiang et al., 1998). Burke (2001) suggested on the basis of research in wheat that it is possible that chromosomal deletions in the A or D genome of cotton would provide an enhanced, acquired thermo‐tolerance system.

HIGH TEMPERATURE EFFECTS AND BREEDING

B. CORRELATED RESPONSE

OF

347

SELECTED TRAIT

In the past, the breeding of agricultural crops for higher yields has been very successful. Breeders usually select for high‐yielding genotypes by using empirical methods, paying less attention to specific plant traits that might be conducive to higher yields. However, comparing old, low‐yielding lines of any crop with advanced, high‐yielding lines shows clearly that many morphological, physiological, and biochemical traits have been altered by the intense selection pressure for higher yield. These changes indicate that selection for high‐yielding genotypes has generated indirect selection pressure on the altered traits. If one excludes eVects of genes that regulate the expression of two or more unrelated traits (pleiotrophic genes), the study of high‐yielding lines might reveal specific traits and genes associated with higher yield. With this information, breeders could explicitly select for yield‐enhancing traits to further improve yields. Lu et al. (1997) speculated that intensive selection for higher yield and heat resistance in Pima cotton has generated indirect selection pressure on photosynthetic rate, stomatal conductance, and leaf areas that parallel the interspecific trait diVerence between upland and Pima cotton and their agronomic performance. This is an example of correlated response to selection. Lu and Zeiger (1994) found that selection for agronomic traits such as yield potential can lead to genetically stable changes in stomatal properties. These changes could be functionally related to other agronomic traits under selection and thus the selection for higher yields has imposed selection pressures for higher photosynthetic rates (Cornish et al., 1991). The higher stomatal conductance would have resulted from a coupling between photosynthesis and conductance (Wong et al., 1979) rather than from selection pressures on higher stomatal conductance per se. Lu and Zeiger (1994) studied conductance in an F2 population derived from an interspecific cross showed a segregation pattern typical of other genetically determined traits. Selection for heat resistance might have favored genotypes having an enhanced evaporative cooling and lower leaf temperature mediated by higher stomatal conductance. Reynolds et al. (2001) used CTD as an indirect selection criterion for genetic gains in wheat yield. They reported that CTD is aVected by many physiological factors, which makes it a powerful integrative trait. Since CTD is directly or indirectly aVected by a number of physiological processes, it is a good indicator of a genotype’s fitness in a given environment. Furthermore, CTD also seems to be aVected by the ability of a genotype to partition assimilates to yield, indicated by the fact that CTD frequently had a closer association with yield and grain number than it does with total above ground biomass. Indirect selection procedures based on the measurement of canopy temperatures using remote sensing could be more eVective than direct selection based on the measurement of the stomatal conductance of individual leaves. Promising progress has been made in applying this

348

Table IV Important Morphophysiological Selectable Traits Against Heat Tolerance/Heat Stress No.

Trait

Characteristics

References

(A) Morphological traits amenable to direct selection 1

Okra leaf type

Lower fruiting height Thicker leaves

4 5

Abundant flowering and fruiting at high temperature Earliness

6 7

Stay‐green eVect Pollen selection

Pettigrew (2004)

Reproductive heat tolerance

Ahmed et al. (1993), Ehlers and Hall (1996) Reynolds et al. (1997) Rodriguez‐Garay and Barrow (1988) Hall (1992)

Heat tolerance Pollen selection through heat treatment Reproductive stage heat tolerance

Wells et al. (1986) Feaster and Turcotte (1985) Hall (2001) Wright et al. (1993) Ehlig and LeMert (1973)

(B) Physiological traits for both direct and/or indirect selection 1

Cell membrane thermostability (CMT)

Measures the resistance of protoplasmic proteins to denaturations Heat and drought tolerance Heat tolerance Independent of developmental stage

Saadalla et al. (1990a), Blum and Ebercon (1981), Bibi et al. (2003), Rahman et al. (2004) Ashraf et al. (1994), Saadalla et al. (1990b)

R. P. SINGH ET AL.

2 3

Higher leaf (N) content Higher CO2‐exchange rate (CER) Higher photoelectron transport rate Reduced nonphotochemical quenching Reduced individual leaf area Higher photosynthesis Greater heat tolerance Higher N content Higher photosynthetic capacity Heat tolerance

2 3

Chlorophyll contents and chlorophyll a:b ratio Carbon isotopes discrimination diVerences

Dry matter and yield Heat tolerance

Al‐Khatib and Paulsen (1984), Saranga et al. (2004) Lu et al. (1996)

1 2

Leaf conductance Crop water stress index (CWSI)

3

Chlorophyll fluorescence

4

Canopy temperature depression (CTD)

5

Thermal stress index (TSI)

Heat tolerance Transpiration rate Vapor pressure deficit (VPD) Plant temperature Net radiation Air temperature Canopy temperature Aerodynamics resistance EYciency of PSII Indication of damage to PSII Leaf conductance Air temperature Soil water status and RH Incident radiations Heat escape Quantify thermal stress Measures enzymatic functions at high temperature The CWSI and TSI are highly correlated Can work at any level of VPD

Lu et al. (1994) Jackson et al. (1981)

Burke et al. (1990) Burke et al. (1990), Jackson et al. (1981) Butler (1978) Hall (2004) Reynolds et al. (1998) Amani et al. (1996) Amani et al. (1996) Amani et al. (1996) Cornish et al. (1991) Burke et al. (1990)

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(C) Screening of traits through infrared/remote sensing for direct selection

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350

technique to spring wheat (Fischer et al., 1998; Reynolds et al., 1998). Important morphophysiological selectable traits against heat tolerance/ heat stress are given in Table IV. Heat tolerance has been a primary selection criterion for higher lint yield in Pima cotton‐breeding programs (Feaster and Turcotte, 1985; Percy and Turcotte, 1991). It has been estimated that nearly 50% of the lint yield increase in Pima cotton at lower elevations of southwestern United States has been the result of increased heat tolerance in improved cultivars (Kittock et al., 1988). It has been demonstrated by Srivastava et al. (1995) that selection pressure for higher lint yield and heat tolerance in Pima cotton has altered intrinsic guard cell properties. Furthermore, Lu et al. (2000) stressed that the characterization of the properties of Pima cotton guard cells may be of importance for design of future programs that incorporate physiological traits into breeding strategies. Remarkable similarity in relationship between stomatal conductance and yield (Lu et al., 1998) in the historical series of Pima cotton and wheat supports the hypothesis that selection pressures for higher yields in irrigated crops grown at supraoptimal temperatures generate strong indirect pressures for higher stomatal conductance. Pollen selection through heat treatment allows screening for a large number of genetic combinations and may be a valuable method of breeding for heat tolerance. Breeding for heat tolerance during reproductive development has been eVective in cowpea (Hall, 1992) and cotton (Rodriguez‐Garay and Barrow, 1988). Burke (2001) speculated that improvements in vegetative heat tolerance might also provide improved heat tolerance during pollen development. Genes for heat tolerance during reproductive development enhance sink strength and harvest index (Ismail and Hall, 1998), and there are indications that they may enhance responsiveness to elevated CO2. Traits aVecting radiation use eYciency like early ground cover; stay green and photosynthetic rate could be expected to be important under heat stress. The stay‐green trait has been used widely in breeding for heat tolerance (Reynolds et al., 2001). In addition, Bibi et al. (2003) studied several physiological parameters of obsolete and modern cultivars and found significant diVerences in chlorophyll fluorescence. Modern cultivars exhibited higher fluorescence than the obsolete cultivars indicating greater stress tolerance of modern cultivars at higher temperatures. There is a need for developing systematic‐screening tools in evaluating stress tolerance in cotton genotypes for high‐temperature stress (Burke, 2004; Kakani et al., 2005).

C. ISOGENIC LINES

TO

STUDY INDIVIDUAL TRAIT PERFORMANCE

Prior to widespread use of specific phenological, physiological, or morphological traits in breeding programs, their value must be clearly established. A rigorous test involves the development of pairs of lines with and without

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the trait but with otherwise similar genetic background (i.e., almost isogenic lines). Ideally, several pairs of isogenic lines should be developed with diVerent genetic backgrounds, because the agronomic value of a gene(s) can depend on the other genes present in the genome (Hall, 2001). Understanding the relationship between traits and yield is being mediated by the identification and marking more of the controlling genes and their alleles. Isogenic comparisons have their limitations, but as more are carried out, the importance of certain genes for yield and other traits are being confirmed. One of the important traits for which isogenic lines were widely used is the okra‐type cultivars with various morphological and physiological traits. The okra leaf trait in upland cotton determines a leaf shape that is duly cleft with narrow lobes, in contrast with normal broad leaf. In addition to a radically diVerent leaf shape, the okra leaf trait exhibits a large change in growth characters (Wells et al., 1986). Pettigrew (2004) demonstrated that okra leaf trait reduced individual leaf area by 37% relative to the comparable normal leaf type, but okra leaf type had 16% greater chlorophyll content compared with normal leaf type isogenic pair. Similarly, Heitholt and Meredith (1998) found that okra leaf types were usually 1–4 days earlier in maturity than their normal‐leaf counterparts, possibly contributing to their overall yield advantage. Meredith et al. (1996) evaluating the eVect of three traits such as subokra leaf, semi smooth leaf, and nectarless in diVerent isolines demonstrated that subokra leaf types produced significantly higher (35 kg ha
1 or 4% more seeds) first harvest than normal leaf types, and seeds of semismooth isolines were heavier than those of hirsutum cottons. Leaf canopy photosynthesis of subokra type was 7% greater than that of normal leaf near isolines and was one of the causes for increased yields associated with subokra leaf trait (Wells et al., 1986). Similarly, Peng and Krieg (1991) reported that okra leaf plants had greater canopy photosynthesis per unit leaf area than normal leaf plants, but Elmore et al. (1967) observed no diVerence in the leaf CER between superokra and normal isolines. The intensity of competition for solar radiation diVers among the leaf types with less mutual shading in communities of superokra leaf plants than in communities of other leaf types. Furthermore, solar radiation interception and dry matter production of cotton are aVected by leaf type and total leaf area development (Kerby and Buxton, 1978). Karami et al. (1980) observed that an okra leaf cotton genotype had significantly higher assimilation under water stress than its isolines with ‘‘normal’’ leaf morphology. Pettigrew et al. (1993) examined cotton leaf‐type isolines and showed superior leaf CER in supraokra and okra leaf cotton compared with normal leaf genotype, Deltapine 50. Dark adapted Fv:Fm was not diVerent for the okra leaf type genotypes compared with normal leaf type genotypes; however, the okra leaf type lines had a 14% greater light adapted PSII eYciency and 14% greater photosynthetic electron transport rate compared with normal leaf type genotypes (Pettigrew, 2004). Nonphotochemical quenching was also 11% lower in

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the okra leaf type relative to normal leaf type genotypes. The two okra leaf type cultivars exhibited 30% higher CER, on average, than any of the normal leaf type varieties. Okra leaf type genotypes had lower stomatal conductance, it has also been reported that the okra leaf trait has higher photosynthesis per unit leaf area and higher water‐use eYciency (Baker and Myhre, 1968; Pettigrew et al., 1993). On the basis of modeling studies, Landivar et al. (1983) concluded that okra leaf cottons are very competitive in yield with normal leaf under favorable growing conditions, but are likely to be less competitive than normal leaf under adverse conditions. In contrast, Stiller et al. (2004) observed that okra leaf cotton cultivars gave higher yield in most of the water stress environments. Meredith and Wells (1986) conclusively demonstrated that certain population has the genetic potential of producing okra leaf cotton with higher yielding ability than that of normal leaf cotton.

D. GENETIC VARIABILITY The value of any trait as a selection character depends on whether it satisfies four basic criteria (Mahon, 1983). These criteria are as follows: (1) presence of suYcient genetic variability in its expression, (2) the characters should be characterized genetically, (3) the character must be related to agronomic benefit (e.g., yield, aspects of quality, and production cost), and (4) it must be measurable in large scale trials. Therefore, in this section the results of various reports with regard to genetic variability of diVerent eco‐morpho‐physiological traits related to high‐temperature tolerance are presented and discussed. McMichael and Burke (1994) found diVerences in temperature characteristics of root growth responses in young cotton seedlings. The root growth in response to temperature was maximal within the optimal temperature predicted by TKW. Farbrother (1960) and Hearn (1976) reported varietal diVerences in root density and their ability to extract water. Burke (2004) also reported genetic diversity in heat tolerance among the six greenhouse‐grown cotton cultivars. Bradow and Davidonis (2000) reviewed that the cotton canopy architecture, particularly with respect to plant height and branch lengths that can be modified by environmental conditions such as temperature, light intensity, and herbivory by insects and management strategies such as growth regulator application. The energy exchanges within a plant canopy can be aVected by size, shape, and orientation of the leaves. In upland cotton germplasm great variability with respect to leaf size and shape has been reported elsewhere (Heitholt et al., 1992). In addition to the normal leaf shape, cotton leaf shapes range from highly cleft (superokra) to only slightly cleft leaves (subokra)

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(Meredith, 1984). It has been established that the variation in leaf shapes can greatly alter canopy light interception characteristics (Wells et al., 1986). The increase in SLW grown under dryland conditions has been reported by Pettigrew (2004) and Wilson et al. (1987). Pettigrew (2004) observed that smaller leaves with occasionally greater SLW for the dryland plants lead to speculation of a higher concentration of photosynthetic apparatus per unit leaf area for the water‐stressed plants. This was further confirmed by the fact that there was 19% higher chlorophyll content in dryland leaves in upland cotton. McNamara et al. (1940) demonstrated that varieties diVering in leaf size and degree of lobing had diVerences in monopodial plastochrons. Bednarz and van Iersel (2001) found that morphological characters, such as deep lobed leaf and pubescence, did not provide enhanced heat tolerance. Kerby and Buxton (1978) speculated that when leaf area per plant is reduced genetically, plastochrons are reduced. It may be related to greater solar radiation penetration into canopies resulting in increased photosynthetic activity of lower leaves and much of the earliness associated with the okra leaf types results from small plastochrons. Sassenrath‐Cole (1995) observed that diVerent leaf type and row spacing altered canopy structure. Furthermore, the boll temperature tracked air temperature due to the absence of evaporative cooling by the bolls. Temperature of the lower canopies was warmer during the day and cooler at night for more open canopies such as okra leaf. The diVerences in temperature profiles within canopies have significant impact on boll maturation over the course of the growing season and may account for the observed increases in rate of earliness of bolls of okra leaf types (Heitholt, 1993). Alterations in leaf size and shape can aVect the temperature of canopies (Mahan et al., 1995). According to Reynolds et al. (2001), heat stress is almost certainly a component of drought stress, since one of the principal eVects of drought is to reduce evaporative cooling from plant surface. Nonetheless not all traits conferring heat tolerance are also associated with genetic variability for drought tolerance, a good example being CMT (Blum, 1988). Genetic variation in CMT has been observed in various field‐grown crops including cotton (Bibi et al., 2003; Rahman et al., 2004). Saadalla et al. (1990a,b) found a high correlation in wheat for CMT between seedling and flag leaves at anthesis for genotypes grown under controlled environmental conditions. Similar results were reported in cotton for this trait. Ashraf et al. (1994) reported the stable performance of cotton genotypes identified during seedling stage for their CMT. The physiological basis for the association of CMT with heat tolerance has not been understood. Plasma membranes are known to be more heat tolerant than the photosynthetic thylakoid membranes. Wise et al. (2004) demonstrated that photosynthesis in field‐grown Pima cotton leaves

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is functionally limited by photosynthetic electron transport and RuBP regeneration capacity, not by Rubisco activity presumably because of limitation in thylakoid reactions needed to support RuBP regeneration. Despite the strong environmental dependence of stomatal conductance, existing genetic variation can be successfully manipulated to produce stable populations with contrasting conductance levels. Crop plants show genetic variation for stomatal characteristics such as stomatal density, aperture size, opening pattern, and sensitivity to changes in internal plant water status and soil water status (Ludlow, 1980; Markhart, 1985). Percy et al. (1996) observed stomatal conductance diVerences in the low‐ and high‐yielding Pima cotton lines and reported that stomatal conductance is genetically controlled. Variation in stomatal conductance to water is also linearly correlated with assimilation with the result that Ci/Ca remains relatively constant across [CO2] (Morison, 1993). Genotypic variation in photosynthetic capacity on a unit leaf area basis has been reported in many crops (Bhagsari and Brown, 1986; Wallace et al., 1972). Perry et al. (1983) confirmed these genetic diVerences in the ratio of photorespiration to net photosynthesis in cotton and found that rates were directly attributed to source:sink ratio diVerences. Lu et al. (1997) observed that an upland cotton cultivar Deltapine 90 (DP‐90) showed 25–35% higher stomatal conductance, 35–50% higher photosynthetic rate, and 45% smaller leaf area than Pima S‐6 (PS‐6). Furthermore, the higher photosynthetic rate and stomatal conductance of DP‐90 leaves were partly related to their sun‐tracking ability. The cultivars DP‐90 and PS‐6 had comparable photosynthetic rate, but the stomatal conductance was higher in DP‐90. Moreover, in the 25–35  C temperature range, photosynthetic rate as a function of temperature remained nearly constant in both cultivars and was higher in upland cotton at all temperatures. In contrast, stomatal conductance showed strong temperature dependence. The slope of the stomatal response to temperature was higher in DP‐90. They also suggested that upland cotton could be used as a source of genetic variability for higher stomatal conductance in Pima cotton‐breeding programs. The Pima cultivars have lower heat tolerance than advanced upland cultivars (Kittock et al., 1988; Reddy et al., 1992b) and lower lint yield in hot environment (Radin, 1992; Silvertooth et al., 1992). Cantrell et al. (1998) reported 12% of the variation in stomatal conductance based upon QTL analysis and confirmed that stomatal conductance is a heritable trait and seems to be significantly associated with lint yield in heat stress environments. Taha et al. (1981) found diVerences in boll set in cultivars ST 3 and B 557 and suggested that in selecting for heat tolerance it is important to choose varieties that develop a large number of bolls of good size before the plants reach cutout phase. Brown and Zeiher (1998) found cultivar response to heat stress during reproductive development, to identify stages during reproductive development

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and plant processes that distinguish heat‐tolerant from heat‐sensitive cultivars. Recent studies showed that there were diVerences among cotton cultivars in temperature response of pollen grains under artificial conditions (Kakani et al., 2005). Cultivars ST 4793R, DP 458B/RR, and DP 5415RR not only had higher pollen germination and longer pollen tubes when germinated at high temperature but also had higher temperature optima, and thus were classified as heat‐tolerant cultivars (Kakani et al., 2005). Rodriguez‐ Garay and Barrow (1988) demonstrated that genes for heat tolerance could be selected in the pollen and eVectively transferred by the backcross method. They observed that cultivars developed in warmer areas were more fertile than those developed in areas where cotton is widely grown. This indicates that genes that allow the sporophyte to function at high temperatures also allow the pollen to retain fertility after heat stress. The literature suggests the presence of genetic variation in cotton for various characteristics such as seed germination, seedling establishment, vegetative stage of development, photosynthesis, photorespiration, chlorophyll contents, chlorophyll fluorescence, CMT, CTD, stomatal conductance, and various morphological traits like, leaf area, leaf thickness, leaf shape, height, and first fruiting node number. Similarly, genetic variation in reproductive development traits (pollen shedding, pollen germination, pollen tube lengths, and boll set) has also been reported in cotton thereby indicating the scope for genetic improvement for heat tolerance.

E. INHERITANCE STUDIES After identification of genotypes suitable for potential utilization in a breeding program for improvement of the trait(s) under consideration, the inheritance studies of the desired trait are necessary to decide the breeding methodologies. On the basis of the existing survey of literature, the inheritance pattern/heritability of the various eco‐morpho‐physiological traits are mentioned. Various reports using transgenic approaches, as reviewed by Sung et al. (2003), have largely validated that tolerance is a multigenes trait. It has been demonstrated that modifying membrane fluidity can influence gene expression (Horvath et al., 1998; Orvar et al., 2000). The importance of proper membrane fluidity in temperature tolerance has been delineated by mutation analysis, transgenic, and physiological studies. Alfonso et al. (2001) reported that a soybean mutant deficient in fatty acid unsaturation showed strong tolerance to high temperature. Similarly, Hugly et al. (1989) showed that the thylakoid membranes of two Arabidopsis mutants deficient in fatty acid unsaturation (fad 5 and 6) showed increased stability to high temperature.

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Tripathy et al. (2000) reported that CMT indicating the polygenic nature of its inheritance with broad‐sense heritability of 34%. Blum et al. (2001) reported the broad‐sense heritability for CMT for high‐temperature tolerance to be 71% in the winter and 67% for the summer wheat. Fokar et al. (1998) reported high heritability for CMT in wheat. Cotton is related to the plants with maternal type inheritance of chloroplasts, so during the selection of parents, a pair with high photosynthetic activity of the apparatus (Nasyrov, 2004) to improve photosynthetic productivity. For example, the cultivar Taskent‐1, which was bred from wild germplasm (Gossypium mexicanum), had higher rates of photosynthesis. In crossing Taskent‐1 and C‐6030 varieties, Nasyrov (2004) observed pronounced eVects of heterosis and there was an increase of Rubisco activity with a coeYcient of 18% and a slight increase of chloroplast number. All these factors lead to considerable increase in yield. Under the reciprocal combination when the cultivar C‐6030 with low photosynthetic activity served as maternal form it got very weak eVect of heterosis. The inheritance of stomatal conductance in Pima cotton varied in complexity from a simple additive‐dominance model to a model displaying digenic epistatic interaction (Percy et al., 1996). The alleles from the dominant markers from the upland cotton parent contributed the highest mean values of stomatal conductance and further suggested that genes from upland cotton may contribute to the increases in conductance in advanced Pima‐breeding lines (Ulloa et al., 2000). Percy et al. (1996) reported broad‐sense heritability estimates of stomatal conductance were 0.16–0.44 mmol m
2 s
1 in cotton. In interspecific populations, additive as well as dominance eVects for stomatal conductance were observed for QTLs. Using genetic mapping to dissect the inheritance of diVerent complex, traits in the same segregating population can be a powerful means to distinguish common heredity from casual association between such traits (Paterson et al., 1988). QTLs have been identified in cotton that confer physiological variations thought to be associated with stress tolerance such as osmotic adjustment (Morgan and Tan, 1996), carbon isotope ratio (13C:12C), stomatal conductance (Ulloa et al., 2000), chlorophyll content, and canopy temperature (Saranga et al., 2001). They showed that the genetic control of diVerence in canopy temperature was markedly influenced by water regime. Among four QTLs found to confer genetic diVerences in canopy temperature, one was specific to arid conditions and a second was specific to relative canopy temperature (GH allele conferring higher stability across environments). The GH allele at the chromosome 6 canopy temperature QTL was associated with higher seed cotton yield and lower osmotic potential. Furthermore, the relatively large number of QTLs associated with 13 C may help identify the important physiological traits that contribute to stomata conductance/photosynthetic capacity relationship.

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Saranga et al. (2004) documented an association between carbon isotope discrimination (D) and chlorophyll content in two genomic regions. These researchers reported that the likelihood that 2 out of 11 D QTLs would be associated with 2 of the 4 chlorophyll a/b QTLs in a genome size of cotton is about 0.02%. Furthermore, QTL alleles associated with higher D under arid conditions coincided with lower chlorophyll contents. This unexpected finding was further supported by the results of a subsequent study of F4 and F5 progenies of the plants from a current study in which the line having the highest D values also had the lowest chlorophyll a and chlorophyll b contents (Cohen, 2001). Saranga et al. (2004) on the basis of QTLs’ analysis concluded that QTLs conferring low canopy temperature and high chlorophyll a (one QTL each); with two QTLs conferring high chlorophyll b and there was a positive correlation between chlorophyll a and dry matter production in both water stress and well‐watered conditions.

F. IMPACT OF HEAT‐TOLERANT GENES Impact of heat‐tolerant genes is well documented in cowpea (Ismail and Hall, 1998, 1999). In cowpea, heat‐tolerant genes progressively enhanced grain yield from first flush of flowers by increasing pod set on the main stem nodes, and enhancing the overall partitioning of carbohydrates into grain with increases in nighttime temperatures above 20  C (Ismail and Hall, 1998). Heat‐tolerant genes (or closely linked genes) also had a progressive dwarfing eVect, mainly resulting from shorter main stem internodes and involving reduced shoot biomass production at night temperatures above 15  C. They concluded that heat‐tolerant (or associated) genes and the dwarfing and reduced biomass production associated with the heat‐tolerant genes could have negative eVects in some environments. Ehlers and Hall (1996) suggested that in the tropical zone, the dwarfing eVect of the heat‐tolerant genes is more pronounced than in subtropical zones, and in the tropics it will be necessary to combine the heat‐tolerant genes with genes that enhance vegetative growth. Cowpea lines that are heat tolerant at both early flowering and pod set produced the highest grain yield, whereas lines that are susceptible to both stages produced the lowest grain yield. The lines that are heat tolerant during early flowering but heat susceptible during pod set had intermediate yield (Ismail and Hall, 1999). Furthermore, the harvest index increased by four‐ to ninefold and pod per peduncle increased by three‐ to sevenfold for lines with heat tolerance during early flowering and pod set, respectively. These results suggest that the heat‐tolerant genes, that are eVective at early flowering and pod set, contribute equally to the final grain yield through their eVects on pod set and harvest index.

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Heritability of high‐temperature resistance has not been clearly ascertained. Transgressive segregation toward higher relative injury values in progeny than in parents of wheat suggests that the parents contributed diVerent genes for high‐temperature tolerance and the trait is not simply inherited (Saadalla et al., 1990b). Cytoplasmic and nuclear interactions in response to high temperature are indicated by significant reciprocal eVects. General and specific combining abilities for heat tolerance in a similar diallel of rice genotypes also are highly significant (Yoshida et al., 1981). Broad‐ sense and narrow‐sense heritability are both high, indicating that most genetic variation is additive and breeding for the trait should be successful.

G. BREEDING

FOR

HIGH‐TEMPERATURE TOLERANCE

Hall and Allen (1993) hypothesized that cultivars with heat tolerance during reproductive development, high harvest index, high photosynthetic capacity per unit leaf area, small leaves, and low leaf area per unit ground area, under the present level of CO2 will be most responsive under both hot and intermediate temperatures. Ismail and Hall (1998) reported that the heat‐tolerant genes confer some of the hypothesized traits, heat tolerance during reproductive development, particularly higher harvest index and less leaf area per unit ground area in cowpea. Similarly, the Pima cotton‐ breeding program has achieved large changes in plant architecture and substantial decreases in leaf size (Lu et al., 1994) and both trends have facilitated increased plant density. Furthermore, denser canopies tighten the coupling between leaf and canopy temperature (Lu et al., 1994) and should enhance adaptive advantages of higher stomatal conductance associated with lower leaf temperature (Lu et al., 1998). The strategy of modern breeding is to improve the intensity of the productive process under optimal partition of assimilates. The increase in productivity must be realized not by means of the vegetation period but by activation of productive process by increased rate of photosynthesis combined with higher number of bolls, increased boll weight, and harvest index up to 50% (Nasyrov, 2004). The productivity of a crop can be limited by any of the physical properties of its environment. However, the concept of environmental limitation is meaningful only in reference to a specific plant type, since the productivity of crop species or cultivars can vary within a single environment. The physiological processes, which restrict productivity in an environment, are referred to as physiological limits. These limits can be overcome by modifying either the environment or the physiological characteristics of the crop and the development of cultural practices and crop cultivars to exploit specific agricultural environments (Mahon, 1983).

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Crop physiology and ecology provide information on plant function and environment that, in principle, could be used to determine the suites of traits and their level that should be adaptive in specific environments (Hall, 2001). Key physiological traits aVecting crop productivity are likely to already have been modified by the extensive genetic manipulation typical of breeding programs. These physiological traits can be identified by comparing obsolete and modern lines grown in the same environment. In cotton, this type of study was conducted by Bridge and Meredith (1983). Lu et al. (1998) observed that stomatal conductance associated with lower canopy temperatures of obsolete and advanced lines exhibits maximal diVerences in the early afternoon, a time at which daily temperature are also maximal. Bibi et al. (2003) observed significant diVerences in chlorophyll fluorescence between the obsolete and modern cultivars at 30.5  C. The obsolete cultivars experienced lower fluorescence than the modern cultivars. This indicates that the obsolete cultivars suVer from more stress than the newer cultivars. Characterization of physiological traits altered in the process of selection for higher yields could make it possible to identify the nature of the selection pressure causing the changes, and the relationship between the altered trait and yield increase. Desirable physiological traits could then be specifically targeted for selection (Lu and Zeiger, 1994). Plant breeders have attempted to increase the capacity for root growth in breeding programs to improve drought resistance of agricultural crops. Most crops show considerable genetic variability in growth rate of roots, indicating that breeding for increased root growth can be eVective. In cotton, it has been demonstrated that root growth is under genetic control (McMichael and Burke, 1994). They suggested that the evaluation of cotton root growth responses to shoot and root temperatures within or below cotton’s TKW enhanced root growth. Breeding for specific canopy architecture has the potential to reduce the occurrence of plant temperature above the optimal thermal range. Such a trait would improve the plant’s ability to resist high temperature through changes in canopy architecture that serve to reduce thermal stresses with minimal eVects on water consumption (Mahan et al., 1995). The development of plant varieties with desirable canopy architecture coupled with management practices designed to avoid temperatures beyond the optimal thermal range may result in improved agronomic performance. Pettigrew et al. (1993) advocated that consideration should be given to utilize the high photosynthetic potential of okra or superokra leaf type in breeding programs. Moreover, another example of okra leaf productivity can be found in Australia where substantial increase in area and yield were reported with okra leaf genotypes (Thomson, 1995). A physiological character can be defined as the measurable expression of the rate or duration of a physiological process. Physiological characters are

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hierarchical in the same sense as yield components. The physiological characters are closely linked to morphology because morphological changes are the end results of physiological processes. Morphological expression can be considered as a physiological or ‘‘morpho‐physiological’’ character if it is assumed to control the rate of a process (Mahon, 1983). On theoretical grounds, it has been suggested that independent selection and controlled recombination of individual physiological traits could be a valuable addition to the normal methods of plant breeding. Perry et al. (1983) suggested that in the long term, genetic modification to reduce photorespiration and increased photosynthetic eYciency would be most desirable. Many studies have shown that attained yield advances in most agricultural crops have resulted from a higher harvest index, rather than from higher photosynthetic rates (Evans, 1983). In the absence of selection pressure for higher photosynthetic rates (as in Pima cotton), higher stomatal conductance could be disadvantageous because of wasteful water use (Lu et al., 1998). Abrol and Ingram (1996) emphasized that increased temperature would aVect the crop calendar in tropical regions. In the tropics, however, global warming, though predicated to be of only small magnitude, is likely to reduce the length of eVective growing season, particularly where more than one crop per year is grown. In semi‐arid regions and other agroecological zones where there is wide diurnal temperature variation, relatively small changes in mean annual temperatures could markedly increase the frequency of higher temperature injury. In cotton, canopy temperature can be 10–15  C higher in dryland cotton than in irrigated cotton (Burke et al., 1988). The global warming would reduce dry matter accumulation in dryland cotton because of increased respiration and reduced photosynthesis (Abrol and Ingram, 1996). Increased cotton yields could be achieved by breeding for simultaneous increases in both the reproductive sink and the photosynthetic source (Evans, 1983). In any breeding program projected changes in climate must be considered. Increases in atmospheric CO2 concentrations will tend to make photosynthetic sources more eVective per unit leaf area. Consequently, maintaining a balance between photosynthetic sources and reproductive sink may require selecting plants with much greater reproductive sinks. Breeding to maintain an appropriate balance will be of particular importance for cases where high temperatures result in greater damage to reproductive development than to the photosynthetic source. From the present literature, it can be seen that diVerent physiological mechanisms may contribute to heat tolerance in the field such as heat‐ tolerant metabolism as indicated by higher photosynthetic rates, increased stomatal conductance, chlorophyll content, fluorescence, stay green and CMT, or heat avoidance as indicated by CTD in addition to leaf types and thickness and crop duration. Breeding programs may measure such traits to

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assist in the selection of heat‐tolerant parents, segregating generation, or advanced lines. According to Evans and Fischer (1999), the identification of yield‐related physiological selection traits (as distinct from morphological or visual ones) has been of great interest to many physiologists and some breeders. Reasons for generally frustrating results have been thoughtfully discussed by Jackson et al. (1996). Accordingly, as field instruments continue to improve, new opportunities arise, as with air borne infrared images to register canopy temperature and other remote‐sensing techniques (Araus, 1996). Such techniques could complement molecular‐aided selection. Carbon dioxide concentration has increased rapidly during the last few decades, and it is expected that CO2 concentration will double by the end of this century. Making full use of elevated CO2 may also require selection to enhance those components of the photosynthetic system, other than Rubisco, that become limiting if the CO2 assimilation per unit leaf area of C3 species is to reach much higher rates. Selection for more open stomata may be useful, except for environments with extreme drought, since elevated CO2 will tend to cause partial stomatal closure. Overall, elevated atmospheric CO2 and global climate change will provide both opportunities that may be exploited by plant breeding to increase productivity and some additional problems for plant breeders and other scientists to solve in the twenty‐ first century (Hall and Ziska, 2000). It has been observed by a number of researchers (Drake et al., 1997; Idso and Idso, 1994; Reddy et al., 1997d, 2000, 2005) that CO2 enrichment alone may increase yields under water‐ limited conditions. Prior et al. (1994) observed that increasing CO2 increased root length and dry weight densities of cotton. Cotton is the most important candidate for such a response. The impacts of elevated CO2 on various physiological and morphological traits of cotton are summarized in Table V. In addition Idso et al. (1987), Long (1991), and Polley (2002) suggested that the eVects of higher temperature and CO2 on plants are not additive, moreover, direction of crop responses to CO2 enrichment and temperature change are species and even cultivar specific (Ziska et al., 1997). The heat‐tolerant genes may enhance adaptation to the climatic conditions of the twenty‐first century with elevated CO2 expected to be warmer (Hall and Allen, 1993). In addition to enhancing grain yield under hot conditions, the heat‐tolerant genes have been shown to enhance responses to elevated CO2 with respect to pod production under both optimum and high night temperature (Ahmed et al., 1993). High‐temperature injury on reproductive development will not likely be ameliorated by high CO2. Controlled environment studies have shown that grain and fruit production will be limited in high‐temperature environments (Baker et al., 1990; Prasad et al., 2002, 2003; Reddy et al., 1996, 1997b,d). Therefore, it becomes imperative that the positive eVects of predicted future CO2 enrichment in C3 crops like cotton can only be exploited by developing cultivars

362

Table V EVect of Elevated CO2 on DiVerent Morphological, Physiological Traits, and Yield Components in Cotton EVect of CO2

Comment

Square and boll

44% increase

Average of five temperature conditions at 720 mmol mol
1 as compared to ambient CO2 360 mmol mol
1 No eVect No eVect of elevated CO2 No eVect of elevated CO2 No eVect of elevated CO2 At 650 mmol mol
1 in comparison to ambient CO2 (under FACE) 350 mmol mol
1 At 550 mmol mol
1 Current ambient CO2 þ 300 mmol mol
1 At 550 mmol mol
1 At 550 mmol mol
1 At doubling the ambient CO2 At all temperature in high CO2 At optimum temperature and twice ambient CO2

Node addition Root:shoot ratio Harvest index Lint percentage Biomass above ground

63% increase

Biomass above ground Yield Yield Lint yield Photosynthetic eYciency Root biomass Root biomass

35% increase 60% increase 40% increase 60% increase 25% increase High Greater

References Reddy et al. (1997b)

Reddy et al. (1995a,c) Reddy et al. (2000) Reddy et al. (2000) Reddy et al. (1999) Kimball and Mauney (1993) Mauney et al. (1994) Reddy et al. (2000) Mauney et al. (1994) Pinter et al. (1996) Reddy et al. (2000) Reddy et al. (1995b) Reddy et al. (1995b)

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tolerant to high temperature in general and especially at the reproductive development stage. Baker et al. (1990) hypothesized that future crop yields will be influenced by complex interactions between the eVects of increased atmospheric CO2 concentration and trace gases such as ozone as well as the eVects of temperature increase brought about by climate change (IPCC, 1995). This could be good or bad news as agricultural productivity is expected to be sensitive to global climate change and increased CO2 concentration should cause increased productivity at least in C3 plants and decrease soil–water use relative to the dry matter produced. Higher temperature and periodic episodes of heat stress and drought, however, could exacerbate the eVect on crop growth and development, reduce crop yields and quality (Reddy et al., 1996, 1999). Acquired tolerance to high and/or low‐temperature stress conditions are complex traits as demonstrated from a vast research of plant breeding and crop improvement eVorts (Sung et al., 2003). Wang et al. (2003) suggested that a comprehensive breeding strategy for abiotic stress tolerance should include the following steps and approaches: (1) conventional breeding and germplasm selection, especially of wild relatives of a species; (2) elucidation of the specific molecular control mechanisms in tolerant and sensitive genotypes; (3) biotechnology‐oriented improvement of selection and breeding procedures through functional genomic analysis, use of molecular probes and markers for selection among natural and bred populations, and transformation with specific genes; and (4) improvement and adaptation of current agricultural practices. Hall (2001) suggested that genetic engineering is useful in ideotype breeding in that, in principle, single genes can be transferred into a cultivar without changing the genetic background, thereby creating an isogenic pair of lines in one step and a relatively short time. In practice, however, many transformed plants must be created and evaluated because factors such as the placement and manner of gene insertion can influence its expression. The traditional back‐crossing procedure for creating almost isogenic lines requires many plant generations and several years, but it can be accelerated by using DNA markers to select for the genetic background of the recurrent parent. DNA markers also can be used to develop indirect selection methods. In this case, DNA markers are needed that are closely linked to the trait of interest. Indirect selection using DNA markers is powerful where it can be used for nondestructive screening of single plants in the first segregating generation. Once a set of stable lines has been bred with selection based on indirect screening procedures, one should either conduct studies to confirm that the desired trait is present, using a more reliable direct screening procedure, or proceed directly to performance trials under field conditions in the target production environment. Cheikh et al. (2000) stressed that molecular biology tools will never replace the input and role

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of crop breeders in improving agronomic traits, but these tools will enable them to be more responsive in both time and breadth of environmentally sensitive traits to meet agricultural market needs and opportunities. Biotechnology tools combined with conventional breeding should position us to be able to take greater care of the production environment and allow us to achieve adequate food production and security for the growing world population.

H. PRACTICAL ACHIEVEMENTS At Phoenix, Arizona, systematic eVorts were started in the late 1950s to develop heat‐tolerant Pima cotton cultivars, and a number of cultivars have been developed and released for commercial production since 1960, Pima S‐ 2 being the first cultivar. The realized genetic gain from Pima S‐1 to Pima S‐5 was 57% at low elevation (<450 m) and 30% at high elevation (>750 m). Furthermore, each release (Pima S‐1 in 1951, Pima S‐2 in 1960, Pima S‐3 and Pima S‐4 in 1966, Pima S‐5 in 1975, Pima S‐6 in 1983, and Pima S‐7 in 1991) progressively increased lint yield (Lu et al., 1998). Stomatal conductance showed a strong, positive correlation with lint yield, and increased about 30 mmol m
2 s
1 per 100 kg ha
1 increases in cotton lint yield (Lu et al., 1998). Some studies showed that photosynthetic rates and stomatal conductance in Pima lines have increased in parallel with yields (Cornish et al., 1991; Lu and Zeiger, 1994). This provides evidence that selection pressures for higher yields could have resulted in an indirect selection for higher photosynthetic rates, stomatal conductance, and heat tolerance (Lu et al., 1998; Radin et al., 1994). However, detailed correlation studies suggested no correlation between photosynthetic rates and lint yield or between photosynthetic rates and the order in which the cultivars were commercially released (Lu et al., 1998). They conclude that overall the observed increases in stomatal conductance in the Pima series have exceeded the increase in photosynthetic rates, which provides further evidence for independent selection pressures on higher stomatal conductance and for relationship between stomatal conductance and yield to be independent of photosynthetic rate (Lu et al., 1996, 1998). Radin et al. (1994) suggest that as breeders have increased the yield of cotton, genetic variability for conductance has allowed inadvertent selection for heat avoidance (evaporative cooling) in a hot environment. Breeding has also increased tolerance to high temperatures in each commercial release of Pima cultivars (Feaster and Turcotte, 1962, 1984; Feaster et al., 1967; Niles and Feaster, 1984). No attempts to modify physiological or morphological traits have been made in this program; instead, improvements

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have been achieved by genetic manipulation of available germplasm variability, extensive selection within segregating populations, and testing advanced generation lines for yield at sites with diVerent temperature regimes. Feaster and Turcotte (1985) conclusively demonstrated that in environments where the adaptation of a cultivar depends largely on its tolerance to high night temperature, the height on the plant at which an appreciable number of bolls begin setting is an eVective indicator of heat tolerance. The stomatal conductance apparently is dependent upon evaporative cooling. This represents a heat avoidance strategy, in that leaf temperature decreases without necessarily increasing tissue tolerance for thermal stress. Genetic variability for an avoidance type of heat tolerance was reported by Radin et al. (1994) for the first time. Evans and Fischer (1999) discussed avoidance of heat stress and its adverse eVects on boll set. Early development may be the explanation of the yield advantage, and cotton is an excellent example of the power of empirical selection for yield. Selection for higher yields and heat resistance has altered the stomatal response to temperature in Pima cotton (Lu et al., 1998). They demonstrated that air temperature in the Pima cotton‐growing areas of Arizona often exceeds 40  C. Leaf–air temperature diVerence in a heat‐sensitive land race, Sea Island, a low‐yielding commercial line, Pima‐32 and a high‐yielding line Pima S‐6 were about
1,
3, and
4.5  C, respectively (Lu et al., 1994; Radin et al., 1994). This trend toward higher stomatal conductance and lower leaf temperature has persisted in a subsequent commercial release of Pima S‐7 (Lu et al., 1998). At Cotton Research Institute, Sakrand, Sindh, Pakistan, one cultivar CRIS‐134, has been developed. This cultivar is capable of producing 32 bolls after 75 days of planting (the hottest days having an average temperature of 41  C) as compared to NIAB‐78 and CRIS‐9, which formed 17 and 11 bolls, respectively. This cultivar (CRIS‐134) was specifically developed to tolerate the hot period of June–August (Soomro, 1998). Similarly, at Indian Agricultural Research Institute, New Delhi, India, heat‐tolerant cotton genotypes have been developed using shuttle‐breeding approach. Shuttle‐breeding approach refers to change of environment during the selection processes. This method is used to select broadly adopted cultivars from the segregating populations. The selection was applied (Singh et al., 2003) for higher numbers of fruiting structures (square/flower/bolls) per plant in addition to early maturity initially in the cultivars and later on in the segregating generations from intra‐ and interspecific crosses. Rosielle and Hemblin (1981) discussed selection approaches under stress and nonstress conditions and suggested that if it is imperative that yields in stress environments be increased, then selection for tolerance may be worthwhile. The genotypes were selected by using this approach for high‐temperature tolerance with the objective to test the suitability to grow during spring–summer season (February–June) in Australia. This season is similar to that in north India which is characterized by low

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temperature during germination (mean minimum temperature of 7.5–18.3  C in second fortnight of February) and high temperatures during reproductive stages (25.4–33.7  C mean minimum temperature and 33.6–43.4  C mean maximum temperature from May 15 to June 30). On the basis of the temperature recorded from 2001 to 2004 (mid‐February to June end averaged over 15 days) it became clear that during summer season both minimum and maximum temperatures are very high, while under the main crop season the maximum temperature is more or less similar to the mean minimum temperature experienced during the critical reproductive phase (mid‐September onward). The success of these selected genotypes depends upon their tolerance to low temperature during germination and plant stand establishment and high‐temperature/heat‐stress tolerance during reproductive stage as suggested by Reddy et al. (1996). Breeding both high and low‐ temperature‐tolerant cultivars is beneficial. Low‐temperature tolerance in cotton would allow the producer to plant the crop earlier and permit a crop canopy to develop earlier in the growing season. This would allow flowering to occur before the mid‐summer high temperature that limits fruit set. Similar conditions of cool temperatures during germination and high temperature during flowering occur in cotton‐producing regions of the United States (Oosterhuis, 1999; Reddy et al., 1995b). The damaging eVect of high temperature on cotton production in Arizona has been recognized (Kittock et al., 1988; Lu et al., 1994). They found that cotton yields in Arizona were limited by high temperature especially if not planted early. The promising heat‐tolerant genotypes can be characterized phenotypically as reported by Singh et al. (2003, 2004). Compact plant type, as Ismail and Hall (1998) also found that the dwarfing and reduced biomass production was associated with the heat‐tolerant genes in cowpea. Ismail and Hall (1998) reported that heat‐tolerant genes slightly enhanced the extent of premature plant senescence occurring just after the first flush of pods was produced. Lower first fruiting node number, as also reported by Feaster and Turcotte (1985), was one of their selection criteria. The leaves of genotype Pusa 17‐52‐10 are also very desirable to withstand very hot summer, and they become droopy exposing less area to direct sunlight. This genotype was shown to have higher boll weight 3 g versus 1.5–2.0 g of the heat‐susceptible genotype and high boll number per plant (14–15) and reduced ginning turnout (by about 30–32% in comparison to 34%) during main season crop. The heat‐tolerant cotton genotype Pusa 17‐52‐10 has been registered with NBPGR (INGR No 03073). This particular genotype demonstrated tolerance to high temperatures consistently with regard to its performance under multilocation centers for 3 years. Moreover, the strains having heat tolerance also exhibited wide adaptability in terms of their maturity (125–135 days), growth habit, and boll number/ plant when grown in diVerent latitudes from northwestern India to coastal

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eastern regions of Sunderban delta (characterized by very hot and humid conditions) to the southern part tested under rice fallow system. Oosterhuis (1999) reported that since cotton fiber is made predominantly of carbohydrate, a decreased availability of carbohydrate can also be manifested in less fiber and lower ginning turnout. Overall the heat‐tolerant genotypes confer some of the hypothesized traits reported by Hall and Allen (1993) and observed phenotypes of heat‐tolerant Pima cotton genotypes reported by Feaster and Turcotte (1984).

VI.

SUMMARY AND CONCLUSIONS

Projected changes in climate due to increasing ‘‘greenhouse’’ gases is a challenging issue to many scientists. Atmospheric CO2 has increased by 37% during the past two centuries to its present level of 380 mmol mol
1, and it is predicted that CO2 could be in the range of 510–760 mmol mol
1 by the middle or later part of this century. The increasing CO2 and other greenhouse trace gases will contribute to global climate change, which in turn is expected to warm the earth by 2–5  C by the end of this century. As the world becomes warmer, the hydrological cycle will also become more intense resulting in more uneven and intense precipitation. This will result in increased summer drying and associated risk of both droughts and floods. The current and projected changes in climate pose a greatest challenge to crop physiologists, crop breeders, and producers to continue to produce ecosystem goods and services in a sustainable manner to the needs of growing population. Since plant growth and crop production are controlled by weather and in particular temperature, it becomes imperative to understand the implications of temperature change on crop production. Cotton, Gossypium species, is of the marvels of the plant kingdom in providing the needs of humankind. It produces the basic raw materials, such as cellulose, protein, and oil, in quantity and quality surpassed by few plant species. The cellulose is pure and in the form of a natural fiber. This crop is an important commodity worldwide, valued at US$20 billion per annum is likely to suVer most by global climate change, since two‐third of the global cotton production come from higher (>30  N) latitude. Nevertheless, it has been predicted that the impact of global warming will be greater in the northern than in the southern hemisphere due to more high latitude area is cultivated in the northern hemisphere. Better understanding of the possible impact of rising temperature on crop photosynthesis and productivity would help in mitigating the adverse eVects of high‐temperature (heat) stress. From the literature surveyed, it has been observed that rising temperature exerts negative influence on CGR,

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photosynthesis, crop phenology, and yield. As the temperature increases further, interception and absorption of PAR will be drastically aVected. Dark and photorespiration overtake net photosynthesis and result in loss of biomass. Breeding cultivars to any abiotic stress is very costly and time‐ consuming process. It requires the concerted eVorts of crop physiologists, biochemists, molecular biologists, and geneticists in addition to the eVorts rendered by the traditional plant breeders. The very basic and first approach is to identify the suitable donor stock(s) for their eVective utilization in tailoring of new cultivars. The conventional screening of large germplasm has been very resource intensive and time consuming because the success of any breeding program depends on the eVective evaluation and utilization of available and suitable germplasm. The use of relatively new physiological techniques such as CMT, LEL, carbon isotope discrimination; ecophysiologically based remote‐sensing/ infrared techniques such as CTD, VPD, chlorophyll fluorescence; and biochemical parameters such as chlorophyll a and b contents and a:b ratio are gaining popularity to screen eYciently and quickly with reliability. The quantification of various environmental parameters in terms of CWSI and TSI has helped to evaluate the genotypes against water and/or heat stress, both CWSI and TSI are correlated with yield under heat stress conditions. The association between CTD and leaf conductance with each other and with yield extends the possibility of coupled selection for both traits. The CTD which is a function of stomatal conductance itself is a mechanism of heat escape in cotton. CTD is directly aVected by a number of physiological processes; it is a good indicator of the fitness of a genotype in a specific environment. Moreover, CTD also seems to be aVected by the ability of a genotype to partition assimilates to yield. The significant positive genetic correlation between yield and CTD, cell membrane thermostability, leaf chlorophyll content, leaf conductance, and photosystem components have been reported under heat stress conditions. It has also been reported in literature that the stomatal component of heat resistance is apparently dependent on evaporative cooling which represents a ‘‘heat avoidance strategy,’’ and the genetic variability for an avoidance of heat resistance has been reported in cotton. Nevertheless, it has also been speculated that intensive selection for higher yield and heat resistance in Pima cotton has generated indirect selection pressure on photosynthetic rate, stomatal conductance, and reduced leaf areas (correlated response). Genetic diVerences in photosynthetic capacity may be detected indirectly by selecting for thicker leaves as they have more dry weight per unit leaf area and usually have higher levels of photosynthetic enzymes and photosystem components per unit leaf area. Direct selection can be applied for morphological traits such as lower fruiting node number, smaller and thicker leaves, okra leaf types, and abundant flowering, and fruiting under high‐temperature conditions.

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Heat tolerance at reproductive stage can be enhanced by using pollen selection through heat treatment. Indirect selection procedures based on the measurement of canopy temperature by remote sensing could be more eVective than direct selection based on the measurement of the stomatal conductance of individual leaves. The stay‐green trait has the potential to be widely used in breeding for heat tolerance. The heritability of useful eco‐morpho‐physiological trait(s) for enhancing heat‐tolerance needs further investigation to make it amenable to selection. From the various reports it is clear that suYcient genetic variability is present in the elite cotton germplasm which could be used eVectively after critical evaluation to develop cotton cultivars for heat tolerance by adopting suitable‐breeding methodologies.

ACKNOWLEDGMENTS Part of the research was funded by the Departments of Energy, Bioenergy, and Biological and Environmental Research programs, US Department of Energy, through Mississippi State University, and the South Central Regional Center of NIGEC, respectively and USDA UV‐B Monitoring and Network, Colorado State University, Fort Collins, CO. We thank Drs. Harry F. Hodges, Jack C. McCarty, and Frank B. Matta for reviewing the chapter and for their helpful comments. Contribution from the Department of Plant and Soil Sciences, Mississippi State University, Mississippi Agricultural and Forestry Experiment Station no. J‐10971 and from the Department of Agronomy, Kansas State University, Manhattan, Kansas (Kansas Agricultural Experiment Station no. 07-53-B).

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Index A Accelerated solvent extraction (ASE), 37 Adenosine 5-triphosphate (ATP), 117, 326 Aeschynomene virginica, 223 AFO. See Animal feeding operations Ageratum conyzoides, 179 Agricultural expansion and intensification, consequences of, 74–5 Agricultural intensification in Africa, 88–9 Agricultural land use, trends in, 73 Agriculture, land area of natural ecosystems converted to, 71–4 Agroecosystems, 154 Agronomic perturbations, 139 Aldrich humic acid, 24 Alisma lanceolatum, 179 Alisma lanceolatum L., 223 Alisma plantago-aquatica, 179 Alisma plantago-aquatica L., 223 Allelopathy, 222–3 Alternanthera alternate, 223 Ammannia baccifera, 178 Anabolics, 9 Anaerobic digesters, 114 Anaerobic digestion, 114–16 Androgens, 34–6 properties of, 17–18 Animal feeding operations (AFO), 100 Animal Health Institute (AHI), 5 Antimicrobials, 1–5 analytical methods, 36–8 quinolones/fluoroquinolones, 45–6 sulfonamide, 44–5 tetracyclines, 38–44 aqueous concentrations of, 24 degradation in aqueous environments, 19–20 in manure and soil, 19–20 development of antimicrobial-resistant bacteria, 29–31 environmental concentrations of, 3 impact of animal husbandry-derived, 4 in large-scale animal husbandry, 3 occurrence, 6–7 potential sources of, 2 sorption by soils and sediments, 13–16 toxicity, 28–9 transport processes, 23

DOM-facilitated transport of, 23 runoff versus drainage, 25 uses, 5–6 in water, 2 Aquaculture and antimicrobials, 7 ArcGIS hillshade, 133 Ascophyllum nodosum, 121 ASE. See Accelerated solvent extraction Atlantic salmon (Salmo salar), 34 ATP. See Adenosine 5-triphosphate

B Bacitracin, 6 Bacopa decumbens, 179 Bacopa maritimus, 178 Bacopa rotundifolia, 185 Bacteria and resistance mechanisms, 31 Bathing Waters Directive (76/160/EEC), 96 Bidens spp., 178 Biochemical oxygen demand (BOD), 135 Biogeochemical cycles, anthropogenic impact on carbon cycle, 80–2 nitrogen cycle, 82–3 phosphorus cycle, 83 Bioherbicides, 223–4 Biomes, distribution of managed-grazing land in, 73 BOD. See Biochemical oxygen demand Bolboschoenus compactus, 178 Bolboschoenus maritimus, 178 Brachionus calyciflorus, 29 Broadcasting practices, 157, 160 Broadcast spreading, 123

C CAFO. See Concentrated animal feed operations Campylobacter, 100, 102–3 Campylobacter spp., 112 Canopy temperature depression (CTD), 337–38, 342 Carassius auratus. See Mature male goldfish Carbadox, 15–16, 19

387

388

INDEX

Carbon cycle, 80–2 Carbon isotopes, 335–6 Carbon pools and fluxes, human-induced changes in global, 81 Cation bridging in soil, 14–15 Cattle slurry, thermophilic aeration of, 113 Cellular membrane thermostability (CMT), 331–3 Cellulose synthesis, 323 Centro Internacional de Mejoramiento de Maı´z y Trigo (CIMMYT), 258, 331 Ceriodaphnia dubia, 29 CGIAR. See Consultative Group on International Agricultural Research Chemical oxygen demand (COD), 135 Chlorophyll content, 333–4 fluorescence, 334–5 Chlortetracycline, 6, 19, 38 Chromolaena odorata, 179 Chromolaena odorata L., 178 Chrysemys picta. See Female painted turtles CIMMYT. See Centro Internacional de Mejoramiento de Maı´z y Trigo CMT. See Cellular membrane thermostability Coccidiosis, 15 COD. See Chemical oxygen demand Codes of good agricultural practice (CoGAP), 102 Coliphages, 114 Colletotrichum gloeosporiodes, 223 Commelina diffusa, 185, 193 Commelina spp., 179 Composting, solid manure (farmyard manure), 108–10 Concentrated animal feed operations (CAFO), 2–3 Constructed wetlands, 134–6 Consultative Group on International Agricultural Research (CGIAR), 258–9, 261, 304 priority areas for, 261 Corchorus spp., 179 Cotton canopy architecture, 343 Cotton fiber, 322–3 Cotton germplasm, 316 Cotton (Gossypium spp.), 314–6 association among ecophysiological, morphological, and yield traits, 341–3

breeding for high-temperature tolerance correlated response of selected trait, 347–50 genetic variability, 352–5 heat-tolerant genes, impact of, 357–8 high-temperature tolerance, breeding for, 358–64 inheritance studies, 355–7 isogenic lines to study individual traits performance, 350–2 practical achievements, 364–7 trait selection, 344–6 effect of high-temperature stress on, morphological and yield traits flower production and fruit set, 319–21 fruit growth, 321–2 growth traits, 324 seedling and root growth, 317–18 vegetative and shoot growth, 318–19 yield and fiber components, 322–4 effect of high-temperature stress on, physiological and biochemical traits, 324–5 gas exchange, 326–7 heat-shock proteins, 327–9 membrane disruption, 325–6 heat stress, definition and levels of, 329 heat tolerance, 329–30 heat-tolerance traits, screening for, 330–1 heat-tolerance traits, screening for, ecophysiological traits aerodynamic resistance, 336–7 quantification of stress index using canopy temperature, 337–40 heat-tolerance traits, screening for, physiological and/or biochemical traits carbon isotope discrimination, 335–6 cellular membrane thermostability, 331–3 chlorophyll content, 333–4 chlorophyll fluorescence, 334–5 Crassocephalum crepidioides, 179 Crop growth rate (CGR), 324 Crop water stress index, 338–9

INDEX Cryptosporidium parvum, 103, 110, 114, 122, 128 in sheeps, 103 Curvularia tuberculata, 223 Cynodon dactylon (L.), 178 Cyperus difformis, 179–80, 185, 187 Cyperus esculentus L., 223 Cyperus iria, 179–80, 185 Cyperus rotundus, 165, 179, 185, 193 Cyperus serotinus, 178

D Damasonium minus, 179, 223 Danio rerio. See Zebrafish Defra, 123 DEM. See Digital elevation models Desoxycarbadox, 19 Dibbling, 160 seeds, 157 Digital elevation model (DEM), 133–4 Digital terrain model (DTM), 133–4 Digitaria ciliaris, 178 Digitaria elongata, 178 Digitaria sanguinalis, 178 Direct-seeded rice (DSR), 160, 177–9 area in diverent rice-growing countries, 161–2 crop–weed competition in, 180–2 future research crop rotations and management practices for reducing weed infestations, identifying, 226–7 decision making, improving, 227–8 developing cultivars with competitive ability, 226 herbicides and IWM, evolving effective, 227 impact of global climate change, 228 molecular biology, using, 227 role of water management on weed population dynamics, 226 yield loss, characterizing scales of, 225–6 global distribution of, 160 integrating weed management practices in, 190–1 methods of, 156–60 occurrence of major weeds in, 164–77

389

systems of world, 158–9 weed communities of, 164–5 Wet- and, 179–80 yield loss due to weeds in, 160–4 Direct-seeded rice, weed management for grass weed control Echinochloa spp., 211–12 weedy and red rice, 211–12 potential weed control methods allelopathy, 222–3 bioherbicides, 223–4 weed management technologies gene flow and its implications in weed management, 221 herbicide resistance in weeds and its management in direct-seeded rice, 216 herbicide-resistant transgenic rice and weed management in direct-seeded rice, 216–21 herbicide use, improving, 214–15 Direct-seeding, 156 Dirty water, 102 DNA markers, 363 DOM, 23–5 DP 458B/RR, 355 DP 5415RR, 355 Drobow, 178 Dry seed, 157 Dry-seeded gogorancah rice, 178 Dry-seeded rice, 200–8 Dry-seeding in India, 160 DTM. See Digital terrain models ‘‘Dust Bowl’’ of 1930s in the United States, 74

E Echinochloa colona, 165, 178–9, 185 Echinochloa crus-galli, 165, 178–80, 184–7, 192 Echinochloa glabrescens, 179, 9 Echinochloa oryzoides, 178–80 Echinochloa phyllopogon, 178–81. See also Watergrass Echinochloa spp., 178–9, 183 Echinochloa stagnina, 192 Eclipta alba, 179 Ecoregional Methodology Fund, 259

390

INDEX

Ecoregional Methodology Fund, examples from projects of developing Kenyan highlands, 266 detecting hot spots for change, 267–9 in retrospect, 272–3 trade-offs in agricultural development, 269–71 verifying the feasibility, 271–2 from environment to human health, 295–8 signaling constraints in sustainable use of water resources on the Tibetan plateau case study, 286–9 mountainous areas, research in, 285–6 Tibetan plateau, 283–5 soil erosion, dealing with, 298–301 South Africa, reestablishing farmers credit in Highveld region, 301–3 southeast Asia, multiple goals for land use in methodology in practice, 294–5 Philippines, illustration for Ilocos Norte province, 291–4 pressing land-use problems, using systems analysis to study, 290–1 trade liberalization, reacting to cost, 279–80 design phase, 276–9 lessons learned, 280–3 signaling phase, 273–6 trade-offs in agricultural development, 269–71 verifying the feasibility, 271–2 EDTA. See Ethylenediaminetetraacetic acid Eleusine indica, 179 ELISA, 27 kits, 50 Endocrine disrupting chemicals (EDCs), 7 Enrofloxacin, 45 Enterococci, 114 Environmental estrogens, exposure to, 7 ENVIROPUR, 118 Enzyme-linked immunosorbent assay. See ELISA 4-epi-tetracyclines, 43 Eragrostis japonica, 193

Escherichia coli, 115, 121–2 Escherichia coli O157, 102, 112, 114, 122, 124 17 -Estradiol, 22 contamination of waterways, 32 in soil, 26 Estrogens, 32–4 properties of, 17–18 Estrogen receptor gene-transcription activity, 11 Ethylenediaminetetraacetic acid (EDTA), 38 17-Ethynyl estradiol, 22 EU Water Framework Directive (2000/60/EC), 97 Exserohilum monoceras, 223

F Farm environment, sources of pathogens in, 97–9 farmyards and animal feeding operations, 106–7 grazing animals, 102–4 manure spreading versus grazing as source, 104–6 manures spread to land dirty water, 102 slurry (liquid manure), 100 solid manure (farmyard manure), 101–2 Farmer decision-making process, 126 Farmer environmental stewardship, 125–7 Farm ponds, 136–7 Farmyard manure (FYM), 98, 101–2 Fecal coliforms (FC), 114 Fecal indicator organisms (FIO), 117–18 Fecal streptococci (FS), 114 Female painted turtles (Chrysemys picta), 32 Fiber elongation, 324 Fimbristylis dichotoma (L.), 185 Fimbristylis littoralis, 179 Fimbristylis miliacea, 178–80, 183, 185 Fimbristylis miliacea L., 178 FIO. See Fecal indicator organisms Fixed film, 116 Flumequine, 20 Fluoroquinolones, binding coefficients for, 24 Food demands for world’s growing population, 83–6 Formalin, 7

INDEX Free water surface treatment wetlands (FWS), 135 Fundulus heteroclitus. See Mummichog FWS. See Free water-surface treatment wetlands FYM. See Farmyard manure

G Gambusia affnis. See Mosquitofish Gene flow and its implications in weed management, 221 Geographic information systems (GIS), 133 Germplasm (Gossypium mexicanum), 336, 356 Giardia intestinalis, 103, 110 GIS. See Geographic information systems Glufosinate-resistant rice, 219–21 Gossypium barbadense, 346 Gossypium barbadense L. See Pima cotton Gossypium hirsutum, 346 Gossypium mexicanum. See Germplasm Gossypium spp. See Cotton Grass weed control Echinochloa spp., 211–12 weedy and red rice, 211–12 Green Revolution technologies, adoption of, 83–4

H Haber-Bosch process, 83 Hand broadcasting, 157 Heat-resistant cultivar, 330 Heat-shock proteins, 327–9 Heat stress, 329 Heat-tolerant germplasm, 316 Herbicide resistance in weeds and its management in direct-seeded rice, 216 resistant transgenic rice and weed management in direct-seeded rice, 216–21 use of, 214–15 Heteranthera limosa, 177 Hormones, 1–5 analytical methods, 36–50

391

determination of, concentrations, 48 impact of animal husbandry-derived, 2 induced endocrine disruption, 31–2 androgens, 34–6 estrogens, 32–4 progesterone, 36 occurrence in animal wastes, 10–12 in aqueous environments, 12–13 potential sources of, 2 sorption by soils and sediments, 13–19 stability in manure, urine, and composted manure, 20–1 in soils and manure-amended soils, 21–3 transport processes, 23 uses, 3–4, 7–10 HSP. See Heat-shock proteins Hydric civilizations, 75 Hydrologic cycle, water consumption and change in, 75–80

I Imidazolinone-tolerant rice, 219 Imperata cylindrica, 179 Integrated weed management (IWM), 190–1 International Rice Research Institute (IRRI), 258, 295 Ionophores, 6, 15 Ipomoea wrightii Gray, 193 IRRI. See International Rice Research Institute Ischaemum rugosum, 179, 183, 185, 187, 193 IWM. See Integrated weed management

J Japanese medaka (Oryzias latipes), 35 Juncellus serotinus, 185

K Knowledge-intensive practice, 215

392

INDEX L

M

-Lactams, 6 Land management engineering and vulnerability mapping, 132–4 Land management strategies, for restricting pathogen transfer, 122–3 measures to reduce pathogen delivery to water constructed wetlands, 134–6 farm ponds, 136–7 land management engineering and vulnerability mapping, 132–4 restricting livestock access to streams, 127 riparian buffer strips, 131–2 vegetated buffer strips, 128–31 measures to reduce pathogen mobilization from land farmer environmental stewardship, 125–7 manure application techniques, 123–5 Lasalocid, 15 Leaf area index (LAI), 324 Leaf area ratio (LAR), 324 Leaf-electrolyte-leakage (LEL), 332 Leersia hexandra, 183 Leersia japonica, 180 Leersia oryzoides, 178 LEL. See Leaf-electrolyte-leakage LEL protocol, 333 Lemna minor, 29 Leptochloa chinensis, 178–80, 183, 185, 193 Leptochloa spp., 180 Lime treatment of slurry, 119 Limnocharis flava, 183 Limnophila erecta, 185 Lindernia spp., 178 Lint index, 324 Lint percentage, 324 Liquid livestock manure, on-farm design of electrolytic treatment for, 117 Liquid manure. See Slurry Listeria, 114 Listeria monocytogenes, 115 Lternanthera philoxeroides, 185 Ludwigia adscendens (L.), 178 Ludwigia hyssopifolia, 178 Ludwigia prostrata, 180 Lygodium flexuosum, 179

Macrolides, 6 Male eelpout (Zoarces viviparous), 33 Male fathead minnows (Pimephales promelas), 33 Malthus’s essay, 90 Manure, sterilization of, 110–11 Manure application techniques, 123–5 Mariscus cylindristachus, 179 Marsilea minuta, 209 Mature male goldfish (Carassius auratus), 33 MCF-7 cells, 34 Medroxyprogesterone, 36 Melastoma sp., 179 Melengestrol acetate (MGA), 9–10, 21 Melochia corchorifolia L., 178 Methanol, 46 MGA. See Melengestrol acetate MIC. See Minimal inhibitory concentrations Michx, 178 Microbial contamination of watercourses, risk of, 138 Microcystis aeruginosa, 28 Minimal inhibitory concentrations (MICs), 30 Modeled scenario analysis, 131 Monensin, 15, 19 Monochoria vaginalis, 183–4 Mosquitofish (Gambusia affnis), 35 Mummichog (Fundulus heteroclitus), 33 Murdannia keisak (Aneilema keisak), 180 Murdannia nudiflora, 178

N Natural ecosystems anthropogenic perturbations of, 80 converted to agriculture, land area of, 71–4 Natural resource management conducting research, new ways of, long-time engagement, 305–7 policy cycle, covering, 304–5 up- and downscaling by using sequences of models, 303–4 new messages to policymakers and land users, 307–8 ways to presenting results, 306–7 Nitrate vulnerable zones (NVZs), 100

INDEX Nitrogen cycle, 82–3 NVZ. See Nitrate vulnerable zones

O Oligolysis, 116 Oncorhynchus mykiss. See Rainbow trout Organic fertilizer, 107 Organophosphate (OP) insecticides, 119 Ormetoprim, 7 Oryza rufipogon Griff. See Wild rice Oryza sativa L. See Rice Oryzias latipes. See Japanese medaka Oxolinic acid, 20 Oxytetracycline, 6–7, 38

P Panicum cambogiense, 179 Panicum dichotomiflorum (L.), 178 Panicum laxum Sw., 179 Panicum repens L., 178 Panicum trichoides, 179 Paspalum conjugatum, 179 Paspalum distichum, 192 Paspalum scrobiculatum L., 178 Paspalum spp., 193 Pasteurization, 116 Pathogenic bacteria, 31 Pathogen numbers reduction, manure management for, 107 liquid manures aeration, 113–14 anaerobic digestion, 114–16 oligolytic treatment, 116–18 pasteurization, 116 slurry additives and disinfectants, 118–20 slurry storage, 111–13 livestock welfare animal health, 120–1 dietary supplementation, 121–2 solid manures composting, 108–10 storage, 107–8 thermal processing (drying), 110–11 Pathogen-stage transition, model of, 99 Penicillin, 6

393

Phosphorus cycle, 83 Photosynthesis, 322, 331, 341 Photosynthetically active radiation (PAR), 340 Photosynthetic electron transport, 354 Pima cotton cultivars, 344 Pima cotton (Gossypium barbadense L.), 315, 319, 327, 336 Pimephales promelas. See Male fathead minnows Platysoma africanum, 178–9 Policy cycle, research in relation to, 262–5 Pollution swapping, 138 Polygonum spp., 178 Poultry manure, 98 Prairie breaker, 74 Pregermination period, 157 Progesterone, 36 Protozoan pathogen attenuation, 128 Pseudokirchneriella subcapitata, 29 Puccinia canaliculata, 223 Pueraria thomsonii, 179

Q QTL. See Quantitative trait loci Quantitative trait loci (QTL), 336 alleles, 357 Quinolones/fluoroquinolones, 45–6

R Rainbow trout (Oncorhynchus mykiss), 34 Rainfed rice, 155 Ravoler-S, 10 Respiration, 331 Restricting livestock access to streams, 127 Rhynchosporium alismatis, 223 Rice cropping, 160 Rice establishment, weed species shifts and weed population dynamics due to changes in methods of weed population dynamics, 185–90 weed species shifts, 182–5 Rice (Oryza sativa L.), 153 direct seeding of (See Direct-seeding of rice) Riparian buffer strips, 131–2

394

INDEX

River Irvine catchment, Scotland, 125 Rotala indica, 180 Rubisco-carboxylase, 356 RuBP regeneration, 354

S Sagittaria guayenensis, 183 Sagittaria guyanensis H.B.K., 223 Sagittaria montevidensis, 179, 185 Salmonella, 102–3, 109 Salmonella dublin, 112 Salmonella spp., 29, 112, 114, 121 Salmonella typhimurium, 29, 115 Salmo salar. See Atlantic salmon Sarafloxacin, 45 SBHG. See Serum hormone binding globulin Schoenoplectus mucronatus, 178 Scirpus grossus, 185 Scirpus mucronatus, 179 Scirpus planiculmis, 185 Septic tank leakages, 106–7 Serum hormone binding globulin (SBHG), 34 Setaria viridis, 178 SFE. See Supercritical fluid extraction Shigella dysenteriae, 115 SIC. See Soil inorganic carbon pool Slurry, lime treatment of, 119 Slurry additives and disinfectants, 118–20 Slurry (liquid manure), 100 Slurry storage, 111–13 Soak-away process, 102 SOC pool. See Soil organic carbon pool Soil cation bridging in, 14–15 degradation for agricultural and forestry land uses, extent of, 75 perturbation, 74 and water resources, stewardship of, 86–9 Soil inorganic carbon (SIC) pool, 81 Soil organic carbon (SOC) pool, 81 Solid manure (farmyard manure), 101–2 composting, 108–10 storage, 107–8 thermal processing (drying), 110–11 Sorghum halepense, 165, 178 Sorption isotherms, 16 Source-mobilization-delivery, 97

Specific leaf weight (SLW), 324 Sphenoclea zeylanica, 179, 223 Sprinkler systems, 102 SSF. See Subsurface flow treatment wetlands Sterilization of manure, 110–11 Stomatal conductance, cotton, 365 ST 4793R, 355 Streptomyces, 15 Subsurface flow treatment wetlands (SSF), 135 Sulfadiazine, 20–1 Sulfadimethoxine, 7, 20–1 Sulfamerazine, 7 Sulfamethazine, 6, 44 Sulfathiazole, 6 Sulfonamide, 44–5 Sulfonamides, 6 Supercritical fluid extraction (SFE), 37 Swine finishing hoop systems, 11 SYNOVEXÒ PLUSÔ , 11 Synthetic pyrethroid (SP) insecticides, 119

T TBA. See Trenbolone acetate Testosterone in soil, 26 Tetracycline ELISA kit, 44 Tetracyclines, 6, 38–44 The metabolite O-mycaminosyltylonolide, 19–20 ‘‘The 4 point plan’’, 126–7 Thermal stress index, 339–40 Thermophilic aeration of cattle slurry, 113 TopManage, 134 Total suspended solids (TSS), 135 Transplanting rice, 155 Trema angustifolia, 179 17 -Trenbolone, 9, 34–6 Trenbolone acetate (TBA), 9–10, 34–6 Triticum aestivum, 29 TTS. See Total suspended solids Tylosin, 6, 20, 25 Tylosin A, 20

U Union of Concerned Scientists (UCS), 5 UN Millennium Development Goals (MDGs), 259 Urochloa platyphylla, 177

INDEX V VBS. See Vegetated buffer strips Vegetated buffer strips (VBS), 128–31 microbial efficiency of, 128 Veterinary antimicrobials, 14 Vibrio fischeri, 29 Vicia sativa, 29 W Watercourses, buffer strip efficiency for reducing fecal microbe delivery to, 129 Watergrass (Echinochloa phyllopogon), 210 Water-seeded rice fields, in Louisiana (USA), 194 Weed control, intervention methods of chemical method of, 200 dry-seeded rice, 200–8 wet-seeded rice, 210–11 manual and mechanical methods of, 198–200 Weed control, preventive methods of land preparation, 192–4 rice cultivars submergence tolerance, 197–8 weed competitiveness, 195–7 water management, 194–5 Weed control methods allelopathy, 222–3 bioherbicides, 223–4

395

Weed management technologies gene flow and its implications in weed management, 221 herbicide resistance in weeds and its management in direct-seeded rice, 216 herbicide-resistant transgenic rice and weed management in direct-seeded rice, 216–21 herbicide use, improving, 214–15 Weed population dynamics, 185–90 Weed species, associated with direct-seeded rice in different countries, 166–77 Weed species shifts, 182–5 Weedy rice (O. sativa) ecotypes, 178 Wet-seeded rice, 210–11 Wild rice (Oryza rufipogon Griff.), 213 Wild rice varieties, 178

Y Yersinia, 114 Yersinia enterocolitica, 115

Z Zebrafish (Danio rerio), 35 Zeranol, 33–4 Zoarces viviparous. See Male eelpout Zoonotic enteropathogens, 29