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 Univer...

Author: Donald L. Sparks

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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

xi

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

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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,


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

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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 liter1, 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 liter1 in the filtered aqueous portion and 2000 mg kg1 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 liter1 in the aqueous fraction and at 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


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 liter1 followed by estrogen at similar levels, which gradually decreased over a 3‐month period to nondetectable levels (100 mg liter1) or genotoxic eVects in Escherichia coli (6.25 to >100 mg liter1). The most sensitive species identified by Isidori et al. (2005) was the freshwater green alga Pseudokirchneriella subcapitata (EC50: 0.002–1.44 mg liter1), 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 liter1). 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 liter1), Brachionus calyciflorus (rotifer; EC50: 0.68–12.21 mg liter1), and Ceriodaphnia dubia (crustacean cladocera; EC50: 0.18–8.16 mg liter1). 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 kg1 reduced elongation of Triticum aestivum, and 1 mg kg1 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 day1, 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

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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 liter1 for chloramphenicol, 2–8 mg liter1 for nalidixic acid, 25 to >300 mg liter1 for penicillin G, and 1 to >80 mg liter1 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 liter1) were substantially lower than the MIC range (4–12.5 mg liter1), 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 liter1) 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


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

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(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 liter1) 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 liter1 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.


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 liter1 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 g1) (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 liter1, whereas complete sex reversals have been reported in fish larvae‐fed diets containing between 5 and 60 mg kg1 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 g1 food) and water (1–10 mg liter1) 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 1010 to 106 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

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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


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 kg1) 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 liter1) 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 liter1 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 liter1) 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 liter1) 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 liter1 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 liter1 versus 0.018 mg liter1 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

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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


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

L. S. LEE ET AL.

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


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)


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


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


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).


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


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 liter1 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.

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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 liter1 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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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

WORLD SOILS AND THE ENVIRONMENT

71

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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RATTAN LAL

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

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