Advances in Agronomy, Volume 109

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AGRONOMY

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ADVANCES IN AGRONOMY Advisory Board

PAUL M. BERTSCH

RONALD L. PHILLIPS

University of Kentucky

University of Minnesota

KATE M. SCOW

LARRY P. WILDING

University of California, Davis

Texas A&M University

Emeritus Advisory Board Members

JOHN S. BOYER

KENNETH J. FREY

University of Delaware

Iowa State University

EUGENE J. KAMPRATH

MARTIN ALEXANDER

North Carolina State University

Cornell University

Prepared in cooperation with the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America Book and Multimedia Publishing Committee DAVID D. BALTENSPERGER, CHAIR LISA K. AL-AMOODI

CRAIG A. ROBERTS

WARREN A. DICK

MARY C. SAVIN

HARI B. KRISHNAN

APRIL L. ULERY

SALLY D. LOGSDON

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DONALD L. SPARKS Department of Plant and Soil Sciences University of Delaware Newark, Delaware, USA

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

Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 32 Jamestown Road, London, NW1 7BY, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2010 Copyright # 2010 Elsevier Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-385040-9 ISSN: 0065-2113 (series) For information on all Academic Press publications visit our website at elsevierdirect.com Printed and bound in USA 10 11 12 10 9 8 7 6 5 4 3 2 1

CONTENTS

Contributors Preface

1. Climate Warming-Induced Intensification of the Hydrologic Cycle: An Assessment of the Published Record and Potential Impacts on Agriculture

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Thomas G. Huntington 1. 2. 3. 4.

Introduction Significance of an Intensification of the Hydrologic Cycle Trends in Hydrologic Variables Mount Pinatubo: The Natural Experiment in Aerosol Optical Depth 5. Hydrologic Responses to Intensification—Extreme Events (Including Droughts) 6. Potential Impacts on Agriculture 7. Conclusions Acknowledgments References

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29 31 35 36 37

2. Extent, Impact, and Response to Soil and Water Salinity in Arid and Semiarid Regions

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Karuppan Sakadevan and Minh-Long Nguyen 1. Introduction 2. Soil Salinity 3. Water Salinity 4. Responding to Soil and Water Salinity 5. Conclusions References

56 57 62 63 69 70

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Contents

3. The African Green Revolution: Results from the Millennium Villages Project

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Generose Nziguheba, Cheryl A. Palm, Tadesse Berhe, Glenn Denning, Ahmed Dicko, Omar Diouf, Willy Diru, Rafael Flor, Fred Frimpong, Rebbie Harawa, Bocary Kaya, Elikana Manumbu, John McArthur, Patrick Mutuo, Mbaye Ndiaye, Amadou Niang, Phelire Nkhoma, Gerson Nyadzi, Jeffrey Sachs, Clare Sullivan, Gebrekidan Teklu, Lekan Tobe, and Pedro A. Sanchez 1. Introduction 2. Description of the Village Clusters 3. Methodology 4. Results 5. Discussion and Way Forward 6. Conclusions Acknowledgments References

4. Interactions Among Agricultural Production and Other Ecosystem Services Delivered from European Temperate Grassland Systems

76 79 84 92 103 111 112 112

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Emma S. Pilgrim, Christopher J. A. Macleod, Martin S. A. Blackwell, Roland Bol, David V. Hogan, David R. Chadwick, Laura Cardenas, Tom H. Misselbrook, Philip M. Haygarth, Richard E. Brazier, Phil Hobbs, Chris Hodgson, Steve Jarvis, Jennifer Dungait, Phil J. Murray, and Les G. Firbank 1. Introduction 2. Methods 3. Interpreting the Interactions 4. Conclusions 5. Future Perspectives Acknowledgments References

5. Halting the Groundwater Decline in North-West India—Which Crop Technologies will be Winners?

118 119 122 141 143 144 144

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E. Humphreys, S. S. Kukal, E. W. Christen, G. S. Hira, Balwinder-Singh, Sudhir-Yadav, and R. K. Sharma 1. Introduction 2. The Hydrogeology and Development of Irrigation in North-West India 3. Water Sources, Sinks, Depletion, and Savings

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Contents

4. Effects of Improved Technologies on Yield, the Nature and Amount of Water Savings, and Water Productivity 5. General Discussion 6. Conclusions Acknowledgements References

6. Biological Control of Insect Pests in Agroecosystems: Effects of Crop Management, Farming Systems, and Seminatural Habitats at the Landscape Scale: A Review

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170 202 204 205 205

219

Adrien Rusch, Muriel Valantin-Morison, Jean-Pierre Sarthou, and Jean Roger-Estrade 1. Introduction 2. Arthropod Dynamics and Trophic Interactions within the Agricultural Landscape 3. The Role of Seminatural Habitats on Pest and Natural Enemy Populations 4. Natural Enemy Biodiversity and Insect Pest Suppression 5. Effects of Crop Management on Pests and their Natural Enemies 6. General Effects of Farming Systems on Natural Enemy Biodiversity, Pests, and Subsequent Biological Control 7. Integrating Farming Systems, Crop Management and Landscape Context to Understand Biological Control Mechanisms 8. Conclusions References Index

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CONTRIBUTORS

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

Balwinder-Singh (155) Charles Sturt University, Locked Bag 588 Wagga Wagga, NSW, Australia Tadesse Berhe (75) MVP Koraro cluster, Center for National Health Development, Addis Ababa, Ethiopia Martin S. A. Blackwell (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Roland Bol (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Richard E. Brazier (117) School of Geography, University of Exeter, Exeter, United Kingdom Laura Cardenas (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom David R. Chadwick (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom E. W. Christen (155) CSIRO Land and Water, PMB 3 Griffith, NSW, Australia Glenn Denning (75) The Earth Institute, Columbia University, New York Ahmed Dicko (75) MVP Tiby Cluster, Segou, Mali Omar Diouf (75) MVP Potou cluster, Louga, Senegal Willy Diru (75) MVP Sauri cluster, Kisumu, Kenya Jennifer Dungait (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Les G. Firbank (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom ix

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Contributors

Rafael Flor (75) MDG Center for West and Central Africa, Bamako, Mali Fred Frimpong (75) MVP Bonsaaso Cluster, Manso-Nkwata, Ashanti, Ghana Rebbie Harawa (75) MVP Mwandama Cluster, Zomba, Malawi Philip M. Haygarth (117) Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom G. S. Hira (155) Punjab Agricultural University, Ludhiana, Punjab, India Phil Hobbs (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Chris Hodgson (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom David V. Hogan (117) Environmental consultant, Exeter, United Kingdom E. Humphreys (155) International Rice Research Institute, DAPO 7777, Metro Manila, Philippines Thomas G. Huntington (1) U.S. Geological Survey, Augusta, Maine, USA Steve Jarvis (117) European Journal of Soil Science, Peninsula Partnership for the Rural Environment, Centre for Rural Policy Research, University of Exeter, Exeter, United Kingdom Bocary Kaya (75) MVP Tiby Cluster, Segou, Mali S. S. Kukal (155) Punjab Agricultural University, Ludhiana, Punjab, India Christopher J. A. Macleod (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Elikana Manumbu (75) MVP Mbola Cluster, Tabora, Tanzania John McArthur (75) Millennium Promise, New York, USA and The Earth Institute, Columbia University, New York

Contributors

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Tom H. Misselbrook (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Phil J. Murray (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Patrick Mutuo (75) MVP Sauri cluster, Kisumu, Kenya Mbaye Ndiaye (75) MVP Potou cluster, Louga, Senegal Minh-Long Nguyen (55) Soil and Water Management and Crop Nutrition Section, International Atomic Energy Agency, Vienna, Austria Amadou Niang (75) MDG Center for West and Central Africa, Bamako, Mali Phelire Nkhoma (75) MVP Mwandama Cluster, Zomba, Malawi Gerson Nyadzi (75) MVP Mbola Cluster, Tabora, Tanzania Generose Nziguheba (75) The Earth Institute, Columbia University, New York Cheryl A. Palm (75) The Earth Institute, Columbia University, New York Emma S. Pilgrim (117) Rothamsted Research, North Wyke, Okehampton, United Kingdom Jean Roger-Estrade (219) INRA/AgroParisTech, UMR211 Agronomie, Thiverval-Grignon, France Adrien Rusch (219) INRA/AgroParisTech, UMR211 Agronomie, Thiverval-Grignon, France Jeffrey Sachs (75) The Earth Institute, Columbia University, New York Karuppan Sakadevan (55) Soil and Water Management and Crop Nutrition Section, International Atomic Energy Agency, Vienna, Austria Pedro A. Sanchez (75) The Earth Institute, Columbia University, New York

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Contributors

Jean-Pierre Sarthou (219) INRA, INPT/ENSAT, UMR1201 Dynamiques Forestie`res dans l’Espace Rural (UMR Dynafor), Castanet-Tolosan, France R. K. Sharma (155) Directorate of Wheat Research, Karnal, Haryana, India Sudhir-Yadav (155) The University of Adelaide, Adelaide, SA, Australia Clare Sullivan (75) The Earth Institute, Columbia University, New York Gebrekidan Teklu (75) MVP Koraro cluster, Center for National Health Development, Addis Ababa, Ethiopia Lekan Tobe (75) MVP Pampaida Cluster, Zaria, Kaduna State, Nigeria Muriel Valantin-Morison (219) INRA/AgroParisTech, UMR211 Agronomie, Thiverval-Grignon, France

PREFACE

Volume 109 contains six first-rate reviews dealing with topics that are of pressing global interest, including climate change, food production and food security, water supply and quality, soil degradation, and insect control. Chapter 1 is a very relevant review on the impact of climate warming on the hydrologic cycle. Chapter 2 provides contemporary information on the degree and impact of soil and water salinity in arid and semiarid regions. Chapter 3 addresses the successful and important efforts of the Millennium Village project in promoting a “Green Revolution” in Africa. Chapter 4 covers interactions among agricultural production and other ecosystem services gained from European temperate grassland systems. Chapter 5 discusses the role of crop technologies in mitigating the serious groundwater degradation in North West India. Chapter 6 is a comprehensive review on biological control of insect pests in agrosystems and the role of management, farming systems, and seminatural habitats on a landscape scale. I am grateful to the authors for their outstanding reviews, which will be of great interest to the broad readership of Advances in Agronomy. DONALD L. SPARKS Newark, Delaware, USA

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Climate Warming-Induced Intensification of the Hydrologic Cycle: An Assessment of the Published Record and Potential Impacts on Agriculture Thomas G. Huntington Contents 1. Introduction 1.1. The hydrologic cycle 1.2. Intensification of the hydrologic cycle 2. Significance of an Intensification of the Hydrologic Cycle 3. Trends in Hydrologic Variables 3.1. Evaporation and evapotranspiration 3.2. Atmospheric water vapor 3.3. Changes in cloudiness 3.4. Precipitation 3.5. Runoff 3.6. Soil Moisture 3.7. Precipitation recycling 4. Mount Pinatubo: The Natural Experiment in Aerosol Optical Depth 5. Hydrologic Responses to Intensification—Extreme Events (Including Droughts) 6. Potential Impacts on Agriculture 6.1. General findings and projections 6.2. Primary effects on forests 6.3. Potential primary effects on cropland, pasture, and livestock 7. Conclusions Acknowledgments References

2 2 4 7 9 9 17 18 19 21 26 26 27 29 31 31 32 33 35 36 37

U.S. Geological Survey, Augusta, Maine, USA Advances in Agronomy, Volume 109 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)09001-2

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Thomas G. Huntington

Abstract Climate warming is expected to intensify and accelerate the global hydrologic cycle resulting in increases in evaporation, evapotranspiration (ET), atmospheric water-vapor content, and precipitation. The strength of the hydrologic response, or sensitivity of the response for a given degree of warming, is a critical outstanding question in climatology and hydrology. In this review chapter, I examine the published record of trends in various components of the hydrologic cycle and associated variables to assess observed hydrologic responses to warming during the period of observational records. Global and regional trends in evaporation, ET, and atmospheric water-vapor content and several large river basin waterbalance studies support an ongoing intensification of the hydrologic cycle. Global trends in precipitation, runoff, and soil moisture are more uncertain than the trends in the variables noted above, in part because of high spatial and temporal variability. Trends in associated variables, such as systematic changes in ocean salinity, the length of the growing season, and the rate of precipitation recycling are generally consistent with intensification of the hydrologic cycle. The evidence for an increase in the frequency, intensity, or duration of extreme-weather events like hurricanes is mixed and remains uncertain. The largest potential impacts to agricultural systems depend greatly on the responses of hydrologic variables that are the most uncertain; for example, intensity and duration of heavy rainfall events; frequency, intensity, and duration of major storms and droughts; and rates of erosion. Impacts on agriculture will depend greatly on how insects, diseases, weeds, nutrient cycling, effectiveness of agrichemicals, and heat stress are affected by an intensification of the hydrologic cycle.

1. Introduction 1.1. The hydrologic cycle The Earth’s hydrologic cycle is driven by solar energy that provides the heat necessary for evaporation (E), transpiration, and sublimation. Over land areas, the sum of evaporation and transpiration is defined as evapotranspiration (ET). Water flux associated with evaporation over the oceans is estimated to be about 413
103 km3 a 1and ET over land is estimated to be about 73
103 km3 a 1 (Trenberth et al., 2007a; Fig. 1). Water vapor in the atmosphere derived from these sources is estimated to be about 12.7
103 km3. Water vapor condenses and precipitation (P) falls as rain or ice (e.g., sleet, snow, hail). Over land P is then either evaporated, transpired, sublimated, or eventually flows back to the oceans as surface water or submarine groundwater discharge, thus completing the hydrologic cycle. The fluxes shown in the hydrologic cycle (Fig. 1) from Trenberth et al. (2007a) are constrained to balance; for example, P  E over land (40,000 km3 a 1) is equal to E  P over the oceans. The estimates of

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Climate Warming-Induced Intensification of the Hydrologic Cycle

Atmosphere 12.7 Ocean to land water vapor transport 40 * * ** * * * * ** Land * ** precipitation * 113

* * ** * * * ** * ** * * Ocean precipitation 373 Ocean Ice evaporation 413 26,350

Evaporation + transpiration 73

Surface flow 40

Ocean 1,335,040

Rivers and lakes 178

Permafrost 22 Groundwater 15,300

Figure 1 The hydrologic cycle. Estimates of the main water reservoirs, given in plain font (103 km3), and the flow of moisture through the system, given in italic font (103 km3 a 1). Modified from Trenberth et al. (2007a), and used with permission.

individual fluxes are not well constrained and recent hydrologic budgets differ in various fluxes and stores (e.g., Oki and Kanae, 2006; Shiklomanov and Rodda, 2003). Evaporation is larger than P over the oceans and this difference is the water vapor that is transported from the oceans to land, resulting in an excess of P over ET over land. To balance the global water budget, the excess (or positive P  E) over land must be equal to total continental runoff þ groundwater discharge to the oceans  the net change in storage terms. Changes in net storage, including in surface water, groundwater, and in the mass of ice and snow on land (Greenland and Antarctic ice sheets and non-ice-sheet glaciers (e.g., ice caps, ice fields, mountain glaciers)), and precipitation recycling over land complicate this simple cycle, but are ignored in this depiction of the global water cycle. Climate change can affect all aspects of the hydrologic cycle through its effect on the Earth’s energy budget (Bates et al., 2008; Kundzewicz et al., 2007; Trenberth et al., 2007b). One of the most important consequences of climate warming on the hydrologic cycle is thought to be an intensification of the cycle itself. (DelGenio et al., 1991; Held and Soden, 2000, 2006; Huntington, 2006; Loaciga et al., 1996; Trenberth, 1999). There are many hydrologic responses to climate change, the potential impacts of

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these responses are far-reaching, and are likely to affect agriculture, forestry, availability of fresh water, habitat sustainability, forest-fire incidence and intensity, pests and pathogens (Bates et al., 2008; Kundzewicz et al., 2007). Another critically important impact of climate warming on the hydrologic cycle involves an increase in atmospheric water-vapor content and the consequent positive feedback on warming because water vapor is a radiatively active “greenhouse” gas in its own right.

1.2. Intensification of the hydrologic cycle Intensification of the hydrologic cycle is here defined as an acceleration or increase in the rates of E, ET, and P. In other words, intensification is an increase in the flux of water between existing ocean, atmosphere, terrestrial, freshwater, and cryospheric pools. It is recognized that as the climate warms and the hydrologic cycle intensifies, it is likely that there will be an increase in the temporal and spatial variability of precipitation and in the intensity and duration of storms and droughts. It is likely that some regions will get wetter and some will get drier, but overall, on a global scale, the fluxes shown in Fig. 1 will increase. The scientific basis for a warming-induced intensification of the hydrologic cycle is that the rate of evaporation increases with increasing temperature and that warmer air will hold more moisture. The relation between surface air temperature and atmospheric water vapor is described by the Clausius–Clapeyron equation that indicates that water vapor will increase by about 7% K 1 (Held and Soden, 2000). Many scientists also conclude that an increase in the frequency, intensity, or duration of major storms would be another consequence of a warminginduced intensification of the hydrologic cycle (e.g., Knutson and Tuleya, 2004; Kundzewicz et al., 2007; Wetherald and Manabe, 2002). It is important to note that increasing P over land does not necessarily imply an increase in continental runoff because it is possible that increases in ET could balance increases in precipitation. Another way of looking at intensification is to consider the case where, for a given region, the net influx of water vapor from outside that region does not increase but P and ET do increase over that region. This would be the case if the P recycling ratio was increasing (e.g., Dirmeyer and Brubaker, 2006; Dominguez et al., 2006). It is widely believed that climate warming has the potential to intensify the hydrologic cycle and increase the concentration of water vapor in the atmosphere, but there is considerable debate about whether the increase will scale according to the Clausis–Clapeyron equation, or at some substantially lower rate (e.g., Allen and Ingram, 2002; Wentz et al., 2007). Allen and Ingram (2002) noted that the mean sensitivity of precipitation to warming of a number of global circulation model (GCM) analyses was approximately 3.4% K 1. Recent analyses of observational data on atmospheric water-vapor content, P, and ET support increases at rates that are more consistent with

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Climate Warming-Induced Intensification of the Hydrologic Cycle

pe

yr

on

15

la

us

iu

s−

C la

10

5

C

Precipitation change (%)

predictions based on the Clausius–Clapeyron equation of about 7% K 1 (Allan and Soden, 2007; Wentz et al., 2007; Willet et al., 2008; Zhang et al., 2007). However, uncertainty remains in the sensitivity of this response to warming (e.g., John et al., 2009). This discrepancy between GCM outputs and observations during the late twentieth century is critically important for understanding the sensitivity of the hydrologic response to future warming. This problem is graphically illustrated in an adaptation of Allen and Ingram’s (2002) original figure that shows sensitivity of the GCMs versus these recent observations (Fig. 2). Resolving this question of the sensitivity of hydrologic fluxes to climate warming may be one of the more fundamental questions in climatology and hydrology, because the potential impacts associated with intensification would be greatly amplified under a system with higher sensitivity, thereby necessitating more aggressive adaptation. The importance of this question is emphasized by historical observed and twenty-first century projected surface air-temperature increases (Trenberth et al., 2007b). These projections reported by the IPCC in their Fourth Assessment report have recently been updated and now indicate that the upper ranges of the 2007 projections are increasingly likely (Rahmstorf et al., 2007; Smith et al., 2009; UNEP, 2009). The fact that atmospheric CO2 concentrations are rising more rapidly than expected (Canadell et al., 2007; Raupach et al., 2007) and climate warming appears to be progressing more rapidly than thought likely in 2007 (e.g., Sokolov et al., 2009) could be attributed to several processes, including ocean acidification, which results in decreased ocean uptake CO2 (e.g., Moy et al., 2009; Park et al., 2008a; Wootton et al., 2008); a possible decrease in land-based carbon sinks (Canadell et al., 2007; Cramer et al.,

0 0

1

2 3 4 Temperature change (K)

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Figure 2 Global-mean temperature and precipitation changes in a wide range of equilibrium CO2 doubling AOGCM simulations (scatter plots) with simple thermodynamic (“slab”) oceans. The solid line shows the best-fit (least squares) linear relationship. All these points would lie on the dashed line if precipitation were to follow the Clausius–Clapeyron. Modified from Allen and Ingram (2002), and used with permission.

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2001; Piao et al., 2008); methane release from degrading permafrost (e.g., Heginbottom et al., in press; Walter et al., 2006); decreases in albedo from declines in Arctic Ocean sea-ice cover (Comiso et al., 2008; Parkinson and Cavaliere, in press); stronger carbon-cycle feedbacks than once thought (Scheffer et al., 2006); poleward migration of vegetation (ACIA, 2004; McGuire et al., 2009) and associated decrease in albedo; higher than expected global CO2 emissions (Auffhammer and Carson, 2008; Raupach et al., 2007; UNEP, 2009); and increase in particulates in the atmosphere such as black carbon (soot) (Ramanathan and Carmichael, 2008). Some negative (cooling) feedbacks may not be as important as once thought; for example, nutrient or water limitations could minimize the capacity of vegetation to assimilate carbon at faster rates under conditions of higher atmospheric CO2 (Leakey et al., 2006, 2009; Long et al., 2006; Thornton, et al., 2009). Gains in water-use efficiency caused by higher atmospheric CO2 concentrations (Gedney et al., 2006) may not be as effective as previously hypothesized (Huntington, 2008). The direction of all of these trends and the implications of potential hydrologic responses add urgency to gaining a better understanding of the sensitivity of the hydrologic cycle to future warming. One approach for gaining insight into this question has been to assess the published observational evidence for or against historical increases in rates of E, ET, P, and other related variables that might indicate hydrologic responses to warming during the twentieth century. This approach has distinct limitations because of a lack of data for comprehensive spatial and temporal coverage, differences in methodologies, and high natural interannual variability, which requires multidecadal time series to conclusively confirm trends detection (Ziegler et al., 2003). There are also errors associated with measurement, estimation of missing data, and spatial averaging. There are large variations among regions (spatial variations) and, in some cases, trends that have reversed (temporal variations) during the period of record. Some of the studies cited in this review have not addressed the potential effects of decadal or multidecadal persistence associated with large-scale patterns of climate variability (climate indices) like the El Nino Southern Oscillation, the Pacific Decadal Oscillation, and the North Atlantic Oscillation. In spite of these concerns, assessments of this type complement modeling studies and lend insight to the problem through synthesis of relevant available data. One such study at the global scale suggested that the weight of evidence supported intensification during the twentieth century (Huntington, 2006). Wentz et al. (2007) examined short-term trends analyzed from satellite-sensor data and concluded that P, E, and atmospheric water-vapor content increased during 1987 through 2006. Regional studies have also substantiated evidence for intensification in Canada (De´ry et al., 2009) and the pan-Arctic region (Rawlins et al., in press; Holland et al., 2006, 2007; Zhang et al., 2009).

Climate Warming-Induced Intensification of the Hydrologic Cycle

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The objective of this chapter is to review the published findings on global and regional trends in various components of the hydrologic cycle and associated variables that could lend insight into the sensitivity of the hydrologic cycle to future warming. Some of this information has been included in earlier IPCC and regional assessments and reviews (e.g., Huntington, 2006; Ziegler et al., 2003), but many more recently published reports are now available that, taken together, provide a more comprehensive analysis. The majority of the studies reviewed involve analysis of historical observational data. In some instances, particularly where data are sparse either spatially or temporally, studies are included that have used modeling as a substitute for missing data. Some studies also include projections of future responses, although a thorough treatment of model forecasts is beyond the scope of this review. As a general rule, there is substantially more uncertainty in GCM projections regarding future rates of precipitation when compared with future temperatures given in prescribed emission scenarios (Bates et al., 2008; Kundzewicz et al., 2007; Trenberth et al., 2007b). This review begins with a discussion of the significance of intensification of the hydrologic cycle, addressing the question “Why should we care about the sensitivity of this response?” This section is followed by the main body of the chapter in which trends in components of the hydrologic cycle and associated variables are reviewed. The next sections discuss the effect of the explosive 1991eruption of Mount Pinatubo, Philippines, on the hydrologic cycle (Trenberth and Dai, 2007), and the evidence for trends in extreme-weather events. The final section of the chapter addresses the implications of an intensification of the hydrologic cycle for agricultural systems.

2. Significance of an Intensification of the Hydrologic Cycle Water vapor is the most important radiatively active “greenhouse” gas, accounting for approximately 60% of planetary atmospheric heat trapping (Kiehl and Trenberth, 1997). Significant changes in atmospheric water-vapor content would therefore have profound effects on the Earth’s radiation budget and resultant surface air temperature. Surface air-temperature warming caused by an increase in other greenhouse gasses (e.g., CO2, CH4, CFCs, N2O, etc.) will very likely result in an increase in atmospheric water-vapor, further amplifying climate warming in what is termed the “water-vapor feedback” process (Held and Soden, 2000, 2006). A lack of understanding of the sensitivity of water-vapor feedback to future warming is one of the reasons for the relatively large differences in GCM climate projections. The higher the sensitivity, the greater the water-vapor feedback and the greater the amplification of warming due to other greenhouse gasses.

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Apart from the water-vapor feedback, there are many other concerns arising from an intensification of the hydrologic cycle. One of the chief concerns is the possibility that intensification will result in an increase in “extreme” weather events, including major storms, floods, and droughts (Bates et al., 2008; Kundzewicz et al., 2007; Tebaldi et al., 2006). An increase could include an increase in intensity, frequency, and/or duration of extreme events, as well as an increase in overall variability in the magnitude, timing, and sequence of weather events. The implications of an increase in extreme events are many and varied; they range from increased risk of flood-related mortality and damage to infrastructure to more frequent and severe crop losses, increases in soil erosion, loss of forest productivity, increased risk of fire and disease, and stress caused by insect infestations. It is likely that some regions will get drier and the frequency of severe drought may increase. This has major consequences for the sustainability of water resources, especially in arid and semiarid areas. Regionally, there are likely to be large changes in the amount of freshwater stored in soils, aquifers, natural lakes and reservoirs, and in snowpack and glaciers that will also influence resource availability (e.g., Barnett et al., 2008). Another concern is that changes in extreme events would adversely affect systems for the management of wastewater and storm runoff because conditions that were once considered to be extremely rare events, and, therefore, not properly engineered for, may become more common (Milly et al., 2008). In some areas (e.g., in the northeastern United States; Burakowski et al., 2008; Hayhoe et al., 2007), reductions in the seasonal duration that snow cover is on the ground will decrease albedo, which is a positive feedback that will amplify warming. An increase in winter precipitation, with more precipitation expected to fall as rain rather than snow would likely change the timing and volume of groundwater recharge and stream runoff. Although more runoff is likely to occur during winter and early spring, the size of the spring freshet (snowmelt) is likely to be reduced because the amount of snow cover at the beginning of spring is likely to decrease over time as more winter precipitation falls as rain rather than snow. If the ground is frozen, no groundwater recharge will occur during rainfall, and there will be an increase in runoff. If snow cover is absent when the ground does thaw, less infiltration will take place, and less groundwater recharge will occur. Intensification-related increases in specific humidity could have adverse effects on human health and the health of crops and forests. Increases in specific humidity are likely to exacerbate the problem of heat stress (Gaffen and Ross, 1998). Although relative humidity is not expected to increase with increasing temperature, specific humidity is, and the human body’s ability to dissipate heat is inversely proportional to specific humidity ( Jendritzky and Tinz, 2009). Heat stress caused by increasing temperature alone is already a major concern associated with projections for increases in

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the number of days of extremely high temperatures (Trenberth et al., 2007b), but projected increases in heat stress will be felt more acutely under conditions of higher specific humidity. Increases in specific humidity could result in increases in susceptibility of plants to diseases, in particular, less resistance to fungal infections (Hatfield et al., 2008). Increases in specific humidity may adversely influence harvesting and susceptibility of harvested crops to fungal infections and insect damage (Hatfield et al., 2008). Increases in specific humidity could increase stomatal conductance (Wang et al., 2009) leading to a decrease in water-use efficiency and increases in plantwater stress. To the extent that, in some regions and during some seasons, intensification will result in an increase in ET that is greater than any increase in P, soil-moisture content will decrease accordingly. Decreases in soil moisture could increase plant-water stress. It is important to note that these conditions can lead to seasonal short-term drought (soil-moisture deficits) in spite of increases in average annual precipitation (e.g., Hayhoe et al., 2007). Seasonal decreases in soil moisture can also adversely affect sensitive biota. For example, pool-breeding amphibians have minimum soil-moisture requirements during the parts of their life cycles spent in soil burrows; decreases in soil moisture and decreases in pool hydroperiod could adversely affect their survival (Brooks, 2009; Semlitsch, 2000).

3. Trends in Hydrologic Variables 3.1. Evaporation and evapotranspiration Solar radiation drives the hydrologic cycle by providing the energy for evaporation and ET. Long-term measurements of these components of the hydrologic cycle are excellent indicators of the intensity of the hydrologic cycle. However, direct measurements of these fluxes over large landscapes are not possible. This section will briefly describe direct measurements from evaporation pans, small plots using massive-weighing lysimeters, and eddy-covariance-flux towers, and will discuss in substantially more detail a number of indirect measurements or measurements of associated variables that can be used to infer trends in evaporation and ET. The indirect measurements include water-balance studies, land-surface modeling, ocean salinity, and satellite measurements. Associated variables include the length of the growing season. 3.1.1. Direct measurements The original massive-weighing lysimeters employed in the former Soviet Union and United States beginning about 1950 could measure ET associated with a change in mass equivalent to 0.25 mm of water per hour in a

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monolith 8 m
2 m and 2 m deep (Harrold and Dreibelbis, 1967). Golubev et al. (2001) reported increasing ET during the post-WWII to 1990 period at most sites in the former Soviet Union using these lysimeters. They reported significant increasing trends at two grassland (steppe) sites and one forest site; increasing, but not significant trends at another forest site, mixed trends at another forest/steppe site, and decreasing, but not significant trends at two taiga sites. These plots had native vegetation and received only natural rainfall. Another method for direct measurement of the net exchange of water vapor between terrestrial landscapes and the atmosphere involves the use of the eddy-covariance-flux approach that can compute flux from high-temporal-resolution measurements of vertical wind speed and watervapor-concentration gradients above the soil and the vegetation canopy. The two largest networks of sites with this type of data are EUROFLUX (Aubinet et al., 2002) and Fluxnet (Law et al., 2002). Although there are no long-term ET measurements with which to evaluate trends anywhere, measured ET is positively correlated with growing-season temperature (GST) for humid regions at the Fluxnet sites. In the Fluxnet program, water-vapor exchange has been measured continuously for several years over forest, grassland, and agricultural ecosystems. Plotting annual ET against GST reported by Law et al. (2002) results in a significant (p-value < 0.0001) positive relation (Pearson’s r2 ¼ 0.58) (Fig. 3). Ordinary least-squares, simple 900 800

AET (mm)

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Figure 3 Annual actual evapotranspiration (AET) versus growing-season temperature for all Fluxnet data reported in Law et al. (2002), except for Aberfeldy, Scotland, in 1997 that was excluded because of a negative value for AET. Line shown is the ordinary least-squares simple linear regression. Modified from Huntington (2006), and used with permission.

Climate Warming-Induced Intensification of the Hydrologic Cycle

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linear regression gives a best-fit line of ETmm ¼ 115 þ 19.7
GST C, indicating a sensitivity of 19.7 mm ET per  C across a broad range of forest ecosystems in Europe and North America and two grassland and two cropland sites in the United States (Huntington, 2006). This relation between ET and temperature suggests that observed temperature increases during the twentieth century may have resulted in increasing ET where moisture is not limiting. Decreases in pan evaporation were observed over most of the United States and the former USSR between 1950 and 1990 (Peterson et al., 1995). Such decreases were generally thought to be inconsistent with observed trends toward increasing temperature and precipitation, resulting in an “evaporation paradox” (Brutsaert and Parlange, 1998). Several analyses have suggested, however, that decreasing pan evaporation is consistent with increasing surface warming and an acceleration of the global hydrologic cycle (Brutsaert, 2006; Brutsaert and Parlange, 1998; Golubev et al., 2001; Roderick and Farquhar, 2002; Szilagyi et al., 2002). Various mechanisms have been suggested to explain the apparent paradox. For example, it has been suggested that decreases in solar irradiance (what some have called “global dimming,” Wild, 2009) resulting from increasing cloud cover and aerosol concentrations, and decreases in diurnal temperature range (DTR) would cause the observed decrease in pan evaporation (Peterson et al., 1995; Roderick and Farquhar, 2002). Brutsaert and Parlange (1998) concluded that increasing water-vapor concentration resulting from a warminginduced increase in ET would inhibit pan evaporation. Golubev et al. (2001) concluded that the observed opposing trends supported the mechanism proposed by Brutsaert and Parlange (1998). These analyses build on application of the principle of complementarity that pan evaporation (a surrogate for potential evaporation) is in a complementary relationship with actual evapotranspiration (AET) (Brutsaert and Parlange, 1998; Kahler and Brutsaert, 2006). The complementary relation states that for fixed radiation inputs in water-limited environments (i.e., excluding land surfaces where free water is exposed to the atmosphere; e.g., wetlands, swamps, rice paddies), as aridity increases, measured pan evaporation will increase, but actual AET will decrease because soil moisture becomes increasingly more limited. Conversely, in water-limited environments, as soil moisture increases (decreasing aridity), AET will increase and pan evaporation will decrease. This decrease in aridity is associated with an increase in specific humidity and a decrease in vapor pressure deficit that, in turn, would suppress evaporation from the free-water surface of a pan. The complementary relation in water-limited environments was recently verified experimentally at two sites in the United States by Kahler and Brutsaert (2006). In another recent study Roderick et al. (2007) reported that the decrease in evaporation in Australia during 1975–2004 was mostly due to decreasing wind speed. The issue of whether trends in pan evaporation indicate an

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intensification of the global hydrologic cycle and the role of global dimming and brightening may not be fully resolved (Ohmura and Wild, 2002; Roderick et al., 2009; Wild, 2009; Wild et al., 2004), but the analyses of Brutsaert and Parlange (1998), Golubev et al. (2001), Brutsaert (2006), and Szilagyi et al. (2002) support increasing ET during this period. 3.1.2. Indirect measurements 3.1.2.1. Water-balance studies Arguably the most compelling evidence for change in the rate of ET from large land areas with multidecadal record length comes from river basin water-balance studies. In these studies, the objective is to estimate ET as the difference between precipitation and runoff, usually on an annual basis. This approach assumes that there are no significant net changes in water storage within the basin (or that the changes could be quantified) such as depletion or accumulation of groundwater, surface water, soil moisture, or snow and ice. In many moist-to wettemperate systems, the assumption of no significant change in storage relative to the magnitude of rainfall and runoff appears to be appropriate. In addition, having many years in the dataset would tend to “average out” small net changes in storage during wet versus dry years. This approach also assumes that there is no significant interbasin exchange or loss of water through groundwater. As basin size decreases, these assumptions become more tenuous. Both precipitation and runoff have increased during the twentieth century in the Mississippi River Basin (Milly and Dunne, 2001; Walter et al., 2004). However, increases in precipitation were substantially higher than increases in runoff, indicating that ET had also increased. Milly and Dunne (2001) reported that the rate of increase in ET from 1949 through 1997 was 0.95 mm a 2. Qian et al. (2007) studied trends in surface-water and energy-budget components of the Mississippi River Basin from 1948 to 2004 using a combination of observations and model simulations and also concluded that ET had increased. Walter et al. (2004) also estimated ET using the water-balance method for several large basins in the United States (Mississippi, Colombia, Colorado, Susquehanna, Sacramento, and southeastern U.S. basins) and found that, on average, ET was increasing at a rate of 1.04 mm a 2 from 1950 to 2000 (Fig. 4). Similar analyses for the La Plata River Basin in southeastern South America, the second largest basin in South America, are consistent with increasing ET (Berbery and Barros, 2002). Berbery and Barros (2002) reported that precipitation had increased by 16%, runoff had increased by 35%, and ET by 9% between the periods 1951–1970 and 1980–1999. This increase in ET corresponds to a rate of 1.29 mm a 2 during the 49 years of record. Streamflow has been stable or decreasing in recent decades in most of Canada (De´ry and Wood, 2005; De´ry et al., 2005; Rood et al., 2005; Schindler and Donahue, 2006) but precipitation has been increasing

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A Susquehanna Columbia

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Figure 4 River basins studied (A), and trend in the area-weighted difference between annual precipitation and annual stream discharge from 1950 to 2000 (B). Modified from Walter et al. (2004), and used with permission.

(Zhang et al., 2000). Together, these observations suggest that ET has been increasing. The most recent analysis of streamflow in northern Canada shows a reversal of trends toward increasing rates of discharge to polar seas from 1989 to 2007 (De´ry et al., 2009). 3.1.2.2. Satellite data and modeling using meteorological and landscape data Wentz et al. (2007) used satellite observations from the Special Sensor Microwave Imager (SSM/I) from 1987 to 2006 to measure

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precipitation, total water vapor, and surface-wind stress over the oceans and a blend of satellite and land-based precipitation gages. ET over the oceans was computed using National Center for Atmospheric Research Community Atmospheric Model 3.0 and ET over land was assigned a constant value of 527 mm a 1 for all of the continents, excluding Antarctica where a value of 28 mm a 1 was used (Wentz et al., 2007). Their analysis suggested that ET, precipitation, and total water vapor had all increased at rates of approximately 7% K 1 over this period. Fernandes et al. (2007) studied trends in ET across Canada (but predominantly in southern Canada) using 1960–2000 meteorological data from 101 sites and a land-surface model. They found that 81 sites had increasing trends (35 were statistically significant) and that the increases were related to temperature, total downwelling surface radiation, and precipitation. Using another land-surface model, Park et al. (2008b) reported that ET was increasing in the Lena River in eastern Siberia. Serreze et al. (2003) concluded that ET was increasing in the Yenisey River in eastern Siberia where ET was computed from P and P  ET, which was computed from the vertically integrated vapor-flux convergence adjusted by the time change in precipitable water. Wang et al. (in press, 2010) used a semiempirical model and observations of surface solar radiation, surface air temperature, humidity, and vegetation at 265 sites over the period 1982–2002 and estimated that 77% of the sites had increasing ET. Zhang et al. (2009) used satellite-remote-sensing inputs, including AVHRR GIMMS NDVI, MODIS land cover and NASA/GEWEX solar radiation and albedo, and regionally corrected NCEP/NCAR Reanalysis daily surface meteorology to develop an algorithm for ET. They determined that temporal trends in ET showed generally positive trends over the pan-Arctic basin and Alaska during the period 1983 to 2005. Zhang et al. (2009) concluded that their data on all components of the water cycle indicated that the hydrologic cycle was intensifying. 3.1.2.3. Ocean salinity Possible trends in evaporation over the oceans and their relation to precipitation and runoff have been addressed indirectly using ocean salinity time-series data. Salinity in the upper water column (surface to approximately 1000-m depth) increased significantly between the periods 1955–1969 and 1985–1999 along a transect in the western basin of the Atlantic Ocean at latitudes between 40 N and 20 S (Fig. 5). (Curry et al., 2003). Curry et al. (2003) also reported systematic freshening poleward of these latitudes. The salinity increase was spatially coherent with measured warming of the sea surface (Curry et al., 2003). Increases in salinity were attributed to changes in evaporation and precipitation because no additional sources of salt exist (from mixing) for these maximum salinity

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EXPLANATION Salinity difference (1985-99) – (1955-69), in practical salinity units 0.5 Saltier 0.1

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Figure 5 Salinity difference (1985–1999) minus (1955–1969) by depth along a western Atlantic Ocean meridonal transect from 64 S latitude (Antarctica) to 80 N latitude (Fram Strait). Black indicates ocean bottom and gray indicates missing data. Modified from Curry et al. (2003), updated and used with permission.

waters (Curry et al., 2003). For 24 N latitude (the salinity maximum), the inferred evaporation  precipitation (E  P) anomaly averaged 5 cm a 1 during the 40-year period (Curry et al., 2003). The increase in E  P could be a result of increases in E or decreases in P. There is no evidence for a decrease in P, and satellite-derived increases in E, SST, and P for this region during 1987 through 2006 (Wentz et al., 2007) support an increase in E as the explanation for the long-term salinity anomaly. Sea-surface warming over the same region and time period as the salinity anomaly suggests an increase in net evaporation that is consistent with predictions derived from the Clausius–Clapeyron equation and possible changes in the hydrologic cycle (Curry et al., 2003). In another recent study covering 1950–2008 Durack and Wijffels (2010) reported similar results in a study of the Atlantic, Pacific, and Indian Ocean from 1950 to 2008. They reported salinity increases in evaporation-dominated regions and freshening in precipitation-dominated regions with the spatial pattern of change similar to the mean salinity field. Increases in salinity also have been reported in some subtropical regions of the Pacific Ocean (Boyer et al., 2005; Wong et al., 1999) and in the Mediterranean Sea (Be´thoux et al., 1998; Roether et al., 1996). Wong et al. (1999) concluded that the salinity changes observed in the Pacific Ocean were consistent with a “strengthening” of the water cycle during an average 22-year period from the mid- to late-1960s to the mid- to late-1980s. Boyer et al. (2005) largely confirmed the trends reported by Curry et al. (2003) for the Atlantic and reported increasing salinity for the Indian Ocean.

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However, the Boyer et al. (2005) findings contrasted with Wong et al. (1999) for the Pacific Ocean. For the Pacific Ocean, Boyer et al. (2005) found no trends in the Tropics or Northern Hemisphere subtropics, but evidence for increasing salinity in the Southern Hemisphere subtropics and generally freshening at higher latitudes. Be´thoux et al. (1998) attributed increases in salinity in the Mediterranean to anthropogenic factors (reduced freshwater inputs, and more saline inputs via the Red Sea), reductions in precipitation, and warming-induced increases in evaporation. 3.1.3. Length of the growing season An increase in the duration of the growing season is a logical response to warmer spring and fall air temperatures in temperate regions where the growing season is confined to the period when air temperatures remain above freezing. Transpiration is greatly reduced during the dormant season. Modeled ET increases as the length of the growing season increases in humid regions of the eastern United States (Eagleman, 1976). Mean annual ET, estimated from measured precipitation minus runoff, increases at a rate of about 3 cm  C 1 in eastern North America (Huntington, 2003a). Thus, any extension of the growing season will increase total annual ET, provided moisture is not limited, thereby intensifying the hydrologic cycle. There is now extensive evidence that the growing season has been getting longer in temperate climates over the historical observational record. Because of this global trend towards lengthening of the growing season, it is reasonable to assume that the seasonal period of active plant transpiration has lengthened in synchrony (White et al., 1999). In the following section, the evidence for a lengthening of the growing season will be reviewed. An increase in the length of the growing season in temperate and boreal ecosystems is inferred from studies that have monitored temporal trends in plant phenology, such as the date of first leaf out, bud break, and flowering during the twentieth century (e.g., see reviews by Menzel et al., 2006; Root et al., 2003; Schwartz et al., 2006). These reviews focus on the Northern Hemisphere, hence responses in the Southern Hemisphere are less certain. Many of the most compelling studies were carefully controlled to minimize variation in phenotype, for example, by planting genetically identical varieties. Advances in the timing of many animal phenological events in the Northern Hemisphere also have been reported (Parmesan and Yohe, 2003; Walther et al., 2002). Together these extensive reviews of phenological studies strongly point to increases in growing-season duration. Substantial increases in growing-season length have also been inferred in regional studies from temperature records (Cooter and LeDuc, 1995) and reports of killing frosts (Baron and Smith, 1996). Fitzjarrald et al. (2001) reported an advance in the timing of the spring decrease in the Bowen ratio in the eastern United States, indicating earlier leaf emergence and rapid increase in the rate of transpiration. Trends in high northern latitude soil-

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freeze-and-thaw cycles have been studied using satellite data from the Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager (Smith et al., 2004). In North America, Smith et al. (2004) reported a trend toward longer growing seasons in evergreen conifer forests and boreal tundra during the period 1988–2002. Smith et al. (2004) found earlier thaw dates in tundra and larch biomes over Eurasia. However, trends toward earlier thaw dates in Eurasian larch forests did not lead to an increase in growing season length because of parallel changes in timing of the fall season (Smith et al., 2004). Increases in growing-season duration also are inferred from a variety of hydrologic and climatologic variables that are correlated with earlier spring warming. For example, earlier spring snowmelt runoff (Cayan et al., 2001; Cunderlik and Burn, 2004; Hodgkins et al., 2003; Leith and Whitfield, 1998, Yang et al., 2002; Zhang et al., 2001a), earlier river ice-out (Hodgkins et al., 2005; Jeffries et al., in press); earlier lake ice-out (Hodgkins et al., 2005; Jeffries, et al., in press; Magnuson et al., 2000), lengthening of the frost-free season (Easterling, 2002; Frich et al., 2002; Kunkel et al., 2004), and decreases in spring snow-cover extent across the former Soviet Union and Peoples Republic of China (Brown, 2000), in the Swiss Alps (Scherrer et al., 2004), and in the Northern Hemisphere (Hall and Robinson, in press). An increase in the length of the growing season was inferred from an advance in the timing of the spring seasonal drawdown in atmospheric CO2 concentrations (Fang et al., 2003; Hicke et al., 2002; Myneni et al., 1997). That drawdown was coincident with an advance in the timing of the “onset of greenness” (inferred from NOAA advanced very high-resolution radiometer (AVHRR) satellite data showing the normalized difference vegetation index) in northern temperate regions (Myneni et al., 1997).

3.2. Atmospheric water vapor Another dimension of an intensification of the hydrologic cycle is an increase in atmospheric water-vapor content as predicted by the Clausius– Clapeyron equation. In spite of substantial regional variation and uncertainty in the data, there is evidence for an increase in water vapor at the surface over most northern latitudes (>30 N), with the exception of Greenland and extreme northeastern Canada, during the period 1975–1995 (New et al., 2000; Rinke et al., 2009). Dai (2006) reported trends of increasing annual mean specific humidity over the surface of the globe between latitude 60 S and latitude 75 N for 1975–2005 (Fig. 6). Willett et al. (2008) reported increased specific humidity at the Earth’s surface from latitude 70 N to latitude 70 S of between 0.07 and 0.11 g kg 1 per decade from 1973 to 2003. Studies using radiosonde measurements have also reported increases in lower troposphere water vapor beginning in 1973 in the Northern Hemisphere (Ross and Elliott,

18

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Thomas G. Huntington

Figure 6 Time series of annual-mean surface specific humidity (g kg 1, solid curve) and surface (air over land and sea surface over oceans) temperature ( C, short-dashed curve) anomalies averaged over 60 S–75 N. The linear trends (dq/dt and dT/dt) and their statistical significance levels (p) are also shown. The error bars are estimated  standard error ranges based on spatial variations. Modified from Dai (2006), and used with permission.

2001; Zhai and Eskridge, 1997) and, more recently, using SSM/I measurements (Trenberth et al., 2005; Wentz et al., 2007). Deficiencies in the data, large interannual and regional variations, the relatively short-term nature of the data, and the association of these trends with ENSO and sea-surface temperature suggest caution in making inferences about long-term trends (Trenberth et al., 2005). Minschwaner and Dessler (2004) report that recent satellite measurements also indicate trends toward increasing water vapor in the tropical (20 S to 20 N) upper troposphere (UT) (above 215 mb) during 1993–1999 that were consistent with model predictions. However, they concluded that models that assume constant relative humidity overestimate the warminginduced water-vapor feedback. Their data indicate that the relationship between UT humidity and sea-surface temperature within the convective regions of the tropical oceans lies between the cases of constant mixing ratio (specific humidity) and constant relative humidity (Minschwaner and Dessler, 2004).

3.3. Changes in cloudiness Trends in cloudiness may also be related to an intensification of the hydrologic cycle. Climate warming-induced changes in cloudiness would be a feedback on the hydrologic cycle because of the influence of clouds on the radiation budget of the earth. Studying the Mississippi River Basin from 1948 to 2004, Qian et al. (2007) noted an increase in cloudiness that was associated with a decrease in net shortwave radiation, but this decrease was

Climate Warming-Induced Intensification of the Hydrologic Cycle

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compensated for by decreases in net longwave radiation and sensible-heat flux, while the latent-heat flux increased in association with wetter soil conditions. Cloudiness increased from the 1940s to 1990 over may continental regions of the United States, over mid-latitude Canada, Europe, Australia, and over the former USSR (Dai et al., 1999). Recent assessments, consistent with Dai et al. (1999), show continuing increases in cloudiness in many continental region of the United Sates, over mid-latitude Canada, western Europe, Australia, and over the former USSR, but they indicate decreases in cloudiness over China, Italy, central Europe, and possibly over certain ocean regions (Dai et al., 2006; Trenberth et al., 2007b). Large interdecadal variability in cloud cover has been reported, including a decrease in cloud cover over global land areas (latitude 60 S to 75 N, but excluding the United States and Canada where cloud-cover trends were increasing) from the late 1970s to the mid-1980s were followed by a gradual increase (Trenberth et al., 2007b). The long-term trend remains uncertain (Folland et al., 2001; Trenberth et al., 2007b). The DTR is strongly and inversely related to cloudiness (Dai et al., 1999), and DTR decreased over most global land areas during the latter half of the twentieth century (Easterling et al., 1997). Given the strong relation between cloudiness and DTR, the longterm downward trend in DTR is an indication that cloudiness has increased during the same time period. Increases in cloudiness that result in significant decreases in solar radiation could decrease ET and act to dampen the hydrologic cycle, thus constituting a negative feedback.

3.4. Precipitation On a globally averaged basis, annual precipitation over land (excluding Antarctica) is estimated to have increased by 9–24 mm (1–3%) during the twentieth century (Dai et al., 1997; Hulme et al., 1998; New et al., 2000). Changes in rainfall amounts over time differ among regions and between different time periods within regions (Trenberth et al., 2007b). Many terrestrial regions experienced significant increases in rainfall; however, other regions experienced decreases during the twentieth century, but the oceans have been poorly studied, so the average global trends remain uncertain. Another recent study averaging all global land surfaces during 1901–2003 found increases in maximum amounts of 1- and 5-day precipitation and in the number of very wet days (Alexander et al., 2006). Regional variations in precipitation amounts are highly significant. For example, zonally averaged precipitation increased by 7–12% between latitude 30 N and 85 N, compared with a 2% increase between latitude 0 S and 50 S, and precipitation decreased substantially in some regions (Folland et al., 2001; Trenberth et al., 2007b). Groisman et al. (2004) reported increases in precipitation over the conterminous United States during the

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twentieth century, with most of the increase confined to spring, summer, and fall. Increases in precipitation have been reported for most of China (Liu et al., 2005; Ye et al., 2004), with the exception of the North China Plain (Fu et al., 2009). Seasonal snow-water equivalent (SWE) can be considered a proxy for winter precipitation in many high-latitude regions. Brown (2000) found systematic increases in winter (December through February) SWE over North America averaging 3.9% per decade during 1915–1992. Increases in winter snow accumulation were also reported in Russia from latitude 60 N to 70 N and from longitude 30 E to 40 E, during 1936–1983 (Ye et al., 1998); Canada, north of approximately latitude 55 N (Karl et al., 1993; Zhang et al., 2000); interior (higher elevations) of Greenland ( Johannessen et al., 2005; Thomas et al., 2006); and during 1992–2002, in East Antarctica (Zwally et al., 2005). Ye et al. (1998) estimated SWE from measured snow depth using a ratio of 10:1 for snow volume to water volume. The large increases in snow depth (4.7% per decade) and the relatively small sensitivity to temperature of the ratio suggest that any error in using a fixed ratio would not alter the results appreciably (Ye et al., 1998). Furthermore, the fact that the observed temperature of the surface air generally increased over this region during most of this period suggests that snow density likely increased, making the fixed ratio over time a conservative estimate. These reports are consistent with the Clausius– Clapeyron relationship, in that increasing winter temperatures result in increased precipitation, depending on the slope of the relationship between snowfall and temperature (Davis et al., 1999). Human activities that increase the atmospheric burden of sulfate, mineral dust, and black carbon aerosols have the potential to affect the hydrologic cycle by suppressing rainfall in polluted areas and reducing the solar irradiance reaching the Earth’s surface (Liepert et al., 2004; Ramanathan et al., 2001; Wild et al., 2004). The primary mechanism for suppressing rainfall is that aerosols increase concentrations of cloud condensation nuclei and reduce the mean size of cloud droplets, resulting in less-efficient coalescence into rain drops (Ramanathan et al., 2001). These effects are thought to be responsible for drier conditions in the north and wetter conditions in the south of China (Menon et al., 2002). Aerosol-induced reduction in solar irradiance reaching the Earth’s surface could reduce surface evaporation and, consequently, precipitation and thus dampen the hydrologic cycle (Ramanathan et al., 2001; Wild et al., 2004). Under conditions of reduced evaporation over land, precipitation can increase over land only if there is a corresponding advection of moist air from the oceans to the land (Wild et al., 2004). Whether the overall effects of aerosols will be primarily a spatial redistribution of precipitation that affects only polluted areas, or a more general weakening of the water cycle is uncertain. On the one hand, there is evidence that solar irradiance reaching the land

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surface has been reduced during the last 50 years (Stanhill and Cohen, 2001), which is consistent with the potential for a dampening of the hydrologic cycle. On the other hand, the evidence for increasing precipitation, evaporation, and runoff over many regions over the same time period suggests that aerosols have not resulted in a widespread, detectable dampening of the hydrologic cycle, at least to date. More recent analyses indicate that trends in aerosol effects on solar irradiance have reversed in recent years and the Earth is now brightening (Wild et al., 2005), thereby reversing the dampening effect on the hydrologic cycle (Andreae et al., 2005; Wild et al., 2008). Dyurgerov (2003) and Dyurgerov and Meier (in press) showed that seasonal changes in mass balance of about 300 mountain and subpolar glaciers increased in amplitude during the period 1961 through 1998 (Fig. 7). These findings indicated that wintertime increases in glacier mass were related to increases in snowfall amounts and that summertime decreases in mass were related to a warming-induced increased rate of melting. Summertime glacier melting outweighed wintertime ice accretion, resulting in an underlying trend toward declining glacier mass throughout the world (Dyurgerov, 2003, Dyurgerov and Meier, in press; Oerlemans, 2005; Williams and Ferrigno, in press). The increase in snowfall at these sites throughout the world where there are very few robust precipitation measurements is another indication of increasing precipitation over land and is consistent with a recent intensification of the global hydrologic cycle.

3.5. Runoff An analysis of trends in continental runoff from major rivers worldwide from 1910 through 1975 found that runoff increased about 3% (Probst and Tardy, 1987). A reanalysis of these trends from 1920 to 1995, in which data were reconstructed to fill in missing records, confirmed an increase in world continental runoff during the twentieth century (Labat et al., 2004). Labat et al. (2004, p. 631) conclude, “ . . . this contribution provides the first experimental data-based evidence demonstrating the link between global warming and the intensification of the global hydrologic cycle.” In a recent global land-surface modeling study, Gerten et al. (2008) reported that during 1901–2002, global river discharge increased by 30.8 km3 a 2, equivalent to 7.7%, due primarily to increasing precipitation. In contrast to these findings, Dai et al. (2009) reported no increase in global river discharge, and recent reviews have been inconclusive (Bates et al., 2008; Trenberth et al., 2007b). In regional studies, increases in precipitation have been associated with corresponding increases in runoff in river basins in the conterminous United States (Groisman et al., 2001; Lins and Slack, 1999; McCabe and Wolock, 2002) (Fig. 8). In Canada, by contrast, increasing temperature, combined with almost no change in precipitation, resulted in no change in annual

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Figure 7 Summer (A), winter (B), and cumulative annual (C) trends in glacier mass balance for about 300 mountain and subpolar glaciers outside Greenland and Antarctica. Figure modified from Dyurgerov (2003), and used with permission.

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1950 Minimum

0 -1 1940

1950

Figure 8 Mean standardized departures of annual maximum (A), median (B), and minimum (C) daily streamflow for 400 sites in the conterminous United States (1941–1999). Modified from McCabe and Wolock (2002), and used with permission.

streamflow from 1947 to 1996 for most regions (Zhang et al., 2001a). One striking exception in Canada is the Winnipeg River Basin, where precipitation and runoff have increased markedly (St. George, 2006). The basins studied in North America were selected because of minimal human perturbations to the hydrologic cycle. Typical criteria for basin selection exclude basins where consumptive use, land-use changes, intrabasin diversions, and/ or significant regulation through the management of reservoir levels could influence flow (Harvey et al., 1999; Slack and Landwehr, 1992). There have been no globally extensive studies on trends in streamflow from minimally impacted basins. Uncertainty remains about whether increasing ET could offset increasing precipitation and the melting of ice and permafrost, ultimately resulting in decreased freshwater inputs to the Arctic (Anisimov et al., 2001). Increases in precipitation and runoff have been shown to be quite variable among different regions (Karl and Riebsame, 1989; Keim et al., 1995). Recent reports indicate increasing annual streamflow in Arctic rivers (Fig. 9) (Lammers et al., 2001; McClelland et al., 2004; Peterson et al., 2002) and in western Russia (Georgievsky et al., 1996). Precipitation increased, snowfall decreased, and runoff decreased or did not change during the latter

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0.07

2200 2000

0.06 1800 1600 1400

0.05 Slope = 2.0 ± 0.7 km3/yr p = 0.005

Eurasian river discharge (Sv)

Eurasian river discharge (km3/yr)

2400

0.04

1200 1940 1950

1960

1970 Year

1980

1990

2000

Figure 9 Trend in combined annual discharge from the six largest Eurasian arctic rivers from 1936 to 1999. Units are in km3 a 1 and in Sverdrup units (1 Sv ¼ 106 m3 s 1). Modified from Peterson et al. (2002), and used with permission.

half of the twentieth century in the Tien Shan mountains in northern Eurasia (Aizen et al., 1997). In other parts of China, trends in streamflow are mixed (Tao et al., 2003). Streamflow has increased in the upper Yangtze River (Zhang et al., 2006) but decreased in the Yellow River (Chen et al., 2003; Jiongxin, 2005). The decrease in runoff may be associated with decreasing meltwater from receding glaciers (Aizen et al., 1997; Khromova et al., 2003). Increases in runoff have been observed in major river basins in South America (Berbery and Barros, 2002; Garcia and Mechoso, 2005). There have also been reported increases in streamflow in Switzerland (Birsan et al., 2005), Finland (Hyva¨rinen, 2003), and other Nordic countries (Hisdal et al., 2004). It is evident that temporal trends in river discharge are variable among regions and that the long-term global trend is not clearly identified (Bates et al., 2008). Human alterations, including irrigation, dam building (including multiple dams on several major river systems), changes in land cover, and extraction of groundwater affect river discharge (Vo¨ro¨smarty and Sahagian, 2000), but these are of minor importance on a global scale compared with precipitation and ET (Gerten et al., 2008). In some regions, climate warming may cause increasing precipitation and compensating increases in ET that, combined, result in no increase in river discharge. These results for major rivers, in conjunction with independent reports of increasing runoff from many smaller rivers in the Northern Hemisphere, provide possible evidence for the validity of the conceptual framework for

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an intensification of the hydrologic cycle. These increases in runoff are consistent with the results of modeling studies that suggest that runoff is likely to increase in high latitudes and in many equatorial regions, but decrease in the middle latitudes and some subtropical regions as a result of differential responses to climate warming in different regions (Alcamo et al., 1997; Kundzewicz et al., 2007; Manabe et al., 2004). A modeling and observational analysis of the Arctic Ocean freshwater budget from 1950 through 2050 is consistent with an acceleration of the Arctic hydrologic cycle: freshwater inputs to the ocean from net precipitation to the ocean surface increased as did river runoff and net ice melt (Holland et al., 2007; Rawlins et al., in press). It is worth noting that if rates of ET increase more than rates of precipitation, then runoff would decrease, even if precipitation increased. Human modifications of the landscape can have large effects on trends in runoff from some river basins. Conversion from forest to agricultural land may increase runoff from rivers (Vo¨ro¨smarty and Sahagian, 2000); in other cases, abandonment of agricultural land and subsequent reforestation could result in decreases in runoff. Consumptive use, such as crop irrigation, has greatly decreased flow from some rivers, such as the Syr Darya River and Amu Darya River, which drain into the Aral Sea in central Asia (Vo¨ro¨smarty and Sahagian, 2000), and the Yellow River in China (Chen et al., 2003). Reservoir construction can have short-term effects on stream flow as reservoirs fill and longer term effects if evaporation losses are high. The net annual effect of reservoirs on the global hydrologic cycle is diminishing, however, because the rate of large reservoir construction has declined markedly in recent decades (Avakyan and Iakovleva, 1998). Major river basins integrate the effects of climate variation, of human engineering projects, and changes in land cover, making it difficult to accurately determine the cause of changes in the basin. In addition, some part of the increase in runoff from river basins containing “permanent” ice and snow is likely attributable to the melting of glaciers and permafrost rather than to increased precipitation (see, e.g., Kulkarni et al., 2003; McClelland et al., 2004; Yang et al., 2002). McClelland et al. (2004) concluded that increasing precipitation was the most viable explanation for increasing Arctic river discharge. The Mississippi River Basin has had well-documented increases in precipitation and runoff during the latter half of the twentieth century. The mean annual discharge from the Mississippi River from 1949 through 1997 was 187 mm a 1 and during this period it increased by 0.85 mm a 2, or 25% (Milly and Dunne, 2001). During the same time period, mean annual precipitation was 835 mm a 1 and during this period it increased by 1.78 mm a 2, or 11% (Milly and Dunne, 2001). During the same time period mean annual ET was 649 mm a 1 and during this period, it increased by 0.95 mm a 2, or 7% (Milly and Dunne, 2001). Anthropogenic changes

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in the hydrologic cycle in the Mississippi River Basin during the twentieth century have been comparatively small and dominated by increases in consumptive use that cause a decrease in runoff (Milly and Dunne, 2001). Two of the more significant changes in the Mississippi River Basin in the twentieth century are the abandonment of cultivated farmlands and their conversion to forest or pasture, particularly in the southeastern part of the basin (Clawson, 1979; Wear and Greis, 2002) and the construction of numerous large dams. Both of these changes would have decreased runoff. Increasing precipitation and runoff in the Mississippi River Basin from 1949 through 1997 is consistent with an intensification of the global hydrologic cycle.

3.6. Soil Moisture Soil-moisture content increased during the last several decades in parts of Eurasia (Robock et al., 2000) and in much of the continental United States during the twentieth century (Andreadis and Lettenmaier, 2006). Recently, Sheffield and Wood (2008) reported a weak trend toward an increase in global soil moisture from 1950 through 2000. This upward trend has occurred simultaneously with an increasing temperature trend that would otherwise (in the absence of increased rainfall) be expected to decrease soil moisture. In this case, increases in precipitation are thought to have been more than compensated for by increased losses due to increases in ET (Robock et al., 2000; Sheffield and Wood, 2008). In addition to directly indicating an intensification of the global hydrologic cycle directly, in soil moisture suggest the potential for increasing ET and thereby indirectly intensifying the global hydrologic cycle. The response of soil moisture to climate warming may not be monotonic; rather, it is possible that in some regions soil moisture might first increase in response to increasing precipitation but then decrease because ET may increase faster than precipitation as temperature rises. Yamaguchi et al. (2005) have shown that soil moisture could initially increase in summer in northern high latitudes as thaw depth increased, but simulations show that in the late twenty-first century, a reduction in soil moisture eventually occurs (Kitabata et al., 2006).

3.7. Precipitation recycling Precipitation recycling is the process whereby precipitation falls within a specific area, returns to the atmosphere over that area by evaporation and transpiration, and condenses and falls as precipitation again over the same area (Brubaker et al., 1993; Eltahir and Bras, 1996). Intensification of the hydrologic cycle can include an increase in the average global rate of precipitation recycling where the precipitation is derived from local evaporation and transpiration rather than an increase in moisture advected from

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outside of the area of interest. Recent investigations have defined the precipitation-recycling ratio as the ratio of precipitation derived from moisture originating within the region of interest to moisture advected from outside the region. These studies have attempted to determine if the P-recycling ratio has changed over time. The P-recycling ratio is proportional to the size of the area of interest; the larger the area, the higher the P-recycling ratio (Dirmeyer and Brubaker, 2007; Dominguez et al., 2006; Trenberth, 1999). A regional decrease in the P-recycling ratio has been associated with the persistence of drought (Brubaker et al., 1993). In global studies using observations and a water-vapor-tracing algorithm, Dirmeyer and Brubaker (2006, 2007) found trends in the P recycling ratio from 1979 through 2003 over large areas at high latitudes that are consistent with an expansion into spring of the warm-season regime of water-vapor recycling. They noted that the trends were consistent with observed vegetation-related changes often attributed to global climate change, and were most evident over northern Europe and North America where the density of meteorological data influencing the atmospheric analyses is high. Dirmeyer and Brubaker (2006, 2007) found that the increase in recycling ratio was much stronger in spring and fall as would be expected if the increased moisture were derived from higher ET resulting from a longer growing season. By contrast, Serreze et al. (2003) reported that there was no trend in the P-recycling ratio for the Arctic basins of the Lena, Yenisey, Ob, and Mackenzie Rivers from 1960 through 1999. For the Amazon River Basin, it has been shown that an increase in precipitation derived from moisture advected from outside the basin, associated with a 50-year trend toward increasing sea-surface temperatures over the South Atlantic, is associated with a decrease in P-recycling (Bosilovich and Chern, 2006).

4. Mount Pinatubo: The Natural Experiment in Aerosol Optical Depth The explosive eruption of Mount Pinatubo in 1991 provided a natural experimental test of the hypothesis that global cooling would dampen (weaken or decelerate) the hydrologic cycle. Whereas this review chapter examines the evidence for a warming-induced intensification of the hydrologic cycle over the long-term historical observations, the response to the Mount Pinatubo explosive eruption constitutes a complementary test of the reverse hypothesis, albeit over a much shorter time period. Evidence for dampening of the hydrologic cycle following cooling would provide evidence of the same mechanism whereby warming causes intensification of the hydrologic cycle.

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The eruption of Mount Pinatubo in 1991 resulted in an injection of sulfur dioxide into the lower stratosphere (Hansen et al., 1992; Harries and Futyan, 2006; Robock and Oppenheimer, 2003). The sulfur dioxide was oxidized to sulfate particles (aerosols) that remained in the atmosphere for more than 1 year. The increase in the atmospheric burden of sulfate aerosols increased atmospheric albedo (reflectance) by up to 0.007 resulting in the reflection of up to an additional 2.5 W m 2 of solar radiation during the following 2 years (Harries and Futyan, 2006; Wielicki et al., 2005). The result of the increase in albedo was a decrease in the absorbed short wave-length solar radiation at the Earth’s surface of 3–4.5 W m 2 from late 1991 through 1992 (Soden et al., 2002). The reduction in absorbed solar radiation, in turn, resulted in a decrease in global average surface air temperature of up to about 0.5  C in 1992 relative to the long-term average prior to the eruption (Soden et al., 2002). Effects on global hydrologic variables were detected in the years following the eruption of Mount Pinatubo that are consistent with the effects of increasing atmospheric sulfate aerosols on the Earth’s radiation budget. Atmospheric water-vapor content (total water column in the atmosphere) decreased by up to about 0.75 mm (3%) in 1992 (Randel et al., 1996; Soden et al., 2002). During the period October 1991 through September 1992, global precipitation was 3.12 standard deviations below normal from 1950 through 2004 (Fig. 10) (Trenberth and Dai, 2007). Moderate or severe

3.30

Freshwater discharge Land precipitation

1.20 3.20 1.16 3.10 1.12

Land precipitation (Sv)

Continental discharge (Sv)

1.24

3.00 1.08

1996

1990

1994

1998

Year

Figure 10 Time series of the annual water year (October to September) continental freshwater discharge and land precipitation in Sverdrup units (1 Sv ¼ 106 m3 s 1). The period clearly influenced by the Mount Pinatubo eruption is indicated by grey shading. Modified from Trenberth and Dai (2007), and used with permission.

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drought (as inferred from the Palmer Drought Severity Index (PDSI)) was widespread in 1992 (Dai et al., 2004). Trenberth and Dai (2007) reported that during October 1991 through September 1992, global continental runoff was by far (3.67 standard deviations below normal) the lowest recorded during the period 1950–2004 (Fig. 10). The observed changes in global surface air temperature, atmospheric water-vapor content (Fig. 10), precipitation, and continental runoff are strong evidence for a global cooling-induced dampening of the hydrologic cycle. This, in turn, supports the hypothesis that warming is intensifying the hydrologic cycle.

5. Hydrologic Responses to Intensification— Extreme Events (Including Droughts) One of the more important potential consequences of an intensification of the hydrologic cycle is that the frequency, intensity, or duration of severe weather may change (Kundzewicz et al., 2007). It is noteworthy that whereas recent evidence points toward increases in atmospheric water vapor and precipitation in the range of 7%  C as discussed earlier, the intensity of precipitation extremes may increase at substantially lower rates (O’Gorman and Schneider, 2009). Considerable emphasis has been placed on testing whether the frequency or intensity of hurricanes, typhoons, floods, and droughts has changed during the period of observational record. Economic losses from damages associated with natural disasters increased during the latter part of the twentieth and early twenty-first century but adjusting for time-variant economic factors and the value of properties in the path of major storms and floods has not shown a large upward trend over time (Rosenzweig et al., 2007). Insurance companies and the international reinsurers that underwrite them have expressed serious concern about their potential for increased liability for claims involving weather-related natural disasters, if climate warming results in increasing frequency, intensity, or both, of severe weather (Berz, 1999; Lindenschmidt et al., 2005). Increases in precipitation in the higher precipitation quantiles have been observed in regional studies (Dai et al., 1997; Folland et al., 2001; Groisman et al., 2004; Hayhoe et al., 2007; Hulme et al., 1998; Klein Tank et al., 2002; Kunkel et al., 2008; Tebaldi et al., 2006; Trenberth et al., 2007b). Increases in property losses (adjusted for increases in property values) due to hailstorms during 1950–2006 increased substantially (Changnon, 2009). Observed twentieth-century increases in precipitation, particularly in higher precipitation quantiles (e.g., Groisman et al., 2004), may have increased the frequency of flooding. However, a review of the empirical evidence to date does not consistently support an increase in the highest flow quantiles globally (Kundzewicz et al., 2005) nor regionally in the

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United States (Collins, 2009; Douglas et al., 2000; Lins and Slack, 1999; McCabe and Wolock, 2002; Vogel et al., 2001), Canada (Zhang et al., 2001b); Scandinavia (Hyva¨rinen, 2003; Lindstrom and Bergstrom, 2004); or central Europe (Bra´zdil et al., 2006; Mudelsee et al., 2003). In contrast with these studies, Milly et al. (2002) reported that the frequency of floods with discharges exceeding 100-year levels from 29 basins larger than 200,000 km2 increased substantially during the twentieth century. Milly et al. (2002) also stated that their conclusions were tentative and that the frequency of floods having return intervals shorter than 100 years has not changed. Several time-series analyses of tropical storms have found no evidence for an increase in frequency (Chan and Liu, 2004; Easterling et al., 2000; Elsner et al., 2004; Folland et al., 2001; Landsea et al., 2009; Solow and Moore, 2002; Vecchi and Knutson, 2008), intensity (Free et al., 2004), or duration of the storm season (Balling and Cerveny, 2003) during the twentieth century. However, other recent analyses have reported increases in storm frequency and intensity. For example, Emanuel (2005) reported increasing destructiveness of tropical cyclones in recent decades. Webster et al. (2005) evaluated data on the intensity of tropical cyclones and on the number of tropical cyclones and cyclone days during the past 35 years; they found a large increase in the number and proportion of hurricanes reaching categories 4 and 5 on the Saffir–Simpson scale, the categories of which range from 1 (least intense) to 5 (most intense). Hoyos et al. (2006) showed that the trend of increasing numbers of category 4 and 5 hurricanes for 1970–2004 is directly linked to the global trend in rising sea-surface temperature. Klotzbach (2006) and Klotzbach and Gray (2008) analyzed trends in global tropical-cyclone activity during recent decades and reported a positive upward trend in tropical-cyclone intensity and longevity for the North Atlantic basin, and a considerable negative downward trend for the Northeast Pacific, but no net trend in global activity. Curry et al. (2006) reviewed the evidence for a linkage between climate warming, increasing sea-surface temperature, and an increase in hurricane intensity; they report substantial evidence to support the hypothesis that warming has resulted in increasing sea-surface temperature and that the number of more intense hurricanes has increased since 1970. Given that storm intensity is related to wind speed, the question of whether wind speed is increasing is of considerable importance. Recent studies suggest a decrease in wind speed measured over land areas in recent decades, although there are inconsistencies depending upon the data or methods used (e.g., Brazdil et al., 2009; McVicar et al., 2008; Pryor et al., 2009; and references therein). The state of science on this issue might be best summarized by the World Meteorological Organization’s “Summary Statement on Tropical Cyclones and Climate Change” released in December 2006: “Although there is evidence both for and against the existence of a detectable anthropogenic signal in the tropical

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cyclone record to date, no firm conclusion can be made on this point.” (http:// www.wmo.ch/pages/prog/avep/tmrp/documents/iwtc_summary.pdf). Drought frequency, intensity, and duration is another aspect of extreme weather that could be affected by intensification, if there are associated changes in the spatial and temporal pattern of precipitation and regional changes in the relative rates of precipitation and ET. From 1900 to 1995, large, multiyear-to-decadal variations in the percentage of land area undergoing severe drought or receiving surplus moisture were observed; however, secular trends were small (Dai et al., 1998). After the late 1970s, the combined percentage of areas with severe drought or moisture surplus expanded, resulting from increased extent of either the drought area (e.g., in the Sahel, eastern Asia, and southern Africa) or of both the drought and wet areas (e.g., in the United States and Europe) (Dai et al., 1998, 2004). For a given value of ENSO intensity, the response in areas affected by drought or by excessive wetness was more extreme after 1970 (Dai et al., 1998). There is great uncertainty in the potential relation between climate warming and the frequency and strength of ENSO events (e.g., Collins and The CMIP Modelling Groups, 2005; Latif and Keenlyside, 2009) although an increase in the frequency or intensity of El Nino events is possible (Herbert and Dixon, 2002; Timmermann et al., 1999) and a regime shift was noted after 1970 (Latif and Keenlyside, 2009). In a global analysis, Dai et al. (2004) concluded that the proportion of the land surface characterized as “very dry” (PDSI < 3.0) more than doubled since the 1970s, and that global “very wet” areas (PDSI > þ3) declined slightly since the 1970s. An increase in the proportion of land area in drought since the 1970s is also reported by Burke et al. (2006). These changes are highly variable among regions and are attributed to both ENSO-induced decreases in precipitation and to warming-induced increases in evaporation and ET; however, the changes are consistent with increasing risk of more frequent and more intense drought over some regions (Dai et al., 2004). In a global analysis using a soil-moisture-based index derived from the variable infiltration capacity (VIC) model, Sheffield and Wood (2008) reported a longer term (1950–2000) trend toward a decrease in drought but a weak trend reversal towards increasing drought after 1970.

6. Potential Impacts on Agriculture 6.1. General findings and projections Recent assessments have evaluated a wide range of potential effects of climate change on agriculture (food and fiber) (Easterling et al., 2007; European Environmental Agency, 2007; CCSP, 2008). A comprehensive review of these effects, even one confined to the potential effects of an

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intensification of the hydrologic cycle, is beyond the scope of this chapter. Interested readers are encouraged to explore the cited international and national assessments. The following section will briefly summarize many of the potential impacts on agriculture that could occur as a result of an intensification of the hydrologic cycle. It should be noted that the assessments cited above include both positive and negative impacts on agriculture from projected increases in temperature, precipitation, atmospheric-CO2 concentration, and increases in the frequency, intensity, and duration of extreme-weather events. Climate changes will also likely result in poleward migration of climates suitable for specific crops or forest tree species (Schro¨ter et al., 2005). The largest uncertainty in assessing impacts on agriculture is whether precipitation regimes will become more or less favorable compared with historical observations. Increasing precipitation during the growing season in regions prone to drier than optimal conditions would likely constitute a positive impact of a warming-induced intensification of the hydrologic cycle, provided extremes in precipitation do not increase to the point where agriculture is adversely affected. The primary impact of an intensification of the hydrologic cycle on agriculture will likely be highly regionally specific and related most closely to changes in precipitation regime, where “regime” includes precipitation frequency, intensity, and duration. Substantial changes that result in wetter or drier conditions could have adverse or favorable effects on crop, pasture, rangeland, forest, and livestock systems. There would also be interactions between changes in precipitation regime, increasing temperature, and lengthening of the growing season, all affecting transpiration, that could affect agriculture in complex ways. Of particular interest is the possibility that intensification could include an increase in frequency of heavy rainfall, flooding, droughts, hurricanes, wind storms, and ice storms. All of these extreme-weather events would be potentially damaging to agricultural production through direct crop losses or indirectly by weakening plant resistance to insects and diseases. Many regions have experienced increases in heavy rainfall or drought conditions and modeling studies have suggested that these regions are likely to experience similar increases in the future (Christensen et al., 2007; Good et al., 2006; Klien Tank, 2004; Kunkel et al., 2008; Palmer and Ra¨isa¨nen, 2002; Palutikof and Holt, 2004).

6.2. Primary effects on forests Increases in precipitation are likely to result in increases in forest productivity in water-limited regions (Knapp et al., 2002) provided there are no other limitations to growth such as nutrients (Boisvenue and Running, 2006). In some regions, increases in precipitation could exacerbate existing nutrient limitations because the increases could accelerate leaching losses; for example, leaching of calcium and magnesium may be accelerated in acidic

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forest soils (Huntington, 2005). Decreases in precipitation and increases in drought are likely to reduce forest productivity, especially in regions where water is already limiting. Changes in precipitation can interact with increasing temperature to result in indirect adverse effects on forests. For example, increasing rainfall and temperature could increase over-winter survival, abundance, or virulence of forest insect pests or diseases. One example is the effect of drought that weakens the resistance of Pinyon Pine to Ips beetle (Ips confusus) that has greatly increased tree mortality in the western United States in recent years (Ryan et al., 2008). Many recent insect-related, forest-mortality events in North America may be related to both increases in temperature and drought (Ryan et al., 2008). Projected climate change in the northeastern United States is expected to increase the negative impacts of insect pests and diseases in the forests (Dukes et al., 2009). An increase in the frequency and severity of forest fires in the western United States (Westerling et al., 2006) and in boreal forests (Kasischke and Turetsky, 2006) has been related to increasing temperature and drier soil conditions. Droughts also weaken trees, making them less likely to survive forest fire (Westerling et al., 2006). It is also likely that forest-species composition will change if precipitation changes substantially (Breshears et al., 2005).

6.3. Potential primary effects on cropland, pasture, and livestock Elevated atmospheric-CO2 concentrations are expected to result in positive effects on crop growth for many agriculturally important plant species, but potential increases in productivity may not be as high as once thought, and increases in temperature and changes in precipitation regime, including increasing frequency of extreme-weather events, could outweigh potential benefits (Easterling et al., 2007). Elevated atmospheric-CO2 concentrations also have the potential to improve water-use efficiency, thereby enhancing adaptive capacity toward drought in some situations, but the global-scale potential benefits are uncertain because of the interactions among the many variables that control plant-water relations (Allen et al., 2003; Centritto, 2005; Huntington, 2008; Scha¨fer et al., 2002; Wullschleger et al., 2002). The primary impacts of an intensification of the hydrologic cycle on crop plants are likely to be a result of changes in precipitation regime that cause increasing frequency of extreme-weather events, including flooding, heavy downpours, droughts, and increases in variability (Easterling et al., 2007; European Environmental Assessment, 2007; Hatfield et al., 2008; Porter and Semenov, 2005). More frequent flooding of fields could lead to crop losses directly or indirectly due to lowering soil O2, increasing susceptibility to root diseases, or increasing soil compaction and subsequent loss of soil aeration due to use of heavy equipment on wet soils (Hatfield et al., 2008; Rosenzweig et al., 2002). Heavy downpours and flooding could

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cause severe erosion and sedimentation that degrade soils and decrease productivity. Excessively wet conditions during harvesting could reduce the quality of many crops, including hay and silage. Increasing frequency of drought would reduce crop yields in non-irrigated areas that are already prone to water limitations and increase water demands in irrigated areas (Easterling et al., 2007). Droughts would be exacerbated by higher temperatures because of increases in crop water requirements under warmer temperatures (Hatfield et al., 2008; Lobell and Field, 2007). Drought adds to the multiple interacting stresses including excessively high temperatures, ozone, pests and pathogens, and soil degradation acting on agricultural systems, reducing resilience and adaptive capacity. More frequent heavy rainfall and flooding would most likely increase losses of agricultural chemicals, which would increase the potential for contamination and eutrophication of water bodies and may result in a need for more frequent chemical applications. Increases in temperature, precipitation, and humidity would also affect plant pathogens (Coakley et al., 1999; Evans et al., 2008). Leaf and root pathogens are highly responsive to increases in humidity and rainfall; therefore, climate changes that lead to these increases would likely lead to an increase in plant diseases (Coakley et al., 1999). Increases in climate extremes may also promote more frequent plant diseases and pest outbreaks, and the range and severity of outbreaks is likely to increase (Easterling et al., 2007; Evans et al., 2008; Gan, 2004). Heat stress can result from excessively high temperatures and highspecific humidity. As humidity increases, the heat stress associated with a given temperature increases. The evidence is mounting that specific humidity is increasing with increasing surface-air temperature while relative humidity remains constant, as noted earlier (Section 3.2). Heat stress can have many negative impacts on livestock, including decreases in weight gain and lower reproductive success (Easterling et al., 2007; Hatfield et al., 2008). One of the effects of heat stress in agricultural systems is that it can cause decreases in milk production (Hatfield et al., 2008; Klinedinst et al., 1993; Wolfe et al., 2008). Heat stress also reduces the ability of livestock to cope with parasites and disease pathogens (Easterling et al., 2007; Hatfield et al., 2008). Parasites or pathogens that thrive under conditions of higher temperatures and higher humidity may become more virulent and migrate poleward as the climate warms (Easterling et al., 2007). Livestock are especially at risk under conditions of increasing drought (Easterling et al., 2007). Human populations are also likely to suffer more from heat stress as the climate warms because of more frequent excessively high temperatures and accompanying increases in specific humidity (Gaffen and Ross, 1998; Jendritzky and Tinz, 2009). Intensification of the hydrologic cycle could have substantial effects on the rate of soil erosion, particularly in cultivated agricultural soils. Nearing

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et al. (2004) reviewed a number of studies that related changes in rainfall regime to changes in erosion rate to assess potential impacts of climate change. The most robust response was that if the intensity (mm h 1) and duration of major rainfall events (erosivity) increases, then the rate of erosion will increase. Increases in rainfall intensity and duration have been observed during the twentieth century and are expected to increase further during the twenty-first century as noted earlier (Section 5). In most studies, increases in rainfall amounts lead to increases in soil erosion (see Nearing et al., 2004 and studies cited therein). Nearing et al. (2004) noted that if more winter precipitation falls as rain rather than snow, as has been observed in parts of the United States (Huntington et al., 2004; Knowles et al., 2006), then soil-erosion rates are likely to increase in these regions. Nearing (2001) used GCM projections together with the Water Erosion Prediction Project (WEPP) model to assess the impacts of climate change on erosion and concluded that increases in erosion between 17% and 58% by 2100 compared with current rates were likely. They noted that there would very likely be large regional variations depending on soil, vegetation, management practices, and biological responses to other aspects of climate change. If warming-soil temperatures result in net losses of soil organic matter, soil structure could be degraded and potential erodibility could be increased (Huntington, 2003b).

7. Conclusions Temporal trends in the components of the hydrologic cycle including evaporation, ET, water vapor, precipitation, and runoff were reviewed to assess whether the evidence suggested an intensification of the hydrologic cycle during the twentieth century. This assessment is complicated by a lack of spatially, temporally, and methodologically consistent data and overall variability in trends among regions and within regions over time. Waterbalance studies based on long-term observations in some large river basins, notably the Mississippi and La Plata Rivers, strongly support an ongoing intensification. Analyses of other river basins, such as those in the pan-Arctic regions that have shorter and less-complete records, are generally consistent with intensification, but with more spatial variability and less certainty for some components of the hydrologic cycle. There is relatively strong support for intensification from trends in variables such as evaporation, ET, and atmospheric water-vapor concentrations. Trends in precipitation, runoff, and soil moisture are more uncertain. One of the more consistent findings is that trends in some regions are consistent with increasing precipitation, while other regions have experienced drying. Regional and hemispheric spatial-scale studies exhibit

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consistent and strongly positive trends toward increases in the duration of the growing season that are consistent with observations of increasing temperature and ET. Taken together, these observations support an ongoing intensification of the hydrologic cycle. Preliminary studies on trends in precipitation recycling in the Northern Hemisphere are also generally consistent with an intensification of the hydrologic cycle. Hydrologic responses to the eruption of Mount Pinatubo provided a natural experimental test that indicated that global cooling weakened the hydrologic cycle, lending further support to the process of warming-induced intensification. The evidence for an increase in the frequency, intensity, or duration of extreme-weather events like hurricanes is mixed and remains uncertain. There are weak trends toward increases in the frequency and intensity of heavy rainfall events; however, some studies have reported weak trends toward increasing frequency of drought. On balance, the preponderance of evidence supports an ongoing intensification of the hydrologic cycle with significant regional variations, including drying trends in some areas. Overall, the trends indicate increases in evaporation, ET, and atmospheric water-vapor content with implications for the strength of the water-vapor feedback and with potential impacts to agricultural systems. Recent projected temperature increases in the twentyfirst century are within the ranges associated with “tipping points” or critical thresholds beyond which the state of specific climate systems could change, resulting in major adverse environmental consequences (Lenton et al., 2008; Ramanathan and Feng, 2008; Schellnhuber et al., 2006; Smith et al., 2009). These analyses have argued that anthropogenic increases in greenhouse gases have already committed the Earth to significant environmental changes. Many effects are likely to involve changes in regional hydrologic regimes and result in impacts on human, other animal, and plant populations. Ironically, one of the most dangerous potential impacts of intensification of the hydrologic cycle is the likelihood that drought will become more prevalent and more severe in some regions. The largest potential impacts to agricultural systems depend greatly on the responses of hydrologic variables that are the most uncertain; for example, intensity and duration of heavy-rainfall events; frequency, intensity and duration of major storms (e.g., hurricanes, typhoons) and droughts; and rates of erosion. Impacts on agriculture will depend greatly on how insects, diseases, weeds, nutrient cycling, effectiveness of agrichemicals, and heat stress are affected by an intensification of the hydrologic cycle.

ACKNOWLEDGMENTS This work was supported, in part, by U.S. Geological Survey funds for climate research and by NASA grants NNH04AA66I and NNH08A157I. M. Todd Walter (Department of

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Biological and Environmental Engineering, Cornell University), Gregory McCabe (U.S. Geological Survey), Ruth Curry (Physical Oceanography Department, Woods Hole Oceanographic Institution), Kevin Trenberth, and Aiguo Dai (National Center for Atmospheric Research) provided helpful information, including permission to reproduce figures. R. S. Williams, scientist Emeritus, U.S. Geological Survey, Woods Hole, MA, and N. Knowles, U.S. Geological Survey, Menlo Park, CA, provided useful comments on earlier drafts of this chapter. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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Extent, Impact, and Response to Soil and Water Salinity in Arid and Semiarid Regions Karuppan Sakadevan1 and Minh-Long Nguyen Contents 56 57 57 59 62 63 64 65

1. Introduction 2. Soil Salinity 2.1. Factors contributing to soil salinization 2.2. Regional soil salinity 3. Water Salinity 4. Responding to Soil and Water Salinity 4.1. Saline water use in irrigation 4.2. Use of salt-tolerant plant and halophytes 4.3. Principles and practices in using salt-affected soils and saline waters 5. Conclusions References

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Abstract Sustainable management of land and water resources in arid and semi-arid regions is of concern as a result of increased population pressure and the need for more food and fiber. Soil and water salinity is widespread across the arid and semi-arid regions of South Asia, Central Asia, Arabian Peninsula, and North Africa and affected agricultural productivity and livelihood of rural population. While natural processes (primary) and anthropogenic activities (secondary) cause salinity, the latter contributed more to agricultural productivity losses in these regions. Recent estimates suggest that up to 50% of irrigated land has become saline in these regions. However, there is cautious optimism for managing salt-affected soils and saline waters for crop and animal production and protection of soil and water resources through research-based interventions using integrated soil–water–plant management practices. Soil and Water Management and Crop Nutrition Section, International Atomic Energy Agency, Vienna, Austria 1 Corresponding author: E-mail address: [email protected] Advances in Agronomy, Volume 109 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)09002-4

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The successful use of salt-affected soils and saline water takes the pressure off using freshwater for irrigation. Significant promises for addressing soil and water salinity through an integrated approach include: (1) the use of salt-tolerant crops, forages, and halophytes for human and animal consumption and bio-fuel production, (2) development of agro-forestry through planting forage crops within the interspaces of salt-tolerant trees that co-exist with forage crops and salt-tolerant shrubs, (3) development of appropriate surface and subsurface drainage systems to remove excess water and salt from the soil, (4) alternate and/or blended use of saline and fresh water to minimize salt accumulation in the soil, and (5) maintenance of proper irrigation scheduling to ensure that adequate water is available for crop growth and at the same time removal of excess salt from crop-rooting zone. Monitoring the effectiveness of the above mentioned technologies is important for maximizing the benefits. Finally, appropriate policy and institutional interventions that encourage the general community to accept the technology are required. Isotopic and nuclear techniques play a key role in developing and monitoring the technology for the sustainable use of salt-affected soils and saline waters and protect land and water resources.

1. Introduction Irrigation agriculture has been instrumental in providing food security to global population with significant improvement in farm income and poverty alleviation (Lipton et al., 2003). As the population would be close to 9.1 billion by the year 2050, the dependency on irrigation agriculture for global food supply will increase and that will require more land and water (FAO, 2006a). The global climate change and variability is expected to increase the extremes of rain events with flooding in some areas and decreased rainfall with increased evaporation losses leading to water scarcity in some other areas of arid and semi-arid regions (Kundzewicz et al., 2007). Such water scarcity will intensify the existing competition between agriculture and other sectors of the economy for water. Apart from increasing water scarcity, global climate change alters the evapotranspiration and water balance at the land surface, and changes the groundwater recharge. In shallow aquifers, the groundwater responds to these changes quickly. When the groundwater moves toward the surface, it brings salt with it and causes soil salinization (Kundzewicz et al., 2007). In coastal areas, the risk of soil and water salinization under climate change is even higher because the increased frequency of tidal waves brings salt water to low lying areas and causes soil salinization. In addition, the salinity of groundwater also increases through saline intrusion. Bangladesh, Indonesia, Egypt, countries in Arabian Peninsula, small island countries, and atolls in the Pacific are particularly vulnerable to soil and groundwater salinization as a

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result of climate change (Nicholls et al., 2007). Under such circumstances, the additional food supply has to be generated through either crop intensification in the existing irrigation systems, or the use of salt-affected soils. Crop intensification requires additional fresh water which is difficult to source under a water scarce situation. Salt-affected soils and saline water (water that contains between 0.5 and 30 g salt/L or an electrical conductivity expressed in Siemens(S) per meter (m) between 0.1 and 6.0 S/m) can be put in to productive use for growing crops and forage (Gopalakrishnan et al., 2008; Harneck et al., 2007). This review provides an assessment of the current status of soil and water salinity in arid and semi-arid regions and response options for the productive use of such soil and water resources for crop and fodder production.

2. Soil Salinity Globally around 4 million square kilometres of land has been affected by primary (natural) salinization to various degrees and at least half of world’s countries have some quantity of land affected by salinity (Corbishley and Pearce, 2007). Most of these salt-affected lands are located in arid and semi-arid zones of the world, the majority of countries affected by salinity being in a broad belt extending from the sub-Saharan Africa through the Middle East and into Central Asia (Fig. 1). In addition to natural salinization, it is estimated that more than 75 million hectares of land is affected by human-induced salinization of which more than 50% occurs in irrigation landscapes. Salinization already affected crop productivity in 20–30% of irrigated lands with an additional 1.5 million hectares affected annually (WCD, 2000). The last two decades or so has witnessed a sharp increase in losses of agricultural land to soil salinity. In arid regions with low rainfall and poor internal drainage, irrigation-induced soil salinity is a major issue affecting crop production with significant impact on rural livelihood (Akram and Azam, 2002).

2.1. Factors contributing to soil salinization A number of factors (both natural and human induced) contribute to soil salinization (Paine, 2003) in the landscape. They include: a. Chemical weathering of the soil parent material in which hydrolysis, hydration, solution, oxidation, carbonation, and other processes slowly release soluble salts. These soluble salts are transported away from their source of origin by surface and ground waters. When they move from more humid to less humid and to arid areas, they become concentrated. Once they are concentrated, they become less soluble and accumulate in

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Area affected by salinity (1000 SKM)

1800

6

1600 1400 1200 1000 800

6 3

600

2

2

.

400 200

1

<1

Europe

North America

0 Asia and the Pacific

North Africa and Near East

Central Asia and Caucases

South and Central America

SubSaharan Africa

Figure 1 Land area affected by salinity in different regions of the world. Numbers on top of the bar represent % area affected by salinity (source: FAO, 2006a).

the soil. Many internal landscapes were once covered by sea. When the sea retreated some 10 million years ago, the sediment was left behind with large quantities of salt. Primary salinization of landscapes occurs as a result of these two processes (Ghassemi et al., 1995). b. Both surface and ground waters contain dissolved salt. Continuous use of such water for irrigation particularly in soils with poor internal drainage systems that have inadequate leaching leads to only a part of the applied salt removed through deep drainage. The remaining salt in irrigation water accumulates in the soil over a period of time (Ghassemi et al., 1995). In soils with sufficient internal drainage and areas with annual rainfall of more than 1000 mm, irrigation-induced soil salinization is very slow (FAO, 2003). c. Replacing native vegetation with shallow-rooted crops such as cereals leads to less evapotranspiration and excess leaching, causing the groundwater levels to rise and brings salts along the upward-moving water. When the water evaporates from the soil surface, leaves behind salt. Salt accumulation in the soil through this process is important in landscapes with shallow (2–3 m) groundwater (Doupe et al., 2006). d. Seawater intrusion to surface soils through tidal waves and salt sprayed from sea to the land. Seawater intrusion accumulates salinity in coastal soils, while salt spray from sea extends salt accumulation a few kilometres inland. As the distance from coast increases, the amount of salt deposited in landscape decreases (Kundzewicz et al., 2007).

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e. Localized redistribution of salt in landscapes increased salinity in some soils and decreased salinity in some other soils. For example, soluble salts move from areas of higher to lower elevations, relatively wet to dry areas and irrigated fields to adjacent unirrigated fields. Salts may also accumulate in areas with restricted natural drainage caused by the construction of roads and rail lines or other developmental activities. Evaporation of stagnant waters may leave considerable amounts of salts on the soil surface (Williamson, 2000).

2.2. Regional soil salinity 2.2.1. Australia In Australia, the Land and Water Resources Audit (2000) has estimated that about 5.7 million hectares of land have the potential to develop dry land salinity and it is predicted to increase to 17 million hectares by 2050 (http:// www.environment.gov.au/land/pressures/salinity/index.html). In the Murray-Darling Basin alone about 100,000 hectares of irrigated land has been affected by soil salinity and the groundwater level is close to two meters in another 500,000 hectares (MDBC, 1999). The economic impact of soil salinity for Australian agriculture was estimated to be about 200 million dollars per year in 2000 and is expected to increase to about 300 million dollars per year in 2020. In addition, the off-site impact of soil salinity such as increased water salinity downstream and its associated treatment costs for municipal and industrial uses was estimated to be around 90 million dollars in 2000 and is expected to increase to 150 million dollars in 2020 (Land and Water Resources Audit, 2000). 2.2.2. Europe Within Europe there are significant areas of saline soils which have arisen naturally or due to past land management. Soil salinization affected about 1–3 million hectares especially in the Mediterranean countries where irrigation farming is very common and many fields have reached soil salinity levels which prevents farmers from raising common crops. It is regarded as a major cause of desertification and therefore is a serious form of soil degradation and endangering the potential use of European soils (Baldock et al., 2000). The direction of future management of these soil systems is diverse, with some being required for agricultural production, in which case protection and remediation from salt damage are anticipated, while others are being conserved or modified to provide valuable support for saline habitats (Eckelmann et al., 2006).

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2.2.3. Arabian Peninsula The Arabian Peninsula, which comprises the countries of Bahrain, Kuwait, Oman, Qatar, the Kingdom of Saudi Arabia, the United Arab Emirates, and the Republic of Yemen, is extremely arid and has limited renewable water resources. The traditional agricultural systems of the Arabian Peninsula changed during the second half of the twentieth century and contributed to increased agricultural production and economic development. As a consequence, the water demand greatly exceeded the available water supply and resulted in consuming nonrenewable groundwater resources (Abdulrazzak, 1995). Currently, the Arabian Peninsula has the lowest per capita renewable water supply, while the per capita consumption is the highest in the world. Further, the region is characterized by high temperatures throughout much of the year and the demand for water to meet human needs is high. Continued use of groundwater led to reduced groundwater levels and as a result saline intrusion occurs in many coastal areas. The farmers in the Arabian Peninsula have also been using brackish water for irrigation ( Jaradat, 2004). The consistent use of saline groundwater and brackish water has contributed to increased soil salinity (Table 1) and it is estimated that some areas almost 100% of the arable land has been affected by salinity (Hussain et al., 2006). Salt-affected soils and saline groundwater are widespread across the Arabian Peninsula and their use for crop and fodder has been promoted. 2.2.4. Central Asia Throughout the twentieth century, the native vegetation in the Central Asia region has been cleared and replaced with shallow-rooted crops (Toderich et al., 2008) that changed the natural hydrology of the landscape. Table 1

Arable and irrigation lands in the Arabian Peninsula

Country

Bahrain Kuwait Oman Qatar Saudi Arabia United Arab Emirates Yemen a b

Land area (km2)

Arable land (ha)

Irrigated landa Salt-affectedb (ha) land (ha)

0.707 17.8 310.0 11.5 2150.0 83.6

1.6 7.1 58.9 6.3 53,000.0 254.9

1.6 7.05 58.89 6.3 1191.4 226.6

1.6 200.0 2000.0 200.0 9300.0 1000.0

421.0

3620.0

679.7

1700.0

In some countries agriculture is completely irrigated. Salt-affected area is given as the total for the country.

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The region faces severe threat from soil salinity in irrigated areas once dominated by rice, vegetables, and cotton cultivation. Poor drainage and excess use of irrigation water have led to soil salinization (Table 2). On average, more than 50% of irrigated land in the region has been affected to various levels by salinity. Soil salinity in the downstream irrigation regions (Turkmenistan, Kyrgyzstan, and Kazakstan) ranges from 11.5% in Kyrgyzstan to 95.9% in Turkmenistan (Kijne, 2005). Farmers have few choices but to continue to grow cotton even though not economically viable (Dukhovny, 2005). 2.2.5. South Asia Almost 16 million hectares (around 20% of land area) of land in Pakistan has been affected by soil salinity, making the land unsuitable for normal agriculture. In irrigated agriculture, about 25% land is affected by salinity and about 1.4 million hectares of all agricultural land has been abandoned (World Bank, 2006). It has been estimated that salinity contributed to some 25% reduction in national agricultural production and in some provinces the impact is up to 60% reduction. The total annual cost of crop losses from salinity in Pakistan has been estimated to be between 270 and 960 million dollars. This is in addition to the 270 million dollars estimated to have been lost from the land that has been rendered unproductive. Taking the average cost of reduced yields as 540 million per year, the costs of salinity in Pakistan are equivalent to 0.6% of gross domestic production in 2004 (Corbishley and Pearce, 2007). Roughly 10% of Pakistan’s population live in regions with salt-affected soils and saline water and finding ways to cultivate on this land can contribute up to 2 billion dollars to the economy annually (Rahmatullah et al., 2006). About 21 million hectares of India’s land area (7%) is affected with the problem of salinity coupled with water logging (FAO, 2006b), which seriously reduce agricultural productivity and has grave implications for food security (http://www.fao.org/ag/agl/agll/terrastat). It was estimated Table 2 Irrigation land use in central Asia (FAO, 2006b) Land area Irrigated Country name (km2) area (ha)

Salt-affected Sodic % Land affected land (ha) soils (ha) by salinity

Kazakhstan Kyrgyztan Tajikistan Turkmenistan Uzbekistan

21,500 100 700 7300 6300

2711 199 142 471 445

2800 1100 719 1744 4220

107,100 0 0 1700 4600

40 1 5 15 14

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that poorly controlled irrigation along with groundwater rises affected about 8.5 million hectares of agricultural land (Vaidyanathan, 1994), serious enough to threaten the growth of agricultural economy ( Joshy et al., 1995). Extensive areas in Punjab, Haryana, and Uttar Pradesh within the Indo Gangetic Basin have been affected by soil salinity. In some areas, soil salinization has increased at a rate of 10% per year. In Bangladesh, salinity is a major factor that reduces crop productivity as a result of excessive and improper use of water in irrigation (Karim et al., 1990). In coastal areas, about 2.8 million hectares of land is salt affected mainly as a result of continuous use of groundwater with high salinity for irrigation and seawater intrusion (BARC, Bangladesh Agricultural Research Council, 2000). Up to 90% of coastal arable land remains fallow after rice harvest as a result of increased soil salinity as there is not enough rainfall for leaching the salt during that period.

3. Water Salinity Globally, about 53% of groundwater is saline (Palaniappan and Gleick, 2009). Almost in every irrigation region in the world, the groundwater is affected by salinity to some degree. In the Arabian Peninsula, the groundwater salinization is much higher than the global average (Al-Ruwaih and Hadi, 2005; Sultan et al., 2008). Both inherent groundwater salinity and salinity due to seawater intrusion have been reported in many coastal states in India (Report by the Ministry of Water Resources, Government of India). In Australia, groundwater salinity is inherent as a result of weathering of parent materials (MDBC, 1999). About 45% of surface water available in world lakes and wetlands has been affected by salinity (Palaniappan and Gleick, 2009). While quantitative information on salinity for all rivers in all countries is difficult to obtain due to poor data availability, salinity information do exists for some major river systems. In the Murray-Darling Basin, prior to 1999 it was considered that river salinity is a problem only for the lower River Murray. But the Salinity Audit of Murray-Darling Basin found that salinity levels in tributary rivers are also rising (MDBC, 1999) and is expected that in future salt load to river shift from irrigation induced to dry land agriculture. The Salt Loads studies by the States of NewSouth Wales, Victoria, South Australia, Queensland, and Australian Capital Territory, a major data source for Salinity Audit, provided estimates for the years 2020, 2050, and 2100. The average salinity of the lower River Murray (monitored at Morgan) will exceed the 800 EC thresholds for desirable drinking water quality in the next 50–100 years. By 2020, the probability of exceeding 800 EC will be about 50% (MDBC, 1999).

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In the United States, salinity in the Colorado River has long been a major concern. Increased salinity has been observed in the downstream part of the river. The river has carried an average salt load of approximately 9 million tons annually past Hoover Dam, the uppermost location at which numeric criteria have been established (Colorado River Basin Salinity Control Forum, 2008). Based upon projected development, salinity concentrations are predicted to exceed 1200 mg/L at Imperial Dam by the year 2010. Annual losses to the basin economy associated with increased salinity will exceed $50 million by the year 2010. It has been estimated that around 50% of river salinization has been attributed to irrigation developments (Vincent and Russell, 2007). The Aral Sea, once the fourth largest inland sea fed by Amu-Darya and Syr-Darya Rivers is now the largest inland salt reservoir as a result of excessive and inappropriate irrigation water use and salt discharge and the Sea itself is reduced by 50% (Cai et al., 2003). In addition, the down streams of both Amu-Darya and Syr-Darya Rivers have been affected by salinity as a result of reduced river flow and increased irrigation drainage. Within the Ganges River, salinity is a major problem in the downstream Bangladesh (Rahman et al., 2000). Large-scale withdrawal of water for irrigation and other uses in the Indian region reduced the river flow and increased the salinity of the river. Both surface and ground water salinization occurs in the same way as the salinization of soils as discussed earlier. Primary salinization of aquifers occurs through water in rock formation under marine conditions and weathering of salt from rock strata and the subsequent movement to aquifers. Salts contained within the sedimentary rocks are easily eroded, dissolved, and transported into the river system.

4. Responding to Soil and Water Salinity Given the presence of salt-affected soils and underlying saline groundwaters in most arid and semiarid regions, there is a need to address soil and water salinity. Plant-based interventions for improved crop and forage production for human and animal consumption is one option for using these salt-affected soils and saline waters. The use of salt-affected soils, saline waters, and appropriate plant type with proper irrigation scheduling and drainage systems through an integrated approach is important to balance salt in the crop rooting zone of the soil and surface and ground waters. Currently, there is no single approach to achieve the safe use of salt-affected soils and saline water for crop and forage production and prevent further development of salt-affected soils. Different approaches with appropriate combinations of practices that suit the economic, climate, and social circumstances of the region can be used to get best outcomes from the use of salt-affected soils and saline waters.

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4.1. Saline water use in irrigation Worldwide, a number of regions and individual countries have been using saline water for irrigation, including the United States (USA), Australia, North Africa (Egypt and Tunisia), South Asia (India, Pakistan and Bangladesh), Arabian Peninsula, and Central Asia. In the United States, saline waters have been used successfully for irrigation in the Southwest (Erickson, 1980; Kaffka et al., 2005; Rhoades, 1990) to grow crops and forages such as cotton, sugar beet, small grains, and alfalfa. Groundwater with total dissolved salt (TDS) up to 6,000 mg/L (electrical conductivity up to 10 dS/m) has been successfully used for irrigation in Pecos Valley in West Texas, Middle Rio Grande Basin in New Mexico, Red Mountain Farms in Arizona, and San Joaquin Valley (Kaffka et al., 2005; Rhoades, 1990). In Australia, the use of saline water for irrigation was first tested during the 1960s (Strickland, 1968). Field studies during the 1990s have shown that grain yield was averaged at approximately 10 tons with rice crop irrigated with saline water (Thompson et al., 1997). Over the last two decades, there has been considerable investment in both research and extension on the use of biological options for managing salinity in Pakistan, in particular, the use of salt-affected soil, saline water, and salt-tolerant plants. Kallar grass (Deplachne fusca) was grown in waterlogged saline soils (Malik et al., 1976) and has been used as a fodder. In some areas, brackish water was used for irrigation to provide feed for livestock (Khan and Qaiser, 2006). Crops are successfully grown in some parts of India under saline conditions quite different from those existing in typical, semiarid regions. The monsoonal rain in India plays a significant role in using saline water. It has been shown that saline waters can be used for irrigation in certain areas without excessive longterm build-up of soil salinity because of the extensive seasonal leaching that occurs in soils from these areas (Pal et al., 1984). Saline groundwaters of electrical conductivity up to 8 dS/m have been used for irrigation in many districts of Haryana State (Boumans et al., 1988). In some districts, the saline water is solely used for irrigation, while in the remaining districts it is blended with fresh canal water or in alternation with the canal water. In Tunisia, groundwater and surface water (saline Madjerda River) with salinity up to 5000 mg TDS/L (electrical conductivity of 8 dS/m) have been successfully used for irrigation (Stenhouse and Kijne, 2006). The main crops grown that used saline water for irrigation include date palm, sorghum, barley, alfalfa, rye grass, and artichokes. Relatively, impervious soils have also been used for irrigation in Tunisia with saline water with carefully selected crops and appropriately scheduled irrigation. In the northern Egypt, use of saline water up to 4,000 mg TDS/L (7 dS/m) drainage water for irrigation is very common as there is no alternative available

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(Amer and Ridder, 1988; Rady, 1990). In many situations, the freshwater from Nile River is blended with drainage water and used for irrigation. It is generally acceptable to farmers of yield reductions between 25% and 30% when using saline or blended water for irrigation. A number of crops including wheat, onion, maize, tomato, and pepper have been grown using saline water or saline waters blended with freshwater. Strategies have been designed to utilize saline water for irrigation (including development of improved irrigation systems), water management, control of salinity within the root zone, and utilization of genetic resources of salt-tolerant plants and halophytes in the Arabian Peninsula ( Jaradat, 2004). Long-term field evaluation of the productivity of highly salt-tolerant species, S. virginicus and Distichlis spicata, showed that, when managed properly, they have the economic and environmental potential in an integrated forage-livestock system (Dakheel et al., 2008). Currently, the two grass species are widely evaluated in several places in coastal environments in the Arabian Peninsula. In Central Asia, huge resources of slightly saline groundwater (500–2500 mg TDS/L with approximate electrical conductivity of 1–5 dS/m) which can be used for irrigation and improving the livelihoods of rural population. Livestock production is an integral part of using saline water in Central Asian saline environment (Toderich et al., 2006). Various trials on the use of salt-affected soils and saline water for agricultural production were established in different agro-climatic zones that differ significantly in soil salinity (Toderich et al., 2008). Pilot production studies on the use of salt-affected soils and saline waters indicated the cost effectiveness of producing large-scale grain and sweet sorghum raw materials for biofuel production in Central Asia.

4.2. Use of salt-tolerant plant and halophytes In many arid and semiarid regions with overlying saline aquifers, the groundwater contains salt levels that are high (5000–10,000 mg/L with an electrical conductivity of approximately 10–20 dS/m) for the irrigation of crops that are salt sensitive (Choukr-Allah, 1997). Salt-sensitive plants reduce yield when water with an electrical conductivity of 1 dS/m or more is used for growing such plants. Crop yield declined by 80% when the salinity of the water reaches 5 dS/m (Fig. 2). Yield is not affected in salt-tolerant crops when irrigated with water of electrical conductivity up to 10 dS/m. Crop yield declined by 80% when the salinity reaches to 30 dS/m (Fig. 2). Many halophytes have special characteristics that their growth will improve at salinity levels up to 5000 mg/L (10 dS/m) compared to salttolerant and salt-sensitive plants (Fig. 2). Some 10,000 halophytic plant species have been identified worldwide, of which around 250 species are potential staple crops (Toderich et al., 2006). Yield reductions are lower

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Karuppan Sakadevan and Minh-Long Nguyen

Relative crop yield (%)

120 100

Halophyte

80 Salt tolerant

60 Salt sensitive

40 20 0 0

5

10

15 20 Salinity (dS/m)

25

30

35

Figure 2 Growth response to salinity by salt-sensitive, salt-tolerant and halophytes plants (source: National Research Council, 1990).

compared to both salt-sensitive and salt-tolerant plants (less than 40% yield reduction observed at electrical conductivity of around 35 dS/m). Some halophytes may even reclaim the land for freshwater plants. They can leach soil salt through enhanced percolation and, to some extent, through storing salt in their leaves that are harvested and removed from the fields. Efforts have been extended by international research and development centers (ICARDA, IWMI, ICRISAT, ICBA, etc.) to promote successful technologies by using salt tolerance crops and halophytes (Qadir et al., 2007, 2009). Field selection and evaluation of new salt-tolerant crops and halophytes against the local varieties have demonstrated that salt-affected lands can be made economical to the farmers, and in the long run the area can be reclaimed to bring other cash crops such as cotton and wheat under production (Grattan et al., 2004; Kushiev et al., 2005). Trials conducted in different farmer fields in Central Asia and the Arabian Peninsula showed great adaptation and production of forage crops including sorghum, pearl millet, and fodder beet (Kushiev et al., 2005; Toderich et al., 2008). Various varieties of pearl millet (for forages and seed production) and two varieties of alfalfa (Medicago sativa) have proved to be far better than all local genotypes in Central Asia and Arabian Peninsula. A number of new halophytes are currently under development. The glasswort (Salicornia bigelovli) is a leafless annual salt-marsh plant with green jointed and succulent stems indigenous to the Arabian Sea and coasts of Pakistan and India. It produces seeds that are 30% oil and 35% protein; the oil is similar in fatty acid composition to safflower oil, and hence suitable for edible oil production. Its yield is also superior to soybeans and other oil seeds. Similarly, the seashore mallow (Kosteletzkya virginica), a perennial halophyte, is one of the many salt-tolerant plants that grow wild on the coastal marshlands or inland brackish lakes, and serves as a source of both feed and fuel. The oil

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content of the seed is 18%, similar to soybean with a fatty acid composition more like that of cotton seed; but unlike them both, it is a perennial, saving a lot of labor in resowing and sequestering more carbon in the deep roots. Another perennial halophyte used in response to salt-affected lands is D. spicata, which is most suited to grow in summer months in southern Australia. They are tolerant to high temperatures and high radiation. Even though the introduction of salt-tolerant plants and halophytes may not necessarily restore the soil to a level that conventional crops can be grown, it improves soil organic matter and aggregation, and reduces soil erosion (National Research Council, 1990) in addition to providing food and fiber. After 8 years of growing D. Spicata, an halophyte, in Western Australia, it was noticed that a marked increase in soil nutrient, reduced salinity and increased infiltration was observed as a result of increased soil organic matter content and improved soil aggregate stability (Sargeant et al., 2008).

4.3. Principles and practices in using salt-affected soils and saline waters The key management principles for the sustainable use of salt-affected soils and saline waters need to consider: (1) salinity management for preventing further increase in soil salinity level, (2) crop production management under saline conditions, and (3) monitoring soil and water salinity. 4.3.1. Salinity management Salinity management constitutes an important aspect of safe use of saltaffected soils and saline water for crop and forage production. Careful and efficient management of salt-affected soils and saline waters with appropriate plant can leave both the soil and groundwater salinity levels unaffected. This requires an understanding of how salinity affects plant growth and soil physical and chemical characteristics, the hydrogeologic processes, and the cropping and irrigation activities that affect soil and water salinity. Important considerations for salinity management in the use of salt-affected soils and saline waters include: 1. Construction of appropriate drainage systems to remove excess water from soil (Smedema et al., 2000). 2. Occasional leaching of salt from crop rooting zone with freshwater or low saline water (Pal et al., 1984). 3. Alternate use of saline water with freshwater (Payero et al., 2009). 4. The irrigation type, scheduling, and intensity that minimize water stress in crop rooting zone (Kruse et al., 1990).

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4.3.2. Crop management Crop management practices for the safe use of salt-affected soils and saline water primarily consists of growing suitable salt-tolerant crops, managing seedbeds, and grading fields to minimize local accumulation of salts, soil management, improving irrigation efficiency and soil, water, and salinity monitoring for assessing leaching and drainage requirements. Important crop management consideration includes (Ahmed and Malik, 2002): 1. Appropriate crop genotypes for satisfactory yield under existing and predicted saline conditions (Toderich et al., 2008). 2. Appropriate planting procedures to minimize salinity near the vicinity of seed (Bernstein and Francois, 1973). 3. Maintaining soil water at relatively high levels for plant growth (Payero et al., 2009). 4. Appropriate soil management such as tillage, ploughing, sanding, and chemical amendments, mineral fertilizers, organic manures, and mulching to improve soil organic matter and increased soil percolation (Ben-Gal et al., 2009). 5. An efficient water distribution system and irrigation scheduling (Kruse et al., 1990).

4.3.3. Monitoring Information on soil, water, and salinity within the crop rooting zone, plant growth, and salinity of drainage water needs to be obtained periodically to identify problem areas and to monitor the effectiveness of the use of saltaffected soils, saline waters, and plants. Normally, this can be done by measuring soil water content and soil electrical conductivity, from which salinity and leaching fraction can be determined. As soil salinity is highly variable over short distance in the field, it is recommended to have multiple samples. As large samples are involved for soil salinity measurements, simple methods for measuring soil salinity are required. Isotopic and nuclear techniques play an important role in monitoring the performance of technologies that use saltaffected soils, saline waters, and plants that grow under saline conditions. Some examples of the application of nuclear techniques are provided below: Isotopic signatures of 13C and 15N in soil organic matter: identify the source of soil salinity such as natural processes or anthropogenic activities (van Groenigen and van Kessel, 2002). 13 C isotope discrimination in plant: serves as a useful selection of criteria in breeding effort to develop salt-tolerant plants (Qian et al., 2004). Isotopic signatures of 15N in drainage, surface, and ground waters: improved understanding of the processes and sources of nitrogen (e.g., fertilizer and soil) in water that originate from irrigated landscapes including saline soils (van Groenigen and van Kessel, 2002; Petitta, et al., 2009).

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18

O and 2H isotopes: The movement of water from soil to crop is important for crop growth and an understanding of plant water uptake provide guidance for improving plant water use efficiency under saline condition. Maintaining appropriate root zone drainage during the growth period is important for leaching salt from crop rooting zone for optimum crop and forage production in salt-affected soils. 18O and 2H are useful to validate root zone drainage estimates made from conventional techniques (Yepez et al., 2003). Chlorine isotopes (35Cl and 37Cl): to study the origin of salinity such as irrigation, rainfall, and natural occurrence in groundwater systems (Nimz, 1999). 3 H and 3He isotopes: are important tools in the sustainable management of water resources and protection of the aquatic environment by providing direct information on groundwater age, flow paths, and flow velocities. Groundwater age estimates allow researchers to calculate recharge rates, assess an aquifer’s susceptibility to contamination, and calibrate complex groundwater flow models (Newmann et al., 2008; Onnis, 2008). Plant growth is reduced much more by water stress under saline conditions than under nonsaline conditions. Therefore, monitoring soil water content under saline condition is important to make sure that adequate water is available for plant growth throughout the growth period. Soil moisture neutron probe is useful for measuring soil water content under saline conditions as conventional soil monitoring devices are not appropriate for salt-affected soils (IAEA, International Atomic Energy Agency, 2008).

5. Conclusions Soil and water salinity in arid and semiarid regions is caused by both natural (primary salinization) and anthropogenic activities. In Arabian Peninsula and Central Asia, anthropogenic activities contributed more to soil and water salinity than primary salinization. The use of salt-affected soils and saline waters for agriculture is important for Arabian Peninsula and Central Asia as the available freshwater resources are not enough to meet the agricultural water requirements and part of arable land is saline. A multicountry regional program for sharing information on soil, water and crop practices leading to the sustainable use and management of salt-affected soils and saline waters for food and forage production is important for food security, poverty alleviation, and improved soil and water resources management. Such approaches include design and development of technology packages for the use of salt-affected soils and saline waters that provide maximum economic and environmental benefits. Transfer of technologies and methodologies of ICBA (International Centre for Biosaline Agriculture) in planting perennial and annual halophytes are a new approach that should be tested in many of these countries affected by soil and water salinity.

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With economically useful plants grown on salt-affected soils using saline water, more food and feed can be made available globally and abandoned land re-used because the soil that has become saline can be put in to use. A supply of saline water that can be used in agriculture will relieve pressure on freshwater resources. Crop diversification under saline soil conditions sustains agricultural productivity in salt-affected lands and will improve profits for farmers. The introduction of new species and varieties of forage crops, grasses, and legumes are important for reducing water logging and contributing to restoration of salt-affected soils. Management principles and practices for the safe use of salt-affected soils and saline waters need to be refined. These management principles and practices include: 1. Land preparation and management including seed bed preparation and the grading of the field to reduce salt accumulation. 2. Identification of salt-tolerant and halophyte plant species that gives satisfactory yield. 3. Maintenance of appropriate level of soil moisture to achieve periodic leaching to reduce salt accumulation. 4. Soil management including tillage, fertilizer application, mulching, and application of soil amendments to improve soil organic matter content, soil aggregation, and soil infiltration rates. 5. Improving the efficiency of irrigation. 6. Monitoring of soil water and salinity for assessing the adequacy of leaching and drainage. Nuclear and isotopic techniques play a key role in developing the principles, practices, and technology packages for using salt-affected soils and saline waters.

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Harneck, D. A., Ellsworth, J. W., Hopkins, B. G., Sullivan, D. M., and Stevens, R. G. (2007). Managing Salt-Affected Soils for Crop Production A Pacific Northwest Extension Publication, 24pp. Hussain, N., AI-Rawahy, S. A., Rabee, J., and AI-Amri, M. (2006). Causes, origin, genesis and extent of soil salinity in the Sultanate of Oman. Pak. J. Agric. Sci. 43(1–2), 1–6. IAEA (International Atomic Energy Agency). (2008). Field Estimation of Soil Water Content: A Practical Guide to Methods, Instrumentation and Sensor Technology. International Atomic Energy Agency, Vienna, Austria. Jaradat, A. A. (2004). Saline Agriculture in the Arabian Peninsula: Innovations in the Management of Marginal Lands and Saline Water Resources [CD-ROM] ASA-CSSA-SSSA Annual Meeting Abstracts, Madison, Wisconsin. Joshy, P. K., Tyagi, N. K., and Svendsen, M. (1995). Measuring crop damage due to soil salinity. In “Strategic Changes in Indian Irrigation” (M. S. A. Gulati, Ed.). Macmillan India Limited, New Delhi. Kaffka, S., Oster, J., Hoque, M., and Corwin, D. (2005). Forage yield, quality and livestock production using saline drainage water in the San Joaquin Valley. Proceedings of the International Salinity Forum, Managing saline soils and water: Science, Technology and Water Issues. April 25–27, 2005, Riverside, CApp. 269-272. Karim, Z., Hussain, S. G., and Ahmed, M. (1990). Salinity problems and crop intensification in the coastal regions of Bangladesh. Soils Publication, Soils and Irrigation Division, BARC, Farmgatepp. 1–20. Khan, M. A., and Qaiser, M. (2006). Halophytes of Pakistan: distribution, ecology, and economic importance. Sabkha Ecosystems: Volume II: The South and Central Asian Countries Kluwer Academic Press, Netherlandspp. 129-154. Kijne, J. W. (2005). Aral sea basin initiative. Towards a Strategy for Feasible Investment in Drainage for the Aral Sea Basin. Synthesis Report, IPTRID-FAO, Rome, Italy80p. Kruse, E. G., Willardson, L., and Ayars, J. (1990). On-farm irrigation and drainage practices. In “Agricultural Salinity Assessment and Management Manual” (K. K. Tanji, Ed.), pp. 349–371. ASCE, New York. Kundzewicz, Z. W., Mata, L. J., Arnell, N. W., Do¨ll, P., Kabat, P., Jime´nez, B., Miller, K. A., Oki, T., Sen, Z., and Shiklomanov, I. A. (2007). Freshwater resources and their management. In “Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change” (M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson, Eds.), pp. 173–210. Cambridge University Press, Cambridge, UK. Kushiev, H., Noble, A. D., Abdullaev, I., and Toshbekov, V. (2005). Remediation of abandoned saline soils using Glycyrrhiza globra: A study for the Hungry Steppes of Central Asia. Int. J. Agr. Sustain. 3, 102–113. Land and Water Resources Audit. (2000). Australian Government. Lipton, M., Litchfield, J., Blackman, R., De Zoysa, D., Qureshy, L., and Waddington, H. (2003). Preliminary review of the impact of irrigation on poverty with special emphasis on India Food and Agricultural Organization of the United Nations, 55 pp. Malik, K. A., Aslam, Z., and Naqvi, M. (1976). Kallar Grass: A Plant for Saline Land Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan, 93 pp. MDBC (1999). The salinity audit of the Murray Darling Basin. Murray Darling Basin Commission, Canberra, Australia. National Research Council (1990). Saline agriculture: Salt tolerant plants for developing countries. Report of the panel of the board on science and technology for international development National Academy Press, Washington DC. Newmann, R. B., Labolle, E. M., and Harvey, C. F. (2008). The effects of dual-domain mass transfer on the tritium-helium-3 dating method. Environ. Sci. Technol. 42, 4837–4843.

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Nicholls, R. J., Wong, P. P., Burkett, V. R., Codignotto, J. O., Hay, J. E., McLean, R. F., Ragoonaden, S., and Woodroffe, C. D. (2007). Coastal systems and low-lying areas. In “Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change” (M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson, Eds.), pp. 315–356. Cambridge University Press, Cambridge, UK. Nimz, G. J. (1999). Lithogenic and cosmogenic tracers in catchment hydrology. In “Isotope Tracers in Catchment Hydrology” (C. Kendall and J. J. McDonnell, Eds.), pp. 247–289. Elsevier. Onnis, G. A. (2008). Interpreting multiple environmental tracer data with a groundwater model in a Perialpine catchment. Diss. ETH No.18003 Swiss Federal Institute of Technology, Zurich. Paine, J. G. (2003). Determining salinization extent, identifying salinity sources, and estimating chloride mass using surface, borehole, and airborne electromagnetic induction methods. Water Resour. Res. 39(3), 1–10. Pal, B., Singh, C., and Singh, H. (1984). Barley yield under saline water cultivation. Plant Soil 81, 221–228. Palaniappan, M., and Gleick, P. H. (2009). Peak Water. In “The World’s Water 2008–2009. The Biennial Report on Fresh Water Resources” (Peter H. Gleick, Ed.), p. 16, Pacific Institute for Studies in Development, Environment and Security. Payero, J. O., Tarkalson, D. D., Irmak, S., Davison, D., and Petersen, J. L. (2009). Effect of timing of a deficit-irrigation allocation on corn evapotranspiration, yield, water use efficiency and dry mass. Agric. Water Manage. 96(10), 1387–1397. Petitta, M., Fracchiolla, D., Aravena, R., and Barbieri, M. (2009). Application of isotopic and geochemical tools for the evaluation of nitrogen cycling in an agricultural basin, the Fucino plains, Central Italy. J. Hydrol. 372, 124–135. Qadir, M., Oster, J. D., Schubert, S., Noble, A. D., and Sahrawat, K. L. (2007). Phytoremediation of sodic and saline-sodic soils. Adv. Agron. 96, 197–247. Qadir, M., Noble, A. D., Qureshi, A. S., Gupta, R. K., Yuldashev, T., and Karimov, A. (2009). Salt-induced land and water degradation in the Aral Sea basin: A challenge to sustainable agriculture in Central Asia. Nat. Resour. Forum 33, 134–149. Qian, Y. L., Follett, R. F., Wilhelm, S., Koski, A. J., and Shahba, M. A. (2004). Carbon isotope discrimination of three Kentucky bluegrass cultivars with contrasting salinity tolerance. Agron. J. 96, 571–575. Rady, A. H. M. (1990). Water, soil and crop management relating to the use of saline water. “Proc. Expert Cons. on Water Soil and Crop Management Relating to the Use of Saline Water, October 1989. AGL/MISC/16/90”, FAO, Rome. Rahman, M. M., Hassan, M. Q., Islam, M. S., and Shamsad, S. Z. K. M. (2000). Environmental impact assessment on water quality deterioration caused by the decreased Ganges outflow and saline water intrusion in south-western Bangladesh. Environ. Geol. 40(1–2), 31–40. Rahmatullah, M. A., Maqsood, T., and Tahir, M. A. (2006). Contribution of shallow water table to salinity/sodicity development under fallow and cropped conditions. Pak. J. Agric. Sci. 43(1–2), 7–12. Rhoades, J. D. (1990). Blending saline and non-saline waters reduces water usable for crop production. In “Proc. 1990 Conf. Irrigation and Drainage,” (S. C. Harris, Ed.), pp. 442– 452, 11–13 July, Durango, Colorado. Sargeant, M. R., Tang, C., and Sale, P. W. G. (2008). The ability of Distichlis spicata to grow sustainably within a saline discharge zone while improving the soil chemical and physical properties. Aust. J. Soil Res. 46(1), 37–44. Smedema, L. K., Abdel-Dayem, S., and Ochs, W. J. (2000). Drainage and agricultural development. Irrigat. Drain. Syst. 14(3), 223–235.

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Stenhouse, J., and Kijne, J. W. (2006). Prospects for Productive Use of Saline Water in West Asia and North Africa International Water Management Institute, Colombo, Sri Lanka (Comprehensive Assessment of Water Management in Agriculture Research Report 11. Central Asia: Biosaline agriculture and utilisation of the salt affected resources. Discussion paper No. 648. Kyoto University, Kyoto, Japan). Strickland, R. W. (1968). The use of saline water for irrigating rice in northern Australia. Aust. J. Exp. Agric. Ani. Hus. 8(33), 491–495. Sultan, M., Sturchio, N., Al Sefry, S., Milewski, A., Becker, R., Nasr, I., and Sagintayev, Z. (2008). Geochemical, isotopic, and remote sensing constraints on the origin and evolution of the Rub Al Khali aquifer system, Arabian Peninsula. J. Hydrol. 356(1–2), 70–83. Thompson, J., Hume, I., Griffin, D., North, S., and Mitchell, D. (1997). Use of saline water in rice based farming systems. National Program for Irrigation Research and development. Final Report, NSW Agriculture, Australia, 9 pp. Toderich, K., Tsukatani, T., Abdusamatov, M., Rakhmatullayev, R., Latipov, R., and Khujanazarov, T. (2006). A farm in Kumsangir of Tajikstan: A perspective of water/ land usealong Pyandzh River. Kier Discussion Paper 619 Kyoto University, Japan,58 pp. Toderich, K., Tsukatani, T., Shoaib, I., Massino, I., Wilhelm, M., Yusupov, S., Kuliev, T., and Ruziev, S. (2008). Extent of salt affected land in Central Asia: Biosaline agriculture and utilisation of salt affected resources. Discussion Paper No. 648 Kyoto Institute of Economic Research, 34 pp. Vaidyanathan, A. (1994). Second India Studies Revisited. Food, Agriculture and Water Madras Institute of Development Studies, Madras, India. van Groenigen, J. W., and van Kessel, C. (2002). Salinity induced patterns of natural abundance carbon-13 and nitrogen-15 in plant and soil. Soil Sci. Soc. Am. J. 66, 489–498. Vincent, J. R., and Russell, J. D. (2007). Alternatives for salinity management in the Colorado River Basin. J. Am. Water Works Assoc. 7(4), 856–866. WCD. (2000). Dams and development: A new framework for decision making. Report of the World Commission on Dams Earthscan, London, UK. Williamson, D. R. (2000). Dryland Salinity in Crisis: Causes and Cures Compared, pp. 25. World Bank. (2006). Pakistan Strategic Country Environmental Assessment, Volume II World Bank, Washington, DC. Yepez, E. A., Williams, D. G., Scott, R. L., and Lin, G. (2003). Partitioning overstory and understory evapotranspiration in a semiarid savanna woodland from the isotopic composition of water vapour. Agric. For. Meteorol. 119, 53–68.

C H A P T E R

T H R E E

The African Green Revolution: Results from the Millennium Villages Project Generose Nziguheba,* Cheryl A. Palm,* Tadesse Berhe,† Glenn Denning,* Ahmed Dicko,‡ Omar Diouf,§ Willy Diru,} Rafael Flor,# Fred Frimpong,k Rebbie Harawa,** Bocary Kaya,‡ Elikana Manumbu,†† John McArthur,*,‡‡ Patrick Mutuo,} Mbaye Ndiaye,§ Amadou Niang,# Phelire Nkhoma,** Gerson Nyadzi,†† Jeffrey Sachs,* Clare Sullivan,* Gebrekidan Teklu,† Lekan Tobe,§§ and Pedro A. Sanchez* Contents 76 79 79 83 83 84 84 84 90 92 92 96 102

1. Introduction 2. Description of the Village Clusters 2.1. Geography, ecology, climate, and soils 2.2. Farming systems and crops 2.3. Farming households 3. Methodology 3.1. Decision-making 3.2. Agricultural interventions 3.3. Data collection and analysis 4. Results 4.1. Crop yields 4.2. Value-to-cost ratios 4.3. Crop and enterprise diversification

* The Earth Institute, Columbia University, New York { MVP Koraro cluster, Center for National Health Development, Addis Ababa, Ethiopia { MVP Tiby Cluster, Segou, Mali } MVP Potou cluster, Louga, Senegal } MVP Sauri cluster, Kisumu, Kenya # MDG Center for West and Central Africa, Bamako, Mali k MVP Bonsaaso Cluster, Manso-Nkwata, Ashanti, Ghana ** MVP Mwandama Cluster, Zomba, Malawi {{ MVP Mbola Cluster, Tabora, Tanzania {{ Millennium Promise, New York, USA }} MVP Pampaida Cluster, Zaria, Kaduna State, Nigeria Advances in Agronomy, Volume 109 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)09003-6

#

2010 Elsevier Inc. All rights reserved.

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5. Discussion and Way Forward 5.1. Crop production 5.2. Organic inputs and soil management practices 5.3. Improved nutrition 5.4. Diversification, primarily with irrigation 5.5. Subsidies and the transition to credit 5.6. Safety nets 5.7. Adaptation to climate change 6. Conclusions Acknowledgments References

103 103 105 107 108 108 109 110 111 112 112

Abstract The Millennium Villages Project (MVP) was initiated in 2005 to implement the recommendations of the UN Millennium Project for achieving the Millennium Development Goals (MDGs). The project is carried out in 14 sites in hunger and poverty hotspots in diverse agroecological zones in sub-Saharan Africa (SSA). The interventions and results for increasing staple crop yields are presented for eight MV sites and cover 52,000 farming households or 310,000 people. By supporting farmers with fertilizers, improved crop germplasm, and intensive training on appropriate agronomic practices, average yields of 3 t ha 1 were exceeded in all sites where maize is the major crop. Teff yields doubled in the Ethiopian site. In contrast, there was little improvement in millet and groundnut yields in the semiarid and arid sites in West Africa. Over 75% of the farms had maize yields of 3 t ha 1 and less than 10% of the households had yields lower than 2 t ha 1. Households produced enough maize to meet basic caloric requirements, with the exception of farms smaller than 0.2 ha in Sauri, Kenya. Value-to-cost ratios of 2 and above show that the investment in seed and fertilizer is profitable, provided surplus harvests were stored and sold at peak prices. Increased crop yields are the first step in the African Green Revolution, and must be followed by crop diversification for improving nutrition and generating income and a transition to market-based agriculture. A multisector approach that exploits the synergies among improved crop production, nutrition, health, and education is essential to achieving the MDGs.

1. Introduction In most parts of the developing world, per capita staple food crop production has increased steadily over the past four decades. This increase is largely the result of Green Revolution technologies, including high-yielding crop cultivars, irrigation, fertilizers, mechanization, and pest and disease control, supported by enabling government policies (Hazell and Wood, 2008). Sub-Saharan Africa (SSA) is the only region where per capita

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production has barely changed (Hazell and Wood, 2008; Jaeger, 1992). While populations continue to grow, yields of major crops remain very low in SSA with average cereal yields of less than 1 t ha 1 compared to averages of 3 t ha 1 Latin America and South Asia (Hazell and Wood, 2008). The absence of the Green Revolution in Africa has been attributed to the lack of adoption of improved crop germplasm or even the absence of appropriate varieties for the continent (Sanchez, 2002) but perhaps more pervasive has been the gradual depletion of soil fertility through decades of removing nutrients with crop harvests but not replenishing them through the addition of sufficient amounts of fertilizer, mineral, or organic (Drechsel et al., 2001; Sanchez, 2002; Stoorvogel et al., 1993). The removal of subsidies for fertilizers in Africa in the 1980s by the “Washington Consensus” structural adjustment programs led to the decline of fertilizer use (World Bank, 2008). Limited physical access to fertilizers has also been identified as a major constraint to the use of fertilizers in many countries in Africa (Larson and Frisvold, 1996). At the Africa Fertilizer summit, a call for increasing the use of fertilizers from the current average of 8 kg ha 1 was made to raise agricultural production (IFDC, 2006). If SSA is to feed its population, a major transformation in agriculture production needs to happen. At the Millennium Summit in 2000, world leaders set forth the Millennium Development Goals (MDGs), quantified and time-bound goals to cut extreme poverty and hunger, reduce disease burden, improve education, gender equality, and reverse land degradation. Although the MDGs have been generally accepted, questions arose regarding how to implement them. In 2002, the United Nations (UN) Millennium Project was commissioned by the UN Secretary General to develop a concrete action plan for the world to achieve the MDGs; task forces were convened to provide recommendations for each of the MDGs. Recommendations from each of the task forces were published in separate reports and summarized in the Investing in Development report (UN Millennium Project, 2005a). Currently, Africa is the only continent severely off-tract to reach the goals (MDG Africa Steering Group, 2008). Several biophysical and policy constraints limit the ability of most African countries to escape from hunger, extreme poverty, and disease; extremely low food production being at the top ( Jayne et al., 2003; Larson and Frisvold, 1996; Sachs et al., 2004). Drawing on the work of the UN Millennium Project Hunger Task Force (Sanchez and Swaminathan, 2005; UN Millennium Project, 2005b), the then Secretary General of the UN, Kofi Annan, made a call for a uniquely African Green Revolution that provided the framework for Africa to achieve the MDG 1, the eradication of extreme poverty and hunger (MDG Center of East and Southern Africa, 2004). The Hunger Task force made seven major recommendations toward the hunger eradication goal:

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Moving from political commitment to action. Reforming policies and creating an enabling environment. Increasing the agricultural productivity of food-insecure farmers, focusing first on soils and water. Improving nutrition for chronically hungry and vulnerable groups. Reducing the vulnerability of the acutely hungry through productive safety nets. Increasing incomes and making markets work for the poor. Restoring and conserving the natural resources essential for food security.

The Millennium Villages Project (MVP) was initiated in 2005 as proof of the concept that, by applying the recommendations from all the UN Millennium Project Task Forces in impoverished rural communities in Africa, they can achieve the MDGs at a local scale by 2015 (Sanchez et al., 2007). The sites were chosen from among hunger hotspots (defined as more than 20% of children under the age of five as underweight for age) that were identified by the UN Millennium Project Hunger Task Force to represent the diverse agroecological zones and farming systems in Africa, as defined by Dixon et al. (2001). The MVP is community-based and applies science- and evidence-based interventions in health, education, agriculture, road and electricity infrastructure, information technology, water and sanitation, and the environment. The community-based approach used in the MVP follows well-established principles of participation, social and gender inclusion, equity, and local stakeholders’ ownership of the decision-making and development processes. Communities are involved in all steps of the project, including assessments and priority setting, planning, implementation, monitoring, and evaluation of project activities. Before implementation, communities went through a selfanalysis process in which they determined the resources available within and outside the community, and identified their main priorities. Project staff (all nationals of the countries) work with the communities to assess potential interventions for the local situations, taking into account short- and long-term objectives, and cost effectiveness. Subsequent steps consisted of developing community action plans to address these priorities and the steps needed to achieve the MDGs by 2015. Community-based institutions or leaders were identified and they play important roles in the implementation of interventions. They included traditional chiefs and elders, local government officials, agricultural extension officers, common interest entrepreneurial groups, farmer associations, women groups, youth groups, self-help groups, and Non Governmental Organizations (NGOs) already working in the villages. Local capacity building plays a major role in achieving community ownership. Before the MVP started, the communities involved typically experienced food shortages for several months in a year, which also had a negative

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impact on other MDGs, such as health and school attendance, and often led to migration from rural to urban areas, particularly of men and youth. Therefore, increasing agricultural production and achieving basic food needs was one of top priorities identified by communities, followed by improved health care services (Sanchez et al., 2007). In this review, we focus on the MDG Goal 1 target of halving hunger, the agriculture-related activities carried out to increase food availability, access, and utilization. We summarize the processes, activities, and results of 3–4 years of interventions in several Millennium Village clusters, followed by a discussion of the next steps in the transition from subsistence agriculture to market-based agriculture.

2. Description of the Village Clusters The MVP operates in 80 villages organized in 14 clusters in Kenya, Ethiopia, Ghana, Malawi, Mali, Nigeria, Senegal, Rwanda, Tanzania, and Uganda (Fig. 1). These villages were selected to represent the principal agroecological zones and farming systems of Africa that are hunger hotspots. Eight clusters (Sauri, Kenya; Bonsaaso, Ghana; Mwandama, Malawi; Pampaida, Nigeria; Mbola, Tanzania; Tiby, Mali; Koraro, Ethiopia; and Potou, Senegal) were selected to illustrate the site-specific activities and achievements in increasing basic food production and other related interventions. Together they constitute 55 out of the 80 Millennium Villages, with approximately 52,000 farming households and 310,000 people. The general characteristics of the sites are presented in Table 1 and summarized below to illustrate the range in conditions in which the MVP is targeting MDG 1. The number of households within the different clusters ranges from less than 1000 in the case of Pampaida, to almost 13,000 in Sauri and Koraro (Table 2).

2.1. Geography, ecology, climate, and soils The eight sites cover a range of agroecological zones: humid, subhumid, dry subhumid, semiarid, and arid tropics. They include tropical rainforest margins (Bonsaaso); dry subhumid Sudan savanna (Pampaida); Sahel (Tiby); coastal Sahara margin (Potou); maize-based bimodal systems (Sauri); maizebased unimodal systems in Miombo Woodlands (Mbola); maize-based unimodal, with small farms (Mwandama), and semiarid highlands with mixed crop-livestock (Koraro). Mean annual rainfall ranges from 270 mm in Potou to 1800 mm in Sauri. Most sites have unimodal rainfall patterns except for Sauri and Bonsaaso, with two rainy seasons where cropping is possible. Landscapes vary from lowlands in West Africa, including a coastal

Millennium villages Koraro, Ethiopia

Potou, Senegal Dertu, Kenya Toya, Mali Tiby, Mali

Bonsaaso, Ghana Agro-ecological zones

Pampaida, Nigeria

Mbola, Tanzania

Maize mixed Highland mixed

Ikaram, Nigeria

Highland perennial Pastoral

Sauri, Kenya

Gumulira, Malawi

Ruhiira, Uganda

Agrosilvopastoral Cereal-root crops mixed: (Sudan savanna) (Southern Miombo)

Root crops: (Guinea savanna) (Miombo) Tree crops Coastal artisanal fishing Irrigated Paddy rice

Mwandama, Malawi

No research villages Mayange, Rwanda

Sparse Large commercial and small holder Forest based Adapted from Dixon et al. 2001. Farming Systems and Poverty. FAO

Millennium village sites featured in this chapter Other millennium village sites

Figure 1 Location of Millennium Villages in sub-Saharan Africa. Adapted from Dixon et al. (2001).

Table 1

Site characteristics, arranged in decreasing order of annual rainfall

Village cluster, location

Farming system and AEZa

Sauri, Nyanza Maize mixed, Province, Kenya Subhumid tropical Bonsaaso, Ashanti Tree crops, humid Region, Ghana tropical forest Cereal root-crops Mwandama, mixed, subhumid Southern region, tropical Malawi Pampaida, Kaduna Agrosilvopastoral, State, Nigeria dry subhumid Mbola, Tabora Maize mixed, dry region, Tanzania subhumid Tiby, Segou region, Cereal root-crops Mali mixed, semiarid Koraro, Tigray Highland mixed, region, Ethiopia semiarid Potou, Louga Arid (pre-Saharan), region, Senegal coastal artesian fishing

a b

Agrocolological zone (Dixon et al., 2001). Grown by at least 50% of the households.

Elevation (m)

Rainfall pattern and annual average (mm)

Length of major rainy season

1400

Bimodal 1800

March–August

Dominant soils

Rhodic Hapludox, clayey 210 Bimodal, 1333 April–July Hapludult, sandy loam 900–1200 Unimodal, 1139 November –April Rhodustalfs, loamy to clayey 615 Unimodal, 1050 June–November Haplustalfs, sandy to loamy 1050 Unimodal, 928 November–April Haplustalfs, sandy 275 Unimodal, 543 July–September structurally inert sandy Ustalfs 1550–2000 Unimodal, 500 June–August Calciustepts, sandy 1–30 Unimodal, 270 July–October Torripsamments (Niayes zone), sandy Haplustalfs (Die´ri zone)

Population density (people per square kilometer) Major cropsb

690

Maize, beans

63 724

Cocoa, plantain, maize Maize

138

Sorghum, maize

40

Maize

98

Millet, cowpea, flooded rice Teff, sorghum, maize Onion, millet, groundnut

63 122

Table 2 Selected characteristics of farming households in baseline study prior to start of the project

a b

Village cluster

Average number of Average area Number of persons per cropped per households household household (ha)

% of Fertilizer N households rate using fertilizer (kg N ha 1)

Sauri Bonsaaso Mwandama Pampaida Mbola Tiby Koraro Potou

12,756 4,164 7,000 952 6,610 5,300 12,632 2,245

40 0 30 77 39 21 79 90

5.7 5.2 4 6 5.6 12.6 4.4 9.7

0.6 4.9 1.0 3.4 3.4 9.6 1.9 1.4

< 10 < 10 < 30 < 30 < 10 < 30 < 10 103b

Fertilizer P rate (kg P ha–1)

% of households using improved seed

5 5 5 5 5 5 < 15 < 15

2 0 20 2.3 Nda 80 2.7 90

Not determined. The rate is for the Niayes zone where vegetables are produced as cash crops and therefore benefiting from high fertilizers. The rate is much lower in the Die´ri zone where millet, groundnut, and cowpea are grown.

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desert site, and highland sites up to 2000 m in East Africa. Soil types vary from sandy Entisols and Inceptisols in Potou and Koraro, Vertisols also in Koraro, to structurally inert sandy Alfisols subject to surface sealing in Tiby, sandy Alfisols in Pampaida, humid tropical Ultisols in Bonsaaso, red loamy to clayey Alfisols in Mwandama, and clayey Oxisols in Sauri.

2.2. Farming systems and crops The farming systems vary from tree crops in the humid tropical forest zone in Bonsaaso, to mixed maize farming in Sauri, Mbola, Mwandama, highland mixed systems in Koraro, agropastoral systems in Pampaida and Tiby, and coastal irrigated desert in Potou. Farmers of Sauri, Mwandama, Pampaida, Mbola, and Koraro produce most of their food from cereal crops that have distinct planting and harvesting seasons. Maize (Zea mays) constitutes the major staple crop in Sauri, Mbola, and Mwandama. Pampaida is dominated by sorghum (Sorghum bicolor) and livestock in the nomadic Fulani zone, but maize and upland rice (Oryza sativa) are also important. The major staple crop in Koraro is teff (Eragrotis tef ), but a variety of cereals, finger millet (Eleusina coracana), sorghum, wheat (Triticum aestivum), barley (Hordeum vulgare), and maize are widely grown along with several grain legumes such as lentil (Lens esculenta). Cassava (Manihot esculenta) and sweet potatoes (Ipomoea batatas) are grown in all but the two driest clusters. The three remaining sites have farming activities that occur at different times of the year. Potou comprises two zones, a coastal Niayes zone where fishing and irrigated onion (Allium cepa) production are the main activities conducted throughout the year, and a rainfed zone (Die´ri) where pearl millet (Pennisetum glaucum), groundnut (Arachis hypogaea), and cowpea (Vigna unguiculata) are grown during a short rainy season. Bonsaaso relies primarily on a system of slash and burn where a few years of annual crops are followed by tree-based agroforests, composed mainly of cacao (Theobroma cacao). Tiby has about half of its area in a large irrigated rice scheme, while the upland areas are planted to millet and cowpeas in the rainy season and to small-scale irrigated vegetable gardens. Cattle are important in all but two sites: in humid tropical Bonsaaso the presence of the tse-tse fly zone limits livestock to small ruminants; and the small farm sizes in Mwandama preclude grazing or forage production, with very few cattle and goats present. Some form of agroforestry, although not dominant is present at all sites. These include improved fallows, tree hedges for livestock feed, as well as fuelwood, timber, and fruit trees.

2.3. Farming households The population density of the sites varies from 40 persons per square kilometer in Mbola to about 700 persons per square kilometer in both Sauri and Mwandama (Table 1). Baseline surveys, conducted prior to the

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interventions, indicate that the average size of household ranges from four persons in Mwandama to 13 persons in Tiby (Table 2). The average area cropped per household varies from about 0.6 ha in densely populated Sauri to 5 ha or more in less-populated sites, such as Bonsaaso, Tiby, and Potou’s upland part. Typical of the African context, the use of mineral fertilizer and improved seeds is low in all sites. The percentage of farmers using any mineral fertilizer was below 50% in five sites, with no use of fertilizer in Bonsaaso. In all sites, including those where the majority of households use fertilizers, the rate of nutrient application was very low, often less than 10 kg N ha 1 and 5 kg P ha 1 per crop. Most households apply whatever limited quantities of animal manure and compost they can collect. While more than 50% of households used improved seeds in Tiby and Potou, less than 3% of households used improved seeds in the other sites.

3. Methodology 3.1. Decision-making Community participation in identifying the problems with agricultural production, assessing possible solutions, developing plans and budgets, and then the subsequent implementation and monitoring is essential; first to achieve ownership and second to assure that the plans are appropriate and localized for the specific site (UNDP, 2007). Village leaders formed agriculture committees through community elections or appointments, or existing committees were strengthened. Efforts were made to assure representation from throughout the villages and to include underrepresented groups, specifically women and young people. These committees together with the project staff made the decisions. Project staff ensured that such decisions were science-based.

3.2. Agricultural interventions In order to increase staple crop productivity basically from 1 to 3 t ha 1 of cereal yields, the villagers and project staff decided on the following interventions for the first two years:  

Reversing soil fertility depletion with subsidized mineral fertilizers. Providing improved seeds, also subsidized, either hybrids or open-pollinated cultivars, of the basic food crops recommended by national agricultural research institutes and Consultative Group in International Agricultural Research (CGIAR) offices in the various countries.  Empowering agricultural extension officers with transportation and laptop computers, in order for them to train farmers in the latest knowledge

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of good agronomic practices, including early planting, spacing, seed and fertilizer placement, harvest and storage methods, small-scale water management, and others.  Farmers agreeing to contribute part of their harvest to the village school feeding programs.  Constructing grain storage facilities to minimize postharvest losses as well as to store crop surpluses in order to sell later at higher prices, rather than immediately after harvest when prices are lowest. After the first 2 years, the following additional interventions were added to trigger the transition from subsistence farming to diversified agriculture for improved nutrition and income generation: 









Promoting enterprise diversification, including high-value crops such as vegetables, fruits, spices, as well as dairy cows and goats, poultry, beekeeping, mushroom production, aquaculture, and various agroforestry systems. Promoting small-scale water management using treadle pumps, drip irrigation, and rainwater harvesting, for supplemental irrigation of highvalue cash crops and dry-season farming. Improving nutritional security, including school-based nutrition programs such as locally produced school meals; introduction and demonstrations of the value of nutritious foods including orange-fleshed sweet potatoes, milk, soybeans, African leafy green vegetables, and fruits. Beginning the transformation to small-scale entrepreneurship: working with existing or new farmer associations; marketing studies to identify local demand for different high-value products; training on banking, credit and business accounting; establishing linkages to financial services for credit for farm inputs and bank accounts for savings; agroprocessing for adding value; use of cell phones for obtaining price information; and linking villagers to the value chain; and to markets starting with local, regional, and even international. Risk reduction via improved weather forecasting and crop insurance.

Improved germplasm as well as several agronomic practices used at each of the clusters (Table 3) were those recommended by research and extension agencies, since no adaptive research was done at the villages, following the philosophy of using knowledge already available. In this chapter, emphasis is given to one major rainfed crop per site, although a brief discussion on irrigated crops is also provided for sites where they constitute the primary farming activities. 3.2.1. Improved germplasm Maize is the major crop of Sauri, Mwandama, and Mbola. Maize was also promoted for diet diversification in Pampaida and Bonsaaso. In Pampaida, soybean and upland rice were also promoted, but at a lower scale.

Table 3

Management applied during cropping seasons in various village clusters

Village, cluster

Crop

Sauri

Maize

Cultivars, variety or hybrid

Method of land pre paration

WS 502, WS Hand 505, WS 402, hoeing, DK 8031 flat Bonsaaso Maize Obatanpa, Hand Golden hoeing, Jubilee ridging Mwandama Maize DKC 8073, Hand DKC 8033 hoeing, tied ridging Pampaida Maize Oba Supa 1, JO- Animal 2, Oba 98 traction, ridging Hand hoe, Mbola Maize SEEDCO, ridging Pannar 67 DK8031 DK8053 Tiby Millet Toronio Animal traction, ridging Koraro Teff DZ-CR-27, Animal DZ-01-947 traction flat Potou Groundnut 55, 437 Animal traction flat a b

Planting fertilizer

Topdressing fertilizers and application time

Plant N rate P rate spacing (kg N ha 1) (kg P ha 1) (cm)

Weeding

Major pests

Stem borer, streak virus, striga Stem borers

DAP, point Urea, at knee placement height

80

25

75  30

Two times

NPKa point (NH4)2SO4 at placement knee height

45

8

80  40

Three times

NPS point Urea, at knee placement height

86

11

75  25

Three times

Stem borer, streak virus, wire worms

NPKa point Urea, at knee placement height

129

26

75  25

Three times

DAP or PRb Urea, at knee point height placement

80

25

90  25

Two times

Stem borer, streak virus, striga Stem borer, streak virus, striga

NPKa broadcast

Urea, at 3 weeks 53

13

50  50

DAP, broadcast

Urea, at 3 weeks 41

20

NPKa, PRb, broadcast

none

28

3

Two– Mildew, three Acarien times broadcast One–two Stem borers, time shoot fly, white grub 50  12 Three Locusts times

NPK basal fertilizers have different formulations (N, P2O5, K2O) as follows: 23–21–10 in Bonsaaso, 15–15–15 in Pampaida and Tiby, and 6–20–10 in Potou. Phosphate rock. Minjingu Phosphate rock replaced DAP (diammonium phosphate) in the third year in Mbola, whereas phosphate rock was used in each season in Potou.

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In Bonsaaso, cowpea was introduced because the prevailing farming system included few protein sources. Interventions on cacao in Bonsaaso focused on improving the current agronomic practices to increase production and reduce pest and diseases. In Tiby, millet and flooded rice were the two crops targeted. In Koraro, interventions targeted various cereals, whereas pulse crops such as chickpea (Cicer arietinum) were introduced. For the drier, rainfed zone of Potou, the project focused initially on improved seeds of millet but switched to groundnut and cowpea in subsequent years. Most of the maize germplasm used were hybrids, except for Golden Jubilee and Obatanpa in Bonsaaso (Table 3). Germplasm of the other crops were all improved varieties. 3.2.2. Land preparation Land preparation followed the traditional practice of hand hoeing in most clusters in humid and subhumid zones. In drier zones (Tiby, Potou, Pampaida, and Koraro), animal traction is practiced (Table 3). In Bonsaaso, Mwandama, Pampaida, and Mbola crops were grown on ridges, whereas flat planting was practiced in Sauri, and Potou. Spacing between ridges was reduced. There was no mechanization and reduced tillage was not practiced. 3.2.3. Plant spacing The spacing of 75 cm  25 cm and with one plant per hole was practiced in Pampaida and Mwandama because it is promoted by Sasakawa Global 2000 in those countries (Table 3). This is in contrast with the traditional plant spacing of 90 cm  90 cm with four seeds planted per hole in Mwandama, which is considered too wide. Within a cluster, various spacing recommendations prevailed depending on whether the crop was grown in monoculture or intercropped with other crops like groundnuts, common beans (Phaseolus vulgaris), cowpeas, pigeon pea (Cajanus cajan), or cassava. Also it depended on rainfall pattern; for example, maize in Sauri is planted at 75 cm  30 cm spacing for monocrop in the wetter areas but 90 cm 30 cm is recommended for drier parts of the cluster. 3.2.4. Fertilizer use The sources of mineral fertilizers, their placement, and rates of application also varied among clusters, depending on their availability and the recommendations from the national research and extension services (Table 3). Diammonium phosphate (DAP) is used as the source of nitrogen and phosphorus for basal applications, and urea for top-dressing in most East African sites. The exception is Malawi, where the planting fertilizers is a unique blend (23 N-21 P2O5-0 K and 4 S) especially imported by the government. Compound NPK fertilizers are used in the most West African sites for basal application, and either urea or ammonium sulfate is used for top-dressing.

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The placement of the basal fertilizer applications is Africa’s version of precision farming. Farmers dig a planting hole at the recommended spacing, calibrate the applied fertilizer with soda bottle caps, cover it, and plant the seeds. The exceptions are in the three driest sites, Tiby, Koraro, and Potou, where basal fertilizer applications were broadcast and incorporated at tillage. Rates of nitrogen application for maize ranged from 45 to 129 kg N ha 1 per crop, while that of phosphorus was 11 to 28 kg P ha 1. The rates of nitrogen applied, except for the highest rate applied in Pampaida, Nigeria, are below those recommended to obtaining maximum yields. 3.2.5. Pest management No herbicides were used. Two weedings were done for the staple crops in all sites, except for Koraro. The major pest for maize at all sites was the stem borer (Busseola fusca) and maize streak virus was the major disease (Table 3). Striga (Striga hermonthica) infestations occurred in Sauri, Pampaida, and Mbola. No insecticides for controlling stem borers were used, except in a few cases in Mbola. The pests and disease attacks did not result in crop failure in any site except for the locust invasion in Potou during the first season. 3.2.6. Irrigated crops In addition to rainfed crops, rice and onions are major irrigated crops in Tiby and Potou, respectively. In Tiby, irrigated rice is grown on half of the cluster’s cropland, and has been supported by the project with inputs. However, the current irrigation scheme requires much improvement in irrigation water control, and land leveling. In Potou, onion is produced in the coastal zone. The MVP provided improved seeds and a change in irrigation practice. Previously, most of the onion fields were irrigated with buckets from the site’s numerous concretelined, shallow wells. The watering rate was 10 l m 2 day 1 done in the middle of the day, when irrigation is least efficient. Consequently, the shallow water table was dropping at an alarming rate of 20 cm year 1, resulting in a high risk of salt intrusion from the Atlantic Ocean. This changed to drip irrigation with a diesel pump using the same wells. One pump can irrigate 0.5 ha day 1, in 12–36 min with drip irrigation. 3.2.7. Grain banks and storage facilities With the anticipated increases in crop yields, storage facilities were organized in advance of surplus harvests. These facilities helped to reduce postharvest losses and also provide an option for farmers so that they do not have to sell their surplus immediately after harvest when prices are generally low. Community-owned storage facilities were constructed or improved in the second year of the project. The community contributed to the construction by making bricks, bringing stones, sand, poles, and labor for

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building the facility, whereas the project contributed cement, roofing materials, metal doors and windows, and skilled masons. 3.2.8. Subsidy and distribution of fertilizers and improved seed The entry point for improving crop production was to provide support of subsidized improved seeds and mineral fertilizers at recommended rates to farmers. Seeds, once they were identified, were purchased from local seed companies operating in the country or region. In some cases, they were donated by international seed companies, but only if they were the recommended varieties. Fertilizers were also purchased from dealers in the region, or received as donations from partners or through government input support programs in the case of Mwandama and Potou. The subsidy rates and how they were implemented also varied among sites; subsidies were initially high ranging from 50 to 100% of the market costs and then gradually decreased in the next 2–3 years with the expectation that farmers would eventually be able to purchase the inputs from credit, based on sales of their increased crop production. The MVP made contracts or distributed vouchers to each farmer stating the conditions of the subsidy. In most sites, farmers were required to pay back a percentage of their harvest in grain to the school meals program; in other sites, harvest payments went into community-run grain banks, where the crop was sold either to support the school meals program or to generate a revolving fund for purchasing seeds and fertilizers in subsequent years. All farming households were eligible to receive the subsidized inputs. The agricultural committees distributed the inputs to all farmers with oversight from agriculture extension officers and village facilitators. Each farmer signed a contract acknowledging the receipt of inputs, certifying that the inputs would be used on their fields, and committing to the partial inkind repayment, generally 100–300 kg of grain per household. The agriculture committees were also responsible for collecting the repayments. 3.2.9. Training Farmers were introduced to and trained in improved inputs and agronomic practices through a variety of methods throughout the cropping season. As a first step, discussions were held with agriculture extension officers to assess if they were up-to-date on information and recommendations on improved cultivars, fertilizer use, integrated soil fertility management, and other agricultural techniques; they were provided with refresher training and information sessions as needed. Farmer training sessions were initiated prior to the beginning of key activities. In these sessions, agricultural extension agents and MVP agriculture facilitators taught groups of about 100 farmers. The first sessions focused on land preparation, fertilizer placement, plant spacing, and specifics regarding improved seeds including their advantages over local seeds. Although the use of improved seeds was

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promoted, farmers were still encouraged to keep plots of their traditional seeds. Subsequent training sessions were conducted just before the start of major activities such as application of top-dressing fertilizers, harvesting, and postharvest management. Each of the training sessions consisted of a short lecture session, followed by practical activities that included land preparation and planting, visits to demonstration plots for best practices, farmer field schools, exchange visits between villages, and visits outside the project area to learn from successful interventions.

3.3. Data collection and analysis 3.3.1. Crop yields At the end of each growing season, yields were measured in a minimum of 30 households per village cluster in plots where improved germplasm and fertilizers were applied. The households were selected randomly from households that had been surveyed for the broader socioeconomic surveys (Sanchez et al., 2007) and represented the geographic and socioeconomic range of households for the sites. Yield estimations were made in 3–6 quadrants placed randomly in each plot, at least 3 m away from the borders. The quadrants size ranged from 9 to 25 m2, depending on the site. All plants in each of the quadrants were harvested, the fresh weights measured and subsamples of grain taken for dry weight measurements. Grain yields are expressed at 14% moisture content. A team of enumerators, members of the agriculture committee, and farmers participated in measuring the yields. Efforts were also made to collect yield data in randomly selected nonintervention plots to serve as controls. Ideally these controls would be located in villages neighboring the cluster, but this type of sampling was possible only in Mwandama and Koraro. In other clusters, it was difficult to obtain permission from farmers outside the MVP area to take yield estimates. In these sites, yield estimates for controls were taken from plots within the MVP area but where inputs were not applied. This type of sampling may underestimate or overestimate actual nonintervention controls. Underestimates of control yields would result if farmers selectively chose their better fields to apply the improved seed and fertilizer inputs and the plots where control yields were estimates were on poorer quality soils. Control yields would be overestimated within the MVP area because farmers had been exposed to training on improved agronomic practices and may have applied these practices to these plots, and therefore such controls do not accurately represent what farmers would have done if they were not participating in the project. Analyses of data were performed using Stata 10 (Hamilton, 2009). Yield data were analyzed by grouping them into four yield quartile groups. Quartiles refer to the 25th, 50th, or 75th percentiles of a frequency distribution divided into four parts, each containing a quarter of the sampled households. Quartile 1 represents the group with the lowest yields, and

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quartile 4 the highest yields, whereas quartile 2 and quartile 3 represent the middle groups between the 25th and 75th percentiles. For sites with bimodal rainfall pattern, only yields during the major season are reported. 3.3.2. Daily caloric requirements Minimum per person grain yields needed to meet basic caloric requirements were estimated by the amount of grain needed to provide 2100 calories per day per person (Latham, 1997). These requirements are equivalent to 219 kg of maize per person per year and 209 kg of teff per person for the case of Koraro. The annual crop production for a household to produce the targeted amount of grain was estimated based on the average number of people per household for each site (Table 2). The area required per household to produce that minimum amount of grain was then calculated based on the yields obtained in each quartile. 3.3.3. Value-to-cost ratios Increasing crop production in itself is important for addressing hunger; however, the ability of farmers to continue achieving such yields depends on the profitability of the crop and the farmers’ ability to save and reinvest in agricultural inputs or other income generating activities. In order to assess this potential, the value-to-cost ratios were calculated for the staple crops for each season and cluster. To make these calculations, prices were collected for: 

Costs of fertilizers and seeds for each cropping season at actual, not subsidized, local market prices.  Farm gate crop prices at harvest time, when prices are generally lowest.  Peak prices occurring later in the year, when the surplus crop was actually sold. Prices were collected in local currencies and converted to US dollars at the prevailing exchange rates. The unsubsidized input costs and the crop peak prices were used to calculate the value-to-cost ratio as a first indicator of acceptability of investment, using the following formula: V =C ¼

ðY  Yc Þ X

where Y ($) is the value of the crop in intervention plots, Yc ($) is the value of the crop harvested in control plots, and X ($) is the cost of inputs (seeds and fertilizers). The cost of producing each extra ton of maize above that produced in the control was also calculated.

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4. Results 4.1. Crop yields For all the Millennium Village clusters growing maize (Sauri, Bonsaaso, Mwandama, Pampaida, and Mbola), average maize yields overall were 4.4 t ha 1 ranging from 5.1 t ha 1 in Sauri to 3.5 t ha 1 in Pampaida (Table 4). Seasonal average maize yields per village cluster were at least 3.2 t ha 1. The initial MVP package of agricultural interventions resulted in at least a doubling of maize yields in Sauri, Mwandama, Mbola, and Pampaida, and teff yields in Koraro, when compared to preintervention yields. Maize yields in Bonsaaso, Ghana were not as responsive but the preintervention and control yields were relatively high. Yields compared to controls were not doubled in Sauri and Pampaida; for the case of Sauri, there are questions about the high control yields obtained based on other data on crop yields with low inputs from the area ( Jama and Kiwia, 2009; Nziguheba et al., 2002a) but for Pampaida, the reasons for relatively low maize yields are unclear. In contrast to the success in doubling yields for maize and teff, there was little improvement in millet yields in Tiby and Potou, and groundnut yields in Potou. Both of these village clusters are in the semiarid to arid zones where rainfall amounts and patterns often result in crop failures. 4.1.1. Interannual yield variation There were slight variations in yields between seasons within a cluster (Table 4, Fig. 2). The yield variations were due to a variety of climatic, cultural, and socioeconomic factors. In Sauri, the variations in maize yields in 2005 (Year 1), 2006, and 2008 are correlated with seasonal rainfall totals. But the lowest yields observed in 2007, the year with the highest seasonal rainfall, are perhaps due to a shift in the management of inputs distribution from the MVP to a local NGO and agro dealers. Some farmers could not readily access the inputs. Nevertheless, a village average of 4.4 t ha 1 is still above the target of 3 t ha 1. In Mbola, the lowest yields observed in the 2006/2007 (year 1) cropping season were linked to low quality of maize seeds used that season and replanting was required in most fields; but also in this first year of the MVP, farmers were reticent to adopt the improved agronomic practices. Many farmers refused to increase the plant density from their normal practices with a result that the population density was low, about half of the 45,000 plants ha 1 that was recommended. Farmers did realize that those who followed the recommendation had very good harvests and in the following season, 2007/2008 (Year 2), the majority of farmers followed the recommended practices. Coupled with good rainfall, this resulted in a bumper harvest, averaging the highest yields of all, 5.9 t ha 1 with all farmers

Table 4 Average grain yields at baseline (preintervention) and those measured during years of MVP implementation in intervention and nonintervention (Control) plots; and the total rainfall during the cropping seasons Village clusters

Intervention type

Yields (t ha 1)

Sauri Maize

Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm) Yield MVP (t ha 1) Yield control (t ha 1) Rainfall (mm)

Preintervention Year 1 4.9 (1.6)a 1.9 Ndb 734 729 4.2 (1.0) 2.2 2.3 (0.8) 615 753 5.2 (1.7) 0.8 2.2 (0.9) 780 1163 3.2 (0.4) 0.8 1.8 (0.5) 687 884 3.3 (1.0) 1.0 1.7 (0.5) 519 720 1.1 (0.5) 0.8 0.8 (0.5) 592 Nd 0.6 Nd 446 Nd Nd 0.5 Nd 350 278

Bonsaaso Maize Mwandama Maize Pampaida Maize Mbola Maize Tiby Millet Koraro Teff Potou Groundnut a b c

Numbers in parentheses are standard deviation. Not determined. To be determined.

Year 2 5.7 (1.6) 3.4 (1.0) 1097 3.8 (1.1) 2.6 (0.8) 647 4.0 (1.3) 1.6 (0.6) 450 3.7 (0.7) 2.0 (0.3) 863 5.9 (1.5) 0.9 (0.4) 758 1.6 (0.6) 1.4 (0.6) 437 1.4 (0.5) 0.6 (0.2) 515 0.8 (0.04) 0.6 (0.02) 217

Year 3 4.4 (1.5) 4.0 (0.9) 1111 5.4 (1.0) 3.6 (0.9) 731 4.3 (1.6) 1.6 (0.7) 992 3.5 (1.1) 2.5 (0.6) 972 4.1 (1.3) 1.9 (1.5) 561 1.2 (0.4) Nd 545 1.5 (0.5) 0.8 (0.3) 618 0.7 (0.02) 0.6 (0.01) 309

Year 4 5.2 (1.8) 2.7 (0.7) 918 Tbdc Tbd Tbd 4.7 (1.2) 1.5 (0.8) 961 Tbd Tbd Tbd Tbd Tbd Tbd Tbd Tbd Tbd 1.2 (0.4) 0.7 (0.3) 268 Tbd Tbd Tbd

Overall cluster average 5.1 3.4 4.5 2.8 4.5 1.8 3.5 2.1 4.4 1.3 1.4 1.1 1.4 0.7 0.8 0.6

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Bonsaaso n = 292

n = 288

n = 114

8 6 4 2 0 2005

2006 2007 Cropping season

Maize grain yield (t/ha)

Maize grain yield (t/ha)

Sauri n = 150

10

n = 179

n = 177

n = 65

8 6 4 2 0 2006

2007 2008 Cropping seasons

n = 56 n = 35

n = 48

6 4 2 0 2006

Maize grain yield (t/ha)

Maize grain yield (t/ha)

n = 146

8

2008

Mwandama 10

10

2007 2008 Cropping seasons Pampaida

10 8

n = 45 n = 30

6 4

n = 30

2 0

2009

2006

2007 2008 Cropping seasons

n = 148

n = 150

6 4 2 0 2007

Teff grain yield (t/ha)

n = 110 n = 109 n = 52

2006

4 3.5 3 2.5 2 1.5 1 .5 0

2007 Cropping seasons

2008

n = 60 n = 72 n = 42

2006

2008 2009 Cropping seasons Koraro

4 3.5 3 2.5 2 1.5 1 .5 0

Millet grain yield (t/ha)

10 8

Tiby

n = 137

Groundnut grain yield (t/ha)

Maize grain yield (t/ha)

Mbola

2007 2008 Cropping Seasons Potou

1 .95 .9 .85 .8 .75 .7 .65

n = 30 n = 30

2007 2008 Cropping seasons

Figure 2 Trend and distribution of grain yields obtained during various cropping seasons with MVP interventions in selected Millennium Villages clusters. Boxes indicate yield ranges in the 25–75% yield quartiles. Bars indicate the limit of the nonoutlier minimum and the nonoutlier maximum. n is the number of sampled plots per season.

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achieving more than 2 t ha 1 (Fig. 2). The decrease of yield in 2008/2009 (Year 3) cropping was due mainly to low seasonal rainfall but also to low adaptability of farmers to the switch from DAP fertilizer to Minjingu phosphate rock plus urea as the basal application. In Tiby, where millet was the first crop targeted, only a slight increase of 37% was observed compared to preintervention levels and control plots (Table 4). Due to the general low productivity of millet, its vulnerability to weather fluctuations, and the low cost of the millet seed, which farmers were able to pay on their own, farmers preferred to support higher value crops, such as irrigated rice and vegetables in subsequent seasons. Therefore, from 2008 (Year 3) onward, the support for millet was limited to agronomic management but not inputs and there was a 25% decrease in millet yields compared to yields in 2007 (Fig. 2). Although teff is a major staple crop grown by all households in Koraro, various other cereals are grown along with teff, and also benefited from the project interventions. For reason of simplicity, the discussion will focus on teff. The average teff yield in the year before intervention was similar to yields measured in the control villages during three consecutive years of intervention (Table 4). In 2006 (Year 2), teff yields doubled in intervention plots compared to yields in control villages. Yield variations in 2007 and 2008 follow rainfall patterns; in particular, in 2008, there was a long dry spell occurring during the cropping season, which was severe in some parts of the cluster. In Potou, long dry spells and many insects, including locust invasions that caused significant damage to millet characterized the first year of interventions. The poor rainfall during this season left farmers unmotivated to support millet. Farmers preferred to support groundnut and cowpea seeds because of their higher costs compared to millet seeds. As a result, the area under millet increased during the first year of intervention from 1186 to 1514 ha, and then decreased drastically to 659 ha in the 2008 cropping season. Groundnuts were supported in the second year of the project. Low yields of groundnuts with only 15–25% increases over the control yields, were obtained during the 2 years of input support (Table 4, Fig. 2) and were attributed to low rainfall in this marginal area. Despite these low improvements in yields, farmers value groundnuts as cash crop, and with project support, the area under groundnut increased from 3157 ha in 2005 (before project) to 4251 ha in 2008. Beside the grain, groundnut stover is utilized by farmers as livestock feed. 4.1.2. Household yield variation Though average maize yields doubled or even tripled across the sites compared to preintervention, there was considerable variation and range in yields among the farms within sites even though all households had access to the project inputs (Fig. 2). In general, 75% or more of the farm plots sampled had maize yields of 3 t ha 1 except for Mbola in 2007 and Pampaida in 2008.

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Most sites, however, also had a few households with yields below 2 t ha 1 in most seasons; such yields are similar to or even below the average yield from the control plots in those sites. Usually, less than 10% of the households had yields less than 2 t ha 1. On the other extreme, in all village clusters and all seasons, households in the highest quartile reached yields of 6 t ha 1, with the exception of Mbola in 2007 and Pampaida in any season. Yields in Pampaida never reached 6 t ha 1. There was also a large variation in teff yields range between seasons in Koraro. In 2006, 32% of sampled households had yields below 1 t ha 1. The value reduced to 17% in 2007 when yields in the second quartile were above 1 t ha 1, while they increased to 42% in 2008. The distribution of yields in quartiles 2 and 3 was wide in 2006 whereas it narrowed in 2008 when all yields in these quartiles were below 1.5 t ha 1 (Fig. 2). 4.1.3. Meeting caloric requirements For all maize growing sites, the annual quantity of maize required for a household to satisfy its caloric needs ranged between 0.9 and 1.3 t (Table 5). An indicator for measuring progress toward the hunger MDG is the percentage of the population below the minimum dietary energy intake level (Palma et al., 2009). Producing the basic caloric requirements for households was essentially not possible on the small farm sizes in Mwandama and Sauri (1.0 and 0.6 ha, respectively) at baseline yields (Table 2, Table 5). The farm size is big enough in the other sites growing maize, but in sites requiring more than 1 ha to produce the basic amount of maize, labor may become a constraint to production. The increased yields with project interventions reduced the area required to produce the basic caloric requirement to only 20–40% of that required at baseline yield levels. Even for farmers in the lowest quartile of yield production, average farm sizes were sufficient (Table 2, Table 5). The only situation for which insufficient maize would be produced with seed and fertilizer to meet this basic requirement is in the lowest farm size quartile in Sauri, which averaged only 0.14 ha. Households with such small farm size cannot meet the caloric needs even if they are able to produce the yields of the highest quartile. Such households, often headed by elderly widows have to depend on social safety nets. In Koraro, the amount of teff required for a household to satisfy its basic caloric needs was estimated to be 0.92 t. This would require an area of 1.5 ha. While the average farm size, 1.9 ha is sufficient to meet this requirement, many other crops are grown in Koraro. Project interventions reduced the required area to less than half using the average yields attained.

4.2. Value-to-cost ratios The investment in inputs proved to be profitable, provided the surplus yields were stored and sold when the value of the crop was at peak prices. Profitability is defined when the value-to-cost ratios are 2 or higher (Morris et al., 2007).

Table 5 Annual amount of maize or teff required for a household to meet the minimum caloric needs and the area required to produce that amount, calculated based on various level of crop production

Village clusters

Sauri Bonsaaso Mwandama Pampaida Mbola Koraro

Maize or teff needed to meet caloric requirement per household (t)

Area required to produce sufficient grains for household basic caloric requirement (ha)

1.2 1.1 0.9 1.3 1.2 0.9

Based on preintervention yields (Baseline) 0.6 0.5 1.1 1.6 1.2 1.5

Based on Average intervention yields 0.24 0.24 0.19 0.37 0.27 0.66

Based on the lowest yield quartile 0.4 0.4 0.3 0.5 0.4 1.2

Based on the highest yield quartile 0.17 0.20 0.13 0.29 0.20 0.47

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The cost of inputs rose slightly between the first year of the project and 2007 in all sites but escalated sharply in 2008 (corresponding to Year 4 in Sauri, Mwandama, and Koraro, and to Year 3 in others) following large hikes in food and fertilizer prices (ODI, 2008). For all sites, seed and fertilizer prices of the 2008 planting almost doubled. In Mbola, the price of DAP in 2008 rose to $1638 t 1 compared to $830 t 1 in 2007 and nearly quadrupled compared to the first season prices ($274 t 1). The decrease in the input costs in Mbola in Year 3 harvest was due to switch from the most expensive P fertilizer (DAP) to Minjingu phosphate rock, which was cheaper ($642 t 1) but has been proved to be an effective source of phosphorus (Szilas et al., 2008). In terms of profitability, the prices of maize and other crops also increased to partially offset the rise in fertilizer prices. For example, the price of maize in Sauri at harvest time rose from $120 t 1 in Year 1 to $154 t 1 in Year 2 and to $196 t 1 in Year 3. But in Year 3, the overall value of the harvested maize decreased compared to the Year 2 value because of lower yields in Year 3; this drop occurred even though the price of maize increased (Tables 4 and 6). Peak prices for the crop usually occurred 6–9 months after harvest, at the time when farmers are preparing for the following season. As expected, selling the product several months after harvest generated higher values than selling at harvest time. The magnitudes of the difference between low and peak prices varied between sites and seasons. For example, the value of the maize at peak price was at least double the value of harvest in Pampaida; whereas, only a slight increase of up to 45% was observed for maize in Bonsaaso and millet in Tiby. There was a general increase in the value of both the harvest and peak prices in 2008 compared to other seasons as a result of the general global hike in prices of food commodities observed during that year. A major challenge in selling surplus crop has been to find buyers for crops grown in remote areas, where markets and buyers are generally not organized. For example, in Koraro and Bonsaaso which are located far from large towns (Makelle and Kumasi, respectively), farmers were organized to sell their agriculture products in bulk and the project facilitated the acquisition of trucks to transport products to the markets; communities were trained to manage the trucks and after an initial period of subsidy, the trucks were to be maintained and run by the community. Various types of buyers were identified for the sites: Tiby sells all its cereals at the annual cereal fair in Segou, the nearby regional capital; Sauri and other clusters sell to local millers, and some are selling to the World Food Program’s Purchase for Progress project, where local foods are purchased for food aid in acutely hungry areas ( Jurry, 2008). The V/C ratios varied between sites and between seasons but were always higher for peak prices compared to harvest prices. The V/Cs at peak price were greater than 2 at all sites, except for millet in Tiby and groundnut in Potou and Year 3 in Sauri. For maize, the highest V/C was observed in Bonsaaso (Ghana) and was higher than 4 using both harvest and

Table 6

Input cost (seed and fertilizers), values of the harvest crop at harvest and peak prices, and the V/C ratios

MV site

Crop type

Category price

Values of harvested crop and cost of input ($ ha–1)

Sauri

Maize

Input costa Harvest Peak Cost per output ($ t 1)b Input cost Harvest Peak Cost per output ($ t 1) Input cost Harvest Peak Cost per output ($ t 1) Input cost Harvest Peak Cost per output ($ t 1) Input cost Harvest Peak Cost per output ($ t 1) Input cost Harvest

Year 1 138 589 1326 Ndc 82 1599 1599 43 155 351 629 52 253 487 3178 181 117 391 1005 73 127 145

Bonsaaso

Maize

Mwandama Maize

Pampaida

Mbola

Tiby

Maize

Maize

Millet

Year 2 139 879 1689 60 106 1447 1771 88 170 285 861 71 297 1805 4547 175 237 1143 2039 47 135 296

Year 3 195 857 1619 488 159 2917 4243 88 202 463 1214 75 487 1360 2720 387 225 744 1370 102 245 290

Year 4 285 1799 2270 144 Tbdd Tbd Tbd Tbd 341 797 1202 107 Tbd Tbd Tbd Tbd Tbd Tbd Tbd Tbd Tbd Tbd

V/C

Year 1 Year 2 Year 3 Year 4 Nd Nd

2.6 5.0

0.4 0.8

2.9 3.7

9.0 9.0

4.3 5.3

6.2 9.0

Tbd Tbd

1.3 2.3

1.0 3.1

1.4 3.7

1.6 2.4

0.8 5.5

2.8 7.2

0.8 1.6

Tbd Tbd

1.6 4.0

4.1 7.2

1.7 3.2

Tbd Tbd

0.3

0.3

Nd

Tbd (continued)

Table 6

MV site

Crop type

Koraro

Teff

Potou

a b c d

(continued) Category price

Peak Input cost Harvest Peak Groundnut Input cost Harvest Peak

Values of harvested crop and cost of input ($ ha–1)

169 Nd Nd Nd Nd Nd Nd

416 78 609 814 250 825 990

389 90 856 1663 215 771 1113

Tbd 155 1143 905 Tbd Tbd Tbd

The cost of inputs (fertilizers and seeds) was calculated based on the actual local market prices, not on subsidized prices. Represents the cost of producing an extra ton of maize over the control yields by using fertilizers and improved seeds. Not determined. To be determined.

V/C

0.4

0.5

Nd

Tbd

Nd Nd

4.5 6.0

4.4 8.2

3.1 2.5

Nd Nd

0.3 0.4

0.3 0.5

Tbd Tbd

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peak prices, and reached as high as 9 during peak prices. The input costs for Bonsaaso were lowest compared to other sites growing maize. The V/C was greater than 2 for two seasons in Sauri. The low V/C in Year 3 was due to high maize yields observed in the control plots, averaging 4 t ha 1; in V/C calculation no input costs were included in the controls, which led to high value of maize produced at zero cost. As mentioned previously, the control yields for Sauri in all seasons are considered as overestimates so the V/C ratios are also probably underestimates. The V/C in Mwandama at harvest prices were always below 2. Despite yields twice that of control plots, the prices of maize were extremely low postharvest, resulting in low value of maize compared to values in any other MV sites. Storing maize and selling it at peak prices resulted in V/Cs greater than 2 all years in Mwandama. A similar scenario was observed in Year 1 and Year 3 in Mbola, and in Year 1 in Pampaida. The use of inputs on millet in Tiby and groundnut in Potou had little effect on grain yields (Table 4) and resulted in unfavorable V/Cs of less than 1 (Table 6). As indicated earlier, input supports on millet were withdrawn in Tiby in 2008. In Potou, groundnut is an important cash crop for the rainfed zone and it was the top priority by the community for input support. Despite the low grain yields and low V/Cs, groundnut is viewed by the community as a very important crop because of its role as livestock feed. Groundnut stover yields are about twice that of grains, and are sold at a price of about 80% of that of the grains but V/Cs have not been calculated with the stover included as part of the sales. In Potou, millet and cowpea are viewed by the community as subsistence crops whereas groundnut and onions are produced for selling; thus the farmers would not invest on inputs for the subsistence crops but rather put them on onion which is the major cash crop. Onion yields have increased from an average of 20 to 30 t ha 1 due to project interventions, and the area under onion expanded from 800 ha in 2006 to 1595 ha in 2008. The marketing of onions has improved due to an organized structure in credit union and to the ban of onion import during the period from March to August. This has lead to increased price of onion from $145 t 1 in 2005 to $310 t 1 resulting in V/C ratios above 4 (data not shown). The income from onion and groundnut are used to purchase food in case of poor performance of millet and cowpea. Many African countries rely on imports to satisfy national food requirements. The cost of imported food is more than that for producing a similar amount within the country; stimulating local production and sourcing is a cheaper alternative to shipping food aid from the United States (estimated to $806 t 1 in 2008) as indicated by the cost of producing a ton of maize in our study (Table 6) (Sanchez et al., 2009; USAID, 2008). This alternative also can increase demand for local products and stimulate local agricultural development.

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4.3. Crop and enterprise diversification Crop diversification activities for the various village clusters started in the second year and now include off-season, or dry-season growing of vegetables (tomatoes, onions, cabbage, melons, and sweet corn) mostly on residual moisture in lowland areas or with drip irrigation; spices (chilies and ginger), and other rainfed crops (orange-fleshed sweet potatoes, tissuecultured banana, groundnuts, sunflower, soybean, and hibiscus (locally known as bissap in Potou)(Table 7)). Livestock activities include support for dairy cattle, dairy and meat goats, poultry, including artificial insemination and veterinary services. Other activities outside the farmed fields were also developed, such as honey, mushroom, and aquaculture production. Table 7 Selected diversification interventions for improving nutrition and income generation in various village clusters

Village name

Type of enterprise

OFSPa Dairy goat Chicken Bonsaaso Cowpea Citrus Mwandama Tomatoes OFSP Goats Pampaida Goats Soybean Rice Mbola OFSP Sunflower Chicken Tiby Vegetables Koraro Tomatoes Chilies Chicken Potou Onion Bissap (Hibiscus) Small ruminants Sauri

a b c

Number of household involved

Number of Area covered livestock heads (ha)

429 340 330 440 122 1,570 200 162 28 544 567 1,500 5,579 700 2,960 2,016 1,992 736 1,700 2,633

53 Nab Na 88 33 60 20 Na Na 300 450 155 2,232 Na 42 210 45

Na 390 4,800 Na Na Na Na 287 56 Na Na Na Na 765 Na 3,680 Na

1,549 399

Na Na

1,409c

Na

48,352

Orange-fleshed sweet potatoes. Not applicable. Interventions consist of veterinary services.

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5. Discussion and Way Forward The results presented constitute evidence-based information on how to get Africa out of its 1 t ha 1 yield trap and move the African Green Revolution forward. We discuss the implications in terms of crop production, incorporating organic nutrient inputs, improved human nutrition, crop and enterprise diversification, subsidies and credit, climate risk and management, irrigation, safety nets, and the value of the integrated multisectorial approach.

5.1. Crop production The initial successes of doubling maize yields and exceeding the overall “green revolution” yield target of 3 t ha 1 in the Millennium Villages confirm the importance of the four key simultaneous interventions; improved germplasm, subsidized mineral fertilizers, intensive training at the community level, which were recommended by the UN Millennium Project Hunger Task Force (UN Millennium Project, 2005b). In addition, planning ahead for the storage of bumper harvests, in order to sell the crop surpluses at peak prices was the crucial fourth point. The results are quick, evident with the first harvest, highly visible, and get communities involved in the project. 5.1.1. Fertilizers Currently, Africa has the lowest fertilizer use among all regions with an average of 8 kg ha 1 of nutrients despite a high prevalence of soils with poor soil fertility (Heisey et al., 2007; Thomson, 2008). Fertilizer application rates for cereals in the Millennium Villages shown in Table 3 averaged 73 kg N ha 1 and 18 kg P ha 1, respectively, resulted in profitable valueto-cost ratios, even when the market price of unsubsidized fertilizers and seeds was used and in spite of the sharp increase in prices experienced in 2008. The fundamental reason for that is that the nitrogen use efficiencies in Africa are in the order of 12–16 kg of maize per kilogram of nitrogen fertilizer applied (MDG Africa Steering Group, 2008). Some of the sources and rates of fertilizers used need to be revised after a better understanding of soil constraints at the different sites. For example, urea is currently used for top-dressing in Koraro, Ethiopia; but the topsoil pH is around 8.2 in some areas. In such circumstances, the urea would volatize and most of the nitrogen applied would be lost. Considering also the visual sulfur deficiency symptoms in maize (Ray Weil, personal communication) we have recommended that the Ethiopian Ministry of Agriculture shift its fertilizer imports from urea to ammonium sulfate for those extensive high pH areas. In Malawi, the standard recommendation is to apply NPS basal fertilizer but crop production is probably not limited by phosphorus in most

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of Malawi (Benson, 1999; Snapp, 1998). Others have found some soils to be less responsive to fertilizers than others (Vanlauwe et al., 2010) either because the sites are already fairly productive without fertilizer applications (as was the case here for Bonsaaso) or because some low productivity sites do not respond to fertilizer application, because of other overriding limiting factors such as compacted topsoils. The production of a digital map of soil properties currently undergoing in Africa at 90-m resolution will improve the effectiveness of fertilizer applications (Sanchez et al., 2009). 5.1.2. Improved germplasm Increasing fertilizer application rates alone is not sufficient for increasing yields and will not work unless high-yielding cultivars are used. Many improved high-yielding crop cultivars are available in Africa (Gabre-Madhin and Haggblade, 2004). However, adoption rates are much lower than other continents (Evenson and Gollin, 2001). Local seed companies are emerging in countries like Kenya where investments in the private sector have been encouraged (Ejeta, 2010). The Africa Seed Investment Fund initiated by the Alliance for the Green Revolution in Africa (AGRA) and African Agriculture Capital will invest in small to medium size seed companies in East and Southern Africa (www.agra-alliance.org). Once those seeds are available, there is need for distribution at local levels, again AGRA has a program directed toward strengthening the capacity of local agrodealers to deliver quality seed and fertilizer as well as technical information to farmers. 5.1.3. Extension services In order to be successful, access to fertilizers and seeds must be accompanied by proper agronomic practices. The role of extension services is therefore important in training farmers on improved agronomic practices such as early planting, correct sources, rates, placement, and timely application of fertilizers, appropriate plant spacing, weeding, integrated soil fertility management, harvest, and postharvest management. In the Millennium Villages, farmers were trained in groups of 100 or fewer by government agricultural extension officers, project agricultural facilitators, and master farmers. Such penetration is important for the wide-scale adoption of specific practices and thus increases in yields. Older farmers often commented that they used to know many of those practices, but forgot them due to the absence on such training for years. In much of Africa, government extension services have received little support, and their presence on the ground is either weak or nonexistent due to insufficient staff or lack of operational funds. The MVP empowered local extension agents with transport and new information, and many of them said they were proud to have the resources to practice their profession. The success in Malawi in the 1980s is attributed to the availability of subsidized inputs to farmers coupled with well-supported extension service active at community level (Sofranko and Fliegel, 1989); the same is

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true nowadays as Malawi became the first African Green Revolution country (Denning et al., 2009). 5.1.4. Planning ahead and selling at peak prices The Sasakawa Global 2000 experience in Ethiopia during the mid 1990s, where successes in using fertilizers, improved seed and extension produced similar yield increases to ours (Quin˜ones et al., 1997), but collapsed when no markets were found to sell the surpluses at an adequate price. Learning from this lesson, the Millennium Villages planned ahead for storage and sale of the expected crop surpluses when crop prices reached their peak value. Market prices are very low at harvest, when small-scale merchants offer to buy grain at minimum prices when farmers need money the most. The grain banks that were established, some using warehouse receipts, provided cash advances to the farmers and sold the surplus at peak prices usually 4–7 months after harvest. The data in Table 6 represent an average of 66% increase in prices when the surplus was sold at peak prices. Not only did farmers double or triple their grain yields but also sold their surplus at much higher prices. This picture, however, was not uniformly rosy. Yield increases in the drier sites of West Africa were small; millet in Tiby and Potou, and to a lesser extent groundnuts in Potou, a crop not adapted to the limited rainfall, all show unprofitable value-to-cost ratios. There have been no significant breakthroughs on millet yields in West Africa for decades and our experience sadly confirms this.

5.2. Organic inputs and soil management practices Readers must be wondering why we started with a mineral fertilizer strategy, while many of us have advocated the combined use of mineral and organic sources of nutrients (Nziguheba et al., 2002b; Palm et al., 1997; Sanchez, 2002; Sanchez et al., 1997; UN Millennium Project, 2005b). The primary main reason was the need to quickly reverse decades of soil nutrient depletion and have a quick impact. Second, the quality and amounts of organic inputs in many of the Millennium villages situations are insufficient as the sole sources of nutrients. Suggestions to begin with improved legume tree fallows were met with advice of the Sauri Agricultural Committee in early 2005 that improved fallows would take a year to develop, thus delaying a significant increase in yields for at least a year. Getting organics into these degraded farmlands is a challenge. Of the various types of organic resources produced under subsistence farming, crops residues, manure, and compost, none are produced in sufficient quantity and adequate quality to provide nutrients required for crop production (Palm et al., 1997; Palm et al., 2001). In addition, crop residues have often multiple uses (livestock feed, fuel for cooking, and fencing materials) that limit their use as soil amendments. With the doubling of crop yields,

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however, crop residue production also doubles, enabling farmers to use crop residues for soil management either directly or through compost and manure. The amounts and quality of animal manure is usually limiting, so it is likely to be a supplement, and a good one, particularly when point-placed. No sustainable farming relies solely on mineral fertilizers. Now that yields have increased and remain high, the current thrust is to bring the organics in with a priority to use nitrogen fixing trees or herbaceous legumes in situ, interplanting them into the maize crop and allowing it to grow during the dry season. This is to avoid the large transport cost of organic sources produced outside the field, which limits their use a supplement. Improved leguminous fallows are a well-documented practice, and can fix 50–100 kg N ha 1 per year, recycle nutrients leached to the subsoil particularly potassium, as well as carbon, control weeds, and in the case of trees provide firewood. But after initial adoption most farmers abandon the practice (Franzel et al., 2002), while a small proportion—the best farmers—thrive on it. We feel the main reason for abandonment is the opportunity cost incurred when land is not used for growing a short rains crop in bimodal systems, or even sacrificing a full rainy season crop in unimodal systems to allow the trees to grow. Financial incentives just like fertilizer subsidies are needed; we intend to develop such incentives for the village clusters that are not in the semiarid or arid tropics. Grain legumes are also being promoted and financed, as sound crop rotation. But beans, soybeans, and groundnuts take most of their fixed nitrogen away in the grain, leaving little for the subsequent maize crop. Grain legumes in Malawi are estimated to add about 30 kg N ha 1 to the subsequent crop (MDG Africa Steering Group, 2008), a very desirable amount, but not sufficient to replace mineral nitrogen applications. Organic inputs are important for building soil organic matter and improving physical and biochemical properties of soil leading to improved fertilizer use efficiency, soil quality, and to sustainable crop production but they can be also a valuable source of nutrients, particularly N, thus reducing the quantity of fertilizers requirement (Alley and Vanlauwe, 2009; Place et al., 2003). N fixing trees for improved fallows or cover crops are particularly important sources of N to complement fertilizers and they also produce large quantity of biomass for soil organic matter building. Yields obtained through improve fallows or cover crops are 60–80% higher than yields without fertilizers but are significantly lower than those obtained with mineral fertilizers (Sileshi et al., 2008). As fertilizer subsidies are reduced or removed and fertilizer prices remain high, farmers have been trained in and supported in different practices to increase the use of these high quality organic inputs. Despite the promising yields and money saved in the reduced amount of N fertilizers that are required, adoption by farmers in the Millenniun Villages have been fairly low both in the number of farmers and the size of land they put under these soil management practices. Small land sizes, labor requirements, and the time and land need to produce

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improved tree fallows have been cited as factors hindering adoption (Keil et al., 2005; Kiptot et al., 2007). Evaluations of the process of adoption and factors that may influence increased adoption are underway in the MV sites where these practices are being promoted. We have also not included yet minimum tillage practices, due to insufficient research evidence (Giller et al., 2009). We know this is not possible in structurally insert sandy Alfisols of West Africa like those of Tiby, but there is potential in other village clusters with loamy to clayey Alfisols and Oxisols.

5.3. Improved nutrition An indicator for measuring progress toward the MDG of halving the percentage of people suffering from hunger is the percentage of the population below the minimum dietary energy intake (Palma et al., 2009). When maize yields surpassed the 3 t ha 1 mark (or equivalent in other crops) in 78% of the village households, the minimum annual energy requirements were achieved and usually exceeded. But meeting household minimum caloric requirements is insufficient in itself to reduce malnutrition (Barrett, 2010). It is the first step in the integrated approach to alleviate hunger and malnutrition in the Millennium Villages. Our nutrition strategy includes an emphasis on food-based models that enhance the security and quality of the diet through local production, processing and storage of foods, the promotion of agricultural biodiversity, complemented by community education and development. Such strategy often falls outside the traditional scope of clinical nutrition intervention like nutritional supplementation (Fanzo et al., 2010). Diets in many rural areas of Africa are limited not only by the amounts consumed but are often based on a staple cereal or root crop with high energy content but low nutritional quality. A major emphasis in the Millennium Villages sites is to support agricultural diversity to include nutritious crops; such as the many African leafy green vegetables, which have been disappearing from farms and diets (National Research Council, 2006), and other nutritious crops such as orange-fleshed sweet potato, fruits, and livestock both at home and in the school feeding school programs (Table 7). Improving nutrition also is a cultural matter and involves changes in food habits particularly if the crops promoted are new to the communities. Educational materials and training sessions with farmers, particularly women, on the importance of nutrition, the nutritious value of various foods, and means of preparing foods are key components of the agricultural diversification and nutrition strategy. Preliminary results from Sauri after just 3 years of the integrated nutrition strategy already show a reduction in chronic malnutrition, measured as underweight (low weight for age) children under 2 years of age from 19% to 6% and stunting (low height for age) from 73% to 35% after 3 years of

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interventions (Fanzo et al., 2010). One supplement that is absolutely necessary is iodized salt to combat iodine deficiency, which is unfortunately prevalent in areas away from the oceans.

5.4. Diversification, primarily with irrigation Nobody is likely to escape the one-dollar-per-day absolute poverty trap by growing maize on half or one hectare no matter how high the yield. The way forward is crop and enterprise diversification. Diversification to high-value crops depends first on the markets, determined through a market survey and analysis. Efforts to expand the scale and efficiency of these activities involve capacity development in aspects of market access such as price variations, produce quality, group selling, and record keeping; and linking farmers to microfinance institutions for saving and microcredit access such as Equity Bank in Sauri, Opportunity International mobile banks in Mwandama, and the Mutuelle d’Epargne et de Cre´dit in Potou. Each of these institutions provides basic services like credit and saving accounts to villagers. Most of the high-value crops being promoted in the villages require some form of irrigation. In most sites, farmers were using water from wells or streams and irrigating with buckets. The project has promoted expansion of water sources through rainwater harvesting in small farm ponds, smallscale dams and water diversion in small channels. Pumps and drip irrigation systems have been introduced. The location of Potou in the coastal zone, and of Tiby on the Niger River has enabled the production of high-value irrigated vegetable crops that play a major role in providing a safety net in the event of food shortages due to crop reductions and failures. In addition to water for irrigation of cash crops, there is a need to find ways to provide water to get staple crops through critical dry spells and avoid crop failures. Water harvesting at the landscape level, which recharges ground water and shallow wells, is also used to fill mini dams and storage ponds in Koraro. This practice should be extended to other village clusters that are likely to experience severe dry spells.

5.5. Subsidies and the transition to credit Subsidies programs have been used in Africa with mixed results. A primary concern has been the disproportionate benefits received by the larger and relatively better-off farmers, even when the target was for poor farmers (Akinola, 1987; Minde et al., 2008). Implementation procedures and the ability to manage subsidies are critical for the success and impact of subsidy programs (Minde et al., 2008). Recently, the concept of smart subsidies has emerged to try and overcome some of the problems. Minde and Ndlovu, (2007) describe “smart” subsidies as those that target farmers who would not

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normally use purchased inputs, or target areas where fertilizer would have larger impacts on yields; in addition those programs should be results oriented and have a time frame of implementation. The Millennium Villages subsidy program followed most of the conditions set forth above as follows: (i) targeted poor communities who were using little or no fertilizers and improved seed; (ii) took place in areas with depleted soils where response to inputs is generally high; (iii) included mostly small farm areas, generally up to 1 acre (0.4 ha), which would not attract large-scale farmers; (iv) involved village agriculture committees in the distribution of inputs to limit the leakage to those not targeted; (v) increased production of major crops, with the first goal of reducing hunger; and (vi) progressively reduced the subsidy during the 5 years of the project. The subsidy program was not without leakage and selling to farmers outside the intervention area, some elite capture or preference to male farmers, but overall increase in yields throughout the clusters indicated that most farmers were receiving the inputs and using them on their staple crops. Eventually, the aim is to have national subsidy programs operating in Africa to provide small holder farmers with access to inputs; most notably is the national input support program of Malawi (Denning et al., 2009) but currently only a few countries included in this review have input subsidy programs. As a consequence, alternative solutions were developed to provide continued access to inputs; these alternatives ranges from loans through financial institutions to revolving funds set up through community-run cereal banks. Farmers paid back loans or subsidies in cash, in-kind with grain, or a combination, again varying from site to site. The major challenges for the transition from input subsidies were: (i) the lack of financial institutions willing to administer credit to poor farmers; (ii) the lack of sufficient capacity or financial capital of local microfinance institutions to provide or manage loans and collect repayment; and (iii) the existence of vulnerable groups that cannot or will not take out loans.

5.6. Safety nets For the vulnerable groups mentioned above, comprising perhaps 10–20% of the households, there is need to identify them, the characteristics that make them vulnerable, and provide means of supporting them. For those that are still capable of farming, direct subsidies could be targeted for agricultural practices appropriate for these groups. For example, in Sauri, widows farming extremely small plots of land have requested support for starting poultry production. Cash transfers or permanent subsidies are likely to be needed for the poorest and most vulnerable in the communities. Food for Work is an example of such support programs. The Koraro village cluster in Ethiopia participates in the MERET program of the World Food Program

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(WFP) and the Ethiopian government, in which food-insecure communities are provided with food for payment on work in environmental rehabilitation projects. The environmental rehabilitation often also results in improved water capture and management. The MV project is exploring such collaborative efforts in other sites.

5.7. Adaptation to climate change Unlike the Green Revolution in Asia which centered on irrigated crops, the African Green Revolution must deal with the challenges of rainfed agriculture to be successful (Binswanger-MKhize and McCalla, 2010; Thomson, 2008). Six out of the eight sites presented in this chapter produce their staple crops exclusively from rainfed agriculture. Even in the two sites where irrigation is practiced, Tiby in Mali and Potou in Senegal, the major subsistence crops (millet, groundnuts) are rainfed. This represents the situation in most of Africa where 96% of agriculture is rainfed (Hazell and Wood, 2008). Yield reductions due to low or erratic rainfall is one of the main reasons for low crop production in sites located in semiarid to arid zones, Tiby, Koraro, and Potou. In addition to inter and intra annual variability in rainfall that determines crop yields, climate change is predicted to impact livelihoods the most in the tropics and subtropics, particularly in Africa, where many poor, smallholder farmers depend on agriculture and have few alternatives for adaptation (IPCC, 2007; Thornton et al., 2009). Developing climate risk management strategies is crucial to the longer term success of the Millennium Villages and the African Green Revolution, where the investments and savings accrued through improved crop production and diversification can be wiped out with two successive crop failures. Strategies being piloted in some village clusters include use of seasonal climate forecasting probabilities to better inform selection of crop varieties and crop management and rainfall/crop insurance programs (Hellmuth et al., 2009), and Food for Work programs. Crop or drought insurance programs are being tested in Africa for climate risk management. The MVP partnered with the International Research Institute for Climate and Society (IRI) and the reinsurance company Swiss Re to develop an index insurance scheme based on NDVI satellite data and local rainfall data (Hellmuth et al., 2009). The index insurance was developed primarily to explore ways to insure the development goals of the project but could perhaps be more widely adapted to individual insurance programs using lessons from projects in Ethiopia (World Food Program, 2007) and Malawi (Hess and Syroka, 2005; Osgood et al., 2008). This is work in progress. A strategy for coping with climate variability and change is to utilize the existing rainfall more efficiently as has been illustrated by Rockstro¨m (2003). He showed that at cereal yields of 1 t ha 1 almost two-thirds of

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the water vapor flow is soil evaporation and one-third transpiration; but for yields of 3 t ha 1 and above, when the crop canopy closes, two-thirds of the vapor flow is through transpiration and one-third through evaporation. Basically, this suggests that increasing yields in SSA from 1 to 3 t ha 1 can be done without increase in water, just better management to assure more of the water moves through transpiration rather than evaporation. Researchers at the International Crops Research Institute for Semiarid Tropics (ICRISAT) confirmed this assumption by modeling 50 years of seasonal rainfall records in a semiarid area, Bulawayo, Zimbabwe (Cooper et al., 2009). With low nitrogen applications, maize yields varied from 0 (a crop failure during the well-known El Nin˜o drought of 1992) to a maximum of 1.6 t ha 1, with an overall mean of 0.86 t ha 1. When recommended nitrogen applications (52 kg N ha 1) are used, average yields increased to 2.75 t ha 1, with a range from 0 to 3.8 t ha 1, including three widely spaced crop failures in 50 years. Overcoming nitrogen deficiency made a quantum leap in overall yields in spite of seasonal rainfall variability, tripling them from the SSA average of less than 1 t ha 1 to almost 3 t ha 1, the target of the African Green Revolution.

6. Conclusions The results presented here demonstrate that the initial interventions of the African Green Revolution, access to subsidized fertilizer, improved crop germplasm adapted to local conditions, and field-based extension services, are able to quickly and dramatically increase maize yields to 3 t ha 1 and above to a large number of farmers. Doubling of teff yields were also realized in Ethiopia. These successes were not realized with millet and groundnut yields in the semiarid zones of West Africa. An increase in staple crop production is only a first step in reducing hunger; but to address wider food and nutritional security and poverty reduction, other steps are necessary. The increased harvests achieved in the MVP sites were potentially sufficient to meet basic caloric requirements of the Millennium Villages community but in order to address undernutrition or hidden hunger of protein and micronutrient deficiencies, these harvests of staple crops must be accompanied by an integrated nutrition strategy that includes nutritional diversity, either through agricultural diversification or the ability to purchase foods through higher incomes, and safety nets for vulnerable groups. The investments in seeds and fertilizers were profitable for farmers if surplus harvests were stored and sold later in the off-season at peak prices. With small farm sizes the surpluses would be generally small and insufficient to reduce poverty significantly. A transition from staple crops to cash crops is essential to realize substantial profits but requires appropriate market studies to

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identify the better options for farmers. Farmers must also be trained in the new crop technologies with an additional focus on product quality and they must often be organized into producers groups that can negotiate higher prices and linkages to buyers. Investments in small-scale water management and irrigation become important for production of high-value crops but financial institutions that provide loans and savings for agricultural investments are an essential element that is currently lacking throughout most of rural SSA as is a reliable network of certified agro input dealers. In the end, improving agriculture in itself is unlikely to get rural communities in SSA out of poverty. The ability to produce sufficient food is diminished if people are suffering from malaria, HIV/AIDS, or neglected tropical diseases. The ability to enter market-based economies is hampered by lack of education. The synergies between reducing hunger and controlling diseases, between school meals provided from surplus harvests and increased learning, are all too evident. The challenge remains to overcome our sector barriers and to think and act in a multisectorial way if the overall goals of the African Green Revolution and the MDGs are to be attained.

ACKNOWLEDGMENTS The authors gratefully acknowledge the financial and in-kind support provided for the actual work by the Millennium Villages Project, Open Society Institute, Governments of countries in which the MVs are located, Government of Ireland, Lenfest Foundation, Sara McCune, Yara Foundation, the Bill and Melinda Gates Foundation, the Government of Japan through the United Nations Develoment Programme’s Human Security Trust Fund, Millennium Promise Alliance, United Nations Development Program, and the Earth Institute at Columbia University. Partnerships, enthusiasm, and contributions of farmers, agriculture committees, and extension agents are what makes this happen in the end.

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C H A P T E R

F O U R

Interactions Among Agricultural Production and Other Ecosystem Services Delivered from European Temperate Grassland Systems Emma S. Pilgrim,* Christopher J. A. Macleod,* Martin S. A. Blackwell,* Roland Bol,* David V. Hogan,† David R. Chadwick,* Laura Cardenas,* Tom H. Misselbrook,* Philip M. Haygarth,‡ Richard E. Brazier,§ Phil Hobbs,* Chris Hodgson,* Steve Jarvis,} Jennifer Dungait,* Phil J. Murray,* and Les G. Firbank* Contents 118 119 119 122 122 125 128 128 135 141 141 143 144 144

1. Introduction 2. Methods 2.1. Describing the Ecosystem Services 2.2. Literature search 3. Interpreting the Interactions 3.1. Negative relationships 3.2. No direct relationship 3.3. Positive relationships 3.4. Inconsistent relationships 3.5. No current evidence of a direct relationship 4. Conclusions 5. Future Perspectives Acknowledgments References

* Rothamsted Research, North Wyke, Okehampton, United Kingdom { Environmental consultant, Exeter, United Kingdom { Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom } School of Geography, University of Exeter, Exeter, United Kingdom } European Journal of Soil Science, Peninsula Partnership for the Rural Environment, Centre for Rural Policy Research, University of Exeter, Exeter, United Kingdom Advances in Agronomy, Volume 109 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)09004-8

#

2010 Elsevier Inc. All rights reserved.

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Abstract Global demand for food is increasing as is the recognition that this must be achieved with minimal negative impacts on the environment or other ecosystem services (ESs). Here we develop an understanding of the relationships among ESs delivered within temperate agricultural grassland systems in lowland Europe. We reviewed the refereed literature on pair-wise interactions between nine different ESs. These were agricultural production, climate regulation, air quality regulation, water quality regulation, hydrological regulation, soil erosion regulation, nutrient cycling, biodiversity conservation, and landscape quality. For each pair, we sought information on how each ES responds to changes in the other. Each interaction was assigned to one of five categories: (i) no direct relationship between the driving ES on the responding ES, (ii) the driving ES has a negative impact on the responding ES, (iii) the driving ES has a positive impact on the responding ES, (iv) the evidence of direction of effect is inconclusive, because of either inadequate information or contradictions in the literature, and (v) there is no current evidence in the current literature for a relationship. Negative relationships resulted only from the effects of increasing the intensity of agricultural production on other ESs. Available evidence infers that erosion regulation and good nutrient cycling were the only two driving ESs shown to enhance agricultural production implying that their protection will enhance our ability to meet future food needs. In order for agriculture to become more sustainable, we need to develop agricultural methods that can minimize the negative impacts of these win–lose relationships.

1. Introduction Agricultural land is one of the largest terrestrial biomes on the planet (Foley et al., 2005), and it is expected to expand over the next decade, driven by an increased demand for both food and bio energy (Steinfeld and Wassenaar, 2007). These pressures almost certainly have to involve bringing new areas of land into production and increasing outputs per unit area on existing managed land. Historically, both strategies have reduced the provision of other ecosystem goods and services that are also important to human well-being (MA, 2005a,b; McIntyre et al., 2009) with the priority given to meeting contemporary human needs at the expense of future requirements; a cycle of demise that has been linked to the collapse of early civilizations (Balmford and Bond, 2005; Montgomery, 2008). It is essential that we learn from this experience, so these conflicts and trade-offs can be managed more effectively (Foley et al., 2005). The relationships between agriculture and individual Ecosystem Services (ESs) have been widely assessed (e.g., FAO, 2006, 2008; Hooper et al., 2005). However, the ESs are not independent from each other. Subsequently where our knowledge of them is incorrect or incomplete, there could be many

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unintended consequences if we manage an area of land for one ES without accounting for these relationships (MA, 2005a,b). Improving our understanding of these interactions will reduce the risk of producing negative trade-offs, squandering potential win–win scenarios and possibly experiencing dramatic and unexpected changes in the provision of ESs (Bennett et al., 2009). Agricultural systems, which cover between 28% and 37% of the earth’s land surface (Porter et al., 2009), provide the best opportunity for increasing global ESs. However, this will be achieved only if we set “appropriate” goals for agriculture- and land-management regimes favoring ES provision (Porter et al., 2009). A more systems-based approach could be used to assess the sustainability of agricultural grasslands (Gibon, 2004) as these systems are judged to be particularly environmentally damaging compared with arable crops (FAO, 2006), for example, through elevated greenhouse gas (GHG) emissions (Dobbie and Smith, 2003), ammonia (NH3) production from livestock waste (Bouwman et al., 1997), and an enhanced risk of phosphorus (P) losses (Bilotta and Brazier, 2008; Bilotta et al., 2008; Haygarth et al., 2006) from livestock compacted/poached/pugged fields. Here, we review the refereed literature to examine the pair-wise interactions between different ESs from a single agricultural system, addressing both positive and negative affects (Pretty et al., 2000). Only direct interactions are included for the sake of simplicity. We describe both the nature of the interactions and the strength of the evidence from published research. We focus on existing lowland intensively farmed temperate grasslands, defined as agricultural landscapes, characterized by high stocking densities (i.e., high number of animals per unit area) and high inputs of both chemical (e.g., fertilizers, pesticides, and imported animal feeds) and energy (e.g., farm machinery, and tractors) resources; in which there are a network of hedgerows and ditches. We do not include the impact of land-use change, that is, conversion of grassland to forestry or arable crops and for simplicity we do not assess mixed farming systems. We only include arable crops to compare the advantages of using a grassland for bioenergy production with planting bioenergy crops. We do not explicitly define factors such as stocking density, or fertilizer rates, as we are seeking general trends in the interactions between two selected ESs. Nor do we address the monetary valuation, the intrinsic environmental or social importance of these ESs.

2. Methods 2.1. Describing the Ecosystem Services The Millennium Ecosystem Assessment (MA) defines an ES as “the benefits people obtain from ecosystems,” (MA, 2003). We used the MA categories as the basis to identify ESs delivered from agricultural grasslands: agricultural

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production, climate regulation, air quality regulation, water quality regulation, hydrological regulation, soil erosion regulation, nutrient cycling, biodiversity conservation, and landscape quality. While we acknowledge that human health is dependent on food quality and availability, we exclude health benefits arising from food consumption and focus explicitly on risks to human health arising from the management of the grassland ecosystem, for example, increased quantities of human pathogens in drinking water. 2.1.1. Agricultural production Agricultural production is defined as the extraction of biological products and services from ecosystems that are innovated and managed by people (following McIntyre et al., 2009). This ES contains all of the provisioning services described in the MA (2005a,b), that is, food (meat and milk), fiber, fuel, etc. With regard to energy, we focus on bioenergy production comparing biocrops (e.g., Miscanthus, Panicum virgatum (switch-grass)) with biogas derived from anaerobic digestion of plant material or livestock wastes. 2.1.2. Climate regulation GHG concentrations in the atmosphere are key factors in regulating climate. The greenhouse effect is produced due to the absorption by certain gases of long-wave radiation emitted by the earth surface. Part of the solar radiation that is absorbed by the earth is reemitted in the form of long-wave infrared radiation. GHGs absorb part of this radiation stopping the heat to escape to space, enhancing the Greenhouse effect. Different land uses affect emissions of GHGs which include: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), ozone (O3), and chlorofluorocarbons, for example, sulfur hexafluoride (SF6), in different ways (FAO, 2006). Once emitted, some gases persist in the atmosphere for a long time, for example, N2O > 100 years (IPCC, 2001) and have a much larger capacity to adsorb radiation than CO2. 2.1.3. Air quality Agricultural grassland systems affect the concentrations of many atmospheric pollutants (e.g., NH3, O3, aerosols, and dust) and consequently they can act as both sources and sinks for them. These contaminants undergo complex atmospheric reactions, simultaneously affecting several aspects of air quality which are either beneficial (e.g., supplying an additional source of nutrients, provided that this is accounted for in nutrient management) or deleterious (e.g., increasing N2O emissions, which will have a negative impact on climate regulation). 2.1.4. Water quality Historically, regulations have focused on chemical determinants, though now the quality of open waters is assessed by using both ecological and chemical methods (Dodkins et al., 2005). In grassland-dominated systems

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water quality is affected by the loss of nutrients primarily, nitrogen (N) and P in addition to carbon (C), sediment and pathogenic organisms from land-based activities to surface and ground waters. The transferral of these pollutants from the land to the water typically follows a mobilizationtransport-delivery continuum (Haygarth and Sharpley, 2000), but it should be noted that it can occur from both diffuse (from the managed land) and point (from Sewage Treatment Works or farmyard hardstandings) sources. 2.1.5. Hydrological regulation Changes in land management can influence the water cycle by changing: hydrological flow paths and rates, storage capacity in the soil, aquifer interactions, as well as plant uptake, storage, and release (MA, 2005a). 2.1.6. Nutrient cycling Nutrients (e.g., N, P, and potassium (K)) move within and between the various biotic and/or abiotic components of the environment. These chemicals can be extracted from their mineral or atmospheric sources or recycled by conversion from organic to ionic form, enabling uptake by biota and ultimate return to the atmosphere or soil (MA, 2005a). 2.1.7. Soil erosion regulation Soil erosion potential and rates are influenced by soil type and structure, landscape morphology, vegetation cover, land management, and weather (i.e., exposure to wind and rainfall). Water-driven soil erosion is an important loss process in temperate grassland systems (Bilotta et al., 2007) as it is across the United Kingdom (Brazier, 2004). 2.1.8. Biodiversity conservation Here we specifically address terrestrial and freshwater aquatic ecosystems and the ecological complexes that they are part of. Most of the research is at the whole organism or at the assemblage level, though the diversity of genes, populations, and species underlies all grassland ecosystem processes (MA, 2005a). 2.1.9. Landscape quality A landscape is an area, perceived by people, the character of which is the result of the action and interaction of natural and/or human factors (HainesYoung et al., 2003). The quality of a specific landscape is a formulation of the aspirations of the public with regard to the landscape features of their surroundings (Council of Europe, 2000) and is therefore a subjective concept or variable.

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2.2. Literature search We sought refereed publications that give evidence on each pair-wise combination of ESs in the context of grazed temperate agricultural grasslands. We used each individual ES and key attributes attached to it as keywords in our literature search (e.g., biodiversity and agriculture), focusing initially on literature reviews to identify key references. We assigned each pair to one of five possible categories of interaction (Fig. 1) to illustrate the influence of one ES on another: i. ii. iii. iv.

no direct relationship between the driving ES and the responding ES the driving ES has a negative impact on the responding ES the driving ES has a positive impact on the responding ES the evidence of the direction of effect is inconclusive, because of either inadequate information or contradictions in the literature, that is, there is evidence of both positive and negative effects v. we believe (based on our expert opinion) that there may be a relationship though no evidence exists in the current literature.

We provide different levels of our confidence in the evidence based on our own judgment of effects described in the literature:



High confidence: Evidence points toward a clearly defined outcome Mixed confidence: Evidence is either less defined or contradictory (i.e., one paper may state a positive interaction while another might suggest the relationship is negative) or both. There may also be less evidence available;
Poor confidence: Very little evidence available. Many management actions affect more than one ES simultaneously at both temporal and spatial scales. Every effort was made to ensure that all the ESs were assessed at the same physical scale, that is, field and landscape, though this was not always possible since scale was not treated consistently in the literature. Where this occurred, we lowered our level of confidence, for example, from mixed to poor confidence.

3. Interpreting the Interactions Of the 72 pair-wise interactions studied, 37 were positive, 21 were inconclusive, and only six were clearly negative. Furthermore, there were only four total gaps in the evidence base and four cases where we believe there is no direct relationship between the ESs (Fig. 2). We next describe these interactions.

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B Ecosystem service B

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Figure 1 Graphs to illustrate the five different types of responses of ecosystem service B (ES B) to ecosystem service A (ES A) driving the interaction: (A) no direct relationship, for example, good water quality regulation has no direct effect on erosion regulation, (B) a decline in ES B, for example, high agricultural production is associated with a decline in biodiversity, (C) an increase in ES B, for example, good erosion regulation has a positive effect on agricultural production, (D) the relationship between ES A and ES B is inconsistent or inconclusive, for example, good air quality regulation has an inconsistent/inconclusive effect on climate regulation, (F) No current evidence in the literature of an interaction between ESA and ESB, for example, currently there is no evidence for that high levels of biodiversity influence air quality regulation.

Responding ecosystem service B

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Figure 2 The relationship between the ecosystem service A (ES A) driving the change and the response of the ecosystem service B (ES B) to this change. Arrows reflect the shape of the graph as shown in Fig. 1: 0 ¼ no direct relationship, # ¼ decline in ES B, " ¼ an increase in ES B, l ¼ evidence of the relationship between ES A and B is divided or inconclusive, $ ¼ no current evidence in the literature of an interaction between ES A and B. The strength of the relationship between ecosystem A and B is reflected in the number of stars *** ¼ highly confident about evidence, ** ¼ mixed confidence about evidence, * ¼ poor confidence in evidence. Cell color reflects scenario type: light grey: win– win, dark grey: lose–lose and bordered cell: variable outcome. For example, we are highly confident that increasing agricultural production in intensively managed grasslands causes a decline in air quality due to the production of, for example, ammonia (NH3) and non-methane volatile organic compounds (NMVOC). This is a win–lose scenario as we increase food production at the expense of air quality which has human health implications.

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3.1. Negative relationships The negative relationships, or win–lose scenarios, all arose from the effects of agricultural production as a driving force on the delivery of other ESs, with consistent negative impacts on air quality, water quality, erosion regulation, nutrient cycling, biodiversity conservation, and landscape quality. We are highly confident that increasing agricultural production in intensively managed grasslands causes a decline in air quality. Intensive agricultural production can reduce air quality in a number of ways. First, agriculture is the major source of NH3 emissions to the atmosphere (Bouwman et al., 1997), derived predominantly from the breakdown of urea excreted by livestock, particularly cattle in Europe (Misselbrook et al., 2000) so strategies to reduce this will affect agricultural grassland management (Webb et al., 2005). Ammonia further reduces air quality by combining with sulphates (SO42) and nitrates (NO3), to form secondary particulates (Erisman and Schaap, 2004). These, together with dust derived from livestock enterprises (MA, 2005a), and agriculturally derived gases, for example, chlorofluorocarbons, NOx, and sulphur dioxides (SO2) which dissolve in air moisture to form acids and oxidants (FAO, 2006) can cause human respiratory problems. These human health issues can be far reaching as winds can carry these airborne compounds far from their source, particularly if the compounds have a long life span (FAO, 2006). Second, manures can release high levels of hydrogen sulfide (H2SO4) and other toxic gases (Tilman et al., 2002) as well as being an important, and perhaps underestimated, source of non-methane volatile organic compounds (NMVOC) to the atmosphere (Hobbs et al., 2004), which are precursors of tropospheric O3 (Dentener et al., 2006). Enhanced levels of ground level O3 are associated with increased plant damage and direct crop loss (Crutzen, 1988; The Royal Society, 2008) which will have a negative impact on agricultural production. A benefit of intensive diary farming in the developed world is the excretion, by cows of excess sulfur they are fed in their breath, particularly during lactation. This creates a small, yet potentially important, amount of dimethyl sulfide (DMS) (Hobbs and Mottram, 2000), a chemical involved in cloud formation and therefore radiative forcing. Thus, this livestock DMS could potentially counter the GHG effect of ruminant CH4 (Hobbs and Mottram, 2000), though this positive affect is likely to be very limited. We are highly confident that increased agricultural production causes a reduction in water quality and this is a well-known trade-off (Carpenter et al., 1998). From a European perspective, diffuse pollution from intensive agriculture is the biggest threat to recreational waters caused by contaminated run-off water containing nutrients (Hawkins and Scholefield, 1996; Hooda et al., 2000; McTiernan et al., 2001; Scholefield et al., 1993), slurries, and manures containing faecal indicator organisms (FIO) (Oliver et al., 2005) as well as

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antibiotics and sediments from eroded pastures (FAO, 2006). These can all contribute to human health problems (Fewtrell et al., 2005) such as the emergence of antibiotic resistance (McIntyre et al., 2009). We are highly confident that increased agricultural production has a negative impact on erosion regulation. Soil compaction was thought to be the most important factor affecting grassland soils though Bilotta et al. (2007) highlight the need for a greater understanding of the factors affecting soil erosion regulation in intensively managed temperate grasslands. Generally an eroded soil will have less structure and fewer nutrients reducing its ability to support an arable or grass crop without the addition of artificial fertilizers. Though soil erosion is a natural process, it can be exacerbated by anthropogenic activities such as modern agricultural methods. The current belief is that the main risk of soil erosion in intensive grassland system occurs during the period of cultivation and reseeding when the soil surface is exposed, from compaction from vehicles as well as livestock traffic (Goulding et al., 2008), and crop sowing (FAO, 2006). Primarily it is the organic and clay fractions of this eroded soil material that carry adsorbed pollutants to surface waters, lowering water quality (Brazier et al., 2007). Small particles, especially colloids, become suspended in water draining from the soil in both surface and subsurface flows, including artificial land drains and ditches (MA, 2005a). The mean rate of erosion for European grassland is estimated at 0.29 t ha 1y 1, compared with 4.34 t ha 1y 1 for arable land and 0.10 t ha 1y 1 for forest (Cerdan et al., 2006). Recently, though erosion rates of up to 1.21 t ha 1 y 1 have recently been recorded (Bilotta et al., 2010) on intensively managed grasslands in the United Kingdom, which are significantly in excess of estimated soil formation rates. This latter point raises a question about the long-term sustainability of intensive approaches to farming grasslands; if soil erosion rates exceed soil formation rates, then already shallow and compacted soils may not be able to support productive agriculture in the very near future (Montgomery, 2008). We are highly confident that intensive agricultural production has a negative impact on nutrient cycling since intensive grassland production perturbs nutrient cycling grossly, potentially creating a very leaky system in which nutrients are lost both into water sources for example, NO3 leaching (Galloway et al., 2003) and into the air, for example, NH3 emissions (Bouwman et al., 1997). Such high nutrient inputs affect the community structure both above and below ground ( Jangid et al., 2008) subsequently impacting on nutrient cycling capabilities. Grassland systems with higher N inputs have faster N processing rates compared to those of a lower N input, with the consequences that there are greater rates of loss of N from the soil to water (Haygarth et al., 1998b; Ryden et al., 1984) and the atmosphere (Ostle et al., 2000). Excess NO3 is potentially toxic to ruminant animals, if ingested in large concentrations, as its conversion in the rumen to nitrite can cause methaemoglobinaemia (Addiscott, 2005) though occurrences of this are rare.

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Manures and other organic wastes, for example, the digestate from biogas production can be used as an organic fertilizer (FAO, 2008) making it an effective method of recycling nutrients from the farm. Potentially the digestate has lower NO3- leaching and N2O (nitrous oxide) emission compared with undigested slurry applications (Moeller and Stinner, 2009). Studies have shown that the digestate also has a greater potential for NH3 emissions, a higher pH and a greater proportion of total N as NH4-N (up to 5%–15% more than in normal slurry) (FAO, 2008; Gerin et al., 2008) which could negate this potential benefit. In contrast, work by Sommer et al. (2006) suggests that slurries with lower dry matter such as the anaerobically digested slurry, infiltrate the soil more quickly, thereby reducing NH3 emissions. This clearly requires further investigation. We are highly confident that increased agricultural production has a negative effect on biodiversity conservation, reducing the numbers and diversity of species as well as other ecosystem functions, for example, future soil formation (MA, 2005a). Agriculture dominates much of Western Europe and consequently a significant part of European wildlife has evolved in association with it (Wade et al., 2008). We know that agricultural intensification has caused declines in the diversity of plants, (Hooper et al., 2005; Marshall et al., 2003; Pilgrim et al., 2004), insects (Asher et al., 2001; Benton et al., 2002; Duffey et al., 1974; Morris, 2000), and birds (Aebisher et al., 2000; Donald et al., 2006; Robinson and Sutherland, 2002; Wilson et al., 1999). However, in grasslands, the mechanisms responsible for bird decline remain poorly understood (Vickery et al., 2001) since increased abundance of insect prey does not enhance bird diversity or abundance (Cole et al., 2007). The majority of agricultural grassland is now species-poor and structurally uniform (Benton et al., 2003) because of greater fertilizer inputs (Firbank et al., 2008), increased stocking levels and a switch from hay making to silage production (Chamberlain et al., 2000; Petit and Elbersen, 2006) all of which potentially discourages foraging birds (Cole et al., 2007). Reversing intensification may lead to a rapid recovery of bird populations (Donald et al., 2006), though more work is needed to identify and understand variations in taxa response to such pressures at the European regional level (Petit and Elbersen, 2006). Grazing animals influence plant biomass, soil nutrient dynamics, and plant species composition (Post and Pedersen, 2008). However, livestock are increasingly being fed concentrate reducing the need for grazing on grasslands (FAO, 2006), so many European pastures, which are diverse long-established ecosystems, are now threatened by abandonment (Baur et al., 2006; FAO, 2006). This will cause a shift in community dynamics as some species will benefit over others (Baur et al., 2006). We are highly confident that intensive agricultural production has a negative effect on landscape quality. Increasing agricultural specialization affects landscape composition and habitat quality over the medium term, often

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reducing it (Haines-Young et al., 2003) and has led to habitat homogenization for birds, fish, plants, and invertebrates (Sax and Gaines, 2003; Smart et al., 2006a; Smart et al., 2006b). Parcels of seminatural grasslands surrounded by intensive grassland farming are the most likely to be at risk of future intensification (Petit and Firbank, 2006), though these threats can be reduced by using agro-environmental schemes to compensate for lost production (Carey et al., 2003; Donald et al., 2006; Dreschsler et al., 2007). In contrast, maintaining landscape features, for example, hedgerows, windbreaks, whose maintenance may reduce farming profit margins, can be beneficial to farmers providing: useful by-products, reduced risk of crop loss during droughts, diversified food and income resources, and reduced vulnerability to environmental risks (Scherr and McNeely, 2008) as well as providing habitats for wildlife.

3.2. No direct relationship We believe that there is no direct relationship when soil erosion regulation is the responding factor and one of the following is the driving factor: air quality, water quality, or hydrological regulation (Fig. 2). We also believe that water quality does not have a direct affect on nutrient cycling (Fig. 2).

3.3. Positive relationships Interactions among the nonagricultural production ESs tended to be either mutually beneficial or inconclusive (see Section 3.4). Nutrient cycling was the only ES of the nine studied found to have a beneficial affect on the other eight ESs while both erosion regulation and nutrient cycling were the only driving ESs to enhance agricultural production. We are highly confident that good climate regulation (i.e., no extreme rain or temperature events) has a positive effect on air quality regulation. Under poor climate regulation, there are elevated quantities of GHGs which can create positive feedback effects for further warming. For example, elevated levels of CO2 enhances CH4 and NOx emissions from soils (Ineson et al., 1998). Warmer temperatures are also likely to increase NH3 emissions further reducing air quality. Plants that are exposed to elevated CO2, produce more Volatile Organic Compounds (VOCs) which act as tropospheric-O3 precursors (Sharkey and Yeh, 2001) promoting O3 production and therefore reducing (i) air quality, (ii) plant growth, and (iii) soil C accumulation when O3 combines with CO2 (Loya et al., 2003). We are highly confident that good climate regulation has a positive effect on water quality The predicted hotter, drier summers with localized more intensive rainfall events (Osborn et al., 2000; Wilby et al., 2006), could cause greater

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losses of pollutants via macro-pore flow in cracked clay soils (Rounsevell et al., 1999), or enhanced overland flow due to infiltration excess processes. Furthermore, water quality could also be impaired by enhanced pathogen loading in water courses (Senhorst and Zwolsman, 2005) and drinking reservoirs (Kistemann et al., 2002). However, reduced flows in water courses in summer will also degrade water quality (Arnell et al., 2001). The process of rewetting these dried soils will stimulate microbial activity. The resultant mineralization of the large N reserve, will lead to more N and P being released from soils and subsequently leached into rivers (Qiu et al., 2004; Turner and Haygarth, 2001; Worrall and Burt, 1999) further reducing water quality. We have mixed confidence that good climate regulation has a positive effect on hydrological regulation. Poor climate regulation through extreme weather events, for example, periods of heavy rainfall, has increased the risk of winter floods in the United Kingdom (Schroter et al., 2005) as the hydrological pathways are unable to cope with the excess water. Floods are further exacerbated by reduced plant transpiration which leads to greater moisture retention, reducing the capacity of soils to store additional rainfall water (Korner, 2000). Contrastingly, substantially reduced flows may affect wetlands, reducing their water regulatory capacity (Sutherland et al., 2008), while increasing global temperatures make it likely that ever-increasing quantities of CO2 will be released from organic soils resulting in a positive feedback to global warming (Freeman et al., 2001). This could be ameliorated by wetland restoration, for example, establishing buffer strips though there may be a long time lag until these wetlands function in a similar way to natural ones (Lal, 2008). We have mixed confidence that good climate regulation has a positive effect on erosion regulation. An increase in temperature and/or atmospheric CO2 content will modify plant growth pattern and subsequently the amount of ground cover, indirectly affecting erosion regulation (Favis-Mortlock et al., 1997), since increased vegetation cover reduces erosion risk. If the frequency of intensive rainstorms increases, they may be accompanied by a clustering of dry periods which could increase water and wind erosion (Sauerborn et al., 1999) with the prediction that for every 1% increase in total rainfall there will be a 1.7% increase in soil erosion (Nearing et al., 2004). We are highly confident that good air quality regulation (i.e., clean air) has a positive effect on water quality. Ammonia deposition can contribute to acidification and eutrophication of surface waters and soil (Danielopol et al., 2003; Galloway et al., 2003; Watson and Foy, 2001). Subsequently, improved air quality will be associated with elevated water quality since decrease in agriculturally derived atmospheric NH3 deposition reduces NH3 concentrations and loads in surface waters (Whitehead et al., 2006).

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We have low confidence that good air quality regulation has a positive effect on hydrological regulation. Aerosols formed in the atmosphere, as a result of NH3 combining with NOx or SO42, are known to have a role in “global dimming,” (Stanhill and Cohen, 2001) whereby solar radiation is reflected back into the atmosphere, a process increased by human activity (Kvalevag and Myhre, 2007). Global dimming is a problem in Europe (Kvalevag and Myhre, 2007), and might have a negative impact on agricultural production, and the hydrological cycle since plants are sensitive to changes in diffuse radiation (Stanhill and Cohen, 2001). However, information and our understanding of NH3 and its role in global dimming is limited (Kvalevag and Myhre, 2007). We are confident that good air quality regulation has a positive effect on nutrient cycling. Nutrient cycling can be adversely affected by soil acidification, whereby rain containing dissolved NH3 falls onto the ground. This can lead to the release of heavy metals, for example, aluminium, which are toxic for some plants and processes such as nitrification (MA, 2005a; Pearson and Stewart, 1993). We are highly confident that good air quality regulation has a positive effect on both biodiversity conservation and landscape quality. It is well known that plant diversity is greater where soil mineral N content is low. Nitrogen deposition, primarily derived from NH3, is at its greatest in northern Europe (Vitousek et al., 1997) reducing the diversity of the landscape (Fangmeier et al., 1994; FAO, 2006; Goulding et al., 1997; Stevens et al., 2004, 2006; Stoate et al., 2001). The plant species able to persist in such highly productive landscapes will vary depending on the type and severity of land-use change in addition to species specific differences in seed bank persistence (Smart et al., 2006a). Acidic habitats are particularly prone to damage through both eutrophication and the different capacities of plants both to utilize and buffer against this nitrogen enrichment (Pearson and Stewart, 1993). We are confident good water quality (i.e., clean water) has a positive effect on both biodiversity conservation and landscape quality. Good water quality is associated with landscape features which also enhance farmland biodiversity, for example, wetlands, ponds, hedges, and managed ditches (Burel, 1996; Haycock and Muscutt, 1995; Viaud et al., 2005). We are confident that good hydrological regulation (i.e., no extreme flood or drought events) has a positive effect on water quality. Wetlands, which play an important role in water regulation, have been described as “kidneys of the landscape” (Mitsch and Gosselink, 2007) because of their ability to improve water quality through processes such as denitrification and sediment retention. Functionally important wetlands within grassland systems can include unimproved pasture or even small patches of wet soils in the corners of fields. If they are drained, then their functional capacity will be lost, though the precise effects are complex and variable (Bullock and Acreman, 2003), causing a reduction in water quality (Blackwell and Maltby, 2006).

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At both the field and farm scale, the amounts of particulate matter (e.g., particulate P, organic matter, and sediment) in the water are likely to be positively related to the quantity of water leaving the land, (Haygarth et al., 2000) and this may increase with improved drainage. Well-managed drainage ditches could also reduce P losses from grasslands (Kroger et al., 2008). We are highly confident that good hydrological regulation has a positive effect on nutrient cycling since slower water flows, which are lower in energy, reduce both nutrient cycling and the potential for sudden large nutrient losses either into water, for example, P (Preedy et al., 2001) or into the atmosphere (Schlesinger et al., 2006). High water flows, which occur after periods of intensive rainfall, with their greater energy, increase nutrient cycling and the possibility of nutrient losses. If hydrological regulation leads to more drying/wetting cycles, then nutrient cycling is likely to be enhanced because of increased mobilization of nutrients in the soils (Turner and Haygarth, 2001). This suggests that it is the efficiency (i.e., a nonleaky system), rather than the speed, of nutrient cycling that is important. We have mixed confidence that good soil erosion regulation (i.e., no erosion occurs) has a positive effect on agricultural production. While agricultural production can be reduced locally on eroded soils, in temperate climates under intensive management, the impact of erosion on production is considered to be minimal (Evans, 1997) though Bilotta et al. (2007) highlight the need for more work in intensively managed grassland landscapes. The greatest cost for the farmer is erosion mitigation with agricultural land losing value through a decline in land quality (Evans, 1993; Montgomery, 2008). We have mixed confidence that good soil erosion regulation has a positive effect on air quality since wind erosion can contribute to poor air quality when the bare surfaces of vulnerable (sandy and peaty) soil types are exposed to strong winds (Evans, 1996). Soil particles suspended in the air are known to travel up to thousands of kilometers (Bennett, 1939) and in grassland systems these conditions can occur when other agents of erosion, for example, water, have removed a protective cover of vegetation. We are highly confident that good soil erosion regulation has a positive effect on water quality since soil erosion tends to reduce water quality (Morgan, 2005). In grassland systems, where erosion is visually less obvious, fewer studies have been carried out (Bilotta et al., 2008; Brazier et al., 2007), though higher levels of soil erosion, perhaps due to overstocking, reduces surface water quality (Bilotta and Brazier, 2008). We have mixed confidence that good soil erosion regulation has a positive effect on hydrological regulation as eroded soils lose their water-holding capacity ( Jankowska-Huflejt, 2006) because bare ground surfaces are susceptible to capping and compaction, increasing the risk of run-off. In temperate climatic areas, the main impact of this run-off and erosion is seen further downstream by increased flooding (Robinson and Blackman, 1990).

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We have mixed confidence that good soil erosion regulation has a positive effect on biodiversity conservation as the increase in nutrients from the eroded land entering water bodies will reduce both terrestrial and aquatic biodiversity through eutrophication (Evans, 1996). Furthermore, the subsequent accumulation of silt will clog up river gravels (Stoate et al., 2001), and could adversely affect the spawning of salmonids (Harrod and Theurer, 2002). We are highly confident that good nutrient cycling (i.e., where there are fewer labile nutrients in the system because of efficient utilization or nutrient turnover is slow), has a positive effect on agricultural production. Balanced fertilizer input, as advocated by Justig von Leibeg in the nineteenth century requires a farmer to replace “by fertiliser all nutrients removed from the field by crop harvest” (Russell, 1912) with the advantage of reducing N leaching, and emissions of NH3 and N2O (Oenema et al., 2009). Post World War II, the use of artificial fertilizers has been fundamental to increase substantially grass and meat production, though as their prices continue to rise, farmers are showing greater dependence on recycling organic nutrients, for example, manure already on the farm. However, applying manure using soil injection methods will produce N2O emissions (Oenema et al., 2009). While N might appear to be abundant, there are concerns about future shortages of P because of diminishing rock reserves (Goulding et al., 2008) which are predicted to run out within 30 years. One potential P source is manure, though timing of manure application is critical to ensure maximum production benefit. As livestock now consume more edible protein than they produce there has been a shift from ruminant production (sheep, cattle, and goats, which are often raised extensively) to monogastric species (pigs and poultry mostly produced in industrial units) as the latter, along with dairy cattle, are more efficient in gathering nutrients from feeding concentrates (FAO, 2006). Globally, N efficiency is: 20% for pigs, 34% for poultry, 40% for dairy and just 5% for beef. In the EU, meat and milk production has grown, despite the reduction in land dedicated to pasture and feedcrops, because of imported feed and increasing the conversion rate from feed to meat or milk (FAO, 2006). We have mixed confidence that good nutrient cycling (i.e., fewer labile nutrients in the system and nutrients are retained in the system for longer) will have a positive effect on climate regulation. Climate regulation is affected by decomposition and nutrient cycling at regional and continental scales through the release of GHGs and C sequestration (MA, 2005a). More efficient management of N will lead to reduced N2O emissions from microbial processes. By improving our understanding of the factors controlling the processing of N by microbes, we will be able to predict the conditions under which significant N loss will occur (Firestone and Davidson, 1989). By optimizing the precision of both the timing and rates of N inputs, we should reduce the quantity of excess N in the soil and subsequently the risk of N losses to air (as N2O) and water (via NO3 leaching).

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We have poor confidence that good nutrient cycling will have a positive effect on air quality since more efficient nutrient cycling will reduce NH3 emissions, and subsequently the formation of secondary particulates in the atmosphere (assuming formation is not limited by other elements). However, the denitrification process also produces NOx, which plays a role in ozone depletion in the stratosphere (Haag and Kaupenjohann, 2001). We are highly confident that good nutrient cycling will have a positive effect on water quality. Poor nutrient cycling leads to the leakage of N (in the forms of NO3, NH4þ and nitrite) (Scholefield et al., 1993) and P into water courses (in the form of dissolved and particulate P, inorganic P, and organic P) (Haygarth et al., 1998a), both of which can cause eutrophication. We can reduce diffuse N sources by: reducing N fertilizer application; using nitrogen fixing crops (though some of these are equally as leaky as systems with high fertilizer inputs); and by either restoring or creating hydrological connections to wetlands (Verhoeven et al., 2006) as well as using N much more efficiently. We are confident that good nutrient cycling will enhance hydrological regulation. Eutrophication caused by leaky nutrient cycles, where excess nutrients are lost to water sources, will stimulate plant growth within water ways (Beegle et al., 2002; Pengelly and Fishburn, 2002), leading to impeded river flow while enhancing flood risk. We have poor confidence that good nutrient cycling can have a positive effect on erosion regulation since nutrient cycling enhances grass growth and vegetation cover slows down both surface water flow and particle and colloid erosion (Bilotta et al., 2007). We have mixed confidence that good nutrient cycling will be have a positive effect on both biodiversity conservation and landscape quality as N is stored in vegetation, soil organic matter, soil, and groundwater. The emission of excess N, which has a negative effect on biodiversity, may be delayed for decades masking past and present N disequilibria and overloads (Haag and Kaupenjohann, 2001). Since current agricultural practices and solutions such as buffer strips may be unsustainable, we need an integrated systems-based approach with tight, close cycles to optimize N fluxes and budgets at site, farm, and region levels (Haag and Kaupenjohann, 2001). However, to increase the sensitivity and predictability of models looking at the consequences of excess nutrients (e.g., NO3 leachates) at these levels, we need more data on soil, climate, and land management at a range of scales in addition to data on livestock and crop production over time (Schmidt et al., 2008). We are confident that enhanced biodiversity conservation has a positive effect on both water quality and hydrological regulation since creating wetlands can provide habitats for plants and animals, while enhancing water quality and regulation (Hillbricht-Ilkowska, 2008). We have mixed confidence that enhanced biodiversity conservation has a positive effect on erosion regulation as grasslands positively mitigate erosion providing

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total plant cover is maintained and plants are not destroyed by heavy machinery or excessive grazing ( Jankowska-Huflejt, 2006). Increasing the diversity of plants and rooting depths (Grime et al., 2008) reduces the risk and negative impacts of erosion by retaining both soil suspensions and structure as well as enhancing nutrient sequestration ( Jankowska-Huflejt, 2006). We have poor confidence that enhanced biodiversity conservation has a positive effect on nutrient cycling. We know that the soil community plays a pivotal role in nutrient dynamics, particularly in low input extensive agricultural grasslands, where they are vital for nutrient acquisition by plants. Carbon availability is one of the limiting factors controlling soil microbial growth (Wardle, 1992), because the quantity and quality of C, coupled with N and P availability determines whether microbial biomass immobilizes or mineralizes N and P. It is probable that changes in C and nutrient flow, through changes in plant species and their composition (Hooper and Vitousek, 1997; Phoenix et al., 2008), will have a major impact on microbial community structure and activity and subsequently nutrient cycling. Grasses, for example, play an important role in retaining nutrients, particularly inorganic N. Subsequently fewer nutrients are returned to the soil from grasses relative to forbs, perhaps reflecting the longer leaf life of grasses (Phoenix et al., 2008). Invertebrates are also important in buffering efficient local recycling of nutrients and preventing their leakage from impaired ecosystems (Lavelle et al., 2006). As ecosystems become more mature, nutrient cycling becomes “closed”, giving them a greater capacity to entrap and hold nutrients than developing communities (Odum, 1969). This increase in internal nutrient cycling may be a mechanism by which late successional plant species compensate for reduced availability of inorganic plant nutrients (Vitousek, 1982). We are highly confident that enhanced biodiversity has a positive effect on landscape quality and vice versa as multiple land use, that is, mixed farming is associated with higher biodiversity (Lindenmayer et al., 2008) and landscape values in comparison with just arable systems (Stoate et al., 2001). This is partly because of increased diversity of habitats, maintenance of metapopulations, and the greater density of ecotones or habitat requirements of some species (Burel and Baudry, 1995; Firbank et al., 2008). However, landscape issues affect different taxa in different ways (Weibull and Ostman, 2003) since larger species with subsequently larger ranges are more influenced by landscape (Firbank et al., 2008; Fuller et al., 2005). Better approaches to connecting suitable habitats through the landscape are required to determine the optimal amount of connectivity per species gained/maintained (Lindenmayer et al., 2008). We have poor confidence that landscape quality has a positive effect on water quality and hydrological regulation as an effective tool for enhancing hydrological regulation and water quality appears to be the maintenance or creation of meadows and pastures with small wetlands and woodlots of small water bodies

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within the farming landscape (Hillbricht-Ilkowska, 2008; Jankowska-Huflejt, 2006). A diverse array of habitats could also impede water flows across fields and subsequently reduce the delivery of nutrients to waters as well-being aesthetically pleasing (Blackwell and Maltby, 2006). Forests and permanent grasslands also help improve air humidity ( Jankowska-Huflejt, 2006). We are confident that landscape quality has a positive effect on erosion regulation as buffer zones and other landscape features can be important in controlling soil erosion as well as offering other water quality benefits, for example, reducing the accumulation of sediments and associated pollutants (Dillaha and Inamdar, 1997; Stevens and Quinton, 2009a,b).

3.4. Inconsistent relationships These set of interactions are reported to be variable and include relationships amongst atmospheric, hydrological, and landscape functions. Much of this variability is probably due to inconsistent effects across spatial and temporal scales and because the evidence base is weaker here than for some of the other interactions. We are highly confident that increasing agricultural production in intensively managed grasslands has an inconsistent effect on climate regulation leading to highly variable trade-offs. There is a clear negative relationship between increasing the intensity of livestock production and climate regulation. Choudrie et al. (2008) show that in 2006 UK agriculture was responsible for: (i) approximately 6.7% of the total GHG emissions (CO2 equivalents); (ii) approximately 38% of the total CH4 emissions, mainly from enteric fermentation and (iii) 66% of N2O emissions. Inorganic fertilizers, livestock manure, and crop residues are all major direct GHG sources while NO3 leaching and N deposition are important indirect GHG sources arising from agriculture (Choudrie et al., 2008). However, there is the potential for grassland agricultural systems to alleviate GHG emissions (Monteny et al., 2006) by limiting and adjusting N inputs (from inorganic fertilizers or livestock manures) to closely match agronomic need; improving N removal by crops, and adjusting feeds to better match nutritional requirements, particularly for ruminants. More than half of the global energy expenditure during livestock production (particularly intensive beef) is for feed production (FAO, 2006). This increase in animal feed requirements further impacts on climate regulation as N fertilizer is used both in crop (FAO, 2006) and silage production. This enhances CO2 release as more fossil fuels need to be burnt during fertilizer production (FAO, 2006). A positive effect of agricultural productions in grassland landscapes, is that their soil systems have a greater potential for C storage, than arable systems, since the soil is not regularly ploughed, reducing the release of CO2 back into the atmosphere. Carbon storage, which involves the conversion

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of atmospheric CO2 into long-lived C pools of both soil organic C (SOC) and soil inorganic C (SIC) (Lal, 2008), is often regarded as a win–win strategy offering multiple benefits without the threat of climate change, though the potential of C storage will be reduced if N is limiting (Lal, 2008). The key is the permanency of the C “storage.” Temporary storage, that is, land reverted to forest for 50 years and then ploughed for cropping, raises the potential problem of “storing” C now and releasing it at a time when the climate is even more sensitive to increased GHG emissions. In considering the impacts of grassland biofuel production on GHG emissions, the whole life cycle (e.g., seed production through to the distribution of the final product) needs to be assessed (FAO, 2008). Biofuels derived from cultivated grasses, for example, Panicum virgatum contribute to CO2 emissions as they require considerable fuel in their production and processing (McIntyre et al., 2009) though their net GHG emissions differ according to N fertilizer use, feedstock, location, agricultural practice, and conversion technology (FAO, 2008). Biogas is created by anaerobic digestion of plant or animal waste product, generating a large volume of CH4 and CO2 for energy use mitigating the gases’ potential negative impact on climate regulation (FAO, 2008). We have mixed confidence that increased agricultural production has an inconsistent effect on hydrological regulation leading to highly variable outcomes. Agricultural production can have a negative effect on hydrological regulation leading to flooding downstream following drainage and isolation of floodplains, drainage of wetlands (Bullock and Acreman, 2003), and the removal of landscape features, for example, hedgerows (Thomas et al., 2008). One unexpected consequence of this agricultural intensification, when coupled with climate change, is that many rivers will have higher discharge rates, becoming more prone to flooding and drying (Sauerborn et al., 1999) with fewer big differences between scenarios (MA, 2005a). Factors including soil properties, position in the landscape, and rainfall patterns will also determine the impact of artificial drainage on agricultural land (Robinson, 1990). Typically though, water on drained land will move more quickly from the land to surface water bodies enhancing flood risk. Draining wetlands can also impede their ability to recharge aquifers which is an important function for hydrological regulation, though Bullock and Acreman (2003) argue that the flood control function largely applies only to floodplain wetlands, while other wetland types might increase flood risk. In contrast, artificial drainage on a heavy soil can have a positive effect as the water storage capacity of the soil is increased. This advantage can be outweighed though by high livestock densities which cause greater compaction of the soil and enhance the quantities of surface/near-surface runoff per volume of rainfall (Bilotta et al., 2008). Certain biofuel crops (e.g., Miscanthus) with their high demand for water may also have a negative impact on water resources (FAO, 2008).

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We have mixed confidence that good climate regulation (i.e., no extreme rain or temperature events) in intensively managed grasslands has an inconsistent effect on agricultural production leading to highly variable trade-offs. This is a complex relationship where a potential positive outcome could have hidden negative consequences. Grassland agriculture may not adapt so readily to climate change, since in comparison with arable systems, it is slow to adopt new methods and technologies (FAO, 2006). Poor climate regulation may affect the productivity and quality of grasslands and increase the incidence of diseases and parasites to which livestock are susceptible. However, a benefit of poor climate regulation, in terms of elevated CO2 levels, is enhanced yields of C3 pasture plants, common in temperate systems (Long et al., 2004) though at a potential cost of reduced plant protein content (Cotrufo et al., 1998), since under elevated CO2 concentrations, N is more likely to become limited in the soil (Gill et al., 2002). Benefits of this could be reduced N excretion, N2O emissions, and enteric CH4 emissions by livestock as well as reduced NO3 leaching from soils. Sowing legumes (Lu¨scher et al., 1998), could reduce the need to apply additional N fertilizer to maximize both yield potential (Kirschbaum et al., 1996; Reich et al., 2006; Schneider et al., 2004), and protein content for animal feed. However, N fixation and utilization will be restricted by low soil P availability (Korner, 2000). Should temperatures increase, livestock farmers could respond by reducing the grazing season and moving to more fully housed systems, where heat stress could be managed and exposure to potential emerging diseases is limited. Compared with systems more reliant on grazing, such measures could have beneficial effects by decreasing N2O and NO3 leaching (which will have a positive impact on water quality) and negative impacts by increasing potential NH3 emissions (which will reduce air quality) (Chadwick et al., 2008). We have mixed confidence that good climate regulation has an inconsistent effect on nutrient cycling. The interactions involved in biological processes (e.g., nitrification, and mineralization) are complex as they are controlled by many factors including temperature and available water, making it difficult to predict an ecosystem response to atmospheric change. However, it is unlikely that there will be an increase in biological N fixation to fuel terrestrial C accumulation (Hungate et al., 2004). We have mixed confidence that good climate regulation has an inconsistent effect on biodiversity conservation. We know that combinations of extreme events involving temperature, rainfall, and wind are liable to have major impacts on biodiversity, but exactly how is unknown (Sutherland et al., 2008). Again the complexity of the interactions involved, coupled with the absence of experimental data, hinders accurate prediction of which species will decline. We believe that poor climate regulation could result in the gradual loss of species as abiotic conditions begin to exceed species’ tolerance limits. These losses may be random (Loreau et al., 2001) as the

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rate at which species distributions are likely to respond to climate change will vary enormously (Sutherland et al., 2008). Therefore, some grassland species may prosper while others will be pushed to, or begin to, exceed their tolerance limits. We have mixed confidence that good climate regulation has an inconsistent effect on landscape quality. Projected land-use change suggests that Northern Europe is unlikely to experience any significant impact from climate change (Rounsevell et al., 2005). However, more extreme weather, for example, flooding, might cause land-management changes (Riedo et al., 2000) resulting in either a greater demand for irrigation (and consequently reservoirs) or drainage depending on the situation. Either scenario will ultimately alter the landscape; whether such changes will be regarded as positive or negative is impossible to prejudge. We have poor confidence that good/improved air quality regulation has an inconsistent or inconclusive effect on agricultural production. Nitrogen deposition arising from NH3 emissions to productive agricultural land (though it is damaging to sensitive ecosystems and species) provides an increase in the available N supply for crop growth. This will only be achieved if land managers account for this by managing other N inputs appropriately. Cleaner air, with lower quantities of N would reduce N deposition and subsequently this “free” atmospheric fertilizer, potentially reducing agricultural production. A positive effect of cleaner air is that it could also reduce the effect of global dimming and its potential to have a negative impact on agricultural production by hindering plant growth (Kvalevag and Myhre, 2007). We have poor confidence that good air quality regulation has an inconsistent effect on climate regulation, leading to highly variable outcomes. Ammonia deposition causes indirect losses of N2O (Baggott et al., 2005) and enhances NOx (N2O þ NO) emissions through nitrification and denitrification. However, applying ammonium can reduce CH4 oxidation in the soil (Bronson and Mosier, 1994) and consequently measures to curb air pollution may actually enhance surface warming. This is complicated further since the mechanisms which we believe to be responsible for global warming, may mask the effects of global dimming, highlighting the need for more research in this area (Kvalevag and Myhre, 2007). We are confident that good water quality has an inconsistent effect on both climate regulation and air quality. It is well known that increased losses of N from agricultural land leads to larger levels of gaseous N loss. Wet soils and buffer zones on farms can improve water quality leaving farms, but they can have a negative impact on climate regulation; the process of denitrification can be enhanced and can result in the production of more N2O, in addition to CH4 and CO2 (Ambus, 1998; Groffman et al., 1991; Mander et al., 2005). We are confident that good water quality has an inconsistent effect on hydrological regulation since the areas on grassland farms where water quality is most

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likely to be improved are typically relatively wet, that is, buffer strips or wetlands. However, the hydrological cycle is likely to be affected, but the precise effects are complex and variable (Bullock and Acreman, 2003). We have mixed confidence that good hydrological regulation (i.e., no extreme periods of drought or floods) has an inconsistent effect on agricultural production leading to variable outcomes. Poor water regulation can result in waterlogging of soils, making it hard to get cattle onto the land (Tyson et al., 1992), though the exact nature of this relationship is affected by individual circumstances (e.g., preceding soil conditions, and rainfall intensity). Grazing and silage production will be reduced if sufficient water is not available during the growing season, though this could be overcome by housing the animals. On floodplains, controlled flooding where it is required provides a flood reduction benefit downstream (Starkel et al., 1991) with the drawback of potentially reducing the productivity of land and grazing capacity (Scherr and McNeely, 2008). Those animals which graze floodplains are also at risk of being lost to floods (Blackwell and Maltby, 2006). We have mixed confidence that good hydrological regulation (i.e., no extreme periods of drought or floods) has an inconsistent effect on climate regulation. There is a clear inverse relationship between hydrological regulation and GHG emissions (Beier et al., 2008), whereby reducing hydrological regulation by draining land will lower GHG emissions, as there will be fewer wet areas in which denitrification can occur. In contrast, maintaining flooding (for natural flood defence), on floodplains, will result in the development of backswamps which will subsequently promote GHG emissions (Bouman, 1990). However, dry soils also emit NOx and O3 (Cardenas et al., 1993) indicating that this is a complex relationship. We have mixed confidence that good soil erosion regulation (i.e., little if any soil erosion occurs) has an inconsistent effect on climate regulation primarily because soil is an important source of and sink for GHG. Organic matter (OM) is an essential component of the soil system which influences a range of factors such as fertility and water-holding capacity. In turn, environmental change influences soil OM content by altering, the rates of C flux, plant productivity, vegetation cover, and land use. Physical loss of soil material through erosion will reduce the soil C store until equilibrium is reestablished for the land use in question. Principally organic-rich soils lose C through oxidation, enhancing CO2 emissions, and the quantities of dissolved organic C in drainage waters (Adger et al., 1991; King et al., 2005). We have mixed confidence that good soil erosion regulation has an inconsistent effect on nutrient cycling since the physical loss of soil material, through soil erosion has a negative impact on nutrient cycling as it interrupts dynamic nutrient processes (especially in topsoils) and is the main cause of P removal (Bilotta and Brazier, 2008; Bilotta et al., 2008; Haygarth et al., 2006). Agricultural practices which degrade soil quality also contribute to the eutrophication of aquatic habitats. Because of this loss, there may be an

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increased need for fertilization to maintain productivity (Foley et al., 2005; Tilman et al., 2002). However, many of the nutrients associated with OM, within a noneroded soil, are not immediately available for plant use (Evans, 1996). Perhaps, we could develop a sustainable method of releasing these nutrients which has a minimal detrimental effect on the environment. We have mixed confidence that enhanced biodiversity conservation has an inconsistent effect on both agricultural production and climate regulation creating variable outcomes. A positive effect of botanically species-rich pastures are that the animals which graze are thought to be beneficial to human health as the nutritional characteristics of milk (Walker et al., 2004), cheese (Hauswirth et al., 2004), and meat (Wood et al., 2004) are enhanced. In 2008, Buller et al., showed that lamb produced on botanically rich grasslands have higher levels of vitamin E (helping to prolong shelf life), lower skatole levels (enhancing taste), and higher levels of nutritionally healthy fatty acids, in comparison with conventionally reared lamb (Buller et al., 2008). There is also evidence that there may be some interactions between species-rich pasture and breed which enhances meat quality. A potential negative impact of grazed biodiverse swards, is that they are more extensively managed and consequently GHG emission per unit of production (e.g., meat or milk) is greater than from an intensively managed farm (Glendining et al., 2009). However, certain components of biodiversity, for example, the characteristics of dominant species and the distribution of landscape units, influences the capacity of terrestrial ecosystems to sequester C and regulate climate at the local, regional, and global scales. Furthermore, soil invertebrates help to control the production or consumption of GHGs through OM sequestration and the creation of instable biogenic macroaggregates (Lavelle et al., 2006). However, changes in land use over large land surface areas will also alter how biodiversity affects climate (MA, 2005a). Grime et al. (2008) suggest that unproductive, species-rich grazed grasslands are highly resistant to climate change, with their real threat being landuse change and overexploitation. Long-lived, slow-growing grasses, sedges and small forbs, with their lower quantities of tissue die back, are thought to be important in helping to resist soil erosion and consequently the impacts of climate change (Kreyling et al., 2008). This suggests that highly diverse grasslands may be more resilient to the affects of climate. We have poor confidence that landscape quality has an inconsistent effect on agricultural production and nutrient cycling since the quality of the landscape, for example, soil type, and climate conditions can affect the suitability of the agricultural system and subsequently its production capability (Herzog et al., 2006), as can land designation and regulation. Landscapes are heterogeneous “patch-works” in which spatial processes and patterns interact (Turner, 1989) enabling the retention or transport of matter (Haag and Kaupenjohann, 2001). The greater the landscape diversity and/or connectivity, the more

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efficient the nutrient cycling and other processes (Haag and Kaupenjohann, 2001). However, uncertainty over the precise effects of these landscape changes on agricultural production still remains. For example, Hesse et al. (2008) used models to show that changing landscape composition by either installing buffer zones around surface water bodies and/or converting both coniferous and mixed forests to deciduous woodland-reduced river nutrient concentrations. However, neither of these methods was as efficient as changing fertilizer regime and point source admissions. We have poor confidence that landscape quality has an inconsistent effect on both climate regulation and air quality since lowering land quality through land-use changes, such as the conversion of woodlands to arable management has increased GHG emissions (Lal, 2008), reducing both air quality and climate regulation. However, the reversion of arable land back into grassland has the potential to enhance C storage, and therefore climate regulation, as discussed above.

3.5. No current evidence of a direct relationship There are the four cases where we think that there is a relationship between the ESs but there is currently no evidence of an interaction between them in the literature: (i) water quality driving agricultural production, (ii) hydrological regulation driving air quality, (iii) biodiversity conservation driving air quality, and (iv) erosion regulation driving landscape quality.

4. Conclusions It is imperative that we improve our knowledge of the interactions among ESs so that we can make sound decisions about how society manages the services provided by nature (MA, 2005b). Unfortunately, most ES science does not examine mechanisms behind ES relationships in depth and cannot distinguish among the causes of typical relationships (Bennett et al., 2009). Subsequently there may be a need to examine and compare the functions that control the services. Indeed, some of our inconclusive findings could result from the broad “service” descriptions which in reality contain a number of functions, and processes, that control those functions. Worldwide pressure on all ESs will increase (MA, 2005b) and policy makers will be forced to show preference for some ESs over others. The MA (2005a) highlights the concept that the supporting services, for example, erosion regulation and nutrient cycling, which are vital “for the production of all other ecosystem services” (MA, 2003) often fare the worst. Available evidence infers that far from being insignificant, erosion regulation and efficient nutrient cycling were the only two driving ESs shown to

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enhance agricultural production, implying that their protection will enhance our ability to meet future food needs. However, general rules about when to expect beneficial trade-offs among ES, how to create them, and how to take advantage of them, even in relatively well-studied agricultural landscapes are lacking (Bennett et al., 2009) and measures must be made to rectify this in future research. Here, we show that the interactions among the nonagricultural production ESs tend to be positive or inconclusive. Thus, efficient nutrient cycling has positive effects on all the other ESs studied; good air quality regulation has positive impacts on water quality, nutrient cycling, biodiversity conservation, and landscape quality, while water quality, biodiversity conservation, and landscape quality are the ESs to benefit the most from interactions with the nonagricultural production ESs. Overall, the least conclusive and consistent effects were shown in the interactions driven by climate regulation and hydrological regulation, possibly reflecting the fact that both ESs operate over the greatest range of temporal and spatial scales. In 2009, Glendining et al. showed that assessing the impact of animal production systems on the provision of other ES is much more complicated than arable systems as the analysis needs to include the influence of animal feeding and housing in addition to grassland management. Our findings support those of Glendining et al. (2009) by showing consistent and welldocumented negative effects of increasing levels of agricultural production on ESs in temperate grasslands. Traditional, low-input, agricultural landscapes are often valued for their cultural and landscape quality, and can be rich in biodiversity. However, at greater levels of production, these ESs are reduced. The influence of livestock themselves is critical; their presence increases N concentrations and GHG emissions. The presence of slurries and manures result in reductions of both air and water quality, while soil disturbance and poaching causes soil erosion and leaching of phosphorus (FAO, 2006). Water quality, hydrological regulation, nutrient cycling, and erosion regulation are all measures of ecosystem health, and so it is not surprising to see that the evidence shows that these functions are mutually reinforcing, and are undermined at high levels of agricultural production. Soils subject to erosion lead to reduced water quality, less effective hydrological regulation and, if livestock are present, increased human health risks from pathogenic bacteria, for example, Escherichia coli O157:H7. Such habitats are unlikely to be highly biodiverse (Evans, 1996). All ESs, but especially those occurring at large spatial or temporal scales, are more likely to be traded-off, as there are no international mechanisms or incentives to protect them (MA, 2005a). However, though most ESs are delivered at the local scale, their supply is influenced by regional or global scale processes (Carpenter et al., 2006). Subsequently, it is vital that

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management regimes which protect ESs incorporate an understanding of the scales of both space and time at which each trade-off occurs and ways to ensure that there is a balance between short- and long-term needs from ESs (Bennett et al., 2009). Such long-term planning is extremely difficult to do, because many managers are only rewarded for short-term success (MA, 2005a). However, if scientists only quantify trade-offs at one point in time or only examine spatial concordance among multiple services, we risk making incorrect assumptions about the mechanisms behind these relationships and therefore managing them ineffectively (Bennett et al., 2009). This highlights the need for, as well as the importance of, long-term monitoring to understand the influence of time, management, and scale on the relationships between ESs (Bennett et al., 2009; Carpenter et al., 2009).

5. Future Perspectives It is anticipated that agro-ecosystems will, in addition to ESs (MA, 2005a,b), need to deal with the anticipated increase in human population, by providing an elevated human food supply in the coming decades (Tilman et al., 2002). Our review was a first attempt to provide a better understanding of the ecological processes that structure relationships between ESs within the context of temperate agricultural lowland grasslands in Europe. We found that in managed temperate grasslands there was always a negative relationship between agricultural production and the delivery of ESs. Fundamentally, this arose from the removal of large amounts of net primary production from ecosystems, the manipulation of nutrient cycles, and a negative influence on biodiversity (Firbank et al., 2008) negatively impacting on ecosystem function and delivery of other ESs. Hence, in order for agriculture to become more sustainable, we need to develop agricultural methods or management techniques which can be implemented to minimize the negative impacts of these win–lose scenarios. Clearly, a better understanding of management of ESs in agricultural landscapes is critical (Bennett et al., 2009). This will require more experimental data to help us gain a better understanding of the outcomes of the interactions between ecosystems services and to help mitigate their detrimental effects. The development of a new generation of models based on our understanding of the ESs of agricultural systems is required that will enable these detailed and complex interactions (as explored in our review) to be addressed in a structured way. The review also suggested that ESs science still has a long way to go, that is, from current insights into ecosystem process and functioning of individual ESs to a full scientific underpinning and understanding of integrated ESs.

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ACKNOWLEDGMENTS North Wyke Research receives grant-aided support from the Biotechnology and Biological Sciences Research Council. This work was funded by the Institute Strategic Programme Grant, “Ecological Processes in Multifunctional landscapes,” and the Cross Institute Programme for Sustainable Soil Function, Soil CIP.

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C H A P T E R

F I V E

Halting the Groundwater Decline in North-West India—Which Crop Technologies will be Winners? E. Humphreys,*,1 S. S. Kukal,† E. W. Christen,‡ G. S. Hira,† Balwinder-Singh,§ Sudhir-Yadav,} and R. K. Sharmak Contents 1. Introduction 2. The Hydrogeology and Development of Irrigation in North-West India 3. Water Sources, Sinks, Depletion, and Savings 3.1. Why is the watertable going down in the rice–wheat belt of north-west India? 3.2. How much water do we need to save to arrest the decline in the watertable? 3.3. Methods for reducing groundwater depletion 4. Effects of Improved Technologies on Yield, the Nature and Amount of Water Savings, and Water Productivity 4.1. Laser leveling 4.2. Planting date 4.3. Varietal duration 4.4. AWD in rice 4.5. Zero till transplanted rice 4.6. Dry seeded rice with AWD 4.7. Rice on beds 4.8. Zero till wheat 4.9. Surface residue retention and mulching 4.10. Wheat on raised beds 4.11. Replacement of rice, crop diversification

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* International Rice Research Institute, DAPO 7777, Metro Manila, Philippines { Punjab Agricultural University, Ludhiana, Punjab, India { CSIRO Land and Water, PMB 3 Griffith, NSW, Australia } Charles Sturt University, Locked Bag 588 Wagga Wagga, NSW, Australia } The University of Adelaide, Adelaide, SA, Australia k Directorate of Wheat Research, Karnal, Haryana, India 1 Corresponding author: E-mail address: [email protected] Advances in Agronomy, Volume 109 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)09005-X

#

2010 Elsevier Inc. All rights reserved.

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4.12. System intensification 5. General Discussion 6. Conclusions Acknowledgements References

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Abstract Increasing the productivity of the rice–wheat (RW) system in north-west India is critical for the food security of India. However, yields are stagnating or declining, and the rate of groundwater use is not sustainable. Many improved technologies are under development for RW systems, with multiple objectives including increased production, improved soil fertility, greater input use efficiency, reduced environmental pollution, and higher profitability for farmers. There are large reductions in irrigation amount with many of these technologies compared with conventional practice, such as laser land leveling, alternate wetting and drying (AWD) water management in rice, delayed rice transplanting, shorter duration rice varieties, zero till wheat, raised beds, and replacing rice with other crops. However, the nature of the irrigation water savings has seldom been determined. It is often likely to be due to reduced deep drainage, with little effect on evapotranspiration (ET). Reducing deep drainage has major benefits, including reduced energy consumption to pump groundwater, nutrient loss by leaching, and groundwater pollution. The impacts of alternative technologies on deep drainage (and thus on irrigation water savings) vary greatly depending on site conditions, especially soil permeability, depth to the watertable, and water management. More than 90% of the major RW areas in north-west India are irrigated using groundwater. Here, reducing deep drainage will not “save water” nor reduce the rate of decline of the watertable. In these regions, it is critical that technologies that decrease ETand increase the amount of crop produced per amount of water lost as ET (i.e., crop water productivity, WPET) are implemented. The best technologies for achieving this are delaying rice transplanting and short duration rice varieties. The potential for replacing rice with other crops with lower ET is less clear.

1. Introduction The irrigated rice–wheat (RW) cropping system of north-west India is fundamental to India’s food security (Timsina and Connor, 2001). The small states of Punjab and Haryana produce 50% of the rice and 85% of the wheat procured by the Government of India (Singh, 2000). The productivity of these systems needs to increase to keep up with population growth in India, which is predicted to increase from 1.12 billion in 2008 to 1.35 billion by 2025 (UNESCO, 1995). Over that time, agricultural production needs to increase by about 25% on the same or less land, but in fact

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yields of rice and wheat are declining or stagnating (Ladha et al., 2003). Furthermore, production must increase in the face of severe soil degradation, increased incidence of pests and diseases, increasing labor scarcity, salinity, and waterlogging in some regions, and perhaps of greatest concern, groundwater depletion in large areas where the RW system prevails (Chhokar and Sharma, 2008; Pingali and Shah, 1999; Sharma et al., 2004a,b, 2007; Singh, 2000). Since the early 1970s, there has been a steady increase in the depth to the groundwater in most of the RW area of north-west India (Ambast et al., 2006; Hira, 2009; Hira and Khera, 2000; Hira et al., 2004; Rodell et al., 2009). The increase in depth has accelerated alarmingly in some areas in recent years; for example, in parts of Ludhiana District in central Punjab, the rate of change increased from about 0.2 m/yr during 1973–2001 to about 1 m/yr during 2000–2006 (Fig. 1). A similar trend was reported in Kurukshetra in Haryana (Sharma et al., 2008a). In 2009, 103 out of 138 administrative blocks were overexploited in Punjab, while 55 out of 108 blocks were overexploited in Haryana (http://cgwb.gov.in/gw_profiles/ st_Haryana.htm). Using satellite-based estimates of groundwater depletion, Rodell et al. (2009) found that groundwater is being depleted at a mean rate of 4.0  1.0 cm/yr across the states of Rajasthan, Punjab, Haryana, and western Uttar Pradesh. Over a period of 6 years (August 2002–October 2008) with close to normal rainfall, they estimated that the volume of groundwater had declined by 109 km3 (109  109 m3), double the capacity of India’s largest surface reservoir. The maximum rates of groundwater depletion appeared to be centered on Haryana and western Uttar Pradesh. 1973

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5 yrs moving avg Annual

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Figure 1 Depth to the watertable in June in Gujjarwal, Ludhiana District, Punjab, India, 1973–2005 (data source: Groundwater Cell, Punjab Department of Agriculture).

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The increase in depth to the groundwater in north-west India has three major negative effects (Hira, 2009): (1) increasing energy requirement and cost of pumping groundwater; (2) increasing tubewell infrastructure costs; and (3) deteriorating groundwater quality, which will ultimately be to the degree that the groundwater becomes unusable because of upwelling of salts from the deeper native groundwater (AICRP, 2009; Kamra et al., 2002), and because of saline groundwater intrusion into fresh groundwater (as a result of reversal of groundwater flows due to the lowering of groundwater levels in fresh groundwater regions below levels in areas with saline groundwater). In an attempt to solve the various problems of RW systems in the IndoGangetic Plain (IGP), many improved technologies referred to as “Resource Conserving Technologies” (RCTs) and “Integrated Crop and Resource Management” (ICRM) have been developed over the past couple of decades (Chauhan et al., 2001; Gupta and Seth, 2006; Ladha et al., 2009; RWC-CIMMYT, 2003; Sharma et al., 2005; Sidhu et al., 2007). These technologies are targeted at increasing the productivity, sustainability, and profitability of rice-based cropping systems through reducing and reversing soil degradation, reducing air pollution, and increasing nutrient, labor, and water use efficiencies. Examples of these technologies include laser leveling, reduced and zero tillage, dry seeding of rice, raised beds, retention of crop residues, balanced fertilization, and crop diversification. Many of the technologies involve adoption of one or more of the three fundamental principles of conservation agriculture—reduced or zero tillage, soil surface cover, and crop rotation (FAO, 2008; Hobbs et al., 2008). The importance of integrated management of the crop and all resources, and of considering the performance of the total cropping system, as opposed to that of individual crops in isolation, is also being increasingly recognized ( Jat et al., 2009; Ladha et al., 2009). This chapter explores the potential of many on-farm technologies to save water and to increase productivity with respect to both irrigation amount and total water depletion (water no longer available for productive use due to its loss from the system or pollution), and to highlight gaps in knowledge and future research needs. The focus is on the IGP of north-west India, where RW systems prevail, and where the problems of groundwater decline are most severe. The analysis commences with a brief description of the hydrogeology of the RW areas of north-west India and the causes of groundwater decline in this region (Sections 2 and 3). Section 4 then examines 12 on-farm technologies with regard to their potential to contribute toward increasing food production and reducing water use.

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2. The Hydrogeology and Development of Irrigation in North-West India The main rice and wheat producing states of north-west India are Punjab (5.0 Mha), Haryana (4.4 Mha), and western Uttar Pradesh (8.1 Mha). They are largely located in the IGP, a flood plain which is the surface expression of a structural depression located immediately south of the Shiwalik Foothills of the Lower Himalayas and filled with alluvium. The topography is gentle (e.g., average slope of 0.3 m/km in Punjab). Most of Punjab and Haryana are underlain by the Indus River plain aquifer, a 560,000 km2 (56 Mha) unconfined to semiconfined porous alluvial formation that also underlies Rajasthan and eastern Pakistan (Zaisheng et al., 2006 as cited in Rodell et al., 2009). The Ganges plain starts in eastern Haryana. The hydrogeology of the IGP is described by Tanwar and Kruseman (1985). The structural depression forms a deep (>3000 m) trough, but south of a line extending north east from Delhi the basement is at much shallower depth (200–1000 m). The underlying geologic formation is of marine origin (Asghar et al., 2002; Kulkarni et al., 1989). The trough is filled with alluvial material deposited by rivers from the Himalayas. Coarse to fine sediments overlay a thick deposit of clay starting at 50–150 m below the ground surface (Kulkarni et al., 1989). In the north, clayey layers are intercalated in medium sand and gravel deposits (Bowen, 1985), while in the south clay and silt layers predominate, although intercalated with fine sand layers. Despite its large number of clay layers, the whole of the aquifer system can be considered as a single heterogeneous unconfined aquifer. Sometimes the clay layers create semiconfined conditions (leaky aquifers) locally, but the clay layers may also be pervious, especially when they contain large amounts of calcium carbonate nodules (often the case). Annual rainfall declines from around 1000 mm in the hilly north-east portions of Punjab and Haryana to 200 mm in the south west of each state. Average rainfall is higher in western Uttar Pradesh (1000 mm) than in Punjab (780 mm) or Haryana (615 mm). Eighty-five per cent of the rain falls during the monsoon season, from late June to early September, the period when rice is grown. Potential evaporation exceeds rainfall except during the peak of the monsoon in July and August (e.g., Fig. 2). Winters are dry, with only the occasional light shower during the period of wheat growth (November to March). Much of the native groundwater of the Indus basin is saline because of its marine origin, but most of the shallower aquifers were flushed of their salt content in the past. Prior to the introduction of irrigation, the depth to the watertable was 20–50 m. In Punjab, groundwater flows from north east to south west. The groundwater quality changes from good quality in the

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Rice season Rain or pan evaporation (mm)

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200 Wheat season

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0 Nov Dec Jan

Feb Mar

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Figure 2 Longterm (1966–1995) monthly mean pan evaporation and rainfall at Ludhiana, Punjab.

north east to poor quality (highly saline and/or sodic) in the south west, and quality also deteriorates with depth (Hira et al., 1998). The northern foothills region (0.65 Mha) and central plains region (2.5 Mha) have fresh and marginal quality groundwater, respectively, which can be used for irrigation. The groundwater in the south-west region (1.9 Mha) is generally unsuitable for irrigation. In Haryana, the groundwater flows from the north east and south toward the center, and from the center toward the west. The north eastern part of the state is underlain by fresh groundwater, and the remaining 2.8 Mha is underlain by brackish to very saline groundwater. The central basin of 1.7 Mha has no proper surface drainage. As in Punjab, the salinity of the groundwater increases with depth (Kamra et al., 2002). The salinity in shallow aquifers, where this occurs, is a result of mixing with deeper saline water and/or evaporation (Kulkarni et al., 1989). Canal irrigation was introduced by the British in the middle of the nineteenth century, but without provision for proper drainage, and watertables rose rapidly due to deep drainage from the canals, irrigated fields, and rainfall (e.g., Fig. 3). In normal monsoon years in the 1970s, vertical recharge from rainfall was about 90 mm/yr in Punjab and Haryana, and higher (215 mm/yr) in western Uttar Pradesh where rainfall is higher (Datta and Goel, 1977; Datta et al., 1973; Goel et al., 1977). As a result, fresh groundwater lenses now overlie the deeper saline groundwater (Hira and Murty, 1985; Qureshi et al., 2008; Sufi et al., 1998). The thickness of the lenses varies depending on the microtopography, hydrogeology, and proximity of channel distributaries, and is greatest near rivers and canals where the depth to the watertable is least (e.g., Fig. 2 in Qureshi et al., 2008).

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Transmissivity values from well tests range from 170 to 2600 m2/d, and specific yield in the depth range affected by water level fluctuations is 10–15%. The rise in the watertable eventually resulted in waterlogging in large parts of Punjab and Haryana in the mid twentieth century. In 1964 most of the present state of Punjab (except the south west) had a watertable within 3 m of the soil surface, and significant areas had a watertable within 1.5 m (Hira and Khera, 2000). Significant secondary salinization occurred in areas with saline groundwater due to mixing with the overlying fresh water and high evaporation (Ritzema et al., 2008; Uppal, 1966). The salt-affected area in Punjab increased from 0.03 Mha in 1950 to 0.68 Mha in 1965. In the second half of the twentieth century there was rapid expansion in groundwater pumping from tubewells due to the inability of the supplydriven canal system to meet the needs of farmers growing the new high yielding, input-responsive rice and wheat varieties, and strongly supported by many institutional and policy factors (Raina and Sangar, 2004). This led to the rapid increase in rice and wheat production known as the “Green Revolution.” In Punjab, the area of rice increased from 0.39 to 2.48 Mha between 1970–1971 and 2001–2002, while the area of wheat increased from 2.29 to 3.42 Mha over the same period (Takshi and Chopra, 2004). Rice and wheat are now grown in rotation on 1.8 Mha (Abrol, 1999). In Haryana, the rice area increased from about 0.3 to 0.9 Mha between 1970–1971 and 2000–2001, and the wheat area increased from 1.1 to 2.2 Mha over the same period (Ambast et al., 2006), with 0.6 Mha of RW systems (Abrol, 1999). In the whole of Uttar Pradesh there are now

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Figure 3 Groundwater rise at Ran Singh Wala village, Faridkot district in south-west Punjab following the introduction of canal irrigation in the nineteenth century (adapted from Hira et al., 1998).

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about 5.6 Mha of RW systems (Abrol, 1999). Across north-west India, the RW cropping system prevails in regions where rainfall is more than 500 mm and the groundwater has fresh or marginal quality, and in these regions district average tubewell density ranges from 15 to 30þ/km2 (Ambast et al., 2006). The number of tubewells in Punjab increased from 0.1 million in 1960 to 0.9 million in 1997 (Hira and Khera, 2000), and to about 1.2 million in 2008. In Haryana there were more than 600,000 wells and tubewells by 2005 (Sharma et al., 2008a). By 1994 there were 2 million tubewells in the whole of Uttar Pradesh (Chadha, 2004). About 85% of the land area in Punjab is now cultivated with a cropping intensity of 189%, and 97% of this land is irrigated. Two-thirds of Punjab’s rice and wheat are produced in the central zone, where the cropping intensity is 201%. In this region, groundwater is used to irrigate 90–97% of the irrigated area of each district (Sarkar et al., 2009). Across the international border in Punjab, Pakistan, groundwater also provides 70% of the requirements for RW systems (Arshad et al., 2008). In Haryana, cropping intensity in the RW area is 215%, and the state average is 182%. Groundwater supplies 46% of the total irrigated area (Kumar, 2004) and is the main source in the RW areas (Ambast et al., 2006). In western Uttar Pradesh, with a cropping intensity of 157%, 4.2 Mha are irrigated using groundwater (79% of the irrigated area) (Rai, 2004). In the most intensive RW regions, almost all irrigation is now by groundwater (Erenstein, 2009; Sarkar et al., 2009). The rapid increase in groundwater pumping in the RW areas led to a rapid decline in groundwater levels. For example, there were declines of 5– 15 m in the past 20 years in 11 districts across Punjab and Haryana (Ambast et al., 2006). The average depth to the watertable in districts of the central zone of Punjab had increased to 15–28 m by 2006 (Hira, 2009). With no interventions, it is predicted that the watertable will fall below 10 m in 75% of Punjab by 2020 (Takshi and Chopra, 2004). Hira (unpublished data) predicts that by 2025, 42 of 134 blocks (30% of Punjab) will have watertables deeper than 30 m, making it impossible to pump out groundwater using hand pumps or small submersible pumps. Of these 42 blocks, the watertable will fall beyond 40 m in 30 blocks, beyond 50 m in 6 blocks, and to 60–90 m in 4 blocks. In western Uttar Pradesh, the groundwater is declining at 0.1–0.75 m/yr (Rai, 2004). In addition to the problem of groundwater decline in the major RW areas, parts of Punjab, Haryana, and western Uttar Pradesh continue to be prone to waterlogging and salinization, caused by rising watertables in canal irrigated areas where the groundwater quality is too poor for irrigation. However, the waterlogged area in south-west Punjab had declined to just a few thousand hectares by 2003 ( Jose et al., 2004), largely as a result of increased use of the fresh groundwater lens (tapped using skimming wells and shallow tubewells, Hira, 1994), and partly due to the installation of surface drains which drain floodwater from submerged areas to the Sutlej

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River. Almost 50% of Haryana has rising watertables and poor quality groundwater (Kumar, 2004), but with potential to greatly alleviate the problem through reducing canal irrigation and increasing the use of the fresh, shallow groundwater overlying the saline groundwater.

3. Water Sources, Sinks, Depletion, and Savings Keller et al. (1996) used the concepts of sources, sinks, and recycling as a means of understanding water in river basins. The sources of water in a river basin are present precipitation, past precipitation (snow, ice), surface stores (river channels, dams, canals, rice paddies, lakes, ponds), subsurface stores (soil profile, aquifers), diversions from other basins, and desalinization of seawater (Seckler, 1996). The sinks are destinations for water, or conditions of water, from where or which it cannot be reused in the basin; the sinks include the atmosphere, oceans, inland seas, saline aquifers, and water that becomes too polluted for further use. When water is withdrawn from a source and used to irrigate a crop, part of it is lost to the atmosphere sink— by plant transpiration and by evaporation from the soil or from water lying on the soil surface. The remainder drains to surface and/or subsurface storages which may be sources or sinks depending on the condition of the water. Water depletion is loss of water to sinks. “Real” water saving occurs when flows to sinks are reduced.

3.1. Why is the watertable going down in the rice–wheat belt of north-west India? Using a water balance model and 10 years (1989–1998) of Ludhiana, Punjab, weather data, Jalota and Arora (2002) estimated annual average crop ET of 964 mm from the irrigated RW system, exceeding average annual rainfall by 128 mm (Table 1). Deep drainage was 1110 mm, 83% of which occurred during the rice phase. As indicated above, deep drainage in the main RW areas flows to the groundwater system from where it can be reused. Assuming that all of the irrigation is from groundwater, and that all of the deep drainage can be reused, the annual net depletion of the groundwater due to the RW system is equal to ET-rain, or 128 mm. Given an aquifer specific yield of 10–15%, annual water depletion of 128 mm is equivalent to a decline in the groundwater level of 1.28–0.83 m/yr. The actual rate of watertable declines at Gujjarwal (Fig. 1) over that period was much less (0.2 m/yr) as there was some irrigation from the canal system (Arshad et al., 2008), because of recharge across the landscape from rainfall, rivers, canals and canal irrigated fields, and because of net subsurface lateral inflow in the groundwater system.

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Table 1 Simulated evaporation and transpiration (mm) for an irrigated rice-fallow– wheat-fallow cropping system in central Punjab, on a sandy loam soil

Period

Rice Short fallow Wheat Long fallow Total Annual water requirement (EþT)

Surplus/Deficit Rainfall Evaporation Transpiration (Rain-ET)

650 22 122 42 836

217 38 83 97 435 964

292 – 237 – 529

þ 141  16  198  55  128

Extracted from Jalota et al. (2002).

The ET water depletion in the study of Jalota and Arora (2002) was due to transpiration from rice and wheat, evaporation from the soil or water lying on the soil surface during these crops, and soil evaporation during the long and short fallow periods (Table 1). Total rainfall during the rice season exceeded total ET by 141 mm, while total rainfall during the wheat, long fallow and short fallow periods was much less than ET. There are few published measurements of the amount of irrigation water that farmers apply to their fields in the RW systems of north-west India. Based on a survey of 398 farmers using groundwater only in Haryana (Erenstein, 2009), average estimated applications to rice and wheat were 1890 and 220 mm, respectively. On a loam soil in central Punjab, Humphreys et al. (2008a) measured irrigation amounts of 2300–2400 mm to continuously flooded rice, 1400–1800 mm to rice with various forms of alternate wetting and drying (AWD) water management, and 290 mm to wheat. In Punjab, Pakistan, mean irrigation amounts over three seasons ranged from 1100 to 1500 mm for rice, and 150 to 260 mm for wheat ( Jehangir et al., 2007). The data indicate that irrigation of rice is very inefficient given that rainfall usually balances or exceeds crop water use requirement (ET) in north-west India, even after allowing for the fact that the monsoon does not start until 2–3 weeks after the crop is transplanted, an estimated water requirement of 250 mm to saturate the rootzone and meet ET demand during that dry period. Thus irrigation water is currently applied to rice at an order of magnitude higher than the theoretical requirement, due to the physiological requirement of near saturated soil for maximum yield (Bouman and Tuong, 2001), the management and fertility advantages of ponding (for weed control and availability of P and micronutrients such as Fe on coarse textured, alkaline soils), and the use of the paddy field as a water storage to buffer against unreliable water (electricity) supply. In contrast to rice, the amount of water applied to wheat is much

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closer to the theoretical requirement (average ET-rain ¼ 198 mm), however, there will also be some residual soil water available to wheat after rice, reducing the irrigation requirement. These calculations suggest that there is considerable scope to increase the irrigation efficiency of rice in this region, and some scope to increase the irrigation efficiency of wheat, and that the potential gains are far greater for rice. But an even more important question is “what is the potential to reduce water depletion due to flows to sinks from where the water cannot be recovered, and to reduce or halt the decline in groundwater levels?”

3.2. How much water do we need to save to arrest the decline in the watertable? The amount of water that needs to be saved from RW systems depends on the rate of groundwater decline, which varies across the region depending on many factors such as hydrogeology, climate, landuse, and management. From a biophysical perspective, the amount of groundwater extraction should not exceed the amount of recharge to maintain an equilibrium water level in the aquifer at the desired depth. The optimum depth for the RW zones has been suggested to be around 6–7 m (Ambast et al., 2006) and 10 m (Hira and Khera, 2000). The reasons for this depth are not reported, but it is shallow enough to minimize the cost of pumping and avoid the need to dig the deep pits needed to lower the electric motors (which results in many fatalities due to collapse of the pits), and deep enough to avoid loss of groundwater by evaporation and problems of waterlogging and salinization. The amount of water that needs to be saved is equal to the net depletion from the aquifer over the time period of interest, and can be calculated from the product of the rate of decline in the groundwater level and the specific yield of the aquifer. Using Gujjarwal, central Punjab as a theoretical example, with a recent watertable decline of 1 m/yr and specific yield of 15%, the net loss from the aquifer is equivalent to 150 mm/yr. This implies that to stabilize the groundwater at Gujjarwal at the 2005 level (16 m below the land surface), annual water depletion across the landscape needs to be reduced by 150 mm, which is about 15% of the estimated ET. What is the potential for improved on-farm technologies to save this much water?

3.3. Methods for reducing groundwater depletion Many methods have been proposed for arresting the decline in the watertable in north-west India (Hira, 2009). These involve decreasing withdrawal of groundwater by reducing on-farm irrigation requirement and/or increasing recharge.

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3.3.1. Methods for simultaneously reducing withdrawal of groundwater and increasing recharge These methods involve increasing surface water supplies, by measures such as: 

Increasing the canal water supply to central Punjab through the construction of new headworks on the Sutlej River to capture some of the 1  109 to 10  109 m3 of water going to Pakistan during the monsoon, and reviving the old canal watercourses (now ploughed in) in central Punjab; this would reduce reliance on groundwater through increasing surface supply, and increase recharge from the canal system  Construction of small and medium dams in the Shiwalik Hills to increase recharge and provide water for irrigation in Punjab; Grewel and Dar (2004) estimated that 15–20% of the groundwater depletion could be met by such measures By how much these methods would reduce net water depletion from the Indus basin as a whole is an important question. For example, if all the water that flows down the Sutlej River to Pakistan during the monsoon ultimately flows to sinks (such as the ocean), then capture and retention of that water in Punjab, India would indeed reduce water depletion from the basin. However, if some of the water that flows to Pakistan is used directly from the river system, or if it recharges fresh groundwater systems, then retention of that water in India would not save water in the basin. Only about 20% of the annual flow in the Indus Basin in Pakistan now reaches the sea (Qureshi et al., 2008). The Indus Basin is considered to be a closing basin, with most of its water already used, and with increasing demand for water from nonagricultural sectors in the future (Qureshi et al., 2008). Therefore, politics aside and allowing for environmental flow requirements, the potential for reducing net depletion from the Indus Basin by retaining more water in India is questionable and requires further in-depth analysis. 3.3.2. Methods for increasing recharge of groundwater Methods for increasing recharge have been proposed at landscape, village, and urban levels, and include: 

Construction of recharge wells in areas where the groundwater is declining, and where there is a thick restricting layer below the soil surface (Ambast et al., 2006; Kamra, 2004)  Adoption of soil conservation practices in the Shiwalik Hills to reduce runoff and increase infiltration, for example, contour trenches, vegetation barriers, bunding of fields  Rainwater harvesting in cities through the use of grass saver tiles  Renovation of village ponds, which are often silted, to increase infiltration

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Methods for increasing recharge by capturing runoff have been shown to have local impacts on groundwater levels, with benefits to local water pumpers. However, the effect on water depletion at larger scales is less clear, and depends on the amount of runoff that is captured and used elsewhere in the system. Analysis at larger scales is needed. 3.3.3. Methods for reducing withdrawal of groundwater Hira (2009) proposed a range of on-farm technologies that would reduce withdrawal of groundwater:   

Delaying transplanting of rice Diversification from rice to other crops Increasing the efficiency of irrigation water use with technologies such as AWD for rice, laser land leveling, raised beds, and mulching

These and other on-farm technologies are discussed in greater detail in Section 4. There are many anecdotal reports and published papers in the popular and scientific literature indicating lower irrigation requirement (thus reduced withdrawal of groundwater) and higher irrigation water productivity (WPI) with many improved technologies in comparison with conventional practice in RW systems (Erenstein et al., 2008; Humphreys et al., 2005, 2008b; Ram et al., 2005; Sharma and Singh, 2002). However, whether these technologies reduce water depletion and/or increase crop productivity with respect to water depletion, and by how much, are not known. 3.3.3.1. Reducing run off and deep drainage Practices that reduce surface runoff and deep drainage to sinks such as saline groundwater and the sea are important ways of reducing water depletion. This is especially the case in regions such as south-west Punjab and southern Haryana, India, and in parts of Punjab and Sindh, Pakistan, where deep drainage water flows into aquifers that are too saline for use (Qureshi et al., 2008). However, even here the fresh drainage water tends to overlie the saline water in thin freshwater lenses. About 50–75% of the freshwater can be captured and reused using technologies such as skimming wells (Ambast et al., 2006; Asghar et al., 2002; Hira, 2009). Of course, the extraction of the fresh water needs to be done with care to extract as little as possible of the deeper saline water (Kamra et al., 2002). The design of the skimming well, depth of the well (distance from the intake to the fresh/saline water interface), and pumping rate and duration are all important factors in this (Sufi et al., 1998). Furthermore, the amount of salt in the freshwater lens will increase over time, mainly due to the salt in the irrigation water (e.g., addition of 1000 mm of fresh river water with a salinity of 0.3 dS/m adds the equivalent of 19 t/ha of sodium chloride). The rate of salinization of the aquifer can therefore be slowed by management practices that minimize the amount of irrigation water applied. Keeping the watertable deep is critical

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to enable leaching of salt from the root zone. Therefore deep drainage needs to be reduced to an amount lower than the rate of dissipation of the groundwater (by leakage to deeper depths, and/or evaporation in the case of shallow watertables, and/or shallow groundwater pumping). Thus, in areas underlain by saline groundwaters, it is critical to employ technologies that reduce deep drainage. The effects of improved technologies on the amount of deep drainage will vary greatly with site conditions (soil type/permeability, presence of a hard pan, degree of soil cracking, depth to the watertable) and with irrigation system design (size of irrigation bays relative to irrigation flow rates, which affects the duration of irrigations). It will also vary depending on water management of the current practice (e.g., whether rice is grown with continuous flooding or AWD). Where surface runoff from individual fields can be captured and reused “downstream,” and where deep drainage can be used by groundwater pumpers, these losses from individual fields are actually flows to water sources and not losses from the system at larger spatial scales (Hafeez et al., 2007; Loeve et al., 2004). This is the case in much of the RW belt of north-west India, because the whole of the IGP is underlain by a single, unconfined aquifer (Section 2). Furthermore, in canal irrigated areas, deep drainage to groundwater protects the water source from loss by evaporation, provided that the watertable is not shallow (Hafeez and Khan, 2006; Khan et al., 2006; Young et al., 2007), and is often the source of water for farmers with inadequate or no canal supply. The evaporative loss of water from the groundwater depends on the depth to the watertable and soil type (Raes and Deproost, 2003; Rasheed et al., 1989). Reducing deep drainage in farmers’ fields will reduce pumping costs, pollution of groundwater, and leaching of nutrients, and should be strongly encouraged. However, it will not halt the decline in groundwater levels in the major RW growing areas of north-west India. Here it is critical to develop and adopt technologies that also increase production per unit of evapotranspiration (WPET). 3.3.3.2. Reducing ET and increasing WPET Reducing ET and increasing WPET is beneficial in all water-limited situations. In groundwater irrigated areas where ET is the only source of water depletion and food production needs to be increased, it is critical. There are several ways that WPET can be increased:

i. increase yield and reduce ET The ideal would be technologies that increase WPET by simultaneously increasing yield and reducing ET, providing the means to both increase food production and reduce water depletion. This is possible with improved technologies in some situations, as was the case with subsurface drip

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irrigated maize in south eastern Australia (O’Neill et al., 2008). However, in general, it is difficult to increase yield without increasing ET because of the strong, positive linear relationship between transpiration and dry matter production (e.g., Farquhar and Richards, 1984; Haefele et al., 2008), together with the fact that dry matter production is an important determinant of yield of cereals up to some optimal level of biomass (e.g., Akita, 1989; Reynolds et al., 2007; Tollenaar, 1991). When yields are at or above about 50% of their potential, yield gains come at a near proportionate increase in ET (Molden et al., 2010). Thus, unless starting at very low yield levels, technologies that increase yield are generally likely to result in higher transpiration and higher ET, unless the yield increase is simply a result of increased harvest index due to factors such as avoidance of heat or cold damage at sensitive reproductive stages. ii. maintain yield and reduce ET Examples of technologies that increase WPET by reducing ET while maintaining yield in north-west India include delaying rice transplanting date (Section 4.2), and growing shorter duration varieties (Section 4.3). As most of the cultivable land in the major RW areas of north-west India is already used, there is little scope for increasing food production with such technologies alone. iii. increase yield and increase ET, but with a proportionately larger increase in yield Technologies that increase WPET by increasing both yield and ET, but which increase yield by more than ET, can also be used to increase food production and reduce ET by reducing the cropped area to the optimum level, but this would be difficult to implement in north-west India for socioeconomic reasons. Furthermore, the impact on water depletion from the noncropped land (and which will be affected by management of that land, e.g., weedy fallow vs. bare fallow vs. cultivated fallow) also needs to be considered, in a landscape scale analysis of WPET. iv. increase yield and maintain ET Technologies that increase WPET by increasing yield while maintaining ET could also serve the dual purpose of increasing food production and reducing water depletion if the total cropped area is reduced, but would be difficult to implement as above (iii). v. reduce yield and reduce ET, but with a proportionately larger reduction in ET Technologies that increase WPET by reducing both yield and ET, with higher reductions in ET, are undesirable if food production is to be increased.

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4. Effects of Improved Technologies on Yield, the Nature and Amount of Water Savings, and Water Productivity This section reviews the findings to date on the effects of a wide range of technologies on yield, components of the water balance, and water productivity. The components of the water balance considered are irrigation, deep drainage, and ET (partitioned into evaporation and transpiration where possible). The measures of water productivity discussed here are with respect to irrigation (WPI) and ET (WPET). Where available, field data are presented. However, it is difficult in field studies to separate most components of the water balance, and few researchers have attempted this. In some cases, the separation has been done using crop models, usually calibrated and validated for the relevant environment and application, and with the advantage of being able to assess performance of the technology over a range of seasonal conditions. The review shows that while there is a considerable amount of data on the impacts of many technologies on yield, irrigation amount and WPI in comparison with conventional practice, this is not the case for all technologies. Furthermore, there have been very few attempts to determine the nature of any irrigation water savings, and in particular, to determine ET and WPET. The main findings of the review are summarized in Table 2. Before discussing the potential benefits of the “improved” technologies, it is important to recognize that there is considerable scope to increase land and water productivity of the RW system through improved agronomic management while retaining current cultural practices (PTR followed by wheat grown using zero till or conventional tillage). District average farmer yields of rice and wheat in Punjab, Haryana, and western UP are considerably below achievable yields on research stations, and 40–70% below potential yields (Pathak et al., 2003; Timsina et al., 2004). The yield gap between the best practice and the farmers’ practice was 18.6% in the north western plains under the frontline demonstration program (Anonymous, 2009a). The gaps between research station and farmer yields indicate considerable scope for increasing food production simply by greater adoption of recommended crop management practices. This would also result in large increases in water productivity with respect to both irrigation and ET. In particular, improved management of continuously flooded PTR is likely to have small or negligible effects on irrigation amount and ET, while increasing yield and thus WPI and WPET. The situation with regard to WPI and WPET of wheat is less clear, and will depend on whether the increase in yield as a result of improved management is greater than any increases in irrigation amount and ET. There is also considerable scope to increase yields of rice, wheat, and alternative crops in the medium term through varietal

Table 2 Estimated impacts of improved technologies on components of the water balance and water productivity in comparison with conventional practice (see Section 4 for explanation)

Section 4 location

Rice 4.1 4.2

Technology

Irrigation

Laser leveling Delayed transplantingb

&100–200 mma & as for irriga þ 0–6% & 75 mm 20 Negligible Negligible May–20 Jun & 75 mm 20 Jun–20 Jul & up to 270 mma,c & up to 200 mma,c Negligible or decrease as for irriga Negligible 200–800 mma ?a & 200–500 mma & 500–800 mma & 300–500 mma

?a & as for irriga & as for irriga & as for irriga

& 50–100 mma & 30–100 mma

& as for irriga ? low rainfall so little deep drainage

4.3

Short duration riceb

4.4

Alternate wetting & drying Zero till transplantb Dry seedingb Aerobic rice Transplanted rice on fresh beds

4.5 4.6 4.6 4.7 Wheat 4.1 4.8

Laser leveling Zero till

Deep drainage

Yield

Effect on rate of groundwater decline

ET

WPET

Negligible & 75 mm & 75 mm

Small increase þ 15% þ 15%

Negligible Large reduction

& 70 mm

þ 20%

Large reduction

Negligible

Negligible

Negligible

Negligible & 0–20% & 30–40% & 10%

Negligible Negligible Decrease Negligible

Negligible & 0–20% ? Small decrease

Negligible Negligible Negligible Negligible

þ 0–20% þ 5%

? ?

? ?

Small reduction Small reduction

(continued)

Table 2

(continued)

Section 4 location

Technology

Irrigation

Deep drainage

Yield

4.9

Mulching of wheat

& 0–40 mm

Negligible

& 100 mm

& as for irriga

Negligible unless Negligible water limiting (increase) þ5% ? Small increase

& 200 mm & 250 mm & 450–500 mm

& as for irriga & as for irriga & as for irriga

230–240 mm 210–250 mm & 50–70 mm

4.10 Wheat on beds Alternatives to rice–wheat 4.11 Sugarcane 4.11 Cotton–wheat 4.11 Maize–wheat

ET

WPET

Effect on rate of groundwater decline

Negligible unless Negligible water limiting (increase) Negligible Negligible Large increase Large increase Medium reduction

Numbers in the tables should be regarded as indicative only, and are derived from the limited available data reported in the text. & 50 mm indicates a decrease of 50 mm; þ 50 mm indicates an increase of 50 mm; ? indicates insufficient data or knowledge to estimate the impact. Comments in italics are suggested impacts based on current understanding, but for which no data are available. a Magnitude of the reduction will depend on many factors, especially soil permeability, depth to watertable, and water management. b Same irrigation scheduling criteria/water management as conventional practice. c Data for a loamy sand—more permeable than a typical rice soil.

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improvement. For example, by breeding for higher yield potential, improved disease and insect resistance, and tolerance to heat during the reproductive stages. However, neither improved varieties nor improved management using current cultural practices address the sustainability problems of resource degradation, labor scarcity, pollution, and water scarcity. Hence there is a need for technologies which seek to address these and other problems, and also the need for the development of improved varieties suited to these improved technologies.

4.1. Laser leveling Despite the fact that fields for RW systems are puddled and leveled every year prior to rice transplanting, the soil surface is often very uneven, resulting in excessive water application to enable the highest portions of the field to be flooded for rice, or wetted during irrigation of wheat. In a recent survey of 300 farmers’ fields in Punjab, India, the difference between the highest and lowest parts of the fields ranged from 8 to 25 cm (H.S. Sidhu, unpublished data). Jat et al. (2006) reported leveling indices (LIs) of up to 13 cm in farmers’ fields in Ghaziabad, where LI is the mean deviation between the desired elevation and the actual elevation. LI increased rapidly with field area up to 1 ha. In 50 m  5 m replicated irrigation blocks on a reclaimed sodic soil, Tyagi (1984) found that the irrigation amount required to cover the block increased from 42 to 95 mm as LI increased from 1 to 7 cm. Average wheat yield decreased from 3.1 to 2.2 t/ha as LI increased from 1 to 7 cm, and the decline in yield was attributed to increased waterlogging (the estimated time for the surface water to disappear was 7 d with LI¼5 compared with 2 d for LI¼1). In 71 farmers’ fields in Punjab, Pakistan, laser guided leveling gave an average reduction in irrigation amount of 76 mm (21%) and an average yield increase of 0.6 t/ha (15%) for wheat (Kahlown et al., 2006). In 71 farmers’ fields in western Uttar Pradesh, India, laser leveling gave reductions in irrigation amount of 50–100 mm in wheat and of 100–150 mm in rice ( Jat et al., 2006). Assuming irrigation applications of 300 mm to wheat and 2000 mm to rice with conventional leveling, this represents irrigation reductions of 17–30% for wheat, and 5–8% for rice. Mean WPI in both crops was increased by about 20% with laser leveling due to reduced irrigation amount and higher yield (by 9% in wheat, 6% in rice). In a small plot replicated experiment on a sandy loam soil in western Uttar Pradesh, laser leveling did not result in significantly higher yields of rice or wheat, however, the total crop system yield with lasering was significantly higher (by 7%) in the second year ( Jat et al., 2009), demonstrating the importance of considering the total system as well as individual crops in the rotation. Total irrigation was lower in the lasered treatment compared with conventional leveling, by about 200 mm (12–23%) in rice and 40 mm (9–13%) in wheat.

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Studies to explain the effects of laser guided leveling on either crop performance or components of the water balance are lacking. The higher wheat yields are probably due to improved soil water status (reduced water logging and/or reduced water deficit stress due to removal of low and high spots). The net effect on ET is likely to be negligible in both flooded rice and wheat. The higher wheat yields probably reflect improved crop growth and thus greater transpiration, while evaporation is likely to be reduced due to reduced duration of free water on the soil surface (due to faster irrigation time and removal of depressions where water would pond after rain or irrigation). It is likely that much of the irrigation water saving in the above studies was due to reduced deep drainage. In that case, the size of the irrigation water saving will depend greatly on soil type, depth to the watertable, and duration of irrigation (which depends on irrigation flow rates in relation to field size). There are no reports of the effects of these factors on the irrigation water savings due to laser leveling in the RW regions. In addition to large reductions in irrigation amount and higher yields, laser leveling has many other benefits including increase in the cultivable area and greater efficiency of machinery operations and inputs (due to reduced overlap of machinery passes and reduced “misses”) ( Jat et al., 2006). Large areas are likely to be laser leveled in the RW systems of the IGP over the next decade, based on initial adoption rates. Laser leveling commenced in western Uttar Pradesh in 2003, and by February 2006, 37 farmers owned laser levelers, and 10,000 acres had been leveled across 10 districts ( Jat et al., 2006). However, the most rapid rates of expansion are now occurring further west. In 2005, about 70,000 ha had already been leveled in Punjab, Pakistan, using laser technology ( Jat et al., 2006). A project was implemented by the Punjab provincial government in 2006–2008 which was to provide 1500 laser units (50% subsidy) with the goal of leveling 0.3 Mha during the life of the project, and Jat et al. (2006) projected that within 10 years about 1.8 Mha would have been laser leveled. Laser leveling is just beginning in Punjab, India, with more than 2000 laser units in that state in August 2009, subsidized by the government (25% in 2008, 33% in 2009) (H. S. Sidhu, personal communication). 4.1.1. Summary—Laser leveling Large reductions in irrigation amount and increases in WPI as a result of laser assisted land leveling have been reported from many farmers’ fields in the north-west IGP, with irrigation water reductions of the order of 100 mm in both rice and wheat, but results are variable. The irrigation water savings are likely to be due to reduced deep drainage, and will therefore vary with site conditions, irrigation system design, and water management. There is no information in the literature on the effects of site conditions on the effects of laser leveling on irrigation water use and WPI, nor on the effects of laser leveling on ET and WPET—WPET could

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increase or decrease depending on effects on crop biomass and harvest index. Laser guided land leveling provides many important benefits for farmers, however, it is unlikely to reduce water depletion and groundwater table decline in the major RW areas where groundwater is used for irrigation. On the other hand, in canal irrigated areas, laser leveling will be very beneficial in reducing the rate of watertable rise and thus the amount of waterlogging and secondary salinization. The reduced irrigation requirement will make more canal irrigation water available for other uses.

4.2. Planting date Shifting planting to a date when a crop can grow under reduced evaporative demand while maintaining yield, and without jeopardizing the ability to sow the next crop at the optimum time, can significantly reduce ET and increase WPET. This is especially the case in north-west India for crops planted prior to the onset of the monsoon. Many field and modeling studies and Department of Agriculture Statistics show that the yield of transplanted rice is relatively stable over a wide range of transplanting dates from early May to mid June or later, although some studies show a yield decline for transplanting after mid June (Arora, 2006; Chahal et al., 2007; Hira and Khera, 2000; Jalota et al., 2009; Khepar et al., 1999). Many studies also show large reductions in ET by delaying transplanting in north-west India from early May to early July. Using 36 years of weather data at Ludhiana and potential ET calculated by the modified Penman method and crop factors as suggested by Doorenbos and Pruitt (1977), Khepar et al. (1999) estimated that ET of rice between transplanting and harvest (duration 110 d) declined from 700 to 490 mm as the date of transplanting was delayed from 1 May to 1 July. Irrigation amounts were least with 1 July transplanting, the date which resulted in the greatest rainfall interception and relatively low ET during the cropping season. Using ORYZA2000 on a sandy loam at Ludhiana, Arora (2006) found that ET of continuously flooded rice decreased from 758 to 569 mm as transplanting date (PR114) was delayed from mid May to 1 July. Jalota et al. (2009) found a reduction in ET of PR 118 (120 d transplanting to maturity) of about 70 mm by delaying transplanting from 25 May to 25 June with safe AWD water management (irrigation 2 d after floodwater dissipated), using the CropSyst model on a loamy sand. Using the CROPMAN model, Chahal et al. (2007) found that delaying transplanting to mid June or later provided more favorable temperatures (reduced heat stress) and reduced risk of rain during flowering. Later rice planting also widens the window between wheat harvest and rice planting and thus increases the ability to include a third crop, such as a short duration pulse, in the RW system (Section 4.12). Until recently, the recommended practice in Punjab was to transplant around mid June to save water and electricity. However, in reality, farmers

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staggered transplanting from early May to the end of June because of limited labor availability, increased pest pressure on later planted crops, and limited availability of electricity for pumping (Hira and Khera, 2000; Singh, 2009). Between 1990 and 2004, 24–64% of the rice crop was transplanted before 31 May, and 49–66% by 15 June (Singh, 2009). During 2006 and 2007, a mass campaign was begun to educate farmers to delay rice transplanting to June 10 or later, and to appeal to the Punjab State Electricity Board to provide 8 h of electricity per day to tubewells from this date onwards (and several hours of electricity were provided every day). The Punjab Preservation of Sub Soil Water Ordinance was implemented in 2008, on the initiative of the Punjab State Farmers’ Commission (Singh, 2009). The Ordinance prohibited planting seedling nurseries prior to 10 May, and transplanting rice prior to 10 June. Farmers who did not comply had their crops ploughed in and were required to pay for the cost of the diesel used to do this. The Ordinance was converted to an Act in March 2009, and a similar Act was passed in Haryana. As a result, the area transplanted by 31 May in Punjab decreased to 1.2% in 2008, while the area transplanted before 15 June decreased to 23%. Based on one year’s data and historic transplanting patterns, rainfall, and groundwater levels, Singh (2009) estimated that implementation of the Act reduced the long-term rate of decline in the groundwater level by about two-thirds, or 30 cm/yr. The saving in electricity due to the Act was estimated to be 1.22  109 Rs/yr ($24 million/yr) (Singh, 2009). Hira (2009) predicted that further delaying the transplanting date from 10 June to 15, 20, 25, and 30 June would reduce the average watertable decline rate from 64 cm/yr to 51, 39, 29, and 20 cm/yr, respectively. 4.2.1. Summary—Rice transplanting date Delaying the transplanting date to mid June will significantly reduce water depletion as ET, while maintaining yield, with important benefits in both groundwater irrigated areas (reduced depletion of the groundwater) and canal irrigated areas (more canal water available for water short areas). The effect of delaying transplanting on deep drainage will be small unless crop duration is significantly affected. As current rice varieties in north-west India are not or only slightly photoperiod sensitive, there will be little effect of changing transplanting date on crop duration. Major constraints to further reducing water depletion by delaying the transplanting date from 10 to 30 June are lower yields for transplanting after mid June, and the lack of labor to transplant millions of hectares of rice over a much shorter time period than has been the case in the past. Mechanical transplanting could potentially solve the latter problem, however, to date attempts to mechanize transplanting in puddled fields have not been successful in north-west India, with negligible farmer uptake. However, mechanized transplanting in nonpuddled fields is a promising new technology (Section 4.4), and would help solve the problem of labor shortage.

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4.3. Varietal duration Reducing varietal duration reduces irrigation water use through decreasing both ET and deep drainage. Using CropSyst on a loamy sand (not a typical rice soil), Jalota et al. (2009) found that ET was reduced by about 70 mm with a short duration hybrid (RH257, 90 d from transplanting to maturity) in comparison with the longer duration PR 118 (120 d), while deep drainage was reduced by about 200 mm. The recently released rice variety PAU 201 matures 15 d earlier than many of the current popular long duration varieties, and yields 20–25% more. Thus shifting to varieties with shorter duration, with similar or higher yield, is a real possibility to reduce both irrigation amount and ET while increasing WPI and WPET. The reduction in ET will reduce groundwater depletion in groundwater irrigated areas, and the reduction in deep drainage will reduce watertable rise in canal irrigated areas.

4.4. AWD in rice Traditional lowland rice production involves flooding, puddling, and transplanting, and the fields are normally kept flooded until shortly before harvest. Rice performs best when grown under continuous flooding or in saturated soil, and yield declines as the soil dries below saturation, with a critical threshold of around 10 kPa (Bouman and Tuong, 2001). AWD (also known as “intermittent irrigation”) involves flooding the field with a shallow depth of water, say 5 cm, and then waiting for a few days after the floodwater has dissipated before irrigating again. AWD reduces seepage and deep drainage losses, more so on more permeable soil (Tuong et al., 1994). With careful management (“safe AWD”), there is no yield loss compared with continuously flooded rice. Safe AWD incorporates shallow ponding for the first 2 weeks after transplanting, and during flowering, to avoid water deficit stress during these sensitive stages. Yield is maintained if the perched watertable is not allowed to fall below about 15 cm below the soil surface the rest of the time. The actual safe depth varies with soil type, but this has not been quantified, and 15 cm is the upper threshold across all soils. Safe AWD is a proven technology for the tropics and subtropics, with practical guidelines for its application using a simple, low-cost “field water tube” (Bouman et al., 2007a) now known as the “panipipe” in Bangladesh and India. It is widely practised in regions of China where there is now irrigation water scarcity (Li and Barker, 2004), and is also the recommended practice in many countries or regions including the IGP of India and Bangladesh (e.g., Anonymous, 2009b; Sandhu et al., 1980; Sattar et al., 2009), the Philippines, and Vietnam. There are many reports from small plot studies in the IGP showing large irrigation water savings (15–40% of the applied water or up to 840 mm) with AWD in puddled transplanted rice

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(PTR) in comparison with continuous flooding, and with no or only small effects on yield (e.g., Choudhary, 1997; Hira et al., 2002; Humphreys et al., 2008a; Sandhu et al., 1980; Sharma, 1989, 1999). The reported irrigation water savings from north-west India are likely to be overestimates in comparison with the situation in farmers’ fields because of disproportionately high underbund seepage from small plots where measures to reduce seepage were not implemented (Humphreys et al., 2008a; Tuong et al., 1994). The irrigation water savings are much larger on the permeable soils with deep watertables in north-west India than on soils of low permeability and/or where watertables are shallow (Belder et al., 2004, 2007; Cabangon et al., 2001). There are a few modeling studies, but very few field studies, which have attempted to determine the nature of the irrigation water savings as a result of AWD in comparison with continuously flooded PTR. On a clay loam in Punjab, Sudhir-Yadav et al. (2010a) observed a consistent trend for declining ET as water management changed from continuous flooding to irrigation scheduled at 20, 40, and 70 kPa, however, the differences were not significant. The main causes of the 50% reduction in irrigation amount in going from continuous flooding to AWD were reduced deep drainage and seepage, plus reduced runoff in one year, and reduced ET in the other year. Arora (2006) used the ORYZA2000 model to compare continuous flooding and AWD for PTR on a sandy loam for 12 years of weather data at Ludhiana, Punjab. The AWD treatment involved continuous flooding for 2 weeks after transplanting, and thereafter irrigation (50 or 75 mm) 2 d after the disappearance of free water from the soil surface. AWD reduced the average (over 12 years) irrigation amount by about 350 mm or 25–30%, but ET was only reduced by about 30 mm. Average water productivity with respect to ET (WPET) was about 5% lower with AWD, while input water productivity (WPIþR) was about 8% higher with AWD due to reduced deep drainage. Belder et al. (2007) and Bouman et al. (2007a,b) also found only very small effects of safe AWD on ET and small to large effects on irrigation amount and deep drainage for PTR in the Philippines and China using ORYZA2000. The reduction in irrigation with AWD was due to reduced drainage, and was highly dependent on rainfall, soil type, and depth to the watertable. While AWD is the recommended practice in India, in reality farmers irrigate according to the availability of water (in canal irrigated systems) or electricity (which is highly subsidized, or even free to farmers in some states such as Punjab) for groundwater pumping. The availability of electricity to rural areas is unreliable and limited to a few hours every day or so, therefore farmers pump continuously whenever free electricity is available because of the uncertainty as to when it will next be available. Thus there is little incentive, and high risk, with adoption of AWD by groundwater pumpers who have access to electricity. Farmers are concerned that if the soil dries to the degree that it cracks, then irrigation requirement will be greatly increased. However, where farmers are dependent on diesel (for which

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they have to pay) to pump groundwater, safe AWD would be a useful technology for minimizing irrigation water (and diesel) use while maintaining rice yield. Hira (2009) proposed charging the full price for electricity to provide an incentive to farmers to irrigate more efficiently, and using half of the income from selling electricity to provide bonuses for rice and wheat. If Punjab State Electricity Board is able to supply 6–8 h of electricity per day to tubewells from 10 June onwards (introduced in 2009), this would enable farmers to practice safe AWD. The distribution of water in the canal systems of north-west India is based on a rotational system known locally as “Warabandi,” and described in detail by Khepar et al. (2000). The canal water may only be available to individual farmers every couple of weeks. Farmers in the lower reaches get much less water per unit area than farmers in the upper reaches because the duration of supply at each farm outlet is in proportion to the holding size, without considering seepage losses from head to tail of the system. Infrequent, unreliable, and inadequate water supply means that it is logistically impossible for farmers reliant on canal irrigation to adopt safe AWD. Furthermore, the cost of canal irrigation water is low (US$2.7/ha in Haryana, Erenstein (2009); US$8.2/ha in Punjab in 2009, up from US $3.8/ha in 2007), so there is no incentive for farmers with better access to water in the upper reaches to save irrigation water. The extent of adoption of safe AWD in the IGP is unknown, but it is likely to be small, in both canal and groundwater irrigated areas, for the above reasons. Where AWD occurs, it is likely to be because the farmers have no other choice because of lack of rain and electricity or canal water, that is, it is “unmanaged” AWD and thus likely to result in yield loss due to water deficit stress (Bouman and Tuong, 2001). 4.4.1. Summary—Safe AWD for rice Safe AWD maintains yield while giving very large irrigation water savings in transplanted rice on permeable soils with deep watertables, in comparison with continuously flooded rice. The reduction in irrigation amount is likely to be due to reduced deep drainage, with little effect on ET and WPET. Conversion from continuously flooded rice to safe AWD will help conserve irrigation water for other uses and reduce watertable rise in canal irrigated areas, but will have little effect on the rate of groundwater depletion in the groundwater irrigated areas. In practical terms, adoption of safe AWD is generally not possible for farmers dependent on canal irrigation or electricity for groundwater pumping because of unreliable and limited supply of water or electricity. There is no incentive to adopt safe AWD because of the low prices of water and electricity. However, safe AWD would be beneficial for farmers who purchase diesel to pump groundwater. Areas where diesel powered pumps are commonly used should be identified and the technology could be promoted immediately.

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There is a need for institutional and policy changes to encourage farmers to adopt safe AWD. In canal irrigated systems, adoption by farmers upstream would improve canal water supplies for downstream farmers. However, this would result in reduced groundwater recharge in upstream reaches, with potential effects on “downstream” farmers dependent on groundwater for irrigation.

4.5. Zero till transplanted rice Mechanical transplanting into noncultivated soil (zero till transplanting) has recently been shown to be a very promising technology for establishing rice in north-west India, with major benefits including large savings in energy and labor, and regular plant spacing (Malik and Yadav, 2008; Sharma et al., 2003, 2005). The technology is particularly relevant to north-west India at present because of the rapidly escalating labor scarcity for transplanting as a result of the National Rural Employment Guarantee Act (2007). This Act promises 100 d paid work in people’s home villages, while transplanting of rice in north-west India has been dependent on millions of migrant laborers from eastern Uttar Pradesh and Bihar. Whether zero till transplanting results in water savings in comparison with transplanting into puddled soil, and the nature of those savings, has not been established. Puddling is practised in rice culture for many reasons including weed control, ease of transplanting, and to help maintain standing water in the field by reducing drainage beyond the rootzone. The relative importance of these benefits varies with many factors such as climate, soil type, and local cultural practices. Reducing deep drainage is most important on coarse textured soils such as those in north-west India, where infiltration rates are very high in the absence of puddling (e.g., 30 mm/d on a sodic silty loam at Modipuram, Uttar Pradesh, Sharma et al., 2002; 72 mm/d on a silty loam in Haryana, Sharma et al., 2004b). The reduction in infiltration rate (and thus of deep drainage) as a result of puddling depends on soil type, depth to the watertable, intensity of prepuddling tillage and puddling, and depth of the floodwater (Adachi, 1992; Cabangon and Tuong, 2000; Gajri et al., 1999; Kukal and Aggarwal, 2002; Kukal and Sidhu, 2004; Kukal et al., 2005; Sanchez, 1973). Thus, with the same water management from transplanting to harvest, deep drainage from puddled fields during this period is likely to be lower than from nonpuddled fields. The magnitude of the difference will depend greatly on water management and site conditions such as soil type, degree of soil cracking at the time of rice establishment, and depth to the watertable. While puddling reduces deep drainage after transplanting, it can also require a large amount of water to undertake the puddling operation, typically 150–250 mm to saturate and flood the soil (Tuong, 1999). In some parts of Asia, there is also a long prepuddling soil soaking period for a

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range of logistical reasons (Cabangon et al., 2002; Tuong, 1999). During this period, large amounts of water can be lost as evaporation and deep drainage. The amount and size of soil cracks has a large influence on deep drainage (Cabangon and Tuong, 2000; Liu et al., 2003; Tuong et al., 1996). Furthermore, the cracks do not necessarily close during soaking and ponding, and may continue to conduct large amounts of water to depth until they are closed by puddling (Ishiguro, 1992; Tuong et al., 1996). Long soaking periods are common in canal irrigation systems where flow rates are inadequate, and where the irrigation water supply is from field to field instead via distributary channels. However, in the major RW regions of north-west India, farmers have installed tubewells to have ready access to water (e.g., an average of 1.8 tubewells per household in Haryana, Erenstein, 2009). Therefore they can normally irrigate and complete puddling within a couple of days, and the irrigation water savings from avoiding puddling for transplanted rice are likely to be small as the field also needs to be soaked prior to zero till transplanting. Furthermore, in both systems, the field needs to be shallow-flooded for a couple of weeks after transplanting for good establishment. There are few studies comparing water use in puddled and non-puddled transplanted rice. Singh et al. (2001) compared zero till and PTR using the same water management—the soil was always saturated, with floodwater depth ranging from 0 to 5 cm. In their 3 year RW experiment in small plots on a sandy loam at Delhi, they found that PTR used on average 125 mm less irrigation water than transplanted rice in nonpuddled soil. Importantly, their irrigation measurements included the prepuddling irrigations, which is not often the case in reports on water use in PTR in north-west India. Given the large irrigation water savings possible with safe AWD, it is also important to compare puddled and zero till transplanted rice under these conditions. Puddled soils tend to crack upon drying; the rate and size of crack development depends on the rate of drying, the amount of clay with shrink/swell properties, and the potential for consolidation of the puddled layer (Cabangon and Tuong, 2000; Ringrose-Voase and Sanidad, 1996; Ringrose-Voase et al., 2000). The cracks grow as the soil dries, which in turn increases the rate of drying as a result of exposure of the crack faces to the atmosphere. Sanchez (1973) found that topsoil drying and cracking 30 d after transplanting, followed by AWD, greatly reduced root development and yield, whereas topsoil drying and cracking 60 d after transplanting had no effect on root development and increased yield. Irrigation water use and deep drainage losses can be much higher once the soil cracks due to bypass flow (flow through vertically continuous macropores) (Cabangon and Tuong, 2000; Sanchez, 1973; Wopereis et al., 1994). Anectodal evidence from India is that cracking commences much sooner in puddled soil than nonpuddled soil. This implies that the safe AWD irrigation interval for PTR may be less than for zero till transplanted rice, which may result in

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irrigation water savings with zero till transplanted rice. Bhushan et al. (2007) compared these two tillage methods in small plots on a silty loam soil at Modipuram, using the same AWD irrigation scheduling rule for both methods (irrigate to a floodwater depth of 5 cm at the first appearance of hairline cracks). In 2002 (which was very dry for the first 2 months), the total amount of irrigation applied to both the puddled and zero till treatments was similar (3050 mm). In 2003 (rains well distributed), there was an 8% reduction (150 mm) in irrigation water use with zero till transplanted rice. The nature of the irrigation water savings was not determined. Yield and yield components of zero till and PTR were similar in both years, therefore it is likely that transpiration was similar in both treatments. To date there are no other published data on water use in zero till transplanted rice compared with PTR. 4.5.1. Summary—Zero till transplanted rice There are insufficient data to predict the impact of changing from puddled to zero till transplanted rice on components of the water balance and measures of WP. The impact needs to be assessed based on optimum irrigation management for each system, and the impact on deep drainage is likely to vary greatly with soil type (permeability, tendency to crack), amount of soil cracking at the time of establishment, and depth to the watertable. The impact on ET is likely to be small.

4.6. Dry seeded rice with AWD Dry seeding provides another mechanical and potentially simpler option for establishment of rice than mechanical transplanting. In dry seeded rice (DSR), the seed is normally drilled into soil tilled in a similar way to conventional tillage for wheat, but it can also be sown using zero tillage (e.g., Bhushan et al., 2007). Water management for DSR can vary from continuous flooding (after establishment) to frequent irrigation (with the goal of similar yield to that of continuously flooded PTR or DSR—that is, DSR with safe AWD) to infrequent irrigation (for situations where lack of irrigation water limits rice yield) to rainfed. 4.6.1. Frequently irrigated DSR There is currently a lot of interest in DSR in north-west India because of the reduced labor requirement. DSR is also attractive to farmers because of the lower irrigation requirement of DSR with AWD than continuously flooded PTR, especially given the reluctance of farmers to adopt PTR with AWD due to concerns about soil cracking if irrigation water (electricity) is not available as needed. In the central to eastern Ganges Plains, where rice establishment is often reliant on the start of the monsoon, dry seeding can provide the opportunity for timely establishment on the first rains (usually

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one to two supplementary irrigations are needed after sowing) prior to the onset of the monsoon proper, rather than waiting for sufficient rain to be able to puddle and flood the soil for transplanted rice. Often the monsoon is late relative to the optimum time for transplanting, resulting in transplanting of seedlings older than the optimum age, and terminal drought due to cessation of the rains prior to maturity of late planted crops. The late rice harvest also delays establishment of wheat beyond the optimum date, lowering wheat yield. However, in north-west India, the optimum time for establishment of DSR is a few weeks prior to the normal start of the monsoon, at a very hot time of year when evaporative demand is very high (typical pan evaporation 8-12 mm/d, Fig. 2). Furthermore, the duration of DSR in the main field is longer (by 2–5 weeks) than the duration of transplanted rice (Cabangon et al., 2002; Sudhir-Yadav et al., 2010b), suggesting that ET of DSR will be higher than ET of PTR. On the other hand, anecdotal reports from farmers and researchers are that the safe AWD irrigation interval in DSR can be much longer than in PTR because the puddled soil cracks much sooner and more strongly. On a clay loam soil in Punjab, Sudhir-Yadav et al. (2010a) observed that the soil water tension at 17–20 cm depth increased to 20 kPa 1–3 d earlier in PTR than DSR, and that crack formation usually started just 1 d after irrigation during the early growth stage when there was little plant cover and hot, dry weather. The longer irrigation interval may result in lower irrigation water use in nonpuddled soil, while the lack of puddling may increase deep drainage and thus irrigation amount. The net result will depend on site conditions, and in the few cases where it has been determined, irrigation amount was reduced with DSR compared with PTR with the same AWD irrigation scheduling (Bhushan et al., 2007; Jat et al., 2009; Sudhir-Yadav et al., 2010a). Bhushan et al. (2007) compared PTR and zero till DSR in small plots on a silty loam at Modipuram. The DSR was sown on the same day as the nursery for PTR. They used the same irrigation scheduling rules for both establishment methods, daily irrigation for the first 2 weeks after transplanting or sowing, followed by irrigation when hairline cracks appeared. There was a 20% reduction in irrigation application with DSR compared with PTR in both the poorly and well-distributed rainfall years. Yields were similar in both treatments in the first year (>7 t/ha), although yield was achieved in different ways—much higher tiller and panicle density and lower floret fertility in DSR compared with PTR. Yield of DSR was significantly lower than of PTR in the second year (by 13%). Sharma et al. (2005) also reported similar yields (>6.5 t/ha) for DSR and PTR. On a sandy loam at Modipuram with similar irrigation management to that of Bhushan et al. (2007), Jat et al. (2009) also found reduced water input (irrigation plus rain) by 9–24% with DSR (zero till or cultivated) in comparison with PTR. The magnitude of the saving was similar in both lasered and nonlasered treatments. Yields of DSR in the second year were

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significantly lower than yields of PTR (by about 30% or 2 t/ha in both lasered and nonlasered treatments), resulting in similar WPI in both DSR and PTR in both leveling treatments. The yield loss with DSR was offset by higher wheat yields after DSR than after PTR in the second year, resulting in similar total system yield, and again demonstrating the importance of considering the total system rather than individual crops. At Delhi the best varieties only produced around 4.5 t/ha when dry seeded and irrigated at a soil water tension of 20 kPa, with about a 10% yield decline when the irrigation threshold tension was increased to 40 kPa (Singh et al., 2008). Irrigation at soil water tensions of 20 and 40 kPa reduced input water by 23% and 32%, respectively, in comparison with irrigation to keep the soil close to saturation. How much of the irrigation water savings in the above studies was due to reduction in ET and/or deep drainage is not known. If the lower yield of DSR was associated with lower biomass, at least part of the irrigation water savings would be due to reduced ET, but the effect on WPET would depend on whether ET was reduced by more than yield. In small plots on a clay loam at Ludhiana, Punjab, Sudhir-Yadav et al. (2010a,b) found similar irrigation water use and yield (>7 t/ha) of continuously flooded PTR and daily irrigated DSR (topped up to 5 cm daily from the time of transplanting the PTR; the DSR and the seedbed for PTR were sown on the same day) (Fig. 4). When irrigations were delayed until the soil water tension increased to 20 kPa at 17–20 cm depth, irrigation amounts in both establishment methods were more than halved, and the amount

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Figure 4 Irrigation water use of PTR and DSR as affected by irrigation scheduling on a clay loam at Ludhiana, Punjab, 2008. Daily ¼ daily irrigation topped up to 5 cm, 20 kPa ¼ irrigated when soil water tension at 17–20 cm increased to 20 kPa. Vertical bar is the least significant difference (p ¼ 0.05) for the interaction between establishment method and irrigation treatment. (Adapted from Sudhir-Yadav et al., 2010a.)

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applied to DSR was 30–50% lower than that applied to PTR, while yields in both treatments were similar to yields of continuously flooded PTR. The larger irrigation amount with PTR-20 kPa than DSR-20 kPa was mainly due to the fact that the PTR was continuously flooded for the first 15 d after transplanting before the irrigation scheduling commenced, and to a much lesser degree because it also required more frequent irrigation once the scheduling commenced. Deep drainage over the whole season was estimated using tritiated water injected at 60 cm at the time of sowing (DSR) or transplanting (PTR) (Munnich, 1968). Deep drainage under DSR-20 kPa (284 and 453 mm in 2008 and 2009, respectively) was significantly higher than in PTR-20 kPa (170 and 255 mm), probably due to the combination of irrigation and rainfall between sowing and the time of transplanting in 2008, and the lack of puddling (higher infiltration rate) in DSR. However, the deep drainage under PTR in 2008 was probably underestimated as it did not include drainage as a result of the large amount of rain that fell between the time of sowing DSR and irrigation for puddling. ET in both treatments was similar each year (means of 640 and 710 mm in 2008 and 2009, respectively), as was WPET (1.1–1.2 kg/m3). The irrigation water saving in DSR was due to reduced seepage and runoff. Whether this is a real water saving would depend on whether the seepage water ultimately flowed to sources or sinks. Yields of both DSR and PTR declined when the soil was allowed to dry to higher tensions than 20 kPa, and yield of DSR declined more rapidly than yield of PTR as tension increased to 40 and 70 kPa (Sudhir-Yadav et al., 2010b). On a marginally sodic silt loam at Modipuram, yield of DSR declined significantly (by 15%) as the threshold for irrigation increased from 10 to 20 kPa at 20 cm (Sharma et al., 2002). The DSR was affected by iron deficiency in the studies of both Sharma et al. (2002) and Sudhir-Yadav et al. (2010b), more so as the threshold tension for irrigation increased. Development of improved varieties targeted for dry seeding with AWD water management is needed, as are management guidelines (e.g., irrigation, nutrients, weeds). The IRRI-led Cereal Systems Initiative for South Asia (CSISA) project which commenced in 2009 includes a major effort to develop varieties for dry seeding with safe AWD. 4.6.1.1. Summary—Dry seeded rice with safe AWD Irrigation amounts of DSR with safe AWD are reduced in comparison with PTR with safe AWD, largely because of the need for continuous flooding during the first 2 weeks after transplanting, and partly because of the shorter irrigation interval to avoid soil cracking in puddled soil. The very limited data available to date (one study) suggest similar ET and WPET from DSR and PTR with safe AWD management, while the results of several studies show similar or lower yields with DSR than PTR.

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4.6.2. Aerobic rice The System of Aerobic Rice (“aerobic rice”) is also a dry seeded system, but one which uses much less irrigation water than well-irrigated DSR. It is referred to as a “System” as it involves the use of both specially developed input-responsive cultivars that are adapted to drier soil conditions than lowland rice varieties, and management practices tailored to maximize input water productivity (WPIþR). Aerobic rice was originally developed for irrigation areas where traditional PTR can no longer be grown due to water scarcity (as a result of physical shortage of water, inaffordability of water to farmers, or policies banning PTR, such as in areas that used to grow PTR around Beijing), and for favorable rainfed upland areas (Wang et al., 2002). The WPIþR of aerobic rice is typically double that of traditional rice culture grown under optimum conditions in the same climate (Bouman et al., 2006; Feng et al., 2007; Yang et al., 2005). In northern China, first-generation aerobic rice varieties have a demonstrated yield potential of 6 t/ha (compared with about 9 t/ha for lowland cultivars) but use only about 50% of the input (irrigation plus rain) water used in paddy rice. While the yield potential of current aerobic rice varieties is only about two-thirds that of lowland varieties grown in saturated or flooded soil, as water input is reduced below that required for continuous soil saturation, yields of traditional varieties fall below those of aerobic rice varieties grown with the same level of water deficit (Fig. 5). Thus aerobic rice is suited to areas where there is insufficient water to grow PTR or high yielding DSR with safe AWD, but where there is a need to continue to grow rice.

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It is also an attractive crop for traditional upland areas where crops such as maize and soybeans are sometimes severely affected by waterlogging, as aerobic rice is tolerant of waterlogging. Templeton and Bayot (2008) conservatively estimated that the potential adoption area for aerobic rice in China is about 5 Mha. Preliminary extrapolation domain analysis based on site similarity (climate, topography, rice growing area, availability of irrigation and poverty level) analysis with pilot aerobic rice sites suggested that the potential area for aerobic rice in India is also very large (several million hectares) and includes much of the IGP (Rubiano and Soto, 2008). Using the ORYZA2000 rice model, Bouman et al. (2006) showed that changing the irrigation threshold for aerobic rice from 10 kPa soil tension at 15–20 cm (equivalent to daily irrigation) to 20 kPa had no effect on yield, ET or WPET with a watertable at 60 cm, in wet and dry years, at Huibei in the Yellow River plain in China. With a deep watertable (1.9 m) in a dry year, both yield and ET declined by about 6% (by  0.5 t/ha, 40 mm, respectively), thus WPET was again hardly affected. WPET of aerobic rice ranged from 1 to 1.2 kg/m3, compared with values in excess of 1.4 kg/m3 for lowland rice in the same locality, for a range of watertable conditions and irrigation schedules. Xue et al. (2008) found higher WPET of around 1.4 kg/ m3 of aerobic rice for irrigation thresholds of 20–100 kPa using ORYZA2000 in deep watertable conditions near Beijing. Yield declined by about 10% (from 7.5 to 6.8 t/ha) over this range of irrigation schedules, while ET declined by about 6% (from about 510 to 480 mm). As for frequently irrigated DSR using varieties with higher yield potential, aerobic rice sometimes performs poorly as a result of factors such as micronutrient deficiency and nematodes (Kreye et al., 2009a,b). Further research is needed to produce germplasm with higher yield potential under limited water, and to develop management guidelines for sustainable aerobic rice-based cropping systems. 4.6.2.1. Summary—Aerobic rice Irrigation input can be further reduced beyond that in DSR using safe AWD using the System of Aerobic Rice, and with small reductions in ET, but the tradeoff is lower yield. The very limited data to date (one study) suggest that WPET of aerobic rice is less than that of well-irrigated PTR. Clearly, further efforts are needed to develop higher yielding aerobic rice systems and to quantify impacts on components of the water balance and water productivity.

4.7. Rice on beds 4.7.1. Transplanted rice on beds Small plot replicated experiments show reductions in the amount of irrigation water applied to transplanted rice on fresh beds compared with PTR (Bhushan et al., 2007; Kukal et al., 2010). In both these studies the same

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AWD irrigation scheduling rules were applied to beds and PTR—irrigation on the appearance of hairline cracks on the soil surface of the flat plots or in the bottom of the furrows (Bhushan et al., 2007), or irrigation 2 d after the disappearance of water from the soil surface or furrows (Kukal et al., 2010), and the furrows were filled almost to the top of the beds at each irrigation. Irrigation amount on fresh beds was reduced by 16% on a silty loam in western Uttar Pradesh (Bhushan et al., 2007), and by 11% and 24% on sandy loam and loam soils, respectively, in Punjab (Kukal et al., 2010). At all three sites, there was a reduction in yield on the beds similar to the reduction in irrigation amount, thus WPI was similar in the transplanted fresh beds and PTR. In a farmers’ field on the loam, irrigation was reduced by 15% while yield was reduced by 8%, resulting in a small increase in WPI. Some of the earliest farmer participatory trials of rice on beds in Ghaziabad, Uttar Pradesh, showed much larger average reductions in irrigation time (around 40%) for transplanted and DSR on raised beds in comparison with farmer practice (PTR), while average yields of all three systems were similar, thus resulting in higher WPI on the beds (Balasubramanian et al., 2003; Gupta et al., 2003). The reasons for the differences are unknown; however, it is likely that the larger irrigation water savings in the farmers’ fields were due to comparison of intermittently irrigated beds with continuously flooded PTR, whereas the studies of Bhushan et al. (2007) and Kukal et al. (2010) compared beds and PTR with similar AWD water management. Results of experiments in small plots comparing transplanted rice on permanent beds and PTR are quite variable in terms of both grain yield and irrigation water use. In general, rice on permanent beds performs much better in the eastern IGP than in the north west (Humphreys et al., 2008b). Results from Bangladesh, Nepal, and Uttar Pradesh show reduced irrigation amounts of 14–38% on permanent beds compared with PTR, on soils ranging in texture from sandy loam to silty clay loam, for beds up to 8 years old (Bhushan et al., 2007; Jat et al., 2008; Lauren et al., 2008; Talukder et al., 2008). In these studies, Bhushan et al. (2007) and Jat et al. (2008) irrigated all treatments at the first appearance of hairline cracks in the flat plots or furrows, while Lauren et al. (2008) irrigated the PTR and beds on the same day. In contrast, the total amount of irrigation water applied to PTR and permanent beds on a sandy loam at Ludhiana was similar on average over 4 years (Kukal et al., 2010). In this case both treatments were irrigated 2 d after the disappearance of water from the surface/furrows (usually on the same day), and the furrows were also filled almost to the top at each irrigation. On a loam at Phillaur with the same irrigation management, irrigation water application to the permanent beds was significantly higher (by 16–21% over 4 years) than in PTR in the small plots, and by 7% in a large (farmer field) block (one year’s data only). Results from Bangladesh and Nepal consistently show similar or higher yields of transplanted rice on permanent beds than PTR (Lauren et al., 2008;

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Talukder et al., 2008), and higher WPI as a result of both higher yields and lower irrigation amounts. In contrast, results from India and Punjab, Pakistan consistently show lower yields on the permanent beds than in PTR, in both small plots and farmers’ fields (Bhushan et al., 2007; Jat et al., 2008; Jehangir et al., 2007; Kukal et al., 2010; Yadvinder-Singh et al., 2008a, 2009), with yield declining as the beds age. The net result in the studies in India was thus similar or declining WPI on the permanent beds compared with PTR. In Punjab, WPI declined to about 50% of that in PTR by the 2nd or 3rd rice crop on the sandy loam and loam soils, respectively, in both small plots and in a farmer’s field (Kukal et al., 2010). Kukal et al. (2010) also found that total irrigation amount was higher on permanent beds than fresh beds with the same irrigation management in small plots on sandy loam and loam soils (by 11% and 24%, respectively), and by 25% in adjacent farmer blocks on the loam soil. They attributed this to bypass flow as a result of greater macroporosity in the permanent beds due to cracking and biopores. In the farmer field blocks, irrigation application depth also had a large effect on the amount of irrigation water applied to both fresh and permanent beds on the loam (Kukal et al., 2010). Half filling the furrows (instead of filling them to the top of the beds) at each irrigation decreased irrigation water amount in the permanent and fresh beds to 68% and 61%, respectively, of that in PTR with the same AWD irrigation scheduling. However, yield also declined by 20–25% when irrigation depth in the furrows was halved. The net result was higher WPI in PTR than on both the fresh and permanent beds irrigated with half furrow depth. 4.7.2. DSR on beds There are only a few reports comparing DSR on beds with DSR on the flat or PTR, all in small plots in north-west India. All these studies show a decline in yield of DSR on the beds relative to PTR, but the results are inconsistent in terms of irrigation amount. Choudhury et al. (2006) compared yield and components of the water balance for DSR on sandy loam and loam soils on fresh beds and on the flat at Delhi. The small plots had plastic lined bunds to reduce underbund seepage, and row spacing on the flats was even (20 cm) or with paired rows (20 cm, 47 cm), the same plant row spacings as on the beds. All three treatments were lightly irrigated every 2nd day to keep the root zone close to field capacity. There was a significant (11%) reduction in irrigation amount on the beds in the first year compared with both DSR flat treatments, but no significant difference in the second year. The reduction in irrigation in the first year was due to a 15% reduction in drainage beyond the rootzone, while ET (calculated from the water balance) was similar on beds and flats with paired row spacing in both years, but significantly lower (by about 12% or 75 mm) than with 20 cm row spacing, probably due to the much lower leaf area and biomass production with the paired rows (on beds and flats).

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Yields of DSR on beds and flats with paired rows were similar, and significantly lower (by 12–24%) than yields of DSR with 20 cm row spacing. Water productivity with respect to ET was thus similar in all three treatments in 1 year, and significantly lower (by 14%) on beds and flats with paired rows than with 20 cm row spacing in the other year. At Modipuram, irrigation water use of DSR on fresh beds was significantly lower (by 9% and 5% on sandy loam and silty loam soils, respectively) than in DSR on the flat (Bhushan et al., 2007; Jat et al., 2008; first crop on the beds in both these permanent bed studies). Yields on the beds were 17% and 14% lower than on the flat, resulting in slightly but significantly lower WPI on the beds. At another sandy loam site at Modipuram, yields of DSR and irrigation amount on fresh beds were both about 25% lower than PTR with the same irrigation scheduling rules (appearance of hairline cracks), resulting in similar WPI in DSR and PTR ( Jat et al., 2009). Yield of DSR on permanent beds (3- and 8-year-old beds) was significantly lower (by 46% and 23%, respectively) than yield of PTR, and 16% lower than yield of DSR on the flat, on two sandy loam sites in Modipuram ( Jat et al., 2008, 2009). While irrigation input was reduced by about 25% (400 mm) on the 3-year-old beds, WPI was significantly lower because of the 46% yield decline ( Jat et al., 2009). On sandy loam and loam soils in Punjab, yields of DSR on beds also declined greatly relative to yield of PTR as the beds aged, while the amount of irrigation water applied to DSR was similar to or higher than that applied to PTR with the same AWD irrigation management (Humphreys et al., 2008a; Yadvinder-Singh et al., 2008a, 2009). The higher irrigation amounts were partly due to the longer duration of DSR in the main field. Constraints to growth of DSR on beds in northwest India included nematodes and severe iron deficiency which could not be fully overcome by the use of iron sprays (Sharma et al., 2002; YadvinderSingh et al., 2008a, 2009). 4.7.3. Summary—Rice on beds Transplanted rice on fresh beds consistently results in irrigation water savings of 15–25% in comparison with PTR with AWD, with irrigations on beds and PTR scheduled using the same rules. However yields on beds in north-west India tend to be lower than yields of PTR, resulting in similar WPI. The nature of the irrigation water savings has hardly been investigated, for both transplanted and DSR on beds, apart from the study of Choudhury et al. (2006). Where rice growth is similar on beds to that of PTR, there is likely to be little effect on ET, and the savings are probably due to reduced deep drainage and thus their magnitude will depend on soil type and depth to the watertable. The size of the irrigation water savings for intermittently irrigated beds will be much higher if they are compared with PTR with continuous flooding rather than with AWD. The magnitude of the water savings of transplanted rice on fresh beds in farmers’ fields in comparison with farmer

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practice (probably PTR with continuous flooding) appears to be similar to the savings with AWD compared to continuous flooding of PTR. The performance of transplanted rice on permanent beds is variable across the IGP. In north-west India yields and WPI generally decline as the beds age in comparison with PTR with the same irrigation scheduling rules. This is not the case in studies in Nepal and Bangladesh. Results are also variable with regard to irrigation amount on permanent beds compared with PTR. Bypass flow on the permanent beds as a result of soil cracking during the long hot fallow, and the development of biopores, appears to lead to higher irrigation requirement on the permanent beds on some soil types. Yield of DSR on beds is consistently inferior to that of PTR, and yield declines greatly as the beds age. Iron deficiency and nematodes are often major problems. To date there has been negligible adoption of rice on fresh or permanent beds in north-west India. Clearly, further research is needed to develop sustainable, high yielding permanent bed systems for rice.

4.8. Zero till wheat Traditional establishment of wheat after rice involves removal of the rice residues (predominantly by burning in north-west India, or manually in eastern India), followed by intensive tillage (Gajri et al., 2002). In the north west, this typically involves a pretillage irrigation followed by a couple of discings then harrowings then plankings to prepare the seed bed for wheat. In Punjab, India the seed is normally sown in rows by a seed drill, whereas in Haryana and the eastern IGP it is commonly broadcast. Adoption of zero tillage in the IGP has been rapid since the mid-1990s, increasing to over 3 million hectares by 2006 (Harrington and Hobbs, 2009). The major driver for adoption is increased profitability as a result of lower establishment costs (Erenstein and Lakshmi, 2008). In 2003–2004, zero till wheat (ZTW) was practised on over 1 million hectares in India, using the Pantnagar or “zero till” seed drill (Erenstein and Lakshmi, 2008). This machine is capable of sowing into bare, nontilled soil and into anchored rice residues, but not into combine harvested rice stubbles because the loose residues left by the harvester block the seed drill. Thus ZTW as it is currently practised involves full or partial burning, or removal of the loose rice residues. In a comprehensive review of ZTW farmer participatory trials and research in RW systems of the IGP, Erenstein and Lakshmi (2008) found that zero till saved one irrigation, and gave average irrigation water savings of 10–30% or up to 100 mm, compared with conventional tillage. This was mainly due to lack of need for a presowing irrigation due the ability to sow sooner after rice harvest while the soil was still moist, and due to the much shorter duration of the first irrigation because of the faster advance of the water over the nontilled soil surface. However, a pre-tillage/sowing

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irrigation may not always be needed for wheat sown into tilled soil (Sharma and Singh, 2002). Yields of ZTW were similar or higher (by an average of 6%) than yields with conventional tillage, thus WPI was also higher. Adoption studies in Haryana (Erenstein et al., 2008) also showed that WPI was significantly (17%) higher in ZTW than with conventional tillage, due to slightly higher yields (by 4%) and slightly lower irrigation amount (by 9%), although the average number of irrigations for both establishment methods was the same. The nature of the irrigation water savings for ZTW in comparison with conventionally tilled wheat has not been investigated. There are four possible causes: (1) reduced transpiration as a result of earlier planting resulting in the crop growing under a period of lower evaporative demand; (2) reduced deep drainage due to the shorter duration of the first irrigation, and due to fewer irrigations where that is the case; (3) reduced soil evaporation due to reduction in the period between rice harvest and wheat as a result of earlier wheat planting; Humphreys et al. (2008a) showed significant drying of the soil profile to depth on sandy loam and loam soils in Punjab between the time of rice harvest in mid October and wheat sowing in early November. As there is often a window of several weeks between rice harvest and the optimum time for wheat sowing in the north west, the use of zero tillage is unlikely to advance the time of wheat sowing significantly, except where rice harvest is late as is the case for basmati rice; considerable areas of basmati are grown in Haryana (0. 4 Mha out of a total rice area of 1 Mha since about 2000, but with a dramatic increase to 0.8 Mha out of 1.2 Mha in 2009), Punjab (20% of the rice area or 0.5 Mha) and Uttar Pradesh; (4) reduced soil evaporation due to nondisturbance of the soil—whether tillage increases total evaporation due to exposure of moist soil aggregates to the atmosphere or reduces it due to breaking of capillarity depends on the time period, soil type, incidence and amount of rain, and evaporative demand ( Jalota et al., 2001). Under typical dry, low evaporative demand conditions after rice harvest, Jalota et al. (2001) found only very small differences in soil profile water content for untilled and cultivated soil after 2 and 3 weeks on sandy loam soils, but on a loamy sand (not a typical rice soil) water content in the untilled soil was 30 mm higher after 3 weeks. The optimum time for wheat sowing in north-west India is the first fortnight in November. Given that rice is generally harvested in early to mid October, and the potential for early establishment of wheat using zero tillage, it is important to understand the tradeoffs between on yield, WPI and WPET with earlier sowing? Using the DSSAT-CSM-CERES Wheat v.4.0 crop model, Timsina et al. (2008) compared yield, components of the water balance, and water productivity of the predominant wheat variety (PBW343) sown at 15 d intervals from 10 October to 10 January. Maximum yield and water productivity with respect to both irrigation (WPI) and ET (WPET) occurred with 25 October and 10 November sowings, suggesting

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sowing can be brought back to at least 25 October, with the potential benefit of capturing residual soil water from rice that would otherwise be lost by evaporation. Yield, WPI and WPET were least with sowing on 10 October. The potential for planting between 10 and 25 October also needs to be explored with regard to yield, water depletion and water productivity, given that earlier sowing provides the opportunity for the crop to mature under cooler conditions and with lower evaporative demand. 4.8.1. Summary—Zero till wheat Adoption rates of zero till wheat are far higher than with any other improved technology for RW systems, with adoption on over 10% of the RW area of India by 2003–2004. A major driver for adoption is increased profitability as a result of lower establishment costs. There is considerable evidence from farmer adoption studies that zero till wheat gives irrigation water saving of at least 10% (at least 20–30 mm) in comparison with conventional practice, while yields are generally slightly higher, leading to higher WPI. Experimental studies indicate that reductions in irrigation amounts of up to 30% are possible. How much of the irrigation water saving is due to reduced ET or deep drainage, and the effect on WPET, are not known.

4.9. Surface residue retention and mulching 4.9.1. The effect of mulch on soil evaporation It is well established from laboratory studies that surface residue retention and mulching decrease soil evaporation, and that the reduction in evaporation depends on the amount of mulch, soil water content, soil type, and evaporative demand (e.g., Bond and Willis, 1970; Gill and Jalota, 1996; Prihar et al., 1996; Steiner, 1989). However, while cumulative evaporation from mulched soil initially lags behind that of bare soil, the difference declines with time (because the mulched soil is wetter) and eventually the total loss from the mulched soil becomes similar to or can even exceed the total loss from the bare soil (Bond and Willis, 1970; Prihar et al., 1996). However, these findings are from laboratory studies in the absence of wetting events after the mulch is applied. Field soils are subjected to wetting by rain and irrigation, and drying by evaporation, root water uptake and drainage, therefore the actual impacts of mulch on evaporation will be site and season specific. 4.9.2. Surface retention of rice residues for wheat The recent development of the Happy Seeder (Sidhu et al., 2007, 2008) and the Rotary Disc Drill (Sharma et al., 2008b) provides RW farmers in the IGP with the capability of sowing ZTW in the presence of loose and anchored rice residues. The Happy Seeder removes the residues in a narrow strip (7.5 cm) in front of the sowing tynes, and chops the residues which flow past the tynes. This enables zero tillage into bare soil, and leaves

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standing straw between the seed rows plus a mulch on the soil surface. The Rotary Disc Drill cuts through the residues and makes a slit in the soil for placing seed and fertilizer. Several experiments in Punjab and Nepal show that rice mulch significantly reduces the rate of soil drying and delays the need for irrigation of wheat (Balwinder Singh et al., 2010a; Rahman et al., 2005; Sidhu et al., 2007; Yadvinder-Singh et al., 2008b). Using microlysimetry, Balwinder-Singh et al. (2010b) showed that the mulch reduced soil evaporation by 35 and 40 mm on a clay loam soil in both a lower than average rainfall year (89 mm) with poor rainfall distribution, and a higher than average rainfall year (159 mm) with good rainfall distribution, respectively (Fig. 6A and B). However, the reduction in soil evaporation was offset by significantly higher transpiration in both years. In the drier year (three postsowing irrigations), ET, yield and WPET were unaffected by mulching. In the other year (one postsowing irrigation), mulching significantly increased biomass and yield compared with the nonmulched control which suffered from water deficit stress for about 10 d after maximum tillering. Again ET was similar with and without mulching, but WPET was significantly increased due to the higher yield. Whether or not mulching reduces the need for irrigation depends greatly on the incidence and amount of rainfall—in some years mulch reduced the number of irrigations by one when scheduled based on soil matric potential, in other years mulched and nonmulched wheat required the same number of irrigations (Balwinder-Singh, 2010a; Yadvinder-Singh et al., 2008b). The results of Balwinder-Singh et al. (2010b) suggest that mulching does not reduce water depletion as ET due to reduced transpiration efficiency in the presence of mulch. This is a disappointing finding which needs further investigation. In addition to retention of rice residues, the Happy Seeder and Rotary Disc Drill provide the capability of sowing on the day of harvest, maximizing the opportunity for productive use of residual soil water rather than losing it by evaporation. The field studies of Jalota et al. (2001) suggest that mulching would result in similar or higher soil profile water content (by up to 50 mm) over a period of 2–4 weeks after rice harvest, in the presence of limited rain. Thus sowing into rice residues immediately after rice harvest could save up to 50 mm of soil water for early use by the crop. Adoption of the Happy Seeder is at an early stage. In 2008–2009, the Happy Seeder was demonstrated in participatory trials on 930 acres across all districts of Punjab, and in a few trials in western UP. At that time there were four manufacturers and a government subsidy of 33%. Twenty-two machines were sold, 10 to farmers and the rest to government, institutions and cooperative societies (Manpreet Singh, personal communication). In May 2010 there were five manufacturers in Punjab, and the state government announced plans to buy 200 Happy Seeders for the 2010–2011 season, providing 80 machines free to Primary Agriculture Cooperative Societies, and a further 120

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Days after sowing B 200

Soil evaporation (mm)

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Figure 6 The effect of mulching on soil evaporation from wheat at Ludhiana, Punjab was measured using mini-lysimeters in (A) 2006–2007 and (B) 2007–2008. The standard error of the mean for each data point is plotted, creating an envelope of variability. (Adapted from Balwinder-Singh et al., 2010.)

with a 50% subsidy http://www.tribuneindia.com/2010/20100602/punjab. htm#2. It was anticipated that this would halt burning on at least 20,000 ha in 2010. While there are government bans on the burning of crop residues in Punjab and Haryana, these have not been implemented to date. 4.9.3. Surface retention of residues during the fallow period between wheat harvest and rice planting Potential evaporation is very high during the 2-month period between wheat harvest and rice planting, with total pan evaporation of the order of 500 mm (Fig. 2); however, the amount of evaporation will depend on soil

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water content. Results from a sandy loam show that the soil profile was relatively dry at the time of wheat harvest, but that there was further loss of water from the 0–20 and 20–40 cm layers between harvest and preirrigation for rice (Fig. 7). The total loss during this period was about 20 mm. The field studies of Jalota et al. (2001) showed losses of around 70 and 40 mm on sandy loam and loamy sand soils during this period, while the modeling studies of Jalota and Arora (2002) predicted higher evaporation (averages of 146 and 97 mm from medium and coarse textured soils, respectively) during this fallow period. To date, little attention has been paid to management of the fallow period after wheat harvest, apart from the possibility of introducing a green manure crop (Yadvinder-Singh et al., 2004), or a short duration food crop (such as mung bean, Section 4.11) during this period. Most of the wheat in north-west India is harvested by combine (Gajri et al., 2002). The loose straw (about two-thirds of the residue) is normally removed for animal feed, and the remaining straw (2 t/ha) is burnt. Would mulching with that amount of straw in that environment significantly reduce evaporation during the fallow period? In laboratory studies, Steiner (1989) found that stage 1 evaporation from a wetted soil was reduced by 85% with less than 1 t/ha of wheat straw. On deeply wetted soils in laboratory experiments, Prihar et al. (1996) found that the introduction of shallow (5 cm) tillage when the cumulative reduction in evaporation due to mulch reached a maximum (a couple of days to about 10 d after mulching, depending on soil type) provided maximum benefit in reducing evaporative loss from a range of soil types. The practical implication of this is that mulching after wheat

0.00 0.0

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0.4 Depth (m)

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8 May 2006 6 Jun 2006

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Figure 7 Drying of the upper soil profile between wheat harvest (11 April 2006) and preirrigation for rice on a sandy loam at Ludhiana. Horizontal bars are standard deviations for the data on 12 April (Humphreys et al., unpublished data).

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harvest in years when there is significant residual soil moisture (e.g., due to rain close to harvest or late irrigation), followed by shallow tillage a few days later, may help conserve residual soil moisture after wheat. However, the soil profile is normally dry at the time of wheat harvest (Humphreys et al., 2008a), and with little likelihood of rain. In their field experiments, Jalota et al. (2001) showed that in the period of high evaporative demand after wheat harvest, and with occasional rains, there was no benefit of mulching (with 6 t/ha of wheat straw) in terms of soil water content. 4.9.4. Summer crops and mulching The reduction in evaporation of irrigated summer crops as a result of mulching is likely to be larger than for wheat because of much higher evaporative demand, especially prior to the onset of the monsoon. Mulching can greatly increase yield of summer crops in north-west India, but results are variable, depending in particular on weather (Ram et al., 2005; Sekhon et al., 2005). Studies on the effects of mulching summer crops on ET in the region are lacking. Using a water balance model, Jalota and Arora (2002) estimated that mulching maize reduced evaporation by means of 185 and 130 mm on medium and coarse textured soils, respectively, while mulching cotton reduced evaporation by means of 225 and 165 mm, respectively. Based on these results, there may also be considerable potential to reduce evaporation from DSR (with AWD) using mulches, and this needs further investigation. 4.9.5. Summary—Mulching Mulching offers the potential to reduce evaporation from wheat by 30–40 mm, which will reduce the number of irrigations needed by one in some years. However, initial results suggest that the reduction in evaporation is offset by increased transpiration, and that under well-irrigated conditions transpiration efficiency is reduced, resulting in similar WPET with and without mulch. Under limited water conditions where mulching reduces water deficit stress and loss of yield, WPET is increased. Preliminary results suggest that mulching of wheat does not reduce water depletion as ET due to reduced transpiration efficiency in the presence of mulch, and further investigations are needed. There seems to be little scope for mulching to reduce soil evaporation during the very hot, dry fallow between wheat and rice harvest, unless there is rain shortly prior to the time for establishment of rice. The potential for water savings through mulching of summer crops, including DSR, has not been investigated to date, but maybe substantial based on the results of limited trials with non-rice summer crops. The potential for mulching to reduce water depletion as ET and increase WPET requires further investigation.

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4.10. Wheat on raised beds There are many anecdotal reports of large irrigation water savings for wheat on beds in comparison with conventional tillage in farmers’ fields. The few published data show reduced irrigation time or amount of 35–50% and slightly higher yield (mean 5%) on the beds (Hobbs and Gupta, 2003; Kahlown et al., 2006; Singh et al., 2002). It is likely that most of these reports from farmers’ fields are for fresh beds. Despite these positive results, there has been negligible adoption of wheat on beds in RW systems. The reasons have not been analyzed, but are likely include the need to purchase a bed planter (although a simple potato ridger can be used) and to knock the beds down after wheat harvest for conventional rice cultivation. Permanent bed RW systems would probably be more attractive to farmers if yields of both rice and wheat could be maintained or increased, because this would greatly reduce establishment costs. However, to date, poor yields of rice on permanent beds in north-west India have discouraged adoption (Section 4.7). Results of replicated experiments generally show similar or higher yields of wheat on permanent beds compared with conventional tillage, and reduced irrigation amounts (Bhushan et al., 2007; Jat et al., 2008; Lauren et al., 2008; Talukder et al., 2008; Yadvinder-Singh et al., 2008a, 2009). The reduction in irrigation amount on permanent beds from replicated experiments is usually smaller than that reported from farmers’ fields (probably fresh beds), perhaps because of the longer duration of irrigation in farmers’ fields and/or increased macroporosity of the permanent beds in comparison with fresh beds, and thus more opportunity for deep drainage losses. In some situations, yields were lower on fresh and permanent beds than with conventional tillage—as a result of more rapid drying of the beds on coarse textured soils, accumulation of salt on the beds on a sodic soil, or inadequate tillering associated with late planting (Choudhury et al., 2006; Jehangir et al., 2007; Sharma et al., 2002; Yadvinder-Singh et al., 2009). These problems could generally be overcome by better management, but suggest that beds require more skilled or precise management than establishment with conventional tillage. There have been few studies to quantify the nature of the irrigation water savings for wheat on beds. In a comparison of zero till wheat on permanent beds with conventionally tilled wheat on sandy loam and loam soils at Delhi, irrigation water use was lower on the beds due to lower ET (Choudhury et al., 2006). The lower ET on the beds was probably due to poorer crop growth (the crop was planted late, and the plants on beds were probably unable to compensate for the wider row spacing on the beds by greater tillering under the cooler weather conditions experienced by late planted crops), and also due to less deep drainage in one of the 2 years of this experiment (Choudhury et al., 2006). The net result was lower WPET on the beds. It is likely that soil evaporation from beds is higher than from a flat

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layout during the first part of the crop season, while the soil is bare and until the canopy develops. This is because the formation of beds increases the soil surface area—by about 50% in the case of the narrow beds (30 cm bed top, 37.5 cm furrow width, 15 cm furrow depth) commonly used in north-west India. Prashar et al. (2004) and Kukal et al. (2008) showed that the beds (10 and 20 cm soil depths) dried more rapidly than conventionally tilled soil after sowing on sandy loam and loam soils, more so on the sandy loam. Model simulations using Hydrus 2D also show substantially greater evaporation from the beds than from the flats with a bare soil surface (F. Cook, personal communication). Mulching of the beds would reduce this loss, and the Happy Seeder approach can provide the capability of direct drilling into crop residues on beds (see cover photo in Humphreys and Roth, 2008). 4.10.1. Summary—Wheat on beds There is much anecdotal evidence that irrigation amounts are reduced greatly and yields are maintained or increased slightly by growing wheat on fresh beds in farmers’ fields in comparison with conventional tillage, and this is also generally the trend in small plot studies. The irrigation water savings are likely to be due to faster irrigation times and reduced deep drainage, and therefore the magnitude of the irrigation savings is likely to depend on soil type and depth to the watertable. Growing wheat on beds is unlikely to decrease ET, and may increase it, especially in situations where beds lead to increased crop growth, such as on soils prone to waterlogging. The effects on WPET are unknown. Adoption of wheat on beds in RW systems is unlikely to be attractive unless it is in a permanent bed cropping system. Yields of wheat on permanent beds are generally similar to or slightly higher than yields with conventional tillage. However, the performance of rice on beds has been unsatisfactory to date in the north-west IGP, hence there has been no adoption of permanent bed RW cropping systems in this region.

4.11. Replacement of rice, crop diversification It is sometimes suggested that replacement of rice with other crops would help solve the declining groundwater problem in Punjab, India (e.g., Hira, 2009). Alternative crops to rice, such as maize, soybean and cotton, have much lower irrigation water requirement than rice (e.g., Jat, 2006; Ram et al., 2005). Depending on the distribution and amount of the monsoon rains and soil type, these crops require from none to four to five irrigations after sowing, with total irrigation application to maize and soybeans of the order of one-fifth to one-tenth of that for PTR. Two important questions are: (1) by how much will replacing rice reduce water depletion, and (2) what is the effect on the productivity of depleted water? Jalota and Arora (2002) used a water balance model to compare components of the water balance for four cropping systems (including fallow

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periods) using 10 years of weather data at Ludhiana, Punjab. Annual total “losses” (as evaporation, transpiration, and deep drainage) on the medium textured soil were greatest for the RW system, followed by sugarcane, cotton–wheat, and maize–wheat (Table 3). The high losses in the RW system on the medium textured soil were due to much higher deep drainage, which was up to four times the deep drainage in the other summer crops. On the coarse textured soil, annual total losses were highest in sugarcane and again least in maize-wheat. ET was highest in sugarcane, followed by cotton–wheat, RW, and maize–wheat. Ahmad et al. (2004) also found higher ET from cotton–wheat than from RW in Punjab, Pakistan, using the SWAP model. The results suggest that simply replacing the RW system with other systems such as cotton–wheat or sugarcane would actually increase water depletion in the major parts of the RW region where most irrigation is from groundwater. The results of Jalota and Arora (2002) also suggest that replacing rice with maize would reduce total annual water depletion by only 50–70 mm. Using the model of Jalota and Arora (2002), Hira et al. (2004) also estimated slightly higher ET for soybeans than rice, but much lower ET for other pulses (450 mm) and pigeon pea (300 mm), and lower ET for (winter) oilseeds (280 mm) and black gram (320 mm) than wheat (400 mm), while ET for winter maize was higher (500 mm). However relative ET of all crops, and particularly in relation to rice, depends greatly on the date of planting (Section 4.2), largely because of the effect on the duration of the crop in the field prior to the onset of the monsoon, when evaporative demand is very high. These modeling results should be regarded as preliminary but indicative, and clearly further work is needed to quantify components of the water balance and water productivity with respect to water depletion for a range of cropping systems. This needs to be done for a range of agroecological (soil type, climate, depth to the watertable) and management conditions (e.g., planting date, irrigation management), using both field measurement and crop modeling. With minimum government support prices and guaranteed purchase for both rice and wheat, together with a lack of good infrastructure and markets for alternative crops, there is currently no incentive for farmers to replace these crops with alternative crops. Table 3 Simulated components of the water balance (annual, mm) for a range of irrigated cropping systems (including fallow periods) at Ludhiana, Punjab (adapted from Jalota and Arora, 2002) Medium textured soil

Coarse textured soil

Cropping system

ET

Deep drainage

ET

Deep drainage

Rice–wheat Maize–wheat Cotton–wheat Sugarcane

1130 1080 1340 1360

810 410 280 210

960 890 1210 1340

770 650 500 550

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4.11.1. Summary—Replacement of rice, crop diversification Replacing rice with another summer crop will greatly reduce the amount of irrigation water applied, with many benefits. In canal irrigated areas with saline groundwaters, replacement of rice will reduce water depletion and the rate of watertable rise and associated problems. But replacement of rice with other summer crops will not reduce the problem of groundwater depletion in areas with fresh groundwater, where groundwater is the main source of irrigation water and ET is the only source of water depletion, unless the alternative crop has lower ET than that of rice. Preliminary studies suggest that replacement of RW with cotton–wheat, soybean– wheat, or sugarcane will actually increase ET losses, while the gains through replacing RW with maize–wheat will be large to negligible depending on rice planting date. Further studies are needed to quantify ET for a range of cropping systems under a range of site, seasonal, and management conditions.

4.12. System intensification Potential evaporation is very high during the long fallow period between wheat harvest and rice planting (Fig. 2, Section 4.9). Wheat planted on 10 November in Punjab reaches physiological maturity around 25 March. Rainfall between 25 March and 25 May is small, and exceeded 50 mm in only 25% of years between 1970 and 2005 at Ludhiana. Inclusion of a short duration crop such as mungbean during this time could make productive use of this rainfall, and also increase productive use of any residual soil water from wheat. Of course this additional crop would also require irrigation and increase total depletion from the system as ET; however, it is the effect on total system production with respect to ET that should be considered. With conventional tillage, mungbean planted after wheat normally requires one presowing irrigation and three to four postsowing irrigations. In 2008–2009, one to two postsowing irrigations were saved by drilling mungbean into wheat residues (after removal of 70% of the wheat straw) which followed wheat drilled into rice residues using the Happy Seeder (Yadvinder-Singh, unpublished data). Furthermore, the residues of the mungbean crop could be retained with other benefits to the total system, including reduction of evaporation from the subsequent rice crop through dry seeding into the residues. Another potential advantage of growing a crop between wheat harvest and rice establishment is reduction or prevention of soil cracking due to the need to keep the soil moist for the crop. This would reduce deep drainage due to crack flow, especially during precultivation irrigation, in the subsequent rice or other summer crop. The impact of crop intensification on productivity of the total system with respect to total water depletion needs to be investigated in field and modeling studies.

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5. General Discussion In regions where water is limiting (or will become limiting in the foreseeable future), and where food production needs to increase, as in the RW regions of north-west India, two of the objectives of improved crop technologies must be to increase production per unit of depleted water and to reduce water depletion. That is, to achieve real water savings. Our review finds that there are very few data available on the impact of most technologies on water depletion, nor on productivity with respect to depleted water. This is consistent with the observations of Kumar et al. (2009) who stated that “There is effectively no research in India quantifying the real water saving and water productivity impacts of water saving irrigation technologies on various crops, at the field level. An extensive review of literature shows that all the data on watersavings are based on applied water . . .. . .Some of the figures on water saving. . ..are quite high. . . the condition of flood irrigation system chosen for comparison influences the findings on water savings and yield. . ..Poorly managed flood irrigation systems used for comparison could significantly affect the result in favor of. . ..” Our review shows that some improved technologies result in reductions in irrigation applications, or “irrigation water savings,” and higher WPI, with major benefits including reduced irrigation/energy costs, and reduced demand on overstretched electricity supplies. The size of the irrigation water saving can be substantial, but is often variable depending on site conditions and the control used for comparison. The choice of control is particularly important in the case of rice—is it PTR with continuous flooding or PTR with the recommended practice, safe AWD? Technologies which generally result in substantial irrigation water savings in RW systems in northwest India in comparison with conventional practice include laser assisted land leveling, delayed rice transplanting, short duration rice varieties, AWD in transplanted and dry seeded rice, aerobic rice, replacing rice with other summer crops, zero till wheat (with and without mulching) and raised beds for wheat. The irrigation water saving can be very large, for example 50–90% (1000–1800 mm) saving by replacing rice with other summer crops, up to 40% or 800 mm for AWD in rice in comparison with continuous flooding, and up to 35% (100 mm) in wheat with laser assisted leveling or zero tillage. The effect of other technologies such as transplanted rice and DSR (on beds or flats, zero till, or cultivated) on irrigation amount in comparison with PTR with safe AWD may be small, but has not been clearly established. However whether or not decreased irrigation applications are due to real water savings is usually unknown, as very few studies have attempted to quantify this. It is likely that much or all of the irrigation water savings with technologies such as laser leveling, safe AWD, raised beds and replacement of rice with other summer crops in the main RW areas is due to reduced deep

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drainage which flows to fresh groundwater systems which are pumped for irrigation. To halt the decline in the watertable, the focus in these regions must be on technologies that reduce depletion as ET and increase WPET. By far the biggest gains in reducing ET come from delaying rice transplanting and growing shorter duration varieties. For example, delaying transplanting in central Punjab from late May to late June reduces ET by about 75 mm while maintaining yield, thus increasing WPET. Recent policies and their implementation have resulted in a major shift in transplanting date, with claims of significant impacts on the rate of groundwater decline already. Reducing rice varietal duration provides another important means of reducing ET, for example, by up to 70 mm in central Punjab, and short duration varieties with similar or higher yield potential to the current longer duration popular varieties are now available. The effect of mulching on ET from summer crops, including DSR, may be very large but has not been investigated. The effect of mulching winter crops on ET is less clear, and the recent findings of Balwinder-Singh et al. (2010b) suggest that the reduction in soil evaporation as a result of mulching wheat is offset by increased transpiration. It is likely that other technologies such as laser leveling, beds and zero till, will not decrease ET, and in fact may increase ET if crop growth is improved. Whether these technologies lead to higher WPET is not known. Of course, there are also many other benefits of irrigation saving technologies even if they do not reduce ET, and these technologies should be promoted provided they do not decrease WPET of the total cropping system. A possible example of a technology that should not be adopted is replacement of the RW cropping system in central Punjab with a cotton–wheat system or sugarcane, based on the ET estimates of Jalota and Arora (2002). In regions where irrigation water savings can be achieved through reduced drainage to ground or surface waters that are too saline or polluted for further use, such as in south-west Punjab and southern and central Haryana, there is large scope for real water savings through technologies that reduce deep drainage (as well as technologies that reduce ET). Here, the biggest potential for saving water is to diversify from rice-based cropping systems to non-rice cropping systems. While conversion from current practice to technologies that provide real water savings is extremely important, it is also important to consider what happens to the saved water. In situations where water is so limiting that some cultivable land is not cropped, farmers may use the saved water to grow additional irrigated crops, with the net result of increased water depletion. This is the case in Punjab Pakistan, where the introduction of zero till wheat and laser leveling led to increased wheat area, primarily on large landholdings (which account for 50% of the RW area) (Ahmad et al., 2007). They estimated that 60% adoption of zero till wheat would increase water depletion as ET by 5%, or 1.3  109 m3. This is probably less of an issue in the irrigated areas of north-west India where almost all cultivable

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land is used, such as in central Punjab where cropping intensity is 201%. However, it may be an issue in parts of Haryana and western Uttar Pradesh where lands are sometimes left fallow due to lack of water, especially if the net result is decreased productivity with respect to water depletion. There have been no studies on the impacts of widescale adoption of improved technologies for RW systems on water depletion and the productivity of that water in north-west India. Widescale adoption of technologies that affect water depletion and deep drainage will have impacts on the depth to groundwater table, demand for water from the canal system, demand for electricity and pollution of groundwater. The impacts will vary depending on site conditions (soils, hydrogeology, climate, source of irrigation water, irrigation and drainage networks) across the landscape. Comprehensive studies using spatial hydrologic models are needed to estimate the likely impacts at higher spatial scales from sub-district to subbasin and basin. Such studies, combined with the results of field, crop modeling, and economic studies, would be useful to help identify the optimum technology options for local conditions.

6. Conclusions This review has focused on the effects of improved technologies for RW systems on components of the water balance, grain yield, and water productivity with respect to irrigation and evapotranspiration (ET). There are many other potential benefits of these improved technologies, such as increased profitability, improved soil properties, reduced labor and energy requirements, and reduced air and water pollution, but these are not the focus of this chapter. There are clearly many technologies with the potential to reduce the amount of irrigation water applied to RW systems. However, the impacts of the technologies in terms of yield, components of the water balance, and water productivity are often variable and are affected by many factors including climate, soil type, and hydrological conditions. The effects of improved technologies on real water savings is poorly understood at the farmer field scale, and have hardly been considered at higher spatial scales. Very few studies have determined the effects of alternative crop technologies on ET and drainage, and whether the drainage losses at the farmer field scale are losses at higher spatial or temporal scales, and thus the real water savings. The irrigation water savings are often likely to be due to reduced deep drainage, with little effect on ET. More than 90% of the major RW areas are irrigated using groundwater. Here, reducing deep drainage will not “save” water nor reduce the rate of groundwater decline, and technologies that decrease ET are needed. The best technologies for reducing ET are

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delayed rice transplanting and use of short duration rice varieties. In areas where the groundwater is highly saline and/or sodic, and not suitable for irrigation, reducing deep drainage provides real water savings in addition to other benefits such as reduced waterlogging and secondary salinization. The performance of the technologies needs to be systematically assessed at the farmer field scale for a range of site conditions, to increase process understanding, and to develop generic knowledge to help target technologies to site conditions. Such targeting needs to be informed by the results of crop simulation modeling. The use of simulation models enables evaluation of technologies over the likely range of seasonal conditions, taking into account soil type, depth to the watertable, and a range of management factors. Crop models also enable estimation of components of the water balance and crop water productivity, parameters which are extremely difficult to measure in the field. Models also allow analysis of risk, and tradeoffs between yield, water depletion, deep drainage, runoff, etc. However, there needs to be significant investment in good data sets for model calibration and evaluation and process understanding to capitalize on the predictive capacity of crop models. This is currently a major gap for RW systems in the IGP. There is also poor understanding of the amount of reduction in water depletion needed to halt the decline in groundwater levels. This will vary depending on local hydrogeological conditions. There is a need for the development and application of models and other approaches for assessing the impacts of widescale adoption of technologies at a range of spatial scales from sub-district to sub-basin and basin. The ultimate challenge is to design land use strategies, cropping systems and management options that will meet food production needs, and that will be biophysically and socio-economically sustainable in the longer term, appropriately targeted to the variable environments across the IGP.

ACKNOWLEDGEMENTS This review is an output of the Cereal Systems Initiative for South Asia (CSISA) funded by the Bill and Melinda Gates Foundation and USAID. Balwinder Singh and Sudhir Yadav are supported by John Allwright Fellowships through the Australian Centre for International Agricultural Research. The development of this chapter owes much to the inspiration, opportunities, and support offered by Dr. Tony Fischer to the senior author over the past decade.

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C H A P T E R

S I X

Biological Control of Insect Pests in Agroecosystems: Effects of Crop Management, Farming Systems, and Seminatural Habitats at the Landscape Scale: A Review Adrien Rusch,* Muriel Valantin-Morison,* Jean-Pierre Sarthou,† and Jean Roger-Estrade* Contents 1. Introduction 2. Arthropod Dynamics and Trophic Interactions within the Agricultural Landscape 3. The Role of Seminatural Habitats on Pest and Natural Enemy Populations 3.1. Alternative hosts and prey 3.2. Alternative sources of pollen and nectar 3.3. Shelter and overwintering areas 3.4. Interface between crop and seminatural habitats 3.5. Effect of landscape context on biological control 4. Natural Enemy Biodiversity and Insect Pest Suppression 5. Effects of Crop Management on Pests and their Natural Enemies 5.1. Within-field diversity 5.2. Host plant resistances 5.3. Nitrogen fertilization 5.4. Tillage 5.5. Sowing date, plant density, and harvesting date 5.6. Crop rotation 5.7. Pesticide use 6. General Effects of Farming Systems on Natural Enemy Biodiversity, Pests, and Subsequent Biological Control

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* INRA/AgroParisTech, UMR211 Agronomie, Thiverval-Grignon, France { INRA, INPT/ENSAT, UMR1201 Dynamiques Forestie`res dans l’Espace Rural (UMR Dynafor), Castanet-Tolosan, France Advances in Agronomy, Volume 109 ISSN 0065-2113, DOI: 10.1016/S0065-2113(10)09006-1

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2010 Elsevier Inc. All rights reserved.

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7. Integrating Farming Systems, Crop Management and Landscape Context to Understand Biological Control Mechanisms 7.1. Integrating farming system 7.2. Integrating crop management 7.3. Interaction between farming practices and landscape context 8. Conclusions References

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Abstract There is a growing body of evidence to suggest that the simplification of land uses associated with a strong dependence on agrochemical inputs is decreasing environmental quality, threatening biodiversity, and increasing the likelihood of pest outbreaks. The development of farming systems with greater reliance on ecosystem services, such as biological control of insect pests, should increase the sustainability of agroecosystems. However, the factors responsible for the maintenance or enhancement of natural pest control remain unclear. The goal of this review is, therefore, to expose which elements, from the field to the landscape scale, influence natural enemy populations and pest regulation. We present here the principal effects of seminatural habitats, farming systems, and crop management on the abundance of insect pests and their biological control, with a view to evaluating their relative importance and identifying key elements that regulate natural pest control interactions. Because of the range of spatial and temporal scales experienced by these organisms, we advocate, in studies investigating trophic relations and biological pest control, a clear description of cropping systems and an explicit consideration of seminatural habitats and more generally of the surrounding landscape. Through this review, we also indicate gaps in knowledge and demonstrate the interest of linking agronomy and landscape ecology to understand trophic interactions, maximize natural pest control, and limit pesticide applications. Quantifying the relative importance of both local and landscape scales is a fundamental step in the design and assessment of ecologically sound integrated pest management strategies for farmers.

1. Introduction Modern agricultural landscapes are generally characterized by a high proportion of arable fields, large field sizes, and a high degree of fragmentation of seminatural habitats into small units (Baessler and Klotz, 2006; Tscharntke et al., 2005). There is also a growing body of evidence to suggest that the simplification of land uses associated with a strong dependence on agrochemical inputs is decreasing environmental quality and threatening biodiversity (Evenson and Gollin, 2003; Millennium Ecosystem Assessment, 2005).

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There is, therefore, a need to reduce pesticide use by developing innovative cropping systems to ensure the sustainability of agricultural production. Biodiversity conservation and the development of farming systems with greater reliance on ecosystem services should together increase the sustainability of agroecosystems and landscapes (Altieri, 1999; Hillel and Rosenzweig, 2005). Ecosystem services include production, nutrient cycling, flood regulation, climate regulation, biological control of pests, and aesthetic value (Costanza et al., 1997; Millennium Ecosystem Assessment, 2005; Zhang et al., 2007). The sustainability of an agroecosystem depends on various ecosystem services, but may also be affected by ecosystem disservices, such as herbivory, which decrease productivity and increase production costs (Zhang et al., 2007). For these reasons, natural pest regulation is considered one of the most important services of biodiversity (Fiedler et al., 2008; Schla¨pfer and Schmid, 1999; Wilby and Thomas, 2002), with an estimated value of more than 400 billion dollars (US) per year worldwide (Costanza et al., 1997). The generalized intensification of agriculture and the use of broad-spectrum pesticides decrease the diversity of natural enemy populations (Basedow, 1990; Koss et al., 2005) and increase the likelihood of pest outbreaks (Lawton and Brown, 1993; Swift et al., 1996). Indeed, pesticide use has been shown to be associated with a large decrease in natural pest control services (Cross et al., 1999; Prokopy et al., 1995). Thus, enhancement of the natural regulation functions of agroecosystems appears to be one of the main ways in which we can decrease the use (Wilby and Thomas, 2002) of chemical pesticides for pest control and increase the sustainability of crop production. However, the factors responsible for the maintenance or enhancement of natural pest control remain unclear. Moreover, the environmental and economic benefits to farmers of increasing the activity of natural enemies of crop pests remain a matter of debate, in the absence of clear scientific evidence. Recent reviews have shown that biological control depends on multiple levels ranging from field to landscape scales (Gurr et al., 2003; Tscharntke et al., 2007). It has been shown that community structure, species richness and abundance, and population dynamics and interactions within and between trophic levels are affected by spatial context (e.g., patch size, spatial configuration, landscape composition, habitat connectivity, or even the structural complexity of habitats) (Bianchi et al., 2006; Finke and Denno, 2006; Kareiva, 1987; Marino and Landis, 1996; Tscharntke and Brandl, 2004; Woodcock et al., 2007; Zabel and Tscharntke, 1998). Crop management and farming systems have also been shown to have major effects on species composition, abundance, and distribution in agroecosystems (Bengtsson et al., 2005; Booij and Noorlander, 1992; Ca´rcamo, 1995). However, the relative contributions of crop management, farming systems, and landscape context to pest abundance, natural enemy abundance, and biological control have been poorly studied (but see Roschewitz et al., 2005b).

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We review here the principal effects of landscape context, farming systems, and crop management on the abundance of insect pests and their biological control, with a view to evaluating their relative importance and identifying key elements that regulate natural pest control interactions. We consider here a system with three trophic levels as a general framework, taking host–parasitoid interactions as a particular example, with the aim of providing a complete overview of all the mechanisms and interactions involved in biological control processes. We will begin by exploring the factors driving arthropod dynamics at the landscape scale. We will then move on to the role of seminatural habitats for pest and natural enemy populations and present a concise overview of the main effects of landscape context on natural pest control. We will then present the state of the art on the relationships between natural enemy biodiversity and pest suppression. Thereafter, we will report the effects of various crop management elements at a local scale (i.e., habitat scale) on pest and natural enemy populations. The effects of farming systems on trophic interactions will then be assessed, with the aim of identifying biological control mechanisms at the farm level. This will lead on to the conclusion, in which we will highlight the value of considering the combined effects of landscape, farming systems, and crop management on biological control interactions, focusing particularly on the effects of crop management, which are frequently neglected. Throughout this review, we will highlight the importance of the precise description of crop areas, crop management, and seminatural habitats in studies of trophic interactions and discuss the direct benefits of such approaches for integrated pest management strategies.

2. Arthropod Dynamics and Trophic Interactions within the Agricultural Landscape Large-scale approaches are required for studies of population dynamics and community ecology (Tscharntke and Brandl, 2004; Tscharntke et al., 2007). The need for a large-scale perspective in studies of predator–prey interactions was first highlighted in spatial ecology studies, principally through theoretical and empirical works on the structure and dynamics of fragmented populations (Cronin and Reeve, 2005). In particular, works on metapopulations have increased our theoretical understanding of the dynamics of insect pests and their natural enemies in fragmented landscapes (Hanski and Gaggiotti, 2004; Levins, 1969). In metapopulation theory, the regional persistence of a population is made possible by a stochastic balance between the extinction of local populations and the colonization of previously empty habitat patches (Levins, 1969). It has been suggested that

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habitat fragmentation and dispersal ability are the driving forces behind the regional persistence of host–parasitoid populations (Hanski and Gilpin, 1997; Hassell et al., 1991). The population dynamics of such systems are highly variable and depend on species characteristics and landscape organization (Tscharntke and Brandl, 2004). According to Hanski and Gilpin (1997), a population functions as a metapopulation when its hosts are distributed in discrete patches, local populations on patches have a high probability of extinction, unoccupied patches are available for colonization, and local subpopulations do not fluctuate asynchronously. As reported by Elliott et al. (2008), the first three of these criteria are usually satisfied for most insect pest populations, but the fourth criterion remains uncertain, because climatic factors generally have a major influence on insect pest dynamics. In the case of host–parasitoid interactions, the small body size, high rate of population increase, and specialization are thought to predispose them to metapopulation dynamics (Cronin and Reeve, 2005). However, experimental evidences for key factors that drive host–parasitoid metapopulation are rare. In their review, Cronin and Reeve (2004) described several experimental studies, in which the spatial population structure of eight different hosts and their parasitoids have been characterized. They demonstrated that (i) the population structures of different host–parasitoid systems are highly variable, (ii) the parasitoid and its host generally respond to spatial subdivision at different spatial scales, (iii) parasitoids can cause the local extinction of host populations, and (iv) parasitoids are usually more prone to extinction than their host. Spatial ecology studies have identified diverse responses of populations to habitat loss and fragmentation. A classical metapopulation (sensu Levins, 1969) is one of several spatial population structures that may emerge. Others include mainland-island metapopulations (Pulliam, 1988), ephemeral aggregations of individuals, isolated populations, and synchronized local populations (Hirzel et al., 2007). Hirzel et al. (2007) showed, by modeling, that five classes of spatio-temporal dynamics could be distinguished (i.e., metapopulation, mainland-island, spiral fragments, spatial chaos, and spirals) for host–parasitoid systems with varying three parameters: proportion of suitable habitat, spatial autocorrelation, and host dispersal rate. This study confirmed that dispersal rate and landscape configuration are major factors influencing local extinction and colonization events, highlighting the importance to take the landscape-scale and species-specific traits into account to understand population dynamics and trophic interactions. While the first approach (the metapopulation approach) is based on a strong theoretical background and on mathematical models to predict the responses of species to spatial context, a second more empirical approach came from landscape ecology. Whereas the metapopulation approach considers the matrix to be an unsuitable habitat, the landscape ecology approach considers different classes of patches in the surrounding landscape according

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to their functional role on population dynamics between and within patches. Dunning et al. (1992) described the principal processes affecting populations in landscape-based approaches. Four classes of ecological processes with important effects on local populations have been identified: landscape complementation, landscape supplementation, source/sink dynamics, and neighborhood effects. Landscape complementation occurs in situations in which a species requires at least two different nonsubstitutable resources at particular points in its life cycle. These resources may be foraging patches, breeding sites, or overwintering sites. The presence of a resource in one type of patch is complemented by the presence of the other type of resource nearby in another type of patch, making it possible to support larger populations in the proximity of these patches. According to the landscape supplementation hypothesis, as described by Dunning et al. (1992), the population of the focal patch may be enhanced if that patch is located close to other patches of the same resource or patches that have the same function. In this process, resources within the landscape are substitutable, increasing their accessibility. Source/sink relationships appear when productive patches serve as sources of emigrants, which disperse to less productive patches. Local populations in sink patches cannot be maintained without this immigration. Finally, neighborhood effects exist when the species abundance in a particular patch is more strongly affected by the characteristics of contiguous patches than by those of patches located further away. These four ecological processes have been demonstrated for various species, by empirical studies at the landscape scale (Dunning et al., 1992; Frouz and Kindlmann, 2001; Haynes et al., 2007; Ouin et al., 2004). The general framework proposed by Dunning et al. (1992) links general landscape pattern (structural composition of the landscape) to the habitatspecific responses of organisms (Kareiva, 1990) and the ecological processes of population dynamics. Both the metapopulation and landscape ecology approaches, with their differences and limitations, suggest that a landscapewide perspective is required if we are to understand the dynamics and interactions between local populations. Communities consist of species influenced by different spatial and temporal scales due to species-specific life-history traits, such as the ability to disperse, body size, competition and sensitivity to disturbance, microhabitat specialization, or trophic position. Parasitoid and their hosts, for example, generally react differently to spatial contexts (Cronin and Reeve, 2005; Ryall and Fahrig, 2005; With et al., 1999). Classically, species at higher trophic levels are thought to operate at larger spatial scales and to be less affected by local patch quality, because they tend to disperse to a greater extent (Holt, 1996). However, Tscharntke et al. (2005) found this to be the case only if there is a positive relationship between trophic level and body size (and thus, dispersal abilities). Indeed, predators of the same trophic level

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may experience the surrounding landscape at different spatial scales, depending on their abilities to disperse and specialization, with generalist predators operating at a larger scale than specialist predators (Tscharntke et al., 2005). However, a species operating at a low trophic level, but with a large capacity for active or passive dispersal, may experience the surrounding landscape at a larger scale than a species operating at a higher trophic level, but with poorer dispersal. For example, Roschewitz et al. (2005b) showed that the abundance of cereal aphids at wheat ripening was significantly influenced by landscape complexity at all five spatial scales (from 1 to 3 km) explored in their study, whereas the parasitoids of these aphids responded to landscape complexity at three spatial scales from 1 to 2 km. Moreover, several studies have shown that habitat fragmentation often affects the abundance and diversity of predators and parasitoids more strongly than those of their herbivorous hosts (Kruess and Tscharntke, 1994; Zabel and Tscharntke, 1998). Indeed, species operating at higher trophic levels may be more prone to extinction than those at lower trophic levels, because of their lower densities, more variable population size, narrower and more fragmented distribution of resources, dependence on the successful colonization of patches by hosts of lower trophic levels, and sometimes smaller capacity for dispersal (Davies et al., 2000; Holt, 1996; Kruess and Tscharntke, 1994; Purvis et al., 2000; Thies et al., 2003). Thus, the control of prey and host species by their specialist natural enemies may be disrupted by increasing seminatural habitat fragmentation. As the scale-dependency differs between species and is determined, in particular, by the ability of different species to disperse, local habitat effects may play a major role in population dynamics of species dispersing over short distances, whereas generalist predators are influenced by landscape context at large spatial scales.

3. The Role of Seminatural Habitats on Pest and Natural Enemy Populations Seminatural habitats, such as forests, hedgerows, field margins, fallows, and meadows support a large number of pest and natural enemy species, as they provide a more stable environment than annual crops. Generally, these habitats house a larger proportion of neutral and beneficial arthropods than detrimental arthropods (Denys and Tscharntke, 2002; Marshall, 2004; Thomas et al., 2002). Indeed, such habitats provide life support functions, maintaining populations of alternative hosts and prey for predators and parasitoids (Fig. 1) (Denys and Tscharntke, 2002; Kozar et al., 1994; Pickett et al., 2000; Sotherton, 1984).

Natural enemy populations

Alternative prey/host, sources of pollen/nectar, and shelter

Top-down process (regulation)

Crop management at field and landscape scale

Seminatural habitat in the landscape

Pest populations

Damages (feeding, reproduction)

Pedo climatic conditions

Crop

Bottom-up process, resources availability, and shelter

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Figure 1 The potential effects of crop management and seminatural habitats on each level of a tritrophic chain (solid lines). Dotted lines represent the trophic interactions between each element of the tritrophic chain. Adapted from Gurr et al. (2003).

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3.1. Alternative hosts and prey Noncrop habitats maintain populations of alternative hosts and prey for the parasitoids and predators of crop pests (Denys and Tscharntke, 2002; Kozar et al., 1994; Pickett et al., 2000; Sotherton, 1984; Wyss, 1996). This enhances natural pest control by providing the natural enemies of pests with alternative hosts and prey during periods in which host and prey density is low in fields, or by increasing the fitness of natural enemies. For example, Bianchi and van der Werf (2004) showed, by modeling, that if the infestation of wheat by pest aphids is delayed, populations of the generalist predator Coccinella septempunctata become increasingly dependent on aphid populations in noncrop habitats. Ladybeetle populations are more vulnerable to periods of food shortage when prey availability in noncrop habitats is low (Bianchi and van der Werf, 2004). However, natural enemy population may increase spectacularly following the infestation of crops with pests, leading to a spillover effect, with these insects moving to seminatural habitats, where they may decrease the prey populations of other nonpest species (Rand et al., 2006), thereby potentially decreasing the size of populations of beneficial secondary zoophagous species. The dependence of natural enemy populations on alternative prey or hosts is greater for generalist predators that may feed upon a variety of prey species than for specialist predator species. Many parasitoids and other natural enemies consume honeydew (Wa¨ckers et al., 2005). The presence of sap-feeding alternative prey in noncrop habitats may therefore enhance the control of crop pests. For example, Evans and England (1996) found that levels of alfalfa weevil parasitism (Hypera postica) by the ichneumonid wasp Bathyplectes curculionis were higher when pea aphids were present. Indeed, access to pea aphid honeydew appeared to increase both the fecundity and adult life span of the wasp significantly. Alternative prey may also enhance the biological control of pests because they decrease intraguild predation (i.e., predation among predators that shares the same prey species) (Dinter, 2002). Meyhofer and Hindayana (2000) also showed that, when provided with alternative prey, such as unparasitized aphids, parasitoid mortality due to consumption of mummified aphids by predators diminished. However, habitats providing alternative hosts or prey may also accommodate pest species, thereby increasing pest populations. Indeed, Lavandero et al. (2006) demonstrated that floral resource subsidies may have various effects on phytophagous insects and their natural enemies. Some plant species increase the fitness of herbivores and parasitoids, whereas other species selectively enhance the fitness of parasitoid. Wyss (1996) reported similar effects on different insect pests, but Pfiffner and Wyss (2003) showed that sown wildflower strips increase the fitness of natural enemies of crop pests sufficiently to contain the increase in pest populations, which may also benefit from the wildflower strips.

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3.2. Alternative sources of pollen and nectar Seminatural habitats also act as sources of pollen and nectar, which are essential for many species (Pickett and Bugg, 1998; Wa¨ckers et al., 2005). Several studies have shown that more diverse vegetation, including flowering weeds, for example, results in a greater availability of pollen and nectar, leading to higher densities of carabid beetles (Lys et al., 1994), syrphid flies (Hausammann, 1996; Sutherland et al., 2001), and parasitoids (Patt et al., 1997; Powell, 1986). It has also been shown that many hymenopteran parasitoid species feed on floral nectar ( Jervis et al., 1993; Wa¨ckers, 2001) and that this may lead to higher rates of parasitism (Berndt et al., 2006; Ellis and Farrell, 1995; Stephens et al., 1998). For example, Winkler et al. (2006) reported that nectar feeding is of crucial importance for the survival and fecundity of Diadegma semiclausum in field conditions. They showed that parasitism rates were very low if female parasitoids were deprived of nectar, and much higher if females were supplied with sufficient food. Wa¨ckers (2001) compared the patterns of sugar used by the parasitoid Cotesia glomerata and its phytophagous host, Pieris brassicae. He found that the parasitoid used more types of sugar than its host and that some sugars increased the life span of the parasitoid by a factor of 15, whereas host life span was increased by no more than a factor of three. He also found that some sugars were of nutritional benefit to the parasitoid but not to P. brassicae.

3.3. Shelter and overwintering areas Woody habitats often provide a more moderate microclimate than the center of fields, protecting natural enemies against extreme temperature variations (Landis et al., 2000; Rahim et al., 1991). Various studies have explored the impact of the proximity of noncrop habitats and have shown that parasitism levels of insect pests are higher and close to the edges of fields bordering noncrop habitats than in the center of fields due to a moderate mild microclimate and nectar availability (Altieri and Schmidt, 1986; Landis and Haas, 1992; Thies and Tscharntke, 1999). Seminatural habitats also provide natural enemies and pests with good conditions for overwintering, determining their spatial distribution in the spring. For instance, they allow Episyrphus balteatus, a major aphid predator syrphid fly, to overwinter at different stages in various types of shelter. It overwinters as adult females along southern edges of fragmented forests and at final larval stage along northern ones where aphids developed in the fall, thus determining its spatial distribution in the spring (Sarthou et al., 2005). According to Keller and Ha¨ni (2000), 9 in every 10 auxiliary species require a noncrop environment at one stage of their life cycle, whereas this is the case for only one in two pest species. Most auxiliary species are, therefore, heavily dependent on the resources provided by seminatural areas, requiring them to travel back

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and forth between uncultivated habitats and crops. However, even if noncrop habitats appear to be less important for insect pest species than for natural enemies, they may nonetheless have a major effect on pest population dynamics, particularly during the overwintering period. Indeed, several studies have reported the overwintering of pest species in uncultivated areas (Leather, 1993; Pywell et al., 2005). Pywell et al. (2005) identified several oilseed rape pest species (Phylotreta atra, P. undulate, and Meligethes aeneus) in hedgerows and field margins, and showed that the abundance of these pests was greater in the hedgerow habitat than in field margins. Of the six major pests of oilseed rape crop (i.e., pollen beetle (M. aeneus), brassica pod midge (Dasineura brassicae), cabbage seed weevil (Ceutorhynchus assimilis), cabbage stem weevil (Ceutorhynchus pallidactylus), rape stem weevil (Ceutorhynchus napi), and cabbage stem flea beetle (Psylliodes chrysocephala)), only two species, the brassica pod midge and the rape stem weevil, are not dependent on seminatural habitats for overwintering or summer diapause. These two pests emerge from the previous year’s oilseed rape fields, and the brassica pod midge may even emerge from fields on which oilseed rape has been grown in the last 4 years (Alford et al., 2003). Leather (1993) also demonstrated that a major cereal pest, the aphid Sitobion avenae, overwinters on perennial grasses. However, Vialatte et al. (2007) showed that the populations of this species (on cereals and on field margins) remain genetically separated. This strongly suggests that fields are not colonized by S. avenae from the field margins, but by aphids coming from early sown wheat crop and crop volunteers.

3.4. Interface between crop and seminatural habitats The agroecological functions of seminatural habitats described earlier have highlighted the complementary nature of crop and noncrop areas for pests and their natural enemies, and emphasized therefore the role of habitat edges. Rand et al. (2006) hypothesized that the resources present in one type of habitat may subsidize shared consumers such that they have a greater impact on resources in the second type of habitat. Seminatural habitats have been seen as important sources of natural enemies that spread into crop fields, potentially enhancing the biological control of pests if in close enough proximity to the field. The variety of resources available in seminatural habitats allows the development of beneficial arthropod populations, which then spill over into crop fields (Tscharntke et al., 2007). Indeed, empirical and modeling studies have demonstrated that the quality and quantity of seminatural habitat patches adjacent to the crop may affect top-down control (Bianchi and Wackers, 2008; Olson and Wackers, 2007). However, Rand et al. (2006) demonstrated that spillover effects from agricultural to seminatural habitats may also occur, highlighting several mechanisms. There is evidence that the primary productivity of the habitat

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determines the direction of spillover effects. Areas of low productivity are strongly affected by spillover effects from more productive habitats. Indeed, highly productive systems, such as cultivated areas, support higher prey densities, resulting in larger natural enemy populations and higher rates of emigration to less productive habitats by passive diffusion. It has also been shown that the temporal dynamics of resources across the landscape, particularly between cultivated and seminatural habitats, greatly affects the size and direction of spillover effects. Indeed, resources in the agricultural landscape vary strongly over time, as cultivated habitats provide highquality resources for only part of the year. The abrupt decline in habitat quality due to harvesting leads to the active emigration of predators from the cultivated areas toward more stable seminatural habitats. Rand et al. (2006) explained that spillover effects may also result from complementation between the resources in seminatural and cultivated areas. The access to resources in both types of habitat and the positive effects of this complementation on fecundity and longevity may account for the greater aggregation of predators and stronger top-down control near field edges.

3.5. Effect of landscape context on biological control Published studies on insect pest dynamics have shown that herbivore and natural enemy populations often respond to a spatial scale encompassing the crop or seminatural habitat patch and various temporal scales. Seminatural habitats have been shown to be key elements for species development and survival. These habitats serve as the starting point for field colonization to various extents by many species that are beneficial, damaging, or neutral to crops (Dennis and Fry, 1992; Denys and Tscharntke, 2002; Marshall, 2004; Nentwig, 1988; Thomas et al., 1992). The distance between fields and seminatural areas and their spatial organization are therefore important in determining insect population dynamics. Most of the studies have adopted a dichotomous approach, considering crop and noncrop habitats in their analyses of the influence of the landscape on pest and natural enemy populations. Bianchi et al. (2006), in a review, tested the hypothesis that biological control of herbivores is enhanced in complex landscapes with a high proportion of seminatural habitats. They analyzed 28 studies focusing on pest pressure and/or natural enemy populations as a function of landscape composition, for various crops. They found that pest pressure was lower in complex landscapes, in 45% of the 10 studies they reviewed. They also found that natural enemy activity was enhanced by complex landscapes in 74% of the studies reviewed (24 publications). In 21% of the studies reviewed, no effect of landscape composition was reported, whereas in 5%, natural enemy activity was lower in complex than in simple landscapes. Thus, although most of the studies showed higher natural enemy activity, only 45% of them showed this to have reduced pest pressure in more

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complex landscapes. This indicates that there is considerable variability in the responses of organisms to landscape structure, with landscape complexity having no clear effect on pest suppression. Ever since this review was conducted, various studies have explored the impact of landscape diversity on natural enemy and pest populations, confirming these general conclusions. All six studies focusing on the impact of landscape diversity on natural enemies (parasitoids, beetles, and spiders) found that landscape complexity significantly increases natural enemy richness or abundance (Bianchi and Wa¨ckers, 2008; Drapela et al., 2008; Gardiner et al., 2009; Marino et al., 2006; Oberg et al., 2008; Perovic´ et al., 2010). Five studies published since 2006 dealing with the effect of landscape context on insect pest abundance or damage reported various responses to landscape organization (Grilli and Bruno, 2007; Perovic´ et al., 2010; Ricci et al., 2009; Valantin-Morison et al., 2007; Zaller et al., 2008b). These studies focused on pest of various crops, including oilseed rape, corn, or orchards. Landscape complexity was not assessed directly, but pest abundance or damage was found to be related to landscape variables that could be interpreted in terms of landscape complexity. For example, Grilli and Bruno (2006) found that the abundance of the corn planthopper (Delphacodes kuscheli) increased with the abundance and connectivity of its host patches. Thus, a simple landscape with a high proportion of the area under corn tends to support higher pest pressures than a more complex landscape. Conversely, in their study of oilseed rape pests, Zaller et al. (2008b) demonstrated that pollen beetle and brassica pod midge pressures decreased with increasing host patch abundance and increased with increasing abundance of noncultivated areas. In this case, more complex landscapes seem to enhance pest pressure. Moreover, conflicting results concerning landscape effects on pest populations have been published. For example, three studies have reported three different effects of landscape context on pollen beetle dynamics (Thies et al., 2003, Valantin-Morison et al., 2007, Zaller et al., 2008b). Thies et al. (2003) found that pollen beetle was not affected by oilseed rape abundance in the landscape, whereas Valantin-Morison et al. (2007) demonstrated a positive effect of host areas and Zaller et al. (2008b) reported a negative effect. Moreover, Thies et al. (2003) found a negative correlation between landscape complexity and pest damage, whereas Zaller et al. (2008b) found a positive relationship between pest abundance and landscape complexity. Thus, the variability of responses of insect pests to landscape complexity reported in the previous studies appears to be multifactorial and not completely understood, implying further studies on pest populations to understand general patterns. Indeed, it depends on biological characteristics of pest species when different pests are involved, methodological differences between studies, geographic position of the studied areas, the way in which the landscape is described (e.g., grain of resolution), and the effect of farming practices dispatched within the landscape. Another complex

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effect that can be observed in conservation biological control studies is that potential pest species may benefit from conditions at the local or landscape scale that also favor natural enemies (Lavandero et al., 2006; Perovic´ et al., 2010). In landscape-scale studies, the relationships between arthropod populations and seminatural habitats within the landscape have generally been explored through a landscape composition approach (i.e., in terms of proportions of each type of land uses). However, such approaches do not take into account the spatial arrangement of land uses (i.e., the functional connectivity) and their specific effects on populations (e.g., the effects of the landscape matrix on dispersal activity). We found one study that investigated the effects of spatial arrangement on biological control, using a cost– distance approach in which land-use types can be assigned different costs to represent the degree of favorability for a given species (Perovic´ et al., 2010). In this study, the authors found various responses to functional connectivity in the landscape depending on the species considered. However, they concluded that the spatial arrangement of noncrop areas has a stronger effect than does noncrop proportions alone on natural enemy abundance with large dispersal abilities. According to the authors, the cost–distance approach makes it possible to identify both suitable habitats in the landscape and the spatial configuration of these habitats, to enhance colonization by natural enemy populations. Therefore, assessing functional connectivity of the landscape and its influence on biological control interactions appears to be an interesting approach for habitat manipulation and pest management strategies.

4. Natural Enemy Biodiversity and Insect Pest Suppression Exploration of the relationships between natural enemy biodiversity and the suppression of arthropod herbivores is of crucial importance in our comprehension of the value of biodiversity and its impact on ecosystem services. Duelli and Obrist (2003) reported that for short-term pest control considerations, the abundance of beneficial organisms may appear more important than species richness, because prey and hosts are reduced by the number of antagonistic individuals rather than by species number. However, with a longer-term perspective, maintenance of a high diversity of natural enemy species is certainly more important than abundance, as a high functional diversity increases the stability of ecological functions and insures resilience (i.e., the capacity of the system to withstand disturbances and reorganize itself after perturbations) (Bengtsson et al., 2003; Tilman, 1996). The regulation of insect pest populations in agricultural landscape may,

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therefore, result in trade-offs between natural enemy abundance and richness. Various effects of natural enemy diversity on herbivores suppression have been proposed in the literature. Recently, Letourneau et al. (2009) have summarized the main possible emergent effects of higher natural enemy biodiversity on pest suppression which can be positive, negative, or neutral: 









Herbivore mortality resulting from different natural enemy species can be equal (additive) or greater (synergetic) than the summed mortality caused by each species. This outcome is based on the species complementary model which includes resource-use differentiation such as predation at different life stages, at different periods in the season, or at different spatial positions, or foraging in ways that facilitate predation by other species. As it has often been observed that one natural enemy species can cause most of the mortality of a given herbivore, then the sampling effect model suggests that if the natural enemy diversity increases, the probability that this superior species will be present, increases too. However, negative sampling effect may also occur, because the probability of including a strongly disruptive natural enemy may increase as species richness increase (Loreau and Hector, 2001; Straub et al., 2008). The insurance model suggests that the more natural enemy species are present, the greater are the chances to establish and maintain positive interactions among natural enemy species, cover heterogeneous conditions, and overcome potential negative interactions (Yachi and Loreau, 1999). Negative interactions among natural enemy species, such as intraguild predation (i.e., predation among predators that share the same prey species), hyperparasitism (i.e., the development of a secondary parasitoid at the expense of a primary parasitoid which already parasitized a host insect), or behavioral interference, may have subtractive effects on herbivore mortality. Neutral effects of increasing natural enemy diversity on pest suppression can be observed due to minimal interactions among natural enemy species or by canceling the effects of positive and negative interactions. Such effects are expected to occur when natural enemy species are functionally redundant (Straub et al., 2008).

In the literature, a large number of studies have reported evidences for each of these possible effects (Finke and Denno, 2005; Rosenheim, 2007; Schmitz, 2009; Snyder et al., 2006; Straub and Snyder, 2006; Wilby et al., 2005). In order to synthesize the state of the art on the relationships between natural enemy biodiversity and herbivore mortality in different ecosystems, Letourneau et al. (2009) performed a meta-analysis on this topic. Their results highlight the importance to take natural enemy biodiversity into account in agricultural systems when interested in insect pest control.

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Moreover, they clarify the general pattern of response of herbivores to higher natural enemy biodiversity in agricultural areas. The authors found that almost 70% of the studies reviewed (a total of 266 studies) reported more effective control for higher levels of natural enemy richness, suggesting that positive, complementary interactions between natural enemy species predominate over negative, antagonistic interactions. Negative interactions, such as intraguild predation, can be reduced in complexstructured vegetation and complex food webs, respectively, through avoidance between natural enemies and higher prey and host availability (Finke and Denno, 2002; Meyho¨fer and Hindayana, 2000). Therefore, these important results suggest that conservation of natural enemy biodiversity and pest control are compatible with each other and, in many cases, complementary goals (Straub et al., 2008). However, the potential negative effects that may occur in some cases imply to always consider pest populations and effective biological control to examine effects of natural enemy diversity in conservation biological control studies. Letourneau et al. (2009) reviewed studies carried out in different ecosystems ranging from natural to agricultural systems, and were therefore able to compare the strength of the relationship between natural enemy diversity and herbivore suppression in each type of system. They found that there was no statistical significant relationship between higher natural enemy diversity and herbivore suppression in natural systems, but that this relationship was very strong in agricultural systems, suggesting an important potential biological control in these systems. These results are consistent with the conclusions of Halaj and Wise (2001) who found that removing predators of herbivores led to higher plant damage in agricultural systems than in natural systems.

5. Effects of Crop Management on Pests and their Natural Enemies Unlike seminatural habitats, arable fields are generally thought to be subject to major disruption due to agricultural practices. Pest and natural enemy populations may depend on arable fields as a source of potential hosts or prey, pollen and nectar resources, and diapause or overwintering areas. This dependence is particularly strong when the proportion of seminatural habitats in the landscape is low. In this case, natural enemies are highly susceptible to the effects of crop management at the field scale. We provide here a concise overview of the main crop management effects on each element of a trophic chain with three levels: the plant, the phytophagous pest, and its natural enemy (Fig. 1). Each trophic level is represented here at the population or community level.

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5.1. Within-field diversity Within-field diversity is known to have a major impact on trophic interactions and biological control (Andow, 1991). In a review, Andow (1991) identified 209 published studies dealing with the relationships between vegetation diversity and phytophagous arthropod species. Of the 287 phytophagous species identified in these studies, 52% appeared to be less abundant in diversified agroecosystems than in monocultures, whereas 15% were found at higher densities in diversified systems. Indeed, crop monocultures are environments in which it is difficult to establish efficient biological pest control, because the resources they provide are insufficient to ensure that natural enemy populations perform well. Thus, increasing diversity in the field by intercropping, cover cropping, or even tolerating weeds may enhance biological control and reduce the damage resulting from insect pest attacks. Many studies have tested this hypothesis and shown that higher crop diversity significantly reduces pest damage (Nickel, 1973; Norris and Kogan, 2005; Perrin, 1977; Risch, 1983; Vandermeer, 1989). Various hypotheses have been put forward to explain the potential mechanisms involved in interactions between within-field diversity and pest damage. Pimentel (1961), and then Root (1973), developed the “Enemy Hypothesis”, according to which, the observed decrease in the number of herbivores in intercropped results partly from the attractiveness of the intercrop for more abundant and/or efficient predators and parasitoids, presumably because more resources and habitats are available than in monocultures. Tahvanainen and Root (1972), and then Root (1973) also developed an alternative “Resource Concentration Hypothesis,” according to which, the probability of herbivores finding their host plant, remaining on that plant, and reproducing on it is higher in monocultures than in mixtures of several species in which the resource is diluted among other resources. This hypothesis is based on chemical and/or physical confusion of the pest due to mixed cues (the Disruptive Crop Hypothesis, Vandermeer, 1989). Finally, the presence of a second crop within or close to the principal crop may also lead to high herbivores densities on the second crop, thereby lowering the incidence of herbivores on the main crop (the Trap Crop Hypothesis, Vandermeer, 1989). However, higher within-field diversity does not always result in better pest control. Increasing diversity may also aggravate pest problems (Andow, 1991) or hinder beneficial insect activity (Andow and Risch, 1985), as it may enhance interspecific competition or intraguild predation (Broatch et al., 2010).

5.2. Host plant resistances Host plant resistance has been shown to decrease herbivore population development and/or the damage caused by pests significantly (Francis et al., 2001; Sharma and Ortiz, 2002; Van Emden, 1991). There are two major types of resistance: induced resistance (triggered by extrinsic biotic or

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abiotic factors) and constitutive resistance (always expressed) (Kogan, 1994). Both types of resistance directly affect herbivore populations through antixenosis, antibiosis, or tolerance. The effects of host plant resistance on entomophagous insects are well documented for interactions in a threelevel trophic system, and several mechanisms have been highlighted. For example, Brewer et al. (1998) reported that parasitoid populations were larger on susceptible barley cultivars than on cultivars resistant to aphids, due to the larger aphid populations on susceptible cultivars. However, parasitism rates were similar for the two cultivars. This density-dependent effect is not the only mechanism, and plant resistance often affects herbivorous species development, fecundity, and population growth. Since natural enemies, particularly parasitoids, select their host depending on weight, size, or growth stage, plant resistance may indirectly affect the biological control of pests. Regarding predation, different aphid host plants can directly affect predator development by supplying preys with different nutritional values. Similarly, different crop habitats may affect the biological traits of predators at the individual or community level, by modifying the abundance of prey available (Bommarco, 1999). Kogan (1994) reviewed the benefits and pitfalls of using host plant resistance as a single pest management factor. Specificity, cumulative efficacy, potential compatibility with other tactics, and persistence were among the advantages of plant resistance identified. However, this approach was also found to be subject to a number of drawbacks, including the time required to develop resistant varieties, genetic limitations, and conflicting resistance traits.

5.3. Nitrogen fertilization Several studies have shown that herbivorous insects usually select their host plants on the basis of potential quality as a host and as a source of food (Dosdall et al., 1996; Finch and Collier, 2003; Hopkins and Ekbom, 1996; Moon and Stiling, 2000). Moreover, plant resistance to insect pests varies considerably with age, growth stage, and physiology of the plant (Altieri and Nicholls, 2003). Nitrogen fertilization may, therefore, play an important role in population dynamics and performances of herbivores by affecting plant resistance, host selection mechanisms, or the ability of plants to recover from the damage inflicted by herbivores. Two hypotheses have been initially developed to account for the interactions between host plant quality and pest populations: the Plant Stress Hypothesis and the Plant Vigor Hypothesis. According to the Plant Stress Hypothesis, physiologically stressed plants are more susceptible to pest attacks due to (i) direct effects, such as improvements in the nutritional quality of the plant (e.g., increase in amino-acid content) or a decrease in its resistance mechanisms, or (ii) indirect effects, such as reduced efficiency of natural enemies (White, 1984). According to the Plant Vigor Hypothesis, many herbivores preferentially feed on vigorous plants, because they provide a

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better source of food (Price, 1991). Several studies have provided evidence supporting these two hypotheses, for a wide range of herbivores (Bruyn et al., 2002; Craig and Ohgushi, 2002; Dosdall et al., 2004; Jones and Coleman, 1988; Mattson and Haack, 1987). Although these two approaches are competing paradigms and that no general pattern is emerging from the literature, both argue that plant physiological status and plant growth are important determinants of the damage inflicted by insect pests, highlighting the major role of plant nitrogen content. According to Pimentel and Warneke (1989), variations in the responses of pest populations to nitrogen fertilization may be explained by differences in the feeding behavior of herbivores. Scriber (1984), in a review of 50 years of research on crop nutrition and insect attack, identified 135 studies reporting higher levels of damage and/or growth for leaf-chewing insects or mites in high nitrogen-fertilized crops, versus fewer than 50 studies in which herbivore damage was reduced by normal nitrogen fertilization. Waring and Cobb (1992), in a review of 186 studies investigating insect and mite responses to soil or host plant nutrient levels, reported a similar pattern, with a predominance of positive responses to nitrogen fertilization among herbivores (60% of the studies). Recent studies have focused on the effect of plant fertilization and quality on the third trophic level (i.e., the natural enemies). Sarfraz et al. (2009) studied the effect of fertilization on the oilseed rape pest Plutella xylostella and its parasitoid Diadegma insulare. They demonstrated that D. insulare performed better on plants grown with high levels of fertilizer and that the proportion of P. xylostella escaping control by D. insulare was higher on plants with low levels of fertilizer. In this study, the quality of the plants on which P. xylostella hosts were reared significantly affected developmental times of both female and male D. insulare. Investigations of the effect of nitrogen fertilization on the different trophic levels and on tritrophic interactions are therefore important, as they highlight the complex bottom-up effects to be taken into account in integrated pest management approaches.

5.4. Tillage Soil tillage is known to have major effects on the local habitat, soil-inhabiting organisms, and relationships between organisms (El Titi, 2003; Kladivko, 2001; Stinner and House, 1990). In particular, the intensity of soil tillage, the method used, the number of operations, the frequency, and the period of soil cultivation seem to have an impact on predatory arthropods. Reduced tillage systems create a more stable environment, encouraging the development of more diverse species (including decomposer communities) and slower nutrient turnover (Altieri, 1999). The general pattern is that both the abundance and diversity of the soil fauna tend to increase with decreasing tillage intensity (Ca´rcamo, 1995; Holland, 2004; Kendall, 2003). However, species differ in their response to soil tillage and local habitat disturbance sometimes

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in opposite ways. Indeed, the response observed is highly dependent on the ecological characteristic of the species concerned, such as body size, life cycle, diet, dispersal abilities, and population size (Baguette and Hance, 1997). Many of the species inhabiting fields may be able to withstand some degree of soil disturbance, but certain life cycle stages, such as pupae, less mobile larvae, and estivating or hibernating adults, are particularly vulnerable (Kendall, 2003). Different patterns of response to soil tillage have been reported: direct effects on natural enemies, especially parasitoids, due to mechanical damage, greater exposure to predation, or the immediate emigration of arthropods to adjacent habitats. Soil cultivation may also have indirect effects on arthropod predators by modifying habitat quality, removing microhabitats for reproduction, or decreasing prey densities. The crop residues left on the soil in reduced tillage systems may indirectly impact herbivore and predator populations, respectively, through physical barrier effects altering host location and increases in organic matter availability which enhances size, diversity, and activity of predators (Kladivko, 2001). Soil tillage has been shown to reduce significantly the abundance of various invertebrates, such as epigeic earthworms (Chan, 2001) and springtails (Petersen, 2002), which may serve as an alternative prey for many polyphagous predators. Reductions in such populations due to intensive tillage may therefore have an indirect effect on predator populations. Thorbek and Bilde (2004) studied the effects of different mechanical crop treatments on generalist predator arthropods and have found that these indirect effects (i.e., habitat deterioration) of soil cultivation may have a stronger overall impact on arthropod dynamics than direct mortality. They also demonstrated that soil cultivation and grass cutting cause the direct and indirect mortality and emigration of generalist predator arthropods, including spiders, in particular. The effects of postharvest soil tillage on parasitoid populations have been studied principally in the case of oilseed rape crop. Nilsson (1985) showed that inversion tillage strongly affects the survival and emergence rates of parasitoids overwintering in the soil. Soil tillage may therefore have an indirect effect on the rates of parasitism of oilseed rape pests in the following year. For example, Ferguson et al. (2003) found that although 24% of the M. aeneus pest population was parasitized, fewer than 2% of the parasitoids survived over winter to emerge as adults in the following spring, indicating a strong impact of soil cultivation on natural enemy populations.

5.5. Sowing date, plant density, and harvesting date Sowing date is known to affect the level of damage resulting from insect pest attacks and the ability of plants to compensate for this damage. Dosdall and Stevenson (2005) demonstrated a strong effect of oilseed rape sowing date on flea beetle (Phyllotreta cruciferae) damage. Indeed, greater damage was observed on spring-sown oilseed rape than on fall-sown oilseed rape. The damage to oilseed rape apical meristems inflicted by flea beetles may

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prevent a compensatory response, but by the time of greatest injury, crops have enlarged apical meristems, making them less susceptible to damage. Oilseed rape sown in the fall is able to progress beyond the vulnerable cotyledon stage by the time that flea beetles inflict the most damage, resulting in less crop damage. A similar effect has been reported for corn. Early-sown corn is less susceptible to corn earworm and stem borer, Diatrae grandiosella (Bajwa and Kogan, 2004). This lower susceptibility results from the tendency of D. grandiosella to lay fewer eggs on more mature plants, which have already passed their critical growth stage before most of the larvae begin to feed (Herzog and Funderburk, 1985). However, studies of insect pest community may reveal antagonist effects of sowing date. For example, Valantin-Morison et al. (2007) have shown that the early sowing of winter oilseed rape tends to increase cabbage root fly (Delia brassicae) damage, but is associated with a lower level of attack by cabbage stem flea beetle (P. chrysocephala). Differences in the functional composition of invertebrate assemblages between sowing seasons have been reported in arable systems, consistent with a direct effect of sowing date on predator communities (Douglas et al., 2010; Hawes et al., 2009). However, the impact of sowing date on top-down control has yet to be evaluated. The original Resource Concentration Hypothesis (Root, 1973; Tahvanainen and Root, 1972) predicted an increase in herbivore density per host plant with increasing plant density. However, despite the confirmation of this hypothesis in many cases (Andow, 1991), several recent studies have invalidated this prediction (see Yamamura, 1999, for a review), providing support for a Resource Dilution Hypothesis (Otway et al., 2005; Rhainds and English-Loeb, 2003) associated with different patterns of responses. For example, Valantin-Morison et al. (2007) found a negative correlation between plant density and oilseed rape damage due to root maggot, cabbage stem flea beetle, and pollen beetle. Harvesting produces a brutal perturbation of the agroecosystem involving microclimate changes that affect natural enemy populations. According to Riechert and Lockley (1984), harvesting has a greater effect on spider communities than the use of pesticides. The effects of harvesting depend on its timing. For spring crops (such as corn), harvesting occurs sufficiently late for most of the predatory species to be at the end of their period of activity and to have reached their overwintering sites. For winter crops (such as winter oilseed rape and most cereals), harvesting dates generally coincide with the period during which the abundance and activity of some predators are maximal (Bu¨chs, 2003).

5.6. Crop rotation Rotation of annual crops has been empirically developed by farmers to reduce and control soil-borne pests and disease proliferation. By the midtwentieth century, a well-developed rotation consisted of six to eight

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different crops in sequence (Ha¨ni et al., 1998). An increase in economic pressure and food demand led farmers to make greater use of pesticides and to maximise land use. The rotation was reduced to a few species, leading to an increase in pest proliferation and a decrease in biodiversity of beneficial species. Bu¨chs et al. (1997) studied the effects of different crop rotation intensities on the arthropod community in a sugar beet rotation and an oilseed rape rotation. They showed that certain pest species were favored by an increase in the intensity of crop rotation, whereas some beneficial insects were unable to establish stable populations in arable crops with intensive rotations. The authors found that the number of individuals, species richness, body length, and reproductive rates of beneficial insects increased with the progressive extensification of crop sequences, particularly in set-aside areas subjected to natural succession. O’Rourke et al. (2008) studied the effects of rotations on ground beetle populations, by comparing assemblages between a system involving conventional chemical and a 2-year rotation system, and a system with low-input levels and a 4-year rotation. They reported the same response pattern as Bu¨chs et al. (1997): carabid beetle activity density and species richness were higher in the low-input, 4-year rotation than in the conventionally managed, 2-year rotation.

5.7. Pesticide use Pesticides have been widely studied and have been shown to have a negative effect on natural enemy populations in many different studies (Chabert and Gandrey, 2005; Koss et al., 2005; Langhof et al., 2003; Tietjen and Cady, 2007). Both direct and indirect effects on the third trophic level have been highlighted. For example, Ulber et al., (2010) have demonstrated that many parasitoid species of oilseed rape pests are directly affected by the late spraying of insecticides, at around the time of flowering and by aphid insecticide on wheat. Indeed, parasitoid populations emerge from previous year oilseed rape field (generally, wheat fields) 1–2 weeks before rapeseed flowering and are particularly active in the crop during flowering, searching for suitable hosts. Different studies have also proved an important detrimental effect of insecticide on the auxiliary fauna (such as spiders, carabids, staphylinids, syrphids, or parasitoids) (Dennis et al., 1993; Gonzalez-Zamora et al., 2004; Langhof et al., 2003;Wang et al., 1993). Walker et al. (2007) have provided evidence of indirect nontarget effects of the insecticides used to control the lettuce aphid, Nasonovia ribisnigri, on one of its predators, Micromus tasmaniae. Other studies have considered the impact of pesticide treatments on behavioral components and the recolonization abilities of beneficial arthropods (Desneux et al., 2006; Salerno et al., 2002). For example, Salerno et al. (2002) demonstrated changes in the behavior of insecticide-treated parasitoids that might influence their foraging ability and parasitism rates, due to changes in their response to host cues. Desneux et al.

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(2006) reported reductions in the recolonization abilities of adult parasitoids from treated crops. Various studies have also demonstrated an indirect negative effect of herbicide applications on invertebrate populations through the reduction of weeds and the resources they provide (Brooks et al., 2003; Heard et al., 2006). Finally, it has been demonstrated at a very large scale that pesticide use reduces the opportunities for biological pest control in agroecosystems throughout Europe, where agricultural intensification has been promoted for several decades (Geiger et al., in press).

6. General Effects of Farming Systems on Natural Enemy Biodiversity, Pests, and Subsequent Biological Control In the light of the previous results, the relationships among farming systems, natural enemy diversity, and insect pest suppression appear to be a key element in our understanding of natural pest control mechanisms. In the last decade, an increasing number of studies have dealt with the impact of farming systems on the diversity and abundance of fauna, particularly as concerns species involved in natural pest control. Most of these studies have compared organic and conventional farming systems (sometimes, integrated farming systems), with the aim of evaluating the impact of organic farming on the diversity of different biological groups (Booij and Noorlander, 1992; O’Sullivan and Gormally, 2002). Hole et al. (2005), in a review of 76 studies, clearly demonstrated that the species abundance and/or richness of several taxa, ranging from plants to mammals and birds, tended to be higher on organic than on conventional farms. Bengtsson et al. (2005) analyzed the effects of organic farming in a meta-analysis of 66 publications comparing organic and conventional systems. They found that species richness was generally about 30% higher, on average, in an organic farm. Analysis of the effects of farming systems on different biological groups, such as birds, arthropods, soil organisms, and plants, revealed a heterogeneous response of species richness to farming systems. The species richness of predatory arthropods appeared to be increased by organic farming, whereas this was not the case for nonpredatory arthropods. Bengtsson et al. (2005) also reported a 50% increase in the species abundance of all organisms in organic farming systems, but with strong variations between groups: predatory insects, soil organisms, and plants responded positively to organic farming, whereas nonpredatory insects and pests did not. However, even if organic farming systems tend to support higher levels of biodiversity (Bengtsson et al., 2005; Hole et al., 2005), this does not necessary imply that such systems provide more effective biological control of pests. A recent study (Macfadyen et al., 2009a) analyzed the differences in natural pest

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control between organic and conventional systems, using a food web approach on a three-level food chain (plant, herbivore, and parasitoid) at the whole-farm scale. The authors showed that biodiversity for all three trophic levels was significantly higher on organic farms and confirmed the results of Bengtsson et al. (2005). They also highlighted significant structural differences in food webs between organic and conventional farms, with herbivores in organic farming systems being attacked by a larger number of parasitoid species than those on conventional farms. However, differences in biodiversity and food web structure between farming systems did not result in a better natural pest control on organic farms, because no difference in parasitism rates was found. The response to farming systems is highly variable and depends on the life-history traits of the species concerned. Some of the elements influencing the abundance and diversity of biological groups are not particularly related to the type of farming system. It is therefore important to consider crop management and farming system features when trying to understand the interactions between natural enemy and herbivore populations. For example, the type of soil tillage is an important element determining the survival of natural enemies that is independent of the farming system. Moreover, several studies have demonstrated that organic farms tend to be located in more heterogeneous landscapes with higher proportions of seminatural habitats, smaller field sizes, and higher and wider less intensively managed hedgerows (Langer, 2001; Norton et al., 2009). It is therefore also important to take into account the landscape context when considering the effects of cropping systems, so that the relative importance of these two aspects can be determined and confounding effects avoided. Indeed, Macfadyen et al. (2009b) found no significant difference in aphid parasitism rates between organic and conventional farming systems, probably because landscape context affected the results and was not taken into account in their study. They concluded that differences between systems may be more obvious in a more homogeneous landscape that brings out cropping system effects. Hole et al. (2005) highlighted several inconsistencies between studies, almost certainly due to the complexity of the interactions between environmental variables and between taxonomic groups. Indeed, other factors, such as location, climate, crop type, and species, are important elements affecting the relationship between farming systems and biological control.

7. Integrating Farming Systems, Crop Management and Landscape Context to Understand Biological Control Mechanisms 7.1. Integrating farming system As pointed out earlier, several studies have reported that organic systems tend to support higher biodiversity levels. Indeed, synthetic chemical insecticides have a major impact on natural enemies, pests, and general biodiversity

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(Duffield, 1991; Koss et al., 2005). Several recent studies have thus integrated different types of farming systems (generally, organic vs. conventional) into landscape studies, to determine whether the landscape structure or the farming system is more relevant when investigating biological control interactions. We therefore collected articles evaluating the impacts of both farming and landscape features on the activity of natural enemy populations. All these studies broke farming systems down into two main types: organic and conventional systems. Generally, pairs of organic and conventional fields embedded within the same landscape were selected to separate the effects of landscape and farming system. Landscapes were mostly described in terms of the percentage of noncrop elements in the landscape or the Shannon habitat diversity index. Different indices were used to quantify natural enemy populations in these studies: species richness, activity-density, parasitism rates, or natural enemy conditions. If different results were reported in a given study, due to an effect of the year or site, for example, we added a coefficient corresponding to the proportion of observations contributing significantly to the related effect (positive, negative, or neutral effect). Few studies have reported both landscape and farming system effects on natural enemy populations and their potential for biological control. We identified nine studies (Clough et al., 2005, 2007; Eilers and Klein, 2009; ¨ stman et al., 2001a,b; Purtauf et al., 2005; Roschewitz et al., 2005b; O Schmidt et al., 2005; Weibull et al., 2003) on natural enemies of insect pests that considered these two factors simultaneously, but only three of them evaluated effective biological control (i.e., have also considered pest populations in the same study). Most of the studies dealt with natural enemies found in cereal fields and involved different types of organisms such as spiders, carabid beetles, staphylinids, and parasitoids. The effect of landscape was generally clear: more complex landscapes with high proportions of seminatural habitats promoted natural enemy populations in 83.3% of cases, and had no significant effects in 16.7% of the studies. The impact of the farming system was more heterogeneous. Indeed, in 50% of cases, the farming system had no particular effect on species richness or in activity density of the natural enemies. In 38.8% of studies, organic systems were found to have a positive effect on the species richness, activity density, or conditions of natural enemies. Negative effects of organic farming on natural enemy populations were also reported in 11.1% of the cases. Landscape context had a stronger effect than the farming system in 50% of cases. Only one study (11.1% of cases) (Clough et al., 2007) found that landscape context had no effect on natural enemies (Staphylinids). Both landscape composition and farming systems were found to have major effects on natural enemy richness, conditions, or activity density in 38.8% of studies. Thus, these studies bring out variable results about natural enemies’ response to farming systems and subsequent pest control. The effect of the surrounding landscape on natural enemies seems to be greater than that of

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the farming system. Bengtsson et al. (2005) reported a similar pattern in a study of biodiversity and abundance in organic agriculture. Farming systems only partly accounted for the variation in species richness, activity density, conditions, or parasitism rates, whereas landscape context effects predominated in the studies reviewed. Thus, these studies revealed that populations may be influenced by farming systems on a small scale and that differences between farming systems may result from behavioral responses and individual decisions (Bengtsson et al., 2005), whereas landscape features provide information about population dynamics tightly linked to species biology and life cycle. Tscharntke et al. (2005), based on the results of Roschewitz et al. (2005a), explained that the influence of farming systems on species richness is more important in simple landscapes than in complex landscapes. According to the authors, the negative impact of conventional systems on species richness is only observed in simple landscape where colonization from the surrounding landscape is limited and therefore very much affected by local farming systems. Therefore, in those landscapes, improvement of the local systems may enhance general biodiversity and biological regulation of insect pest and may counterbalance the negative effects of intensive monoculture landscapes. The classic opposition of different farming systems (organic vs. conventional) may be useful for deciphering general patterns, but it is probably not the most relevant approach for studying the impact of specific farming practices on particular pests and their natural enemies. Indeed, organic and conventional systems comprise a range of very different practices that may have different effects on population dynamics, as outlined earlier. The practices encompassed by organic and conventional farming systems may be sometimes very similar, at least in terms of their impact on biodiversity and trophic interactions. Many of the factors other than farming system that can influence abundance and diversity of natural enemies at the whole-farm scale may be under the control of farmers (e.g., hedgerow management) and are not always included in the analysis. Norton et al. (2009) showed that organic farms tended to be located in more heterogeneous landscapes with higher proportions of seminatural habitats and had smaller field sizes. The design of the study is therefore of crucial importance to prevent confounding effects when comparing farming systems at the landscape scale. Great care must be taken when selecting fields under different farming systems for studies about trophic interactions. Thus, we advocate, in studies about links between biodiversity and farming systems in general, and investigating trophic relations and biological control in particular, a clear description of cropping systems and an explicit consideration of seminatural habitats (quantitatively and qualitatively). All the studies reviewed here considered the farming systems of the fields selected in the center of each landscape. However, it is probably very important to take into account farming systems within the surrounding landscape. Most studies of landscape context have not explicitly taken into

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account the other farming systems within the landscape. However, we found one study (Rundlo¨f et al., 2008) in which the authors studied the effect, at both the local and landscape scales, of organic systems on butterfly species richness and abundance. They found that species richness and abundance were affected very differently on the two scales. Species richness and abundance were increased by organic farming at the local scale. However, the local species richness of both organic and conventional fields was positively influenced by the proportion of organic farming in the landscape. These authors also demonstrated that farming practices within fields had a stronger influence on butterfly abundance if the fields were surrounded by conventional rather than organic fields. Thus, in addition to taking into account seminatural habitats in the landscape and local farming systems, studies should also consider the spatial distribution of farming systems across the surrounding landscape, to determine the real effects of each explanatory variable and to prevent confounding effects.

7.2. Integrating crop management As crop management greatly influences pests and their natural enemies at the local scale and that consideration of the farming system is not always the most relevant approach, several recent studies have focused on crop management variables and landscape configuration to understand insect pest or natural enemy dynamics. We identified seven studies focusing on the effects of crop management and landscape context on insect pests (Valantin-Morison et al., 2007; Zaller et al., 2008a,b) and on natural enemy populations (Drapela et al., 2008; Elliott et al., 1998; Prasifka et al., 2004; Zaller et al., 2009). In all these studies, landscape configuration always influenced pest (in terms of abundance or damage) or natural enemy populations (in terms of species richness, abundance, and activity density or parasitism rates). Various elements of crop management were investigated in these studies, depending on the characteristics of the species considered: sowing date, sowing density, pesticide use, crop height, crop coverage, within-field diversity, or soil quality. It is therefore difficult to determine the general impact of specific practices. However, the main contribution of this approach is that it makes it possible to quantify and, in some cases, to rank the impact of particular farming practices over landscape context effect. For example, Zaller et al. (2008b) found that the damage caused by pollen beetles and stem weevils was positively correlated with the soil quality of the field and with woody areas. Elliott et al. (1998) found that the abundance, species richness, and diversity of aphid predators increased with increasing within-field diversity, noncrop areas, and fragmentation in the landscape. They also demonstrated that landscape variables were included in regression models more frequently than within-field variables, and showed that they accounted for a greater percentage of variation in abundance of aphid predators. It is important to

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determine the relative impact of farming practices to ensure effective biological control within cropping systems, as these practices are more convertible elements than landscape elements. Moreover, such an approach made it possible to quantify the relative contributions of crop management, farming systems, and landscape variables at the different trophic levels. This ranking step appears to be an important stage, improving our understanding of natural pest control mechanisms and pest damage.

7.3. Interaction between farming practices and landscape context The relative influence of the farming system and crop management on biological control is tightly linked to the spatial scale considered. Several authors studying the effects of landscape and farming systems on species richness and abundance reported interactions between landscape and local effects. They showed that organic or low-intensity farming systems have no or low effects on populations in complex landscapes, whereas they have a substantial influence in simple landscapes (Holzschuh et al., 2007; Roschewitz et al., 2005a; Rundlo¨f and Smith, 2006). This important interaction allows explaining why in 50% of the cases farming systems have no particular effects in our previous literature review about the effects of farming system and landscape context. This hypothesis has been originally formulated and confirmed in a study comparing farming systems on arable weed diversity in different landscape types (Roschewitz et al., 2005a; Tscharntke et al., 2005). As this interaction is increased by higher dispersal abilities of organisms, interactions between landscape context and particular crop management on natural enemy and biological control of insect pests may also occur. The important effect of the farming system or crop management in homogeneous landscapes is probably due to the local provision of resources, hosts, shelters, and more generally suitable conditions that enhance species richness and biological control. Local management effect may have lower effects in more complex landscapes, because the local species richness depends on the diversity of habitats and populations in the surrounding landscape (Tscharntke et al., 2005). Thus, in homogeneous landscapes, local management, through adapted crop or field boundaries management, for example, may be an interesting way to enhance functional biodiversity and biological control.

8. Conclusions Ecological studies provided a strong theoretical base of knowledge concerning the way in which species are likely to respond to landscape context and the establishment of population dynamics at the landscape scale.

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However, such studies have generally not taken into account the diversity of cropping areas and their relative managements, assuming arable land to be homogenous. In our review of the effects of crop management on trophic interactions, we demonstrated that farming practices might play an important role in regulating natural enemy and pest populations at a local scale. A clear description of crop management in landscape studies therefore appears to be of crucial importance for identifying the key driver of biological control and ranking the effects of landscape, farming system, and farming practices. This is a fundamental step in the design and assessment of ecologically sound integrated pest management strategies for farmers. It is also important to evaluate the quality of seminatural areas in terms of agroecological functions for natural enemies and pests. Consideration of the habitat quality of crop and noncrop areas for pest and their natural enemies presents agronomists and ecologists with a real challenge in their attempts to design integrated pest management strategies for application at the landscape scale. Moreover, all the studies reviewed here focused on either crop management or the farming system at the local scale and did not consider farming practices over the entire landscape. However, the range of spatial and temporal scales experienced by pests and their natural enemies is likely to result in trophic interactions being influenced by farming practices in the surrounding landscape. If we are to understand how species react at the landscape scale, studies will need to take into account the detailed characteristics of seminatural habitats, local crop management effects, and landscape farming practices. Integrated pest management paradigm holds that pests and their management exist at the crossroads of three major multidimensional fields of study: ecology, socio-economy, and agronomy, with ascending levels of complexity and expanding spatial scales (Kogan, 1998). Integrated pest management strategies may be seen as the complementation of different techniques to meet three main objectives: (i) a production purpose (crop performance and quality of products), (ii) socio-economic imperatives (farm organization, farm income), and (iii) environmental objectives (limitation of pesticide and nitrogen discharge into the environment, minimization of water, and energy use) (Kogan, 1998). The consideration of landscape features in biological control-based pest management strategies seems to be a relevant approach, although this assertion has not been clearly demonstrated, as studies on the effects of landscape and farming practices on natural pest control do not generally consider all the three objectives. Firstly, the enhancement of natural enemy populations does not necessarily imply effective pest control, and the relationships between crop and noncrop habitats are complex and may be antagonistic (e.g., Thies and Tscharntke, 1999; Valantin-Morison et al., 2007; Zaller et al., 2008a). Secondly, the effects of stronger biological control on productivity are unclear and the effects of landscape on pest populations and crop damage have rarely been

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¨ stman et al., 2003), even though they are much documented (but see O more relevant for crop production than any effect on natural enemies (Bianchi et al., 2006). The development of large-scale pest management strategies therefore requires a more holistic approach including the effects of both crop and landscape management. Such an approach would also fill in gaps in our knowledge about the ecology of insect pests (e.g., overwintering areas, pattern of migration) and quantify these effects in terms of environmental (e.g., energy use, pesticide use, and nitrogen discharge) and economic (e.g., crop damage, yield losses, and cost/benefit) consequences. The complementation of empirical studies and on-farm trials with modeling approaches is likely to prove an interesting strategy for improving integrated pest management and meeting this scientific challenge. The service concept at the landscape-scale highlights the link between landscape patterns and human values (Termorshuizen and Opdam, 2009). It can be seen as a chain of knowledge connecting spatial structure, landscape functions, and human values. Studies about such services are therefore predisposed to integer socio-economic dimension and landscape actors or practitioners. However, whereas studies concerning the relationship between structure and functions are an established element of research, efforts need to be made to encourage the study of relationships between landscape function and human values (Termorshuizen and Opdam, 2009). Many studies at the landscape scale suffer from a lack of information about the real effects of crop management and higher levels of biodiversity on natural pest control and yields. Landscape-scale studies about biological control-based integrated pest management should therefore include and quantify the economic output of such strategies for farmers.

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Index

A Actual evapotranspiration (AET), 10–11 Aerobic rice ORYZA2000 rice model, 187 PTR, 186–187 safe AWD, 187 “System of Aerobic Rice”, 186 varieties, 186 AET, see Actual evapotranspiration African Green Revolution, MVP agricultural interventions after first two years, 85 fertilizer use, 85, 87–88 first two years, 84–85 grain banks and storage facilities, 88–89 improved germplasm, 85, 87 irrigated crops, 88 land preparation, 85, 87 pest management, 85, 88 plant spacing, 85, 87 seed and fertilizers, 89 training, 89–90 annual rainfall, site characteristics, 81 climate change, adaptation crop/drought insurance programs, 110 ICRISAT, 111 rainfall, 110–111 yield reductions, 110 crop production extension services, 104–105 fertilizers, 103–104 improved germplasm, 104 planning and peak prices, 105 crop yields caloric requirements, 96, 97 household variation, 95–96 interannual variation, 92–95 data collection and analysis crop yields, 90–91 daily caloric requirements, 91 value-to-cost ratios, 91 decision-making, 84 diversification, irrigation cash crops, 108 high-value crops, 108 enterprise and crop diversification, 102 farming households characteristics, 83

fertilizers, 84 population density, 83 size, 83–84 farming systems and crops cattle, 83 humid tropical forest zone, mixed maize, 83 Potou and Bonsaaso, 83 geography, ecology, climate and soil landscapes, 79, 83 rainfall, 79 hunger eradication goal, 77–78 management, cropping season, 86 nutrition, improved caloric requirement, 107–108 iodized salt, 108 organic inputs and soil management mineral fertilizers, 106 nitrogen fertilizers, 106–107 nutrient, 105 quality and quantity, 105 residues, 105–106 safety nets cash transfers/permanent subsidies, 109 Koraro village cluster, 109–110 subsidies programs conditions for, 109 farmers paid back loans, 109 “smart”, 108–109 value-to-cost ratios inputs, 98–100 maize, Bonsaaso, 98, 101 millet and groundnut input, 101 peak prices, 98–100 Potou, millet and cowpea, 101 profitability, defined, 96 selling, 98 Agricultural production and ESs, European temperate grassland systems air quality, 120 assessment, 118–119 biodiversity conservation, 121 climate regulation, 120 definitions, 120 direct relationship, 141 hydrological regulation, 121 inconsistent relationships, regulation air quality, 138 biodiversity conservation, 140 climate, 135–138

261

262 Agricultural production and ESs, European temperate grassland systems (cont.) hydrological, 136 landscape quality, 140–141 soil erosion, 139–140 water quality, 138–139 interaction description, 122–124 landscape quality, 121 literature search confidence levels, 122 interaction categories, 122 millennium ecosystem assessment (MA), 141–142, 199–120 negative relationships agro-environmental schemes, 128 air quality reduction, 125 on biodiversity conservation, 127 dairy farming, 125 landscape quality, 127–128 manures/organic wastes, 127 nutrient cycling, 126 pollution, 125–126 soil, compaction and erosion, 126 no direct relationship, 128 nutrient cycling, 121 pair-wise interaction, 119 positive relationships air quality regulation, 129–130 biodiversity conservation, 133–134 climate regulation, 128–129 hydrological regulation, 129–131 landscape quality, 134–135 nutrient cycling, 132–133 soil erosion regulation, 131–132 soil erosion regulation, 121 water quality, 120–121 Alliance for the Green Revolution in Africa (AGRA), 104 Alternate wetting and drying (AWD) DSR aerobic rice, 186–187 frequently irrigated, 182–185 irrigation interval, 181–182 scheduling, 189 PTR, 190–191 rice continuous flooding, 202 electricity, groundwater pumping, 178–179 flooded conversion, 179 IGP, 179 institutional and policy changes, 180 intermittent irrigation, 177 PTR, 177–178 Warabandi, 179 Arid and semiarid regions, salinity crop diversification, 70 soil

Index

affected land area, graphical record, 57, 58 factors, 57–59 regions, 59–62 water Aral Sea, 63 groundwater, lakes and wetlands, 62 responses, 63–69 river, 62–63 AWD, see Alternate wetting and drying C Climate change effects, agriculture cropland, pasture and livestock drought, increase in, 34 precipitation regime, changes, 33 soil erosion rates, 34–35 findings and projections effects, 31–32 regime, 32 forests, 32–33 Crop management, pest and natural enemies harvesting, 239 herbivore density, 239 host plant resistance entomophagous insects, 236 induced and constitutive, 235–236 parasitism rates, 236 predation, 236 nitrogen fertilization effect of, 237 hypotheses, 236–237 population dynamics and herbivores, 236 pesticides insecticide-treated parasitoids behavior, 240–241 parasitoid species, 240 rotation annual crops, 239–240 intensities, arthropod community, 240 soil tillage intensity of, 237 invertebrates, 238 postharvest, 238 species response, 237–238 sowing date, oilseed rape, 239 within-field diversity description, 235 hypotheses, 235 Crop yields, African Green Revolution caloric requirements, 96 data collection and analysis, 90 household variation maize, 95–96 teff, 96 interannual variation groundnuts, 95 millet, 95

263

Index

MVP, 92, 95 trend and distribution, 94 D Dry seeded rice (DSR) on beds fresh, 189–190 permanent, 190 E Ecosystem services (ESs); see also Agricultural production and ESs, European temperate grassland systems and agriculture production interaction categories, 122 pair-wise interaction, 119 change and response relationship, 124 definition, MA, 119–120 nonagricultural production, 142 regional/global scale processes, 142–143 response types, 123 ESs, see Ecosystem services Evapotranspiration (ET) definition, 2–3 direct measurements, 10–11 satellite data, 14 soil moisture, 26 water-balance method, 12–13 G Global circulation model (GCM) observational data, 4–5 soil-erosion rates, 35 water-vapor feedback, 7 Groundwater decline halting, North-West India depletion reduction methods recharge, increasing, 166–167 withdrawal, 167–169 hydrogeology and irrigation development canal, 160 evaporation and rainfall, 160 groundwater pumping, 162 IGP, 159 Indus basin, 159–160 pumping, tubewells, 161–162 RW systems, 161–162 salinization and waterlogging, 162–163 tubewells, 162 waterlogging, 161 irrigation applications, 202 negative effects, 158 RW cropping system groundwater depletion, 157 Indo-Gangetic plain (IGP), 158 Punjab and Haryana, 156–157 watertable depth, 157 technologies, yield

AWD, rice, 177–180 components, water balance, 170 crop diversification, rice replacement, 199–201 dry seeded rice, AWD, 180–187 laser leveling, 173–175 planting date, 175–176 rice on beds, 187–191 surface residue retention and mulching, 193–197 system intensification, 201 varietal duration, 177 water, balance and productivity, 170–173 wheat on raised beds, 198–199 zero till wheat, 191–193 watertable, RW system AWD management, 164–165 decline arrest, 165 deep drainage, 163–164 ET depletion, 164 rice-fallow-wheat-fallow cropping system, 164 H Hunger Task force, 77 Hydrologic cycle aerosol optical depth, Mount Pinatubo eruption, 27–28 sulfate aerosols, 28 time series, annual water year, 28–29 agriculture, climate change effect cropland, pasture and livestock, 33–35 findings and projections, 31–32 forests, 32–33 atmospheric water vapour humidity and surface temperature, time series, 17–18 SSM/I measurements, 18 climate change, 3–4 cloudiness changes climate warming-induced, 18–19 increase and decrease in, 19 description, 2–3 ET definition, 2 evaporation and ET growing season, 16–17 measurements, 9–16 events economic and property losses, 29 ENSO intensity, 31 tropical cyclone intensity, 30–31 intensification approach and variations, 6 climate warming, GCM, 4–5 description, 4 global-mean temperature and precipitation changes, 5–6

264

Index

Hydrologic cycle (cont.) historical observational data, reviewed, 7 precipitation aerosol-induced reduction, 20–21 rainfall, 19 regional variations, 19–20 snow-water equivalent (SWE), 20 summer, winter and cumulative annual trends, 21, 22 precipitation recycling, 26–27 runoff alterations, 24 annual streamflow, 23–24 basin usage, 23 data, 21 Eurasian arctic rivers, annual discharge, 23, 24 landscape, modifications, 25 Mississippi River basin, 25–26 precipitation, 21, 23 river discharge, 24–25 standardized departures, streamflow graphical record, 21, 23 significance humidity and heat stress, 8–9 water-vapor feedback process, 7–8 soil moisture, 26 structure, 2–4 I Insect pests biological control arthropod and trophic interaction, landscapes cereal aphids, 225 communities, 224 metapopulation theory, 222–223 parasitoid and hosts, 224 predator–prey, 222 predators, 224–225 spatial ecology, 223 biodiversity conservation and farming systems, 221 crop management effect, natural enemy host plant resistance, 235–236 nitrogen fertilization, 236–237 pesticide use, 240–241 rotation, 239–240 sowing date, plant density and harvesting date, 238–239 tillage, 237–238 within-field diversity, 235 farming system integration chemical insecticides, 242–243 classic opposition, 244 within landscape, 244–245 landscape effect, 243–244 organic and conventional system, 243 species richness and abundance, 245

field to landscape scale, 221 integrated management, 247–248 integration, crop management landscape variables, 245–246 pollen beetles and stem weevils, 245 species characteristics, 245 on trophic, 247 variables and landscape configuration, 245 landscape effects, farming and crop management, 222 and farming practices interaction, 246 patterns and human values, 248 large-scale management, 248 and natural enemy, farming system effect conventional, 241–242 crop management, 242 organic, 241–242 seminatural habitats and natural enemy and crop interface, 229–230 hosts and prey, 227 landscape context effect, 230–232 life support functions, 225 pollen and nectar, 228 potential effects, 226 shelter and overwintering areas, 228–229 suppression and natural enemy biodiversity agricultural landscape, 232–233 herbivore mortality, 233 insurance model, 233 negative interactions, 233–234 neutral effects, 233 short-term and long-term perspective, 232 Integrated crop and resource management (ICRM), 158 International Crops Research Institute for Semiarid Tropics (ICRISAT), 111 K Koraro village cluster, 109–110 M Measurements, hydrologic variables AET vs. growing-season temperature, 10 eddy-covariance-flux approach, 10 EUROFLUX and Fluxnet sites, 10 Fluxnet program, 10–11 “global dimming”, 11–12 lysimeter, 9–10 ocean salinity depth difference, 14–15 evaporation-precipitation (E-P), 15 water cycle strengthening, 15–16 pan evaporation decrease, 11 satellite data and modeling land-surface model, 14 SSM/I, 13–14 water-balance method

265

Index

annual precipitation and stream discharge, 12–13 moist-to-wet temperate system, 13 precipitation and runoff, 12 streamflow, 12–13 Millennium development goals (MDGs) hunger measurement, 107 MVP, 78–79 UN Millennium Project Task Forces, 77–78 Millennium ecosystem assessment (MA) erosion regulation and nutrient cycling, 141–142 ESs definition, 119–120 Millennium Summit in 2000, 77 Millennium Villages Project (MVP); see also African Green Revolution, MVP communities, 78–79 description, 78 grain yields cropping seasons, 93 maize, 92 trend and distribution, 94 International Research Institute for Climate and Society (IRI), 110 seed and irrigation practice, 88 in sub-Saharan Africa, 80 subsidy condition contracts, 89 yield estimates, 90 Mulching effect, soil evaporation, 193, 195 soil percolation, improving, 68 summer crops and, 197 O ORYZA2000 rice model, 187 P Plant stress hypothesis, 236 Plant vigor hypothesis, 236–237 Puddled transplanted rice (PTR); see also Alternate wetting and drying DSR on beds, 189–190 zero till, 183–185 on fresh beds, 187–188 on permanent beds, 188–189 Punjab Preservation of Sub Soil Water Ordinance, 176 Punjab State Farmers’ Commission, 176 R Resource concentration hypothesis, 235 Resource conserving technologies (RCTs), 158 Rice-wheat (RW) cropping system; see also Groundwater decline halting, North-West India; Technologies effect, yield

cotton-wheat system, central Punjab, 203 water depletion, 204 S Seminatural habitats, pest and natural enemy and crop interface agroecological functions, 229 spillover effects, 229–230 hosts and prey, alternative Coccinella septempunctata, 227 parasitoids, 227 landscape effect and arthropod population, 232 complexity, 231–232 herbivore and natural enemy populations, 230–231 life support functions, 225–226 pollen and nectar, alternative sources, 228 shelter and overwintering areas noncrop habitats, 228–229 oilseed rape crop, 229 Soil and water salinity, responses plant-based interventions, 63 principles and practices crop management, 68 monitoring, 68–69 salinity management, 67 saline water usage monsoonal rain, 64 Sporobolus virginicus and Distichlis spicata, 65 TDS, irrigation, 64–65 salt-tolerant plant and halophytes usage Distichlis spicata, 67 growth response, graphical record, 65–66 Kosteletzkya virginica, 66–67 Salicornia bigelovli, 66 trials, 66 Soil salinity affected land area, graphical record, 57, 58 factors chemical weathering, 57–58 localized redistribution, 59 seawater intrusion, 58 regions Arabian Peninsula, 60 Australia and Europe, 59 Central Asia, 60–61 South Asia, 61–62 and water salinity in irrigation, 64–65 principles and practices, 67–69 salt-tolerant plant and halophytes, 65–67 Special sensor microwave imager (SSM/I) measuring humidity, 18 satellite observation, 13–14 SSM/I, see Special sensor microwave imager Surface residue retention

266

Index

Surface residue retention (cont.) fallow period, wheat harvest and rice planting green manure crop, 196–197 potential evaporation, 195–196 rice and wheat Happy Seeder, 193–195 mulching, 194 Rotary Disc Drill, 194 System of Aerobic Rice, 186 T TDS, see Total dissolved salt Technologies effect, yield AWD, rice electricity, groundwater pumping, 178–179 flooded rice conversion, 179 IGP, 179 institutional and policy changes, 180 intermittent irrigation, 177 PTR, 177–178 Warabandi, 179 DSR, AWD aerobic rice, 186–187 ET and WPET, 185 flooding to frequent irrigation, 182 and PTR, 184–185 soil cracking, 182–183 zero till and PTR, 183–184 laser leveling benefits, 174 effects of, 174–175 leveling indices (LIs), 173 reduction, irrigation, 173–174 rice on beds DSR, 189–190 fresh, 190–191 permanent, 191 transplanted, 187–189 rice planting date delaying, 176 May to 1 July, 175 May to mid June, 175 in Punjab, 175–176 rice replacement, crop diversification groundwater, 201 RW system, 200 water balance model, 199–200 surface residue retention and mulching effect, soil evaporation, 193 fallow period, wheat harvest and rice planting, 195–197 summer crops and, 197 transpiration efficiency, 197

wheat, 193–195 system intensification ET, 201 potential evaporation, 201 varietal duration, 177 water, balance and productivity, 170–173 wheat on raised beds fresh, 198 Hydrus 2D, 199 irrigation water savings, 198–199 permanent, 198 RW systems, 199 zero till transplanted rice prepuddling soil soaking period, 180–181 puddling, 180 topsoil drying and cracking, 181–182 ZTW adoption rates, 193 IGP, 191 irrigation water savings, 192 in Punjab Pakistan, 203–204 sowing time, 192–193 Total dissolved salt (TDS), 64–65 Transplanted rice on beds Bangladesh and Nepal, 188–189 fresh, 187–188 permanent, 188 sandy loam and loam soils, 189 U United Nations (UN) Millennium Project, 77 W Water salinity Aral Sea, 63 groundwater, lakes and wetlands, 62 river, 62–63 and soil in irrigation, 64–65 principles and practices, 67–69 salt-tolerant plant and halophytes, 65–67 World Food Program (WFP), 109–110 Z Zero till wheat (ZTW) adoption rates, 193 IGP, 191 irrigation water savings, 192 in Punjab Pakistan, 203–204 sowing time, 192–193