Advances in Agronomy [1 ed.] 978-0-12-000795-0

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Agronomy

D V A N C E S I N

VOLUME

77

Advisory Board Martin Alexander

Ronald Phillips

Cornell University

University of Minnesota

Kenneth J. Frey

Kate M. Scow

Iowa State University

University of California, Davis

Larry P. Wilding Texas A&M University

Prepared in cooperation with the American Society of Agronomy Monographs Committee Lisa K. Al-Almoodi David D. Baltensperger Warren A. Dick Jerry L. Hatfield John L. Kovar

Diane E. Stott, Chairman David M. Kral Jennifer W. MacAdam Matthew J. Morra Gary A. Pederson John E. Rechcigl

Diane H. Rickerl Wayne F. Robarge Richard Shibles Jeffrey Volenec Richard E. Zartman

Agronomy

DVANCES IN

VOLUME

77

Edited by

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

Amsterdam Boston London New York Oxford Paris San Diego San Francisco Singapore Sydney Tokyo

This book is printed on acid-free paper.

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C 2002, Elsevier Science (USA). Copyright 

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

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DESERTIFICATION AND ITS RELATION TO CLIMATE VARIABILITY AND CHANGE Daniel Hillel and Cynthia Rosenzweig I. II. III. IV. V. VI. VII.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Concepts and Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Case Study: The Sahel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Monitoring Desertification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Climatic Variability and Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 3 5 16 20 21 31 35

FATE AND TRANSPORT OF VIRUSES IN POROUS MEDIA Yan Jin and Markus Flury I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Characteristics of Viruses Relevant for Subsurface Fate and Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Virus Sorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Protein Sorption and Denaturation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Virus Survival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. The Role of the Gas–Liquid Interface in Protein/ Virus Inactivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Transport of Viruses in Porous Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII. Indicators for Human Enteroviruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IX. Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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40 43 45 57 64 67 70 86 88 91

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CONTENTS

CURRENT CAPABILITIES AND FUTURE NEEDS OF ROOT WATER AND NUTRIENT UPTAKE MODELING Jan W. Hopmans and Keith L. Bristow I. II. III. IV. V. VI. VII. VIII. IX. X. XI.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Water Transport in Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Linking Plant Transpiration with Assimilation. . . . . . . . . . . . . . . . . . . . . . . . . . Transport of Water and Nutrients in the Plant Root . . . . . . . . . . . . . . . . . . . Nutrient Uptake Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flow and Transport Modeling in Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Root Water Uptake. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nutrient Uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Coupled Root Water and Nutrient Uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comprehensive Example. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Prognosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

104 109 115 120 126 132 135 145 152 162 169 175

MICRONUTRIENTS IN CROP PRODUCTION N. K. Fageria, V. C. Baligar, and R. B. Clark I. II. III. IV. V. VI.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Status in World Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Soil Factors Affecting Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Factors Associated with Supply and Acquisition . . . . . . . . . . . . . . . . . . . . . . . . Improving Supply and Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

186 188 195 206 227 246 247

SOIL SCIENCE IN TROPICAL AND TEMPERATE REGIONS—SOME DIFFERENCES AND SIMILARITIES Alfred E. Hartemink I. II. III. IV. V. VI.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Soil Science in Temperate Regions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Soil Science in Tropical Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diametrically Opposite Interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impact of Soil Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

270 271 274 282 285 286 287

CONTENTS

vii

RESPONSES OF AGRICULTURAL CROPS TO FREE-AIR CO2 ENRICHMENT B. A. Kimball, K. Kobayashi, and M. Bindi I. II. III. IV. V.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results and Discussion of Crop Responses to Elevated CO2 . . . . . . . . . . Compendium and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

294 295 326 350 359 360

THE AGRONOMIC AND ECONOMIC POTENTIAL OF BREAK CROPS FOR LEY/ARABLE ROTATIONS IN TEMPERATE ORGANIC AGRICULTURE M. C. Robson, S. M. Fowler, N. H. Lampkin, C. Leifert, M. Leitch, D. Robinson, C. A. Watson, and A. M. Litterick I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Crop Rotations as the Central Management Tool in Organic Farming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Break Crops for Nutrient Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Break Crops for Improving Soil Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Break Crops for Weed Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Break Crops for Pest and Disease Management . . . . . . . . . . . . . . . . . . . . . . . . VII. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

370 371 391 403 409 411 416 417

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

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

V. C. BALIGAR (185), Alternate Crops and Systems Research Laboratory, Beltsville Agricultural Research Center, USDA-ARS, Beltsville, Maryland 20705 M. BINDI (293), Department of Agronomy and Land Management, University of Florence, 50144 Florence, Italy K. L. BRISTOW (103), CSIRO Land and Water/CRC Sugar, Townsville Qld 4814, Australia R. B. CLARK (185), Appalachian Farming Systems Research Center, USDA-ARS, Beaver, West Virginia 25813 N. K. FAGERIA (185), National Rice and Bean Research Center of EMBRAPA, Santo Antˆonio de Goi´as-GO, 75375-000, Brazil M. FLURY (39), Department of Crop and Soil Sciences, Washington State University, Pullman, Washington 99164 S. M. FOWLER (369), Welsh Institute of Rural Studies, University of Wales, Aberystwyth, SY23 3AL, United Kingdom A. E. HARTEMINK (269), International Soil Reference and Information Center (ISRIC), 6700 AJ Wageningen, The Netherlands D. HILLEL (1), Columbia University Center for Climate Systems Research and NASA Goddard Institute for Space Studies, New York, New York 10025 J. W. HOPMANS (103), Hydrology Program, Department of Land, Air and Water Resources, University of California, Davis, California 95616 Y. JIN (39), Department of Plant and Soil Sciences, University of Delaware, Newark, Delaware 19717 B. A. KIMBALL (293), U.S. Water Conservation Laboratory, USDA, Agricultural Research Service, Phoenix, Arizona 85040 K. KOBAYASHI (293), National Institute of Agro-Environmental Sciences, Tsukuba, Ibaraki 305-8604, Japan N. H. LAMPKIN (369), Welsh Institute of Rural Studies, University of Wales, Aberystwyth, SY23 3AL, United Kingdom C. LEIFERT (369), Tesco Centre for Organic Agriculture, University of Newcastle, Newcastle upon Tyne, NE1 7RU, United Kingdom M. LEITCH (369), Welsh Institute of Rural Studies, University of Wales, Aberystwyth, SY23 3AL, United Kingdom A. M. LITTERICK (369), Land Management Department, SAC, Craibstone Estate, Bucksburn, Aberdeen AB21 9YA United Kingdom

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CONTRIBUTORS

D. ROBINSON (369), Department of Plant and Soil Science, Aberdeen University, Aberdeen, AB24 5UA, United Kingdom M. C. ROBSON (369), Department of Plant and Soil Science, Aberdeen University, Aberdeen, AB24 5UA, United Kingdom C. E. ROSENZWEIG (1), Columbia University Center for Climate Systems Research and NASA Goddard Institute for Space Studies, New York, New York 10025 C. A. WATSON (369), Land Management Department, SAC, Craibstone Estate, Bucksburn, Aberdeen AB21 9YA, United Kingdom

Preface Volume 77 contains seven excellent reviews that should be of great interest to crop, soil, and environmental scientists. Chapter 1 is a timely review on desertification and its relation to climate variability and change that includes discussions on processes, use of the Sahel as a case study, maintaining desertification, and future climatic variability and change. Chapter 2 is a comprehensive review on a very timely topic—fate and transport of viruses in porous media. Topics that are covered include characteristics of viruses, virus sorption, protein sorption and denaturation, survival of viruses, inactivation of viruses, and their transport. Chapter 3 discusses the current capabilities and future needs of root water and nutrient uptake modeling including water transport and uptake in plants, nutrient uptake mechanisms, and flow and transport modeling in soils. Chapter 4 reviews past and present developments in understanding the chemistry and fertility of micronutrients and their role in crop production. Topics that are covered include status of micronutrients in world soils, and factors affecting and ways to improve micronutrient supply and availability. Chapter 5 is an interesting review on the comparisons and contrasts between tropical and temperate region soils. Chapter 6 is an informative review on the response of agricultural crops to free-air CO2 enrichment. Comprehensive discussions are included on methodologies and plant responses to elevated CO2 along with effects on soil processes. Chapter 7 provides a thorough treatment on the agronomic and economic potential of break crops for ley/arable rotations in temperate organic agriculture. The use of break crops in nutrient management, soil structure improvement, weed management, and pest and disease management is discussed. Many thanks to the authors for their superb contributions. DONALD L. SPARKS

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DESERTIFICATION IN RELATION TO CLIMATE VARIABILITY AND CHANGE Daniel Hillel and Cynthia Rosenzweig Columbia University Center for Climate Systems Research and NASA Goddard Institute for Space Studies New York, New York 10025

I. Introduction II. Concepts and Definitions III. Processes A. Drought B. Primary Production and Carrying Capacity C. Soil Degradation D. Water Resources E. Social Factors IV. Case Study: The Sahel V. Monitoring Desertification VI. Future Climatic Variability and Change VII. Prospects References

Ecosystems in semiarid regions appear to be undergoing degradation processes commonly described as desertification. We review the concepts, definitions, and processes pertinent to the problem. Focusing on the long-term drought in the African Sahel as a case study, we analyze the relationships among climatic, biophysical, and social factors. Hypotheses related to the causation and persistence of drought involve the roles of land–surface change, atmospheric dust, and ocean– atmosphere dynamics. Remote sensing techniques have made possible monitoring ecosystem changes on a regional scale. Where fresh water resources are available, irrigation can be an effective way to stabilize and intensify agricultural production, but water resource development needs to be accompanied by water conservation and salinity control. Key social factors include land tenure, institutional structures, and population growth. Projections derived from global climate models suggest that drought conditions in the Sahel may worsen in the coming decades. Given challenges facing semiarid countries, vulnerability to the intertwined effects of degradation and climate change appears to be high. Improvements of scientific understanding of climate phenomena and their interconnections over space and time offer opportunities for controlling destructive land-use practices, augmenting carbon sinks through better soil management, and enhancing  C 2002 Elsevier Science (USA). resilience.

1 Advances in Agronomy, Volume 77 Copyright 2002, Elsevier Science (USA). All rights reserved. 0065-2113/02 $35.00

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I. INTRODUCTION Ecosystems in semiarid and arid regions around the world appear to be undergoing various processes of degradation commonly described as desertification. According to UNEP (1992), all regions in which the ratio of total annual precipitation to potential evapotranspiration (P/ET) ranges from 0.05 to 0.65 should be considered vulnerable to desertification. Such regions constitute some 40% of the global terrestrial area, which totals about 130 million km2 (13 billion ha). Dregne (1983) calculated that the arid, semiarid, and dry subhumid regions of the world occupy 12.1, 17.1, and 9.9% of the world’s total land area. Relatively dry areas cover much of northern Africa, southwestern Africa, southwestern Asia, central Asia, northwestern India and Pakistan, southwestern United States and Mexico, western South America, and much of Australia (Fig. 1, see color insert). Arid and semiarid regions cover over a fourth of the world’s land area, and are home to nearly one-sixth of the world’s population (WRI, 2000). The total population of the world has doubled in the last four decades, resulting in the current total of about 6 billion. As of 1998, some 80% of humanity resided in the so-called developing countries, which contain only 58% of the total land area and 54% of the total cropped area. Moreover, many of the developing countries are located in semiarid regions that are most vulnerable to degradation. According to a report published by the World Resources Institute (WRI, 1998), the total area of land under cropping has increased by some 25% since 1950. In the same period, the world’s population has more than doubled, so the area of cropland per capita has been reduced by nearly a half. At present, the annual growth rate of cropland (0.2%) is only one-seventh the growth in population (Lal, 1997), so the decline in arable land per capita is continuing. That decline is most severe in the developing countries, which are expected to increase their populations most rapidly and will therefore be most in need of increased food production. In sub-Saharan Africa, for instance, the per capita area of arable land, which was 1.6 ha in 1990, is projected to fall to 0.63 ha by 2025 (Scherr, 1999). The lands still available for the expansion of farming are, in large part, marginal lands of relatively low productivity and high vulnerability. Desertification is an emotive term, conjuring up the specter of a tide of sand swallowing fertile farmland and pastures. The United Nations Environmental Programme (UNEP) sponsored projects in the early 1980s to plant trees along the edge of the Sahara, with the aim of warding off the invading sands. While there are places where the edge of the desert can be seen encroaching on fertile land, the more pressing problem is the deterioration of the land due to human abuse in regions well outside the desert. The latter problem emanates not only from the desert but also from the centers of population; not only from the spread of the sand dunes but also from the spread of people and their mismanagement of the land (Hillel, 1992). Therefore, protecting the front line may do nothing to halt the degradation

DESERTIFICATION: CLIMATE VARIABILITY AND CHANGE

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behind it. The true challenge is not so much to stop the desert at the edge of a semiarid region as to protect the entire region from internal abuse of its vegetation and of its soil and water resources. A vicious cycle is already operating in many areas: as the land degrades, it is worked ever more intensively so its degradation accelerates; and as the returns from “old” land diminish, “new” land is brought under cultivation or grazed by encroachment onto marginal or submarginal areas. But attempts to encapsulate these complex problems in the catchall term “desertification” may have obscured its true character and confused the search for its amelioration. In this paper, we review the concepts, definitions, and processes pertinent to desertification, and offer an alternative, more inclusive term, namely, “semi-arid ecosystem degradation.” We use the long-term drought in the Sahelian region of Africa as a case study for analyzing the complex set of climatic, biophysical, and social factors that interweave to create the process of semiarid ecosystem degradation, and we evaluate current monitoring techniques, including remote sensing. We next consider the potentialities and hazards of irrigation development as a possible means to improve agricultural production in semiarid regions. We then ask the question, “How might global climate change affect the Sahelian region of Africa?” and analyze a set of recent projections derived from global climate change scenarios, in light of the region’s vulnerabilities. Finally, we offer our views on prospects for sustaining semiarid ecosystems and agroecosystems in the future.

II. CONCEPTS AND DEFINITIONS Desertification is a single word used to cover a wide variety of effects involving the actual and potential biological productivity of ecosystems in semiarid and arid regions. The term desertification (or desertization) was apparently coined by the French ecologist LeHouerou (1977) to characterize what was perceived to be a northward advance of the Sahara in Tunisia and Algeria. It gained currency following the severe drought that afflicted the Sud region of Africa in the early 1970s, and again in the 1980s, during which the Sahara was reported to be advancing southward into the Sahelian zone as well. For example, Lamprey (1975) estimated that during the period from 1958 to 1975, while mean annual rainfall diminished by nearly 50%, the boundary between the Sahara and the Sahel had shifted southward by nearly 100 km. As defined in recent dictionaries, desertification is the process by which an area becomes (or is made to become) desert-like. The word “desert” itself is derived from the Latin desertus, being the past participle of deserere, meaning to desert, to abandon. The clear implication is that a desert is an area too barren and desolate to support human life. An area that was not originally desert may come to resemble a desert if it loses so much of its formerly usable resources that it can no longer

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provide adequate subsistence to humans. This is a very qualitative definition, since not all deserts are the same. An area’s resemblance to a desert does not make it a permanent desert if it can recover from its damaged state, and, in any case, the modes of human subsistence and levels of consumption differ greatly from place to place. The United Nations Conference on Desertification (UNCOD) was held in Nairobi in 1977. It was convened in response to the severe drought that had befallen the Sahel from the late 1960s through most of the 1970s. Its report defined desertification as “the diminution or destruction of the biological potential of land that can lead ultimately to desert-like conditions . . . under the combined pressure of adverse and fluctuating climate and excessive exploitation.” That statement leaves open several questions, such as the definition of the land’s “biological potential,” the type and degree of damage to the land that can be considered “destruction,” and the exact meaning of “desert-like” conditions. Mainguet (1994) characterized desertification as the “ultimate step of land degradation to irreversible sterile land.” This definition ignores the complex set of processes that progress gradually (and, for a time, reversibly) at different rates. Rather, it confines the term to the final condition that is the extreme culmination of those various processes. An alternative approach would be to define the processes themselves and characterize the degree of degradation at which their separate or combined effects may be considered to have become irreversible. In recent years, the very term desertification has been called into question as being too vague, and the processes it purports to describe too ill-defined. Some critics have even suggested abandoning the term, in favor of what they consider to be a more precisely definable term, namely, “land degradation” (e.g., Dregne, 1994). However, desertification has already entered into such common usage that it can no longer be recalled or ignored (Glantz and Orlovsky, 1983). It must therefore be clarified and qualified so that its usage may be less ambiguous. The United Nations has since modified its definition of desertification as follows: “Land degradation in arid, semiarid, and dry subhumid areas resulting from various factors, including climate variations and human activities” (Warren, 1996). That definition still does not either clarify the relative importance of the two potential causes or imply the possibility that they may be interactive. It merely shifts the issue to the definition of “land degradation.” Does the latter pertain to the soil, and, if so, to just what qualities or attributes of the soil (physical, chemical, and/or biological)? Does it also pertain to the vegetation present on the land, and, if so, to what attributes of the vegetation (biomass, photosynthesis, respiration, transpiration, growth rate, ground coverage, species diversity, etc.)? And what of the animal life associated with the land? “Land degradation” itself is a vague term, since the land may be degraded with respect to one function and not necessarily with respect to another. For example, a tract of land may continue to function hydrologically—to regulate infiltration, runoff generation, and groundwater recharge—even if its vegetative cover is

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changed artificially from a natural species-diverse community to a monoculture, and its other ecological functions may be interrupted. Rather than “land degradation,” we prefer the term “semiarid ecosystem degradation.” A semiarid ecosystem encompasses the diverse biotic community living in this given domain. Included in this community is the host of plants, animals, and microorganisms that share the habitat and that interact with one another through such modes as competition or symbiosis, predation, and parasitism. It also includes the complex physical and chemical factors that condition the lives of those organisms and are in turn influenced by them. A semiarid ecosystem may be a more or less natural one, relatively undisturbed by humans, or it may be an artificially managed one, such as an agroecosystem. Each ecosystem performs a multiplicity of ecological functions. Included among these are photosynthesis, absorption of atmospheric carbon and its incorporation into biomass and the soil, emission of oxygen, regulation of temperature and the water cycle, as well as the decomposition of waste products and their transmutation into nutrients for the perpetuation of diverse interdependent forms of life. Integrated ecosystems may thus play a vital role in controlling global warming and in absorbing and neutralizing pollutants that might otherwise accumulate to toxic levels. An agroecosystem is a portion of the landscape that is managed for the economic purpose of agricultural production. The transformation of a natural ecosystem into an agroecosystem is not necessarily destructive, if the latter is indeed managed sustainably and if it coexists harmoniously alongside natural ecosystems that continue to maintain biodiversity and to perform vital ecological functions. In too many cases, however, the requirements of sustainability fail, especially where agricultural systems expand progressively at the expense of the remaining more or less natural ecosystems. The appropriation of ever-greater sections of the remaining native habitats, impelled by the increase of population as well as by the degradation of farmed or grazed lands due to overcultivation or overgrazing, decimates those habitats and imperils their ecological functions. In the initial stages of degradation, the deteriorating productivity of an agroecosystem can be masked by increasing the inputs of fertilizers, pesticides, water, and tillage. Sooner or later, however, if such destructive effects as organic matter loss, erosion, leaching of nutrients and salination continue, the degradation is likely to reach a point at which its effects are difficult to overcome either ecologically or economically.

III. PROCESSES Key processes related to desertification include drought, primary production and carrying capacity, soil degradation, and water resources. The role of social factors is also important.

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A. DROUGHT A typical feature of arid regions is that the mode (the most probable) amount of annual rainfall is generally less than the mean; i.e., there tend to be more years with a below-average rainfall than years in which the rainfall is above average, simply because a few unusually rainy years can skew the statistical average well above realistic expectations for rainfall in most years. More than 90% of the total variation in annual rainfall can generally be encompassed within a range between one-half and twice the mean. The variability in biologically effective rainfall is yet more pronounced, as years with less rain are usually characterized by greater evaporative demand, so the moisture deficit is greater than that indicated by the reduction of rainfall alone. Timing and distribution of rainfall also play crucial roles. Below-average rainfall, if well distributed, may produce adequate crop yields, whereas average or even above-average rainfall may fail to produce adequate yields if the rain occurs as just a few large storms with long dry periods between them. In semiarid agricultural regions, “drought,” like desertification, is a broad, somewhat subjective term that designates years in which cultivation becomes an unproductive activity, crops fail, and the productivity of pastures is significantly diminished. Drought is a constant menace, a fact of life with which rural dwellers in arid regions must cope if they are to survive. The occurrence of drought is a certainty, sooner or later; only its timing, duration, and severity are ever in doubt. It is during a drought that ecosystem degradation in the form of devegetation and soil erosion occurs at an accelerated pace. Any management system that ignores the certainty of drought and fails to provide for it ahead of time is doomed to fail in the long run. That provision may take the form of grain or feed storage (as in the Biblical story of Joseph in Egypt), or of pasture tracts kept in reserve for grazing when the regular pasture is played out, or of the controlled migration of people and animals to other regions able to accommodate them for the period of the drought. There has been a prolonged period of drought in the Sahelian region of Africa since the early 1970s (Fig. 2). Various hypotheses involving both natural and

Figure 2 Rainfall fluctuations 1901–1998, expressed as a regionally averaged standard deviation (departure from the long-term mean divided by the standard deviation) for the Sahel. (Source: IPCC WG II, 2001).

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anthropogenic factors have been advanced to explain the persistence of this drought. 1. Atmospheric Dust One hypothesis is that the recent droughts are due to a cooling of the land masses of the Northern Hemisphere by about 0.3◦ C between 1945 and the early 1970s, owing to an increase in atmospheric dust from drylands, as well as from air pollution and volcanic eruptions. The cooling may have changed the patterns of air mass movement (Tegen et al., 1996). Evidence in support of this hypothesis seems to be contradicted by the heavy rains that occurred in the Sahel during the 1950s when the Northern Hemisphere cooled, and by the severe Sahel drought that occurred during the early 1980s when the Northern Hemisphere experienced a warming. 2. Ocean–Atmosphere Dynamics Another hypothesis links drought in the Sahel to changes in ocean–atmosphere dynamics, specifically changes in sea–surface temperatures (SSTs) in the world’s oceans. Such changes might tend to reduce the northward penetration of the Intertropical Convergence Zone (ITCZ)—the great band of equatorial clouds whose shifting pattern brings monsoonal rain to the humid tropics as well as to the Sahel (Nicholson, 1986). Many studies have linked interannual variation of SSTs and seasonal precipitation variability in the region (e.g., Druyan, 1987; 1989; Folland et al., 1986; Lough, 1986; Rowell et al., 1995). Droughts in the Sahel tend to be coincident with positive SST anomalies in Southern Hemisphere oceans and the Indian Ocean, and negative SSTs in the Northern Hemisphere oceans, especially the subtropical North Atlantic Ocean. Abundant rain in the Sahel is often, but not always, linked with SSTs of the opposite sign in the Atlantic and other oceans (Lamb and Peppler, 1991, 1992). The interhemispheric SST gradient in the Atlantic Ocean appears to be a key mechanism for precipitation in the Sahelian latitudes (Fontaine and Janicot, 1996; Ward, 1998). Warmer than normal SSTs in the tropical Pacific related to the El Ni˜no/Southern Oscillation (ENSO) phenomenon have similarly been linked with droughts in Australasia, India, South America, and Southern Africa, though these droughts typically do not persist for more than one or two seasons. The Sahelian region of Africa, on the other hand, has had many dry years that are not correlated with Pacific SSTs, so the persistence of the Sahelian drought sets it apart from droughts in other parts of the world. There does appear to be some ENSO-driven teleconnection to drought in West Africa (e.g., Fontaine and Janicot, 1996), but Janicot et al. (1996) show that the strength of the correlation of Sahel rainfall with the Southern Oscillation Index (SOI) is quite variable. Hunt (2000) proposes a mechanism by which tropical Pacific SSTs influence Sahel rainfall by modulating

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the North Atlantic Oscillation (NAO) via the Pacific–North America oscillation. Druyan and Hall (1996) suggest that extreme Pacific Ocean SST anomalies influence climate variability in the Sahel through wave disturbances of the tropical easterly jet, with associated effects on convergence, humidity, and precipitation. These and other ocean–atmosphere relationships are being used to forecast seasonal rainfall in the region (Nnaji, 2001; Ward, 1998). 3. Land–Surface Change Still another hypothesis is that droughts can be caused or worsened by largescale changes in the land surface of Africa, and specifically by the deforestation and overall denudation of the land (Charney, 1975; Sud and Molod, 1988). A process may thus have started whereby the drought can become self-reinforcing. According to the theory of “biophysical feedback,” losses of vegetative cover resulting from the drought as well as from overcultivation, overgrazing, and deforestation, along with the consequent increase of the dust content of the air, combine to enhance the area’s reflectivity to incoming sunlight. That reflectivity, called “albedo,” may rise from about 25% for a well-vegetated area to perhaps 35% or more for bare, bright, sandy soil. As a larger proportion of the incoming sunlight is reflected skyward rather than absorbed, the surface becomes cooler, and so the air in contact with the surface has less tendency to rise and condense its moisture so as to yield rainfall. An additional effect of denudation is to decrease interception of rainfall by vegetation and infiltration, while increasing surface runoff, thereby reducing the amount of soil moisture available for evapotranspiration. Crops and grasses, which have shallower roots than trees and in any case transpire less than the natural mixed vegetation of the savanna, transpire even less when deprived of moisture during a drought. The meteorological consequences of such changes have been explored in modeling studies (Xue and Shukla, 1993). The hypothesis is that such changes may have some effect on regional precipitation, since in many continental areas rainfall is derived in significant part from water evaporated regionally. It proposes that the biophysical and physical processes interact, as lower rainfall leads in turn to more overgrazing, less regrowth of biomass, and further reduction in reevaporated rain owing to the decline in soil moisture. Thus, the feedback hypothesis offers its own explanation as to why the drought in the Sahel has tended to persist for so long. There is still no conclusive evidence, however, that even large-scale changes in land surface conditions do actually affect regional-scale climate (Nicholson et al., 1998; Nicholson, 2000). Key components in semiarid ecosystem degradation processes are increased surface albedo (the reflectance of solar radiation) and increased generation of dust, both of which are consequences of the exposure of bare, dry ground following removal of the original vegetative cover.

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The albedo of a bare soil depends on the organic matter content and the mineral composition of the topsoil. It also depends on the moisture content of the soil surface. A moist soil is generally less reflective (i.e., “darker”) than a dry soil (Hillel, 1998). Thus, Nicholson et al. (1998) found that near the southern edge of the African Sahel (at a latitude of 15 degrees north), where the rainfall was 450 mm, the albedo was about 30%. However, near the northern boundary of the Sahel, where the mean annual rainfall was only 200 mm, the surface albedo was about 43%. Albedo is also affected, to some degree, by the smoothness or roughness of the surface. Above all, however, it is affected by the vegetative cover and its above-ground residues. A widely cited hypothesis, promulgated by Charney (1975), Charney et al. (1975), and Otterman (1974, 1977, 1981), suggested a feedback mechanism between land use and climate change. Specifically, they raised the possibility that an increase in albedo resulting from anthropogenic denudation of the land can in turn cause a diminution of rainfall. The mechanistic reasoning underlying this hypothesis is that an increase in surface reflectivity implies a reduction in the absorption of solar energy, which entails a reduction in soil surface temperature and a consequent reduction in sensible heating of the atmospheric layer in contact with the soil. Proponents of the Charney hypothesis speculated that because a more highly reflective surface should tend to be cooler, it should enhance the subsidence of warm dry air and hence exacerbate the area’s aridity. This, in turn, reduces the upward convective rise of warm air that normally results in condensation of vapor and the formation of clouds. If the rise in albedo occurs over a large enough area, it might thus reduce the regionally generated rainfall. Hence, so the reasoning goes, surface denudation—which is the common effect of humans attempting to survive with their livestock during a drought—is a self-reinforcing process that exacerbates the very drought that initially induced it. Lare and Nicholson (1994) imply that if desertification (i.e., denudation) is extreme, it could indeed evoke the sort of feedback originally postulated by Charney. A striking example of the albedo difference between grazed and ungrazed land can be seen along the border between the western Negev of Israel and northeastern Sinai of Egypt. The two contiguous areas of this arid region had been grazed to the same degree until 1948, after which the newly established State of Israel restricted grazing on its own side of the border. Consequently, the area within Israel developed a relatively dense vegetative cover that appears much darker on aerial and satellite photographs than the neighboring area on the Egyptian side. According to Otterman (1977, 1981), the protected area of the Negev had an albedo of 12% in the visible light and 24% in the infrared range, whereas the corresponding values on the overgrazed Sinai side were as high as 40 and 53%. Recent studies have shown, however, that the darkening is due not only to the shrubs and grasses growing in the area but also to a biological crust (consisting of algae, fungi, and cyanobacteria) that developed on the surface of the sandy soil.

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A vegetated area, though it appears darker in aerial photographs, may not be warmer than a bare area, as long as the plants are actively transpiring. The process of transpiration involves the absorption of latent heat and therefore tends to cool the foliage. During the dry season, however, many of the indigenous plants curtail transpiration so that they, along with the area as a whole, may indeed become warmer than it would be if it were bare of vegetation. Otterman and Tucker (1985) reported radiometric ground temperatures (evidently made in the summer season) of about 40◦ C in Sinai and about 45◦ C in the Negev. More recently, Otterman et al. (2001) reported that measurements made by NOAA satellites have consistently shown the Negev to be warmer than Sinai by about 4.5◦ C during the generally dry period of May to October. In contrast, Balling (1988) and Bryant et al. (1990) found that the surface temperatures on the darker (more densely vegetated) U.S. side of the Mexican border were 2 to 4◦ cooler than on the overgrazed and lighter-colored Mexican side. The latter measurements may well have been made during a period when the vegetation was actively transpiring, and hence produced a cooling effect despite its lower albedo. The persistent presence of dust in the atmosphere itself has an effect on an area’s radiation balance (Fouquart et al., 1987). It tends to scatter and reflect a fraction of the solar (shortwave) radiation, while absorbing longwave radiation emitted from the Earth. In some cases, a turbid atmosphere may actually warm the air near the ground, while in other cases it may do the opposite, depending on such variables as its density as well as its reflective or absorptive properties. Recent studies on the potential effects of aerosols on rainfall have advanced another feedback hypothesis. Denudation of an area’s vegetation is usually associated with biomass burning, which releases smoke into the air. In addition, denudation also results in deflation of the soil surface by wind erosion, which in turn creates a “dust bowl” effect. Rosenfeld and Farbstein (1992), Rosenfeld (1999, 2000) and Rosenfeld et al. (2001) have presented evidence that concentrations of such aerosols in the troposphere can suppress rainfall significantly. The postulated mechanism is that moisture condensed on the dust particles forms small droplets that do no coalesce sufficiently to generate rainfall. The detrimental impact of dust on rainfall is less than that caused by smoke from biomass burning, but the abundance of desert dust in the atmosphere renders it important. The reduction of rainfall affected by desert dust can cause drier soil, which raises still more dust, thus creating a feedback loop to further reduce rainfall.

B. PRIMARY PRODUCTION AND CARRYING CAPACITY The biological productivity of any ecosystem is due to its primary producers (known as autotrophs), which are the green plants growing in it. They alone are

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able to create living matter from inorganic raw materials. They do so by combining atmospheric carbon dioxide with soil-derived water, thus converting radiant energy from the Sun into chemical energy in the process of photosynthesis. Green plants also respire, which is the reverse of photosynthesis, and in so doing they utilize part of the energy to power their own growth. The net primary production then becomes available for the myriad of heterotrophs, which subsist by consuming (directly or indirectly) the products of photosynthesis. A stable ecosystem is one in which production and consumption, synthesis and decomposition, are in balance over an extended period of time. When humans enter into an ecosystem and appropriate some of its products for themselves, they normally do so in competition with, and at the expense of, other potential consumers. Historically, in the hunter-gatherer phase of subsistence, humans merely selected the most readily obtainable and useful (or desirable) plant and animal products, leaving the remainder more or less intact. As their population increased, humans began to manage the ecosystem so as to promote the production of the goods they desired, and to suppress the species that competed for those products. At a still later stage, humans tended to take over sections of the ecosystem entirely, aiming to eradicate all species that did not serve them directly, and to plant (and harvest) only the plants and animals they chose to domesticate. In the process, the ecosystem’s biodiversity and natural productivity were profoundly affected (Hillel, 1992). As long as the tracts dominated by humans consist of small enclaves within a large and continuous ecological domain, the ecosystem as a whole is not seriously affected. However, as population grows progressively and human management becomes both more extensive and more intensive, the ecological integrity of entire regions is threatened. Especially affected are areas within the semiarid and arid regions, which, because of the paucity of water and the fragility of the soil (typically deficient in organic matter, structurally unstable, and highly erodible) are most vulnerable and least resilient. The term “carrying capacity” has been used to characterize an area’s productivity in terms of the number of people or grazing animals it can support per unit area on a sustainable basis (Cohen, 1995). However, the productive yield obtainable from an area—and hence the number of people deriving their livelihood from it, at whatever standard of life—depends on how the area is being used. Under the hunter-gatherer mode of subsistence, an area may be able to carry only, say, 1 person per square kilometer, whereas under shifting cultivation it may carry 10, and under intensive agriculture perhaps 100. The more intensive forms of utilization also involve inputs of capital, energy, and materials, such as fertilizers and pesticides, that are brought in from the outside to enhance an area’s productivity. As the usable productivity is affected by the availability of water (i.e., by seasonal rainfall), it varies from year to year and from decade to decade, and a long-term average

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(as well as variability) is difficult to determine, especially given the prospect of climate change. It is therefore doubtful that any given regions can be assigned an intrinsic and objectively quantifiable “carrying capacity.” Human pressure on the meager resources of arid ecosystems arises primarily because of increasing population and the trend toward sedentarization of formerly nomadic people. What typically follows includes the cutting down of wooded plants for fuel, overcultivation, and overgrazing by livestock (especially in the immediate peripheries of water supply centers such as wells, cisterns, or surfacewater impoundments). The denuded and pulverized soil surface then falls prey to erosion by wind (during the dry season) and by water (during the rainy season). Wind erosion blows away the fertile topsoil and greatly increases the content of dust in the atmosphere. Water erosion also scours away the topsoil and often cuts into the soil to produce deep gullies. During fallow periods, rainfall may also leach away soluble nutrients. The net result can be an overall reduction in biological productivity. Over a long period of time (say, centuries), and in the absence of human intervention, even a severely eroded soil can recover. However, on the time scale of years to a few decades, especially if humans continue to overgraze and/or overcultivate the land, soil erosion may be, in effect, irreversible. One problem is to measure the productivity of an area and its gradual change from year to year or from decade to decade. Quite another problem is to assess the recoverability (or resiliency) of an area following a partial loss of productivity, and the rate of potential recovery, i.e., the time pattern of gradual restoration of productivity and the period needed for its completion (Dregne, 1994). Desertification from anthropogenic and climatic factors in Senegal caused a fall in standing wood biomass of 26 kg C ha− 1 y−1 in the period 1956–1993, releasing carbon at the rate of 60 kg C cap− 1 y− 1 (Gonzalez, 1997). The significance of these quantities in the global balance may be small, but perhaps important nonetheless (Bouwman, 1992; Lal, 2001).

C. SOIL DEGRADATION An important criterion of soil degradation (itself a major component of land and ecosystem degradation) is the loss of soil organic matter. Compared to soils in more humid regions, those in arid regions tend to be inherently poor in organic matter content, owing to the relatively sparse natural vegetative cover and to the rapid rate of decomposition. The organic matter present is, however, vitally important to soil productivity. Plant residues over the surface protect the soil from the direct erosive impact of raindrops and from deflation by wind and help to conserve soil moisture by minimizing evaporation. Plant and animal residues that are partially decomposed and that are naturally incorporated into the topsoil help to stabilize its

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structural aggregates, which in turn enhance infiltrability, minimize water loss by runoff, and enable seed germination and root growth. The organic matter present also contributes to soil fertility by releasing nutrients. When the natural vegetative cover is removed, and especially when the soil is tilled repeatedly, there follows a rapid process of organic matter decomposition and depletion. Accelerated erosion also removes the layer of topsoil that is richest in organic matter. Consequently, the destabilized soil tends to form a surface crust that further inhibits infiltration. Water losses by both runoff and evaporation increase. Moreover, the soil loses an important source of nutrients. These destructive processes can be countered or ameliorated by methods of conservation management, including minimum or zero tillage, maintenance of crop residues, the periodic inclusion of green manures in the crop rotation (ASA, 1983; USDA, 1991), and agroforestry (Nair, 1993). The destructive processes induced by soil mismanagement, and—in contrast— the constructive processes induced by conservation management, though seemingly local, may have—when practiced on a regional scale—an impact on climate. Soils subject to accelerated decomposition of organic matter tend to release carbon dioxide and thus contribute to the enhanced greenhouse effect. Conversely, soils that are being enriched with organic matter can absorb and sequester quantities of carbon that are extracted from the atmosphere in photosynthesis (Bouman, 1992; Lal, 2001).

D. WATER RESOURCES Where fresh water resources are available and can be utilized economically, irrigation can be an effective way to intensify and stabilize production in semiarid or arid regions. Irrigation is the supply of water to agricultural crops by artificial means, designed to permit farming in arid regions and to offset drought in semiarid regions. Even in areas where total seasonal rainfall is adequate on average, it may be poorly distributed during the year and variable from year to year. Wherever traditional rain-fed farming is a high-risk enterprise owing to scarce or uncertain precipitation, irrigation can help to ensure stable production. Irrigation has long played a key role in feeding expanding populations and is expected to play a still greater role in the future. It not only raises the yields of specific crops but also prolongs the effective crop-growing period in areas with dry seasons, thus permitting multiple cropping (two, three, or even four, crops per year) where only a single crop could be grown otherwise. With the security provided by irrigation, additional inputs needed to intensify production further (pest control, fertilizers, improved varieties, and better tillage) become economically feasible. Irrigation reduces the risk of these expensive inputs being wasted by crop failure resulting from lack of water.

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Although irrigated land amounts to only some 17% of the world’s cropland, it contributes well over 30% of the total agricultural production. That vital contribution is even greater in arid regions, where the supply of water by rainfall is least, even as the demand for water imposed by the bright Sun and the dry air is greatest. The practice of irrigation consists of applying water to the part of the soil profile that serves as the root zone, for the immediate and subsequent use of the crop. Inevitably, however, irrigation also entails the addition of water-borne salts. Many arid-zone soils contain natural reserves of salts, which are also mobilized by irrigation. Underlying groundwater in such zones may further contribute salts to the root zone by capillary rise. Finally, the roots of crop plants typically extract water from the soil while leaving most of the salts behind, thus causing them to accumulate. The problem is age-old. From its earliest inception in the Fertile Crescent, some six or more millennia ago, irrigated agriculture, especially in ill-drained river valleys, has induced processes of degradation that have threatened its sustainability. The artificial application of water to the land has ipso facto caused the water table to rise, which in turn induced the self-destructive twin phenomena of waterlogging and salination (Fig. 3). Some investigators include the degradation of irrigated lands, generally by waterlogging and salination, in the category of desertification (Dregne and Chou, 1993). Though the processes taking place differ fundamentally from those in

Figure 3 Waterlogging and salination. The rising water-table in poorly drained land saturates the soil, impedes aeration, and infuses the root zone with salts. (Source: Hillel, 1998).

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rainfed lands, the damage done to injudiciously irrigated lands is indeed in the category of ecosystem degradation (Hillel, 2000). Processes occurring off-site (upstream as well as downstream of the irrigated area) strongly affect the sustainability of irrigation. For example, denudation of upland watersheds by forest clearing, cultivation, and overgrazing induces erosion and the consequent silting of reservoirs and canals, thereby reducing the water supply. The construction of reservoirs often causes the submergence of natural habitats as well as of valuable scenic and cultural sites. Concurrently, the downstream disposal of drainage from irrigated land tends to pollute aquifers, streams, estuaries, and lakes with salts, nutrients, and pesticides. Finally, the irrigation system itself may harbor and spread water-borne diseases, thus endangering public health. So the very future of irrigation is threatened by land degradation as well as by dwindling water supplies and deteriorating water quality. In the last few decades, even as great investments have been made in the development of new irrigation projects, the total area under irrigation has hardly expanded. That is because large tracts of irrigated land have degenerated to the point of being rendered uneconomic to cultivate, or—in extreme cases—have become totally sterile. The dilemma of land deterioration is not exclusive to the less developed nations, where it has caused repeated occurrences of famine. It applies to an equal extent to such technologically advanced countries as Australia, the United States, and the central Asian regions of the former Soviet Union. So pervasive and inherent are the problems that some critics doubt whether irrigation can be sustained in any one area for very long—and they have much evidence to support their pessimism. Irrigated agriculture can be sustained, albeit at a cost. The primary cost is effective salinity control, along with the prevention of upstream, on-site, and downstream environmental damage. Although there will be cases where the costs of continued irrigation (especially if severe damage has already occurred) may be prohibitive in practice, in most instances the cost is indeed well worth bearing. Investing in the maintenance of irrigation can result in improved economic and social well-being as well as in a healthier environment. Developing and implementing an effective salinity control program require an understanding of complex interrelationships with multiple causes, effects, and feedbacks, operating at different scales of space and time. Except in the most problematic locations, irrigation can be maintained, provided that water supplies of adequate quality can be assured, the salt balance and hence the productivity of the land can be maintained, the drainage effluent can be disposed of safely, and the economic returns can justify the costs. The sine qua non of ensuring the sustainability of irrigation is the timely installation and continuous operation of a drainage system to dispose safely of excess salts. All too often, drainage creates an off-site problem, beyond the on-site cost of installation and maintenance, since the discharge of briny effluent can degrade

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the quality of water along its downstream route. Where access to the open sea is feasible, solving the problem is likely to be easier than in closed basins or in areas far from the sea. In those cases, the disposal terminus (whether a lake or an aquifer) may eventually become unfit for future use, hence the importance of reducing the volume and salinity of effluents. Much can be achieved by improving the efficiency of water use. Modern irrigation technology offers the opportunity to conserve water through reduced transport and application losses coupled with increased efficiency of utilization (Hillel, 1997).

E. SOCIAL FACTORS Social factors are necessarily involved in both semiarid ecosystem conservation and its inverse degradation. Farmers who do not have tenure to the land are not likely to invest in its conservation or improvement (Syers et al., 1996). Neither are communities that lack stable institutional structure likely to establish and maintain essential infrastructure and services to enable, encourage, and coordinate farmers’ efforts to implement land improvement and conservation measures (especially on communal lands). And no effective action at all may be possible in the absence of a proactive governmental policy, including the provision of credit or subsidies, professional guidance and training, as well as the preparation and implementation of national and regional drought contingency plans for both farmers and herders (Jolly and Torrey, 1993). The conservation of land resources is a collective societal concern, not merely a private concern of the people utilizing the land directly (Sen, 1981). Finally, there is the most difficult, yet inescapable issue of population numbers. No system of management, however efficient, can be sustained if the population continues to grow without limit. A crucial aspect of population control is the empowerment of women, through education and equal rights (social, political, and economic), as full participants in the management of their societies’ physical, biological, and human resources (Arizpe et al., 1994).

IV. CASE STUDY: THE SAHEL The debate over desertification has tended to focus upon a particular region of Africa south of the Sahara called the Sahel. The word sahil in Arabic means a plain, a coast, or a border. Used geographically, the term refers to a band of territory approximately 200–400 km wide, centered on latitude 15◦ N, lying just south of the Sahara and stretching across most of the width of Africa. The Sahel

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covers well over 2 million km2 and constitutes significant portions of Senegal, Gambia, Mauritania, Mali, Burkina Faso, Niger, Chad, and the Sudan. By some definitions, the Sahel covers a wider latitudinal belt that extends roughly between 10 and 20◦ N into parts of the Ivory Coast, Ghana, Benin, Togo, Nigeria, Cameroon, and Ethiopia. For our climate change analysis, we utilize the broader designation. The mean annual temperature of the more broadly defined Sahel region ranges from 15 to 30◦ C, while rainfall varies from about 100 mm in the north to about 1000 mm in the south (Fig. 4, see color insert). The climatic regime depends on the excursions of the Intertropical Convergence Zone (ITCZ) and the African jetstream and is highly variable. The rainstorms are erratic and occasionally violent, and their variability increases from south to north. The rainy season, lasting 3 to 5 months, alternates with an extended, unrelieved, dry season. The periodic occurrence of drought is an inherent feature of this harsh climate and successive years of drought may be followed by years with torrential rains. The soils of the Sahel are generally of low fertility, particularly poor in phosphates and nitrogen, structurally unstable, with low humus content and low water retention. Hardened layers, laterization, and vulnerability to wind and water erosion are common features. Water for irrigation is available in some places from streams and rivers (Senegal, Niger, and Chari-Logone), and possibly from groundwater aquifers, but the area under irrigation is rather small and the irrigation potential has not been fully developed. The vegetation is a mixed stand of trees, shrubs, and perennial and annual grasses, typical of savannas and steppes. In the African Sahel, and similarly in other regions, the establishment and consolidation of European colonial rule in the 19th century brought about fundamental changes that subsequently were to modify the relation of indigenous societies to their environment. After an initial period of warfare, the area was stabilized and security conditions improved. So did medical and veterinary facilities including vaccination services. These interventions allowed human and animal populations to increase rapidly during favorable periods. At the same time, traditional patterns of land utilization and tenure, and of migration and transhumance, were disrupted by arbitrary boundaries and by imposed political and economic structures. Although the available historical records are rather meager, they suggest that similar major droughts, lasting 12–15 years, evidently occurred in the 1680s, the mid-1700s, the 1820s and 1830s, and the 1910s. In the first half of the 19th century, the level of Lake Chad apparently declined for 2 or 3 decades, to about where it was during the drought of the mid-1980s. The geological record shows several similar falls of the lake level in the past 600 years (Rind et al., 1989). On the other hand, we know that the Sahel has also gone through much wetter periods in the 9th through the 13th centuries, and 16th through the 18th centuries; also from 1870 to 1895, and during the 1950s. The area near Timbuktu, which now has only 100 mm of annual rainfall, was humid enough in the late 19th century for wheat to be grown.

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The fortuitous occurrence of favorable weather conditions during most of the 20th century, and particularly during the abnormally wet period of 1950–1965 following the attainment of independence by the region’s states, obscured the effects of the changes imposed earlier. Given good rains, freshly cleared lands produced good harvests even in areas that normally would have been considered ill-suited for cultivation. Instead of deliberately keeping areas underpopulated and providing for eventual drought, the authorities in some cases encouraged farmers to move into marginally arable lands. Pastoral tribes were then pushed further into even more marginal grazing lands, where they were provided with water by means of mechanically powered tubewells. Inevitably, drought struck. As access to the wells was free to all, traditional control over management of pastures was eliminated. The overall result has been an increase in herd numbers, a decrease in pasture through more widespread cropping, and an abandonment of traditional range management mechanisms (Hillel, 1992). The Sahel region seems to have undergone a general decline of rainfall since the late 1960s (see Fig. 2). There have been several unusually prolonged and severe droughts since then, in marked contrast with the preceding 20 relatively wet years (Rind et al., 1989). At each drought, people may remain on the land in the hope that the rains might soon return, and while waiting, they do what they can to save their herds of goats, sheep, cattle, and camels. When the grass plays out, they may try to increase their animals’ intake of browse by lopping trees already weakened by lack of soil moisture. They also continue to collect firewood from the sparse shrubs and trees. When many months elapse without rain, the vegetation dies out, while the soil—desiccated, pulverized, and trampled—begins to blow away in the wind. And when a sudden rainstorm visits the area, it scours and gullies the erodible topsoil. Finally, the people are left with no choice but to abandon their traditional homes and villages and migrate to the cities, where they seek employment or relief assistance. The drought of 1968–1973 highlighted the basic problems that had been too long ignored. Family and tribal structures and their autonomous traditional practices of resource management and land tenure had been broken down, so the local population was now unable to cope with the drought on its own. The plight of the Sahel was exacerbated by the drought’s recurrence, in even more severe form, during the early 1980s. Consequently, sections of the region were almost emptied of inhabitants, as thousands of people migrated from their villages to refugee camps and overcrowded cities. Semiarid ecosystem degradation has been linked to migrations that may have displaced 3% of the population of Africa since the 1960s (Westing, 1994). Some of the Sahel’s problems have been compounded by ill-conceived development efforts. Some planners seem to have misunderstood the logic of traditional production systems, and have underestimated the difficulty of improving them. They also failed to foresee the potentially negative consequences of intended

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improvements brought in under the imprimatur of “technology transfer.” In many cases, they seem to have neglected the fundamental significance of rainfall variability the probability of drought, and the principle of risk avoidance. Some of the traditional production systems were based on probable outcomes and were therefore better able to contend with droughts (though, of course, no production system can cope with a severe drought prolonged over several successive years). The population of the western African regions of the Sahel and the regions lying south of it, called the Sahelo-Sudanian and Sudanian zones, was estimated at 31 million in 1980. Though the population density is still fairly low throughout, varying from fewer than 2 per square kilometer in Mauritania to nearly 60 in Gambia, it has been increasing steadily. In recent decades, population growth rates have been close to 3% per annum. The area has reached 54 million inhabitants by the year 2000 (75% more than in 1980, and almost three times as many as in 1961). The urban population, incidentally, has been swelling at rates exceeding 5% per year, in large part from the influx of people driven off the land because of drought. Gonzalez (2001) has measured declines in forest species richness and tree density in the West African Sahel in the last half of the 20th century. Such changes have apparently shifted vegetation zones in Northwest Senegal towards areas of higher rainfall at an average annual rate of 500–600 m. Xerophytic Sahel species have expanded in the north, while mesic Sudan and Guinean species have retracted to the south. Rainfall and temperature are identified as the most significant factors explaining tree and shrub distribution. The changes have also decreased human carrying capacity below actual population densities. The rural population of 45 people per square kilometer exceeded the 1993 carrying capacity of firewood from shrubs of 13 people per square kilometer. Gonzalez advocates the traditional practice of regeneration of local species over the planting of exotic species. In the practice of native regeneration, farmers select small trees in their field, protect them, and prune them to promote rapid growth of the apical meristem. The continued destruction of the rural environment is likely to result in further urbanization. As the demand for food, other agricultural products, and firewood continues to mount, it is likely to generate greater exploitation of the region’s meager resources. Policy options include social and educational programs that foster reduced population growth rates and improvements in rural productivity. The latter can be achieved by intensifying the use and conservation of favorable lands, developing the irrigation potential, improving management of range lands, reforesting marginal lands, and raising the efficiency of household energy use so as to curtail the burning of firewood. Above all, adequate provision must be made for the possible occurrence of drought in the future. Fortunately, the land itself exhibits a remarkable resilience. It had suffered many droughts in the past, and when the rains subsequently returned, so eventually did much of the vegetation. In large measure, the recent damage was temporary, and the land can recover if it is rehabilitated, or at least left undisturbed for a sufficient time.

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V. MONITORING DESERTIFICATION The techniques of remote sensing have made possible the monitoring of changes to ecosystems on a regional scale (Fig. 5, see color insert) (e.g., Justice, 1986). Studies based on the remote sensing of the African Sahel were reported by Nicholson et al. (1998). The authors state that there has been no progressive change of either the Saharan boundary or of vegetation cover in the Sahel during the 16-year period of the study, nor has there been a systematic reduction of productivity as assessed by the water-use efficiency of the vegetation cover. In principle, statistical criteria designed to test the probability levels of differences (between sites or between successive measurements on the same site) should not be used to “prove” the opposite, namely that there are no differences. In this case, absence of evidence of change by one criterion or another is not in itself evidence of absence of any change. Measurements (partly indirect) made at various times on large areas may have obscured subtle local changes that may have occurred in specific sites. Generality may tend to ignore specificity. The authors themselves report that while their data “showed little change in surface albedo during the years analyzed, a change in albedo of up to 0.10% since the 1950s is conceivable.” (The figure 0.10% is apparently a misprint of what may have been a 1% or a 10% change in albedo). NDVI is the ratio between the red and near-red infrared reflectance bands, obtained from advanced high-resolution radiometer data from the polar-orbiting satellite of the National Oceanic and Atmospheric Administration (Tucker et al., 1991). In arid and semiarid regions, NDVI evidently correlates with the density of the vegetative cover and its biomass, as well as with its “leaf area index” (Nicholson et al., 1998) and photosynthetic activity (Prince, 1991). Another criticism is in order regarding the use of NDVI (the Normalized Difference Vegetation Index) as a measure of net primary production. That index may indeed indicate the activity of the vegetative cover at the time of measurement, but it is oblivious to the amount of vegetation harvested by humans and/or their animals prior to the time of measurement. Taken to be a general indicator of the “greenness” of an area, NDVI has also been conjectured to correlate with biological productivity, but that correlation may not necessarily hold. In principle, the amount of vegetation present per unit of area should depend on the amount produced in situ, minus the amount removed from it. Therefore, the relation between an area’s productivity and its vegetative biomass at any time must depend on whether the vegetation has been or is being “harvested” (e.g., grazed by livestock, or cut and carried away by humans). An area could be quite productive yet relatively bare, if it had been harvested just prior to the NDVI measurement.

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A more serious caveat is in order: even if there is no discernible change in the density of an area’s overall vegetative cover, there might well be a considerable change in the composition of the vegetation (i.e., in its biodiversity, ecological function, and feed value). For instance, an overgrazed area may exhibit a proliferation of less nutritious plants at the same time that it loses the most palatable species of grasses and legumes that had contributed to the area’s original carrying capacity. Evidence of this effect was demonstrated by Gonzalez (2001). Nicholson et al. (1998) noted that the interannual fluctuations of the desert boundary, as assessed from NDVI, were indeed considerable, with a displacement as great as 3◦ latitude (roughly 300 km) back and forth. These fluctuations corresponded to the variations of the region’s rainfall. However, the investigators could discern no progressive “march” of the desert over West Africa during the period of their study (1980 to 1995). Furthermore, they reported that the ratio of NDVI to rainfall, which they took to represent the rain-use efficiency of the vegetation, indicated little interannual variability and no discernible decline during the 13 years of their analysis. A criterion used by Tucker et al. (1991) to delineate the boundary between the Sahara and the Sahel is the mean annual rainfall contour (isohyet) of 200 mm. Malo and Nicholson (1990) found that this boundary corresponds approximately to an annually integrated NDVI of 1. However, the density of the vegetative cover must depend not only on rainfall but also on whether and to what extent that vegetation is being utilized. As seen in Fig. 2, the annual precipitation in the Sahel has fluctuated widely, but the amounts for the last 3 decades of the 20th century are generally lower than those of the preceding decades. And although the trend in recent years appears to be an upward one, the annual amounts of rainfall are still low relative to the century’s earlier decades. Clearly, an analysis based on any particular short period may be misleading.

VI. FUTURE CLIMATIC VARIABILITY AND CHANGE Climate in arid and semiarid regions is likely to be even more influenced in the future by human activity due to the phenomenon known as global climate change. Emissions of greenhouse gases, among them carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and aerosols due to human activities are altering the atmosphere in ways that are expected to warm the climate. The warming trend, or enhanced greenhouse effect, is attributed to the release into the atmosphere of radiatively active trace gases, which have the property of trapping a growing proportion of the heat emitted by the earth’s surface. The atmospheric concentration

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HILLEL AND ROSENZWEIG Table I Observed and Projected Changes in Extreme Weather and Climate Events Related to Temperature and Precipitationa

Confidence in observed changes (latter half of the 20th century) Likely

Changes in phenomenon

Confidence in projected changes (during the 21st century)

Higher maximum temperatures and more hot days over nearly all land areas Higher minimum temperatures, fewer cold days and frost days over nearly all land areas Reduced diurnal temperature range over most land areas

Very likely

Likely Likely, over many Northern Hemisphere mid- to high-latitude land areas

Increase of heat index over land areas More intense precipitation events

Very likely, over most areas Very likely, over many areas

Likely, in a few areas

Increased summer continental drying and associated risk of drought

Likely, over most mid-latitude continental interiors (lack of consistent projections in other areas)

Very likely

Very likely

a

Very likely

Very likely

Source: IPCC WGI (2001).

of CO2 has increased by ∼30% since 1750, mostly due to fossil fuel burning and partially due to land-use change, especially deforestation. The present CO2 concentration has not been exceeded during the past 420,000 years, and the rate of increase is unprecedented during the past 20,000 years (IPCC, 2001). One of the more insidious manifestations of global climate change may be an increase of climate instability (Rosenzweig and Hillel, 1998). In a warmer world, climatic phenomena are likely to intensify. Thus, episodes or seasons of anomalously wet conditions (violent rainstorms of great erosive power) may alternate with severe droughts, in an irregular and unpredictable pattern. Table I presents the IPCC assessment of confidence in observed changes in extremes of weather and climate during the latter half of the 20th century and projected changes during the 21st century. Nearly all land areas are very likely to experience higher maximum and higher minimum temperatures and more intense precipitation events. A more unstable climatic regime will make it harder to devise and more expensive to implement optimal land use and agricultural production practices, including drought-contingency provisions. Failure to prepare for such contingencies may exacerbate the consequences of such extreme events as floods and

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droughts, to the effect of worsening land degradation and periods of severe food shortages. Working Group I of the Intergovernmental Panel on Climate Change (IPCC) has found that an increasing body of observations reveals that warming at the global scale is already underway (IPCC, 2001). The global average surface temperature has increased over the 20th century by 0.6◦ C +/−0.2◦ C. Most of the warming has occurred during two periods: 1910–1945 and 1976–2000. Since 1975, the Sahelian region has experienced warming of up to 1.5◦ C (Fig. 6, see color insert). The IPCC further finds that the frequency and the intensity of droughts in parts of Africa have increased in recent decades; in particular, there has been a decrease in rainfall over large portions of the Sahel (IPCC, 2001). Working Group II of the Intergovernmental Panel on Climate Change on Impacts, Adaptation, and Vulnerability finds that Africa is highly vulnerable to climate change (IPCC WGII, 2001). Sectors of concern include water resources, food security, natural resources and biodiversity, human health, and desertification (Table II). Global climate models (GCMs) are mathematical formulations of the processes that comprise the climate system, including radiation, energy transfer by winds, cloud formation, evaporation and precipitation of water, and transport of heat by ocean currents (Fig. 7). GCMs are used to simulate climate by solving the fundamental equations for conservation of mass, momentum, energy, and water. For boundary conditions relevant to the Earth’s geographic features and with the relevant parameters, the equations of the GCMs are solved for the atmosphere, land surface, and oceans over the entire globe. GCMs project global climate responses at relatively coarse-scaled resolutions (2.5 to 3.75◦ latitude by ∼3.75◦ longitude). Table II Sectors Vulnerable to Climate Change in Africaa Sector Water resources Food security

Projected impacts Dominant impact is predicted to be a reduction in soil moisture in the subhumid zones and a reduction in runoff. There is wide consensus that climate change, through increased extremes, will worsen food security in Africa.

Natural resources and biodiversity

Climate change is projected to exacerbate risks to already threatened plant and animal species, and fuelwood.

Human health

Vector-borne and water-borne diseases are likely to increase, especially in areas with inadequate health infrastructure.

Desertification

Changes in rainfall, increased evaporation, and intensified land use may put additional stresses on arid, semiarid, and dry ubhumid ecosystems.

a

Source: IPCC WG II (2001).

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Figure 7

The climate system. (Source: WMO, 1985).

The models are used to simulate the climate system’s future responses to additional greenhouse gases and sulfate aerosols emitted into the atmosphere by human activities. Temperature and precipitation changes for the Sahel region of Africa in the 2050s projected by two global climate models (GCMs) are shown in Figs. 8 and 9 (see color inserts). The global climate models are the United Kingdom Hadley Centre (HC) and the Canadian Centre for Climate Modeling and Analysis (CC) (Flato et al., 1997; Johns et al., 1997). There are two types of scenarios for each GCM: the first accounts for the effects of greenhouse gases on the climate (GG), and the second accounts for the effect of greenhouse gases and sulfate aerosols (GS). The GCM simulations for the 21st century are forced with a 1% per year increase of equivalent carbon dioxide (CO2) concentration in the atmosphere. These simulations are based on “businessas-usual” greenhouse gas emission scenarios of the Intergovernmental Panel on Climate Change and account for changes in other greenhouse gases besides CO2 (IPCC, 1996). Sulfate aerosols are emitted as by-products of industrial activities and create a cooling effect as they reflect and scatter solar radiation. Thus, the scenarios that incorporate both greenhouse gases and sulfate aerosols tend to be somewhat cooler than those with greenhouse gas forcing alone. Simulated annual temperature and precipitation were linearly interpolated across the GCM gridboxes in the Sahel region.

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The scenarios vary in the magnitude of the projected temperature changes, but they all project a warming trend for the Sahel region. The GCM models project temperature changes ranging from 2 to 7◦ C in the 2050s. The Canadian Centre for Climate Modeling and Analysis (CC) scenario consistently projects higher temperatures for the region than the United Kingdom Hadley Centre (HC), while the scenarios that combine greenhouse gases and sulfate aerosols (GS) are consistently cooler than those with the greenhouse gases alone (GG). Precipitation projections of the two global climate models show different patterns for the 2050s, indicating uncertainty regarding future hydrological conditions. Changes in precipitation range from −40% to +40% in the 2050s. At three sites across the Sahel (Fig. 10), an analysis was done to project the potential for future drought in the region. Mean monthly temperature and precipitation for Bamako, Mali; Kano, Nigeria; and Kosti, Sudan for the period of record are shown in Fig. 11. (Data were available from 1945 to 1988 in Bamako, Mali; from 1947 to 1965 in Kano, Nigeria; and from 1943 to 1979 in Kosti, Sudan). Mean annual temperature is 28.2, 26.3, and 27.3◦ C for Bamako, Kano, and Kosti, respectively. Mean annual precipitation is low at the Mali (1014 mm y−1) and Nigeria (859 mm y−1) sites, and extremely low at the Sudan site (400 mm y−1), with highest rainfall occurring in August.

Figure 10 Study sites for analysis of future droughts in the Sahel.

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Figure 11 Monthly mean temperature and precipitation for Sahel study sites (Bamako, Mali 1945–1988; Kano, Nigeria 1947–1965; and Kosti, Sudan 1943–1979) (Source: NASA GISS).

For the coming decades, both GCMs project significant warming at all three sites (between ∼4 and 8◦ C by the 2080s) (Fig. 12). Precipitation projections, on the other hand, are mixed, with the Hadley Centre GCM simulating declines up to 30% in Bamako, Mali, in the 2080s, and increases of more than 20% in Kano, Nigeria, in the 2050s (Fig. 13). We explored the potential for drought in the Sahelian region further by calculating potential evaporation (PET) with the Penman–Monteith (Monteith, 1980) equation and the Thornthwaite (1948) equation and then using these formulas to calculate the Palmer Drought Stress Index (Palmer, 1965). The PDSI compares anomalous dry and wet years to normal years and is used to identify relative droughts and floods at particular places (Table III). It uses a water balance approach to calculate infiltration, runoff, and potential and actual evaporation. Inputs are monthly mean temperature and precipitation, soil water capacities, and Thornthwaite (1948) parameters, which are a function of the mean temperature and latitude.

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Figure 12 Projected annual change in temperature for the Sahel study sites for the Hadley Centre (HC) and Canadian Centre (CC) climate change scenarios with greenhouse gases alone (GG) and with greenhouse gases and sulfate aerosols (GS).

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Figure 13 Projected annual change in precipitation for the Sahel study sites for the Hadley Centre (HC) and Canadian Centre (CC) climate change scenarios with greenhouse gases alone (GG) and with greenhouse gases and sulfate aerosols (GS).

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Utilizing the Penman–Monteith equation, the base PET is higher than the Thornthwaite (5.89 compared to 4.85 mm day−1, respectively) and the projected changes in PET are smaller (∼10–15% increases calculated with Penman–Monteith compared to ∼20–25% increases calculated with Thornthwaite) (Fig. 14). When these PET formulations are used to calculate projected changes in the PDSI, the Thornthwaite PDSI projected greater changes than the Penman– Monteith PDSI (∼−6 compared to ∼−4) for the 2080s (Fig. 15). According to the definition of PDSI classes, indices = /4.00 3.00–3.99 2.00–2.99 1.00–1.99 0.50–0.99 0.49– −0.49 −0.50– −0.99 −1.00– −1.99 −2.00– −2.99 −3.00– −3.99 X i,max φ(X i ) = , (37) 1 − X i / X i,max otherwise ρ

where X1 = S + Sin for the solid–water interface, X2 = U + Uin for the air–water interface, and Xi,max represents the maximum sorption capacity at the respective interface. This model has been successfully applied to analyze transport of φX174 through unsaturated sand columns (Fig. 10). Under unsaturated flow conditions in the subsurface, it appears that an adequate description of virus transport requires consideration of solid–water as well as air– water interfacial interactions. These interactions are relevant for both sorption and inactivation processes. Since viruses, as living organisms, are affected by a variety of environmental variables, the modeling of virus transport in the subsurface remains a challenging task.

VIII. INDICATORS FOR HUMAN ENTEROVIRUSES Because detection and enumeration of human enteroviruses (HEV) are difficult and time-consuming, many studies on virus sorption and transport have been conducted using the so-called “indicator” viruses (e.g., MS-2, φX174, and

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PRD-1). In addition, some common disease-causing viruses (hepatitis A virus, rotaviruses, and Norwalk virus) cannot as yet be detected practically, and techniques available for the recovery and identification of human enteric viruses often have limited sensitivity. Use of “indicator” organisms to assess HEV behavior in subsurface medium is necessary and has been practiced for almost a century. Characteristics of coliphages and their suitability to serve as indicator have been reviewed by Snowdon and Cliver (1989). An ideal indicator of viral contamination of groundwater should possess the following particular properties (IAWPRC Study Group on Health Related Water Microbiology, 1991; Snowdon and Cliver, 1989): 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

be applicable in all types of groundwater be unable to reproduce in contaminated water relate specifically to contamination by human feces have a density in contaminated water that directly relates to the degree of fecal pollution enable rapid detection and unambiguous identification be nonpathogenic to humans be present whenever HEV are present, and in greater numbers have physical properties similar to HEV be similar to HEV in adsorption to soils and transport through groundwater have a survival time as long as the most persistent HEV

The suitability of a particular virus as an indicator is evaluated based on relative insensitivity to inactivation (Yates et al., 1985) and its ecological and morphological similarities to human pathogens (Havelaar et al., 1993). Coliphages, particularly RNA-phage, have been proposed as suitable indicators for HEV (Snowdon and Cliver, 1989). Among the coliphages, MS-2 has been suggested to be the most suitable indicator (Springthorpe et al., 1993; Yates et al., 1985). From the hydrological point of view, a worst-case indicator for transport and fate of HEV does not need to include all the criteria listed previously. We propose that such an indicator should 1. be unable to reproduce in contaminated media (soil, water) 2. show similar or less sorption and retention than HEV in porous media under identical conditions 3. be at least as resistant to inactivation under natural conditions as HEV 4. be nonpathogenic to humans and other animals (only if used as tracer in the field) We may call this type of indicator a transport indicator, to differentiate from the pollution indicator that indicates viral pollution of groundwater. Because of the extremely complex sorption and transport mechanisms of viruses, recent studies have raised doubts regarding the applicability of any single

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indicator’s ability to mimic the behavior of HEV. MS-2 has been shown to be relatively easily inactivated in unsaturated systems and in the presence of metal oxides (Chu et al., 2000; Jin et al., 2000a). Penrod et al. (1996) compared the deposition kinetics of bacteriophages MS-2 and λ and found that even subtle differences in viral surface structures could significantly influence the rate at which viruses were removed from the water phase by infiltration. Taking a different approach, Redman et al. (1997) used recombinant Norwalk virus (rNV) particles as a model system to study the filtration behavior of Norwalk virus (NV), the human pathogen. The biochemical procedure used to created the rNV particles is given in Redman et al. (1997). The resulting rNV particles are morphologically and antigenically similar to the native NV but lack the genetic material (i.e., RNA) so they are harmless and cannot infect humans. Such rNV particles may be ideal to be used as a model system for transport studies because they can be grown to high concentration, and their noninfectious character implies that experiments at the field scale may be possible (Redman et al. 1997). A comparison of the behavior between MS-2 and rNV indicates that MS-2 is not a suitable surrogate for NV. Redman et al. (1997) also pointed out that the rNV particle system is not well suited to simulate the inactivation behavior of the real NV. Considering the complex sorption and retention mechanisms of viruses, it is unlikely that any single compound or microorganism will be able to adequately represent the transport behavior of different HEV in porous media (Penrod et al., 1996). Caution should be used when extrapolating results from studies conducted with indicator microorganisms or other types of colloidal particles to the behavior of HEV, as such indicators are likely inadequate to represent human pathogens.

IX. CONCLUDING REMARKS There is evidence that large-scale virus transport occurs in the subsurface environment. The USEPA estimates that annually in the United States16 people are at risk of death and 168,000 people are at risk of viral illness from consuming groundwater contaminated with pathogenic viruses (USEPA, 2000). Development of effective regulations to protect public health from microbial contamination relies on a thorough understanding of key processes governing virus survival and transport in the natural environment. Considerable knowledge has been accumulated from research conducted over the last 20 to 30 years. The influence of the factors affecting virus sorption and inactivation have been extensively studied and well documented. Solution chemistry (pH and ionic strength), virus properties (isoelectric point and surface

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characteristics), soil properties (organic matter content, CEC, presence of metal oxides, etc.) have been found to affect virus sorption to various degrees, while temperature, association with solid particles, and water content are among the factors identified that affect virus survival. Laboratory and field experiments have revealed many factors and processes that attenuate virus transport through porous media. As presented in this article, results from protein research provide some insights as to what mechanisms might be involved in virus sorption that have so far not been studied extensively. For example, the sorption mechanism seems to be affected largely by particle size, and there might be a transition between reversible and irreversible sorption for particles in the size range of viruses. Such information is essential for identifying the appropriate models to describe virus sorption behavior. Also lacking is information on reaction kinetics involved in virus sorption/desorption processes, especially under conditions that are closely related to field conditions. Considering that one single virus can cause infection, the possible slow desorption kinetics of viruses needs detailed investigation. Carefully designed field scale studies are needed to investigate the extent that chemical and physical heterogeneities of natural porous materials affect virus retention and transport. An even more challenging task of future research is to effectively apply fundamental theories from laboratory studies to the field. Some research needs are summarized as follows. r Examine virus sorption mechanisms using both macroscopic and microscopic techniques and identify/develop appropriate models. r Study kinetics of virus sorption/desorption, and develop quantitative descriptions of these processes. r Investigate the influence of physical and chemical heterogeneity on virus transport and retention in natural porous media. r Elucidate mechanisms of virus inactivation during transport in unsaturated systems, and develop appropriate models to quantify these processes. r Study the role and extent of colloids in facilitating virus transport behavior and their effect on virus survival in natural media. r Systematically compare the behavior of the commonly used model viruses with that of the representative pathogens to identify more reliable surrogates for the pathogens. In summary, viruses and other pathogenic microorganisms may be one of the greatest health risks and management challenges for our drinking water resources. Viruses pose a public health threat at a very low level; e.g., the USEPA states a limit of 2 virus particles per 107 L of water to achieve an annual infection risk of less than 10−4 (USEPA, 1994). Such a drinking-water limit can only be achieved through a more thorough understanding of virus fate and transport in the subsurface.

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JIN AND FLURY X. APPENDIX

Symbol

Description

a a aeff A ADE AWI C C Ctot Ctot,in d D DDisp DLVO fom h0 K Kd KL k ka kd kp k1, . . . , k8 L N N0 n pHIEP RSA S S Sin Smax Smin Sie X1, . . . , Xn Som Srxn TPB t v U Uin

Diameter of filter grain Radius of filter grain Effective radius of filter grain Area of mineral surfaces per mass of solid Advection–dispersion equation Air–water interface Concentration of dissolved chemical Concentration of viable viruses in liquid phase Total concentration of viable viruses Total concentration of inactivated viruses Diameter of particle Brownian diffusion coefficient Dispersion coefficient Derjaguin–Landau–Verwey–Overbeek Fraction of organic matter Water-film thickness Constant in Freundlich isotherm Distribution coefficient Constant in Langmuir isotherm Boltzmann’s constant (1.3805 × 10−23 J K−1) Attachment rate Detachment rate Rate coefficient in colloid aggregation Ad- and desorption rate coefficients Length of filter bed or space coordinate Number of particles per unit suspension volume Initial number of particles per unit suspension volume Constant in Freundlich isotherm isoelectric point Random Sequential Adsorption Concentration of sorbed chemical Concentration of sorbed viable viruses Concentration of sorbed inactivated viruses Maximal concentration of sorbed chemical in Langmuir isotherm Concentration of sorbed chemical associated with mineral surfaces Concentration of sorbed chemical bonded by electrostatic forces Various factors affecting virus inactivation Concentration of sorbed chemical associated with organic matter Concentration of sorbed chemical bonded by reversible reaction Triple-phase boundary Time Pore water velocity Concentration of viable viruses at air-water interface Concentration of inactivated viruses at air-water interface

Dimension [L] [L] [L] [L2 M−1]

[ML−3] [ML−3] [ML−3] [ML−3] [L] [L2 T−1] [L2 T−1] [−] [L] [L3 M−1] [L3 M−1] [L3 M−1] [L3 M−1 T−1] [T−1] L3 T−1] [T−1] [L] [L−3] [L−3] [−] [−] [MM−1] [MM−1] [MM−1] [MM−1] [ML−2] [ML−2] [Variable] [MM−1] [MM−1] [T] [LT−1] [ML−3] [ML−3] continues

91

SUBSURFACE VIRUS FATE AND TRANSPORT APPENDIX—continued Symbol z α α0 αp β 1, . . . ,β n βt η ηs ǫ Ŵ Ŵ max κi λ λ0 λl λs λu φ ρ σ ie σ rxn θ ϕ ξ ζ

Description Spatial coordinate Collision efficiency factor for spherical collector model Collision efficiency factor for colloidal aggregation under uniform gradient flow Collision efficiency factor for colloidal aggregation in static solution Coefficients assigned to variables X1, . . . , Xn Coefficient assigned to time t Dynamic viscosity Single-collector efficiency Porosity Surface coverage Jamming limit in RSA Rate coefficients Filtration coefficient Initial filtration coefficient First-order inactivation coefficients for the liquid phase First-order inactivation coefficients for the solid phase First-order inactivation coefficients for the air-water interface Blocking factor in surface excusion models Bulk density Concentration of charged sites on solid surface Concentration of reactive sites on solid surface Volumetric water content Total volume of particles per unit volume suspension Effectiveness of particle removal Volumetric air content

Dimension [L] [−] [−] [−] [−] [−] [MT−1 L−1] [−] [−] [−] [−] [Variable] [L−1] [L−1] [T−1] [T−1] [T−1] [Variable] [ML−3] [ML−2] [ML−2] [L3 L−3] [L3 L−3] [−] [L3 L−3]

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CURRENT CAPABILITIES AND FUTURE NEEDS OF ROOT WATER AND NUTRIENT UPTAKE MODELING Jan W. Hopmans1,∗ and Keith L. Bristow2 1

Department of Land, Air and Water Resources University of California Davis, California 95616 2 CSIRO Land and Water/CRC∗ Sugar Townsville Qld 4814, Australia

I. Introduction II. Water Transport in Plants A. Soil–Plant–Atmosphere Continuum B. Water Potential C. Cavitation D. Commentary III. Linking Plant Transpiration with Assimilation A. Integrating Root Uptake Processes B. Transpiration Coefficient C. Commentary IV. Transport of Water and Nutrients in the Plant Root A. Plant Root Structure B. Apoplastic versus Symplastic Pathway C. Commentary V. Nutrient Uptake Mechanisms A. Active versus Passive Nutrient Uptake B. Michaelis–Menten Description of Nutrient Uptake C. Commentary VI. Flow and Transport Modeling in Soils A. Soil Water Flow B. Solute Transport C. Commentary VII. Root Water Uptake A. Macroscopic Water Uptake B. Root Water Uptake Types I and II C. Other Aspects Affecting Water Uptake D. Commentary

∗ To

whom correspondence should be addressed. [email protected] 103 Advances in Agronomy, Volume 77 Copyright 2002, Elsevier Science (USA). All rights reserved. 0065-2113/02 $35.00

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HOPMANS AND BRISTOW VIII. Nutrient Uptake A. Nutrient Transport in Soils B. Nutrient Transport in the Root C. Nitrate Uptake D. Commentary IX. Coupled Root Water and Nutrient Uptake A. Mechanistic Formulations B. Other Considerations C. Multidimensional Approach D. Commentary X. Comprehensive Example XI. Prognosis References

The importance of root function in water and nutrient transport is becoming increasingly clear, as constraints on agricultural resources are imposed due to water limitations and environmental concerns. Both are driven by the increasing need to expand global food production. However, the historical neglect of consideration of water and nutrient uptake processes below ground has created a knowledge gap concerning the plant responses of nutrient and water limitations to crop production. The review includes sections on (i) notation and definitions of water potential, (ii) the physical coupling of plant transpiration and plant assimilation by way of the principles of diffusion of water vapor and carbon dioxide, (iii) apoplastic and symplastic water and nutrient pathways in plants, (iv) active and passive nutrient uptake, and (v) a discussion of the current state-of-the-art in multidimensional soil water flow and chemical transport modeling. The subsequent review of water uptake, nutrient uptake, and simultaneous water and nutrient uptake addresses shortcomings of current theory and modeling concepts. The review concludes with an example illustrating a possible multidimensional approach for simultaneous water and nutrient uptake modeling. Specific recommendations identify the need for coupling water and nutrient transport and uptake, including salinity effects on root water uptake and the provision of simultaneous passive and active nutrient uptake. It considers the requirement for multidimensional dedicated root water and nutrient uptake experiments to validate and calibrate hypothesized coupled root uptake  C 2002 Elsevier Science (USA). models.

I. INTRODUCTION Comprehensive reviews of water and nutrient uptake concepts have been written by Molz (1981), Boyer (1985), Passioura (1988), Baker et al. (1992), van Noordwijk and van de Geijn (1996), and others. However, upon reading these

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reviews one will notice that while they aspire to address mechanistic description of mass transport in plant–soil water systems, their focus is mostly on either the plant or the soil. There are only a few reviews of the functional interactions between these two subsystems. Also, there has been relatively little progress in the advancement of the basic understanding of transport processes in plants, specifically regarding their control by interfacial fluxes at either the root–soil or leaf–atmosphere interfaces. Both these observations may be a consequence of the way that scientists conduct their research. That is, after being thoroughly taught our scientific discipline of choice, we conduct our research business within its usual narrow disciplinary boundaries without really wondering too much about other closely related disciplines. Venturing too far outside one’s own strictly defined area is usually discouraged for fear of discrediting yourself as being a generalist, and ending up knowing a little about everything. Much more credit is usually given to addressing fundamental issues in narrow disciplines. Moreover, large-scale funding to support all investigators in multidisciplinary research projects is sparse, whereas publication of research findings with multiple authors is challenging and perhaps less appreciated. Alternatively, one could argue that the quantitative plant physiology of plant water transport has been lagging behind, relative to the environmental fluid mechanics studies of soil physical and atmospheric processes. The small-scale processes of atmospheric gas and soil water movement are believed to be well understood from a physical/hydrodynamic point of view. However, their connection with the plant at the interfaces is not. Undoubtedly, this is a complex and complicated area of research. Accordingly, fluxes at the interfaces (plant–soil and plant– atmosphere) are mostly empirically derived, rather than mechanistically, as might be preferred. In part, this is likely caused by the increasing complexity of biological systems, with their functions and mechanisms of internal transport of water and nutrients (xylem) and assimilates (phloem) less well understood. Consequently, water and nutrient uptake in plant growth and soil water flow models is mostly described in an empirical way, lacking a sound physiological or biophysical basis. This is unfortunate, as the exchange of water and nutrients is the unifying linkage between the plant root and the surrounding soil environment. The simplified sink approach was adequate for non-stress-plant-growth conditions and may work adequately for uniform soil conditions. However, it has become increasingly clear that a different approach is required if water and/or nutrient resources become limited in part of the root zone. Increasingly, recommended irrigation water and soil management practices tactically allocate both water and fertilizers, thereby maximizing their application efficiency and minimizing fertilizer losses through leaching toward the groundwater. For example, there has been the rise of new water and nutrient management techniques such as the simultaneous microirrigation and fertilization, or fertigation (Bar-Yosef, 1999), drip irrigation, regulated deficit irrigation (RDI), partial root zone drying (PRD; Lovey et al., 1997; Stoll et al., 2000), and band application of fertilizers. It has been suggested that the rhizosphere might also

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be responsible for accelerated breakdown of organic chemicals by biodegradation (Walton and Anderson, 1990) or extraction of contaminants by photoremediation. As pointed out by van Noordwijk and van de Geijn (1996) in their review of processoriented crop growth models, the “new” agriculture will be directed at minimizing yield losses and crop quality, while keeping environmental side effects at acceptable levels. We suggest that the effectiveness of these practices regarding their effects on crop production and groundwater quality requires a thorough understanding of plant–soil interactions and the plant’s regulatory functions in managing stresses. This includes knowledge of the crops’ responses to the availability of spatially distributed soil water and plant-available nutrients, using a multidimensional modeling approach. It is our objective to integrate principles of soil and plant sciences, by way of reviewing the soils and plant literature on water and nutrient uptake and transport concepts and processes, within the soil–plant system. In doing so, most of the atmospheric–plant interaction literature is excluded, because we assume that the potential transpiration rate is a priori known by prediction from independent measurements. However, there is no doubt about the importance of stomatal conductance and its control on plant transpiration and assimilation and the importance of the stomatal physiological response to changing atmospheric, soil, and plant environmental conditions. Excellent contributions in this field have been presented by Jarvis and McNaughton (1986), Leuning (1995), and Wang and Leuning (1998). The focus of the presented analysis is mostly on the description of the physical mechanisms, likely overlooking some of the basic biological concepts. Indeed, we admit that our background in plant biology is restricted to flow and transport within the soil–plant–atmosphere continuum (SPAC). However, we strived to integrate our understanding of the pertinent biological processes with physical principles. Although we will direct the focus of this review toward spatially distributed root functioning and integration of soil–plant interactions, this treatise does not discuss the fundamental physiological and biogeochemical processes occurring in the rhizosphere. Although it is becoming increasingly clear that rhizosphere processes play a major role in root water and nutrient uptake and plant stress responses, their general understanding is often incomplete, thereby making it difficult to integrate rhizosphere processes in the macroscopic modeling of plant growth and associated root water and nutrient uptake. For example, the root is considered the sensing organ of the soil environment and communicates with the shoot by chemical signals by transport of specific nutrients (e.g., calcium) or plant hormones to the shoot (L¨auchli and Epstein, 1990). As a result, root signals play a major role in mediating soil water and salinity stress. Specifically, root and shoot hormone levels of abscisic acid (ABA) have been shown to increase as a response to water and salinity stress (Davies et al., 2000; Stoll et al., 2000) and induce stomatal closure, whereas ethylene production is suggested to be related to drought resistance (Amzallag, 1997; Kirkham, 1990). Also, differences in soil microbial populations

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and chemical and physical properties between the rhizoshpere and the bulk soil are not specifically treated; however, it is realized that plant growth, water and nutrient uptake, and availability can be largely determined by the local environment in the rhizosphere, including root–soil contact. Hence, the measurement and modeling of processes in the bulk soil may not reflect the environment experienced by the root system. Examples of the influence of the rhizosheath on root growth and uptake processes were presented by Pierret et al. (1999) and Watt et al. (1994). The importance of soil structure and biopores on root and plant growth and nutrient uptake was considered by Passioura (1991), Volkmar (1996), and Pierret et al. (1999). Their examples show that rhizosphere properties and root functioning are different between the macropore and the bulk soil, specifically related to differences in microbiological heterogeneity and root–soil contact. In addition, this review largely ignores the role of mycorrhizae and their influence on plant water and nutrient uptake, particularly regarding phosphorus adsorption (Krikun, 1991). The trend toward the understanding of increasingly greater complexities of root uptake processes will warrant their integration in predictive crop growth modeling in the near future, as new experimental tools and better measurement methods are becoming more available. The developments and applications of innovative measurement techniques were documented by Clothier and Green (1997) and Mmolawa and Or (2000), regarding the measurement of multidimensional plant root–soil interactions, and by Asseng et al. (2000) and Clausnitzer and Hopmans (2000), who demonstrated the application of noninvasive measurement techniques to infer soil transport processes and plant root water uptake at spatial scales of less than 1 mm. This review of root water and nutrient uptake is cast within the context of crop and soil water modeling. This is because simulation models are now almost solely the universally accepted translation mechanism allowing communication and understanding among basic and applied scientists. The choice of computer models as a means to integrate state-of-the-art knowledge in root uptake mechanisms is especially advantageous when considering the integrated and interdisciplinary approach required to conceptualize the complex interactions between subsystems within SPAC. Moreover, simulation models may allow keen interpretation of experimental results, and they can be a useful tool to help understand and quantify uptake and transport processes (Whisler et al., 1986). Despite the usefulness of computer models, their development and application have limitations, as has been highlighted by Passioura (1973, 1996), Whisler et al. (1986), and Philip (1991). A major drawback of computer models is their apparent insatiable appetite for complexities, thereby providing the computer programmer with the opportunity to increase the number of a priori unknown parameters without limitations, and thereby giving the user the “false” appearance of mechanistic understanding of the simulated system. In addition, Philip (1991) forewarned that the increasing application of computer models might eventually substitute for experimentation, thereby preventing their real-word application. It is in this regard that inverse

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modeling may prove to be a more effective simulation tool. This process requires the combination of accurate experimentation with mechanistic modeling to yield appropriate measures of parameters, along with their uncertainties. Applications of such parameter estimation techniques are presented in Hopmans et al. (2002) for soil hydraulic characterization and in Vrugt et al. (2001) for characterizing multidimensional root–water uptake. Before considering root uptake mechanisms a number of related issues will be clarified in the first part of this review. First, there appears to have been a general and widespread confusion about the nature of the driving forces for water transport in plants. Even over the past 10 years, there has been a lively debate as to “how water moves through plants.” Although this difficulty, regarding flow of water and solutes between and across plant cells, is understandable, we interpret this confusion to be also an indication of the current usage of different terminologies and notations. This has led to misunderstandings and confusion between soil and plant scientists. Specifically, when considering water flow, one must clearly distinguish between water potential and water pressure. Second, we argue at the outset that there must be a clear understanding that the processes of plant transpiration (driving root–water uptake) and plant assimilation (driving nutrient uptake) are physically connected by the concurrent diffusion of water vapor and carbon dioxide through the stomata. In theory, assimilation and transpiration processes must be directly linked under both nonstressed and stressed soil environmental conditions. Clearly, this link can be achieved by introducing the notion of transpiration efficiency, defined as the mass of biomass produced per unit of water transpired (Hsiao, 1993). It has been shown that this relationship between assimilation and transpiration, although plant specific, is linear and can be applied to both stressed and nonstressed conditions. Third, a review of the analogies of water and nutrient pathways in plants between apoplastic—along cell walls—and symplastic—between cells—is needed. These will define and allow interpretation of the various plant resistances and control of the driving forces to be considered. It appears that both pathways may occur simultaneously, in parallel, and that some reference to partitioning between these two pathways is needed. Fourth, a general review and definition of active and passive uptake and their differences are needed. In particular, the literature generalizes these two uptake processes without really describing their differences. Their definition arises from thermodynamic considerations, describing transport in terms of phenomenological transport equations. Finally, although short, we review the current state of the art in modeling soil water flow and chemical transport, so that dynamic linkages with plant systems across multiple spatial dimensions can be better understood. After an introduction that elaborates on the research of the preceding five issues, reviews of water uptake, nutrient uptake, and simultaneous water and nutrient uptake will be followed by an example, summarizing a possible multidimensional approach, and a section summarizing the findings, including a synopsis on future

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research needs in root–water and nutrient uptake. It must be pointed out that notation and symbolism used here may not be familiar to everybody, as our backgrounds will vary. In the end, we introduce various alternative uptake models that are consistent with the current state-of-the-art mechanics that describe water and nutrient uptake by roots. These do not add much additional complexity and data requirements to currently used crop growth and soil water flow models.

II. WATER TRANSPORT IN PLANTS A. SOIL–PLANT–ATMOSPHERE CONTINUUM Water is transported through the soil into the roots and plant xylem toward the plant canopy where it eventually transpires into the atmosphere. In a macroscopic sense, water transport within this SPAC can occur only if water is continuous between the soil rooting zone and the plant atmosphere, an assumption that generally triggers little debate. Conceptually, water transport is mathematically described by an Ohm’s law type of relationship, expressing the flux or mass flow rate of water (M L−2 T−1) as a function of a driving force (water potential per unit distance), and a proportionality factor that defines the ability of the transmitting medium to conduct water. In soil science, this relationship is known as Darcy’s law (Darcy, 1856), and its modified form is widely accepted as a means to predict water flow in unsaturated soils from (Buckingham, 1907) Jw = −K

ψt , x

(1)

where Jw denotes water flux density (L T−1); ψt /x is defined as the total water potential gradient (L L−1), and K is known as the unsaturated hydraulic conductivity (L T−1), if ψt is expressed on a per unit weight basis. In plant science a similar expression was stated by van der Honert (1948) to define water flow in plants by Q=

ψrs − ψx , Rr

(2)

where Q denotes the rate of volumetric water flow through the plant (L3 T−1), ψr s and ψx denote the total water potential at the root surface (rs) and in the root xylem (x), both expressed in units of atm by van der Honert (1948), and Rr describes the overall root resistance to water flow (dimension depends on units used for Q and ψ). These mathematical expressions are based on the assumption that flow of water is steady and that the gradient is constant. Therefore, Eqs. (1) and (2) state that the water flow rate is constant with time at any spatial location within

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SPAC; i.e., flow must be at some kind of dynamic equilibrium. In contrast, flow is most often transient, or water fluxes change with time. Nevertheless, the steadystate expression can still be applied as long as the time period over which it is used is short compared to the rate at which the changes in time occur. The relation between flux and volumetric flow rate is determined by the cross-sectional area of the bulk soil over which flow occurs. Although this area may be well defined for soils, the actual flow area in plants is much more difficult to determine. Therefore, in plants it is much straightforward to use volumetric flow rates on a per unit plant or on a per unit leaf area basis. However, in soil water flow models, plant transpiration is defined by dividing the volumetric flow rate by the area of the soil surface represented by the plant. Also, the definition of the proportionality factor is different between plant and soil systems and is caused by the difference in physical size of the water-transmitting medium. A soil system is usually defined by the bulk soil, without consideration of the size and geometry of the individual flow channels or pores. Therefore, the hydraulic conductivity (K ) describes the ability of the bulk soil to transmit water and is expressed in dimensions of L3 L−2 T−1 (volume of water flowing per unit area of bulk soil per unit time). However, in plants one may be more concerned with the conductive ability of a single membrane or organ, where the dimensions of the system are uncertain. Consequently, the water conduction is expressed by resistance, R = x/K, or conductance C = 1/R, with dimensions determined by the units of water potential. Rather loosely, the conductance term is defined as a permeability coefficient, likely derived from the terminology used in irreversible thermodynamics (Slayter, 1967).

B. WATER POTENTIAL When considering flow in a soil–plant system it is imperative that the overall concepts and notation are well defined and universally applied. Flow mechanisms can be then be understood from the same basic principles (see also Oertli, 1996). Recently, the cohesion theory (CT) of water transport in plants has been questioned, in part because of the lack of general consensus about notation and physical principles. The CT was introduced by Dixon and Joly (1895), who suggested that water moved as a continuous stream of water through the plant, driven by the capillary pressure in the leaf canopy, allowing water to move up through tall trees against gravity (as reviewed by Canny, 1977). Recent studies have either questioned this general concept or proposed alternative mechanisms (Canny, 1995; Steudle, 1995; Wei et al., 2000) that were fueled by recent developments allowing direct xylem water potential measurement (Balling and Zimmerman, 1990; Tyree et al., 1995). Most controversies have centered on the origin of the driving force and the sustainability of water transport under low water potentials without the onset of cavitation (see Section II.C.). The analogy of flow between plants and soils is drawn because

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of their similarity in pore size ranges. For example, in plants water is transported upwards through water-conducting elements in the xylem. There are two kinds of such vessels: the tracheids which are spindle shaped and up to 5 mm long and 30 μm in diameter and other vessels that are formed by coalescing rows of cells, creating structures from a few centimeters to meters in length, and varying in diameter from 20 to 700 μm (Kramer and Boyer, 1995). Water movement within the plant is facilitated by pits or narrow pore-wall spaces between xylem vessels. Moreover, water flow in cell walls occurs through pores in the nanometer range (see Section IV.A). In SPAC, the driving force for water to flow is the gradient in total water potential (ψt). Soil water potential is formally defined as (Aslyng, 1963) “the amount of work that must be done per unit quantity of pure water in order to transport reversibly (independent of path taken) and isothermally to the soil water at a considered point, an infinitesimal quantity of water from a reference pool. The reference pool is at the elevation, the temperature, and the external gas pressure of the considered point, and contains a solution identical in composition to the soil water at the considered point.” In other words, the water potential is decreased if the water is at a lower elevation, lower temperature, lower pressure, or for water solutions with increasing solute concentrations. Adapting the Gibbs free energy concept, Nitao and Bear (1996) and Passioura (1980) demonstrated, by using the thermodynamic treatment of Bolt and Frissel (1960), that this formal definition can be extended to include surface forces acting on the surrounding liquid. As a result of this formal definition, mechanical equilibrium requires both chemical and thermal equilibrium. Moreover, the total potential of bulk soil and plant water can then be written as the sum of all possible component potentials, so that the total water potential (ψt ) is equal to the sum of osmotic (ψo ), matric (ψm ), gravitational (ψg ), and hydrostatic pressure potential (ψp), or ψt = ψo + ψm + ψg + ψ p .

(3)

This additive property of water potential assumes that water is in thermal equilibrium and that physical barriers within SPAC behave as perfect semipermeable membranes with a reflection coefficient equal to 1 (see Section IV.A.). Moreover, it makes no distinction between water solution and water as a component of the solution (Corey and Klute, 1985). The negative water potential is effectively the result of suction forces on the water solution toward the solid soil or plant cell surface, so it is often conveniently denoted by a positive suction force. Whereas in physical chemistry, the chemical potential is usually defined on a molar or mass basis, the macroscopic treatment of plants and soils expresses potential with respect to a unit volume of water, thereby giving pressure units (Pascal, Pa). When expressed per unit weight of water, the potential unit denotes the equivalent height of a water column (L). Likely, the common practice to measure water potential by water or mercury column height justifies expressing water potential in pressure terms, such

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as osmotic pressure, capillary pressure, and hydrostatic pressure. However, this notation can lead to misinterpretation of the physical meaning of water potential, since gauge pressure is defined relative to atmospheric pressure. Atmospheric pressure is caused by the weight of the air at the Earth’s surface, and is roughly 1 bar (about 1033 cm of water column, or about 100 kPa = 0.1 MPa) at sea level. Thus in the true sense of pressure, the absolute water pressure can never be smaller than −1 bar relative to atmospheric pressure, or zero absolute pressure. Nevertheless, internal forces within the water can create suction forces that correspond to water potentials much lower than −1 bar. With the introduction of pressure transducers, it is now physically possible to measure these forces that correspond with negative water potentials, much smaller than the pressure equivalent of −1 bar. For example, Steudle and Heydt (1988) and Ridley and Burland (1999) demonstrated the application of pressure transducers to directly measure osmotic and matric potentials in soils down to −0.7 and −1.5 MPa (−7 and −15 bar, respectively) for prolonged times. These negative water potential measurements are only possible if cavitation is prevented. Contributions to the driving force for soil water flow may arise not only from gravity and capillary forces, but total water potential may include osmotic and surface forces. Flow by gravitation is caused by differences in vertical elevation, whereas osmotic potential is caused by a nonzero solution concentration of the bulk soil solution outside the diffuse double layer (ddl). The ddl is defined by the thickness of the water film, in which the ion distribution varies with distance to a charged surface, as a consequence of a balance between diffusive and adsorptive forces. Osmotic potential is effective only when solutes are constrained relative to water mobility, such as by a semipermeable membrane in plant roots. Hence, without such membranes, the total driving force for water flow should exclude the osmotic potential; however, its magnitude will depend on the leakiness or reflection coefficient of the membrane. Whereas the osmotic and gravitational components of the total water potential are generally well understood, the definition of matric and hydrostatic pressure potentials and their distinction require further attention. The matric potential (ψm ) is caused by a combination of capillary and surface forces, resulting in a capillary (ψcap) and surface force component to the total water potential. The following explanation of matric potential considers the various forces with corresponding potentials within the water film around a soil particle, hence considers a microscopic view point. The capillary forces are caused by surface cohesion forces at the air–water interface, combined with the solid–water adhesion forces, creating a concave interfacial curvature and subsequent lowering of the water potential for an air–water interface. The surface forces become important when liquid films are covering the entire solid surface, and they can be composed of various component forces that are (i) molecular-short-range London–van der Waals forces, (ii) electrostatic, and (iii) osmotic. Except for the molecular forces, the other two adsorptive forces

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are a consequence of a charged solid surface. The electrostatic forces are due to the dipolar nature of water molecules that orient themselves because of electrical forces in the ddl of the water solution near the charged soil or plant cell surface. These molecular and electrostatic forces combined create a negative water potential, defined as the adsorptive potential (ψa ), that is, they are most negative at the solid surface and increase toward zero at the end of the diffuse double layer, which is about 1 μm or smaller. The third force acting on water molecules in the double layer is a result of the increasing ion concentration toward the solid surface, resulting in a negative osmotic potential (ψo,ddl ) that is caused by the constrained ions in the double layer. The resulting osmotic potential due to ions in the ddl in excess to those in the bulk soil solution decreases from the pore water solution inward. To attain mechanical equilibrium, the adsorptive and osmotic potentials combined are compensated by an increasing pressure potential toward the soil surface, ψ P , or ψm = ψo,ddl + ψa + ψ P . For a clarification of this concept, a hypothetical water potential distribution within a truncated ddl and a concave air–water interface (ψcap < 0) is presented in Fig. 1, where the various water potential components are shown as a function of distance to the soil particle surface. For a truncated ddl, the water film thickness is smaller than the spatial extend of a fully developed ddl. The disjoining pressure concept (Derjaguin et al., 1957; Tuller et al., 1999) can be included in this concept by defining the pressure potential as the sum of capillary and disjoining pressure (ψd p ), or ψ P = ψcap + ψd p . Its value is maximum at the soil surface and decreases toward the air–water interface or half-distance between solid surfaces for a saturated soil pore (see Fig. 1). It is this disjoining pressure that results

Figure 1 Spatial distribution of water potential components in a truncated diffuse double layer (adapted from Koorevaar et al., 1983).

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in repulsive forces, causing clays to expand upon wetting. Additional explanations of the underlying concepts and definition and application of matric potential were presented in Koorevaar et al. (1983) and Dane and Hopmans (2002). Finally, the last term of Eq. (3) to consider is the macroscopic hydrostatic pressure potential (ψ p ). It is included separately to distinguish its positive value from the other negative matric water potentials (ψm ). In soils, the hydrostatic pressure potential originates from the hydrostatic pressure caused by saturated soil conditions, whereas in plant cells the hydrostatic component is represented by the turgor pressure.

C. CAVITATION Cavitation starts when gas or vapor bubbles are formed in water under tension. Those create embolisms by exceeding the tensile strength of water and disrupting the hydraulic continuity of the conducting soil pore or xylem vessels and tracheids. They prevent the xylem water from sustaining the low water potentials required to drive a given transpiration stream. Vapor bubbles can be triggered at gaseous or other hydrophobic surfaces and by gas seeds already present on the pore surface. Water normally cavitates when the absolute water pressure is slightly smaller than its vapor pressure. However, higher tensions can be sustained if the radii of cavitation nuclei are sufficiently reduced (Guan and Fredlund, 1997; Tyree, 1997). The critical water pressure for cavitation (P∗ ) to occur is controlled by the radius of the seed bubble (r∗ ), as determined from Pbubble − Pxylem =

0.15 2σair−water ≈ , r r

(4)

or the capillary presssure equation of Youngs and Laplace (Pbubble < Pxylem); where σ denotes the temperature-dependent surface tension of water in contact with air, and P and r are expressed in centimeter units. Cavitation by gas bubble growth may occur if the xylem water pressure, Pxylem on the left-hand side of Eq. (4), is less than P∗ for that specific size bubble with radius r = r∗ (Pbubble ≈ 0, when equal to vapor pressure of water). For example, if the gas seed has a radius r∗ = 0.21 μm, cavitation will be triggered only if the xylem water potential is more negative than −0.7 MPa. Subsequently, if Pxylem becomes larger than P∗ , the bubble will reduce in size or collapse. Because of the metastable state of water, conducting pores with r < r∗ will remain conductive for Pxylem > P∗ (Tyree, 1997). Applying this theory to unsaturated soils may lead to situations of cavitation as well, resulting in changes in entrapped air phase and unsaturated hydraulic conductivity in soils, thereby affecting the unsaturated water flow regime. For example, Or and Tuller (2002) suggest that bubble formation can significantly affect the drainage branch of the soil water retention curve, depending on whether the soil is drained by positive gas pressure or under tension. In addition to being formed from small-sized seeds

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already in the xylem system, gas bubbles can also move into the water-conducting vessels by air seeding from neighboring conduits through pore walls (Tyree, 1997) or by temperature fluctuations. However, air access is prevented if these pore radii are small enough (r < r∗ ), or if their air-entry value is not exceeded. Consequently, although cavitation is likely to occur to some degree in xylem vessels at low water potentials, it will disrupt flow only in the larger vessels, which will reduce the xylem hydraulic conductivity. However, this is not such a surprise, knowing that transpiration rates may be significantly reduced and be close to zero anyway at sufficiently low xylem water potentials.

D. COMMENTARY In summary, the driving force for water flow in plants is the total water potential gradient as it is in soils. However, in contrast to soils, the osmotic component must always be considered for flow through the roots, since water can move through cell membranes as a result of osmotic potential gradients. However, water movement along osmotic potential gradients is by diffusion, and flow paths will likely be different from those followed by water driven by matric potential gradients, with each flow path characterized by its own specific hydraulic conductance. Flow can be even more complex as water diffusion through membranes by osmotic gradients in one direction might cause matric potential and/or hydrostatic pressure potential gradients in the opposite direction. Within the xylem vessels and tracheids, water and solute flow is likely by advection, so that osmotic gradients will not have to be considered. However, it is specifically in the xylem system that the gravitational component must be included. For example, to move water up a 25-m-tall tree, the total water potential change in the xylem from the roots to the tree canopy must be equal to or larger than 2.5 bar. For conditions of low water potentials, cavitation may cause embolisms in the xylem, thereby decreasing the axial conductance of water flow through plants. However, water can bypass cavitated parts of the xylem by lateral movement to other water-conducting vessels. Moreover, as in soils, water can move through water films along the xylem cell walls by surface forces, creating adsorption potential gradients (Amin, 1980; Canny, 1977).

III. LINKING PLANT TRANSPIRATION WITH ASSIMILATION A. INTEGRATING ROOT UPTAKE PROCESSES Within the general framework of crop growth modeling, one must take the broad plant–soil–atmosphere approach with linkages between individual system

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components. In the past this approach was limited when crop production research was viewed from the plant perspective only. Rather, there was the development of empirical relationships between yield and water and/or nutrient application (see Viets, 1962). Empirical relationships were considered adequate for soil water and nutrient management, even in the 1970s, when plant productivity was still the main driver and justification for agronomic research. Crop water use research was mostly driven by the need for arid-region-irrigated agriculture where water is a scarce resource (Tanner and Sinclair, 1983). However, the need to integrate plant physiology with environmental sciences such as soil physics, micrometeorology, and agronomy was noted by Slayter in 1967. He justified this by acknowledging the control of plant cell water status on the plant’s environmental surroundings by water exchanges. Moreover, there is increasing evidence that photosynthesis is better correlated with soil water potential than leaf water potential status, indicating that roots respond to stressed soil conditions by transmission of hormonal signals to the shoot (Davies et al., 1994; Johnson et al., 1991; Passioura, 1996). Although much progress was reported in the seminal review of plant responses to water stress by Hsiao (1973), still much more research is needed to improve feedback mechanisms in soil and crop growth modeling (van Noordwijk and van de Geijn, 1996). In part, the historical neglect of consideration of water and nutrient uptake processes below ground has led to a knowledge gap between plant responses to nutrient and water limitations and crop production. The importance of root function in water and nutrient transport becomes increasingly clear, as constraints on agricultural resources are imposed due to water limitations and environmental concerns such as those caused by groundwater contamination. Both of these are driven by the ever-increasing need to expand global food production while taking better care of the environment. Contemporary agriculture is directed toward minimizing yield losses and limiting the degradation of soil and water resources, so as to keep environmental effects of crop production within acceptable levels (van Noordwijk and van de Geijn, 1996). This current state of sustainable agricultural systems justifies the increasing need for combining soil knowledge with plant expertise, in particular as related to root development and functioning. This development may result in a better understanding of water and nutrient stress on crop productivity, in relation to heterogeneous soils with spatial and temporal variations in nutrient and water availability in combination with spatially distributed rooting systems. As was also clearly stated by Clothier and Green (1997), roots serve as big movers of water and chemicals in soils, and a much better understanding of root functioning and uptake mechanisms of roots is needed to establish sustainable crop production protocols. Soil scientists have paid much attention to water movement and chemical transport in the absence of roots, but much less to soil processes that are influenced by root development and function. In part, root systems are neglected because they

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are hidden below the ground, and their extensive branching makes description difficult. For the plant physiologist, it is mostly the above ground portion of the plant that has been the most intriguing. It is here where photosynthesis takes place, and the leaves can be seen! Root growth and root systems nonetheless play critical roles in providing water and basic nutrients for leaf and shoot growth and development (Hoogenboom, 1999). Our physiological knowledge of root water and nutrient uptake and root–shoot interactions lacks a basic understanding, especially when soil water or nutrients are limiting. Consequently, both crop simulation and water flow models tend to treat root uptake mostly by empirically means, thereby limiting their general application. As stated earlier, the need for crop simulation models originally arose from the wish to maximize crop productivity. In a mechanistic sense, the driving force for these crop growth models was generally the radiation use efficiency (RUE) or biomass produced per unit of photosynthetic active radiation (PAR). This has been coupled with plant canopy coverage or leaf area index (LAI), and then extension growth was largely determined by thermal time and leaf N content (van Keulen and Seligman, 1987). Simulation models that focus on crop growth simplify soil water flow and transport and water and nutrient uptake. They ignore the dynamics of soil water and nutrient availability and uptake. In most models, relatively simple algorithms determine crop or soil control of nutrient uptake by a switch, depending on values of cumulative uptake versus demand. Examples of these model types are CERES (Godwin and Jones, 1991; Ritchie and Godwin, 2000), APSIM (Keating et al., 1999; McCown et al., 1996), and NutriAce (GRAZPLAN Project, 1997). Potential crop nitrogen demand is determined by growth-stage-dependent plant N concentration and biomass production. Water and nitrogen stress are quantified by “zero-to-unity” water or nitrogen supply factors that are computed from soil availability to reduce RUE and LAI accordingly (van Keulen and Seligman, 1987). The continued development of soil water modeling has traditionally been justified from the water management point of view considering irrigation and groundwater table management. However, this has been extended because water is the key transport vehicle for dissolved chemicals in soils. In either case, plant growth is considered secondary, although plant evapotranspiration (ET) is among the most important driving forces for water flow in soils. Soil water flow models compute ET from atmospheric variables such as net radiation, air humidity, and wind velocity. These include soil evaporation (Ritchie, 1972) and consider crop-specific transpiration using reference crop ET using growth-stage-dependent crop coefficients (Allen et al., 1998; Doorenbos and Pruitt, 1977). Uncertainties in water flow modeling mostly result from inherent spatial and temporal variability in soil physical properties, and they often lead to preferential transport of water and associated chemicals at much faster rates than predicted. Dynamic water flow models, however, almost exclusively ignore crop growth processes and associated mechanics of water and nutrient uptake. The influence of the plant is included in the water flow

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equation by way of a distributed root water uptake or sink term. The magnitude of this form depends on root distribution and ET. Also, water flow models generally apply “zero-to-one” stress factors to mimic the influence of water shortage, and/or salinity buildup. The exception is those that include soil and plant resistances for water flow, thereby allowing iterative computation of water uptake as controlled by plant water status. Nutrient uptake is either absent or simply coupled to the water uptake term, with an additional “zero-to-one” factor to account for nutrientspecific mechanisms other than by passive uptake. Examples of these types of ˇ unek et al., 1999) and SWIMv2.1 (Verburg et al., models are HYDRUS2D (Sim˚ 1996). In either case, crop simulation or soil water flow modeling, simplified empirical expressions are applied to simulate the effects of soil water and nutrient stress on ET, RUE, and leaf growth rate.

B. TRANSPIRATION COEFFICIENT When combining plant and soil water simulation models, it is essential that net radiation provide the driving force for both biomass production and evapotranspiration. It allows the combined model to be calibrated using independently measured biomass and ET data. Although plant species specific, this ratio of transpiration to assimilation has been shown to be fairly constant (Hsiao, 1993). Despite that only about 60% of all assimilates being used for biomass production, with the remainder lost by respiration, about 95% of total water uptake is lost by transpiration. The transpiration to assimilation ratio (TAR) may vary between 30 and 150 kg/kg depending on meteorological conditions and plant species. van Noordwijk and van de Geijn (1996) introduced the water utilization efficiency (WUTE), defined as the dry weight production per unit volume of transpired water, reporting a range of values between 3 and 7 g/kg. Alternatively, one can define water use efficiency (WUE) or a transpiration coefficient (TRC), both denoting the mass of water transpired per unit biomass produced (Hsiao, 1993). This constant ratio was already introduced by de Wit (1958), when he presented crop-specific, unique relationships between crop yield and plant transpiration, after correction for evaporative demand through division of actual transpiration by potential ET. This almost constant ratio, even under water or nitrogen stress conditions can be explained by the sharing of transport pathways by CO2 and water vapor as they pass between the atmosphere and the intercellular leaf space. Also, this is in response to the dominant control of leaf-intercepted radiation on both assimilation and transpiration, although assimilation only uses the PAR part of total radiation (Hsiao, 1993). Variations in TRC occur between plant species as a result of differences between C3 versus C4 plants, the types of stomatal control, and the size and number of leaf stomata. Also, changes in environmental conditions, such as those caused by variations in CO2 (by elevated CO2 levels in atmosphere) and water vapor

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concentration gradients (by changes in plant leaf temperature), affect the magnitude of TRC (van Keulen and van Laar, 1986; Hsiao, 1993). The inclusion of the TRC concept in crop simulation modeling under stressed soil water conditions was first introduced by van Keulen and Seligman (1987). Their suggestion was to multiply the potential assimilation rate (radiation limited for nonstressed conditions) with the actual to potential transpiration ratio. However, current crop growth or water flow simulation models that incorporate radiation control of both biomass production and transpiration are few. Exceptions are the SWAP model (van Dam et al., 1997) and RZWQM (Ahuja et al., 1999). The SWAP model combines a field-scale water flow and nutrient transport model with a universal crop-growth simulator (Spitters et al., 1989). In this combined model, plant transpiration is computed from potential ET and a crop-stage-dependent LAI, whereas potential photosynthesis is controlled by RUE and LAI. Both ET and photosynthesis are then reduced by water and/or salinity stress factors that are computed from the decreased root water uptake as computed from the water flow model. RZWQM is an integrated physical, biological, and chemical one-dimensional process model, simulating crop growth and movement of water, nutrients, and pesticides over and through the root zone. The model includes a generic crop growth simulator, estimates soil evaporation and plant transpiration, and links total root water and nutrient extraction to atmospheric demand.

C. COMMENTARY For crop growth modeling purposes, there must be a clear and intuitive understanding that plant transpiration and plant assimilation are physically connected by the concurrent diffusion of water vapor and carbon dioxide between the plant canopy and surrounding atmosphere through leaf stomata. Conceptually, assimilation and transpiration processes must be directly linked under both nonstressed and stressed soil environmental conditions. This is achieved in crop growth modeling by introduction of a WUE parameter, such as the transpiration coefficient (TRC). A first attempt to a mechanistic, multidimensional root growth and root uptake modeling approach was presented by Somma et al. (1998), by linking a threedimensional transient flow and nutrient transport model to a root growth simulator. The simulation domain was discretized into a grid of finite elements in which the soil physical properties are distributed. Solute transport modeling included nutrient transport in the soil domain by both convection or mass flow and diffusion. Root water uptake was computed as a function of matric and osmotic potential, whereas absorption of nutrients by the roots was calculated as a result of both passive and active uptake mechanisms. Genotype-specific and environment-dependent root growth processes were described using empirical functions. The most comprehensive modeling level included simulation of root and shoot growth, as influenced

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by soil water and nutrient status, TRC, temperature, and the dynamic allocation of assimilates to root and shoot. However, the extreme complexity of the model has precluded the expected application for plant growth simulations. Moreover, the physiological basis for biomass production and allocation as is generally included in crop growth simulation models was lacking. Nevertheless, the Somma et al. (1998) model included the essential features required for an integrated plant growth–soil water simulation model.

IV. TRANSPORT OF WATER AND NUTRIENTS IN THE PLANT ROOT A. PLANT ROOT STRUCTURE Although variable in size between monocotyledons and dicotyledons, the general structure of root apices is broadly similar for many plants (Russell, 1977). They contain the vascular stele and root cortex (Fig. 2). The inner center contains the stele, which includes the xylem and phloem, which are surrounded by the

Figure 2 Diagrammatic cross-sectional area of the apical zone of a plant root. The stele includes xylem and phloem elements, surrounded by pericycle.

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pericycle. The cortex consists of the inner endodermis, cortex, and hypodermis and is bounded by an outer layer of epidermal cells from where root hairs develop. Some roots will include an exodermis (Peterson, 1989), which is a specialized form of the hypodermis. If present, it can also be a major barrier of transport of water and nutrients through suberization of cell walls and presence of a Casparian band, as occurs in the endodermis. Roots are in contact with the surrounding soil by a film on its surfaces or mucigel which can also play a controlling role on water and nutrient absorption by the plant. The radial pathways for water and nutrients in roots are either intracellular (apoplastic) and/or intercellular (symplastic pathway). The separation of both pathways is controlled by the plasmalemma. The protoplasm of plant cells are connected through plasmadesmata, which form continuous pathways between plant cells, allowing water and solutes to move along the symplastic pathway between cells. The apoplastic pathway occurs through cell walls that are constructed from bundles of cellulose molecules (microfibrils), surrounded by other polymers with a combined size of 3–30 nm, providing pore spaces of 4- to 8-nm-diameter pores (Fig. 3). Within this matrix, water and solutes can move freely within the cell wall solution, unless prohibited by the physical size of large, high-molecular-weight molecules. The second kind of pore space within the cell wall is much larger, about 50 nm, and forms a connection between plant cells by plasmodesmata,

Figure 3 Diagram of apoplast (shaded) of a plant cell and an enlarged view of cell wall. [Reproduced from P. J. Kramer and J. S. Boyer (1995). “Water Relations of Plant and Soils.” Copyright 1995. Academic Press, San Diego, with written permission from Harcourt.]

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providing a low resistance pathway for water and solute movement between plant cells. The plasmodesmata are lined by the plasmalemma and contain protoplasm of cell material, thereby providing opportunity for symplastic transport. Their frequency of presence appears to be well correlated with nutrient fluxes, with a high abundance indicating dominant symplastic transport. The cell walls at a distance of about 1–2 mm from the root tip characteristically include an endodermis, which consists of only one cell layer. However, it plays a major function in the conduction of water and nutrients through the root. This functional aspect of the endodermis is caused by the development of the Casparian band. This is a thickening of the radial walls along the plasmalemma. The Casparian band is impregnated with suberin and lignin between the microfibrils of the cell wall, thereby making the endodermal cell wall hydrophobic and greatly reducing the porosity and permeability of their radial walls. Since the only effective way to move from the cortex to the stele is through the endodermal protoplast, the endodermis provides a major barrier to water flow and acts as a selective membrane for solute transport. When present, the endodermis completely blocks water movement, thereby requiring water to move through the plasmalemma before returning to the walls of the stele cells. Further away from the root tip, some 1–20 cm from the tip, a secondary deposition of suberin lamellae forms over the entire endodermal wall and creates an additional layer of hydrophobic material, preventing exchange of water between cell walls and cytoplasm. This completely blocks the apoplastic pathway, including the wall-to-cell flow route (Epstein, 1966). Consequently, it is believed that the dominant pathways for water uptake occurs directly behind the root tip, where the second layer of suberization is still lacking. However, in certain places suberization may be less well developed, and the effectiveness of the endodermal barrier may be reduced (Slayter, 1967), thereby opening the apoplastic pathways. Cell walls are negatively charged by dissociated carboxyl groups, thereby creating a diffuse double layer, as occurs in soils, along the cell wall. Therefore, the apoplast tends to exclude anions and preferentially absorbs cations such as Ca and K. In addition, ionic interactions within the cell wall slow down diffusion and affect active ion transport by carrier proteins (Clarkson, 1996). A schematic diagram showing flow from the cortex, through the endodermis to the stele, is presented in Fig. 4. One may distinguish at least three different pathways with differences between flow routes determined by the type and number of membrane crossings.

B. APOPLASTIC VERSUS SYMPLASTIC PATHWAY As one might expect, water flow through the cortex is mostly apoplastic, but includes symplastic flow through the endodermis, as flow is diverted because of

Figure 4 Schematic representation of pathways for water and nutrients across root cells from the cortex (left) through the endodermis (center) toward the stele (right).

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the presence of the Casparian band. Approaching the endodermis, water flow may either (i) move through the Casparian band by osmotic gradients or (ii) bypass the endodermis, moving through the cell wall and plasmalemma into the symplastic pathway, returning back to the apoplast once the Casparian band has been passed. In either case, considering water uptake across the whole plant, hydraulic equilibrium requires that the total water potential in the apoplast and symplast be the same (Kramer and Boyer, 1995). However, component potentials may differ, with generally much smaller osmotic potentials in the symplast, resulting in positive hydrostatic water potential, whereas the high osmotic potentials in the apoplast correspond with negative matric pressures in the apoplast. The transport of solutes may occur by active transport (see Section V), such as by ion channels and ion carriers (Russell, 1977) within the endodermis, so that plant nutrients can effectively bypass the Casparian strip as well. In part, the question regarding the contribution of the symplastic and apoplastic pathways to total transport has remained unanswered because transport appears to be dependent on plant species and ion type. Moreover, increasing experimental evidence (e.g., Weatherley, 1963) suggests that cell walls offer an important pathway for water movement by mass flow, possibly because of the occurrence of osmotically driven water flow across the Casparian band or by the occasional absence or incomplete development of the Casparian band. Molz and Ikenberry (1974) and Molz (1981) presented a mathematical development for parallel water transport across roots by symplastic and apoplastic movement. The physical–mathematical treatment of flow of water and solutes across roots for steady mass fluxes of water (Jwater) and solute (Jsolute) can be described by (Dalton et al., 1975; Fiscus, 1975; Steudle, 1994; Zimmerman and Steudle, 1978) Jwater = L (P − σ )

(5)

Jsolute = ω + (1 − σ ) Csoil Jwater + J ∗ .

(6)

and

In this approach, the soil and root system is simplified to a two-compartment (soil solution or apoplast, and cell solution or symplast) system. The compartments are separated by a single effective semipermeable membrane with a reflection coefficient, σ , representing the effectiveness of the membrane complex (plasmalemma and Casparian band) for water flow by a concentration gradient. Thus, if σ = 0, the membrane is fully permeable to both water and solutes. In this situation, the membrane cannot function as a means of driving water by a concentration difference, c, between the comparments. The concentration is here expressed by osmotic pressure, or  = RTc. The parameter, L, reflects the effective permeability of the membrane to water, sometimes also called the filtration coefficient. Hence, in this formulation both apoplastic and symplastic pathways for water flow are

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combined into a single equivalent membrane. Solute transport may occur by diffusion, with ω denoting the effective diffusion coefficient or solute permeability of the membrane (ω = 0, if σ = 1), effectively allowing osmotic adjustment of the symplast to water stress conditions (low matric potential in apoplast), or by advection (Jwater) or solute drag, or by active uptake, J∗ (see Section V.A). Although these transport equations allow for a simple mechanistic description of flow and nutrient transport by roots, the combined expressions (5) and (6) fail to recognize that flow and transport may occur by different pathways, with pathwayspecific permeabilities and reflection coefficients. Nevertheless, the adaptation of the two-compartment model with a single membrane can be justified (Steudle, 1994; Steudle et al., 1987). Moreover, the proposed physical–mathematical model of Dalton et al. (1975) that will be discussed in Section IX.A predicts that the value of the root permeability is dependent on transpiration rate, a finding that has been experimentally confirmed by many investigators (Fiscus, 1983). Steudle et al. (1987) stated that effective root permeability, L, depends on the contribution of the various root-conducting parts to overall water transport, since different root tissues may have different hydraulic resistances. Consequently, root permeability is expected to be plant species dependent and is a function of the developmental stage of the plant. Moreover, it was postulated that flow paths are different depending on whether concentration (osmotic driving force) or water pressure (matric pressure driving force) gradients are induced across the plant root. To investigate water transport in plant roots, a root pressure probe was developed (Balling and Zimmerman, 1990; Steudle et al., 1987) to measure directly root xylem water pressure. In the experiments of Steudle et al. (1987), controlled gradients of water and osmotic pressure were established to study the influence of different driving force types (osmotic or matric pressure) on root conductivity. They concluded that the driving force effect was plant species dependent and that it is determined by differences in flow path mechanisms between species. More specifically, it was shown for maize roots that water flow induced by matric pressure gradients is mainly apoplastic, whereas a major contribution to osmoticinduced flow is the cell-to-cell or symplastic pathway. The small contribution of the apoplastic pathway was caused by the low reflection coefficient value of the endodermis, causing a low permeabililty of the apoplast as induced by a concentration gradient in Eq. (5). Measured hydraulic conductivities between pathways differed by one order of magnitude or more. This new composite transport model with parallel transport of water between plant cells along the symplastic pathway, and through cell walls following the apoplastic pathway, was further refined in Steudle (1994). In their work, the simplicity of the two-compartment plant root system was maintained; however, the effective root membrane reflection coefficient was computed from fractional contributions of cross-sectional areas of apoplastic and symplastic pathways and their respective permeability values (see Section VII.C).

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C. COMMENTARY Water and nutrient transport in the root is mechanistically described by a set of coupled transport equations describing the simultaneous uptake of water and nutrient into the roots. In this approach, the soil and root system is simplified by a two-compartment, system, separated by a single effective semipermeable membrane, separating the soil solution or apoplast from the cell solution or symplast. The driving force for water flow in plants is the total water potential gradient. However, in contrast to soils, the osmotic component must always be considered for flow through the plant roots as cell walls act as a semipermeable membrane. However, water movement by osmotic potential gradients occurs by diffusion, so that water flow paths used as a result of matric potential gradients are likely different from those driven by osmotic potential gradients. For example, it was shown for maize roots that water flow induced by matric potential gradients is mainly apoplastic, whereas a major contribution to osmotic-induced flow is the cell-tocell or symplastic pathway. Measured hydraulic conductances between pathways can differ by one order of magnitude or more. Therefore, the mechanistic description of water flow and nutrient transport through plant roots should consider this parallel transport through symplastic and apoplastic pathways. Also, discrimination between mechanisms of transport in the roots between water and nutrients may dictate differences between the spatial distribution of the main water and nutrient uptake sites within a rooting system and their variation in time.

V. NUTRIENT UPTAKE MECHANISMS Using Eq. (6) in Section IV.B, it is demonstrated that nutrient uptake and transport within the root can occur by three different mechanisms. First, transport is driven by concentration gradients, causing nutrient movement by diffusion, and is generally driven by electrochemical gradients. Second, nutrients move into and through the root by mass transport when dissolved in water. This mechanism is generally designated as the convective transport component of nutrient transport. It is computed from the product of nutrient concentration and water flux density. Third, active uptake occurs by nutrient flows against concentration or electrochemical gradients. It is this third component of nutrient uptake that is sometimes referred to as “magic uptake,” and therefore requires separate treatment.

A. ACTIVE VERSUS PASSIVE NUTRIENT UPTAKE As the plant solution concentration of many macronutrients may be larger than that in the soil solution (Epstein, 1960), their uptake may require specialized

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ion-specific uptake mechanisms against an electrical or concentration gradient. Active transport is by definition a process in which energy, provided by respiration, is expended in moving ions from a zone of lower to higher electrochemical potential or concentration. Energy demand for ion uptake can be large and can consume as much as 35% of the total respiratory energy (Marschner, 1995). The fundamental difference between passive and active transport is determined by the description of coupled flow of water, solute, heat, and electrical charge, using the general theory of irreversible thermodynamics. The resulting set of phenomenological equations defines the flux of each physical unit as a linear function of all possible forces operating in the system. Transport is defined as passive if the flux is the result of any of the gradients included in these coupled transport equations. If, on the other hand, flux occurs irrespective of the presence of the formulated forces, transport is defined as active. This theory is applied in soil physics to describe the simultaneous transport of heat and water in soils, allowing both water and heat transport by water potential and temperature gradients (Taylor and Cary, 1964). When considering the transport of water and solutes in soil–plant systems, this theory leads to the coupled Eqs. (5) and (6), neglecting the influence of temperature on mass transport, with the cross or phenomenological coefficients defining the influence of water potential gradients on solute transport and concentration gradients on water flow. Plant root water uptake is generally considered as passive only, although some active water movement may occur by electro-osmosis and other physiochemical mechanisms (Dainty, 1963; Slayter, 1967). However, the distinction between passive and active uptake is not so clear and depends on which driving forces are considered in describing total mass transport. The differences between “passive or physical” and “active or metabolic” nutrient adsorption were introduced by Epstein (1960). The two different mechanisms lead to transport “down a gradient” and “against a gradient,” respectively. Passive transport occurs in the root’s free space (cell walls) and is kinetically controlled by diffusion and mass flow, with ion exchange occurring between the solution and the negatively charged cell walls. Since diffusion across the plasmalemma or the tonoplast (see Fig. 4) may be severely limited, active transport mechanisms to move specific ions into the cytoplasm, across the plasmalemma, and vacuole, across the tonoplast, are required. Specifically, the transport of water and nutrients is impeded by the presence of the Casparian band in the endodermis. The active ion transport across the plasmalemma and tonoplast is driven by specific energy-driven ion carriers or through ion channels embedded in slowly permeable, hydrophilic lipids within the cell membrane. Cell membranes control transport of nutrients from the apoplast (cell walls) to the symplast (cytoplasm and vacuole) and subsequently into the xylem. Their capability of transport and their regulation are closely related to their chemical composition and molecular structure. These membranes dominantly consist of hydrophobic polar lipids, which are combined by extrinsic proteins on the outside of the membrane with hydrogen

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Figure 5 Generalized model of a plasma membrane structure. [Reproduced from H. Marschner (1995). “Mineral Nutrition of Higher Plants,” second edition. Copyright 1995. Academic Press, San Diego, with written permission from Harcourt.]

bonds (see Fig. 5) to provide hydrophillic sections. In this way, active ion transport is mediated across the membrane; however, ion movement is by a diffusion type of transport. Alternatively, intrinsic proteins may be integrated into the membrane, allowing movement of hydrated nutrients through small open spaces or voids ( ψ3 , the resulting decreasing xylem water potential does not affect Tpot. Osmotic stress can be included by multiplication of the right-hand term of Eq. (19) by a salinity stress response function, as demonstrated by van Dam et al. (1997) and Homae (1999) in Si = αi (ψm ) αi (ψo ) Smax,i ,

(20)

where α(ψo) defines the salinity stress reduction function, also with values between zero and one. Using the analogy of stress and crop yield (de Wit, 1958), an example of an osmotic stress response function is presented in Fig. 9, where soil salinity is

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Stress–response function for salinity stress (adapted from Van Dam et al., 1997).

expressed by electrical conductivity (EC) of the soil saturation extract (ECext), as defined by Maas and Hoffman (1977). An alternative stress response function was presented by van Genuchten (1987), or, α (ψm ) =

1 1+



ψm,i ψm,50

p ,

(21)

where ψm,50 defines the soil water matric potential at which α(ψm ) = 0.5. This model is analogous to the expression introduced by van Genuchten and Hoffman (1984) that included osmotic effects on plant water stress by adding the osmotic potential to the power term in the denominator. Both root water extraction types I and II were examined by Cardon and Letey (1992) to investigate their sensitivity to salinity stress. It was concluded that the mechanistic approach of the type I models, while including the osmotic potential in Eq. (18), was insensitive to salinity with little reduction in Tpot for irrigation water salinities up to 6 dS/m. Moreover, the type I approach occasionally resulted in abrupt changes of plant transpiration, from Tpot to zero, particularly under saline conditions. For such conditions, Shani and Dudley (1996) proposed a combinational approach, using the type I model (Nimah and Hanks, 1973) to account for soil water matric stresses, α(ψm ), in combination with a type II model (van Genuchten, 1987) to account for osmotic stress, α(ψo ), on plant transpiration and crop yield by replacing ψm in Eq. (21) by ψo . Using this combinational approach, the effects of the osmotic and matric potential on crop yield were multiplicative rather than additive. This approach is similar to the one suggested by van Dam (1997) using Eq. (20).

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C. OTHER ASPECTS AFFECTING WATER UPTAKE The effect of soil salinity on water stress can be better understood by considering the uptake expressions (Slayter, 1965) Jwater = L ′ (P − σ )

(22a)

Jwater = L(ψm + σ ψo ),

(22b)

or

which are routinely used when considering flow of water and solutes across the plasmalemma and tonoplast. The matric potential component may instead be replaced by a hydrostatic pressure component if plant water pressure is positive, such as when turgor pressure is considered for transport of water between vacuoles and the soil. The parameter L denotes the effective hydraulic conductance of the root, and σ is the effective reflection coefficient of all water-transporting root membranes combined (Section IV.B). The difference in adopted notation between L′ and L merely reflects the distinction in dimensions between the applied driving forces P (Eq. 22a) or ψm (Eq. 22b). The reflection coefficient value varies between one and zero. Its value is an indication of the effectiveness of the osmotic potential as a driving force for water flow across roots. Using a value of 1, the osmotic potential gradient is equally effective as a matric potential gradient. This is the case for a perfect semipermeable membrane, such as occurs in a well-developed endodermis. In contrast, a reflection coefficient of zero describes a completely leaky membrane where osmotic potentials are not effective in moving water through the roots, such as is the case within the xylem and across cell walls. The true value of the reflection coefficient is a function of solute and plant species, with some values presented in Table 3.2 of Kramer and Boyer (1995). Whereas the formulation in Eq. (22) regards the root as a simple conduit for water transfer, more recent research has demonstrated (see also Section IV.B) that there may be a number of different flow paths for water to move through the root. Specifically, these are the apoplastic and symplastic pathway, each characterized by their permeability and reflection coefficient (see also Weatherley, 1963). Moreover, using detailed pressure probe measurements, it was demonstrated by Steudle et al. (1987) and Steudle (1994) that matric potential gradients move water predominantly through the apoplast with a reflection coefficient close to zero, and that this is possible because the local endodermis is not fully developed with an imperfect Casparian band. Moreover, Steudle (1994) determined from experiments in maize roots that the symplastic root conductance was about 1–2 orders smaller than the apoplastic conductance. It was hypothesized that the osmotic component drives water mainly through the symplast or cell-to-cell pathway, with a reflection

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coefficient close to 1, across the plasmalemma or tonoplast. Hence, this composite transport model allows for a driving-force-dependent water flow pathway. For such a system of two parallel pathways, Steudle (1994) defined a composite reflection coefficient (σ = σ c), which is a function of the fractional contribution of each pathway (f) to the total effective root area, or fapo = Aapo/A and fsym = Asym / A, so that L apo L sym σsym + f apo σapo . (23a) σc = f sym L L In his formulation, the composite root conductance, L, is defined by L = f apo L apo + f sym L sym ,

(23b)

where the subscripts sym and apo refer to the symplastic and apoplastic component of conductance (L), reflection coefficient (σ ), and fractional area of flow ( f ). Accordingly, the composite reflection coefficient is a weighted mean of the reflection coefficients of the two parallel pathways that each contribute according to their individual conductance. After substitution of Eqs. (23a) and (23b) in Eq. (22b), the new formulation predicts that in the apoplastic pathway the effective osmotic driving force is low when osmotic gradients are applied to the root, despite its large hydraulic conductance, because σ apo is close to zero. A close inspection of the final attained composite expression after the stated substitutions will also show that there is no differentiation between apoplastic and symplastic pathways if the Casparian band is fully developed everywhere. In that case all flow must pass through the low conductive plasmalemma with conductance L. Hence, the composite approach assumes that differentiation in flow paths and variability in root water uptake within the rooting system is determined by the presence of undeveloped Casparian bands (Dumbroff and Persion, 1971) or their complete absence. The composite flow theory might also explain the dependency of the total hydraulic conductance on plant species, which is a function of the development of the endodermis and/or presence of suberization of cell walls and Casparian band (Steudle et al., 1987). The composite or three-compartment approach of Steudle (1994) may explain the nonlinear behavior of flow into roots, as inferred from apparent transpirationdependent root conductances (Fiscus, 1975; Passioura, 1984). Specifically, the dominance of the high-resistance symplastic component for low flow uptake conditions causes a relatively low conductance, whereas the osmotic component is obscured when flow is largely controlled by matric potential gradients, resulting in a high flow conductance. The apparent high flow resistance at low uptake rates is accordingly explained by the active transport of solutes into the root stele, thereby causing high-resistance osmotically induced water uptake (Dalton et al., 1975; Fiscus, 1975). After partitioning of the absorbed water into water used for expansive growth and transpiration, the analytical work of Fiscus et al. (1983) showed

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the influence of this partitioning on the nonlinear whole plant water transport behavior. Even more so, selective uptake of water by the roots for conditions when σ c is relatively large may accumulate nutrients at the root–soil interface or apoplast, causing reverse flow of water from the root into the soil by exudation. This is possibly counteracted by diffusion into the roots (Canny, 1990; Stirzaker and Passioura, 1996). However, as stated by Passioura (1984), this buildup of nutrients should increase with transpiration rate, thereby increasing the apparent root conductance. Using a three-compartment numerical model, the effect of changing the driving force on root resistance, causing nonlinear flow behavior and exudation of water by roots, was also demonstrated by Katou and Taura (1989). Another aspect deserving attention is the flow of water from the plant and roots into the surrounding soil, as may occur for dry topsoil conditions with deeper wet root zones or for wet-top and dry deeper soil moisture conditions (Smith et al., 1999). This phenomenon is defined as hydraulic lift (Caldwell and Richards, 1989) and can lead to the accumulation of xylem nutrients and xylem osmotic potential leading to root water pressure buildup (Steudle, 1994). The reverse flow mechanism was experimentally confirmed by Molz and Peterson (1976); however, they determined that the resistance of the reversed flow was much higher. In the general Ohm-type root water uptake formulation, the soil–root resistance is neglected, although it has been demonstrated from experimental work that soil and root shrinking and contact resistance can significantly increase total water flow resistance (Bristow et al., 1984; Herkelrath et al., 1977; Passioura, 1988). Thus, fitted water extraction parameters represent effective values that may not be appropriate for conditions outside the experimental range. In general, one must always use caution when applying this inverse type of approach where experimental data are fitted to a physical model. In addition to the radial root resistance, the longitudinal or axial root resistance in the xylem vessels may also contribute to the total root resistance. Various experimental studies (e.g., Frensch and Steudle, 1989) have shown that axial resistance is generally low. However, it is also intuitively clear that axial resistance might be important under dry soil conditions when cavitation in the xylem vessels can significantly reduce its conductance (Boyer, 1985; Tyree and Sperry, 1989), or when the number of xylem containing roots is limited (Passioura, 1988). Much research has been conducted to understand the relative contribution of soil and plant resistance to root water uptake. In general, it is found from both experimental and modeling studies that plant resistance is larger than soil resistance, at least until the soil’s hydraulic conductivity becomes limiting (Gardner and Ehlig, 1962; Landsberg and Fowkes, 1978; Reicosky and Ritchie, 1976; Rowse et al., 1978). A comprehensive review of root resistance including a discussion on the root–soil interface resistance, axial root resistance, and measurement techniques was presented by Moreshet et al. (1996). Although it is generally accepted that apoplastic and symplastic water moves through pores, the exact biophysical mechanisms of water transport in the root

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was not as evident until the discovery of aquaporins (Maurel, 1997; Tyerman et al., 1999). These water channel proteins within cell membranes facilitate the passive movement of water across membranes by both pressure and osmotic gradients in either direction, thereby increasing their conductance. Aquaporins may function like ion channels or ion carriers; however, water transport does not carry charge along with its movement. The presence of aquaporins may explain the symplastic transport of water across the endodermis, bypassing the Casparian band. Moreover, they can help explain the leakiness of semipermeable membranes, as indicated in Tyerman et al. (1999), and support the composite theory of water transport along parallel pathways (Steudle, 1994, 2000). Finally, it was speculated by Steudle (2000) that water channels may be more operative under conditions of water shortage, thereby allowing ABA signaling from the root to the shoots. However, the molecular basis of water channel selectivity and its regulatory functioning is yet unknown (Tyerman et al., 1999).

D. COMMENTARY Root water uptake has been described at both the microscopic and the macroscopic levels. The microscopic approach requires details about root geometry and soil heterogeneity that are generally not available. In the macroscopic approach, a sink term representing water extraction by plant roots is included in the dynamic water flow equation, allowing spatially and temporally variable uptake as controlled by soil moisture and plant demand. Water stress is determined by either computing effective leaf water potential (type I) or introducing a zero-to-one stress response function (type II). Within the macroscopic approach it is possible to differentiate between apoplastic and symplastic flow using the composite approach, implying pathway-dependent conductance and reflection coefficient values. Moreover, in this composite approach, a distinction is made between water uptake by matric and osmotic water potential gradients. Within the general framework of the SPAC, we might have to reconsider the significance of the plant–root resistance in relation to the atmospheric and soil resistances. Under wet-soil conditions, the largest hydraulic resistance occurs in the leaf with water vapor diffusion into the surrounding air controlled by atmospheric conditions. Under these conditions, plant transpiration is at its potential rate, independent of the flow resistance of the plant, root, or soil. Transpiration is demand controlled rather than supply controlled. As the soil is depleted of water, its flow resistance increases, as controlled by the decreasing unsaturated soil hydraulic conductivity and possibly by the decreasing root–soil contact. At a certain point the soil resistance becomes the dominant factor controlling plant transpiration. Consequently, the potential transpiration rate is decreased by a factor RED. In either case, the plant or root resistance was not considered. Likely, the root

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resistance may be important to determine the timing of the transition from potential to reduced plant transpiration, as it is applied in the type I approach of Nimah and Hanks (1973) or Campbell (1985). In these cases its value may be needed for the accurate modeling of crop growth.

VIII. NUTRIENT UPTAKE As was already established in the previous section, the routes along which both water and nutrients enter into the plant through the roots are likely to be different. Both water and nutrients enter the plant root freely through the apoplast, but their pathways and mechanisms of transport diverge when moving into the symplast. When addressing plant nutrient uptake, we must distinguish between the soil and the plant root transport mechanisms, so that we can determine whether nutrient uptake is either supply controlled or demand controlled. Demand-controlled nutrient uptake is regulated by plant parameters, whereas nutrient supply to the roots is determined by soil nutrient transport.

A. NUTRIENT TRANSPORT IN SOILS Excellent reviews on soil transport and uptake mechanisms of nutrients are presented in Nye and Tinker (1977) and Barber (1984). Nutrient movement toward the root surface occurs by the parallel transport of convective flow and diffusion, with the latter mechanism including dispersion. Nutrient transport by convection describes movement by the water as it moves through the soil. Hence, its magnitude is determined by the solution of Richards’ Eq. (9) and is a function of soil water potential gradients, the unsaturated hydraulic conductivity of the soil, and root water uptake. Larger water flow rates as, for example, those induced by irrigation will provide increased access of dissolved nutrients to the roots, whereas small water flow velocities tend to create depletion of nutrients near the roots. However, increasingly it is suggested that the dominant process of water flow in soils is by preferential flow. This general phenomenon causes accelerated transport of water and dissolved chemicals through the root zone, thereby bypassing large portions of the soil matrix and associated root surfaces. Dispersion and diffusion are caused by nutrient concentration differences near the roots, which may occur because of active nutrient uptake. Alternatively, preferential water uptake may cause accumulation of nutrients near the roots, resulting in their diffusing back into the surrounding soil. The dynamics of nutrient transport in soils can be described by the convective diffusion Eq. (11), including nutrient uptake from which nutrient concentrations can be computed at any time

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within any spatial location of the rooting system. Ion-specific nutrient diffusion is highly dependent on soil water content, with diffusion rates decreasing as the water content decreases. The transport equation includes a linear adsorption coefficient (k), characterizing the adsorption of the specific nutrient to the soil’s solid surface, thereby largely influencing the proportion of total ion content available for transport. Nutrient adsorption is generally described by the adsorption isotherm, characterizing the amount of nutrient adsorbed in equilibrium with the dissolved concentration, and is related to the buffering power or buffer coefficient of Nye (1966), Nye and Tinker (1977), and Claassen and Barber (1976). Although mass flow in general is not ion specific, differences in diffusion and adsorption coefficients between ions result in differences in the soil transport rate and root supply between nutrients. Since nutrient uptake rates can be ion specific, nutrient concentrations at the soil–root interface can be either accumulating or depleting. In addition to soil transport, nutrient uptake is controlled by the spatial distribution of roots, as influenced by its architecture, morphology, and presence of active sites of nutrient uptake, including root hairs. For nutrients that are immobile (e.g., phosphorus) or slowly mobile (ammonium), a root system must develop so that it has access to the nutrients, by increasing their exploration volume. Alternatively, the roots may increase their exploitation power for the specific nutrient by local adaptation of the rooting system, allowing for increased uptake efficiency of the nutrient. In the case of nonadsorbing nutrients, nutrient uptake is controlled by mass flow, as is the case of nitrate–nitrogen, which is hardly adsorbed by the soil. If the nutrient uptake rate or root absorbing power is supply controlled, mechanistic, analytical, and numerical solutions of nutrient transport that include the various transport mechanisms in soils can be used. Examples are presented in Olsen and Kemper (1968) and were reviewed by Jungk (1996). However, most, if not all of these solutions, have severe limitations regarding the portion of dynamics of flow and transport within the soil rooting system. For example, the proposed analytical model for nutrient uptake by growing roots given by Cushman (1979), which is based on Nye and Marriott (1969), assumes that moisture content is constant; and the Yanai (1994) nutrient uptake model assumes steady-state water flow with dynamic root growth. Under these commonly used nutrient supplylimiting conditions (as in Claassen and Barber, 1976), the soil supply is assumed to be equal to the nutrient uptake rate per unit root, which is illustrated schematically in Fig. 10 (from Jungk, 1996). An excellent review of the available mechanistic nutrient uptake models is presented in Silberbush (1996). When considering the many complications and soil–root–nutrient interactions, the predictive ability of these supply-limiting mechanistic nutrient uptake models has been remarkably good (Silberbush and Barber, 1984). This suggests that there is a reasonable level of understanding of the dominant physical and chemical processes of nutrient transport in soils.

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Figure 10 Schematic representation of the mechanistic description of soil-limiting nutrient uptake (adapted from Jungk, 1996).

B. NUTRIENT TRANSPORT IN THE ROOT The differences between transport processes in the roots become clear when considering that solution concentrations are generally much different from the xylem concentrations, with transpiration stream concentration factors (TSCF) larger than 1 (Russell, 1977). This indicates that nutrients have been moved against their concentration gradient. This type of transport is defined as an active, metabolically driven transport. An active transport is very much ion and plant species specific and can move ions in either direction. For example, plant species growing in seawater have Na and Ca concentrations in the cell sap that are much smaller than those in solution. Clearly, when the hydrophobic Casparian band is absent, as is the case for the young root cells near the root apex, water and nutrients can move through the cell walls toward the xylem by the apoplastic pathway. However, the differences in transport mechanisms become evident when approaching the endodermis if the impermeable Casparian band is present. Water and nutrient pathways converge again after both have reached the parenchyma cells of the xylem, moving simultaneously upward toward the plant leaves. However, specific nutrients can diffuse across most parts of the rooting system, independent of water-transporting pathways and age. This is possibly related to the presence of passage cells in the secondary suberized plasmalemma of the endodermis (Clarkson, 1996). When available at the root–soil interface, nutrients must diffuse through the secreted mucigel, the restricted unstirred water layer around the roots of the rhizophere, and across the epidermis to arrive into the free space or apoplast (Clarkson, 1996). Because of their large surface area, young root hairs provide for metabolically driven active uptake through proton pumping across their plasma membranes.

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When in the apoplast, pores are sufficiently large (3–4 nm) to permit unrestricted entry of water, hydrated inorganic ions, and small organic molecules. The net negative charge of the cell walls tends to exclude anions from the narrower pores of the apoplast, thereby likely reducing anion concentrations near the plasmalemma. This subsequently affects magnitudes of active uptake between anions and cations. Once accumulated in the inner spaces, active uptake mechanisms provide for transport across the plasmalemma and other protoplasmic membranes (Epstein, 1960). It is kinetically controlled by cell metabolism, the number of binding sites or nutrienttransporting carriers, the external nutrient concentration, and other environmental factors such as temperature and pH. Moreover, active transport is ion specific. In principle, nutrients can be adsorbed into the symplast by the peripheral cell layers of the cortex, or they can move across the plasmalemma in the endodermis, bypassing the Casparian band. An example of this was presented by Clarkson (1996), where Ca was transported into the cytoplasm by calcium channels and returned into the cell wall by calcium pumping (Fig. 11). Once past the endodermis and

Figure 11 Possible transport mechanism of calcium through the sympast and apoplast, bypassing the Casparian band. [Reprinted from Clarkson, D. T. (1996). Root structure and sites of ion uptake. In “Plants Roots: The Hidden Half,” p.439, by courtesy of Marcel Dekker, Inc.]

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in the symplast, the main pathway for the nutrients is through the cytoplasm and plasmodesmata of neighboring parenchyma cells in the stele, thereby providing a low resistance pathway for both water and dissolved nutrients toward the xylem. The provision of energy for active nutrient transport occurs via cell metabolism by the reduction of ATP. This reaction is an enzymatic reaction, so that the kinetics of active nutrient uptake is traditionally described by Michaelis and Menten enzyme kinetics (see Section V.B). Values for uptake parameters for a large group of crops are listed in Table 10.1 of Clarkson (1974). Generally, a distinction is made between mechanisms I and II, with the kinetic parameters of system I typical for carrier-type transport with the carrier having a high affinity for the moving nutrient (Epstein and Rains, 1966). The type II mechanism of uptake is operative in the higher concentration range and is much less ion specific and faster. These higher uptake rates would be typical for an ion-channel type of uptake and almost act as passive diffusion down an electrochemical potential gradient, since solution concentrations are usually larger than xylem concentrations. Instead of this dualcarrier system, Barber (1972) proposed the dual-isotherm hypothesis, suggesting that phosphate uptake in the low concentration range (mechanism I) was by active uptake, with the external nutrient concentration lower than the tissue concentration. In contrast, he hypothesized that phosphate uptake in the high concentration range of the external solution was passive by diffusion when the concentration gradient was reversed. Most recently, Nissen (1996) suggested that nutrient uptake was universally active across the whole external concentration range and proposed the multiphasic model with different MM parameters for each stage. Also Nissen (1996) proposed that uptake in the high concentration range was increasingly less active and operated more like a diffusion process. In summary, these results indicate that nutrient uptake is dominant by active uptake at low transpiration rates with the xylem nutrient concentration relatively high, whereas passive uptake is likely favored at high transpiration rates when the xylem nutrient concentration is low. Macroscopic models of nutrient uptake for a whole rooting system use a macroscopic sink term S′ (mass of nutrient taken up per unit bulk volume and time; M L−3 T−1), which when combined with the one-dimensional form of Eq. (11) predicts nutrient uptake for each soil layer, zi, for example, Si′ = RDFi Jsolute,i ,

(24)

where RDFi denotes the spatial distribution of active nutrient uptake area roots per unit bulk soil volume (L2 L−3) and Jsolute,i defines the nutrient uptake per unit root area (M L−2 T−1) for each soil layer. The total nutrient uptake is computed from integration of Eq. (24) over the whole rooting zone (e.g., Ran et al., 1994). For soil supply-limited conditions, the resulting total nutrient uptake may be compared with plant demand, with the resulting ratio defined as a nutrient stress factor with a value between zero and 1. This nutrient stress factor then characterizes the effect

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of plant nutrient stress on crop biomass production. The plant nutrient demand, for example, expressed in mass of nitrate required per unit mass dry matter produced, can be computed from the nutrient use efficiency using known values of the biomass produced per unit nutrient taken up (NUTE). This efficiency parameter can be computed from plant tissue concentrations between the various plant organs for unlimited nutrient supply conditions (van Noordwijk and van de Geijn, 1996). The total actual nutrient uptake must be distributed across the rooting zone according to the spatial distribution of nitrate supply rate and active root uptake area. In addition to the presence of roots, it has also been demonstrated that plant root growth responds to local variations in nutrient supply (Robinson, 1994). For example, as was experimentally determined by Drew and Saker (1975), localized proliferation of root growth can occur if part of the rooting zone is supplied with an enhanced supply of nitrate, with nonlimiting other soil environmental conditions. The local high concentration of nitrate was able to offset the limited nutrient supply available to other parts of the rooting system.

C. NITRATE UPTAKE In general, it has been found that NO3− uptake is independent of transpiration, except for conditions when the transpiration and, hence, water uptake rates were small. Under these conditions, nitrate levels in the xylem were high, caused by active nitrate uptake in xylem, inhibiting continued active root uptake of nitrate (Shaner and Boyer, 1976). Their results demonstrated that the the nitrate xylem concentration varied inversely with the transpiration rate, and that nitrate uptake is mostly a function of metabolic rate rather than transpiration rate. Active nitrate uptake is considered to occur via NO3−/H+ co-transport, or NO3−/H+ countertransport via carriers (Haynes, 1986), with the electrochemical gradient generated by proton pumping. Increased values of Km with increasing nitrogen application rates have been related to a corresponding increase in the number of active nitrate carriers in the plasmalemma (Oscarson et al., 1989), whereas Lee and Drew (1986) determined an increased uptake response as quantified by MM parameters as a result of increased nitrate application after nitrate starvation. In another study, Pinton et al. (1999) determined from experiments with young maize root seedlings that certain humic substances could increase root nitrate uptake by enhanced production of the H+-ATPase. Van den Honert and Hooymans (1955) experimentally showed a decrease in nitrate uptake by increasing the pH from 5 to 8, which can be explained by the requirement of electron neutrality in the root cells, resulted in an efflux of OH− into the rhizosphere in proportion to nitrate uptake (Haynes, 1986). In addition, it has been hypothesized that the nitrogen metabolism rate through its reduction to nitrite and ammonia might control uptake. That is, active uptake

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rate is controlled by nitrate efflux from the symplast through nitrate reduction (Deane-Drummond, 1984). Although not strictly proven, it is generally proposed that active uptake dominates in the low supply concentration range and under stress conditions, whereas passive uptake and diffusion become more important at higher soil solution concentrations. When considering the rhizosphere dynamics of water and nutrient uptake, many more mechanisms may have to be considered, including rhizosphere acidification and nitrogen mineralization. Acidification of the rhizosphere occurs because of a cation–anion imbalance of root uptake, resulting in the efflux or excretion of protons by the roots in the surrounding soil, for example, by root uptake of ammonium (Pierre and Banwart, 1973), with degree of acidification variations between plant species, fertilizer type, and contribution from nitrogen fixation and ash alkalinity (Jarvis and Robson, 1983; Tang et al., 1997).

D. COMMENTARY While reviewing the general literature on nutrient uptake by roots, it is indeed perplexing that uptake has been considered in so many different and occasionally opposing ways. Crop growth models (e.g., APSIM, CERES) generally assume little, or no, dynamics in nutrient uptake, considering the changes in the total available nutrient pool of the rooting zone without discriminating between active and passive uptake. In contrast, dynamic water flow and solute transport models (e.g., HYDRUS2D, RZWQM, SWAP) track spatial and temporal changes in water content, solute concentration, and water and solute fluxes. However, these model types regard nutrient uptake solely as a passive process, computing nutrient uptake fluxes from the product of water flux density and soil solution concentration within predefined small root zone volume elements with spatially distributed root densities. In this approach, the nutrient uptake rate is corrected by multiplying the passive nutrient uptake flux by a correction factor, to match predicted with observed total plant nutrient uptake. This correction factor can be both smaller or larger than 1, depending on the magnitude of active uptake, relative to total nutrient uptake. Finally, comprehensive plant nutrient uptake models (Barber, 1984; Nye and Tinker, 1977), although dynamic in root growth and nutrient uptake and transport through the soil, generally assume steady-state water flow with time-independent water content and water fluxes and describe nutrient uptake by active uptake only. Moreover, if passive water uptake through the apoplastic pathway is dominant, as is generally assumed, passive nutrient uptake must occur simultaneously, possibly in parallel with active transport, and most prominently for conditions of high transpiration rates.

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IX. COUPLED ROOT WATER AND NUTRIENT UPTAKE A. MECHANISTIC FORMULATIONS Among the first to study the influence of water uptake on plant nutrient uptake was Brouwer (1956). He found that ion uptake increased with transpiration rate when transpiration was low, but that the coupling disappeared at the higher transpiration rates. Using calcium chloride solutions, he concluded that about 70–80% of total ion uptake was by metabolism-dependent active uptake. A seminal contribution to a better understanding of the coupled uptake of water and nutrients to a single root for steady-state water flow conditions was presented by Dalton et al. (1975), showing that (i) solute flux is related to the water flux, even when active uptake is dominant; and (ii) a nonlinear relationship existed between transpiration rate (or water flux through the plant) and water pressure gradient. Applying the theory of irreversible thermodynamics to flow in plant roots (Dainty, 1963), Dalton et al. (1975) solved the coupled flow Eqs. (5) and (6), repeated in the following for convenience: Jwater = L (P − σ )

(25a)

Jsolute = ω + (1 − σ ) C1 Jwater + J ∗ .

(25b)

and

Using the van ‘t Hoff expression to relate concentration to osmotic pressure ( = RTC) for dilute solutions, the selectivity coefficient (Se) was defined as Se =

σ − RTJ∗ /(1 Jwater ) , 1 + ω RT/Jwater

(26)

where Se = 1, if σ = 1, J∗ = 0, and ω = 0 (perfect semipermeable membrane), and where Se = 0, if σ = 0 and J∗ = 0. Using subscripts 1 and 2 to denote nutrient and xylem concentrations, it was subsequently shown that C2 = (1 − Se)C1

and

Jsolute = (1 − Se)C1 Jwater .

(27)

Equation (27) also shows that the selectivity coefficient, Se, is negative, if the xylem concentration is larger than the solution concentration, leading to a correction factor larger than 1, if total nutrient uptake is estimated from the product of solution concentration and root water uptake (see Section VII.D). Using this twocompartment model it was demonstrated that the xylem concentration decreased and the solute uptake rate increased as the transpiration rate increased, even for a reflection coefficient as high as 0.975. Moreover, it was shown that there exists a

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nonlinear relationship between water flux and pressure gradient for nonzero active uptake. This relation approached linearity if transpiration rates (Jwater) were high. Using a similar approach, but assuming that nutrient uptake was by active uptake only and that the semipermeable membrane was perfect, Fiscus (1975) arrived at similar conclusions from   J∗ Jwater , (28) + RT C2 − P = L Jwater and their computation of the total resistance to water flow (slope of Jw in Fig. 10) equal to 1 RTJ∗ d(P) = + 2 . d(Jwater ) L J water

(29)

The general results are shown in Fig. 12, which was adapted from Fig. 2 of Fiscus (1975), with an external solution osmotic potential of 1 = 1.0. From either expression it is clear that the resistance to flow is nonlinear, becoming linear as Jwater increases, as caused by the changing driving forces rather than a changing flow resistance. Figure 10 also shows that there is nonzero uptake, even when P is zero. This flow is caused by the osmotic contribution, which decreases as transpiration rate increases because of the reduction of the osmotic component

Figure 12 Qualitative relationship between applied pressure, water uptake, and internal osmotic pressure (adapted from Fiscus, 1975).

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with decreasing xylem concentration. As is evident from the Eq. (27), linear relationships between water and solute uptake fluxes are expected if the active uptake term is zero. Moreover, Fiscus (1975) pointed out that the positive relation between water and solute flux is controlled by the relative magnitude of the diffusive and convective components of Eq. (25b). A similar two-compartment system was presented by Zimmerman and Steudle (1978); however, they split the osmotic terms into two components, whereby i and p are the osmotic pressure differences of the impermeable (i) and permeable (p) solutes for which σ < 1, or Jwater = L((P − i ) − σ  p ),

(30a)

so that the effective osmotic pressure effect on water flow is less than that of the total solute concentration (see also Dainty, 1963). The corresponding solute uptake flux equation then allows for diffusive transport for the permeable solute fraction only, or Jsolute = ω p + (1 − σ )C1 Jwater + J ∗ .

(30b)

Rather than a two-compartment model, a three-compartment model could possibly more realistically describe the cortex–symplast–stele pathway, with the compartments separated by two distinct membranes with different membrane transport properties. These membranes could be arranged in either series, or in parallel, from which composite membrane conductance and permeability values are determined. This was done by Celentano et al. (1988) and Zimmerman and Steudle (1978). The three-compartment concept was also suggested by Passioura (1988) to account for nonzero uptake at a zero pressure gradient, allowing for active solute uptake into the stele, thereby generating osmotically driven water flow. Also, Katou and Taura (1989) used the three-compartment approach by applying their double-canal model as a means to explain nonlinear water flow as caused by osmotic gradients.

B. OTHER CONSIDERATIONS A major limitation of current nutrient uptake models, when integrated with dynamic soil water flow models, is their general omission of the influence of soil salinity on nutrient uptake. Specifically, salinity may reduce plant growth by its osmotic effect and/or through toxic effects (Maas and Grattan, 1999; Pasternak, 1987) and reduce water permeability of root cell membranes (Mansour, 1997). Whereas the solute effect on root water uptake is considered to be a function of the total solute concentration or osmotic potential of the soil solution, uptake of specific nutrients will depend on the specific ion concentration in solution, but can be a function of total salinity as well. Moreover, solute interactions can occur in the soil through the soil’s cation-exchange capacity (CEC), making specific nutrient availability functionally dependent on other ions in solution. Mathematical models describing such interactions as between K+ and Na+ and Ca2+ and K+ were

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developed by Bouldin (1989) and Silberbush et al. (1993). Whereas Bouldin (1989) emphasized the importance of ion-exchange processes and the control of partial soil CO2 pressure on cation uptake, Silberbush et al. (1993) proposed a theoretical model for K+ uptake in saline soils, considering soil chemical ion-exchange and ion-specific uptake mechanisms, both active and passive, depending on ion concentrations while maintaining total ion charge neutrality. Another factor that requires attention is the apparent accumulation of salts at the root–soil interface, resulting in rhizophere salt concentrations much higher than those in the bulk soil. The salt accumulation or filtering is caused by salt transport toward the roots by mass flow through the soil. This is followed by preferential adsorption of specific nutrients by active uptake, thereby excluding most other salts at the root–soil interface or in the root apoplast. This salt buildup is expected to increase with transpiration rate, but is moderated by back diffusion into the soil or into the roots. Experimental evidence of salt accumulation was presented by Hamza and Aylmore (1992) from X-ray computed tomography and sodium microelectrode measurements around lupin and radish roots. The salinity buildup in the rhizosphere can lead to large osmotic pressure gradients across the roots, thereby effectively reducing root water uptake. We hypothesize that this rhizosphere effect may explain the failure of the additive stress concept. Specifically, it has been determined (Section VII.B.) that salinity stress cannot be predicted by simply adding the osmotic component to the soil water matric potential component in Eq. (21). To describe the salinity buildup and its effect on nutrient uptake, it is imperative that uptake be considered as a nutrient-specific process, and that the distinction is made between root uptake of the specific nutrient and total salinity. It is of further interest to note that nutrients and water may be taken up by different parts of the root system, so that salt accumulation may occur only at the active water uptake sites, while nutrients are taken up elsewhere within the rooting system (Stirzaker and Passioura, 1996).

C. MULTIDIMENSIONAL APPROACH Although many models (see Sections VI and VII) have been developed to simulate root growth and its interactions with soil water and nutrients, most of these models use simplified forms of the governing equations of soil water flow and solute transport; most notably they are limited to one spatial dimension and assume steady-state flow of water. Moreover, root uptake dynamics is usually related to measured distributions of root length density, ignoring uptake control by root surface area and root age. Consequently, these models will likely fail in predicting spatial variations and the dynamics of soil water–nutrient–plant growth interactions. An alternative is to characterize root water and nutrient uptake by a coupled dynamic approach, linking nutrient extraction to water uptake, controlled by the transient and locally variable supply of water and nutrients to the roots.

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As an example of this type of approach, van Noordwijk and van de Geijn (1996) specifically addressed the need for detailed root water and nutrient uptake models that include root growth and its response to changing local soil conditions such as water content, nutrient status, and mechanical impedance. They related water and nutrient stress to water use and biomass production. Local variations in water and nutrients occur naturally because of inherent large soil heterogeneity, but can also be imposed when using pressurized irrigation systems for fertigation purposes (Hagin and Lowengart, 1996). For such conditions, we must better understand the dynamics of changing patterns of nutrient and water availability and uptake. For example, roots can adjust their uptake patterns, thereby compensating for local stress conditions by enhanced or preferential uptake in other regions of the rooting zone with less stressful conditions. As a result, plants can temporarily deal with local stress and may be more effective in using water and nutrient resources under such conditions. Moreover, an improved understanding of these dynamic processes may provide guidelines in hot spot removal of specific toxic ions from soils as for bioremediation purposes (e.g., Ben-Asher, 1994). Preferential root uptake may minimize spatial variations in water and nutrients, thereby reducing drainage losses and chemical leaching below the rooting zone toward the groundwater. Mmolawa and Or (2000) pointed out that drip irrigation has an enormous potential to improve water and nutrient efficiency but that improper management may compound salinity problems and pollute groundwater resources. The main consideration in the management of pressurized irrigation systems is a priori knowledge of the interactions of irrigation method, soil type, crop root distribution, and uptake patterns and rates of water and nutrients or solutes. During water infiltration and redistribution, soil water content varies both spatially and temporarily, affecting soil solution concentration, composition, and spatial distribution by its control on mass flow and diffusion of solutes, soil-exchange processes, and chemical reactions. Excellent contributions to the significance of multidimensional treatment of water and nutrient transport in soils have been presented by Clothier and Sauer (1988),Green and Clothier (1995), and Clothier and Green (1997). The transport theory of Clothier and Sauer (1988) showed the prediction of ammonium and nitrate fronts, relative to the water fronts when using fertigation by a drip irrigation system. They also showed the negative consequences with prediction of a pH drop in the wetting zone under the emitter. The interaction of root water uptake and soil moisture and their spatial variations within the root zone of a kiwi fruit vine was demonstrated in Green and Clothier (1995). It was shown experimentally that following irrigation, preferential uptake of water shifted to the wetter parts of the soil within periods of days, away from the deeper drier parts of the root zone. Upon rewetting, plant roots recovered and showed enhanced activity by new root growth. A similar shifting of root water uptake patterns was observed by Andreu et al. (1997), using three-dimensional soil water content measurements around a dripirrigated almond tree. The derived three-dimensional water uptake for a 1-week period following irrigation is shown in Fig. 13. The water and chemical trapping

Figure 13 Three-dimensional root water uptake distribution during a 1-week drying period around an almond tree. [Reprinted from Agricultural Water Management 35, J. W. Andreu, J. W. Hopmans, and L. J. Schwanki, Spatial and temporal distribution of soil water balance for a drip-irrigated almond tree, 123–146, Copyright 1997, with permission from Elsevier Science.]

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Figure 14 Diagram linking spatial variations of active root water uptake sites to plant transpiration (Q). [Full credit (Kluwer Academic Publishers, Plant and Soil, Vol. 162 (No.8), p. 539, Roots: The big movers of water and chemical in soil, B. E. Clothier and S. R. Green, Fig, 2, Copyright 1997) is given to the publication in which the material was originally published, with kind permission from Kluwer Academic Publishers.]

mechanisms by roots were illustrated in Clothier and Green (1997), designating roots as “the big movers of water and chemical in soil.” In this uniquely wellwritten justification for root–soil research, their Fig. 2 is reproduced in our Fig. 14. It shows that the overall functioning of the plant and its transpiration are controlled by the complicated variations in root water uptake rates along supply-active root segments within the whole root system. The challenge then is to integrate local uptake variations to total plant uptake, which requires a better understanding of the link between root architecture and morphology and the functioning of root water and nutrient uptake. Based on the analysis so far we conclude that a multidimensional approach should be developed to allow for analysis of the influence of multidimensional distribution of root water and nutrient uptake sites within the root zone on crop growth. In part, nutrient and water supply rates to the roots are controlled by diffusion and mass flow induced by both spatial and temporal variations in soil water and nutrient status within the root zone. However, the extent and shape of the rooting system and their changes with time also play major roles in determining uptake patterns. Therefore, along with the characteristics of the soil nutrient supply,

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it is important to understand root growth dynamics and activity (van Noordwijk and de Willigen, 1991) as well as their spatial variability. This is caused by differences in root adsorption within the rooting zone as caused by root length or root area variations within and between soil layers, spatial variations in root–soil contact due to local soil moisture changes, and variations in root uptake as caused by root age and branching order. 1. Example of Multidimensional Approach It is only recently that multidimensional root water uptake models have been introduced (Coelho and Or, 1996; Vrugt, Hopmans et al., 2001). In the past few years, computing capabilities have significantly improved the effectiveness of multidimensional soil water flow models to study spatial and temporal patterns of root water uptake. A multidimensional approach in root water uptake is needed if uptake is varying in space thereby allowing a more accurate quantification of spatial variability of the soil water regime, including water flux densities below the rooting zone. As an example, Fig. 15 shows the predicted three-dimensional soil water content and root water uptake rates applying the three-dimensional root water uptake model in Eq. (17) of Section VII.A to measured time changes in water content for a sprinkler-irrigated almond tree (Koumanov et al., 1997), providing data similar to that presented in Fig. 13. Corresponding root water uptake parameters (as defined in Eq. (17)) were obtained from inverse modeling (Vrugt, van Wijk et al., 2001), minimizing the residuals of measured and simulated water content values around the almond tree. Simulated water content values were obtained using the transient threeˇ unek et al., 1995) from which drainage dimensional HYDRUS-3D model (Sim˚ fluxes below the rooting zone were computed. The effect of multidimensional root water uptake in an otherwise uniform soil can be illustrated by considering the resulting spatial variation in drainage flux, when calibrated to the almond tree soil moisture data of Andreu et al. (1997). For example, Fig. 16 shows a detailed two-dimensional contour plot of the spatial variability of cumulative flux density (mm) during the monitoring period of the data. Evidently, spatial variability of the drainage rate is large, with values increasing as corresponding root water uptake values decrease. Also, a variability analysis showed (Vrugt, van Wijk et al., 2001) that the spatial variation in drainage rate and root water uptake decreased significantly when simplifying multidimensional soil water flow and root water uptake to decreasing spatial dimensions. The increasing accurate spatial description of root water uptake and soil water flow with increasing spatial dimension is essential to improve model predictions of water fluxes and contaminant transport through the vadose zone. Moreover, the total chemical load to the groundwater will depend on local concentration and fluxes and their spatial variability. Specifically, the actual chemical load can be much larger than

Figure 15 Simulated three-dimensional volumetric water content and potential root water uptake distributions at three times during the monitoring period (Vrugt, van Wijk et al., 2001).

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Figure 16 Two-dimensional contour plot of spatial variability in cumulative drainage at a soil depth of 0.55 m during the monitoring period (Vrugt, van Wijk et al., 2001).

the average chemical load, when computed from average flux and concentration values using strictly one-dimensional simulations. For example, this whould be the case if the local regions in Fig. 14 with high drainage rates corresponded with high nutrient concentration values.

D. COMMENTARY In summary, it is clear that root transport is the result of various root membranes with distinct transport properties that can be nutrient and plant species dependent. Moreover, the formulation of an effective composite membrane allows one to capture the essential membrane characteristics that have been demonstrated under different experimental conditions. This coupled formulation allows the prediction of the experimentally measured decrease in xylem nutrient concentration with increased transpiration rate. It also considers the effect of active ion uptake on the hydraulic pressure gradient required for a given transpiration rate and accounts for

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the experimental evidence of the effects of nutrient concentration, active uptake, and transpiration rate on plant nutrient uptake. The nonlinear relationship between xylem matric potential and transpiration rate allows for temperature effects on active nutrient uptake (Baker et al., 1992). Root water uptake may lead to salt accumulation at the root–soil interface, resulting in rhizophere salt concentrations much higher than those in the bulk soil. This salt accumulation is caused by salt transport toward the roots by mass flow through the soil, followed by the preferential adsorption of specific nutrients by active uptake, thereby excluding most other salts at the root–soil interface or in the root apoplast. The salinity buildup can lead to large osmotic pressure gradients across the roots with corresponding high salinity stress, thereby effectively reducing root water uptake much more than originally believed. To describe such salinity buildup and its effect on water and nutrient uptake, a distinction must be made between nutrient-specific concentration and total salinity. The coupled transport approach of water and nutrients is certainly more complicated than the much simpler uncoupled and passive uptake approach, but is necessary if we intend to progress our understanding and ability to improve predictive capabilities of crop growth models. Although its extrapolation to the whole three-dimensional root zone scale is yet to be fully tested and confirmed, the coupling of water flow with nutrient transport is needed to simulate plant response to stresses in water, nutrients, and salinity, and to predict the space and time distribution of soil solute concentrations that are controlled by the contribution of active nutrient uptake to total uptake. At the same time, the results of these multidimensional studies can be used to develop “simpler” models that capture the effective uptake behavior more correctly for their application in crop management and decision models.

X. COMPREHENSIVE EXAMPLE What follows now are suggestions of the types of water and nutrient uptake modeling that are needed to help us better understand soil–plant interactions, especially under conditions of limited water and nutrient supply. The presented example can be found in two of our research papers (Clausnitzer and Hopmans, 1994; Somma et al., 1998) and is extensively described in Somma et al. (1997). The final result was a transient model for the simultaneous dynamic simulation of water and solute transport, root growth, and root water and nutrient uptake in three dimensions. The model includes formulation of interactions between plant growth and nutrient concentration, thus providing a tool for studying the dynamic relationships between changing soil–water, nutrient status, temperature, and root activity. The model presented offers the most comprehensive approach to date in

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Figure 17 Concept of comprehensive SPAC modeling. [Full credit (Kluwer Academic Publishers, Plant and Soil, Vol. 164, p. 309, Simultaneous modeling of transient three-dimensional root growth and soil water flow, V. Clausnitzer and J. W. Hopmans, Fig. 7, Copyright 1994, with kind permission from Kluwer Academic Publishers.]

the modeling of the dynamic relationship between root architecture and the soil domain. The essential components of the soil–crop model are presented in Fig. 17. The convection–dispersion equation used for the simulation of nutrient transport was considered in its comprehensive form, thus allowing a realistic description of solute fate in the soil domain. Soil–water uptake was computed as a function of matric and osmotic potential, whereas absorption of nutrients by the roots was calculated as a result of passive and active uptake mechanisms. Uptake and respiration activities varied along the root axis and among roots as a result of root age. Genotype-specific and environment-dependent root growth processes such as soil moisture, nutrient concentration, and soil temperature were included using empirical functions. The water flow and solute transport model used for the transient three-dimensional flow and transport was described in Section VI.B. Here, we are mainly concerned with the dynamic growth of roots and the resulting water and nutrient uptake distributions. In concept, the modeling approach followed the requirement that plant transpiration and assimilation are directly coupled through

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the water use efficiency term (see Section III). The root and soil parameters of root length, surface area, age, soil water content, temperature, and nutrient concentration are computed within a priori selected volume elements at any desired temporal resolution. Root water and nutrient uptake was computed at the same time and space scales and were dynamically controlled by root and soil parameters under both unstressed and stressed conditions (soil resistance, temperature, water, and nutrient stress). In order to solve the flow and transport Eqs. (9) and (11) in Section VI, the soil domain was discretisized into a rectangular grid of finite elements, each defined by eight nodes, with the element size defining the spatial resolution of the soil environment. Root growth, architecture, and age are simulated starting from a germinating seed that “grows” at user-defined time intervals with new segments added to the apex of each growing root. The flow and transport model was integrated with the root growth model (Fig. 18), allowing soil–plant–root interactions through water and nutrient uptake as a function of root properties (size and age) and soil properties (water content and nutrient concentration). Moreover, soil water

Figure 18 Discretization of soil domain. [Full credit (Kluwer Academic Publishers, Plant and Soil, Vol. 164, p. 300, Simultaneous modeling of transient three-dimensional root growth and soil water flow, V. Clausnitzer and J. W. Hopmans, Fig. 1, Copyright 1994, with kind permission from Kluwer Academic Publishers.]

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content, resistance, nutrient concentration, and temperature affected root growth and architecture directly. The model tracks each segment by recording its topological position within the root system and its spatial location within the model domain, as well as its age, mass, and surface area. Root growth was simulated as a function of mechanical soil strength, soil temperature, and solute concentration. Root axes were generated at user-defined times. Branching time and spacing were described by user-defined functions of root age and branching order. A root growth impedance factor was calculated for each growing root apex as a function of the local soil strength, nutrient and temperature conditions at each time t to reduce the length of the growing segment from its potential (unimpeded) value. The impedance factor varies linearly between zero and unity (unimpeded growth). Consequently, root growth rates were unaffected by nutrient availability, as long as the latter were maintained within an optimal concentration range. Because the optimal range and minimum and maximum concentrations are both genotype and nutrient specific, nutrientconcentration effects were simulated using a piecewise linear impedance function, varying linearly between zero (c ≤ cmin or cmax ≤ c, no growth) and unity (optimal concentration range). In a similar manner, other impedance functions were defined to simulate the effects of soil strength and soil temperature on local root growth. The sink term S(xj, ψm, ψo, t) in Eq. (9) describing root water uptake was computed at each time step from S(x j , ψm , ψo , t) = α (ψm , ψo , t) RDF(x, y, z, t) Tpot ,

(31)

where RDF(x, y, z, t) denotes the normalized nodal distribution of water uptake sites, as derived from root length or root area distribution or from the spatial distribution of root apices. When integrated over the root zone domain (RZ), its value is equal to 1, or R D F(x, y, z, t) =

β(x, y, z, t) . RZ β(x, y, z, t)

(32)

The localized form of the water-extraction function α (ψm, ψo, t), accounting for the local influence of soil water potential on root water uptake rate, included both the effects of soil water osmotic and matric potential on root water uptake, and uses van Genuchten (1987) α(x, y, z, t) =

[1 + (ψm /ψm,50

) p1 ]

1 , ∗ [1 + (ψ0 /ψ0,50 ) p2 ]

(33)

where ψm,50 and ψ 0,50 denote the soil water matric head and the osmotic head at which the uptake rate is reduced by 50%, respectively, and p1 and p2 are fitting parameters, here both assumed to be 3 (van Genuchten and Gupta, 1993).

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Alternatively, if osmotic effects do not need to be considered, a simplified form of Eq. (33) such as the stress response function of Fig. 8 can be used. The distribution of potential root water uptake sites within the soil domain was lumped into nodal values of a function β(x, y, z, t). At any time, the β value of a particular node increases as the number of active root segments and their respective lengths within its neighboring elements increase, and the distances from the element nodes to the centerpoints of those segments decrease. To account for root-age effects on water uptake, piecewise linear weighting functions were defined, which allow for variations in root water uptake for each branch segment depending on age and branching order. Depending on this weighting factor, whose values vary between unity and zero, each segment in the root system can fully contribute to uptake or is partially or totally excluded. Root nutrient uptake was lumped into nodal values of the sink term S′ (x, y, z, t) of Eq. (11), or, S ′ = f 1 S c + f 2 A,

(34)

where f1 and f2 are partitioning coefficients that distribute total nutrient uptake between passive and active uptake (terms S and A, respectively). Active nutrient uptake was considered to be described by the sum of MM uptake and a linear, diffusive uptake component term (Kochian and Lucas, 1982), or   Jmax c + χ Rd , (35) A= Km + c where Jmax (ML−2 T−1) is the maximum nutrient uptake rate, Km (ML−3) is the Michaelis–Menten constant, Rd (L2 L−3) is the root area as computed from the cumulative root segment surface area within each volumetric element, and χ (LT−1) is the first-order rate coefficient allowing for a linear/diffusive uptake component. Little is known about the relative magnitudes of the partitioning between passive and active uptake ( f1 and f2); however, it is expected that they are plant and ion specific, whereas their values might depend on nutrient availability and plant nutrient demand or deficit. For example, the active uptake contribution may be low if crop demand is low, whereas the contribution of active uptake may increase if either nutrient concentration in soil solution or transpiration rate is low. Therefore, instead of the Somma et al. (1998) approach, using a partitioning factor to quantify active nutrient uptake, we may choose to define potential active root nutrient uptake, Apot (M T−1), as  J ∗, (36) Apot = RZ

so that the local maximum active uptake (Amax,i) is computed from Amax,i = RDFAi Apot

(37)

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where RDFAi defines the spatial distribution function of active nutrient uptake sites (L−3) between elements within the root zone. It is defined as the RDF for water uptake in Eq. (32), but the relative spatial distribution of the nodal values may be different between water and nutrient uptake. Similarly, as was done for root water uptake, a reduced local active nutrient uptake (M L−3 T−1) can then be defined, or Ai = α(?)i Amax,i ,

(38)

where the reduction function α(?) may be a function of soil temperature, pH, or other local environmental condition, and is plant and ion specific. Finally, by integration over the whole root zone domain, the total actual active nutrient uptake (Aact) is obtained. An example of the possible influence of NO3–N concentration on root growth is presented in Fig. 19, which was taken from Somma et al. (1998), assuming passive nitrate uptake only. Both water and NO3–N were supplied through a dripper at the soil surface. Figures 19a and 19b show the simulated root system grown under nonlimiting and deficient NO3–N supply, respectively, at the end of the growth period (25 days). In both cases the soil water content was such that soil strength did not limit root growth. Root density is presented to the left of each root system, with the NO3–N concentration profile is shown on the right. In the example of Fig. 19a, NO3–N was applied continuously with the irrigation water throughout the growth period (nonlimiting N case). The predicted N concentration was higher in the upper part of the soil domain. Similarly, the predicted root density decreased with increasing depth. In Fig. 19b, NO3–N was applied only during a limited time interval at the beginning of the growth period (deficient N case), with the total amount applied equal to the nonlimiting case. Once N application stopped, the subsequent irrigations by the dripper moved the N plume downward, causing a greater root density in the central part of the root zone where the NO3–N content was higher. Indeed, the higher predicted root density in the center of the root system was fostered by the higher N amounts transported downward earlier, thus explaining the slight offset between root density and soil N. The downward movement of the N plume promoted root development at increasing depth, but resulted in a smaller average root density than for the nonlimiting N case. Complementary simulations that included water and nutrient uptake, for both the nonlimiting and N-limited case, also showed clearly the concomitant leaching of nitrate for the N-limited case. This was a result of the single early application of nitrate thereby limiting nutrient availability and potential nutrient uptake in the subsequent growing period. Although the multidimensional and mechanistic modeling approach appears attractive, it is limited by the need of much more additional soil and plant parameters. It is therefore that dedicated experiments, such as those presented in Andreu et al. (1997), are needed. Such data can then be effectively used to obtain soil and plant parameters for conceptual uptake models, as was done in Vrugt, van Wijk et al. (2001) by indirect estimation of three-dimensional

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root water uptake parameters using inverse modeling. It is suggested that a similar inverse approach may be used to improve the mechanistic description of nutrient uptake by roots, using dedicated facilities as the Wageningen Rhizolab (van de Geijn et al., 1994), or large fully instrumented lysimeters. With nitrates being the most problematic and widespread among potential groundwater contaminants (Canter, 1997; Keeney, 1989) in crop production, their uptake in relation to availability is especially important. The fate of NO3–N in cropping systems is determined by the interplay between nitrification, plant uptake, immobilization, denitrification, and mineralization, and is controlled by availability of soil microbes and soil organic carbon and their spatial distribution within the root zone. Most of the transformation processes of nitrogen compounds are fairly rapid and must be considered when nitrogen fate is studied. Since the degree of soil saturation and its variability partly govern these microbial processes, nitrate availability and leaching can be accurately predicted only if soil moisture processes are taken into consideration. However, the nitrogen cycle is a complex system, and simplifications in the experimental designs will be needed to accurately quantify nitrate uptake, its partitioning between passive and active uptake, and its spatial variability as determined by soil moisture, temperature, solution concentration, and root distribution.

XI. PROGNOSIS This final section is a summary, specifically addressing the major findings and recommendations. In general, we found that water and nutrient uptake in plant growth and soil water flow models is mostly described by empirical means, lacking a sound physiological or biophysical basis. This is unfortunate, as the exchange of water and nutrients is the unifying linkage between the plant root and surrounding soil environment. In part, the historical neglect of consideration of water and nutrient uptake processes below ground has led to a knowledge gap between plant responses to nutrient and water limitations and crop production, especially for conditions when soil water or nutrients are limiting.

Figure 19 Simulated three-dimensional root architecture with corresponding root density and nitrate concentration distribution for (a) nonlimiting and (b) deficient nitrogen supply conditions. [Full credit (Kluwer Academic Publishers, Plant and Soil, Vol. 202, No. 2, p. 286, Transient threedimensional modeling of soil water and solute transport with simultaneous root growth, root water and nutrient uptake, F. Somma, J. W. Hopmans, and V. Clausnitzer, Fig. 2, Copyright 1998, with kind permission from Kluwer Academic Publishers.]

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r The simplified approach for description of water and nutrient uptake was adequate for unstressed plant growth conditions and may work adequately for uniform soil conditions. However, it has become increasingly clear that a different approach is required if water and/or nutrient resources become limited in part of the rootzone. Increasingly, recommended irrigation water and soil management practices tactically allocate both water and fertilizers, thereby maximizing their application efficiency and minimizing fertilizer losses through leaching toward the groundwater. Likely, sustainable agriculture will be directed at minimizing yield losses and crop quality, while keeping environmental side effects at acceptable levels. This current state of sustainable agricultural systems justifies the increasing need for combining soil knowledge with plant expertise, in particular as related to root development and functioning. r We suggest that the effectiveness of these practices regarding their effects on crop production and groundwater quality requires a thorough understanding of plant–soil interactions and the plant’s regulatory functions in managing stresses. This includes knowledge of the crops responses to the availability of spatially distributed soil water and plant-available nutrients, using a multidimensional modeling approach. For crop growth modeling purposes, there must be a clear and intuitive understanding that plant transpiration and plant assimilation are physically connected by the concurrent diffusion of water vapor and carbon dioxide between the plant canopy and surrounding atmosphere through leaf stomata. Conceptually, assimilation and transpiration processes must be directly linked in both nonstressed and stressed soil environmental conditions. r This is achieved in crop growth modeling by introduction of a water use efficiency parameter, such as the transpiration coefficient (TRC), defined as the mass of water transpired per unit biomass produced. The driving force for water flow in both soils and plants is the total water potential gradient, as caused by matric, gravity, and hydrostatic pressure forces. However, in contrast to soils, the osmotic component must always be considered for flow through the roots, since water can move through cell membranes as a result of osmotic potential gradients. r For conditions of low water potentials, cavitation may cause embolisms in the xylem, thereby decreasing the axial conductance of water flow through plants. However, water can bypass cavitated parts of the xylem by lateral movement to other water-conducting vessels. Moreover, as in soils, water can move through water films along the xylem cell walls by surface forces, creating adsorption potential gradients.

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Water and nutrient transport in the root is mechanistically described by a set of coupled transport equations, describing simultaneous uptake of water and nutrient into the roots. In this approach, the soil and root system is simplified by a twocompartment system, separated by a single effective semipermeable membrane, separating the soil solution or apoplast from the cell solution or symplast. It has been shown in maize roots that water flow induced by matric potential gradients is mainly apoplastic, whereas a major contribution to osmotic-induced flow is the cell-to-cell or symplastic pathway. Measured hydraulic conductances between pathways can differ by 1 order of magnitude or more. Flow can be even more complex as water diffusion through membranes by osmotic gradients in one direction might cause matric potential and/or hydrostatic pressure potential gradients in the opposite direction. Within the xylem vessels and tracheids, water and solute flow is likely by advection only, so that osmotic gradients will not have to be considered. r The mechanistic description of water flow and nutrient transport through plant roots should consider this parallel transport through symplastic and apoplastic pathways. Also, discrimination between mechanisms of transport in the roots between water and nutrients may dictate differences between the spatial distribution of the main water and nutrient uptake sites within a rooting system, and their variation in time. Root water uptake has been described both at the microscopic and macroscopic levels. The microscopic approach requires details about root geometry and soil heterogeneity that is generally not available. In the macroscopic approach, a sink term, representing water extraction by plant roots is included in the dynamic water flow equation, allowing spatially and temporally variable uptake as controlled by soil moisture and plant demand. r In this macroscopic approach it is possible to differentiate between apoplastic and symplastic flow using the composite approach, implying pathwaydependent conductance and reflection coefficient values. Moreover, in this composite approach, a distinction is made between water uptake by matric and osmotic water potential gradients. The biophysical mechanisms of water transport in roots include the role of aquaporins. These water channel proteins within cell membranes facilitate the passive movement of water across membranes by both pressure and osmotic gradients, thereby increasing their hydraulic conductance. r The presence of aquaporins in roots may explain the symplastic transport of water across the endodermis and the leakiness of semipermeable membranes. Moreover, they support the composite theory of water transport along parallel pathways.

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Within the general framework of the SPAC, we might have to reconsider the significance of the plant-root resistance in relation to the atmospheric and soil resistances. Under wet-soil conditions, the largest hydraulic resistance occurs in the leaf with water vapor diffusion into the surrounding air controlled by atmospheric conditions. Under these conditions, plant transpiration is at its potential rate, independent of the flow resistance of the plant, root, or soil. Transpiration is demand-controlled, rather than supply-controlled. As the soil is depleted of water, its flow resistance increases, as controlled by the decreasing unsaturated soil hydraulic conductivity and possibly by the decreasing root–soil contact. r Hence, while under wet-soil conditions the maximum resistance for plant transpiration occurs in the leaf–atmosphere, the soil resistance becomes the dominant factor controlling plant transpiration under dry soil conditions. In either case, the plant or root resistance is not considered. Crop growth models generally assume little, or no, dynamics in nutrient uptake, considering changes in the total available nutrient pool of the rooting zone without discriminating between active and passive uptake. In contrast, dynamic water flow and solute transport track spatial and temporal changes in water content, solute concentration, and water and solute fluxes. However, these model types regard nutrient uptake solely as a passive process, computing nutrient uptake fluxes from the product of water flux density and soil solution concentration within predefined small root zone volume elements with spatially distributed root densities r While reviewing the general literature on nutrient uptake by roots, it is indeed perplexing that uptake has been considered in so many different and occasionally opposing ways. Nutrient uptake by the roots can occur by diffusion, advection, and active uptake. Prediction of the relative contribution of the advective component requires knowledge of the partitioning between apoplastic and symplastic water uptake components of root water uptake. Active nutrient uptake is driven by specific energy-driven carriers and ion channels and requires the creation of electrochemical gradients across membranes by metabolically driven ion pumps. r In the macroscopic approach, active nutrient uptake and transport within the roots is considered a kinetic process, equivalent to that characterized by Michaelis– Menten type of enzyme kinetics. Also nutrient transport in roots is the result of various root membranes with distinct transport properties that can be nutrient and plant species dependent. The formulation of a single effective composite membrane allows one to capture the essential membrane characteristics that have been demonstrated under different experimental conditions.

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r Specifically, the coupled formulation of water and nutrient uptake accounts for the experimental evidence of the effects of nutrient concentration, active uptake, and transpiration rate on plant nutrient uptake. The coupled transport approach of water and nutrients is certainly more complicated than the much simpler uncoupled and passive uptake approach, but is necessary if we intend to progress our understanding and ability to improve predictive capabilities of crop growth models. Root water uptake may lead to salt accumulation at the root–soil interface, resulting in rhizosphere salt concentrations much higher than those in the bulk soil. This salt accumulation is caused by salt transport toward the roots by mass flow through the soil, followed by preferential adsorption of specific nutrients by active uptake, thereby excluding most other salts at the root–soil interface or in the root apoplast. The salinity buildup can lead to large osmotic pressure gradients across the roots with corresponding high salinity stress, thereby effectively reducing root water uptake much more than originally believed. r To describe such salinity buildup and its effect on water and nutrient uptake, a distinction must be made between nutrient-specific concentration and total salinity. Knowledge of the concentration dependency of nutrient uptake is especially useful when optimizing N fertilization while minimizing environmental effects. Moreover, the intrinsic difference in uptake mechanisms between passive and active uptake leads to different nutrient concentrations in soil solution. r Moreover, a better understanding of ion-specific active root uptake is key to the development of effective strategies for the success of heavy metal removal in soils by phytoremediation. Although many models have been developed to simulate root growth and its interactions with soil water and nutrients, most of these are limited to one spatial dimension, and assume steady-state flow of water. Moreover, root uptake dynamics is usually related to measured distributions of root-length density, ignoring uptake control by root surface area and root age. r Consequently, these models will likely fail in predicting spatial variations and the dynamics of soil water–nutrient–plant growth interactions. An alternative is to characterize root water and nutrient uptake by a coupled dynamic approach, linking nutrient extraction to water uptake, controlled by the transient and locally variable supply of water and nutrients to the roots. r Although the extrapolation of the coupled uptake to the whole three-dimensional root zone scale is yet to be fully tested and confirmed, the coupling of water flow with nutrient transport is needed to simulate plant response to stresses in water, nutrients, and salinity and to predict the space and time distribution of soil solute

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concentrations that is controlled by the contribution of active nutrient uptake to total uptake. At the same time, the results of these multidimensional studies can be used to develop “simpler” models that capture the effective uptake behavior more correctly for their application in crop management and decision models. In part, nutrient and water supply rates to the roots are controlled by diffusion and mass flow induced by both spatial and temporal variations in soil water and nutrient status within the root zone. However, also the extent and shape of the rooting system and their changes with time play a major role in determining uptake patterns. Moreover, it has been shown that multidimensional root water uptake in an otherwise uniform soil can cause large drainage rate variability, with local values increasing as corresponding root water uptake values decrease. Variability analysis has demonstrated that the spatial variation in drainage rate and root water uptake decreased significantly when simplifying multidimensional soil water flow and root water uptake to decreasing spatial dimensions. r The increasing accurate spatial description of root water uptake and soil water flow with increasing spatial dimension is essential to improve model predictions of water and contaminant fluxes and total chemical load of plant nutrients to the groundwater. Although the multidimensional and mechanistic modeling approach appears attractive, it is limited by the need of much more additional soil and plant parameters. It is therefore that dedicated experiments are conducted. Such data can then be effectively used to obtain soil and plant parameters for mechanistic uptake models. r As was demonstrated, estimates of three-dimensional root water uptake parameters can successfully be obtained using inverse modeling. It is suggested that a similar approach may be used to improve the mechanistic description of nutrient uptake by roots, using dedicated facilities such as large fully instrumented lysimeters.

ACKNOWLEDGMENTS This research was made possible through a fellowship of the Land and Water Resources Research and Development Corporation (LWRRDC) and CSIRO Land and Water, Davies Laboratories in Townsville, Australia. We especially thank the reviewers, who collectively have given structure to the paper, thereby greatly improving its readability. They are Brent Clothier, Dani Or, and John Passioura. Also, ad hoc discussions on water potential concepts with Jacob Dane, Ken Kosugi, Dani Or, Ken Shackel, and Alex Globus helped to formulate Section II.B.

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van Keulen, H., and Seligman, N. G. (1987). “Simulation of Water Use, Nitrogen Nutrition and Growth of a Spring Wheat Crop.” Pudoc. Wageningen, The Netherlands. van Keulen, H., and van Laar, H. H. (1986). The relation between water use and crop production. In “Modeling of agricultural production: Weather, Soils and Crops” (H. van Keulen, and J. Wolf, Eds.), Pudoc. Wageningen, The Netherlands. van Noordwijk, M., and de Willigen, P. (1991). Root function in agricultural systems. In “Plant Roots and Their Environment” (B. L. McMichael, and H. Persson, Eds.), pp. 381–395. Elsevier Science, Oxford, UK. van Noordwijk, M., and van de Geijn, S. C. (1996). Root, shoot and soil parameters required for process-oriented models of crop growth limited by water or nutrients. Plant Soil 183, 1–25. Varney, G. T., and Canny, M. J. (1993). Rates of water uptake into the mature root system of maize plants. New Phytolog. 123, 775–786. Verburg, K, Ross, P. J., and Bristow, K. L. (1996). “SWIMv2.1 User Manual,” Divisional Report No. 130. Division of Soils, CSIRO, Australia. Viets, F. G. (1962). Fertilizers and the efficient use of water. Adv. Agron. 14, 223–264. Vogel, T. (1987). “SWM II—Numerical Model of Two-Dimensional Flow in a Variably Saturated Porous Medium,” Research Report No. 87. Wageningen Agricultural Univ., The Netherlands. Volkmar, K. M. (1996). Effects of biopores on the growth and N-uptake of wheat at three levels of soil moisture. Can. J. Soil Sci. 76, 453–458. Vrugt, J. A., Hopmans, J. W., and Simunek, J. (2001). Two dimensional root water uptake model for a sprinkler-irrigated almond tree. Soil Sci. Soc. Am. J. 65, 1027–1037. Vrugt, J. A., van Wijk, M. T., Hopmans, J. W., and Simunek, J. (2001). Comparison of one, two, and three-dimensional root water uptake functions for transient water flow modeling. Water Resour. Res. 37, 2457–2470. Walton, B. T., and Anderson, T. A. (1990). Microbial degradation of trichloroethylene in the rhizosphere: Potential application to biological remediation of waste sites. Appl. Environ. Biol. 56, 1012–1016. Wang, Y. P., and Leuning, R. (1998). A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy. I. Model description. Agric. For. Meteorol. 91, 89–111. Watt, M., McCully, M. E., and Canny, M. J. (1994). Formation and stabilization of rhizosheaths of Zea mays L. Plant Physiol. 106, 179–186. Weatherley, P. E. (1963). The pathway of water movement across the root cortex and leaf mesophyll of transpiring plants. In “The Water Relations of Plants” (A. J. Rutter, and F. H. Whitehead, Eds.), pp. 85–100. A symposium of the Britsh Ecological Society, London, 5–8 April, 1961. Blackwell Scientific, London. Wei, C., Steudel, E., and Tyree, M. T. (2000). Reply—Water ascent in plants. Trends Plant Sci. 5, 146–147. Whisler, F. D., Acock, B., Baker, D. N., Fye, R. E., Hodges, H. F., Lambert, J. R., Lemmon, H. E., McKinion, J. M., and Reddy, V. R. (1986). Adv. Agron. 40, 141–208. Whisler, F. D., Klute, A., and Millington, R. J. (1968). Analysis of steady state evapotranspiration from a soil column. Soil Sci. Soc. Am. Proc. 32, 167–174. Yanai, R. D. (1994). A steady-state model of nutrient uptake accounting for newly grown roots. Soil Sci. Soc. Am. J. 58, 1562–1571. Zimmerman, U., and Steudle, E. (1978). Physical aspects of water relations of plant cells. Adv. Bot. Res. 6, 45–117.

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MICRONUTRIENTS IN CROP PRODUCTION N. K. Fageria,1 V. C. Baligar,2 and R. B. Clark3 1

National Rice and Bean Research Center of EMBRAPA ˆ Santo Antonio de Goi´as-GO, 75375-000, Brazil 2 Alternate Crops and Systems Research Laboratory Beltsville Agricultural Research Center, USDA-ARS Beltsville, Maryland 20705 3 Appalachian Farming Systems Research Center, USDA-ARS Beaver, West Virginia 25813

I. Introduction II. Status in World Soils III. Soil Factors Affecting Availability A. pH B. Organic Matter C. Temperature, Moisture, and Light IV. Factors Associated with Supply and Acquisition A. Deficiencies and Toxicities B. Supply and Uptake C. Oxidation and Reduction D. Rhizosphere E. Interactions with Other Elements V. Improving Supply and Acquisition A. Soil Improvement B. Soil and Foliar Fertilization C. Plant Improvement D. Microbial Associations E. Improved Disease and Insect Resistance and Tolerance VI. Conclusion References

The essential micronutrients for field crops are B, Cu, Fe, Mn, Mo, and Zn. Other mineral nutrients at low concentrations considered essential to growth of some plants are Ni and Co. The incidence of micronutrient deficiencies in crops has increased markedly in recent years due to intensive cropping, loss of top soil by erosion, losses of micronutrients through leaching, liming of acid soils, decreased proportions of farmyard manure compared to chemical fertilizers, increased purity of chemical fertilizers, and use of marginal lands for crop production. Micronutrient deficiency problems are also aggravated by the high demand of modern crop cultivars. Increases in crop yields from application of micronutrients have been reported in many parts of the world. Factors such as pH, redox potential, biological 185 Advances in Agronomy, Volume 77 Copyright 2002, Elsevier Science (USA). All rights reserved. 0065-2113/02 $35.00

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FAGERIA et al. activity, SOM, cation-exchange capacity, and clay contents are important in determining the availability of micronutrients in soils. Plant factors such as root and root hair morphology (length, density, surface area), root-induced changes (secretion of H+, OH−, HCO3−), root exudation of organic acids (citric, malic, tartaric, oxalic, phenolic), sugars, and nonproteinogenic amino acids (phytosiderophores), secretion of enzymes (phosphatases), plant demand, plant species/cultivars, and microbial associations (enhanced CO2 production, rhizobia, mycorrhizae, rhizobacteria) have profound influences on plant ability to absorb and utilize micronutrients from soil. The objectives of this article are to report advances in research on the micronutrient availability and requirements for crops, in correcting deficiencies and toxicities in soils and plants, and in increasing the ability of plants to acquire needed amounts  C 2002 Elsevier Science (USA). of micronutrient elements.

I. INTRODUCTION Essential nutrients may be defined as those without which plants cannot complete their life cycle, irreplaceable by other elements, and directly involved in plant metabolism. Based on the quantity required, nutrients are divided into macro- and micronutrients. Macronutrients are required in large quantities by plants compared to micronutrients. Micronutrients have also been called minor or trace elements, indicating that their concentrations in plant tissues are minor or in trace amounts relative to the macronutrients (Mortvedt, 2000 ). The essential micronutrients for field crops are B, Cu, Fe, Mn, Mo, and Zn. The accumulation of these micronutrients by plants generally follows the order of Mn > Fe > Zn > B > Cu > Mo. This order may change among plant species and growth conditions (e.g., flooded rice). Other mineral nutrients at low concentrations considered essential to the growth of some plants are Ni and Co. Convincing evidence exists to indicate that Ni is essential for certain plants (Brown et al., 1987; Eskew et al., 1983). Even though Co stimulates growth of certain plants, it is not considered essential according to the Arnon and Stout (1939) definition of essentiality. Cobalt is essential for the fixation of N2 by bacteria, but is not required by higher plants (Ahmed and Evans, 1960; Marschner, 1995; Needham, 1983). Rhizobia and other N2-fixing microorganisms have absolute Co requirements whether growing inside or outside root nodules regardless of N source (N2 fixation or mineral N) (Marschner, 1995). Even so, Co is essential for animal nutrition as a component of vitamin B12 (Needham, 1983). Chlorine and Si have often been referred to as micronutrients, even though their concentrations in plant tissue are often equivalent to those of macronutrients. Chlorine will be considered in this article, but since recent reviews have appeared about Si (Epstein, 1994, 1999; Savant et al.,1997, 1999), this element will not be

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considered. Possibly, other essential micronutrients will be discovered in the future because of the recent advances in solution culture techniques and the availability of highly sensitive analytical instruments. Based on physicochemical properties, the essential plant micronutrients are metals except for B and Cl. Even though micronutrients are required in small quantities by field crops, their influence is as important as the macronutrients in crop production. Except for B and Cl, the micronutrients are commonly constituents of prosthetic groups that catalyze redox processes by electron transfer such as with the primary transition elements Fe and Mn and to some extent Cu and Mo. Micronutrients normally form enzyme–substrate complexes (Fe and Zn) and/or enhance enzyme reactions by influencing molecular configurations between enzymes and substrates (Zn) (R¨omheld and Marschner, 1991). Micronutrient deficiencies in crop plants are widespread because of (i) increased micronutrient demands from intensive cropping practices and adaptation of high yielding cultivars which may have higher micronutrient demand, (ii) enhanced production of crops on marginal soils that contain low levels of essential nutrients, (iii) increased use of high analysis fertilizers with low amounts of micronutrient contamination, (iv) decreased use of animal manures, composts, and crop residues; (v) use of soils that are inherently low in micronutrient reserves, and (vi) involvement of natural and anthropogenic factors that limit adequate plant availability and create element imbalances. Plant acquisition of micronutrients is affected by numerous soil, plant, microbial, and environmental factors. Parent material, minerals containing micronutrients, and soil formation processes influence micronutrient availability to plants. Solid-phase materials are important in determining solubility relationships of nutrients in soils (Lindsay, 1991). Available micronutrients in soil are derived from weathering of underlying parent materials, natural processes (e.g., gases from volcanic eruption, rain/snow, marine aerosols, continental dust, forest fires), and anthropogenic processes (industrial and automobile discharges, addition of fertilizers, lime, pesticides, manures, sewage sludges). Soil micronutrients exist in solid phases like primary minerals, secondary precipitates, and adsorbed on clay surfaces (Lindsay, 1991; Shuman, 1991). Soil adsorption reactions are important in determining the bioavailability of B, Cu, Mo, and Zn. Micronutrients in solid phases are not immediately available to plants. Only about 10% of micronutrients in soil are soluble and/or in exchangeable forms for plant acquisition (Lake et al., 1984). Fluctuating temperatures, moisture, and anthropogenic factors change micronutrient concentrations, forms, and distribution among various phases in soil. Soil pH, redox potential, and soil organic matter (SOM) profoundly affect the bioavailability of micronutrients (Stevenson, 1986; Tate, 1987). For most soils, soil SOM contains the largest pool of labile micronutrients in soil and influences micronutrient cycling, distribution of naturally occurring organic ligands, speciation and form (organic or inorganic) of elements in soil solution, and nature

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and stability of micronutrient complexes with humic and fulvic acids, especially with microbe conversion of SOM (Stevenson, 1991). The importance of SOM for influencing micronutrient retention follows the sequence of Cu > Zn > Mn (McGrath et al., 1988). Most metallic micronutrients in soil are complexed by both inorganic and organic ligands. Organic ligands act as carriers to plant roots (Lindsay, 1979), and Cu, Zn, and Mn form stable complexes, especially with carboxyl and phenolic groups, to make these minerals less available to plants (Stevenson, 1991). Organic substances like humic and fulvic acids formed in SOM degradation and transformation are also important in micronutrient cycling (Stevenson, 1986). Plant factors such as root and root hair morphology (length, density, surface area), root-induced changes (secretion of H+, OH−, HCO3−), root exudation of organic acids (citric, malic, tartaric, oxalic, phenolic), sugars, and nonproteinogenic amino acids (phytosiderophores), secretion of enzymes (phosphatases), plant demand, plant species/cultivars, and microbial associations (enhanced CO2 production, rhizobia, mycorrhizae, rhizobacteria) have profound influences on plant ability to absorb and utilize micronutrients from soil (Barber, 1995; Baligar and Fageria, 1997; Marschner, 1995). Macro- and micronutrients have long been recognized as being associated with changes in plant susceptibility or tolerance and resistance to diseases and pests (Engelhard, 1990; Graham and Webb, 1991). Even though research information on the mineral nutrition of plants has advanced significantly in recent years, most of the advances have been associated with macronutrients. Reasons for this may have been that micronutrients are required in such small amounts, and their deficiencies have not been systematically verified under field conditions. The objectives of this article are to report advances in research on the micronutrient availability and requirements for crops, in correcting deficiencies and toxicities in soils and plants, and in increasing the ability of plants to acquire needed amounts of micronutrient elements.

II. STATUS IN WORLD SOILS The amounts and distribution of micronutrients in soils are influenced by parent materials, levels and form of SOM, pH, Eh (oxidizing conditions), mineralogy, particle size distribution, soil horizon, soil age, soil formation processes, drainage, vegetation, and microbial, anthropogenic, and natural processes (Baligar et al., 1998; Stevenson, 1986; Tate, 1987). Micronutrient concentrations are generally higher in surface soil horizons (Ap) and decrease with soil depth. In spite of the relatively high total concentrations of micronutrients reported in soils on a global basis, micronutrient deficiencies have been frequently reported on many crops

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MICRONUTRIENTS IN CROP PRODUCTION

grown in various parts of the world (Cakmak, Sari et al., 1996; Fageria, 2000a; Galr˜ao, 1999; Graham et al., 1992; Grewal and Graham, 1999; Mandal and Mandal, 1990; Martens and Lindsay, 1990). It has been estimated that 3.95 billion ha of the world’s ice-free land area is subject to mineral stresses for plants, with 14% of this area being subject to potential micronutrient stresses (Gettier et al., 1985). The reasons for micronutrient deficiencies are that these elements have not usually been applied regularly to soils through fertilization. Furthermore, increased crop yields, loss of micronutrients through leaching, liming of soils, decreased use of manures compared to chemical fertilizers, and increased purity of chemical fertilizers without micronutrient additions have contributed to accelerated exhaustion of available micronutrients in soils. Hidden micronutrient deficiencies may be more widespread than has generally been suspected. Potential micronutrient deficiencies/toxicities associated with major soil groups (Table I), common soil

Table I Potential Micronutrient Deficiencies or Toxicities Associated with Major Soil Groupsa Element problem Soil order Andosols (Andepts) Ultisols Ultilsols/Alfisols Spodosols (Podsols) Oxisols Histosols Entisols (Psamments) Entisols (Fluvents) Mollisols (Aqu), Inceptisols, Entisols, etc. (poorly drained) Mollisols (Borolls) Mollisols (Ustolls) Mollisols (Aridis) (Udolls) Mollisols (Rendolls) (shallow) Vertisols Aridisols Alfisols/arid Entisols Alfisols/Utisols (Albic) (poorly drained) Alfisols/Aridisols/Mollisols (Natric) (high alkali) Aridisols (high salt)

Soil group Andosol Acrisol Nitosol Podsol Ferralsol Histosol Arensol Fluvisol

Deficiency B, Mo Most micronutrients Most micronutrients Mo Cu Cu, Fe, Mn, Zn

Toxicity

Fe, Mn Mn Fe, Mn

Fe, Mn

Gleysol Chernozem Kastanozem Phaeozem Rendzina Vertisol Xerosol Yermosol

Mn Fe, Mn, Zn Cu, Mn, Zn Fe, Mn, Zn Fe Fe, Zn Co, Fe, Zn

Planosol

Most micronutrients

Solenetz Solonchak

Cu, Fe, Mn, Zn

Fe, Mo

Mo

B, Cl

a Modified from Baligar and Fageria (1999); Clark (1982); Dudal (1976); S. W. Buol, North Carolina State University, Raleigh; H. Eswaren, USDA-NRCS, Washington, DC.

190

FAGERIA et al. Table II Major Soil Minerals Containing Micronutrientsa

Element B

Cl

Cu

Fe

Mn

Mo

Zn

Ni

Co

a

Type Borates (hydrous) Borates (anhydrous) Complex borosilicates Sylvite Kainite Langbeinite Carbonates Oxides Simple sulfides Complex sulfides Carbonates Oxides Sulfides Sulfates Carbonates Simple oxides Complex oxides Silicates Oxides Molybdates Sulfides Carbonates Sulfides Silicates Pentlandite Awaruite Cohenite Haxonite Nickel Cobaltite Skutterudite Erythrite

Mineral Borax—Na2B4O7·10H2O; Kernite—Na2B4O7·4H2O; Colemanite—Ca2B6O11·5H2O; Ulexite—NaCaB5O9·4H2O Ludwigite—Mg2FeBO5; Kotoite—Mg3(BO3)2 Tourmaline; Axinite KCl KCl; MgSO4·3H2O K2SO4·2MgSO4 Malachite—Cu2(OH)2CO3; Azurite—Cu3(OH)2(CO3)2 Cuprite—Cu2O; Tenorite—CuO Chalcocite—Cu2S; Covellite—CuS Chalcopyrite—CuFeS2; Bornite—Cu3FeS4; Digenite—Cu9S5; Enargite—Cu3AsS4; Tetrjedrote—Cu12Sb4S13 Siderite—FeCO3 Hematite—Fe2O3; Goethite—FeOOH; Magnetite—Fe3O4 Pyrite—FeS2; Pyrrhotite—Fe1–xS Jarosite—KFe3(OH)6(SO4)4 Rhodochrosite—MnCO3 Pyrolusite—MnO2; Hausmannite—Mn3O4; Manganite—MnOOH Braunite—(Mn, Si)2O3; Psilomelane—BaMg9O18·2H2O Rhodanate—MnSiO3 Ilsemanite—Mo3O8·8H2O Wulflenite—PbMoO4; Powellite—CaMoO4; Ferrimolybdite—Fe2(MoO4)·8H2O Molybdenite—MoS2 Smithsonite—ZnCO3 Sphalerite—ZnS Hemimorphite—Zn4(OH)2Si2O7·H2O (Fe, Ni)9S8 Ni3Fe (Fe,Ni)3C (Fe,Ni)23C6 Ni CoAsS CoAs2–3 Co3(AsO4)·8H2O

From Chesworth (1991), Dana and Dana (1997), Krauskopf (1972), and Mortvedt (2000)

minerals containing various micronutrient elements (Table II), and concentration ranges of micronutrients in soils and plants (Table III) have been provided to help define where micronutrient problems might occur. Concentrations of B in soils range from about 2 to 100 mg kg−1 (mean of 10 mg kg−1) and generally occurs as H3BO3/B(OH)3 (Goldberg, 1993). Soils

Table III Essential Micronutrients for Plant Growth, Principal Forms Absorbed, Concentration Ranges in Plants and Soils, and Persons Demonstrating Essentiality in Plants Concentration range in plantsa (mg kg−1)

Concentration in soilb,c (mg kg−1)

Element

Form absorbed

Critical

Sufficient

Toxic

B Cl Cu

H3BO3; BO3−; B4O72− Cl− Cu2+

illite > kaolinite (Goldberg, Forster et al., 1996). Hydrous ferric oxides or ferric oxide molybdate complexes and insoluble ferric molybdates may form in well-aerated soils so that Mo solubility and availability to plants are low (Welch et al., 1991). In poorly drained soils, formation of soluble ferrous molybdates or molybdites may lead to high Mo availability to plants. Plants grown in high Mo soils of the intermountain valleys of western United States have been reported to accumulate high Mo which has induced “molybdenosis” (Cu deficiency) in cattle (Welch et al., 1991). Zinc deficiency is a worldwide nutritional constraint for crop production. About 50% of soils used for cereal production in the world contain low levels of plantavailable Zn, which reduces not only grain yield but also nutritional grain quality (Graham and Welch, 1996). Total Zn concentrations in soils range from about 10 to 300 mg kg−1 (mean of 50 mg kg−1)(Lindsay, 1979). Zinc-deficient soils occur in both tropical and temperate regions, but are widespread in Mediterranean countries like Turkey (Cakmak et al., 1997), and in New South Wales, Queensland, and western and south Australia (Donald and Prescott, 1975; Sillanp¨aa¨ and Vlek, 1985). In China, Zn deficiency has been reported on plants grown in calcareous, desert, and paddy soils along the Yangtze river (Takkar and Walker, 1993). In Africa, Zn deficiency has been observed on plants grown in Alfisols and Ultisols (Cottenie et al., 1981) and in low Zn soils of Niger, Guinea, Ivory Coast, Sierra Leone, Sudan, and Zimbabwe, which has often been induced by lime additions to increase soil pH to near 7. In Asia, Zn deficiency is common for plants grown in arid and semiarid soils (Katyal and Vlek, 1985; Welch et al., 1991). Zinc deficiency in the United States has occurred mostly in plants grown in sandy, well-drained acid soils, and in soils formed from phosphate rock parent materials of the southeast. In the Cerrado soils of Brazil (Oxisols and Ultisols), Zn deficiency is widespread (Fageria, 2000b; Lopes and Cox, 1977).

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Serpentine (ultramafic) soils are usually high in Ni, Co, Fe, and Mg, but low in Ca. Nickel levels in soils are usually adequate to provide plant needs. No evidence of Ni deficiency for soil-grown plants has been reported (Dalton et al., 1985), but Ni toxicity has been of concern for plants grown in soils receiving industrial wastes (sewage sludges, by-products) (Marschner, 1995). Cobalt deficiency has been reported for ruminant animals grazing forages grown in soils low in Co such as New Zealand, south and western Australia, The Netherlands, and the United States (Michigan and northeastern states) (Miller et al., 1991). Cobalt is adsorbed on Mn oxides, and liming tends to reduce Co availability to plants.

III. SOIL FACTORS AFFECTING AVAILABILITY Many soil factors such as pH, SOM, temperature, and moisture affect the availability of micronutrients to crop plants. The effects of these factors vary considerably from one micronutrient to another as well as in their relative degree of effectiveness. The availability of micronutrients is largely controlled by the same soil factor(s) where good correlations exist between plant concentrations of two or more micronutrients. The relationships associated with each of the many soil factors are complicated, even though correlations between many factors can be explained with relatively high certainty. A good example of this is the highly significant negative correlation between Mo and Mn. The availability of both Mo and Mn is so strongly affected by soil pH that the other factors are of limited value. While Mn in plants decreases extensively with increasing soil pH, Mo increases, and deficiencies of both Mn and Mo are not expected or do not usually occur in the same soil. Manganese deficiency is often combined with excess Mo and vice versa (Sillanp¨aa¨ , 1982). Copper, Mn, and Zn were predominantly in organically bound forms in Spodosols of Florida, whereas these elements were organically bound and associated with Mn oxides and amorphous forms in Alfisols and Entisols (Zhang et al., 1997a). Available concentrations of Co, Cu, Ni, and Zn increased with increased amounts of clay (Lee et al., 1997).

A. pH Soil pH influences solubility, concentration in soil solution, ionic form, and mobility of micronutrients in soil, and consequently acquisition of these elements by plants (Fageria, Baligar and Edwards, 1990; Fageria, Baligar, and Jones, 1997). As a rule, the availability of B, Cu, Fe, Mn, and Zn usually decreases, and Mo increases as soil pH increases. These nutrients are usually adsorbed onto sesquioxide soil surfaces. Table IV summarizes important changes in micronutrient concentrations

196

FAGERIA et al. Table IV Influence of Soil pH on Micronutrient Concentrations in Soil and Plant Uptakea

Element B Cl

Influence on concentration/uptake Increasing soil pH favors adsorption of B. This element generally becomes less available to plants. Availability and uptake of B decrease dramatically at pH > 6.0. Chloride is bound tightly by most soils in mildly acid to neutral pH soils and becomes negligible to pH 7.0. Appreciable amounts can be adsorbed with increasing soil acidity, particularly by Oxisols and Ultisols, which are dominated by kaolinitic clay. Increasing soil pH generally increases Cl uptake by plants.

Cu

Solubility of Cu2+ is very soil pH dependent and decreases 100-fold for each unit increase in pH. Plant uptake also decreases.

Fe

Ferric (Fe3+) and ferrous (Fe2+) activities in soil solution decrease 1000-fold and 100-fold, respectively, for each unit increase in soil pH. In most oxidized soils, uptake of Fe by crop plants decreases with increasing soil pH.

Mn

The principal ionic Mn species in soil solution is Mn2+, and concentrations decrease 100-fold for each unit increase in soil pH. In extremely acid soils, Mn2+ solubility can be sufficiently high to induce toxicity problems in sensitive crop species.

Mo

Above soil pH 4.2, MoO42− is dominant. Concentration of this species increases with increasing soil pH and plant uptake also increases. Water-soluble Mo increases sixfold as pH increases from 4.7 to 7.5. Replacement of adsorbed Mo by OH− is responsible for increases in water-soluble Mo as soil pH increases. Zinc solubility is highly soil pH dependent and decreases 100-fold for each unit increase in pH, and uptake by plants decreases as a consequence.

Zn Ni

Ni2+ is relatively stable over wide ranges of soil pH and redox conditions. However, availability is usually higher in acidic than in alkaline soils. At pH 7 and higher, retention and precipitation increase. Increasing the pH of serpentine soils through liming from 4 to 7 reduced Ni in plant tissue.

Co

Solubility and availability of Co decrease with extreme soil pH. Presence of CaCO3, and high Fe, Mn, SOM, and moisture.

a

Adriano (1986), Fageria, Baligar, and Jones (1997), and Tisdale et al. (1985).

as influenced by soil pH and consequent acquisition by plants. Table V has been provided to show acquisition of Cu, Fe, Mn, and Zn by rice grown at various soil pH values. Boron is the only micronutrient to exist in solution as a nonionized molecule over soil pH ranges suitable for the growth of most plants. Increasing soil pH decreases B availability by increasing B adsorption onto clay and Al and Fe hydroxyl surfaces, especially at high soil pH (Keren and Bingham, 1985). The highest availability of B was at pH 5.5–7.5, and the availability decreased below or above this pH range. In other studies, B adsorption increased from pH 3 to 8 on kaolinite,

197

MICRONUTRIENTS IN CROP PRODUCTION Table V Influence of Soil pH on Acquisition of Cu, Fe, Mn, and Zn by Upland Rice Grown in an Oxisol of Brazila Soil pH

Cu (μg plant−1)

Fe (μg plant−1)

Mn (μg plant−1)

Zn (μg plant−1)

4.6 5.7 6.2 6.4 6.6 6.8

75 105 78 64 61 51

4540 1860 1980 1630 1660 1570

11,160 5,010 4,310 3,610 2,760 2,360

1090 300 242 262 163 142

r2

0.89b

0.97c

0.99c

0.98c

a

Fageria (2000c). P < 0.05. c P < 0.01.

b

montmorillonite, and two arid zone soils with peak adsorption at pH 8–10 and decreases from pH 10 to 12 (Goldberg, Forster, Lesch et al., 1996). Reduced B availability occurs from liming (called “B fixation”)(Fleming, 1980) as CaCO3 acts as an adsorption surface. As such, B deficiency may occur in plants grown in limed acid soils. Chloride is bound only lightly by most soil-exchange sites in acid to neutral soils and becomes negligible to pH 7.0. Chloride is easily leached from soil. Considerable soil Cu is specifically adsorbed as pH increases. For example, increasing the pH from 4 to 7 increased Cu adsorption (Cavallaro and McBride, 1984), and Cu was adsorbed on inorganic soil components and occluded by soil hydroxide and oxides (Martens and Westermann, 1991). Increases in soil pH above 6.0 induces hydrolysis of hydrated Cu which can lead to stronger Cu adsorption to clay minerals and OM. Readily soluble sources of Cu (exchangeable or sorbed) were highly toxic to citrus, and Cu concentrations decreased considerably with soil pH increases above 6.5 (Alva et al., 2000). Over-liming acid soils may also lead to Cu deficiency. SOM is a primary constituent for Cu adsorption and readily complexes Cu. As the pH increases, the sizes of organic colloids of high molecular weight diminish, thus increasing the surfaces where Cu can be adsorbed (Geering and Hodgson, 1969). The solubility of Fe decreases by ∼1000-fold for each unit increase of soil pH in the range of 4 to 9 compared to ∼100-fold decreases in the activity of Mn, Cu, and Zn (Lindsay, 1979). Iron exists in Fe0 (metallic), Fe2+ (ferrous), and Fe3+ (ferric) forms. Under acidic conditions, Fe0 readily oxidizes to Fe2+, and Fe2+ oxidizes to Fe3+ as the pH increases above 5. Ferric Fe (Fe3+) is reduced to Fe2+ and is readily

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available to plants in acidic soils, but precipitates in alkaline soils. Iron oxides are dominant in governing Fe solubility in soils. Minimum Fe solubility occurs between pH 7.5 and 8.5, which is the pH range of many calcareous soils (Lindsay, 1991). The increases in soil pH or Eh shift Fe from exchangeable organic forms to water-soluble and Fe oxide forms. The solubility of Fe in well-aerated soils is controlled by dissolution and precipitation of Fe3+ (Moraghan and Mascagni, 1991). Decreasing rhizosphere pH with added N (NH4–N) and/or K (KCl and/or K2SO4) was effective for increasing Fe uptake by plants (Barak and Chen, 1984). Applying FeSO4 with acid-forming fertilizer also increased Fe availability to plants (Moraghan and Mascagni, 1991). Soil pH affects solubility, adsorption, desorption, oxidation of Mn, and reduction of Mn oxides in soil. As the pH decreases, Mn is mobilized from various fractions and increases Mn soil solution concentrations and availability. Exchangeable Mn (plant available form) was high at low soil pH (7.0 (McBride, 1981). The breakdown of crop residues by soil microbes may release significant amounts of Cu, but natural complexing substances produced during OM decomposition could complex Cu into unavailable forms (Moraghan and Mascagni, 1991). Iron forms stable complexes with organic compounds that occur in both soil and solid phases (Barber, 1995). Organic acids such as citric, malic, oxalic, and phenolic that form soluble Fe complexes are released when OM decomposes. These Fe complexes enhance the mobility and bioavailability of Fe (Lindsay, 1991). Even though Fe complexes with OM, Fe bioavailability is affected more by soil pH than by OM content. Fulvic and humic ligands form the most stable complexes with Fe compared to the other transition metals, and the effectiveness of these complexes increases with increasing pH because of the enhanced dispersion and ionization of surface ligands (Stevenson, 1991). The formation of soluble Fe complexes by naturally occurring chelating ligands may also increase Fe solubility in soil. The addition of OM to soil leads to reducing conditions, and Fe is changed from less soluble to exchangeable and organic forms under these conditions (Shuman, 1991).The biological degradation of OM also releases electrons or other reducing agents to lower soil redox potentials and significantly increases the solubility of Fe (Lindsay, 1991). Increases in oxalate-extractable Fe (and Al) occurred after decomposition of OM, and Fe and Al oxide adsorption sites became coated or occluded with OM and were active only after removal of OM (Marzadori et al., 1991). In addition, Fe availability improved with the addition of OM in drained and water-logged soils (Tisdale et al., 1985). Soil OM content has been related to increased, decreased, and no effects on Mn availability to crop plants (Reisenauer, 1988). Within soil fractions, exchangeable and organically bound forms of Mn are important to plant availability. The higher accumulation of Mn in surface soil horizons has been reported to indicate that Mn may be closely associated with OM (McDaniel and Buol, 1991). Positive correlations between OM and Mn indicate that Mn has a strong affinity for OM, and higher Mn concentrations in surface soil compared to lower layers are likely due to higher OM in surface horizons (Zhang et al., 1997b). Sites of Mn retention have also been associated not only with OM but also with CaCO3 in pH 8 calcareous soils (Karimian and Gholamalizadeh Ahangar, 1998). Mn2+ especially forms complexes with fulvic and humic acids and humins, and with organic ligands such as organic, amino, and sugar acids, hydroxamates, phenolics, siderophores, and other organic compounds produced by various organisms in soil solution (Marschner, 1995; Stevenson, 1986; Tate, 1987). Hydrated Mn2+ forms complexes with carboxyl

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groups of OM, which helps explain observations that Mn binds weakly to OM compared to Fe, Cu, and Zn (Bloom, 1981). Manganese availability in soils high in OM may also decrease because of the formation of unavailable Mn complexes. Unavailable Mn complexes form in peaty or muck soils. Soil OM appears to have smaller effects on the availability of Mo than does soil pH. Molybdenum availability under acid soil conditions is primarily affected through the adsorption of MoO42− onto inorganic soil components. However, evidence exists that Mo is fixed by OM (Moraghan and Mascagni, 1991). In southeastern United States soils, adsorbed Mo increased with increases in SOM and Fe–oxide contents (Karimian and Cox, 1978). Organic matter may also potentially increase the mobilization of Mo under conditions of impeded drainage. Soil OM appears to affect the availability of Zn by (i) increasing the solubility of Zn through the formation of complexes with organic, amino, or fulvic acids; (ii) forming insoluble Zn–organic complexes that decrease the solubility of Zn; (iii) roots releasing exudates and ligands that may complex Zn in the rhizosphere; and (iv) microbes immobilizing and mineralizing decreased or increased soilavailable Zn (Lindsay, 1972). Increased levels of OM increase exchangeable and organic fractions of Zn and decrease oxide fractions of Zn in soil because of reducing conditions to enhance Zn bioavailability. A widespread Zn deficiency in lowland rice in Asia was related to high soil pH, low available soil Zn, and OM content (Yoshida et al., 1973). The decomposition of OM releases OH−, HCO3−, and organic ligands that tend to immobilize Zn in the root rhizosphere (Yoon et al., 1975). In practice, fine-textured soils and soils with horizons containing high levels of OM had higher Zn sorption capacities than sandy-textured, low OM soils (Stahl and James, 1991). Adsorption of organic anions may also increase negative charges on particle surfaces to enhance Zn adsorption. On the other hand, organic ligands in solution may decrease Zn adsorption by competing with surface sites for Zn. Zinc adsorption onto clays and hydrous oxides may be increased or decreased with organic ligands (Chairidchai and Ritchie, 1990). High SOM levels in Ni-rich soils can solubilize Ni2+ as organic complexes at high soil pH (McBride, 1994). At high soil pH, Co complexes with SOM, and Co bioavailability increases when it is complexed with SOM (McBride, 1994).

C. TEMPERATURE, MOISTURE, AND LIGHT Temperature and moisture are important factors affecting the availability of micronutrients in soils (Cooper, 1973; Fageria, Baligar, and Jones, 1997). The availability of most micronutrients tends to decrease at low temperatures and moisture contents because of reduced root activity and low rates of dissolution and diffusion of nutrients. In soils with low moisture, colloidal particles may become immobilized as a result of micronutrient adsorption on surfaces of soil particles (Harmsen and Vlek, 1985). Light affects mostly metabolic processes of plants.

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Boron and Cl uptake are influenced more than any other mineral for plants grown under hot and dry conditions. For example, increased temperatures in nutrient solutions enhanced B concentrations in shoots of plants by increasing B uptake with increased transpiration (Moraghan and Mascagni, 1991; Vlamis and Williams, 1970). On the other hand, turnip was B deficient when grown in soil with 22

0.12–2.5 0.1–10

2.5–5 4–8 1–2

0.8 3 1.1 0.1 0.26 0.53 0.37 4.8 4.5 7 1.4 3 3.9

0.1–0.3

0.25–2 0.5–3 2–10

0.8 1.1 5 0.86 1

a

From Cox (1987), Martens and Lindsay (1990), Sims (2000), and Sims and Johnson (1991).

toxicity (Parker et al., 1983). Crops that are grown in salt-affected soils and receive irrigation (sprinkler) often have enhanced symptoms of Cl toxicity. Copper deficiency is often observed on plants grown in soils inherently low in Cu (coarse-textured and calcareous soils) and in soils high in OM, where Cu is readily complexed (Alloway and Tills, 1984). Higher than normal Cu supplies usually inhibit root growth more than shoot growth (Lexmond and Vorm, 1981). The use of Cu-containing fungicides and antihelminthic compounds (insecticides) in agriculture has resulted in Cu toxicity in some plants, but naturally occurring Cu toxicity is relatively uncommon (Welch et al., 1991).

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Table VIII Micronutrient Deficiency Symptoms in Crop Plantsa Element B Cl Cu Fe Mn

Mo

Zn

Ni Co

Symptoms Death of growing points of shoot and root. Failure of flower buds to develop. Blackening and death of tissues, especially inner tissue of brassica plants. Reduced leaf size. Yellowing, bronzing and necrosis on leaves. Roots reduced in growth and without hairs. Yellowing of young leaves. Rolling and dieback of leaf tips. Leaves are small. Tillering is retarded. Growth is stunted. Interveinal yellowing of younger leaves with distinct green veins. Entire leaves become dark yellow or white with severe deficiency, and leaf borders turn brown and die. Interveinal tissue becomes light green with veins and surrounding tissue remaining green on dicots (Christmas tree design) and long interveinal leaf streaks on cereals. Develop necrosis in advanced stages. Mottled pale appearance in young leaves. Bleaching and withering of leaves and sometimes tip death. Legumes suffering Mo deficiency have pale green to yellowish leaves. Growth stunted. Seed production is poor. Deep yellowing of whorl leaves (cereals). Dwarfing (rosette) and yellowing of growing points of leaves and roots (dicots). Rusting in strip on older leaves with yellowing in mature leaves. Leaf size reduced. Main vein of leaf or vascular bundle tissue becomes silver-white, and marked stripes appear in middle of leaf. Chlorosis of newest leaves. Ultimately leads to necrosis of meristems. Reduced germination and seedling vigor (low seed viability). Diffuse yellowing in leaves. Young shoots and older leaves have severe localized marginal scorching.

a From Baligar et al. (1998), Bennett (1993), Bould et al. (1983), Brown et al. (1987), Clark and Baligar (2000), and Fageria, Baligar, and Jones (1997).

Iron deficiency is a worldwide problem and occurs in numerous crops (Korcak, 1987; Marschner, 1995; Vose, 1982). Iron deficiency occurs not because of Fe scarcity in soil but because of various soil and plant factors that affect Fe availability to inhibit its absorption or impair its metabolic use (Marschner, 1995; Welch et al., 1991). In the majority of soils, the total concentration of soluble Fe in the rhizosphere is nearly always far below the level required for adequate plant growth (Marschner, 1995). Induced Fe-deficient chlorosis is widespread and is a major concern for plants growing on calcareous or alkaline soils due to their high pH and low Fe (Korcak, 1987). Bicarbonate, nitrate, and environmental factors influence the occurrence of Fe-deficient chlorosis in plants, which occurs in young leaves due to inhibited chloroplast chlorophyll syntheses as a consequence of the low Fe nutrition status of plants (Lucena, 2000). Plant species that commonly become Fe deficient are apple, peach, citrus, grape, peanut, soybean, sorghum, and upland

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FAGERIA et al. Table IX General Description of Mineral Toxicity Symptoms on Plantsa

Element B

Cl Cu

Fe

Symptoms High B may induce some interveinal necrosis, and severe cases turn leaf margins straw color (dead) with distinct boundaries between dead and green tissue. Roots appear relatively normal. High Cl results in burning leaf tips or margins, reduced leaf size, sometimes yellowing, resembles K deficiency, and root tips die. High Cu may induce Fe deficiency (chlorosis). Light colored leaves with red steaks along margins. Plants become stunted with reduced branching, and roots are often short or barbed (like wire). Laterals may be dense and compact. Excess Fe is a common problem for plants grown in flooded acidic soil. May induce P, K, and Zn deficiencies. Bronze or blackish-straw colored leaves extending from margins to midrib. Roots may be dark red and slimy.

Mn

Excess Mn may cause leaves to be dark green with extensive reddish-purple specks before turning bronze yellow, especially interveinal tissue. Uneven distribution of chlorophyll. Margins and leaf tips turn brown and die. Sometimes Fe deficiency appears, and main roots become stunted with increased number and density of laterals.

Mo

Excess Mo induces symptoms similar to P deficiency (red bands along leaf margins), and roots often have no abnormal symptoms. Excess Zn may enhance Fe deficiency. Leaves become light colored with uniform necrotic lesions in interveinal tissue, sometimes damping off near tips. Roots may be dense or compact and may resemble bared wire. High Ni results in white interveinal banding alternating with green semichlorotic areas with irregular oblique streaking, dark green veins, longitudinal white stripes, and brown patches. Yellowing of leaves may resemble Fe or Mn deficiency. Distortion of young leaflets (peg-like or hook type).

Zn

Ni

Co

Pale green leaves with pale longitudinal stripes.

a From Baligar et al. (1998); Bould et al. (1983); Clark and Baligar (2000), and Fageria, Baligar, and Jones (1997).

rice. Iron toxicity (bronzing) can be a serious disorder for the production of crops in water-logged soils. For wetland rice, Fe toxicity is the second most severe yield-limiting mineral disorder after P deficiency. Audebert and Sahrawat (2000) reported that the application of P, K, and Zn with N to an iron-toxic lowland soil in the Ivory Coast reduced Fe toxicity symptoms and increased lowland rice yields. Manganese toxicity is probably more of a problem than Mn deficiency throughout the world. Manganese deficiency occurs on plants grown in organic, alkaline, calcareous, poorly drained, slightly acid soils, and coarse-textured sandy soils (Martens and Westermann, 1991). Over-liming of acid soils may induce Mn deficiency. Manganese toxicity is a major factor for reduced production of crops grown in acid soils, as is Al toxicity. Plant ability to tolerate Mn toxicity is affected by plant genotype, concentration of Si in soils, temperature, light intensity,

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and physiological age of leaves (Horst, 1988). The conditions that lead to the buildup of high levels of Mn in soil solution are high levels of total Mn, soil pH below 5.5, high soluble Mn relative to Ca, reduction of Mn under low oxygen caused by poor drainage, soil compaction, and excess water from irrigation or rainfall (Reisenauer, 1988). Molybdenum deficiency is widespread in legumes, maize, and cauliflower grown in acid mineral soils containing high amounts of iron oxides and hydroxides. Copper/Mo ratios 5 to 10 mg kg−1 dry wt in forage tissue have induced toxicity in ruminants (“molybdenosis or teart”) (Marschner, 1995). Such disorders of Cu occur in forage grown in poorly drained and high organic soils. Zinc deficiency in plants is widespread throughout the world (Bould et al., 1983; Viets, 1966). Increasing pH due to liming reduces plant available Zn. High clay and P supply and low soil temperatures are also known to promote Zn deficiency (Marschner, 1995). Lowland rice grown in limed or calcareous soils often exhibit Zn deficiency (Ponnamperuma, 1972). Chaney (1993) indicated that after “natural” phytotoxicity from Al or Mn in strongly acid soils, Zn phytotoxicity is the next most extensive micronutrient phytotoxicity compared to Cu, Ni, Co, Cd, or other trace element toxicities. As soil pH decreases, Zn solubility and uptake increase, and the potential for Zn phytotoxicity increases. At comparable soil pH and total Zn contents, Zn phytotoxicity is more severe on plants grown in light-textured than in heavy-textured soils. This is mainly because of the differences in the specific Zn adsorption capacities of soil. Continued applications of Zn to alkaline sandy soils low in OM and clay tend to develop Zn toxicity in plants, even though the occurrence of Zn toxicity is relatively rare under field conditions (Rattan and Shukla, 1984). Liming was effective in overcoming Zn toxicity on peanut (Keisling et al., 1977). Even though no clear evidence exists for Ni deficiency in plants, Ni toxicity is of concern for plants grown in soil receiving sewage sludge and industrial by-products. Nickel as well as Co toxicity may also be found on plants grown in soils formed from serpentinite or other ultrabasic rocks (McBride, 1994). Cobalt deficiency may occur on plants grown in highly leached sandy soils derived from acid igneous rocks and in calcareous or peaty soils (Martens and Westermann, 1991) and in coarse-textured, acid-leaching alkaline or calcareous soils and humic rich soils (McBride, 1994).

B. SUPPLY AND UPTAKE Micronutrient uptake by roots depends on nutrient concentrations at root surfaces, root absorption capacity, and plant demand. Micronutrient acquisition includes dynamic processes in which mineral nutrients must be continuously

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FAGERIA et al. Table X Estimated Proportions of Micronutrients Potentially Supplied by Mass Flow, Diffusion, and Root Interception to Maize Roots Grown in a Fertile Alfisola Estimated percentage of total uptake Micronutrient

Mass flow

Diffusion

Root interception

B Cu Fe Mn Zn

1000 219 66 22 230

29 0 21 35 0

29 6 13 43 43

a

From Barber (1966).

replenished in soil solution from the soil solid phase and transported to roots as uptake proceeds. Mineral nutrient transport to roots, absorption by roots, and translocation from roots to shoots occur simultaneously, which means that rate changes of one process will ultimately influence other processes involved in uptake (Fageria, Baligar, and Jones, 1997). In soil systems, mineral nutrients move to plant roots by mass flow, diffusion, and root interception (Barber, 1995). Mass flow is the passive transport of minerals to roots as water moves through soil and occurs when solutes are transported to roots with convective flow of water (soil solution) from soil. The amount of minerals supplied to roots depends on the rates of water flow to roots and the average mineral content of the water. The amounts of mineral nutrients reaching roots by this process depend on the concentrations of nutrients in soil solution and the rates of water transport to and into roots. Diffusion and mass flow could meet plant micronutrient requirements for B, Cu, and Zn, provided sufficient nutrient concentrations are in soil solution. Table X provides estimates of nutrients supplied to maize roots by mass flow, diffusion, and root interception in a fertile Alfisol. Diffusion is defined as the movement of nutrients from regions of high concentration to regions of low concentration. When the nutrient supply to root surfaces is not sufficient to satisfy plant demands by mass flow and root interception, concentration gradients develop and nutrients move by diffusion (Barber, 1966, 1995). Considerable quantities of B, Mn, and Fe move by diffusion. Root interception is another process by which roots obtain minerals. As roots grow in soil, they push soil particles aside and root surfaces come in direct contact with mineral nutrients. Mineral interception by roots depends on soil volume occupied by roots, root morphology, and concentrations of minerals in the soil volume occupied by roots. On average, soil volume occupied by roots of crop

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plants is about 0.7 to 0.9% (Fageria, Baligar, and Wright, 1997). Root interception can provide significant amounts of plant requirements for B, Zn, and Mn. The interaction of soil and plant factors influences the processes of mineral flux in soil. The major soil factors that influence mineral flux are concentrations of mineral ions on exchange sites and in solution, soil buffer capacity, diffusion coefficient, type of clay, soil structure, nature of OM, water content, and temperature. Soil capacity to adsorb mineral nutrients is important in mineral transport to roots. If soil ion-exchange capacity is low, ions are usually freely mobile in solution. In addition, diffusion coefficients of Cu, Mn, and Zn decrease ∼10-fold for various clays in the order of kaolinite > illite > montmorillonite > vermiculite (Lindsay, 1979). The major plant factors that contribute to mineral fluxes are root and root hair density and length, plant demand for mineral nutrients and water, and plant modification of the rhizosphere (Fageria and Baligar, 1993, 1997a,b). The amount of minerals in soil, concentration in soil solution, and transport to roots are key factors influencing mineral uptake by roots. Since B, Mn, and Fe move to plant roots primarily by diffusion, soil properties that affect diffusion govern micronutrient availability to plant roots. Mineral nutrient supply, whether at adequate or toxic levels, can strongly influence root growth, morphology, and distribution of root systems in soil (Baligar et al., 1998; Barber, 1995; Marschner 1995). As most micronutrients may be supplied by diffusion, the size of roots has profound effects on plant ability to acquire required mineral concentrations. Toxic levels of Al, Mn, and H in acid soils and the presence of H2CO3, Na2CO3, B, Na, Mo, SO4–S, and Cl in alkaline or high-salt soils can directly reduce root growth and inhibit ability of roots to explore large soil volumes for minerals and water. Soil weathering, anthropogenic activities, addition of agricultural amendments (fertilizers, organic manures, lime, slags, sewage sludge), and pesticides have contributed to increased levels of essential micronutrients and nonessential trace elements in soil (Baligar et al., 1998). The mobility and bioavailability of these minerals in soil are influenced by pH, temperature, redox potential, cation exchange, anion ligand formation, and composition and quantity in soil solution (Alloway, 1995a,b; Baligar et al., 1998). At any given pH, the relative mobility of some micronutrients in acid soil decreases in the order of B > Ni > Zn > Mn > Cu. Mineral nutrient deficiencies and excesses affect growth (dry mass, root : shoot ratio) and morphology (length, thickness, surface area, density) of roots and root hairs (Baligar et al., 1998). Nutrient deficiencies usually lead to finer roots and trace element toxicities stimulate initiation and growth of second- and third-order lateral roots, while tap roots and first-order laterals (seminal/basal) become suppressed (Hagemeyer and Breckle, 1996). Additional information about toxicity and constraints of micronutrients and trace elements on root growth is available (Baligar et al., 1998). Changes in root growth and morphology affect plant ability to absorb minerals from soil to meet plant demands. Mineral uptake involves selectivity [where certain minerals are absorbed preferentially over others

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(discrimination or exclusion)], accumulation (where minerals accumulate at higher concentrations in cell sap than in external soil solution), and genotype (where distinct differences exist among plant species and within species) (Marschner, 1995). A detailed discussion and reviews of plant and soil factors that affect micronutrient uptake, transport, and utilization in plants are available (Barber, 1995; Chen and Hadar, 1991; Graham et al., 1988; Gupta, 1993; Marschner, 1995; Mengel and Kirkby, 1982; Mortvedt et al., 1991; Robson, 1993; Sumner, 2000; Welch, 1995). Micronutrient cations in soil solution also commonly form organic complexes of varying stability, size, and charge (Tiffin, 1972). Kochian (1991) stated that to understand the overall mechanisms of micronutrient cation uptake in plants there is a need to consider the form of metal chelates in the root rhizosphere at the root–cell plasma membrane, forms of micronutrient cations transported into plant cells, and the nature of the metal chelate complexes, both within cells and involved in long-distance transport. A detailed discussion of the processes associated with mineral uptake and transport is provided in several review articles (Epstein, 1972; Kochian, 1991; Marschner, 1995; Moore, 1972; Mengel and Kirkby, 1982; Tiffin, 1972). Boron is absorbed by roots as undissociated boric acid [B(OH)3 or H3BO3], and it is not clear whether uptake is active or passive (Marschner, 1995; Mengel and Kirkby, 1982). Nevertheless, B uptake by rice appeared to be passive under normal B supplies and active under low B supplies (Yu and Bell, 1998) and was the result of passive assimilation of undissociated boric acid (Hu and Brown, 1997). At high B supplies, passive uptake and active excretion of B were also noted (Yu and Bell, 1998). Boron as well as Cl distribution in plant tissue appear to be primarily governed by transpiration, since B and Cl in soil are highly mobile and move with water. Boron is supplied to roots primarily by mass flow. The factors affecting B uptake include soil type, B content, soil pH, amount of water soil receives, and plant species (Welch et al., 1991). Soil pH affects B absorption kinetics of roots, adsorption on soil particles, and maintenance of B concentrations in soil solution (Barber, 1995). The absorption of B by monocotyledonous plants was less than that by dicotyledonous plants and was passive (Shelp, 1993). Long-distance transport of B from roots to shoots occurs in the xylem and is related to the rates of transpiration (Brown and Shelp, 1997). Copper uptake is an active process (Dokiya et al., 1964) and is influenced by plant species, growth stage, plant part, various soil properties, and added amendments. Copper is relatively immobile in soil, so that large portions of Cu are derived from root interception in soils low in labile Cu (Oliver and Barber, 1966). The exploitation of soil by roots (root volume, density) influenced the Cu absorbed by roots (Barber, 1995). Soil pH did not affect Cu uptake extensively because the soil maintained sufficient levels of Cu, even when free Cu2+ had been reduced with increased soil pH (Barber 1995). Mycorrhizal associations with roots improved Cu uptake by 53 to 62% in white clover (Li et al., 1991).

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In soil solution, Fe3+ dominates and forms organic complexes with degraded OM (fulvic acid) or siderophores (Fe-complexing compounds released by soil microbes and/or plant roots) (Powell et al., 1982). In well-aerated soils, complexed Fe3+ is the major form of Fe. Higher plants use nonspecific and specific processes to increase the solubility and uptake of Fe from the rhizosphere. Uptake of cations over anions is one of the most important nonspecific processes that results in pH decreases in the rhizosphere to increase Fe availability and uptake (R¨omheld and Marschner, 1986). The factors that interfere with ionic balances in plants and contribute to Fe uptake are N source, K supply, plant P status, and genotypic differences (Zaharieva and R¨omheld, 1991). Strategy I processes used by dicotyledons and nongrass monocotyledons (nongraminaceous species) in responding to Fe deficiency are to excrete protons (acidification of rhizosphere) and increase reductase activity at the root–soil interphase. The iron deficiency in dicotyledonous plants is reduced by lowering the rhizosphere pH from the root H+ excretion (proton excretion), root exudation of organic acids (mainly phenolics), enhanced root reduction of Fe3+ to Fe2+, and activated root-reducing capacity at cell plasma membranes. Increased medium acidification and Fe3+ reduction are brought about by plasmalemma-linked H+: ATPase and NADH:Fe3+ reductase activities (Dell’Orto et al., 2000). Organic anions such as citrate and oxalate exudated from the roots contribute to the Fe mobilization in soil, and such a response appears to be the factors under P deficiency for species such as rape or lupin. (Hinsinger, 1998; Jones et al., 1996). In Strategy I plants, reduction activity at the root–soil interface appears to play a dominant role in Fe aquisiton (Bertrand and Hinsinger, 2000; Brown, 1978; Chaney et al., 1972). In Strategy I, plant response to Fe deficiency is the increased capacity of the roots to reduce ferric chelates (Bienfait, 1988), which is affected by HCO3−, Fe, and other metals (Alc´antara et al., 2000). Many monocotyledonous plants, especially those of Poaceae (grasses), transport Fe3+-phytosiderophores (root-derived chelates) across root cells (Strategy II plants), which is an important mechanism by which Fe is acquired by these plants. Strategy II processes are used by graminaceous species, which excrete several types of phytosiderophores as adaptive mechanisms to Fe deficiency (Kanazawa et al., 1993; Takagi et al., 1984). Phytosiderophores are low-molecular-weight polydentate (nonproteinogenic amino acids) ligands which bind Fe3+ to facilitate transport (Kochian, 1991; Marschner, 1995; R¨omheld, 1991; R¨omheld, and Marschner, 1986). Overall, the high pH, redox state, pH buffer (HCO3−, active lime, OM), nitrate, and Fe mineral types affect Fe uptake by plants (Lindsay, 1994; Lucena, 2000; Marschner, 1995; R¨omheld and Marschner, 1986). The rate of phytosiderophore release in cereals under Fe deficiency greatly differs between species, and these differences are positively correlated with the resistance of cereals to Fe deficiency (Marschner et al., 1986; R¨omheld and Marschner, 1990). ¨ urk, Besides Fe, phytosiderophores also mobilize Zn, Mn, and Cu (Cakmak, Ozt¨ et al., 1996; Hopkins et al., 1998; R¨omheld, 1991).

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Manganese uptake is metabolically mediated, and uptake increases from pH 4 to 6 (Maas et al., 1969). Above pH 6, oxidation of Mn2+ to Mn4+ occurs, and Mn2+ uptake is reduced. Soil pH and redox potentials control the Mn supply to roots by mass flow and diffusion. Deficiency of Mn usually occurs when soil pH is >6.2, but Mn2+ may be sufficient in some soils, even though the pH is ≥7.5 (Barber, 1995). The prevailing source of Mn at root surfaces is Mn2+. Manganese forms complexes with organic compounds (trihydroxamic acid, sideramines) of microbial and plant origin, which increases the Mn mobility in soil (Clarkson, 1988). The three major sources of Mn in soils that are primarily responsible for the Mn supply to roots are exchangeable Mn, organically complexed Mn, and Mn oxides (Marschner, 1988). The proportion of these Mn forms vary with soil type, soil pH, and OM. As the soil pH decreases, the proportion of exchangeable Mn increases dramatically, while the proportions of Mn oxides and Mn bound to Mn and Fe oxides decrease. In soils low in available Fe, root reductase activity is stimulated because of acidification of the rhizosphere and may lead to higher Mn mobility and uptake. Greater ranges in foliage Mn were noted for different species of plants growing in the same soil compared to Cu, Fe, or Zn (Gladstones and Loneragan, 1970). These differences were attributed to species ability to acidify soil in the rhizosphere rather than to the Mn requirement. Molybdenum is absorbed as an anion (MoO42−) and is energy dependent; S can interfere, and P enhances Mo uptake (Barber, 1995; Mengel and Kirkby, 1982). Mass flow and diffusion supply Mo to roots in soil (Table X). Zinc is absorbed primarily as a divalent cation (Zn2+) and may be absorbed at high soil pH as a monovalent cation (ZnOH+). It is not clear whether Zn uptake is active or passive, even though Mengel and Kirkby (1982) indicated that Zn was actively absorbed. Zinc is not reduced or oxidized as are Mn, Fe, and Cu. The low availability of Zn in high pH calcareous soils is due to the adsorption of Zn on clay or CaCO3 (Trehan and Sekhon, 1977). In addition, high concentrations of HCO3− inhibit Zn uptake and translocation (Dogar and van Hai, 1980). Zinc uptake is ¨ urk et al., 1996; Hopkins et al., also enhanced by phytosiderophores (Cakmak, Ozt¨ 1998).

C. OXIDATION AND REDUCTION Oxidation–reduction reactions occur when electrons are transferred from a donor to an acceptor. The donor loses electrons to increase in oxidation number, and the acceptor gains electrons to decrease in oxidation number. Redox reactions with various forms of Mn (Mn2+ and Mn4+), Fe (Fe2+ and Fe3+), and Cu (Cu+ and Cu2+) are common in soils (Lindsay, 1979), but Fe and Mn redox reactions are considerably more important than Cu because of their higher concentrations in soil. The primary source of electrons for biological redox reactions in soil is OM,

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217

but aeration, pH, and root and microbial activities also influence these reactions. Redox reactions in soil can also be influenced by organic metabolites produced by roots and microorganisms. Certain forms of micronutrients are more available to plants than others, and concentrations of each mineral form depend on soil conditions affecting redox. The most water-soluble and available forms to plants are Mn2+, Fe2+, and Cu2+, and these may be altered greatly depending on redox conditions. In general, a high pH favors oxidation and a low pH favors reduction of these minerals. The availability of Fe and Mn increases, and sometimes they become toxic to plants grown under highly reducing conditions (flooding). Redox of Mn is thermodynamically favored at relatively higher redox potentials compared to Fe at given pH values. For example, the critical redox potential at which Fe2+ appeared was 100 mV and Mn2+ appeared at 200 mV in a Crowley silt loam soil at pH 6.5 (Patrick and Jugsujinda, 1992). As a result, demonstrated spatial relationships between Mn and Fe precipitation in horizontal sand columns relative to increased redox potentials were observed (Collins and Buol, 1970). Iron precipitated at relatively lower redox potentials compared to Mn, which did not precipitate until reaching more oxidized portions in columns. Liming soil to pH > 5.6 increased oxidation processes and reduced or prevented Mn toxicity (Kamprath and Foy, 1985). Increased reduction of Mn oxides occurred with increased soil temperature (Ross and Bartlett, 1981; Sparrow and Uren, 1987). Hence, warm soils may induce Mn toxicity more readily than cooler soils. Flooding (reducing conditions) had no influence on B concentrations in soils, and B did not undergo redox reactions (Ponnamperuma, 1972). Increasing soil Eh values (oxidation) redistributed Cu from exchangeable and organic fractions to Fe oxide fractions, thereby reducing Cu availability to plants (Shuman, 1991). Under flooded conditions, Cu was adsorbed onto surfaces of reduced Mn and Fe oxides (Iu et al., 1981). Reducing conditions in soil mobilized Fe oxide fractions, which became associated with exchangeable, organic, and Mn oxide fractions to make Fe more available to plants (Shuman, 1991). Increases in Eh or soil pH shifted Fe from exchangeable and organic forms to water-soluble and Fe oxide fractions. Under alternate wetting and drying conditions, adding OM led to reducing conditions and enhanced Fe availability (Shuman, 1988). As redox potentials and/or soil pH increase, the plant availability of Fe decreases due to the insolubility of Fe3+ oxides. The critical redox potential for Fe3+ was −100 mV at pH 8, +100 mV at pH 7, and +300 mV at pH 6 (Gotoh and Patrick, 1974). Water-logging resulted in a decreased redox potential, and a low pH led to increased water-soluble and exchangeable Fe. Excess water in calcareous soil increased the buildup of HCO3−, which reduced soluble Fe3+ and induced Fe deficiency (Moraghan and Mascagni, 1991). Soil pH and redox potential are responsible for Mn transformation from insoluble to water-soluble and extractable forms. Under reducing conditions, Mn

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was released from organic and oxide forms into water-soluble and exchangeable fractions (Sims and Patrick, 1978). Low Eh values (reducing conditions) increased exchangeable Mn to mobilize Mn into more plant-available fractions (Shuman, 1991). In poorly drained soils, organic Mn and Mn oxides dominate compared to well-drained soils. Molybdenum does not appear to be directly involved in redox reactions in soil. However, the increases in soil pH and the reduction of Fe oxides under reducing conditions (low redox values) may increase the solubility of MoO4 (Moraghan and Mascagni, 1991). Zinc is not reduced under low redox conditions, but soil submergence tends to decrease Zn concentrations in soil solution (Ponnamperuma, 1972). Neither Zn nor Cu is affected by redox reactions which occur under most soil conditions. Submergence of soil caused Eh to decrease and pH to increase to enhance solubility and release oxide metals (Shuman, 1991). In flooded rice soils, decreased concentration and mobility of Zn was due to Zn adsorption on surfaces of hydrated Mn oxides (Singh and Bollu, 1983).

D. RHIZOSPHERE The rhizosphere is defined as the zone of soil immediately adjacent to plant roots in which the kinds, numbers, and/or activities of microorganisms differ from those of the bulk soil (SSSA, 1996). This zone usually contains fungi, bacteria, root and microorganism secretions, sloughed off or dead materials from microorganisms and roots, and chemical properties that are markedly different from the bulk soil. The chemistry of the rhizosphere has pronounced effects on the availability of micronutrients. An example of rhizosphere activity is mycorrhizae. Mycorrhizae associated with crop plants are primarily arbuscular mycorrhizal fungi (AMF). The AMF form beneficial symbioses with roots to allow plants to grow considerably better than would be expected under relatively harsh mineral stress conditions. These fungi are ubiquitous in most soils, and about 90% of plants are mycorrhizal. The AMF improve host plant nutrition by improving the acquisition of P and other minerals, especially the low mobile micronutrients Zn, Cu, and Fe (Marschner, 1991a). The AMF accomplish this primarily by extension of root geometry. That is, AMF hyphae are smaller (average diameter = 3–4 μm) than roots and/or root hairs (diameter = >10 μm) and can make contact with soil particles and/or explore pores/cavities that roots would not otherwise contact (Clark and Zeto, 2000). Hyphae also extend away from roots and explore greater volumes of soil than roots themselves. The AMF may also protect plants from excessive uptake of some toxic minerals (Brady and Weil, 1996; Clark and Zeto, 2000). Root colonization with

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AMF can decrease the risk of plants to Mn, Fe, B, and Al toxicity in acid soils (Clark and Zeto, 2000; Marschner, 1991a). Toxicity factors may be reduced by inhibiting the acquisition of toxic minerals and/or from root/hyphae exudations to decrease reactions in the rhizosphere like Mn reduction (Marschner, 1991a). In addition to mycorrhizae, noninfecting rhizosphere microorganisms may affect mineral nutrition of plants through their influence on growth and morphology of roots, physiology and development of roots and shoots, availability of nutrients, and nutrient acquisition (Marschner, 1995). Whether high microbial activity in the rhizosphere leads to increases or decreases in micronutrient availability depends on the conditions. For instance, if root exudates consist mainly of organic acids or complexing compounds with high activity toward mobilizing Mn or Fe, utilization of these organic acids by rhizosphere microorganisms may decrease the acquisition of Mn and Fe. The positive effects of rhizosphere microorganisms on micronutrient availability have generally been noted when sugars are released in root exudates (Marschner, 1991b). Noninfecting rhizosphere microorganisms may also be responsible for oxidation of Mn2+ in bulk and rhizosphere soils and may immobilize (oxidize) or mobilize (reduce) Mn (Marschner, 1995). Roots also induce chemical and microbial changes in the rhizosphere that affect micronutrient availability. The rhizosphere pH may differ by as many as 2–3 units from that bulk of soil (Marschner, 1995). The net excretion of H+,OH−, and HCO3− from roots associated with cation/anion uptake induces pH changes in the rhizosphere, which have been related to soil buffer capacity and source of N. Root excretion of H+ at root surfaces is an effective mechanism for enhancing Zn uptake compared to excretion of complexing agents (Bar-Yosef et al., 1980). Acidification of the rhizosphere generally improves availability of micronutrients, even in calcareous soils, to enhance micronutrient mobilization. This has been noted especially for Fe. Enhanced reducing activity at root surfaces has been noted as root-induced responses to Fe deficiency in dicotyledonous and nongraminaceous monocotyledonous plants (Marschner, 1995). Modification of rhizosphere properties by roots is important in micronutrient acquisition by plants and plant ability to adapt to adverse mineral stress soil conditions (Marschner, 1995). Plant roots release or secrete low- and high-molecular-weight root exudates. Low-molecular-weight exudates include organic, amino, and phenolic acids (including phytosiderophores) and sugars. These low-molecular-weight exudates released from roots mobilize micronutrients in the rhizosphere and assist roots in acquiring less available minerals. The effectiveness with which root exudates dissolve sparingly soluble micronutrients depends on rhizosphere pH, N form, mineral deficiency-induced H+ excretion, and/or microbial acid production (Marschner, 1988). The major components of high-molecular-weight substances released to the rhizosphere are mucilages and ectoenzymes. These substances contribute to

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rhizodeposition (deposition of organic C). High-molecular-weight organic C exudates released into the rhizosphere serve as substrates for microorganisms around roots and may indirectly affect the solubility and availability of micronutrients (Curl and Truelove, 1986; Marschner, 1995). Microorganisms in the rhizosphere can benefit plant growth by enhancing nutrient availability (mineralization, root morphology, fauna activity), increasing nonsymbiotic N2 fixation, improving symbiotic root relationships with other microorganisms (rhizobia, mycorrhizae), enhancing plant responses to microbial metabolites, and decreasing plant pathogen activity and diseases (Curl and Truelove, 1986). Considerable amounts of C may be released by plants into the rhizosphere. On average, 30–60% of the net photosynthetic C is allocated to roots, and appreciable proportions of this C (14 to 40% of fixed C) are released as organic C into the rhizosphere (Marschner, 1995). The amount of C released depends on plant age and growing conditions such as plant water status, soil aeration, soil strength, and nutritional status of plants (Whipps and Lynch, 1986). Rhizosphere deposition of organic C normally increases when various forms of stress such as mechanical impedance, anaerobiosis, drought, and mineral deficiencies occur (Lynch and Whipps, 1990; Whipps and Lynch, 1986). Soil microbes mineralize SOM, thereby releasing large amounts of essential mineral nutrients. Microorganisms at root surfaces may also affect root morphology (main root and root hair density, surface area), and subsequently enhance or reduce mineral absorption (Curl and Truelove, 1986). The release of root exudates increased soluble Cu concentrations (Nielson, 1976), and the dissociation of Cu2+ from organic ligands occurred prior to plant uptake (Goodman and Linehan, 1979). Reducing processes near roots can increase available Fe3+ from dissociation of Fe3+–chelates (R¨omheld and Marschner, 1986). Organic acids may also be responsible for the mobilization of sparingly soluble Fe (Fe3+) in the rhizosphere. Plant responses to Fe deficiency may increase the exudation of phenolic and amino acids, especially phytosiderophores, so that plants may acquire Fe (Marschner, 1995). Root exudation from Fe-deficient barley grown in calcareous soil mobilized considerable amounts of Fe, Zn, Mn, and Cu (Treeby et al., 1989). Organic compounds such as hydroxy-carboxylates released from roots enhanced the Mn availability by reducing Mn4+ oxides and complexing Mn2+ (Godo and Reisenauer, 1980). Such effects of root exudates are particularly important in soils at pH < 5.5. Acquisition of Mn by rice grown in aerobic soil apparently was influenced by Fe uptake and soil pH (Jugsujinda and Patrick, 1977). Increased solubility of MnO2 by root exudates resulted mainly from organic acids (Uren and Reisenauer, 1988). For example, exuded organic, amino, and phenolic acids may directly enhance dissolution of sparingly soluble Mn compounds in soil. The effectiveness of root exudates for dissolution (reduction) of Mn oxides is favored at low and inhibited at high rhizosphere pH.

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E. INTERACTIONS WITH OTHER ELEMENTS The understanding of micronutrient interactions between and among the various mineral nutrients is important for balancing nutrient supplies to plants, improving growth and yields of plants, and eliminating deficiencies and toxicities imposed on plants. Mineral interactions are generally measured in terms of growth responses and changes in mineral nutrient concentrations in plants. An excellent review of the many interactions micronutrients have with other elements has been provided by Olsen (1972), and our article discusses mostly information since that review.

1. Boron The ability of anions to leach adsorbed B from Fe and Al oxides in soil increased in the order of Cl < S ≪ P (Metwally et al., 1974). Magnesium hydroxides also adsorb B (Rhoades et al., 1970). Normal B concentrations in plant tissue usually range from 10 to 50 mg kg−1 dry wt, but some plants like alfalfa require considerably more than others (Mengel and Kirkby, 1982). Positive relations have also been noted between B and K and N fertilizers for improving crop yields (Hill and Morrill, 1975; Moraghan and Mascagni, 1991). High B supplies resulted in low uptake of Zn, Fe, and Mn, but increased uptake of Cu. High pH, Ca, Mg, and N in soil may also reduce B in plants. In low B soil, high N induced B deficiency in plants (Gupta, 1993). However, the effects of P, K, and S on uptake of B are not clear, and these minerals had positive, negative, and/or no effects on B uptake (Gupta, 1993). Zinc deficiency enhanced B accumulation (Graham et al., 1987), and Zn fertilization reduced B accumulation and toxicity on plants grown in soils containing adequate B (Graham et al., 1987; Moraghan and Mascagni, 1991; Swietlik, 1995). Boron deficiency reduced uptake of P by faba bean (Robertson and Loughman, 1974) and reduced uptake of Mn and Zn by cotton (Ohki, 1975). Boron became toxic to maize when grown under P deficiency conditions, and P applications alleviated B toxicity (G¨unes and Alpaslan, 2000). Calcium translocation to shoots was inhibited because of the relatively high xylem sap pH, which was improved by applying B (Singaram and Prabha, 1997). Root Ca concentrations decreased while B concentrations increased, but B in shoots and fruit did not change, indicating that B translocation was not hindered by Ca in plants grown in calcareous soil. On the basis of equivalent Ca/B ratios, both foliar and soil applications of B insured adequate B to shoots and alleviated excess Ca uptake from soil (Moraghan and Mascagni, 1991). Even though the role of B in plants is not clearly understood, B is important in membrane structure, transport across membranes, metabolism of cellular N and P compounds, and viability of seeds (Kastori et al., 1995; Rerkasem et al., 1997). These processes

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would indirectly affect uptake of not only B but also other minerals. Uptake and transport of various mineral nutrients in plants are sensitive to B concentrations in the growth media (Mozafar, 1989). 2. Chlorine Only limited information is available on interactions of Cl with other nutrients. Chlorine is highly mobile in soil, and excessive concentrations can be leached by excess irrigation and/or rainfall. High concentrations of Cl in soil solution may depress mineral nutrient activities and produce abnormal Na/Ca, Na/K, Ca/Mg, and Cl/NO3–N ratios. As a result, plants may become susceptible to osmotic injury as well as nutritional disorders that could reduce plant yield and quality (Grattan and Grieve, 1999). Chloride is often added with K fertilizers, which are added at relatively high rates compared to other micronutrients. Increased levels of Cl reduced NO3–N (Inal et al., 1995) as Cl competes with NO3–N during uptake processes (Mengel and Kirkby, 1982). Evidence exists that if Cl rather than SO4–S is dominant in saline soils, Ca deficiency can be alleviated, and Cl may increase Ca uptake independent of Ca addition (Curtin et al., 1993). Chloride enhancement of Ca may also be related to increases in cation activity from Cl in soil solution or from co-transport resulting in neutralization of positive charges during cation uptake (Marschner, 1995). Ranges of Cl concentrations normal for tissue are high even though amounts needed for plant activity are relatively low (Mengel and Kirkby, 1982). 3. Copper Copper uptake is metabolically mediated and strongly inhibited by other divalent cations, especially Zn2+ (Mengel and Kirkby, 1982). Applications of relatively high levels of N and P fertilizers have induced Cu deficiency on plants grown in low Cu soils. Even though N and Cu interact, no significant effects of NO3–N or NH4–N on Cu uptake have been noted (Kochian, 1991). However, transport of Cu was related to supply and transport of N, and Cu translocation increased with increasing N supplies (Jarvis, 1981b). Increased soil P induced Cu deficiency, but was related to dilution effects from increased growth and depressing effects of P on Cu absorption (Reuter et al., 1981). Copper toxicity has also been noted in P-deficient plants (Wallace, 1984), and K also decreased Cu uptake in sunflower (Graham, 1979). Plants grown in coarse-textured soils with low available P and Fe and high in Cu exhibited Cu toxicity (Moraghan and Mascagni, 1991). Added Fe ameliorated Cu toxicity in spinach (Ouzounidou et al., 1998), and Cu toxicity has induced Fe deficiency in plants (Bowen, 1969). Increased Cu in the growth media, decreased Zn, and increased P levels in soil resulted in a reduced exploration of soil by mycorrhizal roots, which led to low Cu availability and low Cu concentrations

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in plant tissue (Moraghan and Mascagni, 1991). Since Zn and Cu are absorbed by the same carrier, each of these mineral nutrients competitively inhibits uptake of each other (Giordano et al., 1974). Microbial immobilization and antagonistic effects of increased concentrations of Fe and Mn reduced soil-available Cu. 4. Iron High soil levels of several minerals (Ca, P, N, Mn, and Cu) may contribute to the induction of Fe deficiency in many plants (Madero et al., 1993). On the other hand, low soil Fe may also inhibit or promote absorption of other minerals. Of the nutrients that interfere with Fe nutrition, minerals with the greatest effects followed the sequence of P > K > Mg > N > Ca (Luo et al., 1997). High Fe may also reduce uptake of these minerals. Different concentrations of Fe inhibited mineral uptake by rice grown in nutrient solution and uptake of P, K, Ca, Mg, and S by alfalfa, wheat, rice, and red clover also decreased with increased levels of Fe (Fageria, Baligar, and Edwards, 1990; Fageria and Rabelo, 1987). Similarly, uptake of Mn, Zn, and Cu in alfalfa, red clover, and wheat decreased when Fe concentrations increased. Increasing Cu in the growth medium decreased not only Fe but also Zn and Mn (Alva and Chen, 1995). However, the effect on Fe was more pronounced than that on Zn and Mn. Negative interactions between Fe and Mn have also been reported for other crop plants (Moraghan, 1985; Zaharieva, 1986). Soils low in Zn may enhance Fe uptake, especially when soil pH is >7.0 (Fageria and Gheyi, 1999). The effects of high soil P on decreasing plant Fe concentrations because of immobilization of soil Fe are well documented (Olsen, 1972), and high soil P levels decreasing plant Fe concentrations may also be related to inhibition of Fe absorption by roots, subsequent transport to shoots, and inactivation of Fe in plants (Moraghan and Mascagni, 1991). Nitrogen, especially NO3–N, can aggravate Fe deficiency by raising soil pH (Aktas and Van Egmond, 1979; Wallace et al., 1976) and release of HCO3− in the rhizosphere (Chen and Barak, 1982). With or without N fertilizer, the application of Fe resulted in increased N, P, K, Mg, Zn, and Cu concentrations in leaf blades of peanut, but decreased Ca and Mn (Ali et al., 1998). Manganese decreased Fe uptake and adversely affected Fe metabolism (Zaharieva et al., 1988) and increased Mo-decreased Fe uptake (Olsen and Watanabe, 1979). This latter interaction may be important in alkaline soils where Fe availability is low and soluble MoO42− concentrations may be high. Iron toxicity is common for rice grown in flooded soils because of enhanced reducing conditions (Fe3+ to Fe2+), and Fe concentrations in solution and plants increase (Fageria, Baligar, and Wright, 1990). The nutritional status of rice is commonly related to Fe toxicity. When Fe toxicity occurs in rice, Fe concentrations in leaf blades may exceed 300 mg kg−1 dry wt (Fageria, Baligar, and Wright, 1990; Yoshida, 1981). In addition, P, K, Ca, Mg, and Mn deficiencies decrease the capacity of rice roots to exclude Fe, and Fe toxicity may result. In soils where

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problems of Fe toxicity exist, P and K deficiencies appeared before uptake of Mn, Zn, and Cu was reduced. Adequate concentrations of K in soil solution also decreased Fe toxicity in rice (Fageria, Baligar, and Edwards, 1990). Zinc deficiency may accentuate Fe uptake and lead to the accumulation of toxic levels of Fe in plants (Adams and Pearson, 1967).The addition of MnO2 increased soil redox potential and reduced concentrations of Fe2+ and organic reducing products (Fageria, Baligar, and Wright, 1990). Iron toxicity is more severe for plants grown on heavy-textured soils compared to light-textured soils. 5. Manganese The anionic minerals P, S, NO3–N, and Cl and the cationic minerals K and NH4–N affect solubility, mobility, and/or availability of Mn to crop plants (Norvell, 1988). Studies on the interactions between Mn and divalent minerals are also common (Bowen, 1969; Chinnery and Harding, 1980). Manganese uptake is considered to be active and may be inhibited by Ca, Mg, and Zn (Maas et al., 1969; Robson and Loneragan, 1970). Relatively high concentrations of Fe were noted in leaves of soybean grown with low Mn, and Mn concentrations in soybean shoots decreased with increased Fe levels in solution (Chinnery and Harding, 1980). Free CaCO3, high Fe, and strongly alkaline conditions may also induce Mn deficiency in plants. The application of Fe may reduce concentrations of Mn in plants. Plants grown with Fe applications had high plant growth and low shoot Mn concentrations, even to deficiency levels, because of dilution (Romero, 1988). The antagonistic effects of FeEDDHA on Mn accumulation were reported in white lupin, but these effects occurred mainly when relatively high amounts of P were added (Moraghan, 1992). Relatively low levels of Fe (4 mg kg−1 soil) in the absence of added P had only slight negative effects on Mn and even increased Mn concentrations. In contrast, marked depressing effects of FeEDDHA on Mn concentrations were noted for plants grown with high P (120 mg kg−1 soil). Problems associated with Fe–Mn interactions have been related mainly to chemical interactions at the root–soil interface (Kochian, 1991). Increased rhizosphere acidity from plant responses to Fe deficiency may also enhance Mn4+ reduction to Mn2+, and increase Mn2+ solubility (Marschner, 1988). Increased levels of soil P both increased and decreased Mn toxicity in plants, and applications of Zn or Mo fertilization reduced Mn uptake (Moraghan and Mascagni, 1991). Increasing concentrations of Fe (also Ca or Mg) in the growth medium may also decrease Mn toxicity (Marschner, 1995). Excess Mn-induced Fe deficiency in potato and leaves had Mn/Fe ratios of 18 or higher (Lee, 1972). The high Al availability counteracted these effects by increasing Fe in plants and decreasing Mn/Fe ratios. Plants with Fe deficiency had lower Mn/Fe ratios, and plants with higher ratios developed Mn toxicity (Lee, 1972). Manganese toxicity and Fe deficiency symptoms are different in rice, and the range at which Fe toxicity can be remedied by Mn application is narrow (Tanaka

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and Navasero, 1966). High shoot Fe concentrations of Fe-inefficient, Mn-sensitive soybean accentuated Mn toxicity, and high shoot K concentrations of Mn-tolerant soybean alleviated the harmful effects of high internal Mn concentrations (Brown and Jones, 1977). The increased Ca levels in the growth medium decreased Mn uptake and toxicity (Heenan and Carter, 1976). Phosphorus detoxified Mn by precipitating it within plant roots (Heintze, 1968). Soluble sources of Si in the growth medium can also protect plants against Mn toxicity (Foy et al., 1978). Plants low in Si, P, Ca, Mg, and Fe often accumulate high Mn and are susceptible to Mn toxicity (El-Jaoual and Cox, 1998). Silicon may also decrease excessive uptake of Mn and Fe (Foy et al., 1978). Excess Mn can interfere with absorption, translocation, and utilization of P, Ca, Mg, and Fe (Clark, 1982) and reduce concentrations of Si, K, Zn, and Cu (Clark and Baligar, 2000). Increasing Mn concentrations in nutrient solution triggered synergistic effects on Ca, Mg, Na, P, and Cu uptake, but displayed antagonistic action on K and Zn in rice (Lidon, 1999). Translocation of Fe was also inhibited. Increasing Mn levels delayed rice maturation and the concentrations of the minerals accumulated. However, concentrations of potentially toxic minerals in grain were lower than those in vegetative tissues. Concentrations of Ca, K, Na, P, and Zn interacted with increasing Mn concentrations, mostly in shoots, but different patterns were noted for Mg, Cu, and Fe. Manganese acquisition was reduced with the application of Zn (Haldar and Mandal, 1981) and Mo fertilizers (Sims et al., 1975). Interactions of Mn with other elements, particularly Fe and Si, may be extensive (El-Jaoual and Cox, 1998). 6. Molybdenum Sulfur, P, and NH4–N applications may decrease Mo concentrations in plants and accentuate Mo deficiency (Anderson, 1956; Gupta and MacLeod, 1975; Ray et al., 1986). Soil application of Mo increased Mo and N uptake by legumes at soil pH 5 (Mortvedt, 1981). High Fe and Al oxides and good soil aeration (drainage) also reduced Mo availability. Sulfur has been used to decrease Mo uptake and reduce Mo toxicity in plants through decreasing soil pH (Chatterjee et al., 1992). Increased B and decreased K, Mn, and Cu were noted in barley grown with high Mo (Brune and Dietz, 1995). High Mo may also induce Cu deficiency in cattle (“molybdenosis”) (Miller et al., 1991). Although Mo is essential to higher plants, its concentration in tissue is low (usually < 1 mg kg−1 dry wt) and crucial in N metabolizing enzymes (nitrate reductase) (Beevers and Hageman, 1969; Yu et al., 1999). 7. Zinc Zinc interactions with other elements are many and include Zn–P, Zn–N, Zn–K, Zn–Mn, Zn–Fe, and Zn–Cu (Moraghan and Mascagni, 1991; Olsen, 1972). Under

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some conditions, Co and Na may also inhibit Zn absorption (Loneragan and Webb, 1993). The most widely reported interaction with Zn is that of P. High P applied to low Zn soils enhanced the plant accumulation of P thereby increasing the internal plant Zn requirement because of Zn precipitation (Robson and Pitman, 1983). High applications of P fertilizer can induce Zn deficiency (P-induced Zn deficiency) and increase plant requirements for Zn (Robson and Pitman, 1983). Inappropriately high P applications have induced Zn deficiency in plants most likely because of increased P uptake and higher shoot growth, which has led to decreased Zn in shoots because of dilution (Loneragan et al., 1979; Marschner, 1993). Zinc-deficient plants may also have high and potentially toxic P concentrations, and P toxicity symptoms have sometimes been mistaken for Zn deficiency (Fageria and Gheyi, 1999). Nevertheless, Zn-deficiency-induced P toxicity may be an artifact caused by high P concentrations (Loneragan and Webb, 1993). High levels of P have also resulted in increased absorption and retention of Zn in roots and decreased translocation to leaves (Iorio et al., 1996). The processes involved with P–Zn interactions and the subsequent low acquisition of Zn by plants include high P in soil decreasing Zn solubility, reduced root growth, cations added with and H+ generated by P salts to inhibit Zn absorption, and suppressed root colonization by mycorrhizae (Loneragan and Webb, 1993; Robson and Pitman, 1983). Plants with reduced mycorrhizal root colonization had lower Zn concentrations (Lambert et al., 1979), and mycorrhizal plants commonly have higher Zn concentrations than nonmycorrhizal plants (Clark and Zeto, 2000). In certain soils, added P tended to enhance the adsorption of Zn on soil particles rich in hydrated Fe and Al oxides with subsequent inducement of Zn deficiency on plants (Barber, 1995). Many interactions of Zn with macronutrients other than P have been noted. Both monovalent and divalent cations can inhibit Zn uptake, and the importance of these were NH4–N > Rb > K > Cs > Na > Li for monovalent minerals and Mg > Ba > Sr = Ca for divalent minerals (Chaudhry and Loneragan, 1972a,b). The application of gypsum to sodic soils and the addition of manures have also helped alleviate Zn deficiency (Takkar and Walker, 1993). Alkaline soils and soils high in CaCO3, N, and P and low in SOM normally have reduced Zn availability. High levels of H+ also competitively reduced Zn absorption (Barber, 1995). With increased supplies of S, increased Zn was translocated from roots to shoots (Fontes and Cox, 1998a). High levels of Zn decreased uptake of Cu and Mn in upland rice grown in an Oxisols in central Brazil. Zinc interactions with other micronutrients include enhanced B concentrations in Zn-deficient plants (Singh et al., 1990) and B toxicity being reduced with Zn applications (Graham et al., 1987; Singh et al., 1990). Mutually competitive interactions occur between Cu and Zn (Barber, 1995; Loneragan and Webb, 1993). Zinc–Cu interactions affected plant nutrition because Zn strongly depressed Cu absorption, Zn and Cu competitively inhibited each other, and Cu affected

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redistribution of Zn within plants (Loneragan and Webb, 1993). Enhanced Zn supplies improved the growth of Fe-deficient soybean (Fontes and Cox, 1998a), and Fe applications overcame many soybean Zn toxicity effects (Fontes and Cox, 1998b). Increased soil Zn increased translocation of Mn to soybean shoots to induce Mn toxicity (crinkle leaf), and Zn and Mn interfered with Fe utilization in leaves to reduce chlorophyll synthesis (Foy et al., 1978) . In addition, Zn deficiency enhanced uptake of Mn so that Mn concentrations reached phytotoxic levels (Robson and Pitman, 1983). Increased concentrations of Mn, B, and Mo were also noted when barley received Zn applications (Brune and Dietz, 1995). 8. Nickel and Cobalt Maize grown in calcareous soil with Ni applications enhanced Zn and decreased P concentrations (Karimian, 1995), and high levels of Ni increased B, Mn, and Mo in barley (Brune and Dietz, 1995). Simultaneous supplies of NO3–N and NH4–N reduced Ni toxicity in sunflower, and growth was enhanced from added Ni (Zornoza et al., 1999). Low Ni plants became N deficient from lack of urease activity with a high accumulation of urea but low tissue N (Gerendas and Sattelmacher, 1997). Cobalt availability was decreased in soils containing high CaCO3 and high Fe, Mn, SOM, and moisture. Added Co to growth media increased N, P, Ca, and Cu, but had no enhancement effects on K, Mg, Na, and Zn in tomato (Moreno-Caselles et al., 1997). Calcium and Mg noncompetitively inhibited Ni uptake, whereas Cu, Zn, and Co competitively inhibited Ni absorption (Korner et al., 1987).

V. IMPROVING SUPPLY AND ACQUISITION A. SOIL IMPROVEMENT Production potentials of many soils in the world are decreased by low supplies of micronutrients from adverse soil physical and chemical constraints (Baligar and Duncan, 1990; Baligar and Fageria, 1997; Dudal, 1976; Fageria, 1992; Fageria and Baligar, 1997a; Fageria, Baligar, and Edwards, 1997; Fageria, Baligar, and Wright, 1997; Foy, 1984). Major chemical (salinity, acidity, elemental deficiencies and toxicities, low SOM) and physical (bulk density, hardpan layers, structure and texture, surface sealing and crusting, water holding capacity, water-logging, drying, aeration) constraints affect transformation (mineralization, immobilization), fixation (adsorption, precipitation), and leaching or surface runoff of indigenous and added micronutrients (Baligar and Bennett, 1986a,b; Baligar and Fageria, 1997). In tropical regions, common soil micronutrient problems in rainfed systems affecting crop production include Fe toxicity and Zn deficiency (Baligar and

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Fageria, 1997; Fischer, 1998). Acid soils present special micronutrient nutritional problems for plants because of the high availability of Mn and Fe and the reduced availability of Zn and Mo (Baligar and Fageria, 1997; Fageria, Baligar, and Edwards, 1990; Fageria, Baligar, and Wright, 1990; Sumner et al., 1991). In addition, factors enhancing acidification not only lead to micronutrient toxicities/deficiencies but also to soil degradation (Baligar and Ahlrichs, 1998; Baligar et al., 1998; Dudal, 1976; Sumner et al., 1991). Micronutrients commonly occurring in toxic concentrations in salt-affected soils-include Mo and B (Gupta and Abrol, 1990). In recent years, the addition of toxic trace elements like Cd, Cr, Ni, Pb, Cu, Zn, As, Co, and Mn (some of which are considered micronutrients) to agricultural soils has increased from enhanced anthropogenic activity (burning fossil fuels, application of sewage, industrial, mine, municipal products), use of amendments (fertilizers, manures, lime), application of pesticides, and deposition of atmospheric particles (Adriano, 1986; Alloway, 1995a,b; Kabata-Pendias and Pendias, 1992). Excessive levels of trace elements pose phytotoxicities to plants and may reduce growth and acquisition of micronutrients (Baligar et al., 1998; KabataPendias and Pendias, 1992; Marschner, 1995). Temperature, pH, redox potentials, anion ligand formation, and composition and quantity of solution greatly influence the mobility and bioavailability of micronutrients and other trace elements in soil (Alloway, 1995b). The bioavailability of most trace elements is high at low soil pH. Adverse soil physical properties affect longitudinal and radial root growth, root distribution, morphological (stunting, thickening, reduction of lateral roots) and anatomical changes (Bennie, 1996; Russell, 1977; Taylor et al., 1972). High mechanical impedance leads to the loss of root caps and the reduction of root thickening, primarily due to short and wide cells of the same cortex volume (Camp and Lund, 1964) and thick cortex cells (Baligar et al., 1975). Mechanical impedance may also cause changes in the structure of the endodermis and pericycle cells (Baligar et al., 1975; Bennie, 1996). Such changes in root size and internal and external morphology will influence root ability to explore large soil volumes for micronutrients. Excessive or deficient micronutrients also affect morphology (length, thickness, surface areas, density) and growth (dry mass, root : shoot ratio) of roots and root hairs (Baligar et al., 1998; Bennett, 1993; Hagemeyer and Breckle, 1996; Fageria, Baligar, and Jones, 1997; Fageria, Baligar, and Wright, 1997; Foy, 1992; Kafkafi and Bernstein, 1996; Marschner, 1995). Maize root : shoot ratios increased when Zn was decreased and decreased when Mn and Cu were decreased (Clark, 1970). Organic matter helps maintain good soil aggregation, increases water holding capacity and exchangeable ions, leaching of nutrients, and Mn and Fe toxicities (Baligar and Fageria, 1997; Fageria, 1992; von Uexkull, 1986). The addition of crop residues, green manures, composts, animal manures, growing cover crops,

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using reduced tillage, and avoiding elimination (burning) of crop residues can significantly improve SOM levels and eventually lead to improved plant growth and acquisition of micronutrients. Liming has also been effective in correcting soil chemical constraints (Adams, 1984) and has improved the availability of Mo and decreased the availability of Mn, Fe, B, Zn, and Cu, and reduced Mn toxicity (von Uexkull, 1986). Liming also improves root growth to increase plant ability to absorb micronutrients. In addition, liming improves soil capacity to supply needed micronutrients to plants (Baligar and Fageria, 1997; Fageria, 1992; Fageria et al., 1995).Since lime has low mobility in soil, surface-applied lime has little or no effect on improving problems in subsurface soil. However, the tendency for downward movement of Ca from surface-applied gypsum (CaSO4) is high (Farina and Channon, 1988; Farina et al., 2000; Ritchey et al., 1980, 2000) and has long-term positive effects on plant growth (Farina et al., 2000; Toma et al., 1999). The downward movement of Ca in soil improved the rooting depth and increased the levels of micronutrients for maize grown in Cerrado acid soils of Brazil (Sousa et al., 1992). The reduction of subsoil acidity problems usually leads to deeper rooting and improves micronutrient uptake by plants.

B. SOIL AND FOLIAR FERTILIZATION The sources of micronutrients may be inorganic, synthetic chelates, and/or natural organic complexes. The potential exists for creating toxic levels of micronutrient in soil by misapplication, since only small amounts are leached from soil (except B) or small quantities are absorbed by plants (Martens and Westermann, 1991). Micronutrient toxicities are undesirable as they lower yields and product quality, and excessive levels may enter the food chain. The remediation of soils with high levels of micronutrients is relatively difficult. The factors influencing availability and plant acquisition of micronutrients have been discussed in earlier sections. Both organic and inorganic micronutrient sources are used to correct deficiencies in soil. Soil application includes band or broadcast applications before planting or foliar sprays during vegetative growth. Micronutrients are usually blended with or coated onto granular N, P, and K fertilizers or mixed with fluid fertilizers (Mortvedt, 1991, 2000). To prevent chemical alteration of micronutrients, blending should occur relatively soon before application (Mortvedt, 1991). Foliar applications are used to supply micronutrients more rapidly for correction of severe deficiencies commonly induced during the early stages of growth, and are temporary solutions to the problem. Several problems associated with foliar applications include low penetration rates in thick leaves, run-off from hydrophobic surfaces or being washed off by rain, rapid drying of spray solution, limited

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translocation from uptake site to other plant parts, limited amounts of nutrients that can be supplied and often do not meet plant demands, and leaf damage/burn (Marschner, 1995). Reducing the pH of spray solutions may reduce leaf damage. The addition of Si-based surfactants appears to reduce leaf damage and increase spray effectiveness (Horesh and Leavy, 1981). The disadvantages of foliar application are maximum yields which may not be possible if spraying is delayed until deficiency symptoms appear and residual effects from foliar sprays are little, thus multiple sprays may be required for season-long correction (Mortvedt, 2000). However, foliar fertilization has many advantages which include: rates applied are considerably lower than soil applications; uniform applications are possible; crop response to applied micronutrient is almost immediate so that deficiency can be corrected relatively rapidly; problems often associated with inactivation of soil-applied micronutrients may be overcome (Mortvedt, 2000). Plant (leaf age, species, nutritional status and requirements), climatic (light, temperature, humidity), and chemical (form, carrier, adjuvant) factors affect foliar spray effectiveness (Kannan, 1990). Greater absorption by leaves is favored under low light, optimum temperature, and high humidity conditions. Young leaves are metabolically more active than older leaves and are more effective with absorption. Hygroscopic compounds keep micronutrients in solution longer, thereby helping plants absorb these elements more effectively than nonhygroscopic compounds. To increase the effectiveness of foliar uptake, wetting agents are usually added to sprays. These chemicals are neutral nonionic compounds which reduce surface tension and increase wetting of leaf surfaces to enable larger amounts of solution to be absorbed (Kannan, 1990). 1. Correcting Deficiencies The measures for correcting micronutrients are summarized in Table XI. This information includes concentrations of nutrients for soil and foliar spray applications. The concentrations listed are approximate and may vary depending on original soil level, crop species/cultivar, crop yield desired, and climatic conditions. Issues related to soil and foliar fertilization of micronutrients and correcting their deficiencies in soil and plants have been discussed (Martens and Westermann, 1991; Mortvedt, 1991, 2000). Crop recovery of micronutrients is relatively low (5 to 10%) compared to that of macronutrients (10 to 50%) because of poor distribution from low rates applied, fertilizer reactions with soil to form unavailable products, and low mobility in soil (Mortvedt, 1994). The principal sources of micronutrient fertilizers used have been listed in Table XII. Boron is usually applied at 0.25 to 3 kg ha−1, and higher rates are required for broadcast than for band application or foliar sprays (Mortvedt and Woodruff, 1993). Legumes and certain root crops require 2 to 4 kg B ha−1, while lower rates are usually necessary for maximum yields of other crops (Martens and Westermann,

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Table XI Methods of Correcting Micronutrient Deficienciesa Corrective measure Element B Cl Cu

Fe

Soil applicationb 0.25–7 kg borax ha−1 (soil application preferred) 20–50 kg KCl ha−1 1–20 kg CuSO4 ha−1 (every 5–10 years)

Zn

30–100 kg FeSO4 or FeEDDHA ha−1 (need annual treatment of 0.5–10 kg ha−1) 5–50 kg Mn source ha−1 (soil application not recommended) 0.01–1 kg Mo source ha−1 (0.3 Na or NH4 molybdate ha−1) or lime to pH 6.5 0.5–35 kg ZnSO4 or ZnEDTA ha−1

Ni Co

Usually not needed 1–6 kg Co source ha−1 (broadcast)

Mn Mo

Foliar applicationc 0.1–0.25% B solution or 1–10 kg B ha−1 Unknown 0.1–0.2% solution CuSO4·5H2O or 0.1–4.0 kg Cu ha−1 as CuCl2·2H2O, CuSO4·5H2O, or CuO 2% FeSO4·7H2O or 0.02–0.05% FeEDTA solution (several sprays needed) 0.1% MnSO4·H2O solution or 0.3–6 kg Mn ha−1 0.07–0.1% Na or NH4 molybdate (100 g Mo ha−1) 0.1–0.5% ZnSO4·7H2O solution (0.17–1.5 kg ha−1) May be applied as spray 500 mg Co L−1 solution or 500 mg Co kg−1 seed treatment

a From Bould et al. (1983), Fageria, Baligar, and Jones (1997), and Martens and Westermann (1991). b Lower values for soil applications are applicable for band application and higher values are for broadcast applications. c 400 liters of solution is sufficient to spray 1 ha of field crop.

1991). Using the concept of Ca/B ratios, the application of foliar (0.3%) or soil (10 kg ha−1) B ensured adequate B (Moraghan and Mascagni, 1991). Borax or other soluble borates are usually applied to soil before planting. Boron fertilizer should not be placed in contact with seeds or at levels that may be toxic to crops. Boron availability commonly decreases during drought and when acid soils are limed (Martens and Westermann, 1991). Even though Cl has been recognized as essential to plants, comparatively little attention has been given to Cl as a fertilizer because soil levels from inputs and rain are considered adequate to meet crop requirements. Chlorine may become limiting for high yields in intensive production practices. Positive yield responses were noted for application of 400 kg Cl ha−1 for maize (Heckman, 1995). Winter wheat yields were also increased with Cl applications at seven of nine experimental sites (Engel et al., 1994). Only a few land areas are deficient in Cl, and crops grown

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FAGERIA et al. Table XII Principal Sources of Micronutrient Fertilizers to Correct Deficienciesa

Element B

Cl

Cu

Fe

Mn

Mo

Zn

Source

Formula

Boric acid Borax Na borate (anhydrous) Na pentaborate Na tetraborate Boron frits K chloride Zn chloride Ca chloride Mn chloride

H3BO3 [B(OH)3] Na2B4O7·10H2O Na2B4O7 Na2B10O16·10H2O Na2B4O7·5H2O Fritted glass KCl ZnCl2 CaCl2 MnCl2

Cu sulfate (monohydrate) Cu sulfate (pentahydrate) Cu chloride Cuprous oxide Cupric oxide Cu chelate Cu chelate Ferrous sulfate (monohydrate) Ferrous sulfate (heptahydrate) Ferrous ammonium sulfate Ferric sulfate Fe chelate Fe chelate Fe chelate Fe chelate Fe frits Mn sulfate (anhydrous) Mn sulfate (tetrahydrate) Mn chloride Mn carbonate Mn oxide Mn chelate Mn frits Na molybdate Ammonium molybdate Mo trioxide Molybdic acid Mo frits Zn sulfate (monohydrate) Zn sulfate (heptahydrate) Zn chloride Zn oxide Basic Zn sulfate

CuSO4·H2O CuSO4·5H2O CuCl2 Cu2O CuO Na2CuEDTA NaCuHEDTA FeSO4·H2O FeSO4·7H2O (NH4)2SO4·FeSO4·6H2O Fe2(SO4)3·4H2O NaFeEDTA NaFEHEDTA NaFeEDDHA NaFEDTPA Fritted glass MnSO4 MnSO4·4H2O MnCl2 MnCO3 MnO Na2MnEDTA Fritted glass Na2MoO24·2H2O (NH4)6Mo7O24·4H2O MoO3 H2MoO4·H2O Fritted glass ZnSO4·H2O ZnSO4·7H2O ZnCl2 ZnO ZnSO4·4Zn(OH)2

Element (%)

Solubilitya

17 11 20 18 14 1.5–2.5 48 52 64 44 35 25 47 89 75 13 9 33 19 14 23 5–14 5–9 6 10 2–6

Soluble Soluble Soluble Soluble Soluble Sl. solubleb Soluble Soluble Soluble Soluble Soluble Soluble Soluble Insoluble Insoluble Soluble Soluble Soluble Soluble Soluble Soluble Soluble Soluble Soluble Soluble Sl. soluble

23–28 26–28 17 31 41–68 5–12 2–10 39 54 66 53 0.1–0.4

Soluble Soluble Soluble Insoluble Insoluble Soluble Sl. soluble Soluble Soluble Sl. soluble Soluble Sl. soluble

36 23 48–50 50–80 55

Soluble Soluble Soluble Insoluble Sl. soluble continues

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Table XII—continued Element

Ni

Co

a b

Source Zn chelate Zn chelate Zn frits Ni chloride Ni nitrate Ni oxide Co sulfate Co nitrate

Formula Na2ZnEDTA NaZnEDTA Fritted glass NiCl2·6H2O Ni(NO3)2·6H2O NiO CoSO4·7H2O Co(NO3)2·6H2O

Element%

Solubilitya

14 9 4–9 25 20 79 21 20

Soluble Soluble Sl. soluble Soluble Soluble Insoluble Soluble Soluble

From Mortvedt (1991, 2000), and Martens and Westermann (1991). Slightly soluble.

on salt-affected soils often exhibit symptoms of Cl toxicity. Seed germination may be inhibited with high concentrations of Cl, so Cl fertilizers need to be applied in advance of planting (Bould et al., 1983). Copper deficiency can generally be corrected by applying 3.3 to 14.5 kg Cu ha−1 as broadcast CuSO4 (Martens and Westermann, 1991). The rates of banded CuSO4 required to correct Cu deficiency have been as low as 1.1 kg ha−1 for vegetables and as high as 6.6 kg Cu ha−1 for alfalfa, oat, and wheat. Copper deficiency can be corrected by banding or broadcasting Cu to soil or as foliar sprays. Lower rates of Cu application are required to correct Cu deficiency with banded compared to broadcast CuSO4. Foliar sprays are emergency measures, as Cu deficiency is most frequently corrected by soil applications (Murphy and Walsh, 1972) which are more effective than foliar sprays (Solberg et al., 1993). Soil application of CuSO4 is usually more effective than CuO, and Cu might need frequent applications when problems persist (Karamanos et al., 1986). The differences in the rates of Cu required to correct Cu deficiency vary with soil properties, crop requirement, and concentrations of extractable soil Cu. In semiarid regions, drying of top soil reduces Cu availability. Iron deficiency is corrected mainly by foliar sprays because soil applications are generally ineffective unless very high rates are applied. Typical Fe compounds used for foliar application to crops are FeSO4, Fe(NO3)2, and FeDTPA, and a 200 kg ha−1 FeSO4 rate was required to obtain maximum yields of annual crops (Mortvedt, 1991). More than one foliar spray and often three to four are needed during vegetative growth periods to obtain optimum production of crops like sorghum, soybean, and rice. Tree injection with ferric ammonium citrate (8% Fe) and seed treatment with FeEDDHA have had limited success in correcting Fe deficiency. Inorganic Fe sources applied to soils are rapidly converted to unavailable forms (oxidation of Fe2+ to Fe3+) in well-aerated soils, especially as soil pH increases. In Oxisols from central Brazil, Fe deficiency on upland rice was frequently reported where soil had been limed to pH ∼ 6 for the production of common bean

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and soybean in rotations (Fageria et al., 1994). Synthetic Fe chelates are generally the most effective Fe sources for soil and foliar applications, but their cost may be prohibitive. A common source of Fe applied to annual crops is FeSO4, but Fe chelates may be cost-effective if crops are of high value (fruits and berries). Fritted materials are sometimes used in acid soils to maintain Fe for plants (Martens and Westermann, 1991). A common source of Mn applied to soils and as foliar sprays is MnSO4. Soybean and rice commonly develop Mn deficiency during their growth on many soils. Optimum soybean yields were obtained with MnSO4 broadcast (14 kg ha−1) and band (3 kg ha−1) applied, and Mn deficiency was corrected by broadcasting MnSO4 (11 kg ha−1) or banding at half that rate or by timely foliar applications (1–2 kg ha−1) (Hatfield and Hickey, 1981). In other studies, 10 to 40 kg MnSO4 ha−1 was required to achieve maximum soybean yields (Anderson and Mortvedt, 1982). Manganese deficiency on soybeans grown in a Brazilian Cerrado Oxisol at pH 6.7 was corrected with applications of 15 mg MnSO4 kg−1 soil (Novais et al., 1989). Manganese deficiency on rice grown in a drained Histosol at pH ∼ 7 was alleviated with soil applications of ∼15 kg MnSO4 (Snyder et al., 1990). Seed applications of Mn also prevented Mn deficiency and provided near-maximum grain yields, and banded MnSO4 with seed has been equally as effective as sprayed Mn. Soil applications of Mn with acid-forming macronutrient fertilizers in neutral to high pH soils generally increase Mn effectiveness, and Mn deficiencies on plants grown in acid soils may be avoided by not over-liming. Both MnSO4 and MnO were effective as sources of Mn at rates of 20 kg Mn kg−1 for correcting Mn deficiency on soybeans grown in an Oxisol at pH 6.9 (Abreu et al., 1996). Chelated Mn (MnEDTA), MnSO4, and mangasol were equally effective for alleviating Mn deficiency on lupine (Brennan, 1996). Foliar applications of MnSO4 are effective for small grain cereals grown in calcareous and alkaline soils, which tend to dry during the growing season (Reuter et al., 1973). Soybean receiving 1.12 kg MnSO4 foliar sprays during early growth stages (V6) and again during late growth stages (R1) had higher yields than plants receiving single early sprays (Gettier et al., 1985). Multiple applications of foliar MnSO4 are usually superior to single applications on soybean (Cox, 1968). Molybdenum deficiency can be corrected by soil and foliar applications and by seed treatments. Since the availability of Mo increases as soil pH increases, liming acid soils to pH 6.5–7.0 will frequently prevent or correct Mo deficiencies (Martens and Westermann, 1991). The application of 0.01 to 0.5 kg Mo ha−1 will generally correct Mo deficiency. Sodium and/or ammonium molybdates are suitable sources for soil applications. Foliar applications of Mo have usually been more effective than soil applications for crops grown under dry conditions (Martens and Westermann, 1991). Foliar applications of 40 g Mo ha−1 increased bean growth and shoot N concentrations (Viera et al., 1998). High rates of seed-treated Mo

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could be toxic to rhizobia or my induce seedling injury (Sedberry et al., 1973). Even though excess Mo applications could lead to Cu deficiencies in animals (“molybdenosis”), this hazard is low since most Mo becomes relatively insoluble in well-drained soils (Martens and Westermann, 1991). Zinc deficiency can be corrected by either foliar or soil applications of ZnSO4 or ZnEDTA (Martens and Westermann, 1991). Foliar Zn is usually applied in emergencies to salvage crops when Zn deficiencies appear, and one foliar application is usually not adequate for correcting moderate to severe Zn deficiency. Maximum grain yields were obtained with foliar applications of ∼1 mg Zn kg−1 during the third and fourth weeks after plant emergence for maize grown in an Oxisol in central Brazil (Galr˜ao, 1994, 1996) and with 6 mg Zn kg−1 soil for upland rice grown in a greenhouse (Barbosa Filho et al., 1990). Applications of Zn either by broadcast or band usually are more effective than foliar applications (Murphy and Walsh, 1972). Zinc deficiency is common on land where subsoils have been exposed after land leveling, and these normally receive applications of farmyard manure to alleviate deficiencies and improve soil conditions (Martens and Westermann, 1991). Nickel is ubiquitous in soils, and most P fertilizers contain sufficient Ni for plant productivity, so Ni is not usually applied to soils. However, foliar applications have corrected Ni deficiency (Chamel and Newmann, 1987). Cobalt deficiency is usually controlled by soil broadcast applications (0.4 to 6 kg Co ha−1), foliar applications (500 mg Co L−1), and seed treatments (500 mg Co kg−1) (Raj, 1987; Reddy and Raj, 1975). Both sulfate and nitrate salts of Co have been used as fertilizers. 2. Residual Effects Knowledge concerning residual effects of applied micronutrient fertilizers is important to make sound and economic recommendations for succeeding crops. Micronutrient fertilizers have longer residual effects in high silt and clay than in sandy soils. Slightly soluble materials also have longer residual effects than highly soluble materials. Crop yields also determine residual micronutrient effects in soil. Information about long-term micronutrient effects is limited. Since crop recovery of micronutrients is relatively low, long-term residual effects might be expected. Broadcast applications of 2 kg B ha−1 as Borate-65 to a loam soil provided sufficient B for alfalfa and red clover for 2 years (Gupta, 1993). Recommendations for correcting Cu deficiency indicated a relatively high residual availability of applied Cu. For example, residual Cu was effective for 5 to 8 years after application for several crops (Martens and Westermann, 1991). Soil applications of Fe sources usually have no or only limited residual effects, since Fe2+ is rapidly converted to Fe3+ in aerated soils. Band applications of Fe at relatively high rates may be effective for more than 1 year provided tillage operations do not mix fertilizer

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with surrounding soil (Martens and Westermann, 1991). Manganese applied at 20 to 40 kg ha−1 to a sandy loam soil produced maximum soybean yields, but this Mn was insufficient to alleviate deficiency the next year (Gettier et al., 1984). However, optimum soybean yields occurred 2 years after broadcasting 30 kg Mn ha−1 on a clay loam soil (Mascagni and Cox, 1985). Residual effects have usually been higher for MnSO4 than for MnO (Abreu et al., 1996). The results regarding residual effects of Mo fertilization showed that effectiveness decreased ∼50% per year in some soils (Barrow et al., 1985). Broadcast applications of 34 kg ZnSO4 ha−1 were adequate to correct Zn deficiency on maize for 4 to 5 years, but banded Zn had to be applied at 6.6 kg ha−1 for ∼5 years to assure adequate residual Zn (Frye et al., 1978). Economical and long-term residual effects were also obtained for soil applications of Zn on wheat (Yilma et al., 1997).

C. PLANT IMPROVEMENT The steady increases in yields of major crops during the last half-century have been achieved through genetic improvement and improved management practices. The selection of improved genotypes adapted to wide ranges of climatic differences has contributed greatly to the overall gain in crop productivity during this time. In spite of these advances, mean yields of major crops are normally two- to fourfold below recorded maximum potentials (Baligar and Fageria, 1997). Newly developed genotypes of rice, maize, wheat, and soybean have been more efficient in the absorption and utilization of micronutrients compared to older cultivars (Clark and Duncan, 1991; Fageria, 1992). (See Table XV for scientific names of plant species.) The accumulation of micronutrients varies among plant species and cultivars/ genotypes within species (Marschner, 1995; Welch, 1986). Such differences among plant species/cultivars have been attributed to genetics, physiological/biochemical mechanisms, responses to climate variables, tolerance to pest and diseases, and responses to agronomic management practices. Genetic variations in plant acquisition of micronutrients have been reviewed (Brown et al., 1972; Duncan, 1994, Duncan and Carrow, 1999; Gerloff and Gabelman, 1983; Graham, 1984; Marschner, 1995). The development of genotypes/cultivars effective in the acquisition and use of micronutrients and with the desired agronomic characteristics is vital for improving yields and achieving genotypic adaptation to diversified environmental conditions and increased resistance to pests (Baligar and Fageria, 1997; Duncan, 1994; Graham, 1984). Plant and external factors affecting micronutrient use by plants and mechanisms and processes influencing genotypic differences in micronutrient efficiency have been summarized (Table XIII and Table XIV). Plant species differ considerably for B requirements and tolerance to deficient and toxic levels of B in soil (Fixen, 1993; Gupta, 1979; Rerkasem and Loneragan,

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Table XIII Plant and External Factors Affecting Micronutrient Use by Plantsa Plant factors

External factors

Genetic control Species/cultivar/genotype

Agronomic management practices Liming Crop rotation Incorporate crop residue, cover crops Soil Aeration/reducing conditions pH Organic matter levels and forms Temperature Moisture Status Texture/structure Compaction Fertilizers Source Timing, depth, method of placement, and application Use slow release form Elements Toxicities in acid (Al, Mn, pH) and saline (B, Cl) soils Deficiencies in acid (Cu, Zn, Mo) and alkaline (Zn, Fe, Mn, Cu) soils

Physiological Root length, density of main, laterals, and root hairs Higher shoot yield, harvest index, internal demand Higher physiological efficiency Higher nutrient uptake and utilization Excretion of H+, OH−, and HCO3− Biochemical Enzymes: rhodotorulic acid (Fe), ferroxamine b (Fe), ascorbic acid oxidase (Cu), carbonic acid anhydrase (Zn) Metallothionein (trace elements) Proline, aspharagine pinitol (salinity) Abscisic acid, proline (drought). Root exudates (citric, malic, transaconitic acids) Phytosiderophores Others Tolerance to stress (drought, acidity, alkalinity) Tolerance/resistance to diseases/pests Arial temperature, light quality, humidity

a

Others Arbuscular mycorrhizae, beneficial soil microbes Control weeds, diseases, and insects

Baligar and Bennett (1986a,b), Baligar and Fageria (1997), Duncan (1994), and Fageria (1992).

1994). Plants with high requirements for B are alfalfa, apple, red beet, turnip, cabbage, and cauliflower (NRC, 1980). Genotypic differences for tolerance to high B have been observed in wheat, barley, annual medic, and field peas (Nable and Paull, 1991; Paull et al., 1992). Such differences sometimes are related to restricted B uptake and transport. For example, the susceptibility to B deficiency in tomato was due to the lack of plant ability to transport B from roots to shoots (Brown et al., 1972). The genetic variability for B uptake and leaf concentration was noted for maize (Gorsline et al., 1968). Sensitivity to high Cl concentrations varies widely among plant species and cultivars (Eaton, 1966), but Cl toxicity is more extensive worldwide than Cl deficiency,

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FAGERIA et al. Table XIV Soil and Plant Mechanisms and Processes and Other Factors Influencing Genotypic Differences in Micronutrient Efficiency in Plants Grown under Mineral Stressesa

Nutrient acquisition Diffusion and mass flow in soil: buffer capacity, ionic concentration and properties, tortuosity, moisture, bulk density, temperature Root morphological factors: number, length, extension, density, root hair density Physiological: root/shoot ratio, root microorganisms (rhizobia, azotobacter, mycorrhizae), nutrient status, water uptake, nutrient influx and effux, nutrient transport rates, affinity for uptake (Km), threshold concentration (Cmin) Biochemical: enzyme secretion (phosphatases), chelating compounds, phytosiderophores, proton exudate, organic acid exudates (citric, malic, trans-aconitic, malic) Nutrient movement in root Transfer across endodermal cells and transport in roots Compartmentalization/binding within roots Rate of nutrient release to xylem Nutrient accumulation and remobilization in shoots Demand at cellular level and storage in vacuoles Retransport from older to younger leaves and from vegetative to reproductive tissues Rate of chelation in xylem transport Nutrient utilization and growth Nutrient metabolism at reduced tissue concentrations Lower element concentrations in supporting structures, particularly stems Elemental substitution (Fe for Mn, Mo for P, Co for Ni) Biochemical: peroxidase for Fe efficiency, ascorbic acid oxidase for Cu, carbonic anhydrase for Zn, metallothionein for metal toxicities Other factors Soil factors Soil solution: ionic equilibria, solubility, precipitation, competing ions, organic ions, pH, phytotoxic ions Physiochemical properties: organic matter, pH, aeration, structure, texture, compaction, moisture Environmental effects Intensity and quality of light (solar radiation) Temperature Moisture (rainfall, humidity, drought) Plant diseases, insects, and allelopathy a

From Baligar and Fageria (1997), Baligar et al. (1990), Duncan and Baligar (1990), Fageria (1992), and Gerloff (1987).

particularly in arid and semiarid regions. Plant tolerance to Cl has reported strawberry and pea to be very sensitive; lettuce, onion, maize, apple to be moderately sensitive; potato, cabbage, cauliflower, wheat, and ryegrass to be slightly tolerant; and red beet, spinach, rape and barley to be highly tolerant (Marschner, 1995). The genotypic differences in tolerance to Cu and other heavy metals are well known in certain species and ecotypes of natural vegetation (Woolhouse and

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Table XV Common and Scientific Names of Plant Species Mentioned in Text Alfalfa Amaranth, purple Apple Avocado Banana Barley Bean, broad/common/navy Bean, faba Bean, mung Beet, red and sugar Bluestem, big Cabbage Carrot Cauliflower Celery Chickpea Citrus Clover, red Clover, subterranean Clover, white Cotton Cowpea Cucumber Fescue, red Grape Lentil Lettuce Lupine, white Maize Mango Medic, annual (black) Millet, pearl Oat Onion Orchard grass Palm, oil Pea, common/field Peach Peanut (groundnut) Pear Pecan Pepper Potato, white Potato, sweet Radish

Medicago sativa L. Amaranthus cruentus L. Malus domestica Borkh. Persea americana Miller Musa paradisiaca L. Hordeum vulgare L. Phaseolus vulgaris L. Vicia faba L. Vigna radiata L. Beta vulgaris L. Andropogon gerardii Vitman Brassica oleracea var. capitata L. Daucus carota Hoffm. Brassica oleracea var. botrytis L. Apium graveolens L. Cicer arietinum L. Citrus spp. Trifolium pratense L. Trifolium subterraneum L. Trifolium repens L. Gossypium hirsutum L. Vigna unguiculata L. Walp. Cucumis sativus L. Festuca rubra L. Vitus vinifera L. Lens culinaris Medikus Lactuca sativa L. Lupinus albus L. Zea mays L. Mangifera indica L. Medicago spp. (Medicago lupulina L.) Pennisetum glaucum L. R. Br. Avena sativa L. Allium cepa L. Dactylis glomerata L. Elaeis oleifera Kunth Pisum sativum L. Prunus persica L. Arachis hypogaea L. Pyrus communis L. Carya illinoensis Wangenh. Capsicum annuum L. Solanum tuberosum L. Ipomoea batatas L. Raphanus sativus L. continues

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FAGERIA et al. Table XV—continued

Rape Rice Rutabaga/swede Rye Ryegrass, annual Sorghum Soybean Spinach Sugarcane Sunflower Swede/rutabaga Tobacco Tomato Turnip Wheat

Brassica napus L. Oryza sativa L. Brassica napus var. napobrassica Secale cereale L. Lolium multiflorum Lam. Sorghum bicolor (L.) Moench Glycine max (L.) Merr. Spinacia oleracea L. Saccharum officinarum L. Helianthus annuus L. Brassica napus var. napobrassica Nicotiana tabacum L. Lycopersicon lycopersicum (L.) Karsten Brassica rapa L. Triticum aestivum L.

Walker, 1981). It has been known for a long time that special flora (metallophytes) with a high tolerance to metals, including Cu, develop on outcrops of many contaminated mining sites (Marschner, 1995). The differences among plant species/cultivars for resistance to Fe deficiency and toxicity are extensive (Clark and Gross, 1986). Some plant species sensitive to Fe deficiency are apple, avocado, banana, citrus, grape, peach, pecan, bean, peanut, potato, sorghum, and soybean (Chen and Hadar, 1991). The differences among genotypes for Fe deficiency occur because of many physiological and biochemical differences. The recent classification of plants for differences in resistance to Fe deficiency has been categorized as Strategy I or Strategy II plants (R¨omheld and Marschner, 1986). That is, genotypes possessing Strategy I responses increase Fe solubility and uptake from the rhizosphere by enhanced reduction of Fe3+ to Fe2+, increased root H+ efflux and ATPase pumps to lower pH, increased root release of reductants capable of reducing Fe3+ to Fe2+, and increased production of organic acids, particularly citric and phenolics (Hughes et al., 1992). Most dicotyledonous and monocotyledonous plants, except those of the Poaceae (grass) family, exhibit these Fe deficiency stress traits. Genotypes of Poaceae exhibit Strategy II responses which are characterized by the production and release of Fe-solubilizing compounds (phytosiderophores) which complex sparingly soluble Fe3+ and make it available to plants (Hughes et al., 1992). Brown and Jolley (1988) and Jolley et al. (1996) extensively addressed mechanisms affecting Fe availability in different species of crops and plant physiological responses for genotypic evaluation of Fe efficiency associated with Strategy I and Strategy II plants. Selecting and breeding plants with resistance to Fe deficiency have been important for adapting plants for production on many Fe-deficient soils (Chen and Barak, 1982; Clark and Duncan, 1991, 1993; Clark et al., 1990; Rodriquez de

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Cianzio, 1991). The control of Fe deficiency is complicated in some plant species (multiple genes) and relatively simple in others (two genes), and good progress of achieving Fe deficiency resistance in some plant species has been made (Clark and Duncan, 1991, 1993; Clark et al., 1990). Improved germplasm for Fe deficiency has been released for bean, soybean, oat, and sorghum, with considerable progress being achieved with peanut, clover, bluestem grass, pepper, citrus, mango, and avocado (Rodriquez de Cianzio, 1991). Audeber and Sahrawat (2000) reported that the Fe-tolerant lowland rice cultivar “CK4” owed its superior performance under Fe-toxic conditions partly to avoidance (less Fe accumulation in leaves) and tolerance (superior photosynthetic potential in the presence of absorbed Fe in the leaves). Further, they stated that these mechanisms can be enhanced further through the application of P, K, and Zn to soil. Genotypic differences to Mo deficiency/toxicity have been noted (Marschner, 1995), and Mo toxicity tolerance has been closely related to the differences in translocation of Mo from roots to shoots (Marschner, 1995). Plant species and cultivars within species differ considerably in susceptibility to Mn deficiency when grown in low Mn soils (Marschner, 1995). Mechanisms responsible for cultivar differences for resistance to Mn deficiency are not known, but Marschner (1995) speculated that Mn oxidation/reduction reactions in the rhizosphere by roots and microorganisms were involved. Root exudates enhance the reduction of Mn oxides (Godo and Reisenauer, 1980). Both Mn deficiency and toxicity are common among plant species, and wide differences among plant species for resistance/tolerance to low and high Mn have been reported (Foy et al., 1988; Martens and Westermann, 1991; Reuter et al., 1988). Maize and rye are very susceptible to Mn deficiency, but oat, wheat, soybean, and peach are not (Reuter et al., 1988). The genotypic ability to tolerate Mn deficiency has been associated with root geometry, root excretion of substances (H+, reductants, Mn-binding ligands, microbial stimulants) to mobilize insoluble Mn, rates of Mn absorption at low soil Mn levels (low Km and high Vmax values), internal redistribution of Mn, and internal utilization or lower functional Mn requirements (Graham, 1984). Greater ranges of Mn in foliage of different plant species growing in the same soil were noted compared to Cu, Zn, and Fe, and these differences were attributed to species ability to acidify rhizosphere soil rather than with an internal Mn requirement (Gladstone and Loneragan, 1970). Genotypic differences were related to Mn acquisition from soil by rye and wheat (Marschner, 1988) and to geographic origin for barley (Graham, 1984), and not to differences in plant internal utilization and requirement. Some plant species grown in acid soils are more sensitive to Mn toxicity than others, and species differences to Mn toxicity have been reported for subterranean clover, bean, rice, tobacco, orchard grass, cotton, cowpea, apple, amaranth, and red fescue (Foy et al., 1988). Plants that are sensitive to Mn toxicity include cotton, field beans, alfalfa, cabbage, small grains, sugar beets, and pineapple (Martens

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and Westermann, 1991). Differential tolerance for Mn toxicity in plants has been associated with the oxidizing power of roots, uptake and rate of translocation from roots to shoots, entrapment of Mn in nonmetabolic centers, high internal tolerance to excess Mn, and distribution of Si, Cu, and Fe in tissue (Foy et al., 1988). Plant species/genotypes vary widely in resistance/tolerance to Zn-deficient or toxic soils (Graham and Rengel, 1993; Parker, 1997; Rashid and Fox, 1992; Takkar, 1993). The susceptibility of plants to Zn deficiency is high in cotton, bean, maize, and apple compared to pea, wheat, and oat. Maize, rice, lentil, chickpea, pea, and citrus are more sensitive to Zn deficiency than oilseed and cereal crops (Tiwari and Dwivedi, 1990). The differential responses among genotypes for Zn deficiency have also been reported for wheat, barley, oat, maize, sorghum, pearl millet, navy bean, potato, spinach, and soybean (Cakmak et al., 1997; Graham and Rengel, 1993; Takkar, 1993; Takkar and Walker, 1993). The differences in rice cultivars for Zn deficiency, especially those growing in high pH soil, were associated with the differences in susceptibility to HCO3− (Forno et al., 1975). Bicarbonate concentrations of 5 to 10 mM inhibited root growth of a “Zn-inefficient” rice cultivar, but stimulated root growth of “Zn-efficient” cultivars (Yang et al., 1994). Greater Zn acquisition in rice was casually related to the high HCO3− tolerance of roots (Yang et al., 1994). The differential susceptibility of common bean and soybean to Zn deficiency was associated with restricted translocation of Zn from roots to shoots (Ibrikci and Moraghan, 1993). The genotypic differences for “Zn efficiency” have been related to the effectiveness of absorption and translocation capacity of roots, ability of plants to avoid P toxicity when Zn deficiency occurs, root productivity of Zn mobilizing phytosiderophores, and production of seeds with high Zn contents (Graham and Rengel, 1993). Zinc deficiency is known to enhance the release of phytosideophores from roots of graminaceous species, and the release of phytosideophores by roots appears to be an adaptive response to Zn deficiency (Erenoglu et al., 2000). The rate of phytosiderophores released in triticale, rye, and bread wheat genotypes was not related to Zn efficiency or inefficiency. However, phytosiderophores had a role in Zn efficiency in barley cultivars, and it appears that phytosiderophores have a role in the solubility and mobility of Zn in the rhizosphere and within plant tissue (Erenoglu et al., 2000). The mechanisms associated with the differences for Zn deficiency operate in the soil as well as in the plant. Soil mechanisms for differential Zn at low levels include the differential ability of roots to sustain mycorrhizal infections, Zn mobilization and utilization, and Zn extraction from soil. Plant mechanisms include changes in rhizosphere pH, root uptake kinetics and transport, and root exudation of ion complexing and mobilization compounds (phytosiderophores). Crops also differ in susceptibility to toxic levels of Zn. In acid soils, most grasses (monocotyledons) are more tolerant than most dicotyledons, but this order is reversed for plants grown in alkaline soils, and leafy vegetables, legumes, and

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beet family plants are sensitive to high Zn while many dicotyledons tolerate toxic levels of Zn (Chaney, 1993). Bean and soybean cultivars also differ in tolerance to phytotoxic Zn (Chaney, 1993). Sugar beet and spinach are very susceptible to Ni toxicity, while barley, wheat, ryegrass, and broad bean are fairly resistant to Ni toxicity (Hewitt, 1983). The genotypic differences in tolerance to Co concentrations in shoots have been reported (Marschner, 1995).

D. MICROBIAL ASSOCIATIONS Beneficial soil microorganisms such as rhizobia, diazotrophic bacteria, and mycorrhizae may improve growth by enhancing atmospheric N2 fixation, suppressing pathogens, producing phytohormones, enhancing root surface areas to facilitate uptake of less mobile micronutrients, and mobilizing and solubilizing unavailable organic and inorganic mineral nutrients (Cattlelan et al., 1999; Marschner, 1995). Legumes would be unable to fix N2 without microorganisms like rhizobia, which have essential Co requirements (Ahmed and Evans, 1960). Many microorganisms produce siderophores, especially when grown under Fe deficiency conditions, which may enhance the plant acquisition of Fe (Crowley et al., 1987). Siderophores are large organic molecules [e.g., hydroxamates (amide functional groups) produced by fungi and bacteria and catecholates (aeromatic functional groups) produced by bacteria] that strongly and specifically bind metals, especially Fe3+ (Crowley et al., 1987; Germida and Siciliano, 2000; Lynch, 1990). Rhizosphere microorganisms may also be associated with differences among cultivars in their effectiveness to grow with low levels of some minerals. For example, a “Mn-efficient” wheat cultivar (high growth under Mn deficiency conditions) had a higher colonization of soil pseudomonads than “Mn-inefficient” cultivars, and a “Zn-efficient” cultivar had a higher colonization of nonpseudomonads than “Zn-inefficient” cultivars (Rengel et al., 1998). Mycorrhizal colonization of roots increases root surface areas to enhance root exploration of large soil volumes compared to uninfected roots and increases mineral nutrient uptake and plant tolerance to soil chemical constraints (acidity, alkalinity, salinity), toxic elements, and drought (Marschner, 1995). Mycorrhizal fungi and/or mycorrhizal roots have particularly increased acquisition of Cu, Fe, Mn, and Zn in plants grown under deficiency conditions (usually in alkaline soils) and decreased B, Fe, and Mn in plants grown under conditions where these minerals are excessive (usually in acidic soils) (Clark and Zeto, 2000; Marschner and R¨omheld, 1996). Mycorrhizae are also involved in the biological control of root pathogens and in nutrient cycling (solubilization, mineralization) (Marschner, 1995). Microbial interactions may also influence micronutrient mobility. Micronutrients react with microbial products (CO2, siderophores, organic compounds) and

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form microbial-mediated alterations in physical and chemical (pH, redox potentials) environments (Tate, 1987). Iron, Mn, and sometimes Cu are directly reduced by soil microbes or by soil humic acids (Tate, 1987). Several microbes involved in redox reactions in soil have been identified (Mullen, 1998). For example, Thiobacillus, Geobacter, Desulfovibrio, Pseudomonas, and Thiobacillus bacteria are involved in the oxidation of Fe2+ to Fe3+; Arthobacter, Leptothrix, Pseudomonas, and several other bacteria and fungi enhance oxidation of Mn2+ to Mn4+; and Bacillus, Geobacter, and Pseudomonas bacteria enhance Mn4+ reduction to Mn2+ (Paul and Clark, 1989). Noninfecting rhizosphere microorganisms may enhance plant micronutrient nutrition by improving growth and morphology of roots, physiology and development of plants, and micronutrient uptake processes by roots (Bowen and Rovira, 1991). Large numbers of microorganisms may enhance plant disease and insect infestations to reduce crop yields (Fageria, 1992; Lyda, 1981). Soilborne pathogens such as actinomycetes, bacteria, fungi, nematodes, and viruses lead to pathogenic stress and change the morphology and physiology of roots and shoots (Fageria, 1992; Fageria, Baligar, and Jones, 1997; Lyda, 1981). Such changes reduce plant ability to absorb and use micronutrients effectively. Diseases and insects mostly infect plant leaves (site of photosynthesis), and reduced photosynthetic activity results in a lower utilization of absorbed micronutrients (Fageria, 1992). Plant diseases are also greatly influenced by micronutrient deficiencies and/or toxicities (Huber, 1980). The severity of obligate and facultative parasites on plants is influenced by many micronutrients (Engelhard, 1990; Graham and Webb, 1991; Huber, 1980). The lack of Zn, B, Mn, Mo, Ni, Cu, and Fe in plant tissue can enhance various diseases on plants (Engelhard, 1990; Fageria, Baligar and Jones, 1997; Graham and Webb, 1991; Huber, 1980).

E. IMPROVED DISEASE AND INSECT RESISTANCE AND TOLERANCE Plant nutrition has always been an important component of disease control (Huber and Wilhelm, 1988). Mineral nutrients in plant tissue increase resistance by maximizing the inherent resistance of plants, facilitating disease escape through increased nutrient availability or stimulated plant growth, and altering external environments to influence survival, germination, and penetration of pathogens. Micronutrient concentrations in plants are important in host ability to resist or tolerate infectious pathogens. The tolerance of host plants to diseases is measured by the ability to maintain growth and/or yield in spite of infections (Turdgill, 1986). The resistance of the host plants is determined by plant ability to limit penetration, development, and/or reproduction of invading pathogens, and the resistance varies with species or genotype of the two organisms, plant age, and changes in the environment (Graham and Webb, 1991).

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The deficiencies of Cu, Fe, Mn, Mo, and Zn reduced growth and sporulation of the fungus Fusorium oxyspoum (Jones et al., 1990), while increased levels of soil Fe, Mn, and Zn benefitted the growth and sporulation of the pathogen. Take-all diseases of small grains from Gaeumannomyces graminis responded dramatically to the differences in micronutrient nutrition (Huber, 1990). Chlorine, Cu, Fe, Mn, and Zn in plants reduced take-all severity, while Mo increased disease severity. Adequate Cu and Mn could control white potato common scab caused by Streptomyces scabies, and Fe, Zn, and B had beneficial effects on reducing scab (Keinath and Loria, 1990). Boron sufficiency in plants reduced the incidence and severity of diseases, while B deficiency enhanced them. For example, brown-heart (water core) in radish and rutabaga roots, heart rot of beets, brown-heart rot of cauliflower, internal brown spot of sweet potato, and cracked stem of celery were enhanced when plants had insufficient B (Gupta, 1993). Boron sufficiency also reduced the incidence of club root in swede and other crucifers, fusarium in bean, tomato, and cotton, rhizoctonia infection in mung bean, pea, and cowpea, tobacco mosaic virus in bean and tomato, and yellow leaf curl virus in tomato (Graham and Webb, 1991). Chlorine tends to reduce the incidence of disease on many plants (Fixen, 1993; Marschner, 1995). For example, Cl particularly controlled stalk rot and northern leaf blight on maize, stripe rust and take-all on wheat, downy mildew on millet, and root rot on barley (Graham and Webb, 1991; Heckman, 1998). Powdery mildew and leaf rust diseases were suppressed in winter wheat with Cl applications at seven of nine experimental locations (Engel et al., 1994). Copper has been used extensively over time as a fungicide and suppresses many soilborne diseases. Soil applications of Cu decreased many fungal and bacterial diseases, including mildew on wheat and ergot on rye and barley (Graham and Webb, 1991). Iron decreased rust and smut infections on wheat and reduced Colletotrichum musae infections on banana, and foliar Fe sprays enhanced the resistance of apple and pear to Sphaeropsis malorum and tolerance of cabbage to Olpidium brassicae (Graham and Webb, 1991). Manganese increased the resistance and tolerance of plants to both root and foliar fungal and bacterial diseases. The effects of Mn on disease resistance occur over both Mn deficiency and sufficiency ranges of host plants (Graham and Webb, 1991). Manganese concentrations in host tissue commonly decrease as the incidence of disease increases, and the incidence of disease may be related to the reduced absorptive capacity of roots by pathogens and the immobilization of Mn by oxidation. Manganese availability in the rhizosphere and Mn concentrations in roots are important for manifestation of take-all severity. For example, increases in soil pH or using NO3–N versus NH4–N decreased the Mn availability and increased the take-all severity (Huber, 1990). Take-all on wheat was also reduced when seeds contained high compared to low Mn (McCay-Buis et al., 1995). Manganese was

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also effective in controlling other soilborne diseases such as potato common scab and verticillium wilt (Verticillum dahaliac) (Graham and Webb, 1991). Kleb wilt in cotton grown in acidic soil may be due to toxicity of Mn, Al, and possibly other acid soluble micronutrients (Bell, 1990). Even though the specific roles of Mo in protecting plants from diseases are unknown, the indications have been that Mo suppresses verticillium wilt in tomato (Graham and Webb, 1991). Zinc had decreased, increased, and no effects on plant susceptibility to diseases (Graham and Webb, 1991). Nickel salts were effective as fungicides against leaf and stem rusts on wheat (Graham and Webb 1991). The factors by which plants resist pests include physical (surface properties, hairs, color), mechanical (fibers, silicon), and chemical and/or biochemical (stimulants, toxins, repellants) properties (Marschner, 1995). Mineral nutrients can affect these factors to some degree. High amino acids in plants encourage the incidence of sucking parasites. Zinc deficiency can reduce protein synthesis which may lead to the high accumulation of amino acids. Negative relationships were noted between B contents in leaves of oil palm seedlings and attack by red spider mites (Rajaratnam and Hock, 1975). Boron was required for biosynthesis of cyanidin and was related to polyphenol production, which is involved in resistance against some insects (Marschner, 1995). Although Si has not been discussed as a micronutrient, high or adequate Si can restrict fungal and insect penetration of plant cells (and alleviate many diseases) to alleviate many insect and disease problems on plants (B´elanger et al., 1995; Epstein, 1994, 1999; Menzies and B´elanger, 1996; Savant et al., 1997, 1999). Silicon in epidermal cell walls acts as a mechanical barrier to insect and fungal attacks. The importance of Si in insect and disease resistance has been studied extensively in rice, sugarcane, and cucumber (B´elanger et al., 1995; Menzies and B´elanger, 1996; Savant et al., 1997, 1999).

VI. CONCLUSION The incidence of micronutrient deficiencies in crops has increased markedly in recent years due to intensive cropping, loss of top soil by erosion, losses of micronutrients through leaching, liming of acid soils, decreased proportions of farmyard manure compared with chemical fertilizers, increased purity of chemical fertilizers, and use of marginal lands for crop production. Micronutrient deficiency problems are also aggravated by a high demand of modern crop cultivars. Increases in crop yields from application of micronutrients have been reported in many parts of the world. Factors such as pH, redox potential, biological activity, SOM, cation-exchange capacity, and clay contents are important in determining the availability of micronutrients in soils. Further, root-induced changes in the rhizosphere affect the availability of micronutrients to plants. Major root-induced

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changes in the rhizosphere are pH, reducing capacity, redox potentials, and root exudates that mobilize sparingly soluble mineral nutrients. Root exudates may make elements like Fe more available, but they may also produce water-soluble metal chelating agents which reduce metal activity with roots. Compared to macronutrients, micronutrients are required for crop growth in lower amounts and serve mainly as constituents of prosthetic groups in metalloproteins and/or as activators of enzyme reactions. Micronutrients in crop production are important, and micronutrients deserve consideration similar to that of macronutrients. Micronutrient application rates range from 0.2 to 100 kg ha−1, depending on the micronutrient, crop requirement, and method of application. Higher rates are required for broadcast than for banded applications on soil or as foliar sprays. Because recommended application rates of micronutrients are low, most micronutrient sources are combined with macronutrient fertilizers for application to soil. This practice assures uniform micronutrient application. The development micronutrient-efficient and/or tolerant-resistant genotypes appears promising for improving future crop production. Additional information is needed to improve micronutrient recommendations, especially for determining long-term availability, and to evaluate macronutrient fertilizer effects on micronutrient availability. Considerable information about critical deficiency levels of micronutrients is available, but information about critical toxic levels is limited. Information about the interactions of micronutrients with other minerals is also needed.

ACKNOWLEDGMENTS The authors are grateful to Drs. V. D. Jolley, L. M. Shuman, D. C. Martens, G.Ba˜nuelos, and C. D. Foy for their critical review and valuable suggestions for the manuscript. We also thank Dr. L. W. Zelazny for providing information on major soil minerals containing micronutrients.

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Yilma, Z. A., Ekiz, H., Toran, B., G¨ultekin, I., Karanlik, S., Bagci, S. A., and Cakmak, I. (1997). Effect of different zinc application methods on grain yield and zinc concentrations in wheat cultivars grown on zinc deficient calcareous soils. J. Plant Nutr. 20, 461–471. Yoon, S. K., Gilmour, J. T., and Wells, B. R. (1975). Micronutrient levels in the rice plant young leaf as a function of soil solution concentration. Soil Sci. Soc. Am. Proc. 39, 685–688. Yoshida, S. (1981). “Fundamentals of Rice Crop Science.” International Rice Research Institute, Los Banos, Philippines. Yoshida, S., Ahn, J. S., and Forno, D. A. (1973). Occurrence, diagnosis, and correction of zinc deficiency of low land rice. Soil Sci. Plant Nutr. 19, 83–93. Yu, Z., and Bell, P. F. (1998). Nutrient deficiency symptoms and boron uptake mechanisms of rice. J. Plant Nutr. 21, 2077–2088. Yu, M., Hu, C., and Wang, Y. (1999). Influences of seed molybdenum and molybdenum application on nitrate reductase activity, shoot dry matter, and grain yields of winter wheat cultivars. J. Plant Nutr. 22, 1433–1441. Zaharieva, T. (1986). Comparative studies of iron inefficient plant species with plant analysis. J. Plant Nutr. 9, 939–946. Zaharieva, T., Kasabov, D., and R¨omheld, V. (1988). Response of peanuts to iron-manganese interaction in calcareous soil. J. Plant Nutr. 11, 1015–1024. Zaharieva, T., and R¨omheld, V. (1991). Factors affecting cation-anion uptake balance and iron acquisition in peanut plants grown in calcareous soils. In “Iron Nutrition and Interactions in Plants” (Y. Chen and Y. Hadar, Eds.), pp. 101–106. Kluwer Academic, Dordrecht, The Netherlands. Zhang, M., Alva, A. K., Li, Y. C., and Calvert, D. V. (1997a). Chemical association of Cu, Zn, Mn and Pb in selected sandy citrus soils. Soil Sci. 162, 181–188. Zhang, M., Alva, A. K., Li, Y. C., and Calvert, D. V. (1997b). Fractionation of iron, manganese, aluminum and phosphorus in selected sandy soils under citrus production. Soil Sci. Soc. Am. J. 61, 794–801. Zornoza, P., Robles, S., and Martin, N. (1999). Alleviation of nickel toxicity by ammonium supply to sunflower plants. Plant Soil 208, 221–226.

SOIL SCIENCE IN TROPICAL AND TEMPERATE REGIONS—SOME DIFFERENCES AND SIMILARITIES Alfred E. Hartemink International Soil Reference and Information Centre (ISRIC) 6700 AJ Wageningen, The Netherlands

I. Introduction II. Soil Science in Temperate Regions A. After the Second World War B. Funding and Scope III. Soil Science in Tropical Regions A. First Theories B. After the Second World War C. Inorganic Fertilizer Use D. Important Themes E. Number of Publications and Soil Scientists F. Myths about Soils in the Tropics IV. Diametrically Opposite Interests A. Soil Acidity B. Soil Nutrients V. Impact of Soil Science VI. Concluding Remarks References

Little has been written about geographical differences in the progress and development of soil science, whereas such information is of interest for determining research priorities and for an improved understanding of the impact of soil science in various parts of the globe. This paper reviews some of the differences and similarities in soil science of the temperate and tropical regions. It is largely based on Anglo–Dutch literature and focuses on soil fertility research. The range of conditions under which soils are formed is as diverse in the tropical as in the temperate regions, but soil science has a different history and focus in the two regions. In densely populated western Europe soil fertility research started because there was little spare land, whereas in the Russian Empire and the United States land was amply available and soil survey developed. Since the second World War, soil science has greatly benefited from new instrumentation and developments in other sciences. Many subdisciplines and specializations have been formed, and soil science has broadened its scope in the temperate regions. Currently, much research 269 Advances in Agronomy, Volume 77 Copyright 2002, Elsevier Science (USA). All rights reserved. 0065-2113/02 $35.00

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ALFRED E. HARTEMINK is externally funded and has a problem-solving character. Soil research in tropical regions started later, and its scope has not changed much. The feeding of the everincreasing population, land degradation, and maintenance of soil fertility are still important research themes. The amount of research in environmental protection, soil contamination, and ecosystem health is relatively small. More is known about the soil resources in the temperate regions than in the tropical regions despite the fact that one-third of the soils of the world are in the tropics, and these support more than three-quarters of the world population. Some of the common interests are the development of sustainable land management systems and appropriate land quality indicators, quantification of soil properties and processes, fine tuning of models, the sequestration of C in agricultural soils, and the optimum use of agricultural inputs to minimize environmental degradation and maximize profit. Nutrient surplus is a major concern in many temperate soils under agriculture, whereas the increase of soil fertility is an important research topic in many tropical regions. From a soil nutrient perspective it appears that soil fertility research in tropical regions is all about alleviating poverty, whereas in the temperate regions it is mainly about alleviating abundance and wealth. Although efforts have been undertaken to promote soil science to a wider audience, the impact of soil science on the society has been poorly quantified, and this applies to both temperate and tropical  C 2002 Elsevier Science (USA). regions.

I. INTRODUCTION The world would have been different if soil science had not emerged in the 19th century. It grosso modo applies to many—if not all—of the sciences, but for soil science its impact on society and the world at large has been poorly quantified. This is understandable, as it would be almost impossible to unravel the effect of different factors on the state of the world. Besides there are large regional differences. Soil studies are conducted in every agroecological region of the world, but soil science has mostly developed in the temperate regions. In tropical regions, soil science has followed its own path based on different needs and processes affecting soil conditions and plant growth. Sanchez and Buol (1975) summarized some of the differences and similarities between soils and their forming factors in tropical and temperate regions. Aside from the lack of a difference between summer and winter temperatures, the range of conditions under which soils are formed is as diverse in the tropics as in the temperate regions. Similar rock types occur, and also erosional and depositional patterns are similar. In both tropical and temperate regions the time of soil formation may range from very recent on alluvial plains or volcanic deposits to very old on stable geomorphic surfaces. Arid and humid as well as warm and cold climates occur in both temperate and tropical regions. Nevertheless the extent of

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certain soil types is very different. Pleistocene glaciation and wind erosion have had a great impact on the soils in the temperate region, whereas many more soils in the tropics have intensively weathered and are often derived from Precambrian parent materials. Although the extent of recent volcanic ash deposits is greater in the tropics, there is a larger proportion of relatively young soils in the temperate regions. Generalizations beyond these statements begin to lose accuracy (Sanchez and Buol, 1975), and generalizations have done much harm in the advancement of soil science in tropical regions (Lal and Sanchez, 1992). There have been several papers focusing on the developments in soil science in tropical or temperate regions (e.g., Greenland, 1991; Lal, 2000; Theng, 1991; Yaalon, 1997). Little has been written on a comparison of soil science in the temperate and tropical regions, whereas such information is of interest for determining research priorities and for an improved understanding of the impact of soil science in various parts of the world. This paper aims to partly fill the gap, and its objectives are (i) to compare some of the differences and similarities in soil science conducted in tropical and temperate regions, (ii) to give an overview of some recent trends in soil science of the temperate and tropical regions, and (iii) to discuss the impact of soil research in tropical regions. The review is largely based on an analysis of Anglo–Dutch literature and focused mainly on soil fertility aspects. The paper does not aim to present a detailed and historical review of soil science in the tropical and temperate regions, but highlights the main developments and some of the striking differences and similarities.

II. SOIL SCIENCE IN TEMPERATE REGIONS Practitioners of soil science could be roughly divided into those who made maps (pedologists, surveyors) and those who made graphs (the others). Such time has long gone, but the division had clear historical roots. At the beginning of the 20th century there were scientists studying soils in the field (agrogeologists), and there was a group studying soils in the laboratory who were often named agrochemists (van Baren et al., 2000). These groups were found in different parts of the world. In western Europe, there were limited possibilities for extending the agricultural area because the population was relatively dense. Research focused on the improvement of soil conditions in existing fields, e.g., the maintenance of soil fertility under continuous cropping. As a result, agricultural chemistry and the fertilizer industry developed in Europe. In other parts of the temperate region (United States and the Russian Empire) there were large areas of soils that could be used for agricultural expansion, and questions were centered on finding out what soils they had, how to select those responsive to management, and how to avoid wasted effort

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in farm development (Kellogg, 1974). There was a clear need for soil mapping and a better understanding of the concepts of the soils which resulted in the development of soil survey and soil genesis as subdisciplines of soil science. In the United States, soil science and in particular soil fertility research had a slower start than in Europe, as there was no urgency for maintaining the fertility and productivity of the soil—it was easier to move west (Viets, 1977).

A. AFTER THE SECOND WORLD WAR Early experiments with inorganic fertilizers were conducted in the mid-19th century at Rothamsted in England and in some other European countries. Acidulated phosphate rock and guano were mainly used, but in general, inorganic fertilizers were scarce in the 19th century. Inorganic fertilizers became widely used after the Haber–Bosch process had developed in Germany (Smil, 1999). It made fertilizers costs lower, and in addition new products were developed like nitrification inhibitors, new N compounds, coated fertilizers, and synthetic chelates (Viets, 1977). Inorganic fertilizer use in some selected European countries and in the United States is shown in Table I. In the Netherlands inorganic fertilizer use was already high at the beginning of the 20th century, but increased to almost 800 kg N, P2O5, and K2O per hectare in the mid-1980s. The rate of increase in fertilizer consumption in Germany and the UK was similar, but inorganic fertilizer consumption in the United States has been low compared to European countries. It should be borne in mind that these are national averages and that inorganic fertilizer use between states and agricultural sectors may vary greatly. A major development in soil fertility research took place after the second World War. Radioactive and heavy isotopes became available, and this was accompanied by the development of instrumentation like flame and atomic absorption spectrometers, emission and mass spectrographs, X-ray diffractometers and fluorescence, colorimeters, spectrophotometers, column and gas chromatographs, and Table I Inorganic Fertilizer Use in Some Selected European Countries and the United States in Different Periodsa

Germany Netherlands United Kingdom United States

1913

1936

1986

47 146 26 6

64 320 44 8

427 784 356 94

a Modified after Knibbe (2000). Values in kg nutrients (N, P2O5, K2O) per hectare y−1.

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computers (Viets, 1977). Advances in instrumentation allowed improved soil and plant tissue testing for better guidance of fertilizer use. Other developments which greatly aided soil fertility research were advances in statistical theory and designs of field experiments, theories on ion transport from the solid phase to the root surface, and the increased understanding of soil chemical and biological properties and processes. Traditionally, soil science in the temperate regions was concerned with agricultural production (Cooke, 1979). The feeding of the post-second-World-War baby boom demanded a large increase in agricultural production, which resulted indirectly in a leap in soil knowledge. In the 1960s food production exceeded demand, and surplus production followed; and at the height of the cold war the optimism and positivism of the 1950s gradually vanished. Conservationists and environmental groups drew attention to the widespread deterioration of the environment (e.g., Meadows et al., 1972). It brought about changes in the way the public and politicians looked upon agriculture and the environment. Since the 1970s rates of population growth have been declining in most temperate countries. Currently, the focus of attention is more on the problem of aging than on population growth per se (Tuljapurkar, 1997). Moreover overweight of the human population is a problem in many countries. The shift of attention meant new opportunities for soil science (Tinker, 1985), and soil scientists became involved in studies of nonagricultural land use, nature conservation, pollution, contamination, environment protection, soil remediation, and soils in urban environments. An increased emphasis was placed on the relationship between soil processes and water quality, and soil scientists became caught up in global and regional environmental issues (Wild, 1989) and learned to interact with ecologists, economists, and sociologists (Bouma, 1993). Consequently, the focus of soil science was broadened in the temperate regions resulting in the development of various subdisciplines and specializations. By its very nature soil science is an outdoor science, but with the introduction of the microcomputer, soil science has also become an office science where deskwork has increased, and this has occurred sometimes at the expense of laboratory and field work (Hartemink et al., 2001). An emphasis is placed on the use of previously collected data in combination with functional or mechanistic modeling and the development of risk scenarios. Field work concentrates on advanced realtime measurements of soil properties as required for the development of precision agriculture, which is likely to have a large impact (Schepers and Francis, 1998), although its potential in Europe is still under debate (Sylvester-Bradley et al., 1999). Invasive and noninvasive measuring techniques of soil properties require time before they will be fully developed, but progress has been made, particularly in the United States and Australia (Viscarra Rossel and McBratney, 1998). In western Europe there is perhaps more expertise in the environmental aspects and nonagricultural applications of soil science. Another major theme in the temperate regions

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is the role of soils as a sink and source of carbon in relation to global climate change (Lal, Kimble, Follet, and Stewart, 1998) and the development of quantitative techniques in soil science (McBratney et al., 2000; McBratney and Odeh, 1997).

B. FUNDING AND SCOPE Throughout past decades funding opportunities for fundamental soil research have been reduced (Mermut and Eswaran, 1997), and much soil research is externally funded with a strong problem-solving character. With this trend soil science has returned to where it started: little fundamental research and a main focus on adaptive research. There is some fear that this means that soil science will lose its dynamism and independence (Ruellan, 1997). Bouma (1998) finds, however, that the external funding trend should not be rigidly opposed, and he advocates research procedures where applied and basic research logically fit together in so-called research chains. Current soil fertility issues are integrated nutrient management systems aiming to minimize environmental pollution through leaching and denitrification. In a broader sense, research in soil fertility focuses on a reduction of the environmental impact of farming by reducing losses and conservation of fossil fuel energy. Other important factors are the breeding of cultivars tolerant to less favorable soil conditions or heavy polluted soil. Also mine site rehabilitation, bioremediation, and precision agriculture have become important in soil fertility research in temperate regions. Since the mid-1970s, modeling has become a major tool in the advancement of soil fertility research. There is growing interest in biological farming in many western European countries, and although it may have the potential to reduce the environmental impact of farming, it is generally perceived that biological farming cannot feed a rapidly growing population. There are large challenges ahead for soil science and in particular for soil fertility research in the temperate regions, e.g., the development of nutrient management systems, which are both environmental friendly and cost-effective. This need is the same for soil science and soil fertility research in the tropical regions, although the research focus is distinctly different.

III. SOIL SCIENCE IN TROPICAL REGIONS Little was known about tropical soils some 100 years ago. Travelers saw landscapes and vegetation that was never observed in any of the temperate regions, and many tried to comprehend the differences. Between the wars, significant soil research took place in, for example, Trinidad (F. Hardy), East Africa (G. Milne),

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and India (H. H. Mann). A useful overview of early investigations in tropical regions is given by Hilgard (1906). Considerable soil research was conducted in Indonesia (e.g., by E. C. J. Mohr) which included the mapping, chemistry, and formation of tropical soils. Systematic research started after the second World War following rapid developments in soil surveying and soil chemistry, and an overall increased interest ocurred in the natural resources of the tropics. The interest was mainly pedological, and many tropical soil science books were not concerned with the soil as a medium for plant growth (Moss, 1968; NAS, 1972; Nye and Greenland, 1960). Soil fertility was mainly the research terrain of the agronomist.

A. FIRST THEORIES The theory on the fertility of tropical soils has gone through a number of stages. In the late 1800s and early 1900s it was assumed that soil fertility in the humid tropics must be very high because it supports such abundant vegetation such as the rain forest. In the 1890s, the Deutsch Ost-Afrika Gesellschaft based their research station in Amani in the East Usambara mountains (Tanzania), as they thought that underneath the rain forest there must be abundantly productive soils (Conte, 1999). The point of view was fairly popular by tropical agriculturists and was prominently mentioned in the book of J. C. Willis (Willis, 1909), which ran through several editions during the first two decades of the 1900s. The American soil scientist E. W. Hilgard together with V. V. Dokuchaev, founder of modern pedology (Jenny, 1961), thought that soils of the humid tropics were rich in humus because of the abundant vegetation supplying plant material (Hilgard, 1906). Continuous and rapid rock and soil decomposition was thought to be high under the prevailing climatic condition, hence providing a constant supply of minerals for plant growth (Hilgard, 1906). Also Shantz and Marbut (1923) stated that the soil under the tropical rain forest is relatively fertile. It is not surprising that such views existed, since virtually nothing was known about tropical soils at the beginning of the 1900s, and generalizations existed widely. For example, it was thought there were four major soil types which occupied the cultivated area in India, although Hilgard (1906) mentioned that “. . . it is hardly to be expected that so large an area as that of India . . .could be even thus briefly characterized.” The high fertility theory was dispelled when the forest was cut and crops were planted, and it was discovered that yields were disappointingly low. In the subsequent period it was emphasized that soil fertility in the tropics was uniformly low and easily lost by cultivation (Jacks and Whyte, 1939). Travelers in the tropics noted that soils were lighter in color, and hence assumed that such soils had lower organic matter contents and chemical fertility. It is likely that these ideas about lower organic matter contents and soil chemical fertility are an aftermath of the 19th century humus theory, which was dispelled by Baron Justus von Liebig in the 1840s.

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B. AFTER THE SECOND WORLD WAR After the second World War, research emphasis was placed on the improvement of soil fertility by the judicious application of inorganic fertilizers. A very large number of inorganic fertilizer experiments were conducted from the 1950s onward (Greenland, 1994; Singh and Goma, 1995; Traore and Harris, 1995). These experiments focused on the search for balanced nutrition, the economics of fertilizers, credit, subsidies, and marketing of fertilizers, and fertilizer training programs and extension. Attention was focused more on the rate and balance of fertilizer application than on the identification of nutrient disorders. Following the food production decline in the 1960s, FAO launched in 1961 the Freedom From Hunger Campaign (FFHC) which was partly financed by the world fertilizer industry. The FFHC’s main target was to encourage the use of fertilizers by small-scale farmers through education and effective means of distribution and credit. The overall idea was that agricultural production cannot be significantly increased in the developing countries of the world without improving the nutrient status of most soils (Olson, 1970).

C. INORGANIC FERTILIZER USE The increased use of inorganic fertilizers in tropical regions was deemed necessary (i) to increase production per unit of land in the face of a growing shortage of arable land in many developing countries, (ii) to increase marketed food supplies or exports, and (iii) to raise incomes and return to labor (FAO, 1987). Furthermore inorganic fertilizers were needed to make full use of the new high-yielding varieties. The combined package of new crop varieties, pests and disease control, and the use of inorganic fertilizers caused a dramatic increase in crop yields in many parts of the tropics. There is no better summary than the “Fertilizer Guide for the Tropics and Subtropics” published in 1967 and 1973 containing over 5000 references to fertilizer trials throughout the tropics (de Geus, 1973). Locally it was noted that inorganic fertilizers had little or no effect due to crop husbandry practices (poor seedbed preparation, improper seeding, delay in sowing, etc.) or because of wrong fertilizer placement, unbalanced nutrient application, incorrect identification of nutrient limitations, or weed and insect problems. Obviously these factors were eliminated when inorganic fertilizer trials were conducted on a research station, but surfaced when fertilizers were used by subsistence farmers. As an overall result, inorganic fertilizers gave a poor profitability which affected the widespread use. Some of the inorganic fertilizers being used in the tropics were given as aid by the United States and western European countries. On the one hand this was meant to stimulate the use of fertilizers in tropical regions and increase crop production on the other hand European countries could maintain their fertilizer industry which

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suffered from the declining use of fertilizers by European farmers. It also meant that many of the aid funds were retained in Europe. In the 1970s an 1980s environmental concerns about inorganic fertilizers were rising. Excessive use of inorganic fertilizers can have devastating effects on water quality, and a well-known example is the proliferate growth of algae following enrichment with phosphates. In the Netherlands this was, however, mainly due to the use of phosphate in washing detergents and not so much due to the use of excessive amounts of P fertilizers. A second concern is the nitrate content of drinking water which is said to create health hazards for humans under specific conditions (Addiscott et al., 1991). Inorganic fertilizers have also been associated with the destruction of the ozone layer, as nitrous oxides resulting from denitrification can give rise to products which catalyze ozone destruction (Bouwman, 1998). In other words, inorganic fertilizers were regarded as environmentally damaging. Part of the public opinion was probably exaggerated and excessive as was the use of inorganic fertilizers by some farmers in western Europe. The negative image of inorganic fertilizers in the temperate regions probably had some effects on the use of fertilizers in the tropical regions, although the environmental consequences of the continued low use of fertilizers are more devastating than those anticipated from increased fertilizer use in the tropics (Dudal and Byrnes, 1993). The FFHC, which was replaced in the late 1970s by the FAO’s Fertilizer Programme, gradually ceased in the 1990s, and currently FAO has no such program. With few exceptions, large-scale and widespread inorganic fertilizer trials are no longer conducted. Instead of advocating the use of inorganic fertilizers, studies in the late 1980s and early 1990s focused on new arguments to justify the use of inorganic fertilizers. This was the case when nutrient balances were reintroduced as a research tool and widespread soil fertility decline and nutrient mining were being reported, particularly for sub-Saharan Africa (Smaling, 1993). Inorganic fertilizers are not only being advocated to correct the negative nutrient balance, but, integrated nutrient management is also advocated to improve the overall negative nutrient balance and the efficiency of nutrient use (Sanchez, 1994). Fertilizer use in some selected Asian countries is given in Table II. Although the consumption of inorganic fertilizer use is much lower than that in some European countries (Table I), the data show that the rate of increase has been high in Asian countries. The increase in inorganic fertilizers runs parallel with the increase in food production. It is interesting to note that inorganic fertilizer use in Asian countries is on average higher than that in the United States. Inorganic fertilizer use in sub-Saharan Africa countries is lower than 15 kg ha−1. Summarizing the soil fertility paradigms in tropical regions, it can be noted that in the late 1800s and early 1900s it was perceived that tropical soils were uniformly rich. This was followed by a period in which it was believed that tropical soils were of inherent low fertility and quickly lost by cultivation. After the second World War, research efforts largely focused on the use of inorganic fertilizers to overcome low

278

ALFRED E. HARTEMINK Table II Inorganic Fertilizer Use in Some Selected Asian Countries in Different Periodsa

India Indonesia Bangladesh Thailand Vietnam Pakistan

1968–1970

1983–1985

1993–1995

16 16 12 7 36 19

61 111 49 20 62 79

105 135 93 70 170 124

a Modified after Hossain and Singh (2000) based on FAO databases. Values in kg nutrients (N, P2O5, K2O) per hectare y−1.

soil fertility, and a large number of trials were conducted. In the period that followed it was found that inorganic fertilizers, were not widely used, and as a result, soil fertility is being mined leading to a declining agricultural productivity, which particularly applies to sub-Sahara Africa.

D. IMPORTANT THEMES In tropical regions, important soil science themes have not changed much in past decades, and soil science is still closely linked to agriculture and society at large. The feeding of the ever-increasing population, the decreasing food production per capita in some African countries, and soil degradation are as worthy themes today as they were 20 to 30 years ago. About 95% of the current population growth takes place in tropical regions, and a continuing increase in food production is required. Recently, some emphasis has been placed on nature conservation, in particular in relation to rain forests (biodiversity) and dry areas (desertification), but less in savannah areas. Increased contamination of soil and water environment is of particular concern in developing countries where both local industries and often foreign investors have shown a general lack of appreciation of the environment (Naidu, 1998). The amount of research in environmental protection, soil contamination, and ecosystem health is relatively small. Overall there has been an increase in process-oriented research, but the absolute amount is by no means comparable to that conducted in the temperate regions. Soil fertility research in tropical regions has, however, greatly benefited from developments in instrumentation and analytical techniques (Viets, 1977). More is known about soil resources in temperate regions than in tropical regions, despite the fact that one-third of the soils of the world are in the tropics (Eswaran et al., 1992), and these support more than three-quarters of the world population (Fischer and Heilig, 1997). There are a number of reasons that are discussed later,

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but first we will attempt to quantify the differences. Currently about 10,000 publications on soils appear in international and national journals each year (Hartemink, 1999). These are the publications in English only, but many more are written in other major languages in books, conference proceedings, and reports. In the late 1940s and 1950s there were about 1000 to 2000 soil science publications—so the number of soil science publications has greatly increased. This is due to the increase in the number of soil scientists (van Baren et al., 2000), an increase in the number of soil science and agronomic journals (Hartemink, 2000), and an increased pressure to publish, which also resulted in the recycling of ideas and manuscripts. Above all, it demonstrates the enormous increase in soil science knowledge, which is also reflected, for example, in the development of the book—“Soil conditions and Plant Growth” (Greenland, 1997) and the extensive “Handbook of Soil Science”(Sumner, 2000).

E. NUMBER OF PUBLICATIONS AND SOIL SCIENTISTS How many of journal publications deal with the tropics? Arvanitis (1994) estimated from French databases that about 22% of soil publications originate from the tropics. Yaalon (1989) mentioned that the share of all the Third World countries in soil research increased from 9 to 11% in 21 years. Searches through ISI’s databases showed that more publications appear on Australia than on the whole of Africa. On average there are five times more publications on the Netherlands than on Tanzania, whereas the population of Tanzania is twice as large as that of the Netherlands. Three times more publications originate from Europe as compared to Africa. On average there are 30 to 40 times more publications on cancer than on poverty, and twice as many publications on cancer than on soils. There is, however, a clear increasing trend in the number of publications about soil. The increase is on average 5% per year, which was also noted by Yaalon (1989), and found when other literature databases were analyzed (Hartemink, 1999). The difference in the number of publications on tropical soil research compared to soil research in the temperate regions is because, with some exceptions, soil research in the tropics started several decades later than in the temperate regions, and there are (and have been) fewer soil scientists with less advanced research facilities in tropical regions. Educational opportunities are also more limited in these regions. The amount of research funds differs largely between tropical and temperate regions, although exact figures are not available. In Africa the allocation of funds for agricultural research grew rapidly in the 1960s, moderately in the 1970s, and in general stagnated in the 1980s in most countries (Noor, 1998). Currently, developed countries spend on average about $200 a year per farmer on research and extension, whereas developing countries spend $4 (Young, 1998). Most developing countries face reduced funding and a wave of redundancies in the international research centers. There are no signs that the funding situation is

280

ALFRED E. HARTEMINK Table III Number of International Society of Soil Science Members for Different Continents in 1974 and 1998a 1974

Western Europe Eastern Europe +USSR/CIS Middle East Africa Asia Australia + New Zealand Latin America + Caribbean North America

1316 351 104 278 280 348 171 1110

Total

3958

a b

1998 (33)b (9) (3) (7) (7) (9) (4) (28)

2481 379 233 454 881 364 597 1653 7042

Difference 1974–1998(%) (35) (5) (3) (6) (13) (5) (8) (23)

+89 +8 +124 +63 +215 +6 +249 +49 +78

After van Baren et al. (2000) based on ISSS statistics. Percentage of total members is in parentheses.

improving, and, for example, the European Union reduced its contribution to the CGIAR system by U$16 million for the year 2000. The number of soil scientists has greatly increased in the past century, although regional differences are large (Table III). Between 1974 and 1998, the total number of members of the International Society of Soil Science (ISSS) increased by 78%, whereas over the same period the world population increased by 42%, from 4.14 to 5.86 billion. More than half of the ISSS members are based in western Europe and North America. Large increases in ISSS members were found in the Middle East, Asia and Latin America, and the Caribbean, in which the number of members tripled between 1974 and 1998. Few changes in membership were registered in eastern Europe/CIS. The total number of members in Australia increased from 243 to 312 between 1974 and 1998, but the number in New Zealand decreased from 105 to 52 over the same period (van Baren et al., 2000). There is a difference in the number of agricultural and soil scientists between tropical and temperate regions. In the 1960s, the number of research workers per 100,000 farm workers was about 1.0 in Cameroon, 1.2 in India, but 60 in Japan, and 133 in The Netherlands (Olson, 1970). In 1998, there were per 1000 km2 agricultural land about 0.5 soil scientists in India, 1.2 in Brazil compared to 2.8 in The Netherlands and 55.1 in Japan (Table IV). A large number of soil scientists are found in China, the United States, Brazil, and Japan. However, the number of soil scientists per million inhabitants was highest in New Zealand, Australia, Israel, and Spain. With some exceptions the data show that the total number of soil scientists as well as the number of soil scientists per million inhabitants or hectare agricultural land are commonly lower in tropical regions than in temperate regions. A criticism is that developed countries have paid little attention to the education of local soil scientists in tropical regions (Muchena and Kiome, 1995). With time

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Table IV Soil Scientists per Million Habitants and Agricultural Land in 1998 in Some Selected Countriesa

Country Australia Brazil Canada China, P.R. of France Germany India Israel Italy Japan Mexico Netherlands New Zealand South Africa South Korea Spain Thailand Turkey UK United States a

Total number of soil scientists

Soil scientists per million inhabitants

Soil scientists per 1000 km2 agricultural land

1,000 2,900 320 10,200 900 2,500 900 250 300 2,800 700 450 430 270 930 1,450 500 225 1,000 6,050

53.7 17.1 10.4 8.2 15.3 30.5 0.9 44.3 5.3 22.2 7.1 28.6 118.6 6.3 20.0 37.1 8.3 3.5 17.0 22.4

0.2 1.2 0.4 1.9 3.0 14.4 0.5 43.1 1.9 55.1 0.6 22.8 2.6 0.3 49.7 4.7 2.4 0.6 5.8 1.4

Modified after van Baren et al. (2000) based on ISSS statistics and agricultural databases.

the difference in the number of soil scientists may level out, as the number is declining in most countries of the temperate region. Changes in the number of soil scientists is of course directly related to the level of government funding. Arvanitis and Chatelin (1994) mentioned that the number of soil scientists in a country is probably inversely proportional to the pressures exerted on them. Soil scientists in the tropics are often required to conduct applied research in areas of direct national interest such as self-sufficiency and education, or they are even asked to participate actively in politics (Arvanitis and Chatelin, 1994).

F. MYTHS ABOUT SOILS IN THE TROPICS In addition to the quantitative aspects of the number of soil scientists and publications, there are other causes which have restricted the advancement of soil science in tropical regions. Overgeneralizations about soil in tropical regions have led to many misconceptions about its potential (Lal and Sanchez, 1992; Sanchez and Buol, 1975). There have been a number of myths, and the myth of rapid

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laterization under cultivation is probably best known. Up to the 1930s it was thought that the tropics were covered by laterite crust and lateritic soils, because a number of often-quoted writers on laterite had never been in the tropics (Prescott and Pendleton, 1952). Research in Indonesia and East Africa dispelled the theory, but it took many decades before it was fully dispelled from soil science literature (Lal and Sanchez, 1992). Other myths were that soils in the rain forest were extremely rich and able to support the abundance of vegetation, that shifting cultivation was a backward type of agriculture (FAO-Staff, 1957) accelerating the formation of laterite (Vine, 1968), that all soils in the tropics were highly erodible (Jacks and Whyte, 1939), that tropical soils were very low in organic matter (Ruthenberg, 1972), very old, and intensively weathered due to year-round high rainfall and temperatures. These misconceptions were largely eliminated by the works of, among others, Mohr and van Baren (1959), Nye and Greenland (1960), Kellogg (1963), Sombroek (1966), Sanchez (1976), Sanchez et al. (1982), and Greenland et al. (1992). Some misconceptions are hard to eliminate. For example, the concept of zonality introduced by the Russian school of pedology is still being used in some standard texts on tropical forests (Burnham, 1985) and tropical agriculture (Webster and Wilson, 1980; Wrigley, 1982) despite its abandonment in the 1940s (Smith, 1983). The lack of a universally used soil classification system also retarded the advancement of soil knowledge in tropical regions. For example, Latosols has a different meaning to different soil scientists, as it was used in both the national soil classification systems of Brazil and Indonesia. A tremendous effort has been made to develop soil classification systems, but it is unfortunate that the efforts have not resulted in something widely used and understood by nonsoil scientists or even nonpedologists. The World Reference Base for soil resources, which was presented at the 16th World Congress of Soil Science as the international soil classification system, might change the situation.

IV. DIAMETRICALLY OPPOSITE INTERESTS There are a number of common interests in soil research in temperate and tropical regions. In both regions it is recognized that sustainable land management systems need to be developed (Eger et al., 1996), and there is a search for appropriate land quality indicators (Doran and Parkin, 1996; Eijsackers, 1998). Another common interest is the sequestration of C in agricultural and forest soils (Lal, Kimble, and Follet, 1998) and the problems associated with global climate change. Tools and techniques developed in the temperate region are therefore of direct interest to soil science in the tropical regions, and some consider that soil science in developing countries should focus on soil technology adoption only (Yaalon, 1996).

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Nevertheless, it sometimes appears that soil science in temperate and tropical regions has diametrically opposite interests, and two striking examples are discussed here.

A. SOIL ACIDITY In upland soils in tropical regions soil acidity is a major problem which can have pedogenetic (parent material, age) or anthropogenic causes (ammonia-N fertilizers). The upland soils are nevertheless considered the largest remaining potential for future agricultural development (Theng, 1991; Von Uexk¨ull and Mutert, 1995). Several strategies to manage soil acidity have been developed in order to increase and sustain food production on these soils (Myers and de Pauw, 1995; Sanchez and Salinas, 1981). Research has focused not only on methods to increase the pH but also on the development of acid-tolerant crop cultivars (Sanchez and Benites, 1987). In temperate regions, it has been recognized since before Roman times that chalk or marl spread on acid soils improved their fertility, and this was widely used during the 18th century by the pioneers of the English agricultural revolution (Bridges and de Bakker, 1997). This practice lapsed when agricultural lime became available in the 19th century. So the soil acidity problem in the temperate regions was largely overcome through application of pH increasing substances over decades or even centuries. Research interest in soil acidity increased in the 1970s because of the problems associated with acid rain (Reuss and Johnson, 1986). Acid rain studies made many people aware that environmental problems cut across national borders. With falling emission and deposition of N and S (Jenkins, 1999), interest in soil and surface water acidification decreased, and climate change became the new focus of attention. Currently there is renewed interest in soil acidity because of the set-aside policy whereby agricultural land is taken out of production and restored to heathland or forest. In some soils in Scotland restoration to heathland meant that the pH, which was increased through many years of lime applications, had to be reduced by 2 to 3 units for which heavy applications of elemental sulfur were used (Owen et al., 1999). Set-aside problems are unknown in tropical regions where the need for more land has increased because of the growing population (Harris and Kennedy, 1999; Krautkraemer, 1994; Seidl and Tisdell, 1999). The only example from the tropics is the use of elemental sulfur in neutral soils at tea plantations, since tea requires a strongly acid soil (TRFK, 1986). Another example for the renewed interest in soil acidity comes from The Netherlands, where about 25,000 ha or 1% of the total area under agriculture was taken out of production between 1993 and 1996. When sandy soils previously under intensive horticulture with heavy applications of biocides were set aside and

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not cultivated, these soils naturally acidified. As a result mobile Cd originating from the biocides increased, and regular lime applications are needed to these soils to reduce the Cd solubility and mobility (Boekhold, 1992). It is an interesting example how nature restoration—not agriculture—brings to surface the so-called chemical time bomb.

B. SOIL NUTRIENTS Nutrient enrichment, particularly N and P, has occurred in many agricultural soils of western Europe, and nutrient management is a topic of major political interest (de Walle and Sevenster, 1998; Kuipers and Mandersloot, 1999). In most intensive crop and livestock production systems, the input of nutrients exceeds the output resulting in considerable mineral surpluses in the soil. Inorganic fertilizers are relatively cheap, and there is a large import of nutrients with stock feed resulting in more manure than can be spread on the land. Many of the problems in the intensive agricultural systems of western Europe are therefore structural rather than local and cannot easily be solved by transport of manure to other regions (de Walle and Sevenster, 1998). In the 1980s and 1990s, evidence has accumulated that nutrient depletion is a problem in many tropical soils (Dudal, 1982; Greenland, 1981; Lal, 1987; Pieri, 1989; Sanchez et al., 1997). The major cause is the drain of nutrients with the crop yield, erosion, and losses through leaching or denitrification, while little or no inorganic fertilizers are being used. Also the use of manure is insufficient to cover the drain of nutrients, and this shortage is further aggravated as livestock numbers generally decrease with increasing population. Thus, where the soil scientist in the temperate region is concerned with N leaching causing groundwater contamination and eutrophication of surface waters, soil scientists in tropical regions are concerned with leaching because of the loss of N for crop production. There is a common interest in reduction of nutrient losses, although the motives are diametrically opposed. Where in the temperate soils under intensive agriculture P saturation is a concern, the low levels in many tropical soils warrant a similar level of interests in the complex chemistry of soil P. And where the soil scientist in the temperate regions is interested in soil changes when the land is deliberately taken out of production and not cultivated, a key question in the tropics is how the soil can be kept productive when continuously cultivated, and what needs to be done to make, and keep, marginally suitable soils productive. The soil nutrient situation is even more deplorable if it is realized that in the intensive livestock production systems of the temperate region soils are being used as a dumping ground for nutrients, whereas some of these nutrients originate from tropical countries where many soils are chemically poor and few inorganic

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fertilizers are being used (Bouwman and Booij, 1998; van Diest, 1986). From a soil nutrient perspective it appears that soil fertility research in tropical regions is all about alleviating poverty, whereas in the temperate regions it is mainly about alleviating abundance and wealth. The soil appears as a fitting metaphor for the economic differences between the two regions.

V. IMPACT OF SOIL SCIENCE The understanding and knowledge of soils kept pace with the dramatic increase in population and enormous changes in global land use of the past 100 years. Despite this success, the general public has never been widely interested in soils, and there is a deep concern about the public profile and appreciation of soil science (White, 1997). It was noted that soil science goes through a period of reduced funding and public interest, and several conferences and committees were dedicated to the question of how soil scientists should cope with this situation (Mermut and Eswaran, 1997; Sposito and Reginato, 1992; Wagenet and Bouma, 1996). Most authors are optimistic and positive; for example, Mermut and Eswaran (1997) stated that “. . . we believe that the future of soil science is stronger than before and the demand for soil scientists will be greater than before.” Largely absent in these forward-looking publications is the future development of soil science in tropical regions. That is particularly unfortunate as less is known about tropical soils, and evident problems are evolving because of population pressure (Young, 1998). It is in the tropics where soil scientists can have the largest impact on society and where there is incomplete understanding of the soil and a paucity of hard information (Theng, 1991). Although it is generally accepted that soil science is of great importance, very little has been written about the contribution to knowledge and, hence, to society, arising from the scientific study of the soil (Greenland, 1991). This particularly concerns the impact of soil science in tropical regions, and much more is known about agricultural research and the role it has played in the advancement of agriculture and land use in Europe (Porceddu and Rabbinge, 1997). Many soil scientists are concerned by the lack of impact, and authoritative knowledge about soils has failed to reach many government administrators, financial organizations, planners, educational authorities, and land users who would most benefit from the knowledge (Bridges and Catizzone, 1996). Such impact is of course hard to measure directly, but Lal (1995) mentioned that it can be judged from agricultural and food production trends and from the use of science-based input. Much of the credit for the agricultural production increase has deservedly been given to the plant breeders, but demonstration of the importance of proper nutrient management and of the potential to intensify cropping systems and develop new lands was due to soil

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scientists. If it were not for soil scientists, Thomas Malthus would have been right according to Greenland (1991). The situation is different in different continents. In large parts of Asia agricultural productivity has increased largely due to new crop cultivars and other products from the Green Revolution (Table II). Food production in some African countries has been falling (Greenland, 1997; Pinstrup-Andersen, 1998), which could be because the Green Revolution had fewer inroads (Lappe et al., 1998). Or does it imply that soil scientists had limited impact in Africa? We do not know; but quite likely there would have been many more East African Groundnut Schemes if soil science had ignored Africa, although the failure of the scheme was an important stimulus to the use of soil surveys in development projects (Young, 1976). Muchena and Kiome (1995) discussed the role of soil science in agricultural development in East Africa and concluded that it has played a modest role. Unfortunately this role goes largely unquantified. They conclude that despite the activities of numerous foreign experts, there is still inadequate expertise in some key disciplines such as soil physics, land evaluation, and water management. More research is needed. However, a convincing plea for the increasing need for soil research in the tropics should not be based on areas where expertise is inadequate but on a quantitative analysis of the impact of soil science. That may be much needed since donors are less eager to fund soil research in the tropics, and large international organizations like FAO essentially stopped collecting soil data because of the lack of funds from the UNDP and bilaterals for field projects. In past decades, many national soil science institutes in tropical regions have emerged, but the need remains to maintain an active international soil science network for effective exchange of information and to cut costs. The developed world is reducing its willingness to contribute to the development of science in the tropical regions, and this may hinder the advancement of soil science in the tropical regions. A possible option to reverse this trend is to quantify the impact of soil science on development in tropical regions. There have been a number of initiatives to actively promote soil science, but too few studies have quantified the impact of soil science, and that, unfortunately, applies to both tropical and temperate regions.

VI. CONCLUDING REMARKS More is known about soil resources in temperate regions than in tropical regions, despite the fact that one-third of the soils of the world are in the tropics and support more than three-quarters of the world population. In addition, 95% of the population growth takes place in tropical regions. Therefore it is in the tropics that soil scientists can have a large impact on society, because there is an incomplete understanding of the soil and insufficient hard information.

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In temperate regions, the focus of attention is currently shifting to population aging, whereas in tropical regions the increasing population and the associated need to increase food production remain important subjects for soil science. Most attention needs to be given to yield increases, as there is limited potential for an expansion of the agricultural area in most tropical countries. Also environmental soil science in tropical regions needs to be further developed. Some of the common research interests in the temperate and tropical region are the development of sustainable land management systems and appropriate land quality indicators, quantification of soil properties and processes, fine tuning of models, sequestration of C in agricultural soils, and optimum use of agricultural inputs to minimize environmental degradation and maximize profit. Close cooperation on these subjects is of interest for soil science in both temperate and tropical regions. However, it seems that the developed world is reducing its willingness to contribute to the development of science in tropical regions, and this may hinder the advancement of soil science in tropical regions.

ACKNOWLEDGMENTS I am greatly indebted to Professor D. J. Greenland and Mr. J. H. V. van Baren, Mr. J. H. Kauffman, and Dr. W. G. Sombroek for comments on the draft of this paper.

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Smaling, E. M. A. (1993). An agro-ecological framework for integrated nutrient management with special reference to Kenya, Doctoral, Agricultural University, Wageningen. Smil, V. (1999). Detonator of the population explosion. Nature 400, 415. Smith, G. (1983). Historical developments of soil taxonomy—Background. In “Pedogenesis and Soil Taxonomy. I. Concepts and Interactions” (L. P. Wilding, N. E. Smeck, and F. G. Hall, Eds.), pp. 23–49. Elsevier, Amsterdam. Sombroek, W. G. (1966). Amazon Soils, Ph.D. dissertation, Agricultural University, Wageningen. Sposito, G., and Reginato, R. J. (Eds.) (1992). “Opportunities in Basic Soil Science Research.” SSSA, Madison, WI. Sumner, M. E. (Ed.) (2000). “Handbook of Soil Science.” CRC Press, Boca Raton, FL. Sylvester-Bradley, R., Lord, E., Sparkes, D. L., Scott, R. K., Wiltshire, J. J. J., and Orson, J. (1999). An analysis of the potential of precision farming in Northern Europe. Soil Use Manag. 15, 1–8. Theng, B. K. G. (1991). Soil science in the tropics—The next 75 years. Soil Sci. 151, 76–90. Tinker, P. B. (1985). Soil science in a changing world. J. Soil Sci. 36, 1–8. Traore, S., and Harris, P. J. (1995). Long-term fertilizer and crop residual effects on soil and crop yields in the savanna region of Cote d’Ivoire. In “Soil Management—Experimental Basis for Sustainability and Environmental Quality” (R. Lal and B. A. Stewart, Eds.), pp. 141–180. CRC Press, Boca Raton, FL. TRFK (1986). “Tea Growers Handbook,” 4th edition. The Tea Research Foundation of Kenya, Kericho. Tuljapurkar, S. (1997). Demography—Taking the measure of uncertainty. Nature 387, 760–761. van Baren, J. H. V., Hartemink, A. E., and Tinker, P. B. (2000). 75 years. The international Society of Soil Science. Geoderma 96, 1–18. van Diest, A. (1986). The social and environmental implications of large-scale translocations of plant nutrients. In “Proceedings 13th Congress of the International Potash Institute,” pp. 289–299. IPI, Bern. Viets, F. G. (1977). A perspective on two centuries of progress in soil fertility and plant nutrition. Soil Sci. Soc. Am. J. 41, 242–249. Vine, H. (1968). Developments in the study of soils and shifting agriculture in tropical Africa. In “The Soil Resources of Tropical Africa” (R. P. Moss, Ed.), pp. 89–119. Cambridge University Press, Cambridge. Viscarra Rossel, R. A., and McBratney, A. B. (1998). Soil chemical analytical accuracy and costs: implications from precision agriculture. Aust. J. Exp. Agric. 38, 765–775. Von Uexk¨ull, H. R., and Mutert, E. (1995). Global extent, development and economic impact of acid soils. In “Plant Soil Interactions at Low pH” (R. A. Date, R. J. Grundon, G. E. Rayment, and M. E. Probert, Eds.), Vol. acidity, pp. 5–19. Kluwer Academic, Dordrecht. Wagenet, R. J., and Bouma, J. (Eds.) (1996). “The Role of Soil Science in Interdisciplinary Research.” ASA-SSSA, Madison, WI. Webster, C. C., and Wilson, P. N. (1980). “Agriculture in the Tropics,” 2nd edition. Longman, Harlow. White, R. E. (1997). Soil science—Raising the profile. Aust. J. Soil Res. 35, 961– 977. Wild, A. (1989). Soil scientists as members of the scientific community. J. Soil Sci. 40, 209–221. Willis, J. C. (1909). “Agriculture in the Tropics. An Elementary Treatise.” Cambridge University Press, Cambridge. Wrigley, G. (1982). “Tropical agriculture,” 4th edition. Longman, Harlow. Yaalon, D. H. (1989). Who is publishing and where on soil science of the tropics? Scientometrics 15, 313–314. Yaalon, D. H. (1996). Soil science in transition: Soil awareness and soil care strategies. Soil Sci. 161, 3–8.

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RESPONSES OF AGRICULTURAL CROPS TO FREE-AIR CO2 ENRICHMENT B. A. Kimball,1,∗ K. Kobayashi,2 and M. Bindi3 1

U.S. Water Conservation Laboratory, USDA, Agricultural Research Service Phoenix, Arizona, 85040 2 National Institute of Agro-Environmental Sciences Tsukuba, Ibaraki 305-8604, Japan 3 Department of Agronomy and Land Management University of Florence 50144 Florence, Italy

I. Introduction II. Methodology III. Results and Discussion of Crop Responses to Elevated CO2 A. Photosynthesis B. Water Relations C. Peak Leaf Area Index D. Biomass Accumulation E. Radiation-Use Efficiency F. Specific Leaf Area G. Chemical Composition Changes H. Phenology I. Soil Changes IV. Compendium and Conclusions V. Summary References

Over the past decade, free-air CO2 enrichment (FACE) experiments have been conducted on wheat, perennial ryegrass, and rice, which are C3 grasses; sorghum, a C4 grass; white clover, a C3 legume; potato, a C3 forb with tuber storage; and cotton and grape, which are C3 woody perennials. Elevated CO2 increased photosynthesis, biomass, and yield substantially in C3 species, but little in C4. It decreased stomatal conductance in both C3 and C4 species and greatly improved water-use efficiency in all crops. Growth stimulations were as large or larger under water stress compared to well-watered conditions. At low soil N, stimulations of nonlegumes were reduced, whereas elevated CO2 strongly stimulated the growth of the clover legume ∗

To whom correspondence should be addressed. Phone: 602-437-1702 x-248. Fax: 602-437-5291. E-mail: [email protected]. 293 Advances in Agronomy, Volume 77 Copyright 2002, Elsevier Science (USA). All rights reserved. 0065-2113/02 $35.00

294

KIMBALL et al. at both ample and low N conditions. Roots were generally stimulated more than shoots. Woody perennials had larger growth responses to elevated CO2, but their reductions in stomatal conductance were smaller. Tissue N concentrations went down, while carbohydrate and some other carbon-based compounds went up, with leaves being the organs affected most. Phenology was accelerated slightly in most but not all species. Elevated CO2 affected some soil microbes greatly but not others, yet overall activity was stimulated. Detection of statistically significant changes in soil organic carbon in any one study was nearly impossible, yet combining results from several sites and years, it appeared that elevated CO2 did increase sequestration of soil carbon. Comparisons of the FACE results with those from earlier chamber-based results were consistent, which gives confidence that conclusions  C 2002 Elsevier Science (USA). drawn from both types of data are accurate.

I. INTRODUCTION The increasing CO2 concentration of Earth’s atmosphere and associated predictions of global warming (IPCC, 1996) have stimulated research programs to determine the likely effects of the future elevated CO2 levels on agricultural productivity and on the functioning of natural ecosystems (e.g., Dahlman et al., 1985). However, even predating the global change concerns, the effects of atmospheric CO2 enrichment have been studied for more than a century in greenhouses, controlled-environment chambers, open-top chambers, and other enclosures to confine the CO2 gas around the experimental plants (e.g., Drake et al., 1985; Enoch and Kimball, 1986; Schulze and Mooney, 1993). The results of these many chamber-based experiments have been reviewed by Kimball (1983, 1986, 1993), Morison (1985), Cure (1985), Cure and Acock (1986), Kimball and Idso (1983), Poorter (1993), Idso and Idso (1994), Ceulemans and Mousseau (1994), Wullschleger et al. (1997), Cotrufo et al. (1998), Norby et al. (1999), Nakagawa and Horie (2000), Curtis and Wang (1998), and Wand et al. (1999) (although the latter two also included a few observations from recent nonchamber open-field experiments). However, the environment inside enclosures is not generally like that outside (e.g., Kimball et al., 1997; McLeod and Long, 1999); thus, there have been many concerns that the results from such enclosure-based CO2-enrichment experiments might not be representative of future open fields and forests. Therefore, various attempts were made to develop techniques which could maintain the CO2 concentrations over open-field plots at elevated levels despite the challenges imposed by open-field winds causing rapid dispersal of the CO2 (Allen, 1992; Norby et al., 2001). Eventually, engineers from Brookhaven National Laboratory (Upton, New York) working cooperatively with scientists from the

CO2 RESPONSES OF AGRICULTURAL CROPS

295

U.S. Department of Agriculture, Agricultural Research Service, and from Tuskegee University, as well as others, were able to adapt a “vertical vent pipe” technology that could adequately maintain the desired high levels of CO2 over open-field plots all growing-season long (Hendrey, 1993; Norby et al., 2001). The first such experiment with publishable biological data was conducted on cotton in 1989 at Maricopa, Arizona. After success with cotton, the Brookhaven group moved their engineering efforts to the forest, and they were able to increase the scale of the apparatus to accommodate 14-m-tall trees (e.g., Delucia et al., 1999). Once it was demonstrated that such free-air CO2 enrichment (FACE) experiments were feasible, several other research groups also initiated similar experiments in both managed and natural ecosystems. To date, there are about 30 active or planned FACE sites (http://cdiac.esd.ornl.gov/programs/FACE/face.html; http://www.face.bnl.gov/; http://gcte-focus1.org/co2.html). The purposes of this paper are (i) to compile the available data from the FACE experiments on agricultural crops; (ii) to determine the relative responses of the several crops to elevated CO2 with regard to their physiology, growth, yield, water relations, and soil processes; (iii) to search for similarities and differences among species and plant functional types; and (iv) to compare these FACE results with those from prior chamber-based studies.

II. METHODOLOGY We have extracted data from papers and manuscripts generated by our agricultural-crop-oriented free-air CO2 enrichment (FACE) projects at Maricopa, Arizona; Shizukuishi, Iwate, Japan; and Rapolano, Terme, Italy, as well as from the grassland project at Eschikon, Switzerland. The experimental protocols and site characteristics for the several experiments are listed in Table I. From the absolute crop response values, we computed the relative increases (or decreases, which are listed as negative increases) due to the FACE treatment with respect to their corresponding control treatments at ambient CO2, as listed in Table II. The number of FACE experiments is relatively small, so conclusions cannot be as definitive as desired. On the other hand, the relatively large plot size of the FACE projects produces enough plant material to support the research of a large number of cooperating scientists from several disciplines, so the number of processes for which measurements were obtained is comparatively large. The crops include wheat (Triticum aestivum L.), rice (Oryza sativa L.), perennial ryegrass (Lolium perenne), sorghum (Sorghum bicolor (L.) M¨oench), potato (Solanum tuberosum L.), white clover (Trifolium repens), lucerne or alfalfa (Medicago sativa L.), cotton (Gossypium hirsutum L.), and grape (Vitis vinifera L.). These crops are representative of several functional types of plants. Specifically, wheat, rice, and ryegrass are all C3 grasses, and sorghum is a C4 grass.

Table I Experimental Protocols and Site Characteristics for Several Agricultural FACE Experiments FACE experiment (experiment ID)a Parameter Location Species or ecosystem

Latitude (deg, min) Longitude (deg, min) Elevation (m) Experiment start dateb 296 Experiment end dateb

Growing season startc

Growing season endc

FACE startd

FACE endd

Solar rad.e(MJ m−2 day−1) Max. air temp.f(◦ C)

MCCot89–91

MCWht93–94

MCWht96–97

Maricopa, Arizona Cotton (Gossypium hirsutum L.)

Maricopa, Arizona Wheat (Triticum aestivum L.)

Maricopa, Arizona Wheat (Triticum aestivum L.)

33◦ 4′ N 111◦ 59′ W 358 17-04-1989 23-04-1990 16-04-1991 17-09-1989 17-09-1990 16-09-1991 17-04-1989 17-04-1990 16-04-1991 17-09-1989 17-09-1990 16-09-1991 19-05-1989 04-05-1990s 26-04-1991 17-09-1989 17-09-1990 16-09-1991 Avg. 25.1 Avg. 46.3

33◦ 4′ N 111◦ 59′ W 358 15-12-1992 08-12-1993

MCSor98–99

Swiss93–98

RiceFACE98–99

Eschikon, Switzerland Grassland; ryegrass (Lolium perenne) and white clover (Trifolium repens) 47◦ 27′ N 8◦ 41′ E 550 31-5-1993

Shizukuishi, Iwate, Japan Rice (Oryza sativa L.)

33◦ 4′ N 111◦ 59′ W 358 15-12-1995 15-12-1996

Maricopa, Arizona Sorghum [Sorghum bicolor (L.) M¨oench] 33◦ 4′ N 111◦ 59′ W 358 16-07-1998 15-06-1999

24-05-1993 01-06-1994

29-05-1996 28-05-1997

21-12-1998 26-10-1999

Continuing

29-09-1998 24-09-1999

15-12-1992 08-12-1993

15-12-1995 15-12-1996

16-07-1998 15-06-1999

Temp > 5◦ C

21-05-1998 20-05-1999

24-05-1993 01-06-1994

29-05-1996 28-05-1997

21-12-1998 26-10-1999

Temp < 5◦ C

29-09-1998 24-09-1999

01-01-1993 28-12-1993

01-01-1996 03-01-1997

31-07-1998 01-07-1999

1-6-1993

03-06-1998 20-05-1999

16-05-1993 18-05-1994

15-05-1996 12-05-1997

21-12-1998 26-10-1999

Continuing

29-09-1998 24-09-1999

Avg. 18.7 Avg. 38.5

Avg. 19.9 Avg. 40.9

Avg. 21.6 Avg. 44.2

∼14.2 25

Avg. 13.8 24.5

39◦ , 38′ N 140◦ , 57′ E 200 21-05-1998 20-05-1999

Min. air temp.f(◦ C) Plot diameterg(m) No. of replicatesh No. of CO2 levelsi Predilution of the CO2? j Set point or increment?k FACE CO2 conc.(s)l Daily enrichment timem “No-enrichment” criterian Add’nal treat. #1 nameo

297

Avg. −2.8 20 4 2 Yes Set point 550 24 h day− 1 None Water

Avg. −3.7 20 4 2 + Ambient Yes increment +200 24 h day− 1 None Nitrogen

Avg. 2.0 21 4 2 Yes increment +200 24 h day− 1 None Water

−5 18 3 2 Yes Set point 600 Daylight Winter Nitrogen

15.9 10 4 2 No 200 ppm increment 589 (at the ring center) 24 h na Nitrogen

Main or split?p Level 1q (dry or low-N)

Avg. 7.6 18 4 2 Yes Set point 550 Daylight None Water in 1990 and 1991 Split Avg. 1009 mm

Split Avg. 335 mm

Split Avg. 483 mm

Split 140 kg ha− 1 y− 1

Split Low (40 kg N/ha)

Level 2q (wet or high-N)

Avg. 1202 mm

Avg. 679 mm

Split 70 kg N ha− 1 in 1996; 15 kg N ha− 1 in 1997 350 kg N ha− 1

Avg.1133 mm

560 kg ha− 1 y− 1

Standard [80 (1998) or 90 (1999) kg N/ha] High [120 (1998) or 150 (1999) kg N/ha]

1120 kg ha− 1 y− 1

Level 3q (very high-N) Add’nal treat. #2 nameo Main or split?p Level 1q Level 2q Add’nal treat. #3 Main or Split?p Level 1q Level 2q Level 3q Reference(s)r

Pinter et al. (1994), Mauney et al. (1994), Lewin et al. (1994)

Hunsaker et al. (1996), Kimball et al. (1999), GCTE (1996)

Kimball et al. (1999)

Ottman et al. (2001)

Cutting frequency Split 4 cuts y− 1 8 cuts y− 1, then 5 Sward type Split Lolium perenne Trifolium repens Mixture Jongen et al. (1995), Hebeisen et al. (1997), Daepp et al. (2000)

Kim et al. (2001), Kobayashi et al. (2001)

continues

Table I—continued FACE experiment (experiment ID)a Parameter

CLAIRE 94–95

CLIVARA 96–97

Location Species or ecosystem

Rapolano, Terme, Italy Grape (Vitis vinifera cv. Sangiovese)

Rapolano, Terme, Italy Grape (Vitis vinifera cv. Sangiovese)

Latitude (deg, min) Longitude (deg, min) Elevation (m) Experiment start dateb

50◦ 32′ N 8◦ 41.3′ E 172 01-05-1994 19-4-1995 04-10-1994 17-10-1995 01-05-1994 19-04-1995 04-10-1994 17-10-1995 01-15-1994 02-05-1995 04-10-1994 17-10-1995 Avg. 21.3 35.8 0.9 8 × 1.5 3 2 Yes Set point 700 Daylight

50◦ 32′ N 8◦ 41.3′ E 172 22-04-1996 20-04-1997 30-09-1996 07-10-1997 22-04-1996 20-04-1997 30-09-1996 07-10-1997 06-05-1996 11-05-1997 01-10-1996 07-10-1997 Avg. 20.9 Avg. 32.4 Avg. −1.3 8 × 1.5 2 3 Yes Set point 550, 700 Daylight

Experiment end dateb 298

Growing season startc Growing season endc FACE startd FACE endd Solar rad.e(MJ m− 2 day− 1) Max. air temp.f(◦ C) Min. air temp.f(◦ C) Plot diameter g(m) No. of replicatesh No. of CO2levelsi Predilution of the CO2? j Set point or increment?k FACE CO2conc.(s)l Daily enrichment timem

POTATO95 Rapolano, Terme, Italy Potato (Solanum tuberosum cv. Primura) 50◦ 32′ N 8◦ 41.3′ E 172 27-05-1995 05-09-1995 10-06-1995 05-09-1995 10-06-1995 04-05-1995 21.5 35.8 2.9 8 1 4 Yes Set point 460,560,660 Daylight

CHIP98–99 Rapolano, Terme, Italy Potato ( Solanum tuberosum cv. Bintje) 50◦ 32′ N 8◦ 41.3′ E 172 20-05-1998 05-05-1999 18-08-1998 17-08-1999 28-05-1998 26-05-1999 18-08-1998 17-08-1999 28-05-1998 27-05-1999 18-08-1998 17-08-1999 Avg. 21.4 Avg. 37.8 Avg. 5.1 8 3 2 + Ambient Yes Set point 560 Daylight

“No-enrichment” criterian Reference(s)r

a

None Bindi et al. (1995a, 1995b), Raschi et al. (1996), Giuntoli (2000)

None Bindi et al. (2000), Bindi, Fibbi et al. (2001) Bindi, Fibbi, and Miglietta (2001) Giuntoli (2000)

None Miglietta et al. (1997, 1998), Vaccari et al. (2000)

None Bindi et al. (1998, 1999)

Experiment identification names. Dates for the start and end of the experiments. c Calendar year dates or criteria for the start and stop of the growing seasons. d Start and stop dates of the FACE treatment(s). (For most experiments, these dates are the same as the growing season dates.). e Mean daily solar radiation obtained during growing season(s), expressed in MJ m−2 day−1. f Maximum and minimum air temperatures during growing season(s) in ◦ C. g Diameter of useable plot area in m, or for rectangular plots, length and width. h Number of replicate CO2 and other treatment plots. i Number of treatment CO2 levels. A “2” means experiments with FACE and Control treatments or with FACE and ambient treatments. “Control” means plots with air flow near identical to that of the FACE plots but without added CO2. “Ambient” means plots with no forced air flow and no added CO2. “2 + ambient” means experiments with FACE, control, and ambient treatments. For experiments with multiple levels of FACE concentrations, a list of the several CO2 levels is given. j A “yes” means a blower system in the FACE apparatus prediluted CO2 with air, or a “no” means pure CO2 was released. k “Set point” or “increment” indicates whether a constant target CO2 set point was used or whether a target increment in concentration above normal air CO2 levels was used. l The set point CO2 concentration(s) or the increment(s) in CO2 concentration preceded by a “+”. Units of μmol mol−1. m Portion of day CO2 enrichment was done such as “24 h” or “daylight” or other amount. n Constraints that were put on the enrichment, such high-wind cutoff or low-temperature cutoff. o Name(s) of any other additional factorial treatments in the experiment such as low water or low nitrogen. p “Split” or “main” indicates whether the CO2 main plots were split or whether additional full-size main plots of the other factor(s) were added. q Levels of the additional treatment factors with units. r Reference(s) that best describe the experimental conditions. b

299

Table II Percentage Increases in Several Plant Response Parameters to Elevated CO2 of Various Agricultural Crops Grown in Monoculture Relative to Their Responses at Ambient CO2a Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

+SE

Low water

Ample N %

+SE

Low N %

+SE

Ample N %

+SE

References

Net photosynthesis

300

C3 grasses MCWht93 Wheat upper leaf MCWht93 Wheat flag leaf MCWht93 Wheat 8th leaf MCWht93 Wheat 7th leaf (Daily integral of net CO2 uptake) MCWht96 Wheat upper leaf MCWht97 Wheat upper leaf (Seasonal carbon assimilated) MCWht93,96 Wheat ears MCWht97 Wheat canopy Swiss94 Ryegrass 7-day cut Swiss94 Ryegrass uncut C4 grasses MCSor98,99

Sorghum upper leaf

C3 woody perennials MCCot89 Cotton upper leaf MCCot90 Cotton canopy

31.5 25.6 68.6 ∞ 32.8 21.6

Garcia et al. (1998) Osborne et al. (1998) Osborne et al. (1998) Osborne et al. (1998) 5.0 7.3

25.9 19.7

10.0 9.2

Wall, Adam et al. (2001) Wall, Adam et al. (2001)

58.0 19.2 32.5 43.5

19.0 24.1

32.0 8.7 45.2 45.8

8.5

13.5

23.3

21.2

Wall, Brooks et al. (2001)

28.2 32.1

13.0 38.9

17.8

23.3

Hileman et al. (1994) Hileman et al. (1994)

58.0

Wechsung et al. (2000) Brooks et al. (2001) Rogers et al. (1998) Rogers et al. (1998)

20.8 22.4

Water relations: stomatal conductance MCWht93 MCWht96–97

C4 grasses MCSor98–99

301

Wheat Wheat C3 grass means SE

−32.7 −36.0 −34.4 1.7

Sorghum

−37.3

13.8

−32.4

22.6

Wall, Brooks et al. (2001)

−18.2 −12.3 −14.7 3.7 −19.6 −12 −18 −15 −8 −32 −23.0 −6 4 −21.3 −16.0

8.9 3.2

−22.2

14.3

Hileman et al. (1994) Raschi et al. (1996)

C3 woody perennials MCCot90 Cotton CLAIRE95 Grape C3 woody means SE Literature Literature Wheat Literature Rice Literature Sorghum Literature Cotton Literature Potato Literature Literature Woody SE Literature Wild C3 grass Literature Wild C4 grass

Garcia et al. (1998) Wall, Adam et al. (2001)

−44.0

Kimball and Idso (1983) Cure (1985) Cure (1985) Cure (1985) Cure (1985) Cure (1985) Morison (1985) Curtis and Wang (1998)

−14.5

Water relations: canopy temperature (◦ C, not %) C3 grasses MCWht93 MCWht96

Wheat Wheat

0.6 0.6

0.1

1.1

0.1

−12.8

Wand et al. (1999) Wand et al. (1999)

Kimball et al. (1995) Kimball et al. (1999) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

C3 woody perennials MCCot89 Cotton

%

+SE

Low water

Ample N %

0.8

+SE

Low N %

+SE

Ample N %

References

+SE

0.1

Kimball et al. (1992)

Water relations: evapotranspiration or water use

302

C3 grasses MCWht93 MCWht94 MCWht96 MCWht97 MCWht93–97 MCWht96–97

Wheat; water bal. Wheat; water bal. Wheat; water bal. Wheat; water bal. Wheat; energy bal. Wheat; energy bal.

−3.6 −3.3 −3.5 −3.9 −6.7

C4 grasses MCSor98 MCSor99

Sorghum; water bal. Sorghum; water bal.

−11.1 −8.7

C3 woody perennials MCCot90 Cotton; water bal. MCCot91 Cotton; water bal. MCCot91 Cotton; stem flow

−0.7 −1.3

4.5 −2.2

Hunsaker et al. (1996) Hunsaker et al. (1996) Hunsaker et al. (2000) Hunsaker et al. (2000) Kimball et al. (1999) Kimball et al. (1999)

−19.5 3.0 2.6

−1.1 −1.9 0.0

0.0 −6.5

6.2 4.0

Conley et al. (2001) Conley et al. (2001) Hunsaker et al. (1994) Hunsaker et al. (1994) Dugas et al. (1994)

−1.6 −1.6

Water relations: leaf water potential [Negative % increase values indicate FACE plants had higher (i.e., less negative and less stressful) water potentials] C4 grasses MCSor98–99

Sorghum

C3 woody perennials CLAIRE95 Grape

−2.8

5.5

−2.9

1.2

−8.8

4.2

Wall, Brooks et al. (2001) Raschi et al. (1996)

Peak leaf area index C3 grasses MCWht96 MCWht97 Swiss96-97 Swiss96-97

Wheat Wheat Ryegrass, vege. Ryegrass, repro.

16.4 16.5

13.0 24.0 11.1 8.1

6.7 −6.2 −5.6 12.2

1.0

3.5

0.4

Rice

10.8

6.3

2.0

C3 grass means SE

11.0 3.8

10.8 2.9

1.4 2.9

(Vegetative and reproductive stages in pots) RiceFACE98 Rice RiceFACE99

303

C4 grasses MCSor98 MCSor99

Sorghum Sorghum C4 grass means SE

−0.7 −9.8 −5.4 4.7

16.6 14.2

C3 broadleaf forb with tuber storage POTATO95 Potato; 460 ppmv POTATO95 Potato; 560 ppmv POTATO95 Potato; 660 ppmv Chip98 Potato Chip99 Potato Potato means SE

−12.9 5.8 −1.6 −9.8 −11.0 −6.2 3.5

37.7 22.6 11.2 19.0 4.7

C3 woody perennials MCCot89 Cotton MCCot91 Cotton Cotton means SE

3.8 −15.6 −6.4 10.2

23.5 14.2

Brooks et al. (2001) Brooks et al. (2001) Daepp et al. (2001) Daepp et al. (2001) Kobayashi et al. (unpublished) Kobayashi et al. (unpublished)

−0.3 3.1 1.4 1.7

22.5 14.8

Ottman et al. (2001) Ottman et al. (2001)

Miglietta et al. (1998) Miglietta et al. (1998) Miglietta et al. (1998) Bindi et al. (1998) Bindi et al. (1999)

20.8

22.6

Mauney et al. (1992) Mauney et al. (1994)

continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

+SE

Low water

Ample N %

+SE

Low N %

+SE

Ample N %

+SE

References

12.3 16.6

9.1 20.6

Pinter et al. (2002) Pinter et al. (2002)

Biomass accumulation: shoots

304

C3 grasses MCWht93 MCWht94

Wheat Wheat

9.3 7.7

12.2 14.4

[Note: blower effect may have reduced response in 1993 and 1994 (Pinter et al., 2000)] MCWht96 Wheat 4.8 5.8 8.1 MCWht97 Wheat 11.7 15.8 2.8 RiceFACE98 Rice 16.9 7.6 RiceFACE99 Rice 13.9 10.8 8.1 Swiss93 Ryegrass 5.8 3.0 3.7 Swiss94 Ryegrass 8.0 11.0 −8.6 Swiss95 Ryegrass 10.9 9.7 1.6 Swiss96 Ryegrass 18.6 3.0 −6.2 Swiss97 Ryegrass 10.5 5.6 −0.3 Swiss98 Ryegrass 20.1 4.9 6.9 Swiss96–97 Ryegrass, vegetative 20.2 5.1 16.6 5.7 −2.2 Swiss96–97 Ryegrass, reproduc. 25.4 9.6 20.2 9.7 24.2 (Vegetative and reproductive stages in pots) 19.0 C3 grass means SE 2.5

11.5 1.4

3.1 2.6

13.8 15.4

Pinter et al. (2002) Pinter et al. (2002) Kim et al. (unpublished) Kim et al. (2001) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2001) Daepp et al. (2001)

6.1 20.2 20.5 4.6 10.5 8.5 11.3 17.5 14.4 2.2

C4 grasses MCSor98 MCSor99

Sorghum Sorghum C4 grass means SE

6.7 −1.0 2.8 3.9

3.1 4.5

−12.2 −28.6 −20.8 8.6

6.5 5.0

Clover Clover Clover Clover Clover Clover Lucerne; effective Lucerne; effective Lucerne; ineffect. Lucerne; ineffect.

12.0 16.7 7.6 38.3 21.3 28.6 36.4 38.8 2.4 17.4

4.2 10.4 7.9 12.9 9.5

(Inoculated with effective or ineffective nodulators) Legume means SE Legume means SE

24.4 4.5 9.6 7.8

C3 broadleaf forb with tuber storage Chip98 Potato Chip99 Potato Potato means SE

305

C3 legumes Swiss93 Swiss94 Swiss95 Swiss96 Swiss97 Swiss98 Swiss94 Swiss95 Swiss94 Swiss95

15.4 29.0 11.4 24.4

13.3 18.0 15.6 2.4

13.9 16.8

Ottman et al. (2001) Ottman et al. (2001)

Bindi et al. (1998) Bindi et al. (1999)

17.9 19.9 7.9 36.0 19.8 26.3 42.8 37.2 −19.0 −19.8 25.5 4.2 −19.4 0.4

4.8 10.0 7.5 11.9 9.9 16.0 29.2 7.3 14.8

Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (unpub) Hebeisen et al. (unpub) Hebeisen et al. (unpub) L¨uscher et al. (2000) L¨uscher et al. (2000) L¨uscher et al. (2000) L¨uscher et al. (2000) (Clover + lucerne with effective) (Only lucerne with ineffective) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

306

C3 woody perennials MCCot89 Cotton MCCot90 Cotton MCCot91 Cotton CLAIRE94 Grape; 700 ppmv CLAIRE95 Grape; 700 ppmv CLIVARA96 Grape; 550 ppmv

+SE

Ample N %

+SE

32.3 34.2 36.8 27.8 32.4 33.3

11.8

18.3 24.0 26.9

Low N %

+SE

Ample N %

17.8 35.4

CLIVARA96

Grape; 700 ppmv

20.6

15.0

CLIVARA97

Grape; 550 ppmv

42.1

19.8

CLIVARA97

Grape; 700 ppmv

25.1

9.4

C3 woody means SE Means all C3 except lucerne ineffect SE all C3 except lucerne ineffect Means all C3 except legumes SE all C3 except legumes Literature C3 (all) means SE

31.5 2.2 17.3 2.9 15.1 3.4 21 2

19.0 2.5 19.0 2.5

Low water

12.0 3.4 3.1 2.6

+SE

References

Mauney et al. (1992) Mauney et al. (1994) Mauney et al. (1994) Bindi et al. (1995a) Bindi, et al. (1995a) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001)

26.3 9.1 20.2 5.0 20.2 5.0 Kimball (1983, 1986)

307

Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature

C3 herbs C4 herbs N fixing C3 woody C3 herb, crop C3 herb, wild C3 wild fast grow C3 intermediate C3 wild slow gro Dry wt and CER Dry wt and CER Woody coniferous

16 15 5 46 −8 19 21 11 25 21 29 18 27 19 12 20 32 24

Literature

Woody deciduous

40

Literature

Woody total biom. SE Woody SE Wild C3 grasses wild C4 grasses Rice

17 3 42.7 10.1 19.4 4.6 14

Literature Literature Literature Literature

Wheat Rice Sorghum Cotton Potato

5 15 72

16 15 17 10

15

19

39 29

8 2

Cure (1985) Cure (1985) Cure (1985) Cure (1985) Cure (1985) Kimball (1993) Poorter (1993) Poorter (1993) Poorter (1993) Poorter (1993) Poorter (1993) Poorter (1993) Poorter (1993) Poorter (1993) Poorter (1993) Idso and Idso (1994) Idso and Idso (1994) Ceulemans and Mousseau (1994) Ceulemans and Mousseau (1994) Curtis and Wang (1998) Norby et al. (1999)

16.9 2.6

Wand et al. (1999) Wand et al. (1999) Nakagawa and Horie (2000) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

+SE

Low water

Ample N %

+SE

Low N %

+SE

Ample N %

+SE

References

Biomass accumulation: roots

308

C3 grasses MCWht93 RiceFACE98 RiceFACE99 Swiss93 Swiss93 Swiss94 Swiss94 Swiss95 Swiss95 Swiss96

Wheat; at dough Rice Rice Ryegrass; 7 cuts Ryegrass; 4 cuts Ryegrass; 8 cuts Ryegrass; 4 cuts Ryegrass; 8 cuts Ryegrass; 4 cuts Ryegrass

Swiss96–97 Swiss96–97

13.5 10.3

Ryegrass, vegetative 30.6 Ryegrass, 40.0 reproductive (Vegetative and reproductive stages in pots) Swiss93 Ryegrass (Root ingrowth bags) 23.0 C3 grass means SE 7.2 C3 legumes Swiss93 Swiss93

Clover; 7 cuts Clover; 4 cuts

5.9 13.6

27.9 19.5 18.4 29.3 78.8 161.3 39.2 86.5 50.8 85.7

51.3

45.6 79.2 119 50.4 94.3 87.9 83.4

22.0 32.4 38.7 94.3 72.0 27.0 9.1 65.9

47.3 41.0 48.3 36.6 38.4 33.2 147

31.8 17.9

6.1 11.2

33.1 20.8

6.1 10.2

Wechsung et al. (1999) Kim et al. (unpublished) Kim et al. (2001) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Van Kessel, Horwath et al. (2000) Daepp et al. (2001) Daepp et al. (2001)

91.2

@.05

32.8

@.05

Jongen et al. (1995)

47.4 10.2 39.6 31.0

22.7

38.6 7.4 64.3 49.4

19.3 2.6

22.7

57.9 34.3

Hebeisen et al. (1997) Hebeisen et al. (1997)

Swiss94 Swiss94 Swiss95 Swiss95 Swiss96

Clover; 8 cuts Clover; 4 cuts Clover; 8 cuts Clover; 4 cuts Clover

21.7 25.4 5.6 22.2 33.7

Legume means SE

25.2 4.3

309

C3 woody perennials MCCot89 Cotton; taproot MCCot90 Cotton; taproot MCCot91 Cotton; taproot Cotton; taproot means SE MCCot89 Cotton; fine roots MCCot90 Cotton; fine roots MCCot91 Cotton; fine roots Cotton; fine roots means: SE Literature Woody SE Literature Wild C3 grasses Literature Wild C4 grasses

156.9 37.8 60.4 78.4 36.8 100.0 29.3 34.4 51.5

51.2 33.4 35.1 63.0 446

59.4 17.6 77.8 −7.1 2.4

75.4 46.5 78.1 35.4 301

Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Hebeisen et al. (1997) Van Kessel, Horwath et al. (2000)

21.4 11.6 63.8 10.1 16.6

Rogers et al. (1992) Prior et al. (1994) Prior et al. (1994)

31.3

Rogers et al. (1992) Prior et al. (1994) Prior et al. (1994)

22.7 23 3 31.3 8.3

5 6 14.7

Curtis and Wang (1998) Wand et al. (1999) Wand et al. (1999)

Biomass accumulation: agricultural yield C3 grasses with grain yield MCWht93 Wheat MCWht94 Wheat

8.0 12.0

7.4 8.6

21.0 25.0

7.2 18.6

Pinter et al. (1997, 2002) Pinter et al. (1997, 2002) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

+SE

Low water

Ample N %

+SE

Low N %

310

[Note: blower effect may have reduced response in 1993 and 1994 (Pinter et al., 2000)] MCWht96 Wheat 15.0 8.8 12.0 MCWht97 Wheat 17.0 12.7 5.0 RiceFACE98 Rice 13.8 10.3 7.4 RiceFACE99 Rice 8.2 9.8 3.0 11.0 12.0 6.8 C3 grass means SE 2.8 1.4 1.9 C4 grasses with grain yield MCSor98 Sorghum MCSor99 Sorghum Means SE

0.9 −10.7 −5.1 6.0

4.9 6.9

C3 boadleaf forb with tuber yield POTATO95 Potato; 460 ppmv POTATO95 Potato; 560 ppmv POTATO95 Potato; 660 ppmv Chip98 Potato Chip99 Potato Potato means SE

10.8 21.0 27.0 33.8 47.6 27.5 6.3

21.9 10.8 8.1 5.8 7.8

C3 woody perennial with boll (seed + lint) yield MCCot89 Cotton bolls MCCot90 Cotton bolls

22.0 50.9

+SE

Ample N %

+SE

13.1 16.5

References

Pinter et al. (1997, 2002) Pinter et al. (1997, 2002) Kobayashi et al. (2001) Kim et al. (2001) 23.0 2.0 17.2 34.0 25.3 8.7

20.8 42.6

Ottman et al. (2001) Ottman et al. (2001)

Miglietta et al. (1998) Miglietta et al. (1998) Miglietta et al. (1998) Bindi et al. (1998) Bindi et al. (1999)

43.1

Mauney et al. (1992) Mauney et al. (1994)

MCCot91

MCCot89 MCCot90 MCCot91

Cotton bolls Seed cotton means SE Cotton lint Cotton lint Cotton lint Cotton lint means SE

C3 woody perennial with berry yield CLAIRE94 Grape; 700 ppmv CLAIRE95 Grape; 700 ppmv CLIVARA96 Grape; 550 ppmv

42.6 38.0 9.1 20.7 73.4 81.1 55.9 21.4

42.0 42.5 0.6 11.4 45.8 39.3

11.9 21.0 42.7

13.1 26.2 41.7

311

CLIVARA96

Grape; 700 ppmv

24.5

15.6

CLIVARA97

Grape; 550 ppmv

43.0

24.5

CLIVARA97

Grape; 700 ppmv

28.7

11.5

Literature Literature Literature Literature Literature Literature Literature Literature Literature

Woody means SE All mature ag crops C3 grain crops C4 crops Wheat Rice Cotton Potato Many ag. crops Rice

28.1 5.1 15 23 26 19 8 113 28 19 14

51.7 51.5 51.6 0.1

Mauney et al. (1994)

27.3 20.4

Pinter et al. (1996) Pinter et al. (1996) Pinter et al. (1996)

Bindi et al. (1995a) Bindi et al. (1995a) Bindi, Fibbi and Miglietta (2001) Bindi, Fibbi and Miglietta (2001) Bindi, Fibbi and Miglietta (2001) Bindi, Fibbi and Miglietta (2001)

5 14 9

22

9

19

Kimball (1983, 1986) Kimball (1983, 1986) Kimball (1983, 1986) Cure (1985) Cure (1985) Cure (1985) Cure (1985) Kimball (1993) Nakagawa and Horie (2000) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

+SE

Low water

Ample N %

Low N %

+SE

Ample N

+SE

%

+SE

References

Radiation use efficiency

312

C3 woody perennial MCCot89 Cotton MCCot90 Cotton MCCot91 Cotton Cotton means SE

34.7 23.4 26.9 28.3 4.8

Pinter et al. (1994) Pinter et al. (1994) Pinter et al. (1994)

Specific leaf area C3 grass leaves Swiss93 Swiss94 Swiss95 Swiss96 Swiss97 Swiss98 RiceFACE98 RiceFACE99

Ryegrass Ryegrass Ryegrass Ryegrass Ryegrass Ryegrass Rice Rice

C4 grasses MCSor98 MCSor99

Sorghum Sorghum

−1.3 2.5

−14.3 −6.7 −1.0 0.1 −1.5 0.2 −0.8 −1.3

3.2 2.7 3.6 4.3 4.3 3.6

−1.9 −2.5

6.0 10.0

−15.9 −11.1 −9.8 −12.1 −9.8 −10.7

4.4 3.6 4.4 5.2 6.1 4.2

Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Kim et al. (unpublished) Kim et al. (unpublished) 3.5 3.5

6.1 11.8

Ottman et al. (2001) Ottman et al. (2001)

C3 forb with tuber storage POTATO95 Potato; 460 ppm CO2 POTATO95 Potato; 560 ppm CO2 POTATO95 Potato; 660 ppm CO2 Chip98 Potato Chip99 Potato C3 woody perennial CLAIRE94 CLAIRE95 Literature Literature

Grape Grape Wild C3 grasses Wild C4 grasses

−51.1 −19.3 −12.4 −17.1 −7.6

8.5 4.4 4.3 3.3 2.7

Miglietta et al. (1998) Miglietta et al. (1998) Miglietta et al. (1998) Bindi et al. (1998) Bindi et al. (1999)

−5.7 −5.0 −13.4 −3.2

1.1 1.6

Bindi et al. (1995a) Bindi et al. (1995a) Wand et al. (1999) Wand et al. (1999)

−2.6 −8.5 −2.9 2.9 −4.4 −7.3 −15.6 −13.7 −12.6 −15.5 −18.9

6.2 3.9 10.7 8.1

Chemical composition changes: nitrogen concentration

313

C3 grass leaves MCWht93 MCWht94 MCWht96 MCWht97 RiceFACE98 RiceFACE99 Swiss93 Swiss94 Swiss95 Swiss96 Swiss97

Wheat Wheat Wheat Wheat Rice Rice Ryegrass Ryegrass Ryegrass Ryegrass Ryegrass

−13.2 − 6.3

2.2 2.5 2.4 2.5 2.7

−24.6 −18.7

10.6 20.2

−8.9 −12.9 −16.9 −13.1 −14.4 −13.5

3.0 4.2 4.3 4.3 5.1

−5.5 −12.0

5.9 3.8

Sinclair et al. (2000) Sinclair et al. (2000) Sinclair et al. (2000) Sinclair et al. (2000) Miura et al. (unpublished) Miura et al. (unpublished) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID Swiss98

Swiss96–98 314

C3 woody perennial MCCot90 MCCot89 MCCot90 MCCot89 MCCot90 MCCot89 MCCot90 MCCot89 MCCot90 MCCot89 MCCot90 MCCot89 MCCot90

Crop; condition Ryegrass C3 grass means SE Ryegrass litter

%

+SE

−9.8 3.5

Cotton leaves Cotton leaf Cotton leaf Cotton stem Cotton stem Cotton root Cotton root Cotton bur Cotton bur Cotton seed Cotton seed Cotton plant total Cotton plant total

C3 grass whole shoots Swiss93–97 Ryegrass Swiss96–97 Ryegrass vegetative

0.0

4.1

Ample N

Low water Low N

Ample N

%

+SE

%

+SE

−11.0 −9.4 1.9 −5.4

+2.9

−16.4 −15.6 1.5

4.1

ns

Sowerby et al. (2000)

−32.1 1.3 −15.4 2.3 −21.8 −11.6 −20.4 −12.8 −33.8 −7.6 −7.2 −10.0 −12.9

0.2 ns @0.1 ns @0.1 @0.1 @0.1 ns @0.1 @0.1 ns @0.1 @0.1

Huluka et al. (1994) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998) Prior et al. (1998)

−14.6 −5.1

3.7 4.9

−9.1

%

+SE

References Daepp et al. (2000)

−8.8 3.3

5.7

Hartwig et al. (2000) Daepp et al. (2001)

Swiss96–97

Ryegrass reproduct.

(Vegetative and reproductive stages in pots) C3 grass shoot means SE

0.0 0.0 0.0

C3 legume whole shoots Swiss93 Clover shoot Swiss94 Clover shoot Swiss95 Clover shoot Swiss93–97 Clover plant Legume shoot mean SE C3 grass grain MCWht93–94 MCWht96–97 315 Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature Literature

Wheat grain Wheat grain Wheat grain means SE Woody Nonwoody N supply for all Organ—leaf Organ—leaf litter Organ—shoot Organ—stem organ—coarse root Organ—fine root Organ—whole plant C3 C4

−13

8.8

−7.9

10.0

−9.3 2.9

−19.8

17.3

Daepp et al. (2001)

7.7 8.9 16.8

Zanetti et al. (1996) Zanetti et al. (1996) Zanetti et al. (1996) Hartwig et al. (2000)

−14.6 5.5

−4.1 −9.7 −5.4 −5.5 −6.2 1.2

8.1 8.6 15.5 2.5

−5.8 0.0 −2.9 2.9 −15 −12 −13 −16 −7 −13 −9 −15 −7 −17 −16 −7

1.2 2.1

−1.9 −9.1 −3.5 −4.9 2.2

−8.5 −8.5

−15

3.1

−4.0

1.2

Kimball et al. (2001) Kimball et al. (2001)

−4.0 Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) Cotrufo et al. (1998) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID Literature Literature

316

Literature Literature Literature

Crop; condition

%

N2fixing Woody SE Wild C3 grasses Wild C4 grasses Woody mean SE

+SE

Low water

Ample N %

+SE

Low N %

+SE

Ample N %

+SE

References Cotrufo et al. (1998) Curtis and Wang (1998)

−7 −9 1 −10.9 −2.9 −7 4

Wand et al. (1999) Wand et al. (1999) Norby et al. (1999)

−13.0

Chemical composition changes: nitrogen yield C3 grasses RiceFACE98 RiceFACE99 Swiss93 Swiss94 Swiss95 Swiss96 Swiss97 Swiss98 MCWht93–94 MCWht96–97

Rice plant N content Rice plant N content Ryegrass N yield Ryegrass N yield Ryegrass N yield Ryegrass N yield Ryegrass N yield Ryegrass N yield Wheat grain Wheat grain (Protein N yield) C3 grass means SE

13.0 6.4

9.7 3.3

2.7 2.5 −10.4 −7.1 −4.3 −0.6 −10.5 6.3 3.5 16.8 −0.4 2.6

5.2 5.4 4.5 3.0 3.5 5.5 5.3 8.8

−0.9 −10.0 −23.6 −12.3 −19.3 −13.1 −11.6

18.6 16.0 14.9 8.2 12.0 13.3

−0.9

15.0

−11.8 2.8

17.6

17.6 0.0

8.2

Kobayashi et al. (2001) Kim et al. (2001) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Daepp et al. (2000) Kimball et al. (2001) Kimball et al. (2001)

C3 legumes Swiss95 Swiss95

Lucerne; effective Lucerne; ineffective

30.1 6.3

25.1 19.9

24.0 17.1

@0.2 ns

(Inoculated with effective or ineffective nodulators) C3 woody perennial MCCot89 Total cotton plant MCCot90 Total cotton plant

32.5 −26.9

25.7 11.9

L¨uscher et al. (2000) L¨uscher et al. (2000)

Prior et al. (1998) Prior et al. (1998)

Chemical composition changes: carbohydrates and other carbon-based compounds C3 grass leaves Total nonstructural carbohydrates MCWht93 Wheat flag leaf Water-soluble carbohydrates 8 days after cutting Swiss94 Ryegrass leaf 317

Swiss94 Ryegrass pseudo-stem Water-soluble carbohydrates 7 days after cutting or uncut Swiss94 Ryegrass leaf; 7-day cut Swiss94 Ryegrass leaf; uncut C3 grass means SE C3 broadleaf forb with tuber storage Starch concentration Chip98 Potato tuber Chip99 Potato tuber Potato means: SE C3 woody perennials Starch concentration MCCot90 Cotton leaf

15.1

10.0

Nie et al. (1995)

13.0

10.2

37.4

10.6

Fischer et al. (1997)

37.8

12.8

31.0

10.6

Fischer et al. (1997)

24.6

ns

40.6

ns

Rogers et al. (1998)

18.8 21.6 4.4

ns

70.8 44.2 8.7

@.05

Rogers et al. (1998)

0.4 8.7 4.5 4.3

183.3

2.9 1.5

Bindi et al. (1998) Bindi et al. (1999)

277.8

Hendrix et al. (1994) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID MCCot91

Crop; condition Cotton leaf Cotton means SE

%

+SE

Ample N %

+SE

75.0 122.7 60.6

318

3.5

2.9

CLIVARA96

Grape; 700 ppmv

0.9

1.3

CLIVARA97

Grape; 550 ppmv

3.1

4.4

CLIVARA97

Grape; 700 ppmv

0.9

1.9

Grape means SE

2.1 0.7 21.1 0.0 37 9 17.6

Low N %

+SE

Ample N %

+SE

100.0 174.9 102.9

Berry sugar concentration CLIVARA96 Grape; 550 ppmv

Phenolic (isoorientin) concentration MCWht93 Wheat; green leaf MCWht93 Wheat; senescent leaf Literature Woody SE Literature Wild C3 grasses

Low water

5.1 25.0

References Hendrix et al. (1994)

Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001)

0.0 0.0

13.5 25.0

Pe˜nuelas et al. (1999) Pe˜nuelas et al. (1999) Curtis and Wang (1998) Wand et al. (1999)

Phenology (FACE minus control difference in days, not %) MCWht96–97

Wheat

−0.4

0.3

(Average difference in time to eight growth stages from tillering to maturity) RiceFACE98 Rice anthesis −2 RiceFACE99 Rice anthesis −2 −3 MCSor98 Sorghum anthesis −0.3 1.3 MCSor99 Sorghum anthesis −2.7 1.8 Chip98 Potato anthesis −3 9 Chip99 Potato anthesis −1 7 CLAIRE94 Grape; 700 ppmv 0 CLAIRE95 Grape; 700 ppmv 0 CLIVARA96 Grape; 550 ppmv 0

319

CLIVARA96

Grape; 700 ppmv

0

CLIVARA97

Grape; 550 ppmv

0

CLIVARA97

Grape; 700 ppmv (anthesis) Sorghum maturity Sorghum maturity Potato maturity Potato maturity Grape; 700 ppmv Grape; 700 ppmv Grape; 550 ppmv

0

MCSor98 MCSor99 Chip98 Chip99 CLAIRE94 CLAIRE95 CLIVARA96

−6 0 −1 −1 0 0 0

9 8

−0.4 −2

0.2

Pinter et al. (2000)

0.5 0.2

−7

2.4 1.9

Kobayashi et al. (2001) Kobayashi et al. (2001) Ottman et al. (2001) Ottman et al. (2001) Bindi et al. (1998) Bindi et al. (1998) Bindi et al. (1995a) Bindi et al. (1995a) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001b) Bindi, Fibbi, and Miglietta (2001b) Ottman et al. (2001) Ottman et al. (2001) Bindi et al. (1998) Bindi et al. (1998) Bindi et al. (1995a) Bindi et al. (1995a) Bindi, Fibbi, and Miglietta (2001) continues

Table II—continued Percentage increases due to elevated CO2 Ample water Very high N Experiment ID

Crop; condition

%

+SE

Ample N %

320

CLIVARA96

Grape; 700 ppmv

0

CLIVARA97

Grape; 550 ppmv

0

CLIVARA97

Grape; 700 ppmv (maturity)

0

+SE

Low water Low N %

+SE

Ample N %

+SE

References Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001) Bindi, Fibbi, and Miglietta (2001)

Soil changes: soil microbiology Biodegradation of wheat stems by white rot fungi after 6-week incubation MCWht93 Wheat 3.9 12.1 Arbuscular mycorrhizal fungi hyphal length (m g−1) in soil from FACE Sorghum experiment MCSor98 Sorghum 109 47 Water-stable soil aggregates MCSor98 Sorghum Soil N mineralization in laboratory incubations MCCot91 Cotton; 0–30 days MCCot91 Cotton; 30–60 days Soil N mineralization in laboratory incubations MCWht93–94 Wheat; depth, 0–5 cm MCWht93–94 Wheat: 5–10 cm MCWht93–94 Wheat: 10–20 cm

Akin et al. (1995) 267

104

Rillig et al. (2001)

32.0

13.8

27.5

4.2

Rillig et al. (2001)

−16.7 39.1

57.6 62.7

−14.2 107

50.9 211

Wood et al. (1994) Wood et al. (1994)

−36.8 12.3 −14.0

ns ns ns

Prior et al. (1997) Prior et al. (1997) Prior et al. (1997)

Net soil N mineralization Literature Gramminoid Literature Herbaceous (+Cotton) Literature Woody Nematodes in soil under cotton MCCot91 Cotton; June MCCot91 Cotton; August

12 8 5

6 7 40

Zak et al. (2000) Zak et al. (2000) Zak et al. (2000)

2.8 −0.1

8.2 11.4

Runion et al. (1994) Runion et al. (1994)

Rhizoctonia infection on soybean petiole sections after incubation in soil from FACE cotton experiment MCCot91 Cotton; June −1.4 4.2 MCCot91 Cotton; August 15.8 14.0

Runion et al. (1994) Runion et al. (1994)

Mycorrhizae (vesicular–arbuscular) colonization of cotton roots MCCot91 Cotton; June 14.4 MCCot91 Cotton; August 3.0

Runion et al. (1994) Runion et al. (1994)

10.2 7.5

321

Total microbial activity of soil from FACE cotton experiment determined from dehydrogenase assay MCCot91 Cotton; June 13.9 8.2 MCCot91 Cotton; August 19.5 10.1 Soil microbial respiration in laboratory incubations of soil from FACE cotton experiment MCCot91 Cotton; 0–30 days 18.5 28.5 MCCot91 Cotton: 30–60 days 45.0 42.9 Soil microbial respiration in laboratory incubations of soil from FACE wheat CO2 × water experiment MCWht93–94 Wheat; depth, 0–5 cm 20.7 ns MCWht93–94 Wheat: 5–10 cm −23.2 ns MCWht93–94 Wheat: 10–20 cm −39.8