U.S. Climate Change Science Program

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FEDERAL EXECUTIVE TEAM

Acting Director, Climate Change Science Program: ............................................... William J. Brennan

Director, Climate Change Science Program Office: ..................................................... Peter A. Schultz

Lead Agency Principal Representative to CCSP,

Director, Global Change Program Office, 

U.S. Department of Agriculture:........................................................................ William G. Hohenstein

Product Lead, Global Change Program Office,

U.S. Department of Agriculture:...............................................................................Margaret K. Walsh

Chair, Synthesis and Assessment Product Advisory

Group, Associate Director, National Center for

Environmental Assessment, U.S. Environmental

Protection Agency:....................................................................................................Michael W. Slimak

Synthesis and Assessment Product Coordinator, 

Climate Change Science Program Office: ............................................................... Fabien J.G. Laurier

Special Advisor, National Oceanic and Atmospheric

Administration: .............................................................................................................Chad A. McNutt

EDITORIAL AND PRODUCTION TEAM

Managing Editor, U.S. Department of Agriculture: .................................................Margaret K. Walsh

Editorial Coordinator and Chapter Editor, NCAR:............................................................ Greg Guibert

Editorial Coordinator and Chapter Editor, NCAR:..........................................................Rachel Hauser

Publication and Graphics Coordinator, NCAR:.....................................................................Carol Park

Layout Editor, NCAR: ........................................................................................................ Brian Bevirt

Scientific Editing and Review, NCAR:........................................................................... Kathy Hibbard

Web support, NCAR: ..................................................................................................... Kristin Conrad

Web support, NCAR:................................................................................................... Steve Aulenbach

Web support, NCAR:.......................................................................................................Erika Marcum

Graphic Design Support, Smudgeworks:....................................................................... Michael Shibao

Technical Advisor, Climate Change Science Program Office: .................................... David J. Dokken

Disclaimer: This document, part of the Synthesis and Assessment Products described in the U.S. Climate Change 

Science Program (CCSP) Strategic Plan, was prepared in accordance with Section 515 of the Treasury and 

General Government Appropriations Act for Fiscal Year 2001 (Public Law 106-554) and the information quality 

act guidelines issued by the U.S. Department of Agriculture pursuant to Section 515. The CCSP Interagency 

Committee relies on U.S. Department of Agriculture certifications regarding compliance with Section 515 

and Agency guidelines as the basis for determining that this product conforms with Section 515. For purposes 

of compliance with Section 515, this CCSP Synthesis and Assessment Product is an “interpreted product” as 

that term is used in the U.S. Department of Agriculture guidelines and is classified as “highly influential”. 

This document does not express any regulatory policies of the United States or any of its agencies, or provide 

recommendations for regulatory action.
Synthesis and Assessment Product 4.3

 Report by the U.S. Climate Change Science Program 

and the Subcommittee on Global Change Research

CONVENING LEAD AUTHORS:

Peter Backlund, Anthony Janetos, and David Schimel

MANAGING EDITOR:

Margaret Walsh

The Effects of Climate Change

on Agriculture, Land Resources, 

Water Resources, and Biodiversity 

in the United States
II

Members of Congress:

On behalf of the National Science and Technology Council, the U.S. Climate Change Science Program (CCSP) is 

pleased to transmit to the President and the Congress this Synthesis and Assessment Product (SAP), The Effects 

of Climate Change on Agriculture, Biodiversity, Land, and Water Resources in the United States. This is part of 

a series of 21 SAPs produced by the CCSP aimed at providing current assessments of climate change science to 

inform public debate, policy, and operational decisions. These reports are also intended to help the CCSP develop 

future program research priorities. This SAP is issued pursuant to Section 106 of the Global Change Research Act 

of 1990 (Public Law 101-606).

The CCSP’s guiding vision is to provide the Nation and the global community with the science-based knowledge 

needed to manage the risks and capture the opportunities associated with climate and related environmental changes. 

The SAPs are important steps toward achieving that vision and help to translate the CCSP’s extensive observational 

and research database into informational tools that directly address key questions being asked of the research 

community.

This SAP assesses the effects of climate change on U.S. land resources, water resources, agriculture, and biodiversity. 

It was developed with broad scientific input and in accordance with the Guidelines for Producing CCSP SAPs, the 

Federal Advisory Committee Act, the Information Quality Act, Section 515 of the Treasury and General Government 

Appropriations Act for fiscal year 2001 (Public Law 106-554), and the guidelines issued by the Department of 

Agriculture to Section 515.

We commend the report’s authors for both the thorough nature of their work and their adherence to an inclusive 

review process.

Sincerely,

Carlos M. Gutierrez Samuel W. Bodman John H. Marburger III

Secretary of Commerce Secretary of Energy Director, Office of Science

Chair, Committee on Vice Chair, Committee on and Technology Policy

Climate Change Science Climate Change Science Executive Director, Committee

and Technology Integration and Technology Integration on Climate Change Science and 

Technology Integration

June 2008
TABLE OF CONTENTS

Abstract ...............................................................................................................VII

Executive Summary...............................................................................................1

CHAPTER

1...........................................................................................................................11

Introduction

2...........................................................................................................................21

Agriculture

3...........................................................................................................................75

Land Resources: Forest and Arid Lands

4.........................................................................................................................121

Water Resources

5.........................................................................................................................151

Biodiversity

6.........................................................................................................................183

Synthesis

Appendix A: Acronyms and Glossary ..............................................................194

Appendix B: References ...................................................................................197

III
For the Report as a Whole:

CCSP, 2008: The effects of climate change on agriculture, land resources, water resources, and biodiversity in the United States. A 

Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. P. Backlund, A. Janetos,

D. Schimel, J. Hatfield, K. Boote, P. Fay, L. Hahn, C. Izaurralde, B.A. Kimball, T. Mader, J. Morgan, D. Ort, W. Polley, 

A. Thomson, D. Wolfe, M.G. Ryan, S.R. Archer, R. Birdsey, C. Dahm, L. Heath, J. Hicke, D. Hollinger, T. Huxman,

G. Okin, R. Oren, J. Randerson, W. Schlesinger, D. Lettenmaier, D. Major, L. Poff, S. Running, L. Hansen, D. Inouye, 

B.P. Kelly, L. Meyerson, B. Peterson, R. Shaw. U.S. Department of Agriculture, Washington, DC., USA, 362 pp

For the Executive Summary:

Backlund, P., A. Janetos, D.S. Schimel, J. Hatfield, M.G. Ryan, S.R. Archer, and D. Lettenmaier, 2008. Executive 

Summary. In: The effects of climate change on agriculture, land resources, water resources, and biodiversity in the United 

States. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Washington, DC., USA, 362 pp 

For Chapter 1: 

Backlund, P., D. Schimel, A. Janetos, J. Hatfield, M.G. Ryan, S.R. Archer, and D. Lettenmaier, 2008. Introduction. In: 

The effects of climate change on agriculture, land resources, water resources, and biodiversity in the United States. A Report 

by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Washington, DC., USA, 

362 pp 

For Chapter 2:

Hatfield, J., K. Boote, P. Fay, L. Hahn, C. Izaurralde, B.A. Kimball, T. Mader, J. Morgan, D. Ort, W. Polley, A. Thomson, 

and D. Wolfe, 2008. Agriculture. In: The effects of climate change on agriculture, land resources, water resources, and 

biodiversity in the United States. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global 

Change Research. Washington, DC., USA, 362 pp 

For Chapter 3:

Ryan, M.G., S.R. Archer, R. Birdsey, C. Dahm, L. Heath, J. Hicke, D. Hollinger, T. Huxman, G. Okin, R. Oren,

J. Randerson, and W. Schlesinger, 2008. Land Resources. In: The effects of climate change on agriculture, land resources, 

water resources, and biodiversity in the United States. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Washington, DC., USA, 362 pp 

For Chapter 4:

Lettenmaier, D., D. Major, L. Poff, and S. Running, 2008. Water Resources. In: The effects of climate change on agriculture, 

land resources, water resources, and biodiversity in the United States. A Report by the U.S. Climate Change Science Program 

and the Subcommittee on Global Change Research. Washington, DC., USA, 362 pp 

For Chapter 5:

Janetos, A., L. Hansen, D. Inouye, B.P. Kelly, L. Meyerson, B. Peterson, and R. Shaw, 2008. Biodiversity. In: The effects 

of climate change on agriculture, land resources, water resources, and biodiversity in the United States. A Report by the U.S. 

Climate Change Science Program and the Subcommittee on Global Change Research. Washington, DC., USA, 362 pp 

For Chapter 6:

Schimel, D., A. Janetos, P. Backlund, J. Hatfield, M.G. Ryan, S.R. Archer, D. Lettenmaier, 2008. Synthesis. In: The effects 

of climate change on agriculture, land resources, water resources, and biodiversity in the United States. A Report by the U.S. 

Climate Change Science Program and the Subcommittee on Global Change Research. Washington, DC., USA, 362 pp 

RECOMMENDED CITATIONS
AUTHOR TEAM FOR THIS REPORT

Executive Summary Lead Authors: Peter Backlund, NCAR; Anthony Janetos, PNNL/Univ. Maryland; 

David Schimel, National Ecological Observatory Network

Contributing Authors: Jerry Hatfield USDA ARS; Mike G. Ryan, USDA Forest 

Service; Steven Archer, Univ. Arizona; Dennis Lettenmaier, Univ. Washington

Chapter 1 Lead Authors: Peter Backlund, NCAR; David Schimel, National Ecological 

Observatory Network; Anthony Janetos, PNNL/Univ. Maryland

Contributing Authors: Jerry Hatfield USDA ARS; Mike G. Ryan, USDA Forest 

Service; Steven Archer, Univ. Arizona; Dennis Lettenmaier, Univ. Washington

Chapter 2 Lead Author: Jerry Hatfield, USDA ARS

Contributing Authors: Kenneth Boote, Univ. Florida; Philip Fay, USDA ARS; 

Leroy Hahn, Univ. Nebraska; César Izaurralde, PNNL/Univ. Maryland; Bruce 

A. Kimball, USDA ARS; Terry Mader, Univ. Nebraska-Lincoln; Jack Morgan, 

USDA ARS; Donald Ort, Univ. Illinois; Wayne Polley, USDA ARS; Allison 

Thomson, PNNL/Univ. Maryland; David Wolfe, Cornell Univ.

Chapter 3 Lead Authors: Mike G. Ryan, USDA Forest Service; Steven Archer,

Univ. Arizona

Contributing Authors: Richard Birdsey, USDA Forest Service; Cliff Dahm, 

Univ. New Mexico; Linda Heath, USDA Forest Service; Jeff Hicke, Univ. Idaho; 

David Hollinger, USDA Forest Service; Travis Huxman, Univ. Arizona; Gregory 

Okin, Univ. California-Los Angeles; Ram Oren, Duke Univ.; James Randerson, 

Univ. California-Irvine; William Schlesinger, Duke Univ.

Chapter 4 Lead Author: Dennis Lettenmaier, Univ. Washington

Contributing Authors: David Major, Columbia Univ.; Leroy Poff, Colo. State 

Univ.; Steve Running, Univ. Montana

Chapter 5 Lead Author: Anthony Janetos, PNNL/Univ. Maryland

Contributing Authors: Lara Hansen, World Wildlife Fund Intl.; David Inouye, 

Univ. Maryland; Brendan P. Kelly, Univ. Alaska and National Science Foundation; 

Laura Meyerson, Univ. Rhode Island; Bill Peterson, NOAA; Rebecca Shaw, The 

Nature Conservancy

Chapter 6 Lead Authors: David Schimel, National Ecological Observatory Network; 

Anthony Janetos, PNNL/Univ. Maryland; Peter Backlund, NCAR; 

Contributing Authors: Jerry Hatfield USDA ARS; Mike G. Ryan, USDA Forest 

Service; Steven Archer, Univ. Arizona; Dennis Lettenmaier, Univ. Washington

V
ACKNOWLEDGEMENTS

In addition to the authors, many people made important contributions to this document.

Special thanks are due to Margaret Walsh of the USDA Climate Change Program Office. Her 

contributions to the report and the successful completion of this project are too numerous to 

document. 

We are very appreciative of the excellent support from the project team at the University Corporation 

for Atmospheric Research (UCAR) and the National Center for Atmospheric Research (NCAR). From 

NCAR, Carol Park assisted with editing and research, and coordinated all aspects of the project; 

Greg Guibert and Rachel Hauser assisted with editing, technical writing, and research; Brian Bevirt 

contributed to editing and layout; and Kristin Conrad, Steve Aulenbach, and Erika Marcum provided 

web support. From the UCAR Communications Office, Nicole Gordon and Lucy Warner provided 

copy editing services. Michael Shibao of Smudgeworks provided graphic design services. 

We are also grateful to the members of the Committee for the Expert Review of Synthesis and 

Assessment Product 4.3 (CERSAP) who oversaw the project on behalf of USDA and provided helpful 

guidance and insightful comments: Thomas Lovejoy (Heinz Center for Science, Economics, and the 

Environment), J. Roy Black (Michigan State University), David Breshears (University of Arizona), 

Glenn Guntenspergen (USGS), Brian Helmuth (University of South Carolina), Frank Mitloehner 

(UC Davis), Harold Mooney (Stanford University), Dennis Ojima (Heinz Center), Charles Rice 

(Kansas State University), William Salas (Applied Geosciences LLC), William Sommers (George 

Mason University), Soroosh Sorooshian (UC Irvine), Eugene Takle (Iowa State University), and 

Carol Wessman (University of Colorado).

Lawrence Buja (NCAR Climate and Global Dynamics Division (CGD) and Julie Arblaster (NCAR/

CGD and the Australian Bureau of Meteorology) created and provided a series of figures showing 

projections of future climate conditions for the Introduction and Context chapter. Kathy Hibbard 

(NCAR/CGD) provided expert scientific input and review for the Biodiversity chapter. Timothy R. 

Green (Agricultural Engineer, USDA Agricultural Research Division) provided expert scientific 

input and review for aspects of the Water chapter. Chris Milly (USGS Continental Water, Climate, 

and Earth-System Dynamics Project), and Harry Lins (USGS Surface-water Program) also contributed to this chapter by providing figures 4.10 and 4.7, respectively. Figures 4.1 through 4.4 were 

prepared with assistance from Jennifer C. Adam (Washington State University). Authors in the Arid 

Land section of the Land Resources Chapter benefited from information generated by the Jornada 

and Sevilleta Long Term Ecological Research programs, and New Mexico’s Experimental Program 

to Stimulate Competitive Research (EPSCoR). Julio Betancourt (USGS) provided valuable discussions on exotic species invasions. Craig Allen (USGS) provided the thumbnail image of Bandelier 

National Monument.

Finally, we wish to thank everyone who took the time to read and provide comments on this document 

during its various stages of review.

VI
ABSTRACT

This report provides an assessment of the effects of climate change on U.S. agriculture, land 

resources, water resources, and biodiversity. It is one of a series of 21 Synthesis and Assessment Products (SAP) that are being produced under the auspices of the U.S. Climate Change 

Science Program (CCSP).

This SAP builds on an extensive scientific literature and series of recent assessments of the 

historical and potential impacts of climate change and climate variability on managed and 

unmanaged ecosystems and their constituent biota and processes. It discusses the nation’s 

ability to identify, observe, and monitor the stresses that influence agriculture, land resources, 

water resources, and biodiversity, and evaluates the relative importance of these stresses and 

how they are likely to change in the future. It identifies changes in resource conditions that are 

now being observed, and examines whether these changes can be attributed in whole or part 

to climate change. The general time horizon for this report is from the recent past through 

the period 2030-2050, although longer-term results out to 2100 are also considered.

There is robust scientific consensus that human-induced climate change is occurring. Records 

of temperature and precipitation in the United States show trends consistent with the current 

state of global-scale understanding and observations of change. Observations also show 

that climate change is currently impacting the nation’s ecosystems and services in significant 

ways, and those alterations are very likely to accelerate in the future, in some cases dramatically. Current observational capabilities are considered inadequate to fully understand and 

address the future scope and rate of change in all ecological sectors. Additionally, the complex 

interactions between change agents such as climate, land use alteration, and species invasion 

create dynamics that confound simple causal relationships and will severely complicate the 

development and assessment of mitigation and adaptation strategies.

Even under the most optimistic CO2 emission scenarios, important changes in sea level, 

regional and super-regional temperatures, and precipitation patterns will have profound 

effects. Management of water resources will become more challenging. Increased incidence of 

disturbances such as forest fires, insect outbreaks, severe storms, and drought will command 

public attention and place increasing demands on management resources. Ecosystems 

are likely to be pushed increasingly into alternate states with the possible breakdown of 

traditional species relationships, such as pollinator/plant and predator/prey interactions, adding 

additional stresses and potential for system failures. Some agricultural and forest systems may 

experience near-term productivity increases, but over the long term, many such systems are 

likely to experience overall decreases in productivity that could result in economic losses, 

diminished ecosystem services, and the need for new, and in many cases significant, changes 

to management regimes.

VII

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

1

EXECUTIVE SUMMARY

Lead Authors: Peter Backlund, NCAR; Anthony Janetos, PNNL/Univ.

Maryland; David Schimel, National Ecological Observatory Network

Contributing Authors: J. Hatfield, USDA ARS; M. G. Ryan, USDA 

Forest Service; S.R. Archer, Univ. Arizona; D. Lettenmaier, Univ. 

Washington 

1 Introduction and Background

This report is an assessment of the effects of climate change on U.S. land 

resources, water resources, agriculture, and biodiversity. It is one of a 

series of 21 Synthesis and Assessment Products being produced under 

the auspices of the U.S. Climate Change Science Program (CCSP), which 

coordinates the climate change research activities of U.S. government 

agencies. The lead sponsor of this particular assessment product is the 

U.S. Department of Agriculture (USDA). The project was led and coordinated by the National Center for Atmospheric Research (NCAR).

This assessment is based on extensive review of the relevant scientific literature and measurements and data 

collected and published by U.S. government agencies. The team of authors includes experts in the fields of 

agriculture, biodiversity, and land and water resources – scientists and researchers from universities, national 

laboratories, non-government organizations, and government agencies. To generate this assessment of the 

effects of climate and climate change, the authors conducted an exhaustive review, analysis, and synthesis 

of the scientific literature, considering more than 1,000 separate publications.

Scope

The CCSP agencies agreed on the following set of topics for this assessment. Descriptions of the major findings in each of these sectors can be found in Section 4 of this Executive Summary.

•	 Agriculture: (a) cropping systems, (b) pasture and grazing lands, and (c) animal management

•	 Land Resources: (a) forests and (b) arid lands

•	 Water Resources: (a) quantity, availability, and accessibility and (b) quality

•	 Biodiversity: (a) species diversity and (b) rare and sensitive ecosystems

The CCSP also agreed on a set of questions to guide the assessment process. Answers to these questions can

be found in Section 3 of this summary:

•	 What factorsinfluencing agriculture, land resources, water resources, and biodiversity in the United States

are sensitive to climate and climate change?

•	 How could changes in climate exacerbate or ameliorate stresses on agriculture, land resources, water

resources, and biodiversity? What are the indicators of these stresses?

•	 What current and potential observation systems could be used to monitor these indicators?

•	 Can observation systems detect changes in agriculture, land resources, water resources, and biodiversity

that are caused by climate change, as opposed to being driven by other causes?

Our charge from the CCSP was to address the specific topics and questions from the prospectus. This had

several important consequences for this report. We were asked not to make recommendations and we have

adhered to this request. Our document is not a plan for scientific or agency action, but rather an assessment

and analysis of current scientific understanding of the topics defined by the CCSP. In addition, we were 

asked not to define and examine options for adapting to climate change impacts. This topic is addressed in a 

separate CCSP Synthesis and Assessment Product. Our authors view adaptation as a very important issue and 

recognize that adaptation options will certainly affect the ultimate severity of many climate change impacts. 

Our findings and conclusions are relevant to informed assessment of adaptation options, but we have not 

attempted that task in this report.
The U.S. Climate Change Science Program Executive Summary

2

Time Horizon

Many studies of climate change have focused 

on the next 100 years. Model projections out 

to 2100 have become the de facto standard, 

as in the assessment reports produced by the 

Intergovernmental Panel on Climate Change 

(IPCC). This report has benefited greatly from 

such literature, but our main focus is on the 

recent past and the nearer-term future – the 

next 25 to 50 years. This period is within the 

planning horizon of many natural resources 

managers. Furthermore, the climate change that 

will occur during this period is relatively well 

understood. Much of this change will be caused 

by greenhouse gas emissions that have already 

happened. It is thus partially independent of 

current or planned emissions control measures 

and the large scenario uncertainty that affects 

longer-term projections. We report some results 

out to 100 years to frame our assessment, but 

we emphasize the coming decades.

Ascribing Confidence to Findings

The authors have endeavored to use consistent 

terms, agreed to by the CCSP agencies, to 

describe their confidence in the findings and 

conclusions in this report, particularly when 

these involve projections of future conditions 

and accumulation of information from multiple 

sources. The use of these terms represents the 

judgment of the authors of this document; 

much of the underlying literature does not use 

such a lexicon and we have not retroactively 

applied this terminology to previous studies 

by other authors.

Climate Context

There is a robust scientific consensus that 

human-induced climate change is occurring. 

The Fourth Assessment Report (AR4) of the 

IPCC, the most comprehensive and up-to-date 

scientific assessment of this issue, states with 

“very high confidence” that human activities, 

such as fossil fuel burning and deforestation, 

Figure 1 Language for Describing Confidence in Findings

have altered the global climate. During the 20th 

century, the global average surface temperature 

increased by about 0.6°C and global sea level 

increased by about 15 to 20 cm. Global precipitation over land increased about two percent during this same period. Looking ahead, human influences will continue to change Earth’s climate 

throughout the 21st century. The IPCC AR4 

projects that the global average temperature will 

rise another 1.1 to 5.4°C by 2100, depending 

on how much the atmospheric concentrations 

of greenhouse gases increase during this time. 

This temperature rise will result in continued increases in sea level and overall rainfall, changes 

in rainfall patterns and timing, and decline in 

snow cover, land ice, and sea ice extent. It is 

very likely that the Earth will experience a faster 

rate of climate change in the 21st century than 

seen in the last 10,000 years.

The United States warmed and became wetter 

overall during the 20th century, with changes 

varying by region. Parts of the South have cooled, 

while northern regions have warmed – Alaskan 

temperatures have increased by 2 to 4°C (more 

than four times the global average). Much of the 

eastern and southern United States now receive 

more precipitation than 100 years ago, while 

other areas, especially in the Southwest, receive 

less. The frequency and duration of heat waves

has increased, there have been large declines 

in summer sea ice in the Arctic, and there is 

some evidence of increased frequency of heavy

rainfalls. Observational and modeling results 

documented in the IPCC AR4 indicate that these 

trends are very likely to continue. Temperatures 

in the United States are very likely to increase 

by another 1oC to more than 4oC. The West and 

Southwest are likely to become drier, while the 

eastern United States is likely to experience 

increased rainfall. Heat waves are very likely to 

be hotter, longer, and more frequent, and heavy

rainfall is likely to become more frequent.

... our main focus is 

on the recent past 

and the nearer-term 

future – the next 

25 to 50 years. This 

period is within the 

planning horizon 

of many natural 

resources managers. 

Furthermore, the 

climate change that 

will occur during this 

period is relatively 

well understood.
3

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

2 Overarching 

Conclusions

Climate changes – temperature increases, 

increasing CO2 levels, and altered patterns 

of precipitation – are already affecting U.S. 

water resources, agriculture, land resources, 

and biodiversity (very likely). The literature 

reviewed for this assessment documents many 

examples of changes in these resources that are 

the direct result of variability and changes in 

the climate system, even after accounting for 

other factors. The number and frequency of

forest fires and insect outbreaks are increasing 

in the interior West, the Southwest, and Alaska. 

Precipitation, streamflow, and stream temperatures are increasing in most of the continental 

United States. The western United States is experiencing reduced snowpack and earlier peaks 

in spring runoff. The growth of many crops and 

weeds is being stimulated. Migration of plant 

and animal species is changing the composition 

and structure of arid, polar, aquatic, coastal, and

other ecosystems.

Climate change will continue to have significant effects on these resources over the 

next few decades and beyond (very likely). 

Warming is very likely to continue in the United 

States during the next 25 to 50 years, regardless 

of reductions in greenhouse gas emissions, due 

to emissions that have already occurred. U.S. 

ecosystems and natural resources are already being affected by climate system changes and variability. It is very likely that the magnitude and 

frequency of ecosystem changes will continue to

increase during this period, and it is possible that 

they will accelerate. As temperature rises, crops 

will increasingly experience temperatures above 

the optimum for their reproductive development, 

and animal production of meat or dairy products 

will be impacted by temperature extremes. Management of Western reservoir systems is very 

likely to become more challenging as runoff 

patterns continue to change. Arid areas are very 

likely to experience increases erosion and fire 

risk. In arid ecosystems that have not coevolved 

with a fire cycle, the probability of loss of iconic, 

charismatic megaflora such as Saguaro cacti and 

Joshua trees will greatly increase.

Many other stresses and disturbances are 

also affecting these resources (very likely).

For many of the changes documented in this assessment, there are multiple environmental drivers – land use change, nitrogen cycle changes, 

point and nonpoint source pollution, wildfires, 

invasive species – that are also changing. Atmospheric deposition of biologically available 

nitrogen compounds continues to be an important issue, along with persistent ozone pollution 

in many parts of the country. It is very likely 

that these additional atmospheric effects cause 

biological and ecological changes that interact 

with changes in the physical climate system. In 

addition, land cover and land use patterns are 

changing, e.g., the increasing fragmentation of 

U.S. forests as exurban development spreads to 

previously undeveloped areas, further raising 

fire risk and compounding the effects of summer 

drought, pests, and warmer winters. There are 

several dramatic examples of extensive spread 

of invasive species throughout rangeland and 

semiarid ecosystems in western states, and 

indeed throughout the United States. It is likely 

that the spread of these invasive species, which 

often change ecosystem processes, will exacerbate the risks from climate change alone. For example, in some cases invasive species increase 

fire risk and decrease forage quality.

Climate change impacts on ecosystems will 

affect the services that ecosystems provide, 

such as cleaning water and removing carbon 

from the atmosphere (very likely), but we do 

not yet possess sufficient understanding to 

project the timing, magnitude, and consequences of many of these effects. One of the 

main reasons to assess changes in ecosystems 

is to understand the consequences of those

changes for the delivery of services that our 

society values. There are many analyses of the 

impacts of climate change on individual species and ecosystems in the scientific literature, 

but there is not yet adequate integrated analysis

of how climate change could affect ecosystem 

services. A comprehensive understanding of 

impacts on these services will only be possible 

through quantification of anticipated alterations

in ecosystem function and productivity. As 

described by the Millennium Ecosystem Assessment, some products of ecosystems, such as 

food and fiber, are priced and traded in markets. 

Climate changes 

– temperature 

increases, 

increasing CO2

levels, and 

altered patterns 

of precipitation 

– are already 

affecting U.S. 

water resources, 

agriculture, land 

resources, and 

biodiversity.
The U.S. Climate Change Science Program Executive Summary

4

Others, such as carbon sequestration capacity,

are only beginning to be understood and traded 

in markets. Still others, such as the regulation of 

water quality and quantity and the maintenance

of soil fertility, while not priced and traded, are 

valuable nonetheless. Although these points 

are recognized and accepted in the scientific 

literature and increasingly among decision makers, there is no analysis specifically devoted to 

understanding changes in ecosystem services 

in the United States from climate change and 

associated stresses. It is possible to make 

some generalizations from the literature on the 

physical changes in ecosystems, but interpreting 

what these changes mean for services provided 

by ecosystems is very challenging and can only 

be done for a limited number of cases. This is a 

significant gap in our knowledge base.

Existing monitoring systems, while useful 

for many purposes, are not optimized for 

detecting the impacts of climate change on 

ecosystems. There are many operational and 

research monitoring systems in the United States 

that are useful for studying the consequences

of climate change on ecosystems and natural 

resources. These range from the resource- and 

species-specific monitoring systems that landmanagement agencies depend on to research 

networks, such as the Long-Term Ecological 

Research (LTER) sites, which the scientific 

community uses to understand ecosystem processes. All of the existing monitoring systems, 

however, have been put in place for other 

reasons, and none have been optimized specifically for detecting the effects and consequences

of climate change. As a result, it is likely that 

only the largest and most visible consequences

of climate change are being detected. In some 

cases, marginal changes and improvements to 

existing observing efforts, such as USDA snow 

and soil moisture measurement programs, could 

provide valuable new data detection of climate 

impacts. But more refined analysis and/or monitoring systems designed specifically for detecting climate change effects would provide more 

detailed and complete information and probably 

capture a range of more subtle impacts. Such 

systems, in turn, might lead to early-warning 

systems and more accurate forecasts of potential future changes. But it must be emphasized 

that improved observations, while needed, are 

not sufficient for improving understanding of 

ecological impacts of climate change. Ongoing, 

integrated and systematic analysis of existing 

and new observations could enable forecasting 

of ecological change, thus garnering greater 

value from observational activities, and contribute to more effective evaluation of measurement 

needs. This issue is addressed in greater detail 

in Section 3.

3 Key Questions and 

Answers

This section presents a set of answers to the 

guiding questions posed by the CCSP agencies,

derived from the longer chapters that follow this 

Executive Summary.

What factors influencing agriculture, land 

resources, water resources, and biodiversity 

in the United States are sensitive to climate 

and climate change? Climate change affects 

average temperatures and temperature extremes; 

timing and geographical patterns of precipitation; snowmelt, runoff, evaporation, and soil 

moisture; the frequency of disturbances, such

as drought, insect and disease outbreaks, severe 

storms, and forest fires; atmospheric composition and air quality; and patterns of human

settlement and land use change. Thus, climate 

change leads to myriad direct and indirect effects on U.S. ecosystems. Warming temperatures have led to effects as diverse as altered 

timing of bird migrations, increased evaporation, and longer growing seasons for wild and 

domestic plant species. Increased temperatures 

often lead to a complex mix of effects. Warmer 

summer temperatures in the western United 

States have led to longer forest growing seasons 

but have also increased summer drought stress, 

vulnerability to insect pests, and fire hazard. 

Changes to precipitation and the size of storms 

affect plant-available moisture, snowpack and 

snowmelt, streamflow, flood hazard, and water 

quality.

How could changes in climate exacerbate 

or ameliorate stresses on agriculture, land 

resources, water resources, and biodiversity? 

What are the indicators of these stresses?

Ecosystems and their services (land and water 

resources, agriculture, biodiversity) experiExisting monitoring 

systems, while useful 

for many purposes, 

are not optimized 

for detecting 

the impacts of 

climate change on 

ecosystems.
5

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

ence a wide range of stresses, including pests 

and pathogens, invasive species, air pollution, 

extreme events, wildfires and floods. Climate 

change can cause or exacerbate direct stress 

through high temperatures, reduced water 

availability, and altered frequency of extreme

events and severe storms. It can ameliorate stress 

through warmer springs and longer growing 

seasons, which, assuming adequate moisture,

can increase agricultural and forest productivity. 

Climate change can also modify the frequency

and severity of stresses. For example, increased 

minimum temperatures and warmer springs 

extend the range and lifetime of many pests 

that stress trees and crops. Higher temperatures 

and/or decreased precipitation increase drought 

stress on wild and crop plants, animals and 

humans. Reduced water availability can lead to 

increased withdrawals from rivers, reservoirs, 

and groundwater, with consequent effects on

water quality, stream ecosystems, and human

health.

What current and potential observation 

systems could be used to monitor these indicators? A wide range of observing systems 

within the United States provides information on 

environmental stress and ecological responses. 

Key systems include National Aeronautics and 

Space Administration (NASA) research satellites, operational satellites and ground-based 

observing networks from the National Oceanic 

and Atmospheric Administration (NOAA) in 

the Department of Commerce, Department of 

Agriculture (USDA) forest and agricultural 

survey and inventory systems, Department of 

Interior/U.S. Geological Survey (USGS) stream 

gauge networks, Environmental Protection 

Agency (EPA) and state-supported water quality observing systems, the Department of Energy (DOE) Ameriflux network, and the LTER 

network and the proposed National Ecological 

Observing Network (NEON) sponsored by the 

National Science Foundation (NSF). However, 

many key biological and physical indicators are 

not currently monitored, are monitored haphazardly or with incomplete spatial coverage, or are 

monitored only in some regions. In addition, the 

information from these disparate networks is not 

well integrated. Almost all of the networks were 

originally instituted for specific purposes unrelated to climate change and cannot necessarily 

be adapted to address these new questions.

Climate change presents new challenges for 

operational management. Understanding climate 

impacts requires monitoring both many aspects

of climate and a wide range of biological and 

physical responses. Putting climate change 

impacts in the context of multiple stresses and 

forecasting future servicesrequires an integrated

analysis. Beyond the problems of integrating 

the data sets, the nation has limited operational 

capability for integrated ecological monitoring, 

analyses, and forecasting. A few centers exist, 

aimed at specific questions and/or regions, but

no coordinating agency or center has the mission 

to conduct integrated environmental analysis 

and assessment by pulling this information 

together.

Operational weather and climate forecasting 

provides an analogy. Weather-relevant observations are collected in many ways, ranging from 

surface observations through radiosondes to 

operational and research satellites. These data 

are used at a handful of university, federal, and 

private centers as the basis for analysis, understanding, and forecasting of weather through 

highly integrative analyses blending data and 

models. This operational activity requires

substantial infrastructure and depends on federal, university, and private sector research for 

continual improvement. By contrast, no such 

integrative analysis of comprehensive ecological information is carried out, although the 

scientific understanding and societal needs have 

probably reached the level where an integrative 

and operational approach is both feasible and 

desirable.

Can observation systems detect changes in 

agriculture, land resources, water resources, 

and biodiversity that are caused by climate 

change, as opposed to being driven by other 

causes? In general, the current suite of observing systems is reasonably able overall to monitor ecosystem change and health in the United 

States, but neither the observing systems nor 

the current state of scientific understanding is 

Warming 

temperatures have led 

to effects as diverse 

as altered timing 

of bird migrations, 

increased evaporation, 

and longer growing 

seasons for wild 

and domestic plant 

species.
The U.S. Climate Change Science Program Executive Summary

6

adequate to rigorously quantify climate contributions to ecological change and separate these 

from other influences. Monitoring systems for 

measuring long-term response of agriculture

to climate and other stresses are numerous, 

but integration across these systems is limited. 

There is no coordinated national network for 

monitoring changes in land resources associated with climate change, most disturbances, 

such as storms, insects, and diseases, and 

changes in land cover/land use. No aspect of 

the current hydrologic observing system was 

designed specifically to detect climate change 

or its effects on water resources. The monitoring systems that have been used to evaluate the 

relationship between changes in the physical 

climate system and biological diversity were 

likewise not designed with climate variability 

or change in mind.

So for the moment, there is no viable alternative 

to using the existing systems for identifying 

climate change and its impacts on U.S. agriculture, land resources, water resources, and biodiversity, even though these systems were not 

originally designed for this purpose. There has 

obviously been some considerable success so far 

in doing so, but there is limited confidence that 

the existing systems provide a true early warning 

system capable of identifying potential impacts 

in advance. The authors of this report also have 

very limited confidence in the ability of current 

observation and monitoring systems to provide 

the information needed to evaluate the effectiveness of actions that are taken to mitigate or adapt 

to climate change impacts. Furthermore, we 

emphasize that improvements in observations 

and monitoring of ecosystems, while desirable, 

are not sufficient by themselves for increasing 

our understanding of climate change impacts. 

Experiments that directly manipulate climate 

and observe impacts are critical for developing 

more detailed information on the interactions 

of climate and ecosystems, attributing impacts 

to climate, differentiating climate impacts from 

other stresses, and designing and evaluating 

response strategies. Much of our understanding 

of the direct effects of temperature, elevated 

CO2, ozone, precipitation, and nitrogen deposition has come from manipulative experiments. 

Institutional support for such experiments is a 

concern.

4 Sectoral Findings

Agriculture

The broad subtopics considered in this section are cropping systems, pasture and grazing 

lands, and animal management. The many U.S. 

crops and livestock varieties (valued at about 

$200 billion in 2002) are grown in diverse climates, regions, and soils. No matter the region, 

however, weather and climate factors such as 

temperature, precipitation, CO2 concentrations, 

and water availability directly impact the health 

and well-being of plants, pasture, rangeland, 

and livestock. For any agricultural commodity, 

variation in yield between years is related to 

growing-season weather; weather also influences insects, disease, and weeds, which in turn 

affect agricultural production.

•	 With increased CO2 and temperature, the life 

cycle of grain and oilseed crops will likely 

progress more rapidly. But, as temperature 

rises, these crops will increasingly begin to 

experience failure, especially if climate variability increases and precipitation lessens or 

becomes more variable.

•	 The marketable yield of many horticultural

crops – e.g., tomatoes, onions, fruits – is very 

likely to be more sensitive to climate change 

than grain and oilseed crops.

•	 Climate change islikely to lead to a northern

migration of weeds. Many weeds respond 

more positively to increasing CO2 than 

most cash crops, particularly C3 “invasive” 

weeds. Recent research also suggests that 

glyphosate, the most widely used herbicide 

in the United States, loses its efficacy on 

weeds grown at the increased CO2 levels 

likely in the coming decades.

•	 Disease pressure on crops and domestic

animals will likely increase with earlier 

springs and warmer winters, which will allow proliferation and higher survival rates of 

pathogens and parasites. Regional variation 

in warming and changes in rainfall will also 

affect spatial and temporal distribution of 

disease.

Climate change is 

likely to lead to a 

northern migration 

of weeds.
7

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

•	 Projected increases in temperature and a

lengthening of the growing season will likely 

extend forage production into late fall and 

early spring, thereby decreasing need for 

winter season forage reserves. However, 

these benefits will very likely be affected 

by regional variations in water availability.

•	 Climate change-induced shifts in plant species are already under way in rangelands. 

Establishment of perennial herbaceous 

species is reducing soil water availability 

early in the growing season. Shifts in plant 

productivity and type will likely also have 

significant impact on livestock operations.

•	 Higher temperatures will very likely reduce

livestock production during the summer 

season, but these losses will very likely be 

partially offset by warmer temperatures 

during the winter season. For ruminants, 

current management systems generally do 

not provide shelter to buffer the adverse effects of changing climate; such protection is 

more frequently available for non-ruminants

(e.g., swine and poultry).

•	 Monitoring systemsfor measuring long-term

response of agricultural lands are numerous, but integration across these systems is 

limited. Existing state-and-transition models 

could be expanded to incorporate knowledge 

of how agricultural lands and products respond to global change; integration of such 

models with existing monitoring efforts 

and plant developmental data bases could 

provide cost-effective strategies that both enhance knowledge of regional climate change 

impacts and offer ecosystem management 

options. In addition, at present, there are 

no easy and reliable means to accurately 

ascertain the mineral and carbon state of 

agricultural lands, particularly over large 

areas; a fairly low-cost method of monitoring 

biogeochemical response to global change 

would be to sample ecologically important 

target species in different ecosystems.

Land Resources

The broad subtopics considered in this section 

are forest lands and arid lands. Climate strongly 

influences forest productivity, species composition, and the frequency and magnitude of disturbances that impact forests. The effect of climate 

change on disturbances such as forest fire, insect 

outbreaks, storms, and severe drought will 

command public attention and place increasing 

demands on management resources. Disturbance and land use will control the response of 

arid lands to climate change. Many plants and 

animals in arid ecosystems are near their physiological limits for tolerating temperature and 

water stress and even slight changes in stress 

will have significant consequences. In the near

term, fire effects will trump climate effects on 

ecosystem structure and function.

•	 Climate change has very likely increased

the size and number of forest fires, insect 

outbreaks, and tree mortality in the interior 

West, the Southwest, and Alaska, and will 

continue to do so.

•	 Rising CO2 will very likely increase photosynthesis for forests, but this increase will 

likely only enhance wood production in 

young forests on fertile soils.

•	 Nit rogen deposition and warmer temperatures have very likely increased forest 

growth where adequate water is available

and will continue to do so in the near 

future.

•	 The combined effects of rising temperatures

and CO2, nitrogen deposition, ozone, and 

forest disturbance on soil processes and soil 

carbon storage remains unclear.

•	 Higher temperatures, increased drought, and

more intense thunderstorms will very likely 

increase erosion and promote invasion of 

exotic grass species in arid lands.

•	 Climate change in arid lands will create

physical conditions conducive to wildfire, 

and the proliferation of exotic grasses will 

provide fuel, thus causing fire frequencies

to increase in a self-reinforcing fashion.

Climate change has 

very likely increased 

the size and number 

of forest fires, insect 

outbreaks, and 

tree mortality in 

the interior West, 

the Southwest, and 

Alaska, and will 

continue to do so.
The U.S. Climate Change Science Program Executive Summary

8

•	 In arid regions where ecosystems have not

coevolved with a fire cycle, the probability 

of loss of iconic, charismatic megaflora such 

as saguaro cacti and Joshua trees is very 

likely.

•	 Arid lands very likely do not have a large

capacity to absorb CO2 from the atmosphere 

and will likely lose carbon as climateinduced disturbance increases.

•	 River and riparian ecosystems in arid lands

will very likely be negatively impacted 

by decreased streamflow, increased water 

removal, and greater competition from nonnative species.

•	 Changes in temperature and precipitation

will very likely decrease the cover of vegetation that protects the ground surface from 

wind and water erosion.

•	 Current observing systems do not easily

lend themselves to monitoring change associated with disturbance and alteration of 

land cover and land use, and distinguishing 

such changes from those driven by climate 

change. Adequately distinguishing climate

change influences is aided by the collection 

of data at certain spatial and temporal resolutions, as well as supporting ground truth 

measurements. 

Water Resources

The broad subtopics considered in this section 

are water quantity and water quality. Plants,

animals, natural and managed ecosystems, and 

human settlements are susceptible to variations 

in the storage, fluxes, and quality of water, all

of which are sensitive to climate change. The 

effects of climate on the nation’s water storage 

capabilities and hydrologic functions will have 

significant implications for water management 

and planning as variability in natural processes 

increases. Although U.S. water management 

practices are generally quite advanced, particularly in the West, the reliance on past conditions 

as the foundation for current and future planning 

and practice will no longer be tenable as climate 

change and variability increasingly create conditions well outside of historical parameters and 

erode predictability.

•	 Most of the United States experienced increases in precipitation and streamflow and 

decreases in drought during the second half 

of the 20th century. It is likely that these 

trends are due to a combination of decadalscale variability and long-term change.

•	 Consistent with streamflow and precipitation observations, most of the continental 

United States experienced reductions in 

drought severity and duration over the 20th 

century. However, there is some indication 

of increased drought severity and duration 

in the western and southwestern United 

States.

•	 There is a trend toward reduced mountain

snowpack and earlier spring snowmelt runoff peaks across much of the western United 

States. This trend is very likely attributable at least in part to long-term warming, 

although some part may have been played 

by decadal-scale variability, including a 

shift in the phase of the Pacific Decadal 

Oscillation in the late 1970s. Where earlier 

snowmelt peaks and reduced summer and 

fall low flows have already been detected, 

continuing shifts in this direction are very 

likely and may have substantial impacts on 

the performance of reservoir systems.

•	 Water quality is sensitive to both increased

water temperatures and changes in precipitation. However, most water quality changes

observed so far across the continental United 

States are likely attributable to causes other 

than climate change.

•	 Stream temperatures are likely to increase

as the climate warms, and are very likely 

to have both direct and indirect effects on 

aquatic ecosystems. Changes in temperature will be most evident during low flow 

periods, when they are of greatest concern. 

Stream temperature increases have already 

begun to be detected across some of the United States, although a comprehensive analysis 

similar to those reviewed for streamflow 

trends has yet to be conducted.

Stream 

temperatures are 

likely to increase 

as the climate 

warms, and are very 

likely to have both 

direct and indirect 

effects on aquatic 

ecosystems.
9

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

•	 A suite of climate simulations conducted

for the IPCC AR4 show that the United 

States may experience increased runoff in 

eastern regions, gradually transitioning to 

little change in the Missouri and lower Mississippi, to substantial decreases in annual 

runoff in the interior of the west (Colorado 

and Great Basin).

•	 Trendstoward increased water use efficiency

are likely to continue in the coming decades. 

Pressures for reallocation of water will 

be greatest in areas of highest population 

growth, such as the Southwest. Declining 

per capita (and, for some cases, total) water 

consumption will help mitigate the impacts 

of climate change on water resources.

•	 Essentially no aspect of the current hydrologic observing system was designed specifically to detect climate change or its effects 

on water resources. Recent efforts have the 

potential to make improvements, although 

many systems remain technologically obsolete, incompatible, and/or have significant 

data collection gaps in their operational and 

maintenance structures. As a result, many of 

the data are fragmented, poorly integrated, 

and unable to meet the predictive challenges 

of a rapidly changing climate. 

Biodiversity

The broad subtopics considered in this section 

are species diversity and rare and sensitive 

ecosystems. Biodiversity, the variation of life 

at the genetic, species, and ecosystem levels 

of biological organization, is the fundamental 

building block of the services that ecosystems 

deliver to human societies. It is intrinsically 

important both because of its contribution to the 

functioning of ecosystems, and because it is difficult or impossible to recover or replace, once 

it is eroded. Climate change is affecting U.S. 

biodiversity and ecosystems, including changes 

in growing season, phenology, primary production, and species distributions and diversity. It is 

very likely that climate change will increase in 

importance as a driver for changes in biodiversity over the next several decades, although for 

most ecosystems it is not currently the largest 

driver of change.

•	 There has been a significant lengthening

of the growing season and increase in net 

primary productivity (NPP) in the higher 

latitudes of North America. Over the last 19 

years, global satellite data indicate an earlier 

onset of spring across the temperate latitudes 

by 10 to 14 days.

•	 In an analysis of 866 peer-reviewed papers

exploring the ecological consequences of

climate change, nearly 60 percent of the 

1598 species studied exhibited shifts in their 

distributions and/or phenologies over the 20- 

and 140-year time frame. Analyses of fieldbased phenological responses have reported 

shifts as great as 5.1 days per decade, with 

an average of 2.3 days per decade across all 

species.

•	 Subtropical and tropical corals in shallow

waters have already suffered major bleaching 

events that are clearly driven by increases in 

sea surface temperatures. Increases in ocean 

acidity, which are a direct consequence of

increases in atmospheric carbon dioxide, are 

calculated to have the potential for serious 

negative consequences for corals.

•	 The rapid rates of warming in the Arctic

observed in recent decades, and projected 

for at least the next century, are dramatically 

reducing the snow and ice covers that provide denning and foraging habitat for polar 

bears.

•	 There are other possible, and even probable,

impacts and changes in biodiversity (e.g., 

disruption of the relationships between pollinators, such as bees, and flowering plants), 

for which we do not yet have a substantial 

observational database. However, we cannot conclude that the lack of complete observations is evidence that changes are not 

occurring.

•	 It is difficult to pinpoint changes in ecosystem services that are specifically related to 

changes in biological diversity in the United 

States. A specific assessment of changes in 

ecosystem services for the United States as 

a consequence of changesin climate or other

drivers of change has not been done.
The U.S. Climate Change Science Program

10

Executive Summary

•	 The monitoring systemsthat have been used

to evaluate the relationship between changes 

in the physical climate system and biological 

diversity have three components: speciesspecific or ecosystem-specific monitoring 

systems, research activities specifically 

designed to create time-series of population data and associated climatic and other 

environmental data, and spatially extensive 

observations derived from remotely sensed 

data. However, in very few cases were these 

monitoring systems established with climate 

variability and climate change in mind, so 

the information that can be derived from 

them specifically for climate-change-related 

studies is somewhat limited. It is also not 

clear that existing networks can be maintained for long enough to enable careful 

time-series studies to be conducted.

It is also not 

clear that existing 

networks can be 

maintained for long 

enough to enable 

careful time-series 

studies to be 

conducted.
11

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Introduction

Lead Authors: Peter Backlund, NCAR; Anthony Janetos, PNNL/

Univ. Maryland; David Schimel, National Ecological Observatory 

Network

Contributing Authors: J. Hatfield, USDA ARS; M.G. Ryan, USDA 

Forest Service; S. R. Archer, Univ. Arizona; D. Lettenmaier, Univ. 

Washington

This report is an assessment of the effects of 

climate change on U.S. land resources, water 

resources, agriculture, and biodiversity. It is 

based on extensive examination of the relevant 

scientific literature, and is one of a series of 21 

Synthesis and Assessment Products that are 

being produced under the auspices of the U.S. 

Climate Change Science Program (CCSP). The 

lead sponsor of this particular assessment product is the U.S. Department of Agriculture.

The purpose of this assessment and more 

broadly, of all the CCSP Scientific Assessment Products (SAPs) is to integrate existing 

scientific knowledge on issues and questions

related to climate change that are important to 

policy and decision makers. The assessments 

are meant to support informed discussion and 

decision makers by a wide audience of potential 

stakeholders, including, for example, federal and 

state land managers, private citizens, private 

industry, and non-governmental organizations. 

The scientific research community is also an important stakeholder, as an additionally important 

feature of the SAPs is to inform decision making 

about the future directions and priorities of the 

federal scientific research programs by pointing 

out where there are important knowledge gaps. It 

is a goal of the SAPs that they not only be useful 

and informative scientific documents, but that 

they are also accessible and understandable to a 

more general, well-informed public audience.

The team of authors was selected by the agencies 

after asking for public comment, and it includes 

scientists and researchers from universities, 

non-governmental organizations, and government agencies, coordinated by the National 

Center for Atmospheric Research (NCAR). The 

team has reviewed hundreds of peer-reviewed 

papers, guided by a prospectus agreed upon by 

the CCSP agencies (see Appendix C).

Intent of this Report

Strong scientific consensus highlights that 

anthropogenic effects of climate change are 

already occurring and will be substantial 

(IPCC). A recent U.S. government analysis 

(GAO) shows that that U.S. land management 

agencies are not prepared to address this issue. 

This analysis also highlights the need for assessment of climate change impacts on U.S. 

natural resources and assessment of monitoring 

systems needed to provide information to support effective decision making about mitigation 

and adaptation in periods of potentially rapid 

change. This report addresses this issue by providing an assessment specific to U.S. natural 

resources in agriculture, land resources, water 

resources, and biodiversity, and by assessing 

the ability of existing monitoring systems to aid 

decision making. The report documents that (1) 

numerous, substantial impacts of climate change 

on U.S. natural resources are already occurring, 

(2) that these are likely to become exacerbated 

as warming progresses, and (3) that existing 

monitoring systems are insufficient to address 

this issue.

CHAPTER

1

This report is an 

assessment of the 

effects of climate 

change on U.S. 

land resources, 

water resources, 

agriculture, and 

biodiversity.
The U.S. Climate Change Science Program

12

Chapter 1

Scope of this Report

The overall scope of the report has been 

determined by agreement among the CCSP 

agencies. Important features of the scope include 

the topics to be addressed:

Agriculture

•	 Cropping systems

•	 Pasture and grazing lands

•	 Animal management

Land Resources

•	 Forests

•	 Arid lands

Water Resources

•	 Quantity, availability, and accessibility

•	 Quality

Biodiversity

•	 Species diversity

•	 Rare and sensitive ecosystems

Equally important are the elements of the climate change problem that are not addressed by 

this report. Some key issues, such as climate 

impacts on freshwater ecosystems, did not 

receive extensive attention. This is mainly due 

to timing and length constraints – it does not 

represent a judgment on the part of the authors 

that such impacts are not important. In addition, 

while the report was specifically asked to address issues of climate impacts, it was not asked 

to address the challenge of what adaptation and 

management strategies exist, their potential 

effectiveness, and potential costs. While these 

topics are acknowledged to be important in 

the scientific literature (Parsons et al.; Granger 

Morgan et al.; U.S. National Assessment), they 

are the subject of another of the CCSP Synthesis 

and Assessment Products (4.4). Nevertheless, 

the information synthesized in this report is 

meant to be of use to stakeholders concerned 

with planning, undertaking, and evaluating the 

effectiveness of adaptation options. 

This report also deals almost exclusively with 

biological, ecological, and physical impacts of 

climate change. With the exception of some 

information in agricultural systems, market 

impacts on natural resources are not discussed, 

nor are the potential costs or benefits of changes 

in the management of natural resources. We 

recognize that this leaves an incomplete picture 

of the overall impacts of climate change on 

those resources that the nation considers significant. Again, however, further consideration 

of economic effects requires a firm foundation

in understanding the biological, ecological, and 

physical impacts. 

Guiding Questions for this Report

This synthesis and assessment report builds on 

an extensive scientific literature and series of 

recent assessments of the historical and potential 

impacts of climate change and climate variability on managed and unmanaged ecosystems and 

their constituent biota and processes. It discusses 

the nation’s ability to identify, observe, and 

monitor the stresses that influence agriculture, 

land resources, water resources, and biodiversity, and evaluates the relative importance of 

these stresses and how they are likely to change 

in the future. It identifies changes in resource 

conditions that are now being observed, and 

examines whether these changes can be attributed in whole or part to climate change. It 

also highlights changes in resource conditions 

that recent scientific studies suggest are most 

likely to occur in response to climate change, 

and when and where to look for these changes. 

The assessment is guided by five overarching 

questions:

What factors influencing agriculture, land 

resources, water resources, and biodiversity 

in the United States are sensitive to climate 

and climate change?

How could changes in climate exacerbate or 

ameliorate stresses on agriculture, land resources, water resources, and biodiversity?

What are the indicators of these stresses?

What current and potential observation 

systems could be used to monitor these 

indicators?

Can observation systems detect changes in 

agriculture, land resources, water resources, 

and biodiversity that are caused by climate 

change, as opposed to being driven by other 

causal activities?

Strong scientific 

consensus highlights 

that anthropogenic 

effects of climate 

change are already 

occurring and 

will be substantial 

(IPCC).
13

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Ascribing Confidence to Findings

The authors of this document have used language agreed to by the CCSP agencies to describe their confidence in findings that project 

future climate changes and impacts, as shown 

in Figure 1.1. The intent is to use a limited set 

of terms in a systematic and consistent fashion 

to communicate clearly with readers. The use of 

these terms represents the qualitative judgment

of the authors of this document; much of the 

underlying literature does not use such a lexicon. 

Unless explicitly describing a formal statistical 

analysis, the use of these terms by the authors of 

this assessment should be treated as a statement 

of their expert judgment in the confidence of our 

findings and conclusions. There are cases where 

we have not applied the agreed terminology 

because we felt it was not an accurate representation of work published by others.

Time Horizon for this Report

Climate change is a long-term issue and will 

affect the world for the foreseeable future. 

Many studies of climate change have focused 

on the next 100 years and model projections 

out to 2100 have become the de facto standard, 

as reported in the assessment reports produced 

by the Intergovernmental Panel on Climate 

Change (IPCC) and many other documents. In 

this report, however, the focus is on the midterm future. Key results are reported out to 100 

years to frame the report, but the emphasis is on 

the next 25-50 years.

This mid-term focus is chosen for several reasons. First, for many natural resources, planning 

and management activities already address these 

time scales through the development of longlived infrastructure, forest rotations, and other 

significant investments. Second, we will experience significant warming from greenhouse gas 

emissions that have already occurred, regardless 

of the effectiveness of any emissions reduction 

activities. And most emission scenarios for the 

next few decades do not significantly diverge 

from each other because it will take decades to 

make major changes in energy infrastructure in 

the U.S. and other nations. As a result, high- and 

low-emission scenarios only begin to separate 

strongly in the 2030s-2050s. As emissions diverge, so do climate projections, and uncertainty 

about future climates rapidly becomes more 

pronounced. Averaging over climate models, 

a rate of a few tenths of a degree per decade 

can be assumed likely for the next two to four 

decades.

Global Climate Context

There is a robust scientific consensus that 

human-induced climate change is occurring. 

The recently released Fourth Assessment Report 

of the IPCC (IPCC AR4) states with “very high 

confidence,” that human activity has caused the 

global climate to warm. Many well-documented 

observations show that fossil fuel burning, deforestation, and other industrial processes are 

rapidly increasing the atmospheric concentrations of CO2 and other greenhouse gases. The 

IPCC report describes an increasing body of 

observations and modeling results, summarized 

below, which show that these changes in atmospheric composition are changing the global 

climate and beginning to affect terrestrial and 

marine ecosystems.

The global-average surface temperature 

increased by about 0.6°C over the 20th 

century. Global sea level increased by about 

15-20 cm during this period.

Figure 1.1 Language for discussing confidence in findings.

Climate change is 

a long-term issue 

and will affect 

the world for 

the foreseeable 

future.
The U.S. Climate Change Science Program

14

Chapter 1

Observations since 1961 show that the average 

temperature of the global ocean has increased 

to depths of at least 3,000 meters, and that the 

ocean has been absorbing more than 80 percent of the heat added to the climate system.

Long-term temperature records from ice 

sheets, glaciers, lake sediments, corals, tree 

rings, and historical documents show that 

1995-2004 was the warmest decade worldwide 

in the last 1-2,000 years. Nine of the 10 warmest years on record occurred since 1996.

Global precipitation over land increased about 

2 percent over the last century, with considerable variability by region (Northern Hemisphere precipitation increased by about 5 to 10 

percent during this time, while West Africa and 

other areas experienced decreases).

Mountain glaciers are melting worldwide, 

Greenland’s ice sheet is melting, the extent 

and thickness of Arctic sea ice is declining, 

and lakes and rivers freeze later in the fall and 

melt earlier in the spring. The growing season 

Figure 1.2 Temperatures of the Last Millennium and the Next Century. The effects of historical reconstructions of solar variability and volcanic eruptions were modeled using an NCAR climate model and 

compared to several reconstructions of past temperatures. The model reproduces many temperature 

variations of the past 1,000 years, and shows that solar and volcanic forcing has been a considerable impact 

on past climate. When only 20th century solar and volcanic data are used, the model fails to reproduce 

the recent warming, but captures it well when greenhouse gases are included.
15

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

in the Northern Hemisphere has lengthened 

by about 1 to 4 days per decade in the last 40 

years, especially at high latitudes.

The ranges of migrating birds, and some fish 

and insect species are changing. Tropical 

regions are losing animal species, especially 

amphibians, to warming and drying. 

Although much (but not all) of recent increases 

have been in nighttime maximum temperatures 

rather than daytime maxima, the expectation 

for the future is that daytime temperatures 

will become increasingly responsible for higher 

overall average temperatures. 

Change and variability are persistent features of 

climate, and the anthropogenic climate change 

now occurring follows millennia of strictly 

natural climate changes and variability. Paleoclimate records, including natural archives in tree 

rings, corals, and glacial ice, now show that the 

climate of the last millennium has varied significantly with hemispheric-to-global changes 

in temperature and precipitation resulting from 

the effects of the sun, volcanoes, and the climate 

system’s natural variability (Ammann et al. 

2007). The anthropogenic changes now being 

observed are superimposed on this longer-term, 

ongoing variability, some of which can be reproduced by today’s advanced climate models. 

Importantly, the model that captures the past 

thousand years of global temperature patterns 

successfully (Figure 1.2) using only solar and 

volcanic inputs does not accurately simulate the 

20th century’s actual, observed climate unless 

greenhouse gases are factored in (Ammann et 

al. 2007).

It is also clear that human influences will continue to alter Earth’s climate throughout the 21st 

century. The IPCC AR4 describes a large body 

of modeling results, which show that changes in 

atmospheric composition will result in further 

increases in global average temperature and sea 

level, and continued declines in snow cover, 

land ice, and sea ice extent. Global average 

rainfall, variability of rainfall, and heavy rainfall 

events are projected to increase. Heat waves in 

Europe, North America, and other regions will 

become more intense, more frequent, and longer

lasting. It is very likely that the rate of climate 

change in the 21st century will be faster than 

that seen in the last 10,000 years. The IPCC 

AR4 contains projections of the temperature 

increases that would result from a variety of 

different emissions scenarios:

If atmospheric concentration of CO2 increases 

to about 550 parts per million (ppm), global 

average surface temperature would likely increase by about 1.1-2.9oC by 2100.

If atmospheric concentration of CO2 increases 

to about 700 ppm, global average surface temperature would likely increase about 1.7-4.4oC 

by 2100.

If atmospheric concentration of CO2 increases 

to about 800 ppm, global average surface temperature would likely increase about 2.0-5.4oC 

by 2100.

Even if atmospheric concentration of CO2

were stabilized at today’s concentrations of 

about 380 ppm, global average surface temperatures would likely continue to increase by 

another 0.3–0.9oC by 2100.

U.S. Climate Context

Records of temperature and precipitation in the 

United States show trends that are consistent 

with the global-scale changes discussed above. 

The United States has warmed significantly 

overall, but change varies by region (Figure 1.3). 

Some parts of the United States have cooled, but 

Alaska and other northern regions have warmed 

significantly. Much of the eastern and southern 

U.S. now receive more precipitation than 100 

years ago, while other areas, especially in the 

Southwest, now receive less (Figure 1.4).

The scenarios of global temperature change 

discussed in the global climate context section 

above would result in large changes in U.S. 

temperatures and precipitation, with considerable variation by region. Figure 1.5, which is 

based on multiple model simulations, show how 

IPCC global scenario A1B, generally considered 

a moderate emissions growth scenario, would 

affect U.S. temperatures and precipitation by 

2030. The projected temperature increases range 

The United States 

has warmed 

significantly 

overall, but change 

varies by region.
The U.S. Climate Change Science Program

16

Chapter 1

from approximately 1°C in the southeastern 

United States, to more than 2°C in Alaska and 

northern Canada, with other parts of North 

America having intermediate values.

Although precipitation increases are anticipated 

for large areas of the U.S., it is important to note 

this does not necessarily translate into more 

available moisture for biological and ecological 

processes. Higher temperatures increase evapotranspirative losses to the atmosphere, and the 

relative balance of the two factors on average 

in the U.S. leads to less moisture in soils and 

surface waters for organisms or ecosystems to 

utilize both now and in the future.

The average temperature and precipitation are 

not the only factors that affect ecosystems. 

Extreme climate conditions, such as droughts, 

heavy rainfall, snow events, and heat waves 

affect individual species and ecosystems structure and function. Change in the incidence of 

extreme events could thus 

have major impacts on U.S. 

ecosystems and must be 

considered when assessing 

vulnerability to and impacts 

of climate change. Figure 

1.6 shows how the IPCC 

A1B scenario will change 

the incidence of heat waves 

and warm nights by approximately 2030. Figure 1.7 

shows projected changes 

in frost days and growing 

season.

Figure 1.4 Precipitation changes over the past century from the same weather stations as 

for temperature. The changes are shown as percentage changes from the long-term average. 

Courtesy of NOAA’s National Climate Data Center and the U.S. Geological Survey.

Figure 1.3 Mapped trends in temperature across the lower 48 states and Alaska. These 

data, which show the regional pattern of U.S. warming, are averaged from weather stations across the country using stations that have as complete, consistent, and high quality 

records as can be found. Courtesy of NOAA’s National Climate Data Center and the U.S. 

Geological Survey.

Extreme climate 

conditions, such 

as droughts, heavy 

rainfall, snow events, 

and heat waves affect 

individual species and 

ecosystems structure 

and function.
17

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 1.5 U.S. Temperature and Precipitation Changes by 2030. This figure shows how U.S. temperatures and precipitation 

would change by 2030 under IPCC emissions scenario A1B, which would increase the atmospheric concentration of greenhouse gases to about 700 parts per million by 2100 (this is roughly double the pre-industrial level). The changes are shown 

as the difference between two 20-year averages (2020-2040 minus 1980-1999). These results are based on simulations from 

nine different climate models from the IPCC AR4 multi-model ensemble. The simulations were created on supercomputers at 

research centers in France, Japan, Russia, and the United States. Adapted by Lawrence Buja and Julie Arblaster from Tebaldi 

et al. 2006: Climatic Change, Going to the extremes; An intercomparison of model-simulated historical and future changes in 

extreme events, Climatic Change, 79:185-211.

Figure 1.6 Simulated U.S. Heat Wave Days and Warm Nights in 2030. The left panel shows the projected change in number of 

heat wave days (days with maximum temperature higher by at least 5°C (with respect to the climatological norm)). The right panel 

shows changes in warm nights (percent of times when minimum temperature is above the 90th percentile of the climatological 

distribution for that day). Both panels show results for IPCC emissions scenario A1B, which would increase the atmospheric 

concentration of greenhouse gases to about 700 parts per million by 2100 (this is roughly double the pre-industrial level). The 

changes are shown as the difference between two 20-year averages (2020-2040 minus 1980-1999). Shading indicates areas of 

high inter-model agreement. These results are based on simulations from nine different climate models from the IPCC AR4 

multi-model ensemble. The simulations were created on supercomputers at research centers in France, Japan, Russia, and the 

United States. Adapted by Lawrence Buja and Julie Arblaster from Tebaldi et al. 2006: Climatic Change, Going to the extremes; 

An intercomparison of model-simulated historical and future changes in extreme events, Climatic Change, 79:185-211.
The U.S. Climate Change Science Program

18

Chapter 1

Ecological and Biological Context

Climate variability and change have many 

impacts on terrestrial and marine ecosystems. 

Ecosystem responses to climate have implications for sustainability, biodiversity, and the 

ecosystem goods and services available to society. Some of these impacts affect the biological 

systems only, but some create further feedbacks 

to the climate system through greenhouse gas 

fluxes, albedo changes, and other processes.

Much research on terrestrial ecosystems and 

climate change has focused on their role as 

carbon sources or sinks. The observation that 

atmospheric CO2 was increasing more slowly 

than expected from fossil fuel use and ocean 

uptake led to the speculation of a “missing 

sink,” and the conclusion that increased plant 

photosynthesis was due to elevated atmospheric 

CO2 (Gifford et al. 1994). It is now evident that 

several mechanisms, and not just CO2 fertilization, contribute to the ‘missing sink’ (Field et al. 

2007). These mechanisms include recovery from 

historic land use, fertilizing effects of nitrogen in 

the environment, expansion of woody vegetation 

ranges, storage of carbon in landfills and other 

depositional sites, and sequestration in longlived timber products (Schimel et al. 2001).

Responses of photosynthesis and other processes that contribute to overall plant growth 

to warming are nonlinear. Each process (e.g., 

Figure 1.7 Changes in U.S. Frost days and Growing season by 2030. This figure shows decreases in frost days and increases in growing 

season length that would occur by about 2030 if the world follows IPCC emissions scenario A1B, which would increase the atmospheric 

concentration of greenhouse gases to about 700 parts per million by 2100 (this is roughly double the pre-industrial level). The changes 

are shown as the difference between two 20-year averages (2020-2040 minus 1980-1999). Shading indicates areas of high inter-model 

agreement. These results are based on simulations from nine different climate models from the IPCC AR4 multi-model ensemble. The 

simulations were created on supercomputers at research centers in France, Japan, Russia, and the United States. Adapted by Lawrence 

Buja and Julie Arblaster from Tebaldi et al. 2006: Climatic Change, Going to the extremes; An intercomparison of model-simulated 

historical and future changes in extreme events, Climatic Change, 79:185-211.
19

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

photosynthesis, respiration) typically has its own 

optimal response to temperature, which then 

decreases as temperatures change either below 

or above that optimum. The response of plants 

from different ecosystems is usually adapted to 

local conditions. Extreme hot and cold events affect photosynthesis and growth and may reduce 

carbon uptake or even cause mortality. Warming can lead to either increased or decreased 

plant growth, depending on the balance of the 

response of the individual processes.

Comprehensive analyses show that climate 

change is already causing the shift of many 

species to higher latitudes and/or altitudes, 

as well as changes in phenology. Not all species can successfully adjust, and some models 

suggest that biomes that are shifting in a warm, 

high-CO2 world lose an average of a tenth of 

their biota.

Climate will affect ecosystems through fire, 

pest outbreaks, diseases, and extreme weather, 

as well as through changes to photosynthesis 

and other physiological processes. Disturbance 

regimes are a major control of climate-biome 

patterns. Fire-prone ecosystems cover about half 

the land area where forests would be expected, 

based on climate alone, and lead to grasslands 

and savannas in some of these areas. Plant 

pathogens, and insect defoliators are pervasive 

as well, and annually affect more than 40 times 

the acreage of forests in the United States damaged by fire. Disturbance modifies the climatic 

conditions where a vegetation type can exist.

While much of the ecosystems and climate 

change literature focuses on plants and soil processes, significant impacts on animal species are 

also known. A substantial literature documents 

impacts on the timing of bird migrations, on the 

latitudinal and elevational ranges of species and 

on more complex interactions between species, 

e.g., when predator and prey species respond to 

climate differently, breaking their relationships 

(Parmesan and Yohe 2003). The seasonality of 

animal processes may also respond to changes 

in climate, and this effect can have dramatic 

consequences, as occurs, for example, with

changes in insect pest or pathogen-plant host 

interactions. Domestic animals also respond 

significantly to climate, both through direct 

physiological impacts on livestock, and through 

more complex effects of climate on livestock 

and their habitats.

Marine and coastal ecosystems are similarly 

sensitive in general to variability and change in 

the physical climate system, and in some cases 

directly to atmospheric concentrations of carbon 

dioxide. Fish populations in major large marine 

biomes are known to shift their geographic 

ranges in response to specific modes of climate 

variation, such as the Pacific Decadal Oscillation and the North Atlantic Oscillation, and 

there have been shifts in geographical range of 

some fish species in response to surface water 

warming over the past several decades on both 

West and East coasts of North America. Subtropical and tropical corals in shallow waters 

have already suffered major bleaching events 

that are clearly driven by increases in sea surface 

temperatures, and increases in ocean acidity, 

which are a direct consequence of increases in

atmospheric carbon dioxide, are calculated to 

have the potential for serious negative consequences for corals.

Many studies on climate impacts on ecosystems 

look specifically at impacts only of variation and 

change in the physical climate system and CO2

concentrations. But there are many factors that 

affect the distribution, complexity, make-up, and 

performance of ecosystems. Disturbance, pests, 

invasive species, deforestation, human management practices, overfishing, etc., are powerful 

influences on ecosystems. Climate change 

impacts are but one of many such features, and 

need to be considered in this broader context.

Attribution of Ecosystem Changes

It is important to note that the changes due to 

climate change occur against a background of 

rapid changes in other factors affecting ecosystems. These include changing patterns of land 

management, intensification of land use and 

exurban development, new management practices (e.g., biofuel production), species invasions 

and changing air quality (Lodge et al. 2006).

Because many factors are affecting ecosystems 

simultaneously, it is difficult and in some cases 

impossible to factor out the magnitude of each 

Not all species can 

successfully adjust, 

and some models 

suggest that biomes 

that are shifting 

in a warm, highCO2 world lose an 

average of a tenth of 

their biota.
The U.S. Climate Change Science Program

20

Chapter 1

impact separately. In a system affected by, for 

example, temperature, ozone, and changing precipitation, assigning a percentage of an observed 

change to each factor is generally impossible. 

Research on improving techniques for separating influences is ongoing, but in some cases 

drivers of change interact with each other, making the combined effects different from the sum 

of the separate effects. Scientific concern about 

such multiple stresses is rising rapidly.

Summary

The changes in temperature and precipitation 

over the past century now form a persistent 

pattern and show features consistent with the 

scientific understanding of climate change. For 

example, scientists expect larger changes near 

the poles than near the equator. This pattern

can be seen in the dramatically higher rates of 

warming in Alaska compared to the rest of the 

country. Most of the warming is concentrated 

in the last decades of the century. Prior to that, 

large natural variations due to solar and volcanic effects were comparable in magnitude to 

the then-lower greenhouse gas effects. These 

natural swings sometimes enhanced and sometimes hid the effects of greenhouse gases. The 

warming due to greenhouse gases is now quite

large and the “signal” of the greenhouse warming has more clearly emerged from the “noise” 

of the planet’s natural variations. The effects of 

greenhouse gases have slowly accumulated, but 

in the past few years, their effects have become 

evident. Recent data show clearly both the trends 

in climate, and climate’s effects on many aspects 

of the nation’s ecology.

The changes that are likely to occur will continue to have significant effects on the ecosystems of the United States, and the services 

those ecosystems provide. The balance of this 

report will document some of the observed historical changes and provide insights into how 

the continuing changes may affect the nation’s 

ecosystems.

The changes that 

are likely to occur 

will continue to 

have significant 

effects on the 

ecosystems of 

the United States, 

and the services 

those ecosystems 

provide.
21

CHAPTER

2

2.1 Introduction

This synthesis and assessment report builds on 

an extensive scientific literature and series of 

recent assessments of the historical and potential 

impacts of climate change and climate variability on managed and unmanaged ecosystems 

and their constituent biota and processes. It 

identifies changes in resource conditions that 

are now being observed, and examines whether 

these changes can be attributed in whole or part 

to climate change. It also highlights changes in 

resource conditions that recent scientific studies 

suggest are most likely to occur in response to 

climate change, and when and where to look 

for these changes. As outlined in the Climate 

Change Science Program (CCSP) Synthesis and 

Assessment Product 4.3 (SAP 4.3) prospectus, 

this chapter will specifically address climaterelated issues in cropping systems, pasture and 

grazing lands, and animal management.

In this chapter the focus is on the near-term 

future. In some cases, key results are reported 

out to 100 years to provide a larger context but 

the emphasis is on the next 25-50 years. This 

nearer term focus is chosen for two reasons. 

First, for many natural resources, planning and 

management activities already address these 

time scales through the development of longlived infrastructure, plant species rotation, and 

other significant investments. Second, climate 

projections are relatively certain over the next 

few decades. Emission scenarios for the next 

Agriculture

Lead Author: J. L. Hatfield, USDA ARS

Contributing Authors: 

Cropland Response: K.J. Boote, B.A. Kimball, D.W. Wolfe, D.R. Ort

Pastureland: R.C. Izaurralde, A.M. Thomson

Rangeland: J.A. Morgan, H.W. Polley, P.A. Fay

Animal Management: T.L. Mader, G.L. Hahn

few decades do not diverge from each other 

significantly because of the “inertia” of the 

energy system. Most projections of greenhouse 

gas emissions assume that it will take decades to 

make major changes in the energy infrastructure, 

and only begin to diverge rapidly after several 

decades have passed (30-50 years).

To average consumers, U.S. agricultural production seems uncomplicated – they see only the 

staples that end up on grocery store shelves. The 

reality, however, is far from simple. Valued at 

$200 billion in 2002, agriculture includes a wide 

range of plant and animal production systems 

(Figure 2.1).

The United States Department of Agriculture 

(USDA) classifies 116 plant commodity groups 

as agricultural products, as well as four livestock 

groupings (beef cattle, dairy, poultry, swine) 

and products derived from animal production, 

e.g., cheese or eggs. Of these commodities, 

52 percent of the total sales value is generated 

from livestock, 21 percent from fruit and nuts, 

20 percent from grain and oilseed, two percent 

from cotton, and five percent from other commodity production, not including pastureland or 

rangeland production (Figure 2.2).

The many U.S. crops and livestock varieties are 

grown in diverse climates, regions, and soils. No 

matter the region, however, weather and climate 

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity
The U.S. Climate Change Science Program

22

Chapter 2

characteristics such as temperature, precipitation, carbon dioxide (CO2), and water availability directly impact the health and well-being 

of plants and livestock, as well as pasture and 

rangeland production. The distribution of crops 

and livestock is also determined by the climatic 

resources for a given region and U.S. agriculture 

Market Value of Agricultural

Products Sold: 2002

1 Dot = $20,000,000

United States Total

$200,646,355,000

Figure 2.1 The extensive and intensive nature of U.S. agriculture is best represented in the context of the value 

of the production of crops and livestock. The map above presents the market value of all agricultural products 

sold in 2002 and their distribution. (USDA National Agricultural Statistics Service.)

Figure 2.2 The sales value of individual crops and 

livestock is represented at right. As the chart indicates, crops and livestock represent approximately 

equal portions of the commodity value. (USDA 

National Agricultural Statistics Service.)

has benefited from optimizing the adaptive areas 

of crops and livestock. For any commodity, 

variation in yield between years is related to 

growing-season weather effects. These effects 

also influence how insects, disease, and weeds 

affect agricultural production.
23

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

The goal in this chapter is to provide a synthesis 

of the potential impacts of climate on agriculture 

that can be used as a baseline to understand the 

consequences of climate variability. A variety

of agricultural crops will be considered in 

this report. Among them is corn (Zea mays), 

the most widely distributed U.S. crop after 

pastureland and rangeland; wheat, which is 

grown in most states, but has a concentration 

in the upper Great Plains and northwest United 

States; and orchard crops, which are restricted 

to regions with moderate winter temperatures. 

For any of these crops, shifts in climate can affect production through, for instance, variance 

in temperature during spring (flowering) and 

fall (fruit maturity).

Additionally, this chapter will look at beef 

cow production, which is ubiquitous across

the United States (Figure 2.3). Because of the 

regular presence of beef cows across the nation, 

beef cow vitality provides an effective indicator 

of the regional impact of climate change. While 

beef cows are found in every state, the greatest 

number are raised in regions that have an abundance of native or planted pastures (Figure 2.4), 

which provide easy access to accessible feed 

supplies for the grazing animals.

Over the past 25 years, there has been a decline 

in land classified as rangeland, pastureland, 

or grazed forest. Many of these shifts relate 

to changing land use characteristics, such as 

population growth (Table 2.1); the growing 

eastern U.S. has experienced the greatest reduction in such land resources (Table 2.2). This 

chapter will provide an overview of the state of 

pasturelands and rangelands as defined by the 

USDA. Pastureland is a land cover/use category 

of land managed primarily for the production of 

introduced forage plants for livestock grazing. 

Pastureland cover may consist of a single species in a pure stand, a grass mixture, or a grasslegume mixture. Management usually consists 

of cultural treatments: fertilization, weed 

control, reseeding or renovation, and control of 

grazing. Rangeland is a land cover/use category 

on which the climax or potential plant cover is 

Figure 2.3 Distribution of beef cow inventory across the United States 

in 2002. (USDA National Agricultural Statistics Service.)

Figures 2.4a and 2.4b Distribution of pastureland and rangeland across 

the United States in 1997.
The U.S. Climate Change Science Program

24

Chapter 2

composed principally of native grasses, grasslike plants, forbs, or shrubs suitable for grazing 

and browsing, and introduced forage species that 

are managed like rangeland. This would include 

areas where introduced hardy and persistent 

grasses, such as crested wheatgrass, are planted 

and such practices as deferred grazing, burning, 

chaining, and rotational grazing are used, with 

little or no chemicals or fertilizer applied. This 

chapter will also consider the effects of climate 

on these areas.

Year Rangeland

Pastureland

(millions of acres)

Grazed

Forest land

(millions of acres)

Total

(millions of acres)

1982 415.5 131.1 64.3 610.9

1992 406.7 125.2 61.0 592.9

1997 404.9 119.5 58.0 582.4

2001 404.9 119.2 55.2 579.3

2003 405.1 117.0 54.3 576.4

Table 2.1 Non-federal grazing land (in millions of acres). Source: Natural Resources Conservations Service 

(NRCS).

Table 2.2 Changes in pasturelands by major water resource areas (in millions of acres). 

Source: www.nrcs.usda.gov/technical/land/nri03/national_landuse.html

1982 1992 2003

Arkansas-White-Red 18.6 19.0 19.8

California / Great Basin 2.3 2.2 2.3

Great Lakes 5.8 4.7 4.4

Lower Colorado / Upper Colorado 0.8 0.9 0.9

Lower Mississippi 5.6 5.4 5.0

Missouri 20.4 19.2 18.0

New England / Mid Atlantic 7.4 6.3 5.6

Ohio / Tennessee River 20.9 19.8 17.7

Pacific Northwest 4.6 4.7 4.3

Souris- Red-Rainy / Upper Mississippi 14.5 12.7 11.7

South Atlantic-Gulf 15.5 15.9 13.9

Texas-Gulf / Rio Grande 14.7 14.4 13.4

Totals 131.1 125.2 117.0

2.2 Observed Changes and

Responses

2.2.1 Crops

2.2.1.1 Scope of the Agricultural 

Systems

As noted earlier, agriculture is a diverse system 

that covers a wide range of species and production systems across the United States. However, 

this chapter’s scope includes species covered 

in the available scientific literature that evaluates observed responses to changing climate 
25

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

characteristics. In the crops section, the focus 

is on maize (corn), soybean (Glycine max), 

wheat (Triticum aestivum), rice (Oryza sativa), 

sorghum (Sorghum bicolor), cotton (Gossypium hirsutum), peanut (Arachis hypogea), 

dry kidney bean (Phaseolus vulgaris), cowpea 

(Vigna unguiculata), and tomato (Lycopersicon 

esculentum).

Animal production systems cover beef cattle, 

dairy, swine, and poultry as the primary classes 

of animals. While climate changes affect all 

of these animals, the literature predominantly 

addresses beef, dairy, and swine. Poultry are 

primarily grown in housed operations, so the 

effect of climate change more directly affects 

the energy requirements for building operations compared to a direct effect on the animal. 

Similar statements can be made for swine production since the vast majority of the animals 

are housed. Temperature affects animals being 

moved from buildings to processing plants, but 

because these animals are moved quickly from

production to processing, this is a problem only 

in extreme conditions.

Both pasture and rangeland are reviewed in this 

chapter. In the pastureland section, 13 species 

are considered in the analysis; for rangeland, 

species include a complex mixture of grasses 

and forbs, depending on the location.

As much as possible, the conclusions about 

the effects of global change on agriculture and 

other ecosystems are based on observed trends 

as much as possible. However, an immediate 

obstacle to using this observational approach is 

that the productivity of most agricultural enterprises has increased dramatically over the past 

decades due to improvements in technology, 

and the responses to these changes in technology overwhelm responses to global change that 

almost certainly are present but are statistically 

undetectable against the background of large 

technological improvements. Fortunately, numerous manipulative experiments have been 

conducted on these managed agricultural systems wherein temperature, CO2, ozone (O3), 

and/or other factors have been varied. From 

such experiments, the relative responses to the 

changing climate variables can be deduced.

A second challenge, however, is that the details of each experiment have been different 

– different temperature changes have been 

explored, different concentrations of CO2, different crop varieties and so forth. The problem 

remains as to how to represent such experimental variability in methods in a way that provides 

a consistent baseline for comparison.

As noted in the Introduction, in about 30 years, 

CO2 concentrations are expected to have increased about 60 ppm (from today’s 380 ppm 

to about 440 ppm), and temperatures over the 

contiguous United States are expected to have 

increased by an average of about 1.2oC. We 

have therefore used these increments as baseline 

comparison points compared to current CO2 and 

temperatures to estimate the likely responses 

of crops to global change for the 30-year time 

horizon of this report. We have done this by 

constructing mathematical response functions 

for crops and experiments that use the experimental data available.

2.2.1.2 Plant Response to

 Temperature

2.2.1.2.1 General Response

Crop species differ in their cardinal temperatures (critical temperature range) for life cycle 

development. There is a base temperature for 

vegetative development, at which growth commences, and an optimum temperature, at which 

the plant develops as fast as possible. Increasing 

temperature generally accelerates progression 

of a crop through its life cycle (phenological) 

phases, up to a species-dependent optimum 

temperature. Beyond this optimum temperature, 

development (node and leaf appearance rate) 

slows. Cardinal temperature values are presented below, in Tables 2.3 and 2.4, for selected 

annual (non-perennial) crops under conditions in 

which temperature is the only limiting variable.

One caveat is that the various scenarios for global change predict increasing air temperatures, 

but plants often are not growing at air temperature. For example, under arid conditions, amply 

irrigated crops can easily be 10°C cooler than air 

temperature due to transpirational cooling. Solar 

and sky radiation, wind speed, air humidity, and 

plant stomatal conductance are all variables that 

affect the difference in temperature between 

plants and air. While recognizing this problem, 

it is important to understand that published 

cardinal temperatures such as those in Tables 

The goal in this 

chapter is to 

provide a synthesis 

of the potential 

impacts of climate 

on agriculture 

that can be used 

as a baseline to 

understand the 

consequences of 

climate variability.
The U.S. Climate Change Science Program

26

Chapter 2

2.3 and 2.4 are based on air temperature, rather 

than vegetation temperature. That is because air 

temperatures are much easier to measure than 

plant temperatures, and usually only air temperatures are reported from experiments; also 

many crop growth models assume that plants are 

growing at air temperature rather than at their 

own vegetation temperature. Nevertheless, crop 

canopy temperatures are sufficiently coupled to 

air temperatures that for a first approximation, 

we expect future crop canopy temperatures to 

increase by about the same amount as air temperatures with global warming.

Faster development of non-perennial crops is 

not necessarily ideal. A shorter life cycle results 

in smaller plants, shorter reproductive phase 

duration, and lower yield potential. Because of 

this, the optimum temperature for yield is nearly 

always lower than the optimum temperature 

for leaf appearance rate, vegetative growth, or 

reproductive progression. In addition, temperatures that fall below or above specific thresholds 

1Kiniry and Bonhomme (1991):, 2Muchow et al. (1990); 3Herrero and Johnson (1980); 4Hesketh et al. (1973); 5Boote et al. (1998); 

6Boote et al. (1997); 7Boote et al. (2005); 8Hodges and Ritchie (1991); 9Kobza and Edwards (1987); 10Chowdury and Wardlaw (1978); 

11Tashiro and Wardlaw (1990); 12Alocilja and Ritchie (1991); 13Baker et al. (1995); 14Matsushima et al. (1964); 15Horie et al. (2000); 

16Alagarswamy and Ritchie 1991); 17Prasad et al. (2006a); 18Maiti (1996); 19Downs (1972); 20K.R. Reddy et al. (1999, 2005); 21V.R. 

Reddy et al. (1995); 22K.R. Reddy et al. (2005); 23K.R. Reddy et al. (1992a, 1992b); 24Ong (1986); 25Bolhuis and deGroot (1959); 

26Prasad et al. (2003); 27Williams et al. (1975); 28Prasad et al. (2002); 29Laing et al. (1984); 30Adams et al. (2001); 31Peat et al. (1998).

Crop

Base 

Temp Veg

Opt Temp 

Veg

Base Temp 

Repro

Opt Temp 

Repro

Opt Temp 

Range

Veg Prod

Opt Temp 

Range 

Reprod 

Yield

Failure 

Temp 

Reprod 

Yield

Maize 81 341 81 341 18-222 353

Soybean 74 304 65 265 25-376 22-246 397

Wheat 08 268 18 268 20-309 1510 3411

Rice 812 3613 812 3312 3314 23-2613,15 35-3613

Sorghum 816 3416 816 3117 26-3418 2517,19 3517

Cotton 1420 3720 1420 28-3020 3421 25-2622 3523

Peanut 1024 >3024 1124 29-3325 31-3526 20-2626,27 3926

Bean 2328 23-2428,29 3228

Tomato 730 2230 730 2230 22-2530 3031

Table 2.3. For several economically significant crops, information is provided regarding cardinal, base, and optimum temperatures (oC) for vegetative development and reproductive development, optimum temperature for 

vegetative biomass, optimum temperature for maximum grain yield, and failure (ceiling) temperature at which 

grain yield fails to zero yield. The optimum temperatures for vegetative production, reproductive (grain) yield, 

and failure point temperatures represent means from studies where diurnal temperature range was up to 10oC.

at critical times during development can also 

have significant impact on yield. Temperature 

affects crop life cycle duration and the fit of 

given cultivars to production zones. Day-length 

sensitivity also plays a major role in life cycle 

progression in many crops, but especially for 

soybean. Higher temperatures during the reproductive stage of development affect pollen 

viability, fertilization, and grain or fruit formation. Chronic as well as short-term exposure to 

high temperatures during the pollination stage 

of initial grain or fruit set will reduce yield 

potential. This phase of development is one of 

the most critical stages of growth in response 

to temperatures extremes. Each crop has a 

specific temperature range at which vegetative 

and reproductive growth will proceed at the 

optimal rate and exposures to extremely high 

temperatures during these phases can impact 

growth and yield; however, acute exposure from 

extreme events may be most detrimental during 

the reproductive stages of development.
27

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Table 2.4 Temperature thresholds for selected vegetable crops. Values are approximate, and for relative comparisons among groups only. For frost sensitivity: “+” = sensitive to weak frost; “-” = relatively insensitive; “( )” 

= uncertain or dependent on variety or growth stage. Adapted from Krug (1997) and Rubatzky and Yamaguchi 

(1997).

Climatic 

Classification Crop

Acceptable 

Temp (C) For 

Germination

Opt Temp 

(C)

For Yield

Acceptable Temp (C)

Growth Range

Frost 

Sensitivity

Hot Watermelon 21-35 25-27 18-35 +

Okra 21-35 25-27 18-35 +

Melon 21-32 25-27 18-35 +

Sweet Potato 21-32 25-27 18-35 +

Warm Cucumber 16-35 20-25 12-30(35) +

Pepper 16-35 20-25 12-30(35) +

Sweet corn 16-35 20-25 12-30(35) +

Snap bean 16-30 20-25 12-30(35) +

Tomato 16-30 20-25 12-30(35) +

Cool-Warm Onion 10-30 20-25 7-30 -

Garlic 7-25 20-25 7-30 -

Turnip 10-35 18-25 5-25 -

Pea 10-30 18-25 5-25 ( )

Cool Potato 7-26 16-25 5-25(30) +

Lettuce 5-26 16-25 5-25(30) (+)

Cabbage 10-30 16-18(25) 5-25 -

Broccoli 10-30 16-18(25) 5-25 -

Spinach 4-16 16-18(25) 5-25 -

For most perennial, temperate fruit and nut 

crops, winter temperatures play a significant role 

in productivity (Westwood 1993). There is considerable genotypic variation among fruit and 

nut crops in their winter hardiness (that is, the 

ability to survive specific low temperature extremes), and variation in their “winter chilling” 

requirement for optimum flowering and fruitset

in the spring and summer (Table 2.5). Placement 

of fruit and nut crops within specific areas are 

related to the synchrony of phenological stages 

to the climate and the climatic resources of the 

region. Marketable yield of horticultural crops is 

highly sensitive to minor environmental stresses 

related to temperatures outside the optimal 

range, which negatively affect visual and flavor 

quality (Peet and Wolfe 2000).

2.2.1.2.2 Temperature effects on crop yield

Yield responses to temperature vary among 

species based on the crop’s cardinal temperature 

requirements. Plantsthat have an optimum range

at cooler temperatures will exhibit significant 

decreases in yield as temperature increases 

above this range. However, reductions in yield 

with increasing temperature in field conditions 

may not be due to temperature alone, as high 

temperatures are often associated with lack of 

rainfall in many climates. The changes in temperature do not produce linear responses with 

increasing temperature because the biological 

response to temperature is nonlinear, therefore, 

as the temperature increases these effects will be 

larger. The interactions of temperature and water 

deficits negatively affect crop yield.
The U.S. Climate Change Science Program

28

Chapter 2

2.2.1.2.2.1 Maize

Increasing temperature causes the maize life 

cycle and duration of the reproductive phase 

to be shortened, resulting in decreased grain 

yield (Badu-Apraku et al. 1983; Muchow et al. 

1990). In the analyses of Muchow et al. (1990), 

the highest observed (and simulated) grain 

yields occurred at locations with relatively cool 

temperatures (growing season mean of 18.0 to 

19.8oC in Grand Junction, Colo.), which allowed 

long maize life cycles, compared to warmer sites 

(e.g., 21.5 to 24.0oC in Champaign, Ill.), or compared to warm tropical sites (26.3 to 28.9oC). For 

Table 2.5 Winter chill requirement, winter hardiness (minimum winter temperature), 

and minimum frost-free period (growing season requirements) for selected woody perennial fruit and nut crops. Not shown in this table is the fact that flowers and developing 

fruit of all crops are sensitive to damage from mild to moderate frosts (e.g., 0 to -5oC), 

and high temperature stress (e.g., >35oC), specific damaging temperatures varying with 

crop and variety. Values are approximate and for relative comparisons only. Adapted 

from Westwood (1993).

Winter Chill Requirement (hours)1

Crop

Common 

Varieties Other

Minimum

Winter Temp 

(C)

Minimum FrostFree Period 

(days)

Almond 100-500 -10 >180

Apple 1000-1600 400-1800 -46 to -4 <100 (+)

Blueberry 400-1200

(northern 

highbush)

0-200 -35 to -12 <100 (+)

Cherry 900-1200 600-1400 -29 to -1 <100 (+)

Citrus 0 -7 to 4 >280

Grape 

(European) 100-500 -25 to 4 >120

Grape 

(American) 400-2000 (+) -46 to -12 <100 (+)

Peach 400-800 200-1200 -29 to 4 >120

Pear 500-1500 -35 to -1 >100

Pecan 600-1400 -10 >180

Pistachio 600-1500 400-600 (Asian) -10 >180

Plum 800-1200 500-600 (Japanese) -29 to 4 >140

Raspberry 800-1700 100-1800 -46 (+) <100 (+)

Strawberry 300-400 -12 <100 (+)

Walnut 400-1500 -29 >100

1Winter chilling for most fruit and nut crops occurs within a narrow temperature range of 0 to 15oC, with 

maximum chill-hour accumulation at about 7.2oC. Temperatures below or above this range do not contribute 

to the chilling requirement, and temperatures above 15oC may even negate previously accumulated chill.

the Illinois location, simulated yield decreased 5 

to 8 percent per 2oC temperature increase. Using 

this relationship, a temperature rise of 1.2oC 

over the next 30 years in the Midwest may decrease yield by about 4 percent (Table 2.6) under 

irrigated or water-sufficient management.

Lobell and Asner (2003) evaluated maize 

and soybean production relative to climatic 

variation in the United States, reporting a 17 

percent reduction in yield for every 1oC rise 

in temperature, but this response is unlikely 

because the confounding effect of rainfall was 

Marketable yield of 

horticultural crops 

is highly sensitive to 

minor environmental 

stresses related 

to temperatures 

outside the optimal 

range, which 

negatively affect 

visual and flavor 

quality.
29

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

not considered. In a recent evaluation of global 

maize production response to both temperature 

and rainfall over the period 1961-2002, Lobell 

and Field (2007) reported an 8.3 percent yield 

reduction per 1oC rise in temperature. Runge 

(1968) documented maize yield responses to the 

interaction of daily maximum temperature and 

rainfall during the period 25 days prior to, and 

15 days after, anthesis of maize. If rainfall was 

low (0-44 mm per 8 days), yield was reduced 

by 1.2 to 3.2 percent per 1oC rise. Alternately, if 

temperature was warm (maximum temperature 

(Tmax) of 35oC), yield was reduced 9 percent 

per 25.4 mm rainfall decline. The Muchow et al. 

(1990) model, also used to project temperature 

effects on crops, may underestimate yield reduction with rising temperature because it had 

no temperature modification on assimilation or 

respiration, and did not provide for any failures 

in grain-set with rising temperature. Given the 

disagreement in literature estimates and lack of 

real manipulative temperature experiments on 

maize, the certainty of the estimate in Table 2.6 

is only possible to likely.

Yield decreases caused by elevated temperatures 

are related to temperature effects on pollination 

and kernel set. Temperatures above 35oC are 

lethal to pollen viability (Herrero and Johnson 

1980; Schoper et al. 1987; Dupuis and Dumas 

1990). In addition, the critical duration of pollen 

viability (prior to silk reception) is a function of 

pollen moisture content, which is strongly dependent on vapor pressure deficit (Fonseca and 

Westgate 2005). There is limited data on sensitivity of kernel set in maize to elevated temperature, although in-vitro evidence suggests that 

the thermal environment during endosperm cell 

division phase (eight to 10 days post-anthesis) 

is critical (Jones et al. 1984). A temperature of 

35oC, compared to 30oC during the endosperm 

division phase, dramatically reduced subsequent

kernel growth rate (potential) and final kernel 

size, even if ambient temperature returns to 30oC 

(Jones et al. 1984). Temperatures above 30oC increasingly impaired cell division and amyloplast 

replication in maize kernels, and thus reduced 

grain sink strength and yield (Commuri and 

Jones 2001). Leaf photosynthesis rate of maize 

has a high temperature optimum of 33oC to 

38oC. There is a minimal sensitivity of light use 

(quantum) efficiency to these elevated temperatures (Oberhuber and Edwards 1993; Edwards 

and Baker 1993); however, photosynthesis rate 

is reduced above 38oC (Crafts-Brandner and 

Salvucci 2002).

2.2.1.2.2.2 Soybean

Reproductive development (time to anthesis) 

in soybean has cardinal temperatures that are 

somewhat lower than those of maize. A base 

temperature of 6oC and optimum temperature 

of 26oC are commonly used (Boote et al. 1998), 

having been derived, in part, from values of 

2.5oC and 25.3oC developed from field data by 

Grimm et al. (1993). The post-anthesis phase for 

soybean has a surprisingly low optimum temperature of about 23oC, and life cycle is slower 

and longer if mean daily temperature is above 

23oC (Pan 1996; Grimm et al. 1994). This 23oC 

optimum cardinal temperature for post-anthesis 

period closely matches the optimum temperature 

for single seed growth rate (23.5oC), as reported 

by Egli and Wardlaw (1980), and the 23oC 

optimum temperature for seed size (Egli and 

Wardlaw 1980; Baker et al. 1989; Pan 1996; 

Thomas 2001; Boote et al. 2005). As mean 

temperature increases above 23oC, seed growth 

rate, seed size, and intensity of partitioning to 

grain (seed harvest index) in soybean decrease 

until reaching zero at 39oC mean (Pan 1996; 

Thomas 2001).

The CROPGRO-soybean model, parameterized 

with the Egli and Wardlaw (1980) temperature 

effect on seed growth sink strength, and the 

Grimm et al. (1993, 1994) temperature effect 

on reproductive development, predicts highest 

grain yield of soybean at 23-24oC, with progressive decline in yield, seed size, and harvest index 

as temperature further increases, reaching zero 

yield at 39oC (Boote et al. 1997, 1998). Soybean 

yield produced per day of season, when plotted 

against the mean air temperature at 829 sites 

of the soybean regional trials over the United 

States, showed highest productivity at 22oC 

(Piper et al. 1998).

Pollen viability of soybean is reduced if temperatures exceed 30oC (optimum temperature), but 

has a long decline slope to failure at 47oC (Salem 

et al. 2007). Averaged over many cultivars, the 

cardinal temperatures (base temperature (Tb), 

optimum temperature (Topt), and Tmax) were 

13.2oC, 30.2oC, and 47.2oC, respectively, for 

pollen germination, and 12.1oC, 36.1oC, and 
The U.S. Climate Change Science Program

30

Chapter 2

47.0oC, respectively, for pollen tube growth. 

Minor cultivar differences in cardinal temperatures and tolerance of elevated temperature were 

present, but differences were not very large or 

meaningful. Salem et al. (2007) evaluated soybean grown at 38/30oC versus 30/22oC (day/

night) temperatures. The elevated temperature 

reduced pollen production by 34 percent, pollen germination by 56 percent, and pollen tube 

elongation by 33 percent. The progressive 

reduction in seed size (single seed growth rate) 

above 23oC, along with reduction in fertility 

(i.e., percent seed set) above 30oC, results in 

reduction in seed harvest index at temperatures 

above 23-27oC (Baker et al.1989; Boote et al. 

2005). Zero seed harvest index occurs at 39oC 

(Pan 1996; Thomas 2001; Boote et al. 2005).

The implication of a temperature change on 

soybean yield is thus strongly dependent on the 

prevailing mean temperature during the postanthesis phase of soybean in different regions. 

For the upper Midwest, where mean soybean 

growing season temperatures are about 22.5oC, 

soybean yield may actually increase 2.5 percent with a 1.2oC rise (Table 2.6). By contrast, 

soybean production in the southern United 

States, where mean growing season temperatures are 25oC to 27oC, soybean yield would be 

progressively reduced – 3.5 percent for 1.2oC 

increase from the current 26.7oC mean (Table 

2.7) (Boote et al. 1996, 1997). Lobell and Field 

(2007) reported a 1.3 percent decline in soybean 

yield per 1oC increase in temperature, taken 

from global production against global average 

Grain Yield Evapotranspiration

Crop

Temperature

(1.2oC) 1

CO2

(380 to 440 

ppm) 2

Temp/CO2

Combined

Irrigated

Temp

(1.2oC) 3

CO2

(380 to 440 

ppm) 4

% change

Corn – Midwest

(22.5oC) -4.0 +1.0 -3.0 +1.8

Corn – South

(26.7oC)

-4.0 +1.0 -3.0 +1.8

Soybean – Midwest

(22.5oC) +2.5 +7.4 +9.9 +1.8 -2.1

Soybean – South

(26.7oC) -3.5 +7.4 +3.9 +1.8 -2.1

Wheat – Plains

(19.5oC) -6.7 +6.8 +0.1 +1.8 -1.4

Rice – South

(26.7oC) -12.0 +6.4 -5.6 +1.8 -1.7

Sorghum

(full range) -9.4 +1.0 -8.4 +1.8 -3.9

Cotton – South

(26.7oC)

-5.7 +9.2 +3.5 +1.8 -1.4

Peanut – South

(26.7oC)

-5.4 +6.7 +1.3 +1.8

Bean – relative to 23oC -8.6 +6.1 -2.5 +1.8

Table 2.6 Percent grain yield and evapotranspiration responses to increased temperature (1.2oC), increased CO2

(380 to 440 ppm), and the net effects of temperature plus increased CO2 assuming additivity. Current mean air 

temperature during reproductive growth is shown in parentheses for each crop/region to give starting references, although yield of all the cereal crops declines with a temperature slope that originates below current mean 

air temperatures during grain filling.

1Response to temperature summarized from literature cited in the text. 2Response to CO2 with Michaelis-Menten rectangular hyperbola 

interpolation of literature values shown in Table 2.7. 3From Table 2.8 the sensitivity of a standard alfalfa crop to warming at constant 

relative humidity on clear summer day would be 1.489% per °C, so assuming the crop ET will respond similarly with warming by 1.2°C, 

the expected change in ET would be 1.8%. 4From Table 2.7 assuming linear ET response to 60 ppm increase in CO2 interpolated from the 

range, 350 to 700 ppm or 370 to 570 ppm for sorghum.
31

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

temperature during July-August, weighted by 

production area. These two estimates are in 

agreement and likely, considering that Lobell 

and Field (2007) averaged over cool and warm 

production areas.

2.2.1.2.2.3 Wheat

Grain-filling period of wheat and other small 

grains shortens dramatically with rising temperature (Sofield et al. 1974, 1977; Chowdhury and 

Wardlaw 1978; Goudrian and Unsworth 1990). 

Assuming no difference in daily photosynthesis, 

which can be inferred from the sink removal 

studies of Sofield et al. (1974, 1977), yield will 

decrease in direct proportion to the shortening 

of grain filling period as temperature increases. 

This temperature effect is already a major reason 

for the much lower wheat yield potential in the 

Midwest than in northern Europe, even with the 

water limitation removed.

The optimum temperature for photosynthesis in 

wheat is 20-30oC (Kobza and Edwards 1987). 

This is 10oC higher than the optimum (15oC) 

for grain yield and single grain growth rate 

(Chowdhury and Wardlaw 1978). Any increase 

in temperature beyond the 25-35oC range that 

is common during grain filling of wheat will 

reduce the grain filling period and, ultimately, 

yields. Applying the nonlinear slope of reduction in grain filling period from Chowdury and 

Wardlaw (1978), relative to the mean temperatures during grain fill in the wheat growing 

regions of the Great Plains, reduction in yield is 

about 7 percent per 1oC increase in air temperature between 18 and 21oC, and about 4 percent 

per 1oC increase in air temperature above 21oC, 

not considering any reduction in photosynthesis 

or grain-set. Similarly, Lawlor and Mitchell 

(2000) stated that a 1oC rise would shorten the 

reproductive phase by 6 percent, grain filling 

duration by 5 percent, and would reduce grain 

yield and harvest index proportionately. Bender 

et al. (1999) analyzed spring wheat grown at 

nine sites in Europe and found a 6 percent decrease in yield per 1oC temperature rise. Lobell 

and Field (2007) reported a 5.4 percent decrease 

in global mean wheat yield per 1oC increase in 

temperature. Grain size will also be reduced 

slightly. These four references are very much in 

agreement, so the projected temperature effect 

on yield in Table 2.6 is considered very likely.

Effects of rising temperature on photosynthesis 

should be viewed as an additional reduction 

factor on wheat yield, primarily influenced 

via water deficit effects (Paulsen 1994). Temperatures of 36/31oC (maximum/minimum) 

for two to three days prior to anthesis causes 

small unfertilized kernels with symptoms of 

parthenocarpy – that is, small shrunken kernels 

with notching and chalking of kernels (Tashiro 

and Wardlaw 1990). Increased temperature also 

reduces starch synthesis in wheat endosperm 

(Caley et al. 1990).

2.2.1.2.2.4 Rice

The response of rice to temperature has been well 

studied (Baker and Allen 1993a, 1993b; Baker 

et al. 1995; Horie et al. 2000). Leaf-appearance 

rate of rice increases with temperature from a 

base of 8oC, until reaching 36-40oC, the thermal 

threshold of survival (Alocilja and Ritchie 1991; 

Baker et al. 1995), with biomass increasing up 

to 33oC (Matsushima et al. 1964); however, the 

optimum temperature for grain formation and 

yield of rice is lower (25oC) (Baker et al. 1995). 

Baker et al. (1995) summarized many of their 

experiments from sunlit controlled-environment 

chambers and concluded that the optimum mean 

temperature for grain formation and grain yield 

of rice is 25oC. They found that grain yield is 

reduced about 10 percent per 1oC temperature 

increase above 25oC, until reaching zero yield 

at 35-36oC mean temperature, using a 7oC day/

night temperature differential (Baker and Allen 

1993a; Peng et al. 2004).

Grain number, percent filled grains, and grain 

harvest index followed nearly the same optimum 

and failure curve points. Declining yield above 

25oC is initially attributed to shorter grain filling duration (Chowdhury and Wardlaw 1978; 

Snyder 2000), and then to progressive failure 

to produce filled grains – the latter is caused by 

reduced pollen viability and reduced production 

of pollen (Kim et al. 1996; Matsui et al. 1997; 

Prasad et al. 2006b). Pollen viability and production begins to decline as daytime maximum 

temperature exceeds 33oC, and reaches zero 

at Tmax of 40oC (Kim et al. 1996). Because 

flowering occurs at mid-day in rice, Tmax is 

the best indicator of heat stress on spikelet 

sterility. Grain size of rice tends to hold mostly 

constant, declining only slowly across increasing temperature, until the pollination failure 

point (Baker and Allen 1993a). Rice ecotypes, 
The U.S. Climate Change Science Program

32

Chapter 2

japonica and indica, mostly do not differ in 

the upper temperature threshold (Snyder 2000; 

Prasad et al. 2006b), although the indica types 

are more sensitive to cool temperature (night 

temperature less than 19oC) (Snyder 2000).

Screening of rice genotypes and ecotypes for 

heat tolerance (33.1/27.3oC versus 28.3/21.3oC 

mean day/night temperatures) by Prasad et al. 

(2006b) demonstrated significant genotypic 

variation in heat tolerance for percent filled 

grains, pollen production, pollen shed, and pollen viability. The most tolerant cultivar had the 

smallest decreases in spikelet fertility, grain 

yield and harvest index at elevated temperature. 

This increment of temperature caused, for the 

range of 14 cultivars, 9-86 percent reduction 

in spikelet fertility, 0-93 percent reduction in 

grain weight per panicle, and 16-86 percent reduction in harvest index. Mean air temperature 

during the rice grain filling phase in summer in 

the southern United States and many tropical 

regions is about 26-27oC. These are above the 

25oC optimum, which illustrates that elevated 

temperature above current will likely reduce 

U.S. and tropical region rice yield by about 10 

percent per 1oC rise, or about 12 percent for a 

1.2oC rise.

2.2.1.2.2.5 Sorghum

In general, the base and optimum temperatures 

for vegetative development are 8oC and 34oC, 

respectively (Alagarswamy and Ritchie 1991), 

while the optimum temperature for reproductive development is 31oC (Prasad et al. 2006a). 

Optimum temperature for sorghum vegetative 

growth is between 26oC and 34oC, and for 

reproductive growth 25oC and 28oC (Maiti 

1996). Maximum dry matter production and 

grain yield occur at 27/22oC (Downs 1972). 

Grain filling duration is reduced as temperature 

increases over a wide range (Chowdury and 

Wardlaw 1978; Prasad et al. 2006a). Nevertheless, as temperature increased above 36/26oC to 

40/30oC (diurnal maximum/minimum), panicle 

emergence was delayed by 20 days, and no 

panicles were formed at 44/34oC (Prasad et 

al. 2006a). Prasad et al. (2006a) found that 

grain yield, harvest index, pollen viability, and 

percent seed-set were highest at 32/22oC, and 

progressively reduced as temperature increased, 

falling to zero at 40/30oC. Vegetative biomass 

was highest at 40/30oC and photosynthesis was 

high up to 44/34oC. Seed size was reduced 

above 36/26oC. Rice and sorghum have exactly 

the same sensitivity of grain yield, seed harvest 

index, pollen viability, and success in grain 

formation (Prasad et al. 2006a). In addition, 

maize, a related warm-season cereal, may have 

the same temperature sensitivity. Basing the 

yield response of sorghum only on shortening of filling period (Chowdury and Wardlaw 

1978), yield would decline 7.8 percent per 1oC 

temperature rise from 18.5-27.5oC (a 9.4 percent 

yield reduction for a 1.2oC increase). However, 

if site temperature is cooler than optimum for 

biomass/photosynthesis (27/22oC), then yield 

loss from shorter filling period would be offset 

by photosynthesis increase. The response from 

Chowdury and Wardlaw (1978) is supported by 

the 8.4 percent decrease in global mean sorghum 

yield per 1oC increase in temperature reported 

for sorghum by Lobell and Field (2007); therefore, the reported responses are likely.

2.2.1.2.2.6 Cotton

Cotton is an important crop in the southern 

United States, and is considered to have adapted 

to high-temperature environments. Despite this 

perception, reproductive processes of cotton 

have been shown to be adversely affected by 

elevated temperature (Reddy et al. 2000, 2005). 

Being a tropical crop, cotton’s rate of leaf appearance has a relatively high base temperature 

of 14oC, and a relatively high optimum temperature of 37oC, thus leaf and vegetative growth 

appear to tolerate elevated temperature (Reddy 

et al. 1999, 2005). On the other hand, reproductive progression (emergence to first flower) has 

a temperature optimum of 28-30oC, along with 

a high base temperature of about 14oC (Reddy 

et al. 1997, 1999). Maximum growth rate per 

boll occurred at 25-26oC, declining at higher 

temperatures, while boll harvest index was highest at 28oC, declining at higher temperatures, 

reaching zero boll harvest index at 33-34oC 

(Reddy et al. 2005).

Boll size was largest at temperatures less than 

20oC, declining progressively as temperature 

increased. Initially there was compensation 

with increased boll number set as temperature 

increased up to 35/27oC day/night temperature, 

but above 30oC mean temperature, percent boll 

set, boll number, boll filling period, rate of boll 

growth, boll size, and yield all decreased (Reddy 
33

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

et al. 2005). Instantaneous air temperature above 

32oC reduces pollen viability, and temperature 

above 29oC reduces pollen tube elongation 

(Kakani et al. 2005), thus acting to progressively 

reduce successful boll formation to the point of 

zero boll yield at 40/32oC day/night (35oC mean) 

temperature (Reddy et al. 1992a, 1992b). Pettigrew (2008) evaluated two cotton genotypes 

under a temperature regime 1oC warmer than 

current temperatures and found lint yield was 10 

percent lower in the warm regime. The reduced 

yields were caused by a 6 percent reduction in 

boll mass and 7 percent less seed in the bolls.

These failure point temperatures show that cotton is more sensitive to elevated temperature 

than soybean and peanut, but similar in sensitivity to rice and sorghum. There is no well-defined 

cotton-yield response to temperature in the 

literature, but if cotton yield is projected with 

a quadratic equation from its optimum at 25oC

to its failure temperature of 35oC, then a 1.2oC 

increase from 26.7oC to 27.9oC would give a 

possible yield decrease of 5.7 percent.

2.2.1.2.2.7 Peanut

Peanut is another important crop in the southern 

United States. The base temperature for peanutleaf-appearance rate and onset of anthesis are 

10oC and 11oC, respectively (Ong 1986). The 

optimum temperature for leaf appearance rate 

is above 30oC, while the optimum for rate of 

vegetative development to anthesis is 29-33oC 

(Bolhuis and deGroot 1959). Leaf photosynthesis has a fairly high optimum temperature 

of about 36oC. Cox (1979) observed that 24oC 

was the optimum temperature for single pod 

growth rate and pod size, with slower growth 

rate and smaller pod size occurring at higher 

temperatures. Williams et al. (1975) evaluated 

temperature effects on peanut by varying elevation, and found that peanut yield was highest 

at a mean temperature of 20oC (27/15oC max/

min), a temperature that contributed to a long 

life cycle and long reproductive period. Prasad et 

al. (2003) conducted studies in sunlit controlled 

environment chambers, and reported that the 

optimum mean temperature for pod yield, seed 

yield, pod harvest index, and seed size occurred 

at a temperature lower than 26oC; quadratic

projections to peak and minimum suggest that 

the optimum temperature was 23-24oC, with a 

failure point temperature of 40oC for zero yield 

and zero harvest index.

Pollen viability and percent seed-set in that 

study began to fail at about 31oC, reaching zero 

at about 39-40oC (44/34oC treatment) (Prasad et 

al. 2003). For each individual flower, the period 

sensitive to elevated temperature starts six days 

prior to opening of a given flower and ends one 

day after, with greatest sensitivity on the day 

of flower opening (Prasad et al. 1999; Prasad 

et al. 2001). Percent fruit-set is first reduced at 

bud temperature of 33oC, declining linearly to 

zero fruit-set at 43oC bud temperature (Prasad 

et al. 2001).

Genotypic differences in heat-tolerance of 

peanut (pollen viability) have been reported 

(Craufurd et al. 2003). As air temperature in 

the southern United States already averages 

26.7oC during the peanut growing season, any 

temperature increase will reduce seed yields 

(4.5 percent per 1oC, or 5.4 percent for a 1.2oC 

rise in range of 26-28oC) using the relationship 

of Prasad et al. (2003). At higher temperatures, 

27.5-31oC, peanut yield declines more rapidly 

(6.9 percent per 1oC) based on unpublished data 

of Boote. A recent trend in peanut production 

has been the move of production from south 

Texas to west Texas, a cooler location with 

higher yield potential.

2.2.1.2.2.8 Dry Bean and Cowpea

Dry bean is typical of many vegetable crops 

and is grown in relatively cool regions of the 

United States. Prasad et al. (2002) found that 

red kidney bean, a large-seeded ecotype of dry 

bean, is quite sensitive to elevated temperature,

having highest seed yield at 28/18oC (23oC 

mean) or lower (lower temperatures were not 

tested), with linear decline to zero yield as 

temperature increased to 37/27oC (32oC mean). 

In that study, pollen production per flower was 

reduced above 31/21oC, pollen viability was 

dramatically reduced above 34/24oC, and seed 

size was decreased above 31/21oC. Laing et al. 

(1984) found highest bean yield at 24oC, with a 

steep decline at higher temperatures. Gross and 

Kigel (1994) reported reduced fruit-set when 

flower buds were exposed to 32/27oC during the 

six to 12 days prior to anthesis and at anthesis, 

caused by non-viable pollen, failure of anther 

dehiscence, and reduced pollen tube growth. 

Heat-induced decreases in seed and fruit set in 

cowpea have been associated with formation of 

non-viable pollen (Hall 1992). Hall (1992) also 
The U.S. Climate Change Science Program

34

Chapter 2

reported genetic differences in heat tolerance 

of cowpea lines. Screening for temperaturetolerance within bean cultivars has not been done 

explicitly, but the Mesoamerican lines are more 

tolerant of warm tropical locations than are the 

Andean lines, which include the red kidney bean 

type (Sexton et al. 1994). Taking the initial slope 

of decline from data of Prasad et al. (2002), bean 

yield will likely decrease 7.2 percent per 1oC 

temperature rise, or 8.6 percent for 1.2oC above 

23oC (Table 2.6).

2.2.1.2.2.9 Tomato

Tomato is an important vegetable crop known 

to suffer heat stress in mid-summer in southern U.S. locations. The base and optimum 

temperature is 7o and 22oC for rate of leaf appearance, rate of truss appearance, and rate of 

progress to anthesis (Adams et al. 2001). Leaf 

photosynthesis of tomato has a base at 6-8oC 

(Duchowski and Brazaityte 2001), while its 

optimum is about 30oC (Bunce 2000). The rate 

of fruit development and maturation has a base 

temperature of 5.7oC and optimum of 26oC, and 

rate of individual fruit growth has its optimum at 

22-25oC (Adams et al. 2001). Largest fruit size 

occurs at 17-18oC, and declines at progressively 

higher temperature (Adams et al. 2001; De 

Koning 1996). Rate of fruit addition (fruit-set, 

from pollination) has an optimum at or lower 

than 26oC and progressively fails as temperature reaches 32oC (Adams et al. 2001). Peat et 

al. (1998) observed that the number of fruits 

per plant (or percent fruit-set) at 32/26oC day/

night (29oC mean) was only 10 percent of that 

at 28/22oC (25oC mean). The projected failure 

temperature was about 30oC. Sato et al. (2000) 

found that only one of five cultivars of tomato 

successfully set any fruit at chronic exposures 

to 32/26oC, although fruit-set recovered if the 

stressful temperature was relieved.

Sato et al. (2000) also noted that pollen release 

and pollen germination were critical factors affected by heat stress. The anticipated temperature effect on tomato production will depend on 

the region of production and time of sowing (in 

the southern United States); however, at optima 

of 22oC for leaf/truss development, 22-26oC 

for fruit addition, 22-25oC for fruit growth, and 

fruit-set failures above 26oC, temperatures exceeding 25oC will likely reduce tomato production. Depending on region of production, tomato 

yield is projected to decrease 12.6 percent for 

1.2oC rise above 25oC, assuming a non-linear 

yield response and assuming optimum temperature and failure temperatures for yield of 23.5oC 

and 30oC, respectively.

2.2.1.3 Crop Responses to CO2

2.2.1.3.1 Overview of Individual Crop 

Responses to CO2

Reviews of the early enclosure CO2 studies indicate a 33 percent increase in average yield for 

many C3 crops under a doubling CO2 scenario 

(Kimball 1983) at a time when doubling meant 

increase from 330 to 660 parts per million (ppm) 

CO2. The general phenomenon was expressed as 

increased numbers of tillers-branches, paniclespods, and numbers of seeds, with minimal effect 

on seed size. The C4 species response to doubling of CO2 was reported by Kimball (1983) to 

be 10 percent. High temperature stress during 

reproductive development can negate CO2’s 

beneficial effects on yield, even though total 

biomass accumulation maintains a CO2 benefit 

(e.g., for Phaseolus bean, Jifon and Wolfe 2000). 

Unrestricted root growth, optimum fertility, 

and excellent control of weeds, insects, and 

disease are also required to maximize CO2 

benefits (Wolfe 1994). Most C3 weeds benefit 

more than C3 crop species from elevated CO2 

(Ziska 2003).

In recent years, new field “free-air CO2 enrichment” (FACE) technology has allowed evaluation of a few select crops to better understand 

their response under field conditions without 

enclosure-confounding effects. Generally, the 

FACE results corroborate previous enclosure 

studies (Ziska and Bunce 2007), although 

some FACE results suggest yield responses 

are less than previously reported (Long et al. 

2006). Although the continuously increasing 

“ambient” reference concentration is a cause for 

lesser response, the smaller increment of CO2

enrichment requires even better replication and

sampling in FACE to evaluate the response. 

Enclosures are not the only concern; singlespaced plants, or unbordered plants may respond 

too much, and potted plants that are root bound 

may not respond well. Additional research, data 

analysis, and evaluation of a broader range of 

crops using FACE techniques will be required

to sort discrepancies where they exist.
35

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Effects of doubling of CO2 on leaf photosynthesis, total biomass, grain or fruit yield, conductance, and canopy temperature or evapotranspiration (ET) of important non-water-stressed 

crops are shown in Table 2.7. (In addition to 

the specific references cited below, Kimball 

et al. (2002) provide CO2 responses of several 

more crop and soil parameters for a variety of 

species.)

Maize, being a C4 species, is less responsive to 

increased atmospheric CO2. Single leaf photosynthesis of maize shows no effect of CO2 on 

quantum efficiency, but there is a minor increase

in leaf rate at light saturation (3 percent for 376 

to 542 ppm; Leakey et al. 2006). There is a paucity of data for maize grown to maturity under 

elevated CO2 conditions. Until 2006, there was 

only one data set for maize grown to maturity 

under CO2 treatments: King and Greer (1986) 

observed 6.2 percent and 2.6 percent responses 

to increasing CO2 from 355 to 625 and 875 ppm, 

respectively, in a 111-day study. The mean of 

the two levels gives about 4.4 percent increase 

to doubling or more of CO2.

Leakey et al. (2006) conducted a full-season 

FACE study of maize grown to maturity, and 

References: 1Leakey et al. (2006)*; 2King and Greer (1986); 3Ziska and Bunce (1997); 4Maroco et al. (1999); 5Leakey et al. (2006)*; 6Ainsworth et al. (2002); 7Allen and Boote (2000); 8Allen et al. (2003); 9Jones et al. (1985); 10Bernacchi et al. (2007)*; 11Long (1991); 12Lawlor and Mitchell (2000); 13Amthor (2001); 14Wall et al. (2006)*; 15Andre and duCloux (1993); 16Kimball et al. (1999)*; 17Horie et al. 

(2000); 18Baker and Allen (1993a); 19Baker et al. (1997a); 20Prasad et al. (2006a); 21Wall et al. (2001); 22Ottman et al. (2001)*; 23Triggs 

et al. (2004)*; 24K.R. Reddy et al. (1995,1997); 25Reddy et al. (2000); 26Prasad et al. (2003); 27Yoshimoto et al. (2005).

Table 2.7 Percent response of leaf photosynthesis, total biomass, grain yield, stomatal conductance, and canopy 

temperature or evapotranspiration, to a doubling in CO2 concentration (usually 350 to 700 ppm, but sometimes 

330 to 660 ppm). *Responses to increase from ambient to 550 or 570 ppm (FACE) are separately noted.

Crop

Leaf 

Photosynthesis Total Biomass Grain Yield

Stomatal 

Conductance

Canopy

T, ET

% change

Corn 31* 41, 2, 3,4 41, 2 -345

Soybean 396 376 386, 347 -406 -98,-129,10*

Wheat 35l1 15-2712 3113 -33 to -4314* -815,16*

Rice 3617 3017 3017,18 -1019,27

Sorghum 920, 21* 322* 820, 022* -3721* -1323*

Cotton 3324 3624 4424 -3624 -825

Peanut 2726 3626 3026

Bean 5026 3026 2726

reported no significant response of maize to 

a 50 percent increase in CO2 (376 to 542 ppm 

(target: 370 to 550 ppm)). However, they used 

a very small biomass sample size in their FACE 

study (four random plant samples per replicate). 

This small sample size coupled with the small 

increment of CO2 increase raises concern about 

whether these experimental measurements were 

sufficient to detect a statistically significant 

response. Ziska and Bunce (1997) reported 

a 2.9 percent increase in biomass when CO2

was increased from 371 to 674 ppm during a 

33-day, glasshouse study. Maroco et al. (1999) 

reported a 19.4 percent biomass increase when 

CO2 was increased from 350 to 1,100 ppm during a 30-day growth period at very high light 

(supplemented above outdoor ambient) for a 

short duration on young plants. Thus, 4 percent 

increases in both biomass and grain yield of 

maize are possible, with increase in CO2 from 

350 to 700 ppm. This is less than the simulated 

10 percent increase for C4 species to incremental 

CO2 increases (330 to 660 ppm) as parameterized in the CERES-Maize (Crop Environment 

Resource Synthesis) or EPIC (Environmental 

Policy Integrated Climate) models based on 

sparse data (Tubiello et al. 2007).
The U.S. Climate Change Science Program

36

Chapter 2

In summary, the evidence for maize response 

to CO2 is sparse and questionable, resulting in

only a possible degree of certainty. The expected 

increment of CO2 increase over the next 30 years 

is anticipated to have a negligible effect (i.e., 1 

percent) on maize production, unless there is 

a water-savings effect in drought years (Table 

2.6). Sorghum, another important C4 crop, gave 

9, 34, and 8 percent increases in leaf photosynthesis, biomass, and grain yield, respectively, 

with doubling of CO2 when grown in 1-by-2-

meter, sunlit controlled-environment chambers 

(Prasad et al. 2005a). Over an entire season, with 

a CO2 increase from 368 to 561 ppm, sorghum 

grown as part of a FACE study in Arizona gave 

3 and 15 percent increases in biomass, and -4 

percent and +20 percent change in grain yield, 

under irrigated versus water-limited conditions, 

respectively (Ottman et al. 2001).

Soybean is a C3 legume that is quite responsive

to CO2. Based on the metadata summarized 

by Ainsworth et al. (2002), soybean response 

to a doubling of CO2 is about 39 percent for 

light-saturated leaf photosynthesis, 37 percent 

for biomass accumulation, and 38 percent for 

grain yield. (These values are only from soybean 

raised in large, ≥1-square-meter crop stands

grown in soil because yield response to CO2 potted plants was shown to be affected by pot size). 

Allen and Boote (2000) reported a response of 

34 percent in sunlit controlled-environment 

chambers to increases in CO2 from 330 to 660 

ppm. Ainsworth et al. (2002) found that under 

similar conditions, leaf conductance was reduced 

by 40 percent, which is consistent with other C3

and C4 species (Morison 1987), and seed harvest 

index was reduced by 9 percent. The C3 photosynthetic response to CO2 enrichment is well 

documented, and generally 

easy to predict using either 

the Farquhar and von Cammerer (1982) equations, or

simplifications based on 

those equations. The CROPGRO-soybean model (Boote 

et al. 1998), parameterized 

with Farquhar kinetics equations (Boote and Pickering 

1994; Alagarswamy et al. 

2006), was used to simulate 

soybean yield to CO2 rises 

from 350 to 700 ppm. The 

CROPGRO-soybean model 

predicted 29-41 percent increase in biomass, and 29 to 

34 percent increase in grain 

yield (Boote et al. 1997), 

values that are comparable 

to metadata summarized by 

Ainsworth et al. (2002) and 

Allen and Boote (2000). 

Crop models can be used to 

project yield responses to 

CO2 increase from past to 

present and future levels. 

Simulations by Boote et al. 

(2003) suggested that soybean yield in Iowa would 

have increased 9.1 percent 

between 1958 and 2000, 

during which time the CO2

increased from 315 to 370 

Figure 2.5 Relative changes in evapotranspiration due to elevated CO2 concentrations in FACE 

experiments at about 550 ppm. [Wheat and cotton data from Table 2 of Kimball et al. (2002); 

rice datum from Yoshimoto et al. (2005); sorghum datum from Triggs et al. (2004); poplar datum 

from Tommasi et al. (2002); sweetgum from Wullschleger and Norby (2001); soybean datum 

from Bernacchi et al. (2007); and potato datum from Magliulo et al. (2003)].
37

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

ppm; thus some of the past yield trend of soybean was associated with global change rather 

than technological innovation.

Using the same type of Michaelis-Menten 

rectangular hyperbola projection for soybean 

as used for all other crops, a CO2 increase from 

380 to 440 ppm is projected to increase yield by 

7.4 percent (Table 2.7) in the dominant soybeangrowing regions in the Midwest. For this region, 

expected temperatures are so close to the optimum for soybean yield, and the temperature 

increment so small (1.2oC) that the net effect of 

climate change on soybean yield is dominated 

by the CO2 increment. To the extent that wateruse efficiency increases with CO2 enrichment 

and conserves soil water, yield response for 

rainfed regions will be enhanced by a net 0.9 

percent increase in ET.

Other C3 field crop species exhibit similar 

responses to increasing CO2. For wheat, a coolseason cereal, doubling of CO2 (350 to 700 ppm) 

increased light-saturated leaf photosynthesis by 

30-40 percent (Long 1991), and grain yield by 

about 31 percent, averaged over many data sets 

(Amthor 2001). For rice, doubling CO2 (330 to 

660 ppm) increased canopy assimilation, biomass, and grain yield by about 36, 30, and 30 

percent, respectively (Horie et al. 2000). Baker 

and Allen (1993a) reported a 31 percent increase 

in grain yield, averaged over five experiments, 

with increase of CO2 from 330 to 660 ppm. Rice 

shows photosynthetic acclimation associated 

with decline in leaf nitrogen (N) concentration, 

and a 6-22 percent reduction in leaf rubisco 

content per unit leaf area (Vu et al. 1998).

For peanut, a warm-season grain legume, doubling CO2 increased light-saturated leaf photosynthesis, total biomass and pod yield of peanut 

by 27, 36, and 30 percent, respectively (Prasad 

et al. 2003). Doubling CO2 (350 to 700 ppm) 

increased light-saturated leaf photosynthesis, 

biomass, and seed yield of dry bean by 50, 30, 

and 27 percent (Prasad et al. 2002).

For cotton, a warm-season non-legume, doubling 

CO2 (350 to 700 ppm) increased light-saturated 

leaf photosynthesis, total biomass, and boll yield 

by 33 percent, 36 percent, and 44 percent (K. 

R. Reddy et al. 1995, 1997), respectively, and 

decreased stomatal conductance by 36 percent 

(V. R. Reddy et al. 1995). Under well-watered 

conditions, leaf and canopy photosynthesis of 

cotton increased about 27 percent with CO2

enrichment, to 550 ppm CO2 in a FACE experiment in Arizona (Hileman et al. 1994). Mauney 

et al. (1994) reported 37 percent and 40 percent 

increases in biomass and boll yield of cotton 

with CO2 enrichment to 550 ppm. Even larger 

increases in yield and biomass of cotton were 

obtained under the same enrichment for cotton 

under water-deficit situations (Kimball and 

Mauney 1993). An important consideration 

relative to cotton responses in Arizona is that 

the large vapor pressure deficit may have given 

more benefit to elevated CO2 via water conservation effects. So, the degree of responsiveness 

in arid region studies may differ from that in 

humid regions. There were no reported effects 

of doubled CO2 on vegetative or reproductive 

growth stage progression in cotton (Reddy et 

al. 2005), soybean (Allen and Boote 2000; Pan 

1996), dry bean (Prasad et al. 2002), and peanut 

(Prasad et al. 2003).

The certainty level of biomass and yield response of these C3 crops to CO2 is likely to very 

likely, given the large number of experiments 

and the general agreement in response across 

the different C3 crops.

2.2.1.3.2 Effects of CO2 Increase in 

Combination with Temperature 

Increase

There could be beneficial interaction of 

CO2 enrichment and temperature on dry 

matter production (greater response to CO2

as temperature rises) for the vegetative phase 

of non-competitive plants, as highlighted by 

Idso et al. (1987). This effect may be beneficial 

to production of radish (Raphanus sativus), 

lettuce (Lactuca sativa), or spinach (Spinacea 

olervicea), mainly because any factor that 

speeds leaf area growth (whether CO2 or 

temperature) speeds the exponential phase of 

early growth. However, this “beta” factor effect 

does not appear to apply to closed canopies or 

to reproductive grain yield processes.

There are no reported beneficial interactions in 

grain yield caused by the combined effects of 

CO2 and temperature increase for rice (Baker 

and Allen 1993a, 1993b; Baker et al. 1995; Snyder 2000), wheat (Mitchell et al. 1993), soybean 

In recent years, new 

field “free-air CO2 

enrichment” (FACE) 

technology has 

allowed evaluation of 

a few select crops to 

better understand 

their response under 

field conditions 

without enclosureconfounding effects.
The U.S. Climate Change Science Program

38

Chapter 2

(Baker et al. 1989; Pan 1994), dry bean (Prasad 

et al. 2002), peanut (Prasad et al. 2003), or sorghum (Prasad et al. 2005a). In other words, the 

separate main effects of CO2 and temperature 

were present, but yield response to CO2 was not 

enhanced as temperature increased. By contrast, 

there are three reported negative effects caused 

by elevated CO2 and temperature in terms of 

fertility. Elevated CO2 causes greater sensitivity of fertility to temperature in rice (Kim et al. 

1996; Matsui et al. 1997), sorghum (Prasad et 

al. 2006a), and dry bean (Prasad et al. 2002). 

For rice, the relative enhancement in grain yield 

with doubled CO2 decreases, and actually goes 

negative as Tmax increases in the range 32-40oC 

(Kim et al. 1996). Likewise, the relative CO2

enhancement of grain yield of soybean (Baker 

et al. 1989) lessened as temperature increased 

from optimum to super-optimum. In the case 

of rice, sorghum, and dry bean, failure point 

temperature (i.e., the point at which reproduction fails) is about 1-2oC lower at elevated 

CO2 than at ambient CO2. This likely occurs 

because elevated CO2 causes warming of the 

foliage (doubled CO2 canopies of dry bean were 

1.5oC warmer) (Prasad et al. 2002); doubled 

CO2 canopies of soybean were 1-2oC warmer 

(Allen et al. 2003); doubled CO2 canopies of 

sorghum averaged 2oC warmer during daytime 

period (Prasad et al. 2006a). The higher canopy 

temperature of rice, sorghum, and dry bean adversely affected fertility and grain-set. Increases 

in canopy temperature for wheat, rice, sorghum, 

cotton, poplar, potato, and soybean have been 

reported in FACE experiments (Kimball and 

Bernacchi 2006).

In cotton, there was progressively greater photosynthesis and vegetative growth response to 

CO2 as temperature increased up to 34oC (Reddy 

1995), but this response did not carry over to 

reproductive growth (Reddy et al. 1995). The 

reproductive enhancement from doubled CO2

was largest (45 percent) at the 27oC optimum 

temperature for boll yield, and there was no 

beneficial interaction of increased CO2 on reproductive growth at elevated temperature, reaching 

zero boll yield at 35oC (Reddy et al. 1995).

Mitchell et al. (1993) conducted field studies of 

wheat grown at ambient and +4oC temperature 

differential, and at elevated versus ambient 

CO2 in England. While interactions of CO2 and 

temperature did not affect yield, higher temperatures reduced grain yield at both CO2 levels such 

that yields were significantly greater at ambient 

CO2 and ambient temperature compared to 

elevated CO2 and high temperature. Batts et al. 

(1997) similarly reported no beneficial interactions of CO2 and temperature on wheat yield.

In studies with bean (Jifon and Wolfe 2005) 

and potato (Peet and Wolfe 2000), there were 

no significant beneficial effects of CO2 on yield 

in high temperature treatments that negatively 

affected reproductive development, although 

the beneficial effects on vegetative biomass 

were maintained. These results suggest that in 

those regions and for those crops where climate 

change impairs crop reproductive development 

because of an increase in the frequency of high

temperature stress events, the potential beneficial effects of elevated CO2 on yield may not 

be fully realized.

For peanut, there was no interaction of elevated 

temperature with CO2 increase, as the extent of 

temperature-induced decrease in pollination, 

seed-set, pod yield, seed yield, and seed harvest 

index was the same at ambient and elevated CO2

levels (Prasad et al. 2003). For dry bean, Prasad 

et al. (2002) found no beneficial interaction of 

elevated temperature with CO2 increase, as the 

temperature-induced decrease in pollination, 

seed-set, pod yield, seed yield, and seed harvest 

index were the same or even greater at elevated 

than at ambient CO2 levels. The temperaturesensitivity of fertility (grain-set) and yield for 

sorghum was significantly greater at elevated 

CO2 than at ambient CO2 (Prasad et al. 2006a), 

thus showing a negative interaction with temperature associated with fertility and grain-set, 

but not photosynthesis.

2.2.1.3.3 Interactions of Elevated CO2 

with Nitrogen Fertility

For non-legumes like rice, there is clear evidence of an interaction of CO2 enrichment with 

nitrogen (N) fertility regime. For japonica rice, 

Nakagawa et al. (1994) reported 17, 26, and 30 

percent responses of biomass to CO2 enrichment, at N applications of 40, 120, and 200 kg N 

ha-1, respectively. For indica rice, 0, 29, and 39 

percent responses of biomass to CO2 enrichment 

were reported at N applications of 0, 90, and 

200 kg N per hectare, respectively (Ziska et al. 
39

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Table 2.8 Sensitivity of evapotranspiration (ET; percent change in ET per °C change in 

temperature or percent change in ET per percent change in variable other than temperature) to changes in weather and plant variables as calculated by Kimball (2007) from the 

ASCE standardized hourly reference equation for alfalfa (Allen et al. 2005). The weather 

data were from the AZMET network (Brown 1987) for Maricopa, AZ, on a clear summer day (21 June 2000), and for the whole 2000 year. Calculations were made hourly then 

summed for the clear summer day and whole year.

Weather or Plant Variable ET Sensitivity (°C or % change)

Summer Day Whole Year

Tah, air temperature with absolute humidity constant, EC 2.394 3.435

Trh, air temperature with relative humidity constant, EC 1.489 2.052

Rs, solar radiation, % 0.585 0.399

ea, absolute vapor pressure, % -0.160 -0.223

u, wind speed, % 0.293 0.381

gs, surface or canopy conductance, % 0.085 0.160

LAI, leaf area index, % 0.085 0.160

1996). For C4 bahiagrass (Paspalum notatum), 

Newman et al. (2006) observed no biomass 

response to doubled CO2 at low N fertilization 

rate, but observed 7-17 percent increases with 

doubled CO2 when fertilized with 320 kg N per 

hectare. Biomass production in that study was 

determined over four harvests in each of two 

years (the 7 percent response in year one was 

non-significant, but 17 percent response in year 

two was significant).

2.2.1.3.4 Effects of CO2 Increase on Water 

Use and Water Use Efficiency

2.2.1.3.4.1 Changes in Crop Water Use due 

to Increasing Temperature, CO2, 

and O3

Water use (i.e., ET) of crop plants is a physical 

process but is mediated by crop physiological 

and morphological characteristics (e.g., Kimball 

2007). It can be described by the PenmanMonteith equation, whose form was recently

standardized (Allen et al. 2005) (Table 2.8). The 

equation reveals several mechanisms by which

the climate change parameters – temperature, 

CO2, and O3 – can affect water use. These include: (1) direct effects on crop growth and leaf 

area, (2) alterations in leaf stomatal aperture 

and consequently their conductance for water

vapor loss, and (3) physical changes in the vapor 

pressure inside leaves.

When plants are young and widely spaced, 

increases in leaf area are approximately 

proportional to the increases in growth, and 

transpiration increases accordingly. More importantly, duration of leaf area will affect total 

seasonal crop water requirements. Thus, the

lengthening of growing seasons due to global 

warming likely will increase crop water requirements. On the other hand, for some determinate 

cereal crops, increasing temperature can hasten 

plant maturity, thereby shortening the leaf area 

duration with the possibility of reducing the total 

season water requirement for such crops.

Elevated CO2 causes partial stomatal closure, 

which decreases conductance, and reduces loss 

of water vapor from leaves to the atmosphere. 

Reviews of the effects of elevated CO2 on stomatal conductance from chamber-based studies have reported that, on average, a doubling 

of CO2 (from about 340 to 680 ppm) reduces 

stomatal conductance about 34 percent (e.g., 

Kimball and Idso 1983). Morison (1987) calculated an average reduction of about 40 percent, 

with no difference between C3 and C4 species. 

More recently, Wand et al. (1999) performed 

a meta-analysis on observations reported for 

wild C3 and C4 grass species, and found that 

with no stresses, elevated CO2 reduced stomatal 

conductance by 39 and 29 percent for C3 and C4

species, respectively. The stomatal conductance 

of woody plants appears to decrease less than 

that of herbaceous plants in elevated CO2, as 
The U.S. Climate Change Science Program

40

Chapter 2

indicated by an 11 percent reduction in the 

meta-analysis of woody plant data by Curtis and 

Wang (1998). Ainsworth et al. (2002) found an 

average reduction of about 40 percent in conductance of soybean for a wide range of CO2

concentrations, with the reduction for a doubling being about 30 percent. Meta-analysis by 

Ainsworth and Long (2005) and Ainsworth and 

Rogers (2007) of data generated by free-air CO2

enrichment experiments, for which the daytime 

concentrations were 550-600 ppm, versus ambient concentrations of about 360 ppm, produced 

an average reduction in stomatal conductance 

of 20 and 22 percent, respectively. They did 

not detect any significant difference between 

C3 and C4 species. Projecting out 30 years, the 

atmospheric CO2 concentration likely will be 

about 440 ppm (see Introduction). Interpolating 

from these reviews, it appears very likely that 

an increase in CO2 concentration from 380 to 

440 ppm will cause reductions in stomatal conductance on the order of 10 percent compared 

to today’s values.

However, as plants shift from vegetative to 

reproductive growth during their life cycles, proportionately more of the accumulating biomass 

is partitioned to other organs, such as developing grain. At this point, leaf area and biomass 

accumulation are no longer 

proportional. Also, as plants 

grow and leaf area index (LAI) 

increases, the mutual shading 

and interference among the 

leaves within a plant canopy 

cause plant transpiration to 

plateau (Ritchie 1972; Villalobos and Fereres 1990; Sau et 

al. 2004). Further, considering 

that a doubling of CO2 from 

present-day levels is likely to 

increase average C3 species 

growth on the order of 30 percent (e.g., Kimball 1983, 2007; 

Kimball et al. 2002; Table 2.7), 

so projecting out 30 years to 

a CO2 concentration of about 

440 ppm suggests increases 

in C3 plant growth only on the 

order of 10 percent. Therefore, 

because changes in growth 

affect ET mostly while plants 

are small (i.e., after planting), 

and progressively less after canopy closure, 

changes in ET rates over the next 30 years due 

to leaf area index effects are likely to be minor 

(Figure 2.5).

Elevated CO2 concentrations – approximately 

550 ppm or about 180 ppm above ambient – in 

FACE experiments have reduced water use in 

experimental plots by about 2-13 percent, depending on species (Figure 2.6). Interpolating 

linearly to 440 ppm of CO2, the corresponding 

reductions likely would be about one-third 

of those observed in the FACE experiments 

(i.e., 1-4 percent). Because there are fetch 

considerations in extrapolating FACE plot data 

to larger areas (see discussion in Triggs et al. 

2004), reductions in crop water requirements

due to elevated CO2 likely will be significant, 

but smaller yet.

Less research has been done on the effects of elevated O3 on stomatal conductance compared to 

elevated CO2, but some pertinent work has been 

published. Barnes et al. (1995) and Balaguer 

et al. (1995) measured stomatal conductance 

of wheat exposed to elevated CO2 (700 ppm), 

elevated O3 (about 75 ppb), and combined 

elevated CO2 plus O3 in controlled environment chambers. The ozone treatment reduced 

Figure 2.6 Differences in evapotranspiration rate (latent energy, W m-2) 

between soybean plots enriched to 550 ppm from free-air CO2 enrichment 

(FACE) and plots at today’s ambient CO2 levels at Urbana, IL, versus day of 

year (circles, left axis). Corresponding precipitation is also shown (squares, 

right axis). Adapted from Bernacchi et al. 2007.
41

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

conductance by about 20 percent, while both 

CO2 and CO2+O3 reduced conductance by 40 

percent. Wheat was exposed by Donnelly et al. 

(2000) to elevated CO2 (680 ppm) and O3 (50 

or 90 ppb) and CO2+O3 in open-top chambers, 

and they found that all three treatments produced 

reductions in stomatal conductance of approximately 50 percent, with relative order changing 

with days after sowing and year. Using open-top 

chambers with potato, both Lawson et al. (2002) 

and Finnan et al. (2002) report 50 percent reduction of stomatal conductance with elevated CO2

(680 ppm) and a similar amount in combination 

with elevated O3, but their results are variable 

and mutually inconsistent among treatments. 

In a FACE project that included both CO2 and 

O3 treatments, Noormets et al. (2001) measured 

stomatal conductance of aspen leaves. Results 

varied with leaf age and aspen clone, but generally it appears that conductance had the following treatment rank: Control>O3>CO2+O3>CO2. 

Morgan et al. (2003) performed a meta-analysis 

of 53 prior chamber studies in which O3 was 

elevated by 70 ppm above clean air, and found 

that stomatal conductance was reduced by 17 

percent on average. However, in a recent FACE 

soybean experiment in which O3 was elevated 

by 50 percent above ambient conditions, Bernacchi et al. (2007) detected no significant 

effect of O3 on stomatal conductance. Thus, 

while chamber studies comparing the effects 

of O3 on stomatal conductance showed that 

reductions can occur, in the case of field-grown 

plants exposed to present-day ambient levels of 

O3 that are considerably above zero, the effects 

on conductance of the additional increases in 

O3 levels that are likely to occur in the next 30 

years are likely to be rather small.

Water vapor pressure (e) inside leaves is tightly 

coupled to leaf temperature (T) and increases 

exponentially (e.g., as described by the Teten’s 

equation, e=0.61078*exp(17.269*T/(T+237.3)).

Therefore, anything that affects the energy balance and temperature of a crop’s leaf canopy 

will affect leaf water vapor pressure, and ultimately water consumption. Consequently, so

long as there are no significant concomitant 

compensatory changes in other factors such as 

humidity, it is virtually certain that air temperature increases will also increase crop canopy 

temperature, leaf water vapor pressure, and ET 

(Figure 2.5). Based on the sensitivity analysis 

of Kimball (2007; Table 2.8), an increase of 

about 1.2°C with constant relative humidity, 

such as expected in 30 years (see Introduction), 

is likely to cause a small increase of about 

1.8% in summer-day ET of a standard alfalfa 

reference crop if CO2 concentrations were to 

remain at today’s level. As already dicussed, 

CO2 concentrations of about 440 ppm are likely 

to cause small decreases in ET, so therefore, the 

net effect of increased temperature plus CO2

likely will result in insignificant changes in ET 

within the next 30 years.

Another aspect to consider is the dynamics of 

crop water use and the timing of rain/irrigation 

events. The latent energy associated with ET 

from soybean was 10 to 60 W/m2 less in the 

FACE plots compared to the control plots at 

ambient CO2 when the crop had ample water 

(Figure 2.6).

However, on about Day-of-Year (DOY) 233, the 

control plots had exhausted the water supply, 

and their water use declined (Bernacchi et al. 

2006) (Figure 2.6). In contrast, the water conservation in the elevated-CO2 plots enabled plants 

to keep their stomata open and transpiring, and 

for DOYs 237-239, the FACE plots transpired 

more water than the controls. During this latter 

period, the FACE plants had their stomata open, 

while those of the control plots were closed. As 

a result, the FACE plots were able to continue 

photosynthesizing and growing while the controls were not. In other words, elevated concentrations of CO2 can enable some conservation of 

soil water for rain-fed agriculture, which often 

experiences periods of drought, and can sustain 

crop productivity over more days than is true at 

today’s CO2 levels.

The net irrigation requirement is the difference

between seasonal ET for a well-watered crop 

and the amounts of precipitation and soil water 

storage available during a growing season. A 

few researchers have attempted to estimate 

future changes in irrigation water requirements

based on projected climate changes (including 

rainfall changes) from general circulation models (GCMs), and estimates of decreased stomatal 

conductance due to elevated CO2 (e.g., Allen 

et al. 1991; Izaurralde et al. 2003). Izaurralde 

et al. (2003) used EPIC, a crop growth model, 

to calculate growth and yield, as well as future 
The U.S. Climate Change Science Program

42

Chapter 2

irrigation requirements of corn and alfalfa.

Following Stockle et al. (1992a, b), EPIC was 

modified to allow stomatal conductance to be 

reduced with increased CO2 concentration (28 

percent reduction corresponding to 560 μmol

CO2 mol-1), as well as increasing photosynthesis via improved radiation use efficiency. For 

climate change projections, they used scenarios 

generated for 2030 by the Hadley Centre’s (HadCM2J) GCM, which was selected because its 

climate sensitivity is in the midrange of most 

of the GCMs. For corn, Izaurralde et al. (2003) 

calculated that by 2030 irrigation requirements

will change from -1 (Lower Colorado Basin) to 

+451 percent (Lower Mississippi Basin), because 

of rainfall variation. Given the variation in the 

sizes and baseline irrigation requirements of U.S.

basins, a representative figure for the overall U.S. 

increase in irrigation requirements is 64 percent

if stomatal effects are ignored, or 35 percent 

if they are included. Similar calculations were 

made for alfalfa, for which overall irrigation 

requirements are predicted to increase 50 and

29 percent in the next 30 years in the cases of 

ignoring and including stomatal effects, respectively. These increases are more likely due to the 

decrease in rainfall during the growing season 

and the reduction in soil water availability.

2.2.1.3.4.2 Implications for Irrigation and 

Water Deficit

As mentioned above, stomatal conductance is 

reduced about 40 percent for doubling of CO2

for both C3 and C4 species (Morison 1987), 

thus causing water conservation effects, and 

potentially less water deficit. However, actual 

reduction in crop transpiration and ET will not 

be as great as the reduction in stomatal conductance because warming of the foliage to solve 

the energy balance will increase both latent heat 

loss (transpiration) and sensible heat loss. Allen et al. (2003) concluded that both increased 

foliage temperature, and increased LAI associated with CO2 enrichment were responsible 

for the compensatory effects on ET (small to 

non-existent reductions). Jones et al. (1985) 

reported 12 percent reduction in season-long 

transpiration and 51 percent increase in water 

use efficiency (WUE) measured for canopies 

of soybean crops grown in ambient and doubled 

CO2 in sunlit, controlled environment chambers. 

In experimental studies in the same chambers, 

foliage temperatures measured by infrared 

sensors have typically been increased 1-2oC 

for soybean, 1.5oC for dry bean, and 2oC for 

sorghum in response to doubled CO2 (Pan 

1996; Prasad et al. 2002; Prasad et al. 2006a). 

Similarly, in FACE experiments at about 550 

ppm CO2 foliage temperatures increased by an 

average 0.6oC for wheat (Kimball et al. 2002), 

0.4oC for rice (Yoshimoto et al. 2005), 1.7oC for 

sorghum (Triggs et al. 2004), 0.8oC for cotton 

(Kimball et al. 2002), 0.8oC for potato (Magliuo 

et al. 2003), and 0.2 to 0.5oC for soybean (Bernacchi et al. 2007).

Allen et al. (2003) reported that soybean foliage 

at doubled CO2 was, on average, 1.3oC warmer 

at mid-day. Andre and du Cloux (1993) reported 

an 8 percent decrease in transpiration of wheat in 

response to doubled CO2, which compares well 

to a 5 percent reduction in ET of wheat for a 200 

ppm CO2 increase in FACE studies (Hunsaker 

et al. 1997; Kimball et al. 1999) (Figure 2.5). 

Reddy et al. (2000), using similar chambers, 

found an 8 percent reduction in transpiration of 

cotton canopies at doubled CO2, averaged over 

five temperature treatments, while Kimball et al. 

(1983) found a 4 percent reduction in seasonal 

water use of cotton at ambient versus 650 ppm 

CO2 in lysimeter experiments in Arizona. Soybean canopies grown at 550 compared to 375 

ppm in FACE experiments in Illinois had 9-16 

percent decreases in ET depending on season. 

Their data show an average 12 percent reduction 

over three years (Bernacchi et al. 2007). Allen 

et al. (2003) observed 9 percent reduction in ET 

of soybean with doubling of CO2 in the sunlit, 

controlled environment chambers for a 28/18oC 

treatment (about the same mean temperature as 

the Illinois site), but they observed no reduction in ET for a high temperature treatment 

40/30oC. The extent of CO2-related reduction 

in ET appears to be dependent on temperature. 

In their review, Horie et al. (2000) reported the 

same phenomenon in rice, where doubling CO2

caused 15 percent reduction in ET at 26oC, but 

resulted in increased ET at higher temperatures 

(29.5oC). At 24-26oC, rice’s WUE increased 50 

percent with doubled CO2, but the CO2 enrichment effect declined as temperature increased. 

At higher temperature, CO2-induced reduction 

in conductance lessened.

Using observed sensitivity of soybean stomatal 

conductance to CO2 in a crop climate model, 
43

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Allen (1990) showed that CO2 enrichment from 

330 to 800 ppm should cause an increase in foliage temperature of about 1oC when air vapor 

pressure deficit is low, but an increase of about 

2.5 and 4oC with air vapor pressure deficit of 

1.5, and 3 kPa, respectively. At the higher vapor 

pressure deficit values, the foliage temperatures 

simulated with this crop climate model (Allen 

1990) exceeded the differential observed under larger vapor pressure deficit in the sunlit, 

controlled-environment chambers (Prasad et 

al. 2002; Allen et al. 2003; Prasad et al. 2006a). 

Allen et al. (2003) found that soybean canopies 

increased their conductance (lower resistance) 

at progressively larger vapor pressure deficit 

(associated with higher temperature), such that 

foliage temperature did not increase as much as 

supposed by the crop-climate model. Concurrently, the anticipated degree of reduction in 

ET with doubling of CO2, while being 9 percent 

less at cool temperatures (28/18oC), became 

progressively less and was non-existent (no 

difference) at very high temperatures (40/30oC 

and 44/34oC). In other words, the CO2-induced 

reduction in conductance became less as temperature increased.

Boote et al. (1997) used a version of the 

CROPGRO-Soybean model with hourly energy 

balance and feedback of stomatal conductance 

on transpiration and leaf temperature (Pickering 

et al.1995), to study simulated effects of 350 

versus 700 ppm CO2 for field weather from Ohio 

and Florida. The simulated transpiration was 

reduced 11-16 percent for irrigated sites and 7 

percent for a rainfed site in Florida, while the ET 

was reduced 6-8 percent for irrigated sites and 

4 percent for the rainfed site. Simulated water 

use efficiency was increased 53-61 percent, 

which matches the 50-60 percent increase in 

soybean WUE reported by Allen et al. (2003) 

for doubling of CO2. The smaller reduction in 

transpiration and ET for the rainfed site was associated with more effective prolonged use of 

the soil water, also giving a larger yield response 

(44 percent) for rainfed crop than for irrigated 

(32 percent). The model simulated reductions 

in transpiration were close (11-16 percent) to 

those measured (12 percent) by Jones et al. 

(1985), and the reduction was much less than 

the reduction in leaf conductance. The model 

simulations also produced a 1oC higher foliage 

temperature at mid-day under doubled CO2.

Interactions of CO2 enrichment with climatic 

factors of water supply and evaporative demand will be especially evident under water 

deficit conditions. The reduction in stomatal 

conductance with elevated CO2 will cause soil 

water conservation and potentially less water 

stress, especially for crops grown with periodic 

soil water deficit, or under high evaporative 

demand. This reduction in water stress effects 

on photosynthesis, growth, and yield has been 

documented for both C3 wheat (Wall et al. 2006) 

and C4 sorghum (Ottman et al. 2001; Wall et 

al. 2001; Triggs et al. 2004). Sorghum grown 

in the Arizona FACE site showed significant 

CO2-induced enhancement of biomass and grain 

yield for water deficit treatments, but no significant enhancement for sorghum grown with full 

irrigation (Ottman et al. 2001). In the sorghum 

FACE studies, the stomatal conductance was reduced 32-37 percent (Wall et al. 2001), while ET 

was reduced 13 percent (Triggs et al. 2004).

2.2.1.4 Crop Response to Tropospheric

 Ozone

Ozone at the land surface has risen in rural areas 

of the United States, particularly over the past 50 

years, and is forecast to continue increasing during the next 50 years. The Midwest and eastern 

U.S. have some of the highest rural ozone levels 

on the globe. Average ozone concentrations rise 

toward the east and south, such that average 

levels in Illinois are higher than in Nebraska, 

Minnesota, and Iowa. Only western Europe and 

eastern China have similarly high levels. Argentina and Brazil, like most areas of the Southern 

Hemisphere, have much lower levels of ozone, 

and are forecast to see little increase over the 

next 50 years. Increasing ozone tolerance will 

therefore be important to the competitiveness 

of U.S. growers. Numerous models for future 

changes in global ozone concentrations have 

emerged that are linked to IPCC scenarios, so 

the impacts of ozone can be considered in the 

context of wider global change. For example, 

a model that incorporates expected economic 

development and planned emission controls in 

individual countries projects increases in annual 

mean surface ozone concentrations in all major 

agricultural areas of the Northern Hemisphere 

(Dentener et al. 2005).

Ozone is a secondary pollutant resulting from 

the interaction of nitrogen oxides with sunlight 

Ozone at the land 

surface has risen 

in rural areas of 

the United States, 

particularly over 

the past 50 years, 

and is forecast 

to continue 

increasing during 

the next 50 years. 
The U.S. Climate Change Science Program

44

Chapter 2

and hydrocarbons. Nitrogen oxides are produced 

in the high-temperature combustion of any fuel. 

They are stable and can be transported thousands 

of miles in the atmosphere. In the presence of 

sunlight, ozone is formed from these nitrogen 

oxides and, in contrast to most pollutants, higher 

levels are observed in rural than urban areas. 

This occurs because rural areas have more 

hours of sunshine and less haze, and city air 

includes short-lived pollutants that react with, 

and remove, ozone. These short-lived pollutants 

are largely absent from rural areas. Levels of 

ozone during the day in much of the Midwest 

now reach an average of 60 parts of ozone per 

billion parts of air (ppb), compared to less than 

10 ppb 100 years ago. While control measures 

on emissions of NOx and volatile organic carbons (VOCs) in North America and western 

Europe are reducing peak ozone levels, global 

background tropospheric ozone concentrations 

are on the rise (Ashmore 2005). Ozone is toxic 

to many plants, but studies in greenhouses and 

small chambers have shown soybean, wheat, 

peanut, and cotton are the most sensitive of our 

major crops (Ashmore 2002).

Ozone effects on soybean crops have been most 

extensively studied and best analyzed. This is 

because soybean is the most widely planted 

dicotyledonous crop, and is our best model of 

C3 annual crops. The response of soybean to 

ozone can be influenced by the ozone profile 

and dynamics, nutrient and moisture conditions, atmospheric CO2 concentration, and even 

the cultivar investigated, which creates a very 

complex literature to interpret. Meta-analytic 

methods are useful to quantitatively summarize

treatment effects across multiple studies, and 

thereby identify commonalities. A meta-analysis 

of more than 50 studies of soybean, grown in 

controlled environment chambers at chronic 

levels of ozone, show convincingly that ozone 

exposure results in decreased photosynthesis, 

dry matter, and yield (Morgan et al. 2003). Even 

mild chronic exposure (40-60 ppb) produces 

such losses, and these losses increase linearly 

with ozone concentration (Morgan et al. 2003) 

as anticipated from the exposure/response relationship shown by Mills et al. (2000).

The meta-analytic summary further reveals that 

chronic ozone lowers the capacity of carbon 

uptake in soybean by reducing photosynthetic 

capacity and leaf area. Soybean plants exposed 

to chronic ozone levels were shorter with less 

dry mass and fewer set pods, which contained 

fewer, smaller seeds. Averaged across all studies, biomass decreased 34 percent, and seed 

yield was 24 percent lower, but photosynthesis was depressed by only 20 percent. Ozone 

damage increased with the age of the soybean, 

consistent with the suggestion that ozone effects 

accumulate over time (Adams et al. 1996; Miller 

et al. 1998), and may additionally reflect greater 

sensitivity of reproductive developmental stages, particularly seed filling (Tingey et al. 2002). 

The meta-analysis did not reveal any interactions with other stresses, even stresses expected 

to lower stomatal conductance and therefore 

ozone entry into the leaf (Medlyn et al. 2001). 

However, all of the ozone effects on soybean 

mentioned above were less under elevated CO2, 

a response generally attributed to lower stomatal 

conductance (Heagle et al. 1989).

Plant growth in chambers can be different 

compared to the open field (Long et al. 2006), 

and therefore the outcomes of chamber experiments have been questioned as a sole basis for

projecting yield losses due to ozone (Elagoz and 

Manning 2005). FACE experiments in which 

soybeans were exposed to a 20 percent elevation 

above ambient ozone levels indicate that ozoneinduced yield losses were at least as large under 

open air treatment. In 2003, the background 

ozone level in central Illinois was unusually low 

over the growing season, averaging 45 parts per 

billion (ppb). Elevation of ozone by 20 percent 

in this year raised the ozone concentration to 

the average of the previous 10 years. In the 

plots with elevated ozone in 2003, yields were 

reduced approximately 25 percent (Morgan et 

al. 2006). This suggests that, in a typical year 

under open-air field conditions, yield loss due 

to ozone is even greater than predictions from 

greenhouse experiments (Ashmore 2002).

Analysis in the soybean FACE results showed 

a significant decrease in leaf area (Dermody 

et al. 2006), a loss of photosynthetic capacity 

during grain filling, and earlier senescence of 

leaves (Morgan et al. 2004). This may explain 

why yield loss is largely due to decreased seed 

size rather than decreased seed number (Morgan 
45

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

et al. 2006). On average, yield losses in Illinois 

soybean FACE experiments between 2002 and 

2005 were 0.5 percent per ppb ozone increase 

over the 30 ppb threshold, which is twice the 

ozone sensitivity as determined in growth 

chamber studies (Ashmore 2002). These results 

suggest that during an average year, ozone 

is currently causing soybean yield losses of 

10-25 percent in the Midwest, with even greater 

losses in some years. The IPCC forecasts that 

ozone levels will continue to rise in the rural 

Midwest by about 0.5 ppb per year, suggesting 

that soybean yields may continue to decline by 

1 percent every two to four years. The IPCC 

also forecasts that ozone, which is low in South 

America, will remain low in that region over 

the next 50 years.

Meta-analysis has not been conducted for the effects of ozone on any crops other than soybean, 

or across different crops. Nevertheless, there is 

little doubt that current tropospheric ozone levels are limiting yield in many crops (e.g., Heagle 

1989) and further increases in ozone will reduce 

yield in sensitive species further. The effect of 

exposure to ozone on yield and yield parameters 

from studies conducted prior to 2000 are compiled in Table 4 of Black et al. (2000), which 

reveals that, in addition to soybean, the yield 

of C3 crops, such as wheat, oats, French and 

snap bean, pepper, rape, and various cucurbits, 

are highly sensitive to chronic ozone exposure. 

Yield of woody perennial cotton is also highly 

sensitive to ozone (e.g., Temple 1990; Heagle 

et al. 1996). While there are isolated reports that 

maize yield is reduced by ozone (e.g., Rudorff 

et al. 1996), C4 crops are generally much less 

sensitive to ozone. Recent studies by Booker et 

al. (2007) and Burkey et al. (2007) on peanuts 

that evaluated the effect of ozone under CO2

levels from 375 to 730 ppm, and ozone levels 

of 22-75 ppb, showed that CO2 increases offset 

the effects of ozone. Increasing CO2 levels 

overcame the effect of ozone on peanut yield; 

however, in none of the treatments was there a 

change in seed quality, or protein or oil content

of the seed (Burkey et al. 2007).

2.2.2 Pastureland

In general, grassland species have received 

less attention than cropland species for their 

response to projected changes in temperature, 

precipitation, and atmospheric CO2 concentration associated with climate change (Newman 

et al. 2001). Pastureland response to climate 

change is complex because, in addition to the 

major climatic drivers (CO2 concentration, 

temperature, and precipitation), other plant and 

management factors affect this response (e.g., 

plant competition, perennial growth habits, 

seasonal productivity, etc.). Many of the studies in our review of published materials that 

report on temperate-climate pasture responses to 

changes in temperature, precipitation, and CO2

concentrations originate from regions outside 

the United States.

An early comprehensive greenhouse study 

examined the photosynthetic response of 13 

pasture species (Table 2.9) to elevated CO2

(350 and 700 ppm) and temperature (12/7°C, 

18/13°C, and 28/23°C for daytime/nighttime 

temperatures) (Greer et al. 1995). On average, 

photosynthetic rates increased by 40 percent 

under elevated CO2 in C3 species, while those 

for C4 species remained largely unaffected. 

The response of C3 species to elevated CO2

decreased as temperatures increased from 

12-28°C. However, the temperatures at which 

the maximum rates of photosynthesis occurred 

varied with species and level of CO2 exposure. 

At 350 ppm, four species (L. multiflorum, A. 

capillaris, C. intybus, and P. dilatatum) showed 

maximum rates of photosynthesis at 18°C while, 

for the rest, the maximum occurred at 28°C. At 

700 ppm, rates shifted upwards from 18-28°C in 

A. capillaries, and downward from 28-18°C in 

L. perenne, F. arundinacea, B. wildenowii, and 

T. subterraneum. However, little if any correlation existed between the temperature response 

of photosynthesis and climatic adaptations of 

the pasture species.

In Florida, a 3-year study examined the effects 

of elevated atmospheric CO2 (360 and 700 

ppm), and temperature (ambient temperature or 

baseline (B), B+1.5°C, B+3.0°C, and B+4.5°C) 

on dry matter yield of rhizoma peanut (a C3

legume), and bahiagrass (a C4 grass) (Newman 

et al. 2001). On average, yields increased by 
The U.S. Climate Change Science Program

46

Chapter 2

Table 2.9 Pasture species studied for response to CO2 and temperature changes. Adapted from Greer et al. 

(1995).

Species Common name

Photosynthetic 

pathway Growth characteristics

Lolium multiflorum Italian ryegrass C3 Cool season annual grass

Bromus wildenowii C3 Cool season perennial grass

Lolium perenne Ryegrass C3 Cool season perennial grass

Phalaris aquatica C3 Cool season perennial grass

Trifolium dubium C3 Cool season annual broadleaf

Trifolium subterraneum Subterraneum clover C3 Cool season annual broadleaf

Agrostis capillaris C3 Warm season perennial grass

Dactylis glomerata Orchardgrass C3 Warm season perennial grass

Festuca arundinacea Tall fescue C3 Warm season perennial grass

Cichorium intybus C3 Warm season perennial broadleaf

Trifolium repens White clover C3 Warm season perennial broadleaf

Digitaria sanguinalis Crabgrass C4 Warm season annual grass

Paspalum dilatatum Dallisgrass C4 Warm season perennial grass

25 percent in rhizoma peanut plots exposed to 

elevated CO2, but exhibited only a positive trend 

in bahiagrass plots under the same conditions. 

These results are consistent with C3- and C4-type 

plant responses to elevated CO2.

The response of forage species to elevated CO2

may be affected by grazing and aboveground/

belowground interactions (Wilsey 2001). In a 

phytotron study, Kentucky bluegrass and timothy (Phleum pratense L.) were grown together in 

pots during 12 weeks under ambient (360 ppm) 

and elevated CO2 (650 ppm), with and without 

aboveground defoliation, and with and without 

the presence of Pratylenchus penetrans, a rootfeeding nematode commonly found in old fields 

and pastures. Timothy was the only species that 

responded to elevated CO2 with an increase in 

shoot biomass, leading to its predominance in 

the pots. This suggests that Kentucky bluegrass 

might be at the lower end of the range in the 

responsiveness of C3 grasses to elevated CO2, 

especially under low nutrient conditions. Defoliation increased productivity only under ambient 

CO2; thus, the largest response to elevated CO2

was observed in non-defoliated plants. Timothy 

was the only species that showed an increase in 

root biomass under elevated CO2. Defoliation 

reduced root biomass. Elevated CO2 interacted 

with the presence of nematodes in reducing 

root biomass. In contrast, defoliation alleviated 

the effect of root biomass reduction caused by 

the presence of nematodes. This study demonstrates the importance of using aboveground/

belowground approaches when investigating 

the environmental impacts of climate change 

(Wardle et al. 2004).

Kentucky bluegrass might not be the only species showing low response to elevated CO2. 

Perennial ryegrass (Lolium perenne) has been 

reported to have low or even negative yield 

response to elevated CO2 under field conditions but, contradictorily, often shows a strong 

response in photosynthetic rates (Suter et al. 

2001). An experiment at the Swiss FACE 

examined the effects of ambient (360 ppm) 

and elevated (600 ppm) CO2 on regrowth characteristics of perennial ryegrass (Suter et al. 

2001). Elevated CO2 increased root mass by 68 

percent, pseudostems by 38 percent, and shoot 

necromass below cutting height by 45 percent 

during the entire regrowth period. Many of the 

variables measured (e.g., yield, dry matter, and 

leaf area index) showed a strong response to 

elevated CO2 during the first regrowth period 
47

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

but not during the second, suggesting a lack of 

a strong sink for the extra carbon fixed during 

the latter period.

When combined, rising CO2 and projected 

changes in temperature and precipitation may 

significantly change the growth and chemical 

composition of plant species. However, it is not 

clear how the various forage species that harbor 

mutualistic relationships with other organisms 

would respond to elevated CO2. Newman et al. 

(2003) studied the effects of endophyte infection, N fertilization, and elevated CO2 on growth 

parameters and chemical composition of tall 

fescue. Fescue plants, with and without endophyte infection (Neotyphodium coenophialum), 

were transplanted to open chambers and exposed 

to ambient (350 ppm) and elevated (700 ppm) 

levels of CO2. All chambers were fertilized with 

uniform rates of phosphorus (P) and potassium 

(K). Nitrogen fertilizer was applied at rates of 

6.7 and 67.3 g m-2. The results revealed complex 

interactions of the effects of elevated CO2 on the 

mutualistic relationship between a fungus and its 

host, tall fescue. After 12 weeks of growth, plants 

grown under elevated CO2 exhibited apparent 

photosynthetic rates 15 percent higher than those 

grown under ambient conditions. The presence 

of the endophyte fungus in combination with N 

fertilization enhanced the CO2 fertilization effect. Elevated CO2 accelerated the rate of tiller 

appearance and increased dry matter production 

by at least 53 percent (under the low N treatment). Contrary to previous findings, Newman 

et al. (2003) found that elevated CO2 decreased 

lignin concentrations by 14 percent. Reduced 

lignin concentration would favor the diet of grazing animals, but hinder stabilization of carbon in 

soil organic matter (Six et al. 2002).

Climate change may cause reduction in precipitation and, in turn, induce soil moisture 

limitations in pasturelands. An experiment 

in New Zealand examined the interaction of 

elevated CO2 and soil moisture limitations on 

the growth of temperate pastures (Newton et al. 

1996). Intact turves (plural of turf) composed 

primarily of perennial ryegrass and dallisgrass 

(Paspalum dilatatum) were grown for 324 days 

under two levels of CO2 (350 and 700 ppm), 

with air temperatures and photoperiod designed 

to emulate the monthly climate of the region. 

After this equilibration period, half the turves

in each CO2 treatment underwent soil moisture 

deficit for 42 days. Turves under elevated CO2

continued to exchange CO2 with the atmosphere, 

while turves under ambient CO2 did not. Root 

density measurements indicated that roots acted 

as sinks for the carbon fixed during the soil 

moisture deficit period. Upon rewatering, turves 

under ambient CO2 had a vigorous rebound in 

growth while those under elevated CO2 did not 

exhibit additional growth, suggesting that plants 

may exhibit a different strategy in response 

to soil moisture deficit depending on the CO2

concentration.

2.2.2.1 Predictions of Pastureland

 Forage Yields and Nutrient

 Cycling under Climate Change

To evaluate the effect of climate scenarios on 

a forage crop, alfalfa production was simulated 

with the EPIC agroecosystem model (Williams 

1995), using various climate change projections 

from the HadCM2 (Izaurralde et al. 2003), and 

GCMs from Australia’s Bureau of Meteorology 

Research Centre (BMRC), and the University of 

Illinois, Urbana-Champaigne (UIUC) (Thomson et al. 2005). All model runs were driven 

with CO2 levels of 365 and 560 ppm without 

irrigation.

The results give an indication of pastureland 

crop response to changes in temperature, 

precipitation, and CO2 for major regions of 

the United States (Table 2.10). Of these three 

factors, variation in precipitation had the greatest impact on regional alfalfa yield. Under 

the HadCM2 projected climate, alfalfa yields 

increase substantially in eastern regions, with 

declines through the central part of the country 

where temperature increases are greater and precipitation is lower. Slight alfalfa yield increases 

are predicted for western regions. The BMRC 

model projects substantially higher temperatures 

and consistent declines in precipitation over the 

next several decades, leading to a nationwide 

decline in alfalfa yields. In contrast, the UIUC 

model projects more moderate temperature increases along with higher precipitation, leading 

to modest increases in alfalfa yields throughout 

the central and western regions. While these 

results illustrate the uncertainty of model projections of crop yields due to the variation in 

Climate change may 

cause reduction in 

precipitation and, 

in turn, induce soil 

moisture limitations 

in pasturelands. 
The U.S. Climate Change Science Program

48

Chapter 2

global climate model projections of the future, 

they also underscore the primary importance 

of future precipitation changes on crop yield. 

Analysis of the results shown in Table 2.10 

reveals that precipitation was the explanatory 

variable in yield changes followed by CO2 and 

temperature change. Comparing the BMRC, 

HadCM2, and UIUC models showed that future changes in precipitation will be extremely 

important in alfalfa yields with a 1 percent decrease in alfalfa yields for every 4 mm decrease 

in annual precipitation.

Table 2.10 Change in alfalfa yields in major U.S. regions as a percentage of baseline yield with average temperature and precipitation change under the selected climate model for early century (2030) climate change 

projections. Data in table from the simulations provided in Izaurralde et al. (2003).

Region

CO2

HadCM2 BMRC UIUC

ΔT

(°C)

ΔP

(mm)

Yield

% change

ΔT

(°C)

ΔP

(mm)

Yield

% change

ΔT

(°C)

ΔP

(mm)

Yield

% change

Great Lakes

365 1.13 74 17.0 1.79 -6 -0.4 0.96 19 -1.3

560 20.6 0.0 -1.0

Ohio

365 0.70 80 12.5 1.66 -16 -5.2 0.86 25 -3.7

560 13.9 -5.0 -3.8

Upper Mississippi

365 1.24 74 10.9 1.71 -14 -3.4 0.89 29 -2.2

560 14.8 -2.5 -2.1

Souris-Red-Rainy

365 1.40 -30 -30.7 1.73 -3 -1.9 0.96 12 -0.4

560 -25.4 2.1 2.6

Missouri

365 1.42 34 -9.2 1.50 -18 -9.4 0.92 41 3.5

560 -7.1 -9.1 3.1

Arkansas

365 1.77 -2 -18.6 1.53 -32 -9.6 0.76 61 3.8

560 -14.2 -7.3 5.1

Rio Grande

365 3.11 12 5.0 1.41 -20 -9.3 0.84 25 16.2

560 5.3 -8.7 17.8

Upper Colorado

365 2.21 76 5.0 1.48 -18 -15.3 0.97 40 16.2

560 5.4 -14.1 16.7

Lower Colorado

365 1.43 2 7.3 1.31 -23 -16.0 0.97 27 7.8

560 11.9 -19.4 4.7

Great Basin

365 0.62 21 -4.7 1.36 -15 -6.3 1.07 45 24.2

560 -4.5 -7.1 23.7

Pacific Northwest

365 0.45 3 0.4 1.24 -6 2.0 1.11 54 8.4

560 1.7 1.9 8.1

California

365 0.95 58 8.7 1.13 -45 -5.5 1.08 17 6.3

560 9.3 -3.5 4.6

Thornley and Cannell (1997) argued that experiments on elevated CO2, and temperature 

effects on photosynthesis and other ecosystem 

processes may have limited usefulness for at 

least two reasons. First, laboratory or field 

experiments incorporating sudden changes in 

temperature or elevated CO2 are short term 

and thus rarely produce quantitative changes

in net primary productivity (NPP), ecosystem 

C, or other ecosystem properties connected to 

long-term responses to gradual climate change. 
49

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Second, the difficulty of incorporating grazing 

in these experiments prevents a full analysis of 

its effects on ecosystem properties such as NPP, 

LAI, belowground process, and ecosystem C.

Thornley and Cannell (1997) used their Hurley 

Pasture Model to simulate ecosystem responses 

of ungrazed and grazed pastures to increasing 

trends in CO2 concentrations and temperature. 

The simulations revealed three important results: 

1) rising CO2 induces a carbon sink, 2) rising 

temperatures alone produce a carbon source, 

and 3) a combination of the two effects is likely 

to generate a carbon sink for several decades 

(5-15 g C m-2 yr-1). Modeling the dynamics of 

mineral N availability in grazed pastures under 

elevated CO2, Thornley and Cannell (2000) 

ascertained the role of the mineral N pool and 

its turnover rate in slowly increasing C content 

in plants and soils.

2.2.2.2 Implications of Altered

 Productivity, Nitrogen Cycle 

(forage quality), Phenology,

and Growing Season on Species

 Mixes, Fertilizer, and Stocking

In general, the response of pasture species to 

elevated CO2 deduced from these studies is 

consistent with the general response of C3 and 

C4 type vegetation to elevated CO2, although 

significant exceptions exist. Pasture species 

with C3-type metabolism increased their photosynthetic rates by up to 40 percent, but not 

those with a C4 pathway (Greer et al. 1995). 

The study of Greer et al. (1995) suggests shifts 

in optimal temperatures for photosynthesis under elevated CO2, with perennial ryegrass and 

tall fescue showing a downward shift in their 

optimal temperature from 28-18°C. Unlike croplands, the literature for pasturelands is sparse 

in providing quantitative information to predict

the yield change of pastureland species under 

a temperature increase of 1.2°C. The projected 

increases in temperature and the lengthening 

of the growing season should be, in principle, 

beneficial for livestock produced by increasing 

pasture productivity and reducing the need for 

forage storage during the winter period.

Naturally, changes in CO2 and temperature will 

be accompanied by changes in precipitation, 

with the possibility of more extreme weather 

causing floods and droughts. Precipitation 

changes will likely play a major role in determining NPP of pasture species as suggested 

by the simulated 1 percent change in yields of 

dryland alfalfa for every 4-mm change in annual 

precipitation (Izaurralde et al. 2003; Thomson 

et al. 2005).

Another aspect that emerges from this review 

is the need for comprehensive studies of the 

impacts of climate change on the pasture ecosystem including grazing regimes, mutualistic 

relationships (e.g., plant roots-nematodes; Nfixing organisms), as well as C, nutrient, and 

water balances. Despite their complexities, the 

studies by Newton et al. (1996) and Wilsey 

(2001) underscore the importance, difficulties, 

and benefits of conducting multifactor experiments. To augment their value, these studies 

should include the use of simulation modeling 

(Thornley and Cannell 1997) in order to test 

hypotheses regarding ecosystem processes.

2.2.3 Rangelands

The overall ecology of rangelands is determined primarily by the spatial and temporal 

distribution of precipitation and consequences

of precipitation patterns for soil water availability (Campbell et al. 1997; Knapp, Briggs and 

Koelliker 2001; Morgan 2005). Rising CO2 in 

the atmosphere, warming and altered precipitation patterns all impact strongly on soil water 

content and plant water relations (Alley et al. 

2007; Morgan et al. 2004b), so an understanding 

of their combined effects on the functioning of 

rangeland ecosystems is essential.

2.2.3.1 Ecosystem Responses to CO2

and Climate Drivers

2.2.3.1.1 Growing Season Length and 

Plant Phenology

Although responses vary considerably among 

species, in general warming should accelerate 

plant metabolism and developmental processes, 

leading to earlier onset of spring green-up, and 

lengthening of the growing season in rangelands 

(Badeck et al. 2004). The effects of warming are 

also likely to be seen as changes in the timing of 

phenological events such as flowering and fruiting. For instance, experimental soil warming of 

approximately 2oC in a tallgrass prairie (Wan et 

al. 2005) extended the growing season by three 

weeks, and shifted the timing and duration of 
The U.S. Climate Change Science Program

50

Chapter 2

reproductive events variably among species; 

spring blooming species flowered earlier, late 

blooming species flowered later (Sherry et al. 

2007). Extensions and contractions in lengths 

of the reproductive periods were also observed 

among the species tested (see also Cleland et al. 

2006). Different species responses to warming 

suggest strong selection pressure for altering 

future rangeland community structure, and for 

the associated trophic levels that depend on the 

plants for important stages of their life cycles.

Periods of drought stress may suppress warming-induced plant activity (Gielen et al. 2005), 

thereby effectively decreasing plant development time. CO2 may also impact phenology of 

herbaceous plant species, although species can 

differ widely in their developmental responses 

to CO2 (Huxman and Smith; 2001 Rae et al. 

2006), and the implications for these changes 

in rangelands are not well understood. Thus, 

temperature is the primary climate driver that 

will determine growing season length and plant 

phenology, but precipitation variability and CO2

may cause deviations from the overall patterns 

set by temperature.

2.2.3.1.2 Net Primary Production

Increases in CO2 concentration and in precipitation and soil water content expected for 

rangelands generally enhance NPP, whereas 

increased air temperature may either increase 

or reduce NPP.

2.2.3.1.2.1 CO2 Enrichment

Most forage species on rangelands have either 

the C3 or C4 photosynthetic pathway. Photosynthesis of C3 plants, including most woody 

species and herbaceous broad-leaf species 

(forbs), is not CO2-saturated at the present 

atmospheric concentration, so carbon gain and 

productivity usually are very sensitive to CO2

in these species (Drake et al. 1997). Conversely, 

photosynthesis of C4 plants, including many 

of the warm-season perennial grass species of 

rangelands, is nearly CO2-saturated at current 

atmospheric CO2 concentrations (approximately 

380 ppm) when soil water is plentiful, although 

the C4 metabolism does not preclude photosynthetic and growth responses to CO2 (Polley et 

al. 2003). In addition, CO2 effects on rates of 

water loss (transpiration) and plant WUE are at 

least as important as photosynthetic response 

to CO2 for rangeland productivity. Stomata of 

most herbaceous plants partially close as CO2

concentration increases, thus reducing plant 

transpiration. Reduced water loss improves plant 

and soil water relations, increases plant production under water limitation, and may lengthen 

the growing season for water-limited vegetation 

(Morgan et al. 2004b).

CO2 enrichment will stimulate NPP on most 

rangelands, with the amount of increase dependent on precipitation and soil water availability. 

Indeed, there is evidence that the historical 

increase in CO2 of about 35 percent has already 

enhanced rangeland NPP. Increasing CO2 from 

pre-industrial levels to elevated concentrations 

(250 to 550 ppm) increased aboveground NPP 

of mesic grassland in central Texas between 

42-69 percent (Polley et al. 2003). Biomass 

increased by similar amounts at pre-industrial to 

current, and current to elevated concentrations. 

Comparisons between CO2-induced production 

responses of semi-arid Colorado shortgrass 

steppe with the sub-humid Kansas tall grass 

prairie suggest that Great Plains rangelands respond more to CO2 enrichment during dry than 

wet years, and that the potential for CO2-induced 

production enhancements are greater in drier 

rangelands (Figure 2.7). However, in the stilldrier Mojave Desert, CO2 enrichment-enhanced 

shrub growth occurred most consistently during 

relatively wet years (Smith et al. 2000). CO2 enrichment stimulated total biomass (aboveground 

+ belowground) production in one study on annual grassland in California (Field et al. 1997), 

but elicited no production response in a second 

experiment (Shaw et al. 2002).

2.2.3.1.2.2 Temperature

Like CO2 enrichment, increasing ambient air 

and soil temperatures may enhance rangeland 

NPP, although negative effects of higher temperatures also are possible, especially in dry and 

hot regions. Temperature directly affects plant 

physiological processes, but rising ambient temperatures may indirectly affect plant production 

by extending growing season length, increasing 

soil nitrogen (N) mineralization and availability, 

altering soil water content, and shifting plant 

species composition and community structure 

(Wan et al. 2005). Rates of biological processes 

for a given species typically peak at plant temperatures that are intermediate in the range 

over which a species is active, so direct effects 
51

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 2.7 Aboveground plant biomass of native Kansas tallgrass prairie 

(Owensby et al. 1999; 1989-1995) and Colorado Shortgrass steppe (Morgan 

et al. 2004a; 1997-2001), harvested during summer-time seasonal peak. These 

grasses were grown in similarly-designed Open Top Chambers maintained at 

present (ambient, approximately 370 parts per million CO2 in air; no crosshatches) and elevated (approximately 720 parts per million CO2 in air; crosshatches) atmospheric CO2 concentrations. Histograms from different years 

are color-coded (red for dry; yellow for normal; blue for wet) according to the 

amount of annual precipitation received during that particular year compared 

to long-term averages for the two sites (840 mm for the tallgrass prairie, and 

320 mm for shortgrass steppe). Where production increases due to elevated 

CO2 were observed, the percentage-increased production is given within a year 

above the histograms. The involvement of water in the CO2 responses is seen 

in two ways: the relative plant biomass responses occur more commonly and 

in greater magnitude in the shortgrass steppe than in the tallgrass prairie, and 

the relative responses in both systems are greater in dry than wet years.

of warming likely will vary within and among 

years, and among plant species. Because of 

severe cold-temperature restrictions on growth 

rate and duration, warmer plant temperatures 

alone should stimulate production in high- and 

mid-latitude, and high-altitude rangelands. 

Conversely, increasing plant temperature during 

summer months may reduce NPP.

Increasing daily minimum air temperature and 

mean soil temperature (2.5 cm depth) by 2oC 

increased aboveground NPP of tallgrass prairie 

in Oklahoma between 0-19 percent during the 

first three years of study, largely by increasing 

NPP of C4 grasses (Wan et al. 2005). Warming 

stimulated biomass production in spring and 

autumn, but aboveground biomass in summer 

declined as soil temperature increased. Positive effects of warming on production may be 

lessened by an accompanying increase in the 

rate of water loss. Warming reduced the annual 

mean of soil water content in tallgrass prairie 

during one year (Wan et al. 2005), but actually 

increased soil water content in California annual grassland by accelerating plant senescence 

(Zavaleta et al. 2003b).

2.2.3.1.2.3 Precipitation

Historic changes in climatic patterns have 

always been accompanied by changes in grassland vegetation because grasslands have both 

high production potential and a high degree of 

variability in precipitation (Knapp and Smith 

2001). In contrast, aboveground NPP (ANPP) 

variability in forest systems appears to be limited by invariant rainfall patterns, while production potential more strongly limits desert and 

arctic/alpine systems. Projected altered rainfall 

regimes are likely to elicit important changes in 

rangeland ecology, including NPP.

On most rangelands where total annual precipitation is sufficiently low that soil water limits 

productivity more than other soil resources, the 

timing of precipitation can play an important 

role in regulating NPP. Increased rainfall variability caused by altered rainfall timing (no 

change in rainfall amount) led to lower and 

more variable soil water content (between 0-30 

cm depth), an approximate 10 percent reduction 

in ANPP, which was species-specific, and increased root-to-shoot ratios in a native tallgrass 

prairie ecosystem in northeastern Kansas (Fay 

et al. 2003). In general, vegetation responses to 

rainfall timing (no change in amount) were at 

least equal to changes caused by rainfall quantity

(30 percent reduction, no change in timing). 

Reduced ANPP most likely resulted from direct 

effects of soil moisture deficits on root activity, 

plant water status, and photosynthesis.

The seasonality of precipitation is also an important factor determining NPP through its affects 

on locally adapted species, which can differ 

depending on the particular ecosystem. For example, herbaceous plants in the Great Basin are 

physiologically adapted to winter/early spring 

precipitation patterns, where reliable soil water 

recharge occurs prior to the growing season 
The U.S. Climate Change Science Program

52

Chapter 2

(Svejcar et al. 2003). Similarly, Northern Great 

Plains grasslands are dominated by cool-season 

plant species that complete most of their growth 

by late spring to early summer, and NPP primarily depends on sufficient soil moisture going into 

the growing season (Heitschmidt and Haferkamp 2003). Productivity of herbaceous species 

in both of these rangeland systems is highly dependent on early spring soil moisture, which can 

be significantly affected by winter precipitation. 

In contrast, oak savannas of the southwestern 

United States experience a strongly seasonal 

pattern of precipitation, with a primary peak in 

summer and lesser peak in winter (Weltzin and 

McPherson 2003). Here, herbaceous biomass is 

more sensitive to summer precipitation than to 

winter precipitation.

2.2.3.1.3 Environmental Controls on Species 

Composition

At regional scales, species composition of rangelands is determined mostly by climate and soils, 

with fire regime, grazing, and other land uses 

locally important. The primary climatic control 

on the distribution and abundance of plants is 

water balance (Stephenson 1990). On rangelands 

in particular, species composition is highly correlated with both the amount of water plants use 

and its availability in time and space.

Each of the global changes considered here – 

CO2 enrichment, altered precipitation regimes, 

and higher temperatures – may change species 

composition by altering water balance. Unless 

stomatal closure is compensated by atmospheric 

or other feedbacks, CO2 enrichment should affect water balance by slowing canopy-level ET 

(Polley et al. 2007) and the rate or extent of soil 

water depletion (Morgan et al. 2001; Nelson 

et al. 2004). The resultant higher soil water 

content has been hypothesized to favor deeprooted woody plants in future CO2-enriched 

atmospheres because of their greater access to 

stored soil water compared to relatively shallowrooted grasses (Polley 1997). A warmer climate 

will likely be characterized by more rapid 

evaporation and transpiration, and an increase 

in frequency of extreme events like heavy rains

and droughts. Changes in timing and intensity 

of rainfall may be especially important on arid 

rangelands where plant community dynamics are ‘event-driven’ and the seasonality of 

precipitation determines which plant growth 

strategies are successful. The timing of precipitation also affects the vertical distribution of soil 

water, which regulates relative abundances of 

plants that root at different depths (Ehleringer 

et al. 1991; Weltzin and McPherson 1997), and 

influences natural disturbance regimes, which 

feed back to regulate species composition. For 

example, grass-dominated rangelands in the 

eastern Great Plains were historically tree-free 

due to periodic fire. Fires occurred frequently

because the area is subject to summer droughts, 

which dessicated the grasses and provided abundant fuel for wildfires.

In addition to its indirect effect on water balance, 

the direct effect of temperature on plant physiology has long been acknowledged as an important 

determinant of plant species distribution. A good 

example of this is the distribution of cool-season, 

C3 grasses being primarily at northern latitudes 

and warm-season, C4 grasses at southern latitudes (Terri and Stowe 1976). Thus, the relative 

abundances of different plants types (C3 grasses, 

C4 grasses, and shrubs) in grasslands and shrublands of North America are determined in large 

part by soil water availability and temperatures 

(Paruelo and Lauenroth 1996).

Observational evidence that global changes are 

affecting rangelands and other ecosystems is 

accumulating. During the last century, juniper 

trees in the arid West grew more than expected 

from climatic conditions, implying that the 

historical increase in atmospheric CO2 concentration stimulated juniper growth (Knapp 

et al. 2001). The apparent growth response of 

juniper to CO2 was proportionally greater during 

dry than wet years, consistent with the notion 

that access to deep soil water, which tends to 

accumulate under elevated CO2 (Morgan et al. 

2004b), gives a growth advantage to deep-rooted 

woody vegetation (Polley 1997; Morgan et al. 

2007). Such observational reports in combination with manipulative experimentation (Morgan et al. 2004b, 2007) suggest that expansion 

of shrublands over the past couple hundred 

years has been driven in part by a combination 

of climate change and increased atmospheric 

CO2 concentrations (Polley 1997; Archer et 

al. 1995).

On rangelands in 

particular, species 

composition is highly 

correlated with both 

the amount of water 

plants use and its 

availability in time 

and space.
53

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

2.2.3.1.4 Nitrogen Cycle Feedbacks

Plant production on rangelands often is limited 

by nitrogen (N). Because most terrestrial N occurs in organic forms that are not readily available to plants, rangeland responses to global 

changes will depend partly on how quickly

N cycles between organic and inorganic N 

compounds. Plant material that falls to the soil 

surface, or is deposited belowground as the 

result of root exudation or death, is subject to 

decomposition by soil fauna and micro flora 

and enters the soil organic matter (SOM) pool. 

During decomposition of SOM, mineral and 

other plant-available forms of N are released. 

Several of the variables that regulate N-release 

from SOM may be affected by CO2 enrichment 

and climate change, and thus are likely to be 

important factors determining the long-term 

responses of rangelands.

For instance, while CO2 enrichment above 

present atmospheric levels is known to increase 

photosynthesis, particularly in C3 species, 

soil feedbacks involving nutrient cycling may 

constrain the potential CO2 fertilization response (Figure 2.8). The Progressive Nitrogen 

Limitation (PNL) hypothesis holds that CO2

enrichment is reducing plant-available N by 

increasing plant demand for N, and enhancing 

sequestration of N in long-lived plant biomass

and SOM pools (Luo et al. 2004). The greater 

plant demand for N is driven by CO2-enhanced 

plant growth. Accumulation of N in organic 

compounds at elevated CO2 may eventually 

reduce soil N availability and limit plant growth 

response to CO2 or other changes (Reich et al. 

2006a, 2006b; van Groenigen et al. 2006; Parton 

et al. 2007a). Alternatively, greater C input may 

stimulate N accumulation in soil/plant systems. 

A number of processes may be involved, including increased biological fixation of N, greater 

retention of atmospheric N deposition, reduced 

losses of N in gaseous or liquid forms, and more

complete exploration of soil by expanded root 

systems (Luo et al. 2006). Rangeland plants 

often compensate for temporary imbalances in 

C and N availability by maximizing the amount 

of C retained in the ecosystem per unit of N. 

Thus, N concentration of leaves or aboveground 

tissues declined on shortgrass steppe, tallgrass 

prairie, and mesic grassland at elevated CO2, 

and on tallgrass prairie with warming, but total 

N content of aboveground tissues increased with 

plant biomass in these ecosystems and on annual grasslands (Owensby et al. 1993; Hungate 

et al. 1997; King et al. 2004; Wan et al. 2005; 

Gill et al. 2006). The degree to which N may 

respond to rising atmospheric CO2 is presently 

unknown, but may vary among ecosystems (Luo 

et al. 2006), and hasimportant consequencesfor

forage quality and soil C storage, as both depend

strongly on the available soil N.

Warmer temperatures generally increase SOM 

decomposition, especially in cold regions (Reich et al. 2006b; Rustad et al. 2001), although 

warming also may limit microbial activity by 

drying soil or enhancing plant growth (Wan et 

al. 2005). Wan et al. (2005) found that warming 

stimulated N mineralization during the first year 

of treatment on Oklahoma tallgrass prairie, but 

in the second year, caused N immobilization 

by reducing plant N concentration, stimulating 

plant growth, and increasing allocation of carbon 

(C) compounds belowground (Wan et al. 2005). 

Warming can also affect decomposition processes by extending the growing season (Wan et 

Figure 2.8 Nutrient Cycling Feedbacks. While CO2 enrichment may lead to 

increased photosynthesis and enhanced plant growth, the long-term response 

will depend on nutrient cycling feedbacks. Litter from decaying plants and root 

exudates enter a large soil nutrient pool that is unavailable to plants until they 

are broken down and released by microbial activity. Soil microbes may also fix 

available nutrients into new microbial biomass, thereby temporarily immobilizing 

them. The balance between these and other nutrient release and immobilization 

processes determines available nutrients and ultimate plant response. Figure 

reprinted with permission from Science (Morgan 2002).
The U.S. Climate Change Science Program

54

Chapter 2

al. 2005). However, as water becomes limiting, 

decomposition becomes more dependant on soil 

water content and less on temperature (Epstein 

et al. 2002; Wan et al. 2005), with lower soil 

water content leading to reduced decomposition 

rates. A recent global model of litter decomposition (Parton et al. 2007b) indicates that litter 

N-concentration, along with temperature and 

water, are the dominant drivers behind N release and immobilization dynamics, although 

UV-stimulation of decomposition (Austin and 

Vivanco 2006) is especially important in controlling surface litter decomposition dynamics 

in arid systems like rangelands.

Nutrient cycling also is sensitive to changes 

in plant species composition; this may result 

because species differ in sensitivity to global 

changes. Soil microorganisms require organic

material with relatively fixed proportions of C 

and N. The ratio of C to N (C:N) in plant residues thus affects the rate at which N is released 

during decomposition in soil. Because C:N 

varies among plant species, shifts in species 

composition can strongly affect nutrient cycling 

(Allard et al. 2004; Dijkstra et al. 2006; Gill 

et al. 2006; King et al. 2004; Schaeffer et al. 

2007; Weatherly et al. 2003). CO2 enrichment 

may reduce decomposition by reducing the N 

concentration in leaf litter (Gill et al. 2006), for 

example, although litter quality may not be the

best predictor of tissue decomposition (Norby et 

al. 2001). Like CO2, climatic changes may alter 

litter quality by causing species change (Murphy

et al. 2002; Semmartin et al. 2004; Weatherly 

et al. 2003). Elevated atmospheric CO2 and/

or temperature may also alter the amounts and 

proportions of micro flora and fauna in the soil 

microfood web (e.g., Hungate et al. 2000; Sonnemann and Wolters 2005), and/or the activities 

of soil biota (Billings et al. 2004; Henry et al. 

2005; Kandeler et al. 2006). Although changes 

in microbial communities are bound to have 

important feedbacks on soil nutrient cycling and 

C storage, the full impact of global changes on 

microbes remains unclear (Niklaus et al. 2003; 

Ayers et al., in press).

Computer simulation models that incorporate 

decomposition dynamics and can evaluate incremental global changes agree that combined 

effects of warming and CO2 enrichment during 

the next 30 years will stimulate plant production, but disagree on the impact on soil C and N. 

The Daycent Model predicts a decrease in soil 

C stocks, whereas the Generic Decomposition 

And Yield Model (G’Day) predicts an increase 

in soil C (Pepper et al. 2005). Measurements of 

N isotopes from herbarium specimens collected 

over the past hundred years indicate that rising 

atmospheric CO2 has been accompanied by 

increased N fixation and soil N mineralization, 

decreased soil N losses, and a decline in shoot 

N concentration (Peñuelas and Estiarte 1997). 

Collectively, these results indicate that soil N 

may constrain the responses of some terrestrial 

ecosystems to CO2.

2.2.4 Temperature Response of

Animals

2.2.4.1 Thermal Stress

The optimal zone (thermoneutral zone) for 

livestock production is a range of temperatures 

and other environmental conditions for which 

the animal does not need to significantly alter 

behavior or physiological functions to maintain 

a relatively constant core body temperature. As 

environmental conditions result in core body 

temperature approaching and/or moving outside 

normal diurnal boundaries, the animal must 

begin to conserve or dissipate heat to maintain 

homeostasis. This is accomplished through 

shifts in short-term and long-term behavioral, 

physiological, and metabolic thermoregulatory 

processes (Mader et al. 1997b; Davis et al. 

2003). The onset of a thermal challenge often 

results in declines in physical activity and an 

associated decline in eating and grazing activity 

(for ruminants and other herbivores). Hormonal 

changes, triggered by environmental stress, 

result in shifts in cardiac output, blood flow to 

extremities, and passage rate of digesta. Adverse 

environmental stress can elicit a panting or shivering response, which increases maintenance 

requirements of the animal and contributes to

decreases in productivity. Depending on the 

domestic livestock species, longer term adaptive 

responses include hair coat gain or loss through 

growth and shedding processes, respectively. In 

addition, heat stress is directly related to respiration and sweating rate in most domestic animals 

(Gaughan et al. 1999, 2000, and 2005).

Adverse 

environmental 

stress can elicit 

a panting or 

shivering response, 

which increases 

maintenance 

requirements 

of the animal 

and contributes 

to decreases in 

productivity. 
55

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Production losses in domestic animals are largely attributed to increases in aintenance requirement associated with sustaining a constant body 

temperature, and altered feed intake (Mader et 

al. 2002; Davis et al. 2003; Mader and Davis 

2004). As a survival mechanism, voluntary 

feed intake increases (after a one- to two-day 

decline) under cold stress, and decreases almost 

immediately under heat stress (NRC 1987). 

Depending on the intensity and duration of the 

environmental stress, voluntary feed intake can 

average as much as 30 percent above normal 

under cold conditions, to as much as 50 percent 

below normal in hot conditions.

Domestic livestock are remarkable in their 

adaptive ability. They can mobilize coping 

mechanisms when challenged by environmental 

stressors. However, not all coping capabilities 

are mobilized at the same time. As a general 

model for mammals of all species, respiration 

rate serves as an early warning of increasing 

thermal stress, and increases markedly above 

a threshold as animals try to maintain homeothermy by dissipating excess heat. At a higher 

threshold, body temperature begins to increase 

as a result of the animal’sinability to adequately

dissipate the excess heat load by increased 

respiratory vaporization (Brown-Brandl et al. 

2003; Davis et al. 2003; Mader and Kreikemeier 

2006). There is a concomitant decrease in voluntary feed intake as body temperature increases, 

which ultimately results in reduced performance 

(i.e., production, reproduction), health and wellbeing if adverse conditions persist (Hahn et al. 

1992; Mader 2003).

Thresholds are species dependent, and affected 

by many factors, as noted in Figure 2.9. For 

shaded Bos taurus feeder cattle, Hahn (1999) 

reported respiration rate as related to air temperature typically shows increases above a 

threshold of about 21°C, with the threshold for 

increasing body temperature and decreasing 

voluntary feed intake being about 25°C. Recent 

studies (Brown-Brandl et al. 2006) clearly show 

the influences of animal condition, genotype, 

respiratory pneumonia, and temperament on 

respiration rate of Bos taurus heifers.

Even though voluntary feed intake reduction 

usually occurs on the first day of hot conditions, 

Figure 2.9. Response model for farm animals with thermal environmental 

challenges (Hahn 1999).

the animals’ internal metabolic heat load generated by digesting existing rumen contents adds 

to the increased external, environmental heat 

load. Nighttime recovery also has been shown to 

be an essential element of survival when severe 

heat challenges occur (Hahn and Mader 1997; 

Amundson et al. 2006). After about three days, 

the animal enters the chronic response stage, 

with mean body temperature declining slightly 

and voluntary feed intake reduced in line with 

heat dissipation capabilities. Diurnal body temperature amplitude and phase remain altered. 

These typical thermoregulatory responses, 

when left unchecked during a severe heat wave 

with excessive heat loads, can lead to impaired 

performance or death (Hahn and Mader 1997; 

Mader 2003).

2.2.4.1.1 Methods to Identify 

Environmentally Stressed Animals

Temperature provides a measure of the sensible 

heat content of air, and represents a major portion 

of the driving force for heat exchange between 

the environment and an animal. However, latent 

heat content of the air, as represented by some 

measure of the insensible heat content (e.g., 

dewpoint temperature), thermal radiation (shortand long-wave), and airflow, also impacts the 

total heat exchange. Because of the limitations 

of air temperature alone as a measure of the thermal environment, there have been many efforts 

to combine the effects of two or more thermal 
The U.S. Climate Change Science Program

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Chapter 2

measures representing the influence of sensible 

and latent heat exchanges between the organism 

and its environment. It is important to recognize 

that all such efforts produce index values rather 

than a true temperature (even when expressed 

on a temperature scale). As such, an index value 

represents the effect produced by the heat exchange process, which can alter the biological 

response that might be associated with changes 

in temperature alone. In the case of humans, 

the useful effect is the sensation of comfort; 

for animals, the useful effect is the impact on 

performance, health, and well-being.

Contrary to the focus of human-oriented thermal indices on comfort, the primary emphasis 

for domestic animals has been on indices to 

support rational environmental management 

decisions related to performance, health, and 

well-being. Hahn and Mader (1997), Hahn et 

al. (1999), and Hahn et al. (2001) have used 

retrospective climatological analyses to evaluate 

the characteristics of prior heat waves causing 

extensive livestock losses. Although limited 

by lack of inclusion of wind speed and thermal 

radiation effects, the Temperature-Humidity 

Index (THI) has been a particularly useful tool 

for profiling and classifying heat wave events 

(Hahn and Mader 1997; Hahn et al. 1999). In 

connection with extreme conditions associated 

with heat waves, the THI has recently been used 

to evaluate spatial and temporal aspects of their 

development (Hubbard et al. 1999; Hahn and 

Mader 1997). For cattle in feedlots, a THI-based 

classification scheme has also been developed to 

assess the potential impact of heat waves (Hahn 

et al. 1999) (Table 2.11). The classifications are 

based on a retrospective analysis of heat waves 

that have resulted in extensive feedlot cattle 

deaths, using a THI-hours approach to assess 

the magnitude (intensity x duration) of the heat 

wave events that put the animals at risk. When 

calculated hourly from records of temperature 

and humidity, this classification scheme can 

be used to compute cumulative daily THI-hrs 

at or above the Livestock Weather Safety Index (LWSI) thresholds for the “Danger” and 

“Emergency” categories. The THI-hrs provide 

a measure of the magnitude of daytime heat 

load (intensity and duration), while the number 

of hours below THI thresholds of 74 and 72 

indicate the opportunity for nighttime recovery 

from daytime heat.

As applied to Bos taurus feedlot cattle during the 

1995 Nebraska-Iowa heat wave event, evaluation of records for several weather stations in the 

region using the THI-hrs approach reinforced the 

LWSI thresholds for the Danger and Emergency 

categories of risk and possible death (Hahn and 

Mader 1997). Based on that event, analysis indicated that over a successive, three-day span, 

15 or more THI-hrs per day above a THI base 

level of 84 could be lethal for vulnerable animals 

Table 2.11 Heat wave categories for Bos taurus feedlot cattle exposed to single heat wave events (Hahn et al. 

1999). 

Category

Descriptive Characteristics

Duration THI*-hrs ≥79 THI-hrs ≥84*

Nighttime recovery

(hrs # 72 THI*)

1. Slight Limited: 3-4 days 10-25/day None Good: 5-10 hr/night

2. Mild Limited: 3-4 days 18-40/day #5/day Some: 3-8 hr/night

3. Moderate More persistent

(4-6 days usual) 25-50/day #6/day Reduced: 1-6 hr/night

4. Strong Increased persistence

(5-7 days) 33-65/day #6/day Limited: 0-4 hr/night

5. Severe Very persistent

(usually 6-8 days) 40-80/day 3-15/day on 3 or more successive days Very limited: 0-2 hr per night

6. Extreme Very persistent

(usually 6-10+ days) 50-100/day 15-30/day on 3 ormore successive days Nil: #1 for 3 or more successive days

*Temperature Humidity Index (THI). Daily THI-hrs are the summation of the differences between the THI and the base level 

at each hr of the day. For example, if the THI value at 1300 is 86.5 and the base level selected is 84, THI-hr = 2.5. The accumulation for the day is obtained by summing all THI-hr ≥ 84, and can exceed 24.
57

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

(especially those that were ill, recently placed in 

the feedlot, or nearing market weight). The extreme daytime heat in 1995 was exacerbated by 

limited nighttime relief (only a few hrs with THI 

≤ 74), high solar radiation loads(clear to mostly

clear skies), and low to moderate wind speeds 

in the area of highest risk. During this same period, for cattle in other locations enduring 20 or 

more daily THI-hrs in the Emergency category 

(THI ≥ 84) over one or two days, the heat load

was apparently dissipated with minimal or no 

mortality, although these environmental conditions can markedly depress voluntary feed intake 

(Hahn 1999; NRC 1981) with resultant reduced 

performance.

Similar analysis of a single heat wave in August 

1992 further confirmed that 15 or more THI-hrs 

above a base level of 84 can cause deaths of vulnerable animals (Hahn et al. 1999). A contributing factor to losses during that event was lack of 

acclimation to hot weather, as the summer had 

been relatively cool. In the region under study, 

only four years between 1887-1998 had fewer 

days during the summer when air temperature 

was ≥ 32.2°C (High Plains Regional Climate

Center 2000).

There are limitations to the THI caused by 

airflow and changing solar radiation loads. 

Modifications to the THI have been proposed to 

overcome shortcomings related to airflow and 

radiation heat loads. Based on recent research, 

Mader et al. (2006) and Eigenberg et al. (2005) 

have proposed corrections to the THI for use 

with feedlot cattle, based on measures of windspeed and solar radiation. While the proposed 

adjustment-factor differences are substantial, 

there were marked differences in the types and 

number of animals used in the two studies. Nevertheless, the approach appears to merit further 

research to establish acceptable THI corrections, 

perhaps for a variety of animal parameters.

By using body temperatures, a similar approach 

was developed to derive an Apparent Equivalent

Temperature (AET) from air temperature and 

vapor pressure to develop “thermal comfort 

zones” for transport of broiler chickens (Mitchell et al. 2001). Experimental studies to link the 

AET with increased body temperature during 

exposure to hot conditions indicated potential 

for improved transport practices.

Gaughan et al. (2002) developed a Heat Load 

Index (HLI) as a guide to management of 

unshaded Bos taurus feedlot cattle during hot 

weather (>28°C). The HLI was developed following observation of behavioral responses 

(respiration rate and panting score) and changes 

in dry-matter intake during prevailing thermal 

conditions. The HLI is based on humidity, windspeed, and predicted black globe temperature.

As a result of its demonstrated broad success, 

the THI is currently the most widely accepted 

thermal index used for guidance of strategic and 

tactical decisions in animal management during 

moderate to hot conditions. Biologic response 

functions, when combined with likelihood of 

occurrence of the THI for specific locations, 

provide the basis for economic evaluation to 

make cost-benefit comparisons for rational 

strategic decisions among alternatives (Hahn 

1981). Developing a climatology of summer 

weather extremes (in particular, heat waves) 

for specific locations also provides the livestock 

manager with information about how often 

those extremes (with possible associated death 

losses) might occur (Hahn et al. 2001). The THI 

has also served well for making tactical decisions about when to apply available practices 

and techniques (e.g., sprinkling) during either

normal weather variability or weather extremes, 

such as heat waves. Other approaches, such as 

the AET proposed by Mitchell et al. (2001) for 

use in poultry transport, also may be appropriate. An enthalpy-based alternative thermal index 

has been suggested by Moura et al. (1997) for 

swine and poultry.

Panting score is one observation method used 

to monitor heat stress in cattle (Table 2.12). As 

the temperature increases, cattle pant more to increase evaporative cooling. Respiration dynamics change as ambient conditions change, and 

surroundings surfaces warm. This is a relatively 

easy method for assessing genotype differences 

and determining breed acclimatization rates to 

higher temperatures. In addition, shivering score 

or indices also have potential for use as thermal 

indicators of cold stress. However, recent data 

were not found regarding cold stress indicators 

for domestic livestock.
The U.S. Climate Change Science Program

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Chapter 2

2.2.5 Episodes of Extreme Events

2.2.5.1 Elevated Temperature or Rain 

fall Deficit

Episodic increases in temperature would have 

greatest effect when occurring just prior to, or 

during, critical crop pollination phases. Crop 

sensitivity and ability to compensate during 

later, improved weather will depend on the 

synchrony of anthesis in each crop; for example, maize has a highly compressed phase of 

anthesis, while spikelets on rice and sorghum 

may achieve anthesis over a period of a week 

or more. Soybean, peanut, and cotton will have 

several weeks over which to spread the success 

of reproductive structures. For peanut, the sensitivity to elevated temperature for a given flower 

extends from six days prior to opening (pollen 

cell division and formation) up through the 

day of anthesis (Prasad et al. 2001). Therefore, 

several days of elevated temperature may affect 

fertility of many flowers, whether still in their 

formative 6-day phase or just achieving anthesis 

today. In addition, the first six hours of the day 

were more critical during pollen dehiscence, 

pollen tube growth, and fertilization.

For rice, the reproductive processes that occur 

within one to three hours after anthesis (dehiscence of the anther, shedding of pollen, germination of pollen grains on stigma, and elongation 

of pollen tubes) are disrupted by daytime air 

temperatures above 33oC (Satake and Yoshida 

1978). Since anthesis occurs between about 9 

a.m. and 11 a.m. in rice (Prasad et al. 2006b), 

damage from temperatures exceeding 33oC may 

already be common, and may become more 

prevalent in the future. Pollination processes in 

other cereals, maize, and sorghum may have a 

similar sensitivity to elevated daytime temperature as rice. Rice and sorghum have the same 

sensitivity of grain yield, seed harvest index, 

pollen viability, and success in grain formation 

in which pollen viability and percent fertility is 

first reduced at instantaneous hourly air temperature above 33oC, and reaches zero at 40oC 

(Kim et al. 1996; Prasad et al. 2006a, 2006b). 

Diurnal max/min, day/night temperatures of 

40/30oC (35oC mean) can cause zero yield for 

those two species, and the same response would 

likely apply to maize.

2.2.5.2 Intense Rainfall Events

Historical data for many parts of the United 

States indicate an increase in the frequency

of high-precipitation events (e.g., >5 cm in 48 

hours), and this trend is projected to continue 

for many regions. One economic consequence

of excessive rainfall is delayed spring planting, 

which jeopardizes profits for farmers paid a 

premium for early season production of high 

value horticultural crops such as melon, sweet 

corn, and tomatoes. Field flooding during the 

growing season causes crop losses associated 

with anoxia, increases susceptibility to root 

diseases, increases soil compaction (due to use 

of heavy farm equipment on wet soils), and

causes more runoff and leaching of nutrients 

and agricultural chemicals into groundwater 

and surface water. More rainfall concentrated 

into high precipitation events will increase the 

likelihood of water deficiencies at other times 

because of the changes in rainfall frequency

(Hatfield and Prueger 2004). Heavy rainfall 

is often accompanied by wind gusts in storm 

events, which increases the potential for lodging 

of crops. Wetter conditions at harvest time could 

increase the potential for decreasing quality of

many crops.

Score Description

0 Normal respiration

1 Elevated respiration

2 Moderate panting and/or presence of drool or a small amount of saliva

3 Heavy open-mouthed panting, saliva usually present

4 Severe open-mouthed panting accompanied by protruding tongue and excess salivation; 

usually with neck extended forward

Table 2.12 Panting scores assigned to steers (Mader et al. 2006).
59

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

2.3 Possible Future 

Changes and Impacts

2.3.1 Projections Based on

Increment of Temperature and 

CO2 for Crops

Using the representative grain crops – maize, 

soybean, etc. – some expected effects resulting 

from the projected rise in CO2 of 380 to 440 ppm 

along with a 1.2oC rise in temperature over the 

next 30 years are explored.

The responsiveness of grain yield to temperature 

is dependent on current mean temperatures during the reproductive phase in different regions 

(crops like soybean and maize are dominant in 

both the Midwest and southern regions, while 

others, like cotton, sorghum, and peanut, are 

only grown in southern regions). Grain yield 

response to CO2 increase of 380 to 440 ppm 

was 1.0 percent for C4, and 6.1 to 7.4 percent 

for C3 species, except for cotton, which had 9.2 

percent response.

For maize, under water sufficiency conditions 

in the Midwest, the net yield response is -3.0 

percent, assuming additivity of the -4.0 percent 

from 1.2oC rise, and +1.0 percent from CO2 of 

380 to 440 ppm (Table 2.7). The response of 

maize in the South is possibly more negative. 

For soybean under water sufficiency in the 

Midwest, net yield response is +9.9 percent, 

assuming additivity of the +2.5 percent from 

1.2oC rise above current 22.5oC mean, and +7.4 

percent from CO2 increase.

For soybean under water sufficiency in the 

South, the temperature effect will be detrimental, -3.5 percent, with 1.2oC temperature increment above 26.7oC, with the same CO2 effect, 

giving a net yield response of +3.9 percent. For 

wheat (with no change in water availability), the 

net yield response would be +0.1 percent coming from -6.7 percent with 1.2oC rise, and +6.8 

percent increase from CO2 increase. For rice 

in the South, net yield response is -5.6 percent, 

assuming additivity of the -12.0 percent from 

1.2oC rise and +6.4 percent from CO2 increase. 

For peanut in the South, the net yield response 

is +1.3 percent, assuming additivity of the -5.4 

percent from 1.2oC rise and +6.7 percent from 

CO2 increase. For cotton in the South, the net 

yield response is +3.5 percent, assuming additivity of the -5.7 percent from 1.2oC rise and 

+9.2 percent from CO2 increase. The sorghum 

response is less certain, although yield reduction 

caused by shortening filling period is dominant, 

giving a net yield decrease of 8.4 percent in the 

South. Dry bean yield response in all regions is 

less certain, with net effect of -2.5 percent, coming from -8.6 percent response to 1.2oC rise and 

+6.1 percent from CO2 increase. The confidence 

in CO2 responses is likely to very likely, while 

the confidence in temperature responses is generally likely, except for less knowledge concerning maize and cotton sensitivity to temperature 

when these responses are possible.

Projections of crop yield under water deficit 

should start with the responses to temperature 

and CO2 for the water-sufficient cases. However, yield will likely be slightly increased to 

the same extent (percentage) that increased 

CO2 causes reduction in ET but decreased to 

the extent that rainfall is decreased (but that 

requires climate scenarios and simulations not

presented in Table 2.7). Model simulations 

with CROPGRO-Soybean with energy balance 

option and stomatal feedback from CO2 enrichment (350 to 700 ppm, without temperature 

increase) resulted in a 44 percent yield increase 

for water-stressed crops compared to fullyirrigated crops (32 percent). The yield increment was nearly proportional to the decrease in 

simulated transpiration (11-16 percent). Based 

on this assumption, the 380 to 440 ppm CO2

increment would likely further increase yield 

of C3 crops (soybean, rice, wheat, and cotton) 

by an additional 1.4 to 2.1 percent (incremental 

reduction in ET from CO2 in Table 2.7). However, the projected 1.2oC would increase ET 

by 1.8 percent, thereby partially negating this 

water-savings effect of CO2.

2.3.2 Projections for Weeds

Many weeds respond more positively to increasing CO2 than most cash crops, particularly C3

“invasive” weeds that reproduce by vegetative 

means (roots, stolons, etc.) (Ziska and George 

2004; Ziska 2003). Recent research also suggests that glyphosate, the most widely used herbicide in the United States, loses its efficacy on 

weeds grown at CO2 levels that likely will occur 

in the coming decades (Ziska et al. 1999). While 

many weed species have the C4 photosynthetic 

pathway, and therefore show a smaller response 
The U.S. Climate Change Science Program

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Chapter 2

to atmospheric CO2 relative to C3 crops, in most 

agronomic situations crops are in competition 

with a mix of both C3 and C4 weeds. In addition, 

the worst weeds for a given crop are often similar in growth habit or photosynthetic pathway. 

To date, for all weed/crop competition studies 

where the photosynthetic pathway is the same, 

weed growth is favored as CO2 increases (Ziska 

and Runion 2006).

The habitable zone of many weed species is 

largely determined by temperature, and weed 

scientists have long recognized the potential for 

northward expansion of weed species’ ranges 

as the climate changes (Patterson et al. 1999). 

More than 15 years ago, Sasek and Strain (1990) 

utilized climate model projections of the -20oC 

minimum winter temperature zone to forecast 

the northward expansion of kudzu (Pueraria 

lobata, var. montana), an aggressive invasive 

weed that currently infests more than one million hectares in the southeastern U.S. While 

temperature is not the only factor that could 

constrain spread of kudzu and other invasive 

weeds, a more comprehensive assessment of 

potential weed species migration based on the 

latest climate projections for the United States 

seems warranted.

2.3.3 Projections for Insects and 

 Pathogens

Plants do not grow in isolation in agroecosystems. Beneficial and harmful insects, microbes, 

and other organisms in the environment will also 

be responding to changes in CO2 and climate. 

Studies conducted in Western Europe and other 

regions have already documented changes in 

spring arrival and/or geographic range of many 

insect and animal species due to climate change 

(Montaigne 2004; Goho 2004; Walther et al. 

2002). Temperature is the single most important 

factor affecting insect ecology, epidemiology, 

and distribution, while plant pathogens will be 

highly responsive to humidity and rainfall, as 

well as temperature (Coakley et al. 1999).

There is currently a clear trend for increased insecticide use in warmer, more southern regions 

of the United States, compared to cooler, higher 

latitude regions. For example, the frequency of

pesticide sprays for control of lepidopteran insect pests in sweet corn currently ranges from 15 

to 32 applications per year in Florida (Aerts et al. 

1999), to four to eight applications in Delaware 

(Whitney et al. 2000), and zero to five applications per year in New York (Stivers 1999). 

Warmer winters will likely increase populations 

of insect species that are currently marginally 

over-wintering in high latitude regions, such as 

flea beetles (Chaetocnema pulicaria), which act 

as a vector for bacterial Stewart’s Wilt (Erwinia 

sterwartii), an economically important corn 

pathogen (Harrington et al. 2001).

An overall increase in humidity and frequency

of heavy rainfall events projected for many parts 

of the United States will tend to favor some 

leaf and root pathogens (Coakley et al. 1999). 

However, an increase in short- to medium-term 

drought will tend to decrease the duration of leaf 

wetness and reduce some forms of pathogen 

attack on leaves.

The increasing atmospheric concentration of 

CO2 alone may affect plant-insect interactions. 

The frequently observed higher carbon-tonitrogen ratio of leaves of plants grown at high 

CO2 (Wolfe 1994) can require increased insect

feeding to meet nitrogen (protein) requirements

(Coviella and Trumble 1999). However, slowed 

insect development on high CO2-grown plants 

can lengthen the insect life stages vulnerable 

to attack by parasitoids (Coviella and Trumble 

1999). In a recent FACE study, Hamilton et al. 

(2005) found that early season soybeans grown 

at elevated CO2 had 57 percent more damage 

from insects, presumably due in this case to 

measured increases in simple sugars in leaves 

of high CO2-grown plants.

2.3.4 Projections for Rangelands

2.3.4.1 Net Primary Production and 

 Plant Species Changes

By stimulating both photosynthesis and water 

use efficiency, rising CO2 has likely enhanced 

plant productivity on most rangelands over the 

past 150 years, and will likely continue to do so 

over the next 30 years. The magnitude of this 

response will depend on how CO2 enrichment 

affects the composition of plant communities 

and on whether nutrient limitations to plant 

growth develop as the result of increased carbon 

input to rangelands. Increasing temperature will 

likely have both positive and negative effects on 

plant productivity, depending on the prevailing 

To date, for 

all weed/crop 

competition 

studies 

where the 

photosynthetic 

pathway is the 

same, weed 

growth is 

favored as CO2

increases.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

climate and the extent to which warmer temperature leads to desiccation. Like CO2 enrichment, 

warming will induce species shifts because of 

differing species sensitivities and adaptabilities 

to temperatures. Modeling exercises suggest 

generally positive NPP responses of Great 

Plains native grasslands to increases in CO2 and 

temperature projected for the next 30 years (Pepper et al. 2005; Parton et al. 2007a), a response 

which is supported by experimental results 

from shortgrass steppe (Morgan et al. 2004a). 

An important exception to these findings is 

California annual grasslands, where production 

appears only minimally responsive to CO2 or 

temperature (Dukes et al. 2005). Alterations in 

precipitation patterns will interact with rising 

CO2 and temperature, although uncertainties 

about the nature of precipitation shifts, especially at regional levels, and the lack of multiple 

global change experiments that incorporate CO2, 

temperature and precipitation severely limit our 

ability to predict consequences for rangelands.

However, if annual precipitation changes little 

or declines in the southwestern United States 

as currently predicted (Christensen et al. 2007), 

plant production in rangelands of that region 

may respond little to combined warming and 

rising CO2, and may even decline due to increased drought.

Plants with the C3 photosynthetic pathway, forbs 

and possibly legumes will be favored by rising 

CO2, although rising temperature and changes 

in precipitation patterns may affect these functional group responses to CO2 (Morgan 2005; 

Polley 1997). In general, plants that are less 

tolerant of water stress than current dominants 

may also be favored in future CO2-enriched 

atmospheres where CO2 significantly enhances 

plant water use efficiency and seasonal available soil water (Polley et al. 2000). Deep-rooted 

forbs and shrubs may be particularly favored 

because of their strong carbon-allocation and 

nitrogen-use strategies (Polley et al. 2000; 

Bond and Midgley 2000; Morgan et al. 2007), 

including the ability of their roots to access deep 

soil water, which is predicted to be enhanced 

in future CO2-enriched environments. Shifts 

in precipitation patterns toward wetter winters 

and drier summers, which are predicted to favor 

woody shrubs over herbaceous vegetation in the 

desert southwest (Neilson 1986), may reinforce 

some of the predicted CO2-induced changes in 

plant community dynamics. In grasslands of 

the Northern Great Plains, enhanced winter precipitation may benefit the dominant cool-season, 

C3 grass species that rely on early-season soil 

moisture to complete most of their growth by 

late spring to early summer (Heitschmidt and 

Haferkamp 2003). Greater winter precipitation, in addition to rising CO2, may also benefit 

woody plants that are invading many grasslands 

of the central and northern Great Plains (Briggs 

et al. 2005; Samson and Knopf 1994). However, 

by itself, warmer temperature will tend to favor 

C4 species (Epstein et al. 2002), which may 

cancel out the CO2-advantage of C3 plants in 

some rangelands.

There is already some evidence that climate 

change-induced species changes are underway 

in rangelands. The worldwide encroachment 

of woody plants into grasslands remains one 

of the best examples of the combined effects 

of climate change and management in driving 

a species change that has had a tremendous 

negative impact on the range livestock industry. 

In the southwestern arid and semi-arid grasslands of the United States, mesquite (Prosopis 

glandulosa) and creosote (Larrea tridentate) 

bushes have replaced most of the former warm 

season, perennial grasses (Figure 2.10), whereas 

in more mesic grasslands of the Central Great 

Plains, trees and large shrubs are supplanting C3

grasslands (Figure 2.11). While both of these 

changes are due to complex combinations of 

management (grazing and fire) and a host of 

environmental factors (Briggs et al. 2005; Peters et al 2006), evidence is accumulating that 

rising CO2 and climate change are very likely 

important factors influencing these transitions 

(Briggs et al. 2005; Knapp et al. 2001; Polley et 

al. 2002; Morgan et al. 2007; Peters et al. 2006; 

Polley 1997). In contrast, the observed loss of 

woody species and spread of the annual grass 

Bromus tectorum (cheatgrass) throughout the 

Intermountain region of western North America 

also appears driven at least in part by the species 

sensitivity to rising atmospheric CO2 (Smith 

et al. 2000; Ziska et al. 2005), and has altered 

the frequency and timing of wildfires, reducing

establishment of perennial herbaceous species 

by pre-empting soil water early in the growing 

season (Young 1991).
The U.S. Climate Change Science Program

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Chapter 2

2.3.4.2 Local and Short-Term Changes

Our ability to predict vegetation changes at local 

scales and over shorter time periods is more limited because at these scales the response of vegetation to global changes depends on a variety of 

local processes, including soils and disturbance 

regimes, and how quickly various species can

disperse seeds across sometimes fragmented 

landscapes. Nevertheless, patterns of vegetation 

response are beginning to emerge.

•	 Directional shifts in the composition of vegetation occur most consistently when global 

change treatments alter water availability 

(Polley et al. 2000; Morgan et al. 2004b).

•	 Effects of CO2 enrichment on species composition and the rate of species change will 

very likely be greatest in disturbed or earlysuccessional communities where nutrient 

and light availability are high and species 

change is influenced largely by growthrelated parameters (e.g., Polley et al. 2003).

•	 Weedy and invasive plant species likely will

be favored by CO2 enrichment (Smith et al. 

2000; Morgan et al. 2007) and perhaps by 

other global changes because these species 

possess traits (rapid growth rate, prolific 

seed production) that permit a large growth 

response to CO2.

•	 CO2 enrichment will likely accelerate 

the rate of successional change in species 

composition following overgrazing or other 

severe disturbances (Polley et al. 2003).

•	 Plants do not respond as predictably to

temperature or CO2 as to changes in water, 

N, and other soil resources (Chapin et al. 

1995). Progress in predicting the response 

of vegetation to temperature and CO2 thus 

may require a better understanding of

indirect effects of global change factors on 

soil resources. At larger scales, effects of 

atmospheric and climatic change on fire 

frequency and intensity and on soil water and

N availability will likely influence botanical 

Figure 2.10 Today, in most areas of the Chihuahan desert, mesquite bushes have largely replaced perennial, 

warm-season grasses that dominated this ecosystem two centuries ago (photograph courtesy of Jornada 

Experimental Range photo gallery).

Figure 2.11 Gleditsia triacanthos tree islands in Kansas tallgrass prairie

(photograph courtesy of Alan K. Knapp).
63

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

composition to a much greater extent than 

global change effects on production. (See 

Chapter 3, Arid Lands Section for a more 

complete discussion on the interactions and 

implications of fire ecology, invasive weeds, 

and global change for rangelands.)

•	 Rangeland vegetation will very likely be

influenced more by management practices 

(land use) than by atmospheric and climatic 

change. Global change effects will be superimposed on and modify those resulting from 

land use patterns in ways that are as of yet 

uncertain.

2.3.4.3 Forage Quality

2.3.4.3.1 Plant-animal Interface

Animal production on rangelands, as in other 

grazing systems, depends on the quality as well

asthe quantity of forage. Key quality parameters

for rangeland forage include fiber content and 

concentrations of crude protein, non-structural 

carbohydrates, minerals, and secondary toxic 

compounds. Ruminants require forage with at

least 7 percent crude protein (as a percentage of 

dietary dry matter) for maintenance, 10-14 percent protein for growth, and 15 percent protein 

for lactation. Optimal rumen fermentation also 

requires a balance between ruminally-available

protein and energy. The rate at which digesta 

pass through the rumen decreases with increasing fiber content, which depends on the fiber 

content of forage. High fiber content slows 

passage and reduces animal intake.

Change

Examples of positive effects 

on forage quality Examples of negative effects on forage quality

Life-form distributions Decrease in proportion of woody 

shrubs and increase in grasses in 

areas with increased fire frequency.

Increase in the proportion of woody species because of 

elevated CO2, increases in rainfall event sizes and longer 

intervals between rainfall events.

Species or functional group 

distributions

Possible increase in C3 grasses 

relative to C4 grasses at elevated 

CO2.

Increase in the proportion of C4 grasses relative to C3

grasses at higher temperatures. Increase in abundance 

of perennial forb species or perennial grasses of low 

digestibility at elevated CO2. Increase in poisonous or 

weedy plants.

Plant biochemical properties Increase in non-structural 

carbohydrates at elevated CO2. 

Increase in crude protein content of 

forage with reduced rainfall.

Decrease in crude protein content and digestibility of 

forage at elevated CO2 or higher temperatures. No 

change or decrease in crude protein in regions with more 

summer rainfall.

Table 2.13 Potential changes in forage quality arising from atmospheric and climatic change.

2.3.4.3.2 Climate Change Effects on Forage 

Quality

Based on expected vegetation changes and 

known environmental effects on forage protein, 

carbohydrate, and fiber contents, both positive 

and negative changes in forage quality are possible as a result of atmospheric and climatic 

change (Table 2.13). Non-structural carbohydrates can increase under elevated CO2 (Read et 

al. 1987), thereby potentially enhancing forage 

quality. However, plant N and crude protein

concentrations often decline in CO2-enriched 

atmospheres, especially when plant production 

is enhanced by CO2. This reduction in crude 

protein reduces forage quality and counters the

positive effects of CO2 enrichment on plant 

production and carbohydrates (Cotrufo et al. 

1998; Milchunas et al. 2005). Limited evidence 

suggests that the decline is greater when soil nitrogen availability is low than high (Bowler and 

Press 1996; Wilsey 1996), implying that rising 

CO2 possibly reduces the digestibility of forages 

that are already of poor quality for ruminants.

Experimental warming also reduces tissue N 

concentrations (Wan et al. 2005), but reduced 

precipitation typically has the opposite effect. 

Such reductionsin forage quality could possibly

have pronounced negative effects on animal 

growth, reproduction, and mortality (Milchunas 

et al. 2005; Owensby et al. 1996), and could 

render livestock production unsustainable unless animal diets are supplemented with N (e.g., 

urea, soybean meal). On shortgrass steppe, for 

example, CO2 enrichment reduced the crude 

protein concentration of autumn forage below 
The U.S. Climate Change Science Program

64

Chapter 2

critical maintenance levels for livestock in three 

out of four years and reduced the digestibility 

of forage by 14 percent in mid-season and by 

10 percent in autumn (Milchunas et al. 2005). 

Significantly, the grass most favored by CO2

enrichment also had the lowest crude protein 

concentration. Plant tissues that re-grow following defoliation generally are of higher quality

than older tissue, so defoliation could ameliorate 

negative effects of CO2 on forage quality. This

however did not occur on shortgrass steppe 

(Milchunas et al. 2005). Changes in life forms, 

species, or functional groups resulting from 

differential responses to global changes will 

very likely vary among rangelands depending 

on the present climate and species composition, 

with mixed consequencesfor domestic livestock

(Table 2.13).

2.3.5 Climatic Influences on

Livestock

Climate changes, as suggested by some GCMs, 

could impact the economic viability of livestock 

production systems worldwide. Surrounding 

environmental conditions directly affect mechanisms and rates of heat gain or loss by all animals (NRC 1981). Lack of prior conditioning to 

weather events most often results in catastrophic 

losses in the domestic livestock industry. In the 

central U.S. in 1992, 1995, 1997, 1999, 2005, 

and 2006, some feedlots (intensive cattle feeding operations) lost in excess of 100 head each 

during severe heat episodes. The heat waves of 

1995 and 1999 were particularly severe with 

documented cattle losses in individual states 

approaching 5,000 head each year (Hahn and 

Mader 1997; Hahn et al. 2001). The intensity 

and/or duration of the 2005 and 2006 heat waves 

were just as severe as the 1995 and 1999 heat 

waves, although the extent of losses could not 

be adequately documented.

The winter of 1996-97 also caused hardship for 

cattle producers because of greater than normal 

snowfall and wind velocity, with some feedlots 

reporting losses in excess of 1,000 head. During 

that winter, up to 50 percent of the newborn 

calves were lost, and more than 100,000 head 

of cattle died in the Northern Plains of the 

United States.

Additional snowstorm losses were incurred with 

the collapse of and/or loss of power to buildings 

that housed confined domestic livestock. Early 

snowstorms in 1992 and 1997 resulted in the 

loss of more than 30,000 head of feedlot cattle 

each year in the southern plains of the United 

States (Mader 2003).

Economic losses from reduced cattle performance (morbidity) likely exceed those associated with cattle death losses by several-fold 

(Mader 2003). In addition to losses in the 1990s, 

conditions during the winter of 2000-2001 

resulted in decreased efficiencies of feedlot 

cattle in terms of overall gain and daily gain of 

approximately 5 and 10 percent, respectively, 

from previous years as a result of late autumn 

and early winter moisture, combined with prolonged cold stress conditions (Mader 2003). In 

addition, the 2006 snowstorms, which occurred 

in the southern plains around year end, appear to 

be as devastating as the 1992 and 1997 storms. 

These documented examples of how climate 

can impact livestock production illustrate the 

potential for more drastic consequences of

increased variability in weather patterns, and 

extreme events that may be associated with 

climate change.

2.3.5.1 Potential Impact of Climate 

 Change on Livestock

The risk potential associated with livestock production systems due to global warming can be 

characterized by levels of vulnerability, as influenced by animal performance and environmental parameters (Hahn 1995). When combined 

performance level and environmental influences 

create a low level of vulnerability, there is little 

risk. As performance levels (e.g., rate of gain, 

milk production per day, eggs/day) increase, 

the vulnerability of the animal increases and, 

when coupled with an adverse environment, the 

animal is at greater risk. Combining an adverse 

environment with high performance pushes the 

level of vulnerability and consequent risk to

even higher levels. Inherent genetic characteristics or management scenarios that limit the 

animal’s ability to adapt to or cope with environmental factors also puts the animal at risk. At 

very high performance levels, any environment 

other than near-optimal may increase animal 

vulnerability and risk.

The potential impacts of climatic change on 

overall performance of domestic animals can be 
65

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

determined using defined relationships between 

climatic conditions and voluntary feed intake, 

climatological data, and GCM output. Because 

ingestion of feed is directly related to heat production, any change in voluntary feed intake 

and/or energy density of the diet will change 

the amount of heat produced by the animal 

(Mader et al. 1999b). Ambient temperature has 

the greatest influence on voluntary feed intake. 

However, individual animals exposed to the 

same ambient temperature will not exhibit the 

same reduction in voluntary feed intake. Body 

weight, body condition, and level of production 

affect the magnitude of voluntary feed intake 

and ambient temperature at which changes in 

voluntary feed intake begin to be observed. 

Intake of digestible nutrients is most often the 

limiting factor in animal production. Animals 

generally prioritize available nutrients to support 

maintenance needs first, followed by growth or 

milk production, and then reproduction.

Based on predicted climate outputs from GCM 

scenarios, production and response models 

for growing confined swine and beef cattle, 

and milk-producing dairy cattle have been 

developed (Frank et al. 2001). The goal in the 

development of these models was to utilize 

climate projections – primarily average daily 

temperature – to generate an estimate of direct 

climate-induced changes in daily voluntary feed 

intake and subsequent performance during summer in the central portion of the United States 

(the dominant livestock producing region of 

the country), and across the entire country. The 

production response models were run for one 

current (pre-1986 as baseline) and two future 

climate scenarios: doubled CO2 (~2040) and 

a triple of CO2 (~2090) levels. This data base 

employed the output from two GCMs – the 

Canadian Global Coupled (CGC) Model, Version I, and the United Kingdom Meteorological 

Office/Hadley Center for Climate Prediction and 

Research model – for input to the livestock production/response models. Changes in production 

of swine and beef cattle data were represented 

by the number of days to reach the target weight 

under each climate scenario and time period. 

Dairy production is reported in kilograms of 

milk produced per cow per season. Details of 

this analysis are reported by Frank (2001) and 

Frank et al. (2001).

In the central U.S. (MINK region = Missouri,

Iowa, Nebraska, and Kansas), days-to-slaughter 

weight for swine associated with the CGC 

2040 scenario increased an average of 3.7 

days from the baseline of 61.2 days. Potential 

losses under this scenario averaged 6 percent 

and would cost swine producers in the region 

$12.4 million annually. Losses associated with 

the Hadley scenario are less severe. Increased 

time-to-slaughter weight averaged 1.5 days, or 

2.5 percent, and would cost producers $5 million 

annually. For confined beef cattle reared in the 

central U.S., time-to-slaughter weight associated 

with the CGC 2040 scenario increased 4.8 days 

(above the 127-day baseline value) or 3.8 percent, costing producers $43.9 million annually. 

Climate changes predicted by the Hadley model 

resulted in loss of 2.8 days of production, or 

2.2 percent. For dairy, the projected CGC 2040 

climate scenario would result in a 2.2 percent 

(105.7 kg/cow) reduction in milk output, and 

cost producers $28 million annually. Production losses associated with the Hadley scenarios 

would average 2.9 percent and cost producers 

$37 million annually. Figures 2.12, 2.13, and 

2.14 indicate predicted changes in productivity 

in swine, beef and dairy, respectively, for the 

various regions of the United States.

Across the entire United States, percent increase 

in days to market for swine and beef, and the 

percent decrease in dairy milk production for 

the 2040 scenario, averaged 1.2 percent, 2.0 

percent, and 2.2 percent, respectively, using 

the CGC model, and 0.9 percent, 0.7 percent, 

and 2.1 percent, respectively, using the Hadley model. For the 2090 scenario, respective 

changes averaged 13.1 percent, 6.9 percent, 

and 6.0 percent using the CGC model, and 4.3 

percent, 3.4 percent, and 3.9 percent using the 

Hadley model. In general, greater declines in 

productivity are found with the CGC model than 

with the Hadley model. Swine and beef production were affected most in the south-central and 

southeastern United States. Dairy production 

was affected the most in the U.S. Midwest and 

Northeast regions.

In earlier research, Hahn et al. (1992) also derived estimates of the effects of climate change 

of swine growth rate and dairy milk production 

during summer, as well as other periods during 

the year. In the east-central United States, per 
The U.S. Climate Change Science Program

66

Chapter 2

animal milk production was found to decline 

388 kg (~4 percent) for a July through April 

production cycle, and 219 kg (~2.2 percent) for 

an October through July production cycle as a 

result of global warming. Swine growth rate in 

this same region was found to decline 26 percent 

during the summer months, but increased nearly 

12 percent during the winter months as a result 

of global warming. Approximately one-half of 

these summer domestic livestock production 

declines are offset by improvements in productivity during the winter. In addition, high 

producing animals will most likely be affected 

to a greater extent by global climate change than 

animals with lower production levels.

A production area in which global climate 

change may have negative effects that are not 

offset by positive winter effects is conception 

rates, particularly in instances when the breeding 

season primarily occurs in the spring and summer 

months. (This will particularly affect cattle.)

Hahn (1995) reported that conception rates in 

dairy cows were reduced 4.6 percent for each 

unit change when the THI reaches above 70. 

Amundson et al. (2005) reported a decrease in 

pregnancy rates of Bos taurus cattle of 3.2 percent for each increase in average THI above 70, 

and a decrease of 3.5 percent for each increase 

in average temperature above 23.4°C. These 

data were obtained from beef cows in a range 

or pasture management system. Amundson et al. 

(2006) also reported that of the environmental 

variables studied, minimum temperature had the 

greatest influence on the percent of cows getting 

pregnant. Clearly, increases in temperature and/

or humidity have the potential to affect conception rates of domestic animals not adapted 

to those conditions. Summertime conception 

rates are considerably lower in the Gulf States 

compared with conception rates in the Northern 

Plains (Sprott et al. 2001).

In an effort to maintain optimum levels of 

production, climate change will likely result in 

livestock producers selecting breeds and breed 

types that have genetically adapted to conditions 

that are similar to those associated with the 

climate change. However, in warmer climates, 

breeds that are found to be more heat tolerant 

are generally those that have lower productivity 

levels, which is likely the mechanism by which 

Figure 2.12 Percent change from baseline to 2040 of days for swine to 

grow from 50 to 110 kg, beginning June 1 under CGC (bold text) and Hadley 

(italicized text) modeled climate (Frank 2001; Frank et al. 2001).

Figure 2.13 Numerical values represent changes in beef productivity 

based on the number of days required to reach finish weights from baseline 

to 2040, beginning June 1 under CGC (bold text) and Hadley (italicized 

text) modeled climate (Frank 2001; Frank et al. 2001).

Figure 2.14 Percent change of kg fat-corrected milk (FCM) yield/cow/

season (June 1 to October 31) from baseline to 2040, under CGC (bold 

text) and Hadley (italicized text) modeled climate (Frank 2001; Frank et 

al. 2001).
67

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

they were able to survive as a dominant regional 

breed. In addition, climate change and associated variation in weather patterns will likely 

result in more livestock being managed in or 

near facilities that have capabilities for imposing microclimate modifications (Mader et al. 

1997a, 1999a; Gaughan et al. 2002). Domestic 

livestock, in general, can cope with or adapt to 

gradual changes in environmental conditions; 

however, rapid changes in environmental conditions or extended periods of exposure to extreme 

conditions drastically reduce productivity and 

are potentially life threatening.

Estimates of livestock production efficiency 

suggest that negative effects of hotter weather 

in summer outweigh positive effects of warmer 

winters (Adams et al. 1999). The largest change 

occurred under a 5°C increase in temperature, 

when livestock yields fell by 10 percent in 

cow-calf and dairy operations in Appalachia, 

the Southeast, Mississippi Delta, and southern 

Plains regions of the United States. The smallest 

change was one percent under 1.5°C warming 

in the same regions.

Another area of concern is the influence of climate change on diseases and parasites that affect 

domestic animals. Incidences of disease, such 

as bovine respiratory disease, are known to be 

increasing (Duff and Gaylean 2007). However, 

causes for this increase can be attributed to a 

number of non-environmentally related factors. 

As for parasites, similar insect migration and 

over-wintering scenarios observed in cropping 

systems may be found for some parasites that 

affect livestock.

Baylis and Githeko (2006) describe the potential 

of how climate change could affect parasites and 

pathogens, disease hosts, and disease vectors for 

domestic livestock. The potential clearly exists 

for increased rate of development of pathogens 

and parasites due to spring arriving earlier and 

warmer winters that allow greater proliferation and survivability of these organisms. For 

example, bluetongue was recently reported in 

Europe for the first time in 20 years (Baylis and 

Githeko 2006). Warming and changes in rainfall 

distribution may lead to changes in spatial or 

temporal distributions of those diseases sensitive 

to moisture such as anthrax, blackleg, haemorrhagic septicaemia, and vector-borne diseases. 

However, these diseases, as shown by climatedriven models designed for Africa, may decline 

in some areas and spread to others (Baylis and 

Githeko 2006).

2.4 Observing/Monitoring 

Systems 

2.4.1 Monitoring Relevant to Crops

2.4.1.1 Environmental Stress on Crop

 Production

Stress symptoms on crop production include 

warmer canopies associated with increased CO2

(but the increment may be too small to detect 

over 30 years), smaller grain size or lower test 

weight from heat stress, more failures of pollination associated with heat stress, and greater variability in crop production. However, elevated 

CO2 will have a helpful effect via reduced water 

consumption.

Heat stress could potentially be monitored by 

satellite image processing over the 30-year span, 

but causal factors for crop foliage temperature 

need to be properly considered (temporary water 

deficit from periodic low rainfall periods, effects 

of elevated CO2 to increase foliage temperature, direct effects of elevated air temperature, 

offset by opposite effect from prolonged water 

extraction associated with CO2-induced water 

conservation). Increased variability in crop yield 

and lower test weight associated with greater 

weather variability relative to thresholds for 

increased temperature can be evaluated both at 

the buying point, and by using annual USDA 

crop statistics for rainfed crops. Assessments 

of irrigated crops can be done in the same way, 

but with less expectation of water deficit as a 

causal factor for yield loss. The extent of water 

requirement for irrigated crops could be monitored by water management district records and 

pumping permits, but the same issue is present 

for understanding the confounding effects of 

temperature, radiation, vapor pressure deficit, 

rainfall, and CO2 effects.

2.4.1.2 Phenological Responses to 

 Climate Change

A recent analysis of more than 40 years of 

spring bloom data from the northeastern United 

States, the “lilac phenology network,” which 

was established by the USDA in the 1960s, provided robust evidence of a significant biological 
The U.S. Climate Change Science Program

68

Chapter 2

response to climate change in the region during 

the latter half of the 20th century (Wolfe et al. 

2005). 

2.4.1.3 Crop Pest Range Shifts in

 Collaboration with

 Integrated Pest Management 

(IPM) Programs

IPM specialists, and the weather-based weed, 

insect, and pathogen models they currently 

utilize, will provide an important link between 

climate science and the agricultural community. The preponderance of evidence indicates 

an overall increase in the number of outbreaks 

and northward migration of a wide variety of 

weeds, insects, and pathogens. The existing IPM 

infrastructure for monitoring insect and disease 

populations could be particularly valuable for 

tracking shifts in habitable zone of potential 

weed, insect, and disease pests, and for forecasting outbreaks.

2.4.2 Monitoring Relevant to

 Pasturelands

Efforts geared toward monitoring the long-term 

response of pasturelands to climate change 

should be as comprehensive as possible. When 

possible, monitoring efforts should include 

observation of vegetation dynamics, grazing 

regimes, animal behavior (e.g., indicators of 

animal stress to heat), mutualistic relationships 

(e.g., plant-root nematodes; N-fixing organisms), and belowground processes, such as 

development and changes in root mass, carbon 

inputs and turnover, nutrient cycling, and water 

balance. To augment their value, these studies 

should include use of simulation modeling in 

order to test hypotheses regarding ecosystem 

processes as affected by climate change. The 

development of protocols for monitoring the 

response of pasturelands to climate change 

should be coordinated with the development of 

protocols for rangelands and livestock.

2.4.3 Monitoring Relevant to

Rangelands

Soil processes are closely linked to rangeland 

productivity and vegetation dynamics. As a 

result, future efforts to track long-term rangeland-vegetation responses to climate change 

and CO2 should also involve monitoring efforts 

directed toward tracking changes in soils. While 

considerable progress has been made in the application of remote sensing for monitoring plant 

phenology and productivity, there remains a 

need for tracking critical soil attributes, which 

will be important in driving ecological responses 

of rangelands to climate change.

Nationwide, rangelands cover a broad expanse 

and are often in regions with limited accessibility. Consequently, ranchers and public land

managers need to periodically evaluate range 

resources (Sustainable Rangeland Roundtable 

Members 2006). Monitoring of rangelands via 

remote sensing is already an important research 

activity, albeit with limited rancher acceptance 

(Butterfield and Malmstrom 2006). A variety of 

platforms are currently being evaluated, from 

low-flying aerial photography (Booth and Cox 

2006) to satellite imagery (Afinowicz et al. 

2005; Everitt et al. 2006; Phillips et al. 2006; 

Weber 2006), plus hybrid approaches (Afinowicz et al. 2005) for use in evaluating a variety 

of attributes considered important indicators of 

rangeland health – plant cover and bare ground, 

presence of important plant functional groups 

or species – documenting changes in plant 

communities including weed invasion, primary 

productivity, and forage N concentration.

Although not explicitly developed for global 

change applications, the goal of many of these 

methodologies to document changing range conditions suggests tools that could be employed for 

tracking vegetation change in rangelands, and 

correlated to climatic or CO2 data, as done by 

Knapp et al. (2001). For example, state-and-transition models (Bestelmeyer et al. 2004; Briske 

et al. 2005) could be expanded to incorporate 

knowledge of rangeland responses to global 

change. Integration of those models with existing monitoring efforts and plant developmental 

data bases, such as the National Phenology 

Network, could provide a cost-effective monitoring strategy for enhancing knowledge of how 

rangelands are being impacted by global change, 

as well as offering management options.

Fundamental soil processes related to nutrient 

cycling – which may ultimately determine how 

rangeland vegetation responds to global change 

– are more difficult to assess. At present, there 

are no easy and reliable means by which to 
69

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

accurately ascertain the mineral and carbon state 

of rangelands, particularly over large land areas. 

The Natural Resources Conservation Service 

(NRCS) National Soil Characterization Data 

Base is an especially important baseline of soils 

information that can be useful for understanding how soils might respond to climate change. 

However, this data base does not provide a 

dynamic record of responses through time. 

Until such information is easily accessible, or 

reliable methodologies are developed for monitoring rangeland soil properties, predictions of 

rangeland responses to future environments will 

be limited. However, much can be ascertained 

about N cycling responses to global change from 

relatively easily determined measures of leaf-N 

chemistry (Peñuelas and Estiarte 1997). As a 

result, sampling of ecologically important target 

species in different rangeland ecosystems would 

be a comparatively low-cost measure to monitor 

biogeochemical response to global change.

2.5 Interactions Among 

Systems

2.5.1 Climate Change and

Sustainability of Pasturelands

The current land use system in the United States 

requires high resource inputs, from the use of

synthetic fertilizer on crops to the transport of 

crops to animal feeding operations. In addition 

to being inefficient with regard to fuel use, this 

system creates environmental problems from 

erosion to high nutrient degradation of water 

supplies. Recently, scientists have been examining the potential for improved profitability 

and improved sustainability with a conversion 

to integrated crop-livestock farming systems 

(Russelle et al. 2007). This could take many 

forms. One possible scenario involves grain 

crops grown in rotation with perennial pasture 

that also integrates small livestock operations 

into the farming system. Planting of perennial 

pastures decreases nitrate leaching and soil erosion, and planting of perennial legumes also 

reduces the need for synthetic N fertilizer. Diversifying crops also reduces incidence of pests, 

diseases, and weeds, imparting resilience to the 

agro-ecosystem. This resilience will become 

increasingly important as a component of farm 

adaptation to climate change.

2.6 Findings and 

Conclusions

2.6.1 Crops

2.6.1.1 Grain and Oilseed Crops

Crop yield response to temperature and CO2 for 

maize, soybean, wheat, rice, sorghum, cotton, 

peanut, and dry bean in the United States was 

assembled from the scientific literature. Cardinal 

base, optimum, and upper failure-point temperatures for crop development, vegetative, and 

reproductive growth and slopes-of-yield decline 

with increase in temperature were reviewed. In 

general, the optimum temperature for reproductive growth and development is lower than that 

for vegetative growth. Consequently, life cycle

will progress more rapidly, especially given a 

shortened grain-filling duration and reduced 

yield as temperature rises. Furthermore, these 

crops are characterized by an upper failure-point 

temperature at which pollination and grain-set 

processes fail. Considering these aspects, the 

optimum mean temperature for grain yield 

is fairly low for the major agronomic crops: 

18-22oC for maize, 22-24oC for soybean, 15oC 

for wheat, 23-26oC for rice, 25oC for sorghum, 

25-26oC for cotton, 20-26oC for peanut, 23-24oC 

for dry bean, and 22-25oC for tomato.

Without the benefit of CO2, the anticipated 

1.2oC rise in temperature over the next 30 years 

is projected to decrease maize, wheat, sorghum, 

and dry bean yields by 4.0, 6.7, 9.4, and 8.6 

percent, respectively, in their major production 

regions. For soybean, the 1.2oC temperature 

rise will increase yield 2.5 percent in the Midwest where temperatures during July, August, 

September average 22.5oC, but will decrease 

yield 3.5 percent in the South, where mean 

temperature during July, August, and September 

averages 26.7oC. Likewise, in the South, that 

same mean temperature will result in reduced 

rice, cotton, and peanut yields, which will decrease 12.0, 5.7, and 5.4 percent, respectively. 

An anticipated CO2 increase from 380 to 440 

ppm will increase maize and sorghum yield by 

only 1 percent, whereas the listed C3 crops will 

increase yield by 6.1 to 7.4 percent, except for 

cotton, which shows a 9.2 percent increase. The 

response to CO2 was developed from interpolation of extensive literature summarization of 

Diversifying crops 

also reduces 

incidence of pests, 

diseases, and 

weeds, imparting 

resilience to the 

agro-ecosystem. 

This resilience will 

become increasingly 

important as a 

component of farm 

adaptation to climate 

change.
The U.S. Climate Change Science Program

70

Chapter 2

response to ambient versus doubled CO2. The 

net effect of rising temperature and CO2 on yield 

will be maize (-3.0 percent), soybean (Midwest, 

+9.9 percent; South, +3.9 percent), wheat (+0.1 

percent), rice (-5.6 percent), sorghum (-8.4 

percent), cotton (+3.5 percent), peanut (+1.3 

percent), and dry bean (-2.5 percent). The CO2-

induced decrease in measured ET summarized 

from chamber and FACE studies, from 380 to 

440 ppm, gives a fairly repeatable reduction 

in ET of 1.4 to 2.1 percent, although the 1.2oC 

rise in temperature would increase ET by 1.8 

percent, giving an unimportant net -0.4 to +0.3 

percent reduction in ET. This effect could lead 

to a further small -0.4 to +0.3 percent change in 

yield under rainfed production. A similar small 

change in crop water requirement will occur

under irrigated production. 

Thus, the benefits of CO2 rise over the next 30 

years mostly offset the negative effects of temperature for most C3 crops except rice and bean, 

while the C4 crop yields are reduced by rising 

temperature because they have little response 

to the CO2 rise. The two factors also nearly 

balance out on crop transpiration requirements.

Thus, the 30-year outlook for crop production 

is relatively neutral. However, the outlook for 

the next 100 years would not be as optimistic, if 

rise in temperature and CO2 continue, because 

the C3 response to rising CO2 is reaching a saturating plateau, while the negative temperature 

effects will become progressively more severe. 

There are continual changes in the genetic 

resources of crop varieties and horticultural 

crops that will provide increases in yield due to 

increased resistance to water and pest stresses. 

These need to be considered in any future assessments of the climatic impacts; however, 

the genetic modifications have not altered the 

basic temperature response or CO2 response of 

the biological system.

As temperature rises, crops will increasingly begin to experience upper failure point 

temperatures, especially if climate variability 

increases and if rainfall lessens or becomes more 

variable. Under this situation, yield responses 

to temperature and CO2 would move more toward the negative side. Despite increased CO2-

responsiveness of photosynthesis/biomass as 

temperature increases, there were no published 

beneficial interactions of increased CO2 upon 

grain yield as temperature increased because 

temperature effects on reproductive processes, 

especially pollination, are so dominant. On the 

other hand, there are cases of negative interactions on pollination associated with the rise in 

canopy temperature caused by lower stomatal 

conductance. For those regions and crops where 

climate change impairs reproductive development because of an increase in the frequency

of high temperature stress events (e.g., >35oC), 

the potential beneficial effects of elevated CO2

on yield may not be fully realized.

No direct conclusions were made relative to 

anticipated effects of rainfall change on crop 

production. Such assessment requires use of

global climate models and the climate outputs 

to be directed as inputs to crop growth models to 

simulate production for the different crops.

2.6.1.2 Horticultural Crops

Although horticultural crops account for more 

than 40 percent of total crop market value in 

the United States (2002 Census of Agriculture), 

there is relatively little information on their response to CO2, and few reliable crop simulation 

models for use in climate change assessments 

compared to that which is available for major 

grain and oilseed crops. The marketable yield 

of many horticultural crops is likely to be more 

sensitive to climate change than grain and oilseed crops because even short-term, minor environmental stresses can negatively affect visual 

and flavor quality. Perennial fruit and nut crop

survival and productivity will be highly sensitive 

to winter, as well as summer, temperatures.

2.6.2 Weeds

The potential habitable zone of many weed species is largely determined by temperature. For 

example, kudzu (Pueraria lobata, var. montana) 

is an aggressive species that has a northern range 

currently constrained by the -20oC minimum 

winter temperature isocline. While other factors 

such as moisture and seed dispersal will affect 

the spread of invasive weeds such as kudzu, 

climate change is likely to lead to a northern 

migration in at least some cases.

Many weeds respond more positively to increasing CO2 than most cash crops, particularly C3

invasive weeds that reproduce by vegetative 

means (roots, stolons, etc.). Recent research 
71

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

also suggests that glyphosate loses its efficacy 

on weeds grown at elevated CO2. While there 

are many weed species that have the C4 photosynthetic pathway and therefore show a smaller 

response to atmospheric CO2 relative to C3

crops, in most agronomic situations, crops are 

in competition with a mix of both C3 and C4

weeds.

2.6.3 Insects and Disease Pests

In addition to crops and weeds, beneficial and 

harmful insects, invasives, microbes and other 

organisms present in agroecosystems will be 

responding to changes in CO2 and climate. 

Numerous studies have already documented 

changes in spring arrival, over-wintering, and/

or geographic range of several insect and animal 

species due to climate change. Disease pressure from leaf and root pathogens may increase 

in regions where increases in humidity and 

frequency of heavy rainfall events are projected,

and decrease in regions projected to encounter 

more frequent drought.

2.6.4 Pasturelands

Today, pasturelands in the United States extend 

over 117 million acres; however, the area under 

pasturelands has experienced an 11 percent 

decrease over the last 25 years due mainly to 

expansion of urban areas. Consequently, future

reductions in pastureland area will require an

increase in pasture productivity in order to meet 

production needs.

In general, pasture species have been less 

studied than cropland species in terms of their 

response to climate change variables including 

atmospheric CO2 concentration, temperature, 

and precipitation. Pastureland response to climate change will likely be complex because, in 

addition to the main climatic drivers, other plant 

and management factors might also influence 

the response (e.g., plant competition, perennial 

growth habits, seasonal productivity, and plantanimal interactions).

Results of studies evaluating the response of 

pasture species to elevated CO2 are consistent 

with the general response of C3 and C4 type 

vegetation to elevated CO2 but important exceptions exist. C3 pasture species such as Italian 

ryegrass, orchardgrass, rhizoma peanut, tall 

fescue, and timothy have exhibited increased 

photosynthetic rates under elevated CO2. 

Other studies suggest that Kentucky bluegrass 

might be at the lower end of the range in the 

responsiveness of C3 grasses to elevated CO2, 

especially under low nutrient conditions. Perennial ryegrass has shown a positive response in 

terms of photosynthetic rate, but a low or even 

negative response in terms of plant yield. The 

C4 pasture species bahiagrass, an important 

pasture species in Florida, appears marginal 

in its response to elevated CO2. Also, shifts in 

optimal temperatures for photosynthesis might 

be expected under elevated CO2. Species like 

perennial ryegrass and tall fescue may show a 

downward shift in their optimal temperatures 

for photosynthesis.

This review has not yielded sufficient quantitative information for predicting the yield change 

of pastureland species under a future temperature increase of 1.2°C. However, projected 

increases in temperature and the lengthening of 

the growing season should, in principle, extend 

forage production into late fall and early spring, 

thereby decreasing the need for accumulation 

of forage reserves during the winter season. In 

addition, water availability may play a major 

role in the response of pasturelands to climate 

change. Dallisgrass appears to better withstand 

conditions of moisture stress under elevated CO2

than under ambient conditions. Simulation modeling of alfalfa yield response to climate change 

suggests that future alterations in precipitation 

will be very important in determining yields. 

Roughly, for every 4 mm change in annual precipitation, the models predict a 1 percent change 

in dryland alfalfa yields.

In studies using defoliation as a variable, increases in plant productivity under defoliation 

were only observed under ambient CO2 while 

the largest response to elevated CO2 was observed in non-defoliated plants. The effect of 

elevated CO2 on pasture yield may be affected 

by the presence of mutualistic interactions with 

other organisms. Tall fescue plants infected with 

an endophyte fungus and exposed to elevated 

CO2 showed a 15 percent higher yield response 

than under ambient conditions.

An improved understanding of the impacts of 

climate change on pastureland might be obtained 
The U.S. Climate Change Science Program

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Chapter 2

through comprehensive studies that include grazing regimes, mutualistic relationships (e.g., plant 

roots-nematodes; N-fixing organisms), as well as 

the balance of carbon, nutrients and water.

2.6.5 Rangelands

The evidence from manipulative experiments, 

modeling exercises, and long-term observations of rangeland vegetation over the past two 

centuries provide indisputable evidence that 

warming, altered precipitation patterns, and 

rising atmospheric CO2 are virtually certain 

to have profound impacts on the ecology and 

agricultural utility of rangelands.

As CO2 levels and temperatures continue to 

climb, and precipitation patterns change, sensitivity of different species to CO2 will direct 

shifts in plant community species composition. 

However, lacking multiple global change experiments that incorporate CO2, temperature, 

and precipitation, our knowledge about how 

global change factors and soil nutrient cycling 

will interact and affect soil N availability is 

limited, and reduces our ability to predict species change.

Based on current evidence, plants with the C3

photosynthetic pathway – forbs, woody plants, 

and possibly legumes – seem likely to be favored 

by rising CO2, although interactions of species 

responses with rising temperature and precipitation patterns may affect these functional group 

responses (Morgan 2005, 2007). (For instance, 

warmer temperatures and drier conditions will 

tend to favor C4 species, which may cancel out 

the CO2 advantage of C3 grasses.)

There is already some evidence that climate 

change-induced species shifts are underway 

in rangelands. For instance, encroachment of 

woody shrubs into former grasslands is likely 

due to a combination of over-grazing, lack 

of fire, and rising levels of atmospheric CO2. 

Combined effects of climate and land management change can drive species change that can 

have a tremendous negative impact on the range 

livestock industry (Bond and Midgley 2000; 

Morgan et al. 2007; Polley, 1997). In turn, this 

has altered the frequency and timing of wildfires

by reducing establishment of perennial herbaceous species by pre-empting soil water early 

in the growing season (Young 1991). It seems 

likely that plant species changes will have as 

much or more impact on livestock operations 

as alterations in plant productivity.

One of our biggest concerns is in the area of 

how grazing animals affect ecosystem response 

to climate change. Despite knowledge that large 

grazing animals have important impacts on the 

productivity and nutrient cycling for rangelands 

(Augustine and McNaughton 2004, 2006; Semmartin et al. 2004), little global change research 

has addressed this particular problem. Manipulative field experiments in global change research 

are often conducted on plots too small to incorporate grazing animals, so these findings do not 

reflect the effect grazing domestic livestock can 

have on N cycling due to diet selectivity, species changes, and nutrient cycling, all of which 

can interact with CO2 and climate (Allard et 

al. 2004; Semmartin et al. 2004). The paucity 

of data presently available on livestock-plant 

interactions under climate change severely compromises our ability to predict the consequences

of climate change on livestock grazing.

Another important knowledge gap concerns 

the responses of rangelands to multiple global 

changes. To date, only one experiment has 

examined four global changes: rising CO2, temperature, precipitation, and N deposition (Dukes 

et al. 2005; Zavaleta et al. 2003a). Although 

interactions between global change treatments 

on plant production were rare, strong effects 

on relative species abundances and functional 

plant group responses suggest highly complex 

interactions of species responses to combined 

global changes that may ultimately impact nutrient cycling with important implications for 

plant community change and C storage. Such 

results underscore an emerging acknowledgement that while there is certainty that rangeland 

ecosystems are responding to global change, our 

ability to understand and predict responses to 

future changes is limited.

Rangelands are used primarily for grazing. 

For most domestic herbivores, the preferred 

forage is grass. Other plants – including trees, 

shrubs, and other broadleaf species – can lessen 

livestock production and profitability by reducing availability of water and other resources to 

grasses, making desirable plants unavailable to 

livestock or physically complicating livestock 
73

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

management, or poisoning grazing animals 

(Dahl and Sosebee 1991).

In addition to livestock grazing, rangelands 

provide many other goods and services, including biodiversity, tourism, and hunting. They 

are also important as watershed catchments. 

Carbon stores are increasingly being considered 

as an economic product (Liebig et al. 2005; 

Meeting et al. 2001; Moore et al. 2001; Schuman et al. 2001). However, there is still uncertainty about the greenhouse gas sink capacity 

of rangelands, how it will be altered by climate 

change – including rising atmospheric CO2 – 

and, ultimately, the economics of rangeland C 

sequestration (Schlesinger 2006; van Kooten

2006). While the ability to accurately predict 

the consequences of all aspects of climate

change for rangelands is limited, a recent list of 

management options (Morgan 2005) suggests 

the types of choices ranchers and land managers will need to consider in the face of climate 

change (Table 2.14).

A challenge for rangeland scientists, public 

land managers, ranchers, and others interested 

in rangelands will be to understand how the dynamics of climate change and land management 

translate into ecological changes that impact 

long-term use and sustainability. Perhaps more 

than most occupations, ranching in the presentday United States is as much a lifestyle choice as 

it is an economic decision (Bartlett et al. 2002), 

so economics alone will not likely drive decisions that ranchers make in response to climate 

change. Nevertheless, ranchers are already looking to unconventional rangeland uses like tourism or C storage. In regions where vegetation 

changes are especially counter-productive to domestic livestock agriculture, shifts in enterprises 

will occur. Shifts between rangeland and more 

intensive agriculture may also occur, depending 

on the effects of climate-induced environmental 

changes and influence of economics that favor 

certain commodities. However, once a native 

rangeland is disturbed, whether intentionally 

through intensive agriculture or unintentionally through climate change, restoration can be 

prohibitively costly, and in some cases, impossible. Therefore, management decisions on the 

use of private and public rangelands will need 

to be made with due diligence paid toward their 

long-term ecological impacts.

2.6.6 Animal Production Systems

Increases in air temperature reduce livestock 

production during the summer season with 

partial offsets during the winter season. Current 

management systems usually do not provide as 

much shelter to buffer the effects of adverse 

weather for ruminants as for non-ruminants. 

From that perspective, environmental management for ruminants exposed to global warming needs to consider: 1) general increase in 

temperature levels, 2) increases in nighttime 

temperatures, and 3) increases in the occurrence 

of extreme events (e.g., hotter daily maximum 

temperature and more/longer heat waves).

In terms of environmental management needed 

to address global climate change, the impacts 

can be reduced by recognizing the adaptive ability of the animals and by proactive application of 

appropriate countermeasures (sunshades, evaporative cooling by direct wetting or in conjunction 

with mechanical ventilation, etc.). Specifically, 

the capabilities of livestock managers to cope 

with these effects are quite likely to keep up

with the projected rates of change in global temperature and related climatic factors. However, 

coping will entail costs such as application of 

environmental modification techniques, use of

more suitably adapted animals, or even shifting 

animal populations.

Climate changes affect certain parasites and 

pathogens, which could result in adverse effects on host animals. Interactions exist among 

temperature, humidity, and other environmental 

factors which, in turn, influence energy exchange. Indices or measures that reflect these 

interactions remain ill-defined, but research 

to improve them is underway. Factors other 

than thermal (i.e., dust, pathogens, facilities, 

contact surfaces, technical applications) also 

need better definition. Duration and intensity of 

potential stressors are of concern with respect 

to the coping and/or adaptive capabilities of an 

animal. Further, exposure to one type of stressor may lead to altered resistance to other types. 

Other interactions may exist, such that animals 

stressed by heat or cold may be less able to cope 

with other stressors (restraint, social mixing, 

transport, etc). Improved stressor characterization is needed to provide a basis for refinement 

of sensors providing input to control systems.
The U.S. Climate Change Science Program

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Chapter 2

Innovations in electronic system capabilities 

will undoubtedly continue to be exploited for 

the betterment of livestock environments with 

improved economic utilization of environmental measures, and mitigation strategies. There 

is much potential for application of improved 

sensors, expert systems, and electronic stockmanship. Continued progress should be closely 

tied to animal needs based on rational criteria, 

and must include further recognition of health 

criteria for animal caretakers as well. The ability of the animal’s target tissues to respond to 

disruptions in normal physiological circadian 

Table 2.14 CO2 and climate change responses and management options for grazing land factors. Adapted from 

Morgan (2005).

Factor Responses to rising CO2 and climate change Management options

Primary 

production

Increase or little change with rising CO2: Applies to most systems, 

especially water-limited rangelands. N may limit CO2 response in some 

systems.

Increases or little change with temperature: Applies to most temperate 

and wet systems.

Decreases with temperature: Applies to arid and semi-arid systems 

that experience significantly enhanced evapotranspiration and drought, 

particularly where precipitation is not expected to increase.

Variable responses with precipitation: Depends on present climate, 

and nature of precipitation change. Increases in production in regions 

where water is limiting, but increasing temperatures and more intense 

precipitation events will reduce this.

Adjust forage harvesting:

Stocking rates.

Grazing systems.

Develop and utilize adapted forage species 

(e.g. legumes, C4 grasses where appropriate, 

more drought-resistant species and cultivars).

Enterprise change (e.g. movement to more or 

less intensive agricultural practices).

Plant community 

species 

composition

Global changes will drive competitive responses that alter plant 

communities: In some systems, legumes and C3 species may be favoured 

in future CO2-enriched environments, but community reactions will 

be variable and highly site specific. Warmer environments will favor 

C4 metabolisms. Both productive and reproductive responses will be 

featured in community changes. Ultimate plant community responses 

will probably reflect alterations in soil nutrients and water, and 

involve complex interactions between changes in CO2, temperature 

and precipitation. Weed invasions may already be underway, due to 

rising atmospheric CO2. Proximity to urban areas will add complex 

interactions with ozone and N deposition.

All of the above.

Weed control:

Fire management and/or grazing practices to 

convert woody lands to grasslands.

Herbicides where appropriate to control 

undesirables.

Enterprise change or emphasis:

Change between intensive/extensive practices.

C storage strategy.

Tourism, hunting, wildlife.

Biodiversity.

Forage quality Increasing CO2 will alter forage quality. In N-limited native rangeland 

systems, CO2-induced reduction in N and increased fiber may lower 

quality.

Utilize/interseed legumes where N is limiting 

and practice is feasible.

Alter supplemental feeding practices.

Animal 

performance to 

altered climate

Increased temperature, warm regions: Reduced feed intake, feed 

efficiency, animal gain, milk production and reproduction. Increased 

disease susceptibility, and death.

Increased temperature, cold regions: Enhanced animal performance, 

lowered energy costs.

Animal usage:

Select adapted animal breeds from different 

world regions to match new climate.

Improve animal genetics.

Select different animal species (i.e. camels, 

sheep and goats for more drought-prone 

areas).

Alter management (e.g., timing of breeding, 

calving, weaning)

Enterprise change (above)

rhythms may be an important indicator of stress. 

Also, the importance of obtaining multiple measures of stress is also becoming more apparent. 

However, inclusion and weighting of multiple 

factors (e.g., endocrine function, immune function, behavior patterns, performance measures, 

health status, vocalizations) is not an easy task 

in developing integrated stress measures. Establishing threshold limits for impaired functions 

that may result in reduced performance or health 

are essential. Improved modeling of physiological systems as our knowledge base expands will 

help the integration process.
75

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Land Resources: Forests and Arid Lands

Lead Authors: M.G. Ryan and S.R. Archer

Contributing Authors: R.A. Birdsey, C.N. Dahm, L.S. Heath, 

J.A. Hicke, D.Y. Hollinger, T.E. Huxman, G.S. Okin, R. Oren, J.T. 

Randerson, W.H. Schlesinger

r

3.1 Introduction

This synthesis and assessment report builds on 

an extensive scientific literature and series of 

recent assessments of the historical and potential 

impacts of climate change and climate variability on managed and unmanaged ecosystems 

and their constituent biota and processes. It 

identifies changes in resource conditions that 

are now being observed and examines whether 

these changes can be attributed in whole or part 

to climate change. It also highlights changes in 

resource conditions that recent scientific studies 

suggest are most likely to occur in response to 

climate change, and when and where to look 

for these changes. As outlined in the Climate 

Change Science Program (CCSP) Synthesis and 

Assessment Product 4.3 (SAP 4.3) prospectus, 

this chapter will specifically address climaterelated issues in forests and arid lands.

In this chapter the focus is on the near-term 

future. In some cases, key results are reported 

out to 100 years to provide a larger context 

but the emphasis is on next 25-50 years. This 

nearer-term focus is chosen for two reasons. 

First, for many natural resources, planning and 

management activities already address these 

time scales through development of long-lived 

infrastructure, forest rotations, and other significant investments. Second, climate projections 

are relatively certain over the next few decades. 

Emission scenarios for the next few decades 

do not diverge from each other significantly 

because of the “inertia” of the energy system. 

Most projections of greenhouse gas emissions 

assume that it will take decades to make major 

changes in the energy infrastructure, and only 

begin to diverge rapidly after several decades 

have passed (30-50 years).

Forests occur in all 50 states but are most common in the humid eastern United States, the 

West Coast, at higher elevations in the Interior 

West and Southwest, and along riparian corridors in the plains states (Figure 3.1) (Zhu and 

Evans 1994). Forested land occupies about 740 

million acres, or about one-third of the United 

States. Forests in the eastern United States cover 

380 million acres; most of this land (83 percent) 

is privately owned, and 74 percent is broadleaf 

forest. The 360 million acres of forest land in 

the western United States are 78 percent conifer 

forests, split between public (57 percent) and 

private ownership (USDA Forest Service and 

U.S. Geological Survey 2002).

Forests provide many ecosystem services important to the well-being of the people of the United 

States: watershed protection, water quality, and

flow regulation; wildlife habitat and diversity; 

recreational opportunities, and aesthetic and 

spiritual fulfillment; raw material for wood and 

paper products; climate regulation, carbon storage, and air quality; biodiversity conservation.

While all of these services have considerable 

economic value, some are not easily quantified (Costanza et al. 1997; Daily et al. 2000; 

CHAPTER

3

Forested land 

occupies about 740 

million acres, or 

about one-third of 

the United States. 
The U.S. Climate Change Science Program

76

Chapter 3

Figure 3.1 Distribution of forest lands in the continental United States by forest type. This map 

was derived from Advanced Very High Resolution Radiometer (AVHRR) composite images recorded 

during the 1991 growing season. Each composite covered the United States at a resolution of one 

kilometer. Field data collected by the Forest Service were used to aid classification of AVHRR composites into forest-cover types. Details on development of the forest cover types dataset are in Zhu 

and Evans (1994).

Krieger 2001; Millennium Ecosystem Assessment 2005), and many Americans are strongly 

attached to their forests. A changing climate 

will alter forests and the services they provide. 

Sometimes changes will be viewed as beneficial, 

but often they will be viewed as detrimental.

Arid lands are defined by low and highly variable precipitation, and are found in the United 

States in the subtropical hot deserts of the Southwest and the temperate cold deserts of the Intermountain West (Figure 3.2). Arid lands provide 

many of the same ecosystem services as forests 

(with the exception of raw materials for wood 

and paper products), and support a large ranching industry. These diverse environments are 

also valued for their wildlife habitat, plant and 

animal diversity, regulation of water flow and 

quality, opportunities for outdoor

recreation, and open spaces for 

expanding urban environments. 

A changing climate will alter arid 

lands and their services.

Both forests and arid lands face 

challenges that can affect their 

responses to a changing climate: 

the legacy of historical land use, 

non-native invasive species, 

and the slow growth of many 

species. In forests, for instance, 

clearing and farming dramatically increased erosion, and the 

re-established forests are likely 

less productive as a result. In arid 

lands, grazing and exurban development can change plant and 

animal communities. Non-native 

invasive species are a challenge 

for all ecosystems, but especially 

so in arid lands, where non-native 

invasive grasses encourage fire 

in ecosystems where fire was 

historically very rare. The very 

slow growth of many arid land 

and dry forest species hinders 

recovery from disturbance.

Climate strongly influences both 

forests and arid lands. Climate 

shapes the broad patterns of ecological communities, the species 

within them, their productivity, 

and the ecosystem goods and services they 

provide. The interaction of vegetation and climate is a fundamental tenet of ecology. Many 

studies show how vegetation has changed with 

climate over the past several thousand years, 

so it is well understood that changes in climate 

will change vegetation. Given a certain climate 

and long enough time, resultant ecological communities can generally be predicted. However, 

predicting the effects of a changing climate on 

forests and arid lands for the next few decades 

is challenging, especially with regard to the 

rates and dynamics of change. Plants in these 

communities can be long lived; hence, changes 

in species composition may lag behind changes 

in climate. Furthermore, seeds and conditions 

for better-adapted communities are not always 

present.
77

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 3.2 The five major North American deserts, outlined on a 2006 map 

of net primary productivity (NPP). Modeled NPP was produced by the Numerical 

Terradynamic Simulation Group (http://www.ntsg.umt.edu/) using the fraction of 

absorbed photosynthetically active radiation measured by the Moderate Resolution 

Imaging Spectroradiometer (MODIS) satellite and land cover-based radiation use 

efficiency estimates (Running et al. 2000). Desert boundaries based on Olson. 

Courtesy of Grant Casady and the Arizona Remote Sensing Center, University 

of Arizona.

Past studies linking climate and vegetation 

may also provide poor predictions for the future because the same physical climate may 

not occur in the future and many other factors 

may be changing as well. CO2 is increasing in 

the atmosphere; nitrogen deposition is much 

greater than in the past, and appears to be increasing; ozone pollution is locally increasing; 

and species invasions from other ecosystems 

are widespread. These factors cause important 

changes themselves, but their interactions are 

difficult to predict because they represent novel 

combinations.

Disturbance (such as drought, storms, insect outbreaks, grazing, and fire) is part of the ecological history of most ecosystems and influences 

ecological communities and landscapes. Climate 

affects the timing, magnitude, and frequency

of many of these disturbances, and a changing climate will bring changes in disturbance 

regimes to forests and arid lands (Dale et al. 

2001). Trees and arid land vegetation can take 

from decades to centuries to re-establish after a 

disturbance. Both human-induced and natural 

disturbances shape ecosystems by influencing 

species composition, structure, and function 

(productivity, water yield, erosion, carbon storage, and susceptibility to future disturbance). In 

forests, more than 55 million acres are currently 

impacted by disturbance, with the largest agents 

being insects and pathogens (Dale et al. 2001). 

These disturbances cause an estimated financial 

loss of 3.7 billion dollars per year (Dale et al. 

2001). In the past several years, scientists have 

learned that the magnitude and impact of these 

disturbances and their response to climate rivals 

that expected from changes in temperature and 

precipitation (Field et al. 2007).

Disturbance may reset and rejuvenate some 

ecosystems in some cases and cause enduring 

change in others. For example, climate may 

favor the spread of invasive exotic grasses into 

arid lands where the native vegetation is too 

sparse to carry a fire. When these areas burn, 

they typically convert to non-native monocultures and the native vegetation is lost. In another 

example, drought may weaken trees and make 

them susceptible to insect attack and death – a 

pattern that recently occurred in the Southwest. 

In these forests, drought and insects converted 

large areas of mixed pinyon-juniper forests 

into juniper forests. However, fire is an integral 

component of many forest ecosystems, and 

many tree species (such as the lodgepole pine 

forests that burned in the Yellowstone fires of 

1988) depend on fire for regeneration. Climate 

effects on disturbance will likely shape future 

forests and arid lands as much as the effects of 

climate itself.

Disturbances and changes to the frequency or

type of disturbance present challenges to resource managers. Many disturbances command 

quick action, public attention, and resources.

Surprisingly, most resource planning in the 

United States does not consider disturbance, 

even though disturbances are common, and 

preliminary information exists on the frequency

and areal extent of disturbances (Dale et al. 

Arid lands are 

defined by low 

and highly variable 

precipitation, and 

are found in the 

United States in 

the subtropical 

hot deserts of the 

Southwest and 

the temperate 

cold deserts of 

the Intermountain 

West.
The U.S. Climate Change Science Program

78

Chapter 3

2001). Disturbances in the future may be larger 

and more common than those experienced historically, and planning for disturbances should 

be encouraged (Dale et al. 2001; Stanturf et al. 

2007).

The goal of this chapter is to assess how forests 

and arid lands will respond to predicted anticipated changes in climate over the next few 

decades. It will discuss the effects of climate 

and its components on the structure and function 

of forest and arid land ecosystems. It will also 

highlight the effects of climate on disturbance 

and how these disturbances change ecosystems. 

Active management may increase the resiliency 

of forests and arid lands to respond to climate 

change. For example, forest thinning can reduce 

fire intensity, increase drought tolerance and 

reduce susceptibility to insect attack. Grazing 

management and control of invasive species can 

promote vegetation cover, reduce fire risk, and 

reduce erosion. These and other options for managing ecosystems to adapt to climate change are 

discussed in Synthesis and Assessment Product 

4.4 (Preliminary review of adaptation options 

for climate-sensitive ecosystems and resources, 

U.S. Climate Change Science Program).

3.2 Forests

3.2.1 Brief Summary of Key Points 

from the Literature

Climate strongly affects forest productivity and 

species composition. Forest productivity in the 

United States has increased 2-8 percent in the 

past two decades, but separating the role of 

climate from other factors causing the increase 

is complicated and varies by location. Some 

factors that act to increase forest growth are 1) 

observed increases in precipitation in the Midwest and Lake States, 2) observed increases in 

nitrogen deposition, 3) an observed increase in 

temperature in the northern United States that 

lengthens the growing season, 4) changing age 

structure of forests, and 5) management practices. These factors interact, and identifying 

the specific cause of a productivity change is 

complicated by insufficient data. Even in the 

case of large forest mortality events, such as 

those associated with fire and insect outbreaks, 

attributing a specific event to a change in climate 

may be difficult because of interactions among 

factors. For example, in the recent widespread 

mortality of pinyon pine in the Southwest, intense drought weakened the trees, but generally, 

the Ips beetle killed them.

In addition to the direct effects of climate on 

tree growth, climate also affects the frequency

and intensity of natural disturbances such as fire, 

insect outbreaks, ice storms, and windstorms. 

These disturbances have important consequences for timber production, water yield, carbon 

storage, species composition, invasive species, 

and public perception of forest management. 

Disturbances also draw management attention 

and resources. Because of observed warmer and 

drier climate in the West in the past two decades, 

forest fires have grown larger and more frequent

during that period. Several large insect outbreaks have recently occurred or are occurring 

in the United States. Increased temperature and 

drought likely influenced these outbreaks. Fire 

suppression and large areas of susceptible trees 

(over age 50) may have also contributed.

Rising atmospheric CO2 will increase forest 

productivity and carbon storage in forests if 

sufficient water and nutrients are available. Any 

increased carbon storage will be primarily in live 

trees. Average productivity increase for a variety 

of experiments was 23 percent. The response of 

tree growth and carbon storage to elevated CO2

depends on site fertility, water availability, and 

stand age, with fertile, younger stands responding more strongly.

Forest inventories can detect long-term changes 

in forest growth and species composition, but 

they have limited ability to attribute changes to 

specific factors, including climate. Separating 

the effects of climate change from other impacts 

would require a broad network of indicators,

coupled with a network of controlled experimental manipulations. Experiments that directly manipulate climate and observe impacts are critical 

components in understanding climate change 

impacts and in separating the effects of climate 

from those caused by other factors. Experiments 

such as free-air CO2 enrichment, ecosystem 

and soil warming, and precipitation manipulation have greatly increased understanding of 

the direct effects of climate on ecosystems. 

These experiments have also attracted a large 

research community and fostered a thorough 

and integrated understanding because of their 

Climate strongly 

influences both 

forests and arid 

lands. Climate 

shapes the broad 

patterns of ecological 

communities, the 

species within them, 

their productivity, 

and the ecosystem 

goods and services 

they provide. 
79

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

large infrastructure costs, importance and rarity. 

Monitoring of disturbances affecting forests is 

currently ineffective, fragmented, and generally 

unable to attribute disturbances to specific factors, including climate.

3.2.2 Observed Changes or Trends

3.2.2.1 Climate and Ecosystem

 Context

Anyone traveling from the lowlands to the 

mountains will notice that species composition 

changes with elevation and with it, the structure and function of these forest ecosystems. 

Biogeographers have mapped these different 

vegetation zones and linked them with their 

characteristic climates. The challenge facing 

scientists is to understand how these zones and 

the individual species within them will move 

with a changing climate, at what rate, and with 

what effects on ecosystem function.

Temperature, water, and radiation are the primary abiotic factors that affect forest productivity 

(Figure 3.3). Any response to changing climate 

will depend on the factors that limit production 

at a particular site. For example, any site where 

productivity is currently limited by lack of 

water or a short growing season will increase 

productivity if precipitation increases and if the 

growing season lengthens. Temperature controls 

the rate of metabolic processes for photosynthesis, respiration, and growth. Generally, plant 

Figure 3.3 Potential limits to vegetation net primary production based on fundamental physiological limits by 

sunlight, water balance, and temperature. Nutrients are also important and vary locally. From Boisvenue and 

Running (2006).

metabolism has an optimum temperature. Small 

departures from this optimum usually do not 

change metabolism and short-term productivity, 

although changes in growing season length may 

change annual productivity. Large departures 

and extreme events (such as frosts in orange 

groves) can cause damage or tree mortality. Water controls cell division and expansion, which 

promote growth and stomatal opening, which 

regulates water loss and CO2 uptake in photosynthesis. Productivity will generally increase 

with water availability in water-limited forests 

(Knapp et al. 2002). Radiation supplies the energy for photosynthesis, and both the amount of 

leaf area and incident radiation control the quantity of radiation absorbed by a forest. Nutrition 

and atmospheric CO2 also strongly influence 

forest productivity if other factors are less limiting (Boisvenue and Running 2006), and ozone 

exposure can lower productivity (Hanson et al. 

2005). Human activities have increased nitrogen 

inputs to forest ecosystems, atmospheric CO2

concentration, and ozone levels. The effects of 

CO2 are everywhere, but ozone and N deposition 

are common to urban areas, and forests and arid 

lands downwind from urban areas. The response 

to changes in any of these factors is likely to be 

complex and dependent on the other factors.

Forest trees are evolutionarily adapted to thrive 

in certain climates. Other factors, such as fire 

and competition from other plants, also regulate 

species presence, but if climate alone changes 

Temperature, 

water, and radiation 

are the primary 

abiotic factors 

that affect forest 

productivity.
The U.S. Climate Change Science Program

80

Chapter 3

enough, species will adjust to suitable conditions 

or go locally extinct if suitable conditions are 

unavailable (Woodward 1987). One example of 

such a species shift is sugar maple in the northeastern United States. Suitable climate for it may 

move northward into Canada and the distribution will likely follow (Chuine and Beaubien 

2001), assuming the species is able to disperse 

propagules rapidly enough to keep pace with 

the shifting climatic zone. Because trees live for 

decades and centuries, absent disturbance, it is 

likely that forest species composition will take 

time to adjust to changes in climate.

Disturbances such as forest fires, insect outbreaks, ice storms, and hurricanes also change 

forest productivity, carbon cycling, and species 

composition. Climate influences the frequency

and size of disturbances. Many features of 

ecosystems can be predicted by forest age, and 

disturbance regulates forest age. After a standreplacing disturbance, forest productivity increases until the forest fully occupies the site or 

develops a closed canopy, then declines to near 

zero in old age (Ryan et al. 1997). Carbon storage after a disturbance generally declines while 

the decomposition of dead wood exceeds the 

productivity of the new forest, then increases as 

the trees grow larger and the dead wood from the 

disturbance disappears (Kashian et al. 2006). In 

many forests, species composition also changes 

with time after disturbance. Susceptibility to fire 

and insect outbreaks changes with forest age, but 

the response of forest productivity to climate, N 

deposition, CO2, and ozone differs for old and 

young forests is still not understood because 

most studies have only considered young trees 

or forests. Changes in disturbance prompted by 

climate change are likely as important as the 

changes in precipitation, temperature, N deposition, CO2, and ozone for affecting productivity 

and species composition.

3.2.2.2 Temperature

Forest productivity in the United States has 

generally been increasing since the middle 

of the 20th century (Boisvenue and Running 

2006), with an estimated increase of 2-8 percent 

between 1982 and 1998 (Hicke et al. 2002b), 

but the causes of this increase (increases in 

air and surface temperature, increasing CO2, 

N deposition, or other factors) are difficult to 

isolate (Cannell et al. 1998). These effects can 

potentially be disentangled by experimentation, 

analysis of species response to environmental 

gradients, planting trees from seeds grown in 

different climates in a common garden, anomaly 

analysis, and other methods. Increased temperatures will affect forest growth and ecosystem 

processes through several mechanisms (Hughes 

2000; Saxe et al. 2001) including effects on 

physiological processes such as photosynthesis 

and respiration, and responses to longer growing 

seasons triggered by thermal effects on plant 

phenology (e.g., the timing and duration of 

foliage growth). Across geographical or local 

elevational gradients, forest primary productivity has long been known to increase with mean 

annual temperature and rainfall (Leith 1975). 

This result also generally holds within a species (Fries et al. 2000) and in provenance trials 

where trees are found to grow faster in a slightly 

warmer location than that of the seed source 

itself (Wells and Wakeley 1966; Schmidtling 

1994). In Alaska, where temperatures have 

warmed strongly in recent times, changes in soil 

processes are similar to those seen in experimental warming studies (Hinzman et al. 2005). 

In addition, permafrost is melting, exposing 

organic material to decomposition and drying 

soils (Hinzman et al. 2005).

Along with a general trend in warming, the 

length of the northern hemisphere growing 

season has been increasing in recent decades 

(Menzel and Fabian 1999; Tucker et al. 2001). 

Forest growth correlates with growing season 

length (Baldocchi et al. 2001), with longer 

growing seasons (earlier spring) leading to 

enhanced net carbon uptake and storage (Black 

et al. 2000; Hollinger et al. 2004). The ability 

to complete phenological development within 

the growing season is a major determinant of 

tree species range limits (Chuine and Beaubien 

2001). However, Sakai and Weiser (1973) have 

also related range limits to the ability to tolerate 

minimum winter temperatures.

3.2.2.3 Fire and Insect Outbreaks

Westerling et al. (2006) analyzed trends in 

wildfire and climate in the western United 

States from 1974–2004. They show that both 

the frequency of large wildfires and fire season

length increased substantially after 1985, and 

that these changes were closely linked with 

advances in the timing of spring snowmelt, 
81

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

and increases in spring and summer air temperatures. Much of the increase in fire activity 

occurred in mid-elevation forests in the northern 

Rocky Mountains and Sierra Nevada mountains. 

Earlier spring snowmelt probably contributed to 

greater wildfire frequency in at least two ways,

by extending the period during which ignitions 

could potentially occur, and by reducing water 

availability to ecosystems in mid-summer, thus 

enhancing drying of vegetation and surface 

fuels (Westerling et al. 2006). These trends in 

increased fire size correspond with the increased 

cost of fire suppression (Calkin et al. 2005).

In boreal forests across North America, fire 

activity also has increased in recent decades. 

Kasischke and Turetsky (2006) combined fire 

statistics from Canada and Alaska to show 

that burned area more than doubled between 

the 1960s/70s and the 1980s/90s. The increasing trend in boreal burned-area appears to be 

associated with a change in both the size and 

number of lightning-triggered fires (>1000 

km2), which increased during this period. In 

parallel, the contribution of human-triggered 

fires to total burned area decreased from the 

1960s to the 1990s (from 35.8 percent to 6.4 

percent) (Kasischke and Turetsky 2006). As 

in the western U.S., a key predictor of burned 

area in boreal North America is air temperature, 

with warmer summer temperatures causing an 

increase in burned area on both interannual and 

decadal timescales (Gillett et al. 2004; Duffy et 

al. 2005; Flannigan et al. 2005). In Alaska, for 

example, June air temperatures alone explained 

approximately 38 percent of the variance of 

the natural log of annual burned area during 

1950-2003 (Duffy et al. 2005).

Insects and pathogens are significant disturbances to forest ecosystems in the United States 

(Figure 3.4), costing $1.5 billion annually (Dale 

et al. 2001). Extensive reviews of the effects of 

climate change on insects and pathogens have 

reported many cases where climate change has 

affected and/or will affect forest insect species 

range and abundance (Ayres and Lombardero 

2000; Malmström and Raffa 2000; Bale et al. 

2002). This review focuses on forest insect species within the United States that are influenced 

by climate and attack forests that are ecologically or economically important.

Figure 3.4 Satellite image of the extensive attack by mountain pine beetle in lodgepole pine forests in Colorado. 

Pre-outbreak image taken October 2002, and post outbreak image taken August 2007. Images courtesy of 

DigitalGlobe, Inc. (http://digitalglobe.com/)
The U.S. Climate Change Science Program

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Chapter 3

Major outbreaks in recent years include: a 

mountain pine beetle outbreak affected >10 million hectares (Mha) of forest in British Columbia 

(Taylor et al. 2006), and 267,000 ha in Colorado 

(Colorado State Forest Service 2007); more 

than 1.5 Mha was attacked by spruce beetle in 

southern Alaska and western Canada (Berg et 

al. 2006); >1.2 Mha of pinyon pine mortality 

occurred because of extreme drought, coupled 

with an Ips beetle outbreak in the Southwest 

(Breshears et al. 2005); and millions of hectares 

were affected by southern pine beetle, spruce 

budworm, and western spruce budworm in recent decades in southeastern, northeastern, and 

western forests, respectively (USDA Forest Service 2005). Ecologically important whitebark 

pine is being attacked by mountain pine beetle 

in the northern and central Rockies (Logan and 

Powell 2001). For example, almost 70,000 ha, 

or 17 percent, of whitebark pine forest in the 

Greater Yellowstone Ecosystem is infested by 

mountain pine beetle (Gibson 2006). Evident 

from these epidemics is the widespread nature 

of insect outbreaks in forests throughout the 

United States.

Climate plays a major role in driving, or at least 

influencing, infestations of these important 

forest insect species in the United States (e.g., 

Holsten et al. 1999; Logan et al. 2003a; Carroll et al. 2004; Tran et al. in press), and these 

recent large outbreaks are likely influenced by 

observed increases in temperature. Temperature 

controls life cycle development rates, influences 

synchronization of mass attacks required to

overcome tree defenses, and determines winter 

mortality rates (Hansen et al. 2001b; Logan and 

Powell 2001; Hansen and Bentz 2003; Tran et al. 

in press). Climate also affects insect populations 

indirectly through effects on hosts. Drought 

stress, resulting from decreased precipitation 

and/or warming, reduces the ability of a tree 

to mount a defense against insect attack (Carroll et al. 2004; Breshears et al. 2005), though 

this stress may also cause some host species to 

become more palatable to some types of insects 

(Koricheva et al. 1998). Fire suppression and 

large areas of susceptible trees (a legacy from 

logging in the late 1800s and early 1900s (Birdsey et al. 2006)), may also play a role.

3.2.3 Possible Future Changes and 

Impacts

3.2.3.1 Warming

A review of recent experimental studies found 

that rising temperatures would generally enhance tree photosynthesis (Saxe et al. 2001), 

as a result of increased time operating near 

optimum conditions, and because rising levels 

of atmospheric CO2 increase the temperature 

optimum for photosynthesis (Long 1991). 

Warming experiments, especially for trees 

growing near their cold range limits, generally 

increase growth (Bruhn et al. 2000; Wilmking 

et al. 2004; Danby and Hik 2007). The experimental warming of soils alone has been found 

to stimulate nitrogen mineralization and soil 

respiration (Rustad et al. 2001). An important 

concern for all experimental manipulations 

is that the treatments occur long enough to 

determine the full suite of effects. It appears 

that the large initial increases in soil respiration 

observed at some sites decrease with time back 

toward pretreatment levels (Rustad et al. 2001; 

Melillo et al. 2002). This result may come about 

from changes in C pool sizes, substrate quality

(Kirschbaum 2004; Fang et al. 2005), or other 

factors (Davidson and Janssens 2006).

A general response of leaves, roots, or whole 

trees to short-term increases in plant temperature is an approximate doubling of respiration 

with a 10oC temperature increase (Ryan et al. 

1994; Amthor 2000). Over the longer term, however, there is strong evidence for temperature 

acclimation (Atkin and Tjoelker 2003; Wythers 

et al. 2005), which is probably a consequence

of the linkage of respiration to the production 

of photosynthate (Amthor 2000). One negative 

consequence of warming for trees is that it can

increase the production of isoprene and other 

hydrocarbons in many tree species (Sharkey and 

Yeh 2001) – compounds that may lead to higher 

levels of surface ozone and increased plant 

damage. Physiologically, the overall result of 

the few degrees of warming expected over the 

next few decades is likely a modest increase in 

photosynthesis and tree growth (Hyvonen et al. 

2007). However, where increased temperature 

coincides with decreased precipitation (western 

Alaska, Interior West, Southwest), forest growth 

is expected to be lower (Hicke et al. 2002b).

For the projected 

temperature 

increases over 

the next few 

decades, most 

studies support the 

conclusion that a 

modest warming 

of a few degrees 

Celsius will lead 

to greater tree 

growth in the 

United States.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

For the projected temperature increases over 

the next few decades, most studies support the 

conclusion that a modest warming of a few 

degrees Celsius will lead to greater tree growth 

in the United States. There are many causes for 

this enhancement including direct physiological 

effects, a longer growing season, and potentially 

greater mineralization of soil nutrients. Because 

different species may respond somewhat differently to warming, the competitive balance 

of species in forests may change. Trees will 

probably become established in formerly colder 

habitats (more northerly, higher altitude) than 

at present.

3.2.3.2 Changes in Precipitation

Relationships between forest productivity and 

precipitation have been assessed using continental gradients in precipitation (Webb et al. 

1983; Knapp and Smith 2001), interannual variability within a site (Hanson et al. 2001), and by 

manipulating water availability (Hanson et al. 

2001). Forest productivity varies with annual 

precipitation across broad gradients (Webb 

et al. 1983; Knapp and Smith 2001), and with 

interannual variability within sites (Hanson et 

al. 2001). Some of these approaches are more 

informative than others for discerning climate 

change effects.

Gradient studies likely poorly predict the 

response to changes in precipitation, because 

site-specific factors such as site fertility control the response to precipitation (Gower et al. 

1992; Maier et al. 2004). The response of forest productivity to interannual variability also 

likely poorly predicts response to precipitation 

changes, because forests have the carbohydrate 

storage and deep roots to offset drought effects 

over that time, masking any effects that might 

be apparent over a longer-term trend.

The effects of precipitation on productivity 

will vary with air temperature and humidity. 

Warmer, drier air will evaporate more water 

and reduce water availability faster than cooler, 

humid air. Low humidity also promotes the 

closure of stomata on leaves, which reduces 

photosynthesis and lowers productivity even 

where soil water availability is abundant.

Manipulation of water availability in forests 

allows an assessment of the direct effects of 

precipitation (Figure 3.5). Two experiments 

where water availability was increased through 

irrigation showed only modest increases in forest production (Gower et al. 1992; Maier et al. 

2004), but large increases with a combination of 

irrigation and nutrients. In contrast, forest productivity did not change when precipitation was 

increased or reduced 33 percent, but with the 

same timing as natural precipitation (Hanson 

et al. 2005). Tree growth in this precipitation 

manipulation experiment also showed strong 

interannual variability with differences in 

annual precipitation. Hanson et al. (2005) conclude that “differences in seasonal patterns of 

rainfall within and between years have greater 

impacts on growth than percentage changes in 

rainfall applied to all rainfall events.”

No experiments have assessed the effect of 

changes in precipitation on forest tree species 

composition. Hanson et al. (2005) showed that 

growth and mortality changed in response to 

precipitation manipulation for some smaller 

individuals, but we do not know if these changes 

will lead to composition changes. However, 

one of the best understood patterns in ecology 

is the variation of species with climate and 

site water balance. So, if precipitation changes 

substantially, it is highly likely that species 

composition will change (Breshears et al. 2005). 

However, limited studies exist with which to 

predict the rate of change and the relationship 

with precipitation amount.

Drought is a common feature of all terrestrial 

ecosystems (Hanson and Weltzin 2000), and 

generally lowers productivity in trees. Drought 

Figure 3.5 Direct manipulation of precipitation in 

the Throughfall Displacement experiment (TDE) at 

Walker Branch (Paul Hanson, Oak Ridge National 

Laboratory).
The U.S. Climate Change Science Program

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Chapter 3

events can have substantial and long-lasting 

effects on ecosystem structure, species composition, and function by differentially killing 

certain species or sizes of trees (Hanson and 

Weltzin 2000; Breshears et al. 2005), weakening trees to make them more susceptible to 

insect attacks (Waring 1987), or by increasing the incidence and intensity of forest fires 

(Westerling et al. 2006). Forest management by 

thinning trees can improve water available to 

the residual trees. (Donner and Running 1986; 

Sala et al. 2005).

If existing trends in precipitation continue, 

forest productivity will likely decrease in the 

Interior West, the Southwest, eastern portions of 

the Southeast, and Alaska. Forest productivity 

will likely increase in the northeastern United 

States, the Lake States, and in western portions 

of the Southeast. An increase in drought events 

will very likely reduce forest productivity wherever these events occur.

3.2.3.3 Elevated Atmospheric CO2 and

 Carbon Sequestration

The effects of increasing atmospheric CO2 on 

carbon cycling in forests are most realistically 

observed in Free Air CO2 Enrichment (FACE) 

experiments (Figure 3.6). These experiments 

have recently begun to provide time-series 

sufficiently long for assessing the effect of CO2

projected for the mid-21st century on some 

components of the carbon cycle. The general 

findings from a number of recent syntheses 

using data from the three American and one 

European FACE sites (King et al. 2004; Norby 

et al. 2005; McCarthy et al. 2006a; Palmroth et 

al. 2006) show that North American forests will 

absorb more CO2 and might retain more carbon 

as atmospheric CO2 increases. The increase in 

the rate of carbon sequestration will be highest

(mostly in wood) on nutrient-rich soils with 

no water limitation and will decrease with 

decreasing fertility and water supply. Several 

yet unresolved questions prevent a definitive

assessment of the effect of elevated CO2 on 

other components of the carbon cycle in forest 

ecosystems:

•	 Although total carbon allocation to belowground increases with CO2 (King et al. 2004; 

Palmroth et al. 2006), there is only equivocal

evidence of CO2-induced increase in soil 

carbon (Jastrow et al. 2005; Lichter et al. 

2005).

Figure 3.6 FACE ring at the Duke Forest FACE, Durham, North Carolina. (Photo courtesy Duke University.)
85

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

•	 Older forests can be strong carbon sinks

(Stoy et al. 2006), and older trees absorb 

more CO2 in an elevated CO2 atmosphere, 

but wood production of these trees show 

limited or only transient response to CO2

(Körner et al. 2005).

•	 When responding to CO2, trees require and

obtain more nitrogen (and other nutrients) 

from the soil. Yet, despite appreciable effort, 

the soil processes supporting such increased 

uptake have not been identified, leading 

to the expectation that nitrogen availability may increasingly limit the response to 

elevated CO2 (Finzi et al. 2002; Luo et al. 

2004; de Graaff et al. 2006; Finzi et al. 2006; 

Luo et al. 2006).

To understand the complex processes controlling ecosystem carbon cycling

under elevated CO2 and solve these puzzles, longer time series are needed (Walther 2007), yet 

the three FACE studies in the U.S. forest ecosystems are slated for closure in 2007-2009.

Major findings on specific processes 

leading to these generalities

Net primary production (NPP) is defined as 

the balance between canopy photosynthesis 

and plant respiration. Canopy photosynthesis 

increases with atmospheric CO2, but less than 

expected based on physiological studies because 

of negative feedbacks in leaves (biochemical 

down-regulation) and canopies (reduced light, 

and conductance with increasing leaf area index 

(LAI); (Saxe et al. 2001; Schäfer et al. 2003; 

Wittig et al. 2005). On the other hand, plant 

respiration increases only in proportion to tree 

growth and amount of living biomass – that is, 

tissue-specific respiration does not change under elevated CO2 (Gonzalez-Meler et al. 2004). 

The balance between these processes, NPP, 

increases in stands on moderately fertile and 

fertile soils. The short-term (<10 years), median 

response among the four “forest” FACE experiments was an increase of 23±2 percent (Norby 

et al. 2005). Although the average response 

was similar among these sites that differed in 

productivity (Norby et al. 2005), the within-site 

variability in the response to elevated CO2 can 

be large (<10 percent to >100 percent). At the 

Duke FACE site, this within-site variability 

was related to nitrogen availability (Oren et al. 

2001; Finzi et al. 2002; Norby et al. 2005). The 

absolute magnitude of the additional carbon 

sink varies greatly among years. At the Duke 

FACE, much of this variability is caused by 

droughts and disturbance events (McCarthy 

et al. 2006a).

The enhancement of NPP at low LAI is largely 

driven by an enhancement in LAI, whereas at 

high LAI, the enhancement reflects increased 

light-use efficiency (Norby et al. 2005; McCarthy et al. 2006a). The sustainability of the 

NPP response and the partitioning of carbon 

among plant components may depend on soil 

fertility (Curtis and Wang 1998; Oren et al. 

2001; Finzi et al. 2002). NPP in intermediate 

fertility sites may undergo several phases of 

transient response, with CO2-induced enhancement of stemwood production dominating 

initially, followed by fine-root production after 

several years (Oren et al. 2001; Norby et al. 

2004). In high fertility plots, the initial response 

so far appears sustainable (Körner 2006).

Carbon partitioning to pools with different 

turnover times is highly sensitive to soil nutrient 

availability. Where nutrient availability is low, 

increasing soil nutrient supply promotes higher 

LAI. Under elevated CO2 and increased nutrient 

supply, LAI becomes increasingly greater than 

that of stands under ambient CO2. This response 

affects carbon allocation to other pools. Aboveground NPP increases with LAI (McCarthy et 

al. 2006a) with no additional effects of elevated 

CO2. The fraction of Aboveground NPP allocated to wood, a moderately slow turnover 

pool, increases with LAI in broadleaf FACE 

experiments (from ~50 percent at low LAI, to a 

maximum of 70 percent at mid-range LAI), with 

the effect of elevated CO2 on allocation entirely 

accounted for by changes in LAI. In pines, allocation to wood decreased with increasing LAI 

(from ~65 percent to 55 percent), but was higher 

(averaging ~68 percent versus 58 percent) under 

elevated CO2 (McCarthy et al. 2006a). Despite 

the increased canopy photosynthesis, there is 

no evidence of increased wood production in 

pines growing on very poor, sandy soils (Oren 

et al. 2001).

Total carbon allocation belowground and CO2

efflux from the forest floor decrease with 

increasing LAI, but the enhancement under 
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86

Chapter 3

elevated CO2 is approximately constant (~22 

percent) over the entire range of LAI (King et 

al. 2004; Palmroth et al. 2006). About a third 

of the extra carbon allocated belowground 

under elevated CO2 is retained in litter and soil 

storage at the U.S. FACE sites (Palmroth et al. 

2006). At Duke FACE, a third of the incremental carbon sequestration is found in the forest

floor. The CO2-induced enhancement in fine 

root and mycorrhizal fungi turnover has not 

translated to a significant net incremental storage of carbon in the mineral soil (Schlesinger 

and Lichter 2001; Jastrow et al. 2005; Lichter 

et al. 2005). A recent meta-analysis (Jastrow 

et al. 2005), incorporating data from a variety 

of studies in different settings, estimated a median CO2-induced increase in the rate of soil C 

sequestration of 5.6 percent (+19 g C m-2 y-1). 

Because soil C is highly variable and a large 

fraction of ecosystem carbon, a long time-series 

is necessary to statistically detect changes at any 

one site (McMurtrie et al. 2001).

3.2.3.4 Forests and Carbon

Sequestration

Forest growth and long-lived wood products 

currently offset about 20 percent of annual 

U.S. fossil fuel carbon emissions (U.S. Climate 

Change Science Program Synthesis and Assessment Product 2.2 2007). Because a large 

forested landscape should be carbon neutral 

over long periods of time (Kashian et al. 2006), 

the presence of this large forest carbon sink is 

either a legacy of past land use (regrowth after 

harvest or reforestation of land cleared for pasture or crops) or a response to increased CO2

and nitrogen deposition, or both (Canadell et al. 

2007). This carbon sink is an enormous ecosystem service by forests, and its persistence will 

be important to any future mitigation strategy. 

If the sink primarily results from past land use, 

it will diminish through time. If not, it may 

continue until the effects of CO2 and N diminish 

(Canadell et al. 2007).

To understand whether forest growth and 

long-lived forest products will continue their 

important role in offsetting a fraction of U.S. 

carbon emissions, significant unknowns and 

uncertainties would have to be addressed. The 

scale of the problem is large: Jackson and Schlesinger (2004) estimate that for afforestation to 

offset an additional 10 percent of U.S. emissions, immediate conversion of one-third of 

current croplands to forests would be required.

Some of the unknowns and uncertainties are: 1) 

the economics of sequestration (Richards and

Stokes 2004); 2) the timeline for valuing carbon 

stored in forests – should carbon stored today be 

worth more than carbon stored later (Fearnside 

2002); 3) the permanence of stored carbon and 

its value if not permanent (Kirschbaum 2006); 

4) the ability to permanently increase forest carbon stores in the face of changes in climate that 

may change species (Bachelet et al. 2001) and 

increase disturbance (Westerling et al. 2006), 

and change the process of carbon storage itself 

(Boisvenue and Running 2006); 5) how much 

carbon can be counted as “additional” given the 

self-replacing nature of forests; 6) identification 

of methods for increasing carbon sequestration

in a variety of ecosystems and management 

goals; 7) how to account for carbon storage 

“gained” from management or avoided losses 

in fire; 8) identification of uniform methods and 

policies for validating carbon storage; 9) vulnerability ofsequestered carbon to fire, windthrow

or other disturbance; 10) “leakage” or displacement of carbon storage on one component of the 

landscape to carbon release on another (Murray 

et al. 2004); 11) will saturation of the carbon 

sink in North America work against forest C 

sequestration (Canadell et al. 2007)? 12) the

impacts of carbon sequestration on the health of

forest ecosystems and the climate system itself; 

and 13) the impacts of increasing carbon storage on other forest values such as biodiversity 

and water yield.

3.2.3.5 Interactive Effects including 

 Ozone, Nitrogren Deposition, 

and Forest Age

Ozone is produced from photochemical reactions of nitrogen oxides and volatile organic 

compounds. Ozone can damage plants (Ashmore 2002) and lower productivity, and these 

responses have been documented for U.S. 

forests (Matyssek and Sandermann 2003; Karlsson et al. 2004). In the United States, controls 

on emissions of nitrogen oxides and volatile 

organic compounds are expected to reduce the 

peak ozone concentrations that currently cause 

the most plant damage (Ashmore 2005). However, background tropospheric concentrations 

may be increasing as a result of increased global 

emissions of nitrogen oxides (Ashmore 2005). 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

These predicted increases in background ozone 

concentrations may reduce or negate the effects of policies to reduce ozone concentrations 

(Ashmore 2005). Ozone pollution will modify 

the effects of elevated CO2 and any changes in 

temperature and precipitation (Hanson et al. 

2005), but these interactions are difficult to predict because they have been poorly studied.

Nitrogen deposition in the eastern United 

States and California can exceed 10 kg N ha-1

yr-1 and likely has increased 10-20 times above 

pre-industrial levels (Galloway et al. 2004). 

Forests are generally limited by nitrogen availability, and fertilization studies show that this 

increased deposition will enhance forest growth 

and carbon storage in wood (Gower et al. 1992; 

Albaugh et al. 1998; Adams et al. 2005). There 

is evidence that chronic nitrogen deposition 

also increases carbon storage in surface soil 

over large areas (Pregitzer et al. 2008). Chronic 

nitrogen inputs over many years could lead to 

“nitrogen saturation” (a point where the system 

can no longer use or store nitrogen), a reduction in forest growth, and increased levels of 

nitrate in streams (Aber et al. 1998; Magill et 

al. 2004), but observations of forest ecosystems 

under natural conditions have not detected this 

effect (Magnani et al. 2007). Experiments and 

field studies have shown that the positive effect 

of elevated CO2 on productivity and carbon 

storage can be constrained by low nitrogen 

availability, but in many cases elevated CO2

causes an increase in nitrogen uptake (Finzi et 

al. 2006; Johnson 2006; Luo et al. 2006; Reich 

et al. 2006). For nitrogen-limited ecosystems, 

increased nitrogen availability from nitrogen 

deposition enhances the productivity increase 

from elevated CO2 (Oren et al. 2001) and the 

positive effects of changes in temperature and 

precipitation. Overall, there is strong evidence 

that the effects of nitrogen deposition on forest 

growth and carbon storage are positive and 

might exceed those of elevated CO2 (Körner 

2000; Magnani et al. 2007).

Forest growth changes with forest age (Ryan 

et al. 1997), likely because of reductions in 

photosynthesis (Ryan et al. 2004). Because of 

the link of forest growth with photosynthesis, 

the response to drought, precipitation, nitrogen 

availability, ozone, and elevated CO2 may also 

change with forest age. Studies of elevated 

CO2 on trees have been done with young trees 

(which show a positive growth response), 

but the one study on mature trees showed no 

growth response (Körner et al. 2005). This 

is consistent with model results found in an 

independent study (Kirschbaum 2005). Tree 

size or age may also affect ozone response and 

response to drought, with older trees possibly 

more resistant to both (Grulke and Miller 1994; 

Irvine et al. 2004).

3.2.3.6 Fire Frequency and Severity

Several lines of evidence suggest that large, 

stand-replacing wildfires will likely increase in 

frequency over the nextseveral decades because

of climate warming (Figure 3.7). Chronologies 

derived from fire debris in alluvial fans (Pierce 

et al. 2004) and fire scars in tree rings (Kitzberger et al. 2007) provide a broader temporal 

context for interpreting contemporary changes 

in the fire regime. These longer-term records 

unequivocally show that warmer and drier

periods during the last millennium are associated with more frequent and severe wildfires

in western forests. GCM projections of future 

climate during 2010-2029 suggest that the 

number of low humidity days (and high fire 

danger days) will increase across much of the 

western U.S., allowing for more wildfire activity with the assumption that fuel densities and 

land management strategies remain the same 

(Flannigan et al. 2000; Brown et al. 2004). 

Flannigan et al. (2000) used two GCM simulations of future climate to calculate a seasonal 

severity rating related to fire intensity and difficulty of fire control. Depending on the GCM 

used, forest fire seasonal severity rating in the 

Southeast is projected to increase from 10 to 30 

percent and 10 to 20 percent in the Northeast by 

2060. Other biome models used with a variety 

of GCM climate projections simulate a larger 

increase in fire activity and biomass loss in the 

Southeast, sufficient to convert the southernmost closed-canopy Southeast forests to savannas (Bachelet et al. 2001). Forest management 

options to reduce fire size and intensity are 

discussed in Synthesis and Assessment Product 

4.4 (Preliminary review of adaptation options 

for climate-sensitive ecosystems and resources, 

U.S. Climate Change Science Program).

By combining climate-fire relationships derived 

from contemporary records with GCM simulaFuture increases 

in fire emissions 

across North 

America will 

have important 

consequences for 

climate forcing 

agents, air quality, 

and ecosystem 

services.
The U.S. Climate Change Science Program

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Chapter 3

tions of future climate, Flannigan et al. (2005) 

estimated that future fire activity in Canadian 

boreal forests will approximately double by 

the end of this century for model simulations 

in which fossil fuel emissions were allowed 

to increase linearly at a rate of 1 percent per 

year. Both Hadley Center and Canadian GCM 

simulations projected that fuel moisture levels 

will decrease and air temperatures will increase 

within the continental interior of North America 

because of forcing from greenhouse gases and 

aerosols.

Santa Ana winds and human-triggered ignitions 

play an important role in shaping the fire regime 

of Southern California shrublands and forests 

(Keeley and Fotheringham 2001; Westerling 

et al. 2004). Santa Ana winds occur primarily during fall and winter and are driven by 

large-scale patterns of atmospheric circulation 

(Raphael 2003; Conil and Hall 2006). Using 

future predictions from GCMs, Miller and 

Schlegel (2006) assessed that the total number 

of annual Santa Ana events would not change 

over the next 30 years. One of the GCM simulations showed a shift in the seasonal cycle, with 

fewer Santa Ana events occurring in September 

and more occurring in December. The implication of this change for the fire regime was 

unknown.

Figure 3.7 Ponderosa pine after the Hayman fire in Colorado, June 2002. While no one fire can be 

related to climate or changes in climate, research shows that the size and number of Western forest 

fires has increased substantially since 1985, and that these increases were linked with earlier spring 

snowmelt and higher spring and summer air temperature. Photo courtesy USDA Forest Service.

Future increases in fire 

emissions across North 

America will have important consequences for climate forcing agents, air 

quality, and ecosystem services. More frequent fire

will increase emissions 

of greenhouse gases and 

aerosols (Amiro et al. 2001) 

and increase deposition of 

black carbon aerosols on 

snow and sea ice (Flanner 

et al. 2007). Even though 

many forests will regrow 

and sequester the carbon

released in the fire, forests 

burned in the next few decades can be sources of CO2

for decades and not recover 

the carbon lost for centuries 

(Kashian et al. 2006) – an 

important consideration 

for slowing the increase in atmospheric CO2. 

In boreal forests, the warming effects from 

fire-emitted greenhouse gases may be offset at 

regional scales by increases in surface albedo 

caused by a shift in the stand age distribution 

(Randerson et al. 2006). Any climate driven 

changes in boreal forest fires in Alaska and 

Canada will have consequences for air quality

in the central and eastern United States because 

winds often transport carbon monoxide, ozone, 

and aerosols from boreal fires to the south (McKeen et al. 2002; Morris et al. 2006; Pfister et 

al. 2006). Increased burning in boreal forests 

and peatlands also has the potential to release 

large stocks of mercury currently stored in 

cold and wet soils (Turetsky et al. 2006). These 

emissions may exacerbate mercury toxicities 

in northern hemisphere food chains caused by 

coal burning.

3.2.3.7 Insect Outbreaks

Rising temperature is the aspect of climate 

change most influential on forest insect species through changes in insect survival rates, 

increases in life cycle development rates, facilitation of range expansion, and effects on host 

plant capacity to resist attack (Ayres and Lombardero 2000; Malmström and Raffa 2000; Bale 

et al. 2002). Future northward range expansion 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

attributed to warming temperatures has been 

predicted for mountain pine beetle (Logan and 

Powell 2001) and southern pine beetle (Ungerer 

et al. 1999). Future range expansion of mountain pine beetle has the potential of invading 

jack pine, a suitable host that extends across 

the boreal forest of North America (Logan and 

Powell 2001). Increased probability of spruce 

beetle outbreak (Logan et al. 2003a) as well 

as increase in climate suitability for mountain 

pine beetle attack in high-elevation ecosystems (Hicke et al. 2006) has been projected in 

response to future warming. The combination 

of higher temperatures with reduced precipitation in the Southwest has led to enhanced tree 

stress, and also affected Ips beetle development 

rates; continued warming, as predicted by climate models, will likely maintain these factors 

(Breshears et al. 2005).

Indirect effects of future climate change may 

also influence outbreaks. Increasing atmospheric CO2 concentrations may lead to increased 

ability of trees to recover from attack (Kruger 

et al. 1998). Enhanced tree productivity in response to favorable climate change, including 

rises in atmospheric CO2, may lead to faster 

recovery of forests following outbreaks, and 

thus a reduction in time to susceptibility to 

subsequent attack (Fleming 2000). Although

eastern spruce budworm life cycles are tightly 

coupled to host tree phenology even in the presence of climate change, enemy populations that 

are significant in governing epidemic dynamics 

are not expected to respond to climate change 

in a synchronized way (Fleming 2000). Changing fire regimes in response to climate change 

(Flannigan et al. 2005) will affect landscapescale forest structure, which influences susceptibility to attack (Shore et al. 2006).

Nonnative invasive species are also significant 

disturbances to forests in the United States. 

Although little has been reported on climate 

influences on these insects, a few studies have 

illustrated climate control. The hemlock woolly 

adelgid is rapidly expanding its range in the 

eastern United States, feeding on several species of hemlock (Box 1). The northern range 

limit of the insect in the United States is currently limited by low temperatures (Parker et al. 

1999), suggesting range expansion in the event 

of future warming. In addition, the hemlock 

woolly adelgid has evolved greater resistance 

to cold conditions as it has expanded north 

(Butin et al. 2005). The introduced gypsy moth 

has defoliated millions of hectares of forest 

across the eastern United States, with great efforts expended to limit its introduction to other 

areas (USDA Forest Service 2005). Projections 

of future climate and gypsy moth simulation 

modeling reveal substantial increases in probability of establishment in the coming decades 

(Logan et al. 2003a).

As important disturbances, insect outbreaks 

affect many forest ecosystem processes. Outbreaks alter tree species composition within 

stands, and may result in conversion from 

forest to herbaceous vegetation through lack 

of regeneration (Holsten et al. 1995). Carbon 

stocks and fluxes are modified through a large 

decrease in living biomass and a corresponding large increase in dead biomass, reducing 

carbon uptake by forests as well as enhancing 

decomposition fluxes. In addition to effects 

at smaller scales, widespread outbreaks have 

significant effects on regional carbon cycling 

(Kurz and Apps 1999; Hicke et al. 2002a). Other 

biogeochemical cycles, such as nitrogen, are 

affected by beetle-caused mortality (Throop 

et al. 2004). Defoliation, for example as related 

to gypsy moth outbreaks, facilitates nitrogen 

movement from forest to aquatic ecosystems,

elevating stream nitrogen levels (Townsend et 

al. 2004).

Significant changes to the hydrologic cycle occur after a widespread insect epidemic, including increases in annual water yield, advances 

in the annual hydrograph, and increases in low 

flows (Bethlahmy 1974; Potts 1984). Water 

quantity is enhanced through reductions in

transpiration, in addition to reductions in snow 

interception, and subsequent redistribution and

sublimation. These effects can last for many 

years following mortality (Bethlahmy 1974).

Interactions of outbreaks and fire likely vary 

with time, although observational evidence is 

limited to a few studies (Romme et al. 2006). In 

central Colorado, number of fires, fire extent, 

and fire severity were not enhanced following 

outbreaks of spruce beetle (Bebi et al. 2003; 

Bigler et al. 2005; Kulakowski and Veblen 

2007). Other studies of the 1988 Yellowstone 
The U.S. Climate Change Science Program

90

Chapter 3

BOX 1: The Eastern Hemlock and its Woolly Adelgid

Outbreaks of insects and diseases affect forest structure 

and composition, leading to changes in carbon, nutrients, 

biodiversity, and ecosystem services. The hemlock woolly 

adelgid (HWA), native to Asia, was first recorded in 1951 

in Virginia, and has since spread, causing a severe decline 

in vitality and survival of eastern hemlock in North 

American forests (Maps 3.1 & 3.2, Stadler et al. 2006). 

Roads, major trails, and riparian corridors provide for 

long-distance dispersal of this aphid-like insect, probably 

by humans or birds (Koch et al. 2006). Although HWA is 

consumed by some insect predators (Flowers et al. 2006), 

once it arrives at a site, complete hemlock mortality is 

inevitable (Orwig et al. 2002; Stadler et al. 2005).

HWA will change biodiversity and species composition. 

Hemlock seedlings are readily attacked and killed by the 

HWA, so damaged hemlock stands are replaced by stands of black birch, black oaks, and other hardwoods (Brooks 

2004; Small et al. 2005; Sullivan and Ellison 2006). After HWA attack, plant biodiversity increases in the canopy 

and in the understory; invasive shrubs and woody vines of several species also expand in response to the improved 

light conditions (Goslee et al. 2005; Small et al. 2005; Eschtruth et al. 2006). Four insectivorous bird species have 

high affinity for hemlock forest type, and two of these, the blue-headed vireo and Blackburnian warbler, are specialists in the hemlock habitat. Expansion of HWA could negatively impact several million pairs of these birds by 

eliminating their habitat (Tingley et al. 2002; Ross et al. 2004).

Changes in canopy attributes upon replacement of hemlock with deciduous broadleaf species alter the radiation 

regime, hydrology, and nutrient cycling (Cobb et al. 2006; Stadler et al. 2006), and result in greater temperature 

fluctuations and longer periods of times in which streams are dry (Snyder et al. 2002). These conditions reduce 

habitat quality for certain species of fish. Brook trout and brown trout were two to three times as prevalent in 

hemlock than hardwood streams (Ross et al. 2003). Low winter temperature is the main factor checking the spread 

of HWA (Skinner et al. 2003). However, the combination of increasing temperature and the capacity of HWA 

to evolve greater resistance to cold shock as it has expanded its range northward (Butin et al. 2005) means that 

stands that have been relatively protected by cold temperatures (Orwig et al. 2002) may fall prey to the insect in 

the not-so-distant future (Map 3.3).

Map 3.2 Counties in the range of eastern hemlock that are 

uninfested, newly infested, and previously infested. From Onken 

and Reardon (2005).

Map 3.1 Sample sites and range expansion of Adelges 

tsugae relative to the native range of eastern hemlock in North 

America. Map from Butin et al. 2005 (redrawn from USDA 

Forest Service and Little, 1971).

Map 3.3 Estimated future hemlock woolly adelgid spread 

map prepared by Randall Marin, Northeastern Research 

Station, U.S. Forest Service (Souto et al. 1996).
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

fire that followed two mountain pine beetle 

epidemics found mixed fire effects, depending 

on outbreak severity and time since outbreak 

(Turner et al. 1999; Lynch et al. 2006). A quantitative modeling study of fire behavior found 

mixed fire effects following an outbreak of 

western spruce budworm (Hummel and Agee 

2003); more modeling studies that incorporate 

complete effects are needed to explore other 

situations.

Multiple socioeconomic impacts follow severe insect outbreaks. Timber production and 

manufacturing and markets may not be able to 

take advantage of vast numbers of killed trees 

(Ferguson 2004), and beetle-killed timber has 

several disadvantages from a manufacturing 

perspective (Byrne et al. 2006). Perceived 

enhanced fire risk and views about montane 

aesthetics following beetle-cause mortality 

influence public views of insect outbreaks, 

which could drive future public policy. Threats 

to ecologically important tree species may have 

ramifications for charismatic animal species 

(e.g., influences of whitebark pine mortality 

on the grizzly bear) (Logan and Powell 2001). 

Impacts are enhanced as human population, 

recreation, and tourism increase in forested 

regions across the nation.

3.2.3.8 Storms (Hurricanes, Ice Storms, 

 Windstorms)

Predictions of forest carbon (C) sequestration

account for the effect of fires (e.g., Harden et al. 

2000), yet other wide-ranging and frequent disturbances, such as hurricanes (Figure 3.8) and 

ice storms, are seldom explicitly considered. 

Both storm types are common in the southeastern United States, with an average return time 

of six years for ice storms (Bennett 1959) and 

two years for hurricanes (Smith 1999). These, 

therefore, have the potential for significant 

impact on C sequestration in this region, which

accountsfor ~20 percent of annual C sequestration in conterminous U.S. forests (Birdsey and 

Lewis 2002; Bragg et al. 2003). Recent analysis 

demonstrated that a single Category 3 hurricane or severe ice storm could each transfer 

to the decomposable pool the equivalent of 10

percent of the annual U.S. C sequestration, with

subsequent reductions in sequestration caused

by direct stand damage (McNulty 2002; McCarthy et al. 2006b). For example, Hurricanes 

Figure 3.8 Forest damage from Hurricane Katrina. Ricky Layson, Ricky 

Layson Photography, www.forestryimages.org.

Rita and Katrina together damaged a total of 

2,200 ha and 63 million m3 of timber volume 

(Stanturf et al. 2007) which, when decomposed 

over the next several years, will release a total 

of 105 teragrams (Tg) of C into the atmosphere, 

roughly equal to the annual net sink for U.S.

forests (Chambers et al. 2007).

Common forest management practices such 

as fertilization and thinning, forest type, and 

increasing atmospheric CO2 levels can change 

wood and stand properties, and thus may 

change vulnerability to ice storm damage. A 

pine plantation experienced a ~250 g C m-2

reduction in living biomass during a single 

ice storm, equivalent to ~30 percent of the

annual net ecosystem carbon exchange of this 

ecosystem. In this storm at the Duke FACE, 

nitrogen fertilization had no effect on storm 

damage; conifer trees were more than twice 

as likely to be killed by ice storm damages as 

leafless deciduous-broadleaf trees; and thinning increased broken limbs or trees threefold. 

Damage in the elevated CO2 stand was one 

third as much as in the ambient CO2 stand. 

(McCarthy et al. 2006b). Although this result 

suggests that forests may suffer less damage 

in a future ice storm when atmospheric CO2

is higher, future climate may create conditions 

leading to greater ice storm frequency, extent

and severity (da Silva et al. 2006), which may 

balance the decreased sensitivity to ice damage 

under elevated CO2. All of these predictions are 

very uncertain (Cohen et al. 2001).
The U.S. Climate Change Science Program

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Chapter 3

3.2.3.9 Changes in Overstory Species 

 Composition

Several approaches can predict changes in 

biomes (major vegetation assemblages such 

as conifer forests and savanna/woodland) and 

changes in species composition or overstory 

species communities (Hansen et al. 2001a). 

These approaches use either rules that define 

the water balance, temperature, seasonality, etc. 

required for a particular biome, or statistically

link species distributions or community composition with climate envelopes. These efforts 

have mostly focused on equilibrium responses

to climate changes over the next century (Hansen et al. 2001a), so predictions for the next 

several decades are unavailable.

Bachelet et al. (2001) used the Mapped Atmosphere-Plant-Soil System (MAPPS) model with 

the climate predictions generated by seven different global circulation models to predict how 

biome distributions would change with a doubling of CO2 by 2100. Mean annual temperature 

of the United States increased from 3.3 to 5.8 

°C for the climate predictions. Predicted forest 

cover in 2100 declined by an average of 11 percent (range for all climate models was +23 percent to -45 percent). The MAPPS model coupled 

to the projected future climates predicts that 

biomes will migrate northward in the East and 

to higher elevations in the West. For example, 

mixed conifer and mixed hardwood forests in 

the Northeast move into Canada, and decline in 

area by 72 percent (range: -14 to -97 percent), 

but are replaced by eastern hardwoods. In the 

Southeast, grasslands or savannas displace 

forests and move their southern boundaries 

northward, particularly for the warmer climate 

scenarios. In the West, forests displace alpine 

ecosystems, and the wet conifer forests of the 

Northwest decline in area 9 percent (range: 

54 to + 21 percent), while the area of interior 

western pines changes little. Species predictions 

for the eastern United States using a statistical 

approach showed that most species moved north 

60-300 miles (Hansen et al. 2001a).

Authors of these studies cautioned that these 

equilibrium approaches do not reflect the

transient and species-specific nature of the 

community shifts that are projected to occur. 

Success in moving requires suitable climate,

but also dispersal that may lag behind changes 

in climate (Hansen et al. 2001a). Some species 

will be able to move quicker than others, and

some biomes and communities may persist until 

a disturbance allows changes to occur (Hansen 

et al. 2001a). Because trees are long-lived and 

may tolerate growing conditions outside of their 

current climate envelopes, they may be slower 

to change than modeled (Loehle and LeBlanc 

1996). The authors of these studies agreed that 

while climate is changing, novel ecosystems 

will arise – novel because some species will 

persist in place, some species will depart, and 

new species will arrive.

3.2.4 Indicators and Observing

Systems

3.2.4.1 Characteristics of Observing 

Systems

Many Earth observing systems (Bechtold and 

Patterson 2005; Denning 2005) are designed 

to allow for integration of multiple kinds of 

observations using a hierarchical approach that 

takes advantage of the characteristics of each. 

A typical system uses remote sensing to obtain 

a continuous measurement over a large area, 

coupled with statistically-designed field surveys 

to obtain more detailed data at a finer resolution. Statistically, this approach (known as 

“multi-phase” sampling) is more efficient than 

sampling with just a single kind of observation 

or conducting a complete census (Gregoire and 

Valentine, in press). Combining observed data 

with models is also common because often the 

variable of interest cannot be directly observed, 

but observation of a closely-related variable 

may be linked to the variable of interest with 

a model. Model-data synthesis is often an essential component of Earth observing systems 

(Raupach et al. 2005).

To be useful, the system must observe a number 

of indicators more than once over a period, and 

also cover a large enough spatial scale to detect 

a change. The length of time required to detect

a change with a specified level of precision 

depends on the variability of the population 

being sampled, the precision of measurement, 

and the number of samples (Smith 2004). Nonclimatic local factors, such as land use change, 

tend to dominate vegetation responses at small 

scales, masking the relationship with climate 

(Parmesan and Yohe 2003). A climate signal is 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

therefore more likely to be revealed by analyses 

that can identify trends across large geographic 

regions (Walther et al. 2002).

The relationship between biological observations and climate is correlational; thus, it is difficult to separate the effects of climate change 

from other possible causes of observed effects 

(Walther et al. 2002). Inference of causation can 

be determined with carefully controlled experiments that complement the observations. Yet, 

observation systems can identify some causal 

relationships and therefore have value in developing climate impact hypotheses. Schreuder and 

Thomas (1991) determined that if both the potential cause and effect variables were measured 

at inventory sample plots, a relationship could 

be established if the variables are measured 

accurately, estimated properly, and based on a 

large enough sample. But, in practice, additional 

information is often needed to strengthen a 

case – for example, a complementary controlled 

experiment to verify the relationship.

3.2.4.2 Indicators of Climate Change

 Effects

The species that comprise communities respond both physiologically and competitively 

to climate change. One scheme for assessing 

the impacts of climate change on species and 

communities is to assess the effects on: (1) 

the physiology of photosynthesis, respiration, 

and growth; (2) species distributions; and (3) 

phenology, particularly life cycle events such 

as timing of leaf opening. There may also be 

effects on functions of ecosystems such as 

hydrologic processes.

Effects on physiology

Net primary productivity is closely related to 

indices of “greenness” and can be detected by 

satellite over large regions (Hicke et al. 2002b). 

Net ecosystem productivity (NEP) can be measured on the ground as changes in carbon stocks 

in vegetation and soil (Boisvenue and Running 

2006). Root respiration and turnover are sensitive to climate variability and may be good 

indicators of climate change if measured over 

long enough time periods (Atkin et al. 2000; 

Gill and Jackson 2000). Gradient studies show 

variable responses of growth to precipitation 

changes along elevational gradients (Fagre et 

al. 2003). Climate effects on growth patterns of 

individual trees is confounded by other factors 

such as increasing CO2 and N deposition, so 

response of tree growth is difficult to interpret 

without good knowledge of the exposure to 

many possible causal variables. For example, 

interannual variability in NPP, which can mask 

long-term trends, can be summarized from 

long-term ecosystem studies and seems to be 

related to interactions between precipitation 

gradients and growth potential of vegetation 

(Knapp and Smith 2001).

Effects on species distributions

Climate change affects forest composition and 

geographical distribution, and these changes 

are observable over time by field inventories, 

remote sensing, and gradient studies. Both 

range expansions and retractions are important 

to monitor (Thomas et al. 2006), and population 

extinctions or extirpations are also possible. 

Changes in the range and cover of shrubs and 

trees have been observed in Alaska by field 

studies and remote sensing (Hinzman et al. 

2005). Detecting range and abundance shifts 

in wildlife populations may be complicated by 

changes in habitat from other factors (Warren 

et al. 2001).

Effects on phenology

Satellite and ground systems can document 

onset and loss of foliage, with the key being 

availability of long-term data sets (Penuelas 

and Filella 2001). Growing season was found 

significantly longer in Alaska based on satellite 

normalized difference vegetation index (NDVI) 

records (Hinzman et al. 2005). Schwartz et al. 

(2006) integrated weather station observations 

of climate variables with remote sensing and 

field observations of phenological changes using Spring Index phenology models. However, 

Fisher et al. (2007) concluded that species or 

community compositions must be known to 

use satellite observations for predicting the 

phenological response to climate change.

Effects on natural disturbances and 

mortality

Climate change can affect forests by altering 

the frequency, intensity, duration, and timing

of natural disturbances (Dale et al. 2001). The 

correlation of observations of changes in fire 

frequency and severity with changes in climate

are well documented (e.g., Flannigan et al. 
The U.S. Climate Change Science Program

94

Chapter 3

2000; Westerling et al. 2006), and the inference 

of causation in these studies is established by 

studies of fire and vegetation response, and fire 

behavior models. Similar relationships hold for 

forest disturbance from herbivores and pathogens (Ayres and Lombardero 2000; Logan et al. 

2003b). Tree mortality may be directly caused 

by climate variability, such as in drought (Gitlin 

et al. 2006).

Effects on hydrology

Climate change will affect forest water budgets. 

These changes have been observed over time by 

long-term stream gauge networks and research 

sites. Changes in permafrost and streamflow in 

the Alaskan Arctic region are already apparent 

(Hinzman et al. 2005). There is some evidence 

of a global pattern (including in the United 

States) in response of streamflow to climate 

from stream-gauge observations (Milly et al. 

2005). Inter-annual variation in transpiration of 

a forest can be observed by sap flow measurements (Phillips and Oren 2001; Wullschleger 

et al. 2001).

Causal variables

It is important to have high-quality, spatiallyreferenced observations of climate, air pollution, deposition, and disturbance variables. 

These are often derived from observation 

networks using spatial statistical methods (e.g., 

Thornton et al. 2000).

3.2.4.3 Current Capabilities and Needs

There are strengths and limitations to each kind 

of observation system: intensive monitoring 

sites such as Long Term Ecological Research 

(LTER) sites and protected areas; extensive 

observation systems such as Forest Inventory 

and Analysis (FIA) or the U.S. Geological Survey (USGS) stream gauge network; and remote 

sensing. A national climate observation system 

may be improved by integration under an umbrella program such as the National Ecological Observatory Network (NEON), or Global 

Earth System of Systems (GEOSS) (see Table 

3.1). Also, increased focus on “sentinel” sites 

could help identify early indicators of climate 

effects on ecosystem processes, and provide 

observations of structural and species changes 

(NEON 2006).

Intensive monitoring sites measure many of 

the indicators that are likely to be affected by 

climate change, but have mostly been located 

independently and so do not optimally represent either (1) the full range of forest condition 

variability, or (2) forest landscapes that are 

most likely to be affected by climate change 

(Hargrove et al. 2003). Forest inventories are 

able to detect long-term changes in composition 

and growth, but they are limited in ability to 

attribute observed changes to climate, because 

they were not designed to do so. Additions to 

the list of measured variables and compiling 

potential causal variables would improve the 

inventory approach (The Heinz Center 2002; 

USDA 2003). Remote sensing, when coupled 

with models, can detect changes in vegetationresponse to climate variability (Running et al. 

2004; Turner et al. 2004). Interpretation of remote sensing observations is greatly improved 

by associating results with ground data (Pan 

et al. 2006).

Maintaining continuity of remote sensing observations at appropriate temporal and spatial 

scales must be a high priority. NASA’s Earth 

Science division cannot support continued 

operations of all satellites indefinitely, so it 

becomes a challenge for the community using 

the measurementsto identify long-term requirements for satellites, and provide a long-term 

framework for critical Earth science measurements and products (NASA Office of Earth 

Science 2004).

Another high-priority need is to improve ability 

to monitor the effects of disturbance on forest 

composition and structure, and to attribute 

changes in disturbance regimes to changes in 

climate. This will involve a more coordinated 

effort to compile maps of disturbance events 

from satellite or other observation systems, to 

follow disturbances with in situ observations of 

impacts, and to keep track of vegetation changes 

in disturbed areas over time. There are several 

existing programs that could be augmented to 

achieve this result, such as intensifying the permanent sample plot network of the FIA program 

for specific disturbance events, or working with 

forest regeneration and restoration programs to 

install long-term monitoring plots.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Table 3.1 Current and Planned Observation Systems for Climate Effects on Forests

Observation System Characteristics Reference

Forest Inventory and 

Analysis (U.S. Forest 

Service)

Annual and periodic measurements of forest attributes at a large 

number (more than 150,000) of sampling locations. Historical 

data back to 1930s in some areas.

Bechtold and Patterson 2005

AmeriFlux (Department 

of Energy and other 

Agencies)

High temporal resolution (minutes) measurements of carbon, 

water, and energy exchange between land and atmosphere at 

about 50 forest sites. A decade or more of data available at some 

of the sites. 

http://public.ornl.gov/

ameriflux/

Long Term Ecological 

Research network 

(National Science 

Foundation)

The LTER network is a collaborative effort involving more than 

1,800 scientists and students investigating ecological processes 

over long temporal and broad spatial scales. The 26 LTER Sites 

represent diverse ecosystems and research emphases

www.lternet.edu/

Experimental Forest 

Network (U.S. Forest 

Service)

A network of 77 protected forest areas where long-term 

monitoring and experiments have been conducted.

Lugo 2006

National Ecological 

Observation Network 

The NEON observatory is specifically designed to address 

central scientific questions about the interactions of ecosystems,

climate, and land use.

www.neoninc.org/

Global Terrestrial 

Observing System (GTOS)

GTOS is a program for observations, modeling, and analysis of 

terrestrial ecosystems to support sustainable development.

www.fao.org/gtos/

3.2.5 How Changes in One Resource 

can Affect Other Resources

Disturbances in forests such as fire, insect outbreaks, and hurricanes usually kill some or all of 

the trees and lower leaf area. These reductions 

in forest cover and leaf area will likely change 

the hydrology of the disturbed areas. Studies 

of forest harvesting show that removal of the 

tree canopy or transpiring surface will increase 

water yield, with the increase proportional to 

the amount of tree cover removed (Stednick 

1996). The response will vary with climate and 

species, with wetter climates showing a greater 

response of water yield to tree removal. For all 

studies, average water yield increased 2.5 mm 

for each 1 percent of the tree basal-area removed 

(Stednick 1996). High-severity forest fires can 

increase sediment production and water yield 

as much as 10 to 1000 times, with the largest 

effects occurring during high-intensity summer storms (see review in Benavides-Solorio 

and MacDonald 2001). An insect epidemic can 

increase annual water yield, advance the timing of peak runnoff, and increase base flows 

(Bethlahmy 1974; Potts 1984). Presumably, 

the same effects would occur for trees killed in 

windstorms and hurricanes.

Disturbances can also affect native plant species 

diversity, by allowing opportunities for establishment of non-native invasives, particularly 

if the disturbance is outside of the range of 

variability for the ecosystem (Hobbs and Huenneke 1992). Areas most vulnerable to invasion 

by non-natives are those areas that support the 

highest plant diversity and growth (Stohlgren 

et al. 1999). In the western United States, these 

are generally the riparian areas (Stohlgren et al. 

1998). We expect that disturbances that remove 

forest litter or expose soil (fire, trees tipped over 

by wind) will have the highest risk for admitting 

invasive non-native plants.
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3.3 Arid Lands

3.3.1 Brief Summary of Key Points 

from the Literature

Plants and animals in arid lands live near 

their physiological limits, so slight changes 

in temperature and precipitation will substantially alter the composition, distribution, and 

abundance of species, and the products and 

services that arid lands provide. Observed and 

projected decreases in the frequency of freezing temperatures, lengthening of the frost-free 

season, and increased minimum temperatures 

will alter plant species ranges and shift the 

geographic and elevational boundaries of the 

Great Basin, Mojave, Sonoran, and Chihuahuan 

deserts. The extent of these changes will also 

depend on changes in precipitation and fire. 

Increased drought frequency will likely cause

major changes in vegetation cover. Losses of 

vegetative cover coupled with increases in 

precipitation intensity and climate-induced 

reductions in soil aggregate stability will 

dramatically increase potential erosion rates. 

Transport of eroded sediment to streams coupled with changes in the timing and magnitude 

of minimum and maximum flows will affect 

water quality, riparian vegetation, and aquatic

fauna. Wind erosion will have continental-scale 

impacts on downwind ecosystems, air quality,

and human populations.

The response of arid lands to climate change 

will be strongly influenced by interactions with 

non-climatic factors at local scales. Climate effects should be viewed in the context of these 

other factors, and simple generalizations should 

be viewed with caution. Climate will strongly 

influence the impact of land use on ecosystems and how ecosystems respond. Grazing 

has traditionally been the most extensive land 

use in arid regions. However, land use has significantly shifted to exurban development and 

recreation in recent decades. Arid land response 

to climate will thus be influenced by environmental pressures related to air pollution and 

N-deposition, energy development, motorized 

off-road vehicles, feral pets, and horticultural 

invasives, in addition to grazing.

Non-native plant invasions will likely have 

a major impact on how arid land ecosystems 

respond to climate and climate change. Exotic 

grasses generate large fuel loads that predispose 

arid landsto more frequent and intense fire than

historically occurred with sparser native fuels. 

Such fires can radically transform diverse desert scrub, shrub-steppe, and desert grassland/

savanna ecosystems into monocultures of nonnative grasses. This process is well underway in 

the cold desert region, and is in its early stages 

in hot deserts. Because of their profound impact 

on the fire regime and hydrology, invasive 

plants in arid lands may trump direct climate 

impacts on native vegetation.

Given the concomitant changes in climate, 

atmospheric CO2, nitrogen deposition, and 

species invasions, novel wildland and managed ecosystems will likely develop. In novel 

ecosystems, species occur in combinations, and 

relative abundances that have not occurred previously in a given biome. In turn, novel ecosystems present novel challenges for conservation 

and management.

3.3.2 Observed and Predicted 

Changes or Trends

3.3.2.1 Introduction

Arid lands occur in tropical, subtropical, 

temperate, and polar regions and are defined 

based on physiographic, climatic, and floristic 

features. Arid lands are characterized by low 

(typically <400 mm), highly variable annual 

precipitation, along with temperature regimes 

where potential evaporation far exceeds precipitation inputs. In addition, growing season 

rainfall is often delivered via intense convective 

storms,such thatsignificant quantities of water

run off before infiltrating into soil; precipitation 

falling as snow in winter may sublimate or run 

off during snowmelt in spring while soils are 

frozen. As a result of these combined factors, 

production per unit of precipitation can be low. 

Given that many organisms in arid lands are 

near their physiological limits for temperature 

and water stress tolerance, slight changes in 

temperature and precipitation that affect water 

availability and water requirements could have

substantial ramifications. Thus, predicted transitions toward more arid conditions (e.g., higher 

temperatures that elevate potential evapotranspiration and more intense thunderstorms that 

generate more run off; Seager et al. 2007) have 

the real potential to alter species composition 

Plants and animals 

in arid lands 

live near their 

physiological limits, 

so slight changes in 

temperature and 

precipitation will 

substantially alter 

the composition, 

distribution, and 

abundance of species, 

and the products and 

services that arid 

lands provide.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

and abundance, and the ecosystem goods and 

services that arid lands can provide for humans 

(Field et al. 2007).

The response of arid lands to climate and climate change is contingent upon the net effect of 

non-climatic factors interacting with climate at 

local scales (Figure 3.9). Some of these factors 

may reinforce and accentuate climate effects 

(e.g., livestock grazing); others may constrain, 

offset or override climate effects (e.g., soils, 

atmospheric CO2 enrichment, fire, non-native 

species). Climate effects should thus be viewed 

in the context of other factors, and simple generalizations regarding climate effects should be 

viewed with caution. A literature review of the 

relationship between climate change and land 

use indicate land use change has had a much 

greater effect on ecosystems than has climate 

change; and that the vast majority of land use 

changes have little to do with climate or climate 

change (Dale 1997). Today’s arid lands reflect a 

legacy of historic land uses, and future land use 

practices will arguably have the greatest impact 

on arid land ecosystems in the next two to five 

decades. In the near-term, climate fluctuation 

and change will be important primarily as it influences the impact of land use on ecosystems, 

and how ecosystems respond to land use.

3.3.2.2 Bio-Climatic Setting

Arid lands of the continental United States are 

represented primarily by the subtropical hot 

deserts of the Southwest, and the temperate cold 

deserts of the Intermountain West (Figure 3.2). 

The hot deserts differ primarily with respect 

to precipitation seasonality (Figure 3.10). The 

Mojave desert is dominated by winter precipitation (thus biological activity in the cool season), 

whereas the Chihuahuan desert is dominated by 

summer precipitation (thus biological activity 

during hotter conditions). The hottest of the 

three deserts, the Sonoran, is the intermediate, 

receiving both winter and summer precipitation. The cold deserts are also dominated by 

winter precipitation, much of which falls as 

snow, owing to the more temperate latitudes 

and higher elevations (West 1983). These arid 

land formations are characterized by unique

plants and animals, and if precipitation seasonality changes, marked changes in species and 

functional group composition and abundance 

would be expected.

Figure 3.9 Organizational framework for interpreting climate and climate 

change effects on arid land ecosystems.

Figure 3.10 Mean annual precipitation and its seasonality in three hot deserts (from MacMahon and 

Wagner 1985).

There is broad consensus among climate 

models that the arid regions of the southwestern United States will dry in the 21st century 

and that a transition to a more arid climate is 

already underway. In multimodel ensemble 

means reported by Seager et al. (2007), there 

is a transition to a sustained drier climate that 

begins in the late 20th and early 21st centuries. 

Both precipitation and evaporation are expected 

to decrease, but precipitation is expected to 

decrease more than evaporation leading to an 

overall drier climate. The increasing aridity is 

primarily reduced in winter, when precipitation 

decreases and evaporation remains unchanged 

or slightly reduced. The projected ensemble 
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Chapter 3

median reduction in precipitation reaches 0.1 

mm/day in mid-century, though several models 

show that the decrease could occur in the early 

21st century. A substantial portion of the mean 

circulation contribution, especially in winter, 

is explained by the change in zonal mean flow 

alone, indicating that changes in the Hadley Cell 

and extratropical mean meridional circulation 

are important to the climate of this region.

The Great Basin is a cold desert characterized by limited water resources and periodic 

droughts in which a high proportion of the 

year’s precipitation falls as winter snow (Wagner 2003). Snow-derived runoff provides the 

important water resources to maintain stream 

and river channels that support riparian areas 

and human utilization of this region. In the last 

century, the Great Basin warmed by 0.3° to 

0.6°C and is projected to warm by an additional 

5° to 10°C in the coming century (Wagner 

2003). In the last half-century, total precipitation has increased 6-16 percent and this increase 

is projected to continue in the future (Baldwin 

et al. 2003). The increase in total precipitation 

is offset partially by the decrease in snowpack, 

which in the Great Basin is among the largest 

in the nation (Mote et al. 2005). The onset of 

snow runoff is currently 10–15 days earlier than 

50 years ago, with significant impacts on the 

downstream utilization of this water (Cayan 

et al. 2001; Baldwin et al. 2003; Stewart et al. 

2004). Increased warming is likely to continue 

to accelerate spring snowmelt. Warmer temperatures are also likely to lead to more precipitation falling as rain which would further reduce 

overall snowpack and spring peak flow.

Throughout the dry western United States, 

extreme temperature and precipitation events 

are expected to change in the next century. 

Warm extremes will generally follow increases 

in the mean summertime extremes, while cold 

extremes will warm faster than warm extremes 

(Kharin et al. 2007). As a result, what is currently considered an unusually high temperature (e.g., 20-year return interval) will become 

very frequent in the desert Southwest, occurring every couple of years. On the other hand, 

unusually low temperatures will become increasingly uncommon. As a result winters will 

be warmer, leading to higher evapotranspiration 

and lower snowfall. Changes in precipitation 

are also expected. Precipitation events that are 

currently considered extreme (20-year return 

interval) are also expected to occur roughly 

twice as often as they currently do, consistent 

with general increases in rainstorm intensity 

(Kharin et al. 2007).

Changes in species and functional group composition might first occur in the geographic 

regions where biogeographic formations and 

their major subdivisions interface. Extreme 

climatic events are major determinants of arid 

ecosystem structure and function (Holmgren 

et al. 2006). Thus, while changes in mean temperature will affect levels of physiological stress 

and water requirements during the growing

season, minimum temperatures during winter 

may be a primary determinant of species composition and distribution. In the Sonoran Desert, 

warm season rainfall and freezing temperatures 

strongly influence distributions of many plant 

species (Turner et al. 1995). The vegetation 

growing season, as defined by continuous 

frost-free air temperatures, has increased by 

on average about two days/decade since 1948 in 

the conterminous United States, with the largest 

changes occurring in the West (Easterling 2002; 

Feng and Hu 2004). A recent analysis of climate 

trends in the Sonoran Desert (1960-2000) also 

shows a decrease in the frequency of freezing

temperatures, lengthening of the frost-free 

season, and increased minimum temperatures 

(Weiss and Overpeck 2005). With warming 

expected to continue throughout the 21st century, potential ecological responses may include 

contraction of the overall boundary of the 

Sonoran Desert in the southeast and expansion 

northward, eastward, and upward in elevation, 

and changes to plant species ranges. Realization 

of these changes will be co-dependent on what 

happens with precipitation and disturbance 

regimes (e.g., fire).

The biotic communities that characterize many 

U.S. arid lands are influenced by basin and 

range topography. Thus, within a given bioclimatic zone, communities transition from desert 

scrub and grassland to savanna, woodland, and 

forest along strong elevation gradients (Figure 

3.11). Changes in climate will affect the nature 

of this zonation, with arid land communities 

potentially moving up in elevation in response 

to warmer and drier conditions. Experimental 

The vegetation 

growing season, 

as defined by 

continuous frost-free 

air temperatures, 

has increased by 

on average about 

two days/decade 

since 1948 in the 

conterminous 

United States, with 

the largest changes 

occurring in the 

West.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

data suggest shrub recruitment 

at woodland-grassland ecotones 

will be favored by increases 

in summer precipitation, but 

unaffected by increases in winter precipitation (Weltzin and 

McPherson 2000). This suggests 

that increases in summer precipitation would favor the downslope 

shifts in this ecotone. In the 

Great Basin, favorable climatic 

conditions at the turn of the last 

century enabled expansion of 

woodlands into sagebrush steppe 

(Miller and Rose 1999; Miller et 

al. 2005) and ongoing expansion 

is significantly increasing fuel 

loads and creating conditions for 

catastrophic fire. Plant composition and ecosystem processes 

(e.g., plant growth, water and 

nutrient use, herbivory) change along these 

elevation gradients in a manner that broadly 

mimics changes in ecosystem structure and 

function along continental-scale latitudinal 

gradients (Whittaker 1975). Changes along 

local elevation gradients may therefore be 

early indicators of regional responses to climate 

change (Peters 1992).

3.3.2.3 Climate Influences at Local 

Scales

Climate and atmospheric CO2 influence communities at broad spatial scales, but topography, 

soils, and landform control local variation in 

ecosystem structure and function within a given 

elevation zone, making local vegetation very 

complex. Topography influences water balance 

(south-facing slopes are drier), air drainage and 

night temperatures, and routing of precipitation. 

Soil texture and depth affect water capture, 

water storage, and fertility (especially nitrogen). 

These factors strongly interact with precipitation to limit plant production and control species composition. Plants that can access water 

in deep soil or in groundwater depend less on 

precipitation for growth and survival, but such 

plants may be sensitive to precipitation changes 

that affect the recharge of deep water stores. 

If the water table increases with increases in 

rainfall or decreased plant cover, soil salinity 

may increase and adversely affect vegetation 

in some bottomland locations (McAuliffe 

Figure 3.11 Elevation life zones along an arid land elevation gradient (from Brown 1994).

2003). To predict vegetation response to climate 

change, it is necessary to understand these 

complex relationships among topography, soil, 

soil hydrology, and plant response.

3.3.2.4 Climate and Disturbance

Disturbances such as fire and grazing are 

superimposed against the backdrop of climate 

variability, climate change, and spatial variation 

in soils and topography. The frequency and

intensity of a given type of disturbance will 

determine the relative abundance of annual, perennial, herbaceous, and woody plants on a site. 

Extreme climate events such as drought may act 

as triggers to push arid ecosystems experiencing chronic disturbances, such as grazing, past 

desertification ‘tipping points’ (CCSP 4.2 2008; 

Gillson and Hofffman 2007). An increase in 

the frequency of climate trigger events would

make arid systems increasingly susceptible to 

major changes in vegetation cover. Climate is 

also a key factor dictating the effectiveness of 

resource management plans and restoration efforts (Holmgren and Scheffer 2001). Precipitation (and its interaction with temperature) plays 

a major role in determining how plant communities are impacted by, and how they respond 

to, a given type and intensity of disturbance. It 

is generally accepted that effects of grazing in 

arid lands may be somewhat mitigated in years 

of good rainfall and accentuated in drought 

years. However, this generalization is context 
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Chapter 3

dependent. Landscape-scale factors such as 

rainfall and stocking rate affect grass cover in 

pre- and post-drought periods, but grass dynamics before, during, and after drought varies with 

species-specific responses to local patch-scale 

factors (e.g., soil texture, micro-topographic 

redistribution of water) (Yao et al. 2006). As a 

result, a given species may persist in the face 

of grazing and drought in some locales and be 

lost from others. Spatial context should thus 

be factored in to assessments of how changes 

in climate will affect ecosystem stability: 

their ability to maintain function in the face 

of disturbance (resistance), and the rate and 

extent to which they recover from disturbance 

(resilience). Advances in computing power, 

geographic information systems, and remote 

sensing now make this feasible.

Chronic disturbance will also affect rates of 

ecosystem change in response to climate change 

because it reduces vegetation resistance to slow, 

long-term changes in climate (Cole 1985; Overpeck et al. 1990). Plant communities dominated 

by long-lived perennials may exhibit considerable biological inertia, and changes in community composition may lag behind significant 

changesin climate. Conditionsrequired forseed

germination are largely independent of conditions required for subsequent plant survival

(Miriti 2007). Species established under previous climate regimes may thus persist in novel 

climates for long periods of time. Indeed, it has 

been suggested that the desert grasslands of the 

Southwest were established during the cooler, 

moister Little Ice Age but have persisted in the 

warmer, drier climates of the 19th and 20th centuries (Neilson 1986). Disturbances can create 

opportunities for species better adapted to the 

current conditions to establish. In the case of 

desert grasslands, livestock grazing subsequent

to Anglo-European settlement may have been a 

disturbance that created opportunities for desert shrubs such as mesquite and creosote bush

to increase in abundance. Rates of ecosystem 

compositional change in response to climate 

change may therefore depend on the type and 

intensity of disturbance, and the extent to which 

fundamental soil properties (especially depth 

and fertility) are altered by disturbance.

3.3.2.5 Desertification

Precipitation and wind are agents of erosion. 

Wind and water erosion are primarily controlled 

by plant cover. Long-term reductions in plant 

cover by grazing and short-term reductions 

caused by fire create opportunities for accelerated rates of erosion; loss of soils feeds back 

to affect species composition in ways that can 

further reduce plant production and cover. Disturbances in arid lands can thus destabilize sites 

and quickly reduce their ability to capture and

retain precipitation inputs. This is the fundamental basis for desertification, a long-standing 

concern (Van de Koppel et al. 2002). Desertification involves the expansion of deserts into 

semi-arid and subhumid regions, and the loss of 

productivity in arid zones. It typically involves 

loss of ground cover and soils, replacement 

of palatable, mesophytic grasses by unpalatable xerophytic shrubs, or both (Figure 3.12). 

There has been long-standing controversy in 

determining the relative contribution of climatic and anthropogenic factors as drivers of 

desertification. Local fence line contrasts argue 

for the importance of land use (e.g., changes 

in grazing, fire regimes); vegetation change in 

areas with no known change in land use argue 

for climatic drivers.

Grazing has traditionally been the most pervasive and extensive climate-influenced land 

use in arid lands (with the exception of areas 

where access to ground or surface water allows agriculture; see Chapter 2). Large-scale, 

unregulated livestock grazing in the 1800s and 

early 1900s is widely regarded as contributing 

to widespread desertification (Fredrickson et al. 

1998). Grazing peaked around 1920 on public 

lands in the West, and by the 1970s had been 

reduced by approximately 70 percent (Holechek 

et al. 2003). These declines reflect a combination of losses in carrying capacity (ostensibly 

associated with soil erosion and reductions in 

the abundance of palatable species); the creation 

of federally funded experimental ranges in the 

early 1900s (e.g., the Santa Rita Experimental 

Range in Arizona, and the Jornada Experimental Range in New Mexico, which are charged 

with developing stocking rate guidelines); the 

advent of the science of range management; 

federal legislation intended to regulate grazing 

(Taylor Grazing Act of 1934) and combat soil 

There has been 

long-standing 

controversy in 

determining the 

relative contribution 

of climatic and 

anthropogenic 

factors as drivers of 

desertification. 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

erosion (Soil Erosion Act 1935); and the shift 

of livestock production operations to higher 

rainfall regions.

Arid lands can be slow to recover from livestock 

grazing impacts. Anderson and Inouye (2001) 

found that at least 45 years of protection was 

required for detectable recovery of herbaceous

perennial understory cover in cold desert sagebrush steppe. Development of warmer, drier climatic conditions would be expected to further 

slow rates of recovery. On sites where extensive 

soil erosion or encroachment of long-lived 

shrubs occurs, recovery from grazing may not 

occur over time frames relevant to ecosystem 

management. While livestock grazing remains 

an important land use in arid lands, there has 

been a significant shift to exurban development 

and recreation, reflecting dramatic increases in 

human population density since 1950 (Hansen 

and Brown 2005). Arid land response to future 

climate will thus be mediated by new suites of 

environmental pressures such as air pollution 

and N-deposition, energy development, motorized off-road vehicles, feral pets, and invasion 

of non-native horticultural plants and grazing.

Figure 3.12 Desertification of desert grassland (Santa Rita Experimental Range [SRER] near Tucson, AZ).

Collage developed by Rob Wu from photos in the SRER photo archives (http://ag.arizona.edu/SRER/).

3.3.2.6 Biotic Invasions

Arid lands of North America were historically characterized by mixtures of shrublands, 

grasslands, shrub-steppe, shrub-savanna, and 

woodlands. Since Anglo-European settlement, 

shrubs and trees have increased at the expense 

of grasses (Archer 1994). Causes for this shift 

in plant-life-form abundance are the topic of 

active debate, but center around climate change, 

atmospheric CO2 enrichment, nitrogen deposition, and changes in grazing and fire regimes 

(Archer et al. 1995; Van Auken 2000). In many 

cases, increases in woody plant cover reflect the 

proliferation of native shrubs or trees(mesquite,

creosote bush, pinyon, juniper); in other cases, 

non-native shrubs have increased in abundance 

(tamarix). Historically, the displacement of 

grasses by woody plants in arid lands was of 

concern due to its perceived adverse impacts on 

stream flow and ground water recharge (Wilcox 

2002; Owens and Moore 2007) and livestock 

production. More recently, the effects of this 

change in land cover has been shown to have 

implications for carbon sequestration, and land

surface-atmosphere interactions (Schlesinger 

et al. 1990; Archer et al. 2001; Wessman et 
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Chapter 3

al. 2004). Warmer, drier climates with more 

frequent and intense droughts are likely to favor xerophytic shrubs over mesophytic native 

grasses, especially when native grasses are 

preferentially grazed by livestock. However, 

invasions by non-native grasses are markedly 

changing the fire regime in arid lands and impacting shrub cover.

In arid lands of the United States, non-native 

grasses often act as “transformer species” 

(Richardson et al. 2000; Grice 2006) in that 

they change the character, condition, form or 

nature of a natural ecosystem over substantial 

areas. Land use and climate markedly influence the probability, rate, and pattern of alien 

species invasion, and future change for each of 

these drivers will interact to strongly impact 

scenarios of plant invasion and ecosystem 

transformation (Sala et al. 2000; Walther et 

al. 2002; Hastings et al. 2005). Plant invasions 

are strongly influenced by seed dispersal and 

resource availability, but disturbance and abrupt 

climatic changes also play key roles (Clarke et 

al. 2005). Changes in ecosystem susceptibility 

to invasion by non-native plants may be expected with changes in climate (Ibarra et al. 1995; 

Mau-Crimmins et al. 2006), CO2 (Smith et al 

2000; Nagel et al. 2004) and nitrogen deposition (Fenn et al. 2003). Invasibility varies across 

elevation gradients. For cheatgrass, a common 

exotic annual in the Great Basin, invasibility 

is related to temperature at higher elevations 

and soil water availability at lower elevations. 

Increased variability in soil moisture and reductions in perennial herbaceous cover also 

increased susceptibility of low elevation sites to 

cheatgrass invasion (Chambers et al 2007). In a 

45-year study of cold desert sagebrush steppe 

that included the major drought of the 1950s, 

abundance of native species was found to be 

an important factor influencing community 

resistance to invasion (Anderson and Inouye 

2001). Thus, maintenance of richness and cover 

of native species should be a high management 

priority in the face of climate change (see also 

Chapter 5, this report).

Non-native plant invasions, promoted by enhanced nitrogen deposition (Fenn et al. 2003) 

and increased anthropogenic disturbance 

(Wisdom et al. 2005), will have a major impact on how arid land ecosystems respond to 

climate and climate change. Once established, 

non-native annual and perennial grasses can 

generate massive, high-continuity fine-fuel 

loads that predispose arid lands to fires more 

frequent and intense than those with which they

evolved (Figure 3.13). The result is the potential 

for desert scrub, shrub-steppe, and desert grassland/savanna biotic communities to be quickly

and radically transformed into monocultures 

of invasive grasses over large areas. This is 

already well underway in the cold desert region 

(Knapp 1998) and is in its early stages in hot 

deserts (Williams and Baruch 2000; Kupfer 

and Miller 2005; Salo 2005; Mau-Crimmins 

2006). By virtue of their profound impact on 

the fire regime and hydrology, invasive plants 

in arid lands will very likely trump direct climate impacts on native vegetation where they 

gain dominance (Clarke et al. 2005). There is a 

strong climate-wildfire synchrony in forested 

ecosystems of western North America (Kitzberger et al. 2007); longer fire seasons and more 

frequent episodes of extreme fire weather are

predicted (Westerling et al. 2006). As the areal 

extent of fire-prone exotic grass communities 

increases, low elevation arid ecosystems will 

likely experience similar climate-fire synchronization where none previously existed, and 

spread of low elevation fires upslope may constitute a new source of ignition for forest fires. 

Exurban development (Nelson 1992; Daniels 

1999) has been and will continue to be a major 

source for both ignitions (Keeley et al. 1999) 

and exotic species introductions by escape from 

horticulture.

3.3.2.7 A Systems Perspective

As reviewed in the preceding sections, the 

response of arid lands to climate and climate 

change is contingent upon the net outcome 

of several interacting factors (Fig 3.9). Some 

of these factors may reinforce and accentuate 

climate effects (e.g., soils, grazing); others 

may constrain, offset or override climate effects (soils, atmospheric CO2 enrichment, fire, 

exotic species). Furthermore, extreme climatic 

events can themselves constitute disturbance 

(e.g., soil erosion and inundation associated 

with high intensity rainfall events and flooding; burial abrasion and erosion associated with 

high winds, mortality caused by drought and 

extreme temperature stress). Climate effects 

should thus be viewed in the context of other 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 3.13 Top-down view of native big sagebrush steppe (right) invaded by 

cheatgrass, an exotic annual grass (left). Photo: Steve Whisenant.

factors, and simple generalizations regarding 

climate effects should be viewed with caution. 

This is not to say, however, that there is insufficient data and theory to guide prediction of 

future outcomes. Today’s arid lands reflect a 

legacy of historic land uses, and future land use 

practices will arguably have the greatest impact 

on arid land ecosystems in the next two to five 

decades. In the near-term, climate fluctuation 

and change will be important primarily as it 

influences the impact of land use on ecosystems 

and how ecosystems respond to land use. Given 

the concomitant changes in climate, disturbance 

frequency/intensity, atmospheric CO2, nitrogen 

deposition, and species invasions, it also seems 

likely that novel wildland and managed ecosystems will develop (Hobbs et al. 2006). Communities that are compositionally unlike any 

found today have occurred in the late-glacial 

past (Williams and Jackson 2007). In climate 

simulations for the IPCC emission scenarios, 

novel climates arise by 2100 AD. These future 

novel climates (which are warmer than any 

present climates, with spatially variable shifts 

in precipitation) increase the risk of species 

reshuffling into future novel communities 

and other ecological surprises (Williams and 

Jackson 2007). These novel ecosystems will 

present novel challenges and opportunities for 

conservation and management.

The following sections will address specific 

climate/land use/land cover issues in more 

detail. Section 3.10 will discuss climate and 

climate change effects on species distributions and community dynamics. Section 3.11 

will review the consequences for ecosystem

processes. Section 3.12 will focus on climate 

change implications for structure and function 

of riparian and aquatic ecosystemsin arid lands.

Implications for wind and water erosion will be 

reviewed in Section 3.13.

3.3.3 Species Distributions and

Community Dynamics

3.3.3.1 Climate-Fire Regimes

The climate-driven dynamic of the fire cycle 

is likely to become the single most important 

feature controlling future plant distributions in 

U.S. arid lands. Rising temperatures, decreases 

in precipitation and a shift in seasonality and 

variability, and increases in atmospheric CO2

and nitrogen deposition (Sage 1996), coupled 

with invasions of exotic grasses (Brooks et al. 

2004; Brooks and Berry 2006) will accelerate 

the grass-fire cycle in arid lands and promote 

development of near monoculture stands of 

invasive plants (D’Antonio and Vitousek 1992). 

The frequency of fire in the Mojave Desert has

dramatically increased over the past 20 years 

and effected a dramatic conversion of desert 

shrubland to degraded annual-plant landscapes 

(Bradley et al. 2006; Brooks and Berry 2006). 

Given the episodic nature of desert plant establishment and the high susceptibility of the new 

community structure to additional fire, it will 

be exceedingly difficult to recover native plant 

dominance. A similar conversion has occurred 

in many Great Basin landscapes (Knapp 1995, 

1996), and given the longer period of non-native 

annual plant presence (Novak and Mack 2001), 

the pattern is much more advanced and has 

lowered ecosystem carbon storage (Bradley 

et al. 2006). Contemporary patterns in natural 

settings (Wood et al. 2006) and field experiments (Smith et al. 2000) suggest non-native 

response to climate change will be extremely 

important in the dynamics of arid land fire 

cycle, and changes in climate that promote fires 

will exacerbate land cover change in arid and 

semi-arid ecosystems.

There is some debate as to how climate contributed to a non-native component of this 

vegetation-disturbance cycle over the first half 

of the 20th century. For the upper elevations 

in the Sonoran Desert, Lehmann lovegrass, 

a perennial C4 African grass introduced for 
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Chapter 3

cattle forage and erosion control, has spread 

aggressively and independently of livestock 

grazing (McClaran 2003). Its success relative 

to native grasses appears related to its greater 

seedling drought tolerance and its ability to 

more effectively utilize winter moisture. Relatively wet periods associated with the Pacific 

Decadal Oscillation appear to have been more 

important than increases in N-deposition or 

CO2 concentrations in the spread of these species (Salo 2005).

More recently, warm, summer-wet areas in 

northern Mexico (Sonora) and the southwestern 

United States have become incubators for perennial C4 African grasses such as buffelgrass, 

purposely introduced to improve cattle forage 

in the 1940s. These grasses escape plantings 

on working ranches and, like exotic annual 

grasses, initiate a grass-fire cycle (Williams 

and Baruch 2000). In the urbanized, tourismdriven Sonoran Desert of southern Arizona, 

buffelgrass invasion is converting fireproof 

and picturesque desert scrub communities into

monospecific, flammable grassland. Buffelgrass, like other neotropical exotics, is sensitive 

to low winter temperatures. The main invasion 

of buffelgrass in southern Arizona happened 

with warmer winters beginning in the 1980s, 

and its range will extend farther north and 

upslope as minimum temperatures continue to 

increase (Arriaga et al. 2004). This is complicated further by ongoing germplasm research 

seeking to breed more drought- and coldresistant varieties. For example, a cold-resistant 

“Frio” variety of buffelgrass recently released 

by USDA-Agricultural Research Service has 

been planted 40 km south of the Arizona border near Cananea, Mexico. Escape of “Frio” 

north of the United States-Mexico border may 

extend the potential niche of buffelgrass a few 

hundred meters in elevation and a few hundred 

kilometers to the north.

3.3.3.2 Drought and Vegetation 

Structure

Over the past 75 years, the drought of the 1950s 

and the drought of the early 2000s represent two 

natural experiments for understanding plant 

community response to future environmental 

conditions. While both had similar reductions in 

precipitation, the 1950s drought was typical of 

many Holocene period droughts throughout the 

Southwest, whereas the drought that spanned 

the beginning of the 21st century was relatively 

hot (with both greater annual temperatures 

and greater summer maximum temperatures) 

(Mueller et al. 2005; Breshears et al. 2005). The 

1950s drought caused modest declines in the 

major shrubs in the Sonoran Desert, whereas 

the 2000s drought caused much higher mortality rates in numerous species, including the 

long-lived C3 creosote bush, which had shown 

essentially no response to the 1950s drought 

(Bowers 2005). A similar pattern was seen in 

comparing the two time periods for perennial 

species in the Mojave Desert, where dry periods 

close to the end of the 20th century were associated with reductions in C3 shrubs and both 

C3 and C4 perennial grass species (Hereford et 

Figure 3.14 Buffelgrass invasion of saguaro stand in the Tucson Mountains, 

Arizona (left); fire-damaged saguaro (right). Photos courtesy Ben Wilder.
105

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

al. 2006). Thus, the greater temperatures and 

higher rates of evapotranspiration predicted 

to co-occur with drought portend increased 

mortality for the dominant woody vegetation 

typical of North American deserts, and open 

the door for establishment of non-native annual 

grasses. These patterns are mostly driven by 

changes in winter precipitation, but in systems 

where summer rainfall is abundant, woody 

plant-grass interactions may also be important. 

Given the projected increases in the frequency

of these “global warming type” droughts (e.g., 

Breshears et al. 2005), increases in summer active, non-native C4 grasses (such as buffelgrass 

in the Sonoran Desert (Franklin et al. 2006), and 

the increased probability of fire (Westerling et 

al. 2006), a similar pattern of a wide-spread 

woody vegetation conversion to degraded nonnative grasslands can be anticipated for the hot 

deserts of North America – a pattern similar to 

that already seen in the Great Basin (Bradley 

et al. 2006).

3.3.3.3 Plant Functional Group

 Responses

Annual plants are a major source of plant diversity in the North American deserts (Beatley 

1967), but exotic annuals are rapidly displacing 

native annuals. The density of both native and 

non-native desert annuals in the Sonoran Desert, at Tumamoc Hill in Tucson, AZ, has been 

reduced by an order of magnitude since 1982 

(from ~2,000 plants/m-2 to ~150/plants m-2) 

(Venable and Pake 1999). Similar reductions 

have been recorded for the Nevada Test Site 

(Rundel and Gibson 1996). At the same time, 

there has been an increase in the number of 

non-native annual species (Hunter 1991; Salo 

et al. 2005; Schutzenhofer and Valone 2006). 

High CO2 concentrations appear to benefit nonnative grasses and “weeds” more so than native 

species (Huxman and Smith 2001; Ziska 2003; 

Nagel et al. 2004). Thus, when rainfall is relatively high in the Mojave Desert, non-natives 

comprise about 6 percent of the flora and ~66 

percent of the community biomass, but when 

rainfall is restricted, they comprise ~27 percent 

of the flora and >90 percent of the biomass 

(Brooks and Berry 2006). Competition between 

annuals and perennials for soil nitrogen during 

relatively wet periods can be intense (Holzapfel 

and Mahall 1999). At the western fringe of the 

Mojave and Sonoran Deserts, nitrogen deposition is tipping the balance toward the annual 

plant community (typically non-native) with the 

resulting loss of woody native species (Wood 

et al. 2006).

Based on theory and early experiments, rising 

atmospheric CO2 and increasing temperature 

are predicted to increase the competitive ability 

of C3 versus C4 plants in water-limited systems, 

potentially reducing the current pattern of C4

dominance in many warm season semi-arid 

ecosystems (Long 1991; Ehleringer et al. 1997; 

Poorter and Navas 2003). Photosynthesis and 

stomatal conductance of leaves of plants in 

mixed C3/C4 communities often show a greater 

proportional response in C3 as compared to C4

species at elevated CO2 (Polley et al. 2002). 

However, community composition and productivity do not always reflect leaf level patterns 

and more sophisticated experiments show 

complex results. It is likely that whole-system 

water budgets are significantly altered and more 

effectively influence competitive interactions 

between C3 and C4 species as compared to any 

direct CO2 effects on leaf function (Owensby 

et al. 1993; Polley et al. 2002). In the Great 

Basin, which is dominated by C3 plants, CO2

enrichment favors non-native annual cheatgrass 

over native C3 plants (Smith et al. 2000; Ziska 

et al. 2005).

Where C3 species have increased in abundance 

in elevated CO2 experiments (Morgan et al. 

2007), the photosynthetic pathway variation 

also reflected differences in herbaceous (C4) 

and woody (C3) life forms. CO2 enhancement 

of C3 woody plant seedling growth, as compared to growth of C4 grasses, may facilitate 

woody plant establishment (Polley et al. 2003). 

Reduced transpiration rates from grasses under 

higher CO2 may also allow greater soil water 

recharge to depth, and favor shrub seedling 

establishment (Polley et al. 1997). Changes in 

both plant growth and the ability to escape the 

seedling-fire-mortality constraint are critical for 

successful shrub establishment in water-limited 

grasslands (Bond and Midgley 2000). However, 

interactions with other facets of global change 

may constrain growth form and photosynthetic 

pathway responses to CO2 fertilization. Increased winter temperatures would lengthen the 

C4 growing season. Greater primary production at elevated CO2 combined with increased 

Based on theory and 

early experiments, 

rising atmospheric 

CO2 and increasing 

temperature are 

predicted to increase 

the competitive 

ability of C3 versus 

C4 plants in waterlimited systems, 

potentially reducing 

the current pattern of 

C4 dominance in many 

warm season semiarid ecosystems.
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Chapter 3

abundance of non-native grass species may 

alter fire frequencies (see sections 3.2.2.6 and

3.3.3.1 and 3.3.4.1). Nitrogen deposition may 

homogenize landscapes, favoring grassland 

physiognomies over shrublands (Reynolds et 

al. 1993). Changes in the occurrence of episodic 

drought may alter the relative performance of 

these growth forms in unexpected ways (Ward 

et al. 1999). Predicting changes in C3 versus C4

dominance, or changes in grass versus shrub 

abundance in water-limited ecosystems, will 

require understanding of multifactor interactions of global change the scientific community 

does not yet possess.

3.3.3.4 Charismatic Mega Flora

Saguaro density is positively associated with 

high cover of perennial vegetation and mean 

summer precipitation, but total annual precipitation and total perennial cover are the 

best predictors of reproductive stem density 

(Drezner 2006). Because of how these drivers 

co-vary in the southwestern United States, the 

drier western regions have lower saguaro densities than the southeastern region where summer 

rainfall is greater. Additionally, the Northeast 

and Southeast both have very high reproductive stem densities relative to the West. These 

patters reflect the interaction between summer 

rainfall and the frequency of episodic freezing events that constrain the species’ northern 

range boundary. Despite predicted reductions 

in the number of freezing events (Weiss and 

Overpeck 2005), predicted increases in annual 

temperature, loss of woody plant cover from a 

greater frequency of “global warming-type”

droughts, and increasing fire resulting from 

non-native grass invasions (Figure 3.14) suggest a restriction of the Saguaro’s geographic 

range and reductions in abundance within its 

historic range.

The direct effects of rising CO2 on climatic 

tolerance and growth of Joshua trees also suggest important shifts in this Mojave Desert 

species’ range (Dole et al. 2003). Growth at 

elevated CO2 improves the ability of seedlings 

to tolerate periods of cold temperature stress 

(Loik et al. 2000). When applied to downscale 

climate outputs and included in the rules that 

define species distribution, this direct CO2 effect suggests the potential for a slight increase in 

geographic range. However, like all long-lived, 

large-statured species in the North American 

deserts, the frequency of fire will be a primary

determinant of whether this potential will be 

realized.

3.3.4 Ecosystem Processes

3.3.4.1 Net Primary Production and 

 Biomass

Semi-arid and arid ecosystems of the western 

United States are characterized by low plant 

growth (NPP), ranging from 20 to 60 g/m2/yr in 

the Mojave Desert of Nevada (Rundel and Gibson 1996) to 100 to 200 g/m2/yr (aboveground) 

in the Chihuahuan Desert of New Mexico 

(Huenneke et al. 2002). In most studies, the belowground component of plant growth is poorly 

characterized, but observations of roots greater 

than 9 meters deep suggest that root production 

could be very large and perhaps underestimated 

in many studies (Canadell et al. 1996).

With water as the primary factor limiting plant 

growth, it is not surprising that the variation 

in plant growth among desert ecosystems, or 

year-to-year variation within arid ecosystems, is 

related to rainfall. High spatial and interannual 

variation make it difficult to identify trends in 

aboveground net primary production (ANPP) 

over time, especially when disturbances such 

as livestock gazing co-occur as an additional 

confounding factor. In their comparison of cold 

desert sagebrush steppe vegetation structure 

and production during two 10-year studies from 

the late 1950s to the late 1960s and three years 

in the 1990s, West and Yorks (2006) noted high 

coefficients of variation in aboveground plant 

production associated with five-fold differences 

in precipitation at a given locale, sometimes in 

consecutive years. In the Chihuahuan Desert, 

shrub encroachment into desert grassland has 

increased the spatial heterogeneity of ANPP 

and soil nutrients (Schlesinger and Pilmanis 

1998; Huenneke et al. 2002). Although grasslands tended to support higher ANPP than did 

shrub-dominated systems, grasslands demonstrated higher interannual variation. Projected 

increases in precipitation variability coupled 

with changes in species composition would be 

expected to further increase the already substantial variation in arid land plant production. 

Other factors, such as soil texture and landscape 

position, also affect soil moisture availability 

and determine plant growth in local conditions 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

(Schlesinger and Jones 1984; Wainwright et al. 

2002). Increases in temperature and changes 

in the amount and seasonal distribution of precipitation in cold deserts (Wagner 2004) and hot 

deserts (Seager et al. 2007) can be expected to 

have a dramatic impact on the dominant vegetation, NPP, and carbon storage in arid lands.

Jackson et al. (2002) found that plant biomass 

and soil organic matter varied systematically 

in mesquite-dominated ecosystems across west

Texas and eastern New Mexico, demonstrating 

some of the changes that can be expected with 

future changes in rainfall regimes. The total 

content of organic matter (plant + soil) in the 

ecosystem was greatest at the highest rainfall, 

but losses of soil carbon in the driest sites were 

compensated by increases in plant biomass, 

largely mesquite. Despite consistent increases

in aboveground carbon storage with woody 

vegetation encroachment, a survey of published 

literature revealed no correlation between mean 

annual rainfall and changes in soil organic carbon poolssubsequent to woody plant encroachment (Asner and Archer in press). Differences 

in soil texture, topography, and historical land 

use across sites likely confound assessments of 

precipitation influences on soil organic carbon 

pool responses to vegetation change.

3.3.4.2 Soil Respiration

Soil respiration includes the flux of CO2 from 

the soil to the atmosphere from the combined 

activities of plant roots and their associated 

mycorrhizal fungi and heterotrophic bacteria 

and fungi in the soil. It is typically measured 

by placing small chambers over replicated plots 

of soil or estimated using eddy-covariance 

measurements of changes in atmospheric properties, particularly at night. Soil respiration is 

the dominant mechanism that returns plant 

carbon dioxide to Earth’s atmosphere, and it 

is normally seen to increase with increasing 

temperature. Mean soil respiration in arid and 

semi-arid ecosystems is 224 g C/m2/yr (Raich 

and Schlesinger 1992; Conant et al. 1998), 

though in individual sites, it can be expected 

to vary with soil moisture content during and 

between years.

Intensification of the hydrologic cycle due to atmospheric warming is expected reduce rainfall 

frequency, but increase the intensity and/orsize

of individual precipitation events. A change in 

the size-class distribution of precipitation has 

important implications for instantaneous fluxes 

of carbon dioxide from soils and the potential 

for ecosystems to sequester carbon (Austin et

al. 2004; Huxman et al. 2004a; Jarvis et al. 

2007). This is due to differences in the way 

soil microbial populations and plants respond 

to moisture entering the soil following rainfall 

events of different sizes. Larger rainfall events 

that increase the wetting depth in the soil 

profile should increase the number of periods 

within a year where substantial plant activity 

and carbon storage can occur (Huxman et al. 

2004b; Pereira et al. 2007; Kurc and Small 

2007; Patrick et al. 2007). However, reducing 

the frequency of wet-dry cycles in soils will

retard microbial activity and nutrient cycling, 

likely introducing a long-term nitrogen limitation to plant growth (Huxman et al. 2004a). For 

winter rainfall ecosystems, these shifts in wetdry cycles can cause reductions in productivity 

and soil carbon sequestration (Jarvis et al. 2007;

Pereira et al. 2007).

3.3.4.3 Net Carbon Balance

The net storage or loss of carbon in any ecosystem is the balance between carbon uptake by 

plants (autotrophic) and the carbon released by 

plant respiration and heterotrophic processes. 

Although elegant experiments have attempted 

to measure these components independently, 

the difference between input and output is 

always small and thus measurement errors can 

be proportionately large. It is usually easier to 

estimate the accumulation of carbon in vegetation and soils on landscapes of known age. This 

value, NEP, typically averages about 10 percent 

of NPP in forested ecosystems. Arid soils 

contain relatively little soil organic matter, and 

collectively make only a small contribution to 

the global pool of carbon in soils (Schlesinger 

1977; Jobbagy and Jackson 2002). Given the 

low NPP of arid lands, they are likely to result 

in only small amounts of carbon sequestration.

Since soil organic matter is inversely related to 

mean annual temperature in many arid regions 

(Schlesinger 1982; Nettleton and Mays 2007), 

anticipated increases in regional temperature 

will lead to a loss of soil carbon to the atmosphere, exacerbating increases in atmospheric 

carbon dioxide. Recent measurements of NEP 

by micrometeorological techniques, such as

Given the low 

NPP of arid lands, 

they are likely to 

result in only small 

amounts of carbon 

sequestration.
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Chapter 3

eddy covariance, across relatively large spatial 

scales confirm this relatively low carbon uptake 

for arid lands (Grunzweig et al. 2003), but point 

to the role of life-form (Unland et al. 1996), 

seasonal rainfall characteristics (Hastings et al. 

2005; Ivans et al. 2006), and potential access 

to groundwater as important modulators of the 

process (Scott et al. 2006).

Several scientists have suggested that arid lands 

might be managed to sequester carbon in soils

and mitigate future climate change (Lal 2001). 

The prospects for such mitigation are limited 

by the low sequestration rates of organic and

inorganic carbon that are seen in arid lands 

under natural conditions (Schlesinger 1985, 

1990), the tendency for warmer soils to store 

lesser amounts of soil organic matter, and the 

small increases in net productivity that might 

be expected in these lands in a warmer, drier 

future climate. Moreover, when desert lands 

are irrigated, there can be substantial releases 

of carbon dioxide from the fossil fuels used 

to pump irrigation water (Schlesinger 2001). 

Globally, the greatest potential for soil carbon 

sequestration isfound in soilsthat are cold and/

or wet, not in soils that are hot and dry.

In many areas of desert, the amount of carbon 

stored in inorganic soil carbonates greatly 

exceeds the amount of carbon in vegetation 

and soil organic matter, but the formation of 

such carbonates is slow and not a significant 

sink for carbon in its global cycle (Schlesinger 

1982; Monger and Martinez-Rios 2000). Some 

groundwater contains high (supersaturated) 

concentrations of carbon dioxide, which is 

released to the atmosphere when this water is 

brought to the Earth’s surface for irrigation, 

especially when carbonates and other salts precipitate (Schlesinger 2000). Thus, soil carbonates are unlikely to offer significant potential to 

sequester atmospheric carbon dioxide in future

warmer climates.

3.3.4.4 Biogeochemistry

Arid-land soils often have limited supplies 

of nitrogen, such that nitrogen and water can 

“co-limit” the growth of vegetation (Hooper 

and Johnson 1999). These nitrogen limitations 

normally appear immediately after the receipt 

of seasonal rainfall. The nitrogen limitations 

of arid lands stem from small amounts of N 

received by atmospheric deposition and nitrogen 

fixation and rather large losses of N to wind 

erosion and during microbial transformations 

of soil N that result in the losses of ammonia 

(NH3), nitric oxide (NO), nitrous oxide (N2O), 

and nitrogen gas (N2) to the atmosphere (Schlesinger et al. 2006). These microbial processes 

are all stimulated by seasonal rainfall, suggesting that changes in the rainfall regime as a result 

of climate change will alter N availability and 

plant growth. N deposition is spatially variable, 

being greater in areas downwind from major 

urban centers such as Los Angeles, increasing 

the abundance of herbaceous vegetation and 

potentially increasing the natural fire regime 

in the Mojave Desert (Brooks 2003).

In arid lands dominated by shrub vegetation, 

the plant cycling of N and other nutrients is 

often heterogeneous, with most of the activity 

focused in the soils beneath shrubs (Schlesinger 

et al. 1996). It remains to be seen how these local nutrient hot spots will influence vegetation 

composition and ecosystem function in future 

environments. In cold desert shrub steppe, nonnative cheatgrass is often most abundant under 

shrubs, resulting in rapid consumption of the 

shrub during fire and mortality of native plants 

and seed banks; the higher available resources 

on the fertile island enables greater biomass and 

seed production of cheatgrass in the post-fire 

period (Chambers et al. 2007). Thus, the rate 

and extent of invasion of cold desert sagebrushsteppe by cheatgrass may initially be a function 

of the cover and density of sagebrush plants and 

the fertile islands they create.

3.3.4.5 Trace gases

In addition to significant losses of N trace 

gases, some of which confer radiative forcing 

on the atmosphere (e.g., N2O), deserts are also 

a minor source of methane, largely resulting 

from activities of some species of termites, 

and volatile organic compounds (VOC) and 

non-methane hydrocarbon gaseous emissions 

from vegetation and soils (Geron et al. 2006). 

Isoprene, produced by many woody species and 

a few herbaceous species, is the dominant VOC 

released by vegetation; the ability to produce 

significant amounts of isoprene may or may not 

be shared by members of the same plant family 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

or genus (Harley et al. 1999). No phylogenetic 

pattern is obvious among the angiosperms, 

with the trait widely scattered and present (and 

absent) in both primitive and derived taxa, 

although confined largely to woody species. 

VOCs can serve as precursors to the formation 

of tropospheric ozone and organic aerosols, thus 

influencing air pollution. Emissions of such 

gases have increased as a result of the invasion 

of grasslands by desert shrubs during the past 

100 years (Guenther et al. 1999), and emissions 

of isoprene are well known to increase with 

temperature (Harley et al. 1999). The flux of 

these gases from arid lands is not well studied, 

but is known to be sensitive to temperature, 

precipitation, and drought stress. For example, 

total annual VOC emissions in deserts may vary 

threefold between dry and wet years, and slight 

increases in daily leaf temperatures can increase 

annual desert isoprene and monoterpene fluxes 

by 18 percent and 7 percent, respectively (Geron 

et al. 2006). Thus, changes in VOC emissions 

from arid lands can be expected to accompany 

changes in regional and global climate.

3.3.5 Arid Land Rivers and Riparian 

 Zones

Springs, rivers and floodplain (riparian) ecosystems commonly make up less than 1 percent 

of the landscape in arid regions of the world. 

Their importance, however, belies their small 

areal extent (Fleischner 1994; Sada et al. 2001; 

Sada and Vinyard 2002). These highly productive ecosystems embedded within much lower 

productivity upland ecosystems attract human 

settlement and are subjected to a variety of land 

uses. They provide essential wildlife habitat for 

migration and breeding, and these environments 

are critical for breeding birds, threatened and 

endangered species, and arid-land vertebrate 

species. Riparian vegetation in arid lands can 

occur at scales from isolated springs to ephemeral and intermittent watercourses, to perennial 

rivers (Webb and Leake 2006). The rivers and 

riparian zones of arid lands are dynamic ecosystems that react quickly to changing hydrology, geomorphology, human utilization, and 

climate change. Certain types of springs can 

also be highly responsive to these changes. As 

such, spring, river and riparian ecosystems will 

likely prove to be responsive components of arid 

landscapes to future climate change.

Effects of climate change on aquatic organisms

in arid lands are not well known. Introductions of non-native fish and habitat modification have caused the extinction of numerous 

endemic species, subspecies and populations 

of fishes, mollusks and insects since the late 

1800s. Declines in abundance or distribution 

have been attributed to (in order of decreasing 

importance) water flow diversions, competitive 

or predatory interactions with non-native species, livestock grazing, introductions for sport 

fisheries management, groundwater pumping, 

species hybridization, timber harvest, pollution, 

recreation and habitat urbanization (reviewed 

by Sada and Vinyard 2002). Most taxa were 

influenced by multiple factors. It is likely that 

projected climate changes will exacerbate these 

existing threats via effects on water temperature, sedimentation, and flows.

Global climate change can potentially impact 

river and riparian ecosystems in arid regions 

through a wide variety of mechanisms and 

pathways (Regab and Prudhomme 2002). 

Three pathways in which riverine corridors in 

arid lands are highly likely to be affected are 

particularly important. The first is the impact of 

climate change on water budgets. Both sources 

of water and major depletions will be considered. The second is competition between native 

and non-native species in a changing climate. 

The potential importance of thresholds in these 

interactions will be explicitly considered. The 

third mechanism pertains to the role of extreme 

climate events (e.g., flood and droughts) in a 

changing climate. Extreme events have always 

shaped ecosystems, but the interactions of a 

warmer climate with a strengthened and more 

variable hydrologic cycle are likely to be significant structuring agents for riverine corridors 

in arid lands.

3.3.5.1 Water Budgets

Analysis of water budgets under a changing 

climate is one tool for assessing the impact of 

climate change on arid-land rivers and riparian 

zones. Christensen et al. (2004) have produced 

a detailed assessment of the effects of climate 

change on the hydrology and water resources of 

the Colorado River basin. Hydrologic and water 

resources scenarios were evaluated through 

Global climate 

change can 

potentially impact 

river and riparian 

ecosystems in arid 

regions through 

a wide variety of 

mechanisms and 

pathways. 
The U.S. Climate Change Science Program

110

Chapter 3

coupling of climate models, hydrologic models, 

and projected greenhouse gas scenarios for time 

periods 2010-2039, 2040-2069, and 2070-2099. 

Average annual temperature changes for the 

three periods were 1.0°C, 1.7°C, and 2.4°C, 

respectively, and basin-average annual precipitation was projected to decrease by 3, 6, and 

3 percent for the three periods, respectively. 

These scenarios produced annual runoff decreases of 14, 18, and 17 percent from historical 

conditions for the three designated time periods. 

Such decreases in runoff will have substantial 

effects on human populations and river and 

riparian ecosystems, particularly in the lower 

elevation arid land compartments of this heavily appropriated catchment (e.g., Las Vegas and 

southern California).

Changing climate also can have a significant 

effect on major depletions of surface waters 

in arid regions. Dahm et al. (2002) examined 

major depletions along a 320-km reach of the 

Rio Grande in central New Mexico. Major 

Figure 3.15 A water budget for a 320-km segment of the Middle Rio Grande of New Mexico, USA, with water 

sources on the left and top, depletions on the right, and downstream output on the bottom (Dahm et al. 2002). 

The red arrows indicate the direction of change for various water sources and depletions predicted with a warmer 

climate. Otowi Guage values are a 26 year mean with range; releases from Elephant Butte dam are ranges only, 

because releases vary depending on delivery requirements and because releases sometimes include storage 

water (dam volume is being drawn down) or is much less than inflow (water going into storage). Ranges reflect 

both interannual variability and measurement uncertainty. The budget balances, but only coarsely, because of 

the large ranges.

depletions were reservoir evaporation, riparian 

zone evapotranspiration, agriculture, groundwater recharge, and urban/suburban use. All 

of these depletions are sensitive to climate 

warming. Reservoir evaporation is a function 

of temperature, wind speed, and atmospheric 

humidity. Riparian zone evapotranspiration is 

sensitive to the length of the growing season, 

and climate warming will lengthen the period 

of time that riparian plants will be actively 

respiring (Goodrich et al. 2000; Cleverly et al. 

2006), and also increase the growing season 

for agricultural crops dependent on riparian 

water. Temperature increases positively affect 

groundwater recharge rates from surface waters 

through changes in viscosity (Constantz and 

Thomas 1997; Constantz et al. 2002). The net 

result of climate warming is greater depletion of 

water along the riverine corridor (Figure 3.15). 

Global warming will place additional pressure 

on the major depletions of surface water in arid 

regions, in addition to likely effects on the supply side of the equation.
111

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 3.16 Non-native salt cedar (right) has invaded and displaced native cottonwood and poplar forests (left) in many southwestern 

riparian corridors. Photo credits: Jim Thibault and James Cleverly.

3.3.5.2 Native and Non-Native Plant 

 Interactions

Competition between native and non-native 

species in a changing climate is a second area 

where climate change is predicted to have a substantial effect on riparian zones of arid lands. 

Riparian zones of arid lands worldwide are 

heavily invaded by non-native species of plants 

and animals (Prieur-Richard and Lavorel 2000; 

Tickner et al. 2001). Salt cedar and Russian olive 

are particularly effective invaders of the arid 

land riparian zones of the western United States 

(Figure 3.16) (Brock 1994; Katz and Shafroth 

2003). Shallow ground water plays an important 

role in structuring riparian plant communities 

(Stromberg et al. 1996) and groundwater level 

decline, both by human depletions and intensified drought in a changing climate, will alter 

riparian flora. Stromberg et al. (1996) describe 

riparian zone “desertification” from a lowered 

water table whereby herbaceous species and 

native willows and cottonwoods are negatively 

impacted. Horton et al. (2001a, b) describe a 

threshold effect where native canopy dieback 

occurs when depth to ground water exceeds 

2.5-3.0 meters. Non-native salt cedar (Tamarix 

chinensis), however, are more drought tolerant 

when water tables drop, and readily return to 

high rates of growth when water availability 

again increases. Plant responses like these are 

predicted to shift the competitive balance in 

favor of non-native plants and promote displacement of native plants in riparian zones under a 

warmer climate.

Another example of a threshold effect on river 

and riparian ecosystems in arid lands is the 

persistence of aquatic refugia in a variable

or changing climate. Hamilton et al. (2005) 

and Bunn et al. (2006) have shown the critical 

importance of waterhole refugia in the maintenance of biological diversity and ecosystem 

productivity in arid-land rivers. Arid regions 

worldwide, including this example from inland 

Australia, are dependent on the persistence of 

these waterholes during drought. Human appropriation of these waters or an increase in the 

duration and intensity of drought due to climate 

change would dramatically affect aquatic biodiversity and the ability of these ecosystems 

to respond to periods of enhanced water availability. For example, most waterhole refugia 

throughout the entire basin would be lost if 

drought persisted for more than two years in the 

Cooper Creek basin of Australia, or if surface 

diversions of flood waters reduced the available 

water within refugia in the basin (Hamilton et 

al. 2005; Bunn et al. 2006). Desiccation of waterholes could become more common if climate 

change increases annual evapotranspiration 

rates or if future water withdrawals reduce 

the frequency and intensity of river flows to

waterholes. Roshier et al. (2001) pointed out 

that temporary wetland habitats throughout 

arid lands in Australia are dependent upon 

infrequent, heavy rainfalls and are extremely

vulnerable to any change in frequency or magnitude. Climate change that induces drying 

or reduced frequency of large floods would
The U.S. Climate Change Science Program

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Chapter 3

deleteriously impact biota, particularly water 

birds that use these temporary arid land habitats 

at broad spatial scales.

3.3.5.3 Extreme Events

The role of extreme events (e.g., flood and 

droughts) in a changing climate is predicted to 

increase with a warmer climate (IPCC 2007). 

Extreme climatic events are thought to strongly 

shape arid and semi-arid ecosystems worldwide 

(Holmgren et al. 2006). Climate variability, 

such as associated with the El Niño Southern 

Oscillation (ENSO) phenomenon, strongly 

reverberates through food webs in many arid 

lands worldwide. Fluvial systems and riparian 

vegetation are especially sensitive to the timing 

and magnitude of extreme events, particularly 

the timing and magnitude of minimum and 

maximum flows (Auble et al. 1994). GCMs do 

not yet resolve likely future regional precipitation regimes or future temperature regimes. 

A stronger overall global hydrologic cycle, 

however, argues for more extreme events in the 

future (IPCC 2007). The ecohydrology of aridland rivers and riparian zones will certainly 

respond to altered precipitation patterns (Newman et al. 2006), and the highly variable climate 

that characterizes arid lands is likely to become 

increasingly variable in the future.

3.3.6 Water and Wind Erosion

Due to low and discontinuous cover, there is 

a strong coupling between vegetation in arid 

lands and geomorphic processes such as wind 

and water erosion (Wondzell et al. 1996). Erosion by wind and water has a strong impact on 

ecosystem processes in arid regions (Valentin 

et al. 2005; Okin et al. 2006). Erosion impacts 

the ability of soils to support plants and can 

deplete nutrient-rich surface soils, thus reducing the probability of plant establishment and 

recruitment. Although erosion by water has received by far the most attention in the scientific 

literature, the few studies that have investigated 

both wind and water erosion have shown that 

they can be of similar magnitude under some 

conditions (Breshears et al. 2003).

3.3.6.1 Water Erosion

Water erosion primarily depends on the erosivity of precipitation events (rainfall rate, storm 

duration, and drop size) and the erodibility of 

the surface (infiltration rate, slope, soil, and 

vegetation cover). Climate change may impact 

all of these except slope. For instance, it is 

well established that the amount of soil that is 

detached (and hence eroded) by a particular 

depth of rain is related to the intensity at which 

this rain falls. Early studies suggest soil splash 

rate is related to rainfall intensity and raindrop 

fall velocity (Ellison 1944; Bisal 1960). It is also 

well established that the rate of runoff depends 

on soil infiltration rate and rainfall intensity. 

When rainfall intensity exceeds rates of infiltration, water can run off as inter-rill flow, or 

be channeled into rills, gullies, arroyos, and 

streams. The intensity of rainfall is a function of climate, and therefore may be strongly 

impacted by climate change. The frequency

of heavy precipitation events has increased 

over most land areas, including the United 

States, which is consistent with warming and 

observed increases in atmospheric water vapor 

(IPCC 2007). Climate models predict additional 

increases in the frequency of heavy precipitation, and thus highly erosive events. Warming 

climates may also be responsible for changes in 

surface soils themselves, with important implications for the erodibility of soils by water. In 

particular, higher temperatures and decreases 

in soil moisture, such as those predicted in 

many climate change scenarios, have been 

shown to decrease the size and stability of soil 

aggregates, thus increasing their susceptibility 

to erosion (Lavee et al. 1998).

By far the most significant impact of climate 

change on water erosion is via its effects on 

vegetation cover. Vegetation conversion to annual grasses or weedy forbs can result in loss 

of soil nutrients, siltation of streams and rivers, 

and increased susceptibility to flooding (Knapp 

1996). Although some fireproof shrublands in 

the Southwest have been invaded by non-native 

grasses, thus changing the fire ecology and 

endangering those ecosystems (Knapp 1996; 

Bradley et al. 2006), many other areas have 

experienced the loss of native perennial grasses, 

which have been replaced by shrubs (van Auken 

2000; sections 3.9.4 and 3.9.5). This widespread conversion of grasslands to shrublands 

throughout the desert Southwest has resulted in 

significantly greater erosion, though research 

on natural rainfall events to quantify the total

amounts of erosion is ongoing. Flow and erosion plots in the Walnut Gulch Experimental 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Watershed in Arizona and the Jornada LTER 

site in New Mexico have demonstrated significant differences in water erosion between 

grasslands and shrublands (Wainwright et al. 

2000). For instance, greater splash detachment 

rates (Parsons et al. 1991, 1994, 1996), and interrill erosion rates (Abrahams et al. 1988) are 

observed in shrublands compared to grasslands; 

shrubland areas are more prone to develop rills, 

which are responsible for significant increases 

in overall erosion rates (Luk et al. 1993). Episodes of water erosion are often associated with 

decadal drought-interdrought cycles because 

depressed vegetation cover at the end of the 

drought makes the ecosystem vulnerable to 

increased erosion when rains return (McAuliffe 

et al. 2006). No study to date has used climate 

models to estimate how the periodicity of these 

cycles might change in the future.

U.S. arid regions have already experienced 

dramatic increases in erosion rates due to 

widespread losses of vegetation cover. These 

changes have created conditions where anticipated increases in precipitation intensity, 

coupled with reductions in soil aggregate stability due to net warming and drying, will likely 

increase potential erosion rates dramatically in 

coming decades.

3.3.6.2 Wind Erosion

As with water erosion, the magnitude of wind 

erosion is related to both the erosivity of the 

wind and the erodibility of the surface. However, the impact of increased wind erosion in 

deserts can have continental-scale impacts 

because the resulting dust can travel long distances with significant impacts to downwind 

ecosystems, air quality, and populations. Both

hemispheres have experienced strengthening 

of mid-latitude westerly winds since the 1960s 

(IPCC 2007). This trend is likely to continue 

into the near future. Thus, desert regions of 

the United States are likely to experience more 

erosive conditions in the near future.

The susceptibility of soil to erosion by wind is 

determined by both the erodibility of the surface soil and the amount of vegetation present 

to disrupt wind flows and shelter the surface 

from erosion. Anticipated net aridification in 

the desert Southwest (Seager et al. 2007) is 

likely to lead to a decrease in soil aggregate 

size and stability. Increased temperatures and 

drought occurrence will result in lower relative 

humidity in arid lands. Because the top few 

millimeters of soil are in equilibrium with soil

moisture in the overlying air, the decrease in 

relative humidity may result in soilsthat require

less wind power to initiate erosion (Ravi et al. 

2006). Increased drought occurrence throughout the western United States can further lead 

to lower soil moisture content, which can also 

increase the erodibility of the soil (Bisal 1960; 

Cornelis et al. 2004).

Short-term changes in vegetation cause significant changes in the wind erodibility of the 

surface. For instance, Okin and Reheis (2002) 

and Reheis (2006) have shown that annual 

variation in wind erosion on a regional scale 

is related to variation in precipitation. There 

appears to be a one-year lag in this effect, 

with low precipitation one year resulting in 

significant wind erosion and dust emission the 

following year. This lag is hypothesized to be 

due to the fact that the effect of low precipitation must propagate through the system by first 

affecting vegetation cover. This one-year lag 

effect has been observed in other arid systems 

(Zender and Kwon 2005). In addition, dust 

emission from dry lakes or playas in the desert 

Southwest also appears to occur after years of 

particularly intense rainfall. This phenomenon 

seems to result from the increased delivery of 

fine-grained sediment to these playas during 

especially wet years or years with intense rainfall events. Anticipated climatic changes in the 

coming decades include both increased drought 

frequency and also increased precipitation intensity during rain events (IPCC 2007). Both of 

these effects are likely to increase wind erosion 

and dust emission in arid regions due to, in the 

first case, suppression of vegetation and, in the 

second case, greater water erosion resulting in 

increased delivery of sediment to dry lakes.

Long-term and ongoing vegetation changes 

in arid regions, namely the conversion of 

grasslands to shrublands, have dramatically 

increased wind erosion and dust production due 

to increased bare areas in shrublands compared 

to the grasslands they replaced. Measurements 

of aeolian sediment flux in the Chihuahuan 

Desert have shown nearly ten-fold greater rates 

of wind erosion and dust emission in mesquiteLong-term and 

ongoing vegetation 

changes in arid 

regions, namely 

the conversion 

of grasslands 

to shrublands, 

have dramatically 

increased wind 

erosion and dust 

production due 

to increased bare 

areas in shrublands 

compared to the 

grasslands they 

replaced.
The U.S. Climate Change Science Program

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Chapter 3

dominated shrublands compared to grasslands 

on similar soils (Gillette and Pitchford 2004). 

Large-scale conversion of grasslands to shrublands, coupled with anticipated changes in 

climate in the coming decades, and increases 

in wind speed, temperature, drought frequency,

and precipitation intensity, contribute to greater 

wind erosion and dust emission from arid 

lands.

3.3.6.3 Impacts of Water and Wind 

 Erosion

Dust can potentially influence global and 

regional climate by scattering and absorbing 

sunlight (Sokolik and Toon 1996) and affecting 

cloud properties (Wurzler et al. 2000), but the 

overall effect of mineral dusts in the atmosphere 

is likely to be small compared to other human 

impacts on the Earth’s climate system (IPCC 

2007). Desert dust is thought to play a major 

role in ocean fertilization and CO2 uptake (Duce 

and Tindale 1991; Piketh et al. 2000; Jickells 

et al. 2005), terrestrial soil formation, and 

nutrient cycling (Swap et al. 1992; Wells et al. 

1995; Chadwick et al. 1999), and public health 

(Leathers 1981; Griffin et al. 2001). In addition, 

desert dust deposited on downwind mountain 

snowpack has been shown to decrease the albedo of the snowpack, thus accelerating melt by 

as much as 20 days (Painter et al. 2007).

In arid regions, erosion has been shown to 

increase sediment delivery to large rivers (e.g., 

the Rio Grande), and can change the flow 

conditions of those rivers (Jepsen et al. 2003). 

Transport of eroded sediment to streams can 

change conditions in waterways, impacting 

water quality, riparian vegetation, and water

fauna (Cowley 2006).

3.3.7 Indicators and Observing

Systems

3.3.7.1 Existing Observing Systems

A summary of arid land sites with inventory and 

monitoring programs is given in Table 3.2. Data 

from such sites will be important for helping 

track the consequences of climate change, but

unfortunately, most sites do not have this as an 

explicit part of their mission. Furthermore, there 

is virtually no coordination among these sites 

with respect to the variables being monitored, 

the processes being studied, the methodologies 

being used or the spatial and temporal scales 

over which change is occurring. Lack of coordination and standardization across these existing sites, programs and networks constitutes a 

missed opportunity.

Repeat photography is a valuable tool for 

documenting changes in vegetation and erosion. Hart and Laycock (1996) present a bibliography listing 175 publications using repeat 

photography and information on the ecosystems 

photographed, where they are located, number 

of photographs, and dates when the photographs 

were taken. More recent publications have 

added to this list (e.g., Webb 1996; McClaran 

2003; Webb et al. 2007), and Hall (2002) has 

published a handbook of procedures. Timeseries aerial photographs dating back to the 

1930s and 1940s are also a useful source for 

quantifying landscape-scale changes in land

cover (e.g., Archer 1996; Asner et al. 2003b; 

Bestelmeyer et al. 2006; Browning et al. 

2008).

3.3.7.2 Observing Systems Required

 For Detecting Climate

 Change Impacts

While the deserts of North America have been 

the site of many important ecological studies, 

there have been relatively few long-term monitoring sites at an appropriate spatial representation that allow us the means to access changes 

in ecosystem structure and function in response 

to global change. Coordinated measurements of 

plant community composition in plots across 

the North American deserts would enhance 

our ability to detect change and relate that to 

aspects of climate. Several important data sets 

stand as benchmarks – the long-term photographic record at the Santa Rita Experimental 

Range, the long-term vegetation maps and 

livestock management records at the Jornada 

Experimental Range, the long-term perennial 

plant and winter annual plant studies at Tumamoc Hill, the long-term data collected from 

large-scale ecosystem manipulations at Portal 

Arizona, and the new Mojave Desert Climate 

Change Program. Greater spatial representation 

of such efforts is important in future assessment 

of change in these biomes.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Table 3.2 Arid land sites with research and monitoring systems.

Monitoring system Site Location SourceFree-Air CO2 Enrichment (FACE) Site Nevada Desert FACE Nevada Test Site, NV http://www.unlv.edu/Climate_Change_ResearchInternational Biome Project (IBP) Sites Rock Valley Nevada Test Site, NV archived at University of California, Los Angeles, CA

Silverbell Arva Valley, AZ archived at University of Arizona, Tucson, AZ

Land-Surface Flux Assessment Sites Audubon Ranch Ameriflux Sites http:/public.ornl.gov/ameriflux/ 

USDA Agricultural Research Service Flux Tower Network http://edcintl.cr.usgs.gov/carbon_cycle/FluxesReseachActivities.htmlSemi-arid Ecohydrology Array (SECA) http://eebweb.arizona.edu/faculty/huxman/seca/

Research Sites (some with long-term data sets) Desert Experimental Range Pine Valley, UT http://www.fs.fed.us/rmrs/experimental-forests/desert-experimental-range/

V Bar V Ranch Rimrock, AZ http://ag.arizona.edu/aes/vbarv/Valles Caldera National Preserve Jemez Springs, NM http://www.vallescaldera.gov/Sweeny Granite Mountains Desert Research Center Kelso, CA http://nrs.ucop.edu/Sweeney-Granite.htmBoyd Deep Canyon Desert Research Center Palm Desert, CA http://deepcanyon.ucnrs.org/Great Basin Experimental Range Manti-LaSal National Forest, UT http://www.fs.fed.us/rm/provo/great_basin/great_basin.shtmlIndio Mountains Research Station Van Horn, TX http://www.utep.edu/indio/Jornada Experimental Range Jornada Basin, NM http://usda-ars.nmsu.edu/USA National Phenology Network http://www.usanpn.orgThe Portal Project Portal, AZ http://biology.unm.edu/jhbrown/Portal-LTREB/PortalFront.htmReynolds Creek Experimental Watershed Boise, ID http://ars.usda.gov/main/site_main.htm?modecode=53-42-45-00San Juaquin Experimental Range O’Neals, CA http://www.fs.fed.us/psw/ef/san_joaquinSanta Rita Experimental Range Green Valley, AZ http://ag.arizona.edu/SRER/UA Desert Laboratory at Tumamoc Hill Permanent Plots Tucson, AZ http://www.paztcn.wr.usgs.gov/home.htmlU.S. Sheep Experiment Station Snake River Plain, ID http://ars.usda.gov/main/site_main.htm?modecode=53-64-00-00Walnut Gulch Experimental Watershed Tombstone, AZ http://ars.usda.gov/PandP/docs.htm?docid=10978&page=2

Long-Term Ecological Research (LTER) Sites Jornada Basin Las Cruces, NM http://jornada-www.nmsu.edu/

Sevilleta Albuquerque, NM http://sev.lternet.edu/Central Arizona-Phoenix Phoenix, AZ http://caplter.asu.edu/

National Ecological Observatory Network (NEON) Santa Rita Experimental Range Tucson, AZ http://www.sahra.arizona.edu/santarita/

Onaqui-Benmore Salt Lake City, UT http://www.neoninc.org

National Park Service Inventory & Monitoring Program

The NPS has recently initiated Inventory & Monitoring programs at many of its Parks and Monuments in arid lands 

http://science.nature.nps.gov

TRENDS Project Synthesis of long-term data from 44 research sites http://fire.lternet.edu/Trends/Rainfall Manipulations USDA Agricultural Research Service Rainout Shelter Burns, OR Svejcar et al. 2003

Nevada Global Change Experiment Nevada Test Site, NV http://www.unlv.edu/Climate_Change_Research/
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BOX 2: Ecosystem “tipping points.”

There is widespread recognition that ecosystems may exist in “alternate states” (e.g., 

perennial grassland state vs. annual grassland state; grassland state vs. shrubland state). 

Within a given state, ecosystems may tolerate a range of climate variability, stress and 

disturbance and exhibit fluctuation in structure (e.g., species composition) and function 

(e.g., rates of primary production and erosion). However, there may be “tipping points” 

that occur where certain levels of stress, resource availability, or disturbance are exceeded, 

causing the system transition to an alternate state (Archer and Stokes 2000). Thus, change 

in ecosystem structure and function in response to changes in stress levels or disturbance 

regimes may be gradual and linear up to a certain point(s), and then change dramatically 

and profoundly. Once in an alternate state, plant cover, composition and seedbanks, and 

soil physical properties, nutrient status and water holding capacity, etc. may have been 

altered to the point that it is difficult for the system to revert to its previous state even 

if the stresses or disturbance causing the change are relaxed.

In arid lands, threshold examples include shifts from grassland states to shrubland states 

(Archer 1989) and desertification (Schlesinger et al. 1990). It appears that these statetransitions occur as result of various combinations of vegetation-fire, soil, hydrology, 

animal, and climate feedbacks (e.g., Thurow 1991; Wainwright et al. 2002; Okin et al. 

2006, D’Odorico et al. 2006).

While there is substantial observational evidence for these threshold phenomena, our 

quantitative understanding is limited and many questions remain:

• How far, and under what circumstances, can an ecosystem be pushed before entering 

into an alternate state?

• What changes in ecosystem properties and feedbacks are involved in these statetransitions?

• What variables could be monitored to predict when a system is nearing a ‘tipping 

point’?

• How do climate factors influence the risk of exceeding state-transition thresholds?
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Soil moisture is a key indicator and integrator 

of ecological and hydrological processes. However, as noted in the Water Resources chapter 

(Chapter 4), there is a dearth of information 

on the long-term patterns and trends in this 

important variable. Even on well-instrumented 

watersheds in arid lands (e.g., Lane and Kidwell 

2003; NWRC 2007; SWRC 2007) soil moisture 

records are only erratically collected over time 

and are limited in their spatial coverage and 

depth. Thus, there is a pressing need for a distributed network of soil moisture sensors in arid 

lands that would be a component of a network 

of monitoring precipitation, evapotranspiration, and temperature. Ideally, such a network 

would also include collection of plant, soil and 

precipitation samples for determination of the 

stable isotope composition of C, O, and H. Such 

isotope data would provide important clues 

regarding when and where plants were obtaining soil moisture and how primary production 

and water use efficiency are being affected 

by environmental conditions (e.g., Boutton 

et al. 1999; Roden et al. 2000; Williams and 

Ehleringer 2000).

Effects of climate change will be most easily 

observed in relatively few arid land springs. 

Springs that dry periodically are relatively poor 

candidates, as long periods of record will be 

required to determine “baseline” conditions.

Similarly, springs supported by large, regional 

aquifers are also poor candidates, as transmissivity is low and surface discharge is primarily ancient water (Mifflin 1968; Hershey and 

Mizell 1995; Thomas et al. 2001; Knochenmus 

et al. 2007). The USGS maintains quantitative

historic Web-based records of surface water 

discharge from springs. These records could 

provide a “baseline” discharge, but the effect 

of climate change on such springs will not 

be evident for decades or much, much longer. 

Persistent springs fed by aquifers with moderate transmissivity are good candidates to assess 

effects of climate change. In the arid western 

United States, these geologically persistent 

springs are characterized by crenobiontic 

macroinvertebrates, including aquatic insects

and springsnails. They occur on bajadas, at 

the base of mountains, and sometimes on valley floors (Taylor 1985; Hershler and Sada 

2001; Polhemus and Polhemus 2001). While 

discharge from these springs fluctuates, they 

have not dried. Transmissivity through aquifers supporting these springs is relatively high, 

hence their response to changes in precipitation will be relatively rapid and measurable 

(Plume and Carlton 1988; Thomas et al. 1996). 

An existing database, consisting of surveys of 

>2000 springs (mostly Great Basin and in the 

northwestern United States) over the past 15 

years, includes hundreds of springs that would 

qualify as potential climate change monitoring

sites (Sada and Hershler 2007).

Most land-surface exchange research has focused on forested systems. There is, however, 

a need for understanding the seasonal carbon 

dynamics, biomass, annual productivity, 

canopy structure, and water use in deserts 

(Asner et al. 2003a, b; Farid et al. 2006; Sims et 

al. 2006). Studies to date do not yet yield clear 

generalizations. For example, shifts from grass 

to shrub domination may show no net effects on 

evapotranspiration due to offsetting changes in 

radiant energy absorption and the evaporative 

fraction in the contrasting cover types (Kurc 

and Small 2004). However, this may depend 

upon the type of shrubs (Dugas et al. 1996). 

Although net changes in evapotranspiration 

may not occur with this land cover change, 

ecosystem water use efficiency may be significantly reduced (Emmerich 2007). Part of the 

challenge in predicting functional ecosystem 

dynamics in arid lands derives from our relatively poor understanding of non-equilibrium

processes driven by highly episodic inputs of 

precipitation (Huxman et al. 2004). Part derives 

from the importance of the strong, two-way 

coupling between vegetation phenology and the 

water cycle, which is critical for predicting how 

climate variability influences surface hydrology, water resources, and ecological processes 

in water-limited landscapes (e.g., Scanlon et 

al. 2005). Shifts in phenology represent an 

integrated vegetation response to multiple 

environmental factors, and understanding of 

vegetation phenology is prerequisite to interannual studies and predictive modeling of land 

surface responses to climate change (White et 

al. 2005). Along these lines, the ability to detect 

ecosystem stress and impacts on vegetation 

structure will be requisite to understanding

regional aspects of drought (Breshears et al. 

2005) that result in substantial land use and 

land cover changes.
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Chapter 3

In regions where the eroded surfaces are connected to the regional hydraulic systems (i.e., 

not in closed basins), sediment delivery to 

streams and streambeds is an excellent indicator of integrated erosion in the catchment when 

coupled with stream gauging and precipitation 

data. USGS gauges are few and far between 

in arid lands and many have been or are being 

decommissioned due to lack of funds (as is also 

the case for watersheds on U.S. Forest Service 

lands). There is currently no integrated monitoring system in place for the measurement of bedload, but the USGS National Water Information 

System does collect water quality data that could

inform sediment loads. Unfortunately, there are 

very few sites in the arid United States that are 

monitored continuously. Additional arid region 

rivers could be instrumented and sampled to 

provide further monitoring of stream flow as 

well as water erosion. In closed basins, or the 

upland portion of open basins, the development 

and expansion of rills and gullies is the clearest 

indicator of water erosion. There is no system in 

place for the monitoring of these features (Ries 

and Marzolff 2003), but high-resolution remote 

sensing (~1-meter resolution) might be used to 

monitor the largest of these features.

The most important indicator of wind erosion is 

the dust that it produces. Because dust is transported long distances, even a sparse network 

of monitoring sites can identify dust outbreaks. 

For instance, Okin and Reheis (2002) have used 

meteorological data collected as part of the 

National Climatic Data Center’s network of 

cooperative meteorological stations (the COOP 

network) to identify dust events and to correlate 

them to other meteorological variables. The 

expansion of this network to include observations in more locations, and especially at locations downwind of areas of concern, would be 

a significant improvement to monitoring wind 

in the arid portions of the United States. This 

existing observation network might also be integrated with data from NASA’s Aerosol Robotic 

Network (AERONET) on aerosol optical depth 

and radar or lidar systems deployed throughout 

the region, but particularly near urban centers 

and airports. In addition, there are several 

remote sensing techniques that can be used to

identify the spatial extent and timing of dust 

outbreaks (Chomette et al. 1999; Chavez et al. 

2002; Miller 2003), though there is no system 

in place to integrate or track the evolution of 

dust sources through time.

Novel communities (with a composition unlike 

any found today) have occurred in the lateglacial past and will develop in the greenhouse 

world of the future (Williams and Jackson 

2007). Most ecological models are at least 

partially parameterized from modern observations and so may fail to accurately predict ecological responses to novel climates occurring 

in conjunction with direct plant responses to 

elevated atmospheric CO2 and nitrogen deposition. There is a need to test the robustness of 

ecological models to conditions outside modern 

experience.

3.4 Findings and 

Conclusions

3.4.1 Forests

Climate strongly influences forest productivity, 

species composition, and the frequency and

magnitude of disturbances that impact forests. 

The effect of climate change on disturbances 

such as forest fire, insect outbreaks, storms, and 

severe drought will command public attention 

and place increasing demands on management 

resources. Other effects, such as increases in 

temperature, the length of the growth season, 

CO2, and nitrogen deposition may be more 

incremental and subtle, but may have equally

dramatic long-term effects.

Climate change has very likely increased 

the size and number of forest fires, insect 

outbreaks, and tree mortality in the interior 

west, the Southwest, and Alaska, and will 

continue to do so. An increased frequency of

disturbance is at least as important to ecosystem 

function as incremental changes in temperature, precipitation, atmospheric CO2, nitrogen 

deposition, and ozone pollution. Disturbances 

partially or completely change forest ecosystem 

structure and species composition, cause shortterm productivity and carbon storage loss, allow 

better opportunities for invasive alien species to 

become established, and command more public 

and management attention and resources.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Rising CO2 will very likely increase photosynthesis for forests, but the increased 

photosynthesis will likely only increase wood 

production in young forests on fertile soils.

Where nutrients are not limiting, rising CO2

increases photosynthesis and wood production. But on infertile soils the extra carbon 

from increased photosynthesis will be quickly

respired. The response of older forests to CO2

is uncertain, but possibly will be lower than the 

average of the studied younger forests.

Nitrogen deposition and warmer temperatures have very likely increased forest 

growth where water is not limiting and will 

continue to do so in the near future. Nitrogen 

deposition has likely increased forest growth 

rates over large areas, and interacts positively to 

enhance the forest growth response to increasing CO2. These effects are expected to continue 

in the future as N deposition and rising CO2

continue.

The combined effects of expected increased 

temperature, CO2, nitrogen deposition, 

ozone, and forest disturbance on soil processes and soil carbon storage remain unclear. Soils hold an important, long-term store 

of carbon and nutrients, but change slowly. 

Long-term experiments are needed to identify 

the controlling processes to inform ecosystem 

models.

3.4.2 Arid Lands

Disturbance and land use on arid lands will 

control their response to climate change. Many 

plants and animals in arid ecosystems are near 

their physiological limits for tolerating temperature and water stress. Thus, even slight changes 

in stress will have significant consequences.

Projected climate changes will increase the 

sensitivity of arid lands to disturbances such as 

grazing and fire. Invasion of non-native grasses 

will increase fire frequency. In the near-term,

fire effects will trump climate effects on ecosystem structure and function. These factors 

cause important changes themselves, but the 

outcome of their interactions are difficult to predict in the context of increased concentrations 

of atmospheric CO2 and nitrogen deposition. 

This is particularly so because these interactions represent novel combinations.

Figure 3.17 Mojave Desert scrub near Las Vegas, NV (foreground); and area invaded 

by the exotic annual grass red brome (background) following a fire that carried from 

desert floor upslope into pinyon-juniper woodlands. Photo: T.E. Huxman.

Higher temperatures, increased drought and 

more intense thunderstorms will very likely 

increase erosion and promote invasion of exotic grass species. Climate change will create 

physical conditions conducive to wildfire, and 

the proliferation of exotic grasses will provide 

fuel, thus causing fire frequencies to increase

in a self-reinforcing fashion (Figure 3.17). In 

arid regions where ecosystems have not coevolved with a fire cycle, the probability of 

loss of iconic, charismatic mega flora such as 

saguaro cacti and Joshua trees will be greatly 

increased.

Arid lands very likely do not offer a large 

capacity to serve as a “sink” for atmospheric 

CO2 and will likely lose carbon as climateinduced disturbance increases. Climateinduced changes in vegetation cover and erosion 

will reduce the availability of nitrogen in dryland soils, which (after water) is an important 

control of primary productivity and carbon 

cycling.

Arid land river and riparian ecosystems 

will very likely be negatively impacted by 

decreased streamflow, increased water removal, and greater competition from nonnative species. Dust deposition on alpine snow 

pack will accelerate the spring delivery of montane water sources and potentially contribute 
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Chapter 3

to earlier seasonal drought conditions in lower 

stream reaches. Riparian ecosystems will likely 

contract, and in the remainder, aquatic ecosystems will be less tolerant of stress. The combination of increased droughts and floods, land 

use and land cover change, and human water 

demand will amplify these impacts and promote 

sedimentation.

Changes in temperature and precipitation will very likely decrease the cover of 

vegetation that protects the ground surface 

from wind and water erosion. More intense 

droughts and floods will accelerate fluvial 

erosion and higher frequencies of dust storms.

Higher intensity rainfall will result in greater 

sheet erosion. All of these factors will periodically increase the sediment load in water and 

the atmosphere and decrease air and water 

quality.

3.4.3 Observing Systems for Forests 

and Arid Lands

Current observing systems are very likely 

inadequate to separate the effects of changes 

in climate from other effects. The major findings in the Land Resources Chapter relied on 

publications that used data assembled from 

diverse sources, generally for that specific 

study. In many cases, finding, standardizing, 

and assembling the data was the primary task 

in these studies. This was particularly the case 

for studies relating climate and disturbance. 

Findings on the effects of CO2 and nitrogen 

deposition were largely based on short-term, 

small-scale experimental manipulations. Those 

for the interaction of climate and invasive species with vegetation, riparian ecosystems, and 

erosion generally came from long-term monitoring and survey studies. The NOAA weather 

network was invaluable for climate information, 

but most studies needed to extrapolate weather 

data to create uniform coverage across the 

United States. This was and remains a considerable task, and is particularly problematic in arid 

lands where precipitation is highly localized 

and varies significantly across short distances. 

Separating the effects of climate change from 

other impacts would require a broad network of

indicators, coupled with a network of controlled 

experimental manipulations.

There is no coordinated national network for 

monitoring changes associated with disturbance and land cover and land use change.

Because of the spatial heterogeneity of insect 

outbreaks and other disturbances, new sampling and monitoring approaches are needed 

to provide a comprehensive assessment of how 

climate is affecting the disturbance regime of 

forest ecosystems and changes in forest soils.
121

4 Water Resources

Lead Author: D.P. Lettenmaier

Contributing Authors: D. Major, L. Poff, S. Running

CHAPTER

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

4.1 Introduction

This synthesis and assessment report builds on 

an extensive scientific literature and series of 

recent assessments of the historical and potential 

impacts of climate change and climate variability on managed and unmanaged ecosystems 

and their constituent biota and processes. It 

identifies changes in resource conditions that 

are now being observed, and examines whether 

these changes can be attributed in whole or part 

to climate change. It also highlights changes in 

resource conditions that recent scientific studies 

suggest are most likely to occur in response to 

climate change, and when and where to look 

for these changes. As outlined in the Climate 

Change Science Program (CCSP) Synthesis and 

Assessment Product 4.3 (SAP 4.3) prospectus, 

this chapter will specifically address climaterelated issues in freshwater supply and quality.

In this chapter the focus is on the near-term 

future. In some cases, key results are reported 

out to 100 years to provide a larger context, but 

the emphasis is on the next 25-50 years. This 

nearer-term focus is chosen for two reasons. 

First, for many natural resources, planning and 

management activities already address these 

time scales through development of long-lived 

infrastructure, forest or crop rotations, and 

other significant investments. Second, climate 

projections are relatively certain over the next 

few decades. Emission scenarios for the next 

few decades do not diverge from each other 

significantly because of the “inertia” of the 

energy system. Most projections of greenhouse 

gas emissions assume that it will take decades to 

make major changes in the energy infrastructure, 

and only begin to diverge rapidly after several 

decades have passed (30-50 years).

Water is essential to life and is central to society’s welfare and to sustainable economic 

growth. Plants, animals, natural and managed 

ecosystems, and human settlements are sensitive 

to variationsin the storage, fluxes, and quality of

water at the land surface – notably storage in soil 

moisture and groundwater, snow, and surface 

water in lakes, wetlands, and reservoirs, and 

precipitation, runoff, and evaporative fluxes to 

and from the land surface, respectively. These, 

in turn, are sensitive to climate change.

Water managers have long understood the 

implications of variability in surface water supplies at time scales ranging from days to months 

and years on the reliability of water resource 

systems, and many sophisticated methods (e.g. 

Jain and Singh, 2003) have been developed 

to simulate and respond to such variability in 

water resource system design and operation. 

The distinguishing feature of all such methods, 

however, is that they assume that an observed record of streamflow, on which planning is based, 

is statistically stationary – that is, the probability 

distribution(s) from which the observations are 

drawn does not change with time. As noted by 

Water is essential 

to life and central 

to society’s welfare 

and sustainable 

economic growth.
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Chapter 4

Arnell (2002), Lettenmaier (2003), and NRC 

(1998), in the era of climate change this assumption is no longer tenable. In this vein, Milly et 

al. (2008) argue that “stationarity is dead,” and 

advocate the urgent need for a major new initiative at the level of the Harvard Water Program 

of the 1960s (Maass et al.1962) to develop 

more applicable methods for water planning as 

climate changes. These new paradigms would 

provide the basis for assessing plausible ranges 

of future conditions for purposes of hydrologic 

design and operation. Such assessments are also 

needed to understand how changes in the availability and quality of water will affect animals,

plants, and ecosystems.

This chapter briefly reviews the current status of 

U.S. water resources, both in terms of characteristics of the physical system(s), trends in water 

use, and observed space-time variability in the 

recent past. It then examines changes to the natural hydrologic systems (primarily stream flow, 

but also evapotranspiration and snow water 

storage) over recent decades for six regions of 

Figure 4.1 Mean and coefficient of variation of annual precipitation in the continental U.S. and Alaska. Data 

replotted from Maurer et al. (2002).

the United States (the West, Central, Northeast, 

and South and Southeast, as well as Alaska and 

Hawaii, which are defined as aggregates of U.S. 

Geological Survey (USGS) hydrologic regions). 

Finally, recent studies based on climate model 

projections archived for the 2007 IPCC report, 

which project the implications of climate change 

for these six major U.S. regions, are reviewed.

4.1.1 Hydroclimatic Variability in the 

United States

The primary driver of the land surface hydrologic system is precipitation. Figure 4.1 shows 

variations in mean annual precipitation and its 

variability (expressed as the coefficient of variation, defined as the standard deviation divided by 

the mean) across the continental United States. 

The semi-humid conditions of the eastern United 

States yield to drier conditions to the west, with 

the increasing dryness eventually interrupted 

by the Rocky Mountains. The driest climates, 

however, exist in the Intermountain West and 

the Southwest, which give way as one proceeds 

west and north to more humid conditions on 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

the upslope areas of the Cascades and 

coastal mountain ranges, especially in the 

Pacific Northwest. The bottom panel of 

Figure 4.1, which shows the coefficient 

of variation of precipitation, indicates that 

precipitation variability generally is lowest in the humid areas, and highest in the 

arid and semi-arid West, with a tendency 

toward lower variability in the Pacific 

Northwest, which is more similar to that 

of the East than the rest of the West.

Figure 4.2 (upper panel) shows that runoff 

patterns, for the most part, follow those 

of precipitation. The runoff ratio (annual 

runoff divided by annual precipitation; 

second panel in Figure 4.2) generally decreases from east to west, but the decline 

in runoff from east to west is sharper than 

it is for precipitation. The runoff ratio 

increases in headwaters regions of the 

mountainous source areas of the West, 

and more generally in the Pacific Northwest. This increase in runoff ratio with 

elevation is critical to the hydrology of 

the West, where a large fraction of runoff 

originates in a relatively small fraction 

of the area – much more so than in the 

semi-humid East and Southeast, where 

runoff generation is relatively uniform 

spatially. The bottom panel in Figure 

4.2 shows the ratio of maximum annual 

snow accumulation to annual runoff, and 

can be considered an index to the relative 

fraction of runoff that is derived from 

snowmelt. This panel emphasizes the 

critical role of snow processes to the hydrology of the western United States, and 

to a more limited extent, in the northern 

tier of states.

Figure 4.3 shows two key aspects of 

runoff variability – the coefficient of 

variation of annual runoff, a measure 

of its variability, and its persistence in 

time (the latter expressed as the lag one 

correlation coefficient). The coefficient 

of variation of annual runoff generally follows 

that of precipitation; however, it is higher for 

the most part as the hydrologic system tends to 

amplify variability. Annual runoff persistence is 

generally low, but tends to be higher in the East 

Figure 4.2 Mean annual runoff, runoff ratio (annual mean runoff divided by annual mean 

precipitation), and ratio of maximum mean snow accumulation to mean annual runoff in 

the continental U.S. and Alaska. Data replotted from Maurer et al. (2002).
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Chapter 4

(and generally in more humid areas) than in the 

western United States. The differences between 

regions are, however, slight, and Vogel et al. 

(1998) argue that most of the United States can 

be considered to be a “homogeneous region” 

in terms of runoff persistence. It is nonetheless interesting that there is a general gradient 

downward in runoff persistence from east to 

west, which appears not to be entirely related 

to precipitation as the trend is not reversed in 

the generally more humid areas of the northwest 

and Pacific Coast regions.

4.1.2 Characteristics of Managed 

Water Resources in the United 

States

The water resources of the continental United 

States are heavily managed, mostly by surface 

water reservoirs. During the period from about 

1930 through 1980, dams were constructed at 

most technically feasible locations, with the 

result that aside from headwater regions, the 

Figure 4.3 Coefficient of variation of annual runoff (upper panel) and lag one correlation of annual runoff (lower panel). Upper panel replotted from Maurer et al. 

(2002); lower panel from Vogel et al. (1998).

flow of most rivers, especially in the western 

United States, has been heavily altered by reservoir management. Figure 4.4 (modified from 

Graf 1999) shows the extent of reservoir storage across the continental United States. From 

the standpoint of water management, the lower 

panel in Figure 4.4, which shows variations in 

the ratio of reservoir storage to mean annual 

flow, is most relevant. Although the figure scale 

is in terms of quartiles, the lowest quartile has

storage divided by mean annual runoff ratios 

in the range 0.25-0.36, and the upper quartiles

2.18-3.83 (see Graf 1999; Table 4.1). A storage to runoff ratio of one is usually taken as the 

threshold between reservoirs that are primarily 

used to shape within-year variations in runoff 

(small storage to runoff ratios; orange colors in 

Figure 4.4, lower panel) and those that are primarily used to smooth interannual variations in 

runoff (large storage to runoff ratios; dark blue 

in Figure 4.4, lower panel). In subsequent sections, these differences in storage capacity, coupled with the characteristics of the hydrologic 

systems, are defined as critical to the sensitivity 

of water resources to climate change.

4.1.3 U.S. Water Use and Water

Use Trends

The USGS compiles, at five-year intervals, information about the use of water in the United 

States. The most recent publication (Hutson et 

al. 2004) is for the period through 2000. The 

update to this publication, through 2005, unfortunately was not available as of the time of 

this writing. The data compiled by the USGS 

are somewhat limited in that they are for water 

withdrawals, rather than consumptive use. The 

distinction is important, as one of the largest 

uses of water is for cooling of thermoelectric 

power plants, and much of that water is returned 

to the streams from which it is withdrawn (use of 

water for hydroelectric power generation, virtually none of which is consumptively used, is not 

included in this category). On the other hand, a 

much higher fraction of the water withdrawn for 

irrigation is consumptively used.

Despite these limitations, the two key figures 

in the 2004 USGS publication, reproduced here 

as Figure 4.4, are instructive in that they further 

define the trends noted by Gleick et al. (2000) 

that U.S. water withdrawals have decreased 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 4.4 Reservoir storage in the continental U.S. per unit area (upper panel) 

and storage/runoff ratio (lower panel). Colors are for four quartiles of cumulative 

probability distribution. Replotted from Graf (1999).

slightly over the last 20 years in virtually all 

categories, and appear to have stabilized since 

about 1985. This is despite substantial population growth during the same period (Figure 4.4, 

upper panel).

These changes, which follow a 30-year period 

of rapid growth in water withdrawals, have 

occurred for somewhat different, but related 

reasons. Water withdrawals from many streams 

are now limited, particularly during periods 

of low flow, by environmental regulations. 

Furthermore, economic considerations have 

driven more efficient use of water. In the case 

of irrigation, there has been a transition from 

flood to sprinkler irrigation, and (albeit in a 

much smaller number of cases) much more efficient drip irrigation. Irrigation water use has 

also been affected by economic considerations, 

such as the cost of electric power to pump irrigation water.

Industrial water use efficiency gains have been 

driven by pollution control regulations, which 

encourage reduction of wastewater discharge, 

and hence more recycling. Municipal water 

use reductions have been driven by improved 

efficiency of in-house appliances and plumbing 

fixtures, as well as trends to higher density housing, which reduces use of water for landscape 

irrigation. Economic considerations have also 

had an effect on municipal water use, especially 

in municipalities where the cost of wastewater 

treatment is linked to water use. The combined 

result, as shown in Figure 4.5, is that total U.S. 

water withdrawals have been stable, which implies that per capita water use has declined.

Comparison of U.S. per capita water use (see 

Gleick 1996) globally shows that U.S. water use 

is much higher than elsewhere, even compared 

to other industrialized parts of the world such 

as Europe. It seems reasonable then to assume 

that this overall trend toward reduced per capita 

use of water will continue, at least over the next 

decade or two – notwithstanding that the Hutson 

et al (2004) trends are for the continental U.S. 

(including Hawaii in some cases) and are not 

disaggregated spatially, hence regional trends, 

past and future, may well differ.

4.2 Observed Changes in 

U.S. Water Resources

In this section observed trends in U.S. water 

resources – both physical aspects, and water 

quality – are reviewed. In general, much more

work has been done evaluating trends in physical aspects of the land surface hydrologic cycle 

than for water quality, and more attention has

been focused on the western United States than 

elsewhere. For this reason, studies of physical 

aspects are reviewed by region, but water quality

is in aggregate.

4.2.1 Observed Streamflow Trends

The most comprehensive study of trends in 

U.S. streamflow to date is reported by Lins and 
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Chapter 4

Figure 4.5 Trends in U.S. water withdrawals, 1950-2000. Upper panel: trends in 

population, groundwater, and surface water withdrawals. Lower panel: withdrawals 

by sector. Figure from Hutson et al., 2004.

Figure 4.6 Number of increasing and decreasing trends in continental 

U.S. streamflow records for a range of flow quartiles. From Lins and 

Slack (1999).

Slack (1999; 2005). It follows an earlier study 

by Lettenmaier et al. (1994) that dealt also with 

precipitation and temperature, but in less detail 

with streamflow. Given that the Lins and Slack 

study concentrates more directly on streamflow, 

and is somewhat more current, it is the focus of 

the chapter. Although the methodologies, record 

lengths, and locations differ somewhat for the 

two studies, to the extent that the results can be 

compared, they are generally consistent.

Lins and Slack (1999) analyzed long-term 

streamflow records for a set of 395 stations 

across the continental United States for which 

upstream effects of water management were 

minimal, and which had continuous (daily) 

records for the period 1944-93 (updated to 435 

stations for the period 1940-99 by Lins and 

Slack (2005)). For each station, they formed 

time series of minimum and maximum flows, 

as well as flows at the 10th, 30th, 50th, 70th, 

and 90th percentiles of the flow duration curve. 

They found, consistent with Lettenmaier et al. 

(1994), that there was a preponderance of upward streamflow trends (many more than would 

be expected due to chance) in all but the highest 

flow categories (see Figure 4.6), for which the 

number of upward and downward trends was 

about the same. In addition to the 50-year period 

of 1944-93, similar analyses were conducted for 

the smaller number of stations having 60, 70, 

and 80 years of record (all ending in 1993), and 

the fraction of upward and downward trends 

was about the same as for the analysis of the 

larger number of stations with at least 50 years 

of record.

Lins and Slack (2005) update the analysis to a 

“standard” 60-year period, 1940-99, but unlike 

their earlier paper, do not consider longer periods with smaller numbers of stations. Neither the 

1999 nor the 2005 papers attempt to attribute the 

observed trends to climatic warming, although 

the spatial coherence in the trends suggests that 

non-climatic causes (e.g., land cover change), 

are not likely the cause. However, as noted in 

Cohn and Lins (2006), hydroclimatic records by 

nature reflect long term persistence associated 

with climate variability over a range of temporal 

scales, as well aslow frequency effects associated with land processes, so the mere existence of 

trends in and of itself does not necessarily imply 

a causal link with climate change. Summaries of 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 4.7 Statistically significant trends in streamflow across the continental 

United States. At each station location, direction of trend and significance level 

(if statistically significant at less than 0.05 level) are plotted for minimum, 

median, and maximum of the annual flows. Upper panel: 393 stations at which 

data were available from 1944-93; middle panel: same for 1934-93; lower 

panel: same for 1924-93. Data replotted from Lins and Slack (1999).

the Lins and Slack results are shown in Figure 

4.7a-c, which plots the location and strength (as 

significance level) of trends at a subset of USGS 

Hydroclimatic Data Network (HCDN) stations 

with the longest records (note that in Figure 4.7 

green indicates no significant trend at the 0.05 

significance level).

Mauget (2003) used a method based on running 

time windows of length 6-30 years applied to 

streamflow records for the 1939-98 period 

extracted from the same USGS HCDN used 

by Lins and Slack (1999). The Mauget (2003) 

analysis was based only on the 167 stations 

for which data were available for the period 

1939-98, and hence make up a somewhat different station set than was used by Lins and Slack. 

(It is worth noting that many of the stations 

used in the Mauget et al. study are likely the 

same as those used by Lins and Slack in their 

60-year (1934-93) set of 193 stations. It should 

also be noted that the Mauget study is based 

on mean annual flow, while Lins and Slack 

use percentiles of the annual flow distribution, 

including the median.) The results of the Mauget 

et al. (2003) study are broadly similar to Lins 

and Slack (1999) to the extent that comparisons 

are possible. Mauget finds evidence of high 

streamflows being more likely toward the end 

of the record than the beginning in the eastern 

United States, especially in the 1970s, and “a 

coherent pattern of high-ranked annual flow....

beginning during the later 1960s and early 

1970s, and ending in either 1997 or 1998.” By 

contrast, he found a more or less reverse pattern 

in the western United States, with an onset of 

dry conditions beginning in the 1980s.

4.2.2 Evaporation Trends

Several studies have been performed to assess 

changes in evapotranspiration (ET), another 

major influence on the land surface water balance. Unfortunately, there are no long-term ET 

observations. Methods that enable direct measurements (e.g., via eddy flux methods) have 

only been available for about 20 years, and are 

still used primarily in intensive research settings 

rather than for assessing long-term trends. Another source of evaporation data is records from 

evaporation pans, which are generally located 

in agricultural areas and have been used as an 

index to potential evaporation. These records 

are generally longer and a number (several 
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hundred over the continental United States) have 

record lengths approaching 50 years. Several 

studies (e.g., Peterson et al. 1995; Golubev et 

al. 2001) have shown that pan evaporation 

records over the United States generally had 

downward trends over the second half of the 

20th century. This is contrary to the expectation 

that a generally warming climate would increase 

evapotranspiration.

Two explanations have been advanced to account for this trend. The first is the so-called 

evaporation paradox (Brutsaert and Parlange, 

1998), which holds that increasing evaporation 

alters the humidity regime surrounding evaporation pans, causing the air over the pan to be 

cooler and more humid. This “complementary 

hypothesis” suggests that trends in pan and 

actual evaporation should indeed be in the opposite direction. Observational evidence, using 

U.S. pan evaporation data and basin-scale actual 

evaporation, inferred by differencing annual precipitation and runoff, suggests that trends in U.S. 

pan and actual evaporation have in fact been in 

opposite directions (Hobbins et al. 2004).

The second hypothesis is that actual ET may 

also have declined due to reduced net radiation, 

resulting from increased cloud cover (Huntington et al. 2004). This hypothesis is consistent 

with observed downward trends in the daily 

temperature range (daily minimum temperatures 

have generally increased over the last 50 years, 

while daily maxima have increased more slowly, 

if at all); the temperature range is generally related to downward solar radiation, which would 

therefore have decreased. Unfortunately, as with 

actual evaporation, long-term records of surface 

solar radiation are virtually nonexistent, so indirect estimates (such as cloud cover, or daily 

temperature range) must be relied on. Roderick 

and Farquahr (2002) argue that decreasing net

solar irradiance resulting from increased cloud 

cover and aerosol concentrations is a more likely 

cause for the observed changes, and that actual 

evaporation should generally have decreased, 

consistent with the pan evaporation trends.

Brutsaert (2006) argues that “the significance 

of this negative trend [in pan evaporation], as 

regards terrestrial evaporation, is still somewhat controversial, and its implications for the 

global hydrologic cycle remain unclear.” The 

controversy stems from the apparently contradictory views that the observed changes result 

either from global radiative dimming, or from 

the complementary relationship between pan 

and terrestrial evaporation. Brutsaert (2006) 

argues that these factors are in fact not mutually 

exclusive, but act concurrently. He derives a 

theoretical relationship between trends in actual 

evaporation, net radiation, surface air temperature, and pan evaporation, and shows that the 

observed trends are generally consistent, accounting for the generally observed downward 

trend in net radiation (“global dimming”) albeit 

from sparse observations.

4.2.3 U.S. Drought Trends

Andreadis and Lettenmaier (2006) investigated 

trends in droughts in the continental United 

States using a method that combined long-term 

observations with a land surface model. Their 

approach was to use gridded observations of 

precipitation and temperature that were adjusted 

to have essentially the same decadal variability 

as the Historical Climatology Network (HCN) 

stations, which have been carefully qualitycontrolled for changes in observing methods. 

These are used to force a land surface model, 

and then used to evaluate trends in several 

drought characteristics in both model-derived 

soil moisture and runoff. Results show that the 

spatial character of trends in the model-derived 

runoff is in general consistent with the observed 

streamflow trends from Lins and Slack (1999). 

Andreadis and Lettenmaier also show that, generally, the continental United States became wetter over the period analyzed (1915-2003), which 

was reflected in upward trends in soil moisture 

and downward trends in drought severity and 

duration. However, there was some evidence of 

increased drought severity and duration in the 

western and southwestern United States. This 

was interpreted as increased actual evaporation 

dominating the trend toward increased soil wetness, which was evident through the rest of the 

United States.

There is evidence that much more severe 

droughts have occurred in North America prior 

to the instrumental record of roughly the last 

100 years. For instance, Woodhouse and Overpeck (1998), using paleo indicators (primarily 

tree rings), find that many droughts over the 

last 2,000 years have eclipsed the major U.S. 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

droughts of the 1930s and 1950s, with much 

more severe droughts occurring as recently as 

the 1600s. Although the nature of future drought 

stress remains unclear, for those areas where 

climate models suggest drying, such as the 

Southwest (e.g., Seager et al. 2007), droughts 

more severe than those encountered in the 

instrumental record may become increasingly 

likely.

4.2.4 Regional Assessment of

Changes in U.S. Water

Resources

For purposes of this section, the continental 

United States is partitioned into four “superregions” using aggregations of the USGS 

hydrologic regions chosen on the basis of hydroclimatic similarity (Figure 4.8) as follows: West 

(Pacific Northwest, California, Great Basin, 

Upper Colorado, Lower Colorado, Rio Grande, 

and upper Missouri); Central (Arkansas-Red, 

lower Missouri, Upper Mississippi, Souris-RedRainy, and Great Lakes); Northeast (New England, Mid Atlantic, Ohio, and northern half of 

South Atlantic-Gulf); and South and Southeast 

(Tennessee, Lower Mississippi, Texas-Gulf, 

and southern half of South Atlantic-Gulf), as 

well as Hawaii and Alaska. Hawaii and Alaska 

are each treated as separate regions. Observed 

changes over each of these parts of the country 

are summarized below.

4.2.4.1 West

The western United States has been more 

studied than any of the other regions in terms 

Figure 4.8 Super-regions as aggregates of USGS hydrologic regions.

of both observed climate-related changes in 

hydrology and water resources, and the future 

implications. This is because: a) the western 

United States is, in general, more water-limited 

than is the rest of the United States, hence any 

changes in the availability of water have more 

immediate and widespread consequences, and

b) much of the runoff in the western United 

States is derived from snowmelt, and therefore 

western U.S. streamflow is sensitive to ongoing and future climate change in ways that are 

more readily observable than elsewhere in the 

United States.

Much of the recent work on observed changes 

in the hydrology of the western United States 

has focused on changes in observed snowpack. 

Mote (2003) analyzed 230 time series of snow 

water equivalent (SWE) in the Pacific Northwest

(defined as the states of Washington, Oregon, 

Idaho, and Montana west of the Continental 

Divide, and southern British Columbia) for the 

period 1950-2000 (in some cases longer). These 

records originate mostly from manual snow 

courses at which snow cores were taken at about 

the same time each year (in some cases, more 

than once, but at most locations around April 1), 

primarily for the purpose of predicting subsequent spring and summer runoff for water management purposes. Mote (2003) found that over 

this region, there was a strong preponderance 

of downward trends, especially in the Cascade 

Mountains, where winter temperatures generally 

are higher than elsewhere in the region. Also, 

the decreases in SWE were generally larger in 

The western 

United States has 

been more studied 

than any of the 

other regions in 

terms of both 

observed climaterelated changes in 

hydrology and water 

resources, and the 

future implications.
The U.S. Climate Change Science Program

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Chapter 4

absolute value at lower than at higher elevations. He noted that changes in precipitation, 

as well as decadal scale variability (especially 

the widely acknowledged shift in the Pacific 

Decadal Oscillation (PDO) in about 1977) may 

have contributed to the observed trends, but argued that the PDO shift alone could not explain 

changes in SWE over the period analyzed. He 

also concluded that while regional warming has 

played a role in the decline in SWE, “... regional 

warming at the spatial scale of the Northwest 

cannot be attributed statistically to increase in 

greenhouse gasses.”

Mote et al. (2005) expanded the analysis of Mote 

(1999) to the western United States, and used 

a combination of modeling and data analysis, 

similar to the approach used by Andreadis and 

Lettenmaier in their continental United States 

drought analysis, to analyze changes in SWE 

over the western United States for the period 

1915-2003. They used the snow accumulation 

and ablation model in the Variable Infiltration 

Capacity (VIC) macroscale hydrology model 

(Liang et al. 1994) to simulate SWE over the 

entire western United States for the period of 

interest, and then compared simulated trends 

and their dependence on elevation and average 

winter temperature with snow course observations. They found, notwithstanding considerable variability at the scale of individual snow 

courses, that the spatial and elevation patterns of 

trends agreed quite well over the region. They

then analyzed reconstructed records for the 

entire period 1915-2003 and evaluated trends. 

The advantage of this approach is that the longer 

1915-2003 period spans several phase changes 

in the PDO, and therefore effectively filters out 

its effect on long-term trends. They found that 

over the nearly 80-year period, there had been 

a general downward trend in SWE over most of 

the region. The exception was the southern Sierra Nevada, where an apparent upward trend in 

SWE, especially at higher elevations, appeared 

to have resulted from increased precipitation, 

which more than compensated for the generally 

warming over the period.

Hamlet et al. (2005) extended the work of Mote 

et al. (2005) and through sensitivity analysis 

determined that most of the observed SWE 

changes in the western United States can be 

attributed to temperature rather than precipitation changes. Hamlet et al. (2007) used a similar 

strategy of driving the Variable Infiltration Capacity (VIC) hydrological model with observed 

precipitation and temperature and found, over 

the 1916-2003 period, that trends in soil moisture, ET, and runoff generally can be traced 

to shifts in snowmelt timing associated with 

a general warming over the period. In a companion paper, Hamlet and Lettenmaier (2007) 

assessed changes in flood risk using a similar 

approach. Their analysis showed that in cold 

(high elevation and continental interior) river 

basins flood risk was reduced due to overall 

reductions in spring snowpack. In contrast, for 

relatively warm rain-dominant basins (mostly 

coastal and/or low elevation) where snow plays 

little role, little systematic change in flood risk 

was apparent. For intermediate basins, a range 

of competing factors such as the amount of 

snow prior to the onset of major storms, and the 

contributing basin area during storms (i.e., that 

fraction of the basin for which snowmelt was 

present) controlled flood risk changes, which 

were less easily categorized.

Stewart et al. (2005) analyzed changes in the 

timing of spring snowmelt runoff across the 

western United States. They computed several 

measures of spring runoff timing using 302 

streamflow records across the western United 

States, western Canada, and Alaska for the period 1948-2002. The most useful was the center 

of mass timing (CT), which is the centroid of the 

time series of daily flows for a year. As shown 

in Figure 4.9, they found consistent shifts earlier 

in time of CT for snowmelt-dominated (mostly 

mountainous) river basins, but little change (or 

changes toward later runoff) for coastal basins 

without a substantial snowmelt component. 

Although they noted the existence of the PDO 

shift part way through their period of record, 

Stewart et al. (2005) argue that the variance in 

CT is explained both by temporal changes in the 

PDO and a general warming in the region, and 

that variations in PDO alone are insufficient to 

explain the observed trends. This finding is supported by the absence of coherent shifts in CT 

for non-snowmelt-dominated streams.

Pagano and Garen (2005) found that the variability of April-September streamflow at 141 

unregulated sites across the western United 

States has generally increased from about 1980 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 4.9 Changes in western U.S. snowmelt runoff timing, 1948-2002. Source: Stewart et al. (2005).

onward. This contrasts with a period of markedly 

low variability over much of the region from 

about 1930 through the 1970s. Although such 

shifts at decadal time scales have been observed 

before, and are even expected due to the nature 

of decadal scale variability, increased streamflow 

variability is a major concern for water managers, as it tends to diminish the reliability with 

which water demands can be satisfied.

4.2.4.2 Central

There has been relatively little work evaluating 

hydrologic trends in the central United States 

more specific than the U.S.-wide work of Lins 

and Slack (1999), and Mauget (2003). Garbrecht 

et al. (2004) analyzed trends in precipitation, 

streamflow, and evapotranspiration over the 

Great Plains. They found in an analysis of 10 

watersheds in Nebraska, Kansas, and Oklahoma 

with streamflow records starting from 1922 to 

1950 (median start year about 1940) and all ending in 2001, a common pattern of increasing annual streamflow in all watersheds. Most of this 

occurred in spring and winter (notwithstanding 

that most of the annual precipitation in these 

basins occurs in spring and summer). Garbrecht 

et al. also found that the relative changes in 

annual streamflow were much larger than in 

annual precipitation, with an average 12 percent 

increase in precipitation, leading to an average 

64 percent increase in streamflow, but only a 

5 percent increase in evapotranspiration. They 

also note that the large increases in streamflow 

had mostly occurred by about 1990 and in some 

(but not all) of the basins the trend appeared to 

have reversed in the last decade of the record.

Mauget (2004) analyzed annual streamflow 

records at 42 USGS Hydro-Climatic Data 

Network stations in a large area of the central 

and southern United States (stations included 

were as far west as eastern Montana and Colorado, as far east as Ohio, as far north as North 

Dakota, and as far south as Texas). They used 

an approach similar to that of Mauget (2003). 

Although the patterns vary somewhat across the 

stations, in general higher flow periods tended 

to occur more toward the end of the period than 

the beginning, indicating general increases in 

streamflow over the period. A more detailed 

analysis of daily streamflows indicates negative changes in the incidence of drought events 

(defined as sequences of days with flows below

a station-dependent threshold) and increases in 

the incidence of “surplus” days (days with flows 

above a station-dependent surplus threshold). 

These results are broadly consistent with those 

of Lins and Slack (1999), and Andreadis and 

Lettenmaier (2006).

...increased 

streamflow variability 

is a major concern for 

water managers, as it 

tends to diminish the 

reliability with which 

water demands can 

be satisfied.
The U.S. Climate Change Science Program

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Chapter 4

4.2.4.3 Northeast

The Northeast region is distinctive in that many 

records relating to hydrologic phenomena are 

relatively long. Burns et al. (2007) report that 

based on data from 1952 to 2005 in the Catskill 

region of New York State (the source of most 

of New York City’s water supply), peak snowmelt generally shifted from early April at the 

beginning of the record to late March at the 

end of the record, “consistent with a decreasing 

trend in April runoff and an increasing trend in 

maximum March air temperature.” Burns et al. 

(2007) also report increases in regional mean 

precipitation and regional mean potential evapotranspiration (PE), with generally increased 

regional runoff.

Hodgkins et al. (2003) and Hodgkins and Dudley (2006a) studied high flows in rural, unregulated rivers in New England, where snowmelt 

dominates the annual hydrological cycle. They 

showed significantly earlier snowmelt runoff 

(using methods similar to those applied in the 

western United States by Stewart et al. (2005)), 

with most of the change (advances of center of 

volume of runoff by one to two weeks) occurring in the last 30 years. Hodgkins et al. (2002) 

also noted reductions in ice cover in New England. Spring ice-out (when lake ice cover ends) 

records between 1850 and 2000 indicate an 

advancement of nine days for lakes in northern 

and mountainous regions, and 16 days for lakes 

in more southerly regions. These changes were 

generally found to be related to warmer air 

temperatures.

Huntington et al. (2004) analyzed the ratio of 

snow to precipitation (S/P) for Historical Climatology Network (HCN) sites in New England 

and found a general decrease in the ratio and 

decreasing snowfall amounts, which is consistent with warming trends. Hodgkins and Dudley 

(2006b) found that 18 of 23 snow course sites in 

and near Maine with records spanning at least 

50 years had decreases in snowpack depth or 

increases in snowpack density, changes that are 

also consistent with a warming climate.

The Ohio Basin, also included within the defined northeast “super-region,” is relatively 

understudied in terms of climate change (Liu et 

al. 2000) despite its economic and demographic 

importance and the significance of its flow (it 

contributes 49 percent of the total Mississippi 

River flow at Vicksburg). The Lins and Slack 

(1999) study of streamflow trends across the 

United States found increases in minimum and 

median flows at several locations in the Ohio 

basin, but no trend in maximum flows. McCabe 

and Wolock (2002a) describe a step change 

(increases) around 1970 in U.S. streamflow, 

which was most prevalent in the eastern United 

States, including the Ohio River. They related 

this apparent shift to a possible change in climate regime. Easterling and Karl (2001) note 

that during the 20th century there was a cooling 

of about 0.6°C in the Ohio basin, with warming 

in the northern Midwest of about 2°C for the 

same period. But they also report that the length 

of the snow season in the Ohio Valley over the 

second half of the 20th century decreased by as 

much as 16 days. In a study of evaporation and 

surface cooling in the Mississippi basin (including the Ohio River), Milly and Dunne (2001) 

suggest that high levels of precipitation were 

caused by an internal forcing, and that a return 

to normal precipitation could reveal warming 

in the basin.

Moog and Whiting (2002) studied the relationship of hydrologic variables (precipitation, 

streamflow, and snow cover) to nutrient exports 

in the Maumee and Sandusky river basins adjacent to the northern boundary of the Ohio. While 

not focused on climate-related changes directly, 

it allows inferences to be made of how climate 

change might impact water quality in the basin.

Antecedent precipitation and streamflow were 

found to be negatively correlated to pollution 

loading, and snow cover tended to delay nutrient export. These results suggest how shifts in 

seasonal streamflow, and the increases in low 

and median flows observed by Lins and Slack 

(1999), might impact nutrient export from the 

basin.

4.2.4.4 South and Southeast

No studies were found that dealt specifically 

with hydrologic trends in the South and Southeast, although the national study of Lins and 

Slack shows generally increasing streamflow 

over most of this region in the second half of 

the 20th century. This result is consistent with 

Mauget (2003) and the part of the domain 

studied by Mauget (2004) that lies in the South 

and Southeast super-region. A related study 
133

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

by Czikowsky and Fitzjarrald (2004) analyzed 

several aspects of seasonal and diurnal streamflow patterns at several hundred USGS stream 

gauge stations in the eastern and southeastern 

United States, as they might be related to evapotranspiration changes that occur at the onset 

of spring. They found a general shift in runoff 

patterns earlier in the spring in Virginia (as well 

as in New England and New York), but not in 

Pennsylvania and New Jersey.

4.2.4.5 Alaska

Hinzman et al. (2005) review evidence of changes in the hydrology and biogeochemistry of 

northern Alaska (primarily Arctic regions). They 

showed decreases in warm season surface water 

supply, defined as precipitation minus potential 

evapotranspiration, at several sites on the Arctic 

coastal plain over the last 50 years. Precipitation 

was observed and potential evapotranspiration 

was computed using observed air temperature. 

These downward trends were related primarily 

to increased air temperature, as precipitation 

trends generally were not statistically significant 

over the period. Permafrost temperatures from 

borehole measurements at 20-meter depth have 

increased over the last half-century, with the increases most marked over the last 20 years. The 

authors also found some evidence of increasing 

discharge of Alaskan Arctic rivers over recent 

decades, although short records precluded a 

rigorous trend analysis. Records of snow cover 

at Barrow indicate that the last day of snow 

cover has become progressively earlier, by about 

two weeks over 60 years. Stewart et al. (2005), 

in their study of seasonal streamflow timing, 

included stations in Alaska (mostly south and 

southeast), and found that the shifts toward 

earlier timing of spring runoff in the western 

United States extended into Alaska (see Figure 

4.8). Lins and Slack (1999) included a handful 

of HCDN stations in southeast Alaska, for which 

there did not appear to be significant trends over 

the periods they analyzed.

4.2.4.6 Hawaii

Oki (2004) analyzed 16 long-term USGS 

streamflow records from the islands of Hawaii, 

Maui, Molokai, Oahu, and Kauai for the period 

1913-2002. They found that for all stations, 

there were statistically significant downward 

trends in low flows, but that trends were generally not significant for annual or high flows. 

When segregated into baseflow and total flow, 

baseflow trends were significant across almost 

the entire distribution (mean as well has high 

and low percentiles). In general, low and base 

flows increased from 1913 to about the early 

1940s, and decreased thereafter. Oki also found 

that streamflow was strongly linked to the El 

Niño-Southern Oscillation (ENSO), with winter flows tending to be low following El Niño 

events and high following La Niña events. The 

signal is modulated to some extent by the PDO, 

and is most apparent in the total flows, and to a 

lesser extent in baseflows. Oki (2004) noted that 

changes in ENSO patterns could be responsible 

for the observed long-term trends, but did not 

attempt to isolate the portion of the observed 

trends that could be attributed to interannual and 

interdecadal variability attributable to ENSO 

and the PDO.

4.2.5 Water Quality

Water quality reflects the chemical inputs from

air and landscape and their biogeochemical 

transformation within the water (Murdoch et al. 

2000). The inputs are determined by atmospheric processes and movement of chemicals via 

various hydrologic flowpaths of water through 

the watershed, as well as the chemical nature of 

the soils within the watershed. Water quality is

also broadly defined to include indicators of ecological health (e.g. sensitive species). Regional 

scale variation in natural climatic conditions 

(precipitation patterns and temperature) and local variation in soils generates spatial variation 

in “baseline” water quality and specific potential

response to a given scenario of climate change. 

A warming climate is, in general, expected to 

increase water temperatures and modify regional 

patterns of precipitation, and these changes can 

have direct effects on water quality. However,

a major challenge in attributing altered water 

quality to climate change is the fact that water

quality is very sensitive to other nonstationary

human activities, particularly land use practices 

that alter landscapes and modify flux of water, 

as well as thermal and nutrient characteristics 

of water.

In general, water quality issensitive to temperature and water quantity. Higher temperatures

enhance rates of biogeochemical transformation and physiological processes of aquatic

plants and animals. As temperature increases, 

A warming climate 

is, in general, 

expected to 

increase water 

temperatures and 

modify regional 

patterns of 

precipitation, and 

these changes can 

have direct effects 

on water quality.
The U.S. Climate Change Science Program

134

Chapter 4

the ability of water to hold dissolved oxygen 

declines, and as water becomes anoxic, animal 

species begin to experience suboptimal conditions. Nutrients in the water enhance biological 

productivity of algae and plants, which increases 

oxygen concentration by day, but at night these 

producers consume oxygen; oxygen sags can 

impose suboptimal anoxic conditions. Increased 

streamflow can dilute nutrient concentrations 

and thus diminish excessive biological production, however higher flows can flush excess 

nutrients from sources of origin in a stream. The 

overall balance of these competing effects in a 

changing climate is not yet known.

Most studies examining the responses of water 

quality over time have focused on nutrient

loading. This factor has changed significantly 

over time, and there are specific U.S. laws (e.g., 

Clean Water Act) designed to reduce nutrient 

inputs into surface waters to increase their quality. For example, Alexander and Smith (2006) 

examined trends in concentrations of total 

phosphorus and total nitrogen and the related 

change in the probabilities of trophic conditions from 1975 to 1994 at 250 river sites in the 

United States with drainage areas greater than 

1,000 km2. Concentrations in these nutrients 

generally declined over the period, and most 

improvements were seen in forested and shrubgrassland watersheds compared to agricultural 

and urban watersheds. Ramstack et al. (2004) 

reconstructed water chemistry before European 

settlement for 55 Minnesota lakes. They found 

that lakes in forested regions showed very little 

change in water quality since 1800. By contrast,

about 30 percent of urban lakes and agricultural 

lakes showed significant increases in chloride 

(urban) or phosphorus (agricultural). These results indicate the strong influence of land use on 

water quality indicators. Detecting the effects of

climate change requiresthe identification of reference sites that are not influenced by the very 

strong effects of human land use activities.

Recent historical assessments of changes in 

water quality due to temperature trends have

largely focused on salmonid fishes in the western United States. For example, Bartholow 

(2005) used USGS temperature gauges to 

document a 0.5°C per decade increase in water 

temperatures in the lower Klamath River from 

the early 1960s to 2001, driven by basin-wide 

increase in air temperatures. Such changes may 

be related to PDO. Increases in water temperature can directly and indirectly influence salmon 

through negatively affecting different life stages. 

Crozier and Zabel (2006) reported that air temperatures have risen 1.2°C from 1992 to 2003 

in the Salmon River basin in Idaho. Because 

water temperatures show a correlation with air 

temperature, smaller snowpacks that reduce 

autumn flows and cause higher water temperatures are expected to reduce salmon survival. 

Temperature effects can be indirect as well. 

For example, Petersen and Kitchell (2001) examined climate records for the Columbia River 

from 1933 to 1996 and observed variations of 

up to 2°C between “natural” warm periods and 

cold periods. Using a bioenergetics model, they 

showed that warmer water temperatures are associated with an expected higher mortality rate 

of young salmon due to fish predators.

4.3 Attribution of 

Changes

Trend attribution essentially amounts to determining the causes of trends. Among the various 

agents of hydrologic change, the most plausible 

are: a) changing climate, b) changing land cover 

and/or land use, c) water management, and d) 

instrumentation changes, or effects of other systematic errors. Among the causes of streamflow 

trends (the variable assessed by most studies 

reviewed in this chapter), water management 

changes are the easiest to quantify. With respect

to changes in streamflow, the studies cited have 

all used streamflow records selected to be as free 

as possible of water management effects. For 

instance, USGS HCDN stations, used by Lins 

and Slack (1999; 2005), as well as several other 

studies reviewed, were selected specifically 

based on USGS metadata that indicate the effects of upstream water management. Certainly, 

it is not impossible for the metadata to be in error. An earlier study by Lettenmaier et al. (1994) 

that used a set of USGS records that pre-dated 

HCDN, selected using similar methods and 

identified some stations where there were obvious water management effects upstream, despite 

metadata entries to the contrary. However, the 

number of such stations was small, and the clear 

spatial structure in the Lins and Slack results 
135

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

shown in Figure 4.7, for instance, are unlikely 

to be the result of water management effects. 

If they were, it would require a corresponding

spatial structure to errors in the metadata, which 

seems highly unlikely. In short, while it could be 

that some of the detected trends are attributable 

to undocumented water management effects, it 

is highly unlikely that the same could be said for 

the general patterns and conclusions.

Changes in instrumentation are always of 

concern in trend detection studies, as shifts in 

instrumentation often are implemented at a particular time, and hence can easily be confounded 

with other trend causes. This is a problem, 

for instance, with precipitation measurement, 

where changes in gauge types, wind shields, 

and other particulars complicate trend attribution (it should be noted that these problems are 

addressed in precipitation networks like the U.S. 

Historical Climatology Network, which has had 

adjustments made for observing system biases). 

In contrast, for streamflow observations, the 

methods are relatively straightforward; the measured variable is river stage, which is converted 

to discharge via a stage-discharge relationship, 

formed from periodic coincident measurements 

of discharge and stage. The USGS has wellestablished protocols for updating stagedischarge relationships, especially following 

major floods, which may affect the local hydraulic control. Therefore, while there almost 

certainly are cases where bias is introduced 

into discharge records following rating curve 

shifts, it is unlikely that such shifts would persist 

though a multi-decadal record, and even more 

unlikely that observed spatial patterns in trends 

could be caused by rating curve errors.

Distinguishing between the two remaining possible causes of trends – land cover and/or land 

use change and climate – requires more complicated analysis. Some land cover/land use change 

effects have striking effects on runoff. Urbanization is one such change agent, which typically 

decreases storm response time (the time between 

peak precipitation and peak runoff), increases 

peak runoff following storms, and decreases 

base flows (as a result of decreased infiltration). 

However, urban areas are generally avoided in 

selection of stations to be included in networks 

like HCDN, so urbanization is unlikely to be a 

major contributor. Other aspects of land cover 

change, however, such as conversion of land use 

to or from agriculture and forest harvest, tend 

to affect much larger areas. Conversions often 

occur over many decades. Hence, they have time 

constants that are similar to decadal and longer 

scale climate variability. Although many studies 

at catchment scale or smaller have attempted 

to quantify the effects on runoff of vegetation

change such as forest harvest (Stednick et al. 

1996), few studies have evaluated the larger 

scale effects. Matheussen et al. (2000) studied 

land cover change in the Columbia River basin 

from 1900 to 1990, and estimated that changes 

to annual runoff from forest harvest and fire suppression were at most 10 percent (in one of eight 

sub-basins analyzed, more typical changes were 

of order 5 percent) over this time period. Other 

studies have indicated larger changes (Brauman et al. 2007). On the other hand, studies of 

smaller basins, where a large fraction of the basin can be perturbed over relatively short periods 

of time, have projected or measured much larger 

changes (see Bowling and Lettenmaier (2001) 

for an example of modeled changes of forest 

harvest, and Jones and Grant (1996) for an observational study). However, over basins the size 

of which have been analyzed within networks 

like HCDN, more modest changes are likely, 

and over basins with drainage areas typical of 

HCDN (drainage areas hundreds to thousands of 

km2 and up) efforts to isolate vegetation change 

from climate variability have been complicated 

by signal-to-noise ratios that are usually smaller 

for the vegetation than the climatic signal (see 

Bowling et al. 2000 for an example). It must be 

acknowledged, however, that some studies have 

reported changes in the hydrologic response 

of intermediate sized drainage basins, such as 

those included in the HCDN, that appear to be 

attributable to land cover rather than to climate 

change (see e.g. Potter, 1991). In summary, it 

is unlikely that the hydrologic trends detected 

in the various studies reviewed above can be attributed, at least in large part, to land cover and 

land use change, butsufficient questionsremain

that it cannot be definitively ruled out.

The final cause to which long-term hydrological trends might be attributed is climate 

change. Although it is essentially impossible 

to demonstrate cause and effect conclusively, 
The U.S. Climate Change Science Program

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Chapter 4

streamflow (and other land surface hydrological 

variables) clearly are highly sensitive to climate, especially precipitation. Therefore, it is 

possible to compare trends in precipitation, for 

instance, with those in runoff, and most efforts 

in the continental United States that do so (some 

explicit, others more indirect), show a general 

correspondence. Certainly, this effect is clear in 

the Lins and Slack (1999; 2005) results, which 

show generally increased streamflow over most 

percentiles of the flow frequency distribution.

These trends seem to correspond to generally 

upward trends in precipitation across much of 

the continental United States. For the annual 

maxima (floods), the correspondence to precipitation is less obvious. While various studies 

have shown increases in intense precipitation 

across the continental United States (e.g., Groisman et al., 1999), the absence of corresponding 

increases in flood incidence remains a somewhat 

open question. Groisman et al. (2001) used

the same data as Lins and Slack (1999) and 

performed an analysis (updated by Groisman 

et al. (2004), who also used an area averaging 

approach rather than station-specific time series) 

to show that shifts in the probability distribution 

of extreme precipitation in general correspond to 

shifts in flood distributions. Possible reasons for 

the discrepancy between the two sets of studies 

include: a) the “floods” analyzed by Groisman et 

al. (2001) are not of the same general magnitude 

as the annual maxima series analyzed by Lins 

and Slack (1999); b) the shifts in intense precipitation observed by Groisman et al. (1999) and 

others occur mostly during periods of the year 

when extreme floods are uncommon; and/or c) 

the area-averaging approach used in the Groisman et al. studies filters out natural variability 

that obscures trends in the station data. Lins 

(2007), however, offers a more straightforward 

explanation. Groisman et al. (2001; 2004) test 

for trends in a variable that essentially is the 

fraction of the mean contributed by the highest 

5th percentile of the flow distribution (which in 

turn is averaged spatially). Because the distribution of (e.g., daily) streamflow is positively 

skewed, a disproportionate fraction of the mean 

flow is accounted for by the upper percentiles, 

which tends to amplify changes. Lins (2007) 

concludes that “..the differences between the 

Groisman et al. findings and those of the [other 

studies] are apparent and interpretive rather 

than substantive.” It is also noteworthy that 

Groisman et al. (2004) note that by extending 

their data record through 2003, several relatively 

dry years were included in the analysis, and the 

spatially averaged discharge change for the upper 5th percentile no longer had a statistically 

significant change.

Notwithstanding these difficulties related to the 

upper tail of the streamflow distribution, most 

streamflow trends do generally correspond to 

observed trends in precipitation. The question

remains, though, whether these changes are 

evidence of climate change or decadal (or longer) scale variability? This question cannot be

addressed through hydrologic analysis alone. 

For example, observed downward trends in 

streamflow in the Pacific Northwest are difficult 

to discriminate from changes associated with a 

mid-70s shift in the PDO, especially because 

this change occurred at about the mid-point of 

many streamflow records (many stations in the 

Pacific Northwest date to the late 1940s). One 

way to deal with this issue is through use of 

model reconstructions (e.g. Mote et al. 2005; 

Hamlet et al. 2007), which attempt to segregate 

decadal scale variability from longer-term (century or longer) shifts. An alternative approach 

reported by Barnett et al. (2008) involves use 

of a “climate fingerprinting” technique. Barnett

et al. (2008) used a 1600-year control run in 

which a global climate model was used to force 

a regional hydrological model to characterize 

natural variability. Examination of the 1950-99 

period of observations in the context of longerterm natural variability indicated that as much as 

60 percent of the observed trends in streamflow, 

winter air temperature, and snow water equivalent (SWE) were human-induced.

Most of the studies reviewed in this chapter do 

not incorporate methods of trend attribution, 

and conclusions must be qualified to this effect

(as the authors have done explicitly in many 

cases). Trend attribution for hydrologic applications is an evolving field and methods that are 

presently available are not nearly as refined as 

are trend estimation methods. This is an area to 

which research attention seems likely to turn in 

the future.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

4.4 Future Changes and 

Impacts

This section examines recent work that assesses 

the potential impacts of climate change over the 

next several decades on the water resources and 

water quality of the United States. Numerous

studies of the impacts of climate change on U.S. 

water resources have been performed, many of 

which are reviewed in, for instance, special issues of journals (see, for instance, Gleick 1999) 

and IPCC reports (e.g., Arnell and Liu 2001). An 

exhaustive review of this considerable body of 

research is beyond the scope of this chapter, and 

instead is limited to a review of the work that 

derives directly from climate scenarios archived 

for the 2007 IPCC assessment.

This recent work has several particular features. 

First, the global greenhouse gas emissions scenarios used in global model runs archived for 

use with the 2007 IPCC assessment are generally more consistent across models than in previous IPCC studies. Most models were run with 

transient scenarios where global greenhouse 

gases increased over time from an initial condition that typically is consistent with conditions 

as of about 2000, as specified in the IPCC (2000) 

Special Report on Emissions Scenarios (SRES). 

Although this report was issued prior to the 2001 

IPCC Third Assessment Report, the full effect 

of the SRES report was not felt until the IPCC 

Fourth Assessment Report (2007) because of 

the lag time of several years that is required to

run GCMs (often incorporating model improvements) and to archive their output. Second, the 

GCM physical parameterizations have improved 

with time, as has their spatial resolution, notwithstanding that the spatial resolution of most 

models is still coarse relative to the spatial scales 

required for regional impact assessments. Third,

the length of GCM model runs has generally 

increased, with most modeling centers that have 

made runs available for IPCC analyses now producing simulations of length at least 100 years, 

and in many cases with multiple ensembles for 

each of several emissions scenarios. Finally, 

archiving model runs at the Lawrence Livermore 

National Laboratory’s Program for Climate 

Model Diagnosis and Intercomparison (PCMDI) 

in common formats has greatly facilitated user 

access to the climate model scenarios.

Milly et al. (2005) evaluated global runoff 

from a set of 24 model runs archived for the 

IPCC AR4. They pre-screened model results 

by comparing model-estimated runoff from 

20th century retrospective runs (GCM runs using estimated global emissions during the 20th 

century) with observations. The 12 models (total 

of 65 model runs, including multiple ensembles 

for some models) that had the lowest root mean 

square error (RMSE) of runoff per unit area over

165 large river basins globally, for which observations were available, were retained for evaluation of 21st century projections. The rationale 

for retaining only those models with plausible 

reproductions of 20th century runoff globally 

was that future projections for models that are 

unable to reproduce past runoff characteristics 

may be called into question. For the same 12

models, a set of 24 model runs was extracted 

from the PCMDI archive. Each of the model 

runs was performed by the parent global modeling center using the IPCC A1B global emissions 

scenario, which reflects modest reductions in 

current global greenhouse gas emissions trends 

over the 21st century. There were 24 runs for 

the 12 models because multiple ensembles were 

available for some models.

Milly et al. (2005) show projected changes 

in runoff globally for the 24 model runs, as 

both mean changes in fractional runoff for the 

future period 2041-2060 relative to the period 

1900-1970 in the same model’s 20th century 

run, and in the difference between the number 

of models showing increases less the number 

showing decreases. Figure 4.10 shows the 

same results replotted for the 18 USGS water 

resources regions in the continental United 

States, plus Alaska. In Figure 4.10, the shading 

identifies the median fractional change in runoff 

over the 24 model run pairs for 2041-2060 relative to 1901-1970 (using the median rather than 

the mean as in the original paper, which results 

in slightly improved statistical behavior). Figure 

4.10 shows that, taken over all 24 of the model 

run pairs, the projections are for increased runoff 

over the eastern United States, gradually transitioning to little change in the Missouri and lower 

Mississippi, to substantial (median decreases 

in annual runoff approaching 20 percent) in the 

interior of the West (Colorado and Great Basin). 

Runoff changes along the West Coast (Pacific 
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Figure 4.10 Median changes in runoff interpolated to USGS water resources regions from Milly et al. (2005) 

from 24 pairs of GCM simulations for 2041-2060 relative to 1901-1970. Percentages are fraction of 24 runs for 

which differences had same sign as the 24-run median. Results replotted from Milly et al. (2005) by Dr. P.C.D. 

Milly, USGS.

Northwest and California) are also negative, but 

smaller in absolute value than in the western 

interior basins.

Figure 4.10 also shows the consistency in the 

direction of changes across the 24 model pairs. 

In particular, the percentages given in the figure 

body are the fraction of model pairs for which 

the change was in the same direction as the 

indicated change in the model median. Hence, 

for Alaska, all 24 model pairs (100 percent) 

showed runoff increases, whereas for the Pacific 

Northwest, 16 pairs (67 percent) showed runoff 

decreases, while eight pairs (33 percent) showed 

runoff increases.

It is important to note several caveats and clarifications with respect to these results. First, the 

results for the various GCMs were interpolated 

to the USGS water resources regions, and some 

of the regions are small and are not well resolved 

by the GCMs (the highest resolution GCMs 

are less than three degrees latitude-longitude; 

others are coarser). Therefore, important spatial characteristics, such as mountain ranges 

in the western United States, are only very 

approximately accounted for in these results. 

Second, for some regions there is considerable 

variability across the models as indicated above. 

In some cases (for instance, see the example for 

the Pacific Northwest above), there may be a 

substantial number of models that do not agree 

with the median change direction. On the other 

hand, however, it is noteworthy that 23 of 24 

model pairs showed runoff decreases for the 

upper Colorado, which is the source of most of 

the runoff for the entire Colorado basin.

Several other studies have used essentially the 

same model results pool, although not necessarily the same specific group of models, as in 

Milly et al. (2005). These studies use downscaling methods to produce forcings (usually 

precipitation and temperature, but occasionally 

other variables downscaled from the GCMs) for 

a land hydrology model. Downscaling results 

from a higher special resolution grid mesh and 

the lower resolution GCM grid being “trained” 

using historical observations. The advantage of 

these “off line” approaches is that the higher 

resolution land scheme is able to resolve spatial 

features, such as topography in the western United States, which may control runoff response. 

As an example, in mountainous areas there are 

strong seasonal differences in the period of 

maximum runoff generation and ET with elevation and these differences are not captured at the 

coarse spatial resolution of the GCM. However, 

the downside of the off-line approaches is that 

they do not generally preserve the water balance at the larger (GCM) scale. At this point, 

the nature of high-resolution feedbacks to the 

continental and global scale remains an area 

for research.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

4.4.1 Hydrology and Water

Resources

As in Section 4.2.4, the United States is partitioned into the same four super-regions, plus 

Alaska and Hawaii, (Figure 4.7) for review. For 

each of these super-regions, recent studies that 

have evaluated hydrologic and water resources 

implications of the IPCC AR4 archived model 

results were reviewed.

4.4.1.1 The West

Two recent studies have used IPCC AR4 multimodel ensembles to evaluate climate change 

effects on hydrology of the western United 

States. Maurer (2007) used statistical downscaling methods applied to 11 21st century 

AR4 simulations to produce one-eighth degree

latitude-longitude forcings for the VIC macroscale hydrology model over the Sacramento 

and San Joaquin River basins of California.

The GCM runs used reflected SRES A2 and 

B1 emissions scenarios. Maurer (2007) focused 

on four river basins draining to California’s 

Central Valley from the Sierra Nevada, more 

or less along a transect from north to south: the 

Feather, American, Tolumne, and Kings rivers. 

Maurer’s work primarily emphasized the variability across the ensembles relative to current 

conditions and the statistical significance of 

implied future changes given natural variability. All ensembles for both emissions scenarios 

are warmer than the current climate, whereas 

changes in precipitation are much more variable 

from model to model – although in the ensemble 

mean there are increases in winter precipitation 

and decreases in spring precipitation. These 

result in shifts in peak runoff earlier in the year, 

most evident in the higher elevation basins in the 

southern part of the domain. Notwithstanding 

variability across the ensembles, these runoff 

shifts are generally statistically significant, i.e., 

outside the bounds of natural variability, especially later in the 21st century (three periods 

were considered: 2011-2041, 2041-2070, and 

2071-2100).

Although not considered explicitly in the paper, 

the results presented for 2041-2070 and emissions scenario A2 (which generally yields larger 

precipitation and temperature changes than B1) 

imply changes in ensemble mean runoff for the 

four basins as follows: +6.8 percent (increase) 

for the Feather; +3.1 percent for the American; 

+2.2 percent for the Tolumne; and -3.4 percent 

for the Kings River. By comparison, the Milly 

et al. (2005) results for emissions scenario A1B, 

which results in slightly less warming than 

the A2 scenario used by Maurer, indicate reductions in annual runoff of 5-10 percent for 

California.

Christensen and Lettenmaier (2007) used similar methods as Maurer (2007) for the Colorado 

River basin. The 11 GCM scenarios, two emissions scenarios, and the statistical downscaling 

methods used in the two studies were identical. 

Christensen and Lettenmaier (2007) found that 

in the multimodel ensemble average for emission scenario A2 for 2040-2069, discharge for 

the Colorado River at Lees Ferry was predicted 

to decrease by about 6 percent, with a larger 

decrease of 11 percent indicated for 2070-2099. 

By comparison, the Milly et al. (2005) results 

suggest approximately 20 percent reductions in 

Colorado River runoff by mid-century.

The differences in the two downscaled studies 

as compared with the global results raise the 

question of why the off-line simulations (that

is, simulations in which a hydrology model is 

forced with GCM output, rather than extracting 

hydrologic variables directly from a coupled 

GCM run) imply less severe runoff reductions 

(or in the case of three of the four California basins, increases rather than decreases) than do the 

GCM results. The comparisons between Milly et 

al.’s (2005) global results and the off-line results 

from Maurer (2007) and Christensen and Lettenmaier (2007) should be interpreted with care. 

The emissions scenarios are slightly different, 

as are the models that make up the ensembles 

in the two studies. Furthermore, the statistical 

downscaling method used by Christensen and 

Lettenmaier (2007) and also Maurer (2007) does 

not necessarily preserve the GCM-level changes 

in precipitation. However, these factors do not 

seem likely to account entirely for the differences. First, as noted above, there is a negative 

feedback, reflected in the macroscale hydrology 

model results for snowmelt runoff under rising 

temperatures. Because this feedback is specific 

to the relatively high elevation headwaters portions of western U.S. watersheds, it is not well 

resolved at the GCM scale. However, while this 

feedback does appear to be present in the model 

results, it remains to be evaluated whether the 
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Chapter 4

extent of the feedback in the model is consistent 

with observations.

Second, spatial resolution issues also imply 

that precipitation (and temperature) gradients 

are less in the GCM than in either the off-line 

simulations or the true system; for instance, the 

GCM resolution tends to “smear out” precipitation over a larger area, and hence nonlinear 

effects (such as much higher runoff generation 

efficiency at high elevations) are lost at the 

GCM scale. A third factor is the role of the 

seasonal shift (present in both the California and 

Colorado basins) from spring and summer to 

winter precipitation. Although this shift is present in the GCMs, the differential effect may well 

be amplified in the off-line, higher resolution 

runs, where increased winter precipitation leads 

to much larger increases in runoff than would 

the same amount of incremental precipitation 

spread uniformly over the entire basin. It should 

be emphasized, as indicated in Section 4.0, that 

these possible explanations should be cast as 

hypotheses, and not as definitive explanations.

4.4.1.2 Central

No studies based on IPCC AR4 were found that 

have examined water resources implications for 

this region specifically. However, a general idea 

of potential impacts of climate change on the 

Central super-region can be obtained from the 

global results from Milly et al. (2005) as plotted 

to the USGS regions in Figure 4.10. This figure 

shows a general gradation in the ensemble mean 

from increased runoff toward the eastern part 

of the Central super-region (e.g., Ohio, which 

has the largest ensemble mean runoff increases 

within the continental United States), to essentially neutral in the upper Mississippi, to 

moderately negative in the Arkansas-Red. The 

concurrence among models is generally modest 

(i.e., typically at most two-thirds of the models 

are in agreement as to the direction of runoff 

changes) so even in the Ohio basin where the 

ensemble mean shows increased annual runoff 

of 10-25 percent, about one-third of the models 

show downward annual runoff. This contrasts, 

for instance, to the higher preponderance of 

models showing drying in the southwestern 

United States. Also, the results shown in Figure 

4.10 are for annual runoff, and seasonal patterns 

vary. Due to increased summer evaporative 

stress some, although certainly not all, models 

that predict increases in annual runoff may predict decreased summer runoff.

Jha et al. (2004) used a regional climate model 

to downscale a mid-21st century global simulation of the HADCM2 global climate model 

to the upper Mississippi River basin. This is a 

relatively old GCM simulation (not included 

in AR4), and as the authors note, is generally 

wetter and slightly cooler than other GCMs and 

relative to the AR4 ensemble means shown in 

Figure 4.10. Their simulations showed that a 21 

percent increase in future precipitation leads to a 

50 percent net increase in surface water yield in 

the upper Mississippi River basin. This contrasts 

with the much smaller 2-5 percent increase in 

the multimodel mean runoff in Figure 4.10. 

Takle et al. (2006), using an ensemble of seven 

IPCC AR4 models, showed results that are more 

consistent with Figure 4.10 for the Upper Mississippi basin, specifically a multimodel mean 

increase in runoff of about 3 percent for the end 

of the 21st century. They found that these hydrologic changes would likely decrease sediment 

loading to streams, but that the implications for 

stream nitrate loading were indeterminate.

Schwartz et al. (2004) analyzed projections of 

Great Lakes levels produced by three GCM runs 

in the late 1990s for the IPCC TAR. Two of the 

three GCMs projected declines in lake levels, 

and one projected a slight increase. Declining lake levels were associated with increased 

harbor dredging costs, and some loss in vessel 

capacity. However, low confidence must be ascribed to the projected declines in lake levels, as 

FAR model output shows runoff changes in the 

multimodel mean (see Figure 4.10) to be on the 

margin between slightly negative and slightly 

positive, with nearly as many models projecting 

increases as decreases.

4.4.1.3 Northeast

Several studies have evaluated potential future 

climate changes and impacts in the Northeast 

using climate model simulations performed for 

the IPCC’s AR4. Hayhoe et al. (2006) produced 

climate scenarios for the Northeast, which 

they defined as the 9-state area from Pennsylvania through Maine, using output from nine 

atmosphere-ocean general circulation models 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

(AOGCMs) archived in the IPCC AR4 database. 

Three IPCC emissions scenarios were included: 

B1, A2, and A1F1, which represent low, moderately high, and high global greenhouse gas 

emissions over the next century. Results were 

presented as model ensemble averages for two 

time periods: 2035-2064 and 2070-2099. For 

the earlier period, the model ensemble averages 

for increases in temperature are from 2.1 to 

2.9°C, and for increases in annual precipitation, 

5 percent to 8 percent. The authors also used 

hydrologic modeling methods to evaluate the 

corresponding range of hydrologic variables for 

the period 2035-2064. They found increases in 

ET ranging from +0.10 to +0.16 mm/day; increases from 0.09 to 0.12 mm/day; advances in 

the timing of the peak spring flow centroid from 

5 to 8 days; and decrease in the mean number 

of snow days/month ranging from 1.7 to 2.2. 

The authors conclude that “the model-simulated 

trends in temperature and precipitation-related 

indicators...are reasonably consistent with both 

observed historical trends as well as a broad 

range of future model simulations.”

Rosenzweig et al. (2007) use a similar approach 

applied to a smaller geographic region to determine how a changing climate might impact the 

New York City watershed region, which feeds 

one of the largest municipal water systems in 

the United States. They used five models, also 

from the IPCC AR4 archive. Three emissions 

scenarios were considered: B2, A1B and A2, 

representing low, moderate and relatively high 

emissions, respectively (A2 is also used in 

Hayhoe et al. 2006). The scenarios were downscaled to the New York watershed region using 

a weighting procedure for adjacent AOGCM 

gridboxes, and were evaluated using observed 

data. For the 2050s, temperature increases in the 

range 1.1-3.1°C were indicated relative to the 

1970-1999 baseline period, with a median range 

of 2-2.2°C. Precipitation changes ranged from 

-2.5 percent to +12.5 percent, compared to the 

baseline, with the median in the range 5-7.5 percent. This study also produced scenarios of local 

sea level rise, a factor that effects groundwater 

through salt water intrusion; river withdrawals 

for water use through the encroachment of the 

salt front; and sewer systems of coastal cites and 

wastewater treatment facilities through higher 

sea levels and storm surges.

Several studies have been performed on potential future climate change and impacts that are 

relevant to the Ohio River basin, but none are 

based on the most recent IPCC AR4 scenarios 

with multiple models and emissions scenarios. 

McCabe and Wolock (2002b) used prescribed 

future changes in climate, in this case an increase in monthly temperatures of 4°C, to examine changes in mean annual precipitation minus 

mean annual potential evapotranspiration (P-PE) 

and potential evapotranspiration (PE). In the 

Ohio basin, the drop in the first is relatively low, 

and the increase in the latter is moderate, reflecting the greater impact on PE (and thus P-PE) in 

warm regions as compared to cooler regions. 

Another study used a 4°C benchmark to examine 

land use effects relating to climate change. It 

found that land use conversion from commercial 

to low-density residential use decreased runoff 

(Liu et al. 2000). The early scenarios cited by 

Easterling and Karl (2001) suggest decreases of 

up to 50 percent in the snow cover season in the 

21st century, and it is possible that by the end 

of the 21st century sustained snow cover (more 

than 30 continuous days of snow cover) could 

disappear from the entire southern half of the 

Midwest. However, these scenario results and 

others given by Easterling and Karl are based on 

earlier GCMs, and a comprehensive multimodel, 

multi-emissions AR4 scenario evaluation for the 

Ohio needs to be undertaken.

4.4.1.4 South and Southeast

No studies were identified that have assessed the 

implications of IPCC AR4 scenarios for the hydrology of the South and Southeast super-region. 

However, a general idea of potential impacts can 

be obtained from the global results of Milly et al. 

(2005) as plotted to the USGS regions in Figure 

4.10. This figure shows a general gradation 

in the ensemble mean from east to west, with 

slightly increased runoff in the Southeast, near 

zero change in the lower Mississippi, and moderate decreases in the Texas drainages. As for 

the Central super-region, the concurrence among 

models is modest. For all regions within the 

South and Southeast super-region, two-thirds of 

the models are in agreement as to the direction of 

runoff changes, meaning that even for the Texas 

basins where moderate decreases in runoff are 

predicted in the ensemble mean, one-third of 

the models predicted increases. Furthermore, 
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Chapter 4

as for the Central sub-region, these results are 

for annual runoff and shifts in the seasonality 

of runoff. Generally higher summer evaporative 

stress will tend to decrease the fraction of runoff 

occurring in summer, and increase the fraction 

occurring at other times of the year, especially 

winter and spring, although this pattern certainly 

will not be present in all models.

4.4.1.5 Alaska

No studies were identified that have assessed hydrologic changes for Alaska associated with the 

AR4 scenarios. However, Figure 4.10 shows that 

relatively large runoff increases are suggested in 

the global model output for Alaska, a result that 

is consistent with the generally higher increases 

in temperature expected toward the poles. This, 

in turn, results in higher precipitation, in part 

because of increased moisture holding capacity of the atmosphere at higher temperatures, 

which generally results in increased precipitation. Large increases in runoff (10-25 percent, 

larger than anywhere in the continental United 

States) are predicted in the ensemble mean, 

and all models (100 percent) concur that runoff 

will increase over Alaska, a level of agreement 

not present anywhere in the continental United 

States. Nonetheless, Alaska covers a large area 

that encompasses several different climatic 

regions, so considerable subregional, as well 

as seasonal, variability in these results should 

be expected.

4.4.1.6 Hawaii

No studies were identified that have assessed 

hydrologic changes for Hawaii associated with 

the AR4 scenarios. Furthermore, the Hawaiian Islands are far too small to be represented 

explicitly within the GCMs, so any results that 

are geographically appropriate to Hawaii are 

essentially for the ocean and not the land mass. 

This is important as precipitation, and hence 

runoff, over this region is strongly affected by 

orography. The nature of broader shifts in precipitation, as well as evaporative demand over 

land, interacts in ways that can only be predicted 

accurately with regional scale modeling – an 

analysis that has not yet been undertaken.

4.4.2 Water Quality

The larger scale implications of increasing water 

temperature across the nation are illustrated by 

several modeling studies. Eaton and Scheller 

(1996) calculated that cool-water and cold-water 

fishes will shift their distributions nationwide, 

and streams and rivers currently supporting 

salmonids may become inhospitable as temperatures cross critical thresholds (Keleher and Rahel 

1996). Stefan et al. (2001) simulated the warming effects of a doubling of CO2 on 27 lake types 

(defined by combinations of three categories 

of depth, area, and nutrient enrichment) across 

the continental United States, and examined the 

responses of fish species to projected changes 

in lake temperature and dissolved oxygen. They 

found that suitable habitat would be reduced by 

45 percent for cold-water fish and 30 percent for 

cool-water fish, relative to historical conditions 

(before 1980). Shallow and medium-depth lakes 

(maximum depths of 4 meters and 13 meters, 

respectively) were most affected. Habitat for 

warm-water fish was projected to increase in 

all lake types investigated.

Warmer temperatures will also enhance algal 

production and most likely the growth of nuisance species, such as bluegreen algae. Modeling results suggest that increased temperatures 

associated with climate warming will increase 

the abundance of bluegreen algae and thus reduce water quality. This effect is exacerbated

by nutrient loading, pointing to the importance 

of human response to climate change in affecting some aspects of water quality (Elliott et al.

2006). Increased temperatures, coupled with 

lower water volumes and increased nutrients, 

would further exacerbate the problem.

Because warmer waters support more production of algae, many lakes may become more 

eutrophic due to increased temperature alone, 

even if nutrient supply from the watershed 

remains unchanged. Warm, nutrient-rich waters tend to be dominated by nuisance algae, 

so water quality will decline in general under

climate change (Murdoch et al. 2000; Poff et 

al. 2002). The possible increase in episodes of 

intense precipitation projected by some climate 

change models implies that nutrient loading 

to lakes from storm-related erosion could increase. Further, if freshwater inflows during the 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

summer season also are reduced, the dissolved 

nutrients will be retained for a longer time in 

lakes, effectively resulting in an increase in 

productivity. These factors will independently 

and interactively contribute to a likely increase 

in algal productivity.

A warmer and drier climate will reduce streamflows and increase water temperatures. Expected 

consequences would be a decrease in the amount

of dissolved oxygen in surface waters and an 

increase in the concentration of nutrients and 

toxic chemicals due to a reduced flushing rate 

(Murdoch et al. 2000). Reduced inputs of dissolved organic carbon from watershed runoff 

into lakes can increase the clarity of lake surface 

waters, allow biological productivity to increase 

at depth, and ultimately deplete oxygen levels 

and increase the hypolimnetic stress in deeper 

waters (Schindler et al. 1996).

A warmer-wetter climate could ameliorate poor 

water quality conditionsin places where humancaused concentration of nutrients and pollutants 

currently degrades water quality (Murdoch et al.

2000). However, a wetter climate, characterized 

by greater storm intensity and long inter-storm 

duration, may act to episodically increase 

flushing of nutrients or toxins into freshwater 

habitats. For example, Curriero et al. (2001) 

reported that 68 percent of the 548 reported outbreaks of waterborne diseases during the period 

1948-1994 were statistically associated with an 

80 percent increase in precipitation intensity, 

implying that increased precipitation intensity 

in the future carries a health risk via polluted 

runoff into surface waters.

In general, an increase in extreme events will 

likely reduce water quality in substantial ways.

More frequent floods and prolonged low flows

would be expected to induce water quality problems through episodic flushing of accumulated 

nutrients/toxins on the landscape followed by 

their retention in water bodies (Murdoch et al. 

2000, Senhorst and Zwolsman 2005). Clearly, 

human actions in response to climate change 

will influence the ultimate effect of climate on 

water quality. In a modeling example, Chang

(2004) used the HadCM2 GCM scenario for 

five subbasins in southeastern Pennsylvania 

for projected changes in 2030 and found that 

climate change alone would slightly increase 

mean annual nitrogen and phosphorus loads, 

but concurrent urbanization would further increase nitrogen (N) loading by 50 percent. This 

example illustrates how human land use activity interacts with warming climate and altered 

precipitation patterns to induce synergistic water 

quality changes.

4.4.3 Groundwater

In contrast to the many studies that have been 

conducted over the last 20 years of surface water vulnerability to climate change (see Section 

4.2), few studies have examined the sensitivity 

of groundwater systems to a changing climate. 

For this reason, analysis was not restricted to 

the studies based on IPCC AR4 scenarios as no 

such studies of groundwater impacts have been 

performed to date. Instead, several studies are 

summarized that have evaluated groundwater 

sensitivity to climate change across the continental United States (no studies are known that 

are applicable to Alaska or Hawaii).

Among the first published papers in this area 

was a study by Vaccaro (1992) on the sensitivity of the Ellensburg (WA) basin to climate 

and land cover change. Vaccaro examined the 

sensitivity of groundwater recharge to both land 

cover change (over half of the 937 km2 basin 

whose native vegetation was a combination of 

grasslands and arid shrublands is now irrigated, 

mostly from surface water sources) and climate 

change. The climate change scenario considered 

was the average of CO2 doubling scenarios from 

three GCMs. A physically based model of deep 

percolation that accounted for the effects of 

evapotranspiration on percolation to deep soil, 

and hence groundwater recharge, was used. 

For the native vegetation scenario, Vaccaro 

found that under the future climate scenario, 

groundwater recharge increased, whereas under 

current vegetation and future climate conditions, 

recharge was projected to decrease. The reason 

for the difference in signs of predicted recharge 

under the future land use and climate scenarios 

was that for native vegetation evapotranspiration 

peaks during spring, whereas for the irrigated 

condition, it peaks during summer. Therefore, 

total evapotranspiration, and hence recharge, is 

less sensitive to warming for native vegetation 

than for irrigated land use, and the balance of 

A warmer-wetter 

climate could 

ameliorate poor 

water quality 

conditions in places 

where human-caused 

concentration 

of nutrients and 

pollutants currently 

degrades water 

quality (Murdoch et 

al. 2000). However, 

a wetter climate, 

characterized by 

greater storm 

intensity and 

long inter-storm 

duration, may act to 

episodically increase 

flushing of nutrients 

or toxins into 

freshwater habitats.
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Chapter 4

increased precipitation and increased evaporative demand under future climate tips towards 

increased precipitation for native vegetation, 

but toward increased evaporative demand for 

current vegetation.

Loaiciga et al. (2000) studied the sensitivity of 

the Edwards Balcones fault zone (BFZ) aquifer

of south central Texas to climate change, using results from several GCMs. They used an 

adaptation of a simple water balance model 

to estimate recharge, based on the estimated 

streamflow deficit between upstream and 

downstream gauges (accounting for local inflow) of the major stream crossing the aquifer.

A simple pro-rating method was used to relate 

unmeasured lateral inflows to the channel in the 

reach between an upstream and a downstream 

gauge, and climate change effects on streamflow 

were scaled directly from GCM output. For the 

single GCM used (CO2 doubled), projected 

future precipitation and runoff were considerably higher than for current climate, resulting in 

projections of increased recharge, and therefore 

increased discharge of a key spring in the region 

that was considered an index to groundwater 

conditions. Predicted spring discharge was, 

however, highly sensitive to assumptions about 

future groundwater pumping. Loaiciga et al. 

(2000) also considered a more physically based 

approach to estimating groundwater recharge, 

which accounted directly for evapotranspiration as it would change for future climate. In 

this case, six GCM CO2 doubling scenarios 

were considered, all of which, aside from the 

single climate scenario used in the water balance approach, projected reduced precipitation. 

Coupled with higher evaporative demand under 

a warming climate, this resulted in projected 

recharge that was considerably reduced relative 

to current climate.

Scibek and Allen (2006) evaluated the sensitivity of two unconfined aquifers that straddle the

U.S.-Canadian border between British Columbia 

and Washington State to climate change, as predicted by the Canadian Climate Centre GCM. 

The Abbotsford-Sumas aquifer lies in a humid

area west of the Cascade Mountains, whereas the 

Grand Forks aquifer liesin a much drier climate

east of the Cascades. Stream-aquifer interactions

dominate the Grand Forks aquifer, but are less

important in the case of the Abbotsford-Sumas 

aquifer. Recharge was assumed in the case of

the Abbotsford-Sumas aquifer to be directly proportional to precipitation (scaled appropriately 

for different spatially varying recharge zones). 

For the Grand Forks aquifer, river discharge

was related to downscaled climate variables. 

River discharge dominates aquifer variations,

and hence aquifer changes are in turn dominated

by changes in projected river flows, rather than 

recharge. Projected groundwater level change 

closely followed projected changes in river 

discharge, with higher levels in winter and early 

spring accompanying earlier snowmelt runoff, 

and lower levels in summer and fall, which 

result from lower streamflows during those 

periods. An apparent limitation of this study is 

that effects of evapotranspiration, and changes 

therein, on recharge were not accounted for 

directly. For the Abbotsford-Sumas aquifer,

groundwater levels were predicted to decline 

slightly for future climate by mostly less than 

1m. In this case of Abbotsford-Sumas, projected 

groundwater level declines are related entirely 

to projected GCM (downscaled) changes in 

precipitation, and effects of warming are not 

directly considered.

Other studies (e.g., Hansen and Dettinger 2005; 

Gurdak et al. 2007) have investigated effects of 

climate variability at interannual to decadal time 

scales on groundwater levels. In the case of Hansen and Dettinger’s (2005) study of a southern 

California coastal aquifer, downscaled GCM

output was used to evaluate the role of climate 

variations on groundwater levels. However, the 

groundwater model was driven primarily by 

downscaled GCM precipitation. The effects of 

evapotranspiration on recharge were calibrated 

to water levels, rather than being driven by 

computation based on surface variables (e.g., 

air temperature and/or solar radiation) from 

the GCM. Gurdak et al. (2007) investigated the 

influence of climate variability (primarily the 

decadal scale PDO) on groundwater levels in the 

deep High Plains aquifersystem. They show that

in this system the linkage between climate and 

groundwater levels is controlled by hydraulic 

head gradients in the vadose zone, which in turn 

is influenced by evapotranspiration. However, 

their study did not include a modeling element, 

so no attempt was made to predict recharge 

explicitly.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Taken together, these studies suggest that the 

ability to predict the effects of climate and climate change on groundwater systems is nowhere 

near as advanced as for surface water systems. 

A body of literature on the subject is, however, 

beginning to evolve (e.g. Green et al. 2007). 

The interaction of groundwater recharge with 

climate is an area that requires further research.

The papers reviewed have used a variety of 

approaches, some of them physically based, 

but others have essentially “tuned” recharge 

in ways that do not represent the full range of 

mechanisms through which climate change 

might affect groundwater systems.

4.5 Hydrology-Landscape 

Interactions

Across much of the continental United States, 

annual precipitation increased during the 20th 

century, and especially in the second half of the 

century. The average precipitation increase was 

estimated to be about 7 percent by Groisman 

(2004). As noted in Section 4.2.3, Andreadis 

and Lettenmaier (2006) found that as a result, 

droughts generally became shorter, less frequent, and covered a smaller part of the country

toward the end of the 20th century than toward 

the beginning, although they noted that the West 

and Southwest were apparent exceptions. Dai et 

al. (2004) found that the fraction of the country 

under extreme either wet or dry conditions was 

increasing. Walter et al. (2004) found that ET 

has increased by an average of about 55 millimeters in the last 50 years in the conterminous 

United States, but that stream discharge in the 

Colorado and Columbia River basins has decreased since 1950 (also coincidentally a period 

of major reservoir construction).

These changes in physical climate and hydrology are strongly coupled with terrestrial ecosystems. Terrestrial ecosystems both respond to 

and modulate hydroclimatic fluxes and states. 

The most direct and observable connection 

between climate and terrestrial ecosystems is 

in life cycle timing of seasonal phenology, and 

in plant growth responses, annually in primary 

productivity and decadally over changes in biogeographical range. These impacts on seasonality and primary productivity then cascade down 

to secondary producers and wildlife populations. 

The vegetation growing season as defined by 

continuous frost-free air temperatures has increased by an average of two days per decade 

since 1948 in the conterminous United States, 

with the largest change in the West and with 

most of the increase related to earlier warming 

in the spring (Easterling 2002; Feng and Hu 

2004). Global daily satellite data available since 

1981 has detected similar changes in earlier 

onset of spring “greenness” of 10-14 days in 

19 years, particularly over temperate latitudes 

of the Northern Hemisphere (Myeni et al. 1997; 

Lucht et al. 2002). For example, honeysuckle 

first bloom dates have advanced 3.8 days per 

decade at phenology observation sites across 

the western United States (Cayan et al. 2001) 

and apple and grape leaf onset have advanced 

two days/decade at 72 sites in the northeastern 

United States (Wolfe et al. 2004).

As a result of these climatic and hydrologic 

changes, forest growth appears to be slowly 

accelerating (<1 percent/decade) in regions of 

the United States where tree growth is limited 

by low temperatures and short growing seasons (McKenzie et al. 2001; Joos et al. 2002; 

Casperson et al. 2000). On the other hand, radial 

growth of white spruce in Alaska has decreased 

over the last 90 years due to increased drought 

stress on the dry, southern aspects they occupy 

(Barber et al. 2000). Semi-arid forests of the 

Southwest also showed a decreasing growth 

trend since 1895, which appears to be related 

to drought effects from warming temperatures 

(McKenzie 2001).

Climatic constraints on ecosystem activity can 

be generalized as variable limitations of temperature, water availability, and solar radiation, 

the relative impacts of which vary regionally 

and even locally (e.g., south vs. north aspects) 

(Nemani et al. 2003; Jolly et al. 2005). Where 

a single climatic limiting factor clearly dominates, such as low temperature constraints on 

the growing season at high latitudes or water 

limitations of deserts, ecosystem responses will 

be fairly predictable. However, where a seasonally changing mix of temperature and water 

constraints is possible, projection of ecosystem 

responses depends both on temperature trends 

and the land surface water balance. While temperature warming trends for North America are 

well documented, the land water balance trends 

over the past half century suggest that roughly 

Terrestrial 

ecosystems 

both respond to 

and modulate 

hydroclimatic 

fluxes and

states.
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Chapter 4

the western half of the continent is getting drier 

and the eastern half wetter (see e.g. Andreadis 

and Lettenmaier 2006).

These changes have important implications 

for wildfires, especially in the western United 

States, but elsewhere as well. From 1920 to 

1980, the area burned in wildfires in the continental United States averaged about 13,000 

km2/yr. Since 1980, average annual burned 

area has almost doubled to 22,000 km2 /yr, and 

three major fire years have exceeded 30,000 

km2 (Schoennagel et al. 2004). The forested area 

burned from 1987 to 2003 is 6.7 times the area 

burned for the period 1970-1986, with a higher 

fraction burning at higher elevations (Westerling et al. 2006). Warming climate encourages 

wildfires by drying of the land surface, allowing 

more fire ignitions and desiccated vegetation. 

The hot dry weather allow fires to grow exponentially more quickly, ultimately determining

the area burned (Westerling et al. 2003). Relating climatic trends to fire activity is complicated 

by regional differences in seasonality of fire 

activity. Most fires occur in April to June in the 

Southwest and Southeast, and July to August 

in the Pacific Northwest and Alaska. Earlier 

snowmelt, longer growing seasons, and higher 

summer temperatures observed particularly in 

the western United States are synchronized with 

increase of wildfire activity, along with dead 

fuel buildup from previous decades of fire suppression activity (Westerling et al. 2006).

Insects and diseases are a natural part of all 

ecosystems. However, in forests periodic insect 

epidemics can erupt and kill millions of hectare 

of trees, providing dead, desiccated fuels for 

large wildfires. The dynamics of these epidemic 

outbreaks are related to insect life cycles that are 

tightly tied to climate fluctuations and trends 

(Williams and Liebhold 2002). Many of the 

northern insects have a two-year life cycle, and 

warmer winter temperatures now allow a higher 

percentage of overwintering larvae to survive. 

Recently, Volney and Flemming (2000) found 

that spruce budworm in Alaska have successfully completed their life cycle in one year, 

rather than two. Earlier warming spring temperatures allow a longer active growing season, 

and higher temperatures directly accelerate the 

physiology and biochemical kinetics of the life 

cycles of the insects (Logan et al. 2003). The 

mountain pine beetle has expanded its range 

in British Columbia into areas previously too 

cold to support its survival (Carroll et al. 2003). 

Multi-year droughts also reduce the available 

carbohydrate balance of trees, and their ability 

to generate defensive chemicals to repel insect 

attack (Logan et al. 2003).

4.6 Observing Systems

Observations are critical to understanding the 

nature of past hydroclimatic changes and for 

interpreting the projections of potential effects 

of future changes reviewed in Sections 4.4. 

However, essentially no aspect of the current 

hydrologic observing system was designed 

specifically for purposes of detecting climate 

change or its effects on the hydrologic cycle 

– whether relatively slow, decadal or longer 

changes in mean quantities, or more rapid,

“abrupt” climate change.

In the case of streamflow observations, the 

stream gauging network was first established 

in the late 1800s to provide basic information 

on water resource availability. More specifically, stream gauges were installed to help determine the natural variability of runoff from 

which decisions about how much water could 

be extracted from a reservoir or reservoirs of a 

given size could be made. Over time, as the era 

of dam construction waned in the 1960s and 

1970s, the purpose of the stream gauge network 

shifted to focus more on water management 

than on design. Arguably, the network now is 

configured more to address accounting issues 

(i.e., stations are situated above and below major 

water management structures and/or diversions) 

than to address questions of long-term change,

which requires location of stations where the

confounding effects of water management and 

other anthropogenic influences are minimized.

The HCDN is a subset of the USGS stream 

gauges first identified by Langbein and Slack 

(1982), with then record lengths of at least 20 

years, which were considered “suitable for the 

study of variation of surface-water conditions 

in relation to climate variation” (see also Slack 

et al. 1993). The stations were selected to be 

mostly free of major anthropogenic influences, 

especially regulation by dams. Originally, more 

than 1,600 stations were included in this network. However the number of active stations is 

While temperature 

warming trends for 

North America are 

well documented, the 

land water balance 

trends over the past 

half century suggest 

that roughly the 

western half of the 

continent is getting 

drier and the eastern 

half wetter.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 4.11 Number of HCDN active stations 1905-2005 (upper 

panel), and location of discontinued stations as of 2005. Figure 

courtesy U.S. Geological Survey.

now substantially smaller (see Figure 4.11) due 

to discontinuation of stations over the years. In 

most cases, HCDN stations are not supported, at 

least in their entirety, by federal funds. The most 

common funding mechanism is the USGS Cooperative (Co-op) Program, in which states and 

local agencies share the cost of station operation. 

Although the Co-op program allows leveraging 

of federal funds and hence operation of a much 

larger stream gauging program than would be 

possible from federal funds alone, it makes the 

station network susceptible to short-term budget 

issues in the cooperating agencies, and the loss 

of stations indicated in Figure 4.11 is, in large 

part, the result of such issues. It is important to 

note that essentially all of the studies reviewed 

in this chapter that have analyzed long-term 

streamflow trends in the United States (e.g., 

Lettenmaier et al. 1994; Lins and Slack, 1999, 

2005; Garbrecht et al. 2004; Mauget 2004; and 

McCabe and Wolock 2002a, among others) have 

been based on subsets of the HCDN network, 

hence the absence of a long-term strategy is of 

critical concern and needs to be addressed.

Another key hydrologic variable that especially 

affects the western United States in addition 

to parts of the upper Midwest and Northeast 

is snow, specifically snow water equivalent or

SWE. In the western United States, SWE was 

historically observed at manual snow courses, at 

which observations were mostly taken by Natural Resources Conservation Service (NRCS) 

(in California, observations have been taken 

by the Department of Water Resources). These 

observations are relatively costly to collect, as 

they involve travel to remote, mostly mountainous areas, and for this reason observations were 

collected only a few times per year (usually 

around April 1, at about the time of maximum 

snow accumulation). In the early 1980s, NRCS 

began to transition to an automated network 

of snow pillows, which essentially record the 

weight of snow on a pressure sensor and then 

convert to SWE. In California, there has been a 

similar transition from manual snow course to 

snow pillows, although California’s Department 

of Water Resources continues to collect manual 

snow course data as well. The major advantage 

of the snow pillows is that data are essentially 

continuous, and the data transmission system 

provides additional channels that allow other 

variables such as temperature and precipitation 

to be transmitted as well. Analyses of long-term 

snow trends have faced the problem of merging 

the snow course and SNOTEL data. There are 

a variety of problems in doing so. For instance, 

thermodynamic properties of snow sensors are 

different from those of the surrounding natural 

landscape, and this can affect the rate of spring 

melt and statistics like “last date of snow.” 

Furthermore, standard protocol for snow course 

measurements is to average a number (usually at 

least 10) of manual cores taken along or transects 

that cover a larger area than do the snow pillows, 
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Chapter 4

so the representation of local spatial variability 

differs (see e.g. Dressler et al. 2006). Pagano et 

al. (2004) have shown how the transition from 

manual snow courses to the SNOTEL network 

has affected the accuracy of seasonal streamflow 

forecasts across the West.

Like HCDN, the purpose of the snow course 

and SNOTEL networks was not monitoring of 

climate change and variability, but rather support of water management through provision 

of basic data used in water supply forecasting. 

However, as demands for information related to 

long-term climate-related shifts in snow properties have grown, the networks have begun to 

be used increasingly for these other purposes. 

NRCS’s National Water and Climate Center has 

initiated a study to evaluate effects of changes in 

SNOTEL instrumentation (e.g. metal or hypalon 

pillows), their comparison with manual snow 

courses, as well as systematic changes in snow 

courses and SNOTEL sites related to changes in 

vegetation and other site-specific characteristics, 

to provide better background information as to 

sources of systematic errors in long-term SWE 

records. A significant number of SNOTEL sites 

have been augmented with soil moisture and soil 

temperature sensors to improve spring runoff 

forecasts and basin-specific water management. 

The SNOTEL network also supports snow 

depth, relative humidity, wind speed/direction, 

and solar radiation measurements.

As noted in Section 4.2.2, evaporation pans do 

not provide a direct measurement of either actual or potential evaporation. Nonetheless, they 

provide a relatively uncomplicated measuring 

device, and the existing long-term records, taken 

together with the analyses discussed in Section 

4.2.2, do provide a land surface data record that 

has some value. Pan evaporation data are most 

commonly collected at agricultural experiment 

stations, and are archived by the National Climatic Data Center.

Actual evaporation can be measured in several ways. One is weighing lysimeters, which 

generally are only practical for relatively short 

vegetation, such as crops, and are complicated 

by the disturbance to the surface inherent in 

their construction. The second is Bowen ratio 

sensors, which measure the gradient of humidity and air temperature close to the surface, the 

ratio of which is equal to the ratio of sensible to

latent heat (the Bowen ratio). The Bowen ratio 

is used to partition the residual of net radiation 

and ground heat flux, both of which must be 

measured, into latent heat (equal to evapotranspiration, when adjusted by a proportionality 

factor) and sensible heat. Another method of 

estimating evapotranspiration (or more accurately, latent heat) directly is through eddy 

correlation, which measures high frequency

variations in the vertical component of wind and 

humidity, the product of which, when averaged 

over time, is the latent heat flux. Both the Bowen 

ratio and eddy correlation methodsrequire some

assumptions (see Shuttleworth 1993). However, 

the eddy correlation method, which is somewhat more direct, seems to have gained favor 

recently. The AmeriFlux network consists of 

about 200 stations across the continental United 

States at which evapotranspiration is measured. 

The longest term records at these stations are 

somewhat longer than 10 years, not nearly 

long enough for meaningful trend analysis. 

Furthermore, instrumentation has evolved over 

time, and there is a need for careful calibration 

and maintenance, as well as quality control to

assure, for instance, that the measured energy 

flux terms balance. In the long-term, however, 

the quality and reliability of the instrumentation

will improve and this network appears to offer 

the best hope for direct, long-term measurements of evapotranspiration.

Soil moisture is a key indicator of the hydrologic 

state of the land system. However, until recently, 

there was no national soil moisture network, and 

the NRCS SCAN (Soil Climate and Analysis 

Network; Schaefer et al. 2007) dates only to 

1998. At present it consists of fewer than 150 

stations, although eventually, if fully funded, 

plans exist to create 1,000 stations. The most 

established soil moisture network is operated 

by the state of Illinois, and for about 25 years 

has produced data at about 20 stations statewide. 

More recently, the Oklahoma Mesonet network 

has observed soil moisture on a county-bycounty basis in Oklahoma. A few other state networks have been initiated. These networks will 

become increasingly important as time passes, 

particularly given concerns over possible effects 

of climate change on drought. Steps are needed 

to assure the longevity of a core network of soil 

moisture stations with an appropriate national 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

distribution. One shortcoming of most current 

in situ methods for soil moisture observation is 

that their “footprint” is quite small, typically

considerably less than 1 meter, and hence the observations reflect the effects of local scale spatial 

variability that can only be reduced by replicate 

sampling (e.g., by clusters of instruments). This 

in turn substantially increases expense. Evolving 

technologies, such as cosmic ray probes (Zreda 

and Desilets 2005) have a footprint on the order 

of 100 meters, and hence are able to average out 

much of the local scale spatial variability that 

is inherent in current automated soil moisture 

observing systems.

4.7 Findings and 

Conclusions

Most of the United States has experienced 

increases in precipitation and streamflow and 

decreases in drought during the second half 

of the 20th century. It is likely these trends are 

due to a combination of decadal-scale climate 

variability, as well as long term change.

With respect to drought, consistent with 

streamflow and precipitation observations, 

most of the continental United States experienced reductions in drought severity and 

duration over the 20th century. However, there 

is some indication of increased drought severity 

and duration in the western and southwestern 

United States that may have resulted from increased actual evaporation dominating the trend 

toward increased soil wetness.

There is a trend toward reduced mountain 

snowpack, and earlier spring snowmelt runoff peaks across much of the western United 

States. This trend is very likely attributable, at 

least in part, to long-term warming, although 

some part may have been played by decadal 

scale variability, including shift in the Pacific 

Decadal Oscillation in the late 1970s. Where 

shifts to earlier snowmelt peaks and reduced 

summer and fall low flows have already been 

detected, continuing shifts in this direction are 

very likely and may have substantial impacts on 

the performance of reservoir systems.

Trends toward increased water use efficiency 

are likely to continue in the coming decades. 

Pressures for reallocation of water will be greatest in areas of highest population growth, such 

as the Southwest. Declining per capita (and for 

some water uses, total) water consumption will 

help mitigate the impacts of climate change on 

water resources.

Paleo reconstructions of droughts show that 

much more severe droughts have occurred 

over the last 2,000 years than those that have 

been observed in the instrumental record 

(notably, the Dust Bowl drought of the 1930s, 

and extensive drought in the 50s).

Water quality is sensitive both to increased 

water temperatures, and changes in patterns 

of precipitation, however most observed 

changes in water quality across the continental United States are likely attributable 

to causes other than climate change, primarily changes in pollutant loadings. There 

is some evidence, however, that temperatures 

have increased in some western U.S. streams, 

although a comprehensive analysis has yet to 

be conducted. Stream temperatures are likely 

to increase as the climate warms, and are very 

likely to have both direct and indirect effects on 

aquatic ecosystems. Changesin temperature will

be most evident during low flow periods.

Stream temperatures are likely to increase 

as the climate warms, and are very likely 

to have both direct and indirect effects on 

aquatic ecosystems. Changes in temperature 

will be most evident during low flow periods, 

when they are of greatest concern. Stream 

temperature increases have already begun to 

be detected across some of the United States, 

although a comprehensive analysis similar to 

those reviewed for streamflow trends has yet 

to be conducted.

A suite of climate simulations conducted for 

the IPCC AR4 show that the United States 

may experience increased runoff in eastern 

regions, gradually transitioning to little 

change in the Missouri and lower Mississippi, 

to substantial decreases in annual runoff in 

the interior of the west (Colorado and Great 

Basin). Runoff changes along the West Coast 
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Chapter 4

are also negative, but smaller in absolute value 

than in the western interior basins. The projected drying in the interior of the West is quite

consistent among models. The only projections 

that are more consistent among models are for 

runoff increases in Alaska. These changes are, 

very roughly, consistent with observed trends in 

the second half of the 20th century, which show 

increased streamflow over most of the United 

States, but sporadic decreases in the West.

Essentially no aspect of the current hydrologic observing system was designed specifically for purposes of detecting climate change 

or its effects on water resources. Many of the 

existing systems are technologically obsolete, 

are designed to achieve specific, often noncompatible management accounting goals, and/

or their operational and maintenance structures 

allow for significant data collection gaps. As a 

result, many of the data are fragmented, poorly 

integrated, and in many cases unable to meet 

the predictive challenges of a rapidly changing 

climate.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

5 Water Resources

Lead Author: D.P. Lettenmaier

Contributing Authors: D. Major, L. Poff, S. Running

CHAPTER

Biodiversity

Lead Author: A.C. Janetos

Contributing Authors: L. Hansen, D. Inouye, B.P. Kelly,

L. Meyerson, W. Peterson, R. Shaw

5.1 Introduction and 

Framework

This synthesis and assessment report builds on 

an extensive scientific literature and series of 

recent assessments of the historical and potential 

impacts of climate change and climate variability on managed and unmanaged ecosystems 

and their constituent biota and processes. It 

identifies changes in resource conditions that 

are now being observed, and examines whether 

these changes can be attributed in whole or part 

to climate change. It also highlights changes in 

resource conditions that recent scientific studies 

suggest are most likely to occur in response to 

climate change, and when and where to look 

for these changes. As outlined in the Climate 

Change Science Program (CCSP) Synthesis 

and Assessment Product 4.3 (SAP 4.3) prospectus, this chapter will specifically address 

climate-related issues in species diversity and 

rare ecosystems.

In this chapter the focus is on the near-term 

future. In some cases, key results are reported 

out to 100 years to provide a larger context 

but the emphasis is on next 25–50 years. This 

nearer-term focus is chosen for two reasons. 

First, for many natural resources, planning and 

management activities already address these 

time scales through development of long-lived 

infrastructure, forest rotations, and other significant investments. Second, climate projections 

are relatively certain over the next few decades. 

Emission scenarios for the next few decades 

do not diverge from each other significantly 

because of the “inertia” of the energy system. 

Most projections of greenhouse gas emissions 

assume that it will take decades to make major 

changes in the energy infrastructure, and only 

begin to diverge rapidly after several decades 

have passed (30–50 years).

The potential impacts of climate change on 

biological diversity at all levels of biological and ecological organization have been of 

concern to the scientific community for some 

time (Peters and Lovejoy 1992; IPCC 1990; 

Lovejoy and Hannah 2005). In recent years, 

the scientific literature has focused on a variety 

of observed changes in biodiversity and has 

continued to explore the potential for change 

due to variation in the physical climate system 

(IPCC 2001; IPCC 2007; Millennium Ecosystem Assessment (MEA) 2005). The focus of the 

chapter is mainly, although not exclusively, on 

ecosystems within the United States; in some 

areas, little work has been done here but analogs 

exist in other regions. Because there have been 

several recent comprehensive reviews of the 

overall topic (Lovejoy and Hannah 2005; Parmesan 2007; IPCC 2007), we will not attempt 

another encyclopedic review in this chapter. 

Instead, the chapter will focus on the particular 

issues of particular concern to U.S. decisionmakers, as outlined in the governing prospectus. 

The chapter also explores the implications of 
The U.S. Climate Change Science Program

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Chapter 5

Figure 5.1 Changes in U.S. vegetation observed by satellite (NDVI, or Normalized Difference Vegetation Index) 

between 1982 and 2003 (NDVI units per year). The NDVI reflects changes in vegetation activity related to climate variability, land-use change, and other influences, and shows substantial trends in much of the conterminous 

United States. Figure provided by J. Hicke, University of Idaho, based on data from C. Tucker, NASA Goddard 

Space Flight Center.

changes in biological diversity for the provision of ecosystem services (MEA 2005) and, 

finally, the implications of these findings for 

observation and monitoring systems. In each of 

the following sections, we provide a summary 

of current examples in the literature of the topics identified. There are inevitably some topics 

that have not been explored, although a growing 

literature exists (e.g., Poff et al. 2002). This is 

purely a function of the governing prospectus 

for the assessment.

This chapter thus summarizes and evaluates the 

current knowledge, based on both observed and 

potential impacts with respect to the following 

topics:

•	 Changes in Distributions and Phenologies

in Terrestrial Ecosystems

•	 Changes in Coastal and Near-Shore

Ecosystems

•	 Changes in Pests and Pathogens

•	 Changes in Marine Fisheries and

Ecosystems

•	 Changes in Particularly Sensitive

Ecosystems

•	 Ecosystem Services and Expectations for

Future Change

•	 Adequacy of Monitoring Systems

5.2 Changes in Distribution

 and Phenologies in

Terrestrial Ecosystems

As previous chapters have demonstrated, terrestrial ecosystems are already being demonstrably 

impacted by climate change. Changes in the 

geographic distribution of species and timing of 

specific biological processes such as pollination 

or migration have long been expected because, 

as is widely known, over the long-term these are 

often controlled by large-scale patterns in climate. In this section, we examine some of those 

specific changes as they have been analyzed in 

the recent literature.

5.2.1 Growing Season Length and 

Net Primary Production Shifts

There is evidence indicating a significant 

lengthening of the growing season and higher 

net primary productivity (NPP) in the higher 

latitudes of North America, where temperature 

increases are relatively high. Over the last 19 

years, global satellite data indicate an earlier 

onset of spring across the temperate latitudes 

by 10–14 days (Zhou at al. 2001; Lucht 2002), 

an increase in summer photosynthetic activity 

(Zhou et al. 2001), and an increase in the amplitude of the annual CO2 cycle (Keeling 1996); 

climatological and field observations support 

these findings (Figure 5.1).
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

In the higher latitudes in Europe, researchers 

detected a lengthening of the growing season 

of 1.1 to 4.9 days per decade since 1951, based 

on an analysis of climate variables (Menzel et 

al. 2003). Numerous field studies have documented consistent earlier leaf expansion (Wolfe 

et al. 2005; Beaubien and Freeland 2000) and 

earlier flowering (Schwartz and Reiter 2000; 

Cayan et al. 2001) across different species and 

ecosystem types. Accordingly, NPP in the continental United States increased nearly 10 percent 

between 1982–1998 (Boisvenue and Running 

2006). The largest increases in productivity have 

been documented in croplands and grasslands of 

the central United States, as a consequence of

favorable changes in water balance (Lobell et 

al. 2002; Nemani et al. 2002; Hicke and Lobell 

2004).

Forest productivity, in contrast, generally limited by low temperature and short growing seasons in the higher latitudes and elevations, has 

been slowly increasing at less than 1 percent per 

decade (Boisvenue and Running 2006; Joos et 

al. 2002; McKenzie et al. 2001; Caspersen et al. 

2000). The exception to this pattern is in forested 

regions that are subject to drought from climate 

warming, where growth rates have decreased 

since 1895 (McKenzie et al. 2001) and longer 

growing seasons have reduced productivity in 

forested subalpine regions (e.g., Monson et al. 

2005; Sacks et al. 2007). Recently, widespread 

mortality over 12,000 km2 of lower-elevation 

forest in the Southwest is consistent with the 

impacts of increased temperature and the associated multiyear drought (Breshears et al. 2005) 

even though previous studies had found productivity at treeline had increased (Swetnam and 

Betancourt 1998). Disturbances created from the 

interaction of drought, pests, diseases, and fire 

are projected to have increasing effects on forests and their future distributions (IPCC 2007). 

These changes in forests and other ecosystem 

types will cascade through the trophic structure 

with resulting impacts on other species.

5.2.2 Biogeographical and 

 Phenological Shifts 

Evidence from two meta-analyses (Root et al. 

2003; Parmesan and Yohe 2003) and a synthesis 

(Parmesan 2006) on species from a broad array 

of taxa suggests that there is a significant impact from recent climatic warming in the form 

of long-term, large-scale alteration of animal 

and plant populations including changes in 

distribution (Root and Schneider 2006; Root et 

al. 2003; Parmesan 2003). If clear climatic and 

ecological signals are detectable above the background of climatic and ecological noise from a 

0.6°C increase in global mean temperature over 

roughly the last century, by 2050 the impacts on 

ecosystems are very likely to be much larger 

(Root and Schneider 2006).

Movement of species in regions of North America in response to climate warming is expected to 

result in shifts of species ranges poleward, and 

upward along elevational gradients (Parmesan 

2006). Species differ greatly in their life-history 

strategies, physiological tolerances, and dispersal abilities, which underlie the high variability 

in species responses to climate change. Many 

animals have evolved powerful mechanisms 

to regulate their physiology, thereby avoiding 

some of the direct influences of climate change, 

and instead interact with climate change through 

indirect pathways involving their food source, 

habitat, and predators (Schneider and Root 

1996). Consequently, most distributional studies, which incorporate integrated measures of 

direct and indirect influences to changes in the 

climate environment, tend to focus on animals 

while phenological studies, which incorporate 

measures of direct influences, focus on plants 

and insects. Although most studies tend to separate distributional and phenological effects of 

climate change, it is important to keep in mind 

that the two are not independent and interact 

with other changing variables to determine 

impacts to species (Parmesan 2006). In addition, most of the observed species responses 

have described changes in species phenologies 

(Parmesan 2006). This section will cover both 

by major taxa type.

Parmesan (2006) describes three types of studies 

documenting shifts in species ranges: (1) those 

that measure an entire species’ range, (2) those 

that infer large-scale range shifts from observations across small sections of the species’ range, 

and (3) those that infer large-scale range shifts 

from small-scale change in species abundances 

within a local community. Although very few 

studies have been conducted at a scale that encompasses an entire species’ range (amphibians 

(Pounds et al. 1999; Pounds et al. 2006), pikas 
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Chapter 5

(Beever et al. 2003), birds (Dunn and Winkler 

1999), and butterflies (Parmesan 2006, 1996)), 

there is a growing body of evidence that has 

inferred large shifts in species range across a 

very broad array of taxa. In an analysis of 866 

peer-reviewed papers exploring the ecological 

consequences of climate change, nearly 60

percent of the 1,598 species studied exhibited 

shifts in their distributions and/or phenologies 

over the 20- and 140-year timeframe (Parmesan 

and Yohe 2003). Field-based analyses of phenological responses of a wide variety of different 

species have reported shifts as great as 5.1 days 

per decade (Root et al. 2003) with an average of 

2.3 days per decade across all species (Parmesan 

and Yohe 2003).

5.2.2.1 Migratory birds 

For migratory birds, the timing of arrival to 

breeding territories and over-wintering grounds 

is an important determinant of reproductive 

success, survivorship, and fitness. Climate variability on interannual and longer time scales can 

alter phenology and range of migratory birds by 

influencing the time of arrival and/or the time of 

departure. The earlier onset of spring has consequencesfor the timing of migration and breeding

in birds that evolved to match peak food availability (Visser et al. 2006). It should be expected 

that the timing of migration would track temporal 

shifts in food availability caused by changes in 

climate and the advancement of spring.

The phenology of migration to summer and wintering areas may be disrupted for long-distance, 

continental migrations as well regional local 

or elevational migrations. Since short-distance 

migrants respond to changes in meteorological 

cues whereas long-distance migrants often rely 

on photoperiod, it has been assumed that the 

climate signature on changes in phenological 

cycles would be stronger in short distance than 

in long-distance migrants (Lehikoinen et al. 

2004). If true, this would lead to greater disruption in the timing of migration relative to 

food availability for long-distance, continental 

migrants relative to short-distance migrants. Recent studies of long-distance migration provide 

evidence to the contrary. In a continental-scale 

study of bird phenology that covered the entire 

United States and Canadian breeding range of a 

tree swallow (Tachycineta biocolor) from 1959 

to 1991, Dunn and Winkler (1999) documented 

a 9-day advancement of laying date which correlated with the changes in May temperatures 

(Winkler et al. 2002; Dunn and Winkler 1999). 

In a study of the first arrival dates of 103 migrant 

bird species (long-distant, and very long-distant 

migrants) in the Northeast during the period 

1951–1993 compared to 1903–1950, all migrating species arrived significantly earlier, but the 

birds wintering in the southern United States 

arrived on average 13 days earlier while birds 

wintering in South America arrived four days 

earlier (Butler 2003). MacMynowski and Root 

(2007) have found, in a study of 127 species 

over 20 years of migratory birds that use the 

migratory flyway through the central United 

States, that short-range migrants typically 

respond to temperature alone, which seems to 

correlate with food supply, while long-range 

migrants respond more to variation in the overall 

climate system.

Conversely, in a reversal of arrival order for 

short- and long-distance passerines, Jonzen et al. 

(2006) showed that long-distance migrants have 

advanced their spring arrival into Scandinavia 

more than short-distance migrants, based on 

data from 1980 to 2004. Similarly, in a 42-year 

analysis of 65 species of migratory birds through 

Western Europe, researchers found autumn migration of birds wintering south of the Sahara 

had advanced, while migrants wintering north 

of the Sahara delayed autumn migration (Jenni 

and Kéry 2003). Finally, a study that combined 

analysis of spring arrival and departure dates 

of 20 trans-Saharan migratory bird species to 

the United Kingdom found an 8-day advance 

in the arrival and the departure time to the 

breeding grounds, but with no change in the 

residence time. The timing of arrival advanced 

in relation to increasing winter temperatures 

in sub-Saharan Africa, whereas the timing of 

departure advanced in response to elevated 

summer temperatures in their breeding ground 

(Cotton 2003). But, without an understanding 

of how this change correlates with phenology of 

the food resource, it is difficult to discern what 

the long-term consequences might be (Visser

and Both 2005).

As these studies suggest, when spring migration 

phenology changes, migrants may be showing a 

direct response to trends in weather or climatic 

patterns on the wintering ground and/or along 

Climate variability 

on interannual 

and longer time 

scales change can 

alter phenology 

and range of 

migratory birds 

by influencing the 

time of arrival 

and/or the time of 

departure.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

the migration route, or there may be indirect 

microevolutionary responses to the selection 

pressures for earlier breeding (Jonzen et al. 

2006). A climate change signature is apparent 

in the advancement of spring migration phenology (Root et al. 2003), but the indirect effects 

may be more important than the direct effects 

of climate in determining the impact on species persistence and diversity. Indeed, there is 

no a priori reason to expect migrants and their 

respective food sources to shift their phenologies at the same rate. A differential shift will 

lead to mistimed reproduction in many species, 

including seasonally breeding birds. There may 

be significant consequences of such mistiming

if bird populations are unable to adapt (Visser 

et al. 2004). Phenological shifts in migration 

timing in response to climate change may lead 

to the failure of migratory birds to breed at the 

time of abundant food supply (Visser et al. 2006; 

Visser and Both 2005; Stenseth and Mystread 

2002) and, therefore, may have implications for 

population success if the shift is not synchronous 

with food supply availability. Understanding 

where climate change-induced mistiming will 

occur and the underlying mechanisms will be 

critical in assessing the impact of global climate change on the success of migratory birds 

(Visser and Both 2005). The responses across 

species will not be uniform across their ranges, 

and are thus likely to be highly complex and 

dependent on species-specific traits, characteristics of local microhabitats, and aspects of local 

microclimates.

5.2.2.1.1 Mismatches and extinctions

Many migratory birds, especially short-range 

migrants, have adapted their timing of reproduction to the timing of the food resources. 

A careful examination of food resource availability relative to spring arrival and egg-laying 

dates will aid in the understanding of impacts 

of climate change. There is a suite of responses 

that facilitates an adaptive phenological shift; a 

shift in egg-laying date or a shift in the period 

between laying of the eggs and hatching of the 

chicks. In a long-term study of the migratory 

pied flycatcher (Ficedula hypoleuca), researchers found that the peak of abundance of their 

food resource (caterpillars) has advanced in 

the last two decades and, in response, the birds 

have advanced their laying date. In years with 

an early caterpillar peak, the hatching date was 

advanced and clutch sizes were larger. Populations of the flycatcher have declined by about 

90 percent over the past two decades in areas 

where food for provisioning nestlings peaks 

early in the season, but not in areas with a late 

food peak (Both 2006).

Climate change will lead to changing selection 

pressures on a wide complex of traits (Both and 

Visser 2005). It is the mistiming of the migration arrival, the provisioning of food resources 

and the lay dates that drive population declines. 

Predicting the long-term effects of ecological 

constraints and interpreting changes in life-history traitsrequire a better understanding of both

adaptive and demographic effects of climate 

change. Environmental stochasticity has the 

most immediate effect on the risk of population 

extinction because of its effects on parameters 

characterizing population dynamics, whereas 

the long-term persistence of populations is 

most strongly affected by the specific population growth rate (Saether et al. 2005). Research 

focused on both will aid in the understanding of 

the impacts of climate change.

5.2.2.2 Butterflies

Since temperature determines timing of migration and distribution, it is not surprising that 

many studies have documented changes in 

phenology of migration and significant shifts 

in latitudinal and elevational distribution of 

butterflies in response to current-day warming. 

The migration of butterflies in spring is highly 

correlated with spring temperatures and with 

early springs. Researchers have documented 

many instances of earlier arrivals (26 of 35 species in the United Kingdom (Roy and Sparks 

2000); 17 of 17 species in Spain (Stefanescu et al. 

2004); and 16 of 23 species in central California 

(Forister and Shapiro 2003)). An analysis of a 

113-year record of nine migrating butterflies and 

20 migrating moths found increasing numbers of 

migrants with increasing temperature along the 

migration route in response to fluctuation in the 

North Atlantic Oscillation (Sparks et al. 2005).

Butterflies are also exhibiting distributional and/

or range shifts in response to warming. Across 

all studies included in her synthesis, Parmesan 

(2006) found 30–75 percent of species had 

expanded northward, less than 20 percent had 

contracted southward, and the remainder were 

In a long-term study 

of the migratory 

pied flycatcher 

(Ficedula hypoleuca), 

researchers found 

that the peak of 

abundance of their 

food resource 

(caterpillars) has 

advanced in the last 

two decades and, in 

response, the birds 

have advanced their 

laying date.
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Chapter 5

stable (Parmesan 2006). In a sample of 35 nonmigratory European butterflies, 63 percent have 

ranges that have shifted to the north by 35–240 

km during this century, and 3 percent that have 

shifted to the south (Parmesan et al. 1999). In 

North America, butterflies are experiencing both 

distributional shifts northward, with a contraction at the southern end of their historical range, 

and to higher elevations, as climate changes.

In a 1993–1996 recensus of Edith’s checkerspot 

butterfly (Euphydryas editha) populations, 

Parmesan et al. (1996) found that 40 percent of 

the populations below 730 meters had become 

extinct despite the availability of suitable physical habitat and food supply, compared to only 

15 percent extinct above the same elevation 

(Parmesan 1996). Wilson et al. (2007) documented uphill shifts of 293 meters in butterfly 

species richness and composition in central 

Spain between 1967–1973 and 2004–2005, 

consistent with an upward shift of mean annual 

isotherms, resulting in a net decline in species 

richness in approximately 90% of the study region (Wilson et al 2007). In Britain, Franco et al. 

(2006) documented climate change as a driver 

of local extinction of three species of butterflies 

and found range boundaries retracted 70–100 

km northward for Aricia artaxerxes, Erebia 

aethiops and 130–150 meters uphill for Erebia 

epiphron; these changes were consistent with 

estimated latitudinal and elevational temperature 

shifts of 88 km northward and 98 meters uphill 

over the 19-year study period.

An investigation of a skipper butterfly (Atalopedes campestris) found that a 2–4°C warming 

had forced a northward range expansion over the 

past 50 years, driven by increases in winter temperatures (Crozier 2003, 2004). A study investigating the altitudinal and latitudinal movements 

of 51 British butterfly species related to climate 

warming found that species with northern and/

or montane distributions have disappeared from 

low elevation sites, and colonized sites at higher 

elevations consistent with a climate warming, 

but found no evidence for a systematic shift 

northward across all species (Hill et al. 2002). 

A subsequent modeling exercise to forecast

potential future distributions for the period 

2070–2099 projects 65 and 24 percent declines 

in range sizes for northern and southern species, 

respectively (Hill et al. 2002).

5.2.2.2.1 Mismatches and extinctions

As is the case for birds, changes in timing of 

migrations and distributions are likely to present 

resource mismatches that will influence population success and alter the probability of extinction. Predictions of climate-induced population 

extinctions are supported by geographic range 

shifts that correspond to climatic warming, and 

a few studies have linked population extinctions 

directly to climate change (McLaughlin et al. 

2002; Franco et al. 2006). As populations of 

butterfly species become isolated by habitat loss, 

climate change is likely to cause local population extinctions.

Modeling of butterfly distribution in the future 

under climate change found that while the potential existed to shift ranges northward in response 

to warming, lack of habitat availability caused 

significant population declines (Hill et al. 2002). 

Similarly, phenological asynchrony in butterflyhost interactions in California led to population 

extinctions of the checkerspot butterfly during extreme drought and low snowpack years 

(Singer and Harter 1996; Thomas et al. 1996; 

Ehrlich et al. 1980; Singer and Ehrlich 1979). 

A modeling experiment of two populations of 

checkerspot butterfly suggested that decline of 

the butterfly was hastened by increasing variability in precipitation associated with climate 

change. The changes in precipitation amplified 

population fluctuations leading to extinction in 

a region that allowed no distributional shifts 

because of persistent habitat fragmentation 

(McLaughlin et al. 2002).

Whether there is evidence of actual evolutionary 

change in insects in response to climate change 

is presently unclear. A study of the speckled 

wood butterfly (Pararge aegeria) in England 

found that evolutionary changes in dispersal 

were associated with reduced investment in reproduction, which affects the pattern and rate of 

expansion at range boundaries (Hughes 2003). 

But this result is only suggestive of a potential 

interaction of the factors that control the pattern 

and rate of expansion at range boundaries and 

the response to a changing climate system.

5.2.2.3 Mammals

Mammals are likely to interact with climate 

through indirect pathways involving their food 

source, habitat, and predators, perhaps more 

In North America, 

butterflies are 

experiencing both 

distributional shifts 

northward, with 

a contraction at 

the southern end 

of their historical 

range, and to higher 

elevations as climate 

changes.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

strongly than through direct effects on body temperature (Schneider and Root 2002), although 

Humphries et al. (2004) also demonstrate that 

overall bioenergetic considerations are important, especially in northern species. Over periods of geological time, mammals’ geographic 

distributions have been demonstrated to respond 

to long-term changes in climatic conditions. 

Guralnick (2007) has shown that for mammal 

species of long duration in North America (i.e., 

those that have had good distributional records 

in both the Late Pleistocene and modern times), 

flatland species had large northward changes 

in the southern edge of their distributions as 

a response to the warming of the interglacial 

period. Montane species showed more upward 

and northward shifts during this time period, 

with the consequence that their overall ranges

appeared to expand rather than to simply to 

track to new climatic conditions. Guralnick’s 

results are not specific to the problems posed 

by recent changes in the physical climate system, or to projected changes, because these 

are happening much faster than interglacial 

warming. However, they are indicative of the 

direction of change that even mammal species 

are expected to undergo as the physical climate 

system changes.

Guralnick (2007) was not able to specify mechanisms by which such range adjustments occurred 

in his statistical analysis of existing data. It is 

likely, however, that climate change will alter 

the distribution and abundance of northern mammals through a combination of direct, abiotic 

effects (e.g., changes in temperature and precipitation) and indirect, biotic effects (e.g., changes 

in the abundance of resources, competitors, and 

predators). The similar results of MartinezMeyer et al. (2004) suggest that the methods of 

modeling climate change response in mammals’ 

geographic ranges as a function of changes in 

climate should provide robust results, at least 

over time periods that are long enough to allow 

the individual species to respond. In the United 

States, the General Accounting Office (2007) 

has identified several examples of mammals in 

the system of U.S. public lands for which the 

consequences of climate change are expected

to be noticeable – among these are grizzly 

bears, bighorn sheep, pikas, mountain goats, 

and wolverines. In each case, the responses 

to climate-driven changes do not appear to be 

direct physiological responses to temperature 

and precipitation as much as they are responses 

to changes in the distribution of habitats, and in 

particular the compression and loss of habitats 

at higher elevations in mountainous areas.

The pika is a particularly interesting example, 

as several populations appeared to be extirpated 

in the United States when resampled during the 

1990s (Beever et al. 2003). The pika lives in 

talus habitats at high elevations in mountainous 

areas and has a very short active season during 

the growing season, when it gathers grass for 

food for survival during the winter months. 

Seven out of 25 previously reported (early 20th

century) populations appeared to have disappeared. Beever et al. (2003) concluded that local 

extirpations were best explained in a multifactorial way, and that changes in climatic factors that 

affected available habitat and food supply were 

one of the important factors. Similar phenomena have been reported for a different species 

of pika in Xinjiang Province in China (Li and 

Smith 2005). Climate effects are known to be 

important in both situations.

5.2.2.4 Amphibians

Many amphibian species are known to be undergoing rapid population declines, and there has 

been considerable discussion in the literature 

about the degree to which climate change might 

be involved (Stuart et al. 2004; Pounds, 2001; 

Carey et al. 2001). Carey et al. (2001) constructed a large database that included sites at which 

amphibian declines had been documented, and 

others at which they had not been. There were 

correlations of global environmental change in 

the climate system with evidence of decline, but 

their conclusion was that it was unlikely that the 

change in climate itself was the principal source 

of mortality in those populations. Rather, they 

hypothesized that changes in the global environment may have acted as an enabling factor, 

leading to other, more immediate causes of 

pathology and population declines.

There is some evidence that amphibian breeding is occurring earlier in some regions, and 

that global warming is likely the driving factor 

(Beebee 2002; Blaustein et al. 2001; Gibbs and 

Breisch 2001). Some temperate-zone frog and 

toad populations show a trend toward breeding 

earlier, whereas others do not (Blaustein et al. 
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2001). Statistical tests (Blaustein et al. 2002) 

indicate that half of the 20 species examined 

by Beebee (1995), Reading (1998), Gibbs and 

Breisch (2001), and Blaustein et al. (2001) are 

breeding earlier. Of the half not exhibiting statistically significant earlier breeding, they are 

showing biologically important trends toward 

breeding earlier that, if continued, will likely 

become statistically significant (Blaustein et 

al. 2002). When taken together, these important 

data suggest that global warming is indeed affecting amphibian breeding patterns in many 

species. There is, however, marked unevenness 

of climate-change effects on amphibian breeding. For example, Fowler’s Toad, Bufo fowleri, 

a late breeder, has bred progressively later in 

spring over the past 15 years on the north shore 

of Lake Erie (Blaustein 2001).

Kiesecker et al. (2001), in their study of amphibian populations in the U.S. Pacific Northwest, 

which are declining, point out that there are 

potential interactions among a number of environmental factors, including interannual climate 

variability, exposure to UV-B radiation causing egg and embryo mortality, and persistent 

climate change. It is very difficult to use field 

studies by themselves to sort out the relative 

contributions of each. However, two of the bestknown examples of a climate-mediated rapid 

decline in amphibian populations are provided 

by the Golden Toad and Harlequin Frog, both

of which are found in Costa Rica in the Monte 

Verde cloud forest. Pounds and Crump (1994) 

documented disappearances of the previously 

abundant populations of both animals as a consequence of climate-mediated stresses, in this

case initially with the severe El Niño episode 

of 1987.

The discovery of a new disease caused by a 

previously unknown chytrid fungus has complicated the picture somewhat. But several studies, 

summarized recently by Wake (2007), conclude 

that even with the presence of the chytrid fungus, climate change has clearly had an impact 

in many of the well-documented amphibian declines and extinctions. Wake (2007) also points 

out that in at least one case, declines have also 

been found in nearby lizard species in the same 

habitats, although lizards are not known to be 

susceptible to the chytrid fungus.

5.2.3 Geographical and

Distributional Responses

of Plants

In this assessment, the chapters on forests, arid 

lands and agriculture largely consider changes 

in either individual plant or ecosystem processes – e.g., photosynthesis and transpiration, soil 

respiration, allocation of carbon to above- and 

below-ground components of ecosystems, and 

overall carbon capture and sequestration. Those

chapters, as well as a subsequent section in this

chapter, also consider disturbances of different 

types as they affect ecosystem composition

and processes, including fire, pests, and invasive species.

But a fundamental tenet of ecology is that the 

geographical distribution of plant species is 

determined in large part by climatic conditions. 

It is therefore natural to ask whether there is evidence of changes in plant distributions as a result 

of climate variability and change as well as in 

plant/ecosystem functional performance. It is 

also important to understand the degree to which 

changes might be expected to occur in the future 

in plant distributions, both at the functional level 

and at the individual species level.

Iverson and Prasad (2001) provide a comprehensive review of methods to determine both 

empirical and modeling approaches to understanding how vegetation responds to changes in 

climate. They point out that paleoecological observations demonstrate not only that tree species 

did respond to long-term changes in climate, 

but that they did so individually, leading to new 

combinations of species than previously existed. 

Iverson and Prasad (2001) show the results of 

statistical modeling for the potential future distribution of tree species in the eastern United 

States, using several different model-derived 

climate scenarios. Out of a pool of 80 common 

tree species, they conclude that some forest 

types (e.g., oak-hickory) are likely to expand, 

while others (maple-beech-birch) will likely 

contract, and still others (spruce-fir) are likely 

to be extirpated within the United States. Their 

results appear to be robust to different climate 

scenarios, and are consistent with what we know 

about these species in the paleo record.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Dirnbock et al. (2003) document both the existing relationships between the distribution of 85 

alpine plant species in Europe and climate and 

land-use variables. They then use simple projections of both land-use and climate variables 

to assess the likely responses of these plants to 

changes in climate over the next several decades, 

concluding that climate forcings and land-use 

changes will interact substantially to determine 

future distributions.

Burkett et al. (2005) and the Government Accounting Office (2007) provide a number of 

current examples of vegetation changes that are 

clearly the result of responses to variability in 

climatic forcings, and supply mechanisms for 

those changes. Examples include changes in 

wetland vegetation in Michigan that occur as 

a result of the interaction of water withdrawals 

and drought occurrence, and extension of tree 

line in U.S. sub-Arctic and Arctic regions – the 

latter clearly responding to the observed large 

regional warming of the past several decades.

A growing community of ecosystem modelers 

using Dynamic Global Vegetation Models has 

developed a capability to simulate the changes 

in potential natural vegetation as a function of 

changes in the physical climate system (Cramer 

et al. 2001). These simulations can be used to 

investigate the potential for future changes in 

the distribution of plant functional types, and 

serve as a guide for assessing risk. Scholze et al. 

(2006) provide one such example, concluding 

that for an analysis that considered 16 different 

climate/atmospheric composition scenarios, 

there was a large risk of considerable change in 

forested ecosystems and freshwater supply in 

many regions around the world, including the 

eastern United States. However, such analyses 

do not include land management or land-use 

processes, and thus establish the potential for 

change, rather than serving as quantitative predictions of change.

5.3 Changes in Coastal

 and Near-shore

Ecosystems

Coastal and marine ecosystems are tightly coupled to both the adjacent land and open ocean 

ecosystems and are thus affected by climate in 

multiple ways. In the tropics, coral bleaching 

and disease events have increased, and in the 

Atlantic, hurricane intensity and destructive 

potential has increased. In temperate regions, 

there are demonstrated range shifts and possible 

alterations of ocean currents and upwelling 

strength. In the Arctic, there have been dramatic 

reductions in sea ice extent and thickness, as 

well as related coastal erosion. Marine species 

were the first to be listed as threatened species 

due to physical stresses that are clearly related 

to variability and change in the climate system 

(Federal Register 2006). Coastal and near-shore 

ecosystems are vulnerable to a host of climate 

change-related effects, including increasing air 

and water temperatures, ocean acidification, 

altered terrestrial run-off patterns, altered currents, sea level rise, and altered human pressures due to these and other related changes 

(such as development, shipping, pollution, and 

anthropogenic adaptation strategy implementation). This section will discuss some of the most 

prominent effects of climate change observed 

to date in the coastal and near-shore regions 

of the United States, with some consideration 

given to applicable examples from other parts 

of the world.

5.3.1 Coral Reefs

Tropical and subtropical coral reefs around 

the world have been known for some time to 

be under a wide variety of stresses, some of 

them related to changes in the climate system, 

and some not (Bryant et al. 1998). The United 

States has extensive coral reef ecosystems in 

both the Caribbean Sea and the Pacific Ocean. 

Coral reefs are very diverse ecosystems, home 

to a complex of species that support both local 

and global biodiversity and human societies. It 

has been estimated that coral reefs provide $30 

billion in annual ecosystem service value (Cesar 

et al. 2003), including both direct market values 

of tourism, and estimates of the market value of 

other services, such as provision of habitat for 

fish breeding, and protection of coastline. A 
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Chapter 5

variety of regional estimates of economic value 

(Cesar 2000) have also been made that show 

substantial variation in their totals, depending 

in part on which services are taken into consideration. In some small developing countries, 

coral reefs may supply substantial fractions of 

total economic return through their contribution 

to tourism and as habitat for coastal fisheries; 

even in the United States and Australia where 

coral reefs provide small fractions of the total 

revenue, they generate many billions of dollars 

and can be very important in regional economies 

(Hoegh-Guldberg et al. 2007).

Corals and tropical regions where they live are 

experiencing increasing water temperatures, a 

reduction in surface water pH (Ravens et al. 

2005), and there is evidence for increasing storm 

intensity (Emmanuel 2005), as well as a host of 

other ongoing challenges created as a result of 

development/tourism, fishing, and pollution. 

The effects of climate change in marine systems 

is highlighted by the 2006 proposed listing as 

Threatened under the Endangered Species Act of 

two species of corals in the Caribbean (Federal 

Register 2006). The major threats that motivated 

the proposed listings of Elkhorn (Acropora 

palmata) and Staghorn (A. cervicornis) corals 

were disease, elevated sea surface temperatures, 

and hurricanes – all of which relate to climate 

change and its effects (Muller et al. 2007; Mann 

and Emmanuel 2006).

5.3.1.1 Increasing Temperature and 

Acidification of Ocean Waters

The El Niño-Southern Oscillation (ENSO) 

event of 1982–83 marked the first contemporary 

broad-scale coral reef bleaching and mortality 

event (Glynn 1984). Since then, there have 

been subsequent bleaching events including the

1997–98 ENSO. The rate of occurrence (annually in some cases), and almost global scale 

since the early 1980s is in stark contrast to the 

trend of the first half of the century in which 

bleaching events were localized and linked to 

local events (D’Elia et al. 1991; Glynn 1993). 

From 1876–1979 only three bleaching events 

were recorded, whereas 60 are on record between 1980 and 1993 (Glynn 1993). Bleaching 

is considered to be a stress response caused primarily by increased water temperature (Glynn 

1993) and synergistically enhanced by increased 

irradiance levels (Fitt and Warner 1995; Jokiel 

and Coles 1990; Lesser et al. 1990). Corals 

become stressed if exposed to slight increases 

in water temperature – increases of only 1 to 

2oC over the average annual thermal maxima 

for days to weeks can result in a bleaching 

event (Hoegh-Guldberg 1999). Field studies 

have correlated increased temperatures with 

mass bleaching events (Brown 1997; HoeghGuldberg et al. 1997; Glynn 1993). Additionally, 

the National Oceanic and Atmospheric Administration (NOAA) “Hotspot” program (Goreau 

and Hayes 1994) predicted bleaching for most 

geographic regions where bleaching occurred 

in 1998, adding further weight to the assessment that elevated temperature is the primary 

trigger for bleaching (Hoegh-Guldberg 1999). 

The final effect of the 1997–98 bleaching event 

has been assessed, with estimates indicating that 

10–16 percent of world’s living coral reefs died 

during this event. In the western Indian Ocean, 

coral reefs lost up to 46 percent of living, reefbuilding corals (Hoegh-Guldberg 2005).

In 2005, the Caribbean basin saw unprecedented 

water temperatures and some dramatic bleaching, followed by coral disease and mortality. The 

most dramatic monitored bleaching took place 

in the U.S. Virgin Islands, where National Park 

monitoring showed that at some sites 90 percent 

of the coral bleached. Afterward there appeared 

to be a period of recovery as water temperatures 

decreased. Unfortunately, this was short-lived as 

disease appeared in November of the same year 

on many of the previously bleached corals. To 

date there is an estimated 50 percent combined 

mortality from bleaching and disease in the 

Virgin Island National Park surveys. As of yet, 

there are no reports of recovery as amounts of 

mortality continue to increase (Eakin et al., in 

press, accepted). In the Florida Keys, equally

massive bleaching was anticipated when temperatures exceeded 9-degree heating weeks in 

late August 2005 (NOAA Coral Reef Watch), 

and in fact some bleaching was observed. But 

the arrival of hurricanes Katrina and Rita reduced water temperatures and appear to have 

provided some respite for corals in the Keys. 

However, the same pattern of disease was seen 

in the Keys in those corals that did bleach, with 

bleaching setting in around mid-August, followed by disease in early September (Brandt, 

in press, accepted).

Coastal and nearshore ecosystems are 

vulnerable to a host of 

climate change-related 

effects, including 

increasing air and 

water temperatures, 

ocean acidification, 

altered terrestrial 

run-off patterns, 

altered currents, sea 

level rise, and altered 

human pressures due 

to these and other 

related changes (such 

as development, 

shipping, pollution, 

and anthropogenic 

adaptation strategy 

implementation).
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Both intensities and frequencies of bleaching

events clearly driven by warming in surface 

waters have increased substantially over the 

past 30 years (Hughes et al. 2003). At least 30 

percent of reefs globally have been severely 

damaged, and relatively simple projections 

based on temperature changes alone suggest that 

within the next several decades, as many as 60 

percent of the world’s reefs could be damaged 

or destroyed (Hughes et al. 2003). While there is 

some evidence of short-term recovery, in many 

locations the frequency of bleaching events

could become nearly annual within several 

decades under a variety of reasonable climate 

scenarios (Donner et al. 2005). Such changes 

would be significantly more rapid and pose 

significant problems for coral reef management 

on a global scale (Hughes et al. 2003; Pandolfi 

et al. 2003; Hoegh-Guldberg et al. 2007).

Additionally, as CO2 concentrations increase in 

the atmosphere, more CO2 is hydrolyzed in the 

surface waters of the world’s oceans, leading 

to their acidification (Orr et al. 2005; HoeghGuldberg et al. 2007) (Figure 5.2). The chemical 

reactions governing the dissolution of CaCO3 in 

surface waters, and therefore the availability of 

material for building corals’ calcium carbonate 

skeletons (as well as those of other calcifying 

organisms) are pH-dependent, and increases in 

acidity can lead to decreases in available CaCO3

(Yates and Halley 2006). During the past 200 

years, there has been a 30 percent increase in 

hydrogen-ion concentration in the oceans, and 

it is anticipated that this will increase by 300 

percent by the end of this century (Ravens et 

al. 2005). There is evidence from site-specific 

studies (Pelejero et al. 2005) that in the Pacific 

Ocean there is natural decadal variability in the 

pH levels that individual reefs actually experience, and that the variability matches well with 

Interdecadal Pacific Oscillation variability.

However, even though some reef species may be 

more resistant to increases in acidity than others, the longer-term decreases in ocean pH due 

to increased atmospheric CO2 concentrations 

may be occurring much more rapidly than in the 

recent history. And, when these long-term trends 

occur in phase with the IPO, even relatively 

resistant reefs would be exposed to extremely 

low pH levels that they have not experienced 

before. There are predictions that oceans could 

become too acidic over the long term for corals 

– as well as other species – to produce calcium 

carbonate skeletons (Caldeira and Wickett 2003; 

Figure 5.2 The figure above depicts various direct and indirect effects of changes in atmospheric CO2 concentrations on coral reef ecosystems. Solid lines indicate direct effects, dashed lines indicate indirect effects, and dotted 

lines indicate possible effects. Fe = iron; SST = sea surface temperature; CO3

2- = carbonate ion.
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Chapter 5

Hoegh-Guldberg 2005; Kleypas et al. 1999). 

More recent reviews of both experimental studies, modeling projections, and field observations 

suggest that the combination of changes in ocean 

surface temperatures, increasing ocean acidity, 

and a host of other stresses could bring coral 

reef ecosystems to critical ecological tipping 

points (Groffman et al. 2006) within decades 

rather than centuries, and that some regions 

of the ocean are already near that point from 

a biogeochemical perspective (Orr et al. 2005; 

Hoegh-Guldberg 2007).

Increasing sea surface temperatures are expected to continue as global temperatures rise. 

It is possible that these warmer waters are also 

increasing the intensity of the tropical storms in 

the region (Mann and Emmanuel 2006; Sriver 

and Huber 2006; Elsner 2006; Hoyos et al. 

2006). As global temperatures rise, sea level 

will continue to rise providing additional challenges for corals. Increasing depths change light 

regimes, and inundated land will potentially 

liberate additional nutrients and contaminants 

from terrestrial sources, especially agricultural 

and municipal.

5.3.2 Coastal Communities and

Ecosystems

5.3.2.1 Wetlands and Barrier Islands

The marine-terrestrial interface is vitally important for biodiversity as many species depend on 

it at some point in their life cycles, including 

many endangered species such as sea turtles 

and sea birds. In addition, coastal areas provide 

a wide variety of ecosystem services, including 

breeding habitat and buffering inland areas from 

the effects of wave action and storms (MEA 

2005). There is a wide variety of different 

types of habitat in coastal margins, from coastal 

wetlands, to intertidal areas, to near-shore ecosystems, all of which are subject to a variety of 

environmental stresses from both the terrestrial, 

inland environments and from oceanic environments (Burkett et al. 2005). The additional proximity of large numbers of people makes coastal 

regions extremely important natural laboratories 

for global change.

Mangroves and sea grasses protect coastlines 

from erosion, while also protecting near-shore 

environments from terrestrial run-off. Sea level 

rise, increased coastal storm-intensity and temperatures contribute to increased vulnerability 

of mangrove and sea grass communities (e.g., 

Alongi 2002). It has been suggested that the 

dominant sea grass species (Zostera marina) is 

approaching its thermal tolerance for survival in 

the Chesapeake Bay (Short and Neckles 1999). 

It has also been estimated that a 1-meter increase 

in sea level would lead to the potential inundation of 65 percent of the coastal marshlands and 

swamps in the contiguous United States (Park et 

al. 1989). In addition to overt loss of land, there 

will also be shifts in ìqualityî of habitat in these

regions. Prior to being inundated, coastal watershed will become more saline due to saltwater 

intrusion into both surface and groundwater. 

Burkett et al. (2005) provide several excellent 

examples of documented and potential rapid, 

non-linear ecological responses in coastal wetlands to the combination of sea-level rise, local 

subsidence, salinity changes, drought, and sedimentation. Of particular concern in the United 

States are coastlines along the Gulf of Mexico 

and the Southeast Atlantic, where the combination of sea level rise and local subsidence has 

resulted in substantially higher relative, local 

rates of sea-level rise than farther north on the 

Atlantic Coast, or on the Pacific Coast (Burkett 

et al. 2005). In Louisiana alone, more than 1/3 

of the deltaic plain that existed in the beginning 

of the 20th century has since been lost to this 

combination of factors. In the Gulf of Mexico 

and the South Atlantic, the ecological processes 

that lead to accretion of wetlands and continued 

productivity (Morris et al. 2002) have not been 

able to keep pace with the physical processes 

that lead to relative rising sea level (Burkett et 

al. 2005).

Barrier islands are particularly important in 

some regions where vulnerability to sea level 

rise is acute. In the northwest Hawaiian Islands, 

which were designated a National Monument 

in 2006, sea level rise is a threat to endangered 

beach nesting species and island endemics, including green sea turtles, Hawaiian monk seals, 

and the Laysan finch (Baker et al. 2006). Another example of an endangered island-locked 

species is the Key Deer, which is now limited to 

living on two islands in the Florida Keys. Their 

habitat is also at risk with most of the Keys at 

less than two meters above sea level. Median 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

sea level rise coupled with storm surges would 

inundate most of the available habitat either 

permanently or episodically, further threatening 

this endangered species.

5.3.2.2 Rocky Intertidal Zones

Rocky intertidal habitats have been studied 

extensively with respect to their observed 

and potential responses to climate variability 

and change, both in Europe and in the United 

States (Helmuth et al. 2006; Mieszkowska et 

al. 2007; Mieszkowska et al. 2005; Bertness 

et al. 1999; Sagarin et al. 1999; Thompson et 

al. 2002; Mieszkowska et al. 2006; Barry et al. 

1995). These systems react quite differently

from wetlands because of the large differences 

in substrates. Nevertheless, the typical biota of 

gastropods, urchins, limpets, barnacles, mussels, etc., show reproductive, phenological, 

and distributional responses, similar in kind to 

responses of birds, butterflies, and mammals reported earlier in this chapter. However, Helmuth 

et al. (2006) point out that range shifts of up to 

50 kilometers per decade have been recorded 

for intertidal organisms – far faster than documented for any terrestrial species to date.

Responses include reacting to changes in the 

thermal habitat, which results in heat stress, 

and subsequent low growth rates and early,

stress-induced spawning of mussel species in 

New Zealand (Petes et al. 2007). Long timeseries of observational data across several quite

different taxonomic groups in the British Isles 

show consistent trends for species in response 

to strong regional warming trends observed 

since the 1980’s, including: range extensions of 

northern species into previously colder waters; 

some range extension eastward of southern 

species into the English channel; a few species 

with southern range retractions; and several 

southern species showing earlier reproduction, 

greater survival rates, and faster growth rates 

than northern species (Mieszkowska et al. 2005). 

These responses are extremely similar to the 

biological responses shown by rocky intertidal 

species in the United States in several different 

locations (Bertness et al. 1999; Helmuth et al. 

2006; Barry et al. 1995; Sagarin et al. 1999) on 

both the Pacific and Atlantic coasts. There is 

some suggestion in Europe that there could be 

food-web level effects on the supply of food for 

shore birds, but interactions among shore bird 

predators, gastropods and other rocky intertidal 

organisms, and algal cover are complex and 

extremely difficult to predict (Kendall et al. 

2004).

Thompson et al. (2002), Helmuth et al. (2005) 

and Helmuth et al. (2006) all point out that the 

observational base of responses of intertidal 

organisms to changes in climate is well enough 

understood that reasonable projections of future 

change can be made. However, knowledge of 

the particular physiological mechanisms for the 

individual species’ responses is especially important (Helmuth et al. 2005) in order to distinguish the reasons for the variation in responses, 

and in order to understand how climate changes 

operate in these systems in the presence of other 

physical and biological stresses.

Because of its importance as a contributing 

stress to coastal and intertidal habitats, projections of mean sea-level rise have been important 

to understand. Projections for sea level rise by 

2100 vary from 0.18 to 0.59 m (±0.1-0.2) (IPCC 

2007) to 0.5 to 1.4 m (Rahmstorf 2007). Some 

observational evidence suggests that recent 

IPCC estimates may be conservative and underestimate the rate of sea level rise (Meehl et 

al. 2007). The IPCC projection of 18–59 cm in 

this century assumes a negligible contribution 

to sea level rise by 2100 from loss of Greenland 

and Antarctic ice. Melting of the Greenland ice 

sheet has accelerated far beyond what scientists 

predicted even just a few years ago, with a more 

than doubling of the mass loss from Greenland 

due to melting observed in the past decade 

alone (Rignot and Kangaratnam 2006). The 

acceleration in the rate of melt is due in part 

to the creation of rivers of melt water, called 

ìmoulins,î that flow down several miles to the

base of the ice sheet, where they lubricate the 

area between the ice sheet and the rock, speeding the movement of the ice toward the ocean. 

Paleoclimatic data also provide strong evidence 

that the rate of future melting and related sealevel rise could be faster than previously widely 

believed (Overpeck et al. 2006).
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Chapter 5

5.4 Climate Change, Marine

Fisheries and Marine

Ecosystem Change

The distribution of fish and planktonic species 

are also predominately determined by climatic 

variables (Hays et al. 2005; Roessig et al. 2004) 

and there is recent evidence that marine species 

are moving poleward, and that timing of plankton blooms is shifting (Beaugrand et al. 2002; 

Hays et al. 2005; Richardson and Schoeman 

2004). Similar patterns have been observed in 

marine invertebrates and plant communities 

Figure 5.3 Diagram of nutrient dynamics. a) Summer: a profile view of 

a ria and the adjacent continental shelf, illustrating the “loop” consisting 

of upwelling-enriched primary production, which leads to export, sinking, and accumulation on the bottom of particulate organic matter. This 

organic matter decays and remineralizes, enriching the waters beneath 

the nutricline. b) Fall: After fall relaxation of upwelling, lighter oceanic 

surface water collapses toward the coast, producing a zone of downwelling 

in the ria. This depresses the nutricline and cuts off upwelling-produced 

enrichment of the photic zone. Vertically migrating dinoflagellates may 

access the nutrient pool beneath the nutricline and transport them upward to levels of higher illumination, where they can use them to support 

photosynthesis. From Bakun 1996.

(Beaugrand et al. 2002; Sagarin et al 1999), 

Southward et al. (1995) document extensive 

movement of ranges and distributions of both 

warm and cold-water species of fish and other 

marine life around the British Isles and northern Europe over the past several decades, with 

long-time series of data from fish landings. They 

point out that much of the original research on 

fisheries biology in these regions took place 

from the 1930s–1970s, a period of relative 

constancy in the marine climate system in these 

regions. Changes in distributions since then appear to be much more pronounced.

Similar phenomena have been documented 

in Europe for Arctic and Norwegian cod in 

the Barents Sea (Dippner and Ottersen 2001), 

and Atlantic cod (Drinkwater 2005), where 

spawning, survival, and growth rates are affected in predictable ways by ocean temperature 

anomalies. In each case, the climate variability 

analyzed is tied to particular oscillations in the 

physical climate system (e.g., the North Atlantic 

Oscillation for cod), or to longer-term changes 

in climate. Fields et al. (1993) provide a general overview of the factors associated with the 

marine ecosystem responses to climate change. 

As in other systems examined in this report, 

the particular biological mechanisms of species 

responses are important in determining overall 

patterns. In addition, Hsieh et al. (2005) show 

that these large marine ecosystems are intrinsically non-linear, and thus subject to extremely 

rapid and large changes in response to small 

environmental forcings.

In coastal regions, decreased upwelling can 

decrease nutrient input to surface waters, reducing primary productivity (Soto 2002; Field et 

al. 2001). The food-web-level effects that such 

changes cause have been documented off the 

coast of Southern California after an abrupt, 

sustained increase in water temperature in the 

1970s (Field et al. 1999). Conversely, climate 

change may alter wind patterns in ways that 

accelerate offshore winds and thus upwelling 

(Bakun 1990) (Figure 5.3).

Seven large marine ecosystems (LMEs) are 

recognized for U.S. waters: eastern Bering 

Sea, Gulf of Alaska, California Current, Gulf 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

of Mexico, southeast U.S. continental shelf, 

northeast U.S. continental shelf and the greater 

Hawaiian Islands. Each is being studied to varying degrees with regard to the impacts of climate 

variability and change on ecosystem structure, 

biodiversity and marine fisheries. Much of the 

research in these systems has been carried out by 

U.S. and Canadian scientists associated with the 

International Geosphere-Biosphere Programme 

GLOBal Ocean ECosystem Dynamics (IGBPGLOBEC), or by scientists following GLOBEC 

standards. The GLOBEC model focuses on 

study of the coupling of physical forcing and 

biological response in fisheries-rich ecosystems, 

and is detailed at www.globec.org. This approach has been taken due to the tight coupling 

between physics and biology in the oceans as 

compared to terrestrial ecosystems (Henderson 

and Steele 2001).

It has been well established that the large basinscale atmospheric pressure systems that drive 

basin scale winds can suddenly shift location 

and intensity at interannual-to-decadal time 

scales, with dramatic impacts on winds and 

ocean circulation patterns. These low frequency

oscillations are known as the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation 

(PDO), and the El Nino-Southern Oscillation 

(ENSO). Perhaps the greatest discovery of the 

past 10 years is that these shifts have dramatic 

impacts on marine ecosystems.

The NAO has been strongly positive since the 

1980s. Increases in the strength of the winds 

have resulted in dramatic impacts on Northeast 

Atlantic ecosystems. For instance, increased 

flow of oceanic water into the English Channel 

and North Sea has contributed to a northward 

shift in the distribution of zooplankton such that 

the zooplankton communities are dominated 

by warm water species (Beaugrand, 2004) with 

concomitant changes in dominance in fish communities from whiting (hake) to sprat (similar to 

a herring). Similar ecosystem shifts in the Baltic 

Sea have occurred where drastic changes in both 

zooplankton and fish communities have been 

observed (Kenny and Mollman 2006). Linkages 

between the NAO, zooplankton and fisheries 

have also been described for the Northwest Atlantic waters off eastern Canada and the United 

States. The recovery of the codfish populations, 

which collapsed in the early 1990s (presumably 

as a result of overfishing), may be difficult due 

to changes in the structure of forage and food 

chains (Pershing and Green 2007).

In the North Pacific, the PDO refers to the 

east-west shifts in location and intensity of the 

Aleutian Low in winter (Mantua et al. 1997). 

Widespread ecological changes have been 

observed including increased productivity of 

the Gulf of Alaska when the PDO is in positive 

phase, resulting in dramatic increases in salmon 

production (Mantua et al. 1997), and a reversal 

of demersal fish community dominance from 

a community dominated by shrimps to one 

dominated by pollock (Anderson and Piatt 

1991). Associated changes to the California 

Current ecosystem include dramatic decreases 

in zooplankton (McGowan et al. 1998) and 

salmon (Pearcy 1991) when the PDO changed 

to positive phase in 1977. There is also evidence that the large oscillations in sardine and 

anchovy populations are associated with PDO 

shifts, such that during positive (warm) phases, 

sardine stocks are favored but during negative 

(cool) phases, anchovy stocks dominate (e.g., 

Chavez et al. 2003).

ENSO is another major driver of climate variability. El Niño events negatively impact zooplankton and fish stocks resulting in a collapse 

of anchovy stocks in offshore ecosystems of 

Peru. Loss of anchovies, which are harvested 

for fish meal, affect global economies because 

fish meal is an important component of chicken 

feeds as well high-protein supplements in aquaculture feed. In waters off the west coast of the 

United States, plankton and fish stocks may collapse due to sudden warming (by 4–10°C) of the 

waters as well as through poleward advection 

of tropical species into temperate zones. Many 

of the countries most affected by ENSO events 

are developing countries in South America and 

Africa, with economies that are largely dependent upon agricultural and fishery sectors as a 

major source of food supply, employment, and 

foreign exchange.

5.4.1 Other Climate-driven Physical

Forces that Affect Marine

Ecosystems

The California Current (CC) example represents an excellent case study for one Large 

Marine Ecosystem. The CC flows in the North 

In coastal regions, 

decreased upwelling 

can decrease 

nutrient input to 

surface waters, 

reducing primary 

productivity
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Chapter 5

Pacific Ocean from the northern tip of Vancouver Island (Canada), along the coasts of 

Washington, Oregon and California, midway 

along the Baja Peninsula (Mexico) before turning west. For planktonic organisms and some 

fish species, the northern end of the Current is 

dominated by sub-arctic boreal fauna whereas 

the southern end is dominated by tropical and 

sub-tropical species. Faunal boundaries, i.e., 

regions where rapid changes in species composition are observed, are known for the waters 

between Cape Blanco, Oregon/Cape Mendocino, California, and in the vicinity of Point 

Conception, California. Higher trophic level 

organisms often take advantage of the strong 

seasonal cycles of production in the north by 

migrating to northern waters during the summer to feed. Animals that exhibit this behavior 

include pelagic seabirds such as black-footed 

albatross and sooty shearwaters, fishes such 

as Pacific whiting and sardines, and gray and 

humpback whales.

5.4.2 Observed and Projected

Impacts

Based on long-term observation records, global 

climate models, regional climate models, and 

first principles, there is a general consensus 

on impacts of climate change for the United 

States with regard to climate modes, biophysical 

processes, community and trophic dynamics 

and human ecosystems. The type, frequency

and intensity of extreme events are expected 

to increase in the 21st century, however Meehl 

et al. (2007) suggest that there is no consistent 

indication of discernable changes in either the 

amplitude or frequency of ENSO events over

the 21st century (Meehl et al. 2007). Climate 

models from the fourth IPCC assessment project roughly the same timing and frequency of

decadal variability in the North Pacific under 

the impacts of global warming. By about 2030, 

it is expected that the minima in decadal regimes will be above the historical mean of the 

20th century (i.e., the greenhouse gas warming 

trend will be as large as natural variability). 

Regional analyses suggest that for California, 

temperatures will increase over the 20th century with variable precipitation changes by region (Bell et al. 2004), which is consistent with 

global projections (Tebaldi et al. 2006).

Among other findings, IPCC assessment results for the United States suggest there will 

be a general decline in winter snowpack with 

earlier snowmelt triggered by regional warming 

(Hayhoe et al. 2004; Salathé 2005).

Additionally, warmer temperatures on land surfaces, contributing to low atmospheric pressure 

combined with ocean heating may contribute to 

stronger and altered seasonality of upwelling in 

western coastal regions (Bakun 1990; Snyder et 

al. 2003). Migration patterns of animals within 

the California Current (e.g., whiting, sardines, 

shearwaters, loggerhead turtles, Grey Whales) 

may be altered to take advantage of feeding 

opportunities. Recent disruptions of seasonal 

breeding patterns of a marine seabird (Cassin’s Auklet) by delayed upwelling have been 

reported by Sydeman et al. (2006).

Warmer ocean temperatures will contribute to 

changes in upwelling dynamics and decreased 

primary production along the California Current. Global declines in NPP (as estimated from 

the SeaWiFS satellite sensor) between 1997 

and 2005 were attributed to reduced nutrient 

enhancement due to ocean surface warming 

(Behrenfeld et al. 2006; Carr et al. 2006). A 

recent example during the summer of 2005 

was characterized by a three-month delay to 

the start of the upwelling season resulting in 

a lack of significant plankton production until 

August (rather than the usual April–May time 

period). Fish, birds and mammals that relied 

upon plankton production occurring at the 

normal time experienced massive recruitment 

failure (Schwing et al. 2006; Mackas et al. 2006; 

Sydeman et al. 2006). In contrast, the summer 

of 2006 had some of the strongest upwelling 

winds on record yet many species again experienced recruitment failure, in part because there 

was a one-month period of no winds (mid-May 

to mid-June).

Snyder et al. (2003) suggest that wind-driven 

upwelling in the California current is likely 

to continue its long, 30-year increase in the 

future, as a function of changes in the physical 

climate. Such a change could lead to enhanced 

productivity in the coastal marine environment, and subsequent changes throughout the

ecosystem.
167

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 5.4 Aerial view of the U.S. Forest Service Rocky Mountain Research Station’s Fraser Experimental Forest 

near Winter Park, Colorado, May 2007, and a mountain pine beetle (inset). The green strips are areas of forest 

that had been harvested decades earlier, and so have younger faster growing trees. The red and brown areas show 

dead and dying trees caused by bark beetle infestation. A more recent photo would show less contrast because, 

due to drought and beetle epidemic, mortality rates of young trees have also risen. Photo courtesy USFS, Rocky 

Mountain Research Station.

5.5 Changes in Pests and

 Pathogens

5.5.1 Interactions of Climate Change

with Pests, Pathogens, and

Invasive Species

Increasing temperatures and other alterations 

in weather patterns (e.g., drought, storm events) 

resulting from climate change are likely to have 

significant effects on outbreaks of pests and 

pathogens in natural and managed systems, and 

are also expected to facilitate the establishment 

and spread of invasive alien species. For the purposes of this chapter, “pests and pathogens”refers 

to undesirable outbreaks of either native or 

introduced insects or pathogens. Non-native 

species are those that are non-indigenous to a 

region, either historically or presently, while invasive species are those non-native species that 

harm the environment, the economy or human 

health. Initially, the most noticeable changes in 

plant and animal communities will most likely 

result from direct effects of climate change (for 

example, range expansions of pathogens, and 

invasive plants). The longer term consequences,

however, may be the result of indirect effects 

such as disruptions of trophic relationships or a 

species decline due to the loss of a mutualistic 

relationship (Parmesan 2006).

Interactions between increasing global temperature and pests and pathogens are of particular 

concern because of the rapid and sweeping 

changes these taxa can render. While it is still 

difficult to predict specifically how climate 

change will interact with insect pests, or plant 

and animal diseases, some recent events have 

provided glimpses into the kinds of impacts 

that might unfold.

5.5.1.1 Mountain Pine Beetle Explosion

The mountain pine beetle (Dendroctonus ponderosae) is a native species that has co-existed 

with western conifers for thousands of years 

and plays an important role in the life cycle of 

North American western forests (Bentz et al. 

2001; Powell and Logan 2001). However, the 

magnitude of recent outbreaks is above historical levels with historically unprecedented 

mortality (Logan et al. 2003). A recent outbreak 

in 2006 caused the death of nearly five million 

lodgepole pines (Pinus contorta) in Colorado, 

a four-fold increase from 2005. The infestation 

covers nearly half of all Colorado’s forests. Such 

outbreaks are not confined to Colorado, but 

are also occurring in other parts of the United 

States and Canada, affecting tens of thousands 

of square miles of forest (Figure 5.4).
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Chapter 5

Multiple factors, including climate change, have 

been implicated in driving outbreaks in North 

America (e.g., Romme et al. 2006; Logan and 

Powell 2001; Logan et al. 2003). First, many 

North American conifer forests are primarily 

mature, even-aged stands due to widespread 

burning and heavy logging of the region during settlement 100 years ago. Mountain pine 

beetles prefer the mature trees resulting from 

these disturbances. Second, long-term drought 

stresses trees and makes them more vulnerable 

to the beetles because they cannot effectively 

defend themselves. Third, warmer summers 

also cause stress and increase growth rates of 

the insects, and, fourth, milder winters increase 

the chances of survival for the insect larvae 

(Romme et al. 2006; Powell and Logan 2005; 

Powell et al. 2000). While there is not yet definitive proof that climate change is behind the 

high levels of mountain pine beetle infestation, 

a recent study showed that over the last century 

Colorado’s average temperatures have warmed 

(NRC 2007). It is therefore reasonable to expect 

that warmer temperatures in the future may lead 

to similar or more intensive events than those 

that are now occurring.

5.5.1.2 Poleward Migration of Plant

 Pests and Pathogens

Latitudinal gradients in plant defenses and herbivory are widely known but the basis for these 

defenses (i.e., genetic versus environment) are 

not fully understood. A potential outcome under 

warming global temperatures is a relatively rapid poleward migration of pests and pathogens, 

and a relatively slower rate of adaptation (e.g., 

increased defense against herbivory) for plants. 

Biogeographic theory predicts increased insect 

herbivory (i.e., greater loss of leaf area to herbivores) in the lower latitudes relative to higher 

latitudes (MacArthur 1972; Vermeij 1978; 

Jablonski 1993). As with the mountain pine 

beetle described above, higher population densities of other herbivorous insects and therefore 

herbivory occur because dormant season death 

(i.e., winter dieback) of herbivores is absent, or 

greatly reduced at warmer temperatures, and/

or plant productivity is generally greater than 

at higher latitudes (Coley and Aide 1991; Coley 

and Barone 1996). Because of this greater herbivory, plants are thought to be better defended 

or otherwise less palatable at low latitudes as 

a result of natural selection (e.g., MacArthur 

1972; Hay and Fenical 1988; Coley and Aide 

1991; Coley and Barone 1996). Alternatively, 

plants at low latitudes could be better defended 

because high latitude populations have had 

fewer generations since the last glaciation to 

evolve such defenses (Fischer 1960).

5.5.1.3 Climate Change and Pathogens

Evidence is beginning to accumulate that links 

the spread of pathogens to a warming climate. 

For example, the chytrid fungus (Batrachochytrium dendrobatidis) is a pathogen that is 

rapidly spreading worldwide and decimating 

amphibian populations. A recent study by 

Pounds et al. (2006) showed that widespread 

amphibian extinction in the mountains of 

Costa Rica is positively linked to global climate 

change. To date, geographic range expansion 

of pathogens related to warming temperatures 

has been the most easily detected (Harvell et 

al. 2002), perhaps most readily for arthropodborne infectious disease (Daszak et al. 2000). 

However, a recent literature review found additional evidence gathered through field and 

laboratory studies that supports hypotheses 

that latitudinal shifts of vectors and diseases are 

occurring under warming temperatures. Based 

on their review, Harvell et al. (2002) gathered 

evidence that:

•	 Arthropod vectors and parasites die or fail

to develop below threshold temperatures.

•	 Rates of vector reproduction, population

growth, and biting increase (up to a limit) 

with increasing temperature.

•	 Parasite development rates and period of

infectivity increase with temperature.

Furthermore, Ward and Lafferty (2004) conducted an analysis that revealed that disease 

for some groups of marine species is increasing 

while others are not. Turtles, corals, mammals, 

urchins, and mollusks all showed increasing 

trends of disease, while none were detected for 

sea grasses, decapods, or sharks/rays. The effects of increasing temperature on disease are 

complex, and can increase or decrease disease 

depending on the pathogen (Ward and Lafferty 

2004).

Expansion of an invader may not always be 

simply explained by warming temperatures. For 

example, Roman 2006 suggests that the north-
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

ern expansion of the invasive European green 

crab (Carcinus maenas) in North America was 

facilitated through the introduction of new 

lineages of C. maenas to Nova Scotia from 

the northern end of its native range in Europe. 

These northern populations may be better 

adapted to the colder temperatures found in 

northern Nova Scotia, relative to more southerly waters. Furthermore, the construction of a 

causeway and subsequent “super port” in the

Strait of Canso, Nova Scotia, appears to be at 

the epicenter of the high diversity of new C. 

maenas haplotypes (Roman 2006).

5.5.1.4 Climate Change and Invasive 

 Plants

Projected increases in CO2 are expected to 

stimulate the growth of most plants species, and 

some invasive plants are expected to respond 

with greater growth rates than non-invasive 

plants (Dukes 2000; Ziska and George 2004; 

Moore 2004; Mooney et al. 2006). Some invasive plants may have higher growth rates 

and greater maximal photosynthetic rates 

relative to native plants under increased CO2, 

but definitive evidence of a general benefit of 

CO2 enrichment to invasive plants over natives 

has not emerged (Dukes and Mooney 1999). 

Nonetheless, invasive plants in general may 

better tolerate a wider range of environmental 

conditions and may be more successful in a 

warming world because they can migrate and 

establish in new sites more rapidly than native 

plants, and they are not usually limited by pollinators or seed dispersers (Vila et al, in press, 

accepted).

Finally, it is critical to recognize that other 

elements of climate change (e.g., nitrogen deposition, land conversion) will play significant 

roles in the success of invasive plants in the 

future, either alone or under elevated CO2

(Vila et. al., in press, accepted). For example, 

several studies have brought to light the role of 

increasing nitrogen availability and the success 

of invasive grass species (e.g., Huenneke et al. 

1990; Brooks 2003). Disturbance at both global 

and local scales has been shown to be an important factor in facilitating species invasions 

(e.g., Sher and Hyatt 1999; Mooney and Hobbs 

2001; D’Antonio and Meyerson 2002), and 

land conversion that occurred more than 100 

years ago may play a role in current invasions 

(Von Holle and Motzkin 2007). Recent work 

by Hierro et al. (2006), which compared the 

effects of disturbance on Centaurea solstitialis

in its native and introduced ranges, suggests 

that disturbance alone does not fully explain 

invasion success. Instead, it appears that, for C. 

solstitialis, it is the combination of disturbance 

and escape from soil pathogens in the native 

range that has encouraged invasion.

5.6 Particularly Sensitive

Systems

5.6.1 Impacts of Climate Change on

Montane Ecosystems

Temperate montane ecosystems are characterized by cooler temperatures and often increased 

precipitation compared to surrounding lowlands. Consequently, much of that precipitation

falls in the form of snow, which serves to insulate the ground from freezing air temperatures, 

stores water that will be released as the snow 

melts during the following growing season, and 

triggers vertical migration by animal species 

that cannot survive in deep snow. Changes in 

historical patterns of snowfall and snowpack 

are predicted as a consequence of global climate

change, in part due to changes in spatial patterns 

of precipitation, and in part due to the warming 

that will result in more precipitation falling as 

rain rather than snow (Beniston and Fox 1996; 

MacCracken et al. 2001). Areas that historically 

have most of their annual precipitation as snow 

are now seeing more of it as rain; documentation of this trend comes from the Sierra Nevada 

Mountains, where Johnson found from analysis 

of a 28-year dataset (Johnson 1998) that below 

2400 meters, less snow is accumulating and 

it is melting earlier. Diaz et al. (2003) (Figure 

5.5) also reported that all the major continental 

mountain chains exhibit upward shifts in the 

height of the freezing level surface over the past 

three to five decades.

Increased variation in precipitation and temperatures is also predicted by climate change 

models, and Johnson (1998) also found that 

“Higher elevations exhibit greater variability, 

with most stations accumulating more snow 

and melting earlier. This could be the result 

of warmer air masses having higher moisture 

contents.”
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In addition to the influences of global climate 

change, which could affect both precipitation 

and temperature, regional effects can be important. For example, in the Colorado Rocky 

Mountains there are significant ENSO and PDO 

effects on winter precipitation. ENSO has also 

been shown to effect changes in freezing level 

in the American Cordillera (Diaz et al. 2003). 

Of course, all downstream water flows with 

headwaters in mountain areas are also affected 

by the variation in both timing and quantity of

snowmelt (e.g., Karamouz and Zahraie 2004).

These environmental changes are resulting in 

the disappearance of glaciers in most montane 

areas around the world. The changes in patterns and abundance of melt water from these 

glaciers have significant implications for the 

sixth of the world’s population that is dependent 

upon glaciers and melting snowpack for water 

supplies (Barnett et al. 2005). Plant and animal communities are also affected as glaciers 

recede, exposing new terrain for colonization 

in an ongoing process of succession (e.g., for 

Figure 5.5 Linear trends in near surface air temperatue for 5 different 

mountainous regions, based on the NCEP/NCAR Reanalysis data set. Top 

panel is for 1958–2000, lower panel for the period 1974–1998. From 

Diaz et al. 2003.

0.6

0.4

0.2

0

-0.2

-0.4

-0.6

0.6

0.8

0.4

0.2

0

-0.2

-0.4

-0.6

-0.8

1960 1965 1970 1975 1980 1985 1990 1995 2000

Year

Degrees Celsius Degrees Celsius

1960 1965 1970 1975 1980 1985 1990 1995 2000

Year

East Africa

Mediterranean

Caucasus

Himalayas

Cordillera

spider communities, see Gobbi et al. 2006). 

One group of organisms whose reproductive 

phenology is closely tied to snowmelt is amphibians, for which this environmental cue is 

apparently more important than temperature 

(Corn 2003). Hibernating and migratory species that reproduce at high elevations during 

the summer are also being affected by the 

ongoing environmental changes. For example, 

marmots are emerging a few weeks earlier than 

they used to in the Colorado Rocky Mountains, 

and robins are arriving from wintering grounds 

weeks earlier in the same habitats (Inouye et 

al. 2000). Species such as deer, bighorn sheep, 

and elk, which move to lower elevations for 

the winter, may also be affected by changing 

temporal patterns of snowpack formation and 

disappearance.

The annual disappearance of snowpack is the 

environmental cue that marks the beginning of 

the growing season in most montane environments. Flowering phenology has been advancing 

in these habitats (Inouye and Wielgolaski 2003) 

as well as in others at lower altitudes, mirroring 

what is going on at higher latitudes (Wielgolaski and Inouye 2003). There is a very strong 

correlation between the timing of snowmelt, 

which integrates snowpack depth and spring air 

temperatures, and the beginning of flowering by 

wildflowers in the Colorado Rocky Mountains 

(e.g., Inouye et al. 2002; Inouye et al. 2003). For 

some wildflowers there is also a strong correlation between the depth of snowpack during the 

previous winter and the abundance of flowers 

produced (Inouye et al. 2002; Saavedra et al. 

2003). The abundance of flowers can have 

effects on a variety of consumers, including 

pollinators (Inouye et al. 1991), herbivores, 

seed predators, and parasitoids, all of which are 

dependent on flowers, fruits, or seeds.

An unexpected consequence of earliersnowmelt

in the Rocky Mountains has been the increased 

frequency of frost damage to montane plants, including the loss of new growth on conifer trees, 

of fruits on some plants such as Erythronium 

grandiflorum (glacier lilies), and of flower buds 

of other wildflowers (e.g., Delphinium spp., 

Helianthella quinquenervis, etc.) (Inouye 2008). 

Although most of these species are long-lived 

perennials, as the number of years in which 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

frost damage has negative consequences on

recruitment increases, significant demographic 

consequences may result. These and other responses to the changing montane environment 

are predicted to result in loss of some species 

at lower elevations, and migration of others to 

higher elevations. Evidence that this is already 

happening comes from studies in both North 

America (at least on a latitudinal scale, Lesica 

and McCune 2004) and Europe (Grabherr et al. 

1994). It is predicted that some animal species 

may also respond by moving up in elevation, 

and preliminary evidence suggests that some 

bumble bee (Bombus) species in Colorado have 

moved as much as a couple of thousand feet 

over the past 30 years (J. Thomson, personal 

communication).

5.6.2 Arctic Sea-Ice Ecosystems

Sea ice seasonally covered as much as 

16,000,000 km2 of the Arctic Ocean before it 

began declining in the 1970s (Johannessen et al. 

1999; Serreze et al. 2007). For millennia, that 

ice has been integral to an ecosystem that provisions polar bears and the indigenous people. The 

ice also strongly influences the climate, oceanography, and biology of the Arctic Ocean and 

surrounding lands. Further, sea ice influences 

global climate in several ways, including via its 

high albedo and its role in atmospheric and oceanic circulation. In the past 10 years, the rate of 

decline in the areal extent of summer sea ice in 

the Arctic Ocean has accelerated, and evidence 

that the Arctic Ocean will be ice-free by 2050 is 

increasing (Stroeve et al. 2005, 2007; Overland 

and Wang 2007; Serreze et al. 2007; Comiso et 

al. 2008). Many organisms that depend on sea 

ice – ranging from ice algae to seals and polar 

bears – will diminish in number and may become extinct. Ecosystem changes already have 

been observed and are predicted to accelerate 

along with the rates of climate change. Many 

of the changes will not be readily obvious and 

may even counterintuitive. Here, we summarize 

expected changes and provide a few expected 

responses involving upper trophic levels that 

are thought to be illustrative.

At the base of the sea ice ecosystem are epontic 

algae adapted to very low light levels (Kühl 

et al. 2001; Thomas and Dieckmann 2002). 

Blooms of the those algae on the undersurface 

of the ice are the basis of a food web leading 

through zooplankton and fish to seals, whales, 

polar bears, and people. Sea ice also strongly 

influences winds and water temperature, both 

of which influence upwelling and other oceanographic phenomena whereby nutrient rich water 

is brought up to depths at which there is sufficient sunlight for phytoplankton to make use of 

those nutrients (Buckley et al. 1979; Alexander 

and Niebauer 1981; Legendre et al. 1992).

Among the more southerly and seasonally icecovered seas, the Bering Sea produces our nation’s largest commercial fish harvests as well 

as supports subsistence economies of Alaskan 

Natives. Ultimately, the fish populations depend 

on plankton blooms regulated by the extent and 

location of the ice edge in spring. Naturally, 

many other organisms, such as seabirds, seals, 

walruses, and whales, depend on primary production, mainly in the form of those plankton 

blooms. As Arctic sea ice continues to diminish, the location, timing, and species make-up 

of the blooms are changing in ways that appear to favor marked changes in community 

composition (Hunt et al. 2002; Grebmeier et al. 

2006). The spring melt of sea ice in the Bering 

Sea has long favored the delivery of organic 

material to a benthic community of bivalve 

mollusks, crustaceans, and other organisms. 

Those benthic organisms, in turn, are important 

food for walruses, gray whales, bearded seals, 

eider ducks, and many fish species. The earlier 

ice melts resulting from a warming climate, 

however, lead to later phytoplankton blooms 

that are largely consumed by zooplankton near 

the sea surface, vastly decreasing the amount 

of organic material reaching the benthos. The 

likely result will be a radically altered community favoring a different suite of upper level 

consumers. The subsistence and commercial 

harvests of fish and other marine organisms 

would also be altered.

Walruses (Odobenus rosmarus) feed on clams 

and other bottom-dwelling organisms (Fay 

1982). Over a nursing period of two or more 

years, the females alternate their time between 

attending a calf on the ice and diving to the bottom to feed themselves. The record ice retreats 

observed in recent summers extend northward 

of the continental shelf such that the ice is over 

An unexpected 

consequence of 

earlier snowmelt in 

the Rocky Mountains 

has been the 

increased frequency 

of frost damage to 

montane plants, 

including the loss 

of new growth on 

conifer trees, of 

fruits on some plants 

such as Erythronium 

grandiflorum 

(glacier lilies), and 

of flower buds of 

other wildflowers 

(e.g., Delphinium 

spp., Helianthella 

quinquenervis, etc.). 
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Chapter 5

water too deep for the female walruses to feed 

(Kelly 2001). The increased distance between 

habitat suitable for adult feeding and that 

suitable for nursing young is likely to reduce 

population productivity (Kelly 2001; Grebmeier 

et al. 2006).

The major prey of polar bears and an important 

resource to Arctic Natives, ringed seals (Pusa 

hispida) are vulnerable to decreases in the snow 

and ice cover on the Arctic Ocean (Stirling and 

Derocher 1993; Tynan and DeMaster 1997; 

Kelly 2001). Ringed seals give birth in snow 

caves excavated above breathing holes they 

maintain in the sea ice. The snow caves protect 

the pups from extreme cold (Taugbøl 1984) and, 

to a large extent, from predators (Lydersen and 

Smith 1989). As the climate warms, however, 

snow melt comes increasingly early in the Arctic (Stone et al. 2002; Belchansky et al. 2004), 

and the seals’ snow caves collapse before the 

pups are weaned (Kelly 2001; Kelly et al. 2006). 

The small pups are exposed without the snow 

cover and die of hypothermia in subsequent

cold periods (Stirling and Smith 2004). The 

prematurely exposed pups also are more vulnerable to predation by Arctic foxes, polar bears, 

gulls, and ravens (Lydersen and Smith 1989). 

Gulls and ravens are arriving increasingly 

early in the Arctic as springs become warmer, 

further increasing their potential to prey on the 

seal pups.

Polar bears (Figure 5.6) are apex predators of 

the sea ice ecosystem, and their dependence 

on ice-associated seals makes them vulnerable to reductions in sea ice. While polar bears 

began diverging from brown bears (Ursus 

arctos) 150,000 to 250,000 years ago (Cronin 

et al. 1991; Talbot and Shields 1996; Waits et 

al. 1998), their specialization as seal predators 

in the sea ice ecosystem apparently is more 

recent, dating to 20,000 to 40,000 years ago 

(Stanley 1979; Talbot and Shields 1996). The 

bears’ invasion of this novel environment was 

stimulated by an abundance of seals, which had 

colonized the region earlier in the Pleistocene 

(Deméré et al. 2003; Lister 2004). Adapting to 

the sea ice environment and a dependence on 

seals – especially ringed seals – exerted strong 

selection on the morphology, physiology, and 

behavior of polar bears.

The polar bear’s morphological adaptations to 

the sea ice environment include dense, white 

fur over most of the body (including between 

foot pads), with hollow guard hairs; short, 

highly curved claws; and dentition specialized 

for carnivory. Physiologically, polar bears are 

extremely well adapted to feed on a diet high in 

fat; store fat for later future energy needs; and 

enter and sustain periods of reduced metabolism 

whenever food is in short supply (Derocher et 

al. 1990; Atkinson and Ramsay 1995). Feeding 

success is strongly related to ice conditions; 

when stable ice is over productive shelf waters, 

polar bears can feed throughout the year on 

their primary prey, ringed seals (Stirling and 

McEwan 1975; Stirling and Smith 1975; Stirling 

and Archibald 1977; Amstrup and DeMaster 

1988; Amstrup et al. 2000). Less frequently,

they feed on other marine mammals (Smith 

1980, 1985; Calvert and Stirling 1990) and 

even more rarely on terrestrial foods (Lunn and 

Stirling 1985; Derocher et al. 1993). Polar bears 

exhibit the behavioral plasticity typical of toplevel predators, and they are adept at capturing 

seals from the ice (Stirling 1974; Stirling and 

Derocher 1993).

Today, an estimated 20,000 to 25,000 polar 

bears live in 19 apparently discrete populations 

distributed around the circumpolar Arctic (Polar Bear Specialists Group 2006). Their overall 

distribution largely matches that of ringed seals, 

which inhabit all seasonally ice-covered seas in 

the Northern Hemisphere (Scheffer 1958; King 

1983). Polar bears are not regularly found, however, in some of the marginal seas (e.g., the Okhotsk Sea) inhabited by ringed seals. The broad 

distribution of their seal prey is reflected in the 

home ranges of polar bears that, averaging over 

125,000 km2, are more than 200 times larger 

than the averages for terrestrial carnivores of 

similar size (Durner and Amstrup 1995; Ferguson et al. 1999). Most polar bear populations 

expand and contract their range seasonally with 

the distribution of sea ice, and they spend most 

of year on the ice (Stirling and Smith 1975; 

Garner et al. 1994). Most populations, however, retain their ancestral tie to the terrestrial 

environment for denning, although denning on 

the sea ice is common among the bears of the 

Beaufort and Chukchi seas (Harrington 1968; 

Stirling and Andriashek 1992; Amstrup and 

Whether the 

changes underway 

today will be 

survived by 

walruses, seals, 

polar bears, and 

other elements of 

he ecosystem will 

depend critically 

on the pace of 

change.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 5.6 Polar bear lounges near the Beaufort Sea, along Alaska’s coastline. 

Image by Susanne Miller, from the U.S. Fish & Wildlife Service’s digital library 

collection.

Gardner 1994; Messeir et al. 1994; Durner et al. 

2003). Dens on land and on ice are excavated 

in snow drifts, the stability and predictability 

of which are essential to cub survival (Blix and 

Lentfer 1979; Ramsay and Stirling 1988, 1990; 

Clarkson and Irish 1991).

The rapid rates of warming in the Arctic observed in recent decades and projected for at 

least the next century are dramatically reducing 

the snow and ice covers that provide denning 

and foraging habitat for polar bears (Overpeck 

et al. 1997; Serreze et al. 2000; Holland et al. 

2006; Stroeve et al. 2007). These changes to 

their environment will exert new, strong selection pressures on polar bears. Adaptive traits 

reflect selection by past environments, and 

the time needed to adapt to new environments 

depends on genetic diversity in populations, the 

intensity of selection, and the pace of change. 

Genetic diversity among polar bears is evident 

in the 19 putative populations, suggesting 

some scope for adaptation within the species 

as a whole even if some populations will be at 

greater risk than others. On the other hand, the 

nature of the environmental change affecting 

critical features of polar bears’ breeding and 

foraging habitats, and the rapid pace of change 

relative to the bears’ long generation time (circa 

15 years) do not favor successful adaptation.

The most obvious change to breeding habitats 

is the reduction in the snow cover on which 

successful denning depends (Blix and Lenter 

1979; Amstrup and Gardner 1994; Messier 

et al. 1994; Durner et al. 2003). Female polar 

bears hibernate for four to five months per year 

in snow dens in which they give birth to cubs, 

typically twins, each weighing just over 0.5 kg 

(Blix and Lentfer 1979). The small cubs depend 

on snow cover to maintain thermal neutrality. 

Whether it remains within the genetic scope of 

polar bears to revert to the ancestral habit of 

rearing in earthen dens is unknown.

Changes in the foraging habitat that will entail new selection pressures include seasonal 

mismatches between the energetic demands of 

reproduction and prey availability; changes in 

prey abundance; changes in access to prey; and 

changes in community structure. Emergence 

of female and young polar bears from dens 

in the spring coincides with the ringed seal’s 

birthing season, and the newly emerged bears 

depend on catching and consuming young seals 

to recover from months of fasting (Stirling 

and Øritsland 1995). That coincidence may be 

disrupted by changes in timing and duration of 

snow and ice cover. Such mismatches between 

reproductive cycles and food availability are 

increasingly recognized as a means by which 

animal populations are impacted by climate 

change (Stenseth and Mysterud 2002; Stenseth 

et al. 2002; Walther et al. 2002).

The polar bear’s ability to capture seals depends 

on the presence of ice (Stirling et al. 1999; 

Derocher et al. 2004). In that habitat, bears take 

advantage of the fact that seals must surface to 

breathe in limited openings in the ice cover. 

In the open ocean, however, bears lack a hunting platform, seals are not restricted in where 

they can surface, and successful predation is 

exceedingly rare (Furnell and Oolooyuk 1980). 

Only in ice-covered waters are bears regularly 

successful at hunting seals. When restricted 

to shorelines, bears feed little if at all, and terrestrial foods are thought to be of little significance to polar bears (Lunn and Stirling 1985; 

Ramsay and Hobson 1991; Stirling et al. 1999). 

Predation on reindeer observed in Svalbard, 

however, indicates that polar bears have some 

capacity to switch to alternate prey (Derocher 

et al. 2000).
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Seal and other prey populations also will be 

impacted by fundamental changes in the fate 

of primary production. For example, in the 

Bering and Chukchi seas, the reduction in sea 

ice cover alters the physical oceanography in 

ways that diminish carbon flow to the benthos 

and increase carbon recycling in pelagic communities (Grebmeier et al. 2006). The resultant 

shift in community structure will include higher 

trophic levels. The exact composition of future 

communities is not known, nor is it known 

how effectively polar bears might exploit those 

communities.

Recent modeling of reductions in sea ice cover 

and polar bear population dynamics yielded 

predictions of declines within the coming 

century that varied by population but overall 

totaled 66 percent of all polar bears (Amstrup 

et al. 2007). Some populations were predicted to 

be extinct by the middle of the current century. 

While population reductions seem inevitable 

given the polar bear’s adaptations to the sea ice 

environment (Derocher et al. 2004), quantitative predictions of declines are less certain as 

they necessarily depend on interpretations of 

data and professional judgments.

During previous climate warmings, polar bears 

apparently survived in unknown refuges that 

likely included some sea ice cover and access 

to seals. Within the coming century, however, 

the Arctic Ocean may be ice-free during summer (Overpeck et al. 2005), and the polar bear’s 

access to seals will be diminished (Stirling 

and Derocher 1993; Lunn and Stirling 2001; 

Derocher et al. 2004). As snow and ice covers 

decline, polar bears may respond adaptively 

to the new selection pressures or they may 

become extinct. Extinction could result from 

mortality outpacing production, competition 

in terrestrial habitats with brown bears, and/or 

from re-absorption into the brown bear genome. 

Crosses between polar bears and brown bears 

produce fertile offspring (Kowalska 1965), and 

a hybrid was recently documented in the wild. 

Extinction through hybridization has been 

documented in other mammals (Rhymer and 

Simberloff 1996).

Predicted further warming inevitably will entail 

major changes to the sea ice ecosystem. Some 

ice-adapted species will become extinct; others 

will adapt to new habitats. Whether the changes 

underway today will be survived by walruses, 

seals, polar bears, and other elements of the 

ecosystem will depend critically on the pace 

of change. Ecosystems have changed before; 

species have become extinct before. Critically 

important in our changing climate is the rapid 

rate of change. Biological adaptation occurs 

over multiple generations varying from minutes 

to many years depending on the species. The 

current rates of change in the sea ice ecosystem, 

however, are very steep relative to the long 

generation times of long-lived organisms such 

as seals, walruses, and polar bears.

5.7 Ecosystem Services and

Expectations for

Future Change

The Millennium Ecosystem Assessment (2005) 

is the most comprehensive scientific review of 

the status, trends, conditions, and potential futures for ecosystem services. It is international 

in coverage, although individual sections focus 

on regions, ecosystem types, and particular ecosystem services. The MEA categorized services 

as supporting, provisioning, regulating, and 

cultural (Figure 5.7). Some of these services are 

already traded in markets, e.g. the provision of 

food, wood, and fiber from both managed and 

unmanaged ecosystems, or the cultural services 

of providing recreational activities, which generate substantial revenue both within the United 

States and globally. The United States, for example, has a $112 billion international tourism 

market and domestic outdoor recreation market 

(World Trade Organization 2002; Southwick 

Associates 2006).

Other services, in particular many cultural 

services, regulating services, and supporting 

services are not priced, and therefore not traded 

in markets. A few, like provision of fresh water 

or carbon sequestration potential, are mostly not

traded in markets, but could be, and especially 

for carbon, there are many developing markets. 

In all cases, the recognition of a service provided by ecosystems is the recognition that they 

are producing or providing something of value 

to humans, and thus its value is shaped by the 

social dimensions and values of our societies 

as well as by physical and ecological factors 

(MEA 2005).
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 5.7 Categorization of ecosystem services, from MEA 2005.

An example of an ecosystem service that has an 

increasingly recognized value is that provided 

by pollinators. Part of this increased recognition is a consequence of the recent declines

in abundance that have been observed for 

some pollinators, particularly the introduced 

honey bee (Apis mellifera) (National Research 

Council 2006). The economic significance of 

pollination is underscored by the fact that about 

three-quarters of the world’s flowering plants

depend on pollinators, and that almost a third 

of the food that we consume results from their 

activity. The majority of pollinators are insects, 

whose distributions, phenology, and resources 

are all being affected by climate change (Inouye 

2007). For example, an ongoing study at the 

Rocky Mountain Biological Laboratory (Pyke, 

Thomson, Inouye, unpublished) has found evidence that some bumble bee species have moved 

up as much as a few thousand feet in elevation 

over the past 30 years. Unfortunately, with the 

exception of honey bees and butterflies, there 

are very few data available on the abundance 

and distribution of pollinators, so it has been 

difficult to assess their status and the changes 

that they may be undergoing (National Research 

Council 2006).

Biological diversity is recognized as providing an underpinning for all these services in a 

fundamental way. A major finding of the MEA 

from a global perspective was that 16 out of 24 

different ecosystems services that were analyzed were being used in ultimately unsustainable ways. While this finding was not specific 

to U.S. ecosystems, it does set a context for 

considering the consequences of documented

ecosystem changes for services.

A subsequent question is whether any such

changes in services can be reasonably attributed to climate change. The MEA evaluated 

the relative magnitudes and importance of a 

number of different direct drivers (Nelson et al. 

2006) for changes in ecosystems, and whether 

the importance of those drivers was likely to 

increase, decrease, or stay about the same over 

the next several decades. The conclusion was 

that although climate change was not currently 

the most important driver of change in many 

ecosystems, it was one of the only drivers whose 

importance was likely to continue to increase 

in all ecosystems over the next several decades 

(Figure 5.8).

5.8 Adequacy of Observing

Systems

One of the challenges of understanding changes 

in biological diversity related to variability and 

change in the physical climate system is the 

adequacy of the variety of monitoring programs

that exist for documenting those changes.

It is useful to think about such programs as 

falling into three general categories. The first 

is the collection of operational monitoring systems that are sponsored by federal agencies, 

conservation groups, state agencies, or groups 

of private citizens that are focused on particular 

taxa (e.g., the Breeding Bird Survey) or particular ecosystems (e.g., Coral Reef Watch). These 

tend to have been established for very particular 

purposes, such as for tracking the abundance 

of migratory songbirds, or the status and abundance of game populations within individual 

states, or the status and abundance of threatened 

and endangered species.
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Chapter 5

The second category of monitoring programs is 

those whose initial justification has been to investigate particular research problems, whether 

or not those are primarily oriented around biodiversity. For example, the existing Long-Term 

Ecological Research Sites (LTERs) are important for monitoring and understanding trends in 

biodiversity in representative U.S. biomes, although their original justification was oriented 

around understanding ecosystem functioning. 

The yet-to-be established National Ecological 

Observatory Network (NEON) would also 

fall into this category. NEON’s design for site 

locations samples both climate variability and 

ecological variability within the United States 

in a much more systematic way than ever before 

Figure 5.8 Relative changes in magnitude to ecosystem services caused by changes in habitat, climate, species 

invasion, over-exploitation, and pollution.

done for a long-term research network, so there 

are likely to be very powerful results that can 

come from network-wide analyses.

The third category of monitoring systems is 

those that offer the extensive spatial and variable temporal resolution of remotely sensed 

information from Earth-orbiting satellites. 

These are not always thought of as being part 

of the nation’s system for monitoring biological diversity, but in fact, they are an essential 

component of it. Remotely sensed data are the 

primary source of information on a national 

scale for documenting land-cover and landcover change across the United States, for example, and thus they are essential for tracking 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Figure 5.9 NASA budget for earth science research and applications demonstrations (1996–2012,

fixed 2006 dollars).

changes in perhaps the biggest single driver of 

changes in biodiversity, i.e. changes in habitat. 

Over the decades of the 1990s and 2000s, the 

remarkable profusion of Earth observation 

satellites has provided global coverage of 

many critical environmental parameters, from 

variability and trends in the length of growing 

season, to net primary productivity monitoring, 

to the occurrence of fires, to the collection of 

global imagery on 30-meter spatial resolution 

for more than a decade. Observational needs 

for biodiversity monitoring and research were 

recently reviewed by the International Global 

Observations of Land Panel, in a special report 

from a conference (IGOL 2006).

The National Research Council has recently 

released the first-ever Decadal Survey for Earth 

Science and Observations (NRC, 2007), which 

makes a comprehensive set of recommendations for future measurements and missions 

that would simultaneously enhance scientific 

progress, preserve essential data sets, and benefit a wide variety of potential applications. 

The report found that “the extraordinary U.S. 

foundation of global observations is at great 

risk. Between 2006 and the end of the decade, 

the number of operating missions will decrease 

dramatically, and the number of operating sensors and instruments on NASA spacecraft, most 

of which are well past their nominal lifetimes, 

will decrease by some 40 percent.”

Although there are lists of specifications for 

monitoring systems that would be relevant 

and important for recording changes in biodiversity associated with climate variability and 

change (e.g., IGOL 2007), at present there is no 

analysis in the literature that directly addresses 

the question of whether existing monitoring

systems are adequate. For the moment, there is

no viable option but to use existing systems for 

recording biodiversity changes, even if it means 

that the scientific community is attempting to 

use systems originally designed for alternate 

purposes.

The Government Accountability Office (2007) 

has documented extensively that one of the 

greatest perceived needs of federal land management agencies is for targeted monitoring 

systems that can aid them in responding to 

climate change. These agencies (e.g., U.S. Forest Service, National Park Service, Bureau of 

Land Management, NOAA, the U.S. Geological Survey) each face situations in which they 

recognize that they are already beginning to 

see the biological and ecological impacts of 

climate change on resources that they manage. 

GAO identified the improvement of monitoring capabilities to formulate effective adaptation and management responses as a priority. 

Remedying this situation was identified as a 

critical priority.

The Government 

Accountability 

Office (2007) 

has documented 

extensively that 

one of the greatest 

perceived needs 

of federal land 

management agencies 

is for targeted 

monitoring systems 

that can aid them in 

responding to climate 

change.
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Chapter 5

5.9 Major Findings

In this section, we list the major findings from 

each section of the chapter, by topic heading. 

We then draw some general conclusions about 

the observed and potential impacts of climate 

change on biological diversity, the relationships to ecosystem services, and the adequacy

of existing monitoring systems to document 

continuing change.

5.9.1 Growing Season and Phenology

•	 There is evidence indicating a significant

lengthening of the growing season and 

higher NPP in the higher latitudes of North 

America where temperature increases are 

relatively high.

•	 Over the last 19 years, global satellite data

indicate earlier onset of spring across the 

temperate latitudes by 10–14 days (Myneni, 

2001; Lucht, 2002), an increase in summer 

photosynthetic activity (normalized difference vegetation index satellite estimates) 

(Myneni 2001) and an increase in the amplitude of annual CO2 cycle (Keeling 1996), 

all of which are supported by climatological 

and field observations.

•	 Forest productivity, in contrast, which is generally limited by low temperature and short 

growing seasons in the higher latitudes and 

elevations, has been slowly increasing at less 

than 1 percent per decade (Boisvenue and 

Running 2006; Joos et al.2002; McKenzie 

2001; Caspersen et al. 2000).

•	 The exception to this pattern is in forested

regions that are subject to drought from 

climate warming, where growth rates have 

decreased since 1895 (McKenzie 2001). 

Recently, widespread mortality over 12,000 

km2 of lower elevational forest in the 

southwest United States demonstrates the 

impacts of increased temperature and the 

associated multiyear drought (Breshears et 

al. 2005) even as productivity at tree line 

had increased previously (Swetnam and 

Betancourt 1998).

•	 Disturbances created from the interaction

of drought, pests, diseases, and fire are projected to have increasing impacts on forests 

and their future distributions (IPPC 2007).

5.9.2 Biogeographical and

 Phenological Shifts

•	 Evidence from two meta-analyses (Root et 

al. 2003; Parmesan 2003) and a synthesis 

(Parmesan 2006) on species from a broad 

array of taxa suggests that there is a significant impact of recent climatic warming in 

the form of long-term, large-scale alteration 

of animal and plant populations.

•	 Movement of species in regions of North

America in response to climate warming is 

expected to result in shifts of species ranges 

poleward and upward along elevational gradients (Parmesan, 2006).

•	 In an analysis of 866 peer-reviewed papers

exploring the ecological consequences of

climate change, nearly 60 percent of the 1598 

species studied exhibited shifts in their distributions and/or phenologies over a 20- and 

140-year time frame {Parmesan 2003).

•	 Analyses of field-based phenological responses have reported shifts as great as 5.1 

days per decade (Root et al. 2003), with an 

average of 2.3 days per decade across all 

species (Parmesan and Yohe 2003).

5.9.3 Migratory Birds

•	 A climate change signature is apparent in the 

advancement of spring migration phenology 

(Root et al. 2003) but the indirect effects may 

be more important than the direct effects of 

climate in determining the impact on species 

persistence and diversity.

5.9.4 Butterflies

•	 The migration of butterflies in the spring is 

highly correlated with spring temperatures 

and with early springs. Researchers have 

documented many instances of earlier arrivals (26 of 35 species in the United Kingdom 

(Roy and Sparks 2000); 17 of 17 species 

in Spain, (Stefanescu 2004); and 16 of 23 

species in central California (Forister and 

Shapiro 2003).

•	 Butterflies are also exhibiting distributional

and/or range shifts in response to warming. 

Across all studies included in her synthesis, 

Parmesan (2006) found 30–75 percent of 
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

species had expanded northward, less than 

20 percent had contracted southward, and the 

remainder were stable (Parmesan 2006).

5.9.5 Coastal and Near Shore

Systems

•	 In the tropics there have been increasing 

coral bleaching and disease events and increasing storm intensity.

•	 In temperate regions there are demonstrated

range shifts in rocky intertidal organisms, 

coastal fisheries, and in marine fisheries as 

well, and possible alterations of ocean currents and upwelling sites.

5.9.6 Corals

•	 Corals and tropical regions where they live

are experiencing increasing water temperatures, increasing storm intensity (Emmanuel 

2005), and a reduction in pH (Ravens et al. 

2005), all while experiencing a host of other 

on-going challenges from development/tourism, unsustainable fishing and pollution. 

Acidification presents a persistent threat 

that is increasing in magnitude for shallow 

water corals and free-swimming calcifying 

organisms. 

•	 Corals in many tropical regions are experiencing substantial mortality from increasing 

water temperatures and intense storms, both 

of which could be exacerbated by a reduction 

in pH. Increases in ocean acidity are a direct 

consequence of increases in atmospheric

carbon dioxide. 

5.9.7 Marine Fisheries

•	 Large, basin-scale atmospheric pressure 

systems that drive basin-scale winds can 

suddenly shift their location and intensity at 

decadal time scales, with dramatic impacts 

on winds and ocean circulation patterns. 

Perhaps the greatest discovery of the past 10 

years is that these shifts also have powerful 

impacts on marine ecosystems.

•	 Examples of ecosystems impacts include

increased flow of oceanic water into the 

English Channel and North Sea resulting 

in a northward shift in the distribution of 

zooplankton. As a result, the zooplankton 

community became dominated by warm 

water species (Beaugrand, 2004) with concomitant changes in fish communities from 

one dominated by whiting (hake) to one 

dominated by sprat (similar to a herring).

•	 Similar (and drastic) ecosystem changes are

known for the Baltic Sea (Kenny and Mollman 2006), where drastic changes in both 

zooplankton and fish communities were 

observed. Cod were replaced by sprat and 

dominance in zooplankton switched from 

lipid-rich (and high bioenergetic content) 

species to lipid-poor species.

•	 Linkages between the NAO, zooplankton

and fisheries have also been described for 

the Northwest Atlantic, including waters off 

eastern Canada and the United States; Pershing and Green (2007) report a decrease in 

salinity, and an increase in biomass of small 

copepods (zooplankton).

5.9.8 Pests and Pathogens

•	 Evidence is beginning to accumulate that 

links the spread of pathogens to a warming 

climate. For example, the chytrid fungus 

(Batrachochytrium dendrobatidis) is a pathogen that is rapidly spreading worldwide, 

and decimating amphibian populations. 

A recent study by Pounds and colleagues 

(2006) showed that widespread amphibian 

extinction in the mountains of Costa Rica is 

positively linked to global climate change.

•	 To date, geographic range expansion of

pathogens related to warming temperatures 

have been the most easily detected (Harvell 

et al. 2002), perhaps most readily for arthropod-borne infectious disease (Daszak et al. 

2000). However, a recent literature review 

found additional evidence gathered through 

field and laboratory studies that support 

hypotheses that latitudinal shifts of vectors 

and diseases are occurring under warming 

temperatures.

5.9.9 Invasive Plants

•	 Projected increases in CO2 are expected to 

stimulate the growth of most plants species, and some invasive plants are expected 

to respond with greater growth rates than 

non-invasive plants. Some invasive plants 

may have higher growth rates and greater 
The U.S. Climate Change Science Program

180

Chapter 5

maximal photosynthetic rates relative to 

native plants under increased CO2, but 

definitive evidence of a general benefit of 

CO2 enrichment to invasive plants over natives has not emerged (Dukes and Mooney 

1999).

•	 Nonetheless, invasive plants in general may

better tolerate a wider range of environmental conditions and may be more successful in 

a warming world because they can migrate 

and establish in new sites more rapidly than 

native plants and they are not usually limited 

by pollinators or seed dispersers (Vila et al., 

in press, accepted).

•	 Finally, it is critical to recognize that other

elements of climate change (e.g., nitrogen 

deposition, land conversion) will play a significant role in the success of invasive plants 

in the future, either alone or under elevated 

CO2 (Vila et. al., in press, accepted).

5.9.10 Particularly Sensitive Systems

•	 One group of organisms whose reproductive phenology is closely tied to snowmelt 

is amphibians, for which this environmental 

cue is apparently more important than temperature.

•	 Hibernating and migratory species that

reproduce at high elevations during the 

summer are also being affected by the ongoing environmental changes. For example, 

marmots are emerging a few weeks earlier 

than they used to in the Colorado Rocky 

Mountains, and robins are arriving from 

wintering grounds weeks earlier in the same 

habitats. Species such as deer, bighorn sheep, 

and elk, which move to lower elevations for 

the winter, may also be affected by changing 

temporal patterns of snowpack formation 

and disappearance.

•	 There is a very strong correlation between

the timing of snowmelt, which integrates 

snowpack depth and spring air temperatures, 

and the beginning of flowering by wildflowers in the Colorado Rocky Mountains.

•	 An unexpected consequence of earlier

snowmelt in the Rocky Mountains has been 

increased frequency of frost damage to

montane plants, including the loss of new 

growth on conifer trees, of fruits on some 

plants such as Erythronium grandiflorum 

(glacier lilies), and of flower buds of other 

wildflowers (e.g., Delphinium spp., Helianthella quinquenervis, etc.) . Although most

of these species are long-lived perennials, as 

the number of years in which frost damage 

has negative consequences on recruitment

increases, significant demographic consequences may result.

5.9.11 Arctic Sea-Ice Ecosystems

•	 Today, an estimated 20,000–25,000 polar 

bears live in 19 apparently discrete populations distributed around the circumpolar 

Arctic (IUCN Polar Bear Specialists Group 

2005). Their overall distribution largely 

matches that of ringed seals, which inhabit all seasonally ice-covered seas in the 

northern hemisphere (Scheffer 1958; King 

1983), an area extending to approximately 

15,000,000 km2.

•	 Most polar bear populations expand and

contract their range seasonally with the 

distribution of sea ice, and they spend most 

of year on the ice (Stirling and Smith 1975; 

Garner et al. 1994).

•	 The rapid rates of warming in the Arctic

observed in recent decades and projected for 

at least the next century are dramatically reducing the snow and ice covers that provide 

denning and foraging habitat for polar bears 

(Roots 1989; Overpeck et al. 1997; Serreze 

et al. 2000; Stroeve et al. 2007).

•	 During previous climate warmings, polar

bears apparently survived in some unknown 

refuges. Whether they can withstand the 

more extreme warming ahead is doubtful 

(Stirling and Derocher 1993; Lunn and 

Stirling 2001).
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

5.10 Conclusions

Terrestrial and marine systems are already being demonstrably affected by climate change. 

This conclusion can be made with very high 

confidence. There are observable impacts of 

climate change on terrestrial ecosystems in 

North America including changes in the timing 

of growing season length, phenology, primary 

production, and species distributions and diversity. Some important effects on components of 

biological diversity have already been observed 

and have been increasingly well documented 

over the past several decades. This statement 

is true both for U.S. ecosystems, and ecosystems and biological resources around the world 

(IPCC 2007).

There is a family of other impacts and changes 

in biodiversity that are theoretically possible, 

and even probable (e.g., mismatches in phenologies between pollinators and flowering plants), 

but for which we do not yet have a substantial 

observational database. However, we cannot 

conclude that the lack of a complete observational database in these cases is evidence that 

they are not occurring – it is just as likely that 

it is simply a matter of insufficient numbers or 

lengths of observations.

It is difficult to pinpoint changes in ecosystem 

services that are specifically related to changes 

in biological diversity in the United States. The 

Millennium Ecosystem Assessment (2005) 

is the most recent, and most comprehensive, 

scientific assessment of the state of ecosystem services around the world, the drivers of 

changes in both ecosystems and services, the 

inherent tradeoffs among different types of 

ecosystem services, and what the prospects 

are for sustainable use of ecological resources. 

The MEA concludes that climate change is very 

likely to increase in importance as a driver for 

changes in biodiversity over the next several 

decades, although for most ecosystems it is 

not currently the largest driver of change. But 

a specific assessment of changes in ecosystem 

services for the United States as a consequence

of changes in climate or other drivers of change 

has not been done.

We can think of the monitoring systems that 

have been used to evaluate the relationship 

between changes in the physical climate system and biological diversity as having three 

components.

•	 There is a plethora of species-specific or

ecosystem-specific monitoring systems, 

variously sponsored by the U.S. federal 

agencies, state agencies, conservation organizations, and other private organizations. 

However, in very few cases were these 

monitoring systems established with climate 

variability and climate change in mind.

•	 Augmenting the monitoring systems that

make routine measurements is a set of more 

specific research activities that have been 

designed to create time-series of population 

data and associated climatic and environmental data.

•	 The third component is spatially extensive

observations derived from remotely sensed 

data. Some of these satellite data are primarily focused on land-cover, and thus are 

a good indicator of the major single driver 

of changes in biodiversity patterns. Others 

produce estimates of NPP and changes in the 

growing season, and thus reflect functional 

changes in ecosystems. However, similarly 

to the in situ monitoring networks, the future 

of space-based observations is not assured. 

The NRC (2007) has recently released a 

major survey of data and mission needs for 

the Earth sciences to address this issue, so 

we will not pursue it further here.

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

183

6 Water Resources

Lead Author: D.P. Lettenmaier

Contributing Authors: D. Major, L. Poff, S. Running

CHAPTER

Synthesis

Lead Author: D. Schimel, A.C. Janetos, P. Backlund

Contributing Authors: J. Hatfield, D.P. Lettenmaier, M.G. Ryan

6.1 Introduction

The preceding chapters have focused on the 

observed and potential impacts of climate variability and change on U.S. agriculture, land 

resources, water resources, and biodiversity. 

This section synthesizes information from those 

sectoral chaptersto address a series of questions

that were posed by the CCSP agencies in the 

prospectus for this report and formulate a set of 

overarching conclusions.

6.2 Key Questions and 

Answers

CCSP Question: What factors influencing 

agriculture, land resources, water resources, 

and biodiversity in the United States are sensitive to climate and climate change?

Climate change affects average temperatures 

and temperature extremes, timing and geographical patterns of precipitation; snowmelt, 

runoff, evaporation and soil moisture; the frequency of disturbances, such as drought, insect

and disease outbreaks, severe storms, and forest 

fires; atmospheric composition and air quality,

and patterns of human settlement and land use 

change. Thus, climate change leads to myriad 

direct and indirect effects on U.S. ecosystems. 

Warming temperatures have led to effects as 

diverse as altered timing of bird migrations, 

increased evaporation and longer growing 

seasons for wild and domestic plant species. 

Increased temperatures often lead to a complex 

mix of effects. Warmer summer temperatures 

in the western U.S. have led to longer forest 

growing seasons, but have also increased summer drought stress, increased vulnerability to 

insect pests and increased fire hazard. Changes 

to precipitation and the size of storm events 

affect plant-available moisture, snowpack and 

snowmelt, streamflow, flood hazard, and water 

quality.

Further Details: The direct effects of changes 

to air temperature and precipitation are relatively 

well understood, though some uncertainties 

remain. This report emphasizes that a second 

class of climate changes are also very important. Changes to growing season length are 

now documented across most of the country 

and affect crops, snowmelt and runoff, productivity, and vulnerability to insect pests. Earlier 

warming has profound effects, ranging from 

changes to horticultural systems to expansion 

of the mountain pine beetleís range. Changes to 

humidity, cloudiness, and radiation may reflect 

both the effect of anthropogenic aerosols and 

the global hydrological systemís response to 

warming at the surface, humidity, and, hence, 

evaporation. Since plants and, in some cases, 

disease organisms are very sensitive to the 

near-surface humidity and radiation environment, this is emerging as an important ìhiddenî

global change. Finally, changes to temperature 

... climate change 

leads to myriad 

direct and indirect 

effects on U.S. 

ecosystems.
The U.S. Climate Change Science Program

184

Synthesis

and water are hard to separate. Increasing temperatures can increase evapotranspiration and 

reduce the growing season by depleting soil 

moisture sooner, reduce streamflow and degrade 

water quality, and even change boundary layer

humidity.

Disturbance (such as drought, storms, insect outbreaks, grazing, and fire) is part of the ecological history of most ecosystems and influences 

ecological communities and landscapes. Climate 

affects the timing, magnitude, and frequency of

many of these disturbances, and a changing climate will bring changes in disturbance regimes 

to forests and arid lands. Ecosystems can take 

from decades to centuries to re-establish after a 

disturbance. Both human-induced and natural 

disturbances shape ecosystems by influencing 

species composition, structure, and function 

(productivity, water yield, erosion, carbon storage, and susceptibility to future disturbance). 

Disturbances and changes to the frequency or

type of disturbance present challenges to resource managers. Many disturbances command 

quick action, public attention, and resources.

Climate and air quality–chemical climate–also

interact. Nitrogen deposition has major chemical 

effects in ecosystems. It can act as a fertilizer 

increasing productivity, but can also contribute 

to eutrophication. High levels of deposition 

have been associated with loss of species diversity and increased vulnerability to invasion, 

and there is some evidence that climate change 

exacerbates these effects. On the other side of 

the ledger, increases in atmospheric CO2 and 

nitrogen availability can increase crop yields if 

soil water is available.

Climate change can also interact with socioeconomic factors. For example, how crop responses 

to changing climate are managed can depend on 

the relative demand and price of different commodities. Climate change mitigation practices, 

such as the promotion of biofuel crops, can also 

have a major impact on the agricultural system 

by increasing the demand and prices for some 

crops.

CCSP Question: How could changes in climate exacerbate or ameliorate stresses on 

agriculture, land resources, water resources, 

and biodiversity? What are the indicators of 

these stresses?

Ecosystems and their services (land and water 

resources, agriculture, biodiversity) experience a 

wide range of stresses, including effects of pests 

and pathogens, invasive species, air pollution, 

extreme events and natural disturbances such 

as wildfire and flood. Climate change can cause 

or exacerbate direct stress through high temperatures, reduced water availability, and altered 

frequency of extreme events and severe storms.

Climate change can also modify the frequency

and severity of other stresses. For example, 

increased minimum temperatures and warmer 

springs extend the range and lifetime of many 

pests that stress trees and cops. Higher temperatures and/or decreased precipitation increase 

drought stress on wild and crop plants, fruit and 

nut trees, animals and humans. Reduced water 

availability can lead to increased withdrawals 

from rivers, reservoirs, and groundwater, with 

consequent effects on water quality, stream

ecosystems, and human health.

Further Details: Changes to precipitation 

frequency and intensity can have major effects.

More intense storms lead to increased soil erosion, flooding, and decreased water quality (by

transporting more pollutants into water bodies 

through runoff or leaching through soil layers), 

with major consequences for life and property. Changing timing, intensity and amount 

of precipitation can reduce water availability 

or the timing of water availability, potentially 

increasing competition between biological and 

consumptive water use at critical times. Flushing 

of pollutants into water bodies or concentration 

of contaminants during low-flow intervals can 

increase the negative consequences of effects

of other stresses, such as those resulting from 

development, land use intensification, and 

fertilization.

Climate change may also ameliorate stress. 

Carbon dioxide “fertilization,” increased 

growing-season length, and increased rainfall 

may increase productivity of some crops and 

forests, increase carbon storage in forests, and 

Climate change 

may also 

ameliorate stress. 

Carbon dioxide 

“fertilization,” 

increased growingseason length, and 

increased rainfall 

may increase 

productivity of some 

crops and forests, 

increase carbon 

storage in forests, 

and reduce water 

stress in arid land 

and grazing land 

ecosystems.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

reduce water stress in arid land and grazing land 

ecosystems. Increased minimum temperatures 

during winter can reduce winter mortality in 

crops and wild plants and reduce low-temperature stresses on livestock. Increased rainfall can 

increase groundwater recharge, increase water 

levels in lakes and reservoirs, and flow levels in 

rivers. Increased river levels tend to reduce water temperatures and, other things being equal,

can help limit the warming of water that might 

otherwise occur.

Indicators of climate change-related stress are 

incredibly diverse. Even a short list includes 

symptoms of temperature and water stress, such 

as plant and animal mortality, reduced productivity, reduced soil moisture and streamflow, 

increased eutrophication and reduced water 

quality, and human heat stress. Indicators of

stress can also include changes in species ranges, 

occurrence and abundance of temperature- or 

moisture-sensitive invasive species and pest/

pathogen organisms, and altered mortality and 

morbidity from climate-sensitive pests and 

pathogens. Many stresses are tied to changes in 

seasonality. Early warning indicators include 

timing of snowmelt and runoff, as early snowmelt has been related to increased summer-time 

water stress, leading to reduced plant growth, 

and increased wildfire and insect damage in 

the western U.S. Phenology can provide warning of stresses in many ways. Changes to crop 

phenology may presage later problems in yield 

or vulnerability to damage, changes to animal 

phenology (for example, timing of breeding) 

may come in advance of reduced breeding success and long-term population declines. Changes 

in the abundance of certain species, which 

may be invasive, rare, or merely indicative of 

changes, can provide warning of stress. For 

example, some C4 plants may be indicative of 

temperature or water stress, while other species 

reflect changes to nitrogen availability. Changes 

to the timing of animal migration may indicate 

certain types of stress, although some migration 

behavior also responds to opportunity (e.g., food 

supply or habitat availability).

CCSP Question: What current and potential 

observation systems could be used to monitor 

these indicators?

A wide range of observing systems within 

the United States provides information on 

environmental stress and ecological responses. 

Key systems include National Aeronautics and 

Space Administration (NASA) research satellites, operational satellites and ground based 

observing networks from the National Oceanic 

and Atmospheric Administration (NOAA) in 

the Department of Commerce, USDA forest 

and agricultural survey and inventory systems, 

Department of Interior/U.S. Geological Survey 

(USGS) stream gauge networks, Environmental 

Protection Agency (EPA) and state-supported 

water quality observing systems, the Department

of Energy (DOE) Ameriflux network, and the 

LTER network and the proposed National Ecological Observing Network (NEON) sponsored 

by the National Science Foundation (NSF). 

However, many key biological and physical 

indicators are not currently monitored, are monitored haphazardly or with incomplete spatial 

coverage, or are monitored only in some regions. 

In addition, the information from these disparate 

networks is not well integrated. Almost all of the 

networks were originally instituted for specific 

purposes unrelated to climate change, and are 

challenged by adapting to new questions.

Climate change presents new challenges for 

operational management. Understanding climate 

impacts requires both monitoring many aspects

of climate and a wide range of biological and 

physical responses. Understanding climate 

change impacts in the context of multiple 

stresses and forecasting future services requires

an integrated analysis approach. Beyond the 

problems of integrating the data sets, the nation 

has limited operational capability for integrated 

ecological monitoring, analyses and forecasting. 

A few centers exist, aimed at specific questions

and/or regions, but no coordinating agency or 

center has the mission to conduct integrated 

environmental analysis and assessment by 

pulling this information together. Operational 

weather and climate forecasting provides an 

analogy. Weather-relevant observations are 

collected in many ways, ranging from surface 

observations through radiosondes to operational 

and research satellites. These data are used as 
The U.S. Climate Change Science Program

186

Synthesis

the basis for analysis, understanding, and forecasting of weather through highly integrative 

analyses blending data and models in a handful 

of university, federal and private centers. This 

activity requires substantial infrastructure to

carry out operationally and depends on multiagency federal, university and private sector research for continual improvement. By contrast, 

no such integrative analysis of comprehensive 

ecological information is carried out, although 

the scientific understanding and societal needs 

have probably reached the level where an integrative and operational approach is both feasible 

and desirable.

Further Details: Operational and research 

satellite remote sensing provides a critical capability. Satellite observations have been used to 

detect a huge range of stresses, including water 

stress (directly and via changes to productivity), invasive species, effects of air pollution, 

changing land use, wildfire, spread of insect 

pests, and changes to seasonality. The latter is 

crucial, as much of what we know about changing growing season length comes from satellite 

observations. Changing growing seasons and 

phenology are crucial indicators of climate and 

climate stress on ecosystems. Aircraft remote 

sensing complements satellite remote sensing, 

and provides higher resolution and, in some 

cases, additional sensor types that are useful in 

monitoring ecosystems. Remote sensing also 

provides essential spatial context for site-based 

measurements, that, when used in the appropriate analysis framework, allows the results of 

local studies to be applied over regions large 

enough to be useful in management.

Ground-based measurements, such as USDA 

forest and agricultural surveys ,provide regular 

information on productivity of forest, rangeland, and crop ecosystems, stratified by region 

and crop type. Somewhat parallel information 

is reported on diseases, pathogens, and other 

disturbances, such as wind and wildfire damage. 

Current systems for monitoring productivity are 

generally more comprehensive and detailed than 

surveys of disturbance and damage. Agricultural 

systems are monitored much more frequently

than are forest ecosystems, due to differences 

in both the ecological and economic aspects of 

the two systems.

Climate stress itself is monitored in a number 

of ways. NOAA operates several types of 

observing networks for weather and climate, 

providing detailed information on temperature 

and precipitation, somewhat less highly resolved 

information on humidity and incoming solar 

resolution, and additional key data products, 

such as drought indices and forecasts, and 

flood forecasts and analyses. DOE’s ARM 

network provides key process information on 

some atmospheric processes affecting surface 

radiation balance, but at a limited number of 

sites. The USDA SNOTEL network provides 

partial coverage of snowfall and snowmelt in 

high elevation areas, though many of the highest 

and snowiest mountain ranges have sparse coverage. Several even more detailed meteorological networks have been developed, such as the 

Oklahoma Mesonet, which provide dense spatial 

coverage, and some additional variables.

Broad purpose climate and weather networks are 

complemented by more specialized networks. 

For example, the Ameriflux network focuses 

on measuring carbon uptake by ecosystems using micrometeorological techniques, and also

provides very detailed measurements of the 

local microclimate. The National Atmospheric 

Deposition Network monitors deposition of 

nitrogen and other compounds in rainwater 

across the continent, while several sparser 

networks monitor dry deposition. Ozone is 

extensively monitored by the Environmental 

Protection Agency, though rural sites are sparse 

compared to urban because of the health impacts 

of ozone. The impact of ozone on vegetation, 

though believed to be significant, is less well 

observed. Water resources are monitored as 

well. Streamflow is best observed through the 

USGS networks of stream gauges. The number 

of watersheds, of widely varying scale, and the 

intensity of water use in the United States make 

monitoring in-stream water extremely complicated. Establishing basic trends thus requires

very careful analysis. Lake and reservoir levels 

are fairly well measured. Groundwater, though 

critical for agricultural and urban water use 

in many areas, remains poorly observed and 

understood, and very few observations of soil 

moisture exist.

In addition to observing networks developed for 

operational decision making, several important 

Broad purpose 

climate and 

weather 

networks are 

complemented 

by more 

specialized 

networks.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

research networks have been established. The 

Ameriflux network was described above. The 

LTER network spans the United States, and 

includes polar and oceanic sites as well. LTER 

provides understanding of critical processes, 

including processes that play out over many 

years, at sites in a huge range of environments, 

including urban sites. While the LTER network 

does not emphasize standardized measurements 

(but rather addresses a core set of issues, using 

site-adapted methods), the proposed new NEON 

program will implement a set of standardized 

ecological sensors and protocols across the 

county.

Because climate change is just one of the 

multiple stresses affecting ecosystems, the 

fact that the existing observing systems are at 

best loosely coordinated is a major limitation. 

Interoperability of data remains an issue, despite efforts in standardization and metadata, 

and co-location of observations of drivers and 

responses to change occurs only haphazardly. 

This contributes to the difficulties discussed 

below of quantifying the relative contributions

of climate change and other stressors.

CCSP Question: Can observation systems 

detect changes in agriculture, land resources, 

water resources, and biodiversity that are 

caused by climate change, as opposed to being 

driven by other causal activities?

In general, the current suite of U.S. observing 

systems provides a reasonable overall ability 

to monitor ecosystem change and health in the 

United States, but neither the observing systems 

or the current state of scientific understanding 

are adequate to rigorously quantify climate

contributions to ecological change and separate 

these from other influences. It is very difficult, 

and in most cases, not practically feasible, to 

quantify the relative influences of individual

stresses, including climate change, through 

observations alone.

In the case of agriculture, monitoring systems 

for measuring long-term response of agricultural 

lands are numerous, but integration across these 

systems is limited. In addition, at present, there 

are no easy and reliable means to accurately 

ascertain the mineral and carbon state of agricultural lands, particularly over large areas.

For land resources, current observing systems 

are very likely inadequate to separate the effects

of changes in climate from other effects. There is 

no coordinated national network for monitoring 

changes associated with disturbance (except for 

forest fires) and alteration of land cover and land 

use. Attempts to date lack spatial or temporal 

resolution, or the necessary supporting ground 

truth measurements, to themselves adequately

distinguish climate change influences. Separating the effects of climate change from other 

impacts would require a broad network of indicators, coupled with a network of controlled 

experimental manipulations.

Essentially no aspect of the current hydrologic 

observing system was designed specifically for 

purposes of detecting climate change or its effects on water resources. Many of the existing 

systems are technologically obsolete, are designed to achieve specific, often non-compatible 

management accounting goals, and/or their 

operational and maintenance structures allow for 

significant data collection gaps. As a result, the 

data is fragmented, poorly integrated, and very 

likely unable to meet the predictive challenges 

of a rapidly changing climate.

In the case of biodiversity, there is a collection 

of operational monitoring systems that are sponsored by federal agencies, conservation groups, 

state agencies, or groups of private citizens that 

are focused on particular taxa (e.g. the Breeding Bird Survey), or on particular ecosystems 

(e.g. Coral Reef Watch), or even particular 

phenomena (e.g. the National Phenology Network). These tend to have been established for 

very particular purposes, e.g. for tracking the 

abundance of migratory songbirds, or the status and abundance of game populations within 

individual states, or the status and abundance of 

threatened and endangered species. There is a 

second category of monitoring programs whose 

initial justification has been to investigate particular research problems, whether or not those are 

primarily oriented around biodiversity. The third 

category of monitoring systems is those that offer the extensive spatial and variable temporal 

resolution of remotely sensed information from 

Earth-orbiting satellites. None of these existing 

monitoring systems are likely to be completely 

adequate for monitoring changesin biodiversity

associated with climate variability and change. 
The U.S. Climate Change Science Program

188

Synthesis

Although there are lists of specifications for 

monitoring systems that would be relevant and 

important for this purpose (e.g. IGOL 2007), 

there is at present no analysis in the literature 

that has addressed this question directly.

So for the moment, there is no viable alternative 

to using the existing systems for identifying 

climate change and its impacts on U.S. agriculture, land resources, water resources, and biodiversity, even though these systems were not 

originally designed for this purpose. There has 

obviously been some considerable success so far 

in doing so, but there is limited confidence that 

the existing systems provide a true early warning 

system capable of identifying potential impacts 

in advance. The authors of this report also have 

very limited confidence in the ability of current 

observation and monitoring systems to provide 

the information needed to evaluate the effectiveness of actions that are taken to mitigate or adapt 

to climate change impacts. Furthermore, we 

emphasize that improvements in observations 

and monitoring of ecosystems, while desirable, 

are not sufficient by themselves for increasing 

our understanding of climate change impacts. 

Experiments that directly manipulate climate 

and observe impacts are critical for developing 

more detailed information on the interactions 

of climate and ecosystems, attributing impacts 

to climate, differentiating climate impacts from 

other stresses, and designing and evaluating response strategies. Institutional support for such 

experiments is a concern.

Further Details: One of the great challenges 

of understanding climate change impacts is that 

these changes are superimposed on an already 

rapidly changing world. Ecosystems across the 

United States are subject to a wide variety of 

stresses, most of which inevitably act on those 

systems simultaneously. It is rare in these cases 

for particular responses of ecosystems to be 

diagnostic of any individual stress – ecosystemlevel phenomena, such as reductions in net 

primary productivity, for example, occur in 

response to many different stresses. Changes 

in migration patterns, timing, and abundances 

of bird and/or butterfly species interact with 

changes in habitat and food supplies.

In some cases, effects due to climate variability 

and change can be quite different from those

expected from other causes. For example, the 

upward or northward movements of treeline in 

montane and Arctic environments are almost 

certainly driven by climate, as no other driver 

of change is implicated. Other changes, such 

as those in wildfire behavior, are influenced by 

climate, patterns of historical land management, 

and current management and suppression efforts. Disentangling these influences is difficult. 

Some changes are so synergistic that our current 

scientific understanding cannot separate them 

solely by observations. For example, photosynthesis is strongly and interactively controlled by 

levels of nitrogen, water availability, temperature, and humidity. In areas where these are all 

changing, estimating quantitatively the effects

of, say, temperature alone is all but impossible. 

In regions of changing climate, separating effects of climate trends from other influencing 

factors with regard to biodiversity and species 

invasions is very challenging, and requires detailed biological knowledge, as well as climate, 

land use, and species data.

Separating climate effects from other environmental stresses is difficult but in some cases feasible. For example, when detailed water budgets 

exist, the effects of land use, climate change and 

consumptive use on water levels can be calculated. While climate effects can be difficult to 

quantify on small scales, sometimes, regional

effects can be separated. For example, regional 

trends in productivity, estimated using satellite methods, can often be assigned to regional 

trends in climate versus land use, although on 

any individual small-scale plot, climate may be 

primary or secondary. In other cases, scientific 

understanding is sufficiently robust that models 

in conjunction with observations can be used 

to estimate climate effects. This approach has 

been used to identify climate effects on water 

resources and crop productivity, and could be 

extended to forests and other ecological systems 

as well.

While it is not yet possible to precisely determine and separate the effects of individual 

stresses, it is feasible to quantify the actual

changes in ecosystems and their individual 

species, in many cases through observations. 

There are many monitoring systems and reporting efforts set up specifically to do this, 

and while each may individually have gaps and 

So for the moment, 

there is no viable 

alternative to using 

the existing systems 

for identifying climate 

change and its impacts 

on U.S. agriculture, 

land resources, 

water resources, and 

biodiversity, even 

though these systems 

were not originally 

designed for this 

purpose.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

weaknesses, there are many opportunities for 

improvement. This report identifies a number 

of opportunities, and many other documents 

have addressed the nationís need for enhanced 

ecological observations as well. Many networks 

exist, but for the integrative challenges of understanding and quantifying climate change

impacts, they provide limited capability. Most 

existing networks are fairly specialized, and at 

any given measurement site, only one or a few 

variables may be measured. The ongoing trend 

of more co-location of sensors, and development 

of new, much more integrative networks (such 

as NEON and the NOAA Climate Reference 

Network) is positive. By measuring drivers of 

change and ecological responses, the processes 

of change can be understood and quantified, and

the ability to separate and ultimately forecast 

climate change enhanced.

6.3 Designing Systems to 

Monitor Climate 

Change Impacts

This assessment makes clear that there are many 

changes and impacts in many US ecosystems 

that are being driven by changes in the physical climate system, including both long-term 

changes and climate variability. Documentation 

of such changes has largely been a function of 

assessing results from individual studies that 

have been creative in their use of information 

from existing monitoring systems, all of which 

were originally designed for other purposes. But 

because the observed changes are proving to be 

both large and rapid, and because management 

agencies and organizations are ill-prepared to 

cope with such changes (GAO 2007), there is 

a growing need to develop strategies for adapting to ecological changes, and for managing 

ecosystems to ameliorate climate impacts. In 

addition, because changes in climate and subsequent impacts in ecosystems are very likely

to continue to occur, adaptive management 

strategies for adapting to change are going to be 

quite important (GAO 2007). Observation and

monitoring systems, therefore, must be able to 

support analyses that would contribute to this 

management challenge, i.e. adapting to change, 

documenting the rapidity of ecological changes 

so that management strategies can be adjusted, 

and most importantly, forecasting when potential thresholds of change might occur, and how 

rapidly changes will occur. Ecological forecasting is one of the specific goals of international 

programs such as Global Earth Observation 

System of Systems (GEOSS), but exactly how 

such programs will fulfill these goals is still 

being developed.

In order to fulfill the goal of providing observations for responding the climate change, there 

are at least five issues that such systems must 

be able to address.

Monitoring changes in overall status, regardless of cause: This need has been most cogently 

articulated by the work of the NRC (NRC 2000 

[Orians report]), and the Heinz Center on indicators of status of US ecosystems (Heinz Center 

2004). The argument is straightforward; there is 

both scientific and societal value to the US to 

know the extent, status, and condition of its own 

natural resources and ecosystems. Both the NRC 

and the Heinz Center present recommendations 

for specific indicators that either derived from 

scientific concerns (NRC) or from a broader, 

stake-holder driven process (Heinz Center). 

In either case, no attempt is made to attribute 

changes in the indicators to particular stresses 

strictly through use of the monitoring data. Both 

recognize, however, that such analyses are necessary for both scientific and policy purposes. 

The system of indicators is ultimately dependent 

on existing monitoring systems, most of which 

have been put in place for other reasons. In 

addition, the degree to which the ecosystem 

indicators identified either by the NRC or the 

Heinz Center process are sensitive to expected 

changes due to climate variability and change 

is as yet unknown.

Early warning of changes due to climate: As 

of now, there are no routine monitoring systems 

established specifically for early warning of 

changes due to climate change. The impacts 

documented in this report and elsewhere are 

the results of analyses of existing monitoring 

systems and research projects, but those systems 

have not been optimized for early warning purposes. Without changing the configuration of 

existing in situ monitoring systems, or initiating 

new systems, it will be difficult to be sure that 

we have constructed an adequate early warning system and the ability to determine overall 

consequences of climate change may be limited.

In order to 

fulfill the goal 

of providing 

observations for 

responding the 

climate change, 

there are at least 

five issues that 

such systems must 

be able to address.
The U.S. Climate Change Science Program

190

Synthesis

Fortunately, enough is now known about the 

existing responses of ecosystems and species 

to changes in climate and climate variability to 

define monitoring systems that are optimized 

for early warning of subsequent changes. For

example, one could set up systematic monitoring of ocean pH and alkalinity along with coral 

observations to track whether or not there were 

early indications of difficulties in calcification 

due to increasing pCO2 in surface waters. One 

might also systematically sample vegetation 

along montane transects to detect early changes 

in flowering phenology and/or change in establishment patterns of seedlings that would result 

in species range changes to higher elevations as 

a result of warming temperatures.

In the near-term, stratification of existing systems holds promise for providing reasonable 

information about early responses. Monitoring 

of snow pack and streamflow is being used in 

just this way, as are long time series of ice-out 

dates in northern lakes and national phenology 

data. At a minimum, identifying systems known 

to be at risk of early change (e.g. high latitude 

ecosystems, high elevation systems, coastal 

wetlands, migratory bird species), either because 

similar systems have already exhibited change 

or because they are in locations that are likely 

to experience rapid change, and investigating 

existing monitoring data from them would be 

more likely to reveal early evidence of expected 

changes than broad-based monitoring. Over 

the longer term, studies of existing monitoring 

data that are stratified with respect to either 

observation-based or model-based expectations 

of change would probably lead to better designs 

for future monitoring, but such studies have not 

yet been done.

Monitoring programs that are optimized for 

early warning would not be appropriate for other 

purposes, such as calculating average damages 

in ecosystems or average changes in ecosystem services, precisely because they would be 

more likely to detect changes than the overall 

ecosystem average. This is not a drawback to 

early warning systems, but it is a caution that 

information from them cannot simply be used 

to calculate overall expected damages.

Development and monitoring of indicators 

of climate change impacts: We are early in 

our understanding of ecological changes due to 

climate variability and change, and we should 

expect that understanding to grow and mature 

over time. Some indicators of change are already 

clear from current studies: earlier dates of snowmelt and peak streamflow, earlier ice-out dates 

on northern lakes, earlier spring arrival dates 

for migratory birds, northward movement of 

species distributions, and so forth. Others are 

more subtle or would become evident over a 

longer time period, but are measurable in principle: increase in the severity and/or frequency

of outbreaks of certain forest or agricultural 

pests or changes in the frequency of drought

conditions. However, since these indicators are 

already known from current studies, one could 

certainly design monitoring programs or analyses of existing monitoring data to determine 

whether they are intensifying or becoming less 

prevalent. Current research on the relationships 

between climate variability and change and ecological status and processes could also be used to 

develop new indicators of the effects of climate 

change. Any new indicators that are developed 

will need to be examined for their sensitivity to 

change in climate drivers, and for the expense 

of the systems to measure and report them, to 

determine whether they are good candidates for 

long-term programs (NRC 2000).

Experiments to isolate the impacts of climate 

change from other impacts: Experiments 

that directly manipulate climate variables and 

observe impacts are a critical component in 

understanding climate change impacts and in 

separating the effects of climate from those 

caused by other factors. Direct manipulations 

of precipitation, CO2, temperature, and nitrogen 

deposition have yielded much useful information and many surprises (such as the increased 

growth and toxicity of poison ivy when exposed 

to higher CO2). Because many factors change 

in concert under ambient conditions, manipulations are especially useful at isolating the effect 

of specific factors. In fact, manipulative experiments that reveal information about underlying 

ecological processes are crucial to ensuring that 

a true forecasting capacity is developed.

...in principle it is 

possible to evaluate 

both damages and 

benefits from climate 

change for any region 

and/or ecosystem, 

but such studies 

will need to be very 

carefully designed and 

implemented in order 

to yield defensible 

quantification.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Evaluating damages and benefits from climate change: Over the long term, we need to 

understand the extent to which climate change is 

damaging or enhancing the goods and services 

that ecosystems provide and how additional 

climate change would affect the future delivery 

of such goods and services. This information 

cannot currently be provided for any ecosystem 

for several reasons. In some cases we lack sufficient understanding to identify the observations 

that are required. In others, we lack observations

that we know would be helpful. In yet others, 

we have observations but are not integrating 

these in modeling and analysis frameworks that 

could enable forecasting of potential changes. 

But probably the most important difficulty is 

that we do not have a national system for ecosystem valuation that takes into account both 

goods that ecosystems produce that are priced 

and are traded in markets, and those services 

that are not priced, but are nevertheless valuable 

to society. Even services that can in principle 

result in economic gains, such as wetlands or 

mangroves protection of shorelines from storm 

surge and flooding, have not been estimated on 

large regional or national bases.

Again, in principle it is possible to evaluate both 

damages and benefits from climate change for 

any region and/or ecosystem, but such studies 

will need to be very carefully designed and 

implemented in order to yield defensible quantification. Until then, we will need to continue to 

rely on a combination of existing observations 

made for other purposes and on model output 

to construct such estimates.

6.4 Integration of Eco- 

 system Observa­tions,

Modeling, Experiments

 and Analysis

The rapid changes in ecosystems that have already been documented pose special challenges 

to monitoring systems. If their locations cannot 

be adequately forecast, it is possible for rapid

changes to be missed in monitoring data until 

they become so large that they are obvious. This 

is especially problematic if the intent of the 

monitoring program is to provide early warning 

capabilities. There is currently no analysis in the 

literature that addresses this problem. A second 

particular challenge for monitoring ecosystem 

change due to climate change is the inescapable 

fact that ecosystems respond to many different 

factors, of which climate variability and change 

is only one. Monitoring systems that are established in ways that presuppose one particular 

driver of change could lead to problematic 

estimates of change due to other agents.

Ultimately, a national capacity for documenting and evaluating the extent and magnitude of 

ecosystem changes due to changes in climate 

will require new system designs that draw on

experimentation, modeling and monitoring 

resources. Expectations derived from modeling 

time-series can be periodically challenged with 

observational and experimental data, and the 

results then fed back to ecosystem models in 

order to improve their forecasting quantitatively.

Such procedures would be analytically similar 

to data assimilation techniques in wide use in

weather and climate modeling, but obviously on 

very different time scales. It will be necessary 

for such a system to have systematic sampling 

of ecosystems with respect to climate variability, 

and have models that are then capable of ingesting both process observations and observations 

of ecosystem state and extent.

6.5 Overarching 

Conclusions

Climate changes – temperature increases, 

increasing CO2 levels, and altered patterns 

of precipitation – are already affecting U.S. 

water resources, agriculture, land resources, 

and biodiversity, and will continue to do so 

(very likely). The results of the literature review 

undertaken for this assessment document case 

after case of changes in these resources that are 

the direct result of variability and changes in 

the climate system, even after accounting for 

other factors. The number and frequency of

forest fires and insect outbreaks are increasing 

in the interior West, the Southwest, and Alaska. 

Precipitation, streamflow, and stream temperatures are increasing in most of the continental 

U.S. The western U.S. is experiencing reduced 

snowpack and earlier spring runoff peaks. The 
The U.S. Climate Change Science Program

192

Synthesis

growth of many crops and weeds is being stimulated. Migration of plant and animal species is 

changing the composition and structure of arid, 

polar, aquatic, coastal and other ecosystems.

Climate change will continue to have significant effects on these resources over the next 

few decades and beyond (very likely). Warming is very likely to continue in the United States 

during the next 25-50 years, regardless of the 

efficacy of greenhouse gas emissions reduction 

efforts, due to greenhouse gas emissions that 

have already occurred. U.S. ecosystems and 

natural resources are already being affected by 

climate system changes and variability. It is 

very likely that the magnitude and frequency

of ecosystem changes will continue to increase 

during this period, and it is possible that they 

will accelerate. As temperature rises, crops will 

increasingly begin to experience higher temperatures beyond the optimum for their reproductive 

development. Management of Western reservoir 

systems is very likely to become more challenging as runoff patterns continue to change. Arid 

areas are very likely to experience increases 

erosion and fire risk. In arid region ecosystems 

that have not co-evolved with a fire cycle, the 

probability of loss of iconic, charismatic mega 

flora such as saguaro cacti and Joshua trees will 

greatly increase.

Many other stresses and disturbances are 

also affecting these resources (very likely).

For many of the changes documented in this 

assessment, there are multiple environmental drivers – land use change, nitrogen cycle 

change, point and non-point source pollution, 

wildfires, invasive species, and others – that 

are also changing. Atmospheric deposition of 

biologically available nitrogen compounds 

continues to be an important issue, along with 

persistent, chronic levels of ozone pollution 

in many parts of the country. It is very likely 

that these additional atmospheric effects cause 

biological and ecological changes that interact 

with changes in the physical climate system. In 

addition, land cover and land use patterns are 

changing, e.g., the increasing fragmentation of 

U.S. forests as exurban development spreads to 

previously undeveloped areas, further raising 

fire risk and compounding the effects of summer 

drought, pests, and warmer winters. There are 

several dramatic examples of extensive spread 

of invasive species throughout rangeland and 

semi-arid ecosystems in western states, and 

indeed throughout the United States. It is likely 

that the spread of these invasive species, which 

often change ecosystem processes, will exacerbate the risks from climate change alone. For example, in some cases invasive species increase 

fire risk and decrease forage quality.

Climate change impacts on ecosystems will affect the services that ecosystems provide, such 

as cleaning water and removing carbon from 

the atmosphere (very likely), but we do not yet 

possess sufficient understanding to project 

the timing, magnitude, and consequences of 

many of these effects. One of the main reasons 

for needing to understand changes in ecosystems 

is the need to understand the consequences of

those changes for the delivery of services that 

our society values. Many analyses of the impacts of climate change on individual species 

and ecosystems have been published in the 

scientific literature, but there is not yet adequate

integrated analysis of how climate change could 

affect ecosystem services. A comprehensive 

understanding of the way such services might be 

affected by climate change will only be possible 

through quantification of anticipated alteration

in ecosystem function and productivity. As 

described by the Millennium Ecosystem Assessment, some products of ecosystems, such as 

food and fiber, are priced and traded in markets. 

Others, such as carbon sequestration capacity,

are only beginning to be understood and traded 

in markets. Still others, such as the regulation of 

water quality and quantity, and the maintenance

of soil fertility, are not priced and traded, but are 

valuable nonetheless. Yet although these points 

are recognized and accepted in the scientific 

literature and increasingly among decision makers, there is no analysis specifically devoted to 

understanding changes in ecosystem services 

in the United States from climate change and 

associated stresses. It is possible to make some 

generalizations from the existing literature on 

the physical changes in ecosystems, but interpreting what this means for services provided 

by ecosystems is very challenging and can only 

be done for a limited number of cases. This is a 

significant gap in our knowledge base.

Many analyses of 

the impacts of 

climate change on 

individual species 

and ecosystems 

have been published 

in the scientific 

literature, but there 

is not yet adequate 

integrated analysis 

of how climate 

change could affect 

ecosystem services.
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The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

Existing monitoring systems, while useful 

for many purposes, are not optimized for 

detecting the impacts of climate change on 

ecosystems. There are many operational and 

research monitoring systems that have been 

deployed in the United States that are useful for 

studying the consequences of climate change

on ecosystems and natural resources. These 

range from the resource- and species-specific 

monitoring systems, which land-management 

agencies depend on, to research networks, 

such as the Long-Term Ecological Research 

(LTER) sites, which the scientific community 

uses to understand ecosystem processes. All of 

the existing monitoring systems, however, have 

been put in place for other reasons, and none 

have been optimized specifically for detecting 

the effects and consequences of climate change.

As a result, it is likely that only the largest and 

most visible consequences of climate change are

being detected. In some cases, marginal changes 

and improvements to existing observing efforts, 

such as USDA snow and soil moisture measurement programs, could provide valuable new data 

detection of climate impacts. But more refined 

analysis and/or monitoring systems designed 

specifically for detecting climate change effects 

would provide more detailed and complete information and probably capture a range of more 

subtle impacts. This in turn would hold promise 

of developing early warning systems and more 

accurate forecasts of potential future changes. 

But it must be emphasized that improved observations, while needed, are not sufficient for 

improving understanding of ecological impacts 

of climate change. Ongoing, integrated and 

systematic analysis of existing and new observations could enable forecasting of ecological 

change, thus garnering greater value from 

observational activities, and contribute to more 

effective evaluation of measurement needs.
194

Appendix A: Acronyms and Glossary

APPENDIX A: ACRONYMS AND GLOSSARY

ACRONYMS

AET Apparent equivalent temperature

ANPP Aboveground net primary 

productivity

AOGCM Atmosphere-ocean general 

circulation models

BT Body temperature

CCSM Community Climate System Model

CCSP U.S. Climate Change Science 

Program 

CGC Canadian Global Coupled Model

DOY Day of year

ET Evapotranspiration

ENSO El Niño-Southern Oscillation

FACE Free-Air CO2 Enrichment

GCM General Circulation Model

GFDL Geophysical Fluid Dynamics 

Laboratory

HadCM2 Hadley Centre for Climate 

Prediction and Research’s Climate 

Model 2

HCN Historical Climatology Network

HI Harvest index

HLI Heat load index

IBP International Biome Project

IPCC Intergovernmental Panel on 

Climate Change

IPCC AR4 Intergovernmental Panel on Climate 

Change 4th Assessment Report

IPCC TAR Intergovernmental Panel on Climate 

Change 3rd Assessment Report

IPM Integrated pest management

LAI Leaf area index

LTER Long Term Ecological Research

LWSI Livestock weather safety index

NCAR National Center for Atmospheric 

Research

NEON National Ecological Observatory 

Network

NPP Net primary productivity

NRCS Natural Resources Conservation 

Service

NRCS SCAN Natural Resources Conservation 

Service Soil Climate and Analysis 

Network

NRC National Research Council

NWS COOP National Weather Service 

Cooperative Observer Program

PCMDI (Lawrence Livermore National 

Laboratory’s) Program for Climate

Model Diagnosis and 

Intercomparison

PDO	 Pacific Decadal Oscillation

PE Potential evaporation

ppb Parts per billion

ppm Parts per million

RH Relative humidity

RMSE	 Root mean square error

RR Respiration rate

SOM Soil organic matter

SRAD Solar radiation

SRES Special Report on Emissions Scenarios

SWE Snow water equivalent

TBCA Total carbon allocation belowground

THI Temperature-humidity index

USDA United States Department of 

Agriculture

USGS United States Geological Survey

USGS HCDN United States Geological Survey 

Hydro-Climatic Data Network

VFI Voluntary feed intake

VIC Variable Infiltration Capacity

VOC Volatile organic compound

VPD Vapor pressure deficit

WS Wind speed

WUE Water use efficiency
195

The Effects of Climate Change on Agriculture, Land Resources, Water Resources, and Biodiversity

GLOSSARY

Anthesis

The period during which a flower is fully open and

functional.

Boll

The seed-bearing capsule of certain plants, especially 

cotton and flax.

C3 species

Almost all plant life on Earth can be divided into two 

categories based on the way they assimilate carbon 

dioxide into their systems. During the first steps in CO2

assimilation, C3 plants form a pair of three carbon-atom 

molecules. C3 species continue to increase photosynthesis 

with rising CO2. C3 plants include more than 95 percent of 

the plant species on Earth.

C4 species

C4 plants initially form four carbon-atom molecules. C4

plants include such crop plants as sugar cane and corn. 

They are the second-most prevalent photosynthetic type, 

and do not assimilate CO2 as well as C3 plants.

Carbon sink

A carbon reservoir. Carbon sinks include the oceans, and 

plants and other organisms that remove carbon from the 

atmosphere via photosynthetic processes.

Carbon source

The term describing processes that add carbon dioxide to 

the atmosphere.

Carbon sequestration

The term describing processes that remove carbon dioxide 

from the atmosphere.

Climate

Climate in a narrow sense is usually defined as the

“average weather” or more rigorously as the statistical 

description in terms of the mean and variability of relevant 

quantities over a period of time ranging from months

to thousands or millions of years. The classical period 

is 30 years, as defined by the World Meteorological

Organization (WMO). These relevant quantities are most

often surface variables such as temperature, precipitation, 

and wind. Climate in a wider sense is the state, including a 

statistical description, of the climate system. 

Climate Change

Climate change refers to a statistically significant

variation in either the mean state of the climate or in its 

variability, persisting for an extended period (typically 

decades or longer). Climate change may be due to 

natural internal processes or external forcings, or to 

persistent anthropogenic changes in the composition 

of the atmosphere or in land use. Note that the United 

Nations Framework Convention on Climate Change

(UNFCCC), in its Article 1, defines “climate change”

as: “a change of climate which is attributed directly or 

indirectly to human activity that alters the composition 

of the global atmosphere and which is in addition to 

natural climate variability observed over comparable time 

periods.” The UNFCCC thus makes a distinction between 

“climate change” attributable to human activities altering 

the atmospheric composition, and “climate variability” 

attributable to natural causes. See also climate variability.

Climate Variability

Climate variability refers to variations in the mean state 

and other statistics (such as standard deviations, the 

occurrence of extremes, etc.) of the climate on all temporal 

and spatial scales beyond that of individual weather 

events. Variability may be due to natural internal processes 

within the climate system (internal variability), or to 

variations in natural or anthropogenic external forcing

(external variability). See also climate change.

CO2 enrichment

Addition of CO2 to the atmosphere.

Coefficient of variation of annual runoff

A measure of the variability of runoff

Complementary hypothesis

This hypothesis states that trends in actual evaporation and 

pan evaporation should be in opposite directions.

Cucurbits

Any of various mostly climbing or trailing plants of 

the family Cucurbitaceae, which includes the squash,

pumpkin, cucumber, gourd, watermelon, and cantaloupe.

Endophyte

A plant living within another plant, usually as a parasite.

Evaporation paradox

Temperature, precipitation, stream flow and cloud cover

records indicate that warmer, rainier weather is now more 

common in many regions of the world. However, pan 

evaporation readings, taken at weather stations, indicate 

that less moisture has been rising back into the air from 

these pans.

Evapotranspiration

The sum of evaporation and plant transpiration. 

Evaporation accounts for the movement of water to the 

air from sources such as the soil, canopy interception, and 

water bodies. Transpiration accounts for the movement of 

water within a plant and the subsequent loss of water as

vapor through stomata in its leaves.

Free-Air CO2 Enrichment (FACE)

FACE is a method and infrastructure used to 

experimentally enrich the atmosphere enveloping portions 

of a terrestrial ecosystem with controlled amounts of 

carbon dioxide (and in some cases, other gases), without 

using chambers or walls.
The U.S. Climate Change Science Program

196

Appendix A: Acronyms and Glossary

Forb

A broad-leaved herb (not a grass), especially one growing 

in a field, prairie, or meadow.

Global dimming

The gradual reduction in the amount of global direct 

irradiance at the Earth’s surface that was observed for 

several decades after the start of systematic measurements 

in 1950s.

Herbivores

Animals that feed chiefly on plants.

Homeostasis

The scientific study of periodic biological phenomena,

such as flowering, breeding, and migration, in relation to

climatic conditions.

Instream flow

The term used to identify a specific stream flow (typically

measured in cubic feet per second, or cfs) at a specific

location for a defined time, and typically following

seasonal variations. Instream flows are usually defined as

the stream flows needed to protect and preserve instream

resources and values, such as fish, wildlife and recreation.

Instream flows are most often described and established in

a formal legal document, typically an adopted state rule. 

Irrigation Modes

Drip irrigation allows water to drip slowly to the roots 

of plants through a network of valves, pipes, tubing, and 

emitters.

Flood irrigation pumps water onto the fields. The water

then flows freely along the ground among the crops.

Spray irrigation relies on machinery to spray water in all 

directions.

Latent heat

The heat required to change the phase of a substance,

for example a solid to vapor (sublimation), liquid to

vapor (vaporization) or solid to liquid (melting); the

temperature does not change during these processes. Heat 

is released for the reverse processes, for example vapor to 

solid (frost), liquid to solid (freezing), or vapor to liquid

(condensation). 

Leaf area index (LAI)

The ratio of total upper leaf surface of a crop divided by 

the surface area of the land on which the crop grows.

Lignin

An organic substance that, with cellulose, forms the chief 

part of woody tissue.

Lysimeter

A device for collecting water from the pore spaces of soils, 

and for determining the soluble constituents removed in 

the drainage.

Mutualistic relationship

A positive, reciprocal relationship between two species. 

Through this relationship, both species enhance their 

survival, growth or fitness.

Net primary productivity (NPP)

The ratio of all biomass accumulation and biomass losses 

in units of carbon, weight or energy, per land surface unit, 

over a set time interval (usually a year).

Pan evaporation

Pans used to determine the quantity of evaporation at a

given location. These are generally located in agricultural 

areas, and have been used as an index to potential 

evaporation.

Panicle

The complete assembly of spikelets on a rice plant.

Phenology

The study of periodic biological phenomena (flowering

of plants, breeding, and species migration) in relation to 

climatic conditions.

Potential Evapotranspiration

A representation of the environmental demand for

evapotranspiration and represents the evapotranspiration 

rate of a short green crop, completely shading the ground, 

of uniform height and with adequate water status in the

soil profile. It is a reflection of the energy available to

evaporate water, and of the wind available to transport the 

water vapor from the ground up into the lower atmosphere.

Runoff ration

The total amount of runoff divided by the total moisture 

that falls during a precipitation event.

Ruminant

Even-toed, cud-chewing, hoofed mammals of the suborder 

Ruminantia, such as domestic cattle.

Sensible heat

Heat that can be measured by a thermometer.

Spikelet

The individual places on a rice plant where a grain 

develops.

Stomatal

One of the minute pores in the epidermis of a leaf or stem 

through which gases and water vapor pass.

Tiller

New shoots that develop at the base of the plant.
197

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Director, Climate Change Science Program Office: ..................................................... Peter A. Schultz

Lead Agency Principal Representative to CCSP,

Director, Global Change Program Office, 

U.S. Department of Agriculture:........................................................................ William G. Hohenstein

Product Lead, Global Change Program Office,

U.S. Department of Agriculture:...............................................................................Margaret K. Walsh

Chair, Synthesis and Assessment Product Advisory

Group, Associate Director, National Center for

Environmental Assessment, U.S. Environmental

Protection Agency:....................................................................................................Michael W. Slimak

Synthesis and Assessment Product Coordinator, 

Climate Change Science Program Office: ............................................................... Fabien J.G. Laurier

Special Advisor, National Oceanic and Atmospheric

Administration: .............................................................................................................Chad A. McNutt

EDITORIAL AND PRODUCTION TEAM

Managing Editor, U.S. Department of Agriculture: .................................................Margaret K. Walsh

Editorial Coordinator and Chapter Editor, NCAR:............................................................ Greg Guibert

Editorial Coordinator and Chapter Editor, NCAR:..........................................................Rachel Hauser

Publication and Graphics Coordinator, NCAR:.....................................................................Carol Park

Layout Editor, NCAR: ........................................................................................................ Brian Bevirt

Scientific Editing and Review, NCAR:........................................................................... Kathy Hibbard

Web support, NCAR: ..................................................................................................... Kristin Conrad

Web support, NCAR:................................................................................................... Steve Aulenbach

Web support, NCAR:.......................................................................................................Erika Marcum

Graphic Design Support, Smudgeworks:....................................................................... Michael Shibao

Technical Advisor, Climate Change Science Program Office: .................................... David J. Dokken

Disclaimer: This document, part of the Synthesis and Assessment Products described in the U.S. Climate Change 

Science Program (CCSP) Strategic Plan, was prepared in accordance with Section 515 of the Treasury and 

General Government Appropriations Act for Fiscal Year 2001 (Public Law 106-554) and the information quality 

act guidelines issued by the U.S. Department of Agriculture pursuant to Section 515. The CCSP Interagency 

Committee relies on U.S. Department of Agriculture certifications regarding compliance with Section 515 

and Agency guidelines as the basis for determining that this product conforms with Section 515. For purposes 

of compliance with Section 515, this CCSP Synthesis and Assessment Product is an “interpreted product” as 

that term is used in the U.S. Department of Agriculture guidelines and is classified as “highly influential”. 

This document does not express any regulatory policies of the United States or any of its agencies, or provide 

recommendations for regulatory action.
U.S. Climate Change Science Program

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