United States Department of Agriculture

Effects of Drought on Forests and 

Rangelands in the United States: 

A Comprehensive Science Synthesis

Forest Service Gen. Tech. Report WO-93b January 2016
January 2016

Forest Service

Research & Development

Gen. Tech. Report WO-93b

Photographs are provided courtesy of the U.S. Department 

of Agriculture (USDA) Forest Service, Agricultural Research 

Service, and Natural Resources Conservation Service; the 

U.S. Geological Survey; and other Federal and State agencies, 

universities, and nongovernmental organizations. Individual 

photo credits are provided.

Cover Photographs (from top to bottom):

J.S. Quick, Colorado State University, Bugwood.org 

Ronald F. Billings, Texas Forest Service, Bugwood.org

U.S. Geological Survey
Effects of Drought on

Forests and Rangelands

in the United States:

A Comprehensive Science Synthesis

editors

James M. Vose

James S. Clark

Charles H. Luce

Toral Patel-Weynand

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Science (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources, Raleigh, 

NC 27695.

J.S. Clark is the Nicholas Professor of Environmental Science and Professor of Statistical 

Science, Nicholas School of the Environment, Duke University, Durham, NC 27708-0338.

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station, Boise, ID 83702.

T. Patel-Weynand is Director of the Forest Management Sciences’ (SFMR) staff, 

U.S. Department of Agriculture, Forest Service, Research and Development (R&D), 

Washington, DC 20024.
ii

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

ACKNOWLEDGMENTS & ABSTRACT

Acknowledgments

The editors thank the authors who contributed to this report. We also thank the 

technical reviewers who provided comments and suggestions on earlier drafts. 

We thank Jennifer Plyler and Stephanie Laseter for their assistance with editing 

and formatting. We thank the Southern Research Station for its work to publish 

this report; specifically, we thank Donna Burnett for technical editing and ensuring 

compliance with the U.S. Government Publishing Office, Maureen Stuart for 

technical editing and leading the publication process, and Helen Robinson for 

graphic design. The U.S. Department of Agriculture, Forest Service, Southern 

Research Station (J.M. Vose), Rocky Mountain Research Station (C.H. Luce), and 

National Research and Development Washington Office (T. Patel-Weynand and 

James S. Clark) provided support for the editors and the publication process.

Abstract

This assessment provides input to the reauthorized National Integrated Drought 

Information System (NIDIS) and the National Climate Assessment (NCA), and 

it establishes the scientific foundation needed to manage for drought resilience 

and adaptation. Focal areas include drought characterization; drought impacts 

on forest processes and disturbances such as insect outbreaks and wildfire; and 

consequences for forest and rangeland values. Drought can be a severe natural 

disaster with substantial social and economic consequences. Drought becomes 

most obvious when large-scale changes are observed; however, even moderate 

drought can have long-lasting impacts on the structure and function of forests and 

rangelands without these obvious large-scale changes. Large, stand-level impacts 

of drought are already underway in the West, but all U.S. forests are vulnerable 

to drought. Drought-associated forest disturbances are expected to increase with 

climatic change. Management actions can either mitigate or exacerbate the effects 

of drought. A first principal for increasing resilience and adaptation is to avoid 

management actions that exacerbate the effects of current or future drought. 

Options to mitigate drought include altering structural or functional components 

of vegetation, minimizing drought-mediated disturbance such as wildfire or insect 

outbreaks, and managing for reliable flow of water.

Keywords: Climate change, drought, forest disturbances, natural disasters, water 

quantity and quality.
iii

TABLE OF CONTENTS

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Contents

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

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

Overview and Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Topics Addressed in This Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Key Messages From the Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Managing Forests and Rangelands To Increase Resiliency and Drought Adaptation . . . . . . . . . . . 7

1 Understanding and Anticipating Potential Drought Impacts . . . . . . . . . . . . . . . . . . 9

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 

2 Characterizing Drought for Forested Landscapes and Streams . . . . . . . . . . . . . . . . 13

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

What Is Drought? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Drought Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Drought Influences on Forest and Stream Ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Ecological Drought Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Measures of Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Paleoclimatic Context for Evaluating Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Historical and Recent Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Climate Change Impacts on Drought Frequency and Severity . . . . . . . . . . . . . . . . . . . . . . . . . 34

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

3 Physiological Responses of Forests to Future Drought . . . . . . . . . . . . . . . . . . . . . . 49

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

A Plant’s Perspective on Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Belowground Mechanisms to Survive Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

The Interaction of Drought, Host Physiology, and Multi-Trophic Community Dynamics . . . . . . . . 54

Can CO2 Fertilization Mitigate Drought Impacts? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Do Ecosystem Models Include Plant Drought-Response Mechanisms? . . . . . . . . . . . . . . . . . . 55

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

4 Impacts of Increasing Drought on Forest Dynamics, 

Structure, Diversity, and Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

Evidence for Drought Impacts on Forests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Drought-Mediated Biogeographic and Biome Shifts in U.S. Forests . . . . . . . . . . . . . . . . . 70

Implications for Forest Management Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

Research to Better Anticipate Drought Effects on U.S. Forests . . . . . . . . . . . . . . . . . . . 82

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
iv

TABLE OF CONTENTS

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

5 Forest Biogeochemistry in Response to Drought . . . . . . . . . . . . . . . . . . . . . . 97

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

Drought and Forest Biogeochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

Drought and Carbon Balance in Forests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

Management Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

Representation of Drought in Ecosystem and Global Models . . . . . . . . . . . . . . . . . . . 105

Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

6 Forest Insect and Fungal Pathogen Responses to Drought . . . . . . . . . . . . . . . 113

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114

Tree Responses to Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114

Insect and Pathogen Responses to Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

Regional and Sub-Regional Differences and Interactions . . . . . . . . . . . . . . . . . . . . . . 122

Anticipating Impacts: Predictions of Future Drought-Related Insect and Disease Impacts . . . . 125

Summary and Research Needs for Insects and Pathogens . . . . . . . . . . . . . . . . . . . . 126

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128

7 Fire and Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

Introduction and Historical Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

Characterizing Drought: Metrics of Fire Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

Regional Differences in Fire and Interactions With Other Stressors . . . . . . . . . . . . . . . . 141

Quantifying and Projecting Drought Effects on Wildfire: Biological and Physical Factors . . . . . 146

Management and Social Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

8 Rangeland Drought: Effects, Restoration, and Adaptation . . . . . . . . . . . . . . . 155

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

Types and Patterns of Rangeland Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157

Effects of Drought on Rangelands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163

Drought Interactions With Other Disturbances and Stressors . . . . . . . . . . . . . . . . . . . 169

Effects of Drought on, or in Combination With, Human Uses and Practices . . . . . . . . . . . . 173

Increasing Rangeland Ecosystem Resilience to Drought . . . . . . . . . . . . . . . . . . . . . . 177

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
v

TABLE OF CONTENTS

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

9 Detecting and Monitoring Large-Scale Drought Effects 

on Forests: Toward an Integrated Approach . . . . . . . . . . . . . . . . . . . . . . . . 195

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

Existing Approaches Used for Broad-Scale Drought Impact Detection and Monitoring . . . . . . 204

Integrating Broad Monitoring With Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . 214

“Big Data” Integration: A Contextual Learning Approach to Drought . . . . . . . . . . . . . . . 219

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225

10 Ecohydrological Implications of Drought . . . . . . . . . . . . . . . . . . . . . . . . . . 231

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232

Relationship Between Meteorological Drought and Hydrologic Drought . . . . . . . . . . . . . . 233

Species Composition, Vegetation Dynamics, and Drought Interactions With Streamflow . . . . . 235

Range Shifts in Major Ecosystem Types in Response to Climate Change . . . . . . . . . . . . . 238

Groundwater Interactions With Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240

Challenges to Predicting the Impacts of Drought on Hydrological Processes . . . . . . . . . . . 240

Drought Impacts on Water Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241

Management Options for Minimizing the Impacts of Drought on Water Quantity and Quality . . 244

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245

11 Economics and Societal Considerations of Drought . . . . . . . . . . . . . . . . . . . 253

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254

General Economic and Social Effects of Drought in Forests and Rangelands . . . . . . . . . . . 254

Examples of Drought Effects on the Forest and Rangeland Sectors . . . . . . . . . . . . . . . . 260

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275

Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279

12 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

Characterizing Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

Drought Effects on Wildlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

Socioeconomic Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Critical Research Needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286

Management Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288

Executive Summary

James M. Vose

James S. Clark

Charles H. Luce

Toral Patel-Weynand

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Science (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources, Raleigh, 

NC 27695.

J.S. Clark is the Nicholas Professor of Environmental Science and Professor of Statistical 

Science, Nicholas School of the Environment, Duke University, Durham, NC 27708-0338.

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station, Boise, ID 83702.

T. Patel-Weynand is Director of the Forest Management Sciences’ (SFMR) staff, 

U.S. Department of Agriculture, Forest Service, Research and Development (R&D), 

Washington, DC 20024.

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

EXECUTIVE SUMMARY

1

Overview and Purpose 

This assessment provides input to the reauthorized National 

Integrated Drought Information System (NIDIS) and the National 

Climate Assessment (NCA); it also establishes the scientific 

foundation needed to manage for drought resilience and adaptation. The 

NIDIS Act1 was signed into law in 2006 and reauthorized by Congress 

in 2014.2 NIDIS will be implemented through a network of agencies 

and partners to integrate drought monitoring and forecasting systems 

at multiple levels (Federal, State, and local). It will support research 

that focuses on drought risk assessment, forecasting, and monitoring. 

Produced every 4 years, the NCA evaluates the effects of global climate 

change on forests, agriculture, rangelands, land and water resources, 

human health and welfare, and biological diversity, and it projects major 

trends. The NCA is based on technical information produced by public 

agencies and nongovernmental organizations. 

As drought regimes change, the ability to quantify and predict 

the impacts on forests and rangelands is critical to developing 

and implementing management actions to increase resiliency and 

adaptation. The U.S. Department of Agriculture (USDA), Forest 

Service, Research and Development scientists in partnership with 

Duke University authored this assessment, entitled, Effects of Drought 

on Forests and Rangelands in the United States: A Comprehensive 

Science Synthesis. The assessment is a collaborative effort authored 

by 77 scientists from the Forest Service and other Federal agencies, 

research institutions, and various universities across the United States. 

The authors identified key issues from a series of virtual workshops 

involving scientists and stakeholders. Focal areas in the assessment 

include drought characterization, drought impacts on forest processes 

and disturbances such as insect outbreaks and wildfire, and the 

consequences on forest and rangeland values. The assessment closely 

follows the Intergovernmental Panel on Climate Change (IPCC) process, 

which is organized with convening authors, lead chapter authors, and 

contributing authors. The convening authors for the assessment had 

the chapters individually peer reviewed, and the lead and contributing 

authors revised the text in response to reviewer comments. 

1 National Integrated Drought Information System Act of 2006. P.L. 109-430 (December 20, 2006). 

15 U.S.C. § 313d.

2 National Integrated Drought Information System Act of 2014. P.L. 113-86 (March 6, 2014). 

This assessment establishes 

the scientific foundation 

needed to manage forests 

and rangelands for resilience 

and adaption to drought. 

Photo credits (from top to bottom):

Craig D. Allen, U.S. Geological Survey

J.S. Quick, Colorado State University, Bugwood.org
2

EXECUTIVE SUMMARY

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Topics Addressed in This Assessment 

l Characterizing Drought for Forested Landscapes 

and Streams

l Physiological Responses of Forests to Future Drought

l Impacts of Drought on Forest Dynamics, Structure, 

Diversity, and Management

l Forest Biogeochemistry in Response to Drought

l Insect and Pathogen Responses to Drought

l Fire and Drought

l Rangeland Drought: Effects, Restoration, and Adaptation

l Detecting and Monitoring Large-Scale Drought Effects 

on Forests: Toward an Integrated Approach

l Ecohydrological Implications of Drought

l Economics and Societal Considerations of Drought in 

Forests and Rangelands

This assessment focuses on 

drought characterization, the 

impacts on forest processes 

and disturbances, and the 

consequences on forest and 

rangeland values.

Photo credits (from top to bottom):

Craig D. Allen, U.S. Geological Survey

John M. Randall, The Nature Conservancy, Bugwood.org

U.S. Geological Survey
EXECUTIVE SUMMARY

3

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Key Messages From the Report 

Characterizing and Predicting Future Drought

In simple terms, drought is a lack of water over a given temporal 

and spatial scale. Drought can be a severe natural disaster with 

substantial social and economic consequences. Drought becomes 

most obvious when large-scale changes are observed (e.g., insect 

outbreaks or wildfires) or when water requirements for human or 

agricultural needs are not met; however, even moderate drought can 

have long-lasting impacts on the structure and function of forests and 

rangelands without these obvious large-scale changes. Droughts are 

generally identified as one of four types: (1) meteorological, 

(2) hydrologic, (3) agricultural, or (4) socioeconomic. Meteorological 

and hydrologic droughts relate water availability to a reference 

condition (e.g., long-term mean); agricultural and socioeconomic 

droughts relate to impacts. In agricultural systems producing annual 

crops, characterizing and assessing drought impacts can be fairly 

straight forward; however, in systems with perennial vegetation (both 

natural and agricultural systems), characterizing and assessing drought 

impacts is much more complex, as responses can vary in space, time, 

and among species. 

Historical and paleoclimatic evidence shows that drought has 

always impacted the physical environment and will continue to do 

so. The direction of trends in recent history varies from region to 

region, with the Western United States showing a trend toward dry 

conditions while trends in the East are more variable and complex. 

Much of the variability in how drought is characterized depends on 

definitions for terms, for reference conditions, and for methods of 

averaging short-term weather into climate statistics. Predicting future 

changes in drought frequency and severity has proven difficult using 

General Circulation Models (GCMs), but recent trends are a growing 

global concern. Uncertainty arises primarily from limited capacity to 

predict future precipitation changes, particularly long-term lapses in 

precipitation. Despite this uncertainty, there is growing consensus that 

extreme precipitation events (e.g., lapses in precipitation and more 

intense storms) will increase in frequency, and warmer temperatures 

will exacerbate the impacts of drought on forests and rangelands in the 

future (chapter 2).

Drought becomes obvious 

when large-scale changes 

such as insect outbreaks, 

(top) or wildfires (center) are 

observed and when water 

requirements for human or 

agricultural needs are not 

met (bottom).

Photo credits (from top to bottom):

USDA Forest Service, Bugwood.org

National Interagency Fire Center, Bugwood.org

Gerald Holmes, California Polytechnic State University, 

 Bugwood.org
4

EXECUTIVE SUMMARY

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Understanding the Effects of Drought on Forests and Rangelands

There is a critical need to understand how drought affects forests and 

rangelands, in part because drought severity and drought-associated 

forest disturbances are expected to increase with climatic change. 

Drought affects forest and rangeland systems both directly and 

indirectly. In regions where seasonal droughts are common, forest 

and rangeland ecosystems respond through various physiological and 

morphological adaptations. In regions where drought is less common, 

responses can be substantial because ecosystems are not well adapted 

to drought conditions. 

High evaporative demand, the combination of high temperature and 

low humidity, combines with low soil moisture to induce stress through 

closure of stomata, which can lead to carbon stress, loss of hydraulic 

function, and mortality. Species vary in their vulnerability to drought 

due to differences in their allocation to roots, mycorrhizal associations, 

and xylem anatomy (chapter 3). Large stand-level impacts of drought 

are already underway in the West, but all U.S. forests are vulnerable 

to drought. Changes in climate will continue to stress forests and alter 

suitable habitat. Combined field evidence and models suggest that 

climate change is causing relocation of habitats at rates much faster than 

populations of trees can migrate. Reorganizations of stand structure and 

species composition are expected to lag behind shifts in habitat caused 

by increasing drought and temperature change (chapter 4).

Droughts are predicted to accelerate the pace of invasion by some 

nonnative plant species into rangelands and grasslands. Drought can also 

promote plant invasion indirectly by modifying the environment to favor 

nonnative species. For example, opportunities for invasion are created 

when drought kills native plants leaving open niches and bare ground 

(chapter 8). Drought is also an important contributor to the invasive 

annual grass-wildfire loop that threatens ecosystems not adapted to fire 

(e.g., cheatgrass’ positive feedback with fire in parts of western North 

America’s sagebrush biome). In this self-perpetuating cheatgrass-fire 

loop, drought increases the frequency of wildfires, and nonnative plants 

(especially annual grasses) are likely to invade burned sites. 

Drought alters ecosystem processes such as nutrient, carbon, and 

water cycling in ways that are not yet well understood (chapter 

5). Drought tends to slow nutrient uptake by plants and reduce retranslocation of foliar nutrients with premature leaf senescence. 

Dieback that results from combinations of drought and natural enemies 

Ecosystem structure and 

processes are altered by 

drought. Cheatgrass (top) 

is a nonnative plant that 

invades burned sites. 

Dieback (bottom) can 

have global impacts on 

carbon cycles. 

Photo credits (from top to bottom):

Craig D. Allen, U.S. Geological Survey

Chris Evans, Illinois Wildlife Action Plan, Bugwood.org
EXECUTIVE SUMMARY

5

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

can severely reduce carbon exchange between atmosphere and 

biosphere. Recent large diebacks have had global impacts on carbon 

cycles, including carbon release from biomass and reductions in carbon 

uptake from the atmosphere, although impacts may be offset by 

vegetation regrowth in some regions. Multi-year or severe droughts can 

have substantial impacts on hydrological and stream biogeochemical 

processes. 

Indirect effects of drought on forests can be widespread and 

devastating. Notable recent examples include insect and pathogen 

outbreaks (chapter 6) and increased wildfire risk (chapter 7). Available 

evidence suggests a nonlinear relationship between drought intensity 

and bark beetle outbreaks; moderate drought reduces outbreaks 

whereas long, intense drought can increase it. As a consequence of 

long-term drought and warming in the Western United States, bark 

beetles are currently the most important biotic agent of tree mortality. 

Multiple large outbreaks have killed hundreds of millions of trees 

in recent decades. Host trees weakened by drought allow beetle 

populations to build. Warming facilitates northward range expansion. 

In contrast, there is little current evidence for a role of drought in bark 

beetle outbreaks in coniferous forests of the Eastern United States. 

Fungal pathogens are poorly understood, but available evidence 

suggest reduced pathogen performance and host impacts in response 

to drought for primary pathogens and pathogens whose lifecycle 

depends directly on moisture. In comparison, secondary pathogens that 

depend on stressed hosts for colonization are anticipated to respond to 

drought with greater performance and host impacts. 

Historical and pre-settlement relationships between drought and 

wildfire have been well documented in much of North America, with 

forest fire occurrence and area burned clearly increasing in response 

to drought. This body of evidence indicates that the role of drought in 

historical and likely future fire regimes is an important contingency that 

creates anomalously high potential for ignition, fire spread, and large fire 

events. However, drought is only one aspect of a broader set of controls 

on fire regimes, and by itself is insufficient to predict fire dynamics or 

effects. Whereas the relationships between fire occurrence or area 

burned and drought are well documented, the relationship between 

drought and fire severity can be complex. For example, north-facing 

slopes might offer some degree of local protection during mild 

droughts, but even they become dry under extreme conditions, 

reducing fine-scale heterogeneity in vegetation consequences. 

Drought can increase 

the intensity of insect 

and pathogen outbreaks 

including bark beetles (top), 

Dothistroma needle blight 

(center), and hemlock woolly 

adelgid (bottom).

Photo credits (from top to bottom):

Ronald F. Billings, Texas Forest Service, Bugwood.org

Robert L. James, USDA Forest Service, Bugwood.org

Elizabeth Willhite, USDA Forest Service, Bugwood.org
6

EXECUTIVE SUMMARY

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Streamflow and groundwater recharge respond directly to drought 

through reductions in precipitation (rain and/or snowfall), and they 

respond indirectly via evapotranspiration responses to changing 

evaporative energy and water availability. Hydrologic responses to 

drought can be either mitigated or exacerbated by forest vegetation, 

depending on vegetation water use and how drought affects forest 

population dynamics (chapter 10). Drought affects water quality both 

directly and indirectly. Direct impacts are primarily physical, as reduced 

streamflow concentrates nutrients and sediment and warms more 

quickly. Indirect effects include a combination of terrestrial, riparian, 

and instream processes that impact sediment and nutrient 

concentrations and fluxes.

Detecting and Monitoring Future Droughts

The ability to detect drought effects on forest and rangelands over 

broad scales is limited, especially for episodic droughts of moderate 

severity. Compared to agricultural systems, detecting drought impacts 

on trees and other perennial vegetation may require a multi-year 

“memory” of antecedent conditions. With broad-scale monitoring, it is 

often not possible to detect drought effects, as moisture stress is not 

expressed uniformly across vegetation types. 

Remote sensing approaches attempt to observe direct, secondary, 

and longer term effects of drought on vegetation (chapter 9). Remote 

sensing methods integrate across entire mixed-vegetation pixels and 

rarely distinguish the effects of drought on a single species, nor can 

they disentangle drought effects from those caused by various other 

disturbance agents. An integrated data-mining approach may hold the 

most promise for enhancing our ability to resolve drought impacts to 

forests. Efforts to integrate meteorological and remotely sensed data 

streams, together with other ancillary datasets such as vegetation 

type, wildfire occurrence, and pest activity, may help to identify and 

characterize drought effects.

Economic and Social Consequences of Drought

Drought has direct consequences to forest and rangeland production 

(chapter 11). Droughts can negatively impact forest inventories by 

increasing mortality and reducing growth. Drought in rangelands 

reduces forage and water available for livestock grazing. Reduced 

vegetative cover can lead to wind and water erosion. Drought-related 

disturbance, such as wildfire, can have protracted effects that include 

significant timber market losses. 

Drought impacts streams 

(top) by concentrating 

sediments and nutrients. 

In rangelands, drought can 

reduce vegetative cover, 

leading to wind and water 

erosion (bottom). 

Photo credits (from top to bottom):

Carol J. VanDyke, U.S. Geological Survey

Seth Munson, U.S. Geological Survey
EXECUTIVE SUMMARY

7

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Reduced water yield from forests and rangelands during extended 

meteorological drought can have substantial impacts on domestic 

and agricultural water supplies, which often results in water markets 

implementing quantity controls. Drought can also have nonmarket 

effects on forests and rangelands. For example, drought affects outdoor 

recreation, where low reservoir levels can reduce availability of fishing, 

recreational boating, swimming, and camping (although some net 

benefit can result from more precipitation-free days). Low winter snow 

cover reduces economic benefits from skiing and related activities. 

Ongoing drought in the Western United States, where most tribal lands 

exist, is expected to continue to affect tribal health, culture, economies, 

and infrastructure. Competing demands for dwindling water resources 

challenge Federal trust responsibilities. Complicating factors, including 

warming streams and hydrologic-cycle changes, affect fish populations 

important to tribal diets and ceremonies. Because of their natural 

resource dependence for income, employment, and cultural practices, 

many tribes are also vulnerable to higher rates of forest and rangeland 

disturbances, including invasive species spread, increased occurrences of 

epidemic pest populations and their associated damages, and wildfires. 

Managing Forests and Rangelands To 

Increase Resiliency and Drought Adaptation 

How can forest and rangeland practices adapt to changing drought 

regimes? Frequent low-severity drought may selectively favor more 

drought-tolerant species and create forests and rangelands better 

adapted to future conditions without the need for management 

intervention. By contrast, severe drought (especially in combination with 

insect outbreaks or fire), may threaten large-scale changes that warrant 

substantial management responses. Actions could range from reducing 

vulnerability, facilitating post-drought recovery, or facilitating a transition 

to a new condition.

Management actions can either mitigate or exacerbate the effects of 

drought. A first principal for increasing resilience and adaptation would 

be to avoid management actions that exacerbate the effects of current 

or future drought. Options can include altering structural or functional 

components of vegetation, minimizing drought-mediated disturbance 

Drought in rangelands 

reduces forage and water 

available for livestock grazing 

(top). Lower reservoir and 

winter snow levels impact 

outdoor recreation activities 

(bottom).

Photo credits (from top to bottom):

Keith Weller, USDA Agricultural Research Service, Bugwood.org

U.S. Geological Survey
8

EXECUTIVE SUMMARY

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

such as wildfire or insect outbreaks, and managing for reliable flow 

of water. Managers can implement structural changes by thinning or 

density management of planted forests. Thinned stands require less 

water and may be less vulnerable to water stress and insect outbreaks. 

Reduced fuel loads in thinned stands can also reduce wildfire risk. 

Managers can also implement functional changes by favoring or planting 

more drought-adapted species. Management for a diversity of species 

can reduce stand vulnerability to drought, as uncertainty in future climate 

can encourage management for mixtures of drought-tolerant species and 

genotypes. Species diversity can also reduce intensity of insect attacks. 

In some regions of the United States, planting or favoring more droughttolerant species may conflict with management objectives that favor 

rapid accumulation of biomass, as fast-growing woody species often use 

more water and exacerbate drought impacts. 

While harvesting increases annual water yield in some forest 

ecosystems, a large reduction of forest cover is needed to have 

an appreciable effect on water yield. Hence, potential increases in 

streamflow through forest cutting are limited by the amount of land 

that managers can harvest. In addition, streamflow responses are 

often short term due to rapid forest regrowth, and the aggrading postcut forest may actually have lower streamflow than the uncut forest. 

In contrast to management actions that are intended to augment 

streamflow, increasing drought stress in some forest ecosystems 

may warrant management strategies that retain water (and hence 

reduce streamflow) on the landscape in order to keep trees alive. 

Land managers may need to plan the timing of some management 

activities to ensure that ecosystems have optimal growing conditions 

and that these activities do not disturb streams during low-flow 

periods. Removal and alteration of riparian vegetation increases stream 

temperatures; therefore, maintaining or increasing shading from solar 

radiation through riparian buffer zone conservation and restoration may 

mitigate any changes in stream temperatures caused by drought.

In summary, this assessment synthesizes information from the 

published literature to better understand the impacts of drought on 

forests and rangelands in the United States. Our expectation is that this 

assessment will provide researchers, land managers, policymakers, and 

other stakeholders a set of realistic inferences of drought effects that 

can be applied to help predict future impacts and evaluate management 

options for adaptation and mitigation.

Management strategies, such 

as thinning (top) and riparian 

buffer zone conservation 

(bottom), may help to mitigate 

the effects of drought.

Photo credits (from top to bottom):

Scott Roberts, Mississippi State University, Bugwood.org

USDA Natural Resources Conservation Service
CHAPTER 1

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Science (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources, Raleigh, 

NC 27695.

J.S. Clark is the Nicholas Professor of Environmental Science and Professor of Statistical 

Science, Nicholas School of the Environment, Duke University, Durham, NC 27708-0338.

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID, 83702.

T. Patel-Weynand is Director of the Forest Management Sciences’ (SFMR) staff, 

U.S. Department of Agriculture, Forest Service, Research and Development (R&D), 

Washington, DC 20024.

Understanding and Anticipating 

Potential Drought Impacts 

James M. Vose

James S. Clark

Charles H. Luce

Toral Patel-Weynand
10

CHAPTER 1

Understanding and Anticipating Potential Drought Impacts

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Droughts have been a major factor influencing forests 

and rangelands in the United States for millennia (Cook 

and others 2007, Cook and others 2014), and they can 

have substantial social and economic consequences 

(Andreadis and others 2005, Wilhite and BuchananSmith 2005). Cook and others (2007) suggest that the 

Western United States has recently entered a period 

of protracted aridity, and drought has become more 

frequent and severe in the Southeastern United States 

since the 1980s (Melillo and others 2014, Pederson 

and others 2012, Seager and others 2009). In forests, 

these recent droughts have contributed to large-scale 

insect outbreaks (Weed and others 2013), forest 

die-off and reduced growth (Allen and others 2010, 

Breshears and others 2005, Klos and others 2009), 

and increased wildfire risk and area burned (Littell 

and others 2009, Westerling and others 2003), all of 

which impact forest biogeochemical cycling (Goetz and 

others 2012, Johnson and others 2007) and hydrologic 

processes (Guardiola-Clarmonte and others 2011, 

Holden and others 2012). In rangeland ecosystems, 

severe drought can limit production (Knapp and 

Smith 2001), alter nutrient cycling (Evans and Burke 

2013), and increase wildfire risk and susceptibility 

to invasive plant species (Abatzoglou and Kolden 

2011). Quantifying the economic and social impacts 

of drought on forests and rangelands is complex due 

to the wide array of ecosystem services impacted; 

however, impacts such as reduced forest growth and 

carbon (C) accumulation (Amiro and others 2010, 

Hicke and others 2012), increased wildfire suppression 

costs (Prestemon and others 2008), and degraded 

rangeland conditions (Polley and others 2013) are well 

documented.

Although it is clear that shifts in circulation patterns, 

energy for evapotranspiration (ET), and air temperatures 

are changing in ways that enhance the consequences 

of drought on forests and rangelands, there is less 

certainty about the effects of climate change on drought 

occurrence in the future (Seneviratne and others 2012, 

Trenberth and others 2014). Despite this uncertainty, 

many of the General Circulation Models predict that 

some regions of the United States (e.g., the Southwest) 

may experience a greater frequency of severe droughts 

(Swain and Hayhoe 2015). When combined with greater 

air temperatures, droughts could have a greater impact 

on forests and ranges (Adams and others 2009, Allen 

and others 2010), even if severity and occurrence is 

unchanged in the future. The prospect of increasing 

frequency and severity of future droughts motivates a 

fresh synthesis of evidence for changes underway now, 

their cause, and how they may affect forest and range 

ecosystems and management responses.

Forest and rangeland ecosystems are inherently resilient 

to climate variability at time scales ranging from daily to 

millennia. This resiliency has ensured that ecosystems 

can endure short-term and minor climatic variation 

without substantial losses in structure and function. 

In areas where drought is common and ecosystems 

have some level of adaptive capacity (Breda and others 

2006, Mariotte and others 2013, Milbau and others 

2005), a key unknown is whether current species 

and associated ecosystem processes will be able to 

endure more severe (or different) droughts in the future. 

Tipping points may have already been reached in some 

ecosystems, with large-scale mortality resulting from 

“global-change-type” droughts (Adams and others 

2009, Breshears and others 2005) in forests in the 

Southwestern United States. Less is known in more 

mesic regions, where observational data on the impacts 

of historical droughts are limited (Klos and others 

2009); however, an increased frequency of episodic 

events such as severe droughts may have even greater 

impacts because some species are not as well adapted 

to increasing aridity (Pederson and others 2014). In this 

case, drought may favor more drought-tolerant species 

and alter successional pathways (Meinzer and others 

2013). In either case, it is likely that drought will be a 

major disturbance force in the future and will present 

challenges for natural resource managers as they deal 

with the implications of changing forest conditions and 

disturbance regimes. A better understanding of drought 

impacts on forest and rangeland values will help land 

managers anticipate responses and inform management 

actions that increase adaptive capacity.

The need to better understand current changes and 

to anticipate potential impacts of drought on U.S. 

forests and rangelands is addressed in this assessment 

by science leaders from Government agencies, 

national labs, and the academic community. The 

assessment is divided into three main components: 

(1) characterizing drought, (2) understanding the 

effects of drought on forests and rangelands, and (3) 

assessing the consequences of drought on forest and 

rangeland values. The first component, characterizing 

drought, provides a thorough analysis of how drought 

is quantified and provides metrics and approaches 

best suited for forest and rangeland ecosystems. The 

second component addresses direct effects on growth, 

mortality, and biogeochemical cycling processes, as 

well as indirect effects on wildfires and insect and 
11

CHAPTER 1

Understanding and Anticipating Potential Drought Impacts

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

pathogen outbreaks. The final component addresses 

impacts on water resources and economic and social 

systems. We developed inferences from the published 

literature that included results from direct observation, 

experiments, and modeling. Due to the uncertainty 

of future predictions of drought occurrence, we do 

not explicitly predict the impacts of future climate 

change on forest and rangeland ecosystems; however, 

observations from recent extended droughts in many 

regions of the United States may provide a realistic set 

of inferences that can be projected into the future.

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U.S. deserts: potential for increased wildfire and invasive annual 

grasses. Rangeland Ecology & Management 64: 471-478. 

Adams, H.D.; Guardiola-Claramonte, M.; Barron-Gafford, G.A. 

[and others]. 2009. Temperature sensitivity of drought-induced 

tree mortality portends increased regional die-off under globalchange-type drought. Proceedings of the National Academy of 

Sciences. 106(17): 7063-7066.

Allen, C.D.; Macalady, A.K.; Chenchouni, H. [and others]. 2010. A 

global overview of drought and heat-induced tree mortality reveals 

emerging climate change risks for forests. Forest Ecology and 

Management. 259(4): 660-684.

Amiro, B.D.; Barr, A.G.; Barr, J.G. [and others]. 2010. Ecosystem 

carbon dioxide fluxes after disturbances in forests of North 

America. Journal of Geophysical Research. 115: 1-13.

Andreadis, K.M.; Clark, E.A.; Wood, A.W. [and others]. 2005.

Twentieth-century drought in the conterminous United States. 

Journal of Hydrometeorology. 6: 985-1001.

Breda, N.; Huc, R.; Granier, A. [and others]. 2006. Temperate 

forest trees and stands under severe drought: a review of 

ecophysiological responses, adaptation processes and long-term 

consequences. Annals of Forest Science. 63(6): 625-644.

Breshears, D.D.; Cobb, N.S.; Rich, P.M. [and others]. 2005.

Regional vegetation die-off in response to global-change-type 

drought. Proceedings of the National Academy of Sciences. 102: 

15,144-15,148.

Cook, E.R.; Seager, R.; Cane, M.A. [and others]. 2007. North 

American drought: reconstructions, causes, and consequences. 

Earth-Science Reviews. 81(1): 93-134.

Cook, B.I.; Smerdon, J.E.; Seager, R. [and others]. 2014. Pancontinental droughts in North America over the last millennium. 

Journal of Climate. 27(1): 383-397.

Evans, S.E.; Burke, I.C. 2013. Carbon and nitrogen decoupling 

under an 11-year drought in the shortgrass steppe. Ecosystems. 

16:20-33. 

Goetz, S.J.; Bond-Lamberty, B.; Law, B.E. [and others]. 2012.

Observations and assessments of forest carbon dynamics 

following disturbance in North America. Journal of Geophysical 

Research. 117: 1-17.

Guardiola-Claramonte, M.; Troch, P.; Breshears, D. [and others]. 

2011. Decreased streamflow in semi-arid basins following droughtinduced tree die-off: a counter-intuitive and indirect climate impact 

on hydrology. Journal of Hydrology. 406(3-4): 225-233.

Hicke, J.A.; Allen, C.D.; Desai, A. [and others]. 2012. The effects 

of biotic disturbances on carbon budgets of North American 

forests. Global Change Biology. 18: 7-34.

Holden, Z.A.; Luce, C.H.; Crimmins, M.A. [and others]. 2012. 

Wildfire extent and severity correlated with annual streamflow 

distribution and timing in the Pacific Northwest, USA (1984–2005). 

Ecohydrology. 5(5): 677-684. 

Johnson, D.; Murphy, J.D.; Walker, R.F. [and others]. 2007.

Wildfire effects on forest carbon and nutrient budgets. Ecological 

Engineering. 31: 183-192.

Klos, R.J.; Wang, G.G.; Bauerle, W.L. [and others]. 2009. Drought 

impact on forest growth and mortality in the Southeast USA: 

an analysis using Forest Health and Monitoring data. Ecological 

Applications. 19(3): 699-708.

Knapp, A.K.; Smith, M.D. 2001. Variation among biomes in temporal 

dynamics of aboveground primary production. Science. 291: 

481-484. 

Littell, J.S.; McKenzie, D.; Peterson, D.L.; Westerling, A.L. 2009.

Climate and wildfire area burned in western U.S. ecoprovinces, 

1916-2003. Ecological Applications. 19(4): 1003-1021.

Mariotte, P.; Vandenberghe, C.; Kardol, P. [and others]. 2013.

Subordinate plant species enhance community resistance against 

drought in semi-natural grasslands. Journal of Ecology. 101: 

763-773.

Meinzer F.C.; Woodruff, D.R.; Eissenstat, D.M. [and others]. 

2013. Above- and belowground controls on water use by trees 

of different wood types in an eastern U.S. deciduous forest. Tree 

Physiology. 33(4): 345-356.

Melillo, J.M.; Richmond, T.; Yohe, G.W. 2014. Climate change 

impacts in the United States: the third national climate 

assessment: U.S. Global Change Research Program. 841 p. 

doi:10.7930/J0Z31WJ2. http://nca2014.globalchange.gov. [Date 

accessed: October 14, 2015].

Milbau, A.; Scheerlinck, L.; Reheul, D. [and others]. 2005.

Ecophysiological and morphological parameters related to survival 

in grass species exposed to an extreme climatic event. Physiologia 

Plantarum. 125: 500-512.

Pederson, N.; Bell, A.; Knight, T.A. [and others]. 2012. A longterm perspective on a modern drought in the American Southeast. 

Environmental Research Letters. 7(1): 014034.

Pederson, N.; Dyer, J.M.; McEwan, R.W. [and others]. 2014. The 

legacy of episodic climatic events in shaping temperate, broadleaf 

forests. Ecological Monographs. 84(4): 599-620. doi: 10.1890/13-

1025.1. [Published online: August 1, 2015].

Polley, H.W.; Briske, D.D.; Morgan, J.A. [and others]. 2013.

Climate change and North American rangelands: trends, 

projections, and implications. Rangeland Ecology & Management. 

66: 493-511. 

Prestemon, J.P.; Abt, K.; Gebert, K. 2008. Supression cost 

forecasts in advance of wildfire seasons. Forest Science 54(4): 

381-396.

Seager, R.; Tzanova, A.; Nakamura, J. 2009. Drought in the 

Southeastern United States: causes, variability over the last 

millennium, and the potential for future hydroclimate change. 

Journal of Climate. 22(19): 5021-5045.

Seneviratne, S.I.; Nicholls, N.; Easterling, D. [and others]. 2012.

Changes in climate extremes and their impacts on the natural 

physical environment. In: Field, C.B.; Barros, V.; Stocker, T.F. 

[and others], eds. Managing the risks of extreme events and 

disasters to advance climate change adaptation. A Special Report 

of Working Groups I and II of the Intergovernmental Panel on 
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Understanding and Anticipating Potential Drought Impacts

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Climate Change (IPCC). Cambridge, UK, and New York, NY, USA: 

Cambridge University Press: 109-230. 

Swain, S.; Hayhoe, K. 2015. CMIP5 projected changes in spring and 

summer drought and wet conditions over North America. Climate 

Dynamics. 44(9-10): 2737-2750. doi: 10.1007/s00382-014-2255-

9. [Published online: August 12, 2014].

Trenberth, K.E.; Dai, A.; van der Schrier, G. [and others]. 2014.

Global warming and changes in drought. Nature Climate Change. 

4(1): 17-22.

Weed, A.S.; Ayres, M.P.; Hicke, J.A. 2013. Consequences of 

climate change for biotic disturbances in North American forests. 

Ecological Monographs. 83: 441–470.

Westerling, A.L.; Gershunov, A.; Brown, T.J. [and others]. 2003.

Climate and wildfire in the Western United States. Bulletin of the 

American Meteorological Society. 84(5): 595-604.

Wilhite, D.A.; Buchanan-Smith, M. 2005. Drought as hazard: 

understanding the natural and social context. In: Wilhite, D.A., ed. 

Drought and Water Crises: Science, Technology and Management 

Issues. Boca Raton, FL: Taylor and Francis: 3-29.
CHAPTER 2

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID 83702.

N. Pederson is a Senior Ecologist, Harvard Forest, Petersham, MA 01366.

J. Campbell is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Northern Research Station (NRS), Durham, NH 03824.

C. Millar is a Paleoecologist, U.S. Department of Agriculture, Forest Service, Pacific 

Southwest Research Station (PSW), Albany, CA 94710.

P. Kormos is a Research Associate, U.S. Department of Agriculture, Agricultural Research 

Service (ARS), Boise, ID 83712.

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Science (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources, 

Raleigh, NC 27695. 

R. Woods is a Senior Lecturer, Faculty of Engineering, University of Bristol, Bristol, 

BS8 1TH, UK.

Characterizing Drought 

for Forested Landscapes 

and Streams

Charles H. Luce 

Neil Pederson

John Campbell 

Connie Millar 

Patrick Kormos 

James M. Vose 

Ross Woods
14

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

The changing nature of drought is a growing global 

concern (Cook and others 2015, Dai 2011, Seneviratne 

and others 2010, Sheffield and Wood 2008b, Trenberth 

and others 2014, Wilhite and others 2014). Drought 

can be a severe natural disaster with substantial social 

and economic consequences affecting large areas with 

extended durations (Wilhite and Buchanan-Smith 2005). 

Although it is clear that shifts in circulation patterns, 

energy for evapotranspiration, and air temperatures are 

changing in ways that enhance the consequences of 

drought, there is only weak consensus about the effects 

of climate change on drought occurrence (IPCC 2013, 

Seneviratne and others 2012, Trenberth and others 

2014). Some of that uncertainty stems from the complex 

nature of quantitatively defining drought, but also 

because some of the changes in drought characteristics 

are only partially reflected in traditional drought metrics 

[Palmer Drought Severity Index (PDSI) and the 

Standardized Precipitation Index (SPI)]. Furthermore, 

although these traditional metrics have adequately 

reflected the consequences of meteorologically derived 

moisture deficits on agricultural commodities and 

water supply, there is a poorer (although improving) 

understanding of how drought interacts with forests 

and rangelands and their associated aquatic habitats. 

Understanding the potential impacts of future drought 

on forests and rangelands requires knowledge of how 

droughts impact forest, shrub, and rangeland structure 

(covered in other chapters in this assessment) and how 

drought projections are characterized in the General 

Circulation Model (GCM) output.

The purpose of this chapter is to explore drought 

as a hydrometeorological phenomenon and reflect 

broadly on the characteristics of drought that influence 

forests, rangelands, and streams. It is a synthesis of 

understanding about drought processes, hydrology, 

paleoclimatology, and historical climate variability, 

and how this understanding can help predict potential 

future droughts and their consequences to forests and 

rangelands. It describes alternative approaches for 

characterizing drought and highlights additional work 

that could inform projection and adaptation for future 

droughts.

What Is Drought?

Drought is a lack of water. This simple wording implies 

potentially complex stories. The most important 

implication is that drought is characteristic of time, not 

of place. A place can be dry or wet, but droughts occur 

in given locations over time. For example, the Sonoran 

Desert may have a lack of water for many purposes, 

but conceptually it has just the right amount of water 

for the Sonoran Desert, and it occasionally experiences 

droughts. Wet places, like the coastal rain forests in 

Washington State, also experience droughts when there 

is an unusually dry summer. Consistently dry seasons 

would not merit the designation of “drought” in and 

of themselves; however, variations in how dry or long 

the dry season is from year to year are relevant. In 

places like the Western United States, where there is a 

coincidence of the dry season with the growing season 

every year, it does not make sense to frame summer as 

a “drought” so much as to note the seasonal aridity of 

the location (Seneviratne and others 2012, Wilhite and 

Buchanan-Smith 2005).

Although drought is generally defined from a climatic 

perspective (precipitation levels that are much 

lower than the annual average), short-term moisture 

fluctuations also provide important ecological context. 

A wet period leading to a vegetation flush, followed 

by a long dry spell, for instance, may not constitute 

a “drought” relative to long-term averages, but the 

inability to meet the temporarily increased water 

demand would nonetheless represent a meaningful 

drought. From the perspective of a plant, it may look 

like a temporary enhancement of seasonal aridity 

contrasts. An example of this is seen in fire risks 

in rangeland ecosystems where wet springs can 

produce an overabundance of fine fuels from invasive 

annual grasses (Littell and others 2009, Swetnam 

and Betancourt 1998, Westerling and others 2003). 

Similarly, such fluctuations have been tied to forest 

mortality, with timing having an important influence on 

outcomes (Anderegg and others 2013).

This descriptive definition also speaks to a purpose 

for water. Lack of water is most relevant when water 

requirements for sustaining terrestrial and aquatic 

ecosystems or providing for human uses cannot be 

met. In natural ecosystems, those requirements broadly 

relate to climatological expectations (in a statistical 

sense) for water supply. Similarly, in rational agricultural 

management, climatological expectations should 

still provide a basic norm for distinguishing drought 

conditions, although sometimes drought is claimed 

when slightly dry conditions endanger marginally suited 

crops. Generally, drought is perceived as a concern 

during the growing season or warm season, as these 

are when there is a demand for water. However, 
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droughts can have substantial ecological consequence 

related to lack of snow cover, particularly for wildlife 

(McKelvey and others 2011) or plants that are protected 

from cold extremes by a layer of snow.

Drought Classification

Most of the indices applied to classify drought are 

tied to common meteorological measurements, like 

precipitation and temperature, because these are widely 

available with relatively long records. The long records 

make it possible to compare particular precipitation 

amounts or water-balance estimates to the local 

climatological distribution, in essence gauging risk or 

probability levels of current meteorological events. The 

meteorologically based indices are commonly applied 

for drought forecasting based on weather forecasts, 

given that weather is the most fundamental driver 

and also the most fundamental uncertainty in drought 

estimation. Despite common application, there is 

some concern about the utility of drought indices in 

understanding conditions related to changes in land 

cover, land use, or climate (Alley 1984, Sheffield and 

others 2012).

The context of utility or need for water frames much 

of the traditional way of defining and describing 

drought. Drought is most commonly thought of in 

terms of the harm it can induce. It is broadly seen as 

one of the most potentially severe natural disasters 

in terms of either human lives or capital loss because 

it covers large areas and can lead to famine for large 

populations (Wilhite and Buchanan-Smith 2005). 

Drought has generally been framed in four classes or 

“types” (Wilhite and Glantz 1985): (1) meteorological 

drought, (2) hydrologic drought, (3) agricultural 

drought, and (4) socioeconomic drought (table 2.1). 

These four classes are not mutually independent, 

but refer to different ways to measure, identify, or 

conceptualize drought conditions. Almost all types of 

drought relate to meteorological conditions leading 

to a lack of water, such as a lack of precipitation or 

excess demand from evapotranspiration. Hydrologic, 

agricultural, and socioeconomic drought are filters 

placed on meteorological drought to frame how they 

affect human demands and values for water, ranging 

from food production to electrical power production, 

recreation, and wildlife management. Generally the 

context is economic, although environmental benefits 

of water are recognized as well. They also frame 

different time scales of response to meteorological 

forcing. Most of these drought types frame drought 

as an event. In this framing, a drought is a type 

of disturbance, or even disaster, with a distinct 

occurrence. This framing is particularly relevant to 

crops of limited lifespan, seasonal cycles of water 

Table 2.1—The four drought classes

Drought class Primary focus Estimation

Meteorological Dry weather Indices built from weather station or 

weather forecast information targeted 

toward soil moisture and agricultural or 

hydrologic drought. Weather changes 

rapidly, but indices aggregate weather 

over time.

Hydrologic Streamflow and 

reservoir levels

Measured or modeled runoff and 

reservoir levels. Some meteorological 

drought indices target this particular 

outcome.

Agricultural Productivity and 

survival of crops

Measured or modeled crop yields. 

Some meteorological drought indices 

target this particular outcome.

Socioeconomic Economic outcomes 

of drought

Measured and modeled financial 

consequences of water supply or 

agricultural production deficits.
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demand (municipal supply, hydropower demand, 

water-oriented recreation), and other activities 

where short-term interruptions in water supply are 

economically relevant (e.g., manufacturing).

Meteorological Drought

Meteorological drought definitions refer to atmospheric 

components of the water balance, precipitation and 

evapotranspiration, where low precipitation and high 

evapotranspirative demand lead to a relative lack of 

water. In practice, estimates of these components 

or proxies for their estimation (e.g., temperature) are 

generally used. Despite the name, meteorological 

drought metrics use modeling or simple logic to 

reframe short-term meteorological measurements into 

indices of impacts to terrestrial and aquatic systems. 

Meteorological drought can be framed strictly in terms 

of the amount of precipitation over a time period, as 

with the SPI (McKee and others 1993), or processed 

with temperature information to estimate a soil water 

balance, as in the PDSI (Palmer 1965). The KeetchByram Index model (Keetch and Byram 1968) has 

a similar conceptualization (though with feedback 

between moisture level and loss rate) directed towards 

vegetation and fuel moisture levels. Details of these 

indices are discussed later in this chapter.

Hydrologic Drought

Hydrologic drought is focused more directly on water 

available as streamflow or in surface or near-surface 

storage, such as reservoirs or shallow aquifers. While 

hydrologic drought follows from meteorological drought, 

its measurement or estimation focuses primarily on 

the various uses of streamflow or reservoirs, such 

as aquatic habitat, irrigation, hydroelectric power 

generation, or recreation. There is a temporal lag 

between unusually dry meteorological conditions and 

actual stream and lake levels, and factors other than 

those indexing meteorological drought may influence 

actual outcomes for streams, shallow groundwater, 

lakes, or reservoirs. For instance, precipitation intensity 

or its distribution in time can markedly influence its 

potential for generation of runoff in both the short and 

long term. Multiple brief or small rainfall events may 

increase the amount of precipitation received, but much 

of that water would likely be returned to the atmosphere 

through subsequent evaporation after being intercepted 

in trees or only shallowly penetrating the soil. On the 

other hand, focusing an equivalent amount of water into 

a single, brief storm with high intensity may result in 

increased runoff but little recovery in soil or vegetation 

moisture levels.

For some purposes, a lack of streamflow represents 

a drought more than a lack of precipitation. A lack of 

water can yield profound impacts for stream fishes, 

as it affects volume of available fish habitat, stream 

temperature (Isaak and others 2012), and food supply 

to fishes (Harvey and others 2006). In western U.S. 

mountains, runoff from accumulated snowpacks feeds 

reservoirs and irrigation to downstream farms. Although 

these farms may get occasional rain in the summer 

months, that precipitation amount may never really be 

sufficient to support crops. In such a case, the local 

precipitation or water balance is not as relevant as the 

potential hydrologic drought of the stream providing 

irrigation water.

Simple meteorological indices of drought do not 

consistently predict the streamflow consequences of 

a drought. While there is a connection between a lack 

of precipitation and a lack of streamflow, there are 

subtleties of shift in precipitation characteristics, or even 

of changes in vegetation or soil characteristics that can 

change the runoff efficiency of precipitation events 

that occur within the context of a prolonged drought 

(Guardiola-Claramonte and others 2011, Potter and 

Chiew 2011). There can also be mismatches between 

return intervals of precipitation amounts (or index 

values) and streamflow volumes (Potter and Chiew 

2011), reflective of the complexity of runoff generation 

processes.

Agricultural Drought

Agricultural drought, also termed soil moisture drought 

by Seneviratne and others (2012), is tied to productivity 

and mortality of crops. It is functionally related to the 

soil moisture reservoir. Once precipitation has stopped, 

soils dry through evaporation at the surface and via 

evapotranspiration of water through the crop. The 

contribution of direct evaporation at the surface to 

total evapotranspiration declines as the soil dries. As 

the soil moisture content drops, roots cannot uptake 

water as rapidly, and plant productivity falls off as 

stomata remain closed for a greater fraction of the time. 

Eventually, the water in the soil is bound so strongly by 

capillary and osmotic potentials that plant roots cannot 

extract more water. Crops can die before this level is 

reached simply if productivity falls below the needs for 

maintenance respiration. Metrics of agricultural drought 

(PDSI) were developed for annual crops or vegetation 

managed as an annual crop. As such, they are best 

suited for shallow-rooted plants and may overestimate 

drought experienced by deep-rooted perennial forest 

and shrub species.
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Socioeconomic Drought

Socioeconomic drought follows from both agricultural 

and hydrologic drought. Agricultural losses from 

drought represent a fairly direct economic impact, 

but this also cascades into lack of materials for 

agricultural manufacturing and support industries and 

services. Similarly, a lack of water for municipal supply, 

manufacturing, irrigation, hydroelectric production, 

or recreation can reverberate through the economy. 

These economic impacts may substantially lag 

behind the meteorological drought event that triggers 

socioeconomic consequences. The relationship between 

drought and its economic consequences also varies with 

associated historical decisions (chapter 11). This complex 

interplay of drought, environmental consequences, 

and impacts to humans, followed by human-mediated 

responses to drought (e.g., technological advances 

and altered land values), leads to broadening economic 

ramifications over time and space.

Drought Influences 

on Forest and 

Stream Ecosystems

For forest and stream ecosystems, meteorological 

and hydrologic drought frameworks are useful for 

characterizing impacts of a given drought event. For 

example, meteorological or hydrologic drought may 

presage or correlate to fire events (chapter 7) or 

insect outbreaks (chapter 6). Most of the work in later 

chapters and information on drought changes in this 

chapter relate to the common metrics above. However, 

it is worthwhile to also reflect on ways that drought 

influences forest ecosystems outside of the traditional 

harm-oriented framework. It serves as context for 

drought metrics, trends, and projections described later.

Forests offer a unique challenge to the traditional 

framing of drought because they persist over long time 

scales. Forests have adapted to droughts both through 

their resilience to drought effects and resistance to 

drought occurrence. While fires, insect outbreaks, and 

other forest mortality events are tied to drought, it is 

generally only the most severe droughts that produce 

large-scale or landscape-scale changes. Most droughts 

reduce productivity or carbon fixation in trees rather 

than kill them. As the climate changes, drought may 

become a stronger driver for changes in vegetation 

species composition and life form (shrub, woodland, 

forest) (Dale and others 2001, Jentsch and others 

2007, Luce and others 2012). Reframing drought as a 

driver that determines relative fitness among species 

adds new context for characterizing drought. To 

address this, we can draw on ecological theory and our 

understanding of the hydrometeorological process to 

assess how long-term changes in drought climatology 

(frequency, severity, or spatiotemporal scaling) might 

drive large-scale changes in vegetation.

In addition to drought impacts on terrestrial vegetation, 

there are impacts to forest aquatic ecosystems. 

Forests are generally the largest source for high-quality 

water supplies, and they provide extensive habitat for 

coldwater fishes (Rieman and others 2003). Droughtrelated changes in forests cause changes in runoff 

generation, with the potential for immediate negative 

impacts on stream ecology. However, drought is also 

a fundamental driver of instream ecological processes, 

and some highly prized aquatic species are present 

because they are better adapted to drought-related 

effects to streams and surrounding forests than are 

other species. Changes in drought characteristics may 

consequently be a driver of long-term and large-scale 

changes to instream ecological processes. Fish species 

are substantially less long-lived than trees, but presence 

of a given population in a stream is a comparably 

persistent aspect of the problem. The interaction of 

drought with local population and metapopulation 

dynamics is a more important consideration than 

losses from a single generation. For example, increased 

drought-related disturbance may promote migratory 

life histories over resident life histories (Dunham and 

others 2003). Another example is the range of drought 

adaptations of some fishes in the Great Plains (Falke 

and others 2011, Fausch and others 2002). Local 

extirpations of some fishes could result if small streams 

become both more unpredictable in low flows and less 

productive (reducing the potential for migratory life 

histories).

Ecological Drought 

Characterization

The impacts of dry conditions on ecological processes 

are about tradeoffs. Some biota benefit from drought 

primarily because other biota are more negatively 

impacted. This view of drought ecology—where 

drought stress is viewed as a driver of ecosystem 

processes—is part of what makes application of 

traditional drought metrics difficult. Although indices 

with single values are easier to present and apply in 

quantitative analysis, ecological drought characterization 

is more complex and multidimensional. Some of the key 

dimensions are:
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lSeverity–defined as degree of moisture deficit

lFrequency–level of deficit, alternatively probability

lTemporal patchiness–autocorrelation in time that 

incorporates duration and short-term variability

lSpatial coherence–or spatial distribution across the 

landscape

lCorrelation with other factors (e.g., season or 

temperature)

Some current metrics conflate one or more of the 

aforementioned dimensions. Calculation of PDSI, 

for example, incorporates lack of precipitation, air 

temperature, and duration of an event. SPI is a simple 

metric of severity, but the complete range of options 

for SPI values with varying temporal footprints 

reveals that it also can offer temporal autocorrelation 

information. It is likely that drought cannot be measured 

or characterized along any one of these dimensions 

absent some others; however, exploring the different 

dimensions can be informative for explaining 

component contributions in part for ecological drought.

The most natural and direct measures of drought 

severity for forest and stream ecosystems are probably 

reflected in measures such as soil moisture, streamflow, 

or fuel moisture. These measures have a particular value 

at a given time, but they reflect spatial and temporal 

integration of precipitation and evapotranspiration. 

Consequently, there is some need to explicitly recognize 

the role of time if only meteorological information is 

used. A day without precipitation occurs often, but 

multiple days without precipitation cause drier soils and 

reduced streamflow. Nonetheless, we can see that 

with an appropriately informative footprint (discussed 

briefly below), variations in the amount of precipitation 

received or precipitation less evapotranspiration are 

informative quantities.

Frequency of a given level of severity is critical in 

understanding the ecological role of drought because 

the relationship of the frequency of mortalityinducing drought to generation or recovery times is a 

fundamental descriptor of ecosystem dynamics. At one 

end of the spectrum, species that mature more slowly 

than the frequency at which mortality-inducing weather 

events occur are not well fit to the local climate. At 

the other end, species that take advantage of frequent 

disturbance may not compete well with species that 

invest toward longer term gains when disturbance is 

infrequent. In most cases, disturbances will occur within 

a species lifetime, and there are different strategies 

and adaptations related to different frequencies. 

Relationships between frequency and severity are 

commonly embedded within those adaptations. It is 

unusual to have severe fire or insect outbreaks on a 

frequent basis, simply because it is hard to regrow 

adequate fuel or food to sustain the next severe event. 

Although fire, pathogen, and insect outbreaks are 

general examples in this area, trees adapted to lowproductivity arid sites, such as bristlecone pine (Pinus 

aristata), offer another example where the isolation 

offered by frequent severe drought builds a degree of 

resilience to other mechanisms of mortality spread by 

abundance of neighbors.

The concept of temporal patchiness is a metric to 

describe how slowly moisture states vary. Broadly, high 

year-to-year autocorrelation in moisture reflects longterm dry states, whereas low autocorrelation reflects 

high variability in moisture states over short timeframes. 

Both ends of this spectrum can have substantial 

impacts on ecological processes and disturbance 

regimes. For example, high contrasts in moisture over 

relatively short (seasonal to interannual time scales) can 

increase the severity of drought-related stressors such 

as fire or insects. Such is the case in shrublands with 

wet winters and springs that promote heavy growth of 

annual grasses (e.g., Bromus spp.) and lead to more 

severe and larger fires during the following dry summer 

(Abatzoglou and Kolden 2011, Littell and others 2009). 

Substantial growth in a forest in a wet year contrasted 

to dry conditions the next year can lead to increased 

moisture stress because of increased leaf area. While 

duration is well captured by common drought indices, 

the high contrast risk is not, and the two are related in 

a given climate and soil. While the former is important 

to critical water supply levels and agricultural crops, the 

latter has greater context in less regulated systems.

Meteorological drought has substantial spatial 

coherence, with a footprint of much greater scale than 

is typical for landscape ecology. Severe meteorological 

droughts, sometimes termed “megadroughts” may 

encompass multiple regions of the United States at 

a given time (e.g., Coats and others 2014, Cook and 

others 2014a). While this scale has potential importance 

for distribution of fire suppression equipment or 

response to insect outbreaks, more-local scales are also 

relevant because a particular meteorological drought 

may play out differently within a landscape. North-facing 
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slopes retain moist conditions longer into the growing 

season than south-facing slopes, which is reflected in 

productivity and plant species. One consequence is that 

fire severity can vary substantially across topographic 

position, such as aspect or riparian proximity (Dillon 

and others 2011, Dwire and Kauffman 2003). The 

outcome for vegetation communities is that the spatial 

scales of drought-related mortality are related to the 

grain of topographic variation, or hillslope facets, in 

historical examinations (Hessburg and Agee 2003). The 

severity of the meteorological drought can, itself, have 

some influence on this patchiness, and topographic 

relationships to fire severity are damped in the driest 

years (Dillon and others 2011).

Correlation of drought to other meteorological 

characteristics is an increasingly important area of study. 

If we look through the list of key dimensions, there is a 

sense of increasing levels of information or organization 

(sensu Blöschl 1996) of outcomes for drought events. 

At the basic level, there is the question of how dry it 

is (severity), followed by how dry an event is relative 

to other events (probability/frequency), followed by 

how quickly or slowly the moisture levels transition 

(temporal patchiness), and how different places within 

a landscape experience a given meteorological drought 

(spatial coherence). The next level of organization is 

how drought might relate to other factors of importance 

in ecology. In the following section, we discuss the 

linkage between temperature and drought because it 

has substantial relevance to the broad discussion on 

climate change and drought (Dai 2011, Sheffield and 

others 2012, Trenberth and others 2014), particularly in 

the context of forest ecology (Adams and others 2009, 

Allen and others 2010, Breshears and others 2005).

The causal relationship between temperature and 

drought arises from interactions mediated by solar 

heating. Clearly, warmer air has lower relative 

humidity (given a fixed specific water content in the 

air), and warmer air has the capacity to impart more 

sensible heat to the energy balance. However, the 

great majority of the heat in the energy balance is 

incoming solar radiation. Some solar heating goes to 

evaporating water and some goes into heating soil, 

vegetation, and air. As a consequence, air temperature 

and evapotranspiration are correlated simply because 

they share the same driver (i.e., solar radiation), not 

because air temperature substantially adds to the 

energy available for evapotranspiration. This makes 

temperature a simple index for framing both the energy 

available for evapotranspiration and the capacity of air 

to hold additional moisture. For example, temperature 

is a variable in the Thornthwaite equation (Thornthwaite 

1948), which is used in calculation of the PDSI. When 

there is less water available (due to a lack of antecedent 

precipitation), more of the incoming solar energy goes 

into raising temperature; however, when conditions 

are dry, the increase in temperature is at the expense 

of evapotranspiration. Energy goes into warming, 

not evaporating. Under dry conditions, temperature 

becomes an index of the lack of water available for 

evapotranspiration. Thus, within historic contexts, 

temperature can be used as an index of dryness: dry is 

warm, and warm is dry.

Under a changing climate, in contrast, temperature will 

rise independently of aridity. Warmer temperatures 

will result from increased atmospheric emissivity and 

a changed energy balance of the air. Net radiation 

will increase, slightly increasing the energy available 

for evaporation, but the relationship between relative 

humidity (or vapor pressure deficit) and temperature 

for warming on that slow of a scale will not be the 

same as it is in current empirical contexts. In short, the 

correlation between air temperature and drought will 

still exist, but its value will not be in indexing drought 

conditions in relation to current conditions.

Instead, warmer temperatures paired to drought will 

represent a greater challenge for plants to cope with 

drought (Adams and others 2009). This context of 

drought being warmer has been termed “global-changetype drought” (Breshears and others 2005) to reflect 

the idea that whether or not “drought” is worse under 

a changing climate, the consequences of a given level 

of drought could be worse in combination with warmer 

temperatures. Because warmer temperatures elevate 

metabolism and respiration, a higher productivity will 

be required to match the demand. As plants shut down 

during moisture stress, they will exhaust carbon stores 

more quickly, and survival times between wetting 

events will shorten. The physiological mechanisms 

underlying drought mortality are discussed in chapter 3.

The correlation of drought to the season in which it 

occurs is another important characteristic that may 

also shift with warming. For example, if the period of 

common drought corresponds to the warm season 

(growing season), drought effects will be more severe, 

in a broad sense. Expansion of the growing season as 

temperatures warm could draw soil water down sooner 

as well, yielding deeper dryness in the soil earlier in 

the growing season; this would effectively increase 
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the duration of the summer drought and have potential 

consequences for wildfire (e.g., Westerling and others 

2006). Where precipitation is more abundant during the 

growing season, the susceptibility to drought is related 

to interruptions in that precipitation supply.

Measures of Drought

The drought types mentioned earlier offer some 

distinction for classifying drought prediction tools. 

Some measures target characterizing drought for broad 

purpose based primarily on weather measurements, 

while others target understanding hydrologic drought. 

Given the general interest in forecasting drought, 

both approaches are based on meteorological 

measurements and meteorological model outputs. 

Meteorological drought indices are either directly tied to 

the measurements or placed in a context for convoluting 

precipitation and temperature with time to give a 

mixed drought and exposure index. Hydrologic drought 

is necessarily more local in nature as it depends on 

characteristics of the basin of concern. Some reporting 

tools, such as the U.S. Drought Monitor, use a blend 

of hydrologic and meteorological drought metrics along 

with expert guidance.

Fundamentally, every kind of drought is meteorological 

in nature, but outcomes are shaped through local 

topographic, geologic, and biotic filters. In so far as 

models correctly reflect the hydrologic processes of 

interest, weather forecasts or stochastic simulations 

contingent on seasonal climatological forecasts can 

provide useful information on potential outcomes. We 

briefly discuss the most common ones here (see Hayes 

and others 2011 for a more thorough listing).

Meteorological Drought Metrics

Three of the most common metrics in this class are 

the Standardized Precipitation Index (SPI) (McKee and 

others 1993), the Palmer Drought Severity Index (PDSI) 

(Palmer 1965), and the Keetch-Byram Drought Index 

(Keetch and Byram 1968). Although these metrics 

theoretically address potential outcomes of drought 

(such as soil moisture, streamflow, or crop productivity 

and mortality), they are approximate models.

The SPI is a relatively simple approach to characterizing 

a precipitation anomaly (McKee and others 1993). 

Precipitation totals are calculated for a given window 

of specific dates over a series of years. A cumulative 

density function (CDF) of the values is computed and 

the quantiles are mapped to a normal CDF, allowing the 

probability of exceedance above and below the mean 

to be translated into approximate standard deviations 

of departure. The index is only applicable locally, and it 

is relative to the mean precipitation over the period of 

interest.

The PDSI and related derivatives are conceptually 

related to the water balance of a relatively thin, twolayer soil incorporating estimates of evaporation 

and runoff. The precipitation component is relatively 

straightforward, and runoff is computed based on the 

water-holding capacity of the soil column (porosity at 

field capacity). Evapotranspiration (ET) is drawn from 

the two layers of soil independently, with the thin 

top layer being available for direct evaporation, while 

the second soil layer retains water for transpiration. 

ET is calculated based on air temperature using the 

Thornthwaite method (Thornthwaite 1948). Because 

drier soils evapotranspire less than moist soils, there 

is a seasonal adjustment to the Thornthwaite estimate 

for well-watered soils. This seasonal adjustment does 

not respond to actual evolution of conditions, however, 

and close inspection reveals the adjustments to be 

relatively minor. A limit is ultimately placed on ET to 

prevent violation of the mass balance. To calculate the 

index, a convolution of the soil moisture estimated using 

this method over time provides a metric that combines 

both dryness and the length of time plants are exposed 

to the dryness. These calculations are then treated 

similarly to the SPI to derive a local dryness index.

The Keetch-Byram Index (Keetch and Byram 1968) is 

absolute in nature and not locally indexed. It is based on 

an exponential decay conceptualization of soil moisture 

in fuels. Precipitation less interception (constant) rewets 

fuels, and loss each day is calculated (in tables) as a 

function of the daily air temperature and the previous 

day’s drought index. As the index approaches its driest 

extreme, the effect of further drying is diminished 

asymptotically.

Hydrologic Drought Metrics

Hydrologic drought metrics are generally based upon 

measurements of streamflow. Hydrologic drought may 

be defined as uncharacteristically low streamflows; 

however, values depend heavily on the averaging 

period for the quantification of flows (Vidal and others 

2010). For example, annual-scale hydrologic drought is 

quantified by comparing total annual flow values among 

a series of years and finding quantiles of the distribution. 

Because there is a pronounced annual cycle, this 

averaging scale can be useful for a range of purposes. 
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For consequences that manifest at shorter time scales, 

shorter averaging periods are necessary and can be 

characterized by one of many methods of quantifying 

how low flows are in a particular low-flow period. In 

places with noted seasonality in runoff, such as those 

associated with seasonal precipitation or snowmeltdominated runoff, season-scale averages can suffice. 

In places where precipitation and runoff do not show 

pronounced seasonality, a shorter time-scale average 

has greater utility.

Differences in seasonality related to presence and 

absence of snow and temperature-precipitation 

correlation form the basis for a comprehensive 

classification of hydrologic drought types (Van Loon and 

Van Lanen 2012). One example dichotomy is flows that 

are low because the warm season has low precipitation 

versus flows that are low because the precipitation 

is frozen in winter. Ecological considerations of how 

aquatic species respond to low flows in warm-dry 

versus frozen seasons might require examining these 

two types of hydrologic drought separately.

Common formal quantification of low flows occurs in 

two metrics: the 7Q10 metric and the return intervals of 

given percentile on the flow duration curve. The 7Q10 

is the minimum weekly flow (drawn from the period 

of interest, such as winter or summer) in each year 

with a return period of 10 years. For example, with a 

record length of 20 years, the second to the lowest of 

the observed annual weekly minimum flow would be 

the 7Q10. Flow duration curves define the quantiles 

of flow in each year, and the 20th percentile daily flow 

would be that flow that is exceeded in 80 percent of the 

year (i.e. 292 days have higher flows, and 72 days have 

lower flows in that year). That value can be sampled 

from each year, and comparison can be made by way 

of quantiles of the distribution again (the 5- or 10-year 

return period, for example).

Physically Based Hydrologic Models as Metrics

Advances in computing have resulted in development 

of more computationally intensive, physically based 

hydrological models, which, like their computationally 

simpler predecessors, estimate soil moisture content. 

Although there is greater expectation or promise for 

precision and transferability, some of the promise of 

such models has yet to be realized (Blöschl and others 

2013). Despite the availability of such models and 

example applications (e.g., Sheffield and Wood 2007), 

much work is still focused on use of common (less 

computationally intensive) drought metrics. Although 

there is a range of reasons for such choices, a key 

point is that the basic inputs of precipitation and radiant 

energy inputs (or proxies) shared in common across 

various models and metrics means that the outputs 

are relatively well correlated (Williams and others 

2014), making the indices a more practical and efficient 

approach.

This capacity to use indices in a correlative manner, 

however, may limit the advancement of causative 

modeling. Although short-term (within a year) drought 

forecasting is conceptually intended to look at potential 

future outcomes (e.g., river levels, soil moisture 

levels, crop mortality, or fire danger), the development 

and validation of the historical/conceptual drought 

forecasting models have not focused on prediction 

of these values, per se; rather, they have focused on 

correlation between the indices and local outcomes. 

This leaves us with the strongest predictive capacity 

for droughts that have been observed in the past, 

without necessarily providing the best information for 

predicting drought consequences under a changed 

climate. Identifying and revising those parameterizations 

within physically based models that intrinsically 

rely on empirical relationships could help advance 

understanding of drought risks in a changing climate.

Because of their more comprehensive set of 

calculations, more detailed water-balance models blur 

the line between meteorological drought forecasting 

and hydrologic drought forecasting. These models offer 

a more flexible approach in estimating persistence of 

moisture availability; therefore, they may eventually 

become more useful than current indices for 

characterizing forest-related drought.

Relationships Between Meteorological 

Drought and Hydrologic Drought

Although both are referred to as “drought,” the 

relationship between meteorological drought and 

hydrologic drought is not linear. Complex interactions 

among changes in precipitation, evapotranspiration, 

and streamflow (particularly at the extremes) result in 

lags and nonlinearities in responses. Understanding this 

complexity has similarities to understanding ecological 

consequences of meteorological drought.

While the basics are fairly clear (less input generally 

means less output), there are a number of aspects 

that make the problem more complex, and defined 

relationships offer some use in prediction of places 

and times of relative sensitivity. A number of statistical 
22

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

and physically based modeling tools have been 

applied to the problem of relating weather to low 

streamflows (Laaha and others 2013). Analysis of the 

relationship is commonly framed within a sensitivity 

or similar modeling framework, such as the Budyko 

(1974) relationship between precipitation, net radiation 

(energy for evapotranspiration), and how precipitation 

is partitioned into evapotranspiration versus runoff, 

or simpler sensitivity/elasticity frameworks (sensu 

Schaake 1990) that empirically relate precipitation and 

temperature to streamflow.

The effects of precipitation variability on streamflow are 

fairly pronounced (Milly and Dunne 2002); generally, 

when there is less precipitation there is less runoff 

(e.g., fig. 2.1). Thus, meteorological drought results 

in hydrologic drought; however, the lag in streamflow 

response after precipitation stops means that hydrologic 

drought integrates precipitation inputs over time, and 

the lowest streamflows result from some combination 

of low initial soil/groundwater recharge, a long period 

since last precipitation, and evapotranspirative demand. 

Rapid evapotranspiration, at an event time scale, 

contributes to reduced flows in many circumstances, as 

it makes water unavailable for runoff. However, at long 

time scales (e.g., annual), evapotranspiration in many 

places is functionally limited by available soil moisture 

and tends to positively co-vary with streamflow 

(Milly and Dunne 2002). In other words, years with 

hydrologic drought may also experience reduced 

evapotranspiration.

One approach to understanding the relationships 

between meteorological drought and hydrologic drought 

is with direct correlations between flow data and indices 

such as PDSI, SPI, and variants (e.g., Haslinger and 

others 2014). These kinds of relationships often work 

best in rainfed agricultural catchments with limited 

snowpack, similar to validations where they were 

developed (Palmer 1965). Lag times from substantial 

snow accumulation or deep groundwater weaken 

relationships with these indices.

The water balance provides another approach, at 

least at interannual time scales. Using the water 

balance of soil (which is conceptually thin enough that 

we can ignore storage changes at interannual time 

scales) where Q represents both surface runoff and 

recharge to groundwater (from which it is assumed 

little evapotranspiration occurs, but which could store 

substantial recharge), we can write:

P = Q + ET (1)

Precipitation (P) is the largest term and is split into Q

and ET. When P goes down, both Q and ET tend to 

decrease as well. However, we expect the fraction of 

precipitation allocated to Q versus ET to be a function 

of the ratio of net radiation (energy available for ET) to 

P (Budyko 1974, Milly and Dunne 2002). The general 

expectation is that as conditions become drier, a greater 

fraction of the P becomes ET (fig. 2.2), exacerbating 

hydrologic drought as meteorological drought 

progresses.

Figure 2.2 describes the Budyko relationship, where 

the red and blue lines represent physical limits related 

to energy and water availability for evaporation. The 

bottom axis is an aridity index, which is the ratio of the 

incoming energy (which can evaporate water if it is 

available) to precipitation (normalized by the latent heat 

of evaporation to put it in energy units). The left axis is 

the ratio of actual evapotranspiration to precipitation. 

Note that while the bottom axis can range to large 

values (lots of energy and little water), the vertical axis 

is constrained to be less than one because you cannot 

evaporate water you do not have. The curved line is 

Budyko’s (1974) empirically derived relationship from 

a large number of rivers around the World. The black 

and gray points represent potential river basins one 

might find. Some rivers plot above the curve; others, 

particularly the gray ones, plot below. Points below the 

line partition more water into runoff than average, while 

points above the line evaporate more water. Variations 

2000

1750

1500

1250

1000

750

500

250

0

Water (mm)

1960 1970 1980 1990 2000 2010

Precipitation Streamflow Evapotranspiration

Figure 2.1—Streamflow variability as related to variations in 

precipitation and evapotranspiration at Hubbard Brook in the 

Northeastern United States.
23

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

above and below the line relate to factors, such as those 

discussed below, that enhance partitioning into runoff 

versus evapotranspiration.

The related climate elasticity of streamflow approach 

(Sankarasubramanian and others 2001, Schaake 1990) 

uses changes in precipitation or temperature to form 

estimates for annual streamflow changes. This method 

uses the relative (and interactive) roles of temperature 

and precipitation to understand variations in and 

mediation of streamflow (Fu and others 2007, Harman 

and others 2011, Potter and others 2011, Vano and 

others 2012).

In addition to aridity, a number of factors influence the 

partitioning of water into evapotranspiration rather than 

runoff/recharge (Woods 2003). A primary example is 

the soil depth or rooting depth. The more soil there is to 

hold water for trees to utilize, the greater the proportion 

that tends to evapotranspire. Similarly, coarse soils and 

steep slopes—both of which promote drainage of the 

soil profile—tend to reduce evapotranspiration. When 

more precipitation falls in cool months, interception 

losses are smaller than when it falls in warm months 

(Wolock and McCabe 1999). Runoff from basins 

where snowmelt dominates tends to be generated 

more efficiently than rain-related runoff (Berghuijs and 

others 2014). Forest cover and tree species may vary 

independent of the slightly more static features, and 

they can exert substantial control on partitioning as 

well (e.g., Zhang and others 2001). Soil and vegetation 

controls are covered in more detail in chapter 10, but 

are mentioned here to illustrate potential controls on 

drought responses related to site characteristics.

Changes in precipitation characteristics with prolonged 

or extensive droughts could be important as well. 

Circulation changes associated with large-scale drought 

may promote variations in intensity, duration, and 

volume statistics for storms; these variations alter a 

storm’s runoff generation potential (Potter and Chiew 

2011). For example, if storms have similar frequency, 

but each delivers less water, a greater fraction may be 

lost to interception.

Spatial differences also play a role in the relationships 

between drought characteristics and streamflow 

characteristics, and these differences have been 

explored through hydrologic modeling approaches. For 

example, in the Western United States, framing the lowflow response in terms of both the annual recharge and 

the length of the dry season can highlight the influence 

of bedrock geology on late summer low flows (e.g., 

Tague and Grant 2009). The sensitivity of low flows 

to timing and amount of recharge is a function of how 

much groundwater levels are drawn down through a 

given volume of evapotranspiration or runoff. A range 

of recession analysis techniques have been applied 

for periods without precipitation (e.g., Kirchner 2009, 

Tallaksen 1995).

There are a number of ways in which meteorological 

extremes may ultimately manifest in low streamflows or 

similar hydrologic outcomes (Van Loon and Van Lanen 

2012). Increasingly, physically based hydrologic models 

are being applied to evaluate historical and potential 

future droughts (e.g., Sheffield and others 2004) as 

opposed to more simple approaches related to indices 

such as SPI or PDSI. Unfortunately, not all models are 

equally suited for drought prediction, and scientists are 

actively testing across multiple models (e.g., Tallaksen 

and Stahl 2014).

Paleoclimatic Context 

for Evaluating Drought

Historic climate can be reconstructed through the use 

of many types of proxy variables. Interpretations of 

past climates, including drought, have been developed 

using tree rings; pollen, chironomids, diatoms, 

1 2 3

Rn / P

0 4

1.0

0.8

0.6

0.4

0.2

0.0

E / P

Figure 2.2—The Budyko (1974) relationship relating the aridity 

index given as the ratio of the net radiation (Rn, energy available 

for evapotranspiration) to precipitation (P) to the ratio of the 

actual evaporation (E) to precipitation. The blue line shows the 

energy limitation for potential evaporation where Rn = P. After 

there is sufficient net radiation to evaporate all precipitation, 

there is simply a limitation on evaporation given by the red line 

where Ea = P. Budyko’s curve fits below these physical limits 

(black line) as an empirical relationship derived by plotting 

several of the World’s rivers on these axes. The points (black 

and gray) represent some hypothetical streams. When equation 

1 (see text) applies, the ratio of flow to precipitation (Q / P) is 

1 – E / P, or the distance between the red line and the point.
24

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

sediment, and isotopes taken from lake-sediment 

cores; records of Aeolian deposits in sand dunes; 

micro- and macrofossil remains in woodrat middens; 

speleothems; glacial and periglacial deposits; lake 

levels; and archeological records (Bradley 1999). These 

records are able to reveal small- to broad-scale changes 

in climate from decades to millennia. Each of these 

has certain biases and strengths. For example, plant 

macrofossils (leaves, fruit, etc.) can place a species at 

a specific location, while microfossils (pollen) have a 

range of uncertainty including source region and limited 

botanical identification. The most robust reconstructions 

derive from use of multiple proxies. Together with the 

continual development of varying climate proxies from 

sediment cores (e.g., Booth 2002), reconstructions of 

past climates will improve.

Tree rings are an important and common source for 

understanding late-Holocene droughts. Trees from 

mid to high latitudes produce annual growth rings, and 

the variation in ring width is influenced by a multitude 

of factors, including water availability, at various time 

scales. When aggregated from stand to continental 

scales, ring-width measurements can reflect these 

factors at various spatial and temporal scales. 

Fundamental to dendrochronology is the identification 

of the pattern of large and small rings through time 

in a collection of tree cores (i.e., cross-dating), which 

affords the ability to precisely date rings to a calendar 

year. Cross-dating (Douglass 1920) allows scientists 

retrospective estimates of past climatic and ecological 

change. Separating the climatic influence from the 

effects of genetic diversity and ecological effects, or, 

more realistically, reducing the nonclimatic input on 

growth from the climatic signal in tree rings, requires 

sophisticated standardization. The process involves 

transforming raw ring widths into time series of radial 

indices that are most likely to be a proxy of past 

climates. Advances in dendrochronology over the last 

60 years (including techniques to interpret past climate 

through ring density and stable isotope composition as 

well as width) have enabled researchers to reconstruct 

climate from the stand and regional scale to continental 

and hemispheric scales (Cook and others 2004, 

Cook and others 2007, Cook and others 2010, Fritts 

1976, Jacoby and D’Arrigo 1989, Meko and others 

1993). Besides inferences about climate from growth 

increments, tree rings are used to date environmental 

disturbances tied to drought, like fire (Heyerdahl and 

others 2008, Whitlock and others 2003) and canopy 

disturbance (Lorimer 1985, Rubino and McCarthy 

2004). These advances aid in the understanding of 

long-term spatiotemporal variations in drought and the 

atmospheric dynamics behind them.

The North American Drought Atlas (NADA) is the best 

source for understanding spatial and temporal patterns 

of tree-ring-reconstructed moisture variability over the 

last 500–1,000 years (Cook and Krusic 2004, Cook and 

others 2004). Chronology length and coverage varies 

in the atlas, with stronger fidelity in the Southwestern 

United States and weaker fidelity in New England 

and the Great Lakes region. The New England and 

Great Lakes regions generally show similar trends 

and patterns as other eastern regions, but more work 

is required to refine estimates of long-term drought 

severity and frequency. Another important note is 

that drought in the NADA is represented by different 

seasons in different regions. Winter precipitation is the 

primary signal reconstructed from tree rings from the 

Pacific Northwest to Northern Mexico and west Texas, 

while the eastern half of the atlas contains a summer 

moisture index (St. George and others 2010).

Continental and Subcontinental 

Patterns in Paleoclimate

Regional aridity and warmth was widely expressed 

during the middle Holocene. In many parts of 

southwestern and central North America, this was the 

warmest and driest interval of the past 10,000 years 

(Dean and others 1996, Spaulding 1991, Yu and others 

1997). Proxy records from pollen, woodrat middens, 

tree-rings, lake levels, and Aeolian indicators document 

extensive warmth and aridity from 8 ka (kiloannus, or 

thousand years) to 3.8 ka, peaking at 6 ka (Benson and 

others 2002, Dean and others 1996, Holliday 1989, 

Mensing and others 2004). In contrast, the dry interval 

for the Pacific Northwest and parts of the northern 

Rocky Mountains was before 8ka (Brunelle and others 

2005, Whitlock and others 2003).

In northeastern North America, various proxy records 

show that the mid-Holocene was a period of high 

aridity (Hardt and others 2010, Marsicek and others 

2013, Menking and others 2012, Newby and others 

2011, Newby and others 2014, Nichols and Huang 

2012, Shuman and Donnelly 2006). Supporting earlier 

work by Webb and others (1993), these same studies 

indicate trends toward more moist conditions since 

the mid-Holocene aridity up to the 20th century. High 

hydroclimatic variability punctuated this trend, most 

notably between 3,900 and 5,200 years before present 

(e.g., Booth and others 2005, Foster and others 2006, 

Newby and others 2014).
25

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Although pan-continental droughts were relatively rare 

during the last 1,000 years, the North American Drought 

Atlas indicates that they occurred more frequently during 

the Medieval Climate Anomaly (MCA) and could be related 

to defined climate modes (Cook and others 2014b). 

Notable pan-continental droughts include 1344–1353 C.E. 

(Common Era), 1661–1671 C.E., and 1818–1820 C.E. 

(Cook and others 2007). Cook and others (2014b) highlight 

the unusual nature of the 2012 pan-continental drought, 

but also indicate the potential for some predictability 

of these events as well as increased severity of pancontinental droughts as a result of greenhouse gas forcing.

Over the last 1,100 years, there have been several largescale, hydroclimatic events in the conterminous United 

States. The MCA is widely recognized and regionally 

expressed as warm and/or dry (Bradley and others 

2003, Lamb 1965, Mann and others 2009). Extensive 

periods of aridity characterized western North America 

during two centennial-scale arid periods, from 900 

to 1100 C.E. and 1200 to 1350 C.E. (Cook and others 

2010, MacDonald 2007, Stine 1994). In eastern North 

America, great droughts also characterize the MCA 

period, although the timing is shifted. Megadroughts 

(i.e., severe droughts of a decade or more) are seen in 

the extensive tree-ring record from the mid-Mississippi 

River Valley during the mid-900s C.E., 1100–1250 C.E., 

and then 1340–1400 C.E. (Cook and others 2010). 

Sediment core records document dry conditions during 

the MCA in the Eastern United States as well (Minckley 

and others 2011, Pederson and others 2005). These 

droughts come at the tail end of more-frequent drought 

conditions during the MCA across the Western United 

States (Cook and Krusic 2004, Cook and others 2004).

A persistent trend of increasing wetting was present 

across the Western United States during the Little Ice 

Age (Cook and others 2004). This trend was punctuated 

by severe droughts, such as the late 14th century and 

the 1805–1806 C.E. droughts centered on the Great 

American Desert (Cook and others 2007), the 1379–1388 

C.E. drought centered on the Mississippi Valley, and 

the 16th century megadrought (Cook and others 2007, 

Stahle and others 2000). [The 16th century megadrought 

has been recently documented in the Northeastern 

United States (Ireland and Booth 2011) and is the most 

synchronous sustained drought in the Eastern United 

States of the last 500 years (Pederson and others 2013b).]

Regional Patterns in Paleoclimate

Eastern United States—As discussed previously, 

analyses of basin-scale streamflow records do not 

show an increase in drought frequency over the past 

several decades; however, there are several important 

aspects of the changing hydroclimate in the Eastern 

United States (figs. 2.3–2.6). Notably, there is a 

recent divergence in moisture conditions between the 

Northeastern and Southeastern United States (Melillo 

and others 2014). Meteorological drought has become 

more frequent and severe in the Southeastern United 

States since the 1980s drought (Laseter and others 

2012, Melillo and others 2014, Pederson and others 

2012, Seager and others 2009). While the 1980s 

drought was one of the more severe droughts since 

1700 (Cook and others 1988), reconstructions of PDSI 

from tree rings indicates that prior centuries were 

generally drier and had more severe and extended 

drought (figs. 2.3 and 2.5). The most recent severe 

droughts fall short of the more severe droughts in the 

last millennium (Stahle and others 2013b, Stahle and 

Cleaveland 1992).

The Northeastern United States is currently 

experiencing one of the wettest growing-season 

pluvials since 1531 C.E. (figs. 2.3, 2.4, and 2.6) 

(Pederson and others 2013b). Variation in reconstructed 

PDSI occurs at decadal to multi-decadal time steps with 

a positive shift in increased moisture availability and 

extreme events since the early 2000s (Matonse and 

Frei 2013, Melillo and others 2014, Pederson and others 

2013b). These shifts are observed across New England 

in rising streamflow and groundwater tables (Dudley 

and Hodgkins 2013, Weider and Boutt 2010). Varved 

sediments also indicate the Northeast is undergoing one 

of the wettest periods in the last 1,000 years (Hubeny 

and others 2011). These findings are supported at even 

longer time scales. Lake levels across Massachusetts 

indicate a positive trend in effective moisture over the 

last 3,000 years resulting in “exceptionally high” levels 

of water in the recent era (Newby and others 2014). 

The centennial trend of increased moisture in the treering reconstruction and various hydrological measures 

in the Northeast generally follow the trajectory of the 

Massachusetts lakes indicating that the current period 

could be one of the wettest of the last 3,000 years.

Plains and Midwest—Reconstructions of moisture 

in the Plains and Midwest contain many of the same 

trends described above (fig. 2.3), although there is 

some spatial complexity in trends during the most 

recent century. The northwestern portion of the Prairie 

Pothole Region of the upper Great Plains has become 

drier over the past century while the southeastern 

portion, bordering on the western edge of the eastern 
26

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Year

2000

-8

-6

-4

-2

0

2

4

6

1500 1600 1700 1800 1900

Upper Mississippi River Valley

Northeast

-5

0

5

1000 1200 1400 1600 1800

Lower Mississippi River Valley

Coastal Carolinas

2000

2000

Year

PDSI

Year

PDSI

Figure 2.3—Time-series of Palmer Drought Severity Index (PDSI) over the last 500 years (Upper 

Mississippi River Valley and Northeast) and 1000 years (Lower Mississippi River Valley and Coastal 

Carolinas). Notable features in these series are the relative absence of annual values during the 16th 

century megadrought in the Upper Mississippi River Valley and Northeastern United States (upper panel) 

and similar features during the 12th and 13th centuries in regions to the south (lower panel). Annual 

values are shown in faint, thin lines, and 20-year smoothed data with the dark, thicker lines. The horizontal 

line at 0 represents the 1900–2005 mean. These data are drawn from reconstructions of PDSI from the 

North American Drought Atlas (Cook and others 2007) for the Upper Mississippi River Valley, Lower 

Mississippi River Valley, and Coastal Carolinas, and Pederson and others (2013b) for the Northeast.
27

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

16th Century

17th Century

18th Century

19th Century

20th Century

> 1950

PDSI

12th Century

13th Century

16th Century

17th Century

20th Century

> 1950

Upper 

Mississippi

River Valley

Northeast

Lower 

Mississippi

River Valley

Coastal Carolinas

PDSI

PDSI

PDSI

Density

0.35

0.25

0.15

0.05

Density

0.35

0.25

0.15

0.05

-8 -6 -4 -2 -0 2 4 6 -8 -6 -4 -2 -0 2 4 6

-8 -6 -4 -2 -0 2 4 6 -8 -6 -4 -2 -0 2 4 6

Figure 2.4—Density of Palmer Drought Severity Index (PDSI) over the last 500 years (Upper Mississippi River Valley and Northeast) 

and 1000 years (Lower Mississippi River Valley and Coastal Carolinas). The gray area represents the 1500–2005 and 1000–2005 

distributions, respectively. The areas under the blue line and purple line represent the 1900–2000 and 1950–2005 periods, 

respectively. The end of the 20th century, a period of intense forest study, is generally one of the wettest periods in each region, 

indicating a general shift towards wetter conditions across the Eastern United States. The vertical line at 0 represents the 1900–2005 

mean, so the values on the horizontal axis are departures from the mean. These data are drawn from reconstructions of PDSI from 

the North American Drought Atlas (Cook and others 2007) for the Upper Mississippi River Valley, Lower Mississippi River Valley, and 

Coastal Carolinas, and Pederson and others (2013b) for the Northeast.
28

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

30

25

20

15

10

5

0

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Upper Mississippi River Valley Drought events

16th Century

17th Century

18th Century

19th Century

Number of events

20th Century

Duration (years) 30

25

20

15

10

5

0

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Number of events

Duration (years)

30

25

20

15

10

5

0

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Number of events

30

25

20

15

10

5

0

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Number of events

Duration (years)

Duration (years)

Northeast

Lower Mississippi River Valley

Coastal Carolinas

Drought events

12th Century

13th Century

16th Century

17th Century

20th Century

Figure 2.5—Frequency of discrete drought events of 2 years or more for key centuries over the last 500 years (Upper 

Mississippi River Valley and Northeast) and 1000 years (Lower Mississippi River Valley and Coastal Carolinas). In 

these four corners of the Eastern Deciduous Forest region, extended drought has been relatively unusual during the 

20th century (blue). Droughts of the longest duration (>5 years) occur mostly in the 16th and 17th centuries in the 

north and the 12th and 13th centuries in the south. These data are drawn from reconstructions of PDSI from the North 

American Drought Atlas (Cook and others 2007) for the Upper Mississippi River Valley, Lower Mississippi River Valley, 

and Coastal Carolinas, and Pederson and others (2013b) for the Northeast.
29

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Number of events

Duration (years)

Upper Mississippi River Valley

Northeast

Lower Mississippi River Valley

Coastal Carolinas

Pluvial events

16th Century

17th Century

18th Century

19th Century

20th Century

Pluvial events

12th Century

13th Century

16th Century

17th Century

20th Century

2 3 4 5 6 7 8 9 10 11 12 13

25

20

15

10

5

0

Duration (years)

Number of events

2 3 4 5 6 7 8 9 10 11 12 13

25

20

15

10

5

0

Number of events

Duration (years)

2 3 4 5 6 7 8 9 10 11 12 13

25

20

15

10

5

0

Number of events

Duration (years)

25

20

15

10

5

0

2 3 4 5 6 7 8 9 10 11 12 13

Figure 2.6—Frequency of discrete pluvial events of 2 years or more for key centuries over the last 500 years (Upper 

Mississippi River Valley and Northeast) and 1000 years (Lower Mississippi River Valley and Coastal Carolinas). In 

these four corners of the Eastern Deciduous Forest region, extended pluvials (>5 years) have been more frequent 

in the Lower Mississippi River Valley and the Northeast during the 20th century (blue). These data are drawn from 

reconstructions of PDSI from the North American Drought Atlas (Cook and others 2007) for the Upper Mississippi 

River Valley, Lower Mississippi River Valley, and Coastal Carolinas, and Pederson and others (2013b) for the 

Northeast.
30

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

U.S. forest, has become wetter (Millett and others 

2009). Generally, droughts were more severe and of 

greater duration prior to the 20th century (figs. 2.5 and 

2.6) (Cleaveland and Stahle 1989, Cook and others 

2004, Cook and others 2010, Stahle and others 1985, 

Stahle and others 2007, Woodhouse and Overpeck 

1998). Outstanding findings from reconstructed 

PDSI include more severe and extended droughts 

during the MCA (900s and 1100–1200), early Little 

Ice Age (late-1300s), and late 16th century (Cook and 

others 2010, Stahle and others 2007, Woodhouse and 

Overpeck 1998). During the past 500 years, however, 

the Dust Bowl drought was second only to the 16th 

century megadrought (Fye and others 2003). Since 

1500 C.E., less extreme drought conditions (similar to 

the 1950s drought) have occurred 12 times; drought 

conditions that exceeded those of the 1950s drought 

have occurred 4 times during that same period (Fye 

and others 2003). Interestingly, there is a circa 600-

year trend in wetting in the mid-Mississippi River 

Valley that peaks late in recent decades (fig. 2.3) 

(Cook and others 2010). Similar to the Northeastern 

United States, this trend towards increasing moisture 

is reflected in the southeastern Prairie Pothole Region, 

where a survey of ponds during the month of May 

suggests a substantial increase in the number of ponds 

since 1995 versus the period between 1974 and 1994 

(Ballard and others 2014).

Southwestern United States Including California 

and the Great Basin—The Southwestern United 

States is an example of where understanding of 

long-term climate dynamics is crucial for sustainable 

management of environmental resources. Both an early 

and a recently updated reconstruction of streamflow 

in the Colorado River Basin indicate that water 

management agreements were developed during one of 

the wettest periods of the last 500 years (Stockton and 

Jacoby 1976, Woodhouse and others 2006). Creation of 

water distribution policies during such extreme periods 

(like the early 20th century pluvial) can lead to an overexpectation of water delivery when the climate system 

returns to “normal” or drought conditions. Since the 

early 20th century pluvial, there has been significant 

drying in the region.

Megadroughts were more common in the Southwest 

during the past several millennia. The most long-lasting 

and severe drought interval of the late Holocene is 

documented by multiple proxies across the central 

Great Basin extending to Great Salt Lake, and lasting 

from 2,800 to 1,850 years before present (Mensing 

and others 2013). During this period, wetlands and 

meadows shrunk in size, lake levels decreased, and 

waters became more saline. Drought was zonally 

limited, and areas of the northern Great Basin remained 

or grew wetter. This pattern of dry in the southwest 

and wet in the northwest across the Great Basin 

is supported by large-scale spatial climate pattern 

hypotheses involving ENSO (El Niño-Southern 

Oscillation), PDO (Pacific Decadal Oscillation), AMO 

(Atlantic Multidecadal Oscillation), and the position of 

the Aleutian Low and North Pacific High, particularly 

during winter (Mensing and others 2013).

As elsewhere in North America, droughts were most 

notable during the MCA (Cook and others 2004). 

Reconstructed droughts during this period were not 

only relatively more severe versus those during recent 

centuries (Cook and others 2010, Meko and others 

2007), but drought during the MCA also covered a 

considerably greater portion of the Western United 

States. Approximately 30 percent of the Western United 

States experienced annual drought during the 20th 

century versus approximately 41.3 percent between 900 

and 1300 C.E. (Cook and others 2004). Treelines were 

elevated in the Sierra Nevada and White Mountains 

during the MCA (LaMarche 1973, Lloyd and Graumlich 

1997), and growth patterns indicate extended warm and 

dry conditions (Graumlich 1993, Scuderi 1993).

Reconstructions of hydroclimate covering the last 

2,000 years indicate the occurrence of drought equal 

to or greater in severity than those during the MCA. A 

reconstruction of the San Juan River from bristlecone 

pine indicates a severe, 51-year drought from 122 to 172 

C.E. (Routson and others 2011). [Although this record 

has low tree replication during this period, comparison 

to other records of drought in and adjacent to this 

region substantiates the severity of second century 

drought (Cook and others 2004, Cook and others 2007, 

Knight and others 2010).] The extent of this drought, 

from southern New Mexico to Idaho, is similar to the 

12th century megadrought (Routson and others 2011), 

suggesting perhaps a recurring forcing.

Over the past 2,740 years, oscillations in hydrologic 

balance are documented throughout the region, 

with droughts occurring about every 150 years and 

intervals between droughts ranging from 20 to 100 

years (Benson and others 2002). Similar patterns 

of synchronous drought exist from the Great Basin 

through New Mexico and coincide with Ancient 

Puebloan withdrawals and abandonments in Arizona 
31

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Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

and Colorado, documenting the likely wide extent and 

impact of these droughts (Benson and others 2002, 

Dean 1996, Grissino-Mayer 1996).

Insight into seasonal dynamics of precipitation delivery 

within the North American Monsoon region was 

recently revealed. Using indices of early-wood and 

late-wood widths from two tree species over a large 

region, Griffin and others (2013) reconstructed coolseason and monsoonal precipitation going back to 1539 

C.E. The two records of reconstructed precipitation 

indicate periods of dry, cool-season conditions followed 

by a failure of the monsoon during the 1570s, 1660s, 

1770s, and early 2000s. Similarly, the early 20th century 

pluvial was characterized by synchronous, dual-season 

surplus precipitation. Interestingly, much of the period 

during the instrumental record is characterized by 

a high frequency of asynchronous cool-season and 

monsoonal precipitation or “opposing-sign precipitation 

anomalies” (Griffin and others 2013). What this study 

reveals, however, is that this anti-phasing of cool-season 

and monsoonal precipitation is more of an exception 

rather than the rule during the 470-year reconstructions. 

Therefore, a fuller understanding of climate dynamics 

of the North American Monsoon region likely requires 

an understanding of the dynamics outside of the 

instrumental record.

More than half of California was in a state of moderate 

drought between June 2013 and June 2014, at which 

time 100 percent of the State reached that level of 

drought. The conditions in 2014 culminated in the 

driest 3-year period of the last century (Griffin and 

Anchukaitis 2014). To place this drought in a longterm context, tree-ring analysis of blue oak (Quercus 

douglasii) around the Central Valley of California was 

used to characterize annual variations of drought history 

over the past seven centuries (Meko and others 2001, 

Meko and others 2011, Stahle and others 2001, Stahle 

and others 2013a). Independent reconstructions of 

November–April precipitation for North and South Coast 

Ranges indicate strong annual correlations during the 

common period (1584–2003), although there were 

eras of asynchrony between the two regions during 

the 1770s, 1810s–1840s, and 1970s, for example 

(Stahle and others 2013a). Winter storm track position 

is thought to control the more extreme periods in the 

tree-ring records. An updated reconstruction of drought 

in this region using blue oak collected following the 

2014 growing season indicates unprecedented drought 

conditions in 2014 compared to the prior 1,200 years 

(Griffin and Anchukaitis 2014).

Ecological Outcomes of Paleoclimate on Forests

Ecological responses at regional scales were widespread, 

with changes in ecosystem structure, composition, 

and range toward dry-adaptations and changes in 

disturbance patterns reflecting drier conditions. Forest 

response included, for example, conversion from mesic 

forest to prairie in the Midwest (Baker and others 1992), 

dominance of dry-adapted taxa (Chrysolepis, Quercus) 

at high elevations that are currently occupied by Abies

and Pinus in the Sierra Nevada of California (Anderson 

and Smith 1994), and expansion of warm-adapted pines 

and oaks in the Colorado Plateau (Betancourt 1990). 

Regionally warm and dry climates evolved in the middle 

Holocene as a combined effect of insolation changes 

due to orbital relations, which affected the amount and 

seasonality of precipitation, and changes in the position of 

jet streams, storm tracks, and blocking of warm maritime 

air (Baker and others 1992, Dean and others 1996, Yu 

and others 1997).

The ecological impact of the Medieval Climate Anomaly 

droughts in the Western United States is reflected by 

the presence of in-situ stumps in present-day rivers and 

lakes (Kleppe and others 2011, Stine 1994); lowered 

lake levels (Stine 1990); decreased alpine treelines 

(LaMarche 1973, Lloyd and Graumlich 1997); decreased 

growth of trees (LaMarche 1974); and changes in 

species distributions, elevation zonation, and abundance 

(Lloyd and Graumlich 1997, Millar and others 2006). 

Shifts toward warm and dry conditions also altered 

fire regimes, such that fire activity was highest relative 

to the entire Holocene during the MCA in the Pacific 

Northwest and parts of the Northern Rocky Mountains 

(Brunelle and others 2005, Whitlock and others 2003), 

whereas changes in forest structure related to aridity 

(low fuel density, sparse stands) resulted in many 

small fires in the western Sierra Nevada relative to 

mesic intervals (Swetnam 1993). Mechanistic forcing 

for the dry centuries of the Medieval period has been 

related to changes in ocean circulation, in particular 

the development of persistent positive North Atlantic 

Oscillation conditions (Trouet and others 2009), and 

northward shifts in storm tracks across the eastern 

North Pacific with a contraction of the Aleutian Low 

(Graham and others 2007, MacDonald and Case 

2005). More recent reconstructions suggest that the 

causes were more complex and that the MCA was 

characterized by an enhanced zonal Indo-Pacific Sea 

Surface Temperature (SST) gradient with resulting 

changes in Northern Hemisphere tropical and extratropical circulation patterns and hydroclimate regimes 

(Graham and others 2011).
32

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Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

An important hydroclimatic event with ecological 

implications in the Western United States is the early 

20th century pluvial, one of the most contiguous pluvial 

events of the last 1,000 years (Cook and others 2011, 

Stahle and others 2007). This pluvial—a period of 

extended, above average moisture condition—covered 

about half of the continent and is thought to have 

been an important trigger in tree recruitment in the 

Southwestern United States (Savage and others 1996). 

Generally, the 20th century was a substantially wetter 

period across the United States versus the prior three to 

eight centuries (Cook and others 2004, Cook and others 

2010, Stahle and Cleaveland 1992, Stahle and others 

1988, Stahle and others 2007).

The ecological impact of historic droughts is well 

documented throughout the Holocene in the Eastern 

United States. Throughout the Holocene, drought has 

been an important contributor to forest change (Shuman 

and others 2009a). Drought variation during the MCA 

was an important factor contributing to the decline in 

American beech (Fagus grandifolia) in the Great Lakes 

region (Booth and others 2012). In a surprising contrast, 

drought is seen to be an important factor of deciduous 

forest expansion in Minnesota early in the Little Ice 

Age (Shuman and others 2009b). Abrupt hydroclimatic 

variability is attributed to peatland development in 

Pennsylvania (Ireland and Booth 2011). The 16th century 

megadrought likely influenced stand dynamics in a large 

wetland complex in the Mississippi Valley (Stahle and 

others 2006), while repeated droughts during the mid18th century appear to be contributors of regional-scale 

canopy disturbance in the Southeastern United States 

(Pederson and others 2014). The latter finding follows 

observations of oak growth decline and mortality in the 

Midwestern United States during the late 20th century 

(Pedersen 1998).

Periods of abundant moisture could be key elements 

of forest dynamics in the mesic Eastern United States. 

An expansion of yellow birch (Betula alleghaniensis) 

occurs during a period of increased moisture and high 

lake levels (Jackson and Booth 2002). The rise of maple 

(Acer spp.) and other mesophytic species during the 

20th century occurs towards the end of a centennial 

wetting trend (McEwan and others 2011, Pederson and 

others 2013b); however, given the complexity of factors 

in this region, it is yet to be determined whether this 

wetting is an important factor of this rise. However, if 

the trend in wetting over the last 2,000–3,000 years 

in the Northeastern United States (Newby and others 

2014) is similar to the wetting trend over the Eastern 

United States from the end of the Little Ice Age into 

the 20th century (Pederson and others 2013a), there is 

much to investigate regarding drought-forest dynamics 

over this mesic region across spatial and temporal 

scales. Greater detail on the ecological impact of 

drought on forests is found in chapter 4.

Historical and Recent Drought

Approaches to quantifying changes in drought depend 

on how “drought” is defined (Trenberth and others 

2014). In this context, we suggest two important 

observations: (1) climate variability occurs at multiple 

time scales (Hurst 1951), and (2) widespread droughtrelated forest mortality is occurring (Allen and others 

2010, Breshears and others 2005, van Mantgem and 

others 2009). The first point is that many hydrologic 

phenomena show cycles at a large range of time scales, 

some tied to known climatic modes (e.g., El Niño, PDO, 

AMO), and others at longer scales. The implication is 

that the ability to detect trends in hydrologic phenomena 

may depend upon whether the time period of interest 

encompasses one or more of these cycles. The primary 

value in finding hydrologic trends, then, is in relating 

different co-occurring trends to one another to learn 

about potential causal relationships.

The second point is that, in many regions of the World, 

large numbers of long-lived plants seemed to be dying 

at rates unprecedented in historical times, indicating 

that hydrologic processes may be changing in ways 

that are ecologically meaningful. Because of this, we 

require an understanding of what aspects of changing 

drought regimes are causing these significant ecological 

impacts. The drought metrics and understanding of 

forest physiology and ecology outlined above indicate 

water balance, temperature (both as index to ET and 

as it affects physiology), and time are three key ways 

drought may be changing. This is a complex mix, 

particularly considering that the interactions among 

these three are of fundamental importance. A rich 

literature on historical (relying on the instrumental 

record) changes tying variability to known climate 

modes can help us interpret some of the trends and 

patterns of change. The recent literature is rich on the 

topic of recent trends for many regions in the United 

States, but only two regions are discussed here as 

examples.

Eastern United States

Compared to most other areas of the United States, 

the East receives large amounts of precipitation, with 
33

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

30-year (1981–2010) normals ranging from 80 to 200 

cm across the region (PRISM 2013). Precipitation is 

spatially and temporally variable in the East due to 

a combination of many factors, including proximity 

to the Atlantic Ocean and Gulf Stream, influence of 

the Great Lakes, and orographic effects associated 

mountains, including the Appalachian chain that 

extends from Alabama to north of Maine (Huntington 

and others 2009, Mulholland and others 1997). 

Broad-scale circulation patterns influence the eastern 

climate, contributing to patterns in precipitation. In the 

Southeast, precipitation is associated with El Niño/

Southern Oscillation (ENSO), with dry conditions 

occurring during La Niña events (Piechota and Dracup 

1996, Ropelewski and Halpert 1986, Roswintiarti and 

others 1998). During the growing season, precipitation 

has been linked to the North Atlantic Subtropical High 

in the Southeast (Li and others 2011). Precipitation in 

the Northeast also suggests possible linkages with 

ENSO, as well as the North Atlantic Oscillation (NAO) 

(Bradbury and others 2003, Kingston and others 2007), 

with evidence of a relationship between negative NAO 

conditions and drought (Bradbury and others 2002, 

Seager and others 2012). A positive NAO promotes 

pluvial conditions (Seager and others 2012), although 

the ultimate causes of pluvials are complex (Ning and 

Bradley 2014, Seager and others 2012).

Despite the relatively abundant supply of precipitation 

in the East, droughts are a natural part of the climate 

system and occur with regularity. Over the last 100 

years, eastern droughts generally last only 1–2 years, 

unlike arid regions of the Central and Western United 

States that experience more intense and prolonged 

meteorological droughts (Seager and others 2009). 

A notable example of a severe eastern drought is 

the drought of the early 1960s that lasted 4 years 

and affected a broad area, including New England, 

the Mid-Atlantic States, and parts of the Midwest 

(Namias 1966). The Southeastern United States has 

also experienced severe droughts over the last several 

decades, including one from 1984 to 1988 (Cook and 

others 1988) and more recently from 2006 to 2008 

(Kam and others 2014).

Analyses of past occurrences of drought show no 

indication that they are becoming more frequent in 

the Eastern United States. In fact, precipitation has 

increased throughout the region, especially in the 

Northeast (Melillo and others 2014), which has resulted 

in an overall reduction in drought conditions (Andreadis 

and Lettenmaier 2006, Sheffield and Wood 2008a). 

These increases in precipitation have led to documented 

regional increases in streamflow and are consistent with 

patterns observed in many other regions of the United 

States (Groisman and others 2001, McCabe and Wolock 

2002). Although there are no apparent increasing 

trends in drought during the recent past (Patterson 

and others 2013, Sheffield and Wood 2008a), most 

models indicate that drought frequency in the Eastern 

United States will increase by the end of the century, 

despite projected concurrent increases in precipitation 

(Hayhoe and others 2007, Sheffield and Wood 2008b). 

This paradox is largely explained by enhanced future 

evapotranspiration associated with longer growing 

seasons and warmer air temperatures. This may already 

be occurring in some regions. For example, recent 

analyses suggest that although there are no observable 

trends towards increasing drought frequency over the 

past 70+ years, overall streamflow has decreased by 

about 7 percent in the South Atlantic region of the 

Eastern United States (Patterson and others 2013).

Although droughts in the Eastern United States are not 

as severe as those in the Southwest and Great Plains, 

the affects can be acute because of the high population 

density and associated demands for water (Patterson 

and others 2013). The southeastern drought of 2006 

to 2008 caused societal and economic hardships, with 

agricultural losses exceeding a billion dollars (Manuel 

2008). The drought also led to interstate disputes over 

water use as supplies diminished. Recent evidence 

suggests that severe, short-duration droughts in the 

East can also have lasting effects on forest ecosystems 

(Klos and others 2009, Pederson and others 2014). 

These events can alter the structure of forests for 

centuries, particularly if they are exacerbated by other 

broad-scale disturbances, such as frost, ice storms, and 

insect outbreaks. Understanding the effects of extreme 

climatic events, such as droughts, will help determine 

how eastern forests will respond to future climate 

change.

Northwestern United States

Temperature recorded at long-term stations has 

increased in the Northwest since the early 20th century, 

with some of the cause attributed to increased carbon 

dioxide (CO2) (Abatzoglou and others 2014). Less 

certain, however, are precipitation trends and their 

causes, as suggested by the long-term instrumental 

record and modeling studies. Most of the data for 

these long-term studies come from stations at lower 

elevations, where they can be collected more reliably. 

Because much of the water in the Northwestern United 
34

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

States comes out of mountains, further data collection 

and analysis is needed at high elevations to gain a better 

understanding.

One of the most frequently discussed changes to 

Northwest hydroclimatology is trends in snowpacks 

(e.g., Mote 2003). Summers are very dry compared to 

winters in much of the Northwest, although there are 

June peaks in precipitation in the Northern Rockies and 

some summer monsoonal moisture over southeastern 

Oregon and southern Idaho. Because of the general 

lack of summer precipitation, snowmelt is a critical 

part of the water supply in forests and rivers during the 

Northwest’s growing season. A lack of snow for melt 

means that the snowpack ablates earlier and stream 

runoff occurs earlier (Cayan and others 2001, Stewart 

and others 2005) because a shallower snowpack 

takes less time to melt. What has previously been 

unclear is the relative contributions of temperature and 

precipitation to these snowpack trends (Luce and others 

2013, Mote and others 2005), which has important 

consequences for leveraging current trend information 

for application to future projections.

Streamflow has been declining in the Northwest 

since the late 1940s (Clark 2010, Dai and Trenberth 

2002, Luce and Holden 2009), particularly droughtyear flows. The declines have been driven primarily by 

winter precipitation declines (Luce and others 2013). 

Streamflow declines have shown a pattern where the 

driest years (25th percentile), in particular, are showing 

the strongest trends, approaching a 50-percent decline 

in drought-year flows over the last 60+ years (Luce 

and Holden 2009). This pattern is consistent with other 

observations of increasing variance in runoff in the 

Western United States (Pagano and Garen 2005) and 

with expectations for increasing variance in runoff (P

– E) with warming (Seager and others 2012). Previous 

work missed detecting changes in precipitation because 

it was based on analysis of low-elevation stations (Mote 

and others 2005, Regonda and others 2005), while the 

decreases in runoff were related to decreased highelevation precipitation driven by reduced westerly wind 

speeds over the region.

The twin contexts of decreasing precipitation and 

warming temperatures, with consequent changes 

in snowpack, make evaluation of drought effects in 

the region multifaceted. For example, earlier work 

showed that wildfire was more prevalent in the region 

in association with earlier snowmelt, presumed to 

be a function of warming temperatures alone (e.g.,

Westerling and others 2006). An awareness of the 

declining precipitation, though, has revealed that the 

precipitation variability has historically been a more 

important control on interannual variability in burned 

area (Abatzoglou and Kolden 2013, Holden and others 

2012, Riley and others 2013), and increasing wildfire 

area is consistent with increasing drought severity as 

indexed by the lower streamflow quartile.

Low flows during the dry summer months are also 

showing declines (Dittmer 2013, Leppi and others 2011, 

Lins and Slack 2005). Some of this is related to earlier 

runoff timing, as the time between recharge of the 

soil mantle and groundwater and the runoff increases; 

but some is also related to declining recharge volumes 

(Safeeq and others 2013). Again, most of the effect 

has been attributed to earlier snowmelt and reduced 

accumulation as a function of increasing temperatures, 

but the precipitation variations affect both timing and 

total annual streamflow (Holden and others 2012, Luce 

and Holden 2009). More work in this area is needed to 

identify the relative contributions in the historical record.

Drought in the Pacific Northwest is strongly tied to 

several modes of climate variability, ENSO, the Pacific 

North America Pattern (PNA), and the Pacific Decadal 

Oscillation (PDO). The most severe droughts generally 

occur during El Niño events (Cayan and others 1999, 

Piechota and Dracup 1996, Redmond and Koch 1991, 

Ropelewski and Halpert 1987). ENSO-mediated 

precipitation variations may disproportionately affect 

mountain watersheds (Dettinger and others 2004). 

Precipitation variations are also well correlated to 

the PNA at intraseasonal to interannual time scales 

(Abatzoglou 2011) and the PDO (Mantua and others 

1997) at decadal time scales. Trends in these indices 

are weakly related to the observed trends in westerly 

winds over the region, and consequently with trends 

in runoff and precipitation (Luce and others 2013). The 

related changes in pressure pattern driving the wind 

changes are consistent with increased CO2 content, but 

the change in winds and pressure exceed the average 

expectation for wind decreases by 2080.

Climate Change Impacts 

on Drought Frequency 

and Severity

Will drought be more or less frequent in the future? 

Will it be more or less severe in the future? These 

questions are very difficult to answer with climate 

change projections from GCMs (Dai 2013, Hoerling 
35

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

and others 2012, Sheffield and Wood 2008b, Trenberth 

and others 2014). For example, some researchers have 

used the PDSI conceptualization of “drought,” which 

in a warming future may index temperature more than 

it indexes water balances (Cook and others 2014a, 

Hoerling and others 2012, Sheffield and others 2012, 

Trenberth and others 2014), leading to suggestions 

of alternative models or indices of drought that may 

be more indicative. A more relevant question for 

this report is: will forests and rangelands be more 

severely impacted by drought in the future? Answers 

for this question are more complex, but potentially 

more informative and certain. For example, warming 

means that the droughts we have now are more likely 

to produce tree mortality for a given level of water 

deficit (e.g., Adams and others 2009). Beyond that, 

answers to the question of whether other aspects of 

drought will change in the future, particularly those 

related to precipitation, are much more challenging 

to elicit from GCMs. Despite these challenges, the 

recent Intergovernmental Panel on Climate Change 

(IPCC 2013) report provides some expectations of 

how climate change will impact drought frequency and 

severity in the United States.

General Drought Projection Information

A number of different projections are given in the IPCC 

(2013) Working Group 1 (WG1) report that relate to 

drought, such as changes in annual and seasonal 

precipitation (fig. 2.7) and associated changes in runoff 

and soil moisture (fig. 2.8). Except as specifically noted, 

in this chapter we discuss the multi-model means for 

RCP 8.5 2081–2100 compared to 1986–2005 averages 

from IPCC (2013) chapters 12 and 14. Generally, 

expected runoff patterns correlate strongly to 

expectations of future precipitation, but future soil 

moisture is expected to decline in most land areas. 

Theoretically, this is related to increased 

evapotranspiration, itself tied to increased downwelling 

longwave radiation. The combination of increased 

runoff, which is related to increased precipitation, and 

decreased soil moisture is intriguing. Usually soil 

2081–2100 DJF

2081–2100 MAM

2081–2100 JJA

2081–2100 SON

-50 -40 -30 -20 -10 0 10 20 30 40 50

(%)

Figure 2.7—Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model average percentage change in seasonal mean 

precipitation relative to the reference period 1986–2005 averaged over the period 2081–2100 under the RCP 8.5 forcing scenario. 

Hatching indicates regions where the multi-model mean change is less than one standard deviation of internal variability. Stippling 

indicates regions where the multi-model mean change is greater than two standard deviations of internal variability and where at 

least 90 percent of models agree (from fig. 12.22 of IPCC 2013). Thirty-nine CMIP5 models were used for each panel. From top to 

bottom, the figures describe northern hemisphere winter (Dec.–Feb.), spring (Mar.–May), summer (Jun.–Aug.), and autumn (Sep.–

Nov.). RCP means Representative Concentration Pathway.
36

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

moisture and runoff vary together in forested 

watersheds. The differential trends in soil moisture and 

runoff is explained conceptually by the fact that 

increased precipitation comes by way of increased 

precipitation intensity, meaning that more of the water 

might be expected to run off. It is not clear that this is 

an appropriate re-partitioning in forested landscapes, 

however, and might just be an artifact of the land 

surface model in the GCMs. An additional model output 

is also conceptually tied to increased precipitation 

intensity. The argument that similar or slightly increased 

total precipitation is delivered in higher intensity events 

yields an estimate that interstorm periods will be longer, 

increasing the number of consecutive dry days in most 

years, although the effect is minor across much of the 

continental United States (fig. 2.9).

Post-processing of GCM outputs has also been applied 

to examine how changes in precipitation amount, 

timing, and form (snow versus rain) interact with energy 

available for ET to estimate details of potential future 

conditions (e.g., Cook and others 2015, Elsner and 

others 2010, Hamlet and others 2013, Sheffield and 

others 2004, Vano and others 2012, Wood and others 

2004). Some of these are essentially more-detailed 

versions of the land-surface models used to describe 

the lower boundary condition of the GCMs. These 

approaches relatively directly disentangle a range of 

drought definitions to describe how the components of 

drought are likely to change in the future. An important 

consideration in interpreting output of these simulations 

is that they can double count the effects of increased 

incoming longwave radiation on ET (Milly 1992).

Other approaches directly estimate PDSI values with 

projected temperature and precipitation changes (e.g.,

Dai 2013). Whether the calculated changes in PDSI 

reflect actual changes in drought severity is a subject 

of substantial debate (Cook and others 2014a, Hoerling 

and others 2012, IPCC 2013, Sheffield and others 

-25 -20 -15 -10 -5 0 5 10 15 20 25

(days)

Soil Moisture Runoff

(A) (B)

-0.5-0.4-0.3-0.2-0.1 0 0.1 0.2 0.3 0.4 0.5

(mm day-1)

-2 -1.6 -1.2 -0.8-0.4 0 0.4 0.8 1.2 1.6 2

(mm)

Figure 2.8—Change in annual mean (A) soil moisture (mass of water in all phases in the uppermost 10 cm of the soil) (mm), and (B) 

runoff relative to the reference period 1986–2005 projected for 2081–2100 under RCP 8.5 from the Coupled Model Intercomparison 

Project Phase 5 (CMIP5) ensemble. Hatching indicates regions where the multi-model mean change is less than one standard 

deviation of internal variability. Stippling indicates regions where the multi-model mean change is greater than two standard 

deviations of internal variability and where at least 90 percent of models agree. RCP means Representative Concentration Pathway. 

(From figs. 12.23 and 12.24 of IPCC 2013).

Figure 2.9—Projected change in the annual maximum number 

of consecutive dry days when precipitation is <1 mm, over 

the 2081–2100 period in the RCP 8.5 scenario (relative to 

the 1981–2000 reference period) from the Coupled Model 

Intercomparison Project Phase 5 (CMIP5) models. Stippling 

indicates gridpoints with changes that are significant at the 

5-percent level using a Wilcoxon signed-ranked test. RCP means 

Representative Concentration Pathway. (From fig. 12.26 of IPCC 

2013; updated from Sillmann and others 2013).
37

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

2012, Trenberth and others 2014). Applicability of this 

index to future conditions and their consequences 

will depend in part on how the various components 

of the PDSI relate to the phenomenon of interest. 

For instance, applicability may vary depending upon 

whether forest die-off is more related to shallow 

soil versus how long it has been since precipitation 

has occurred. Most of the projections of increasing 

PDSI values in the United States are associated with 

increases in temperature, although an increase in the 

number of consecutive dry days during monsoon 

season may be important for areas affected by the 

North American Monsoon System (IPCC 2013). There is 

again the concern of double accounting of energy (first 

for heating and then for evapotranspiration) in using a 

temperature-based potential evaporation model (Milly 

1992). This is increasingly well known for applications 

of the original formulation of the PDSI, which uses 

temperature explicitly through the Thornthwaite (1948) 

evaporation model. The Penman-Monteith potential 

evaporation formulation (Monteith 1965), which has 

been adapted for use in PDSI and as part of more 

complex water-balance models (Cook and others 2014a, 

Sheffield and others 2012), implicitly carries a strong 

temperature dependence in the calculation of the vapor 

pressure deficit term as well. Distinguishing between 

contributions in future drought caused by increased 

evapotranspiration rates versus precipitation lapses may 

be helpful in interpreting this kind of work.

Projections of Relevant Factors

Temperatures are expected to increase 4–7 °C across 

the continental United States, with stronger increases 

in the interior than near the coasts. Summer relative 

humidity is expected to drop in the neighborhood of 

4–8 percentage points, with weakest declines in the 

Southwest, where summer humidity is already low. 

Temperature increases in Alaska range from 4 to 9 °C, 

with greater increases farther north. Projected 

temperature increases around Hawaii are in the 3–4 °C 

range. Both Alaska and Hawaii have nearly no projected 

change in relative humidity.

Winter precipitation (DJF) increases on the order of 

0–10 percent (with large differences among models) 

are expected over most of the continental United 

States, except for the Southwest where declines of 

0–10 percent are projected. Alaska shows increases of 

10–50 percent, increasing with latitude. Hawaii has a 

minor and uncertain decline. Summer precipitation (JJA) 

is projected to decline (0–20 percent) over most of the 

continental United States, except for the East and Gulf 

Coasts where 0–10 percent increases are projected. 

Alaska shows increases of 0–20 percent, increasing 

with latitude. Hawaii has a minor and uncertain increase.

Duration of dry spells is expected to increase in western 

U.S. mountains, where less snowpack accumulation 

and earlier melt combine to extend the dry summers 

(Barnett and others 2008, Westerling and others 2006). 

Some areas dependent on rainfall for moisture will also 

see increased dry-spell length. The maximum number 

of consecutive dry days (precipitation <1 mm) in a year 

is not projected to change substantially over most of 

the United States, except in the Southwestern United 

States (AZ, NM, TX) and Pacific Northwest (WA, OR, 

ID), which may see 5- to 10-day increases in dryspell duration. In the Southwestern United States, the 

increases are expected to occur in summer months 

in association with changes in the North American 

Monsoon.

Teleconnections from tropical SST patterns are a 

primary control on drought occurrence in the United 

States (Dai 2011, Rajagopalan and others 2000). 

Despite substantial intermodel variability in projections 

of ENSO, it is expected to continue to be the dominant 

mode of climate variability. The interannual variability 

driven by ENSO provides some insights into future 

WHAT DOES RCP MEAN?

Representative concentration pathways (RCP) is 

a shorthand way of saying, let us assume that the 

concentrations of anthropogenic greenhouse gases 

reach a certain level as indicated by the additional 

radiative forcing they cause by 2100. Four levels were 

considered in the Intergovernmental Panel on Climate 

Change Fifth Assessment Report (IPCC 2013): 2.6, 

4.5, 6, and 8.5 W/m2 (Watts per square meter). 

Each “pathway” has a slightly different trajectory 

in greenhouse gas concentrations (and consequent 

forcing) over time, with the RCP 2.6 scenario, for 

example, showing higher forcing at mid-century 

and recovering toward the end of the century. The 

wattages associated with each RCP level are strictly 

related to the anthropogenic greenhouse gases, and 

increased water vapor that comes as feedback to the 

initial forcing may multiply the increased longwave 

radiation effect three- to four-fold. Thus, an RCP 

of 8.5 could yield a net increase in downwelling 

longwave radiation of 34 W/m2.
38

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

drought, insofar as it reflects variance in precipitation. 

Broadly, the sense that wet places get wetter while the 

dry get drier can also be applied to temporal variations 

in precipitation as controlled by ENSO (Seager and 

others 2012). Because a warmer atmosphere can 

hold (and release) more water, circulation dynamics 

leading to greater runoff (P – E) will be enhanced in 

contrast to those that do not. An increase in interannual 

variability of P – E of about 10–20 percent is expected 

across most of the continental United States, except 

the Southwestern United States where a decline 

in variance is expected (Seager and others 2012). 

Increases in interannual variability on the order of 

30–40 percent are expected in Alaska.

Challenges for Interpreting Projections

Does a projected trend in precipitation or temperature 

portend a trend in drought? There are two important 

aspects of this question: (1) the time scale 

associated with the changes, and (2) whether the 

trends affect those extremes in weather that we 

term “drought.” The first point is mostly one of an 

appropriate datum from which to measure a shift 

or departure. If the future of a location is drier, does 

it also represent an increased drought condition? If 

we are conceptually contrasting two time periods as 

two separate ecological equilibriums, simply being 

drier does not necessarily imply increased drought 

conditions or severity if the water “needs” of the new 

landscape shift in conjunction with the availability. 

However, during the transition, as natural and human 

communities adjust to the shifting dryness, increased 

“droughtiness” is a possibility. For example, one 

could ask, “Is Nevada a dry place, or has it been in a 

drought since the end of the Pleistocene?” Sagebrush 

and bristlecone pine researchers may, appropriately, 

have different answers. Similarly, increased moisture 

may not preclude a future with more severe drought 

episodes. For example, increased variance in 

precipitation may produce years that are extremely 

challenging to a moist-adapted landscape. While this 

question could be taken as one of semantics, it is more 

appropriately applied in a quantitative context by tying 

characteristic time scales of processes of interest 

(e.g., life spans, age to reproduction, seed durability) 

to drought as a transient phenomenon with its own 

time scales associated with duration and frequency 

(for a given intensity). Recognizing this aspect calls for 

greater precision in specifying the nature of the kind 

of drought of concern rather than just identifying a 

comparatively dry period in a time series as a drought 

without reference to time scales.

Coupled to this concern is the lack of knowledge of 

how interannual to interdecadal scale climate modes 

(e.g., teleconnections such as ENSO, PDO, AMO) 

might shift in response to increased atmospheric 

CO2. There is evidence that the inability of GCMs 

to capture low-frequency modes of internal climate 

variability could lead to underestimation of risks of 

persistent drought (Ault and others 2014). Multiple 

years of drought may be more stressful to forests than 

single-year droughts, and the relative risks of reduced 

precipitation for several years to decades may not be 

well represented in GCMs.

The second point is that trends in means may or may 

not reflect changes in extremes. Projections specifically 

of changes in extremes or variance or identification of 

their trends is much more informative with respect to 

drought impacts (Seneviratne and others 2012). Drought 

is an extreme in moisture availability, and several recent 

studies show increased variance along with lower 

annual precipitation in some western U.S. mountains 

(Luce and others 2013, Luce and Holden 2009, Pagano 

and Garen 2005) (fig. 2.10). Shifts in extremes may 

result from shifts in the entire distribution without a 

change in variability, or they may result from a shift in 

the variability with no shift in the mean (e.g., “Summary 

for Policy Makers” in Field and others 2012) (fig. 2.11). 

A shift in variance or mean could change the probability 

of exceeding a threshold or proceeding into novel 

weather (Field and others 2012, Jentsch and others 

1950 1960 1970 1980 1990 2000

800

700

600

500

400

300

200

Annual flow (mm)

Figure 2.10—Annual runoff in the Boise River near Twin Springs, 

ID for water years 1948 to 2006. The dashed red line is the trend 

in, the mean annual flow, and the solid black line is the trend in 

median annual flow. The upper and lower black dashed lines 

are the 75th and 25th percentile annual flows, respectively. Note 

that while the wetter years show nearly no trend, drought years 

(the 25th percentile) have trended significantly, with about a 

30-percent decline over the period of record. This shows a shift 

from a narrow distribution in the 1950s to a wide one in the 

2000s (this would appear as (C) in fig. 2.11).
39

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Flow without climate change Flow with climate change

Probability density

(A)Probability density Probability density

(B)

(C)

Less extreme

wet weather

Less wet 

weather

More 

extreme

dry

weather

More 

dry 

weather Shifted 

mean

Increased 

variance

More extreme

wet weather

More wet 

weather

More 

extreme

dry 

weather

More 

dry 

weather

Shifted 

mean

Increased 

variance 

Little change

in extreme

wet weather

Little change

in wet weather

More 

extreme

dry 

weather

More 

dry 

weather

Figure 2.11—Different changes in runoff distributions between present and future climate and 

their effects on extreme values of the distributions: (A) effects of a simple shift of the entire 

distribution toward drier weather; (B) effects of an increase in runoff variability with no shift 

in the mean; (C) effects of an altered shape of the distribution, in this example a shift in mean 

weather toward drier conditions with an increase in variance. Vertical lines are means. [After 

fig. SPM.3 in Field and others (2012); also see Anderegg and others (2013)].
40

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

2007). These kinds of changes are important both in the 

context of a trend acting on existing vegetation, wherein 

a single crossing into unprecedented weather or 

drought severity is a critical concern, and in the context 

of potential future plant communities, which may be 

shaped more by the extremes in future climate than 

the means. Extremes, and the events associated with 

them, will likely be critical determinants of ecological 

change (Dale and others 2001, Easterling and others 

2000, Jentsch 2007).

This sense of drought as an extreme is of particular 

concern with respect to GCM outputs, which are 

poor at representing interannual variability (e.g.,

Sperna Weiland and others 2010). Only a few GCMs 

accurately recreate the ENSO pattern, a driver of 

interannual scale variability in weather across much of 

the World (IPCC 2013, Seager and others 2012). Most 

outputs of GCM information are ensemble averages 

of several realizations from a given model and across 

models. This allows comparison of climatic averages 

across models, and maps of these average changes 

are the common maps of change shown in IPCC 

reports (e.g., figs. 2.7–2.9). Common downscaling 

procedures draw directly from this kind of information 

to specify an average difference for a given month 

or season for each GCM grid cell (Wood and others 

2004). For example, interannual variability in Variable 

Infiltration Capacity (VIC) hydrologic projections (Vano 

and others 2012) is a legacy of the historical time 

series on which the changes in the averages 

are placed.

GCMs are also more challenged by precipitation 

estimates than other climate characteristics (Blöschl 

and Montanari 2010, Johnson and Sharma 2009). 

GCMs show substantial agreement with metrics like 

pressure and temperature, but notable discrepancies 

in precipitation, and the differences among the 

models are not well understood (IPCC 2013). Some 

of the issue is almost certainly that precipitation 

processes occur at scales much smaller than those 

of GCM grid cells (e.g., Rasmussen and others 2011). 

While GCMs can model general circumstances of 

temperature, temperature stratification, and vapor 

that are more or less encouraging of precipitation, 

they ultimately must rely on sub-grid-scale 

parameterizations to estimate precipitation. That is to 

say that semi-empirical equations or rules are applied 

instead of solution to partial differential equations 

derived from the basic physics, as is done for 

temperature and pressure. One consequence of the 

large grid-cell size is also that most GCMs produce 

what amounts to a persistent drizzle (e.g., Gao and 

Sorooshian 1994, Pitman and others 1990), reflecting 

the general scale-related issue that it is almost always 

raining somewhere within a GCM cell, but it is usually 

a fairly small proportion of the area experiencing 

precipitation. As an addition to the problem, GCMs 

do not model the control that mountains place on 

precipitation generation, which has led to efforts 

to regionally downscale the GCMs to better 

reflect topographic influences on precipitation in 

mountainous areas using Regional Climate Models, 

which have higher spatial resolution (Rasmussen and 

others 2011, Salathé and others 2010).

Projections of the key climate phenomena feeding 

moisture to the continental United States in the 

summer—the North American Monsoon System 

(NAMS) and North Atlantic tropical cyclones—are 

uncertain (IPCC 2013); however, there appears to 

be a tendency toward drier conditions, according 

to the climate models with the strongest historical 

performance (Maloney and others 2014, Sheffield 

and others 2013). The most consistent projection 

for NAMS relevant to drought is an increase in the 

number of consecutive dry days by 15–40 percent 

(interquartile range). In the context of a warming 

future, an increase in the time between precipitation 

events could have substantial ecological importance 

(Adams and others 2009).

Applying Drought Projections To Predict Impacts

The overall consensus on drought projections is that 

there is a great deal of uncertainty, primarily because of 

uncertainty in projecting future precipitation; however, 

drought projections can be useful when placed in 

the proper context. Drought is a derived quantity 

with dimensions of severity, frequency, scale, and 

organization. It can be thought of as a collection of 

“extreme” events that must occur simultaneously to 

create a situation of concern, such as tree mortality or 

water scarcity. There is some sense that drought will 

intensify faster (or alternatively, drought effects will 

manifest more quickly during a dry spell) than it has 

in the past (Trenberth and others 2014). For example, 

“global-change-type drought” infers that drought is 

occurring in the context of much warmer weather 

(Adams and others 2009, Allen and others 2010) 

and, hence, the effects on forests are greater. When 

combined with projections of longer interstorm periods 

in some locations, impacts on terrestrial ecosystems 

could be substantial.
41

CHAPTER 2

Characterizing Drought for Forested Landscapes and Streams

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Summary

Historical and paleoclimatic evidence clearly shows that 

the nature of drought has always changed and continues 

to change. The direction of trends in recent history 

vary from region to region, with the western half of the 

United States indicating broadly drier conditions while 

the eastern regions show broadly wetter conditions. 

Although these patterns are often used to generalize 

about changing drought regimes (e.g., rarer, more 

frequent, more severe, or unchanging), individual 

findings can conflict with one another because the 

definitions or quantification methods for “drought” differ 

among many studies (Seneviratne and others 2012).

The relationship between forested landscapes and 

drought may differ substantially from that of the 

engineered or agricultural landscape. In particular, 

water supply thresholds may exist for particular crops 

or industries. In contrast, forest ecosystems often 

have mechanisms of resilience to drought, such that 

their ultimate response to drought may not relate to 

the initial perturbation after a drought event, but rather 

the context of that event and others like it in time and 

across landscapes and stream systems. While there is a 

well-developed science on how various biota respond to 

individual events, it is this longer term consequence that 

will have a lasting effect on species distributions.

Droughts severe enough to affect forest ecosystems 

may be driven primarily by periodic deficits in 

precipitation, as opposed to changes in potential 

evaporation (e.g., Abatzoglou and Kolden 2013, Holden 

and others 2012). Although incoming radiation is 

adequate in most places in the continental United States 

to evaporate a substantial fraction of the annual water 

balance (see fig. 2a in Sankarasubramanian and Vogel 

2003), variation in annual precipitation is the dominant 

driver of variations in annual water balance (Milly and 

Dunne 2002). On longer time scales, however, the 

availability of warmer and drier air may more broadly 

shift many places to more consistently arid conditions. 

If drought is considered from the viewpoint of a global/

absolute threshold, as might be the case for a particular 

plant or an engineered system, this broad shift could 

presage a drought from the point of view of system 

tolerance. However, if drought is defined in terms of 

variability over time (given a particular time-averaging 

window), which has substantial relevance to selfregulating or temporally dynamic systems, increasing 

potential evapotranspiration pressure primarily has 

relevance to the rapidity of drought onset after 

precipitation stops. This variation in framing has been a 

central issue in debates on the kinds of metrics to apply 

in evaluating trends in droughts and making projections.

The future of drought is uncertain. One aspect of 

uncertainty is that precipitation projections in GCMs 

are fairly poor. A second aspect of uncertainty is 

that persistently wetter or drier conditions do not 

necessarily reflect drought risks in natural systems the 

same way that they might be observed in engineered 

or agricultural systems. In natural systems, there is 

adjustment to gradual shifts in means or even regimes; 

however, variability on the order of a few years to 

a few decades can have substantial impacts on 

ecosystems. These intermediate time scales pose the 

greatest challenge for GCM projections. Improving our 

understanding of temporal trends in teleconnections 

and climate indices may be a fruitful alternative in 

understanding future variations at these intermediate 

time scales.

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CHAPTER 3

N. McDowell is a Staff Scientist, Earth and Environmental Sciences Division, Los Alamos 

National Lab, Los Alamos, NM 87545.

P.J. Hanson is a Corporate Fellow and Group Leader, Climate Change Science Institute 

and Environmental Science Division, Oak Ridge National Lab, Oak Ridge, TN 37830.

I. Ibáñez is an Associate Professor, School of Natural Resources and Environment, 

University of Michigan, Ann Arbor, MI 48109.

R.P. Phillips is an Associate Professor, Department of Biology, Indiana University, 

Bloomington, IN 47405.

M.G. Ryan is a Senior Research Scientist, Natural Resource Ecology Laboratory, Colorado 

State University, Fort Collins, CO 80523.

Physiological Responses 

of Forests to 

Future Drought

Nate McDowell

Paul J. Hanson

Inés Ibáñez

Richard P. Phillips

Michael G. Ryan
50

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Physiological Responses of Forests to Future Drought

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

Drought has long been viewed as a dominant factor 

regulating the distribution, productivity, and survival 

of plants (Running and others 2004). The nature of 

drought impacts is currently changing, however, due 

to a warming climate. As air warms, it can hold more 

water, making dry conditions relatively drier because 

the air extracts more water from the soil and from 

plant canopies (Held and Sodden 2006). In essence, 

a survivable drought of the past can become an 

intolerable drought under a warming climate (Williams 

and others 2013). In this chapter, we revisit the concept 

of drought from the perspective of plants and how 

they deal with droughts under warmer conditions, 

and we examine how models simulate future drought 

responses.

A Plant’s Perspective 

on Drought

At the most basic level, drought for a plant is defined 

as a deficit in the amount of water available for 

transpiration relative to plant and atmospheric demand. 

Quantifying this imbalance requires understanding 

how much water is available to plants from subsurface 

reservoirs, the evaporative demand, and the plant’s 

hydraulic conducting system. Thus, mechanistic 

measures of plant physiological responses to drought 

require an expression of “plant available” water.

Soil Water Potential

Water is generally most available for plant uptake when 

soils are between field capacity and species-specific 

wilting points (Kozlowski and Pallardy 2002). While 

the leaf wilting point is relatively fixed at species- and 

condition-specific values, variability in soil water, 

expressed as soil water potential, can drive a large 

amount of variation in transpiration (E) as seen from 

Fick’s law

E = ks (Ψleaf – Ψsoil) (1)

where ks is plant hydraulic conductance, and Ψleaf and 

Ψsoil are leaf and soil water potentials, respectively. 

As can be seen, variation in Ψsoil is one of the critical 

parameters defining E.

Unfortunately, direct measures of the physiologically 

relevant Ψsoil (and Ψleaf) are difficult to obtain in the 

field and are often replaced with either gravimetric or 

volumetric measures of the amount of water stored in 

a given sample of soil volume or mass. It is possible 

to translate such data to soil matric potential, but the 

necessary nonlinear functions are not readily available 

for all sites and vary considerably across sites and with 

soil depth at a given site (Saxton and Rawls 2006). As 

a result, plant available soil water has often also been 

expressed as the relative amount of water stored in 

a soil with respect to its maximum saturated water 

capacity (Waring and Running 2010). The choice of the 

expression of soil water status impacts our impression 

and definition of drought. This is demonstrated using an 

example from a long-term study in Tennessee (see the 

text box on the following page).

Many models use relative water content as an 

expression of available water in soils (Hanson and 

others 2004), but such a metric does not account for 

the nonlinear nature of soil moisture availability with 

drying. Future assessments of drought effects on 

forests and the modeling of such effects should strive 

to employ soil water potential for various soil depths to 

better characterize drought severity across events and 

years. An integrated sum of daily water potential values 

(becoming more negative with drought severity) has 

been suggested as a metric for comparing the nature of 

one drought versus another (Hanson and others 2003).

Evaporative Demand

While soil moisture is critical for defining the ability of 

a plant to transpire, the evaporative demand placed 

upon the plant’s canopy is equally important to defining 

drought impacts on plants. This is because of the 

application of Fick’s law to transpiration (E) at the 

canopy scale:

E = gs • VPD (2)

where VPD is vapor pressure deficit, or the 

difference in vapor pressure between the leaf and 

the atmosphere, and gs is stomatal conductance. 

VPD rises with temperature (for a given absolute 

humidity) due to the greater water holding capacity 

of warmer air, and drought is often associated with 

high temperature extremes and lower relative and 

absolute humidity resulting in higher VPD. From a 

plant’s perspective then, drought means not only 

periods of low soil water availability but can also 

include periods of warmer temperatures and higher 

VPD. High VPD impacts plants by either stressing 

the water conducting system or by eliciting stomatal 

closure (or a combination)—both mechanisms can 

negatively affect plants. If plants do not regulate gs, 
51

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

THE WALKER BRANCH WATERSHED: 

Drought Characterization Varies as 

Different Metrics are Employed 

The long-term record of soil water observations available for the Walker Branch Watershed in Tennessee 

(Hanson and others 2003) demonstrates the concept of how use of the water potential metric changes the 

“expression” of drought in a wet eastern forest, where years exist with both minimal and severe moisture 

stress. If soil water content below field capacity is chosen as the metric of water deficit associated with 

drought (fig. 3.1A), one might conclude that “drought” was occurring in approximately 11 of the 13 years. 

However, if soil matric potential is derived from soil water content using soil moisture release characteristics, 

a very different picture emerges. The soil matric potential data show reduced water availability in the surface 

soils for only 5 of 13 years, and perhaps for no more than 3 of 13 years when deeper soil water supplies are 

evaluated (fig. 3.1B). Matric or total soil water potential, the more mechanistic expression of what influences 

plant water status, provides a different view of soil water availability to plants than does soil water content. In 

this example for a wet eastern forest, the number of years characterized as “drought years” is appropriately 

reduced when the water potential metric is employed. Soil water potential (MPa)

(B) 0

-0.5

-1

-1.5

-2

-2.5

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Measurement year

Soil water content

(percent by volume)

(A) 30

25

20

15

10

5

0

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Figure 3.1—A 13-year record of (A) soil water content or (B) soil water potential at two measurement depths (0–35 and 35–70 

cm) for the Walker Branch Watershed in Tennessee [modified from data in Hanson and others (2003)]. The dashed line in 

graph B represents a hypothetical threshold for critical plant water stress response. It is clear that similar surface water (0–35 

cm depth) potentials are approaching critical drought thresholds while somewhat deeper soils (35–70 cm depth) retain ample 

soil water for plant function.
52

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

then high VPD can cause E to be higher than the plant 

can sustain because of low soil moisture and limits 

on the hydraulic conductance of the water transport 

pathway from soil to leaf. Excessively high E thus

results in cavitation, or the nucleation of air bubbles 

within xylem, which blocks water transport (Sperry 

and others 1998). Cavitation can be repaired, but only 

when the demand for water is significantly less than 

soil moisture availability, which is unlikely to occur 

during severe drought. If left unchecked, cavitation can 

lead to hydraulic failure and subsequent desiccation 

of foliage (McDowell and others 2011). Plants can 

close their stomata by reducing gs during periods of 

high VPD in order to minimize E (equation 2), thereby 

minimizing the risk of hydraulic failure. This comes at 

the cost of reduced photosynthesis, however, because 

of lower carbon dioxide (CO2) supply to the foliage 

as the plant’s stomata remain closed. If drought lasts 

sufficiently long, lowered photosynthesis can cause 

reductions in carbohydrate reserves because metabolic 

consumption of carbohydrates continues through 

respiration and other processes (McDowell and others 

2011). Ultimately, this may cause carbon starvation, 

or the process leading to death from cessation of 

metabolism and inability to defend against pest 

attacks as the available carbohydrate supply declines 

(McDowell 2011). Thus, elevated VPD, as occurs 

during drought and with warming air temperature, is 

equally important to plant drought response as soil 

water availability (Breshears and others 2013).

In summary, the climatic conditions that are relevant to 

a plant during drought are largely dominated by Ψsoil and 

VPD (and their influence on Ψleaf), with a key regulation 

existing within the hydraulic conducting pathway of 

the plant. Many drought indices exist (reviewed in Mu 

and others 2013), but we propose that future research 

consider plant-relevant drought indices that are most 

appropriate for management, prognostic forecasting, 

and ecological understanding. Indices that capture 

Ψsoil and, or VPD duration and intensity would be most 

useful.

Belowground Mechanisms 

to Survive Drought

As highlighted in the material earlier, plant regulation of 

the hydraulic pathway is essential during drought. There 

are many above- and belowground aspects of hydraulic 

regulation to be considered during drought, with 

coordination among the plant hydraulic system being 

required for cavitation avoidance (Manzoni and others 

2014). Among the most important regions of regulation 

is belowground. Plants have evolved a number of 

belowground traits and rooting strategies to cope with 

drought. These include morphological traits that are 

relatively fixed for a given species (root architecture, 

anatomy, depth, and type of mycorrhizal association) 

as well as more plastic physiological responses (shifts 

in belowground carbon (C) allocation, increased 

rhizodeposition, hydraulic redistribution) that depend 

on species and environmental context. Unfortunately, 

far more is known about interspecific and intraspecific 

differences in leaf-level responses to water stress than 

belowground responses (Breda and others 2006). Much 

of what is known about root traits and rooting strategies 

of trees comes from studies of seedlings and saplings 

grown under controlled conditions or in common 

gardens rather than from mature trees growing in 

forests (Hanson and Weltzin 2000); though a notable 

exception is the use of water isotopes to track depth 

of uptake (Dawson 1993). Hence, an important priority 

moving forward is to better quantify how root traits 

and belowground processes influence tree species’ 

sensitivities to drought in mature forests.

Morphological Traits

Several morphological root traits are known to influence 

plant responses to water stress. Plants that produce 

small diameter absorptive roots (i.e., roots with high 

mass-specific length or mass-specific surface area) 

increase the amount of root surface area in contact with 

soil water, and thus minimize the impacts of drought by 

exploring a greater volume of soil (Comas and others 

2013). Among the absorptive roots, those with small 

xylem diameters may be more tolerant of drought due 

to their reduced risk of cavitation and embolism, which 

is generally greater in roots relative to shoots (Jackson

and others 1996, 2000). Root architecture and depth 

distribution (dimorphic distribution; presence/absence 

of a tap root) also influence plant responses to water 

stress, if roots growing deep into the soil profile can 

access subsurface sources of water that are uncoupled 

from recent precipitation events. Finally, the mycorrhizal 

status of a plant represents an additional “root trait” 

for coping with water stress. Nearly all plants’ roots are 

colonized to some degree by mycorrhizal fungi. These 

fungi produce thin filamentous structures in soil (i.e., 

hyphae) that increase water uptake and transport by 

increasing absorptive surface area and by exploiting 

water in soil micropores.

Tree species’ differences in root traits likely contribute 

to their drought tolerance. In theory, tree species 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

with an abundance of small-diameter absorptive roots 

should be better buffered from drought impacts than 

those with larger diameter fine roots. This is generally 

true across temperate tree species: oak trees (Quercus

spp.) have smaller diameter absorptive roots than 

maple trees (Acer spp.) which have finer diameters 

than tulip poplar trees (Liriondendron tulipifera) 

(McCormack and others 2012, Pregitzer and others 

2002), and such differences generally correspond to 

the drought tolerance of these species (Brzostek and 

others 2014). However, the greater drought tolerance 

of most oak trees also may relate to other factors 

such as deeper rooting depths and ring porous wood 

anatomy (Meinzer and others 2013).

The mycorrhizal association of tree species may 

influence their tolerance to drought. The two dominant 

types of mycorrhizal fungi that associate with trees are 

arbuscular mycorrhizal (AM) fungi and ectomyocrrhizal 

(ECM) fungi. AM fungi promote drought resistance by 

synthesizing metabolites that act as osmolytes, thereby 

lowering the plant’s water potential (Rapparini and 

Peñuelas 2014). ECM fungi may increase or decrease 

a tree’s susceptibility to drought (Lehto and Zwiazek 

2011) depending on the exploration type of the fungi 

and the ability of the fungi to produce aquaporins, or 

actively regulated water transport channels (Breda and 

others 2006, Lehto and Zwiazek 2011). While studies 

of dual colonists (i.e., tree species that can associate 

with both AM or ECM) suggest that AM tree roots are 

more drought-tolerant than ECM roots (Querejeta and 

others 2009), an analysis of the drought tolerance of the 

20 most common deciduous tree species (>300,000 

trees) in the Midwestern United States suggests that 

ECM trees may be more tolerant of water stress than 

AM trees (Brzostek and others 2014). Such opposite 

trends indicate the need for more research to better 

understand the role of mycorrhizal fungi and mycorrhizal 

association in facilitating water uptake and enhancing 

drought tolerance.

Physiological Responses

Optimal allocation (or partitioning) theory suggests 

that plants should increase C allocation to fine roots 

as soils dry down and water and nutrient limitation 

is exacerbated (Bloom and others 1985). While 

there is some evidence of this at the biome scale 

(Kozlowski and others1991, Schenk and Jackson 2002), 

demonstrations of increases in fine root allocation 

during drought (either absolute or relative) in forest trees 

are inconsistent (Cudlin and others 2007, Eamus 2003, 

Gower and others 1992). In a multi-year throughfall 

displacement study, Joslin and others (2000) found 

that 30-percent reductions in water input induced no 

changes in fine root biomass, fine root turnover, or 

root-to-shoot ratio. Additionally, in a study of 14 mature 

forest stands of European beech (Fagus sylvatica L.) 

across a precipitation gradient, Meier and Leuschner 

(2008) reported that fine root biomass (alone, or per 

unit leaf area) did not decline but rather increased 

with soil moisture, though root diameters generally 

decreased on drier soils (Hertel and others 2013). These 

findings suggest that fine root responses of trees may 

more closely parallel leaf-level responses, and that root 

allocation may depend on whole plant responses to 

water stress (Anderegg 2012). For example, anisohydric 

tree species maintain particularly negative water 

potentials via relatively open stomata and, hence, may 

be more likely to increase belowground C allocation 

during drought than isohydric species that close their 

stomata in response to water stress.

Despite the limited evidence that trees alter allocation to 

fine roots in response to water stress, there is support 

for the hypothesis that water-stressed trees increase 

allocation to roots growing deeper in the soil profile 

(Breda and others 2006, Schenk and Jackson 2002). 

Deeper rooting allows trees to access subsurface water 

resources in both saturated and unsaturated zones; 

if they possess the appropriate traits, trees may also 

transfer water from moist regions of soil to dry regions 

of soil through the nocturnal process of hydraulic 

redistribution (HR), which generally correlates with the 

degree of water limitation in an ecosystem (Schenk 

and Jackson 2002). While there is still some debate 

about the quantitative significance of HR (Neumann 

and Cardon 2012), the phenomenon appears to be 

widespread, occurring in plantation forests (Brooks

and others 2002, Domec and others 2010), old growth 

forests (Brooks and others 2002, Oliveira and others 

2005, Warren and others 2007), and in most tree 

species growing in savannas (Bleby and others 2010, 

Ludwig and others 2003). The ecological consequences 

of HR include enhanced understory growth during 

drought (Dawson 1993, Domec and others 2010), 

increased nutrient availability (McCulley and others 

2004, Sardans and Peñuelas 2014), increased root life 

span (Bauerle and others 2008), and maintenance of the 

vitality of mycorrhizal fungi (Querejeta and others 2007). 

However, it is important to note that the amount of 

water transported through HR also depends on soil type 

and underlying geology (soil texture, depth to bedrock 

and water table, etc.). In shallow soils, for example, 

HR is likely to have limited effects on resilience to 
54

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

drought. Thus, tree species that have the capacity to lift 

large quantities of subsurface water [e.g., sugar maple 

(Dawson 1993)] may still show strong growth decline in 

response to moderate water stress if soils are shallow 

(Brzostek and others 2014).

The Interaction of 

Drought, Host Physiology, 

and Multi-Trophic 

Community Dynamics

Large mortality events in forests are commonly 

associated with the incidence of several stressors (Allen 

and others 2010). Drought can modify trees’ resilience 

and responses to diseases and herbivores by changing 

the tree’s susceptibility to the biotic stressor or by 

combining the effects of multiple stressors (Anderegg 

and Callaway 2012). To certain extents, moderate water 

stress can stimulate tree defenses to resist insect 

attacks or diseases, but severe water stress decreases 

the individual’s capacity to defend against those attacks 

(Herms and Mattson 1992, McDowell 2011). Thus, 

drought may compromise an individual’s recovery from 

other stressors and may also promote their incidence or 

exacerbate their damage (Das and others 2013, Rouault 

and others 2006).

When several stressors affect individual trees 

simultaneously, such as drought and herbivory, the 

combined effects on the physiological functionality 

of the individual tree may be amplified (synergistic 

effects), accounting for more than the sum of the single 

stressors and potentially causing damage from which 

the individual cannot recover (Jactel and others 2012). In 

other cases, the combination of stressors may add up to 

less than the sum of the parts (positive or antagonistic 

effects), and the exposure to a previous stressor may 

ameliorate the effects of a subsequent one (Bansal and 

others 2013). For example, mild drought may reduce 

cell growth but enhance cell differentiation as more 

resources are then available for this process (Lorio 

1986). This would result in thicker cell walls and higher 

concentrations of secondary products that would 

protect the plant from insect pests and diseases (Lorio 

1986, Sharpe and others 1985).

Such disparate and ad hoc interactions make it very 

difficult to predict the outcome of multiple stressors 

and whether threshold-type responses may occur. 

Still, there are sufficient studies to allow for an 

informed assessment of the potential outcomes of the 

combined effect of drought and other biotic stressors.

In addition to the direct effects of drought on tree 

physiological performance, drought conditions can 

also promote the outbreak of forest pests (Ayres and 

Lombardero 2000, McDowell and others 2011, Raffa 

and Berryman 1983), exacerbating the effects of 

water-stress on the trees and ultimately on the whole 

ecosystem (Breshears and others 2005). The damage 

from insect pests under drought conditions seems to 

be related to both the intensity of the drought and the 

insect feeding guild (Jactel and others 2012). Typical 

outbreaks result in increased insect damage of waterstressed trees for chewing and galling insects, and 

decreased damage for sucking and boring pests.

Under drought conditions, the concentration of 

nitrogen compounds and sugars increase in plant 

tissue (Huberty and Denno 2004, Kramer 1983), 

especially in younger aboveground tissues (Mattson 

and Haack 1987), making plants more attractive to 

insect herbivores (Albert and others 1982, Haack 

and Slansky 1987, Mattson and Scriber 1987). The 

increase in concentrations of certain compounds and 

their volatilization may also change under drought 

conditions, promoting host acceptance and aiding 

insects in detection of stressed plants (Kimmerer and 

Kozlowski 1982, Mattson and Haack 1987, Visser 

1986). These same physiological responses in the host 

plant could also explain how drought may promote 

mutualistic organisms associated with insect pests 

(Barras and Hodges 1969, Koricheva and others 1998) 

that could further favor the outbreak.

The link between drought and incidence of plant diseases 

is less documented, and only circumstantial evidence 

points to an increase in plant diseases with drought 

(Desprez-Loustau and others 2006; Maurel and others 

2001a, 2001b). Commonly, disease agents that cause 

increased damage in plants under drought conditions 

are already present on or in their host as saprophytes 

or endophytes (Bachi and Peterson 1985; Blodgett and 

others 1997a, 1997b; Stanosz and others 2001).

The mechanism behind the interaction between drought 

and pathogen attack could be due to the water-stressed 

tissue of the plant being a better substrate for growth of 

the pathogen, or to water stress decreasing the plant’s 

resistance to diseases (Boyer 1995). Trees can respond 

to drought by increasing glucose production and other 

compounds, which could then promote the attack 

and growth of pathogenic fungi (Belanger and others 

1990, Popoola and Fox 2003, Wargo 1996). In other 

cases, the stress caused by drought jeopardizes the 
55

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

plant’s capacity to produce antifungal or antimicrobial 

compounds (Kruger and Manion 1994, Madar and 

others 1995).

As the responses to several stressors are activated 

by overlapping signaling systems, mild exposures to 

one stressor could induce resistance to succeeding 

stressors (Bowler and Fluhr 2000, Jactel and others 

2011). There are instances when the attack of common 

soil pathogens has been reduced by drought and 

where dry soils have decreased the virulence of these 

pathogens (Marcais and others 1993). Resistance to 

drought could also be enhanced by a priori pathogenic 

infestation that conditions the plant to close the 

stomata and to produce stress-related hormones 

(Fujita and others 2006).

Can CO2 Fertilization 

Mitigate Drought Impacts?

While rising CO2 contributes to climate change and 

subsequently to higher intensity of droughts, it is 

important to note that elevated atmospheric CO2 may 

also reduce plant water stress (Franks and others 2013). 

Higher atmospheric CO2 increases the diffusion of CO2

into leaves through the stomata, effectively increasing 

the availability of this critical resource to the plants. 

Most plants have been observed to increase their 

water-use efficiency (the ratio of CO2 uptake to water 

loss) with increases in CO2, and recent reports suggest 

that this may be sustaining the C sink of temperate 

forests (Keenan and others 2013). Additionally, elevated 

CO2 generally increases root growth and rooting depth 

(Iversen 2010), which may help deep-rooted species 

overcome water stress. This short-term benefit of 

elevated CO2 can yield sustained and significant 

increases in the growth of forests. However, multiple 

negative costs have also been observed. Increased 

growth results in higher leaf area of individual trees, 

which predisposes them to even greater drought 

stress (compared to a non-CO2 fertilized stand) when 

and if a drought strikes (Warren and others 2011). 

This is because they hold greater transpiring leaf area, 

thus the consumption of water is higher from these 

larger canopies, requiring more water to maintain 

hydraulic function. This mechanism has been invoked 

as a primary driver of oak (Quercus robur) mortality in 

Europe (Levanič and others 2011).

At the global scale, CO2 fertilization has been observed 

to increase growth in only 20 percent of forests 

(Geldanhoff and Berg 2010). The authors indicated that 

the remaining 80 percent of forests were constrained 

from capitalizing on the CO2 benefits by drought, and 

in some cases nutrient limitations. Furthermore, longterm studies of forest survival indicate that forests are 

dying at greater rates than they are regenerating (Peng 

and others 2011, van Mantgem and others 2009), and 

particularly large mortality events are being witnessed 

with increasing frequency (Allen and others 2010, 

Carnicer and others 2011). This increase in mortality 

is happening as atmospheric CO2 is increasing, thus 

negating the inference that CO2 is promoting greater 

forest survival (Franks and others 2013). Even in 

systems where growth is increasing, these benefits, 

which can take decades to manifest, are often wiped 

out in a single drought event (Allen and others 2010).

Do Ecosystem Models 

Include Plant DroughtResponse Mechanisms?

Unfortunately, ecosystem biogeochemical cycling 

models contain a limited capacity to capture plant 

responses to drought. Model-data intercomparison 

summaries have emphasized that biogeochemical 

cycling models perform poorly under drought 

conditions (Hanson and others 2004) stemming largely 

from the lack of root and stem hydraulic characteristics 

in those models. Iversen (2010) characterized root 

traits and function within models dealing with elevated 

CO2 response as ranging from being absent to being 

included as the presence of root mass density with 

depth. Warren and others (2015) further detail the role 

of roots within models and concluded that significant 

improvements need to be pursued to include root 

characteristics and function into ecosystem models. 

The lack of known drought response mechanisms 

within models limits their capacity for the prediction 

of plant and ecosystem response to current and future 

drought, and typically produces model results that 

overestimate the sensitivity of plants and ecosystems 

during drought. This error is perhaps greater in wetter 

ecosystems [eastern forests (Hanson and others 

2004, Hanson and Weltzin 2000)] where models are 

“tuned” to nondrought conditions. Improved long-term 

assessments of forest responses to drought demand 

that ecosystem models include many of the drought 

mechanism described in this section. Major advances 

have been made in the representation of within-plan 

hydraulics and carbohydrate allocation (McDowell and 

others 2013). Parolari and others (2014) take further 

steps in this direction with a focus on capturing the 

process of forest mortality.
56

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Conclusions

There are a number of aspects of the physiological 

responses of plants to drought that are clearly well 

understood, such as regulation of transpiration. In 

contrast, the response of the belowground system, 

ecosystem interactions across multiple trophic scales, 

and the interaction of drought with elevated CO2 are 

less well understood and are critical areas for future 

research. Understanding these responses will greatly 

enhance our ability to simulate future forest responses 

to drought.

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Academic Press. 440 p. 

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CHAPTER 4

J.S. Clark is the Nicholas Professor of Statistical Science at Duke University, Nicholas School 

of the Environment, Durham, NC 27708.

L. Iverson is a Landscape Ecologist, U.S. Department of Agriculture, Forest Service, 

Northern Research Station (NRS), Delaware, OH 43015.

C.W. Woodall is a Research Forester, U.S. Department of Agriculture, Forest Service, 

Northern Research Station (NRS), St. Paul, MN 55108.

C.D. Allen is a Research Ecologist in Ecosystem Dynamics, Jemez Mountain Field Station, 

Bandelier National Monument, U.S. Geological Survey (USGS), Los Alamos, NM 87544; 

D.M. Bell is a Research Forester, U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station (PNW), Corvallis, OR 97331; D.C. Bragg is a Research Forester, 

U.S. Department of Agriculture, Forest Service, Southern Research Station (SRS), Monticello, 

AR 71656; T. D’Amato is an Associate Professor in Silviculture and Applied Forest Ecology, 

University of Vermont, Burlington, VT 05405; F.W. Davis is a Professor of Landscape Ecology 

and Conservation Planning, Bren School of Environmental Science and Management, 

University of California, Santa Barbara, CA 93106; M. Hersh is a Professor of Biology, Sarah 

Lawrence College, Yonkers, NY 10708; I. Ibáñez is an Associate Professor; School of Natural 

Resources and Environment, University of Michigan, Ann Arbor, MI 48109; S.T. Jackson

is Director of Southwest Climate Science Center, U.S. Geological Survey (USGS), Tucson, 

AZ 85719; S. Matthews in an Ecologist, U.S. Department of Agriculture, Forest Service, 

Northern Research Station (NRS), Delaware, OH 43015; N. Pederson is a Senior Ecologist, 

Harvard Forest, Petersham, MA 01366; M. Peters is a Geographic Information System (GIS) 

Technician, U.S. Department of Agriculture, Forest Service, Northern Research Station (NRS), 

Delaware, OH 43015; M. Schwartz is a Professor of Conservation Science for Climate 

Change Adaptation, Department of Environmental Science and Policy, University of California 

at Davis, Davis, CA 95616; K. Waring is an Associate Professor, School of Forestry, Northern 

Arizona University, Flagstaff, AZ 86001; N.E. Zimmermann is a Senior Scientist, Swiss 

Federal Research Institute WSL, Zurich, Switzerland. 

Impacts of Increasing Drought 

on Forest Dynamics, Structure, 

Diversity, and Management

James S. Clark

Louis Iverson

Christopher W. Woodall

contributors

Craig D. Allen, David M. Bell, Don C. Bragg, Tony D’Amato, 

Frank W. Davis, Michelle Hersh, Inés Ibáñez, Stephen T. Jackson, 

Stephen Matthews, Neil Pederson, Matthew Peters, Mark Schwartz, 

Kristen Waring, and Niklaus E. Zimmermann
60

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

At the time of this writing in 2015, drought conditions 

have sustained over much of the continental United States 

for up to 4 years. Drought, a moisture limitation resulting 

from below average precipitation, high temperatures, or 

both, represents a departure from the “mean climate” of 

a region—and more frequent and severe droughts change 

this mean climate. Multi-year droughts have occurred 

throughout history (chapter 2); recent concern about 

prolonged drought has arisen because the increasing 

rainfall variation of recent decades (Janssen and others 

2014, Li and others 2011) was a predicted consequence 

of greenhouse gas-driven warming (IPCC 1995, Overpeck 

and others 1990). While combined warming and variable 

precipitation have amplified forest drought severity in 

the last two decades (Allen and others 2015, Millar and 

Stephenson 2015) across the country (see text box 

below), the Western United States in particular has 

experienced numerous and widespread drought-related 

stand replacement events (e.g., Allen and others 2010, 

Breshears and others 2005, Ganey and Vojta 2011). 

FOREST DROUGHTS HAVE INCREASED IN RECENT DECADES

What changes in drought are in progress now? Drought severity and frequency have been especially high 

during the last few decades in the West, Southeast, and Lake States, and are at least part of the explanation 

for tree mortality (fig. 4.1). The Cumulative Drought Severity Index (CDSI) shows the sum of monthly Palmer 

Drought Severity Index (PDSI) drought classes (1–moderate, 2–severe, 3–extreme) from 1987–2013. Values 

are aggregated by climate division and shown for the 21 forest cover types defined by the USDA Forest Service 

(2000). Locations of documented drought-related mortality generally correspond with locations of high CDSI. 

Compared with the previous 27-year period (1960–1987), the West saw increases in all drought classes and 

only minor change in the East (fig. 4.2). 

Severe multi-year drought episodes in the West are linked to drought-related tree mortality. There are fewer 

documented examples of recent drought-induced tree mortality in eastern U.S. forests. Note that the map of 

cumulative drought over 27 years does not always capture short-term intense drought events.

21 19 

1,2 

5,16 

3,4,11,15 

5 

6 

7 

8 

20 

13 

9 18 

17 

12 

10 

22 

23 

23 

14 

CDSI

< 50

51 – 100

101 – 150

151 – 200

201 – 250

> 250

Figure 4.1—Cumulative drought severity index (CDSI) for 

forested lands from 1987–2013 with selected locations of 

drought- and heat-induced tree mortality indicated by blue 

circles and dots. 

Numbers on map correspond to the following supporting references: 1–Anderegg 

and others (2012); 2–Anderegg and others (2013b); 3–Breshears and others (2005); 

4–Breshears and others (2009); 5–Creeden and others (2014); 6–DeRose and Long 

(2012); 7–Faber-Langendoen and Tester (1993); 8–Fahey (1998); 9–Fellows and 

Goulden (2012); 10–Ganey and Vojta (2011); 11–Garrity and others (2013); 12–Kaiser 

and others (2012); 13–Klos and others (2009); 14–Kukowski and others (2012); 15–

Macalady and Bugmann (2014); 16–Meddens and others (2012); 17–Millar and others 

(2012); 18–Minnich (2007); 19–Moore and others (In press); 20–Olano and Palmer 

(2003); 21–Twidwell and others (2014); 22–Williams and others (2013); 23–Worrall 

and others (2013). (modified from Peters and others 2014).

0

2

4

6

8

10

12

14

16

WEST

1960-1986

WEST

1987-2013

EAST

1960-1986

EAST

1987-2013

Percent of months

Moderate Severe Extreme

Figure 4.2—Drought for forested land of the conterminous 

United States for two 27–year periods from 1960 to 2013. For 

each forest type, drought conditions were summarized as the 

percentage of months during the 324–month period (27 years) 

among climate divisions that contained the forested land. 

(Peters and others 2014).
61

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

The work that follows examines not only these 

well-publicized western forest diebacks, but also 

considers inherent forest vulnerabilities to drought; it 

also highlights how little we actually know about the 

consequences of drought at all levels. Understanding 

how climatic changes already in progress will impact 

forests can help us anticipate socioeconomic impacts 

(chapter 11) and consequences for biodiversity. This 

synthesis of current understanding begins with an 

evaluation of the data available, followed by a synopsis 

of studies ranging from short-term observations, 

paleoecological research, and modeling work across 

a range of scales from individual trees to forest 

stands, landscapes, and regions. For example, there 

are numerous drought-related observations that 

generally hold for individual trees, such as drought 

tolerance increasing with tree size and age in many 

species (Cavender-Bares and Bazzaz 2000). We then 

translate how changes to plant-available moisture may 

affect the distributions of species, the biodiversity 

of landscapes, wildfire, net primary production, and 

virtually all goods and services provided by forests, 

including the development of a better understanding 

of tree biogeography. Finally, we provide advice for 

how management practices might be adapted to more 

frequent drought and address research needed to 

expand our understanding of forest response to drought.

Evidence for Drought 

Impacts on Forests

An Assessment of Available Data

To date, much of what we know about the effects of 

drought on the structure, composition, and function 

of forests in the United States has arisen from 

observations and data-driven interpretations of resource 

gradients, providing valuable if limited insights. Data 

sets that span sufficient temporal variation in climate 

are improving. Two censuses can be used to generate 

estimates of (1) mortality rates from numbers of trees 

that die during the interval (Dietze and Moorcroft 2011, 

Lines and others 2010); (2) recruitment rates from 

individuals appearing in a census not present previously 

(Zhu and others 2014); and (3) growth rates from 

changes in size (Vanderwel and others 2013). However, 

estimates of change over time, including forest 

demographic responses to climate change, require 

a minimum of three censuses. Forest Inventory and 

Analysis (FIA) data provide two consistent censuses 

for most of the Eastern United States (a third census is 

now available for some locations), but only one census 

for most of the West because nationally consistent 

sample design and plot protocols were not adopted by 

FIA until the late 1990s (Goeking 2015). This uneven 

coverage makes it possible to consider the geographic 

correlation of climate effects on demographic rates 

(Dietze and Moorcroft 2011, Lines and others 2010, 

Purves 2009, Vanderwel and others 2013), but using 

them to understand change over time is difficult.

In addition, potentially long plot observation periods 

complicate the interpretation of specific climate effects. 

FIA inventory plots have been resampled at intervals of 

4 to 10 or more years, which means data derived from 

them could encompass exceptionally warm, cold, dry, 

and wet years (Williams and others 2013). An individual 

tree contributes to a growth study one observation for 

each year of growth. By contrast, one tree contributes 

to a survival study a single event (survival or not). 

However, attribution of tree responses to drought based 

on observational studies is challenging because many 

factors can contribute to morbidity (Adams and others 

2009, Allen and others 2010, Manion 1981, McDowell 

and others 2011, Radtke and others 2012, Wang and 

others 2006). Even the most complete inventories 

are hampered by inconsistent temporal coverage 

of observed droughts. As an example, droughts are 

predicted to increase in the Northeast (Melillo and 

others 2014), a region with droughts evident in the 

paleorecord (Pederson and others 2013) (chapter 2) but 

lacking severe events in recent decades when much of 

the most reliable forest inventory data was collected.

The previous point on inconsistent contemporary 

observations highlights the fact that many other types 

of important data are also uneven in their coverage. For 

example, many studies of the paleorecord on vegetative 

responses to climate come from wet environments, 

and thus overrepresent wetland species. Similarly, 

tree-ring data come primarily from trees expected to 

be most sensitive to climate (Fritts 1976)—often dry, 

sparsely forested locations. In these tree-ring-based 

climate reconstructions, old canopy trees are preferred, 

but these individuals respond differently to drought 

and heat stress than younger trees and may not reflect 

genetic selection pressures that may influence the 

responsiveness of future forests to drought stress. 

Although inferences using spatiotemporal variation 

have long provided some of the most valuable insights 

on how forests respond to moisture and temperature 

gradients, those effects can be confounded by land 

use, management history, soils, complex hydrological 

patterns, and atmospheric chemistry change. For 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

example, inferences on drought impacts to different 

landowners are confounded by who owns what forest 

where. In the Pacific Northwest, private landowners 

primarily control productive low-elevation forests 

managed for timber production, whereas State and 

Federal agencies usually manage the less-productive 

and high-elevation old-growth forests of this region 

(Ohmann and Spies 1998) less intensively (if at all). 

Hence, Pacific Northwest forests reflect a multidimensional set of climatic, geological, and land-use 

gradients that are both driven and influenced by their 

composition, meaning that predicting future drought 

effects will be very difficult. In the Piedmont Plateau 

of the Southeast, moisture gradients are confounded 

by land use and stand age: wet bottomlands were left 

uncultivated and hence tend to have mature forests 

with older trees, while younger forests established on 

previously cultivated sites about a century ago and xeric 

sites were grazed and often remain in pasture (Oosting 

1942, Quarterman and Keever 1962). Attributing forest 

changes to climate can be challenging when they are 

simultaneously experiencing rising levels of atmospheric 

ozone (O3) and carbon dioxide (CO2), greater nitrogen 

(N) deposition, and increasing overall stand age 

(McMahon and others 2010). 

As a consequence of these factors and many others, 

observational data may not yield unambiguous 

relationships, and they offer only a subset of conditions 

that may prevail in the future. Hence, observational data 

are poorly suited for predicting how forests may respond 

to droughts because they provide a phenomenological, 

not mechanistic, interpretation of change. 

Experimentation addresses some of the limitations of 

observational data by providing controlled manipulations 

of the environment. However, to date, relatively few 

experiments have been conducted at a scale that 

provides general insight for climate changes that affect 

diverse habitats. For example, there are still only a 

few rainfall exclusion and redistribution experiments 

on mature forests (e.g., Hanson and Weltzin 2000, 

McDowell and others 2013). In addition, species will 

outrun some of their mutualists, competitors, and 

natural enemies, and encounter new ones. Some of 

these processes are too slow, too small, or too large to 

observe directly or manipulate experimentally; others 

do not become apparent until thresholds are crossed 

and dramatic shifts in composition and structure are 

witnessed (Millar and Stephenson 2015). Experiments 

sufficiently large and long-term to determine effects 

on stand composition and structure are also costly. 

Because of these constraints, future combinations of 

climate, competition, and natural enemies cannot be fully 

anticipated by controlled experiments.

Influence of Drought on Individual Trees

Drought and tree growth—Many conifers and some 

hardwoods show growth responses to temperature at 

high elevations and at northern range margins (Bhuta 

and others 2009, Brubaker 1980, Cook and others 1998, 

Littell and others 2008, Salzer and others 2009). Tree-ring 

studies support the interpretation that growth in moist 

cove sites of the Southern Appalachians is sensitive 

to moisture variation (Martin-Benito and Pederson 

2015, Maxwell and others 2011, Pederson and others 

2012) (fig. 4.3). Not surprisingly, growth sensitivity to 

drought differs between species. Tree-ring studies from 

the Hudson River Valley in New York ranked growth 

responses to spring-summer Palmer Drought Severity 

Index (PDSI) as eastern hemlock (Tsuga canadensis) > 

tuliptree (Liriodendron tulipifera) > pignut hickory (Carya 

glabra) > chestnut oak (Quercus montana) > northern 

red oak (Quercus rubra) > black oak (Quercus velutina) 

(Pederson and others 2013). A 13-year study in Indiana 

found tuliptree and sassafras (Sassafras albidum) to be 

more sensitive to drought than oaks (Brzostek and others 

2014). However, in southern Indiana, white oak (Quercus 

alba) responded more to summer PDSI variation than 

did tuliptree, whereas northern red oak responded less 

than either species (Brzostek and others 2014, Maxwell 

and others 2014). Even in mesic sites, tuliptree can 

experience larger growth sensitivity to drought than cooccurring white oak and black oak (Orwig and Abrams 

1997). Evidence for drought effects on species of 

many of the same genera in Europe appears consistent 

with these observations. In central Germany, growth 

responses to PDSI ranked as European beech (Fagus 

sylvatica) > Scots pine (Pinus sylvestris) > durmast oak 

(Quercus petraea), with greatest sensitivity on the site 

with low rainfall (Friedrichs and others 2009). Durmast 

oak survival exceeded that of European beech over the 

1976 drought in England (Cavin and others 2013).

Drier than normal conditions tend to have less impact 

on growth rates of oaks than other species (Clark and 

others 2011, 2014a; Elliot and Swank 1994; Klos and 

others 2009), probably related to physiology and deep 

rooting (Abrams 1990, Abrams and Kubiske 1990, 

Iverson and others 2008b) (chapter 3). The rank order of 

growth sensitivity of mesic hardwood > pine > oak from 

Clark and others (2014b) is consistent with growth and 

mortality trends reported for the 1999–2001 drought 

from analysis of FIA data (Klos and others 2009). 

Despite low growth sensitivity to drought on average, 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

white oak growth rates can be correlated with moisture 

available early in the growing season, particularly in 

dry climates (LeBlanc and Terrell 2009, Pasho and 

others 2011). A combination of high temperatures 

and a reduction in moisture could further benefit oaks 

because many nonoak hardwoods display intermediate 

drought sensitivity for growth (Clark and others 2013, 

Klos and others 2009). Although oaks in the red oak 

subgenera can be susceptible to mortality during 

drought (Clinton and others 1993, Elliott and Swank 

1994, Haavik and others 2011, Hursh and Haasis 1931, 

Jenkins and Pallardy 1995, Pedersen 1998, Starkey and 

others 1988, Voelker and others 2008), white oaks can 

show stronger growth responses.

Local environmental conditions further mediate drought 

impacts on individual tree growth. For most species 

of the southeastern Piedmont and Appalachians, the 

largest growth sensitivity to drought occurs for trees at 

high light levels, a positive light-drought interaction. This 

positive interaction has been shown for juvenile growth 

of loblolly pine (Pinus taeda) (fig. 4.4), but it is not 

evident for adult growth or for fecundity. The interaction 

between localized soil moisture conditions and drought 

has implications for whether or not moist sites can 

provide a refuge for some species if droughts intensify. 

Short-term responses in mesic sites could be important 

for the drought-sensitive species dependent on such 

habitats. Furthermore, specific edaphic characteristics 

also influence the severity of droughts. For example, 

fragipan soils in some pine flatwoods of the Southeast 

restrict root depth and access to deep moisture 

(Rahman and others 2006, Wackerman 1929).

Large growth and fecundity responses to drought 

in southeastern forests could occur initially for trees 

4

2

0

-2

-4

-6

Kentucky mesic trees Eastern Kentucky drought

Reconstructed summer PDSI

Normalized radial increment

1800 1850 1900 1950 2000

Year

4

2

0

-2

-4

-6

Figure 4.3—Growth responses to summer drought on mesic sites in Kentucky, 1796-2005. Average tree growth 

(orange line with circles) correlates with an independent reconstruction of summer Palmer Drought Severity Index 

(PDSI) (June, July, August) (r = 0.55, blue line). Chronologies plotted in light gray include eastern hemlock (Tsuga 

canadensis), tuliptree (Liriodendron tulipifera), chinquapin oak (Quercus muehlenbergii), and blue ash (Fraxinus 

quadrangulata). Despite differences in collections and land-use histories, they show a similar change in direction 

during specific PDSI conditions: positive growth during wet conditions (PDSI ≥ 2) and vice-versa (adapted from 

Pederson and others 2012).
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

at high moisture levels, where leaf area, and thus, 

moisture demand is greatest (fig. 4.5) (Clark and 

others 2014b). Mesic sites might see more dramatic 

transitions because they often support sensitive species 

dependent on abundant moisture (Clark and others 

2014b, Elliot and Swank 1994). Still another possibility is 

that sensitivity could be highest on sites of intermediate 

moisture (Dormana and others 2013). Moreover, the 

sign of the interaction between drought index and 

local drainage might shift from short-term positive 

(loss of moisture-demanding species on mesic sites) 

to negative (eventually the moist sites provide refuges 

for some species). Both phenomena could occur 

simultaneously. Stand response to sequential drought 

impacts will differ from individual events (Miao and 

others 2009). 

Drought and tree health—Opportunistic reports of 

mortality following drought are common (Hough and 

Forbes 1943, Parshall 1995), but connections between 

drought and tree death are more difficult to quantify 

than those for tree growth. For example, extensive 

drought across much of the Western United States 

and adjoining Canada coincides with declining tree 

growth, which can anticipate mortality (Allen and others 

2010, Hicke and others 2013, Joyce and others 2014, 

O’Connor 2013, Williams and others 2013). Extended 

morbidity can precede death, a legacy of low vigor 

spanning decades (Wyckoff and Clark 2002), potentially 

related not only to repeated drought (Pedersen 1998, 

Pederson and others 2014, Voelker and others 2008) 

but also to any other risk factors that occur during the 

interval. Mortality rates in some old-growth forests 

during nondrought years have increased since the 

1970s, attributed in part to warming temperatures in 

southwestern forests (van Mantgem and others 2009) 

and boreal forests in western Canada (Luo and Chen 

2013, Peng and others 2011). Even where adequate 

moisture is available, rising temperatures could affect 

the health of individual trees. 

Juvenile sensitivity to warming may restrict future 

habitats to mesic sites (McLaughlin and Zavaleta 

2012). For trees beyond the seedling stage, Luo and 

Chen (2013) argue that warming has greatest impact 

on mortality rates of young trees, but there are also 

reports that old white spruce (Picea glauca) (Wang 

and others 2006) and English oak (Quercus robur) 

(Rozas 2005) show the strongest response to climate. 

Decreased vigor of trees due to drought and/or heat 

stress makes them more vulnerable to secondary 

mortality events. Pathogen-drought interaction studies 

Winter temperature (w) Summer PDSI (m)

Juvenile growth Adult growth Fecundity

Light (C)

Figure 4.4—A joint distribution of three demographic responses is obtained when all responses 

are fitted simultaneously, as part of the same model. This example shows interactions that 

control responses of loblolly pine (Pinus taeda) to winter temperature (above) and summer 

Palmer Drought Severity Index (PDSI) (below) with light availability. Effects differ for growth 

and fecundity, in juveniles and adults. Amplifying positive interactions (growth) and buffering 

negative interactions (fecundity) are both evident. In all panels, contours increase from low at 

lower left to high at upper right (Clark and others 2013).
65

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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

have thus far focused on cankers and root pathogens, 

with less emphasis on foliar diseases and biotrophic 

pathogens (Desprez-Loustau and others 2006). Many 

pathogens can tolerate a greater range of water stress 

than the plants they infect, and the combination of 

pathogen infection and moisture stress on host trees 

can increase disease severity (Desprez-Loustau and 

others 2006). Fungi that commonly occur in plant tissue 

may become pathogenic with reduced resistance 

from a water-stressed host (Desprez-Loustau and 

others 2006). Drought conditions can increase damage 

from secondary pathogens (those infecting tissue in 

poor physiological condition) while reducing damage 

from primary pathogens (those infecting healthy 

tissue) (Jactel and others 2012). Some examples of 

the interactions include increased mortality of holly 

oak (Quercus ilex) seedlings from the pathogenic 

oomycete Phytophthora cinnamomi (Corcobado and 

others 2014) and the transition from quiescent to 

pathogenic Sphaeropsis sapinea on red pine (Pinus 

resinosa) seedlings (Stanosz and others 2001) under 

water stress. Such interactions are also reported in the 

tropics (Brenes-Arguedas and others 2009). Conversely, 

mutualistic associations with mycorrhizae and other 

beneficial microbes may mitigate the effects of 

drought. Drought can decrease mycorrhizal colonization 

(Compant and others 2010) and alter structure and 

function of rhizosphere microbial communities in 

ways that are not yet well understood (Evans and 

others 2014, Hawkes and others 2011). Many fungal 

and oomycete pathogens require moisture for spore 

dispersal, germination, or infection (Desprez-Loustau 

and others 2006). The moisture-pathogen interaction 

is complicated by the fact that moist conditions that 

promote fungal infection can also benefit the host plant 

(Hersh and others 2012).Combined effects may depend 

on the pathogen’s mode of attack and on the degree of 

host stress (Desprez-Loustau and others 2006, Jactel 

and others 2012).

Drought and tree recruitment—This synthesis 

emphasizes growth and mortality, not because they 

are more important than recruitment, but rather due to 

the fact that recruitment is poorly understood. Indeed, 

recruitment warrants special consideration, both for 

its central role in decade-scale responses to drought, 

and because it has been especially difficult to study 

at the regional scale, to represent in models, and to 

predict. Drought can impact future forest composition 

through reduced fecundity, limited seed germination, 

and mortality of shallow-rooted seedlings that have 

limited carbohydrate and water storage (chapter 

3). Unfortunately, most empirical studies of climate 

effects on seed production are limited to a few years 

(or less) and a few small study plots (Clark and others 

1999). Some of the longer studies focus on interannual 

variation, but few provide evidence for decade-scale 

effects of increasing drought.

Drought effects on fecundity are complicated by 

feedbacks with other factors that contribute to masting 

cycles and recruitment success, and the interactions 

involving weather and seed production can span several 

years, thereby precluding simple generalizations on 

effects of drought. For instance, the development 

of moisture limitation over successive years appears 

especially important for fecundity. In general, female 

function in trees is stimulated by resources, including 

moisture (Perez-Ramos and others 2010), CO2 (LaDeau 

and Clark 2001), and light availability (Clark and others 

Sensitivity

1

0

-1

Figure 4.5—Drought effects on growth interact with soil 

moisture. For American elm (Ulmus americana) on the 

Piedmont Plateau in North Carolina, growth is most sensitive to 

drought on wet sites at low elevation (see contours), potentially 

contrary to the intuition that xeric stands are at greatest risk 

of drought. This is a positive moisture index/Palmer Drought 

Severity Index (PDSI) interaction, with the largest response to 

PDSI occuring on moist sites (Clark and others 2014b).
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

2014b). Seed production of many species shows 

positive interactions between moisture and light, with 

trees at high light levels showing the greatest response 

to moisture availability (Clark and others 2014b). Warm, 

dry weather may be beneficial during flower induction 

the year before seeds ripen (Houle 1999, Pucek and 

others 1993), a situation imposed artificially by water 

restriction in some fruit crops (Owens 1995). This 

effect may be enhanced if dry conditions follow a wet 

year (Piovesan and Adams 2001). Drought-induced 

increases in fecundity may be followed by reduced 

seed production up to several years thereafter (Bréda 

and others 2006, Innes 1994). In Mediterranean oaks, 

moisture availability is critical during the time when 

seeds are maturing; masting cycles can be disrupted by 

low rainfall (Koenig and Knops 2013, Perez-Ramos and 

others 2010).

Not all drought influences on tree recruitment should 

be construed as negative. Seedling recruitment and 

resprouting may increase following drought-related 

disturbances that impact the local environment, often 

for many years (Cooper-Ellis and others 1999, Dietze 

and Clark 2008, Kayes and Tinker 2012). Interactions 

with canopy structure and hydrology are important for 

tree recruitment in many different forests. On xeric sites 

in the Western United States, recruitment can benefit 

from a facilitation effect of the canopy on seedlings and 

saplings, an effect that is reduced by drought-related 

reductions in leaf area (Caldeira and others 2014, 

Royer and others 2011). On mesic sites, increased light 

penetration could promote recruitment and sapling 

growth (Galiano and others 2013, McCarthy-Neumann 

and Ibáñez 2012). First-year seedling mortality can be 

high due to damping-off fungi, particularly in cool, wet, 

shaded understories (Hood and others 2004, Ichihara 

and Yamaji 2009); hence, drier conditions may reduce 

these losses on some sites. 

Drought-influenced processes that occur within 

individuals can affect organismal resource allocation, 

growth, maturation rates, fecundity, and survival, 

each of which can react to drought in different ways 

dependent on the responses of others (fig. 4.4). Taken 

together, the studies summarized in these sections 

clearly demonstrate individual tree vulnerability to 

drought, but they only hint at the complex biotic 

interactions that help determine where on a forested 

landscape drought will have the most profound impacts. 

While we have built on our current understanding of 

climate effects on individual trees (chapter 3), our 

intent is to anticipate consequences for forest structure 

and composition. After all, many factors contribute to 

the challenge of forecasting how increasing drought 

will affect forest structure and diversity. Changing 

temperature and precipitation are producing climate 

combinations that alter frequency, intensity, and 

seasonality of drought (Allen and others 2015, Dai 2012, 

Wehner and others 2011). As a result, novel forest 

assemblages will emerge as individual trees respond 

and populations shift their landscape positions and 

migrate geographically. For example, it is possible that 

moist sites will provide refuges if climate becomes 

more xeric and an alternative positive interaction could 

result from competition—the water-demanding species 

on wet sites fully utilize more abundant moisture supply 

and thus are especially vulnerable when moisture 

availability declines (Frelich and Reich 2010). This 

transition is a collective response of individuals in the 

context of the populations and communities found in 

their local environment.

Influence of Drought on Stands and Landscapes

Many of the open questions summarized in the 

previous sections arise from the challenge of 

translating improved understanding of demographic 

consequences for trees to predictions of change in 

forests. Because of the complex interactions between 

organisms, populations, communities, sites, and other 

environmental determinants, many of the observations 

on individual trees (fig. 4.3) only poorly translate to 

predictions of stand-level responses. The following 

sections emphasize drought impacts on the forest 

stand, long considered the fundamental scale both for 

management and community ecology (e.g., O’Hara and 

Nagel 2013). 

Interactions and the size-species distribution—

Some interactions occur between individuals, such 

as competition in crowded stands, and represent one 

of the most influential determinants of tree growth 

and survival. Drought may operate differently in 

stands of different density and age (Esper and others 

2008). Stands with open canopies or ones in which 

leaf area index decreases during drought (chapter 3) 

could experience increased understory irradiance and 

transpiration demand. Klos and others (2009) likewise 

found that the effects of drought on growth and survival 

might increase with stand age in the Southeastern 

United States. Due to the large sample interval in many 

climate-mortality studies, evidence is equivocal. The 

disparate results could also indicate the importance 

of unobserved variables that co-vary with density and 

stand age (D’Amato and others 2013). 
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Climate variation that promotes growth or survival 

of individual trees usually has similar effects on 

their neighboring competitors, depending on the 

size-species distribution (SSD) of the stand. The 

SSD is the distribution of trees across species and 

size classes. The SSD results from interactions of 

individuals, as each tree responds to local conditions 

and weather. Competition and climate affect the 

species and size classes that make up stands in 

different ways. There is feedback—the structure itself 

determines how the SSD will respond to drought 

through shading and transpiration. Biogeographic 

patterns in distribution and abundance emerge 

as individual responses translate to SSDs across 

heterogeneous landscapes. Management aims 

to modify SSDs (for example, via thinning and 

encouraging regeneration) to meet specific objectives, 

including controlling the SSD of stands to regulate 

bark beetle outbreaks (chapter 6). The fact that the 

SSD responds to climate change as a joint distribution 

of species and size classes has challenged our ability 

to anticipate the impact of drought.

MOISTURE AND SIZE-SPECIES DISTRIBUTIONS 

How can the effects of drought on forest structure and diversity be quantified? Conversely, what 

can structure and diversity tell us about past and potential future responses? Such questions require 

effective summaries of how temperature, precipitation, and day and season length together influence forest 

demography—changes in the size-species distribution (SSD) of stands. Annual temperature and precipitation 

partly explain biodiversity and productivity gradients at sub-continental scales. But their combined effects 

depend on stand structure and on seasonal timing, more like the hydrothermal surplus (HTS) and hydrothermal 

deficit (HTD) in the degree-hours during months with positive and negative water balance, respectively (fig. 

4.6). Unlike annual values, HTS and HTD describe the seasonal convergence of factors that affect competition 

between size-species classes. High temperatures and precipitation contribute to long, warm, wet growing 

seasons along the Gulf Coast. The resultant high HTS values extend up the moist Southern Appalachians, 

declining to the north and west, but different from either temperature or precipitation alone, in part due to 

summer deficits. The HTD is especially large in the Piedmont Plateau, Coastal Plain, and western Gulf Coast. 

The length of the growing season is short in the Northern United States, but during the growing season days 

are long. At this time, moisture is more available in the Northeast than the upper Midwest. 

The hydrothermal surplus and deficit (see figs. 4.6 and 4.7 on the next page) and PDSI (the basis for CDSI 

of the text box on page 60) are two examples of variables used to explain forest properties. Note agreement 

between CDSI (fig. 4.1) and HTD (fig. 4.6) in the South, but disagreement in the upper Midwest. One reason 

for this difference is the fact that CDI counts every month when PDSI is low, progressively amplifying their 

effects from month to month, whereas HTD considers the entire growing season as a unit.

Perhaps most important are changes in surpluses and deficits, shown as a different map in Figure 4.7. 

Despite the fact that deficits dominate in specific regions (the West and Southeast), forests throughout the 

East are exposed to increasing deficits (fig. 4.7).

The SSD is a stand-level variable, a distribution of species and sizes, related through history, climate, 

and competition (histograms in fig. 4.6). Knowledge of the SSD is required for understanding demography, 

biodiversity, competitive interactions, fuel structure, and response to moisture stress. SSDs are a focus of 

management practice. For a given stand there is a distribution of stems across species (vertical axes) and 

size classes (horizontal axes). Disturbance and succession affect the species composition of large and small 

size classes. Advance regeneration in small classes provides clues to future stand composition. SSDs vary 

geographically with climate, soils, and time. For example, species present in the largest size classes can have 

disproportionate access to light and moisture, thereby suppressing competitors. Crowding affects canopy 

architecture of individuals, thus influencing their vulnerabilities to drought (fig. 4.12). Thus, different SSDs are 

expected to respond to drought differently. For this reason, physiology and tree-ring studies of individuals do not 

directly translate to the forest stand. Thus far, models used to anticipate forest response to drought are based 

on estimates of how individuals respond to climate. We suggest new efforts to quantify the SSD response.

(continued next page)
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MOISTURE AND SIZE-SPECIES DISTRIBUTIONS 

Figure 4.6—Expressed on a relevant scale for trees, such as the number of degree hours at positive 

(hydrothermal surplus, HTS) and negative (hydrothermal deficit, HTD) water balance, large geographic contrasts 

contribute to size-species distributions (histograms). Surplus (above) and deficit (below) both reach maximum 

values near 3000 degree hours, but in different locations. With sufficient moisture, high temperature (up to a 

point) increases development. Long days and growing seasons combined with moisture (high HTS) benefit 

species capable of exploiting these conditions in competition with individuals of other species. Conversely, a 

large number of degree hours at negative water balance benefits species capable of tolerating drought. In the 

Southeast, surpluses and deficits are both common. The upper Midwest has much lower precipitation, but also 

lower temperatures and shorter growing seasons. The Northeast benefits from infrequent deficits, despite lower 

temperatures. Size-species distributions (SSD), shown for four different regions, reflect climate differences and 

stand history (Clark and others, In press).

1970 – 1985 Change since 1985

Figure. 4.7—Deficits commonly develop throughout the Eastern United States each growing season, particularly 

in the Midwest and Southeast. At left is the difference between surplus and deficit (black isohydrotherm is drawn 

at -1000 degree hours) from 1970 to 1985. The recent shift to larger deficits is nearly ubiquitous in the Eastern 

United States (black line is drawn at zero difference before and after 1985). (Clark and others, In press).

(continued from previous page)
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Understanding why individual responses do not readily 

extrapolate to the SSDs of stands is related to how the 

SSD mediates a climate response. For instance, when 

using an analysis of FIA data specifically targeting 

the 1999–2001 drought in the Southeast, Klos and 

others (2009) found a weak relationship between 

stand diversity and drought impacts, suggesting 

that the partitioning of resources occurring in many 

stands buffered at least some drought effects. For 

codominant trees in crowded stands (trees with 

crowns in the main canopy), growth and mortality 

rates are dominated by competition. Canopy individuals 

that might respond positively to a moist growing 

season are constrained by the fact that the competing 

neighbors largely benefit at the same times. At the 

stand level, mortality can increase as a result of 

favorable conditions, because thinning rates increase 

with growth rates, despite the fact that conditions 

have improved on average. 

Hence, the interdependence of individual responses 

that make up the stand response is harder to 

measure, replicate, and quantify than the response 

of an individual tree. For example, drought impacts 

depend on the species and size classes of individuals 

competing for moisture and light (see Moisture and 

Size-Species Distributions text box on pages 67 and 

68). Soil moisture depends on an interaction that 

involves climate, redistribution by local drainage, 

and uptake by competing trees (fig. 4.5) (Ackerly 

and others 2010, Loik and others 2004). Conversely, 

drought that depresses growth of individual trees 

can also decrease crowding effects, reducing the 

competitive pressure on growth and survival. In fact, 

the competition interaction with climate can reverse 

the apparent effect of climate, depending on whether 

the focus is the individual tree or the stand (Clark 

and others 2014b). In contrast to codominant trees 

that experience high competition for light, the tallest 

(dominant) trees with emergent crowns may respond 

more directly to climate. The rare individuals that make 

up the right-most extremes in the preceding text box 

are the focus of many tree-ring studies, but they would 

almost never appear in small [0.0672-ha (hectare)] FIA 

plots (note that trees are sampled on the larger 0.4-ha 

macroplots in Western States). Best represented in 

plot-based studies are the smallest size classes, which 

in crowded stands can be limited by both light and 

moisture. The large number of positive interactions 

between light and drought result from the fact that 

individuals not severely light-limited can respond most 

to climate variation (Clark and others 2014b). 

Interactions that occur within stands mean that 

stand-level responses to drought will not necessarily 

agree with studies of individual growth and survival. 

Responses of individual trees at low moisture availability 

do not tell us how the abundances of different species 

will change as a result of drought. Response of sizespecies structure depends on how these individual 

responses translate to population growth rates, each 

population being an aggregate across individuals 

of all size classes, competitive environments, and 

microhabitats (see Moisture and Size-Species 

Distributions text box on pages 67 and 68). If species 

that can tolerate xeric conditions progressively increase 

in abundance within stands that lose productivity and 

have lower transpiration demand, then the moisture for 

which trees compete becomes a competition feedback 

(D’Amato and others 2013). Development of better 

methods to combine the evidence from different scales 

is a goal of biodiversity research. The uncertainty that 

comes from climate-competition interaction effects on 

SSDs at the landscape scale must be met with studies 

that evaluate responses at both scales. 

For example, climate-competition interactions are 

evident in several studies at the individual-tree scale 

(Cescatti and Piutti 1998, Martin-Benito and others 

2011), at the stand scale (D’Amato and others 2013), 

and even across plot networks (Clark and others 2011, 

2014b). However, climate variables often emerge as 

weak predictors of large-scale mortality, at best (Dietze 

and Moorcroft 2011, Gustafson and Sturtevant 2013, 

Lines and others 2010), and any patterns may be hard 

to interpret. A tendency toward higher mortality rates 

in warmer climates is expected on the basis of higher 

productivity in warmer climates—partly explained by 

the fact that high growth is attended by rapid thinning 

(Assmann 1970, Clark 1990). Some of the largest 

studies involving FIA data provide relationships that are 

geographic, rather than change over time. For example, 

a synthesis of plot data on 48,000 trees spanning 

50 years over 4 Midwestern States did not find a 

link between precipitation and mortality, but rather 

highlighted the importance of competition (Yaussy and 

others 2013). While increased rainfall variability in recent 

decades (Li and others 2011, Melillo and others 2014) 

may influence geographic variation in mortality rates, 

the relationship between temperature and mortality 

does not necessarily constitute a threat of climate 

change—a study of geographic variation in mortality 

rate with average temperature did not necessarily find 

a vulnerability to temperature (Zhu and others 2014). 

Dieback events are also attributed to combinations 
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of physiological stress (Breshears and others 2009, 

Williams and others 2013), insect outbreaks (Gaylord 

and others 2013, Raffa and others 2008), and increased 

extent and severity of wildfire (Littell and others 2009, 

Westerling and others 2006, Williams and others 2013). 

Recruitment failure (Bell and others 2014, Brown and 

Wu 2005), growth decline (Chen and others 2010, 

Hogg and others 2008, Williams and others 2013), loss 

of canopy cover (Rehfeldt and others 2009, Worrall 

and others 2013), and extensive mortality (Allen and 

others 2010, Breshears and others 2005) have all played 

different roles in specific dieback episodes.

Even when drought does not directly kill trees, its 

effects on reduced vigor on competitive ability has 

implications for forest composition and structure. The 

critical roles of recruitment response to drought for 

future forests range from effects on migration potential 

to recolonization of diebacks. The relationship between 

diversity and resilience to drought may also vary among 

ecosystems (Grossiord and others 2014). Year-to-year 

volatility and high spatial variation that comes with 

the many feedbacks involving weather, competitors, 

fungal symbionts, and pathogens make it difficult to 

quantify. For example, ecologists have long suspected 

that pathogens mediate competition between trees of 

the same species when that species is at high density 

(Connell 1970, Janzen 1970), commonly termed 

density-dependence. Increases in natural enemies that 

occur where a host is abundant decrease the likelihood 

of any one species becoming dominant. If the host treepathogen relationships that promote diverse community 

structure are modulated by moisture availability, then 

drought effects could be unpredictable (Benítez and 

others 2013, Hersh and others 2012).

Evidence that temperate forest stands may see a longterm increase in oaks (Bachelet and others 2003, Clark 

and others 2014b) presents an apparent paradox, given 

that oak recruitment has declined in many regions 

(Abrams 2003, Fei and others 2011) (fig. 4.11). Advantages 

for oak trees under more xeric conditions are consistent 

with the population-scale tendency for oaks to expand in 

regions of low rainfall, but recruitment response remains 

questionable. In part, this may arise because seedling 

germination, establishment, and early survival are 

especially susceptible to environmental variation (Grubb 

1977, Harper 1977, Ibáñez and others 2007, Silvertown 

1987). The increased susceptibility of juvenile trees may 

be particularly acute in dry regions where interannual 

climatic variation is associated with episodic recruitment 

(Brown and Wu 2005, Jackson and others 2009). High 

mortality of seedlings relative to adults suggests a 

bottleneck on population growth rate, but direct evidence 

for its effects on fitness of many interacting species is 

lacking. For example, competition in the years following 

seedling establishment may sometimes blur the impacts 

of high interannual variability on recruitment. 

Increasing attention to interactive relationships among 

demographic processes is moving in the direction of 

more comprehensive synthesis, involving both individual 

growth (Bugmann 2001) and mortality (Allen and others 

2010, Breshears and others 2005, van Mantgem and 

Stephenson 2007, van Mantgem and others 2009). 

The fact that drought impacts depend on interactions 

highlights the need to study both individual- and 

stand-level responses. For instance, those interactions 

involving drought and the biotic environment contribute 

to recruitment variation following disturbance, canopy 

gaps, fires, landslides, ice storms, timber harvesting, 

and pest outbreaks (Brown and Wu 2005, Hubbell and 

others 1999, Pederson and others 2008, Savage and 

others 1996). Specific examples of the interactions 

that can occur between disturbance and moisture 

availability include the increased recruitment near the 

prairie-forest ecotone in Minnesota during the 1930s 

drought (Shuman and others 2009) and in the Great 

Basin following fire suppression, livestock introduction, 

and wet climatic conditions in the late 1800s (Miller and 

Rose 1999). Thus far, there is much more information 

available on responses of individual trees than of 

stands, and the important interactions that will control 

stand responses to drought remain poorly understood. 

Questions remain if we can anticipate which effects of 

anticipated drought-mediated change are likely to be 

most severe, in what ways, and on which parts of the 

landscape.

Drought-Mediated 

Biogeographic and Biome 

Shifts in U.S. Forests

This section extends stand-level effects to 

biogeographic responses at regional to subcontinental 

scales. Biogeographic change in forests can include 

migration (change in distribution) and changing 

abundances within current ranges. While much of the 

literature on climate change and species migration 

does not focus specifically on effects of drought, 

this literature is relevant to increasing drought, which 

depends on interactions between temperature and 

precipitation (chapter 3). Evidence that species 

distributions are responding to climate change has been 
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both a source of concern and a reassurance that species 

may have the capacity to migrate to new locations. The 

climate change-species migration studies suggesting 

that potential distributions of many species are shifting 

faster than are the populations themselves could apply 

not only to temperature but also to drought. 

Evidence Regarding Changes 

in Species Distributions

Forests respond to drought through both changes to 

the SSD and to immigration and local extinction (Chen 

and others 2011, Parmesan and Yohe 2003). Changes 

in species distributions occur when regeneration is 

successful beyond the current population frontier or 

when regeneration fails in a portion of the current range. 

In some cases, drought may relocate suitable habitats 

within the geographic range, such as shifts from areas of 

low to high moisture availability—for instance, at higher 

or lower elevations or adjacent to wetlands or bodies 

of water. Migration studies usually combine knowledge 

of species traits, paleo evidence for past spread, and 

modern landscape heterogeneity (Prasad and others 

2013). However, migration occurs at and beyond range 

limits, where local heterogeneity in recruitment success 

(Ibáñez and others 2007, Morin and others 2007, Pitelka 

and others 1997), low population density, the potential 

importance of rare dispersal and establishment events 

over broad regions, and a lack of good distributional data 

on most species make migration difficult to detect and 

to quantify (Clark and others 2003).

Further complicating matters is that the concept 

of migration is not applied consistently. For plants, 

“migration” most often refers to accumulated gains 

and losses in the area occupied by a species, typically 

at a regional scale. Poleward or upslope expansions 

in response to warming climate are examples of 

this usage. A different definition of migration refers 

to latitude- or elevation-weighted abundance or 

performance (Feeley and others 2011, 2013; Gottfried 

and others 2012). Such weighted averages can be 

calculated for samples where observations are individual 

organisms, abundances of species on plots, or a 

performance measure (Lenoir and others 2008, Woodall 

and others 2009). For example, growth rates of trees 

can be used to calculate performance-weighted mean 

latitude for the species. The mean latitude calculated 

by this approach can change from one survey to the 

next, regardless of whether or not the population 

moves—even if the range is static, the mean will 

change if individuals in different parts of the range grow 

faster/slower than before. Like weighted averages, 

parametric functions fitted to occurrence, abundance, 

or demographic rates (Canham and Thomas 2010, Clark 

and others 2014a, Mok and others 2012, Vanderwel and 

others 2013, Zhu and others 2014) can be dominated by 

samples where the species is abundant and insensitive 

to range margins. The smooth declines in performance 

near species distribution limits assumed in many 

models are not widely observed in demographic data 

(fig. 4.8). Hence, metrics that focus on population 

Diameter growth (cm)

Temperature (°C) Precipitation (mm)

10 15 20 1000 1500 2000

2.0

1.5

1.0

0.5

00

Figure 4.8—Models of distribution and abundance impose unrealistic relationships on Forest Inventory and Analysis data from the 

Eastern United States. The ubiquitous assumption that abundance and performance decline at range boundaries (e.g., a Gaussian 

model) contrasts with a spline smoothing (dashed red) of data (dots). Example shown here is red maple (Acer barbatum) (Clark and 

others, In press).
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centroids can provide valuable insight on geographic 

patterns and migration trends, but it is important not to 

interpret them as a change in distribution of the species.

Although latitudinal migration in response to warming 

could be occurring for some species, evidence of 

poleward movement of trees is even less obvious 

than upslope migration. Warming over the last century 

in the continental United States has been most rapid 

in the upper Midwest and Northeast, due to the 

combination of regional climate change and low relief 

(chapter 2). Poleward migration would be identified 

by establishment of new recruitment out ahead of 

established range boundaries, especially in these areas 

of rapid change. This pattern is not evident in FIA data 

(Zhu and others 2012). It is important to point out that 

there are only a few examples of rapid contemporary 

natural tree migrations (Fastie 1995, Pitelka and others 

1997). The paleo record may also provide examples 

of rapid spread in response to climate change, such 

as hazelnut (Corylus) expansion into western Europe 

in the early Holocene (Huntley and Birks 1983). 

However, many paleorecords are not well suited for 

determining rates of species migration or localized 

responses to short-term drought. For example, the 

sporadic occurrence of fossils in lake sediments can 

mean that a few trees are nearby or that many trees are 

far away, making it difficult to infer when a population 

arrives or disappears from a region. Interpretations of 

paleorecords to suggest rapid tree migrations, which 

were common in the past, are inconsistent with current 

understandings of species dispersal and life history 

observations (McLachlan and others 2005). Pollen 

records tend to lack fine-scale temporal resolution and 

can be ambiguous about the relationships between 

climate and vegetation patterns, especially when data 

are limited (e.g., Minckley and others 2008).

While some latitudinal migration may be underway, 

it is likely sporadic and difficult to detect—a pattern 

predicted by some models (Clark and others 2001). 

For example, FIA data failed to detect the southern 

magnolia (Magnolia grandiflora) expansion in the 

southeastern Piedmont (Gruhn and White 2011). The 

spread of this species is facilitated by horticultural 

practice, but populations are clearly capable of invading 

shaded understories of Piedmont forests. One of 

the few examples suggesting rapid spread from the 

Zhu and others (2012) analysis is American holly (Ilex 

opaca), which has ripe berries available for northward 

migrating birds in spring. Loss of paper birch (Betula 

papyrifera) and black spruce (Picea mariana) from 

the Blackrock Forest in New York could be explained 

not only by increasing temperatures, but also by 

successional trends in these aging forests (Schuster 

and others 2008). However, new arrivals at that site 

in this century include some that are near or beyond 

their commonly recognized range limits, including 

southern catalpa (Catalpa bignonioides), cockspur 

hawthorn (Crataegus crus-galli), red mulberry (Morus 

rubra), cottonwood (Populus deltoids), and slippery 

elm (Ulmus rubra). In each of these cases, researchers 

found that migrations are difficult to detect due to 

the fact that establishment is sporadic. Although 

researchers could argue that migrations are simply 

undetected, it appears clear that waves of rapid spread 

exceeding 103 meters per year that would be required to 

match the pace of shifting habitats are not occurring.

Opportunities for migration to track changing potential 

distributions are also found in landscapes with 

topographic relief and, thus, variable drainage and a 

range of suitable microclimates. The most effective 

migration could be expected in mountainous regions of 

compact climate gradients, where habitat shifts might 

not require long distances. For example, Beckage and 

others (2008) found that northern hardwood species 

invaded plots at a lower boundary of boreal forest in the 

Green Mountains of Vermont over the last half century. 

In this location, the ecotone is sharp, concentrated 

within 200 m of elevation. The mountainous terrain of 

the West can provide nearby upslope locations with 

lower temperature and higher precipitation (Jump and 

others 2009). Species in the Rocky Mountains that 

are not already at high elevations may lose much of 

their current habitat but could potentially find suitable 

habitats at different elevations (Bell and others 2014). 

Coops and Waring (2011) predict a large distributional 

shift and reduction in range extent for lodgepole pine 

(Pinus contorta) in the Pacific Northwest due to a 

projected increase in late summer drought. Using the 

same approach, Coops and others (2011) discuss why 

western redcedar (Thuja plicata) and western hemlock 

(Tsuga heterophylla) may expand their ranges, whereas 

ponderosa pine (Pinus ponderosa), lodgepole pine, grand 

fir (Abies grandis), and noble fir (Abies procera) ranges 

may contract. Still, even in such topography where 

dispersal is probably not limiting, tree upslope shifts 

appear to lag climate change in the Alps (Gehrig-Fasel 

and others 2007) and Andes (Feeley and others 2011).

Large-scale disturbance could accelerate migration, 

opening stands for invasion by propagules that would 

otherwise fail to invade competitive understories 
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(Dukes and others 2009, Weed and others 2013). 

Changes in land cover and diebacks resulting from 

combinations of climate, disease, and human action 

can all contribute to expanding or contracting ranges 

(Man 2013). Expansion of chaparral at the expense 

of forest is predicted for the San Francisco Bay Area 

(Cornwell and others 2012). Franklin and others (2013) 

predict changing distributions of 13 tree and 29 shrub 

species in California, with moisture being the most 

important cause. Declines in conifers and broadleaf 

deciduous trees and increases in grasses and shrubs 

are projected in parts of the West (Jiang and others 

2013). Because many drought-tolerant species are 

also tolerant of fire, new range limits can depend 

on changes in fire regime. Increased fire frequency, 

size, and/or intensity (all of which have increased in 

the Western United States over the past 30 years) 

(Miller and others 2009) in forest types that are firemaintained can rapidly shift composition, structure, 

and function of forests. Replacement of conifer forest 

by mixed evergreen forest and conversion of shrubland 

to grassland may be accelerated by fire (Lenihan and 

others (2008). Declines in the extents of valley oak 

(Querus lobata) and blue oak (Quercus douglasii) are 

possible in California (Kueppers and others 2005).

However, the extent to which large diebacks could 

promote migration remains uncertain (Kane and others 

2011, Linares and others 2009). In part, this is because 

future range shifts are difficult to anticipate due to 

limited evidence on the combinations of variables that 

control current range limits. For example, there is no 

clear indication that demographic rates, such as growth, 

survival, and reproduction (in other words, the patterns 

that would allow us to estimate factors that control 

distributions), decline near population frontiers (Abeli 

and others 2014, Tardiff and others 2006) (fig. 4.5). Yet 

the capacity for drought-induced dieback to accelerate 

change, including interactions involving fire and insects, 

suggests that change could occur at different rates, 

over centuries, and may be punctuated by episodic 

transitions. Tracking potential distributions could also 

depend on fire and other disturbances that accelerate 

migration. Therefore, the combination of large projected 

habitat shifts with limited evidence for the rapid 

migration that would be needed to track it suggests that 

biogeographic patterns could substantially lag climate 

change.

Our desire to anticipate the effects of increased 

drought on species diversity highlights the challenge of 

understanding an inherently stand-level consequence 

that can vary regionally. In an example from the 

Eastern United States, Clark and others (2014a) found 

that the strongest relationship between species 

diversity and climate resides in the upper Midwest for 

precipitation and in the upper Midwest and Northeast 

for temperature. In western forests, especially those 

in warm and dry climates at low elevations, increasing 

drought could result in loss of some species, and this 

loss could be accelerated by dieback (Bell and others 

2014, Kelly and Goulden 2008). The following sections 

take a more regional perspective on some of the likely 

biogeographic consequences of increasing drought in 

forests.

Drought-Related Changes in Eastern Forests 

The last century does not include droughts as severe 

as some of those in previous centuries in some parts 

of the East (Cook and others 2010, McEwan and 

others 2011, Pederson and others 2013, Stahle and 

Cleaveland 1992, Stahle and others 1988). Drought 

effects on tree growth and survival in eastern forests 

are important not only in upland habitats (Abrams 1990, 

Graumlich 1993, Pederson and others 2012) but also 

in bottomlands and coastal wetlands (Cook and others 

1999, Stahle and Cleaveland 1992). Drought effects also 

include coincidental events that could impact growth 

and mortality. For example, fires in the Eastern United 

States have increased in frequency and area burned 

during periods of low precipitation, high temperatures, 

or both (Clark 1989, Lafon and Quiring 2012, Lynch and 

Hessl 2010).

Regionally based growth-related drought responses 

of nonoak hardwood and conifer species are diverse. 

High temperatures appear to limit tree growth in many 

species, perhaps more in the South and Midwest 

(St. George and Ault 2014, Williams and others 2011) 

than in the North (Martin-Benito and Pederson 2015, 

St. George and Ault 2014, Williams and others 2011). 

Growing-season moisture deficits are common in the 

southeastern Piedmont and Southern Appalachians, 

and drought sensitivity of some pine species is high 

in this region (fig. 4.9) (Clark and others 2014a, Cook 

and others 2001, Henderson and Grissino-Mayer 2009, 

Schumacher and Day 1939), with possible exceptions 

at northern range margins and higher elevations (Bhuta 

and others 2009, Cook and others 1998, DeWeese and 

others 2010). Loblolly pine plantations along the coasts 

of Florida, Georgia, and the Carolinas may benefit from 

more consistent late-summer rainfall, a longer growing 

season, and a higher water table than is common in the 

more deficit-prone Piedmont (Jordan and others 2008). 
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The interactions involving competition and drought could 

contribute to habitat shifts in the Eastern United States. 

Klos and others (2009) suggested that dense stands may 

experience the most severe impacts of drought, which 

agrees with the positive interaction between drought and 

competition found in studies of single species in Europe 

(Cescatti and Piutti 1998, Martin-Benito and others 2011), 

at the stand level in the upper Midwest (fig. 4.12), and 

at the tree scale for many species in the Eastern United 

States (Clark and others 2011, 2014b). In the upper 

Midwest and Lake States, stand composition may shift as 

drought-tolerant pines and oaks potentially expand relative 

to drought-intolerant quaking aspen (Populus tremuloides), 

bigtooth aspen (Populus grandidentata), and paper birch 

(Betula papyrifera) (Handler and others 2014, Scheller and 

Mladenoff 2008). Boreal and lowland conifers, northern 

hardwoods, aspen-birch, and riparian communities may 

decline with increased drought predicted for this region 

(Handler and others 2014). Eastern oak-hickory forests 

could potentially expand as other species become less 

competitive (Handler and others 2014). 

Taken together, many species are vulnerable to drought 

in eastern forests. How this vulnerability at the individual 

scale translates to future forest composition and structure 

remains uncertain. Geographic variation with species 

occurrence is in many cases clearly linked to regional 

climate. However, few studies show direct connections 

between species distributions and geographic variation 

in mortality as opposed to, say, recruitment success. 

The effects of climate variation, such as drought, could 

differ for a species that is absent from a region because 

individuals cannot establish or established individuals 

cannot survive. The unclear role of mortality in species 

distributions (as opposed to recruitment) and how it is 

affected by drought complicates predictions of future 

forest responses to drought.

Drought-Related Changes in Western Forests

Unlike the Eastern United States, where large-scale 

drought effects are less well documented than 

the physiological responses of individual trees, the 

Western United States has experienced a number of 

catastrophic, widespread, stand-replacement events 

that are directly or indirectly related to drought (Allen 

and others 2010, Breshears and others 2005, Ganey 

and Vojta 2011, Gitlin and others 2006, Mueller 

and others 2005, van Mantgem and others 2009, 

Worrall and others 2013) (see Forest Droughts have 

Increased in Recent Decades text box on page 

60). Since 1996, about 20 percent of southwestern 

forest area has been affected by high levels of tree 

mortality from combinations of drought stress, barkbeetle attacks, and fire (Williams and others 2010). 

In Arizona and New Mexico, high temperatures 

combined with droughts coincide with widespread 

mortality of diverse mesic montane tree species 

(Ganey and Vojta 2011, Gitlin and others 2006, Mueller 

and others 2005) and patchy die-off in two-needle 

pinyon (Breshears and others 2005, 2009). Other 

prominent examples of large die-offs include spruce 

in Alaska (Berg and others 2006) and Utah (DeRose 

and Long 2012); juniper, oaks, and pines in Texas in 

2011 (Kukowski and others 2012, Twidwell and others 

2014); whitebark pine (Pinus albicaulis) in the Sierra 

Nevada Mountains (Millar and others 2012); southern 

California conifers (Minnich 2007); and millions of 

hectares of lodgepole pine from Colorado (Creeden 

and others 2014) and Montana (Kaiser and others 

2012) to British Columbia (Kurz and others 2008). 

An increase in drought-related quaking aspen 

mortality, sometimes termed sudden aspen decline, 

extends from Alberta to Colorado (Anderegg and 

others 2012, 2013a; Hogg and others 2008; Worrall 

and others 2013). 

Score

200

0

-200

Species marked by mean score

Growth/fecundity sensitivity to summer drought (PDSI)

Figure 4.9—The joint distribution of growth and fecundity provides a sensitivity estimate to drought 

for southeastern tree species. High prediction scores on the vertical axis indicate high sensitivity 

(relative rather than absolute scores are meaningful). Species without bars at right are off the scale and 

insensitive relative to those at left (Clark and others 2013).
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Juvenile growth Adult growth

NDVI Percent dead

1980 1990 2000 2010

FDSI

1980 1990 2000 2010

1980 1990 2000 2010

1980 1990 2000 2010

Area (km2

) Area (km2

)

6-year FDSI 2-year FDSI FDSI

0.45

0.4

0.35

2

1

0

-1

-2

25

20

15

10

5

-1

0

1

10000

1000

100

10

1

-1

0

1

-2

0

2

10000

1000

100

10

r = 0.83

Pinyon

Ponderosa pine

Douglas-fir

r = -0.84

r = -0.82

Bark-beetle area

Wildlife area

75

% 50

25

(A)

(B)

(C)

(D)

-1 0 1

Figure 4.10—Forest productivity and mortality and the Forest Drought Severity Index 

(FDSI) (see text). (A) Annual average late-June to early-August Normalized Difference 

Vegetation Index (NDVI). (B) Percent standing dead trees from FIA plot data for the three 

most common southwestern conifer species. (C) Aerial estimates of area having 10 trees 

per acre killed by bark-beetle attack. (D) Satellite-derived moderately and severely burned 

forest and woodland in the Southwest. Inset shows percent of years within a given FDSI 

class that were top 10 percent fire-scar years during AD 1650–1899 (the horizontal line is 

at the expected frequency of 10 percent, bins are 0.25 FDSI units wide). Note the inverted 

axes for FDSI in B–D. (Graphic from Williams and others 2013).
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The combination of low species diversity, low forest 

cover in some extensive forest types (for example, 

ponderosa pine and pinyon-juniper woodlands), low 

moisture availability on average, and frequent fire in the 

West shifts attention from the complexities of climatecompetition interactions to the more immediate threats 

of stand-level replacement at regional scales. These 

transformations involve many of the dominant species. 

In addition, large diebacks have the potential to change 

species distributions more rapidly than has occurred 

in the past (Fellows and Goulden 2012, Millar and 

others 2012, Swetnam and Betancourt 1998). Droughtinduced mortality in the 1950s is probably responsible 

for extensive upslope retreat of ponderosa pine in New 

Mexico (Allen and Breshears 1998) and alligator juniper 

(Juniperus deppeana) in southeast Arizona (Brusca 

and others 2013). Rapid redistribution of coniferous 

and broadleaf species occurred in southern California 

mountains during droughts of the early 2000s (Fellows 

and Goulden 2012). 

Experimental evidence suggests that high temperatures 

can sometime increase drought-induced mortality in 

pinyon (Adams and others 2009). In many cases, high 

temperatures are thought to have a relatively minor 

direct effect on tree growth in western forests (although 

high surface temperatures can be lethal for seedlings) 

(Chmura and others 2011, Kolb and Robberecht 

1996). Instead, warming is generally considered 

more important for phenology (Cayan and others 

2001), seasonal soil-water balance due to changes in 

snowpack dynamics or evapotranspiration (Williams 

and others 2013), and insect populations (Bentz and 

others 2010). Changes in actual evapotranspiration and 

water deficit appear to be primary drivers of historical 

variations in tree recruitment and background as well as 

episodic tree mortality (Rapacciuolo and others 2014). A 

combination of high temperatures and low winter-spring 

precipitation of the previous year can explain much of 

the variation in conifer growth rates in the Southwest 

[primarily two-needle pinyon (Pinus edulis), ponderosa 

pine, and Douglas-fir (Pseudotsuga menziesii)] (fig. 

4.10) and northern California [white fir (Abies concolor), 

red fir (Abies magnifica), sugar pine (Pinus lambertiana), 

ponderosa pine, and Douglas-fir] (Yeh and Wensel 

2000). Similar relationships between moisture, heat, 

and growth variation are observed for white spruce in 

interior Alaska (Barber and others 2000), for Douglasfir in the central and southwest Rocky Mountains and 

Mexico (Chen and others 2010), and for quaking aspen 

in western Canada (Hogg and others 2005). 

Contributions From Regional-Scale 

Models of Biogeographic Change

Models are an important part of the research on climate 

effects. They continue to improve, but all are subject to 

important limitations. First is the uncertainty in climate 

itself. Two recent versions of three General Circulation 

Models (GCMs) project 2100 climates that differ by up 

to 4 °C for mean annual temperature and 60 percent 

for precipitation over North America (McKenney and 

others 2011). Additional uncertainty comes from the 

heterogeneity not captured in GCM output, from 

redistribution of precipitation within local drainages (wet 

and dry sites occupy the same grid cell for regional 

climate prediction), and from variation in temperature 

with local topography and vegetation cover. Second, 

many, if not most, models of forest response to climate 

change rely on parameters fitted independently to 

recruitment, growth, and mortality, and primarily 

from observations on individual trees. This narrow 

derivation may not adequately capture larger scale biotic 

interactions critical to understanding and predicting 

drought-related biogeographic shifts. Third, regional 

models of climate effects on forests are of several 

types and thus subject to critical limitations of scale, 

applicability, and compatibility. Some models represent 

individual trees, while others aggregate to species, life 

form, functional type, life stage, or patch structure. 

Some are static calibration-prediction models (species 

distribution models), while others are dynamic and vary 

in resolution from small plots (Shuman and others 2011) 

to patchy landscapes (Medvigy and Moorcroft 2012) and 

lattice grids (Franklin and others 2013), and yet others 

focus on abundance in nonspatial settings (Guisan and 

Thuiller 2005, Scheller and Mladenoff 2007). 

Even with these limitations, models have significantly 

contributed to our understanding of the large-scale 

impacts of increasing drought on U.S. forests. Species 

distribution models (SDMs) have been used to map 

potential future species habitats under predicted 

climate scenarios (Franklin 2010, Guisan and Thuiller 

2005, Matthews and others 2011, Prasad and others 

2013, Rehfeldt and others 2006). To accomplish this, 

species distributions are first calibrated to climate, 

and then the fitted models are combined with climate 

predictions to identify regions of future suitable climate. 

Whether or not populations can move to regions of 

future suitable climate depends on migration. Potential 

distributions predicted from SDMs can be bracketed 

by two extremes: (1) no migration (species lose but do 

not gain habitat) and (2) unlimited migration (species 
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Longitude Longitude

Longitude Longitude

Latitude LatitudeLatitude Latitude

Figure 4.11—New recruits to FIA plots are relatively rare for oaks (upper panels) in comparison 

to other species having similar abundances in adult size classes (below). This comes at a time 

when moisture deficits are becoming more severe throughout the East (fig. 4.7) and despite the 

fact that many models predict increasing oaks. Red circles are in proportion to density of new 

recruits per ha. Gray shading shows the same for large size classes. Quantiles are shown for 98 

percent of observations at sites where adults occur (Clark and others, In press).
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

occupy all suitable habitat) (Iverson and others 2008c, 

Meier and others 2012, Thuiller and others 2005). Some 

SDMs incorporate simple population dynamics (Cabral 

and Schurr 2010, Dullinger and others 2012, Iverson and 

others 2004, Meier and others 2012, Pagel and Schurr 

2012, Prasad and others 2013, Saltre and others 2013). 

SDMs that assume climate effects on establishment 

and mortality (Crookston and others 2010, Sork and 

others 2010) have been used to interpret potential 

risks for eastern (Iverson and others 2008b, Potter and 

others 2010) and western forest species (Dobrowski 

and others 2011, Notaro and others 2012, Rehfeldt and 

others 2009). Current efforts seek to include a better 

understanding of species interactions (Fitzpatrick and 

Hargrove 2009, Ibáñez and others 2006, Wiens and 

others 2009) and ways to incorporate multiple species 

into models (Baselga and Araújo 2010, Clark and others 

2014b, Guisan and Rahbek 2011).

SDMs have provided some of the strongest evidence 

that potential distributions of tree species are changing 

(McKenney and others 2007, 2011). In the Eastern 

United States, with its typically low relief, modest 

changes in climate can translate to large geographic 

shifts in suitable habitat (IPCC 2014, Loarie and others 

2009, Zhu and others 2012), in agreement with models 

suggesting large reductions in potential range in the 

East (Potter and others 2010, Potter and Hargrove 

2013). By 2100, mean latitudes are predicted to move 

northeastward from 400 km (kilometers) for a less 

CO2-sensitive model (PCM) with high energy-resource 

efficiency (B1) to 800 km for a more sensitive model 

(HadleyCM3) with a “business as usual” scenario 

(A1F1) (Iverson and others 2008b). For the latter case, 

habitats for 66 species gain and 54 species lose about 

10 percent of their current distributions. Species in Lake 

States and central hardwoods are predicted to be most 

vulnerable in the northern parts of their ranges (Brandt 

and others 2014, Handler and others 2014, Swanston 

and others 2011). Other drought-related predictions 

for the end of the 21st century include savanna-like 

conditions and loss of boreal forests from the Great 

Lakes region (Bachelet and others 2008). 

Two other types of models have also contributed 

significantly to our understanding of drought impacts. 

In the nonspatial Dynamic Global Vegetation Models 

(DGVMs) (e.g., Daly and others 2000, Jiang and others 

2013, Sitch and others 2003), species are aggregated as 

functional types, such as coniferous forests, deciduous 

forests, mixed forests, savannas and woodlands, or 

grasslands and shrublands (Bachelet and others 2003). 

Some DGVMs also incorporate fire, atmospheric CO2

(King and others 2013, Lenihan and others 2008), 

establishment mechanisms (Song and Zeng 2014), and 

patch age structure (Medvigy and Moorcroft 2012). 

Forest landscape models (FLMs) simulate forest 

demography on landscapes that may include drought, 

fire, land use, and pathogens. FLMs have been used 

to examine the stand-level consequences of species 

differences in vulnerability of individuals, with some 

FLM-based studies explicitly focusing on climate change 

impacts (Loehman and others 2011, Scheller and 

Mladenoff 2008), including migration (Gustafson and 

Sturtevant 2013, Lischke and others 2006, Nabel and 

others 2013, Scheller and Mladenoff 2008, Snell 2014).

Implications for Forest 

Management Practices

Timber harvest and land use are at least as influential 

in shaping forests as natural disturbances, particularly 

in the Southeastern and Northwestern United 

States (Masek and others 2011). As stated earlier, 

management practices modify the SSD and related 

forest elements (see Moisture and Size-Species 

Distributions text box on pages 67 and 68), which in 

turn influence a broad range of ecosystem services. 

Drought, especially prolonged and/or severe drought, 

similarly directly and indirectly impacts most of the 

ecosystem services provided by forests, including 

timber yield (Woodall and others 2013b), carbon 

storage (chapter 5), recreational value (Sheppard and 

Picard 2006), wildlife habitat (Banko and others 2013), 

and water yield and quality (Brown and others 2008) 

(chapter 10). Forestry practices that target one or more 

of these ecosystem services should be capable of 

addressing droughts, particularly in areas expected to 

receive more frequent and longer term drought events. 

To this end, we consider changes that may occur 

within stands as a function of drought as influenced by 

management practices and their potential biogeographic 

consequences.

Stand Density and Structural Management

Management actions can mitigate or exacerbate 

effects of drought, and effects can differ at both the 

tree and stand level. Most thinning treatments are 

designed to increase individual tree growth; increase 

stand resiliency to droughts, insects, and disease; 

and reduce standing fuels. For example, in dense red 

pine (Pinus resinosa) stands undergoing substantial 

self-thinning (fig. 4.12), some trees are under severe 

moisture limitation due to the combined effects of 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

competition and drought (D’Amato and others 2013). 

Thinning overstocked stands can provide short-term 

benefits through a variety of mechanisms. Harvesting 

stands to limit crown competition (Gyenge and others 

2011, McDowell and others 2006) also reduces canopy 

interception of precipitation, thus increasing moisture 

that reaches the forest floor (Aussenac 2000, Stogsdili 

and others 1992). Likewise, trees in thinned stands 

usually expand their root systems to take advantage of 

improved soil moisture availability (Dawson 1996). Slow 

growth in older, denser (and often water-limited) stands 

has long been associated with beetle outbreaks (Fettig 

and others 2007, Hicks and others 1979); slow-growing, 

stressed host trees have diminished defenses to insect 

pests (Fettig and others 2007, Shaw and others 2005).

However, silvicultural practices intended to reduce 

vulnerability of remaining trees to drought can increase 

future (long-term) vulnerability through alterations 

to tree architecture and physiology. For instance, 

increased leaf-to-sapwood area ratios following 

thinning can increase individual tree water demand 

(Kolb and others 2007, McDowell and others 2006). 

Therefore, even if stand-level water use declines 

following thinning, the high leaf-to-sapwood ratio 

promoted by reduced post-treatment competition may 

be disadvantageous during future drought. For this 

same reason, even though thinning beetle-affected 

stands usually increases residual tree growth (Fettig 

and others 2007, Kolb and others 1996, Skov and 

others 2004, Thomas and Waring 2014, Zausen and 

others 2005) and vigor over the short-term, it may 

also increase vulnerability to post-thinning droughts. 

Thinning also indirectly increases stand vulnerability 

to drought. Stands thinned and/or burned to promote 

regeneration (Covington and others 1997, Moore and 

others 1999) may increase vulnerability to drought due 

to increased evaporative losses (Aussenac 2000) and 

increased understory competition for soil moisture 

(Nilsen and others 2001, Zahner 1958). 

Basal area (m2/ha)

Trees/ha

Figure 4.12—Hypothetical zones of drought susceptibility within a size/density management 

diagram for red pine. Trees may be susceptible to drought in two size/density situations: (1) at 

high density of large trees, with intense competition, and (2) at low density and high leaf-area 

to sapwood-area ratios, which promote canopy and root architecture that can put individual 

trees at risk.
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Managers may want to adjust their silvicultural 

practices in stands expected to face increasing drought 

frequencies and durations. For example, thinning to 

manage for SSDs targeted to control those structural 

attributes sensitive to drought can improve stand 

resistance and resilience (Guldin 2014). Managers often 

take steps to maximize belowground development prior 

to and immediately after planting (Burdett 1990), or to 

shelter future crop trees during this vulnerable phase 

(Aussenac 2000). Recently planted seedlings with 

limited root development are particularly vulnerable 

to desiccation. Though more expensive, the betterdeveloped and protected root systems of containerized 

nursery stock tend to survive and grow better than 

bare-root seedlings on xeric sites (Grossnickle 2005, 

Nilsson and Örlander 1995), and hence may be needed 

when drought is expected during planting. If bare-root 

seedlings are to be used, those with large root systems 

(shoot-to-root ratios below 2:1) are preferred (Haase and 

Rose 1993, Pinto and others 2012). Tree shelters can 

also enhance seedling survival on moisture-limited sites 

(Taylor and others 2009). 

Maintenance of two- or uneven-aged stands may 

reduce stand-wide vulnerability to drought by spreading 

the risk across ages/sizes of different vulnerabilities. 

Uneven-aged management can reduce the microclimate 

extremes that limit regeneration following clearcuts 

(Aussenac 2000). Where management objectives 

require even-aged stands, shelterwoods can provide 

partial shading for regeneration (Castro and others 

2004). However, there are drought-related complications 

associated with managing for multi-storied stands. 

Competition for moisture may be important enough to 

warrant understory control only during drought years 

(Carter and others 1984). In eastern forests, even-aged 

pine stands with a hardwood understory can experience 

greater soil moisture depletion than stands where the 

understory is reduced through prescribed burns or by 

other means (Zahner 1968). 

Species Composition Management

Species composition is another silviculturally controllable 

aspect of U.S. forests. Some have called for the longterm strategy of managing for a diversity of genotypes 

and species to reduce stand-level vulnerability to 

drought, particularly in light of the uncertainty in future 

climate (Guldin 2014, Ledig and Kitzmiller 1992). There 

are also short-term options, such as the alteration of 

species composition through the selective removal 

of moisture-demanding species. The loss of less 

drought-tolerant species can release established 

but suppressed individuals of more drought-tolerant 

species, as is currently being witnessed in the droughtinduced dieback of the pinyon-juniper ecosystem of 

the Western United States (Floyd and others 2009). 

Managers can also encourage the natural regeneration 

of more drought-tolerant trees by exploiting their 

propensity to resprout, a characteristic of some species 

with extensive root systems [for example, post oak 

(Quercus stellata), Gambel oak (Quercus gambelii), 

or alligator juniper] (Larsen and Johnson 1998, Savage 

and others 2013). Indeed, such targeted treatments to 

favor sprouters can be most effective during droughts, 

as their extensive established root systems give them 

an advantage to those species that can only establish 

via seed. However, note that not all sprouters can 

take advantage of droughts. Quaking aspen, a prolific 

sprouter under favorable moisture conditions, is 

susceptible to drought and declines can be magnified 

by other factors such as ungulate browsing (Bartos and 

others 2014, Rogers and Mittanck 2014, Rogers and 

others 2014). 

It is worth noting that species management through 

regeneration may prove more costly as droughts 

become more frequent (Nyland 2007). Despite some 

advantages of natural regeneration (including lower 

costs), drought may increase reliance on artificial 

regeneration (in other words, plantings) and/or seedbed amelioration (e.g., seedling shelters). Artificial 

regeneration may become especially important for 

conifers that fail to regenerate or are out-competed 

by sprouting species (Feddema and others 2013, 

Haire and McGarigal 2008, Zhang and others 2008). 

Knowledge of how different species and genotypes 

respond on different sites (Blazier and others 2004, 

Erickson and others 2012, Will and others 2010) should 

guide decisions regarding how to manage forests 

for drought resistance. Regardless of stand origin, 

successful regeneration during drought depends on 

microsite conditions, including competition from less 

desirable species, so more intervention may be needed 

to help ensure the desired silvicultural outcomes. 

For example, competition control may become vital 

during prolonged droughts, particularly on sites with 

pronounced moisture limitations due to xeric conditions 

(Pinto and others 2012, Powers and Reynolds 1999, 

Wagner and Robinson 2006) or aggressive competitors. 

Additional steps, such as exposing mineral soil (Wagner 

and Colombo 2001) or mulching to increase moisture 

availability using harvest residues (Roberts and others 

2005, Trottier-Picard and others 2014), may become 

increasingly important on some sites. These treatments 
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can add to the expense of silvicultural practices and 

could negatively impact other ecosystem services.

Fire and Fuels Management

In the Western United States, fire and harvest practices 

have contributed to increased fuel loads and a shift to 

high-density/small-diameter stands (e.g., Brown and 

Wu 2005, Covington and Moore 1994, Dolanc and 

others 2013, Fulé and others 2009, Lutz and others 

2009, Mast and Wolf 2006, Parsons and DeBenedetti 

1979). Prescribed fire can be used to manage complex 

stand structures following initial mechanical restoration 

treatments (Covington and others 2007, Roccaforte 

and others 2010), although extended droughts have 

reduced opportunities to conduct prescribed burns. 

Tree regeneration in western pine forests is resilient to 

surface fire in sustainable uneven-aged stands (Bailey 

and Covington 2002) except where regeneration is 

sufficiently dense to increase crown fire risk (Bailey and 

Covington 2002, Roccaforte and others 2010). 

There are regional differences in the role of interactions 

between drought, fire, climate change, and human 

suppression of fire (Allen 2007, Joyce and others 2014, 

Littell and others 2009, Westerling and others 2006). In 

the Eastern United States, fire suppression may have 

led to “mesophication” as forest canopies closed, fuel 

conditions changed, and sites became increasingly 

more mesic (Nowacki and Abrams 2008). In recent 

decades, this combination of climate, land use, plantanimal interactions, and fire suppression may have 

contributed to recent increases in red maple (Acer 

rubrum) and sugar maple (Acer saccharum) recruitment 

at the expense of oak (Abrams 1998, Brose and others 

2013, Fei and others 2011, Hutchinson and others 

2008, Iverson and others 2008a). Similarly, decreased 

flammability may have followed the replacement of 

American chestnut (Castanea dentata) by maples in 

many eastern stands (Engber and Varner 2012, Kreye 

and others 2013), although historic alterations to fire 

regimes and fuel loads make it difficult to characterize 

presettlement fire regimes (Clark and Royall 1996, 

Guyette and others 2006, Parshall and Foster 2003). 

Some have speculated that elevated maple recruitment 

in the East could be reversed by increasingly dry 

conditions (Belden and Pallardy 2009, McEwan and 

others 2011, Woodall and others 2009); however, if fire 

suppression is primarily responsible for reduced oak 

regeneration in the East, then climatic trends favoring 

oak, including warmer temperatures and less rainfall, 

could be offset by mesophication. 

Assisted Migration

SDMs suggest that shifts in potential distributions 

may occur faster than many tree populations can 

accommodate through migration. While there is 

substantial evidence that more mobile terrestrial and 

aquatic invertebrates, birds, and herbaceous plants are 

changing their distributions sufficiently to keep pace 

with rapid warming (Chen and others 2011, Parmesan 

and Yohe 2003), many tree populations are moving 

northward (Zhu and others 2012) and upward (GehrigFasel and others 2007) much slower than changes 

in climate. Fearful of local extinctions, some have 

proposed that managers engage in “assisted migration” 

or “managed relocation” to establish species outside 

their historic distributions as a biological diversity 

conservation measure (Schwartz and others 2012). 

Assisted migration is a deliberate effort to establish 

populations in areas that are expected to have a 

suitable climate in the future, including populations 

sensitive to drought, to at least partially offset losses 

on sites no longer suitable. However, the effectiveness 

of widespread assisted migration is not yet known 

(Williams and Dumroese 2013), and some have 

expressed concerns about the risk of introducing 

invasive species (Mueller and Hellman 2008).

Centuries of horticultural and decades of silvicultural 

practices show that growth and establishment 

(reproductive success) of many tree species is possible 

well outside of their native ranges. Many commercial 

(e.g., loblolly pine) and ornamental species have had 

their ranges greatly expanded across the Southeastern 

United States. The widespread plantings of the 

southern magnolia in the southeastern Piedmont (Gruhn 

and White 2011) and upper Coastal Plain, and bois 

d’arc (Maclura pomifera) across the Eastern United 

States (Burton 1990) are examples of such facilitated 

migrations, helping to establish these species well 

beyond their native ranges. While these cultivated 

successes could be viewed as examples of the 

potential conservation value of assisted migration, far 

less is known about the likelihood of success of this 

management practice for the species most directly 

threatened by climate-induced environmental change. 

Efforts are currently underway to see if assisted 

migration can help with the federally endangered Florida 

torreya (Torreya taxifolia) as well as a number of other 

tree species imperiled by the anticipated impacts of 

increased drought and higher temperatures on their 

limited native distributions (McLachlan and others 2007, 

Williams and Dumroese 2013).
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Research to Better 

Anticipate Drought 

Effects on U.S. Forests

Anticipated impacts of increasing drought, possibly 

leading to more xeric conditions in general, currently 

depend on a legacy of observational evidence along 

natural climate and hydrologic gradients. The value 

of such relationships is widely recognized and they 

provide the foundations for species distribution 

modeling and paleoclimate reconstructions (e.g., 

tree-ring studies). Despite many important insights 

from observational evidence, their lack of experimental 

control and uncertainties in future climate change 

poses new challenges and suggests some possible 

research directions.

Perhaps the greatest obstacle to understanding 

impacts of future drought on U.S. forests is the limited 

understanding of drought consequences at stand-tolandscape scales. We need more research to better 

understand the connections from individual tree to 

stand, based on both empirical (observational) and 

theoretical (modeling) evidence. For example, how does 

decline in individual tree health translate to population 

structure and abundance of a species, when individuals 

of all species are responding to climate, often in similar 

ways (Clark and others 2011)? The climate changes 

that place individuals at risk can have unpredictable 

effects on the stand, so empirical evidence is needed 

to evaluate both the individual responses and how they 

propagate to stand dynamics. At the individual scale, 

long-term data with regional coverage are needed to 

infer demographic processes under a range of climates 

and to detect early signs of change (Breshears and 

others 2009). While there exists a wealth of information 

on seed dispersal of common tree species in North 

America (e.g., Brown and others 1988, Chambers and 

MacMahon 1994, Farmer 1997, Matlack 1987) and 

Europe (e.g., Jensen 1985, Matlack 1987, Stöcklin 

and Bäumler 1996), many species are poorly studied, 

especially those with limited commercial value. The 

studies that are available on more abundant species 

show large variation in fecundity (Clark and others 2004, 

Koenig and Knops 2013) and recruitment (Ibáñez and 

others 2007)—what can be expected from rare taxa? 

Furthermore, even detailed knowledge of dispersal is 

not necessarily predictive of migration rates because of 

the influence of rare, long-distance dispersal events on 

population spread (Clark and others 2003, Higgins and 

Richardson 1999, Kot and others 1996, Schwartz 1993). 

However, predicting changes in stands also requires 

stand-level inference. The observable physiological 

responses to temperature and moisture stress must 

be linked to demographic potential of individuals and 

to stand attributes, such as SSDs and abundance. 

Additional insight might be gained from more research 

on natural gradients in regions expected to differ in 

sensitivity to moisture and temperature, particularly that 

emphasizing the connections from individuals to stands 

and landscapes.

Interpretation of Holocene tree migration will remain 

the subject of considerable research—insights gained 

from this work may allow researchers to determine 

how paleo droughts may have influenced forest 

patterns. Understanding biogeographic patterns would 

likewise benefit from a better understanding of how 

current biogeography emerges from the responses of 

individual trees to climate (Murphy and others 2006, 

Rehfeldt and others 2006). Habitat interactions make 

it important to consider entire landscapes (e.g., Guisan 

and Zimmermann 2000), and recognizing past and 

present range limits is key to determine migration 

potential (Gaston 2009). For example, the range limits 

mapped for many North American vascular plants by 

Little (1971, 1976, 1977) can be updated with FIA data 

(and combined, perhaps, with habitat and/or climate 

envelope models) to better identify current distributions, 

recent trends, and limitations in knowledge (Murphy 

and others 2006, Peters and others 2013, Purves 2009, 

Rehfeldt and others 2006, Woodall and others 2013a). 

Understanding whether or not species can expand or 

retreat from population frontiers requires experimental 

evidence, with sufficient replication and control to 

evaluate competition-climate interactions. Currently, 

only a few experimental studies have addressed 

controls on recruitment near population frontiers (Ibáñez 

and McCarthy-Neumann 2014, McCarthy-Neumann 

and Ibáñez 2012); this work suggests the value of more 

extensive networks of such experiments. 

In addition to a better understanding of tree range 

dynamics, more research on genetic variation of planting 

stock and the facilitation of regeneration in the context 

of drought is critical. As suggested earlier, some 

managers are moving ahead with assisted migration 

even though success is far from assured, and science 

has not comprehensively studied the ecological and 

socioeconomic implications of this practice. For example, 

the scarcity of information on tree regeneration in rare 

species constrains our ability to determine if assisted 

migration will prove to be a cost-effective option for 

biological conservation (Williams and Dumroese 2013). 
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Undoubtedly, we will benefit from developing a better 

understanding of the factors that control establishment 

of seeds that are moved to new locations (Bugmann 

2001, Lischke and others 2006). Further research is also 

needed on the effectiveness of conventional silvicultural 

treatments in established stands to determine both 

the short- and long-term consequences of increasing 

droughts, particularly if they become more severe 

(drier and longer) than recent history suggests. To date, 

very little proactive silviculture has been implemented 

across the United States with regards to the worsening 

droughts and higher temperatures anticipated under 

most climate change scenarios—the socioeconomic 

implications of drought-related catastrophic failures in 

the heretofore more-mesic “woodbaskets” of the United 

States have not been fully considered.

These challenges (and many others) highlight the 

need for models that accommodate environmental 

change and forest response as a coherent joint 

distribution of species and sizes which respond to 

drought with feedbacks and interactions. The decadeold “scaling problem” (Levin 1992, Luo and others 

2011) persists despite proliferation of bigger models, 

faster processing, and increased computer memory. 

Complex models can provide only limited guidance 

without the empirical basis for translating fine-scale 

to aggregate behavior, in the form of allocation 

constraints, species interactions, and feedbacks. 

These constraints are needed in models when they are 

fitted to field and experimental data. Not surprisingly, 

models combining these estimates predict migration 

rates that are highly uncertain due to large variability 

in these processes (Clark and others 2003), and 

land cover provides additional variability (Iverson 

and others 2004, Prasad and others 2013). Limited 

evidence of migration during the 21st century, a time 

when scientists have verified that climate change has 

been substantial in the Northern United States (Zhu 

and others 2012), diverges from predictions of rapid 

spread—and we need to understand why. 

Dynamic stand models have become increasingly 

sophisticated, but they still lack a connection to standlevel data under different climate settings. Stand 

simulators, including forest gap (Botkin and others 

1972, Bugmann 2001, Dixon 2002, Pacala and others 

1996) and succession models (Mladenoff and others 

1996, Scheller and Mladenoff 2008), recognize the 

importance of interactions among individuals. Efforts to 

connect physiology to stand dynamics in more general 

ways have increased in recent years (Keenan and others 

2008, Ogle and Pacala 2009, Scherstjanoi and others 

2014) but are still insufficient in many regards. For 

example, numerous models have examined the effects 

of disturbance (Caldwell and others 2013, Menard 

and others 2002, Papaik and Canham 2006, Reinhardt 

and Holsinger 2010, Saunders and Arseneault 2013, 

Uriarte and others 2009) and several have included 

drought (Gustafson and Shinneman 2015, Gustafson 

and Sturtevant 2013). However, unlike some types of 

disturbance that can be treated as an extrinsic force, 

drought involves a feedback with water use by the 

stand and thus is more difficult to model (Miller and 

others 2008, Morales and others 2005).

Indeed, all calibration-prediction and simulation 

approaches are challenged by the fact that parameters 

relating drought to recruitment, growth, and survival 

typically come from separate studies of individual 

trees across a range of spatial and temporal scales. 

Concerns include the need for better estimates of 

climate-mediated mortality (McDowell and others 

2011) and recruitment (Ibáñez and others 2006). The 

interactions that affect the combined responses of 

individuals (fig. 4.4) and size-species structure of stands 

(see Moisture and Size-Species Distributions text box 

on pages 67 and 68) could benefit from estimates of 

the SSD as a joint distribution. Furthermore, to better 

model migration, we must enhance our understanding 

of how drought affects seed production, seed banks, 

and seedling establishment near range limits, and 

in particular, their role in local extinctions and recolonization (Jackson and others 2009, Zimmermann 

and others 2009). 

Conclusions

The widespread nature of recent droughts and their 

impacts on U.S. forests suggest transformations that 

will have far-reaching consequences. In addition to 

the declining growth rates with increasing drought 

conditions that may be expected during the 21st 

century, the extent and severity of drought impacts 

on western forests raises concern for biodiversity and 

carbon storage if these trends continue. Some of this 

change will occur following alterations to disturbance 

regimes. For instance, recent drought-related increases 

of high-severity fire in stands that historically were 

subject to high-frequency but low-severity fires may 

contribute to the loss of forests (Barton 2002, Goforth 

and Minnich 2008, Savage and Mast 2005, Savage 

and others 2013). A similar forest loss has also been 

suggested as a possible consequence of climate 
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change in the historically infrequent but high-severity 

fires for lodgepole pine forests in the Yellowstone 

region (Westerling and others 2011). In addition to direct 

losses to drought, increasing frequency or severity of 

related disturbances may increase prevalence of early 

successional species (e.g., bark-beetle infestations or 

wildfire), possibly leading to widespread forest-type 

conversions (Pelz and Smith 2013, Shinneman and 

others 2013). 

Observational studies remain the largest source of 

information on drought effects, but they are difficult to 

extrapolate. Experimental studies are still few, small, 

and relatively short term. Taken together, the evidence 

for drought effects on forest structure and composition 

remains mostly indirect. Because individual trees can 

be studied experimentally more readily than forest 

stands, there is more evidence of drought effects 

on trees than on stand-level attributes, such as SSD. 

Indeed, in the Eastern United States, drought effects 

are still primarily observed as individual tree responses. 

At this scale, much is known about the differences 

among species that make some especially vulnerable 

to increased drought and other taxa less so. However, it 

is not clear how these species differences translate to 

future stand structure and composition. This is because 

observations are limited of stand-level responses that 

evaluate how changes in climate relate to changing 

effects of competitors, mutualists, and natural enemies, 

which are also responding to climate change. In the 

West, stand-level forest transformations are currently in 

progress, thus highlighting interactions among warming 

temperatures, drought, insect attacks, and fire. Recent 

western droughts show some of the drastic impacts 

that can occur when drought overwhelms other factors 

that contribute to the structure and diversity of more 

mesic forests. 

There is broad consensus from modeling studies, 

increasingly supported by observations, that 

combinations of heat and moisture limitation, and 

their corresponding indirect effects, will change 

the health, dynamics, abundance, and distribution 

of tree species—changes that may accelerate in 

coming decades. This provides a sense of urgency for 

many forest managers who would like to proactively 

treat their forests. After all, management decisions 

regarding the size, age, and compositional conditions 

of any given stand have important implications for the 

degree of functional resistance and resilience to future 

drought (e.g., Guldin 2014). Although drought-based 

advice is context-dependent, in general management 

strategies expecting increasing drought should benefit 

from developing more resilient forests by promoting 

tree (genotypic) diversity (especially drought-tolerant 

species or families) in lower density stands. Assisted 

migration, or drawing on species or genotypes outside 

their current geographic ranges, remains an option 

but needs to be better understood before it is widely 

implemented.

Research should be prioritized to include more 

attention on effects of drought beyond the individual; 

for example, it should focus on the combined 

size-species interactions that control diversity and 

productivity of stands. It remains difficult to quantify 

controls on range limits of species. Opportunistic or 

designed experiments are needed to better understand 

geographic variation in the effects of drought. Models 

will continue to play an important role, one that 

depends on improved understanding of stand-level 

responses and the acquisition of suitable, long-term 

data for detection, parameterization, calibration, and 

validation.

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CHAPTER 5

W.H. Schlesinger is a Biogeochemist and President Emeritus, Cary Institute of 

Ecosystem Studies, Millbrook, NY 12545.

M.C. Dietze is an Assistant Professor, Department of Earth and Environment, Boston 

University, Boston, MA 02215.

R.B. Jackson is a Professor and Senior Fellow, School of Earth, Energy and Environmental 

Science, Stanford University, Stanford, CA 94305.

R.P. Phillips is an Associate Professor, Department of Biology, Indiana University, 

Bloomington, IN 47405.

C.C. Rhoades is a Research Biogeochemist, U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station (RMRS), Fort Collins, CO 80526.

L.E. Rustad is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Northern Research Station (NRS), Durham, NH 03824.

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Synthesis (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources,

Raleigh, NC 27695.

Forest Biogeochemistry 

in Response to Drought

William H. Schlesinger

Michael C. Dietze

Robert B. Jackson

Richard P. Phillips

Charles C. Rhoades

Lindsey E. Rustad

James M. Vose
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

Historical records of drought extend to Biblical times 

when lack of rainfall reduced crop yields, leading to 

famine and mass human migrations. Studies of tree 

rings also show periods of reduced forest growth that 

can be linked to historical records of low rainfall. In 

these examples, drought is taken to result from low 

rainfall, but in some cases, this linkage is too simple. 

Some trees may access deep sources of water that 

allow forests to avoid all but the most catastrophic 

periods of reduced rainfall. In other cases, extreme 

warmth can lead to drought-like symptoms even when 

rainfall is normal. In many cases, direct observations 

of plant responses to drought, as seen in lower leaf 

conductance to water loss or early leaf abscission, 

are better indications of drought than changes in 

meteorological or soil variables alone.

Changes in the forest canopy due to drought have 

impacts that extend throughout the ecosystem, 

affecting the input of organic materials to the soil and 

subsequent responses of the soil microbial community. 

The thresholds of physiological response may differ 

considerably between higher plants and soil microbes, 

with altered biogeochemical cycling often continuing 

in the soil long after severe drought has caused a 

reduction in physiological activities in the aboveground 

plant tissues. Since most biogeochemical cycling occurs 

in soils, advances in our understanding of drought will 

come from studies that consider the response of entire 

ecosystems to limited water availability, which is likely 

to manifest first in plants (fig. 5.1).

Often, drought affects forest biogeochemical cycling 

through indirect pathways. Many drought-stressed trees 

are susceptible to insect attack (chapter 6), which can 

alter the movement of essential elements [e.g., nitrogen 

(N) and phosphorus (P)] from plants to the soil. Severe 

drought also makes fires more likely, and these fires 

release essential elements from live and dead organic 

matter in ecosystems to the atmosphere and to runoff 

waters (chapter 7). It may take many years to replace 

the nutrients that are lost from a single fire.

This chapter summarizes what we know about the 

effects of drought on forest biogeochemistry. Much 

of what we know derives from observations during 

prolonged droughts and from field experiments that 

have imposed artificial drought on ecosystems (Wu 

Figure 5.1—Mortality of Ashe’s juniper (Juniperus ashei) at Colorado Bend State Park, TX, after the 

2011 drought. (photo by Rob Jackson, Stanford University)
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

and others 2010). These experiments offer a glimpse 

of what we should expect to occur more frequently 

in a warmer and drier World of the future and what 

climate change will mean for forest productivity and 

management.

Drought and Forest 

Biogeochemistry

The degree to which droughts impact nutrient cycling 

in vegetation depends on multiple factors: the severity 

and duration of the drought; the morphology, phenology, 

sensitivity, and physiology of the dominant trees; and 

the nutrients of interest. Prolonged droughts originating 

early in the growing season, for example, may induce 

some tree species to lose leaves (and possibly roots) 

prematurely—a process that would reduce nutrient 

uptake and accelerate nutrient losses from plants. Most 

nutrients are mobilized and transported in soil water, so 

water stress may lead to nutrient stress.

Nutrient Uptake

The acquisition of nutrients by plants requires the 

availability of water. Nutrients move toward the surface 

of an absorptive root by diffusion and mass flow and are 

taken up and transported through the plant as a result 

of water potential gradients between root, xylem, and 

leaf cells. Thus, as soils dry during prolonged drought, 

nutrient uptake is generally reduced, resulting in lower 

leaf nutrient concentrations and reduced photosynthetic 

activity (Rustad and others 2011). However, the 

impact of drought on nutrient uptake is species- and 

nutrient-dependent (Grabarova and Martinkova 2001). 

Hanson and others (2003) reported that after 6 years of 

experimentally induced drought (33-percent reduction 

in throughfall), foliar N was reduced in some tree 

species (relative to controls) but not in others. Some 

species respond to drought by reducing their leaf area 

but show little or no change in the nutrient content in 

their remaining leaves (Pilon and others 1996). In an 

experimental plantation of Norway spruce, Nilsson and 

Wiklund (1994) reported higher nutrient concentrations 

and greater nutrient uptake in drought treatments 

relative to controls.

A possible explanation for sustained nutrient 

uptake under drought conditions may be related to 

belowground responses of trees to water stress. 

Hanson and others (2003) reported that some species 

likely accessed water and nutrients from deep soil via 

tap roots or by preferentially allocating carbon (C) to 

subsurface roots (Joslin and others 2000).

Allocation of C to mycorrhizal fungi may also represent 

a viable rooting strategy for overcoming water/

nutrient stress (Hawkes and others 2011, Lehto 

and Zwiazek 2011, Rapparini and Penuelas 2014). 

Mycorrhizal fungi can access water in soil micropores 

and hydraulically redistribute water to nutrient-rich 

surface soils (Neumann and Cardon 2012, Querejeta 

and others 2007). Moreover, deciduous hardwood 

forests may differ in their sensitivities to drought based 

on the abundance of trees associating with arbuscular 

mycorrhizal fungi (AM) relative to ectomycorrhizal fungi 

(ECM), as AM trees are generally less tolerant of water 

stress than ECM trees (Brzostek and others 2014).

In N-fixing trees, reduced nutrient uptake from the 

soil appears to be at least partially compensated by 

increased N-fixation in root-associated symbiotic 

bacteria. In experimental studies, drought increased 

nodule biomass in Alnus (Tobita and others 2010) and 

nitrogen fixation in black locust (Robinia pseudoacacia) 

(Wurtzburger and Miniat 2014), potentially increasing 

nitrogen inputs to forest ecosystems.

Aboveground Nutrient Cycling

While less quantitatively important than uptake by roots, 

some plant canopies acquire nutrients directly from 

precipitation and gases (Schlesinger and Bernhardt 

2013). As such, drought may exacerbate nutrient stress 

by reducing foliar uptake of growth-limiting nutrients 

such as N. Drought-induced reductions in foliar uptake 

are likely to depend on the morphology of the crown 

(a function of the species, age, and stand structure), 

but may also depend on the availability of nutrients in 

soil relative to inputs in precipitation. In regions of the 

World where much of the N in soil is found in slowdegrading soil organic matter, for example, reductions 

in foliar N uptake owing to drought may be ecologically 

significant (Lockwood and others 2008, Sparks, 2009). 

Rain can also enhance nutrient losses from the canopy 

by leaching nutrients from leaves (throughfall) and 

stems (stemflow); as such, decreases in rain can reduce 

the cycling of mobile nutrients such as potassium (K) 

(Gundersen and others 1998).

Retranslocation

The reabsorption of nutrients from senescing leaves 

(i.e., retranslocation) plays a critical role in nutrient 

retention, as trees generally reabsorb approximately 

50 percent of N and P from leaves prior to senescence 

(Aerts 1996, Vergutz and others 2012). While 

retranslocation rates are highly species- and sitedependent, there is some evidence that resorption 
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efficiencies are sensitive to changes in soil moisture 

(Boerner 1985, Killingbeck 1996, Minoletti and Boerner 

1994). Drought may impact retranslocation in one of 

two ways: (1) by inducing early senescence of leaves, 

or (2) by altering the physiology of leaves in ways that 

impair nutrient resorption prior to senescence. Del 

Arco and others (1991) reported that N retranslocation 

depended on rates of leaf abcission, with trees that 

retained leaves longer resorbing less N.

Differences in the drought response of deciduous trees 

may also relate to the plant’s overall strategy for dealing 

with water stress. Mesophytic tree species (e.g., Acer, 

Liriodendron, Prunus) may be more likely to drop leaves 

early during a drought than xerophytic tree species (e.g., 

Quercus, Carya), which often do not close stomates 

during drought and operate close to the margin of 

hydraulic failure (Choat and others 2012). In one of the 

few studies offering a direct examination of the effects of 

drought on leaf senescence and retranslocation, Marchin 

and others (2010) found that 4 of 18 tree species in the 

Southeastern United States dropped leaves early during 

drought. The early senescence of leaves resulted in 

greater reabsorption of N, P, and K (relative to species 

that retained their leaves), and enabled these trees to 

reabsorb nutrients before the leaf desiccated.

Susceptibility to Insect Attack

Forest ecologists have long recognized that when 

trees are stressed, such as by drought, they are 

more vulnerable to insect attack (chapter 6). Insect 

defoliation increases the rate of biogeochemical cycling 

in forests and may ultimately lead to the mortality of 

trees and increased susceptibility to forest fires, which 

have huge impacts on ecosystem biogeochemistry 

(Schlesinger and Bernhardt 2013). Some tree species 

are less able to allocate photosynthetic resources 

to the synthesis of protective compounds, such as 

terpenes, during droughts (Bonello and others 2006, 

McDowell and others 2013, Waring and Schlesinger 

1985). Experimental drought, for example, stimulated 

insect attack on pinyon pine (Gaylord and others 2013). 

Mortality of oak in Arkansas and Missouri is related 

to drought and insect attack by oak borer (Fan and 

others 2008). Recent widespread bark beetle attack 

on western coniferous forests may be related to the 

drought stress encountered in recent warmer, drier 

conditions (Kurz and others 2008). Tree-ring records 

show that periods of spruce beetle attack have been 

correlated with drought in Colorado since 1650 C.E. 

(Hart and others 2014). When trees are defoliated, 

there are major changes in the form and rate of 

nutrient return to the soil, especially by reducing the 

retranslocation of nutrients before leaf abscission 

(Lovett and others 2002).

Recent mountain pine beetle activity in the Rocky 

Mountain States was synchronized by regionalscale drought conditions that occurred around 2002 

(Chapman and others 2012, Creeden and others 2014). 

In lodgepole pine (Pinus contorta), mountain pine 

beetles introduce blue-stain fungi to the tree’s vascular 

system that blocks water uptake within weeks of a 

successful attack and causes drought-like symptoms 

and tree mortality (Hubbard and others 2013). Along 

with reduced water uptake, plant-available soil N pools 

increase soon after beetle attack (Clow and others 2011, 

Morehouse and others 2008). Deposition of relatively 

N-enriched litter is a common feature of beetle attacks 

in various forest types. Needle fall beneath beetleinfested ponderosa pine (Pinus ponderosa) contained 

1.1 percent N compared to 0.6 percent in uninfested 

stands in Arizona (Morehouse and others 2008). Similar 

patterns occurred following infestation of lodgepole 

pine [0.75 percent versus 0.45 percent N for beetleinfested and healthy trees; Griffin and others (2011)] and 

Douglas-fir [1.4 percent versus 0.9 percent N; Griffin 

and Turner (2012)].

Drought-related insect outbreaks that reduce leaf 

area or kill trees can also have a substantial impact 

on ecosystem C cycling (Weed and others 2013). For 

example, Clark and others (2010) found that gypsy moth 

defoliation (75 percent canopy defoliation) reduced net 

ecosystem annual carbon dioxide (CO2) exchange by 

41–55 percent in upland forests, and severe bark beetle 

outbreaks (40 to >80 percent trees impacted) in the 

Western United States reduced aboveground woody C 

production by 20–60 percent (Hicke and others 2012). 

In severe cases, insect outbreaks can switch the forest 

from being a C sink to a source, at least over the short 

term (Amiro and others 2010).

Cycling of Elements in Soils

Drought and consequent reductions in soil water have 

a myriad of direct and indirect effects on the cycling 

of elements in soils. These include consequences for 

belowground microbial activity, nutrient availability, and 

solid- and solution-phases of soil chemistry. Changes 

in the timing and reductions of precipitation associated 

with drought also affect soil aeration and erosion by 

runoff, with effects on soil nutrient status.
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For aerobic soil conditions, studies report a decline 

in rates of microbially driven processes such as N 

mineralization, nitrification, respiration, and litter 

decomposition with declining moisture, particularly 

as soil moisture falls below critical thresholds (Arnold 

and others 1999, Burton and others 1998, Emmett 

and others 2004, Pilbeam and others 1993, Rey and 

others 2002, Rustad and others 2000, Tate and others 

1988). Stark and Firestone (1995) observed that 

ammonium oxidizers are sensitive to dry conditions, so 

during drought the rate of nitrification and nitrate (NO3) 

losses in runoff decrease (Wetselaar 1968). Schimel 

and others (2007) estimated that osmolyte production 

by soil microbes during dry conditions immobilizes 

10–40 percent of the N mineralization in grasslands, 

and perhaps a similar amount in forests. Nitrous oxide 

production is also lower in dry soils (Davidson and others 

2008, Schlesinger 2013), and there is evidence that 

forest soils can even become net sinks for N2O under 

drought (Goldberg and Gebauer 2009). Experimental 

drought treatments also show greater methane 

consumption by soils (Borken and others 2006, Castro 

and others 1995, Davidson and others 2008).

Declines in soil microbial processes during drought 

lead to reduced availability and leaching of C, N, P, 

and base cations [e.g., calcium (Ca2+), magnesium 

(Mg2+), potassium (K+)]. Some of these effects are 

transient. For example, for red maple (Acer rubrum), 

O’Neill and others (2003) reported that lower rates of 

decomposition during a precipitation-exclusion in the 

spring were matched by higher rates under normal 

precipitation regimes later in the year, so that the 

annual rate of decomposition was similar in drought 

and control plots. These observations probably derive 

from the long-noted effect of wetting and drying on 

soil microbes, where microbial activity fluctuates with 

moisture availability (Sorensen 1974, Stevenson 1956).

In hydric soils such as wetlands, where soils are 

permanently or seasonally saturated by water, oxygen is 

limiting, and anaerobic processes dominate (Brady and 

Weil 2008), drought can actually induce more favorable 

conditions for aerobic microbial processes by increasing 

the oxygen status of the soils (Emmett and others 

2004). Concurrently, rates of anaerobic processes, such 

as methanogenesis and denitrification, will decline.

Changes in the biomass, distribution, and physiology 

of plant roots have direct impacts on the cycling of 

elements in soils by altering plant nutrient uptake, 

autotrophic root respiration, root-mycorrhizal 

interactions, and belowground detrital inputs via the 

turnover of roots (Borken and others 2002, Bryla 

and others 2001, Burton and others 1998, Rey and 

others 2002). Drought can decrease fine root biomass 

due to decreased root elongation and increased root 

cavitation and mortality (Jackson and others 2000, 

Joslin and others 2000). Field studies suggest that 

tree root systems respond to water stress by vertically 

and temporally shifting growth rates. This can result in 

less root growth in shallow soil layers (where moisture 

stress is greatest) and more root growth deeper in 

the soil (where moisture can be more available) or 

increases and decreases in root growth over time 

tracking changing soil moisture conditions (Jackson and 

others 2000, Joslin and others 2001). A decrease in fine 

roots during droughts is sometimes compensated by 

greater production during more favorable times of the 

year, as was shown at the Walker Branch Throughfall 

Displacement Experiment in Tennessee (Joslin and 

others 2000).

Over longer periods of time, trees adapt to dry climate 

regimes or longer term drought by increasing fine root 

biomass, increasing root-to-shoot ratios, and increasing 

rooting depth. Evidence for these responses to drought 

is apparent at the biome scale, where plants growing 

in xeric environments tend to have higher root-to-shoot 

ratios and deeper root systems compared to plants 

occupying more mesic environments (Schenk and 

Jackson 2005). In all cases, the redistribution of roots in 

response to water stress will directly affect the cycling 

of C, N, P, base cations, and trace elements in soils.

Soil water status directly affects solid- and solutionphase soil chemistry. In addition to changing the 

availability of elements through the biologic processes 

described above, changes in soil moisture also impact 

abiotic processes associated with ion-exchange 

reactions, leaching, diffusion, and weathering. 

Declines in soil water, for example, will increase ionic 

concentration in soils, resulting in intensified soil-surface 

exchange reactions (Sverdrup 1990). Decreased soil 

water also decreases rates of ion diffusion within 

soils, leaching loss of elements, and rates of mineral 

weathering (Schlesinger and Bernhardt 2013).

The rate of soil erosion by wind and water is typically 

low under closed-canopy forests, due to the moderating 

influence of the canopy on the energy of raindrops and 

threshold friction velocity of wind (Waring and 
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Schlesinger 1985). Erosion increases dramatically 

after forest harvest and forest fire, when soils are 

bare (Bormann and others 1974). These losses could 

be further exacerbated if a long period of drought is 

followed by intense rainfall. Globally, the greatest rates 

of erosion are typically when such events occur in semiarid climates (Langbein and Schumm 1958).

Increased soil water stress and drought will also 

have significant impacts on the cycling of elements 

in soils via indirect pathways, including changes in 

forest composition, pests and pathogens, and fire. 

To the extent that drought reduces streamflow, a 

lower frequency of flooding will reduce nutrient inputs 

to floodplain forests, which are often subsidized by 

seasonal delivery of sediments (Mitsch and Rust 1984).

Fire

Prolonged droughts increase the likelihood of fires 

in many ecosystems (chapter 7). Drought-induced 

wildfires cause periodic C and nutrient losses from 

many ecosystems in gaseous and particulate forms 

released to the atmosphere (Raison and others 1985) 

and through leaching and erosion in runoff waters 

(Dunnette and others 2014). The biogeochemical 

consequences of wildfire are proportional to fire 

severity and depend on factors such as the amount of 

woody fuel and forest floor consumed, the duration 

of combustion, the depth of heat penetration into the 

soil, and the spatial extent of the fire. Nitrogen losses 

from wildfires in conifer forests can range from 300 

to 855 kg N/ha (Johnson and others 1998), equivalent 

to 10–40 percent of the N in aboveground vegetation 

and forest floor layers (Schlesinger and Bernhardt 

2013). In contrast, low-intensity fires cause relatively 

small N losses (i.e., 10–40 kg/ha from southeastern 

pine forests) (Richter and others 1982, Wells 1971). 

Low-severity surface fires (e.g., prescribed fires), 

which rarely cause mortality among canopy trees, may 

actually increase growth and C accumulation rates of 

the remaining trees due to reduced competition and 

temporarily increased nutrient availability (Anning and 

McCarthy 2013, Fiedler and others 2010, Hurteau and 

North 2010).

Recovery and regrowth of vegetation after fire restores 

carbon pools and the rate of nutrient cycling, such that 

long-term impacts on the ecosystem may be small 

(Kashian and others 2006, Ryan and others 2010, 

Wiedinmyer and Hurteau 2010). However, wildfires 

that cause high post-fire mortality (i.e., “stand replacing 

fires”), large fuel consumption, and slow post-fire 

recovery can often result in large and long-lasting 

impacts on the magnitude and direction of carbon 

cycling processes (Amiro and others 2010, Kolb and 

others 2013). Carbon lost from wildfires in forests of the 

continental United States can be substantial, with recent 

estimates ranging from 13.4 Teragram (Tg) C/year for 

the period 1990–1999 to 25.6 Tg C/year for 1980–1989 

(Goetz and others 2012). For comparison, the net 

primary productivity (NPP) of forests in the United 

States is about 3,500 Tg C/year (Xiao and others 2010) 

and total carbon sequestration is estimated at 100–200 

Tg C/year (Zhang and others 2012).

Nutrient leaching usually increases after wildfire, 

though enhanced export to surface and groundwater 

is typically short-lived and small relative to losses to 

the atmosphere (Belillas and Feller 1998; Johnson 

and others 1998, 2007). Combustion of vegetation 

and forest floor litter exposes the mineral soil surface 

and increases erosion of C and nutrients. In areas that 

receive high-intensity rain storms, post-fire losses of 

forest floor C and nutrients by erosion can equal or 

exceed those from combustion. The consequences 

of these elemental losses are proportional to the 

extent of an area burned at high severity (Riggan and 

others 1994). For example, in the 2002 Hayman fire 

in Colorado, watersheds that sustained high severity 

wildfire on >45 percent of their area had streamwater 

NO3 and turbidity roughly threefold higher than other 

watersheds that were subject to severe burns on only 

10 percent of their area (Rhoades and others 2011).

Wildfires induce biogeochemical transformations that 

commonly increase nutrient availability in soils, despite 

losses of C and nutrients from vegetation and soils 

(Raison 1979, Wan and others 2001). Nutrients bound 

in vegetation and soil organic matter are released by 

combustion, adding inorganic forms of K, Ca, Mg, P, 

and N to the soil. Soil ammonium (NH4) is increased 

by oxidation of organic matter, ash inputs, and release 

of N from interlayer clay exchange sites. Post-fire soil 

NH4 typically remains elevated for about a year and is 

followed by an increase in soil NO3 (Certini 2005). In 

addition to changes in the exchangeable forms of soil 

N, net N mineralization and nitrification can increase 

dramatically (DeLuca and Sala 2006, Grady and Hart 

2006, Koyama and others 2010). Fires consume organic 

acids and release cations balanced by (bi)carbonates 

and hydroxides, reducing soil and stream acidity; these 

changes are often short-lived (Cerdà and Doerr 2008), 

though elevated soil pH may persist for years (Ulery and 

others 1993). Heating also affects the composition of 
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the organic matter remaining after a fire. Fires consume 

a greater proportion of the labile C and leave stable 

pyrogenic Ch (charcoal) that has implications for longterm C storage and N cycling (DeLuca and Aplet 2008, 

DeLuca and others 2006). Complex interactions between 

biotic and abiotic conditions in post-fire environments 

influence the duration and spatial scale of biogeochemical 

changes within and among ecosystem types.

The pace of biogeochemical recovery from wildfires 

depends on the magnitude and extent of elemental 

losses and transformations caused by the fire, coupled 

with the growth rate and composition of post-fire 

revegetation. Severe stand-replacing wildfires may 

reduce ecosystem N pools for decades to centuries 

(Certini 2005, Smithwick and others 2005). Post-fire 

recovery of plant and organic cover and nutrient demand 

relies on the persistence of soil microbes and vegetation 

capable of sprouting or germinating in burned soils 

or dispersing into burned areas. In Glacier National 

Park, rapid post-fire growth of residual vegetation was 

credited for the return of summertime stream NO3

concentrations to pre-burn levels within 2 years (Mast 

and Clow 2008). Conversely, after the Hayman fire in 

Colorado, dry conditions inhibited recovery of vegetation 

in ponderosa pine (Pinus ponderosa) forests, and 

stream NO3 remained elevated for more than 5 years 

(Rhoades and others 2011).

The abundance of nitrogen-fixing herbaceous plants 

and shrubs usually increases after wildfire. These 

species are known to add 10–100 kg N/ha/year and 

replace lost N within a few decades (Binkley and 

others 1982, Busse 2000). Nitrogen-fixing plants 

may contribute an order of magnitude more N than 

atmospheric deposition in regions not impacted by 

industry (Johnson and others 2005).

Tree mortality and large fires have increased 

significantly in the Western United States in recent 

years, likely in response to warmer and drier conditions 

(Dennison and others 2014, van Mantgem and others 

2009); however, similar patterns are not yet apparent in 

the East (Dietze and Moorcroft 2011). Landscape-scale 

patterns of species composition, vegetation structure, 

ground cover, and litter layer conditions contribute to 

long-term wildfire effects (Giesen and others 2008, 

Turner and others 2003). Patterns of forest succession 

after fire are well known for many ecosystems, yet 

the biogeochemical responses and recovery from the 

more severe and higher frequency fires projected under 

warmer, drier climates remain poorly understood.

Drought and Carbon 

Balance in Forests

Large-scale droughts in recent decades have stimulated 

interest in field studies and modeling projections to 

assess the effects of future droughts on the carbon 

balance of forests. Most field experiments that impose 

drought show reduced net primary production and 

net carbon exchange (Wu and others 2010). Drought 

led to reduced gross primary productivity and carbon 

sequestration across Europe in 2003 (Ciais and others 

2005) and the Amazon Basin in 2010 (Gatti and others 

2014). Global estimates of the long-term trends in forest 

NPP show a 1-percent decline during 2000–2009, largely 

as a result of droughts in the Southern Hemisphere 

(Zhao and Running 2010). We can expect reductions in 

global NPP during the transient period of drought that is 

anticipated in most models of future global climate.

Severe drought in the Amazon Basin turned a system 

that is typically a carbon sink into carbon source. Tian 

and others (1998) reported losses of 0.2 Petagram 

(Pg) C from the Amazon Basin during hot, dry years 

associated with El Niño conditions in 1987 and 1992. 

In 2005 and 2010, Amazonian droughts extended 

across 2–3 million km2 of tropical forests. Lewis and 

others (2011) estimated that the severe drought of 2010 

reduced carbon uptake by ~2.2 Pg C, compared to a 

decrease of 1.6 Pg C during the 2005 drought. Gatti 

and others (2014) reported a net loss of 0.48 Pg C from 

the Amazon Basin during the 2010 drought, compared 

to a net uptake of 0.25 Pg C during normal conditions. 

This reduced carbon uptake during drought is large, 

equivalent to about 5 percent of total global carbon 

emissions from fossil fuel burning.

In other regions, including Central America and 

Southeast Asia, field experiments and modeling 

both suggest that the combination of increasing 

temperatures and drought could alter the balance of 

photosynthesis and respiration, leading to higher net 

CO2 fluxes to the atmosphere and reducing carbon 

uptake (Cleveland and others 2010, Moser and others 

2014, Wood and others 2012).

The effects of drought have been increasingly visible 

in boreal forests during the last decade. Boreal forests 

cover >10 million km2 of the Earth’s surface and 

contain >50 Pg of biomass C (Pan and others 2013). 

Tree mortality in Canada’s boreal forests increased 4.7 

percent per year from 1963 to 2008, with recent climate 

change and drought-induced water stress estimated to 
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be the dominant cause of this mortality (Ma and others 

2012, Peng and others 2011). Drought stress decreased 

biomass accumulation particularly in western Canada, 

where moisture deficiency was greater, and increased 

annual tree mortality from <0.5 percent of biomass 

in the early 1970s to approximately 1.8 percent more 

recently (Pan and others 2013, Peng and others 2011). 

If the results apply to all of Canada’s boreal forests, then 

the reduction in the carbon sink from mature forests 

would be 7.3 Tg C/year, equivalent to approximately 

4 percent of Canada’s fossil fuel emissions (Ma and 

others 2012).

In boreal forests, individual species show different 

vulnerabilities and potential for large-scale dieback 

as a result of drought. Michaelian and others (2011) 

used a combination of remotely-sensed, field, and 

modeling data to examine mortality of aspen (Populus 

tremuloides) across 115,000 km2 (approximately 

45,000 square miles) of Saskatchewan, Canada. The 

severe drought of 2001–2002 led to >50 percent aspen 

mortality across large areas of the region, reducing 

aboveground biomass by 20 percent and having 

consequences similar to those of a large-scale fire. In 

the southern part of the region where the drought was 

most severe, a third of the aspen trees died. Overall, 

the amount of dead biomass was estimated to contain 

approximately 45 meitnerium carbon (Mt C).

Each year, forests in the United States accumulate 

enough C (833 Tg C/year) to offset approximately 16 

percent of U.S. fossil fuel emissions (Joyce and others 

2014); however, the rate of C accumulation varies from 

year to year due to climatic variability, disturbances, 

and management practices (Xiao and others 2011), 

and drought can substantially decrease C accumulation 

rates (Schwalm and others 2012). Brzostek and others 

(2014) reported that droughts can reduce the C sink of 

deciduous forests in the United States by as much as 17 

percent. In these forests, a 17-percent reduction in the 

C sink translates to an additional 1 to 3 days of global C 

emissions from fossil fuel burning each year. Further, 

the authors found that drought impacts can offset C 

gains of longer growing seasons as a result of warmer 

climate. For example, using decade-long records of 

climate and tree growth at the Morgan Monroe State 

Forest in Indiana, Brzostek and others (2014) found that 

despite 26 more days per year of C assimilation owing 

to milder temperatures, drought decreased the number 

of days of wood production by about 42 days over the 

same period, resulting in a 41-percent decrease in the 

amount of C stored in woody biomass. The impacts of 

drought on forest carbon balance would be expected to 

vary considerably across the continental United States 

due to differences in the biophysical environment, 

species composition, and management intensity.

Ecosystem carbon models and long-term eddy 

covariance studies that include drought years provide 

an estimate of the net effects of drought on ecosystem 

carbon balance and suggest causal factors. Modeling 

studies suggest different carbon-cycling responses 

depending on the climate regime, where humid 

sites (such as in the Eastern United States) were 

generally less responsive to lower precipitation than 

drier sites (such as in the Western United States) 

(Gerten and others 2008). In the Southeast United 

States, Powell and others (2008) reported little 

change in the net ecosystem production (NEP)—

NEP=gross ecosystem productivity minus ecosystem 

respiration—during drought in slash pine (Pinus elliotti) 

due to the counteracting effects of decreased canopy 

photosynthesis and soil respiration. Elsewhere in the 

Southeast, NEP in a loblolly pine (Pinus taeda) plantation 

was reduced by drought, primarily through decreased 

canopy and whole-tree leaf conductances (Noormets 

and others 2010), without a corresponding decrease in 

ecosystem respiration. In forests of the Western United 

States, net CO2 uptake reported from eddy-flux towers 

during a prolonged drought indicated a reduction in 

NEP of 63 g/m2/year and a decline of 30 to 298 Tg C/

year in the current carbon sink in that region (Schwalm 

and others 2012). For western coniferous forests, 

NEP declined primarily as a result of decreased gross 

ecosystem production, whereas ecosystem respiration 

declined only slightly (Schwalm and others 2012).

Management Implications

Forests will respond to existing and new disturbance 

regimes; however, the resulting forest structure and 

function may be inconsistent with the desired future 

conditions and associated ecosystem services. A key 

question is whether and how forest management can 

be used to maintain desired conditions and ecosystems 

services. Increased drought severity and frequency are 

likely to make forests more vulnerable to both direct 

(e.g., reduced growth and mortality) (chapter 4) and 

indirect (e.g., insect outbreaks, pathogens, wildfire) 

(chapters 6 and 7) impacts (Choat and others 2012, 

Dale and others 2001, Liu and others 2013, Weed and 

others 2013). Exactly how these impacts manifest 

will depend in large part on the nature of drought. For 

example, frequent low-severity drought may selectively 
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favor more drought-tolerant trees and create forests 

better adapted to future conditions without the need for 

management intervention. In contrast, severe drought 

(especially in combination with insect outbreaks or 

fire), may result in large-scale changes that warrant 

substantial management responses. These responses 

range from reducing vulnerability to drought, facilitating 

post-drought recovery, or facilitating a transition to a 

new forest condition (Millar and others 2007). Here, 

we focus primarily on management options that reduce 

vulnerability.

Forest management actions to minimize drought 

impacts on biogeochemical cycling will require altering 

forest structure and function in ways that increase 

adaptive capacity and/or reduce vulnerability to 

drought. Management options are highly site specific 

and constrained by a wide variety of factors; however, 

from the perspective of biogeochemical cycling, 

maintaining forest cover and minimizing forest floor 

loss and soil erosion are key objectives. Reducing 

stand density by thinning may decrease water 

demand and subsequent drought stress (D’Amato 

and others 2013, Dore and others 2012, McDowell 

and others 2006), with the potential added benefit 

of reducing fuel loading and wildfire risk (McIver and 

others 2009). Stand structure can also be altered 

and managed using multi-aged systems that may 

create stands with higher water-use efficiency 

(O’Hara and Nagel 2006). Some evidence suggests 

that younger (smaller) trees are more vulnerable to 

drought than larger trees (DeLucia and Schlesinger 

1990, Hanson and others 2001) and older trees (Klos 

and others 2009), indicating that stand age and size 

class distributions could be managed to decrease 

vulnerability. Our current understanding of differences 

in functional attributes related to transpiration demands 

(Ford and others 2011) and rooting characteristics 

(Joslin and others 2000, Schenk and Jackson 2005) 

could be used to favor more drought-tolerant (or 

water-use efficient) tree species in existing stands 

and developing and planting more drought-resistant 

species for new stands. In some regions of the United 

States, planting or favoring more drought-tolerant 

species may conflict with management objectives that 

favor rapid accumulation of biomass, as fast-growing 

woody species often use more water and exacerbate 

drought impacts (King and others 2013). Drought 

impacts could also be reduced by designing road and 

drainage networks to keep more of the water in the 

forest (Grant and others 2013), instead of moving 

it rapidly to the streams or concentrating it in small 

areas of the landscape as is typically the case (Kolka 

and Smidt 2004). Successful forest management in 

the face of drought will likely require a combination 

of many approaches. For example, Grant and others 

(2013) used simulation modeling to demonstrate the 

advantages of combining increased water availability, 

thinning, and mulching to reduce drought stressrelated mortality in ponderosa pine (Pinus ponderosa) 

during an extreme drought.

Representation of 

Drought in Ecosystem 

and Global Models

To anticipate how forest biogeochemistry will 

respond to future drought, it is important to assess 

the representation of drought in ecosystem and 

biogeochemical models as these are our primary 

means of extrapolating the response of ecosystems 

into novel or rare conditions. Particularly useful in this 

assessment are the results of model inter-comparison 

projects (MIPs), where the performance of multiple 

models is judged against data from one or more sites 

or experiments. These give a better measure of the 

performance of the community of models, rather than 

assessing individual models tuned to individual sites. In 

a recent comparison of 22 ecosystem models against 

44 eddy-covariance towers across North America, 

the biases and chi-squared error in the net ecosystem 

exchange (NEE) of carbon were only marginally higher 

under dry conditions, and this error was only apparent 

during the growing season (Schwalm and others 2010). 

This is encouraging since these errors were smaller than 

the errors across seasons or among biomes in the same 

models.

The same MIP found that model errors in gross 

primary productivity (GPP) were substantially higher 

under low-humidity conditions (Schaefer and others 

2012). Furthermore, while all models captured the 

shape of the GPP response to moisture under high 

humidity conditions, for many models the shape of the 

GPP response curve was substantially different from 

observations, indicating underlying structural errors 

rather than simple miscalibration. Similarly, a MIP at the 

Duke and Oak Ridge FACE (Free Air CO2 Enrichment) 

experiments showed substantial differences among 

11 models that could be attributed to differences in 

moisture responses at the leaf level (stomatal closure), 

at the whole plant level (water uptake), and at the stand 

level (boundary layer exchange of water vapor) (De 

Kauwe and others 2013).
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Likewise, a detailed analysis of the sources of uncertainty 

within a single model applied to 4 North American 

biomes and 17 vegetation types 4 that water uptake and 

stomatal closure responses were the second and third 

(respectively) largest sources of uncertainty in predicting 

NPP (Dietze and others 2014). Sims and others (2014) 

found that many deciduous forests don’t lose their 

“greenness” in remote-sensing images taken during 

drought, despite large reductions in photosynthesis at 

the canopy scale (chapter 9). Given that satellite data 

products predicting GPP and NPP assume a relationship 

between greenness and photosynthesis, this implies 

that such global data products may underestimate 

the magnitude of droughts in terms of net ecosystem 

balance. As a whole, there is pressing need to improve 

the ecophysiological responses of plants to drought in 

ecosystem and global models.

Few MIPs have focused on belowground 

biogeochemical responses. Traditionally, heterotrophic 

respiration has been modeled as proportional to soil 

carbon pool size and a temperature-varying turnover 

rate, with the effects of soil moisture entering as a 

scaling function (0–1) (Parton and others 1993). In 

such models, drought generally causes a substantial 

reduction in heterotrophic respiration. One recent MIP 

looking specifically at seven oak woodlands growing in 

Mediterranean climates found that across five models 

there was a tendency to overestimate ecosystem 

respiration during droughts (Vargas and others 2013).

In many cases models impose a tight stoichiometric 

coupling between soil carbon and nitrogen; thus, the 

reduction in respiration also results in a slowing of the 

nitrogen cycle. Recently, some models have considered 

microbial activity and soil enzymes more explicitly 

(Allison and others 2010, Davidson and others 2011, 

Lawrence and others 2009, Xu and others 2014). Such 

approaches improve predictions of transient fluxes that 

occur during post-drought rewetting (Lawrence and 

others 2009) and explain how drought can decouple the 

typical temperature-respiration responses (Davidson 

and others 2011). In contrast to soil CO2, most models 

devote much less attention to the cycling of other 

nutrients in response to drought, largely because 

the other biogenic greenhouse gas (GHG) emissions 

considered by models are associated with wet 

conditions [nitrogen dioxide (NO2), methane (CH4)], 

while tree volatile organic compounds (VOCs) such as 

isoprene, which respond to heat stress, are seldom 

considered. Finally, many ecosystem models include 

a representation of fire, with fire probability explicitly 

a function of either fuel moisture or soil moisture, and 

thus generate an interaction between fire and drought. 

By contrast, insects and pathogens are absent from 

most models, or are limited to case studies, as more 

general approaches to modeling their impacts has 

been lacking (Dietze and Matthes 2014, Hicke and 

others 2012). As such, models will, in general, miss 

the known interactions between drought and outbreak 

susceptibility.

Summary and Conclusions

Drought affects forest growth and carbon storage by 

lowering the rate of photosynthesis, while causing 

lesser effects on respiration, except in extreme 

conditions. Trees alter their use and allocation of 

nutrients in response to drought, and changes in soil 

nutrient cycling and trace gas flux (N2O and CH4) are 

observed when experimental drought is imposed on 

forests. In extreme droughts, trees are increasingly 

susceptible to attack by pests and pathogens, which 

can lead to major changes in nutrient flux to the soil. 

Extreme droughts often lead to more common and 

more intense forest fires, causing dramatic changes in 

the nutrient storage and loss from forest ecosystems. 

Changes in the future manifestation of drought will 

affect carbon uptake and storage in forests, leading 

to feedbacks to the Earth’s climate system. We must 

improve the recognition of drought in nature, our ability 

to manage our forests in the face of drought, and the 

parameterization of drought in Earth system models for 

improved predictions of carbon uptake and storage in 

the World’s forests.

Acknowledgments

This research was supported by the Cary Institute 

of Ecosystem Studies. R.B. Jackson acknowledges 

additional grant support from the U.S. Department of 

Agriculture–Agriculture and Food Research Initiative 

(USDA-AFRI) grant number 2012-00857, and M.C. 

Dietze acknowledges support from a National Science 

Foundation (NSF) Macrosystems grant number 

1241894.

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CHAPTER 6

T.E. Kolb is a Professor, Northern Arizona University, School of Forestry, Flagstaff, 

AZ, 86001.

C.J. Fettig is a Research Entomologist, U.S. Department of Agriculture, Forest Service, 

Pacific Southwest Research Station (PSW), Davis, CA 95618.

B.J. Bentz is a Research Entomologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Logan, UT 84321.

J.E. Stewart is an Assistant Professor, Colorado State University, Department of 

Bioagricultural Sciences and Pest Management, Fort Collins, CO 80521.

A.S. Weed is a Postdoctoral Research Associate, Dartmouth College, Department of 

Biological Sciences, Hanover, NH 03755.

J.A. Hicke is an Associate Professor, University of Idaho, Department of Geography, 

Moscow, ID 83844.

M.P. Ayres is a Professor, Dartmouth College, Department of Biological Sciences, 

Hanover, NH 03755.

Forest Insect and 

Fungal Pathogen 

Responses to Drought

Thomas E. Kolb

Christopher J. Fettig

Barbara J. Bentz

Jane E. Stewart

Aaron S. Weed

Jeffery A. Hicke

Matthew P. Ayres
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Introduction

Recent changes in precipitation patterns and in the 

occurrence of extreme temperature and precipitation 

events have been documented in many forested regions 

of the United States (Ryan and Vose 2012). Changes 

in drought intensity and frequency have the potential 

to alter populations and impacts of tree-damaging 

forest insects and pathogens (Ayers and Lombardero 

2000, Dale and others 2001, Weed and others 2013). 

Scientists, forest managers, and environmental 

policymakers need to better understand the role of 

drought in outbreaks of forest insects and diseases in 

order to anticipate the future condition of U.S. forests 

and to consider actions to mitigate undesirable changes.

Here we review evidence for a role of drought in 

outbreaks of, and tree damage by, herbivorous insects 

and fungal pathogens in forests of the United States. 

First, we describe our understanding of how drought 

affects host nutritional quality and susceptibility to 

attack, and how damage by insect herbivory and 

pathogens affect tree responses to drought. Second, we 

review the responses of herbivorous forest insects (bark 

beetles, defoliators, sapfeeders) and fungal pathogens 

to drought. Third, we highlight regional differences in 

the roles of drought on forest insects and diseases by 

contrasting the Western United States with the Eastern 

United States. Fourth, we discuss predictions of future 

drought-related insect and disease impacts to western 

and eastern forests. Finally, we summarize our findings 

and highlight important research needs.

Tree Responses to Drought

Host Tree Nutrition and Susceptibility to Attack

Drought affects many components of tree nutritional 

quality. Several reviews of hundreds of studies (Huberty 

and Denno 2004, Mattson and Haack 1987, Rouault 

and others 2006) have concluded that drought often 

increases plant tissue concentrations of nitrogen 

compounds such as amino acids and nitrate; osmolytes 

such as sugars and inorganic ions; and allelochemicals 

such as cyanogenic glycosides, terpenoids, and 

alkaloids. The responses of most of these compounds 

are hypothesized to be dome-shaped with increases in 

tissue concentration during mild or moderate drought, 

when water stress constrains growth more than 

photosynthesis and root uptake of nutrients, followed by 

decreases during long and severe drought when intense 

water stress constrains growth, photosynthesis, and 

root uptake (Mattson and Haack 1987).

Drought-induced changes in nitrogen content of tree 

tissues have been investigated in many studies because 

of the importance of nitrogen in insect metabolism 

and its influence on population growth (White 1984). 

Drought often increases nitrogen content of tree 

tissues. Positive effects of drought on tree damage by 

foliage-feeding insects are often attributed to increased 

nitrogen content of water-stressed leaves (Jactel 

and others 2012). For example, lepidopteran larval 

survival is positively associated with pine leaf nitrogen 

concentration (Hodar and others 2002).

Drought often causes early senescence of older 

leaves that remobilizes nitrogen into soluble forms 

through vascular tissues to younger tissues, where 

concentrations in water-stressed plants often exceed 

concentrations in non-stressed plants (White 1984). 

All forms of drought reduce tree tissue water content, 

which often interferes with insect utilization of nitrogen 

(Huberty and Denno 2004). Timing and duration of 

water stress are important controls over insect capacity 

to use concentrated zones of nitrogen in plants. For 

example, Huberty and Denno’s (2004) pulsed stress 

hypothesis predicts that sapfeeding insects benefit by 

feeding on drought-stressed plants when drought is 

followed by wetter periods that increase plant turgor 

and hence allow insects to benefit from droughtinduced increase in plant tissue nitrogen.

Drought often alters plant defenses. The growthdifferentiation-balance hypothesis (GDBH) (Herms 

and Mattson 1992) predicts that drought has nonlinear 

impacts on carbon-based plant defenses, such 

as terpenes, and defenses that ultimately require 

carbohydrates to support metabolic costs of synthesis. 

Specifically, mild or moderate water stress that does not 

cause closure of plant stomata is predicted to increase 

carbon-based defense due to surplus carbohydrates 

that result from a negative effect of stress on the use 

of carbohydrates for growth that is greater than the 

production of carbohydrates by photosynthesis (Lorio 

1986, Reeve and others 1995). In contrast, intense 

water stress causes plants to close stomata to avoid 

excessive water loss, which consequently reduces 

photosynthesis (McDowell and others 2008, Pallardy 

2008). Prolonged periods of low photosynthesis during 

intense water stress are predicted by the GDBH to 

reduce carbohydrate supply and metabolism of all 

plant processes, including defense. Intense drought 

likely causes defense failure due to a combination of 

tree carbon starvation and hydraulic failure (McDowell 

and others 2011, Tague and others 2013). The current 
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understanding of drought impacts on chemical 

composition of tree defenses is poor and largely based 

on experiments with seedlings that may not scale 

directly to mature trees (Lusebrink and others 2011, 

Turtola and others 2003). The few experimental studies 

of mature trees (Gilmore 1977, Hodges and Lorio 1975) 

have shown that drought can alter chemical composition 

of resin monoterpenes in pines, but effects of such 

alterations on tree defense and insect populations are 

not known. Drought-induced changes in tree defense 

compounds are rooted in alterations in transcription of 

genes associated with stress resistance (Arango-Velez 

and others 2014).

Drought often alters insect feeding by increasing leaf 

toughness. Physical characteristics of plant tissues, such 

as leaf toughness, are strongly associated with plant 

resistance against insects. A recent review reported 

stronger roles of physical traits than chemical and 

secondary metabolic traits in plant resistance to insect 

herbivory (Carmona and others 2011). During drought, 

leaf water content decreases and leaf toughness and 

dry matter content increases (McMillin and Wagner 

1996, Pasquier-Barre and others 2001). These changes 

are associated with reduction in folivore feeding and 

reproduction (Awmack and Leather 2002, Pasquier-Barre 

and others 2001, Wagner and Zhang 1993).

Drought can increase plant attractiveness to insects 

by altering clues used to identify hosts (Mattson and 

Haack 1987, Rouault and others 2006). Leaf yellowing 

that often accompanies drought may be a spectral 

clue detected by insects, and warmer temperature of 

drought-stressed plant tissues may be detected by 

insect thermal sensors. Xylem cavitation in plants caused 

by drought results in ultrasonic acoustic emissions that 

likely are detectable by some insects (Haack and others 

1988). Insect chemoreceptors may detect droughtinduced changes in suites of plant compounds. For 

example, drought may induce plant production of volatile 

compounds and ethanol that are olfactory attractants for 

some insects, such as bark beetles (Kelsey and Joseph 

2001, Kelsey and others 2014, Manter and Kelsey 2008, 

Miller and Rabaglia 2009).

Influence of Pathogens and Herbivory 

in Tree Drought Response

Few studies have addressed the impact of previous 

insect herbivory on tree response to drought. Insect 

defoliation of conifers during experimentally induced 

drought has been reported to reduce water stress 

(e.g., less negative xylem water potential) of isolated 

potted trees (Kolb and others 1999), but to have little 

effect on water stress of trees sharing the same soil 

resources (Jacquet and others 2014). Feeding by the 

hemlock woolly adelgid (Adelges tsugae) on eastern 

and Carolina hemlocks (Tsuga canadensis and Tsuga 

caroliniana, respectively) increased tree water stress 

and predisposed trees to drought in a field observational 

study (Domec and others 2013, Gonda-King and others 

2014). The few studies of the combined effects of 

previous herbivory and drought on tree growth and 

carbohydrate pools show largely additive effects. For 

example, an experimental study of 10-year-old maritime 

pine (Pinus pinaster) found additive effects with no 

interaction of artificial defoliation and water stress 

on tree growth and carbohydrate pools (Jacquet and 

others 2014). In this study, carbohydrate pools of whole 

trees, roots, and stems were lowest in water-stressed 

trees exposed to 100 percent defoliation. Defoliation 

also redistributed carbohydrates from roots to stems, 

a response which likely predisposes defoliated trees 

to future drought by reducing root growth. In another 

example, experimental defoliation of aspen (Populus 

tremuloides) reduced stem hydraulic conductance 

because of a decrease in xylem growth (Anderegg 

and Callaway 2012). This response likely predisposes 

aspen to water stress in future droughts. Moreover, 

defoliation of aspen reduced tree carbohydrate storage 

and increased occurrence of fungal cankers, stem 

borers, and bark beetle attacks (Anderegg and Callaway 

2012). These findings show that previous herbivory that 

alters tree carbohydrate pools and defense metabolism 

can, in turn, influence tree response to future drought 

and insect and pathogen attacks. For example, whereas 

the associated mechanisms are not fully understood, 

previous tip moth (Rhyacionia frustrana) attacks 

predispose trees to higher levels of attack in subsequent 

generations (Coody and others 2000).

Fungal pathogens predispose trees to drought stress 

and drought-induced mortality. A recent framework 

(Oliva and others 2014) predicts that necrotrophs, 

which obtain nutrients from dead tree cells, accelerate 

drought-induced tree mortality by depleting tree 

resources as a result of repair and compartmentalization 

processes. Vascular wilts have been hypothesized to 

accelerate drought-induced tree mortality by reducing 

sapwood conductance of water and impairing phloem 

transport. Biotrophs, which obtain nutrients directly 

from living tree tissues, are expected to be negatively 

affected by drought because of the strong connection 

between their performance and tree nutritional status. 

However, if biotrophs are able to invade stressed 
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trees, they are expected to cause more severe drought 

impacts on trees because they deplete carbohydrate 

reserves important for tree drought tolerance (Oliva and 

others 2014).

Parasitic plants typically intensify negative impacts of 

drought on tree water stress and growth by obtaining 

water and nutrients from tree hosts (Sanguesa-Barreda 

and others 2012, Stanton 2007, Stewart and Press 

1990). High transpiration rates by xylem-tapping 

parasites, such as the true mistletoes (Phoradendron

spp.), often reduce xylem water potential, stomatal 

conductance, net photosynthetic rate, and water-use 

efficiency of host branches and leaves (Ehleringer 

and others 1986, Orozco and others 1990, SanguesaBarreda and others 2013, Zweifel and others 2012). 

Moreover, infection by xylem-tapping parasites 

can decrease xylem hydraulic conductivity of host 

branch portions distal to the infection (Tennakoon and 

Pate 1996). Xylem-tapping parasites often reduce 

ectomycorrhizae on tree roots (Gehring and Whitham 

1992), which reduces host nutrient and water uptake. 

Phloem-tapping parasitic plants, such as the dwarf 

mistletoes (Arceuthobium spp.), predispose trees to 

drought by several processes including alteration of 

host hormones (Logan and others 2013) and hydraulic 

processes (Sala and others 2001), reduction of host 

net photosynthetic rate and water-use efficiency 

(Marias and others 2014, Meinzer and others 2004), 

and depletion of host carbohydrates transported in 

phloem (Knutson 1979, Stewart and Press 1990). 

These carbohydrate losses likely reduce tree capacity 

for metabolic processes of drought tolerance and 

reduce root uptake of water and nutrients because 

less carbohydrate is allocated to roots (Knutson and 

Toevs 1972, Stewart and Press 1990). Phloem-tapping 

parasitic plants, such as the dwarf mistletoes that occur 

on conifers, also predispose trees to lethal bark beetle 

attacks during drought (Kenaley and others 2008).

Insect and Pathogen 

Responses to Drought

Outbreaks of some herbivorous insects and fungal 

pathogens occur during or following drought (Koricheva 

and others 1998, Mattson and Hack 1987, Sturrock 

and others 2011). Performance and impacts of insects 

and pathogens during and following drought differ 

depending on the type of food substrate (i.e., woody 

or foliar), feeding guild, duration of stress, and the type 

and importance of host defenses. The intrinsic capacity 

for drought resistance, which can vary among individual 

trees, species, and regions, will also influence tree 

response to water stress, insect herbivory, and fungal 

pathogens. Below we review impacts of drought and 

tree water stress on performance and impacts of major 

tree-feeding insect guilds (i.e., bark beetles, defoliators, 

sapfeeders) and tree fungal pathogens.

Bark Beetles

Bark beetles are chewing insects that feed on phloem 

and woody tissue beneath the bark of trees. A few 

notable species feed on live tissues causing death 

of the host tree, resulting in extensive economic and 

ecological impacts when widespread population 

outbreaks occur (Wood 1982) (fig. 6.1). Host trees have 

evolved defensives, however, that include chemical, 

physical, and histological components. A variety of 

chemical groups are involved in tree defense against 

bark beetle attack including terpenes, which are both a 

constituent and an inducible component of tree resin. 

Terpene concentrations can increase to levels that are 

repellant and toxic in a matter of days following beetle 

attack (Franceschi and others 2005). Structural aspects 

of trees, such as the number and size of resin ducts in 

the xylem and phloem, are also important as they are 

responsible for the production and storage of resin (Kane 

and Kolb 2010). Both terpene production and resin duct 

formation are dependent on carbon allocation within a 

tree, and carbon allocation can be nonlinearly influenced 

Figure 6.1—Mountain pine beetle (Dendroctonus ponderosae) 

is one of several bark beetle species that has caused extensive 

tree mortality in pine forests of western North America. Tree 

mortality increased in multiple areas during the mid-2000s 

following a severe drought in the early 2000s. On the Helena 

National Forest, Montana, tree mortality exceeded 70 percent in 

some lodgepole (Pinus contorta) and ponderosa (P. ponderosa) 

pine stands. (photo by Barbara Bentz, U.S. Department of 

Agriculture, Forest Service) 
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by drought (Herms and Mattson 1992). Intense drought 

reduces carbon assimilation, water transport, and cell 

turgor, thereby decreasing the synthesis and mobilization 

of secondary metabolites, such as terpenes, that are 

used in defense against bark beetle attack (Sala and 

others 2012). The level of water stress, however, 

may influence the allocation of assimilated carbon to 

defense and growth, as described above using the 

GDBH. Although at severe levels of water stress both 

growth and defense are most likely reduced, moderate 

water stress could lead to increased resistance if only 

growth is constrained, providing a surplus of carbon 

for resin synthesis and duct formation (Herms and 

Mattson 1992, Lieutier 2004, Rouault and others 2006). 

Although water stress can reduce overall emissions of 

volatile compounds due to stomatal closure, the relative 

concentrations of some terpenes can change (e.g., 

ethanol, α-pinene and β-pinene), often making trees 

more attractive to bark beetles (Cates and Alexander 

1982, Hodges and Lorio 1975, Kelsey and Joseph 2001, 

Kelsey and others 2014, Kimmerer and Kozlowski 1982).

Bark beetles that feed in phloem can be either positively 

or negatively affected by drought, depending on drought 

intensity, duration, and tree water stress (Jactel and 

others 2012). Positive feedbacks between drought 

and bark beetle outbreaks have occurred in semi-arid 

forests of the Western United States during intense 

drought (fig. 6.2), whereas negative feedbacks are more 

likely in the more mesic forests of the Eastern United 

States that experience milder drought than in the West. 

Although severely water-stressed trees may be more 

attractive to bark beetles and easier to overcome due 

to low defense capability, low levels of carbohydrates 

and nitrogen and reduced moisture content of phloem 

in such trees may negatively affect development of bark 

beetles and their associated fungi. This suggests that 

continuously stressed trees could result in poor bark 

beetle population performance as observed for other 

feeding guilds (Huberty and Denno 2004).

Few studies have experimentally investigated the effect 

of drought on bark beetle performance (Gaylord and 

others 2013); instead most studies have retrospectively 

analyzed the effect of either moisture- or temperatureinduced drought on tree mortality due to bark beetles. 

Empirical associations have been found between 

reduced precipitation in the current year and years 

leading up to outbreaks of mountain pine beetle 

(Dendroctonus ponderosae) (Chapman and others 

2012, Creeden and others 2014, Evangelista and 

others 2011, Thomson and Shrimpton 1984), spruce 

beetle (Dendroctonus rufipennis) (DeRose and Long 

2012, Hart and others 2014, Hebertson and Jenkins 

2008), and pinyon ips (Ips confusus) (Raffa and others 

2008). The role of drought in predisposing pinyon pine 

to pinyon ips attacks has been confirmed by a recent 

experimental manipulation of precipitation (Gaylord and 

others 2013). The effect of drought on tree mortality 

from bark beetles can also vary depending on the lag 

time (Preisler and others 2012), and the duration of 

the outbreak event will depend on the species. For 

example, mountain pine beetle and spruce beetle are 

capable of causing widespread tree mortality for several 

years after drought has ceased when positive feedbacks 

on their populations, due to extensive host abundance, 

concentrated beetle density, optimal symbiotic 

associations, and escape from natural enemies, amplify 

over spatial and temporal scales (Raffa and others 

2008). Conversely, pinyon ips depends more directly on 

stressed trees for successful reproduction, as illustrated 

by a rapid reduction in the population outbreak and tree 

mortality in the Southwestern United States during the 

early 2000s when wetter conditions returned (Raffa

and others 2008) (fig. 6.3). The drought in the early 

2000s that influenced outbreaks of mountain pine 

beetle, spruce beetle, and pinyon ips created conditions 

of severe water stress (Breshears and others 2009, 

Gaylord and others 2007), as it was one of the most 

severe droughts in the past 500 years in many parts 

of the Interior Western United States (Pielke and 

Figure 6.2—The aftermath of a western pine beetle 

(Dendroctonus brevicomis) outbreak. In the early 2000s, the 

mountain ranges of southern California experienced elevated 

levels of tree mortality due to western pine beetle, which many 

experts associated with severe drought (i.e., precipitation was 

the lowest in recorded history during 2001–2002) although 

other predisposing, inciting, and contributing factors were likely 

important. Despite continuing drought and an availability of 

suitable hosts, western pine beetle populations rapidly declined 

in 2004. This outbreak is considered by many to be among 

the largest recorded for this species of bark beetle. (photo 

by Christopher Fettig, U.S. Department of Agriculture, Forest 

Service) 
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others 2005). This drought was also associated with 

warm temperatures that can have a direct positive 

effect on bark beetle population survival and growth 

(Breshears and others 2005). Warm winters can reduce 

cold-induced mortality (Bentz and Mullins 1999, Trân 

and others 2007), and warm summers can reduce 

generation time (Bentz and others 2014, Thatcher and 

Pichard 1967). In general, warm summer temperatures 

positively influence bark beetle population success, 

and drought likely magnifies the effect. The effect 

of drought on bark beetle population growth is not 

straightforward, however, as increased precipitation can 

also have a positive effect on bark beetle population 

growth (Duehl and others 2011, Gumpertz and Pye 

2000, Preisler and others 2012) by providing a more 

nutritious food resource for developing larvae, and by 

reducing tree defense because carbon is preferentially 

allocated to growth as predicted by the GDBH (Herms 

and Mattson 1992, McDowell and others 2011).

Defoliators

Forest defoliators consume, mine, and/or skeletonize 

the foliage of trees. A number of species may cause 

tree mortality depending on the timing, frequency, and 

severity of feeding, and a few are capable of causing 

extensive levels of tree mortality over large areas (e.g., 

eastern spruce budworm, Choristoneura fumiferana). 

While outbreaks of forest defoliators have been linked 

to drought (Mattson and Haack 1987), much of the 

associated evidence supporting this relationship is 

largely circumstantial. There is considerable variation 

in the magnitude and direction of insect responses 

to drought, and this is perhaps best typified among 

defoliators. For example, several studies have shown 

drought increases the performance and impact of 

defoliators while others have shown the opposite (Jactel 

and others 2012). To that end, Jactel and others (2012) 

suggested that the type of trophic substrate impacted 

(e.g., foliage versus wood) may be a more appropriate 

criterion for evaluating the responses of forest insects to 

drought than feeding guild.

Research has focused on the indirect effects of 

drought on defoliators as mediated through changes 

in host tree physiology, primarily leaf chemistry and 

palatability. Due to the inherent difficulties of studying 

the responses of defoliators to drought-stressed 

mature trees in forest environments, much of what is 

known comes from laboratory studies on seedlings. 

These seedling data may or may not be indicative of 

responses to mature trees, and therefore a distinction 

should be made between them. Furthermore, it is 

important to emphasize that responses observed in 

laboratory studies are likely not indicative of responses 

that occur at the population level (Larsson 1989), and 

therefore such extrapolations should be viewed with 

some caution. Consequently, little is known about the 

direct effects of drought on populations and impacts 

of defoliators and their common associates, including 

predators, parasites, and competitors. Some insect 

fungal pathogens important in regulating defoliator 

populations are likely to be negatively impacted by 

drought. For example, Entomophaga maimaiga, which 

causes extensive epizootic outbreak in populations of 

the gypsy moth (Lymantria dispar) in the Eastern United 

States, requires high levels of moisture for conidial 

production and discharge (Hajek 1999). Interestingly, 

drought-stressed plants are consistently warmer than 

unstressed plants because reduced transpiration limits 

plant cooling, with differences as great as 15 °C being 

observed (Mattson and Haack 1987). This has obvious 

implications to populations and impacts of the insects 

colonizing them due to positive responses of many 

insects to increasing temperature.

Many defoliators preferentially feed on leaves with high 

protein and water content, low leaf toughness, and low 

concentrations of secondary metabolites (Dury and 

others 1998). As described earlier, drought often affects 

Figure 6.3—Mortality of pinyon pine (Pinus edulis) due to 

pinyon ips (Ips confusus) associated with intense drought in 

the Southwestern United States. In some areas, tree mortality 

exceeded 90 percent. Populations of pinyon ips rapidly declined 

when wetter conditions returned to the region. (photo by 

Thomas Kolb, Northern Arizona University)

`
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the nutritional quality of foliage by causing changes in 

water, carbohydrate, and nitrogen concentrations. It 

has been well demonstrated that the magnitude and 

direction of responses to drought by defoliators are 

influenced by the severity and duration of drought stress 

(Jactel and others 2012). However, drought stress 

severity should be viewed in the context of the overall 

drought resistance of a given tree species. For example, 

trees that have narrow xylem conduits (gymnosperms) 

can generally maintain physiological function and 

recover from more severe drought than trees that have 

wide xylem conduits (most angiosperms) (Brodribb and 

Cochard 2009). Overall, compromised physiological 

function and reduced productivity often leads to a higher 

vulnerability to insect attack (Bolton 2009).

Nitrogen concentrations often increase in foliage 

during drought stress (White 1969, 1984), which may 

increase the performance of defoliators as nitrogen 

is often a limiting growth factor (Mattson and Haack 

1987). Rouault and others (2006) commented that 

some defoliators benefited from increased nitrogen in 

plant tissues associated with moderate water stress 

during the drought and heat waves that occurred 

in Europe during 2003. For some insects, nutrients 

in unstressed foliage are below levels optimal for 

development and even moderate stress has been 

reported to cause significant changes in the quality of 

foliage that affect defoliator performance (Herms and 

Mattson 1992, Larsson 1989, Larsson and Björkman 

1993, Mattson and Haack 1987, Rouault and others 

2006). Alternatively, Craig and others (1991) found no 

consistent evidence that drought stress led to increased 

performance of sawflies (Neodiprion spp.) in ponderosa 

pine (Pinus ponderosa) trees. Furthermore, they 

reported that performance was better on nonstressed 

trees during some years. In another study, sawfly 

performance was greatest on needles from ponderosa 

pine seedlings exposed to intermittent rather than 

continuous water stress (McMillin and Wagner 1995). 

Severe drought stress is generally recognized as causing 

a deterioration of host tissue quality; however, some 

defoliators may be attracted to chlorotic foliage as 

many insects are attracted to yellow hues (Prokopy and 

Owens 1983).

Drought may negatively impact the performance 

of defoliators through reduced leaf water content, 

which usually increases leaf toughness resulting in 

reduced palatability and lower leaf consumption. For 

example, leaf water content is thought to be one of 

the most important factors influencing the growth of 

autumnal moth (Epirrita autumnata) and winter moth

(Operophtera brumata) in Europe (Henriksson and 

others 2003, Tikkanen and Lyytikäinen-Saarenmaa 

2002). Similarly, Scriber (1977) showed that cecropia 

moth (Hyalophora cecropia) larvae reared on waterstressed leaves of black cherry (Prunus serotina) in the 

laboratory grew more slowly and were less efficient 

at utilizing plant biomass than larvae that fed on leaves 

fully supplemented with water.

Concentrations of secondary metabolites often increase 

in foliage as a result of drought stress, which has 

been shown to negatively impact defoliators. Hale and 

others (2005) demonstrated that concentrations of total 

phenolic glycosides, important secondary defensive 

compounds (Hemming and Lindroth 1995), were lower 

in well-watered black poplar (Populus nigra) seedlings, 

and higher in drought-stressed seedlings despite the 

latter being constrained by a smaller carbon budget. 

In their study, continuous drought stress decreased 

the growth of gypsy moth larvae likely as a result of 

decreased foliar nitrogen and increased total phenolic 

glycoside concentrations, but had no effect on whitemarked tussock moth (Orgyia leucostigma) larvae, which 

is thought to be less sensitive to increases in phenolic 

glycosides than gypsy moth (Kopper and others 2002). 

In another study, Roth and others (1997) investigated 

the effects of carbon dioxide and water availability on 

quaking aspen and sugar maple (Acer saccharum) 

seedlings. Foliar nitrogen levels declined and secondary 

metabolite concentrations increased under enriched 

carbon dioxide, but starch and sugar levels were 

unaffected. All phytochemicals, with the exception of 

simple sugars, declined or did not change in response 

to drought. Carbon dioxide and drought-mediated 

changes reduced performance of forest tent caterpillar 

(Malacosoma disstria) (Roth and others 1997).

In a recent meta-analysis, Jactel and others (2012) 

concluded that primary agents that feed on tree foliage 

inflicted greater damage on drought-stressed trees than 

unstressed trees, but the effect was largely attributed to 

gall-making insects and fungal pathogens. Their metaanalysis included 100 comparisons of forest insects 

and fungi on drought-stressed and unstressed trees 

(based on 40 publications, 1975–2010). Among foliage 

feeders, such notable forest pests as gypsy moth and 

forest tent caterpillar, as well as several sawflies, aphids 

(Aphididae), and leaf pathogens, were included. Results 

for chewing insects on foliage were highly variable 

among 20 studies included in the meta-analysis, and the 

overall effect of drought on foliage damage by chewing 
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insects was positive, but not significantly different from 

zero based on a 95-percent confidence interval.

Sapfeeders

Water stress is hypothesized to positively influence 

phloem sapfeeders, such as aphids and adelgids 

(Adelgidae), through an increase in host tissue 

nitrogen content. Meta-analyses, however, suggest 

that the response is highly variable among studies and 

dependent on the level of stress and resultant turgor 

pressure of the tree (Huberty and Denno 2004, Jactel 

and others 2012, Koricheva and others 1998). Similar 

to other phloem feeders, spruce aphid (Elatobium 

abietnum) performance and population growth was 

greatest when water stress was intermittent and 

was lowest when the stress was continuous (Major 

1990). Under continuous water stress, leaf and phloem 

nitrogen are diminished due to reduced turgor, but 

moderate or periodic stress provides available nitrogen 

during periods of periodic turgor recovery. These results 

suggest that the optimum host would be a plant that 

has experienced long-term intermediate stress, and 

then temporarily released from the stress by abundant 

precipitation during insect feeding (Mopper and 

Whitham 1992). The response of sapfeeders, such as 

the Eastern spruce gall adelgid (Adelges abietis), which 

has both a sucking and galling life stage, can also vary 

with life stage. The sucking stage is often positively 

influenced by drought, while the galling life stage, which 

requires expanding plant tissues for successful gall 

formation, is negatively influenced (Björkman 2000).

Fungal Pathogens

Relatively few studies have directly addressed the 

effects of drought on fungal tree pathogens. However, 

it has been predicted that drought could alter the 

prevalence, severity, and geographic patterns of 

many forest pathogens because forest diseases are 

strongly influenced by environmental conditions, such 

as humidity and temperature (Sturrock and others 

2011). On one hand, drought that increases tree water 

stress and reduces resources available for defense 

could make trees more susceptible to pathogens. On 

the other hand, drought may retard the development, 

survival, reproduction, and dispersal of fungal pathogens 

because many rely on moisture availability to cause 

infection (Klopfenstein and others 2009). Changes 

in moisture availability could directly influence fungal 

pathogen sporulation and infection of host species 

(Sturrock and others 2011). However, it is not clear how 

drought affects pathogen survival, as fungal pathogens 

are highly adaptable and have diverse reproductive 

systems that are designed for coping with changing 

environmental conditions (Olatinwo and others 2013).

Several recent reviews have addressed impacts of 

drought on tree fungal pathogens and have highlighted 

sources of variation in drought response. DesprezLoustau and others (2006) suggested that duration 

of drought is an important predictor of forest disease 

impact on trees as more infections are likely to develop 

during or after prolonged drought. Jactel and others 

(2012) reported that the most important factors for 

determining disease severity under drought conditions 

were pathogen status (primary or secondary), affected 

tree part (foliar versus woody organs), and water stress 

severity. Further, they reported that primary pathogens 

that infect wood and foliage of healthy trees inflict less 

damage on trees during drought (Jactel and others 

2012). Moreover, pathogens whose reproduction, 

spread, infection, and survival are directly tied to the 

availability of moisture have been predicted to be 

negatively impacted by drought (Sturrock and others 

2011). In contrast, drought is expected to increase host 

damage by secondary pathogens that colonize stressed 

trees and woody organs, such as root rot pathogens, 

stem wound colonizers, and latent colonizers of 

sapwood (Desprez-Loustau and others 2006, Jactel and 

others 2012, Sturrock and others 2011).

Needle diseases, which are caused by rust pathogens, 

and diseases caused by Phytophthora species are 

sensitive to precipitation and humidity, as rates of 

reproduction, spread, and infection are greater when 

conditions are moist (Harvell and others 2002). 

Therefore, drought may decrease the incidence and 

severity of these diseases (Thompson and others 2014). 

Rates of infection for many needle pathogens, such 

as Dothistroma septosporum and D. pini that cause 

Dothistroma needle blight of pine, spruce, larch, and 

Douglas fir (Pseudotusga menziesii) (Barnes and others 

2004), and Phaeocryptopus gaeumannii that causes 

Swiss needle cast of Douglas fir, are closely linked to 

temperature and moisture (Hansen and others 2000, 

Stone and others 2008). High levels of moisture were 

particularly critical for infection by D. septrosporum.

This pathogen required 10 or more consecutive hours of 

needle wetness at temperatures ranging from 16 °C to 

20 °C for infection to occur (Bulman 1993). High levels 

of moisture have also been shown to be required for 

infection by P. gaeumannii. High levels of P. gaeumannii

incidence have been positively correlated with winter 

rainfall accumulation and leaf wetness hours (Manter 

and others 2005). Similar to needle and foliar diseases, 
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drought conditions could also decrease the severity of 

stem rust diseases.

It has been suggested that the incidence of rust 

diseases will be affected not only by drought conditions, 

but also by the presence or absence of alternate hosts. 

Many stem rust pathogens, such as fusiform rust 

and white pine blister rust, are unusual as pathogens 

because in addition to the requirement of extended 

periods of free moisture to complete their lifecycles, 

they also require the presence of primary and secondary 

hosts. Drought conditions could alter the geographic 

range of primary and secondary hosts (Olatinwo and 

others 2013). Fusiform rust is a significant pathogen on 

pine, especially in southeastern species. The alternative 

host in the Southeast is primarily water oak (Quercus 

nigra). Fusiform rust would not complete its lifecycle 

if the geographic range of water oak changes during 

future drought and climate change. White pine blister 

rust, caused by Cronartium ribicola, was introduced to 

North America from Asia in the early 1900s. Infection 

causes branch dieback, productive failure, and tree 

mortality (Bega 1978). Environmental requirements for 

disease progression of C. ribicola are well documented. 

Needle infection requires 48 hours of 100 percent 

relative humidity and temperatures less than 20 °C (Van 

Arsdel and others 1956). Drought will likely result in 

less white pine blister rust infection in regions where 

moisture is or becomes a limiting factor to the rust 

(Kinloch 2003).

Phytophthora ramorum, the causal agent of sudden oak 

death, is a serious and devastating pathogen. Recently 

introduced, this pathogen has had a significant impact 

on tanoak (Notholithocarpus densiflorus) and live oak 

(Quercus agrifolia) in California and Oregon forests. 

P. ramorum has been demonstrated to be a high risk 

pathogen to many forests in North America because 

of its ability to infect a wide range of hosts (Dodd 

and others 2008). However, like all Phytophthora 

species, extended periods of rainfall in fall or spring are 

essential to the persistence of P. ramorum. Therefore 

infections by Phytophthora spp. would likely decrease 

during extended drought unless drought is followed by 

periods with extended rainfall (Venette 2009, Weed 

and others 2013).

Root rot pathogens of trees, such as Armillaria spp. and 

Heterobasidion spp., are predicted to become more 

severe and move into new geographic regions during 

drought because these pathogens most successfully 

colonize stressed trees (Olatinwo and others 2013, 

Sturrock and others 2011). Armillaria root rot is a 

global disease caused by both primary and secondary 

pathogens that infect primarily pines and hardwoods 

(Kile and others 1991). Infections cause wood decay, 

overall growth reduction and tree mortality, and increase 

tree susceptibility to colonization by bark beetles or 

other insect pests (Sturrock and others 2011). On 

forested sites under drought conditions causing tree 

stress, Armillaria root rot severity could increase 

significantly and cause widespread tree mortality 

(Klopfenstein and others 2009, La Porta and others 

2008, Shaw and Kile 1991). Similarly, Heterobasidion 

root rot caused by Heterobasidion irregulare and 

H. occidentale, could increase in geographic range 

and incidence during drought (Kliejunas and others 

2009, Otrosina and Garbelotto 2010). Currently in 

the Southeastern United States, Heterobasidion root 

rot causes significant losses on conifers, and it has 

been suggested that with increased drought, growing 

numbers of trees will be impacted by this disease 

(Duerr and Mistretta 2013). In the central western coast 

of Italy, where environmental conditions are becoming 

increasingly hotter and drier, widespread morality of 

Corsican pine (Pinus nigra var. maritime) was caused 

by Heterobasidion root rot (Gonthier and others 2007). 

In these drier conditions, the pathogen appears to be 

increasing its geographic range and incidence.

Several studies have reported increased severity of 

stem canker pathogens during drought because waterstressed trees are less effective at mechanisms of 

canker resistance, such as compartmentalization and 

callusing (Bevercombe and Rayner 1980, McIntyre and 

others 1996). Cankers caused by Septoria musiva on 

poplar (Populus spp.) stems were significantly larger 

on water-stressed trees compared to unstressed trees 

(Desprez-Loustau and others 2006, Maxwell and 

others 1997). Likewise, increased severity of Diplodia 

shoot blight caused by Diplodia sapinea has also been 

associated with water stress of trees in several studies 

(Blodgett and others 1997, Paoletti and others 2001).

Drought and forest pathogens often are implicated 

as causal factors in tree diseases of complex etiology 

or decline diseases (Manion 1981). Decline diseases 

are caused by a multitude of predisposing, inciting, 

and contributing factors including drought and fungal 

pathogens. In a review of aspen decline in North 

America, Worrall and others (2013) concluded that 

recent declines in many regions, including the Western 

United States, were primarily induced by drought, but 

biotic agents, including fungal pathogens, also played 
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a role. Primary pathogenic agents such as sootybark canker; multi-year defoliation by tent caterpillars 

(Malacosoma spp.); and secondary agents such as 

boring insects, fungal cankers, and Armillaria root 

disease have been associated with drought-induced 

aspen mortality in most studies (Worrall and others 

2013). Previous defoliation likely increases aspen 

susceptibility to drought and secondary biotic agents 

via carbon limitation (Anderegg and Callaway 2012). 

Tree-ring studies in the Western United States show 

that chronically low growth rate predisposes aspens 

to die during severe drought (Hanna and Kulakowski 

2012, Ireland and others 2014, Kane and Kolb 2014). 

Data from these studies strongly suggest that stresses 

leading to aspen death accrue over decades and that 

“sudden aspen death” is not due solely to recent severe 

drought. Overall, the role of drought and biotic agents 

in aspen mortality in the Western United States is 

consistent with Manion’s decline disease framework 

(Manion 1981) with drought acting as an inciting factor 

and biotic agents as contributing factors.

Regional and Sub-Regional 

Differences and Interactions

In the West

Bark beetles are the main biotic agent of tree mortality 

in the Western United States. Multiple large outbreaks 

have killed hundreds of millions of trees in recent 

decades (Meddens and others 2012). Aggressive 

bark beetle species such as mountain pine beetle and 

spruce beetle are able to kill healthy trees when beetle 

populations are large, and climate plays an important 

role in driving epidemics of these beetles through 

effects on the insects and on host trees (Bentz and 

others 2010, Raffa and others 2008). Drought provides 

an increased source of susceptible host trees, which 

allows beetle populations to build. Temperature-induced 

drought in the 1990s in Alaska and moisture-induced 

drought in the early 2000s in the Western conterminous 

United States have been linked to bark beetle outbreaks 

(Berg and others 2006, Chapman and others 2012, 

Creeden and others 2014, Hart and others 2014, Shaw 

and others 2005). Others have also found a relationship 

between drought and historic spruce beetle outbreaks 

(DeRose and Long 2012, Hebertson and Jenkins 2008, 

Sherriff and others 2011). However, when drought 

is relieved, epidemics of some species, including 

mountain pine beetle and spruce beetle, can continue 

due to positive feedbacks that allow high numbers of 

beetles to overwhelm the defenses of trees, despite 

their recovery from drought stress (Creeden and others 

2014, Raffa and others 2008). The northward range 

expansion of mountain pine beetle into the Canadian 

boreal forest and the extensive outbreaks in highelevation five-needle pines of the Western United 

States have been attributed to warming (Carroll and 

others 2004, Logan and others 2010). Drought may 

have played a role in initiating these outbreaks and 

facilitating population increase to levels that killed 

healthy trees, but warming was the primary reason for 

these epidemics occurring in historically unknown or 

rare locations.

In contrast to aggressive beetle species, successful 

attacks of less aggressive bark beetles in the Western 

United States are limited to stressed hosts, and as such 

outbreaks are closely tied to drought and associated 

warm temperatures. The pinyon pine (Pinus edulis and 

P. monophylla) mortality caused by severe drought 

and pinyon ips is an excellent example. In the early 

2000s, a “global-change-type drought” occurred in the 

Southwest in which extremely dry conditions occurred 

during a period of time when conditions were already 

warmer than in the past (Breshears and others 2005). 

Ips populations increased in conjunction with the 

drought and warm temperatures, and together with 

extreme tree physiological stress, caused mortality in 

millions of hectares of pinyon pine stands (Breshears 

and others 2005, Meddens and others 2012, Raffa and 

others 2008). When wetter conditions returned after 

several years, Ips populations declined (Raffa and others 

2008). Ips lack the positive feedback mechanisms that 

allow for increased population growth with increased 

beetle numbers. Outbreaks of other bark beetle 

species, such as Douglas-fir beetle (Dendroctonus 

pseudotsugae), western balsam bark beetle 

(Dryocoetes confusus), fir engraver (Scolytus ventralis), 

and pine engraver (Ips pini), also caused extensive 

tree mortality in the early 2000s (Meddens and others 

2012), although the role of drought is less clear.

The role of drought in the Western United States in 

influencing outbreaks of another class of insects—

defoliators—is less understood. The primary defoliating 

insect of the West is western spruce budworm, 

which attacks multiple conifer species and periodically 

erupts, causing widespread tree damage and death. 

Budworm outbreaks have been linked to drought 

conditions that cause tree stress or are related to the 

important synchrony of caterpillar development and 

foliage phenology (Campbell and others 2006, Thomson 

and others 1984, Williams and Liebhold 1995a), 

although other studies have found that outbreaks 
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were associated with wetter conditions at the end of 

droughts that increase food resources (Flower and 

others 2014, Ryerson and others 2003, Swetnam 

and Lynch 1993). Multiple drought influences may be 

important, and they may vary regionally (Lynch 2012). 

For many defoliators, either drought is not important or 

its influence is unknown (Jactel and others 2012).

Pathogens are also important forest disturbance agents 

in the Western United States. As described earlier, 

some forest pathogens important in the West, such as 

those causing Phytophthora root rot, sudden oak death, 

Dothistroma needle blight, Swiss needle cast, and 

white pine blister rust, prefer moist conditions, thereby 

suggesting that drought plays a limiting role in these 

outbreaks (Jactel and others 2012, Sturrock and others 

2011). Other fungal pathogens, such as those causing 

Armillaria root disease or various cankers, are indirectly 

affected by drought through increasing stress of host 

trees, implying that drought leads to more favorable 

conditions for outbreaks (Jactel and others 2012, 

Klopfenstein and others 2009, Sturrock and others 2011).

In the East

The role of drought in insect and fungal pathogen 

outbreaks is less clear in mesic forests of the Eastern 

United States than in the more arid regions of the 

Western United States, where drought has been 

linked to outbreaks of certain insects and diseases. 

The generally mild droughts of the Eastern United 

States (i.e., compared to portions of the Western 

United States) can increase the concentration of plant 

secondary metabolites that are important for resisting 

pathogens and insects (Hale and others 2005, Herms 

and Mattson 1992, Lombardero and others 2000).

Hardwood forests—Water stress of broad-leaved 

hardwood trees generally decreases water content 

and increases concentrations of soluble nitrogen and 

secondary metabolites in plant tissues, but these 

physiological changes may have positive, negative, or 

neutral effects on insect growth and fitness depending 

on the species (Hale and others 2005, Huberty and 

Denno 2004, Mattson and Haack 1987, Scriber 1977). 

For example, experimental water stress of black 

poplar led to reduced concentrations of total phenolic 

glycosides and reduced feeding performance of gypsy 

moth, but not white-marked tussock moth (Hale and 

others 2005). Chakraborty and others (2013) found 

no effects of drought in either of two ash species 

on constitutive or induced phenolics in the phloem. 

Roth and others (1997) reported a rare case of 

drought-induced reductions in defensive compounds in 

quaking aspen.

In the East, aspen and poplar, maple, oak, hickory, 

beech, ash, and birch are all widely distributed, 

important components of mixed-hardwood forests. 

These forests are periodically subjected to outbreaks 

from forest tent caterpillar, gypsy moth, winter moth, 

and other defoliators, and significant effects on forest 

composition and structure are expected with the 

arrivals of the nonnative emerald ash borer (Agrilus 

planipennis), thousand cankers disease, and laurel 

wilt into the region. The impacts of these hardwood 

pests seem largely unrelated to drought (Olatinwo and 

others 2013, Weed and others 2013). One exception 

could be the recent epidemic of red oak mortality in 

the Ozark Mountains (Jones and others 2014) that has 

been associated with drought and the wood-boring 

beetle, Enaphalodes rufulus (Haavik and Stephen 2010). 

However, even this case is not simple to interpret due 

to potentially confounding influences of forest age, 

structure, and Armillaria root rot (Wang and others 

2007).

Conifer forests—Insects and pathogens are also 

continuous threats to the health of conifer forests 

in the Eastern United States. The southern pine 

beetle (Dendroctonus frontalis) is the most important 

disturbance agent of southern pine ecosystems; white 

pine blister rust is a perennial stress on eastern white 

pine (Pinus strobus); invasive adelgids threaten the 

persistence of mature hemlock and Fraser fir (Abies 

fraseri) stands across the mid-Atlantic; and eastern 

spruce budworm outbreaks periodically disturb the 

eastern boreal forest. Early hypotheses suggested that 

water stress would improve host quality to herbivores 

by favoring the balance of nutrients that are important 

for insect growth (Mattson and Haack 1987. However, 

oleoresin is the primary mechanism in conifers 

conferring resistance to herbivores and especially bark 

beetles (Raffa and Berryman 1983), and oleoresin flow 

and its chemical composition are key determinants of 

bark beetle success (Lombardero and others 2000, 

Lorio 1986, Raffa and others 2005). There is a pervasive 

suggestion in the scientific literature and among forest 

health managers that drought stress compromises tree 

defenses to a point where outbreaks of aggressive 

species such as southern pine beetle are permitted, 

but the growing, albeit small body of scientific evidence 

indicates that constitutive resin defenses actually 

increase at the moderate levels of drought stress that 

occur in the Eastern United States (Dunn and Lorio 
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1993, Lombardero and others 2000, Lorio and others 

1995, Reeve and others 1995).

Resin flow in loblolly pine (Pinus taeda), the most 

abundant pine of the Southeastern United States, 

increases significantly under conditions of moderate 

water deficit (Dunn and Lorio 1993, Lombardero and 

others 2000, Reeve and others 1995), and does not 

decrease until drought is extreme (Lorio and others 

1995). This matches expectations derived from the 

GDBH, which we describe in earlier sections (Lorio 

1986, Lorio and others 1982). Resin flow of loblolly 

pine tends to be highest during seasonal periods of 

suboptimal growth, such as under moderate water 

stress (Lombardero and others 2000). Studies of 

conifers from other regions also show that moderate 

drought can increase some tree defensives. For 

example, foliar tannins, another class of important 

phenolic anti-herbivore defenses, had a nonlinear 

response to soil water deficits with greatest 

concentrations in Douglas-fir needles occurring at 

moderate water stress (Horner 1990). In Europe, 

drought stress generally increased the concentrations 

of several individual monoterpenes and resin acids in 

the woody tissues and needles of Scots pine (Pinus 

sylvestris) and Norway spruce (Picea abies) (Turtola and 

others 2003).

The hypothesis that drought triggers outbreaks of 

southern pine beetle has been under investigation for 

nearly a century (Dunn and Lorio 1993, Hodges and 

Lorio 1975, Lorio 1986, Lorio and others 1995, McNulty 

and others 1997, Reeve and others 1995, St. George 

1930, Turchin and others 1991). However, drought tends 

to increase defenses of southern pines rather than 

decrease them (above). Furthermore, analyses of time 

series data have failed to reveal the expected relations 

between drought and southern pine beetle fluctuations 

(McNulty and others 1997, Turchin and others 1991); 

if anything, southern pine beetle outbreaks have been 

positively correlated with rainfall (Duehl and others 2011, 

Gumpertz and Pye 2000). This correlation is consistent 

with a broad pattern in which the secondary colonizers 

of dying trees benefit from drought, rather than the 

aggressive tree-killing species such as southern pine 

beetle (Jactel and others 2012). Diverse evidence 

argues against the hypothesis that southern pine beetle 

outbreaks are promoted by drought (fig. 6.4).

Figure 6.4—A local infestation (“spot”) of southern pine beetle (Dendroctonus frontalis) in east Texas. 

In the Eastern United States, southern pine beetles are a dominant source of disturbance in pine forests 

from New Jersey to Texas. Epidemics are believed to be unrelated to drought, but instead are most 

prevalent in pine forests that are fast growing, unthinned, and overstocked. (photo by Ronald Billings, 

Texas A&M Forest Service)
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Similar to hardwood species in the Eastern United 

States, we lack strong evidence that sustained 

population outbreaks of insects and pathogens on 

eastern conifers are triggered by water stress or 

drought. Whereas water stress and drought are often 

cited as a predisposing factor to pest and pathogen 

outbreaks (Edmonds and others 2000), evidence 

for a strong role of drought on insect and pathogen 

outbreaks in forests of the Eastern United States is 

not yet convincing. The few examples of positive 

correlations between spatial and temporal outbreak 

patterns of insects and pathogens in the Eastern United 

States (Haavik and Stephen 2010) may be spurious 

or associated with other mechanisms. One such 

mechanism could be the powerful effects of warming 

temperatures on developmental rates and fitness of 

insects and pathogens that together with reduced 

precipitation create drought-like conditions (Weed and 

others 2013).

Anticipating Impacts: 

Predictions of Future 

Drought-Related Insect 

and Disease Impacts

In the West

Future anthropogenic-induced changes to the Earth’s 

climate are likely to include increases in temperature 

and significant changes in precipitation patterns. Across 

the Western United States, temperature increases are 

projected to exceed global mean increases and more 

frequent extreme weather events, such as droughts, 

are expected (Levinson and Fettig 2014). Winter 

precipitation is projected to increase in some areas, but 

to decrease by up to 20 percent in the Southwestern 

United States by the 2050s. Summer precipitation is 

projected to decrease by 10−30 percent throughout 

the West by the 2050s (Fettig and others 2013). 

Observed increases in temperature have been greater 

in winter and spring than in summer (IPCC 2007, 

Melillo and others 2014). Warming during winter will 

further exacerbate recent declines in snowpack. As 

such, many forests in the Western United States will 

experience further increases in drought stress whether 

associated with reductions in precipitation or increases 

in evaporative demand associated with elevated 

temperature. Williams and others (2013) reported that 

if the vapor-pressure deficit continues increasing in the 

Southwestern United States, as projected by climate 

models, by the 2050s mean forest drought stress will 

exceed that of the most severe droughts in the past 

1,000 years.

As might be expected, an increase in the frequency 

and severity of some biotic disturbances is expected as 

a result of more intense drought stress and increasing 

temperature (Allen and others 2010, Bentz and others 

2010, Fettig and others 2013, Sturrock and others 2011, 

Weed and others 2013). However, our understanding 

of these relationships in the Western United States 

is largely limited to select insects in conifer forests. 

Among insects, range expansions and increases in 

the frequency and severity of outbreaks by some bark 

beetle species have already been documented (Bentz 

and others 2009), and further changes are anticipated 

(Bentz and others 2010, Fettig and others 2013, 

Sambaraju and others 2012, Sturrock and others 2011, 

Williams and Liebhold 2002). It is thought that increasing 

temperatures and drought stress, exacerbated by high 

densities of suitable and susceptible hosts (Fettig and 

others 2007, Hicke and Jenkins 2008), have contributed 

to the positive feedbacks necessary for these range 

expansions and epidemic populations to occur (Raffa 

and others 2008). For example, Preisler and others 

(2012) reported that in addition to beetle pressure, 

climate variables with the largest effect on the odds of 

a mountain pine beetle outbreak exceeding a certain 

size in Oregon and Washington were minimum winter 

temperature and drought in the current and previous 

year. Precipitation levels the year prior to an outbreak had 

a positive effect on outbreak size, perhaps because of 

the positive influence of precipitation on the production 

of phloem, which is where larvae feed. While increases 

in the impact of several bark beetle species are expected 

with future climate change (Bentz and others 2010), it is 

important to note that significant areas of the Western 

United States have already suffered high levels of tree 

mortality due to bark beetles (Meddens and others 

2012), and susceptible hosts may be currently depleted 

in these areas, which will dampen future outbreaks for 

decades.

Our understanding of the anticipated impacts of 

defoliators on drought-stressed forests in the Western 

United States is limited. This partially results from 

inconsistencies in the direction and magnitude of their 

responses to drought (see earlier), and because bark 

beetle outbreaks and wildfire have overshadowed 

the impacts of defoliators as primary disturbances 

associated with drought-stressed forests in the West, 

particularly in recent decades. Williams and Liebhold 

(1995a, 1995b) investigated potential changes in 

spatial distribution of outbreaks of western spruce 

budworm (fig. 6.5) in eastern Oregon under several 

climatic change scenarios. With an increase of 2 °C, the 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

projected defoliated area decreased relative to ambient 

conditions, as was projected when temperature was 

increased and precipitation decreased. However, 

with an increase in temperature and precipitation, the 

defoliated area was projected to increase. Despite 

this, considerable uncertainty remains about the future 

impacts of defoliators to drought-stressed forests in the 

Western United States (Weed and others 2013).

Outbreaks of forest diseases caused by native and 

introduced pathogens are generally thought to become 

more frequent and severe as a result of climate change 

(Sturrock and others 2011). However, diseases caused 

by pathogens directly affected by climate (e.g., needle 

blights) are projected to have reduced impacts under 

warmer and drier conditions. These groups of pathogens 

may cause disease in healthy hosts if the pathogen’s 

environmental requirements are met, many of which 

require moist conditions (Sturrock and others 2011).

In the East

In the Eastern United States, effects of drought on biotic 

disturbance in forests are anticipated to be modest 

relative to effects from warming and introductions of 

nonnative insects and pathogens (Duehl and others 

2011, Olatinwo and others 2013, Weed and others 

2013). In the Northeastern United States, droughts 

have been historically rare and are projected to remain 

low in intensity through this century (Hayhoe and 

others 2007). Since projections of future changes in 

precipitation for the Eastern United States are generally 

flat (Ryan and Vose 2012), the eastern forests that are 

most likely to experience drought in the future are those 

already subject to occasional droughts (e.g., forests 

near the edge of the Great Plains). Forests with red 

oak may be at greater risk because drought can permit 

increased mortality from wood-boring beetles (Haavik 

and Stephen 2010) and Armillaria species (Clinton and 

others 1993). Impacts on ash from the emerald ash 

borer could be exacerbated by drought (Chakraborty and 

others 2013). There may be a tendency for drought to 

increase the susceptibility of hardwood trees to woodboring beetles (Dunn and others 1990, Muilenburg and 

Herms 2012). Fortunately, the extensive and productive 

pine forests of the Southeastern United States do not 

seem dangerously vulnerable to drought-triggered 

outbreaks of tree-killing bark beetles (Duehl and others 

2011, Duerr and Mistretta 2013, McNulty and others 

1997, Weed and others 2013).

Summary and Research 

Needs for Insects 

and Pathogens

Bark Beetles

Our review of impacts of drought on bark beetle 

performance and tree mortality in U.S. forests is 

consistent with predictions of plant carbon allocation 

models (Herms and Mattson 1992, McDowell and 

others 2011) that suggest moderate drought/tree water 

stress can reduce bark beetle population performance 

and subsequent tree mortality, whereas intense 

drought increases bark beetle performance and tree 

mortality (fig. 6.6). Figure 6.6 provides a framework for 

understanding the apparent difference in the effect of 

drought on bark beetle performance and tree damage 

between eastern and western forests.

Most eastern forests have considerably higher 

precipitation and less severe drought than western 

forests, especially compared to forests east of the 

Sierra Nevada and Cascade Mountain crests and west 

of the Great Plains. Current evidence strongly suggests 

that the relatively moderate droughts that occur in 

eastern conifer forests do not increase performance 

and tree mortality from native bark beetles, but instead 

may reduce performance and impact. Because western 

arid forests are more water-limited than eastern mesic 

forests and at times experience more severe drought, 

insect-caused tree mortality has been more often 

Figure 6.5—Western spruce budworm (Choristoneura 

occidentalis) defoliation. Some experts suggest that defoliation 

due to western spruce budworm will decline in the future due to 

increasing drought. However, there is considerable uncertainty 

about the role of drought on the performance of defoliators and 

their influence on drought-stressed forests in the United States. 

(photo by Lia Spiegel, U.S. Department of Agriculture, Forest 

Service)
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

correlated with severe drought in the Western United 

States. The “global-change-type drought” that occurred 

in the Southwestern United States in the early 2000s 

(Breshears and others 2005) is an excellent example 

and provided an opportunity to examine the role of 

drought and temperature in bark beetle outbreak 

potential. We suggest that future research on the role of 

drought in bark beetle outbreaks should focus on:

lthe relative role of temperature in drought-induced 

outbreaks of bark beetles;

lidentification of species which are capable of selfperpetuating outbreaks after drought subsides;

lthe level of drought-associated tree mortality that 

would occur without bark beetle attacks;

lthe effectiveness of manipulating forest composition 

and structure to reduce drought stress and bark beetle 

attacks in semi-arid forests; and

lthe level of drought intensity in pine forests of the 

Eastern United States that would shift the role of 

drought in beetle outbreaks from a negative to a 

positive driver (fig. 6.6).

Defoliators

In contrast to bark beetles, our review found 

inconsistent impacts of drought on defoliator 

performance and tree damage. Whereas individual 

studies have reported both positive and negative 

impacts of drought on defoliator performance and 

damage, cumulative results over many studies are 

too variable to allow generalization of drought impacts 

on this insect guild. While substantial inconsistency 

and uncertainty exist in the response of defoliators to 

drought, it is clear from climate-change projections 

(Melillo and others 2014, Ryan and Vose 2012) that 

forest defoliators will increasingly interact with droughtstressed hosts. As such, we underscore the need for 

a greater understanding of the impacts of drought on 

defoliators.

Sapfeeders

The collective response of tree sapfeeders to drought 

is nonlinear based on available evidence (fig. 6.7). 

Sapfeeders typically have the highest performance 

and cause the most tree damage at moderate drought 

intensity, and when periods of intense drought are 

interrupted by precipitation, resulting in plant tissues 

enriched with nitrogen and with high turgor.

Fungal Pathogens

Our review highlights a complex response of tree 

fungal pathogens to drought (fig. 6.8). The overall 

consensus of our review and others is that some forest 

pathogens will become less severe during drought 

whereas some diseases will become more severe 

(Desprez-Loustau and others 2006, Jactel and others 

2012, Klopfenstein and others 2009, Sturrock and 

others 2011). Specifically, available evidence suggests 

that drought reduces performance and damage by 

primary pathogens that infect healthy trees and foliage, 

Low High 

Drought intensity 

Low 

High 

Bark beetles 

Insect performance/tree damage 

Figure 6.6—Nonlinear response trend of bark beetle 

performance and tree damage to drought intensity based on our 

literature review and tree carbon allocation frameworks.

Figure 6.7—Nonlinear response trend of sapfeeder performance 

and tree damage to drought intensity for U.S. forests based on 

our literature review. 

Low High 

Drought intensity 

Insect performance/tree damage 

Low 

High 

Sapfeeders
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

such as rusts (Phytophtora and Dothistroma) and 

pathogens whose performance is directly tied to high 

availability of moisture. In contrast, drought typically 

increases performance and damage by secondary 

pathogens that colonize stressed trees and woody 

organs, such as stem cankers, root rots, and Armillaria. 

The response trends in figure 6.8, however, are based 

on knowledge about the role of available water on 

fungal performance and spread, and a few empirical 

studies of impacts of drought or tree water stress on 

pathogen performance and damage. There is a strong 

need for empirical data and predictive tools on how 

changes in drought frequency and severity will alter 

forest fungal pathogens. Future research using these 

data to model and predict forest disease incidents for 

forest ecosystems under different drought conditions 

would be useful for management (Klopfenstein and 

others 2009), as it will give forest managers additional 

foresight into potential outbreak conditions of the future.

Conclusions

It is clear that drought and associated temperature 

changes can significantly influence outbreaks of forest 

insects and pathogens, both positively and negatively, 

and that both drought and temperature are projected 

to increase in many parts of the United States in future 

years. In this review, we highlight specific research on 

insect and pathogens that is needed to better predict 

future climate-related impacts to forest ecosystems 

across the United States. Because eastern forests are 

generally less limited by water availability than western 

forests, less is known about the potential for drought 

impacts on insects and their role in tree mortality in 

eastern forests. Climate-change projections, however, 

strongly suggest an increase in temperature in eastern 

forests, which will intensify drought even if precipitation 

does not change (Ryan and Vose 2012). Interactions 

between drought and biotic disturbances are crucial 

in determining continental-scale forest productivity, 

ecotones between forests and shrubland or grasslands, 

carbon balance, and many other forest ecosystem 

services. Emerging and new knowledge of the role of 

drought and associated temperature changes in forest 

insect and pathogen-caused tree mortality will be 

essential components of models and frameworks for 

future forest management planning.

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`

CHAPTER 7 CHAPTER 7

J.S. Littell is a Research Ecologist, U.S. Geological Survey (USGS), U.S. Department 

of the Interior, Alaska Climate Science Center, Anchorage, AK 99508.

D.L. Peterson is a Research Biologist, U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station (PNW), Pacific Wildland Fire Sciences Lab, Seattle, 

WA 98103.

K.L. Riley is a Research Geoscientist, University of Montana, Numerical Terradynamic 

Simulation Group, Missoula, MT 59808.

Y.-Q. Liu is a Research Meteorologist, U.S. Department of Agriculture, Forest 

Service, Southern Research Station (SRS), Center for Forest Disturbance Science, 

Athens, GA 30602.

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID 83702.

Fire and Drought

Jeremy S. Littell

David L. Peterson

Karin L. Riley

Yongqiang Liu

Charles H. Luce
136

CHAPTER 7

Fire and Drought

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction and 

Historical Perspective

Historical and presettlement relationships between 

drought and wildfire have been well documented in 

much of North America, with forest fire occurrence 

and area burned clearly increasing in response to 

drought. Drought interacts with other controls (forest 

productivity, topography, and fire weather) to affect fire 

intensity and severity. Fire regime characteristics (area, 

frequency, severity) are the product of many individual 

fires, so both weather and climate—including short- and 

long-term droughts—are important. It is worth noting, 

however, that the factors controlling fire events and 

fire regimes are complex and extend beyond drought 

and climate alone, and so fire regimes and wildfires are 

affected by other variables from local-to-global scales. 

Fire history evidence from diverse climate regimes and 

forest ecosystems suggests that North American forest 

fire regimes were moderately to strongly controlled 

by climate prior to Euro-American settlement and 

subsequent fire exclusion and fire suppression (Flatley 

and others 2013, Hessl and others 2004, Heyerdahl 

and others 2002, Heyerdahl and others 2008, Swetnam 

1990, Swetnam and Betancourt 1998, Weisberg and 

Swanson 2003). These presettlement fire histories 

indicate a relationship between low precipitation 

anomalies and widespread fire activity, especially in 

the Western United States. This is consistent with a 

regional depletion of soil and atmospheric moisture, 

which leads to low moisture in foliage and surface 

fuels and ultimately to the potential for widespread fire 

(Swetnam and Betancourt 1998). Some fire histories 

in the American Southwest also demonstrate a lagged 

relationship with above-average antecedent precipitation 

(Swetnam and Betancourt 1998) and/or cooler 

temperatures (Veblen and others 2000) in the year(s) 

prior to years of widespread fire. Most of these records 

are derived from fire-scarred trees that survived fire 

events and thus are primarily indicative of low- or mixedseverity fire regimes, although some work has focused 

also on evidence from high-severity fire regimes 

(Heyerdahl and others 2002).

In the mid- to late-20th century, relationships between 

area burned and climate parallel those in the fire history 

record. From 1980 forward, area burned on Federal 

lands was related to monthly Palmer Drought Severity 

Index (PDSI), and the sign and magnitude of the 

relationships were consistent with reconstructed fire 

histories (Westerling and others 2003). Littell and others 

(2009) documented ecologically and geographically 

variable responses of area burned to year-of-fire climate, 

with area burned increasing with increased temperature, 

decreased precipitation, or anomalously low (negative) 

PDSI in most forests and in some nonforest vegetation. 

Area burned in nonforested systems is associated 

with drought, but in some fuel conditions and regions, 

stronger relationships exist between anomalously high

antecedent precipitation (or positive PDSI) and area 

burned (Littell and others 2009). This body of evidence 

indicates that the role of drought in historical, and 

likely future, fire regimes is an important contingency 

that creates anomalously high potential for ignition, 

fire spread, and large fire events. However, drought 

is only one aspect of a broader set of controls on fire 

regimes, and by itself is insufficient to predict fire 

dynamics or effects. Whereas the relationships between 

fire occurrence or area burned and drought are well 

documented, the relationship between drought and fire 

severity is still emerging. Clear relationships between 

years with extensive fires and the proportion of area 

with high severity do not exist (Dillon and others 2011, 

Holden and others 2012); however, the years with more 

widespread fires show substantially less landscape and 

topographic controls on severity (Dillon and others 2011). 

For example, north-facing slopes might offer some 

degree of local protection during mild droughts, but even 

they become dry under extreme conditions, reducing 

fine-scale heterogeneity in vegetation consequences.

The conditions that affect fires after ignition, from initial 

spread to eventual extinguishment, exert the strongest 

control over fire behavior (Rothermel 1972) and thus the 

ultimate outcomes in terms of area burned and severity. 

Drought influences the likelihood of ignition and 

availability of fuels at multiple time scales, and shorterterm weather affects fuel moisture and propagation, but 

intensity and severity are also determined by other more 

local factors that interact with drought.

At long time scales (seasons to centuries or longer), 

moisture availability and drought affect fuel availability 

via controls on ecosystem characteristics and 

productivity, and at short time scales (seasons to years) 

via controls on fuel structure and flammability (Loehman 

and others 2014). Climate, therefore, acts to facilitate 

fire by both producing fuels through vegetation growth 

and making those fuels flammable. The paleoecological 

record indicates that on time scales of centuries to 

millennia, the tension between climatic controls on fuel 

availability and fuel flammability manifests as the fire 

regime, with fire responding to the limits of available 

fuels (vegetation) and vegetation responding to the 
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frequency, severity, and extent of fire resulting from 

changes in flammability (Prichard and others 2009, 

Whitlock and others 2010).

Climate exerts a strong control over fire, but other factors 

that affect fuel abundance, frequency of flammability, and 

propensity for ignition can affect fire regimes. Human 

management of landscapes and fuels, suppression of 

fire, and use of fire all exert control in tandem with the 

effects of climate (Moritz and others 2005). Collectively, 

the fire regime and how it changes through time are 

a function of fuels and how other factors affect their 

availability and flammability. Climate, management, and 

land use affect availability, flammability, continuity of 

fuels, and probability of ignition differently in different 

parts of the World. At the scale of seasons to decades, 

drought directly affects flammability and thus the 

frequency of conditions conducive to large fires and 

possibly the severity of those fires. At the scale of years 

to millennia, drought directly affects the distribution 

and abundance of vegetation and indirectly affects 

disturbances including fire.

Characterizing Drought: 

Metrics of Fire Risk

Which Drought Metrics Relate to Fire Risk?

Drought is not a necessary or sufficient condition for 

fire, because fires burn during conditions of normal 

seasonal aridity (e.g., dry summers that occur annually 

in California), and drought occurs without wildfires in the 

absence of ignitions. However, when drought occurs, 

both live and dead fuels can dry out and become more 

flammable, and probability of ignition increases along 

with rate of fire spread (Andrews and others 2003, 

Scott and Burgan 2005). If drought continues for a long 

period, the number of days with elevated probability 

of ignition and fire spread increases, raising the risk of 

widespread burning. Long droughts are not necessary 

to increase risk of large wildfires; anomalous aridity of 

30 days or more is sufficient to dry fuels substantially 

in all size classes (Cohen and Deeming 1985, Riley and 

others 2013) as well as live fuels. Drought can therefore 

be defined in meteorological terms, or in relative terms 

with respect to hydrology or ecosystems (chapter 2).

Because drought influences fire both directly via fuel 

moisture and indirectly through biological and ecological 

effects on vegetation, fire risk can be quantified by both 

drought indices and fire behavior metrics. Interpretation 

of these metrics is complicated by the fact that not all 

vegetation types respond the same to meteorological 

drought in terms of fuel availability and flammability, 

but the probability of ignition increases in most fuels 

when fuel moisture is low. Although fuels are capable 

of burning under different conditions in different 

ecosystems, even short-term drought generally increases 

wildfire risk through its effects on fuel moisture, and thus 

on probability of ignition and spread rate.

Palmer Drought Severity Index—Palmer Drought 

Severity Index (PDSI) (Palmer 1965) is commonly 

used in fire occurrence research in the United States 

(Balling and others 1992, Collins and others 2006, Littell 

and others 2009, Miller and others 2012, Westerling 

and others 2003). PDSI was designed to capture 

agricultural drought, using a water-balance method 

to add precipitation to the top two layers of soil, and 

a temperature-driven evapotranspiration algorithm to 

remove moisture (Thornthwaite 1948). PDSI assumes 

all precipitation falls as rain rather than snow, making 

its application less reliable where snow comprises a 

significant proportion of annual precipitation. Because 

the algorithm does not include some of the important 

drivers of evapotranspiration (relative humidity, solar 

radiation, wind speed), its correlation with soil moisture 

is weak (r = 0.5–0.7; Dai and others 2004). Correlation 

between PDSI and soil moisture peaks during late 

summer and autumn, corresponding with fire season in 

much of the Western United States. PDSI does not have 

an inherent time scale, but its “memory” varies from 2 

to 9 months depending on location (Guttman 1998).

During the past century, PDSI is weakly to moderately 

associated with fire occurrence in many parts of the 

Western United States. In Yellowstone National Park 

(Wyoming, MT), year-of-fire summer PDSI calculated 

for two adjacent climate divisions had a Spearman’s 

rank correlation of -0.55 to -0.60 (1895–1990), with 

the correlation decreasing to -0.23 to -0.27 during the 

previous winter and -0.2 for the previous year (Balling 

and others 1992). Regional PDSIs for groups of Western 

States using the average of the PDSI value for each 

State were r2 = 0.27–0.43 (1926–2002) for current 

year PDSI and area burned (Collins and others 2006). 

Including the PDSI from the two antecedent years 

increased correlations with area burned to r2 = 0.44–

0.67, indicating that multi-year droughts may increase 

fire occurrence.

PDSI was a significant predictor, along with precipitation 

and sometimes temperature, in modeling area burned 

in 12 of 16 ecoregions in the Western United States for 

the period 1916–2003 (Littell and others 2009). During 
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the period 1910–1959, summer PDSI explained 37 

percent of area burned and number of fires in national 

forests of northwestern California. However, during the 

later period of 1987–2008, total summer precipitation 

was a significant predictor, not PDSI (Miller and others 

2012). Among an array of possible drought indices, PDSI 

values from the previous October showed the strongest 

correlation with nonforested area burned in the western 

Great Basin (r2=0.54 for 1984–2010), indicating that 

wet conditions during the previous autumn predicted 

area burned during the next fire season. The index 

did not perform well in other regions (Abatzoglou and 

Kolden 2013).

Precipitation totals (monthly, seasonal)—

Precipitation totals and anomalies are a measure of 

meteorological drought. In addition to the study by 

Miller and others (2012) referenced earlier, monthly 

and seasonal precipitation anomalies have been used 

in several studies relating drought to fire occurrence 

(Balling and others 1992, Littell and others 2009, 

Morgan and others 2008). Littell and others (2009) 

further demonstrated that seasonal precipitation was 

a significant factor in multivariate models predicting 

area burned in most ecoregions in the Western 

United States. However, the magnitude and sign of 

the precipitation term varied; in mountain and forest 

ecoregions, summer precipitation was generally 

negatively correlated with area, but in nonforested 

ecoregions, antecedent (usually winter) precipitation 

was positively correlated with area burned.

In Yellowstone National Park, total annual precipitation 

had a Spearman’s rank correlation of -0.52 to -0.54 with 

area burned, which was a stronger correlation than was 

demonstrated in the same study using PDSI (Balling and 

others 1992). Summer precipitation had the strongest 

relationship among drought indices with area burned in 

nonforested areas of the Pacific Northwest (r2=0.48) 

and eastern Great Basin (r2=0.31; Abatzoglou and 

Kolden 2013).

Standardized Precipitation Index—The Standardized 

Precipitation Index (SPI) is a measure of meteorological 

drought, calculated as the difference of precipitation 

from the mean for a specified time period divided 

by the standard deviation (McKee and others 1993). 

Because the distribution of precipitation amounts is 

generally right-skewed (Riley and others 2013), it must 

be normalized before this equation is applied (LloydHughes and Saunders 2002). One can calculate SPI for 

any time period, typically ranging from 1 to 24 months. 

Because SPI is normalized, one can use it to estimate 

probability of a drought of a certain severity, and the 

index has a similar meaning across ecosystems (e.g., 

a value of -1 means that precipitation is one standard 

deviation below normal). Riley and others (2013) 

found that 3-month SPI explained 70 percent of the 

variability in area burned and 83 percent of variability 

in number of large fires in the Western United States. 

With increasing time intervals for calculating SPI, 

correlations decreased until 24-month SPI explained 

essentially none of the variability. Fernandes and 

others (2011) also found strong correlations between 

3-month SPI and anomalies in fire incidence in the 

western Amazon.

Energy Release Component—Energy Release 

Component (ERC) is a fire danger metric used in the 

National Fire Danger Rating System for the United 

States and a proxy for fuel moisture or amount of 

fuel available to burn. The calculation of ERC is based 

on recent weather (temperature, solar radiation, 

precipitation duration, and relative humidity). ERC can 

be calculated for different fuel conditions, but is most 

commonly used to estimate fire occurrence for larger 

fuels (>7.5–20 cm diameter) (Andrews and others 2003, 

Bradshaw and others 1983). ERC approximates dryness 

(a proxy for amount of fuel available to burn) based on 

weather during the previous 1.5 months, the amount of 

time required for fuels 7.5–20 cm diameter (i.e., 1,000-

hour fuels) to equilibrate to atmospheric conditions 

(Fosberg and others 1981). Because ERC varies across 

different ecosystems, the raw values are commonly 

converted to percentiles to indicate departure from 

average conditions (Riley and others 2013).

Over the population of individual wildfires, ERC 

percentile during the first week of burning is highly 

correlated with fire occurrence at the scale of the 

Western United States, explaining over 90 percent of 

the variability in area burned and number of large fires 

for the period 1984–2008 (Riley and others 2013). 

Probability of a large fire ignition can be predicted from 

ERC (Andrews and Bevins 2003, Andrews and others 

2003), although the prediction parameters vary with 

location because fires are likely to ignite at different 

ERCs, depending on local fuels and climate. Because 

of its strong association with fire occurrence, ERC is 

used operationally as an indicator of heightened fire risk 

(Calkin and others 2011). It was shown to be correlated 

with area burned in southern Oregon and northern 

California (Trouet and others 2009) and the U.S. 

Northern Rockies (Abatzoglou and Kolden 2013).
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Keetch-Byram Drought Index—The KeetchByram Drought Index (KBDI) is an indicator of soil 

moisture deficit and is based on a number of physical 

assumptions (Keetch and Byram 1968). Soil water 

transfer to the atmosphere through evapotranspiration 

is determined by temperature and annual precipitation, 

which is used as a surrogate for vegetation cover (areas 

with higher annual rainfall are assumed to support more 

vegetation). KBDI was developed and evaluated for 

the Southeastern United States, and has been used 

for guidelines on expected fire conditions and potential 

suppression problems for this region (Melton 1989). 

KBDI has been useful beyond the Southeastern United 

States, with possible limitations in some cases (Liu and 

others 2010, Xanthopoulos and others 2006).

Wildfire potential is divided into four levels based on 

KBDI values (National Interagency Fire Center 1995):

lLow (KBDI=0–200)—soil moisture and fuel 

moistures for large fuels are high and do not 

contribute much to fire intensity;

lModerate (200–400)—lower litter and duff layers 

are drying and beginning to contribute to fire intensity;

lHigh (400–600)—lower litter and duff layers 

contribute to fire intensity and will actively burn; and

lExtreme (600–800)—intense, deep burning fires 

with significant downwind spotting can be expected.

The four KBDI levels are typical of spring dormant 

season following winter precipitation, late spring and 

early in the growing season, late summer and early 

autumn, and severe drought and increased wildfire 

occurrence, respectively.

The fire hazard measured by KBDI shows large 

spatial, seasonal, and interannual variability across the 

continental United States (Liu and others 2013b). In 

winter, there are high values in the intermountain region, 

which decrease rapidly towards the east and become 

<200 (low fire potential) in the Great Plains. This spatial 

pattern remains during other seasons but with some 

changes. In summer, KBDI values >300 (moderate fire 

potential) are observed in the Southern United States. In 

autumn, KBDI values are higher in both the Western and 

Southern United States, with values >400 in the latter 

(high fire potential). Multiple-year trends of seasonal fire 

hazard measured by the slope of a linear line fitting the 

normalized KBDI time series show a positive sign in all 

seasons and regions except three seasons in the Pacific 

Northwest and two seasons in the Southeast.

Fosberg Fire Weather Index—The Fosberg Fire 

Weather Index (FFWI) measures fire potential and 

hazard (Fosberg 1978). It is dependent on temperature, 

relative humidity, and wind speed, assuming constant 

grass fuel and equilibrium moisture content (Preisler and 

others 2008). In order to gauge fire-weather conditions, 

FFWI combines the equilibrium moisture content 

(Simard 1968) with Rothermel’s (1972) rate of spread 

calculation (Crimmins 2006). FFWI demonstrated 

significant skill in explaining monthly fire occurrence in 

the Western United States (Preisler and others 2008). 

To further include the effect of precipitation, a modified 

version of FFWI (mFFWI) was developed by adding 

KBDI as a factor (Goodrick 2002). One can use the 

mFFWI as a refinement of KBDI by adding the effects 

of relative humidity and winds.

Evapotranspiration—Evapotranspiration (ET), 

the combined evaporation from the surface and 

transpiration from plant tissues, is affected by 

meteorological conditions near the surface, plant 

physiology, and soil characteristics. Summer 

evapotranspiration had the highest correlations 

among drought indices with forested area burned 

in the Southwest and southern California, and with 

nonforested area burned in the U.S. Northern Rockies 

and Southwest (r2=0.44–0.83) (Abatzoglou and Kolden 

2013). June through September values of potential 

evapotranspiration, the evapotranspiration that could 

occur if plants did not limit water loss through stomata, 

was a significant predictor (r2=0.19–0.61) of area burned 

in forested Pacific Northwest ecoregions during recent 

decades (1980–2009) (Littell and Gwozdz 2011, Littell 

and others 2010).

Ecological water deficits: water balance deficit 

and climatic water deficit—Various algorithms are 

used to define water deficit, but all approach deficit as 

the evaporative demand not met by available water. It 

is estimated as the difference between atmospheric 

demand for water from plants and the land surface 

and how much water is available to meet that demand. 

Like PDSI, water deficit attempts to integrate energy 

and water balance of some area to describe water 

availability. Some calculations of water deficit attempt 

to account for more of the factors in the soil-plantatmosphere continuum than PDSI (e.g., storage in 

snow, effects of plant canopy energy balance, albedo, 

and wind).
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Stephenson (1990, 1998) defined water balance 

deficit (WBD) as the difference between potential 

evapotranspiration (PET) and actual evapotranspiration 

(AET), and related it to the coarse distribution of 

biomes. Littell and Gwozdz (201) showed that PET, AET, 

and WBD are related (i.e., WBD = PET – AET) with a 

range of R 2=0.25–0.78 to area burned in ecosystems 

of the Pacific Northwest. Summer WBD had the 

highest correlation of several indices with area burned 

in forested areas of the Pacific Northwest (r2=0.66) 

(Abatzoglou and Kolden 2013). Others have used a 

version closer to Thornthwaite’s (1948) approximation 

and defined deficit as PET – precipitation.

Relationship to Hydrologic Drought

Many of the same factors affecting moisture in 

vegetation also affect moisture available for streamflow 

(chapter 2), and both fire and hydrologic drought occur 

with some lag after meteorological drought begins. 

Understanding such relationships could be useful 

for operational fire forecasts based on the same 

mechanisms that could be built from the substantial 

infrastructure and capacity for forecasting hydrologic 

drought. Broad changes and trends in snowpack, 

streamflow timing, and streamflow volume have been 

noted in various parts of the Western United States 

(Luce and Holden 2009, Luce and others 2012, Mote 

and others 2005, Regonda and others 2005, Stewart 

2009), as have recent trends in fire occurrence related 

to climatic forcings (Dennison and others 2014).

Analysis of wildfire occurrence across the Western 

United States with streamflow records noted a 

moderately strong interannual correlation between 

the first principal component of streamflow center 

of timing and burned area in forests (Westerling and 

others 2006). Other work contrasting the correlation 

with total streamflow volume and center of timing in the 

Northwestern United States found similar relationship 

strength between burned area and annual streamflow 

volumes and between burned area and streamflow 

timing (Holden and others 2012). In the Pacific 

Northwest, a decline in streamflow and precipitation, 

particularly during drought years, suggested that much 

of the trend in fire in the historic record may be related 

to precipitation trends (Luce and Holden 2009, Luce and 

others 2013).

Synthesis of Index Relationships

The time window, over which the drought indices 

discussed earlier are computed, determines both the 

mechanistic relationships with fire they capture and their 

skill in predicting different aspects of fire regimes 

(fig. 7.1). For example, for fire occurrence at the spatial 

scale of the Western United States, ERC (calculated 

based on fuel moistures during the previous 1.5 

months) is strongly correlated with both number of 

large fires and the burned area (Riley and others 2013). 

Monthly precipitation anomalies were comparably 

correlated. As the time window for the index increases 

to longer lags, the correlation with fire occurrence 

decreases. At finer scales, however, the relationships 

differ significantly across ecosystems. For example, 

above-normal precipitation in the year(s) prior to fire is 

associated with higher area burned in the Southwestern 

United States (Littell and others 2009, Swetnam and 

Betancourt 1998, Westerling and others 2003) and 

Great Basin (Littell and others 2009, Westerling and 

others 2003). Long-term drought (>4 months) is not 

necessarily a prerequisite for extensive area burned, and 

seasonal climate can override the effect of antecedent 

climate (Abatzoglou and Kolden 2013).

Tree 

Stand Landscape Ecoregion 

Daily 

Seasonal 

Annual 

Decadal 

Centennial 

Climate Millennial 

Fire Regime 

Fire Event 

Synoptic 

Weather 

Weather 

Climate 

ENSO 

PDO 

AMO 

KBDI 

ERC 

SPI 

Spatial scale (ha) 

Temporal scale (days) 

Deficit (PET-AET) 

Drought 

Figure 7.1—Scaling of controls on fire events, fire regimes 

(top, after climatic scaling of Clark [1985]), drought metrics, 

and climatic drivers related to their variation. In general, 

drought metrics are temporally coincident with fire events. The 

correlation between drought metrics and components of the fire 

regime in a location varies with time and space. Climatic factors 

that affect probability of ignitions, spread, area burned, and 

severity in a location in a given year is the product of multiscale 

influences of the climate system (top down) on fuel flammability 

and historical controls on fuel availability. Atlantic Multidecadal 

Oscillation (AMO), El Niño Southern Oscillation (ENSO), and 

Pacific Decadal Oscillation (PDO) refer to modes of climatic 

variability. AET=actual evapotranspiration; PET=potential 

evapotranspiration; ERC=Energy Release Component; 

KBDI=Keetch-Byram Drought Index; and SPI=Standardized 

Precipitation Index.
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Regional Differences 

in Fire and Interactions 

With Other Stressors

Drought clearly increases probability of fire occurrence in 

forest ecosystems, but other disturbances and stressors, 

both biotic and abiotic, interact with drought and fire in 

stress complexes that affect the vigor and sustainability 

of forest ecosystems (McKenzie and others 2009). 

Although some of these interactions are predictable, 

they are poorly quantified and complicated by the fact 

that most ecosystems are rarely in dynamic equilibrium 

with biophysical processes. In addition, equilibrium 

rarely occurs even in relatively constant climate, and it is 

typically punctuated by disturbance episodes that may 

or may not be associated with climatic variability; these 

disturbance episodes allow succession to proceed along 

multiple pathways (Frelich and Reich 1995) and create 

forest dynamics that are difficult to project accurately. 

These dynamics and their consequences reflect natural 

processes in many forest ecosystems. However, the 

role of climate change in increasing the probability of 

drought and the simultaneous effects of climate on 

forest processes that feed back to disturbance bears 

consideration of interactions that may result in more 

rapid change than drought alone.

Increasing air temperatures are expected to change 

the frequency, severity, and extent of wildfires (Littell 

2006, McKenzie and others 2004, Moritz and others 

2012). Large wildfires that have occurred during a 

warmer climatic period during the past two decades 

portend a future in which wildfire is an increasingly 

dominant feature of western landscapes. Similarly, bark 

beetles, whose life cycles are accelerated by increased 

temperatures, are causing extensive mortality across 

the West (Logan and Powell 2001, Swetnam and 

Betancourt 1998, Veblen and others 1991).

Tropospheric ozone, a stressor of forest ecosystems, 

is an indirect product of fossil fuel emissions and is 

exacerbated by sunlight and high temperature, although 

most other air pollutants are the direct result of humancaused emissions. Fire and insect disturbance clearly 

interact, often synergistically, thus compounding rates of 

change in forest ecosystems (Veblen and others 1994). 

For example, mountain pine beetles (Dendroctonus 

ponderosae)—which have caused high mortality, 

mostly in lodgepole pine (Pinus contorta subsp. latifolia) 

forests across 20 million ha in western North America—

may significantly increase fine fuels and fire hazard for 

years following outbreaks (see review by Hicke and 

others 2012), though there is some uncertainty as 

to whether the probability of severe fires is affected 

positively or negatively by bark beetle mortality after 

dead needles have fallen (Lundquist 2007, Pollet and 

Omi 2002). In addition, fire severity in subalpine forests 

can be altered by a combination of bark beetles and 

annual-scale drought (Bigler and others 2005).

To explore the consequences of these interactions for 

different ecosystems, we extend a pathological model 

of cumulative stress in trees (Manion 1991, 2003) to 

forest ecosystems by describing interacting disturbances 

and stresses as stress complexes that have potentially 

far-reaching effects. Temperature increases are a 

predisposing factor causing often lethal stresses on forest 

ecosystems, acting both directly through increasingly 

negative water balances (Littell 2006, Milne and others 

2002, Stephenson 1998) and indirectly through increased 

frequency, severity, and extent of disturbances (chiefly 

fire and insect outbreaks) (Logan and Powell 2001, 

2009; McKenzie and others 2004; Skinner and others 

2006). Increased disturbances can in turn cause rapid 

changes in forest structure and function and will be more 

important than temperature increase alone in altering the 

distribution and abundance of plant and animal species. 

We use examples from several forest ecosystems to 

document the existence of stress complexes and how 

they may be affected by a warmer climate.

Pinyon-Juniper Woodlands 

of the American Southwest

Pinyon pine (Pinus edulis) and various juniper species 

(Juniperus spp.) are among the most drought-tolerant 

trees in western North America, and characterize lower 

treelines across much of the West. Although pinyonjuniper woodlands appear to be expanding in some 

areas, possibly due to fire suppression or cessation 

of Native American fuelwood harvesting (Samuels 

and Betancourt 1982), they are clearly water-limited 

systems. At fine scales, pinyon-juniper ecotones are 

affected by local topography and existing canopy 

structure that may buffer trees against drought to 

some degree (Milne and others 1996), although severe 

multi-year droughts periodically cause massive dieback 

of pinyon pines, overwhelming any local buffering. 

Dieback of pine species—both ponderosa pine (Pinus 

ponderosa) and pinyon pine—occurred during and 

before the 20th century (Allen and Breshears 1998, 

Breshears and others 2005), and the recent (since the 

early 2000s) dieback is clearly associated with low 

precipitation and higher temperatures (Breshears and 

others 2005).
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In the stress complex for pinyon-juniper woodlands 

(fig. 7.2), climate change is a predisposing factor; 

pinyon pine mortality and fuel accumulations result from 

warming and can lead to other impacts. Ecosystem 

change, possibly irreversible, comes from largescale, severe fires that lead to colonization of invasive 

species, which further compromise the ability of pines 

to regenerate. However, it is worth noting that severe 

fires were historically characteristic of some pinyon pine 

systems (Floyd and others 2004).

Mixed-Conifer Forests of the Sierra 

Nevada and Southern California

Dominated by various combinations of ponderosa pine, 

Jeffrey pine (Pinus jeffreyi), sugar pine (P. lambertiana), 

Douglas-fir (Pseudotsuga menziesii), incense cedar 

(Libocedrus decurrens), and white fir (Abies concolor), 

these forests experience a Mediterranean climate in 

which summers are dry and long. Despite increasing 

temperatures since the early 20th century, fire 

frequency and extent did not increase in the mid- to 

late-20th century (McKelvey and others 1996). Rather, 

20th century fire frequency and likely area were at 

lower levels than those present over the rest of the 

last 2,000 years (Swetnam 1993, Swetnam and Baisan 

2003). Stine (1996) attributes this to decreased fuel 

loads from sheep grazing, decreased Native American 

fire management, and fire exclusion. Fire exclusion has 

led to increased fuel loadings and competitive stresses 

on individual trees as stand densities have increased 

(Ferrell 1996, van Mantgem and others 2004).

Elevated levels of ambient ozone, derived from vehicular 

and industrial sources in urban environments upwind, 

are phytotoxic and reduce net photosynthesis and 

growth of ponderosa pine, Jeffrey pine, and possibly 

other species in the Sierra Nevada and the mountains 

of southern California (Byternowicz and Grulke 1992, 

Miller 1992, Peterson and Arbaugh 1988, Peterson and 

others 1991). Sierra Nevada forests support endemic 

levels of a diverse group of insect defoliators and bark 

beetles (typically Dendroctonus spp.), but bark beetles 

in particular have reached outbreak levels in recent 

years, facilitated by protracted droughts. Ferrell (1996) 

refers to biotic complexes in which bark beetles interact 

with root diseases and mistletoes. Dense stands, fire 

suppression, and nonnative pathogens such as white 

pine blister rust (Cronartium ribicola) can exacerbate 

MORE SEVERE AND EXTENDED DROUGHTS

Stress complex for pinyon-juniper woodlands

Insects 

Pinyon pine mortality Fuel accumulation

Large, severe fires 

Changes in species composition (including exotics) 

GLOBAL WARMING

Figure 7.2—Stress complex in pinyon-juniper woodlands of 

the American Southwest. The effects of disturbance regimes 

(insects and fire) will be exacerbated by global warming. Standreplacing fires and drought-induced mortality both contribute to 

species changes and exotic invasions. (Adapted from McKenzie 

and others 2009).

Bark beetles

and defoliators

Tree mortality 

Fuel 

accumulation 

Large, severe fires 

Changes in species composition (including exotics) 

Fire exclusion 

High stand

densities

Ozone 

Higher temperatures and 

more severe and 

extended droughts 

Stress complex for Sierra Nevada and 

Southern California mixed-conifer forests

GLOBAL WARMING

Figure 7.3—Stress complex in Sierra Nevada and southern 

Californian mixed-conifer forests. The effects of disturbance 

regimes (insects and fire) and fire exclusion will be exacerbated 

by global warming. Stand-replacing fires and drought-induced 

mortality both contribute to species changes and exotic 

invasions. Dashed lines indicate potential direct effects of 

higher temperature and drought. (Adapted from McKenzie and 

others 2009).
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both biotic interactions (van Mantgem and others 2004) 

and drought stress. The stress complex associated 

with Sierra Nevada forest ecosystems (fig. 7.3) is likely 

applicable to the mountain ranges east and north of the 

Los Angeles basin as well.

Interior Lodgepole Pine Forests

Lodgepole pine is widely distributed across western 

North America and is the dominant species over much 

of its range, forming nearly monospecific stands that 

are maintained either because poor soils preclude other 

species or through adapting to stand-replacing fires via 

cone serotiny (Burns and Honkala 1990). Lodgepole 

pine is the principal host of the mountain pine beetle, 

and older, low-vigor stands are vulnerable to massive 

mortality during beetle outbreaks. Recent beetle 

outbreaks have caused extensive mortality across 

western North America, with large mature cohorts (age 

70–80 years) contributing to widespread vulnerability. 

Warmer temperatures facilitate insect outbreaks by 

drought stress, making trees more vulnerable to attack 

and speeding up the reproductive cycles of some insect 

species (Logan and Bentz 1999, Logan and Powell 

2001). Scientists accept that warming temperatures will 

exacerbate these outbreaks northward and into higher 

elevations (Hicke and others 2006, Logan and Powell 

2009), but lodgepole pine ecosystems are poised for 

significant changes even at current levels of mortality.

In the stress complex for lodgepole pine forests 

(fig. 7.4), warmer temperatures combine with the highly 

flammable dead biomass (associated with beetleinduced mortality), and this combination exacerbates 

the natural potential for severe crown fires for roughly 

5 years. Then, after fine fuels decompose and 

become compressed, the fire hazard may be lessened 

considerably.

Interior Alaskan Forests

A combination of large crown fires and outbreaks of 

spruce bark beetle (Dendroctonus rufipennis) in southcentral Alaska has affected millions of hectares of boreal 

forest during the past 20 years (Berg and others 2006). 

Although periodic beetle outbreaks have occurred 

in southern Alaska and the southwestern Yukon 

throughout the historical record, the recent outbreaks 

are unprecedented in extent and percentage mortality 

(over 90 percent in many places) (Berg and others 

2006, Ross and others 2001). Summer temperatures 

in the Arctic have risen 0.3–0.4 °C per decade since 

1961 (Chapin and others 2005), and wildfire and 

beetle outbreaks are both likely associated with this 

temperature increase (Berg and others 2006, Duffy 

and others 2005, Werner and others 2006). Although 

fire-season length in interior Alaska is associated with 

the timing of onset of the late-summer precipitation, the 

principal driver of annual area burned is early summer 

temperature (Duffy and others 2005).

White spruce (Picea glauca) and black spruce (P. 

mariana) are more flammable than co-occurring 

deciduous species [chiefly paper birch (Betula 

papyrifera)]. Similarly, conifers are a target of bark 

beetles, so spruce in south-central Alaska will be 

disadvantaged compared to deciduous species, most of 

which respond to fire by sprouting. The stress complex 

for Alaskan boreal forests (fig. 7.5) projects a significant 

transition to deciduous species via more frequent 

and extensive disturbance associated with warmer 

temperatures. Scientists contend that this transition 

is unlikely without changes in disturbance regimes, 

because both empirical data and modeling suggest that 

warmer temperatures alone will not favor a life-form 

transition (Bachelet and others 2005, Boucher and 

Mead 2006, Johnstone and others 2004).

Bark beetles

and defoliators

Salvage logging

Large, severe fires Fuel accumulation

Changes in species composition (including exotics) 

Stand-replacing 

fire regime

Extensive mature

cohorts (70–80 years)

Higher temperatures and more 

severe and extended droughts 

Lodgeple pine mortality

Stress complex for lodgepole pine forests

GLOBAL WARMING

Figure 7.4—Stress complex in interior lodgepole pine forests. 

The effects of disturbance regimes (insects and fire) will be 

exacerbated by global warming. Stand-replacing fires, beetle 

mortality, and other stressors contribute to species changes. 

Dashed lines indicate potential direct effects of higher 

temperature and drought. (Adapted from McKenzie and 

others 2009).
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Southern Pine Forests

Much of the forested landscape in the Southeastern 

United States is adapted to frequent fire, and unlike 

most of the rest of the country, prescribed fire is a 

mainstay of ecosystem management. Fire-adapted 

inland forests overlap geographically with coastal areas 

affected by hurricanes and potentially by sea-level rise 

(Ross and others 2009); therefore, interactions between 

wildfires and hurricanes are synergistic (fig. 7.6). For 

example, dry-season (prescribed) fires may have 

actually been more severe than wet-season (lightning) 

fires in some areas, causing structural damage via 

cambium kill and subsequent increased vulnerability to 

hurricane damage (Platt and others 2002). The stress 

complex for Southern pine forests is represented 

conceptually in figure 7.6, where different disturbances 

“meet” in the outcomes for forest ecosystems.

Increasing frequency and magnitude of drought is 

expected to increase the flammability of both live and 

dead fine fuels in upland forests and pine plantations 

(Mitchell and others 2014). This may increase the 

frequency and intensity of some wildfires, and it may 

also reduce opportunities for safe implementation of 

prescribed burning. Both drought and increased fire 

may lead to greater dominance by invasive species 

[e.g., cogongrass (Imperata cylindrical)], which can in 

turn alter the flammability of fuels (Mitchell and others 

2014). Proactive fuel reduction through prescribed 

burning, a common practice in Southern pine forests, 

will be even more important in a warmer climate.

Discussion

Rapid climate change and qualitative changes in 

disturbance regimes may send ecosystems across 

thresholds into dominance by different life forms and 

cause significant changes in productivity and capacity 

for carbon storage. For example, in the Southwest, 

stand-replacing fires are becoming common in what 

were historically low-severity fire regimes (Allen and 

South-central forests 

or interior forests on

permafrost-free soils 

Interior forests on permafrost soils 

Ice-rich lowlands

(deciduous forests) Upland coniferous forests 

Higher temperatures 

Beetles 

Large fires 

Species conversion 

More deciduous forest 

Thermokarst ponds 

Wetlands, fens, 

and bogs

Coniferous and 

deciduous forest

More stand-replacing fires Fuel accumulation 

Permafrost degradation 

Stress complex for Alaskan boreal forests

GLOBAL WARMING

Figure 7.5—Stress complex in interior and coastal forests of Alaska. Rapid increases in 

the severity of disturbance regimes (insects and fire) will likely be triggered by global 

warming. Stand-replacing fires, mortality from insects, and stress-induced dieback 

contribute to species changes and conversion to deciduous species. (Adapted from 

McKenzie and others 2009).
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others 2002), and protracted drought is killing species 

(ponderosa pine) that are adapted to low-severity 

fire (Allen and Breshears 1998). If these trends 

continue, ponderosa pine may be lost from some of 

its current range in the Southwest, and productivity 

of these systems will decline. In contrast, if warming 

temperatures accelerate mountain pine beetle 

reproductive cycles (Logan and Powell 2001) such 

that outbreaks are more frequent and more prolonged, 

lodgepole pine might be replaced by a more productive 

species such as Douglas-fir, at least on mesic sites 

where conditions for establishment are favorable.

As the climate warms, we expect that more 

ecosystems will become water limited (Albright and 

Peterson 2013, Littell 2006, Milne and others 2002), 

more sensitive to variability in temperature (due to its 

controls on both phenological and ecophysiological 

processes), and prone to more frequent disturbance. 

Consequently, productivity may decline across much 

of the West (Hicke and others 2002), and long-term 

carbon sequestration may be limited by a continuous 

mosaic of disturbances of various severities. Species 

and ecosystems will be affected in various ways and 

not all undesirable changes will be preventable by 

management intervention (McKenzie and others 2004).

There is no historical or current analog for the 

combination of climate, disturbance regimes, and landuse changes expected by the end of the 21st century. 

For example, tempering the idea of “desired future 

conditions” with “achievable future conditions” will 

facilitate more effective adaptive management and 

more efficient allocation of resources to maintain forest 

resilience. Conceptual models of stress complexes 

improve our understanding of disturbance interactions 

in forest ecosystems affected by climate change. 

Quantitative models of stress complexes are now 

needed to characterize alternative future states for a 

broad range of forest ecosystems across North America.

Drought and warmer temperatures

Upland forests Coastal forests

Seasonal flooding

Wildfire threatens wildlandurban interface 

Forest change

Reduced

productivity 

More flammable fuels 

Species conversion

More stand-replacing fires, larger patches

More severe hurricanes Sea-level rise

More dead fuels 

Air quality limits Rx fire, 

fire suppression, and 

other treatments 

Stress complex for Southern U.S. pine forests

GLOBAL WARMING

Figure 7.6—Stress complex in interior and coastal forests of the southeastern United 

States. Increases in the severity of hurricanes are triggered by global warming. Warmer 

and drier climate in uplands leads to longer periods with flammable fuels. Changes in fire 

and hydrologic regimes, and responses to them, lead to species change and altered carbon 

dynamics.
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Quantifying and Projecting 

Drought Effects on Wildfire: 

Biological and Physical Factors

In chapter 2 of this publication, drought is defined as 

an area-specific anomalous lack of water. Here, we 

expand this definition to an uncharacteristic lack of 

water, specific to an ecosystem and a time scale. Risk 

is often defined as the product of the probability of an 

event and its consequences. Wildland fire researchers 

calculate fire risk as the probability of fire of a certain 

intensity times the effect on resource values (Bratten 

1982, Calkin and others 2011, Mills and Bratten 1982). 

Wildfire probability increases as the moisture stored in 

fuels (live and dead vegetation) declines. Wildfire risk 

therefore responds to meteorological drought, and fire 

occurrence and area are correlated with metrics that 

measure precipitation delivery, relative humidity, and/

or fuel moisture, reflecting both supply of water and 

demand for it (Abatzoglou and Kolden 2013, Littell and 

others 2009, Littell and Gwozdz 2011, Riley and others 

2013). Drought is related to fire risk because it increases 

fuel dryness (in both live and dead fuels), which is 

correlated with probability of ignition and increases rate 

of spread. Drought may also increase the number of 

days with heightened probability of ignition.

Wildfire risk differs across the continental United States 

(Finney and others 2011, Preisler and Westerling 2007, 

Radeloff and others 2005) as a function of probability 

of burning and values at risk (buildings, municipal 

watersheds, endangered species habitat, etc.). Fire 

probability is generally related to the inverse of fire 

return interval, with longer fire return intervals having a 

lower annual probability of burning; for example, annual 

probability of burning in forests that burn infrequently is 

lower than that of chaparral which burns frequently (Agee 

1993, Frost 1998). Probability of burning is also affected 

by quantity and distribution of fuels, land management, 

fire suppression, and invasive plants. Because many 

ecosystems in the United States were structured by fire 

until effective suppression, some consider wildfire to be a 

regulating ecosystem service through periodic reduction 

of fuels, which would otherwise require costly treatment. 

Cessation of Native American burning combined with fire 

suppression may have reduced area burned annually in 

the United States by an order of magnitude (Leenhouts 

1998, Marlon and others 2012). If that burning takes 

place preferentially under extreme drought conditions 

when it cannot be suppressed, it is more likely to be 

of uncharacteristically high severity than if it took place 

under more moderate conditions.

Tree-ring evidence of North American “megadroughts” 

indicates that droughts of severity and duration not 

yet encountered by modern societies occurred on a 

widespread basis in the past (Cook and others 2007). 

Currently, only thin consensus exists regarding the effect 

of climate change on drought occurrence (Maloney 

and others 2014; chapter 2). High confidence exists for 

projected temperature increases across most of the 

planet in future decades, whereas altered precipitation 

and relative humidity are uncertain (Blöschl and Montanari 

2010, Walsh and others 2014), and that uncertainty varies 

geographically. As temperatures continue to warm, all 

else being equal, droughts of given magnitude and low 

fuel moistures may become more likely in summer-dry 

climates even if precipitation increases, because potential 

evapotranspiration will also increase.

Seasonal timing of increases or decreases in 

precipitation would have important effects on 

risk, leading to geographic heterogeneity driven 

by historical fire regimes, ecological responses to 

climate change, and management. Regardless of 

specific climatic mechanisms, fire risk may increase 

or decrease depending on temporal scale and factors 

influencing probability and consequences of fires. Fire 

occurrence probabilities could be affected both through 

fuel production (frequency or severity of drought, 

affecting species assemblages and thus fire regime 

through fuels) or through flammability (fire frequency 

responds to flammability and drives changes in species 

assemblages). As noted in chapter 2, leaf area of some 

forests may decrease in response to prolonged drought, 

which could increase the water available for understory 

plants. In this case, understory plants could contribute 

to the intensity of surface fires.

Expected Changes in Drought 

and Consequences for Wildfire

It is important to account for physical, hydrological, 

ecological, and human dimensions in translating 

projected climate into future fire risk. However, in 

the near term (e.g., the first half of the 21st century) 

it can be argued that changes in fire risk will occur 

on landscapes and within management strategies 

that already exist. Given that expected physical and 

hydrologic changes can be quantified, we present 

projections of two fire-related drought indicators 

discussed earlier: an ecohydrological indicator (define 

as PET – AET) (fig. 7.7) and the hydrologic indicator 

7Q10 (the lowest 7-day average flow that occurs on 

average once every 10 years) (fig. 7.8). A composite 

of 10 General Circulation Models shows that summer 
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Ecohydrological drought indicator PET–AET Hydrologic drought indicator 7Q10

Figure 7.7—Downscaled change (2030–2059) in summer 

(June through August) water-balance deficit from historical 

(1916–2006): potential evapotranspiration (PET) – actual 

evapotranspiration (AET), measured in total mm water. Waterbalance deficit (WBD) is well correlated with many climate 

effects on vegetation. In this representation, positive responses 

reflect an increase in deficit (less water availability and brown 

shaded), while negative responses reflect a decrease (more 

water availability and blue shaded). Ten-model composite 

(upper left) and output from the Weather Research and 

Forecasting (WRF) model (upper right) is followed by four 

bracketing General Circulation Model (GCM) scenarios [Coupled 

Model Inter-comparison Program (CMIP3)/AR4, after Littell 

and others 2011 and Elsner and others 2010] (Figure: Robert 

Norheim. Data source: U.S. Geological Survey, Western U.S. 

Hydroclimate Scenarios Project Datasets.)

Figure 7.8—Changes (2030–2059) from historical (1916–2006) in 

7Q10 (the lowest weekly average flow that occurs on average 

once every 10 years)—a measure of extreme low-flow periods 

in streams. The climate-change driven variation in low flows 

depends on characteristics unique to watersheds, regions, and 

future climate. Upper left: composite of statistically downscaled 

changes from 10 climate models. Upper right: dynamically 

downscaled changes from a single climate model (ECHAM5). 

Lower four panels illustrate bracketing General Circulation 

Models (warmer drier, warmer wetter, less warming drier, 

less warming wetter). (Figure: Robert Norheim. Data source: 

U.S. Geological Survey, Western U.S. Hydroclimate Scenarios 

Project Datasets.)
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(June through August) water-balance deficit is projected 

to increase in much of the West except in portions 

of the Southwest that have significant monsoon 

precipitation and in some mountainous areas in the 

Pacific Northwest. The geographic distribution and 

magnitude of projected changes differ among climate 

models. Four climate models that bracket the range 

of projected changes in temperature and precipitation 

suggest that extreme low streamflows would be more 

frequently exceeded in the Cascades than in other areas 

of the West. Model output suggests that the Columbia 

Basin, upper Snake River, and southeastern California/

southwestern Oregon may exceed extreme low flows 

less frequently than they did historically. Given the 

historical relationships between fire occurrence and 

drought indicators such as water-balance deficit and 

streamflow, climate change can be expected to have 

significant effects on fire risk.

Similarly, future fire hazards as measured by KBDI are 

projected to increase in most seasons and regions of 

the continental United States in the 21st century (Liu 

and others 2013b). The largest increases in fire hazard 

are in the Southwest, Rocky Mountains, northern Great 

Plains, and Southeast and Pacific Coasts, mainly caused 

by future temperature increase. The most pronounced 

increases occur in summer and autumn, including an 

extended fire season in several regions.

Fire Feedbacks to Drought

Drought is caused by changes in one or more of three 

atmospheric properties: thermal instability, water vapor 

supply, and dynamic systems creating upward motion. 

Wildfires can contribute to these properties from 

local to global scales by emitting particles and gases 

that affect atmospheric dynamics and by modifying 

land cover, feedbacks that were not systematically 

investigated until recently (Liu and others 2013a).

Smoke Particles

Fires emit particles including organic carbon (OC), 

which is bound in various compounds derived from 

plant tissue, and black carbon (BC), which is a 

pure carbon component of fine particulate matter 

[<2.5 μm (micrometers)] formed through incomplete 

combustion as soot. BC emissions from biomass 

(forest and savanna) burning account for 5–10 percent 

of fire smoke particles and about 40 percent of total 

global BC emissions (Bond and others 2004). These 

smoke particles can affect atmospheric radiative 

budgets by scattering and absorbing solar radiation 

(direct radiative forcing). This can further affect cloud 

cover and precipitation at regional scales. Koren and 

others (2004) analyzed Moderate Resolution Imaging 

Spectroradiometer (MODIS) satellite measurements 

during biomass burning in the Amazon region and found 

that cloud cover was reduced from 38 percent in clean 

conditions to nearly 0 percent for heavy smoke.

The radiative forcing of smoke can affect regional 

precipitation in many ways (fig. 7.9), but especially 

by modifying atmospheric thermal stability. The land 

surface and the atmosphere below the smoke layer are 

cooled by scattering and absorption of solar radiation by 

smoke particles. During a wildfire near Boulder, CO, in 

2010, the surface under the smoke plume was cooled 

2–5 °C (Stone and others 2011). Meanwhile, the upper 

air with smoke particles was warmed by solar radiation 

absorption. These changes in the vertical temperature 

profile stabilize the atmosphere and suppress cloud 

development.

Air relative humidity of the smoke layer is reduced from 

the warming effect of solar radiation absorption by BC, 

and cloud formation is inhibited. Relatively low cloud 

cover over the ocean has been documented due to the 

large concentration of soot aerosols, which leads to 

higher air temperature and lower relative humidity that 

help to “burn out” clouds (Ackerman and others 2000). 

Clouds and precipitation are reduced during the burning 

season over the Amazon because water vapor transport 

from the ground is low, and the planetary boundary 

layer to clouds is weakened from lower turbulent activity 

(Liu 2005a).

Atmospheric horizontal airflow convergence and vertical 

ascending in the lower troposphere favor cloud and 

precipitation formation. The radiative forcing of smoke 

particles leads to cooling on the ground and in the 

lower troposphere, despite possible warming at some 

elevations due to solar radiation absorption by BC. In a 

simulation study of the 1988 Yellowstone National Park 

wildfires that occurred during a drought (Liu 2005b), 

absorption of solar radiation by smoke particles over the 

fire area released heat in the upper smoke layer. This 

phenomenon altered westerly airflows, transporting 

warmer air downwind and converging in the trough 

area over the Midwest. The trough weakened, reducing 

clouds and rainfall, which suggests that feedbacks from 

wildfires may enhance drought.

Greenhouse Gases

Carbon dioxide is the largest fire emission component, 

accounting for 87–92 percent of total carbon burned 
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(Urbanski and others 2008). Average annual global 

fire carbon emissions were about 2 picograms (Pg) 

in the recent decade, about one-third of total carbon 

emissions. BC emissions enhance the greenhouse 

effect in the atmosphere, and deposition of BC 

emissions on snow and ice at high latitudes reduces 

albedo and increases solar radiation absorbed by 

the surface, which in turn accelerates snow melting 

(Hansen and Nazarenko 2004). Boreal fires contribute 

more BC to the Arctic than human sources in summer 

based on multi-year averages (Stohl and others 2006). 

As a major source of atmospheric carbon dioxide 

and BC, wildfire emissions contribute significantly to 

atmospheric carbon dynamics and radiation absorption. 

Analyses of the Coupled Model Inter-comparison 

Program phase 3 (CMIP3) and phase 5 (CMIP5) 

indicate that future drought occurrence, duration, 

and severity will likely increase in response to the 

greenhouse effect globally and in many mid-latitude 

areas including the United States (Maloney and others 

2014). Increasing drought amplifies the warming effect 

over decades to centuries.

Land Cover Change

Water transfer from the land surface, a local water 

vapor source for precipitation, is much higher on 

vegetated lands through evapotranspiration than 

unvegetated lands through evaporation. Leaf area 

after stand-replacing fires decreases greatly from prefire conditions, and evapotranspiration is temporarily 

reduced, leading to reduced water transfer through 

transpiration. The Bowen ratio (a ratio of sensible 

to latent heat flux) increases after burning, meaning 

that more solar energy absorbed on the surface is 

converted to sensible heat instead of being used as 

latent energy for water-phase change. After fire, the 

capacity of soil to store water is reduced, canopy 

and understory interception is decreased, and 

evapotranspiration from live vegetation is decreased, 

with a net effect of increased runoff and reduced soil 

water available for transfer to the atmosphere despite 

the reduction in evapotranspiration. As a result, the 

atmosphere will receive more heat energy and more 

intense convective activities, but less water from the 

ground for a long post-fire period.

During the 2004 Alaska fire season, wildfires altered 

land cover over large areas, leading to changes 

in dynamic, radiative, vegetative, thermal, and 

hydrological surface characteristics (Möldersa and 

Kramma 2007). A simulation to quantify the effects of 

fire-caused land cover changes indicated that sensible 

heat fluxes into the atmosphere increased by up to 

225 Watts per square meter (W/m2) over burned 

areas. There was enough enhanced lifting in the areas 

with large burns to produce areas of increased clouds 

followed by an area of decreased clouds downwind of 

them. Precipitation increased significantly in the lee of 

burned areas, but decreased slightly a few days after 

large fires.

F I R E

Emissions 

Land cover change

Evapotranspiration Soil moisture

Water vapor 

Land-air

interaction 

Local precipitation 

Drought 

Global precipitation

Organic carbon Black carbon CO2

Radiative

effect 

 

Black carbon – 

snow feedback 

Greenhouse

effect 

Regional precipitation 

Thermal

stability

Burning

effect Circulation

Figure 7.9—Physical processes for feedbacks of wildfires to drought.
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Management and 

Social Implications

To the extent that drought affects fire directly, 

management implications mirror those associated with 

changes in fire regimes stemming from climate change 

(Littell and others 2009). In regions where area burned 

has historically been higher with high temperature 

and low precipitation anomalies (most of the Western 

United States), area burned will likely increase with 

temperature and possibly the frequency of drought 

(Committee on Stabilization Targets for Atmospheric 

Greenhouse Gas Concentrations, National Research 

Council 2011). Fire severity and frequency may 

also increase, but blanket statements about these 

phenomena are strongly affected by local conditions 

and therefore differ considerably. However, larger fires 

and higher area burned will continue to challenge fire 

suppression efforts and budgets, and may require 

rethinking historical approaches to fire management 

on landscapes. If annual area burned increases >200 

percent in most of the Western United States as 

projected for the mid-21st century (Peterson and Littell 

2014), the proportion of landscapes recently burned 

would also increase. Combined with the effects of 

increasing temperature on climatic suitability for 

regeneration, ecosystem function and structure may 

change rapidly (Littell and others 2010), thus altering 

the landscapes for which land management agencies 

have responsibility.

In some regions of the United States, a longer season 

during which fuels are highly flammable may affect 

management activities intended to reduce the quantity 

of those fuels. Even if there is minimal change in 

probability of historically extreme droughts, effective 

or “ecological” drought due to increased water 

demand may decrease favorable conditions for 

prescribed fire. However, the duration of time when 

burning can be conducted (relative to fuel conditions, 

regulatory compliance, and social acceptance) could 

simply move to earlier in spring and later in autumn. If 

drought-caused wildfire activity increases, wildlandurban interface areas will face increased fire risk, thus 

increasing suppression costs and potentially altering 

social perceptions of management and risk in fireprone human communities.

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CHAPTER 8

D.M. Finch is a Biologist with U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station (RMRS), Albuquerque, NM 87102.

R.L. Pendleton is a Research Plant Ecologist with U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station (RMRS), Albuquerque, NM 87102.

M.C. Reeves is a Research Ecologist with U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Missoula, MT 59807.

J.E. Ott is a Research Geneticist with U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID 83702.

F.F. Kilkenny is a Research Biologist with U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID 83702.

J.L. Butler is a Research Ecologist with U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Rapid City, SD 57702.

J.P. Ott is a Post-Doctoral Research Botanist with U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station (RMRS), Rapid City, SD 57702.

J.R. Pinto is a Research Plant Physiologist with U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station (RMRS), Moscow, ID 83843.

P.L. Ford is a Research Ecologist with U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Albuquerque, NM 87102.

J.B. Runyon is a Research Entomologist with U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station (RMRS), Bozeman, MT 59717.

M.A. Rumble is a Research Wildlife Biologist with U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station (RMRS), Rapid City, SD 57702.

S.G. Kitchen is a Research Botanist with U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Provo, UT 84606. 

Rangeland Drought: 

Effects, Restoration, 

and Adaptation

Deborah M. Finch

Rosemary L. Pendleton 

Matt C. Reeves

Jeffrey E. Ott

Francis F. Kilkenny

Jack L. Butler

Jacqueline P. Ott

Jeremy R. Pinto

Paulette L. Ford

Justin B. Runyon

Mark A. Rumble

Stanley G. Kitchen
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

Drought can have severe impacts on rangeland 

ecosystems in North America. For the purposes of 

this chapter, rangelands include natural grasslands, 

savannas, shrublands, many deserts, tundras, alpine 

communities, marshes, meadows, and woodlands. 

Drought impacts vary depending on the severity, 

frequency, duration, and aerial extent of the drought(s); 

how the land is managed; and whether plans are in 

place and implemented to respond to drought. Drought 

can be simply defined as “a lack of water” characteristic 

of time, not of place; or it can be defined in a climatic 

context, as “precipitation levels that are much lower 

than the annual average” (chapter 2). Chapter 2 

identifies four drought classifications: (1) meteorological 

drought which focuses on water in the atmosphere, (2) 

hydrologic drought which focuses on available surface 

water, (3) agricultural or soil moisture drought which 

emphasizes crop response to declining moisture in 

soils, and (4) socioeconomic drought which emphasizes 

the social and economic impacts of drought. These 

classifications emphasize the harmful impacts of 

drought, particularly on managed systems and people.

One of the most harmful droughts impacting American 

rangelands and farmlands was the drought of the 

1930s known as the Dust Bowl. Direct effects of the 

drought were both agricultural and socioeconomic; 

the drought caused damage to crops, livestock, and 

ultimately humans. The 1930s drought was several 

distinct events occurring in such rapid succession that 

affected regions were unable to recover adequately 

before another drought began. These severe, sequential 

droughts and the vast aerial extent the droughts 

covered, in combination with poor agricultural practices, 

overexpansion, and poverty associated with the Great 

Depression, made the 1930s drought period the most 

widely accepted “drought of record” for the United 

States (Hurt 1981, Warrick 1980). Reduced plant cover 

and increased bare ground led to dust storms (during 

high winds) and loss of topsoil. The resulting agricultural 

depression contributed to the Great Depression’s bank 

closures, business losses, increased unemployment, 

and other physical and emotional hardships. 

Many lessons in resiliency and adaptation were 

learned in response to the calamitous effects of the 

Dust Bowl. Proactive measures following the 1930s 

drought included increased conservation practices and 

irrigation, improved farming and ranching practices, and 

diversified regional economy. Other actions included 

new or enlarged reservoirs, improved domestic water 

systems, new insurance and aid programs, and removal 

of some of the most sensitive agricultural lands from 

production (Riebsame and others 1991). These learned 

strategies helped to reduce the region’s vulnerability to 

the negative impacts associated with drought.

With these adaptations, the likelihood of having a 

rangeland drought as catastrophic as the Dust Bowl has 

lessened substantially. Nevertheless, given the recent 

history, paleo-record, and recurring nature of drought 

and its relationship to climate change, it remains critical 

to understand the full range of its effects on natural and 

managed lands; to know techniques to reduce species 

and ecosystem vulnerability to drought; and to have 

information available that will assist in recovering natural 

and managed systems from the impacts of drought. 

High temperatures and lack of precipitation associated 

with the Dust Bowl would not only have affected crops, 

livestock, and people, they would also have affected 

native plants and animals, and they would have created 

water shortages—yet these ecological effects were not 

well-understood or reported at the time. Thus, while 

agricultural and socioeconomic classifications of drought 

have sharp bearing on rangelands and farmlands, 

they do not adequately encompass the ecological 

impacts of drought on native rangeland species, plant 

communities, and wildlife habitat. The direct and indirect 

consequences of severe and extended drought are 

complex, interactive, and numerous. There are a number 

of early ecological indicators that signal the impending 

possibility of serious agricultural and socioeconomic 

drought on rangelands, and they are important to 

understand and monitor. Listed sequentially, these early 

ecological indicators include: 

lWater shortages stress plants and animals

lVegetation production is reduced 

lPlant mortality increases

lPlant cover is reduced

lAmount of bare ground increases 

lSoil erosion become more prevalent 

lHabitat and food resources for wildlife are reduced 

lWildlife mortality increases
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lRangeland fires may increase 

lSome insect pests and invasive weeds may increase

lForage value and livestock carrying capacity 

decreases 

lEconomic depression in the agricultural sector sets in

To convey the full importance of drought impacts on 

rangelands in both natural and managed settings, our 

goals in this chapter are to describe: (1) the ecological 

history of rangeland drought, (2) the ecological 

consequences of drought to native rangeland species 

and ecosystems, (3) the effects of drought on natural 

disturbances, (4) the effects of drought on land 

management practices, and (5) the adaptive responses 

of ecosystems to drought. 

Types and Patterns 

of Rangeland Drought 

Droughts are of grave concern to policymakers, 

livestock producers, and the agricultural sector because 

droughts are among the most costly of disasters 

(Andreadis and others 2005), and they significantly 

impact numerous goods and services. Large-scale, 

persistent droughts have periodically occurred across 

North American rangelands and are not unusual 

(Andreadis and others 2005, Cook and others 2007, 

Weakley 1965). Dai and others (1998) suggest that 

trends in drought intensity over the past two to three 

decades derive from global warming. While severe, 

these conditions have not yet clearly exceeded drought 

severity in the 20th century (e.g., the Dust Bowl era) 

(Cook and others 2010). Similarly, a review of drought 

trends by Cook and others (2010) suggests that the 

Western United States has recently entered a period 

of protracted aridity; a perspective accentuated by the 

particularly troublesome, ongoing situations in Texas 

and California. The year 2011 was the single worst year 

on record for Texas with drought continuing into a third 

year. That year, wildfires in Texas burned 2.7 million 

acres along with 2,725 residential homes (National 

Interagency Fire Center; http://www.predictiveservices.

nifc.gov/intelligence/2011_statssumm/fires_acres.pdf, 

date accessed: October 15, 2015). Cattle sector losses 

were reported at $3.23 billion just for a single year 

(Amico and others 2011). 

The 2011 drought conditions in Texas are an example 

of “flash drought” when soils dry very rapidly. These 

events coincide with high temperatures, low cloud 

cover, low rainfall, and high winds. Because they 

generally occur during the growing season, flash 

droughts can be particularly devastating for agriculture 

and livestock grazing (Otkin and others 2013). 

Drought Trends and Regional Effects 

To understand long-term trends and impacts of drought 

over rangelands of the coterminous United States, we 

present trends from three sources including Parameterelevation Relationships on Independent Slopes Model 

(PRISM) project data (1982–2012), weekly drought 

maps from the U.S. Drought Monitor (2000–2013), and 

Normalized Difference Vegetation Index (NDVI) from 

the Moderate Resolution Imaging Spectroradiometer 

(MODIS) at 250-m2 spatial resolution (2000–2013). We 

wanted to illustrate the number of seasonal periods 

indicative of a drying landscape where seasonal or 

annual temperatures have been increasing while 

precipitation has been decreasing. Such an index is 

a practical way to assimilate large amounts of data 

for understanding impacts of changing climates on 

vegetation and other resources (Zargar and others 2011). 

In figure 8.1, warmer tones indicate increasingly 

restrictive growth conditions. Since 1982, the 

southern part of the United States has been exhibiting 

unfavorable trends in growing conditions resulting from 

warmer temperatures and decreasing precipitation. 

Relative to other western regions, much of Arizona, 

Texas, New Mexico, and the Oklahoma Panhandle 

exhibit the most notable decreasing trends in growing 

conditions. The reddish regions in north central New 

Mexico correspond with the massive dieoff (90 

percent) of pinyon pine (Pinus edulis) and illustrate 

the scale of vegetation change these conditions 

can induce (Breshears and others 2005). A loss of 

this magnitude of a long-lived, arid-adapted tree is 

attributed to persistent drought accompanied by 

warmer temperatures, resulting in greatly reduced soil 

moisture and water stress (Breshears and others 2005). 

Conversely, much of the upper Midwest and northern 

Great Plains have become wetter and slightly warmer, 

indicating improved growing conditions. It is worth 

noting that this type of climatic trend assessment will 

not usually capture the episodic or ephemeral droughts; 

those events are more appropriately captured in shorter 

timeframes, such as the weekly spatially explicit data 

from the U.S. Drought Monitor. 

Since 2000, there have been several significant events 

in which intense drought has enveloped western 
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Synthesized trends in 

temperature and precipitation: 

An indicator of long-term drought 

(1982–2012)

Trends in satellite derived NDVI:

Short-term indication of 

vegetation performance 

(2000–2013)

(B)

(A)

Change in growing conditions

-

+

< 180000 ha of rangelands

Change in vegetation abundance

-

+

< 180000 ha of rangelands

Figure 8.1—Drought intensity and effects on vegetation. Top panel (A) represents trends in gridded surface climatology from the 

Parameter-elevation Relationships on Independent Slopes Model (PRISM) project, 1982–2012. Warmer tones indicate areas where 

temperature has been increasing while precipitation has been decreasing; cooler tones represent improved growing conditions. 

Bottom panel (B) represents the trend of Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging 

Spectroradiometer (MODIS) at 250-m2 spatial resolution averaged over ecological subsections (Bailey and Hogg 1986), 2000–2013. 

Warmer tones indicate where vegetation abundance has been decreasing through time (i.e., a “browning” of the landscape), while 

cooler tones represent greater vegetation (i.e., a “greening”) of the landscape. (Maps created by Matt Reeves).
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rangelands (fig. 8. 2). Since 2011, the average area 

occupied by the most significant drought category 

(D4 in fig. 8.2) has more than doubled compared with 

2000–2010 records. The information in figure 8.3 was 

developed from weekly estimates of drought categories 

very similar to that represented in figure 8.2. Figure 8.2 

depicts the ongoing drought conditions over much of 

Texas and California. These drought episodes combined 

with longer term deterioration of growing conditions 

seen in other regions (fig. 8.1) have negatively affected 

the growth and abundance of rangeland vegetation. 

Because rangeland vegetation responds relatively 

quickly to changing meteorological conditions, it can be 

efficiently monitored using satellite remote sensing. 

Reeves and Baggett (2014) developed an algorithm 

for quantifying trends in MODIS 250-m2 NDVI for 

the United States. For this report, we evaluated 

vegetation types or U.S. Ecological Systems (Comer 

and others 2003) associated with negative vegetation 

trends since 2000. Table 8.1 indicates that many 

vegetation types have experienced declining trends 

on over 30 percent of the total area they occupy in 

the coterminous United States. Over 41 million ha of 

vegetation (~15 percent of all rangeland vegetation in 

the coterminous United States) (Reeves and Mitchell 

2011) has exhibited declining trends in abundance 

since 2000. From a regional perspective, vegetation 

has responded in a similar pattern as indicated by the 

PRISM climatology. Note the decline of rangeland 

vegetation abundance on the southern Great Plains 

area in addition to the marked declines in the central 

California region (fig. 8.1). Although drought events in 

California in the 20th century were less frequent than 

previous patterns, there have been a number of recent 

drought episodes of significance to natural systems 

and socioeconomic well-being (Hughes and Brown 

1992). At least three drought years (2000, 2002, 2008) 

occurred in the Southwestern United States during the 

2000s, making the early 21st century the driest period 

in several centuries (Cayan and others 2010). Even 

more recently, California has been in drought since 

2012, with record dry years reported and the majority 

of the State in extreme or exceptional drought as of 

the spring of 2014 (see fig. 8.2) (U.S. Drought Monitor 

report http://www1.ncdc.noaa.gov/pub/data/cmb/sotc/

drought/2014/04/20140429_usdm.jpg. Date accessed: 

April 29, 2014). The climatological index derived here 

using PRISM data does not reflect the recent drought 

episodes in California, due to the relatively longer 

time period of the climate data compared with the 

recentness of the drought period. This illustrates the 

need to include a variety of data sources over multiple 

time periods to more completely understand drought 

effects on vegetation and other resources. 

Variability in North American Drought 

Over Time: The Paleo-Record

Recurrent drought is to be expected with frequencies 

in sync with the phenomena that drive fluctuations 

in climate across broad spatial and temporal scales 

(Herweijer and others 2007). Droughts vary across 

time (frequency and duration), space, and severity in 

rangelands and other ecosystems. An understanding of 

the full range of natural variability in each dimension is 

needed to provide context for assessing the “normality” 

of historic drought in rangelands relative to past 

events and for projecting the novelty of future climatic 

conditions.

Consistent characterization of a drought or series of 

droughts is dependent upon selection of appropriate 

metrics that remain consistent across time and space. 

Instrumental meteorological data are sufficiently 

D4 Exceptional drought 

D3 Extreme drought

D2 Severe drought

D1 Moderate drought

D0 Abnormally dry

None

0

10

20

30

40

50

60

70

80

90

100

200020012002200320042005

2006

2007200820092010

2011

201220132014

Average weekly proportion (percent)

Year

Figure 8.2—Drought categories derived from annualized U.S. 

Drought Monitor maps (weekly), 2000–2014 in the coterminous 

United States. Data courtesy of the U.S. Department of 

Agriculture (USDA) and the National Oceanic and Atmospheric 

Administration (NOAA). The y-axis represents the annual 

average of weekly proportion of land in each drought category. 

So, for the year 2000, averaged over 52 data points (weeks), 

about 50 percent of lands experienced “none”, i.e., no drought. 
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Figure 8.3—These data represent drought categories for the week of May 6, 2014. Notice the exceptional drought category in 

central California and northern Texas. Data courtesy of the U.S. Department of Agriculture (USDA) and the National Oceanic and 

Atmospheric Administration (NOAA). 
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Table 8.1—Breakdown of the top 20 U.S. Ecological Systems exhibiting negative 

trends in vegetation performance since 2000

Ecological System

Negative

NDVI

area 

(ha)

Area in 

declining 

trend 

(percent)

Tamaulipan Mixed Deciduous Thornscrub 225,588 56

California Annual Grassland 1,942,520 43

Tamaulipan Calcareous Thornscrub 604,070 41

South Texas Sand Sheet Grassland 434,402 40

Tamaulipan Mesquite Upland Scrub 3,460,482 37

Western Great Plains Mesquite Woodland and Shrubland 7,058,207 35

Edwards Plateau Limestone Shrubland 4,141,955 35

Southern California Coastal Scrub 938,878 33

Tamaulipan Savanna Grassland 634,618 33

Central Mixedgrass Prairie 8,473,944 32

Central and Southern California Mixed Evergreen Woodland 646,718 32

Sonora-Mojave Semi-Desert Chaparral 425,250 32

Western Great Plains Sandhill Steppe 3,782,085 30

Southern California Oak Woodland and Savanna 253,198 29

Chihuahuan-Sonoran Desert Bottomland and Swale Grassland 174,880 29

Western Great Plains Shortgrass Prairie 16,499,262 28

California Mesic Chaparral 1,220,700 27

Western Great Plains Foothill and Piedmont Grassland 256,282 26

Southern California Dry-Mesic Chaparral 837,099 25

Sonora-Mojave Mixed Salt Desert Scrub 352,823 24

NDVI = Normalized Difference Vegetation Index.
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consistent but lack temporal depth for long-term 

analysis. Historic documents extend the record for 

North American drought by a few centuries, but have 

major spatial and temporal gaps. In addition, these 

records are largely subjective and difficult to quantify, 

rendering them of limited value by themselves for 

analyzing large-scale patterns of variability. During the 

Holocene (last 10,000+ years), western North America 

experienced multi-century episodes when conditions 

were consistently drier than the present. Examples 

include the mid-Holocene warm period lasting from 

7,500–6,000 years before present (YBP) (Benson and 

others 2002, Grayson 2011) and a late-Holocene period 

of persistent drought that occurred in the central Great 

Basin (but not further north) from about 2800 to 1850 

YBP (Mensing and others 2013). The later dry period 

was characterized by drops in lake levels, shifts to more 

xeric-adapted vegetation, an upward shift in upper tree 

line, and increased alluvial fan aggradation; collectively, 

those changes have been attributed to conditions that 

were warmer and drier than present. 

Numerous studies have used tree-ring-based 

reconstructions of the Palmer Drought Severity Index 

(PDSI) (Cook and others 1999, 2004; Herweijer and 

others 2007) and other supportive data to compare 

the severity, duration, and spatial patterns of historical 

drought to those that occurred during the last 2,000 

years. Long-term reconstructed streamflow for the 

Potomac (Maxwell and others 2011) and the Colorado 

Rivers (Meko and others 2007) reveal more severe and 

longer lasting droughts prehistorically than those known 

from 20th century instrumented records. Analyses of 

paleo-drought from the Central United States using 

multiple proxies (Woodhouse and Overpeck 1998) and 

continental-scale studies (Herweijer and others 2007) 

using tree-ring reconstructions of PDSI suggest that 

megadroughts during the Medieval Climate Anomaly 

(MCA), also known as Medieval Warm Period, were of 

similar severity but longer duration (20–40 years) and 

possibly greater spatial extent than those of the 20th 

century. Temporal analyses identified climate cycles at 

interannual to centennial scales (Herweijer and others 

2007, Meko and others 2007, Stambaugh and others 

2011). Herweijer and others (2007) determined that 

the central and western regions of the continent had 

the highest climate variability, and the Central and 

Southwestern United States were drought centers 

with highest drought activity over time. Drought spatial 

patterns supported a strong linkage of drought to the El 

Niño Southern Oscillation (ENSO) of Pacific sea surface 

temperature (SST), and this and other studies (Cole and 

Overpeck 2002, Cook and others 2004, Stahle 

and others 2000) suggest a persistent La Niña-like phase, 

unlike any observed in recent centuries, may have been 

responsible for prolonged drought events in the past. 

Collectively, these studies indicate that 20th century 

measures of climate, including drought, represent only a 

subset of the full range of conditions experienced in the 

past as a result of natural variation. Although drivers and 

feedback mechanisms are not fully understood, there 

is sufficient indication from past climate records and 

future projections to prioritize development of effective 

strategies for coping with the consequences of more 

frequent, more severe, and longer drought, especially 

in central and western regions of North America where 

water resources are already scarce.

The Future of Drought on Rangelands

Although it is difficult to model a detailed picture 

predicting the occurrence and extent of future drought, 

it is clear that higher temperatures will increase severity 

of drought episodes when they occur. Drought in 

North America appears to be strongly related to Pacific 

Ocean SSTs and is sensitive to even small temperature 

changes (Cayan and others 2010). Change in SSTs 

induced the recent severe drought in California, 

2013–2014, and the associated circulation patterns 

were intensified— perhaps even created—by global 

warming (Wang and others 2014). Higher temperatures 

will reduce soil moisture critical to plant productivity, 

species composition, and erosion potential (Polley 

and others 2013). Models of net primary productivity 

predict overall better growing conditions for the 

northern Great Plains, while the opposite is true of the 

southern Great Plains (Polley and others 2013, Reeves 

and others 2014). Trends indicated by PRISM and NDVI 

data may continue with persistent and increasing aridity 

for the southern Great Plains and central California 

(figs. 8.1 and 8.2). Cayan and others (2010) predict 

droughts in this century will extend for periods of time 

of ≥12 years in the Southwest, which will severely tax 

already limited water supplies (Foti and others 2012). 

More frequent drought episodes interspersed with 

fewer episodes of higher-than-average rainfall indicate 

vegetation in the Southwest may not recover to what is 

currently considered a typical or average state (Seager 

and others 2007).

Although the future of SST patterns is uncertain, 

warmer temperatures will exacerbate any deficit in 

soil moisture, and several studies point towards more 

frequent and severe drought along with large-scale 
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ecological change for the future (Breshears and 

others 2005, Cayan and others 2010, Cook and 

others 2007). Drying may be particularly pervasive in 

the Southwestern United States, northern Mexico, 

and the interior West (Andreadis and Letternmaier 

2006, Seager and others 2007). California can expect 

continued intensification of drought episodes (Wang 

and others 2014). 

Drought severity has not increased recently in other 

regions of the United States, including the northern 

Great Plains; this indicates that although these 

regions will still be subject to periodic drought, they 

may be better able to recover after drought episodes 

under current management practices (Andreadis and 

Letternmaier 2006, Clark and others 2002). Of particular 

interest to the sustainability of ecosystem services 

are megadroughts—spanning decades rather than 

years, they are unprecedented for our recorded history, 

and thus not integrated into disaster preparedness or 

resource contingency plans (Cook and others 2010). It 

is unclear if global change will induce megadroughts or 

not, but predicted warmer temperatures and unchanged 

or declining precipitation across rangelands could induce 

negative, persistent impacts. 

Effects of Drought 

on Rangelands

This section reviews how drought influences water 

availability, soil moisture, and plant physiology, as well 

as plant growth, abundance, and productivity, vegetation 

changes, and wildlife habitat.

Water Availability, Soil Moisture, 

and Plant Productivity

Soil moisture is affected by a number of factors in 

addition to the amount of annual precipitation. Soil 

recharge is heavily influenced by the season, timing, 

and amount of precipitation events. Event size, number 

of events, and length of time between events influence 

vegetation in different ways (Lauenroth and Sala 

1992). In hot summer months, moisture is quickly lost 

through evaporation from the soil surface and vegetative 

transpiration. In winter, evaporation and transpiration are 

reduced, allowing moisture to accumulate and infiltrate 

to deeper soil levels (Weltzin and others 2003). Cooler 

summer temperatures may explain the observation of 

decreased interannual variability in grass production 

in northern regions as compared with hotter southern 

regions (Sala and others 1988). Infiltration from gentle 

rains of long duration is most effective at recharging 

soil profiles. Infrequent, small precipitation events may 

wet only the soil surface, where moisture is quickly 

lost through evaporation. Lauenroth and Sala (1992) 

reported that a precipitation event of at least 15–30 

mm was necessary in order to wet those soil layers 

that have largest effect on production. High-intensity 

summer storms may result in sheet runoff, with most 

infiltration occurring in lower lying areas. Dry, bare 

ground can take nearly three times longer to rewet than 

vegetated areas (Weaver and Albertson 1943). 

Vegetative growth and reproduction is ultimately and 

directly linked to soil moisture. Multiple studies have 

reported a direct correlation between aboveground 

net primary production (ANPP) and mean annual 

precipitation (Briggs and Knapp 1995, Haddad and 

others 2002). Variability in annual rainfall may affect 

productivity more in grasslands than in all other 

biomes of North America (Knapp and Smith 2001). 

An analysis of 9,500 sites across the Central United 

States confirmed the tremendous importance of water 

availability to plant productivity (Sala and others 1988). 

Regional patterns in ANPP were correlated with an 

east-to-west gradient in annual precipitation. Production 

levels during years of drought were observed to shift 

eastward, with high production levels restricted to 

the more mesic eastern plains. Vicente-Serrano and 

colleagues (2013), using satellite imagery for the 

continental United States, also found a direct correction 

between precipitation and ANPP. 

Plant Physiological Responses to Drought

The consequences of drought on plant physiological 

functioning can vary depending on the duration and 

severity of the drought. When droughts occur, critical 

edaphic variables such as soil moisture, temperature, 

and vapor pressure deficit (VPD) are affected and have 

impacts on plant physiological functioning. Of largest 

consequence for grassland plants is the reduction in 

soil water content, which leads to plant moisture stress 

and possibly mortality (Poirier and others 2012). This 

is because the critical link between desiccation and 

carbon gain (or starvation) is regulated through plant 

stomata, where fluxes of carbon dioxide (CO2) and 

water vapor share the same pathway. The longer plants 

can withstand desiccation, the better their prospects for 

drought survival and recovery (Larcher 2003). 

Drought, to varying degrees, will impact plant available 

moisture in the soil profile (James and others 2003). 

For periods of short drought duration, large deficits 

in plant available water may occur at the soil surface; 
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conversely, deeper in the soil profile, plant available 

water may be higher. As droughts lengthen in duration 

and become more severe, deeper soil moisture 

reserves will also decrease. These spatial and temporal 

differences are critical for short- versus long-rooted 

species as well as their strategies for avoiding or 

tolerating drought effects (Kozlowski and Pallardy 1997, 

Larcher 2003).

As drought severity increases and water availability 

decreases for perennial grassland species, a number of 

ecophysiological strategies can be employed to prevent 

mortality (fig. 8.4) (Volaire and others 2014). Growth 

maintenance, dehydration delay, dehydration tolerance, 

and dormancy strategies work on a continuum from no 

drought to severe drought, respectively. From a whole 

plant perspective, low-to-moderate drought stress may 

still allow some leaf and root growth, albeit reduced. 

These low soil moisture conditions are often linked to 

reduced stomatal conductance and photosynthesis 

(Milbau and others 2005). From this, corresponding 

shifts in carbon allocation patterns emerge: leaf growth 

is reduced, followed later by reduced root growth, while 

carbon reserves may increase. As drought conditions 

increase, leaf senescence is employed to reduce 

transpirational surface area. Eventually, extreme drought 

stress will cause irreversible damage to the protoplasm, 

leading to leaf and tiller mortality.

Shrub species in grasslands employ similar strategies 

to endure drought conditions. Dehydration delay and 

the control of transpiration during drought are critical for 

maintaining water balance in woody species. Kozlowski 

and Pallardy (1997) list five adaptations to reduce 

Leaf growth

Leaf senescence

Photosynthesis

Carbon reserves

Leaf turgor

Root growth

Carbon reserves

Dehydrins

Membrane stability

Growth maintenance

Dehydration delay

Dehydration tolerance

Summer dormancy

Tissue hydration

MERISTEMS

STRATEGIES

WHOLE PLANT Lamina mortality

Tiller mortality

None Low Moderate High Severe drought

100

0

0

0

0

0

0

0

0

Figure 8.4—Perennial grass whole plant and meristem responses and ecophysiological strategies 

to increasing drought. Volaire and others (2014).
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transpiration: (1) reduced capacity for growth, (2) reduced 

leaf size and altered morphology, (3) leaf abscission, (4) 

cuticular effectiveness, and (5) stomatal control. Kolb and 

Sperry (1999) found that these adaptations are similarly 

employed by different subspecies of big sagebrush 

(Artemesia tridentata) across elevation and precipitation 

gradients of the Great Basin of North America. However, 

their ability to withstand dry conditions and preserve 

hydraulic functioning varied. The subspecies from an 

arid locale showed greater resistance to xylem cavitation 

(50-percent loss) than subspecies from mesic conditions. 

In some cases, plants are known to acclimate to drought 

conditions through repeated exposure (Bruce and others 

2007). In Mediterranean shrubs, two species showed 

differences in photosynthesis and water-use efficiency 

from repeated drought and re-watering cycles, with one 

species showing much better photosynthesis recovery 

and improved water-use efficiency (Galle and others 

2011). Grass has also shown acclimation to drought 

repetition with improved photoprotection, yet plants still 

experience an overall reduction in photosynthesis (Walter 

and others 2011). The mechanisms by which “stress 

imprints” occur are still largely under investigation. 

Drought-stress recovery will no doubt vary by species 

and degree, but the critical question is whether 

grassland species have the capacity and resiliency for 

the potentially repeated and worsened events caused by 

climate change (Scheffer and others 2001).

Effects of Drought on Vegetation

Climate instability and recurrence of extreme events 

can have a more profound effect on vegetation than 

do changes in average conditions (Weltzin and others 

2003). Climate of the 20th century and early 21st 

century has been highly variable, exhibiting fairly 

rapid shifts between wet and dry periods that vary 

geographically (Grissino-Mayer and others 2002). This 

period has been marked by several large-scale droughts 

as well as several more local short-term droughts. The 

Great Plains experienced the unprecedented Dust 

Bowl drought of the 1930s. New Mexico experienced 

its worst multiyear drought between 1945 and 1963 

(Betancourt and others 1993, Swetnam and Betancourt 

1998), known as the 1950s drought. This drought 

extended from southern Arizona north to the Colorado 

River Basin, and east to western Texas and some 

parts of the Southeast. In 1985, there was a largescale drought throughout much of the West, whereas 

the central and eastern portions of the United States 

experienced large-scale drought in 1988 (Kogan 1995). 

The effects of drought are cumulative. The longer a 

drought persists without water recharge, the greater the 

severity. Using a standardized precipitation index, McKee 

and others (1993) reported that the single worst drought 

of the 20th century was that of the 1950s, whereas four 

consecutive droughts of shorter duration combined to 

produce the exceptional water deficits of the 1930s. 

Vegetation response to historic drought—The 

great drought of the 1930s resulted from the combined 

effects of widespread cultivation of the soil and 

overgrazing brought on by the post-war demand for 

meat, and it was exacerbated by 6 preceding years 

of below average precipitation and high temperatures 

(Albertson and Weaver 1942). Average precipitation 

was 33–39 percent below normal, with most of the 

deficit occurring during the growing season. High 

winds whipped the dry, friable soil particles, creating 

enormous dust storms and smothering vegetation with 

thin blankets or deep drifts of silt. 

Albertson and Weaver (1942, 1944) documented 

vegetation response and recovery from the drought over 

an 11-year period from 1933 to 1943 at locations near 

Hays, KS. Grasses and forbs died as deeper soil layers 

were depleted (Weaver and Albertson 1943). Basal area 

of little bluestem (Andropogon scoparius) declined 78 

percent between 1932 and 1939, disappearing entirely 

from many areas, with little recovery exhibited by 1944 

(Albertson and Weaver 1944). Hillsides dominated 

by little bluestem converted to more drought-tolerant 

sideoats grama (Bouteloua curtipendula) and shortgrass 

species. Uplands dominated by buffalograss (Buchloe 

dactyloides) and blue grama (Bouteloua gracilis) 

declined in cover, but recovered with only slight shifts 

in dominance. Big bluestem (A. gerardii), decreased 

79 percent in cover between 1932 and 1939, but 

did survive and later reestablished. Bare areas 

gradually recovered to shortgrass prairie dominated by 

buffalograss and blue grama. Species that reproduce 

vegetatively or those having deeper root systems 

were more resilient to drought. The overall result 

was a long-lasting shift in species composition: loss 

of little bluestem and an increase in grama grasses, 

buffalograss, and wheatgrass (Agropyron smithii). 

The 1930s drought extended far beyond the southern 

plains. Sagebrush steppe of the upper Snake River 

Plain experienced several periods of severe drought. 

The summer of 1934 was the driest on record, 

accompanied by high temperatures and strong winds. 

The preceding years had also been drier than normal 

(Pechanec and others 1937). Shrub density, mostly of 
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sagebrush (Artemisia spp.), decreased to 46.8 percent 

of that present in 1932; the decrease was caused by 

dieback or death of whole plants. Basal area of perennial 

grasses declined 60 percent. The disintegration and 

death of grass clumps continued well into 1935 despite 

favorable conditions. Anderson and Inouye (2001) 

monitored vegetation at a similar location in the Snake 

River Plain between 1950 and 1975. Perennial grass 

cover increased from 0.5 percent in 1950 to 6.2 percent 

in 1975. Shrub cover, dominated by big sagebrush 

(Artemisia tridentata), increased from 17 percent in 

1950 to 25 percent in 1975, although a subsequent 

drought during the late 1970s resulted in substantial 

mortality of big sagebrush. The authors postulated that 

high rainfall years can set up species for death when 

followed by sudden drought. They further noted that a 

lag time can occur between the resumption of normal 

rainfall and the response of vegetation. The presence 

of a lag time before vegetative recovery has also been 

noted by others (Ji and Peters 2003).

Ellison and Woolfolk (1937) documented the effects of 

a sustained drought near Miles City, MT, that peaked in 

1934; this drought was aggravated by above-average 

temperatures and preceding years of below-normal 

precipitation. They documented substantial death of 

pine, juniper, and cottonwood, but also noted declines 

in sagebrush and other species. All shrubs experienced 

considerable dieback. Grass cover was reduced by up 

to 79 percent depending on the species. Effects of 

the drought were multiyear despite a favorable season 

in 1935. Needle-and-thread grass (Stipa comata) 

and Sandburg bluegrass (Poa secunda) were able to 

recover relatively quickly, despite mortality, through 

the establishment of new seedlings. Stands of big 

sagebrush experienced considerable mortality and did 

not regenerate, whereas silver sagebrush (A. cana) was 

able to resprout from the base. 

Reports from other droughts also document large 

reductions in perennial grass cover, as well as shifts 

in plant community composition. Lauenroth and Sala 

(1992) found that 39–45 percent of the interannual 

variation in forage production over a 52-year period in 

north-central Colorado was explained by precipitation. 

Tilman and El Haddi (1992) reported an initial 

47-percent decrease in plant biomass due to the 1980s 

drought. While biomass did recover within 2 years, 

species richness did not. Hobbs and others (2007) 

observed considerable changes in individual species’ 

abundance over a 20-year study 

in response to variation in rainfall amounts. Species 

richness also varied with precipitation. Morecroft and 

others (2004) recorded an approximate 50-percent 

reduction in vegetative cover in response to a drought 

occurring from 1995 to 1997. The relative proportion 

of vegetation also changed from one dominated by 

perennial grasses to one dominated by ruderal forbs. In 

a drought manipulation experiment, Evans and others 

(2011) found that 11 years of drought resulted in large 

reductions in total cover and cover of the dominant 

species, but significant differences did not emerge 

until the fourth and seventh year of drought.

Mechanisms of vegetation change—Ecosystems 

differ in their response to drought (Knapp and Smith 

2001). On a biome scale, vulnerability to drought is 

thought to be greater in more humid regions, such 

as tallgrass prairie, where drought has historically 

occurred less frequently. Vegetation of arid and semiarid 

regions is more resilient to drought, as many species 

are adapted to water shortage. The response of the 

dominant vegetation may depend on the average timescale at which drought typically occurs (Vicente-Serrano 

and others 2013). Seasonality of precipitation also 

affects ecosystems differently. In the southern Great 

Plains, precipitation during the summer growing season 

had the greatest effect on productivity (Albertson and 

Weaver 1942, 1944; Pechanec and others 1937). In the 

Great Basin and regions northward, accumulation of 

winter snow recharges soil moisture, resulting in a flush 

of spring growth.

Individual plant species also differ in their ability to 

tolerate and recover from drought. Deep-rooted species, 

such as big bluestem, can persist through longer periods 

of drought provided the deeper soil layers were moist 

to begin with (Albertson and Weaver 1942, Fay and 

others 2003, Morecroft and others 2004). An ability to 

reproduce vegetatively through resprouting, tillering, or 

the production of rhizomes or stolons, may also increase 

a plant’s ability to recover from drought (Albertson and 

Weaver 1942, Pechanec and others 1937). Dominant 

species in wet areas may not tolerate drought well 

(Swemmer and others 2007). Plants of more arid regions 

have many adaptations for coping with moisture deficits. 

Small leaves, thick cuticles, sunken stomates, trichomes, 

or photosynthetic stems limit the amount of water vapor 

lost through evapotranspiration. Avoidance adaptations, 

such as drought-deciduous leaves or an annual habit, limit 

periods of photosynthesis to the most favorable times of 

year (Rundel and Gibson 1996).
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Plants differ in their depth of rooting as well as in root 

morphology, both of which affect their ability to take up 

water from different soil layers (Ehleringer and others 

1991, Schwinning and Ehleringer 2001, Walter 1971 

as cited in Schwinning and others 2005). Grasses with 

shallow fibrous roots can extract water rapidly after a 

pulse event, but they are also the first to run out of water 

as soils dry (Schwinning and others 2005). Species 

with taproots can take up water from deeper levels and, 

consequently, are able to take up water during longer 

periods of drought. Many dominant shrubs, including 

juniper, have an extensive shallow root system in addition 

to roots that can penetrate to several meters in depth 

(Krämer and others 1996, Lin and others 1996). This 

allows them to exploit moisture from multiple soil depths, 

giving them an advantage over herbaceous root systems 

during drought. Reynolds and others (2000) postulated 

that such water resource partitioning can only occur 

when annual precipitation exceeded a certain threshold. 

Otherwise, soil recharge was not sufficiently deep to 

allow extraction from deeper soil layers. 

Variability in species responses to drought can help 

to buffer productivity. Although species richness 

often declines during periods of drought (Cleland and 

others 2013, Hobbs and others 2007, Tilman and El 

Haddi 1992), plots with greater diversity have been 

reported to be more stable over time (Hobbs and others 

2007). Cleland and others (2013) suggest that a large 

regional species pool can buffer site-level diversity 

from variation in climate. Known as the insurance 

hypothesis, this hypothesis states that differential 

species’ responses to environmental change allow for 

functional compensation, as individual species come 

and go. Overall plant cover can then be maintained 

despite variations in species makeup (Yachi and Loreau 

1999). Rates of species turnover are higher in dry areas, 

largely as a function of rare or annual species (Cleland 

and others 2013, Morecroft and others 2004, Tilman 

and El Haddi 1992).

A lag in plant recovery response after drought, even 

when precipitation is good, has been noted by a number 

of researchers (Ellison and Woolfolk 1937, Ji and Peters 

2003, Lauenroth and Sala 1992, Pechanec and others 

1937) and may result from a number of reasons. Plants 

may need to build up reserves before expending energy 

on renewed growth. A 2-year lag may result as seed is 

matured during the first good year followed by a year 

of recruitment. Many arid land species have inherently 

low growth rates, requiring substantial amounts of time 

before cover is restored to pre-drought levels.

Plant productivity and nutrient cycling—Another 

potential reason for reduced productivity in years 

following drought is due to changes in nutrient cycling. 

Haddad and others (2002), working in tallgrass prairie, 

followed plant production and diversity over an extended 

period that included a 2-year drought. Production was 

stable for 5 years preceding the drought, then oscillated 

on a 2-year cycle for 9 years after the drought. They 

concluded that the drought-induced oscillation was 

related to nutrient resources. In mesic systems, carbon 

and nitrogen cycling are coupled through production 

and decomposition of organic matter because water 

is available for plant and decomposer metabolism. In 

more arid systems and under drought conditions, these 

cycles become decoupled and nutrients accumulate 

until moisture is sufficient to reactivate biogeochemical 

processes (Asner and others 1997, Austin and others 

2004, Evans and Burke 2013). 

The loss of herbaceous cover due to drought can result 

in a substantial increase in soil erosion by both water 

and wind, with an accompanying loss of soil nutrients 

(Li and others 2007, Okin and others 2001, Schlesinger 

and others 2000). Grasses, in particular, help to bind 

together soil particles of the upper horizon (Worster 

1982). The more sparsely distributed woody species 

are generally ineffective in reducing wind erosion 

compared with grasses (Li and others 2007). Erosion 

by wind differentially removes finer soil particles that 

contain more of the soil nutrients, resulting in a coarser, 

less fertile soil (Hennessy and others 1986, Leys 

and McTainsh 1994). Blowing dust redistributes soil, 

denuding some areas while killing plants by burial or 

abrasion (Okin and others 2001). 

Biological soil crusts—Where vegetation is sparse, 

interspaces in rangelands are often colonized by 

biological soil crusts (BSCs), a group of organisms 

consisting of algal filaments, lichens, and mosses that 

bind surface soil particles together, reducing wind 

erosion (Belnap and Gillette 1997, Williams and others 

1995). BSCs occur from the Columbia River Basin, 

south through the Great Basin and Colorado Plateau 

to the southern Mojave, Sonoran, and Chihuahuan 

Deserts, and from California chaparral east to the Great 

Plains. Smooth crusts composed of cyanobacteria 

and green algae dominate in hot desert sites, with 

lichen and moss cover increasing northward to the 

less arid conditions of the Great Basin and Columbia 

River Basin (Rosentreter and Belnap 2003). Crusts 

of those areas with colder winters are pinnacled or 

gently rolling in topography. In the Great Plains, BSCs 
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are most abundant in short-grass steppe and consist 

mostly of green algae and cyanobacteria, along with 

vagrant lichens that roll about, unattached to the soil. 

The highly pinnacled crusts of the Colorado Plateau 

are composed of cyanobacteria, with up to 40-percent 

cover of lichens and mosses. Many crust species are 

ubiquitous and can be found throughout the Western 

United States. Others are adapted to a specific range 

of temperatures or to certain substrates, such as 

calcium carbonate or gypsum (Rosentreter and 

Belnap 2003). 

Biological soil crusts fix both carbon and nitrogen, 

adding to fertility of the soils. They also increase soil 

surface roughness, thereby increasing the capture of 

nutrient-rich soil fines (dust) and water-holding capacity 

of the soil (Belnap 2003). The organisms comprising 

soil crusts are only metabolically active when wet 

and are highly responsive to temperature (Belnap 

2003, Stradling and others 2002). Most are adapted 

to withstand extended periods of high heat with little 

or no water by suspending all metabolic processes. 

However, prolonged periods of drought can effectively 

starve soil crust organisms, increasing the incidence 

of mortality. Lichens and mosses are particularly 

vulnerable, and the resulting crust composition is 

simplified, mimicking an earlier successional state 

(Belnap 2003). The timing of precipitation events also 

has an impact on crust function. Small, frequent events 

during periods of high temperature means that crusts 

dry quickly, resulting in less carbon available to produce 

or repair protective pigments and a loss of lichen cover 

and richness (Housman and others 2006). Conversion 

of soil crusts back to early successional stages results 

in large reductions of carbon and nitrogen inputs into 

the ecosystem (Housman and others 2006), which 

can affect plant growth and competitive interactions. 

Recovery rates from early to later successional stages 

is thought to be on the order of decades or centuries, 

depending on the amount of effective precipitation 

(Belnap 2003). Recovery, if it occurs, would be 

significantly slowed under extensive drought conditions. 

Loss of soil crusts would result in increased rates of 

wind erosion, blowing dust, and soil deposition similar 

to that described earlier. 

Effects of Drought on Wildlife 

and Wildlife Habitat

Wildlife habitat occupancy is typically associated with 

structural characteristics of rangeland vegetation 

communities (Rotenberry and Wiens 1980, Wiens 

and Rotenberry 1985). Precipitation is the primary 

cause of variability in grasslands (Wiens 1974), and 

structure and production of herbaceous vegetation is 

reduced during drought and can lag behind recovery 

of the precipitation (Laurenroth and Sala 1992). Height 

and density of herbaceous vegetation (structure) 

is strongly related to biomass (Benkobi and others 

2000). Drought and grazing alter plant community 

composition and habitat structure. These vegetation 

changes influence positive and negative responses 

of wildlife (Benkobi and others 2007, Knowles 1986, 

Uresk 1990). For example, black-tailed prairie dog 

towns expand when vegetation cover and biomass 

decrease (Cincotta and others 1988, Uresk 1987), 

whether influenced by grazing or drought. Severe 

drought in North Dakota resulted in significant declines 

of a number of grassland-nesting bird species owing 

to nest abandonment, reduced nesting success, 

and a truncation of the nesting season in mid-June 

(George and others 1992). In early seral communities, 

small mammals and birds that prefer low vegetation 

structure and bare ground are more abundant, whereas 

those that prefer taller vegetation and litter are more 

abundant in higher seral vegetation communities 

(Agnew and others 1986, Fritcher and others 2004). 

Thus, sustained drought would shift bird and small 

mammal communities to favor those associated with 

early seral habitats. In prairie woodlands, drought and 

grazing reduce regeneration of trees and shrubs (Uresk 

and Boldt 1986), which in turn alters the bird and small 

mammal communities (Rumble and Gobeille 1998, 

2001, 2004) toward species associated with early seral 

vegetation. Shrub-nesting bird populations may lag in 

response to loss of herbaceous understory vegetation 

if the shrub structure remains (Wiens and Rotenberry 

1985).

Most, if not all, birds feed on or consume insects when 

the physiological needs of reproduction or early growth 

of young are high. Insect abundance is highly related 

to biomass of herbaceous vegetation (Healy 1985, 

Ramobo and Faeth 1999, Rumble and Anderson 1997, 

Wenninger and Inouye 2008). The amino acids that 

occur in birds reflect those of the insects they consume 

(Hurst and Poe 1985)—they are what they eat. Birds 

that are not able to consume enough insect protein 

do not develop properly or die (Johnson and Boyce 

1990). Abundance and biomass of insects in southcentral Wyoming exhibited significant correlations with 

grass and forb cover.1 Drought in 2012 affected nest 

1 Personal communication. Mark Rumble, Research Wildlife Biologist, 

U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station, Rapid City, SD 57702. 
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productivity and chick survival of greater sage-grouse 

(Centrocercus urophasianus) (Schreiber 2013) and 

insect abundance was significantly lower than in 2011 

when nest productivity and chick survival was greater. 

Lek counts in south-central Wyoming made each year 

from 2011 through 2013, showed approximately a 

15-percent decline in the maximum male attendance 

the year following the drought of 2012 (see footnote 1). 

Low precipitation and high temperatures had negative 

effects on recruitment, survival, and population growth 

of sage-grouse populations in Nevada (Blomberg and 

others 2012), and precipitation the preceding spring 

influenced sage-grouse nesting success (Holloran and 

others 2005). Vegetation responses to precipitation 

(e.g., taller grass) is associated with greater nest 

success of sage-grouse (Herman-Brunson and others 

2009, Holloran and others 2005, Kaczor and others 

2011a) and is selected for by sage-grouse broods 

(Kaczor and others 2011b). Brood success of sagegrouse is associated with greater insect abundance and 

vegetation communities with high cover of herbaceous 

vegetation (Harju and others 2013). 

Increased prevalence of severe drought increases 

the chances that local sage-grouse populations are 

extirpated (Aldridge and others 2008). Drought also 

tends to concentrate sage-grouse around water where 

they may be susceptible to West Nile Virus (Naugle 

and others 2004). Sage-grouse are not unique in 

their response to drought. Gambel’s quail (Lophortyx 

gambellii) populations fluctuate considerably in direct 

response to increases and decreases in precipitation 

and in response to food availability from forb seeds 

(Gullion 1960). Pheasant populations in South Dakota 

demonstrate a quadratic relation to precipitation; low 

populations are associated with drought and extremely 

wet conditions (Runia 2013). Regions of South Dakota 

where the 2012 drought was considered exceptional or 

extreme showed population declines of 12–13 percent, 

whereas populations in regions where drought was 

moderate to severe only declined 2 percent (Runia 

2013). Plains sharp-tailed grouse (Tympanuchus 

phasianellus jamesi) populations also decline in 

association with heat stress and low precipitation during 

June (Flanders-Wanner and others 2004), and it has 

long been known that nesting success by sharp-tailed 

grouse increases when height-density of grassland 

vegetation increases from 5 to 20 cm (Prose 1987).

Drought Interactions 

With Other Disturbances 

and Stressors 

Grasshopper Outbreaks

Rangeland and grassland ecosystems worldwide are 

prone to periodic outbreaks of native insect herbivores. 

The most common and noticeable insect outbreaks 

in western North America involve grasshoppers 

(Orthoptera), which contribute significantly to the 

structure and function of grasslands and other 

rangelands (Branson and others 2006). Grasshopper 

outbreaks can have severe economic impacts on the 

grazing industry, especially during periods of drought 

when available forage is already scarce (Hewitt and 

Onsager 1983). Climate, especially drought, is thought 

to play a key role in outbreaks of grasshoppers and 

other insect species on rangelands, but the underlying 

mechanisms are poorly understood (Capinera and 

Horton 1989, Gage and Mukerji 1977, Kemp and 

Cigliano 1994, White 1976). Drought can have both 

direct effects on the growth and survival of insects and 

also indirect effects via changes in food quality and 

susceptibility to disease.

Non-severe drought and warm temperatures generally 

have a positive effect on grasshopper populations. 

Warm, dry weather in winter and early spring can 

lead to increased survival, early egg hatch, and faster 

population growth; warm, dry weather in the fall can 

extend the life of females and allow them to produce 

and lay more eggs (Joern and Gaines 1990, Kemp 

and Sanchez 1987). Moreover, grasshoppers often 

prefer to feed on drought-stressed plants, partly due to 

drought-induced changes in plant chemistry (Bernays 

and Lewis 1986, Haglund 1980, Lewis 1982). Drought 

could further promote grasshopper populations by 

reducing incidence of disease, especially due to fungi 

as many fungi require moisture (Hajek and St. Leger 

1994, Streett and McGuire 1990). However, extreme or 

prolonged drought can negatively affect grasshoppers 

through desiccation (especially eggs) or by killing their 

food plants (Farrow 1979, Joern and Gaines 1990, 

Mukerji and Gage 1978). Therefore, short-term, lesssevere droughts can increase grasshopper outbreaks, 

but longer term, severe droughts will likely have a 

strong negative effect on grasshoppers and rangeland/

grassland biodiversity in general (Kemp and Cigliano 

1994, Tilman and El Haddi 1992).
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Invasive Species 

Droughts are predicted to accelerate the pace of 

invasion by some nonnative plant species into 

rangelands and grasslands (Abatzoglou and Kolden 

2011, Everard and others 2010, Ford and others 

2012, Runyon and others 2012). One route by which 

drought promotes plant invasions is through increased 

movement of hay across State lines to feed livestock 

in drought-affected areas (Conn and others 2010). 

Drought conditions can also exacerbate invasions 

by favoring invasive species over native species. For 

example, invasive saltcedar (Tamarix ramosissima) 

is more drought tolerant than co-occurring native 

species, and its capacity to invade is predicted to 

increase with drought (Cleverly and others 1997). In 

California, it has been argued that invasive grassland 

species tolerate drought-like conditions better than 

native species and that drought was a contributor 

to the invasion of annual species into California 

grasslands (Corbin and D’Antonio 2004, D’Antonio 

and Vitousek 1992, Everard and others 2010, Jackson 

1985). However, Funk and Zachary (2010) found no 

differences in physiological responses to drought of 

three native versus three invasive species in southern 

California, suggesting that not all invasive species will 

be favored. Conversely, invasive species could be 

negatively affected by drought; for example, some 

have attributed drought to a recent decline in spotted 

knapweed (Centaurea stoebe) in western Montana 

grasslands [but biological control could have played a 

role, see discussion in Ortega and others (2012)].

Drought can also promote plant invasion indirectly by 

modifying the environment to favor nonnative species. 

For example, opportunities for invasion are created 

when drought kills native plants leaving open niches 

and bare ground (Breshears and others 2005). This 

was apparently the case following the Dust Bowl of the 

1930s which resulted in increases in nonnative plant 

abundance (Weaver and Albertson 1936, 1939). 

Drought is also an important contributor to the invasive 

annual grass–wildfire loop that threatens ecosystems 

not adapted to fire [e.g., cheatgrass (Bromus tectorum) 

forms a positive feedback with fire in parts of western 

North America’s sagebrush biome] (Abatzoglou and 

Kolden 2011, D’Antonio and Vitousek 1992). In this selfperpetuating cheatgrass–fire loop, drought increases 

the frequency of wildfires (Abatzoglou and Kolden 

2011), and burned sites are more likely to be invaded by 

nonnative plants, especially annual grasses (Balch and 

others 2013). Drought-induced fire also threatens to 

convert Sonoran Desert ecosystems to monocultures 

of nonnative plants such as buffelgrass (Pennisetum 

ciliare) and Lehmann lovegrass (Eragrostis lehmanniana) 

(Finch and others 2012). 

Not only can drought affect invasions by nonnative 

plants, but it can also affect the tools used to manage 

them. The effectiveness of both herbicides and 

biological control can be altered by drought. To be 

effective, herbicides must be taken up through the 

leaves and stems of actively growing, green plants 

(Ashton and Crafts 1981). Herbicides applied to the 

foliage during periods of drought are usually much 

less effective than those applied when moisture is 

adequate (Bussan and Dyer 1999, Kogan and Bayer 

1996). This is because many plant responses to 

drought—including reduced growth, closed stomata, 

thickened waxy cuticle, and increased pubescence—

can reduce the uptake or translocation of herbicides 

(Kogan and Bayer 1996). For example, Morrison and 

others (1995) found that drought stress reduced 

translocation of herbicides and control of Russian 

knapweed (Acroptilon repens), a problematic rangeland 

weed in the Western United States. Therefore, our 

ability to manage invasive plants using herbicides could 

be reduced during periods of drought. 

There is also some evidence that drought can alter the 

effectiveness of biological control of invasive plants. 

Historically, drought stress in plants was thought to 

benefit plant-feeding insects (Mattson and Haack 1987), 

which suggested that drought could benefit biocontrol 

using insects. However, a meta-analysis by Huberty 

and Denno (2004) found that continuous drought stress 

in plants negatively affected many insect herbivores, 

suggesting that biocontrol efficacy could generally 

be reduced by drought. Few studies have explicitly 

examined the effect of drought on biocontrol. Corn and 

others (2007) report that drought had little effect on 

the impact of the root weevil Cyphocleonus achates

on spotted knapweed (Centaurea stoebe). However, 

Ortega and others (2012) found that the impact of C. 

achates on spotted knapweed was negated by drought 

conditions. Shishkoff and Bruckart (1996) found that 

drought stress has no effect on damage to yellow 

star-thistle (Centaurea solstitialis) caused by the rust 

fungus Puccinia jaceae in the laboratory. More research 

is needed to better understand how drought will affect 

biological control, an important management tool of 

rangeland invasive plants. 
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Wildfire and Drought

In the Unites States, more than 80 percent of all 

wildfires are started by humans. Lightning strikes are 

another common cause for natural wildfires (National 

Wildfire Coordinating Group Fire Investigation Working 

Team 2005). Recent increases in fire activity in some 

parts of the World have been attributed to climate 

change (Gillett and others 2004, Kasischke and Turetsky 

2006, Pinol and others 1998, Westerling and others 

2006). U.S. ecoregions with increasing trends in the 

number of large fires and total fire area also displayed 

increasing trends in drought severity (Dennison and 

others 2014). The incidence of large fires and extent 

of area burned have increased across the Western 

United States. Fire activity trends were most significant 

in southern and mountain ecoregions. Increased fire 

in these ecoregions coincided with increased drought 

severity (Moritz and others 2012). Under extended 

drought condition, wildfires are getting bigger, and more 

fires are starting earlier in the year. Since 1984, the area 

burned by the West’s largest wildfires—those of more 

than 1,000 acres—increased by about 87,700 acres 

per year, and the areas where fire has been increasing 

the most are areas where drought has been worsening 

(Dennison and others 2014). 

Climate change can indirectly affect rangeland 

vegetation by altering fire regimes. Increasing fire 

frequency leads to a replacement of fire-sensitive plant 

species with those that are more fire-tolerant (Nelson 

and Hu 2008). Most wildfires in the Western United 

States occur during the hottest, driest portion of the 

year (Westerling and others 2006), and the size of the 

area burned during any single year is correlated with 

the current drought condition (i.e., PDSI) and with 

wetter-than-normal conditions in May and August of 

the previous year (Polley and others 2013). In grassand shrub-dominated ecosystems, fires are largest 

when unusually wet summers (during which fine fuels 

accumulate) are followed by dry conditions that enhance 

fuel flammability and ignition (Littell and others 2009). 

Fire activity is projected to increase considerably in the 

Western United States as the climate becomes both 

warmer and drier (Pechony and Shindell 2010, Polley 

and others 2013). 

The largest U.S. grassland region is the Great Plains, 

a vast area of prairie, agriculture, and rangelands 

extending from the Dakotas through Iowa, Nebraska, 

Kansas, Oklahoma, and parts of Texas, and including 

the eastern parts of Montana, Wyoming, Colorado, 

and New Mexico (Bagne and others 2012). Fire is an 

important feature of many Great Plains rangelands, and 

its frequency, intensity, and seasonality are likely to be 

affected by changes in climate, productivity, and species 

composition. Fire was an important factor in maintaining 

grass dominance in the more productive rangelands 

of the eastern Great Plains. In more recent times, 

the removal of fire and/or changes in its seasonality, 

along with rising CO2, have encouraged woody plant 

encroachment in many of these productive rangelands 

(Morgan and others 2008). 

Indeed, woody encroachment has emerged as the 

dominant threat to grassland ecosystem services in 

the Great Plains (Engle and others 2008). In areas of 

long-term juniper encroachment, fires have shifted from 

frequent, grass-driven surface fires that vary in flame 

length (range ≤ 0.1 m to well over 3.4 m) (Finney and 

others 2011) to infrequent, juniper-driven crown fires 

that consistently exhibit extremely long flames (>14 m) 

and are of increasing societal concern (Twidwell and 

others 2013). Such alterations to the fire regime and 

fire suppression potential are important contributors to 

the recent rise in housing losses, suppression costs, 

and human injuries and deaths resulting from wildfires 

in the Great Plains (Tidwell and others 2013). Predicted 

changes in precipitation patterns are likely to encourage 

more frequent and intense fires in the future, with 

increased winter precipitation driving early-season 

plant growth, and warmer, drier summers desiccating 

vegetation, thus increasing the probability of fire 

(Morgan and others 2008).

A chief concern in the arid and semiarid rangelands of 

the Western United States is the rapid conversion of 

shrublands and desert into annual grassland through 

the spread of invasive annual grass species and the 

negative impacts this conversion will have on wildfire 

regimes, surface hydrology, and loss of critical habitat 

for threatened and endangered species (Abatzoglou 

and Kolden 2011, Bradley and Mustard 2005, Brooks 

and Esque 2002, Brooks and others 2004, Mack 

1981, Wilcox and Thurow 2006). Over the past three 

decades, there has been a significant increase in the 

abundance and extent of invasive annual grass species 

in the Southwest, including cheatgrass across the Great 

Basin Desert, red brome (Bromus rubens) across the 

Mojave Desert, and buffelgrass across the Sonoran 

Desert (Betancourt 2007, Bradley and Mustard 2005, 

Brooks and Esque 2002). This change, along with a 

change in climate, has coincided with an increase in 

the number of large fires and area burned across the 

arid and semiarid Western United States (Brooks and 
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others 2004, Westerling and others 2006, Whisenant 

1990). For example, in the Great Basin, fires were 

found to be more likely to start in cheatgrass than in 

other vegetation types, and cheatgrass is associated 

with increased fire frequency, size, and duration. 

As sites burn, more and more of the sites are likely 

to become cheatgrass grasslands, thus increasing 

their future probability of burning (Balch and others 

2013). Also, elevated cheatgrass biomass following El 

Niño events is strongly linked to increased risk of fire 

during the following years’ summer (Balch and others 

2013). Future projections of climate change suggest 

that the Western United States is likely to become 

warmer and have greater precipitation variability, which 

could increase or decrease cheatgrass fire probability 

depending on how much warmer temperatures 

influence moisture availability. In general, evidence 

suggests that observed changes in climate have 

assisted in the spread of invasive annual grasses 

across western U.S. deserts both directly through 

changes in temperature and precipitation and indirectly 

through their influence on wildfire (Abatzoglou and 

Kolden 2011). For example, increased temperature and 

reduced humidity during spring and summer associated 

with recent protracted drought conditions since 2000 

have doubled the frequency of extreme fire danger in 

the Sonoran Desert, resulting in an earlier start and 

lengthening of the fire season (Abatzoglou and Kolden 

2011, Weiss and others 2009). 

Pinyon-juniper woodlands—the third largest vegetation 

type in the West—characterize many Rocky Mountain 

and Intermountain rangelands and are vitally important 

for biodiversity, aesthetics, and commodity production 

(Mitchell and Roberts 1999, West 1999). Extreme 

drought conditions have characterized the American 

Southwest during the past decade, causing widespread 

mortality in pinyon-juniper woodlands. While 

comparably low precipitation levels have occurred at 

other times in the past century, rising temperatures 

have accompanied the latest drought, increasing water 

stress on vegetation and triggering increases in bark 

beetle-caused mortality. Drought-related outbreaks in 

bark beetles have killed pinyon pines on over 12,000 

km2 in the Southwest (Breshears and others 2005, 

Floyd and others 2009, Shaw and others 2005). The 

current severe, regional drought is providing the dry 

conditions necessary for extensive wildfire activity. 

Historical fire rotation for pinyon-juniper woodlands 

has been estimated across the Unites States. Studies 

report very long fire rotations—for example, 410 years 

in Barrett Canyon of central Nevada (Bauer 2006), 

480 years in southern California (Wangler and Minnich 

1996), 400–600+ years on the Uncompahgre Plateau 

in western Colorado (Shinneman and Baker 2009), and 

400+ years on Mesa Verde in southwestern Colorado 

and on the Kaiparowits Plateau of southern Utah (Floyd 

and others 2004, 2008; Romme and others 2009). An 

upsurge of large fires (>400 ha) in forested landscapes 

throughout much of the Western United States began in 

the mid-1980s (Westerling and others 2006). Increasing 

trends in large fire frequency and total area burned 

are particularly noticeable in regions having extensive 

pinyon-juniper woodlands (e.g., the Southwest and 

the northern Great Basin). For example, a greater 

proportion of the pinyon-juniper woodland on Mesa 

Verde, Colorado, burned in the decade between 1995 

and 2005 than had burned throughout the previous 

200 years (Floyd and others 2004, Romme and others 

2009). A combination of canopy fuel build-up during 

two wet decades before 1995 and the current drought 

conditions resulted in unprecedented fire activity 

(six large wildfires between 1996 and 2003) when 

compared with the reference period 1700–1900 (Floyd 

and others 2004).

Given the very long fire rotations that naturally 

characterize pinyon-juniper woodlands, it has not 

yet been determined whether the recent increase in 

frequency of large fires occurring in this vegetation 

type represents genuine directional change related 

to changing climate or fuel conditions, or whether 

it is simply a temporary episode of increased fire 

activity, comparable to similar episodes in the past. 

Ultimately, the suite of current and upcoming broadscale environmental changes including warming 

temperatures, increasing tree densities in some areas, 

and expansion of fire-promoting species, such as 

cheatgrass, may all interact to dramatically increase 

the amount of burning in pinyon-juniper and other 

vegetation types over the next century (Romme and 

others 2009). 

In the near term, the most consistent increases in 

fire activity occur in biomes with already somewhat 

warm climates (Moritz and others 2012). However, as 

the Arctic warms, wildfire may become increasingly 

important even within the coldest of all terrestrial ecosystems: tundra (Joly and others 2012). Tundra covers 

over 5,000,000 km2 of the Arctic (Walker and others 

2005), including a large portion of Alaska. Warmer 

and drier summers are associated with greater area 

burned in Alaska (Duffy and others 2005). The effects 
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of climate change are already apparent in the Arctic 

(Callaghan and others 2004, IPCC 2007). Mean annual 

temperatures have increased by 2–3 °C in the region in 

recent decades, with larger increases apparent during 

the winter months (Hinzman and others 2005, Joly and 

others 2012, Stafford and others 2000). 

Climate change impacts on the habitats of Arctic land 

mammals are predicted to be severe (Lawler and 

others 2009) and have already been implicated in the 

decline of caribou (Rangifer tarandus) populations there 

(Vors and Boyce 2009). Mechanisms by which climate 

change may negatively impact caribou include increased 

frequency of wildland fire on winter ranges (Joly and 

others 2012). Although wildfires occur during the 

summer, they negatively impact caribou winter range. 

Migratory caribou rely heavily on tundra plants to sustain 

them through the winter months, and these plants can 

take 50 or more years to recover after wildland fires 

consume them (Joly and others 2012). Tundra has the 

potential to re-burn much more quickly than boreal 

forests, so warmer summer conditions could lead to 

additional fires (Joly and others 2009). 

Effects of Drought on, or in 

Combination With, Human 

Uses and Practices

Drought Impacts on Livestock, 

and Forage Yield and Availability

Drought and livestock grazing are two major drivers 

of rangeland structure and productivity within the 

Great Plains. No geographic location is immune to the 

wide-ranging social and economic impacts of drought 

(Riebsame and others 1991). The Great Plains were 

historically grazed by bison until settlement in the 19th 

century when cattle were introduced as the major 

livestock. Ungulate grazing often leads to an increase 

in spatial heterogeneity and species diversity (Adler 

and others 2001, Bakker and others 2003a). However, 

grazing severity and timing largely determine the effect 

of ungulate grazers on rangelands. 

Rangeland drought management is influenced by both 

historical perceptions and the drought class framework 

of the manager. Vegetation reports of the early explorers 

in the 19th century depended on the year observations 

were made (Coupland 1958). Early settlers expected 

productive lands and were accustomed to the more 

predictable and dependable precipitation patterns of 

the Eastern United States. Therefore, initial farming and 

ranching practices failed to accommodate the abiotic 

and biotic changes associated with a highly variable 

climate and the combined effects of periodic drought 

and livestock grazing. Although current land managers 

have gained more experiential knowledge in these arid 

environments, management decisions in response to 

drought are still affected by the first perceptions of the 

early settlers. In recent years, unsustainable rangeland 

use has exacerbated the effect of drought, causing 

more land managers to experience financial hardship 

and perceive that meterological drought is increasing in 

frequency (Thurow and Taylor 1999). Land managers 

are encouraged to plan proactively for drought and 

maintain flexibility in rangeland management by 

diversifying livestock operations and types of land use 

(Coppock 2011, Kachergis and others 2014, Thurow and 

Taylor 1999). 

Depending on intensity and frequency, grazing and 

drought independently can adversely impact the 

ecology and management of rangeland ecosystems 

by reducing plant cover and forage availability, 

reducing root growth, shortening the season of forage 

production, and exposing the soil to erosion (Vallentine 

1989). However, because grazing and drought often 

occur at the same time, identifying the relative 

contribution of grazing and drought to these impacts 

is a difficult task requiring long-term monitoring 

(Fuhlendorf and others 2001). While the effects 

of grazing can occur relatively quickly to produce 

obvious contrasts, droughts often emerge slowly 

with cumulative effects that merge gradually into a 

catastrophic event (Riebsame and others 1991). 

The separate and interactive effects of drought and 

grazing on rangeland vegetation can also be amplified by 

a variety of direct and indirect factors. For example, the 

broad-scale effects of drought are locally modified by 

variation in soil and topography (slope and aspect, which 

interact to influence water infiltration and runoff) and 

soil moisture retention. Often, the effects of drought are 

first observed on hilltops and ridges, followed by side 

slopes, and then depressions and valleys. South-facing 

slopes are impacted more than north-facing slopes, 

especially at higher latitudes (Coupland 1958, Weaver 

and others 1935). Concentrated and continuous grazing 

causes soil compaction that reduces water infiltration 

and increases surface erosion, thus exacerbating the 

effects of drought (Vallentine 1989). Droughts are 

also frequently accompanied by high populations of 

grasshoppers and accumulations of wind-blown soil 

particles, which can develop into drifts up to 3 feet deep 

(Coupland 1958, Weaver and Albertson 1940). 
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Grazing effects can produce a significant and somewhat 

predictable directional change in vegetation composition 

and productivity, which is primarily augmented directly 

by water stress and secondarily by additional factors 

that accompany drought. Water stress and grazing 

have been considered convergent selection pressures 

that involve the periodic reduction of biomass (Koerner 

and Collins 2014, Milchunas and others 1988). 

Consequently, plant traits selected due to a reduction 

in biomass by one driver, such as grazing, can enhance 

plant survival when exposed to other drivers, such 

as drought. Semiarid grassland communities with a 

long evolutionary history of grazing are dominated by 

relatively short-statured, grazing-tolerant, rhizomatous 

or stoloniferous grasses that compete primarily for 

soil resources (Milchunas and others 1988). In semiarid grasslands, grazing before and during drought has 

little impact on community composition and structure 

(Heitschmidt and others 1999.) 

By contrast, in sub-humid grasslands where mid- and 

tall-grasses must compete for light, grasses are not as 

tolerant of grazing because growth of the aboveground 

canopy is primarily vertical. Therefore, depending on 

the grazing evolutionary history, grazing in more mesic 

grasslands would have moderate to large effects 

on composition and canopy structure (Milchunas 

and others 1988). However, during droughts prior to 

settlement, free-ranging grazers (e.g., bison) would 

have either died and/or migrated out of the impacted 

area (Heitschmidt and others 1999). Consequently, 

grazing and severe drought may have not occurred 

together historically in some rangeland ecosystems, 

except possibly for short periods of time. 

Relative contributions of drought and grazing to biomass 

reduction and shifts in vegetation composition within 

a rangeland may shift between mesic and more arid 

rangelands. In mesic tallgrass prairies, grazing and 

fire had a greater effect on community structure than 

precipitation (Koerner and Collins 2014). However, in the 

semi-arid northern Great Plains, climatic variation had a 

greater effect on vegetation composition and production 

than grazing intensity (Biondini and others 1998, Olson 

and others 1985). Semi-arid and arid grasslands of the 

Western United States are noted for their small (<5 

mm) rainfall events and intervening dry periods (Loik 

and others 2004). Although small rainfall events may 

not contribute measurable increments in biomass, 

they are able to increase leaf water potential and help 

sustain physiological activity between larger rainfall 

events (Sala and Lauenroth 1982). Reduction in the 

occurrence of small rainfall events during drought may 

explain the greater sensitivity of more arid grasslands 

to precipitation than grazing. In sagebrush steppe, both 

drought and grazing independently reduce perennial 

grass and forb cover (Anderson and Inouye 2001; West 

1983, 1988). Although dominant shrubs such as big 

sagebrush can be affected by drought, they are affected 

to a lesser degree than grasses and increase in relative 

abundance within the shrubland community (Pechanec 

and others 1937, West 1983).

Rangeland response to the effects of drought and/

or grazing was exemplified by observational studies 

conducted before, during, and following the 1930s 

extreme drought in the Great Plains (i.e., the Dust Bowl) 

[see Weaver (1954) and references there-in, Pechanec 

and others (1937)]. Severe drought substantially 

reduced plant cover and forage availability. Continuous 

grazing at almost any level during severe drought can 

adversely impact rangeland structure and function. 

Heavy grazing can have the greatest impact and 

substantially increase the length of the recovery period 

(Albertson and others 1957). With low vegetative cover 

and high winds that usually accompany drought, the 

potential for soil erosion is high. Despite the negative 

long-term impacts, grazing during drought was a 

common practice used to maintain livestock herds until 

favorable conditions returned (Weaver 1954). 

The directional, selective influence of grazing on 

vegetation is especially prominent in heavily grazed, 

mixed-grass prairies. Prolonged heavy grazing can 

simultaneously decrease grass basal area and increase 

plant density (Briske 1991 and references there-in). 

Grazed sites with a high density of plants with small 

basal areas may be subject to higher drought-induced 

mortality compared to a lower density of plants with 

larger basal areas in lightly and moderately grazed 

grasslands (Albertson and others 1957, Fulhlendorf 

and others 2001). A high density of plants with small 

basal areas may serve as a valuable indicator of pending 

compositional changes during drought conditions 

(Fuhlendorf and others 2001). During the drought of 

the 1930s, drought-induced plant mortality under heavy 

grazing increased the amount of bare soil, which was 

often quickly colonized by Russian thistle (Salsola kali) 

(Albertson and others 1957). 

Moderate grazing also influences the long-term 

directional change of vegetation that is magnified by 

drought, but to a lesser degree than heavy grazing 

(Coupland 1958). Actually, reductions in basal area 
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during periodic droughts were sometimes less in 

moderately grazed grasslands compared to ungrazed 

grasslands (Coupland 1958, Weaver and Albertson 

1936). Weaver and Albertson (1936) attributed the 

higher basal area observed in moderately grazed 

pastures compared to lightly and ungrazed pastures 

to grazing-induced increases in drought-resistant 

species such as blue grama and buffalograss. 

However, buffalograss is more sensitive to drought 

than blue grama, which often becomes the dominant 

species during periodic droughts. On the other hand, 

buffalograss has the ability to rapidly produce new 

stolons once favorable conditions return. If the drought 

is not severe or prolonged, then moderate grazing also 

allows the less drought-resistant species to persist. 

However, during prolonged, severe drought, the 

drought-sensitive mid-grasses will suffer high mortality 

(Coupland 1958). Post-drought vegetation recovery 

was always slower on sites dominated exclusively by 

blue grama compared to sites with a combination of 

blue grama and buffalograss (Albertson and Weaver 

1944). Consequently, blue grama was important for 

protecting the soil during drought, while buffalograss 

was important for recovery following the drought. 

Vegetation recovery following drought is generally 

proportional to the intensity of grazing before, during, 

and after the drought (Albertson and Weaver 1944). 

Weaver (1954) described several cases where 

livestock were sold during the drought of the 1930s 

because of severe shortages of forage. Because of 

economic hardships (including The Great Depression), 

producers were unable to re-stock their pastures with 

livestock for several years. Therefore, many rangelands 

damaged by combinations of grazing and drought 

were rested, especially heavily grazed pastures 

where forage was reduced very early in the drought 

cycle. In this context, rangeland recovery during a 

severe drought was more rapid than recovery during 

a short-term drought event where herds of cattle 

were maintained during and immediately following the 

drought (Weaver 1954). 

In general, moderately grazed, mixed-grass prairie can 

recover fairly quickly from moderate (Coupland 1958) 

and severe drought (Albertson and Weaver 1944). 

Vegetation recovery on heavily grazed grasslands with 

few remnants of the pre-drought vegetation remaining 

and considerable bare soil will include several years of 

an annual weed stage, which will substantially delay 

recovery of native perennial grasses. If dry conditions 

return during the post-drought recovery, the annual 

weed stages could persist for several years (Albertson 

and Weaver 1944). In contrast, sagebrush shrublands 

that have transitioned from a sagebrush-native perennial 

grass mixture to a heavily shrub-dominated community 

remain in this stable state even after grazers are 

excluded for multiple years (West and others 1984). 

Few perennial grass seeds persist in the soil for more 

than 5 years, with the seeds of some species living 

<1 year (Baskin and Baskin 1998). Consequently, 

recovery of perennial grasses from drought and/or 

grazing is dependent upon stem recruitment from 

belowground meristematic tissue (the bud bank 

sensu Harper 1977; Benson and Hartnett 2006). 

Weaver and Albertson (1936) reported that with 

the return of normal precipitation following the 

1930s drought, western wheatgrass (Pascopyrum 

smithii) rapidly expanded into areas of bare soil 

created by the drought. Because the drought had 

significantly reduced (eliminated) opportunities for 

sexual reproduction, the rapid expansion of western 

wheatgrass most likely occurred through vegetative 

growth via the bud bank. A few small precipitation 

events during drought may play a significant role in 

maintaining the viability of bud banks through extreme 

dry conditions (Sala and Lauenroth 1982). 

As individual drivers, drought and grazing can have a 

similar effect on rangelands. In combination, the relative 

contributions of drought and grazing to the response and 

recovery of a rangeland strongly depend on the severity 

of each driver and the climate and dominant vegetation 

of the rangeland. Although effects of drought and 

grazing on rangeland community structure and function 

continue to be documented, a more mechanistic 

understanding of the impact of drought and grazing 

should be sought. Understanding how drought and 

grazing alter factors such as nutrient availability or the 

bud bank will provide land managers with more tools to 

respond to joint drought and grazing issues. 

Effects of Drought on Restoration Success

Ecological restoration encompasses a variety of 

management actions intended to restore or repair 

degraded ecosystems. Degradation can range from 

minor deviations of vegetation structure and community 

composition from a desired state, to complete 

denudation of vegetation, soil loss, and associated 

disruption of ecosystem function (Allen 1995, 

Bainbridge 2007, SER 2004). Many U.S. rangelands 

have been dramatically altered by intensive uses 

such as agriculture, mining, military operations, and 
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vehicular traffic (Bainbridge 2007). Other grasslands 

and shrublands remain intact but have been degraded 

to various degrees by overgrazing or mismanagement, 

often resulting in depletion of forage and encroachment 

by woody plants (Archer and others 2011). Invasive 

exotic species are also a serious problem in many areas 

(Brown and others 2008, Sheley and others 2011).

Different types of restoration are applicable to different 

circumstances. Grazing management, prescribed 

fire, herbicides, and mechanical treatments such as 

mowing and chaining may be used to selectively reduce 

undesirable species (Archer and others 2011, Briske 

and others 2011, Fuhlendorf and others 2011, Vallentine 

1989). If desirable species are not present in sufficient 

quantity to recover on their own, active planting 

(seeding or transplanting) may be necessary (Bainbridge 

2007, Hardegree and others 2011). On severely 

degraded sites, soil remediation or topsoil replacement 

may be required (Pinchak and others 1985, Schuman 

and others 1985). 

The ultimate goal of full-scale ecological restoration 

is to reestablish functioning ecological communities 

resembling those that existed prior to intensive human 

disturbance (SER 2004), as illustrated by longstanding 

efforts to restore native prairies in agricultural regions 

of the U.S. Midwest (Rowe 2010). In other settings, 

site integrity and productivity are the primary goals, 

and the terms rehabilitation or reclamation are 

applicable (SER 2004); for example, reclamation of 

surface mine disturbances (OSM 1997), rehabilitation 

following wildfire on Federal lands (Beyers 2004), and 

rehabilitation of agricultural lands in the Conservation 

Reserve System (Baer and others 2009). Although 

nonnative plants have a long history of use for 

rehabilitation and reclamation in the United States, 

current policies encourage use of native species on 

Federal lands (Johnson and others 2010a, Richards and 

others 1998) and some sites previously planted with 

nonnatives have been targeted recently for restoration 

with natives (Bakker and others 2003b, Hulet and others 

2010, Wilson and Gerry 1995). 

Because of the critical role of water in plant 

establishment, growth, and survival, restoration 

plantings are directly impacted by drought conditions. 

Insufficient precipitation has been invoked to explain 

suboptimal plant establishment for many restoration 

plantings in grassland and shrubland systems (Bakker 

and others 2003b, Bleak and others 1965, Fehmi 

and others 2014, Glenn and others 2001, Hulet and 

others 2010, Ratzlaff and Anderson 1995). If low 

plant establishment is accompanied by intensive soil 

disturbance (e.g., seeding using rangeland drills), there 

may be a risk of increased erosion by wind (Miller 

and others 2012) or water (Pierson and others 2007), 

as well as impacts to preexisting plants (Ratzlaff 

and Anderson 1995). Even in cases where plant 

establishment is initially successful, plantings may later 

die back during drought years (Bleak and others 1965, 

Currie and White 1982). 

Although drought conditions are a disadvantage for 

plantings, they can be advantageous for plant control to 

the extent that water deficits make undesirable plants 

more susceptible to mechanical treatments, herbicides, 

or fire. For example, control of crested wheatgrass 

(Agropyrum cristatum) by clipping or herbicides has 

been shown to work better under drier conditions 

(Bakker and others 2003b, Hansen and Wilson 

2006). The effectiveness of foliar herbicides may be 

reduced under drought conditions because of poor 

translocation following application (Vallentine 1989), 

although this differs by herbicide and plant species 

(Abbott and Sterling 2006, Lauridson and others 1983, 

Morrison and others 1995, Roche and others 2002). 

Soil herbicides require water for dissolution and soil 

penetration and are thus likely to be less effective 

during drought (Vallentine 1989).

The use of prescribed fire as a restoration tool during 

drought requires special considerations. In desert 

grasslands encroached by mesquite, drought conditions 

may make prescribed fire difficult to implement because 

of insufficient fine herbaceous fuel (Britton and Wright 

1971, Teague and others 2010, White and Loftin 2000). 

In other settings where fuel is more abundant, it may be 

especially dry during drought, and this combined with 

low air humidity can make fires explosive and difficult to 

control (Ralphs and Busby 1979). 

Narratives of escaped prescribed fires frequently 

include drought as a contributing factor, leading to 

loss of control and ensuing damage (Brunson and 

Evans 2005, Earles and others 2004). Furthermore, 

the effects of prescribed fires may be different during 

drought compared to wetter years. Increases in light, 

higher temperatures, and nutrient inputs to soils that 

represent positive effects of fire under high moisture 

conditions could become detrimental when soil 

moisture is low (Augustine and others 2010, Bremer 

and Ham 1999, Teague and others 2008, Whisenant 

and others 1984).
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Depending on the seasonal incidence of drought 

conditions, optimal dates for prescribed burning might 

also differ compared to normal years. Burns intended to 

control certain species or groups (e.g., annual weeds, 

cool-season grasses) by burning during their active 

stage (Adkins and Barnes 2013, Anderson and others 

1970, DiTomaso and others 2006) might be constrained 

by smaller windows of opportunity due to early onset of 

dormancy. On the other hand, if the purpose of burning 

can be met during the dormant stages (Brockway 

and others 2002, Ford and Johnson 2006), then the 

window of time for burning may be longer during 

drought. Benefits of prescribed fire ultimately depend 

on vegetation regrowth, which may be diminished if 

drought occurs during the post-fire period. Ladwig and 

others (2014) found that drought conditions delayed 

expected grass recovery following prescribed fire in a 

Chihuahuan Desert grassland, and that effects of burn 

timing (spring, summer, and fall) were short-lived due to 

the overriding influence of the drought. 

Increasing Rangeland 

Ecosystem Resilience 

to Drought

Adaptive Strategies for Managing Livestock

Land managers and livestock producers must 

periodically cope with and adapt to drought, both in the 

short term and in the long term. Adaptive strategies 

can vary regionally, but appropriate measures must be 

taken to provide adequate recovery of vegetation to 

ensure proper ecological function and economic returns. 

Greatest success will be achieved with careful planning 

of strategies to employ before, during, and after 

droughts. Some adaptive responses to drought include:

lReducing stocking rate to allow plant recovery

lUsing fencing and other developments to manage 

livestock distribution

lUsing drought-resistant feed crops

lUsing drought-adapted stock

lAdjusting season of use

lDiversifying ways for economic gain

lImplementing deferred grazing system

lDeveloping, restoring, or reclaiming water

lProviding shade structures for livestock

lReducing the time livestock graze a specific pasture/

unit/paddock 

lIncreasing the time or rest between periods of 

grazing

l	Testing new techniques for responding to drought

The most obvious and arguably the single most 

important strategy for adapting to drought is reduction in 

stocking rate because plants that have been overgrazed 

or cropped too frequently are less able to recover after 

drought (Hart and Carpenter 2005). Conservative 

and flexible stocking rates enable maintenance of 

proper amounts of residual forage. Where droughts 

are relatively common, breeding stock should only 

represent 50–70 percent of the total carrying capacity 

(Hart and Carpenter 2005). Grazing time in pastures 

can also be reduced, as an action or in combination 

with other actions, such as supplemental feeding and 

reducing number of livestock. In addition, ranchers can 

first sell stocker cattle as a means of herd reduction 

during drought to protect the breeding herd so that restocking after recovery is easily accomplished. Another 

technique for coping with drought is use of fencing, salt, 

water development, and strategic herding to increase 

uniformity of use. Likewise, some animals inherently 

make more uniform use of the landscape than others, 

suggesting that selective breeding can preemptively aid 

drought adaptation (Howery and others 1998). 

As a last measure, supplemental forage can be used 

to augment the sparse forage that drought conditions 

induce; however, use of supplemental forage can 

potentially exacerbate the problem by maintaining an 

unsustainable number of animals. In addition, animals 

will likely continue to use greener, more-palatable 

rangeland vegetation even if ample supplemental 

feed is supplied. From a herd-management or 

economic perspective, consideration should be given 

to selling animals before they have lost excessive 

weight and weaning calves earlier than normal which 

reduces forage demand (Howery 1999). Additionally, 

nonproductive animals or animals with low fertility rates 

should be culled first during drought periods. 

Since economic returns and ecological integrity are 

linked to vegetative resources, careful consideration 

of vegetation conditions is required, during and after 

droughts in concert with herd management adaptations. 
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In this vein, extra monitoring is prudent to ensure that 

forage yields and ecological integrity can be maintained 

in the future. Extra rest periods can aid recovery while 

ranges are recovering after a drought. The timing of 

grazing also becomes a critical factor in determining 

recovery after a drought. For example, use of ranges 

when nondesirable species are green and palatable and 

deferring grazing until perennial species have produced 

seed can aid recovery. However, this generalization 

does not always apply as it may be more advantageous 

to utilize perennial grasses during the early vegetative 

stages but prior to the booting phase, emphasizing the 

importance of planning and monitoring before, during, 

and after drought. 

Regardless of the strategies used, adaptation to and 

recovering from drought requires careful planning 

before, during, and after for maximum effectiveness. 

Moreover, the single most important outcome that 

can be controlled by management is selecting an 

appropriate and flexible stocking rate. 

Adjusting Restoration Practices 

Under Drought Conditions

Drought conditions generally pose constraints for 

restoration practices such as planting or prescribed 

burning (see previous section). Such practices might 

best be deferred during periods following extended 

drought or preceding predicted drought conditions. 

However, postponing a restoration project may not 

be satisfactory in situations where policy, funding, 

logistics, or other concerns favor immediate action. In 

such cases, restoration practices can be implemented 

but modified in ways that compensate for limited soil 

moisture (e.g., irrigation, water catchments) or use 

alternative techniques to achieve the desired outcome 

(e.g,. mechanical treatment instead of prescribed fire). 

If a decision is made to use prescribed fire during a 

drought, it should be done with careful planning and 

precautions. As reported by Guse (2009), The Nature 

Conservancy successfully carried out a ca. 730-ha 

prescribed burn during extreme drought conditions in 

southern Texas, noting that the drought provided an 

unprecedented opportunity to restore shrub-invaded 

grasslands. The success of the operation was attributed 

to extensive commitments of resources (reportedly 2-3 

times the minimum required number of firefighters and 

water delivery systems), by assuring that firefighters 

were well trained and equipped, and implementing 

burns in incremental, manageable stages over a period 

of 9 days (Guse 2009).

During periods of drought, it may be best to focus 

restoration efforts on removal of undesirable plants 

as opposed to planting treatments. In reference to 

native grassland restoration in the northern Great 

Plains, Bakker and others (2003b) recommended that 

crested wheatgrass control measures be undertaken 

during drier years while seeding of native species 

take place in wetter years. In the Great Basin, juniper 

removal by mastication (shredding) can be beneficial for 

herbaceous species by both releasing competitive water 

use of the woody overstory and enhancing soil moisture 

beneath shredded debris (Young and others 2013).

If planting is deemed necessary during a drought year, a 

variety of strategies and techniques can be employed to 

increase the probability of successful plant establishment 

in the short term and species persistence in the long 

term. Plant materials should be carefully selected to 

ensure that the species and ecotypes are adapted to 

drought conditions, especially during the establishment 

phase, and are resilient if drought is episodic or longterm climate change is projected. The ability to rapidly 

extend roots downward into the soil is an important 

trait for seedlings facing a soil drying front (Abbott and 

Roundy 2003). Equally important is the capacity of seeds 

to remain dormant until soil moisture is sufficient to 

sustain seedling growth (Biedenbender and others 1995, 

Frasier and others 1987). Larger seeds will likely have 

greater capacity to endure water limitations during the 

critical establishment phase compared to smaller seeds 

(Hallett and others 2011, Leishman and Westoby 1994). 

In addition, larger seeds are better able to emerge when 

buried beneath soil, and can thus be planted at depths 

where they are buffered from surface soil moisture 

fluctuations (Carren and others 1987, Monsen and 

Stevens 2004, Montalvo and others 2002). 

As seedlings become larger, they tend to become 

less sensitive to moisture fluctuations, hence, it may 

be advantageous to transplant seedlings (or even fully 

grown plants) rather than attempting to establish plants 

from seed. Transplanting has been found to be effective 

for establishing shrubs and forbs in water-limited 

environments, especially if transplants are hardened off 

prior to planting and provided with supplementary water 

afterwards (Anderson and Ostler 2002, Bainbridge 

2007, Glenn and others 2001, Grantz and others 1998a, 

Holden and Miller 1995, Watson and others 1995). The 

use of water-holding materials such as sepiolite clay and 

hydrogels in root plugs of transplants may enhance their 

survival in dry soils (Chirino and others 2011, Minnick 

and Alward 2012).
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Irrigation can be helpful for restoration plantings, 

although it may be untenable for large restoration 

projects or remote sites where transport is an issue 

and water sources are distant (Anderson and Ostler 

2002). Its feasibility is perhaps highest when restoring 

abandoned agricultural sites with an existing irrigation 

infrastructure. Roundy and others (2001), Chambers 

and others (2014), and Porensky and others (2014) 

demonstrated benefits of sprinkler irrigation for 

restoring abandoned agricultural fields in western 

deserts, although Banerjee and others (2006) noted 

problems with this approach due to weed proliferation 

and accumulation of salinity in the soil from lowquality irrigation water. Alternative irrigation techniques 

such as drip-lines, wicks, and clay pots can be used 

to direct water toward specific plants and/or deeper 

horizons (Bainbridge 2007). Precipitation data from 

weather stations near restoration sites have reportedly 

been used to determine how much irrigation water to 

supply (i.e., to ensure that total monthly water matches 

amounts recorded during years with average to aboveaverage moisture) (Anderson and Ostler 2002, Bashan 

and others 2012, Belnap and Sharpe 1995, Hall and 

Anderson 1999). The importance of watering during 

the appropriate season was highlighted by Allen (1995), 

who found that summer irrigation did not compensate 

for lack of springtime moisture when seeding purple 

needlegrass (Stipa pulchra), a cool-season grass, at a 

summer-drought environment in California.

Beyond direct irrigation, a variety of measures can be 

implemented to enhance or conserve existing water 

supplies at restoration sites. By placing seed at the 

bottom of furrows, drill seeding enhances precipitation 

capture for seedling establishment, and the effect 

can be amplified by deepening the furrows (Monsen 

and Stevens 2004). In a similar manner, pitters and 

imprinters can be used to create micro-catchments that 

capture and concentrate water (Bainbridge 2007, Dixon 

1995, Holden and Miller 1995). Edwards and others 

(2000) found that catchments of 4–25 m2 improved 

establishment for many, but not all, shrub species 

tested at a Mojave Desert site. Because ponded water 

appeared to adversely affect some species planted in 

catchment bottoms, they recommended planting on 

the berm in cases where the soil has low infiltration 

(Edwards and others 2000).

Other treatments aim to improve soil infiltration 

or water-holding capacity. Deep ripping reportedly 

improves water-holding properties of the soil, as well 

as making soil more accessible to plant roots (Brown 

and others 2008, Montalvo and others 2002, Schmidt 

and Belford 1994). Short-term intensive trampling by 

livestock has reportedly increased infiltration on crusted 

sandy loam soils (Roundy and others 1992). On recently 

burned sites, soil water repellency is a common problem 

that could potentially be mitigated through tillage or 

the application of wetting agents (Madsen and others 

2012a, 2012b). Mulches made from materials such as 

straw, gravel, wood chips, and shredded brush may be 

helpful for moderating soil temperatures and reducing 

evaporative water loss from the soil surface (Bainbridge 

2007, Eldridge and others 2012, Nyamai and others 

2011, Winkel and others 1995, Young and others 2013). 

However, Belnap and Sharpe (1995) concluded that dry 

straw mulch was not helpful for plant establishment 

in a cold desert environment with sandy soils having 

poor water-holding capacity. They hypothesized that the 

mulch absorbed water that would otherwise have been 

available to plants, and that by concentrating water near 

the soil surface, plants were triggered to germinate at 

times when deeper water supplies were not actually 

present to sustain them. Fehmi and Kong (2012) drew 

similar conclusions upon finding that mulching led to 

lower seeded plant establishment on very coarsetextured soils (very gravelly sands). Mulches may 

also be problematic if they are applied too thickly and 

thereby have an inhibitory effect on seedling emergence 

(Dodson and Peterson 2010, Winkel and others 1995).

In areas receiving snow, snow fences can be placed 

upwind of plantings to increase soil moisture through 

the accumulation of snowdrifts (Greb 1980). David 

(2013) described snow fences constructed and 

arranged so as to maximize snow capture for sagebrush 

establishment on abandoned natural gas pads in 

Wyoming. Stubble from winter-sown annual crops has 

been used to capture snow on agricultural land in the 

northern Great Plains (Greb 1980), although its effects 

may be negligible in areas with low snowfall and shifting 

wind patterns (Hart and Dean 1986).

Because of water limitations during droughts, it may 

not be possible to establish plants at desired densities 

even when applying the strategies described earlier. 

Resources might thus best be focused on the most 

favorable sites, such as drainages or areas of naturally 

occurring snowdrifts (Meyer 1994), which could later 

serve as centers for vegetation spread. In situations 

where rapid plant establishment is desired for soil 

stabilization, as in post-fire rehabilitation on public 

lands (Beyers 2004), greater emphasis could be placed 

on physical erosion control measures as opposed 
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to revegetation treatments. Runoff and sediment 

loads from recently burned slopes can be reduced 

independent of vegetation by applying straw, bark, 

or wood shred mulch (Fernandez and Vega 2014; 

Groen and Woods 2008; Robichaud and others 2013a, 

2013b) or constructing erosion barriers such as contour 

trenches (Robichaud and others 2008). Wind erosion 

and dust emissions from burned areas have been 

reduced using wind fences, dispersed barriers (e.g., 

plastic cones), and mechanical soil furrowing applied 

perpendicular to prevailing winds (Grantz and others 

1998a, 1998b). Recently developed soil aggregating 

agents (He and others 2008, Liu and others 2012, Orts 

and others 2007, Stabnikov and others 2013) might also 

prove useful for erosion control in certain settings.

Given the cyclical nature of drought, some years will 

likely be much better for restoration plantings than 

others (Holmgren and Scheffer 2001), and to the degree 

that favorable years can be predicted, they should be 

utilized to initiate plant communities that will be able 

to withstand subsequent periods of drought. Plant 

materials selected for restoration plantings should ideally 

be adapted, collectively if not individually, to the full 

range of conditions expected over time at the planting 

sites. If some species are better adapted for higher 

moisture and others for drier conditions, shifts from one 

group to the other may help protect communities from 

extreme fluctuations in biomass during drought cycles 

(Richardson and others 2010, Seabloom 2007, Tilman 

1996, Tilman and Downing 1994). Accordingly, overreliance on one or few species in restoration plantings 

can increase their susceptibility to drought perturbations 

in comparison to more diverse plantings, although 

diversity in and of itself may not be advantageous 

if the species do not complement or compensate 

for each other in some way (Carter and Blair 2012, 

Seabloom 2007). Complementary/compensatory traits 

relevant to restoration of grasslands and shrublands 

include functional type (e.g., grass versus shrub versus 

forb), leaf phenology (e.g., evergreen versus droughtdeciduous; cool- versus warm-season), drought 

dormancy strategy (e.g., seeds versus buds), rooting 

depth, water-use efficiency, and responsiveness to 

changes in water availability within the soil profile 

(Carter and others 2012; Munson 2013; Schwinning and 

others 2002, 2005; Volaire and others 2014; Weaver 

and others 1935). Mariotte and others (2013) found that 

competitiveness of dominant grassland species declined 

during drought, allowing drought-resistant subordinate 

species to assert greater dominance. The subordinates 

in turn reduced the degree to which the dominants 

declined, apparently through facilitative interactions in 

the soil environment (Mariotte and others 2013).

Techniques for restoring species diversity in grasslands 

and shrublands are continually being evaluated and 

improved. Seeding equipment such as the rangeland 

drill, originally designed for seeding a limited class of 

large-seeded grasses, has been modified over time 

to handle a greater diversity of seed types that can 

be planted at different depths (Monsen and Stevens 

2004, Vallentine 1989). The difficulty of establishing 

subordinate forbs in the presence of competitive 

dominant prairie grasses has prompted strategies 

involving seeding rate adjustments and allowing forbs to 

establish prior to interseeding with grasses (Kindscher 

and Fraser 2000) or seeding subordinate and dominant 

species in separate patches (Dickson and Busby 2009).

Genetics-Based Strategies To 

Manage for Drought Resilience

Strategies to manage for drought resilience in grassland, 

shrubland, and desert ecosystems need to incorporate 

an understanding of the genetics of drought tolerance 

in plants (Khasanova and others 2013), how adaptive 

responses to drought vary within and between plant 

species (Cony 1995), and how natural selection 

operates on drought tolerance traits both before and 

after management practices are put into effect (Kulpa 

and Leger 2013). In this section, we explore the 

ecological genetics of drought tolerance in arid-land 

plants and discuss current management strategies that 

incorporate genetic information in drought resilience and 

how these practices might evolve in the face of rapid 

global change.

Ecological genetics of drought tolerance—Drought 

tolerance in plants can be defined as persistence 

through periods of low water availability (Passioura 

1996). A suite of traits that increase water-use 

efficiency by decreasing water loss and/or water use 

through morphological and physiological means, or 

shift phenology and dormancy to avoid water stress 

can contribute to drought tolerance (Chaves and others 

2003, Reich and others 2003). Underlying these traits 

is an array of genetic and developmental pathways that 

control the timing of seed germination, plant growth, 

and reproduction; the development of morphological 

structures, such as leaf shape and lignification; and 

physiological processes, including protein synthesis 

and recycling, carbon uptake, and osmotic adjustment 

(Chaves and others 2003, Ingram and Bartels 1996, 

Peñuelas and others 2013). 
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Traits that have positive effects on plant survival and 

reproduction under drought stress are considered 

adaptive and will be favored by natural selection in 

drought-prone environments (Ackerly and others 2000). 

Because the climatic factors leading to drought stress 

vary substantially through both time and space (Cook 

and others 2004, McKee and others 1993) and interact 

with physiological processes and life history in complex 

ways, plant species will generally exhibit a combination 

of traits that contribute to drought tolerance (Reich and 

others 2003). Also, because species often persist in a 

variety of climatic conditions, populations are likely to be 

adapted to local water availability conditions (Heschel 

and others 2002), which will lead to intraspecific 

variation in drought tolerance across the species range.

Climate change is likely to increase the severity 

and frequency of droughts (Cook and others 2004); 

therefore, plant populations that currently persist in arid 

and semi-arid ecosystems are likely to face increasing 

selective pressure to evolve more robust droughttolerance traits or face local extirpation (Aitken and 

others 2008). With recent climate change, some plant 

species have undergone rapid evolution due to increased 

drought stress (Franks and others 2007). However, 

as rates of change increase, conditions may shift too 

rapidly for most species to evolve rapidly enough (Aitken 

and others 2008). The rate of evolutionary response 

of plant populations to increased drought severity and 

frequency will also depend on a number of species 

and population-specific constraints (Ackerly and others 

2000), including: (1) available genetic variation—

populations with low genetic variation in important 

drought-tolerance traits will be less likely to keep pace 

with changing conditions; (2) life history traits—species 

with complex mating systems, such as those that 

depend on specific pollinators, or species with longer 

generation times, such as trees and shrubs, may be 

more vulnerable to environmental shifts; and (3) genetic 

correlations between selected traits—when selection 

acts in different directions on multiple traits that are 

linked through developmental, physiological, or genetic 

pathways, populations will be less likely to evolve.

Ecological genetics and management strategies—

An understanding of the ecological genetics of drought 

tolerance can help managers practice “evolutionarily 

enlightened management” in drought-prone 

ecosystems (Ashley and others 2003). In particular, 

efforts to conserve plant communities in situ will 

benefit from genetic vulnerability assessments that 

take into account a population’s adaptive match to its 

current environment, its rate of evolutionary response 

as climates shift, and possible constraints on its further 

evolution as conditions continue to change. Plant 

populations that demonstrate adaptive mismatches, 

slow evolutionary rates, or numerous evolutionary 

constraints will require more attention and resources 

than populations that do not face these challenges.

Restoration efforts will also benefit from a genetic 

approach. The use of seed sources that are adapted to 

environmental conditions at a restoration site is widely 

recommended, because these plants are more likely to 

establish and reproduce (Lesica and Allendorf 1999). 

Plants from nearby sources are more likely to have 

adaptive advantages than more distant sources because 

they are likely to have evolved in similar environments 

and be related to local ecotypes. In addition, nearby 

seed sources may be less likely to cause genetic 

swamping, where genotypes of local remnants are 

replaced by introduced genotypes, or outbreeding 

depression, where hybridization with local remnants 

leads to a loss of fitness through the disruption of locally 

adapted gene complexes (Hufford and Mazer 2003).

Artificial selection for drought tolerance—One 

way to use genetic information in wildland drought 

management strategies is through artificial selection 

for drought tolerance. Indeed, since the later part of the 

20th century, greater attention has been directed at 

selecting for drought tolerance in wildland restoration 

species (Johnson and Asay 1993). Delayed stress 

onset, a type of drought resistance in agricultural 

crops developed through genetic engineering, has not 

yet been developed or applied in rangeland or forest 

ecosystems (Lawlor 2013). Assessment of drought 

tolerance in wildland species is often more challenging 

than in agricultural species because plants are rarely 

grown in conditions that approximate their source 

environments, and often little is known about their 

molecular genetics. Therefore, a suite of measurable 

phenotypic traits, such as rapid seedling emergence, 

root development, specific leaf area, and water-use 

efficiency, have generally been used to assess potential 

drought tolerance in wildland plant breeding programs 

(Johnson and Asay 1993).

It is important for managers to understand the selection 

criteria of a germplasm release before using it in 

restoration projects, particularly in drought-prone plant 

communities. In the Western United States, artificial 

selection for drought tolerance has primarily been 

performed on nonnative grasses that are common 
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components of post-fire stabilization seedings (Asay 

and others 2003), though some programs have 

used drought tolerance as a selection criterion in the 

development of native plant releases (Jensen and 

others 2012, Mukherjee and others 2011). Most native 

plant releases have been selected for high growth rates 

and seed production (Asay and others 2003), which 

can lead to high fitness at some wildland sites, but 

may be counter-productive to success in drought-prone 

environments (Kulpa 2010). For example, Kulpa and 

Leger (2013) studied the squirreltail (Elymus elymoides

ssp. Californicus) Toe Jam Creek accession (Jones 

and others 2003, 2004) in two post-fire seedings 

with very low establishment success; they found that 

the surviving populations had undergone extreme 

directional selection for smaller plant and seed size, 

as well as earlier flowering phenology. These traits 

have been associated with drought tolerance in many 

plant species, but ran counter to the initial traits of the 

Toe Jam Creek accession, which was selected for 

release because of its high biomass and seed size. This 

mismatch may have contributed to the low success rate 

of the plantings.

Seed transfer guidelines, drought tolerance, and 

assisted migration—Seed transfer guidelines are 

useful in identifying seed sources that are likely to be 

well adapted to a given transplant location (Campbell 

1991, Ying and Yanchuk 2006). The use of seed transfer 

guidelines dates back to the 1920s in North American 

forestry, when foresters recognized large differences in 

hardiness and growth of trees with different geographic 

origins (Bates 1928, Thrupp 1927). Tree seed transfer 

guidelines were initially based on variation in climatic 

zones within a species range (Haddock 1962), and 

they have been updated as genetic information from 

common garden studies has become more available 

(Campbell 1986, St. Clair and others 2005). In the past 

decade, managers and researchers have recognized the 

usefulness of seed transfer guidelines in the restoration 

of nonforest communities, particularly in arid and 

fire-prone environments (Erickson 2008; Johnson and 

others 2004, 2010a), and seed transfer guidelines have 

been developed for grass (Erickson and others 2004, 

Johnson and others 2010b, St. Clair and others 2013), 

forb (Johnson and others 2013), and shrub (Horning and 

others 2010) species in the intermountain west. 

While seed transfer guidelines do not focus on drought 

tolerance per se, they do delineate climatic zones where 

populations of a given species are likely to be adapted, 

which can be useful in finding seed sources that can 

persist in arid conditions (Ying and Yanchuk 2006). In 

addition, species-specific guidelines are developed 

using multivariate analyses of common garden data 

on climatically based adaptive traits (Campbell 1991), 

and these data allow researchers to find traits that 

correlate with specific environmental conditions. For 

example, St. Clair and others (2013) found that in 

bluebunch wheatgrass (Pseudoroegneria spicata), leaf 

length-to-width ratio (measure of length adjusted leaf 

narrowness) was highly correlated with annual heat 

moisture index (a measure of aridity). This makes sense 

because narrower leaves are less likely to suffer from 

water loss in stressful conditions due a lower number of 

exposed stomata. To help refine seed source selection 

decisions, research is needed to identify populations 

with traits that contribute to drought tolerance.

Assisted migration, a management strategy where 

organisms are translocated from sites with suboptimal 

environmental conditions to sites with more optimal 

conditions, may become integral to conservation 

strategies as the rate of climate change increases 

(Peters and Darling 1985). Assisted migration can 

encompass a broad range of goals, from minimizing 

loss of biodiversity to preventing extinction, and operate 

at a range of spatial scales, from local to continental 

(Williams and Dumroese 2013). Seed transfer 

guidelines, because they determine transfer distances 

that avoid maladaptation (Johnson and others 2004) and 

can be re-projected using models of expected future 

environmental conditions (Thomson and others 2010), 

will play an integral role in the planning of assisted 

migration efforts under global change.

Conclusions

To conclude, drought has significant ecological 

impacts—both direct and indirect—on native rangeland 

plant species, including effects on their physiology, 

growth, reproduction, physiognomy, and abundance. 

Drought also impacts rangeland ecosystem functioning 

and resilience through impacts on water availability, 

soil integrity, habitat, wildlife populations, livestock, and 

humans. Drought influences the likelihood and dynamics 

of other stressors and disturbances such as insect 

outbreaks, invasive species, wildfire, and human land 

uses. Drought often requires adjustments in methods 

for managing livestock and restoring plant communities. 

Managing and restoring native plant communities 

resilient to drought and climate change involves 

matching seed sources and adaptive traits to appropriate 

environmental and climatic conditions. Seed transfer 
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guidelines and assisted migration techniques are being 

developed to aid managers in need of restoration tools in 

the face of drought and climate change. 

Acknowledgments

We thank anonymous reviewers for their helpful 

comments, Karen Bagne for assistance in literature 

review, and Nancy Shaw for review of sections of the 

chapter. 

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CHAPTER 9 CHAPTER 9

S.P. Norman is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Eastern Forest Environmental Threat Assessment 

Center (EFETAC), Asheville, NC 28801.

F.H. Koch is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Eastern Forest Environmental Threat Assessment 

Center (EFETAC), Asheville, NC 28801.

W.W. Hargrove is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Eastern Forest Environmental Threat Assessment 

Center (EFETAC), Asheville, NC 28801.

Detecting and Monitoring 

Large-Scale Drought Effects 

on Forests: Toward an 

Integrated Approach

Steven P. Norman

Frank H. Koch

William W. Hargrove
196

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Detecting and Monitoring Large-Scale Drought Effects on Forests: Toward an Integrated Approach

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

Although drought is recognized as an important and 

overarching driver of ecosystem change, its occurrence 

and effects have been difficult to describe over large 

geographic areas (Hogg and others 2008, Panu and 

Sharma 2002). In forests, drought contributes to tree 

stress and mortality through the direct impacts of 

reduced moisture and high temperatures (Anderegg 

and others 2013, Wang and others 2012), and through 

indirect pathways such as increased disturbance 

from insects or fire (Martínez-Vilalta and others 2012, 

Mattson and Haack 1987, Meyn and others 2007, 

Raffa and others 2008, Schowalter and others 1986, 

Trouet and others 2010). Detecting drought effects 

on plant species demands detailed knowledge of 

where those species occur, but with few exceptions, 

only coarse vegetation maps are available for broad 

areas (Allen and others 2010). Long-term monitoring 

is helpful, but longer term assessments struggle with 

causal attribution. Numerous meteorologically based 

drought measures have been constructed to depict 

moisture deficits in agricultural contexts, but they may 

not accurately portray the effects of those deficits on 

forests, grasslands, or other natural vegetation types, 

where the constituent species may have diverse 

drought responses (Mishra and Singh 2010, VicenteSerrano and others 2012). Furthermore, in order to 

examine those responses, meteorologically based 

approaches must make an inference about the impact of 

a given level of moisture deficit on the plants. Remote 

sensing-based measures are also available that exploit 

known differences in reflected radiation among stressed 

and unstressed vegetation (Peters and others 1991, 

Peters and others 2002, Zhang and others 2013), yet 

short-term stress may not be a precursor for ecological 

impacts that could take multiple seasons or even years 

to materialize.

Measures available from meteorological station data 

can be used to infer likely moisture and temperature 

impacts on trees or other vegetation (Vicente-Serrano 

and others 2012). When summarized for different time 

periods deemed relevant (e.g., with respect to tree 

mortality, multiple consecutive years of severe drought) 

(Guarín and Taylor 2005, Millar and others 2007), they 

can better approximate impacts like vegetation loss or 

cover change. Further assessments can come from 

direct measurements from remotely sensed or plot 

data (Ji and Peters 2003, Vicente-Serrano and others 

2012, Vicente-Serrano and others 2013, Wullschleger 

and Hanson 2006, Zhang and others 2013). With 

advances in near-real-time meteorological and remotely 

sensed response technology, it is now possible to 

generate reasonable coarse-scale forecasts of certain 

drought effects, such as declines in crop yields (Arshad 

and others 2013, Hao and others 2014, Luo and 

Wood 2007). However, finer-scale translation of such 

expectations for forested areas remains challenging 

due to a lack of species- and community-specific longterm impact assessments (Carnicer and others 2011, 

Martínez-Vilalta and others 2012, Michaelian and others 

2011). This chapter reviews the status and role of data 

mining approaches using diverse ancillary data sets that 

can be brought to bear on monitoring and assessment, 

and clarifies ways in which they can be leveraged 

to reduce the uncertainties associated with drought 

impacts in forested ecosystems.

Fundamental Challenges

Drought can have a range of species- and communitylevel consequences for forests, many of which are 

poorly understood (Hanson and Weltzin 2000, Mueller 

and others 2005). The drought responses that can be 

systematically monitored at regional scales are only 

a detectable subset of all those that likely occur or 

matter, and this introduces uncertainty into monitoring 

and assessment. Breadth and efficiency are often the 

practical tradeoffs of having depth of understanding. 

With such uncertainties, our expectations for broadscale monitoring are somewhat different from what can 

be obtained through local field-based observations.

Broad-scale monitoring is intended to describe the scope 

and relative severity of coarse drought impacts, rather 

than to quantify effects directly with precision that often 

depend on local knowledge of topography, weather, 

or species responses. The coarse-scale expectations 

of such efforts justify application of relative drought 

indices instead of actual biophysical measurements such 

as soil moisture, temperature, or precipitation. In turn, 

broad-scale drought monitoring produces only relative 

likelihoods, but such insights may be the most relevant 

for a particular set of management questions.

To progress as an applied science, broad-scale drought 

monitoring must confront four fundamental challenges 

that are described below. Meeting these challenges will 

improve our ability to comprehend, predict, and address 

the risks posed to forests by drought.

Challenge 1: Measuring drought in ways that 

matter for different forests—Our conventional 

perceptions of drought and its effects have primarily 
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developed from how drought impacts agricultural 

production and water supplies (Wilhite and Glantz 1985). 

Yet the conventional meteorological measures of drought 

that estimate effects to field or stream may be less than 

optimal for characterizing drought impacts to forests.

When a broad-scale drought response is detected for 

forests, its implications are far more complex than 

mono-specific crop yield reduction or lowered water 

levels in reservoirs, where there is a clearer expectation 

of loss. Forests and their constituent species are highly 

variable in their tolerance of and response to drought, 

such that no single metric or indicator is likely to capture 

expected impacts (Martínez-Vilalta and others 2012, 

Mishra and Singh 2010, Svoboda and others 2004). 

Unlike annual field crops, most perennials within forest 

communities are tolerant of one or more years of 

moderate drought stress, and so scientists contend that 

multiyear measures of drought are needed (Allen and 

others 2010, Mishra and Singh 2010, Niinemets 2010, 

Panu and Sharma 2002, Wilhite and others 2007).

Interpretations of drought responses are especially 

difficult in areas of high compositional or structural 

complexity, as the sensitivity of deciduous and 

evergreen trees, shrubs, and grasses are generally not 

equivalent (Hanson and Weltzin 2000). Interpretation of 

drought effects becomes more challenging in areas that 

have been recently disturbed as these landscapes have 

vegetation in various stages of successional recovery 

with dominant species that may differ in their response 

to drought from one decade to the next (Sousa 1984). 

Similarly, it can be difficult to make sense of broad-scale 

drought responses in highly fragmented landscapes 

where forest, field, and developed areas occur in close 

proximity (Ewers and Didham 2006, Laurance 2004). 

We need clearer drought response indicators for these 

types of landscapes.

The ramifications of drought for species depend on 

when the drought occurs with respect to species’ 

seasonal phenologies (Anderegg and others 2013). 

In the Eastern United States, spring and summer 

growth often responds to winter, spring, and summer 

temperature and precipitation, but summer and fall 

drought can shorten the growing season. A number of 

western tree species depend heavily on winter rains or 

snowpack to provide a pool of available soil moisture for 

the subsequent growing season, which is effectively 

shortened when this pool is reduced (Hanson and 

Weltzin 2000). The relative importance of heat and 

moisture stress may differ (Bréda and others 2006, 

Mueller and others 2005, Orwig and Abrams 1997) due 

to fundamental regional differences in the evolutionary 

climatic environment. Because of these inherent climatic 

differences, regional patterns of species adaptations 

affect how meteorological drought is experienced, and 

how effects are shown (fig. 9.1).

Challenge 2: Establishing context from historical 

data—In an operational sense, drought is more 

than heat and dryness (chapter 2). It involves some 

measure of departure from baseline conditions for a 

given location and specified time period. Both spatial 

and temporal aspects of this definition are critical for 

accurate recognition and prediction of broad-scale 

drought effects. Extended periods of seasonal and 

interannual dryness are a normal part of many forest 

environments, particularly across much of the Western 

United States (fig. 9.1). Multiyear or decadal averages, 

as reflected in the term “normal,” can mask this climate 

variability, yet depending on the frequency and intensity 

of droughts that occur, both species and community 

attributes may be adapted to climatic extremes as much 

as, if not more than, any measure of central tendency.

Historical climate data provide both meteorological 

and biologically relevant context. Long-term 

paleoclimatological insights help contextualize the 

duration and intensity of recent drought events (chapter 

2), but the relevance of historical drought patterns for 

contemporary forests and values can be difficult to 

ascertain where forest structure or composition have 

changed. From a meteorological perspective, the length 

of climatically meaningful baselines has been long 

debated (Lamb and Changon 1981, Livezey and others 

2007, Wilks 2013), yet determining the period that is 

appropriate for understanding forest change may be far 

more difficult.

Commonly used 30-year baseline conditions may not 

be representative of the climate that existed when 

the longest lived trees established or developed. Tree 

species that produce many vegetative sprouts (as 

opposed to slower growing seedlings) after disturbance 

may subsequently have so many saplings that they 

retain demographic dominance in a site for centuries, 

regardless of the age of existing stems, and sprouting 

trees dominate many forest landscapes (Bellingham 

and Sparrow 2000, Bond and Midgley 2001, Del 

Tredici 2001, Vesk and Westoby 2004). Moreover, the 

relevant climate context for old forests may be longer 

than for adjacent areas affected by disturbance and 

recent succession. For example, the timing of drought 
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NY-3 OR-8 

TX-6 

NC-1 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

CA-6 

NY-3 

OR-8 

CA-6 

Precipitation (inches) Precipitation (inches) 

NC-1 

TX-6 

 Mean NDVI Mean NDVI Mean NDVI 

Precipitation (inches) 

Figure 9.1—Regional differences in normal seasonal precipitation can affect how forests respond to drought. These graphs show 

historical variability in monthly precipitation for five National Climate Data Center (NCDC) Climate Divisions, 1895–2013, compared 

to the mean land surface phenology of forested Moderate Resolution Imaging Spectroradiometer (MODIS) pixels in those divisions 

as measured by the Normalized Difference Vegetation Index (NDVI) for the period 2000–2012. Box-whisker plots show the mean, 

extremes, and upper and lower quartiles of precipitation. Biweekly NDVI (green line) was derived from a National Land Cover Data 

(NLCD-2006) conditional filtering of majority forested ForWarn-MODIS data that included the following count of randomly selected 

cells: CA-6, n=110; NC-1, n=480; NY-3, n=474; OR-8, n=571; TX-6, n=247.
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episodes during the late 20th century affected the 

establishment success of white pine (Pinus strobus) in 

old fields of the North-Central United States (Dovčiak 

and others 2005). Similarly, long-lasting cohorts of 

ponderosa pine (Pinus ponderosa) established during 

favorable climate windows in the Southwestern 

United States during the early 20th century (Savage 

and others 1996). Although forest changes caused by 

drought-associated mortality may be rapid (Mueller and 

others 2005, Wang and others 2012), we may need a 

long climatic perspective to make sense of observed 

changes over the lifespan of these forest dominants.

The relevance of past forest responses to drought 

for understanding those of the present is sometimes 

questionable, as the structure and composition of many 

forests has changed over the last century in response 

to logging, invasive insects, diseases and plants, fire 

exclusion, and livestock grazing (Norman and Taylor 

2005, Nowacki and Abrams 2008). Increases in stand 

density and a decline in drought-tolerant species such 

as pines, oaks, and chestnut can make forests less 

resilient today than they were decades ago to drought 

or drought-associated disturbances such as fire (chapter 

7). This potential shift in the implications of a given 

drought erodes the predictive capacity of efforts that 

rely only on meteorological data.

Trends in climate can pose serious problems for 

developing meaningful baselines (Wilks 2013). Such 

gradual transitions may reflect the progressive effects 

of a drying climate, and that rate of change is difficult to 

detect without long-term monitoring or broad-scale plot 

data (Woodall and others 2009). Mesophytic species 

may be expanding in importance from fire management, 

which could increase forest vulnerability if severe 

drought returns (Nowacki and Abrams 2008). Forests 

may be more vulnerable because of the increased 

water needs of denser stands or more mesophytic, 

less drought-tolerant species composition (Allen and 

Breshears 1998, Guarín and Taylor 2005, Savage 1997). 

While meteorological data provide insights into where 

meteorological trends are occurring (fig. 9.2), our 

knowledge of long-term trends in forest susceptibility is 

more limited.

Our primary broad-scale insights into how forests 

respond to drought comes from satellite observations, 

yet high-resolution satellite data have only been available 

for a third of the time that meteorological data have 

been collected on a wide scale. This shorter observation 

window limits what we can learn from historical 

drought responses as shown through comparison of 

growing-season drought duration during the Moderate 

Resolution Imaging Spectroradiometer (MODIS) satellite 

period with prior baseline periods (fig. 9.3). In this 

example, drought duration was derived from monthly 

National Oceanic and Atmospheric Administration 

(NOAA) National Climate Data Center (NCDC) Climate 

Division data (Guttman and Quayle 1996). Satellites 

that pass overhead frequently, such as Terra and Aqua 

that carry the MODIS sensor, can be used to identify 

short-term stress and longer term recovery or type 

conversion; however, their coarser resolution makes 

them less useful for monitoring species-specific stress 

in mixed stands over broad areas than less frequent, but 

higher resolution data. Derived products from satellite 

observations can help characterize similarities and 

differences among droughts, as observations coarsely 

quantify how forests are affected by drought and 

drought-associated disturbances.

Challenge 3: Capturing diverse drought effects—

As an indicator for a suite of other potential drought 

impacts, vegetation stress monitoring is efficient, even 

if it does not predict specific individual tree responses. 

Such efforts only capture a fraction of drought-induced 

effects to forests, but those aspects that can be 

monitored can be strong indicators of system dynamics 

overall. For example, morphological adaptations, such as 

deeper rooting, are nearly impossible to quantify from 

either a remote-sensing or field-based perspective, but 

defoliation or canopy stress can be readily monitored.

It is difficult to translate community-level observations 

to species- or population-level responses when the 

constituent species in a region vary in their susceptibility 

and tolerance to drought (Bigler and others 2007, Floyd 

and others 2009, Hanson and Weltzin 2000, McDowell 

and others 2008, McDowell and others 2011). Individual 

species drought responses can be wide-ranging, 

divergent, or delayed (chapter 3) (Archaux and Wolters 

2006). Community-level responses include reduced 

productivity and altered composition or structure 

largely through selective mortality (chapter 4) (Archaux 

and Wolters 2006). Drought can also have secondary 

effects on the population dynamics of insects and 

diseases (chapter 6) (fig. 9.4), or on the occurrence, 

attributes, or consequences of wildfire (chapter 7), 

since stressed trees are often more susceptible. 

Drought stress induces ponderosa pine to leave 

stomates open at night, increasing exposure to ozone 

and other airborne pollutants (Grulke and others 2004). 

Grulke (2011) reported that drought stress increases 
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WA-1 MN-3 

CA-6 

TX-6 

WY-1 

PA-10 

FL-1 

Slope

< -0.05

-0.05 to -0.01

-0.01 to 0.00

0.00 to 0.01

0.01 to 0.05

>0.05

MODIS period 

Figure 9.2—Long-term trends (black line) in the mean April–September Palmer Modified Drought Index (PMDI), 1895–2013, by 

National Climate Data Center (NCDC) Climate Division for the conterminous United States. Selected climate divisions are shown. 

The representativeness of the Moderate Resolution Imaging Spectroradiometer (MODIS) period relative to the past is suggested by 

the blue bar in the lower right of each inset graph. 
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(A)

(B) 

(C)

MODERATE DROUGHT

PMDI < -1.0 

SEVERE DROUGHT

PMDI < -2.0 

Growing season drought duration departure in years 

 

 

Longer drought 

during prior period 

Longer drought

during MODIS period

-5 -4 -3 -2 -1 0 1 2 3 4 5

Figure 9.3—Annual departure, by National Climate Data Center (NCDC) Climate Division, of mean April–September Palmer 

Modified Drought Index (PMDI) drought duration for the Moderate Resolution Imaging Spectroradiometer (MODIS) period 

(2000–2013) compared to historical drought duration for three baseline periods: (A) 1900–1999, (B) 1950–1999, and (C) the 

14 pre-MODIS years, 1986–1999. Differences at two levels of drought severity are shown: severe drought (PMDI <-2.0) and 

moderate (PDMI <-1.0).
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Figure 9.4—Variation in regional Palmer Hydrological Drought Index (PHDI) for northwestern Colorado and its relationship 

to outbreaks of the spruce beetle (Dendroctonus rufipennis). Regional drought is strongly influenced by hemispheric-scale 

variation in sea surface temperatures, particularly the Atlantic Multi-decadal Oscillation (AMO). 
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susceptibility to many pathogens that may be emerging 

with climatic change. While community-level response 

may not represent all impacts of concern, it provides the 

spatial pattern of likely effects across the landscape.

Variation in community-wide growing season stress 

may be the easiest drought-sensitive indicator to 

measure using remote sensing technologies. Highfrequency observations can detect drought progression 

or near-real-time stress or mortality from wildfire or 

insects and disease (Hargrove and others 2009). From 

programmatic high-frequency datasets, measures of 

temperature and moisture-sensitive phenomena can 

be derived such as change in the onset of spring and 

fall and the duration of the growing season. These 

community-level measures of observed land surface 

phenological changes can be related to the responses 

of individual species and seasonal disturbances such as 

wildfire.

Some drought effects are difficult to recognize or 

track without ancillary information. The drought 

responses of different vegetation types are known to 

vary (Lobo and Maisongrande 2006, Sims and others 

2014), so knowing the vegetation composition within 

particular remotely sensed grid map cells is critical for 

understanding both drought response and multiyear 

drought effects. Tree mortality can be delayed for years, 

and reduced vigor can invite second-order effects 

(Bigler and others 2007). This potential lag in response 

makes attribution more difficult without long-term 

datasets and modeling. Impacts from disturbance 

such as wildfire, insects, and diseases can be difficult 

to attribute to drought, since these are often a natural 

part of forests. With complex drivers in play, ancillary 

datasets can improve interpretations and predictions.

Conceptual models provide a graphical means of 

communicating these complex direct and indirect 

interactions. Figure 9.5 shows two example conceptual 

models for drought: a basic model of the direct 

relationships between drought, other drivers of forest 

disturbance, and their impacts (fig. 9.5A), as well as 

a more detailed model of the indirect relationships 

between drought and other landscape-level processes 

in the Interior West (fig. 9.5B). Within such models, 

contingencies can be structured as management 

options that can mitigate or prevent undesirable 

drought-associated effects. For example, in California’s 

Yosemite National Park, where tree mortality has 

been associated with drought, drought susceptibility 

may have increased due to a fire management history 

that has resulted in uncharacteristically dense stand 

structures that affect competition and water stress 

(Guarín and Taylor 2005). Thus, silvicultural methods 

such as mechanical thinning or fire may be viable 

options for improving stands and reducing the likelihood 

of drought-related tree mortality.

Challenge 4: Making drought-effect monitoring 

more applied—Broad drought-monitoring efforts 

capture changes to vegetation rather than impacts to 

individual trees. Detection of local effects is inferential 

due to the coarse nature of broad-scale observations. 

Local forest managers are usually aware when drought 

and drought-associated stresses are affecting their 

forests, yet recognizing and tracking drought effects 

becomes more difficult over States or regions. When 

large areas are affected by drought, the broad-scale need 

is often to identify those areas that are hardest hit and 

to prioritize areas for response. Such decisions can be 

greatly informed by relatively straightforward measures 

derived from systematic drought monitoring efforts.

Fire Mortality 

Drought 

Fuels 

Beetles 

Response 

Management 

Ignition 

Composition & 

structure 

Stress 

Burn 

conditions 

(B)

Disturbance Outcome 

Drought 

Nondrought 

drivers 

indirect direct 

indirect direct 

(A)

Figure 9.5—Conceptual models show how outcomes can result 

from direct and indirect climate effects or from unrelated 

nondrought drivers, such as land use change, management 

actions, or succession or other biological processes (A). For 

specific environments such as the dry forests of the Interior 

West, causal models can organize and communicate more 

explicitly the complex interconnectedness of landscape 

processes such as drought, fire, beetles, and management on 

tree mortality (B).
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Near-real-time drought-effect monitoring has been 

implemented for agricultural and grazing systems that 

are sensitive to seasonal and short-term drought effects 

(Brown and others 2008). Efforts have also been 

developed to improve fire hazard assessments using 

near-real-time information about the state of droughtsensitive fuels (Schneider and others 2008). These 

systems are highly applicable to areas with relatively 

homogenous, drought-sensitive vegetation types, but 

where land use is mixed, drought-effects monitoring 

systems are less likely to provide clear information 

for forest managers. Forests, especially those with 

an evergreen component, are generally less sensitive 

to drought than are grasslands or crops. In areas of 

more fragmented land use, this variable sensitivity 

makes it far more difficult to interpret drought effects. 

Geographic patterns in observed stress responses 

could result from actual differences in drought intensity 

or they could be from different sensitivities caused 

by the mix of cover type. Year-to-year changes in land 

use make interpretation more difficult. Use of ancillary 

datasets can help to filter out these less reliable areas 

entirely, or can be used to develop vegetation-specific 

models calibrated to their drought sensitivities (Lobo 

and Maisongrande 2006).

Finer resolution imagery can be useful for identifying 

specific drought responses, particularly for localized 

areas. While even fine-resolution imagery can harbor a 

mix of cover types that can hamper interpretations of 

drought effects, the mixture of grass, shrub, trees, or 

crops generally decreases at finer spatial resolutions 

(fig. 9.6). Small inholdings of drought-sensitive 

vegetation could also be important drought indicators 

in mixed landscapes, particularly where meteorological 

station data are lacking.

While local needs often benefit from high-resolution 

drought monitoring products, these come at a 

computational cost, which usually involves reduced 

product frequency (fig. 9.7). To detect and monitor 

forest drought stress, coarse-resolution products can 

be effective, but for questions of tree mortality or 

other detailed impacts, finer resolution research may 

be necessary. Such local management questions 

may require local assessments that are calibrated and 

tempered with information gathered in the field.

Existing Approaches Used 

for Broad-Scale Drought Impact 

Detection and Monitoring

Extended periods of extreme drought result from 

persistent continental- to global-scale climate patterns 

that affect landscapes and regions. The large extent 

and contiguity of potential drought impacts helps us 

identify where drought is occurring because long-term 

meteorological or stream gauge data are sparse and their 

use normally requires interpolation. Drought can also be 

inferred from satellite-based observations of temperature 

or precipitation, though not without difficulties. Further 

insights into drought occurrence can be harvested from 

drought effects to sensitive vegetation as observed from 

satellites, yet vegetation change can also be caused by 

factors other than drought, such as disturbance. While 

these individual approaches for detecting and tracking 

1000 m 232 m 30 m 

(A) (B) (C) 

Figure 9.6—Mixed vegetation or land cover types that can result from different spatial resolutions, including: (A) 1000 m, (B) 232 m, 

and (C) 30 m grid cell widths. Products delivered at these resolutions would only provide one value for each unit area above, which 

typically decrease in diversity from left to right depending on the patch size of the vegetation.
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drought have limitations, integrated monitoring systems 

can combine their particular strengths (Lawrimore and 

others 2002, Steinemann 2003, Svoboda and others 

2002, Svoboda and others 2004, Tadesse and others 

2005). It should be noted, however, that none of these 

integrated systems specifically focus on drought stress 

in forested ecosystems.

Meteorology-Based Measures of Drought

Primary meteorological measurements are not 

themselves the strongest predictors of drought effects. 

Various combinations of mostly temperature and 

precipitation measurements have been formulated 

into indices that are designed to provide droughtspecific interpretations (table 9.1). These indices can 

be calculated directly at the locations of meteorological 

stations, producing a point-based map, or from gridded 

datasets (e.g., interpolated station data or reanalysis 

files). Although all of the indices in table 9.1 estimate 

the degree of moisture deficit in some context, they are 

typically associated with a particular class of drought—

meteorological, agricultural, or hydrological drought 

(chapter 2). Some indices, such as the Surface Water 

Supply Index (SWSI), have distinctive formulations that 

are clearly applicable to one drought class (hydrological 

drought, in this case). For other indices, however, 

these class associations appear to derive from subtle 

differences in how the indices operate through time. 

For instance, the Palmer Hydrological Drought Index 

(PHDI) rebounds less quickly from moisture surpluses 

or deficits than the similarly calculated Palmer Drought 

Severity Index (PDSI), which is generally considered a 

meteorological drought index (Palmer 1965). Likewise, 

the related Palmer Z-index (considered an index of 

agricultural drought) is more responsive to short-term 

moisture anomalies than either the PHDI or PDSI.

Most of the indices in table 9.1 are, like the PDSI, 

calculated using a water-balance approach between 

precipitation and potential evapotranspiration (PET). 

Indeed, many of the indices in table 9.1 represent direct 

modifications of the PDSI in response to perceived 

limitations. For instance, Heddinghaus and Sabol (1991) 

introduced Palmer Modified Drought Index (PMDI), a 

revised version of the PDSI. Their revision addressed 

one of the major areas of criticism regarding the PDSI: 

the determination of wet and dry spells. The PMDI 

yields a continuous measure that is less volatile than 

the PDSI, such that it can accurately capture a linear 

combination of temperature and precipitation effects 

across broad geographic regions (fig. 9.8).

A notable departure from the PDSI and other waterbalance-based indices is the Standardized Precipitation 

Index (SPI). The SPI characterizes moisture conditions 

during multiple, well-defined time windows; it is also 

considered more consistent across geographic space. 

Nonetheless, it only uses precipitation data, which 

could be an important limitation in the face of increasing 

recognition that high temperatures exacerbate drought 

impacts on forest mortality (Allen and others 2010, 

Breshears and others 2005, McDowell and others 

2008, Mitchell and others 2014, Vicente-Serrano 

and others 2013, Williams and others 2013). The 

Standardized Precipitation Evapotranspiration Index 

(SPEI) incorporates temperature into the water-balance 

equation via PET, but also follows the multi-temporal 

implementation of the SPI. The SPEI has outperformed 

the PDSI for monitoring drought impacts on “vulnerable 

systems” (i.e., for capturing impacts on indicator 

variables such as streamflow, soil moisture, forest 

growth, and crop yields), and appears to be better 

than the SPI at capturing drought conditions during the 

summer, when drought monitoring is arguably most 

critical (Vicente-Serrano and others 2012).

Ultimately, no meteorology-based drought index—

regardless of its specific strengths or limitations—is 

appropriate in all circumstances. For national- or 

regional-scale analysis of drought, no single indicator 

is likely to be sufficient (Steinemann 2003). The U.S. 

Drought Monitor (DM), developed by the National 

1

100

10,000

1,000,000

100,000,000

10,000,000,000

1,000,000,000,000

100,000,000,000,000

1 30 232 1,000

Number of pixels

Resolution (m)

Annual Monthly Weekly

Figure 9.7—Potential tradeoffs between spatial and temporal 

resolution measured in terms of the number of pixels per 

year needed to cover the conterminous United States with a 

remotely sensed product set of a given frequency and spatial 

resolution. Standard vegetation products from Landsat are 

at 30-m resolution, while products from Moderate Resolution 

Imaging Spectroradiometer (MODIS) are 232-m resolution, and 

products from Advanced Very High Resolution Radiometer are 

1000-m resolution. 
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Table 9.1—Major meteorological (i.e., weather-station-based) drought indices used in the United States and elsewhere

Index Key citation(s) Typea Foundation Components/inputs RemarksPalmer Drought Severity Index (PDSI)

Palmer (1965) M Water balance model Precipitation and temperature; 

Accounting done with five parameters: precipitation, evapotranspiration (ET) potential evapotranspiration (PET), soil moisture loss and recharge, and runoff

Preceded by a number of less sophisticated indices; like many other indices, enabled by the work of Thornthwaite (1948) on modeling PET; the PDSI has often been criticized but has been widely accepted despite its limitations

Palmer Hydrological Drought Index (PHDI) 

Palmer (1965) H Water balance model Precipitation and temperature; 

calculated during an intermediate step when computing PDSI

Very similar to the PDSI; uses same water balance model, but rebounds less quickly from a moisture deficit or surplus than the PDSI 

Palmer Moisture Anomaly Index (Z-index)

Palmer (1965) A Water balance model Precipitation and temperature; also 

calculated as an intermediate step when computing PDSI

Reflects departure of weather in a particular month from the average moisture climate for that month, regardless of conditions in prior or subsequent months; more responsive to short-term moisture anomalies that the PDSI or PHDI

Crop Moisture Index (CMI)

Palmer (1968) A Water balance model Precipitation and temperature; uses 

weekly means

Also developed by Palmer; effective at measuring agricultural drought during the growing season; like the Z-index, focuses on short-term moisture conditions

Keetch-Byram Drought Index (KBDI)

Keetch and Byram (1968); Burgan (1988) 

M Water budget model Precipitation and soil moisture Forest Service product; developed for wildfire managers 

in the Southeastern United States, but implemented as a stand-alone drought index by Burgan (1988); values (hundredths of inches) range from 0 (no soil moisture depletion) to 800 (completely saturated soil)

Surface Water Supply Index (SWSI)

Shafer and Dezman (1982); revised by Garen (1993)

H Available surface water 

including snowmelt

Measurements for snowpack, precipitation, streamflow, reservoir storage

Statistical properties poorly understood; difficult to compute; mostly used for western United States river basins (i.e., places where snowmelt strongly influences streamflow)

Soil Moisture Anomaly Index

Bergman and others (1988)

A Water balance model Uses PET (Thornthwaite 1948) Developed for global-scale climate monitoring; values 

change at an intermediate rate somewhere between the CMI (fast) and the PDSI (slow)

Palmer Modified Drought Index (PMDI)

Heddinghaus and Sabol (1991)

M Water balance model Same inputs as PDSI. Still uses X1 

and X3 terms, but in a slightly different fashion (see next box)

Operational modification of the PDSI; modified rules for index response during wet and dry spells; prevents sudden flipping from positive to negative index values (and vice versa); modified index is continuous and likely to be normally distributed

Standardized Precipitation Index (SPI)

McKee and others (1993)

M Precipitation probability Precipitation only; standardized 

departure with respect to a rainfall probability distribution

Typically calculated for multiple time windows (e.g., 1, 3, 6, 9, and 12 months); main criticism is that it only includes precipitation

Soil Moisture Percentiles

Andreadis and others (2005)

H Available soil moisture Modeled soil moisture values Modeled values from precipitation and soil information, 

which across regions or continents may lack detail/accuracy

Standardized Precipitation Evapotranspiration Index (SPEI)

Vicente-Serrano and others (2010)

M Water balance model Precipitation and temperature Multi-scale (i.e., incorporates multiple time windows) like 

the SPI, but also includes temperature via PET (calculated using the Thornthwaite method)

a Type: M = meteorological, H = hydrological, A=agricultural.
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Drought Mitigation Center (NDMC) with cooperation 

from the U.S. Department of Commerce and U.S. 

Department of Agriculture (Svoboda and others 2002), 

and the related North American Drought Monitor 

(NADM) (Lawrimore and others 2002), were designed 

to integrate six key and numerous supplementary 

indicators—some from station data, others via 

remote sensing—to estimate drought severity, albeit 

subjectively. The PDSI and the SPI are key indicators 

in the U.S. and North American Drought Monitors, 

while the Crop Moisture Index (CMI), the KeetchByram Drought Index (KBDI), and the Surface Water 

Supply Initiative (SWSI) are among the supplementary 

indicators (see table 9.1).

Strengths and weaknesses of meteorology-based 

indices—The primary strengths of meteorology-based 

indices are that precise monthly meteorological data 

are widely available for most portions of the United 

States, and regional data extend back in time a century 

or more to provide a relatively consistent climate 

context. Individual monthly temperature station records 

in the Global Historical Climatology Network (GHCN) 

date to as early as 1701 (Lawrimore and others 2011). 

Observations from 69 countries and territories were 

available by 1880. A fairly robust station network was in 

place for the continental United States (and Hawaii) by 

the late 1800s (Menne and others 2012).

Satellites are comparatively expensive to manage and to 

maintain a calibrated and continuous record (Lawrimore 

and others 2011, Mendelsohn and others 2007, Menne 

and others 2012). However, the low spatial density of 

meteorological stations necessitates the use of spatial 

interpolation, which, despite significant methodological 

advances in recent decades (Daly and others 2002, 

Daly and others 2008), can fail in heterogeneous 

terrain and microclimates. The GHCN daily dataset 

has data from more than 80,000 weather stations 

worldwide, but about two-thirds of the stations only 

record precipitation, and not temperature (Menne and 

others 2012). By comparison, the GHCN monthly mean 

temperature dataset provides data for 7,280 stations 

from 226 countries and territories, plus ongoing monthly 

updates for more than 2,000 stations (Lawrimore and 

others 2011). The continental United States has one 

of the greatest temperature station densities, both 

historically and currently of any World region (Menne 

and others 2012). GHCN stations represent only about 

10 percent of all weather stations available in the United 

States (Daly and others 2008), although missing data 

are still an analytical impediment.

(A) Precipitation

(B) Temperature

(C) Palmer Modified Drought Index

Pearson’s r values

-1.00 to -0.67

-0.66 to -0.34

-0.33 to 0.00

0.01 to 0.33

0.34 to 0.66

0.67 to 1.00

Figure 9.8—Correlations (Pearson’s r) between mean March–

September Moderate Resolution Imaging Spectroradiometer 

(MODIS)-based ForWarn Normalized Difference Vegetation 

Index (NDVI) and National Land Cover Data Climate Division 

mean monthly March–September for (A) temperature, (B) 

precipitation, and (C) Palmer Modified Drought Index (PMDI), 

2000–2012, based on 250,000 random points sampled with a 

1-km buffer.
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Another issue is that the formulations of most 

meteorology-based indices are biased in favor of crops 

that are harvested after a single growing season. Few 

of these indices carry much information about historical 

conditions, and when they do, it is on the order of 

months rather than years. For example, the SPI considers 

a 12-month history; the SPEI is the longest, with a 

24-month “memory.” Trees are more resilient to drought 

effects, making it necessary to track antecedent moisture 

conditions over the prior several years (see fig. 9.4). 

Few researchers have devised and regularly employed 

drought indices that include multiyear prior conditions of 

the sort needed when gauging forest impacts. Koch and 

others (2013a, 2013b, 2014, 2015) have used a set of 

drought indices consisting of 1-, 3-, and 5-year histories 

for an annual chapter in the last four national reports 

issued by the U.S. Department of Agriculture, Forest 

Service, Forest Health Monitoring program.

Fundamentally, with a meteorology-based approach to 

characterizing drought, impacts are inferred rather than 

measured directly. Anderegg and others (2013) argued 

that we have yet to link any meteorology-based drought 

measure to forest damage or mortality at broader spatial 

scales. Drought indices are not designed to predict 

levels of drought damage or mortality in forests or 

any other vegetation type—just moisture deficit, in an 

abstract sense. This problem is universal, regardless of 

the selected drought index or the spatial and temporal 

coverage provided by stations for the area of interest. 

Impacts on vegetation due to drought conditions can 

only be inferred, since vegetation responses are not 

measured by stations.

Nevertheless, Mitchell and others (2014) highlighted 

a possible way to employ meteorology-based indices 

to identify geographic areas where drought-induced 

tree mortality is most likely. They looked at 41 different 

forest die-off events across Australia (in different 

forest types over a period of about 80 years) and 

found 3 things they had in common: (1) water deficits, 

(2) maximum temperatures outside of 98 percent of 

the observed range in drought intensity, and (3) the 

presence of at least 1 heat wave (3 consecutive days 

above the 90th percentile for maximum temperature). 

While these specific threshold values may not translate 

to new locations—Australian ecosystems are more 

water-limited than many U.S. forest ecosystems—

the concept laid out by Mitchell and others (2014) is 

worth further research. Toward this end, moisture 

and temperature extremes for the United States are 

reasonably well documented from weather station 

data or from spatially interpolated products such as the 

gridded maps produced by the PRISM Climate Group 

at Oregon State University (Daly and others 2002, Daly 

and others 2008).

Remote Sensing-Based Measures 

of Drought Impacts

Various remote sensing-based indices have been 

proposed and utilized to detect drought occurrence and 

severity (table 9.2). The continuous gridded nature of 

these remotely sensed indices is an innate advantage 

over the meteorological indices shown in table 9.1, 

which are derived from dispersed meteorological 

stations. This advantage is counterbalanced, however, 

by the relatively brief observational history that any 

particular class of satellite sensors provides. New orbital 

sensors have substantially different characteristics, 

yet may not share overlapping periods of operation 

to calibrate with the sensors that they are replacing. 

The decade-or-more service lifetimes of MODIS and 

Advanced Very High Resolution Radiometer (AVHRR) 

are considered long records for remote sensing 

platforms, yet they are short with regard to tree 

lifetimes and forest successional dynamics.

In contrast to meteorology-based measures of 

drought, remote sensing indices measure certain 

impacts of drought to vegetation and disturbance 

directly (Deshayes and others 2006). Sensors 

integrate vegetation conditions across the entire grid 

cell at the resolution of the sensor, averaging across 

vegetation types and plant species. Because of these 

basic distinctions from ground-based measurements, 

and because these indices represent an emergent 

vegetation property, the trajectory of such integrating 

measures across seasons has been referred to as Land 

Surface Phenology (LSP) (de Beurs and Henebry 2004), 

and interannual differences in the timing and magnitude 

of LSP have been suggested as potential indicators of 

environmental change.

Conceived initially by Rouse and others (1973) but 

popularized by Tucker (1979), the Normalized Difference 

Vegetation Index (NDVI) has proven to be useful both 

alone and as a component of other indices, and also as 

a fertile starting point, since many variants of this index 

have been devised. Chief among its advantages is the 

automatic normalization for differences in sun-andsensor geometry that is provided by the “differenceover-sum” format of its arithmetic construction, a 

form that has been frequently borrowed for other 

indices. NDVI is colloquially referred to as “greenness” 
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Table 9.2—Remote sensing indices for drought detection and monitoring

Index Formula Purpose Strengths Weaknesses Reference

Normalized 

Difference 

Vegetation 

Index (NDVI)

(NIR-Red)/

(NIR+Red)

National Inventory Report 

(NIR)

Monitor vegetation 

condition and health

Self-normalizing 

across different sunsensor geometries

Affected by soil color; may 

saturate at high vegetation 

densities

Tucker (1979)

Normalized 

Difference 

Vegetation 

Moisture Index 

(NDMI)

(NIR-MIR)/

(NIR+MIR)

Miscellaneous Inventory 

Report (MIR)

Uses MIR, which 

is sensitive to leaf 

moisture

Measures 

vegetation 

water relative to 

chlorophyll

Not all sensor platforms 

have MIR band

Wilson and 

Sader (2002)

Ratio to Mean 

NDVI

(RMNDVI)

((NDVIi-NDVImean)/

NDVImean) * 100%

Percentage change 

relative to mean of last 

n years

Depicts current 

status relative to a 

multi-year history

Mean greenness may not 

show sensitivity to drought 

impacts

Vegscape

Ratio to 

Previous NDVI

(RPNDVI)

((NDVIi-NDVIi-1)/

NDVI) * 100%

Percentage change 

relative to this time last 

year

Depicts current 

status relative to 

prior year

Prior year may not 

be representative of 

“normal”; seasonal timing 

may be shifted

Vegscape

Enhanced 

Vegetation 

Index (EVI)

((NIR-Red)/

(NIR+6Red-7.5Blue+1)) * 

2.5

Lower saturation risk Lessens soil 

background effect

Atmospheric effects; 

requires standardization

Huete and 

others (2002)

Soil-Adjusted 

Vegetation 

Index (SAVI)

((NIR-Red)/

(NIR+Red+L)) * (1+L)

Correction Factor (L)

Corrects NDVI when 

vegetative cover is low 

and soil color is visible

Adds a soil 

“brightness” 

correction factor, 

L; when L=0, 

SAVI=NDVI

Must know amount of 

vegetation to set L, and 

this is somewhat circular

Huete (1988)

Vegetation 

Condition Index 

(VCI)

((NDVIi-NDVImin)/

(NDVImax-NDVImin)) *

100%

Shows current value 

relative to dynamic 

range of previous years

Normalizes current 

value to past range

Shows other disturbances 

besides drought; Divisor 

grows with additional 

history

Kogan (1995)

MeanReferenced 

Vegetation 

Condition Index 

(MVCI)

((NDVIi-NDVImean)/

NDVImean) * 100%

Shows current value 

relative to mean of 

previous years

Normalizes current 

value to past mean

Change from mean of 

past years is relatively 

insensitive

Vegscape

MODIS Global 

Disturbance 

Index (MGDI)

(LSTmax, i/EVIpost LST max, i)/

(LSTmax, n-1/EVIpost max, n-1)

Land Surface Temperature 

(LST)

Detects large-scale 

vegetation disturbances; 

separate annual and 

historical formulations

Disturbances cause 

LST and EVI to 

exceed normal 

variability

Requires annual and 

historical maximum 

composite LST and EVI 

data; current year excluded 

from denominator

Mildrexler and 

others 2007), 

Mildrexler and 

others (2009)

Note: All are calculated on a cell-by-cell basis, often with respect to past values in that same cell. There are many variants of the Normalized Difference Vegetation Index 

(NDVI) not covered here, including the Normalized Built-up Index (NDBI), the Normalized Difference Water Index (NDWI) and Modified NDWI (MNDWI), the Normalized 

Difference Soil Index (NDSI), the Modified Soil Adjusted Vegetation Index (MSAVI and MSAVI2), the Transformed Soil Adjusted Vegetation Index (TSAVI), the Anomaly 

Vegetation Index (AVI), the Crop Moisture Index (CVI), and uncounted others. We treat the modeled multivariate VegDRI and GIDMaPS indices separately as Drought 

Detection System entries in table 9.3 (Zhang and others 2013).
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although Tucker (1979) never used this term himself. 

A majority of remote sensing indices attempt to track 

drought impacts on growth by tracking changes in this 

“greenness” using the logic that observed changes in 

photosynthetic machinery can be used to infer drought 

impacts indirectly (albeit more directly than the purely 

meteorological indices shown in table 9.1). Classical 

NDVI, however, saturates at high vegetation densities, 

giving rise to the “Enhanced” and “Soil-Adjusted” 

variants (table 9.2).

Most of the remote sensing indices rely on changes in 

“greenness” (sometimes in concert with leaf moisture 

or land surface temperature) relative to the same value 

calculated for the equivalent time interval in a previous 

year or years. This common construction represents an 

intention to compare a current value with an historical 

“normal.” This “normal” may be the local value at 

the same time the previous year [i.e., NDVI or Ratio 

to Previous NDVI (RPNDVI)]; it may be the ratio to 

mean (or RMNDVI), median, or maximum value from 

a number of prior years; or it may be scaled to the full 

dynamic range of the local value (i.e., VCI). Differences 

in the mechanism used to characterize this normal 

baseline are responsible for much of the proliferation 

of variant forms of these basic indices. Indeed, it 

may be more challenging to quantify the normal, 

expected trend than it is to monitor the current status. 

Development of the standard against which drought 

or greenness departures are measured may represent 

the most difficult part of drought detection, whether by 

meteorology-based or remotely sensed impact metrics.

The appropriateness and temporal equivalency of a 

“same date” comparison strategy across years relies 

on the stationarity of seasonal progressions in LSP. 

However, LSP is known to shift dynamically across 

years (Hargrove and others 2009). The degree of these 

seasonal phenology shifts will affect the detection 

sensitivity of drought indices based on such interannual 

comparisons, yet an earlier-than-normal fall season may 

be an indicator of drought (Hwang and others 2014). 

In the spring, where greenup is typically temperature 

limited, drought could result in either higher or lower 

values or both depending on what portion of the 

spring is considered. Such broad swings in detection 

sensitivity serve to demonstrate the confounded nature 

of drought impacts with other types of disturbances, 

including climatic effects (see Challenge 3 above).

Several indices evaluate the current situation relative 

to the mean of prior years. While the mean may 

characterize the entire prior distribution, the goal of a 

detection index is unlikely to be detection of a shift in 

the entire distribution itself. Comparisons with multiyear 

median may be only marginally more sensitive. It may 

be more effective to detect an onset of drought based 

on comparisons with maximum historical greenness, 

but this comparison will show increasing sensitivity 

as current greenness is compared with ever-higher 

values from particularly verdant prior years experiencing 

unusually favorable conditions.

A key need is to translate remotely observed changes in 

vegetation to actual impacts on the ground, such as tree 

mortality, annual growth reduction, or changes related 

to secondary disturbance risks, such as annual fuels 

for wildfire or insect and disease responses. Because 

short-term vegetation responses may not necessarily 

equate to long-term impacts, the multiyear monitoring 

capabilities that remote sensing provides are critical for 

detecting substantive lasting change apart from shortterm drought responses related to immediate reductions 

in seasonal greenness.

Limitations of Remote Sensing-Based 

Approaches: An Illustrative Example

Remote sensing-based methods for drought detection 

and monitoring are not a panacea. Interpretation of 

results shown by remotely sensed products may 

not be straightforward, and interpretations can be 

complicated by both the technical aspects of the 

sensor technologies, as well as by the intricacies and 

interconnections of the ecological processes.

A recent example highlights the magnitude of 

controversy that is possible surrounding interpretation 

of forest drought impacts from remote sensing 

observations. Impressed by global simulation results 

with the Hadley Center model in particular (Cox and 

others 2004), the Intergovernmental Panel on Climate 

Change (IPCC) AR4 report (IPCC 2007) issued warnings 

suggesting that the rain forests of the Amazon might 

collapse under climatic change, being replaced by 

savanna-like vegetation (Nepstad and others 2008). In 

addition to the radical transformation of the ecosystem 

and loss of biodiversity, Phillips and others (2009) 

claimed that massive Amazon tree mortality would 

temporarily change the forest from a carbon dioxide 

(CO2) sink (2 billion tons absorbed yearly) to a carbon 

monoxide (CO) source (3 billion tons released).

In part to test short-term predictions of decreases in 

forest photosynthesis following drought, Saleska and 
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others (2007) examined MODIS Enhanced Vegetation 

Index from 2000–2006, and reported that Amazon 

forests actually became greener during the severe 

drought that occurred in the region in 2005. Myneni 

and others (2007) found that Amazon forests become 

greener in the dry season due to an increase in leaf 

area index. Huete and others (2006) suggested that 

photosynthesis in Amazon forests might be limited 

by light availability, and that the observed increase 

of greenness during the dry season is stimulated by 

increased sunlight. Huete and others (2006) speculated 

that the normal dry season may be the forests’ most 

productive time of year because the rain clouds clear 

up and more sunlight reaches the forest, in the same 

way that some areas in the United States show positive 

correlations between drought and NDVI (see fig. 9.8). 

They also suggested that soil water content was not 

a limiting factor for Amazon greenness. Saleska and 

others (2007) concluded that Amazon forests might 

be more resilient to climate changes than ecosystem 

models assume.

These counterintuitive findings were immediately 

challenged by other studies, which concluded that 

the 2005 drought had no impact on the greenness 

of Amazon forests. Samanta and others (2011) found 

“no evidence of large-scale greening of intact Amazon 

forests during the 2005 drought.” They suggested that 

the previous findings were attributable to artefacts 

resulting from contamination of satellite-based 

observations by clouds and aerosols. Zhou and others 

(2014) showed widespread decline in greenness of 

Congolese forests over the last decade, even though 

such forests are probably more drought-tolerant, with 

their drier conditions and higher composition of semievergreen trees.

Recently, Morton and others (2014) showed that the 

apparent increase in greenness in Amazon forests 

could be explained by seasonal variations in lighting 

caused by changes in sun-sensor geometry. They 

suggested that it is soil moisture rather than light that 

determines the balance between photosynthesis and 

respiration in Amazon forests [summarized in Soudani 

and François (2014)]. These results tip the balance 

back toward interpretations that the Amazon is very 

sensitive to rainfall and, as the IPCC report indicated, 

may be prone to conversion and loss in a warmer, drier 

future in the tropics.

The emergence of such a surprising amount of 

controversy might discourage those considering a 

remote sensing perspective on drought detection and 

monitoring. However, tropical forests represent one of 

the most challenging of all locations for remote sensing 

work (Asner and Alencar 2010). A combination of 

complicating factors in tropical forest exacerbates the 

interpretation of remote imagery in these locations. 

High tree diversity in Amazonian forests leads to mixed 

responses from differential plant sensitivity, and there 

are potential saturation issues for some greennessbased indices. Clouds are nearly ever-present, and 

aerosols and terpenes may be in high concentration, 

as are particulates, soot, and smoke from fires. Most 

importantly, not many long-term ground observations 

and datasets exist, with few exceptions (Phillips 

and others 2009). This alignment of challenges may 

make tropical locations one of the worst-case remote 

sensing scenarios (Huete and Saleska 2010). More 

straightforward and direct interpretations of drought 

might be expected in temperate or boreal locations. An 

all-data approach, where remote sensing methods are 

leveraged with other ancillary data streams, including 

ground-based measurements, may represent the 

most promising approach for detecting and monitoring 

drought in these and other, less-challenging locations.

Existing Systems for Drought 

Detection and Monitoring

Table 9.3 shows 11 existing systems for detecting 

and monitoring drought, all of which include remote 

sensing as a fundamental component. The geographic 

extent that is monitored ranges from single countries to 

continents to the globe. Systems can be identified that 

are primarily the product of meteorologists, agricultural 

scientists, computational scientists, remote sensing 

specialists, and even political and social policy analysts. 

Not surprisingly, each system retains and exhibits the 

approaches, interests, and perspectives of the group 

producing and operating it. Some have a practical 

emphasis, while others are more research-oriented. 

Systems benefiting from the participation of more 

than a single one of these domain perspectives are 

likely to be the most useful in the long term. Although 

the oldest system has been operational for nearly 3 

decades, the majority have been initiated within the last 

5 years. There is a clear tendency among these newer 

systems to take a multivariate approach to drought 

detection rather than relying on one or a few indicators. 

Many of the drought systems are designed primarily for 

detecting food and agricultural drought effects, including 

verification for crop insurance settlements. Some of 

the tree-based systems are aimed at carbon accounting 
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Detection system Operated by Year started

Spatial 

extent

Release 

frequency Input data

Famine Early Warning 

Systems Network 

(FEWS Net)

U. S. Agency for International 

Development (USAID)

1985 Africa, Asia, 

Central 

America, and 

the Central 

Tropics

Every 

20 days; 

predictions 

6–12 months 

ahead

Subjective combination of agro-climatology, 

production, market data, nutrition, and 

scenario development

Vegetation Drought 

Response Index (VegDRI)

USGS (Earth Resources 

Observation Systems) (EROS), 

Univ. of Nebraska Lincoln, USDA 

Forest Service Resource and 

Monitoring Analysis (RMA)

7 States 

in 2006, 

CONUS in 

2009

Conterminous 

United States

Weekly AVHRR and eMODIS NDVI, combined with 

PDSI and SPI drought indices, land cover, soil 

water capacity, elevation, ecological setting, 

using three seasonal Regression Tree models

ForWarn Forest Service, National Aeronautic 

Space Administration (NASA) 

Stennis Space Center (SSC)

2010 Conterminous 

United States

Every 8 days Moderate Resolution Imaging 

Spectroradiometer (MODIS), Modis 

Vegetation Index Algorithm (MOD13), 

Vegetation Indices for Operational Drought 

Monitoring (eMODIS)

Forest Disturbance 

Mapper (FDM)

Forest Service Remote Sensing 

Application Center (RSAC)/

Forest Service Forest Health 

Technology Enterprise Team

(FHTET)

2010 Conterminous 

United States

Every 8 days Forest type map, USGS map zones, local 

MODIS downloads

United States Drought 

Monitor

Forest Service, NOAA, and Univ. 

Nebraska Lincoln

1999 Conterminous 

United States

Weekly Rain, snow, observer reports on wildlife and 

crop effects

North American 

Drought Monitor

USDA, NOAA, University of 

Nebraska-Lincoln (UNL), National 

Meteorological Service (SMN) 

Mexico, National Water Commission 

(CNA) Mexico, Agrifood Canada, 

Meteorological Service Canada

2002 Canada, 

Mexico, 

United States

Bi-weekly Subjective maps from the three member 

countries, which may not line up at 

international borders

Global Drought Monitoring 

Portal (GDMP)

NOAA NCDC 2012 startup, 

seeking global 

participation

Global Monthly Thresholded Global Precipitation Climatology 

Center SPI with up to 24-month history, other 

metrics where available

Vegscape Vegetation 

Condition Explorer/

CropScape

USDA National Agricultural 

Statistics Service (NASS)/

George Mason

2013/

2011

Conterminous 

United States

Daily, weekly, 

bi-weekly 

composites

MODIS NDVI, Enhanced Vegetation Index

(EVI)

Global Agricultural 

Monitoring (GLAM) 

Production System/Global 

Inventory Monitoring and 

Modeling Studies (GIMMS))

NASA Goddard, USDA Foreign 

Agricultural Service (FAS)

2001 Terra, 

2002 Aqua

Global Every 8 days MODIS Terra and Aqua, treated separately

Global Integrated Drought 

Monitoring and Prediction 

System (GIDMaPS)

Univ. California, Irvine 2013 Global, 1980–

2014, coarse 

resolution

Monthly Precipitation and soil moisture from 

simulations and remote sensing, including 

Modern Era-Retrospective Analysis for 

Research and Applications (MERRA), North 

American Land Data Assimilation System 

(NLDAS), Global Drought Climate Data 

Record (GLDAS), and Global Drought Climate 

Data Record (GDCDR) historical data sets

ALERTS 1.0/

Planetary Skin

NASA Ames, Univ. of Minnesota, 

National Space Research Institute 

(INPE) Brazil, Planetary Skin Institute

In 

development, 

beta available

Global, 1 km Biweekly MODIS NDVI, Land Surface Temperature 

(LST)
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Purpose

Meteorology 

or vegetation 

effects Algorithm Web site URL

Drought effects 

on food security

Vegetation, 

specifically 

food

Based originally on AVHRR in Northern 

Africa; has grown beyond a strictly remote 

sensing system

www.fews.net

Monitor 

vegetation stress 

to improve 

preparedness 

and response

Vegetation AVHRR and eMODIS VegDRI index from 

CART; Percent of Average Seasonal 

Greenness (PASG) ratio is relative to 20-

year mean Seasonal Greenness

vegdri.unl.edu, vegdri.cr.usgs.gov; 

Web viewer at 

 vegdri.cr.usgs.gov/viewer/viewer.

htm

Broad forest 

change 

detection, 

tracking, and 

recovery

Vegetation % NDVI difference between current NDVI 

versus given NDVI baseline

forwarn.forestthreats.org; 

Web viewer at 

 forwarn.forestthreats.org/fcav

Assist IDS flight 

planning and map 

disturbances

Vegetation Difference of current vs. historical spectral 

reflectances, followed by calculation of 

NDMI in Western United States, or NDVI 

in Eastern United States

foresthealth.fs.usda.gov/portal; 

Web viewer at 

 foresthealth.fs.usda.gov/portal/Flex/

FDM

Monitor broadscale drought 

impacts

Meteorology/

Vegetation 

(inferred)

Subjectively combine inputs into five 

Drought Intensity categories

droughtmonitor.unl.edu

Monitor broadscale drought 

impacts at 

continental scale

Meteorology/

Vegetation 

(inferred)

Experts balance conflicts from three 

countries into five subjective Drought 

Intensity categories

www.drought.gov/nadm; 

Web viewer at 

 gis.ncdc.noaa.gov/map/drought/NA

Provide a global 

snapshot of 

water scarcity

Meteorology A combination of existing continentalscale drought systems, with efforts to 

harmonize at country borders

gis.ncdc.noaa.gov/map/drought/Global

Monitor crop 

vegetation 

conditions

Vegetation Compares NDVI change ratio to previous 

year, to median and to mean NDVI

nassgeodata.gmu.edu/vegscape

Monitor global 

food production

Vegetation % NDVI anomaly, calculated from 

historical all-year mean NDVIs

glam1.gsfc.nasa.gov

Drought 

prediction and 

probability that 

drought will 

persist

Meteorology SPI, SSI, or Multivariate Standardized 

Drought Index (MSDI), mapped as five 

levels of wetness and five levels of 

drought

drought.eng.uci.edu

Improve 

detection, 

awareness, and 

decisionmaking

Vegetation Multi-resolution Global Water Stress Index 

Algorithm

www.planetaryskin.org, www.

planetaryskin.org/rd-programs/

resource-nexus/global-land-changedetection, viewer at ourplanetaryskin.

org/ps/is/cs/run.php?uid=guest

Table 9.3—Existing operational 

and experimental systems for 

detecting the extent and severity 

of drought Forest Service Forest 

Inventory Analysis (FIA), Insect 

and Disease Survey (IDS), 

National Oceanic and Atmospheric 

Administration (NOAA) Historical 

Climatology Network (HCN) 

meteorological stations, U.S. 

Geological Survey (USGS) Stream 

Gauge network, and SNOwpack 

TELemetry (SNOTEL) are related 

networks that, while providing 

invaluable ancillary information, 

are not specifically designed to 

detect or monitor extent, duration, 

or impact of drought
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or global deforestation, while others monitor drought 

effects on forests, particularly tree mortality.

Integrating Broad 

Monitoring With 

Assessment

Remote sensing platforms see everything; this is 

simultaneously both an advantage and a drawback 

of these methods. Observing all vegetation types, all 

disturbances, and all locations synoptically on a regular 

interval maximizes the likelihood of understanding the 

local situation. Nevertheless, remote sensing methods 

also see nondrought disturbance effects, both abiotic 

and biotic, and these can be difficult to distinguish and 

disentangle. Local information, history, and expertise 

can greatly inform the conclusions made from remote 

data, and may be a requisite for the successful use of 

remote sensing to detect drought impacts. Remote 

sensing platforms alone are insufficient for most 

drought assessment purposes. However, as discussed 

in the following sections, they can be extremely useful 

for drought assessment when combined with ancillary 

datasets.

Land Surface Phenology Datasets

Phenology, the timing of foliage greenup and 

browndown, can provide one of the earliest indications 

of drought effects. In particular, comparison of current 

greenness with historical phenological behavior can show 

departures from expected trajectories caused by drought 

(Hargrove and others 2009). However, such phenological 

differences might be caused by other, nondrought 

effects, or might be delayed significantly from when 

original drought events occurred. These operational 

difficulties mirror the conceptual difficulties in isolating 

indirect from direct drought stressors (fig. 9.5).

Drought detectability using remote sensing is variable 

over time and space. Drought response is not just 

a function of weather, but also of spatial variation in 

phenological cover types and fractional vegetation 

cover, which is often imperfectly known. Conifers 

remain green even while dormant, while deciduous 

woody plants and grasses can have an extended period 

of brown dormancy that can mimic drought conditions 

(Volaire and Norton 2006). Vegetation response to 

drought is muted outside the growing season, although 

winter drought can cause needle loss and reduction in 

net primary productivity in conifers that can theoretically 

be detected remotely (Berg and Chapin 1994). This 

disparate responsiveness of land surface phenology can 

be isolated, but drought effects become confounded 

when the composition of a grid cell is mixed. It can be 

challenging to know when the remote sensing signal is 

changing due to disturbance or successional recovery 

and when it is changing from drought.

High-frequency land surface phenology datasets provide 

a means to interpret drought responses, particularly for 

reliably drought-sensitive vegetation types. In opencanopy forests, savannas, or forest edges, increased 

grass, shrub, or herb cover can increase drought 

sensitivity. Deciduous trees may respond to drought 

by earlier leaf senescence (Hwang and others 2014). 

Although senescence can also be triggered by frost 

(Vitasse and others 2009), an unusually early onset of 

leaf browning and/or abscission may serve as a seasonspecific indicator of drought in some forests. Highfrequency land surface phenology datasets may provide 

a number of drought indicators that can distinguish 

drought responses among cover types.

In high-elevation or mountainous areas, winter variation 

in snowpack extent and duration provides an important, 

albeit temporally delayed source of precipitation that 

can be monitored. At high elevations, limited snowpack 

has been associated with the early onset of spring 

green-up (Hu and others 2010), although this may 

result from warmer temperatures. Winter drought can 

extend the subsequent wildfire season and can reduce 

fuel moisture (Littell and others 2009, Westerling 

and others 2006). Early green-up may also affect 

drought-associated insects and diseases (Ayres and 

Lombardero 2000). The delayed effects of snowpack 

variation are captured in the next growing season by 

existing phenological datasets that track NDVI and other 

vegetation indices (table 9.4).

Insect and Disease Surveys

The Insect and Disease Surveys (IDS) aerial survey 

program (table 9.4), administered by the Forest Service 

Forest Health Protection (FHP) program could serve as 

a national-scale source of geospatial data about biotic 

impacts triggered by drought. In some cases, IDS 

data also document direct impacts from drought and 

other abiotic disturbance agents. Under the program, 

surveyors use aerial sketch-mapping hardware and 

software to delineate geospatial features (typically 

polygons) that depict forest health impacts such as 

tree mortality or defoliation. The surveyors assign 

disturbance agent codes, as well as certain measures 

of the intensity of the impact (e.g., trees per acre 

defoliated), to each feature. The IDS data are compiled 
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Table 9.4—Ancillary datasets that may be useful for interpretation during drought detection and monitoring

Dataset

Developers/owners Contents Value added for drought detection Reference

National Land Cover Database (NLCD); NLCD 2011 Forest Service Tree Canopy product

USGS, along with the Multi-Resolution Land Characteristics (MRLC) Consortium

16-class Landsat-based 30-m resolution land cover database for the United States; updated every 5 years; Tree Canopy product provides estimated percent canopy cover plus standard error

Shows vegetation and land cover types to assist estimation of drought impacts across areas with variable sensitivity; enables land cover conditional filtering of drought impacts

www.mrlc.gov/

Snowpack/SNOTEL

NOAA Ground-based remote sensing of 

snow accumulations

Future drought impacts in areas dependent on snowmelt water

www.nohrsc.noaa.gov/nsa

MODIS hotspots showing recent wildfires

NASA, Remote Sensing Applications Center (RSAC) Active Fire Mapping Program

Thermal detection of wildfires at 1-km resolution

Fire may be the final outcome of drought; separates fire effects from extreme drought effects

activefiremap.fs.fed.us

Monitoring Trends in Burn Severity (MTBS) and GeoMac

Remote Sensing Applications Center (RSAC) and USGS

Mapped perimeters of past wildfires, with burn severity estimates

Fire may be the final outcome of drought; separates fire effects from extreme drought effects

www.mtbs.gov, www.geomac.gov

Active fire maps Incident Information 

System (INCIWEB)

Status of active wildfires and large prescribed burns

Fire progression maps show effects of near-real-time drought conditions

www.inciweb.org

Historical Insect and Disease Survey (IDS) maps 

Forest Health Technology Enterprise Team (FHTET) 

Aerial disturbance surveys from aircraft for a portion of U.S. forests

Shows the pattern and landscape position of pest mortality and defoliation events

www.fs.fed.us/foresthealth/technology

Stream depth and flow USGS Stream Gauge 

Network

Depth and amount of flow of rivers and streams

Monitor changes in runoff and surface flow downstream of drought areas

waterdata.usgs.gov

LANDFIRE Disturbance database

USDA Forest Service LANDFIRE

Vegetation and fuel disturbances 1999-2010

Separate other disturbances and harvests from drought mortality

www.landfire.gov/disturance.php

Forest Inventory and Analysis (FIA)

USDA Forest Service Inventoried forest plots in a 

statistical design, remeasured every 5/10 years

Shows long-term cumulative effects and mortality of drought

www.fia.fs.fed.us

Phenology data, phenoregion maps

USGS, USDA Forest Service

NDVI and other vegetation indices, statistically created maps of multivariate clusters of NDVI through time

Shows departure from normal timing of greenness, maps major vegetation types having similar phenology behavior, empirically determined

phenology.cr.usgs.gov, forwarn.forestthreats.org, White and others (2005)

Note: These data sets and systems, while not directly useful in drought detection, may provide useful surrogate information when used conjointly to support core data in a multivariate “big data” approach to drought detection and monitoring. Most of these data sources are restricted in extent to the United States.
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on an annual basis, and so they are not sources of nearreal-time information.

Meddens and others (2012) noted several additional 

obstacles to using the IDS data. First, the amount 

of forest surveyed varies from year to year, and not 

all forests are surveyed; flights are targeted at areas 

where disturbances are most likely to have occurred 

(in response to ground reports), so it is possible that 

some affected areas are missed. Second, IDS polygons 

are delineated broadly, and they typically also include 

healthy trees. Hence, the severity of a disturbance is not 

reported consistently. IDS observations are recorded 

by different observers having a wide range of skills and 

experience, which introduces further variability in the 

reported severity and extent of a disturbance.

A related obstacle is a lack of standardized causal 

attribution. Depending on the aerial surveyor, IDS 

polygons could be labeled as having been caused by 

drought, or instead, by insect activity driven by drought. 

Causal attribution is assigned from the air, with limited 

field validation. IDS data users must consider multiple 

agents when trying to ascertain the extent of an 

impact. For instance, when analyzing pinyon and juniper 

mortality in the Southwestern United States, Breshears 

and others (2005) combined IDS polygons attributed to 

various bark beetles as well as drought. To circumvent 

these ambiguities, IDS data are probably best used to 

delineate general geographic regions where multiple 

years of forest damage and/or mortality have been 

attributed to a complex of biotic and abiotic agents 

associated with drought (Huang and Anderegg 2012). 

These regions can then be adopted as the setting for 

further retrospective analysis into relationships between 

the agents, using ancillary data sources (Williams and 

others 2010, Williams and others 2013).

Wildfire Mapping Datasets

Wildfire often causes tree mortality and initiates 

successional recovery that destabilizes the historical 

pattern of climate sensitivity of communities within 

burned areas. Despite being an indirect outcome of 

drought (Westerling and others 2006), burned areas 

are likely to provide a less consistent measure of direct 

drought effects than are adjacent undisturbed areas. 

Increases in grass or shrub cover after fire may make 

burned landscapes more climate-sensitive than when 

they were dominated by dense conifers. Existing 

wildfire datasets (see table 9.4) can be used to isolate 

burned portions of the landscape that may differ in their 

drought response for a more accurate understanding 

of the system in post-fire years. As with insect and 

disease data, burned areas can be selectively masked 

for regional interpretations of drought responses, or 

they could be targeted for understanding the cumulative 

effects of drought and disturbance.

The 2011–12 Texas drought and drought-associated 

fires illustrate how remote-sensing-based change 

monitoring can be better interpreted with ancillary 

wildland fire data. This Texas drought was remarkable 

(Nielson-Gammon 2012) because of its severity and 

duration, and because of the extensive area burned 

during the 2011 wildfire season (fig. 9.9). Where and 

when they co-occur, drought and wildfire may have 

additive or redundant effects on reducing NDVI. For two 

nearby MODIS pixels in figure 9.10, the effects of fire 

and drought are at least partially additive. The NDVI of 

these two pixels tracks each other closely for years prior 

to 2011, suggesting they had quite similar vegetation, 

and the 2011 drought effects were likely identical given 

their proximity. However, the immediate reduction from 

burning and drought clearly exceeded that of drought 

alone, and this effect persisted through 2012.

Retrospective analyses of drought effects across 

different vegetation types provide coarse-filter insights 

into differential responses. For a random sample of 

MODIS pixels across west Texas, annual variation in 

NDVI clearly varies by majority vegetation type, as 

filtered by the National Land Cover Database (fig. 9.11).

Shrub- and grass-dominated areas have greater yearto-year amplitude in NDVI, which is consistent with 

expectations of their greater climate sensitivity than 

forests. All vegetation types show a general decline that 

could be an indication of widespread mortality caused 

by the 2011 Texas drought.

Land Use/Land Cover Datasets

Changes in land use and land cover are typically so 

fine-scale that they are unlikely to influence more 

coarse-scale estimates of climate departure. But taken 

over decades, extensive areas of certain regions have 

experienced substantive urban and infrastructural 

development (Riitters and others 2002, Riitters and 

Wickham 2003). Conversion from forest to nonforest 

land cover often increases dominance by grass, shrubs, 

and ruderal or early-successional species that are 

generally more responsive to drought than are many 

forests. In areas that have experienced these changes, 

baselines from long-term, remotely sensed time series 

may be less desirable than efforts to model effects 

based on recent land cover over shorter periods. For the 
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Kent Co. Stonewall Co. 

Dickens Co. King Co. 

Scurry Co. Fisher Co. Jones Co. 

Haskell Co. 

% Change in NDVI Knox Co. 

-61 to -99

-30

-20

-15

-12.5

-10

-5

-3

-1.5

0

+25

+100

Figure 9.9—ForWarn change in Normalized Difference Vegetation Index (NDVI) from the All Year Mean Baseline for the 3-week 

period ending August 28, 2011, showing the severity of drought and wildfire on nonagricultural lands across northcentral Texas. 

Wildfire boundaries for 2011 are shown by dashed white lines.
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0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Unburned

Burned

Year

 NDVI 

Figure 9.10—A comparison of two nearby woodland ForWarn pixels in west Texas on similar sites, one that burned 

and one that did not during 2011. Note that effects persisted through 2012 on both sites, but that the cumulative 

effects of drought and wildfire were more pronounced than drought alone. Site locations: unburned site location 

31.8295, -100.6636; burned site location: 31.8390, -100.6455.

Mean NDVI 

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Forest (N = 289)

Shrub (N = 5,775)

Grass (N = 1,590)

Year

Figure 9.11—Mean NDVI for a random sample of unburned majority forest, shrub, or grass pixels within Texas 

climate divisions 1, 2, 5, and 6 (west Texas) using the ForWarn dataset. Note the extreme decline in NDVI during 

the 2011 drought that affected all vegetation types.
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United States, the National Land Cover Database 

(NLCD) (see table 9.4) provides complete national 

coverage for multiple time steps (1992, 2001, 2006, 

and 2011), allowing analysts to distinguish patterns of 

land cover change that may be pertinent for interpreting 

drought response.

More subtle changes in forest management, crop type, 

or livestock grazing intensity can be difficult to monitor 

and assess. Crop types and livestock grazing intensity 

can fluctuate with changes in market prices in ways that 

confound drought response. Similarly, broad-scale forest 

restoration that involves stand thinning via mechanical 

means or prescribed fire has the potential to reduce a 

forest’s sensitivity to drought as grass and shrubs are 

removed; yet restoration efforts are rarely extensive 

enough to be widely detected except when they involve 

wildfire use. Far less logging has occurred over the last 

decade on most Forest Service lands, suggesting that 

there was far more drought-sensitive early successional 

habitat during the 1980s than exists in the 2000s. As 

large wildfires become increasingly common in the 

West, extensive areas of forest could become far more 

drought-sensitive than they were earlier. Certain derived 

land use/land cover datasets, such as the percent tree 

canopy cover layer developed by the Forest Service 

for the 2011 NLCD, may offer limited insight into these 

landscape dynamics.

“Big Data” Integration: 

A Contextual Learning 

Approach to Drought

To understand broad-scale drought impacts, both 

meteorology-based measures of drought and remote 

sensing observations need interpretation, and, as we 

have seen, interpretations are not straightforward. Many 

ancillary spatial datasets may be useful for selecting, 

masking out, or simply interpreting different effects that 

are observed (table 9.4). As noted above, identifying 

areas that have been affected or not affected by 

disturbance provides an effective way to isolate direct 

and indirect drought effects. Comparisons of different 

vegetation types, whether as specific dominant forest 

species types, or generally as evergreen, conifer, or 

mixed forest types, are useful for understanding how 

drought responsiveness and effects differ on the ground.

At a national scale, conditional filtering of sites based 

on their drought sensitivity and disturbance history 

can provide insights into the regional relationships 

between drought and NDVI (fig. 9.12). While the 

MODIS NDVI period is limited to 2000–present, 

most filtered or masked vegetation types show a 

strong response of reduced NDVI with increasing 

drought, with some exceptions. The NDVI response 

of northeastern hardwood forests runs counter to 

expectations, perhaps because this area has not 

experienced the drought and temperature extremes 

as have hardwood forests of the Southeast (figs. 9.2 

and 9.8). With their evergreen attributes, conifers 

only show some sensitivity to drought stress (fig. 

9.12). In contrast, grass and shrublands show as 

highly sensitive to drought, particularly in areas that 

have experienced extreme drought during the MODIS 

period. The sensitivities described here, of course, 

are with respect to the speed and magnitude of NDVI 

responses. Such responses are useful to the degree 

that they reflect actual vegetation impact from realized 

drought stresses.

Using a random sample of 250,000 MODISForWarn grid cells out of the 14.6 million cells in 

the conterminous United States, we found that 

20.4 percent of the continental U.S. forest area 

was mapped as disturbed by wildfire, insects, or 

diseases between 2000 and 2012 (estimated using 

IDS, Monitoring Trends in Burn Severity (MTBS), and 

GeoMac data; see table 9.4). The drought response 

of these areas may be misleading for certain analyses, 

particularly when disturbance or drought occurs 

nonuniformly during the analysis period. For example, 

a gradual increase in NDVI associated with postdisturbance succession and recovery may overwhelm 

any reduction in NDVI caused by drought (see fig. 

9.10). By masking out disturbed forests, however, the 

response of the remaining areas is more likely to relate 

to direct drought effects (fig. 9.12A).

The majority of the remote sensing indices in table 

9.2 scale or proportionalize the absolute changes in 

greenness into relative terms. Usually the scaling 

divisor is some metric of total greenness (or range of 

greenness) in this location. Such formulations suggest 

a conceptual model (implicit or otherwise) that trees, 

which are “greener” than grasses, for example, 

are somehow better able to withstand a particular 

absolute decrease in greenness than their less-green 

grass counterparts. Thus, the estimated impact of a 

drought that causes a uniform absolute decrease in 

greenness will be reported by such indices as relatively 

more severe for grasses, since it represents a greater 

proportion of their total greenness, and relatively less 

severe for trees.
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(A) All forests (D) Majority shrub

(B) Majority conifer forest (E) Majority grassland

(C) Majority hardwood forest (F) Majority crops

Pearson’s r values

-1.00 to -0.67

-0.66 to -0.34

-0.33 to 0.00

0.01 to 0.33

0.34 to 0.66

0.67 to 1.00

Figure 9.12—Correlations (Pearson’s r) between mean March–September Moderate Resolution Imaging Spectroradiometer 

(MODIS)-based ForWarn Normalized Difference Vegetation Index (NDVI) and National Land Cover Data Climate Division mean 

monthly March–September Palmer Modified Drought Index (PMDI) for majority land cover types derived from the NLCD showing 

areas of known disturbance by wildland fire or biotic insect or disease in black for (A) all forests, (B) majority conifer, (C) majority 

hardwood, (D) majority shrub, (E) majority grassland, and (F) majority crops, 2000–2012. Wildland fire was derived from http://

www.MTBS.gov (2000–2012) and http://www.GeoMac.gov (2013) (accessed September 1, 2014); insect and disease disturbance 

was compiled from Forest Service Forest Health Protection (FHP) Insect and Disease Survey (IDS) data. Data shown are based on 

250,000 random points, sampled with a 1-km buffer.
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Yet such relative sensitivities are diametrically opposite 

to the differential drought response patterns across 

vegetation types demonstrated here (Lobo and 

Maisongrande 2006, Sims and others 2014; see also 

Challenge 3). Figure 9.12 shows a version of fig. 9.8C 

that has been filtered by vegetation type. Small stature, 

low biomass vegetation types like grasses and shrubs 

are the quickest to show decreases in greenness 

under drought conditions, but grass and herbaceous 

perennials can recover quickly following an end to 

drought. In contrast, when drought leads to tree or 

shrub mortality, full recovery may take decades. Thus, 

grasses are a sensitive indicator vegetation type that 

may be useful as a harbinger of regional drought stress 

(Sims and others 2014). The NDVI of conifer-dominated 

forests are relatively unresponsive to drought. For 

example, at higher elevations, the coastal Northwest, 

and in New England, NDVI may actually increase as 

PMDI decreases (fig. 9.12). Weighting the severity of 

effects by scaling with absolute greenness would seem 

to be counter-indicated, and also acts to reduce the 

sensitivity of indices to drought effects on trees.

As noted earlier, remote sensing provides a coarse-filter 

type approach. Observations are frequent, extensive, 

and continuous in space, but are not detailed (fig. 9.7), 

and average across many vegetation types. Sensors are 

not species-specific and integrate across all vegetation 

growing in an area to produce a single value. Such 

integration may actually be advantageous, averaging 

out noise and measuring land surface phenology as a 

repeatable, emergent property of the entire vegetated 

ecosystem. An ideal drought detection approach 

would leverage both the extent and the temporal 

completeness of remote sensing approaches, while at 

the same time utilizing the longer historical record of 

meteorological records, which offer longer histories than 

remote sensing platforms. Ironically, the length of the 

MODIS or AVHRR record is considered long by remote 

sensing standards, yet it is very short relative to the 

depth of the climatic records, much less tree lifespans 

within forests. For even longer comparisons, one must 

employ other, even more-removed proxies, like tree-ring 

data (Herweijer and others 2007).

Combining Remote Sensing 

With Context-Based Learning

The broad spatial coverage and frequent, multiyear 

temporal sampling are powerful strengths of remote 

sensing approaches to the analysis of drought effects. 

It is not possible to do experiments on drought at the 

landscape scale. The extent is too large to randomize, 

to replicate, or to apply droughts as experimental 

treatments [but see the Walker Branch Throughfall 

Displacement Experiment near Oak Ridge, TN, 

described by Hanson and others (2003)]. An inability 

to apply the classical scientific method does not, 

however, prevent a remote sensing approach to drought 

effects from making progress (Hargrove and Pickering 

1992). Scientific progress on drought effects at large 

scales is simply limited to inference, based on what 

we can see happening. In this, remote sensing of 

drought is similar to a scientific field like astronomy, in 

which rich observation without the possibility of direct 

manipulation is the only avenue for advancement.

We suggest that a filtering approach that carefully 

considers both vegetative and climatic conditions 

can leverage the strengths of extensive drought data 

collected with remote sensing to best advantage. 

The identification of past situations whose drought 

outcomes might be informative or discriminating forms 

the keystone of this approach. A cycle starting with the 

postulation of an hypothesis, followed by identification 

and selection of relevant past “natural” experiments, 

followed by observation of the outcomes that resulted 

could be expected to produce inferences about the 

general principles at work, which would, in turn, result 

in refinement or rejection of hypotheses, beginning the 

cycle anew.

Such context-based learning, involving the isolation 

and examination of relevant prior circumstances, 

would leverage the availability of “big data” volumes 

of historical observations. Essentially, it is a form of 

empirical data mining. This type of time sequence 

approach is sometimes called space-for-time 

substitution, an approach that has been employed 

elsewhere in large-scale ecology (Pickett 1989). Figure 

9.12 demonstrates the utility of such a filtering approach 

by showing the differential responses of various 

vegetation types to drought.

Empowered by ancillary datasets, powerful post hoc 

opportunistic analyses of drought may be possible 

when advantage can be taken of past droughts that are 

embedded within these specific relevant contexts of 

particular past times and locations. Such observationbased approaches carry with them the dangers of 

pseudoreplication, or at least an inability to replicate at 

will (Hurlbert 1984). Nevertheless, a strategy of coarse 

filtering by vegetation type, antecedent conditions, 

and drought severity could obtain targeted insights 

based on the weight of evidence from past outcomes. 
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Searching an extensive database of observations for 

the occurrence and review of particularly relevant 

chronosequences in time and space might be an 

effective way to make observation-based progress in 

our understanding of drought effects.

We advocate a data-mining, “big data” approach for 

detection and monitoring of drought impacts, relying 

primarily on remote sensing platforms, but also 

leveraging the longer term meteorological data and 

ancillary datasets for context-based interpretation. 

Figure 9.13 shows a conceptual model of how a “big 

data” approach might be used in developing a system 

for monitoring drought impacts in forests. This type 

of circumstantial data harvesting is the method most 

likely to increase our understanding of the impacts of 

drought stress on forests. Such a cycle might even 

advance our scientific understanding of landscape-scale 

drought effects with greater efficiency than classical 

experimental approaches (Tilman 1989). The strategy is 

empirical, allowing patterns to emerge passively from 

the data, without preconceived notions or hypotheses. 

Despite their neutrality and passive observational 

nature, space-for-time filtering approaches can be 

highly constructive, as they will generate large numbers 

of testable hypotheses for the next round of conditional 

analysis.

Unambiguous establishment of causation (even in 

a limited pragmatic sense of learning to recognize 

correlated antecedent conditions) is difficult using 

these observational methods. Drought impacts 

are confounded and are difficult or impossible to 

disentangle without the use of relevant ancillary data 

(see fig. 9.13). With drought, however, this difficulty 

in separating proximate from ultimate drivers may not 

matter. Managers may be satisfied to monitor combined 

cumulative primary and secondary drought effects, 

unless they feel that they possess management options 

that would be effective against one or more of the 

separated drivers. Managers will want to recognize 

individual drivers only if they believe that they know 

how to relieve or mitigate some of the potential drivers. 

Otherwise, in practical terms, it is the sum total of the 

cumulative effects that acts to reduce the productivity 

of their forests.

Meteorologically 

based departure 

Remotely sensed 

stream data 

Areas of potential

drought impacts 

Detailed analyses 

confirm actual impacts 

Defining 

expectations

from phenology 

Magnitude

Duration

Frequency

Extent 

Remote-sensingbased departure 

Distinguishing wildland 

fire influence 

Distinguishing 

management influence 

Distinguishing insect/ 

disease influence 

Meteorological 

data stream 

Drought

impacts

Drought

measures

Integration

Figure 9.13—Conceptual model of how a “big data” integration approach might be 

employed in a system for monitoring drought impacts in forests. Fundamentally, areas 

of potential impacts occur where and when signals from both the remotely sensed 

and meteorological data streams coincide. Because the remotely sensed data stream 

documents all kinds of departures from normal vegetation conditions, the integration 

phase must include ancillary data that can distinguish departures unrelated or only 

indirectly related to drought. Detailed confirmatory analyses might include, for example, 

using Forest Inventory and Analysis (FIA) data retrospectively to look for tree growth 

declines or increases in tree mortality in areas where drought impacts were predicted. 
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Many of the newest generation of remote-sensingbased drought monitoring systems (table 9.3) are 

adopting such multivariate approaches. These 

multivariate approaches mirror appropriately the 

multivariate nature of drought effects and impacts 

themselves (as shown in fig. 9.5B). However, we must 

avoid subjective or quantitative “black box” solutions 

that infer impacts. We must move beyond such blind 

methods if we are to increase our basic understanding 

of complex drought impacts and the processes 

controlling them. A filtering approach that isolates 

particular conditions of vegetation and weather before, 

during, and after drought can, by looking across space, 

provide needed “experiments” that can yield insights 

into drought responses under more stringent conditions, 

isolating particular effects. Combined with groundbased sampling and monitoring data, such a hybrid 

approach can inform and enlighten our understanding of 

drought effects on forests.

Embedding Local Monitoring

Large-scale drought monitoring may not be capable 

of addressing local drought effects with the desired 

precision, even when the portions of broad landscapes 

that are likely to be hardest hit can be efficiently 

identified by large-scale monitoring efforts. Intensive 

local assessments can fill in the gaps that are not 

captured by coarse-scale monitoring (fig. 9.13). These 

efforts may consist of detailed mapping using highresolution imagery that may or may not be calibrated 

with plot data or systematic plot inventories to capture 

changes of concern, such as reduced growth or tree 

mortality.

The Forest Inventory and Analysis (FIA) program 

administers an annualized system of field plot 

inventories. Under this system, first implemented in the 

late 1990s, plots are remeasured systematically on a 

cycle ranging from 5 (Eastern United States) to 10 years 

(Western United States). Thus, in the Western United 

States, one-tenth of the established FIA plot locations 

in any given State are sampled each year. These annual 

samples attempt to be free of geographic bias (Shaw 

and others 2005), appear to be sufficient for annual 

time series analysis of forest growth and mortality, and 

are able to detect relatively low levels of forest change 

(Shaw and others 2005). However, because of the 

temporal remeasurement interval, it may be impractical 

to link a short-term (e.g., single-year) drought event to 

mortality or any other impact observed on a plot, since 

the timing of that impact (i.e., exactly when during the 

several years since the plot was last visited) cannot 

be determined (Liknes and others 2012). Long-term 

trends (i.e., more than a decade) typically must be 

studied using a combination of annualized and older 

periodic inventory data between which there may have 

been methodological differences. In addition, there is 

roughly 1 FIA plot per 6,000 forested acres, and there 

are about 130,000 forested plots nationwide. FIA data 

are probably best suited to analysis of status and trends 

at broader spatial scales (Shaw and others 2005). Plot 

density may be insufficient to detect impacts that are 

patchy in nature, even if they are manifested over a 

relatively large geographic region (Liknes and others 

2012). Unfortunately, drought-induced tree mortality is 

often patchy (Allen and others 2010).

Despite such limitations, Gustafson and Sturtevant 

(2013) concluded that a drought-induced tree mortality 

signal in the upper Great Lakes region could be 

uncovered using FIA data. Gustafson (2014) similarly 

used FIA data to construct predictive models of droughtinduced tree mortality (based in part on correlation with 

the NDSI and SPI) in the Northeastern United States. 

He found that the reliability of these models varied 

substantially; models for drought-intolerant tree species 

performed most poorly. Gustafson hypothesized that 

this may have occurred because long drought periods 

did not occur in the Northeast during the period when 

FIA inventories were available.

A major challenge when using FIA data is the inability 

to ascertain the actual cause of mortality or any other 

forest health change (Gustafson and Sturtevant 2013). 

If plots are disturbed, FIA field crews do have the 

option to assign damage agent codes, and drought is 

one possible code. However, these codes are reported 

inconsistently, and, as with the IDS data, field crews 

may label a disturbed plot according to the primary 

agent (drought) or the secondary disturbance agent 

(insect or disease activity). They can also assign 

multiple agent codes, which might provide some 

data filtering opportunities. The coarse temporal FIA 

remeasurements probably lead most field crews to 

assign secondary damage agents, concealing that these 

impacts may have been triggered initially by drought.

Ultimately, the best use of FIA data may be for 

retrospective analyses linking tree mortality and 

reduced growth to possible explanatory drivers, 

including drought. For this approach, FIA data might be 

used in concert with a variety of other data sources, 

including tree-ring data, remote sensing, meteorological 

drought index maps, and others. A number of studies 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

have employed this multivariate approach (Dietze 

and Moorcroft 2011, Klos and others 2009, Shaw and 

others 2005, Williams and others 2013). Additionally, 

through specially commissioned FIA remeasurement 

surveys, it may be possible to quantify areas 

experiencing major forest impacts in terms of trees lost 

and extent of the affected area, as was done by the 

Texas A&M Forest Service after the exceptional Texas 

drought in 2011. Final estimates of tree losses and 

subsequent economic impacts were released within a 

year (Nielson-Gammon 2012).

Summary

There is much recent interest in understanding how 

drought effects forests in part because drought and 

drought-associated forest disturbances are expected 

to increase with climatic change (Adams and others 

2009, Allen and others 2010, Anderegg and others 

2012, Breshears and others 2005, Breshears and 

others 2009, Carnicer and others 2011, Martínez-Vilalta 

and others 2012, Westerling and others 2006). Yet 

our ability to systematically and accurately recognize 

drought effects to forests over broad scales is limited. 

The most compelling research efforts mostly focus on 

catastrophic droughts rather than episodic droughts of 

moderate severity. The collective outcomes of more 

routine occurrences of moderate drought may be just 

as important and as impactful as rare, exceptional 

drought events. In any case, better tools, systems, 

and indices for dealing operationally with more 

commonplace drought events of moderate intensity 

are needed by forest managers and other resource 

professionals.

Drought is a value-laden term as concerns about 

particular impacts are implicit in the measures designed 

and baselines employed. No standard or universal 

definition is possible or even desirable, given the range 

of possible effects. Disentangling the various impacts 

of drought with different measures and ancillary data 

is part of the extraordinary challenge of dealing with 

drought effectively. With broad-scale monitoring, it is 

not possible to cleanly distinguish the effects of drought 

from the recipients of those effects, as moisture stress 

is not expressed uniformly across vegetation types 

(fig. 9.12). The relative composition of vegetation types 

must be considered in order to gauge the impact of 

any drought event accurately. In addition to utilizing 

nonforest species as indicator types that can be used to 

show what drying or wetting effects trees may be 

experiencing, it may become possible to utilize the 

extreme sensitivity of grasses to drought as a means 

to “standardize” drought intensity universally across 

all vegetation types, including trees. Understanding 

drought impacts on trees may require a longer history 

and a longer period of calculating baselines. Similarly, 

drought metrics for trees may require a longer, multiyear 

“memory” of antecedent conditions in order to be 

useful. New indices specific to trees are needed, 

because while metrics repurposed from agricultural 

crop use may work well for forests, these drought 

indices could be adapted in ways that increase their 

relevance for forests, in particular. Adaptations might 

include reformulating drought measures to capture 

long-duration multiyear drought, targeting drought 

measures to the sensitive seasons of the year based 

on phenological insights, or embracing baselines that 

relate better to the nonequilibrium nature of forested 

ecosystems.

Taking a broad view, drought effects to forests include 

direct and secondary effects that must all be addressed 

to understand each individually and the effects of 

climate extremes more fully. While wildfire, insects, and 

diseases can only partially be attributable to drought 

(fig. 9.5B), a change in drought-sensitive disturbance 

regimes may be the primary means by which drought 

alters forests in coming decades. While some droughtsensitive disturbances can be monitored using the 

same types of systems used for monitoring changes 

in productivity or mortality, attribution back to drought 

as the prime mover often requires integration of 

independent wildfire and insect and disease inventories 

and datasets.

Because of their inherently multivariate nature, efforts 

to characterize drought effects on forest landscapes 

will necessarily involve the integration of information, 

as knowledge of species, communities, disturbances, 

and mitigating factors are obtained from a multitude 

of different programmatic efforts. Interpretation is not 

inherent in monitoring when indicators are sensitive 

but coarse, and “big data” help translate observations 

to effects of specific concern (fig. 9.13). To make 

large-scale drought monitoring and assessment more 

accessible, we need an integrating framework for 

organizing knowledge that efficiently narrows down 

what is and is not likely to be a drought effect. This 

knowledge can help prioritize applied efforts for 

drought mitigation, adaptation, or response more 

generally.
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

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CHAPTER 10

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Science (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources, Raleigh, 

NC 27695.

C.F. Miniat is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Watershed Science, Coweeta Hydrologic 

Laboratory, Otto, NC 28763.

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID 83702.

H. Asbjornsen is an Associate Professor, University of New Hampshire, Department 

of Natural Resources, Durham, NH 03824; P.V. Caldwell is a Research Hydrologist, 

U.S. Department of Agriculture, Forest Service, Southern Research Station, Center for 

Watershed Science, Coweeta Hydrologic Laboratory, Otto, NC 28763; J.L. Campbell is 

a Research Ecologist, U.S. Department of Agriculture, Forest Service, Northern Research 

Station (NRS), Center for Research on Ecosystem Change, Durham, NH 03824; 

G.E. Grant is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station (PNW), Ecological Process and Function Program, 

Forestry Science Laboratory, Corvallis, OR 97331; D.J. Isaak is a Research Fish 

Biologist, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station (RMRS), Boise, ID, 83702; S.P. Loheide is an Associate Professor, University 

of Wisconsin, Civil and Environmental Engineering, Madison, WI 53706; G. Sun is a 

Research Hydrologist, U.S. Department of Agriculture, Forest Service, Southern Research 

Station (SRS), Eastern Forest Environmental Threat Assessment Center (EFETAC), 

Raleigh, NC 27695.

Ecohydrological 

Implications of Drought

James M. Vose

Chelcy Ford Miniat

Charles H. Luce

contributors

Heidi Asbjornsen, Peter V. Caldwell, 

John L. Campbell, Gordon E. Grant, 

Daniel J. Isaak, Steven P. Loheide, and Ge Sun
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Introduction

Ecohydrology focuses on the interactions and 

interrelationships between hydrological processes and 

the structure and function of vegetation (Breshears 

2005, Rodriguez-Iturbe 2000). It builds on a long history 

of watershed science that quantified how changes 

in vegetation (e.g., through purposeful manipulation, 

succession, or natural disturbances) alters water and 

streamflow dynamics at catchment scales (Bosch and 

Hewlett 1982, Vose and others 2014). Recent papers 

have broadened the scope to include understanding 

soil moisture dynamics (D’Odorinco and others 

2010, Emanuel and others 2010), human-dominated 

landscapes (Jackson and others 2009), and the 

sensitivity of ecosystem transitions after disturbance 

(Viglizzo and others 2014). In this chapter, we focus 

on how drought affects the interrelationships among 

forest structure and function, hydrologic processes, and 

streamflow dynamics.

Forests naturally grow where water is sufficient 

to support perennial woody vegetation, as forest 

evapotranspiration (ET) is typically much greater 

than other vegetation types (Frank and Inouye 1994, 

Sun and others 2011). Where precipitation (P) inputs 

substantially exceed ET losses, surface water draining 

forest land is typically of high quality and supports many 

human uses, including drinking water, agriculture, and 

industrial activities (Binkley and Brown 1993, Vose and 

others 2011). Forests also maintain relatively clean and 

cold water and are important for supporting aquatic 

ecosystems, particularly coldwater fishes (Peterson and 

others 2013, Rieman and others 2003). In addition to 

being important for providing high-quality surface water 

supply, forests modulate the quantity and timing of 

streamflows by intercepting and transpiring precipitation 

(Sun and others 2011) and influence snowmelt timing 

(Cristea and others 2013). Forests are also commonly 

important areas for groundwater recharge (Price 2011) 

and flood mitigation (Beschta and others 2000, Jones 

and Perkins 2010).

In simple terms, drought means less water—less 

water for plants and less water for streams. In 

some regions, seasonal droughts are common, 

and forest and stream ecosystems often adapt to 

these somewhat predictable disturbances through 

various physiological, morphological, and behavioral 

adaptations (Lytle and Poff 2004, McDowell and 

others 2008). In contrast, multiyear or severe 

droughts are less predictable, and hydrological 

and biogeochemical responses can be substantial 

(Lake 2003). This is especially true when very low 

precipitation is combined with warmer temperatures 

(Diffenbaugh and others 2015). The relationships 

among drought, surface water flow, soil water 

availability, and groundwater recharge are not 

straightforward for most forest ecosystems due to 

several factors, including the role of vegetation in the 

forest water balance. Hydrologic responses to drought 

can be either mitigated or exacerbated by forest 

vegetation depending upon vegetation water use and 

how drought affects forest population dynamics.

We can conceptualize a simple framework for assessing 

the drought sensitivity of a forest catchment by 

describing it as a series of four hydrologic pools: (1) 

vegetation, (2) soil, (3) groundwater, and (4) streams 

(fig. 10.1). Examining the sensitivity of streamflow to 

drought can be framed by looking at the duration that 

water is held in each pool and how much evaporative 

or transpiration losses occur from those pools. The 

first pool to intercept P is the vegetation surface (i.e., 

leaves, stems, boles). Some of the intercepted P 

(10–40 percent) evaporates back into the atmosphere. 

The wide range in intercepted P lost to evaporation 

is primarily related to vegetation surface area and 

rainfall characteristics, with a greater percentage of P 

intercepted with larger surface area and during light rain 

events (Eagleson 2002, Waring and Schlesinger 1985). 

Precipitation that is not intercepted (i.e., throughfall 

and stemflow) enters the forest floor where some 

(or all) may evaporate from the litter layer, or it may 

Figure 10.1—Conceptualization of major water pools and fluxes 

in a forested catchment. The catchment water balance can be 

viewed as partitioning of precipitation into evapotranspirative 

and drainage fluxes.
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move across the leaf/soil surface as overland flow. The 

remainder enters the soil water storage pool. Stored 

soil water can be evaporated or transpired by plants 

before becoming streamflow or recharging groundwater. 

While some water is temporarily stored in the roots 

and boles, most of the soil water taken up by tree roots 

moves through the internal vegetation pool quickly and 

returns to the atmosphere. For some forests, roots 

capture much of the water that does not freely drain 

to groundwater within a brief period after precipitation 

(Brooks and others 2009). If roots can access 

groundwater, they can deplete groundwater pools. 

However, when groundwater pools contain sufficient 

water, they can provide long-term base flows (Tague and 

Grant 2009), buffering streamflow against long periods 

without P.

The connections among the pools can be expressed 

using a simple water balance equation:

Q = P – ET – ∆S

where Q represents streamflow and is the balance of 

precipitation inputs (P) after losses to evapotranspiration 

(ET), which is the sum of interception, transpiration, and 

soil evaporation, and changes in storage (∆S). Over the 

short term, all four variables can change dramatically; 

however, over the long term (e.g., annually), change in 

∆S is typically minor and is therefore often assumed 

to be zero. Thus, Q can be estimated as P minus ET. 

The assumption that changes in storage are zero under 

severe drought conditions may not be correct in some 

instances and may yield incorrect interpretations of 

the impacts of drought on Q using P – ET approaches 

(Creutzfeldt and others 2012, Vose and Swank 1994). 

Regardless, Q can change in response to drought directly 

through reductions in P and indirectly via ET responses 

to changing evaporative energy and water availability; 

however, these responses are especially complex.

For a particular watershed, drought effects on Q can 

vary greatly in space and time depending on the timing 

of reduced precipitation inputs (growing season versus 

nongrowing season), the magnitude of precipitation 

deficit, and watershed characteristics (e.g., vegetation, 

watershed size and configuration, terrain features, soil 

depth and storage capacity, and hydrogeology). For 

example, on shorter time scales, ET can exceed P, 

particularly when water used in ET is derived from soil 

water stores or deeper groundwater stores, rather than 

recent or local P (Loheide and others 2005, Lubczynski 

and Gurwin 2005).

In this chapter, we (1) review the relationships between 

meteorological and hydrologic drought; (2) examine how 

differences in forest species composition and structure 

impact evapotranspiration, and we interpret these changes 

in the context of mitigating or exacerbating hydrologic 

drought; and (3) discuss the impacts of hydrologic drought 

on watershed processes and water quality.

Relationship Between 

Meteorological Drought 

and Hydrologic Drought

Meteorological drought is defined as the degree and 

duration of dryness relative to the average (chapter 2); 

the effects of meteorological drought on streamflow 

may differ across and within forest ecosystems. 

Hydrologic drought, defined as decreases in streamflow 

below a threshold level (chapter 2), is complex and 

difficult to relate to meteorological drivers. In this 

section, we describe how catchment characteristics and 

precipitation patterns influence the relationship between 

meteorological and hydrologic drought.

Catchment-Scale Sensitivity 

to Meteorological Drought

The catchment water-balance equation provides 

a conceptual framework for evaluating differential 

sensitivities of ET and Q to drought. In general, 

sensitivity depends most strongly on temporal and 

spatial storage in soil and groundwater pools, as well 

as snowpack in snow-dominated ecosystems. For 

example, in places with deep soils and hence greater 

soil water storage, there may be an apparent reduced 

sensitivity of ET and Q to reduced precipitation (Boggs 

and others 2013, Ohnuki and others 2008) that may 

help enhance resilience to drought (Taylor and others 

2013). In contrast, steep, coarse, and shallow soils 

that cannot retain water may represent systems with 

high ET and Q sensitivity to reduced precipitation. 

If accessible by trees roots, soil stores are more 

vulnerable to ET, so they deplete more rapidly and 

approach a state of near zero discharge much sooner 

(Fan and Miguez-Macho 2011).

The sensitivity of low flows to meteorological drought 

in places with deep or substantial groundwater storage 

should be thought of in two ways (Tague and Grant 

2009). In terms of absolute flow, they are more 

sensitive than systems with little storage because they 

generally sustain greater baseflow than systems with 

shallow and tight bedrock, and even a small fractional 

decline in low flows can be a large amount of water. In 
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contrast, places with little baseflow cannot decline far 

in absolute terms, simply because there is already so 

little runoff. However, when cast as a percent change 

due to either drought duration or precipitation recharge, 

the systems with greater groundwater storage are less 

sensitive. This differs from sensitivity to variations in 

the soil store, as we defined it, because water stored in 

soils (generally places where roots are more abundant) 

is vulnerable to ET, but deep groundwater is not.

Streamflow from forests where the snowpack makes 

up a large proportion of annual P is more sensitive to 

precipitation declines. When the annual precipitation 

is delivered as meltwater in one relatively large pulse, 

runoff generation is more efficient, and variations in 

potential ET have little effect on the total annual runoff, 

which is essentially dependent on how much snow 

accumulates and then melts. Similarly, if most of the 

precipitation falls in the cold season, it is less vulnerable 

to evaporation and is converted more efficiently to 

runoff. In such cases, ET may vary little as a function of 

precipitation, but variations in P will be transmitted to 

runoff reliably on an annual scale (Berghuijs and others 

2014, Wolock and McCabe 1999), similar to more humid 

locations (Milly and Dunne 2002) and locations with 

greater seasonality in P (Wolock and McCabe 1999).

High degrees of snow heterogeneity caused by drifting 

or large elevation ranges in a basin provide substantial 

buffering of Q variation through the year because deep 

drifts and high-elevation snowpacks do not melt until 

late in the summer (Luce and others 1998, Wolock 

2003). Snowpack meltwater is slowly released during 

warmer periods in these systems, making them less 

vulnerable to variations in summertime precipitation. 

Buffering from snow heterogeneity is probably most 

pronounced in the high mountains of the Western 

United States (Clark and others 2011). We illustrate 

the spatial variability of drought sensitivity impacts on 

water yield as a response to a uniform reduction of 

precipitation in figure 10.2 (Sun and others 2015).

Interactions With Precipitation Patterns

Reduced P not only affects Q through the amount of 

water available, but also through its timing. For example, 

in snowpack-dominated areas of the Western United 

States, a low snowfall winter creates a shallower 

snowpack that takes less time to melt and can create 

Percent reduction in water yield

-33 to -20

-19 to -10

-9 to -5

-4 to 0

Figure 10.2—Spatial distribution of annual forest water yield response (percent reduction in water yield) to a 

10-percent decrease in precipitation across the conterminous United States. Darker shades represent a greater 

percent reduction relative to lighter shades. Simulation results at the U.S. Geological Survey HUC-8 scale are 

presented at 1-km resolution by a mask of forest land cover (Source: Sun and others 2015).
235

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an expectation for lower flows in late summer (Cayan 

and others 2001, Stewart and others 2005, Tague and 

Grant 2009). While low elevation snowpacks are more 

sensitive to temperature in determining the melt timing 

(Mote 2006), the effect of P variability on center of 

timing of outflow can be quite pronounced from high 

elevation basins (Luce and Holden 2009). Warming can 

also shift the elevation of the transition zone between 

rain and snow, and rain on snow events (Surfleet 

and Tullos 2013), both of which impact streamflow 

timing. The synoptic weather patterns giving rise to 

prolonged drought can also shape the nature of P

events, making the relationship between hydrologic 

drought and meteorological drought dynamic (Potter 

and Chiew 2011). If limited ET occurs due to dry land 

surface conditions, convective storms may produce less 

intense P and less P during a given storm. The reduction 

in P has implications for a greater proportion being 

intercepted by canopies or held in soil, reducing runoff. 

Water added to wet soils or vegetation is more likely 

to contribute to recharge compared to periodic wetting 

of a relatively dry soil or canopy. Higher interception 

evaporation maximizes the potential for recirculation 

of water between land and atmosphere, but also 

exacerbates Q responses during prolonged dry periods.

Species Composition, Vegetation 

Dynamics, and Drought Interactions 

With Streamflow

Understanding and predicting the complex interactions 

among species, vegetation dynamics, and streamflow 

requires integrating atmospheric conditions, aboveand belowground plant physiological processes, forest 

stand dynamics, soil water availability, and streamflow 

generation processes. Many of these components are 

discussed in detail in other chapters of this assessment 

(i.e., chapter 2 characterizes drought for forests and 

rangelands; chapter 3 summarizes the physiological 

responses of forest tree species to drought; and chapter 

4 addresses drought impacts on forest structure, 

dynamics, and diversity).

Assessing the ecohydrological implications of drought 

requires quantification and understanding of how the 

individual components interact to determine hydrologic 

responses. Due to the challenges associated with 

linking ecological and hydrological processes, much 

of our insight into ecohydrologic feedbacks has been 

derived from quantifying short-term, species-specific 

physiological processes from experimental studies; 

linking and projecting long-term vegetation dynamics; 

and interpreting long-term streamflow dynamics under 

varying ecohydrological conditions.

Vegetation structure and species composition 

directly impact the hydrologic cycle because they 

exert significant control on several hydrologic fluxes: 

evaporation, transpiration, canopy interception, 

forest floor interception, infiltration, overland flow, 

groundwater recharge, and streamflow (fig. 10.1). Given 

that transpiration can represent up to approximately 70 

percent of ET (Schlesinger and Jasechko 2014) and ET

can represent >100 percent of P (e.g., when ET includes 

stored soil water or groundwater sources) (Sanford and 

Selnick 2012), changes in transpiration (e.g., due to 

shifts in species assemblages) can substantially impact 

stand water balance and downstream water supply. 

If drought frequency and duration increase, these will 

likely lead to significant changes in vegetation structure 

and species composition. While some trees will die as 

a direct consequence of moisture stress and cavitation 

(chapter 3), the interaction between drought and other 

stressors such as insects and pathogens may be an 

even more important driver of drought-related mortality 

(chapter 6).

Extreme droughts and heat waves have already 

triggered widespread tree mortality globally (Allen 

and others 2010, Weed and others 2013), and there is 

observational evidence that forests across all biomes 

might be equally vulnerable to drought (Choat and others 

2012). The detailed physiological mechanisms and 

thresholds that determine when mortality or dieback will 

occur for different species are addressed in chapter 3. 

Here we provide an overview of the potential impacts of 

drought on species assemblages and consequences for 

ecohydrological processes, while highlighting examples 

from different regions within the United States that 

illustrate possible scenarios for future change.

Generally, when mortality rates increase for a particular 

species or set of species, whether due to climatic, 

biotic, or other drivers, stand density of live mature trees 

decreases and stand leaf area index and productivity 

decline. This process may either occur abruptly, as 

in the case of rapid mortality in response to an acute 

stressor [e.g., eastern hemlock (Tsuga canadensis) 

mortality following attack by hemlock woolly adelgid 

(Adelges tsugae), or western juniper (Juniperus 

occidentalis) mortality following severe drought], or 

gradually, as in the case of chronic diseases that slowly 

diminish the health of host trees [such as with beech 

bark disease (Neonectria spp.) infecting American 
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beech (Fagus grandifolia Ehrh.)]. Extensive research in 

mesic forest ecosystems has shown that a reduction in 

forest cover generally reduces stand transpiration and 

leads to an increase in streamflow (Bethlahmy 1974, 

Bosch and Hewlett 1982, Hadley and others 2008, 

Stednick 1996, Zhang and others 2001); however, these 

forest-streamflow relationships are less well understood 

in semi-arid regions and are potentially very different 

than mesic regions (Wilcox and Thurow 2006). In 

northern temperate regions, the reduction in canopy 

cover leads to greater snow accumulation and more 

rapid snowmelt due to decreased canopy interception 

and increased solar radiation reaching the forest floor 

(Boon 2012, Pugh and Small 2012). Depending on the 

temporal and spatial dynamics of the die-off process, 

resources that become available after tree mortality 

are eventually utilized by existing co-dominant mature 

trees and/or existing or newly regenerating seedlings 

and saplings in the understory and mid-story; often (but 

not always) these changes are associated with a shift in 

species composition.

Because different species and functional groups vary 

in their ecophysiological traits that influence water use 

patterns (chapter 3), changes in species assemblages 

can alter hydrological processes from the stand to the 

watershed scales. Below, we highlight examples from 

different regions of the United States of species shifts 

resulting from global change drivers to illustrate the 

potential ecohydrological impacts.

Northeastern Region

Although the Northeastern United States is expected 

to experience an increase in total annual precipitation 

(mostly in the winter and spring), and an increase in 

large rainfall events, it is also projected to have more 

prolonged rainless periods, particularly in mid- to latesummer (Swain and Hayhoe 2014). While the mixed 

deciduous-coniferous forest ecosystems that dominate 

the Northeast are more limited by radiation and nutrients 

than water (Vadeboncoeur 2010), paleoecological 

evidence suggests that previous droughts have strongly 

influenced changes in species assemblages and 

ecosystem dynamics; consequently, such extreme 

events may be outside the range of species’ capacities 

for adaptation and resilience (Pederson and others 

2014). Future drought stress will likely be concomitant 

with biotic stressors that also may be outside the 

physiological tolerance of these forests (Dietze and 

Moorcroft 2011, Groffman and others 2012, Lovett and 

others 2006). Thus, the ecohydrological effects of tree 

mortality due to these multiple stressors are particularly 

relevant for managing water resources in the Northeast. 

Here, we discuss two species affected by such climate 

change-biotic agent interactions specifically within 

the context of increasing drought stress and potential 

ecohydrological implications.

Eastern hemlock, an ecologically important species 

throughout much of its geographical range, is currently 

experiencing rapid decline due to the hemlock woolly 

adelgid (HWA), an exotic insect that has invaded 

forests from Georgia to Maine (Fitzpatrick and others 

2012). The primary factor limiting the spread of HWA 

is overwintering temperatures; increasing winter 

temperature has accelerated the invasion process 

and associated hemlock mortality (Paradis and others 

2008). Once attacked, eastern hemlock trees usually 

die within 4–5 years (Young and others 1995); thus, 

HWA infestations create an acute disturbance event that 

abruptly changes stand structure and composition.

The most likely scenario for these forests is that 

hemlock will be replaced by broadleaved deciduous 

species (Ellison and others 2005, Ford and others 2012). 

Research shows that this shift in the dominant species 

will result in higher annual transpiration rates and total 

ET, in turn causing small decreases in streamflow during 

the growing season and increased peakflow after large 

storm events in the dormant season due to decreased 

canopy interception (Brantley and others 2013, Brantley 

and others 2014, Ford and Vose 2007). Another 

hydrologic control of these dense evergreen canopies 

is their insulating effect on snowcover (Lustenhouwer 

and others 2012); consequently, hemlock loss and 

subsequent warming air temperatures will likely alter 

snowmelt and runoff dynamics during the winterspring transition period. Post mortality regeneration 

may offset these impacts to some degree, but impacts 

will be long lasting if the evergreen canopy is replaced 

with a deciduous canopy. Finally, while the above 

studies show that hydrologic impacts of hemlock loss 

are likely, eastern forests may experience minimal 

long-term effects on carbon fluxes (Albani and others 

2010) because although there can be rapid mortality 

of hemlock trees following HWA invasion, subsequent 

replacement by other species—such as red maple (Acer 

rubrum L.), birch (Betula spp.), oaks (Quercus spp.) and 

American beech (Fagus grandifolia Ehrh.)—also occurs 

relatively rapidly (Cobb 2010, Ford and others 2012).

American beech has experienced decline since the 

early 20th century due to beech bark disease (BBD), 

which is caused by infestation by the exotic scale insect, 
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Cryptococcus fagisuga (Lind.), and subsequent infection 

by one or more fungi (Kasson and Livingston 2012). 

In contrast to HWA, BBD is a chronic disturbance that 

slowly diminishes the host tree’s vitality and health, 

but usually does not directly cause mortality. Evidence 

also suggests that a prolonged period of mild winters 

and drier-than-normal late summers (including a major 

drought) triggered a significant growth decline and 

mortality in BBD-infected trees in Maine (Kasson and 

Livingston 2012); this suggests that the disease lowers 

the resistance of trees to other stressors. Predictions 

for future BBD-affected stands are that other associated 

or co-dominant species, particularly sugar maple (Acer 

saccharum) and yellow birch (Betula alleghaniensis), 

will replace this species (Forrester and others 2003, 

Hancock and others 2008, Lovett and others 2013).

Given the slow progression rate of BBD, the shift in 

forest structure and species composition is expected 

to also occur gradually, which is confirmed by the 

lack of a significant change observed in aboveground 

net primary production in BBD-affected stands in the 

Catskills region of New York (Hancock and others 

2008). Consequently, impacts on the hydrologic 

cycle may also be gradual (Busby and Canham 

2011). Moreover, because many of the associated 

species (e.g., sugar maple, yellow birch) have similar 

ecological characteristics and functions to American 

beech, including transpiration, leaf hydraulic traits, and 

vulnerability to cavitation (Hoffmann and others 2011, 

Wullschleger and others 2001), these changes may not 

significantly alter stand transpiration and, hence, runoff 

and streamflow dynamics, although effects will likely 

vary across different forests and geographic regions.

Western Mountain Region

Recent warming trends and more prolonged and 

frequent droughts have accelerated the spread and 

intensity of attacks by mountain pine beetle (MPB) 

(Dendroctonus ponderosae) and increased the 

susceptibility of host trees, resulting in widespread 

mortality of five-needle pine and affecting more than 

600,000 km2 of coniferous forests in western North 

America since 1996 (Weed and others 2013). Forests 

that are already water stressed appear to be more 

vulnerable to severe MPB attacks (Kaiser and others 

2013). Because these outbreaks often kill nearly all of 

the canopy trees within forest stands, they influence 

the energy balance of the land surface and potentially 

affect many hydrologic processes (Potts 1984, Pugh 

and Gordon 2013). MPB-infested watersheds will 

likely experience a decrease in ET, but an increase in 

snow accumulation and earlier and faster snowmelt; 

combined, these processes would lead to increases in 

runoff volume and a change in timing (Mikkelson and 

others 2013). As a whole, MPB-infested watersheds 

would be at greater risk for flooding in the spring and 

drought in the summer (Mikkelson and others 2013).

Similarly, increased wildfire in western U.S. forests 

(chapter 7) would be expected to change water yield, 

timing, and flood potential in basins after fire. Small 

basins (on the order of 10–20 km2) have shown 

substantial increases in post-fire debris flows and 

flooding (Cannon and others 2001, Istanbulluoglu and 

others 2004, Moody and Martin 2009). However, 

increases in post-fire flooding have not been noted for 

large basins on the order of 2,000 km2, despite a great 

enough portion of the basin burning to cause increases 

in basin water yield by 5 percent (Luce and others 2012).

Southwestern Pinyon-Juniper Woodlands

One region and vegetation type most severely 

affected by extreme drought and heat events—

often in combination with associated increases in 

stress from biotic agents—is the pinyon-juniper 

woodlands of the Southwest United States. As a 

result of these extreme events, this vegetation type 

has experienced major changes in mortality rates and 

species composition throughout much of this region, 

with significant ecohydrological consequences. For 

instance, widespread mortality has occurred in pinyon 

pine populations, while western juniper trees have 

exhibited relatively high survival (Plaut and others 2012) 

(chapter 3 for mechanisms). During the 2000–2002 

severe drought event, streamflow from southwestern 

watersheds decreased following tree die-off, likely 

due to increases in the understory vegetation after 

release from competition and shade, and subsequent 

reductions in overland flow (Guardiola-Claramonte 

and others 2011). Widespread vegetation die-off can 

have contrasting ecohydrological impacts in waterlimited versus high rainfall regions; these observations 

underscore the need for more research to understand 

the vegetation-drought-hydrology interactions and 

feedbacks that determine watershed scale effects on 

streamflow dynamics (Adams and others 2012).

Southern Region

Extensive forest areas in the Southern United States have 

experienced severe droughts in recent years causing 

widespread tree mortality in many regions (Elliott and 

Swank 1994, Klos and others 2009). Some tree species 

and size classes are more vulnerable than others (chapter 
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4), suggesting the potential for drought-mediated shifts 

in both species composition and structure. For example, 

Klos and others (2009) reported higher drought-related 

mortality in pine and mesophytic species groups 

(e.g., Liriodendron tulipifera, Acer spp., Betula, Fagus, 

Magnolia) than in oaks (Quercus spp.). In contrast, Clinton 

and others (1993) documented a higher mortality in larger 

and older oak (especially Quercus coccinea) associated 

with interactions between drought and root pathogens.

Tree-level sapflow data suggest wide variation in 

whole-tree daily water use among species groups, and 

different sensitivities to water stress depending on 

xylem anatomy. A two- to three-fold difference among 

species (holding tree size constant) in mean daily water 

use can occur in these forests (Ford and others 2011b), 

with oaks (e.g., Quercus rubra, Quercus prinus) generally 

having lower water use than more mesophytic species 

(e.g., Betula lenta, Liriodendron tulipifera) (figs. 10.3 

and 10.4). While oaks and hickories have a potential for 

high water use based on the diameter of their xylem 

conduits, field observations across the region suggest 

that these species operate under a fraction of this 

potential, thus lending support for their low observed 

water use (fig. 10.4). These tree-based data suggest 

that drought-related shifts in species composition may 

impact streamflow, as has been demonstrated by 

sapflow and ecohydrological studies on species such as 

eastern hemlock (discussed earlier), and in small paired 

watershed studies of hardwood to pine conversions 

(Ford and others 2011b); however, drought-related 

changes in species composition may be much more 

difficult to detect, especially in diverse stands and at 

larger spatial scales (Patterson and others 2013).

Range Shifts in Major 

Ecosystem Types in Response 

to Climate Change

Thus far we have focused the discussion on the 

ecohydrological impacts of tree mortality of certain 

species due to drought and interactions with biotic 

agents; but model projections and some empirical 

evidence suggest that entire communities will shift 

their range in response to climate change. In the New 

England region, models project that by the late 21st 

century 71–100 percent of boreal conifer forests will be 

lost; the range of mixed oak-hickory forests will shift 

northward by 100–200 km and expand by 149–431 

percent; and northern deciduous hardwoods will 

decrease in area by 26 percent (Iverson and Prasad 

2001, Tang and Beckage 2010, Tang and others 2012). 

However, within a community type, individual species’ 

responses will depend on phenology and physiology, 

with some species benefiting more from decreased 

stomatal conductance and increased water use 

efficiencies in response to rising carbon dioxide (CO2) 

(Tjoelker and others 1998).

Observed

growing season

water use

232

Average growing season

daily water use (kg)

Diameter (cm)

Species Xylem element type

Diffuse porous B. lenta

N. sylvatica

C. florida

L. tulipifera

A. rubrum

P. occidentalis

Carya spp.

T. canadensis

P. strobus

Q. prinus

Q. rubra

Tracheid

Ring porous

180

165

150

135

120

105

90

75

60

45

30

15

0

0 10 20 30 40 50 60 70 80 90

Semi-ring porous

Figure 10.3—Average growing season daily water use across species sampled in the Coweeta Basin. 

(Source: Ford and others 2011).
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For example, species with evergreen sclerophyllous 

leaves that characteristically have high mesophyll 

resistance are predicted to benefit more from increased 

CO2 concentrations compared to deciduous broadleaved 

species (Niinemets and others 2011). The amount of time 

required for communities to reach a new equilibrium is 

uncertain; however, observations from past migration 

rates suggest that species may not keep pace with their 

climate envelopes (Loarie and others 2009).

Changes in future rainfall patterns may also affect the 

competitive interactions among species and thus affect 

the outcome of range shifts (Clark and others 2014a, 

Clark and others 2014b). For example, because northern 

deciduous hardwoods tend to be physiologically less 

drought tolerant than mixed oak-hickory, an increase in 

precipitation [as predicted by Swain and Hayhoe (2014)] 

may favor the former and enable them to persist to a 

greater extent within their current range. Because trees 

are long-lived, range shifts of forest ecosystems will 

be a slow process; however, initial shifts are already 

being detected in the understory regeneration. For 

instance, Fisichelli and others (2014) showed that 

seedlings and saplings of temperate forest tree species 

are establishing across local ecotones into boreal forest 

patches in central North America, a process facilitated 

by warmer temperatures.

Boreal conifer regeneration has been negatively 

correlated with the regional temperature gradient and 

only displayed high abundance at the boreal end of local 

ecotones at cool northern sites, suggesting a reduced 

range for boreal forests in the future (Fisichelli and others 

2014). In the Western United States, models project 

shifts in major vegetation types in response to climate 

change (Bachelet and others 2001). In addition to climate, 

an overarching influence on future vegetation types for 

the Western United States is fire and biotic disturbances 

(Hicke and others 2012, McKenzie and others 2004). 

Using models that combine changing fire regimes and 

climate, Halofsky and others (2013) project an overall 

decline in cool needle-leaf and subalpine forest vegetation 

types, and an increase in xeromorphic shrubland types.

Predicting how these changes will impact hydrologic 

processes at larger spatial scales presents a 

considerable challenge. Although tree-level physiological 

data and small watershed studies suggest a strong 

interaction between vegetation type, structure, and 

hydrologic processes, we do not know how these 

interactions and gradual changes will play out at larger 

landscapes and longer time scales.

Diffuse porous Ring porous Tracheid

80

70

60

50

40

30

20

10

0

ACRU LITU QUAL QUCO PIRI

ACRU LITU QUAL PITA

LIST NYSY CELO USLP PITA

Loss of stem hydraulic 

conductivity percent

Loss of stem hydraulic 

conductivity percent

Loss of stem hydraulic 

conductivity percent

(A) Southern Appalachian

(B) Piedmont

(C) Coastal Plain

80

70

60

50

40

30

20

10

0

80

70

60

50

40

30

20

10

0

Figure 10.4— Percent loss of hydraulic conductivity (PLC) for 

co-occurring species varied by xylem type across a regional 

gradient from (A) Southern Appalachian forests to (B) Piedmont 

forests to (C) Coastal Plain forests. Ring-porous trees had 

>50 percent dysfunction under the same soil water potentials 

as diffuse porous and tracheid-type species. Evidence 

suggests that mortality occurs when plants experience >80 

percent dysfunction. Bars represent the mean PLC across five 

individuals from each species sampled three times throughout 

the growing season (May, August, and October 2010). Bars are 

standard error. PLC was determined using a flowmeter (Xyl’em, 

Bronkhorst,® France) and the following equation: {[ks(max)-

ks(P)]/ks(max)}, where ks(P) is the hydraulic conductivity 

at the time of sampling from the field, and ks(max) is the 

conductivity determined after fully saturating the sample under 

vacuum for 24 hours or with high positive pressure. ACRU=red 

maple; LITU=tulip poplar; LIST=sweetgum; NYSY=black gum; 

QUAL=white oak; QUCO=scarlet oak; CELO=sugarberry; 

ULSP=American elm; PIRI=pitch pine; PITA=loblolly pine. 

(Source: unpublished data;C.F. Miniat and J.M. Vose. On file 

with: C.F. Miniat, Coweeta Hydrologic Laboratory, 3160 Coweeta 

Lab Road, Otto, NC 28763; cfminiat@fs.fed.us).
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Groundwater 

Interactions 

With Drought

When available to tree roots, groundwater may help 

vegetation avoid drought-induced effects (Ehleringer 

and Dawson 1992). This strategy is well-known in 

groundwater-dependent ecosystems (Orellana and 

others 2012) such as wetlands and riparian forests 

(Busch and others 1992, Thorburn and others 1992), but 

has also been recognized in upland systems (Dickson 

and Tomlinson 1996, Miller and others 2010), which can 

be referred to as groundwater-influenced ecosystems.

Groundwater-dependent ecosystems dominated by 

phreatophytes, plants dependent on groundwater for 

their water supply (Meinzer 1927, Robinson 1958), are 

well studied. Examples include deep-rooted trees and 

shrubs including cottonwood (Populus spp.), willow 

(Salix spp.), salt cedar (Tamarix spp.), greasewood 

(Adenostoma fasciculatum, Baccharis sarothroides, 

Glossopetalon spinescens, Larrea tridentate, and

Sarcobatus vermiculatus.), and mesquite (Prosopis spp.). 

Phreatophytes can be obligate or facultative depending 

on whether they rely on perennial access or intermittent 

access to groundwater to avoid drought (Smith and 

others 1998), with examples in the latter category 

including sagebrush (Artemesia spp.) and rabbitbrush 

(Chrysothamnus spp.) (Nichols 1994). Phreatophytes 

(particularly those in arid regions) also employ a diverse 

array of other drought-avoidance and drought-tolerance 

strategies to survive dry periods including control of the 

magnitude and timing of leaf area, osmotic potential, leaf 

conductance, and maintenance of turgor at low leaf water 

potential (Nilsen and others 1984).

The groundwater subsidies, as defined by Lowry and 

Loheide (2010), are provided to groundwater-dependent 

and groundwater-influenced ecosystems buffering 

them from adverse effects of drought. Maps depicting 

estimates of depth to groundwater (see fig. 4 in Fan and 

others 2013) reveal that it is generally <5 m across vast 

regions of the United States, which is within the critical 

range required to help offset the impacts of drought in 

forests and many other ecosystems ( Lowry and Loheide 

2010, Maxwell and Kollet 2008, Soylu and others 2014). 

Even when groundwater is not regionally shallow, riparian 

and other areas may have shallow groundwater (Fan and 

others 2013) resulting in local areas where groundwater 

is not sufficient to buffer drought. Heterogeneity in 

groundwater depth across the landscape suggests the 

potential for management and protection strategies 

aimed at specific resources as the landscape becomes 

further fragmented into natural, urban, and agricultural 

systems (Jackson and others 2009).

Challenges to Predicting 

the Impacts of Drought on 

Hydrological Processes

Sensitivity analysis and empirical data suggest that the 

magnitude of hydrologic responses to droughts, due to 

climate warming or/and reduction in precipitation, vary 

tremendously under different regimes (Lu and others 

2013, Ma and others 2008). Predicting short-term 

responses to moderate- and short-duration droughts 

is generally straightforward, especially if drought does 

not change above- and belowground forest structure. 

For example, at monthly or annual time scales over 

large areas, hydrologic models can capture much of the 

drought-related streamflow dynamics that occur simply 

as a direct result of reduced precipitation, or indirectly 

using an empirical soil moisture feedback (Caldwell and 

others 2012, Sun and others 2011).

In addition to climatic dryness (potential ET/P), terrain 

characteristics, land cover types, biomass, and 

soils all influence the potential impacts of droughts 

on watershed hydrology. This complexity poses 

considerable challenges for predicting the impacts of 

drought on hydrological processes. Adding leaf-level 

physiological responses (either mechanistically or 

empirically) and soil moisture dynamics can increase 

predictive ability (Hanson and others 2004), although 

often these are “big-leaf” models that homogenize 

canopy variation and belowground responses.

Considerable uncertainty can result if models are unable 

to accurately account for above- and belowground 

structural and functional vegetation responses that can 

occur after severe and/or long-term drought (Luo and 

others 2008, Tague and others 2013). Examples of longterm vegetation responses to drought include reduced 

leaf area index from abscission or mortality, altered 

root-to-shoot ratios (Joslin and others 2007), differential 

species responses in mixed species stands (Ford and 

others 2011a), and changing species composition 

(Anderegg and others 2013, Klos and others 2009). 

All of these factors drive or feed back to ET, ultimately 

influencing stand water balance and streamflow.
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One of the limitations of physically based modeling 

approaches is that changes in vegetation structure 

(e.g., reduced leaf area, changing root distributions, 

etc.) and function (e.g., shifts to species with different 

mechanisms for regulation of water use) that may 

occur in response to severe drought are often not 

explicitly incorporated in the framework and require 

direct empirical investigation to understand (Powell 

and others 2013). For example, short-term droughts 

(e.g., <1 year) may dry up depressional forested 

wetlands in the Southeastern United States, but 

hydrologic processes recover quickly and trees are 

rarely subject to water stress due to changes in soil 

water storage in wetlands (Lu and others 2009, Sun 

and others 2010). However, long-term droughts could 

alter wetland hydrology to an extent that causes 

permanent changes in plant community composition 

and fire regimes (De Steven and Toner 2004) resulting 

in altered hydrologic processes at larger spatial scales. 

Furthermore, lumped parameter ecosystem models 

that intend to describe the effects of soil water on 

ecological processes such as carbon cycling, often 

treat soil water and nutrient movement in a rather 

simplified fashion. For example, lateral flow and 

topographic effects on soil water distribution on the 

landscape are usually not accounted for in ecosystem 

models (Govind and others 2009); however, modeling 

approaches that account for subsurface hydrologic 

connectivity suggest strong spatial controls on 

ecosystem processes (Emanuel and others 2010, 

Hwang and others 2009).

More accurate predictions of the impacts of severe 

and longer term drought (especially when vegetation 

changes occur) will require models that couple 

hydrologic and ecosystem processes in a dynamic 

context with appropriate feedbacks (Law 2014). It is 

expected that ecosystem-specific models are needed 

to more fully determine hydrologic responses to 

extreme droughts, especially recent observations of 

“exceptional drought” arising from the combination 

of very low precipitation and warmer temperatures 

(Diffenbaugh and others 2015). This is not a trivial 

expectation, as it requires models that couple leaflevel physiology, above- and belowground whole-tree 

responses, root dynamics and soil water access, stand 

level responses, and physical hydrology (Tague and 

others 2013) and usually results in complex models 

that are difficult to parameterize and calibrate over 

large spatial scales.

Drought Impacts 

on Water Quality

Droughts not only affect the quantity of water in and 

flowing from forest ecosystems, but also water quality, 

having important implications for stream ecosystem 

services. Drought affects water quality both directly 

and indirectly. Direct impacts are primarily physical, 

as reduced streamflow concentrates nutrients and 

sediment, and warms more quickly. Indirect effects 

include a combination of terrestrial, riparian, and 

instream processes that impact sediment and nutrient 

concentrations and fluxes. The impacts of drought 

on terrestrial biogeochemical cycling processes are 

discussed in chapter 5. Here we focus primarily how 

those and other drought-related impacts influence water 

quality in forest streams.

Importance of Intermittent 

and Ephemeral Streams

Much of our understanding of the linkages among 

drought, streamflow, and water quality is derived 

from gauged perennial streams; less information is 

available on the impacts of drought on ephemeral 

and intermittent streams, despite the fact that these 

streams are a critical component of the hydrologic 

network in forested watersheds and river systems 

(Acuña and others 2014, Larned and others 2010, 

Lowe and Likens 2005). In terms of ecohydrological 

functions, intermittent and ephemeral streams serve 

critical roles for elemental cycling, connecting materials 

and energy exchange in watersheds (Lowe and Likens 

2005) and river networks, and providing unique habitat 

for plants (Katz and Moore 2011) and aquatic and 

terrestrial species (McDonough and others 2011). They 

are most common in arid and semi-arid regions of the 

United States (Levick and Rogers 2008), but also occur 

frequently in the headwaters of forested watersheds in 

all regions (Hansen 2001, Larned and others 2010).

Intermittent streams are typically seasonal, and surface 

flows occur in response to snowmelt or elevated 

groundwater resulting from high precipitation or 

reduced ET, whereas ephemeral streams flow as a 

result of discharging groundwater and in response to 

runoff events (McDonough and others 2011). Due to 

their dependence on precipitation and/or snowmelt, 

intermittent and ephemeral streams are particularly 

vulnerable to drought (Palmer and others 2008). 

Increasing the duration or frequency of drought will 
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increase and alter periods of “no-flow” conditions 

and change hydrologic processes and aquatic habitats 

(Godsey and others 2014, Jaeger and Olden 2012).

These changing flow regimes are likely to have 

important implications for the timing and quantity of 

carbon, nutrient, and sediment exchanges with the 

perennial stream network, and alter habitat availability 

for fish and other aquatic organisms (Brooks 2009). 

Species that utilize ephemeral and intermittent streams 

already have adaptations to survive dry periods; 

however, whether these traits will allow for survival 

under longer, more frequent, and more extreme 

droughts is uncertain (Robson and others 2011) but 

of concern (Acuña and others 2014, Brooks 2009). 

For example, a prolonged drought had a much greater 

impact on fish and invertebrates in ephemeral and 

intermittent streams than in perennial streams in a 

Mediterranean climate (Beche and others 2009).

Stream Chemistry and Sediment

The terrestrial biogeochemical consequences of 

drought (chapter 5) are closely linked to changes in 

vegetation and hydrology (Dahm and others 2003). 

However, the effects on water quality can be highly 

variable depending on the characteristics of the site 

and broader region. The role of tree species on nutrient 

cycling is well documented (Finzi and others 1998, 

Pastor and others 1984); therefore, shifts in species 

composition may affect biogeochemical processes in 

soil that ultimately impact the chemical composition 

of streamwater (chapter 5). For example, Wurzburger 

and Miniat (2014) found that tree species that have the 

ability to form nitrogen gas (N2)-fixing nodules in their 

roots do so more under conditions of moderate drought, 

adding a new source of nitrogen (N) into these systems 

that could be available for uptake and eventual leaching 

and stream export.

Drought may also affect the productivity of vegetation, 

having implications for stream chemistry. For example, 

Lutz and others (2012) suggested that streamwater 

nitrate concentrations are affected by temporal trends 

in fine root production and mortality during drought. In 

the early stages of drought, root production may initially 

increase as trees attempt to access soil water over 

broader areas (Hendrick and Pregitzer 1996), resulting 

in lower streamwater nitrate concentrations. Following 

drought, root mortality returns N to the system, resulting 

in higher stream nitrate concentrations. Secondary 

influences of drought on disturbances such as wildfire 

can also impact water chemistry and sediment (Goode 

and others 2012, Smith and others 2011, Spencer and 

others 2003) (chapter 7 includes discussion of how 

drought affects fire severity and probability).

The combination of biological and hydrologic controls 

on water quality results in high complexity and spatial 

heterogeneity in response to drought. Concentrations 

of a particular solute in streamwater can increase at 

one location while decreasing at another. Droughts can 

have a concentrating effect on solutes in streamwater 

due to the limited volume of water. However, the flux 

of solutes in streamwater is generally lower during 

drought periods because less water is moving through 

the watershed. As streamflow declines, nutrients 

moving downstream are cycled more rapidly (Fisher 

and others 1998). This more rapid uptake of solutes 

within streams can have a strong influence on their 

concentration. For example, high streamwater silica 

concentrations are often observed during dry periods 

because silica is derived from mineral weathering and 

tends to increase when groundwater inputs dominate 

(Johnson and others 1969). However, several studies 

have reported declines in the concentration of 

dissolved silica during drought (Wall and others 1998, 

Williams and Melack 1997).

Wall and others (1998) determined that the low 

silica concentrations during a drought at Canajoharie 

Creek, New York, could only be attributed to instream 

processing, resulting from uptake by diatoms. Reduced 

streamflow velocity also enhances sediment and 

particulate organic matter deposition (Acuña and 

others 2007, Wood and Armitage 1999). Fine sediment 

deposition during drought has been shown to negatively 

affect stream organisms, such as macroinvertebrates 

and fish (Hakala and Hartman 2004, Kaller and Hartman 

2004, Kemp and others 2011, Wood and Armitage 

1997). In cases where streamflow ceases entirely, 

water becomes stagnant, and sediment, organic matter, 

and nutrients can accumulate in the pools that form. 

Severely reduced or eliminated flow, along with warmer 

temperatures, may promote algal growth (Caramujo 

and others 2008) and reduce dissolved organic carbon 

(DOC) in streams (Everard 1996). In most cases, the 

concentration and flux of DOC in streamwater are low 

during drought years compared to normal or wetter 

years. The reduced export of DOC during droughts has 

been attributed to factors such as diminished flow and 

changing flow paths (Eimers and others 2008, Portal 

and others 2009, Schindler and others 1997, Worrall and 

Burt 2008), decreased organic matter solubility during 

acidic episodes (Clark and others 2005, Clark and others 
243

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Ecohydrological Implications of Drought 

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

2006), and decreased production of DOC due to the 

inhibition of microbial processes associated with dry or 

acidic conditions during drought (Scott and others 1998).

Subsurface hydrologic flowpaths can also play a 

critical role in regulating the concentration of solutes in 

streamwater. During droughts, groundwater continues 

to travel along deep, long flowpaths, whereas less 

water flows along shallow groundwater paths. As 

the water residence time increases along these deep 

flowpaths, the contact time between groundwater and 

bedrock lengthens. This results in a higher concentration 

of streamwater solutes derived from geological 

weathering of bedrock. In contrast, during high flows, 

water tends to move more rapidly through upper soil 

horizons, resulting in higher concentrations of elements 

derived from organic matter, such as carbon (C) and 

nitrogen (N) (Raymond and Saiers 2010, Swistock 

and others 1989). Local lithology largely determines 

which elements will become more concentrated in 

streamwater during drought.

While it is typically difficult to determine when a drought 

begins, droughts are often punctuated by a more abrupt 

ending, at which point their biogeochemical impacts 

are most apparent. The first flush of water following 

drought has high concentrations of products that 

have accumulated in the soil (Burt and others 2014). 

Aerobic processes in the vadose zone produce nitrate, 

sulfate, and DOC that are transported to surface waters 

when a drought ends. The flushing of solutes can last 

for multiple storms, as saturated zones enlarge and 

hydrologic connections expand. Some solutes can have 

complex responses to drought, such as potassium, 

which has been shown to be influenced by changes 

in flowpaths, sediment transport, and the chemical 

properties of streamwater (Stott and Burt 1997). Other 

solutes with more predictable responses to drought are 

those that are sensitive to oxidation-reduction reactions. 

For example, sulfate and nitrate tend to exhibit the 

strongest and most predictable responses to drought, 

especially in streams that drain wetland and riparian 

zones, which are typically saturated.

Stream Temperature

Streamwater temperature is a critical water quality 

parameter that affects the chemical, biological, and 

ecological processes and functions of watersheds 

(Caissie 2006), and it influences the growth and 

distribution of aquatic organisms (Hester and Doyle 

2011, Mohseni and others 2003). Droughts impact 

streamwater temperatures primarily by decreasing 

stream discharge (flow volume and velocity) and 

increasing solar radiation (exacerbating wildfires and 

limiting vegetation density), and to a lesser extent by 

changing atmospheric (precipitation, air temperature) 

and streambed factors (groundwater input). The low 

flows associated with droughts during warm periods 

cause stream temperatures to increase because 

thermal capacity is lower when flow volume decreases 

(Hockey 1982, Webb 1996, Webb and others 2003) and 

slower water velocities allow streams to more strongly 

equilibrate to local climatic conditions (Isaak and others 

2012, Meier and others 2003).

Warmer waters hold less dissolved oxygen, and 

drought conditions concentrate aquatic organisms in 

smaller habitat volumes. Droughts, therefore, can cause 

significant stress to fish and other aquatic organisms 

by increasing metabolic costs and the intensity of 

interspecific competitive interactions. For some highly 

valued, coldwater species like trout and salmon, 

temperatures often define the geographic extent of 

their habitat, and drought conditions may temporarily 

constrain those habitats or even incur direct mortalities 

during extreme events. The lethal temperature limit for 

a coldwater trout species such as eastern brook trout 

(Salvelinus fontinalis) is approximately 25 °C (Bjornn and 

Reiser 1991, Hokanson and others 1977); but, reduced 

growth begins to occur at temperatures well below 

this limit. Most aquatic organisms are ectothermic, so 

the limitations imposed by temperature and dissolved 

oxygen during droughts have broad implications for 

the growth and survival of individuals in many species 

(Bjornn and Reiser 1991), including coldwater species.

Atmospheric, topographic, and vegetative shade; 

streambed; and stream and groundwater discharge 

factors all play a role in stream temperature dynamics. 

Atmospheric factors are most influential on larger 

streams and less so in smaller headwater streams. 

For example, Evans and others (1998) found that 82 

percent of the heat energy exchange in a stream with a 

109-km2 drainage area in the United Kingdom occurred 

at the air/water interface, while 15 percent occurred at 

the streambed interface. In smaller headwater streams, 

temperature dynamics are more strongly controlled 

by the amount of local groundwater (Deitchman 

and Loheide 2012) and the role of topographic and 

vegetative shade in mediating the solar radiation that a 

stream receives (Johnson 2003, Luce and others 2014). 

Solar radiation is the single largest energy input to most 

streams, accounting for as much as 97 percent of the 

total energy gains (Evans and others 1998).
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Ecohydrological Implications of Drought 

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Management Options 

for Minimizing the Impacts 

of Drought on Water 

Quantity and Quality

The concept of managing forests to augment annual 

streamflow is not new (Douglass 1983); however, 

recent severe drought in many areas of the United 

States has increased awareness of the relationship 

among forest disturbance and management, drought, 

and streamflow (Ford and others 2011b, Jones and 

others 2012). Since harvesting often increases annual 

water yield, it has been suggested that the effects 

of drought could be mitigated by cutting forests 

(McLaughlin and others 2013). A major challenge in 

managing forests to enhance water supply is that a 

large proportion of the watershed has to be cut in order 

to increase annual runoff (Bosch and Hewlett 1982). 

Consequently, the potential increases in streamflow 

through forest cutting are minimal due to limitations on 

the amount of land that can be harvested at any given 

time (Kattelmann and others 1983).

Streamflow responses are often short term due to 

rapid forest regrowth (e.g., especially in the Eastern 

United States) (Swank and others 2014), and the 

aggrading post-cut forest may actually have lower 

streamflow than the uncut forest (Ford and others 

2011b). Additionally, because of the unpredictable 

nature of droughts, it is impractical to plan the timing 

of harvesting operations so that the streamflow 

response occurs rapidly enough to offset the effect 

of drought. Furthermore, in contrast to management 

actions that are intended to augment streamflow, 

increasing drought stress in some forest ecosystems 

may warrant management strategies that retain water 

(and hence reduce streamflow) on the landscape in 

order to keep trees alive (Grant and others 2013).

Replanting cut forests with species that consume less 

water is a longer term solution that may be warranted in 

some cases, if it is economically feasible and does not 

adversely affect other forest management objectives, 

such as forest productivity, carbon sequestration, wildlife 

habitat, and water quality (King and others 2013). In 

snow-dominated, coniferous forests of the Western 

United States, small patch cuts and thinning have been 

shown to enhance snow accumulation by reducing snow 

interception and evaporation (Ffolliott and others 1989, 

Meiman 1987); however, these responses are transient 

as regrowing forests fill in the openings. Since much of 

the water supply in the West originates as snowmelt 

from montane ecosystems, managing subalpine forests 

to enhance snow accumulation may alleviate the effects 

of drought in this region.

As with other natural disturbances, droughts are 

difficult to prepare for because they are unpredictable. 

However, there are management options that may be 

implemented to minimize the impacts of drought on 

water quality. In more developed areas, an obvious 

measure is to limit streamwater withdrawals (Meier and 

others 2003, Webb and Nobilis 1995) and wastewater 

discharge during periods of low flow, and encourage 

reuse of treated wastewater to help reduce higher 

temperature effluent volume from entering streams 

(Kinouchi and others 2007). In forested areas, efforts 

should focus on minimizing inputs of sediments and 

nutrients into the stream. It may be beneficial to plan 

the timing of management activities so they do not 

disturb streams during low-flow periods and to avoid 

vulnerable areas during droughts. Another management 

option is to practice riparian buffer conservation and 

restoration strategies that will maintain or increase 

shading from solar radiation (Burton and Likens 1973, 

Kaushal and others 2010, Peterson and Kwak 1999, 

Swift and Baker 1973); buffering stream temperatures 

against drought becomes important because removal 

and alteration of riparian vegetation increases stream 

temperatures (Beschta and others 1987, Groom and 

others 2011), particularly following timber harvest 

(Sun and others 2004, Swift and Baker 1973, Swift 

and Messer 1971, Wooldridge and Stern 1979) and 

wildfires (Dunham and others 2007, Isaak and others 

2010). Other mitigation strategies, such as releases of 

cold water from the hypolimnions (i.e., the lower layers 

of water) of deep reservoirs, can have a significant 

cooling effect in downstream reaches (Null and others 

2013), as can discharge of municipal wastewater from 

underground pipes, which may cool streams in the 

summer (Bogan and others 2003).

Conclusions

Forest vegetation has a strong influence over the water 

balance and biogeochemical cycling processes that 

determine streamwater quality. Hence, understanding 

and predicting how drought will impact hydrological 

processes requires linking vegetation drought responses 

across fine (e.g., stomatal regulation) and coarse scales 

(e.g., community dynamics at watershed scales). Where 

impacts are large and sudden, and species diversity is 

less complex (such as widespread drought-mediated 

mountain pine beetle mortality in the Western United 
245

CHAPTER 10

Ecohydrological Implications of Drought 

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

States), assessing short- and long-term responses may 

be possible with existing models (Tague and others 

2013). However, where impacts are smaller scale and 

longer term (such as selective mortality in eastern 

U.S. forests), predicting impacts will be much more 

difficult and uncertain. If drought frequency and severity 

increases as expected (Swain and Hayhoe 2014), 

understanding the ecohydrological implications will 

become even more critical. To improve understanding, 

we recommend several areas of research need:

lBetter understanding of species’ differences in 

water use and sensitivity to drought, as well as the 

thresholds that determine species’ physiological 

capacity to survive drought.

lBetter understanding of competitive interactions 

among species, especially novel species 

combinations that might result with climate change or 

other disturbance regimes.

lBetter understanding of belowground processes (e.g., 

root dynamics, hydraulic lift, and soil water access) 

that interact with drought responses.

lImproved ability to scale from tree-level, plots, and 

small watersheds to landscape scales in order to 

better understand and predict the ecohydrological 

consequences of tree-level responses to water 

balance and streamflow dynamics.

lBetter understanding of the impacts of multiple cooccurring stressors on drought responses.

lBetter understanding of how water quality is 

influenced by subsurface flow paths and hydrological 

connectivity.

lImproved ecohydrological models that couple 

hydrologic, ecosystem, and plant physiological 

processes in a dynamic context with appropriate 

feedbacks.

lIncreased efforts to monitor the effectiveness of 

management options to mitigate droughts.

lBetter understanding of the effectiveness of postdisturbance (e.g., direct and indirect effects of 

drought) restoration for improving watershed function.

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CHAPTER 11

J.P. Prestemon is a Research Forester, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Forest Economics and Policy Research, Forestry 

Sciences Laboratory, Research Triangle Park (RTP), NC 27709.

L. Kruger is a Research Social Scientist, Alaska Native and American Indian Special 

Emphasis Program Manager, and Tribal Liaison, Pacific Northwest Research Station 

(PNW), U.S. Department of Agriculture, Forest Service, Juneau Forestry Sciences 

Laboratory, Juneau, AK 99801.

K.L. Abt is a Research Economist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), RTP, NC 27709; J.M. Bowker is a Research Social 

Scientist, U.S. Department of Agriculture, Forest Service, SRS, Athens, GA 30605; 

C. Brandeis is a Research Forester, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Knoxville, TN 37919; D.E. Calkin is a Research Forester, 

U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station 

(RMRS), Missoula, MT 59802; G.H. Donovan is a Research Forester, U.S. Department 

of Agriculture, Forest Service, Pacific Northwest Research Station (PNWRS), Portland, 

OR 97204; C. Ham is a Postdoctoral Scholar, North Carolina State University, Department 

of Forestry and Environmental Resources, Raleigh, NC 27709; T.P. Holmes is a Research 

Economist, U.S. Department of Agriculture, Forest Service, Southern Research Station 

(SRS), RTP, NC 27709; J. Kline is a Research Forester, U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station (PNWRS), Corvallis, OR 97331; 

T. Warziniack is a Research Economist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Ft. Collins, CO 80526.

Economics and Societal 

Considerations of Drought

Jeffrey P. Prestemon

Linda Kruger

contributors

Karen L. Abt, J.M. Bowker, Consuelo Brandeis,

David E. Calkin, Geoffrey H. Donovan, Charlotte Ham,

Thomas P. Holmes, Jeffrey Kline, and Travis Warziniack
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

The economic and social effects of drought are 

diverse and related to physical characteristics of 

drought, including spatial extent, severity, duration, 

and frequency that combine to determine drought’s 

overall effects on society. Most of the attention given 

to economic and social impacts of drought focuses on 

adverse consequences, but technology, public policies, 

economic activity, and social systems are largely 

adapted to the historical occurrence of drought—at least 

within the normal range. This chapter covers traditional 

impacts from drought, and also highlights possible 

adaptations, noting when adaptation may be difficult 

due to growing stresses on water resources in response 

to changes in global climate and regional demographics.

Droughts of particular combinations of severity, duration, 

and spatial extent occur at varying frequency—say, once 

in 50 years or once in 100 years. These dimensions 

can be relatively stationary in a location’s climate, 

or they can change along with climate. The multiple 

dimensions of any given drought determine its effects 

on forest and rangeland systems, on society, and on the 

economy (Hornbeck 2012, McLeman and others 2014). 

Short, local, or mild droughts may have effects that are 

imperceptible in the larger forest and rangeland sector 

because of adaptation to these variations in water status 

and flows. The historical occurrence of these “average” 

droughts have created the conditions that determined 

forest and rangeland characteristics as well as the 

land use, technology, and production patterns of the 

associated human communities.

In contrast to the adaptations that society has made 

to more typical droughts, the United States has 

experienced droughts that were extreme in one or more 

of their characteristics, with significant consequences 

for technology, policies, economic activity in watersensitive sectors, and social systems. Extreme droughts 

could occur more often or more widely in the United 

States in the future (Wuebbles and others 2014). 

Predictions from Wuebbles and others (2014) include 

significant drying in the winter and spring months in the 

North American monsoon region of the West (affecting 

mainly Arizona, New Mexico, and parts of Utah and 

Colorado). For the Southeastern United States, models 

project greater interannual variability in precipitation. 

Models project overall average drying of the continental 

United States throughout the 21st century, relative 

to 20th century conditions. Much of the projected 

drying in the Southeastern United States would occur 

through overall higher average temperatures, leading to 

increased evapotranspiration, compared to the average 

levels observed in recent history.

Wuebbles and others (2014) refer to shifts in 

distributions of precipitation and temperature—and 

hence drought—in ways that make droughts either 

longer in duration, more severe, more frequent, or, 

potentially, more widespread. The overall implication is 

that the likelihood of large magnitude droughts could 

be higher in the coming decades. As a result, we 

might expect society in general and local economies 

in particular to be challenged more regularly and more 

forcefully to adapt to these climate changes. Adaptation 

could entail the development of new and application 

of existing technologies, policies, and resource 

management approaches that can aid water-sensitive 

economic sectors—and society more broadly—to better 

withstand the negative consequences of drought.

In this chapter, we discuss how drought affects 

economic and social systems and then evaluate some 

specific effects of drought on forest and rangeland 

economies and societies. We describe a conceptual 

model of social and economic systems that defines 

where and how droughts are expected to influence 

these systems, and we examine social and economic 

resilience and the policies and programs that have been 

enacted to promote and maintain resilience. We address 

the direct effects of drought on the timber products 

sector, forest and rangeland water supplies, and the 

rangeland sector; and the indirect effects of drought on 

wildfire suppression expenditures. Finally, we examine 

nonmarket effects that include changes in recreation, 

effects on urban communities, and effects on tribal 

values and lifeways.

General Economic and 

Social Effects of Drought 

in Forests and Rangelands

An Economic and Social 

Conceptual Model of Drought

We begin by describing a conceptual model of drought 

impacts on the economy and society more broadly 

(fig. 11.1). The model shows how market and 

nonmarket goods and services are produced by an 

economy interacting with nature and how drought 

affects that production. Figure 11.1 shows that society 

has two broad classes of inputs that can be used to 

obtain desired goods and services: free inputs and 

purchased inputs. Free inputs are those that nature 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

provides (but humans can alter them subsequently 

and intervene to affect their distribution or character), 

such as water and sunshine and air. Purchased inputs, 

including capital and labor, are provisioned by society.1

Two parts of society, described as sectors, are either 

water-intensive or water-extensive.2 Each of these two 

sectors produces market and nonmarket goods and 

services. Drought alters the quantities (and qualities) 

of free inputs that are available to produce goods 

and services in both sectors, thus altering production 

possibilities and shifting supply curves in the markets 

for goods and services that depend on them. Drought 

also directly and indirectly results in costs and losses. 

Direct losses include the flows of timber, range forage, 

and water services. Direct costs include research 

(Miao and Popp 2014) and actions (e.g., construction) 

1 Capital and labor, however, embody some water themselves, but this 

does not alter the general principles laid out in this conceptual model. 

2 A water-intensive sector is one for which some form of water is 

a major input to producing an output. A water-extensive sector is 

one for which water is a minor input, perhaps only embodied in the 

capital and labor used to produce the output.

designed to reduce the extent of losses. Indirect 

losses derive from changes in ecological conditions, 

which means that drought changes the quantities of 

free inputs available to society for future production 

of goods and services. In terms of market goods and 

services that are water-intensive, possible categories 

of goods and services (there could be more) include 

timber (requiring water to grow), water for agriculture 

and communities (direct human consumption), 

developed recreation (e.g., downhill skiing, motorized 

water-based sports), and undeveloped recreation 

(e.g., cross-country skiing, nonmotorized water-based 

sports).3 Nonmarket goods and services in forests and 

rangelands that are water-intensive include ecosystem 

health, plant and animal habitat, and the general quality 

of landscape esthetics.

3 We note that the terms “water-intensive” and “water-extensive” 

are most often associated with agriculture and cropping systems, 

and thus entirely appropriate in most parts of the economy that 

we examine in this chapter. Recreation activities, on the other hand, 

might more accurately be classified as “water-dependent” 

or “nonwater-dependent.”

Labor 

Purchased inputs

Capital 

Water-intensive

sectors 

Future

ecological

conditions

Drought 

Water-extensive

sectors 

Disturbances 

Wildfire

———

Insect

and

disease

epidemic

———

Others 

Nonmarket

goods

and services 

Water for

ecosystems

———

Undeveloped

recreation

———

Other non-

 use values

Nonmarket

goods

and services

Market 

goods

and services

Timber

———

Water for

agriculture and

communities

———

Developed

recreation

———

Rangeland

forage

Free inputs 

Water Others 

———

Costs and

losses 

Social/traditional

losses

———

Human health

losses

———

Property and

resource losses

Management

costs

Market

goods

and services 

Figure 11.1—A conceptual model of an economy and society, which can produce and consume goods and 

services that are either water-intensive or water-extensive, and are affected by drought. (Colored boxes within 

encompassing squares are subcategories or examples).
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Much of the research on the economic effects of 

drought on forests and rangelands has focused on 

quantifying how drought might affect the quantities 

and market values of the goods and services shown in 

the subcategories (mustard and gray boxes) in figure 

11.1, as opposed to quantifying the effects on the 

economic value of market production and consumption 

(welfare). Our conceptual model attempts to address 

Logar and van den Bergh’s (2013) criticism that while 

there have been many attempts to quantify the “costs” 

of drought, there is no comprehensive framework for 

understanding drought’s effects on an entire economy 

or society in terms of overall economic welfare. Taking 

this broad perspective, Logar and van den Bergh (2013) 

delineate the societal effects of drought into three 

categories: (1) direct, focusing on costs and losses on 

primary producing sectors that consume and manage 

water; (2) indirect, by altering the amounts of inputs 

available for production in other sectors and by adding 

effects on disturbances such as wildfires and insect 

and disease epidemics, which themselves affect free 

inputs available to society and also induce allocation of 

purchased inputs for management; and (3) nonmarket, 

including effects on human and ecosystem health and 

social and cultural values.

Table 11.1 combines our conceptual model with the 

categorization advanced by Logar and van den Bergh 

(2013). As such, it lists several categories of goods and 

services production that could represent some of the 

subcategories (mustard and gray boxes) shown in figure 

11.1. The forest and rangeland-related market goods 

and services that are water-intensive include timber 

production, forest and rangeland water supply sources, 

and rangeland production. The nonmarket effects 

coincide with those in the water-intensive nonmarket 

goods and services box shown in figure 11.1. Table 11.1 

indicates whether the effect is direct, indirect, and/or 

nonmarket as well as the specific effects that occur and 

sometimes can be measured. In latter sections of this 

chapter, we provide some examples of effects found by 

researchers in most of these categories.

Figure 11.1 does not show many of the dynamics of 

society, specifically how drought that affects production 

of one category of good or service may change 

conditions faced in the production of another good or 

service. This chapter’s appendix provides a graphical 

description of how drought can lead to shifts in supply 

and demand, affecting equilibrium market prices and 

quantities and economic welfare (Just and others 1982) 

in water-intensive and water-extensive parts of an 

economy. The appendix also describes how neoclassical 

economics would approach quantification of the effects 

of drought on markets for goods and services produced 

by forests and rangelands.

The economic effects of drought are complex 

because of the interplay among physical, social, and 

technological responses to drought. For example, 

drought lowers output in the water-intensive sectors 

of an economy, lowering wages, the price of capital 

(interest rates), and the prices of other inputs to 

production in the water-intensive sector, such as land. 

Drought also leads to lower income through its negative 

effects on the price of capital and labor (wage rates). 

Water-extensive sectors, however, can benefit from 

drought, as the costs of labor and capital decline; 

output increases while the prices of goods in those 

sectors decrease. Nevertheless, the overall effect on 

the economy, when both water-intensive and waterextensive sectors are combined, is to reduce wages, 

interest rates, and income. New technology introduced 

to the water-intensive sector can help to mitigate the 

negative effects of drought, allowing for more efficient 

use of water for each unit of water-intensive good 

output. Technology can be introduced through efforts 

of either the private sector or the public sector. It should 

be noted that capital markets are large and fluid, so 

technology investments would put only very slight 

upward pressure on interest rates.

There are a few notable studies on describing 

societies’ responses to drought and their ability to 

mitigate negative impacts through new investments 

in technology. Banerjee and others (2013) describe 

the direct and indirect economic effects of drought 

from an ecosystems perspective, quantifying the 

“Millennium Drought” in Australia (1997–2010). The 

study focuses on quantifying impacts, not on measuring 

how economic welfare (see appendix) was affected by 

drought or how it would be in the future as a result of 

drought-related investments. It does, however, list the 

expenditures on mitigation and investments designed 

to help the region withstand future droughts with 

lower overall negative consequences for economic 

welfare. The study indicated that AU$810 million 

[US$745 million, at 2010 exchange rates (OZF-REX 

Foreign Exchange Services 2014)] was spent during the 

drought to mitigate the drought’s effects and to better 

withstand future droughts. Expenditures included those 

by the national government to build a new system of 

integrated water pipelines to more efficiently allocate 

water among agricultural and potable water users. 
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Table 11.1—Economic and societal effects of drought in forests and rangelands

Type of effect

Economic subsector 

or aspect Mechanism Effects

Direct and 

indirect

Timber products sector Reduced net volume 

growth

Lower income and employment, altered land use away from active 

forestry

Direct and 

indirect

Forest- and rangelandbased waterReduced water quantity 

and quality

Lower consumption quantities, lower water quality, shifted water 

provision timing, higher water prices and treatment costs

Indirect Wildfire management Higher wildfire activity Increased expenditures on suppression, fuels management, 

prevention, and post-fire mitigation by public and private 

landowners; greater losses of natural resources, reduced 

overall economic output in the economy due to wildfire-related 

evacuations, morbidity, and mortality

Indirect Insect and disease 

management

Increased insect and 

disease activity

Increased expenditures on monitoring, suppression, and mitigation 

by public agencies and private individuals; higher prices and lower 

overall output and spatio-temporal shifts in production of valued 

ecosystem goods and services

Indirect Rangeland sector Reduced growth of 

vegetation needed by 

livestock and wildlife

Lower livestock production, higher livestock prices; lower wildlife 

populations and therefore fewer opportunities for hunting

Indirect Urban and residential 

communities

Reduced growth to 

landscape plants, 

increased tree mortality, 

higher vulnerability to 

other disturbances

Lower property values, reduced shading resulting in higher energy 

costs, deterioration in human health and welfare 

Nonmarket Recreation sector Altered ability of forests 

and rangelands to provide 

various types of recreation 

opportunities

Shifts in spending by recreationists across time, space, type, 

and to other sectors; lower fish populations and fewer fishing 

opportunities

Nonmarket Human health Increased air particulate 

matter

Increased rates of respiratory illness-related admissions to medical 

facilities due to wind-blown dust and wildfire smoke

Nonmarket Indigenous cultures Altered provision of wateraffected ecosystem goods 

and services valued by 

indigenous cultures

Changes in the consumption and therefore the religious 

experiences available; altered rates of consumption of nontimber 

forest products

Nonmarket Wildlife habitat Reduced quantity and 

quality of habitat with 

potential endangerment 

or extinction of at-risk 

species

Increased management cost for species identified as threatened 

or endangered; potential cost of management restrictions on 

identified critical habitat; potential loss of genetic diversity
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The South Australian government also bought water 

allocations from agricultural users and used this water 

to meet critical human needs and protect important 

drought-threatened riparian habitat. Mitigation costs 

also included expenditures by the South Australian 

government to repair levees damaged by floodplain 

subsidence; modify bridges, ferry landings, and 

pipelines to low-flow conditions; repair roads damaged 

by subsidence-related slumping and collapse; build 

new monitoring systems for threatened infrastructure; 

buy new and more efficient irrigation infrastructure; 

lime drought-exposed lakebeds to help reduce droughtrelated soil acidification; revegetate drought-exposed 

lakebeds; and buy water from the water market to 

create an environmental water reserve.

The Banerjee and others (2013) study described the 

extensive efforts of Australian government entities to 

mitigate and adapt to drought in anticipation that future 

droughts might be as severe. The study provides a 

specific example of how drought affected the production 

of goods and services and stimulated actions by 

government to help mitigate it. A study by Hornbeck 

(2012) details some of the economic and social effects 

of the American Dust Bowl of the 1930s, a drought 

that had large economic and social consequences, as 

well. This study is informative of how scientists can use 

historical data to analyze drought’s economic effects. 

The study also highlights the consequences of an 

inability to anticipate or respond to severe drought: the 

region affected was not resilient enough to absorb its 

impacts without profound economic and social change. 

Hornbeck (2012) compares the long-run fates of low-, 

medium- and high-erosion counties in the affected region 

of the Great Plains. One effect was the reallocation of 

farmland from water-intensive to less water-intensive 

uses (especially from crops to pasture for livestock). 

However, the majority of the Dust Bowl’s effects in the 

agricultural sector were manifested in significant net outmigration of people from affected regions and associated 

reductions in income, rather than through reallocations 

of resources to other sectors locally such as to industry 

or through investments into new technologies. As a 

result, agricultural sector impacts are quantified through 

changes in land values, which embody the long-run 

expected value of profits from these agricultural uses. In 

the affected region, land values declined by 30 percent 

in highly eroded counties and by 17 percent in mediumeroded counties, when compared to less-eroded 

counties. Further, losses in land values in most affected 

counties persisted at least into the 1990s—60 years. 

Hornbeck (2012) emphasizes that there were spatial 

effects tied to soil losses, creating shifts in production 

from more-eroded to less-eroded counties, coupled 

with an overall decline in output and hence higher prices, 

which resulted in land value increases in the latter 

that partially compensated for the land value losses 

in the former. Maladaptation by farmers to dustbowl 

conditions and the buildup of farm debt created additional 

vulnerability of the local population. In summary, drought 

(as with any natural disaster) can result in spatial as well 

as spatio-temporal reallocations of resources within 

affected sectors, which can mitigate overall losses to the 

sector. Moreover, drought can force reallocations across 

sectors, and these effects can be quantified by changes 

in incomes generated in each sector.

Societal and Economic Resilience

The experience of the 1930s Dust Bowl in America 

highlights the importance of societal and economic 

resilience in the face of large-scale and intense 

disturbances. In general, ecosystem stress due to 

drought increases societal and economic costs (such as 

those associated with emigration from drought-stricken 

areas) and losses (such as diminished land values 

resulting from reduced productivity) (Hornbeck 2012). 

The ability to withstand and recover from ecosystem 

stresses with minimal costs and losses reflects the 

degree of societal and economic resilience (Holmes and 

others 2014). For typical drought conditions, societal 

and economic resilience may be fairly high. For example, 

when confronted with normal dry spells, homeowners 

typically increase irrigation of their lawns and other 

landscaping to a degree sufficient to alleviate vegetative 

stress. Although simple actions such as these may 

entail costs and losses, they often are relatively modest. 

Further, resilience to typical drought conditions is high 

because a low-cost technology (irrigation) is usually 

accessible due to prevailing institutions (such as 

markets and public water supplies) and prior knowledge 

is adequate. However, as the severity, duration, and 

spatial extent of drought conditions increase, routine 

mitigation actions based on prior knowledge and 

accessible technology may not always produce the 

desired effect, and communities may incur substantial 

cost plus loss amounts. In particular, societal and 

economic cost plus loss amounts may increase at an 

increasing rate with greater ecosystem stress as the 

ability to mitigate damages is reduced and resilience 

is gradually exceeded. This dynamic process is shown 

graphically in figure 11.2, where the horizontal axis 

measures any or a combination of the three dimensions 

of ecosystem stress (severity, duration, spatial extent). 

Modest cost plus loss amounts associated with typical 
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drought conditions are illustrated by points along the 

lower curve (moving along the curve from point d to a). 

The increasing slope indicates that as the capacity to 

manage greater ecosystem stress is diminishing, cost 

plus loss amounts are rapidly increasing.

Extreme levels of ecosystem stress may cause a 

dramatic upward shift in the cost-plus-loss function 

as the services provided by ecosystems degenerate 

and societal and economic resilience is exceeded 

(illustrated by the move from point a to point b on the 

upper curve in fig. 11.2). Even as the level of ecosystem 

stress subsides, communities may continue to invest in 

recovery efforts, keeping cost-plus-loss amounts on the 

upper curve in the figure (moving from point b to point 

c). However, over time, damage mitigation investments 

are diminished and communities recover, perhaps fully 

(illustrated by the recovery threshold and the move from 

c to d in the figure). When the damage to ecosystems is 

sufficiently severe, communities may fail to fully recover 

(moving from point c to point e).

Using the American Dust Bowl of the 1930s as an 

example, we see evidence of this dynamic process of 

ecological stress, catastrophic societal and economic 

loss, and (partial) recovery. Although the Great Plains 

historically experienced episodic periods of drought, an 

emerging cadre of “agricultural capitalists” willing to 

take entrepreneurial risks resulted in the Great Plowup (Worster 1986), pushing much of the southern 

Great Plains beyond an unstable cropland-grassland 

equilibrium (McLeman and others 2014). Combined 

with the severe drought of the 1930s, enormous 

societal and economic costs and losses were exacted 

(e.g., associated with the costs of human migration, 

foreclosure of homes, and lost agricultural and other 

business income). Recent evidence shows that, 

despite the economic adjustments that occurred in the 

region since the 1930s, communities that experienced 

the worst drought conditions have not fully recovered 

(Hornbeck 2012).

People generally learn from their experience and 

make efforts to find ways to adapt to threatening 

environmental conditions, which increases societal 

and economic resilience. One strategy for increasing 

resilience is to create flexible institutions that can readily 

adapt to ecosystem stresses. For example, Welsh and 

others (2013) demonstrated how formal rules (water 

laws), in combination with informal rules governing local 

use of common-pool resources, have been effective in 

adapting to drought conditions by farmers in the Western 

United States. Another strategy for increasing social 

and economic resilience is to develop new technologies 

that are less vulnerable to ecosystem stresses. Using a 

statistical model linking historical droughts with patent 

applications for drought-resistant crops, Miao and Popp 

(2014) show how historical drought events have spurred 

innovation in agricultural biotechnology.

The societal and economic resilience in forest and 

rangelands to drought depends upon efforts to 

improve the adaptive capacity of communities across 

many spatial scales. Three adaptation strategies are 

suggested. First, increased knowledge of the impacts 

of drought on trees and forests and rangeland plants 

(including a better understanding of drought-fire-pest 

interactions) may help predict the timing, location, 

and severity of ecosystem stress so that pre-emptive 

mitigating actions can be taken. A second strategy 

would be the development of drought-resistant tree 

and rangeland plant species, but these investments 

will probably only occur if drought stress is anticipated 

to substantially reduce the productivity of important 

tree crops. Third, the development of institutions, such 

as local communication networks among forest and 

rangeland stakeholders, may facilitate more rapid and 

better informed responses to emerging ecosystem 

stressors such as drought.

Programs and Policies To Address Resilience

U.S. society has faced drought conditions throughout 

its history. As the United States grew economically 

and in population, local, State, and Federal 

governments created institutions that work to reduce 

c

d

b

a

Cost + loss (dollars)

Recovery

threshold 

Catastrophic

threshold 

Ecosystem

stress

e

Figure 11.2—Economic impacts resulting from increasing 

levels of a disturbance may entail catastrophic surprises, and 

economic systems may fail to fully recover.
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the overall negative impacts from droughts and other 

natural phenomena—in short, to help to create a 

more economically and socially resilient society by 

building new economic policy infrastructure. The 

Federal Emergency Management Agency responds 

to large-scale disasters such as floods, hurricanes, 

and earthquakes to help victims. Firefighting agencies 

exist to mitigate the overall losses caused by wildfires 

on public and private lands. In the agricultural sector, 

programs have been developed—from price supports 

to crop insurance—to help farmers cope with natural 

disasters, from insect epidemics to hail storms to 

drought.

Although there are numerous programs and policies 

that address drought, drought impacts, and drought 

assistance, few of these are tailored for forest 

landowners. Livestock grazing is an exception where 

some forest and rangeland owners could receive 

assistance but only due to damage to the livestock—not 

forest products. The Agriculture Act of 20144 includes 

a provision that now allows orchardists (including 

Christmas tree farm operators) to qualify for drought 

assistance based on demonstrated damages.

Drought assistance programs are designed to relieve 

some of the financial burden to farmers, ranchers, and 

local governments that result from serious or severe 

droughts. Typically, a severe drought in a county 

will trigger an emergency notice, which will enable 

assistance to affected farmers [see USDA Farm Service 

Agency (2014) for a more complete description of the 

process]. Most of these programs are longstanding and 

have served farmers for decades (Western Drought 

Coordination Council, USDA Farm Service Agency, and 

Federal Emergency Management Agency 1999). No 

programs exist to specifically address issues of forest 

lands that are affected by drought.

Lessons from the Dust Bowl led to the creation of the 

Prairie States Forestry Project, in which the Forest 

Service, U.S. Department of Agriculture promoted 

the planting of trees along edges of croplands to 

shelter wheat fields from blowing winds and slow the 

displacement of soil. Between 1937 and 1942, when 

the project ended, the Forest Service planted nearly 220 

million trees creating 18,600 miles of windbreaks that 

occupied 238,000 acres on 30,000 farms (Munns and 

Stoeckeler 1946). It also led to the purchase of lands 

for soil conservation, many of which form the heart of 

4 Agriculture Act of 2014. P.L. 113-79 (February 7, 2014). 

designated national grasslands, which are also managed 

by the Forest Service.

Continuing Federal interest in the impacts of drought 

on communities is demonstrated by the November 

2013 Executive Order regarding preparedness for 

Climate Change (Office of the White House 2013a), 

which led to the introduction of the National Drought 

Resilience Partnership (Office of the White House 

2013b). The primary focus of these actions is on 

streamlining the provision of Federal assistance 

(and the accompanying expenditures by the Federal 

Government) to private landowners (mostly farmers, 

some ranchers, and a few Christmas tree farmers) and 

on increasing the resiliency of local communities that 

face increasing stress from drought.

There is evidence that landowners who face higher 

drought risk are more likely to participate in Federal land 

management programs that help landowners droughtproof their farms and ranches (Wallander and others 

2013). Measuring damage to a forest from drought, 

however, is problematic: there is no easily referenced 

counterfactual to show that it was actually the drought 

that reduced forest growth, and thus income, by a 

specific amount. Further, any program that reduces the 

losses experienced by individuals, through payments 

or other forms of assistance, carries with it issues of 

moral hazard (where covered individuals undertake 

greater risks as a consequence of having losses covered 

by others) and adverse selection (where individuals 

seeking coverage have above-average risk profiles).

Government programs in response to natural 

disturbances such as drought are one way in which 

resilience can be increased. Because such programs are 

not widely applied to the forest and rangeland sector, 

there is a paucity of research that elaborates drought’s 

effects on the sector. The following part of this chapter 

provides some details on how drought does affect 

water-intensive parts of the sector.

Examples of Drought 

Effects on the Forest and 

Rangeland Sectors

The above discussion provides context for a description 

of the effects of drought on specific segments of the 

forest and rangeland dependent economy and its social 

systems. In the following sections, we provide a general 

summary of the effects of droughts on the forest and 

rangeland sectors. Detailed discussions of many of these 
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effects are provided in other chapters of this report. In 

this chapter, we discuss direct, indirect, and nonmarket 

effects, as suggested in Logar and van den Bergh (2013). 

Note, however, that adding up the costs and losses 

and other effects into an overall economic impact is not 

appropriate from an economics perspective. As noted 

above, “impact” depends on the many dimensions of 

drought. Moreover, there is much that is not understood 

about how drought affects the markets (and hence 

market prices or unit values) of the goods and services 

provided by forest and rangeland ecosystems.

Little is known about how drought redistributes wealth, 

and the production and consumption of goods and 

services across space, time, or economic sectors. For 

example, the costs incurred in firefighting are gains to 

the markets for firefighting inputs (e.g., fire engines, 

airplanes, firefighting labor). Likewise, the losses 

experienced in the market for one kind of recreation 

might reappear as gains in the market for another kind 

of recreation, due to substitutions across recreation 

types. Also, because humans are adaptable, societal 

changes induced by drought often have uncertain 

overall effects on the human condition, even if we can 

measure the effects on specific segments of society. 

Our examples, while classified according to direct, 

indirect, or nonmarket effects of drought (Logar and van 

den Bergh 2013), do not always fit neatly within this 

structure. For example, trees in forests can be killed by 

drought (a direct effect), but the effects of their loss 

is manifested in part in how their loss affects timber 

products supply and demand conditions, which translate 

into economic losses in that market. Moreover, not all 

effects are precisely quantified in these examples, nor 

are all even quantifiable given existing methods or data.

Direct Effects of Drought in 

Forest and Rangeland Sectors

The timber products industry—The timber products 

industry is directly responsible for close to 1.2 million 

U.S. jobs and over 72 billion dollars in labor income. 

Based on estimates from a contribution analysis of the 

U.S. forest sector using IMPLAN (IMpact analysis for 

PLANning) software and 2012 dataset (MIG 2012), 

economic activity associated with the forest sector 

generates an additional 4 million jobs with $210 billion 

of associated labor income, constituting 2 percent of 

the U.S. economy (MIG 2012). Droughts can affect the 

forest industry through their effect on forest inventories, 

which are assumed to affect the supply function for 

stumpage. Lower inventories lead to a contraction of 

supply and a corresponding increase in the market 

price and a decrease in the quantity of production. The 

magnitude of these effects on any particular forest 

parcel depends, in part, on the severity, duration, and 

frequency of drought events; the economy-wide effects 

depend on the spatial extent of the drought. Droughts 

can negatively impact forest inventories in two ways: 

(1) by increasing mortality, and (2) by reducing growth. 

Prolonged periods of dry conditions increase the 

likelihood of forest fires; increase tree vulnerability to 

pests and diseases; and, due to water stress, can lead 

to higher mortality of saplings and seedlings (Elliott and 

Swank 1994, Hanson and Weltzin 2000).

Although droughts occur periodically across the United 

States, an increase in frequency, severity, and duration 

could significantly affect forest species composition and 

live tree volumes. Prolonged periods of water stress not 

only increase the likelihood of tree mortality and pest 

outbreaks, but they can also lead to gradual changes 

in forest composition (chapters 3, 4, and 6) (Hanson 

and Weltzin 2000). During the drought experienced in 

South Carolina in 1998–2000, State foresters reported 

regeneration success that was 5 to 20 percent below 

the historical average (Knutson and Hayes 2001). 

Faced with higher rates of artificial regeneration failure, 

forest landowners can respond by introducing droughtresistant seedlings or by using natural regeneration 

methods. Although extreme, the possibility of 

landowners changing land use also exists. Lower 

success in tree establishment could lead to an age class 

gap over a prolonged drought, which could be a factor 

contributing to the current South Carolina shortage of 

small-diameter feedstock for pulp mills, oriented strand 

board mills, and other small-timber uses (Abt and others 

2013). Pulp mills contribute a significant portion of the 

jobs in the primary wood processing industry; therefore, 

changes to the supply chain could trigger notable 

negative impacts.

The eventual decrease in forest inventories resulting 

from prolonged droughts could lead local industries 

to expand their procurement zones. However, 

transportation costs can limit a mill’s ability to increase 

its procurement area. Given that product prices are 

set at the regional or national level, higher costs of 

roundwood inputs could make the affected mills less 

competitive, resulting in mill closures. Additionally, 

extended periods of water shortages could lead to 

higher electricity costs, affecting mill operating costs. 

Mills needing water in their production process, such 

as pulp and paper mills, could have their operations 

hampered and profits reduced (English 2007).
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When viewed at a landscape scale, the effects of 

drought vary widely across stands because of the 

varying mix of species and site types. Several factors 

determine how drought affects tree growth, including 

tree species, forest composition, soil characteristics, 

and site hydrology. Studies show that pine species 

respond to water stress by reducing their growth 

rate, often by up to 30 percent (Amateis and others 

2013, Vose and Swank 1994). For hardwood species, 

resilience to drought varies from high (e.g., oaks) to low 

(e.g., tulip poplar) (Elliott and Swank 1994, Klos and 

others 2009, Orwig and Abrams 1997). During a severe 

drought, trees on mesic sites likely experience higher 

competition than trees on xeric sites more adapted to 

drier conditions, leading to more severe impacts in the 

former sites than the latter (Orwig and Abrams 1997).

Ultimately, drought’s tendency to reduce tree growth 

and increase tree mortality can potentially lead 

to job losses and income declines in rural, forestdependent communities that are more acute than in 

more diversified, urban areas. For instance, Waters 

and others (1994) evaluation of a wood supply shock 

found a significant difference in job losses between 

a metropolitan area and the surrounding rural area, 

with the rural area experiencing the highest drop in 

employment and likely negative growth given higher 

difficulty for replacement of lost jobs.

Forest droughts that lead to large disturbance events, 

such as wildfire, can produce time-dependent impacts 

in the forest sector and the local economy. For example, 

wildfires can generate positive short-term impacts in 

local communities where external resources are brought 

in to fight the fires and where post-fire timber salvage 

and burn area rehabilitation activities generate economic 

activity (Nielsen-Pincus and others 2014). For instance, 

the salvage recovery plan for the 2006 fire affecting a 

section of the Malheur National Forest in Grant County, 

Oregon, estimated employment impacts ranging from 

3 to 8 percent, depending on the volume or wood 

recovered (USDA Forest Service 2008).

Butry and others (2001) predicted that owners of 

salvaged timber would gain $33 to $61 million in 

salvage revenues following the drought-driven, halfmillion acres of wildfires in northeast Florida in May and 

June of 1998. Prestemon and others (2006) determined 

that post-wildfire salvage in the Bitterroot National 

Forest following the drought-enhanced 2000 Bitterroot 

Fire in western Montana would also generate more than 

$10 million of net benefits to the local economy, mainly 

through higher profits earned by wood processors that 

are partially offset by lower profits earned by owners 

of unburned timber in the region. Prestemon and 

Holmes (2008) estimated that post-wildfire salvage 

from the 2002 Biscuit Fire in southwest Oregon would 

generate from about $24 million at low salvage rates 

to $265 million in salvage sales at high salvage rate. 

In the long term, however, large wildfires can result in 

significant timber market losses (Prestemon and others 

2006; Prestemon and Holmes 2008), with attendant 

employment declines (Nielsen-Pincus and others 2014).

Studies on the effects of policy-related harvest 

restrictions can inform the expected spatial effects 

of long-duration and large-scale droughts. Studies by 

Guan and Munn (2000) and Wear and Murray (2004) 

documented shifts in forest industry capital investment 

and production from the Pacific Northwest to the 

Southeastern United States as the result of efforts by 

Federal decisionmakers to protect spotted owl habitat 

and other ecosystem values. Waters and others (1994) 

analysis found that such restrictions resulted in an 

estimated 22-percent employment loss in the timber 

industry of western Oregon.

Forest and rangeland based water supplies—

National forests are the single largest source of fresh 

water in the United States, accounting for 14 percent 

of all runoff. Over 900 cities rely on water originating 

from National Forest lands (Sedell and others 2000). 

These amounts vary widely by location across the 

United States. In the West, where most of the water 

originates in the mountains, half of all water originates 

in National forests. In Colorado, the percentage of water 

originating from National forests climbs to almost 70 

percent. In the Mississippi River basin, by comparison, 

only 2–5 percent of water originates on National Forest 

land (Brown and others 2008). Weidner and Todd (2011) 

show how runoff from all forests affects communities 

by weighting water yield by the population served. 

They show a high dependence on forested watersheds 

throughout the Eastern United States, Rocky 

Mountains, Cascades, and Sierra Nevada (fig. 11.3).

Forests and rangelands are critical to water flow 

regulation and groundwater recharge (chapter 10). 

These ecosystems help regulate the supply of water 

by stabilizing surface flow (i.e., reducing streamflow 

flashiness) and allowing more subsurface recharge. 

When drought happens in forest or rangeland, 

vegetation will grow more slowly; in a severe drought, 

vegetation may die. Extensive mortality may increase 
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overall streamflow; however, flows will be likely more 

variable and groundwater recharge reduced (chapter 

10). The end result is that the marginal cost of water 

(i.e., the cost of providing an additional unit of water) to 

downstream communities is higher when the forests 

and rangelands at the water supply source are under 

drought.

The increase in the marginal cost of water connects to 

three characteristics of U.S. drinking water markets. 

First, demand for water is inelastic—i.e., water 

consumers change their consumption little in response 

to water price changes, at least within the range of 

prices set by local water authorities (Dalhuisen and 

others 2003, Espey and others 1997). Research shows 

that a 10-percent increase in the marginal price (the 

price charged for an additional unit) of water is expected 

to reduce residential water demand by 3–4 percent in 

the short run and by 6 percent in the long run (Olmstead 

and Stavins 2009). Conversely, reducing water demand 

by 20 percent in the short run would require water 

prices to increase by 50 percent. Second, prices set by 

water authorities are typically below, and sometimes 

well below, the marginal costs of supplying water. This 

means that many water-providing agencies do not cover 

their production costs with the prices that are charged 

to consumers. Third, water is typically perceived to be 

a public good—it should be available to everyone and 

be clean and abundant—so efforts to recover costs 

through price increases are met with public and political 

opposition. Such price increases carry with them issues 

of legality, political constraints, and equity due to the 

larger-than-average impact to low-income households 

(Agthe and Billings 1987, Mansur and Olmstead 2012, 

Renwick and Archibald 1998).

The full economic cost of water includes costs of 

storage, transmission, and treatment, as well as 

opportunity costs associated with other uses and 

maintaining instream flows. Boland and Whittington 

(2000) note that significant efficiency and equity gains 

could be achieved by setting a single price that raises 

enough revenue to not only cover costs but provide 

enough funds to redistribute the extra revenues in 

the form of rebates back to low-income households. 

Alternatively, tier-based pricing schemes, called 

increasing block tariffs, could allow quantities deemed 

to be of subsistence value to be priced lower and larger 

quantities to be priced high enough to be responsive 

to price signals (Olmstead and others 2007). Such 

pricing policies, particularly if made flexible to respond 

to reduced water supplies, could therefore also help 

reduce consumption during times of drought. Further, 

pricing policies can provide the revenue for investments 

FIMP index value

0 – 10

11– 20

21 – 30

31 – 40

41 – 50

51 – 60

61 – 70

71 – 80

81 – 90

91 – 100

Figure 11.3—Index of forest importance (FIMP) to surface drinking water; higher values (shown in shades of blue) 

indicate greater importance (Source: Sedell and others 2000).
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that are longer run solutions to drought-induced water 

shortages, including water reservoirs and tertiary 

water treatment facilities that produce water for reuse 

following initial consumption.

The net effect of these three market characteristics—

inelastic water demand, water prices set below costs, 

and the public good view of water—is that water 

markets typically use quantity controls when shortages 

loom, despite evidence that quantity controls are 

economically inefficient compared to cost-based pricing 

policies (Brennan and others 2007, Collinge 1994, Krause 

and others 2003, Timmins 2003). Quantity controls 

can result in the amount of water demanded exceeding 

the amount of water available, especially in dry years 

when water is scarce. The larger the scarcity, the 

greater the divergence between marginal cost and price. 

For many communities, water shortages are already 

common. In 2015, for example, Governor Jerry Brown 

issued the first-ever executive order for mandatory 

water restrictions in California. The order requires a 

statewide 25-percent reduction in potable urban water 

use compared to 2013 usage. It also prohibits irrigation 

with potable water of ornamental turf on public street 

medians and outside of newly constructed homes and 

buildings without drip or microspray systems (Executive 

Department, State of California 2015). As long as 

municipal water prices lie below the true cost of supply, 

there will always be a perceived shortage among the 

86 percent of U.S. households that get their water from 

municipal water companies.

Because of public and political opposition to higher 

water prices, and given that quantity controls create 

shortages, water authorities and communities gravitate 

toward measures that do not directly involve pricing 

policies or additional quantity controls. These measures 

are directed toward water conservation. Conservation 

policies focus on technologies to improve efficiency of 

water use and on rationing outdoor water use. Lawnwatering restrictions are commonplace in droughtstricken western communities. Governments have 

mandated the use of more water-efficient technologies, 

as well: Federal law requires new toilets, the largest 

user of in-home water, to use no more than 1.6 gallons 

per flush, a 73-percent decrease from the 6 gallons 

many older toilets use. Communities also subsidize 

adoption of water-efficient lawn irrigation systems 

(City of San Diego 2014, Kjelgren and others 2000) 

and the switch from older to new water-efficient toilets 

(Bennear and others 2013). While such policies are 

more palatable to the public, the fact that households 

achieve these water use reductions through regulations 

and incentives rather than through pricing policies 

implies that these measures are economically 

suboptimal, creating losses in consumer benefits 

(economic welfare) from water consumption (Brennan 

and others 2007, Collinge 1994, Krause and others 

2003, Timmins 2003). 

Insights into the underlying causes of water disputes 

and the reason for tight water regulation emerge by 

examining not just the marginal cost of water provision 

but also by examining the value that consumers place 

on the water that they consume. Values tend to be 

higher in places where water is scarcer. In particular, 

the differences in amounts of water provisioned by 

forests, along with the types of water uses in the basin, 

affect its marginal value (the value to the consumer 

of an additional unit of water consumed). This implies 

that the effects of drought are felt economically more 

acutely during times of water scarcity, including during 

droughts. Brown (2004) reports rough estimates of 

marginal values of instream flow for water resource 

regions throughout the country (table 11.2). Although 

users should consider that these values are rough 

approximations, the values are useful for comparing 

relative values among regions, and they illustrate how 

marginal values vary due to both the quantity of water in 

the region and how the community is using that water. 

Small changes in the quantity of water in New England 

or in the Mississippi River basin, where people and 

communities consider that water is abundant, are not 

likely to have a great concern because the value of a 

lost unit of water is small. Conversely, the quantity (and 

value) of water in relatively water-scarce regions such 

as the Lower Colorado River basin can have significant 

impacts, because the value of a lost unit of water is 

considered much larger.

Effects of drought on rangeland production—

Drought in rangelands affects society and the 

economy by (1) reducing forage and water available 

for livestock grazing, and (2) by reducing overall 

vegetative land cover, which can lead to wind erosion 

and water erosion. In range management, drought 

is defined as the level of soil moisture that causes 

extreme plant stress and wilt (Carr 1966). Thus, the 

severity of drought in the rangeland sector is also 

a function of the timing of both water supply and 

plant demand. Drought also depends on temperature 

and wind through its effects on plant water demand 

and soil infiltration, soil texture, and soil depth. 

These variables are part of the Palmer (1968) Crop 
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Moisture Index, which reflects expected weekly 

evapotranspiration and plant specific needs (Meyer 

and others 1993).

A chief concern for long-term sustainability of rangeland 

is topsoil health and its ability to retain water (Mannering 

1981, Marshall 1973). Semi-arid environments often 

have insufficient vegetative cover to protect the soil 

from wind and water erosion, whose effects are 

amplified by grazing (Dankwerts and King 1984, 

Robinson 1982). On western U.S. rangelands, typical 

erosion rates can be up to 1 mm/year (Mannering 

1981), though topsoil only replenishes at a rate of less 

than 0.1 mm/year (Pimental and others 1976, 1995). 

Because animal stocking rates are generally determined 

by expected precipitation, degradation can occur quickly 

if drought occurs and grazing persists. Some of this 

erosion can be mitigated by vegetative buffers (Lee and 

others 2003, Osborne and Kovacic 1993).

The role of irrigation in rangeland and agriculture—

Although soil conservation practices and modern 

irrigation have reduced the impact of episodic droughts, 

the effects of severe drought remain a prominent 

concern in rangeland-dependent communities. 

Nationally, irrigation accounts for 37 percent of total 

freshwater withdrawals (Barber and others 2009). In 

the West where water is scarce, 90 percent of water 

consumption is for irrigated agriculture. During the 

drought of 2002, direct Federal aid in South Dakota 

reached $100 million, and the total estimated impact 

was as high as $1.4 billion (Dierson and others 2002, 

Dierson and Taylor 2003). That same year, impacts to 

Missouri’s agricultural sector were $251 million (Ding 

and others 2010).

Quantifying the economic effects of drought on 

crop and livestock production requires an accurate 

description of water markets. Water demand 

characterization requires measurement of the benefits 

of water used in the production of market goods and 

services, including for irrigation. Prices in the water 

sector are quantified by measuring the shadow price 

of water, that is, the change in net profits given a small 

change in water use by the water demanding goods 

and services market. Measuring the shadow price of 

water is done frequently in production economics with 

mathematical programming (Scheierling and others 

2006), field experiments, and hedonic methods (Colby 

1989, Young 2005).

Increasing water scarcity has led farmers to invest 

in water-saving techniques such as improved drip 

irrigation systems. In 1984, 71 percent of irrigation 

in the West was done with inefficient gravity-fed 

furrows. By 2008, that percentage had fallen to 48 

percent; pressurized sprinkler systems represented 52 

percent of irrigation water. This technology adoption 

in irrigation explains how, although total irrigated acres 

increased in the West by 2.1 million acres from 2004 

to 2008, the water used in irrigation decreased by 

100,000 acre-feet during that period (Schaible and 

Aillery 2012). Decreased use of water in agriculture, 

and the associated decrease in runoff of fertilizers 

and pesticides, has the added benefit of increasing 

downstream water quality (Warziniack 2014).

Table 11.2—Marginal value of instream flow by water 

resource region (WRR) (year 2003 dollars per acre-foot 

per year)

Water resource region Off-stream Hydroelectric Instream

New England 0.62 1.73 5.01

Mid-Atlantic 3.09 1.03 4.91

South-Atlantic-Gulf 1.87 1.56 5.03

Great Lakes 6.3 5.54 4.88

Ohio 3.17 0.71 4.96

Tennessee 3.18 7.02 5.16

Upper Mississippi 4.08 0.72 4.98

Lower Mississippi 0.4 0.35 4.75

Souris-Red-Rainy 0.29 0.26 6.45

Missouri 20.99 4.29 16.82

Arkansas-White-Red 4.08 2.05 7.7

Texas-Gulf 13.25 0.54 7.49

Rio Grande 16.54 1.42 28.26

Upper Colorado 13.32 17.79 26.32

Lower Colorado 25.56 16.19 42.46

Great Basin 36.08 1.31 16.52

Pacific Northwest 1.45 9.44 9.34

California 10.95 10.64 23.07

Source: Brown (2004).
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In spite of its widespread use in the water-scarce 

Western United States, most studies show that 

irrigation is an inefficient, low-value use of water, and 

the price of water charged to farmers is so low that it 

rarely factors into on-farm production decisions. The 

average price of an acre-foot of water in the West 

($24 or $66 per acre of cropland) is lower than the cost 

of power to pump it out of the ground and distribute 

it through a sprinkler system ($76 for groundwater 

and $38 for surface water). Because of the low price 

charged for water for agriculture, water used for 

irrigation is often leased during wet years, when 

supply is plentiful and demand for other uses is low 

(Brown 2006).

Societal structural barriers exist to achieving more 

economically efficient water allocation in forest and 

rangeland systems in the United States. Economically 

efficient allocation of water would equate the value of 

a unit of water across uses, including instream uses 

for ecological sustainability. In reality, value between 

uses diverges substantially for two reasons. First, in the 

West, the doctrine of prior appropriation determines 

allocations, and while water rights are transferable, 

market transactions are limited by geographic structure 

of rivers and water pathways, costs of storing and 

transferring water, and impacts to other water users 

along the waterway. Second, most water use is highly 

subsidized, so when prices are charged, they rarely 

reflect the full cost of provision. Water rights that are 

leased or sold in markets are characterized by seniority 

and location, making each water right a unique good 

with high transaction costs.

Brown (2006) reviews 1,380 transactions in Western 

water markets between 1990 and 2003. He finds that 

water markets are far from competitive. Only three 

States (California, Colorado, and Texas) saw significant 

transactions during the period studied, representing 

two-thirds of all water transfers. Over half the sales 

were to municipal areas to satisfy the needs of fast 

growing cities, such as those along the Colorado Front 

Range, near Las Vegas, and near Reno. As well, over 

half of the sellers were irrigators. The median lease 

price for municipal uses was $56 per megaliter (ML, 1 

million liters), or 4.6 times that paid for irrigation ($12/

ML). The median sale prices were $2,120/ML for 

municipal uses and $1,917/ML for irrigation. Despite 

numerous studies suggesting agriculture-to-urban 

transfer of water rights would be welfare improving, 

few transfers have actually taken place (Brewer and 

others 2007, Brown 2006, Howe 1997). Reasons for 

the limited number of transfers include lack of markets, 

legal restrictions, and reluctance to further constrain 

local agriculture.

Research also indicates that government efforts to 

achieve ecological goals through water allocation and 

purchase decisions can have effects that create new 

conflicts while moving water allocations toward greater 

equity. Eleven percent of water rights purchases studied 

in Brown (2006) were for environmental purposes, sold 

for a median price of $706/ML. Most of these (105 of 

the 113) purchases were by government entities for 

the protection of aquatic species. And while regulations 

such as the Endangered Species Act5 may require 

minimum flows for species preservation, instream 

water is also valued for its contribution to recreation and 

for riparian and wetland restoration. In a study of 67 river 

basins in the United States with significant irrigation, the 

marginal value of instream water for fishing exceeded 

that for irrigation in 51 basins (Hansen and Hallam 

1991). Loomis and others (2000) found the benefits 

of purchasing water leases and farmland easements 

to restore a section of the Platte River near Denver 

outweighed the costs.

Indirect Effects of Drought in Forest and Rangeland 

Sectors: Federal Wildfire Expenditures

Forest and rangeland management is significantly 

affected by drought, and perhaps most acutely in 

its management of wildfires. Longstanding western 

drought is a likely cause of recent increased wildfire 

activity in forests and rangelands in much of the 

Western United States (Westerling and others 2003). 

Aside from sometimes justified increased investments 

to manage landscapes to be more resilient to wildfire 

(USDA Forest Service 2000), greater wildfire activity 

generally leads to increased expenditures needed for 

suppressing fires (Prestemon and others 2008).

To characterize the importance of the fire-suppression 

effect of drought in forests and rangelands, we 

compared Forest Service regional fire suppression 

average expenditures during drought years with average 

expenditures during nondrought years. The Palmer 

Hydrological Drought Index (PHDI) was selected as a 

“real time” measure of drought (Alley 1984) because 

it captures persistent, long-term effects that impact 

surface and subsurface water supply levels (Heim 

2002). The index is available from the National Oceanic 

5 Endangered Species Act of 1973. P.L. 93-205. (December 28, 

1973), as amended through P.L. 107–136 (January 24, 2002). 16 

U.S.C. 1531.
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and Atmospheric Administration (NOAA) (2014) and 

is created using temperature and precipitation data 

by climatic divisions; however, these exclude Hawaii 

and Alaska. The index is based on the identification of 

an existing water budget needed to maintain current 

production levels of ecosystem services in a place and 

time. The index represents the difference between 

the amount of water required to support the existing 

water requirement and the amount of actual water 

available. When the difference is negative, the location 

is considered to be experiencing drought while positive 

differences indicate the location is wet.

An average PHDI for each Forest Service region (fig. 

11.4) for each month was created by overlaying the 

regions and the climate divisions and weighting the 

contribution of each climate division based on the 

proportion of Forest Service land area to obtain the 

agency’s regional averages. Next, a fire season PHDI 

for each region was created by averaging the monthly 

regional PHDI averages over the months that are 

considered the fire season for each region (see Calkin 

and others 2005, table 11.3). Then, aggregate measures 

were created by averaging the regional fire season 

PHDIs for the western Regions (including Regions 1 

through 6), the eastern Regions (including Regions 8 

and 9), and in total [including all Regions 1 through 9, 

but excluding Region 10 (Alaska)]. The Forest Service 

regional suppression expenditure data were obtained 

by the authors from the Washington Office of Fire and 

Aviation Management and are calculated based on the 

Federal fiscal year (October 1 to September 30). All 

regions’ fire seasons are within a single year, except 

for Region 5, which has a fire season that does not fall 

within the same fiscal year; to accommodate this fiscal 

year-spanning season for Region 5, we included the 

previous October PHDI in the average even though that 

October was technically in the previous fire season.

In table 11.3, we provide a comparison of Forest Service 

wildland suppression expenditures during drought 

conditions (where PHDI is negative) with those during 

nondrought conditions (where PHDI is positive) over 

the fiscal years 1995–2013 by Forest Service region, 

by West/East aggregates, and in total (millions of 

2014 dollars). All regions and regional aggregates had 

statistically significantly higher wildland fire suppression 

expenditures in drought years than in nondrought 

years. Over the timeframe of this analysis, suppression 

expenditures during drought years were double those 

in nondrought years in total and across both the West 

and East aggregates, as well as in Regions 3, 5, 6, and 

9. The factor column shows the multiple that drought 

expenditures were over nondrought expenditures 

(e.g., “2” means that expenditures in drought years 

were double the expenditures in nondrought years). 

Expenditures were triple in Regions 4 and 8, quadruple 

in Region 2, and quintuple in Region 1. Average 

expenditures from 1995 to 2013 are also reported in 

table 11.3, as well as average expenditures during years 

of drought and nondrought years, from which the factor 

of the relationship between average expenditures during 

drought versus nondrought years were calculated. 

All Forest Service regions had statistically different 

expenditures during drought versus nondrought years 

based on t-tests (p-values reported in table 11.3).

While decisions on fire suppression spending do not 

necessarily have to be based on damage mitigation 

alone, so that increased wildfire due to drought 

does not require greater suppression spending 

(Donovan and Brown 2005), they do demonstrate 

historical correlations with drought that are robust and 

informative. So while this analysis is not necessarily 

predictive of future experiences with suppression 

spending, evidence suggests that decisions by 

governments to invest more in protection as a result of 

greater drought-related wildfire disturbances are likely. 

The implications here are clear: markets for wildfire 

suppression services such as aerial fire suppression 

and the market for wildfire-related labor are benefited 

by increased severity, spatial extent, frequency, and 

duration of droughts. With increased drought resulting 

from climate change (Wuebbles and others 2014), 

these markets would therefore likely experience 

welfare gains (appendix), even while wildfires deliver Figure 11.4—National Forest Service Regions. Note: there is no 

Region 7.
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higher fire-related damages due to affected forests and 

rangelands and associated communities.

Nonmarket Effects of Drought in the 

Forest and Rangeland Sectors

Recreation impacts—Recreation services in forests 

and rangelands are provided by a combination of nature, 

labor, and capital. While service markets exist, such as 

the market for developed downhill skiing services (i.e., 

offering a place, the snow, the ski lifts, and associated 

built facilities), the majority of research in the economics 

of recreation has focused on recreation activities—

specifically, valuing those activities and understanding 

what factors affect the benefits that the activities 

provide to those who participate in them. So discussion 

on recreation in this section is limited to describing how 

drought could affect recreation activities.

A limited amount of research has shown that drought 

conditions affect outdoor recreation activities in the 

United States, generally, and in forests and rangelands 

in particular. Notable studies include those by Creel and 

Loomis (1992), who quantified the overall recreational 

benefits of water; Ward and others (1996), who focused 

in particular on the connections between drought and 

water recreation, with evidence from California; and 

Thomas and Wilhelmi (2013), who examined all forms 

of recreation and tourism in southwestern Colorado. 

Drought can lower reservoir levels and therefore reduce 

the availability of water-based activities (such as fishing 

and recreational boating) and lakeside activities (such as 

swimming and camping). In the Ward and others (1996) 

study, the “use-value” marginal value estimates of 

water per acre-foot in reservoirs of California varied from 

$6 to $700/year. This range covers previous estimates 

for wetland areas in the San Joaquin Valley of California 

quantified by Creel and Loomis (1972), $348/acre-foot/

year.

Thomas and Wilhelmi (2013), using a limited-resource 

survey and two focus groups, identified how drought 

in southwest Colorado affects the recreation sector. 

One finding was that drought affects winter recreation 

differently than summer recreation, due to dependence 

especially on snow in the winter (i.e., downhill and 

cross-country skiing, snowboarding, and snowmobiling) 

and on water and a wide variety of other resource 

values provided in the summer (i.e., boating/rafting/

Table 11.3—Fiscal year suppression expenditures (2014 dollars in millions) on USDA Forest Service lands in the 

United States, by region, regional aggregate, and in total according to drought status (1995–2013)

Region Factora

Average

expenditures

Average 

expenditures 

during drought

Average 

expenditures not 

during drought

t-test 

p-value Fire season

R1 5 92 139 28 0.01 June, July, Aug.

R2 4 39 57 14 0.01 June, July, Aug., Sept.

R3 2 95 107 59 0.02 May, June, July

R4 3 85 127 38 0.01 June, July, Aug., Sept.

R5 2 272 340 178 0.02 Oct. (-1), July, Aug., Sept.

R6 2 136 181 95 0.02 June, July, Aug.

R8 3 41 57 22 0.01 March, April, May, June

R9 2 13 16 9 0.04 March, April, May

West (R1-6) 2 718 959 386 0.01

East (R8-9) 2 53 63 26 0.01

Total (R1-9) 2 771 831 450 0.04

a Factor = Average expenditures during drought/average expenditures not during drought.

Note: there is no Region 7.
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canoeing, fishing, hiking, camping, horseback riding, 

wildlife viewing, off-road vehicle driving). In the winter, 

lower snowfall from drought generally reduces the 

economic net benefits in the recreation sector. In 

summer, drought can worsen water-based activities but 

conceivably can increase the provision of some dryland 

activities such as hiking and camping, owing to the 

greater number of rain-free days. In all times of the year, 

drought can alter animal migration patterns and thereby 

affect hunting and wildlife viewing. Drought may also 

have effects on insect and disease outbreaks in forests, 

affecting aesthetic values, and it can yield dry vegetation 

that is more prone to large and intense wildfires, which 

can force campground and forest closures, reducing 

summer recreational uses. Drought-induced reduction in 

tourism results in fewer jobs and lower economic output 

compared to nondrought periods.

While targeted studies have examined drought effects 

on recreation at fine spatial scales or for particular 

resources, recreation research from the most recent 

Resources Planning Act Assessment (Bowker and 

others 2012) indicates that prolonged drought in parts 

of the United States can have effects on a broad set of 

recreation activities. Bowker and others (2012) projected 

the probability of an individual’s participation in various 

recreation activities as a function of socio-demographic 

and climate variables (including precipitation, potential 

evapotranspiration, and temperature). From their 

analysis, they concluded that: (1) in climate scenarios 

involving drier overall conditions in forests and 

rangelands, snow-dependent recreation activities 

are the most negatively affected of any category of 

recreation; and (2) there are some kinds of recreation 

activities that benefit from drier conditions, including 

nature center and historic site visitation, motorized offroad vehicle use, and adult equestrian participation.

Despite previous research efforts, a thorough 

understanding of the effects of a drought on recreation 

is lacking, which hampers our ability to fully characterize 

the overall effects of drought on this sector. Data are 

needed that can connect the levels of specific types 

of recreation at specific locations to the weather or 

climate conditions existing at the time and place of the 

specific activity. Although Bowker and others (2012) and 

other studies have advanced understanding of a few 

key relationships, a comprehensive understanding of 

drought effects across the entire spectrum of recreation 

activities would require additional recreation (panel) data. 

Panel data would quantify how drought in one time and 

place affects each specific type of recreation activity 

occurring in that same time and place, as well as how it 

affects participation in all activities in other locations and 

in future time periods. As Thomas and Wilhelmi (2013) 

and Thomas and others (2013) emphasize, estimates of 

recreation impacts from drought would be overestimated 

if these within- and across-activity spatio-temporal 

substitution opportunities available to recreationists are 

not accounted for.

Urban and residential communities—Most studies 

of the effects of water stress and high temperatures 

on tree and forest mortality have been designed to 

detect changes in background mortality and large scale 

die-off events in wildland forest areas (Allen and others 

2010). Although drought-induced forest mortality in 

wildlands can alter the supply of ecosystem goods 

and services, large magnitude drought events can 

also alter the benefits experienced by people where 

most live and work—in cities. Evidence suggests that 

trees in cities are significantly affected by drought, 

and their responses lead to changes in the services 

that city trees provide. For example, the drought and 

heat event associated with the American Dust Bowl 

drought in 1934 killed approximately 20 percent of 

the trees in Manhattan, KS, and damaged another 

30 percent (Stiles and Melchers 1935). Although the 

pre-drought tree density varied considerably across the 

urban forest, as many as 235 trees per city block were 

recorded in residential areas, so the overall number of 

affected trees was large. The city and property owners 

therefore incurred considerable expenses to remove and 

eventually replace many of the affected trees.

To our knowledge, the economic consequences of tree 

mortality due to drought and high temperatures have 

not been quantified. However, there is a growing body 

of research documenting how trees provide a variety 

of benefits to homeowners and residential and urban 

communities. Trees have been shown to enhance 

property values (Anderson and Cordell 1988; Donovan 

and Butry 2010, 2011) and lower crime rates in urban 

areas (Donovan and Prestemon 2012, Kuo and Sullivan 

2001, Troy and others 2012). Tree shading has been 

found to reduce energy use in homes (Akbari and 

others 1997, Donovan and Butry 2009, McPherson 

and Simpson 2003), in this way mitigating some of the 

negative effects of the heat and sun associated with 

many droughts. Urban forests also have been shown 

to benefit stormwater management in built-up areas, 

reducing flooding and water-handling costs for cities and 

their residents (Sanders 1986, Wang and others 2008, 

Xiao and others 1998).
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With respect to tree mortality, the loss of trees is 

connected to worsened human and urban environments 

and lowered house values. Recent research links tree 

mortality caused by pests to adverse public health 

outcomes (Donovan and others 2011, 2013; Lovasi and 

others 2008; Nowak and others 2014). Research also 

has documented how tree mortality resulting from other 

natural disturbances in residential forests is capitalized 

into property values. Losses in values are in the range 

of 1 to 10 percent of a home’s value (Holmes and 

others 2010, Kovacs and others 2011). We anticipate 

that similar losses in value would result from droughtinduced tree mortality.

Homeowners living within forests are often willing to 

incur expenses, such as irrigation, to help protect tree 

health, although such options may be limited when 

municipal water restrictions are enforced. Trees killed 

by drought conditions are generally removed when they 

threaten the safety of homeowners or other residents. 

Hazard trees that are removed may be replaced with 

different species that may be more drought resistant, 

although much remains to be learned about the 

selection of trees that improve the resilience of urban 

trees to drought conditions (Clark and Kjelgren 1990).

Although it is not currently known whether water 

deficits are more severe in urban trees than in trees 

growing in rural areas, there is growing concern that 

urban land uses create novel stresses on urban forests 

(Carreiro and Tripler 2005). Given the recognized high 

economic value of residential forests across the urbanrural gradient, greater attention to policies and potential 

technologies that improve urban forest resilience in the 

face of drought could yield positive net benefits.

Impacts of Drought on Tribal Values and Lifeways

There are 566 federally recognized tribes and more than 

34 State-recognized tribes in the United States. These 

tribes, distributed across both drought-prone and mesic 

ecosystems throughout the country, are diverse in their 

cultural practices, the structure of their tribal economies, 

and their degree of dependence on forest and rangeland 

ecosystems. Hence, the effects of drought on tribal 

values and lifeways (defined here as the customs and 

practices of tribal societies) vary across all of these 

dimensions. In some places and for some peoples, the 

effects of drought are compounded and complicated 

by ongoing social, economic, and rapid ecosystem 

changes, making scientific attribution of the effects of 

drought alone difficult. Effects of drought, however, 

would likely be more acute for local populations whose 

livelihoods are most tightly connected to natural 

resources. For example, American Indians and Alaska 

Natives (AIAN) are particularly vulnerable because of 

their resource-based economic activities and spiritual 

and cultural values (Wildcat 2013).

General impacts of drought on tribes in the United 

States—As for all potentially drought-affected sectors 

or parts of an economy or community, it is important 

to identify risk, potential impacts, and vulnerabilities, 

especially related to water supply and water rights. 

Ongoing drought in the Western United States, where 

most tribal lands exist, is expected to continue to affect 

tribal health, culture, economies, and infrastructure. 

Competing demands for dwindling water resources 

challenge Federal trust responsibilities. Complicating 

factors, warming streams and hydrologic cycle 

changes affect fish populations important to tribal diets 

and ceremonies. Because of their natural resource 

dependence for income, employment, and cultural 

practices, many tribes are also vulnerable to higher rates 

of forest and rangeland disturbances, including invasive 

species spread, increased occurrences of epidemic 

pest populations and their associated damages, and 

wildfires. These disturbances increase forest mortality 

and reduce the quality and quantity of forest products 

valued by tribes (Voggesser and others 2013). Tribal 

elders have voiced concern for “bio-cultural” loss, 

defined as “the intimate innate connection that exists 

between tribal language, customs, and traditions and 

the biological health of their land, resources, and its 

inhabitants” (Collins and others 2010).

In order to successfully address environmental change, 

many scholars, tribal leaders, and agencies charged with 

consulting with tribes are calling for the incorporation of 

traditional ecological knowledge (TEK) in monitoring and 

assessing environmental change impacts, developing 

tribal community adaptation plans, and for “respectful 

partnering and collaboration of indigenous peoples and 

their communities with nonindigenous governments 

and organizations” (Wildcat 2013). Incorporating 

traditional values and TEK in these ways can support the 

perpetuation of traditional lifeways.

Relatedly, a workshop on climate change and drought 

on western native lands (Collins and others 2010) 

identified the ways that data and institutions could 

be marshalled to help mitigate overall impacts. The 

workshop participants concluded that inadequate 

communication of current conditions and potential 

impacts to tribes has resulted in a lack of attention to 
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drought-related issues. Participants called for increasing 

documentation of impacts and data collection and 

monitoring in an effort to build awareness and bring 

attention to potential impacts and related needs. 

Participants also identified critical needs, such as for:

“...reliable resources to support tribal drought 

planning and response; methods for integrating 

local and traditional knowledge into environmental 

monitoring and planning; education and outreach 

programs about drought, climate change, and 

water scarcity; and technical training opportunities 

related to climate monitoring for tribal resource 

managers...” (Ferguson and others 2011).

Finally, workshop participants identified four priorities 

for developing a regional drought early warning system: 

(1) integrate tribal observations and data into national 

and State monitoring efforts; (2) ensure maintenance 

and sustainability of existing observation networks; (3) 

facilitate data sharing and access; and (4) explore ways 

to use existing data and provide technical training for 

tribal staff (Ferguson and others 2011).

The Forest Service notes that this call for collaboration 

is now a catalyst to developing tools and sponsoring 

webinars and face-to-face training in climate adaptation 

planning and strategies, which make partnerships 

through the Tribal Climate Change Project (University 

of Oregon 2015) mutually beneficial to all involved. 

Partners include the Institute for Tribal Environmental 

Professionals at Northern Arizona University, the Pacific 

Northwest Tribal Climate Change Network at the 

University of Oregon, and the Forest Service Pacific 

Northwest Research Station.

The National Wildlife Federation suggests that drought 

may result in the most pervasive climate-related 

changes to impact tribes (Curry and others 2011). It 

could be the most pervasive because water is the 

foundation for tribal lifeways, economies, subsistence, 

and treaty rights (Curry and others 2011). In addition, 

water is considered by many as a traditional food (Lynn 

and others 2012). Cozzetto and others (2013) synthesize 

this argument (italics in original):

“Water is sacred. This is tradition. In contrast to the 

non-tribal utilitarian view of water, Native Americans 

revere water and water is life. It is integral to many 

Native American practices such as purification 

and blessing rituals and is used to acknowledge 

all relations and to establish connection to Mother 

Earth and Father Sky. Water is a holistic and 

integrating component connecting continents, 

humans, animals, and plants through a continuous 

cycle of liquid, solid, and vapor states. Without 

water, life would not exist as we know it. Water 

is the one thing we all need, all of us, all of life. 

As Native Americans, we honor and respect the 

tradition of water and must protect it always.” 

Indigenous peoples depend on a wide variety of native 

species for food, medicine, ceremonies, community, 

and economic health. “The indigenous relationship 

between food and people is intimately tied to the 

cultural, physical, emotional, psychological, and spiritual 

health of tribal communities” (Lynn and others 2013). 

Drought tends to reduce the production of traditional 

foods, and this reduction is compounded by ongoing 

background effects of disease, pollution, invasive 

species, and unsustainable resource management 

activities. Declining ability to access and harvest 

traditional foods is leading to increasing health problems 

including obesity, diabetes, heart disease, and cancer 

(Lynn and others 2013). Disruption in resource 

availability and drought-associated changes in species 

composition could therefore negatively impact tribal 

subsistence-food production, health, culture, economic 

activities, and lifeways.

Specific impacts of drought on tribes in the United 

States—Drought has varying effects according 

to the location of the tribe, which is connected to 

biophysical, cultural, and economic contexts. Drought 

in the Southwestern United States has effects on 

livestock, agriculture, water supply, water rights, soil 

quality, and aquatic species (Cozzetto and others 2013), 

requiring tribal peoples to use marginal resources 

and travel farther to haul water. Cozzetto and others 

(2013) identified five categories of tribal water 

resources impacts; these include impacts on: (1) water 

supply and management (including water sources 

and infrastructure); (2) aquatic species important for 

culture and subsistence; (3) ranching and agriculture, 

particularly from climate extremes (e.g., droughts, 

floods); (4) tribal sovereignty and rights associated with 

water resources, fishing, hunting, and gathering; and 

(5) soil quality (e.g., from coastal and riverine erosion 

prompting tribal relocation or from drought-related land 

degradation).

In a drought preparedness workshop in Flagstaff, AZ, 

in 2010 for tribes in the Four Corners Region, current 

drought effects and vulnerabilities were catalogued: 
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multiple impacts from seasonal dust storms; shifting 

plant ranges and absence of or reduction in ceremonial 

and medicinal plants; drying of springs and declines in 

surface water supplies; livestock reductions tied to poor 

range conditions; inadequate water infrastructure for the 

growing water demand in the region; bureaucratic and 

institutional conflict; and a rising degree of economic, 

social, and cultural vulnerability due to changing society 

and climate (Ferguson and others 2011). Workshop 

participants acknowledged impacts from complacency 

and a lack of respect for the precious nature of water 

and the threat of drought.

Many of the listed impacts of droughts on tribes in the 

United States are illustrated by specific experiences. For 

example, a multiyear drought in the early 2000s forced 

the Hualapai Tribe in Arizona to sell cattle because 

of high water and feed costs, resulting in increased 

wildfires, road closures associated with wildfires, 

increased invasive species and wildlife diseases, 

lost wetlands, wind erosion, and visibility problems 

(Cozzetto and others 2013). In the Pacific West, drought 

has reduced forage quantity (Bender and others 2011). 

Changes in ecosystem water status in the Midwest, 

Northeast, and South have reduced forest nut crop 

abundance and have stressed ecosystems used by 

tribes (McKenney-Easterling and others 2000, Speer 

and others 2009, Voggesser and others 2013).

The effects of drought are recognized to be greatest 

in locations of the United States where water is 

both scarce and key to tribal livelihoods. Reservoirs, 

hydropower facilities, irrigated agriculture, municipal 

water systems, tribal water rights, freshwater aquatic 

systems, and water-intensive recreation are all impacted 

by drought conditions (Dalton and others 2013). Solar 

and wind facilities, more common in the water-scarce 

Western United States, also require water for periodic 

cleaning of solar-collection and reflection surfaces 

and, for thermal power plants, turning steam turbines 

(Solar Energy Industries Association 2014); the water 

necessary to successfully support these alternative 

energy facilities may be lacking, especially during 

drought (Collins and others 2010).

But drought’s effects, perhaps manageable for 

short-duration, low-severity, or moderate spatialscale droughts, require addressing multiple tradeoffs and longstanding water use allocation disputes 

when droughts increase in magnitude along these 

dimensions. Competition for limited water resources 

pits the interests and needs of hydropower, solar 

power, irrigation, drinking water, aquatic systems, 

and water-intensive recreation. In the Northwest, for 

example, many water supplies are overallocated (more 

demand than water available), leading to conflicts 

among potential users and uses (Curry and others 

2011). And in spite of the tribes’ historical, treaty-based 

senior water-rights status, which gives them priority 

under normal (nondrought) conditions, when water is 

scarce, existing laws often mean that nontribe water 

consumers are given water allocation priority in order to 

provide water to livestock and for household (domestic) 

uses. Moreover, tribes’ treaty-based seniority is often in 

legal dispute. Competition for water, the issue of treaty 

water rights, and how to interpret those rights in light of 

changing conditions, will become increasingly important 

and contentious (Lynn and others 2013).

Also, in the case of large-magnitude and persistent 

drought, fisheries disputes emerge between recreational 

fishers and native subsistence fishers. In the midst 

of drought and ongoing climate change, changes 

in streamflow and temperature threaten aquatic 

ecosystems, especially the spawning and migration of 

salmon and trout species. Cascading effects of limited 

water will impact recreational, commercial, and tribal 

fisherman. In Alaska, Alaska Natives and rural residents 

participate in a subsistence fishery that may experience 

catch limits and season reductions.

Just as for nontribal communities, indirect and direct 

effects of drought can result in health and economic 

losses. Because droughts increase wildfire activity, 

tribes in fire-prone landscapes may experience 

economic effects when wildfires force the closure of 

roads and recreation areas that they are dependent 

upon for their livelihood (Dalton and others 2013). 

Wildfire smoke and particulate matter is also a health 

concern in many tribal areas. In addition, drought is 

associated with food insecurity, especially for the 

poor and those living in rural communities, due to 

drought’s direct effects on agricultural production. In 

some parts of the country, particularly the Colorado 

Plateau, drought impacts are compounded by warming 

temperatures that increase evapotranspiration rates, 

reduce soil moisture, and increase stress on vegetation 

and water resources, creating circumstances for 

increased soil erosion (Ferguson and others 2011). 

And, as highlighted in another section of this chapter, 

drought affects forest- and rangeland-based water 

production, which in extreme cases can limit access 

to clean and affordable drinking water (Ferguson and 

others 2011).
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Conclusions

The U.S. economy and society more broadly is adapted 

to the rhythm of drought, in terms of its severity, 

duration, spatial extent, frequency, and seasonality. 

The effects of moderate, short-duration, and spatially 

limited droughts are easily handled by our economy 

through adjustments in inputs and outputs without 

altering our technologies, local economies, locations 

of human populations, or traditions. Intense, longduration, and spatially expansive droughts that America 

has experienced, on the other hand, affect all of these 

components of society in sometimes profound ways, 

with impacts that can span decades.

While economists have a basic understanding of how 

drought affects forest and rangeland systems, we 

still know very little about how drought affects the 

economic and social systems of the United States (table 

11.4). For example, although we have fairly precise 

measures of droughts’ effects on Federal wildfire 

management expenditures, we know little about the 

scale of these impacts on State and local firefighting 

expenditures. Long-term or persistent droughts or 

indeed climate change related dryness, would further 

affect the required size of the overall firefighting 

capacity of all agencies of governments, for which we 

know very little. 

Likewise, although we understand some of the benefits 

of trees in urban settings, we know less about how 

drought affects the production of those benefits 

in these same urban settings because effects are 

transmitted through loss of trees, and there is much 

to be learned about how drought affects mortality of 

the urban trees. Water effects of drought seem clearly 

quantified, yet less is understood about the long-term 

economic effects of water mining (the permanent 

draw-down of water supplies residing underground). 

While researchers have quantified some effects of 

drought on recreation-based goods and services, very 

little is known about how the various types of recreation 

activities substitute and complement each other across 

space and time, or how other modes of consumption 

outside of the recreation sector can mitigate some of 

the losses experienced by specific types of recreation. 

In the timber products sector, silviculturists have 

a general understanding of the effects of drought 

on growth and yield. However, while the effects of 

drought on growth and yield in particular forest types 

in particular places might be acute, economies are 

global: substitution possibilities for consumers of forest 

products and across producing regions reduce some of 

the negative impacts felt in the specific location of the 

drought, reducing net overall economic losses.

Finally, when describing the economic and social 

impacts of drought, all such effects need to be scaled 

by the size of the forest and rangeland based economy, 

the national economy, and the sizes of local and national 

human populations. Although smaller economies may 

be more greatly affected in terms of impacts on sectors, 

larger economies and more numerous populations are 

likely to experience greater overall impacts of drought 

due to potentially larger spatial coverage and because 

these economies are often less diverse economically 

(have fewer sectors), limiting substitution opportunities 

among labor, capital, and goods markets that can 

mitigate its most acute impacts.

Although this chapter describes some of the economic 

and social effects of drought in forest and rangelands 

(table 11.4), our examples did not address how a 

greater amount of sun (lower cloud cover), which is 

correlated with drought, can itself have separate effects 

on economies and societies and alter the suitability of 

habitats directly affected by sunshine. We also have 

sidestepped discussion of how forests and rangelands 

themselves might help to mitigate some of the negative 

effects of drought: trees provide shade that reduces 

energy use and water demands in urban settings; they 

provide shade for precipitation that is stored in the form 

of snow in high elevations; and they provide a refuge 

for hikers and campers seeking to escape high heat 

and sun associated with drought. With further study, 

these mitigating effects could be better quantified, 

and the missing pieces can be filled in. This additional 

study could help wildland managers and policymakers 

design new and adapt existing approaches to reducing 

the overall negative impacts of drought. The urgency 

of such policy and managerial responses could 

become greater as climate change alters the severity, 

duration, spatial extents, and frequencies of droughts 

in forests and rangelands, and as economies grow and 

populations grow into the future.

The research cited in this chapter also outlines many 

ways that the private sector, Government, and tribes 

can work to mitigate the overall effects of drought in 

society. Private-sector actors can respond to drought 

by pursuing innovative research and deploying new 

technology meant to improve water use efficiency; and 

governments can help by funding similar research and 
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Table 11.4—Measured effects of drought on the forest and rangeland sector, as reported in this chapter

Economic 

subsector 

or aspect Mechanism

Ownership, 

spatial and 

temporal 

scope Some effects identified

Timber 

products sector

Reduced net volume 

growth, leading to 

lower overall inventory 

quantities

National Lower success in post-harvest and new planted forest seedling establishment 

success, reduced harvest volumes, lowered overall employment, increased 

fire-related timber salvage, timber production shifts to less drought-prone 

locations, altered timber procurement zones, changed locations of pulp and 

paper manufacturing facilities

Forest- and 

rangelandbased water

Reduced water quantity 

and quality

National Forests 

and Rangelands 

of the United 

States

Home Use: Drought encourages adoption of new municipal ordinances 

or graduated pricing that changes water-use by appliances in homes and 

outdoors on properties

Commercial: lost output due to transfers of water use priorities away from 

agriculture and water-using manufacturing toward municipal users, to protect 

water-dependent wildlife and meet inelastic final consumer demand

Rangeland and Agriculture: higher soil erosion rates and therefore long-run 

effects on productivity, planting of more drought-tolerant grasses, increased 

rates of tree-planting (including shelter belts), increased use of water-efficient 

irrigation technologies and techniques

Wildfire 

management

Higher wildfire activity National Forests 

and Rangelands 

of the United 

States

Higher wildfire suppression and post-fire mitigation expenditures, 65 percent 

higher during drought compared to nondrought conditions

Recreation Altered precipitation 

patterns, temperatures, 

and precipitation 

seasonality

National Reduced snow-based recreation opportunities, reduced water-based 

recreation opportunities, enhanced equestrian and off-road vehicle activities, 

perhaps higher rates of visitation to nature interpretive centers

Urban and 

residential 

communities

Killing of valuable 

residential and street 

trees, due in particular 

to additional stresses 

from physical structures 

and infrastructure, 

higher vulnerability to 

other disturbances

Urban/residential 

areas; national

In the American Dust Bowl, 235 trees/block killed in Manhattan, KS; tree 

mortality reduced home values 1-10 percent; higher home energy costs due to 

lower shading, greater flooding risks and increased storm water management 

costs, deterioration in human health and welfare (including higher incidences 

of asthma, worsened human birth outcomes, higher human mortality)

Tribal values 

and lifeways

Altered provision 

of water-affected 

ecosystem goods and 

services valued by 

indigenous cultures, 

through effects on 

wildfire, insects, 

diseases, invasive 

species, altered 

production of nontimber 

forest and rangeland 

products

National Increased epidemics of native and exotic pests, which reduces the supply of 

forest and rangeland-based ecosystem goods and services; bio-cultural losses 

due to worsened ecosystem health status; lost goods and services provided 

directly by water, including the spiritual value of water as a traditional “food,” 

water as a symbol for life, water as vehicle and instrument of purification 

and blessing rituals, water as a connection to wildlife; reduced availability 

of medicinal plants and traditional foods, adversely affecting human health; 

reduced productivity of, and income from, rangeland livestock managed by 

tribal peoples; increased marginalization of tribal peoples in the competition 

with the wider society for water supplies, fishing; reduced income and 

electricity provided by tribally owned hydroelectric facilities and other energy 

resources; lost income from recreation on tribal lands due to higher wildfire 

activity; increased use of local and traditional knowledge as a means of 

mitigating drought’s impacts
275

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Economics and Societal Considerations of Drought

EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

development (Miao and Popp 2014). Decisionmakers 

in the private and public sectors can act to reduce 

the negative effects of drought on wages, the cost of 

capital, income earned, and prices paid to consume 

water-intensive goods by investing in new technology 

that can reduce water input per unit of output. By 

investing in new water-storage technologies, for 

example, public and private organizations can reduce 

evaporation and water waste. Governments can also 

more directly collaborate with tribes to better monitor 

drought conditions and design interventions that can 

alleviate the special vulnerabilities that tribal societies 

face. This collaboration could include joint efforts to 

diversify tribal energy portfolios, protect traditional 

fishing and hunting rights when drought reduces animal 

populations, and create more effective mechanisms to 

respond to drought-related natural disturbances.

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APPENDIX:

Graphical Description of the 

Economic Effects of Drought 

on Production of a Good

Depending on its severity and persistence, one can 

view drought either as a transitory state or as a new 

“permanent” state, both of which have the potential to 

alter the distribution of inputs to productive economic 

activity. Figure 11.A1 describes how water scarcity 

(drought) would lead to a shift in resources used. It 

is a stylized model of one produced good (B) and 

two inputs, water (W) and another input (X) in the 

production of B. The vertical axis identifies the quantity 

of water used and the horizontal axis identifies the 

quantity of the other input in production in this twoinput production technology. Two curves, labeled B1

and B2, are shown. All along B1 the output quantity is 

the same, but different quantities of W and X can be 

used to produce B1. The same is true for B2: output is 

constant along the entire curve, and the quantities of 

W and X can be varied to produce that output quantity. 

Assume that B1 is the range of output quantities of B—a 

water-intensive good—that can be produced in normal 

(nondrought) conditions, while B2 is the (lower) quantity 

produced under drought conditions. The angled straight 

lines identify the relative prices of the two inputs: the 

flatter the slope of these lines, the more expensive is 

water relative to the other input. Optimal production, in 

terms of minimizing costs of inputs, is defined where 

the straight lines are tangent to the curved lines of 

B. Assume that the two parallel-angled straight lines 

represent the relative price of W to X. Without a drought, 

the production is at point a, using the quantity Wa of 

water Xa of the other input. Without a change in the 

relative prices of the inputs during drought, production 

would shift to the curve B2, implying lower levels of both 

inputs to production level defined at point b, with Wb

units of water and Xb units of the other input. During a 

drought, however, water can become more expensive, 

flattening the sloped line to the single-angled one shown 

in figure 11.A1. In that case, the optimal combination of 

inputs would favor production at point c, implying a still 

lower quantity, Wc, of water but a higher quantity, Xc, of 

the other input. In this way, with higher relative prices 

for water, drought would increase demand for the other 

input and reduce the demand for water.

B1 and B2 in this example are produced by the same 

technology. In the face of persistent drought or changes 

in drought severity or frequencies or spatial extents, 

producers might invest in a technology that is more 

water efficient at producing the same good, to avoid 

persistently higher prices paid for the water as an input 

in production. New technology conceivably would use 

water less intensively and other inputs more intensively, 

yielding a comparable quantity of good produced but at 

lower cost.

Another way to view the effects of drought on an 

economy is to consider its effects on the supply and 

demand of goods and services that depend on water in 

their production and thereby affect the overall welfare 

or value produced by the production and consumption 

of goods whose production depends on water. [See 

Just and others (1982) for details of welfare analytical 

techniques.] Figure 11.A2 is an abstract expression of 

B1

B2

a

b

c

Xc Xb Xa

Wc

Wa Water quantity (W)

Other input quantity (X)

Wb

Figure 11.A1—Optimal quantities of water and other inputs in 

the production of a good, B. 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

the supply and demand for a good that depends on 

water for some of its production. The supply of this 

good is a function of the price per unit of capital (r), 

price per unit of labor (w), and the initial quantity of 

water provided by nature (N0) available. The position 

of the supply function in price-quantity space is also 

a function of technology for producing the waterintensive good (z) (discussed later). Supply increases 

with the price of the good: a higher price of the good 

encourages more production as a rational response to 

greater potential profits earned by producers. Water 

provided by nature (N) affects the position of the supply 

curve (S0) in price-quantity space; higher N would move 

supply outward (to the right). The prices of capital and 

labor also shift supply; if the price of either capital or 

labor is higher, then supply shifts back (to the left). 

Demand, D, is a function of total income of potential 

consumers (higher income shifts demand outward) 

and the quantity-demanded decreases with the price 

of the good. One way that income can change is if the 

prices of either capital or labor change. For example, 

if either the price of capital (also known as the return 

to capital or the interest rate) or the price of labor (the 

wage rate) decreases, then income would decrease. 

The area bounded by the vertical axis on the left, the 

supply curve on the bottom, and demand curve on 

the top is economic surplus, the sum of consumer 

surplus and producer surplus, commonly referred to 

welfare (Welfare0)—the blue shaded portion in figure 

11.A2. Consumer surplus is defined as the sum of what 

all demanders (consumers) of the good would be willing 

to pay minus what they would actually pay (the area 

above price and below the demand curve). Producer 

surplus is defined as the costs incurred in producing 

each good minus the prices received for those goods in 

the market, defined by the area above the supply curve 

and below the equilibrium market price. The price in 

equilibrium is P0 and the quantity supplied is Q0.

Now, imagine a situation that reduces the provision 

of water, altering N1, as in the case of drought (figure 

11.A3). This acts to shift supply back to S1. With 

demand fixed, welfare is reduced to a smaller area, to 

Welfare1. The welfare lost is shaded in orange. Price 

increases to P1 and quantity supplied decreases to Q1.

We note here that lower output would eventually 

lead to the freeing up of capital and labor from the 

water-intensive sector due to lower overall output, 

and this labor and capital would be available to the 

water-extensive sector of the economy. The price of 

capital and labor would decline as a result. The waterextensive sector, therefore, can gain as a result of the 

drought, mitigating some of the overall losses in the 

Welfare D (Y) 0

P0

Q0 Quantity

Price

S0 (w0,r0,N0;z)

Figure 11.A2—A water-intensive goods market.

D (Y)

Welfare1

P1

Q1 Q0

Lost welfare 

Quantity

Price

P0

S1 (w0,r0,N1;z) S0 (w0,r0,N0;z)

Figure 11.A3—A reduction in the quantity of water available in a 

water-intensive goods sector.
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

economy. Figure 11.A4 illustrates this scenario. For a 

good produced in the water-extensive economic sector, 

initial supply is SO0, expressed as a function of the initial 

price of capital (r0) and labor (w0). Demand for the good 

in that sector is DO, a function of total income (Y), as 

before. For the good in this water-extensive sector, PO0

is the initial market price and QO0 is the initial production 

quantity. Initial welfare in the market for this good is 

represented by the blue triangle and labeled Welfare0. 

With drought, the prices of labor and capital drop to r1

(and r1< r0) and w1 (and w1< w0). Supply therefore shifts 

out to SO1, with a new and lower equilibrium price, 

PO1, and a higher equilibrium quantity, QO1. The effect 

for the market for this good is a gain in overall market 

welfare, adding the shaded tan area to the blue area. 

The above discussion is focused on particular goods, 

but it could apply to a whole basket (aggregate) of 

goods that are either water intensive (figs. 11.A1–11.A3) 

or not (fig. 11.A4) in their production.

The graphical representations in figures 11.A2–11.A4 

ignore shifts in demand that would occur because of 

the lower prices of capital and labor, meaning overall 

lower income in the economy (Y). Losses in the waterintensive sector would tend to outweigh the gains in the 

water-extensive sector of the economy. In other words, 

the demand curves in figures 11.A3–11.A4 would also 

shift back slightly, causing further adjustments in prices, 

quantities, and overall welfare in all markets. Other 

inputs to production could also be described beyond just 

labor, capital, and water. For example, land is an input 

common in the water-intensive sector—especially in 

agriculture. So if a drought affects the agricultural sector, 

just as for capital and labor, the market price of land 

would also drop.

One could also conceive of two kinds of labor: labor in 

the water-intensive sector and labor in the nonwaterintensive sector of the economy; in this case, the two 

kinds of labor might not be perfect substitutes for each 

other, due to specialized skills. If demand for labor in 

the water-intensive sector drops due to lower overall 

production possibilities, then some—but not all—

labor could migrate to the nonwater-intensive sector 

of the economy; some labor, however, might remain 

idle until water returns (the drought ends) or the labor 

acquires new skills (e.g., through training) that makes 

it equivalent to the specialized labor of the nonwaterintensive sector.

Finally, not described in the figures, is a role for 

technology (z in figures 11.A2 and 11.A3) used in the 

water-intensive sector. New technology could be 

developed and used in the water-intensive sector that 

allows for more efficient use of water (smaller quantities 

used for each unit of output). This would cause the 

supply curve to shift outward, allowing for greater 

overall production levels at each price received for the 

water-intensive good in the market. This would serve 

to mitigate the overall negative consequences for the 

water-intensive sector, helping to support prices and 

keep wages and interest rates (and hence incomes) 

higher than they would be without the new technology. 

Producers of the water-intensive good could invest in 

research and development (Miao and Popp 2014) of 

new water-efficient technology, or governments can 

provide it or do research that makes its use feasible. 

An example of a water-efficient technology is a drip 

irrigation system, which uses less water than a sprinkler 

system in the agricultural sector.

DO (Y)

Welfare0

PO0

QO0 QO1

Gained welfare 

Quantity

Price

PO1

SO0 (w0,r0) SO1 (w1,r1)

Figure 11.A4—Goods production in other sectors not directly 

affected by drought (water-extensive sectors). 

CHAPTER 12

C.H. Luce is a Research Hydrologist, U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station (RMRS), Boise, ID 83702.

J.S. Clark is the Nicholas Professor of Statistical Science at Duke University, Nicholas 

School of the Environment, Durham, NC 27708-0338.

J.M. Vose is a Research Ecologist, U.S. Department of Agriculture, Forest Service, 

Southern Research Station (SRS), Center for Integrated Forest Science (CIFS), North 

Carolina State University, Department of Forestry and Environmental Resources, Raleigh, 

NC 27695.

T. Patel-Weynand is Director of the Sustainable Forest Management Research (SFMR) 

staff, U.S. Department of Agriculture, Forest Service, Research and Development (R&D), 

Washington, DC 20024.

Summary and Conclusions

Charles H. Luce

James S. Clark

James M. Vose

Toral Patel-Weynand
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Introduction

Drought is a common disturbance force that drives 

many ecosystem processes (Dale and others 2001, 

Luce and others 2012). Forests and rangelands are 

inherently resilient to drought; however, recent droughts 

have had severe impacts on forests and rangelands 

in the United States (Breshears and others 2005, 

Westerling and others 2006), and there is a growing 

recognition that outcomes of drought in forests and 

rangelands in a warmer and drier future could be even 

more severe (Littell and others 2009, Vose and others 

2012). Although most of the apparent changes thus 

far are in the West, all U.S. forests are vulnerable 

to drought. While projections of changes in drought 

regimes are uncertain, natural resource managers 

will be better prepared to manage for resiliency and 

adaptation to drought with an improved understanding 

of how drought affects forests and rangelands. 

To provide that understanding, the preceding 

syntheses focused on several key aspects of drought: 

characterizing drought in forests and rangelands, 

understanding drought impacts on ecosystem structure 

and function, and assessing the socioeconomic 

impacts. In the following sections, we summarize some 

of the key findings from our synthesis.

Characterizing Drought

Drought is characterized by the magnitude of the 

precipitation deficit (i.e., the difference from a 

reference condition such as a long-term mean) and 

its duration (chapter 2). Common metrics of drought 

incorporating these two factors include the Palmer 

Drought Severity Index (PDSI) (Palmer 1965) and 

the Standardized Precipitation Index (SPI) (McKee 

and others 1993). The SPI is strictly a function of 

precipitation and time, whereas the PDSI incorporates 

potential evapotranspiration. The question of whether 

precipitation droughts are becoming more severe 

as a consequence of climate change is open and 

being vigorously discussed (Luce and others 2013, 

Mann and Gleick 2015, Swain and others 2014, 

Trenberth and others 2014). Most forms of potential 

evapotranspiration-based drought indices implicitly 

include air temperature, consistently yielding increased 

drought severity, or even persistent drought, in future 

projections even where precipitation might be projected 

to increase or remain the same (e.g., Cook and others 

2015, Dai 2011, Sheffield and others 2012). As a result, 

even unchanged drought characteristics in the future 

would likely yield increasing stress on plants because 

of warmer temperatures at the very least (Adams and 

others 2009, Allen and others 2010, Breshears and 

others 2005, Diffenbaugh and others 2015).

Regardless of our capacity to project future drought with 

precision, it is increasingly important to detect its effects 

on forests and rangelands at large scales (chapter 9). 

Commonly used meteorological drought indices may 

not be appropriate for forests, so the ability to remotely 

sense drought symptoms in forests will become 

increasingly important. A number of spectral reflectance 

properties of forests change as trees become more 

water stressed, offering promise for the progress of 

drought to be monitored by remote sensing; but, the 

relationship between drought and spectral properties 

is not straightforward for forests due to factors such 

as lags in response and varying species sensitivities. 

Combining multiple data sources (e.g., remote sensing, 

climate, and plant data) will be required to determine the 

progress of the ecological consequences of drought.

Drought Effects on Wildlands

Drought affects forests in complex ways, ranging from 

reduced growth to mortality by starvation, desiccation, 

fire, or insects and pathogens. Drought also has an 

ecological role that shapes the structure and function 

of many forests. For example, fire-adapted ecosystems 

may also be thought of as “drought-adapted” because 

drought predisposes forest to wildfire. Similarly, 

some species that live in droughty conditions, such 

as bristlecone pine (Pinus longaeva), gain some 

resistance to spreading pathogens through a lack of 

nearby neighbors. Understanding some of these unique 

adaptations requires a broader understanding of the 

basic effects of drought on individual trees and forest 

communities.

The effects of drought on plants depend on the matric 

potential of soil water in the rooting zone (chapter 3). As 

leaves become drier due to a lack of available moisture 

in the soil to rewet them at night, stomata will close 

when the evaporative demand of the air (a function 

of warm temperatures and low humidity) becomes 

too great. When stomata close, plants are unable 

to fix carbon dioxide, leading to metabolic stress. If 

metabolic stress is severe, and the stomata are open, 

continued evaporation from leaves can lead to hydraulic 

failure, interrupting the flow of water up the stem to 

the leaves. Species differences in their allocation to 

roots, mycorrhizal associations, and xylem anatomy all 

contribute to species differences in drought tolerance. 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Although elevated carbon dioxide (CO2) can increase 

water use efficiency, the combined effects of rising CO2

and drought are poorly understood. Translating impacts 

on trees to the stand and landscape scale is challenging; 

however, combined field evidence and models suggests 

that climate shifts are moving habitats faster than tree 

species can keep up (chapter 4). Hence, stand structure 

and species composition are expected to lag behind 

shifts in habitat caused by increasing drought and 

temperature change.

Increased drought tends to hinder nutrient uptake 

by plants, and it may reduce retranslocation of foliar 

nutrients if premature leaf senescence occurs (chapter 

5). However, nutrients in the foliage tend to become 

more concentrated because carbon fixation and water 

uptake decrease. Microbial activity in soils may be 

reduced as soils dry out, but those portions of the soil 

with enough moisture may see more rapid metabolism 

if temperatures rise. Mortality associated with drought 

may increase carbon available to the soil in the short and 

medium term. Dieback can also severely limit carbon 

fixation by the biosphere. Recent, large diebacks have 

had global impacts on carbon cycles, including release 

of carbon from dead biomass and reduced vegetation 

uptake of carbon.

Natural enemies may capitalize on drought stress in 

trees, leading to large diebacks (Breshears and others 

2005). Severe moisture stress reduces both chemical 

and physical defenses of trees to insects, and droughts 

are commonly precursors to severe outbreaks (Creeden 

and others 2014, Raffa and others 2008). Insects 

also benefit from the increased nutritional content of 

drought-stressed trees, making both defoliating and 

boring insect outbreaks more potent during drought 

conditions (chapter 6). Some fungal infections may 

be hampered by drier conditions, although many 

species may benefit from drought-related damage 

after moist conditions return. Insect attacks and fungal 

pathogens can further impair plant defenses against 

drought mortality. Prolonged and severe moisture 

stress can ultimately have negative feedbacks on insect 

populations simply through reduced production of food 

and food quality.

Fire commonly occurs in concert with drought, 

particularly more widespread fires (Heyerdahl and 

others 2008, Morgan and others 2008), and a range of 

meteorological drought indices offer some predictive 

capability for the amount of fire on the landscape 

(chapter 7). Drought can, inversely, limit the growth 

of fuels, particularly in more arid locations, creating 

an interesting outcome where anomalously moist 

conditions preceding the dry season predict more fire 

(Abatzoglou and Kolden 2013, Littell and others 2009). 

Forest fires that occur in moist years tend to be less 

widespread (in part because they are easier to control), 

and severity patterns in these fires are controlled by 

topographic factors affecting soil moisture distributions 

(Dillon and others 2011). Conversely, fires are more 

likely to escape control during drought years, affecting 

more acreage. Although the fractional area of high 

severity is similar between drought and nondrought 

years, severity patterns show less discrimination in 

drought years. Land management and fire management 

choices that affect fuels can greatly affect the spread 

and severity of fires through their control on fuel 

availability.

When there is less water, there is less for trees and 

less for streams (chapter 10). Both evapotranspiration 

and streamflow react negatively to drought, and the 

sensitivity of streamflow to drought is not the same 

everywhere. Different soil, topography, vegetation 

types, and precipitation seasonality all affect changes 

in the partitioning of precipitation and energy inputs to 

the system to determine its response. Streams become 

generally warmer with lower flows, but water chemistry 

changes are substantially more complex, having some 

relation to changes in nitrogen fixing and uptake.

Rangelands are at the arid end of the spectrum of 

wildland ecosystems encompassing woodland, 

shrubland, and grassland ecosystems, and moisture 

deficits may be expressed on much shorter time scales 

than in forest ecosystems. Consequently, management 

and utilization of these systems is fairly responsive to 

drought indications as a result of historical experience 

(chapter 8). Native plant restoration is a strong focus 

of efforts to improve drought resilience in rangeland 

ecosystems.

Socioeconomic Impacts

Drought has direct consequences to forest and 

rangeland production that can translate into economic 

impacts. For example, droughts can negatively impact 

forest inventories and reduce forage and water available 

for livestock grazing in rangelands. Drought-related 

disturbance, such as wildfire, can have protracted 

effects. Wildfires can generate positive short-term 

impacts in local communities, including external 

resources to fight fire and economic activities in 
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post-fire timber salvage and burn area rehabilitation. 

However, long-term effects can include significant 

timber market losses. Reduced water yield from 

forests and rangelands during extended meteorological 

drought can have substantial impacts on domestic 

and agricultural water supplies. Drought can also have 

nonmarket effects on forests and rangelands, such as 

water-based outdoor recreation activities.

It is important to identify risk, potential impacts, and 

vulnerabilities related to water supply and water rights 

on tribal lands. Ongoing drought in the Western United 

States, where most tribal lands exist, is expected to 

continue to affect tribal health, culture, economies, 

and infrastructure. Competing demands for dwindling 

water resources challenge Federal trust responsibilities. 

Complicating factors, including warming streams 

and hydrologic cycle changes, affect fish populations 

important to tribal diets and ceremonies. Because 

of their natural resource dependence for income, 

employment, and cultural practices, many tribes are 

also vulnerable to higher rates of forest and rangeland 

disturbances, including invasive species spread, 

increased occurrences of epidemic pest populations and 

their associated damages, and wildfires.

Critical Research Needs

Despite the recognition of drought as a key driver of 

ecosystem processes and the impacts of drought on 

human well-being, there are significant uncertainties 

that limit our ability to predict the direct and indirect 

impacts of drought on our Nation’s forests and 

rangelands. Examples of key areas of research needs 

identified by authors of this assessment include:

lImproved Metrics for Quantifying, Detecting, and 

Predicting Drought in Forests and Rangelands—

Unlike agricultural-based metrics, drought metrics for 

forests and rangelands may require a longer, multiyear 

“memory” of antecedent conditions. Adaptations 

might include reformulating drought measures to 

capture long-duration multiyear drought, targeting 

drought measures to the sensitive seasons of the 

year based on phenological insights, or embracing 

baselines that relate better to the nonequilibrium 

nature of forested and rangeland ecosystems. 

Empirically relating hydrologic drought measures (e.g., 

streamflow measures) and ecosystem outcomes 

at individual-to-stand levels may be one useful path 

toward advancing prediction, particularly given parallel 

ecosystem values as encompassed in the terms 

“green water” and “blue water” (Falkenmark and 

Rockström 2006).

Ecohydrologic models that relate drought stress in 

plants and plant productivity as a function of available 

water and climate (e.g., Running and Hunt 1993, 

Tague and Band 2004) may yield useful insights with 

respect to which drought characteristics are likely 

most stressful in different kinds of plant communities 

depending on the basic climate in which they reside. 

Advances in understanding from such modeling, 

however, are contingent on improvements in plant 

physiology within these models.

l Better Models for Predicting Drought Impacts 

on Ecosystem Processes and Population 

Dynamics—Existing biogeochemical cycling models 

perform poorly under drought conditions, stemming 

largely from the lack of root and stem hydraulic 

characteristics in those models. Scientists need to 

better understand the response of the belowground 

system, ecosystem interactions across multiple 

trophic scales, and the interaction of drought with 

elevated CO2. These dynamics are critical areas for 

future research. We also need to better understand 

drought consequences at the stand-to-landscape 

scales. This challenge is related to the need for 

models to accommodate environmental change 

and forest response as a coherent joint distribution 

of species and sizes that responds to drought with 

feedbacks and interactions. Unlike some types of 

disturbance that might be treated as an extrinsic 

force, drought involves a feedback with water use 

by the stand and, thus, is more difficult to model. 

Understanding these feedback mechanisms requires 

a better understanding of species’ differences in 

water use and sensitivity to drought, as well as the 

thresholds that determine species’ physiological 

capacity to survive drought.

l Improved Understanding of the Indirect Effects 

of Drought—Drought-productivity relationships 

related to physiological behaviors dominate the 

discussion of drought effects on forests, but the 

leveraging of drought by disturbance through insects, 

pathogens, and fire may be of greater influence in 

some places (Dale and others 2001). The stochastic 

nature of disturbance makes direct prediction through 

models difficult, but information about risk can be 

validated at landscape scales.
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

Despite bark beetle outbreaks impacting millions 

of forested acres in the United States, we still have 

a limited understanding of: (1) the relative role of 

temperature and precipitation deficit in droughtinduced outbreaks of bark beetles; (2) identification 

of species which are capable of self-perpetuating 

outbreaks after drought subsides; (3) the level of 

drought-associated tree mortality that would occur 

without bark beetle attacks; (4) the effectiveness 

of manipulating forest composition and structure 

to reduce drought stress and bark beetle attacks 

in semi-arid forests; and (5) the level of drought 

intensity in pine forests of the Eastern United 

States that would shift the role of drought in beetle 

outbreaks from a negative to a positive driver. 

The impact of defoliators and fungal pathogens 

has been variable, underscoring the need for a 

greater understanding of the impacts of drought on 

defoliators’ pathogens.

Drought and fire relationships show broadly a 

relationship between drier conditions and fire 

(e.g., flammability of fuels), but there is a growing 

recognition and examples demonstrating that 

the relationship of drought to development 

and accumulation of fuels is important as well. 

The principle area of uncertainty in drought-fire 

relationships is in understanding the relative roles 

of precipitation and temperature as controls on risk. 

From the observational point of view related to fire 

occurrence and size, the window of opportunity is an 

important quantity in its own right, but if that window 

occurs in warm period, it exacerbates the drying of 

vegetation as well; separating these influences would 

be important in exploring climate change impacts, 

which affect timing and drying intensity through 

different mechanisms.

l Improved Understanding of Genetic 

Contributions to Resilience in Native Rangeland 

Plants—Drought adaptation in rangelands is arguably 

well developed with respect to balancing range 

utilization, simply out of the long-term lessons about 

recovery of rangelands with respect to herbivory. 

Important areas of learning, however, are occurring 

in the area of native plant restoration in the context 

of strong invasive species presence and changing 

climate. Finding seed sources with strong resilience 

to drought is an example of how research can help 

with assisted migration of important genetic diversity 

within the native plant communities.

l Improved Quantification of Socioeconomic 

Impacts—Although we have fairly precise measures 

of droughts’ effects on Federal wildfire management 

expenditures, we know little about the scale of these 

impacts on State and local firefighting expenditures. 

Long-term or persistent droughts or indeed climatechange-related dryness, would further affect the 

required size of the overall firefighting capacity of all 

agencies of governments. Water effects of drought 

are quantifiable, yet less is understood about the 

long-term economic effects of water mining (the 

permanent draw-down of water supplies residing 

underground). While researchers have quantified 

some effects of drought on recreation-based goods 

and services, very little is known about how the 

various types of recreation activities substitute and 

complement each other across space and time, or 

how other modes of consumption outside of the 

recreation sector can mitigate some of the losses 

experienced by specific types of recreation. We 

need an improved understanding of the effects of 

scale on economic impacts. For example, the effects 

of drought on growth and yield in particular forest 

types in particular places might be acute; however, 

economies are global and substitution possibilities for 

consumers of forest products and across producing 

regions reduce some of the negative impacts felt 

in the specific location of the drought, reducing net 

overall economic losses.

Management Responses

How can forest and rangeland practices adapt to 

changing drought regimes? Frequent, low-severity 

drought may selectively favor more drought-tolerant 

species and create forests and rangelands better adapted 

to future conditions without the need for management 

intervention. By contrast, severe drought (especially 

in combination with insect outbreaks or fire) may 

threaten large-scale changes that warrant substantial 

management responses. Actions could range from 

reducing vulnerability, facilitating post-drought recovery, 

or facilitating a transition to a new condition.

Management actions can either mitigate or 

exacerbate the effects of drought. A first principal for 

increasing resilience and adaptation would be to avoid 

management actions that exacerbate the effects of 

current or future drought. Options can include altering 

structural or functional components of vegetation. 

Structural changes can be implemented by thinning 
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EFFECTS OF DROUGHT ON FORESTS AND RANGELANDS IN THE UNITED STATES

or density management of planted forests. Thinned 

stands require less water and can be less vulnerable 

to water stress and insect outbreaks. Reduced fuel 

loads in thinned stands can also reduce wildfire risk. 

Increasing species and age-class diversity within 

stands can reduce insect attack intensity as well. 

Functional changes can be implemented by favoring 

or planting more drought- and disturbance-adapted 

species. Management for a diversity of species can 

reduce stand vulnerability to drought, as uncertainty 

in future climate can motivate management for a mix 

of drought-tolerant species and genotypes. In some 

regions of the United States, planting or favoring more 

drought-tolerant species may conflict with management 

objectives that favor rapid accumulation of biomass, as 

fast-growing woody species often use more water and 

can exacerbate drought impacts.

Since forest harvest has been shown to increase annual 

water yield, some have proposed that the effects of 

drought on water supply could be mitigated by cutting 

forests, but there are concerns that such an approach 

could be maladaptive (Brown and others 2005, Troendle 

and others 2010). A major challenge in managing forests 

to enhance water supply is the large reduction of forest 

cover that might be needed to create an appreciable 

effect on water yield. Hence, potential increases in 

streamflow through forest cutting are limited by the 

amount of land that can be harvested or maintained 

in early seral stages at a given time. In addition, 

streamflow responses are often short term due to 

rapid forest regrowth, and the aggrading post-harvest 

forest may actually transpire water more rapidly than 

the uncut forest. Because drought is unpredictable, it 

may not be possible to time harvesting precisely when 

needed to offset the effects of drought. Furthermore, 

in contrast to management actions that are intended 

to augment streamflow, increasing drought stress in 

some forest ecosystems may warrant management 

strategies that retain water on the landscape (and 

hence reduce streamflow) in order to keep trees alive. 

Management efforts should focus on minimizing inputs 

of sediments and nutrients into the stream. It may be 

beneficial to plan the timing of management activities 

so they do not disturb streams during low-flow periods 

and to avoid vulnerable areas during droughts. Since 

removal and alteration of riparian vegetation increases 

stream temperatures, maintaining or increasing shading 

from solar radiation through riparian buffer conservation 

and restoration may help protect streams against high 

temperatures during drought.

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This assessment provides input to the reauthorized National Integrated Drought 

Information System (NIDIS) and the National Climate Assessment (NCA), and it 

establishes the scientific foundation needed to manage for drought resilience and 

adaptation. Focal areas include drought characterization; drought impacts on forest 

processes and disturbances such as insect outbreaks and wildfire; and consequences 

on forest and rangeland values. Drought can be a severe natural disaster with substantial 

social and economic consequences. Drought becomes most obvious when large-scale 

changes are observed; however, even moderate drought can have long-lasting impacts 

on the structure and function of forests and rangelands without these obvious largescale changes. Large, stand-level impacts of drought are already underway in the West, 

but all U.S. forests are vulnerable to drought. Drought-associated forest disturbances 

are expected to increase with climatic change. Management actions can either mitigate 

or exacerbate the effects of drought. A first principal for increasing resilience and 

adaptation is to avoid management actions that exacerbate the effects of current or 

future drought. Options to mitigate drought include altering structural or functional 

components of vegetation, minimizing drought-mediated disturbance such as wildfire or 

insect outbreaks, and managing for reliable flow of water.

Keywords: Climate change, drought, forest disturbances, natural disasters, water 

quantity and quality.
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