Forest

Service

Indicators of Climate Impacts for Forests: 

Recommendations for the U.S. National 

Climate Assessment Indicators System

United States Department of Agriculture

General Technical

Report NRS-155

Northern

Research Station December 2015
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Manuscript received for publication May 2015

The Third National Climate Assessment (NCA) process for the United States focused in 

part on developing a system of indicators to communicate key aspects of the physical 

climate, climate impacts, vulnerabilities, and preparedness to inform decisionmakers and 

the public. Initially, 13 active teams were formed to recommend indicators in a range of 

categories, including forest, agriculture, grassland, phenology, mitigation, and physical 

climate. This publication describes the work of the Forest Indicators Technical Team. 

We briefly describe the NCA indicator system effort, propose and explain our conceptual 

model for the forest system, present our methods, and discuss our recommendations. 

Climate is only one driver of changes in U.S. forests; other drivers include socioeconomic 

drivers such as population and culture, and other environmental drivers such as nutrients, 

light, and disturbance. We offer additional details of our work for transparency and to 

inform an NCA indicator Web portal. We recommend metrics for 11 indicators of climate 

impacts on forest, spanning the range of important aspects of forest as an ecological 

type and as a sector. Some indicators can be reported in a Web portal now; others 

need additional work for reporting in the near future. Indicators such as budburst, which 

are important to forest but more relevant to other NCA indicator teams, are identified. 

Potential indicators that need more research are also presented. 

Cover 

Cover art by Eric Fiegenbaum, Madbury, NH. 

Abstract

Quality Assurance 

This publication conforms to the Northern Research Station’s Quality Assurance 

Implementation Plan which requires technical and policy review for all scientific 

publications produced or funded by the Station. The process included a blind technical 

review by at least two reviewers, who were selected by the Assistant Director for 

Research and unknown to the author. This review policy promotes the Forest Service 

guiding principles of using the best scientific knowledge, striving for quality and 

excellence, maintaining high ethical and professional standards, and being responsible 

and accountable for what we do. 
Indicators of Climate Impacts for Forests: 

Recommendations for the U.S. National Climate 

Assessment Indicators System

Linda S. Heath, Sarah M. Anderson, Marla R. Emery, 

Jeffrey A. Hicke, Jeremy Littell, Alan Lucier, Jeffrey G. Masek, 

David L. Peterson, Richard Pouyat, Kevin M. Potter, 

Guy Robertson, Jinelle Sperry, Andrzej Bytnerowicz, 

Sarah Jovan, Miranda H. Mockrin, Robert Musselman, 

Bethany K. Schulz, Robert J. Smith, and Susan I. Stewart
Team Members and Authors

Linda S. Heath is a research forester with the U.S. Forest Service, Northern 

Research Station, 271 Mast Road, Durham, NH 03823, Lheath@fs.fed.us.

Sarah M. Anderson is a graduate research assistant and NSPIRE-IGERT

Fellow, Washington State University, School of Biological Sciences, 

P.O. Box 644236, Pullman, WA 99164, sarah.anderson2@email.wsu.edu. 

Marla R. Emery is a research geographer with the U.S. Forest Service, 

Northern Research Station, 81 Carrigan Drive, Burlington, VT 05405, 

memery@fs.fed.us.

Jeffrey A. Hicke is an associate professor, University of Idaho, Department 

of Geography and Environmental Science Program, Moscow, ID 83844, 

jhicke@uidaho.edu.

Jeremy Littell is a research ecologist, U.S. Geological Survey, USGS 

Alaska Climate Science Center, 4210 University Drive, Anchorage, AK 99508, 

jlittell@usgs.gov.

Alan Lucier (deceased) was vice president, National Council for Air and 

Stream Improvement, Inc., Raleigh, NC.

Jeffrey G. Masek is a research scientist, National Aeronautics and 

Space Administration, Goddard Space Flight Center, Greenbelt, MD, 

jeffrey.g.masek@nasa.gov.

David L. Peterson is a senior research biologist with the U.S. Forest Service, 

Pacific Northwest Research Station, 400 N. 34th Street, Suite 201, Seattle, WA 

98103, peterson@fs.fed.us.

Richard Pouyat is the national program leader for air quality research, 

U.S. Forest Service, 1400 Independence Avenue SW, Washington, DC 20250, 

rpouyat@fs.fed.us.

Kevin M. Potter is a research associate professor, North Carolina 

State University, Department of Forestry and Environmental Resources, 

3041 Cornwallis Road, Research Triangle Park, NC 27709, 

kpotter@ncsu.edu.

Guy Robertson is the national sustainability program leader, U.S. 

Forest Service, 1400 Independence Avenue SW, Washington DC, 20250, 

grobertson02@fs.fed.us.

Jinelle Sperry is a wildlife biologist with the U.S. Army Engineer Research 

and Development Center, 2902 Newmark Drive, Champaign, IL 61826, 

Jinelle.Sperry@usace.army.mil.
Contributing Authors

Andrzej Bytnerowicz is a senior scientist, U.S. Forest Service, 

Pacific Southwest Station, 4955 Canyon Crest Drive, Riverside, CA 92507, 

abytnerowicz@fs.fed.us.

Sarah Jovan is a research ecologist, U.S. Forest Service, Pacific Northwest 

Research Station, 620 SW Main Street, Suite 400, Portland, OR 97205, 

sjovan@fs.fed.us.

Miranda H. Mockrin is a research biologist, U.S. Forest Service, Rocky 

Mountain Research Station (colocated with the Northern Research Station), 

5523 Research Park Drive, Suite 350, Baltimore, MD 21228, 

mhmockrin@fs.fed.us.

Robert Musselman is scientist emeritus, U.S. Forest Service, Rocky 

Mountain Research Station, 240 West Prospect Road, Fort Collins, CO 80526, 

rcmusselman@fs.fed.us.

Bethany K. Schulz is a research ecologist, U.S. Forest Service, Pacific 

Northwest Research Station, 161 East 1st Avenue, Anchorage, AK 99501, 

bschulz@fs.fed.us.

Robert J. Smith is a graduate research assistant, Oregon State University, 

Department of Botany & Plant Pathology, 2082 Cordley Hall, Corvallis, OR 

97330, smithr2@onid.oregonstate.edu.

Susan I. Stewart is a senior scientist, University of Wisconsin, Department 

of Forest Ecology and Management, 1630 Linden Drive, Madison, WI 53706, 

sistewart@wisc.edu.

Preface: CONTEXT AND SCOPE 

The Third National Climate Assessment (NCA) process for the United States 

focused in part on developing a system of indicators to communicate key aspects 

of the physical climate, climate impacts, vulnerabilities, and preparedness to 

inform policy makers, managers, and the public in their decisionmaking. To 

maximize access to the indicators, an ultimate goal of the NCA indicators process 

is to produce a Web portal which will be maintained, updated, and accessible to 

the public. Because climate is interwoven with all facets of the environment and 

society, the climate issue was delineated into commonly used categories such as 

agriculture or energy to organize the work. A team of scientists was convened for 

each category to conduct research to develop a basis from which to recommend 

core indicators. 

Initially, 13 teams were organized: adaptation and hazards, human health, 

mitigation and greenhouse gas emissions, oceans and coasts, physical 

climate, freshwater ecosystems, grassland, forest, agriculture, water cycle and 

management, phenology, energy, and infrastructure. The adaptation and hazards 

team started later due to the need for additional research. A 14th team on 

biodiversity was added during the overall effort. This publication documents the 

work of the Forest Indicator Technical Team. 

Forest team members were invited for their expert understanding of forests 

either as a sector or as an ecological type, or both. As our work proceeded, we 

invited scientists to serve as contributing authors in specific areas where more 

expertise was needed. In addition, we recognized that some important ecological, 

societal, or climatic processes relevant to forests were also likely to be even more 

important and relevant to other teams. To ensure the important aspects were not 

overlooked, we also provided a list of indicators for other teams. 

The two appendixes are included for full transparency of the process and to 

maximize use of the information our team produced. Appendix 1 features our 

detailed responses to the requested evaluation criteria. Appendix 2 contains 

the memo on potential indicators and research gaps which we produced and 

submitted to the NCA Indicator Working Group. This request memo highlights 

research needs and opportunities to guide future research. We have attempted to 

minimize duplication of text between the main text and the appendixes, but some 

material is repeated for ease of comprehension.
The long list of authors reflects the scope and significance of forestland of the 

United States. Major contributors to each indicator are listed with that particular 

indicator in the main text, and they also contributed to that indicator’s section 

in Appendix 1. Authors listed as team members determined the final list of 

recommended indicators. Contributing authors focused mainly on the sections 

associated with their names. All authors were given the opportunity to comment 

on the entire work. Sarah Anderson, Guy Robertson, and Rich Pouyat in 

particular worked on the forest conceptual model; Anderson also provided the 

summary of forest and cross-cutting indicators in the main text, and compiled the 

input from team members into an initial report. Pouyat assisted with coordination 

issues for ecological indicators. Marla Emery gave steady advice and assistance 

throughout the effort from a social science perspective. As team lead, Linda 

Heath suggested and invited additional team members, designed the general 

outline and the conceptual model for the forest team’s overall effort (see Figure 1 

on page 8), and wrote the introduction and methods section. She coordinated 

handling the review comments, and went through final drafts and modified or 

augmented the text as needed for the document to “flow” with consistency. 

We sadly report that team member Dr. Alan Lucier passed away in March 2014. 

Al was always a steady, dedicated, insightful force for forests and people. He 

provided important contributions and ideas to our effort, and he enriched the 

discussion on our recommended indicators.

In addition to the authors, we recognize the team leading the overall NCA 

indicator system efforts, including coordinating the technical teams and working 

with principals of agencies and working groups: Melissa A. Kenney (principal 

investigator of Indicators Research Team, University of Maryland), Anthony C. 

Janetos (National Climate Assessment and Development Advisory Committee 

Indicators Working Group chair, Boston University), Richard Pouyat (Indicators 

Research Team, U.S. Forest Service), and Ainsley Lloyd (Indicators Research 

Team, University of Maryland). The work of Kenney and the Indicators Research 

Team was supported by NOAA grant NA14NES4320003 (Cooperative Institute 

for Climate and Satellites-CICS) at the University of Maryland/ESSIC. We also 

recognize and thank H. Ken Cordell, scientist emeritus, U.S. Forest Service, 

Southern Research Station for his suggestions and contribution on possible 

recreation and amenity indicators, and Linda Geiser, air program manager of 

the U.S. Forest Service, lgeiser@fs.fed.us, for her contributions to the potential 

lichen diversity indicator. We thank Elizabeth Burrill, U.S. Forest Service, 

Durham, NH, for developing Figures 3 and 8. We appreciate the many reviewers 

who provided comments throughout the process, especially review comments 

from anonymous reviewers from the blind-peer review process of the U.S. Forest 

Service, Northern Research Station, for helping improve the quality of this effort. 

We view our work as a first version of indicators that will be coordinated 

with other NCA indicator system teams, to be refined and updated in the 

future. We hope our effort will focus additional research on important forestclimate indicators, and encourage the collection of critical measurements and 

observations.
table of contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Why U.S. Forests Are a Category in the NCA Indicator System . . . . . . . . 2

Forest Indicators Related to Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Template . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Additional Decision Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Domains of the National Climate Assessment Indicator System . . . . . . . 7

Definition of Forestland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Conceptual Model for Forest Indicators . . . . . . . . . . . . . . . . . . . . . . . . . 10

Recommended Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Important Links Between the Forest Team and Other Teams . . . . . . . . . 16

Description of Recommended Forest Indicators . . . . . . . . . . . . . . . . . . . 18

Forest Extent Indicator: Forestland Area and Extent . . . . . . . . . . . . . 19

Structure and Function Indicator: Forest Biomass Density . . . . . . . . 20

Ecosystem Services Indicator: Diversity/Abundance 

 of Forest-associated Floral and Faunal Species . . . . . . . . . . . . . . . 22

Structure and Function Indicator: Forest Growth/Productivity . . . . . . 24

Disturbance Indicator: Wildfire Effects . . . . . . . . . . . . . . . . . . . . . . . . 25

Disturbance Indicator: Forest Insect and Disease Damage . . . . . . . . 27

Biophysical Indicator: Water Balance Deficit—

 An Indicator of “Plant-Relevant” Drought . . . . . . . . . . . . . . . . . . . . 28

Extent/Socioeconomic Indicator: 

 U.S. Wildland-Urban Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Climate Impacts on Human Domain via Forest: 

 Cost to Mitigate Wildfire Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Human Domain Influences on Climate Domain 

 via Forest: Energy Produced from Forest-based Biomass . . . . . . . 33

Socioeconomic/Ecosystem Services Indicator: 

 Outdoor Recreation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Research Gaps and Potential Indicators . . . . . . . . . . . . . . . . . . . . . . . . 36

Summary of Research Gaps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Summary of Potential Indicators and Metrics . . . . . . . . . . . . . . . . . . 36

Summary and Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

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

Appendix 1: Additional Indicator Details . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Appendix 2: Forest Indicators Technical Team Research Memo . . . . . . . 115

INTRODUCTION

The Third National Climate Assessment (NCA) process for the United States 

focused in part on developing an indicators system to communicate key aspects 

of the physical climate, climate impacts, vulnerabilities, and preparedness to 

provide both decisionmakers and the public scientific information which is 

useful for decisionmaking. An indicator system is an approach that provides 

specific information about the state or condition of an area of interest, used 

to focus attention on items of fundamental importance. Workshops were held 

on ecological, societal, and physical indicators (U.S. Global Change Research 

Program [USGCRP] 2011a, 2011b, 2012, and additionally summarized in Janetos 

et al. 2012). The overall effort is led by the National Climate Assessment and 

Development Advisory Committee (NCADAC), chartered under the Federal 

Advisory Committee Act, for the Subcommittee on Global Change Research, 

Office of Science and Technology Policy.

The goals for the NCA indicators are to:

• Provide meaningful, authoritative climate-relevant measures about the 

status and trends of key physical, ecological, and societal variables and 

values; 

• Inform decisions on management, research, and education at local to 

regional to national scales; 

• Identify climate-related conditions and impacts to help develop effective 

mitigation and adaptation measures; and

• Provide clear analytical methods by which user communities can derive 

their own indicators for particular purposes.

The NCA indicator system is not intended to be a vehicle for documenting 

rigorous cause-and-effect relationships, but rather to serve as an information 

base for: 1) those factors that may affect variability and change in the climate 

system; 2) the resources and sectors of concern that are affected by climate; and 

3) how society chooses to respond. These indicators will be tracked as a part of 

ongoing assessment activities, with adjustments as necessary to adapt to changing 

conditions and understanding. A Web portal is planned to make the indicator 

system publicly available. 

Climate has an effect on all facets of the environment and society. Initially, 

13 teams were organized: adaptation and hazards, human health, mitigation 

and greenhouse gas emissions, oceans and coasts, physical climate, freshwater 
2 Indicators of Climate Impacts for Forests:

ecosystems, grassland, forest, agriculture, water cycle and management, 

phenology, energy, and infrastructure. The adaptation and hazards team started 

later due to the need for additional research, and other teams were asked not to 

focus on adaptation. A 14th team was added later on biodiversity. Each team was 

charged with recommending indicators for use in this system. To keep the full 

indicator set manageable, the guidance to each team was to recommend about 

10 or fewer indicators. 

This study was conducted by the Forest Indicator Technical Team (hereafter 

called the forest team). Like all teams, we were assigned a specific format to 

follow with a list of evaluation criteria, with the objective of recommending 

indicators for forestland. Specific details we developed and used for this effort 

are presented in Appendix 1. First, we present general facts about forests in 

the United States, and use this exploration to help formulate a systems model 

for forests as a sector and ecological type. We discuss our refined approach 

for identifying the indicators that we recommend for use by the NCA indicator 

system, and present our recommendations including example outputs which 

can be derived from existing or needed data. Indicators considered to be more 

relevant to the topic areas of other teams, are also discussed. Finally, we discuss 

research gaps on recommended indicators, and also areas that look promising for 

indicators but would need more research. The details of our work on potential 

indicators and research gaps are provided in Appendix 2. 

Why U.S. Forests Are a Category in the NCA Indicator System

U.S. forests are significant. Forestland is a foundation for improved livelihoods 

and a premium quality of life. Forests provide major opportunities for recreation, 

hunting and fishing, breathtaking vistas and unbroken serenity; are a major 

source of superior freshwater supply; protect soil from erosion and build organic 

matter stores; clean our air and provide other human health benefits; are essential 

for wood supply to build our homes and to manufacture a wide variety of 

products from renewable materials; sequester and store a significant amount of 

carbon with continued storage in long-lived wood products; contribute to local 

livelihoods and the national economy; and provide a major source of renewable 

energy. Forests are the home for much biodiversity—wildlife, plants, and other 

organisms—and have an intrinsic existence value. Forests offer low-cost options 

for climate mitigation, which delivers other additional multiple environmental 

and social benefits, and forests can play a significant role in ecosystem-based 

adaptation activities. 

The following points illustrate the importance of U.S. forests:

• Forests account for about one-third of the total land base in the United 

States (Oswalt et al. 2014). 

• In recent decades, U.S. forests have sequestered substantial amounts of 

carbon, annually offsetting 10 to 20 percent of U.S. fossil fuel emissions 

(Heath et al. 2011).
Recommendations for the U.S. National Climate Assessment Indicators System 3

• In 2009, almost 19 billion activity days were spent viewing or 

photographing nature in forests, 2 billion activity days were devoted to 

backcountry activities, and 408 million activity days were spent hunting. 

In 2000, 56 million people went camping in forests (Cordell 2012).

• Total forest-related direct jobs are estimated to be almost 3 million, 

about 2 percent of all U.S. employment (U.S. Forest Service 2012), and 

receive about $102 billion in payroll. Jobs in forestry, forest products 

manufacturing, and wholesaling produce $262 billion in annual sales and 

contribute 6.7 percent of total manufacturing revenue (Wan and Fiery 

2013). 

• More than 200,000 plant and animal species have been documented on 

the lands and waters of the United States (Stein et al. 2000). Many of 

these species are associated with forests in at least part of their range 

or life cycle. Twenty percent of U.S. forestland is under some type of 

conservation program (Alvarez 2007).

• Energy from wood biomass accounts for at least 20 percent of renewable 

energy consumption in the United States (U.S. Energy Information 

Administration 2013).

As complex ecosystems, forests are vulnerable to impacts from climate change 

(Melillo et al. 2014). Climate change is expected to alter U.S. forestlands and the 

goods and services they produce. 

Forest Indicators Related to Climate

Given the significance of forests in the United States and their relationship to 

climate, forest is an important category for the NCA indicator system. In this 

effort, we focus on indicators related directly to forest ecosystems, as well 

as associated social and economic systems as they relate to climate change 

detection, mitigation, and adaptation. An existing set of indicators designed to 

measure the sustainability of forest ecosystems may include indicators relevant 

to the NCA effort. The existing set, the Montreal Process Criteria and Indicators 

for Forest Sustainability, has been used to produce two periodic reports on forest 

conditions and their sustainability in the United States (U.S. Forest Service 

2004, 2011). The most recent report1 (U.S. Forest Service 2011) identifies the 

interaction of forest, climate change, and bioenergy as an overarching issue that 

promises to be of crucial importance in future years. That report discusses how 

certain Montreal Process indicators relate to climate change, but these indicators 

were not developed to specifically measure climate change impacts.

Recently published forest-focused NCA and related documents should also 

prove useful in this effort; in particular, see Vose et al. (2012) and Melillo et al. 

(2014). Additionally, the Resource Planning Act (RPA) Assessment (U.S. Forest 

Service 2012) analyzes current and projected forest conditions based on the 

1

A third edition of the report is due for publication in 2016.
4 Indicators of Climate Impacts for Forests:

Intergovernmental Panel on Climate Change (IPCC) climate scenarios (IPCC 

2007). The RPA Assessment projections, however, are not based on an explicit 

conceptual model of indicators, but some of the outputs could prove useful to 

indicators of climate impacts for forests.

METHODS 

The charge to each team from the USGCRP through the NCADAC Indicators 

Working Group was to: 1) develop a conceptual model for this sector or land 

use; 2) identify and recommend core indicators which could be addressed within 

a year, including a few that would be already available for an early pilot Web 

site; and 3) identify gaps in research on the recommended indicators. A common 

template was provided for each team to complete for reporting.

As stated previously, one goal of the effort is for the USGCRP to host a Web 

portal that would feature the approximately 120 climate-related indicators 

recommended through this process. The target audience includes policy 

makers, analysts, and the public. The following decision criteria were to guide 

teams’ approach to identifying indicators: Indicators should 1) be scientifically 

defensible, 2) link to the conceptual framework, 3) have a defined relationship 

to climate, and 4) be scalable; the team should 5) build on or augment existing 

agency efforts (in other words, consider existing datasets, data availability, and 

data use) and 6) consider both current and leading indicators. 

Template

The template provided to each team consisted of specific questions about the 

decision criteria and other information for each indicator. Because this template 

was a fundamental part of our methods and documentation, we provide the 

content of the template here:

1. Summary About the Indicator (Text)

a) Additional descriptive text, b) Data sources, c) What is the link to 

climate variability and change or relevance? d) What are the drivers of this 

indicator, and what are their impacts? e) Has this indicator been used as an 

indicator by anyone else; if so, by whom, and how was it used and when 

was it initiated? f) Relevance to management decisions, g) Other indicators 

considered but not recommended at this time, h) Usefulness for education 

purposes.

2. Data Availability

a) Length of records of dataset, b) Metadata, c) Stability/Longevity of 

dataset and indicator, d) Notes about the data (recent changes in analysis 

or collection methods), e) Spatial and temporal scalability, f) Models/

Scenarios (if leading indicator or based on model output). 
Recommendations for the U.S. National Climate Assessment Indicators System 5

3. Details About the Indicator

a) Type of indicator (current, leading, both; if both, need to describe 

data/models and methods separately because of different approaches), b) 

Geographic scope and scale of analysis, c) Approach (e.g., single measure, 

composite), d) Purposes and conceptual framework, e) Composition and 

methodology; f) Scientific validity of indicator, g) What are the plans for 

further development of the indicator?

4. Considerations for Selection of Indicator

a) Advantages, b) Disadvantages

5. Literature Cited 

6. Other Resources

Literature cited and other resources may include Web site links, peerreviewed publications about the indicator, and contact information about 

the data or indicator.

Janetos et al. (2012: 5) provide the definitions for current and leading indicators: 

“Current indicators describe current status and trends relative to a historical 

baseline. Leading indicators are used to project changes in important parameters 

that could result from possible climate changes.” In other words, leading climaterelated indicators foretell that climate is changing. To describe some phenomena, 

a single indicator may be adequate, or multiple indicators may be necessary, 

or a composite of multiple indicators may prove ideal. A composite indicator 

is typically based on a theoretical framework in which single indicators are 

combined in a way to reflect what is being measured. The template concluded 

with a summary table (see Table 1) for the recommended indicator; we present 

this table as an illustration of one step of our methods. For full transparency of 

the information we developed and considered in our process, and to provide 

details for those developing a Web portal of the indicators, the completed 

templates and summary tables are provided in Appendix 1.

Additional Decision Criteria

In addition to the guidance provided to the team on the process for identifying 

recommended indicators, the forest team adopted a strategy after some discussion 

early in the effort. We agreed that 1) the indicators should cover the range of the 

proposed conceptual model to the extent possible, 2) our indicator set should 

feature at least a few indicators that could currently be reported on, 3) we should 

consider indicators that were used for other purposes such as sustainability, 

but that also are related to climate change, 4) we should consider indicators 

needed for information to interpret climate change effects related to forest such 

as the extent of forest, and 5) we should consider important indicators that 

could require much more development and data collection, but that had notable 

potential. In some cases practical issues associated with data availability and 

tractability helped determine our choice of indicators. The resulting indicator 

set was designed to be updated as new information and research results become 

available, rather than a permanent set. In other words, we focused on providing 

a first version of indicators, some of which could be incorporated in a pilot Web 
6 Indicators of Climate Impacts for Forests:

Table 1.—Summary of information for decision criteria completed for one of the resulting 

recommended indicators (Human influence on Climate Domain via Forest)a

Decision criterion Ranking Justification 

Link to conceptual framework Best Explicit link to conceptual model (arrows 4 and 

11)

Defined relationship to climate, feedbacks, 

or impacts

Best Direct link to human response to climate 

change and carbon stocks and fluxes resulting 

from human activity

Spatial scalability Sufficient National unit of analysis. Some components 

may be scalable to regional and state levels.

Temporal scalability Best Annual time series data are available.

Of national (not necessarily nationwide) 

significance? Should link to the conceptual 

model

Best Strong link to influences in atmospheric 

carbon concentration and forest conditions. 

Responsive to national climate policy as it 

relates to energy production.

Relevance to management decisions Best Tracks U.S. industry’s response

Usefulness for educational purposes Sufficient Information is useful but could be more fully 

described in relation to other categories such 

as emissions.

Is it a leading indicator? Needs 

improvement

Not proposed as a leading indicator

Builds on existing data sources Best Indicator already developed and published

Builds on existing indicator products Best Indicator already exists in Montreal Process 

and national reports

If new indicator proposed, likelihood of 

development and testing within 1 year 

given existing funding sources (no funding 

available from USGCRP or indicator system 

team)

Existing 

indicator, but 

could use some 

attention

Existing indicator reported on for sustainability. 

Usefulness in terms of climate and how it could 

contribute to full suite of NCA indicators could 

be more fully developed, but additional funding 

is unlikely.

Stability/Longevity of dataset Sufficient Domestic portion of indicator has already been 

successfully produced for two report iterations, 

but indicator is dependent on disparate data 

reporting streams.

Stability/Longevity of indicator Sufficient See preceding (stability of dataset).

Scientific validity of indicator Sufficient Previous iterations have been subject to peer 

review.

Data publicly available and transparent Sufficient Data are available, but analysis and 

transformation are required.

Indicator methods fully transparent and 

documented

Best Full documentation of previous indicator 

development is available.

a Acronyms: NCA = National Climate Assessment; USGCRP = U.S. Global Change Research Program
Recommendations for the U.S. National Climate Assessment Indicators System 7

portal that decisionmakers and the public could visit and thereby concretely 

experience the usefulness of the indicators system. We also provide information 

that could lead scientists to work on indicators more relevant to future indicator 

efforts.

Based on our collective experience, we recognized that different technological 

methods may be in current use that could provide perhaps conflicting data for 

the same indicator. Methods typically have advantages and disadvantages. Often 

the difference is a combination of what various audiences need and the perceived 

maturity of the methods. Therefore, we decided to adopt a broader definition 

of indicators, one that encompasses metrics. In some approaches, indicators are 

defined as the measurable factors of interest, and the term “metric” is not used. 

In our approach, the term “indicator” refers to the factor of interest, and the 

term “metric” describes the specific item that is the measure. For example, the 

extent of forest is an important indicator because location is needed to ensure 

the area being analyzed is forest. However, it is also important to delineate the 

location of forestland, grasslands, and croplands (agriculture), simply to help 

define these individual categories in the indicators system, including the shifts 

of land between these categories as vegetation changes. The extent of forest can 

be determined by a remote sensing approach, or by a forest inventory approach, 

which uses ground plots (and traditionally uses a second phase involving aerial 

photographs or remote sensing). One approach produces extent of forest by land 

cover, whereas the other approach results in extent by land use. We describe and 

present each as a possible metric (measure) of the indicator forest extent.

Domains of the National Climate Assessment Indicator System

The forest team is one of many indicator teams working on the suite of NCA 

indicators. To better understand this context, we developed a conceptual model 

to represent the overall system from our point of view. Our conceptual model 

(Fig. 1) shows all the categories of indicators included in the initially proposed 

indicator set in five domains: 1) climate, 2) forest, 3) other land use, 4) other 

environmental, and 5) human. In addition, categories can span more than one 

domain. We call the categories which include multiple domains phenomena. 

An example of a phenomenon is phenology. After the completion of most of 

our study, a biodiversity team was added to the effort. Biodiversity is also a 

phenomenon, and if we added it to Figure 1, it would be shown in a box parallel 

to phenology.

Forestland is dynamic because over time it can be converted to or from 

other land uses (Other Land Use Domain), and there can be changes in the 

structure and function of ecosystems within the Forest Domain as well. We 

focused on indicators that are strongly related to the Forest Domain. If we 

identified an indicator with strong links to other teams, we spoke with other 

teams to encourage them to recommend the indicator. If the other teams do 

not recommend the indicator, the forest team needs to reconsider including the 

indicator. 
8 Indicators of Climate Impacts for Forests:

Figure 1.―The Forest Indicator Technical Team’s conceptual model showing how the team viewed the role of forests 

in relation to other National Climate Assessment indicator categories (teams).

An advantage of having NCA teams focused on cross-cutting phenomena is that 

the resulting indicators in theory would be seamless and consistent across land 

uses and thus facilitate integrated consideration of adaptation and mitigation 

options across ecosystem boundaries. A disadvantage is that some methods 

may be more accurate (and therefore more applicable) for some land uses or 

sectors than for others. Coordinating with the relevant teams would ensure broad 

usefulness of the indicators.

Definition of Forestland

Not all land with trees is considered forest. We adopt the definition of forestland 

used by the U.S. Forest Service’s Forest Inventory and Analysis (FIA) program to 

compile forest inventory statistics for the nation (Oswalt et al. 2014):
Recommendations for the U.S. National Climate Assessment Indicators System 9

Land at least 120 feet wide and 1 acre in size with at least 10 percent 

cover (or equivalent stocking) by live trees, including land that 

formerly had such tree cover and that will be naturally or artificially 

regenerated. Trees are woody plants having a more or less erect 

perennial stem(s) capable of achieving at least 3 inches (7.6 cm) 

in diameter at breast height, or 5 inches (12.7 cm) diameter at root 

collar, and a height of 16.4 feet (5 meters) at maturity in situ. The 

definition here includes all areas recently having such conditions and 

currently regenerating or capable of attaining such condition in the 

near future. Forestland also includes transition zones, such as area 

between forest and nonforest land that has at least 10 percent cover 

(or equivalent stocking) with live trees and forest area adjacent to 

urban and built-up land. Unimproved roads and trails, streams, and 

clearings in forest areas are classified as forest if they are less than 

120 feet (37 meters) wide or an acre (0.4 hectare) in size. Forestland 

does not include land that is predominantly under agricultural or 

urban land use. 

Note that lands with tree cover such as urban land are not considered forestland, 

whereas areas of forest that have been harvested but that are not being converted 

to other land cover or uses continue to be designated as forest. Forest indicators 

currently do not include urban forests unless explicitly noted otherwise. We 

recognize, however, that urban forest represents a notable and growing gap in 

An extensive windbreak system. This is an example of agroforestry practices that do not 

generally meet the definition of forest even though they use trees and provide a variety of 

forest-derived benefits in support of other land. Photo by Natural Resources Conservation 

Service.
10 Indicators of Climate Impacts for Forests:

our understanding of the U.S. landscape. Urban areas in the conterminous United 

States covered 60 million acres (3.1 percent of the land area) in 2000, and if 

growth patterns continue, urban land is projected to reach 8.1 percent of the land 

base by 2050, with a considerable amount of this increase occurring on existing 

forestland (Nowak et al. 2013). In 2005, tree cover within urban areas was 

estimated at 35.0 percent (Nowak et al. 2013). 

On agricultural land in the United States, trees in agroforestry systems provide 

forest-derived services which can support more climate-resilient productive 

agricultural operations and landscapes (Schoeneberger et al. 2012) or other 

nonforest uses. For example, agroforestry practices across the rural/urban 

continuum may serve multiple purposes, such as creating wildlife corridors 

across highly fragmented agricultural landscapes or treating stormwater runoff. 

There is little information about the extent and type of agroforestry practices 

occurring in the United States because they generally occur on nonforest land 

and are not included in operational forest inventories. At the same time, the 

agricultural community tends to focus on crop production and may not collect 

adequate information about the tree portion of their operations. These systems of 

increasing human–forest and human–tree interaction and their associated climate 

change impacts warrant additional consideration in an indicator system in the 

future. 

In summary, indicators in the forest category focus on the Forest Domain, and 

we also consider important forest indicators with strong links to other domains 

and categories. In the future, more formal consideration should be given to urban 

forest and settlements as well as to agroforestry systems.

RESULTS

Conceptual Model for Forest Indicators

Our forest indicator conceptual model (Fig. 2) provides one way of looking 

at the key components of forest ecosystems as they relate to important drivers 

of change within these ecosystems. The model depicts forests assuming a 

broad-scale analysis for identification of indicators. The boxes outlined in 

blue represent the four main domains affecting the Forest Domain, which 

is represented in the center (shaded) box. The domains are: Climate, Other 

Environmental, Other Land Use (other than forest), and Human.

The three primary drivers of forest response are shown in the orange boxes. 

These “drivers” can directly or indirectly affect forest extent and ecosystem 

structure and function, and ultimately ecosystem services and goods that are 
Recommendations for the U.S. National Climate Assessment Indicators System 11

Figure 2.―The Forest Indicator Technical Team’s conceptual model of the Forest Domain and important drivers and 

links. See text for explanation of numbered arrows.

provided by forestland. Drivers are climate (e.g., changes in variability and 

extremes of temperature and precipitation), other environmental factors 

(e.g., nutrients, light, disturbance, pollution), and socioeconomic factors 

(e.g., population, culture, governance, risk, management, response strategies 

of adaptation and mitigation). All three categories of drivers can affect the 

Forest Domain directly (represented by orange arrows) or indirectly through 

interactions with other drivers (represented by blue arrows). Thus, feedbacks 

mediated by each driver are implicitly included in the conceptual model. Within 

the Human Domain, people gather and assess information about all domains, 

along with risks to those domains associated with climate variability and change. 

Based on these risks, adaptation and mitigation response strategies are formed 

and response actions can then feed back to the Forest and other Domains. Also 

within the Human Domain, activities that depend on preferences, such as outdoor 

recreation, may be derived from the Forest Domain and in turn those activities 

may affect the Forest Domain.
12 Indicators of Climate Impacts for Forests:

Different climatic, anthropogenic, and natural drivers can cause areas to 

transition between land use types. Forestland can be converted to agriculture or 

agroforestry due to socioeconomic drivers. Conversely, abandoned rangeland or 

agriculture land can change back to forestland over time. These different land 

uses can be dynamic in a given area depending on climatic, other environmental, 

and socioeconomic drivers affecting forest ecosystems. 

Major drivers of forest change are climate variability and change, other 

environmental change such as disturbances (e.g., wildfire, and natural forest 

growth and dynamics), and socioeconomic drivers that result in development 

or change which creates land use other than forest. As a result, forest extent, 

structure, and function, ecosystem services and goods, and disturbance 

effects are major attributes of forestland, interacting over time and across the 

landscape of the Forest Domain. These components encapsulate major aspects, 

relationships, and characteristics of forest systems that are and will be affected 

by environmental change including climate change. One example of a driver is 

a strong hurricane (disturbance) that blows down or breaks off the tops of many 

trees (structure), some of which are harvested (goods), thereby affecting forest 

growth (function) and carbon sequestration (service), and increasing biomass 

of dead wood (structure); some of the disturbed forest area may potentially be 

completely cleared and developed, reducing forest area (extent). Extent defines 

the area designated as forestland, which is dynamic and can change to and from 

other land use types (indicated by arrow 13 between Forest Domain and Other 

Land Use Domain). Structure and function are core characteristics of forestland. 

Ecosystem services and goods are measures of the global- to national- to locallevel environmental and societal benefits provided by forestland. Disturbances 

permeate the Forest Domain and their effects show up in the attributes extent, 

structure and function, and ecosystem services and goods.

Arrows define different relationships and feedbacks between domains and 

components within the Forest Domain. Arrows are defined as follows:

Arrow 1

This arrow illustrates ways in which climate affects the Human Domain through 

forest ecosystem responses. One example of a climate event with major effects is 

“heat waves.” A heat wave may directly affect the Human Domain by increasing 

heat-related fatalities, but may also indirectly affect the Human Domain through 

impacts on some aspect of the forest ecosystem structure, function, and services. 

In this example, an indirect effect is increased tree mortality, which then affects 

the Human Domain through reduced carbon sequestration, increased fuel for 

wildfires, and reduced value of timber. Other examples are the indirect effects 

that climate may have on pollen production in ragweed (Ambrosia spp.), which 

aggravates allergies and affects human health, and the direct effects that changes 

in snow cover have on forest-based recreation activities such as cross-country 

skiing. 
Recommendations for the U.S. National Climate Assessment Indicators System 13

Arrow 2

This arrow represents Human Domain drivers that indirectly influence climate 

through forest management or policy decisions. These drivers include those that 

influence deforestation (feedback loop that increases CO2 emissions), and those 

that influence the use of harvested wood to produce bioenergy and renewable 

materials (feedback loop that mitigates CO2 emissions).

Arrows 3, 4, and 5 and Overarching Disturbance Effects

Forest extent, structure and function, and ecosystem services and goods are 

important attributes of the Forest Domain, interacting over time and across the 

landscape. Disturbance processes combine with endogenous growth, mortality, 

and recruitment to help determine the nature of these three components in 

a dynamic fashion. Forest area (extent) is determined by definition, and the 

delineated forest is additionally characterized by structure and its ability to 

function as a forest (arrow 4). Due to changes in market prices or opportunities, 

for example, the production of goods may result in conversion of nonforest 

to forestland or of forestland to nonforest (arrow 3, with land transferring 

through arrow 13), and changes in forest extent will affect the amount of 

ecosystem services and goods. Production of goods or recognition of services 

such as through designating protected areas can affect numbers and sizes of 

trees (structure) by changes in harvest or by planting or the growth of forests 

(function), perhaps by fertilization (arrow 5). Large-scale disturbances affect 

structure and function, can affect extent, and affect ecosystem services and 

goods. 

Arrow 6

The Climate Domain affects the Forest Domain system through physical drivers 

such as temperature, precipitation, and atmospheric conditions, and there are 

interacting feedbacks from the Forest Domain to the Climate Domain through 

changes in evapotranspiration, trace gas fluxes, and albedo. 

Arrows 7, 9, and 10

Other environmental drivers also interact with the Forest Domain directly and 

indirectly; drivers in the Other Environmental Domain additionally interact with 

the Climate Domain and Human Domain. Heightened frequency or intensity of 

forest fires owing to increased fuel loading from fire suppression activities is an 

example of an interaction between Other Environmental and Forest Domains 

(arrow 7). Chemicals released to the atmosphere resulting from activities in the 

Human Domain affect the Other Environmental Domain (arrow 10). Sunlight 

in the Other Environmental Domain can act on certain chemicals producing, 

for example, ozone, which in turn affects human health in the Human Domain. 

Black carbon from forest fires (arrow 7) can cause atmospheric warming when it 

is in the atmosphere (arrow 9), and absorbs more solar radiation when deposited 

on snow, leading to accelerated melting of the snow. The Other Environmental 

Domain interactions with the Climate Domain and Human Domain serve as a 

pathway through which Climate Domain drivers, Human Domain drivers, and the 

Forest Domain system may interact indirectly or through feedback loops.
14 Indicators of Climate Impacts for Forests:

Arrow 8

Interacting components of the Forest Domain are affected by various 

socioeconomic drivers from the Human Domain such as management activities. 

These activities include response strategies to climate change such as adaptation 

and mitigation measures and responses to other environmental drivers (arrow 10) 

and other land use (arrow 12). Complex socioeconomic drivers in the Human 

Domain such as outdoor recreation may link to many arrows, domains, and 

attributes. Management takes into account risks, or at least perceived risks, to 

forestland and the larger human population while acting within the confines 

imposed by cultural norms and governance. 

Arrows 11 and 12

Like the Forest Domain, the Other Land Use Domain is influenced by and 

interacts with both the Climate Domain and Human Domain. It is affected by 

climatic drivers such as temperature and precipitation and by Human Domain 

drivers such as management, response strategies, and use, with interacting 

feedbacks to these domains. 

Arrow 13

Conversions between land use types due to drivers including development 

(e.g., conversion of forest to housing lots), management (e.g., plantations), and 

ecological succession are captured by arrow 13. The Forest Domain and Other 

Land Use Domain are not static but change as they are affected by each other, 

and by the other three domains: Climate, Other Environmental, and Human. 

The complexity of the NCA indicator system effort (as well as the strengths and 

limits of our conceptual model) is easily revealed when using our conceptual 

model for complex socioeconomic activities and drivers in the Human Domain 

that are linked to the Forest Domain, such as outdoor recreation. For example, an 

outdoor recreation activity such as developed skiing that is affected positively by 

climate will probably cause forest to be converted to other land use, will affect 

forest structure, is an ecosystem service and good, and may affect the Other 

Environmental Domain in terms of pollution. Discussing individual activities 

when using this conceptual model may involve arrows 3, 4, 5, 6, 8, 11, 12, and 

13, all domains, and the attributes in the Forest Domain.

Recommended Indicators

To ensure a manageable suite of indicators across all teams, each team was 

asked to identify about 10 or fewer indicators in this effort. We recommend 

11 indicators (Table 2). Each indicator is described in the next section, with 

additional information about each in Appendix 1.
Recommendations for the U.S. National Climate Assessment Indicators System 15

Table 2.—Recommended indicators of climate impacts for forests

Domain Indicator group Indicator title Brief description

Forest Extent Forestland area and extent Forestland area as defined by land use or 

forest area as defined by forest cover

Structure and 

function

Forest biomass density Calculated from U.S. Forest Service, Forest 

Inventory and Analysis (FIA) program data

Ecosystem services Diversity/abundance of 

forest-associated floral and 

faunal species

Assessing change in forest plant diversity 

through information from FIA; assessing 

change in forest faunal species through 

information from U.S. Geological Survey 

Breeding Bird Survey data to track avian 

population trends

Structure and 

function

Forest growth/productivity Net annual growth calculated from field data 

from FIA and moderate resolution imaging 

spectroradiometer (MODIS) for forest net 

primary productivity

Disturbance Wildfire effects Burned area with supplemental information 

on number of large fires and burn severity

Disturbance Forest insect and disease 

damage

Area affected by insects and diseases

Biophysical Water balance deficit—an 

indicator of “plant-relevant” 

drought

The difference between potential and actual 

evapotranspiration as estimated from 

surface climate observations and vegetation 

data

Human 

and Forest

Extent/ 

Socioeconomic

U.S. wildland-urban 

interface

Area and population of wildland area 

containing human residents and structures 

under risk of wildfire as defined by 

combining information from U.S. Census 

Bureau data and National Land Cover 

Dataset

Climate impacts on 

the Human Domain 

via Forest

Cost to mitigate wildfire 

risk

Expenditures on fire suppression activity, 

expenditures on forest treatments to mitigate 

fire risk, total payments for insurance 

premiums for policies against damage from 

forest fire

Human Domain 

influences on the 

Climate Domain via 

Forest

Energy produced from 

forest-based biomass

Energy produced, domestically or in export 

markets, from biomass harvested from U.S. 

forests in British thermal units per year or 

carbon dioxide equivalent

Socioeconomic/

Ecosystem services

Outdoor recreation Number of U.S. ski/snowboarder visits, 

revenue of ski areas, participation days in 

cross-country skiing
16 Indicators of Climate Impacts for Forests:

Table 3.—Indicators recommended by the Forest Indicator Technical Team to other technical teams

Team Indicator Descriptiona

Physical climate Temperature A measure of temperature, either station measurements or a 

modeled and gridded interpolation such as PRISM (PRISM 

Climate Group 2015)

Precipitation A measure of precipitation, either station measurements or a 

modeled and gridded interpolation such as PRISM (PRISM 

Climate Group 2015)

Wind Either a monthly wind climatology or wind direction and speed 

from reanalysis

Physical climate or 

Water cycle

Drought (in addition 

to the water balance 

deficit)

Measurements of soil moisture or drought indices, such as the 

Palmer Drought Severity Index or Standardized Precipitation 

Index

Health Health impacts related 

to forests

Asthma and related respiratory impacts and health issues, such 

as Lyme disease, strongly related to forest

Phenology Senescence Possibly measured either from satellites such as MODIS or VIIRS 

or through the National Phenology Network

Budburst Possibly measured either from satellites such as MODIS or VIIRS 

or through the National Phenology Network

a Acronyms: PRISM = parameter-elevation regressions on independent slopes model; MODIS = moderate resolution imaging 

spectroradiometer; VIIRS = visible infrared radiometer suite

We identified other indicators of importance to forestland but that seemed more 

relevant to the other teams. We encouraged other teams to consider and include 

those indicators (see Table 3). Due to direction from the coordinators of the 

overall effort, we limited our discussion of adaptation response indicators related 

to forest. Once the work of all the teams is completed, the next priority step 

would be to revisit the entire list of indicators that could be of most relevance to 

forest, and reconsider our core list of recommended indicators and metrics. Some 

metrics for a given forest indicator may work better than others. The criteria to 

identify and decide on the best indicators that are relevant to multiple teams need 

to be clearly determined before evaluating the indicators. 

Important Links Between the Forest Team and Other Teams 

We also identified multiple important links between forest and categories 

represented by other teams. Wildfire indicators are relevant to the forest, 

grassland, and phenology teams. The phenology and forest teams have developed 

slightly different metrics for a wildfire indicator to meet different stakeholders’ 

needs. The forest team also sees many areas for collaboration with the phenology 

team besides those already mentioned. Species migrations and seasonal 

distributions of animals (namely birds), spring indices such as first leaf and 

first bloom especially for forest species, and phenological measurements from 

satellites are all phenology indicators that the forest team supports and endorses. 
Recommendations for the U.S. National Climate Assessment Indicators System 17

The grassland and forest teams (and perhaps other teams) have a shared interest 

in indicators of primary ecosystem productivity. The vegetation productivity 

indicator identified by the grassland team may be meaningful to forest, but 

current discussion indicates that optimal approaches differ for the two land uses. 

Productivity is a major aspect of forestland, and a shared indicator potentially 

can be developed by using satellite data from the moderate resolution imaging 

spectroradiometer (MODIS) or another approach. 

Drought has been identified as an important topic by the forest, agriculture, 

physical climate, and water cycle teams and has relevance to the freshwater and 

grassland teams as well. Additional work is needed to determine the best drought 

indicator and measurements most critical to decisionmakers in these various 

sectors. Alternatively, several indicators of drought may be needed to be most 

informative for specific teams.

The freshwater ecosystems team has overlapping interests with all the terrestrial 

land use teams. Topics of interest to both the freshwater and forest teams include 

wetland and riparian systems in forested landscapes and ecological aspects of 

these systems, such as biodiversity or methane generation. Indicators related to 

these and other topics merit discussion between the freshwater and forest teams.

Freshwater forested landscape illustrating need for links between teams. Photo by Sarah 

M. Anderson, Washington State University, used with permission.
18 Indicators of Climate Impacts for Forests:

Several indicators representative of the physical climate system are highly 

important to forest ecosystems. Some of these indicators are temperature, 

precipitation, and wind measurements. In future efforts, the forest team sees 

advantages in working with the physical climate team to ensure that indicators 

selected by the physical climate team will help support the forest team and our 

specialized issues and specific decisionmakers.

Last, the forest team shares terrestrial emission indicators for CO2 and non-CO2

emissions with the mitigation and greenhouse gas sources and sinks team. The 

land use and land management indicator proposed by the mitigation team also 

has details highly pertinent to the forest ecosystems. Forests currently serve as a 

major CO2 sink. Covering one-third of the United States, they sequester and store 

large amounts of carbon, and are therefore important to consider when estimating 

terrestrial emissions and sequestration of greenhouse gases. The forest team 

would prefer to endorse this indicator to be housed within the mitigation and 

greenhouse gas sources and sinks team. 

Description of Recommended Forest Indicators

In this section, we present summary descriptions of each indicator, and 

the metrics for each recommended indicator. Although we would prefer to 

recommend fully functional indicators for this effort, many of the recommended 

indicators need additional work before they can be considered operational 

because this is a first effort. We have generally arranged the indicators so that the 

ones nearer the front are more developed and could be used for a pilot indicator 

Web site.

For each indicator we provide a figure or table of example data to better convey 

our recommendations. Some of these examples may be ready to use as an 

indicator in a Web portal system; others need more work, including one based 

on hypothetical data. Additional details for each indicator are presented in 

Appendix 1, following the template that the NCA indicator system coordinating 

team asked each team to fill out.
Recommendations for the U.S. National Climate Assessment Indicators System 19

Forest Extent Indicator: Forestland Area and Extent

Major contributors: Linda S. Heath and Alan Lucier

Metrics: Forestland area by land use, Forest area based on forest cover only 

Extent of forest is important as an indicator partly because it defines forest 

boundaries and area. Extent of forestland can vary due to differences in definition 

or estimation approach, and can be locally dynamic due to human activities. 

Climate affects forest extent directly (e.g., long-term changes in climate may alter 

the continental forest distribution) particularly in climate-limited regimes such as 

alpine treeline or grassland/forest ecotones, and indirectly (for example, climate 

may influence insect outbreaks that cause broad-scale tree mortality). Specific 

management strategies to mitigate or adapt to climate change effects (e.g., fuels 

management, introduction of new tree hybrids, protected area establishment) 

could be informed by improved tracking of forest area.

The main metric is based on land use because this is the approach for the official 

forest statistics for the United States, which come from FIA data (U.S. Forest 

Service 2013). This approach uses the same definition of forestland as in the U.S. 

national greenhouse gas inventories submitted to the United Nations Framework 

Convention on Climate Change. Forest area in the United States was about 

751 million acres (304 million hectares) in 2010 (U.S. Forest Service 2011). 

This is a mature metric, although it continues to be be improved. In practice, the 

estimation procedures may include observations that form the basis of the second 

metric.

The National Land Cover Dataset (NLCD) (Homer et al. 2012) based on remote 

sensing provides a second, geospatial metric of forest area, which is defined 

by forest (tree) cover (see Fig. 3). Some types of forest as defined by land use 

may be labeled “shrubland” or “woody wetland” in the NLCD, and some areas 

designated forest based on forest cover may be defined as nonforest based 

on land use. A remote sensing approach has advantages, such as wall-to-wall 

consistency and identification of changes in gross forest cover. However, this 

approach is computationally intensive, and interpretation can still be misleading, 

especially regarding temporary loss of cover that is misidentified as conversion to 

nonforest (Hansen et al. 2010, Nowak and Greenfield 2010). In addition, the level 

of consistency in the results may not be as high as expected, especially across 

forest types. Estimation procedures for this metric continue to be improved.
20 Indicators of Climate Impacts for Forests:

Figure 3.—Example map of forest and other land cover classes using the National Land Cover Dataset (MultiResolution Land Characteristics Consortium 2014), which could be used for this metric. Some areas defined as 

woody wetlands may be forestland and some areas may be shrubland. Conterminous U.S. map associated with the 

year 2006; Alaska, Hawaii, and Puerto Rico associated with the year 2001.

Structure and Function Indicator: Forest Biomass Density 

Major contributor: Linda S. Heath

Metrics: Aboveground live tree biomass per unit area, Dead wood mass per unit area 

The indicator group Structure and function was identified in our conceptual 

model because these two features are often mentioned together. Because we can 

propose only a limited number of indicators, we chose aboveground live biomass 

of trees per unit area as the indicator even though it represents only structure, not 

function. Climate influences may result in a greater amount of dead biomass in 

relation to live biomass, so a second important metric is biomass in dead wood 
Recommendations for the U.S. National Climate Assessment Indicators System 21

per unit area. Biomass in terms of dry weight of live and dead trees is about 50 

percent carbon, so carbon can be estimated by multiplying dry weight biomass by 

50 percent. As trees age, they accrue biomass through photosynthesis, and store 

mass and therefore carbon in their wood. Dead wood emits carbon as it decays. 

The use of aboveground live biomass density (tons biomass per acre or metric 

tons biomass per hectare) as a metric of forest structure conveys information 

related not only to climate mitigation in terms of forest stocks, but also to 

potential availability of biomass for bioenergy, which can be used to produce 

energy as a substitute for fossil fuel. Biomass amounts are affected by 

climate, and climate variability can affect mortality, growth, regeneration, and 

decomposition; therefore, mass of both live trees and dead wood is important. 

Demand for biomass to lower overall emissions may result in decreased stocks of 

biomass.

Availability of data on biomass of trees in forests allows for biomass maps. As an 

example that could be used for this metric, forest aboveground live-tree biomass 

carbon stock per unit area by county shown in Figure 4 (U.S. Forest Service 

2011), but estimates are relevant at all geographic sales, from national to local. 

Live biomass density or dead biomass density by county could be calculated 

annually or periodically. These estimates are calculated from FIA data (U.S. 

Forest Service 2013). Data for both metrics are available, and continue to be 

updated and improved.

Figure 4.―Possible example metric of forest aboveground live-tree biomass: carbon stock density (metric tons of CO2

equivalent per hectare) by county for the United States, 2006. Results are reported only for counties with more than 

5 percent forestland, because small areas can be highly influenced by a few unusual observations. Source: U.S. 

Forest Service (2011).
22 Indicators of Climate Impacts for Forests:

Ecosystem Services Indicator: Diversity/Abundance of Forest-associated Floral and 

Faunal Species 

Major contributors: Kevin M. Potter (floral spp.) and Jinelle Sperry (faunal spp.)

Metrics: Forest tree biodiversity status and trends, Forest fauna biodiversity status and trends 

Forest ecosystems serve as habitat for a wide range of floral and faunal species; 

consequently, climate-induced alterations in forest structure could have profound 

implications for forest-associated species. In turn, biodiversity conveys many 

functional benefits to forest ecosystems, including reduced susceptibility to 

invasive species after disturbance and enhanced ecosystem reliability (Balvanera 

et al. 2006). Research also has linked biodiversity to ecosystem primary 

productivity (Cardinale et al. 2007). Robust indicators of change in forest 

biodiversity will therefore be important for tracking forest community response 

to climate change. Dissimilarities in life history and population characteristics 

between plants and animals, in addition to differences in data availability, 

will require different approaches for tracking changes in biodiversity for each 

group. These metrics require additional work, especially for faunal species. We 

anticipate that these two metrics will be distinct enough that they each may have 

to be made a distinct indicator. When team efforts are reconciled, discussion with 

the biodiversity team would be useful for these indicators.

The foundation for assessing change in forest floral diversity is information 

available through the FIA program (Fig. 5). Spatially explicit analyses of changes 

in tree species diversity over time are therefore possible across much of the 

United States. Plant species are expected to respond in one of three ways to the 

numerous climate change effects that could push their current habitat out of their 

tolerance limits: 1) persistence in situ if within species’ tolerance limits, 2) range 

shift, or 3) local extirpation (Davis et al. 2005). Indicators of change in seedling 

diversity are particularly useful (Potter and Woodall 2012). 

It would be meaningful to consider several other possible indicators using the 

FIA data, including change in importance value of native tree species, mortality 

of mature native trees, and richness or cover of nonnative invasive plant species. 

Because we are limited in the number of indicators we can recommend, however, 

we propose the fundamental metric of tree biodiversity change.

In terms of metrics of biodiversity change for fauna, measures of forest-dwelling 

animals tend to focus on tracking trends in population and conservation status. 

Climate change can influence biodiversity through a variety of mechanisms 

including shifts in geographic range, phenological changes, and physiological 

stress (Thuiller 2007). Assessing trends in population would allow for a dynamic 

examination of possible climate change effects and could also help in studies 

of species range expansions and contractions (e.g., Hitch and Leberg 2007). 

The U.S. Geological Survey’s (USGS’s) national Breeding Bird Survey may 

currently offer the greatest potential (Fig. 6). Teasing out the responses of faunal 

populations to changes in climate versus changes in other factors will probably 

be challenging regardless of the data, so we expect more research will be needed 

to have confidence in the results. 
Recommendations for the U.S. National Climate Assessment Indicators System 23

Figure 5.―Forest floral diversity (mean number of tree species per plot) by county, based on U.S. Forest Service, 

Forest Inventory and Analysis (FIA) data. This is an example of a potential illustration.

Figure 6.―Trends (percentage change) in number of birds counted in forest and other 

land use habitat based on, in part, the U.S. Geological Survey’s Breeding Bird Survey data 

(figure from North American Bird Conservation Initiative, U.S. Committee 2014). This is 

only an example of how the final metric could be displayed. 
24 Indicators of Climate Impacts for Forests:

Structure and Function Indicator: Forest Growth/Productivity 

Major contributors: Linda S. Heath and Jeffrey G. Masek

Metrics: Net annual forest growth, Forest net primary productivity 

Net annual growth can be estimated from FIA data, and is defined as the 

average annual net increase in volume of trees during the period between 

inventories2 (Oswalt et al. 2014). The volume of trees that died or that became 

nonmerchantable over the period is subtracted from the growth only of live trees, 

which means net growth may be a negative number. Net growth is important 

because it can be affected by changes in temperature, water availability, length 

of growing season, and increases in atmospheric CO2 . Silvicultural activities 

(e.g., fertilization, thinning, regeneration strategy) and ecological states can also 

affect growth, so results should be carefully interpreted. Net annual growth in 

U.S. forests totaled nearly 26.7 billion cubic feet in 2006, which is about threeand-one-half times the rate of mortality (Oswalt et al. 2014). Figure 7 is an 

example graphic of net annual growth.

We also propose that net primary productivity (NPP) estimated by using a remote 

sensing (i.e., MODIS) approach also be presented for forests, as a cross-cutting 

indicator that the phenology team could consider (see USGS, Land Processes 

Distributed Active Archive Center 2015 for observations). The MODIS product 

for gross primary productivity (GPP) and NPP, called MCD17, is based on a 

light-use efficiency model for photosynthesis, taking into account the satellitebased fraction of photosynthetically active radiation (fPAR) and leaf area. 

Productivity is modulated by water availability (e.g., vapor pressure deficit) 

derived from meteorological inputs (Running et al. 2004). There are a number 

of studies of ways to improve the standard MODIS NPP product for forests, and 

these should be considered (Turner et al. 2006). As an indicator, NPP can be more 

closely related to climate than can GPP because NPP records the biologic activity 

of forests, and depends directly on temperature, precipitation, and available solar 

radiation. Both metrics are available, and continue to be updated. 

2 Specifically, components of net annual growth include “the increment in net volume 

of trees at the beginning of the specific year surviving to its end, plus the net volume of 

trees reaching the minimum size class during the year, minus the volume of trees that 

died during the year and minus the net volume of trees that became cull trees during the 

year” (Oswalt et al. 2014).
Recommendations for the U.S. National Climate Assessment Indicators System 25

Figure 7.―Average net annual growing-stock growth per acre (cubic feet per acre per 

year) by U.S. region and inventory year (Oswalt et al. 2014). This is an example display 

for this metric. 

Disturbance Indicator: Wildfire Effects 

Major contributors: David L. Peterson and Linda S. Heath

Metrics: Burned area, Number of large fires, Fire severity 

Wildfire is one of the most significant disturbance agents in U.S. forest and 

rangeland ecosystems. It can drive changes in forest composition, structure, 

and function. Wildfire management is arguably the greatest current challenge 

for federal land management in the Western United States with respect both to 

vegetation management and restoration issues, and to financial expenditures for 

fire suppression and hazardous fuel reduction. Sufficient data exist to use wildfire 

as an indicator, but several metrics need to be considered to establish clear 

relationships between fire characteristics and climatic parameters. Observations 

are available from the National Interagency Fire Center (2015) and from the 

Monitoring Trends in Burn Severity (2013) project. The methods exist to produce 

these metrics, and they are currently available.

0

25

50

75

100

1952 1976 1986 1996 2006 2011

Cubic feet per acre per year

Year

Pacific Coast

South

North

Rocky Mountain
26 Indicators of Climate Impacts for Forests:

Burned area is a simple summation for a given area and time period, can be 

displayed on a map, and has been shown to be related to climate. Empirical 

analysis of annual area burned (1916 to 2003) for federal land in the West 

projected that for a temperature increase of 1.6 °C (2.8 °F), burned area 

will increase two to three times in most states. Number of large fires can be 

determined by summing occurrence at different threshold sizes. No particular 

threshold for “large” is assumed at this time. Fire severity typically is a 

quantification of canopy mortality caused by fire for a particular location; it can 

be expressed as area with a particular magnitude of severity. Fire intensity is 

expected to increase significantly as a result of warmer temperatures. However, 

fuel loading, and interannual and longer term variability in climate–fire 

relationships can affect trends, making it difficult to infer whether climate 

change is responsible. See Figure 8 for an example map of this indicator.

Figure 8.—Example indicator map for areas burned by wildfire on both forest and nonforest land for a range of years 

in the conterminous United States (Monitoring Trends in Burn Severity 2013). Fire severity class of each area is also 

available. 
Recommendations for the U.S. National Climate Assessment Indicators System 27

Disturbance Indicator: Forest Insect and Disease Damage 

Major contributor: Jeffrey A. Hicke 

Metric: Area affected by insects and diseases 

Forest insects and diseases are major disturbance agents of forest ecosystems 

of the United States (Dale et al. 2001), and climate is an important driver 

influencing outbreaks of insects and diseases directly (Bentz et al. 2010, Sturrock 

et al. 2011) and indirectly by affecting host trees, which are then more susceptible 

to attack (e.g., Weed et al. 2013). The U.S. Forest Service conducts annual aerial 

surveys of insect- and disease-caused tree damage. Affected area is reported by 

insect or disease type and tree species, and is available at fine (polygon) and 

coarse (national) scales for summarizing as national totals for each disturbance 

agent as well as for producing maps (Fig. 9). These metrics are available, but 

more work is needed to use them as an indicator. In the future, ForWarn (U.S. 

Forest Service, Eastern Forest Environmental Threat Assessment Center 2015) 

may be developed enough to be used.

Figure 9.―Example map of insect activity in Alaska for 2010 that could be used for this metric (U.S. Forest Service, 

State and Private Forestry and U.S. Geological Survey, Alaska Geographic Science Office 2013). Note: Many of 

the most destructive diseases are not represented on the map because the agents are not detectable from aerial 

surveys. The Significant Pest Activity polygons are accented with a large border for visualization.
28 Indicators of Climate Impacts for Forests:

This indicator could focus on insects and diseases that damage trees over 

large areas: 1) bark beetles, including mountain pine beetle (Dendroctonus 

ponderosae), western pine beetle (D. brevicomis), spruce beetle (D. rufipennis), 

pinyon ips (Ips confusus), Douglas-fir beetle (D. pseudotsugae), and southern 

pine beetle (D. frontalis); 2) defoliating insects, such as spruce budworms 

(Choristoneura spp.); 3) pathogens, including Dothistroma needle blight, Swiss 

needle cast (Phaeocryptopus gaeumannii), and Phytophthora root disease; 

4) declines, including sudden aspen decline and yellow-cedar decline; and 

5) invasive insects and diseases that have a connection with climate, such 

as sudden oak death (Phytophthora ramorum), emerald ash borer (Agrilus 

planipennis), gypsy moth (Lymantria dispar), and woolly adelgids 

(Adelges spp.). 

Biophysical Indicator: Water Balance Deficit—An Indicator of “Plant-Relevant” Drought 

Major contributor: Jeremy Littell

Metric: Water balance deficit (calculated as a difference) 

Water balance deficit is the difference between potential evapotranspiration 

(PET) and actual evapotranspiration (AET) (Fig. 10). Some metrics use ratios 

of the two variables (AET/PET; e.g., Shinker and Bartlein 2010). The difference 

(or, if used, the ratio) is an indicator of the terrestrial water budget, which is 

the atmospheric demand for water via evaporation and transpiration from the 

land surface (PET) and the supply of water to satisfy that demand from the 

land surface and transpired by plants (AET). When PET exceeds AET, there is 

deficit; when AET is equal to PET, there is no deficit or surplus. There will be 

surplus water (runoff or infiltration) when water supply is greater than PET. In 

North America, water balance deficit is correlated with the distribution of biome 

vegetation (Stephenson 1990), tree growth in the Pacific Northwest (Littell et al. 

2008), and area burned by fire in the Western United States (Littell and Gwozdz 

2011; Littell et al. 2009, 2010). 

The more-familiar Palmer Drought Severity Index (PDSI; Palmer 1965) is an 

index of crop-available soil moisture. Water balance deficit and climatic water 

deficit (see Appendix 1) have been shown to be at least as well correlated with 

both ecological (Littell et al. 2008) and hydrologic (Abatzoglou et al. 2014) 

responses as PDSI is. Mu et al. (2013) discuss some of the limitations of PDSI 

compared to more direct indicators of plant water status, but for ecological 

applications the two most important are that PDSI does not adequately address 
Recommendations for the U.S. National Climate Assessment Indicators System 29

snowpack storage and melt processes in its estimation of drought and that PDSI does not adequately 

account for evapotranspiration occurring at the potential rate. Dai (2011) advocated adopting metrics of 

water deficit other than PDSI. Additionally, both PET and AET can be estimated on continuous timescales 

and therefore can be related to extreme events at the timescales of weather or at longer term (monthly, 

seasonal to annual) timescales associated with climate. Dependence on longer (monthly) timescales is 

built in to PDSI, smoothing its response to shorter term moisture anomalies, and limiting application for 

some purposes. More information about issues with PDSI is provided in Appendix 1.

Direct measurements are less commonly made for PET and AET than for temperature, precipitation, 

and other climate variables. There are multiple methods to estimate both forms of evapotranspiration 

that range from simple to complex and also differ in the degree to which they approximate realistic 

observations for a given purpose. Most methods are based at least on surface climate observations (e.g., 

temperature and precipitation) and to varying degrees incorporate weather (e.g., wind and solar radiation), 

soil (e.g., field capacity and infiltration), and vegetation (e.g., aerodynamics and vegetation-specific 

resistance). Data sources exist and are either modeled or based on remote sensing, but more research is 

needed to make water balance deficit an operational indicator. 

Figure 10.―Example maps for water balance deficit in the Western United States that could be used as the display 

for this metric. Left: mean summer precipitation deficit (millimeters), 1916-2006. Right: 2030-2059 ensemble change 

(from 1970-1999) in mean summer precipitation deficit (millimeters); ensemble is 10 global circulation models from 

the Intergovernmental Panel on Climate Change (2007) under SRES A1B.
30 Indicators of Climate Impacts for Forests:

Extent/Socioeconomic Indicator: U.S. Wildland-Urban Interface 

Major contributors: Miranda H. Mockrin and Susan I. Stewart

Metrics: Area of wildland-urban interface, Population residing in wildland-urban interface

The wildland-urban interface (WUI) is the locus of direct interactions between 

human beings and wildland flora and fauna. Wildfire in the WUI may be of 

particular concern, especially in an era of global climate change (Fig. 11). 

The WUI is a context indicator that is arguably a result of adaptation to fire 

risk, which will also be important in adaptation to climate change. The WUI 

indicates where housing exists above the federally recognized density limit of 

15.98 housing units per square mile (6.17 housing units per square kilometer) 

(U.S. Department of the Interior and U.S. Department of Agriculture 2001) and 

wildland vegetation is retained. 

Figure 11.―Example map of the wildland-urban interface (WUI) in the United States, 2010, which could be used as a 

display for this metric (Stewart and Radeloff 2015).
Recommendations for the U.S. National Climate Assessment Indicators System 31

Expansion of the WUI is not driven by global climate change (Theobald and 

Romme 2007). However, changes in the area and human population of the 

WUI are associated with processes that will affect wildland contributions 

and responses to climate change, such as degradation of wildland vegetation, 

migration of floral or faunal species, altered hydrology, increasing impervious 

surface, and introduction of exotic species of both flora and fauna (Fall et al. 

2009; Radeloff et al. 2005, 2010). The growing size and spatial extent of human 

populations in wildland areas will bring people into immediate contact with 

climate change effects on wildland, magnifying social impacts with implications 

for human health, government budgets, recreation, and other social processes. 

The rate of WUI growth varies with people’s environmental preferences, as well 

as economic and social constraints of their migration decisions. The past decades 

of WUI expansion have been driven by preferences for wild landscapes, rural 

lifestyles, flexible work patterns and new technologies (telecommuting), and 

lower home prices in rural areas. If these patterns change, the steady expansion 

of the WUI could slow.

Metrics for this indicator are currently available for operational use. Although 

we present this indicator as covering all wildland, we as the forest team can only 

recommend that this indicator be adopted as a cross-cutting indicator for land 

uses other than forest. 

Climate Impacts on Human Domain via Forest: Cost to Mitigate Wildfire Risk 

Major contributor: Guy Robertson

Metrics: Expenditures on fire suppression activity, Expenditures on forest treatments to mitigate fire 

risk, Total payments for insurance premiums for policies against damage from forest fire. Units are 

inflation-adjusted dollars per year by category and (if available) by geographic region.

The extent of forest wildfires is currently measured in a biophysical sense, but 

the actual cost of fire to society extends well beyond the damages associated 

with specific fire events to include fire suppression and avoidance costs as well 

as premiums paid to insure against fire damage. Many of these costs are hidden 

(at least in comparison to the impact of major fire events), but they still impose a 

major cost on society and can act as a reliable proxy for the full financial impact 

of forest fires on society. We propose “Cost to mitigate wildfire risk” as an 

indicator to recognize the indicator group Climate impacts on the Human 

Domain via Forest. 

More research is needed on this indicator, but the feasibility of providing 

metrics for this indicator is medium to high (e.g., see Lynch 2004). Federal 

fire suppression costs are readily available (Gorte 2011), but state and local 
32 Indicators of Climate Impacts for Forests:

expenditures make up an important piece of the picture, and their tabulation will 

likely entail state-by-state summation (see Figure 12, which uses only federal 

expenditures). The same is true for avoidance costs (i.e., for forest restoration 

and fuels treatments) with the added complication of defining what actually 

constitutes avoidance as opposed to forest management activities for other goals. 

Insurance premiums will depend on the availability of industry tabulations. 

Figure 12.―Federal fire suppression costs, 1985-2014, in millions of dollars adjusted for 

inflation to base year 2010 shown for the U.S. Forest Service and for Department of the 

Interior agencies. This example lacks state and local forest wildfire suppression costs. 

Similar displays could be compiled for avoidance and insurance costs for all wildlands. 

Data: National Interagency Fire Center (2015). 
Recommendations for the U.S. National Climate Assessment Indicators System 33

Human Domain Influences on Climate Domain via Forest: Energy Produced from 

Forest-based Biomass 

Major contributor: Guy Robertson

Metric: Energy produced, domestically or in export markets, from biomass harvested from U.S. 

forests. Units are in British thermal units (Btu) per year and, if possible, CO2 equivalent. (This is 

a measure of human influences on carbon sequestration.)

This indicator is proposed as a measure of human impact on atmospheric carbon 

concentrations via the forest sector and, more generally, as an indicator of social 

response to climate change (arrow 2 in the conceptual model). Aside from forest 

carbon sequestration, using forest-based biomass to produce energy is one of 

the most significant ways in which humans can influence atmospheric carbon 

through forest management activities. Forestland has long been used for energy 

production, either through the burning of wood in homes or, beginning in the last 

century, for cogeneration of heat and electricity in association with production of 

industrial wood products. In the last few years, pellet exports to Europe (in part 

as a response to the region’s current carbon-neutral energy targets) have been 

expanding rapidly. Similarly, the use of wood to generate energy on an industrial 

scale independent of wood products manufacturing has been increasing, though 

the amount generated remains relatively small. And finally, the production of 

cellulosic ethanol and related fuels has been identified as a potentially nascent 

forest industry if the required technology becomes available. For all these 

reasons, forest-based bioenergy production is a key indicator relating climate 

change and forest to human activity. 

Data readily exist to populate most of the indicator; a similar indicator has 

already been developed by the U.S. Forest Service (U.S. Forest Service 2011). 

We use an illustration from that source as a sample illustration for climate 

impacts (Fig. 13). Wood exports for foreign energy generation are not currently 

tracked, so work is needed to determine how to deal with measures or estimates 

of export volumes. 
34 Indicators of Climate Impacts for Forests:

Figure 13.―Example display of a forest biomass energy indicator (metric tons of CO2 equivalent per year). Source: 

U.S. Forest Service (2011).

Socioeconomic/Ecosystem Services Indicator: Outdoor Recreation 

Major contributor: Linda S. Heath, with major input from H. Kenneth Cordell

Metrics: Number of U.S. ski/snowboarder visits, Revenue of ski areas, Participation days in crosscountry skiing

Outdoor recreation activities are a notable contribution to the U.S. national 

economy (see Cordell 2012), are of major importance to local and regional 

economies, and will be affected by climate variability (e.g., see Bowker et al. 

2012, 2014). Snow sports such as downhill skiing, snowboarding, and crosscountry skiing are associated with areas that have forests, although developed 

land use areas are not forestland. (However, when forest is identified by forest 

cover methods, developed land use areas that have trees may be considered 

forestland.) Snow-dependent activities are all expected to be influenced by 

climate variability, and by economic conditions and demographics. We chose 

developed skiing and cross-country skiing as the indicator area on which to 

focus. The links to climate are complex, so the impacts on the skiing industry 

are complex (Irland et al. 2001). For example, increased winter precipitation 

may be good for the skiing if it falls as snow and if skiers can travel to the slopes. 

But if the increase is in the form of rain, the effects are different. 
Recommendations for the U.S. National Climate Assessment Indicators System 35

Undeveloped cross-country skiing is thought to be affected most by ski 

conditions because resorts can manufacture snow for developed skiing, given 

adequate temperatures and access to adequate water. Using metrics for both 

developed and undeveloped areas may aid interpretation while more research 

is conducted.

Number of ski/snowboarder visits is a function of adequate snow, economic 

conditions, and demographics. It is defined as one person visiting a ski area for 

all or any part of a day or night one time. Participation days in cross-country 

skiing is the number of days during which an individual has participated in 

cross-country skiing regardless of location. This activity is more closely affected 

by climate variability than developed snow skiing overall. Revenue of ski areas 

is the amount of revenue that ski resorts receive. In 2011, total revenue was 

projected to be $2.6 billion, with net profit estimated at $182.6 million (Doré 

Group 2015). Table 4 provides an example of available data for number of visits. 

Although these data are not new, and some have been used as indicators 

previously, more work is needed to ensure indicators are based on consistent 

datasets. Nearly all Americans enjoy some form of outdoor recreation, and 

data on participation in outdoor activities are collected at many levels. Some 

data sources from the recreation industry are available for purchase. Outdoor 

recreation is perceived to be strongly related to climate. To choose metrics 

relevant and useful to this indicator, we sought a major form of recreation 

clearly related to climate.

Table 4.—Number of skier/snowboarder visits to developed ski areas, by region

Skier visitsa (millions)

Season Northeast Southeast Midwest Rockies Pacific Total

2012–2013 13.3 5.2 7.1 19.5 11.6 56.6

2011–2012 11.0 4.4 6.4 19.1 10.0 51.0

2010–2011 13.9 5.8 7.8 20.9 12.2 60.5

2009–2010 13.4 6.0 7.7 20.4 12.3 59.8

2008–2009 13.7 5.7 7.2 20.0 10.7 57.4

a The National Ski Areas Association defines a skier/snowboarder visit as one person visiting a ski area for all or any part of a day 

or night one time. This includes full-day, half-day, night, complimentary, adult, child, season, and any other ticket type that gives one 

the use of an area’s facility. Data from National Ski Areas Association (2014); other data sources may show different estimates or 

trends (e.g., Cordell 2012).
36 Indicators of Climate Impacts for Forests:

Research Gaps and Potential Indicators

Coordinators of the effort noted that many teams indicated more research is 

needed. After additional discussion, each team (including the forest team) was 

asked to submit a memo identifying high-priority indicators requiring more 

research, and discussing research gaps (see Appendix 2 for a revised copy of 

the memo). In this section, we first summarize research gaps for recommended 

indicators. Second, six areas are identified and described for additional indicator 

research. Although some of these indicators, such as permafrost, are not strictly 

focused on forestland, we list them here because our team members proposed 

them, and in addition it was unclear if the indicators fit well in another team. For 

more information on research gaps and potential indicators, see Appendix 2.

Summary of Research Gaps

We identified four areas of research or development that would benefit all 

the recommended indicators. These areas are: research on the direct link and 

interpretation of indicators to climate impacts, discussions about links with 

indicators for other teams, guidance for determining when new approaches are 

better than existing approaches, and exploration about the concept of risk and its 

usefulness in terms of the indicators. For direct link and interpretation, studies 

are needed which explicitly investigate the connections between climate and the 

forest indicators, interpretation, and implications. 

We have identified indicators that are useful to forests but most relevant to other 

teams, and discussing those links is crucial. Some users of these indicators may 

prefer a newer approach for the data, and uncertainty is inherent in all data. 

Guidance on how to decide between approaches for measures is needed to keep 

choices objective. Will the indicators be sensitive to response measures so that 

the effect of response activities will be detected? Furthermore, if the idea of risk 

is important to convey, how can risk be best conveyed through indicators? For 

additional details, see Appendix 2.

Specific research gaps or data needs were noted for four indicators (Table 5). 

Because of the differences in floral and faunal species in terms of trends in 

diversity/abundance, research gaps in these metrics are discussed separately. See 

Appendix 2 for the full text.

Summary of Potential Indicators and Metrics

“Tribes and climate change” was proposed as an indicator, with three metrics: 

1) Number of Native coastal communities relocated or needing to relocate in the 

next decade as a result of sea level rise or permafrost thaw, 2) Number of tribes 

developing climate change adaptation plans, and 3) Number of tribes and Native 

communities engaged with Climate Science Center/Landscape Conservation 

Cooperatives. As forest- and natural resource-dependent communities, Native 

peoples are among the first to be directly affected by accelerating climate 
Recommendations for the U.S. National Climate Assessment Indicators System 37

change. With centuries to millennia in place, Native peoples also have a wealth 

of experience adapting to changes. In addition to humanitarian concerns, sea 

level rise and relocation of Native communities may challenge federal and state 

capacities to comply with treaty obligations, the American Indian Religious 

Freedom Act (1978), and other bodies of law. Because of the lack of information, 

these simple metrics based on numbers are suggested. 

Indicator or metric Research gaps or data needs

Diversity/Abundance 

of forest-associated 

faunal species

1. Possible deficiencies in U.S. Geological Survey’s Breeding Bird Survey data: a) Data 

collection focuses on single taxon, rather than a spectrum of forest-associated species; 

b) Known biases exist in data; some have been addressed, but others have not. 

2. More work is needed to link trends to climate change effects. 

3. Additional work is needed on the relation of faunal populations to influential factors 

other than climate. 

Diversity/Abundance 

of forest-associated 

floral species

1. Two issues for underlying data: a) Data from before 2000 are not consistent and 

methods to use them are needed; b) Options are needed for time-series use of Western 

U.S. data, which are expected to be measured only every 10 years; data series in 

the Eastern United States may not be long enough yet to assess biodiversity change 

associated with climate change. 

2. Research is needed to determine the extent to which change in forest seedling 

diversity represents a leading indicator of climate change effects for overall forest 

biodiversity. 

3. Research is needed to establish whether simple measures of biodiversity are 

sufficient, or whether biodiversity metrics that account for evolutionary relationships 

among species would be needed.

Climate impacts 

on Human Domain 

via Forest: Cost to 

mitigate wildfire risk

1. Federal expenditures for fuels treatments and related mitigation activities can be 

accessed from federal budget reports, but the interpretation and use of measures need 

additional consideration. 

2. Design of reporting activities for forest restoration activities will probably involve 

tallying expenditures to the state level, and may be labor-intensive. 

3. Insurance premiums and related measures require additional exploration and 

conceptual development. 

Human influence 

on Climate Domain 

via Forest: Energy 

produced from forestbased biomass

1. A method or methods are needed to determine and include exports of forest biomass 

for energy production in current statistics. 

2. Estimates of residential use and other diffuse energy production may require 

additional refinement, especially for emerging technologies or shifting markets.

Outdoor recreation 

(Developed skiing and 

cross-country skiing)

Additional available datasets could be used, especially in conjunction with local ski area 

monitoring, to better tie participation in developed skiing to location, and then to climate. 

Table 5.—Specific research gaps or data needs for selected recommended indicators
38 Indicators of Climate Impacts for Forests:

“Outdoor recreation and amenities” was proposed as an indicator area requiring 

more work, with three preliminary candidate metrics: 1) Mean high water, 

2) Net internal rural migration rate, and 3) Number of participants and days 

of participation in hiking. This is an exploration of the current recommended 

indicator on outdoor recreation, augmented with amenities. An amenity is “an 

attribute that enhances a location as a place of residence” (McGranahan 1999). 

Although not strictly related to forest, mean high water would be of interest 

because in most coastal states, recreational access to beaches is granted to the 

public under the Public Trust Doctrine. As climate becomes warmer and sea 

levels rise, the public’s opportunities for using this outdoor recreation resource 

will change. Net internal migration rate, the difference between domestic inmigration to the area and out-migration from the same area during a time period, 

has been shown to be climate-sensitive (Cordell et al. 2011). Hiking is a popular 

activity that has been shown to be sensitive to climate (e.g., see Bowker et al. 

2014). 

A Permafrost indicator was discussed with a metric or metrics on extent and 

distribution of permafrost and peatland and associated changes in the depth of 

the active layer within boreal forest and tundra. Boreal forest and woodland are 

found in landscapes that include nonforest ecosystems. The ability to predict 

how climate change may affect these boreal systems hinges on our knowledge of 

the extent and distribution of permafrost and peatland, and the changes in active 

layer depth, typically rich in soil carbon. Permafrost is responding to changing 

temperature regimes, but it is unclear how this will affect near-surface processes 

in the long term (Abraham 2011). Advances in remote sensing techniques in 

recent years have provided new methods for mapping permafrost features 

(Abraham 2011) and peatland (Krankina et al. 2008, Torbick et al. 2012). The 

joint development of remote sensing methods with ground-based measurements 

to calibrate and verify remotely sensed results is critical, and appears to be within 

reach. Although permafrost does not occur throughout the United States, broadscale changes in permafrost dynamics can have national implications.

A Lichen biodiversity indicator, in the indicator group Ecosystem services and 

goods, was proposed with metrics based on epiphytic lichen biodiversity or 

epiphytic lichen functional group. Lichens are highly climate-sensitive because 

they lack roots and are unable to retain water. Consequently, basic metabolic 

processes and fitness are closely tied to ambient temperature and moisture. 

We propose that a climate indicator be developed by using the FIA-based 

Lichen communities indicator. There already exists a large dataset of more 

than 8,000 epiphytic lichen surveys (1998-2013) collected by FIA and the U.S. 

Forest Service Region 6 Air Management Program, including many repeat 

measurements. Given the sensitivity of some lichens, these show promise as a 

potential leading indicator of climate change.

A Ground layer indicator, in the indicator group Structure and function, was 

proposed with metrics for effects of moss and lichen mats on biomass, elemental 
Recommendations for the U.S. National Climate Assessment Indicators System 39

content (i.e., carbon and nitrogen), 

and functional importance. The 

indicator is based on the premise 

that simple measurements of 

the depth and area covered by 

mosses and lichens can be scaled 

into landscape-level estimates of 

biomass and elemental content based 

on prior calibrations. Functional 

importance is assigned to a dozen 

easily recognizable morphological 

groups, examples of which are soil 

stabilizers, nitrogen fixers, water 

regulators, and wildlife forage 

groups. Changing climates have 

the potential to shift species ranges, 

resulting in the gain or loss of major 

functional groups in ground layers. 

For example, a warming and drying 

climate can promote shrub expansion 

that excludes forage lichens 

(Heggberget et al. 2002). In wetland, 

lowered water tables coupled with 

more severe wildfires can eliminate critical peat deposits and the Sphagnum

mosses which form them (Turetsky et al. 2011). Similar to the biodiversity of 

lichens, mosses may be a very climate-sensitive indicator.

Ozone is an important greenhouse gas that also indirectly affects climate by 

limiting sequestration of CO2 by vegetation (Sitch et al. 2007). An Ozone 

indicator with a metric of ozone concentrations in natural ecosystems may be 

strongly linked to climate. Additional research on the interaction of increased 

CO2 , temperatures, and ozone effects on individual forest tree species is needed. 

Little is known about the interaction of longer growing season, increased 

summertime ozone, and increased climate-induced vegetation stress such as 

drought on ecosystem response. Some data are available because an ozone 

indicator has been used previously in the U.S. Forest Service, Forest Health 

Monitoring program, although not in the context of climate change.

As stated earlier, this effort was designed in such a way that we did not consider 

adaptation indicators. There may be a number of crucial potential indicators 

of adaptation which are related to forests that will emerge only with dedicated 

attention to this area. For example, ecosystem-based adaptation is a commonly 

discussed management approach that merits greater attention. In addition, we 

may be recommending indicators and metrics which could be improved with 

a view that includes adaptation. We recommend additional investigation of 

indicators of forest-related adaptation. 

Usnea longissima (Methuselah’s beard), 

a good indicator of climate change. It is 

used by wildlife and requires a mild, moist 

habitat. Its main mode of reproduction is by 

fragmentation, which makes this species 

dispersal-limited. Photo by Sarah Jovan, 

U.S. Forest Service.
40 Indicators of Climate Impacts for Forests:

Many aspects of U.S. forestland are of national significance. Climate change 

impacts will also be of national significance. Response strategies in terms of 

mitigation are nationally important as well. We have identified 11 informative 

core indicators that have metrics available or close to being available for use 

in the NCA indicator system. The indicators are based on a comprehensive 

conceptual model we developed in which we treated forest as a land use 

and a sector. 

We also identified seven indicators that are important in terms of climate impacts 

on forest, but that we thought were more relevant to other teams. Examples are 

temperature and precipitation, which we think the physical climate team will 

include, and budburst, which we encourage the phenology team to include. 

Wildfire indicators are relevant not only to forestland, but also to the grassland 

team and the phenology team. The phenology and forest teams to date, however, 

have developed different wildfire metrics, and the grassland team currently does 

not have a wildfire indicator. Additional discussions between the teams could 

help provide a leaner set of indicators with broader applicability.

As we worked through the assigned process, we realized there were many 

candidate indicators. We developed and adopted additional selection criteria, 

including the following: that overall our recommendations cover the range 

of our conceptual model, that selections feature a few indicators which could 

be reported on currently, and that we also consider important indicators not 

currently accessible for reporting. This approach provides immediate inputs for 

an indicator web portal, and identifies indicators requiring additional research to 

focus work on these areas. We did not identify any leading indicators within our 

core indicators. With more research, some of the potential indicators may serve 

as a leading indicator of climate impacts on forests.

We recognize that some indicators could be based on several different sources 

of data, each of which has various advantages and disadvantages to different 

stakeholders. We therefore adopted the definition of indicators as a description 

of the item, with the actual measure for the indicator called a metric. Additional 

research linking the metrics with climate change may prove one metric to be 

more broadly applicable than the others.

Because there are many interacting drivers of forest change, indicators may have 

a limited ability to represent only the impacts of climate change on forest. For 

example, land use decisions influenced primarily by economic considerations 

are expected to be major drivers affecting rates of afforestation and deforestation 

in the United States during the 21st century (Man 2012). Understanding the full 

context of the important drivers is necessary to properly interpret results.

SUMMARY AND OBSERVATIONS
Recommendations for the U.S. National Climate Assessment Indicators System 41

In the future, more formal consideration of urban forest and settlements as well as 

agroforestry systems would be worthwhile. Although our charge did not include 

adaptation, activities involving urban forest and agroforestry are commonly 

mentioned in the scientific literature as possible adaptation approaches, and 

there is a need for forest-related adaptation indicators. In addition, one of our 

recommended indicators, the U.S. wildland-urban interface, may be an important 

indicator for adaptation responses. The indicator highlights urbanizing forest 

areas where social impacts of climate variability effects on wildland vegetation 

are expected to be magnified. This indicator is arguably a result of adaptation to 

wildfire risk, but it is also useful for adaptation responses to climate change. We 

also recognize the concept of risk in the context of indicators and climate change 

is important for decisionmaking, but more fundamental work is needed in that 

area before recommending an approach for use in an indicator system.

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Appendix 1: Additional Indicator Details 49

APPENDIX 1: Additional Indicator Details

We are including the material in this appendix for full transparency of our 

deliberations, and to provide details of the metrics and specifics of the 

recommended indicators for those who will be developing the Web portal. 

Some information presented here may be duplicated in the main text, but we 

have worked to reduce duplication while striving to make the entire publication 

understandable and readable.

FOREST EXTENT INDICATOR: FORESTLAND AREA AND EXTENT 

Metrics: Forestland area by land use, Forest area based on forest cover only 

Summary

Forestland area by land use is determined from U.S. Forest Service, Forest 

Inventory and Analysis (FIA) program information (U.S. Forest Service 2013) 

and may include observations from the National Land Cover Dataset (NLCD) 

(Multi-Resolution Land Characteristics Consortium [MRLC] 2014) or U.S. 

Census for area calculations. Units are acres (hectares).

Forest area based on forest cover only is determined by using a remote sensing 

approach, with observations compiled into the NLCD (MLRC 2014). Units are 

acres (hectares). 

Both metrics are currently available, and are periodically updated and improved.

Additional Descriptive Text

This indicator (Table 6) defines the forest category in terms of location on the 

land, distinguishing it from other land uses such as grassland. Climate affects 

forest extent directly (e.g., through increased mortality or enhanced recruitment), 

and indirectly (e.g., through increased prevalence of wildfires). 

In terms of land use, forestland area in the United States was about 751 million 

acres (304 million hectares) in 2010 (U.S. Forest Service 2011). Scenario 

projections indicate decreases in forestland are likely in the future (U.S. Forest 

Service 2012). Since 2003, forestland area has shown a net increase by about 
50 Indicators of Climate Impacts for Forests

Decision criterion Ranking Justification 

Link to conceptual 

framework

Collectively, the metrics 

are best.

The extent attribute largely indicates the geographic location 

of the Forest Domain, with changes and interactions 

illustrated by arrows 3, 4, 6, 7, 8, and 13. Each metric has its 

advantages and disadvantages. Showing the map and listing 

the statistics in a table is a good compromise.

Defined relationship to 

climate, feedbacks, or 

impacts

Individually, each is 

sufficient; collectively, 

the metrics are best.

Broad pervasive link to climate, but many confounding 

factors present

Spatial scalability Best One approach is best graphically; the other, statistically.

Temporal scalability Sufficient to best One approach may be available annually; the other is 

periodic.

Of national (not 

necessarily nationwide) 

significance. Should 

link to the conceptual 

model

Best for context in 

particular

We need to know where the Forest Domain is to discuss it.

Relevance to 

management decisions

Best for context in 

particular

We need to know where the Forest Domain is to discuss it.

Usefulness for 

educational purposes

Individually, each is 

sufficient; collectively the 

metrics are best

Yes, it is important to understand the location of forest.

Is it a leading 

indicator?

No Not applicable

Builds on existing data 

sources

Yes Yes, information is readily available but not necessarily for a 

specific year.

Builds on existing 

indicator products

Yes Both build on existing sources.

If new indicator 

proposed, likelihood 

of development and 

testing within 1 year 

given existing funding 

sources

Not applicable Not applicable

Stability/Longevity of 

dataset

Best One may go back to the 1970s and the other to the 1950s, 

but these data are improved over time. Looking forward, the 

future of both datasets is sound.

Stability/Longevity of 

indicator

Collectively best Improvements in research and development may eventually 

result in one map and one set of statistics but not yet.

Scientific validity of 

indicator

Each approach is valid 

in its own way.

Improvements in research and development may eventually 

result in one map and set of statistics but not yet.

Data publicly available 

and transparent

Best Data are available on Web sites and are generally 

transparent.

Indicator methods 

fully transparent and 

documented

Sufficient to best Access continues to improve. Both are documented, and 

documentation continues to improve. 

Table 6.—Decision criteria for Forest extent indicator: Forestland area and extent
Appendix 1: Additional Indicator Details 51

7.9 million acres (3.2 million hectares). In coastal areas, forestland is decreasing 

due to urban development, whereas in the interior United States, an increase 

in forest area is attributed to woody plant encroachment in grassland from 

fire suppression, changes in grazing patterns, or abandonment of agricultural 

land. The national estimates are updated about every 5 years. As noted in the 

Introduction, the FIA definition of forestland does not include narrow corridors or 

small patches of trees, and thus may not include riparian corridors, agroforestry, 

or urban forests.

The National Land Cover Dataset may also be used in conjunction with the U.S. 

Forest Service ground data estimates to increase mapping accuracy. Methods 

continue to be refined, thus improving the results and interpretation. Therefore, 

the approaches used for this indicator probably will have to be periodically 

updated, and the metrics recalculated for consistency over time.

What Is the Link to Climate Variability and Change or Relevance?

Forest area responds to climate directly (through increased mortality or enhanced 

recruitment, or both) and indirectly (e.g., through increased prevalence of fire and 

insect outbreaks). Particularly in climate-limited regimes such as alpine treeline 

or grassland/forest ecotones, the area of forest can provide a direct indicator of 

biologic response to climate change.

What Are the Drivers of This Indicator, and What Are Their Impacts?

Both human activities and climate affect forestland extent and area, as described 

above.

Relevance to Management Decisions

The timber industry is important for the U.S. economy, and accounts for about 

2 percent of U.S. employment. Understanding climate-induced changes in the 

distribution of U.S. forest cover will allow improved forecasting of U.S. timber 

production. Specific management strategies to mitigate climate change effects 

(fire suppression, introduction of new tree hybrids, establishment of protected 

areas) could be informed by improved tracking of forestland area.

Other Indicators Considered But Not Recommended at This Time 

Other remote sensing products include the National Aeronautics and Space 

Administration’s (NASA’s) moderate resolution imaging spectroradiometer 

(MODIS) land cover product (global since 2000). The resolution of the MODIS 

product is relatively coarse, however, and prospects for continuation past the 

current MODIS satellite lifetime are unclear. The U.S. National Resources 

Inventory (NRI) provides an alternate source for land cover information, but only 

on nonfederal land. 

Usefulness for Educational Purposes

Visualizing the distribution and changes to U.S. forestland can provide a graphic 

understanding of how climate and climate change affect the nation’s timber 

resources.
52 Indicators of Climate Impacts for Forests

Data Availability

Length of Records of Dataset

FIA: Forest survey established by McSweeney-McNary Forest Research Act in 

1928; continuous improvements since then. Transition to national, annualized 

reporting in 2000. 

NLCD: First generated in 1992; subsequent versions in 2001, 2006. The 2011 

version of NLCD is currently in production.

Stability/Longevity of Dataset and Indicator

Both NLCD and FIA are long-term, operational products; FIA is Congressionally 

mandated. 

Notes About the Data (Change in Analysis or Collection Methods)

Both FIA and NLCD have improved their methods over time, and attention must 

be paid to whether observed decadal changes represent methodological effects, or 

real changes to forest cover.

Spatial and Temporal Scalability

The FIA dataset is based on a geographic sample of forest cover, with known 

sampling error as a function of the land area being assessed. The NLCD is 

spatially explicit (30-m [100-ft] resolution), with per-pixel and regional accuracy 

evaluated by comparison with the FIA-based ground data.

Details About the Indicator

Type of Indicator (Current, Leading, Both)

Current

Geographic Scope and Scale of Analysis

National

Approach of Indicator (e.g., Single Measure, Composite)

The main metric on extent of forest is based on land use because this is the 

traditional approach used for the official forest statistics for the United States, 

based on FIA data (U.S. Forest Service 2013). Ground plots are visited and 

measurements taken. Based on the plots and census data estimates of land area, 

forestland area is calculated. Maps of forest biomass (e.g., Wilson et al. 2013) 

based on the plot data can be used for forestland.

A second metric on extent of forest can be based on the NLCD (Homer et al. 

2012, MLRC 2014). This is a remote sensing approach, which differentiates 

forest based on forest cover using remote sensing with limited consideration of 

some land uses. The NLCD approach is also currently used to determine urban 

forest extent (e.g., see Nowak and Greenfield 2008), but there are methodological 

issues for use in determining forest as described in Nowak and Greenfield (2010). 
Appendix 1: Additional Indicator Details 53

Purposes and Conceptual Framework

The extent attribute largely indicates the geographic location of the Forest 

Domain, with changes and interactions illustrated by arrows 3, 4, 6, 7, 8, and 13. 

Extent of forest is important as an indicator because it defines forest boundaries 

and the area involved. The amount of forestland can be locally dynamic due 

to human activities and can vary due to differences in definition or estimation 

approach. Climate affects vegetation and amount of forestland directly 

(e.g., extended drought may cause tree mortality or impede regeneration) and 

indirectly (e.g., climate may influence insect outbreaks that cause broad-scale 

tree mortality). Knowledge of forestland area and change of forestland over time 

by broad forest-group class is especially important for climate mitigation because 

decreases in forestland translate directly into increased greenhouse gas emissions 

from the forest sector. Scenarios indicate decreases in forestland are likely in the 

future (U.S. Forest Service 2012).

Considerations for Selection of Indicator

Advantages 

Together, FIA and NLCD provide both a sample-based and geospatial 

representation of U.S. forestland, which is consistent with U.S. reporting to 

the United Nations Framework Convention on Climate Change. 

Disadvantages

Methodological changes in both FIA and NLCD can make long-term trend 

analysis difficult. The error characterization of remote sensing products such as 

NLCD needs to be carefully considered as a function of cover type, geography, 

and data quality.

Literature Cited

Homer, C.H.; Fry, J.A.; Barnes, C.A. 2012. The National Land Cover 

Database, U.S. Geological Survey Fact Sheet 2012-3020. 4 p. Available at 

http://pubs.usgs.gov/fs/2012/3020/. (Accessed 12 February 2015).

Multi-Resolution Land Characteristics Consortium [MRLC]. 2014. National 

Land Cover Dataset (NLCD). Available online at http://www.nrlc.gov/. 

[Date accessed unknown].

Nowak, D.J.; Greenfield, E.J. 2008. Urban and community forests of New 

England: Connecticut, Maine, Massachusetts, New Hampshire, Rhode 

Island, Vermont. Gen. Tech. Rep. NRS-38. Newtown Square, PA: U.S. 

Department of Agriculture, Forest Service, Northern Research Station. 62 p.

Nowak, D.J.; Greenfield, E.J. 2010. Evaluating the National Land Cover 

Database tree canopy and impervious cover estimates across the 

conterminous United States: a comparison with photo-interpreted 

estimates. Environmental Management. 46: 378–390.
54 Indicators of Climate Impacts for Forests

U.S. Forest Service. 2011. National report on sustainable forests—2010.

FS-979. Washington, DC: U.S. Department of Agriculture, Forest Service. 

212 p.

U.S. Forest Service. 2012. Future of America’s forests and rangelands: Forest 

Service 2010 Resources Planning Act Assessment. Gen. Tech. Rep. WO-87. 

Washington, DC: U.S. Department of Agriculture. 198 p. 

U.S. Forest Service. 2013. Forest Inventory and Analysis national program: 

data and tools. Available at http://apps.fs.fed.us/fiadb-downloads/datamart.html. 

(Accessed 17 June 2013).

Wilson, B.T.; Woodall, C.W.; Griffith, D.M. 2013. Imputing forest carbon 

stock estimates from inventory plots to a nationally continuous coverage.

Carbon Balance and Management. 8: 1. DOI: 10.1186/1750-0680-8-1.

STRUCTURE AND FUNCTION INDICATOR: FOREST BIOMASS DENSITY 

Metrics: Aboveground live tree biomass density, Dead wood mass density 

Summary

Aboveground live tree biomass density (biomass per unit area) is calculated by 

using FIA data (U.S. Forest Service 2013). Data are measured from a statistically 

designed series of ground plots across the United States, using documented 

methods. Units are tons per acre (metric tons per hectare).

Dead wood mass density is calculated by using FIA data (U.S. Forest Service 

2013). Data are measured from a statistically designed series of ground plots 

across the United States, using documented methods. In some cases, dead wood 

may be estimated. Units are tons per acre (metric tons per hectare).

Both metrics are currently available, and are periodically updated and improved.

Additional Descriptive Text

The use of aboveground live biomass density as a metric of forest structure 

(Table 7) conveys information related not only to climate mitigation in terms of 

forest stocks, but also to potential availability of biomass for bioenergy, which 

can be used as a substitute for fossil fuel to produce energy. Climate change may 

directly affect live biomass by influencing mortality, growth, and regeneration; 

or the demand for biomass to lower overall emissions may result in decreased 

stocks of biomass. Forest health issues may result in a greater amount of dead 

mass in relation to live biomass, so a second important metric is dead wood mass 

density.
Appendix 1: Additional Indicator Details 55

Decision criterion Ranking Justification 

Link to conceptual framework Best Fundamental attribute of structure (within structure and 

function attribute within Forest Domain), with changes and 

interactions represented by arrows 4 and 5, as well as 

connections with arrows 6, 7, 8, and 13.

Defined relationship to 

climate, feedbacks, or impacts

Best Climate is one of the fundamental drivers of potential 

vegetation, and major structural changes across landscapes 

will affect weather. If changes are large enough, this 

becomes climate change.

Spatial scalability Best Data nationally available, but limited at small scales. 

Methods can be used locally for data to derive estimates.

Temporal scalability Sufficient Annual estimates can be derived.

Of national (not necessarily 

nationwide) significance? 

Should link to the conceptual 

model

Best Yes, sequestration in U.S. forests offsets 10–20 percent of 

fossil fuel emissions. Indicator is of key significance to the 

Forest Domain.

Relevance to management 

decisions

Best Direct impacts on forests usually affect forest area or forest 

structure (e.g., in terms of biomass) or both, making biomass 

density a very relevant indicator. Biomass (carbon) is a 

fundamental consideration in terms of climate mitigation.

Usefulness for educational 

purposes

Best Yes, Americans are passionate about their forests. Increased 

mortality (in relation to live biomass) will be of interest, and 

will provide a basis for education on forest ecosystems and 

how they function.

Is it a leading indicator? No But projections are available, and it does speak to climate 

mitigation by forests.

Builds on existing data 

sources

Yes, best Based on FIA data, is standard for the United States

Builds on existing indicator 

products

Best It can build on existing indicator products or official reporting 

statistics. These will be similar but not the same.

If new indicator proposed, 

likelihood of development and 

testing within 1 year given 

existing funding sources

Not applicable Not applicable

Stability/Longevity of dataset Best FIA dataset has existed for decades, and is expected to 

continue.

Stability/Longevity of indicator Best This is a fundamental indicator and is expected to be 

available for the long term.

Scientific validity of indicator Best to 

sufficient

There are questions about the biomass equations, and 

research is currently being conducted. But the estimates are 

considered valid as is.

Data publicly available and 

transparent

Yes Available for download

Indicator methods fully 

transparent and documented

Best More research would be useful in terms of the connection 

with climate. Documentation in terms of the climate impacts 

on forests would be useful.

Table 7.—Decision criteria for Structure and function indicator: Forest biomass density
56 Indicators of Climate Impacts for Forests

Biomass per unit area can be more closely linked to climate than can total 

forest biomass, which is biomass per unit area multiplied by forest area. The 

interpretation of total forest biomass is confounded by the change in forest area, 

a change that may or may not be related to climate. We have included forest area 

as an indicator so that the effects of changing forest area can be more directly 

interpreted. 

Total forest biomass stock is important in terms of policy-relevant climate 

impacts. For example, values for total live and dead wood forest carbon (which 

is a direct function of biomass) for the United States are required for the annual 

national greenhouse gas inventory reporting to the United Nations Framework 

Convention on Climate Change; the latest report is U.S. Environmental 

Protection Agency [EPA] (2013) (Table 8). Terrestrial contribution to greenhouse 

gas inventories is being considered as an indicator for the mitigation team. The 

carbon estimates are calculated by multiplying the carbon estimates by two to 

express carbon as dry weight biomass. Dividing by forest area produces the 

metric biomass density (per unit area), and conversely multiplying biomass 

density by forest area produces total biomass.

What Is the Link to Climate Variability and Change or Relevance?

An overarching issue identified in the National Report on Sustainable Forests—

2010 (U.S. Forest Service 2011) is the interaction of forests, climate change, 

and bioenergy. Climate change was recognized as presenting a profound 

challenge for forests and forestry in the United States, with possible altered forest 

patterns in the future (U.S. Forest Service 2012). Forests in the United States 

currently serve as a large carbon sink (Heath et al. 2010) and as a main source 

of renewable energy. Because aboveground tree biomass and dead wood mass 

are major components of carbon in forests reported in the national greenhouse 

gas inventories, this indicator is an important link to climate mitigation. Biomass 

estimates are important to inform possible availability for bioenergy. Biomass 

amounts are affected by climate, and climate variability can affect mortality, 

growth, regeneration, and decomposition, so mass of both live trees and dead 

wood is important.

Table 8.—Million metric tons of total aboveground live and dead wood mass in U.S. forestland 

(U.S. EPA 2013)

Year

Component 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2011

Aboveground 

tree biomass 24,568 24,962 25,368 25,808 26,258 26,682 27,110 27,580 28,062 28,512 28,952 29,172

Dead wood 4,322 4,358 4,396 4,434 4,492 4,546 4,600 4,656 4,708 4,766 4,822 4,852
Appendix 1: Additional Indicator Details 57

What Are the Drivers of This Indicator, and What Are Their Impacts?

Both climate and human activities affect this variable, as described above.

Has This Indicator Been Used as an Indicator by Anyone Else; If So, 

By Whom, and How Was It Used and When Was It Initiated?

Biomass or carbon density of aboveground live trees and dead wood have been 

formally used as indicators at the national level (e.g., see U.S. Forest Service 

2011) and are used at the project level. 

Relevance to Management Decisions

Biomass density of live trees and dead wood is the cumulative effect of changes 

to the forest. Accurate and precise biomass estimates are needed for climate 

mitigation reporting, determination of forest mitigation activities, and supply for 

bioenergy. Biomass estimates will help inform planning for ecosystem-based 

adaptation activities, such as those along riparian areas or shade for livestock. 

Biomass estimates are relevant at all geographic scales, from national to local.

Other Indicators Considered But Not Recommended at This Time 

Other forest carbon ecosystem components were considered for structure, 

but aboveground biomass density is the most dynamic and most precise. We 

considered reporting these as carbon stock density rather than in terms of 

biomass, but a simple conversion (biomass = 2 × carbon) is reasonably accurate. 

Biomass density is useful for bioenergy supply, although green weight biomass 

may be preferred for bioenergy. Biomass change was also considered, but 

greenhouse gas changes are more applicable for the mitigation category.

Usefulness for Educational Purposes

Visualizing the distribution and changes to live and dead mass density can 

provide a graphic understanding of the cumulative effects of how land use, 

management, and climate change affect the nation’s forest resources. Changes 

in tree biomass density in locations not under direct human management such as 

at high elevations, and significant changes in the amount of dead wood mass in 

comparison to live mass may be due to climate. Biomass density is also directly 

essential for telling the story of the demand and supply for human needs for 

energy and resulting emissions, and identifying those areas where wood 

biomass may be available for bioenergy.

Data Availability

Length of Records of Dataset

FIA: Forest survey established by McSweeney-McNary Forest Research Act in 

1928; continuous improvements since then. Transition to national, annualized 

reporting in 2000. Practically speaking, individual state-level tree datasets are 

available beginning in the late 1980s. Projections of this indicator, consistent 

with the current data, are available (e.g., see U.S. Forest Service 2012).
58 Indicators of Climate Impacts for Forests

Stability/Longevity of Dataset and Indicator

The FIA program is Congressionally mandated, and the data are expected 

to continue to be collected. Older datasets are occasionally revised and the 

sample design or protocols may change. Models to estimate biomass from 

tree measurements may occasionally change. However, these changes can be 

controlled for over time.

Notes About the Data (Recent Changes in Analysis 

or Collection Methods)

The FIA program has updated its methods over time, and attention must be paid 

to whether observed changes represent methodological effects, or real changes.

Spatial and Temporal Scalability

The FIA dataset is based on a geographic sample, with known sampling error 

as a function of volume or basis. 

Details About the Indicator

Type of Indicator (Current, Leading, Both)

Current

Geographic Scope and Scale of Analysis

National to state to county, although precision of the estimates decreases for 

smaller areas. 

Approach of Indicator (e.g., Single Measure, Composite)

The use of aboveground live biomass density as a metric of forest structure 

conveys information related not only to climate mitigation in terms of forest 

stocks, but also to potential availability of biomass for bioenergy, which can be 

used as a substitute for fossil fuel to produce energy. Climate change may directly 

affect live biomass by changing mortality, growth, and regeneration; or the 

demand for biomass to lower overall emissions may result in decreased stocks 

of biomass. The FIA program provides the official forest statistics for the United 

States, based on its data (U.S. Forest Service 2013); FIA’s approach is the one 

traditionally used for this indicator.

Forest health issues may result in a greater amount of dead wood mass in 

relation to live biomass, so a second important metric is dead wood mass density. 

This metric is also relevant for the same reasons as live tree biomass, and the 

dynamics are related to live biomass in the sense that dead wood comes from live 

biomass. But the resulting fate of dead wood may be quite different. Past data on 

dead wood are limited.

Purposes and Conceptual Framework

This indicator applies directly to the Structure and function attribute in the 

conceptual model. Aboveground biomass of trees is a fundamental, multipurpose 
Appendix 1: Additional Indicator Details 59

indicator for context and climate mitigation. It can also be a useful measure to 

inform ecosystem-based adaptation planning, projects, and implementation. 

Biomass is a key determinant as to whether a land area is forest or some other 

land use.

Scientific Validity of Indicator

The validity of the estimates is well established for climate mitigation purposes. 

More research is needed for understanding the direct effects that climate 

variability or change may have on biomass across the landscape. 

What Are the Plans for Further Development of the Indicator?

Research is currently being conducted to improve biomass equations. Much 

research is also being conducted by using new measurement techniques such as 

light detection and ranging (LIDAR). However, these have not been coordinated 

activities to improve the indicator per se.

Considerations for Selection of Indicator

Advantages 

Data from FIA provide a sample-based representation of forest biomass that is 

consistent with U.S. reporting to the United Nations Framework Convention 

on Climate Change. These estimates are well used and well accepted by a wide 

range of stakeholders in the United States.

Disadvantages

Methodological changes in FIA data can complicate long-term trend analysis. 

Estimates for dead wood mass are particularly limited before recent time periods. 

Literature Cited

Heath, L.S.; Smith, J.E.; Skog, K.; Nowak, D.; Woodall, C. 2011. Managed 

forest carbon estimates for the U.S. Greenhouse Gas Inventory, 

1990–2008. Journal of Forestry. April/May 2011: 167–173.

U.S. Environmental Protection Agency [EPA]. 2013. Inventory of U.S. 

greenhouse gas emissions and sinks: 1990–2011. EPA 430-R-13-001.

U.S. Forest Service. 2011. National report on sustainable forests—2010.

FS-979. Washington, DC: U.S. Department of Agriculture. 212 p.

U.S. Forest Service. 2012. Future of America’s forests and rangelands: Forest 

Service 2010 Resources Planning Act Assessment. Gen. Tech. Rep. WO-87. 

Washington, DC: U.S. Department of Agriculture. 198 p.

U.S. Forest Service. 2013. Forest Inventory and Analysis national program: 

data and tools. Available at http://apps.fs.fed.us/fiadb-downloads/datamart.

html. (Accessed 17 June 2013).
60 Indicators of Climate Impacts for Forests

ECOSYSTEM SERVICES INDICATOR: TRENDS IN DIVERSITY/ABUNDANCE

OF FOREST-ASSOCIATED FLORAL AND FAUNAL SPECIES 

Metrics: Forest tree biodiversity status and trends, Forest bird biodiversity status and trends 

Summary

Forest-associated floral biodiversity status and trends would be represented by 

data on forest tree diversity, using FIA data (U.S. Forest Service 2013). Spatially 

explicit analyses of tree species over time are possible for much of the United 

States. Units would be number of tree species; percentage change over time or 

change in species occurrence could be used.

Forest-associated faunal biodiversity status and trends would be represented 

by data on forest-associated bird species. A metric with the greatest near-term 

potential would use, in part, the national-level U.S. Geological Survey (USGS) 

Breeding Bird Survey (BBS) (USGS 2015b) data. Units would be number of 

birds; percentage change over time or difference from an average for categories 

of types of birds (i.e., eastern, western, boreal) could be shown.

Both metrics need further research and technical work, especially on fauna.

Additional Descriptive Text

We propose the development of metrics for a forest biodiversity indicator that 

track biodiversity status and trends in forest tree (Table 9) and bird (Table 10) 

populations. Dissimilarities in life history and population characteristics between 

plants and animals, in addition to differences in data availability, will require 

different approaches for tracking biodiversity change between the two metrics.

Forest Faunal Biodiversity Status and Trends

Although national-level data are limited for fauna other than birds, efforts such 

as the USGS Amphibian Research and Monitoring Initiative Database (see USGS 

2015a) are currently expanding and may serve as useful indicators for other taxa. 

Forest-associated species population status could also be monitored through 

changes in species conservation status. The International Union for the 

Conservation of Nature (IUCN) Red List of Threatened Species identifies 

conservation status of more than 45,000 species globally. Species are assigned 

to a Red List category, identifying their risk of extinction, based on a suite of 

objective criteria (IUCN 2001). Changes in the Red List category for a species 

can indicate changing population size, and a broad-scale analysis of suites of 

species (in this case, forest-associated) can provide a measure of changes in 

biodiversity (e.g., Butchart et al. 2004).
Appendix 1: Additional Indicator Details 61

Decision criterion Ranking Justification 

Link to conceptual framework Best Links directly to Ecosystem services and goods 

attribute, coupled with Structure and function, arrows 

4 and 5

Defined relationship to climate, 

feedbacks, or impacts

Best Studies show long-term impacts of climate on 

biodiversity; modeling studies indicate relationship.

Spatial scalability Best FIA data are collected (across about 130,000 plots) 

in a nationally consistent sampling protocol, with one 

plot representing 6,000 ac (2,428 ha) of land.

Temporal scalability Best FIA plots are inventoried every 5 to 7 years in the 

East and every 10 years in the West.

Of national (not necessarily 

nationwide) significance? Should 

link to the conceptual model 

Best Yes for national reporting. Several possible important 

management priorities are tied to biodiversity, so it is 

very relevant.

Relevance to management 

decisions

Best Biodiversity is one of several possible management 

priorities. 

Usefulness for educational 

purposes

Sufficient Unless effects are dramatic, the metrics may not be 

easily understood by public. 

Is it a leading indicator? Not applicable Not proposed as leading indicator

Builds on existing data sources Best Readily available

Builds on existing indicator 

products

Best Readily available

If new indicator proposed, 

likelihood of development and 

testing within 1 year given 

existing funding sources 

This is not 

necessarily new, 

but would be new 

in this context.

To our knowledge, no targeted funding specifically for 

this 

Stability/Longevity of dataset Best FIA program is well-established.

Stability/Longevity of indicator Sufficient Additional calculations are needed for indicators.

Scientific validity of indicator Best Many scientific studies confirm its validity, although 

more research on the information that the indicator 

provides in a climate context could be useful.

Data publicly available and 

transparent

Sufficient Data publicly available but somewhat complicated to 

use

Indicator methods fully 

transparent and documented

Best See existing literature.

Table 9.—Decision criteria for Ecosystem services indicator: Trends in diversity/abundance of 

forest tree species
62 Indicators of Climate Impacts for Forests

Table 10.—Decision criteria for Ecosystem services indicator: Trends in diversity/abundance of 

forest-associated bird species

Decision criterion Ranking Justification 

Link to conceptual framework Sufficient Links directly (arrows 3 and 5, and Ecosystem services 

and goods attribute)

Defined relationship to climate, 

feedbacks, or impacts

Sufficient Although data suggest that climate change is affecting 

avian populations, numerous other drivers probably 

influence this indicator as well.

Spatial scalability Best Breeding Bird Survey data allow analyses at the regional 

through national-level scales.

Temporal scalability Best Data are available from 1966 through the present.

Of national (not necessarily 

nationwide) significance? Should 

link to the conceptual model

Best Data have national-level coverage and are available for 

more than 400 avian species.

Relevance to management 

decisions

Sufficient Numerous management strategies have been 

suggested or implemented for maintaining avian 

biodiversity under climate change. The Breeding 

Bird Survey provides one measure of biodiversity (as 

included in the framework) but has data on only one 

taxon.

Usefulness for educational 

purposes

Best This indicator already incorporates public education/

outreach and, given widespread interest in bird species, 

has additional possibilities.

Is it a leading indicator? Not applicable Not applicable

Builds on existing data sources Best Data are readily available.

Builds on existing indicator 

products

Best Data are readily available.

If new indicator proposed, 

likelihood of development and 

testing within 1 year given 

existing funding sources 

Relatively new 

in this context

To our knowledge, no targeted funding specifically for 

this

Stability/Longevity of dataset Best Continuous data collection since 1966

Stability/Longevity of indicator Sufficient Additional research may be needed, but sufficient 

information is available. 

Scientific validity of indicator Best More than 450 scientific journal articles have used 

Breeding Bird Survey data in analyses.

Data publicly available and 

transparent

Best Data (raw and trend estimates) are available on Web 

site.

Indicator methods fully 

transparent and documented

Best Methods are well documented on Web site and 

in numerous published articles. More research to 

understand the information that the indicator provides 

in a climate context would be useful. There are many 

different species. Some may be more indicative of 

climate impacts than others. Additional research could 

prove fruitful.
Appendix 1: Additional Indicator Details 63

This indicator of climate change impacts on forest biodiversity status and trends 

will be particularly relevant given the importance of considering biodiversity in 

policy and management decisions, especially those involving large temporal and 

spatial scales (Hooper et al. 2005). The BBS will be the focus of the forest fauna 

biodiversity indicator because this team believes it to have the greatest potential. 

Other indicators that we considered are referenced in the text above and in the 

section on other considered indicators.

What Is the Link to Climate Variability and Change or Relevance?

Forest ecosystems serve as habitat for a wide range of floral and faunal species. 

Consequently, climate-induced alterations in forest structure could have profound 

implications for forest-associated species. In turn, biodiversity conveys numerous 

functional benefits to forest ecosystems, including reduced susceptibility to 

invasion after disturbance and enhanced ecosystem reliability (Balvanera et al. 

2006). Research also has linked biodiversity to ecosystem primary productivity 

(Cardinale et al. 2007). Robust indicators of change in forest biodiversity will 

therefore be important for tracking forest community response to climate change.

What Are the Drivers of This Indicator, and What Are Their Impacts?

Forest floral biodiversity status and trends—Plant species are expected to 

respond in one of three ways to the numerous climate change effects that could 

push their current habitat out of their tolerance limits: 1) persistence in situ if 

within species’ tolerance limits, 2) range shift, or 3) local extirpation (Davis et al. 

2005). As plant species are eliminated from existing areas and are successfully 

dispersed to new areas, the last two responses could affect forest biodiversity 

and its associated ecological benefits. Weak correlations between change in tree 

seedling diversity and latitude have been detected in the Eastern United States, 

along with regional increases in the seedling diversity of species with longerdistance dispersal capacity (Potter and Woodall 2012). 

Forest faunal biodiversity status and trends—Climate change can affect 

faunal biodiversity through a variety of mechanisms including shifts in 

geographic range, phenological changes, and physiological stress (Thuiller 

2007). The ability of a species to respond or adapt to these changes is probably 

specific to the species and region.

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, By Whom and How Was It Used and When Was It Initiated?

Forest tree biodiversity status and trends—The fundamental importance of 

biodiversity to forest management and forest health monitoring at a national 

scale is recognized by its incorporation into indicators of forest sustainability, 

including the Montreal Process Criteria and Indicators for the Conservation 

of Sustainable Management of Temperate and Boreal Forests (see U.S. Forest 

Service 2011). 
64 Indicators of Climate Impacts for Forests

Forest bird biodiversity status and trends—The use of wild bird surveys as an 

indicator of biodiversity and ecosystem health is widespread around the world. 

Wild bird indicators are in use by numerous European national governments 

(Gregory and van Strien 2010) and the Biodiversity Indicators Partnership. A 

recent study using BBS data found a general pattern of northward shifts in avian 

breeding range, consistent with expectations of climate change (Hitch and Leberg 

2007). 

Relevance to Management Decisions

Forest tree biodiversity status and trends—Forest tree biodiversity is an 

important management concern at multiple scales. The following is from the 

FIA program Web site: “As the Nation’s continuous forest census, our program 

projects how forests are likely to appear 10 to 50 years from now. This enables 

us to evaluate whether current forest management practices are sustainable in the 

long run and to assess whether current policies will allow the next generation to 

enjoy America’s forests as we do today” (U.S. Forest Service 2013).

Forest bird biodiversity status and trends—Maintaining or increasing floral 

and faunal diversity is a goal of numerous land management agencies. A variety 

of management strategies, such as maintaining movement corridors, have been 

suggested for maintaining biodiversity under climate change. An indicator that 

allows examination of avian population trends could be used to help inform these 

management decisions.

Other Indicators Considered But Not Recommended at This Time 

Forest floral biodiversity status and trends—We considered two other 

metrics. One was assessments of tree species range shifts. These analyses may 

be possible. Most of the analyses would probably involve use of FIA data, 

but would require the identification of indicator species, which could prove 

challenging. Additionally, research is ongoing regarding how best to quantify 

tree range shifts. Finally, extra cycles of measurements on FIA plots over time 

may be required to be able to detect meaningful shifts. The other floral metric 

we considered was understory flora biodiversity status and trends. However, 

inventories of understory plants have been conducted on a subset of FIA plots in 

only a few regions, with remeasurements occurring on only a small number of 

plots. Indicators of forest plant diversity exclusive of trees would have to rely on 

static, county-level occurrence data available through the USDA Plants Database 

(Natural Resources Conservation Service 2015); assessing change over time 

would not be possible. Because of these limitations, we did not recommend either 

of these.

Forest fauna biodiversity status and trends—We considered a variety 

of indicators including indicators based on number of species (e.g., Global 

Biodiversity Information Facility [GBIF]) and indicators based on changes 

in species conservation status (e.g., IUCN Red List of Threatened Species). 

The advantage of these two approaches over the population trend indicator 

that we have suggested is that they include data for a large suite of taxa. The 

disadvantage of these types of biodiversity indicators is that many of them rely 

on museum records and so provide only a static representation of diversity. In 

contrast, the trend data allow a more temporally dynamic picture (which would 
Appendix 1: Additional Indicator Details 65

be important for climate change). The disadvantage of the IUCN Red List of 

Threatened Species is that this index is not as quantitative and would not allow 

fine-scale spatial and temporal analyses of population trends. Data from BBS are 

available both in raw form and as estimates of trends.

Usefulness for Educational Purposes

Forest tree biodiversity status and trends—Change in forest tree biodiversity 

is a relatively simple concept; people can easily grasp the concept of forests 

containing fewer or more species. The spatial scalability of the indicator can 

allow people to understand how climate change (along with other drivers) could 

be affecting the diversity of tree species that occur in their areas. 

Forest bird biodiversity status and trends—The BBS can be useful for 

educational purposes for several reasons. First, education is already inherent in 

the indicator because the survey is conducted primarily by citizen scientists and 

thus relies on public education and outreach to achieve high-quality data. Second, 

bird watching is a popular recreational activity for a large number of people. 

An indicator that incorporates a taxon with such widespread popularity enables 

additional educational opportunities.

Data Availability

Length of Records of Dataset 

Forest tree biodiversity status and trends—Initial federal forest inventory 

efforts were undertaken starting in 1930. The inventory program evolved over 

time, with additional information collected by using a variety of methods across 

the United States. The FIA sampling protocol was standardized across the 

country beginning about 2000, and the program’s annual data collection 

approach is ongoing.

Forest bird biodiversity status and trends—The BBS has data available from 

1966 through the present. Survey routes have been added over time, so earlier 

datasets cover less geographic area than more recent years’ efforts.

Metadata 

Forest tree biodiversity status and trends—The FIA data and documentation 

are available at U.S. Forest Service (2013).

Forest bird biodiversity status and trends—Metadata are available at USGS 

(2015b).

Stability/Longevity of Dataset and Indicator 

Forest tree biodiversity status and trends—Standardized data collection 

began about 2000, varying by state. Eastern states (on a 5- or 7-year cycle) have 

finished their first inventory of plots and, in some places, the second inventory. 

Some western states have completed their first inventory of plots (on a 10-year 

cycle), but some lag. Ongoing data collection is expected to remain stable, 

depending on federal funding.

Forest bird biodiversity status and trends—The BBS appears to be very stable 

and has been gaining interest since its introduction in 1966.
66 Indicators of Climate Impacts for Forests

Notes About the Data (Recent Changes in Analysis 

or Collection Methods) 

Forest tree biodiversity status and trends—Inventory data are available 

from before the transition from periodic to annual inventory (ca. 2000), but it is 

difficult to compare data collected under the two inventory approaches.

Forest bird biodiversity status and trends—Although the general data 

collection protocols have remained fairly consistent over time, the BBS is 

increasingly taking advantage of current statistical analyses and geospatial 

technology to augment the survey data. 

Spatial and Temporal Scalability 

Forest tree biodiversity status and trends—Data from FIA are highly scalable 

spatially and, to a lesser degree, temporally. Data are collected (across about 

130,000 forest plots) in a nationally consistent sampling protocol, with one plot 

representing 6,000 acres (2,428 hectares) of land. Plots are inventoried every 

5 or 7 years in the East and every 10 years in the West.

Forest bird biodiversity status and trends—Data from the BBS allow regional 

through continent-wide analyses of avian species populations trends. 

Details About the Indicator

Type of Indicator (Current, Leading, Both) 

Current

Geographic Scope and Scale of Analysis

Forest tree biodiversity status and trends—The geographic scope of the 

analysis would be national, using data from about 130,000 FIA plots. Plot-level 

results would be aggregated, most likely to ecoregions.

Forest bird biodiversity status and trends—Data are available for more than 

4,100 survey routes and 400 avian species across the United States and Canada. 

Approach (e.g., Single Measure, Composite)

Forest tree biodiversity status and trends—The difference in data collection 

between the eastern and western states will require different approaches for 

the two regions. Given that the first 10-year cycle of data collection is not yet 

complete in much of the West (although plots have been revisited in some areas 

of some states), it will be necessary to determine baseline forest tree biodiversity 

for this region. Data would be collected for both trees and seedlings. In the 

East, most states are well into their second 5- or 7-year inventory cycle (with 

some starting their third), so it will be possible to establish baseline biodiversity 

and to assess change over time in biodiversity. Again, this effort would be for 

both trees and seedlings, as change in seedling diversity is expected to be a 

leading indicator of change in overall forest biodiversity. Biodiversity would be 

quantified primarily as number of tree species, although biodiversity metrics that 

account for the evolutionary relationships among species also have utility.
Appendix 1: Additional Indicator Details 67

Forest bird biodiversity status and trends—Data from the BBS are available 

both in raw form and as trend data. Analyses could be conducted at the regional 

level up through a continent-wide approach. Data could be used in a variety 

of ways including general monitoring of forest avian population trends (e.g., 

increases/decreases in single or multiple species populations), changes in forest 

avian community structure, or changes in population ranges.

Purposes and Conceptual Framework

In terms of the conceptual framework, biodiversity of flora links directly to the 

Ecosystem services and goods attribute, coupled with Structure and function, 

arrows 4 and 5. Biodiversity of fauna links directly to arrows 3 and 5, and 

the Ecosystem services and goods attribute. The fundamental importance of 

biodiversity to forest management and forest health monitoring at a national 

scale is recognized by its incorporation into indicators of forest sustainability, 

including the Montreal Process Criteria and Indicators for the Conservation of 

Sustainable Management of Temperate and Boreal Forests. Years of research 

have documented many functional benefits of biodiversity to natural ecosystems, 

including reduced susceptibility to invasion, enhanced ecosystem reliability, 

and increased productivity. Changes in forest biodiversity as a result of altered 

climatic conditions may affect the ability of forests to provide these functional 

benefits.

Composition and Methodology

Forest tree biodiversity status and trends—Data can be used to evaluate 

change in the biodiversity over time of forest trees and seedlings on as many as 

130,000 FIA plots across the conterminous United States and southeast Alaska, 

with plot-level results aggregated to the ecoregion scale.

Forest bird biodiversity status and trends—Methods of collecting data for the 

BBS may be described as follows:

Each year during the height of the avian breeding season, June for 

most of the United States and Canada, participants skilled in avian 

identification collect bird population data along roadside survey 

routes. Each survey route is 24.5 miles long with stops at 0.5-mile 

intervals. At each stop, a 3-minute point count is conducted. During 

the count, every bird seen within a 0.25-mile radius or heard is 

recorded. Surveys start one-half hour before local sunrise and take 

about 5 hours to complete (USGS 2015b).

Scientific Validity of Indicator

Forest tree biodiversity status and trends—Sampling protocols and data 

sampling methods for FIA are thoroughly documented and are based on years of 

rigorous statistical design; checks are conducted on data quality. Use of the FIA 

data to assess changes in forest tree and seedling biodiversity over time has been 

peer reviewed (Potter and Woodall 2012).
68 Indicators of Climate Impacts for Forests

Forest bird biodiversity status and trends—Breeding Bird Survey data are 

widely applied across the scientific and ornithological communities. These data 

have been used in more than 450 scientific journal articles and in prominent 

national reports such as the U.S. Department of the Interior’s “State of the Birds.”

What Are the Future Plans for Further Development of the Indicator?

Forest tree biodiversity status and trends—The indicator has been applied 

in eight eastern states, using two plot measurements 5 years apart on about 

7,000 FIA plots. The statistical power and geographic extent of these analyses 

will increase as FIA remeasurement data continually become available from the 

approximately 130,000 plots across the conterminous United States and southeast 

Alaska, and as plot measurements are also repeated at regular intervals over a 

longer period of time. Repeated analyses will therefore occur at regular intervals.

Forest bird biodiversity status and trends—According to USGS documents 

(Ziolkowski et al. 2010), future developments for the BBS include continued 

geographic expansion (particularly into Mexico), improvements in population 

estimation analyses, and increased incorporation of geospatial information in 

trend analyses.

Considerations for Selection of Indicator

Advantages

Forest tree biodiversity status and trends—

1) Forest tree biodiversity is easily understood.

2) Changes in climate are expected to affect forest tree biodiversity.

3) Data are collected in a systematic fashion from FIA plots across the 

conterminous United States and southeast Alaska, at a relatively high 

spatial intensity. 

4) The spatial intensity of the FIA data allows for analyses at multiple scales.

5) Plots are revisited on a regular basis, and will continue to be (assuming 

continued federal funding for the program), thus allowing for time-series 

analyses.

6) The FIA data are publicly available.

Forest bird biodiversity status and trends—

1) Data are available for more than 400 avian species across the United States 

and Canada.

2) Data are collected in a systematic fashion and, in many areas, has been 

continuously collected for decades.

3) The spatial intensity allows for analyses at multiple scales.

4) Data are publicly available (both raw data and trend estimates) at the BBS 

Web site.
Appendix 1: Additional Indicator Details 69

Disadvantages

Forest tree biodiversity status and trends—

1) The FIA data have been collected in a systematic fashion nationally only 

since about 2000. Data are available before that, but problematic to use.

2) The 10-year panel system in the West means that the options for time-series 

analyses in this region are limited, as each plot is visited only once every 

10 years.

3) The 5- to 7-year window in the East may be too short a time to evaluate 

biodiversity change resulting from climate change, but additional 

measurements will extend the window of time.

Forest bird biodiversity status and trends—

1) Although an indicator that includes a wide range of forest taxa would 

be preferable, the BBS has data only for birds. Similar national-level 

wildlife survey efforts have been initiated for several other taxa (e.g., 

USGS Amphibian Research and Monitoring Initiative, National Ecological 

Observatory Network [NEON] efforts) but do not currently have the 

quantity and geographic range of the BBS.

2) Avian point count surveys, particularly those like the BBS that are 

conducted along roadways, have a variety of documented shortcomings, 

including species-specific detection probabilities. This method of surveying 

may not be suitable for all avian species. 

Literature Cited

Balvanera, P.; Pfisterer, A.B.; Buchmann, N.; He, J.S.; Nakashizuka, T.; Raffaelli, 

D.; Schmid, B. 2006. Quantifying the evidence for biodiversity effects on 

ecosystem functioning and services. Ecology Letters. 9: 1146–1156.

Butchart, S.H.M.; Stattersfield, A.J.; Bennun, L.A.; Shutes, S.M.; Akakaya, H.R.; 

Baillie, J.E.M.; Stuart, S.N.; Hilton-Taylor, C.; Mace, G.M. 2004. Measuring 

global trends in the status of biodiversity: Red List Indices for birds.

PLoS Biology 2. e383.

Cardinale, B.J.; Wright, J.P.; Cadotte, M.W.; Carroll, I.T.; Hector, A.; Srivastava, 

D.S.; Loreau, M.; Weis, J.J. 2007. Impacts of plant diversity on biomass 

production increase through time because of species complementarity. 

Proceedings of the National Academy of Sciences. 104: 18123–18128.

Davis, M.B.; Shaw, R.G.; Etterson, J.R. 2005. Evolutionary responses to 

changing climate. Ecology. 86: 1704–1714.

Gregory, R.D.; van Strien, A. 2010. Wild bird indicators: using composite 

population trends of birds as measures of environmental health.

Ornithological Science. 9: 3–22.

Hitch, A.T.; Leberg, P.L. 2007. Breeding distributions of North American bird 

species moving north as a result of climate change. Conservation Biology. 

21: 534–539.
70 Indicators of Climate Impacts for Forests

Hooper, D.U.; Chapin, F.S.; Ewel, J.J.; Hector, A.; Inchausti, P.; Lavorel, S.; 

Lawton, J.H.; Lodge, D.M.; Loreau, M.; Naeem, S.; Schmid, B.; Setala, H.; 

Symstad, A.J.; Vandermeer, J.; Wardle, D.A. 2005. Effects of biodiversity 

on ecosystem functioning: a consensus of current knowledge. Ecological 

Monographs. 75: 3–35.

International Union for the Conservation of Nature and Nature Resources 

[IUCN]. 2001. IUCN Red List categories and criteria, Version 3.1. Gland, 

Switzerland: IUCN Species Survival Commission. Available at http://www.

icunredlist.org/technical-documents/categories-and-criteria/2001-categoriescriteria. [Date accessed unknown].

Natural Resources Conservation Service. 2015. The PLANTS Database home 

page. Greensboro, NC: U.S. Department of Agriculture, Natural Resources 

Conservation Service, National Plant Data Team. Available at http://plants.

usda.gov. (Accessed 12 February 2015).

Potter, K.M.; Woodall, C.W. 2012. Trends over time in tree and seedling 

phylogenetic diversity indicate regional differences in forest biodiversity 

change. Ecological Applications. 22: 517–531.

Thuiller, W. 2007. Biodiversity: climate change and the ecologist. Nature. 

448: 550–552.

U.S. Geological Survey. 2015a. Amphibian Research and Monitoring 

Initiative home page. Available at http://armi.usgs.gov/. (Accessed 

12 February 2015).

U.S. Geological Survey. 2015b. North American Breeding Bird Survey 

home page. Available at https://www.pwrc.usgs.gov/BBS/. (Accessed 

12 February 2015). 

Ziolkowski, D., Jr.; Pardieck, K.; Sauer, J.R. 2010. On the road again for a bird 

survey that counts. Birding. 42(4): 32–40.

Other Resources 

Major contact: Forest Inventory and Analysis (FIA) program of the U.S. Forest 

Service (http://www.fia.fs.fed.us/)
Appendix 1: Additional Indicator Details 71

STRUCTURE AND FUNCTION INDICATOR: FOREST GROWTH/PRODUCTIVITY 

Metrics: Net annual forest growth per unit area, Forest net primary productivity 

Summary 

Net annual forest growth per unit area (acre or hectare) is defined as the average 

annual net increase in volume or mass of trees during the period between 

inventories. The volume of trees that died or that became nonmerchantable over 

the period is subtracted from the summed growth on live trees, which means net 

growth may be a negative number. Net annual forest growth is available from 

FIA data. Units are tons of carbon per acre (metric tons of carbon per hectare) per 

year or equivalent.

Forest net primary productivity (NPP) can be estimated by using a remote 

sensing approach based on MODIS. The estimates are modeled from 

observations, with estimates available annually. Units are kilograms of carbon 

per square meter per year or equivalent.

Both metrics are available, and continue to be updated. For the phenology team, 

NPP may be a more appropriate metric.

Additional Descriptive Text

Net annual growth in U.S. forests totaled nearly 26.7 billion cubic feet in 2006, 

which is about three-and-one-half times the rate of mortality (Oswalt et al. 2014). 

Net growth is an important indicator because it can be affected by changes 

in temperature, water availability, length of growing season, and increases in 

atmospheric carbon dioxide (CO2 ). The result may be an increase or a decrease 

in net growth (U.S. Forest Service 2011). Management activities can also affect 

growth, including species composition, so results should be carefully interpreted. 

Net annual growth is defined as the average annual net increase in volume of 

trees during the period between inventories. The volume of trees that died or that 

became nonmerchantable over the period is subtracted from the growth, which 

means net growth can be a negative number. 

Net annual growth can be calculated for a range of geographic levels (e.g., 

national, subnational, ecological unit, and state). The smaller the area, the larger 

the confidence level around the estimate, so a smaller geographic resolution 

should be carefully considered. Because field data are remeasured every 5 or 

more years, growth changes are reported as averages over the period and changes 

cannot be easily attributed to any one year, which is often of interest when 

looking at climate events. Initial measurements begin in 1952, with a number of 

5- to 10-year growth periods occurring through to current measurements. A new 

annualized inventory design was initiated state-by-state starting in different years 

in the 2000s, with net growth now being calculated from remeasured plots rather 

than changes in results aggregated over landscapes. 
72 Indicators of Climate Impacts for Forests

The MODIS product (USGS, Land Processes Distributed Active Archive Center 

2015) is created every 8 days. Thus annual estimates of net growth can be 

derived, which is not feasible from the FIA data (Table 11).

What Is the Link to Climate Variability and Change or Relevance?

Forest productivity is a biologic rate controlled directly by climate. On short 

timescales, productivity can be affected by interannual variability (e.g., drought). 

On 10- to 100-year timescales productivity is affected by shifts in temperature, 

growing season length, and moisture availability. In addition, increased CO2 in 

the atmosphere has been postulated to enhance growth of individual plants, an 

effect that should be manifest in this indicator. Productivity can also be indirectly 

affected by climate (e.g., by increasing drought- or insect-related mortality).

What Are the Drivers of This Indicator, and What Are Their Impacts?

Both human and climate drivers can affect forest productivity. Forest 

management can affect stand-level productivity through silvicultural practice 

(including fertilization, regeneration strategy, and thinning) and fire suppression.

Relevance to Management Decisions

Growth rates directly affect the volume of merchantable timber within the United 

States and the rate at which that timber can be extracted. Slowing growth rates 

would influence both forest management decisions and the timber industry.

Other Indicators Considered But Not Recommended at This Time 

Productivity is a crucial aspect of forests that is known to be affected by climate. 

Growing degree days may be a similar indicator, but we thought that productivity 

was a more direct measure of change in forests, and that other teams may include 

growing degree days.

Data Availability

Length of Records of Dataset

FIA: net growth data available since 1952; available in annual panels based on 

remeasured plots since 2000.

MODIS: MODIS NPP product available at 8-day resolution, beginning in 2000.

Stability/Longevity of Dataset and Indicator

The FIA program is operational and Congressionally mandated. Research 

supporting MODIS NPP is a long-term activity, although prospects for 

continuation past the MODIS lifetime are unclear.

Spatial and Temporal Scalability

Data from FIA give regional information on growth rates with known sampling 

error as a function of number of plots incorporated into the analysis. MODIS 

NPP is a geospatial product with spatial resolution of 500 m (0.3 miles). The FIA 

program remeasures plots every 5 to 10 years, whereas MODIS NPP products are 

generated every 8 days, subject to cloud cover limitations.
Appendix 1: Additional Indicator Details 73

Table 11.—Decision criteria for Structure and function indicator: Forest growth/productivity

Decision criterion Ranking Justificationa

Link to conceptual framework Best Links directly to Structure and function attribute. 

NPP through MODIS directly links to climate; net 

growth links to climate over a longer term.

Defined relationship to climate, 

feedbacks, or impacts

Best MODIS NPP links directly to climate, so it may be 

an excellent visual to show climate change; net 

growth is the result of an actual measure and is 

directly affected by climate over the period.

Spatial scalability MODIS best graphically; 

growth statistically

MODIS scalable to pixels; growth scalable down 

to counties or plots.

Temporal scalability Best MODIS available to an 8-day window; growth to 

5-year period.

Of national (not necessarily 

nationwide) significance? 

Should link to the conceptual 

model

Individually sufficient; 

together best

Fundamental knowledge needed about forests, 

including in terms of climate mitigation.

Relevance to management 

decisions

Best Knowledge of growth is a fundamental need to 

management, including management for climate 

response.

Usefulness for educational 

purposes

Best MODIS NPP is actually related to climate and is 

visual, so it is easy to convey information about it.

Is it a leading indicator? No Not applicable

Builds on existing data 

sources

Best Data sources exist and are available.

Builds on existing indicator 

products

Yes Both build on existing sources.

If new indicator proposed, 

likelihood of development and 

testing within 1 year given 

existing funding sources 

Not applicable Not applicable

Stability/Longevity of dataset Best for net growth; 

probably sufficient for 

MODIS NPP, which is a 

research product

Datasets are available; sometimes updates are 

made. The datasets are generally very stable.

Stability/Longevity of indicator Best for net growth; 

probably sufficient for 

MODIS NPP, which is a 

research product

Indicator is expected to be of interest and stable 

for long term.

Scientific validity of indicator Each approach is valid in 

its own way.

Peer-reviewed literature is available for both.

Data publicly available and 

transparent

Best to sufficient Data are publicly available.

Indicator methods fully 

transparent and documented

Best to sufficient Some research approaches for MODIS NPP will 

be less transparent than others.

a Acronyms: NPP = net primary productivity; MODIS = moderate resolution imaging spectroradiometer
74 Indicators of Climate Impacts for Forests

Details About the Indicator

Type of Indicator (Current, Leading, Both) 

Current

Geographic Scope and Scale of Analysis

National to state to county, although precision of the estimates decreases for 

smaller areas. Net primary productivity available as pixels. 

Approach (e.g., Single Measure, Composite)

The use of net growth as a metric of productivity provides measured data that 

are consistent with the approach used for greenhouse gas inventories, climate 

mitigation, and bioenergy supply. The FIA program provides the official forest 

statistics for the United States, based on data from its plots (U.S. Forest Service 

2013), and thus this is the approach traditionally used. However, field data are 

remeasured no more often than every 5 years, so growth changes are reported 

as averages over the period. Thus changes cannot be easily attributed to any one 

year, which is often of interest when looking at climate events. 

A second metric for the productivity indicator NPP is estimated by using a 

remote sensing (MODIS) approach. This may be a cross-cutting indicator 

across land uses, which another team might take the lead on. The MODIS GPP 

(gross primary productivity)/NPP product (MCD17) is based on a light-use 

efficiency model for photosynthesis, taking in the satellite-based fraction of 

photosynthetically active radiation (fPAR) and leaf area. There are many studies 

of ways to improve the standard MODIS NPP product for forests, and these 

should be considered (Turner et al. 2006). As an indicator, NPP can be more 

closely related to climate because it records the biologic activity of forests, and 

depends directly on temperature, precipitation, and available solar radiation. In 

addition the MODIS product is created every 8 days. However, MODIS NPP is 

an output of research products as opposed to being an operational product, and 

its longevity is not clear.

Purposes and Conceptual Framework

In the conceptual framework, productivity links directly to the Structure and 

function attribute; NPP through MODIS directly links to climate and net growth 

links to climate over a longer term. Productivity (growth) is a fundamental 

important feature of forests driven by climate and affected by management.

Scientific Validity of Indicator

The validity of the net growth approach is well established for climate mitigation 

purposes. Although the net growth approach is operational and has been 

scientifically valid for centuries, and the MODIS NPP approaches continue to 

be debated in scientific studies, the MODIS NPP approach may be thought of as 

being more relevant because its model is directly dependent on climate-related 

variables. 
Appendix 1: Additional Indicator Details 75

What Are the Plans for Further Development of the Indicator? 

MODIS NPP continues to be debated and methods improved in the scientific 

literature. In some ways it is a composite indicator of climate effects.

Considerations for Selection of Indicator

Advantages

Forest growth rates are strongly influenced by local climate, and long-term 

changes in growth rates provide unique information on how climate change 

affects forest ecology. Metrics of NPP from FIA and satellite-based sources 

provide complementary, mutually reinforcing information.

Disadvantages

Changes in growth rates due to climate change can be expected to evolve slowly 

through time (over several decades), requiring careful, consistent measurement. 

The MODIS NPP record is a research product, and additional work is needed to 

understand its compatibility with long-term FIA measures of net growth.

Literature Cited

Oswalt, S.N.; Smith, W.B.; Miles, P.D.; Pugh, S.A. 2014. Forest resources of the 

United States, 2012: a technical document supporting the Forest Service 

2015 update of the RPA Assessment. Gen. Tech. Rep. WO-91. Washington, 

DC: U.S. Department of Agriculture, Forest Service. 218 p.

U.S. Forest Service. 2011. National report on sustainable forests—2010.

FS-979. Washington, DC: U.S. Department of Agriculture. 212 p. 

U.S. Geological Survey [USGS], Land Processes Distributed Active Archive 

Center. 2015. MODIS data products table. Sioux Falls, SD: U.S. 

Department of the Interior. Available at https://lpdaac.usgs.gov/products/

modis_products_table. (Accessed 1 April 2015).

Other Resources

U.S. Geological Survey, Land Processes Distributed Active Archive Center. 

2015. MODIS data products table. Sioux Falls, SD: Department of the 

Interior. Available at https://lpdaac.usgs.gov/products/modis_products_table. 

(Accessed 1 April 2015).

National Aeronautics and Space Administration [NASA]. 2015. Earth 

observatory, global maps of net primary productivity. Available at http://

earthobservatory.nasa.gov/GlobalMaps/view.php?d1=MOD17A2_M_PSN. 

(Accessed 15 March 2015). [Contains example images of the net primary 

productivity indicator.]
76 Indicators of Climate Impacts for Forests

Running, S.W.; Nemani, R.R.; Heinsch, F.A.; Zhao, M.S.; Reeves, M.; 

Hashimoto, H. 2004. A continuous satellite-derived measure of global 

terrestrial primary production. Bioscience. 54: 547–560.

U.S. Forest Service. 2013. Forest Inventory and Analysis national program: 

data and tools. Available at http://apps.fs.fed.us/fiadb-downloads/datamart.

html. (Accessed 17 June 2013).

DISTURBANCE INDICATOR: WILDFIRE EFFECTS 

Metrics: Burned area, Number of large fires, Fire severity

Summary

The following metrics for wildfire effects (Table 12) are available from the 

Monitoring Trends in Burn Severity (MTBS; 2013) dataset, derived from remote 

sensing observations:

Burned area is an identification and simple summation for a given area and time 

period. The minimum burned area identified in the Western United States in the 

MTBS dataset is 1,000 acres, and 500 acres in the Eastern United States.

Number of large fires is determined by quantifying the statistical distribution of 

fire size over time. No particular threshold for “large” is assumed at this time. 

However, the minimum burned area identified in the MTBS dataset is 1,000 acres 

in the Western United States, and 500 acres in the Eastern United States.

Fire severity (typically damage to vegetation) is a function of the intensity 

(energy release during active burning) of fire. 

Although wildfire is stochastic in space and time, sufficient data exist to establish 

clear relationships between fire characteristics and climate parameters. The 

methodology exists to produce these metrics, and they are currently available 

with some technical work and perhaps research.

Additional Descriptive Text

Most of the variability in historical Burned area is attributed to combinations of 

seasonal temperature and precipitation. In most forest ecosystems, fire area is 

primarily associated with drought conditions, specifically, increased temperature 

and decreased precipitation in the year of fire and seasons before the fire season. 

In arid forests and woodland in the Southwest, fire area is influenced primarily 

by the production of fuels in the year before fire and secondarily by drought in 

the year of the fire. 
Appendix 1: Additional Indicator Details 77

Decision criterion Ranking Justificationa

Link to conceptual 

framework

Best Links directly (arrow 7 and Disturbance effects attribute), as 

well as to Forest extent.

Defined relationship to 

climate, feedbacks, or 

impacts

Best It is a simple indicator that has already been shown to be well 

correlated with climate variability on an annual and seasonal 

basis. 

Spatial scalability Best For NIFC data, should be possible. For MTBS data, polygons 

available to be summarized at different scales; minimum 

resolution differs in the Western and Eastern United States. 

Of national (not necessarily 

nationwide) significance? 

Should link to the conceptual 

model 

Best Of national significance because area burned potentially 

leads to needs of land management and help to communities; 

policies need to consider these needs as well as operations.

Temporal scalability Best Annual, and can be aggregated 

Relevance to management 

decisions

Best Relevant in many ways: equipment and personnel needs, 

understanding for healthy forests and silvicultural needs, 

national policies and budgets.

Usefulness for educational 

purposes

Best The drama of extensive damage will make this indicator of 

great interest to the public and policy makers; strong for 

education opportunities in climatic, biological, atmospheric, 

and ecological sciences, including the fact that wildfire has a 

natural place in forests and the world.

Is it a leading indicator? Not being 

proposed as one

Research may show this could be used as a leading 

indicator.

Builds on existing data 

sources

Best Yes, NIFC data available since 1916. MTBS data available 

since 1984.

Builds on existing indicator 

products

Best Readily available

If new indicator proposed, 

likelihood of development 

and testing within 1 year 

given existing funding 

sources 

New only in this 

context

It is unknown if resources are targeted for studying this 

indicator for this purpose. There are many studies regarding 

wildfire.

Stability/Longevity of dataset Best to Needs 

improvement

The NIFC dataset is standard; additional information from 

MTBS dataset may not be funded going forward.

Stability/Longevity of 

indicator

Best Expected to be of great interest as an indicator so should be 

stable.

Scientific validity of indicator Best Datasets accepted as standard, and many publications 

available.

Data publicly available and 

transparent

Sufficient The data can be obtained from NIFC, but requires a formal 

request; the data are not online. MTBS data are available 

online.

Indicator methods fully 

transparent and documented

Sufficient, could 

use improvement

Additional research to understand the information that the 

indicator provides in a climate context would be useful.

Table 12.—Decision criteria for Disturbance indicator: Wildfire effects

Burned area

a Acronyms: NIFC = National Interagency Fire Center; MTBS = Monitoring Trends in Burn Severity
78 Indicators of Climate Impacts for Forests

Table 12 (continued).—Decision criteria for Disturbance indicator: Wildfire effects

Number of large fires (showing only those rows which differ from decision criteria for Burned area) 

Decision criterion Ranking Justification 

Defined relationship to climate, 

feedbacks, or impacts

Sufficient Correlated with climate variability on an annual and seasonal 

basis, but not as closely as Burned area

Of national (not necessarily 

nationwide) significance? Should 

link to the conceptual model 

Best This is of national significance because 2 percent of the 

fires (the largest fires) are enormously expensive. This point 

currently is routinely being made in federal budget requests.

Relevance to management 

decisions

Best Relevant in many ways: equipment and personnel needs, 

understanding for healthy forests and silvicultural needs, 

national policies and budgets. Fighting large fires has 

specialized needs as compared to average sized fires.

Fire severity (showing only those rows which differ from decision criteria for Burned area)

Decision criterion Ranking Justificationa

Defined relationship to climate, 

feedbacks, or impacts

Sufficient It is at least partially caused by weather conditions, 

although fuel loading and conditions are also 

important.

Spatial scalability Sufficient For MTBS data, polygons available to be summarized 

at different scales; minimum resolution differs in 

Western and Eastern United States. 

Temporal scalability Needs 

improvement

Data are available only for 1984–2010, but are 

available annually.

Of national (not necessarily 

nationwide) significance? 

Should link to the conceptual model 

Best to 

sufficient

This is of national significance because increased 

fire severity could slow or stop regeneration, lead to 

increased erosion, and create major threats to health 

of forests and land; policies need to consider these 

implications as well as operations.

Relevance to management decisions Best Fire is especially viewed as linked to climate. Relevant 

in many ways: equipment and personnel needs, 

understanding for healthy forests and silvicultural 

needs, national policies and budgets.

Usefulness for educational purposes Sufficient Caution is needed to explain interaction of weather and 

fuels.

Builds on existing data sources Best Readily available online

Builds on existing indicator products Sufficient More research to understand the information that the 

indicator provides in a climate context is needed.

If new indicator proposed, likelihood 

of development and testing within 1 

year given existing funding sources

Only new in 

this context

Unlikely funding would happen.

Stability/Longevity of dataset Needs 

improvement

Additional information from MTBS dataset may not be 

funded going forward.
Appendix 1: Additional Indicator Details 79

Table 12 (continued).—Decision criteria for Disturbance indicator: Wildfire effects

Fire severity (showing only those rows which differ from decision criteria for Burned area)

Decision criterion Ranking Justificationa

Stability/Longevity of indicator Needs 

improvement

In a theoretical sense, the need for the indicator is 

recognized. 

Scientific validity of indicator Sufficient More research to understand the information that the 

indicator provides in a climate context is needed.

Data publicly available and 

transparent

Sufficient The data can be obtained online; users need to 

spend time understanding how the data were derived. 

User satisfaction with these data differs for different 

applications.

Indicator methods fully transparent 

and documented

Sufficient Methods documentation could be improved.

a Acronym: MTBS = Monitoring Trends in Burn Severity

Number of large fires can be determined by iteratively using a different threshold 

to determine the number of fires exceeding it. The distribution of large fires over 

time probably will differ by region in the United States.

Fire intensity is expected to increase significantly as a result of warmer 

temperature. However, fuel loading, and interannual and longer term variability 

in climate–fire relationships can affect trends, making it difficult to infer whether 

climate change is responsible. In addition, forests with high fuel loading due 

to fire exclusion will continue to be susceptible to crown fire in the absence of 

active management. Longer time series of fire occurrence, when available, will 

allow better quantification of the influence of multi-decadal climate variability 

(e.g., Pacific Decadal Oscillation and Atlantic Multi-decadal Oscillation).

What Is the Link to Climate Variability and Change or Relevance?

The effects of climate variability on burned area have been clearly documented, 

and one would expect this relationship to persist as the climate continues to 

warm. The relationship to number of large fires is not quite as strong, but is still 

apparent, especially in years when burned area is very high. Relationships to fire 

severity are mediated by local weather, which will on average be more extreme 

as the climate warms, and by fuel loading at any particular location.

What Are the Drivers of This Indicator, and What Are Their Impacts?

Dry, combustible fuels (including both live and dead vegetation) are conditioned 

to burn under states of high temperature and low precipitation. Therefore, “dry” 

years almost always have more burned area and more large fires; in some cases, 

more severe fires occur. Increased burned area will be a potentially major driver 

of ecosystem change, because it causes such a rapid change in forest structure 

and processes, “clearing the slate” for regeneration and competition of a new 

cohort of forest vegetation. Increased fire severity may have the additional effect 
80 Indicators of Climate Impacts for Forests

of altering species composition in some locations, especially if it occurs over 

large areas, thus modifying seed sources.

Has This Indicator Been Used as an Indicator by Anyone Else; If So, 

by Whom, and How Was It Used and When Was It Initiated?

It has been suggested anecdotally that burned area in the Western United States 

during the past 30 years has been caused at least partially by climate change. This 

inference is confounded by normal multi-decadal climate variability and cannot 

be supported by the current time series of fire data.

Relevance to Management Decisions

Wildfire management is arguably the greatest current challenge for federal land 

management in the Western United States in terms of vegetation management 

and restoration issues, as well as financial expenditures for fire suppression and 

hazardous fuel reduction.

Other Indicators Considered But Not Recommended at This Time 

Fire season length—Available from the National Interagency Fire Center. Our 

evaluation is that length of fire season is a poor quantitative indicator of climate 

change impacts, and we recommend that it not be used. This indicator may sound 

straightforward and definable, but it is not. First, there are many ways that could 

be used to define it, rather than one universally accepted way. Second, the time 

series of fire occurrence varies each year. If one early big fire is followed by 

2 months without fire in a season, is this still defined as an “early” fire season? 

Third, the energy release component, which is derived from fuel moisture, is 

highly variable based on seasonal variations in weather. It is also confounded by 

the magnitude and spatial distribution of fuel loading in any particular location. 

Fourth, defining seasonality of flammability for any location would vary greatly 

by elevation, aspect, topography, and vegetation type. Finally, length of fire 

season is likely to be affected by multi-decadal modes of variability (e.g., Pacific 

Decadal Oscillation), thus obscuring any climate change “signal” for fire season, 

even across several decades.

Fire evacuation costs (Canadian indicator)—This appears to be more of an 

effect than an indicator. We are unsure of a source of this information in the 

United States.

Fire suppression costs—This appears to be more of an effect than an indicator. 

We are unsure of a source of this information in the United States.

Usefulness for Educational Purposes

In the words of Flannigan and colleagues (2000: 227), “[T]he almost 

instantaneous response of the fire regime to changes in climate has the potential 

to overshadow importance of direct effects of global warming on species 

distribution, migration, substitution and extinction. Thus, fire is a catalyst for 

vegetation change.” Wildfire is a dramatic and well-publicized component 

of forest disturbance, one that is increasingly affecting both urban and rural 

communities. This creates an opportunity for education about living with fire, 

especially in a warmer climate.
Appendix 1: Additional Indicator Details 81

Data Availability

Length of Records of Dataset

Data on burned area and to some extent fire size are available from some federal 

lands since 1916, and data on fire severity for all western U.S. lands are available 

since 1984. Data are sporadic for other public and private lands. 

Stability/Longevity of Dataset and Indicator

Good for burned area and fire size. Continuity of burn severity data after 2010 

is uncertain. 

Notes About the Data (Recent Changes in Analysis 

or Collection Methods)

The early part of the dataset for burned area must be adjusted to account for 

inadequate reporting of fire from remote locations. Littell et al. (2009) made 

these adjustments at the state level for the 11 western states.

Spatial and Temporal Scalability

Spatial and temporal scaling should be possible, but characteristics such as 

wildfire size and severity differ greatly between regions of the United States. 

Details About the Indicator

Type of Indicator (Current, Leading, Both)

All are current indicators. 

Approach

Burned area is a simple summation for a given area and time period. Fire size 

can be determined by summing occurrence at different threshold sizes. Severity 

typically is a quantification of canopy mortality caused by fire for a particular 

location; it can be expressed as area with a particular magnitude of severity.

Metadata

Historical data on burned area and fire sizes are available from the National 

Interagency Fire Center (www.nifc.gov). Data on fire severity are available 

from the Monitoring Trends in Burn Severity data archive (www.mtbs.gov).

Composition and Methodology

Each wildland fire that occurs on federal and tribal lands and most fires greater 

than about 100 acres (40 ha) on state and private lands are recorded by the 

National Interagency Fire Center. 

Scientific Validity of Indicator

Underlying data will meet Information Quality Act requirements. Wildfireburned area, and, to some extent, fire size, has been associated with climate 

variability and change in the peer-reviewed scientific literature. Fire severity is 

well documented at the MTBS Web site (www.mtbs.gov) and has been used in 

the peer-reviewed literature for several applications.
82 Indicators of Climate Impacts for Forests

What Are the Plans for Further Development of the Indicator?

The indicator is operational and used extensively throughout the United States 

to support predictive services that are responsible for providing information that 

wildland fire response organizations use to determine resource allocation for 

wildland firefighting resources. Future development is focused on finer grained 

generalizations of fuel characteristics, denser networks of weather stations, 

enhanced technology for interpolating between reporting stations, and more 

consistent and high-resolution historical observed weather datasets.

Considerations for Selection of Indicator

Advantages

1) Burned area and fire size are straightforward and easily understood, and 

will presumably be collected in perpetuity.

2) Because a small number of fires make up the majority of burned area, there 

is little opportunity for error even if some small fires on private land are 

not reported.

3) Fire severity data are available online to all users.

Disadvantages

1) Fire severity data are not available before 1984 and may not be available 

after 2010.

Literature Cited

Flannigan, M.; Stocks, B.; Wotton, B. 2000. Climate change and forest fires.

Science of the Total Environment. 262(3): 221–229.

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: 1003–1021.

Monitoring Trends in Burn Survey [MTBS]. 2013. Home page. Available at 

www.mtbs.gov. [Date accessed unknown]. [Images of all metrics derived 

from MTBS can be found by year between 1984 and 2011 at this Web site. 

In addition to the conterminous United States, images are often available for 

Alaska, Hawaii, and Puerto Rico. However, the images show wildfires (above 

a certain minimum size) on all lands, not just forests. To show only wildfires 

in forests, maps would have to be overlaid.]

Other Resources

Major contact: National Interagency Fire Center (NIFC), Boise, ID; National 

Wildland Fire Coordinating Group

Eidenshink, J.; Schwind, B.; Brewer, K.; Zhu, Z.L.; Quayle, B.; Howard, S. 2007. 

A project for monitoring trends in burn severity. Journal of the Association 

for Fire Ecology. 3: 3–21.
Appendix 1: Additional Indicator Details 83

Gedalof, Z.; Peterson, D.L.; Mantua, N.J. 2004. Atmospheric, climatic and 

ecological controls on extreme wildfire years in the northwestern United 

States. Ecological Applications. 15: 154–174.

Key, C.H.; Benson, N.C. 1999. Measuring and remote sensing of burn 

severity: the CBI and NBR. Poster abstract. In: Neuenschwander, N.L.; 

Ryan, K.C., eds. Proceedings Joint Fire Science Conference and Workshop. 

Vol. II. Moscow, ID: University of Idaho and International Association of 

Wildland Fire: 15–17.

McKenzie, D.; Gedalof, Z.; Peterson, D.L.; Mote, P. 2004. Climatic change, 

wildfire, and conservation. Conservation Biology. 18: 890–902.

Westerling, A.L.; Hidalgo, H.G.; Cayan, D.R.; Swetnam, T.W. 2006. Warming 

and earlier spring increase western U.S. forest wildfire activity. Science. 

313: 940–943.

DISTURBANCE INDICATOR: FOREST INSECT AND DISEASE DAMAGE 

Metrics: Area affected by insects and diseases

Summary

Area affected by insects and diseases (Table 13) is identified and reported by 

insect or disease type and tree species by the U.S. Forest Service, which conducts 

annual aerial surveys of insect- and disease-caused tree damage. Affected area 

is available at fine (polygon) and coarse (national) scales for summarizing as 

national totals for each disturbance agent as well as for producing maps. This 

indicator will focus on insects and diseases that damage trees over large areas. 

Units are number of acres (hectares) affected by a particular insect or disease.

These metrics are available, but more work is needed to use them as an indicator, 

and to fully interpret results in the context of climate. 

What Is the Link to Climate Variability and Change or Relevance?

Climate affects insects and diseases directly through effects on development 

rates and life cycles and range limitation. In addition, the indirect effects of high 

temperatures and low precipitation increase stress in host trees, which then are 

typically more susceptible to attack by biotic disturbance agents. Recent warming 

and drought have been linked to extensive tree damage caused by multiple 

outbreaks of insects and diseases (Weed et al. 2013).
84 Indicators of Climate Impacts for Forests

Table 13.—Decision criteria for Disturbance indicator: Forest insect and disease damage

Decision criterion Ranking Justification 

Link to conceptual 

framework

Sufficient 

to best

Direct link indicated by Disturbance effects attribute and Structure 

attribute

Defined relationship to 

climate, feedbacks, or 

impacts

Best Climate affects insects and diseases directly as well as affecting host 

tree susceptibility. Because of the extensive damage, trees affected 

by insects and diseases have impacts on climate through changes in 

carbon sequestration, energy, and water fluxes.

Spatial scalability Best Fine-scale polygons available to be summarized at different spatial 

scales

Temporal scalability Sufficient 

to best

Annual datasets available. Life cycles for many major biotic 

disturbance agents are 1 year, suggesting that annual resolution is 

sufficient. Other agents have multiple life cycles per year, and thus an 

annual observation does not resolve the time of year of tree damage.

Of national (not 

necessarily nationwide) 

significance? Should link 

to the conceptual model 

Sufficient 

to best

Yes, extensive areas of forest damage are of national significance, 

especially because they can lead to increased fire risk, and issues in 

other sectors including the human economy.

Relevance to management 

decisions

Best Healthy forests and ecosystems are important for a sustainable 

planet and a sustainable human society.

Usefulness for educational 

purposes

Best Extensive damage can be visible indicators to the public and policy 

makers; strong for education opportunities in climate, biology, and 

ecosystems, including the fact that insects and disease have a 

natural place in forests.

Is it a leading indicator? Not 

applicable

Not currently proposed as a leading indicator

Builds on existing data 

sources

Best Aerial surveys are conducted annually by the U.S. Forest Service.

Builds on existing 

indicator products

Best Aerial surveys are conducted annually by the U.S. Forest Service, 

and summarized at the national scale in annual “Forest Insect and 

Disease Condition” reports.

If new indicator proposed, 

likelihood of development 

and testing within 1 year 

given existing funding 

sources 

This is not 

necessarily 

new, but 

would be 

new in this 

context.

There are many different species of insects and diseases. Some may 

be more indicative of climate impacts than others. Additional research 

could prove fruitful.

Stability/Longevity of 

dataset

Best U.S. Forest Service maintains these datasets.

Stability/Longevity of 

indicator

Best U.S. Forest Service maintains these datasets.

Scientific validity of 

indicator

Sufficient 

to best

The subjective nature of the aerial surveys confers uncertainty about 

the consistency and accuracy of the product.

Data publicly available 

and transparent

Best Yes

Indicator methods 

fully transparent and 

documented

Sufficient Methods are documented, but more research to understand the 

information that the indicator provides in a climate context, and to 

make that information clear and easily understandable, would be 

useful.
Appendix 1: Additional Indicator Details 85

What Are the Drivers of This Indicator, and What Are Their Impacts?

In addition to climate, drivers of insect and disease outbreaks include factors 

related to distribution of hosts (of which only one or a few species may be 

attacked by a particular insect or disease) and host stress (older trees and resource 

limitations associated with site conditions or stand structure). Impacts include 

changes in timber yield, wildlife habitat, carbon sequestration, and energy and 

water fluxes (Chan-McLeod 2006, Edburg et al. 2012, Hicke et al. 2012, Pugh 

and Gordon 2012). Large outbreaks causing tree mortality have had substantial 

impacts at watershed and broader scales (Bethlahmy 1974, Kurz et al. 2008).

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, by Whom, and How Was It Used and When Was It Initiated?

Indicator 3.15 of Forest Sustainability was discussed by the U.S. Forest Service 

(2011).

Relevance to Management Decisions

Tree damage (reduced growth or mortality, or a combination thereof) caused by 

insects and diseases is relevant to forest managers because of its impacts to forest 

ecosystems and its widespread extent.

Other Indicators Considered But Not Recommended at This Time 

Mortality area, which is the canopy area of live trees (Meddens et al. 2012); not 

recommended because of lack of funding to produce this annually.

ForWarn, from the U.S. Forest Service’s Eastern Forest Environmental Threat 

Assessment Center, which produces near real-time maps of potential forest 

threats; not recommended at this time because of the lack of maturity of the 

product, including lack of explicit identification of insect and disease outbreaks.

The following tabulation summarizes other disturbance indicators that we 

considered but did not choose:

Disturbance type Indicator Indicator source Notes

Invasive plants Range, 

populations

U.S. Forest Service, 

Forest Health 

Monitoring

Less related to 

climate change

Drought Tree mortality U.S. Forest Service, 

Forest Inventory 

and Analysis

Difficult to ascribe 

cause–effect 

relationships 

Storms Tree damage 

and mortality

Unsure Good potential 

indicator if time 

series of data can 

be developed

Effects of abiotic agents 

(e.g., fire, storms, land 

clearance) beyond 

reference conditions

Area affected Unsure Covered by above 

indicators
86 Indicators of Climate Impacts for Forests

Usefulness for Educational Purposes

Tree damage from insect and disease outbreaks, especially bark beetle-caused 

tree mortality, is an indicator of climate change that is clearly visible to the 

public.

Data Availability

Length of Records of Dataset

National, consistent datasets of insect- and disease-affected area are available 

electronically back to 1997. Some regions of the United States have earlier 

electronic datasets (e.g., back to 1980 in Washington and Oregon). Earlier 

hardcopy versions are also available in some regions, and earlier national 

summaries are available as well (e.g., for mountain pine beetle; Man 2012). 

Stability/Longevity of Dataset and Indicator

The U.S. Forest Service maintains these electronic datasets. Major forest insect 

and disease conditions are surveyed and reported on annually, beginning in 1940 

or earlier. Any changes to protocols are documented, and made available to the 

public. The datasets are stable and continued collection is expected. 

Notes About the Data (Recent Changes In Analysis 

or Collection Methods)

Aerial surveys report affected area, which is the area of polygons drawn by 

observers in airplanes in locations affected by tree damage. These polygons 

include both live and damaged trees. Not all forest areas are surveyed every year 

by the U.S. Forest Service. For instance, wilderness areas and national parks are 

not typically included.

Spatial and Temporal Scalability

This indicator is spatially scalable because the aerial survey polygons are 

available and can be summarized by political and ecological units.

This indicator is temporally scalable because the aerial survey polygons are 

available for each year of the period of record.

Details About the Indicator

Type of Indicator (Current, Leading, Both)

Current

Approach

Observers in planes fly over forest areas annually, drawing polygons in locations 

affected by tree damage. Observers record damage causal agent (insect or 

disease) and tree species, and sometimes include levels of damage (e.g., number 

of trees killed by bark beetles or defoliation severity).
Appendix 1: Additional Indicator Details 87

This indicator will focus on insects and diseases that damage trees over large 

areas: 1) bark beetles, including mountain pine beetle, western pine beetle, spruce 

beetle, pinyon ips, Douglas-fir beetle, and southern pine beetle; 2) defoliating 

insects, such as spruce budworms; 3) pathogens, including Dothistroma needle 

blight, Swiss needle cast, and Phytophthora root disease; 4) declines, including 

sudden aspen decline and yellow-cedar decline; and 5) invasive insects and 

diseases that have a connection with climate, such as sudden oak death, emerald 

ash borer, gypsy moth, and woolly adelgids. 

Affected area polygons will be summarized at the national scale for each of these 

disturbance agents and across agents. In addition, maps of new infestations and 

cumulative infestations will be produced for each agent as well as summed across 

agents.

Metadata

Aerial surveys and their results are described by:

Man, G., comp. 2012. Major forest insect and disease conditions in the 

United States: 2010 update. FS-988. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 32 p.

U.S. Forest Service. 2005. Aerial survey geographic information system 

handbook: sketchmaps to digital geographic information. Forest Health 

Monitoring Program and State and Private Forestry Forest Health Protection. 

88 p. Available at http://www.fs.usda.gov/Internet/FSE_DOCUMENTS/

stelprdb5361666.pdf (last accessed 21 July 2015).

Composition and Methodology

See above for description of approach. 

Scientific Validity of Indicator

Aerial surveys are conducted by observers in planes. Some accuracy assessments 

have been performed (Backsen and Howell 2013, Johnson and Ross 2008). 

However, variations in observer skill and experience and flying conditions confer 

uncertainty in accuracy and consistency in the aerial survey datasets. Not all 

forest areas are flown over every year. Given these issues, this indicator is best 

considered at larger spatial scales.

What Are the Plans for Further Development of the Indicator? 

Expected to continue being implemented by the U.S. Forest Service. 
88 Indicators of Climate Impacts for Forests

Considerations for Selection of Indicator

Advantages

1) This indicator quantifies the extent of affected area and type of tree damage 

caused by insects and diseases. 

2) Aerial surveys have been conducted for many years, and the program is 

currently active within the U.S. Forest Service. 

3) The U.S. Forest Service prepares the survey data, produces the electronic 

database, and summarizes information annually about forest insects and 

diseases.

Disadvantages

1) Aerial surveys are conducted subjectively, and not all forest areas are flown 

over every year. 

2) Electronic datasets are available nationally only back to 1997, thus lacking 

the capacity to provide a longer term evaluation of changes in insect and 

disease activity. 

Literature Cited

Backsen, J.C.; Howell, B. 2013. Comparing aerial detection and photo 

interpretation for conducting forest health surveys. Western Journal of 

Applied Forestry. 28: 3–8.

Bethlahmy, N. 1974. More streamflow after a bark beetle epidemic. Journal 

of Hydrology. 23: 185–189.

Chan-McLeod, A.C.A. 2006. A review and synthesis of the effects of 

unsalvaged mountain-pine-beetle-attacked stands on wildlife and 

implications for forest management. BC Journal of Ecosystems and 

Management. 7: 119–132.

Edburg, S.L.; Hicke, J.A.; Brooks, P.D.; Pendall, E.G.; Ewers, B.E.; Norton, 

U.; Gochis, D.; Gutmann, E.D.; Meddens, A.J.H. 2012. Cascading impacts 

of bark beetle-caused tree mortality on coupled biogeophysical and 

biogeochemical processes. Frontiers in Ecology and the Environment. 

10: 416–424.

Hicke, J. A.; Allen, C.D.; Desai, A.R.; Dietze, M.C.; Hall, R.J.; Ted Hogg, E.H.; 

Kashian, D.M.; Moore, D.; Raffa, K.F.; Sturrock, R.N.; Vogelmann, J. 2012. 

Effects of biotic disturbances on forest carbon cycling in the United States 

and Canada. Global Change Biology. 18: 7–34.

Johnson, E.W.; Ross, J. 2008. Quantifying error in aerial survey data.

Australian Forestry. 71: 216–222.

Kurz, W.A.; Dymond, C.C.; Stinson, G.; Rampley, G.J.; Neilson, E.T.; Carroll, 

A.L.; Ebata, T.; Safranyik, L. 2008. Mountain pine beetle and forest carbon 

feedback to climate change. Nature. 452: 987–990.
Appendix 1: Additional Indicator Details 89

Man, G., comp. 2012. Major forest insect and disease conditions in the 

United States: 2010 update. FS-988. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 32 p.

Meddens, A.J.H.; Hicke, J.A.; Ferguson, C.A. 2012. Spatiotemporal patterns of 

observed bark beetle-caused tree mortality in British Columbia and the 

western United States. Ecological Applications. 22: 1876–1891.

Pugh, E.; Gordon, E. 2012. A conceptual model of water yield effects from 

beetle-induced tree death in snow-dominated lodgepole pine forests.

Hydrologic Processes.

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

for biotic disturbances in North American forests. Ecological Monographs. 

84: 441–470.

Other Resources 

Alaska Department of Natural Resources, Division of Forestry. 2011. Aerial 

detection survey, significant pest activity. Available at http://forestry.alaska.

gov/pdfs/insects/map1_as2011_rfs.pdf. (Accessed 23 March 2015). [Images 

of a map of significant insect and disease activity effects on forests in Alaska.]

Alaska Department of Natural Resources, Division of Forestry. 2011. Alaska 

aerial detection survey flight paths. Available at http://forestry.alaska.gov/

pdfs/map2_as2011.pdf. (Accessed 23 March 2015). [Example images of flight 

lines for the aerial detection survey in Alaska.]

Dale, V.H.; Joyce, L.A.; McNulty, S.; Neilson, R.P.; Ayres, M.P.; Flannigan, 

M.D.; Hanson, P.J.; Irland, L.C.; Lugo, A.E.; Peterson, C.J.; Simberloff, D.; 

Swanson, F.J.; Stocks, B.J.; Wotton, B.M. 2001. Climate change and forest 

disturbances. Bioscience. 51: 723–734.

Sturrock, R.N.; Frankel, S.J.; Brown, A.V.; Hennon, P.E.; Kliejunas, J.T.; Lewis, 

K.J.; Worrall, J.J.; Woods, A.J. 2011. Climate change and forest diseases.

Plant Pathology. 60: 133–149.

U.S. Forest Service, Eastern Forest Environmental Threat Assessment Center. 

[N.d.]. ForWarn: Satellite-based change recognition and tracking.

Available athttp://forwarn.forestthreats.org/. [Date accessed unknown].

U.S. Forest Service, Forest Health Protection. [N.d.]. Insect & disease detection 

survey data explorer. Available at http://foresthealth.fs.usda.gov/portal/Flex/

IDS. [Date accessed unknown].

U.S. Forest Service, Forest Health Protection, Forest Health Technology 

Enterprise Team, Fort Collins, CO

U.S. Forest Service, Forest Health Technology Enterprise Team. [N.d.]. FHTET 

products—insect and disease detection surveys. Available at http://www.

fs.fed.us/foresthealth/technology/adsm.shtml. [Date accessed unknown].
90 Indicators of Climate Impacts for Forests

BIOPHYSICAL INDICATOR: WATER BALANCE DEFICIT—

AN INDICATOR OF “PLANT-RELEVANT” DROUGHT 

Metric: Water balance deficit (calculated as a difference) 

Summary

Water balance deficit is the difference between potential evapotranspiration 

(PET) and actual evapotranspiration (AET), and is a measure of “plant-relevant” 

drought (Stephenson 1990). Units are millimeters or equivalent.

More research would be needed to make this metric operational.

Additional Descriptive Text

Most methods of determining water balance deficit (Table 14) are based at 

least on surface climate observations (e.g., temperature and precipitation) 

and to varying degrees incorporate specific characteristics of soil (e.g., field 

capacity, infiltration, declining availability) and vegetation (e.g., aerodynamics, 

vegetation-specific resistance, stomatal conductance). Methods for estimating 

PET include Hamon, Thornthwaite, Penman-Monteith, and Priestly-Taylor. Data 

products from the Department of the Interior, Bureau of Reclamation (2015) and 

from the University of Washington, Climate Impacts Group (2015) use PenmanMonteith with specific soil and vegetation characteristics. The data product from 

the University of Delaware (2015) uses a modified version of Thornthwaite 

(Willmott et al. 1985). Abatzoglou et al. (2014) define a related variable, climatic 

water deficit, as the unmet atmospheric demand, or the difference between 

growing season reference evapotranspiration for a reference crop and actual 

evapotranspiration.

What Is the Link to Climate Variability and Change or Relevance?

Water balance deficit varies with weather conditions and climate variability 

on timescales of days to centuries because it is partially determined by both 

temperature (via the contribution to PET) and precipitation (via the contribution 

to AET). Moreover, the seasonal demand for and availability of water during the 

growing season in combination determine the consequences for plant responses, 

so the role of storage in snowpack, for example, is key. Climate variability on 

timescales of years to decades influences water balance deficit in ways similar to 

more familiar drought metrics (such as Palmer Drought Severity Index [PDSI]; 

Palmer 1965) but also accounts for the type of vegetation more explicitly. 

Therefore, from decades to centuries, as the vegetation responds to the limiting 

or facilitating effects of climate, the consequences of a certain deficit can change 

too. Climate variation thus affects water deficit directly in the short term to midterm (seasons to decades), and also indirectly over longer periods via cumulative 

effects on vegetation through controls on disturbance and succession.
Appendix 1: Additional Indicator Details 91

Table 14.—Decision criteria for Biophysical indicator: Water balance deficit—an indicator of 

“plant-relevant” drought

Decision criterion Ranking Justification

Link to conceptual 

framework

Sufficient 

to best

Links to arrows 6, 7, and 9. Deficit integrates some of the Other 

Environmental physical drivers with Climate Domain physical drivers 

and forest responses.

Defined relationship to 

climate, feedbacks, or 

impacts

Best The estimation of the components of deficit is well defined in the 

hydrologic and climate literature. There is an evolving literature 

specific to water balance deficit effects on forests; see Introduction.

Spatial scalability Sufficient 

to best

As fine-scale as vegetation, soil, and climate can be estimated. Soils 

and vegetation data are limiting, and interpolation of climate variables 

is limited at fine timescales.

Temporal scalability Best Same as spatial scalability, though vegetation and soil can be 

considered static if needed and sub-daily variation can be modeled.

Of national (not 

necessarily nationwide) 

significance? Should 

link to the conceptual 

model 

Sufficient Best developed in the Western United States; could be developed 

further for effects on ecosystems in the Eastern United States and 

Pacific Islands.

Relevance to 

management decisions

Sufficient Future projections of water balance deficit give a quick estimate of 

forest vulnerability in the future because deficit has been related 

specifically to tree performance, vegetation distribution, and 

disturbance.

Usefulness for 

educational purposes

Sufficient Deficit is a good way to explain the interaction between physical 

climatology, hydrology, and ecological variations and can be done in 

terms of a systems approach.

Is it a leading indicator? Not 

applicable

Not being proposed as a leading indicator

Builds on existing data 

sources

Needs 

improvement

Existing distributed hydrologic modeling, gridded and interpolated 

climatologies, and forest responses can be mined for responses and 

impacts. 

Builds on existing 

indicator products

Best This builds on existing indicator products in the sense that we have 

recommended other teams consider the Palmer Drought Severity 

Index, which is especially limited for vegetation in mountainous areas. 

If carried by other teams, this approach can be more appropriately 

applied to forests.

If new indicator 

proposed, likelihood 

of development and 

testing within 1 year 

given existing funding 

sources 

This is not 

necessarily 

new, but it 

is relatively 

new in this 

context.

Some development may occur, but dedicated funding is not available.

Stability/Longevity of 

dataset

Sufficient Dedicated funding is needed for stability.

Stability/Longevity of 

indicator

Sufficient Indicator has much promise and may have longevity. Some research 

is needed, and some funding may be needed for development to 

stabilize indicator.

Scientific validity of 

indicator

Best Has been peer reviewed 

Data publicly available 

and transparent

Sufficient Available, but technical expertise required for use

Indicator methods 

fully transparent and 

documented

Best Peer-reviewed papers and funding reports on development exist. More 

information in the popular literature is needed, as well as additional 

technology transfer to help convince users of advantages of using this 

approach.
92 Indicators of Climate Impacts for Forests

What Are the Drivers of This Indicator, and What Are Their Impacts?

Water balance deficit is controlled by drivers that influence both potential and 

actual evapotranspiration, which include climatic (physical) controls, hydrologic 

controls, and ecological controls. The most inclusive estimates of PET (e.g., 

Penman-Monteith or Priestly-Taylor) incorporate more controls than simpler 

versions (e.g., Hamon or Thornthwaite), and are superior, provided appropriate 

data can be used. Most important in long-term estimates is to consider the role 

of changing vegetation and, separately, changing relative humidity in addition to 

climate variables such as temperature, precipitation, and snowpack. 

Currently, the largest drivers of change in water deficit are assumed to be 

changes in temperature and precipitation, in that order. However, land use clearly 

has a role in that changes in vegetation affect both the amount and timing of 

evapotranspiration from the vegetation and also the relative humidity.

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, by Whom, and How Was It Used and When Was It Initiated?

The information presented here has a record of more than 20 years in the 

ecological literature, but we know of no cases where it has been used as an 

indicator. The argument we present, however, is that if PDSI and related variables 

have such disparate consequences for the same value of indicator from place to 

place, a more overarching suite of variables—such as water balance deficit—

should be used.

Other Indicators Considered But Not Recommended at This Time 

We considered PDSI, but it has several issues that make it less desirable than 

water balance deficit specifically for forests. First, deficit is hydrologically 

consistent: it is measured in millimeters of water and is therefore directly 

comparable from place to place, whereas PDSI is an index that ranges, often, 

from -6 to +6 with the meaning of that index varying. A “-2” drought in Tucson, 

AZ, for March to May of a given year is different from a “-2” drought in 

Bozeman, MT, for the same timeframe. But in both locations the water deficit 

might be 100 mm, a meaningful measurement to ecologists and one on which 

they could base discussion of probable consequences for productivity and 

summer fire activity. Second, deficit is at least as well correlated with functional 

responses in forests (from fire disturbance to radial growth). Third, projection 

of future deficit has a mechanistic linkage to the physical, hydrologic, and 

ecological controls on it, which are more difficult with PDSI. Fourth, PDSI, 

which is closely related to the Thornthwaite approximation for deficit, does not 

consider the physical and ecophysiological limitations of vegetation as directly as 

deficit; regional parameterization of PDSI is required (Heim 2002). From a plant 

and ecosystem perspective, therefore, there are sound reasons that deficit is a 

better choice. However, the two can be complementary, as human socioeconomic 

consequences (e.g., farming subsidies during drought) correspond to PDSI. 

Another approach by Peters et al. (2014) was brought to our attention during the 

review process, but that publication was not available to use during our writing 

and discussion phase.
Appendix 1: Additional Indicator Details 93

Data Availability 

Length of Records of Dataset 

The length of records differs among the four methods used to calculate water 

balance deficit. Data for variable infiltration capacity are available for 1950 

through 1999 at 12 km, monthly or daily, from the Bureau of Reclamation 

(2015) or for the Western United States for 1916 through 2006 at 6 km monthly 

(University of Washington, Climate Impacts Group 2015). Global data are 

available for 1900 through 2010 at 5° latitude/longitude from the University of 

Delaware (2015), or for 2000 through 2012 at 1 km monthly for the MERRA/

MODIS satellite record from the University of Montana (2015).

Stability/Longevity of Dataset and Indicator

The Bureau of Reclamation and University of Washington sources are being 

updated on an as-needed and as-funded basis. The information for the Bureau 

of Reclamation will probably be updated, but it is not known whether the 

information for the University of Washington, Climate Impacts Group will 

continue to be updated.

Models/Scenarios (If Leading Indicator or Based on Model Output)

Data products from the Bureau of Reclamation and from the University of 

Washington are based on Variable Infiltration Capacity (VIC) hydrologic 

model output, and the approach to evapotranspiration is described in Elsner 

et al. (2010). The VIC model is a spatially explicit hydrologic model that uses 

observed daily or inferred sub-daily weather observations of temperature and 

precipitation in conjunction with land surface characteristics (soil, vegetation, 

topography) and empirical relationships to derive hydrologic fluxes, including 

PET and AET. The VIC model uses several different PET algorithms for standard 

crops, realistic vegetation, and other attributes.

What Are the Plans for Further Development of the Indicator? 

Progress continues to be made on the development of the measure. 

Considerations for Selection of Indicator

Advantages

The advantages of water balance deficit over other indicators of drought (soil 

moisture, PDSI) are: 1) it is vegetation specific; 2) it is more explicitly related 

to both the energetic and hydrologic processes of plant performance, response, 

and disturbance; and 3) it better accommodates winter and spring relationships 

between snowpack and the growing season water budget.

Disadvantages

Disadvantages include lack of measurement or verification (shared with 

PDSI) and lack of real-time network of observations and updates. Another 

disadvantage is that there are both simple and complex approaches to calculating 

the components of deficit (PET and AET) and also possible confusion with 

“climatic water deficit,” which is PET minus precipitation. See “Drivers” section 
94 Indicators of Climate Impacts for Forests

for description of different approaches. We recommend the more complicated 

Penman-Monteith approach because it includes the capacity for differential 

changes in deficit due to vegetation changes (e.g., stomatal resistance, surface 

roughness, and albedo).

Type of Indicator (Current, Leading, Both; If Both, Need to Describe 

Data/Models and Methods Separately Because of Different 

Approaches)

There currently exist no real-time updates of the indicator. At best, water balance 

deficit is calculated after the fact from observations of climate and weather.

Literature Cited

Abatzoglou, J.T.; Rupp, D.E.; Mote, P.W. 2014. Seasonal climate variability 

and change in the Pacific Northwest of the United States. Journal of 

Climate. 27: 2125–2142.

Climate Impacts Group. [N.d.] Variable infiltration capacity hydrologic 

model: Western U.S., 1916-2006* at 6km, monthly. Available at http://cses.

washington.edu/picea/USFS/pub/summaries/. (Accessed 22 July 2015).

Department of the Interior, Bureau of Reclamation. 2015. Downscaled CMIP3 

and CMIP5 climate and hydrology projections. Available at http://gdo-dcp.

ucllnl.org/downscaled_cmip_projections/dcpInterface.html. (Accessed 

23 July 2015). [In particular, variable infiltration capacity hydrologic model 

for 1950–1999 at 12 km, monthly or daily.]

Elsner, M.M.; Cuo, L.; Voisin, N.; Deems, J.; Hamlet, A.F.; Vano, J.A.; 

Mickelson, K.E.B.; Lee, S.Y.; Lettenmaier, D.P. 2010. Implications of 21st 

century climate change for the hydrology of Washington State. Climatic 

Change. 102(1-2): 225–260. DOI: 10.1007/s10584-010-9855-0.

Heim, R.R., Jr. 2002. A review of twentieth-century drought indices used in 

the United States. Bulletin of American Meteorology Society. 83: 

1149–1165.

Palmer, W.C. 1965. Meteorological drought. Research Paper 45. Washington, 

DC: U.S. Department of Commerce, U.S. Weather Bureau. 58 p.

Peters, M.; Iverson, L.; Matthews, S. 2014. Spatio-temporal trends of drought 

by forest type in the conterminous United States, 1960–2013. [scale 

1:12,000,000]. Res. Map NRS-7. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station.

Stephenson, N.L. 1990. Climatic control of vegetation distribution: the role of 

the water balance. American Naturalist. 135: 649–670.
Appendix 1: Additional Indicator Details 95

University of Delaware. 2015. Global maps time series. Available at http://

climate.geog.udel.edu/~climate/html_pages/Global2011/Precip_revised_3.02/

GlobalWbTs2011.html. (Accessed 23 July 2015). [In particular, global, 

1900–20101 at 0.5° latitude/longitude.]

University of Montana. 2015. MODIS Global Evapotranspiration Project 

(MOD 16). http://www.ntsg.umt.edu/project/mod16. Missoula, MT: 

University of Montana, Numerical Terradynamic Simulation Group. 

(Accessed 23 July 2015). [In particular, global, 2000–20121 at 1 km, monthly.]

University of Washington. 2015. Climate Impact Group datasets and other 

data sources. Available at http://cses.washington.edu/picea/USFS/pub/

summaries/. (Accessed 23 July 2015). Also see http://cses.washington.edu/cig/

data/index.shtml. (Accessed 23 July 2015). [In particular, variable infiltration 

capacity hydrologic model—western United States, 1916–20061 at 6 km, 

monthly.]

Willmott, C.J.; Rowe, C.M.; Mintz, Y. 1985. Climatology of the terrestrial 

seasonal water cycle. Journal of Climatology. 5: 589–606.

Other Resources

Shinker, J.J.; Bartlein, P.J. 2010. Spatial variations of effective moisture in 

the Western United States. Geophysical Research Letters. 37(2). DOI: 

10.1029/2009GL041387.

1

As of the writing of this publication, these are the years of data available; more years of 

data are expected.

EXTENT/SOCIOECONOMIC INDICATOR: AREA AND POPULATION 

OF THE U.S. WILDLAND-URBAN INTERFACE 

Metrics: Area of forest wildland-urban interface, Population residing in forest wildland-urban interface

Although we present this indicator (Table 15) as covering all wildlands, we as the 

forest team can only recommend that this indicator be adopted as a cross-cutting 

indicator for land uses other than forest. 

Additional Descriptive Text

Because of the way the National Land Cover Database identifies vegetation 

from remote sensing, highly urbanized areas may not be included as wildlandurban interface (WUI) if the areas retain enough vegetation cover at the 30-m 

pixel scale to be classified as wildland. The population residing in the WUI is 

the number of people residing in areas determined to be in a WUI. This value is 

calculated from U.S. Census data, after the WUI is mapped. 
96 Indicators of Climate Impacts for Forests

Table 15.—Decision criteria for Extent/Socioeconomic indicator: Area and population of the U.S. 

wildland-urban interface

Decision criterion Ranking Justification 

Link to conceptual 

framework

Sufficient This is a context indicator that is arguably a result of adaptation 

to fire risk. Links most directly from interactions of the Human 

Domain with Forest, Other Land Use, and Other Environmental 

Domains, particularly arrows 8 and 12.

Defined relationship to 

climate, feedbacks, or 

impacts

Sufficient This indicator identifies where greater climate impacts to people 

and wildland are expected.

Spatial scalability Best Scalable to national, regional, state and local levels

Temporal scalability Sufficient No vegetation or housing data are currently available on an 

annual basis at this spatial scale.

Of national (not 

necessarily nationwide) 

significance? Should link 

to the conceptual model 

Best for context Need to identify these areas for mitigation or adaptation 

responses

Relevance to 

management decisions

Best The current WUI population as well as ongoing growth expected 

in the WUI will magnify the social impacts of global climate 

change effects on wildland landscapes.

Usefulness for 

educational purposes

Yes The designation of the WUI targets the audience that especially 

needs to be educated about fire.

Is it a leading indicator? Not applicable Not applicable

Builds on existing data 

sources

Yes Datasets are updated every 10 years.

Builds on existing 

indicator products

Best This indicator appears to be gaining use in the fire community.

If new indicator proposed, 

likelihood of development 

and testing within 1 year 

given existing funding 

sources 

Could be viewed 

as new in this 

context

Could possibly be more useful if updated more often than every 

10 years. Research on how informative it can be for climate 

purposes would be useful.

Stability/Longevity of 

dataset

Needs 

improvement

Existing datasets are well archived. Future funding is not 

guaranteed.

Stability/Longevity of 

indicator

Needs 

improvement

The dataset is being updated every 10 years. Now have 3 

decennial censuses’ worth of data.

Scientific validity of 

indicator

Needs 

improvement

Could use additional investigation in terms of use in climate 

effects

Data publicly available 

and transparent

Best Widely available and well-documented

Indicator methods 

fully transparent and 

documented

Sufficient Methods are documented, but more research to understand the 

information that the indicator provides in a climate context would 

be useful. 
Appendix 1: Additional Indicator Details 97

In the final decade of the 20th century, the WUI expanded throughout the United 

States. By 2039, the WUI is expected to grow by an additional 10 percent 

nationally (Theobald and Romme 2007) and by 17 percent around national 

forests, national parks, and wilderness areas (Radeloff et al. 2010).

What Is the Link to Climate Variability and Change or Relevance?

Increases in the area and human population of the WUI are associated with 

processes that will affect forest and rangeland contributions and responses to 

climate change, such as degradation of wildland vegetation, altered hydrology, 

increasing impervious surface, and introduction of exotic species of both flora 

and fauna (Fall et al. 2009; Radeloff et al. 2005, 2010). In addition, as the 

WUI grows, so too will society’s experience of the effects of climate change 

on natural systems, potentially degrading recreation experiences, exacerbating 

fire problems, and increasing the demand for government remediation of or 

protection from forest degradation. Expected ongoing housing growth in the WUI 

and expansion of the WUI will magnify the social impacts generated by climate 

change effects on wildland vegetation.

What Are the Drivers of This Indicator, and What Are Their Impacts?

Expansion of the WUI is caused by residential development (housing above 

15.98 housing units per square mile, or 6.17 housing units per square kilometer) 

in areas that retain wildland vegetation. The WUI has been expanding in the 

United States in the past several decades, driven by reasons including Americans’ 

preference for rural areas with natural amenities, small towns, and a lower cost of 

living; and technological innovations such as reliable cars and extensive highway 

networks, air conditioning, telecommunication, and Internet service. All of these 

advances have made these regions attractive to home buyers and businesses. 

The ecological impacts of WUI expansion encompass all the effects of 

humans living in or near wildland and modifying their property, and thereby 

the landscape as a whole. Human activity is responsible for the majority of 

wildland fire ignitions. Development (e.g., roads, houses, and infrastructure) 

fragments habitat. Landscaping introduces exotic and invasive species. Wildlife 

is harassed by traffic and pets. Light and noise levels increase. As a result of all 

of this human activity, biodiversity declines and ecosystem function is altered. 

Environmental impacts of increased housing result not only from the larger 

number of houses, but from their density and distribution on the landscape. The 

low-density residential growth found in the WUI is of particular environmental 

concern, because houses are dispersed through previously undeveloped areas 

and on larger lots, spreading the impacts of each house over a larger area and 

maximizing the cumulative footprint of each housing development.

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, by Whom, and How Was It Used and When Was It Initiated?

This indicator is used by the National Wildfire Coordinating Group (see 

http://www.nwcg.gov/var/data-standards/wildland-urban-interface-indicator) 
98 Indicators of Climate Impacts for Forests

to determine whether the presence of WUI increases the cost or management 

complexity of a wildfire. It is used in the National Cohesive Wildland Fire 

Management Strategy to characterize wildfire problems and policy responses 

(http://www.forestsandrangelands.gov/strategy/).

Relevance to Management Decisions

The WUI data and maps are used by national-level policy makers assessing the 

scope and growth of the WUI across the country, and by regional and state policy 

makers for allocating funds to support wildland fire mitigation. 

Other Indicators Considered But Not Recommended at This Time 

This is a context indicator to pinpoint areas where the social impacts of climate 

change effects on forests are expected to be magnified, in comparison to more 

rural forests. Response strategies to climate variability or change will probably be 

different in these areas. We considered using the urban forest area, but that is not 

as well defined and is likely to be a heterogeneous area.

Data Availability

Length of Records of Dataset

Dataset is updated every 10 years, with decennial census. Data from 1990, 2000, 

and 2010 are available.

Metadata

The WUI is the area where houses meet or intermingle with undeveloped 

wildland vegetation. By using geographic information systems (GIS), researchers 

integrate U.S. Census and National Land Cover data (MRLC 2014) to map the 

WUI in accordance with the Federal Register definition (U.S. Department of the 

Interior and U.S. Department of Agriculture 2001). These data are useful within a 

GIS for mapping and analysis at national, state, and local levels.

Stability/Longevity of Dataset and Indicator

Data are updated with each 10-year census. Researchers process the data with 

GIS so that the WUI can be tracked over different censuses, as the shape changes 

between censuses. Researchers provide datasets that facilitate direct comparison 

of decadal WUI products. Data for changes between 1990 and 2000 are available, 

and change data for 2000–2010 will be released in 2015.

Notes About the Data (Recent Changes in Analysis 

or Collection Methods)

The current version of the WUI uses a nationwide map of “protected areas with 

no housing units.” These areas were derived from the Public Areas Database 

(Conservation Biology Institute 2010) and included all publicly owned areas—

federal, state, regional, and local government-owned lands—where housing 

cannot occur.
Appendix 1: Additional Indicator Details 99

Spatial and Temporal Scalability

Data are available for the conterminous 48 states, at the level of the census block. 

Because WUI data rely on housing counts, the dataset is updated every 10 years 

with the decennial census.

Details About the Indicator

Type of Indicator (Current, Leading, Both)

Current

Geographic Scope and Scale of Analysis

Conterminous United States

Approach of Indicator (e.g., Single Measure, Composite)

Data are generated by combining information on housing, land cover, and 

protected areas. See “Metadata” and “Composition and Methodology” for more 

information.

Purposes and Conceptual Framework

The WUI data and maps were created to provide a nationwide assessment of 

the wildland-urban interface specific to fire management and policy. The WUI 

concept originates in wildland fire management and policy and was codified 

(U.S. Department of the Interior and U.S. Department of Agriculture 2001) 

following passage of the National Fire Plan in 2001. Thus, the WUI concept is 

arguably a need that resulted from societal adaptation to fire risk. The indicator 

results more directly from interactions of the Human Domain, and Forest, Other 

Land Use, and Other Environmental Domains, in particular, arrows 8 and 12.

Composition and Methodology

Method to determine area of WUI—Occasionally the datasets showed housing 

units within protected area boundaries, where housing units would not normally 

occur by definition. This location was thought to be in error. We relabeled these 

units as belonging to neighboring privately owned blocks with the same block 

identification label. If the same block had no private areas, then houses remained 

within the protected land boundary (unmoved).

Housing data—Bureau of Census housing data were used at the block level, 

along with the Public Areas Database (Conservation Biology Institute 2010), 

to refine census blocks so that the area in each census block could be used to 

calculate housing density. These data occur only on privately owned land. 

Land cover data—The National Land Cover Dataset is used to determine the 

density and location of wildland vegetation.
100 Indicators of Climate Impacts for Forests

Processing—

1) Working in GIS, we calculate housing density and exclude blocks with 

less than 15.98 housing units per square mile (6.17 housing units per 

square km). 

2) In remaining blocks, we determine where wildland vegetation density 

is greater than 50 percent. Those blocks with >15.98 housing units per 

square mile (6.17 housing units per square km) and >50 percent wildland 

vegetation are intermix WUI. 

3) We estimate where wildland vegetation is greater than 75 percent, and 

for remaining blocks that meet the housing density minimum, any block 

or portion of a block that falls within 1.5 miles (approximating how far a 

firebrand can fly), these areas are interface WUI.

Process for estimating WUI population—Population residing in the WUI is 

estimated from the Census of Population at the block level. The steps are:

1) Determine which blocks are entirely within WUI and sum the population 

census counts for those blocks.

2) Determine which blocks are partly in WUI and what proportion are within 

the WUI. Use the proportion of census population counts to represent their 

populations. Sum these and add to above.

Scientific Validity of Indicator

Social validity is indicated by the number and variety of uses made of the WUI 

map by policy makers and resource managers. Biophysical validity of the data 

as an indicator of where homes are at risk of fire has been assessed for western 

states. In an analysis of 2006 fires in the West, 93 percent of homes within 1 mile 

of fire perimeters were classified as WUI; within 10 miles of fire perimeters, 

73 percent of homes were classified as WUI (Stewart et al. 2007).

What Are the Plans for Further Development of the Indicator?

The U.S. Forest Service has supported research on the WUI under the National 

Fire Plan since 2001. The U.S. Forest Service has an extensive program of 

research which updates and maintains the WUI data, and uses the data to 

understand the social and ecological dynamics of fire in the WUI, and of human 

impacts on ecosystems more generally. See also Pellegrino et al. (2013).

Literature Cited

The Conservation Biology Institute. 2010. PAD-US 1.1 (CBI edition). Corvallis, 

OR. Available at http://consbio.org/products/projects/pad-us-cbi-edition. 

[Date accessed unknown.]

Fall, S.; Niyogi, D.; Gluhovsky, A.; Pielke, R.A., Sr.; Kalnay, E.; Rochon, G. 

2009. Impacts of land use land cover on temperature trends over the 

continental United States: assessment using the North American Regional 
Appendix 1: Additional Indicator Details 101

Reanalysis. International Journal of Climatology. 30: 1980–1993.

Multi-Resolution Land Characteristics Consortium [MRLC]. 2014. National 

Land Cover Dataset (NLCD). Available online at http://www.nrlc.gov/. 

[Date accessed unknown].

Pellegrino, J.L.; Bryner, N.P.; Johnsson, E.L. 2013. Wildland-urban interface 

fire research needs—workshop summary report. NIST Special Publication 

1150. U.S. Department of Commerce, National Institute of Standards and 

Technology. 117 p. Available at http://dx.doi.org/10.6028/NIST.SP.1150. 

(Accessed 23 July 2015). 

Radeloff, V.C.; Hammer, R.B.; Stewart, S.I. 2005. The wildland urban 

interface in the United States. Ecological Applications. 15: 799–805. 

[Describes the number of homes and extent of WUI in the lower 48 states.]

Radeloff, V.C.; Stewart, S.I.; Hawbaker, T.J.; Gimmi, U.; Pidgeon, A.M.; Flather, 

C.H.; Hammer, R.B.; Helmers, D.P. 2010. Housing growth in and near 

United States’ protected areas limits their conservation value. Proceedings 

of the National Academy of Sciences. 107: 940–945.

Theobald, D.M.; Romme, W.H. 2007. Expansion of the US wildland-urban 

interface. Landscape and Urban Planning. 83: 340-354.

U.S. Department of the Interior and U.S. Department of Agriculture. 2001. 

Urban wildland interface communities within the vicinity of Federal 

lands that are at high risk from wildfire. 66 Fed. Reg. 751. January 4. 

pp. 751–777. Available at https://federalregister.gov/a/01-52. (Last accessed 

13 July 2015).

Other Resources 

Major contacts: SILVIS Lab at the University of Wisconsin – Madison. 

[Manages and maintains WUI data and maps. All are available to the public 

at http://silvis.forest.wisc.edu/maps/wui_main. This page also provides more 

information about the WUI methods.] Contact: Volker Radeloff (University 

of Wisconsin, Forest Ecology/SILVIS Lab). Others involved in research 

supported by the National Fire Plan include: Roger Hammer (Oregon State 

University, Sociology Department), Susan Stewart (former U.S. Forest 

Service, Northern Research Station research social scientist), and Miranda 

Mockrin (U.S. Forest Service, Rocky Mountain Research Station research 

ecologist).

Bar Massada, A.; Radeloff, V.C.; Stewart; S.I. 2011. Allocating fuel breaks 

for optimal protection of structures in the wildland-urban interface.

International Journal of Wildland Fire. 20: 59–68. [Especially contains 

information about developing a method for mapping the WUI by using 
102 Indicators of Climate Impacts for Forests

structure location data.]

Bar Massada, A.; Syphard, A.D.; Radeloff, V.C.; Hawbaker, T.J.; Stewart, S.I. 

2011. Effects of ignition models on the spatial patterns of simulated 

wildfires. Environmental Modelling and Software. 26(5): 538–592. 

[Discusses modeling the relationship between WUI housing density and 

location, and wildland fire occurrence.]

Gavier Pizarro, G.I.; Stewart, S.I.; Huebner, C.; Keuler, N.S.; Radeloff, V.C. 

2010. Housing is positively associated with invasive exotic plant species 

richness in New England, USA. Ecological Applications. 20(7): 1913–1925. 

[Demonstrates relationships between WUI housing growth and invasive 

species richness and abundance.]

Hammer, R.B.; Stewart, S.I.; Radeloff, V.C. 2009. Demographic trends, the 

Wildland-Urban Interface, and wildfire management. Society and Natural 

Resources. 22: 777–782. [Describes the demographic trends that drive WUI 

growth and change.]

Radeloff, V.C.; Hammer, R.B.; Stewart, S.I. 2005. Rural and suburban 

sprawl in the U.S. Midwest from 1940 to 2000 and its relation to forest 

fragmentation. Conservation Biology. 19(3): 793–805. [Analyzes housing 

growth at the sub-county scale.]

Radeloff, V.C.; Stewart, S.I.; Hawbaker, T.J.; Gimmi, U.; Pidgeon, A.M.; Flather, 

C.H.; Hammer, R.B.; Helmers, D. 2010. Housing growth in and near United 

States’ protected areas limits their conservation value. Proceedings of the 

National Academy of Sciences. 107(2): 940–945. [Analyzes housing growth 

in and around national parks, national forests, and wilderness areas.]

Stewart, S.I.; Wilmer, B.; Hammer, R.B.; Aplet, G.H.; Hawbaker, T.J.; Miller, C.; 

Radeloff, V.C. 2009. Wildland-Urban Interface maps vary with purpose 

and context. Journal of Forestry. 107(2): 78–83. [Contains information on 

mapping the WUI in 1990 and 2000 across the United States.] 

Syphard, A.D.; Stewart, S.I.; McKeefry, J.; Hammer, R.B.; Fried, J.; Holcomb, 

S.S.; Radeloff, V.C. 2009. Assessing housing growth when census 

boundaries change. International Journal of Geographical Information 

Science. 23(7): 859–876. [Contains information on mapping the WUI in 1990 

and 2000 across the United States.] 
Appendix 1: Additional Indicator Details 103

CLIMATE IMPACTS ON HUMAN DOMAIN VIA FOREST: 

COST TO MITIGATE WILDFIRE RISK 

Metrics: Expenditures on fire suppression activity, Expenditures on forest treatments to mitigate fire risk, 

Total payments for insurance premiums for policies against damage from forest fire. Units are inflationadjusted dollars per year by category and (if available) by geographic region.

Summary

Expenditures on fire suppression activity are compiled on an annual basis from 

federal, state, and local sources. 

Expenditures on forest treatments to mitigate fire risk would be compiled on an 

annual basis from federal, state, and local sources.

Total payments for insurance premiums for policies against damage from forest 

fire would be compiled from insurance companies on an annual basis. 

More research is needed on this indicator (Table 16), but the feasibility of 

providing metrics for this indicator is medium to high.

What Is the Link to Climate Variability and Change or Relevance?

Owing to anticipated increases in temperature and moisture deficits, climate 

change is expected to increase wildfire frequency and intensity. The biophysical 

impacts can be measured by indicators of fire extent, frequency, and intensity. 

The socioeconomic impacts, however, can take many different forms, ranging 

from loss of life and property to aesthetic impacts. Mitigation costs (suppression, 

fuels reduction treatments, and insurance) are one such measure.

What Are the Drivers of This Indicator, and What Are Their Impacts?

Temperature and moisture are major drivers of fire ignition, spread, and intensity, 

and they likewise help determine vegetative growth and thereby available 

fuels for wildfires. Fire activity will influence suppression costs. Fire risk will 

influence levels of forest treatment activity and insurance premiums. Note that 

several confounding factors will also affect each of these expenditure categories: 

general federal and state budgetary considerations will influence availability of 

funds and thereby suppression and treatment expenditures, and development in 

the WUI will influence demand for insurance against wildland fire risk.

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, by Whom, and How Was It Used and When Was It Initiated?

Not to our knowledge. At the federal level, budget allocations by the U.S. Forest 

Service and Department of the Interior for wildfire control and management are 

reported through various channels. These allocations and related measures of 

wildfire costs are analyzed by various entities and in various contexts (e.g., see 

Gorte 2011). In this sense, these data serve a similar role as “indicators,” but 
104 Indicators of Climate Impacts for Forests

Table 16.—Decision criteria for Climate impacts on Human Domain via Forest: Cost to mitigate 

wildfire risk

Decision criterion Ranking Justification 

Link to conceptual framework Best Links directly (arrow 1)

Defined relationship to climate, 

feedbacks, or impacts

Sufficient Strong causal link to climate change but confounding 

factors also present

Spatial scalability Best Scalable to national, regional, and state levels

Temporal scalability Sufficient Federal suppression costs available in annual time series 

from 1985

Of national (not necessarily 

nationwide) significance? Should 

link to the conceptual model 

Best Potentially significant impact of climate change on human 

populations, with strong implications for national and local 

management activities

Relevance to management 

decisions

Best Fire expenditure is a major budget category for land 

management agencies. Addressing fire will be a major 

challenge facing these agencies in the coming decades.

Usefulness for educational 

purposes

Sufficient Budget allocations may not be a very exciting topic, but 

they do reveal an important cost imposed on society by 

climate change.

Is it a leading indicator? Not applicable Not proposed as a leading indicator

Builds on existing data sources Sufficient Federal fire suppression costs are readily available. 

Other cost categories will require varying levels of 

development.

Builds on existing indicator 

products

Needs 

improvement

Builds on existing reporting categories, but not indicators 

per se

If new indicator proposed, 

likelihood of development and 

testing within 1 year given 

existing funding sources 

Sufficient Federal suppression costs can be reported easily. Other 

indicator components are not likely to be produced in 1-

year timeframe with available resources.

Stability/Longevity of dataset Sufficient Federal suppression costs are well established. Other 

categories will require development.

Stability/Longevity of indicator Sufficient This indicator needs more work, but some information is 

likely to be available. 

Scientific validity of indicator Sufficient Budgetary expenditures are not subject to the same level 

of analysis as biophysical indicators. Causal links are not 

explicitly defined; more research would be useful.

Data publicly available and 

transparent

Sufficient Federal suppression costs are available and reasonably 

transparent.

Indicator methods fully 

transparent and documented

Sufficient Federal budget reporting conventions are well 

established, but meaning is sometimes obscure. More 

research on the information that this indicator provides in 

a research context would be useful.
Appendix 1: Additional Indicator Details 105

they do not appear to be formally integrated into well-known sustainable forest 

management indicator sets. Insurance premiums associated with wildland fire 

risk are commonly cited as an interesting avenue for future research, but they 

have not yet been compiled and are therefore merely potential candidates for 

future development.

Relevance to Management Decisions

Wildfire control and management costs have many implications for management, 

ranging from the spatial and temporal allocation of resources to more general 

calculations of the costs of climate change. To the extent that wildfire increases 

in the coming decades as a response to climate change (in combination with other 

factors), wildfire management will be a major challenge for natural resource 

managers and a major drain on their budgets, thus requiring focused planning. 

Insurance premiums related to wildfire will act as a direct market indicator of 

perceived risk—high premiums will indicate high risk, and low premiums low 

risk—that may then be used to allocate resources for fuels reduction and fire 

preparedness.

Other Indicators Considered But Not Recommended at This Time 

The following indicators were also considered: number of lives lost to wildfire, 

number of structures lost to wildfire, number of structures and lives lost to 

wildfire, and the value of structures and other improvements lost to wildfire.

Usefulness for Educational Purposes

This indicator will aid society in understanding, in explicit terms, one dimension 

of the costs imposed by climate change. 

Data Availability

Length of Records of Dataset

Federal wildfire suppression costs: 1985–present

Federal fuels reduction treatment costs will require compilation: 

 likely 2000–present

State-level activities require compilation; length of record unknown.

Wildfire-related insurance costs need compilation; length of record unknown.

Data Sources

Tabulation of federal, state, and local suppression/avoidance costs: See National 

Interagency Fire Center at www.nifc.gov/fireInfo/fireInfo_statistics.html; consult 

National Association of Insurance Commissioners and allied groups.

Notes About the Data (Recent Changes in Analysis 

or Collection Methods)

As is true with most time series compiled from various sources, collection 

methods and reporting conventions are subject to change. Federal wildfire 

suppression costs appear to have an established time series with consistent 

reporting. Other federal wildfire control and treatment costs will be subject to 

changing budget categories, definitions, and other reporting conventions. 
106 Indicators of Climate Impacts for Forests

Models/Scenarios (If Leading Indicator or Based on Model Output)

Not proposed as a leading indicator. Fire incidence is modeled at various scales, 

and federal agencies incorporate anticipated fire activity in budgets of future 

years, but this does not constitute an integrated or consistent modeling projection 

framework.

Details About the Indicator

Type of Indicator (Current, Leading, Both)

Current

Geographic Scope and Scale of Analysis

National, regional, state

Approach of Indicator (e.g., Single Measure, Composite)

Composite indicator with discrete display for component parts. Federal fire 

suppression costs are the most likely candidate for initial development.

Purposes and Conceptual Framework

Applies directly to “Climate impacts on Human Domain via Forest” (arrow 1 in 

current conceptual model). Fuels reduction activities would apply to “Human 

Domain influences on Climate Domain via Forest” (arrow 2 in current conceptual 

model).

Composition and Methodology

Compilation of budget allocation and expenditure documents. Display in simple 

aggregate by category. Insurance premiums, if developed, would involve census, 

if possible; otherwise statistical sampling may be needed.

What Are the Plans for Further Development of the Indicator?

Initial focus on display of federal suppression costs, followed by compilation of 

similar data and display for state-level suppression costs, and then incorporation 

of fuels treatment and mitigation costs (federal and state). Insurance premiums 

are a candidate for future research and development as feasible and appropriate.

Considerations for Selection of Indicator

Advantages

1) Measures major category of impact on humans via forest

2) Provides data that is useful in many contexts (especially if state and local 

tabulations are available)

3) Amenable to quantitative measurement
Appendix 1: Additional Indicator Details 107

Disadvantages

1) Insurance premiums may confound value at risk with probability of fire.

2) Attribution of fire, and thereby costs, to climate change as opposed to other 

causes will call for external analysis.

3) Accounting definitions may be problematic (e.g., distinction between 

“wildland” and “forest” fire, or “forest restoration” and “fuels treatment”).

4) Data compilation for state-level costs may be a tedious exercise.

Literature Cited

Gorte, R.W. 2011. Federal funding for wildfire control and management. 

Congressional Research Service. 7-5700 RL33990. Available at 

http://fas.org/sgp/crs/misc/RL33990.pdf. (Accessed 12 February 2015). 

Other Resources

Major contact: National Interagency Fire Center 

(http://www.nifc.gov/fireInfo/fireInfo_statistics.html) 

Brown, T.J.; Hall, B.L.; Westerling, A.L. 2004. The impact of twenty-first 

century climate change on wildland fire danger in the western United 

States: an applications perspective. Climatic Change. 62(1-3): 365–388.

Lynch, D.L. 2004. What do forest fires really cost? Journal of Forestry. 

102(6): 42–49.

Summary

Energy produced, domestically or in export markets, from biomass harvested 

from U.S. forests. Data readily exist to populate most of the indicator. More work 

and data are needed on the export market information. 

Units are British thermal units (Btu) per year, which is a traditional and common 

measure of energy and, if possible, CO2 equivalent assuming appropriate 

conversion (e.g., national electricity generation average ratio of carbon to Btu).

The Decision Criteria table for this indicator is shown in the main text (see 

Table 1 on page 6) to provide a clear description of the methods. To reduce 

duplication, we are not including it here.

HUMAN INFLUENCE ON CLIMATE DOMAIN VIA FOREST: 

ENERGY PRODUCED FROM FOREST-BASED BIOMASS 

Metric: Energy produced, domestically or in export markets, from biomass harvested from U.S. forests
108 Indicators of Climate Impacts for Forests

Additional Descriptive Text

Wood exports for foreign energy generation are not currently tracked in the U.S. 

Forest Service indicator, but estimates of export volumes may be developed from 

U.S. International Trade Commission (ITC) trade data. This process, however, 

will involve some form of modeling as explicit North American Industry 

Classification System (NAICS) codes for wood pellets and related wood-based 

fuels do not exist.

Metadata

The U.S. Department of Energy (2013); U.S. Forest Service FIA Timber Products 

Output Database; U.S. International Trade Commission ITC Database. Indicator 

prototype available as Indicator 5.24 in National Report on Sustainable Forests—

2010 (U.S. Forest Service 2011), specifically at http://www.fs.fed.us/research/

sustain/criteria-indicators/indicators/indicator-524.php.

What Is the Link to Climate Variability and Change or Relevance?

This indicator is proposed as a measure of human impact on atmospheric carbon 

concentrations via the forest sector and, more generally, as an indicator of social 

response to global climate change (arrow 2 in the current conceptual model). 

Through carbon sequestration and bioenergy production, forests and forest 

management provide positive opportunities for human action to mitigate climate 

change. Moreover, industrial-scale bioenergy production will potentially result 

in significant impacts to forest ecosystems and thus represent a channel through 

which climate-driven policy decisions can affect forests.

What Are the Drivers of This Indicator, and What Are Their Impacts?

Climate change-related drivers include perceived risk resulting from climate 

variability, which then drives policy responses favoring forest-based bioenergy 

production. Forest-based bioenergy production will occur in the context of 

broader energy markets, and energy prices determined by factors both related 

to climate change and not related to climate change (e.g., relative scarcity of 

alternative fuels). Technology innovations in areas such as cellulosic ethanol, 

or for competing nonwood energy sources, will likewise influence uptake and 

dispersion of forest-based bioenergy production.

Impacts include changes in atmospheric carbon concentrations (per full lifecycle analysis) and changes in forest characteristics resulting from bioenergy 

management activities. 

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, by Whom, and How Was It Used and When Was It Initiated?

A similar indicator, “Avoided Fossil Fuel Carbon Emissions by Using Forest 

Biomass for Energy,” is included in the Montreal Process Criteria and Indicators 

for Sustainable Forest Management (Indicator 5.c, http://www.montrealprocess.

org/). A U.S. domestic-only version (omitting exports used for foreign energy 
Appendix 1: Additional Indicator Details 109

production) has been incorporated in the two editions of the U.S. National Report 

on Sustainable Forests published to date (indicator 5.24, U.S. Forest Service 2004 

and 2011). The estimation of forest biomass energy production was the primary 

component of the indicator, and the avoided emissions component was calculated 

by simply scaling forest biomass energy production by a fixed ratio of carbon to 

Btu (e.g., the average ratio pertaining to coal energy production). This approach 

ignores many of the complexities of a full carbon accounting based on life-cycle 

analysis. For this reason, we are proposing an energy measure as opposed to the 

avoided carbon emissions used by the Montreal Process. Conversion to carbon 

measures could easily be provided, but sufficient caveats accompanying the 

estimates are necessary. 

Relevance to Management Decisions

Changes in carbon emissions and sequestration as a result of forest biomass 

energy production could serve as inputs to national carbon accounting efforts. 

Identification of growing energy applications in the forest sector could help 

managers target future investments and mitigation measures.

Other Indicators Considered But Not Recommended at This Time 

The other indicators considered were: volume and value of forest-based carbon 

credits exchanged in relevant markets; amount of carbon sequestered by forest 

management activities explicitly aimed at increasing in situ forest carbon stocks; 

number of structures or lives, or both, lost to wildfire; and value of structures and 

other improvements lost to wildfire.

Usefulness for Educational Purposes

This indicator could help inform the public about a little-known source of energy. 

Periodic updates would allow for tracking of activity and identification of nascent 

opportunities for industrial development.

Data Availability

Length of Records of Dataset

Domestic energy production from forest biomass: 1990–present, though 

compilation is needed for each new iteration of the time series (i.e., it is not 

routinely published as a survey or census statistic).

Exports of forest biomass for energy production: compilation/estimation needed.

Stability/Longevity of Dataset and Indicator

The domestic component is dependent upon Department of Energy reporting 

activities. It is unclear whether the department will continue to publish estimates 

in this area. The U.S. Forest Service, however, is committed to producing an 

estimate for this indicator on a 5-year cycle as part of its responsibility to the 

Montreal Process.
110 Indicators of Climate Impacts for Forests

Notes About the Data (Recent Changes in Analysis 

or Collection Methods)

Presentation, data transformation, and estimation protocols would follow those 

presented in the U.S. Forest Service report (U.S. Forest Service 2011), though 

modifications could be incorporated as appropriate. Protocols for collection of 

export data need to be developed.

Spatial and Temporal Scalability

May be scalable to regional and state levels, but this is primarily a national-level 

indicator.

Details About the Indicator

Type of Indicator (Current, Leading, Both) 

Current

Geographic Scope and Scale of Analysis

The scope is national to international (depending on incorporation of export 

markets). For carbon accounting purposes, scale of analysis is national (i.e., 

nation is the primary unit of analysis). Regional display may be warranted to 

ascertain location of impacts to forest ecosystems.

Approach of Indicator (e.g., Single Measure, Composite)

Composite of different energy categories (i.e., fuelwood, wood pellets, wood 

products industry cogeneration, liquid biofuels, other)

Purposes and Conceptual Framework

Applies directly to “Human Domain influences on Climate Domain via Forest” 

(arrow 2 in the current conceptual model). Additionally, to the extent that forest 

bioenergy development is driven by climate response policy, the indicator 

would help track “Climate impacts on Human Domain via Forest” (arrow 1). 

The purpose is to track changes in forest-based energy production, allowing 

for associated estimation of carbon stocks and fluxes, and impacts of energy 

development on forest ecosystems. 

Composition and Methodology

Composite indicator compiled from multiple reporting streams estimating forestbased energy production/consumption.

Scientific Validity of Indicator

U.S. National Report on Sustainable Forests (U.S. Forest Service 2011) indicator 

5.24 has been subject to peer review. Given data and analysis issues associated 

with compilation of disparate data streams, the validity of the indicator is not as 

strong as a statistical estimate based on a consistent sample or census.

What Are the Plans for Further Development of the Indicator? 

Incorporation of export volumes. Development of consistent protocols for 

compilation, analysis, and reporting.
Appendix 1: Additional Indicator Details 111

Considerations for Selection of Indicator

Advantages

1) Conceptually straightforward and amenable to quantitative measurement

2) Good data availability

3) Key measure linking forests, climate change, and human activity if forestbased bioenergy emerges as major industry

Disadvantages

1) Ambiguous in terms of implications for atmospheric carbon concentrations 

(long-term carbon neutrality vs. short-term emissions)

2) Lack of variance or significant levels in historical record (relevance is 

predicated on emergence of new energy uses)

3) Tracking export volumes for energy usage may be problematic.

Literature Cited

U.S. Energy Information Administration. 2013. Electricity: detailed state data. 

U.S. Department of Energy. Available at http://www.eia.doe.gov/cneaf/

electricity/epa/epa_sprdshts.html. (Last accessed 18 July 2015). [State-level 

utility data.]

U.S. Forest Service. 2004. National report on sustainable forests—2003.

FS-766. Washington, DC: U.S. Department of Agriculture, Forest Service. 

139 p.

U.S. Forest Service. 2011. National report on sustainable forests—2010.

FS-979. Washington, DC: U.S. Department of Agriculture, Forest Service. 

212 p.

Other Resources

McKechnie, J.; Colombo, S.; Chen, J.; Mabee, W.; MacLean, H.L. 2011. Forest 

bioenergy or forest carbon? Assessing trade-offs in greenhouse gas 

mitigation with wood-based fuels. Environmental Science & Technology. 

45(2): 789–795.

U.S. Forest Service. 2015. Forest sustainability reporting in the United 

States, Indicator 5.24: avoided fossil fuel carbon emissions by using 

forest biomass for energy. Available at http://www.fs.fed.us/research/sustain/

criteria-indicators/indicators/indicator-524.php. (Accessed 15 March 2015). 

[An alternative display of this indicator in a nationally summarized form over 

time.] 

Zerbe, J.I. 2006. Thermal energy, electricity, and transportation fuels from 

wood. Forest Products Journal. 56: 6–14.
112 Indicators of Climate Impacts for Forests

SOCIOECONOMIC INDICATOR: DEVELOPED AND CROSS-COUNTRY SKIING 

Metrics: Number of U.S. ski/snowboarder visits, Revenues of ski area, Participation days in 

cross-country skiing 

Summary

Socioeconomic activities that are forest- and snow-dependent such as downhill 

skiing, snowboarding, and cross-country skiing are expected to be influenced by 

climate. More work is needed to ensure datasets are consistent for the indicators, 

and to understand the links between climate variability and these metrics. See 

Table 17 for a summary of the justifications for choosing this specific indicator 

and metrics.

What Is the Link to Climate Variability and Change or Relevance?

Winter skiing and snowboarding are dependent on snow and on temperature 

conditions that support snow. The effect of climate variability on these activities 

is clear, although developed skiing is less affected by climate, given that resorts 

can manufacture snow. Some regions are more affected than others by climate 

variability due to the nature of the skiing visits (Irland et al. 2001). 

What Are the Drivers of This Indicator, and What Are Their Impacts?

Economic conditions, income, demographics, and climate variability are all 

drivers of this indicator (e.g., see Bowker et al. 2012). 

Has This Indicator Been Used as an Indicator by Anyone Else; 

If So, by Whom, and How Was It Used and When Was It Initiated?

Cross-country skiing and number of snow skiing facilities on public land were 

included as part of an indicator on visits attributed to recreation and tourism and 

related to facilities available for forest sustainability (U.S. Forest Service 2012). 

Relevance to Management Decisions

Developed ski areas are major investments, and often occur on or in conjunction 

with public land. Their development and planning is costly and long-term. This 

indicator would inform these decisions. Cross-country skiing could also benefit 

for similar reasons, although the infrastructure investment is usually not as large.

Other Indicators Considered But Not Recommended at This Time 

Significant socioeconomic variables such as employment in the forestry sector 

and revenues from production of wood products were considered. These will also 

be affected by climate variability, but there are many drivers affecting them, and 

they are available in other indicator compilations (see U.S. Forest Service 2012). 

This indicator is perceived to be strongly related to climate. Nearly all Americans 

enjoy some form of outdoor recreation, and choosing a major form of recreation 

clearly related to climate was deemed more relevant and useful to this set of 

proposed indicators. 
Appendix 1: Additional Indicator Details 113

Table 17.—Decision criteria for Socioeconomic indicator: Developed and cross-country skiing

Decision criterion Ranking Justification 

Link to conceptual framework Sufficient Example of a complex impact, involving all domains, but 

focused on the Human and Forest Domains, and arrows 

3, 4, 5, 6, 8, 12, and 13

Defined relationship to climate, 

feedbacks, or impacts

Sufficient Climate directly influences activity, which directly affects 

forest extent, is an ecosystem good, and can affect forest 

structure.

Spatial scalability Sufficient National to regional to county. Some datasets are tied 

only to participation, not to location. Work is needed to 

monitor local participation.

Temporal scalability Best Annual data are available.

Of national (not necessarily 

nationwide) significance? Should 

link to the conceptual model 

Sufficient This is more important in some regions than others, but 

nationally it is of interest owing to the United States’ 

tradition of having ski areas.

Relevance to management 

decisions

Best Relevant to policy-level decisionmaking and long-term 

planning

Usefulness for educational 

purposes

Skiing is perceived as being tied to climate, and is 

popular across age groups. It has a wide appeal and is 

therefore useful for educational purposes.

Is it a leading indicator? No Not applicable

Builds on existing data sources Sufficient Some data sources from industry are available for 

purchase.

Builds on existing indicator 

products

Not applicable No current indicator products

If new indicator proposed, 

likelihood of development and 

testing within 1 year given 

existing funding sources 

Needs 

improvement

Although the data are not new, and some have been 

used as indicators previously, more work is needed to 

ensure indicators are based on consistent datasets.

Stability/Longevity of dataset Needs 

improvement

Some data are proprietary; other datasets are available 

and research could prove them useful.

Stability/Longevity of indicator Sufficient This indicator could be reported; however, more work is 

needed to ensure consistency with longevity.

Scientific validity of indicator Sufficient More research is needed, especially to understand 

the information that the indicator provides in a climate 

context.

Data publicly available and 

transparent

Needs 

improvement

Some data are proprietary. More work is needed.

Indicator methods fully 

transparent and documented

Needs 

improvement

Methods are documented, but more research to 

understand the information that the indicator provides in a 

climate context would be useful.
114 Indicators of Climate Impacts for Forests

Usefulness for Educational Purposes

This indicator can be reported on an annual basis, and the immediate obvious 

relationship between this indicator and climate creates a strong educational 

opportunity for all age groups.

Literature Cited

Bowker, J.M.; Askew, A.E.; Cordell, H.K.; Betz, C.J.; Zarnoch, S.J.; Seymour, L. 

2012. Outdoor recreation participation in the United States—projections 

to 2060: a technical document supporting the Forest Service 2010 RPA 

Assessment. Gen. Tech. Rep. SRS-160. Asheville, NC: U.S. Department of 

Agriculture Forest Service, Southern Research Station. 34 p.

Irland, L.C.; Adams, D.; Alig, R.; Betz, C.J.; Chen, C.-C.; Hutchins, M.; McCarl, 

B.A.; Skog, K.; Sohngen, B.L. 2001. Assessing socioeconomic impacts 

of climate change on U.S. forests, wood-product markets, and forest 

recreation. BioScience. 51(9): 753–764.

National Ski Areas Association. 2014. Kottke national end of season survey 

2012/13: preliminary report. Available at http://www.snowsports.org/

Retailers/Research/SnowSportsFactSheet. (Accessed 9 January 2014).

U.S. Forest Service. 2012. Future of America’s forests and rangelands: Forest 

Service 2010 Resources Planning Act Assessment. Gen. Tech. Rep. WO-87. 

Washington, DC: U.S. Department of Agriculture, Forest Service. 198 p.

Other Resources

Bowker, J.M.; Askew, A.E.; Poudyal, N.; Zarnoch, S.J.; Seymour, L.; Cordell, 

H.K. 2014. Climate change and outdoor recreation participation in the 

southern United States. In: Vose, J.M.; Klepzig, K.D., eds. Climate change 

adaptation and mitigation management options: a guide for natural resource 

managers in southern forest ecosystems. Boca Raton, FL: CRC Press: 

421–450.

Cordell, H.K. 2012. Outdoor recreation trends and futures: a technical 

document supporting the Forest Service 2010 RPA Assessment.

Gen. Tech. Rep. SRS-150. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southern Research Station. 167 p. 
Appendix 2: Forest Indicators Technical Team Research Memo 115

APPENDIX 2: Forest Indicators Technical Team Research Memo1

This material is being included in this appendix for full transparency of our 

deliberations. We were asked to provide information about research gaps on the 

recommended indicators, as well as indicators that appear promising but which 

would probably need more than 1 year of research to be ready for use in an 

operational system. Some information presented here is also in the main text. 

We have worked to reduce duplication, yet make the entire publication as easy 

to read and understand as possible.

1

 Slightly updated from version dated December 18, 2014.

INTRODUCTION

This memo has three main sections: 1) general concerns, 2) research gaps for 

selected recommended indicators, and 3) recommended potential indicators and 

metrics. Most of the 11 recommended indicators need technical work to make 

them ready to be included on a Web site available to the public. For these, we 

briefly describe the work that is needed. For the potential indicators, we provide 

a more extensive description of each potential indicator, possible metrics, and 

needed research. The potential indicators are not a comprehensive list. They were 

determined by team members, and other scientists who expressed an interest in 

championing an indicator for forests.

General Concerns

Direct Link to Climate Impacts

For more than a decade, indicators have been used for forest conditions and 

their sustainability in the United States (e.g., see U.S. Forest Service 2011). The 

interaction of forests, climate change, and bioenergy as a crucial overarching 

issue has already been identified as an area needing more attention (U.S. Forest 
116 Indicators of Climate Impacts for Forests

Service 2011). Studies that are focused on the explicit links between climate and 

the forest indicators, interpretation, and implications are needed.

Links With Other Teams

Similar indicators for different teams also require additional thought in the forest 

indicator effort. Additional research or discussion would help to ensure that 

similar indicators for different teams are either shared or made appropriately 

consistent. For example, teams may prefer different indicators of drought. The 

agriculture team may prefer the Palmer Drought Severity Index, whereas the 

forest team is suggesting a newer indicator that is proving to be more appropriate 

for forests.

Protocols for Determining When New Approaches Are Better

A third issue is related to the perceptions (or realities) that new technologies 

can provide more accurate, effective estimates for recommended or potential 

indicators. Indicators for sustainability have a rich history in a forest context 

(e.g., U.S. Forest Service 2011), and a notable number of these indicators may 

be of core importance for climate change impacts in forests. Indicators for other 

land uses or land covers may not have the same level of data availability or 

history of use as do indicators for forests. Scientists or traditional stakeholders 

may consider the approaches to data collection in other land uses to be less 

accurate than those for existing forests. Disagreement over accuracy provides 

an additional level of complexity and even uncertainty when interpreting 

and explaining these indicators. Research is needed to determine when new 

technologies are ready to be implemented, or to clarify interpretation of 

indicators during the major transitions of approaches and technologies. A topic 

of much discussion is statistical and other quantitative approaches for detecting 

change. There are many techniques for time series and change detection, and 

different scientists or practitioners may have different opinions on which is best. 

Questions to consider are: Does a parsimonious set of techniques exist that would 

pass peer review? Should the approach be consistent across different indicators? 

Sensitivity and Risk

A final yet very important issue is about responses to impacts. Will the indicators 

be sensitive to response activities so that the effect of response activities will be 

detected? In addition, a concept often discussed in relation to response is that of 

risk. Even if probabilities are known that a result will occur, how decisionmakers 

choose to act based on that knowledge will probably differ. If the idea of risk is 

important to convey, how can risk be best conveyed through indicators? Research 

is needed to determine the importance of risk, and, if it is important, how to best 

convey the idea of risk through indicators.
Appendix 2: Forest Indicators Technical Team Research Memo 117

RESEARCH GAPS FOR SELECTED RECOMMENDED INDICATORS

Ecosystem Services Indicator: Trends in Diversity/Abundance 

of Forest-associated Floral and Faunal Species

The primary indicator that we recommend for monitoring trends in faunal species 

diversity/abundance is the Breeding Bird Survey (BBS) of the Department of the 

Interior, U.S. Geological Survey (USGS). This indicator is fairly comprehensive 

in terms of spatial and temporal coverage. The dataset, both in raw and analyzed 

form, is readily available through USGS (2015). However, deficiencies are 

present that may limit the usefulness of the data as a robust climate change 

indicator. First, the BBS focuses only on a single taxon (birds) and does not 

encompass the broad spectrum of forest-associated faunal species. Efforts are 

underway to collect similar, national-level data on a variety of other taxa (e.g., 

USGS North American Amphibian Monitoring Program, National Ecological 

Observatory Network [NEON]). To date, those fledgling datasets are not as 

comprehensive or uniform. If the efforts continue, the resulting databases would 

serve well to document trends in forest-associated species. 

Second, more work is needed to link trends in faunal diversity/abundance to 

the effects of climate change. Data from the BBS have been used to document 

population trends associated with a variety of factors including habitat loss/

fragmentation (Herkert 1994) and, more recently, climate change (Hitch and 

Leberg 2007). Additional studies are needed to determine how to tease apart 

these various factors. Third, known biases exist in the BBS dataset such as 

observer differences (Sauer et al. 1994), roadside survey bias (Keller and 

Scallan 1999), and limitations for certain species (e.g., raptors, nocturnal birds). 

Numerous studies have worked to address some of these biases, but caution 

should be used when applying this dataset as an indicator for certain species or 

for certain regions until additional research is conducted to address these issues 

fully. 

For our primary indicator of trends in forest-associated floral biodiversity, we 

recommend monitoring change over time in forest tree diversity across Forest 

Inventory and Analysis (FIA) plots maintained by the U.S. Forest Service. The 

advantages of this indicator include its broad spatial extent (about 130,000 

plots across the conterminous United States and southeast Alaska); a nationally 

consistent sampling protocol across all forest ownerships, based on a rigorous 

statistical design; the regular remeasurement of plots across time; and the public 

availability of the FIA data online. Additionally, the FIA plot system allows for 

aggregation to larger spatial scales, such as ecoregions and counties. 

However, two issues present challenges for the use of the FIA data for this 

indicator, at least in the short term. First, FIA data have been collected in a 

systematic fashion nationally since only about 2000; data are available from 
118 Indicators of Climate Impacts for Forests

before that, but are problematic to use. Second, options for time-series analyses 

in the Western United States will be limited for some time, as each plot in the 

region is visited only once every 10 years. At the same time, the number of 

5-year remeasurement cycles in the Eastern United States may not yet be 

adequate to assess biodiversity change associated with climate change. 

In addition, work is necessary to determine the extent to which change in forest 

tree seedling diversity represents a leading indicator of climate change effects 

on overall forest biodiversity because of seedlings’ additional sensitivity to 

environmental conditions. A recent study using FIA data in the Eastern United 

States detected weak broad-scale patterns of change in tree seedling diversity that 

are consistent with expected early effects of climate change (Potter and Woodall 

2012). However, other factors may be affecting changes in seedling diversity 

over time. Additional research is also needed to establish whether simple 

measures of biodiversity are sufficient in such a context, or whether biodiversity 

metrics that account for the evolutionary relationships among species also have 

utility (e.g., Potter and Woodall 2014).

Climate Impacts on Human Domain via Forest: 

Cost to Mitigate Wildfire Risk

Federal suppression costs are the most easily accessible data element for this 

indicator and can be relatively easily compiled for display. Federal expenditures 

for fuels treatments and related mitigation activities can likewise be accessed 

from federal budget reports, but measures in this area may call for additional 

development. Many forest restoration activities aim to improve multiple aspects 

of forest condition (including fire susceptibility and resilience) even if they are 

categorized directly under fuels treatments. Extension of these reporting activities 

to the state level will probably involve tallying expenditures for individual states 

and may be labor-intensive.

Insurance premiums and related measures require additional exploration and 

conceptual development. Whereas insurance markets have the benefit of 

representing actual market transactions and may thereby reveal new information 

about fire risk and expense, the use and interpretation of statistics in this area 

need careful consideration.

Human Influence on Climate Domain via Forest: 

Energy Produced from Forest-based Biomass

Major components of this indicator have already been developed by the U.S. 

Forest Service (2011). However, exports of forest biomass for energy production, 

notably the growing volume of wood pellets being shipped overseas to help fulfill 

renewable energy goals, are not included in current statistics. A full accounting of 

wood-based energy production should include exports, though mapping product 

reporting categories into specific energy usages may be challenging.
Appendix 2: Forest Indicators Technical Team Research Memo 119

Additional improvements to the indicator may be obtained by further 

consolidating and developing statistics in the domestic energy production sector. 

Wood energy from industrial installations, particularly as a byproduct of wood 

products manufacturing, is well reported and responsible for a major proportion 

of wood energy generation. Residential use and other diffuse energy production 

activities are less well reported, and estimates for them may require additional 

refinement. This is especially true in the presence of emerging technologies or 

shifting markets. 

Socioeconomic/Ecosystem Service: Outdoor Recreation 

(Developed Skiing and Cross-Country Skiing)

Mining additional available datasets could improve this indicator, especially in 

conjunction with local ski area monitoring, to more strongly tie participation in 

developed skiing to location. 

RECOMMENDED POTENTIAL INDICATORS AND METRICS

The forest team recommends six high-priority areas for further indicator research 

(Table 18). Several of these may be more appropriately housed within other 

teams, but we included them here due to their perceived importance as well as 

the interest of our team’s scientists.

Area for additional indicator research Potential indicator metrics

Tribes and climate change 1) Number of Native coastal communities relocated or needing to 

relocate in the next decade as a result of sea level rise or permafrost 

thaw, 2) Number of tribes developing climate change adaptation plans, 

3) Number of tribes and Native communities engaged with Climate 

Science Center/Landscape Conservation Cooperatives

Recreation 1) Mean high water, 2) Net internal rural migration rate, 3) Number of 

participants and days of participation in hiking

Permafrost Extent and distribution of permafrost and peatland and associated 

changes in the depth of the active layer within boreal forests and 

tundra

Diversity of lichens Lichen biodiversity status and trends, Lichen functional group state and 

trends

Ground layer (of moss/lichen mats) Biomass, Elemental content (carbon, nitrogen), and Functional groups 

of moss/lichen mats which form ground layer (in Alaska and Pacific 

Northwest)

Relationship of ozone to climate change Ozone concentrations in natural ecosystems

Table 18.—High-priority potential indicator areas and metrics
120 Indicators of Climate Impacts for Forests

Indicator: Tribes and Climate Change 

Major contributor: Marla R. Emery

Metrics: Number of Native coastal communities relocated or needing to relocate in the next 

decade as a result of sea level rise or permafrost thaw, Number of tribes developing climate change 

adaptation plans, Number of tribes and Native communities engaged with Climate Science Center/

Landscape Conservation Cooperatives

General Description of What Is Being Measured

As forest- and natural resource-dependent communities with centuries-tomillennia in place, Native peoples are among the first to be directly affected 

by accelerating climate change (Fig. 14). Native peoples also have a wealth of 

experience adapting to past changes. Three high-priority research areas address 

the impacts of climate change on indigenous peoples in the United States and 

the potential contributions of Native peoples to adaptation planning for their 

communities and the larger world. We considered using the metric Proportion 

of communities or tribes affected, but chose Number of tribes and Native 

communities because obtaining data for this metric is more feasible. Additionally, 

“number of” provides a core metric that can be used to calculate other values 

such as financial resources needed to address this pressing humanitarian need. 

Figure 14.―Map of Alaska showing the locations of the 31 Alaska Native villages that the U.S. Government 

Accountability Office (2009) identified as “imminently threatened.” Map source: U.S. Government Accountability Office 

(2009: 18).
Appendix 2: Forest Indicators Technical Team Research Memo 121

Number of Native Coastal Communities Relocated 

or Needing to Relocate by 2025 and Beyond

As stated in Bennett et al. (2014), the impacts of climate change on tribal lands 

and resources, such as accelerated sea level rise, erosion, permafrost thaw, and 

increased intensity of weather events, are resulting in current and potential 

future relocation of indigenous communities in Alaska, Louisiana, the Pacific 

Islands, and other coastal locations. These relocations are already causing a loss 

of community and culture, health impacts, and economic decline. At present, 

no lead agency is responsible for assessing, tracking, or assisting Native coastal 

communities needing to relocate as a result of climate change-related impacts 

(Bennett et al. 2014). Making this a high-priority research need would provide 

base information to focus attention on this escalating impact. 

Relevance to policy and management decisions—In addition to humanitarian 

concerns, sea level rise and relocation of Native communities may challenge 

federal and state capacities to comply with treaty obligations, the American 

Indian Religious Freedom Act (AIRFA 1978), and other bodies of law. 

Has this been used as an indicator by anyone else?—This issue is raised as a 

key message in the Third National Climate Assessment’s chapter on indigenous 

peoples, land, and resources (Bennett et al. 2014). However, we are not aware of 

a U.S. or international effort in which this was used as an indicator.

Needs for indicator development—A formal process is needed to compile 

local and regional data and fill in data gaps. U.S. federal agencies tracking 

sea level include the U.S. Environmental Protection Agency (EPA), National 

Aeronautics and Space Administration, and National Oceanic and Atmospheric 

Administration (NOAA). Organizations with the capacity to conduct or facilitate 

research incorporating Native peoples in the United States and its island 

protectorates include:

• Pacific Northwest Tribal Climate Change Project, University of Oregon: 

http://tribalclimate.uoregon.edu/

• Institute for Tribal Environmental Professionals, Northern Arizona 

University: 

www7.nau.edu/itep/main/home (accessed 25 September 2015) 

• American Indian and Alaska Native Climate Change Working Group, 

Haskell Indian Nations University: 

http://www.haskell.edu/climate/

• Pacific Islands Climate Change Cooperative: 

http://hawaiiconservation.org/activities/pacific-islands-climatechangecooperative 
122 Indicators of Climate Impacts for Forests

Number of Tribes and Native Communities Developing 

Climate Change Adaptation Plans

Tribes across the country are becoming actively engaged in developing climate 

change adaptation plans and other climate initiatives (e.g., Swinomish Climate 

Change Initiative). These efforts address, among other topics, the likely impacts 

of climate change on health, culture, and the built and natural environments, as 

well as actions that could be taken to counteract these impacts. Though focused 

first and foremost on the communities that implement these programs and the 

resources (including forests) on which they depend, actions often also encompass 

planning and cooperation with surrounding communities and local, state, and 

federal governments. Such plans would provide a window into fine-scale climate 

change effects of particular concern to resource-dependent communities.

Relevance to policy and management decisions—An understanding of U.S. 

Native peoples’ climate change initiatives would support:

• Incorporation of traditional ecological knowledge (TEK) into climate 

change adaptation and mitigation in a manner that is culturally appropriate 

and honors tribal sovereignty

• Anticipation of and planning for compliance with legal guarantees to U.S. 

Native peoples that may be compromised by climate change

• Identification of opportunities for partnerships to benefit U.S. Native 

peoples and others.

Has this been used as an indicator by anyone else?—No.

Needs for indicator development—Native peoples actively resist the notion that 

they are hapless victims of climate change. Rather, their cultures have millennia 

of experience adapting to a wide variety of environmental and other changes; 

they wish to be active players in devising solutions for their own communities 

and humanity at large. Currently, there is no clearinghouse or other single source 

of information on climate change initiatives by U.S. Native peoples. Preliminary 

information about tribal climate change adaptation plans is available through 

sources including:

• Institute for Tribal Environmental Professionals: 

www7.nau.edu/itep/main/climatechange/ 

(accessed 25 September 2015) 

• Pacific Northwest Tribal Climate Change Project: 

http://tribalclimate.uoregon.edu/

• Northern Institute of Applied Climate Science:

www.mtu.edu/forest/research/partnerships/niacs.html
Appendix 2: Forest Indicators Technical Team Research Memo 123

Number of Tribes and Native Communities Engaged With 

Climate Science Center/Landscape Conservation Cooperatives

U.S. Department of the Interior Secretarial Order 3289 of 2009 (amended 

2010), “Addressing the Impacts of Climate Change on America’s Water, Land, 

and Other Natural and Cultural Resources,” resulted in the establishment of 

partner-based Climate Science Centers (CSCs) and Landscape Conservation 

Cooperatives (LCCs) with the mandate for CSCs and LCCs to apply “scientific 

tools to increase understanding of climate change and to coordinate an effective 

response to its impacts on tribes and on the land, water, ocean, fish and wildlife, 

and cultural heritage resources that the Department manages.” As a result, CSCs 

and LCCs are focal points for engaging U.S. Native peoples in collaborative 

climate change efforts. 

Relevance to policy and management decisions—Preparedness and adaptation 

activities are of increasing importance to decisionmakers. This indicator provides 

information useful for targeting such efforts to protect the interests of Native 

communities, particularly for determining what is to be protected, why, and how. 

Has this been used as an indicator by anyone else?—No.

Needs for indicator development—Climate Science Centers and Landscape 

Conservation Cooperatives support substantive participation by tribes in 

deliberations on climate-related mechanisms, agreements, and rules and 

regulations. Understanding these efforts will enhance national capacity to plan 

for climate change adaptation and mitigation for all communities. Potential 

sources of data include:

• U.S. Institute for Environmental Conflict Resolution survey of tribal 

engagement in Landscape Conservation Cooperatives:

http://www.ecr.gov/; Sarah Palmer, federal-tribal engagement, 

palmer@ecr.gov

 • Climate Science Centers:

http://www.doi.gov/csc/index.cfm

 • Landscape Conservation Cooperatives:

http://www.fws.gov/landscape-conservation/lcc.html 

• College of Menominee Nation, Sustainable Development Institute:

http://sustainabledevelopmentinstitute.org/ 

Some additional selected literature on the impact of climate change on tribal 

communities can be found in Alexander et al. (2012), Bronen (2013), Malconado 

et al. (2013), and Salick and Ross (2010).
124 Indicators of Climate Impacts for Forests

Indicator: Outdoor Recreation and Amenities 

Major contributor: Linda S. Heath, with major input from H. Kenneth Cordell

Metrics: Access to coastal land, Amenities, Hiking

General Description of What Is Being Measured

Climate change impacts on forests naturally include impacts on rural 

communities and people linked to forests (Melillo et al. 2014). The term 

“outdoor recreation” covers a wide range of activities such as walking on the 

beach, hiking, bird-watching, hunting, canoeing, skiing, and camping. Many 

of these activities may be affected by climate variability and change, but the 

response effect is complex and the outcome may be unexpected (e.g., Irland 

et al. 2001). Research has investigated the relation of specific types of outdoor 

recreation to climate broadly, as well as the relationship of amenities to climate 

(Bowker et al. 2014; Cordell et al. 2011, 2012). 

An amenity is “an attribute that enhances a location as a place of residence” 

(McGranahan 1999). In the United States, people prefer rural areas that include 

a mix of forestland, and mild winters and cool summers. Research has shown 

that because of this preference, amenities are strongly linked to climate (Cordell 

et al. 2011). If a location is rich in amenities, people want to move there; this 

consequence is confirmed by data which show net internal migration rates 

are positive to amenity-rich locations. We include the following as potential 

indicators.

Access to coastal land (Mean high water)—In most coastal states, recreational 

access is granted to the public under the Public Trust Doctrine. This access 

(ordinarily) is afforded the public between mean low tide up through the “soft 

sand” beach areas to the vegetation line. As climate grows warmer, sea level 

will rise and the public’s opportunities for using this outdoor recreation resource 

will change. Additional research is needed to understand how well this indicator 

relates to climate impacts on outdoor recreation. Another possible metric is the 

area of land between mean lower low tide and mean higher high tide. These tidelevel data are all standard NOAA measures (see NOAA 2015). Some research 

highlighting the use of these coastal areas for outdoor recreation, linked with a 

metric from NOAA data, could prove fruitful.

Amenities: Net internal rural migration rate—Net internal migration rate is 

an amenity metric. It is the difference between domestic in-migration to an area 

and out-migration from the same area during a set time period. Domestic in- and 

out-migration consist of moves where both the origin and the destination are 

within the United States, excluding Puerto Rico. The rate expresses net domestic 

migration during a time period as a proportion of an area’s population at the 

midpoint of the time period. Rates are expressed per 1,000 people. Research has 

shown this rate to be climate-sensitive (Cordell et al. 2011) at a scale as fine as 

the county level. 
Appendix 2: Forest Indicators Technical Team Research Memo 125

Indicator: Permafrost 

Major contributor: Bethany K. Schulz 

Metrics: Extent and distribution of permafrost and peatland, Associated changes in the depth of the 

active layer within boreal forests and tundra

Boreal forest and woodland occur across landscapes that include nonforest 

ecosystems. Collectively, the landscape response to disturbance, succession, 

and climate change is linked to the distribution of permafrost, soil types, and the 

dynamics of the layer of soil that thaws during the growing season. Our ability 

to predict how climate change may affect these boreal systems hinges on our 

knowledge of the extent and distribution of permafrost and peatland and the 

changes in depth of the active-layer.

Number of participants and Days of participation in hiking—Hiking is a 

popular activity in the United States, with 1.2 billion activity days of day hiking 

in 2007–2008 (U.S. Forest Service 2011). Number of participants and days of 

participation in hiking have been shown to be linked to warm-season climate. 

These variables are available as regional current estimates and as projections. 

Projections will be updated as new underlying information becomes available. 

Local and state-level projections are not currently available. Research indicates 

that day hiking would be negatively affected under several of the currently used 

climate change projections (Bowker et al. 2014). Additional research is needed 

to use climate impacts on hiking as an indicator. 

Boreal landscape of a mix of forest and nonforest in Alaska. U.S. Forest Service photo by 

Jon Williams.
126 Indicators of Climate Impacts for Forests

General Description of What Is Being Measured

Extent and distribution of permafrost—Permafrost, which is permanently 

frozen ground, is a major feature of arctic and subarctic biomes, affecting 

ecosystem function as well as engineering of human infrastructure. At the 

highest latitudes, it may be continuous over vast landscapes. Where permafrost 

becomes discontinuous, it is difficult to map over scales meaningful to ecological 

processes or infrastructure planning. Permafrost is responding to changing 

temperature regimes, but it is unclear how changes in climate will affect nearsurface processes in the long term (Abraham 2011). The extent of permafrost in 

Alaska is shown in Figure 15.

Extent and distribution of peatlands—Peatlands feature deep organic soils 

associated with live, dead, and decaying peat mosses. Although all peatlands 

store abundant amounts of carbon, boreal peatland is of special interest when 

it coincides with permafrost. Boreal peatland is generally insulated from air 

temperatures by thick layers of sphagnum moss (Sphagnum spp.) (Chapin 

et al. 2010, Krankina et al. 2008). 

Figure 15.―Map of the permafrost extent in Alaska (Brown et al. 1998).
Appendix 2: Forest Indicators Technical Team Research Memo 127

Changes in the depth of the active layer—The active layer is the portion of the 

soil horizon that melts in the growing season; it supports plant growth and soil 

respiration, and is subject to decomposition. In general, the active layer responds 

to air temperature on an interannual basis. In areas with tree cover, however, thaw 

depth is associated with snow cover (or lack thereof), forest canopy, and ground 

surface vegetation layers (Brown et al. 2000).

What is the link to climate variability and change or relevance?—Permafrost 

represents a large reservoir of stored carbon. These soils are subject to the 

changing global climate (Zimov et al. 2006) and their distribution is predicted to 

decrease in response to climate warming (Stendel and Christensen 2002). A better 

understanding of the dynamic distribution and physical properties of permafrost, 

continuous and discontinuous, will provide knowledge of how the permafrost 

environment may change in the future and help inform engineering and natural 

resource response strategies (Abraham 2011).

Mapping the distribution and extent of peatland, where permafrost is insulated 

by thick moss mats, provides a basis for calibration of estimates of carbon loss, 

which is expected due to temperature changes. Even in warming conditions, peatdominated communities can continue to store carbon (Chapin et al. 2010). Once 

degraded, however, they can quickly become sources of atmospheric carbon. 

Knowing the distribution and extent of these lands is critical for understanding 

how continued warming may tip the balance of carbon sequestration in the boreal 

zone.

Vegetation shifts are directed in different trajectories according to the substrates 

and underlying permafrost conditions. Where water accumulates, peatland 

may expand; if water drains away, shrubs and trees may encroach into wetland 

(Pitkänen et al. 2013). Tracking the changes in the depth of the active layer in 

relation to permafrost and peatland distribution will aid our understanding of 

ecosystem response to a changing climate. 

Relevance to management decisions—A better understanding of the extent 

and distribution of permafrost, peatland, and the changes to the active layer 

can inform engineers tasked with building roads, pipelines, and infrastructure. 

This indicator would help resource managers predict shifts in vegetation that 

might influence tree growth, wildlife habitat, or wildfire activity as well as the 

ways that specific management activities may affect carbon storage or release. 

The carbon stored in permafrost is highly decomposable (Waldrop et al. 2010) 

once exposed to warming temperatures. However, permafrost under peatland is 

protected by thick moss layers which may continue to act as a carbon sink even 

as air temperatures rise. These lands provide an enormous reservoir of carbon 

storage, and would provide a valuable ecosystem service if managed accordingly.
128 Indicators of Climate Impacts for Forests

Understanding the dynamics of carbon storage and release in boreal systems 

is critical for accurate estimation of the terrestrial contribution to the global 

carbon cycle. Underscoring the continued need for carbon emission reductions 

at the global level, Zimov et al. (2006) conclude with a stern warning: “Factors 

inducing high-latitude climate warming should be mitigated to minimize the 

risk of a potentially large carbon release that would further increase climate 

warming.” 

Has this indicator been used as an indicator by anyone else?—Remote 

sensing techniques for mapping permafrost features have been developed to 

provide information for groundwater models of the Yukon River Basin; the 

implications for engineering infrastructure and natural resource management 

are acknowledged (Abraham 2011). However, metrics for this indicator and 

techniques to provide measurements need additional development.

Needs for indicator development—Peatland mapping techniques have been 

developed, but are less reliable when tree cover is present (Krankina et al. 2008). 

This difficulty emphasizes the need for ground measurements of moss and 

lichen mats and measurements of the active layer (see “Ground layer indicator” 

later in this appendix). Changes in the depth of the active layer have long been 

recognized as an important factor for predicting the changing dynamics of 

carbon storage. The Circumpolar Active Layer Monitoring (CALM) Network has 

established more than 200 sites in the last two decades to measure active-layer 

thickness and observe soil temperatures (Brown et al. 2000, CALM Network 

2015). Even with data from these sites, however, active layer characteristics are 

difficult to assess over large regions without additional specialized techniques. 

Indeed, advances in remote sensing techniques in recent years have provided 

promising new methods for mapping permafrost features (Fig. 16) (Abraham 

2011) and peatlands (Krankina et al. 2008, Torbick et al. 2012). The CALM 

Network’s sites are invaluable, but remote sensing techniques could bridge 

the gap between in situ point measurements and areal averages to provide 

information at regional scales. 

The joint development of remote sensing methods with ground-based 

measurements (see “Ground layer indicator,” later in this appendix) to calibrate 

and verify remotely sensed results is critical. The extent and distribution of 

permafrost and peatland, along with the dynamics of the active layer, provide 

for a meaningful indicator for climate assessments. Given recent advances in 

technology, estimates for this indicator appear within reach. Solutions derived 

from multi-agency efforts, with a focused implementation, would facilitate data 

sharing for larger regional assessments. 
Appendix 2: Forest Indicators Technical Team Research Memo 129

Figure 16.―(a) Description of airborne electromagnetic systems, a promising tool 

for subsurface permafrost mapping (source: Abraham 2011); (b) three-dimensional 

cutout view showing results for the resistivity model for an example in Alaska. The gray 

isosurface is the interpreted base of the permafrost in the subsurface (source: Abraham 

2011). 

a

b
130 Indicators of Climate Impacts for Forests

Indicator: Lichen Biodiversity 

Major contributor: Sarah Jovan

Metrics: Lichen biodiversity status and trends, Lichen functional group status and trends

General Description of What Is Being Measured

Lichens are a large component of biodiversity in North American forests. To date, 

5,355 species of lichens and allied fungi are known to inhabit the continental 

United States and Canada (Esslinger 2012). Under optimal conditions, epiphytic 

(i.e., living on tree surfaces) lichen biomass may exceed 0.83 tons per acre 

(1.87 metric tons per ha) (McCune 1993). The role of this epiphytic layer 

in regulating water and nutrient cycling in forest ecosystems is not widely 

recognized. Lichens increase capture of rain and nutrients from the atmosphere; 

captured nutrients are slowly released to the canopy and forest floor through 

leaching and decomposition of lichen litter (Pike 1978). 

Lichens are highly climate-sensitive because they lack roots and are unable to 

retain water. As a result, basic metabolic processes and fitness are closely tied to 

ambient temperature and moisture. In some ways this life strategy is beneficial—

for instance, by allowing species to grow independently of the soil (e.g., 

epiphytically or on rocks and leaves) and for short-term endurance of drought 

and other unfavorable conditions whereupon lichens dry out and go “dormant.” 

However, dependence on atmospheric conditions becomes a liability with 

longer term climate changes, which may damage tissue directly or unbalance 

photosynthesis and respiration rates. 

We propose that a climate indicator be developed using the FIA Lichen 

communities indicator (U.S. Forest Service 2015a). A dataset already exists of 

more than 8,000 epiphytic lichen surveys (1998–2013) collected by FIA and the 

U.S. Forest Service, Region 6 Air Management Program, including many repeat 

measurements (Fig. 17). Use of these data for climate assessment has so far been 

cursory (but see Root et al. 2014, 2015).

What Is the Link to Climate Variability and Change or Relevance?

Optimal levels of moisture, temperature, and nutrient availability differ widely by 

lichen species as does stress tolerance to suboptimal conditions. Sustained shifts 

in any of these drivers cause changes in lichen community composition, which 

affect species that use lichens directly or depend upon the ecological services 

they provide. 

Some of the most climate-sensitive lichens have specialized functions. One 

example is the bearded alectorioid lichens. This functional group serves as 

nesting material and critical winter forage for a variety of wildlife species in the 

temperate and boreal forest biomes. (For example, see “Lichen Use by Wildlife 

in North America” at http://www.lichen.com/fauna.html.) Another example of 
Appendix 2: Forest Indicators Technical Team Research Memo 131

Figure 17.―Sites surveyed for epiphytic lichen communities by the U.S. Forest Service, Forest Inventory and 

Analysis and partner agencies. Some of these data have been only recently released. Used with permission from 

Jennifer Phelan, RTI International.

a lichen group highly sensitive to climate is the cyanolichens, a group that fixes 

atmospheric nitrogen (N) into a form that is usable by plants. Under favorable 

conditions, a single species (Lobaria oregana) can fix as much as 14.2 pounds N 

per acre per year (16 kg N per ha per year) (Antoine 2004), and total biomass of 

cyanolichen may exceed 892 pounds per acre (1,000 Kg per ha) (McCune 1993). 

This group is distributed in patches across the landscape and requires a relatively 

narrow range of moisture and temperature. 

Community-level and species-level responses to climate have been demonstrated 

in several studies (Ellis 2013, Ellis et al. 2007), and we are starting to understand 

effects at the physiological level (Song et al. 2012). However, few studies 

investigate changes over time, and little work has been done for U.S. forest 

ecosystems.
132 Indicators of Climate Impacts for Forests

Has This Indicator Been Used as an Indicator by Anyone Else?

The U.S. Forest Service uses the Lichen communities indicator extensively for 

indicating air quality effects on forests. Studies stemming from that effort also 

document strong community patterns relating to spatial temperature and moisture 

gradients. Describing these results and following them over time has not been a 

high priority, however.

Needs for Indicator Development

In the summer of 2014 we collected baseline data on community composition 

and health of lichen transplants at the U.S. Forest Service Marcell Experimental 

Forest in Minnesota, as part of the Spruce and Peatland Responses Under 

Climatic and Environmental Change (SPRUCE) project (http://mnspruce.ornl.gov/), 

a state-of-the-art open-topped chamber warming experiment. We are seeking 

support for periodic remeasurements and for a graduate research assistant to 

conduct research on the dataset of 9,000 lichen surveys for use as indicator 

species and response indices, as well as to work on estimates of change by 

using remeasured data.

Indicator: Ground Layer 

Major contributors: Robert J. Smith and Sarah Jovan

Metrics: Ground layer moss/lichen biomass, Ground layer moss/lichen elemental content, and Ground 

layer moss/lichen functional group status and trends

General Description of What Is Being Measured 

Mosses and lichens extensively carpet boreal regions with thick “ground layers” 

which are responsible for stabilizing and cooling soils, halting permafrost thaw, 

regulating water tables, slowing decomposition rates, and building deep deposits 

of peat (Turetsky et al. 2012). Peatlands sequester one-third of the global soil 

carbon budget (Yu et al. 2011), and carbon release from peatlands is highly 

sensitive to changes in climate and fire regimes (Turetsky et al. 2011). Until 

recently, however, we have lacked reliable tools for quantifying terrestrial carbon 

and ecosystem functions in ground layers at landscape scales.

To address such gaps, we are testing a Ground layer indicator with metrics that 

evaluate biomass, elemental content (i.e., carbon and nitrogen content), and 

functional group status and trends in moss and lichen ground layers (Smith et al. 

2015). The indicator is based on the premise that simple measurements of the 

depth and area covered by mosses and lichens can be scaled into landscape-level 

estimates of biomass and elemental content based on prior calibrations. Ground 

layer moss/lichen biomass is the amount of biomass by dry weight of mosses/

lichens. A separate ground layer moss/lichen elemental content metric allows for 
Appendix 2: Forest Indicators Technical Team Research Memo 133

tracking changing carbon and nitrogen content in this layer. Ground layer moss/

lichen functional group status and trends is a measure of functional importance, 

which is assigned to nine easily recognizable morphological groups, examples of 

which are soil stabilizers, nitrogen fixers, water regulators, and wildlife forage 

groups. The lichens in this indicator are independent of and not related to the 

epiphytic lichens in the Lichen biodiversity indicator.

What Is the Link to Climate Variability and Change or Relevance?

Changing climate has the potential to shift species ranges, resulting in the gain 

or loss of major functional groups in ground layers. For example, a warming and 

drying climate can promote shrub expansion into boreal tundra that excludes 

forage lichens (Heggberget et al. 2002). Similarly, increasing aerial nitrogen 

deposits are associated with the loss of tundra and boreal forest lichens, which 

are indicators of air quality (Pardo et al. 2011). In wetland, lowered water tables 

coupled with more severe wildfires can eliminate both critical peat deposits and 

the Sphagnum mosses which form them (Turetsky et al. 2011).

Climatic change also affects carbon cycling between ground layers and the 

atmosphere. If boreal climates warm as expected, decomposition of peat liberated 

from degraded permafrost may release methane (CH4 )and carbon dioxide (CO2 ) 

in a feedback loop that would amplify additional carbon losses (McGuire et al. 

Boreal peatland deeply carpeted with mosses and peat. Peatlands represent vast stores 

of global carbon, yet they are increasingly vulnerable to climate fluctuations and land use 

changes. Photo by Robert J. Smith, Oregon State University, used with permission.
134 Indicators of Climate Impacts for Forests

2009). However, longer and warmer growing seasons might alternatively 

promote the expansion of peat-forming mosses that raise water tables, which 

would enhance soil cooling, permafrost retention, and decomposition rates 

(Chapin et al. 2010). The wide range of uncertainty among possible outcomes 

highlights the importance of monitoring ground layers as vital contributors to 

ecosystem functioning and global carbon budgets.

What Are the Drivers of This Indicator and What Are its Impacts? 

The Ground layer indicator arose from the need to make status and trend 

information available to researchers, resource managers, and policy makers. It 

represents not only an inventory of current ground layer conditions, but also the 

launching point for process-based studies that seek to understand the causes and 

consequences of environmental change and resulting regime shifts. However, the 

utility of the indicator extends beyond academics and specialists because it can 

guide policy makers and educators. Likewise, the indicator is not constrained to 

any geographical region; its simplicity means that the indicator has the flexibility 

to be implemented not only in high-latitude terrestrial systems, but also in forest, 

steppe, grassland, and wetland habitats throughout all regions. It is also readily 

scaled from plot to landscape levels.

Sphagnum peat-moss, a desirable keystone species responsible for regulating water 

levels, soil temperature, and rates of decomposition. Photo by Bernd Haynold, under 

Creative Commons license.
Appendix 2: Forest Indicators Technical Team Research Memo 135

Relevance to Management Decisions

Land management (or decisions which may result in land use change) such as 

wildfire prescription/suppression, invasive species control, and groundwater use 

entails impacts to ground layers (both positive and negative) which managers 

must understand if they are to retain the suite of ecosystem services that ground 

layers provide. The Ground layer indicator will give resource managers baseline 

information useful for gauging how land use changes and environmental 

alterations may affect the provision of ecosystem functions and carbon 

budgets in boreal forests and beyond.

Has This Indicator Been Used as an Indicator by Anyone Else?

No previous indicator has attempted to quantify the biomass, elemental content, 

and functional importance of the ground layer. To date, the Ground layer 

indicator has undergone extensive field trials throughout interior Alaska and 

the U.S. Pacific Northwest (Smith et al. 2015). 

Needs for Indicator Development

The protocol in Smith et al. (2015) is still flexible enough to be modified where 

local needs dictate (e.g., some regional locations may have different plant 

functional groups not found elsewhere). It would be fruitful to extend the work to 

different habitat types and to explore and test methods for deep peat sampling. 

Portion of the ground layer in Alaska tundra. A 6-inch portion can fulfill many functional 

roles, such as fixing nitrogen, stabilizing soils, and providing winter forage for wildlife. 

Photo by Robert J. Smith, Oregon State University, used with permission.
136 Indicators of Climate Impacts for Forests

Indicator: Ozone: Relationship of Ozone to Climate Change 

Major contributors: Robert Musselman and Andrzej Bytnerowicz

Metric: Ozone concentrations in natural ecosystems 

General Description of What Is Being Measured: Ozone 

We propose the development of a climate indicator using ambient ozone in 

forests. Many forest areas already exceed the current National Ambient Air 

Quality Standard (40 CFR part 50) for ozone (Fig. 18) assessed by U.S. EPA. 

Ozone (O3 ) is a pollutant produced in the atmosphere by chemical reaction of 

precursor chemicals, which are produced by burning fossil fuels. Climate change 

is expected to result in additional ozone and increased plant stress. Higher 

temperatures may increase the amount of chemical precursors for O3 formation, 

the rate of chemical reactions creating O3 , and the sensitivity of plant species 

from new climate-induced stress not previously encountered. 

What Is the Link to Climate Variability and Change or Relevance?

Ozone is a greenhouse gas that plays an important role in the energy budget of 

the atmosphere. It features the third largest positive radiative forcing among the 

atmospheric greenhouse gases (Gauss et al. 2003). Because O3 is a precursor for 

Figure 18.―Concentration of ozone (parts per billion) in the United States in terms of the 3-year average of the fourth 

highest daily maximum 8-hour average for 2009 through 2011 (AMEC Environment & Infrastructure, Inc. 2013).
Appendix 2: Forest Indicators Technical Team Research Memo 137

oxidizing reactions, it strongly influences the lifetime of other greenhouse gases 

such as methane and hydrofluorocarbons (HFCSs), which in turn affects radiative 

forcing (Gauss et al. 2006). In addition, it also indirectly affects climate by 

limiting sequestration of CO2 by vegetation (Sitch et al. 2007). 

Modeling the link between climate change and ozone is only in its early phases 

(U.S. EPA 2009), but most models predict a link between climate change and 

increased O3. For example, emissions of the O3 precursor volatile organic 

compounds (VOCs) and nitrogen oxides (NOx ) are expected to increase, with 

a significant contribution of those generated in southeast Asia (Doherty et al. 

2013). Increases in summertime peak O3 concentrations are particularly evident 

in model results (U.S. EPA 2009). Lengthening of the summertime high-O3

season is also expected concurrent with an increase in the length of the growing 

season (U.S. EPA 2009). 

Vegetation is very sensitive to high O3 concentrations. Ozone already exceeds 

the current standard in some forested mountain areas of the Rocky Mountains 

(Musselman and Korfmacher 2014), and U.S. EPA has proposed strengthening 

the ozone standard to protect vegetation and trees (U.S. EPA 2004). Therefore, 

the importance of O3 to management is expected to continue to grow. Interactions 

of increases in CO2 and increases in O3 will likely cause genetic changes in plant 

populations (Moran and Kubiske 2013). Increased O3 effects on ecosystems will 

most likely cause changes in ecosystem function such as carbon sequestration 

and in distribution, quality, and quantity of streamwater (Bytnerowicz et al. 

2013a, McLaughlin et al. 2007). Recent years have shown increases in the 

number of wildfires in U.S. forests, partially a result of climate-increased 

ambient temperatures and increased weather extremes, such as drought. A direct 

link between wildfires and increased O3 has been reported (Bytnerowicz et al. 

2013b). 

Has This Indicator Been Used as an Indicator by Anyone Else?

The Ozone indicator has been used by the U.S. Forest Service’s Forest Health 

Monitoring program to indicate sensitivity of plant species in forests to ambient 

O3 (U.S. Forest Service 2015b). However, the explicit link to climate has not 

been made.

Needs for Indicator Development

The model results linking ozone to climate change differ greatly by region 

(U.S. EPA 2009). Additional research on the interaction of increased CO2 , 

temperatures, and O3 effects on individual forest tree species is needed. Little 

is known about the interaction of longer growing season, increased levels 

of summertime O3 , and increased climate-induced vegetation stress, such 

as drought, on vegetation or ecosystem response. The relationship between 

climate change and emissions of O3 precursors needs additional study. Finally, 

determining the metric that will most clearly convey the impact of ozone on 

climate and forests needs additional work.
138 Indicators of Climate Impacts for Forests

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Printed on recycled paper

Heath, Linda S.; Anderson, Sarah M.; Emery, Marla R.; Hicke, Jeffrey A.; Littell, 

Jeremy; Lucier, Alan; Masek, Jeffrey G.; Peterson, David L.; Pouyat, Richard; 

Potter, Kevin M.; Robertson, Guy; Sperry, Jinelle; Bytnerowicz, Andrzej; 

Jovan, Sarah; Mockrin, Miranda H.; Musselman, Robert; Schulz, Bethany K.; 

Smith, Robert J.; Stewart, Susan I. 2015. Indicators of climate impacts for 

forests: recommendations for the U.S. National Climate Assessment indicators 

system. Gen. Tech. Rep. NRS-155. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station. 143 p. 

The Third National Climate Assessment (NCA) process for the United States 

focused in part on developing a system of indicators to communicate key aspects 

of the physical climate, climate impacts, vulnerabilities, and preparedness to inform 

decisionmakers and the public. Initially, 13 active teams were formed to recommend 

indicators in a range of categories, including forest, agriculture, grassland, 

phenology, mitigation, and physical climate. This publication describes the work of 

the Forest Indicators Technical Team. We briefly describe the NCA indicator system 

effort, propose and explain our conceptual model for the forest system, present our 

methods, and discuss our recommendations. Climate is only one driver of changes 

in U.S. forests; other drivers include socioeconomic drivers such as population and 

culture, and other environmental drivers such as nutrients, light, and disturbance. 

We offer additional details of our work for transparency and to inform an NCA 

indicator Web portal. We recommend metrics for 11 indicators of climate impacts 

on forest, spanning the range of important aspects of forest as an ecological type 

and as a sector. Some indicators can be reported in a Web portal now; others 

need additional work for reporting in the near future. Indicators such as budburst, 

which are important to forest but more relevant to other NCA indicator teams, are 

identified. Potential indicators that need more research are also presented. 

Key words: forest extent indicator, forest biomass indicator, wildfire indicator, 

 forest insect and disease damage indicator, 

 water balance deficit indicator, WUI indicator, fire risk cost indicator, 

 biomass energy indicator, forest growth indicator, 

 biodiversity indicator, skiing indicator, NCA indicator system 

In accordance with Federal civil rights law and U.S. Department of Agriculture (USDA) civil rights 

regulations and policies, the USDA, its Agencies, offices, and employees, and institutions participating 

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