Effects of Climate Change 

on Natural Resources 

and Communities: A 

Compendium of Briefing 

Papers

United States 

Department of 

Agriculture

Forest Service

Pacific Northwest 

Research Station

General Technical 

Report

PNW-GTR-837

March 2011
The Forest Service of the U.S. Department of Agriculture is dedicated to the principle of 

multiple use management of the Nation’s forest resources for sustained yields of wood, 

water, forage, wildlife, and recreation. Through forestry research, cooperation with the 

States and private forest owners, and management of the National Forests and National 

Grasslands, it strives—as directed by Congress—to provide increasingly greater service to a 

growing Nation.

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activities on the basis of race, color, national origin, age, disability, and where applicable, sex, 

marital status, familial status, parental status, religion, sexual orientation, genetic information, 

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public assistance program. (Not all prohibited bases apply to all programs.) Persons with 

disabilities who require alternative means for communication of program information (Braille, 

large print, audiotape, etc.) should contact USDA’s TARGET Center at (202) 720-2600 (voice 

and TDD). To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, 

1400 Independence Avenue, SW, Washington, DC 20250-9410 or call (800) 795-3272 (voice) 

or (202) 720-6382 (TDD). USDA is an equal opportunity provider and employer.

Authors

Janaki Alavalapati is professor and head, Department of Forestry, College of 

Natural Resources, Virginia Polytechnic Institute and State University, Blacksburg, 

VA 24061. Ralph J. Alig is a research forester, U.S. Department of Agriculture, 

Forest Service, Pacific Northwest Research Station, 3200 SW Jefferson Way, 

Corvallis, OR 97331. Pankaj Lal is a Ph.D. Candidate, School of Forest Resources 

and Conservation, University of Florida, Gainesville, FL 32611. D. Evan Mercer 

is a research economist, U.S. Department of Agriculture, Forest Service, Southern 

Research Station, P.O. Box 12254, Research Triangle Park, NC 27709. Anita 

T. Morzillo is an assistant professor, senior research, Department of Forest 

Ecosystems and Society, College of Forestry, Oregon State University, Corvallis, 

OR 97331. Edward A. Stone is a graduate research assistant, Department of 

Agricultural and Resource Economics, Oregon State University, Corvallis, OR 

97331. Eric M. White is a research associate, Department of Forest Engineering, 

Resources and Management, College of Forestry, Oregon State University, 

Corvallis, OR 97331.

Cover photograph by Ralph J. Alig.
Effects of Climate Change 

on Natural Resources and 

Communities: A Compendium 

of Briefing Papers

Ralph J. Alig, Technical Coordinator

U.S. Department of Agriculture, Forest Service

Pacific Northwest Research Station

Portland, Oregon

General Technical Report PNW-GTR-837

March 2011
Abstract

Alig, Ralph J., tech. coord. 2011. Effects of climate change on natural resources 

and communities: a compendium of briefing papers. Gen. Tech. Rep. PNWGTR-837. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 169 p.

This report is a compilation of four briefing papers based on literature reviews and 

syntheses, prepared for USDA Forest Service policy analysts and decisionmakers 

about specific questions pertaining to climate change. The main topics addressed 

here are effects of climate change on wildlife habitat, other ecosystem services, 

and land values; socioeconomic impacts of climate change on rural communities; 

and competitiveness of carbon offset projects on nonindustrial private forests in 

the United States. The U.S. private forest offset projects tend to be less costly than 

European projects but more expensive to implement than those in tropical forests 

in developing countries. Important policy considerations involving any mitigation 

actions include effects on other ecosystem services, such as wildlife habitat, and 

determining baselines and additionality. Stacking of ecosystem services payments or credits with carbon offset payments may be crucial in improving the 

participation of private forest owners. Potential social impacts of climate change 

are discussed in terms of health effects on rural communities and climate change 

sensitivity of indigenous communities. Potential economic impacts on rural communities are discussed for agriculture, forestry, recreation and tourism, fisheries, 

water resources, and energy. Salient findings from the literature are summarized in 

the synthesis of the literature, along with identified research needs. 

Keywords: Climate change, wildlife habitat, land values, ecosystem services, 

vulnerability, rural communities.
Summary

Periodic syntheses of the ever-expanding knowledge about climate change, 

impacts on natural resources and associated ecosystems, land use and values, and 

human communities are critical to effective policy formulation. We also need to 

better understand how adaptation to and policies for addressing climate change 

may affect landscapes, ecosystems, ecosystem services, and local economies. 

Policy deliberations will be aided by better information on the economic viability 

of forest-related offsets relative to other greenhouse gas (GHG) offset options. 

Forest ecosystems can transfer carbon from the air as part of the GHG complex 

and sequester it into plant tissue through the process of photosynthesis during the 

growth of trees and in other ecosystem components such as the understory and 

soil. Such forest sinks have a significant potential to help in mitigating climate 

change, and this report is a compilation of briefing papers prepared for USDA 

Forest Service policy analysts and decisionmakers about specific forest carbon 

sequestration topics. The briefing papers are part of a larger set prepared by agency 

scientists and cooperators, including a related one regarding forest bioenergy by 

White1

 and another set pertaining to economic modeling of the effects of climate 

change on the U.S. forest sector and mitigation options.2 Given the large topic 

of climate change and forests, this report only touches on selected aspects, and 

readers are referred to the growing literature for information on specific topics 

such as incorporating climate change considerations into specific natural resource 

management.3

In the first chapter, Morzillo and Alig review the literature pertaining to effects 

of climate change on wildlife and wildlife habitat at a broad scale. Because climate 

change is such a far-reaching topic, research opportunities focusing on climate 

change impacts on wildlife and wildlife habitat are likely to be most informative 

for policymakers if formulated using an integrated and multidisciplinary systems 

analysis approach and adaptive management. An adaptive process will facilitate 

1

 White, E. 2010. Woody biomass for bioenergy and biofuels in the United States—a 

briefing paper. Gen. Tech. Rep. PNW-GTR-825. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station. 45 p.

2

 Alig, R. 2010. Economic modeling of effects of climate change on the forest sector and 

mitigation options: a compendium of briefing papers. Gen. Tech. Rep. PNW-GTR-833. 

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Research Station. 169 p. 

3

 Joyce, L.A.; Haynes, R.W.; White, R.; Barbour, R.J., tech. coords. 2006. Bringing 

climate change into natural resources management: proceedings. Gen. Tech. Rep. 

PNW-GTR-706. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 150 p. 
results from research involving land-use changes, forest management, wildlife 

management, mitigation alternatives, and society’s willingness to undertake actions 

to formulate more policy alternatives, along with confronting other components of 

the global climate issue. 

The second chapter by Alig et al. assesses research about effects of climate 

change on land productivity and values, including influences on provision of 

ecosystem services. Climate change policies may in turn affect land and resource 

markets, thereby modifying land values, land use, and forest cover distribution. A 

broad examination of such changes necessitates assessing multiple markets, including those for carbon sequestration as an ecosystem service, especially if policies 

arise to promote carbon sequestration as a mitigation activity. 

In the third chapter, Lal et al. look at effects of climate change on rural communities. Their review suggests that rural communities tend to be more dependent on 

climate-sensitive livelihood activities and have fewer resources and social support 

systems compared to urban populations. They suggest that rural communities could 

face large potential impacts from future climate change events. 

In the fourth chapter, Mercer et al. review competitiveness of forest-based 

carbon offset projects, relative to other offset options in agriculture, clean transportation, carbon capture and sequestration, nuclear and other advanced technologies, 

increasing energy efficiency, renewable energy, and other options. They examine 

estimates of per unit costs of removing atmospheric carbon through domestic offset 

projects, and find that estimates differ widely. 
Contents

1 Chapter 1: Climate Change Impacts on Wildlife and Wildlife Habitat

 Anita T. Morzillo and Ralph J. Alig

1 Introduction

2 Ecological and Behavioral Responses of Wildlife to Climate Change

2 Range Shifts

6 Environmental Processes Affecting Migration

8 Functional Roles Within Ecosystems

10 Impacts of Climate Change on Wildlife Habitat

10 Relationships Between Vegetation and Wildlife

11 Disturbance

13 Microclimate

14 Interaction Between Climate Change and Land Use

16 Impacts of Climate Change Mitigation on Wildlife Habitat

16 Afforestation

18 Carbon and Bioenergy Markets

19 Incentive Programs for Landowners

23 Linkages of Climate Change Model Projections and Impacts From 

 Global to Local Scales

27 Thinking Toward the Future

28 English Equivalents

29 Literature Cited

43 Chapter 2: Land Value Changes and Carbon Sequestration as an 

 Ecosystem Service in a Climate-Changed Environment

 Ralph J. Alig, Edward A. Stone, and Eric M. White

43 Introduction

43 Changes in Land Values

45 Ecosystem Service Markets

52 Examples of Land Value Projections Using the FASOM-GHG 

 Modeling System

53 Modeling Changes From Climate Change

55 Modeling Changes in Land Values With Policies and Carbon Markets

58 Evidence of Carbon Markets

61 Land Value Data Needs
65 Conclusions and Research Needs

67 English Equivalents

67 References

73 Chapter 3: Socioeconomic Impacts of Climate Change on 

 Rural Communities in the United States

 Pankaj Lal, Janaki Alavalapati, and D. Evan Mercer

73 Introduction

75 Vulnerability of Rural Communities

82 Impacts on Rural Communities

83 Social Impacts

87 Economic Impacts

104 Conclusions

106 Acknowledgments

106 Metric Equivalents

106 Literature Cited

119 Chapter 4: Competitiveness of Carbon Offset Projects on 

 Nonindustrial Private Forest Lands in the United States

 D. Evan Mercer, Pankaj Lal, and Janaki Alavalapati

119 Introduction

121 Forestry-Based Carbon Offset Projects

123 Factors Influencing Forestry Offset Projects

125 Management Practices

126 Product Longevity

128 Opportunity Cost of Land and Discount Rates

130 Price Effects of Forest and Agricultural Products

131 Transaction Costs

132 Cost Comparison of Offset Projects

132 Forest Offsets

134 Agriculture Offsets

137 Capture and Storage/Destruction of GHG Emissions

137 Offset Cost Competitiveness

139 Policy Environment

139 Cap-and-Trade Initiatives

140 Incentive-Based Policies
142 Support Programs

143 Effectiveness of Forest Incentives

143 Impacts of Potential Offset Rules and Criteria

144 Additionality and Baseline

145 Permanence of Offsets

146 Leakage

146 Stackability

149 Summary and Conclusions

151 English Equivalents

152 Literature Cited

161 Glossary

165 Appendix 1: Eligible Offset Projects Listed in 2010 American 

 Power Act (Kerry-Lieberman)

167 Appendix 2: Costs of Removing Atmospheric CO2 Through 

 Forest Offset Projects

1

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Anita T. Morzillo and Ralph J. Alig 

Introduction

Climate change is affecting environmental conditions for people and wildlife. As a 

result of changing environmental conditions, climate change affects wildlife species 

both directly and indirectly. Current policies influence the area and distribution 

of potential wildlife habitat. In response to climate change, policies adopted to 

influence the management of ecosystems are expected also to affect the wildlife 

habitat and populations that depend on these ecosystems (IPCC 2007, MEA 2005). 

Many researchers have explored potential impacts of climate change on wildlife 

populations and habitats, as well as shifts in vegetation communities resulting from 

projected climate change. The focus of this paper is to provide a broad-scale review 

and synthesis of existing knowledge about potential direct and indirect impacts of 

climate change on terrestrial wildlife and wildlife habitat within a systems analysis 

context. To do this, we rely on existing research that has suggested climate-influenced impacts on particular species and their habitats. Although the readers of this 

document may have primary interest in U.S. policy, we use examples from around 

the world to illustrate phenomena that have potential to be relevant to wildlife 

within the United States.

Many studies have addressed observed and projected changes in land cover 

and land use as a result of climate change (e.g., Backlund et al. 2008, Harsch et al. 

2009, Iverson et al. 2008, Shafer et al. 2001, White et al. 2010). For our purposes, 

we define land cover as the observed biophysical cover of the Earth’s surface (e.g., 

oak-hickory forest, grassland). In contrast, land use is the means by which land is 

used by humans (e.g., protected areas, timberland, agriculture). Research focused 

on the impacts of climate change on wildlife, such as those discussed in this paper, 

expand on earlier studies focused on land cover and land use change to illustrate 

and project how organisms that depend on particular attributes of land cover and 

land use may respond to changes. Wildlife species depend on vegetation characteristics for cover (e.g., shelter from predators), reproduction (e.g., trees for denning 

and nesting), and food (e.g., pollen, seeds, and fruits). We describe direct ecological 

and behavioral responses of wildlife to climate change, such as geographical range 

shifts by species. Many studies have focused on location-specific case studies (e.g., 

Moritz et al. 2008) or shifts by individual or groups of organisms (e.g., Chen et al. 

2009), but others provide a comprehensive analysis across many species and locations (e.g., Hughes 2000, Lawler et al. 2009, Parmesan 2006, Thomas and Lennon 

1999). Although it is not our objective to quantitatively evaluate net change across 

Chapter 1: Climate Change Impacts on 

Wildlife and Wildlife Habitat 
2

GENERAL TECHNICAL REPORT PNW-GTR-837

all species, or provide an exhaustive review, we summarize existing literature by 

focusing on both spatial and temporal aspects of range shifts, and the biological 

effects of such shifts (Root et al. 2003). 

The next section illustrates impacts of climate change on wildlife habitat. Here 

we focus on impacts that ecosystem changes in vegetation characteristics and 

associated abiotic variation may have on the species that depend on them. Topographical landscape variation (e.g., continental drift and other geologically induced 

change) may be slow in many cases from a human perspective. However, other 

effects of abiotic factors and combined abiotic and biotic influences may be more 

apparent (e.g., Harsch et al. 2009). Habitat variation as a result of climate change is 

expected to affect individual species differently, based on life history characteristics 

and ability to adapt to changing habitat conditions. We describe impacts of climate 

change mitigation on wildlife habitat from mainly an economic perspective, such as 

decisions that landowners may make in response to climate change. For example, 

potential return from emerging carbon and bioenergy markets may affect landowner decisions about land management, which may affect availability of habitat 

for particular species. 

To integrate the first three parts of the paper, we describe and follow linkages 

between models for evaluating climate change and land use impacts on wildlife, 

including global circulation models, ecological process models, economic models, 

ecosystem services models (e.g., wildlife habitat), climate (or bioclimatic) envelope 

models, and attendant feedbacks, and critique the linkages to identify needs for 

better understanding of potential impacts. Finally, we suggest focal areas for future 

research to address climate change impacts, specifically the need to evaluate concurrent influences of climate change and land use on wildlife and wildlife habitat. 

Ecological and Behavioral Responses of 

Wildlife to Climate Change 

Adjusting to climate-influenced variation in resources they depend on is a 

challenge for wildlife. This variation may include changes in spatial distribution 

in food resources, timing of food resource availability, and differences in cover, 

ground moisture, and water requirements. 

Range Shifts

Many abiotic (e.g., physical barriers, climate) and biotic (e.g., competition, population dynamics, life history, genetics) factors individually, and in combination, affect 

the geographic distribution of species (Gaston 2003). Researchers are observing 

variation over space and time in species distributions that appear to be range shifts 
3

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

in response to climate change. Geographical range shifts may be latitudinal, which 

are defined as extinction of a species at the historically observed southern (in the 

Northern Hemisphere; northern in the Southern Hemisphere) boundary or net 

colonization by the species at the northern (or southern in Southern Hemisphere) 

boundary (Parmesan et al. 1999). Parmesan and Yohe (2003) completed a metaanalysis of 1,700 species to evaluate consistencies between recent biological trends 

in species range distributions and climate change predictions. For wildlife, this 

analysis included both timing of life history events (phenology) and distributional 

changes in taxa including insects and other invertebrates, fish, reptiles and amphibians, birds, and mammals. Globally, on average across all studies evaluated, northern and upper elevation boundaries are estimated to have shifted approximately 6 

km per decade toward the poles, which follows trends in climate models (Parmesan 

and Yohe 2003). The same authors suggested that changes in distributions of 

approximately 280 species followed a systematic trend in global cooling and warming periods since 1930. 

Besides changes along latitudinal gradients, geographic range shifts also may 

occur along elevation gradients. The same meta-analysis that suggested many range 

distributions to be shifting toward the poles also noted elevation shifts upward of 

approximately 6 m per decade (Parmesan and Yohe 2003). In Costa Rica, variation 

in sea surface temperatures is influencing forest mist frequency, which then affects 

vertebrate abundance along elevation gradients that cannot be attributed to other 

land uses (Pounds et al. 1999). From fixed plots, observations of breeding populations of species typically found in areas lower than approximately 1500 m have 

increased in frequency above 1540 m. For example, the formerly lowland-breeding 

keel-billed toucan (Ramphastos sulfuratus) now breeds among the cloud-forestbreeding quetzals (Pharomachrus moccino) (Pounds et al. 1999). Moths (Chen et 

al. 2009) and butterflies also have exhibited elevational changes in distribution. 

Ranges of populations of Edith’s checkerspot (Euphydryas editha) and sachem 

skipper butterfly (Atalopedes campestris) in North America (Crozier 2003, 2004; 

Parmesan 1996), as well as Apollo butterfly (Parnassius apollo) and other species 

(Descimon et al. 2005, Parmesan 1996, Parmesan and Yohe 2003, Wilson et al. 

2005), have shifted upward along elevational gradients as compared to historical 

ranges. 

Similar upward-elevation trends have been observed with high-altitudeassociated mammals. Several pika (Ochotona princeps) populations across the 

Western United States are suspected to have gone extinct since first observed in the 

1930s (Beever et al. 2003). In a followup evaluation, Parmesan and Galbraith (2004) 

suggested that extinct populations had occurred at significantly lower elevations 
4

GENERAL TECHNICAL REPORT PNW-GTR-837

than surviving populations. A re-creation of Grinnell’s survey of a 3000-m elevation gradient in Yosemite National Park also suggested elevational shifts among 

mammal communities. For example, approximately half of high-elevation species, 

including the alpine chipmunk (Tamias alpinus) and Belding’s ground squirrel 

(Spermophilus beldingi), experienced a narrowing of elevational limits (decreased 

range sizes), whereas approximately half of low-elevation species (e.g., pocket 

mouse [Chaetodippus californicus] expanded their upper elevation maximum 

(Moritz et al. 2008). 

Several long-term studies across broader taxonomic groups also report range 

shift dynamics. For example, in Britain, the northern margins of many breeding 

bird species distributions have moved north by 19 km during a 20-year period 

(Thomas and Lennon 1999). Similar trends have been reported for butterflies. 

Parmesan et al. (1999) observed that ranges of 22 out of 35 (63 percent) species 

of nonmigrating European butterflies have shifted north by 35 to 240 km since 

1900. Comparable shifts have been reported for North America and for different 

habitat types (NABCI 2010) (fig. 1-1). According to the National Audubon 

Society, Christmas Bird Count results suggest that more than half (170 out of 

305) of commonly observed species are shifting their wintering ranges northward 

by an average of 35 miles (NABCI 2009, 2010; The Audubon Society 2010) 

(fig. 1-2). These species include the purple finch (Carpodacus purpureus), wild 

Climate-induced microhabitat changes that affect small mammal and bird populations may also 

affect predators that depend on such populations for food. 

D. Canning
5

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Figure 1-1—Forty-year (1960s–2006) latitudinal distance moved north by North American bird 

species across different land use types as observed from Christmas Bird Count data. The greatest 

shifts were observed among species associated with urban and suburban habitats. Adapted from 

NABCI 2010.

Figure 1-2—As the temperature warms across North America, the winter habitat of many birds is 

shifting northward. Dotted lines indicate approximate changes in wintering locations of 20 bird 

species. Adapted from The Associated Press and Audubon Society 2010.
6

GENERAL TECHNICAL REPORT PNW-GTR-837

turkey (Meleagris gallopavo), marbled murrelet (Brachyramphus marmoratus), 

boreal chickadee (Poecile hudsonicus), and house finch (Carpodacus mexicanus) 

(The Audubon Society 2010). The U.S. Committee of the North American Bird 

Conservation Initiative has reported that American robins (Turdus migratorius), 

tree swallows (Tachycineta bicolor), red-winged blackbirds (Agelaius phoeniceus), 

and eastern bluebirds (Sialia sialis) are breeding at least 1 week earlier than 30 

years ago (NABCI 2009). In contrast, populations of other species, including the 

burrowing owl (Athene cunicularia) and eastern and western meadowlark (Sturnella 

magna and S. neglecta, respectively), may continue to decline as climate affects 

habitat quality, and lack of adequate habitat limits the ability of species to move 

northward (The Audubon Society 2010). 

Temporal range shifts also exist in response to climate change. Temporal 

changes may be gradual, and indicate wildlife response to individual climate 

variables, such as variation in spring temperature. For example, the North Atlantic 

Oscillation may affect arrival dates for migratory bird species in New England 

(Wilson 2007). Although temporal cyclical climate phenomena may be attributed 

to behavior, other research has suggested noncyclical temporal changes. In Massachusetts, between 1970 and 2002, a 2 °C increase in average temperatures was 

accompanied by earlier timing of phenological events for 22 species including wood 

duck (Aix sponsa), ruby-throated hummingbird (Archilochus colubris), ovenbird 

(Seiurus aurocapillus), and chipping sparrow (Spizella passerine) (Ledneva et al. 

2004). Similar results were observed for birds during a 61-year period in Wisconsin 

(Bradley et al. 1999), and particularly among short-distance migrants in Poland 

(Tryjanowski et al. 2002). In central New York, four species of frogs are calling 10 

to 13 days earlier than observed during the early 20th century, which may signal a 

potential shift toward earlier reproductive behavior (Gibbs and Breisch 2001). It also 

is suspected that a combination of temporal climate variation affecting ultraviolet 

radiation and environmental contamination may contribute to declines in amphibian populations (Beebee and Griffiths 2005, Blaustein et al. 2001). 

Environmental Processes Affecting Migration

Wildlife also may be affected by the interaction of spatial and temporal characteristics of environmental processes. Discussion of climate change often focuses on 

impacts on ecological systems. However, the interaction between ecological and 

abiotic systems characteristics may hinder a species’ ability to adapt to ecological 

changes. Deviation of concurrent timing of abiotic and biotic environmental events 

may result in species vulnerability. Annual photoperiod (i.e., sunlight per 24 hours) 

cycles are relatively constant, and not related to climatic shifts. In other words, the 
7

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

same date each year has approximately the same amount of sunlight regardless 

of climatic events. Thus, innate behaviors triggered by length of daylight period 

(Gwinner 1996) may not be affected by climate change. Migratory birds often 

depend on changes in photoperiod, temperature, and wind to determine timing of 

spring and fall migrations (Gwinner 1996, Price and Glick 2002). Similarly, migratory butterflies use sensors in their antennae to determine timing for migration 

based on photoperiod (Kyriacou 2010). In short, particular ecological and behavioral events have become synchronized with photoperiod characteristics. Consequentially, species that migrate based on photoperiod characteristics have become 

adapted to using resources in winter and summer ranges that are available when a 

particular species arrives in the respective range. As ecological communities adapt 

to climate change, species behavior based on photoperiod likely will become out 

of synch with ecosystem processes in different parts of an organism’s range. It is 

unknown whether wildlife will be able to adapt to asynchrony between photoperiod 

and ecosystem processes.

Although the preceding paragraphs have focused mainly on flying migratory 

species, it is important to note that climate change also impacts nonflying migrants. 

Many factors influence the ability of wildlife to migrate over land, including 

variation in forage quantity and quality, snow depth, ability to use particular 

(“traditional”) areas and migration routes, and water availability (Harris et al. 

2009). Long-term changes in any one of these properties may affect migration 

success. For example, forage moisture and access to water are important factors in 

resource quality for American pronghorn (Antilocapra americana) and influences 

migration behavior of this species (Harris et al. 2009). Plant biomass, including 

protein content, affects caribou selection of calving grounds and potential 

nutritional intake of both females and calves (Griffith et al. 2002). In Alaska and 

Canada, changing plant phenology has resulted in earlier visits to calving grounds 

by caribou (Rangifer tarandus) since the mid-1990s, and misplacement of forage 

availability combined with predation risk could result in a decrease in caribou herd 

size (Griffith et al. 2002). In support of such speculation, results of a long-term 

study (1988–2003) of caribou on the Québec-Labrador peninsula suggest that both 

climate and habitat variables have affected annual spatial and temporal movement 

patterns of and habitat use by caribou (Sharma et al. 2009). Regional corridor 

networks have been suggested as a means to maintain migration routes within 

changing landscapes (Berger 2004), but such efforts require a large amount of 

societal cooperation at the local level. 

From a societal perspective, presence of mass-migrating species plays an 

important role in local and regional economies. For example, wildlife-related 
8

GENERAL TECHNICAL REPORT PNW-GTR-837

tourism is an important industry in Africa, and absence of mass-migrating 

wildlife (e.g., wildebeests [Connochaetes taurinus] and the predators that rely 

on them) could result in great impacts to regional tourism economies. Similarly, 

caribou hunting in the Arctic is not only an economic activity, but also a source of 

sustenance for native societies (Berkes and Jolly 2001, Sharma et al. 2009). Loss of 

the aforementioned economic sectors may force dependent locals to switch to more 

traditional yet environmentally intensive practices such as livestock and agriculture 

(Harris et al. 2009). In contrast, concern about migration routes could affect 

regional economic activity such as development. For example, various types of 

development (e.g., energy development) may affect migration routes and potentially 

the health of migratory wildlife populations such as mule deer (Odocoileus 

hemionus) and pronghorn (Sawyer et al. 2002, 2007), and uncertainty exists about 

how climate change may affect such migration routes and related relationships with 

particular land uses (Harris et al. 2009). Ultimately, tradeoffs exist between human 

resource use and mass-migrating species, particularly if wildlife show fidelity to 

particular migratory routes and locations that may be affected by climate change. 

Functional Roles Within Ecosystems

There are important implications of climate change on wildlife beyond survival of 

the species themselves, such that displacement of land-migrating species as well as 

other wildlife may affect the greater ecosystem. For example, large ungulates are 

critical for driving ecosystem functions such as enriching grassland production and 

replenishing soil nutrients (Harris et al. 2009). In Africa, browsing by ungulates 

plays an important role in maintaining cooperative relationships between nectarfeeding ants and Acacia spp. trees by limiting the presence of antagonistic ant 

species (Palmer et al. 2008). However, climate-induced ecosystem changes are 

not limited to effects on larger ungulates, but may extend to other prey species. 

Increasingly warm early springs in Norway may be influencing humidity and snow 

characteristics that affect cyclical population irruptions of lemmings (Lemmus 

lemmus) (Kausrud et al. 2008). It is speculated that loss of lemming population 

irruptions already may be having profound impacts on nutrient cycling, functioning 

of plant groups, and predator populations (e.g., arctic fox [Alopex lagopus] and 

snowy owl [Bubo scandiacus]) (Kausrud et al. 2008). In northern New York, 

projected changes in spring runoff may affect distribution of beaver (Castor 

canadensis) populations and associated impounded wetlands, the presence of 

which is depended upon by mink frogs (Rana septentrionalis) for mating and 

reproduction (Popescu and Gibbs 2009). Ultimately, the climate-related impacts on 

one species may have cascading effects on other species within an ecosystem. 
9

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Researchers have not reached consensus on which wildlife species are most 

vulnerable to the effects of climate change. Some suggest that long-distance 

migratory species may be particularly vulnerable because of their dependence on 

the interaction between abiotic cues and ecological resources, as described in this 

section (NABCI 2009, 2010; Price and Glick 2002; Price and Root 2005; Robinson 

et al. 2009). However, nonmigrating leaf-feeding insects and other herbivores also 

can exhibit phenological synchrony with host plants (van Asch and Visser 2007). 

Others suggest that species with limited climatic ranges (e.g., alpine species such 

as pikas) or restricted reproductive strategies or physiologies may be most at risk 

(Issac 2009, Tewksbury et al. 2008). For example, many small mammals such 

as mice (e.g., Peromyscus spp.) are capable of breeding multiple times per year, 

whereas many larger mammals (e.g., black bears, Ursus americanus) reproduce on 

an annual cycle only. Regardless of vulnerability, researchers speculate that climate 

change may affect morphological and genetic species traits (Issac 2009, Root et al. 

2003), which has potential to affect species-habitat relationships. There is a great 

need to better understand the spatial and temporal adjustments that wildlife will 

have to make to climate-induced habitat changes (described in the next section), 

which ultimately is a concern for all wildlife. 

No consensus exists on which wildlife species are most vulnerable to effects of climate change.

Ralph Alig
10

GENERAL TECHNICAL REPORT PNW-GTR-837

Impacts of Climate Change on Wildlife Habitat

The previous section highlighted ecological and behavioral responses of wildlife 

to climate change. However, climate change impacts to wildlife also may include 

disturbances that drive changes in wildlife habitat. Examples of climate-influenced 

changes that may indirectly affect wildlife are variation in vegetation community 

composition or other ecosystem components, as well as pest outbreaks and other 

disturbances such as wildfire. Some species may be relatively more sensitive to 

overall habitat change than other species. For example, amphibians have received 

a large amount of recent attention in that the presence of additive habitat-related 

elements (e.g., chytrid fungus [Batrachochytrium dendrobatidis]) has had potentially major impacts on their populations. Other factors that may affect habitat, such 

as the interaction between land use and climate change, are only now becoming a 

focus of research. 

Relationships Between Vegetation and Wildlife

Vegetation type, often identified as a main characteristic of land cover (e.g., 

evergreen forest), is an important predictor of species occurrence. Temperature 

(Körner 2007) and interaction between position and temperature (Körner and 

Paulsen 2004) often are considered primary drivers of plant species distribution, 

although other factors also may be influential, such as precipitation, disturbance, 

and community interactions (Harsch et al. 2009). Globally, many researchers have 

suggested that plant communities are shifting toward the poles, upward in elevation, 

and blooming earlier in the season, any of which likely will affect the wildlife that 

depend on them. 

Research has identified relationships between treeline range shifts and climate 

variables. In a meta-analysis, Harsch et al. (2009) evaluated a global data set of 166 

sites across more than 100 studies for which treeline dynamics since 1900 could 

be classified; most sites were in North America or Europe. The authors observed 

recruitment of treelines at increasingly higher altitudes or latitudinal advancement of treelines at 87 out of 166 sites, which corresponded with sites that also 

exhibited warming during the winter months. Treelines with diffuse form (gradual 

merge between tree communities or to treeless areas) were strongly associated 

with changes in annual and winter temperatures. In contrast, shift of abrupt and 

krummholz (stunted) treelines were more associated with winter warming and were 

potentially affected by other constraints on tree survival (e.g., wind, ice) (Harsch 

2009). At a regional level, 78 percent of 542 leafing, flowering, and fruiting records 

across 21 European countries were observed to have advanced in latitude since 

1971 (Menzel et al. 2006). Along with trees, herbs, and shrubs, even symbiotic 
11

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

organismal groups such as lichens are susceptible to range shifts that would be 

projected by climate change (Parmesan and Yohe 2003). 

Vegetation range shifts that may affect the distribution of habitat also may be 

influenced by interactions between climatic variables and disturbance. In New 

Mexico, Allen and Breshears (1998) reported a ≥2-km shift in ponderosa pine 

(Pinus ponderosa Dougl. ex Laws.) and piñon-juniper woodland over a 5-year 

period, a result of several interrelated climate-influenced events. In the same study, 

a combination of drought, fire suppression, and a bark beetle outbreak may have 

been factors in a concurrent expansion of the piñon-juniper community. Piñonjuniper eventually may have competed with the ponderosa pines for limited water, 

which resulted in enhanced susceptibility of the ponderosa pines to bark beetle 

attack and related mortality (Allen and Breshears 1998). Ultimately, climate change 

impacts on plant communities could affect temporal aspects of resource use and 

consumption by dependent wildlife species, and survivorship of dependent wildlife 

populations. 

Integration of climate model simulations with bioclimatic variables suggest 

shifts in vegetation taxa to continue with anticipated changes in climate. Shafer et 

al. (2001) suggested that projected range changes for particular tree and other species may be multidirectional, and could result in range fragmentation, both of which 

may affect associated wildlife. In an analysis by Iverson et al. (2008), a simulation 

modeling approach was used to project suitable habitat for 134 tree species across 

the Eastern United States. Results suggest that approximately 66 species would gain 

suitable habitat (e.g., southern oaks and pines), whereas 54 species would lose at 

least 10 percent of their current suitable habitat (e.g., spruce-fir). Range shifts were 

predicted to move up to several hundred miles in a generally northeastern direction. 

From the same study, the authors concluded that proactive means to lower greenhouse gases may limit range disruptions (Iverson et al. 2008). 

Disturbance

It is expected that climate change will affect the frequency, extent, duration, and 

severity of disturbances, but a challenge exists in projecting specific outcomes 

(Dale et al. 2000). Individual disturbances may affect landscape structure or 

composition, which in turn affect wildlife habitat (Inkley et al. 2004). Even though 

disturbance is part of the natural landscape, climate-influenced variation of 

disturbance occurrence may affect the ability of wildlife to respond and adapt to 

individual disturbances. 

Insect infestations within forest ecosystems is one type of disturbance that 

is believed to be affected by climate change. It has been speculated that warmer 
12

GENERAL TECHNICAL REPORT PNW-GTR-837

winters and summers and reduced summer precipitation have facilitated mountain 

pine beetle (Dendroctonus ponderosae) outbreaks in western Canada (Kurz et al. 

2008) and the expansion of this pathogen’s range into previously uninfected forests 

and different forest communities (Logan and Powell 2001). In Alaska, a combination of higher than average summer temperatures, increased winter survival of the 

spruce beetle pathogen, shortened pathogen maturation rate (2 years to 1 year), 

regional drought, and an adequate number of spruce trees all were likely contributors to a massive spruce beetle outbreak during the 1990s (Berg et al. 2006). The 

same authors suggested that continued warming trends may result in beetle populations being great enough to infect trees as soon as trees are mature enough to be 

susceptible to the insects. Insect infestations and resulting tree mortality have been 

estimated to cause as much as twice the diminution to forests as other disturbances 

in the boreal forests of Canada (Volney and Flemming 2000). As such, climateinduced projected increases in infestation occurrence and range (Williams and 

Liebhold 2002) are expected to have potential to cause changes to not only wildlife 

habitat, but also other forest processes such as carbon sequestration (Volney and 

Flemming 2000).

Changes in both climate and habitat variables, such as those that affect forage moisture and water 

availability, have potential to affect migration behavior of pronghorn. 

Anita Morzillo
13

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

The number and severity of forest fires are expected to be affected by climate 

change. Flannigan et al. (2000) used two general circulation climate models to 

project climatic effects on forest fire severity. Forest fire severity was projected 

to increase between 10 and 50 percent for most of the United States, but details of 

the projections differed between climate models. Integrating projections from both 

climate models, the same authors suggested a majority of increases in fire severity may be expected in Alaska and the Southeastern United States, whereas other 

climate variables may result in lower expected fire severity in other locations (e.g., 

northern Great Plains). It is important to note that many locally affected variables 

(e.g., fuel load and type) were not included in these projections, and inclusion of 

them may lead to potential forecasting variation at a local level (Flannigan et al. 

2000). Ultimately, fire occurrence likely will affect community composition and 

result in variation in habitat available for particular wildlife species. 

Climate-affected disturbance also may influence the ability of exotic species to 

invade and potentially outcompete native vegetation. In southeastern Texas, Harcombe et al. (1998) suggested that frequency and intensity of natural disasters, such 

as hurricanes, floods, and droughts, may have more profound effects on changes 

to the vegetation community than climate-induced changes on individual species 

growth rates. From the same study, results of long-term observation indicate that 

presence of Chinese tallow (Triadica sebifera (L.) Small.) or Sapium sebiferum (L.) 

Roxb.), which establishes itself in gaps within the forest, has increased in population 

size by a factor of 30 between 1981 and 1995. This range expansion may be attributed to the fast-growing Chinese tallow outcompeting other species (Harcombe et 

al. 1998), a process that is expected to continue to spread as winter freeze extent 

and severity shift northward. If the frequency of natural large-scale disaster disturbances increases the frequency of forest disturbance, then fast-growing exotics such 

as Chinese tallow may interrupt establishment of native forest communities and 

reduce regeneration of plant species depended upon by wildlife. 

Microclimate

Climate-related impacts present special conservation challenges for particularly 

abiotic-sensitive species such as amphibians (Carey and Alexander 2003), which 

may serve as indicators of environmental stress (Blaustein and Wake 1995). As 

noted in the preceding section, such species are known to respond to stresses initiated by regular oscillations such as El Niño (Pounds and Crump 1994). For example, an increase in amount of ultraviolet radiation as a result of climate variation has 

been observed to affect survivorship of amphibian eggs and embryos (Kiesecker et 

al. 2001). Amphibians also are susceptible to changes in water availability, which 
14

GENERAL TECHNICAL REPORT PNW-GTR-837

has been associated with warming-influenced dry periods (Pounds et al. 1999). 

Consequently, progressive climate-influenced factors may be additive when other 

stressors act on amphibian populations simultaneously. For example, a combination 

of ultraviolet radiation and toxins (e.g., pesticides) may enhance the potential of 

each to contribute to amphibian mortality (Blaustein et al. 2003) (fig. 1-3). Some 

researchers have suggested that climate change may play a role in creating better 

growing conditions for chytrid fungus, which has been attributed to the decline of 

mass extinctions of amphibians (Pounds et al. 2006). However, others argue that the 

causal link between chytrid fungus and global warming is not well supported at this 

time (Rohr et al. 2008). In fact, the long-term observation of declines in amphibian 

and lizard species in Costa Rica suggest that the chytrid fungus, which is specific 

to amphibians, may be an additive factor of mortality in addition to the greater 

potential threat of climate change (Wake 2007). In the same study, the authors suggested that trees are retaining leaves longer, and decomposition rates may be faster, 

both of which decrease potential refuge for wildlife on the forest floor and decrease 

an important environmental component for amphibians and reptiles. However, 

Wake (2007) suggested the need to test such inferences further. 

Interaction Between Climate Change and Land Use

Climate change impacts also may be enhanced by concurrent human-caused drivers 

of habitat change. Many researchers have evaluated direct effects of disturbance 

on particular species resulting from land use. For example, Laliberté et al. (2010) 

observed an inverse relationship between land use intensification and both diversity 

among traits representing plant function (e.g., leaf size, nutrient uptake strategy) 

and response to disturbance (e.g., resprouting ability, age of reproduction), which 

suggests that land use intensification may decrease the resiliency (ability to successfully respond to stressors) of the overall affected ecosystem. If plant resiliency 

decreases, then it is possible that dependent wildlife will be increasingly vulnerable 

during disturbances. 

Ultimately, however, few studies evaluate concurrent interactions between 

climate change and land use and resulting effects on wildlife habitat. Warren et 

al. (2001) observed that a majority of 46 British butterfly species that may have 

responded positively, via range expansion, to climate-induced changes suffered 

negative responses to habitat loss from development. Ultimately, habitat generalists 

adapted more successfully to both disturbances than habitat specialists (Warren 

et al. 2001). In another example, bird community composition change on Cape 

Cod since 1930 was suggested to be attributed more to global warming than to 
15

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

urbanization (Valiela and Bowen 2003). From the same study, observations included 

increase in southern-associated species across all local habitat types, and decrease 

in northern-associated species since 1970. Although changes in northern-associated 

species since 1970 may be attributed to land cover change (increase in edge habitat 

from urbanization), collective changes were more associated with temperature 

increases than land use. McAlpine et al. (2009) argued the need to evaluate interactions between climate and land cover, and the importance of vegetation in maintenance of regional climatic conditions. Focusing on the Australian continent, the 

authors suggest that historical clearing for agriculture (approximately 15 percent of 

Figure 1-3—The simultaneous interactions between biotic and abiotic factors or stressors affecting 

amphibians. Either ultraviolet-B (UV-B) radiation or contaminants alone may affect mortality. For 

example, UV-B may depress the immune system, leaving species more susceptible to infection. 

Contaminants and UV-B radiation interacting together could heighten lethal effects. Ultimately, 

individual stressors or combinations of stressors may lead to declines in amphibian populations. 

Adapted from Blaustein et al. 2003. 

Stressors

Ultraviolet-B Contaminants

Population

declines

Immune system

depression

Elevated rates

of infection

Increased mortality

of individuals
16

GENERAL TECHNICAL REPORT PNW-GTR-837

the continent) and other land use changes that resulted in removal of native vegetation not only reduced ecosystem resilience but also may have contributed to climate 

changes across the continent. Such drastic change may have drastic implications 

for wildlife at the continental level, but this assertion has not been tested. Although 

beyond the scope of this paper, it is speculated that both climate change and land 

use change may have profound effects on sediment load in streams within the Alps, 

which in turn may affect brown trout (Salmo trutta) habitat (Scheurer et al. 2009). 

In the end, potential interactions between climate change and land use effects on 

wildlife may suggest a need to consider both factors in planning processes and 

mitigation policy (McAlpine et al. 2009). 

Impacts of Climate Change Mitigation on 

Wildlife Habitat

As landscape conditions respond to climate change, resource managers will be 

forced to respond to the new landscape conditions as well as any related climate 

change policy. Mitigation for climate change, defined as policies or actions that 

seek to decrease the impact of climate change, likely will influence decisions about 

land use. In turn, wildlife habitat likely will be affected by decisions about land use 

such as afforestation, carbon and bioenergy markets, and incentive programs for 

landowners. Interactions between mitigation and adaptation activities also will play 

a role, although very little currently is known about such interactions and will not 

be discussed further here. 

Afforestation

Policies supporting afforestation may affect amount of habitat available for wildlife, 

as well as habitat quality. Increased area and quality of wildlife habitat, particularly 

for forest species, is a possible co-benefit of conversion of land use from row-crop 

agriculture to forest land. Matthews et al. (2002) used econometric models of land 

use to simulate the response of landowners to planting trees on land currently used 

for agriculture in South Carolina, Maine, and southern Wisconsin. These models 

then were used in combination with breeding bird survey data to evaluate responses 

of forest and farmland bird populations. For a scenario of 10-percent conversion of 

agriculture for carbon sequestration, projected land conversion between agriculture 

and forest differed in amount from state to state. Following these projected changes 

in land use, results from Matthews et al. (2002) also suggested overall losses of 

farmland birds, and only small increases in forest bird species. However, from the 

same study, overall total bird populations were projected to decrease between 1 

and 3 percent across all three states. The authors suspected that these differences 
17

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

were effects of overlaps between econometric predictions of locations converted and 

spatial patterns of bird species richness. Ultimately, tradeoffs between biodiversity 

and economic benefits will need to be evaluated by policymakers and landowners. 

Other research has evaluated the potential benefits for afforestation, such as 

conservation of wildlife habitat, which may be derived from carbon sequestration 

programs in the upper Midwestern United States (Feng et al. 2007, Plantinga and 

Wu 2003). Decreased soil erosion, nitrogen pollution, and atrazine pollution were 

among additional benefits that could be derived from the afforestation program, in 

addition to improvement of wildlife habitat (Plantinga and Wu 2003). From the same 

study, the authors suggested that overall benefits derived from the program would 

be the same order of magnitude as the costs associated with the carbon sequestration 

program. Feng et al. (2007) expanded earlier work by suggesting 

that particular benefits and transfers of them may vary geographically. 

Although afforestation may offer a means to provide additional habitat for wildlife, particularly forest species, unintended consequences that affect other ecosystem 

components are possible. In Ireland, policy was initiated to double the percentage of 

forest land by 2035 (Allen and Chapman 2001). From the same study, thus far, afforestation efforts and resulting update and storage (by trees and soil) of water have 

led to a reduction in precipitation runoff by as much as 20 percent. However, new 

Expanded afforestation as part of climate change mitigation could provide additional habitat 

for wildlife.

Gary Wilson, Natural Resources and Conservation Service
18

GENERAL TECHNICAL REPORT PNW-GTR-837

forestry operations have the potential to enhance risk of flooding within the area. 

In addition, a slower rate of groundwater recharge occurred, along with concerns 

about water quality (Allen and Chapman 2001). As another example, Thompson 

et al. (2009) suggested that afforestation efforts may be a factor in absorption of 

more solar radiation by forests and result in local warming temperatures. This local 

warming may neutralize or counter efforts to offset climate change by afforestation 

(Thompson et al. 2009). As such, the authors suggested a geographically targeted 

approach that seeks to increase forest land in locations naturally occupied by 

forests. 

Carbon and Bioenergy Markets

The emergence of natural resource markets, such as for carbon and bioenergy, may 

result in changes for wildlife habitat. Ultimately, however, negative impacts of 

market-associated activities to some species likely will result in positive impacts 

to others. From an economic perspective, participating landowners may seek to 

maximize net financial returns from land management activities. For example, 

because older trees typically can store more carbon, some landowner decisions 

in response to carbon markets may include longer rotation times between timber 

harvests (White et al. 2010). An increase in rotation times between forest harvests 

could result in a decrease in habitat for early- to mid-succession wildlife species. At 

the same time, longer rotation times also may be beneficial for species that prefer 

relatively older growth forest habitat. Likewise, a decrease in number of timber 

harvests over time may result in decreased forest fragmentation. 

Emergence of bioenergy markets also may result in both positive and negative 

impacts to wildlife habitat. Fargione et al. (2009) suggested that impacts from biofuels production run on a continuum between low and high wildlife habitat benefits 

(table 1-1). An example from the continuum suggests that cropland may hold less 

potential benefit for wildlife than diverse native habitats. Plant community research 

supports the notion that greater plant diversity is directly related to community productivity (Spehn et al. 2005, Tilman et al. 2001) and carbon storage (Tilman et al. 

2001), and that limited diversity can affect other nonplant species and trophic levels 

within the ecosystem (Knops et al. 1999). Other research speculates that biomass 

feedstock may have a greater negative impact on wildlife if planted in marginal 

cropland than if planted within its respective geographic range with associated 

wildlife species that depend on it as a habitat resource (Fargione et al. 2009). 

Although positive and negative effects of biofuels feedstock production on 

wildlife habitat have been identified conceptually (Bies 2006), research results 

are starting to emerge that focus on site-specific examples. Walter et al. (2009) 
19

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

evaluated impacts of conversion of cropland to native grassland, forest land, and 

aquatic vegetation on white-tailed deer (Odocoileus virginianus) within the DeSoto 

National Wildlife Refuge in eastern Nebraska. During the study, cropland (corn, 

soybeans, sorghum, alfalfa, and wheat-clover mix) was reduced by 44 percent 

between 1991 and 2004. Changes in plant communities did not affect overall 

landscape use by deer, but deer did shift home ranges to access remaining cropland 

(Walter et al. 2009). The authors suggested that such home range shifting may 

influence disease transmission rates as a result of new interactions between deer 

social groups (Walter et al. 2009). 

Incentive Programs for Landowners

There are many means by which private landowners may derive benefits from their 

land while managing land for wildlife habitat. For example, hunting leases may 

provide forest-land owners extra income while also promoting biodiversity (Johnson 

1995). Researchers also have assessed economic benefits of landowners adopting 

“green” practices, such as conservation tillage (Kurkalova et al. 2006). More 

broadly and formally, incentive programs may serve as a vehicle to entice private 

landowners to manage land in ways that are beneficial for habitat of particular 

wildlife species. For example, incentives created by the U.S. Department of 

Agriculture Conservation Reserve Program (CRP) have influenced availability of 

wildlife habitat. Establishment of more than 985,000 acres (398 615 ha) of 

grasslands coincided with a large increase in Henslow’s sparrow (Ammodramus 

henslowii) populations in Illinois (Herkert 2007). Similarly, Niemuth et al. (2007) 

projected that loss of CRP lands would result in large declines in grassland bird 

populations among the prairie pothole region of North and South Dakota. Other 

Table 1-1—Factors influencing wildlife habitat value and impacts on wildlife as related to bioenergy crops

Factors Better for wildlife Worse for wildlife

Habitat type Diverse native habitats Cropland

Plant diversity Diverse native grasslands/forests Exotic monocultures

Invasiveness of planted material Native, noninvasive Nonnative, invasive

Harvest and disturbance timing Late fall, early spring Breeding or nesting season

Harvest frequencies Single harvest not more than once per year Multiple harvests per year

Stubble height postharvest Tall stubble or regrowth Little or no stubble

Habitat refugia Unharvested area within field No unharvested area nearby

Landscape context Complex of habitat patches Isolated habitat patches

Type of land use replaced with biomass Marginal cropland Native habitat

Fertilizer use Minimal High

Pesticide use Minimal High

Soil erosion and sedimentation Perennial plants and low erosion Annual plants and high erosion

Adapted from Fargione et al. (2009).
20

GENERAL TECHNICAL REPORT PNW-GTR-837

incentive programs, such as the CRP Longleaf Pine Initiative, target a particular 

vegetation species. This program seeks to restore up to 250,000 acres (101 171 ha) 

of longleaf pine forests in nine Southern States, the benefit of which includes 

enhancement of native wildlife habitat (USDA 2006) and may also contribute to 

carbon sequestration. 

As another example, the Wetlands Reserve Program is a voluntary program 

managed by the USDA Natural Resources Conservation Service (NRCS) that offers 

landowners the opportunity to protect, restore, and enhance wetlands on their 

property (USDA NRCS 2010). The NRCS goal is to achieve the greatest wetland 

functions and values, including wildlife habitat, and the agency provides technical 

and financial support to help landowners with wetland restoration efforts. Thus, this 

program offers landowners an opportunity to establish long-term conservation and 

wildlife practices and protection. There are three enrollment options: (1) permanent 

easement, (2) 30-year easement, and (3) restoration cost-share agreements. The 

2008 Farm Bill changed the process for determining the easement value, increased 

the number of acres that could be enrolled, and set guidelines for payments and 

landownership tenure. By 2008, approximately 2 million acres (809 371 ha) nationwide were enrolled in the Wetlands Reserve Program. In the next chapter, Alig et 

al. discuss how such programs and climate change programs could influence value 

of ecosystems services and land values, thereby influencing landowner behavior 

regarding land conservation and climate change mitigation. 

It is suspected that private lands will play an important role in future biodiversity conservation. Two-thirds of all watersheds that are associated with privately 

owned forest land contain at least one at-risk species that is listed under the U.S. 

Endangered Species Act or ranked globally (Robles et al. 2008, Stein et al. 2010). 

The same studies show that many of the watersheds with the greatest number of 

species and highest density of each species are located in states within the southeast 

and within Appalachia, as well as along the Pacific coast. These locations also 

align with the highest proportion of estimated private forest conversion during the 

next 20 years (Robles et al. 2008). The authors suggested conservation easements 

and other incentive programs as potential vehicles to maintain biodiversity through 

landowner forest management programs. 

Besides forest management programs, other competing land uses such as 

agriculture may be targeted for maintenance of wildlife habitat and promotion of 

biodiversity. From an economic perspective, Feng et al. (2006) evaluated alternative approaches to conservation on the same parcel of land: retirement of land from 

production versus a change in farming practices on working land. The authors 

concluded that changes to working land were more cost-effective to the landowner 
21

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

if the objective is low levels of environmental benefits, such as a single benefit of 

erosion reduction, carbon sequestration, or wildlife habitat. However, land retirement was suggested to be more cost-effective if multiple benefits were sought, such 

as a combination of the aforementioned benefits (Feng et al. 2006). Plantinga (1996) 

also evaluated tradeoffs between keeping marginal farmland in production or conversion to forest to increase other environmental benefits, and suggested that many 

of the derived benefits from retiring agricultural land would result in enhancement 

of public goods (e.g., wildlife habitat, scenery, carbon sequestration, reduced soil 

erosion). However, Nelson et al. (2008) suggested that tradeoffs will exist between 

meeting objectives of policies designed to promote carbon sequestration and habitat 

conservation in heterogeneous landscapes. 

Impacts of climate change on timing of production of seasonal forage such as buds, insects, flowers, 

and berries may affect the ability of species such as the ptarmigan (Logopus spp.) to meet food 

resource needs, particularly during young-rearing periods. 

Anita Morzillo

Carbon markets were highlighted in the preceding section as related to mitigation that may result in changes to wildlife habitat. Building upon this notion, 

emerging carbon markets also may serve as an incentive program for promoting 

land management for wildlife habitat. Diaz et al. (2009) described compliance and 

voluntary markets as the two existing categories of carbon markets in the United 

States. Compliance markets function through regulatory organizations that limit 

the number of offset allowances (for the polluter) and credits (for offseting pollution activities) that are available throughout a marketplace. Commonly called 
22

GENERAL TECHNICAL REPORT PNW-GTR-837

cap-and-trade systems, such a system was established by the U.S. Environmental 

Protection Agency to reduce pollution as part of the Acid Rain Program (Diaz et al. 

2009). Essentially, pollution allowances not used by one organization may be sold to 

another organization that has not met emission reduction requirements. Voluntary 

markets, however, function as an altruistic mechanism for which participation is 

influenced by responsibility to society. As noted by Diaz et al. (2009), the two current types of voluntary carbon markets are the Chicago Climate Exchange and overthe-counter transactions. The Chicago Climate Exchange involves trading emission 

allowances and credits among member companies, whereas over-the-counter 

transactions are based on privately established contracts (Diaz et al. 2009). In terms 

of actual transactions, buyers of ecosystem services purchase carbon credits on the 

Chicago Climate Exchange to offset activities that emit greenhouse gases. In turn, 

the Chicago Climate Exchange buys credits from projects that offset the accumulation of greenhouse gases in the atmosphere. Many existing forestry programs that 

can enhance wildlife habitat also offset greenhouse gas emissions, and some are 

already generating income for forest-land owners. However, the total dollar amount 

of traded projects has been relatively limited, and carbon prices on the exchange in 

recent times have fallen below $1 per ton (see chapter 2). 

Regarding the future, there is substantial interest in identifying approaches 

and policies to minimize impacts of climate change on wildlife. Mawdsley et al. 

(2009) suggested strategies for wildlife management and biodiversity conservation 

as related to anticipated impacts of climate change. Strategies described include, 

among others, increasing size of protected areas, designing new natural areas and 

restoration sites, protecting land to increase connectivity, managing for ecosystem 

processes, reducing deforestation (e.g., Alig et al. 2010a), and enhancing the landscape to support movements by many species. Incorporating anticipated impacts of 

climate change into any land management plan and programs likely will be costly 

and difficult to implement across all involved organizations (Mawdsley et al. 2009). 

Any strategy is likely to require cooperation with private landowners. For example, 

increasing the size of a protected area likely will need to account for private land 

holdings beyond the protected area boundary. At the same time, policies that 

specifically target wildlife habitat may not maximize other benefits (Nelson et al. 

2008). At this time, there is a need to develop knowledge about which strategies 

may be feasible, ethical, and potentially successful. 
23

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Linkages of Climate Change Model Projections and 

Impacts From Global to Local Scales

Conceptually, the process of projecting adaptation to and mitigation in response 

to climate change impacts on wildlife requires multiple levels of analysis, and 

consideration of wildlife habitat at a unit of observation (or scale) appropriate for 

ecology of individual species and meaningful to a policy analysis. Thinking hierarchically and within a systems analysis perspective, a constellation of individual 

assessment tools may be used, such as global climate models, regional climate 

models, vegetation (e.g., forest inventory projection) and land cover and land use 

models, species-level bioclimatic envelope models, and site-specific analyses that 

may consider local abiotic and biotic characteristics (Hannah et al. 2002, Sulzman 

et al. 1995). All of these components also need to be able to model key feedbacks, 

both positive and negative. Because of constantly evolving technology, rapid 

information exchange, and broadening intellectual resources, the process of climate 

change research and projection modeling is extremely dynamic. We provide a brief 

review of assessment tools, but because of limited understanding about interactions 

between possible future adaptation and mitigation activities, that topic is left for 

future research and is not covered here. 

The constellation of assessment tools spans from global to local. Broadly at 

the global and limited regional levels, general circulation models (GCMs) simulate 

atmospheric characteristics (e.g., radiation, precipitation) and interactions between 

the atmosphere and land surface characteristics that affect climate (e.g., oceans, 

land topography) (Sulzman et al. 1995). General circulation models are used by 

climate policy authorities (IPCC 2007), and are updated continuously with development of new research tools (Pope et al. 2002). Variation in prediction exists among 

GCMs, as each differs based on parameterization characteristics such as resolution 

of analysis (Murphy et al. 2004). The GCMs are a typical starting place for projecting climate change effects on biodiversity because they are the only tools that can 

consider broad complex atmospheric processes and variability (Hannah et al. 2002, 

Murphy et al. 2004). 

To evaluate effects of climate change on biodiversity, GCMs often are used 

in tandem with land cover and land use models (Sulzman et al. 1995; see Peng 

and Wen (2006) for an overview of major types of forest simulation models). 

Ravenscroft et al. (2010) used the forest ecosystem model LANDIS-II to evaluate 

projected interactions of forest management and climate change in northern 

Minnesota. Results suggested that climate change may result in an overall 

decreased forest-tree diversity, and replacement of current forest composition 
24

GENERAL TECHNICAL REPORT PNW-GTR-837

by other dominant tree species. As another example, Cramer et al. (2001) used 

an ocean-atmospheric model coupled with a combination of six dynamic global 

vegetation models (DGVMs) to estimate impacts of climate change on vegetation 

carbon and water exchange and carbon storage. From this study, results differed 

among DGVMs, but all six models projected similar trends in decreasing carbon 

storage (sink) after 2050. The authors suggested the projected decrease in carbon 

storage to be partially a result of respiration among heterotrophs (species that do not 

photosynthesize their food), projected variation and reductions in precipitation, and 

deforestation (Cramer et al. 2001).

In addition to DGVMs, investigators also have used biogeochemistry and 

biogeographic models that simulate the gain, loss, and internal cycling of carbon, 

nutrients, and water. Biochemistry models project climate impacts on changes 

in temperature, precipitation, soil moisture, atmospheric carbon dioxide, and 

other climate-related factors, which can be examined for their influence on such 

processes as ecosystem productivity and carbon storage. Biogeographic models 

examine the influence of climate on the geographic distribution of plant species 

or plant types such as trees, grasses, and shrubs. For example, Alig et al. (2002) 

used scenarios representing combinations of climate projections from two GCMs 

(Canadian and Hadley), which in turn were fed into two ecological process 

models that are classified as biogeochemical models (Century and Terrestrial 

Ecosystem Models) (Irland et al. 2001). The latter models simulate the impacts of 

climate on forest productivity. Estimates of changes in forest productivity were 

fed into the FASOM-GHG1 economic optimization model (Alig et al. 2002). The 

modeling includes forest land converted to urban/developed (Alig et al. 2010b) 

and agricultural uses, as well as afforested land, with responses to different policy 

incentives such as carbon prices (Alig et al. 2010a). The authors presented a wide 

variety of outputs, including changes in forest age classes, forest types, vegetation 

carbon, and other attributes that may affect wildlife habitat. 

Climate change is expected to influence multiple sectors of the global economy. 

Agarwal et al. (2002) described methods for integrating land use change models 

into evaluations of impacts of climate change. As related to the forest sector, climate change effects on forests may consequently impact the forest product market 

(Perez-Garcia et al. 2002a, 2002b). Sohngen et al. (2001) projected that timber 

production will increase in low- and mid-latitude forests as a result of planting of 

short-rotation plantations, whereas higher latitude areas may experience a decrease 

in production based on planting of relatively long-rotation species. Irland et al. 

1

 Forest and Agricultural Sector Optimization Model–Greenhouse Gas.
25

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

(2001) suggested that climate change may affect not only forest products, but also 

nonmarket sectors of the forest economy such as forest-based outdoor recreation. 

The authors suggested that particular activities that rely on winter precipitation, 

such as downhill skiing, may be affected by climate change, but potential impacts 

are uncertain. 

Returning the focus to individual species and communities, another type 

of model used to evaluate impacts of climate change on wildlife are climate (or 

environmental or bioclimatic) envelope models. These models consider the distribution of a species as under an “envelope” of particular environmental conditions, and 

then evaluate how the location of the envelope may change under different climate 

change scenarios. Lawler et al. (2009) used a climate envelope approach coupled 

with 30 scenarios developed by use of an atmosphere-ocean general circulation 

model (AOGCM) to project changes in geographic ranges of 2,954 vertebrate 

species (amphibians, birds, and mammals) in the Western Hemisphere. The authors 

reported that climate change projections suggest varying amounts of species losses 

and gains across the Western Hemisphere. Ultimately, the same authors projected 

relatively large changes in local species communities (fig. 1-4). From the same 

study, it is expected that the greatest changes would be among amphibians and, 

at higher latitudes and in the Andes Mountains and Central America (including 

Climate change may affect both market and nonmarket segments of the forest sector. 

Ralph Alig
26

GENERAL TECHNICAL REPORT PNW-GTR-837

Mexico), all vertebrate groups (Lawler et al. 2009). For climate envelope models, 

some research suggests that occurrence of rare species may be more sensitive to 

stochastic events than more common species (Green et al. 2008), that spatial scale 

of analysis is of considerable importance (Pearson and Dawson 2003), and that 

results may differ based on species used in the analysis (Araujo et al. 2009, Beale 

et al. 2008). However, such models may be useful tools for policymakers for evaluating environmental indicators of interest. 

Several other modeling techniques may be used to link wildlife habitat information to climate change projections, and are mentioned only briefly here. For 

example, ecological niche models incorporate a computer algorithm and spatial 

data layers to estimate potential distribution of species. Peterson (2003) coupled 

ecological niche and climate model scenarios to evaluate the role of topography 

in affecting distribution of bird species in the western and central North America. 

As another example, Maxent models are used to integrate land cover and climaterelated variables to assess habitat suitability (Stabach et al. 2009). In addition, 

simulation models and tools that may be parameterized with wildlife life history 

information are used to evaluate effects of landscape change on individual species 

(Lookingbill et al. 2010, Schumaker et al. 2004). 

It is important to note, however, that any modeling approach to address global 

climate change has its limitations, and projections should be interpreted with 

caution. Even with efforts to obtain the best analytical results, to state implications 

of model projections across scales (global to local) requires the user to make 

Figure 1-4—Predictions of species composition turnover for (A) amphibians, (B) birds, and 

(C) mammals as a result of climate change. Such turnover may result in drastic differences in 

composition of local wildlife communities. Adapted from Lawler et al. 2009.
27

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

assumptions about how results of one model may connect to or integrate well with 

the parameters of another model. As noted earlier in this section, climate model 

projections can differ widely based on parameterization methods (Murphy et al. 

2004). It is also difficult to evaluate performance of climate models, as future 

environmental characteristics are unknown (Araújo et al. 2005, Thullier 2007). In 

fact, some researchers suggest a coarse-filter approach and other spatial analysis 

tools rather than coupling projection models with high uncertainty (Beier and Brost 

2010). Additionally, because vegetation land cover and particular microhabitat 

features are important components of wildlife habitat, projecting climate impacts on 

vegetation communities is an important linkage for assessment of climate impacts 

on wildlife, and often is not considered when coupling GCMs and species range 

maps to make projections (Botkin et al. 2007). Although a critique of different 

modeling tools is beyond the scope of this paper, Botkin et al. (2007) provided a 

comprehensive comparison of different methods to project effects of climate change 

on biodiversity. 

Thinking Toward the Future 

Climate change is a complex and far-reaching issue, both spatially and temporally, 

and involves a relatively large amount of uncertainty even beyond the typical 

human inability to predict the future. Both adaptation and mitigation actions in 

the future are unknown, as is their interaction over time and space. An adaptive 

process will facilitate incorporation of research results into management, as well as 

ongoing consideration of land-use changes, forest management, wildlife management, mitigation alternatives, and society’s willingness to undertake actions to 

formulate policy alternatives and confront other components of the global climate 

issue. Needs for additional knowledge focus, for example, on the following areas:

• For individual species and populations, we have the most empirical 

knowledge about range shifts and migration patterns; less is known about 

nonmigratory species, particularly over the long term. 

• Effects of range shifts on competition between new species and species 

already within an area, and adaptive behaviors of species that are successfully adjusting to climate change impacts. 

• Small-scale studies to verify and validate large-scale patterns and modeling 

projections (Root and Schneider 2006). 

• Assessment of multiple stressors such as direct and additive impacts of 

concurrent land use and climate change (Inkley et al. 2004), and potential 

climate-related effects on landscape characteristics such as habitat 

connectivity. Few studies have incorporated empirical land use and climate 
28

GENERAL TECHNICAL REPORT PNW-GTR-837

data concurrently (see McAlpine et al. 2009), particularly for building 

of (see Knowlton and Graham 2010) and application to (see McRae et al. 

2008) models designed to make projections for individual plant and animal 

species. 

• Indirect effects of multiple climate-related abiotic stressors, such as the 

aforementioned cascading effects of precipitation, snowmelt, erosion, and 

sediment loads in rivers on trout habitat and spawning (Scheurer et al. 

2009). 

• Integrating projected climate-related impacts on vegetation communities 

to make stronger linkages between GCMs and wildlife information (Botkin 

et al. 2007). 

• Assessment of vulnerability of species in habitats in proximity to development, and evaluation of adaptation strategies for and adaptive management 

of climate change impacts on wildlife and wildlife habitat. Mawdsley et al. 

(2009) suggested numerous potential adaptation strategies as a foundation, 

but more research is needed to determine the feasibility, ethics, and potential success of such strategies. 

Climate change is a complex and uncertain issue. It affects and is affected by 

both natural and social systems at multiple scales ranging from global to local. In 

one perspective, more weight may be warranted for short-term research that may 

support and inform management and policy decisions regarding both adaptation and 

mitigation. For the case of wildlife, for which potential ability to adapt to changing conditions may be limited, there may not be time to pursue long-term research 

while avoiding varying levels of extinction. Rather, research results may be valuable as information to use within broader and immediate adaptive management 

processes dealing with climate change, while also maintaining natural resource 

management and societal objectives. 

English Equivalents

When you know: Multiply by: To get:

Meters (m) 3.28 Feet

Kilometers (km) .621 Miles

Hectares (ha) 2.47 Acres

Degrees Celsius (°C) 1.8 °C + 32
29

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Chapter 2: Land Value Changes and Carbon 

Sequestration as an Ecosystem Service in a 

Climate-Changed Environment

Ralph J. Alig, Edward A. Stone, and Eric M. White

Introduction

Global climate change induced by anthropogenic release of greenhouse gases 

(GHGs), including carbon dioxide (CO2), may modify the growth and geographic 

distribution of forests, as well as productivity of competing land uses. Impacts on 

agriculture and forests could arise from increases in atmospheric CO2 concentrations, change in temperature regimes, and variations in patterns of rainfall over the 

course of a year. Shifts in global climatic conditions could affect agricultural crop 

and forest growing conditions, and hence land values for those uses. Climate change 

policies may in turn affect land and resource markets, thereby modifying land 

values, land use, and forest cover distribution. A broad examination of such changes 

necessitates assessing multiple markets, including those for carbon sequestration as 

an ecosystem service, especially if policies arise to promote carbon sequestration as 

a mitigation activity. 

Carbon credits and carbon markets are often key components of proposed 

national and international attempts to mitigate the growth in concentrations of 

GHGs. At the same time as policy is causing land-use changes, climate change itself 

is expected to cause changes to environmental conditions, influencing the characteristics and growth of forests in rural and urban settings, as well as agricultural 

production and that of other competing land uses. The focus of this paper is how 

climate change may change land values at broad scales, both from the direct impact 

from future altered climate conditions and from policies formulated to address 

climate change and increase the supply of tradable carbon credits. We summarize 

findings from U.S. studies, to illustrate examples of land value changes in response 

to climate change and associated policies. Understanding land use changes and land 

values in the face of climate change is important for creating efficient strategies for 

the mitigation of climate change at local, regional, and global levels. We focus on 

the domestic situation, and readers interested in land use and climate change connections for other countries are referred to Rai (2009) and works for other countries. 

Changes in Land Values

Land resources such as forest land can produce a future flow of recurring net 

returns or land rents. Land values typically represent the present value of such 

net returns, dependent on estimating the future net returns and the choice of an 
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appropriate capitalization rate (Barlowe 1978). Theoretical models of land-use 

change are grounded in the landowner’s dynamic optimization problem. A landowner is assumed to choose the land use that maximizes the net present value 

(NPV) of the stream of rents to his or her land. A basic model posits that a change 

in land use occurs whenever the NPV of the rents to an alternative land use exceeds 

the NPV of the rents to the current land use by more than the cost of conversion.1

Over time, changes in supply and demand for land affect relative land rents (Alig 

and Plantinga 2004). The rents accruing to any particular land use are determined 

by a host of factors such as land productivity, location, and demographics (e.g., 

population or income changes). Usefully, land rents reflect the interaction of these 

determinants of land values, which are frequently difficult to observe. Many 

empirical analyses of land-use change use the rents accruing to different land uses 

to model and forecast land-use transitions. Given the infinite time horizon, our lack 

of perfect knowledge and foresight complicates the determination of future rents. 

To the extent that we are interested in how the allocation of land uses may change 

with possible carbon revenues, we are also interested in how land values as a key 

measure may be affected by carbon markets.

Some empirical studies also incorporate market values of land, which when 

expressed as a stream of rents are conceptually similar to net rents. However, 

market values may incorporate expectations about the future differently than do 

calculated net returns. First, market values may incorporate expectations of changes 

in land use. For example, forest-land prices anticipate future development close to 

urbanizing areas (e.g., Wear and Newman 2004). The market value of land can be 

thought of as having two components: (1) the value of present assets (e.g., structures 

or standing crops or timber) and (2) the speculative value of future land uses and 

assets that incorporates expectations about a wide range of variables including 

commodity prices, development patterns, government policies such as for carbon 

sequestration, and regional population and income levels. Inconsistencies between 

real estate values and rents for the current land use can be indicative of an expected 

land-use change. Second, the time horizon for which expectations are formed is 

likely to be longer for market values.

Projected shifts in land use reflect economic and soil quality conditions in the 

case of forest and agriculture, whereas conversion of forest land to development is 

influenced significantly in many cases by location. Increases in population and the 

demand for land can give rise to incentives to bring less fertile lands into use. For 

1

 In the presence of risk or uncertainty the landowner’s decision problem is more 

complicated, particularly where the cost of conversion is large or the land-use 

change is irreversible.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

example, with expanded development, growing scarcity of forest land acts to raise 

timber prices. If timber prices and associated timber-related incomes rise enough, it 

may be profitable for some owners to intensify timber management on some lands 

and also afforest additional land. At the same time, changes in transportation costs 

may affect the extent of the area within which forest products can be profitably 

produced. Such changes affect land values in forestry.

Urban and developed uses typically sit on top of the economic hierarchy of land 

uses, with rents often at least an order of magnitude higher than those for forest 

land (Alig and Plantinga 2004). Alig and Plantinga (2004) reported that the ratio of 

average value of land in urban use compared to forest use is approximately 87 in 

the Southeast and 111 in the Pacific Northwest Westside region. The highest forest values on a county basis in the Pacific Northwest Westside are about 0.04 the 

lowest urban values and 0.007 the highest urban value. The ratios in the Southeast 

are roughly similar; however, overall, the Pacific Northwest Westside has much 

larger land values in forest use and urban use. The Pacific Northwest Westside has 

14 counties with land values at least $200,000 per acre ($494,200 per ha) in urban 

use and $2,000 per acre ($4,942 per ha) in forest use, and the Southeast has none. 

Such higher rents mean that determinants of land-use transitions in many cases are 

demand-side factors pertaining to developed uses, such as population and income. 

Thus, in interface areas such as metro or urbanizing locations, the economic 

hierarchy of land uses suggests that, in land markets, development-related land-use 

factors tend to strongly dominate forestry-related ones. 

Ecosystem Service Markets

In this section we discuss the implications of climate change for ecosystem service 

provision and examine how changes in ecosystem service provision affect land 

values. 

Defining ecosystem services—

Broadly defined, ecosystem services are the benefits people derive from the natural 

processes that sustain ecosystems. They can be generally catalogued into four broad 

areas: supporting, regulating, provisioning, and cultural (MEA 2005). Supporting 

services include basic ecosystem functions like soil formation, and provisioning 

services are important sources of food and fiber. Regulating services help control 

climate change through carbon sequestration. Cultural services include recreation 

and education. So ecosystem services comprise both goods and processes. 

Although the concept of ecosystem services is inherently based on the value or 

importance to humans, the underlying ecological structure and processes involve 

complexities that complicate quantifying these services at different scales. In some 
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cases, the linkage between structure, processes, and resulting services is fairly 

straightforward. For example, the degree to which a specific plant community 

can support a given wildlife population can be determined directly by measuring 

community attributes such as species composition, height, and age. Other services, 

such as improving water quality by converting nitrate to nitrogen gas through 

denitrification, are controlled by more complex interactions among multiple ecosystem attributes that are more difficult to measure (for example, carbon, redox 

status, denitrifier population, and temperature). These relationships are also altered 

by temporal and condition gradients, which result in dynamic processes and significant variability across and within different ecosystems, making them difficult to 

measure and quantify at large spatial scales. Ecological production function models 

based on biophysical inputs are often used to produce spatial estimates of specific 

services (Nelson et al. 2009). 

An ecosystem service differs from an ecosystem function because a service 

takes the human context into account. For example, consider a wetland that provides, among other benefits, flood control. The level of this ecosystem function 

is the wetland’s capacity to absorb rising flood waters and gradually release them 

over time. The level of ecosystem service is the benefit of that flood control; thus it 

depends on what lies downstream. A wetland that contributes to flood control for 

a town or city provides a higher level of service than a wetland protecting undeveloped land. Location is important.

Efforts to reduce the divergence between the private provision of ecosystem services and socially 

optimal amounts has involved payments for ecosystem services.

Ralph Alig
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Theoretically, ecosystem services tend to be under supplied by the private sector because they often represent a positive externality. Although a landowner could 

manage to increase the provision of an ecosystem service, little economic incentive 

exists to do so because the benefits of these management practices do not accrue 

solely to the landowner and little increased revenue may result from increased 

provision of that service. Ultimately, the provision of ecosystem services flowing 

from private lands is less than what is desirable to society collectively. Payments 

for ecosystem services (PES) constitute one strategy to increase the provision 

of ecosystem services via an economic incentive. Examples include government 

programs (e.g., the U.S. Conservation Reserve Program [CRP]), eco-labeling and 

certification programs (if the rents flow to farmers), and purchase of conservation 

easements (e.g., by The Nature Conservancy for increasingly prevalent land trusts). 

The provision of ecosystem services from private lands could also be increased 

through regulations (e.g., best management practices for forestry). In this context, 

regulations mandate desirable management practices, and PES programs incentivize desirable management practices.

The goal of PES programs is to increase, on the margin, the provision of ecosystem services by paying landowners to adopt beneficial management practices. 

Carbon sequestration is a prominent example in this context. Sequestering carbon 

should mitigate negative climate change impacts for society at large. In the absence 

of some sort of carbon market, landowners will sequester too little carbon because 

they do not reap the full benefits of sequestration. A carbon market or allowance 

system incentivizes private land sequestration by making sequestration pay. Given 

the opportunity to increase revenues, many landowners may change behavior to 

increase carbon sequestration to levels that are more socially desirable. 

The level of ecosystem service provision from a parcel or a region depends on 

site characteristics (e.g., soil, typical climate conditions—average rainfall, typical 

growing season, etc.), stochastic shocks (e.g., variable weather patterns, natural 

disasters), and land management practices. Altering management practices should 

alter the provision of services, holding other factors constant. Thus, the relationship between ecosystem service and ecosystem function varies with management 

practices.

Effects of changing climate—

In general, changing climate conditions can be expected to result in changes to site 

characteristics and stochastic shocks—changes to ecosystem function. Thus, for 

a given site, the average conditions will change as will the frequency and severity 

of departures from that average. The implications for ecosystem service provision 

depend on management response. With static management, ecosystem service and 
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function should move together. However, human adaptation to changing conditions 

can mitigate the ecosystem service impacts. For example, Sohngen and Mendelsohn 

(1998) showed that climate change impacts on forestry in North America would be 

significantly altered by management practices including salvaging dead trees and 

speeding up the transition between species. In fact, their results suggest gains for 

the U.S. forestry sector from climate change. Thus, climate change interacts with 

human behavior, determining the outcome in terms of ecosystem services in the 

process. Although there is a general scientific consensus that climate change will be 

costly overall, the impacts on particular sectors or services may be positive in some 

regions.

Changes in land values from ecosystem services provision—

But how does ecosystem service provision affect land value, and thus how will 

climate-induced changes in ecosystem service provision affect land value? First, 

climate change affects land value through changes in productivity. In forestry and 

agriculture, site productivity drives land values and rental rates. So as climate 

change affects productivity, land value changes. Over time, land tends to move to 

the highest value use. Thus, if we see land moving from forestry to agriculture, we 

can surmise that returns to agriculture currently outstrip returns to forestry.

However, returns to agriculture and forestry do not depend solely on productivity of traditional products. Returns also depend on payments landowners receive 

from other sources (e.g., government conservation programs, conservation groups, 

carbon markets). Payments for ecosystem service schemes enhance the returns to 

a particular land use or management strategy, rendering that strategy relatively 

more attractive. Recent years have seen significant expansions of PES schemes. 

Government expenditures have increased steadily in both the United States and the 

European Union (USDA ERS 2006), and the involvement of conservation groups 

and institutional actors (such as the Chicago Climate Exchange) is also on the rise. 

Payment for ecosystem services programs essentially create markets for services 

that previously had no markets. As more and more markets come online, this should 

push land values up. Indeed, empirical evidence shows that the CRP, a PES program that pays farmers to remove environmentally sensitive land from production, 

has resulted in higher values for both agricultural and developed land (Wu and Lin 

2010). Simultaneously, the share of land value attributable to ecosystem services 

should rise, assuming all other things being held constant. 

Growing concern over climate change (and other environmental problems) is a 

major driver of PES programs, which could affect land value. Carbon sequestration 

is a particularly important ecosystem service in this context. With a carbon-trading 

scheme in place, landowners will have the option of managing to enhance carbon 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

sequestration and selling this enhanced sequestration potential in the form of 

carbon credits. Agriculture and forestry differ in terms of carbon sequestration 

potential, so the introduction of a carbon market affects relative returns, land value, 

and land use.

Of course, carbon sequestration rates, similar to other ecosystem services, will 

vary with climate change. The direction of this movement is important. If carbon 

sequestration potential rises with increased CO2 concentration, we have a positive 

feedback loop. Higher CO2 concentrations could lead to enhanced sequestration 

rates. Holding land use constant, the effect of sequestration on climate is self-limiting, with a limit on how long the positive feedback would be significant or exist. If, 

on the other hand, sequestration potential falls with increased CO2 concentration, 

we have a negative feedback loop. Higher concentrations lead to lower sequestration, so concentrations continue to rise.

In either case, the market response will enhance the feedback effects. If carbon 

sequestration potential rises with CO2 concentration, the return from using a given 

parcel to sequester carbon also rises. On the margin, some land moves into carbon 

sequestration, dampening climate change further. If sequestration falls as concentration increases, the return from using a parcel to sequester carbon also falls. Thus, 

on the margin, some land will move to other uses, contributing to further increases 

in CO2 concentration.

Given the economic hierarchy of land uses, the addition of carbon-related 

revenues associated with that ecosystem service are not likely to cause major 

changes in land allocation between developed uses and forestry in interface areas or 

urbanizing areas. However, adding carbon-related revenues to the future stream of 

net returns for forestry may boost benefits enough to change the allocation of land 

between forestry and agriculture in some regions. Agricultural land is afforested 

in the study by Alig et al. (2010a) because expected incomes per hectare under 

forest use rise above the expected returns per hectare associated with continuing 

agricultural use. Increasing financial incentives to plant trees, where plantations 

store multiple metric tons of forest carbon per hectare, would boost forest incomes 

in some cases well beyond land rental rates from agriculture. As an example, 

afforested cropland in mixed hardwood forest in the Corn Belt region is estimated 

to sequester approximately 60 metric tons of forest ecosystem carbon per ha by age 

20 (Birdsey 1992). A $15 price per metric ton of CO2 is equivalent to about $55 per 

metric ton of carbon. At this price, the carbon payments from the hardwood stand 

would amount to $8,154 per hectare ($3,300 per acre) as a lump sum at age 20. As 

an equal annual payment over the same 20-year period, that would be equivalent 

to about $274 per hectare ($111 per acre) per year (at a 4 percent real discount rate). 
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The $15 price for CO2 could result in several hundred thousand more hectares of 

afforestation in the Corn Belt region as compared to business as usual (Alig et al. 

2010a). If that price per metric ton is doubled to $30, then about 2.5 million more 

hectares could be afforested with carbon markets. 

Other ecosystem services also provide benefits, and some values could be 

estimated using techniques such as the benefit transfer method (e.g., Johnston and 

Rosenberger 2010). However, unless the amounts are very large, they are not likely 

to tip the land allocation balance between forest and developed uses. Further, unless 

there is some sort of market or PES scheme, enhanced ecosystem services may 

enhance landowner utility, but may not be as likely to be capitalized in land value. 

One example of another service is nitrogen uptake, sometimes discussed alongside 

carbon sequestration. In addition to benefits, analysts need estimates of costs for 

providing ecosystem services, such as converting agricultural land to wetlands. 

Considering both benefits and costs allows for net benefits to be estimated, including examining the present values of benefits and costs. Although costs of a mitigation activity may be significant, values of the marketable commodities along with 

the potential ecosystem services values could be even greater. Thus, depending 

on the assumptions of the benefits to be included, the return on investment in the 

mitigation activity could be significant. 

Afforestation on erodible or other environmentally sensitive agricultural land can enhance ecosystem 

services and co-benefits, such as enhanced wildlife habitat, in addition to contributing to climate 

change mitigation.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Explicitly recognizing the complex relationships between ecosystem structure, 

processes, and services is critical to understanding the potential ancillary effects 

of carbon sequestration strategies. Any change, either anthropogenic or naturally 

occurring, that affects structural components such as plant community composition 

or processes such as nutrient cycling, will affect the quality, quantity, and types of 

services produced from that ecosystem. Quantification of the effect is a difficult 

task, as some services, such as biodiversity, can be both a cause of ecosystem functioning and a response to changing management activity. Thus, effects of carbonspecific components are hard to separate. Another problem is that the responses 

of multiple services to specific carbon-related management activities have not 

been well studied. Nelson et al. (2008) concluded that policies aimed at increasing 

carbon sequestration did not necessarily increase species conservation and that 

highly targeted policies were not necessarily better than more general policies. The 

study by Nelson et al. (2008) demonstrates the likelihood that many of the possible 

management activities and sequestration strategies will affect ecosystem services of 

direct importance to landowners and managers. For example, afforestation designed 

to increase carbon sequestration will alter migratory bird habitat depending on 

the location and species composition of the forest, so ecological tradeoffs will be 

involved. 

Understanding prospects for carbon markets—

The promise of ecosystem service markets greatly depends on the particular 

circumstances of program implementation, including what services are to be traded 

and whether they are amenable to trading, the ability to enact and enforce regulation sufficient to induce trading, and how expected program results compare with 

those likely to arise from other conservation policy approaches (Kline et al. 2009). 

In the case of tradable forest carbon credits, still needed from an institutional 

viewpoint is a cap on the amount of carbon emissions. In an unregulated world, 

carbon emissions exemplify the problem with externalities and public goods. Carbon emitters can carry out production without fully internalizing the social costs of 

the carbon they emit. All producers contribute to total atmospheric carbon and the 

resulting negative externality of global climate change. The lack of property rights 

to the atmosphere provides producers little incentive not to pollute, because they 

need not pay for the right to emit carbon. 

With a regulatory approach, one proposal is to reduce total emissions by 

establishing a uniform cap on the emissions that individual producers can emit. 

Thus, the total cap is the uniform cap times the number of producers. A uniform 

cap is not the least-cost option for achieving the total cap because different producers face different marginal pollution control costs. The least-cost or cost-effective 
52

GENERAL TECHNICAL REPORT PNW-GTR-837

option equalizes marginal control cost across producers. The intent of creating a 

carbon market is to provide a compliance option for heavy emitters—the ability to 

purchase allowances to maintain production without having to reduce their carbon 

emissions. Increasing the flexibility of compliance options for emitters in this way 

equalizes marginal cost and lowers the cost of achieving the total cap. Over time, 

the regulatory agency could ratchet down the overall cap on emissions to gradually 

reduce total carbon emissions. 

In this carbon market, forest owners could conceivably participate by selling 

offsets in the form of tradable carbon credits, increasing the supply of emission or 

damage allowances in a market. The forest carbon owners are performing activities 

that offset damage caused by others (Kline et al. 2009). Landowners might be given 

the right to sell emissions allowances based on forest management or afforestation 

activities that increase forest carbon storage on their lands above some predetermined baseline. 

Next, we summarize aspects of land-use changes, land markets, and land values 

based on modeling studies. The opportunity for exurban and urban developments 

to influence the supply of terrestrial carbon sequestration is outside the scope of 

this chapter, and interested readers are referred to Alig et al. (2004) and White et 

al. (2009) for examples of development area projections. In this chapter, we focus 

on land-use change within a climate change context, although land-use change can 

have many implications for a landscape and society (Alig et al. 2004). Land-use 

changes can also affect product prices (White et al. 2010), wildlife habitat (see chapter 1), and many other parts of ecosystems and the interconnected economic system. 

Examples of Land Value Projections Using the 

FASOM-GHG Modeling System

Global questions involving forestry’s and agriculture’s potential contributions to 

climate change mitigation are framed within a context of increased demands for 

cropland, forage, and wood products to help feed and house an additional 3 billion 

people globally by 2050, increased land demand for bioenergy production, and 

millions of hectares of land needed to house another 125 million U.S. residents by 

midcentury (Alig et al. 2010b). Here we illustrate how the Forest and Agricultural 

Sector Optimization Model—Greenhouse Gas (FASOM-GHG) modeling system is 

used to examine such linked forestry and agricultural issues. Examples of components in FASOM-GHG’s integrated mitigation analysis include (a) simultaneous 

consideration of the agricultural (including both crops and livestock) and forestry 

sectors; (b) discount rate; (c) modeling of impacts on traditional industries; (d) 

dynamic modeling of forest stand growth and investment; (e) GHG accounting, 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

including non-CO2 gases; (f) GHG (e.g., CO2) prices; (g) modeling conversion of 

forest and agricultural lands to developed uses (e.g., urban); (h) examination of 

bioelectricity as part of bioenergy analyses; and (i) land-use changes between the 

forestry and agricultural sectors, among other components. 

Examining land use change and climate change can involve looking at effects 

of climate change on forestry and agricultural activities, adaptation activities, mitigation activities, and the interplay among all three. Within the narrower mitigation 

modeling, such modeling should account both for the GHG impacts of substituting 

bioenergy for fossil fuels and any GHG changes owing to land-use change—so we 

should get the net GHG impact of any change to bioenergy production. Increasingly, modeling could point out exactly the kinds of perverse GHG incentive results 

described in some of the literature. For example, some types of subsidies could lead 

to reduced carbon sequestration as an ecosystem service. Including both the agricultural and forest sectors, modelers can directly recognize the tradeoffs between 

the needs to reduce GHG emissions and expand food production. Models such as 

the Forest and Agricultural Optimization Model (e.g., Alig et al. 2010a) demonstrate 

the forest environmental impacts of different types of policies. Tradeoffs with 

food and environment will occur, and we can use models such as FASOM-GHG to 

investigate such tradeoffs along the path to reducing net GHGs. 

In the next section, we examine studies that project how future climate conditions may impact land values, as well as how policies proposed in response to 

climate change may affect forest-land values. This involves using models that link 

expected forest changes from climate change to the inputs and parameters used in 

forest sector economic models (White et al. 2010). A linked model of the forest and 

agricultural sectors simulates land-use competition between the two sectors, with 

resultant impacts on land allocation and land values in the sectors. 

Modeling Changes From Climate Change

Most studies thus far have assumed that the total area of land in agriculture and the 

total area of land in forests will remain about the same even as climate changes. 

For example, Sohngen and Mendelsohn (1998) valued the impact of climate change 

as a large-scale ecological change in the U.S. timber market, without a mechanism 

for accounting for any productivity-related shifts between forestry and agriculture. 

Although the total area of land in agriculture and forestry may indeed remain 

relatively constant over time, climate change could alter the distribution of land 

uses over time. Given that forest areas could be affected and the potential human 

and social consequences of these impacts, it is important to consider and assess the 

implications of climate change on the distribution of U.S. land uses. 
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GENERAL TECHNICAL REPORT PNW-GTR-837

Differential impacts of climate change in agriculture and forestry could lead 

to land-use shifts as one possible adaptation strategy by landowners. For example, 

if climate change results in relatively higher agricultural productivity per hectare, 

some hectares may be converted from forests to agricultural use. Such changes 

would alter the supply of products to national and international markets, changing 

the prices of forest products and the economic well-being of both producers and 

consumers. Conversely, if climate change renders forestry more attractive than 

agriculture in terms of yields and production costs, land could shift from agriculture to forestry as these two sectors adjust. Given that the agricultural and forestry 

sectors sometimes compete for the same land, shifts in productivity of agricultural 

land could affect the ultimate distribution of forest land, and vice versa. 

Using four climate change scenarios from the national assessment of climate 

change, Alig et al. (2002) found that less forested area was projected under four 

climate scenarios relative to the base case (no climate change). Furthermore, less 

cropland and more pasture land were projected to convert to forests under all 

scenarios. In general, climate change was projected to increase the overall supply 

of timber, causing timber prices to fall and reducing forest-land values. The net 

conversion of forest land to agricultural use was prompted by aggregate increases 

in forest productivity relative to agriculture, with price signals in markets leading 

to adjustments. Although climate change is likely to affect the margin between 

forestry and agriculture differently in specific locations, aggregate productivity 

changes in forestry appear larger overall than aggregate productivity changes in 

agriculture. 

Land values represent key links between forestry and agriculture land markets.

Ralph Alig
55

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Other studies have examined impacts of climate change on agricultural yields. 

For example, Schlenker and Roberts (2008) estimated impacts of climate change on 

crop yields, considering the importance of nonlinear temperature effects. However, 

they did not consider any land use shifts involving forestry that might arise from 

impacts on productivity in the two sectors. Similarly, Sohngen and Mendelsohn 

(1998) examined impacts on forest productivity but did not account for land use 

shift possibilities. 

To our knowledge, no study to date has isolated the impacts on forest-land values from carbon sequestration owing to climate change. The earlier version of the 

FASOM model employed by Alig et al. (2002) did not have carbon-related prices in 

the objective function. Alig et al. (2002) did note changes in economic welfare by 

sector associated with the different climate change scenarios, with changes relatively small compared to those associated with policy scenarios. 

Economic impacts of climate change on land use distribution could also 

involve human migration patterns and impact the amount and pattern of urban and 

developed areas by region. Regional patterns of growth and decline in the United 

States show shifts in population and property value to more vulnerable areas (van 

der Vink et al. 1998), and concerns about climate change and severe weather events 

could alter coastal settlement patterns. A large amount of uncertainty surrounds 

any such movement of population and land use impacts, and is outside the scope 

of this paper. 

Modeling Changes in Land Values With Policies and 

Carbon Markets

Forests are cost-competitive in their ability to play some role in U.S. carbon sequestration activities (Richards and Stokes 2004). Cost studies of forest carbon sequestration over more than a dozen years have estimated costs of between about $10 and 

$150 per metric ton of carbon (Dempsey et al. 2010, Richards and Stokes 2004). 

Some estimates point to forests being able to sequester between approximately 250 

and 500 million metric tons in the United States per year, mirroring the growth 

of the forest and storage of carbon in the accumulating woody biomass. Richards 

and Stokes (2004) pointed out that the cost effectiveness of forest-based sequestration depends on the secondary benefits of sequestration (e.g., habitat creation and 

watershed improvement). 

Next, we look at the use of the FASOM-GHG model to investigate changes 

in values for forestry, agriculture, and tradable carbon credits with carbon-related 

policies. The FASOM-GHG modeling framework can also be used to examine how 

expectations of land-base shifts between the agriculture and forest sectors impact 
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GENERAL TECHNICAL REPORT PNW-GTR-837

potential policy effectiveness. Because market equilibrium is determined with 

endogenous interaction between the forest and agriculture sectors, varying levels of 

future land use patterns can be explored by the introduction of constraints. 

Alig et al. (2010a) used the FASOM-GHG modeling system to investigate 

effects of carbon dioxide equivalent (CO2 e) prices of between $0 and $50 per 

metric ton. These carbon-related values are added to the objective function in a 

symmetric fashion. A symmetric system, also called a carbon subsidy-tax system, 

pays forest owners for increments and “taxes” them for any decrements in carbon 

stock. Hypothetical policies involving carbon-related prices could cause landowners 

to undertake changes in forest management as well as afforest additional agricultural land. Although outside the scope of this chapter, climate change policies may 

involve mitigation actions that promote reduced deforestation. Alig et al. (2010a) 

summarized findings about such efforts to conserve forest land and the impacts on 

carbon sequestration and storage and on traditional forest industries. 

The CO2 pricing scenarios reported by Alig et al. (2010a) included a CO2 price 

of zero, $25/metric ton, and $50/metric ton. The $25/metric ton price approximates 

levels estimated by Murray et al. (2005), who estimated that costs of mitigation 

actions in forestry and agriculture would range from $15 to $25/metric ton of CO2

mitigated. Their analysis using FASOM model runs indicated that between 10 and 

25 percent of current U.S. GHG emissions could be offset through a combination 

of actions in forestry and agriculture, including reduced cropland tillage, afforestation, improved forest management, improved nutrient management, manure 

management, and bioenergy production (Murray et al. 2005). They also simulated a 

scenario with $50/metric ton to investigate effects of a higher CO2 price.

Alig et al. (2010a) reported that soil expectation values (SEV), as one proxy for 

effect on land values, on average almost doubled with a $25 CO2 price compared to 

the base case with no carbon price. These are “bare” forest-land values. Moving to 

a $50 CO2 price increased the SEV values by more than 2.5 times compared to the 

base case. 

Although these are substantial increases, the increases in land value are a 

magnitude of order smaller than the differential between forest land and developed 

use values reported by Alig and Plantinga (2004). For example, in the Southeast, 

SEV timberland values in the Alig et al. (2010a) base run were approximately $500 

to $750 per hectare (approximately $200 to $300 per acre) on average. Doubling 

or tripling such land values would leave them short of $2,500 per hectare ($1,000 

per acre), whereas Alig and Plantinga (2004) reported average urban values in the 

Southeast of more than $90,000 per hectare ($36,000 per acre), an average of more 

than 30 to 40 times as much. 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Therefore, although carbon-related revenues are not likely to appreciably affect 

the land competition between forestry and developed uses in urbanizing areas, 

such carbon revenues can conceptually cause switches in land use between forestry 

and agriculture. As shown in figure 2-1, with afforestation area sensitive to CO2

prices, projected net change in forest area involving land exchanges with agriculture 

(afforestation area minus area deforested to agriculture) summed over the first 50 

years of the projection was positive with a $20 CO2 price, in the Alig et al. (2010a) 

study. In contrast, net change levels without a CO2 price are negative. Afforestation 

dominates deforestation to agriculture early in the projection with $25 CO2, but 

then is exceeded by such deforestation for most of the projection period. The degree 

of land use change associated with a particular carbon price will vary by region. 

For example, Lewandrowski et al. (2004) showed that the Pacific Northwest region 

is relatively less responsive to incentive payment levels for afforestation than the 

Southeast/Appalachia region.

Figure 2-1—Net projected afforestation under different carbon dioxide prices. Adapted from Alig et al. 2010a. 

-30

-20

-10

0

10

20

30

40

0 5 10 15 20 25 30 35 40 45 50

Afforestation/deforestation (million hectares)

CO2e price (dollars per metric ton)

Afforestation from agriculture

Deforestation to agriculture

Deforestation to development

Deforestation to all

Net afforestation
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GENERAL TECHNICAL REPORT PNW-GTR-837

Projected area of afforestation follows a generally declining trend over time in 

the Alig et al. (2010a) national study. Afforestation area with $50/metric ton CO2

averages 0.92 million hectares for the first 25 years of the projection, and then 

drops to 0.31 million hectares over the next 25 years. The highest CO2 prices boost 

forest area by 55 percent compared to the base case, especially in the South and 

North. Doubling the CO2 price from $25 to $50 per metric ton boosts forest area 

in 2050 by 17 percent. 

Deforestation for conversion to agricultural use is sensitive to the CO2 price 

assumption. Deforestation to agriculture is reduced to about one-fifth the base 

area amount with $25 CO2 prices (Alig et al. 2010a). With $50 CO2, the amount of 

deforestation to agriculture drops essentially to zero over the first two projection 

decades. However, even with $50 CO2 prices, the deforestation for agricultural use 

does increase later in the projection period (Alig et al. 2010a), given the expanded 

forest area and changes in land prices across the two sectors. 

Altering the assumption of no loss of forest to development has a smaller effect 

than having CO2 payments for landowners (Alig et al. 2010a). Compared to the base 

level assumption, avoiding deforestation to urban and developed uses can boost 

forest area in 2050 by about 9 percent, about half the increase in moving from $25 

to $50 CO2 prices. The projected base level of forest converted to development is 

approximately 15 million hectares over 50 years, drawn from exogenous projections 

for the 2010 Resources Planning Act (RPA) Land Base Assessment by the USDA 

Forest Service (Alig et al. 2010b; Lubowski et al. 2006, 2008; Plantinga et al. 2007). 

The largest projected losses are in the South and Northeast, consistent with recent 

historical trends. 

Evidence of Carbon Markets

The section above pertains to hypothetical policies for carbon sequestration. 

However, what is actually going on with carbon markets in the United States? 

Currently, there is no binding global agreement to reduce carbon emissions, and 

no associated carbon market. Climate change is a topic replete with uncertainty 

and the progress of carbon markets would require a regulatory cap for significant 

offset values to arise. Ecosystem service markets are one approach among several 

for ecosystem protection and part of the future course of such markets will depend 

on recognition of whether greater global ecosystem protection is necessary. The 

Europeans have had a cap-and-trade market running since 2005. The first few years 

were experimental. Initially, there was a lot of price volatility and a fundamental 

imbalance between supply of tradable carbon credits and demand for them. With 

a more stable and clear regulatory framework, the European carbon trading 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

experiment continues. A mature trading program will provide valuable data and 

give economists the opportunity to observe interaction between carbon trading 

policy and a real economy. Future transactions in forest carbon credits could 

constitute a market of billions of dollars annually and involve potentially large 

transfers of funds between players in our economy. 

In terms of actual transactions, buyers of ecosystem services can already 

purchase carbon credits on the Chicago Climate Exchange (CCX) to offset activities that emit GHGs. In turn, the CCX buys credits from projects that offset the 

accumulation of GHGs in the atmosphere. Many forestry projects do just that, and 

some are already generating income for forest landowners. One example is carbon 

currently being traded on the CCX. Figure 2-2 shows that carbon prices in recent 

times have fallen below $1 per metric ton. 

A number of organizations are angling to position forest landowners to be able 

to trade carbon sequestered on their land on the CCX. In October 2007, California 

Air Resources Board adopted the first standards in the United States for forestgenerated, CO2 emissions reduction projects. AgraGate Climate Credits Corp. is 

0

200

400

600

800

1000

Jan. 2004

May 2004

Sept. 2004

Jan. 2005

May 2005

Sept. 2005

Jan. 2006

May 2006

Sept. 2006

Jan. 2007

May 2007

Sept. 2007

Jan. 2008

Volume (metric kilotons)

0

1

2

3

4

5

6

7

8

Price 

(dollars per metric ton)

May 2008

Sept. 2008

Jan. 2009

May 2009

Sept. 2009

Jan. 2010

May 2010

Figure 2-2—Monthly price and volume data for Carbon Financial Instrument (CFI) contracts on the 

Chicago Climate Exchange (CCX).
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GENERAL TECHNICAL REPORT PNW-GTR-837

now able to provide a Forestry Offset contract on the CCX to forest owners. F&W 

Forestry Services, Inc. is in a similar position. The Georgia Carbon Sequestration Registry assists in the application of land management practices to sequester 

carbon and creates new economic opportunities for landowners. The Texas Forest 

Service received approval as an Authorized Verifier of Forestry Offset Projects for 

the CCX. FORECON EcoMarket Solutions, LLC announced its successful development, presentation, and approval from the CCX for the first managed forestry 

carbon offset project for a timber investment management organization. The pilot 

project covered about 4050 ha (10,000 acres), mostly in Pennsylvania.

However, challenges include the fact that standards lack any sort of national 

uniformity. There are no compliance-based forest programs in the United States, 

and monitoring actual implementation of carbon offset programs is challenging. 

Struck (2010) suggested that some people are buying into projects that are never 

completed, or paying for ones that would have been done anyway. Some green 

schemes range from selling protection for existing trees to the promise of planting 

new ones that never thrive. In some cases, the offsets have consequences that their 

purchasers never foresaw. Struck (2010) characterized carbon offsets as the environmental equivalent of financial derivatives: complex, unregulated, unchecked, 

and—in some cases—not worth their price.

Implementation issues also include possible leakage effects, which could result 

in governments spending large amounts of money while gaining little or no net gain 

in carbon reductions. Thus, although it is possible to increase carbon sequestration 

in forests through afforestation or forest management activities, the net effects 

on overall carbon sequestration may not be as large as anticipated because land 

markets in areas where forests are unprotected may respond by moving some 

forests back into agriculture (i.e., deforestation) (Alig et al. 1997). Alig et al. (1997), 

for example, found an approximate one-to-one correspondence between hectares 

converted to forests from agriculture and hectares converted the opposite direction, 

suggesting the need for a comprehensive policy that recognizes leakage. Murray 

et al. (2004) found similarly large leakage effects for some regions of the United 

States, and Sohngen and Brown (2004) found smaller, though still potentially 

substantial, leakage effects for tropical regions. More recent efforts suggest 

that efficient policies with flux constraints or carbon pricing could provide net 

sequestration, and that these would increase timber supply both in the short run and 

long run (Adams et al. 1999, Murray et al. 2005, Sohngen and Mendelsohn 2003).

It is also important for any carbon credit (offset) to prove a concept called 

additionality. The concept of additionality addresses the question of whether the 

project would have happened anyway, even in the absence of revenue from carbon 
61

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

credits (see for example, Langpap and Kim 2010). Only carbon credits from projects 

that are additional to the business-as-usual scenario represent a net environmental 

benefit. Thus, assessing additionality requires specifying some sort of baseline—

what would have happened without carbon markets. Carbon projects that yield 

strong financial returns even in the absence of revenue from carbon credits, that 

are compelled by regulations, or that represent common practice in an industry are 

usually not considered additional, although a full determination of additionality 

requires specialist review.

Land Value Data Needs

Forest-use valuation is increasingly complicated, as is our understanding and 

modeling of our environment and economy. The increasing recognition of forest 

resource values other than timber, such as for tradable carbon credits, is part of a 

larger societal concern about sustainability of land to provide the goods and services that we as a society demand (Beuter and Alig 2004). Given the fixed amount 

of land, we need to ask what prices we are willing to pay for those goods and 

services and how that will affect land values. We need improved databases pertaining to land markets that provide evidence on revealed behavior about what people 

are willing to actually pay for a bundle of rights necessary to gain access to land 

that can provide goods and services into perpetuity. 

On the empirical side, analyses of land-use change over the past two decades 

have tended to express land value in terms of the stream of rents, or net returns, 

accruing to a particular land use. Three general types of data used to estimate net 

returns are (1) land coverage data, (2) production data, and (3) land value or price 

data. Land coverage data identify a particular land use at a point in time and may 

also provide a measure of land quality or suitability for alternative uses (e.g., soil 

classification). Production data identify the quantities of output associated with a 

particular land use for a specific geographic area and period. An example of a need 

for improved production data is afforestation yields on former cropland and pastureland in all regions. Price data identify input and output prices for the production and 

sale of goods related to a particular land use, such as for forest carbon sequestration. 

Efforts to improve land valuation for climate change studies would likely benefit 

most from attention to the latter category. Increased interest in carbon markets has 

resulted from growing awareness about climate change and the need for mitigation 

activities, many of which could involve terrestrial carbon sequestration. Ecosystem service markets lately have become a popular topic among environmental 

policymakers (Kline et al. 2009), and carbon sequestration has received a lot of 

attention. However, with emerging or nascent markets, many questions remain to 
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be answered. For example, will demand for various ecosystem services be complementary or competitive, and how may pricing of new services affect land use, food 

prices, and the prospects for biofuels or other bioenergy production? 

One information need is for monitoring of emerging forest carbon markets and 

the relationship to land values. Emerging markets may involve speculative elements 

and often include nontraditional markets for forest goods and services. Valuation 

information for these emerging markets may be notably more limited than for 

commodity-related forest products. Further, forest carbon sequestration opportunities exist on both private and public lands and often are a joint or byproduct of 

forest management for other objectives. 

One example of a database as a candidate to be built upon is Lubowski’s (2002) 

construction of a nationwide database of net return estimates for several major land 

uses on private lands. It should be noted that the construction of such estimates can 

be labor intensive and may require a large degree of extrapolation or inference. His 

database was constructed to support national land-use modeling, and was later used 

in other studies (e.g., Alig et al. 2010b). 

In general, gaps exist in land value data, such as for forest-land values based 

on actual transactions generally available to the public. For forest-land values, 

Lubowski (2002) estimated the weighted net present value (NPV) of sawtimber 

Carbon markets are emerging in some areas, and further expansion could affect forest-based 

mitigation opportunities.

Ralph Alig
63

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

from different forest types at the county level. The area of each forest type 

was identified using the USDA Forest Service’s Forest Inventory and Analysis 

data. Timber yields for different forest types were based on existing forest-land 

estimates developed by Birdsey (1992), and need to be augmented for afforestation 

possibilities. State-level stumpage prices were obtained from state and federal 

agencies or from private companies. Where state-level stumpage prices for private 

forest were unavailable, sales prices from state or national forests were used. 

Unavailability of nationwide stumpage price data is an impediment to estimating 

rents. Although Timber Mart-South has historical records of stumpage prices, 

its coverage is limited to 11 Southern States. In constructing nationwide rents, 

Lubowski (2002) proceeded state by state to gather reported stumpage prices by 

surveying various state agencies and private sources. Hence, price data are likely to 

be inconsistent in terms of methodology and quality (varying both regionally and 

over time). Furthermore, developing a nationwide database of stumpage prices in 

this manner is likely to be labor intensive.

Other data sources may be able to complement, approximate, or improve upon 

more established sources at the regional, if not national, level. Some of the sources 

identified below are real estate values. Although real estate values will typically be 

similar to stream of rent values, they cannot be considered perfect substitutes. Real 

estate values incorporate expectations about future land uses that may differ from 

the current use. For example, the real estate value of forestry or agricultural land on 

the fringe of urban development may be well in excess of the NPV of indefinite forestry or agricultural rents because the land value is “ripening” in accordance with 

buyers’ expectations about its impending change to developed land. In this sense, 

disparities between market land values and rent values may indicate an impending 

land use change (Kilgore and MacKay 2007, Wear and Newman 2004). 

Since 1997, USDA’s National Agricultural Statistics Service (NASS) (e.g., 

2009) as a public source has published agricultural land value and rental rate data 

at the state level, but 2009 marks the first time NASS published the information at 

the county level. For 2009, NASS reports mean county-level cash rents per acre for 

cropland (irrigated and nonirrigated) and pastureland. The population target for the 

data is all farms and ranches, and information is collected primarily by telephone 

interview. The county-level rents are available online in tabular and map formats 

(see fig. 2-32

), providing a readily available proxy for cropland net returns at the 

county level. State-level cash rents are available from 1994 to present. However, 

similar data are not available for forest land.

2

 The data in figure 2-3, as well as data for nonirrigated rents, are available at 

http://www.nass.usda.gov/Charts_and_Maps/Land_Values_and_Cash_Rents/index.asp.
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GENERAL TECHNICAL REPORT PNW-GTR-837

Conceptually, the cash rent data are the same as the net returns to cropland 

calculated by Lubowski (2002). To obtain a single rent figure for cropland, irrigated 

and nonirrigated rents should be weighted proportionally to those lands’ acreages. 

The cash rent data could supplement future updates to the crop rent database by 

serving as a comparative check or by providing an easy way to expand the database.

In addition to cash rent data, NASS publishes regional and state estimates 

of average real estate value per acre for irrigated, nonirrigated, and pastured 

agricultural land. These real estate values could be used to compute annual rents. 

The disparity between average real estate value and crop rents could be used as a 

measure of development pressure. 

Figure 2-3—2009 National Agricultural Statistical Service (NASS) cash rents, across all cropland. Note that NASS cash rents 

are based on a survey of farmers. Data are unavailable for parts of Nevada, California, and New England, which appear white in 

the map.
65

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Conclusions and Research Needs

Land prices and other measures of values reflect society’s valuation of land for 

different uses. Modeling changes in land values from climate change and climate 

change policies can provide valuable information to landowners, managers, and 

policymakers as society grapples with how to deal with climate change. One facet 

is how land values may change with increased demand for tradable carbon credits. 

Transactions in forest carbon credits could constitute a market of billions of dollars 

annually and involve potentially large transfers of funds between players in our 

economy. 

Forest carbon credits could add significantly to the possible streams of income 

from timberland. In addition to the growth and harvest of timber, the possibility 

of selling carbon credits would affect investments in timberland. Forest lands in 

general sequester (bind up from the atmosphere) substantial amounts of carbon, 

which in markets could be translated into carbon credits. Revenues from carbon 

credits would tend to boost forest-land values, especially in comparison to some 

agricultural alternatives in some regions. One example of a key activity for which 

better forest and carbon yield data are needed is afforestation of former agricultural 

lands. In general, we need to better understand how land productivity for different uses may change under future climate change in the various regions. Climate 

change is being monitored, with some 24 separate indicators (USEPA 2010) showing how climate change affects the health and environment of U.S. citizens. That 

could be usefully augmented with related indicators about how land productivity is 

being affected.

Ecosystem service provision can be expected to change with climate. Productivity will change with climate, affecting land value and land use. Additionally, 

concern over environmental degradation and climate change has increasingly led 

to the establishment of conservation programs, which can augment land value. A 

central ecosystem service in the climate change context is carbon sequestration. 

The direction of the relationship between CO2

 concentration and sequestration 

determines whether we have a negative or positive feedback loop. In both cases, 

incorporating the effect on land values tends to reinforce the loop.

If global carbon markets emerge, a comprehensive assessment of the carbon 

storage and GHG fluxes within the Nation’s ecosystems would aid in the evaluation 

of potential policy and mitigation actions. Such an assessment is inherently 

complex, as it is geographically broad; covers many different ecosystems, pools, 

and flux types; and is influenced by many present and future potential conditions 

(such as climate change, population change, land cover change, ecosystem 

disturbances, land management activities). If policies adopted to address climate 
66

GENERAL TECHNICAL REPORT PNW-GTR-837

change influence the extent, composition, and management of future forests as 

well as competing land uses, effects are likely to differ by region. In addition, the 

nature of the altered climate could vary substantially by region, so that comparative 

advantages in forest and agricultural production across regions could be affected 

along with land values. 

The policy development process must be supported with integrated, systems 

analysis. Continued investment in developing and refining the models that provide 

this type of analysis is critical. The over-arching nature of the climate change issue, 

which potentially could affect all facets of our lives and work activities (e.g., Fox 

et al. 2009), means our reliance on integrated models and analysis will continue to 

increase as policymakers grapple with a confusing array of choices and tradeoffs. 

Climate change may substantially affect baseline emissions as well as the cost and 

effectiveness of mitigation options. Although there has been increasing recognition 

of these linkages, there remains a need for additional model development and analyses to improve our understanding of the implications for mitigation, adaptation, and 

risk management policy. Demands for bioenergy feedstocks, carbon sequestration, 

food, fiber, and ecosystem benefits from our land base are increasing. At the same 

time, the land base faces enormous potential changes in productivity and risks of 

extreme events. Thus, there are significant needs to improve our understanding 

of potential effects and to model the complex interactions between competing 

demands under changing conditions. Risk management has an important role in 

influencing responses to climate impacts and in developing appropriate mitigation 

and adaptation policy. There is a need to improve our understanding of how people 

will change their land use and production practices and the implications for agriculture, forests, and natural ecosystems as they respond to changing risks within the 

context of policies influencing management choice. 

As ecosystem services become scarcer owing to population growth and rising 

global standards of living (consumption), interest grows in devising markets 

and other means for procuring these benefits. Research to support carbon policy 

analyses includes compensation amounts needed as incentives for landowners to 

participate in tradable carbon credit markets. Land-use change is a key part of 

global change in that deforestation, urban sprawl, agriculture, and other human 

influences have substantially altered and fragmented our global landscape. Such 

disturbances of the land can change the global atmospheric concentration of CO2 , 

the principal heat-trapping gas, as well as affect local, regional, and global climate 

by changing the energy balance on Earth's surface. Research questions relate 

to the relationship between land market activity, land management, and carbon 

sequestration on the global landscape. For example, given that land management 
67

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

can notably alter future levels of forest carbon sequestration (e.g., Adams et al. 

1998), interplay between land markets and markets for products and services can 

influence the path of carbon sequestration over time. Thus, how might variations 

in landowner behavior by region, including development of different densities and 

types, influence the land market outcomes? 

Land use change plays a very significant role in climate change mitigation 

and adaptation, and a land value database could provide both direct and indirect 

benefits. Land prices or values integrate supply and demand information and could 

also provide better information on future land-base conditions for climate change 

analysts. For example, for forest ecosystems, they could provide a thorough and 

unified description of anticipated change in the valuation by society. 

English Equivalents

When you know: Multiply by: To get:

Hectares (ha) 2.47 Acres 

Metric tons 1.102 Tons

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73

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Chapter 3: Socioeconomic Impacts of Climate 

Change on Rural Communities in the United States

Pankaj Lal, Janaki Alavalapati, and D. Evan Mercer

Introduction

Climate change refers to any distinct change in measures of climate such as temperature, rainfall, snow, or wind patterns lasting for decades or longer (USEPA 

2009). In the last decade, there has been a clear consensus among scientists that 

the world is experiencing a rapid global climate change, much of it attributable to 

anthropogenic activities. The extent of climate change effects (e.g., future temperature increase) is difficult to project with certainty, as scientific knowledge of 

the processes is incomplete and the socioeconomic factors that will influence the 

magnitude of such increases are difficult to predict (IPCC 2001). However, even if 

greenhouse gas (GHG) emissions are reduced significantly over the coming years, 

significant increases in temperature and sea level rise may still occur. 

The impacts of climate change can be broadly grouped under three headings: 

ecological, social, and economic. The ecological impacts of climate change include 

shifts of vegetation types and associated impacts on biodiversity; change in forest density and agricultural production; expansion of arid land; decline in water 

quantity and quality; and stresses from pests, diseases, and wildfire. Salient social 

impacts may include changes in employment, equity, risk distribution, and human 

health, and relocations of populations. Economic impacts include increased risk and 

uncertainty of forest or agricultural production, alteration in productivity for crops 

and forest products, reduction in supply of ecosystem goods and services, increased 

cost of utilities and services, and altered energy needs. 

Climate change will most likely affect populations through impacts on the 

necessities and comforts of life such as water, energy, housing, transportation, food, 

natural ecosystems, and health systems. Considerable uncertainty remains about 

the nature and magnitude of climate change impacts, particularly those related 

to rural communities, in view of (1) the complex nature of farm decisionmaking, 

in which there are many nonclimatic issues to manage; (2) the likely diversity of 

responses within and between regions; (3) the difficulties that might arise if climate 

changes are nonlinear or increase climate extremes; (4) timelags in responses of 

communities; and (5) the possible interactions among different adaptation options 

and economic, institutional, and cultural barriers that inhibit such strategies. In 

light of these uncertainties, there is a need to increase our understanding of how 

ecosystems, social and economic systems, human health, and infrastructure will be 

affected by climate change in the context of other stresses.
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GENERAL TECHNICAL REPORT PNW-GTR-837

The climate change literature specifically addressing social and economic 

effects of climate change in rural versus urban areas is limited. Although potential 

threats to urban and rural populations have been described in recent reports (e.g., 

USGCRP 2009), information delineating the impacts of climate change specifically 

on rural communities is scarce. The research has largely been sector-specific, such 

as delineating impacts on agriculture, health, transportation, demography, energy, 

etc., and has rarely addressed how these impacts might differ across urban or rural 

communities.1 Similarly, knowledge of the comparative impacts of climate change 

in different geographical regions is limited. Because much of the climate change 

literature does not specifically address social and economic effects of climate 

change, we make inferences about these effects from national or sector assessments dealing largely with biophysical impacts. In addition, very few studies have 

attempted to delineate impacts across different spatial scales in terms of severity. 

Also, it is difficult to compare severity of impacts in light of future uncertainties. 

The capacity of the community to act in response to climate change and community 

resilience has been largely absent in climate change research (Flint and Luloff 

2005). However, delineating the impacts of climate change on rural populations is 

critical, as they tend to depend on climate-sensitive livelihoods and are especially 

vulnerable to climate change events.

One difficulty in analyzing the impacts of climate change on rural communities, is the lack of a clear demarcation between rural and urban areas, as evidenced 

by the wide variety of definitions of “rural” employed by researchers and policymakers. For example, the USDA Economic Research Service (USDA ERS 2010g) 

lists as many as nine definitions for “rural.” Whether an area is categorized as rural 

or urban depends in large part on how urban spaces are demarcated, i.e., whether 

urban spaces are defined in terms of administrative boundaries, land use patterns, 

or economic influence, and the minimum population thresholds established for 

delineating areas as urban or rural (Cromartie and Bucholtz 2008). Administrative 

definitions identify urban space along municipal or other jurisdictional boundaries. 

Definitions based on land use demarcate urban areas based on population density, 

whereas economic definitions incorporate the influence of cities beyond densely 

settled cores and demarcate based on broader commuting areas. The Office of 

Management and Budget (OMB) identifies counties as rural if they are not core 

counties (core counties contain one or more urban areas of 50,000 people or more) 

or economically tied to the core counties, as measured by the share of the employed 

population that commutes to and from core counties. For the purpose of this study, 

1

 The literature that focuses on indigenous communities tends to be more developed than 

the literature on rural areas in general.
75

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

we follow the OMB definition and discuss impacts of climate change on nonmetro 

(rural) areas comprising about 2,052 counties lying outside metro boundaries. 

Vulnerability of Rural Communities

Rural regions contain about 17 percent of the U.S. population but extend across 80 

percent of the land area (fig. 3-1). The communities residing in these areas differ 

from their urban counterparts in terms of demography, occupations, earnings, 

literacy, poverty incidence, dependency on government funds, housing stress, 

mortality rates, etc. These differences tend to reshape economic and sociocultural 

conditions across rural counties and can provide insights as to why rural populations might have different vulnerabilities2

 to climate change than their urban 

counterparts. Vulnerability is a function of the character, magnitude, and variability 

rate of climate change to which a community is exposed, and the community’s 

sensitivity and adaptive capacity (IPCC 2007). The community adjusts (adapts) in 

response to actual or expected climatic stimuli or their effects, in order to mitigate 

(moderate) adverse impacts or exploit beneficial opportunities. The higher a community’s adaptive capacity, the lower is its vulnerability to climate change.

Figure 3-1—Nonmetro and metro counties, 2003. Source: USDA ERS 2010f.

2

 Vulnerability is defined as the degree to which a system is susceptible to, and unable to 

cope with, adverse effects of climate change, including climate variability and extremes 

(IPCC 2007).
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GENERAL TECHNICAL REPORT PNW-GTR-837

Because 19.6 percent of nonmetro countries are farm dependent3 as compared 

to just 3.4 percent of metro counties (USDA ERS 2010d) (fig. 3-2), rural communities are expected to disproportionately experience the brunt of the climatic impacts 

on agriculture. However, the specific impacts will vary across the United States. 

For example, the Midwest and Great Plains regions where farming is the predominant land use should experience larger impacts compared to other regions such as 

the Southeast, Northeast, or Lake States. 

Figure 3-2—Farming-dependent counties, 1998–2000. Source: USDA ERS 2010c.

3

 Farming-dependent counties have either (1) 15 percent or more of average annual labor 

and proprietors' earnings derived from farming or (2) 15 percent or more of employed 

residents who work in farm occupations. See USDA ERS 2010e for details.

Rural counties tend to be poorer than their urban counterparts, as shown in 

figure 3-3. The per capita income in urban areas ($32,077) far exceeded per capita 

income in micropolitans ($23,338) (counties with cities of 10,000 to 49,999 residents 

and socioeconomic ties to adjacent counties), and noncore counties with neither a 

city over 10,000 residents nor socioeconomic ties to a city of that size, ($21,005) 

(USDA ERS 2010j). Among rural counties, per capita income is generally higher 

in the Northeast than in the Southeast or Southwest. The lower rural earning levels 

indicate lower shares of highly skilled jobs and lower returns to college degrees in 

rural labor markets (USDA ERS 2010l). Unemployment is also often higher in rural 
77

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

areas. For example, 396 of the 460 counties classified as having low employment4

were rural (Whitener and Parker 2007). The rural regions in the Southeast stand out 

as being plagued by high unemployment. Higher unemployment suggests a higher 

sensitivity and lower capacity to cope with the adverse impacts of climate change. 

The rural-urban income gap has been widening recently (USDA ERS 2010j). 

For example, between 1993 and 2004, rural areas averaged 0.5 percent annual 

growth in real earnings compared to 1.2 percent per year in urban areas (USDA 

ERS 2010h). The rural-urban income gap is associated with lower costs of living 

in rural areas, lower educational attainment, less competition for workers among 

employers, and fewer highly skilled jobs in the rural occupational mix. As 

vulnerability to climate change is directly related to income levels (Yohe and Tol 

2002), the rural communities’ vulnerability to climate-related risk is expected to be 

higher than that of urban communities. Incidence of poverty is another factor that 

will influence a community’s vulnerability to climate change. Turner et al. (2003) 

4

 Less than 65 percent of residents 21 to 64 years old were employed in 2000. See 

USDA ERS 2010e for details.

Figure 3-3—Per capita income in micropolitan and noncore counties, 2001. Source: USDA ERS 2010j.
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GENERAL TECHNICAL REPORT PNW-GTR-837

suggested that the poor and marginalized in Canada and the United States have 

historically been most at risk from weather shocks. Rural communities also tend 

to suffer from higher incidence of persistent poverty as evidenced by the data for 

counties5 (fig. 3-4). 

Rural communities tend to be less ethnically diverse than urban areas (USDA 

ERS 2010i). Of the 442 rural counties categorized as high-poverty counties in 2000, 

three-fourths were classified as predominately Black, Hispanic, or Native American 

counties. There were 210 predominantly Black high-poverty counties, mostly in the 

Southeast; 72 Hispanic high-poverty counties, mostly in Texas and New Mexico; 

and 40 high-poverty counties dominated by Native Americans primarily in Alaska, 

New Mexico, Utah, Arizona, Oklahoma, Montana, South Dakota, and North 

Dakota. Of the remaining one-fourth of high-poverty counties, most (91 counties) 

are in the southern highlands of eastern Kentucky, West Virginia, and parts of 

Missouri and Oklahoma and are dominated by non-Hispanic Whites. The remainder of the high-poverty counties (27) includes thinly populated farming areas in 

the northern Great Plains, where annual income levels range widely depending on 

Figure 3-4—Persistent poverty counties, 1970–2000. Source: USDA ERS 2010i.

5

 Counties in which 20 percent or more residents were poor as measured by last four 

censuses, 1970–2000. See USDA ERS (2010e) for details.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

wheat and cattle prices and output, and two high-poverty counties where Asians are 

the dominant ethnic group. 

The Intergovernmental Panel for Climate Change (IPCC) identifies economic 

wealth, technology, information and skills, infrastructure, institutions, and 

equity as significant features of adaptive capacity (Smit et al. 2001). Wealthier 

communities tend to have greater access to technology, information, developed 

infrastructure, and stable institutions (Easterling et al. 2007) and thus possess 

higher adaptive capacity for climate change. According to the USDA Economic 

Research Service (2010i), rural communities in the South and West account for 

approximately 59 percent of the total rural population in the country and have the 

highest poverty rates in the country. Thus, we would expect these areas to have 

generally lower adaptive capacity to cope with future climate risks (fig. 3-5). Just 

because a community may have high socioeconomic status, however, does not 

mean it is effective at making collective decisions and meeting the needs of the 

broader population. Social relations are difficult to quantify and compare across 

communities and regions. In this paper, we primarily use socioeconomic status, 

technology, infrastructure, and skills to make inferences about the relative adaptive 

capacity of communities. 

Figure 3-5—Poverty rates by region and metro status, 2006. Source: USDA ERS 2010b.

Another factor that adds to the vulnerability of rural areas is their dependence 

on government transfer payments. Based on 2001 data (USDA ERS 2010k), 

government transfer payments averaged $4,365 per person per year in rural, 

nonmetro areas compared to $3,798 for metro areas. Federal and state government 

30

20

10

0

Northeast Midwest South West U.S. total

11.4 11.4 11.1 11.5

19.2

12.5

14.4

11.3

15.2

11.8

Region

Nonmetro

Metro

Population in poverty (percent)
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GENERAL TECHNICAL REPORT PNW-GTR-837

transfers accounted for about one-fifth of rural income as compared to just oneeighth of metro income. Unless government transfer payments to rural areas are 

able to keep up with increased need resulting from climate change impacts, rural 

areas may experience greater vulnerability to climate change than urban areas.

Most outdoor recreation areas are in rural counties of the United States; for 

example, 334 of the 368 (91 percent) recreation-dominated counties6 were rural 

and only 34 were urban in 2003 (Whitener and Parker 2007) (fig. 3-6). Many of the 

jobs that are usually associated with recreation, such as those in hotels and restaurants, often are low paying with few fringe benefits (Deller et al. 2001). However, 

in rural areas, which have lower incomes and higher poverty incidence than their 

urban counterparts, even these low-paying jobs might be quite important for the 

livelihoods of communities. If climate change dramatically reduces or shifts job 

opportunities in recreation, most of the impact will be felt by rural communities, 

where most of the recreation employees reside (Morello et al. 2009). However, as 

Figure 3-6—Nonmetro recreation counties, 1999. Source: Source: USDA ERS 2010a.

6

 Rural counties have been classified using a combination of factors by Economic Research 

Service, including share of employment or share of earnings in recreation-related industries 

in 1999, share of seasonal or occasional-use housing units in 2000, and per capita receipts 

from motels and hotels in 1997. See USDA ERS 2010e for details.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

we discuss below, impacts of climate change on recreation will vary considerably 

geographically.

Rural residents tend to have higher rates of age-adjusted mortality, disability, 

and chronic disease than their urban counterparts, although mortality and disability 

rates vary more by region than by metro status (Jones et al. 2009). Furthermore, 

as young adults move out of small, rural communities, many rural communities 

tend to reflect an increasingly vulnerable demographic of very old and very young 

people, placing them more at risk for climate change effects than urban communities. Climate impacts, coupled with demographic shifts in rural communities, may 

make it more difficult to supply adequate and efficient public health services and 

educational opportunities to rural areas (USGCRP 2009). Detrimental climate 

change effects are also likely to be compounded by additional stresses and disturbances such as increased land use change, pollution, wildfires, and invasive species 

(USGCRP 2009). 

The accessibility of health care resources tends to decline as population density 

declines and geographic isolation increases. As a result, rural residents tend to face 

higher financial and travel costs to access health care and pay a greater share of 

household income for health care than their urban counterparts (Jones et al. 2009). 

Furthermore, emergency response systems are often less effective in rural areas 

because the population is dispersed and geographically isolated. The combined 

Climate change may have different effects geographically and on different parts of rural and urban 

communities.

Ralph Alig
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effects of changing demographics and increasing health costs are likely to make 

it more difficult to supply adequate and efficient public health services to rural 

areas in the future. Therefore, with lower access to health infrastructure and higher 

proportion of income spent on health services, rural communities are likely to be 

more vulnerable to adverse health impacts caused by climate change. 

A changing climate will mean reduced opportunities for some activities and 

locations and expanded opportunities for others, leading to regional differentiation 

of impacts in term of incidence and intensity. Certain facets of climate change may 

impact one particular region but not others. For example, increased risk of drought, 

pests, and extreme weather events may add additional economic stress and tension 

to rural communities (Motha and Baier 2005, Parton et al. 2007). However, as we 

explore below, climate-driven shifts in crop types and recreation areas may also 

benefit some rural communities. Similarly, impacts on water quality and quantity 

owing to climate change will differ across regions. For example, reduced snowpack 

and earlier snowmelt because of warmer temperatures will alter the timing and 

amount of water supplies, impacting the Western United States harder than the 

Eastern United States (USGCRP 2009). Climate change events may also differentially affect the culture and livelihood patterns of indigenous communities in the 

United States. 

Impacts on Rural Communities

Climate change impacts will differ by region and sector, and so will the capacity 

to handle the resulting challenges. Climate change will likely produce a range 

of impacts depending on specific attributes of the affected rural communities or 

industries. Some communities may benefit from climate-induced changes, whereas 

others may face large losses. For example, communities dependent on oil and gas 

extraction and mining-related industries are likely to experience climate change 

differently than predominantly agricultural communities (USGCRP 2009). Furthermore, agricultural communities in different parts of the United States will likely 

also differ in how climate change affects them. For example, farming communities 

in the Great Lakes States may benefit from warming climate owing to improved 

growing conditions for some crops (like fruit production) that are currently limited 

by length of growing season and temperature, whereas farming communities in the 

Midwest may face adverse impacts of climate change owing to lower availability of 

irrigation water (Hatfield et al. 2008).
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Social Impacts

Important characteristics of rural society make it vulnerable to climate change 

impacts and affect how the risks and costs may be distributed among different 

regions. Salient social impacts include impacts on human health via direct effects 

(e.g., thermal stress) and indirect effects (e.g., disease vectors and infectious agents), 

increase in societal conflicts, and high vulnerability of particular community 

groups such as Native Americans.

Human health—

Climate change will affect human health through both direct and indirect pathways. Direct impacts will result from increased exposure to temperature (heat 

waves, winter cold) and other extreme weather events (floods, cyclones, storm 

surges, droughts) and increased production of air pollutants and aeroallergens 

such as spores and molds (USGCRP 2009). Figure 3-7 shows temperature changes 

projected under two GHG emission scenarios. The average U.S. temperature is 

projected to increase by approximately 7 to 11 °F for the higher emissions scenario 

and 4 to 6.5 °F for the lower emission scenario (USGCRP 2009). Although most of 

the country will face greater warming in summer than in winter, Alaska is expected 

to experience far more warming in winter than summer (Christensen et al. 2007).

The occurrence of extreme heat events like the Chicago heat wave of 1995, 

which lasted for 5 days and resulted in an 85-percent increase in heat-related 

mortality and an 11-percent increase in heat-related hospitalizations, are expected 

to become more frequent as a result of climate change. However, rural counties, 

which have lower builtup area than cities, should be less vulnerable to extreme heat 

events. This is due to the fact that concrete and asphalt in cities absorb and hold 

heat, while tall buildings prevent heat from dissipating and reduce air flow leading 

to a “heat island effect.” The larger amounts of vegetation in rural areas also tend to 

provide more shade and evaporative cooling than in urban areas.

Human health may also be indirectly affected by an increase in water, food, and 

vector-borne diseases. Kilpatrick et al. (2008) suggested that increasing temperatures significantly increases dissemination and transmission of viral infection, most 

likely through increased viral replication. The distribution and abundance of vector 

organisms and intermediate hosts can also be affected by physical factors such as 

temperature, precipitation, humidity, surface water, and wind and by biotic factors 

such as vegetation, host species, predators, competitors, and parasites, all of which 

may be altered by climate change (PSR 2010). 
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There are clear trends of increasing incidents of very heavy precipitation in the 

Nation as a whole, and particularly in the Northeast, Midwest, Alaska, and islands 

as shown in figure 3-8. 

Heavy downpours can lead to increased sediment in runoff and outbreaks 

of waterborne diseases (Ebi et al. 2008, Field et al. 2007). Degradation of water 

quality and increases in pollution carried to lakes, estuaries, and the coastal ocean 

Figure 3-7—Projected temperature change (Fahrenheit) from 1961–1979 baseline for two emission 

scenarios. Based on projections of future temperature by 16 of the Coupled Model Intercomparison 

Project Three climate models for IPCC higher and lower scenarios. The brackets on the thermometers represent the likely range of model projections, although lower or higher outcomes are possible. 

Source: USGCRP 2009.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Figure 3-8—Increases in amounts of very heavy precipitation, 1958–2007. Source: USGCRP 2009 

based on Groisman et al. 2004.

following heavy downpours, especially when coupled with increased temperature, 

can also result in blooms of harmful algae and bacteria and increased risk of waterborne parasites such as Cryptosporidium and Giardia. Incidences of heavy rain and 

flooding can also contaminate food crops with feces from nearby livestock or wild 

animals, increasing the likelihood of food-borne disease (Ebi et al. 2008). Projected 

increases in carbon dioxide (CO2) can also stimulate the growth of stinging nettle 

and leafy spurge, two weeds that cause rashes when they come into contact with 

human skin (Ziska 2003).

Impacts on indigenous communities—

Native American communities, which are predominantly rural, may face 

disproportionately higher levels of climate change impacts on their livelihoods, 

rights and access to natural resources, future growth, and in some cases, their 

culture, which depends on traditional ways of collecting and sharing food 
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GENERAL TECHNICAL REPORT PNW-GTR-837

(Hanna 2007, Nilsson 2008, Tsosie 2007, USGCRP 2009). For many indigenous 

communities, climate change may also reduce the availability and accessibility of 

such traditional food sources as seals, whose migration patterns depend on their 

ability to cross frozen rivers and wetlands (USGCRP 2009). It is estimated that 

climate change may increase flooding and erosion in 184 out of 213, or 86 percent, 

of Native Alaskan communities (USGAO 2003). Native cultures in the Great 

Plains and Southwest are also vulnerable to climate change effects. Many of these 

tribes have limited capacity to respond to climate change and already face severe 

problems with water quantity and quality—problems likely to be exacerbated by 

climate change. 

Relocation options tend to be limited for many Native Americans who live on 

established reservations and may be restricted to reservation boundaries (NAST 

2001). Having already been relocated to reservations, these communities have 

historically been disconnected from their traditional life, prohibited from engaging 

in important social and cultural practices, and allowed limited participation in land 

management and planning (Tsosie 2007). Furthermore, Native American communities may be more vulnerable to climate change impacts, as their rights and livelihoods tend to be interwoven with specific lands limiting their relocation options in 

the face of alterations in resource availability (Donoghue et al. 2009). 

The melting of permafrost, which has already turned solid ground into 

mush in some places in Alaska, threatens the economies and cultures of many 

Alaskan tribes as they may be required to relocate at large economic and cultural 

cost (NTAA 2009). For example, the way of life of the Inupiaq Tribe in Alaska 

is threatened owing to climate change. The traditional method of food storage 

of Inupiaqs is being disrupted by warming, as “permafrost” does not remain 

permanent, leading their belowground storages (sigulaqs in native language) to 

be thawed and sometimes flooded with meltwater. The resulting spoiled meat 

increases the risk of food-related illness.

Subsistence cultures such as Native Alaskans adapt to year-to-year fluctuations 

of game species by shifting practices and target species, which implies some 

ability to adapt to effects of near-term climate change (USGCRP 2009). Integrating 

the adaptation insights of indigenous peoples in terms of access, process, and 

the outcomes of climate policy and planning should be helpful in reducing 

impacts (Nilsson 2008). However, these adaptation opportunities may be severely 

constrained, as warming in Alaska is especially likely to reshape patterns of human 

settlement and intertwined economic activities (Wilbanks et al. 2007). 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Economic Impacts

Major parts of the rural economies of the United States are directly sensitive to 

climate change, including the agriculture, recreation and tourism, forestry, water 

resources, energy, and fisheries sectors. 

Agriculture—

Agriculture will certainly face significant changes from climate change. Longer 

growing seasons and increased CO2

 have positive effects on some crop yields, 

although this might be counterbalanced in part by the negative effects of additional 

disease-causing pathogens, insect pests, and weeds (USGCRP 2009). Hatfield et 

al. (2008) suggested that even moderate increases in temperature will decrease 

yields of corn, wheat, sorghum, bean, rice, cotton, and peanut crops. More frequent 

temperature extremes will also create problems for crops. For example, tomatoes, 

which are well-adapted to warmth, produce lower yields or quality when daytime 

maximum temperatures exceed 90 °F for even short periods during critical reproductive stages (Kunkel et al. 2008). Some crops, however, benefit from higher 

temperatures, and global warming will likely result in a longer growing season for 

crops like melon, okra, and sweet potato (Hatfield et al. 2008). Significant technological progress might also temper adverse climate change impacts. For example, 

corn yields have shown an upward trend even in light of variation caused by climate 

events (fig. 3-9). However, U.S. Global Change Research Program (2009) argued 

that it is difficult to maintain this historical upward trend without dramatic technological innovations. 

Climate change may increase agricultural production costs for a number of 

reasons. For example, the expansion of weeds may be exacerbated by climate 

change if weeds benefit more from higher temperatures and CO2 levels than 

traditional crops (Hatfield et al. 2008). With continued warming, invasive weed 

species are expected to expand northward and increase costs and crop losses as 

evidenced by the fact that loss of crops owing to weeds is higher in the South 

than in the North. For example, southern farmers lose 64 percent of the soybean 

crop to weeds, whereas northern farmers lose just 22 percent (Ryan et al. 2008). 

Controlling weeds currently costs the United States more than $11 billion a year, 

with the majority spent on herbicides (Kiely et al. 2004). This cost is likely to 

increase as temperatures rise. The problem is aggravated by the fact that the most 

widely used herbicide in the country, glyphosate, loses its efficacy at CO2

 levels 

that are projected to occur in the coming decades (Wolfe et al. 2007). Another 

potential impact of climate change is premature plant development and blooming, 

resulting in exposure of young plants and plant tissues to late-season frosts. For 
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GENERAL TECHNICAL REPORT PNW-GTR-837

example, the 2007 spring freeze in the Eastern United States led to widespread 

devastation of crops and natural vegetation, because the frost occurred during 

the flowering period of many trees and during early grain development on wheat 

plants (Gu et al. 2008).

Climate change is projected to increase the intensity of precipitation, resulting 

in heavy downpours across the country (Kunkel et al. 2008). This excessive rainfall 

may delay spring planting, in turn lowering profits for farmers who are paid a premium for early-season production of high-value crops such as melons, sweet corn, 

and tomatoes. Field flooding during the growing season by heavy downpours leads 

to low oxygen levels in the soil, higher susceptibility to root diseases, and increased 

soil compaction from the use of heavy farm equipment on wet soils. Increased 

intensity of precipitation can also result in reduced quality of many crops. 

The projected warmer temperatures are expected to increase livestock 

production costs owing to lower feed intake and increased requirements for energy 

to maintain healthy livestock at higher temperatures. Forage production may 

also be affected by climate change. Rising atmospheric CO2 concentrations can 

increase the quantity of forage produced, but it might reduce forage quality, as plant 

nitrogen and protein concentrations often decline with higher concentrations of 

CO2

 (Hatfield et al. 2008). The dairy industry is also quite sensitive to temperature 

Figure 3-9—United States corn yield trend since 1960. Source: USGCRP 2009 based on NAST 2001.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

changes, as dairy cows’ productivity decreases above 77 °F (25 °C). By late in 

this century, all Northeastern States except the northern parts of Maine, New 

Hampshire, New York, and Vermont are projected to suffer declines in July milk 

production under the higher emissions scenario (USGCRP 2009). In California, 

an annual loss of $287 to $902 million is expected for this $4.1 billion industry. In 

parts of Connecticut, Massachusetts, New Jersey, New York, and Pennsylvania, 

climate change is projected to produce a large decline in milk production from 10 to 

20 percent or greater (USGCRP 2009).

Climate change impacts on rural communities engaged in agriculture will 

differ across regions; some will likely benefit while others lose depending on their 

geographic location and adaptive capacity. Heat and water stress from droughts and 

heat waves is likely to decrease yields and adversely affect crops like wheat, hay, 

corn, barley, cattle, and cotton in the Great Plains (Motha and Baier 2005). Much of 

the Northwest region's agriculture will experience detrimental impacts. Particularly 

impacted will be specialty crops in California such as apricots, almonds, artichokes, 

figs, kiwis, olives, and walnuts (Lobbel et al. 2006). By late in this century, winter 

temperatures in many important fruit-producing regions such as the Northeast may 

be too warm to support fruit production. For example, Massachusetts and New 

Jersey supply nearly half the Nation’s cranberry crop. By the middle of this century, 

these areas may not be able to support cranberry production owing to lack of winter 

chilling (Frumhoff et al. 2007, Wolfe et al. 2007). 

Climate change may affect costs and production levels for forestry and agricultural enterprises.

Emily Jederlinich
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GENERAL TECHNICAL REPORT PNW-GTR-837

In contrast, warming is expected to improve the climate for fruit production in regions such as the Great Lakes (Field et al. 2007) or Midwest (USGCRP 

2009). However, even farms and regions that temporarily benefit from altered 

environmental conditions (e.g., carbon fertilization and extended growing season) 

risk economic losses if temperatures exceed those preferred by the crops they 

currently produce (Ruth et al. 2007). In the Midwest, the projected increases in 

winter and spring precipitation and flooding are likely to delay planting and crop 

establishment.

Recreation and tourism—

Outdoor recreation activities depend on the availability and quality of natural 

resources, such as beaches, forests, wetlands, snow, and wildlife (USGCRP 

2009). Johnson and Beale (2002) identified 329 recreation-dependent counties by 

geographic location, natural amenities, and form of recreation.7

 Most of the rural 

recreation counties are concentrated in the West, the Upper Great Lakes, and the 

Northeast regions (Reeder and Brown 2005). Recreation counties in general tend 

to have relatively low population densities, and more of their residents live in rural 

parts of the county (Jones et al. 2009). In the West, rural counties reflect opportunities for hiking, mountain climbing, fishing, and wintertime sports found in 

the many national parks and ski resorts. On the other hand, recreation-dependent 

counties in the Upper Great Lakes and Northeast—especially in New England and 

Upstate New York—are largely due to second homes in areas with lakes. Many of 

these areas also have significant wintertime recreation activities, including snowmobiling and skiing.

Increased temperatures and precipitation owing to climate change are expected 

to have a direct effect on the enjoyment of tourism activities, and on the desired 

number of visitor days and associated levels of visitor spending and employment. 

Climate change could affect recreation through three pathways: winter activities 

such as downhill and cross-country skiing, snowshoeing, and snowmobiling; nature 

7

 Recreational counties were identified based on a multistep selection procedure combining 

empirical measures of recreational activity along with a review of recreation-related contextual material existing in the counties. These empirical measures used were (1) wage and 

salary employment in entertainment and recreation, accommodations, eating and drinking 

places, and real estate as a percentage of all employment reported in the Census Bureau’s 

County Business Patterns for 1999; (2) percentage of total personal income reported for 

these same categories by the Bureau of Economic Analysis; (3) percentage of housing units 

intended for seasonal or occasional use reported in the 2000 Census; and (4) per capita 

receipts from motels and hotels as reported in the 1997 Census of Business. For details see 

Johnson and Beale 2002.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

tourism and related activities such as biking, walking, hunting, etc.; and waterrelated sports such as diving, sailing, and fishing. A changing climate will mean 

reduced opportunities for some activities and locations and expanded opportunities 

for others (Sussman et al. 2008). The length of the season, and, in many cases, the 

desirability of popular activities like walking; visiting a beach, lakeshore, or river; 

sightseeing; swimming; and picnicking might increase because of small near-term 

increases in temperature. On the other hand, snow- and ice-dependent activities, 

including skiing, snowmobiling, and ice fishing, could be adversely affected by 

even small increases in temperature. Hunting and fishing opportunities will change 

as animals’ habitats shift and as relationships among species in natural communities are disrupted by their different responses to rapid climate change (USGCRP 

2009). In the longer term, as climate change affects ecosystems and seasonality 

becomes more pronounced, the net economic effect on recreation and how it will 

influence different population groups in different regions is not known (Wilbanks 

et al. 2007).

The impact of climate change on ski, snowmobile, and other winter sport industries is expected to be more pronounced in the Northeast and Southwest regions. 

The ski resorts in the Northeast have three climate-related criteria to remain viable: 

the average length of the ski season must be at least 100 days, there must be a good 

probability of being open during the lucrative winter holiday between Christmas 

and the New Year, and there must be enough nights that are sufficiently cold to 

enable snowmaking operations. By these standards, only one area in the region 

(fig. 3-10) is projected to be able to support viable ski resorts by the end of this 

century under a higher emissions scenario (USGCRP 2009).

Figure 3-10—Ski areas at risk in the Northeastern United States. Source: USGCRP 2009 based on 

Frumhoff et al. 2007.
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Reduced snowmaking in the Southwest owing to climate change is also 

expected to shorten the ski season substantially, with projected losses of 3 to 6 

weeks (by the 2050s) and 7 to 15 weeks (2080s) in the Sierra Nevada of California 

(Hayhoe et al. 2004, Scott and Jones 2005). Projections indicate later snow and less 

snow coverage in ski resort areas, particularly those at lower elevations and in the 

southern part of the Southwest region. Decreases from 40 to almost 90 percent are 

likely in end-of-season snowpack under a higher emissions scenario in counties 

with major ski resorts from New Mexico to California (Zimmerman et al. 2006). 

The snowmelt dates are also projected to shift earlier at most sites (fig. 3-11). 

Figure 3-11—Observed spring snowmelt dates in Western United States. Source: USGS 2005.

In addition to shorter seasons, earlier wet snow avalanches could force ski 

areas to shut down many runs before the season would otherwise end (Lazar 

and Williams 2008). Resorts require a certain number of days just to break 

even; cutting the season short by even a few weeks, particularly if those occur 

during the lucrative holiday season, could easily render a resort unprofitable. The 

snowmobiling industry is also vulnerable to climate change as it relies on natural 

snowfall. Some predict that by the 2050s, a reliable snowmobile season will 

disappear from most regions of the East (Scott and Jones 2006, Scott et al. 2008). 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Nature-based tourism—hiking; camping; bird watching; visiting a beach, lakeshore, or river; sightseeing; swimming; and picnicking—is a major market segment 

in many parts of the country, with over 900 million visitor-days in national, state, 

and local parks reported in 2001 (USGCRP 2009). The length of the nature tourism 

season is likely to be enhanced by small near-term increases in temperature. Visits 

to national parks are projected to increase by 9 to 25 percent (2050s) and 10 to 40 

percent (2080s) as a result of a lengthened warm-weather tourism season (Scott and 

Jones 2006). Nearby communities may benefit economically, but visitor-related 

ecological pressures could be exacerbated in some parks. Activities like hunting 

and wildlife-related tourism will change as habitats shift and relationships among 

species in natural communities are disrupted by their different responses to rapid 

climate change (USGCRP 2009). Climate-induced environmental changes (e.g., 

loss of glaciers, altered biodiversity, fire- or insect-impacted forests) may also affect 

nature tourism, although uncertainty is higher regarding the regional specifics and 

magnitude of these impacts (Richardson and Loomis 2004, Scott et al. 2007). 

The impacts on water-related tourism are likely to be exacerbated by rising 

sea levels and storm severity especially in areas projected to get drier, such as the 

Southwest, and in beach communities that are expected to see rising sea levels 

(Clark et al. 2008, Kleinosky et al. 2005, Williams et al. 2009, Wu et al. 2002). 

There is evidence that the global sea level is currently rising at an increased rate 

(Bindoff et al. 2007, Rahmstorf et al. 2007, Vermeer and Rahmstorf 2009). Water 

sports that depend on the flows of rivers and sufficient water in lakes and reservoirs 

are already being affected, and much larger changes are expected in the future 

(Sussman et al. 2008). Higher sea levels may erode beaches, and along with increasing water temperatures, destroy or degrade natural resources such as mangroves 

and coral reef ecosystems that attract tourists (Mimura et al. 2007). However, the 

vulnerability of key recreation areas in the coastal United States to climate change 

events has not been comprehensively assessed (USGCRP 2009).

Recreational fisheries in many rural counties will also be impacted by climate 

change. For example, approximately half of the wild trout populations are expected 

to disappear from the Southern Appalachian Mountains owing to rising stream 

temperatures. Losses of western trout populations may exceed 60 percent in certain regions. About 90 percent of bull trout (Salvelinus confluentus), which live in 

western rivers, are projected to be lost on account of warming. The state of Pennsylvania is predicted to lose 50 percent of its trout habitat in the coming decades, 

and warmer states such as North Carolina and Virginia, may lose up to 90 percent 

(Willliams et al. 2007). 
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The U.S. islands (Hawaii, Puerto Rico, Virgin Islands, Guam, American 

Samoa) face potentially large impacts from climate change. For island fisheries 

sustained by healthy coral reefs and marine ecosystems, climate change impacts 

exacerbate stresses such as overfishing (Mimura et al. 2007), affecting both fisheries and tourism. Any adverse impacts on tourism threaten the livelihood of many 

island communities. For example, in 1999, the Caribbean Islands had tourism-based 

gross earnings of $17 billion, providing 900,000 jobs and making the Caribbean one 

of the most tourism-dependent regions in the world (Heileman et al. 2004). 

Forestry—

The impacts of climate change on forestry are expected to arise from shifts in forest 

distribution and types, increased wildfire risk, increased chance of pest attacks and 

diseases, and adverse impacts on biodiversity. Projected changes in climate and the 

consequent impact on forests could affect market incentives for investing in intensive forest management (such as planting, thinning, genetic conservation, and tree 

improvement) and developing and investing in wood-conserving technologies. The 

effect on rural communities will differ depending on the geography, demographics, 

and social and economic conditions each community faces; as with agriculture, 

some may benefit while others lose. 

Potential habitats for trees favored by cool environments are likely to shift 

north (NAST 2001) (fig. 3-12). As tree species migrate northward or to higher 

elevations, habitats of alpine and subalpine spruce-fir could possibly be eliminated 

(IPCC 2007). Aspen and eastern birch communities are also likely to contract 

dramatically in the United States and largely shift into Canada. Potential habitats 

that could possibly expand in the United States are oak/hickory and oak/pine in the 

Eastern United States and ponderosa pine and arid woodland communities in the 

West. The changing forest distribution is already being observed in many areas. 

For example, in Colorado, aspen (Populus sp. Michx.) has advanced into the more 

cold-tolerant spruce-fir forests over the past 100 years (Elliott and Baker 2004). 

The northern limit of the lodgepole pine (Pinus contorta Douglas ex Louden) range 

is advancing into the zone previously dominated by the more cold-tolerant black 

spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) in the Yukon (Johnstone 

and Chapin 2003). In addition, many of the economically valuable timber species in 

the Midwest—aspen, jack pine (Pinus banksiana Lamb.), red pine (Pinus resinosa 

Aiton), and white pine (Pinus strobus L.)—may be lost owing to global warming 

(Easterling and Karl 2001). If the forests in the South and Northeast shift to oak and 

hickory species in lieu of softwoods, the pulp/wood fiber industry could experience 

large losses (USGCRP 2009), in turn impacting the rural communities who depend 

on these industries for their livelihoods.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Warmer summer temperatures and reduced rainfall in the West are projected to 

extend the annual window of wildfire risk by 10 to 30 percent (Brown et al. 2004). 

These factors are contributing to an overall increase in the area of forest burned 

each year in the Pacific Northwest and in the United States as a whole (USDA FS 

2000). Westerling et al. (2006) analyzed wildfire trends in the Western United 

States and found a sixfold increase in the area of forest burned since 1986 compared 

with the 1970–86 period. The average duration of fires increased from 7.5 to 37.1 

days—mostly because of an increase in spring and summer temperatures and 

earlier thawing of snowpacks. The increased incidences of wildfires could affect 

communities in a number of ways including loss of forest recreation opportunities 

and increased costs for fire suppression and recovery. For example, Ruth et al. 

(2007) predicted that the climate-change-induced warming will mean that the state 

of Washington will face fire suppression cost increases of over 50 percent by 2020 

and over 100 percent by 2040, raising the expenses to $93 million and $124 million, respectively. Because many rural communities reside adjacent to forest or are 

dependent on forest industries for their livelihood, they tend to be directly affected 

by these wildfires. These wildfires are adversely impacting indigenous communities as well (NTAA 2009).

Figure 3-12—Projected shift in forest types in Eastern United States under a midrange warming 

scenario. Source: USGCRP 2009 based on NAST 2001.
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GENERAL TECHNICAL REPORT PNW-GTR-837

Climate change is also likely to result in more disturbances from insects, 

invasive species, and diseases (Alig et al. 2004, Gan 2004, Logan et al. 2003). For 

example, Ryan et al. (2008) predicted an increase in the frequency and intensity of 

mountain pine beetle (Dendroctonus ponderosae) and other insect attacks, further 

increasing fire risk and reducing timber production. Insects, historically controlled 

by cold winters, more easily survive milder winters and produce larger populations 

in warmer climates. In a changing climate, populations of some pests such as 

red fire ants (Solenopsis invicta Buren), better adapted to a warmer climate, are 

projected to increase (Cameron and Scheel 2001, Levia and Frost 2004). Invasive 

weed species that disperse rapidly are likely to find increased opportunities under 

climate change. Pests can also impact rural communities and especially Native 

American communities by reducing the availability of nontimber forest products 

(NTAA 2009).

Damages to forest resources from pests can be significant. For example, spruce 

bark beetle (Dendroctonus rufipennis) outbreaks in the Kenai Peninsula of Alaska 

(red areas in fig. 3-13) have led to the loss of over 5 million acres of spruce forests. 

The recent spread of southern pine beetle (Dendroctonus frontalis Zimmermann), 

attributable, in part, to climate change, has affected sawtimber and pulpwood 

production in Alabama, Louisiana, Mississippi, Tennessee, Kentucky, and the 

Carolinas. On average, annual losses have reached over 1 percent of gross state 

product (Ruth et al. 2007). 

Changes in temperature and precipitation affect the composition and diversity 

of native animals and plants through altering their breeding patterns, water and 

food supply, and habitat availability (Feng and Hu 2007). Therefore, we expect 

increased extinction of local populations and loss of biological diversity if climate 

change outpaces species’ ability to shift their ranges and form successful new 

ecosystems. Residents of Alaska are likely to experience the most disruptive 

impacts of climate change in the near term, including shifts in the range or 

abundance of wild species crucial to the livelihoods and well-being of indigenous 

populations (Houser et al. 2001, Parson et al. 2001). 

Higher temperatures, decreased soil moisture, and more frequent fires may 

stress forest ecosystems and ultimately may lead to a conversion of some forests to 

savannah and grassland (Burkett et al. 2001). Grassland and plains birds, already 

besieged by habitat fragmentation, could experience significant shifts and reductions in their ranges (Peterson 2003). Biodiversity impacts of climate change may 

also alter distribution of prominent game and other bird species (e.g., waterfowl, 

warblers, perching bird species) in many recreational rural counties. The conversion of forest land, habitat fragmentation, and reduced hunting and birdwatching 
97

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

could have adverse impacts on forest-sensitive rural communities in terms of lower 

employment and income. 

Although current research suggests that timber supply will expand nationally, 

regional impacts are much more uncertain. A higher level of atmospheric CO2

in the atmosphere results in trees capturing more carbon from the atmosphere 

and higher growth rates in some regions, especially in relatively young forests on 

fertile soils (Ryan et al. 2008). This increased growth could be tempered, however, 

by local conditions such as moisture stress, nutrient availability, or increased 

tropospheric ozone (Karnosky et al. 2005, Triggs et al. 2004). In the absence of 

dramatic increases in disturbance, effects of climate change could result in larger 

timber inventories (Perez-Garcia et al. 2002). Climate change scenarios predicting 

increased harvests, however, tend to lead to lower prices and, as a consequence, 

reduced harvests in regions with higher production costs (Perez-Garcia et al. 2002, 

Sohngen and Sedjo 2005). Warmer winters with more sporadic freezing and thawing are likely to increase erosion and landslides on forest roads, and reduce access 

for winter harvesting (USGCRP 2009), in turn, increasing cost and reducing supply 

of forest products. Under these conditions, a shrinking forest industry would lead to 

loss of employment for many rural communities. 

Figure 3-13—Spruce forest loss in Kenai Peninsula, Alaska. Source: USGCRP 2009 based on 

Berman et al. 1999.
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The effect of climate change on forest-dependent communities will vary regionally. Wildfire risk is expected to be most severe in the Southwest and Northwest, 

largely because of higher summer temperatures and earlier spring snowmelt. Higher 

temperatures could lead to increased incidences of pest attacks and tree diseases all 

across the United States. Altered harvesting frequency and associated impacts on 

forest product prices could be felt nationwide. The impact, however, is expected to 

be higher in the timber-producing regions of the Southeast and old-growth forests of 

the West. 

Water resources—

Impacts of climate change on water resources could result in increasing incidences 

of droughts, changing precipitation intensity and runoff, lower availability of water 

for irrigation, changing water demands, and lower water availability for energy 

production. Incidences of drought have dramatically changed during the last 50 

years (fig. 3-14). Much of the Southeast and West have faced increases in drought 

severity and duration, while decreases have been observed in much of Midwest, 

Great Plains, and Northeast. 

Figure 3-14— United States drought trends, 1958–2007. Crosshatched areas have statistically 

significant trends. Source: USGCRP 2009 based on Guttman and Quale 1996. 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Limitations imposed on water supply by projected temperature increases 

are likely to be made worse by substantial reductions in rain and snowfall in the 

spring months, when precipitation is most needed to fill reservoirs to meet summer 

demand (Milly et al. 2008). The number of dry days between precipitation events is 

also projected to increase in the Southwest and the Mountain West, two of the most 

rapidly growing areas of the country. Continued population growth in these arid 

and semiarid regions would also stress water supplies, although the impact will be 

more severe for urban centers than rural counties. 

Floods are also projected to be more frequent and intense as regional and 

seasonal precipitation patterns change and rainfall becomes more concentrated 

in heavy events. For the past century, total precipitation has increased by about 7 

percent, while the heaviest 1 percent of rain events increased by approximately 20 

percent (Gutowski et al. 2008). In general, International Panel for Climate Change 

climate models agree that northern areas are likely to get wetter and southern areas 

drier. Figure 3-15 outlines projected average precipitation changes by the 2090s in 

terms of light, moderate, and heavy storm events. The lightest precipitation is projected to decrease, and the heaviest will increase, continuing the observed trends.

Figure 3-15—Projected changes in light, moderate, and heavy precipitation in North America (based 

on Intergovernmental Panel for Climate Change higher and lower emission scenarios). Source: 

USGCRP 2009 based on Gutowski et al. 2008.
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Climate change is also projected to cause changes in runoff, the amount of 

precipitation that is not evaporated, stored as snowpack or soil moisture, or filtered 

down to groundwater. Figure 3-16 shows that the eastern part of the country will 

experience increased runoff, accompanied by declines in the West, especially the 

Southwest. This means that wet areas are projected to get wetter and dry areas 

drier, thus adding to the woes of agricultural and forest-dependent communities 

whose livelihoods (or incomes) in many cases are sensitive to water availability. 

The farming-dominated counties in the Great Plains and Midwest, however, are 

not expected to experience as large an impact as their Northeastern, Western, or 

Southwestern counterparts.

Figure 3-16—Projected changes in annual runoff for 2041–2060 relative to 1901–1970 for emissions 

in between the lower and higher emissions scenarios. Crosshatched areas indicate greater confidence 

in projection because of strong agreement among model projections. White areas indicate divergence 

among model projections. Source: USGCRP 2009:45 based on Milly et al. 2008. 

Meeting the challenge of climate change has important implications for the 

United States in terms of intervention and resolution of intra- and intergroup conflicts. For example, decreased water availability in different regions of the country 

owing to increased temperature and lower or infrequent precipitation, along with an 

increase in water demand from increased population or agricultural activities, could 

produce more frequent and intense conflicts over water rights. The U.S. Bureau of 

Reclamation (2005) has identified many areas in the country that are already at risk 

for serious conflicts over water, even in the absence of climate change. Figure 3-17 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

shows regions in the West where water supply conflicts are likely to occur by 2025, 

based on a combination of factors such as population trends and endangered species 

need for water without factoring in climate change effects, which might exacerbate 

many of these conflicts. 

Rural communities engaged in activities like farming are expected to be under 

additional water stress from climate change. For example, climate change increases 

the chance of water-related conflicts in already water-scarce regions like the Great 

Plains and Southwest. Current water use in the Great Plains is unsustainable, as 

the High Plains aquifer continues to be tapped faster than the rate of recharge. 

Similarly, groundwater pumping is lowering water tables, and rising temperatures 

reduce riverflows in vital rivers (Barnett et al. 2008)

Figure 3-17—Likely water supply conflict regions in Western United States by 2025 without climate 

change effects. Source: USGCRP 2009 based on U.S. Bureau of Reclamation 2005.
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Energy—

With increasing pressure on existing energy sources, rural communities’ access to 

traditional energy sources could be threatened by climate change. Increased demand 

for energy as well as lower or uncertain supplies in many areas will accentuate such 

threats. Scott and Huang (2007) projected that temperature increases are likely to 

increase peak demand for electricity in most regions of the country. The energy 

demand for cooling is also expected to increase along with peak demands and higher 

temperatures. The increase in demand will be higher in the South, a region with especially high per capita electricity use (Scott and Huang 2007). The Southern region 

accounts for most of the persistently poor rural counties in the United States. Rural 

communities in the South might not be able to cope with the higher costs associated 

with increased demand, in turn increasing their vulnerability to climate change.

Renewable sources of energy, such as biomass-based energy, are already being 

promoted to increase energy supply, create jobs, reduce reliance on fossil fuels, and 

improve access to rural communities. The federal and state government incentives 

and mandates such as renewable fuel standards, blending incentives, research and 

development support, among others, are accelerating the process of making such 

energy sources commercially viable. The biomass-based energy markets could benefit rural landowners in terms of higher product prices as well as increased avenues 

for employment. 

Fisheries— 

America’s coastlines and fisheries are especially at risk from climate change. Fisheries feed local people and provide livelihood to rural communities and indigenous 

peoples in many parts of the country. The habitats of some mountain species and 

coldwater fish, such as salmon and trout, are very likely to contract in response to 

warming, whereas some warm-water fishes such as smallmouth bass (Micropterus 

dolomieu) and bluegill (Lepomis macrochirus) might expand their ranges (Janetos et 

al. 2008). Apart from changes in species composition and availability of native fish 

species, aquatic ecosystem disruptions are likely to be compounded by invasion of 

nonnative invasive species, which tend to thrive under a wide range of environmental 

conditions.

In Alaska, climate change is already causing significant alterations in marine 

ecosystems (fig. 3-18), restricting fisheries and adding to the hardships of the rural 

people who depend on them (USGCRP 2009). Historically, warm periods in coastal 

waters have coincided with relatively low abundances of salmon, and cooler ocean 

temperatures have coincided with relatively high salmon numbers (Crozier et al. 

2008). It has been estimated that as much as 40 percent of Northwest salmon populations may be lost by 2050 owing to climate change (Battin et al. 2007). 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Figure 3-18—Marine species shift in Alaska from 1982 to 2006. Source: USGCRP 2009 based on 

Mueter and Litzow 2007.

Climate change has caused alterations in marine ecosystems in Alaska.

Alaska leads the country in terms of its commercial and subsistence fishing 

catch. Most of the Nation’s salmon, crab, halibut, and herring come from Alaska. 

In addition, many native communities depend on local harvests of fish, walruses, 

seals, whales, seabirds, and other marine species for their food supply. Subsistence 

Bob Czaro
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fishing accounts for a large share of the food consumed in rural Alaska. The state’s 

rural residents harvest an average of 225 pounds of fish per person (U.S. Fish and 

Wildlife Service 2010). The warmer water is already leading to a lower catch of 

salmon in Alaska creating hardships on the rural people and indigenous tribes who 

are dependent on these fishes for subsistence or employment (NTAA 2009).

In the Northeast, lobster fisheries are projected to continue a northward 

shift, and the cod fisheries in the Northeast are likely to be diminished with 

increasing ocean temperatures associated with climate change (USGCRP 2009). 

The possibility of ocean acidification owing to climate change may also endanger 

fisheries in the Northeast. For example, increased acidification in Passamaquoddy 

and Cobscook Bays and Bay of Fundy threaten shellfish including clams, scallops, 

and lobsters. 

Climate change is also expected to reduce coral reefs and reef fish species 

(Graham et al. 2006). Changes in the species composition of coral reef ecosystems 

will likely have significant repercussions for both subsistence and commercial 

fishing in Hawaii, Puerto Rico, U.S. Virgin Islands, Guam, and American Samoa 

(Janetos et al. 2008). Change in fish availability owing to climate change may hit 

Guam and American Samoa particularly hard as almost all communities within the 

Pacific Islands derive between 25 and 69 percent of their animal protein from fish 

(Hotta 2000). The Southeast United States will most likely also observe a decline of 

wetland-dependent coastal fish and shellfish populations owing to the rapid loss of 

coastal marsh from rising sea levels associated with climate change (Zimmermann 

et al. 2002). 

Conclusions

The potential impacts of climate change on rural communities include increased 

risks to human health, changes to the agricultural and forestry sectors, stress on 

water resources and fisheries, increased conflicts over scarce resources, impacts on 

recreation and tourism, adverse effects on indigenous communities, and additional 

impacts related to an increase in adverse weather events. Directly or indirectly, 

positively or negatively, climate change will affect all sectors and regions of the 

country, although the impacts will not be homogenous across regions, sectors, 

population groups, or time. 

The impact of climate change on rural communities depends on complex 

interactions among different sectors, regions, and population groups and 

the environment. However, there is a dearth of information and literature 

on how the myriad socioeconomic and demographic factors will react to the 

biophysical changes accompanying climate change and virtually none on how 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

the interconnected socioeconomic/ecological systems will respond. Most of the 

current literature is based on such coarse temporal and spatial resolution as to 

offer only very general guidance for investment and policymaking. For example, 

understanding the economic effects of climate change on timber production is 

constrained by limited scientific understanding of several key factors that control 

the response of natural and managed forests to climate change. Timber production 

will depend not only on climatic factors but also on stresses from pollution (e.g., 

acid rain), future trends in forest management practices, economic demand for 

forest products, and land-use change. Clarification of the uncertainties concerning 

how all of these factors will interact in the face of climate change will permit more 

informed policy and programmatic responses to reducing the vulnerability of rural 

communities to the impacts of climate change. 

Climate change will affect rural communities through changes in availability 

or access to climate-sensitive resources that occur at local, regional, or national 

levels. The vitality of local communities (Hutton 2001, Jensen 2009, Wall et al. 

2005), changes in monetary conditions (Ikeme 2003), status of emergency facilities 

and preparedness and planning (Murphy et al. 2005), condition of the public health 

system (Kinney et al. 2001), and exposure to conflict (Barnett 2003) all have the 

potential to either exacerbate or ameliorate the vulnerability of rural communities 

to climate change. Vulnerability to climate change tends to be greater for rural 

communities who typically have fewer resources and fewer alternatives than urban 

areas. Therefore, the climate risk mitigation and adaptive capacity of rural communities remains an important area for public policy interventions and future research. 

A suite of adaptation and mitigation policy options needs to be developed to reduce 

vulnerability of rural communities under a variety of climate change scenarios.

In light of the potential impacts of climate change on rural communities, 

enhancing their coping and adaptive capabilities is crucial. However, public 

discussion about adaptation is at an early stage in the United States (Moser 2005). 

An active dialogue among stakeholders and political institutions could help clarify 

the opportunities for adapting to and coping with climate change. A significant 

difference in infrastructure needs between rural and urban areas suggests that 

research focusing on assessing rural communities’ adaptive capacity, costs and 

effectiveness of adaptation options, implementation impediments, and expected 

consequences is warranted.

Although much data on the biophysical impacts of climate change are already 

freely and readily available to a broad range of users, sociocultural and economic 

data and information related to how climate change will affect rural communities, 
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their resilience, and adaptive capacity are scarce. Developing effective data collection systems and analyses of these issues first requires agreed-upon baseline 

indicators and measures of environmental, demographic, and economic conditions 

that can be used to track the effects of changes in climate on rural communities 

(Karl et al. 2009). A set of regional studies is needed to improve our understanding 

of climate change impacts and the distribution of costs and benefits of the impacts 

across rural and urban communities in the United States, and to develop appropriate 

policies to mitigate the impacts. 

Acknowledgments

The authors thank the following reviewers for their helpful comments: Linda 

Langner, National Program Leader for the Resource Planning Act Assessment, 

J. Michael Bowker of the Southern Research Station, and Ellen M. Donoghue 

of Pacific Northwest Research Station, all of U.S. Forest Service, as well as G. 

Andrew Stainback of the Department of Forestry, University of Kentucky. 

Thanks also go to Jaganaddha Rao Matta, Forestry Officer of Finance, Food 

and Agricultural Organization of the United Nations for his helpful insights.

Metric Equivalents

When you know: Multiply by: To get:

Acres (ac) 0.405 Hectares

Pounds (lb) 454 Grams

Tons .907 Tonnes (metric tons)

Degrees Farenheit (°F) .55(°F – 32) Degrees Celsius

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119

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

D. Evan Mercer, Pankaj Lal, and Janaki Alavalapati 

Introduction

Growing concerns over the impacts of human-induced greenhouse gas (GHG) 

emissions have led U.S. policymakers to consider creating markets to regulate 

GHG emissions, although no bill has yet become law. For example, the House 

passed the American Clean Energy and Security Act (aka Waxman-Markey) on 

June 26, 2009, and three bills were submitted to the Senate in 2009 and 2010: the 

Clean Energy Jobs and American Power Act (Kerry-Boxer), the American Power 

Act (Kerry-Lieberman), and the Carbon Limits and Energy for America's Renewal 

Act (Cantwell-Collins). Waxman-Markey, Kerry-Boxer, and Kerry-Lieberman 

would create markets for emitting and offsetting carbon dioxide (CO2 ) and permit 

the purchase of up to 2 billion metric tons of carbon offsets annually.1 CantwellCollins would not allow emitters to purchase offsets; however, it would provide for 

the establishment of a trust fund to provide incentives—loans and grants to fund 

offset-like projects that reduce, avoid, or sequester GHG emissions through forestry 

and other land use initiatives. Appendix I provides a list of the eligible offset 

projects allowed in the 2010 American Powers Act (Kerry-Lieberman), the only 

current legislation to include a list of eligible offset projects. In addition to forestry 

and agricultural offset projects, potential offset projects include carbon capture and 

storage, methane collection, recycling and waste minimization, biochar production, 

and a variety of land management changes. 

Parry et al. (2007) estimated that 10 to 20 percent of the world's anticipated 

GHG emissions could be offset over the next 50 years through forest preservation, 

tree planting, and improved farming methods. Currently, forests, urban trees, and 

agricultural soils offset approximately 15 percent of total U.S. CO2

 emissions 

from the energy, transportation, and other sectors (USEPA 2009a). McCarl and 

Schneider (2001) suggested that an additional 3 to 5 percent of carbon sequestration 

per year could be achieved through changes in agricultural and forest management, 

tree planting, and biofuel substitution. However, the market for U.S.-based forest 

offset projects in the current, voluntary over-the-counter market remains small. For 

Chapter 4: Competiveness of Carbon Offset 

Projects on Nonindustrial Private Forest Lands 

in the United States

1

 Waxman-Markey allows 1 billion metric tons of offsets from domestic sources and 1 billion 

from international sources, and Kerry-Boxer allows 1.5 billion metric tons from domestic 

and 0.5 billion metric tons from international sources. If domestic sources are unable to 

satisfy the demand for offsets, however, the cap on international offsets can be raised to 1.5 

billion metric tons under Waxman-Markey and 1.25 billion under the Kerry-Boxer bill. 
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GENERAL TECHNICAL REPORT PNW-GTR-837

example, as shown in table 4-1, U.S.-based forestry carbon projects account for only 

4 percent of all carbon offset projects worldwide, 17 percent of all U.S.-based offset 

projects, and 15 percent of forestry projects worldwide (Carbon Catalog 2010). 

Table 4-1—Number of carbon offset projects by type: total worldwide, total in 

United States, and percentage United States represents for each category

Worldwide United States U.S.

Number Number Percentage

Offset project type of projects of projects of category

 Percent

Wind power 125 27 22

Forestry 114 17 15

Methane from animal biomass 67 22 33

Industrial methane 36 13 36

Fuel efficiency 25 2 8

Solar power 19 6 32

Fuel substitution 18 3 17

Efficient lighting 9 1 11

Efficient buildings 8 1 13

Hydroelectric power 6 1 17

Heat-electricity cogeneration 4 1 25

Material substitution 4 2 50

Public transportation 3 2 67

Geothermal 1 0 0

 Total 439 98 22

Source: Adapted from Carbon Catalog (2010).

The total amount and specific mix of offset projects will depend on the price 

of CO2 and the relative costs of implementing and managing the individual offset 

projects. With about 40 percent of the 303 million ha (749 million acres) of U.S. 

forest land owned by nonindustrial private forest (NIPF) landowners (Smith et al. 

2009), assessing the potential of NIPF lands to sell carbon offsets vis-à-vis other 

options is crucial to developing appropriate carbon offset and forestry policies and 

programs. Therefore, the objective of this paper is to review the available literature 

to assess the viability of U.S. forest offset projects relative to alternative carbon offset options to develop a better understanding of how NIPF landowners will respond 

should Congress pass carbon cap-and-trade legislation. Although a relatively large 

literature has emerged over the past two decades concerning the costs for a wide 

variety of carbon offset projects, most of the analyses are sector wide and few, if 

any, have been directed at the circumstances facing NIPF landowners. In this paper, 

we review the larger literature on cost of carbon offset projects and make inferences 

about NIPF lands. 
121

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Forestry-Based Carbon Offset Projects

Forests sequester carbon in their biomass through photosynthesis in which CO2 is 

absorbed from the atmosphere and stored in roots, stems, leaves, and branches of 

trees; understory plants; floor litter; and soils. Additional carbon can be sequestered 

by forests through afforestation, reforestation, or changes in forest management. 

Afforestation consists of planting trees on previously nonforested lands (e.g., 

conversion of marginal cropland to trees), whereas reforestation is the replanting of 

trees on previously forested lands, excluding the planting of trees immediately after 

timber harvests (USEPA 2009a). Forest management offset projects modify existing 

forestry practices to enhance carbon storage over time. Examples include lengthening the harvest-regeneration cycle, increasing management intensity, fire control, 

fertilization, altering stocking densities, choosing alternative tree species, reducing 

dead biomass removal, reducing harvest intensity, and adopting low-impact logging 

(Adams et al. 1999, Im et al. 2007, Shaikh et al. 2007, Sohngen and Mendelsohn 

2003, Stainback and Alavalapati 2002, USEPA 2009a). Agroforestry2

 systems can 

also be used to increase carbon sequestration on agricultural lands (Schoeneberger 

2005). 

Figure 4-1 illustrates Gorte and Ramseur’s (2008) estimates from EPA’s (2005: 

C4 p. 21) use of the FASOM-GHG model (see chapter 2) (Adams et al. 2010) of the 

relative amounts of GHG mitigation from afforestation and improved forest management that may occur at various CO2e prices. At a CO2e price of $50 ($15) per 

metric ton (mmt), more than 800 (100) mmt of CO2e could be sequestered through 

afforestation activities, and approximately 380 (210) mmt through improved forest 

management activities. Table 4-2 shows the amount of land (and percentage of total 

U.S. agricultural, rangeland, and private forest land) required to sequester 100 to 

800 mmt of CO2e. The values in table 4-2 are based on average rates of sequestration from afforesting nonforest land or through changes in forest management on 

private forest lands from Lewandrowski et al. (2004) and USEPA (2005) and land 

use data from the USDA Natural Resources Inventory (USDA NRCS 2003).

The United States currently has a total of 729 million ha of undeveloped lands 

that could be used for forest based carbon sequestration (149 million ha of crop and 

pastureland, 164 million ha of rangeland, and 164 million ha of private forestland). 

Afforesting enough land to sequester 100 to 800 mmt C would require planting 

trees on 25 to 203 million ha of land, 13 to 103 percent of all cropland or 53 to 430 

percent of all rangeland. This would represent an increase of private forest land in 

2

 Agroforestry is a joint forest production system whereby land, labor, and capital inputs 

are combined to produce trees and agricultural crops (or livestock) on the same unit of land 

(Mercer and Pattanayak 2003).
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GENERAL TECHNICAL REPORT PNW-GTR-837

Figure 4-1—Estimated U.S. greenhouse gas mitigation totals for afforestation and forest management: annualized averages, 2010–2110. Source: EPA 2005, Gorte and Ramseur 2008.

the United States by 15 to 124 percent, an unprecedented change in land use in the 

United States for which the economic and ecological repercussions are unknown. 

The most recent report on tree planting on all lands in the United States showed 1.1 

million ha (2.6 million acres) planted in 1997 (Gorte 2009b). Using changes in 

forest management to sequester 100 to 800 mmt C would require changes in management on 83 to 664 percent of all private forest lands in the United States.

Table 4-2—Land required for carbon sequestration by 

afforestation and management

Sequestered carbon

(million metric tons)

Carbon offset strategy/land area 100 400 800

Afforestation:

Land required (million ha) 25.4 101.6 203.2

U.S. agricultural land (percent) 12.9 51.7 103.5

U.S. range land (percent) 53.6 214.5 429.0

U.S. private forest land (percent) 15.5 61.8 123.6

Forest management:

Land required (million ha) 33.8 135.1 270.1

U.S. private forest land (percent) 20.5 82.2 164.4

Sources: Lewandrowski et al. 2004, USEPA 2005, USDA NRCS 2003.

900

800

700

600

500

400

300

200

100

0

CO2e (million metric tons)

1 5 15 30 50

Average CO2e price (dollars/metric ton of CO2e)

Afforestation

Forest management
123

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Figure 4-2—Variation in average carbon stock in different biomes. Source: IPCC 2005. Adapted from Gorte (2009a).

Avoiding emissions by preventing the conversion of forest to nonforest 

land may also earn offset credits under several of the cap-and-trade proposals. 

Dedicating lands to continuous forest cover can be established through processes 

such as long-term conservation easements or transferring forest ownership to the 

government (CAR 2009). However, the challenge for avoided deforestation projects 

lies in establishing that forest-land use was threatened by logging or clearing. 

Compared to reforestation and afforestation, few studies have examined carbon 

sequestration through avoided deforestation in the United States (Baral and Guha 

2004, Langpap and Kim 2010). 

Factors Influencing Forestry Offset Projects

A number of factors influence the potential for forest offset projects to reduce GHG 

emissions including tree species and site characteristics, management practices, 

longevity of wood products and disposal methods, opportunity costs of land, 

discount rates, and forest and agricultural prices. These factors result in wide 

variation in generated GHG mitigation benefits as well as per-unit costs of forestbased GHG reduction. 

The ability to sequester carbon in plants and forest soils differs across biomes 

as shown in figure 4-2. Hardwood (e.g., oak-hickory), softwood (e.g., southern pine, 

Douglas-fir), and mixed pine-hardwood (e.g., oak-pine) temperate forests are the Carbon stock (metric tons/hectare)

Soils

Vegetation

900

800

700

600

500

400

300

200

100

0

Tropical

forest

Temperate

forest

Boreal

forest

Tundra Cropland Savanna Temperate

grassland

Desert/

semidesert

Wetland Weighted

average

Soils

Vegetation

136

133

106

62

378

72

141

7

89

2

128

32

259

7

47

2

709

47

146

35
124

GENERAL TECHNICAL REPORT PNW-GTR-837

predominant forest types in the contiguous United States. The carbon sequestered 

in these types of forests is lower than tropical forests found in the United States 

(e.g., Hawaii, Puerto Rico, Virgin Islands, Guam, Samoa) and boreal forests in 

Alaska and Canada. Within a biome, carbon sequestration potential differs across 

species, climate, soil type, forest age, location, and previous land use. Figure 4-3 

illustrates the average distribution of carbon in different components of the forest. 

Forest soils and vegetation 

account for most of the carbon 

accumulated in forests, 59 and 31 

percent, respectively.

Rates of carbon sequestration 

vary widely across the United 

States, ranging from 2.0 to 

10.3 t/ha (0.9 to 4.6 tons/acre) 

per year (Stavins and Richards 

2005). Fast-growing, long-lived 

tree species would be preferred 

for carbon sequestration and 

storage. However, few species 

have both characteristics. The 

choice is generally between younger, faster growing trees and older, slower growing 

stands. Whether slower growing trees can potentially store more carbon over time 

owing to longer lives depends on a number of factors including geography, site 

characteristics, management and harvesting regimes, and how the harvested wood 

is used. For example, Stavins and Richards (2005) showed that carbon sequestration 

in a southern loblolly pine (Pinus taeda L.) plantation peaks at 10.1 t/ha (4.5 tons/

acre) per year and then declines rapidly and becomes insignificant after 70 years. 

Ponderosa pine (Pinus ponderosa C. Lawson) grown in the Mountain States 

sequesters carbon at a more gradual rate peaking at about 6.7 t/ha (3 tons/acre) 

per year in year 65 and then declining slowly over the next 100 years. Although 

ponderosa pine may sequester substantially more carbon than loblolly over the 

lifetime of the plantation, the carbon uptake occurs much sooner with loblolly. 

Therefore, species and site choice will depend on the desired timeframe for 

sequestering carbon. 

Within a geographic region, site characteristics play a large role in carbon 

sequestration potential. Generally, all other things equal, sites with higher site 

indices will sequester more carbon than those with lower site indices. In addition, 

less management effort is usually required in higher quality sites resulting in lower 

Figure 4-3—Average carbon distribution among forest 

components. Source: Birdsey 1992.

Forest soils

(59%)

Trees

 (31%)

Forest litter (9%) Understory (1%)
125

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

marginal costs making the offset projects more lucrative to the landowner. However, species differ in their nutrient needs and growth attributes so that a site that is 

high quality for one species may not be for other species. 

Management Practices

Although most agree that creating new forests through reforestation or afforestation 

or avoiding the deforestation of existing forests are the most direct and least controversial methods for increasing forest carbon sequestration, many believe that there 

are relatively few opportunities for large-scale reforestation in the United States 

(Gorte 2009b, Plantinga et al. 1999, Ray et al. 2009). Because the carbon storage 

potential of forests depends, in large part, on how the forest is managed, a considerable debate has emerged recently concerning the feasibility of increasing carbon 

sequestration and storage through changes in forest management.

Forest management practices influence biomass levels, growth patterns of 

trees, and structure and composition of soils and understory, all of which directly 

impact carbon sequestration and storage. Actions like thinning (removing some 

trees to increase growth of desired species) and release (killing competing vegetation chemically or mechanically) may increase carbon sequestration rates by 

reducing competition for light and nutrients (Gorte 2009a). Newell and Stavins 

(2000), however, predicted that periodic harvests may increase sequestration costs. 

Others argued that thinning or release cuts selectively increase total carbon storage 

in young stands with severe competition, but in other cases, the carbon storage is 

simply redistributed to fewer large trees (Smith et al. 1997). 

The impact of prescribed fire on carbon sequestration remains unclear. In the 

near term, prescribed fires lead to increased carbon emissions in the atmosphere. 

Low-intensity prescribed fire usually results in little change in soil carbon, but 

intense prescribed fire or wildfire can result in significant soil carbon loss (Johnson 

1992). Empirical evidence, however, suggests that prescribed burning reduces both 

the risk of wildfire and the intensity of wildfires, both of which could reduce carbon 

emissions (Gorte 2009a, Mercer et al. 2007). 

It is possible that harvesting timber from mature forests could increase 

carbon sequestration as young trees grow faster and sequester carbon faster than 

older trees. However, this depends on how the harvested wood is utilized and 

the harvesting methods used. Long-lived products like furniture or construction 

materials can sequester carbon over long periods. However, if the wood is burned as 

fuel or converted into pulp, paper, or other short-lived products, the carbon will be 

returned to the atmosphere relatively quickly. Therefore, Perez-Garcia et al. (2005) 

argued that intensive management, short rotations, and substituting the harvested 
126

GENERAL TECHNICAL REPORT PNW-GTR-837

wood for more energy-intensive building materials may result in a substantial net 

reduction in atmospheric carbon. Most of the reduction is due to increasing the rate 

of product substitution rather than by storing more carbon in trees. 

If product substitution does not occur, it appears that “passive” forest management may sequester more carbon than intensive forest management because of 

interactions among storage and uptake rates, basic production ecology, conversion 

efficiencies from trees to wood products, fuel used for harvesting and management 

operations and transporting wood to mills and markets, and the dynamics of longterm storage (Perez-Garcia et al. 2005, Ray et al. 2009). Others suggested that harvesting may actually increase the cost of forest-based carbon sequestration (Newell 

and Stavins 2000, Plantinga and Mauldin 2001, Plantinga et al. 1999). Additional 

studies are required to determine the conditions under which forest harvesting leads 

to a net increase or decrease in carbon sequestration. 

Product Longevity

The amount of carbon stored in wood products is determined by the type of product 

and how the products are used. For example, wood used for residential construction can have a usable life of 100 years, whereas paper products generally have a 

usable life of less than a year (Skog and Nicholson 1998). In addition to the carbon 

stored (and eventually released) in wood products, a full accounting should include 

carbon emissions produced during primary and secondary processing, maintenance, repairs, and disposal. Figure 4-4 illustrates Ingerson’s (2009) estimate of 

carbon loss from harvesting wood for a variety of uses. Solid wood products are 

expected to lose almost 99 percent of the carbon in standing trees within 100 years. 

However, Ingerson fails to account for the “substitution benefit” of wood compared 

to petroleum-based products. Although accounting for carbon in products results 

in a modest increase in carbon storage, including the substitution for more energyintensive products such as steel or concrete dramatically increases the amount of 

avoided carbon emissions (Baral and Guha 2004, CORRIM 2009). 

Figure 4-5 depicts carbon storage in forests in terms of short- and long-lived 

products, displacement of fossil fuels, and harvesting and processing emissions for 

an 80-year rotation. Although the substitution effect is initially about the same as 

the carbon stored in wood products, over time, the substitution effect dominates. 

Estimating the total carbon impact of wood products requires data on (1) GHG 

(carbon) loss occurring at each step in the processing chain from tree harvest to 

final wood product conversion; (2) carbon emissions resulting from machinery 

use, transportation, transformation into various products, customer delivery, and 

disposal into landfills; and (3) carbon savings owing to substitution of wood for 
127

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Figure 4-4—Carbon loss from standing trees to products. Source: Ingerson 2009.

Figure 4-5—Carbon in the forest and product pools, including substitution for concrete construction, for 80-year rotation. 

Source: CORRIM 2009. 

100

90

80

70

60

50

40

30

20

10

0

Standing tree carbon remaining (percent)

Total tree Minus

logging

losses

Minus

fuelwood

Minus pulp Minus

primary

mill waste

Minus

secondary

mill and

construction

Minus 100

years in use

Net CO2 equivalent in active processing chain

Net CO2 equivalent stored in landfill wood

800

700

600

500

400

300

200

100

0

-100

Metric tons per hectare

Year

Harvest and processing emissions

Forest carbon

pools

Substitution

Long-lived products

Chips

20002010202020302040205020602070208020902100

2110

21202130214021502160

Biofuel

Substitution

Displacement

Manufacturing emissions

Harvest emissions

Lumber

Chips

Dead

Litter

Crown

Root

Stem
128

GENERAL TECHNICAL REPORT PNW-GTR-837

high-carbon products such as concrete and steel. However, product substitution is 

not likely to qualify as offsets in cap-and-trade programs in which steel, cement, 

and petroleum are all regulated sectors. 

Opportunity Cost of Land and Discount Rates

The opportunity cost of land, the forgone monetary return from the land in its 

next best use, is the most important factor in the large variation in the cost of 

forest offset projects (Stavins and Richards 2005). A number of factors influence 

the opportunity cost of the land including location, fertility, existing use, climate, 

market availability, and estimation method. Estimates of the opportunity cost of 

land have varied from $0 to $8,400 per ha (Moulton and Richards 1990, New York 

State 1991). Some studies factor in anticipated increases in agricultural land prices 

along with carbon sequestration program expansions and associated reductions in 

nonforestry land use. The resulting opportunity costs of land range between $274 to 

$5,070 (Richards et al. 1993) and $116 to $6,170 per ha (Richards 1997). Typically, 

carbon sequestration cost estimates in studies that incorporate opportunity costs 

of land tend to be 2 to 3.5 times higher than others (Manley et al. 2005) and when 

included, increase total costs by about $25/t of CO2 equivalents (CO2e),3

 on average 

(van Kooten and Sohngen 2007). 

Stavins and Richards (2005) provided a useful summary of the impact of 

including opportunity costs in three estimation methods: (1) bottom-up engineering 

cost studies, (2) optimization models that analyze behavioral responses in the forest 

and agricultural sectors, and (3) econometric analyses of the revealed preferences 

of landowners for allocating their land to forestry or other alternative land uses. 

Engineering studies tend to use average of opportunity costs (e.g., average rents for 

agricultural lands) to estimate the forgone profits from alternative land uses and 

combine these with tree planting costs to produce a total cost estimate. Sectoral 

optimization studies use the same basic approach as the engineering studies but 

also include indirect costs of carbon sequestration programs between different 

sectors of the economy. For example, if land is converted from agriculture to forest 

owing to the carbon offset program, the lowered supply of agriculture land may 

result in increases in agricultural land prices. This would provide incentives for 

landowners to convert non-carbon-project forest land to agriculture producing a 

“leakage” of the sequestered carbon. 

3

 1 $US/t C = 3.67 $US/t CO2e.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Figure 4-6 illustrates the effect of including the direct costs of land in estimating the impact of prices on forest offset projects. The sector optimization studies 

(McCarl and Schneider 2001, USEPA 2005) account for both direct costs and 

the indirect effects on land and other markets, whereas the engineering studies 

(Moulton and Richards 1990, Richards 1997) only include direct costs. As a result, 

the engineering studies find significantly greater sequestration at all prices. 

Figure 4-6—Estimates of the annual carbon sequestration through afforestation in the United States 

at different carbon dioxide (CO2

) prices. EPA 2005 = USEPA 2005; ERS 2004 = Lewandrowski et 

al. 2004; MS 2001 = McCarl and Schneider 2001; R 1997 = Richards 1997; MR 1990 = Moulton and 

Richards 1990. Source: CBO 2007.

In contrast, econometric studies are based on actual landowner responses to 

market conditions. These are also referred to as revealed preference approaches 

because they use the behavior of landowners to reveal their preferences between 

different land uses given changes in relative forest and agricultural prices. This 

approach allows researchers to include a number of additional indirect factors that 

may influence carbon offset project costs such as uncertainty of the irreversibility 

of some land use changes, option values, nonmarket benefits (e.g., recreation, 

aesthetics, biodiversity), liquidity constraints, and other benefits or costs associated 

with alternative land uses (Stavins and Richards 2005). Typically econometric 

studies tend to produce higher cost estimates than the engineering or sectoral 

optimization approaches.

The discount rate also affects the relative cost of offset projects because of 

the long time horizons for carbon sequestration (Stavins and Richards 2005). The 

discount rate is simply a particular rate of interest used to bring past or future costs 

70

60

50

40

30

20

10

0

Price of CO2 (dollars per metric ton)

CO2 equivalents sequestered (million metric tons)

0 500 1,000 1,500 2,000 2,500 3,000

Sector

Optimization

Study

(MS 2001)

Sector

Optimization

Study

(EPA 2005)

Sector

Optimization

Study

(ERS 2004)

Engineering

Study

(R 1997)

Engineering

Study

(MR 1990)
130

GENERAL TECHNICAL REPORT PNW-GTR-837

or benefits to the present. Discount rates affect cost estimates by producing changes 

in (1) the present value of economic variables such as the value of forgone future 

revenues from harvests, (2) the optimal rotation or harvest age, and (3) the present 

value of future carbon flows (Stavins and Richards 2005). 

One difficulty in comparing forest offset cost estimates is the wide variation 

in discount rates. For example, a discount rate of 10 percent was used by Moulton 

and Richards (1990), New York State (1991), and Adams et al. (1993); 7 percent 

by Creyts et al. (2007); 5 percent by Stavins (1999) and Plantinga et al. (1999); 

and 4 percent by Parks and Hardie (1995) and Alig et al. (1997). Probably the best 

approach is to apply a range of discount rates (e.g., 0, 2, 5, and 8 percent) to determine the sensitivity of the results to the discount rate (Richards 1997). For example, 

Richards et al. (1993) found that increasing the discount rate from 3 to 7 percent 

doubled the marginal cost of sequestration. However, van Kooten and Sohngen 

(2007) found that the discount rate had no statistically significant influence on 

financial costs in their meta-analysis of 68 forest offset cost studies. They attribute 

this to the fact that most of the financial costs occur in the earliest years of forestry 

projects, reducing the importance of discounting.

Price Effects of Forest and Agricultural Products 

As landowners can switch between agriculture and forest land uses in search 

of higher profits, changes in prices for agricultural and forest products play an 

important role in evaluating the potential role and competitiveness of forest offsets. 

However, the direction of the effect is not always simple or as one might expect. For 

example, an anticipated increase in future forest product prices compared to agriculture reduces the opportunity cost of forest land and in turn reduces the marginal 

cost of carbon sequestration and vice versa. Higher forest prices, however, may also 

produce more frequent harvesting, which may increase sequestration costs (Stavins 

and Richards 2005). Furthermore, Adams et al. (1993) showed that large-scale conversion of agricultural lands to forestry would produce higher agricultural prices 

relative to timber prices, which in turn would incentivize landowners to convert 

their forest land back to agriculture. Newell and Stavins (2000) found that increases 

in forest land area owing to carbon sequestration subsidies do not necessarily result 

in continuous increases in carbon storage if the reduced supply of agricultural 

lands results in higher agricultural prices. They also found that higher agricultural 

product prices lead to a substantial amount of deforestation, which would at least 

partially negate the impact of policies subsidizing forest offset projects. 
131

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Transaction Costs

Transaction costs of offset projects typically include consulting fees, search and 

feasibility fees, planning, project documentation, monitoring and verification 

fees, process determination expenses, insurance charges, and negotiation fees. 

The transaction flow for a typical forest offset project is illustrated in figure 

4-7. Economies of scale hold for transaction costs associated with offset projects 

because fixed costs (e.g., administrative fees) remain constant, while variable costs 

decrease with increasing project size (Mooney et al. 2004). As a result, smaller 

NIPF landowners generally will have to enter into contracts with aggregators to 

remain competitive with larger projects. 

Figure 4-7—Transaction flow for typical forest offset project. Source: Haller and Thoumi 2009. 

Validator 

and verifier

Dollars 

(offset charge)

Project 

developer

Dollars 

(offset sale)

Offset 

buyer

Percentage

from 

offset sale

Landowners

Galik et al. (2009a) analyzed a hypothetical forest management offset project 

under multiple accounting methodologies or protocols for a period of 100 years and 

estimated median transaction costs to be $1.63/t CO2e sequestered across different 

regions, forest types, project sizes, and rotation extension lengths. They found that 

forest offset transaction costs differ by protocol and tend to decrease with project 

size and length of rotation and that transaction costs can be significant for small 

forest management offset projects. They conclude that although transaction costs 

are important, they appear to be less of a factor than the actual accounting scheme 

(e.g., baselines, leakage, permanence) under which the project is operating. Furthermore, the rules and regulations that would operate under a federal compulsory 

carbon market regime are still uncertain. Methodology standardization and greater 

institutional infrastructure will tend to reduce transaction costs and investor uncertainty, whereas more stringent and complex rules and regulations could increase 

these costs. 
132

GENERAL TECHNICAL REPORT PNW-GTR-837

Cost Comparison of Offset Projects

Forest Offsets

The many issues, underlying assumptions, and factors discussed above result in 

a wide variation in the cost estimates of forest offset projects. For example, in a 

meta-regression analysis of 68 studies, van Kooten and Sohngen (2007) found that 

total costs ranged from about $2 to $280/t CO2e. European projects were the most 

expensive, $48 to $280/t CO2e, with costs typically $212 higher than elsewhere for 

similar projects.4 Tropical projects in developing countries, where land and labor 

costs are low and tree growth rates rapid, are the least expensive ($2 to $35/t CO2e), 

and U.S. based forest offset projects are competitive ranging from about $2 to $77/t 

CO2e (van Kooten and Sohngen 2007). 

Scientists at Resources for the Future have developed a forest carbon index 

to analyze the potential of “every piece of land on Earth” to sequester and store 

carbon in forests (Deveny et al. 2009). The index combines geographic spatial data 

with forest market data (prices, quantities, revenues), opportunity costs, carbon 

sequestration potential, investment risks, and cost for government to rank areas 

and nations according to their likelihood for generating and selling forest carbon 

credits. First, Deveny et al. (2009) estimated the average cost for forest carbon 

sequestration for all sources in all countries assuming a market price for carbon less 

than $20/t CO2e. Average forest carbon offset costs range from $2.11/t CO2e in the 

Congo to $18.95/t CO2e in Lichtenstein. The United States has the 25th lowest cost 

($7.64 t CO2e) out of 109 countries studied.

The Forest Carbon Index (FCI) combines each country’s carbon offset profit 

potential (based on average cost and available lands) with risk factors to rank the 

best places to invest in forest carbon on a 100-point scale. Brazil is the top ranked 

country (FCI = 100) owing to a combination of high profit potential and low risk. 

The remaining top 10 countries are Peru (FCI = 95), Bolivia (94), Columbia (93), 

Indonesia (92), Republic of Congo (92), Russia (91), Central African Republic (91), 

Democratic Republic of Congo (91), Gabon (91), and Guyana (91). The United 

States ranks 30th with an FCI of 85. Other temperate zone countries include 

Canada, ranked 15th with an FCI of 89, and Sweden, Finland, and Australia, all 

with FCIs of 81 and ranked 40th in the world. Deveny et al. (2009) concluded that 

10 countries (Democratic Republic of Congo, Brazil, Angola, Central African 

Republic, Republic of Congo, Bolivia, Peru, Gabon, Russia, and Cameron) account 

for 70 percent of the global profit potential for selling carbon credits.

4

 Van Kooten and Sohngren (2007) speculated that the lack of competitiveness of forest 

offsets in Europe may explain why Europe has opposed using biological sinks to offset 

carbon emissions.
133

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Table 4-3—Costs (in 2005 dollars) of removing atmospheric carbon dioxide (CO2) through afforestation 

offset projects 

Cost

Total Total Per Per Per Discount Study

Forest carbon sink studies carbon area hectare t carbon t CO2 Estimation method rate location

Million Million - - - - - - - Dollars - - - - - - - Percent

metric hectares

tons

Adams et al. 1993 140 59 442.28 73.2 19.94 Sector optimization 10 U.S.

 model

Adams et al. 1999 2023.08 145.6 401.52 29.16 7.95 Sector optimization 4 U.S.

 model

Baral and Guha 2004 316.75 1 18 602.34 63.3 17.25 Bottom-up approach N/A U.S. South

Callaway and McCarl 1996 119.32 29.62 143.39 34.09 9.29 A modified version of 10 U.S.

 the Agricultural

 Sector Model (ASM)

Dixon et al. 1994 5.98 0.03 180.72 4.73 1.29 Bottom-up calculations 4 Oregon, Utah

McCarl and Callaway 1995 243.88 47.39 383.74 72.36 19.72 Sector optimization 10 U.S.

through modified ASM

New York State 1991 0.5 0.8 17.33 29.51 8.04 Bottom-up calculations 10 New York

Parks and Hardie 1995 29.96 6.58 967.26 260.29 70.92 Engineering cost 4 U.S.

 curve approach

Plantinga and Mauldin 2001 41.55 0.28 5457.4 36.28 9.89 Econometric 5 Maine, South

 estimation method Carolina,

 Wisconsin

Plantinga et al. 1999 12.8 0.19 4596.33 67.61 18.42 Econometric 5 Maine, South

 estimation method Carolina,

 Wisconsin

Richards et al. 1993 42 903 86.4 3446.72 6.94 1.89 Engineering cost 5 U.S.

 curve approach

Average 4167 34.26 3149 61.59 16.78

Median 119.32 6.58 442.28 36.28 9.89

Minimum 0.50 0.03 17.33 4.73 1.29

Maximum 42 903 145.60 18 602 260.29 70.92

Standard deviation 12 262 45.13 5233 67.06 18.27

Source: Adapted from van Kooten and Sohngen (2007).

Tables 4-3 and 4-4 present cost estimates from 15 studies of 11 U.S. afforestation offset projects and four forest management offset projects, respectively. Further 

details on the individual studies can be found in appendix 1. 

Costs for afforestation projects ranged from $1.29 to $70.92/t CO2e with an 

average of $16.78/t CO2e and median of $9.89/t CO2e. Although the range of cost 

estimates for forest management projects was smaller ($12.16 to $49.35/t CO2e), 

the average and median costs were higher at $27.65/t CO2e and $24.54/t CO2e, 

respectively. This suggests that, in general, afforestation projects will be more cost 

competitive than forest management projects. Likewise, Sohngen and Mendelsohn 

(2003) predicted that sequestration costs would be higher for forest management 

projects compared to afforestation projects. 
134

GENERAL TECHNICAL REPORT PNW-GTR-837

Table 4-4—Costs (in 2005 dollars) of removing atmospheric carbon dioxide (CO2) through forest management 

offset projects 

Cost

Total Total Per Per Per Discount Study

Forest carbon sink studies carbon area hectare t carbon t CO2 Estimation method rate location

Million Million - - - - - - - Dollars - - - - - - - Percent

metric hectares

tons

Huang and Kronrad 2001 0.06 0 838.78 44.63 12.16 Average cost of carbon 2.5–15 Texas storage calculated through optimal rotation age, different interest rate, and site index

Sohngen and Brown 2006 2.28 0.22 1921.95 130 35.42 Engineering cost 6 U.S. South 

 curve approach and West

Sohngen and Haynes 1997 29 198 7.34 50.1 13.65 Linking forest fire 5 Contiguous mortality model to U.S. forest inventory model

Newell and Stavins 2000 7.66 2.07 699.79 181.13 49.35 Econometric estimation 5 Arkansas, 

 approach Louisiana,

 and 

 Mississippi

Average 9.75 50.07 866.97 101.47 27.65

Median 7.66 2.07 838.78 101.47 24.54

Minimum 0.06 0.00 7.34 44.63 12.16

Maximum 29.00 198.00 1921.95 181.13 49.35

Standard deviation 11.45 85.41 685.69 57.07 15.55

Source: Adapted from van Kooten and Sohngen (2007). The cost estimates in the table are drawn from meta regression analysis. As studies in 

their sample provided multiple estimates of one or more projects or regions, the averaged values across a study were calculated by van Kooten and 

Sohngen (2007). 

Although most studies calculate average costs (total project cost divided by the 

number of units of CO2e sequestered), a more useful measure is the marginal cost 

(the cost of reducing one additional unit of CO2e). In contrast to average costs, marginal cost analysis allows the cost to change with market situations. For example, 

Stavins and Richards (2005) used a normalized set of forest studies and a 5-percent 

discount rate to find that 300 million metric tons of carbon can be sequestered at 

a carbon price of $7.50 to $22.50 per metric ton of CO2e but that as the amount of 

sequestration increases, e.g., to 600 million metric tons per year, the marginal cost 

increases significantly. 

Agriculture Offsets

Agricultural projects can produce carbon credits in two ways, increasing the 

amount of carbon sequestered in the soil or implementing management practices 

that reduce the amount of agricultural emissions. Activities that increase carbon in 

the soil include altered tillage practices (e.g., low tillage or no tillage), planting winter cover crops and other practices to increase biomass returned to the soil, rotating 
135

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

crops, converting monocultures to diverse systems, reducing carbon emissions from 

organic soils, and establishing perennial vegetation on steep slopes. Projects aimed 

at reducing emissions include reducing nitrogen fertilizer use or increasing nitrogen 

use efficiency, changing frequency and duration of flooding of rice paddies, and, 

reducing GHG emissions from manure and effluents owing to changes in animal 

management practices, including dietary modifications. 

Figure 4-8 provides the Congressional Budget Office (CBO 2007) comparison 

of estimates of annual per-unit sequestration costs for agricultural sector offset 

projects by McCarl (2007), USEPA (2005), McCarl and Schneider (2001), and 

Lewandrowski et al. ( 2004). All the studies in figure 4-8 used sector optimization 

techniques and include both direct and indirect (opportunity) costs in their analyses.

Figure 4-8—Estimates of the annual carbon sequestration from U.S. croplands at different carbon 

dioxide (CO2

) prices. M 2007 = McCarl 2007; EPA 2005 = USEPA 2005; ERS 2004 = Lewandrowski et al. 2004; MS 2001 = McCarl and Schneider 2001. Source: CBO 2007.

140

120

100

80

60

40

20

0

Price of CO2 (dollars per metric ton)

CO2 equivalents sequestered (million metric tons)

0 50 100 150 200 250 300

M 2007

ERS 2004

EPA

2005

MS 2001

Initially when the price of CO2 is below $15, sequestration and associated costs 

are quite low. However, costs rise rapidly as more agricultural sequestration takes 

place and more valuable and productive land would be required to increase sequestration, resulting in a backward bending supply curve. The upper bound of carbon 

sequestration potential from agriculture is reached at a price between $15 and $20/t 

CO2. However, the projected amount of sequestration at different prices differs 

widely among the studies in figure 4-8. For example, at a price of $10/t CO2, the 

projected amount of carbon sequestered ranges from about 10 to 260 million metric 

tons, and at a price of about $40, estimated carbon sequestered ranges from 80 to 

190 million metric tons. 
136

GENERAL TECHNICAL REPORT PNW-GTR-837

Table 4-5 provides a summary of studies providing estimates of sequestration 

costs for a variety of agricultural offset projects including no tillage, conservation 

tillage, shifting from crops to grass, and shifting to continuous cropping. Costs 

range from about $2 to $215/t CO2e with an average of $64.93 and median of 

$55.90/t CO2e. 

Table 4-5—Costs (in 2005 dollars) of removing atmospheric carbon dioxide CO2 through agricultural offset 

projects

Cost Discount Study

Type of offset project Range Average Estimation method rate location Citations

- - - - - $/t CO2 e - - - - - Percent

No tillage agriculture 68.62 to 360.98 214.80 Econometric model linked N/A Iowa Pautsch et al. 2001 with a biophysical model to get changes in soil carbon

Reduced tillage 3.08 to 154.46 78.77 The ASMGHG model—a 4 U.S. McCarl and

 market and spatial equilibrium Schneider 2001

 sector optimization model

No till versus 1.68 to 153.93 77.81 Experimental yields, input N/A Kansas Pendell et al. 2006

conventional tillage rates, field operations, and prices simulate a distribution of net returns for production systems

Conservation tillage 3.31 to 41.43 22.37 The U.S. Agricultural Sector 5 U.S. Lewandrowksi et al. 

 Model (USMP), a spatial and 2004

 market equilibrium model

No tillage 0.53 to 2.74 1.64 Meta-regression analyses of 52 N/A South Manley et al. 2005

 studies of net returns and 51

 studies of carbon soil uptake

No tillage 44.31 to 113.00 78.66 Meta-regression analyses of 52 N/A Prairies Manley et al. 2005

 studies of net returns and 51

 studies of carbon soil uptake

No tillage 25.27 to 42.7 33.99 Meta-regression analyses of 52 N/A Corn Belt Manley et al. 2005 studies of net returns and 51 studies of carbon soil uptake

Change from crops to 16.95 to 169.39 93.17 Field-level econometric N/A Montana Antle et al. 2001

permanent grass production models combined

 with crop ecosystem model

Change from crops to 3.31 to 41.43 22.37 The U.S. Agricultural Sector 5 U.S. Lewandrowksi et al.

permanent grass Model (USMP), a spatial and 2004

 market equilibrium model

Shift to continuous 4.07 to 47.47 25.77 Field-level econometric N/A Montana Antle et al. 2001

cropping production models combined

 with crop ecosystem model

Average 64.93

Median 55.90

Minimum 1.64

Maximum 214.80

Standard deviation 58.24
137

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Capture and Storage/Destruction of GHG Emissions 

Carbon dioxide capture and storage (CCS) projects capture CO2 from electric 

powerplants or industrial sources and place it in long-term storage, e.g., by injecting 

it underground or storing it in oceans. Another option is to destroy non-CO2 GHGs 

through activities like methane management in coal mining and natural gas and 

petroleum systems, and controlling nitrous oxides and fluorocarbons in production 

processes. These CCS projects are predicted to potentially reduce 15 to 55 percent 

of total carbon emissions by the end of the century (Metz et al. 2005) at a cost ranging between $15 and $90/t CO2e (CBO 2007). The variation in the cost of CCS is 

a result of variation in the types and sizes of proposed CCS projects. For example, 

Herzog et al. (2003) estimated the cost of coal-based CCS to be $50 to $65/t CO2e 

compared to gas-based CCS at $85/t CO2e. 

The CCS technology is still at a very early stage of deployment, with few plants 

operational worldwide. A major impediment is the energy loss as CCS technology 

is expected to use somewhere between 10 and 40 percent of the energy produced by 

the plant (Rochon 2008). As compared to CCS projects, projects that destroy nonCO2 GHGs tend to have lower costs per unit CO2e reduction. Creyts et al. (2007) 

estimated per-unit net cost for these projects to be $3/t CO2e compared to $49 for 

CCS projects.

Offset Cost Competitiveness

Table 4-6 compares the gross and net costs of GHG mitigation for different 

offset options. The gross costs are derived from tables 4-3, 4-4, and 4-5. Creyts 

et al.’s (2007) estimates of net costs in table 4-6 are a weighted average of the 

opportunities within each sector and reflect the capital, operating, and maintenance 

costs minus any energy savings associated with abating 1 metric ton of CO2e per 

year over a 25-year forecast period using a 7-percent discount rate. Net cost values 

in parentheses represent options that provide net benefits; i.e., the energy benefits 

are greater than the costs of the options. All estimates (gross and net) do not include 

transaction costs, taxes, tariffs, subsidies, or incentives. 

Conservation tillage is expected to produce net benefits of $7/t CO2e owing to 

energy savings from reduced use of machinery and fertilizers with reduced- or notillage systems. All other biological sequestration sources are expected to produce 

positive gross and net costs and are expected to be competitive with all other 

sources except recovery and destruction of non-CO2

 GHGs. 

Of the forest offset options, afforesting pasturelands appears to be the most 

cost-effective option. Afforesting croplands is more costly because of the higher 

opportunity cost of cropland compared to pastureland. Creyts et al. (2007) 
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GENERAL TECHNICAL REPORT PNW-GTR-837

estimated that 6.9 million ha of pasture land (4.2 percent of all rangeland in the 

United States) and 5.3 million ha of agricultural lands (2.7 percent of all agricultural 

land) could be reforested. Reforesting pastureland is expected to sequester 130 

million metric tons of CO2e annually with 50 percent of the carbon reduction 

occurring in the South owing to the region’s rapid carbon uptake, low conversion 

costs, and relatively low opportunity costs. Afforesting croplands is expected 

to sequester about 80 million metric tons of CO2e with the most cost-effective 

opportunities in the South. The CBO (2007) concluded that a price of $5/t CO2e 

would prompt enough tree planting to sequester between 2 and 50 mmt annually 

and that a price of $50/t CO2e would increase the amount sequestered to 500 to 

800 mmt annually. However, others suggest that the lack of availability of lands 

for afforestation may limit the usefulness of this option in the United States (Gorte 

2009b, Plantinga et al. 1999, Ray et al. 2009).

Along with the per-unit cost estimation, scalability of different types of offset 

projects also needs to be factored in. Some options like CCS are in the early stages 

of development and require large upfront costs, making them quite limited in scope 

for now. In contrast, soil carbon sequestration through agriculture offsets might 

make their most substantial contribution at low CO2

 prices; however, the total 

amount of soil carbon that can be sequestered is limited owing to requirements 

for soil saturation potentials ranging from 25 to 260 mmt (Gorte 2009a).

Table 4-6—Cost competitiveness of U.S. offset projects 

Average Average

Type of greenhouse gas offset option gross cost net cost Potential 

Million metric

2005 dollars/ton CO2e tons CO2e 

Forest offsets:

Afforestation of cropland 17 39 80

Afforestation of pastureland 17 18 130

Improved forest management 28 23 110

Agricultural offsets:

Conservation tillage 73 7 80

Winter cover crops 47 27 40

Reducing already-emitted greenhouse gases:

Industrial carbon capture and storage 38 49 95

Carbon capture and storage in powerplants 38 44 290

Recovery and destruction of non-CO2 n/a 3 255

 greenhouse gases

 Source: Creyts et al. (2007) and author compilation.
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Policy Environment

A number of current and proposed policies and programs may influence the 

competitiveness of forest offset projects. Some of these policies are directed 

specifically at GHG reduction, whereas others influence offset projects indirectly. 

Regulatory mechanisms, incentive-based policies, and government support 

programs may influence the competitiveness of forest carbon offset projects. 

Regulatory mechanisms include polices that set goals/targets/limits, and compel 

certain types of behavior. Incentive-based policies provide financial incentives such 

as cost-shares, tax reductions, subsidies, or grants, and low- or no-interest loans 

for project financing. Support programs create supportive infrastructure, provide 

research and development support, and facilitate public educational outreach.

Cap-and-Trade Initiatives

In the absence of federal leadership on climate change, a number of states have 

taken the initiative to establish regional cap-and-trade regulations. The Regional 

Greenhouse Gas Initiative (RGGI) is an agreement between 10 Northeastern and 

Mid-Atlantic States to reduce CO2 emissions by 10 percent by 2018. The RGGI 

allows regulated emitters to use offsets to satisfy 3.3 percent of their compliance 

obligations initially with provisions to allow offset ceilings to rise to 5 percent and 

10 percent of total emissions if the 12-month rolling average allowance reaches 

The Southern United States has many opportunities for additional afforestation as part of 

climate change mitigation.
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$7 and $10 per ton of CO2 (in 2005 dollars), respectively. Eligible offset projects 

include landfill methane capture and destruction, afforestation, sulphur fluoride 

reduction in the electricity sector, avoided agricultural methane emissions, and 

energy-efficient building projects. The Western Climate Initiative (WCI) is a 

comprehensive regional effort by the governors of seven U.S. states and premiers of 

four Canadian provinces to reduce GHG emissions to 15 percent below 2005 levels 

by 2020 (WCI 2007). Offset projects will be allowed, but the program is still in the 

planning stages. Nine states and two Canadian provinces are also developing the 

Midwestern Regional Greenhouse Gas Reduction Accord (MGGRA). The MGGRA 

is scheduled to start in 2012 and will incorporate a regional cap-and-trade system 

covering most sectors of the economy with an emissions target of 16 percent below 

2005 levels. Offset criteria, eligibility, and implementation remain in the planning 

stage.

In addition, a number of states are compiling GHG inventories and designing 

and implementing emission reduction programs. Over 45 states have completed 

GHG inventories, and more than 38 have developed (or are in the process of developing) state action plans to reduce emissions (USEPA 2009b). Various states have 

also promulgated different options to deal with GHG emissions. As many as 35 

states have some sort of energy portfolio standards, 13 have appliance/equipment 

standards for energy efficiency, 42 have energy standards for public buildings, and 

all the states have energy codes for buildings (NCSC et al. 2010). Many states have 

also formulated alternative fuels vehicle acquisition regulations, whereby states set 

priorities for purchasing alternative-fuel vehicles for state or local agencies.

Incentive-Based Policies

A number of programs and policies provide financial incentives to encourage the 

adoption of a wide array of agricultural, forest, and other land uses to enhance the 

production of specific commodities; encourage the production of ecosystem services; and to promote sustainable production systems. These incentives complicate 

the analysis of the competitiveness of alternative carbon offset projects as they 

influence the opportunity costs of alternative land uses and production processes. 

It is also uncertain how receiving incentive payments from these various programs 

will affect eligibility to sell carbon offset credits, i.e., whether stacking of payments 

will be allowed and how they will affect additionality. 

Motivated by fears of timber scarcity, state and federal governments first 

introduced programs providing financial incentives to NIPFs in the 1940s with the 

goal of increasing timber production and supply for the postwar construction boom. 

A variety of approaches were tried including cost sharing; technical assistance; 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

property, estate, and income tax reductions; and preferential capital gains treatment 

for timber production (Kilgore et al. 2007). Beginning with the 1990 Farm Bill, 

incentive programs for forest landowners began to shift focus from timber to forest 

stewardship, conservation, and the production of ecosystem services. Although the 

objectives have changed over the past 60 years, the policy levers have remained 

fairly constant emphasizing cost sharing, technical assistance, and tax incentives. 

Currently there are at least 14 federal programs that encourage private landowners 

to adopt stewardship practices to enhance ecosystem services through improved 

forest management, retention of lands in forest or undeveloped uses, protection of 

soil and water quality, enhancement and preservation of forested wetlands, and 

wildlife habitat improvement. 

Several federal forest and agriculture programs also provide incentives for 

mitigating GHGs. For example, the Environmental Quality Incentives Program 

provides cost-share assistance to install GHG mitigating technologies and the 

Conservation Reserve Program, Wildlife Habitat Incentives Program, and Landowners Incentive Program provide financial assistance to landowners for a variety 

of conservation goals including carbon sequestration. The Forest Land Enhancement Program promotes additional carbon sequestration as well as other ecosystem 

benefits through cost-share partnerships with landowners, and the Biomass Crop 

Assistance Program provides financial assistance to producers that deliver eligible 

biomass material to designated biomass conversion facilities. 

State governments began initiating cost-share programs in the 1970s and 1980s 

to supplement federal funding. Similar to federal programs, the availability of state 

management and cost-share assistance funding has fluctuated over the years. The 

largest programs in terms of payments and area treated have historically been in 

the South. Although state programs initially focused on timber productivity, over 

the past 25 years, the focus has expanded beyond timber to promote the retention 

of agricultural and forestry land uses, protection of riparian areas and wetlands, 

enhancement of wildlife habitats, and water quality and soil conservation. State 

programs primarily assist with development of management plans and cost-share 

assistance to implement stewardship practices. At least 27 states have adopted costshare assistance programs; these include eight in the South, nine in the Midwest, 

five in the West, and five in the East. Most state programs prohibit payments from 

both federal and state sources for the same practice, but a few do allow both sources 

of funding up to 100 percent of the cost of the project (Greene et al. 2005).

Property taxes have the greatest potential of any state tax to influence land use 

decisions. All states in the United States assess or tax forest land at preferential 

rates, either as timberland or as agricultural or unproductive land. The states differ 
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substantially in the approaches they use and the methods by which they apply them. 

Many states—particularly in the North—use a yield tax approach, in which the 

forest is divided into land and timber components. The land is taxed annually, but 

the tax on the timber is deferred until it is harvested. Other states—particularly in 

the South—use a modified assessment approach, in which rural land is assessed 

differently from other property. 

The assessed value may be fixed, 

calculated using a reduced assessment rate, or based on the land’s 

actual use instead of its “highest 

and best” use. Still other states 

use an exemption approach, which 

removes forest land, timber, or both 

from the property tax rolls, either 

permanently or for a set number of 

years. A number of states use two 

or more of these approaches (Siegel 

and Hickman 1989).

Support Programs

A robust system of agricultural and 

forestry extension support programs 

at federal and state agencies and 

universities facilitate knowledge 

transfers, technology demonstrations, and information sharing to 

landowners and producers. Extension agents and specialists at land 

grant universities and government 

institutes transfer natural resource 

management (including GHG mitigation information) knowledge to farmers, forest 

owners, foresters, and other natural resource managers. These programs are also 

being used for extending knowledge regarding GHG mitigation and offset benefits. 

Examples include GHG technology demonstration initiatives such as anaerobic 

digesters, geothermal, and wind power to farmers, local government, communities, industries, landowners, and consumers. The USDA collaborates with private 

partners to develop pilot projects for testing forest and agriculture GHG sequestration and mitigation technologies and practices. 

Landowners have retained subsidized afforested 

stands at high rates and well beyond government 

program life.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Effectiveness of Forest Incentives

Although several studies have demonstrated that cost-share payments have 

increased reforestation and tree planting behavior (Brooks 1985, de Steiguer 1984, 

Hyberg and Holthausen 1989, Lee et al. 1992), others have concluded that many 

landowners received cost-share payments for activities they would have done 

anyway and that the cost-share payments effectively substitute public for private 

investment (Baughman 2002, Boyd 1984, Brockett and Gerhard 1999, James et 

al. 1951, Kluender et al. 1999, Zhang and Flick 2001). For example, Cohen (1983) 

concluded that 30 to 50 percent of all land reforested under cost-sharing agreements 

would have been planted without the incentives. Others, however, found that the 

cost-share payments allowed landowners to expand the number of acres they were 

able to reforest (Bliss and Martin 1990). 

Following a thorough review of more than 50 years of literature and conducting 

focus groups of landowners across the United States, Greene et al. (2005) concluded 

that most financial incentives actually have little effect on forest owner behavior. 

In their meta-analysis of 41 econometric studies, Beach et al. (2005) examined the 

impacts of four categories of factors that influence forest management decisions: 

market drivers (e.g., prices, costs, and returns to alternative investments), policy 

variables (tax incentives, cost-sharing, and technical assistance), owner characteristics, and site conditions. Policy variables were the most likely to be significant 

when included (87 percent), followed by plot/resource conditions (79 percent), 

owner characteristics (77 percent), and market drivers (73 percent). Both Beach et 

al. (2005) and Greene et al. (2005) concluded that NIPF owners more often respond 

to targeted government programs than to market prices or other financial incentives 

and that three approaches have consistently succeeded in changing forest management decisions by private landowners: technical assistance, cost-share payments, 

and direct contact with professional foresters or natural resource specialists. For 

example, as early as 1951, forest landowners were shown to prefer technical assistance over financial or tax incentives (James et al. 1951). More recently, Greene and 

Blatner (1986), Baughman (2002), and Kilgore and Blinn (2004) found technical 

assistance to be the most effective way to change forest landowner behavior in both 

the United States and Canada. 

Impacts of Potential Offset Rules and Criteria

The specific rules and regulations for implementing and receiving credit for offset 

projects will have a major impact on the competitiveness of forest offset projects. 

Offset criteria like additionality, baselines, permanence, leakage, and stackability, 

may influence the competitiveness of forest offset projects.
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Additionality and Baseline

Eligible offset projects in all existing and proposed cap-and-trade programs are 

required to sequester carbon that is in addition to what would have been sequestered 

in the absence of the project. To prove additionality, most cap-and-trade proposals 

require that projects be able to show that they have sequestered carbon above and 

beyond an established preproject baseline. Establishing baselines for afforestation 

projects should not be too difficult. However, establishing baselines for sequestering carbon through changes in forest management practices (e.g., extending rotation 

ages) is difficult, controversial, and potentially costly. In addition, once the baseline 

rotation age is established, periodic monitoring and verification will likely be 

required. This will entail reviews of records, site visits, and independent measurements of the carbon stocks, all of which will incur additional cost (Sohngen and 

Brown 2006). 

The two general approaches for establishing carbon baselines are business as 

usual (BAU) and base year. In the BAU approach, a reference case of projected 

future carbon stocks in the absence of the project is established as the minimum 

performance standard for selling offset credits. Following project implementation, the actual increases in forest carbon stocks are compared to the reference 

case. The BAU can be applied to specific projects (project-specific performance 

standards) or to broad project types or economic sectors (standardized or group 

performance standards). The base year approach determines the difference in the 

carbon stocks from one time (the base year) to another. Any additions to the carbon 

stock during the period would be eligible. Within these two general approaches, a 

number of accounting schemes or protocols have recently been suggested to track 

the mitigation achieved by individual forest management projects. 

Galik et al. (2009b) examined the impacts of seven proposed accounting 

systems on simulated 100-year forest management projects extending the rotation 

age in loblolly pine stands in South Carolina. One hundred years post project implementation, net sequestration among the seven protocols differed by almost an order 

of magnitude. The wide variation is due to differences in how protocols address 

individual carbon pools, baseline, leakage, certainty, and buffers. 

The variation in net sequestration has a significant impact on the break-even 

carbon price, potentially leading to higher project costs than estimated in previous 

aggregate national analyses (Galik et al. 2009b). Break-even carbon prices range 

from $10 to almost $200/t CO2e depending on the accounting method and the 

range of values for baseline, reversal, leakage, and uncertainty used in the analysis. 

Sohngen and Brown (2006) also found higher marginal costs and lower potential for 

carbon offset projects based on extending rotation ages than previous studies.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Permanence of Offsets

The likelihood that sequestered carbon will be permanently removed from the 

atmosphere is a major issue associated with forest carbon offset projects owing to 

uncertainties over the possibility of reversal associated with future timber harvests, 

land use change, and natural disturbances such as wildfire, hurricanes, and pest 

and disease outbreaks. Permanence also is a major issue for agricultural offsets. 

For example, Lewandrowski et al. (2004) found that all the carbon stored from 20 

years of conservation tillage could be released into the atmosphere within 1 year 

after returning to conventional tillage practices. Permanence uncertainty puts forest 

and agricultural offset projects at a significant disadvantage relative to fugitive 

emissions5

 reduction offsets such as methane digesters. 

A variety of approaches to the permanence problem have been suggested. 

These include developing some sort of insurance or risk pooling mechanism; 

requiring a version of a conservation easement or deed restriction (Climate Action 

Reserve, Georgia Forestry Commission, RGGI); developing buffer pools in which 

a percentage of issued credits are placed in a “savings account” (Chicago Climate 

Exchange, RGGI, Voluntary Carbon Standard); requiring carbon banks of forest 

lands managed for carbon sequestration as replacement reserves should reversals 

occur; and requiring projects to engage in management activities that reduce the 

risk of wildfire, pests, and diseases. 

Other approaches include developing a conversion factor to convert temporary 

carbon storage into a permanent equivalent exchange rate in term of ton-years 

(Dutschke 2002, Herzog et al. 2003, Watson et al. 2000). Estimates of exchange 

rates range from 42 to 150 ton-years of temporary storage to cover 1 permanent ton 

(van Kooten and Sohngen 2007). Another alternative would be to issue temporary 

carbon emission reduction credits (TCERs) that would expire after a set period (e.g., 

5 to 15 years). Upon expiration of the stipulated period, TCERs would be reissued 

or substituted for other credits. Others (Bigsby 2009, Chomitz and Lecocq 2004, 

Marland et al. 2001) have proposed a rental system in which carbon emitters would 

rent carbon credits from landowners for a set period. The annual rental rate would 

be the market-determined price of a permanent emission credit multiplied by the 

discount rate. Bigsby (2009) takes this rental market a step forward by proposing 

a carbon banking scheme like capital markets, where the bank creates a “carbon 

pool” from carbon credit deposits by carbon owners who receive annual payments. 

The banks could then loan the carbon credits to borrowers who pay an annual 

rental.

5

 Fugitive emissions are pollutants released into air from leaks in equipment, pipelines, 

seals, valves, etc., and not from the usual sources such chimneys, stacks, and vents.
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Leakage

Leakage refers to changes in emissions or sequestration influenced by a project, 

policy, market, or other entity that occur outside the boundaries of the particular 

project, policy, market, or other entity. Several forms of leakage are possible. Internal leakage refers to changes in nonproject areas (under the same ownership) to 

make up for changes made in the project area. For example, shortening the timber 

rotation in one area in response to extending rotation ages in others would be a form 

of internal leakage. When a project activity produces changes by other owners or 

entities, external leakage has occurred. Market leakage occurs when the project 

changes the availability of market goods that results in changes in emissions. For 

example, reducing harvest in the United States could result in increasing harvests in 

other countries to make up for the reduced supply of wood products. Jenkins et al. 

(2009) described six potential policy approaches for dealing with leakage:

• Improve project monitoring and design.

• Discount offset credits to account for leakage.

• Develop systemwide (e.g., sectoral, regional, national) accounting protocols 

to track and reconcile leakage. 

• Reduce carbon cap to account for leakage. 

• Expand scope of eligible activities so that fewer can leak.

• Ignore leakage but acknowledge the potential for error in the system.

Methods for dealing with leakage vary widely between the carbon accounting 

protocols. Of the protocols analyzed by Galik et al. (2009b), only the Voluntary 

Carbon Standard (VCS) and Harnessing Farms and Forests (HFF) require quantification of leakage and provide guidelines. Assessing and quantifying leakage 

were optional under the California Climate Action Registry (CCAR), but the new 

forestry protocol for the California Action Reserve requires an estimate of leakage 

(which they sometimes call “secondary effects”) for all forestry projects. The state 

of Maine proposed that RGGI require project lands to be certified against leakage 

or that harvests meet or exceed average removal rates for the area. The estimated 

impact of these requirements are deductions from creditable carbon ranging from 

0 percent (CCAR, RGGI) to 10 percent (VCS) to 43 percent (HHF) of the annual 

creditable carbon (Galik et al. 2009b). 

Stackability

The issue of stackability involves offset projects that in addition to sequestering 

carbon produce other ecosystem services for which additional payments are 

available (e.g., from government incentive programs such as the Conservation 

Reserve Program [CRP]. For example a reforestation project could produce habitat 
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

for wildlife species, enhance biodiversity, reduce soil erosion, and improve water 

quality while at the same time sequestering carbon. One might imagine that a 

landowner for such a project would be eligible to receive cost-share payments from 

government programs, tax credits or incentives, water quality trading credits, or 

hunting lease payments in addition to selling the carbon offset credits. This would 

allow landowners to manage an entire portfolio of payments for ecosystem services. 

Another example would be combining a carbon offset project with forested riparian 

buffers that generate water quality market credits and understory thinnings to 

generate endangered species habitat credits (RFF 2009). 

The additional revenues associated with stacked payments for multiple ecosystem services could be crucial for enhancing the competitiveness of NIPF offset 

projects. Based on the available data, Mercer et al. (in press) found that between 

2005 and 2007, landowners received annual payments for ecosystem services (PES) 

of at least $1.9 billion per year for forest-based ecosystem services. In 2007, private 

forest landowners in the United States received $727 million for wetland mitigation bank credits, $34 million for conservation bank credit, $1.7 million for sales 

of carbon offsets, $315 million for conservation easements, and $410 million for 

hunting leases. 

Nevertheless, few landowners participate in these programs. For example, 

wetland mitigation accounted for the largest percentage of forest-based ecosystem 

service payments, with 38 percent of all payments in 2007. However, these payments were received by only about 173 mitigation banks, about 0.00002 percent of 

all private forest landowners. In addition, only 5.5 percent of family forest landowners ever received cost-share payments and only 1.8 percent have conservation 

easements (Butler 2008). As a result, private forest landowners consistently report 

that forest-based PES have had little impact on changing their behavior (Greene et 

al. 2005). A large literature has questioned the additionality of forest-based PES in 

the United States, suggesting that a large portion of government incentive payments 

paid landowners for what they would have done without the financial incentives 

(Baughman 2002, Boyd 1984, Brockett and Gerhard 1999, Cohen 1983, James et al. 

1951, Kluender et al. 1999, Zhang and Flick 2001).

Existing programs and pending legislation do not fully address stacking of 

carbon (GHG) payments with other federal or state payments or programs (Olander 

et al. 2010). Two major issues that would need to be addressed are additionality and 

double-counting (RFF 2009). The additionality issue becomes more complex with 

stacked payments, as the landowner would need to insure that all payments (not 

just the carbon payments) result in additional provision of the targeted ecosystem 

service. For example, paying for carbon offsets under a cap-and-trade regime 
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and for other ecosystem services under government conservation programs for a 

project that would be implemented with only one of the funding sources would be 

socially inefficient. To receive both payments, the landowners would likely need to 

show that the practices that produce the additional ecosystem services would not 

have occurred without additional investments. Similarly double counting might 

occur when a landowner manages for a single ecosystem service but attempts to 

receive payments for multiple service streams. For example, RFF (2009) suggested 

that allowing landowners to sell water quality credits from land that is only being 

managed for carbon would not generate the correct incentives for landowners and 

undercut the effectiveness of the water quality market. 

Baker and Galik (2009) evaluated the impacts of offset payments on the CRP. 

They found that when lands and projects produce low rates of carbon sequestration, a direct offset market-induced shift out of the CRP is unlikely. In areas that 

can produce high sequestration rates, however, offset payments could exceed CRP 

payments at a carbon price of $5.56/t CO2e. Above this price, implementation of 

cap-and-trade legislation may induce landowners to drop out of the CRP program. 

Baker and Galik (2009) suggested three approaches for avoiding this scenario: (1) 

increase CRP rental payments, (2) alter the Environmental Benefits Index (EBI) to 

put more weight on carbon storage, or (3) allow CRP contract holders to participate 

Forest-based activities can involve multiple benefits in addition to contributing to climate change 

mitigation, such as afforestation on erodible or other environmentally sensitive agricultural land, 

reducing water pollution, and enhancing wildlife habitat.

Ralph Alig
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

in the carbon offset market. Increasing rental payments or altering the EBI would 

maintain the basic structure of CRP while adding flexibility to its implementation. 

However, it would also likely result in large increases in the CRP budget, which 

may not be politically or fiscally feasible. Allowing CRP contract holders to participate in a federal carbon offset program would resolve some of the budget concerns. 

Although CRP landowners are currently allowed to sell carbon credits in voluntary 

markets, a number of complicated issues concerning additionality, baselines, and 

double counting would have to be resolved before CRP landowners would be 

allowed to sell carbon credits in a federal cap-and-trade system. 

Summary and Conclusions

A large literature on carbon offset economics and policy has developed over the 

past two decades. However, few carbon offset studies concentrate on NIPF landowners. Therefore, we have reviewed the general forest and nonforest carbon offset 

literature to evaluate the competitiveness of U.S. forest offset projects. From this literature review we make inferences concerning the direction of influence on NIPFs. 

The cost comparisons reported here reflect studies from the available literature that 

are not completely comparable to one another in terms of assumptions and methodologies. Therefore, the study findings and cost comparisons should be interpreted 

with caution as general trends rather than definitive conclusions.

A number of factors influence the potential for forest offset projects to reduce 

GHG emissions including tree species and site characteristics, management practices, longevity of wood products and disposal methods, opportunity costs of land, 

discount rates, and forest and agricultural prices. Differences in opportunity cost of 

land, discount rates, impacts of agriculture sector prices, carbon loss occurring during conversion to wood products and disposal, and biological factors result in wide 

variation of unit cost estimates. Cost estimates for producing U.S. forest offsets 

range from about $2 to $77/t CO2e (not including transactions costs or costs to meet 

regulatory rules concerning additionality, baselines, permanence, leakage, etc.). 

United States forest offset projects tend to be less costly than European projects but 

more expensive to implement than those in tropical forests in developing countries. 

Afforestation projects tend to be more cost effective than forest management 

(e.g., extending rotation age) projects. Estimated costs for U.S. afforestation projects 

ranged from $1.29 to $70.92/t CO2e with an average of $16.78/t CO2e and median 

of $9.85/t CO2e. Although the range of cost estimates for U.S. forest management 

projects was smaller ($12.16 to $49.35/t CO2e), the average and median costs were 

higher at $27.65/t CO2e and 24.54/t CO2e, respectively. Afforesting pasturelands 

appears to be more cost effective than afforesting croplands owing to the higher 
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opportunity cost of cropland. The CBO (2007) study concluded that a price of $5/t 

CO2e would prompt enough tree planting to sequester between 2 and 50 million 

metric tons annually and that a price of $50/t CO2e would increase the amount 

sequestered to 500 to 800 million metric tons annually. However, others suggest 

that the lack of availability of lands for afforestation may limit its usefulness in the 

United States (Gorte 2009a, Plantinga et al. 1999, Ray et al. 2009). 

Our review of the literature suggests that the opportunity cost of land, transaction costs, and costs associated with meeting eligibility criteria such as establishing 

baselines and insuring additionality and permanence are the most important factors 

driving the costs of forest offset projects. The literature suggests that transaction 

costs will vary depending on project size and activities (e.g., reforestation vs. 

extending rotation ages) and could be a significant cost and deterrent for NIPF 

participation in the offset market. Transaction costs are one of the key challenges 

that private forest landowners may face in participating in emerging carbon markets. Nevertheless, although transaction costs may be a crucial factor in total project 

costs, they may dim in comparison to the costs associated with complying with 

various project criteria and accounting requirements. The most important of these 

are establishing baselines, additionality, and permanence.

Eligibility criteria in proposed and existing offset programs in the United States 

differ widely in how they address individual carbon pools, baselines, additionality, 

permanence, and leakage. As a result, the amount of creditable carbon generated 

for a project and the required break-even price of carbon offset credits also differ 

dramatically under the different protocols. Failing to account for the added costs 

associated with these protocols would likely result in underestimating forest offset 

project costs. 

Although forest carbon offset projects on NIPF lands may be at a competitive 

disadvantage compared to a number of carbon offset alternatives, there are a range 

of policy options that might narrow the gap. The most important are rules for determining baselines and additionality. Many of the cap-and-trade proposals require 

establishing a business-as-usual baseline. However this produces a number of challenging hurdles to forest projects and particularly for NIPF landowners as they must 

develop a projection of future carbon stocks (in the absence of the project) in the 

face of major uncertainties concerning future market prices, laws, regulations and 

policies, and ecological and social conditions. The simpler base-year performance 

standard approach would likely facilitate NIPF landowner participation, reduce 

costs, and improve competitiveness (Fenderson et al. 2009). However, it is viewed 

by many as an inferior approach that might result in significant amounts of “nonadditional” tons being credited. 
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Three options for ensuring permanence are typically offered in most capand-trade proposals: insurance, offset reserves, and term offset credits. Upfront 

costs should be lower under term contracts than requiring landowners to purchase 

insurance or establish an offset reserve. The Southern Group of State Foresters 

(Fenderson et al. 2009) suggest that long-term contracts or conservation easements 

would deter many NIPF owners and that term credits of 10 to 20 years would be 

most beneficial for NIPF landowners in the South given rotation lengths that range 

from 25 to 80 years. However, under the Kyoto agreement, TCERs have suffered a 

price disadvantage compared to “normal” credits. 

Finally, stacking of ecosystem services payments or credits with carbon offset 

payments may be one of the more important issues in improving the participation 

of NIPF landowners. Although care needs to be taken to insure additionality and 

avoid double counting and leakage, permitting landowners to profit from producing a range of services including carbon may be necessary for NIPF landowners to 

be able to compete in future offset markets. However, given the myriad financial 

incentive programs with multiple and often conflicting goals currently influencing 

land use, this needs to be done based on sound policy research, as changes to these 

policies will determine future landowner participation in both carbon markets and 

traditional land conservation programs. Research is needed to understand how to 

resolve potential conflicts between government conservation programs and the 

possible federal GHG offset market to produce maximum participation by NIPFs. 

Research in this area should endeavor to understand how landowners respond to a 

wide combination of market and policy incentives and education and communitybased initiatives. Knowledge of how multiple incentives with different goals 

interact and what outcomes, in terms of landowner behaviors, ensue is essential 

for developing cost-effective and efficient policies.

English Equivalents

When you know: Multiply by: To get:

Hectares (ha) 2.47 Acres

Metric tons (t) 1.102 Tons

Metric tons per hectare (t/ha) 0.45 Tons per acre

Dollars per metric ton ($/t) 0.907 Dollars per ton

Dollars per hectare($/ha) 0.405 Dollars per acre
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Glossary 

afforestation—The forestation, either by human or natural forces, of nonforest 

land.

Conservation Reserve Program (CRP) land—A land cover/use category that 

includes land under a CRP contract. The CRP is a federal program established 

under the Food Security Act of 1985 to assist private landowners to convert highly 

erodible cropland to vegetative cover for 10 years.

cropland—A land cover/use category that includes areas used for the production of 

adapted crops for harvest. Two subcategories of cropland are recognized: cultivated 

and noncultivated. Cultivated cropland comprises land in row crops or close-grown 

crops and also other cultivated cropland, for example, hay land or pastureland that 

is in a rotation with row or close-grown crops. Noncultivated cropland includes 

permanent hay land and horticultural cropland.

developed land—In the National Resources Inventory (NRI), developed land 

consists of urban and built-up areas, as well as land devoted to rural transportation. 

This is a broader category than the “urban” land use considered in this study. This 

study has not attempted to model net returns to rural transportation use, so this 

report focuses only on the urban component of developed land.

forest land—Land at least 10-percent stocked by forest trees of any size, including land that formerly had such tree cover and that will be naturally or artificially 

regenerated. Forest land includes transition zones, such as areas between heavily 

forested and nonforested lands that are at least 10-percent stocked with forest trees 

and forest areas adjacent to urban and built-up areas. The minimum area for classification of forest land is 1 acre (0.405 ha). Roadside, streamside, and shelterbelt 

strips of timber must have a crown width of at least 120 feet (36.6m) to qualify as 

forest land. Unimproved roads and trails, streams, and clearings in forest areas are 

classified as forest if less than 120 feet wide.

Intergovernmental Panel on Climate Change (IPCC)—The IPCC was established to provide decisionmakers and others interested in climate change with an 

objective source of information about climate change. The IPCC does not conduct 

any research nor does it monitor climate-related data or parameters. Its role is 

to assess on a comprehensive, objective, open, and transparent basis the latest 

scientific, technical, and socioeconomic literature produced worldwide relevant to 

the understanding of the risk of human-induced climate change, its observed and 

projected impacts, and options for adaptation and mitigation. For more information, 

see http://www.ipcc.ch/.
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land area—The area of dry land and land temporarily or partly covered by water, 

such as marshes, swamps, and river flood plains; streams, sloughs, estuaries, and 

canals less than 200 feet (61 m) wide; and lakes, reservoirs, and ponds less than 4.5 

acres (1.8 ha).

land cover/use—A term that includes categories of land cover and categories of 

land use. Land cover is the vegetation or other kind of material that covers the land 

surface. Land use is the purpose of human activity on the land; it is usually, but 

not always, related to land cover. The NRI uses the term land cover/use to identify 

categories that account for all the surface area of the United States. The six major 

land use categories considered in this study are (1) cropland, (2) pasture, (3) range, 

(4) Conservation Reserve Program (CRP), (5) forest, and (6) urban. These uses are 

described in this glossary.

large urban and built-up areas—These areas include developed tracts of 10 acres 

(4 ha) and more.

nonindustrial private forest (NIPF)—An ownership class of private lands where 

the owner does not operate commercial wood-using plants.

National Resources Inventory (NRI)—A statistical survey of land use and natural 

resource conditions and trends on U.S. non-federal lands. The NRI is led by Natural 

Resources Conservation Service (NRCS), the Department of Agriculture’s lead 

conservation agency. For more information, see http://www.nrcs.usda.gov/technical/

NRI/.

other rural land—A land cover/use category that includes farmsteads and other 

farm structures, field windbreaks, barren land, and marshland. Some reports refer 

to this as NRI minor land cover/uses.

pastureland—A land cover/use category of land managed primarily for the production of introduced forage plants for livestock grazing. Pastureland cover may consist 

of a single species in a pure stand, a grass mixture, or a grass-legume mixture. 

Management usually consists of cultural treatments: fertilization, weed control, 

reseeding or renovation, and control of grazing. For the NRI, it includes land that 

has a vegetative cover of grasses, legumes, or forbs, regardless of whether or not it 

is being grazed by livestock. 

public—An ownership class composed of land owned by federal, state, county, or 

municipal governments.
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rangeland—A land cover/use category on which the climax or potential plant cover 

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

for grazing and browsing, and introduced forage species that are managed like 

rangeland. This would include areas where introduced hardy and persistent grasses, 

such as crested wheatgrass, are planted and such practices as deferred grazing, 

burning, chaining, and rotational grazing are used, with little or no chemicals 

or fertilizer being applied. Grasslands, savannas, many wetlands, some deserts, 

and tundra are considered to be rangeland. Certain communities of low forbs and 

shrubs, such as mesquite, chaparral, mountain shrub, and pinyon-juniper, are also 

included as rangeland. 

residential area—Residential area is the sum of acres in lots used for housing 

units.Estimates of residential area, urban and rural, are based on data from the 

American Housing Surveys.

timberland—Forest land that is producing or is capable of producing crops of 

industrial wood and not withdrawn from timber utilization by statute or administrative regulation. (Note: Areas qualifying as timberland are capable of producing in 

excess of 20 cubic feet [1.4 cubic meters] per acre per year of industrial wood in 

natural stands. Currently inaccessible and inoperable areas are included.)

urban area—Nationally, there are two main sources of data on urban area. First, 

the U.S. Department of Commerce Bureau of the Census compiles urban area every 

10 years, coincident with the census of population. Second, the U.S. Department of 

Agriculture, Natural Resources Conservation Service, publishes area of developed 

land, including urban components, at 5-year intervals as part of the NRI. Although 

the U.S. Geological Survey, National Aeronautics and Space Agency, Housing and 

Urban Development Department, and several local, state, and federal agencies also 

collect data or conduct special-purpose studies on urban area, the census and the 

NRI provide the only nationally consistent historical series. Because of differences 

in data-collection techniques and definitions, the NRI estimates of “large urban and 

built-up areas” is usually higher than the census “urban area” estimates for nearly 

all states. The census urban area series runs from 1950, whereas the NRI started 

providing a consistent series in 1982. Historically, the Economic Research Service 

(ERS) major land use time series (MLUS) has used census urban area numbers. 

Prior to 1982, census urban area was the only reliable national source of urban area 

data available. Since 1945, census urban area has been used in the MLUS time 

series to maintain a consistent series. For comparison purposes, census urban area 

is checked against the NRI to help project and interpolate census trends between 

decennial census years.
164

GENERAL TECHNICAL REPORT PNW-GTR-837

urban and built-up areas—These areas consist of residential, industrial, commercial, and institutional land; construction and public administrative sites; railroad 

yards, cemeteries, airports, golf courses, sanitary landfills, sewage plants, water 

control structures, small parks, and transportation facilities within urban areas. 
165

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Appendix 1: Eligible Offset Projects Listed in 

2010 American Power Act (Kerry-Lieberman)

• Methane collection at mines, landfills, and natural gas systems and reduction of methane emissions from non-landfill organic waste streams including manure management, composting, or anaerobic digestion projects.

• Capturing fugitive emissions from the oil and gas sector that reduce greenhouse gas emissions that would otherwise have been flared or vented.

• Capture and geological sequestration of uncapped greenhouse gas 

emissions.

• Recycling and waste minimization projects.

• Biochar production and use.

• Abating the production of nitrous oxide at stationary sources. 

• Destruction of ozone-depleting substances that have been phased out of 

production.

• Agricultural, grassland, and rangeland practices, including:

▪ Altered tillage practices, including the avoided abandonment of 

conservation practices.

▪ Winter cover cropping, continuous cropping, and other means to 

increase biomass returned to soil in lieu of planting followed by 

fallowing.

▪ Improved management of nitrogen fertilizer use.

▪ Reduction in methane emissions from rice cultivation.

▪ Reduction in carbon emissions from organically managed soils and 

farming practices used on certified organic farms.

▪ Reduction in greenhouse gas emissions due to changes in animal 

management practices, including dietary modifications and pasturebased livestock systems. 

▪ Resource-conserving crop rotations of at least 3 years. 

▪ Practices that will increase the sequestration of carbon in soils on 

cropland, hayfields, native and planted grazing land, grassland, or 

rangeland. 

▪ Reducing greenhouse gas emissions from manure and effluent, 

including waste aeration; biogas capture and combustion, improved 

management or application to agricultural land.
166

GENERAL TECHNICAL REPORT PNW-GTR-837

• Forest offset projects, including:

▪ Afforestation or reforestation of acreage not forested as of 

January 1, 2009.

▪ Forest management resulting in an increase in forest carbon 

stores, including harvested wood products.

▪ Management of tree crops.

▪ Adaptation of plant traits or new technologies that increase 

sequestration by forests.

• Land management changes, including:

▪ Improved management or restoration of cropland, grassland, 

rangeland, and forest land.

▪ Avoided conversion that would otherwise release carbon stocks.

▪ Reduced deforestation.

▪ Management and restoration of peatland or wetland.

▪ Urban tree-planting, landscaping, greenway construction, 

and maintenance.

▪ Restoring or preventing the conversion, loss, or degradation 

of vegetated marine coastal habitats.
167

Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Appendix 2: Costs of Removing Atmospheric CO2 Through 

Forest Offset Projects

Forest carbon Total Total

sink studies carbon area Cost Cost Cost Location Project type Method

Million

metric Thousand Dollars/ Dollars/ Dollars/

tons hectares hectare t C t CO2e

Adams et al. 140.00 59.00 442.28 18 4.90 Contiguous Afforestation The marginal cost

1993 U.S. (averaged across all

 regions) per ton is

 calculated using a price-

 endogenous, spatial

 equilibrium model of

 the U.S. agricultural

 sector known as the 

 Agricultural Sector 

 Model (ASM).

Adams et al. 2023.08 145.60 401.52 29.16 7.95 Contiguous Afforestation The analysis measures 

1999 U.S. and forest cost as the net change management in producer and consumer changes surpluses in markets for forest and agricultural commodities through an optimization model for the U.S. forest and agricultural sectors.

Alternative carbon flux targets are examined by constraining the model to 

find market solutions that allow achievement of the targets.

Baral and 316.75 1.00 18,602.34 63.30 17.25 Southern U.S. Afforestation To evaluate the carbon

Guha 2004 and fossil fuel mitigation potential of

 substitution afforestation and fossil 

 fuel substitution, bottom-

 up models based on 

 aboveground tree growth 

 rate, carbon uptake in soil 

 and litter, harvest and 

 storage losses, and energy 

conversion efficiency 

 are used.

Callaway and 119.32 29.62 143.39 34.09 9.29 Contiguous Afforestation A modified version of the

McCarl 1996 U.S. ASM was used in this 

 analysis.

Dixon et al. 5.98 0.030 180.72 4.73 1.29 Oregon, Utah Afforestation Project-based carbon

1994 sequestration calculation 

 based on bottom-up 

study by PacifiCorp.

Huang and 0.06 0.00 838.78 44.63 12.16 Texas Forest Optimal carbon sequesKronrad 2001 management tration rotation calculation using Faustmann approach for different site index and interest rates.

McCarl and 243.88 47.39 383.74 72.36 19.72 Contiguous Afforestation Integrates forestry data

Callaway 1995 U.S. from the Timber Assess-

 ment and Market study

 (Adams and Haynes 

 1980) with the ASM.
168

GENERAL TECHNICAL REPORT PNW-GTR-837

Forest carbon Total Total

sink studies carbon area Cost Cost Cost Location Project type Method

Million

metric Thousand Dollars/ Dollars/ Dollars/

tons hectares hectare t C t CO2e

New York State 0.50 0.80 17.33 29.51 8.04 New York Afforestation The carbon reduction cost

1991 is calculated based on

 cost per acre and carbon 

 sequestration potential of 

 forest species.

Newell and 7.66 2.07 699.79 181.13 49.35 36 counties Forest Econometric estimated

Stavins 1999 in Arkansas, management parameters of a

 Louisiana, and structural model of

 and afforestation land use where changes

 Mississippi in alternative land uses 

 are linked with changes in the time paths of CO2 emission and sequestra-

 tion. The econometric

 estimates of the costs

 of carbon sequestration 

 are derived from 

 observations of 

 landowners’ actual behavior when confronted with the opportunity costs of alternative land uses.

Parks and 29.96 6.58 967.26 260.29 70.92 Contiguous Afforestation Engineering cost approach 

Hardie 1995 U.S. to derive a supply 

 schedule for carbon 

 sequestered in trees 

 planted on marginal 

 agricultural lands in the 

 United States. The 

 schedule is used to 

 develop criteria for 

 enrolling lands in a 

 national carbon 

 sequestration program 

 modeled after the 

 Conservation Reserve 

 Program.

Plantinga and 41.55 0.28 5457.40 36.28 9.89 Maine, South Afforestation An econometric model of 

Mauldin 2001 Carolina, land use is used to calcu-

 Wisconsin late carbon sequestration

 potential and cost. 

 Econometric parameters

 are estimated from data

 on observed land allo-

 cation decisions to

 quantify the relationship 

 between the share of land 

 in forest and the net 

 returns to forestry, 

 among other land use 

 determinants.

Plantinga et al. 12.80 0.19 4596.33 67.61 18.42 Maine, South Afforestation Econometric land use of

1999 Carolina, models to estimate

 Wisconsin the marginal costs of

 carbon sequestration in 

 the three states.
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Effects of Climate Change on Natural Resources and Communities: A Compendium of Briefing Papers

Forest carbon Total Total

sink studies carbon area Cost Cost Cost Location Project type Method

Million

metric Thousand Dollars/ Dollars/ Dollars/

tons hectares hectare t C t CO2e

Richards et 42 903 86.40 3446.72 6.94 Contiguous Afforestation Engineering or “least to 

al. 1993 U.S. and forest cost” approach is used

 management to develop marginal and 

 total cost curves for the 

 use of tree planting and 

modified forestry practices to capture atmospheric carbon on marginal agricultural land and forest land in the United States. 

Sohngen and 2.28 0.22 1921.95 130.00 35.42 12 states in Forest Engineering cost approach

Brown 2006 southern management of calculating marginal

 and costs of carbon seques-

 western tration in forests. Optimal

 regions of rotation period with and

 the U.S. without terms for the

 valuation of carbon

 storage for a range of

 carbon price for given 

 yield function and forest 

 product price are used to 

 estimate carbon seques-

 tration values.

Sohngen and 29 198 7.34 50.10 13.65 Continental Reducing Linking forest fire 

Haynes 1997 U.S. forest fire mortality model to forest

 frequency inventory model to

 (damage) determine how changes

in the frequency of fires 

 will impact forest 

 inventories. Changes in 

 inventory levels can be 

 used to project both the 

 amount of carbon stored 

 and an economic 

 response.

Source: Adapted from van Kooten and Sohngen (2007). Costs are in 2005 U.S. dollars. The cost estimates in the table are drawn from 

meta-regression analysis by van Kooten and Sohngen (2007). As studies in their sample provided multiple estimates of one or more 

projects or regions, the averaged values across a study was calculated by them. $1/t CO2e = $3.67/metric ton CO2.

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