Baseline and Projected Future Carbon Storage and 

Greenhouse-Gas Fluxes in Ecosystems of the 

Western United States

U.S. Department of the Interior

U.S. Geological Survey

Professional Paper 1797
Front of cover: A stand of mixed conifer trees in Glacier National Park, northwestern Montana. 

The mesic, closed-canopy forests are typically distributed on mountain slopes with high moisture 

gradients and include western hemlock, western redcedar, Douglas-fir, lodgepole pine, as well 

as spruce and fir species. These types of forests are affected by natural disturbances such as 

wildland fires with relatively long fire-return intervals. The major land-management activities 

affecting forests include fire suppression, timber harvesting, and recreation. (Photograph by 

Zhiliang Zhu.)

Inside of cover: An open-canopy scrub landscape under late-afternoon sun in Petrified Forest 

National Park, northeastern Arizona. The desert ecosystem is composed primarily of creosote 

bush, saltbush, winterfat, and Mormon tea. (Photograph by Zhiliang Zhu.)

Back of cover: A riparian grassland on Antelope Flats in Grand Teton National Park near Jackson, 

Wyoming. In the fall, the grassland provides a strong contrast with the Teton Range and its forestcovered foothills in the background. (Photograph by Benjamin M. Sleeter.)
Baseline and Projected Future Carbon 

Storage and Greenhouse-Gas Fluxes in 

Ecosystems of the Western United States 

By Zhiliang Zhu and Bradley C. Reed, Editors

Professional Paper 1797

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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Suggested citation:

Zhu, Zhiliang, and Reed, B.C., eds., 2012, Baseline and projected future carbon storage and greenhouse-gas fluxes 

in ecosystems of the Western United States: U.S. Geological Survey Professional Paper 1797, 192 p. 

(Also available at http://pubs.usgs.gov/pp/1797/.)
iii

Acknowledgments

Many people helped with the development of the methods and the models, the preparation and 

analysis of data, and the preparation of this report. The development of soil and wetland data 

was provided by Norman Bliss of Arctic Slope Regional Corporation Research and Technology 

Solutions and Kristin Byrd of the U.S. Geological Survey (USGS). Guidance on the use of the U.S. 

Department of Agriculture (USDA) Forest Service’s forest inventory and assessment data was 

provided by Samuel Lambert, Elizabeth LaPoint, Patrick Miles, Ronald Piva, Jeffery Turner, and 

Brad Smith of the USDA Forest Service’s Forest Inventory and Analysis Program. Software, data, 

and computation support was provided by Brian Davis, Layth Grangaard, Ronald Kanengieter, 

and Rob Quenzer of Stinger Ghaffarian Technologies, Inc. Guidance on the wildland-fire-model 

codes and computation was provided by Mark Finney, Matt Jolly, and Robert Keane of the USDA 

Forest Service’s Missoula Fire Sciences Laboratory; Elizabeth Reinhardt of the USDA Forest 

Service’s Office of the Climate Change Advisor; and Jodi Riegle of the USGS. Ashwan Reddy 

(USGS) and Feng Zhao (University of Maryland) provided literature review and data-processing 

support. Christopher Torbert of the USGS provided management support for the project. 

Special thanks go to 10 anonymous peer reviewers of this report.
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v

Contents

Acknowledgments ......................................................................................................... iii

Executive Summary— Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in 

Ecosystems of the Western United States

By Zhiliang Zhu, Brian A. Bergamaschi, David Butman, David W. Clow, Todd J. Hawbaker, 

Jinxun Liu, Shuguang Liu, Cory P. McDonald, Benjamin M. Sleeter, Richard A. Smith, 

Terry L. Sohl, Sarah M. Stackpoole, Anne Wein, and Yiping Wu ................................. 1

Chapter 1.—An Assessment of Carbon Sequestration in Ecosystems of the Western United States—

Scope, Methodology, and Geography

By Zhiliang Zhu, Benjamin M. Sleeter, Glenn E. Griffith, Sarah M. Stackpoole, Todd J. 

Hawbaker, and Brian A. Bergamaschi ............................................................... 5

Chapter 2.—Baseline Land-Use and Land-Cover Changes in the Western United States Between 

1992 and 2005

By Terry L. Sohl, Benjamin M. Sleeter, Tamara S. Wilson, Michelle A. Bouchard, Rachel R. 

Sleeter, Kristi L. Sayler, Ryan R. Reker, Christopher E. Soulard, and Stacie L. Bennett ......... 17

Chapter 3.—Baseline Wildland Fires and Emissions for the Western United States

By Todd J. Hawbaker and Zhiliang Zhu ............................................................... 29

Chapter 4.—Major Land-Management Activities and Natural Disturbances Considered in This 

Assessment

By Shuguang Liu, Jennifer Oeding, Zhengxi Tan, Gail L. Schmidt, and Devendra Dahal ...... 39

Chapter 5.—Baseline Carbon Storage, Carbon Sequestration, and Greenhouse-Gas Fluxes in

Terrestrial Ecosystems of the Western United States

By Shuguang Liu, Jinxun Liu, Claudia J. Young, Jeremy M. Werner, Yiping Wu, 

Zhengpeng Li, Devendra Dahal, Jennifer Oeding, Gail L. Schmidt, Terry L. Sohl, 

Todd J. Hawbaker, and Benjamin M. Sleeter......................................................... 45

Chapter 6.—Projected Land-Use and Land-Cover Change in the Western United States

By Benjamin M. Sleeter, Terry L. Sohl, Tamara S. Wilson, Rachel R. Sleeter, Christopher E. 

Soulard, Michelle A. Bouchard, Kristi L. Sayler, Ryan R. Reker, and Glenn E. Griffith ......... 65

Chapter 7.—Climate Projections Used for the Assessment of the Western United States 

By Anne Wein, Todd J. Hawbaker, Richard A. Champion, Jamie L. Ratliff, Benjamin M. 

Sleeter, and Zhiliang Zhu .............................................................................. 87

Chapter 8.—Projected Future Wildland Fires and Emissions for the Western United States

By Todd J. Hawbaker and Zhiliang Zhu ............................................................... 97

Chapter 9.—Projected Future Carbon Storage and Greenhouse-Gas Fluxes of Terrestial 

Ecosystems in the Western United States

By Shuguang Liu, Yiping Wu, Claudia J. Young, Devendra Dahal, Jeremy M. Werner, 

Jinxun Liu, Zhengpeng Li, Zhengxi Tan, Gail L. Schmidt, Jennifer Oeding, Terry L. Sohl, 

Todd J. Hawbaker, and Benjamin M. Sleeter...................................................... 109

Chapter 10.—Baseline Carbon Sequestration, Transport, and Emission From Inland Aquatic 

Ecosystems in the Western United States

By Sarah M. Stackpoole, David Butman, David W. Clow, Cory P. McDonald, 

Edward G. Stets, and Robert G. Striegl ............................................................ 125

Chapter 11.—Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and 

Their Effects on Coastal Carbon Storage Rates

By Brian A. Bergamaschi, Richard A. Smith, Michael J. Sauer, and Jhih-Shyang Shih...... 143

Chapter 12.—Toward an Integrated Assessment of Baseline and Projected Future Carbon Storage 

and Greenhouse-Gas Fluxes in Ecosystems of the Western United States—

Further Analyses and Observations

By Shuguang Liu, Zhiliang Zhu, Terry L. Sohl, Todd J. Hawbaker, Benjamin M. Sleeter, 

Sarah M. Stackpoole, and Richard A. Smith ...................................................... 159

References Cited ...................................................................................................... 171
vi

Conversion Factors

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Area

square meter (m2) 0.0002471 acre 

hectare (ha) 2.471 acre

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2) 

hectare (ha) 0.003861 square mile (mi2) 

square kilometer (km2) 0.3861 square mile (mi2)

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

Flow rate

cubic meter per second (m3/s) 70.07 acre-foot per day (acre-ft/d) 

meter per second (m/s) 3.281 foot per second (ft/s) 

meter per day (m/d) 3.281 foot per day (ft/d)

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

cubic meter per second (m3/s) 22.83 million gallons per day (Mgal/d) 

millimeter per year (mm/yr) 0.03937 inch per year (in/yr) 

Hydraulic conductivity

meter per day (m/d) 3.281 foot per day (ft/d) 

Application rate

kilograms per hectare per year 

[(kg/ha)/yr]

0.8921 pounds per acre per year 

[(lb/acre)/yr]

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

The resolution of pixels in spatial datasets follows the conventions used in the spatial data and 

modeling communities. The format is “n-meter resolution,” where n is a numerical value for the 

length. The usage translates into a pixel with a length of n on all sides that covers an area of 

n meters × n meters. 

How Megagrams, Gigagrams, Teragrams, and Petagrams Relate to Metric Tons

1 megagram (Mg) = 1 million grams (106 g) = 1 metric ton (t)

1 gigagram (Gg) = 1 billion grams (109 g) = 1,000 metric tons

1 teragram (Tg) = 1 trillion grams (1012 g) = 1 million metric tons (Mt)

1 petagram (Pg) = 1 quadrillion grams (1015 g) = 1 billion metric tons (Gt)
vii

μatm microatmospheres

μeq/L microequivalents per liter 

AMLE Adjusted Maximum Likelihood Estimation

ANC acid neutralizing capacity

ARMS Agricultural Resource Management Survey

AUC area under the curve

AUM animal unit month

BGC biogeochemical

°C Celsius 

C carbon 

C3 cool-season grasses

C4 warm-season grasses

Cburial carbon in buried sediment

CCONC carbon concentration in sediments

CCCma CGCM3.1 The Third Generation Coupled Global Climate Model of the Canadian Centre 

for Climate Modelling and Analysis

CENTURY a biogeochemical model

CFS Canadian Forest Service

CH4 methane

CMIP3 Coupled Model Intercomparison Project phase 3 

CO carbon monoxide 

CO2 carbon dioxide

CO2-air concentration of CO2

 in the atmosphere

CO2-eq carbon dioxide equivalent

CO2-eq/yr carbon dioxide equivalent per year

CO2-water dissolved CO2

 concentrations

CO2

3

− carbonate

CONUS conterminous United States

CRM crop residue management

Cs cesium

CSIRO–Mk3.0 Australia’s Commonwealth Scientific and Industrial Research Organisation 

Mark 3.0

CTIC Conservation Technology Information Center

DB 0.33 bar H2

O the oven-dry weight of the less than 2 mm soil material per unit volume of 

soil at a water tension of 1/3 bar (as used in the SSURGO database)

DIC dissolved inorganic carbon

DOC dissolved organic carbon

ECHAM5 European Centre for Medium-Range Weather Forecasts—Hamburg 5

EDCM Erosion-Deposition-Carbon Model

EISA Energy Independence and Security Act

EPA Environmental Protection Agency 

ERC energy release component

ETM+ Enhanced Thematic Mapper Plus

FCCS Fuel Characterization Classification System

FIA U.S. Forest Service Forest Inventory and Analysis Program

FIPS Federal Information Processing Standard

FLM fuel loading model

FOFEM First Order Fire Effects Model

Abbreviations, Acronyms, and Chemical Symbols
viii

FORE–SCE “forecasting scenarios of land-cover change” model 

FS U.S. Forest Service

g gram

gC grams of carbon

gC/m2 grams of carbon per square meter

gC/m2

/d grams of carbon per square meter per day

gC/m2

/yr grams of carbon per square meter per year

GCM general circulation model

gCO2-eq grams of carbon dioxide equivalent

gCO2-eq/m2 grams of carbon dioxide equivalent per square meter

gCO2-eq/m2

/d grams of carbon dioxide equivalent per square meter per day

gCO2-eq m2

/yr grams of carbon dioxide equivalent per square meter per year

GEMS General Ensemble Modeling System

GFDL Geophysical Fluid Dynamics Laboratory

GFED Global Fire Emissions Database

Gg gigagrams

Gg/yr gigagrams per year

GgC/yr gigagrams of carbon per year

GHG greenhouse gas

GIS geographic information system

GISS Goddard Institute for Space Studies

GLM general linear model

GPP gross primary productivity

GWP global warming potential

H2

CO3 carbonic acid

HadCM2 Hadley Centre Coupled Model 2

HadCM3 Hadley Centre Coupled Model 3

HCO−

3 bicarbonate

HR heterotrophic respiration

HUC hydrologic unit code

IAM integrated assessment model

IMAGE The Netherlands Environmental Assessment Agency’s Integrated Model to 

Assess the Global Environment

IPCC Intergovernmental Panel on Climate Change

k gas transfer velocity

kCO2 kilograms of carbon dioxide

K factor soil erodibility factor

kg kilogram

kg/d kilograms per day

kg/yr kilograms per year

kgC kilograms of carbon

kgC/m2 kilograms of carbon per square meter

kgCO2-eq/m2

/yr kilograms of carbon dioxide equivalent per square meter per year

km2 square kilometers

km2

/yr square kilometers per year

L liter

LANDFIRE Landscape Fire and Resource Management Planning Tools Project

Landsat USGS and NASA Satellite Program

Abbreviations, Acronyms, and Chemical Symbols—Continued
ix

LOADEST USGS Load Estimator program

LPDAAC Land Processes Distributed Active Archive Center 

LULC land use and land cover

CH4 methane 

Mha megahectares

MIrAD–US MODIS-derived national irrigated agricultural dataset

MIROC 3.2–medres Model for Interdisciplinary Research on Climate version 3.2, medium 

resolution

MLR multiple linear regression

MODIS Moderate Resolution Imaging Spectroradiometer

moles/L moles per liter

MSS Multispectral Scanner

MTBS Monitoring Trends in Burn Severity project

MT–CLIM Mountain Climate Simulator

MTT minimum travel time

N nitrogen

NA not applicable

NASS National Agricultural Statistics Service

NBCD National Biomass Carbon Dataset

NECB net ecosystem carbon balance

NED National Elevation Dataset

NEE net ecosystem exchange 

NEP net ecosystem production

NFDRS National Fire Danger Rating System

NHD National Hydrography Dataset

NID National Inventory of Dams

N2

O nitrous oxide 

NLA National Lakes Assessment

NLCD National Land Cover Database

NO3 nitrate

NOAA National Oceanic and Atmospheric Administration

NPP net primary productivity

NRCS National Resources Conservation Service

NTSG Numerical Terradynamic Simulation Group

NWIS National Water Information Service

Pb lead

PCM Parallel Climate Model

pCO2 partial pressure of carbon dioxide

PDSI Palmer Drought Severity Index

Pg petagram

PgC petagrams of carbon

PgC/yr petagrams of carbon per year

PHREEQC USGS computer program that simulates chemical reactions and transport 

processes in natural or polluted water

PRDX potential maximum production parameter

PRISM parameter-elevation regressions on independent slopes model

PRMS Precipitation-Runoff Modeling System

R2 coefficient of determination

Abbreviations, Acronyms, and Chemical Symbols—Continued
x

RESSED Reservoir Sedimentation Database

RMSE root mean square error

RPA U.S. Forest Service Forest and Rangeland Renewable Resources Planning 

Act of 1974

R–FME Flexible Modeling Environment using R software

SCE Shuffled Complex Evolution

SOC soil organic carbon

SPARROW “spatially referenced regression on watershed attributes “ water-quality 

model

SRES IPCC’s Special Report on Emissions Scenarios

SSURGO Soil Survey Geographic database (NRCS)

Tg teragram

TgC teragrams of carbon

TgC/yr teragrams of carbon per year

TgCO2

/yr teragrams of carbon dioxide per year

TgCO2-eq teragrams of carbon dioxide equivalent

TgCO2-eq/yr teragrams of carbon dioxide equivalent per year

Tg/yr teragrams per year

TM Landsat’s Thematic Mapper

TN total nitrogen

TOC total organic carbon

TPO timber product output

TSS total suspended sediment

USDA U.S. Department of Agriculture

U.S. EPA U.S. Environmental Protection Agency 

USFS U.S. Forest Service

USGS U.S. Geological Survey

VCT vegetation change tracker

WCRP World Climate Research Programme

Abbreviations, Acronyms, and Chemical Symbols—Continued
Executive Summary—Baseline and Projected Future 

Carbon Storage and Greenhouse-Gas Fluxes in 

Ecosystems of the Western United States

By Zhiliang Zhu1, Brian A. Bergamaschi2, David Butman3, David W. Clow4, Todd J. Hawbaker4, Jinxun Liu5, 

Shuguang Liu6, Cory P. McDonald7, Benjamin M. Sleeter8, Richard A. Smith1, Terry L. Sohl6, Sarah M. 

Stackpoole4, Anne Wein8, and Yiping Wu9

This is the second in a series of reports produced by the 

U.S. Geological Survey (USGS) to fulfill the requirements 

of section 712 of the Energy Independence and Security Act 

(EISA) of 2007 and to conduct a comprehensive national 

assessment of carbon (C) storage and flux (flow) and the fluxes 

of other greenhouse gases (GHGs, including carbon dioxide 

(CO2), methane (CH4), and nitrous oxide (N2O)). These 

carbon and GHG variables were examined in the Western 

United States for major terrestrial ecosystems (forests, 

grasslands/shrublands, agricultural lands, and wetlands) and 

aquatic ecosystems (rivers, streams, lakes, estuaries, and 

coastal waters) in two time periods: baseline (the first half of 

the 2000s) and future (projections from baseline to 2050). 

The major questions that this assessment attempted to 

answer included the following: (1) How much carbon was 

stored in ecosystems of the Western United States? (2) How 

much carbon could be stored in future years? (3) How were 

the carbon storage and fluxes in the Western United States 

influenced by both natural and anthropogenic processes such 

as land use, wildland fire, and climate change? (4) How might 

carbon storage, carbon flux, and the natural and anthropogenic 

processes that influence carbon cycling in western ecosystems 

vary both geographically and temporally?

The assessment covered 2.66 million square kilometers 

(km2) in the Western United States, which is divided into 

in five level II ecoregions (as defined by the Environmental 

Protection Agency (EPA)): Western Cordillera, Marine West 

Coast Forest, Cold Deserts, Warm Deserts, and Mediterranean 

California. The assessment was based on measured and 

1U.S. Geological Survey, Reston, Va.

2

 U.S. Geological Survey, Sacramento, Ca.

3Yale University, New Haven, Conn.

4U.S. Geological Survey, Denver, Colo.

5Stinger Ghaffarian Technologies, Inc., Sioux Falls, S.D.

6U.S. Geological Survey, Sioux Falls, S.D.

7U.S. Geological Survey, Boulder, Colo.

8U.S. Geological Survey, Menlo Park, Calif.

9Arctic Slope Regional Corporation Research and Technology Solutions, Sioux Falls, S.D.

remotely sensed data collected by the USGS and many other 

agencies and organizations combined with statistical methods 

and simulation models. The major findings and discussion 

follow below.

Baseline and Projected Future 

Land-Use and Land-Cover Change 

• In 2005, the total area of the Western United States 

(2.66 million km2) was distributed over these 

ecosystems: grasslands/shrublands (58.9 percent), 

forests (28.1 percent), agricultural lands (6.1 percent), 

water (1.5 percent), wetlands (0.38 percent), and other 

land types (5.2 percent). Between 1992 and 2005, 

changes in land use (such as croplands) and land 

cover (such as wetlands) in the Western United States 

affected 2.9 percent of that land area and were driven 

by demands for forest products, urban development, 

and agriculture. The change in land use and land cover 

(LULC) from 2006 to 2050 for all ecosystems in the 

Western United States was projected to be between 

5.8 and 7.8 percent. The most active ecoregions of 

projected land use and cover (LULC) change were the 

Marine West Coast Forest, Western Cordillera, and 

Mediterranean California.
2 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

• The projected changes (to 2050) in both LULC and 

climate were used in this assessment to support the 

projection of future potential carbon storage and fluxes 

in relation to both ecological and economic processes. 

The resulting projections were highly variable 

across regions as were the assumptions that were 

made. Between the regions and the assumptions, the 

overall rates of projected LULC change varied from 

1.3 percent to 45 percent. The models of projected 

climate change (using general circulation model data) 

indicated (1) a projected general increase in both 

the mean temperature and in extreme temperatures 

throughout the Western United States, and (2) a 

projected high variability in precipitation change that 

depended on the ecoregion, seasonality, downscaling, 

and interannual variability.

Baseline Carbon Storage and Flux

• The estimated average total carbon storage in 

the ecosystems of the Western United States in 

2005 was approximately 13,920 (12,418–15,460) 

teragrams of carbon (TgC), which was distributed 

in forests (69 percent), grasslands/shrublands 

(25 percent), agricultural lands (4.3 percent), wetlands 

(0.46 percent), and other lands (0.63 percent). 

Geographically, the estimated total and per-unit-ofarea carbon stocks ranged from 700.2 TgC (the Cold 

Deserts) to 8,162.8 TgC (the Western Cordillera) 

and from 1.5 kilograms of carbon per square meter 

(kgC/m2) (the Cold Deserts) to 16.1 kgC/m2 (the 

Marine West Coast Forest), respectively. On average, 

the forests in the Western United States maintained the 

largest stock of carbon per unit of area among all of 

the ecosystems at 13.0 kgC/m2, followed by wetlands 

(6.3 kgC/m2), agricultural lands (3.7 kgC/m2), 

grasslands/shrublands (2.2 kgC/m2), and other land 

types (0.5 kgC/m2). Overall, live biomass and soil 

organic carbon (assessed in the top 20-cm-thick layer) 

accounted for 38 and 39 percent of the total carbon 

stock, respectively, and woody debris and other surface 

carbon pools represented the remaining 23 percent.

• The net carbon flux was calculated as the change of 

carbon stock between two points in time. A negative 

number indicates carbon uptake, carbon sequestration, 

or a carbon sink; a positive number indicates a 

carbon emission or a carbon source. From 2001 to 

2005, an average annual net flux of −86.6 (−162.9 to 

−13.6) TgC/yr was estimated for all of the terrestrial 

ecosystems in the Western United States. In lakes and 

reservoirs throughout the Western United States, an 

additional −2.4 (−3.7 to −1.2) TgC/yr was estimated 

to be buried and sequestered in sediments. The flux 

in the Pacific coastal waters was approximately 

−2.0 TgC/yr. Thus, the combined estimates 

resulted in a total annual carbon-sequestration rate 

of −91 TgC/yr across all of the major ecosystems in 

the Western United States; this rate is equivalent to 

4.9 percent of the nation’s net fossil-fuel emissions 

in 2010 as reported by the U.S. Environmental 

Protection Agency (EPA, 2010). Most of the net 

carbon flux was in forests (62.2 percent, −72.1 grams 

of carbon per square meter per year, or gC/m2/yr), 

followed by grasslands/shrublands (29.6 percent, 

−16.4 gC/m2/yr), agricultural lands (7.1 percent, 

−38.3 gC/m2/yr), and wetlands (0.96 percent, 

−82.1 gC/m2/yr). For comparison, a recent study found 

that the net carbon fluxes in forests were approximately 

−93 gC/m2/yr for the United States as a whole and 

−103 gC/m2/yr for the world’s temperate forests (Pan, 

Birdsey, and others, 2011). Of the total carbon sink, 

live biomass accounted for 32 percent, soil organic 

matter accounted for 45 percent, and dead biomass 

accounted for 23 percent. 

Projected Future Potential Carbon 

Storage and Flux

In order to project the future potential carbon storage 

amounts and flux rates, combinations of LULC scenarios and 

climate projections, developed on an annual basis between 

2006 and 2050, were used along with multiple biogeochemical 

models for the assessment. The results of these combinations 

led to a range of estimates for both carbon storage and flux 

under a range of projected future conditions. The results 

of projected future potential carbon stock and flux were 

highly variable among multiple model runs, ecoregions, and 

ecosystems

• The total amount of carbon that potentially could 

be stored in the ecosystems of the Western United 

States in 2050 was projected to range from 13,743 

to 19,407 TgC, which is an increase of 1,325 to 

3,947 TgC (or 10.7 to 25.5 percent) from baseline 

conditions of 2005. Among the five ecoregions, the 

Western Cordillera potentially could store the most 

carbon, accounting for 60 percent of the projected 

future total carbon storage for the Western United 

States, followed by the Cold Deserts (18 percent of 

the total), Marine West Coast Forest (10 percent), 

Mediterranean California (8 percent), and Warm 

Deserts (4 percent). Among the different ecosystems, 

the forests potentially could store the most carbon, 

accounting for 70 percent of the total potential carbon 

storage in the Western United States, followed by 

grasslands/shrublands (23 percent of the total), and 

agricultural lands (6 percent).
Executive Summary 3

• The potential mean annual net carbon flux between 

2006 and 2050 was projected to range from 

−113.9 TgC/yr to 2.9 TgC/yr. When compared 

to the baseline net carbon flux estimates (−162.9 

to −13.6 TgC/yr), the projected future carbonsequestration rates in the Western United States 

represented a potential decline by 16.5 to 49 TgC/yr. 

The projected decline came largely from ecosystems of 

grasslands/shrublands and forests and was distributed 

mostly in the Western Cordillera ecoregion.

Baseline and Projected 

Future Potential Wildland Fire 

Combustion Emissions

Wildland fire is a major ecosystem disturbance in the 

Western United States that is influenced by changes in both 

climate and land use and leads to a considerable interannual 

and regional variability in GHG emissions. 

• Between 2001 and 2008 in the Western United 

States, the burned areas and their GHG emissions 

from combustion ranged from 3,345 to 25,206 

square kilometers per year (km2/yr), and from 6.8 to 

75.3 teragrams of carbon dioxide equivalents per 

year (TgCO2-eq/yr) (1.9 to 20.6 TgC/yr), respectively, 

mostly in the Western Cordillera and Cold Deserts 

ecoregions. The annual average GHG emission from 

the fires was 36.7 TgCO2-eq/yr (10.0 TgC/yr), which 

was equivalent to 11.6 percent of the estimated average 

rate of carbon sequestration by terrestrial ecosystems 

in the Western United States.

• Under future projections of climate change, the area 

burned by wildland fires was projected to increase by 

31 to 66 percent and the GHG combustion emissions 

from wildland fires were projected to increase by 

28 to 56 percent, relative to baseline conditions. These 

projections, combined with the projected decline in 

future terrestrial carbon sequestration, could lead to 

wildland fire combustion emissions equivalent to 

27 to 43 percent of carbon sequestration by terrestrial 

ecosystems in the Western United States. Under 

extreme climate conditions, wildland fire emissions 

were projected to increase 73 to 150 percent relative 

to baseline conditions. Carbon stored in the arid 

and semiarid parts of the Western United States is 

especially vulnerable to wildland-fire emissions.

Carbon Cycling in Aquatic Ecosystems 

of the Western United States

Carbon cycling in and out of the aquatic ecosystems 

was studied separately from the terrestrial ecosystems in 

the Western United States. Carbon fluxes and rates of burial 

within sediments in inland water bodies and coastal waters 

were estimated using separate methods. The derived results 

are as follows. 

• Using data collected between the 1970s and the 

present, rivers and streams throughout the Western 

United States were estimated to transport between 

5.5 and 8.9 (average 7.2) TgC/yr (or an average of 

3.4 gC/m2/yr in yield per unit of area) of dissolved 

inorganic and total organic carbon annually from 

upstream sources to estuaries and the coastal oceans, 

where most was returned to the atmosphere. The 

emissions of carbon dioxide to the atmosphere from 

inland waters of the Western United States ranged from 

16.8 to 48.7 (average 28.2) TgC/yr (or an average of 

14.8 gC/m2/yr in yield per unit of area); 93 percent of 

the total emissions were from rivers and streams and 

7 percent were from lakes and reservoirs. 

• The rate of carbon burial (sequestration) in the 

sediments in the lakes and reservoirs was estimated 

to range from −1.2 to −3.7 (average 2.4) TgC/yr (or 

an average of −1.2 gC/m2/yr in yield per unit of area), 

whereas in coastal waters the average burial rate was 

approximately 2.0 TgC/yr. The estimates of carbon 

fluxes in aquatic ecosystems were highly variable 

because of differences in precipitation, topography, 

lithology, and other controlling processes.

Baseline and Projected Future 

Greenhouse-Gas Fluxes

• In addition to the baseline net carbon flux 

estimates (−162.9 to −13.6 TgC/yr, or −597.7 to 

−50.0 TgCO2-eq/yr), the baseline methane (CH4) and 

nitrous oxide (N2O) flux rates were also estimated 

and were relatively low and highly variable among 

ecosystems and ecoregions. Overall, the estimated flux 

rate of methane during the baseline years ranged from 

−3.1 to −2.9 TgCO2-eq/yr. The estimated flux rate of 

nitrous oxide remained stable over the baseline years 

and averaged 1.7 TgCO2-eq/yr. The balance between the 

three GHGs was projected to continue to 2050, with 

a large but weakened sink for CO2 and a weak sink or 

source for CH4 and N2O, depending on the variability 

of the projected results.
4 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

Limitations of the Assessment Report

The known limitations of the assessment report include 

the following: (1) Forest thinning and rangeland grazing were 

not considered in estimating the carbon stocks and fluxes. 

(2) The effects of conservation and recreation management 

were not specifically analyzed in this report. (3) Wildlandfire combustion emissions were estimated, but the long-term 

effects of wildland fires on the production of carbon in 

ecosystems were not analyzed separately in this report. (4) 

Methane and nitrous oxide fluxes were projected to future 

years based on a set of LULC scenarios without considering 

the effects of climate change projections. (5) The baseline 

carbon fluxes were estimated for the first time for aquatic 

ecosystems, but the existing carbon storage in the sediments 

of the aquatic ecosystems was not estimated. (6) Uncertainties 

from model runs of different components of the assessment 

were quantified using simple statistical methods to account 

for the spread of the estimates. Other sources of uncertainties 

were described in the report but were not quantified. As a 

result, the total uncertainty of the assessment is unknown. 

In addition, there were limitations resulting from the 

methodology used for the assessment; specifically, (a) the 

changes in vegetation types or structures as the result of plant 

succession or climate change were not addressed, and (b) the 

mapping and modeling of major components (such as LULC 

and wildland fires) of the assessment were not coupled in a 

completely integrative modeling system.
Chapter 1. An Assessment of Carbon Sequestration 

in Ecosystems of the Western United States—Scope, 

Methodology, and Geography

By Zhiliang Zhu1, Benjamin M. Sleeter2, Glenn E. Griffith2, Sarah M. Stackpoole3, Todd J. Hawbaker3, and 

Brian A. Bergamaschi4

1.1. Scope and General Methodology of 

the Assessment

This is the second in a series of reports produced by the 

USGS for a national assessment of carbon sequestration and 

greenhouse-gas (GHG) fluxes in ecosystems. The first report 

(Zhu and others, 2011) covered ecosystems of the Great Plains 

region of the United States. This report covers ecosystems 

in the Western United States, which extends from the Rocky 

Mountains in the east to the Pacific coastal waters in the west. 

The area of coverage is approximately 2.66 million square 

kilometers (fig. 1.1).

The carbon sequestration and GHG flux assessment was 

mandated by the Energy Independence and Security Act of 

2007 (EISA; U.S. Congress, 2007), which directed the U.S. 

Department of the Interior to produce a methodology and 

conduct a national assessment to quantify (1) the amount of 

carbon stored in ecosystems, (2) the capacity of ecosystems 

to sequester carbon, and (3) the rate of GHG fluxes in and 

out of the ecosystems. This regional assessment has two 

major objectives: (1) implement the EISA mandate to conduct 

a national assessment of carbon sequestration and GHG 

fluxes, and (2) improve the understanding of the regional 

carbon cycling by focusing on changes in carbon stocks and 

fluxes in all the major ecosystems, and on the major natural 

and anthropogenic processes that control carbon cycling 

(such as climate change, land use, and wildland fires). The 

GHGs considered in this assessment were carbon dioxide 

(CO2), carbon monoxide (CO, from wildland fires only), 

dissolved inorganic carbon (DIC), methane (CH4), and nitrous 

oxide (N2O). 

The major ecosystems evaluated in this study are both 

terrestrial (forests, wetlands, grasslands/shrublands, and 

agricultural lands) and aquatic (rivers, lakes, estuaries, and 

coastal waters). The thematic definitions of the ecosystems 

and their spatial boundaries are outlined in table 2.1 of 

chapter 2 of this report and in Zhu and others (2010). The 

definitions are largely based on the National Land Cover 

Database (NLCD; Vogelmann and others, 2001; Homer and 

others, 2007), which was the primary source of initial land-use 

and land-cover (LULC) data for this assessment. The LULC 

data derived from remote sensing datasets were used to define 

the spatial boundaries of the ecosystems that were assessed in 

this study; because the remote-sensing data allowed for wallto-wall coverage of the Western United States, the resulting 

spatially and temporally explicit data products and estimates 

are considered to be comprehensive.

Within the NLCD database, both land use (for example, 

agricultural lands) and land cover (for example, forests) are 

mapped using using data acquired from Landsat satellites. 

Within the LULC classes, land-management activities were 

defined as those actions that were aligned with the LULC 

classes and modified the way land was used, but did not 

change the LULC classes; for instance, cropland irrigation 

or fertilization was a land-management activity that did not 

change the LULC class of the land. Ecosystem disturbances 

were defined as those natural disturbances that altered the 

production of carbon or other functions in an ecosystem. For 

this assessment, wildland fire was the only natural disturbance 

that was considered. 

1U.S. Geological Survey, Reston, Va.

2U.S. Geological Survey, Menlo Park, Calif.

3U.S. Geological Survey, Denver, Colo.

4U.S. Geological Survey, Sacramento, Calif.
6 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

CR

CR

CR

KM

C

C

WV

NC

ECSF

CP

BM

BM

NC

NBR

SRP

NR

NR

MR

CR

MR

MR

PL

WB

CP

WUM

CBR

MBR

SBR

ANM

ANM ANM

ANM

ANP

CCV

SCCCOW

SCCCOW

MA

CD

SR

SNM

SCM

ARIZONA

NEW MEXICO

TEXAS

OKLAHOMA

UTAH

COLORADO

WYOMING

SOUTH

DAKOTA

NORTH

DAKOTA

NEBRASKAKANSAS

MONTANA

IDAHO

NEVADA

CALIFORNIA

OREGON

WASHINGTON

120° 110°

45°

40°

35°

30°

MEXICO

CANADA

PACIFIC

OCEAN

Base from 2001 National Land Cover Database

(Homer and others, 2007)

0 100 200 300 KILOMETERS

0 100 200 300 MILES
Chapter 1 7

Figure 1.1 (see facing page). Map showing the spatial 

extent of this assessment. The Western United States 

region consists of five level II ecoregions (modified from 

U.S. Environmental Protection Agency, 1999); they are 

the Marine West Coast Forest, Western Cordillera, Cold 

Deserts, Warm Deserts, and Mediterranean California. The 

level III ecoregions also are shown. The total area of the 

Western United States is approximately 2.66 million square 

kilometers. The land-use and land-cover classes shown on 

the map represent conditions that existed around 2005.

Marine West Coast Forests

Western Cordillera

Warm Deserts

Mediterranean

California

Index map of

Level II ecoregions in the

Western United States

Cold

Deserts

Water

Developed

Mechanically disturbed 

 (national forest)

Mechanically disturbed 

 (other public protected)

Mechanically disturbed 

 (private land)

Mining

Barren

Deciduous forest

Evergreen forest

Mixed forest

Grassland

Shrubland

Agriculture

Hay/pasture

Herbaceous wetland

Woody wetland

Ice/snow

Level III

Level II

Ecoregion boundary

Land cover Western Cordillera

C Cascades

NC North Cascades

ECSF East Cascades—

 Slopes and Foothills

KM Klamath Mountains

BM Blue Mountains

SNM Sierra Nevada Mountains

NR Northern Rockies

CR Canadian Rockies

WUM Wasatch-Uinta Mountains

MR Middle Rockies

SR Southern Rockies

ANM Arizona-New Mexico Mountains

Marine West Coast Forest

CR Coast Range

PL Puget Lowland

WV Willamette Valley

Cold Deserts

CP Columbia Plateau

SRP Snake River Plain

NBR Northern Basin and Range

CBR Central Basin and Range

WB Wyoming Basin

CP Colorado Plateaus

ANP Arizona-New Mexico Plateau

Warm Deserts

MBR Mojave Basin and Range

SBR Sonoran Basin and Range

MA Madrean Archipelago

CD Chihuahuan Deserts

Mediterranean California

CCV Central California Valley

SCM Southern California Mountains

SCCCOW Southern and Central California 

 Chaparral and Oak Woodlands

EXPLANATION
8 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The assessment was conducted using a methodology 

framework that (1) linked land use, land management, and 

climate data with statistical and process-based methods and 

models to generate spatially and temporally explicit carbon 

storage and GHG flux estimates; (2) used remote sensing 

input data, existing resource and soil inventories, climate 

histories, and measurements made by a national network 

of streamgages; and (3) applied a set of future land- and 

climate-change scenarios to the assessment to estimate a 

range of carbon stocks and sequestration rates in ecosystems. 

The major components of the assessment methodology and 

their connections are shown in figure 1.2, with corresponding 

chapters of this report marked in the boxes and methodological 

details described in the chapters. 

The methodology framework shown in figure 1.2 is both 

spatially and temporally explicit. The spatial foundation of 

the assessment is the LULC modeling component (chapter 2), 

in which the ecosystems were mapped seamlessly, and all 

pixels were partitioned into LULC and LULC-change classes. 

The temporal foundation of the assessment was twofold and 

included baseline data (currently available data for various 

controlling variables) and future projected data (generated 

by the use of scenarios; chapter 6). Both the baseline and 

future projected data (from contemporary time to 2050) were 

collected in a manner consistent with the Intergovernmental 

Panel on Climate Change (IPCC) Special Report on Emission 

Scenarios (Nakicenovic and others, 2000). The area burned 

by, severity of, and emissions from wildland fires during both 

the baseline and future projection periods were estimated by 

integrating remote sensing data with statistical and landscape 

modeling (chapters 3 and 8). The baseline and future projected 

terrestrial ecosystems’ carbon stocks and fluxes were estimated 

by using process-based models, which took into account 

various biomass and soil-carbon input data as well as the 

the results of LULC and wildland-fire modeling (chapters 5

and 9). Estimates of baseline carbon flux and sequestration in 

both inland and coastal aquatic ecosystems were calculated 

separately and were based on a series of studies detailed in 

chapters 10 and 11. General circulation models of future 

climate-change projections (described in chapter 7) were 

Figure 1.2. Flow diagram showing the general methodology 

framework. The heading in each box represents a major 

component of the assessment. The chapter numbers indicate 

where in this report those components are discussed. Arrows 

LULC scenarios 

(chapter 6)

Regional LULC change scenarios 

aligned with IPCC-SRES scenarios

A1B, A2, and B1, projected to 2050

Climate projections

(chapter 7)

General circulation models 

aligned with IPCC-SRES scenarios 

A1B, A2, and B1, projected to 2050

LULC modeling 

(chapters 2 and 6)

Including baseline and projected 

future annual LULC and 

forest age maps

Fire modeling 

(chapters 3 and 8)

Including baseline and projected 

future fire areas, severity, and 

GHG combustion emissions

Aquatic carbon estimation

(chapters 10 and 11)

Including carbon fluxes and burials

in inland and coastal waters

Terrestrial carbon and GHG modeling 

(chapters 5 and 9)

Including baseline and

projected future carbon stocks,

carbon fluxes, and GHG fluxes

Estimates and data products

(Various chapters and chapter 12)

Including spatially and temporally explicit estimates

of baseline and projected future carbon stocks,

carbon fluxes, other GHG fluxes, and analyses

Input data 

(Various chapters)

Including biomass,

GHG emission

factors, data 

derived from 

remote sensing, 

soils, and landmanagement

variables

show relations between components. GHG, greenhouse gas; 

IPCC-SRES, Intergovernmental Panel of Climate Change Special 

Report on Emissions Scenarios (Nakicenovic and others, 2000); 

LULC, land use and land cover.
Chapter 1 9

incorporated into the assessment to allow for an analysis of 

the effects of future climate change. The relation between the 

estimates of carbon sequestration and flux and natural and 

anthropogenic processes is briefly presented in chapter 12.

Both current and projected future changes in carbon 

storage and GHG fluxes were estimated in the assessment in 

order to establish a baseline and provide a range of potential 

carbon-sequestration capacities, which is a requirement of 

the EISA. The term “baseline” is defined as the average 

contemporary annual conditions to be assessed. Different 

components of the assessment have different ranges of 

baseline years because they are limited by the years for 

which data were available, as follows: LULC (1992–2005), 

wildland fires (2001–2008), terrestrial carbon and GHG 

fluxes (2001–2005), and aquatic carbon fluxes (1920s to 

present). The input datasets used for the assessment include 

those developed by the USGS and other agencies and 

organizations. The output datasets are in the form of either 

annual digital maps or annual statistics. The digital maps have 

a nominal spatial resolution of 250 by 250 meters. Because the 

assessment was conducted at both national and broad regional 

scales, the resulting information and data products should be 

applied only at the regional scale or broader.

The methodology was developed to meet the above‐noted 

objectives, particularly to analyze the carbon dynamics in 

relation to land use, land management, and climate changes. 

This assessment did not include a GHG life-cycle analysis 

or an economic feasibility modeling of land use changes. In 

addition, vegetation dynamics from succession or climate 

change were not modeled for the assessment, and the 

major components of the assessment were not coupled in a 

completely integrative modeling system (such a modeling 

system is not yet available for such a comprehensive 

assessment). The justification of the methodology, design 

rationales, and technical specifications are detailed in Zhu and 

others (2010) and are therefore not repeated in this report. 

This assessment is organized by five level II ecological 

regions (ecoregions), which were adapted from the U.S. 

Environmental Protection Agency ecoregion map (EPA, 

1999): (1) Western Cordillera, (2) Marine West Coast Forest, 

(3) Cold Deserts, (4) Warm Deserts, and (5) Mediterranean 

California (fig. 1.1). All of the assessment models were 

parameterized and the results were calibrated and validated on 

the basis of these ecoregions. In this report, the term “region” 

is often used in a general sense, depending on the context, 

whereas the term “ecoregion” refers to the EPA ecoregion 

hierarchy (EPA, 1999). The major terrestrial and aquatic 

ecosystems are analyzed within these ecoregions. The use 

of the ecoregions and the NLCD’s LULC classes chosen for 

the ecosystems in this assessment suggests that the reported 

results are meaningful within the defined ecoregion and 

ecosystem boundaries and may not be directly comparable 

with other national-level or regional estimates because of 

the different boundary definitions. Further discussion of 

the ecoregions and ecosystems may be found in Zhu and 

others (2010). 

The term “flux” refers both to emissions of GHG (such 

as carbon) to the atmosphere and to uptake by ecosystems. In 

presenting the results of terrestrial carbon flux assessment, the 

terms “net flux” and “net ecosystem carbon balance” (NECB) 

are also used interchangeably in the report to refer to the 

net rate of the change in carbon storage in ecosystems. The 

terms used in calculating NECB and (or) net flux include “net 

ecosystem production” (NEP, which is the difference between 

the net primary production and the heterotrophic respiration), 

“long-term fire emissions,” and “biomass harvesting.” When 

reporting losses or gains in carbon storage, a negative number 

indicates carbon uptake, carbon sequestration, or a carbon 

sink; a positive number indicates a carbon emission or a 

carbon source. These conventions are used throughout the 

report unless noted. The usages follow standard conventions 

found in the literature on this topic (such as Chapin and others, 

2006; EPA, 2012) and are consistent with the terms used in 

the assessment report for the Great Plains region (Zhu and 

others, 2011).

In addition to assessing carbon storage and fluxes in 

ecosystems, the fluxes or emissions of other GHGs (such as 

CO2, CH4, CO, DIC, and N2O) were also assessed. Fluxes 

or emissions of the other GHGs are reported as carbon 

dioxide equivalent (CO2-eq) values and flux estimates were 

calculated on the basis of their respective global warming 

potential factors. 

The units of measurement used in this report also follow 

previous usages. The total amount of carbon for a given region 

is reported in teragrams of carbon (TgC). When reporting 

carbon stock per unit of area, the values are given in kilograms 

of carbon (kgC). When reporting the carbon flux per unit of 

area, the values are given in grams of carbon (gC). 

Whenever possible, the estimates are provided as a range 

of values in order to represent the spread of variability in 

assessment results. The ranges of values were derived on the 

following basis: (1) the range of baseline values was derived 

from the minimum and maximum of averages of model runs 

over the years 2001 to 2005, and (2) the range of projected 

future values was derived from the means of the unique LULC 

scenarios, climate-change projections, and biogeochemical 

models over projection years (2006–2050). The same 

calculations were applied to the baseline and future potential 

components of the wildland-fire assessment (chapters 3

and 8). For the aquatic ecosystem assessment (chapter 10), the 

range of values was derived from the 5th and 95th confidence 

intervals of Monte Carlo simulations.
10 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

1.2. Regional Geography

The five level II ecoregions covered by this assessment 

include the Western Cordillera, the Marine West Coast Forest, 

the Cold Deserts, the Warm Deserts, and Mediterranean 

California. The five ecoregions can be grouped into two 

large areas: (1) the Western Cordillera and Marine West 

Coast Forest, and (2) the Cold Deserts, Warm Deserts, and 

Mediterranean California. The following sections summarize 

the climate, physiography, hydrology, vegetation, and land 

use in these groupings of ecoregions. This geographic 

characterization provides a foundation for understanding 

the differences in carbon sequestration and fluxes between 

ecoregions in the Western United States. 

1.2.1. The Western Cordillera and Marine West 

Coast Forest 

The maritime and inland mountains and forests of the 

Western United States generally coincide with the Western 

Cordillera and Marine West Coast Forest (fig. 1.2). The 

mountainous areas of the Pacific Coast States include the 

Coast Range, the Cascades (including the North Cascades 

and the East Cascades—Slopes and Foothills), the Klamath 

Mountains, and the Sierra Nevada Mountains. Inland, the 

mountainous areas include the Rocky Mountains (Canadian 

Rockies, Northern Rockies, Middle Rockies (including 

the Black Hills), and Southern Rockies), Blue Mountains, 

Wasatch-Uinta Mountains, and the Arizona-New Mexico 

Mountains. These ecoregions contain some of the country’s 

wettest climates (coastal temperate rain forests) and extremely 

cold climates (high alpine peaks), as well as semiarid and arid 

areas at low elevations, especially in the southern portions of 

the area. Although this area is mostly forested in comparison 

to the surrounding ecoregions, grasslands/shrublands also 

cover some parts of it. Forestry, mining, livestock grazing, 

wildlife habitat, tourism, and recreation are major land uses, 

along with some cropland and pasture in the larger valleys.

The Western United States is generally more arid than 

the rest of the country. Because of the topographic effect of 

the mountains, however, precipitation and runoff amounts 

in these two ecoregions are higher than in the adjacent 

ecoregions in the Great Plains, Basin and Range, and deserts. 

As much as 80 percent of the runoff is snowmelt (Stewart and 

others, 2004) and runoff distinctly increases with elevation, 

contributing to the headwaters of major rivers such as the 

Columbia and Colorado Rivers. A large portion of runoff 

originates in a relatively small fraction of the area compared 

to the Eastern United States, where runoff is relatively and 

spatially more uniform (Lettenmaier and others, 2008). 

Another distinct hydrologic feature is the Great Basin, a 

large endorheic (closed) basin that is disconnected from 

any coastal outlet. Therefore, any water that falls as rain or 

snow into this region does not escape out of it; surface water 

either evaporates or percolates instead of flowing toward the 

ocean (Orme, 2002).

The Western Cordillera ecoregion is a region of high, 

rugged, mostly forested mountains with a few open valleys. 

Plants, animals, and land use vary greatly with elevation. 

The lower elevations are commonly covered by grasslands/

shrublands, the middle elevations are mostly forested, and 

most of the higher alpine areas above the timberline are 

covered with snow and ice for much of the year. Coniferous 

forests vary by latitude, elevation, and proximity to maritime 

influence but are primarily dominated by species such as 

Douglas‐fir (Pseudotsuga menziesii), western hemlock (Tsuga 

heterophylla), western red cedar (Thuja plicata), subalpine 

fir (Abies lasiocarpa), grand fir (A. grandis), Engelmann 

spruce (Picea engelmannii), whitebark pine (Pinus albicaulis), 

lodgepole pine (P. contorta), ponderosa pine (P. ponderosa), 

and quaking aspen (Populus tremuloides).

Numerous small- to medium-sized streams and rivers 

and many small, naturally formed mountain lakes are found 

at high elevations (Melack and others, 1997; EPA, 2009). 

Caldera lakes, such as Crater Lake in Oregon and Yellowstone 

Lake in Wyoming, are located in the ecoregion (EPA, 2009). 

Several large rivers, such as the Columbia, Snake, Missouri, 

and Colorado River, have their headwaters in this region; 

downstream, these rivers are totally or partially regulated 

(Benke and Cushing, 2005). Grazing, which is the leading 

land use in the valleys and lower elevations of the Western 

Cordillera, has had a major impact on the quality of lands and 

streams. Timber harvesting is an important land use in the 

more heavily forested lower and middle elevations. Mining 

activities cover relatively small but numerous areas. Wildland 

fires are common and can burn extensive areas during drought 

years, especially when preceded by moist years with high 

vegetation productivity (Swetnam and Betancourt, 1990; 

Westerling and others, 2006; Littell and others, 2009). Large 

areas of the region are Federally managed public lands. 

The Marine West Coast Forest ecoregion is characterized 

by a cool, moist climate with dry summers and wet, generally 

snowless winters. The low mountains of the Coast Range 

are covered by highly productive, rain-drenched needleleaf 

evergreen forests. The high levels of precipitation contribute 

to the magnitude of the streamflow found in many of the 

large rivers of the ecoregion, particularly the Columbia River. 

The Columbia, Umpqua, Rogue, Klamath, and Sacramento 

Rivers have their headwaters in the Western Cordillera and 

run through the maritime forests before draining to the Pacific 

Ocean. Sitka spruce (Picea sitchensis) forests originally 

dominated the fog-shrouded coast, and a mosaic of western 

red cedar, western hemlock, and seral Douglas-fir blanketed 

the inland areas. Wildland fires are rare, largely because of 

the moisture regime of this ecoregion; however, wildland fires 
Chapter 1 11

can be severe and extensive when they do occur (Agee, 1993; 

Littell and others, 2009). Today, Douglas-fir plantations are 

prevalent on the intensively logged and managed landscape 

and play a major role in producing forest carbon stocks. In 

California, redwood (Sequoia sempervirens) forests, which 

represent one of the largest carbon stocks in the country, 

are a dominant component of the region, along with some 

hardwoods such as tanoak (Lithocarpus densiflorus), 

Pacific madrone (Arbutus menziessi), bigleaf maple (Acer 

macrophyllum), and red alder (Alnus rubra). This ecoregion 

includes the drier, flatter, and more populated Willamette 

Valley and Puget Lowland, which are in the rain shadow of 

the Coast Range and Olympic Mountains. The fertile soil and 

temperate climate make the Willamette Valley an extremely 

productive agricultural area. 

1.2.2. Cold Deserts, Warm Deserts, and 

Mediterranean California

The Cold Deserts, Warm Deserts, and Mediterranean 

California ecoregions stretch from Canada to Mexico and from 

the Pacific to the Great Plains, covering portions of 11 Western 

States. They are distinguished from the adjacent Western 

Cordillera and Marine West Coast Forest ecoregions by their 

aridity; mostly shrub, grass, and desert scrub vegetation; 

and generally lower relief and elevations. The dominant 

landforms include plains with hills and low mountains, 

plateaus and high-relief tablelands, some high mountains, and 

intermountain basins and valleys. The climate of the deserts 

is generally dry and Mediterranean California has a milder 

Mediterranean (hot summer and mild, wet winter) climate. 

Because of the climate, the hydrology of the ecoregions is 

different than that of the Western Cordillera and Marine 

West Coast Forest ecoregions. The annual precipitation in 

these ecoregions is highly variable and extreme droughts 

are not uncommon. Most streams and small rivers in these 

ecoregions are ephemeral, and the few perennial rivers 

originate in the adjacent forested mountainous ecoregions. 

A high proportion of the region is Federally managed public 

land, and the hydrology of many of the larger rivers has been 

greatly modified by dams, irrigation projects, and groundwater 

and surface-water extraction. The dry conditions and water 

withdrawals have caused some internal drainages to end in 

saline lakes (such as Utah’s Great Salt Lake) or desert basins 

without reaching the ocean.

The Cold Deserts ecoregion is arid and includes a variety 

of physiographic features, such as basin-and-range terrain 

(a series of alternating linear valleys and mountain ranges), 

broad plateaus, and other mountains ranges and valleys. The 

ecoregion includes the Columbia Plateau and Snake River 

Plain (both of volcanic origin), the northern and central Great 

Basin, the Wyoming Basin, and the Colorado Plateau. The 

ecoregion is almost completely surrounded by the wetter, 

higher, more rugged, and forested mountain ranges of the 

Western Cordillera ecoregion. These wetter regions feed some 

of the headwaters and upper reaches of smaller rivers such as 

the Humboldt, Bear, Truckee, and Sevier Rivers. Vegetation 

is sparse and typically dominated by cold-temperate species 

such as sagebrush (Artemisia spp.), various bunchgrasses, and 

saltbush (Atriplex spp.); in the southern part of the ecoregion, 

there is more blackbrush (Coleogyne ramosissima), winterfat 

(Krascheninnikovia lanata), and greasewood (Sarcobatus 

vermiculatus). Juniper (Juniperus spp.), pinyon pine (Pinus 

edulis), and singleleaf pinyon (P. monophylla) grow in the 

mountains, along with other conifers at higher elevations. 

Some areas are barren. Wildland fires are common and 

their occurrence is strongly related to climate, vegetation 

productivity, and the presence of invasive species such as 

cheatgrass (Bromus tectorum) (D’Antonio and Vitousek, 1992; 

Brooks and others, 2004; Mensing and others, 2006). Most 

of the ecoregion is used as rangeland. There are agricultural 

lands where irrigation is possible, either by groundwater or 

by diverting water from the Snake and Columbia Rivers, 

which flow through the region. Lakes formed by mainstem 

impoundments are common, including Lake Powell (the 

reservoir formed by Glen Canyon Dam on the Colorado River) 

and Franklin D. Roosevelt Lake (formed by the Grand Coulee 

Dam on the Columbia River). 

The Warm Deserts ecoregion includes the Mojave, 

Sonoran, and Chihuahuan Deserts of the southwestern United 

States. Most of the ecoregion consists of basin-and-range 

terrain, where typically north-to-south-trending mountains 

are separated by broad basins and valleys bordered by sloping 

alluvial fans. As the name implies, this ecoregion is warmer 

than the Cold Deserts to the north, and large parts of the 

ecoregion are drier and at lower elevations. Winter snow 

is rare. Compared to the Cold Deserts, a larger percentage 

of the annual precipitation in this more subtropical desert 

ecoregion falls during the summer months and contributes 

to the rich diversity of plants and animals. This ecoregion 

encompasses the middle and lower sections of the Colorado 

and Rio Grande Rivers, which drain southward to the Gulf 

of California and the Gulf of Mexico, respectively. In many 

areas of the Mojave and western and central Sonoran Deserts, 

desert scrub commonly consists of creosote bush (Larrea 

tridentata) and white bursage (Ambrosia dumosa). In the 

eastern Sonoran Desert, the palo verde (Cercidium spp.)-

cacti-mixed scrub vegetation includes the saguaro (Carnegia 

gigantea). Farther to the east, the high Chihuahuan Desert 

includes some desert grassland and large areas of arid 

shrubland dominated by creosote bush. The higher mountains 

in the ecoregion are forested by oak (Quercus spp.), juniper, 

and pinyon woodlands. Historically, wildland fires have been 

rare in the Warm Deserts, but the presence of invasive species 

has lead to an increase in wildland-fire occurrence (D’Antonio 

and Vitousek, 1992; Brooks and others, 2004; Brooks and 
12 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Chambers, 2011). Large parts of the Warm Deserts ecoregion 

are Federally owned, and many large lakes in the southwestern 

canyon regions are the products of large dam construction 

projects (EPA, 2009). The largest reservoir in the United 

States, Lake Mead (which was formed by the construction of 

the Hoover Dam), is located in this ecoregion. Water levels in 

reservoirs throughout this ecoregion can vary greatly because 

of drought and large-scale water removal for municipal and 

agricultural uses. 

The Mediterranean California ecoregion is distinguished 

by a warm, mild Mediterranean climate, shrubland vegetation 

consisting of chaparral mixed with areas of grassland and 

oak savanna, agriculturally productive valleys, and a high 

population (over 30 million people) in extensive urban 

agglomerations. The vegetation on the chaparral-covered 

hills includes ceanothus (Ceanothus spp.), California buckeye 

(Aesculus californica), manzanita (Arctostaphylos spp.), scrub 

oak (Quercus spp.), and mountain-mahogany (Cercocarpus

spp.). Coast live oak (Quercus agrifolia), canyon live oak (Q. 

chrysolepis), Pacific poison oak (Toxicodendron diversilobum), 

and California black walnut (Juglans californica) also grow 

in this ecoregion. The coastal sage scrub consists of chamise 

(Adenostoma fasciculatum), red shank (A. sparsifolium), white 

sage (Salvia apiana), black sage (Salvia mellifera), buckwheat 

(Eriogonum fasciculatum), golden-yarrow (Eriophyllum 

confertifolium), and coastal cholla (Cylindropuntia prolifera). 

Wildland fires occur frequently in Mediterranean California. 

Although wildland fires are driven by climate in the arid parts 

of the Western United States, human influences, invasive 

species, and extreme winds are particularly important drivers 

in the Mediterranean California ecoregion (Keeley, 2006; 

Syphard and others, 2007; Moritz and others, 2010). Most 

of the larger perennial streams in the ecoregion originate 

in the bordering higher, wetter, mountainous ecoregions. 

Although the ecoregion is centered on the broad San 

Joaquin and Sacramento Valleys, it also contains several 

low coastal mountain ranges and, in the south, some higher 

mountain ranges, all of which are of sufficient elevation to 

contain perennial streams. The bigger rivers in the area—the 

Sacramento, San Joaquin, and Salinas Rivers—all drain to 

the Pacific Ocean. The widespread and diversified agriculture 

with many high-value crops and supporting hydrological 

engineering have greatly altered the ecosystems that occupy 

this ecoregion. Urban, suburban, and industrial land uses are 

significant drivers of land-cover change in some parts of the 

ecoregion. The central foothills and some of the coastal ranges 

are livestock grazing areas. 

The river discharge into the Pacific coastal waters 

is dominated by small mountainous rivers. These small 

mountainous rivers tend to be short, drain watershed areas 

with high relief, and typically have river mouths discharging 

near the coast rather than into an estuary (Milliman and 

Syvitski, 1992; Wheatcroft and others, 2010). The result is 

that the Pacific coastal waters receive disproportionately 

large sediment loads compared to the other regions, which 

bury carbon directly or help transport it into the deep ocean 

(Hedges and Keil, 1995). The two largest rivers in the west, 

the Columbia and Sacramento Rivers, both drain areas of 

intensive agriculture and carry elevated nutrient loads to 

coastal waters, leading to an elevated carbon uptake by 

phytoplankton. Another important physiographic attribute 

is the shape of the Pacific Ocean basin, which allows the 

California Current to supply nutrients very close to the coast, 

which also contributes to phytoplankton production and—

because of the high influx of sediment—the sequestration of 

carbon in coastal waters (Cotrim Da Cunha and others, 2007; 

Aufdenkampe and others, 2011). Finally, the presence of a 

narrow continental shelf results in the transport of a large 

proportion of sediment- and phytoplankton-derived carbon 

into the deep ocean, where it is effectively sequestered from 

the atmosphere (Hedges and Keil, 1995).

1.3. National and Regional Studies of 

Carbon Stock and Greenhouse-Gas 

Fluxes in Ecosystems 

Existing estimates of carbon storage, sequestration, and 

GHG fluxes varied widely by ecosystem and by region in the 

Western United States. Forests occupy significant land areas 

and are the most important carbon sink. The forest inventories 

that were conducted by the U.S. Department of Agriculture 

(USDA) Forest Service indicated that in 2005, the forests 

in the Pacific Coast and Rocky Mountain regions (Forest 

Service regions 1 through 6), regardless of ownership, had a 

combined carbon stock of 15,095 teragrams of carbon (TgC) 

(15.7 kilograms of carbon per square meter, or kgC/m2); the 

carbon stock in forests managed by the Forest Service was 

8,278 TgC (18.0 kgC/m2) (J.E. Smith and Heath, 2008; Heath 

and others, 2011).

Among the major forest carbon pools in the Western 

United States, live biomass represented approximately 

50 percent of the total carbon stock, with the remaining 

carbon stock approximately evenly divided between soil 

organic carbon and dead woody debris (Donnegan and others, 

2008; USDA, 2011). Furthermore, forests in the region 

sequestered carbon at an approximate rate of 87 teragrams of 

carbon per year (TgC/yr,) or 90.85 grams of carbon per square 

meter per year (gC/m2/yr) (excluding the soil organic carbon 

pool) (J.E. Smith and Heath, 2008). In a separate analysis of 

recent forest inventories, the carbon stock in western forests 

was calculated for the five ecoregions used for this assessment 

(Brad Smith, USDA Forest Service, unpub. data, 2010; USDA 

Forest Service, 2012b). The results of the analysis showed 

that, among the five ecoregions and for all the major carbon 

pools, the Western Cordillera ecoregion contained the most 

stored carbon in forests and the Marine West Coast Forest had 

the largest carbon stock per unit of area in forests (table 1.1). 
Chapter 1 13

Table 1.1. Total and per-unit-of-area carbon stock from all of 

the major pools in the forest ecosystems in the five ecoregions 

of the Western United States. 

[Data were derived from recent USDA Forest Service inventories and 

provided by Brad Smith (USDA Forest Service, unpub. data, 2010). 

Ecoregions are modified from EPA (1999). EPA, Environmental Protection 

Agency; kgC/m2, kilograms of carbon per square meter; TgC, teragrams of 

carbon]

Modified level II EPA ecoregion

Carbon 

stock

(TgC)

Carbon stock per 

unit of area

(kgC/m2

)

Western Cordillera 9,878.0 15.9

Marine West Coast Forest 1,809.5 29.6

Cold Deserts 1,248.8 7.0

Warm Deserts 291.5 6.7

Mediterranean California 351.4 11.4

Western United States (total) 13,579.2 14.5

The most recent national GHG inventory report covering 

the conterminous United States suggested a net flux of 

−293.1 TgC in 2010 by forests, grasslands, agricultural lands, 

and settled areas, which represented an offset of approximately 

15.4 percent of the total carbon dioxide emissions in the 

United States (EPA, 2012). Although the national inventory 

did not differentiate between regions, the net carbon flux per 

unit of area may be derived for three main categories that were 

similar to the ecosystem categories used for this assessment: 

forestlands remaining as forestlands, croplands (which include 

both row crops and hay and pasture and are similar to the 

agricultural lands ecosystem of this assessment) remaining 

as croplands, and grasslands (which include both shrublands 

and grasslands and are similar to the grasslands/shrublands 

ecosystem of this assessment) remaining as grasslands. 

From 2005 to 2010 for the conterminous United States, the 

derived mean net carbon flux rate per unit of area was −96.75, 

−3.42, and −0.97 gC/m2/yr, respectively, for the above three 

categories. Using similar input data, Hayes and others (2012) 

separately determined that from 2000 to 2006, the average 

annual net fluxes for forests and croplands in the United States 

were −244.4 and −264.3 TgC/yr, respectively.

Using forest inventory data collected from 2000 to 2008 

and covering the six USDA Forest Service regions (regions 1 

through 6) in the Western United States (from the Pacific 

Coast to the Rocky Mountains), Heath and others (2011) 

estimated that net annual average carbon flux from forested 

land ranged from 24.9 to −111.2 TgC/yr (mean value of −43.1 

TgC/yr, or −93.8 gC/m2/yr). The annual carbon sink in the 

Western United States’ forested land was from publicly owned 

forests; privately owned forests were a minor source (Heath 

and others, 2011). In a separate study for the State of Oregon, 

where climate and other biophysical conditions are favorable 

for carbon sequestration (particularly in the Marine West 

Coast Forest part of the State), D.P. Turner, Gockede, and 

others (2011) used forest-inventory data, land-use maps, and 

a process-based model to obtain estimates of per-unit-of-area 

net ecosystem production (NEP) for 2007 (a year with nearaverage climate conditions). The estimates were −101, −143, 

−88, 18, and −7 gC/m2/yr, respectively, for forests, agricultural 

lands, woodlands, grasslands, and shrublands ecosystems. 

Carbon sequestration is a function of the biogeochemical 

exchange between plants and the atmosphere, and it is 

strongly influenced by key controlling processes such as land 

use, land-management activities, ecosystem disturbances, 

and climate (Bachelet and others, 2003; Law and others, 

2004; Running, 2008). Because water availability is the 

most limiting factor in the Western United States, carbon 

production in ecosystems tends to follow a precipitation 

gradient from west to east (Derner and Schuman, 2007). As a 

result, there is a high degree of year-to-year variation driven 

by the availability of moisture and the frequency or severity 

of related ecosystem disturbances, such as wildland fires. In 

a study comparing a year with normal average precipitation 

with a drought year, it was found that drought can reduce 

the NEP in forests of the Pacific Northwest by as much as 

81 percent (D.P. Turner, Gockede, and others, 2011). On the 

other hand, simulation studies (such as Hudiburg and others, 

2009; Smithwick and others, 2009) indicated that, under future 

climate-change scenarios with more precipitation and higher 

temperatures, increases in both carbon storage and the rate of 

sequestration may be expected.

Recent studies have documented an increase in 

wildland‐fire activity in the Western United States as a 

result of climate change (Swetnam and Betancourt, 1990; 

Gedalof and others, 2005; Westerling and others, 2006; 

Littell and others, 2009). The impact of wildland fires on 

carbon sequestration in ecosystems included both (1) the 

immediate release of GHGs from combustion emissions and 

(2) the long-term combined effects of decomposing biomass, 

which releases carbon into the atmosphere, and regenerating 

vegetation, which increased the uptake of carbon (Law and 

others, 2004; Hurteau and Brooks, 2011; D.P. Turner, Ritts, 

and others, 2011). Although the short-term combustion 

emissions may be estimated relatively accurately by using 

remote-sensing data and emission models (van der Werf 

and others, 2010; French and others, 2011; chapter 3 of 

this report), other studies have shown that emissions from 

decomposition over the long term (years and decades) can be 

higher but more uncertain because burned landscapes may 

require years or decades for their NEP to return to pre-fire 

levels (Kashian and others, 2006; Cleary and others, 2010; 

Hurteau and Brooks, 2011; Kashian and others, in press). 

If the increases in fire frequency since 2000 in the Western 

United States continue into the future, the effects on carbon 

sequestration in ecosystems can be profound and need to be 

properly accounted for.
14 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Various land-use policies and land-management actions 

in the Western United States have been implemented over 

the last 30 years to adapt to the changing climate and to the 

societal needs for ecosystem services. For example, since the 

1980s in the Pacific Northwest, a decline in forest clearcutting, 

which was the result of changes in forest-management 

policies, has led to an increased per-unit-of area net flux of 

carbon: from 48 gC/m2/yr (a source) in the 1980s to −141 and 

−136 gC/m2/yr (sinks) in the 1990s and 2000s, respectively 

(D.P. Turner, Ritts, and others, 2011). A similar trend with an 

overall smaller magnitude of change was also observed for 

private forests in the above study. In the forested landscapes 

of the Northern Rockies, forest thinning, prescribed burning, 

and mechanical fuel treatment are frequently applied forestmanagement practices. Such practices have been studied 

for both the positive and negative effects on restoring the 

fire regime and reducing fire emissions to the atmosphere; 

the results were mixed across landscape types in the 

Western United States. The mechanical fuel treatments 

were generally found to reduce fire severity, fire risks, and 

immediate combustion emissions (Stephens and others, 2009; 

Wiedinmyer and Hurteau, 2010; North and Hurteau, 2011); 

however, their long-term effects on carbon sequestration 

in ecosystems were mixed. The use of mechanical fuel 

treatments and forest thinning as a means to reduce emissions 

and increase carbon sequestration were found to be ineffective 

or counterproductive in the Pacific Northwest (Hudiburg and 

others, 2011; Mitchelle and others, 2009) and the Northern 

Rockies (Reinhardt and Holsinger, 2010), but beneficial in the 

Sierra Nevada in California (North and Hurteau, 2011).

Grasslands/shrublands are the most prevalent ecosystem 

types in the Western United States, occupying almost 

60 percent of the total land area. They are distributed primarily 

in the semiarid Great Basin and Colorado Plateau, as well 

as along the slopes of the major mountain systems. As with 

the forest ecosystems, carbon storage and sequestration in 

grasslands/shrublands ecosystems were highly correlated to 

the moisture gradient and influenced by land-management 

activities, particularly grazing-intensity management (Lal, 

2004; Derner and Schuman, 2007). Heavy grazing during 

extended seasons may cause changes in species composition 

(including C4 grasses replacing C3 grasses and the dominance 

of cheatgrass (Bromus tectorum) in sagebrush communities), 

which may lead to a reduced amount of aboveground 

biomass, accelerated soil decomposition, and a loss of soil 

organic carbon stock to the atmosphere (Bradley and others, 

2006; Derner and Schuman, 2007; Schuman and others, 

2009). Reducing (but not necessarily excluding) grazing 

intensity usually helps improve soil-carbon preservation and 

sequestration because there is more decomposed vegetation 

contributing to the soils (Schuman and others, 2009). Although 

the net flux of carbon per unit of area in arid lands tends to be 

small or negligible, grasslands/shrublands cover vast areas; as 

a result, land use and management still exerts profound effects 

on the overall carbon balance of the ecosystem (Follett, 2001). 

Most of the agricultural lands covered by this assessment 

are concentrated in the Mediterranean California ecoregion 

(where mainly orchards and annual vegetable crops are grown) 

and the Columbia River Basin and Snake River Plain in the 

Cold Deserts ecoregion (where irrigated row crops, hay, and 

pastures are dominant). In a study to quantify the effect of 

agriculture on California’s carbon balance, Kroodsma and 

Field (2006) modeled changes in biomass and soil carbon 

in all of the agricultural lands in the State. Between 1980 

and 2000, the study estimated the average annual net carbon 

flux for orchards (−26 gC/m2/yr), vineyards (−26 gC/m2/yr), 

annual vegetable crops (−14 gC/m2/yr), and annual silages 

(about 0 gC/m2/yr), with a mean value of −19 gC/m2/yr 

for all agricultural lands in California. The per-unit-of-area 

estimate for California was higher than the current-year (2010) 

EPA estimate (EPA, 2012) for all agricultural lands in the 

conterminous United States (CONUS), but was much lower 

than the estimate of −143 gC/m2/yr for the State of Oregon 

(D.P. Turner, Gockede, and others, 2011). In comparison, the 

assessment conducted for the Great Plains region (Zhu and 

others, 2011) produced an estimate of −18.8 gC/m2/yr for 

potential carbon sequestration by agricultural lands.

Bridgham and others (2006), who synthesized data from 

the literature, estimated that wetlands represented 11 percent 

of the total area of the United States (7 percent in Alaska, 

4 percent in the CONUS). Most of the CONUS wetlands are 

distributed in the Atlantic and Gulf Coast Coastal Plains, the 

Great Lakes States, and the Great Plains. In the five western 

ecoregions of this assessment, wetlands represented less 

than half of one percent of the total area, as mapped using 

the 1992 NLCD (Vogelmann and others, 2001). Although 

they noted that uncertainties were very high, Bridgham and 

others (2006) put the carbon stock and sequestration rates in 

the wetlands of the CONUS at 19,600 TgC and 17.3 TgC/yr, 

respectively, which translated to 45.5 kgC/m2 for the per-unitof-area of carbon stock and 40.1 gC/m2/yr for the per-unitof-area sequestration rate in the CONUS. The sequestration 

rate of wetlands in the CONUS was considered to be evenly 

distributed between peatlands, freshwater mineral soils, and 

tidal marshes (estuaries). Sequestration in estuaries is mostly 

accomplished as the result of sedimentation (Bridgham and 

others, 2006). Brevik and Homburg (2004) found that the 

net carbon flux in an estuary in southern California averaged 

−33 gC/m2/yr on the basis of an analysis of sediment samples 

spanning 5,000 years. Chmura and others (2003), however, 

estimated that sequestration in coastal salt marshes occurs 

at a much higher rate, ranging from 136.5 gC/m2/yr on the 

East Coast, to 206.3 gC/m2/yr in an estuary in southern 

California, to 296.6 gC/m2/yr on the Gulf Coast. Methane 
Chapter 1 15

emissions from ecosystems in the CONUS were estimated at 

approximately 50.4 TgCO2-eq/yr (Bridgham and others, 2006) 

and were mostly emitted from freshwater, mineral-rich soil in 

wetlands because of its low salinity content (Poffenbarger and 

others, 2011).

The emission, transport, and sequestration of carbon by 

aquatic ecosystems should be considered when estimating 

carbon balances in ecosystems (Chapin and others, 2006; Cole 

and others, 2007; Tranvik and others, 2009; Aufdenkampe 

and others, 2011). The existing national-scale studies 

suggested that lateral transport of carbon fixed within the 

CONUS and exported to coastal areas can represent between 

about 10 percent of the total carbon sequestered in forests 

(trees and soils), croplands, and shrublands (Pacala and 

others, 2001). Nearly all of the 3.9 to 5.2 gC/m2/yr consisted 

of inorganic carbon. Also, human-made reservoirs can 

also be sinks for carbon and can sequester between 1.3 and 

5.2 gC/m2/yr (Pacala and others, 2001). Although the role of 

aquatic ecosystems in transporting and sequestering carbon 

may be well documented for the CONUS, recent global 

studies have indicated that inland waters can also be sources 

of carbon emitted into the atmosphere (Cole and others, 

2007; Tranvik and others, 2009; Aufkenkampe and others, 

2011). The effect of carbon dioxide emissions from lakes and 

rivers and their roles in regional carbon budgets has yet to be 

determined for the Western United States. 

The above-referenced studies produced a range of net 

carbon flux estimates that were spatially and temporally 

variable; however, these estimates also provided a set of 

reference points against which this assessment may be 

compared. Table 1.2 provides a summary of the net carbon 

fluxes per unit of area from a sample of the referenced works 

for the four major terrestrial ecosystems covered in this 

assessment. Uncertainties and caveats reported in these studies 

were not reproduced for the table.

Table 1.2. Estimates of the mean net carbon flux per unit of area from a selected sample of studies. 

[Three sample estimates are included for each of the four major terrestrial ecosystems: forests, agricultural lands, grasslands/

shrublands, and wetlands. CONUS, conterminous United States; EPA, Environmental Protection Agency; gCm2/yr, grams of 

carbon per square meter per year]

Geography Mean net carbon flux 

(gC/m2

/yr) Source Timeframe of thesourced work

Forests

Western States −90.85 J.E. Smith and Heath (2008) Early 2000s.

CONUS −96.75 EPA (2012) 2010.

Oregon −136 D.P. Turner, Gockede, and others (2011) Early 2000s.

Agricultural lands

CONUS −3.42 EPA (2012) 2010.

Oregon −143 D.P. Turner, Ritts, and others (2011) 2007.

California −19 Kroodsma and Field (2006) 1980–2000.

Grasslands/shrublands

CONUS −0.97 EPA (2012) 2010.

Oregon1 18 D.P. Turner, Ritts, and others (2011) 2007.

Oregon2 −7 D.P. Turner, Ritts, and others (2011) 2007.

Wetlands

CONUS −40.1 Bridgham and others (2006) Various, previous decades.

Southern California3 −33 Brevik and Homburg (2004) Over 5,000 years.

Southern California3 −206.3 Chmura and others (2003) 1990s.

Aquatic ecosystems

CONUS4 3.9 to 5.2 Pacala and others (2001) Various, previous decades.

CONUS5 −1.3 to 5.2 Pacala and others (2001) Various, previous decades.

1

Grasslands only.

2

Shrublands only.

3

Specifically, coastal salt marsh.

4

Inland to coastal carbon export.

5

Carbon burial in reservoirs.
16 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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Chapter 2. Baseline Land-Use and Land-Cover Changes 

in the Western United States Between 1992 and 2005

By Terry L. Sohl1, Benjamin M. Sleeter2, Tamara S. Wilson2, Michelle A. Bouchard3, Rachel R. Sleeter2, 

Kristi L. Sayler1, Ryan R. Reker3, Christopher E. Soulard2, and Stacie L. Bennett4

2.1. Highlights

• Annual, 250-m resolution land-use and land-cover 

(LULC) maps were produced for the baseline period of 

1992 to 2005.

• Observed data derived from remotely sensed sources 

were used when possible for the baseline map 

products.

• When annual, observed data were not available, a 

spatial LULC model based on input data derived from 

LULC studies was used to produce the annual LULC 

maps.

• The baseline LULC change was relatively low but 

variable between ecoregions; some ecoregions 

experienced significant amounts of change and some 

ecoregions experienced very little change.

• LULC change associated with forestry was the most 

common form of LULC change, followed by urban 

development.

2.2. Introduction

As indicated in figure 1.2 (a graphic representation of the 

overall methodology for this assessment) of chapter 1 of this 

report, the mapping and modeling of LULC described in this 

chapter are some of the spatial foundations of this regional 

assessment and help define the boundaries and compositions 

of the assessed ecosystems. The results of the LULC mapping 

and modeling component feed into other components of 

the assessment, particularly chapter 5 (baseline terrestrial 

carbon storage and greenhouse-gas fluxes) and chapter 6

(development of future LULC scenarios).

The LULC in the Western United States is diverse; 

vast forests, shrublands, and grasslands are interspersed 

with human agricultural activities, mining, and some of the 

largest urban areas in the United States. Topography, soils, 

climate, and water availability interact to determine the 

landscape potential and anthropogenic land use, producing a 

mosaic of different LULC types across the West. Silviculture, 

agriculture, urban development, mining, and natural 

disturbances such as wildland fires have dramatically altered 

portions of the Western United States, but the LULC change 

is fragmented; some areas have experienced little change 

over the last century and others have experienced rapid and 

frequent changes. 

The annual LULC maps for the Western United States 

serve as the spatial and temporal foundation for assessing the 

baseline carbon storage and fluxes for terrestrial ecosystems 

(chapter 5). The classification scheme (as discussed below) 

is a combination of land-use and land-cover classes that 

closely follows the classes used by the 1992 National Land 

Cover Database (NLCD) (Vogelmann and others, 2001). 

The disturbance of ecosystems by wildland fires is discussed 

separately (chapter 3). Land-management activities (for 

example, crop tillage, crop rotation, and fertilization) are 

also discussed separately (chapter 4). In order to provide a 

partitioned spatial framework for the Western United States, 

the region was divided into five level II ecoregions (modified 

from U.S. Department of Environmental Protection (EPA), 

1999): Western Cordillera, Marine West Coast Forest, Cold 

Deserts, Warm Deserts, and Mediterranean California. The 

five ecoregions were mapped and modeled to create annual 

LULC maps for the baseline period of 1992 to 2005. The 

following sections discuss the data sources and methodologies 

used to map and model annual LULC change and the baseline 

LULC results. 

1

 U.S. Geological Survey, Sioux Falls, S.D.

2U.S. Geological Survey, Menlo Park, Calif.

3Arctic Slope Regional Corporation Research and Technology Solutions, Sioux Falls, S.D.

4U.S. Geological Survey, Sacramento, Calif.
18 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

2.3. Input Data and Methods

The baseline period for this assessment was defined as 

the period from 1992 to 2005. The baseline period allowed for 

an examination of recent LULC change and for the calibration 

of both the LULC and biogeochemical modeling frameworks 

before beginning the simulations of future LULC. The year 

1992 was chosen as the start of the baseline period because 

it marked the earliest year for which consistent, nationwide, 

high-spatial-resolution LULC data were available. A modified 

version of the 1992 National Land Cover Dataset (NLCD) 

(Vogelmann and others, 2001) served as the initial LULC data 

for this work; the NLCD data had been extensively assessed 

for accuracy (Stehman and others, 2003; Wickham and 

others, 2004). The year 2005 was chosen as the endpoint for 

the baseline period. The choice of the baseline years 1992 to 

2005 thus maximized the use of consistent, spatially explicit, 

nationwide, observed LULC data available when work on the 

assessment began. Scenario-based projections of potential 

future land-cover change were created to cover 2006 through 

2050 (see chapter 6 of this report) (fig. 2.1).

The NLCD thematic classification system provides a 

level of thematic detail that allows for an examination of the 

effects of LULC change on fluxes of carbon and greenhouse 

gases, but the classification system can also be directly 

collapsed to the primary ecosystem types that were analyzed 

for this assessment (table 2.1). The original resolution of the 

1992 NLCD was 30 meters, but the data were resampled to 

250 meters for this assessment to reduce the volume of data 

and hold the modeling requirements to a more manageable 

level. Several adjustments were made to the thematic classes 

in order to facilitate this assessment, including the collapsing 

of the four urban classes from the 1992 NLCD into one 

“urban/developed” class. Similarly, three agricultural classes 

from the 1992 NLCD (row crop, small grains, and fallow) 

were collapsed into one “agriculture” class that represented 

cultivated crops. 

The 1992 NLCD dataset was also augmented by 

incorporating information from LANDFIRE’s vegetation 

change tracker (VCT) data (Chengquan Huang and 

others, 2010) (fig. 2.2). The VCT data mapped natural and 

anthropogenic disturbances by analyzing historical layers 

of Landsat Thematic Mapper (TM) data. Polygons of 

clearcut forest derived from VCT data were used to populate 

“mechanically disturbed” classes 3, 4, and 5 (table 2.1) for 

1992. The three mechanically disturbed classes represented 

clearcuts that occurred on land owned by three different 

entities: (1) national forest, (2) other public land, and 

(3) private land. Given that each of these ownership types 

have varying management strategies, the Protected Area 

Database of the United States (PAD–US Partnership, 2009) 

was used to spatially distinguish ownership for the three 

disturbance classes. The PAD–US database includes Federal, 

State, and local protected lands, as well as information from 

national nonprofit organizations. The database does not 

cover all protected lands (such as conservation easements), 

but it is the most comprehensive and accurate protected 

lands database available for the United States. Thematically 

distinguishing clearcutting by these three different classes 

of ownership resulted in an improved ability to map and 

model LULC change related to forestry and thus improved 

the ability to examine the effects of forestry on carbon and 

greenhouse-gas fluxes.

Integrated model to assess the global environment (IMAGE 2.2)

IPCC-SRES scenarios—A1B, A2, B1

Baseline

Figure 2.1.

USGS Land Cover Trends project

Vegetation change tracker 1992 2000

200620102020203020402050

National Land Cover

Database

Figure 2.1. Timeline for LULC change mapping and modeling for both the baseline and scenario-based projections. The 

baseline period runs from 1992 to 2005; the modeled scenarios (from the Intergovernmental Panel on Climate Change’s 

Special Report on Emissions Scenarios (IPCC–SRES; Nakicenovic and others, 2000) were run from 2006 to 2050. The 

data sources at the top of the graphic were used to support the analysis of baseline, scenarios, or both. USGS, U.S. 

Geological Survey.
Chapter 2 19

Table 2.1. Thematic land-use and land-cover classes used in this assessment, the corresponding ecosystems defined for this 

assessment, percent area (from 1992) of the Western United States, and the source of the input data.

[LANDFIRE, Landscape Fire and Resource Management Planning Tools Project (Rollins, 2009); NLCD, National Land Cover Dataset (Vogelmann and others 

(2001); VCT, vegetation change tracker (a product of LANDFIRE; Chengquan Huang and others, 2010)]

Land-use and land-cover 

(LULC) class Ecosystem Area (percent) Source

Open water Aquatic ecosystems 1.5 NLCD—Open water.

Urban/developed Other lands 1.0 NLCD—Low-intensity residential.

NLCD—High-intensity residential.

NLCD—Commercial/industry/transportation.

NLCD—Urban/recreational grasses.

Mechanically disturbed—National forest Forests 0.4 LANDFIRE VCT.

Mechanically disturbed—Other public land Forests 0.1 LANDFIRE VCT.

Mechanically disturbed—Private land Forests 0.1 LANDFIRE VCT.

Mining Other lands 0.1 NLCD—Quarries/strip mines/gravel pits.

Barren Other lands 3.8 NLCD—Bare rock/sand/clay.

Deciduous forest Forests 2.0 NLCD—Deciduous forest.

Evergreen forest Forests 23.9 NLCD—Evergreen forest.

Mixed forest Forests 1.4 NLCD—Mixed forest.

Grassland Grasslands/shrublands 13.9 NLCD—Grassland/herbaceous.

Shrubland Grasslands/shrublands 45.1 NLCD—Shrubland.

Cultivated crop Agricultural lands 3.6 NLCD—Row crops.

NLCD—Small grains.

NLCD—Fallow.

Hay/pasture Agricultural lands 2.5 NLCD—Pasture/hay.

Herbaceous wetland Wetlands 0.1 NLCD—Emergent herbaceous wetlands.

Woody wetland Wetlands 0.3 NLCD—Woody wetlands.

Ice/snow Other lands 0.1 NLCD—Perennial ice/snow.

The modified 1992 NLCD data served as the initial 

land cover dataset for the assessment. Annual LULC maps 

for the baseline period were required to adequately portray 

gross changes between LULC classes that could be missed 

by a wider temporal interval and thus could affect carbon and 

GHG calculations; however, there were no annual, nationally 

consistent, spatially explicit LULC data available for the entire 

baseline period of 1992 to 2005. NLCD data were available 

for 1992, 2001, and 2006 (Vogelmann and others, 2001; 

Homer and others, 2007; Xian and others, 2009), but different 

classification systems and different mapping methodologies 

between NLCD versions precluded the use of NLCD alone 

for providing LULC data for the 1992 to 2005 period. The 

VCT data were available on an annual basis, but only provided 

information on areas of disturbance such as forest clearcuts 

and fires (Chengquan Huang and others, 2010). The USGS 

Land Cover Trends project (Loveland and others, 2002) 

provided historical LULC data, but only sample-based data 

were available for 1992 and 2000. Even though the individual 

datasets could not provide the consistent, annual, wall-to-wall 

LULC maps needed for the assessment, they could be used 

to directly inform a spatial modeling framework to produce 

annual LULC maps from 1992 to 2005. 

The spatial modeling framework, “forecasting scenarios 

of land-cover change” (FORE–SCE), was used to produce 

annual LULC maps from 1992 to 2005. FORE–SCE was 

successfully used to model annual LULC maps for large 

geographic regions (Sohl and Sayler, 2008; Sohl, Sleeter, Zhu, 

and others, 2012; Sohl, Sleeter, Sayler, and others, 2012). The 

FORE–SCE model used separate but linked “Demand” and 

“Spatial Allocation” components to produce spatially explicit, 

annual LULC maps. The “Demand” component provided 

aggregate-level quantities of LULC change for a region, or 

a “prescription” for the overall regional LULC proportions. 

The “Spatial Allocation” component ingested “Demand” and 

produced spatially explicit LULC maps using a patch-based 

allocation procedure. 
20 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

122°00'W 121°45'W 121°30'W

47°

00'

N

46°

50'

N

46°

40'

N

122°00'W 121°45'W 121°30'W

47°

00'

N

46°

50'

N

46°

40'

N

EXPLANATION

Year of vegetation change

(forest cutting}

[Part C]

Ownership of land

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

Mount Rainier National Park

National forest

Other public land

Private land

0 5 10 MILES

0 5 10 KILOMETERS

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Figure 2–2.

N

Water

Developed

Mining

Barren

Deciduous forest

Evergreen forest

Mixed forest

Grassland

Shrubland

Agriculture

Hay/pasture

Herbaceous 

 wetland

Woody wetland

Ice/snow

Land cover

[Parts A and B]

A B

C

Mount Rainier National Park boundary

Figure 2.2. Map showing how data from LANDFIRE’s vegetation 

change tracker (VCT) provided information on ecosystem 

disturbances. In this assessment, the VCT data were used 

to identify polygons that represented forest clearcuts for the 

baseline period (1992–2005). A, Land-use and land-cover map 

of a portion of the Western United States. B, Inset map showing 

land use and land cover of Mount Ranier National Park and the 

surrounding national forest, other public land, and private land. 

C, Inset map showing vegetation changes in the same area as 

part B. The small colored polygons outside of the national park 

boundary (national forest, other public land, and private land) 

represent forest clearcuts, color-coded by the year in which the 

clearcutting occurred. LANDFIRE, Landscape Fire and Resource 

Management Planning Tools Project.
Chapter 2 21

The “Demand” for the baseline LULC change was 

split into two time periods to take advantage of temporally 

specific historical data. Demand from 1992 to 2000 was 

provided by USGS Land Cover Trends data (U.S. Geological 

Survey, 2012a). The USGS Land Cover Trends project used 

a sampling approach and the historical archive of Landsat 

Multispectral Scanner (MSS), Thematic Mapper (TM), and 

Enhanced Thematic Mapper Plus (ETM+) data to produce 

estimates of LULC change for each of the 84 level III 

ecoregions (modified from EPA, 1999) in the conterminous 

United States (Loveland and others, 2002). Although the 

coarser-scale level II ecoregion framework was used for the 

overall assessment in the Western United States, the finer‐scale 

level III ecoregion framework served as the primary 

framework for all FORE–SCE-based LULC modeling, thus 

improving the representation of spatial LULC change patterns 

in the very heterogeneous Western United States. As a result, 

the “Demand” information from the USGS Land Cover Trends 

project was provided separately for each level III ecoregion, 

and the “Spatial Allocation” component of FORE–SCE was 

parameterized individually for each level III ecoregion. For 

the 1992 to 2000 period, USGS Land Cover Trends data 

provided baseline regional proportions of LULC change 

(“Demand”) for each level III ecoregion; however, these data 

were thematically less detailed than the LULC classes used for 

this assessment (table 2.1). For example, USGS Land Cover 

Trends only estimated one aggregate “forest” class, while 

this assessment differentiated between deciduous, evergreen, 

and mixed forest types. To obtain the three forest types and 

their transitions from the USGS Land Cover Trends data 

for 1992 to 2000, proportions of the three forest types from 

the 1992 NLCD were used to disaggregate the USGS Land 

Cover Trends single forest class for each level III ecoregion. 

A similar disaggregation of USGS Land Cover Trends classes 

using the 1992 NLCD was performed to split the class 

“grass/shrub” into the “grassland” and “shrubland” classes, 

split “wetland” into the “herbaceous wetland” and “woody 

wetland” classes, and split “agriculture” into “hay/pasture” 

and “cultivated crop.” Finally, the 1992 to 2000 estimates by 

ecoregion were annualized to produce annual rates of change 

that served as annual “Demand” for the FORE–SCE model.

A similar methodology was used to populate the 

“Demand” component of the model for 2001 to 2005. The 

“Demand” for this period was provided by the 2001 to 2006 

NLCD change-product data (Xian and others, 2009). The 2001 

and 2006 NLCD data provided a LULC change product that 

provided consistent, wall-to-wall LULC data for the United 

States. The level of thematic detail was compatible with this 

assessment, and, unlike the USGS Land Cover Trends data 

for 1992 to 2000, no disaggregation to a finer thematic scale 

was necessary. The 2001 to 2006 NLCD change data were 

annualized to produce rates of change that served as yearly 

“Demand” for 2001 to 2005 for the FORE–SCE model.

The 1992 to 2005 annual “Demand” for LULC served 

as input to the spatial modeling component of FORE–SCE. 

FORE–SCE used logistic regression to quantify empirical 

relationships between LULC and spatially explicit biophysical 

and socioeconomic variables. Suitability surfaces were 

produced for each unique LULC class that was modeled 

(table 2.1) for each level III ecoregion. The suitability surfaces 

were used to guide the placement of individual patches 

of LULC change; the characteristics of the patches were 

parameterized using historical LULC data from the USGS 

Land Cover Trends project. The US–PAD data were used to 

restrict the placement of specific forms of LULC change on 

certain types of protected lands (for example, restricting urban 

development in national park lands). Individual patches of 

LULC were placed on the landscape for a given annual model 

run until “Demand” was met for that year. The processing then 

continued to the next year until the baseline period of 1992 

to 2005 was complete. Additional details on the FORE–SCE 

model structure may be found in Sohl and Sayler (2008); Sohl, 

Sleeter, Zhu, and others (2012); and Sohl, Sleeter, Sayler, and 

others (2012).

The age of forest stands was also tracked spatially and 

temporally and was estimated in the modeling environment. 

Data about forest-stand ages were used to ensure realistic 

clearcutting cycles (based on the typical age when a forest 

stand is ready for harvesting) for a given geographic area, 

and provided information on forest structure that could be 

used for biogeochemical or climate modeling. An initial map 

of forest‐stand ages was generated for the region using a 

combination of data from LANDFIRE’s VCT and the U.S. 

Forest Service’s (USFS’s) Forest Inventory and Analysis (FIA; 

USDA Forest Service, 2012b). Where the LANDFIRE VCT 

measured a disturbance, the forest-stand age was directly 

calculated for the initial year of 1992. In areas where no 

disturbance was measured by the LANDFIRE VCT, the FIA 

data points were used to create an interpolated, continuous 

surface of forest-stand age. The FORE–SCE model tracked 

forest-stand age for each yearly model iteration and reset the 

stand age to “0” whenever a new forest area was generated 

or whenever a forest was clearcut; however, to ensure the use 

of as much observed spatial data as possible for the baseline 

period, the clearcutting of forests (classes 3, 4, and 5) in table 

2.1 was not modeled using the procedures outlined above; 

instead, the models were extracted from the LANDFIRE VCT 

data. All areas of forest that the VCT had identified as clearcut 

between 1992 and 2005 were “burned in” to the appropriately 

dated LULC maps produced from the FORE–SCE model (for 

example, all 1994 clearcut areas identified by the VCT were 

burned in to the 1994 LULC map produced from the FORE–

SCE model). The forest-stand age was appropriately updated 

throughout the baseline period, mimicking measured dates of 

forest clearcuts from the VCT.
22 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The result of the mapping and modeling efforts for 1992 

to 2005 LULC were annual, 250-meter-resolution LULC maps 

depicting the LULC classes (shown in table 2.1) and annual, 

250-meter-resolution data on forest-stand age. Given the 

limitations of available, spatially and thematically consistent 

LULC data for 1992 to 2005, the combined mapping and 

modeling technique ensured that the overall proportions 

of the 1992 to 2005 LULC maps were as representative as 

possible of the real, measured LULC change distributions 

that were provided by the USGS Land Cover Trends, NLCD, 

and LANDFIRE VCT projects. The location of LULC change 

after the initial 1992 year was a mix of actual mapped change 

and modeled change. The VCT provided the actual locations 

of clearcut forest patches between 1992 and 2005, a welcome 

dataset given that forest clearcutting represented the largest 

LULC change in the Western United States per unit of area 

(Benjamin M. Sleeter, USGS, unpub. data, 2012). For other 

LULC types, the “Spatial Allocation” component for LULC 

change was modeled using the FORE–SCE model. 

The validation of the baseline 1992 to 2005 LULC 

maps was accomplished through a combination of qualitative 

and quantitative assessment. A quantitative assessment of 

the model’s performance was obviously preferred. The 

quantitative validation of LULC model output could be 

performed by examining measures of quantity disagreement 

and allocation disagreement that reflected the model’s 

capability to map the correct quantity and location of LULC 

change, respectively (Pontius and Millones, 2012). An 

examination of quantity disagreement was unnecessary for 

this assessment, however. The quantity of LULC change was 

dictated by the USGS Land Cover Trends project for 1992 to 

2000 and by the NLCD 2001 to 2006 change product for 2001 

to 2005. The FORE–SCE model was designed to precisely 

match prescribed proportions of LULC change as dictated by 

the “Demand” component of the model. Given the design of 

the FORE–SCE model, quantity disagreement was, therefore, 

not an issue because the model matched the annual, prescribed 

LULC “Demand” for 1992 to 2005 on a regional basis. 

Given that all level III ecoregions were parameterized 

and modeled independently, the allocation disagreement was 

already partially mitigated because the proportions of change 

were spatially distributed to the ecoregion level. The allocation 

disagreement was only an issue within a level III ecoregion. 

The allocation disagreement (where LULC change was 

mapped) was not an issue for the clearcutting of forests (the 

most prevalent form of LULC change in the Western United 

States) because the 1992 to 2005 polygons of forest change 

were mapped by the LANDFIRE VCT, not modeled by 

FORE–SCE. All of the other types of LULC change, however, 

were modeled by FORE–SCE and were thus subject to 

allocation disagreement. There were difficulties in performing 

an assessment of allocation disagreement, however, given 

the inability to directly compare USGS Land Cover Trends, 

the 1992 NLCD, and the 2001 and 2006 NLCD data. The 

2001 and 2006 NLCD data were produced using a consistent 

methodology and could theoretically be used to evaluate the 

allocation disagreement of the modeled LULC change for that 

period; however, outside of the dominant LULC change in 

the Western United States (forest clearcutting and associated 

forest regeneration, mapped by VCT and not modeled), other 

LULC change was very minor as only 0.76 percent of the 

region changed between 2001 and 2006. An assessment of the 

model’s performance by examining small amounts of LULC 

change over very short temporal intervals is of questionable 

value (Sohl, Sleeter, Zhu, and others, 2012). Allocation 

disagreement for classes other than forest clearcutting was 

thus evaluated through qualitative assessment. During the 

modeling process, the performance of the model from 1992 

to 2005 was evaluated independently for each level III 

ecoregion using a visual assessment of the LULC-change 

distribution. An unacceptable distribution of LULC change 

resulted in a re-parameterization of the FORE–SCE model and 

a subsequent new model was run until the model performance 

was deemed acceptable.

2.4. Results and Discussion

2.4.1. Baseline LULC Mapping and Modeling—

Results for the Western United States

At the beginning of the simulation period in 1992, the 

Western United States as a whole was dominated by shrubland 

(45.1 percent), evergreen forest (23.9 percent), and grassland 

(13.9 percent)—three LULC classes that covered nearly 

83 percent of the Western United States. The less common 

but significant LULC classes included cultivated crop 

(3.8 percent), barren (3.8 percent), hay/pasture (2.5 percent), 

and developed (1.0 percent). The three mechanically 

disturbed classes, derived from the LANDFIRE VCT data 

and representing clearcut forest, covered nearly 1.0 percent of 

the region. 

Between 1992 and 2005, 2.9 percent of the land area in 

the Western United States changed its LULC class at least 

once. Most LULC classes experienced relatively small net 

changes during the study period (table 2.2). The three largest 

LULC classes—shrubland, evergreen forest, and grassland—

changed by −2,854 km2, +5,201 km2, and −1,426 km2, 

respectively. Although the areal change may seem large for 

the three major classes, the amount of net change was less 

than 1 percent of the total area for each LULC class during the 

time period. 

The most dynamic changes to LULC classes in the 

Western United States, both in terms of absolute net change 

and in terms of relative change for a given LULC class, 

were changes related to (1) forest clearcutting and (2) urban 

development. The area covered by the three mechanically 
Chapter 2 23

Table 2.2. Mapped and modeled land-use and land-cover (LULC) change (in square kilometers) indicating trends 

in mapped and modeled LULC classes for the Western United States for the baseline period (1992–2005). 

[km2, square kilometers; LULC, land use and land cover]

LULC class 1992 

(km2

)

2005

(km2)

Change

(km2)

Percent 

change

Water 39,289 39,744 455 1.2

Urban/developed 27,430 32,486 5,056 18.4

Mechanically disturbed—National forest 9,227 3,888 −5,339 −57.9

Mechanically disturbed—Other public 2,544 1,909 −635 −25.0

Mechanically disturbed—Private 11,580 8,103 −3,476 −30.0

Mining 1,329 2,032 703 52.9

Barren 100,658 100,783 125 0.1

Deciduous forest 52,088 53,791 1,704 3.3

Evergreen forest 636,190 641,391 5,201 0.8

Mixed forest 36,286 37,289 1,003 2.8

Grassland 369,279 367,853 −1,426 −0.4

Shrubland 1,199,764 1,196,910 −2,854 −0.2

Cropland 95,943 95,893 −50 −0.1

Hay/pasture 65,573 64,820 −753 −1.2

Herbaceous wetland 6,913 6,890 −22 −0.3

Woody wetland 2,913 3,223 310 10.7

Ice/snow 1,521 1,521 0 0

disturbed classes of forest clearcutting experienced a total net 

decline of nearly 9,500 km2 by 2005, which was a reduction 

of over 40 percent in areal extent since 1992 (fig. 2.3). The 

5,201 km2 increase in evergreen forest during the same 

time period was strongly tied to the reduction in overall 

clearcutting rates. Although clearcutting declined in all classes 

of mechanically disturbed lands, the sharpest decline in 

clearcutting was on national forest lands, which declined by 

58 percent between 1992 and 2005. Clearcutting on privately 

held forested land also declined sharply (by 30 percent), 

but at a much lower rate than the clearcutting on National 

Forest land.

A number of factors drove the lower rates of forest 

clearcutting in the Western United States during the baseline 

time period of 1992 to 2005. Federal environmental policy 

strongly affected clearcutting practices in the Pacific 

Northwest. On June 23, 1990, the Northern Spotted Owl 

(Strix occidentalis caurina) was listed as “threatened” under 

the Endangered Species Act. On May 21, 1991, a U.S. District 

Court blocked further clearcutting on national forest lands 

in the region. Those restrictions held until the passing of the 

Northwest Forest Plan in 1993, an agreement which limited 

the clearcutting of forested public lands to 1 billion board feet 

annually, which was roughly one-fourth of the clearcutting 

rates during the 1980s. Those timber harvesting constraints 

rippled through the global timber export markets; the higher 

prices lead Asian importers to look for cheaper timber from 

New Zealand, Chile, Russia, and elsewhere (Daniels, 2005). 

Figure 2–3.

0 

5,000 

10,000 

15,000 

20,000 

25,000 

20052004200320022001200019991998199719961995199419931992

Area, in square kilometers

EXPLANATION

Mechanically disturbed land

National forest

Other public

Private

Year

Figure 2.3. Chart showing the declining trend of forest 

clearcutting in the Western United States between 1992 and 

2005. The areal extent of mechanically disturbed (clearcut) land 

declined significantly over the baseline study period of 1992 to 

2005. The strongest declines were noted on national forest lands. 
24 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The Asian demand for timber products from the Western 

United States declined even further in response to the Asian 

economic crisis in 1997 (Daniels, 2005). Predictions of the 

decline in forest clearcutting rates in the Western United 

States, however, had been made far in advance of the passage 

of the Northwest Forest Plan or the Asian economic crisis in 

the 1990s, as studies noted that the rates of forest clearcutting 

in parts of the Western United States before the 1990s 

were unsustainable (Beuter and others, 1976). The decline 

in clearcutting noted in this assessment was preceded by 

additional declines before 1992. Timber harvests in the Pacific 

Northwest declined by 87 percent from 1988 to 1996 (Warren, 

1999; Daniels, 2005). 

Urban development was the other most active LULC 

class in terms of absolute net change relative to initial 

1992 LULC conditions. Urban development in the Western 

United States increased by over 5,000 km2 from 1992 to 

2005, which was an 18.4 percent increase in area (fig. 2.4). 

Although the rate of increase in development was realistic, 

the initial extent of urban development in the 1992 LULC 

data was likely an underestimation of the actual urban extent 

because it was difficult to identify and map low-density 

residential areas using Landsat data (Claggett and others, 

2004; McCauley and Goetz, 2004). In addition, the 2001 

NLCD data had significantly more urban land mapped than the 

1992 NLCD, which was likely due to improved source data 

and methodologies just as much as actual urban expansion. 

Although urban development was likely underestimated in 

the initial 1992 map, urban lands still represented only a 

small portion of the Western United States landscape, and the 

“story” of urban growth was represented through the measured 

rates of urban development between 1992 and 2005. 

The net change of other LULC types in table 2.2 was 

relatively minor. The evergreen forest class increased by 

over 5,200 km2 (0.8 percent) from 1992 to 2005, as did 

deciduous forest (+1,704 km2, or 3.3 percent) and mixed forest 

(+1,003 km2, or 2.8 percent). As noted above, the increase 

in area of the three forest classes was primarily related to the 

reduction in the rates of forest clearcutting, which resulted 

in more area categorized as forest in 2005 because of the 

regeneration of forest in formerly clearcut areas. Other notable 

LULC changes included an increase of 700 km2 of mining 

by 2005, which was a 60 percent increase from 1992. The 

two agricultural classes, cultivated crop and hay/pasture, 

each declined with a negligible decline for cultivated crop 

and a decrease of 1.1 percent in hay/pasture from 1992 to 

2005. Grassland and shrubland both declined, with grassland 

losing 1,426 km2 and shrubland losing 2,854 km2. Given 

the vast expanses of grassland and shrubland in the Western 

United States, however, this only represented a net loss of 

−0.39 percent and −0.24 percent, respectively, from the initial 

1992 extents of grassland and shrubland. 

25,000

30,000

35,000

20052004200320022001200019991998199719961995199419931992

Area, in square kilometers

Figure 2–4.

Year

Figure 2.4. Chart showing the increasing trend in the areal extent 

of urban development in the Western United States between 1992 

and 2005. The data were derived from the USGS Land Cover Trends 

project for the 1992 to 2000 period and from the National Land Cover 

Dataset (NLCD) 2001 to 2006 change product for the 2001 to 2005 

period. A consistent annual rate of change was modeled between 

1992 and 2000, and again for 2001 to 2005, on the basis of the USGS 

Land Cover Trends and NLCD data, respectively. The measured rate 

of urban development for those two periods was nearly constant.

2.4.2. Regional Results 

Although table 2.2 indicates overall net changes in the 

primary LULC types for the Western United States from 

1992 to 2005, regional variability resulted in a heterogeneous 

pattern of LULC change during the study period. Within 

the level III ecoregions where significant amounts of forest 

clearcutting had occurred, 20 percent or more of the land 

area changed its LULC class at some point between 1992 and 

2005, whereas within the ecoregions covered primarily by 

desert, 1 percent or less of the area changed its LULC class 

(fig. 2.5). The total spatial change closely mimicked the spatial 

variability of forest clearcutting, which was the most prevalent 

form of LULC conversion in the Western United States 

(fig. 2.6). Forest clearcutting was only one part of the story, 

however. Each ecoregion had greater internal homogeneity 

than the Western United States’ landscape as a whole, and 

each had a unique “story” about its baseline land-cover change 

from 1992 to 2005. The following sections describe the basic 

characteristics of each level II ecoregion and discuss the 

primary LULC changes from 1992 to 2005, including a brief 

discussion of the major driving forces of the changes.
Chapter 2 25

0 5 10 15 20

0 100 200 300 400 500 MILES

2500 500 KILOMETERS

Spatial variability of land-use and land-cover change in the 

 Western United States, by level III ecoregion, in percent

EXPLANATION

Level II ecoregion

Level III ecoregion

Figure 2.5.

N

Figure 2.5. Map showing the spatial variability of land-use and 

land-cover change in the Western United States between 1992 

and 2005. The spatial change (the percent of area that changed 

at least once from 1992 to 2005) varied greatly between the 

ecoregions. See figure 1.1 in chapter 1 for ecoregion names.

0 100 200 300 400 500 MILES

2500 500 KILOMETERS

EXPLANATION

0 5 10 15 20

Level II ecoregion

Level III ecoregion

Figure 2.6.

N

Spatial variability of forest clearcutting in the Western 

 United States, by level III ecoregion, in percent

Figure 2.6. Map showing the spatial variability of forest 

clearcutting in the Western United States from 1992 to 2005. Given 

that forestry activity was the primary driver of measured land-use 

and land-cover (LULC) change in the region, the distribution of 

clearcutting by ecoregion was very similar to the overall pattern of 

LULC change of Western United States. See figure 1.1 in chapter 1

for ecoregion names.
26 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

2.4.2.1. Western Cordillera

The Western Cordillera ecoregion covers most of the 

forested lands in the interior of the Western United States 

and consists of a number of geographically disparate regions 

stretching from the Canadian border in Washington to the “sky 

islands” of New Mexico and Arizona. The Western Cordillera 

is characterized by generally rugged topography (including 

mountain ranges that have the highest elevations in the 

Western United States) and predominantly natural landscapes. 

In 1992, forest cover (evergreen, mixed, and deciduous forest) 

alone covered 60.8 percent of the ecoregion. The “natural” 

land-cover classes (forested classes, grassland, shrubland, 

wetland classes, and water) covered over 95.9 percent of 

the ecoregion whereas anthropogenic land uses (urban 

development, forest cutting, mining, and agriculture) covered 

only 4.1 percent of the ecoregion (fig. 2.7). 

Approximately 4.4 percent (38,447 km2) of the ecoregion 

experienced LULC change at least once during the baseline 

period (1992–2005). Although a relatively small proportion 

of the ecoregion changed, this was the second most active 

level II ecoregion in the Western United States for this 

period. Between 1992 and 2005, the vast majority of LULC 

change was associated with forestry activity; 87.8 percent 

(33,739 km2) of the changed pixels were associated with 

either clearcutting for timber or the regeneration of the 

clearcut areas. As with the Western United States as a whole, 

the net changes in LULC classes were small, and the largest 

changes by absolute area and by percentage loss or gain 

were associated with the timber industry (fig. 2.7). Between 

1992 and 2005, clearcutting activity declined sharply in 

all three mechanically disturbed classes (national forests, 

other public forests, and private forests). The cutting rates 

on national forest land experienced both the largest absolute 

change (−5,130 km2) and relative change (−57.7 percent) 

from 1992 to 2005. Forested lands (evergreen, deciduous, and 

mixed forest) increased by 1.4 percent (7,335 km2), which 

was primarily due to the declines in clearcutting rates. The 

developed lands experienced a modest increase of 367 km2, or 

an increase of 16.2 percent, between 1992 and 2005.

2.4.2.2. Marine West Coast Forest

The Marine West Coast Forest ecoregion covers 

the maritime forests along the West Coast of the United 

States. This ecoregion was the most heavily forested of the 

five level II ecoregions in the Western United States with 

approximately 70 percent of the land area covered by one of 

the three forest classes in 1992. This ecoregion was similar 

to the Western Cordillera ecoregion in that the “natural” 

land-cover classes covered the majority of the ecoregion, 

and a smaller percentage (24.8 percent) of the land area of 

this ecoregion was categorized by anthropogenic land uses in 

1992. In 1992, the terrestrial portion of the Marine West Coast 

Forest had higher proportions of clearcut land (7.9 percent), 

a higher proportion of developed lands (4.5 percent, mostly 

around the Puget Sound and around the Willamette Valley), 

and significantly more agricultural land (12.4 percent, 

the majority of which was hay/pasture) than the Western 

Cordillera (fig. 2.7). 

The spatial footprint of LULC change between 1992 

and 2005 was much higher in this ecoregion than in any other 

level II ecoregion in the Western United States. Approximately 

19.7 percent (16,850 km2) of the landscape changed LULC 

classes at least once between 1992 and 2005 with the vast 

majority of the change related to forestry activity (a spatial 

footprint of 15,061 km2). As with the Western Cordillera 

ecoregion, forest clearcutting declined from 1992 to 2005, 

although not as sharply with a total decline of 24.9 percent 

(1,671 km2). Forest clearcutting on National Forest land 

dropped by nearly 70 percent; however, most of the forested 

land in this ecoregion was privately held, and the more modest 

declines in clearcutting rates on private land mitigated the 

decline in the ecoregion’s overall rate of clearcutting. Despite 

the overall decline in clearcutting rates, the amount of land in 

the three forest classes only increased slightly—by 0.5 percent 

(520 km2)—between 1992 and 2005. The increase in forested 

land was less than that in the Western Cordillera largely 

because the decreases in forest clearcutting were partially 

offset by clearing forested land for urban development. 

Even though the Marine West Coast Forest ecoregion is 

smaller in area than the Western Cordillera ecoregion, it had 

1,563 km2 more developed land in 1992 and more new urban 

development between 1992 and 2005 (893 km2 in the Marine 

West Coast Forest compared to 367 km2 in the Western 

Cordillera). The net change within the other LULC classes 

was minor; no land area categorized by those classes changed 

by more than 200 km2 between 1992 and 2005.

2.4.2.3. Cold Deserts 

The Cold Deserts ecoregion encompasses the temperate 

and cooler arid lands of the interior Western United States. 

Grassland and shrubland were the most common land-cover 

types in the ecoregion; in 1992, they covered 61.9 percent 

and 14.5 percent of the ecoregion, respectively. In 1992, 

forests (evergreen, deciduous, and mixed) covered 9.2 percent 

of the ecoregion and were found throughout the ecoregion 

in scattered pockets of land with suitable soils, moisture, 

and climate. In 1992, agricultural lands (cultivated crop 

and hay/ pasture) covered 7.7 percent of the ecoregion; 

the majority was irrigated agricultural land located in 

the Columbia Plateau and the Snake River Plain level III 

ecoregions. The Cold Deserts ecoregion had a low population 

density with only a few large urban areas, including Salt 

Lake City, Utah, and Albuquerque, New Mexico. Urban 

development covered 5,085 km2 of the ecoregion at the 

beginning of the baseline period in 1992.
Chapter 2 27

Open water

Developed

Mechanically disturbed (national forest)

Mechanically disturbed (other public land)

Mechanically disturbed (private land)

Mining

Barren

Deciduous forest

Evergreen forest

Mixed forest

Grassland

Shrubland

Agriculture

Hay/pasture

Woody wetland

Herbaceous wetland

Ice/snow

EXPLANATION

Figure 2–7.

Land-use or land-cover class

[Pie charts represent data for 2005]

Open waterDevelopedMechanically disturbed (national forest)Mechanically disturbed (other public)Mechanically disturbed (private)MiningBarrenDeciduous forestEvergreen forestMixed forestGrasslandShrublandAgricultureHay/pastureWoody wetland

Herbaceous wetlandIce/snow

Western Cordillera ecoregion

1992 (area, in km2) 7,827 2,260 8,896 1,557 5,987 266 14,916 30,213 483,704 16,541 110,982 166,953 4,977 12,289 2,229 1,176 1,507

2005 (area, in km2) 7,939 2,627 3,767 1,113 3,889 393 15,004 31,104 489,702 16,987 110,983 166,892 4,778 11,944 2,303 1,353 1,507

Net change in area

 (in km2

) 111 367 –5,130 –444 –2,099 127 88 891 5,998 446 1 –61 –200 –346 74 177 0

Change in area 

 (in percent)

1992 (area, in km2

)

2005 (area, in km2

)

Net change in area

 (in km2

)

Change in area 

 (in percent)

1992 (area, in km2

)

2005 (area, in km2

)

Net change in area

 (in km2

)

Change in area 

 (in percent)

1992 (area, in km2

)

2005 (area, in km2

)

Net change in area

 (in km2

)

Change in area 

 (in percent)

1992 (area, in km2

)

2005 (area, in km2

)

Net change in area

 (in km2

)

Change in area 

 (in percent)

 1.4 16.2 –57.7 –28.5 –35.1 48.0 0.6 2.9 1.2 2.7 0.0 0.0 –4.0 –2.8 3.3 15.0 0.0

Marine West Coast Forest ecoregion

9,964 3,823 290 953 5,471 32 505 10,082 38,077 10,880 2,846 1,367 2,561 8,042 182 347 0

10,004 4,715 89 783 4,170 52 499 10,888 37,345 11,326 3,037 1,507 2,516 7,902 223 364 0

40 892 –201 –170 –1,301 20 –6 806 –732 446 191 140 –45 –140 41 17 0

 0.4 23.3 –69.3 –17.8 –23.8 62.5 –1.2 8.0 –1.9 4.1 6.7 10.2 –1.8 –1.7 22.5 4.9 0.0

Cold Deserts ecoregion

12,804 5,085 11 20 61 645 48,201 6,089 89,580 1,499 152,950 653,289 51,675 29,562 3,538 1,037 10

12,924 6,237 2 4 11 937 48,284 6,098 89,552 1,513 152,684 651,974 51,865 29,325 3,458 1,177 10

121 1,153 –9 –16 –50 291 84 9 –28 14 –267 –1,315 190 –237 –80 139 0

 0.9 22.7 –80.0 –81.0 –81.8 45.2 0.2 0.2 0.0 1.0 –0.2 –0.2 0.4 –0.8 –2.3 13.4 0.0

Warm Deserts ecoregion

2,424 4,618 16 7 19 322 33,539 497 7,120 466 55,915 348,558 7,168 4,286 129 205 0

2,446 5,747 12 3 3 507 33,450 499 7,100 466 55,806 347,586 7,097 4,240 135 191 0

21 1,129 –3 –4 –16 185 –89 2 –20 0 –109 –972 –71 –46 6 –14 0

0.9 24.4 –21.9 –52.3 –83.4 57.6 –0.3 0.4 –0.3 0.0 –0.2 –0.3 –1.0 –1.1 4.8 –6.8 0.0

Mediterranean California ecoregion

6,270 11,645 14 7 42 64 3,498 5,207 17,709 6,901 46,586 29,598 29,562 11,393 835 149 3

6,431 13,160 18 6 31 144 3,547 5,202 17,692 6,997 45,343 28,951 29,638 11,409 772 139 3

162 1,515 4 –1 –11 80 49 –5 –17 96 –1,243 –646 76 16 –64 –10 –0

2.6 13.0 25.9 –16.5 –26.5 123.5 1.4 –0.1 –0.1 1.4 –2.7 –2.2 0.3 0.1 –7.6 –6.4 –4.0

Land-use or land-cover class

Figure 2.7. Charts showing the proportions of land use and land cover (LULC) at the end of the baseline period (pie charts for 2005) and 

the net change in the mapped and modeled LULC classes between 1992 and 2005, by level II ecoregion.
28 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The spatial footprint of LULC change between 1992 and 

2005 was only 1.1 percent of the ecoregion area. Commercial 

forestry activity and other forest clearcutting, which were 

major sources of LULC change in the Western Cordillera and 

Marine West Coast Forest ecoregions, were negligible in the 

Cold Deserts ecoregion because of the absence of suitable 

forest resources. Urban development was responsible for the 

largest net changes in LULC types, as shown in figure 2.7. An 

estimated 1,153 km2 of new urban lands were developed by 

2005, which was a net increase of 22.7 percent over the 1992 

urban extent. The largest absolute net change by class was a 

1,315 km2 loss of shrubland, which was primarily due to the 

conversion of shrubland to urban development and irrigated 

agriculture; however, given the prevalence of shrubland in 

this ecoregion, the areal extent of shrubland declined by only 

0.2 percent from 1992 to 2005. The absolute net changes in 

all other LULC classes were minor. No land area categorized 

by those classes changed by more than 300 km2 from 1992 

to 2005. Mining lands, however, increased by 291 km2 from 

1992 to 2005, an increase of 45.2 percent. 

2.4.2.4. Warm Deserts 

The Warm Deserts ecoregion covers the warmer 

deserts and arid regions of the interior Southwestern United 

States. Three LULC classes alone covered 94.1 percent of 

the ecoregion in 1992: shrubland, 74.9 percent; grassland, 

12.0 percent; and barren land, 7.2 percent. Forests and 

agricultural lands were only found in a few scattered locations 

in the ecoregion. The forested lands (evergreen, deciduous, 

and mixed) were primarily found in a few areas of higher 

elevation and near water sources and together covered 

1.7 percent of the ecoregion in 1992. The agricultural lands 

(cultivated crop and hay/pasture) were primarily found in 

areas where irrigation sources were available, such as near the 

Salton Sea in California and near Phoenix, Arizona; in 1992, 

they covered 2.5 percent of the ecoregion. Urban development 

only covered 1.0 percent of the ecoregion in 1992, yet several 

large urban centers are located in this ecoregion, including 

Phoenix and Tucson in Arizona, and Las Vegas, Nevada.

The spatial footprint of LULC change between 1992 and 

2005 was only 0.8 percent of the Warm Deserts ecoregion, 

making it the ecoregion with the least amount of LULC 

change in the Western United States. Urban development 

increased by 1,129 km2, a 24 percent increase from 1992. 

Shrubland declined by 972 km2, a decline of 0.3 percent, with 

most of the loss attributed to the conversion of shrubland to 

urban development. Other LULC changes in the ecoregion 

were minor. Commercial forestry was negligible in the 

ecoregion. Mining lands expanded by 185 km2, an increase of 

57.6 percent from 1992.

2.4.2.5. Mediterranean California

The LULC of the Mediterranean California ecoregion is 

more heterogeneous than the other ecoregions in the Western 

United States. This ecoregion is the only one where forests 

(evergreen, mixed, and deciduous) or shrubland alone did 

not cover a majority (>50 percent) of the ecoregion area. 

Grassland (27.5 percent), agricultural classes (24.2 percent 

for the two classes), forest (17.6 percent for the three classes), 

shrubland (17.5 percent), and urban development (6.9 percent) 

each represented the dominant LULC class for specific 

portions of the ecoregion in 1992. Grassland was scattered 

throughout the ecoregion but there was a high concentration 

around the periphery of the Central California Valley level III 

ecoregion. Agricultural land was concentrated in the Central 

California Valley, although there were smaller, scattered 

patches in western and southern California. Forested lands 

were concentrated in the Southern California Mountains level 

III ecoregion and along the edges of the Southern and Central 

California Chaparral and Oak Woodlands level III ecoregion. 

The vast majority of shrubland was found in the far southern 

third of the ecoregion, and areas of dense urban development 

were found throughout the ecoregion. 

The spatial footprint of LULC change between 1992 

and 2005 was 3.5 percent of the ecoregion area. The greatest 

amount of change by area was associated with the gross 

change between the cultivated crop and hay/pasture classes. 

The net change in those two classes was very small, with 

cultivated crop increasing by 76 km2 (0.3 percent) and 

hay/ pasture increasing by 16 km2 (0.1 percent). Underlying the 

small amount of net change, however, were large amounts of 

gross change with near balances of cultivated crop converting 

to hay/pasture and vice versa. The highest net changes in 

LULC classes were associated with urban development. Over 

1,500 km2 of new urban development occurred between 1992 

and 2005, which was a 13.0 percent increase over the 1992 

extent. Grassland declined by 1,243 km2 (2.7 percent) and 

shrubland declined by 646 km2 (2.2 percent), with the majority 

of the declines caused by conversion to urban development. 

Other LULC changes in the ecoregion were minor.
Chapter 3. Baseline Wildland Fires and Emissions for the 

Western United States

By Todd J. Hawbaker1 and Zhiliang Zhu2

3.1. Highlights

• Wildland fires burned an annual average of 13,173 km2

between 2001 and 2008 in the Western United States.

• The interannual variability in the area that was burned 

between 2001 and 2008 was high; as few as 3,345 km2

burned in 2004 and as much as 25,206 km2 burned 

in 2007.

• The annual average emissions from wildland fires from 

2001 to 2008 were 36.7 TgCO2-eq/yr (10.0 TgC/yr), 

with a median value of 41.0 TgCO2-eq/yr (11.2 TgC/

yr), and a range from 6.8 TgCO2-eq (1.9 TgC/yr) in 

2004 to 75.3 TgCO2-eq (20.6 TgC/yr) in 2007. 

• The minimum, average, and maximum emissions from 

wildland fires in the Western United States from 2001 

to 2008 were equivalent to 7.9 percent, 11.6 percent, 

and 87.0 percent, respectively, of the mean terrestrial 

carbon sequestration estimated for the Western 

United States in this study.

• The minimum, average, and maximum emissions from 

annual wildland fires in the Western United States 

from 2001 to 2008 were equivalent to 0.1 percent, 

0.7 percent, and 1.3 percent, respectively, of the 2010 

fossil-fuel emissions for the entire United States.

• The Western Cordillera ecoregion produced 77 percent 

of all emissions in the Western United States during the 

baseline period.

3.2. Introduction

The methodology for this assessment explicitly addressed 

ecosystem disturbances, including human- and naturally 

caused wildland fires, as required by the EISA legislation 

(U.S. Congress, 2007; Zhu and others, 2010). As indicated 

by figure 1.2 in chapter 1 of this report, the estimates for 

the baseline biomass combustion emissions from wildland 

fires are presented in this chapter. The projected future 

potential wildland fire emissions are described in chapter 8. 

The baseline burned areas and the projected future potential 

burned areas for wildland fires and their severity, described 

in the two chapters, were used as input into the assessment 

of baseline and projected future potential terrestrial 

carbon and greenhouse-gas fluxes (chapters 5 and 9 of this 

report, respectively).

Wildland fires are a critical component of the global 

carbon cycle because they produce an immediate release of 

greenhouse gases—carbon monoxide (CO), carbon dioxide 

(CO2), and methane (CH4)—when biomass is consumed 

through combustion (Seiler and Crutzen, 1980). Wildland fires 

also have long-term effects on ecosystem carbon cycling by 

influencing the rate of carbon sequestration after combustion, 

both through the decomposition of dead vegetation and 

through photosynthesis, which helps establish new vegetation; 

because of those effects, years to decades can pass before 

carbon stocks return to pre-fire conditions (M.G. Turner 

and others, 1998; Cleary and others, 2010; Hurteau and 

Brooks, 2011; Kashian and others, in press). If fire regimes 

are stable, the long-term effects of wildland fires on carbon 

1U.S. Geological Survey, Denver, Colo.

2U.S. Geological Survey, Reston, Va.
30 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

cycling are typically negligible because carbon sequestration 

through vegetation growth and carbon loss through wildland 

fire emissions cancel out each other over long time periods 

(Balshi, McGuire, Duffy, Flanigan, Kicklighter, and Melillo, 

2009; Flannigan and others, 2009). If a fire regime changes, 

however, the vulnerability for carbon storage is high because 

the amount of carbon stored in the ecosystem can be altered 

or lost through emissions. Substantial evidence is available 

to document that fire regimes are not static. For example, 

the frequency of wildland fires has been greatly reduced 

since settlement of the United States began, mainly due to 

land‐use changes and the success of fire suppression in the last 

century (Cleland and others, 2004); however, the frequency 

of wildland fires has been increasing since the 1990s because 

of an increasingly earlier snowmelt (Westerling and others, 

2006). Therefore, any credible assessment of carbon storage 

and fluxes in ecosystems through time must account for the 

potential changes in wildland-fire occurrence and emissions.

In the conterminous United States (CONUS), the net 

carbon flux in ecosystems reported by the Environmental 

Protection Agency (EPA) was 1,075 TgCO2-eq/yr (293 TgC/yr) 

in 2010, the majority of which was sequestered within forests 

(EPA, 2012). The estimates of emissions from wildland fires 

in the United States were highly variable; after converting 

the reported emissions to carbon dioxide equivalent, they 

were as follows: (1) from 15 to 73 TgCO2-eq/yr, (2001–2008; 

Global Fire Emissions Database (GFED), Oak Ridge National 

Laboratory Distributed Active Archive Center, 2012; see also 

Giglio and others, 2010; van der Werf and others, 2010); (2) 

from 29 to 199 TgCO2-eq/yr (2001–2008; French and others, 

2011; Michigan Tech Research Institute, 2012), and (3) from 

157 to 283 TgCO2-eq/yr (2002–2006; Wiedinmyer and Neff, 

2007). When compared with the 2010 net carbon flux of 

ecosystems in the CONUS (EPA, 2012), the annual emissions 

from wildland fires were equivalent to 1 to 26 percent of the 

ecosystem’s total annual flux. In contrast, from 2001 to 2008, 

the combustion of fossil fuels produced 5,642 TgCO2-eq/yr 

(EPA, 2012) and flux increased at a rate of 1 percent per year 

(Pacala and others, 2007). Based on these rates, the annual 

emissions from wildland fires were equivalent to 0.3 to 5.1 

percent of the emissions from fossil-fuel consumption.

The differences among the accuracy and quality of these 

data, their spatial and temporal resolution, and assumptions 

about variations in combustion efficiency were the primary 

sources of uncertainties in wildland-fire emissions estimates 

(Larkin and others, 2009; French and others, 2011). The 

assumptions about the proportion of aboveground biomass 

consumed by wildland fire, especially aboveground woody 

biomass in forests, can have a substantial influence on 

emission estimates (Campbell and others, 2007; Meigs and 

others, 2009). The methods used for calculating emissions 

relied on estimates of the area that was burned, fuel loads 

(available live and dead biomass for burning), combustion 

efficiency, and emission factors (Seiler and Crutzen, 1980; 

Albini and others, 1995; Wiedinmyer and Neff, 2007; 

Ottmar and others, 2008). For instance, the GFED (Giglio 

and others, 2010; van der Werf and others, 2010) estimates 

biomass consumption and emission at fire locations detected 

by MODIS (Roy and others, 2002; Giglio and others, 2003) 

on the basis of land-cover types, combustion completeness, 

soil moisture, and land-cover specific emission factors. 

GFED also incorporates changes in fuel loads using the 

Carnegie Ames Stanford Approach to characterize biomass 

production (Potter and others, 1993, 2012). Wiedinmyer and 

Neff (2007) also used active wildland fire observations from 

NASA’s MODIS (Giglio and others, 2003), but calculated the 

emissions based on static land-cover types, percent land cover, 

and biomass at 1-km resolution. French and others (2011) 

used the CONSUME model (Ottmar and others, 2008), which 

calculated fuel consumption and emission using fuel loads 

derived from the Fuel Characterization Classification System 

(FCCS; Ottmar and others, 2007) and fuel moistures derived 

from weather-station data.

These existing studies provided an estimate of the effects 

of wildland fires on a national scale but lacked the regional 

detail required by this assessment. Furthermore, there were 

few projections of future potential wildland-fire emissions that 

were consistent with the existing baseline emission estimates. 

Therefore, a set of baseline emissions (this chapter) and 

projected future potential emissions (chapter 8) was developed 

to ensure consistency throughout this and other regional 

assessments. This chapter focuses on the baseline estimates 

of wildland-fire occurrence and emissions for the Western 

United States and strives to answer two primary questions: 

(1) What were the patterns of wildland-fire occurrence and 

emissions in the Western United States?, and (2) How did 

wildland fires vary temporally and spatially among the 

ecoregions of the Western United States? The results from this 

chapter were also used in the assessment of baseline carbon 

storage, sequestration, and greenhouse-gas fluxes of terrestrial 

ecosystems (chapter 5).

3.3. Input Data and Methods

The baseline estimates for the number of wildfires, the 

area burned, and emissions were derived from the Monitoring 

Trends in Burn Severity (MTBS) database (Eidenshink and 

others, 2007) and the First Order Fire Effects Model (FOFEM; 

Reinhardt and others, 1997) for the major GHGs: carbon 

dioxide (CO2), carbon monoxide (CO), and methane (CH4). 

This method was applied to each wildland fire in the region 

that was in the MTBS database to produce estimates of CO2, 

CO, and CH4 emissions (converted to CO2 equivalent). The 

results were aggregated to produce an estimate of emissions 

for the Western United States as a whole and for each level II 

ecoregion within it.
Chapter 3 31

The locations of wildland-fire scars were taken from the 

MTBS database, which includes information about wildland 

fires in the Western United States that occurred between 1984 

and 2008 and that were greater than 404 ha (1,000 acres). 

The MTBS data were selected because of the high degree 

of confidence in the data (fire size and severity were 

derived manually). Other data sources were considered but 

ultimately not used, including the various versions of Federal 

wildland‐fire databases, because of the spatial inaccuracies 

and duplicate records that would have introduced uncertainties 

(T.J. Brown and others, 2002). The MODIS active fire (Giglio 

and others, 2003) and burned area (Roy and others, 2002) 

products were also considered but not used because they 

contained no information about the causes of the wildland 

fires and had a coarse spatial resolution that complicated the 

calculations of emissions and the modeling of future trends.

Wildland-fire emissions were calculated for each burned 

pixel in the MTBS database using the FOFEM, which used 

fuel loads along with fuel moistures to estimate the amount 

of forest litter and downed deadwood that was consumed 

(Albini and others, 1995; Albini and Reinhardt, 1995, 1997). 

The consumption of duff (decaying forest litter), trees, plants, 

and shrubs was estimated as a function of the region, season, 

fuel moistures, and fuel loads. Canopy fuel consumption 

was estimated as a function of the burn severity provided by 

the MTBS data. The emissions of CO2, CO, and CH4 were 

then calculated on the basis of the amount of fuel consumed, 

the organic-matter content of the fuel, and how efficiently it 

burned. The required input data for the FOFEM included fuel 

loads, burn severity, and dead and live fuel moistures (fig. 3.1).

Fuel-load data provided an estimate of the amount 

of biomass that was available for consumption and were 

derived from the LANDFIRE project’s Fuel Loading Models 

data layer (FLM; Lutes and others, 2009). These fuel-load 

data were categorized by 1-, 10-, 100-, and 1,000-hour fuel 

classes (Lutes and others, 2009) for dead biomass, decaying 

biomass (duff and forest litter), and live biomass (grass, 

shrubs, and tree canopy). In the FOFEM, the amount of tree 

canopy that was consumed was a direct function of burnseverity values from the MTBS data. The amount of canopy 

foliage that was consumed in the high, moderate, and low 

burn-severity categories was assumed to be 100, 60, and 

20 percent, respectively. Similarly, the consumption of the 

canopy’s branch wood was set at 50, 30, and 10 percent 

for the high, moderate, and low burn-severity categories, 

respectively. These values were based on previously published 

estimates (Spracklen and others, 2009; Zhu and others, 

2010) and on a comparison of the FOFEM emissions with 

previously published results for selected wildland fires. Prior 

to processing with the FOFEM, the LANDFIRE FLM and 

MTBS raster data were aggregated to 250 m resolution using 

a nearest-neighbor method to match the resolution of other 

MTBS LANDFIRE Weather

Fire effects

(FOFEM) 

Burned

area 

Emissions

Figure 3–1.

Figure 3.1. Flowchart showing the process for calculating 

baseline estimates of greenhouse-gas emissions from wildland 

fires.

raster data being used in this assessment. The emissions were 

calculated for wildland fires occurring between 2001 and 

2008, which is the baseline time period for this component 

of the assessment. Wildland fires before 2001 were excluded 

because the LANDFIRE fuels data were derived from circa 

2001 Landsat imagery. The year-to-year variability in the 

amount of burned area was high. Therefore, data on all 

wildland fires that occurred after 2001 were included to help 

reduce the influence of extreme wildland fire years (either high 

or low occurrence) on the baseline statistics.

Fuel moistures were estimated by applying the National 

Fire Danger Rating System (NFDRS; Bradshaw and others, 

1983) algorithms to a 1/8° gridded daily weather dataset 

that spanned the conterminous United States (Maurer 

and others, 2002). These data spanned 1950 to 2010 and 

included the minimum and maximum daily temperature 

and daily precipitation. The Mountain Climate Simulator 

(MT–CLIM) algorithms (Glassy and Running, 1994) were 

used to calculate relative humidity based on minimum and 

afternoon daily temperatures (Kimball and others, 1997). 

Dead and live fuel moistures were calculated by using the 

NFDRS (Deeming and others, 1977; Bradshaw and others, 

1983; Burgan, 1988). The NFDRS algorithms required 

information about the beginning of both spring (“green-up”) 

and fall (“brown-down”) to estimate live fuel moistures. To 

generate the green-up and brown-down dates, a technique was 

implemented that determined the dates of seasonal changes in 

live fuel on the basis of the daily amount of exposure to light, 

minimum temperature, and the vapor-pressure deficit (Jolly 

and others, 2005).
32 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

3.4. Results

In the five ecoregions of this assessment, the number of 

wildland fires between 2001 and 2008 averaged 303 per year, 

but was as high as 467 in 2006 and as low as 131 in 2004 

(table 3.1 and fig. 3.2). The area burned by wildland fires 

averaged 13,173 km2/yr or 0.49 percent of the Western United 

States, which has a total area of approximately 2.66 million 

km2. The area burned ranged from 3,345 km2 (0.13 percent 

of total area) in 2004 to 25,206 km2 (0.94 percent of total 

area) in 2007. The emissions from wildland fires and their 

interannual variability followed the patterns of the burned area 

and averaged 36.7 TgCO2-eq/yr, ranging from 6.8 TgCO2-eq in 

2004 to 75.3 TgCO2-eq in 2007. When normalized for the area 

burned, the annual emissions averaged 2.9 kgCO2-eq/m2/yr,

but ranged from 1.7 to 3.9 kgCO2-eq/m2/yr (or 0.8 kgC/m2/yr, 

ranging from 0.4 to 1.1 kgC/m2/yr).

Table 3.1. Summary statistics for the number of wildland fires, area burned, and emissions, by EPA level II 

ecoregion and for the entire Western United States region between 2001 and 2008.

[km2, square kilometers; TgCO2-eq, teragrams of carbon dioxide equivalent]

Western 

Cordillera

Marine West 

Coast Forest

Cold

Deserts

Warm

Deserts

Mediterranean 

California

Western

United States

Number of wildfires per year

Mean 123 5 121 25 31 303

Standard deviation 34.1 5.5 72.4 20.0 7.8 97.1

Minimum 61 1 36 7 15 131

Median 117 3 115 19 32 290

95th quantile 168 12 225 57 39 434

Maximum 173 13 245 66 39 467

Area burned per year (km2

)

Mean 5,708 79 5,056 785 1,585 13,173 

Standard deviation 2,966 87 4,212 702 1,198 6,736 

Minimum 1,856 9 583 198 301 3,345 

Median 5,371 58 3,962 544 1,220 12,136 

95th quantile 9,926 178 10,926 1,920 3,292 23,261 

Maximum 10,449 191 11,237 2,217 3,304 25,206 

Emissions per year (TgCO2-eq)

Mean 28.2 0.3 4.1 2.4 1.8 36.7

Standard deviation 18.9 0.3 2.6 2.2 1.4 21.3

Minimum 4.7 0.0 0.8 0.5 0.3 6.8

Median 28.8 0.2 4.0 2.1 1.3 41.0

95th quantile 54.7 0.6 7.1 6.0 3.6 65.0

Maximum 64.1 0.7 7.1 7.4 3.7 75.3

The Western Cordillera ecoregion had the most wildland 

fires and the highest emissions among all the Western United 

States ecoregions (table 3.1 and fig. 3.3A). The number of 

wildland fires between 2001 and 2008 averaged 123/yr and 

ranged from 61 in 2004 to 173 in 2003. The burned area and 

the emissions averaged 5,708 km2/yr and 28.2 TgCO2-eq/ yr, 

respectively. The interannual variability was high and the 

area burned and the emissions ranged between 1,856 km2

and 4.7 TgCO2-eq in 2004 and 10,449 km2 and 64.1 TgCO2-eq

in 2007, respectively. The Western Cordillera covers 

approximately 872,000 km2. After normalizing the area burned 

and the emissions for the ecoregion’s area, the annual area 

burned ranged between 0.21 and 1.20 percent and the annual 

emissions ranged between 2.6 and 6.2 kgCO2-eq/m2/yr for the 

entire Western Cordillera.
Chapter 3 33

2001 2002 2003 2004

Year

2005 2006 2007 2008

Number of wildfires

0

200

400

600

Area burned, in square kilometers

0

10,000

30,000

20,000

0

20

40

60

80

Figure 3–2.

Emissions, in teragrams of

carbon dioxide equivalent

Figure 3.2. Graphs showing the annual number of wildland 

fires, area burned, and emissions for the baseline time period 

(2001–2008) in the Western United States.

Of all the ecoregions in the Western United States, the 

Marine West Coast Forest ecoregion had the fewest wildland 

fires, the smallest area burned, and the lowest emissions 

(table 3.1 and fig. 3.3B). The number of wildland fires 

averaged 5/ yr and ranged from 1 to 13. The area burned 

ranged from 9 to 200 km2 and averaged 79 km2/yr. The 

emissions from the Marine West Coast Forest ranged from 

0 to 0.7 TgCO2-eq /yr and averaged 0.3 TgCO2-eq/yr. The area 

of the Marine West Coast Forest ecoregion is approximately 

98,000 km2. After normalizing the wildland-fire-occurrence 

statistics for area, from 0.01 to 0.13 percent of the ecoregion 

burned each year and emissions ranged from 2.6 to 

4.8 kgCO2-eq/m2/yr.

The Cold Deserts ecoregion is the largest ecoregion in the 

Western United States at 1 million km2 and had nearly as much 

wildland-fire activity as the Western Cordillera (table 3.1

and fig. 3.3C). On average, there were 121 wildland fires per 

year, but the interannual variability was high; as few as 36 

wildland fires were observed in 2004 and as many as 245 were 

observed in 2006. The amount of area burned each year in 

the Cold Deserts ecoregion was similar to that of the Western 

Cordillera and averaged 5,056 km2/yr, ranging from 583 km2

in 2004 to 11,237 km2 in 2007. This range is equivalent to 

0.06 to 1.07 percent of the area of entire ecoregion; however, 

because the vegetation in the Cold Deserts is predominantly 

grass and shrubs, emissions were lower, averaging only 

4.1 TgCO2-eq/yr and ranging from 0.8 to 7.1 TgCO2-eq in 2004 

and 2007, respectively. 

In the Warm Deserts ecoregion, wildland fires were 

infrequent with an average of 25 wildfires per year, but 

as many as 66 in 2005 and as few as 7 in 2004 (table 3.1

and fig. 3.3D). The amount of area burned was also small 

and ranged from 198 km2 in 2004 to 2,217 km2 in 2005 

with an average of 785 km2/yr. This range equated to 

0.16 to 0.46 percent of the ecoregion area, which was 

478,000 km2. The emissions were generally low, with an 

average of 2.4 TgCO2-eq/yr; the variability in emissions was 

high, however, and varied from 0.5 TgCO2-eq in 2004 to 

7.4 TgCO2-eq in 2008. When normalized for the area burned, 

the emissions ranged from 1.0 to 3.5 kgCO2-eq/m2/yr.

The Mediterranean California ecoregion is the 

smallest in the Western United States (173,000 km2) but 

still had a substantial amount of wildland-fire activity. On 

average, there were 31 wildland fires per year with a range 

from 15 to 39 (table 3.1 and fig. 3.3E). The area burned 

averaged 1,585 km2/yr and had a range of 301 to 3,304 km2

in 2001 and 2003, respectively. The emissions averaged 

1.8 TgCO2-eq/ yr but ranged from 0.3 to 3.7 TgCO2-eq in 

2005 and 2008, respectively. The amount of area burned 

and emissions were large relative to the total area of the 

ecoregion. The area burned ranged from 0.17 to 1.91 percent 

of the entire ecoregion (the highest percent area in the 

Western United States), and the emissions ranged from 0.6 to 

1.2 kgCO2-eq/ m2/yr.
34 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

2001 2002 2003 2004 2005

Year Year Year

2006 2007 2008 2001 2002 2003 2004 2005 2006 2007 2008 2001 2002 2003 2004 2005 2006 2007 2008

Number of wildfires Area burned,

in square kilometers

0

50

100

150

200

A. Western Cordillera

0

4,000

8,000

12,000

0

20

40

60

80

0

4

8

12

14

B. Marine West Coast Forest

0

50

100

150

200

250

0

0.2

0.4

0.6

0.8

0

100

200

300

C. Cold Deserts

0

4,000

12,000

8,000

0

2

4

6

8

0

20

40

60

80

D. Warm Deserts

1,000

1,500

500

0

2,000

2,500

0

2

4

6

8

0

10

20

30

40

50

E. Mediterranean California

0

1,000

3,000

4,000

2,000

0

1

2

3

4

Figure 3–3.

Emissions, in teragrams of

carbon dioxide equivalent

Figure 3.3. Graphs showing the annual number of wildland fires, area burned, and emissions for the baseline time period 

(2001–2008) for level II ecoregions in the Western United States (EPA, 1999). The vertical scales are not constant among 

ecoregions.
Chapter 3 35

3.5. Discussion

From 2001 to 2008, wildland-fire activity in the 

Western United States was substantial; large wildland 

fires numbered between 131 and 467 per year and burned 

from 3,345 to 25,206 km2 each year. These western 

wildland fires represented 58 percent of all the wildland 

fires that occurred nationwide from 2001 to 2008 and 

are mapped in the MTBS database, and accounted for 

75 percent of the all area burned. The annual emissions 

averaged 36.7 TgCO2-eq/yr, which was equivalent to 0.7 

percent of the nationwide fossil-fuel emissions in 2010 

(5,594 TgCO2-eq/yr; EPA, 2012). The interannual variability 

in emissions was high and ranged from 6.8 to 75.3 TgCO2-eq

in the Western United States, which was equivalent to 

0.1 to 1.3 percent of the nationwide fossil‐fuel emissions, 

respectively. Thus, the relative contribution of wildland fires 

of the Western United States to nationwide greenhouse-gas 

emissions was small when compared to the contribution of 

anthropogenically generated emissions.

There was a large amount of year-to-year variability in 

wildland-fire occurrences, area burned, and emissions among 

the five ecoregions in the Western United States (table 3.1

and fig. 3.3), which was related to differences in vegetation 

and fire regimes. The Marine West Coast Forest and Western 

Cordillera ecoregions are dominated by coniferous forests, but 

have quite different fire regimes. Precipitation is high in the 

Marine West Coasts Forest, which results in highly productive 

vegetation, but the infrequent wildland fires can be severe 

(Agee, 1993). The forests in the Western Cordillera tend to 

exist in a drier climate with more frequent wildland fires, but 

the severity is mixed and depends on drought and vegetation 

conditions (Schoennagel and others, 2004). In both the 

Marine West Coast Forest and Western Cordillera ecoregions, 

wildland-fire emissions can be high under severe conditions 

because large amounts of canopy fuels can be consumed by a 

crown fire. The Marine West Coast Forest did not produce a 

substantial amount of emissions in this analysis, but that may 

be in part because the wildland-fire frequency was low in this 

ecoregion and the 25-year span covered by the MTBS did not 

include a sizeable amount of fire activity there. The results 

of this assessment, however, do highlight the importance of 

wildland-fire emissions in the Western Cordillera at both a 

regional and national scale because this ecoregion produced 

77 percent of all emissions in the Western United States during 

the baseline period.

In contrast to the Marine West Coast Forest and the 

Western Cordillera, the Cold Deserts, Warm Deserts, and 

Mediterranean California ecoregions are dominated by the 

grasslands/shrublands ecosystem and other ecosystems 

(primarily deserts). Wildland fires were frequent in all three 

ecoregions but were more common in the Cold Deserts and 

Mediterranean California than in the Warm Deserts. The fire 

regimes in the desert ecoregions were related to vegetation 

productivity and climate (Mensing and others, 2006; Brooks 

and Chambers, 2011). These same drivers influenced wildland 

fires in the Mediterranean California ecoregion, but human 

influences and extreme winds also played a large role 

(Syphard and others, 2007; Moritz and others, 2010). Invasive 

species were also present in all three ecoregions, often 

displacing native vegetation and thus increasing wildland-fire 

frequency (D’Antonio and Vitousek, 1992; Brooks and others, 

2004; Keeley, 2006). These results suggest that an extensive 

amount of area can burn in these regions, but the emissions are 

generally lower than those of the forested ecoregions simply 

because of the difference in the amount of available fuel.

3.6. Limitations and Uncertainties

The MTBS data used in this assessment did not include 

small wildland fires, but they still captured the majority of the 

area burned because they included the largest wildland fires 

which contributed most to the amount of area burned (Strauss 

and others, 1989; Stocks and others, 2002). A comparison 

of the MTBS data with the Federal wildland-fire-occurrence 

database (U.S Department of the Interior, 2012) showed 

that the MTBS listed only 2 percent of all wildland fires but 

that 2 percent accounted for 80 percent of the area burned in 

the five ecoregions covered by this assessment. Therefore, 

the results of this assessment captured the general patterns 

and trends of western wildland fires, but provided a slight 

underestimate of wildland-fire emissions.

In this assessment, the estimates of area burned and of 

emissions also did not include the influence of prescribed 

and agricultural fires (for example, burning crop residues); 

however, the emissions produced by those types of fires were 

suspected to be low relative to the wildland-fire emissions. 

The influence of prescribed fires on emissions was difficult to 

assess because the data characterizing prescribed fires were 

generally poor based on inconsistent reporting about them 

across the country. The existing estimates of emissions from 

prescribed fires suggested that they produced only 10 percent 

of the emissions from wildland fires (Y. Liu, 2004), in part 

because prescribed fires usually burn under less extreme 

meteorological conditions than wildland fires. The influence 

of agricultural fires was also estimated to be about 10 percent 

of the wildland-fire emissions in the GFED database. In the 

Western United States, the relative amount of emissions 

produced by prescribed and agricultural fires was likely to be 

even lower, because agricultural fires were more common in 

the Great Plains and the Eastern United States (Korontzi and 

others, 2006; Tulbure and others, 2011) and prescribed fires 

in the Western United States only accounted for 22 percent 

of the area burned by prescribed fires nationwide (National 

Interagency Fire Center, 2012).
36 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The emissions results generated for this assessment 

differed and were generally lower than past estimates 

of emissions for the Western United States. The highest 

emissions estimates were from Wiedinmyer and Neff (2007), 

who used the active wildland fire data from the MODIS 

from 2002 to 2006 and estimated the mean and standard 

deviation of annual emissions at 105.0 and 42.0 TgCO2-eq, 

respectively, for the following States: Arizona, California, 

Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, 

Utah, Washington, and Wyoming; the five ecoregions in this 

assessment do not cover the exact same area. French and 

others (2011) calculated emissions using the MTBS data and 

CONSUME model (Ottmar and others, 2008) for wildland 

fires occurring from 2001 to 2008; their results are available 

online as ecoregion-level summaries (Michigan Tech Research 

Institute, 2012). When their results were summarized across 

the Western United States, the average and standard deviation 

of annual emissions was 78.4 and 43.3 TgCO2-eq, respectively, 

which is nearly twice the amount of the emissions estimated 

in this assessment. The emission estimates from both of 

these analyses were substantially greater than the estimates 

generated for this assessment. The differences are most likely 

due to differences in methods, data, and the resolution of 

the data used. Wiedinmyer and Neff (2007) relied on 1-km 

resolution, active-wildland-fire data from MODIS and fuels 

data from the Fuels Characterization Classification System 

(FCCS; USDA Forest Service, 2012d). They also assumed that 

all of the available biomass could potentially burn, and that 

is often not the case, especially for woody fuels (Campbell 

and others 2007; Meigs and others, 2009). French and others 

(2011) also used the 1-km-resolution FCCS fuels data and 

aggregated 1-km-resolution MTBS data. The fuels data in 

their report differed from the data layer used in this assessment 

both in terms of information and resolution. The methods 

used in this assessment made use of fuel moistures, which are 

based on gridded daily weather data. The methods used by 

French and others (2011) also made use of fuel moistures, but 

recommended 10 percent levels for 1,000-hour availability 

and duff moistures, which are very favorable conditions for 

combustion. The full effects of the differences in fuel maps 

and moisture levels on this assessment were difficult to 

assess, but these comparisons suggest that the results in this 

assessment are more conservative than previously published 

estimates of wildland-fire emissions.

3.7. Implications for Management 

and Mitigation

For this assessment, the effects of different strategies for 

wildland-fire management and mitigation on fire emmissions 

were not explicitly addressed, but there is a growing body of 

literature from which to draw some conclusions. Increasing 

the effectiveness of fire suppression (which includes 

firefighting, prevention, and education) is a popular first 

choice but unlikely to work to reduce fire emmissions given 

that fire suppression over the past 100 years has had mixed 

success (Rollins and others, 2001; Keane and others, 2002; 

Stephens and Ruth, 2005). In some ecoregions, reducing the 

area that could potentially be burned may be possible and 

critical to maintain ecosystem health, especially in areas 

where wildland‐fire frequency is suspected to be unnaturally 

high because of the increase in human influence due to 

arson, accidental ignitions, or the accidental or deliberate 

introduction of invasive species, such as in Southern 

California (Keeley and others, 1999) and in the grasslands, 

shrublands, and deserts of the Southwestern United States 

where fire-adapted invasive species are altering wildland-fire 

cycles (D’Antonio and Vitousek, 1992; Brooks and others, 

2004; Keeley, 2006).

A more effective way to reduce wildland-fire emissions 

from forests may be to implement management strategies 

designed to reduce wildland-fire severity, which is directly 

related to the amount of biomass consumed. In many parts 

of the Western United States, fire suppression has resulted 

in unnaturally high fuel loads producing wildland fires that 

are of uncharacteristically high severity (Stephens, 1998; 

Keane and others, 2002; Agee, 2003; Stephens and Ruth, 

2005). Fuel treatments, including mechanical forest thinning 

and prescribed fires, are designed to reduce fuel loads so that 

wildland fires are less intense and easier to manage if they do 

occur (Agee and Skinner, 2005; Reinhardt and others, 2008). 

Most of the evidence suggests that fuel treatments can reduce 

carbon loss through wildland-fire emissions over the long term 

even though there is a short-term loss in carbon storage due 

to biomass removal (Stephens and others, 2009; Reinhardt 

and Holsinger, 2010; Wiedinmyer and Hurteau, 2010; North 

and Hurteau, 2011). Such treatments are most effective in 

forests where fuel loads are uncharacteristically high and may 
Chapter 3 37

not be ecologically appropriate in other forest and vegetation 

types (Sibold and others, 2006; Mitchell and others, 2009). 

To produce a noticeable effect at a regional scale, between 

20 and 40 percent of the Western United States’ forests 

need to be treated (Finney, 2001, 2007). The potency of fuel 

treatments can be short-lived, on the order of 10 to 20 years 

(Collins and others, 2011); therefore, 1 to 4 percent of the 

forested landscape would need to be treated annually (Finney 

and others, 2007). Given that wildland fires are rare events, the 

proportion of the landscape that must be treated is much larger 

than the proportion of the landscape that burns and because 

of that relation, the amount of carbon removed from biomass 

pools in fuel treatments may be greater than the amount of 

carbon protected from fire (Campbell and others, 2012).

In some nonforested ecosystems in the Western United 

States (especially southern California, the Great Basin, and 

the Sonoran and Mojave Deserts), the frequencies of wildland 

fires are uncharacteristically high and are driven by human 

ignition of some fires and by invasive species which provide 

extra fuel (D’Antonio and Vitousek, 1992; Keeley and others, 

1999; Brooks and others, 2004; Keeley, 2006). Wildland-fire 

emissions in these nonforested ecosystems are likely to be 

greater and carbon stocks lower than in historic time because 

native woody vegetation has been replaced by invasive 

grasses (Bradley and others, 2006). Even though wildland-fire 

emissions from these nonforested ecosystems are low relative 

to those from forested ecosystems, reducing the wildland-fire 

frequency to the historical range of variability may result in 

only slightly reduced overall wildland-fire emissions. In other 

nonforested ecosystems in the Western United States (such as 

grasslands/shrublands), the opposite has happened. Grazing 

pressure has reduced the grass cover and the frequency of 

wildland fires, thus allowing woody vegetation to expand its 

range and increase in cover (Van Auken, 2000). The expansion 

of woody vegetation usually results in an increase in carbon 

stocks (Asner and others, 2003); however, it is uncertain 

if the increased carbon stocks will persist over long time 

periods given changes in climate and fire regimes (Barger and 

others, 2011).

Much uncertainty remains about the short- and long-term 

effects of wildland-fire management on carbon budgets in 

many ecosystems in the Western United States. Any carbonmanagement strategy focused on increasing ecological carbon 

stocks or sequestration rates should carefully consider the 

benefits and risks of wildland-fire management over both 

short and long time periods, as well as the effects on other 

ecosystem characteristics and services (Jackson and others, 

2005; McKinley and others, 2011; Olander and others, 2012).
38 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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Chapter 4. Major Land-Management Activities and 

Natural Disturbances Considered in This Assessment

By Shuguang Liu1, Jennifer Oeding2, Zhengxi Tan3, Gail L. Schmidt2, and Devendra Dahal2

4.1. Introduction

Carbon stocks and fluxes of ecosystems are strongly 

influenced by, among other factors, land-management 

activities and natural disturbances. The U.S. Forest Service 

(USFS) estimated that approximately 4.05 million hectares 

(or 1.3 percent) of forested land is harvested each year (W.B. 

Smith and Darr, 2004), which may significantly affect the 

carbon cycle at local to national levels (Cohen and others, 

1996; Pan, Birdsey, and others, 2011). Although the effects of 

natural disturbances and land management on carbon dynamics 

are significant, few datasets exist that adequately describe the 

spatial and temporal characteristics of various land-management 

activities. This chapter provides a brief review of major natural 

disturbances and land-management activities in the Western 

United States in relation to carbon sequestration, describes 

the status of data availability for the activities, and introduces 

those activities that were included in the assessment and their 

data-processing steps. Wildland fires are the most significant 

natural disturbances in the Western United States. Chapters 3

and 8 of this report provide extensive treatment of wildland 

fires; therefore, the primary focus of this chapter is on the landmanagement activities that were considered in the modeling 

process for this assessment.

4.2. Review of Major Land-Management 

Activities and Natural Disturbances 

Major land-management activities and natural 

disturbances, their impacts on carbon dynamics, and the status 

of the geospatial data layers characterizing their spatial and 

temporal changes in the Western United States are briefly 

reviewed below. 

4.2.1. Forest Harvesting

There are many examples of forest harvesting data at 

a local scale, but they are rarely available at a national or 

regional scale in a spatial format. The USFS Forest Inventory 

and Analysis (FIA) Program (USDA Forest Service, 2012b) 

provides nationwide information on the extent, condition, 

volume, growth, and removal of trees. The FIA is the best 

available resource for information on forest-management 

activities and its database was extensively used in support 

of this assessment. On the other hand, the FIA is a sitespecific characterization of forest conditions, which was 

both an advantage and a limitation. The lack of wall-to-wall 

geospatial information from the FIA often made it difficult 

to identify the real clearcutting patterns for modeling efforts 

over a large area. Current approaches that merge remotely 

sensed land-cover-change information with FIA inventories 

have shown promising results (for example, Hicke and others, 

2007; Goward and others, 2008; Cho-ying Huang and others, 

2010; D.P. Turner, Gockede, and others, 2011; Williams and 

others, 2012).

4.2.2. Wildland Fires

Wildland-fire combustion releases carbon into the 

atmosphere and resets the pathways for carbon-sequestration 

across the landscape (Running, 2008). For this assessment, 

the treatment of both the baseline and the projected future 

potential fire emissions is covered in chapters 3 and 8; the 

fire-extent and fire-severity data layers were used to support 

the biogeochemical modeling (see chapters 5 and 9).

1U.S. Geological Survey, Sioux Falls, S.D.

2Stinger Ghaffarian Technologies, Inc., Sioux Falls, S.D.

3Arctic Slope Regional Corporation Research and Technology Solutions, Sioux Falls, S.D.
40 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

4.2.3. Insects and Disease 

Insects and disease, such as the western pine bark beetle, 

cause extensive defoliation, mortality, and reduced carbon 

stocks in forests across the Western United States (Fellin 

and Dewey, 1992; Man, 2010; Pfeifer and others, 2011). The 

carbon-cycle processes that are affected by insects or disease 

depend on the type of disturbance and whether it causes 

defoliation or tree mortality (S. Liu and others, 2011). The 

USFS FIA database (USDA Forest Service, 2012b) contained 

information related to the types and severity of insects and 

disease and related information on defoliation and mortalities; 

however, the database was limited by a lack of repeated 

inventories, which limited the analysis for insects and disease. 

4.2.4. Grazing on Grasslands and Shrublands

Grazing on grasslands and shrublands in the Western 

United States, particularly in the Great Basin and the Colorado 

Plateau, is a leading land-use activity and has had a major 

effect on the carbon cycle and other qualities of the landscape 

(Wagner, 1978; Crumpacker, 1984; Fleischner, 1994). Many 

studies have documented the effects of grazing on carbon 

cycles (for example, Lal, 2004; Derner and Schuman, 2007; 

Schuman and others, 2009), but often at the local scale. The 

USGS carbon-sequestration assessment for the Great Plains 

(Zhu and others, 2011) relied on assumed relationships 

between the animal unit month (AUM, the amount of forage 

required by an animal unit for one month; Ruyle and Ogden, 

1993) and carbon removal, but the uncertainty was very high. 

Ultimately, any regional or national assessment of the effects 

of grazing is limited by the absence of synthesized data or a 

georeferenced database. 

4.2.5. Crop Rotation and Tillage

Tillage is one of the major land-management activites 

that could substantially affect carbon storage in and GHG 

fluxes from the soil (Ogle and others, 2005; Alluvione and 

others 2009). Crop rotation, residue management, and tillage 

practices are exercised in all agricultural areas of the Western 

United States. In practice, both residue management and 

tillage practices (either no tillage, conventional tillage, or 

reduced tillage) are commonly coupled to form a cropping 

system. The data by acreage for both practices are usually 

reported as county-based statistics by the Conservation 

Technology Information Center (CTIC, 2012). For this 

assessment, although the CTIC data were not georeferenced, 

they were allocated to each crop type using a method by 

Schmidt and others (2011). 

4.2.6. Irrigation and Drainage

The Snake River Plain and Columbia River Basin support 

agriculture production (row crops, hay and pasture) with 

large-scale irrigation projects. Irrigation can increase soil 

moisture, improve crop yields, and potentially enhance carbon 

sequestration in soil (Lal and others, 1998). The drainage 

of wet soils may increase crop and animal productivity 

and reduce methane emissions, but it may also lead to a 

loss of soil organic carbon (SOC) stock by increasing the 

decomposition of soil organic matter and the leaching of 

dissolved organic carbon (Watson and others, 2000); however, 

data about irrigation are limited (Wu and others, 2008). A 

nationwide MODIS-derived dataset about irrigated agriculture 

(MIrAD-US) was developed by the USGS for 2002 (USGS, 

2010) and 2007 (Pervez and Brown, 2010) at both 1,000-m 

and 250-m resolution. They are available at USGS (2010). 

4.2.7. Manure Application

Manure is widely used in agricultural fields to supply 

nutrients because of the high price of fertilizers (Lentz 

and Lehrsch, 2010). According to MacDonald and others 

(2009), about 15.8 million acres of cropland, equivalent 

to about 5 percent of all cropland in the United States, are 

fertilized with livestock manure. Data on manure production 

and application are usually estimated through the USDA’s 

Agricultural Resource Management Survey (ARMS; USDA 

Economic Research Service, 2011a). The EPA estimated 

the annual manure-related GHG emissions at both State 

and national levels on the basis of annual yields of animal 

products and determined that manure application was one 

of the major contributors to the total GHG emissions from 

agricultural lands, amounting to up to 19.88 TgCO2-eq in 2010 

over the Western United States, of which California made the 

greatest contribution (52 percent), followed by Idaho (about 

20 percent) (EPA, 2012).
Chapter 4 41

4.3. Data Processing for Major 

Land-Management Activities and 

Natural Disturbances Included in 

the Assessment

As with the Great Plains assessment conducted by the 

USGS (Zhu and others, 2011), this assessment relied on 

nationwide geospatial data layers in order to characterize the 

spatial and temporal dynamics of land-management activities 

and natural disturbances (Schmidt and others, 2011). Table 4.1

lists the data layers used for major land-management activities 

and natural disturbances for this assessment and figure 4.1

depicts the spatial patterns of some data layers for 2005. 

The spatial resolution of some of the data layers 

in table 4.1, especially those derived from censuses and 

inventories, was at the county, State, or FIA-unit level. These 

data layers were further downscaled to pixels to generate 

spatially explicit map layers using a Monte Carlo procedure, 

land cover, and other information (Schmidt and others, 2011). 

The most common pixel resolution among all the map layers 

was 250 meters. The data covered the time period from 1992 

to 2050 on an annual basis. Annual maps showing areas of 

forest clearcutting were produced as part of the LULC-change 

modeling detailed in chapter 2 of this report. Annual maps of 

wildland-fire disturbances were modeled using an approach 

described in chapter 3 of this report.

Table 4.1. Summary of data for the major land-management activities and natural disturbances that were considered as part of this 

assessment.

[CFS, Canadian Forest Service; CTIC, Conservation Technology Information Center; m, meter; NA, not applicable; PRISM, parameter-elevation regressions on 

independent slopes model; USDA, U.S. Department of Agriculture; USDA ERS, USDA Economic Research Service; USDA FIA RPA, USDA Forest Inventory 

Analysis Resource Planning Act; TPO, timber product output; USGS, U.S. Geological Survey]

Type Source Spatial 

resolution Time period Reference

Crop management

Crop yield USDA crop yield table County 1992–2050 USDA National Agricultural Statistics 

Service (2011).

Fertilization USDA ERS fertilization table County 1992–2050 USDA Economic Research Service 

(2011b).

Manure USDA manure table County 1996–2050 USDA Economic Research Service 

(2011a).

Tillage CTIC tillage table County 1992–2050 CTIC (2011); USDA Economic Research 

Service (2011a).

Irrigation USGS 250 m NA USGS (2010).

Derived crop management

Derived crop type, manure, tillage, 

and fertilizer

Derived grids for this assessment 250 m 1992–2050 Schmidt and others (2011).

Fire

Extent, severity, frequency This assessment 250 m 1992–2050 Chapters 3 and 8 of this report.

Forest clearcuts

Forest-stand age USGS Land Cover Trends Project 250 m 1992–2050 USGS (2012a).

Timber product output TPO from USDA FIA RPA State 2002 USDA Forest Service (2011)

Drought

Precipitation PRISM and CFS 250 m 1992–2050 Canadian Forest Service (2012); PRISM 

Climate Group (2012).
42 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

0 0

2,909

958

52

199 11

26616 193

Marine

West

Coast

Forest

Western Cordillera

Warm

Deserts

Mediterranean

California

Cold

Deserts

A. Land cover, 2005 B. Manure, 2005

0 200 400 MILES

0 200 400 KILOMETERS

Figure 4–1.

C. Tillage, 2005 D. Irrigation, 2005 

N

Figure 4.1. Maps showing examples of the data layers for land-management activities and natural disturbances in 

the Western United States for 2005. A, Land cover. B, Manure. C, Tillage. D, Irrigation. E, Fire severity. F, Stand age. See 

figure 1.1 in chapter 1 for ecoregion names.
Chapter 4 43

Water

Developed

Mechanically 

 disturbed 

 national forest

Mechanically 

 disturbed other

 public land

Mechanically 

 disturbed 

 private land

Mining

Barren

Deciduous forest

Evergreen forest

Mixed forest

Grassland

Shrubland

Hay/pasture

Woody wetlands

 Herbaceous 

 wetlands

Perennial ice/snow

Barley

Beans

Corn grain

Corn silage

Cotton

Flaxseed

Lentils

Sorghum silage

Oats

Peanuts

Peas

Potatoes

Rice

Rye

Safflower

Sorghum

Soybeans

Sugarbeets

Sunflowers

Tomatoes

Wheat durum

Wheat spring

Wheat winter

Carbon

Nitrogen

Land use and land cover

EXPLANATION

Total manure

 application

 per level II 

 ecoregion—

 In kilograms

Irrigation

Non-irrigated

Irrigated

Tillage

None

Ridge

Mulch

Reduced

Conventional

Fire severity

Low

Moderate

High

Stand age—

 In years

0

1 to 5

6 to 10

11 to 15

16 to 30

31 to 50

51 to 100

101 to 250

>250

E. Fire severity, 2005 F. Stand age, 2005

0 200 400 MILES

0 200 400 KILOMETERS

Figure 4–1.—Continued

N

1,500

750

Level III

Level II

Ecoregion

 boundary

Figure 4.1.—Continued
44 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The crop-management information used in this 

assessment includes crop type, crop rotation, fertilization, 

manure addition, tillage practices, irrigation, and harvesting 

practices. All of the crop-management activities were 

specific to various crops and locations. All of the pixels 

representing agricultural lands in the land-cover data layers, 

generated in the LULC mapping and modeling process 

described in chapter 2 of this report, were downscaled 

(using a probability-based Monte Carlo approach) to crop 

types according to the crop-composition information 

derived from the USDA agricultural census data (USDA 

National Agricultural Statistics Service, 2011). All of the 

crop‐management data layers (except irrigation) were 

subsequently generated from these land-cover data layers and 

more than 20 major crops were presented consistently for the 

United States (Schmidt and others, 2011). The tabular data 

about manure application were derived from the USDA census 

(USDA, Economic Research Service, 2011a), which included, 

for each crop type in each State, the following information: the 

State Federal Information Processing Standard (FIPS) code, 

the year, the total planted area, the percentage of the planted 

area that was treated with manure, the amount of manure that 

was applied, the rate at which the manure was applied, the 

rate at which the nitrogen in the manure was applied, and rate 

at which the carbon in the manure was applied. A gridded 

manure dataset for all agricultural lands in the region was 

generated from this tabular data along with the land-cover 

maps using a Monte Carlo procedure. 

The information about tillage practices was acquired 

from the CTIC in tabular format. The tabular data include 

the following information: the State FIPS code, the year, 

the total planted area that was tilled, the total percentage of 

residue on all tilled areas, the planted area for each tillage 

type, and the percentage of residue for each tillage type by 

crop type within the State. The tillage practices included in 

the database included conventional, mulch, no-till, reduced, 

and ridge tillage. A gridded dataset showing the spatial and 

temporal changes of tillage practices for all agricultural lands 

was generated from this tabular data along with the land-cover 

maps using a Monte Carlo procedure. Figure 4.1 shows the 

spatial distribution of tillage practices in the Western United 

States in 2005. An irrigation map derived from the MODIS for 

the United States (USGS, 2010) was used to characterize the 

locations of irrigated land. Because of the lack of data showing 

the temporal changes in irrigation across the Western United 

States, this assessment assumed that the locations of irrigated 

land did not change over time during the assessment period. 

Only nitrogen fertilization was considered in this 

assessment. A nationally consistent procedure was put in place 

to generate crop- and location-specific nitrogen-fertilization 

data for all croplands (see Schmidt and others, 2011). The 

tabular dataset included the State FIPS code, year, the total 

planted area where nitrogen fertilizer was applied, the 

percentage of total area that was fertilized with nitrogen, the 

rate of application for nitrogen fertilizer, and the total amount 

of nitrogen fertilizer applied for each crop type within each 

State. Because several States in the Western United States 

did not report this information, this assessment assumed that 

croplands were automatically fertilized every year in order to 

satisfy growth requirements. 

4.4. Land-Management Activities or 

Natural Disturbances Not Included in 

the Assessment 

Because of the lack of input data and constraints on 

resources, this assessment did not explicitly consider the 

following activities:

• Selective or partial forest cutting. One of major 

factors driving carbon dynamics in forest ecosystems 

is selective or partial forest cutting, which should 

have been considered for the modeling steps in this 

assessment. Unfortunately, there were no spatial 

datasets available that characterized the spatial and 

temporal changes of selective or partial forest cutting 

in the Western United States.

• Insects and diseases. Various studies and inventories 

of natural disturbances by insects and diseases have 

been conducted at a broad regional scale. For example, 

Raffa and others (2008) provided an estimate of forest 

mortality caused by bark beetle eruptions in western 

North American forests. These types of data were not 

included in this assessment because their spatial and 

temporal extents and resolution were usually limited. 

• Grazing. Grazing on grasslands and shrublands is 

extensive and varies in both time and space; however, 

there are no geospatial datasets available that 

characterize grazing in the Western United States.
Chapter 5. Baseline Carbon Storage, Carbon 

Sequestration, and Greenhouse-Gas Fluxes in Terrestrial 

Ecosystems of the Western United States

By Shuguang Liu1, Jinxun Liu2, Claudia J. Young2, Jeremy M. Werner1, Yiping Wu3, Zhengpeng Li4, Devendra 

Dahal2, Jennifer Oeding2, Gail L. Schmidt2, Terry L. Sohl1, Todd J. Hawbaker5, and Benjamin M. Sleeter6

1U.S. Geological Survey, Sioux Falls, S.D.

2Stinger Ghaffarian Technologies, Inc., Sioux Falls, S.D.

3Arctic Slope Regional Corporation Research and Technology Solutions, Sioux Falls, S.D.

4

University of Maryland, College Park, Md.

5

U.S. Geological Survey, Denver, Colo.

6

U.S. Geological Survey, Menlo Park, Calif.

5.1. Highlights 

• From 2001 to 2005 in the Western United States, 

the average annual total carbon stored in vegetation 

and soils (up to 20 cm in depth) was estimated to be 

13,920 TgC, ranging from 12,418 to 15,461 TgC. 

• The Western Cordillera ecoregion stored the most 

carbon (59 percent of the total), followed by the 

Cold Deserts (19 percent), Marine West Coast Forest 

(11 percent), Mediterranean California (6 percent), 

and Warm Deserts (5 percent) ecoregions. 

• Forests, grasslands/shrublands, and agricultural 

lands stored 69 percent, 25 percent, and 4.3 percent 

of the total carbon in ecosystems of the Western 

United States, respectively. 

• Live biomass, soil organic carbon (SOC) in the 

top 20 cm of the soil layer, and dead biomass 

(forest litter and dead woody debris) accounted 

for 38 percent, 39 percent, and 23 percent, 

respectively, of the total carbon stored in the Western 

United States.

• The average annual net carbon flux in the terrestrial 

ecosystems of the Western United States was 

estimated to be −86.5 TgC/yr, ranging from −162.9 

to −13.6 TgC/yr from 2001 to 2005. (Negative values 

denote a carbon sink.)

• Forests were the largest carbon sink (62 percent of 

the average), followed by grasslands/shrublands 

(30 percent), and agricultural lands (7 percent). 

• The live biomass pool provided about one-third of 

the carbon sink; the rest was provided by the dead 

biomass and the SOC pools.

• The ecosystems of the Western United States served 

as a greenhouse-gas (GHG) sink for three gases: 

carbon dioxide (CO2), nitrous oxide (N2O), and 

methane (CH4). These GHGs accumulated at an 

estimated −599.1 to −51.3 TgCO2-eq/yr. Overall, the 

carbon dioxide sink provided by the ecosystems was 

responsible for about 99 percent of the total GHG flux. 

The fluxes of nitrous oxide (for which the Western 

United States was a source) and methane (for which 

the Western United States was a sink) were relatively 

very small.

5.2. Introduction 

This chapter describes the modeling and analysis of 

the baseline carbon storage and GHG flux in ecosystems of 

the Western United States. As indicated by the methodology 

diagram (figure 1.2 of chapter 1 of this assessment), this 

component of the assessment uses land-use and land-cover 

(LULC) mapping and modeling results (chapter 2) and 

wildland-fire modeling results (chapter 3) as the primary 

input data in addition to other input data described later in this 

chapter. The definitions of the ecosystems and the descriptions 

of the ecoregions are provided in chapters 1 and 2 of this 

report. See table 2.1 of chapter 2 of this report for definitions 

of the ecosystems covered in this chapter. The tables in this 
46 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

chapter present the results of carbon stock, carbon flux, and 

GHG fluxes in terms of the following pools: live biomass 

(both aboveground and belowground), soil organic carbon 

(SOC; measured in the top 20 cm of the soil layer), and dead 

biomass (forest litter and dead, woody debris).

Land-use and land-cover change, natural disturbances, 

and climate change directly alter carbon fluxes and carbon 

stocks in ecosystems. Although these influences on the 

carbon cycle have been observed from local to global 

scales, there is increasing scientific and political interest in 

regional patterns and causes of terrestrial carbon sources 

and sinks (Intergovernmental Panel on Climate Change, 

2007; Piao and others, 2009; Pan, Birdsey, and others, 2011). 

Many studies have evaluated the carbon stocks and fluxes 

in diverse ecosystems and addressed their complicated 

interactions with climate change, LULC change, and natural 

disturbances. The U.S. Environmental Protection Agency 

(EPA) has reported annual carbon fluxes for the United 

States since 1997 and estimated that U.S. forests sequestered 

approximately −256 TgC/yr (EPA, 2012). The U.S. Forest 

Service (USFS) estimated a combined stock of 15,095 TgC 

in all of the major pools of the Pacific Coast and Rocky 

Mountain regions for 2005 and that, on average between 2000 

and 2008, the forest ecosystems sequestered approximately 

−43.1 TgC/yr in those two regions (Heath and others, 

2011). Hudiburg and others (2011) estimated that the net 

biome production (NBP) of the forests in the Pacific coastal 

regions of Washington, Oregon and California averaged 

−95 TgCO2-eq/yr (−25.9 TgC/yr) between 2001 to 2006. 

In California, the annual carbon flux for all forests in 2010 

was estimated to be −30 TgCO2-eq/yr on the basis of USFS 

permanent-plot data, forest-growth models, wildland‐fire 

emission estimates, and timber harvest data (California 

Department of Forestry and Fire Protection, 2010; Robards, 

2010). A separate study found that forests and rangelands in 

California in the 1990s were responsible for a net removal 

of –7.55 TgCO2-eq per year from the atmosphere and that 

agricultural lands were responsible for a net emission of 

0.35 TgCO2-eq/yr (S. Brown, Pearson, Dushku, and others, 

2004). Citing wildland-fire disturbances and human‐induced 

land-cover changes as two key factors that drive carbon 

balance in ecosystems of California, J. Liu and others (2011) 

estimated that California’s natural ecosystems were generally 

carbon neutral from 1951 to 2000 (with an average NBP of 

−0.3 TgC/yr), even when the balancing effects of carbon 

dioxide fertilization and climate‐induced increases in the 

length of the growing season were considered. In Oregon and 

the rest of the Pacific Northwest, the net ecosystem production 

(NEP) for forests, agricultural lands, woodlands, grasslands, 

and shrublands was estimated using forest‐inventory data, 

land-use maps, and a process-based model (D.P. Turner, Ritts, 

and others, 2011). The study concluded that a decline in forest 

clearcutting (the result of changes in forest-management 

policies since the 1990s) has had a profound effect on carbon 

storage and sequestration, resulting in a switch from a carbon 

source to a carbon sink around 1990. Some recent regional 

studies of carbon stocks and fluxes are listed in tables 1.1 and 

1.2 of chapter 1 of this report. 

As noted in chapter 1, conventional carbon and GHG 

terminology (such as Chapin and others, 2006) was followed 

in the assessment. Two concepts are most relevant here. The 

first is the net ecosystem carbon balance (NECB), which is 

defined as the net rate of carbon-storage change in ecosystems. 

The second is the NEP, which is defined as the imbalance 

between the gross primary production and ecosystem 

respiration, or the difference between the net primary 

production and heterotrophic respiration. For this assessment, 

the NECB was calculated as the carbon storage change of an 

ecosystem over a period of time. For example, the NECB for 

year t was calculated as the carbon storage in year t-1 minus 

the carbon storage in year t. Therefore, a negative value for the 

NECB indicates a carbon accumulation or sequestration in an 

ecosystem and a positive value indicates a loss of carbon from 

the ecosystem, which is the opposite suggested by Chapin and 

others (2006). The negative value indicates a carbon loss in 

the atmosphere because of carbon sequestration in ecosystems. 

This convention is consistent with the Great Plains assessment 

report (Zhu and others, 2011).

5.3. Input Data and Methods

5.3.1. Input Data for Baseline 

Simulation Modeling

A variety of input data were needed to model the 

biogeochemical processes related to carbon stocks, carbon 

fluxes, and GHG fluxes in the Western United States, 

including data about climate, LULC, soils, elevation, forest 

types, biomass, land and forest management, and natural 

disturbances. The treatment of land-management activities 

and natural disturbances in ecosystems is discussed in detail 

in chapter 4 of this report. Table 5.1 lists the input data 

layers that were used to provide the baseline information for 

the assessment.

Each of the input datasets was obtained from the 

indicated data source in table 5.1 and converted to standard 

spatial and temporal resolutions, projection, and data format. 

Some examples of input data layers (maps) are provided in 

figure 5.1. 
Chapter 5 47

A. Soil organic carbon, 2005 B. Total annual precipitation, 2005

C. Land use and land cover, 2005

EXPLANATION

<125

126 to 250

251 to 500

501 to 1,000

1,001 to 1,500

1,501 to 2,000

>2,000

High: 21.5688

Low: 0

Precipitation,

 in millimeters

Soil organic carbon,

 in kilograms

 of carbon per 

 square meter 

Figure 5–2.

Level II 

ecoregion 

boundary

Water

Developed

Mechanically 

 disturbed 

 national forest

Mechanically 

 disturbed other

 public land

Mechanically 

 disturbed 

 private land

Mining

Barren

Deciduous forest

Evergreen forest

Mixed forest

Grassland

Shrubland

Hay/pasture

Woody wetlands

 Herbaceous 

 wetlands

Perennial ice/snow

Barley

Beans

Corn grain

Corn silage

Cotton

Flaxseed

Lentils

Sorghum silage

Oats

Peanuts

Peas

Potatoes

Rice

Rye

Safflower

Sorghum

Soybeans

Sugarbeets

Sunflowers

Tomatoes

Wheat durum

Wheat spring

Wheat winter

Land use and land cover

N

0 200 400 MILES

0 200 400 KILOMETERS

Figure 5.1. Examples of maps showing input data for 

the Western United States. A, Soil organic carbon (SOC) 

for the top 0 to 5 centimeters of the soil layer; the data 

were derived from the Soil Survey Geographic (SSURGO) 

Database (USDA Natural Resources Conservation Service, 

2009). B, Total annual precipitation in 2005 (PRISM Climate Group, 

2012). C, Land cover in 2005 from chapter 2 of this report with the 

agricultural land class downscaled to the crop types (chapter 4 of 

this report). See figure 1.1 in chapter 1 for ecoregion names.
48 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Table 5.1. Input data used in the baseline-data model runs for the assessment. 

[Most of the input data have a 250-m spatial resolution and variable temporal characteristics, although most data cover the first decade of the 21st century. Db 

0.33 bar H2O, the oven-dry weight of the less than 2 mm soil material per unit volume of soil at a water tension of 1/3 bar (as used in the SSURGO database). 

EDCM, Erosion-Deposition-Carbon Model; FIA, USDA Forest Service’s Forest Inventory & Analysis; FIPS, Federal Information Processing Standard; K factor, 

an erodibility factor that quantifies the susceptibility of soil particles to detachment by water; LP DAAC, Land Processes Active Archive Center; LULC, land use 

and land cover; mm, millimeter; MODIS, Moderate Resolution Imaging Spectrometer on board NASA’s Terra satellite; NASA, National Aeronautics and Space 

Administration; NPP, net primary productivity; NRCS, USDA’s Natural Resources Conservation Service; NTSG, Numerical Terradynamic Simulation Group; 

PRISM, parameter-elevation regressions on independent slopes model; RPA, U.S. Forest Service Forest and Rangeland Renewable Resources Planning Act of 

1974; SSURGO, Soil Survey Geographic Database (NRCS); TPO, timber product output; USDA, U.S. Department of Agriculture]

Data category Data type Data source

Model

Spreadsheet EDCM CENTURY

LULC LULC classes Chapter 2 of this report X X

Climate Monthly minimum and maximum 

temperature, monthly total 

precipitation

PRISM Climate Group (2012) X X

Soils Total sand SSURGO (USDA NRCS, 2009) X X

Total clay X X

Total silt X X

Soil thickness X

Soil organic carbon X X X

Available water capacity X

Db 0.33 bar H2O X

K factor

Forests Biomass Geodata (USDA Forest Service, 

2012c)

X

Stand age Chapter 2 of this report X X X

FIA species growth curves, 

height, diameter, and biomass 

measurements

USDA FIA (USDA Forest Service, 

2012b)

X

Timber product output USDA FIA RPA (USDA Forest 

Service, 2012b); USDA RPA 

TPO (USDA Forest Service, 

2011)

X

Crops Derived crop type Schmidt and others (2011); 

Chapter 4 of this report

X X X

USDA crop yield table USDA National Agricultural 

Statistics Service (2011)

X X

USDA fertilization table USDA Economic Research Service 

(2011b)

USDA manure table USDA Economic Research Service 

(2011a)

CTIC tillage table Conservation Technology 

Information Center (2011); 

USDA Economic Research 

Service (2011a)

Management Derived manure Schmidt and others (2011); 

Chapter 4 of this report

X X X

Derived tillage Schmidt and others (2011); 

Chapter 4 of this report

X X X

Derived fertilizer Schmidt and others (2011); 

Chapter 4 of this report

X X X

Irrigation USGS (2010) X X X
Chapter 5 49

Data category Data type Data source

Model

Spreadsheet EDCM CENTURY

Elevation Elevation USGS (2012b)

Remote sensing NPP M. Zhao and others (2005) X X

Wildland fires Fire size, severity, combustion 

emissions

Eidenshink and others (2007); 

Chapter 3 of this report

X X

Reference 

information 

State and county FIPS codes U.S. Census Bureau (2012) X X X

Initial conditions Forest litter biomass Chapter 5 of this report X X

Aboveground live biomass Chapter 5 of this report X X

Belowground live biomass Chapter 5 of this report X X

Deadwood biomass Chapter 5 of this report X X

Standing wood biomass Chapter 5 of this report X X

CENTURY ...

Figure 5–1.

PRISM, GCMs

Land cover

Drought

Irrigation

LAI

NDVI

Fire

Insects

and

diseases

Storms

C, N, H2

O cycles

Stocks and fluxes

N2

O and CH4 fluxes

Fire C emissions

Lateral C movement

Grain yield

Timber harvest

Biological processes (FIA, FLUXNET, NEON)

Management (USDA NRI)

Data

assimilation

(SCE, R–FME, 

PEST, EnKF)

Rem

ote se

nsing

Climate

Ecosyste

m dy

namics

Ground observations

Spreadsheet

EDCM

5.3.2. The General Ensemble 

Biogeochemical Modeling System 

The General Ensemble Biogeochemical 

Modeling System (GEMS) (S. Liu and others, 2012) 

was developed to integrate the well-established 

biogeochemical models for ecosystems with various 

spatial databases in order to simulate biogeochemical 

cycles over large areas. Figure 5.2 shows the overall 

structure of the GEMS. Some of the key features of 

the GEMS are described below.

5.3.3. Using the Biogeochemical Model 

Ensemble to Address Model Biases

All models are imperfect and have simulation 

biases and errors. As an example, comparison studies 

by the North American Carbon Program of major 

biogeochemical models yielded variable estimates of 

carbon stocks and fluxes (Schwalm and others, 2010; 

Huntzinger and others, 2012). To minimize biases 

and errors in the individual models and to quantify 

the uncertainty of the model outputs, multiple 

site scale biogeochemical models were encapsulated 

into the GEMS and used simultaneously to simulate 

ecosystem dynamics over time and space.

Figure 5.2. Diagram of the General Ensemble Modeling System (GEMS) 

showing (1) the inputs (climate, remote sensing, and ground observations) 

and outputs (ecosystem dynamics), (2) the underlying biogeochemical models

(spreadsheet, EDCM, and CENTURY), and (3) the data assimilation procedures. 

Abbreviations are as follows: C, carbon; CH4

, methane; EDCM, ErosionDeposition-Carbon Model; EnKF, Ensemble Kalman Filter; FIA, U.S. Forest 

Service’s Forest Inventory & Analysis Program; FLUXNET, flux network; GCM, 

General Circulation Model; H2

O, water; LAI, leaf area index; N, nitrogen; N2O, 

nitrous oxide; NDVI, Normalized Difference Vegetation Index; NEON, National 

Ecological Observatory Network; NRI, Natural Resource Conservation 

Service’s National Resources Inventory; PEST, model independent parameter 

estimation application; PRISM, parameter-elevation regressions on 

independent slopes model; R–FME, R Flexible Modeling Environment; SCE, 

Shuffled Complex Evolution; USDA, U.S. Department of Agriculture.

Table 5.1. Input data used in the baseline-data model runs for the assessment.—Continued 

[Most of the input data have a 250-m spatial resolution and variable temporal characteristics, although most data cover the first decade of the 21st century. Db 

0.33 bar H2O, the oven-dry weight of the less than 2 mm soil material per unit volume of soil at a water tension of 1/3 bar (as used in the SSURGO database). 

EDCM, Erosion-Deposition-Carbon Model; FIA, USDA Forest Service’s Forest Inventory & Analysis; FIPS, Federal Information Processing Standard; K factor, 

an erodibility factor that quantifies the susceptibility of soil particles to detachment by water; LP DAAC, Land Processes Active Archive Center; LULC, land use 

and land cover; mm, millimeter; MODIS, Moderate Resolution Imaging Spectrometer on board NASA’s Terra satellite; NASA, National Aeronautics and Space 

Administration; NPP, net primary productivity; NRCS, USDA’s Natural Resources Conservation Service; NTSG, Numerical Terradynamic Simulation Group; 

PRISM, parameter-elevation regressions on independent slopes model; RPA, U.S. Forest Service Forest and Rangeland Renewable Resources Planning Act of 

1974; SSURGO, Soil Survey Geographic Database (NRCS); TPO, timber product output; USDA, U.S. Department of Agriculture]
50 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

 For this assessment, the CENTURY model (Parton and 

others, 1987; Parton and others, 1994), the ErosionDeposition-Carbon Model (EDCM, S. Liu and others, 2003), 

and a spreadsheet model were incorporated into the GEMS 

to simulate dynamics of carbon stocks, carbon fluxes, and 

fluxes of the GHG. These three models were already linked 

to the GEMS for the assessment of the Great Plains (Zhu and 

others, 2011). 

Two modifications were made to the CENTURY model 

for the assessment. First, the model’s data input and output 

interface was modified and linked to the GEMS system by 

using a static FORTRAN library with shared memory to 

increase the efficiency of the computations. The change 

did not affect the format of the input and output data for 

the model. Second, the regional-level NPP and grain-yield 

calibration process (see section entitled “Calibration of the 

Model,” below) were modified.

Improved modeling of water availability is critical for 

the predictions of ecosystem productivity and soil organic 

matter decay because both processes are strongly controlled 

by soil moisture. The EDCM, which was modified from the 

CENTURY model, used up to 10 soil layers in a soil profile, 

compared to the CENTURY model, which used one layer for 

SOC simulations. In the EDCM, the thickness of the surface 

soil layer was fixed at the plowing depth of either 20 or 

30 cm, whereas the thicknesses of other layers were flexible. 

The thickness and SOC dynamics of each of the layers were 

then simulated by modeling the interactions of erosion or 

deposition, forest-litter input, decomposition, and leaching 

(Liu and others, 2000; S. Liu and others, 2003). The five SOC 

pools (metabolic, structural, fast, slow, and passive) in each 

soil layer were used in the EDCM to characterize the quantity 

and quality of the SOC, which was similar to the structure 

for the surface soil depth in the CENTURY model (Parton 

and others, 1987; Metherell and others, 1993; Parton and 

others, 1993). 

The spreadsheet model (described in Zhu and others, 

2010) was developed for this assessment and is based on a 

simple accounting approach. For SOC, 10 soil layers from the 

Soil Survey Geographic Database (SSURGO; USDA Natural 

Resources Conservation Service, 2009) (Sundquist and others, 

2009) were used to represent the SOC at each location or 

pixel. Simplicity in the spreadsheet model was maintained by 

keeping the SOC unchanged after the model was initialized. 

For biomass carbon, the grassland/shrubland and agricultural 

biomass pools were held as constants, whereas the forests 

biomass pools (including aboveground and belowground 

live biomass, standing wood, deadwood, forest litter, and 

other carbon pools) were assigned as a function of forest 

types (evergreen, broadleaf, and mixed forest) and forest age 

(both from the LULC modeling described in chapter 2 of 

this report), as well as the forest age-carbon stock relation. 

The forest age-carbon stock relation is a set of growth curves 

specific for forest types (such as softwood, hardwood, and 

mixed) and FIA units. Derived from FIA inventory data, the 

relation describes quantitatively the amount of biomass carbon 

as a function of average forest age. Each forest type has a 

distinct forest age-carbon stock relation unless the number 

of FIA plots was not large enough to derive such a relation. 

In this case, a representative regional forest age-carbon stock 

relation was used. 

On the basis of the forest age-carbon stock relation 

(growth curve) discussed above and the LULC maps, the 

effects of either forest aging or clearcutting were quantified 

in the spreadsheet model. The spreadsheet model, however, 

was not intended to quantify the effects of climate variability 

and change or of carbon-dioxide fertilization on carbon. The 

algorithms for estimating wildland-fire emissions were not 

implemented in the spreadsheet model for this assessment. 

Following a recommendation by the Intergovernmental 

Panel on Climate Change, the spreadsheet model estimated 

methane and nitrous-oxide fluxes for different LULC classes 

using emission factors that were compiled from an extensive 

review of the literature (Mosier and others, 1997; Kessavalou 

and others, 1998; Gleason and others, 2007; Sainju, 2008; 

Liebig and others, 2010). Emission factors were compiled 

and synthesized by ecosystem type and ecoregion for 

this assessment. 

Although the biogeochemical models in the GEMS have 

different output variables, their common output variables 

include gross and net primary productivity (GPP, NPP), 

autotrophic and heterotrophic respiration, grain production, 

and carbon stock estimates over time in vegetation and soil 

pools for terrestrial ecosystems. 

5.3.4. Model Initializations

The following soil properties were initialized on the basis 

of data from the SSURGO database (USDA Natural Resources 

Conservation Service, 2009): soil thickness, organic carbon 

storage, texture (fractions of sand, silt, and clay), bulk density, 

and drainage. Forest biomass carbon pools (aboveground and 

belowground live biomass, or dead biomass consisting of 

forest litter and dead, woody debris) were initialized using the 

initial forest-age map (derived from FIA data; USDA Forest 

Service, 2012b), forest type (evergreen, broadleaf, and mixed), 

and the forest age-carbon stock relation. For consistency and 

to avoid potential errors, the initialization of the SOC and 

biomass was done using the spreadsheet model, and its outputs 

for 1992 (the first year of the model simulations) were then 

read directly by the CENTURY model and the EDCM as their 

initial conditions. The years from 1992 to 2000 were used as a 

period of calibrations to achieve relative stabilization (that is, 

model spin-up) for the EDCM and CENTURY simulations. 
Chapter 5 51

5.3.5. Model Calibration 

Models usually contain parameters that (1) cannot be 

determined by using local field measurements or (2) can 

be measured locally but cannot be used regionally because 

of the effects of the scale of the measurements. Models are 

calibrated by adjusting such model parameters to optimize 

the agreement between observation and simulation. The 

observed data available for calibrating carbon-flux model 

runs from 2001 to 2005 included (1) county-based grainyield-survey data by crop type, published by the USDA 

(USDA, National Agricultural Statistics Service, 2011); 

and (2) 250-m resolution NPP data from the MODIS for 

other LULC types such as forests and grasslands (Zhao and 

others, 2005). The MODIS NPP was found to lack consistent 

performance for calibrating crop production on agricultural 

lands and, therefore, crop yields from the USDA were used. 

An automated calibration was implemented for the EDCM 

using the Shuffled Complex Evolution (SCE) (Duan and 

others, 1992) and an R software package, Flexible Modeling 

Environment (R–FME) (Soetaert and Petzoldt, 2010; Wu and 

Liu, 2012). On the other hand, manual calibration was used 

for the CENTURY model. The potential maximum production 

parameter (PRDX) was adjusted by comparing the modeled 

grain yield and the forest NPP with the USDA’s county-level 

statistics of grain yield and county-level, MODIS-derived NPP 

from 2001 to 2005. 

5.3.6. Model Validation 

Maps, binned scatterplots, and correlation plots were 

generated for different ecosystems in each ecoregion of the 

Western United States in order to compare the simulated 

results of the three models run within the GEMS with 

observational data (for example, the USDA FIA biomass 

estimate, an estimate from the National Biomass and 

Carbon Dataset 2000 (Kellndorfer and others, 2004), the 

MODIS‐derived NPP (Zhao and others, 2005), and the USDA 

grain yield (USDA, National Agricultural Statistics Service, 

2011) for 2006, 2008, and 2010. Simple linear-regression 

modeling, the coefficient of determination, and the root mean 

square error (RMSE) between the observed and modeled data 

were calculated to evaluate the performance of the models. 

Some of the results of the validation are shown in figure 5.3

and table 5.2.

5.3.7. Model Run Setup

The simulation models were run for every year from 1992 

to 2050, with the years 1992 to 2000 used as model spin-up, 

2001 to 2005 used as the baseline period (this chapter), and 

2006 to 2050 as the projection period (chapter 9). A total 

of three GEMS simulations (by the spreadsheet model, 

CENTURY model, and the EDCM) were used to support the 

assessment of carbon dynamics during the baseline period. As 

noted previously, the purpose of using multiple models was 

to minimize the potential biases and errors that were inherent 

in the models and to provide an opportunity to quantify 

structure-related uncertainties in the models.

Before the full-resolution or wall-to-wall simulations 

were run to produce spatial data products for this assessment, 

a systematic sampling approach was used first to improve 

the performance of the model simulations. Both the EDCM 

and the CENTURY model were run with a 10×10 systematic 

subsample factor to ensure adequate time for processing, 

generating statistics, and calibrating the estimates. Therefore, 

for these two models, the results reported here were based 

on a systematic sample of 1 percent of the total pixels. A 

comparison of the sampling results with the full-resolution 

simulations indicated that the sampling approach provided the 

same regional statistics as the full-resolution simulation.

Table 5.2. Comparison of the three different biogeochemical models in the General 

Ensemble Modeling System (GEMS) based on aggregated results at the county level, 

for 2006. 

[MODIS NPP, net primary productivity derived from the Moderate Resolution Imaging 

Spectroradiometer; NBCD, National Biomass and Carbon Dataset (Kellndorfer and others, 2004); 

USDA FS, U.S. Forest Service; R2, coefficient of determination; RMSE, root mean squared error; 

USDA U.S. Department of Agriculture].

Observation Model Land use or land cover RMSE R2

NBCD live biomass Spreadsheet Forests 7.312 0.61

USDA FS live biomass Spreadsheet Forests 4.376 0.90

MODIS NPP CENTURY Forests 0.216 0.95

MODIS NPP EDCM Forests 0.167 0.98

MODIS NPP CENTURY Grasslands/shrublands 0.100 0.74

MODIS NPP EDCM Grasslands/shrublands 0.038 0.96

USDA grain yield CENTURY Winter wheat 0.003 0.97

USDA grain yield EDCM Winter wheat 0.005 0.94
52 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

A. MODIS, 2006 B. CENTURY, MIROC 3.2–medres, and scenario A1B, 2006

C. EDCM, MIROC 3.2– medres, and scenario A1B, 2006

EXPLANATION

0 to 0.12

0.13 to 0.25

0.26 to 0.49

0.50 to 1.00

1.01 to 1.41

1.42 to 2.00

2.01 to 2.28

Net primary production, 

 in kilograms of carbon

 per square meter

Figure 5–3.

Level II ecoregion boundary

N

0 200 400 MILES

0 200 400 KILOMETERS

Figure 5.3. Maps showing a comparison of net primary 

productivity (NPP) in the Western United States for 2006 

estimated by three different methods and tools . A, Data from 

the Moderate Resolution Imaging Spectroradiometer (MODIS). 

B, The CENTURY model run under IPCC–SRES scenario A1B and 

using the MIROC 3.2-medres general circulation model. C, The 

Erosion-Deposition-Carbon Model (EDCM) run under IPCC–SRES 

scenario A1B and using the MIROC 3.2-medres general circulation 

model. IPCC–SRES, Intergovernmental Panel on Climate Change 

Special Report on Emissions Scenarios (Nakicenovic and others, 

2000). MIROC 3.2-medres, Model for Interdisciplinary Research on 

Climate version 3.2, medium resolution. See figure 1.1 in chapter 1

for ecoregion names.
Chapter 5 53

5.4. Results and Discussion

5.4.1. Carbon Stocks in 2005 

The magnitude and spatial pattern of the carbon stock 

estimated from 2001 to 2005 remained relatively stable, 

therefore the estimates for 2005 are presented here. The 

map in figure 5.4A shows the spatial distribution of the 

mean amount of carbon stored (based on the average of 

three carbon-stock maps from the three models) in all of the 

ecosystems of the Western United States in 2005, and the 

standard deviation of the results, which indicates a measure 

of uncertainty. The total carbon stored included carbon in 

live biomass, SOC in the top 20 cm of the soil layer, and 

dead biomass. The map indicates that forests in the Marine 

West Coast Forest and Western Cordillera ecoregions stored 

the most carbon, whereas there was relatively less carbon 

stored in the grasslands/shrublands-dominated Cold Deserts 

and Warm Deserts ecoregions and in the mixed agricultural 

lands, grasslands/shrublands, and forests of the Mediterranean 

California ecoregion. The standard deviation of the estimates 

of the three models was generally higher in the coastal 

forests and in the Cascades, which is likely the result of the 

high biomass levels and logging rates. The uncertainties in 

the carbon stock were lower in the interior forests, where 

the biomass levels and logging rates were lower. The 

uncertainties were also lower in landscapes dominated by 

grasslands/shrublands.

A B

EXPLANATION

Average carbon storage in 2005, in 

 kilograms of carbon per square meter

EXPLANATION

Standard deviation of the mean carbon storage

 for 2005, in kilograms of carbon per square meter

0 200 400 MILES

0 200 400 KILOMETERS

≤1

1.1 to 2.0

2.1 to 4.0

≤2.0

2.1 to 10.0

10.1 to 20.0

20.1 to 30.0

30.1 to 50.0

50.1 to 100.0

4.1 to 8.0

8.1 to 10.0

>10.0

Level II ecoregion boundary Level II ecoregion boundary

Figure 5–4.

N

Figure 5.4. Maps showing the mean amount of carbon stored and the standard deviation for 2005. A, The estimated 

mean amount of carbon stored in 2005, which was derived by averaging the results from the three General Ensemble 

Modeling System (GEMS) models (spreadsheet, CENTURY, and EDCM). B, The standard deviation of the three modeling 

results around the mean. EDCM, Erosion-Deposition-Carbon Model. See figure 1.1 in chapter 1 for ecoregion names.
54 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Annual maps of estimated carbon stocks by the terrestrial 

ecosystems and ecoregions from 2001 to 2005 were produced 

using the three models, as previously described. At the 

regional scale, temporal variability remained relatively small 

between the years. Table 5.3 gives the range (minimum to 

maximum) of the estimated amounts of carbon stored as 

simulated by the three models (spreadsheet, EDCM, and 

CENTURY) for 2005, the last year of the baseline conditions. 

During 2005, the average total amount of carbon stored in the 

entire Western United States was estimated to be 13,920 TgC 

(ranging from 12,418 to 15,461 TgC). The estimates for 

the Western United States are about 8 percent lower than a 

previously published estimate of 15,095 TgC for all major 

carbon pools in the Pacific Coast and Rocky Mountain 

regions in 2005 (J.E. Smith and Heath, 2008). Among all the 

ecoregions, the Western Cordillera stored the most carbon at 

over 8,162 TgC (59 percent), followed by the Cold Deserts 

(19 percent), the Marine West Coast Forest (11 percent), 

Mediterranean California (6 percent), and the Warm Deserts 

(5 percent). Live biomass, SOC, and dead biomass accounted 

for 39.0 percent, 38.3 percent, and 22.7 percent, respectively, 

of the total carbon stored in the Western United States. 

In terms of ecosystems, forests, grasslands/shrublands, 

and agricultural lands stored 69 percent, 25 percent, and 

4.3 percent, respectively, of the total carbon. Among the 

different ecosystems, forests stored the most carbon in 

the Western Cordillera, Marine West Coast Forest, and 

Mediterranean California ecoregions; grasslands/shrublands 

stored the most carbon in the Cold Deserts and Warm 

Deserts ecoregions.

Using table 5.3, the carbon density (that is, the 

amount of carbon stored per unit of area) could be derived 

by ecosystem and ecoregion. Forests stored the most 

carbon in the Marine West Coast Forest (21.9 kgC/m2), 

followed by Mediterranean California (14.9 kgC/m2), 

the Western Cordillera (13.0 kgC/m2), the Cold Deserts 

(6.7 kgC/m2), and the Warm Deserts (5.2 kgC/m2). The 

ecoregions that had highest and lowest carbon densities in 

grasslands/shrublands were the Marine West Coast Forest at 

6.6 kgC/m2 and the Warm Deserts at 1.5 kgC/m2, respectively. 

Although agricultural lands covered only a small percentage 

of the Western United States, most of this ecosystem stored 

more carbon than grasslands/shrublands. For example, in 

the Western Cordillera ecoregion, the carbon density in the 

top 20 cm of soil for forests, grasslands/shrublands, and 

agricultural lands was 3.3, 2.4, and 3.9 kgC/m2, respectively. 

Further results for each ecoregion are provided below.

5.4.1.1. Western Cordillera

The Western Cordillera is the second largest ecoregion 

in the Western United States. In 2005, the average total 

amount of carbon stored in this ecoregion was estimated to 

be 8,163 TgC (ranging from 7,488 to 8,793 TgC), of which 

an average of 43 percent was in live biomass, 32 percent in 

soil, and 25 percent in dead biomass. Among the different 

ecosystems, forests occupied 63 percent of the total land 

area and stored an average of 87 percent of the total carbon 

stock (7,123 TgC or 13.0 kgC/m2). Grasslands/shrublands 

occupied 32 percent of the total land area but only stored an 

average of 11 percent of the total carbon stock (923 TgC, or 

3.3 kgC/m2). Agricultural lands occupied a small area of the 

ecoregion (2 percent) and stored only an average of 1 percent 

of the total carbon stock (72 TgC, or 4.3 kgC/m2). 

5.4.1.2. Marine West Coast Forest

In 2005, the average total amount of carbon stored in 

the Marine West Coast Forest was estimated to be 1,534 TgC 

(ranging from 1,447 to 1,646 TgC), of which an average 

of 48 percent was in live biomass, 33 percent in soil, and 

19 percent in dead biomass. Forests stored the most carbon 

in the ecoregion (an average of 1,415 TgC, 92 percent of the 

total), followed by agricultural lands (an average of 67 TgC, 

4 percent of the total) and grasslands/shrublands (an average 

of 30 TgC, 2 percent of the total). This small coastal ecoregion 

had the highest percentage of its total land area covered by 

forests (68 percent) and those forests had the highest average 

carbon density (21.9 kgC/m2) of any forests in the five 

ecoregions. The carbon densities in grasslands/shrublands 

(6.6 kgC/m2) and agricultural lands (6.4 kgC/m2) were also 

higher than the carbon densities in the same ecosystems in the 

other ecoregions. 

5.4.1.3. Cold Deserts

The Cold Deserts ecoregion is the largest in the Western 

United States and was dominated by the grasslands/shrublands 

ecosystem (76 percent of the total land area). In 2005, the 

average total amount of carbon stored in this ecoregion was 

estimated to be 2,651 TgC (ranging from 2,267 to 3,124 TgC), 

of which an average of 23 percent was in live biomass, 

58 percent in soil, and 18 percent in dead biomass. The 

grasslands/shrublands stored the most carbon in the ecoregion 

(an average of 1,672 TgC, 63 percent of the total), followed 

by forests (an average of 647 TgC, 23 percent of the total) 

and agricultural lands (an average of 282 TgC, 18 percent of 

the total). The average total carbon density in this ecoregion 

was 2.5 kgC/m2, which was lower than that of the Western 

Cordillera (9.4 kgC/m2) and the Marine West Coast Forest 

(16.1 kgC/m2).

5.4.1.4. Warm Deserts

The vegetation in the extremely arid Warm Deserts 

ecoregion was also dominated by the grasslands/shrublands 

ecosystem (87 percent of total land area). In 2005, the average 

total carbon stored in this ecoregion was estimated to be only 

700 TgC (ranging from 525 to 921 TgC), of which 26 percent 
Chapter 5 55

Table 5.3. Minimum and maximum estimates of carbon stored in the Western United States in 2005, by carbon pool for each ecoregion 

and ecosystem. 

[Only soil organic carbon (SOC) in the top 20 cm of the soil layer was calculated. km2, square kilometers; max, maximum; min, minimum; TgC, teragrams of 

carbon or 1012 grams of carbon].

Ecoregion Ecosystem Area

(km2)

Live biomass

(TgC)

Soil

(TgC)

Dead biomass 

(TgC)

Total

(TgC)

Min Max Min Max Min Max Min Max

Western 

Cordillera

Forests 546,533 3,304.6 3,689.4 1,599.5 1,887.7 1,398.0 2,348.2 6,648.2 7,557.6

Grasslands/shrublands 277,874 71.5 148.6 629.1 718.9 0.0 222.5 745.8 1,090.0

Agricultural lands 16,722 0.1 2.4 64.4 65.3 0.0 8.1 67.7 72.6

Wetlands 3,656 4.7 5.2 13.8 18.4 2.4 5.7 23.2 28.8

Other lands 27,469 0.2 0.4 1.9 43.9 0.0 0.7 2.9 44.1

Total 872,253 3,381.1 3,846.0 2,308.7 2,734.2 1,400.4 2,585.2 7,487.7 8,793.1

Marine West 

Coast Forest

Forests 64,601 696.0 829.8 398.7 416.4 235.8 336.2 1,347.6 1,510.5

Grasslands/shrublands 4,542 1.7 4.0 19.1 23.4 0.0 6.0 20.7 32.7

Agricultural lands 10,418 0.1 1.5 61.1 64.6 0.0 6.0 65.9 67.2

Wetlands 588 2.3 2.8 3.0 3.8 0.4 1.0 5.6 7.1

Other lands 15,262 0.0 1.0 4.0 28.4 0.0 2.2 7.0 28.4

Total 95,411 700.1 839.0 485.8 536.6 236.2 351.5 1,446.9 1,645.9

Cold Deserts Forests 97,180 269.4 293.6 179.6 213.5 131.7 222.2 638.8 685.1

Grasslands/shrublands 804,658 275.1 371.8 960.1 1,191.0 0.0 519.6 1,370.9 2,066.1

Agricultural lands 81,191 0.1 12.9 222.0 254.3 0.0 41.9 234.9 296.3

Wetlands 4,635 2.6 3.7 14.9 20.0 1.9 5.3 21.0 27.9

Other lands 68,392 0.0 0.3 2.7 49.0 0.0 0.3 3.0 49.0

Total 1,056,055 547.2 682.4 1,379.3 1,727.9 133.6 789.4 2,268.6 3,124.4

Warm Deserts Forests 8,084 20.1 22.7 7.3 10.4 8.7 19.8 39.9 49.8

Grasslands/shrublands 403,390 120.4 193.5 300.3 418.1 0.0 204.1 470.7 815.7

Agricultural lands 11,334 0.0 2.0 10.7 25.4 0.0 8.6 12.6 35.5

Wetlands 326 0.2 0.3 0.3 0.5 0.0 0.6 0.5 1.1

Other lands 42,150 0.0 0.2 0.8 18.4 0.0 0.2 0.9 18.9

Total 465,285 140.6 218.6 319.4 472.8 8.8 233.3 524.6 921.0

Mediterranean 

California

Forests 29,945 250.9 296.0 56.9 85.7 88.3 119.0 424.9 469.8

Grasslands/shrublands 74,294 28.1 37.2 125.9 179.9 0.0 62.9 154.0 279.8

Agricultural lands 41,046 0.0 7.4 94.2 146.6 0 35.1 101.6 188.4

Wetlands 910 0.5 0.9 4.4 5.0 0.4 1.5 5.8 7.0

Other lands 23,259 0.0 0.4 3.9 31.2 0.0 0.3 4.3 31.2

Total 169,455 279.5 341.8 285.3 448.4 88.7 218.8 690.5 976.3

Western United 

States (total)

Forests 746,343 4,541.0 5,131.4 2,242.0 2,613.8 1,862.6 3,045.5 9,099.4 10,272.8

Grasslands/shrublands 1,564,759 496.7 755.0 2,034.4 2,531.2 0.0 1,015.1 2,762.0 4,284.2

Agricultural lands 160,711 0.3 26.1 452.4 556.2 0.0 99.7 482.7 660.0

Wetlands 10,114 10.2 12.8 36.3 47.7 5.1 14.1 56.1 71.9

Other lands 176,532 0.2 2.4 13.4 171.0 0.0 3.8 18.1 171.7

Total 2,658,459 5,048.5 5,927.8 4,778.5 5,919.9 1,867.7 4,178.2 12,418.3 15,460.6
56 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

was in live biomass, 56 percent in soil, and 18 percent in dead 

biomass. The grasslands/shrublands stored the most carbon 

in the ecoregion (623 TgC, an average of 89 percent of total), 

followed by forests (42 TgC, an average of 6 percent of total) 

and agricultural lands (24 TgC, an average of 3 percent of 

total). The carbon densities were the lowest among all of the 

ecoregions (5.1, 1.5, and 2.1 kgC/m2 for forests, grasslands/

shrublands, and agricultural lands, respectively).

5.4.1.5. Mediterranean California

In 2005, the Mediterranean California ecoregion 

stored an estimated average total carbon stock of 873 TgC 

(ranging from 691 to 976 TgC), of which 34 percent was in 

live biomass, 45 percent was in soil, and 20 percent was in 

dead biomass. Forests stored half of the total carbon stock 

(448 TgC, an average of 51 percent of total), followed by 

grasslands/shrublands (246 TgC, an average of 28 percent 

of total) and agricultural lands (157 TgC, an average of 

18 percent of total). The percentage of agricultural land in 

this ecoregion was high compared to the other ecoregions in 

the Western United States. The estimated carbon densities 

were approximately 15.0, 3.3, and 3.8 kgC/m2 for forests, 

grasslands/shrublands, and agricultural lands, respectively).

5.4.1.6. Discussion of Baseline Carbon Storage 

For the five western ecoregions in 2005, the estimated 

average amount of carbon stored in 74.6 megahectares 

(Mha) of forest ecosystems, as mapped and modeled using 

the assessment methodology, was approximately 9,675 TgC 

(ranging from 9,099 to 10,273 TgC), distributed in live 

biomass (4,674 TgC, ranging from 4,541 to 5,131 TgC), the 

top 20 cm of the soil (SOC; 2,503 TgC, ranging from 2,242 

to 2,614 TgC), and dead biomass (2,498 TgC, ranging from 

1,863 to 3,046 TgC). The average per-unit-of-area forest 

carbon stock density estimates were derived from the total 

forest carbon stock and total forest area estimates and ranged 

from 12.2 to 13.8 kgC/m2 with a mean of 13.0 kgC/m2. As a 

comparison, a separate analysis using the USFS FIA carbon 

stock and forest area estimates (Brad Smith, USDA Forest 

Service, unpub. data, 2010) suggested a total carbon stock of 

13,579 TgC in 93.6 Mha of forested area (or an average of 

14.5 kgC/m2) in the same five ecoregions. The differences 

in estimates of the total carbon stock and stock density 

between the two studies may be primarily attributed to (1) the 

different amount of area that was categorized as forest, which 

was derived on the basis of different forest definitions and 

mapping or modeling approaches (Nelson and Vissage, 2005; 

chapter 2 of this report) and (2) the fact that only carbon in 

the top 20 cm of the soil layer was modeled as SOC in this 

assessment, compared to the FIA SOC estimate, which was 

based on the top 1 m of the soil layer. 

5.4.2. Baseline Carbon Flux from 2001 to 2005 

The magnitude and spatial distribution of the mean net 

carbon fluxes across the Western United States are shown in 

figure 5.5, which indicates that the forested regions of the 

Pacific Coast gained the most carbon. The standard deviations 

were generally positively correlated with carbon gains, 

as expected. 

Table 5.4 gives the range (minimum and maximum) of 

the net carbon flux in the Western United States from 2001 to 

2005 by ecoregion, ecosystem, and carbon pool (live biomass, 

soil, and dead biomass). The estimated overall carbonsequestration rate ranged from −162.9 to −13.6 TgC/yr with 

an average of −86.6 TgC/yr, of which −27.6 TgC/yr may be 

attributed to live biomass accumulation and −58.9 TgC/yr to 

the dead biomass and soil carbon pools. The forest ecosystem 

was the largest carbon sink (62 percent of the total), followed 

by grasslands/shrublands (30 percent) and agricultural lands 

(7 percent). In forests, the major portion of sequestered carbon 

was allocated to live biomass. In grasslands/shrublands and 

agricultural lands, carbon accumulated mainly in soil and 

dead biomass. 

On a per-unit-of-area basis, the estimated average carbon 

net flux by forests, grasslands/shrublands, and agricultural 

lands was −72, −16, and −38 gC/m2/yr, respectively, from all 

carbon pools. Of these estimates, the soil carbon pool was 

responsible for –23, –10, and –26 gC/m2/yr, respectively for 

the ecosystems. The gain by soil in agricultural lands was 

higher than the gain by soil in grasslands/shrublands. Two 

possible reasons for the higher gain by soil in agricultural 

lands are increased biomass productivity due to genetically 

improved seeds and improved management practices 

including fertilizer and (or) irrigation, which may have lead 

to the overall higher yield of biomass than in the grasslands/

shrublands. Although both the Western Cordillera and the 

Cold Deserts ecoregions were considered to be carbon sinks 

from 2001 to 2005, the grasslands/shrublands in these two 

ecoregions were estimated to have lost carbon in the live 

biomass at an average estimated rate of 0.23 and 3.82 TgC/yr, 

respectively. Further descriptions of the net carbon fluxes for 

each ecoregion are provided below.

5.4.2.1. Western Cordillera 

From 2001 to 2005, the average estimated net carbon 

flux in the Western Cordillera was −50 TgC/yr (ranging from 

−86.1 to −19.1 TgC/yr), of which 48 percent was allocated 

to live biomass, 37 percent to soil, and 15 percent to dead 

biomass. Among the different ecosystems, forests sequestered 

an estimated average of −43 TgC/yr (85 percent of total), 

grasslands/shrublands sequestered an estimated average 

of −7 TgC/yr (14 percent of total), and agricultural lands 

sequestered an estimated average of –0.22 TgC/yr (less than 

1 percent of total).
Chapter 5 57

0 200 400 MILES

0 200 400 KILOMETERS

Figure 5–5.

A B

EXPLANATION

Total mean net carbon flux from 2001 to 2005, in 

 kilograms of carbon per square meter per year

EXPLANATION

Standard deviation of mean net carbon flux 

 from 2001 to 2005, in kilograms of carbon 

 per square meter per year

<1.0

1.1 to 2.0

2.1 to 4.0

–5.0 to –2.1

–2.0 to –0.6

–0.5 to 0.4

0.5 to 1.9

2.0 to 4.9 4.1 to 8.0

8.1 to 10.0

>10.0

Level II ecoregion boundary

Level II ecoregion boundary

N

Figure 5.5. Maps showing carbon flux in ecosystems of the 

Western United States. A, The mean net carbon flux derived from 

each of the three models (spreadsheet, CENTURY, and EDCM) and 

averaged for the baseline years, 2001 to 2005. B, The standard 

5.4.2.2. Marine West Coast Forest 

From 2001 to 2005, the estimated average net carbon flux 

in the Marine West Coast Forest was −3.8 TgC/yr (ranging 

from −6.9 to −1.0 TgC/yr). Forests sequestered an estimated 

average of −3.4 TgC/yr, followed by grasslands/shrublands at 

an estimated average of −0.5 TgC/yr. Agricultural lands lost 

carbon to the atmosphere at a low estimated average rate of 

0.04 TgC/yr, mostly from soil organic matter. 

5.4.2.3. Cold Deserts 

From 2001 to 2005, the estimated average net carbon 

flux in the Cold Deserts ecoregion was −12.3 TgC/yr 

(ranging from −32.6 to 5.7 TgC/yr). In forests, live biomass 

and soil sequestered carbon (estimated average rate of 

−3.72 TgC/yr) but dead biomass lost carbon (estimated 

average rate of 0.77 TgC/yr). Conversely, live biomass in 

grasslands/shrublands lost carbon (estimated average rate of 

3.82 TgC/yr) but soil and dead biomass sequestered carbon 

(estimated average rate of −11.1 TgC/yr). Agricultural 

lands sequestered carbon at an estimated average rate of 

−1.82 TgC/yr.

5.4.2.4. Warm Deserts

The Warm Deserts ecoregion was dominated by 

grasslands/shrublands (87 percent of total land area). From 

2001 to 2005, the estimated average net carbon flux was 

−6.8 TgC/yr (ranging from −18.6 to 2.9 TgC/yr); carbon 

sequestration occurred mainly in the grasslands/shrublands 

ecosystem. Agricultural lands also sequestered an estimated 

average of −0.84 TgC/yr while forests only gained carbon at 

−0.18 TgC/yr.

deviation of the three models for the baseline years. Negative 

values indicate net carbon gains and positive values indicate net 

carbon losses. EDCM, Erosion-Deposition-Carbon Model. See 

figure 1.1 in chapter 1 for ecoregion names.
58 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Table 5.4. Minimum and maximum estimates of net carbon flux in the Western United States from 2001 to 2005, by carbon pool for each 

ecoregion and ecosystem.

[Negative numbers indicate carbon sequestration; positive numbers indicate a loss of carbon to the atmosphere. Only soil organic carbon (SOC) in the top 20 cm of 

the soil layer was calculated. km2, square kilometers; max, maximum; min, minimum; TgC/yr, teragrams of carbon per year, or 1012 grams of carbon per year]

Ecoregion Ecosystem Area

(km2

)

Net carbon flux

(TgC/yr)

Live biomass Soil Dead biomass Total

Min Max Min Max Min Max Min Max

Western 

Cordillera

Forests 546,533 −29.7 −16.5 −21.7 0 −18.9 9.4 −70.3 −19.6

Grasslands/shrublands 277,874 −0.5 1.1 −7.7 0.2 −6.4 0 −14.6 0.2

Agricultural lands 16,722 0 0 −0.1 0.1 −0.2 0 −0.4 0

Wetlands 3,656 −0.1 0 −0.5 −0.1 −0.1 0 −0.7 −0.1

Other lands 27,469 0 0 −0.2 0.4 0 0 −0.2 0.4

Total 872,253 −30.3 −15.4 −30.2 0.6 −25.6 9.4 −86.1 −19.1

Marine West 

Coast Forest

Forests 64,601 −2.4 −0.4 −2.8 0.2 −1.7 0.3 −6 −1.3

Grasslands/shrublands 4,542 −0.2 0 −0.4 0 −0.1 0 −0.7 0

Agricultural lands 10,418 0 0 0.1 0.2 −0.1 0 0 0.1

Wetlands 588 0 0.1 −0.1 0 0 0 0 0

Other lands 15,262 0 0 −0.2 0.2 0 0.1 −0.2 0.2

Total 95,411 −2.6 −0.3 −3.4 0.5 −1.9 0.4 −6.9 −1

Cold Deserts Forests 97,180 −4.6 −1.5 −1.6 0.3 −1.6 3.5 −7.8 1.5

Grasslands/shrublands 804,658 0 5.5 −13.4 0.1 −10.9 0 −20.9 3.8

Agriculture 81,191 −0.2 0 −2.1 0.2 −1 0 −3 0

Wetlands 4,635 0 0 −0.5 0 −0.1 0 −0.6 0

Other lands 68,392 0 0 −0.3 0.4 0 0 −0.3 0.4

Total 1,056,055 −4.8 4.1 −17.8 1 −13.6 3.5 −32.6 5.7

Warm Deserts Forests 8,084 −0.3 −0.1 −0.1 0 −0.2 0.4 −0.6 0.2

Grasslands/shrublands 403,390 −3 2.8 −5.4 0.1 −7.7 0.7 −16.1 2.7

Agricultural lands 11,334 0 0 −1.1 0 −0.7 0 −1.8 0

Wetlands 326 0 0 0 0 0 0 0 0

Other lands 42,150 0 0 −0.1 0.1 0 0 −0.1 0

Total 465,285 −3.3 2.7 −6.7 0.2 −8.6 1.1 −18.6 2.9

Mediterranean 

California

Forests 29,945 −2.9 −2.3 −2.1 0 −1.8 −0.1 −6.1 −2.6

Grasslands/shrublands 74,294 −0.6 0.1 −5 0.2 −2.2 0 −6.4 0.3

Agricultural lands 41,046 0 0.1 −4.3 0.1 −1.3 0 −5.6 0.2

Wetlands 910 0 0 −0.1 0.1 0 0 −0.1 0.1

Other lands 23,259 0 0 −0.4 −0.1 0 0 −0.4 −0.1

Total 169,455 −3.6 −2.1 −11.9 0.2 −5.4 0 −18.7 −2.2

Western United 

States (total)

Forests 746,343 −39.8 −20.8 −28.3 0.6 −24.1 13.4 −90.7 −21.8

Grasslands/shrublands 1,564,759 −4.3 9.5 −31.9 0.6 −27.3 0.7 −58.7 7

Agricultural lands 160,711 −0.3 0.1 −7.5 0.5 −3.3 0 −10.8 0.3

Wetlands 10,114 −0.1 0.2 −1.2 −0.1 −0.3 0 −1.5 0

Other lands 176,532 −0.1 0 −1.1 0.9 −0.1 0.1 −1.2 0.9

Total 2,658,459 −44.6 −11.1 −70 2.5 −55 14.2 −162.9 −13.6
Chapter 5 59

5.4.2.5. Mediterranean California

From 2001 to 2005, the estimated average net carbon 

flux in the Mediterranean California ecoregion was 

−13.7 TgC/yr (ranging from −18.7 to −2.2 TgC/yr). The 

total rate of carbon sequestration was attributed to forests 

(−4.8 TgC/yr), grasslands/shrublands (−5.3 TgC/yr), and 

agricultural lands (−3.3 TgC/yr).

5.4.2.6. Discussion of Baseline Net Carbon Flux

In the Western United States, the evergreen forest of 

the Pacific Coast was the most productive ecosystem and 

sequestered a significant amount of carbon. D.P. Turner, 

Gockede, and others (2011) estimated that the per-unit-ofarea NEP of Oregon’s coastal forests (an average of private 

and public forest) during 2007 was around −75 gC/m2/yr. 

In this assessment, the average estimated net carbon flux 

for the Marine West Coast Forest ecoregion in the baseline 

period was −52 gC/m2/yr on a per-unit-of-area basis, about 

30 percent lower. For the five western ecoregions, the 

estimated average net carbon flux in forests was −54 TgC/yr 

(ranging from −90.7 to −21.8 TgC/yr), which is comparable 

to an estimate by Heath and others (2011) of −43.1 TgC/yr 

(ranging from 24.9 to −111.2 TgC/yr) for the years 2000 to 

2008. The average annual net carbon flux estimates from the 

two studies may be expressed as per-unit-of-area carbon flux: 

−72.4 gC/m2/yr from this assessment and −93.8 gC/m2/yr from 

Heath and others (2011).

Estimates of net carbon flux in California’s agricultural 

lands were variable. Kroodsma and Field (2006) estimated 

that California’s agricultural lands sequestered an average of 

−19 gC/m2/yr between 1980 and 2000. For this assessment, 

however, the Mediterranean California ecoregion (not the 

entire state of California) was estimated to have sequestered 

an average of −81 gC/m2/yr (−3.3 TgC/yr over 41,046 km2) 

during the baseline period. The large gap between the results of 

this assessment and those of the earlier studies can be attributed 

to several observations. First, Kroodsma and Field (2006) 

estimated that the conversion of annual crops to vineyards or 

orchards generated a carbon sink of −68 to −85 gC/m2/yr, which 

was very close to the estimate in this assessment. Second, they 

also indicated that rice fields sequestered −55 gC/m2/yr due to a 

reduction of field burning. This assessment did not include field 

burning of crop residue, and therefore the estimated carbon sink 

in this assessment should be high.

As noted previously (see section entitled “Model Run 

Setup”), the purpose of using multiple models on the GEMS 

platform was to provide an opportunity to quantify uncertainties 

related to model structures and inherent biases and errors. 

Table 5.5 shows the average estimates of carbon stocks and 

carbon fluxes derived by each of the three models for each of 

the five ecoregions. A variability value (in percent) was also 

calculated by dividing the range of the minimum and maximum 

estimates of the subset by their mean, and multiplying by 100.

5.4.3. Greenhouse-Gas Fluxes in Baseline Years

Methane and nitrous oxide (CH4 and N2O) fluxes in and out 

of the terrestrial ecosystems were included in the assessment and 

were modeled using the spreadsheet model. The fluxes of the 

two gases were converted to carbon dioxide equivalent (denoted 

as CO2-eq) by using the respective global warming potential 

(GWP) factors—21 for methane and 310 for nitrous oxide (EPA, 

2003). The carbon flux estimates reported in the previous section 

were converted to carbon dioxide equivalent using a conversion 

factor of 3.664 and a GWP factor of 1 (EPA, 2003). The average 

estimated fluxes of the three gases during the baseline years 

are presented in table 5.6. Note that these flux estimates do not 

include the aquatic fluxes presented in chapter 10 of this report. 

The combined flux estimates in a regional carbon budget are 

presented and discussed in chapter 12 of this report.

Table 5.5. Comparison of estimated average carbon stocks and fluxes in the five ecoregions of the Western United States, by 

the three simulation models.

[Negative numbers indicate carbon sequestration; positive numbers indicate loss of carbon to the atmosphere. EDCM, Erosion-Deposition-Carbon 

Model; TgC, teragrams of carbon; TgC/yr, teragrams of carbon per year]

Models

Ecoregions

Western 

Cordillera

Marine West 

Coast Forest

Cold

Deserts

Warm

Deserts

Mediterranean 

California

Western 

United States

Carbon stock 

(TgC)

CENTURY 7,867.7 1,474.9 3,055.1 910.3 920.6 14,228.7

EDCM 8,365.9 1,560.7 2,342.8 529.2 861.3 13,659.8

Spreadsheet 8,439.0 1,632.7 2,362.6 582.7 762.3 13,779.2

Model variability (percent) 7 10 28 57 19 4

Carbon flux 

(TgC/yr)

CENTURY −85.3 −6.2 −30.1 −18.4 −18.0 −158.0

EDCM −24.6 −2.0 1.9 2.7 −13.2 −35.2

Spreadsheet −19.7 −2.1 −1.9 −0.2 −2.4 −26.3

Model variability (percent) 152 121 320 398 139 180
60 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Table 5.6. Minimum and maximum estimated averages of annual carbon dioxide, methane, and nitrous oxide fluxes and their 

total global warming potential from 2001 to 2005 in the Western United States, by greenhouse-gas type for each ecosystem in each 

ecoregion.

[Estimates of methane (CH4) and nitrous oxide (N2O) were generated by the spreadsheet model. The carbon-dioxide (CO2) estimate is the average of the EDCM 

and CENTURY model simulations. Global warming potential is the sum of carbon dioxide, methane, and nitrous oxide; TgCO2-eq/yr, teragrams of carbon 

dioxide equivalent per year] 

Ecoregion Ecosystem

Carbon dioxide 

(TgCO2-eq/yr)

Methane

(TgCO2-eq/yr)

Nitrous oxide 

(TgCO2-eq/yr)

Global warming 

potential

(TgCO2-eq/yr)

Min Max Min Max Min Max Min Max

Western 

Cordillera

Forests −257.9 −72.0 −0.9 −0.9 0.3 0.3 −258.5 −72.6

Grasslands/shrublands −53.6 0.8 −0.8 −0.8 0.2 0.2 −54.2 0.2

Agricultural lands −1.4 0.1 0.0 0.0 0.0 0.0 −1.4 0.1

Wetlands −2.7 −0.4 0.4 0.4 0.0 0.0 −2.3 0.0

Other lands −0.6 1.6 0.0 0.0 0.0 0.0 −0.6 1.6

Total −316.1 −69.9 −1.3 −1.3 0.6 0.6 −316.8 −70.6

Marine West 

Coast 

Forest

Forests −21.9 −4.9 −0.2 −0.2 0.0 0.0 −22.1 −5.1

Grasslands/shrublands −2.5 −0.2 0.0 0.0 0.0 0.0 −2.5 −0.2

Agricultural lands 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.4

Wetlands −0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.2

Other lands −0.9 0.9 0.4 0.4 0.0 0.0 −0.5 1.3

Total −25.3 −3.7 0.3 0.3 0.1 0.1 −24.9 −3.3

Cold Deserts Forests −28.6 5.7 −0.4 −0.4 0.1 0.1 −29.0 5.3

Grasslands/shrublands −76.6 13.9 −2.8 −2.8 0.2 0.2 −79.2 11.3

Agricultural lands −11.2 0.0 −0.1 −0.1 0.1 0.1 −11.1 0.1

Wetlands −2.2 0.1 0.8 0.8 0.0 0.0 −1.4 0.9

Other lands −0.9 1.3 0.4 0.4 0.0 0.0 −0.5 1.7

Total −119.6 21.0 −2.1 −2.0 0.4 0.4 −121.3 19.4

Warm Deserts Forests −2.1 0.8 0.0 0.0 0.0 0.0 −2.1 0.8

Grasslands/shrublands −59.0 10.0 −1.0 −1.0 0.4 0.4 −59.7 9.4

Agricultural lands −6.6 −0.2 0.0 0.0 0.0 0.0 −6.6 −0.2

Wetlands −0.1 0.0 0.1 0.1 0.0 0.0 0.0 0.1

Other lands −0.4 0.1 0.1 0.1 0.0 0.0 −0.3 0.2

Total −68.2 10.8 −0.9 −0.9 0.4 0.4 −68.7 10.3

Mediterranean 

California

Forests −22.5 −9.6 −0.1 −0.1 0.0 0.0 −22.6 −9.7

Grasslands/shrublands −23.6 1.0 −0.2 −0.2 0.1 0.1 −23.7 0.9

Agricultural lands −20.5 0.7 0.8 0.9 0.1 0.1 −19.6 1.7

Wetlands −0.5 0.3 0.2 0.2 0.0 0.0 −0.4 0.5

Other lands −1.5 −0.5 0.2 0.2 0.0 0.0 −1.3 −0.3

Total −68.6 −8.2 0.9 1.0 0.2 0.2 −67.5 −7.0

Western 

United 

States 

(total)

Forests −333.0 −80.1 −1.7 −1.7 0.4 0.4 −334.2 −81.3

Grasslands/shrublands −215.3 25.5 −4.8 −4.8 0.9 0.9 −219.2 21.6

Agricultural lands −39.7 0.9 0.7 0.8 0.3 0.3 −38.8 2.0

Wetlands −5.5 0.2 1.6 1.6 0.0 0.0 −4.0 1.8

Other lands −4.3 3.4 1.1 1.2 0.1 0.1 −3.1 4.6

Total −597.7 −50.0 −3.1 −2.9 1.7 1.7 −599.1 −51.3
Chapter 5 61

The data in table 5.6 indicate that the fluxes of methane 

and nitrous oxide in the ecoregions of the Western United 

States were generally low. As a whole, the Western United 

States served as a GHG sink, sequestering GHGs at an 

estimated average rate of −232.51 TgCO2-eq/yr (ranging 

from −599.1 to −51.3 TgCO2-eq/yr). The CO2 sink dominated 

the contribution (about 99 percent) to the total GWP of the 

GHGs. The overall GHG sink in the terrestrial ecosystems 

of the Western United States is equivalent to 4.9 percent 

of the Nation’s total greenhouse gas emissions in 2010, 

as reported by the EPA’s 2012 national greenhouse gas 

inventory report (EPA, 2012). The average annual nitrous 

oxide emission rate for the entire Western United States was 

1.65 TgCO2-eq/yr, of which the Western Cordillera and Warm 

Deserts ecoregions contributed 61 percent even though they 

cover only 50 percent of the land area. The Marine West 

Coast Forest and Mediterranean California ecoregions acted 

as methane sources at 0.3 and 0.9 TgCO2-eq/yr, respectively, 

for the baseline years, whereas other ecoregions acted as 

methane sinks. The Mediterranean California ecoregion is 

only 1.8 times larger in area than the Marine West Coast 

Forest but its methane emissions were 3 times greater 

because Mediterranean California had more wetlands and 

agricultural lands, which had higher methane emission rates 

than other ecosystems (fig. 5.6). Whether an ecoregion was 

a sink or source of methane was largely associated with the 

land‐cover composition, especially its proportion of wetlands 

and agricultural lands. Agricultural lands and wetlands tended 

to emit methane, whereas forests and grasslands/shrublands 

tended to sequester methane.

On average, all of the ecosystems in the Western 

United States were carbon dioxide sinks and nitrous-oxide 

sources; for the baseline years, both forests and grasslands/

shrublands were methane sinks, and wetlands were 

methane sources. The methane budget varied regionally; 

Mediterranean California was a source (estimated average 

of 0.82 TgCO2-eq/yr) and the other ecoregions were 

sinks. The grasslands/shrublands ecosystem in the Cold 

Deserts and the Western Cordillera consumed methane

at −5.9 and −9.4 gCO2-eq/m2/yr, respectively (fig. 5.6B). 

The wetlands ecosystem for the Western United States 

emitted the largest amount of methane at an average rate of 

105 gCO2-eq/m2/yr (fig. 5.6B). Agricultural lands emitted 

nitrous oxide at a rate of 97.9 gCO2-eq/m2/yr in some parts 

of Mediterranean California, higher than for any of the other 

ecosystems (fig. 5.6C). The spatial distribution of the GWP 

for each GHG generally coincided with the spatial distribution 

of the ecosystems (fig. 5.6). A higher carbon dioxide uptake 

was associated with forested areas (green color in figure 5.6A), 

but higher carbon dioxide emissions were associated with 

agricultural lands and clearcut areas of forests (red color 

in figure 5.6A). Overall, forests covered 28 percent of the 

land area of the Western United States (746,343 km2) but 

accounted for 64 percent of the GHG flux. On the other hand, 

grasslands/shrublands covered 59 percent of the area but 

accounted for only 32 percent of the GHG flux. Agricultural 

lands covered only 6 percent of the area but emitted 15 percent 

of nitrous oxide, whereas wetlands covered only 0.4 percent 

of the area and emitted roughly the same amount of methane 

(1.6 TgCO2-eq/yr) as all other emitters combined. 

5.5. Summary 

The total carbon stocks and fluxes in terrestrial 

ecosystems were estimated using three biogeochemical 

models on the GEMS platform. The modeling was constrained 

by the USDA FIA forest inventory data, the USDA NASS 

grain-yield statistics, and the MODIS NPP product. For 

carbon stocks in the ecosystems of the entire Western United 

States in 2005, the biomass and the top 20 cm of the soil 

layer contained an estimated average of 13,920 TgC (ranging 

from 12,418 to 15,460 TgC). The Western Cordillera stored 

the most carbon (59 percent of the total), followed by the 

Cold Deserts (19 percent), the Marine West Coast Forest 

(11 percent), the Mediterranean California (6 percent), and the 

Warm Deserts (5 percent). Forests, grasslands/shrublands, and 

agricultural lands stored 69 percent, 25 percent, and 4 percent 

of the total carbon, respectively. As a comparison, the total 

forest area, the average total forest carbon stock, and the 

average forest stock density estimated by this assessment for 

2005 in the five ecoregions were 74.6 Mha, 9,675 TgC, and 

13.0 kgC/m2, respectively. A separate analysis (Brad Smith, 

USDA Forest Service, unpub. data, 2010) using the USFS FIA 

forest area and forest carbon stock estimation methods (Nelson 

and Vissage, 2005; J.E. Smith and Heath, 2008) suggested a 

total of 93.6 Mha of forested area, a total forest carbon stock 

of 13,579 TgC, and an average forest carbon stock density 

of 14.5 kgC/m2 for the same five ecoregions. The differences 

between the two studies may be attributed to two factors: 

(1) the total forest area used by the two studies was different, 

and (2) only carbon in the top 20 cm of the soil layer was 

modeled as SOC in this assessment, compared to the FIA SOC 

estimate, which used the top 1 m of the soil layer.
62 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

A B 

0 200 400 MILES

0 200 400 KILOMETERS

Level II ecoregion 

 boundary

< –250

–250 to < –50

–50 to <50

50 to 250

C D

<10

10 to <25

EXPLANATION

Nitrous oxide, in grams of 

 carbon dioxide equivalent

 per square meter per year

25 to 50

>50

EXPLANATION

Global warming potential,

 in grams of carbon dioxide 

 equivalent per square meter per year

>250

< –250

–250 to < –50

–50 to <50

50 to 250

EXPLANATION

Carbon dioxide, in grams of 

 carbon dioxide equivalent 

 per square meter per year

>250

< –15

–15 to < – 5

–5 to <5

5 to 15

EXPLANATION

Methane, in grams of carbon 

 dioxide equivalent per square

 meter per year

>15

N
Chapter 5 63

Figure 5.6. (see facing page). Maps showing the spatial 

distribution of the average annual carbon dioxide, methane, and 

nitrous oxide fluxes and their total global warming potential from 

2001 to 2005 in the Western United States. The flux of carbon 

dioxide is an average of estimates derived from the spreadsheet 

model, CENTURY model, and the EDCM in the General Ensemble 

The overall average annual net carbon flux in terrestrial 

ecosystems of the Western United States was estimated to 

be −86.5 TgC/yr (ranging from −162.9 to −13.6 TgC/yr) 

from 2001 to 2005. Forests were the largest carbon sink 

(62 percent of the total), followed by grasslands/shrublands 

(30 percent) and agricultural lands (7 percent). Of the total 

carbon sequestered on an annual basis, about one-third was 

accumulated in live biomass and the rest was allocated to 

the dead biomass (forest litter and dead, woody debris) and 

soil carbon pools. For the baseline years of 2001 to 2005, the 

estimated average annual net carbon flux in forests estimated 

in this assessment (−54 TgC/yr, ranging from −90.7 to 

−21.8 TgC/yr) was comparable to an estimate by Heath 

and others (2011) of −43.1 TgC/yr (ranging from 24.9 to 

−111.2 TgC/yr) for the years 2000 to 2008. The average 

annual net carbon flux estimates from the two studies may be 

expressed as per-unit-of-area carbon flux: −72.4 gC/m2/yr 

from this assessment and −93.8 gC/m2/yr from Heath and 

others (2011).

A comparison of carbon stock and flux indicates that 

there are still profound differences and uncertainties within 

carbon estimation methods, models, and data sources. Further 

comparisons between models may help to reveal the major 

causes of those differences, such as model structure, parameter 

sensitivity, and data assimilation.

Modeling System (GEMS). The fluxes of methane and nitrous 

oxide were derived from the spreadsheet model alone in the 

GEMS. A, Carbon dioxide. B, Methane. C, Nitrous oxide. D, Global 

warming potential. EDCM, Erosion-Deposition-Carbon Model. See 

figure 1.1 in chapter 1 for ecoregion names.
64 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

This page intentionally left blank.
Chapter 6. Projected Land-Use and Land-Cover Change 

in the Western United States

By Benjamin M. Sleeter1, Terry L. Sohl1, Tamara S. Wilson1, Rachel R. Sleeter1, Christopher E. Soulard1, 

Michelle A. Bouchard1

, Kristi L. Sayler2, Ryan R. Reker3, and Glenn E. Griffith1

1U.S. Geological Survey, Menlo Park, Calif.

2U.S. Geological Survey, Sioux Falls, S.D.

3Arctic Slope Regional Corporation Research and Technology Solutions, Sioux Falls, S.D.

6.1. Highlights

• The projected changes in land use and land cover 

are highly variable across ecoregions and scenarios. 

The overall rates of projected change varied from 

1.3 percent in the Warm Deserts ecoregion under the 

A2 scenario to 44.9 percent in the Marine West Coast 

Forest ecoregion under the A1B scenario. 

• Land-use and land-cover change was generally 

projected to be greatest under the economically 

oriented scenarios and smaller in the 

environment-oriented scenarios. 

• Forest harvesting and regrowth accounted for the 

greatest amount of projected land-use and land-cover 

change under all of the scenarios; however, the 

projected rates of change were highly variable across 

the level III ecoregions and were driven by the 

regions’ enabling environmental characteristics and 

resource potential.

• Urbanization was a key component of projected 

land-use and land-cover change in all of the scenarios 

and was most pronounced in the Mediterranean 

California and Marine West Coast Forest ecoregions.

• Forests were projected to decline in the economically 

oriented scenarios, resulting primarily from the 

projected high demand for urban land uses and, to a 

lesser extent, the expansion of agricultural land. 

6.2. Introduction and Review 

of Methods

The current and projected changes in land use and land 

cover (LULC) are key components for this assessment of 

carbon and greenhouse-gas (GHG) stocks and fluxes (Zhu and 

others, 2010). As noted in chapter 1 of this report, mapping 

of the baseline (1992–2005) LULC conditions, discussed 

in detail in chapter 2 of this report, provided a spatial 

foundation for the wall-to-wall assessment of carbon stocks 

and GHG fluxes in various ecosystems. The development 

of a range of future potential LULC projections, together 

with corresponding climate-change projections, allowed 

for an evaluation of future potential carbon sequestration 

capacities and vulnerabilities as influenced by these projected 

drivers. This chapter provides an overview of the methods 

used to develop alternative future scenarios of LULC and 

presents the spatially explicit LULC modeling results for 

each level II ecoregion in the Western United States. The 

relation between the future LULC scenarios described in this 

chapter and other components of the assessment is depicted 

in figure 1.2 of chapter 1. The level II and level III ecoregion 

names and boundaries are modified from the Commission for 

Environmental Cooperation (2006) and U.S Environmental 

Protection Agency (EPA, 1999).
66 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

6.2.1. Scenario Framework

In 2001, the Intergovernmental Panel on Climate 

Change (IPCC) published the Special Report on Emission 

Scenarios (SRES) (Nakicenovic and others, 2000). The 

IPCC–SRES documented the development of a global set 

of greenhouse-gas-emissions scenarios, which were based 

on an underlying set of socioeconomic conditions that were 

consistent with the current (at the time) scenario literature. The 

IPCC–SRES scenarios were designed to assess the impacts 

of alternative GHG-emission pathways on coupled human 

and environmental systems and evaluate future vulnerabilities 

on those systems under various combinations of projected 

change. The IPCC–SRES scenarios consist of four basic 

narrative storylines, each of which describe alternative 

developments in the major drivers of GHG emissions, such as 

population growth, economic growth, technological change, 

energy use, globalization, and environmental protection. 

The four storylines are oriented along two axes with either 

economic growth (A) or environmental protection (B) aligned 

along one axis and either global development (1) or regional 

development (2) aligned along the other; for example, the 

B1 scenario assumes strong environmental protection and 

global cooperation. 

In order to explore sensitivities in the energy sector, 

the A1 storyline was subdivided into three subscenarios that 

focused on fossil-fuel use (A1FI), renewable technologies 

(A1T), and a balanced energy sector that did not rely on 

any particular energy source (A1B). Six modeling teams 

characterized the various storylines, ultimately producing 

40 quantified scenarios. No probability of occurrence was 

assigned to any one of the IPCC–SRES scenarios and all 

should be considered equally plausible with none considered 

more or less preferable. Furthermore, no integrated climatechange policies, such as the emissions targets of the Kyoto 

Protocol (United Nations Framework Convention on Climate 

Change, 1997), are incorporated into any of the scenarios; 

therefore, the scenarios serve as reference conditions to 

evaluate the effects of potential mitigation actions and 

strategies. Since the inception of the IPCC–SRES scenarios, 

a suite of future climate-change projections (known as the 

general circulation model (GCM) data) have also become 

available and correspond to the major storylines. At the early 

stage of this assessment, GCM data corresponding to the B2 

storyline were not available. Because this assessment required 

the use of both the LULC scenarios and climate-change 

projection scenarios, only the A1B, A2, and B1 scenarios were 

used in the assessment. See table 6.1 for assumptions about 

the major driving forces associated with each scenario.

Table 6.1. Assumptions about the primary driving forces affecting land-use and land-cover change. 

[These assumptions were used to downscale the A1B, A2, and B1 scenarios of the Intergovernmental Panel for Climate Change’s Special Report on Emission 

Scenarios (Nakicenovic and others, 2000). Population and per-capita income projections are from Strengers and others (2004)]

Driving forces A1B A2 B1

Population growth (global and 

United States)

Medium. Globally, 8.7 billion by 

2050, then declining; in the 

United States, 385 million by 

2050

High. Globally, 15.1 billion by 

2100; in the United States, 

417 million by 2050

Medium. Globally, 8.7 billion by 

2050, then declining; in the 

United States, 385 million by 

2050.

Economic growth Very high. U.S. per-capita income 

$72,531 by 2050

Medium. U.S. per-capita income 

$47,766 by 2050

High. U.S. per-capita income 

$59,880 by 2050.

Regional or global orientation Global Regional Global.

Technological innovation Rapid Slow Rapid.

Energy sector Balanced use Adaptation to local resources Smooth transition to renewable.

Environmental protection Active management Local and regional focus Protection of biodiversity.
Chapter 6 67

6.2.2. Scenario Downscaling

In order to use the global scenarios, a scenario 

downscaling process was needed to translate the coarse-scale 

scenario data to finer geographic scales while maintaining 

consistency with the original dataset and local data (van 

Vuuren and others, 2007, 2010). Land-change scenarios 

were developed using a modular modeling approach. A 

global integrated assessment model (IAM) was used to 

supply future projections of land use at the national scale. An 

accounting model was developed to refine the national‐scale 

IAM projections and to downscale to hierarchically nested 

ecoregions. The ecoregion-based projections were then 

converted into annual maps of LULC using a spatially explicit 

LULC change model. The approach used for this assessment 

follows the methods described in Zhu and others (2010) and 

more recently in Sohl, Sleeter, Zhu, and others (2012) and 

Sleeter, Sohl, Bouchard, and others (2012). A brief review of 

each of the major components is found below.

Initial quantities of projected LULC changes (scenario 

“demand”) were formulated by implementing a land‐usescenario downscaling accounting model (described in 

detail in Sleeter, Sohl, Bouchard, and others, 2012). 

National‐scale LULC projections were based on national‐scale 

projections from the Integrated Model to Assess the Global 

Environment (IMAGE, version 2.2), land-use histories, 

and expert knowledge. IMAGE was used to simulate future 

environmental change, including GHG emissions and land-use 

changes, for the three SRES marker scenarios (A1B, A2, B1) 

(Strengers and others, 2004). IMAGE used a series of linked 

modules to project environmental consequences resulting from 

anthropogenic activity (Alcamo and others, 1998; IMAGE 

Team, 2001). Environmental changes were projected for 

17 world regions (the United States was treated as a single 

region) with some data (land use and land cover) available 

in a 30′ × 30′ grid. IMAGE produced projections of demand 

for agriculture and forest harvest, which were incorporated 

directly into the scenario downscaling model described in 

Sleeter, Sohl, Bouchard, and others (2012). Future projections 

of development and mining were developed through the use 

of proxy data (population and coal usage, respectively) from 

the IMAGE. Land-use histories were then used to expand the 

scenario projections of net change in major land-use classes 

into comprehensive projections of gross changes between all 

major LULC types. 

Land-use histories described the recent historical LULC 

changes occurring in ecoregions of the United States. These 

data came primarily from the USGS Land Cover Trends 

project, which provided ecoregion-based estimates on the 

rates, extent, and types of LULC change for multiple dates 

between 1973 and 2000 (Loveland and others, 2002; Sleeter, 

Wilson, and Acevedo, 2012). USGS Land Cover Trends 

data were incorporated into the scenarios’ construction and 

downscaling in two primary ways. First, the data were used 

to expand projections of net change in development, mining, 

and agriculture into gross conversions between all primary 

LULC classes at the national scale. Second, the data were 

used to proportionally downscale these LULC conversions 

to ecoregions of the conterminous United States. Throughout 

the downscaling process, regional and sectoral experts were 

consulted in a series of workshops and ad-hoc consultations. 

The data served as a default parameter for downscaling, and 

experts were able to modify certain variables in order to 

produce regionally specific scenarios that retained consistency 

with the IPCC–SRES storylines. A complete description of the 

downscaling process can be found in Sleeter, Sohl, Bouchard, 

and others (2012). 

Regional LULC scenarios, developed in the process 

as described above, were used as input to the “forecasting 

scenarios of land-use change” (FORE–SCE) model (Sohl 

and Sayler, 2008; Sohl, Sleeter, Sayler, and others, 2012). 

The FORE–SCE model produced annual, spatially explicit 

LULC maps from 2006 to 2050 that were consistent with the 

scenario assumptions and LULC proportions from the scenario 

downscaling process. The initial LULC map for the start of the 

simulation period was the 2005 LULC map produced from the 

baseline LULC modeling described in chapter 2 of this report. 

The suitability-of-occurrence surfaces that were used for the 

modeling of the baseline LULC change guided the placement 

of patches of change for the 2006 to 2050 scenarios. The 

Protected Area Database (PAD–US) used in the modeling 

of baseline LULC was also used for the scenario modeling. 

Different decision rules were used for each scenario, with 

more land protected from significant LULC change in the 

environment-oriented B1 scenario and more lands available 

for development in the economically oriented A1 and 

A2 scenarios. Each level III ecoregion was individually 

parameterized and modeled by applying the FORE–SCE 

model for each of the three IPCC–SRES scenarios. The 2006 

to 2050 models of LULC provide spatial representations 

of plausible outcomes that are based on the IPCC–SRES 

scenarios. When combined with the mapped and modeled 

baseline (1992 to 2005) LULC maps described in chapter 2, 

the baseline and modeled scenarios resulted in a continuous, 

consistent LULC map database from 1992 to 2050.
68 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

6.3. Results

6.3.1. Scenario Downscaling Results for the 

Western United States

The projected changes in LULC were variable across 

ecoregions and scenarios. The LULC-change footprint was the 

area of the Western United States that changed at least once 

over the projection period. Under the three scenarios used for 

this assessment, the projected LULC change ranged from a 

low of 5.8 percent in the B1 scenario to a high of 7.8 percent 

in the A1B scenario; in the A2 scenario, the LULC change 

was 6.4 percent. The scenarios that indicated the greatest 

(A1B) and smallest (B1) amounts of projected LULC change 

shared the same assumptions about population growth; 

however, the greatest change indicated by the A1B scenario 

resulted from high demand for forest products, agricultural 

intensification, and high rates of urbanization. The B1 scenario 

was characterized by strengthening environmental protections, 

which limited the anthropogenic conversion of natural land 

covers to either agricultural land or urbanized land. The 

demand for forest products and agricultural commodities 

was reduced in scenario B1 compared to A1B, and the 

environmental emphasis associated with scenario B1 resulted 

in a more compact pattern of urbanization. The variability was 

even greater between the level II ecoregions in the Western 

United States (table 6.2). The greatest projected LULC change 

of any of the ecoregion regions was in the Marine West Coast 

Forest, followed by the Western Cordillera and Mediterranean 

California. The projected LULC change of the Cold Deserts 

and Warm Deserts ecoregions was below 3 percent (table 6.2

and fig. 6.1).

Forest ecosystems accounted for 746,370 km2 of the 

Western United States in 2005 and were projected to decline 

by 5,630 km2 in the A1B scenario and by 5,350 km2 in 

the A2 scenario by 2050 (fig. 6.2) with the harvesting of 

evergreen forests accounting for more than 80 percent of the 

loss. In the B1 scenario, forests were projected to remain 

relatively stable, declining by 630 km2 by 2050 (fig. 6.3). The 

projected net forest loss was driven primarily by the demand 

for urbanization and new agricultural lands. New developed 

areas were projected to increase by 62 percent in the B1 

scenario, 69 percent in the A2 scenario, and 90 percent in the 

A1B scenario, whereas agriculture was projected to increase 

by 12 percent in the A1B scenario and 4 percent in the A2 

scenario, and decline by 1 percent in the B1 scenario (fig. 6.2). 

The projected changes in urban and built-up areas for 

each ecoregion and scenario can be found in figure 6.4. Forest 

harvesting was also a major driver of forest change in the 

west. The rate of forest harvesting was projected to increase in 

both the A1B and A2 scenarios but decline in the B1 scenario. 

By 2050, clearcut logging was projected to affect 21 percent of 

Western United States’ forests in the A1B scenario, 19 percent 

in the A2 scenario, and 17 percent in the B1 scenario. The 

grasslands/shrublands ecosystem was projected to experience 

the greatest areal changes of any ecosystem in the Western 

United States, declining in all scenarios. Figure 6.2 shows 

the projected net change in major ecosystem types between 

2005 and 2050 for each of the three scenarios, and figure 6.3

shows the projected trends in ecosystem composition over 

time. Below is a brief overview of the major projected LULC 

changes in each of the five level II ecoregions in the Western 

United States for each of the three IPCC–SRES scenarios. 

Table 6.2. The projected land-use- and land-cover-change footprint in the level II ecoregions 

of the Western United States.

[Values given in the A1B, A2, and B1 column are the percent of each level II ecoregion that experienced a 

change in land use or land cover at least once between 2005 and 2050]

Ecoregion

Area 

(square 

kilometers)

A1B 

(percent 

change)

A2 

(percent 

change)

B1 

(percent 

change)

Western Cordillera 872,023 12.7 11.1 9.6

Marine West Coast Forest 85,324 44.9 41.6 34.9

Cold Deserts 1,056,072 2.7 1.8 1.8

Warm Deserts 464,312 2.0 1.3 1.5

Mediterranean California 164,481 12.1 7.9 8.5

Western United States (total) 2,642,212 7.8 6.4 5.8
Chapter 6 69

A. Scenario A1B B. Scenario A2

C. Scenario B1

EXPLANATION

Figure 6–1.

Level II

Ecoregion boundary

0 to 2

>2 to 5

>5 to 10

>10 to 20

>20 to 50

Percent of ecoregion area 

 projected to experience 

 land-use or land-cover 

 change at least once 

 between 2005 and 2050

Level III

N

0 200 400 MILES

0 200 400 KILOMETERS

Figure 6.1. Maps showing the projected land-use- and land-cover-change footprint for each of the level III ecoregions 

in the Western United States. The footprint represents the percent of the ecoregion that changed at least once between 

2005 and 2050. A, Scenario A1B. B, Scenario A2. C, Scenario B1.
70 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

746

1,565

161

10

177

0

500

1,000

1,500

2,000

A. Baseline ecosystem composition, 2005

–6

–43

19

30

–50

–30

–10

10

30

50

B. Net change in ecosystem area–Scenario A1B

Figure 6–2.

C. Net change in ecosystem area–Scenario A2

D. Net change in ecosystem area–Scenario B1

–5

–24

6

–1

–1

24

–50

–30

–10

10

30

50

Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other

Area, in thousands of square kilometers

–1

–19

–2

1

20

–50

–30

–10

10

30

50

Figure 6.2. Chart showing the baseline composition of and 

projected net change in major ecosystems between 2005 and 2050 

in the Western United States, for the end of the baseline period 

and for each scenario. A, The percent of land area assigned to 

each of the major ecosystems at the end of the baseline period 

(2005). B, The projected net land-use- and land-cover-change, 

in percent, between 2005 and 2050 for scenario A1B. C, The 

projected net land-use- and land-cover-change, in percent, 

between 2005 and 2050 for scenario A2. D, The projected net 

land-use- and land-cover-change, in percent, between 2005 and 

2050 for scenario B1. Forests that had been harvested (logged) 

were included within the forest ecosystem totals. The “other” 

ecosystem includes developed land, mined land, barren land, 

and water.
Chapter 6 71

Figure 6–3.

710

715

720

725

730

735

A. Forest

Scenario A1B

Scenario A2

Scenario B1

1,500

1,510

1,520

1,530

1,540

1,550

1,560

1,570

B. Grassland/shrubland

130

140

150

160

170

180

190

C. Agriculture

0

2

4

6

8

10

12

D. Wetland

160

170

180

190

200

210

E. Other

0

5

10

15

20

25

F. Logged

0

10

20

30

40

50

60

70

2005 2015 2025 2035 2045

2005 2015 2025 2035 2045 2005 2015 2025 2035 2045

G. Developed

Area, in thousands of square kilometers

EXPLANATION

Figure 6.3. Graphs showing trends in the projected composition of the major land-use and land-cover classes over the 

projection period (2005 to 2050) for the Western United States, by scenario. A, Forest. B, Grassland/shrubland. C, Agriculture. 

D, Wetland. E, Other (includes developed land, mined land, barren land, and snow/ice). F, Logged (shown separately from 

other forests because it is a major driver of forest change). G, Developed.
72 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

6.3.2. Regional Results 

6.3.2.1. Western Cordillera

 The Western Cordillera level II ecoregion includes 

12 level III ecoregions: Cascades, North Cascades, Eastern 

Cascades—Slopes and Foothills, Klamath Mountains, Blue 

Mountains, Sierra Nevada Mountains, Northern Rockies, 

Canadian Rockies, Wasatch-Uinta Mountains, Middle 

Rockies, Southern Rockies, and Arizona-New Mexico 

Mountains. The ecoregion includes the high mountains of the 

interior Western United States and highly variable climate, 

vegetation, and land use because of its rugged topography 

and extensive ranges in elevation. A large proportion of this 

ecoregion is publicly owned, which affects land-use and 

land-management practices. Landscapes range from grassand shrub-covered lowlands, forested middle elevations, 

and alpine areas of rock, snow, and ice. Livestock grazing 

is common in valleys and the lower to middle elevations, 

and logging is typical in forested areas. Recreation, wildlife, 

and land-management issues related to watersheds or water 

supply also influence the LULC. Forestry activity over recent 

historical times has accounted for as much as two-thirds of 

all of the regional LULC change; however, forestry activities 

were highly variable across the level III ecoregions. Data from 

the USGS Land Cover Trends project (Sleeter, Soulard, and 

others, 2012) indicated that 74 percent of all logging activity 

in the past three decades occurred in four level III ecoregions: 

Cascades, Northern Rockies, Eastern Cascades—Slopes 

and Foothills, and Klamath Mountains. Furthermore, the 

overall amount of LULC change was geographically highly 

variable and ranged from 1 percent in the Southern Rockies 

to 25 percent in the Cascades. Approximately three-fourths of 

the Western Cordillera is Federally managed public land, and 

within it, 22 percent is designated as either highly protected 

wilderness or a national park, which spatially limits timber 

harvesting and other anthropogenic activities. Population 

growth is sparse and scattered in this ecoregion due to the 

rugged terrain, lack of infrastructure, and proximity to goods 

and services, which limits the growth of urban and developed 

land. Agriculture is also limited and is generally confined to 

lower elevations, where livestock grazing is common.

In all of the scenarios, the projected LULC change 

in the Western Cordillera ecoregion centered on forestry 

activities. Approximately three-fourths of all logging was 

projected to occur in the Cascades, Eastern Cascades—Slopes 

and Foothills, Northern Rockies, and Klamath Mountains 

level III ecoregions.

In the A1B scenario, 92,990 km2 of forested land was 

projected to be harvested between 2005 and 2050. Most of the 

projected harvest was conifer forest, with 58 percent occurring 

in national forests and 32 percent in privately owned forests 

(table 6.3). The overall extent of forested land was projected 

to decline from 546,560 km2 in 2005 to 545,010 km2 by 2050 

(fig. 6.5). Agricultural lands were projected to expand by 

3,500 km2 (from 16,720 km2 in 2005); the Blue Mountains 

ecoregion was projected to have the largest increase in 

agricultural land (1,220 km2), with most of the increase 

due to the conversion of grasslands/shrublands (880 km2). 

The primary type of agricultural land was hay/pasture land. 

Between 2005 and 2050, developed land was projected to 

more than double, expanding by 2,940 km2 (from 2,630 km2

in 2005); 44 percent of this growth was projected to occur near 

Spokane, Washington, and Coeur d’Alene, Idaho, within the 

Northern Rockies ecoregion.

In the A2 scenario, 82,730 km2 of forested land was 

projected to be harvested between 2005 and 2050 (table 6.3). 

As in the A1B scenario, national forests were projected to 

account for the majority of forest harvesting. The overall 

forested area was projected to decline from 546,560 km2 in 

2005 to 545,170 km2 in 2050, while agricultural land was 

projected to increase by 1,400 km2 (from 16,720 km2 in 2005) 

(fig. 6.5). Most of the agricultural expansion was projected to 

occur because of the conversion of grasslands/shrublands to 

hay/pasture lands to support livestock. Developed land was 

projected to double in area, increasing from 2,630 km2 in 2005 

to 5,090 km2 in 2050 (fig. 6.4). The projected expansion of 

agricultural and developed land resulted in a projected decline 

in the grasslands/shrublands ecosystem of 1 percent, from 

277,880 km2 in 2005 to 275,110 km2 in 2050 (fig. 6.5).

Figure 6–4.

0

5

10

15

Scenario A1B Scenario A2 Scenario B1

Area, in thousands of

square kilometers

EXPLANATION

Western Cordillera

Marine West Coast Forest

Cold Deserts

Warm Deserts

Mediterranean California

Level II ecoregion

Figure 6.4. Chart showing projected change in area of developed 

land by level II ecoregion for the A1B, A2, and B1 scenarios for the 

period 2005 to 2050.
Chapter 6 73

Figure 6–5.

0

100

200

300

400

500

600

–10

–8

–6

–4

–2

0

2

4

–10

–8

–6

–4

–2

0

2

4

–4

–6

–2

0

2

4

Area, in thousands of square kilometers

Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other

A. Baseline ecosystem composition, 2005 B. Net change in ecosystem area–Scenario A1B

C. Net change in ecosystem area–Scenario A2 D. Net change in ecosystem area–Scenario B1

Table 6.3. Projected extent of forest logging (driven by demand for forest products) in national, other publicly owned, and 

privately owned forests in the Western United States and two ecoregions, by ecoregion and ownership category, for the A1B, A2, 

and B1 scenarios. 

[For each set of data, the area is the projected sum of all logged area between 2006 and 2050 and the percentages are the allocation of logged area across 

the three ownership categories. Data for other three ecoregions covered in this assessment were not included because timber harvesting is not a major 

economic activity in these regions]

A1B A2 B1

Western United States (includes all ecoregions) Total cut area (km2) 124,288 110,576 93,485

National forests (percent) 43.9 44.0 43.2

Other publicly owned forests (percent) 11.9 12.2 11.4

Private forests (percent) 44.2 43.7 45.4

Western Cordillera ecoregion Total cut area (km2) 92,986 82,728 69,944

National forests (percent) 57.9 57.6 57.3

Other publicly owned forest (percent) 10.2 10.2 10.3

Private forests (percent) 31.8 32.2 32.4

Marine West Coast Forest ecoregion Total cut area (km2) 30,991 27,576 23,307

National forests (percent) 1.9 3.5 0.8

Other publicly owned forests (percent) 17.0 18.2 14.7

Private forests (percent) 81.1 78.2 84.5

Figure 6.5. Charts showing the baseline composition of and 

projected net change in major ecosystems between 2005 and 

2050 in the Western Cordillera ecoregion, for the final year of the 

baseline period and for each scenario. A, The percent of land 

area assigned to each of the major ecosystems at the end of the 

baseline period (2005). B, The projected net land-use- and landcover-change, in percent, between 2005 and 2050 for scenario 

A1B. C, The projected net land-use- and land-cover-change, in 

percent, between 2005 and 2050 for scenario A2. D, The projected 

net land-use- and land-cover-change, in percent, between 

2005 and 2050 for scenario B1. Forests that had been harvested 

(logged) were included within the forest ecosystem totals. The 

“other” ecosystem includes developed land, mined land, barren 

land, and water. The large projected net changes in the “other” 

class were primarily attributed to the projected increases in 

developed land.
74 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

In the B1 scenario, the demand for wood products 

was projected to be lower than in the other scenarios, 

resulting from a large focus on conservation and protection 

of biodiversity. Forest harvesting was projected to affect 

93,490 km2 of forest cover. The Cascades was the only 

level III ecoregion where the overall change was projected 

to be greater than 20 percent (fig. 6.1); however, cutting 

was still projected to occur at relatively high rates in the 

East Cascades—Slopes and Foothills, Klamath Mountains, 

Northern Rockies, and North Cascades. In contrast to the 

economically oriented scenarios, the forested area in this 

scenario was projected to decrease by only 140 km2 (from 

546,560 km2 in 2005), while agricultural lands were projected 

to decrease by 50 km2 (from 16,700 km2 in 2005) (fig. 6.5). 

Furthermore, the B1 scenario is the only one that indicated a 

projected increase in wetlands; in 2005, wetlands accounted 

for 3,660 km2 and in 2050 they were projected to account for 

3,750 km2. Similar to the A2 scenario, developed areas were 

projected to increase by 1,940 km2 and were concentrated 

around the city of Spokane, Washington, in the Northern 

Rockies. Figure 6.6 shows a comparison of projected LULC 

changes resulting from forest harvesting activities near Crater 

Lake, Oregon, in the Cascades and East Cascades—Slopes 

and Foothills.

6.3.2.2. Marine West Coast Forest

The Marine West Coast Forest level II ecoregion 

includes the Coast Range, Puget Lowland, and Willamette 

Valley level III ecoregions. The ecoregion consists of a 

highly dynamic, heterogeneous landscape with regionally 

unique LULC. The conifer-covered, rolling hills of the 

sparsely populated Coast Range give way to the low-lying, 

agriculture-dominated Willamette Valley to the east and 

the intensively developed Puget Lowland in the north. The 

three subregional economies are distinct from each other and 

contribute to marked differences in projected LULC change. 

Forestry and forest products are major drivers of the region’s 

economy, along with agriculture, information technology, 

manufacturing, construction, and service industries (Sleeter, 

Soulard, and others, 2012). Although timber harvesting is 

common throughout the ecoregion, privately owned forests 

in the Coast Range and along the periphery of the Willamette 

Valley are the most heavily logged. Much less cutting has 

occurred on public lands since the Federal enactment of 

species protection through the Northwest Forest Plan (U.S. 

Department of Agriculture and U.S. Department of the 

Interior, 1994). According to the USGS Land Cover Trends 

data (Sleeter, Soulard, and others, 2012), forest cutting in the 

past three decades was the highest ranking LULC change and 

affected over 16 percent of the total land area. Urbanization 

was also an important LULC transition with large areas of 

forest and agriculture converted to urban land in the Puget 

Lowland and Willamette Valley, respectively. Overall, the 

Marine West Coast Forest ecoregion experienced the highest 

rates of late-20th-century LULC change in the Western 

United States. The drivers of LULC change included regional 

and global timber demand, market competition, population 

expansion, conversion of forested lands to agricultural lands, 

and environmental protection (Daniels, 2005). 

The projected LULC change was greatest in the 

Marine West Coast Forest in comparison with the other four 

ecoregions in the Western United States; 20 percent or more 

of the ecoregion was projected to experience LULC change 

in all of the scenarios. Forest harvesting was projected to 

be greatest in each of the three scenarios with the majority 

of harvesting occurring in the Coast Range. The extent 

of developed lands was projected to increase in all of the 

scenarios, with most new development occurring in the Puget 

Lowland and successively smaller amounts occurring in the 

Willamette Valley and Coast Range. Agricultural land was 

projected to increase in the A1B and A2 scenarios and decline 

in the B1 scenario. Figure 6.7 shows the baseline ecosystem 

composition and the projected net change for each ecosystem 

in each scenario studied for this assessment. 

In the A1B scenario, anthropogenic land-use demand 

was projected to increase almost a full percent of the land area 

(to 25.6 percent) while natural land covers were projected to 

decline (to 74.4 percent) from the baseline conditions. The 

projected forest-related LULC change was the greatest of any 

of the scenarios, with nearly 31,000 km2 of the forested part 

of the ecoregion harvested between 2005 and 2050 (table 6.3) 

and over 2,500 km2 cleared for development. More than 

81 percent of all cutting was projected to occur on private 

lands, whereas the Coast Range included more than half of 

the modeled clearcut land. Overall, forests were projected to 

decline by 3,760 km2 (from 64,600 km2 in 2005). By 2050, 

developed lands were projected to increase by 79 percent 

(3,510 km2) from 4,720 km2 in 2005. The Puget Lowland was 

projected to grow the most (64 percent of all new developed 

lands) followed by the Willamette Valley (27 percent of all 

new developed lands). In the Puget Lowland, 67 percent of 

all new developed land was projected to be converted from 

forested land. Another notable change was the projected 

addition of 560 km2 of new hay/pasture land (from 7,900 km2

in 2005), mostly in the Coast Range as cleared forests were 

converted to agricultural land. 

In the A2 scenario, more than 27,500 km2 of forests was 

projected to be harvested by 2050. In this scenario, nearly 

22 percent of all trees harvested came from public lands (both 

national forests and other public forests; table 6.3), which was 

the greatest percentage of any scenario. In the Coast Range, 

nearly 25 percent of all forest cutting was projected to occur 

in public forests, the highest percentage for any scenario. 
Chapter 6 75

122°00'

122°30' 122°00'

43°00'

43°00'

42°30'

Cascades

East Cascades—

Slopes and Foothills

0 10 20 KILOMETERS

0 10 20 MILES

A B

C D

Figure 6–6.

Marine West

Coast Forest

Map

area

Western

Cordillera

Warm Deserts

Mediterranean

California

Level II ecoregions

Cold

Deserts

EXPLANATION

Area projected to

 experience land-use

 or land-cover change

Land use and land cover

Water

Developed

Logging, national forest

Logging, other public land

Logging, private land

Mining

Barren

Deciduous forest

Evergreen forest

Level III ecoregion 

 boundary

Mixed forest

Grassland

Shrubland

Cultivated crops

Hay/pasture

Woody wetland

Herbaceous wetland

Snow/ice

Area projected to

 experience logging

Figure 6.6. Maps showing land use and land cover (LULC) in 2005 and a comparison of the projected LULC changes in the A1B, A2, 

and B1 scenarios in 2050 for the area around Crater Lake, Oregon, in the Western Cordillera ecoregion. Changes were projected to be 

the result of either land-use change or forest clearcutting. A, LULC in 2005. B, Projected LULC change in the A1B scenario. C, Projected 

LULC change in the A2 scenario. D, Projected LULC change in the B1 scenario. Crater Lake is located in the center of the image. 
76 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

0

10

20

30

40

50

60

70

–4

–2

0

2

4

–4

–2

0

2

4

–4

–2

0

2

4

Area, in thousands of square kilometers

Figure 6–7.

Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other

A. Baseline ecosystem composition, 2005 B. Net change in ecosystem area–Scenario A1B

C. Net change in ecosystem area–Scenario A2 D. Net change in ecosystem area–Scenario B1

New developed land was projected to expand by 3,450 km2

to 8,160 km2 by 2050, which was an increase of 77 percent 

over 2005 levels. More than 500 km2 of natural land cover 

(forest, wetlands, and grasslands/shrublands) was projected 

to be converted to agricultural land. Agricultural land was 

projected to increase by 5 percent, from 10,400 km2 in 2005 

to 10,900 km2 in 2050; cultivated cropland was projected to 

remain relatively stable at 2,500 km2, whereas hay/pasture 

was projected to increase from 7,900 km2 to 8,410 km2. In the 

Willamette Valley, agricultural land was projected to remain 

relatively stable, whereas in the Coast Range ecoregion, a 

large resource base and low demand for urban land use was 

projected to result in both cultivated cropland and hay/pasture 

land increasing by 40 km2 and 680 km2, respectively. By 2050, 

natural land cover was projected to account for 74.9 percent 

of all land area, while anthropogenic LULC was projected to 

account for 25.1 percent. 

The projected LULC change was lowest under the B1 

scenario. Overall, the projected forest harvest levels were the 

lowest of the three scenarios with roughly 23,300 km2 of forest 

cutting projected to occur between 2005 and 2050, which is 

25 percent less than the area projected in scenario A1B. The 

strong environmental regulation of public land was projected 

to lead to a higher proportion of forest cutting occurring 

in privately owned forests compared to the A1B and A2 

scenarios. By 2050, nearly 80 percent of all land in the Marine 

West Coast Forest was projected to be natural land cover 

(from 75.2 percent in 2005), the highest proportion of any 

scenario. Developed land use was projected to expand, albeit 

at a slower rate than in the economically oriented scenarios. 

Only 2,030 km2 of new developed lands was projected to be 

added by 2050 (from 4,720 km2 in 2005), with the majority 

of the land conversions coming from agricultural lands and 

hay/ pasture lands. Agricultural land was projected to decline 

by 12 percent with projected losses of nearly 340 km2 of 

cultivated crops and 900 km2 of hay/pasture lands; nearly 

60 percent of the projected loss in agricultural land was in the 

Willamette Valley ecoregion. Figure 6.8 shows a comparison 

between projections for the A1B, A2, and B1 scenarios.

Figure 6.7. Charts showing the baseline composition of and 

projected net change in major ecosystems between 2005 and 

2050 in the Marine West Coast Forest ecoregion, for the final 

year of the baseline period and for each scenario. A, The 

percent of land area assigned to each of the major ecosystems 

at the end of the baseline period (2005). B, The projected net 

land-use- and land-cover-change, in percent, between 2005 and 

2050 for scenario A1B. C, The projected net land-use- and landcover-change, in percent, between 2005 and 2050 for scenario A2. 

D, The projected net land-use- and land-cover-change, in percent, 

between 2005 and 2050 for scenario B1. Forests that had been 

harvested (logged) were included within the forest ecosystem 

totals. The “other” ecosystem includes developed land, mined 

land, barren land, and water. The large projected net changes 

in the “other” class were primarily attributed to the projected 

increases in developed land.
Chapter 6 77

!( !(

Salem

Albany

Keizer

Corvallis

Coast Range

Willamette Valley

123°30'

124°00' 123°30'

123°00'

45°00'

45°00'

44°30'

0 10 20 KILOMETERS

0 10 20 MILES

EXPLANATION

Figure 6.8.

Area projected to

 experience land-use

 or land-cover change

Land use and land cover

Marine West

Coast Forest

Map

area

Western

Cordillera

Warm Deserts

Mediterranean

California

Level II ecoregions

Water

Developed

Logging, national forest

Logging, other public land

Logging, private land

Mining

Barren

Deciduous forest

Evergreen forest

A B

C D

Level III ecoregion 

 boundary

Mixed forest

Grassland

Shrubland

Cultivated crops

Hay/pasture

Woody wetland

Herbaceous wetland

Snow/ice

Area projected to

 experience logging

Cold

Deserts

Figure 6.8. Maps showing land use and land cover (LULC) in 2005 and a comparison of projected LULC changes in the A1B, A2, and B1 

scenarios in 2050 for an area near Salem, Oregon, in the Marine West Coast Forest ecoregion. Changes were projected to be the result of 

either land-use change or forest clearcutting. A, LULC in 2005. B, Projected LULC change in the A1B scenario. C, Projected LULC change 

in the A2 scenario. D, Projected LULC change in the B1 scenario.
78 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States Area, in thousands of square kilometers

0

200

400

600

800

1,000

–20

–15

–10

–5

0

5

10

15

–20

–15

–10

–5

0

5

10

15

–20

–15

–10

–5

0

5

10

15

Figure 6–9.

Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other

A. Baseline ecosystem composition, 2005 B. Net change in ecosystem area–Scenario A1B

C. Net change in ecosystem area–Scenario A2 D. Net change in ecosystem area–Scenario B1

Figure 6.9. Charts showing the baseline composition of and 

projected net change in major ecosystems between 2005 and 2050 

in the Cold Deserts ecoregion for the final year of the baseline 

period and for each scenario. A, The percent of land area assigned 

to each of the major ecosystems at the end of the baseline period 

(2005). B, The projected net land-use- and land-cover-change, 

in percent, between 2005 and 2050 for scenario A1B. C, The 

projected net land-use- and land-cover-change, in percent, 

between 2005 and 2050 for scenario A2. D, The projected net 

land-use- and land-cover-change, in percent, between 2005 

and 2050 for scenario B1. Forests that had been harvested 

(logged) were included within the forest ecosystem totals. The 

“other” ecosystem includes developed lands, mined lands, 

barren lands, and water. The large projected net changes in the 

“other” class were primarily attributed to projected increases in 

developed lands.

6.3.2.3. Cold Deserts

The Cold Deserts level II ecoregion includes the 

following level III ecoregions: Columbia Plateau, Snake River 

Plain, Northern Basin and Range, Central Basin and Range, 

Wyoming Basin, Colorado Plateaus, and Arizona-New Mexico 

Plateau. The ecoregion is characterized by low rainfall and 

large temperature contrasts between winter and summer. This 

arid region has a variety of landforms, including a series of 

basins and mountain ranges, broad plateaus, and valleys. 

Rare perennial streams typically originate in the bordering 

mountainous ecoregions. The few small perennial streams 

that originate in the higher mountain ranges within the Cold 

Deserts commonly disappear before they reach the lower 

elevations, which contributes to the aridity. Natural landscapes 

dominate, with about three-fourths of the region covered by 

natural grasslands and shrublands. Agricultural land is the 

most common anthropogenic land use where irrigation is 

possible from groundwater or from the Snake or Columbia 

Rivers. Urbanization is sparse and dispersed because of the 

vast open space, limited access to water, and poor proximity 

to goods and services. Salt Lake City, Utah; and the Reno 

and Carson City, Nevada, corridor are the two most notable 

developed areas. Data from the USGS Land Cover Trends 

project indicated that only 3 percent of the Cold Deserts 

experienced a change in land use or land cover between 1973 

and 2000 (Sleeter, Soulard, and others, 2012). Historically, the 

largest conversion was an increase of 6,000 km2 in agricultural 

lands from grasslands/shrublands. Over 50 percent of this 

change occurred in the Columbia Plateau. In general, LULC 

change was geographically highly variable and ranged from 

9.2 percent in the Columbia Plateau to 1.2 percent in the 

Arizona-New Mexico Plateau. 

In the A1B scenario, the projected LULC change between 

2005 and 2050 was characterized by agricultural expansion 

coupled with a moderate increase in developed lands (fig. 6.9). 
Chapter 6 79

Agricultural lands were projected to increase by 16 percent, 

from 81,190 km2 in 2005 to 94,040 km2 in 2050. The most 

common projected conversion was from grasslands/shrublands 

to agricultural lands. Approximately 80 percent of this 

conversion was projected to occur in the Columbia Plateau 

and Snake River Plain. The increase in agricultural land 

was driven by the projected increase of cultivated cropland 

(11,400 km2) and a small projected increase in hay/pasture 

land (1,450 km2). Developed land was projected to expand by 

4,440 km2 (from 6,240 km2 in 2005). About 50 percent of the 

new developed land was projected to be located in the Central 

Basin and Range, where the urban areas associated with Salt 

Lake City, Utah; and Reno, Nevada, are located. Collectively, 

the projected expansion of agricultural and developed lands 

contributed to over 17,100 km2 in grassland/shrubland losses 

by 2050, a 2 percent decline from the baseline areal extent. 

Figure 6.10 shows a comparison of agricultural growth and 

grassland/shrubland loss between the three scenarios.

In the A2 scenario, the projected expansions of 

agricultural and new developed lands were common 

themes, although less pronounced than in the A1B scenario. 

Agricultural lands were projected to increase from 81,190 km2

in 2005 to 86,160 km2 in 2050, while grasslands/shrublands 

were projected to decrease by 9,160 km2 (from 804,700 km2

in 2005). A total of 6,690 km2 of grasslands/shrublands was 

projected to be converted to cultivated cropland between 

2005 and 2050, which accounted for the largest amount of 

LULC change in the A2 scenario for the projected time period; 

however, 2,800 km2 of cultivated cropland and hay/ pasture 

was projected to be converted to new developed lands, 

thus offsetting the projected increases in agricultural land. 

Developed lands were projected to expand by 4,370 km2 (from 

6,240 km2 in 2005), which is a rate similar to that projected in 

the A1B scenario. Collectively, the expansion of agricultural 

and developed lands resulted in the projected decline of 

grasslands/shrublands by 1 percent, from 804,660 km2 in 2005 

to 795,500 km2 in 2050.

The projected LULC change was smallest under the 

B1 scenario. Between 2005 and 2050, agricultural land 

was projected to increase by less than 1 percent, by only 

190 km2 (from 81,190 km2 in 2005). Cultivated crops 

were projected to expand by 270 km2 (from 51,870 km2 in 

2005), while hay/ pasture land was projected to decline by 

80 km2 (from 29,330 km2 in 2005). Developed land was 

projected to increase by 3,620 km2 (from 6,240 km2 in 2005), 

primarily in the Central Basin and Range (by 1,700 km2) 

and the Columbia Plateau (by 600 km2). The projected loss 

of grasslands/ shrublands to anthropogenic land use totaled 

3,980 km2 by 2050 (from 804,660 km2 in 2005). Wetlands 

were projected to remain relatively stable with a small 

increase of 110 km2 (from 4,640 km2 in 2005) because of the 

projected reduction in demand for agricultural and developed 

land in this scenario.

6.3.2.4. Warm Deserts

The Warm Deserts level II ecoregion includes four level 

III ecoregions: Mojave Basin and Range, Sonoran Basin and 

Range, Madrean Archipelago, and Chihuahuan Deserts. The 

ecoregion is characterized by the subtropical continental 

Mojave, Sonoran, and Chihuahuan Deserts and the Sky 

Islands (mountains surrounded by lowlands of a drastically 

different environment in the Madrean Archipelago ecoregion). 

The basin-and-range terrain has typically north-to-southtrending mountains separated by broad basins, and these 

valleys are bordered by sloping alluvial fans. The region is 

also characterized by extreme aridity and extremely high air 

and soil temperatures. Winter snow is rare. Compared to the 

Cold Deserts to the north, most of the annual precipitation in 

these deserts falls during the summer months, contributing to 

a diversity of plants and animals. Desert scrub consisting of 

creosote bush and white bursage is common in the Mojave 

Desert and western and central Sonoran Desert. In the eastern 

Sonoran Desert, the vegetation consists of various palo verde 

and cacti species, and mixed scrub. The higher Chihuahuan 

Desert to the east consists of some desert grassland and large 

areas of arid shrubland dominated by creosote bush. Oaks, 

juniper, and pinyon woodlands occur on the higher mountains. 

Large parts of the Warm Deserts are Federally owned.

Urbanization was the primary projected type of 

LULC change in the Warm Deserts. In the A1B scenario, 

developed land was projected to increase by 119 percent 

between 2005 and 2050 with a projected increase of 

6,840 km2 of new urban‐industrial areas. Nearly all of the 

new developed land use was projected to be converted 

from the grasslands/ shrublands ecosystems, which were 

projected to decline by 2 percent, from 403,390 km2 in 

2005 to 395,350 km2 in 2050. The projected spatial pattern 

of urbanization was distributed heterogeneously across 

the landscape, with most expansion projected to occur 

adjacent to the Las Vegas, Nevada, Phoenix, Arizona, and 

Tucson, Arizona, metropolitan areas. Urban expansion 

was also projected to be common along the boundary of 

the Mojave Basin and Range and the Southern California 

Mountains near the Los Angeles, California, metropolitan 

area. Major environmental factors (limited moisture and high 

temperatures) potentially limit the expansion of agricultural 

lands throughout the Warm Deserts; however, small areas, 

generally near perennial streams, potentially could support 

the production of cultivated crops and hay/pasture land. 

These areas were projected to increase by 7 percent in the 

A1B scenario, from 11,340 km2 in 2005 to 12,130 km2 in 

2050. Forests and wetlands remained relatively unchanged 

throughout the projection period.
80 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

118°00'

118°00'

118°30'

118°30'

47°00'

47°00'

46°30'

A B

C D

0 10 20 KILOMETERS

0 10 20 MILES

Figure 6.10.

Marine West

Coast Forest

Map

area

Western

Cordillera

Warm Deserts

Mediterranean

California

Level II ecoregions

Cold

Deserts

Columbia Plateau

Snake River

EXPLANATION

Area projected to

 experience land-use

 or land-cover change

Land use and land cover

Water

Developed

Logging, national forest

Logging, other public land

Logging, private land

Mining

Barren

Deciduous forest

Evergreen forest

Level III ecoregion 

 boundary

Mixed forest

Grassland

Shrubland

Cultivated crops

Hay/pasture

Woody wetland

Herbaceous wetland

Snow/ice

Area projected to

 experience logging

Figure 6.10. Maps showing land use and land cover (LULC) in 2005 and a comparison of the A1B, A2, and B1 scenarios in 2050 for an 

intensively agricultural area along the Snake River in Washington in the Cold Deserts ecoregion. Changes were projected to be the 

result of either land-use change or forest clearcutting. A, LULC in 2005. B, Projected LULC change in the A1B scenario. C, Projected 

LULC change in the A2 scenario. D, Projected LULC change in the B1 scenario. 
Chapter 6 81

Area, in thousands of square kilometers

0

100

200

300

400

500

–10

–5

0

5

10

–10

–5

0

5

10

–10

–5

0

5

10

Figure 6–11.

Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other

A. Baseline ecosystem composition, 2005 B. Net change in ecosystem area–Scenario A1B

C. Net change in ecosystem area–Scenario A2 D. Net change in ecosystem area–Scenario B1

Figure 6.11. Charts showing the baseline composition of and 

projected net change in major ecosystems between 2005 and 

2050 in the Warm Deserts ecoregion for the final year of the 

baseline period and for each scenario. A, The percent of land 

area assigned to each of the major ecosystems at the end of the 

baseline period (2005). B, The projected net land-use- and landcover-change, in percent, between 2005 and 2050 for scenario 

A1B. C, The projected net land-use- and land-cover-change, in 

percent, between 2005 and 2050 for scenario A2. D, The projected 

net land-use- and land-cover-change, in percent, between 

2005 and 2050 for scenario B1. Forests that had been harvested 

(logged) were included within the forest ecosystem totals. The 

“other” ecosystem includes developed lands, mined lands, barren 

lands, and water. The large projected net changes in the “other” 

ecosystem were primarily attributed to projected increases in 

developed lands.

The A2 scenario had the smallest projected increase in 

new developed land of all the scenarios. New urban areas were 

projected to increase 71 percent, from 5,750 km2 in 2005 to 

9,810 km2 in 2050. The result is a projected 1 percent decline 

in grasslands/shrublands (a projected loss of 4,860 km2). 

All of the other ecosystems remained relatively stable 

throughout the projection period (fig. 6.11). In the B1 scenario, 

developed land was projected to increase by 86 percent, 

rising to 10,710 km2 by 2050. As in the economically 

oriented scenarios, the vast majority of the projected new 

developed land resulted from the projected conversion of 

grasslands/ shrublands. Overall, grassland/shrublands were 

projected to decline by 5,340 km2, a loss of 1 percent of their 

area from 2005. Forests, agricultural lands, and wetlands were 

projected to remain relatively stable (fig. 6.11). Figure 6.12

shows both the initial and the projected urbanization near Las 

Vegas, Nevada, in all three scenarios.
82 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Henderson

Las Vegas

115°00'

115°30' 115°00'

36°30'

36°00'

36°00'

Mojave Basin and Range

Central Basin and Range

A B

C D

0 10 20 KILOMETERS

0 10 20 MILES

Figure 6–12.

Marine West

Coast Forest

Map

area

Western

Cordillera

Warm Deserts

Mediterranean

California

Level II ecoregions

Cold Deserts

EXPLANATION

Area projected to

 experience land-use

 or land-cover change

Land use and land cover

Water

Developed

Logging, national forest

Logging, other public land

Logging, private land

Mining

Barren

Deciduous forest

Evergreen forest

Level III ecoregion 

 boundary

Mixed forest

Grassland

Shrubland

Cultivated crops

Hay/pasture

Woody wetland

Herbaceous wetland

Snow/ice

Area projected to

 experience logging

Figure 6.12. Maps showing land use and land cover (LULC) in 2005 and a comparison of the A1B, A2, and B1 scenarios in 2050 for the 

Las Vegas, Nevada, area in the Warm Deserts ecoregion. Changes were projected to be the result of either land-use change or forest 

clearcutting. A, LULC in 2005. B, Projected LULC change in the A1B scenario. C, Projected LULC change in the A2 scenario. D, Projected 

LULC change in the B1 scenario.
Chapter 6 83

6.3.2.5. Mediterranean California

The Mediterranean California level II ecoregion includes 

three unique level III ecoregions in California: the Southern 

and Central California Chaparral and Oak Woodlands (referred 

to herein as “Oak Woodlands” for simplicity), the Central 

California Valley, and the Southern California Mountains. The 

ecoregion is distinguished by its warm, mild Mediterranean 

climate with alternating wet and dry seasons. There is great 

variability in annual precipitation, and extreme droughts are 

not uncommon. The shrubland vegetation of chaparral mixed 

with areas of grassland and oak savanna is prone to wildland 

fires. The ecoregion has several agriculturally productive 

valleys and contains a high population (over 30 million 

people) in extensive urban agglomerations. Low coastal 

mountain ranges and the Sierra Nevada foothills surround the 

broad San Joaquin and Sacramento Valleys. Higher mountain 

ranges are located in the southern part of the ecoregion, 

which includes large areas of Federally owned land. In the 

larger valleys, the hydrological and ecological systems have 

been greatly altered by widespread agriculture and some 

sprawling urban and suburban development. Recent historical 

LULC change has been characterized most visibly by rapid 

urbanization. The Oak Woodlands and the Central California 

Valley combined contain most of the population of California, 

which has seen a 37 percent increase in the State’s developed 

landscape since 1973 (Sleeter and others, 2011). Demand for 

agricultural land has also been an important component of 

LULC change in the ecoregion despite remaining relatively 

stable in terms of total area. Agricultural land in some parts 

of the ecoregion expanded while others experienced losses 

(Sleeter and others, 2011). 

Urban development was the primary type of projected 

LULC change in the ecoregion in all three of the scenarios. In 

the A1B scenario, developed land was projected to increase 

89 percent, from 13,160 km2 in 2005 to 24,820 km2 in 2050. 

New developed land was projected to increase primarily in the 

Oak Woodlands (7,650 km2) and the Central California Valley 

(3,040 km2). The low-lying valleys of the Oak Woodlands and 

periphery of large urban areas in the Central California Valley 

were projected to be the main locations for urban expansion. 

Grasslands/shrublands were projected to experience the largest 

change of any LULC class, declining 17 percent between 2005 

and 2050 (from a baseline of 74,300 km2) while forests and 

wetlands were projected to remain relatively stable (fig. 6.13). 

Agricultural lands were projected to increase by 1,320 km2 by 

2050 (from 41,050 km2 in 2005); however, projected changes 

involving agricultural lands affected a much greater area than 

is reflected in the net change projections alone. For example, 

4,750 km2 of agricultural land was projected to be converted 

to developed land, whereas only 870 km2 of agricultural 

land was projected to be converted to grasslands/ shrublands. 

Conversely, the projected increased demand for new 

agricultural land resulted in a projected 6,700 km2 of 

grassland/shrubland converting into new cultivated croplands 

or hay/pasture lands. 

In the A2 scenario, developed land was projected 

to increase by 62 percent, from 13,160 km2 in 2005 to 

21,380 km2 in 2050. The location of new developed land 

was projected to be generally in the same areas as in the 

A1B scenario, with the vast majority in the Oak Woodlands 

(62 percent) and Central California Valley (33 percent). New 

developed land was projected to increase by approximately 

450 km2 in the Southern California Mountains. The high 

demand for new developed land was projected to result in 

a 2 percent decline in agricultural lands (from 41,050 km2

in 2005 to 40,060 km2 in 2050) and an 8 percent decline 

in grasslands/shrublands (from 74,300 km2 in 2005 to 

67,390 km2 in 2050) (fig. 6.13). By 2050, 3,870 km2 of 

grasslands/shrublands and 4,200 km2 of agricultural land 

was projected to be converted to new developed land; 

however, like the A1B scenario, the projected net change 

masked overall projected rates of LULC change; 3,600 km2

of grasslands/ shrublands were projected to be converted 

into agricultural land, whereas 530 km2 of agriculture was 

projected to be converted into grasslands/shrublands. Forests 

and wetlands remained relatively stable (fig. 6.13).
84 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Despite dramatically different storylines, by 2050 the 

B1 scenario was projected to follow trends in LULC change 

that were similar to those in the A2 scenario. Developed 

land was projected to increase by 57 percent (7,500 km2), 

with most of the expansion projected to occur in the Oak 

Woodlands and Central California Valley. Nearly 4,940 km2

of grasslands/ shrublands were projected to be converted to 

developed lands, whereas 2,500 km2 of agricultural land 

was projected to be converted to developed land. By 2050, 

agricultural land was projected to decline by 3 percent, from 

41,050 km2 to 39,980 km2. Also similar to the A2 scenario 

was the projected 9 percent decline in grasslands/shrublands 

needed to meet the projected demand for new developed land 

and agricultural land. Forests remained relatively unchanged 

at approximately 29,950 km2. The greatest divergence 

from the economically oriented scenarios was the projected 

trend in wetlands. The strengthening of environmental 

protection in the B1 scenario resulted in a projected increase 

in wetlands of 62 percent, from approximately 910 km2 to 

1,470 km2. Figure 6.14 shows both the initial LULC and the 

projected modeling results for each scenario for an area near 

Sacramento, California, in the Central California Valley.

Figure 6–13.

Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other Forests Grasslands/

shrublands

Agricultural

lands

Wetlands Other

0

20

40

60

80

–15

–10

–5

0

5

10

15

–15

–10

–5

0

5

10

15

–15

–10

–5

0

5

10

15

A. Baseline ecosystem composition, 2005 B. Net change in ecosystem area–Scenario A1B

C. Net change in ecosystem area–Scenario A2 D. Net change in ecosystem area–Scenario B1

Figure 6.13. Charts showing the baseline composition of and 

projected net change in major ecosystems between 2005 and 2050 

in the Mediterranean California ecoregion for the final year of 

the baseline period and for each scenario. A, The percent of land 

area assigned to each of the major ecosystems at the end of the 

baseline period (2005). B, The projected net land-use- and landcover-change, in percent, between 2005 and 2050 for scenario 

A1B. C, The projected net land-use- and land-cover-change, in 

percent, between 2005 and 2050 for scenario A2. D, The projected 

net land-use- and land-cover-change, in percent, between 

2005 and 2050 for scenario B1. Forests that had been harvested 

(logged) were included within the forest ecosystem totals. The 

“other” ecosystem includes developed lands, mining lands, barren 

lands, and water. The large projected net changes in the “other” 

ecosystem were primarily attributed to projected increases in 

developed lands.
Chapter 6 85

!( !(

Davis

Woodland

Fairfield

Vacaville

Roseville

Sacramento

Citrus

Heights

West

Sacramento

121°30'

121°30'

122°00'

122°00'

39°00'

38°30'

38°30'

A B

C D

0 10 20 KILOMETERS

0 10 20 MILES

Figure 6.14.

Marine West

Coast Forest Western

Cordillera

Warm Deserts

Mediterranean

California

Level II ecoregions

Map area

Cold Deserts

Central California Valley Southern and Central

California Chaparral

and Oak Woodlands

EXPLANATION

Area projected to

 experience land-use

 or land-cover change

Land use and land cover

Water

Developed

Logging, national forest

Logging, other public land

Logging, private land

Mining

Barren

Deciduous forest

Evergreen forest

Level III ecoregion 

 boundary

Mixed forest

Grassland

Shrubland

Cultivated crops

Hay/pasture

Woody wetland

Herbaceous wetland

Snow/ice

Area projected to

 experience logging

Figure 6.14. Maps showing land use and land cover (LULC) in 2005 and a comparison of the A1B, A2, and B1 scenarios in 2050 for an 

area near Sacramento, California, in the Mediterranean California ecoregion. A, LULC in 2005. B, Projected LULC change in the A1B 

scenario. C, Projected LULC change in the A2 scenario. D, Projected LULC change in the B1 scenario. Changes were projected to be the 

result of either land-use change or forest clearcutting. 
86 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

0

1

2

3

4

2006 2010 2020 2030 2040 2050

Agreement, in percent

A1B-A2

Quantity

Allocation

Total

2006 2010 2020 2030 2040 2050

A1B-B1

Figure 6–15.

2006 2010 2020 2030 2040 2050

A2-B1

EXPLANATION

Figure 6.15. Graphs showing the quantity and allocation disagreement by scenario pair from 2006 to 2050. The total disagreement 

between scenario pairs is similar for A1B-A2, and A1B-B1 and smaller for A2-B1. Allocation disagreement makes up a higher proportion 

of total disagreement than does quantity disagreement for all scenario comparisons.

6.4. Validation and Uncertainty

A formal validation of the projected LULC changes is 

impossible because there is no reference data for a future time 

frame. Chapter 2 provides a summary of validation concerns 

for the LULC modeling they applied to the baseline period; 

however, the same quantity and allocation disagreement 

measures discussed in chapter 2 can be used to examine issues 

of uncertainty in the projected period of 2006 to 2050, and 

more specifically, to examine the sources of the differences 

between modeled scenarios (Pontius and Millones, 2012; Sohl, 

Sleeter, Zhu, and others, 2012). In this context, a quantity 

disagreement measure can be used to examine the differences 

in projected LULC proportions between scenarios, and an 

allocation disagreement measure can be used to examine 

differences in how the projected LULC changes are spatially 

allocated between scenarios.

In this assessment, the proportions of the projected 

LULC change in the scenarios themselves were used to frame 

overall uncertainties regarding future LULC proportions. 

Given that the FORE–SCE model can duplicate scenarioprescribed LULC proportions, there were no uncertainty 

issues related to the ability to accurately map the quantity 

of LULC change. Quantity disagreement was thus used to 

examine differences in the prescribed proportions of LULC 

change from the scenarios themselves. The spatial modeling 

component of the FORE–SCE model introduced allocation 

disagreement between scenarios in that the spatial pattern 

of change differed between scenarios even if the prescribed 

scenario LULC proportions were similar. An application 

of quantity and allocation disagreement measures to each 

scenario pair allowed for a determination of whether the 

differences between scenarios were because of the scenario 

LULC prescriptions themselves or were a result of the spatial 

modeling and the placement of LULC change.

The proportion of quantity disagreement and allocation 

disagreement varied by scenario pair (fig. 6.15). Total 

disagreement was lowest between the A2-B1 scenario pair, 

and higher but similar for the A1B-A2 and A1B-B1 pairs. 

Despite that similarity, quantity disagreement made up a 

much higher percentage of the total disagreement in the 

A1B-B1 scenario pair. In all of the scenario pairs, allocation 

disagreement made up a significantly higher proportion of 

the total disagreement than did quantity disagreement, which 

indicated that on a per-pixel basis, the differences between the 

spatially explicit scenarios were due more to the FORE–SCE 

spatial allocation model than to quantitative differences in 

the prescribed amounts of LULC change from the scenarios. 

These differences were expected, given the relatively low 

amount of LULC change projected to occur in the Western 

United States; however, the scenario-specific parameterization 

of the FORE–SCE model was a contributing factor. For 

example, assumptions were made that urban development 

will be more compact in the B1 scenario than in the two other 

scenarios, and the FORE–SCE model was parameterized 

accordingly for the individual scenarios. The parameterization 

of the spatial model thus affected the spatial allocation of 

change, and, as a result, the proportion of disagreement due 

to allocation. It is impossible to determine how much of the 

allocation disagreement is due to the random nature of the 

placement of LULC change versus the difference in model 

parameterization between scenarios. Overall, it is clear that the 

A1B and B1 scenarios were most dissimilar when accounting 

for the quantified scenarios, as that scenario pair exhibited the 

highest overall quantity disagreement.
Chapter 7. Climate Projections Used for the Assessment 

of the Western United States

By Anne Wein1, Todd J. Hawbaker2, Richard A. Champion1, Jamie L. Ratliff1, Benjamin M. Sleeter1, and

Zhiliang Zhu3

1U.S. Geological Survey, Menlo Park, Calif.

2

 U.S. Geological Survey, Denver, Colo.

3U.S. Geological Survey, Reston, Va.

7.1. Highlights

• Models of projected climate change were used in this 

assessment to further interpret the effects of climate 

change on the potential for carbon sequestration 

and greenhouse-gas (GHG) emissions in terrestrial 

ecosystems in the ecoregions of the Western United 

States. Climate-change data were used to support two 

modeling exercises: future potential wildland‐fire 

emissions (chapter 8 of this report) and future potential 

carbon storage and sequestration (chapter 9 of 

this report).

• Climate-change data were represented in three general 

circulation models (GCMs) for each of three scenarios 

(A1B, A2, B1). The models of wildland fires and 

the biogeochemical modeling of carbon and GHGs 

used different sources of downscaling for the same 

GCMs because of the tasks’ unique requirements. The 

projected patterns of precipitation differed between the 

two sources, particularly in mountainous areas. 

• The models indicated a projected seasonal increase 

in mean temperature throughout the Western United 

States. Warming was projected to be most prevalent in 

summer and fall and in the eastern part of the Western 

United States. 

• The projected warming was greater in scenarios A1B 

and A2; the MIROC 3.2-medres model projected 

the most warming and the CSIRO–Mk3.0 model 

projected the least. The projected increases in seasonal 

temperature extremes (minimums and maximums) 

generally followed patterns of projected increases in 

mean temperature. 

• The projected precipitation patterns were highly 

variable among the GCMs, scenarios, seasons, and 

within the level II ecoregions, which necessitated the 

analyses of variabilities within each ecoregion.

• The variability in temperature and precipitation 

changes of the GCMs made the ranges of climate 

change for each scenario less distinct.

7.2. Introduction

Climate-change projections are required for modeling 

future potential ecosystem properties and processes. This 

chapter characterizes the baseline climate data and the projected 

climate-change data from general circulation models (GCMs); 

these data were used in this assessment for the wildland-fireemission modeling discussed in chapter 8 and for the terrestrial 

ecosystem carbon-storage and GHG-flux modeling discussed in 

chapter 9. The relation between this chapter and other chapters 

of this report is shown in figure 1.2 of chapter 1 of this report, 

where climate data is featured in the “input data” and “climate 

projections” boxes of the diagram.

The term “climate change” refers to the changes in daily 

and weekly weather over months, seasons, centuries, and 

millennia. The climate affects the carbon cycle in terrestrial 

and aquatic systems through biogeochemical processes and 

natural disturbances (such as wildland fires), and also influences 

where land-use and land-cover (LULC) changes occur. This 

assessment sought to answer two questions related to the effects 

of climate change on carbon sequestration and GHG fluxes: 

(1) What are the projected potential changes to the critical 

climate variables within the ecoregions of the Western United 

States, and (2) What are the uncertainties for the climate-change 

projections in each of the ecoregions? 

The climate-change data described here, along with the 

projected LULC scenarios (chapter 6) were aligned with the 

Intergovernmental Panel on Climate Change’s Special Report 

on Emission Scenarios (IPCC–SRES; Nakicenovic and others, 

2000). Although multiple scenarios (A1B, A2, and B1) provided 

the emission projections, the assessment used outputs from 

the GCMs, which were forced by the scenarios to capture the 

uncertainties of the analyses. The three GCMs used in this 

study are The Third Generation Coupled Global Climate Model 

of the Canadian Centre for Climate Modelling and Analysis 

(CCCma CGCM 3.1), Australia’s Commonwealth Scientific and 

Industrial Research Organisation Mark 3.0 (CSIRO–Mk3.0) 

model, and the Model for Interdisciplinary Research on Climate 

version 3.2, medium resolution (MIROC 3.2-medres). The 

selection of GCMs represents a range of projected climate 

change that was constrained by the availability of suitably 

downscaled versions and resources to simulate multiple effects 

of climate change.
88 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The GCMs are mathematical representations of 

atmospheric, oceanic, cryospheric, and land-surface processes 

that express how those processes interact and respond to 

changes in GHG concentrations (Randall and others, 2007; U.S. 

Climate Change Science Program (CCSP), 2008). The GCMs 

subdivide the world into volumetric pixels (voxels) representing 

the layers of the atmosphere, land, and ocean at regularly spaced 

locations. The GCM outputs may include hourly, daily, and 

monthly estimates of temperature, precipitation, air pressure, 

wind, cloud cover, soil moisture, snow, humidity, or short- and 

long-wave fluxes of solar radiation. According to McAvaney and 

others (2001), projected surface-air temperatures generally have 

less uncertainty than projected precipitation, whereas projected 

cloud cover and humidity have the greatest uncertainty. Each 

GCM made different assumptions about global energy budgets; 

therefore, no single GCM projection was considered to be valid 

on its own and multiple models complement each other (Pierce 

and others, 2009). The components of this assessment that relied 

on GCM outputs incorporated data from multiple GCMs to help 

characterize uncertainties in climate projections.

The GCM outputs generally were produced at a coarse 

spatial resolution on the order of 1° to 3°, and spatial 

downscaling was performed to produce the resolution required 

for regional analyses. Fowler and others (2007) observed that, in 

general, downscaled temperature variables were more consistent 

with the original data than downscaled precipitation variables; 

downscaled winter climate variables were more consistent with 

the original data than downscaled summer climate variables; 

and downscaled wetter climate variables were more consistent 

with the original data than downscaled drier climate variables. 

These temperature and precipitation observations were not 

confirmed in a separate study for the Western United States 

(Pierce and others, 2009). Temperature and precipitation were 

the most common variables used in this assessment when the 

influence of climate change on carbon cycling was simulated. 

Other climate-related variables, such as humidity, were then 

derived from temperature and precipitation. Therefore, the 

discussion of potential climate change focuses on temperature 

and precipitation variables. 

Climate and weather input data were required in 

order to model both wildland fires (chapters 3 and 8) and 

biogeochemical processes of carbon and GHG fluxes (chapters 5

and 9); however, two sources of downscaled climate and 

weather data were used for the same GCMs because of the 

unique requirements of the respective models. 

The wildland-fire analyses (chapters 3 and 8) required 

daily weather data, including temperature, precipitation, 

relative humidity, and wind speeds for both the baseline and 

future time periods. The daily weather data were originally 

measured at weather stations, but were interpolated to 1/8° 

spatial resolution (approximately 12 km) for the conterminous 

United States (Maurer and others, 2002). These data span the 

years 1950 to 2010 and include minimum and maximum daily 

temperature and daily precipitation. The afternoon wind speeds 

and directions were taken from the 1/3° (approximately 32-km 

resolution) North American Regional Reanalysis data (Mesinger 

and others, 2006) and were joined to the daily temperature and 

precipitation data assembled by Maurer and others (2002). To 

model projected future wildland fires and emissions, the data 

from the three GCMs and the three climate-change scenarios 

were corrected for biases and downscaled to the baseline 

weather data (Maurer and others, 2002, 2007). Figures 7.1 and 

7.2 show the baseline (1970–1999) mean daily temperature (in 

degrees Celsius, °C) and total precipitation (in centimeters) by 

season in both map and graph formats, which are based on data 

from Maurer and others (2002).

Winter Spring Summer Fall

Temperature Precipitation

Temperature, in degrees Celsius

EXPLANATION

Figure 7–1.

Precipitation, in centimeters

–15–20 –5 0 5 10 15 20 25 30 35 40 0 6 12 24 36 48 60

Figure 7.1. Maps showing the baseline (1970–1999) seasonal mean daily temperature (in degrees Celsius, °C) and total precipitation (in 

centimeters) by season. Data were from Maurer and others (2002). Winter included December, January, and February; spring included 

March, April, and May; summer included June, July, and August; and fall included September, October, and November.
Chapter 7 89

Figure 7–2.

Mean daily temperature,

in degrees Celsius

−10 0 10 20 30

Total precipitation,

in centimeters

0 20 40 60 80 100 120

Southern California Mountains

Southern and Central California

Chaparral and Oak Woodlands

Central California Valley

Sonoran Basin and Range

Mojave Basin and Range

Madrean Archipelago

Chihuahuan Deserts

Wyoming Basin

Snake River Plain

Northern Basin and Range

Columbia Plateau

Colorado Plateaus

Central Basin and Range

Arizona-Mexico Plateau

Willamette Valley

Puget Lowland

Coast Range

Wasatch-Uinta Mountains

Southern Rocky Mountains

Sierra Nevada Mountains

Northern Rockies

North Cascades

Middle Rockies

Klamath Mountains

Eastern Cascades—Slopes and Foothills

Western

Cordillera

Level II ecoregion Level III ecoregion Temperature Precipitation

Marine

West Coast

Forest

Cold

Deserts

Warm

Deserts

Mediterranean

California

Cascades

Canadian Rockies

Blue Mountains

Arizona-New Mexico Mountains

EXPLANATION

Season

Winter Spring Summer Fall

Figure 7.2. Chart showing the baseline summaries of mean daily temperature (in degrees Celsius, °C) and total precipitation (in 

centimeters) by season and grouped by both level II and level III ecoregions. Data were from Maurer and others (2002).
90 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The biogeochemical modeling framework (chapter 9

of this report) required climate data that characterized the 

monthly mean of daily minimum and maximum temperatures 

and the monthly precipitation. For both the model testing 

period (that is, model spin up) from 1992 to 2000 and the 

baseline time period (2001–2005), these data were derived 

from the PRISM climate dataset (Daly and others, 2000; 

PRISM Climate Group, 2012) at 4-km spatial resolution. The 

projected monthly mean of daily minimum and maximum 

temperatures and the projected monthly precipitation were 

provided by the three GCMs under all three scenarios 

(Joyce and others, 2011). Change factors were calculated 

at the original resolution of the GCMs relative to the 1961 

to 1990 normals, which were then spatially downscaled 

using ANUSPLIN software (Hutchinson, 2010) and added 

to (for temperatures) or multiplied by (for precipitation) the 

historical normals to produce the future climate projections at 

1/12° resolution (approximately 10 km).

7.3. Climate Patterns 

Visualizations of seasonal baseline climate patterns 

and potential future changes are presented in figure 7.3 for 

each GCM and each climate-change scenario used in the 

assessment. Descriptions are provided to the extent possible 

for within-ecoregion variations by using the level III ecoregion 

names (EPA, 1999); please refer to figure 1.1 of chapter 1

of this report for the geographic locations of the level II and 

III ecoregions. The seasonal aggregation of results reduced 

the information about monthly variations while preserving 

information aligned with the seasonal carbon cycles of 

winter carbon sources and summer carbon sinks (Miller, 

2008). The climate variables included the temperature and 

precipitation variables used in the disturbance and terrestrial 

biogeochemical components: mean daily temperature, monthly 

minimum and maximum temperatures, and total precipitation. 

7.3.1. Baseline Climate Patterns of the Western 

United States

Assessments of climate change are usually made 

relative to a baseline period that provides benchmark climate 

summaries. The choice of baseline periods is somewhat 

arbitrary, but for climate summaries, a 30-year period is 

desirable. For this general overview of potential long-term 

climate changes, the baseline period was the recent and 

relatively stable (climatically) period of 1970 to 1999.

The modeled baseline data indicated that the baseline 

mean daily temperatures and total precipitation had high 

spatial and seasonal variability across the Western United 

States (figs. 7.1 and 7.2). Summer temperatures were most 

extreme in the Warm Deserts level II ecoregion, where mean 

daily summer temperatures were as high as 31°C in the 

Sonoran Basin and Range level III ecoregion. In contrast, the 

Western Cordillera level II ecoregion tended to include the 

coldest winter temperatures, with mean daily temperatures 

reaching as low as −10°C in the Middle Rockies level III 

ecoregion and −7°C in the Southern Rockies and WasatchUinta Mountains level III ecoregions. The Wyoming Basin 

level III ecoregion in the Cold Deserts level II ecoregion 

had the greatest range of seasonal temperatures, with a 

24°C difference between summer and winter. In other level 

II ecoregions, such as the Marine West Coast Forest and 

Mediterranean California, the seasonal temperature variability 

was relatively low and temperatures remained above freezing 

for most of the year.

The Marine West Coast Forest level II ecoregion received 

extreme precipitation, up to an average of 1,841 millimeters 

per year (mm/yr). At the other extreme, the annual 

precipitation in the Warm Deserts and Cold Deserts level II 

ecoregions averaged only 268 and 313 mm/yr, respectively. 

For most of the level II ecoregions in the Western United 

States, the majority of the precipitation fell primarily during 

the winter, with the spring and fall receiving lesser amounts. 

Summer tended to be the driest season in most areas except in 

the Warm Deserts level II ecoregion.

7.3.2. Projected Climate Patterns of the Western 

United States

The climate projections for 2040 to 2069 were 

compared with the baseline data from 1960 to 1999 in order 

to capture gross patterns of climate change. The variability 

in climate-change projections appeared to be greater among 

the GCMs than among the three IPCC–SRES scenarios. The 

maps in figure 7.3 show the projected changes in mean daily 

temperatures and mean total precipitation, by season, scenario, 

and GCM. The graphs in figure 7.4 show the projected 

changes in mean daily temperature and precipitation, by 

season for each ecoregion. The maps and graphs were based 

on data from Maurer and others (2007). All of the GCMs 

projected climate warming throughout the entire region. The 

projected warming was most pronounced in fall and summer; 

however, in the northern and central Columbia Plateau and 

Northern Basin and Range (of the Cold Deserts) and the Blue 

Mountains and Northern Rockies (of the Western Cordillera), 

the greater projected increases in mean temperature occurred 

in the winter and were associated mostly with projected 

increases in the mean winter minimum temperatures rather 

than projected increases in the mean winter maximum 

temperatures. The least amount of projected temperature 

change occurred in the spring for all ecoregions, with the 

exceptions of (1) the Warm Deserts and (2) the Arizona-New 

Mexico Mountains in the southernmost part of the Western 

Cordillera ecoregion, where the least amount of temperature 

change occurred in the winter. 
Chapter 7 91

Scenario A1B

Temperature change

Scenario A2

Precipitation change

Scenario B1

Winter Spring Summer Fall

CCCMA CGCM 3.1 CSIRO–Mk3.0 MIROC 3.2–medres CSIRO–Mk3.0 MIROC 3.2–medres CSIRO–Mk3.0 MIROC 3.2–medres CCCMA CGCM 3.1 CCCMA CGCM 3.1

Winter Spring Summer Fall

Temperature change, in degrees Celsius

Figure 7–3.

Precipitation change, in centimeters

–2 –1 0 1 2 3 4 8 10 –7.5 –5 –2.5 –0.5 0 0.5 2.5 5 7.5

EXPLANATION

Figure 7.3. Maps showing the projected changes in mean daily temperature (in degrees Celsius, °C) and total 

precipitation (in centimeters) by season, calculated using the difference in mean values from 2040 to 2069 and from 

1970 to 1999. Data were from Maurer and others (2007).
92 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Figure 7–4.

Mean daily temperature,

in degrees celsius

0 1 2 3 4 5

Seasonal precipitation,

in centimeters

−20 −10 0 10 20

Western

Cordillera

Level II ecoregion Level III ecoregion Temperature change Precipitation change

Marine

West Coast

Forest

Cold

Deserts

Warm

Deserts

Mediterranean

California

Southern California Mountains

Southern and Central California

Chaparral and Oak Woodlands

Central California Valley

Sonoran Basin and Range

Mojave Basin and Range

Madrean Archipelago

Chihuahuan Deserts

Wyoming Basin

Snake River Plain

Northern Basin and Range

Columbia Plateau

Colorado Plateaus

Central Basin and Range

Arizona-Mexico Plateau

Willamette Valley

Puget Lowland

Coast Range

Wasatch-Uinta Mountains

Southern Rocky Mountains

Sierra Nevada Mountains

Northern Rockies

North Cascades

Middle Rockies

Klamath Mountains

Eastern Cascades—Slopes and Foothills

Cascades

Canadian Rockies

Blue Mountains

Arizona-New Mexico Mountains

EXPLANATION

Season Scenario

Winter Spring Summer Fall

B1

A1B

A2

Figure 7.4. Chart showing summaries of the projected seasonal changes in mean daily temperature (in degrees Celsius, °C) and 

total precipitation (in centimeters) by season and grouped by both level II and III ecoregions for all general circulation models and 

scenarios. Squares represent the A1B scenario, circles represent the A2 scenario, and triangles represent the B1 scenario. Data 

were from Maurer and other (2007).
Chapter 7 93

Overall, seasonal warming was projected to be greatest 

under the A1B and A2 scenarios and least under the B1 

scenario. There was variability in the projected temperature 

changes among the GCMs. The greatest projected increases 

in mean temperature were from the MIROC 3.2-medres 

model for the A1B and A2 scenarios in the eastern parts of 

the Western United States. Specifically, the projected seasonal 

mean temperature exceeded 4°C during the nonwinter 

seasons in the Middle Rockies, Wasatch-Uinta Mountains, 

Southern Rockies, and Arizona-New Mexico Mountains in 

the eastern Western Cordillera ecoregion; the Wyoming Basin, 

Colorado Plateaus, and Arizona-New Mexico Plateau in the 

Cold Deserts ecoregion; and the Chihuahuan Deserts in the 

Warm Deserts ecoregion. Similarly, the greatest projected 

increases in mean seasonal maximum temperatures of 4°C 

to 6°C occurred in these same ecoregions during nonwinter 

months, particularly in the summer. In contrast, the CSIRO–

Mk3.0 model projected the smallest temperature increases. In 

particular, the projected change in mean spring temperature 

from the CSIRO–Mk3.0 model for the B1 scenario was less 

than 0.5°C in the Marine West Coast Forest ecoregion and 

parts of adjacent regions and in the nearby Eastern Cascades—

Slopes and Foothills in the Western Cordillera ecoregion.

Across all of the climate-change scenarios and GCMs, 

the variability in the projected warming (as measured by the 

standard deviation) was greatest in the eastern ecoregions 

of the Western United States and corresponded largely with 

those ecoregions where relatively large increases in mean 

and maximum temperatures were projected and least in the 

western ecoregions located in California and western Oregon 

and Washington. 

The fire-disturbance-modeling data source presented 

distinct precipitation change patterns in geographical areas 

of the Western United States. Table 7.1 summarizes these 

patterns of mean change from all the scenarios and GCMs in 

terms of level II and level III ecoregions. In this dataset, only 

the Marine West Coast Forest and Mediterranean California 

level II ecoregions had a consistent projected seasonal 

precipitation change pattern across GCMs and scenarios. 

The projected precipitation patterns varied geographically 

within the other level II ecoregions. Overall, the projected 

increases in mean seasonal precipitation occurred in the 

northern and western portions of the Western United States, 

especially in the winter, spring, and fall; however, projected 

summer precipitation tended to decrease in these areas. In the 

southern and eastern portions of the Western United States, 

precipitation was projected to decrease during most seasons. 

In regions where mean seasonal precipitation was projected to 

decrease, the reductions were most prevalent during the spring 

and winter (in the west) and during the fall (in the east). 

The greatest precipitation reductions were from the 

MIROC 3.2-medres model. The projected reductions 

occurred mostly in winter, but also in the spring across all 

climate-change scenarios in the Mediterranean California 

ecoregion and in the Sierra Nevada Mountains in the Western 

Cordillera ecoregion. The projected decreases in mean 

seasonal precipitation ranged from 7 to 24.5 cm, with the 

greatest projected decrease occurring in the Sierra Nevada 

Mountains. Across all of the GCMs, the greater projected 

precipitation decreases and lesser projected precipitation 

increases were associated with the B1 scenario. Conversely, 

the greatest projected seasonal precipitation increases of 

10 to 22 cm were associated most often with the A1B and A2 

scenarios and by the CCCma CGCM 3.1 model in the winter 

and fall in the Marine West Coast Forest and in the level III 

ecoregions within the northern part of the Western Cordillera. 

The smallest precipitation changes were projected to occur in 

the central Cold Deserts and in the adjacent Mojave Basin and 

Range in the Warm Deserts. In relative terms, however, the 

Warm Deserts and adjacent level III ecoregions were projected 

to be most affected by proportionate decreases in precipitation 

across all seasons, scenarios, and GCMs. Decreases in the 

mean winter and spring precipitation of more than 40 percent 

were projected by the MIROC 3.2-medres model in these 

ecoregions. Conversely, the noncoastal ecoregions to the 

north were projected to receive relatively more precipitation 

(increases of more than 20 percent in nonsummer months) 

across all scenarios and GCMs (in particular, the CCCma 

CGCM3.1 model). 

In contrast to the projected mean temperature change, 

the projected mean seasonal precipitation changes from 

the two climate data sources diverged in some regions with 

both negative and positive change. An examination of the 

terrestrial biogeochemical climate-data source revealed some 

differences in the climate-change patterns that were mostly 

explainable in terms of the level II ecoregions. In particular, 

the mean seasonal precipitation was projected to decrease in 

all seasons, notably spring and winter, in all of the Western 

Cordillera level III ecoregions (except for the Arizona-New 

Mexico Mountains), the Coast Range of the Marine West 

Coast Forest, and the Northern Basin and Range of the 

Cold Deserts. Where the projected increases in mean winter 

precipitation were observed above in table 7.1, projected 

decreases in winter precipitation prevailed, with the greatest 

projected decreases in mean winter precipitation occurring 

in the Canadian Rockies, Sierra Nevada Mountains, and 

Klamath Mountains, which presented a disagreement with 

the wildland-fire climate projections of up to 27 cm of mean 

winter precipitation change. Conversely, for the Southern 

and Central California Chapparral and Oak Woodlands and 

the Central California Valley level III ecoregions within 

the Mediterranean California ecoregion, the reductions in 

average winter precipitation in the wildland-fire disturbance 

climate dataset contrasted with increases in average winter 

precipitation in the terrestrial biogeochemical climate datasets. 
94 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Similarly, the terrestrial biogeochemical climate-change data 

projected greater precipitation increases, including positive 

summer precipitation change, in the Puget Lowland and 

Willamette Valley when using the terrestrial biogeochemical 

climate-change data compared with the climate-change data 

related to wildland-fire disturbances. Finally, the terrestrial 

biogeochemical climate projections indicated less of a 

decrease in the mean winter precipitation and increases in the 

mean fall precipitation in the Southern California Mountains 

and Madrean Archipelago level III ecoregions. Otherwise, 

mostly in the Warm and Cold Deserts, the projected changes 

in precipitation patterns in the biochemical climate data 

were comparable to those described for the wildland-firedisturbance data. 

In addition, proportional seasonal precipitation changes 

differed between climate data sources. In the biogeochemical 

model’s climate data source, the A2 and A1B scenarios and the 

MIROC 3.2-medres and CCCma CGCM3.1 models indicated 

a projected precipitation decrease of approximately 40 percent 

in the Canadian Rockies during the winter, in the Southern 

Rockies and Arizona-New Mexico Mountains in the spring, 

and in the Madrean Archipelago in winter and spring. The 

B1 and A1B scenarios and mostly the CSIRO–Mk3.0 model 

indicated a projected seasonal mean precipitation increase of 

more than 30 percent in the Warm Deserts and Mediterranean 

California in all seasons except spring, and in the Central Basin 

and Range and Colorado Plateaus of the Cold Deserts during 

the summer.

Table 7.1. Projected changes in precipitation patterns derived from averaging the results from all the scenarios and general 

circulation models. 

[Data from Maurer and others (2007)]

Projected change in precipitation pattern Affected level II ecoregions Affected level III ecoregions

Increases in winter, spring, and fall Marine West Coast Forest All.

Western Cordillera Cascades, North Cascades, Blue Mountains, 

Northern Rockies, Canadian Rockies.

Cold Deserts Columbia Plateau.

Increases in winter and fall Western Cordillera Klamath Mountains, East Cascades—Slope and 

Foothills.

Increases in winter and spring Western Cordillera Middle Rockies.

Cold Deserts Wyoming Basin.

Increases in winter Western Cordillera Wasatch-Uinta Mountains, Southern Rockies.

Cold Deserts Northern Basin and Range.

Decreases in all seasons; greatest decrease in 

winter and spring

Mediterranean California All.

Western Cordillera Sierra Nevada Mountains.

Warm Deserts Mojave Basin and Range, Sonoran Basin and 

Range.

Decreases in all seasons; greatest decrease in 

fall and spring

Cold Deserts Central Basin and Range, Colorado Plateaus, 

Arizona-New Mexico Plateau.

Decreases in all seasons; greatest decrease in 

fall, spring, and winter

Western Cordillera Arizona-New Mexico Mountains.

Warm Deserts Madrean Archipelago, Chihuahuan Deserts.
Chapter 7 95

7.4. Summary and Discussion of 

Caveats Using the Climate Data

Climate data was integral to this assessment and 

for scenario evaluation. The use of projected future 

climate‐change data, however, contributed to uncertainties 

in the assessment results. The following caveats should be 

considered:

• The wildland-fire modeling (chapter 8) and 

biogeochemical modeling (chapter 9) relied heavily 

on weather and climate data to characterize baseline 

conditions and estimate future potential changes, 

but several different climate and weather datasets 

were used to complete the simulations. The baseline 

wildland-fire-disturbance data consistently indicated 

a wetter baseline climate than did the biogeochemical 

baseline data; however, the discrepancies that occurred 

in the projected changes of precipitation patterns, in 

mountainous areas in particular, were attributable to 

differences in the downscaled climate projections. In 

mountainous areas, the interpolation of precipitation 

patterns have been more challenging because of 

the orographic effects of the topography (Daly and 

others, 1993).

• Although future LULC allocation algorithms can 

incorporate climate-change data to allow for adaptation 

(Mu and others, 2012), the dynamic interactions 

between climate and LULC change is currently an 

unsolved problem (Mendelsohn and Dinar, 2009). 

For example, the IMAGE 2.2 model was the first to 

incorporate the consequences of the IPCC–SRES 

emissions scenarios on the carbon cycle in combination 

with the dynamically modeled LULC-change maps, 

but the biogeophysical effects of LULC change were 

not accounted for in that simple climate model (Sitch, 

2005). On the other hand, although the LULC-change 

scenarios developed for this assessment (chapter 6) did 

not directly incorporate GCM data, an indirect effect of 

climate change on the viability and, therefore, resolved 

demand for future LULC is inherent in the use of the 

IMAGE 2.2 global model (Image Team, 2001) results. 

The IMAGE 2.2 model was developed on the basis of 

an alternative GCM (Hadley Centre Coupled Model 2, 

HadCM2; Johns and others, 1997). The projected 

LULC allocations have been further complicated by 

the projected seasonal changes in precipitation and 

snowmelt and the implications for irrigation (for 

example, Vano and others, 2010). This assessment 

assumes that agricultural irrigation practices were 

static despite changes in precipitation patterns. 

• The assessment of carbon cycling in inland aquatic 

ecosystems (chapter 10) was for the baseline time 

period only; projections were not made for future 

carbon fluxes. The incorporation of climate change 

into the aquatic system components would require 

water-discharge projections from downscaled climate 

predictions and the application of flow-generation 

models, such as the Precipitation-Runoff Modeling 

System (PRMS, Leavesley and others, 1983). 

• In addition to the documented uncertainties in the 

GCM outputs, the challenges of using GCMs for 

modeling effects of climate change in biogeochemical 

and wildland-fire models included the number of GCM 

datasets to use in the model runs. In their study of 

the Western United States, Pierce and others (2009) 

emphasized the importance of having ensembles of 

climate model runs with enough realizations to reduce 

the effects of the natural internal climate variability; 

they determined that a projected mean derived from a 

multimodel ensemble was superior to a projected mean 

derived from just one individual model because of the 

cancellation of offsetting errors and they advised that 

five models may be sufficient to derive an appropriate 

projected mean. There are practical and computational 

limitations, however, to using multiple GCMs; 

therefore, only three were used for this assessment.

• The projected potential changes in seasonal 

temperatures and precipitation were characterized 

in this chapter to provide a general understanding 

of when and where climate shifts may occur. Other 

relevant carbon-cycling models, such as the Palmer 

Drought Severity Index (PDSI), were not calculated. 

The wildland-fire projections, however, relied 

heavily on fuel-moistures data for live and dead 

biomass, which are a function of temperature, relative 

humidity, precipitation, and the delayed change in 

moisture conditions.
96 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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Chapter 8. Projected Future Wildland Fires and 

Emissions for the Western United States

By Todd J. Hawbaker1 and Zhiliang Zhu2

8.1. Highlights

• Wildland-fire occurrence and greenhouse-gas 

emissions increased in the Western United States under 

all of the climate-change scenarios considered in this 

assessment.

• The projected median amount of area burned annually 

from 2041 to 2050 was 31 to 66 percent greater than 

the median amount of area burned annually during 

the baseline years from 2001 to 2008 (12,136 km2, 

reported in chapter 3). The median annual emissions 

were projected to increase 28 to 56 percent from 

the baseline median annual emissions, which were 

approximately 41.0 TgCO2-eq/yr (11.2 TgC/yr) 

(reported in chapter 3).

• Extreme fire years are projected to become more 

extreme. The 95th percentile of the amount of area 

burned annually was projected to increase 79 to 

95 percent from the baseline conditions of 2001 to 

2008 (23,261 km2, reported in chapter 3), and the 

95th percentile of annual wildland-fire emissions 

was projected to increase 73 to 150 percent from 

the baseline 95th percentile estimate, which was 

approximately 65.0 TgCO2-eq (17.7 TgC/yr) (reported 

in chapter 3).

8.2. Introduction

An assessment of the area burned by, the severity of, 

and the emissions from wildland fires during the baseline 

period (2001 to 2008) for the Western United States is 

presented in chapter 3 of this report; this chapter focuses on 

the projected future extent and severity of, and emissions from 

wildland fires for the period 2041 to 2050. Modeling of future 

wildland-fire characteristics required input from the baseline 

wildland-fire assessment (chapter 3) and projected future 

climate changes (chapter 7). The wildland-fire projections 

described in this chapter were provided as input into the 

modeling of projected future terrestrial carbon storage and 

greenhouse-gas fluxes described in chapter 9. The relations 

between this chapter and others are depicted in figure 1.2 of 

chapter 1 of this report. 

Wildland-fire regimes are a function of the interactions 

between vegetation, land use, and, ultimately, the climate 

(Swetnam and Betancourt, 1990; Gedalof and others, 2005; 

Westerling and others, 2006; Falk and others, 2007). A 

changing climate may result in changes in wildland-fire 

regimes, including their occurrence, severity, and frequency. 

Hessl (2011) outlined the primary pathways through which 

climate change may alter wildland-fire regimes, including 

(1) altered fuel conditions, such as a change in fuel moisture; 

(2) altered fuel loads; and (3) changes in ignitions. The 

effects of climate change on wildland-fires in the Western 

United States are expected to be significant and result in 

changes in weather patterns that would alter (1) ignition 

patterns, (2) wildland-fire behavior, and (3) to a lesser extent, 

the distribution of vegetation. No single study, however, 

has addressed all three types of changes simultaneously 

at the scale required by this assessment (Flannigan and 

others, 2009).

Potential shifts in weather patterns and wildland-fire 

behavior, as indicated by variables such as the Keetch-Byram 

Drought Index (Y. Liu and others, 2010), the seasonal severity 

rating computed by Flannigan and others (2000), and an 

energy-release component (ERC) (T.J. Brown and others, 

2004), are influenced by climate change and could increase 

the duration of the wildland-fire season and the severity 

of conditions under which fires may burn. Climate-driven 

changes in ignition patterns are not as well understood, but 

lightning ignitions were projected to increase as much as 

44 percent across the United States under a scenario where 

the atmospheric carbon-dioxide concentration was doubled 

(Price and Rind, 1994). Regional changes may be greater; for 

1U.S. Geological Survey, Denver, Colo.

2U.S. Geological Survey, Reston, Va.
98 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

instance, Westerling and Bryant (2008) examined wildland-fire 

risk (the probability of a >200-hectare (ha) fire) in California, 

Nevada, and parts of neighboring States. They compared the 

observed risk from 1961 to 1990 with the projected risk for 

2070 to 2099 using a logistic regression under the A2 and 

B1 climate-change scenarios (Nakicenovic and others, 2000) 

with data from the Geophysical Fluid Dynamics Laboratory 

(GFDL; Delworth and others, 2006) model and the Parallel 

Climate Model (PCM; Washington and others, 2000) general 

circulation models (GCMs). The results indicated a projected 

increase in wildland-fire risk that ranged from 12 to 40 percent 

for the entire region and ranged from 15 to 90 percent for 

California alone; the results also indicated that there was 

substantial spatial variability among the GCMs and scenarios 

where the changes in risk occurred.

Projections of the extent of the burned area under 

climate-change scenarios have been made using climate 

data, sometimes with derived wildland-fire-behavior indices, 

at national and regional scales. The aforementioned Price 

and Rind (1994) study of climate change and fires ignited 

by lightning also suggested that a 44 percent increase in 

lightning ignitions may result in a 78 percent increase in the 

extent of the burned area across the conterminous United 

States. Bachelet and others (2003) suggested a 4 to 31 percent 

increase in the extent of the burned area by 2100, and Lenihan 

and others (2008) suggested a 9 to 15 percent increase in the 

extent of the burned area by 2100 on the basis of simulations 

made with the MC1 Dynamic General Vegetation Model 

(DGVM) model (Bachelet and others, 2001) under various 

climate-change scenarios for the conterminous United States. 

Multiple regional analyses also suggested that the extent of 

the burned area is likely to increase under the climate-change 

scenarios. Littell and others (2010) projected the annual 

area burned within ecosections defined by Bailey (1995) in 

Washington State under the A1B climate-change scenario 

and data from the Third Generation Coupled Global Climate 

Model of the Canadian Centre for Climate Modelling and 

Analysis (CCCma CGCM3.1; Flato and Boer, 2001) and the 

Hadley Centre for Climate Prediction and Research Couple 

Model 3 (HadCM3; Gordon and others, 2000); their results 

suggested that the annual extent of area burned may more 

than double by the 2040s and triple by the 2080s. Interannual 

variability also increased and the probability of having an 

extreme fire year (defined as a year in which the area burned is 

greater than the 95th percentile of the long-term distribution of 

total areas burned) increased from 0.05 to 0.48 by the 2080s. 

A study by Rogers and others (2011) yielded similar results 

for area burned and also demonstrated that burn severity was 

projected to increase in the Pacific Northwest. Litschert and 

others (2012) used an approach that was similar to Littell and 

others (2010) in the Southern Rocky Mountains and fit models 

to project the percent of area burned each year under the A2 

and B1 climate-change scenarios using data from the HadCM3 

model and the Max Planck Institute for Meteorology’s 

European Centre for Medium-Range Weather Forecasts—

Hamburg 5 (ECHAM5; Roeckner and others, 2003) model; 

their projections suggested that the median annual area burned 

may increase up to 500 percent between 1970 and 2006 and 

between 2010 and 2070. These studies demonstrated that the 

extent of the area affected by wildland fires in the Western 

United States was projected to increase under a range of 

climate-change scenarios and GCMs; however, the studies do 

not provide the necessary information to estimate changes in 

wildland-fire emissions.

Few studies have addressed how wildland-fire emissions 

might change with the projected increases in the extent 

of burned areas under climate-change scenarios for the 

conterminous United States, but there has been an extensive 

amount of work completed for boreal regions (Flannigan 

and others, 2005; Balshi, McGuire, Duffy, Flanigan, 

Kicklighter, and Melillo, 2009). Most of the existing estimates 

demonstrated that emissions usually changed in proportion 

to the amount of area burned (Spracklen and others, 2009), 

unless disturbances or climate change caused substantial shifts 

in vegetation. For instance, work by Spracklen and others 

(2009) used climate-change projections from the Goddard 

Institute for Space Studies (GISS; Russell and others, 2000) 

GCM under a scenario in which the concentration of carbon 

dioxide was doubled (2×CO2); the simulation indicated a 

projected increase in mean annual area burned of 50 percent 

and a projected near doubling of carbonaceous aerosol 

emissions by 2050 across the Western United States, with 

the majority of the change projected to occur in the Pacific 

Northwest and Rocky Mountain regions. An earlier study 

by Bachelet and others (2004) used the MC1 DGVM model 

(Bachelet and others, 2001) to simulate past (1905–1995) 

and future (1996–2100) carbon stocks and fluxes with 

climate data from the HadCM2Sul (Johns and others 1997) 

and the CCCma CGCM1 (Flato and others, 2000) models; 

their results showed that biomass consumed by wildland 

fires steadily increased from 110 teragrams of carbon per 

year (TgC/yr) to 180 TgC/yr in the Western United States 

(specifically, Arizona, California, western Colorado, western 

New Mexico, Nevada, western Texas, and Utah) and from 

100 TgC/yr to 160 TgC/yr in the Northwestern United 

States (specifically, Oregon, Washington, Idaho, and western 

Montana). A more recent study by Lenihan and others (2008) 

using the MC1 DVGM model suggested that carbon stocks 

in the Western United States are projected to remain stable, 

largely because projected increases in primary productivity 

would result in the storage of additional carbon, which would 

outweigh the carbon losses from the projected increase in 

wildland fires.

In spite of the large amount of research linking wildland 

fires to climate change, there is no existing framework that 

fully incorporates the mechanisms through which climate 

change will influence wildland-fire occurrence, behavior, and 

effects (Flannigan and others, 2009; Hessl, 2011); therefore, 

a model was developed for this assessment to simulate the 

influence of climate change on patterns of wildland-fire 

ignitions, spread, and emissions. This simulation model was 

calibrated using historical fire, weather, and climate data and 
Chapter 8 99

then used to generate projections under the climate-change 

scenarios. The simulations were designed to address the 

following questions: (1) What are the potential changes in 

wildland-fire occurrence and emissions for the Western United 

States under climate change? (2) How do the potential changes 

vary among ecoregions and climate-change scenarios? This 

chapter focuses primarily on the results of the wildland-fire 

simulations, although wildland-fire scars for both the baseline 

and projection periods were also used in the analysis of 

projected future carbon storage and greenhouse-gas fluxes of 

terrestrial ecosystems (chapter 9).

8.3. Input Data and Methods

The studies described above generally indicated that the 

area affected by large wildland fires and their emissions was a 

function of both ignition patterns and fire behavior, primarily 

spread; both were largely influenced by weather conditions, 

fuels, and topography (Cary and others, 2009) and, in some 

regions, ignitions were influenced by human activity (Cardille 

and others, 2001; Syphard and others, 2007). Projecting 

the potential changes in wildland-fire patterns, therefore, 

required an understanding and accurate characterization of the 

drivers that created the observed, past patterns of ignitions, 

spread, and emissions (Keane and others, 2003; Flannigan 

and others, 2009; Hessl, 2011). Accordingly, the wildlandfire modeling approach used for this assessment incorporated 

three primary components: wildland-fire ignitions, spread, and 

effects (fig. 8.1). The parameters for the ignition and spread 

components were selected through a calibration process using 

the baseline observed data and then used to simulate future 

potential wildfires. The datasets and methods used by the 

various wildland-fire modeling components are described in 

the following sections.

The wildland-fire models were applied to each level III 

ecoregion in the Western United States. Some ecoregions 

that had similar fire regimes and were adjacent to each other 

were grouped to improve the data-processing efficiency. The 

following level III ecoregions were grouped together to form 

one region each: (1) the Cascades, North Cascades, and East 

Cascades—Slope and Foothills; (2) the Northern Rockies and 

Canadian Rockies; and (3) the Southern and Central California 

Chaparral and Oak Woodlands and the Southern California 

Mountains. In a few other level III ecoregions (the Puget 

Lowland, Willamette Valley, and Central California Valley), 

there were too few wildland fires to analyze. 

After simulations were completed for the level III 

ecoregions, the results were aggregated to each level II 

ecoregion and to the entire Western United States for 

reporting. The simulated number of wildland fires, area 

burned, and emissions were summarized by climate-change 

scenario for each decade as the 50th and 95th percentiles, 

which represented typical and extreme fire years, respectively. 

Additionally, the relative change between the baseline decade 

(2001–2010) and the future decade (2041–2050) is reported.

8.3.1. Wildland-Fire Data

The locations of wildland-fire scars were taken from the 

Monitoring Trends in Burn Severity data (MTBS; Eidenshink 

and others, 2007) to calibrate the ignition and spread 

components of the wildland-fire modeling system. The MTBS 

data described fires that occurred from 1984 to 2008 and that 

were greater than 404 ha (1,000 acres) and 202 ha (500 acres) 

in the Western and Eastern United States, respectively. The 

MTBS data did not include small fires but captured the 

majority of the area burned because they included the largest 

fires, which contributed most to total area burned (Strauss 

and others, 1989; Stocks and others, 2002). Each wildland 

fire detailed in the MTBS database was identified in State 

or Federal fire records, and its burn scar and severity were 

manually mapped using pre- and post-fire Landsat scenes. 

Because of the MTBS methodology, there was a high degree 

of confidence in the spatial and temporal accuracy of the 

wildland-fire data, whereas other wildland-fire databases had 

known problems, including duplicate records and erroneous 

locations (T.J. Brown and others, 2002), which would require 

laborious error checking before use.

MTBS LANDFIRE Weather

Fire spread

(MTT) 

Fire effects

(FOFEM) 

Ignition

probability

Burned

area 

Emissions

Figure 8–1.

Figure 8.1. Flowchart showing the components of the 

disturbance model, which was used for generating projections 

of future potential wildland-fire ignitions, burned area, and 

emissions. FOFEM, First Order Fire Effects Model; LANDFIRE, 

Landscape Fire and Resource Management Planning Tools 

project; MTBS, Monitoring Trends in Burn Severity project; MTT, 

minimum travel time.
100 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

8.3.2. Weather and Climate Data

The assessment methodology required daily weather data, 

including temperature, precipitation, relative humidity, and 

wind speeds, for both the baseline and future time periods. 

For the baseline time period, gridded daily weather data for 

the conterminous United States with 1/8° spatial resolution 

(approximately 12 km) were used (Maurer and others, 2002). 

These data, which span the period from 1950 to 2010, were 

interpolated from weather stations and included the minimum 

and maximum daily temperature and daily precipitation. The 

data on afternoon wind speed and direction from the 1/3° 

(approximately 32 km) North American Regional Reanalysis 

(Mesinger and others, 2006) were joined to the 1/8° daily 

temperature and precipitation data.

In order to simulate the effects of the climate-change 

scenarios on wildland-fire occurrence and emissions, 

downscaled monthly climate data provided by the World 

Climate Research Programme’s (WCRP’s) Coupled Model 

Intercomparison Project phase 3 (CMIP3) multimodel dataset 

were used. The CMIP3 data were corrected for bias and 

spatially downscaled to match the 1/8°-resolution baseline 

weather data (Maurer and others, 2007). For this analysis, the 

downscaled data from the CCCma CGCM 3.1 (Flato and Boer, 

2001), Australia’s Commonwealth Scientific and Industrial 

Research Organisation Mark 3.0 (CSIRO–Mk3.0; Gordon 

and others, 2002) model, and the Model for Interdisciplinary 

Research on Climate version 3.2, medium resolution 

(MIROC 3.2-medres; Hasumi and Emori, 2004) for each 

of the A1B, A2, and B1 climate-change scenarios were 

downloaded from the Bias Corrected and Downscaled WCRP 

CMIP3 Climate Projections archive (Maurer and others, 

2007; Lawrence Livermore National Laboratory, 2012). The 

GCMs and scenarios were selected on the basis of their ability 

to capture past climate patterns (Balshi, McGuire, Duffy, 

Flanigan, Walsh, and Melillo, 2009). Additionally, the range 

of variability among the projections generally bracketed 

the extremes of temperature and precipitation projections 

for the conterminous United States (Gonzalez, Neilson, and 

others, 2010). Climate-change summaries for temperature and 

precipitation are provided in chapter 7 of this report.

The downscaled climate data only provided monthly 

temperature and precipitation values, so a temporal 

disaggregation algorithm (Wood and others, 2002) was 

implemented to produce the daily values necessary for 

wildland-fire simulations. This algorithm randomly rearranged 

year-long sequences of the baseline weather data for each 

future year and then adjusted the disaggregated daily values 

of temperature and precipitation so that their monthly means 

matched the values provided by the monthly climate forecasts. 

Using this methodology, 3 replicate weather sequences 

were generated for each GCM and climate-change scenario 

combination for a total of 27 simulation runs. The number of 

GCMs used and replicate runs was somewhat arbitrary but 

limited by computing power and processing times.

For both the baseline and future climate change 

scenarios, additional processing steps were taken to produce 

the live and dead fuel moisture variables required for 

simulating wildland-fire spread and behavior. First, the 

Mountain Climate Simulator (MT–CLIM) algorithms (Glassy 

and Running, 1994) were used to calculate relative humidity 

based on minimum and afternoon daily temperatures (Kimball 

and others, 1997). Once humidity was estimated, the National 

Fire Danger Rating System (NFDRS) algorithms were used to 

estimate daily values for live and dead fuel moistures, as well 

as wildland-fire behavior indices such as the energy release 

component (ERC) (Deeming and others, 1977; Bradshaw and 

others, 1983; Burgan, 1988). The NFDRS algorithms required 

information about the beginning of both spring (“green-up”) 

and fall (“brown-down”) to estimate live fuel moistures. To 

generate green-up and brown-down dates, a methodology was 

implemented that determined the dates of seasonal changes 

based on the daily photoperiod, minimum temperature, and the 

vapor-pressure deficit (Jolly and others, 2005).

8.3.3. Fuels and Topography

In addition to daily weather sequences, the methodology 

relied on the LANDFIRE vegetation, fuels, and topography 

data (Rollins, 2009). These data included information about 

existing vegetation, fire-behavior fuel models, and tree canopy 

fuels (cover, height, base height, and bulk density), as well 

as the elevation, slope, and aspect of the terrain. To calculate 

emissions from wildland fires, the LANDFIRE fuel-loading 

model data layer (FLM; Lutes and others, 2009) was also 

used. Vegetation and fuels were held static throughout the 

simulations and were not altered by simulated disturbances 

and other types of land-use and land-cover (LULC) change. 

All raster data were aggregated to 250-m resolution in order 

to improve the processing efficiency using a nearest-neighbor 

rule. The nearest-neighbor aggregation was desirable because 

it preserved the proportion of vegetative-cover types within 

the study area, whereas other aggregation methods were 

more likely to result in common vegetative-cover types 

being overrepresented and uncommon vegetative-cover types 

being underrepresented.

8.3.4. Model Components

8.3.4.1 Ignitions

General linear models (GLMs) with a binary response 

were constructed to predict daily ignition probabilities within 

each 1/8° weather grid cell. From the data described above, 

a suite of potential predictor variables was compiled that 

included daily weather statistics (minimum and maximum 

temperature and energy release component), monthly 

weather summaries (temperature and precipitation), seasonal 

weather summaries (temperature and precipitation), as well 

as regional summaries of temperature and precipitation, both 
Chapter 8 101

at monthly and seasonal time steps. Also included within the 

1/8° weather grid cells as potential predictors in the GLM 

modeling were the proportions of land area classified as public 

or urban, as well as existing vegetation type groups from the 

LANDFIRE database.

Most observations (grid cells with daily weather data) 

had no data on ignitions; therefore, a subsample was selected 

using a case-control sampling design. Any observation 

with precipitation greater than 0.25 cm was removed. All 

observations with ignition data were retained along with 

a randomly selected set of observations without ignition 

data. The number of observations without ignition data was 

10 times the number of observations with ignition data. The 

choice of design was somewhat arbitrary, but justified because 

the predictive performance of models using case-control 

sampling designs has been shown to increase with the ratio of 

cases to controls (Hastie and others, 2009). The intercept of 

the GLM was adjusted using equation 1 to account for unequal 

proportions of cases (ignitions) and controls (non-ignitions) in 

the sample compared with the population (Preisler and others, 

2004; Hastie and others, 2009).

- log log -

sample sample

population population

non ignitions ignitions

non ignitions ignitions

      − 

  

(1)

To build the GLMs, an initial set of predictor variables 

was selected using forward stepwise regression, including 

only variables with p-values ≤0.05 and limiting the number of 

predictors to 1/10 the number of wildland-fire observations. 

Each GLM was then evaluated and modified as needed 

to ensure that the selected predictor variables accurately 

described weather and climate conditions known to affect 

wildland-fire occurrence in a given ecoregion. The overall 

performance of the final GLM was judged using the area 

under the curve (AUC) of a receiver-operator characteristic 

plot (Hanley and McNeil, 1982). The AUC measured the 

probability of correctly classifying a random pair of fire and 

non-fire observations; an AUC value of 0.5 indicated that the 

model predictions were equivalent to a random guess and an 

AUC value of 1.0 indicated perfect predictions. AUC values 

above 0.8 were generally considered to be good.

8.3.4.2. Spread

During the simulations, the MTT algorithm (Finney, 

2002) was used to simulate the spread of wildland fires after 

ignition. The MTT algorithm has been used extensively 

for local and national-scale simulations of burn probability 

(Calkin and others, 2011; Finney and others, 2011). In 

addition to an ignition location, the MTT algorithm relied 

on fuels (surface and canopy), topography (elevation, slope, 

and aspect), weather (wind speed and direction), and live and 

dead fuel moistures data. The MTT algorithm also required a 

specified number of days and minutes per day that a wildland 

fire can spread. The outputs produced by the MTT algorithm 

included the arrival time (duration of the wildland fire since 

ignition) of every pixel representing burned area, as well as 

wildland-fire-behavior metrics such as fireline intensity and 

crown-fire activity.

8.3.4.3. Emissions

To calculate emissions, the First Order Fire Effects Model 

(FOFEM; Reinhardt and others, 1997; Reinhardt and Keane, 

2009) was applied to each pixel that indicated burned area 

in the simulated wildland fires. The FOFEM used fuel loads 

along with fuel moistures to estimate the amount of forest litter 

and downed deadwood that was consumed (Albini and others, 

1995; Albini and Reinhardt, 1995, 1997). The consumption 

of duff (decaying forest litter), trees, plants, and shrubs was 

estimated as a function of the region, season, fuel moistures, 

and fuel loads. The emissions of carbon monoxide (CO), 

carbon dioxide (CO2), and methane (CH4) were then calculated 

on the basis of the amount of fuel consumed, the organic 

content of the fuel, and how efficiently it burned.

The FOFEM also required estimates about the proportion 

of the tree canopy affected by crown fires. In the simulated 

wildland fires, burn severity estimates were used to quantify 

the proportion of canopy fuels consumed; the burn-severity 

categories (low, medium, and high) were assigned randomly 

on the basis of their observed frequencies in LANDFIRE’s 

existing vegetation groups. When calculating emissions with 

the FOFEM, 20-, 60-, and 100-percent canopy consumption 

was assumed for low, moderate, and high burn severity, 

respectively, on the basis of published literature (Spracklen and 

others, 2009; Zhu and others, 2010).

To simplify the reporting of results, the emission estimates 

were summarized for all carbon-containing constituents to 

carbon dioxide equivalent (CO2-eq) using equation 2.

CO CO 2.33 CO 21.0 CH 2 eq 2 − =+ ×+ × ( ) ( ) 4 (2)

8.3.4.4. Calibration

A number of calibration simulations were required to 

determine the appropriate number of days and minutes per day 

to allow wildland fires to spread using the MTT algorithm. The 

initial values for the minimum and maximum number of days 

to allow the spread and minutes of spread per day were selected 

on the basis of values derived from Federal fire records. Nine 

replicate simulations were run using the baseline weather 

data (1984–2008). After the simulations were complete, 

a 2-sided t-test was used to determine if there was a significant 

difference in the annual average area burned between the 

simulated fires and observed fires in the MTBS data.

If the differences were significant, the number of days of fire 

spread and the minutes of spread per day were altered and the 

calibration process was repeated until the p-value of the t-test 

was less than 0.05, indicating that the calibration simulations 

reproduced the baseline fire patterns.
102 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

8.3.4.5. Simulations of Future Fires

After calibration, future potential wildland-fire ignitions, 

spread, and emissions were generated for three replicate 

simulations for each of the climate-change scenarios and 

GCMs, starting in 2001 and ending in 2050. The replicate 

simulations were run to help quantify uncertainty because of 

the stochastic nature of the models; more replicate simulations 

would have been ideal, but processing times limited the 

number of replicates to three. The results of each simulation 

were summarized in terms of area burned and amount of 

carbon emissions per year.

8.4. Results

General linear models were fit to each level III ecoregion 

and used to generate daily ignition probabilities in the 

simulations. In general, the model fits were quite good with 

the AUC values averaging 0.90 and ranging from 0.80 to 

0.93. The best model fits were in the level III ecoregions 

within the Cold Deserts and the worst model fit was for the 

Mediterranean California ecoregion. Most models included the 

ERC as a predictor (which captured day-to-day variability in 

fuel moistures) and monthly and seasonal weather summaries 

(which captured seasonal and year-to-year variability). Most 

ecoregions also included at least one vegetation predictor. 

Developed land (which included high- and low-density urban 

areas, golf courses, urban parks, and highways) typically was 

not included, except in the Wyoming Basin and Mediterranean 

California ecoregions.

Calibration simulations were run for each level III 

ecoregion to ensure that the patterns of wildland-fire 

occurrence from 1984 to 2008 could be reproduced. For all 

of the ecoregions, there was no significant difference in the 

average annual burned area between the calibration simulation 

and the observed values from the MTBS database, assuming 

that differences were not significant when a p-value of 0.05 

or greater was calculated using a 2-sided t-test that assumed 

unequal variance. After the calibration process, the simulated 

wildland fires were allowed to spread 240 minutes/day, and 

the burn durations ranged from 1 to 21 days, depending on 

the ecoregion.

Across all of the climate-change scenarios, the 

simulations resulted in a projected increase in wildland-fire 

ignitions, area burned, and emissions between the first and last 

decades (2001–2010 and 2041–2050; fig. 8.2 and table 8.1). 

In typical years (50th percentile), the number of ignitions 

was projected to increase 39 to 70 percent. The greatest 

projected increases in ignitions were observed under the A2 

(70 percent) and A1B (58 percent) scenarios and the smallest 

projected increase was observed under the B1 (39 percent) 

scenario. The area burned was projected to increase, ranging 

from a 31 percent increase in the B1 scenario to a 66 percent 

increase in each of the A1B and A2 scenarios. Wildland-fire 

emissions followed similar patterns, with projected increases 

of 56 percent, 54 percent, and 28 percent under the A1B, A2, 

and B1 scenarios, respectively. The simulated changes in 

ignitions, area burned, and emissions were greater in extreme 

fire years (95th percentiles), and across the Western United 

States, ignitions were projected to increase between 62 and 

74 percent, area burned was projected to increase between 

79 and 95 percent, and emissions were projected to increase 

between 73 and 150 percent (fig. 8.2 and table 8.1). The rate 

of change was generally nonlinear and the greatest increases in 

ignitions, area burned, and emissions were projected to occur 

in from 2031 to 2040 and from 2041 to 2050.

Projected increases in ignitions, area burned, and 

emissions were simulated for all three climate-change 

scenarios in the Western Cordillera ecoregion (fig. 8.3 and 

table 8.2). The number of ignitions per year was projected to 

increase between 21 and 38 percent in typical fire years, and 

between 39 and 99 percent in extreme fire years. The changes 

in the extent of area burned were more variable but generally 

were projected to increase in typical fire years under the A1B 

(34 percent) and A2 (55 percent) scenarios, but decrease 

slightly under the B1 (−5 percent) scenario. The extent of 

the area burned in extreme years was projected to change at 

much greater rates than typical fire years, up to 167 percent 

under the A2 scenario. Emissions were projected to increase 

in both typical (15–64 percent) and extreme (28–188 percent) 

fire years. The projected increases were greatest for the A2 

Table 8.1. Projected relative change (increases) in the 50th 

and 95th percentiles for wildland-fire ignitions, area burned, 

and emissions between the first and last decades (2001–2010 

and 2041–2050), by climate-change scenario, for the Western 

United States.

[Climate-change scenarios are from the Intergovernmental Panel on Climate 

Change Special Report on Emissions Scenarios (Nakicenovic and others, 

2000)]

Climate-change 

scenario Percentile

Relative change

(percent)

Ignitions Area 

burned Emissions

A1B 50th 58 66 56

95th 74 95 73

A2 50th 70 66 54

95th 62 84 150

B1 50th 39 31 28

95th 73 79 118
Chapter 8 103

5th percentile

Minimum

95th percentile

50th percentile (median)

Maximum

EXPLANATION

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Area burned, in square

kilometers per year

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dioxide equivalents per year

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Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1

Figure 8.2. Graphs showing summaries of projected wildland-fire ignitions, area burned, and emissions for the Western United States 

for each decade between 2001 and 2050. The X-axis labels indicate the last year in the decade; for example, “2010” corresponds to the 

decade from 2001 to 2010. Scenarios are from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios 

(Nakicenovic and others, 2000).

scenario but were also high for the B1 scenario. The projected 

changes under the A1B scenario tended to be smaller than 

under the other two scenarios, in part because fewer ignitions 

were projected to occur and a smaller area was projected to 

burn during the 2041 to 2050 decade under the A1B scenario.

Of the five level II ecoregions, the least amount of 

wildland-fire activity was observed in the Marine West Coast 

Forest and the simulated changes in wildland-fire occurrence 

and emissions were minimal (fig. 8.3 and table 8.2). The 

projected number of ignitions did not change in both typical 

and extreme years, except under extreme years in the A2 

scenario, where ignitions actually declined. The projected 

extent of area burned and emissions were less stable, and 

there were no clear patterns in the projected changes (fig. 8.3), 

sometimes increasing (A1B and B1 scenarios) and other times 

decreasing (A2 scenario, extreme years). 

In the baseline analysis (chapter 3 of this report), there 

was substantial wildland-fire activity in the Cold Deserts 

ecoregion. The simulations of future wildland fires projected 

a substantial increase in wildland-fire activity across all three 

climate-change scenarios (fig. 8.3 and table 8.2). The projected 

increases in wildland-fire ignitions ranged from 39 to 

85 percent and from 72 to 103 percent for typical and extreme 

fire years, respectively. These projected increases in ignitions 

resulted in (1) projected increases in burned area of 34 to 95 

percent in typical fire years and 58 to 101 percent for extreme 

fire years and (2) projected increases in emissions of 44 to 

87 percent in typical years and 88 to 129 percent in extreme 

years. The projected changes in burned area and emissions 

were generally greatest under the A1B and A2 scenarios.

In the Warm Deserts ecoregion, ignitions were 

projected to increase by 5 to 64 percent (typical years) and 

19 to 133 percent (extreme years), the area burned was 

projected to increase by 1 to 80 percent (typical years)

and 22 to 155 percent (extreme years), and emissions were 

projected to increase by 3 to 69 percent (typical years) and 

–12 to 98 percent (extreme years) (fig. 8.3 and table 8.2). The 

projected changes in ignitions, area burned, and emissions 

were consistently high under the A1B climate-change scenario 

for both typical and extreme fire years, respectively. Under 

the B1 scenario, wildland-fire activity was limited in the 

decade between 2001 and 2010, and the changes relative 

to that decade were large. The changes projected under the 

A2 scenario were minimal, but ignitions, area burned, and 

emissions tended to be greater in all decades under the A2 

scenario than they were under both the A1B and B1 scenarios.

In the Mediterranean California ecoregion, wildland fire 

ignitions, area burned, and emissions were projected to 

increase under all three climate-change scenarios (fig. 8.3 and 

table 8.2), but the differences between typical and extreme 

fire years were less pronounced than in other ecoregions. The 

projected number of wildland-fire ignitions for the decade 

between 2041 and 2050 was 36 to 62 percent greater than in 

the decade between 2001 and 2010 in typical years and 43 to 

67 percent greater in extreme years. The projected increase 

in the number of ignitions resulted in a projected increase 

in burned area of 47 to 86 percent in typical years and 48 to 

61 percent in extreme years. Emissions were projected to 

increase up to 80 percent in typical fire years and up to 

55 percent in extreme years.
104 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

0

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Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1 Scenario A1B Scenario A2 Scenario B1

Figure 8–3. (See figure 8–2 for explanation.)

Number of wildland fires per year Area burned, in

square kilometers per year

Emissions, in carbon dioxide

equivalents per year A. Western Cordillera

B. Marine West Coast Forest

C. Cold Deserts

D. Warm Deserts

E. Mediterranean California

Figure 8.3. Graphs showing summaries of projected wildland-fire ignitions, area burned, and emissions by level II ecoregion, for 

each decade between 2001 and 2050. The X-axis labels indicate the last year in the decade; for example, “2010” corresponds to 

the decade from 2001 to 2010. Scenarios are from the Intergovernmental Panel on Climate Change Special Report on Emissions 

Scenarios (Nakicenovic and others, 2000). See figure 8.2 for an explanation of the bars.
Chapter 8 105

8.5. Discussion

Wildland-fire ignitions and area burned were projected 

to increase across all the climate-change scenarios for the 

Western United States as a whole and in almost all of the 

climate-change scenarios in each of the five ecoregions in 

the Western United States. Emissions were also projected to 

increase, but the pattern was more variable, possibly because 

the projected increase in the area burned may have resulted 

in relatively more light fuels (grass and shrub) and less heavy 

fuels (coniferous forest) being consumed. The projected 

increases in emissions were greater in extreme fire years 

(73–150 percent) than in typical fire years (28–56 percent). 

Given that the baseline wildland-fire emissions were roughly 

equivalent to 11.6 (7.9–87.0) percent of the mean sequestered 

carbon in terrestrial ecosystems (chapter 3), future efforts to 

increase carbon storage in ecosystems may be challenged by 

the potential carbon losses due to the projected climate-driven 

increases in wildland-fire occurrence.

The projected changes in wildland-fire patterns in the 

Western Cordillera ecoregion were most likely a result of the 

projected increases in temperatures during most of the seasons 

and the projected decreases in precipitation during the spring 

and summer, the seasons in which wildland fires are most 

common. In terms of the entire Western United States, the 

Western Cordillera ecoregion accounted for a large proportion 

of the baseline area burned and the majority of wildland-fire 

emissions (chapter 3). The results of the simulations made 

for this assessment indicate that wildland-fire ignitions, area 

burned, emissions, and associated management challenges, 

will likely increase in the future compared to other regions in 

the nation.

Table 8.2. Relative projected changes in the 50th and 95th percentiles for wildland-fire ignitions, area burned, and emissions per year 

between the 2001-to-2010 decade and the 2041-to-2050 decade, by scenario and level II ecoregion.

[Climate-change scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (Nakicenovic and others, 2000)]

Climate-change 

scenario Percentile

Level II ecoregion 

(percent)

Western 

Cordillera

Marine West 

Coast Forest

Cold

Deserts

Warm

Deserts

Mediterranean 

California

Ignitions

A1B 50th 38 0 74 64 62

95th 39 0 95 133 67

A2 50th 32 0 85 5 53

95th 99 −15 72 19 53

B1 50th 21 0 39 34 36

95th 58 0 103 68 43

Area burned

A1B 50th 34 53 62 80 86

95th 63 19 101 155 48

A2 50th 55 29 95 22 47

95th 167 −70 58 31 52

B1 50th −5 0 34 1 49

95th 72 22 74 22 61

Emissions

A1B 50th 28 42 75 69 80

95th 28 22 129 98 43

A2 50th 64 13 87 3 48

95th 188 −66 88 −12 55

B1 50th 15 −12 44 6 38

95th 141 44 105 68 44
106 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

In the Marine West Coast Forest, wildland-fire activity 

has been historically infrequent and minimal changes were 

projected under the climate-change scenarios modeled in 

this assessment. The climate-change projections indicated a 

warming trend in this ecoregion; however, this ecoregion was 

also projected to have the greatest increase in precipitation 

under all of the climate-change scenarios among all the 

ecoregions of the Western United States, especially during 

the winter, spring, and fall. Because of the lag effects in fuel 

moistures, these projected changes could limit and even 

reduce wildland-fire activity. Because vegetation in this region 

historically has been highly productive, the wildland fires were 

extensive and severe when they occurred during droughts. 

This phenomenon most likely produced the highly variable 

projected trends in wildland-fire activity in the simulations.

The climate-change projections were variable for 

the Cold Deserts. As with most of the ecoregions in the 

Western United States, the temperatures were projected to 

increase. Drying patterns were projected in the southern and 

western portions of the ecoregion, especially in the spring, 

but increased precipitation in the summer was projected in 

the northern parts of the ecoregion. The exception was the 

simulation by the MIROC 3.2-medres model, which largely 

projected a drier climate across the entire ecoregion. These 

projected climate changes resulted in consistent projected 

increases in wildland-fire ignitions, area burned, and 

emissions, regardless of the climate-change scenario.

The Warm Deserts ecoregion was projected to have a 

consistently drier climate than the other ecoregions for most 

seasons under all scenarios, except under the B1 scenario 

during the summer (when projected by the CSIRO–Mk3.0 

model) and winter (when projected by the CCCma CGCM3.1 

model). Higher summer and fall temperatures were also 

projected. Wildland-fire activity and emissions were projected 

to increase under the A1B and A2 scenarios, although they 

were projected to be somewhat reduced under the B1 scenario. 

Similarly, the projected warmer temperatures (especially 

in the summer and fall) and drier spring and fall seasons 

in the Mediterranean California ecoregion corresponded to 

the projected increases in wildfire ignitions, area burned, 

and emissions. 

The projected increases in fire activity that were 

simulated in the Cold Desert, Warm Deserts, and 

Mediterranean California ecoregions for this assessment were 

likely to be conservative estimates because vegetation types 

and fuel loads were static throughout the 50-year simulation 

period. There were strong and positive correlations between 

wildland-fire activity and the presence of invasive species after 

fire in all three ecoregions. These correlations suggest that 

as wildland-fire frequency increases, native ecosystems may 

be at risk of invasion by exotic grasses, which in turn may 

further increase the likelihood of wildland fires by providing 

fuel under some climate conditions (D’Antonio and Vitousek, 

1992; Brooks and others, 2004; Keeley, 2006; Brooks and 

Chambers, 2011). The results of the wildland-fire simulations 

produced for this assessment may have been amplified if those 

feedback relations had been included.

The methods used here to simulate wildland fires were 

quite different than those used in most of the previously 

published studies that examined the effects of climate change 

on wildland-fire occurrence. Previous studies did not explicitly 

simulate the wildland-fire ignition locations, spread, or the 

effects on ecosystems; instead, they projected the probability 

that a grid cell contained a wildland-fire ignition (Westerling 

and Bryant, 2008) or the proportion of an ecoregion that 

burned (Littell and others, 2010; Litschert and others, 

2012). The one exception is the recent paper by Westerling 

and others (2011), which projected wildland-fire ignition 

locations and size separately but did not explicitly simulate 

ignition locations and spread on the landscape. In spite of the 

differences in the methods used in this assessment, the results 

presented here were somewhat similar to past studies in that 

all of them projected an increase in the area burned in the near 

future; however, this assessment projected a smaller, more 

conservative increase in area burned than did the previously 

published estimates.

8.6. Limitations and Uncertainties

The MTBS database does not typically include wildland 

fires less than 404 ha (1,000 acres) in size in the Western 

United States, and because the simulation models used for 

this assessment were calibrated using the MTBS data, they 

were not influenced by smaller fires. Smaller fires are not 

likely to change the baseline results by much, but there is the 

possibility that ignitions which historically resulted in a small 

burned area and emissions could grow into large fires under 

different climate conditions. Thus, for this assessment, the 

simulated changes in wildland-fire occurrence and emissions 

may yield conservative estimates.

Throughout the wildland-fire simulations, vegetation 

and fuels remained static, which introduced some limitations 

into the assessment. Because of succession and disturbances, 

the composition and structure of forest vegetation may 

change substantially over the 50-year time span used in this 

assessment (Cooper, 1960; Aplet and others, 1988; Moore 

and others, 2004). These changes were often projected to 

result in altered surface and canopy fuels that determined 

potential wildland-fire behavior and emissions. Disturbances 

were especially important to consider because they were 

projected to reduce fuel loads and effectively act as fire breaks 

for future wildland fires. By holding vegetation and fuels 

static, the interactions among wildland fire and LULC change 

were oversimplified, which are limitations that are shared 
Chapter 8 107

by many broad-scale studies of projected climate change 

and wildland fires. Vegetation dynamics have often been 

ignored in climate-change projections in part because of the 

difficulty of parameterizing the successional trajectories of 

each individual ecosystem type and the lack of information 

about how ecosystems may shift across the landscape under 

climate change. The influence that vegetation dynamics 

might have had on the results of this assessment is uncertain. 

In spite of the projected increases in wildland-fire ignitions 

and area burned simulated for this assessment, the extent of 

the area burned each year was projected to be quite small 

relative to the extent of area that could potentially burn in an 

ecoregion. Thus, in the Western United States, it is unlikely 

that the amount and arrangement of burnable vegetation on 

the landscape will limit wildland fires. Shifts in vegetation, 

however, might affect the type of vegetation and the amount 

of fuel available to burn; thus, past wildland fires might alter 

the fuels, behavior, and emissions of future wildland fires 

(Bachelet and others, 2001, 2003). Incorporating vegetation 

dynamics into the ecosystem-disturbance model component is 

a priority task for future carbon assessments (Running, 2008; 

Goetz and others, 2012).

There was a large amount of variability in wildland-fire 

ignitions, area burned, and emissions in the simulations under 

the three climate-change scenarios. For each of the 3 GCMs, 

3 replicate simulations were run, resulting in 9 simulations 

for each climate-change scenario, or 27 simulations total. It 

is uncertain whether those simulations fully characterized 

the variability in the simulated changes. Ideally, more 

simulations for different GCMs would have been incorporated 

to better characterize the variability, but practical limitations 

on computing resources and processing times effectively 

restricted the number of simulations that were run in this 

assessment. As a test in this study, additional GCMs were used 

in simulations for the Southern Rockies level III ecoregion 

with a greater number of replicates. The results suggested 

that the general projected patterns reported here will not 

change substantially.

8.7. Management Implications

Wildland-fire emissions produce greenhouse gases that 

may contribute to and accelerate climate change (Crutzen and 

Andreae, 1990; Andreae and Merlet, 2001) and may alter the 

structure and function of ecosystems (Bachelet and others, 

2003; Lenihan and others, 2008). Fire-management strategies 

may need to be reassessed to determine whether and how 

best to counteract the projected increases in wildland-fire area 

burned and greenhouse-gas emissions, especially because 

managing wildland fires to reduce greenhouse-gas emissions 

might be at odds with other fire-management objectives, such 

as maintaining the historical range of variability in ecosystem 

disturbance regimes (McKenzie and others, 2004; Fule, 2008).

In certain cases, increased fire suppression efforts 

might be appropriate. Past simulation studies suggested 

that fire suppression in some ecosystems in the Western 

United States may increase carbon stocks by as much as 10 

percent because of the unchecked woody encroachment and 

increased vegetation growth rates (Lenihan and others, 2008). 

In ecosystems where wildland‐fire frequency has increased 

beyond the historical range of variability because of the 

influence of human development (Syphard and others, 2007) 

and invasive species (Brooks and others, 2004; Keeley, 2006), 

increased fire suppression might be a management strategy 

that meets the multiple goals of reducing greenhouse-gas 

emissions while maintaining ecosystem dynamics. The 

potential success of increasing wildland-fire suppression 

efforts remains unknown, however; fire suppression and 

containment efforts may become more difficult as the results 

of this assessment suggested that fires in both typical and 

extreme fire years were projected to be more severe in the 

future.

In other ecosystems, especially the dry forests in the 

Western United States, years of wildland-fire suppression 

have led to increased fuel loads and more severe fires, and 

increasing the suppression efforts in these areas may lead to 

additional undesirable effects (Stephens, 1998; Keane and 

others, 2002; Agee, 2003; Stephens and Ruth, 2005). These 

same ecosystems have been the targets of restoration efforts 

designed to reduce fuel loads and fire severity to historical 

conditions (Agee and Skinner, 2005; Reinhardt and others, 

2008), and fuel treatments have been shown to benefit both 

ecosystem restoration and efforts to reduce greenhouse-gas 

emissions (Stephens and others, 2009; Reinhardt and 

Holsinger, 2010; Wiedinmyer and Hurteau, 2010; North 

and Hurteau, 2011). In forests at higher elevations, where 

the effects of suppression have not substantially altered 

fire regimes, the usefulness of fuel treatments to reduce 

wildland‐fire severity and greenhouse-gas emissions is 

questionable (Schoennagel and others, 2004; Sibold and 

others, 2006; Mitchell and others, 2009). Some authors, 

however, have indicated that a more active management 

approach should be considered in forests at higher elevations 

in order to encourage ecosystem migration under changing 

climates and wildland‐fire regimes (Hansen and others, 2001; 

Fule, 2008).

Uncertainty about the short- and long-term advantages 

and disadvantages of wildland-fire management and fuel 

treatments is high even without considering climate change, 

but may increase when climate change is considered. 

Additional analyses would be required to assess the effects 

of various management scenarios. Even though wildland-fire 

emissions in the Western United States are greater than in 

other parts of the country, they are still relatively small when 

compared to fossil-fuel emissions, and it is questionable 

whether any strategy designed to reduce wildland-fire 

emissions will have a measureable effect at a national scale.
108 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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Chapter 9. Projected Future Carbon Storage and 

Greenhouse-Gas Fluxes of Terrestrial Ecosystems in 

the Western United States

By Shuguang Liu1, Yiping Wu2, Claudia J. Young3, Devendra Dahal3, Jeremy M. Werner1, Jinxun Liu3, 

Zhengpeng Li4, Zhengxi Tan2, Gail L. Schmidt3, Jennifer Oeding3, Terry L. Sohl1, Todd J. Hawbaker5, and 

Benjamin M. Sleeter6

1U.S. Geological Survey, Sioux Falls, S.D.

2Artic Slope Regional Corporation Research and Technology Solutions, Sioux Falls, S.D.

3Stinger Ghaffarian Technologies, Inc., Sioux Falls, S.D.

4University of Maryland, College Park, Md.

5U.S. Geological Survey, Denver, Colo.

6U.S. Geological Survey, Menlo Park, Calif.

9.1. Highlights 

• On the basis of the land-use and land-cover 

(LULC) scenarios, climate-change projections, and 

biogeochemical models used in this assessment, 

the total carbon stored in the ecosystems of the 

Western United States in 2050 was projected to range 

from 13,743 to 19,407 TgC, an increase of 1,325 

to 3,947 TgC from the mean baseline conditions 

(2001–2005; chapter 5 of this report). The amount of 

projected future potential carbon stored was highly 

variable among multiple model runs, ecoregions, 

and ecosystems.

• The Western Cordillera ecoregion was projected to 

store the most carbon, accounting for 60 percent of 

the projected total stored carbon in Western United 

States, followed by the Cold Deserts (18 percent of 

the total), Marine West Coast Forest (10 percent), 

Mediterranean California (8 percent), and Warm 

Deserts (4 percent) ecoregions.

• Among the different ecosystems, forests were 

projected to store the most carbon, accounting for 

70 percent of the projected total carbon stored in 

the Western United States, followed by grasslands/

shrublands (23 percent of the total), agricultural 

lands (6 percent), and other lands (1 percent). 

• About 80 percent of the projected total carbon 

storage was evenly distributed in aboveground 

live biomass and soil organic carbon in the top 

20 centimeters of the soil layer, with the remaining 

20 percent stored in dead biomass (forest litter and 

dead, woody debris). 

• Between 2006 and 2050, and depending on the LULC 

scenarios, climate projections, and biogeochemical 

models used in this assessment, the mean annual 

net carbon flux was projected to range between 

−113.9 and 2.9 TgC/yr for the Western United States. 

(Negative values denote a carbon sink.) Compared 

to the baseline net carbon flux estimates (−162.9 to 

−13.6 TgC/yr; chapter 5 of this report), the future 

carbon-sequestration rates in the Western United States 

were projected to decline by 16.5 to 49 TgC/yr.

• The Western Cordillera ecoregion was projected to 

be the largest carbon sink, accounting for 65 percent 

of the total carbon sequestered in the Western 

United States, followed by the Mediterranean 

California (17 percent of the total), the Cold Deserts 

(11 percent), and the Marine West Coast Forest 

(7 percent) ecoregions. The Warm Deserts ecoregion 

was projected to be either a minor carbon source or 

carbon neutral. 

• All of the major ecosystems modeled in the 

assessment were projected to gain more carbon 

than lose it to the atmosphere. The carbon uptake 

in forests was projected to account for 73 percent 

of the projected total sink, followed by agricultural 

lands (13 percent of the total), grasslands/shrublands 

(11 percent), wetlands (1 percent), and other lands 

(2 percent). 

• Of the total projected carbon sink, about 50 percent 

was projected to accumulate in live biomass, 

44 percent was projected to accumulate in soil 

organic carbon, and the remaining 5 percent was 

projected to accumulate in dead biomass. 
110 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

• The Western United States was projected to be a 

weak sink for methane (−3.1 to −2.8 TgCO2-eq/yr) 

and a weak source for nitrous oxide (1.6 to 

1.7 TgCO2-eq/yr); these results were similar to the 

baseline estimates (chapter 5 of this report). When 

combined with the projected net carbon fluxes 

(−113.9 to 2.9 TgC/yr, or −417.9 to 10.9 TgCO2-eq/yr), 

the net total flux of these three greenhouse gases was 

projected to be −419 to 10 TgCO2-eq/yr by 2050. 

9.2. Introduction 

The results of the terrestrial carbon storage and flux 

modeling for the baseline years (2001–2005) were introduced 

in chapter 5 of this report. This chapter presents the methods 

and results of assessing the projected amounts of carbon stored 

in terrestrial ecosystems and projected greenhouse-gas (GHG) 

fluxes. The task of modeling future carbon storage and flux 

projections is linked with land-use and land-cover (LULC) 

mapping and modeling (chapter 2), future LULC scenarios 

(chapter 6), future climate-change projections (chapter 7), 

and the projected future extent and severity of wildland fires 

(chapter 8). The relations between this chapter and the other 

chapters are depicted in figure 1.2 of chapter 1 of this report. 

The definitions of the ecosystems used in this assessment are 

found table 2.1 of chapter 2 of this report.

The atmospheric concentrations of the major GHGs—

carbon dioxide (CO2,), methane (CH4,), and nitrous oxide 

(N2O)—increased by 36, 148, and 18 percent, respectively, 

from 1750 (the pre-industrial era) to 2006, mainly because 

of increased human activities (Intergovernmental Panel on 

Climate Change, 2007). According to the most recent inventory 

provided by the U.S. Environmental Protection Agency (EPA, 

2012), GHG emissions in the United States increased at an 

average rate of 0.5 percent per year since 1990, and the total 

emissions for the United States were 6,821.8 teragrams of 

carbon dioxide equivalent (TgCO2-eq) in 2010, which was an 

increase of 213.5 TgCO2-eq (or 3 percent) over the 2009 level. 

This increase, as reported in EPA (2012), was principally 

attributed to an increase in energy consumption across all 

economic sectors and an increased demand for electricity 

induced by a warming period (especially warmer summers 

during this period in the United States).

Studies that used both atmospheric and ground-based 

methods agreed on the presence of a carbon sink in the 

conterminous United States (Houghton and others, 1999; 

Pacala and others, 2007; Pan, Birdsey, and others, 2011). 

A global carbon sink of approximately 2 to 6 petagrams of 

carbon per year (PgC/yr) was estimated for 1990 through 

2100, and the variability of the sink depended on the emissions 

scenarios that were used in the studies (Levy and others, 2004). 

Projections of future carbon sources and sinks in the United 

States were highly variable (Bachelet and others, 2001, 2003; 

Hurtt and others, 2002). Hurtt and others (2002) suggested 

that a significant reduction in the sink may be possible during 

the 21st century and that the carbon sink in the United States 

would decline from 0.33 PgC/yr in the 1980s to 0.21 PgC/yr 

by 2050 to 0.13 PgC/yr by 2100. This modeled decline was 

based on the premise that the ecosystem recovery process 

that had been primarily responsible for the contemporary 

carbon sink in the United States would slow down over the 

21st century. For temperate forests in the United States, 

recent studies yielded uncertain results. Heath and Birdsey 

(1993) estimated a smaller carbon sink during a projected 

period between 1987 and 2050 (average of 60 teragrams of 

carbon per year, or TgC/yr) than during the period between 

1952 and1987 (average of 250 TgC/yr). On the basis of forest 

inventory data, Pan, Birdsey, and others (2011) determined 

that the United States’ forests were a stronger carbon sink 

during the 2000s (94 grams of carbon per square meter per 

year, or gC/m2/yr) than during the 1990s (72 gC/m2/yr). 

According to Hurtt and others (2002), the existing carbon 

sink in the United States could become a source under the 

scenario of a failed wildland-fire-suppression effort, resulting 

in a loss of 20 PgC to the atmosphere during the 21st century. 

Smithwick and others (2002) suggested that the carbonsequestration potential of the Pacific Northwest region could 

be much higher than the current rates. The National Forest 

Carbon Inventory Scenarios for the Pacific Southwest Region 

(California) indicated that the national forests may become a 

carbon source in the mid-21st century due to wildfire, disease, 

and other disturbances (Goines and Nechodom, 2009; U.S. 

Department of Agriculture (USDA) Forest Service, 2012a). 

The purpose of this chapter is to report the estimated 

projections of carbon sequestration and GHG emissions 

reduction in the Western United States from 2006 to 2050. 

The input data and methods used in this chapter followed 

an overall assessment methodology (Zhu and others, 2010), 

which included climate-change projections; LULC-change 

projections; simulations of wildland-fire extent, severity, and 

emissions; and biogeochemical modeling of carbon dynamics 

and GHG fluxes. 

9.3. Input Data and Methods 

For the biogeochemical component of this assessment, 

the General Ensemble Biogeochemical Modeling System 

(GEMS) (S. Liu and others, 2012; S. Liu, 2009; chapter 5 of 

this report) was used to simulate the carbon sources and sinks 

and GHG fluxes in the Western United States. The modeling 

framework incorporated several biogeochemical models: the 

CENTURY model (Metherell and others, 1993), the ErosionDeposition-Carbon Model (EDCM; S. Liu and others, 2003), 

and a spreadsheet model (Zhu and others, 2010). The input 

and output data layers used with these models were described 

in S. Liu and others (2009, 2011; chapters 4 and 5 of this 
Chapter 9 111

report). Examples of some of the specific input data are shown 

in figure 9.1 below. The GEMS was calibrated and validated 

extensively using net primary productivity data derived from 

the Moderate Resolution Imaging Spectroradiometer (MODIS 

NPP) and U.S. Department of Agriculture (USDA) grain yield 

information (chapter 5 of this report). 

In order to explore the carbon dynamics and GHG 

emissions under a wide range of projected future conditions, 

21 GEMS model runs were performed for the future 

projections. These runs were as follows:

• Three spreadsheet model runs. Each run represented 

carbon dynamics and GHG fluxes under an LULC 

scenario that was developed in accordance with 

storylines A1B, A2, or B1 from the Intergovernmental 

Panel on Climate Change Special Report on Emissions 

Scenarios (IPCC–SRES; Nakicenovic and others, 2000; 

chapter 6 of this report). The spreadsheet model did not 

simulate the effects of climate change. 

• Nine EDCM simulations. Each simulation was a 

unique combination of an LULC-change scenario 

corresponding to an IPCC–SRES storyline and a 

climate-change projection by a general circulation 

model (GCM). In this assessment, three IPCC–SRES 

scenarios (A1B, A2, and B1) were used (Sleeter, Sohl, 

Bouchard, and others, 2012) along with climate-change 

projections by three GCMs: Model for Interdisciplinary 

Research on Climate 3.2 medium resolution (MIROC 

3.2–medres), Australia’s Commonwealth Scientific and 

Industrial Research Organisation Mark 3.0 (CSIRO–

Mk3.0), and The Third Generation Coupled Global 

Climate Model of the Canadian Centre for Climate 

Modelling and Analysis (CCCma CGCM3.1) (Joyce 

and others, 2011).

• Nine CENTURY model simulations. The setups for 

the CENTURY model runs were the same as for 

the EDCM. 

As with the baseline model runs, a sampling strategy was 

used to improve overall modeling efficiency. The spreadsheetmodel simulations were performed for all ecosystems at 250-m 

resolution; however, a 1 percent systematic sampling rate 

was used to accelerate the CENTURY model and and EDCM 

simulations for the Western United States. As noted in chapter 5

of this report, this sampling procedure was representative of the 

whole population (all pixels). 

For the rest of the modeling process, the modeling 

architecture, initialization, and execution were the same as 

for the baseline years (chapter 5 of this report). Therefore, the 

rest of this chapter focuses on the methods and results that 

were relevant to the future projections. The key concepts and 

terminology used in this chapter, including net carbon flux, net 

primary production (NPP), net ecosystem production (NEP), 

and net ecosystem carbon balance (NECB), follow conventions 

used in the literature, as described in chapter 1 of this report.

9.4. Results and Discussion

9.4.1. Projected Carbon Stocks in 2050 

Annual maps of total carbon stock in ecosystems from 

2006 to 2050 were generated for the Western United States on 

the basis of the 21 simulation model runs described previously. 

As a result, there were 21 carbon stock maps for each year 

from 2006 to 2050. Figure 9.2 represents an average of the 

21 annual maps and shows the spatial distribution of the 

average total amount of carbon (carbon in biomass plus SOC 

in the top 20 cm of the soil layer) stored in ecosystems in the 

Western United States in 2050 (the final year of the scenario 

period) and the standard deviation around the mean value for 

the 21 simulation model runs. The spatial pattern of stored 

carbon in 2050 was in general agreement with that of 2005 

(chapter 5 of this report). 

The projected minimum and maximum amounts of 

stored carbon from the 21 simulation model runs are provided 

in table 9.1, by carbon pool, ecosystem, and ecoregion 

in the Western United States for 2050. The overall total 

carbon stored in all five ecoregions was projected to range 

from approximately 13,743 to 19,406 TgC, compared to 

12,418 to 15,460 TgC in 2005. Among the ecoregions, the 

Western Cordillera was projected to have the most carbon 

stored by 2050, accounting for 60 percent of the total 

carbon stored in the Western United States, followed by the 

Cold Deserts (18 percent of the total), Marine West Coast 

Forest (10 percent), Mediterranean California (8 percent), 

and Warm Deserts (4 percent) ecoregions. Among the 

different ecosystems, forests were projected to store the 

most carbon (70 percent) in the Western United States, 

followed by grasslands/shrublands (23 percent of the total), 

agricultural lands (6 percent), and other lands (1 percent). 

About 80 percent of the total carbon stored was projected to 

be equally allocated to the live biomass and SOC pools and 

the remaining 20 percent was projected to be stored in dead 

biomass (such as forest litter and dead, woody debris). The 

projected allocation was similar to the pattern of total carbon 

stored in the same pools in 2005 (chapter 5 of this report). 

The projected average future carbon density (carbon 

stored per unit of area) of the ecosystems varied substantially 

across ecoregions (fig. 9.2A and table 9.1); ranging from 

high to low, they were forests (15.2 kilograms of carbon per 

square meter, or kgC/m2), wetlands (9.0 kgC/m2), agricultural 

lands (5.4 kgC/m2), grasslands/shrublands (2.4 kgC/m2), 

and other lands (0.6 kgC/m2). Geographically, the projected 

average future carbon density in forests alone was distributed 

in the Marine West Coast Forest (24.7 kgC/m2), Mediterranean 

California (20.7 kgC/m2), Western Cordillera (15.4 kgC/m2), 

Cold Deserts (7.9 kgC/m2), and Warm Deserts (5.9 kgC/m2) 

ecoregions. Similarly, the highest and lowest carbon densities 

for grasslands/shrublands were projected to be found in the 

Marine West Coast Forest (9.7 kgC/m2) and the Warm Deserts 

(1.5 kgC/m2). The projected carbon stored in 2050 is briefly 

described by ecoregion, below.
112 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

A. Precipitation, 2050—MIROC Scenario A1B B. Precipitation, 2050—MIROC Scenario A2

C. Precipitation, 2050—MIROC Scenario B1 D. Land cover, 2050—Scenario A1B

0 200 400 MILES

0 200 400 KILOMETERS

Figure 9–1.

N

Figure 9.1. Maps showing projected total annual precipitation 

under the three IPCC–SRES scenarios and projected land 

cover under the A1B scenario in 2050. A, Projected total annual 

precipitation under the A1B scenario in 2050. B, Projected total 

annual precipitation under the A2 scenario in 2050. C, Projected 

total annual precipitation under the B1 scenario in 2050. 

D, Projected land use and land cover (LULC) map under the A1B 

scenario in 2050 in 2050. The precipitation data were projected 

by the MIROC 3.2–medres general circulation model (Joyce and 

others, 2011). The projected LULC change was from chapter 6

of this report with downscaling of agriculture to crop types by 

Schmidt and others (2011). IPCC–SRES, Intergovernmental Panel 

on Climate Change Special Report on Emissions Scenarios 

(Nakicenovic and others, 2000); MIROC 3.2–medres, Model for 

Interdisciplinary Research on Climate 3.2 medium resolution. 
Chapter 9 113

Figure 9.2. Maps showing the projected mean carbon stored 

and the standard deviation in 2050. A, Projected mean carbon 

stored in 2050 derived from 21 simulation model runs using three 

biogeochemical models (spreadsheet model, CENTURY model, 

and EDCM) under three IPCC–SRES scenarios (A1B, A2, and 

B1) and three general circulation models (MIROC 3.2–medres, 

CSIRO–MK3.0, and CCCma CGCM). B, The projected standard 

deviation around the mean of the 21 simulation model runs. 

CCCma CGCM3.1, The Third Generation Coupled Global Climate 

Model of the Canadian Centre for Climate Modelling and Analysis; 

CSIRO–Mk3.0, Australia’s Commonwealth Scientific and Industrial 

Research Organisation Mark 3.0; EDCM, Erosion-DepositionCarbon Model; IPCC–SRES, Intergovernmental Panel on Climate 

Change Special Report on Emissions Scenarios (Nakicenovic 

and others, 2000); MIROC 3.2–medres, Model for Interdisciplinary 

Research on Climate 3.2 medium resolution.

A B

0 200 400 MILES

0 200 400 KILOMETERS

EXPLANATION

Average carbon storage in 2050, in 

 kilograms of carbon per square meter

EXPLANATION

Standard deviation of the mean carbon storage

 for 2050, in kilograms of carbon per square meter

≤1

1.1 to 2.0

2.1 to 4.0

≤2.0

2.1 to 10.0

10.1 to 20.0

20.1 to 30.0

30.1 to 50.0

50.1 to 100.0

4.1 to 8.0

8.1 to 10.0

>10.0

Level II ecoregion boundary Level II ecoregion boundary

Figure 9–2.

N
114 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

9.4.1.1. Western Cordillera

The total carbon stored in the Western Cordillera 

ecoregion (the largest of the five ecoregions) was projected 

to range between approximately 8,703 and 10,670 TgC in 

2050 (table 9.1). Live biomass, SOC, and deadmass were 

projected to store an average of 46, 32, and 22 percent of the 

total carbon, respectively. Among the different ecosystems, 

forests were projected to store the most carbon (average of 

87 percent of the total) followed by grasslands/shrublands 

(12 percent). The carbon stored in agricultural lands, wetlands, 

and other lands (combined) was projected to be only 1 percent 

of the total carbon. The projected allocation of carbon varied 

substantially between the three pools (live biomass, soil 

organic carbon, and dead biomass) across ecosystems. Live 

biomass was projected to account for 51 percent of the total 

carbon stored in forests, which was more than the projected 

sum of the other two pools. In contrast, soil organic carbon 

was projected to be the dominant storage pool in 2050, 

holding 76, 86, 64, and 90 percent for grasslands/shrublands, 

agricultural lands, wetlands, and other lands, respectively. 

9.4.1.2. Marine West Coast Forest

The estimated carbon stored in the Marine West Coast 

Forest in 2050 was projected to range from approximately 

1,513 to 1,908 TgC (table 9.1). Live biomass and soil 

organic carbon were projected to contain 48 and 33 percent, 

respectively, of this total amount which was similar to 

the projected allocation pattern in the Western Cordillera. 

Among the different ecosystems, forests were projected 

to store the most carbon (91 percent of the projected total 

carbon), followed by agricultural lands (4.5 percent), 

and grasslands/shrublands (2.5 percent). The total carbon 

projected to be stored in wetlands and other lands accounted 

for only 2.4 percent of the projected total carbon stored in 

this ecoregion. The live biomass carbon pool was projected 

to contain the most carbon in both forests and wetlands, 

accounting for 52 and 46 percent of their totals, respectively, 

whereas the soil organic carbon pool was projected to be 

the largest for other ecosystems accounting for 75, 87, and 

78 percent of the total carbon stored in grasslands/shrublands, 

agricultural lands, and other lands, respectively.

9.4.1.3. Cold Deserts

The estimated carbon stored in the Cold Deserts 

ecoregion was projected to range from approximately 2,260 to 

4,060 TgC in 2050 (table 9.1). In contrast to the Western 

Cordillera and Marine West Coast Forest ecoregions, soil 

organic carbon was projected to be the primary carbon pool 

(accounting for 61 percent of the projected total amount of 

carbon), followed by live biomass (20 percent). Unlike the 

Western Cordillera and Marine West Coast Forest, grasslands/

shrublands were projected to serve as the primary carbon 

storage pool (58 percent), followed by forests (26 percent) 

and agricultural lands (13.7 percent). The total percentage of 

carbon stored in wetlands and other lands was projected to be 

about 2 percent. Like the Western Cordillera and the Marine 

West Coast Forest ecoregions, live biomass was projected to 

serve as the major carbon pool in forests (52 percent of the 

total forests), but for the other ecosystems, most carbon was 

projected to be stored in the soil organic carbon pool, ranging 

from 69 percent (for grasslands/shrublands) to 98 percent 

(for other lands). The difference in the projected carbon 

allocation among ecosystems in the Cold Deserts ecoregion 

compared with that of the Western Cordillera and Marine 

West Coast Forest was most likely caused by the different 

projected land-cover fractions. The Cold Deserts ecoregion 

was projected to be dominated by grasslands and shrublands, 

and the Western Cordillera and Marine West Coast Forest 

ecoregions were projected to be dominated by forests.

9.4.1.4. Warm Deserts

The Warm Deserts ecoregion stored the least amount 

of carbon in 2005 (chapter 5 of this report). By 2050, this 

ecoregion was projected to still store the least amount of 

carbon of all the ecoregions, with projected estimates ranging 

from approximately 465 to 1,177 TgC from all simulation 

runs (table 9.1). The projected allocation of carbon across the 

various ecosystems in the Warm Deserts was similar to that of 

the the Cold Deserts because of the similarities in ecosystem 

composition and processes. Like the Cold Deserts ecoregion 

(although much smaller in extent), soil organic carbon was 

projected to be the primary carbon pool by storing 63 percent 

of the total carbon, and live biomass was projected to store 

only 23 percent. Grasslands/shrublands were projected to 

store the most carbon (84 percent of the total), followed by 

agricultural lands (7.3 percent) and forests (6.9 percent). Live 

biomass was projected to account for 58 percent of the total 

carbon stock in forests, and soil organic carbon was projected 

to be the primary pool in grasslands/shrublands (64 percent), 

agricultural lands (82 percent), wetlands (41 percent), and 

others lands (97 percent).

9.4.1.5. Mediterranean California

For the Mediterranean California ecoregion, the total 

carbon stored in 2050 was projected to range from 801.5 to 

1,591.2 TgC (table 9.1). Soil organic carbon was projected 

to be the primary carbon pool (storing 49 percent of the total 

carbon) and live biomass was projected to store 33 percent. 

The majority of the stored carbon was projected to be in 

forests (48.5 percent of the total) across all scenarios, followed 

by grasslands/shrublands (26 percent) agricultural lands 

(22 percent), and other lands (less than 1 percent). As with 

other ecoregions, live biomass was projected to be the primary 
Chapter 9 115

Table 9.1. Minimum and maximum projections of carbon stored in in the Western United States in 2050, based on 21 simulation model 

runs, by ecosystem and ecoregion. 

[Only soil organic carbon (SOC) in the top 20 cm of the soil layer was calculated. Numbers may not sum due to rounding. km2, square kilometers; max, maximum; 

min, minimum; TgC, teragrams of carbon or 1012 grams of carbon]

Ecoregion Ecosystem Area

(km2)

Live biomass

(TgC)

Soil organic

carbon

(TgC)

Dead biomass 

(TgC)

Total

(TgC)

Min Max Min Max Min Max Min Max

Western 

Cordillera

Forests 545,522 3,980.7 4,649.6 1,592.7 2,577.4 1,696.6 2,353.1 7,874.3 9,002.6

Grasslands/shrublands 274,643 72.3 146.9 616.4 1,023.8 0.0 277.8 731.0 1,446.5

Agricultural lands 18,338 0.2 4.3 64.1 97.8 0.0 20.8 66.7 119.6

Wetlands 3,531 6.5 8.3 12.2 32.1 2.4 8.6 24.4 47.7

Other lands 30,234 0.2 2.2 5.5 53.9 0.0 2.6 7.3 54.1

Total 872,268 4,060.0 4,811.4 2,290.9 3,785.1 1,699.0 2,662.9 8,703.6 10,670.4

Marine West 

Coast 

Forest

Forests 61,889 699.6 953.9 375.7 508.9 249.5 367.0 1,411.2 1,710.9

Grasslands/shrublands 4,347 1.6 6.4 18.0 36.0 0.0 7.9 19.5 47.2

Agricultural lands 10,342 0.3 4.7 56.2 74.2 0.0 14.6 57.9 89.6

Wetlands 575 3.6 5.2 3.1 5.4 0.6 1.7 7.3 12.3

Other lands 18,259 0.0 5.8 10.4 48.0 0.0 7.3 16.9 48.0

Total 95,411 705.1 976.0 463.3 672.6 250.1 398.5 1,512.9 1,907.9

Cold Deserts Forests 97,202 332.9 501.6 159.9 290.9 114.9 234.8 674.6 987.4

Grasslands/shrublands 794,594 208.8 370.0 962.9 1,625.8 0.0 540.4 1,321.5 2,458.3

Agricultural lands 87,191 0.1 17.4 221.6 421.9 0.0 87.6 235.8 509.8

Wetlands 4,401 2.3 5.2 13.2 34.5 2.0 8.0 21.5 45.3

Other lands 72,666 0.0 1.1 6.7 59.5 0.0 0.3 6.8 59.5

Total 1,056,055 544.1 895.3 1,364.3 2,432.6 116.9 871.0 2,260.2 4,060.3

Warm 

Deserts

Forests 8,045 21.0 34.1 6.7 15.6 6.5 21.5 38.1 62.7

Grasslands/shrublands 397,311 91.0 191.6 276.9 598.0 0.0 210.3 411.1 991.8

Agricultural lands 11,700 0.0 2.4 10.8 78.6 0.0 15.4 12.9 95.7

Wetlands 322 0.3 0.5 0.3 2.0 0.1 2.1 0.9 4.6

Other lands 47,907 0.0 0.7 2.0 22.3 0.0 0.3 2.1 22.3

Total 465,285 112.2 229.5 296.6 716.4 6.6 249.6 465.0 1,177.0

Mediterranean 

California

Forests 29,830 361.0 405.6 56.5 158.5 119.5 128.4 557.9 686.4

Grasslands/shrublands 65,480 23.5 43.0 103.2 296.6 0.0 81.9 126.7 414.0

Agricultural lands 40,799 0.0 8.1 88.8 341.2 0.0 65.0 96.3 413.9

Wetlands 1,019 0.6 1.9 4.0 18.2 0.5 4.5 5.6 22.6

Other lands 32,327 0.0 2.8 14.7 54.4 0.0 0.6 15.0 54.4

Total 169,455 385.2 461.4 267.2 868.9 119.9 280.4 801.5 1,591.2

Western 

United 

States 

(total)

Forests 742,488 5,395.2 6,544.9 2,191.5 3,551.4 2,187.0 3,104.8 10,556.0 12,449.9

Grasslands/shrublands 1,536,375 397.2 758.0 1,977.4 3,580.0 0.0 1,118.3 2,609.8 5,357.8

Agricultural lands 168,371 0.7 37.0 441.4 1,013.7 0.0 203.4 469.6 1,228.5

Wetlands 9,847 13.3 21.2 32.7 92.3 5.5 24.8 59.6 132.4

Other lands 201,393 0.2 12.5 39.2 238.1 0.0 11.1 48.2 238.3

Total 2,658,474 5,806.7 7,373.5 4,682.2 8,475.5 2,192.5 4,462.4 13,743.2 19,406.8
116 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

carbon pool for forests, accounting for 61 percent of the total 

carbon stored in forests, whereas in other ecosystems, most 

carbon was projected to be stored in the soil organic carbon 

pool, ranging from 73 percent in grassslands/shrublands to 

95 percent in other lands.

9.4.2. Projected Future Net Ecosystem Carbon 

Fluxes Between 2006 and 2050 

The projected future annual net carbon fluxes (or net 

ecosystem carbon balance (NECB)) between 2006 and 2050 

were calculated as the difference in carbon stock between 

two consecutive years. A mean annual NECB was derived 

by averaging all 21 simulation model runs from 2006 to 

2050. The standard deviation of the 21 model runs over the 

simulation time period was also calculated. The resulting 

models are depicted by the two maps shown in figure 9.3. 

Figure 9.3A indicates that the projected high levels of carbon 

sequestration (negative NECB, shown by green hues on 

the map) were strongly associated with the presence of 

forest ecosystems and that simulated disturbances, such 

as clearcutting in the Pacific Northwest, were projected 

to be responsible for a large number of carbon-release hot 

spots (positive NECB, indicated by red hues on the map). 

Carbon sequestration was also projected to occur in the 

agricultural lands of the Central California Valley and the 

Columbia Plateau level III ecoregions. The mean annual 

NECB was projected to be minimal in the majority of arid 

lands of the Western United States. The standard deviation 

map was spatially similar to the pattern of the mean annual 

NECB, and the spread was projected to be generally greater 

in areas with higher mean annual NECB value or higher 

carbon sequestration. 

The projected minimum and maximum mean annual 

NECB values—from the 21 simulations and averaged 

annually between 2006 and 2050—are provided in table 9.2 by 

carbon pool, ecosystem, and ecoregion in the Western United 

States. The mean annual NECB values listed in this table 

represent the projected net carbon gain or loss after harvesting 

(timber and grain harvest) and wildland-fire emissions. The 

mean annual NECB estimates were projected to vary between 

−113.9 and 2.9 TgC/yr in the Western United States, which 

generally agrees with a projected increase in future carbon 

gains that has been documented elsewhere (Bachelet and 

others, 2001; J.E. Smith and Heath, 2008).

As shown in table 9.2, the mean annual NECB in the 

ecoregions of the Western United States was projected to be 

highly variable. Although the Western Cordillera ecoregion 

was projected to maintain the greatest carbon sink in the 

Western United States (accounting for 65 percent of the total 

mean annual NECB), other ecoregions were projected either 

to have smaller shares of the total mean annual NECB or to 

fluctuate between the carbon sink and source. Indeed, this 

was the case for the entire Western United States, with the 

overall mean NECB from the 21 model runs projected to vary 

between −113.9 and 2.9 TgC/yr. When compared with the 

estimated range of the mean annual NECB during the baseline 

years (−162.9 to −13.6; see chapter 5 of this report), the 

projected future mean annual NECB for the entire assessment 

region was down by 16.5 to 49 TgC/yr. Among all ecosystems, 

forests were projected to remain strong terrestrial carbon sinks, 

accounting for approximately 73 percent of the projected 

total mean NECB. The other ecosystems also were projected 

to have the potential to sequester carbon, but the interannual 

variability between carbon sinks or sources was projected to 

be high. On average, about 50 percent of the total carbon was 

projected to accumulate in live biomass, 44 percent in soil 

organic carbon, and the remaining 5 percent in dead biomass 

(forest litter and dead, woody debris). Wetlands were projected 

to have the highest mean annual NECB per unit of area 

(−57 gC/m2/yr), compared with forests (−50 gC/m2/yr), 

agricultural lands (−40 gC/m2/yr), grasslands/shrublands 

(−3.9 gC/m2/yr), and other lands (−3.5 gC/m2/yr). The 

projected carbon sequestration rate per unit of area by forests 

in the Western United States was lower than the estimate of 

75 gC/m2/yr for 2007 by D.P. Turner, Gockede, and others 

(2011). The simulated carbon-sequestration rate in agricultural 

lands was higher than the estimate of 19 gC/m2/yr by 

Kroodsma and Field (2006). Detailed descriptions for each 

ecoregion are given below.

9.4.2.1. Western Cordillera

In the Western Cordillera ecoregion, the projected mean 

annual NECB between 2006 to 2050 ranged from −61.9 to 

−6.7 TgC/yr (table 9.2). Among the different ecosystems, 

forests were projected to gain −27.9 TgC/yr (86 percent of the 

total), averaged across all model runs, followed by grasslands/

shrublands with 3.9 TgC/yr (11 percent of the total), and the 

sum of the rest of the ecosystems at −0.9 TgC/yr (2.8 percent 

of the total). 

9.4.2.2. Marine West Coast Forest

The projected mean annual NECB in the Marine West 

Coast Forest ecoregion between 2006 to 2050 ranged from 

−9.5 TgC/yr (a sink) to 1.8 TgC/yr (a source) (table 9.2), 

depending on which LULC scenarios, climate-change 

projections, or biogeochemical models were used. The 

projected mean annual NECB for forests in this ecoregion 

was –2.4 TgC/yr (or 73 percent of the total) across all model 

runs, followed by grasslands/shrublands (–0.3 TgC/yr) and 

agricultural lands (–0.2 TgC/yr). Wetlands and other lands 

were projected to account for −0.4 TgC/yr, or 12 percent of the 

total mean annual NECB.
Chapter 9 117

Figure 9.3. Maps showing the projected mean annual net 

ecosystem carbon balance (NECB), averaged annually from 

2006 to 2050, and the standard deviation. A, Projected mean 

annual NECB derived from 21 simulation model runs using three 

biogeochemical models (spreadsheet model, CENTURY model, 

and EDCM), three IPCC–SRES scenarios (A1B, A2, and B1) and 

three general circulation models (MIROC 3.2–medres, CSIRO–

MK3.0, and CCCma CGCM). Negative mean annual NECB values 

indicate projected carbon sinks or carbon gains by terrestrial 

ecosystems, and positive values denote projected carbon 

losses. B, The projected standard deviation around the mean 

of the 21 simulation model runs between 2006 and 2050. CCCma 

CGCM3.1, The Third Generation Coupled Global Climate Model 

of the Canadian Centre for Climate Modelling and Analysis; 

CSIRO–Mk3.0, Australia’s Commonwealth Scientific and Industrial 

Research Organisation Mark 3.0; EDCM, Erosion-DepositionCarbon Model; IPCC–SRES, Intergovernmental Panel on Climate 

Change Special Report on Emissions Scenarios (Nakicenovic 

and others, 2000); MIROC 3.2–medres, Model for Interdisciplinary 

Research on Climate 3.2 medium resolution.

A B

0 200 400 MILES

0 200 400 KILOMETERS

Level II ecoregion boundary

Level II ecoregion boundary

EXPLANATION

Total mean net carbon flux averaged annually 

 from 2006 to 2050, in kilograms of carbon

 per square meter per year

EXPLANATION

Standard deviation of mean net carbon flux

 averaged annually from 2006 to 2050, in 

 kilograms of carbon per square meter per year

<1

1.1 to 2

2.1 to 4

≤–5

–5 to –2.1

–2 to –0.6

–0.5 to 0.4

0.5 to 1.9

2.0 to 4.9

≥5

4.1 to 8

8.1 to 10

>10

N

Figure 9–3.
118 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Table 9.2. The projected minimum and maximum mean net ecosystem carbon balance (NECB) values simulated in 21 model runs and 

averaged between 2006 and 2050, by ecoregion and ecosystem in the Western United States. 

[Negative NECB values indicate carbon uptake or sequestration by ecosystems. Only soil organic carbon (SOC) in the top 20 cm of the soil layer was calculated. 

Numbers may not sum due to rounding. km2, square kilometers; max, maximum; min, minimum; TgC, teragrams of carbon or 1012 grams of carbon]

Ecoregion Ecosystem Area

(km2)

Carbon net flux (TgC/yr)

Live

biomass

Soil organic

carbon

Dead

biomass Total

Min Max Min Max Min Max Min Max

Western 

Cordillera

Forests 545,522 −28.6 −6.5 −15.3 0.1 −8.4 4.5 −52.3 −7.0

Grasslands/shrublands 274,643 −0.7 0.5 −6.8 0.3 −1.2 0.0 −7.9 0.3

Agricultural lands 18,338 0.0 0.0 −0.7 0.0 −0.3 0.0 −1.0 0.0

Wetlands 3,531 −0.1 0.0 −0.3 0.0 −0.1 0.0 −0.4 0.0

Other lands 30,234 0.0 0.0 −0.2 0.1 0.0 0.0 −0.2 0.0

Total 872,268 −29.5 −6.0 −23.4 0.6 −10.0 4.5 −61.9 −6.7

Marine West 

Coast Forest

Forests 61,889 −5.0 0.9 −2.1 0.5 −1.0 0.3 −8.1 1.8

Grasslands/shrublands 4,347 −0.1 0.0 −0.3 0.0 0.0 0.0 −0.4 0.0

Agricultural lands 10,342 −0.1 0.0 −0.3 0.2 −0.2 0.0 −0.5 0.2

Wetlands 575 −0.1 0.0 0.0 0.0 0.0 0.0 −0.1 0.0

Other lands 18,259 −0.1 0.0 −0.4 −0.1 −0.1 0.0 −0.5 −0.1

Total 95,411 −5.3 0.9 −3.1 0.6 −1.3 0.3 −9.5 1.8

Cold Deserts Forests 97,202 −4.6 −0.9 −1.7 0.6 −1.4 0.8 −7.7 −0.8

Grasslands/shrublands 794,594 −0.7 3.3 −9.7 0.7 −0.5 3.8 −8.7 4.5

Agricultural lands 87,191 −0.1 0.0 −3.7 0.0 −1.0 0.0 −4.7 0.0

Wetlands 4,401 0.0 0.0 −0.3 0.0 −0.1 0.0 −0.4 0.0

Other lands 72,666 0.0 0.0 −0.2 0.1 0.0 0.0 −0.2 0.1

Total 1,056,055 −5.4 2.4 −15.7 1.5 −2.9 4.6 −21.8 3.8

Warm Deserts Forests 8,045 −0.3 0.0 −0.1 0.0 −0.1 0.1 −0.5 0.0

Grasslands/shrublands 397,311 0.0 2.3 −4.0 0.6 −0.1 2.5 −3.9 5.4

Agricultural lands 11,700 0.0 0.0 −1.2 0.0 −0.2 0.0 −1.3 0.0

Wetlands 322 0.0 0.0 0.0 0.0 0.0 0.0 −0.1 0.0

Other lands 47,907 0.0 0.0 −0.1 0.1 0.0 0.0 −0.1 0.0

Total 465,285 −0.3 2.3 −5.4 0.7 −0.4 2.6 −5.9 5.4

Mediterranean 

California

Forests 29,830 −3.4 −1.8 −1.6 0.0 −0.8 −0.1 −5.8 −2.0

Grasslands/shrublands 65,480 −0.3 0.1 −2.6 0.5 −0.4 0.0 −3.0 0.6

Agricultural lands 40,799 0.0 0.0 −4.3 0.1 −0.7 0.0 −5.0 0.1

Wetlands 1,019 0.0 0.0 −0.3 0.0 −0.1 0.0 −0.3 0.0

Other lands 32,327 −0.1 0.0 −0.5 −0.1 0.0 0.0 −0.5 −0.2

Total 169,455 −3.9 −1.7 −9.3 0.5 −2.0 0.0 −14.7 −1.4

Western United 

States (total)

Forests 742,488 −42.0 −8.2 −20.9 1.3 −11.7 5.7 −74.4 −8.0

Grasslands/shrublands 1,536,375 −1.7 6.1 −23.3 2.1 −2.3 6.3 −23.9 10.8

Agricultural lands 168,371 −0.3 0.0 −10.3 0.3 −2.3 0.0 −12.6 0.3

Wetlands 9,847 −0.2 −0.1 −1.0 0.1 −0.2 0.0 −1.4 0.0

Other lands 201,393 −0.2 0.0 −1.5 0.0 −0.2 0.0 −1.5 −0.1

Total 2,658,474 −44.4 −2.1 −57.0 3.9 −16.7 12.0 −113.9 2.9
Chapter 9 119

9.4.2.3. Cold Deserts

The projected mean annual NECB in the Cold Deserts 

ecoregion between 2006 to 2050 ranged from −21.8 to 

3.8 TgC/yr (table 9.2) across all model runs. The projected 

variability was represented by both forests and agricultural 

lands, each with 45 percent of the total mean annual NECB. 

9.4.2.4. Warm Deserts

The projected mean annual NECB in the Warm 

Deserts ecoregion between 2006 to 2050 ranged from 

−5.9 to 5.4 TgC/yr (table 9.2). Among all the ecoregions, this 

ecoregion was projected to be the only carbon source, with a 

mean carbon emission of 0.3 TgC/yr. The dominant ecosystem 

in the ecoregion, grasslands/shrublands, was projected to 

contribute about 1 TgC/yr in emissions, whereas forests and 

agricultural lands combined were projected to account for 

−0.7 TgC/yr. 

9.4.2.5. Mediterranean California

The projected mean annual NECB in the Mediterranean 

California ecoregion between 2006 and 2050 ranged from 

−14.7 to −1.4 TgC/yr, of which forests were projected to 

accumulate the most carbon (−3.7 TgC/yr or 42 percent of 

the total), followed by agricultural lands (−2.8 TgC/yr) and 

grasslands/shrublands (−1.9 TgC/yr). Wetlands and other 

lands were each projected to accumulate about –0.1 TgC/yr, or 

1 percent of the total mean annual NECB in this region. 

9.4.3. Variability in the Projected Mean Carbon 

Stock and Mean Net Ecosystem Carbon Balance

As noted previously, 21 simulation model runs were 

conducted. The objective was to project a range of estimates 

for the amount of carbon stored and the NECB in order to 

assess the future carbon storage and sequestration capacities 

in the region. The variability in the ranges of the resulting 

estimates represents a major portion of the uncertainty in the 

assessment results. Table 9.3 compares the projected estimates 

of mean carbon stocks in 2050 and the mean annual NECB 

from 2006 to 2050. The data were derived by averaging all of 

the combinations of the 21 model runs for each ecosystem, for 

each of the five ecoregions, and for the entire Western United 

States. A variability value was also calculated as a percent 

measure for each of the three subsets of the model runs by 

dividing the range of the minimum and maximum estimates of 

the subset by their mean, and multiplying by 100. 

Among the three biogeochemical models, the EDCM 

and the spreadsheet model performed similarly, whereas 

the CENTURY model consistently led to a higher projected 

estimate of stored carbon than the other two. The models 

performed differently across ecoregions with the smallest 

discrepancy found in the Marine West Coast Forest (6 percent 

variability across three models) and the highest in the Warm 

Deserts (58 percent). For the projected mean annual NECB 

estimates, the CENTURY model almost always yielded the 

highest estimates, followed by the EDCM, and the spreadsheet 

model (table 9.3). The variability among the models in 

projecting the mean annual NECB was very high, ranging 

from 129 percent in the Cold Deserts to 258 percent in the 

Warm Deserts, suggesting that future effort should be directed 

to investigating the causes of the divergence of the models and 

reducing the models’ uncertainties.

The variability in the projected carbon stock estimates 

among the three LULC scenarios was small, ranging from 1 to 

9 percent across the ecoregions (table 9.3). The variability of 

in the projected mean annual NECB under these scenarios 

was relatively higher than that of the carbon stock, ranging 

from 4 percent in the Mediterranean California to 200 percent 

in the Warm Deserts. The higher variability of the projected 

mean annual NECB across scenarios in some ecoregions did 

not necessarily indicate that there was a big difference among 

the results of the scenario modeling. The high variability may 

have been simply related to the low projected mean annual 

NECB estimates in the arid regions and how the percent 

variability was defined. Overall, the projected estimates of 

carbon stock and mean annual NECB were not significantly 

affected by the GCMs (table 9.3), with variability ranging 

from 0.4 to 25 percent for projected carbon stocks and from 

3 to 1,139 percent for the projected mean annual NECB. 

Again, the large relative variability was associated with the 

low projected mean annual NECB. The projected mean annual 

NECB varied from −62.2 TgC/yr under the CSIRO–Mk3.0 

model to −51.2 TgC/yr under the MIROC 3.2–medres model. 

9.4.4. Projected Future Greenhouse-Gas Fluxes 

from 2006 to 2050 

For this assessment, carbon dioxide (CO2) fluxes were 

simulated by the EDCM and the CENTURY model as part of 

the carbon flux assessment described in the previous section 

of this chapter, whereas methane (CH4) and nitrous oxide 

(N2O) fluxes were simulated separately by the spreadsheet 

model. To calculate the global warming potential (GWP) in 

carbon dioxide equivalent (CO2-eq), a factor of 21 was used 

for methane and of 310 for nitrous oxide (EPA, 2003). The 

uptake of GWP indicates that GHG fluxes into ecosystems 

were greater than fluxes out of ecosystems. The projected 

minimum and maximum mean annual fluxes and their total 

GWP for 2006 to 2050 are listed by ecoregion and ecosystem 

in table 9.4. Note that these flux estimates did not include the 

wildland-fire emission estimates presented in chapter 8 of this 

report and that the climate-change projections (using GCMs) 

were not considered in modeling the methane and nitrous 

oxide fluxes.
120 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The Western United States was generally projected 

to incur low levels of methane and nitrous oxide fluxes 

annually over the projection period of 2006 to 2050, which 

was similar to the baseline years of 1992 to 2005. As 

presented in chapter 5, the baseline estimates for methane 

and nitrous oxide ranged from −3.1 to −2.9 TgCO2-eq/yr 

and from 1.7 to 1.7 TgCO2-eq/yr, respectively, for the two 

gases. In comparison, the projected future methane and 

nitrous oxide fluxes, in comparison, ranged from −3.1 to 

−2.8 and from 1.63 to 1.68 TgCO2-eq/yr, respectively, 

which indicates virtually no change over the two periods 

of the assessment. When combined with the projected net 

carbon dioxide fluxes for 2006 to 2050, which ranged from 

−418 to 11 TgCO2-eq/yr, the total resulting GWP for the 

Western United States was projected to range from −419 to 

9.8 TgCO2-eq/yr. The details of methane and nitrous oxide 

fluxes by ecoregion are described below.

Table 9.3. Comparison of projected mean carbon stocks in 2050 and projected mean annual net ecosystem carbon balance from 

2006 to 2050, and their percent variability, derived from combinations of three biogeochemical models, three land-use and land-change 

scenarios, and three general circulation models for each of the five ecoregions and for the entire Western United States. 

[EDCM, Erosion-Deposition-Carbon Model; NA, not applicable; NECB, net ecosystem carbon balance; TgC, teragrams of carbon; TgC/yr, teragrams of carbon 

per year]

Projected mean carbon stock in 2050 

(TgC)

Projected mean annual NECB from 2006 to 2050 

(TgC/yr)

Western 

Cordillera

Marine 

West 

Coast 

Forest

Cold 

Deserts

Warm 

Deserts

Mediterranean 

California

Western 

United 

States 

(total)

Western 

Cordillera

Marine 

West 

Coast 

Forest

Cold 

Deserts

Warm 

Deserts

Mediterranean 

California

Western 

United 

States 

(total)

Biogeochemical models

CENTURY 10,302.1 1,744.7 3,402.7 898.6 1,495.0 17,843.1 −54.1 −6.0 −7.7 0.3 −12.8 −80.3

EDCM 9,217.6 1,637.5 2,583.1 510.6 1,186.2 15,135.1 −18.9 −1.7 −5.3 0.4 −7.2 −32.8

Spreadsheet 8,874.0 1,653.3 2,429.1 586.7 849.6 14,392.7 −9.7 −0.5 −1.5 −0.1 −1.9 −13.6

Variability 15 6 35 58 55 22 161 204 129 258 148 158

Land-use and land-change scenarios 

A1B 9,540.0 1,631.1 2,909.8 678.8 1,261.1 16,020.8 −30.6 −2.2 −5.8 0.5 −8.6 −46.7

A2 9,615.1 1,648.1 2,902.2 681.0 1,273.6 16,120.1 −32.3 −2.5 −5.6 0.4 −8.9 −48.9

B1 9,744.8 1,777.9 2,925.1 703.5 1,276.7 16,428.0 −35.2 −5.4 −6.1 −0.1 −9.0 −55.7

Variability 2 9 1 4 1 3 14 97 9 200 4 18

General circulation models

CCCma 

CGCM 9,772.1 1,699.2 2,979.3 682.0 1,342.7 16,475.2 −36.8 −4.0 −6.2 0.8 −10.0 −56.2

CSIRO– 

Mk3,0 9,775.0 1,682.7 3,138.2 802.2 1,345.6 16,743.7 −36.8 −3.7 −9.8 −1.8 −10.1 −62.2

MIROC 

3.2–

medres

9,732.5 1,691.5 2,861.2 629.6 1,333.6 16,248.4 −35.9 −3.9 −3.6 2.0 −9.8 −51.2

Variability 0 1 9 25 1 3 3 10 94 1,139 3 19

All combinations

Minimum 9,062.1 1,580.6 2,468.4 479.2 1,172.2 NA −60.9 −8.6 −18.4 −5.8 −13.3 NA

Maximum 10,606.9 1,862.0 3,882.4 1,169.5 1,520.5 NA −15.5 −0.4 0.5 4.1 −6.9 NA

Overall 

variability 16 17 47 98 26 NA −124 −212 −290 2,937 −64 NA
Chapter 9 121

9.4.4.1. Western Cordillera

The mean annual GWP of the Western Cordillera ecoregion 

between 2006 and 2050 was projected to range from −227.9 

to −25.1 TgCO2-eq/yr (table 9.4). The mean methane uptake 

in this ecoregion was projected to be −1.3 TgCO2-eq/yr with 

the highest contribution from forests (−0.89 TgCO2-eq/yr) and 

grasslands/shrublands (−0.81 TgCO2-eq/yr). The rate of methane 

emissions in wetlands was projected to be 0.40 TgCO2-eq/yr. 

The mean annual emission of nitrous oxide was projected to be 

0.58 TgCO2-eq/yr, of which forests and grasslands/shrublands 

contributed 52 percent and 40 percent, respectively.

9.4.4.2. Marine West Coast Forest

The mean annual GWP of the Marine West Coast Forest 

ecoregion between 2006 and 2050 was projected to range from 

−34.42 to 7.11 TgCO2-eq/yr (table 9.4), depending on the model 

runs. Most of the uptake was due to the projected future carbon 

sequestration in the region, which was estimated to sequester 

the most carbon among all ecoregions on a per-unit-area 

basis. The methane and nitrous-oxide fluxes were projected to 

continue to remain emission-neutral. 

9.4.4.3. Cold Deserts

The mean annual GWP of the Cold Deserts 

ecoregion between 2006 and 2050 was projected to 

range from −81.89 to 12.23 TgCO2-eq/yr (table 9.4). 

The mean methane uptake was projected to be about 

−2 TgCO2-eq/yr with contributions from grassslands/

shrublands (−2.77 TgCO2-eq/yr), forests (−0.42 TgCO2-eq/yr), 

and agricultural lands (−0.06 TgCO2-eq/yr). Wetlands and other 

lands were projected to emit about 1.2 TgCO2-eq/yr of methane. 

The mean emission of nitrous oxide was 0.40 TgCO2-eq/yr, of 

which grasslands/shrublands and agricultural lands contributed 

about 47 percent and 34 percent, respectively.

9.4.4.4. Warm Deserts

The mean annual GWP of the Warm Deserts ecoregion 

between 2006 and 2050 was projected to range from −22.32 to 

19.5 TgCO2-eq/yr (table 9.4). The methane and nitrous oxide 

fluxes were projected to remain emission-neutral. 

9.4.4.5. Mediterranean California

The mean annual GWP of the Mediterranean California 

ecoregion between 2006 and 2050 was projected to range from 

−53.68 to −3.88 TgCO2-eq/yr (an overall sink; table 9.4). In a 

separate study, the major GHG fluxes in forests of the State 

of California in recent years (2000–2006) were estimated to 

be −10.7 TgCO2-eq/yr (California Environmental Protection 

Agency Air Resources Board, 2009). The projected mean 

annual emissions of methane and nitrous oxide remained 

low compared to the carbon sink in the ecoregion. Forests 

and grasslands/shrublands were projected to sequester 

methane (−0.25 TgCO2-eq/yr), but not enough to offset 

methane emissions of 1.2 TgCO2-eq/yr from agricultural 

lands, wetlands, and other lands. The projected mean annual 

emission of nitrous oxide was 0.18 TgCO2-eq/yr, of which 

agricultural lands and grasslands/shrublands contributed about 

48 percent and 38 percent, respectively.

9.4.4.6. Mean Annual Global Warming Potential 

of Ecosystems

Among the ecosystems in the Western United States, 

grasslands/shrublands were projected to play a primary 

role in the uptake of methane and release of nitrousoxide with a combined mean annual flux rate of −4.0 to 

−3.8 TgCO2-eq/yr for the two gases, followed by forests 

(−1.25 to −1.21 TgCO2-eq/yr). Wetlands were projected to 

have the highest methane emissions with a mean annual rate 

of 1.43 to 1.75 TgCO2-eq/yr. Grasslands/shrublands, which 

were projected to cover about 59 percent of the Western 

United States, were projected to contribute the most nitrous 

oxide emissions (53 percent of the total). Agricultural lands, 

which were projected to cover only 6 percent of the Western 

United States, were projected to emit 16 percent of the total 

nitrous oxide.

Figure 9.4 shows the projected GHG fluxes in the 

Western United States from 2006 to 2050, by LULC 

scenario. The projected carbon dioxide fluxes indicated more 

interannual variability than either the projected methane or 

nitrous oxide fluxes because the carbon dioxide projections 

included climate-change projections and the projected 

fluxes of the other two GHGs did not. The projected fluxes 

of methane ranged from 2.8 to 3 TgCO2-eq/yr and diverged 

among the three IPCC_SRES scenarios, with an increasing 

trend (less than 0.004 TgCO2-eq/yr) under the B1 scenario and 

slightly decreasing trends under the A1B and A2 scenarios. 

The projected nitrous-oxide emissions indicated minimal 

variability over time, with a projected mean annual flux of 

1.7 TgCO2-eq/yr in the Western United States.
122 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Table 9.4. The projected minimum and maximum of the mean annual carbon dioxide, methane, and nitrous oxide fluxes and their total 

global warming potential (GWP), averaged from 2006 to 2050, by ecoregions and ecosystems. 

[Projected fluxes of methane and nitrous oxide were estimated by the spreadsheet model, and projected flux of carbon dioxide was estimated from the 

spreadsheet model, CENTURY model, and EDCM. TgCO2-eq, teragrams of carbon dioxide equivalent per year]

Ecoregion Ecosystem Area

(km2)

Carbon dioxide

(TgCO2-eq/yr)

Methane

(TgCO2-eq/yr)

Nitrous oxide

(TgCO2-eq/yr)

Global warming

potential

(TgCO2-eq/yr)

Min Max Min Max Min Max Min Max

Western 

Cordillera

Forests −191.9 −25.9 −0.89 −0.88 0.3 0.31 −192.49 −26.47 −7.0

Grasslands/shrublands −29.1 1.2 −0.82 −0.81 0.23 0.24 −29.69 0.63 0.3

Agricultural lands −3.8 0.1 −0.01 −0.01 0.02 0.02 −3.79 0.11 0.0

Wetlands −1.5 0 0.37 0.42 0 0 −1.13 0.42 0.0

Other lands −0.8 0.1 0.03 0.03 0.01 0.01 −0.76 0.14 0.0

Total −227.2 −24.4 −1.29 −1.26 0.58 0.58 −227.91 −25.08 −6.7

Marine West 

Coast Forest

Forests −29.5 6.5 −0.22 −0.2 0.03 0.03 −29.69 6.33 1.8

Grasslands/shrublands −1.3 0.1 −0.01 0 0 0 −1.31 0.1 0.0

Agricultural lands −1.8 0.7 −0.01 0 0.01 0.01 −1.8 0.71 0.2

Wetlands −0.4 −0.1 0.12 0.15 0 0 −0.28 0.05 0.0

Other lands −1.7 −0.5 0.42 0.42 0.02 0.02 −1.26 −0.06 −0.1

Total −34.8 6.7 0.32 0.34 0.06 0.07 −34.42 7.11 1.8

Cold Deserts Forests −28.4 −2.9 −0.42 −0.42 0.06 0.06 −28.76 −3.26 −0.8

Grasslands/shrublands −32.1 16.4 −2.8 −2.74 0.18 0.19 −34.72 13.85 4.5

Agricultural lands −17.4 −0.1 −0.07 −0.06 0.13 0.16 −17.34 0 0.0

Wetlands −1.4 0.1 0.74 0.87 0 0 −0.66 0.97 0.0

Other lands −0.9 0.3 0.41 0.41 0.02 0.02 −0.47 0.73 0.1

Total −80.2 13.8 −2.08 −1.99 0.39 0.42 −81.89 12.23 3.8

Warm Deserts Forests −1.9 0.1 −0.02 −0.02 0 0 −1.92 0.08 0.0

Grasslands/shrublands −14.4 19.7 −1.03 −1.01 0.37 0.38 −15.06 19.07 5.4

Agricultural lands −4.9 0 −0.01 −0.01 0.02 0.02 −4.89 0.01 0.0

Wetlands −0.3 0 0.07 0.07 0 0 −0.23 0.07 0.0

Other lands −0.4 0.2 0.05 0.05 0.02 0.02 −0.33 0.27 0.0

Total −21.8 20 −0.94 −0.92 0.42 0.42 −22.32 19.5 5.4

Mediterranean 

California

Forests −21.3 −7.2 −0.11 −0.11 0.02 0.02 −21.39 −7.29 −2.0

Grasslands/shrublands −10.9 2.2 −0.16 −0.13 0.06 0.07 −11 2.14 0.6

Agricultural lands −18.4 0.4 0.79 0.86 0.08 0.1 −17.53 1.36 0.1

Wetlands −1.3 0 0.13 0.24 0 0 −1.17 0.24 0.0

Other lands −1.9 −0.6 0.23 0.24 0.01 0.01 −1.66 −0.35 −0.2

Total −53.8 −5.1 0.94 1.03 0.18 0.19 −52.68 −3.88 −1.4

Western 

United 

States (total)

Forests −273.1 −29.3 −1.66 −1.63 0.41 0.42 −274.35 −30.51 −8.0

Grasslands/shrublands −87.8 39.6 −4.82 −4.7 0.84 0.88 −91.78 35.78 10.8

Agricultural lands −46.4 1.1 0.69 0.77 0.26 0.31 −45.45 2.18 0.3

Wetlands −5 0 1.43 1.75 0 0 −3.57 1.75 0.0

Other lands −5.6 −0.5 1.14 1.15 0.08 0.08 −4.38 0.73 −0.1

Total −417.9 10.9 −3.05 −2.8 1.63 1.68 −419.32 9.78 2.9
Chapter 9 123

2000 2010 2020 2030 2040 2050

–3.2

–3.1

–3.0

–2.9

–2.8

–2.7

Methane, in teragrams of

 carbon dioxide equivalent per year

2000 2010 2020 2030 2040 2050

1.635

1.630

1.640

1.645

1.650

1.655

1.660

1.665

Nitrous oxide, in teragrams of

carbon dioxide equivalent per year

2000 2010 2020 2030 2040 2050

–300

–400

–200

–100

0

Year

Year

Carbon dioxide, in teragrams of

carbon dioxide equivalent per year

Scenario A1B

Figure 9–4.

Scenario A2

Scenario B1

Mean

EXPLANATION

A B

C

Figure 9.4. Graphs showing the baseline and projected temporal changes in global warming potential (GWP) of carbon dioxide, 

methane, and nitrous oxide fluxes from 2006 to 2050. A, Carbon dioxide. B, Methane, C, Nitrous oxide. TgCO2-eq/yr, teragrams of 

carbon dioxide equivalent per year.

9.5. Summary 

Using multiple biogeochemical models on the GEMS 

platform, projected LULC change data, and climatechange scenarios, the projected dynamics of carbon stocks, 

net ecosystem carbon balance, and GHG fluxes during 

the period from 2006 to 2050 were assessed. The results 

indicated that the total carbon stored in the ecoregions of the 

Western United States was projected to reach from 13,743 

to 19,406 TgC by 2050, with the variability resulting from 

using different biogeochemical models, the LULC scenarios, 

and climate-change projections. About 80 percent of the total 

carbon stored would be equally allocated to the live biomass 

and soil organic carbon pools, and the rest would be allocated 

to the dead biomass pool (such as forest litter and dead, woody 

debris). The Western Cordillera ecoregion was projected to 

store the most carbon by 2050 (59 percent of the total) in the 

Western United States, and the Warm Deserts ecoregion was 

projected to store the least (4 percent). Forests were projected 

to have the highest carbon density with average stocks of 

15.3 kgC/m2, followed by wetlands (9.0 kgC/m2), agricultural 

lands (5.4 kgC/m2), grasslands/shrublands (2.4 kgC/m2), and 

other lands (0.6 kgC/m2).
124 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The projected mean annual NECB varied from −113.9 

to 2.9 TgC/yr as the result of the 21 simulation model runs, 

with approximately 50 percent of the total carbon accumulated 

in live biomass, 44 percent in soil organic carbon, and the 

remaining 5 percent in dead biomass. Compared to the 

baseline net carbon flux estimates for 2001 to 2005 (−162.9 

to −13.6 TgC/yr, chapter 5 of this report), the projected future 

carbon-sequestration rates in the Western United States 

indicated a decline of 16.5 to 49 TgC/yr by 2050 (the end 

of the projection period). The Western Cordillera ecoregion 

was projected to be the largest carbon sink, sequestering 

65 percent of the total stored carbon in the Western United 

States, whereas the Warm Deserts ecoregion was projected 

to be a small carbon source, emitting 0.2 TgC/yr. Wetlands 

and forests were projected to have relatively strong mean 

per-unit-of-area carbon-sequestration rates (−57 gC/m2/yr and 

−50 gC/m2/yr, respectively), followed by agricultural lands 

(−40 gC/m2/yr), other lands (−3.9 gC/m2/yr), and grasslands/

shrublands (−3.5 gC/m2/yr). The projected NECB and perunit-of-area flux estimates varied spatially among ecoregions 

and ecosystems, and they varied temporally over the 

projection period, which indicated that each of the ecosystems 

could be a carbon sink or source for a given ecoregion, driven 

by LULC, climate, land management, and wildland-fire 

disturbance conditions.

The projected mean annual fluxes of methane and nitrous 

oxide were shown to be largely low to neutral, continuing the 

trend from the baseline period. The Western United States was 

projected to take up methane at a mean annual rate of −3.1 to 

−2.8 TgCO2-eq/yr. The annual average nitrous oxide emission 

was projected to range from 1.63 to 1.68 TgCO2-eq/yr. 

Given that the mean annual net flux of carbon dioxide in 

the Western United States was projected to range from 

−417.9 to 10.9 TgCO2-eq/yr, the total combined GWP for the 

Western United States was projected to range from −419.3 to 

9.8 TgCO2-eq/yr. Although forests and grasslands/shrublands 

were projected to be a sink for methane, with an average 

sequestration rate ranging from −1.7 to −4.8 TgCO2-eq/yr, 

the other ecosystems (agricultural lands, wetlands, and other 

lands) acted as a methane source, with wetlands emitting the 

most methane (1.6 TgCO2-eq/yr).
Chapter 10. Baseline Carbon Sequestration, Transport,

and Emission From Inland Aquatic Ecosystems in the 

Western United States

By Sarah M. Stackpoole1, David Butman2, David W. Clow1, Cory P. McDonald3, Edward G. Stets4, and 

Robert G. Striegl4

1U.S. Geological Survey, Denver, Colo.

2

U.S. Geological Survey, New Haven, Conn.

3Wisconsin Department of Natural Resources, Madison, Wis.

4U.S. Geological Survey, Boulder, Colo.

10.1. Highlights

• There was considerable variability in the estimated 

aquatic carbon fluxes among the five ecoregions in 

the Western United States, most likely because of 

differences in precipitation, levels of organic matter 

inputs, lithology, and topography.

• Inland aquatic ecosystems in the Western United States 

were both sources and sinks of carbon. Riverine and 

lacustrine systems were sources of carbon dioxide to 

the atmosphere, but lacustrine systems also buried 

carbon in sediments. Total aquatic carbon flux rates 

were estimated for all five ecoregions in the Western 

United States using empirical data from 1920 to 

2011. The carbon dioxide efflux from lacustrine and 

riverine systems (combined) was estimated to be 

28.1 teragrams of carbon per year (TgC/yr) (confidence 

interval from 16.8 to 48.7 TgC/yr). The dissolved 

inorganic and total organic carbon export from riverine 

systems was estimated to be 7.2 TgC/yr (confidence 

interval from 5.5 to 8.9 TgC/yr). The carbon burial 

in sediments of lacustrine systems was estimated to 

be −2.1 TgC/yr (confidence interval from −1.1 to 

−3.2 TgC/yr). 

• The total aquatic yields (flux rates normalized by 

land area) for all five western ecoregions were 

estimated using empirical data from 1920 to 2011. 

The carbon dioxide efflux yield from riverine systems 

was estimated to be 14.0 grams of carbon per square 

meters per year (gC/m2/yr; confidence interval from 

6.0 to 17.1 gC/m2/yr) and from lacustrine systems 

was estimated to be 0.5 gC/m2/yr (confidence interval 

from 0.0 to 1.0 gC/m2/yr). The dissolved inorganic 

and total organic carbon export yield from riverine 

systems was estimated to be 3.4 gC/m2/yr (confidence 

interval from 2.6 to 4.2 gC/m2/yr). The carbon burial 

yield in sediments of lacustrine systems was estimated 

to be −1.2 gC/m2/yr (confidence interval from −0.6 to 

−1.8 gC/m2/yr). 

10.2. Introduction

The aquatic ecosystems discussed in this chapter include 

streams, rivers, perennial ponds, lakes, and impoundments. 

Despite the small portion of the land surface area that they 

cover, lacustrine systems (perennial ponds, lakes, and 

impoundments) and riverine systems (rivers and streams) can 

play a major role in the regional and continental-scale carbon 

budgets (Dean and Gorham, 1998; Cole and others, 2007; 

Battin and others, 2008). These ecosystems are constantly 

exchanging carbon with the terrestrial and atmospheric 

environments, so they can be active sites for transport, 

transformation, and storage of carbon (Cole and others, 2007; 

Striegl and others, 2007; Tranvik and others, 2009). 

Many processes affect the overall magnitude of fluxes 

in aquatic ecosystems and determine whether the system is a 

source or a sink of carbon. Estuarine and lacustrine systems 

can be sinks of carbon derived from both autochthonous 

sources (formed at the site of deposition) and allochthonous 

sources (formed outside of the site of deposition), and riverine 

systems can transport carbon from upland terrestrial systems 

to the ocean. Riverine and lacustrine systems, however, can 

also be supersaturated in carbon dioxide and, therefore, can be 

sources of carbon to the atmosphere (Kling and others, 1991; 

Cole and others, 1994, 2007; Aufkenkampe and others, 2011). 

Some important drivers of carbon fluxes in aquatic ecosystems 

include (1) timing and magnitude of precipitation and flow, 

(2) autochthonous and allochthonous carbon production, 

and (3) physical parameters such as topographic slope, air 

and water temperature, and seasonality (Michmerhuizen 

and others, 1996; Tranvik and others, 2009; Einola and 

others, 2011).
126 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Due to a shortage of empirical data and the lack of a 

coupled terrestrial and aquatic modeling framework, carbon 

fluxes and burial rates in the inland aquatic ecosystems of the 

Western United States were assessed separately from those 

of the terrestrial processes (chapters 5 and 9), as depicted in 

figure 1.2 of chapter 1 of this report. This chapter provides 

baseline estimates of carbon fluxes from inland aquatic 

systems that were calculated using empirical data spanning 

a time period from 1920 to 2011. More specifically, this 

chapter will provide estimates of (1) coastal export and 

within-ecoregion transport of both dissolved inorganic carbon 

(DIC) and total organic carbon (TOC) in riverine systems, 

(2) gaseous carbon emissions in the form of carbon dioxide 

from lacustrine and riverine systems, and (3) carbon burial 

rates in sediments of lacustrine systems. In contrast, the 

following chapter (chapter 11) supplies both baseline and 

projected changes in TOC fluxes from 1992 to 2050 to coastal 

areas and assesses the effect of nutrients and land cover on 

carbon burial rates in coastal estuaries, which are transition 

zones between the riverine and the oceanic systems.

The baseline estimates of carbon fluxes in inland 

aquatic ecosystems presented in this chapter benefited from 

two strengths in the methodology: (1) the estimated values 

were all based on large, spatially consistent datasets of 

water chemistry, flow, and sedimentation rates, and (2) the 

models made use of updated national hydrographic datasets 

in the conterminous United States, which improved the 

accuracy of these broad-scale fluxes. The value of computing 

these estimates is that it is possible to compare the relative 

magnitude of all fluxes across ecoregions, where changes in 

physiography and land-use associated with each ecoregion can 

have a large effect on carbon storage, transport, and loss to the 

atmosphere. Additionally, these baseline estimates can be used 

in an integrated analysis (chapter 12) to estimate an overall 

regional carbon budget that encompasses all of the ecosystems 

in the Western United States. 

10.3. Input Data and Methods

10.3.1. Lateral Carbon Transport in 

Riverine Systems

Lateral carbon fluxes in riverine systems included 

carbon derived from terrestrial ecosystems (forests, wetlands, 

agricultural lands), groundwater, and in-stream production 

(photosynthesis) minus the losses from sedimentation and 

carbon dioxide efflux to the atmosphere. Water-quality 

data were obtained from the National Water Information 

Service (NWIS) Web site (U.S. Geological Survey, 2012d). 

The dissolved inorganic carbon (DIC) concentration was 

estimated from pH, temperature, and either filtered or 

unfiltered alkalinity. The estimated total organic carbon (TOC) 

concentration was taken directly from water-quality data or 

was calculated as the sum of dissolved and particulate organic 

carbon (Stets and Striegl, 2012). 

Carbon fluxes (in kilograms per day, kg/day) were 

estimated from water-quality and daily streamflow data using 

the U.S. Geological Survey’s (USGS’s) Load Estimator 

Model (LOADEST; Runkel and others, 2004). LOADEST 

is a multiple-regression Adjusted Maximum Likelihood 

Estimation (AMLE) model which uses measured DIC 

or TOC concentration values to calibrate a regression 

between constituent load, streamflow, seasonality, and time 

(equation 1). 

( )

( )

2

01 2 3

2

4 5 6

0 1

ln a a ln a ln a sin 2

 a cos 2 a a 

where

ln was the natural log of the constituent load

(kg/d),

was the discharge,

was time in decimal years, a ,a ,..

LOAD Q Q dtime

dtime dtime dtime

LOAD

Q

dtime

=+ + + ∏

+ ∏ + + +ε

n .a were

regression coefficients, and

was an independent and normally distributed

error.

ε

(1)

The model calibration required at least 12 paired 

water-quality and daily streamflow values. The input data 

were log-transformed to avoid bias and centered to avoid 

multicollinearity. The models that were used to estimate loads 

for individual USGS stations varied in terms of coefficients 

and estimates of log load (equation 1), and the program was 

set to permit LOADEST to select the best of nine models 

based on Akaike’s Information Criterion (Runkel and others, 

2004). The estimated loads and their standard errors were used 

to develop 95-percent confidence intervals for various time 

periods. The model’s performance was examined by reviewing 

its output, such as the AMLE’s coefficient of determination 

(R2) values and residuals (model error). 

Two different datasets were used to estimate lateral TOC 

and DIC transport in riverine systems: the Coastal Export 

Dataset and the Ecoregional Comparison Dataset. The Coastal 

Export Dataset included data on NWIS sites located just 

upstream from the point where a river meets the coast or a 

national border. The coastal export of carbon was important 

to include in this assessment because the significant amounts 

of carbon transferred from terrestrial systems by rivers 

and delivered to coastal areas can help balance the overall 

regional or continental-scale carbon budgets (Schlesinger and 

Melack, 1981). 
Chapter 10 127

The Colorado River and the Rio Grande deliver carbon 

to the Gulf of California and western Gulf of Mexico, 

respectively. Carbon is delivered to the coastal Pacific Ocean 

from watersheds in California, Oregon, and Washington. The 

largest watershed is that of the Columbia River. In addition, 

several large endorheic basins (basins that do not drain to the 

ocean) exist in the Western United States, the largest of which 

is the Great Basin. Endorheic basins may contain streams 

and, although there is lateral carbon movement within them, 

they do not reach the ocean; therefore, the carbon from those 

streams was not included in estimates of lateral carbon flux 

to the coastal ocean. The total exorheic drainage area (basins 

that do drain to the ocean) in the Western United States was 

1.66 million square kilometers (km2). The Coastal Export 

Dataset included TOC and DIC export estimates from 36 sites 

in the Western United States (fig. 10.1A). 

The carbon export to the ocean was estimated by 

summing the mean observed carbon export from individual 

sites and then correcting for the drainage area that was not 

represented by the watersheds included in the database (Stets 

and Striegl, 2012). The total carbon export estimate (Total EC) 

was calculated using equation 2:

C C(IN) TOT IN ( )

C(IN)

TOT

IN

Total E E A /A

where

E was the carbon export estimated from

sites included in the database,

A was the total exorheicdrainage area, and

A was the total drainage for which lateral

flux estim

= ×

ates could be made.

(2)

This correction assumed an equivalent areal carbon yield from 

the remaining (unmeasured) exorheic drainage area. This 

estimate was performed separately for the Colorado River, Rio 

Grande, and for basins draining to the coastal Pacific Ocean.

Fluxes calculated from streamgages located near coastal 

waters were assigned to an associated coastal receiving 

waters’ region; however, some rivers within one receiving 

waters’ region often crossed ecoregional boundaries, so they 

were not necessarily instructive about differences in carbon 

fluxes among the ecoregions. Because a primary goal of this 

assessment was to explore ecoregional variability in carbon 

storage and fluxes across all of the Western United States, a 

second dataset (the Ecoregional Comparison Dataset) was 

created to include drainage basins contained entirely within 

single ecoregions in order to characterize lateral carbon flux. 

This dataset also included fluxes that were estimated from 

streamgages located upstream from coastal areas. This dataset 

included DIC estimates from 333 sites and TOC estimates 

from 94 sites (fig. 10.1B). These estimates were derived from 

smaller drainage basins ranging in size from 1.1 to 16,000 km2

and draining a total area of 327,902 km2.

The methods used for uncertainty analysis were applied 

in a similar manner for results from both the Coastal Export 

and Ecoregional Comparison Datasets. Daily carbon fluxes 

(kg/d) were summed by ecoregion for each representative 

station’s flux within either dataset. Then, daily fluxes were 

converted to annual fluxes (kilograms per year, kg/yr), 

and 95-percent confidence intervals were calculated from 

associated standard errors. Each flux value was connected to 

a USGS streamgage station, which had an associated drainage 

area (km2). The drainage areas for fluxes included in a 

particular receiving waters’ region or ecoregion were summed. 

The total DIC and TOC yields for an ecoregion (in grams of 

carbon per square meter per year, gC/m2/yr) were calculated 

by dividing the summed ecoregional annual fluxes by the 

summed drainage areas. All of the ecoregion boundaries used 

in this chapter are consistent with those presented in chapter 1

and are slightly modified from the U.S. Environmental 

Protection Agency’s (EPA’s) level II ecoregions (EPA, 1999).

10.3.2. Carbon Dioxide Efflux From 

Riverine Systems

Three values were required to measure the gas fluxes 

from aquatic systems: (1) the concentration of dissolved 

carbon dioxide, (2) the gas transfer velocity (k), and (3) the 

surface area of the water body. The vertical efflux of carbon 

dioxide from riverine systems in the Western United States 

was modeled according to established methods (Butman and 

Raymond, 2011) and as outlined in equation 3:

2 ( 2-water 2-air 2 )

2

2-water

CO Flux CO CO kCO SA

where

CO Flux was the total net emission of carbon

dioxide from riverine systems of 

the Western United States (in

teragrams of carbon per year, 

TgC/yr),

CO was the ri

= − ∗∗

2-air

2

verine carbon dioxide

concentration (in moles per liter,

 moles/L),

CO was the carbon dioxide concentration in

the atmosphere (in moles/L),

kCO was the gas transfer velocity of carbon

dioxide across the

2

 air-water interface

(in meters per second, m/s), and

SA was the riverine surface area (in square

meters, m ).

(3)

The total flux was estimated by summing all of the mean 

annual fluxes for a stream order (Strahler, 1952) within 

an ecoregion.
128 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The dissolved carbon dioxide concentrations 

(CO2-water) were estimated from riverine alkalinity data 

available through NWIS using the CO2SYS program5 

(van Heuven and others, 2009). CO2SYS linked parameters 

such as temperature, pH, and alkalinity to estimate the 

dissolved carbon dioxide concentrations by incorporating 

disassociation constants for carbonic acid (H2CO3) into its 

values. Disassociation constants are mathematical values that 

describe the tendency of a large molecule such as carbonic 

acid (H2CO3) to disassociate into smaller molecules such as 

bicarbonate (HCO 3

−), carbonate (CO 2

3

−), and carbon dioxide 

(CO2) in an aqueous environment. The disassociation constants 

used in the CO2SYS equations for this assessment were from 

Millero (1979). 

Water-chemistry data were collected from the late 1920s 

through 2011, and daily measurements of pH paired with 

temperature and alkalinity measurements were used to estimate 

dissolved carbon dioxide. For the five ecoregions in the Western 

United States, 1,545 USGS streamgaging-station locations 

had an adequate chemistry record, and their data were used for 

the carbon dioxide efflux estimate (fig. 10.2B). A minimum of 

12 sampling dates was required for inclusion in this analysis. A 

total of 101,852 daily chemical measurements was identified. 

The concentration of carbon dioxide in the atmosphere 

(CO2-air) was assumed to be constant at 390 ppm for all of the 

ecoregions in the Western United States in equation 3.

The gas transfer velocity (kCO2), which is the rate of 

exchange of carbon dioxide across the air-water interface, was 

based on the physical parameters of stream slope and water 

velocity (Melching and Flores, 1999; Raymond and others, 

2012). The average slope was derived from the NHDPlus 

datasets (Horizon Systems Corporation, 2005) for each 

stream order within each ecoregion in the Western United 

States. The average stream velocity estimates were based on 

hydraulic geometry parameters for each stream order. The 

stream discharge (volume of water per unit of time, in cubic 

Contributing drainage area to

 receiving water’s regions

Western Gulf of Mexico

Gulf of California

Coastal Pacific Ocean

Watershed associated

 with streamgage stations

EXPLANATION EXPLANATION

Level II ecoregion

Western Cordillera

Marine West Coast Forest

Cold Deserts

Warm Deserts

Mediterranean California

NWIS streamgage 

NWIS streamgage station station

N

A. Lateral export to coast B. Lateral flux by ecoregion

0 200 400 MILES

0 200 400 KILOMETERS

Figure 10.1. Maps showing the locations of the National Water Information System (NWIS) streamgage stations and 

associated drainage areas. A, Stations included in the Coastal Export Dataset. B, Stations included in the Ecoregional 

Comparison Dataset. 

5Mathworks, Inc., Natick, Mass.
Chapter 10 129

meters per second, m3/s) was dependent on the width (m) 

and depth (m) of the stream channel as well as the velocity 

of the water moving within the stream (meters per second, 

m/s) (Leopold and Maddock, 1953; Park, 1977). The stream 

surface area (SA) in square meters (m2) was calculated as the 

product of the average width and total length of the stream by 

stream order. 

Error propagation and uncertainty analyses were 

performed for each component of equation 3. A bootstrapping 

technique outlined in Efron and Tibshirani (1993) and Butman 

and Raymond (2011) was used to estimate error. Bootstrap 

with replacement (α=0.05) was run for 1,000 iterations 

to calculate 95-percent confidence intervals for the 

concentrations of pCO2 for each stream order within an 

ecoregion. Similarly, bootstrap with replacement was used to 

estimate confidence intervals associated with the hydraulic 

geometry coefficients derived from the measurements of 

stream width and velocity, which were subsequently used 

to estimate both the stream surface area and gas transfer 

velocity (R Development Core Team, 2008). The overall bias 

associated with the estimates of pCO2 remained low and had 

a negligible effect on the error associated with the use of the 

mean value for each stream order. Similarly, the effect of 

bootstrapping the hydraulic geometry parameters produced 

minimal bias. 

A Monte Carlo simulation was performed for each 

stream-order estimate of the total flux (TgC/yr) from riverine 

surfaces (equation 3). The 5th to 95th confidence intervals 

derived from the bootstrapping discussed above were used 

to constrain the Monte Carlo simulation for each parameter 

of equation 3. The total flux calculation was replicated 

1,000 times. This approach was considered to be conservative 

as it allowed for the same probability of all combinations 

of each parameter in the total flux equation to be selected 

for each stream order and may have overestimated the error 

associated with the riverine efflux. 

All of the estimates for the total carbon flux within an 

ecoregion were presented with the 5th and 95th confidence 

intervals derived from the Monte Carlo simulation. By using 

this conservative approach, the range of estimates generally 

had a high bias because of a slight positive skew in the 

distribution of pCO2 concentration within a stream order 

and ecoregion. The mean concentrations were chosen over 

the median values because the broader spatial representation 

was better approximated by incorporating mean values in 

the Western United States. All of the estimates derived from 

the Monte Carlo simulation were adjusted to account for 

monthly temperatures below freezing because it was assumed 

that riverine efflux did not occur when monthly temperatures 

averaged below 0°C. This adjustment reduced the estimated 

efflux measurements for the Western Cordillera and the Cold 

Deserts ecoregions by 25 percent and 19 percent, respectively. 

10.3.3. Carbon Dioxide Efflux From 

Lacustrine Systems

Water-chemistry data were obtained from the EPA’s 

2007 National Lakes Assessment (NLA; EPA, 2009a). The 

NLA used a probability-based survey design to select lakes 

and reservoirs that met the following criteria: (1) greater 

than 4 hectares (ha) in area, with a minimum of 0.1 ha of 

open water; (2) at least 1 m deep; and (3) not classified or 

described as treatment or disposal ponds, or as brackish-water 

or ephemeral bodies (EPA, 2009a). Of the 68,223 lakes and 

reservoirs in the conterminous United States, 1,028 met those 

criteria. Of those, 252 were located in the Western United 

States; their locations are shown in figure 10.2C.

Sampling took place during the summer of 2007; 

50 percent of the samples were obtained between July 12 and 

August 23, and nearly all (99 percent) were obtained between 

June 1 and September 30. Twenty-two lakes were sampled 

twice, and these replicates helped to increase the sample data 

accuracy. For the lakes that were sampled twice, the data were 

averaged. The data were assigned to one of the five ecoregions 

in the Western United States. The number of lakes ranged 

from 12 to 166 per ecoregion, or one lake for every 38,700 to 

2,300 km2 of total area (including both land and water). 

Various biological, physical, and chemical indicators 

were measured during the NLA (EPA, 2009a), and only a 

subset of water-chemistry and physical data was used in 

this assessment: acid-neutralizing capacity (ANC, assumed 

to be equal to alkalinity), pH, temperature, and dissolved 

organic carbon (DOC). The final working dataset represented 

260 observations from 245 sites.

The estimated carbon dioxide flux from lacustrine 

systems was calculated using the general equation 3. 

The estimated dissolved carbon dioxide (CO2water) was 

computed using the equilibrium geochemical model 

PHREEQC (Parkhurst and Appelo, 1999). This model 

is similar to CO2SYS in that parameters such as water, 

temperature, pH, and alkalinity were used to estimate carbon 

dioxide concentrations.

The gas transfer velocity (k) for lacustrine systems is 

largely a function of windspeed (m/s) Cole and Caraco (1998). 

The estimated mean summer (June to September) wind 

speeds for each ecoregion were determined from the National 

Aeronautics and Space Administration’s (NASA’s) surface 

meteorology and solar energy data (NASA, 2012; Cory P. 

McDonald, USGS, unpub. data, 2012). The surface areas of 

lakes and reservoirs were tabulated for each ecoregion, as in 

McDonald and others (2012). 
130 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Figure 10.2. Maps showing the estimated relative magnitude 

of carbon yields, in grams of carbon per square meter per year 

(gC/m2/yr). A, Lateral carbon fluxes in riverine systems. B, Carbon 

dioxide emissions from riverine systems. C, Carbon dioxide 

emissions from lacustrine systems. D, Carbon burial rates in 

0 200 400 MILES

0 200 400 KILOMETERS

A. Lateral carbon fluxes B. River and stream carbon dioxide emissions

Carbon yield, in grams of carbon 

 per square meter per year

0 to 750

>750 to 1,000

>1,000 to 2,000

>2,000 to 3,000

>3,000 to 6,000

>6,000 to 12,000

>12,000 to 24,000

0 to 4.4

>4.4 to 6.6

>6.6 to 8.8

>8.8 to 11.0

EXPLANATION

0 to 5

>5 to 10

>10 to 20

>20 to 40

Carbon yield, in grams of carbon

 per square meter per year

EXPLANATION

Partial pressure of carbon dioxide, 

 in microatmospheres 

lacustrine systems. Parts B to D show locations of calibrated 

sample data, and parts B and C also indicate the estimated 

relative magnitude of the partial pressure of carbon dioxide 

(pCO2

) concentrations at the sampling locations.
Chapter 10 131

C. Lake and reservoir carbon dioxide emissions D. Lake and reservoir carbon burial

Modeled percent

 organic carbon 

0 to –0.8 Sedimentation model

–0.9 to –1.2

–1.3 to –1.6

0 to 0.3

>0.3 to 0.5

>0.5 to 1.0

>1.0 to 1.2

Carbon yield, in grams of carbon

 per square meter per year

EXPLANATION

Carbon yield, in grams of carbon

 per square meter per year

EXPLANATION

Partial pressure of carbon dioxide, 

 in microatmospheres 

0 to 400

>400 to 600

>600 to 1,000

>1,000 to 2,000

>2,000 to 5,000

>5,000 to 10,000

>10,000 to 30,000

Figure 10.2.—Continued
132 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Many of the parameters involved in these calculations 

violated normality assumptions; therefore, nonparametric 

confidence intervals (95 percent) were determined on 1 million 

ordinary bootstrap replicates. The confidence intervals for 

the estimated fluxes were determined by propagation of 

uncertainty, except for the total values (for example, the sum 

of the regional estimates). In those cases, the confidence 

intervals were assumed to be additive (uncertainty was 

not propagated) because potential errors in the regional 

estimates were likely to be systematic. For the two ecoregions 

with extended periods of below-freezing air temperatures 

(the Western Cordillera and the Cold Deserts), the lower 

confidence interval was adjusted by assuming that carbon 

dioxide only degasses (at the estimated rate) during the icefree season. This approach was conservative because carbon 

dioxide stored under ice is released when the ice melts.

10.3.4. Carbon Burial in Lacustrine Systems 

Carbon burial in lacustrine systems is a function of 

sedimentation rates, carbon concentrations in lacustrine 

sediments, and the areal extent of lacustrine systems:

12

burial conc WB

burial

2

conc

C SedRt C SA 10

where

C was the carbon burial rate (in TgC/yr),

SedRt was the sedimentation rate (in gC/m /yr),

C was the concentration of carbon 

in sediments (in percent by dry 

weig

− = ∗∗ ∗

WB

2

12

ht),

SA was the surface area of the water 

body (in m ), and

10 was a conversion factor to convert 

from grams to teragrams.

−

(4)

Data on sedimentation rates and on carbon concentrations 

in sediments were sparse, necessitating an empirical approach 

that relied on existing data to build geostatistical models, 

which were then used to estimate carbon burial rates. The 

input data included (1) sedimentation rates derived from 

a national database (for reservoirs) and peer-reviewed 

literature (for lakes) and (2) carbon concentrations obtained 

from measurements on sediment samples collected as part 

of a national-scale synoptic survey on the water quality of 

lacustrine systems. 

The areal extents of lacustrine systems were derived from 

the high-resolution (1:24,000) USGS National Hydrography 

Dataset (NHD; USGS, 2012c). Both sedimentation rates in 

lakes and carbon concentrations in lake sediments are usually 

different from those in reservoirs (Mulholland and Elwood, 

1982; Dean and Gorham, 1998); thus, the water bodies were 

separated into lake and reservoir classes. Water bodies were 

classified as reservoirs if they met any of the following 

criteria: (1) the water body was tagged as a reservoir in the 

NHD, (2) the water body name included the word “reservoir” 

in it, or (3) the water body was included in the National 

Inventory of Dams database (U.S. Army Corps of Engineers, 

2012). Water bodies that were not classified as reservoirs 

were assumed to be lakes. A comparison with ground-based 

observations on the 697 lakes that were visited during the 

2007 NLA (EPA, 2009a) indicated that this classification 

scheme was correct 80 percent of the time; however, 

misclassification rates might have been higher for small water 

bodies (≤4 ha), such as farm ponds, which were not sampled 

during the NLA.

The best available national dataset of reservoir 

sedimentation rates was the Reservoir Sedimentation Database 

(RESSED; Advisory Committee on Water Information, 

Subcommittee on Sedimentation, 2012), which included 

sedimentation-rate data on over 1,800 georeferenced 

reservoirs in the United States (Mixon and others, 2008; 

Ackerman and others, 2009). The sedimentation rates in the 

RESSED database were estimated from repeat bathymetric 

surveys and were expressed in acre feet per year to facilitate 

the estimation of storage losses. On the basis of the hypothesis 

that sedimentation rates were related to land use, topography, 

soils, and vegetation characteristics in the area surrounding 

the reservoirs, a GIS analysis was performed to quantify 

these characteristics for each hydrologic unit (represented by 

a 12-digit hydrologic unit code, or HUC; U.S. Department 

of Agriculture, Natural Resources Conservation Service, 

2012) adjacent to each reservoir. The sedimentation rates 

in the RESSED database strongly correlated with the net 

contributing area (coefficient of determination, R2=0.94). 

The values for the net contributing area, however, were not 

available for most reservoirs in the United States; therefore, 

a reservoir’s surface area, which should scale with the 

net contributing area, was used as a surrogate for the net 

contributing area. 

The RESSED dataset was split evenly into calibration 

and validation datasets, and a stepwise multiple-linearregression (MLR) analysis was performed on the calibration 

data, where the sedimentation rate was the dependent variable 

and the land-use and basin characteristics were explanatory 

variables. The explanatory variable that explained the most 

variance in the sedimentation rate entered the model first. The 

variances explained by the remaining explanatory variables 

were recalculated, and the variable that explained the next 

greatest amount of variance entered the model next. This 

iterative process was repeated until no additional variables 

showed statistically significant correlations to sedimentation 

rates, using a p-value ≤0.1. The multicollinearity among 

explanatory variables was evaluated using the variance 

inflation factor (1/1–R2) (Hair and others, 2005), which had 

a threshold for exclusion of 0.2. The resulting MLR equation 

was used to estimate the sedimentation rates for all of the 

reservoirs in the NHD. The standard error of the equation 

was used to calculate uncertainty with 95-percent confidence 

intervals for the predicted sedimentation rates for sites in the 

validation dataset. 
Chapter 10 133

A national dataset of lake sedimentation rates does not 

exist; therefore, sedimentation rates were estimated on the 

basis of data in peer-reviewed literature. Lake sedimentation 

rates have been calculated for over 80 lakes around the 

world using 210Pb and 137Cs isotope dating techniques 

on sediment cores; in most studies, multiple cores were 

collected from each lake. A review of peer-reviewed literature 

identified data for sites in North America, Europe, Africa, 

Asia, New Zealand, and Antarctica. The data were compiled 

and a statistical analysis was performed to characterize a 

probability distribution function (pdf) of lake sedimentation 

rates. A sedimentation rate was assigned to each lake in 

the NHD using random sampling with replacement. This 

procedure was repeated 100 times, drawing a new value 

from the statistical distribution each time, in order to obtain 

100 possible sedimentation-rate values. Each of these values 

was used to calculate a carbon burial rate using equation 4, 

providing a range of carbon burial estimates for each lake in 

the NHD. Uncertainty at the 95-percent confidence level was 

calculated as 2×F-pseudosigma, which is a nonparametric 

equivalent to the standard deviation when sample data have a 

normal distribution.

Carbon concentrations were measured on sediment 

samples collected from 697 water bodies during the 2007 

NLA (EPA, 2009a). The data were split into calibration 

and validation datasets, and a stepwise MLR analysis was 

performed using the same methods and explanatory variables 

as in the reservoir sedimentation-rate analysis. The resulting 

equation was used to estimate carbon concentrations in lake 

and reservoir sediments in unsampled water bodies across the 

Western United States. Uncertainty and model performance 

were evaluated as in the reservoir sedimentation-rate analysis.

10.4. Results 

10.4.1. Lateral Carbon Transport in 

Riverine Systems

The total carbon export from exorheic basins, calculated 

using the Coastal Export Dataset, was estimated to be 7.2 

(ranging from 5.5 to 8.9) TgC/yr (table 10.1), with more 

than 75 percent of the export occurring as DIC. The carbon 

exported to the western Gulf of Mexico and the Gulf of 

California was a small proportion of this total, estimated at 

approximately 0.1 TgC/yr (table 10.1); the remainder, an 

estimated 7.1 TgC/yr, was exported to the coastal Pacific 

Ocean (table 10.1). The Columbia River exported the highest 

carbon load in this region at an estimated 3.1 TgC/yr. The 

Klamath River, which had the next highest load, carried 

approximately one-tenth the carbon load of the Columbia 

River at an estimated 0.32 TgC/yr.

Table 10.1. Estimated carbon exports, carbon yields (fluxes normalized to watershed areas), and percentages of the total 

export as dissolved inorganic carbon organized by the three main receiving waters’ regions in the Western United States. 

[Sites represent U.S. Geological Survey streamgaging stations for which data were available to calculate estimated carbon fluxes from exorheic 

basins. The 95-percent confidence intervals for the yields and exports are given in the parentheses. The estimated total exports and yields were 

calculated by summing the dissolved inorganic carbon (DIC) and total organic carbon (TOC). gC/m2/yr, grams of carbon per square meter per 

year; TgC/yr, teragrams of carbon per year] 

Receiving water’s region Number

of sites

Estimated total export 

(95-percent 

confidence interval)

(TgC/yr)

Estimated total yield 

(95-percent 

confidence interval)

(gC/m2

/yr)

Estimated flux

as dissolved 

inorganic carbon

(percent of total export)

Coastal Pacific Ocean 35 7.10 (5.42, 8.78) 6.29 (5.90, 6.68) 77

Western Gulf of Mexico1 1 0.020 (0.011, 0.028) 0.06 (0.05, 0.07) 79

Gulf of California2 1 0.076 (0.074, 0.079) 0.12 (0.10, 0.13) 93

All regions 37 7.20 (5.52, 8.88) 3.38 (2.59, 4.17) 77

1Rio Grande, partially drains the South-Central Semi-Arid Prairies ecoregion of the Great Plains region.

2Colorado River.
134 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The estimated carbon yields and fluxes, calculated using 

the Ecoregional Comparison Dataset, were highest in the 

Marine West Coast Forest ecoregion and lowest in the Warm 

Deserts ecoregion (table 10.2; fig. 10.2A). The Marine West 

Coast Forest ecoregion had a relatively high estimated total 

carbon yield, but the estimated total export was low because 

of the ecoregion’s small area, which is approximately 10 times 

smaller than the Western Cordillera ecoregion. Conversely, 

the Cold Deserts had a relatively high estimated export value 

because of its extensive land surface area, which is the largest 

in the Western United States at 1,055,715 km2. The estimated 

dissolved inorganic carbon was between 65 and 75 percent of 

the estimated total carbon export from all regions. 

Much of the variability in ecoregional estimates can be 

explained by differences in the mean runoff and in mean DIC 

and TOC concentrations. There was substantial variability 

in the mean runoff among the ecoregions (ranging from an 

estimated 14 to 1,259 millimeters per year, or mm/yr). The 

greatest mean runoff was estimated in the Marine West Coast 

Forest and the Western Cordillera ecoregions and the smallest 

amount was in the Warm Deserts ecoregion. For each of the 

ecoregions, the estimated mean DIC concentrations were 

higher than the estimated mean TOC concentrations, but 

the estimated mean DIC concentrations in the Cold Deserts 

ecoregion (62.4 milligrams per liter, or mg/L) were nearly 

eight times higher than the estimated mean DIC concentrations 

in the Marine West Coast Forest ecoregion (8.7 mg/L). 

10.4.2. Carbon Dioxide Efflux From 

Riverine Systems

The estimated mean concentration of dissolved carbon 

dioxide in riverine systems across the Western United States 

exceeded atmospheric concentrations, indicating that these 

ecosystems were sources of carbon to the atmosphere. The 

estimated mean pCO2 concentration was greatest in the Warm 

Deserts at 2,391 microatmospheres (μatm; 6.1 times greater 

than the atmospheric concentrations of carbon dioxide) and 

smallest in the Western Cordillera at 1,357 μatm (3.4 times 

greater than the atmospheric concentrations of carbon 

dioxide). The estimated mean pCO2 for all five ecoregions 

combined was 1,893 μatm (3.4 times greater than the 

atmospheric concentrations of carbon dioxide) (fig. 10.2C).

Stream surface areas ranged from 365 km2 in the 

Mediterranean California ecoregion to 2,336 km2 in the 

Western Cordillera (table 10.3), which was from 0.22 to 

0.27 percent of the total area of the ecoregion, respectively. 

Although its total area was small, the percentage of area 

covered by riverine systems in the Marine West Coast Forest 

was the highest of all the ecoregions at 0.73 percent. The total 

stream surface area for the Western United States region was 

6,076 km2, which was 0.23 percent of the region’s area. 

Table 10.2. Estimated carbon fluxes, yields (fluxes normalized to watershed areas), and percentages of total flux as dissolved 

inorganic carbon from riverine systems in the Western United States. 

[Sites represent U.S. Geological Survey streamgaging stations in both endorheic and exorheic basins for which data were available to calculate 

estimated dissolved inorganic carbon (DIC) and total organic carbon (TOC) fluxes, respectively. The 95-percent confidence intervals for the yields 

and exports are presented in parentheses. The estimated total fluxes and yields were calculated by summing the estimated DIC and TOC. An asterisk 

(*) indicates DIC values only. gC/m2/yr, grams of carbon per square meter per year; NA, not available; TgC/yr, teragrams of carbon per year] 

Ecoregion

Number of sites

(DIC fluxes, 

TOC fluxes)

Estimated total flux

(95-percent 

confidence interval)

(TgC/yr)

Estimated total yield

(95-percent 

confidence interval)

(gC/m2

/yr)

Estimated flux 

as dissoved 

inorganic carbon

(percent of total flux)

Western Cordillera 224, 61 4.57 (4.15, 5.09) 5.23 (4.76, 5.83) 74

Marine West Coast Forest 11, 6 0.9 (0.68, 0.1.38) 11.0 (7.97, 16.24) 66

Cold Deserts 72, 23 2.41 (2.00, 2.9) 2.29 (1.9, 2.75) 80

Warm Deserts 3, NA 1.00 (0.85, 1.18)* 2.17 (1.83, 2.55)* NA

Mediterranean California 23, 4 0.43 (0.25, 0.86) 2.61 (1.54, 5.20) 75

Western United States (total) 333, 94 9.35 (7.93, 11.41) 3.64 (3.18, 4.33)
Chapter 10 135

The estimated total riverine vertical carbon efflux for 

the Western United States was converted to carbon dioxide 

equivalent, which produced a value of 95.6 teragrams of 

carbon dioxide equivalent per year (TgCO2-eq/yr; confidence 

interval from 57.0 to 166.3 TgCO2-eq/yr). The estimated 

carbon efflux ranged from a high of 43.1 TgCO2-eq/yr 

(confidence interval from 26.7 to 77.0 TgCO2-eq/yr) in the 

Western Cordillera to a low of 5.5 TgCO2-eq/yr (confidence 

interval from 2.9 to 10.6 TgCO2-eq/yr) in the Warm Deserts 

(table 10.3). The estimated riverine efflux for the Western 

United States on a per-unit-of-area basis was 14.0 gC/m2/yr 

(confidence interval from 7.2 to 20.63 gC/m2/yr); on 

an ecoregional basis, the estimated efflux ranged from 

3.6 gC/m2/yr (confidence interval from 1.8 to 6.1 gC/m2/yr) in 

the Warm Deserts to 35.7 gC/m2/yr (confidence interval from 

23.7 to 86.6 gC/m2/yr) in the Marine West Coast Forest. 

10.4.3. Carbon Dioxide Efflux from 

Lacustrine Systems

The estimated mean concentration of pCO2 in lacustrine 

systems of the Western United States was 733 μatm 

(fig. 10.2C), which was greater than the atmospheric 

concentrations for all of the ecoregions; this estimated mean 

pCO2 indicated that the lakes generally were sources of carbon 

to the atmosphere. The estimated mean pCO2 was greatest in 

the Western Cordillera at 1,036 μatm (2.7 times greater than 

the atmospheric concentration of carbon) and smallest in the 

Marine West Coast Forest at 599 μatm (1.5 times greater than 

the atmospheric concentration of carbon). 

The estimated flux of carbon dioxide across the air‐water 

interface was primarily determined by the gradient between 

the dissolved and atmospheric concentrations of carbon. 

The greatest flux was estimated for the Western Cordillera 

at 106 gC/m2/yr (or 389 gCO2-eq/m2/yr), and the smallest 

flux was estimated for the Marine West Coast Forest at 

36.5 gC/m2/yr (or 134 gCO2-eq/m2/yr). These fluxes were 

given as the mass flow per unit of area of the water surface. 

The estimated mean flux across the air-water interface for all 

of the ecoregions was 58 grams of carbon per square meter 

per day (gC/m2/d), or 219 grams of carbon dioxide equivalent 

per square meter per day (gCO2-eq/m2/d). The estimated gas 

transfer velocity was less variable than the estimated pCO2

among all of the ecoregions—smallest in Western Cordillera 

(0.93 meters per day, or m/d) and greatest in the Warm 

Deserts (1.22 m/d).

The ecoregional estimates of total annual carbon 

dioxide efflux from lacustrine systems (table 10.4) 

ranged from 0.02 TgC/yr in the Marine West Coast Forest 

to 1.0 TgC/yr in the Western Cordillera, or from 0.1 to 

3.6 TgCO2-eq/yr, respectively. The total carbon dioxide 

efflux from the Western United States was estimated to 

be 2.1 TgC/yr (95-percent confidence interval of 1.1 to 

3.3 TgC/yr), or 7.6 TgCO2-eq/yr. The estimated ecoregional 

efflux values were directly related to the surface area of 

the lacustrine systems (table 10.4), which varied among 

the ecoregions, partially because of differences in regional 

morphology and climate but mainly because of differences in 

the size of the ecoregions.

Table 10.3. Estimated vertical effluxes and yields of carbon dioxide from riverine systems in the five ecoregions of the 

Western United States.

[Sites are U.S. Geological Survey streamgaging stations for which data were available to calculate the estimated pCO2. Errors associated with both 

the total flux and areal flux estimates are presented in parentheses and represent the 5th and 95th percentiles derived from Monte Carlo simulation. 

Estimated carbon yields were calculated by dividing the estimated total flux by the ecoregion area. gC/m2/yr, grams of carbon per square meter per 

year; km2, square kilometers; TgC/yr, teragrams of carbon per year]

Ecoregion Number of 

sites

Stream area 

(km2

)

Estimated total flux 

(5th and 95th 

percentiles)

(TgC/yr)

Estimated total yield

(5th and 95th 

percentiles)

(gC/m2

/yr)

Western Cordillera 518 2,336 11.76 (7.3, 21.0) 9.87 (8.4, 24.1)

Marine West Coast Forest 151 619 4.04 (2.0, 7.37) 35.72 (23.7, 86.5)

Cold Deserts 607 2,305 6.15 (4.1, 9.1) 7.16 (3.9, 8.7)

Warm Deserts 107 451 1.53 (0.8, 2.9) 3.57 (1.8, 6.1)

Mediterranean California 162 365 2.65 (1.5, 5.0) 17.1 (8.8, 30.5)

Western United States (total) 1,545 6,076 26.13 (15.7, 45.4) 14.03 (6.0, 17.1)
136 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

In order to facilitate a direct comparison between 

lake and reservoir gas fluxes, lateral carbon transport, 

carbon burial, and terrestrial processes, the estimated 

carbon dioxide flux values were normalized to the total 

land surface area in each ecoregion to provide the carbon 

yield (table 10.4, fig. 10.2C). The estimated carbon yields 

ranged from 0.3 gC/m2/yr in the Warm Deserts ecoregion 

to 1.1 gC/m2/yr in the Western Cordillera ecoregon. The 

estimated mean carbon yield (expressed as carbon dioxide 

efflux per unit of area) from lacustrine systems in the Western 

United States was 0.6 gC/m2/yr.

10.4.4. Carbon Burial in Lacustrine Systems 

The estimated total annual carbon burial rate 

in lacustrine systems of the Western United States 

was −2.42 TgC/yr and varied substantially among 

ecoregions (table 10.5; fig. 10.2D). The Western 

Cordillera ecoregion had the highest estimated carbon 

burial rate of −1.14 TgC/yr (confidence interval from 

–1.71 to –0.57), and the Marine West Coast Forest 

ecoregion had the lowest estimated carbon burial rate 

of −0.10 TgC/yr (confidence interval from –0.15 to 

–0.05). The estimated carbon yield in lacustrine systems, 

normalized by ecoregion area, was −1.2 gC/m2/yr 

(confidence interval from –1.8 to −0.6 gC/m2/yr). The 

estimated yields ranged from −0.4 gC/m2/yr (confidence 

interval from −0.8 to −0.3 gC/m2/yr) in the Warm 

Deserts ecoregion to −1.3 gC/m2/yr (confidence interval 

from −2.0 to −0.7 gC/m2/yr) in the Marine West Coast 

Forest ecoregion. 

The estimated sedimentation rates in reservoirs in the 

Western United States ranged from 8,622 to 10,068 gC/m2/yr 

(TgC/yr normalized to the area of the water body). The lowest 

estimated rates were in the Warm Deserts ecoregion, and the 

highest estimated rates were in the Western Cordillera and 

Cold Deserts ecoregions. The estimated sedimentation rates 

for lakes compiled from the literature followed an exponential 

distribution, with an abundance of lakes having low rates and 

relatively few having high rates. The estimated mean mass 

sedimentation rates in the lakes were much lower than those in 

reservoirs, with the mean lake sedimentation rate estimated to 

be 2,488 gC/m2/yr.

The carbon concentrations in lacustrine sediments varied 

substantially among the ecoregions of the Western United 

States. Sediment concentrations were highest in the Marine 

West Coast Forest ecoregion (11.4 percent) and relatively low 

in the Warm Deserts ecoregion (5.0 percent). The specific 

carbon burial rates (rates normalized to the area of a water 

body) indicated the intensity of carbon cycling in lacustrine 

systems. The estimated specific carbon burial rates (per unit 

of area) were highest in the Marine West Coast Forest at 

−147 gC/m2/yr (confidence interval from –222 to –72) and 

lowest in the Warm Deserts at −84 gC/m2/yr (confidence 

interval from –126 to –42).

Overall, the estimated specific carbon burial rates 

were strongly correlated with the estimated amounts of soil 

organic carbon (SOC, in gC/m2) near the water bodies; the 

R2 value between estimated carbon burial rates in reservoirs 

and estimated SOC was 0.96 (p-value=0.01), and the R2

value between estimated carbon burial rates in lakes and 

estimated SOC was 0.99 (p-value=<0.001). These results 

Table 10.4. Estimated vertical flux of carbon dioxide from lacustrine systems in the five ecoregions of the 

Western United States. 

[Sites are from the 2007 National Lakes Assessment (EPA, 2009a). The data from the 2007 NLA were used in the calculation of 

pCO2. Errors associated with both the estimated total flux and yield are presented in parentheses. They represent the bootstrapped 

5th and 95th confidence intervals. Estimated carbon yields were calculated by dividing the estimated total flux by the ecoregion 

area. gC/m2/yr, grams of carbon per square meter per year; km2, square kilometers; TgC/yr, teragrams of carbon per year]

Ecoregion Number of 

sites

Lake and

reservoir area 

(km2

)

Estimated total flux

(5th and 95th

confidence intervals)

(TgC/yr)

Estimated total yield

(5th and 95th

confidence intervals)

(gC/m2

/yr)

Western Cordillera 137 9,410 0.99 (0.63, 1.28) 1.15 (0.73, 1.49)

Marine West Coast Forest 18 689 0.02 (0.00, 0.08) 0.29 (–0.01, 1.00)

Cold Deserts 68 13,500 0.88 (0.43, 1.54) 0.84 (0.41, 1.47)

Warm Deserts 10 2,630 0.12 (0.06, 0.17) 0.25 (0.14, 0.37)

Mediterranean California 12 1910 0.07 (0.00, 0.16) 0.46 (0.00, 1.02)

Western United States (total) 245 28,139 2.08 (1.13, 3.25) 0.80 (0.43, 1.24)
Chapter 10 137

indicate strong connections between SOC, lacustrine sediment 

carbon concentrations, and carbon burial rates in lacustrine 

systems. Of the five ecoregions in the Western United States, 

the Marine West Coast Forest had the highest estimated SOC 

(1,824 gC/m2) and the highest estimated specific carbon 

burial rates (−147 gC/m2/yr). The Warm Deserts had the 

lowest estimated SOC (246 gC/m2) and lowest estimated 

specific carbon burial rates (−84 gC/m2/yr). In reservoirs, 

the estimated specific carbon burial rates were positively 

correlated to the prevalence of forests in nearby areas 

(R2=0.79, p-value=0.04); in lakes, the specific carbon burial 

rates were more strongly associated with wetlands (R2 =0.78, 

p-value=0.05). 

10.5. Discussion

10.5.1. Coastal Export, Lateral Transport, and 

Carbon Dioxide Efflux From Riverine Systems

The coastal export values represented the estimated 

amount of carbon that exited the terrestrial landscape and 

was delivered to the coast. This carbon could potentially 

have been stored in the ocean or could have contributed to 

coastal ocean ecosystem processing. The Gulf of California 

and western Gulf of Mexico, both located adjacent to the 

drier regions of the Western United States, received waters 

from one dominant watershed, either the Colorado River or 

Rio Grande, respectively. The Pacific Northwest, however, 

experienced much higher precipitation, and many more river 

basins (about 30) delivered carbon to the receiving waters of 

the Pacific Ocean; in fact, the highest proportion of land area 

represented as riverine systems (0.73 percent) was found in 

the Marine West Coast Forest ecoregion, which was more than 

double the surface area represented by riverine systems in the 

other remaining ecoregions. One of the defining characteristics 

of the Marine West Coast Forest was the high rate of 

precipitation, and higher annual precipitation increased the 

transfer of carbon, in either organic or inorganic forms, from 

the terrestrial environment to streams and rivers (Omernik and 

Bailey, 1997).

Riverine systems in the Marine West Coast Forest 

delivered more carbon at a higher estimated rate per unit 

of area than either the Rio Grande or the Colorado River. 

Despite the geographic prominence of large river basins, 

such as the Colorado River and the Rio Grande, the large 

annual runoff in the Marine West Coast Forest caused this 

ecoregion to dominate carbon delivery such that even much 

smaller rivers with coastal endpoints in this ecoregion 

were important sources of carbon export to coastal areas. 

These rivers included (1) the Eel River in Scotia, California 

(drainage=8,031 km2), (2) the Elder River near Branscomb, 

California (drainage=17 km2), and (3) the Queets River near 

Clearwater, Washington (drainage=1,148 km2). The Rio 

Grande, despite its large drainage size, had an annual runoff 

of only 1 mm/yr compared with annual runoff exceeding 

3,000mm/yr just from several rivers in coastal Washington. 

The coastal carbon yields were defined as the amounts 

of carbon remaining after balancing the inputs and outputs 

within a watershed, which ranged in area between about 

20and 650,000 km2. Many of the larger watersheds crossed 

ecoregional boundaries; for example, the Snake River’s 

headwaters are in the Western Cordillera, but its flow path 

traverses the Cold Deserts twice before reaching the mainstem 

portion of the Columbia River, which ultimately meets 

Table 10.5. Estimated carbon burial rates in lacustrine sediments in the five ecoregions of the Western United 

States. 

[Sites are from the 2007 National Lakes Assessment dataset (EPA, 2009a), which was used to estimate carbon concentrations in 

sediment. The 95-percent confidence intervals associated with the estimated total fluxes and yields are presented in parentheses. 

Estimated carbon yields were calculated by dividing the estimated total flux divided by the ecoregion area. gC/m2/yr, grams of carbon 

per square meter per year; TgC/yr, teragrams of carbon per year]

Ecoregion Number of 

sites

Estimated total flux

(95-percent

confidence interval)

(TgC/yr)

Estimated total yield

(95-percent

confidence interval)

(gC/m2

/yr)

Western Cordillera 71 −1.14 (−1.82, −0.57) −1.1 (−1.8, −0.6)

Marine West Coast Forest 10 −0.10 (−0.15, −0.05) −1.3 (−2.0, −0.7)

Cold Deserts 46 −0.74 (−1.07, −0.36) −1.3 (−2.0, −0.7)

Warm Deserts 7 −0.20 (−0.26, −0.09) −0.4 (−0.8, −0.3)

Mediterranean California 4 −0.24 (−0.35, −0.12) −1.3 (−2.0, −0.7)

Western United States (total) 138 −2.42 (−3.65, −1.22) −1.2 (−1.8, −0.6)
138 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

the Pacific Ocean in the Marine West Coast Forest. The 

headwaters of many of the larger rivers (such as the Rogue, 

Klamath, and Sacramento Rivers) that contribute to coastal 

fluxes in the Mediterranean California and Marine West Coast 

Forest ecoregions are located in the uplands of the Western 

Cordillera ecoregion. This spatial mismatch is important to 

consider in terms of ecoregional carbon budgets because 

rivers are not passive transporters of material, and much of the 

carbon from the headwater source may be transformed or lost 

before it reaches the ocean.

In order to estimate meaningful ecoregional lateral flux 

values, the Ecoregional Comparison Dataset included data 

only from watersheds that fell entirely within the ecoregional 

boundaries. The benefit of this approach was that the entire 

watershed, and therefore both the riverine carbon sources and 

sinks, were defined by the ecoregion’s unique characteristics. 

By using this approach, the differences in flux based on 

climate, vegetation, and topography could be more easily 

discerned. This approach skewed the dataset toward smaller 

watersheds and rivers, but the larger watersheds of the Western 

United States—in particular, the Columbia River, the Colorado 

River, and the Rio Grande—were represented in the coastal 

export section well. 

Both the estimated coastal export and ecoregional 

lateral‐flux values demonstrated that runoff or precipitation 

was a major driver in the variability of both DIC and TOC 

yields (Amiotte-Suchet and Probst, 1995; Raymond and 

Oh, 2007; Hartmann, 2009). The two sets of results also 

highlighted the dominant role of DIC in total carbon export to 

the coast, as DIC was between 77 to 93 percent of all carbon 

exports and was between 65 and 80 percent of ecoregional 

lateral fluxes. In contrast, recent global carbon studies have 

suggested that the global TOC and DIC export was nearly 

equal (Meybeck, 1982; Amiotte-Suchet and Probst, 1995). 

The higher proportion of DIC in the Western United States 

reported in this study may have had several causes: (1) a large 

portion of the ecoregions were in dry and arid environments, 

so there was little contribution of organic matter to overall 

fluxes; (2) the presence of easily weathered carbonate bedrock 

contributed unusually high amounts of DIC to the streams; 

and (3) the high temperatures and the prevalence of dams 

and reservoirs increased the residence time of water within 

the streams, which encouraged the organic matter to be 

mineralized to DIC. In general, DIC was a smaller proportion 

of total carbon fluxes estimated from the Ecoregional 

Comparison Dataset than from the Coastal Export Dataset 

(tables 10.1 and 10.2). The in-stream processing of organic 

matter may have allowed DIC to become more prominent in 

the coastal export values.

The concentrations of riverine DIC were especially high 

in the Cold Deserts ecoregion relative to the other ecoregions, 

which could have been caused by lithology (Amiotte-Suchet 

and Probst, 1995; Hartmann, 2009; Moosdorf and others, 

2011). For example, there is a large carbonate-rock aquifer that 

extends throughout the eastern part of the Great Basin, which 

includes much of the Cold Deserts (Harrill and Prudic, 1998). 

Chemical weathering and physical erosion releases carbon into 

rivers, and alkalinity for rivers overlying carbonate rocks can 

be nearly 20 times higher than for rivers overlying igneous or 

metamorphic rocks (Amiotte-Suchet and others, 2003). 

Considering the variability of the DIC concentrations 

among the five ecoregions, variation in the estimated pCO2

values in riverine systems was expected. The contact with 

groundwater in these carbonate systems (in particular, in 

the Cold Deserts, as indicated above) could have affected 

the DIC concentrations, which resulted in higher estimated 

in-stream pCO2 concentrations. Additionally, the carbon 

dioxide efflux from streams and rivers was probably supported 

by carbon dioxide inputs either directly from the terrestrial 

environment or through mineralization of terrestrially derived 

organic matter. It should be noted that for each ecoregion, the 

estimated total carbon dioxide efflux from riverine systems 

was always higher than the estimated total lateral flux of DIC; 

that is, the amount of carbon dioxide being emitted from a 

stream was higher than the amount of dissolved inorganic 

carbon material in a stream. For now, the best explanations 

for this apparent imbalance are that (1) uncertainty in the 

estimated carbon dioxide fluxes inadvertently resulted in the 

higher values (field validation may provide more accurate 

measurements) and (2) the estimates were not fully integrated 

with terrestrial ecosystem models (further integration may help 

account for additional sources of carbon to riverine systems).

Additional variables other than lithology and terrestrially 

derived carbon dioxide are probably needed to explain 

the variation in dissolved carbon dioxide in streams and 

rivers across the ecoregions in the Western United States. 

In general, water sources at high elevations originate 

from snowmelt. A study by Wickland and others (2001) 

indicated that runoff from snowmelt, if originating from 

the surface of the snowpack, was in close equilibrium with 

the atmosphere; however, throughout the year, the sources 

of dissolved carbon dioxide at high elevations shifted from 

snowmelt runoff to water that was in contact with the carbon 

dioxide produced from soil respiration, thus causing the 

mean annual carbon dioxide concentration to remain well 

above atmospheric levels. In the Warm Deserts, where the 

estimated concentrations of pCO2 were highest, groundwater 

may have contributed a significant proportion of dissolved 

carbon dioxide or carbonates to the estimated total riverine 

carbonflux.

The very high estimated per-unit-of-area fluxes of carbon 

from the Marine Western Coast Forest were again indicative 

of the relatively high estimated pCO2 concentrations and 

a diverse landscape along the Coast Range. Estimated gas 

transfer velocities ranged from 3.2 to 54 m/d, and estimated 

dissolved carbon dioxide ranged from 3,214 μatm in first‐order 

drainage systems down to 824 μatm at the terminus of the 

large rivers at the coast. The combination of high carbon 
Chapter 10 139

concentrations, high gas transfer velocities, and high stream 

surface area in a relatively small ecoregion resulted in the 

very high estimated per-unit-of-area flux estimate. The error 

analysis for the carbon dioxide flux in streams and rivers of 

the Marine West Coast Forest suggested an uncertainty in the 

estimate of up to 33 percent, which should be acknowledged 

when interpreting the reported values. In general, the very high 

estimated carbon dioxide flux from streams and rivers in the 

Western Cordillera was both a function of the steep terrain and 

relatively fast velocities associated with the Western Cordillera 

and Gila Mountains (in the Warm Deserts ecoregion). The 

estimated gas transfer velocities ranged from 10 to 80 m/d and 

most likely drove the high estimated gaseous flux. 

10.5.2. Carbon Dioxide Efflux From and Carbon 

Burial in Lacustrine Systems

There was significant variability in the number and type 

of water bodies in each ecoregion. The Western Cordillera 

contained a balanced mix of natural and artificial lakes or 

reservoirs (50 percent of each), and the Marine West Coast 

Forest and Cold Deserts contained fewer natural water bodies 

(23 percent and 15 percent, respectively). The Warm Deserts 

and Mediterranean California included only artificial water 

bodies. The variability in the origin of the water body (natural 

or artificial) did not appear to be related to the variability 

in carbon dioxide efflux, however, because carbon dioxide 

efflux from lacustrine systems was greatest in the Western 

Cordillera and lowest in the Marine West Coast Forest, the two 

ecoregions with the most natural water bodies.

The estimated dissolved carbon dioxide in lacustrine 

systems was in excess of atmospheric concentrations; the 

excess dissolved carbon dioxide must ultimately have been 

derived from external inputs of either organic or inorganic 

carbon. A greater portion of the carbon dioxide in the 

lacustrine systems of the Western Cordillera appears to have 

originated from terrestrial organic carbon inputs relative 

to the other ecoregions. Water bodies in more arid regions 

(such as the Cold Deserts, Warm Deserts, and Mediterranean 

California) all exhibited relatively high estimated mean 

alkalinities (3,200, 2,700, and 2,000 microequivalents per 

liter, or μeq/L, respectively), suggesting that a large amount of 

inorganic carbon was delivered to the lacustrine systems from 

their watersheds. The estimated mean DIC concentrations 

determined from lateral fluxes in the ecoregional riverine 

systems supported this hypothesis. For example, the estimated 

mean riverine DIC concentrations in the Cold Deserts and 

Mediterranean California were relatively high (62.4 and 

44.9 mg/L, respectively) compared to those in the Western 

Cordillera and Marine West Coast Forest (19.8 and 8.7 mg/L, 

respectively). Such hydrologic inputs of inorganic carbon have 

been demonstrated to contribute to dissolved carbon dioxide 

in some systems (Striegl and Michmerhuizen, 1998; Stets and 

others, 2009). 

The mean alkalinity was lower in the Western Cordillera 

(1,100 μeq/L) despite the fact that the estimated pCO2 was 

greatest in this region, which suggests that a greater fraction 

of the dissolved carbon dioxide was not derived from 

riverine inputs, but from the products of in-lake processing of 

terrestrial organic carbon. The extent to which organic carbon 

inputs drove carbon dioxide fluxes from lacustrine systems 

in the Marine West Coast Forest was not clear because both 

alkalinity (estimated mean=500 μeq/L) and estimated mean 

pCO2 were low. It should be noted that the estimated carbon 

burial rate (expressed on a watershed-area basis) was highest 

in the Marine West Coast Forest at 119±60 gC/m2/yr. In 

contrast, the comparable estimated carbon dioxide efflux from 

this same ecoregion was lower than any other ecoregion at 

37gC/m2/yr. Additionally, this ecoregion had a high estimated 

riverine pCO2 yield, implying that there was a considerable 

amount of carbon emitted from the stream environment per 

unit of area, which may be a factor in the low alkalinities of 

the downstream lacustrine systems. 

The differences in the estimated total annual carbon 

burial in lacustrine systems among the five ecoregions 

reflected variations in the estimated specific carbon burial 

rates, which were controlled by (1) soil organic carbon (SOC), 

(2) vegetation, and (3) sedimentation rates. The estimated 

specific carbon burial rates were strongly correlated with the 

estimated amounts of SOC (gC/m2) near the water bodies. Of 

the five ecoregions in the Western United States, the Marine 

West Coast Forest had the largest estimated amount of SOC 

(gC/m2) and the highest estimated specific carbon burial rates. 

The Warm Deserts had the smallest estimated amount of SOC 

(gC/m2) and lowest specific carbon burial rates. Regarding 

vegetation, the estimated specific carbon burial rates for 

reservoirs were positively correlated to the prevalence of 

forests in nearby areas; for lakes, the estimated carbon burial 

rates were more strongly associated with wetlands. Both 

types of vegetation (forests and wetlands) contributed to the 

accumulation of carbon in soils near the water bodies. Soil 

erosion in forested areas contributed allochthonous carbon, 

which is particularly important in reservoirs (St. Louis and 

others, 2000; Tranvik and others, 2009). Because wetlands 

are areas of active carbon cycling (Bridgham and others, 

2006), they may contribute particulate and dissolved carbon 

to lakes. Finally, estimated sedimentation rates, particularly in 

reservoirs, were strongly related to the reservoir’s area; larger 

reservoirs had higher estimated sediment accumulation rates.
140 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

10.5.3. Limitations and Uncertainties

The lateral flux values determined from the Ecoregional 

Comparison Dataset (table 10.2) represented only smaller 

watersheds, with boundaries that lay entirely within 

ecoregional boundaries. This bias was balanced by also 

providing estimates of larger western watersheds in the 

Western United States that drain to the Pacific coast in the 

Coastal Export Dataset. There was a paucity of data, however, 

for the smaller watersheds, and the values presented in 

table 10.2 represented only 0.05 to 25percent of the total 

ecoregional area. Because of the limited dataset and the large 

extrapolation of these values, they should be interpreted 

with caution.

In this assessment, the estimated carbon dioxide efflux 

rates from riverine systems dominated the estimated aquatic 

carbon fluxes. Validation data to support fluxes of this 

magnitude do not currently exist; however, recent research 

measuring oxygen transfer rates suggests that gas transfer 

velocities in the upper reaches of the Colorado River can range 

from 9 m/d in the larger main channels up to 338 m/d in rapids 

(Hall and others, 2012). It is important to note that the model 

to estimate gas transfer velocity of carbon dioxide outlined 

in Raymond and others (2012) and used for this assessment 

was developed from a dataset that did not include any 

measurements from steep-slope or high-altitude locations, and 

as such, the application of this model in highly diverse riverine 

landscapes must be done with appropriate caution. 

The contribution of organic acids to the calculation of 

total alkalinity could have caused an overestimation of the 

dissolved pCO2 concentrations (Tischenko and others, 2006; 

Hunt and others, 2011). In typical naturally occurring fresh 

water, the only major contributor to noncarbonate alkalinity 

is organic acid, primarily humic and fulvic acids (Lozovik, 

2005). The concentration of free organic ions was estimated 

for the lakes included in the 2007 NLA (EPA, 2009a) using 

the empirical relations of Oliver and others (1983). The 

estimated organic anion concentration for each lake or 

reservoir was subtracted from the measured alkalinity prior 

to performing an analysis of pCO2; however, an appropriate 

correction algorithm has not been developed for the dataset 

used for the flux calculation in riverine systems because of 

the limited locations of paired dissolved organic carbon and 

alkalinity measurements within the USGS’s NWIS database. 

Because the current methodology for estimating alkalinity 

in riverine systems does not account for organic acids, some 

of the existing estimate of riverine fluxes may be high. 

Uncertainties in the estimates may be reduced by accounting 

for noncarbonate alkalinity (organic acids) when deriving 

pCO2 concentration from total alkalinity measurements. 

The stream and river surface-area estimates for each 

ecoregion ranged from 0.2 to 0.73 percent of the total 

area, and they are consistent with other published values 

(Downing and others, 2009; Aufdenkampe others, 2011); 

however, the accuracy of stream and river surface area 

estimates may improve by using remote-sensing techniques 

to further constrain the hydraulic geometry parameters that 

are appropriate at the ecoregion scale (Striegl and others, in 

press). Specifically, there is a need to constrain the surface 

areas of first-order stream systems (headwaters areas) that may 

be poorly characterized within the NHDPlus dataset. Regional 

efforts to physically map first-order stream-surface areas in 

combination with scaling laws would reduce uncertainties. 

The location of USGS streamgaging stations, which 

were used in calculating the hydraulic geometry coefficients, 

introduced a bias because the stations were placed in a location 

that was best suited for accurate discharge measurements 

(Leopold and Maddock, 1953; Park, 1977). Therefore these 

station locations most likely do not represent the entire 

range of variability in the relationships among stream depth, 

width, and velocity that exists along the flowpaths of rivers 

in the Western United States. The results from the Monte 

Carlo simulation suggested levels of uncertainty approaching 

50percent for the Western Cordillera and about 30 percent 

for each of the four other ecoregions. In addition, the current 

application of bootstrapping and simulation was considered 

very conservative; however, as suggested above, without 

extensive efforts in field validation for both the gas transfer 

velocity and dissolved carbon dioxide concentration in small 

stream environments, the model estimates reported in this 

assessment represent the most comprehensive to date.

Using the available data, it was not possible to accurately 

model the impact of seasonality on estimated mean carbon 

dioxide efflux from lacustrine systems. In dimictic lakes 

(lakes that experience ice cover and mix completely in the 

spring and fall), carbon dioxide concentrations build up 

under ice cover and in the hypolimnion (bottom waters) 

during stratification as a result of heterotrophic respiration 

and are degassed rapidly during mixing (Michmerhuizen and 

others, 1996; Riera and others, 1999). Because the available 

data for the assessment were collected from surface waters 

only during the summer, this aspect of the seasonal pCO2

dynamics was not included in the estimates, which most likely 

affected the results from the Western Cordillera and the Cold 

Deserts ecoregions, where lakes are at high elevations and 

mean air temperatures are below freezing for approximately 

100 days each year. The Marine West Coast Forest, the Warm 

Deserts, and Mediterranean California ecoregions do not, on 

average, experience sustained below-freezing temperatures, 

but monomictic lakes (lakes that vertically mix once a year) 

potentially also experience one large degassing event per year. 
Chapter 10 141

10.6. Summary and Conclusions

There was great variability in estimated carbon fluxes 

among the aquatic ecosystems of the five ecoregions in the 

Western United States, most likely because of differences 

in (1) precipitation, (2) organic matter production, 

(3) lithology, and (4) physical characteristics of watersheds 

such as stream width and slope. The estimated total riverine 

carbon dioxide efflux in the Western United States was 

high (26.1 TgC/yr) relative to other aquatic ecosystems. 

Considering the additional estimated total carbon dioxide 

efflux from lacustrine systems (2.1 TgC/yr) and riverine export 

to coastal areas (7.2 TgC/yr), the sum of these losses totaled 

35.4 TgC/yr. This loss was offset by an estimated total carbon 

burial rate of –2.4 TgC/yr in lacustrine systems. 

Even though the extent of aquatic ecosystem fluxes 

presented in this chapter was extensive, it was not exhaustive. 

For example, it was not known how much carbon was 

produced by photosynthesis, lost by respiration, or buried in 

riverine systems; therefore, it was not possible to present a 

complete aquatic carbon budget for the Western United States, 

and the full impact of aquatic carbon fluxes on a terrestrial 

carbon budget could not be determined. The sum of losses 

from aquatic ecosystems listed above was equivalent to about 

25 percent of the net ecosystem production (NEP) obtained by 

the terrestrial ecosystem component of this report (chapter 12). 

This value must be interpreted with caution; because the 

terrestrial and aquatic modeling systems were decoupled, it 

was not clear how much of the carbon dioxide efflux from 

riverine and lacustrine systems was already captured in a 

terrestrial carbon dioxide efflux value. This comparison does, 

however, indicate that the linkage between terrestrial and 

aquatic ecosystems is critically important to fully understand 

the role natural ecosystems play in greenhouse-gas storage 

and cycling. The relationship between aquatic and terrestrial 

ecosystem fluxes will be further explored in chapter 12. 
142 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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Chapter 11. Terrestrial Fluxes of Sediments and

Nutrients to Pacific Coastal Waters and Their Effects on 

Coastal Carbon Storage Rates

By Brian A. Bergamaschi1, Richard A. Smith2, Michael J. Sauer1, and Jhih-Shyang Shih3

1U.S. Geological Survey, Sacramento, Ca.

2

 U.S. Geological Survey, Reston, Va.

3Resources for the Future, Washington, D.C.

11.1. Highlights

• Riverborne fluxes of total organic carbon, total 

nitrogen, and total suspended sediment to the Pacific 

coastal waters of the Western United States under 

baseline (1992) conditions were estimated at 1.60, 

0.40, and 66.78 Tg/yr, respectively. The projected 

(2050) future fluxes of these same constituents under 

a regionally downscaled land-use and land-cover 

(LULC) scenario aligned with the Intergovernmental 

Panel on Climate Change’s (IPCC’s) A2 scenario 

were 1.62, 0.50, and 63.78 Tg/yr, respectively, 

which indicated a projected change of –1.4 percent, 

+27.7 percent, and −4.5 percent, respectively. 

• The southern California region exhibited the largest 

projected proportional changes in flux values under 

the IPCC A2 scenario compared with the baseline 

conditions, largely due to projected changes in 

population and urban development. 

• For the Pacific coastal waters of the Western United 

States, the projected nitrogen fluxes were particularly 

elevated under the IPCC A2 scenario conditions 

compared with the baseline conditions, suggesting 

a possible increase in the frequency and duration of 

coastal and estuarine hypoxia events and harmful 

algal blooms.

• The projected carbon storage in coastal environments 

(those supported by terrestrial processes) represented 

a significant sink for carbon compared with terrestrial 

biomass carbon sinks; also, the projected carbon 

storage was sensitive to changes in land use and 

population. The estimated rate of carbon storage 

in Pacific coastal waters was 2.02 TgC/yr under 

baseline conditions. The projections of land use and 

population changes through 2050 under the IPCC 

A2 scenario had a small effect on projected coastal 

carbon storage processes, reducing carbon storage rates 

to 1.93 TgC/yr, a –4.4 percent change over baseline 

conditions.

• The results of this modeling exercise indicate that 

the projected size of the carbon sink associated with 

terrestrial exports is substantial and sensitive to 

anthropogenic activity. Thus, future evaluations of how 

land-use policy and management actions may alter 

carbon storage may benefit from an evaluation of the 

effects of prospective alterations in terrestrial processes 

on coastal carbon storage rates. 

11.2. Introduction

This chapter assesses the effect of terrestrial processes 

on carbon storage rates in the Pacific coastal waters of the 

Western United States as part of the larger assessment of 

carbon stocks, carbon sequestration, and greenhouse-gas 

(GHG) fluxes in ecosystems of the Western United States. In 

order to model the baseline (1992) and projected (2050) fluxes 

of total organic carbon (TOC), total nitrogen (TN), and total 

suspended sediment (TSS) to the coastal waters, the results 

of LULC mapping and modeling described in chapter 2 and 

models of future land-use and land cover (LULC) change 

scenarios were required. The results of the baseline and future 

potential carbon fluxes and burial in the Pacific coastal waters 

presented in this chapter were used in an integrated analysis 

(chapter 12) to assemble a regional estimate of the baseline 

and projected amounts of carbon stored in ecosystems of the 

Western United States. The relation between this chapter and 

the other chapters is depicted in figure 1.2 of chapter 1 of 

this report.
144 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

Globally, coastal ocean processes account for the 

removal of an estimated 1.1 petagrams of carbon per year 

(PgC/yr) from the atmosphere through the processes driving 

the production of carbon by phytoplankton and the burial 

of organic carbon in sediments (Hedges and Keil, 1995; 

Sarmiento and Gruber, 2002; Muller-Karger and others, 

2005; Hales and others, 2006; Dunne and others, 2007). This 

carbon sink is greater than the terrestrial biomass carbon 

sink (Sarmiento and Gruber, 2002) and is also susceptible to 

disruption by anthropogenic activities in terrestrial systems. 

In particular, changes to the supply of sediments and nutrients 

to coastal oceans can alter the magnitude of this carbon sink; 

ample evidence exists that they already have been significantly 

altered by anthropogenic activity (Syvitski and others, 2005; 

Boyer and others, 2006).

The inputs of sediment and nutrients from the terrestrial 

environment to the coastal waters exert significant control 

on the carbon storage processes in the marine coastal 

systems. Although the vast majority of carbon buried in 

coastal sediments or exported to the deep ocean has a 

marine provenance (Blair and others, 2004; Burdige, 2005), 

the fluxes of nutrients from the continents support coastal 

phytoplankton production and sediment fluxes aid the 

transport of this material from the photic zone to the deep 

ocean and bury it outside of the zone of oxygen penetration, 

where mineralization rates are dramatically reduced. Thus, to 

quantify the anthropogenic effects on the carbon storage rates 

in coastal environments, it is necessary to quantify the fluxes 

of TOC, TN, and TSS exported from terrestrial environments 

to coastal oceans, all of which have been demonstrably 

affected by anthropogenic activity (U.S. Climate Change 

Science Program, 2007). 

The properties of the watersheds that drain into the 

Pacific coastal waters and the physical attributes of the 

adjacent continental shelf affect the rate of carbon storage that 

occurs under current conditions and how it may be altered in 

the future. Globally, large river deltas are responsible for much 

of the coastal carbon burial because of their high productivity 

and rapid sediment accumulation rates (Blair and others, 

2004; Syvitski, 2011); however, because of the relatively steep 

bathymetry just offshore of the Western United States, there 

are few accreting delta systems associated with large river 

mouths. For example, the relatively steep bathymetry prevents 

the formation of a distinct accreting delta for the fourth 

largest river in the United States, the Columbia River. Instead, 

sediment from the Columbia River is deposited in deeper 

waters, relatively far from the mouth (Gross and Nelson, 

1966; Sternberg, 1986). The Western United States possesses 

additional physiographic characteristics, however, that do act 

to increase the storage of carbon. Discharge into the Pacific 

coastal waters is dominated by small, mountainous rivers, 

which carry high loads of sediment and nutrients. These rivers 

tend to be short, draining watershed areas with high relief, 

and their mouths typically discharge near the coast rather than 

into an estuary (Milliman and Syvitski, 1992; Wheatcroft and 

others, 2010). Globally, the sediment discharge from small, 

mountainous river systems accounts for nearly half the coastal 

sediment that buries carbon (Milliman and Syvitski, 1992; 

Leithold and others, 2005; Wheatcroft and others, 2010).

The amount of sediment and nutrients delivered to 

coastal oceans has changed considerably over the past several 

decades, significantly altering patterns of coastal carbon 

burial (Leithold and others, 2005; Syvitski and others, 2005; 

Mayorga and others, 2010). Increasing population and changes 

in land use are expected to accelerate these changes (Harrison 

and others, 2005; Syvitski and others, 2005; Mayorga and 

others, 2010). Although much of the discharge into Pacific 

coastal waters is from small, mountainous rivers, both the 

Columbia and Sacramento Rivers (the two largest rivers in the 

Western United States) drain areas of intensive agriculture and 

carry elevated nutrient loads to coastal waters, thus promoting 

higher phytoplankton production (Hales and others, 2008). 

The riverborne supply of these external nutrients to Pacific 

coastal waters is important because phytoplankton production 

supported by the externally supplied nutrients contributes to 

the potential net removal of carbon from the atmosphere. 

The estimates of carbon storage rates in the Pacific 

coastal waters can be complicated by a decoupling in the 

timing of sediment and nutrient supply. The burial of the 

phytoplankton biomass in the coastal sediments requires 

coherence between inputs of nutrients and inputs of 

sediments—phytoplankton production must occur near the 

time of the episodic delivery of the sediments (Wheatcroft and 

others, 2010). Although nutrients supporting phytoplankton 

production in Pacific coastal waters are largely supplied by 

the summer upwelling of nutrient-rich, deep-ocean water, 

the nutrient supply by rivers is also significant, particularly 

in Oregon and Washington (Hales and others, 2008). Any 

increases or decreases in the nutrient supply by rivers will 

affect the potential productivity in the adjacent coastal 

area. Changes in nutrient supply can be caused by changes 

in population, river discharge, agricultural practices, 

reforestation, and many other similar land-use- or climaterelated variables (Billen and Garnier, 2007). Under the 

projected future conditions, an increase in nutrients associated 

with the sediment contained in discharge waters could have 

the potential to improve the efficiency of carbon transport 

and burial. 

This coastal assessment focused exclusively on 

characterizing the potential magnitude of processes in the 

coastal marine system that have been, and potentially could 

be, affected by changing land use and population (fig. 2.1). 

The focus was only on the terrestrial sources of nutrients 

and sediments that influence marine carbon storage rates and 

not on marine processes such as the upwelling of oceanic 

nutrients, which also significantly contribute to primary 

productivity and total carbon storage rates in coastal waters. 

To accomplish this task, the fluxes of total organic carbon 

(TOC), total nitrogen (TN, organic and inorganic), and total 

suspended sediment (TSS) to coastal waters were estimated 

on the basis of current and projected land use using a model 

that was calibrated using long-term water quality and stream 
Chapter 11 145

discharge data. The baseline and projected amounts of carbon 

that were buried were estimated according to established 

models of oceanographic processes (Armstrong and others, 

2002; Dunne and others, 2007). 

The geographic extent of the assessment was from the 

northern to the southern borders of the Western United States 

and included all of the watersheds that drain this region into 

the adjacent coastal waters (herein referred to as the “Pacific 

coastal waters”). The coastal waters of the Gulf of California, 

which receives the discharge of the Colorado River, were 

not included because other sources of discharge into those 

coastal waters extended beyond the geographic boundary of 

the conterminous United States. The assessment considered 

only processes affected by the terrestrial supply of nutrients 

and sediments to coastal waters. These processes extended 

from the coast into the deep ocean with no western boundary 

because carbon exported into the deep ocean was presumed 

to be sequestered (Sarmiento and Gruber, 2002, Hales and 

others, 2006).

The riverine delivery of carbon, nutrients, and sediment 

to coastal waters can be estimated from routine monitoring 

data, provided that the records cover a sufficient length of 

time and include accurate streamflow measurements (Cohn 

and others, 1992). Determining the sources of the transported 

material is much more difficult, however, especially in the 

case of large rivers with heterogeneous basin characteristics. 

Isotopic methods have been developed to distinguish specific 

classes of sources of nutrients (for example, atmospheric or 

sewage effluent) with good success, but require specialized 

analytical procedures and have not been used historically in 

broad-scale, long-term monitoring programs (Kendall and 

McDonnell, 1998). There has been considerable progress in 

the past two decades: (1) development of statistical modeling 

approaches, which can be used to identify the sources of 

constituents; (2) continuing development of geographic 

information systems (GIS) technology; and (3) availability 

of spatial data on basin characteristics (Peters, 1984; R.A. 

Smith and others, 1997; Goolsby and others, 1999). The use 

of the SPARROW model (a “spatially referenced regression 

on watershed attributes” water-quality model; R.A. Smith 

and others, 1997) for regional interpretations of contaminant 

sources is now a routine part of the U.S. Geological Survey’s 

water-quality assessment activities (Preston and others, 2011).

11.3. Input Data and Methods

The modeling approach used here divides the analysis of 

Pacific coastal waters into three components: (1) the supply 

of TOC, TN, and TSS from terrestrial systems to the coastal 

ocean, (2) phytoplankton production supported by terrestrial 

nutrients, and (3) storage rates of carbon in coastal sediments 

or deep ocean waters. The first model component assesses the 

TOC, TN, and TSS supply from rivers to the coastal ocean 

under baseline (1992) and projected (2050) conditions. 

A hybrid statistical-mechanical modeling approach 

was used to calculate the fluxes of TOC, TN, and TSS from 

rivers to the coastal waters. The SPARROW model (R.A. 

Smith and others, 1997; Schwarz and others, 2006) consists 

of process-based mass-transport components for water flow 

paths, in-stream processing, and mass-balance constraints 

on model inputs, losses, and outputs (Schwarz and others, 

2006). Modeled estimates of TSS, TN, and TOC fluxes were 

produced for each coastal or inland hydrologic unit (by 

12-digit hydrologic unit code; U.S. Department of Agriculture, 

Natural Resources Conservation Service, 2012) that produced 

runoff to the western coast of the United States. Both the 

baseline LULC and LULC projections by the “forecasting 

scenarios of land cover change” (FORE–SCE) model, as 

described in chapter 2 of this report, were included in the 

SPARROW modeling process. Estimates of TOC that were 

developed using a different modeling approach (presented in 

chapter 10 of this report) agree with those presented here. The 

SPARROW model, however, permits assessment using the 

future potential land use and population conditions in 2050, 

which are presented in chapter 2.

For surface-water monitoring stations that had 

sufficient data on discharge and water quality, parameters 

were estimated by spatially correlating the stream data with 

georeferenced data on the constituent sources (for example, 

atmospheric deposition, fertilizers, human and animal wastes) 

and delivery factors (for example, precipitation, topography, 

vegetation, soils, and water routing). Parameter estimation 

ensured that the calibrated model would not be more complex 

than can be supported by the data. 

SPARROW models describe mass transport in watersheds 

as three sequential processes: (1) source supply, (2) landto-water transport, and (3) channel-network transport (R.A. 

Smith and others, 1997). Data describing these processes are 

developed on a stream reach and associated catchment basis. 

There are approximately 13,000 reaches or catchments in the 

Western United States assessment area and 63,000 reaches 

or catchments in the national-scale data set, which were used 

to calibrate the models. Table 11.1 provides information on 

the TOC, TN, and TSS models used here to quantify the flux 

of material to coastal waters. More detailed information is 

available from the references provided in the table. 

The source variables (table 11.1) were of particular 

importance because they served as the basis for translating 

the projected LULC changes under the A2 scenario (from 

the Intergovernmental Panel on Climate Change’s Special 

Report on Emissions Scenarios, IPCC–SRES; Nakicenovic 

and others, 2001) into changes in coastal delivery of TOC, TN, 

and TSS from the baseline period to 2050. The IPCC–SRES 

scenarios are discussed in more detail in chapter 6 of this 

report. Table 11.2 summarizes the correspondence between 

the LULC classes and the SPARROW model’s source 

categories. An underlying assumption made in modeling the 

future changes in coastal flux was that the rate of the source 

supply will change in proportion to the LULC changes in each 
146 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

Table 11.1. Variables used in the SPARROW models of total organic carbon, total nitrogen, and total suspended sediment fluxes, and 

their sources.

[SPARROW, “spatially referenced regressions of watershed attributes” water-quality model]

Model Number 

of sites

Coefficient of 

determination 

(R2

)

Source variables Reference

Total organic 

carbon (TOC)

1,125 0.928 Cultivated land, pasture, deciduous forest, evergreen forest, 

mixed forest, rangeland, urban land, wetlands, in-stream 

photosynthesis

Shih and

others (2010)

Total nitrogen 

(TN)

425 0.933 1990 population, atmospheric total nitrogen deposition, corn or 

soybean fertilizer, alfalfa fertilizer, wheat fertilizer, other crop 

fertilizer, farm animal waste, forest, barren land, shrubland

Alexander and

others (2008)

Total suspended 

sediment 

(TSS)

1,828 0.711 Urban area, forest, crop and pasture land, Federal land, other 

marginal land, channel storage and erosion

Schwarz (2008)

Table 11.2. Assumed correspondences between the SPARROW model’s source categories and the land-use and land-cover classes 

used in this assessment.

[See chapter 2 of this report for definitions of the LULC classes. LULC, land use and land cover; NA, not applicable; SPARROW, “spatially referenced 

regressions of watershed attributes” water-quality model]

Total organic carbon

(TOC) model

Total nitrogen

(TN) model

Total suspended sediment

(TSS) model

Model source Land use and land 

cover class Model source Land use andland cover class Model source Land use and land cover class

Cultivated land Agriculture Human population Developed land Developed land Developed land

Pasture Hay/pasture Atmospheric nitrate 

(NO3) deposition

Developed land Forested land Deciduous, 

evergreen, 

mixed forests

Deciduous forest Deciduous forest Fertilizer nitrogen 

applied to 

agriculture

Agriculture Federally managed 

land

Barren land, 

grassland and 

shrubland

Evergreen forest Evergreen forest Nitrogen content of 

farm animal waste

Grassland and 

shrubland

Crop and pasture 

land

Agriculture

Mixed forest Mixed forest Forest Deciduous, 

evergreen, 

mixed forests

Other land Barren land, 

grassland, and 

shrubland

Rangeland Grassland and 

shrubland

Barren land Barren land Stream channels No LULC 

correspondence; 

assumed to be 

constant

Developed land Developed land Shrubland Shrubland NA NA

Wetlands Herbaceous and 

woody wetland

NA NA NA NA

In-stream 

photosynthesis

No LULC 

correspondence; 

assumed to be 

constant

NA NA NA NA
Chapter 11 147

model’s catchment. The A2 scenario was selected because it 

is consistent with this assumption in one important aspect: it 

projects that population growth by 2050 (+48 percent) may be 

nearly matched by an increase in area classified as developed 

land (+46 percent). Thus, for example, the change in the 

value of the population variable in the TN model within each 

catchment was approximated by the projected change in the 

developed land area presented in chapter 6 of this report. The 

A2 scenario also assumed that environmental sustainability 

remains approximately constant, which is reflected in the 

LULC and SPARROW modeling (Sohl, Sleeter, and Zhu, 

2012; also see chapter 6 of this report). Thus, for example, 

the per-acre fertilizer application rates and point and nonpoint 

pollution-control efficiencies are assumed to remain constant.

The 90-percent confidence intervals for the coastal flux 

estimates in table 11.3 were developed through a “bootstrap” 

procedure in which 200 equally likely estimates for each entry 

in the table were randomly generated on the basis of the error 

characteristics of the model determined during calibration. 

The width of the confidence intervals surrounding the 1992 

and 2050 flux estimates included both coefficient error and 

residual (that is, model specification) error (Schwarz and 

others, 2006). It was assumed that the residual errors of the 

flux estimates for individual coastal rivers within each region 

reflected idiosyncrasies of the river watersheds. The estimated 

errors surrounding the “percent-change” estimates for each 

coastal river, however, were assumed to be caused only by 

coefficient error on the basis of the further assumption that 

the idiosyncrasies of a given river can be assumed to be the 

same in 1992 and 2050. Thus, the confidence intervals for 

the percent-change estimates were smaller than those for the 

separate 1992 and 2050 flux estimates. 

The effects of climate change have not been specifically 

modeled because there is no known consensus regarding their 

effects on nutrients or biota in the coastal ocean. Although 

the effects of climate change may alter TOC, TN, and TSS 

fluxes in the future, LULC is expected to be the main driver 

of the variability in these parameters between 1992 and 2050, 

suggesting that uncertainty in the model is controlled by 

LULC. The A2 scenario was chosen to represent the projected 

changes in coastal carbon sequestration stemming from 

LULC. The use of the A2 scenarios limits the SPARROW 

model’s runtime and represented a worst-case scenario 

for population increase and anthropogenic emissions with 

continued regional fragmentation in economic growth and 

technology. In contrast to the other IPCC–SRES scenarios 

(A1B and B1), environmental protection and sustainability 

were not considered to be important in A2. 

Table 11.3. Estimates of total organic carbon, total nitrogen, and total suspended sediment fluxes to the Pacific coastal waters of the 

conterminous United States (with 90-percent confidence intervals) and the total carbon burial rate under baseline (1992) and projected 

(2050) conditions.

[A2 scenario selected from Intergovernmental Panel on Climate Change’s Special Report on Emissions Scenarios (Nakicenovic and others, 2001). Numbers may 

not sum precisely due to rounding. Tg/yr, teragrams per year; TgC/yr, teragrams of carbon per year]

Variables Region

1992 baseline

estimate

(90-percent

confidence

interval)

2050 projected

estimate under

A2 scenario

(90-percent

confidence

interval)

Percent change 

(90-percent

confidence interval)

Total organic carbon flux 

(TgC/yr)

Southern California 0.04 (0.01 to 0.08) 0.04 (0.02 to 0.10) 18.2 (17.95 to 18.45)

Northern California 0.32 (0.13 to 0.71) 0.33 (0.13 to 0.73) 2.5 (2.43 to 2.57)

Oregon and Washington 1.24 (0.49 to 2.97) 1.25 (0.49 to 2.99) 0.6 (0.56 to 0.64)

Total 1.60 (0.63 to 3.77) 1.62 (0.64 to 3.82) 1.4 (1.34 to 1.46)

Total nitrogen flux (Tg/yr) Southern California 0.04 (0.01 to 0.10) 0.05 (0.03 to 0.13) 31.7 (31.52 to 31.88)

Northern California 0.06 (0.02 to 0.15) 0.08 (0.13 to 0.19) 34.7 (34.18 to 35.22)

Oregon and Washington 0.29 (0.09 to 0.72) 0.37 (0.12 to 0.93) 25.7 (24.88 to 26.52)

Total 0.40 (0.13 to 0.96) 0.50 (0.17 to 1.24) 27.7 (27.00 to 28.40)

Total suspended sediment 

flux (Tg/yr)

Southern California 6.27 (0.22 to 19.88) 7.69 (0.27 to 24.28) 22.7 (22.20 to 23.20)

Northern California 19.75 (0.69 to 55.44) 19.31 (0.65 to 54.39) −2.2 (−2.68 to −1.72)

Oregon and Washington 40.76 (0.65 to 111.5) 36.78 (0.53 to 99.24) −9.8 (−10.37 to −9.23)

Total 66.78 (1.55 to 187.8) 63.78 (1.45 to 178.9) −4.5 (−4.91 to −4.09)

Total carbon burial rate 

(TgC/yr)

Southern California 0.12 (0.01 to 0.39) 0.16 (0.01 to 0.52) 33.5 (33.8 to 35.2)

Northern California 0.65 (0.29 to 1.87) 0.67 (0.06 to 1.93) 3.6 (2.9 to 4.5)

Oregon and Washington 1.25 (0.03 to 3.51) 1.1 (0.03 to 3.05) −12.1 (−11.8 to −13.2)

Total 2.02 (0.06 to 5.78) 1.93 (0.09 to 5.50) −4.4 (−4.7 to −4.2)
148 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

Sediment and carbon transport from the surface ocean 

into the deep ocean and carbon burial in sediments were 

modeled using the methods presented by Dunne and others 

(2007). This approach modeled the transport of terrestrial and 

marine, photosynthetically derived carbon to the sediment 

surface in coastal waters or to the deep ocean using an 

empirical modeling approach. The same approach was used 

to model sedimentation to the pycnocline. A hypsographic 

valuation of the bathymetric properties of the sediment 

deposition zones was determined by using a GIS and the 

NOAA bathymetric database. The burial of organic carbon 

in sediments was modeled as a function of the sediment 

deposition rate (Berger, 1989, Dunne and others, 2007) 

with no net deposition assumed above 10 meters because of 

wave- or event-driven resuspension of sediment. Sediment 

in the water column above 10 m depth was presumed to 

be transported to deeper regions with a 50 percent loss in 

carbon by mass and no dissolution of terrestrial sediments 

during transit (Armstrong and others, 2002). Carbon 

buried in sediments below the depth of oxygen penetration 

or transported to the deep ocean below the level of the 

pycnocline was considered to be “stored” for the purpose 

of this assessment, as this carbon has mean turnover times 

of hundreds to thousands of years (Hedges and Keil, 1995). 

The 90-percent confidence intervals for the coastal carbon 

accumulation shown in table 11.3 were developed using the 

confidence intervals from the flux estimates and assumed no 

additional error in the coastal model. Note that the modeling 

effort did not include an evaluation of silica, iron, and 

other micronutrient fluxes or of the coastal phytoplankton 

production that such fluxes may affect.

11.4. Results

11.4.1. Flux of Organic Carbon, Nitrogen, and 

Suspended Sediment to Coastal Waters

The model estimates of TOC, TN, and TSS fluxes 

to the Pacific coastal waters under baseline and projected 

(2050) conditions and based on the IPCC–SRES scenario 

A2 are presented in tables 11.3 and 11.4. Estimates are 

presented for each of the three physiographic provinces in 

the region: southern California (northern boundary at latitude 

37°), northern California (to the Oregon State line), and 

the Pacific Northwest, which includes the States of Oregon 

and Washington.

11.4.1.1. Total Organic Carbon

The total baseline flux of TOC to the Pacific coastal 

waters for the three regions was estimated to be approximately 

1.6 TgC/yr (tables 10.3, 10.4; fig. 11.1A–C). About 78 percent 

of the total flux was delivered to coastal waters of Oregon 

and Washington, reflecting the interaction of a large coastal 

drainage area, high streamflows, and extensive forest cover 

in the region (table 11.4; fig. 11.1C). By contrast, a much 

lower estimated baseline TOC flux (2 percent of total) was 

delivered from the smaller and drier Southern California 

region, largely from urban sources. The estimated baseline 

TOC flux from the Northern California region (especially 

that draining to San Francisco Bay) reflects a combination of 

urban and agricultural sources (table 11.4; fig. 11.1C). The 

model estimates of TOC yield to the coastline after in-stream 

losses are subtracted are shown in figure 11.1B. Regardless of 

the TOC source, the catchments with the highest coastal yield 

are typically located either near the coast or near large rivers, 

which tended to have low in-stream loss rates (Alexander 

and others, 2000). It should be noted that the preponderance 

of evidence suggests that terrestrial organic carbon borne by 

rivers into the coastal ocean is largely remineralized, and little 

is stored (Hedges and others, 1997; Blair and others, 2004; 

Burdige, 2005). 

The estimated projected changes in TOC flux to the 

coastal waters from the 1992 to 2050 (tables 11.3, 11.4; 

fig. 11.1D–G) were relatively small in the two northern 

regions, but the estimated projected change was greater (more 

than 18 percent) in the Southern California region, where 

population and urban development were projected to increase 

dramatically by mid-century. The near absence of change in 

total TOC flux from Oregon and Washington (0.8 percent) 

over the period masked the occurrence of more substantial but 

opposing trends in the region: a decreasing flux from the loss 

of forest and forested wetlands versus an increasing flux from 

population growth.

11.4.1.2. Total Nitrogen 

The SPARROW model estimated a baseline total TN 

flux of 0.395 Tg/yr (tables 11.3, 11.4; fig. 11.2A–C). As with 

TOC, approximately three quarters of the estimated TN flux 

entered the Pacific coastal waters from the large, wet parts of 

Oregon and Washington, where forest cover and atmospheric 

deposition together supplied about 63 percent of the regional 

flux (table 11.4). Farther south, in the northern and southern 

California regions, TN was mainly from urban sources 

(table 11.4).

The estimated TN flux from all three coastal regions was 

projected to greatly increase (table 11.4), mainly because of 

the importance of urban and atmospheric sources of nitrogen 

(and, to a lesser extent, agricultural sources in the northern 

California region). Under the A2 scenario, the U.S. population 

was projected to increase to 417 million by 2050, and 

nationwide agricultural production was projected to increase 

substantially in order to meet elevated worldwide demand. 

The estimated TN flux from all three regions was projected to 

increase more than 25 percent, with increases in the northern 

California region alone projected to be a third more than the 

baseline estimate (table 11.3; fig. 11.2D–G).
Chapter 11 149

Table 11.4 Estimates of total organic carbon, total nitrogen, and total suspended sediment fluxes to the Pacific coastal waters of the 

conterminous United States by source of the fluxes, under baseline (1992) and projected (2050) conditions.

[Numbers may not sum precisely due to rounding. Gg/yr, gigagrams per year; GgC/yr, gigagrams of carbon per year]

Source

Southern California Northern California Oregon and Washington

1992 2050 Change 1992 2050 Change 1992 2050 Change

Total organic carbon (GgC/yr)

Cultivated land 3.38 2.64 −0.74 24.24 23.67 −0.57 71.43 74.67 3.24

Deciduous forest 0.33 0.33 −0.01 5.87 5.85 −0.02 26.74 27.12 0.38

Evergreen forest 5.52 5.46 −0.06 96.16 95.00 −1.16 387.83 375.65 −12.18

Mixed forest 2.94 2.91 −0.03 25.34 25.79 0.45 72.10 68.79 −3.31

Urban land 17.53 25.01 7.49 19.74 31.73 12.00 31.35 54.97 23.62

Wetlands 0.67 0.51 −0.16 24.04 21.47 −2.56 57.86 53.19 −4.67

In-stream 

photosynthesis

5.33 5.33 0.00 126.17 126.17 0.00 593.73 593.73 0.00

Total 35.71 42.19 6.49 321.55 329.68 8.13 1,241.1 1,248.1 7.07

Total nitrogen (Gg/yr)

Population 37.39 50.76 13.36 26.55 42.11 15.56 22.27 38.97 16.70

Atmospheric 

deposition

0.37 0.72 0.36 5.82 11.53 5.71 65.02 128.71 63.69

Corn and soybean 0.03 0.02 −0.01 1.02 1.01 −0.02 4.97 5.06 0.09

Alfalfa 0.04 0.03 −0.01 1.43 1.47 0.04 6.87 7.19 0.33

Wheat 0.03 0.03 0.00 0.57 0.56 −0.01 8.49 8.62 0.13

Other crops 2.33 1.69 −0.64 5.91 6.08 0.17 26.40 27.70 1.30

Farm animal waste 0.20 0.17 −0.03 3.58 3.22 −0.36 15.27 14.76 −0.51

Forest 0.29 0.28 0.00 13.40 13.27 −0.13 120.76 118.43 −2.33

Barren land 0.04 0.04 0.00 0.40 0.36 −0.04 15.85 12.29 −3.56

Shrubland 0.30 0.27 −0.03 1.47 1.44 −0.03 8.17 7.85 −0.32

Total 41.02 54.01 13.00 60.15 81.04 20.89 294.06 369.57 75.51

Total sediment supply (Gg/yr)

Urban 1,646.68 3,094.10 1,447.40 4,020.00 6,598.27 2,578.08 4,105.60 5,076.30 970.67

Forest 36.05 35.65 −0.40 576.30 573.32 −3.01 963.74 945.16 −18.58

Federal land 2,715.14 2,800.60 85.48 7,231.00 4,995.05 −2,235.84 12,033.00 8,237.03 −3,796.00

Crop and pasture 

land

240.03 240.85 0.82 999.40 1,042.56 43.14 2,541.20 2,878.60 337.36

Grassland, 

shrubland, 

barren land 

1,260.02 1,149.60 −110.45 3,968.00 3,143.52 −823.93 3,056.40 1,581.30 −1,475.10

Channel storage 

or erosion

367.61 367.61 0.00 2,956.00 2,956.70 0.00 18,063.00 18,063.00 0.00

Total 6,265.50 7,688.40 1,422.80 19,751.00 19,309.40 −441.56 40,763.00 36,781.30 −3,981.70

11.4.1.3. Total Suspended Sediment

The total baseline TSS flux to the three Pacific coastal 

regions averaged 66.8 Tg/yr (tables 11.3, 11.4; fig. 11.3A–C). 

Again, there was a pronounced increasing gradient in flux 

from south to north, with Oregon and Washington coastal 

waters receiving more than half of the total (61 percent). The 

important sources of transported sediment in the three regions 

(table 11.4; see also table 11.2) included urban runoff, but also 

soil loss from several types of sparsely vegetated land cover 

types, including rangeland, shrubland, grassland, and barren 

land, much of which is Federally owned. Of note, however, is 

that the major source of sediment in Oregon and Washington 

was stored and eroded sediment from stream channels in 

the region, as was estimated in SPARROW’s TSS model 

calibration (Schwarz, 2008).
150 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

Figure 11.1. Maps showing total organic carbon flux and 

yield under baseline (1992) and projected (2050) conditions with 

projected percent change between 1992 and 2050. Flux is to 

Pacific coastal waters and yield is from catchments draining 

to Pacific coastal waters of the conterminous United States. 

A, Estimated coastal flux of total organic carbon (TOC) in 105

kilograms per year (kg/yr) under baseline (1992) conditions. 

B, Estimated delivered yield (in kilograms per hectare per year, 

kg/ha/yr) of TOC from catchments draining to Pacific coastal 

waters under baseline (1992) conditions. Delivered yield reflects 

the effects of in-stream carbon losses occurring during transport 

from the outlet of a catchment through the stream and river 

system to coastal waters. C, Major sources of TOC in model 

catchments under baseline (1992) conditions. D, Projected 

estimates of coastal flux of TOC (in 105

 kg/yr) under future (2050) 

conditions based on IPCC–SRES scenario A2. E, Projected 

estimates of delivered yield (in kilograms per hectare per year, 

kg/ha/yr) of TOC from catchments draining to the Pacific coastal 

waters under future (2050) conditions. Delivered yield reflects the 

projected effects of in-stream carbon losses occurring during 

transport from the outlet of a catchment through the stream and 

river system to coastal waters. F, Projected percent change 

in estimated coastal flux of TOC between 1992 and 2050 based 

on IPCC–SRES scenario A2. G, Projected percent change in 

yield of TOC from catchments between 1992 and 2050 based on 

IPCC–SRES scenario A2. IPCC–SRES, Intergovernmental Panel 

on Climate Change Special Report on Emissions Scenarios 

(Nakicenovic and others, 2000).

0 200 400 MILES

0 200 400 KILOMETERS

0 to 3.88

>3.88 to 9.89

>9.89 to 17.14

EXPLANATION

1992 total organic carbon

 delivered incremental

 yield, in kilograms per 

 hectare per year 

Level II ecoregion boundary

>17.14 to 33.35

>33.35

EXPLANATION

1992 total organic carbon

 flux, in 105 kilograms 

 per year

0 to 1.27

>1.27 to 3.20

>3.20 to 7.55

> 7.55 to 19.20

>19.20

EXPLANATION

Major source of total organic

 carbon, by land use, land

 cover, or process

Level II ecoregion boundary

Cultivated land

Deciduous forest

Evergreen forest

Mixed forest

Urban

Wetlands

In-stream photosynthesis

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

A

C

B

N
Chapter 11 151

0 to 3.88

>3.88 to 9.89

>9.89 to 17.14

EXPLANATION

2050 total organic carbon

 delivered incremental

 yield, in kilograms per 

 hectare per year 

Level II ecoregion boundary

>17.14 to 33.35

>33.35

EXPLANATION

Percent change total 

 organic carbon flux,

 for 1992 to 2050

< –50

>– 50 to –25

>–25 to 0

>0 to 25

>25 to 50

>50

EXPLANATION

Percent change total 

 organic carbon delivered

 incremental yield, for

 1992 to 2050

Level II ecoregion boundary

< –50

>– 50 to –25

>–25 to 0

>0 to 25

>25 to 50

>50

EXPLANATION

2050 total organic carbon

 flux, in 105 kilograms 

 per year

0 to 1.27

>1.27 to 3.20

>3.20 to 7.55

> 7.55 to 19.20

>19.20

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

D E

F G

N

Figure 11.1—Continued
152 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

A

C

0 200 400 MILES

0 200 400 KILOMETERS

B

0 to 0.54

>0.54 to 1.32

>1.32 to 2.35

>2.35 to 6.03

>6.03

EXPLANATION

1992 total nitrogen

 delivered incremental

 yield, in kilograms per 

 hectare per year 

Level II ecoregion boundary

EXPLANATION

1992 total nitrogen flux, in

 104 kilograms per year

0 to 1.25

>1.25 to 3.63

>3.63 to 8.46

> 8.46 to 25.65

>25.65

EXPLANATION

Major source for total nitrogen,

 by land use, land cover,

 or process

Level II ecoregion boundary

Population

Atmospheric deposition

Corn and soybean

Alfalfa

Wheat

Other crops

Animal waste

Forest

Barren

Shrub

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

N

Figure 11.2. Maps showing total nitrogen flux and yield under 

baseline (1992) and projected (2050) conditions with projected 

percent change between 1992 and 2050. Flux is to Pacific coastal 

waters and yield is from catchments draining to Pacific coastal 

waters of the conterminous United States. A, Estimated coastal 

flux of total nitrogen (TN) in 105 kilograms per year (kg/yr) under 

baseline (1992) conditions. B, Estimated delivered yield (in 

kilograms per hectare per year, kg/ha/yr) of TN from catchments 

under baseline (1992) conditions. Delivered yield reflects the 

effects of in-stream nitrogen losses occurring during transport 

from the outlet of a catchment through the stream and river 

system to coastal waters. C, Major sources of TN in model 

catchments under baseline (1992) conditions. D, Projected 

estimates of coastal flux of TN (in 105

 kg/yr) under future (2050) 

conditions based on IPCC–SRES scenario A2. E, Projected 

estimates of delivered yield (in kilograms per hectare per year, 

kg/ha/yr) of TN from catchments draining to Pacific coastal 

waters under future (2050) conditions. Delivered yield reflects 

the projected effects of in-stream nitrogen losses occurring 

during transport from the outlet of a catchment through the 

stream and river system to coastal waters. F, Projected percent 

change in estimated coastal flux of TN between 1992 and 2050 

based on IPCC–SRES scenario A2. G, Projected percent change 

in yield of TN from catchments between 1992 and 2050 based 

on IPCC–SRES scenario A2. IPCC–SRES, Intergovernmental 

Panel on Climate Change Special Report on Emissions Scenarios 

(Nakicenovic and others, 2000). 
Chapter 11 153

D E

0 to 0.54

>0.54 to 1.32

>1.32 to 2.35

EXPLANATION

2050 total nitrogen

 delivered incremental

 yield, in kilograms per 

 hectare per year 

Level II ecoregion boundary

>2.35 to 6.03

>6.03

F G

EXPLANATION

Percent change total 

 nitrogen flux, for

 1992 to 2050

< –50

>– 50 to –25

>–25 to 0

>0 to 25

>25 to 50

>50

EXPLANATION

Percent change total 

 nitrogren delivered

 incremental yield 

 for 1992 to 2050

Level II ecoregion boundary

< –50

>– 50 to –25

>–25 to 0

>0 to 25

>25 to 50

>50

EXPLANATION

2050 total nitrogen flux, in

 104 kilograms per year

0 to 1.25

>1.25 to 3.63

>3.63 to 8.46

>8.46 to 25.65

>25.65

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

N

Figure 11.2—Continued
154 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

0 200 400 MILES

0 200 400 KILOMETERS

0 to 54.83

>54.83 to 223.65

>223.65 to 592.61

>592.61 to 1,337.16

>1,337.16

EXPLANATION

1992 total suspended sediment 

 delivered incremental 

 yield, in kilograms per 

 hectare per year 

Level II ecoregion boundary

EXPLANATION

1992 total suspended sediment

 flux, in 105 kilograms per year

0 to 6.31

>6.31 to 16.76

>16.76 to 36.58

> 36.58 to 117.84

>117.84

EXPLANATION

Major source for total 

 suspended sediment, 

 by land use, land cover, 

 or process

Level II ecoregion boundary

Urban

Forest

Federal land

Crop and pasture

Grass, shrub, and barren

Channel storage or erosion

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

N

A

C

B

Figure 11.3. Maps showing total suspended sediment flux 

and yield under baseline (1992) and projected (2050) conditions 

with projected percent change between 1992 and 2050. Flux is 

to Pacific coastal waters and yield is from catchments draining 

to Pacific coastal waters of the conterminous United States. 

A, Estimated coastal flux of total suspended sediment (TSS) in 

105 kilograms per year (kg/hr) under baseline (1992) conditions. 

B, Estimated delivered yield (in kilograms per hectare per year, 

kg/ha/yr) of TSS from catchments draining to Pacific coastal 

waters under baseline (1992) conditions. Delivered yield reflects 

the effects of in-stream suspended-sediment losses occurring 

during transport from the outlet of a catchment through the 

stream and river system to coastal waters. C, Major sources 

of TSS in model catchments under baseline (1992) conditions. 

D, Projected estimates of coastal flux of TSS (in 105

 kg/yr) 

under future (2050) conditions based on IPCC–SRES scenario 

A2. E, Projected estimates of delivered yield (in kilograms per 

hectare per year, kg/ha/yr) of TSS from catchments draining to 

Pacific coastal waters under future (2050) conditions. Delivered 

yield reflects the projected effects of in-stream suspendedsediment losses occurring during transport from the outlet of 

a catchment through the stream and river system to coastal 

waters. F, Projected percent change in estimated coastal flux of 

TSS between 1992 and 2050 based on IPCC–SRES scenario A2. 

G, Projected percent change in yield of TSS from catchments 

between 1992 and 2050 based on IPCC–SRES scenario A2. 

IPCC–SRES, Intergovernmental Panel on Climate Change Special 

Report on Emissions Scenarios (Nakicenovic and others, 2000).
Chapter 11 155

EXPLANATION

2050 total suspended sediment

 delivered incremental

 yield, in kilograms per 

 hectare per year 

Level II ecoregion boundary

EXPLANATION

Percent change total 

 suspended sediment flux

 for 1992 to 2050

< –50

>– 50 to –25

>–25 to 0

>0 to 25

>25 to 50

>50

EXPLANATION

Percent change total 

 suspended sediment

 delivered incremental

 yield for 1992 to 2050

Level II ecoregion boundary

< –50

>– 50 to –25

>–25 to 0

>0 to 25

>25 to 50

>50

EXPLANATION

2050 total suspended sediment

 flux, in 105 kilograms per year

0 to 6.31

>6.31 to 16.76

>16.76 to 36.58

>36.58 to 117.84

>117.84

0 to 54.83

>54.83 to 223.65

>223.65 to 592.61

>592.61 to 1,337.16

0 200 400 MILES >1,337.16

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

0 200 400 MILES

0 200 400 KILOMETERS

N

D E

F G

Figure 11.3—Continued
156 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

The projected future regional changes in TSS flux to the 

Pacific coastal waters were mixed and included a substantial 

increase (23 percent) in the southern California region and 

decreases of 10 and 2 percent, respectively, in Oregon and 

Washington and in the northern California region (tables 11.3, 

11.4; fig. 11.3D–G). The reasons for the projected changes in 

TSS flux vary. The large projected increase in the southern 

California region stemmed from projections of continued 

urban development, and the moderate projected decrease in 

Oregon and Washington stemmed largely from the projected 

development of marginal lands (table 11.4). 

11.4.2. Carbon Processes in Coastal Waters

The baseline rate of coastal carbon storage 

due only to terrestrial processes in Pacific coastal waters 

was estimated to be 0.12 TgC/yr for the southern California 

region, 0.65 TgC/yr for the northern California region, and 

1.25 TgC/yr, for Oregon and Washington (table 11.3). For 

all three regions combined, the baseline rate of total carbon 

storage due only to terrestrial processes was 2.0 TgC/yr 

(table 11.3). From 1992 to 2050, the total baseline carbon 

storage due only to terrestrial processes in Pacific coastal 

waters was roughly 100 TgC. The results suggest that under 

baseline conditions, approximately 82 percent of this carbon 

was stored at water depths less than 100 m. Between water 

depths of 50 and 100 m, relatively little carbon storage was 

due to burial in sediments (17 percent), whereas between 

0 and 50 m, a moderate amount of carbon storage was due to 

burial in sediments (70 percent). Approximately 18 percent 

of the total carbon stored was in water depths below 100 m. 

These estimates were generally in agreement with previous 

estimates of sediment and carbon transport to Pacific coastal 

waters (Sternberg, 1986; Hales and others, 2006).

Most of the current and projected carbon storage in 

Pacific coastal waters occurred in regions of high nutrient 

and sediment load, with an estimated 62 percent of the 

modeled baseline carbon storage occurring in the coastal 

waters of Oregon and Washington (table 11.3). The Columbia 

River alone discharged 27.9 TgC/yr of sediment, resulting 

in a model-estimated rate of coastal carbon storage of 

0.9 TgC/yr or 46 percent of the total carbon stored in Pacific 

coastal waters. The San Francisco Bay region also contributed 

significant nutrient and sediment fluxes and accumulated 

significant carbon, according to the model; however, much 

of this production and storage likely occurred within the San 

Francisco Bay, which was not modeled separately.

The changes in sediment and nutrient loadings to Pacific 

coastal waters under the projected land-use and population 

changes envisioned in the IPCC–SRES A2 scenario resulted 

in a change in the estimated projections of carbon that was 

transported and buried in the deep ocean. Under the A2 

scenario in 2050, the rate of carbon storage in Pacific coastal 

waters was projected to increase by 33 percent in the southern 

California region and by 4 percent in the northern California 

region (table 11.3). In Oregon and Washington, however, 

where most of carbon storage presently occurs, the model 

projected a 12 percent decline in the rate of carbon storage. 

Taken together, the cumulative effect of projected land-use 

change by 2050 under the A2 scenario was a decrease in the 

projected rates of carbon storage in Pacific coastal waters by 

4 percent overall. This decrease corresponded to a projected 

decrease in the total carbon storage to 112 TgC over the 

58 years between 1992 and 2050, for a net difference of 

3 percent.

The nutrient fluxes that support phytoplankton production 

Pacific coastal waters are largely supplied by seasonal 

upwelling (Kudela and others, 2006; Hales and others, 2008). 

Nevertheless, higher rates of annual phytoplankton production 

have been observed close to rivers (Kudela and others, 2006; 

Hales and others, 2008), and the model results indicated the 

total nitrogen supply to Pacific coastal waters may support up 

to 15 percent of the total production under baseline conditions 

(G.C. Anderson, 1964; Kudela and others, 2006). The 

projected cumulative changes to the rate of carbon storage in 

Pacific coastal waters that were due to a projected increase in 

nutrient exports by 2050 under the A2 scenario were relatively 

minor in comparison to the changes due to sediment flux; 

even though the projected increase in total nitrogen flux due to 

land‐use and population change was in the range of 28 percent, 

there was less than a 3 percent projected increase in the total 

nutrients available to support phytoplankton production.

11.5. Discussion

The results indicate that the rate of carbon storage in the 

Pacific coastal waters that resulted directly from terrestrial 

processes contributed significantly to the carbon balance of 

the Western United States under both baseline and projected 

future conditions. The rate of modeled carbon storage that 

was due to terrestrial fluxes accounted for half to two thirds 

of the total estimated carbon storage in the same region (3 to 

4 TgC/yr) (Hales and others, 2008). The rate of modeled 

carbon storage due to terrestrial fluxes is comparable to the 

estimated 1.2 TgC/yr rate in inland reservoirs (chapter 10), 

but much lower than the estimated 86 TgC/yr rate in terrestrial 

ecosystems (chapter 5). 
Chapter 11 157

The majority of terrestrial contribution to coastal 

carbon storage occurred in the coastal waters of Oregon and 

Washington under both the baseline and projected future 

conditions because of the large discharge of nutrients and 

sediments from the rivers located in that region. Sediment 

discharge and carbon storage was also high in the vicinity 

of the Eel River in the northern California region and 

near San Francisco Bay, but much lower in the southern 

California region.

The majority of the coastal carbon sequestration 

related to terrestrial processes resulted from the transport 

of TOC below the level of the pycnocline rather than burial 

in sediments. Of the total carbon stored, the model results 

suggested that approximately 70 percent was directly 

transported to the deep ocean and approximately 30 percent 

was buried in coastal sediments. For the amount buried in 

sediments, the model results indicated that approximately 

70 percent was buried at depths less than 50 m, approximately 

15 percent was buried between 50 m and 100 m depth, and the 

remainder (approximately 15 percent) was buried in the deep 

ocean. The decreased burial in the deeper zones was because 

of the lower sediment flux in this region and the deeper water 

column. These results agree with Dunne and others (2007), 

who suggested that previous ocean models of carbon storage 

rates did not account for the appreciable carbon storage that 

occurs in shallow coastal sediments. 

The projected increase in sediment flux in the southern 

California region (23 percent from the baseline flux) 

corresponded with a projected increase in carbon storage rates 

in coastal waters, but the projected overall decline in sediment 

flux in the other regions resulted in an overall decrease in 

the projected coastal carbon storage rates for the region. 

The increase in carbon storage rates in southern California 

was driven by the elevated modeled fluxes from small, 

mountainous rivers in southern California which respond more 

sensitively to land-use and population changes than larger 

river systems, such as those in northern California and the 

Pacific Northwest.

Small, mountainous rivers were important generally 

to coastal carbon storage processes despite their relatively 

small watershed areas because of their large sediment loads 

(Milliman and Syvitski, 1992; Blair and others, 2004). For 

example, in 1992, the modeled sediment discharge from the 

Columbia River was 28 Tg/yr, while the discharge from small, 

mountainous rivers was 21 Tg/yr for the same year. Small, 

mountainous rivers, therefore, contributed 75 percent of the 

sediment discharge of the fourth largest river in the United 

States. These results indicated that small, mountainous rivers 

should be included in estimates of terrestrial and ocean carbon 

balances and that focusing only on large river systems may 

significantly underestimate fluxes and coastal carbon storage. 

The model results suggest that under the land-use projections 

of scenario A2 in 2050, rates of carbon storage due to small, 

mountainous rivers was projected to decrease by 12 percent; 

however, and perhaps more importantly, nutrient discharges 

for these rivers were projected to increase by 26 percent.

The concomitant increase in sediment and nutrients 

in small, mountainous rivers has the potential to increase 

carbon storage rates beyond that which was estimated by 

the model because the projected increase in nutrients may 

stimulate additional phytoplankton production at the same 

time and location that sediment fluxes are projected to increase 

(Wheatcroft and others, 2010). Normally, phytoplankton 

production is elevated in the summer due to the upwelling 

of nutrient-rich waters, while sediment flux peaks in winter 

with peak river discharge (Wheatcroft and others, 2010). 

The projected coincidence of phytoplankton production and 

sediment concentration is expected to accelerate the transport 

of phytoplankton carbon from the surface ocean to the deep 

ocean (Armstrong and others, 2009) and, therefore, increase 

carbon burial efficiency.

The projected increases in nutrient fluxes that would 

result from land-use and population changes under the A2 

storyline in 2050 may have additional effects that were 

not captured by the model. Depending on future waterquality regulations and the form of the nutrients, the 

additional nutrients may (1) exacerbate hypoxia that has 

been periodically observed at the mouth of the Columbia 

and elsewhere on the Pacific Coast or (2) stimulate the 

production of harmful algal blooms (Glibert, 2010). Despite 

the obvious deleterious effects on water quality, broader areas 

of hypoxia in surface or bottom water will likely increase the 

rates of carbon storage in these regions (Bergamaschi and 

others, 1997). 
158 Terrestrial Fluxes of Sediments and Nutrients to Pacific Coastal Waters and Their Effects on Coastal Carbon Storage Rates

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Chapter 12. Toward an Integrated Assessment of

Baseline and Projected Future Carbon Storage and 

Greenhouse-Gas Fluxes in Ecosystems of the Western 

United States—Further Analyses and Observations

By Shuguang Liu1, Zhiliang Zhu2, Terry L. Sohl1, Todd J. Hawbaker3, Benjamin M. Sleeter4, Sarah M. 

Stackpoole3, and Richard A. Smith2

1U.S. Geological Survey, Sioux Falls, S.D.

2

 U.S. Geological Survey, Reston, Va.

3U.S. Geological Survey, Denver, Colo.

4U.S. Geological Survey, Menlo Park, Calif.

12.1. Highlights 

• The sum of the estimated mean net fluxes of carbon 

from terrestrial and aquatic pools was approximately 

−91.0 teragrams of carbon per year (TgC/yr) in the 

Western United States from 2001 to 2005. Terrestrial 

ecosystems sequestered 95 percent of the total 

carbon sequestered in the region. This rate of the 

total ecosystem carbon sequestration is equivalent to 

4.9 percent of the total greenhouse-gas emissions from 

the United States in 2010. 

• Compared with the baseline net ecosystem carbon 

balance (NECB) estimates for terrestrial ecosystems, 

which ranged from −162.9 to −13.6 TgC/yr, the 

projected future potential NECB for terrestrial 

ecosystems in the Western United States ranged 

from −113.9 to 2.9 TgC/yr, representing a potentially 

significant decline by as much as 30 to 121 percent (or 

from 16.5 to 49 TgC/yr). This projected decrease was 

estimated by considering land-use- and land-cover- 

(LULC-) change scenarios and general circulation 

models, incorporating simulated wildland-fire 

disturbances, and using biogeochemical models. 

• The estimated baseline wildland-fire emissions were 

equivalent to 11 to 12 percent of the estimated rate of 

sequestration by terrestrial ecosystems in the Western 

United States. Because wildland-fire emissions were 

projected to increase and sequestration by terrestrial 

ecosystems was projected to decline under future 

climate conditions, the projected wildland-fire 

emissions could potentially be equivalent to 27 to 

43 percent of the projected sequestration by terrestrial 

ecosystems. The carbon stored in arid and semiarid 

regions of the Western United States was especially 

vulnerable to wildland-fire emissions under both the 

baseline and projected future conditions.

12.2. Introduction

This assessment was a multidisciplinary effort to study 

carbon stocks, carbon sequestration, and greenhouse-gas 

(GHG) fluxes in terrestrial and aquatic ecosystems in the 

context of major controlling processes such as land-use 

and land-cover (LULC) changes, climate changes, and 

wildland‐fire occurrences. All of the major ecosystems were 

included in the assessment in a spatially and temporally 

explicit fashion, thus allowing for opportunities to analyze 

relations between input and output data, parameters 

and estimates, drivers and results, and geographies and 

time horizons. Specifically, there are four objectives for 

this chapter:

1. Examine the baseline carbon stocks, sequestration, and 

fluxes that were estimated from the different assessment 

components (chapters 2, 3, 5, 10, and 11) in order to 

provide a heuristic view of the carbon cycle and budget in 

the Western United States. 

2. Compare similarities and differences between the 

estimated baseline and projected terrestrial net carbon 

fluxes and greenhouse-gas (GHG) fluxes. Because 

projections were not available for inland aquatic 

ecosystems, the comparison does not include processes 

related to them.

3. Synoptically examine the impacts of LULC change, 

disturbances, and climate change on carbon stocks and 

sequestration across the Western United States. 

4. Discuss and summarize the major accomplishments and 

limitations of this assessment.
160 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

12.3. Observations and Examinations

12.3.1. Carbon Cycle and Budget in Terrestrial 

and Aquatic Systems During the Baseline 

Period 

The estimated baseline (2001–2005) carbon stocks 

and changes in carbon stocks (fluxes) of the pools that were 

studied in the Western United States and were calculated 

during this assessment are shown in figure 12.1. The diagram 

depicts the results from the previous chapters. For simplicity, 

the estimated carbon stocks in all terrestrial ecosystems were 

lumped together in this diagram within two carbon pools: 

one for biomass carbon and the other for soil organic carbon 

(chapter 5 of this report). The emissions from wildlandfire combustions represented average conditions between 

2001 and 2008 (chapter 3 of this report). Aquatic fluxes and 

sequestration (chapters 10 and 11) were based on input data 

representing average conditions from the 1970s to 2012. 

Atmosphere

Biomass

8,492

SOC

5,427 Lakes Rivers Coast

NPP

(726.7)

HR

(599.5)

Fire

(10.03)

CH4

(0.8)

Decay

(NA)

Evasion

(26.1)

Evasion

(2.1)

Wood

product

(11.7)

7.2

46.9 39.7 2.4 2.0

Grain

(18.9)

9.5

Stock, in TgC/yr

Stock change, in TgC/yr

Flux, in TgC/yr

EXPLANATION

Figure 12–1.

NA NA NA

Figure 12.1. Flow diagram showing average carbon 

stocks and fluxes and changes in average carbon stock for 

primary carbon pools in the Western United States during 

the baseline period (2001–2005). Not all carbon stocks and 

fluxes are included in this diagram; only those stocks and 

fluxes that were examined in the assessment are shown. 

Changes in carbon storage rates in lacustrine systems (lakes 

and reservoirs) and in coastal waters (by burial in sediment) 

were included, but the carbon stocks in these ecosystems 

were not included. In quantifying the changes in average 

carbon stocks of soils and biomass, carbon combustion by 

fire and transfer to products by harvesting were considered but 

not their export to the aquatic ecosystems. There was no coupling 

between the estimates of carbon stocks in the terrestrial and 

aquatic systems. Positive carbon stock change indicates a carbon 

storage increase, and therefore represents carbon sequestration. 

The dotted arrow under the “Rivers” box indicates the lateral flux 

of carbon within the streams and rivers. NA, not applicable, due 

to either a lack of input data or the choice of methods; NPP, net 

primary production of terrestrial ecosystems; HR, heterotrophic 

respiration of terrestrial ecosystems; SOC, soil organic carbon; 

TgC/yr, teragrams of carbon per year.
Chapter 12 161

As noted in chapter 1 of this report and above, the baseline 

years varied for different components of the overall carbon 

cycle because of the varying availability of input data. As 

a result, figure 12.1 should be interpreted as a composite 

representation of contemporary carbon-cycle processes in the 

region. The common time period for all the components was 

from 2001 to 2005, which is the nominal baseline period for 

this assessment (chapter 1 of this report). 

On average, the terrestrial ecosystems (forests, 

agricultural lands, grasslands/shrublands, wetlands, and 

other lands) in the five ecoregions of the Western United 

States stored a total of 13,919 TgC during the baseline period 

(2001–2005). Carbon in biomass pools (such as live and 

dead vegetative materials aboveground and belowground, 

except for those removed from agricultural fields and forests) 

accounted for 8,492 TgC (61 percent) of the total, and the rest 

was stored in the top 20 cm of the soil layer. Carbon stored in 

other pools (such as grain and wood products removed from 

the landscape) was not estimated in this assessment, although 

its influx was calculated. The regional NECB was estimated to 

be −91.0 TgC/yr in the Western United States. This estimate 

represented the sum of carbon removed from the atmosphere 

and sequestered in terrestrial pools and in sediments in 

lakes, reservoirs, and coastal waters in this region. Of 

the total NECB in the region, the terrestrial ecosystems were 

responsible for an average of −86.6 TgC/yr (95 percent of the 

total NECB), including −46.9 TgC/yr and −39.7 TgC/yr 

in biomass and soils, respectively (fig. 12.1). The average 

amount of carbon sequestered annually in the Western United 

States during the baseline period was equivalent to about 

4.9 percent of the fossil-fuel emissions in the United States in 

2010 (EPA, 2012). 

Among the various types of flux, the largest were the 

net primary production (NPP) and heterotrophic respiration 

of the terrestrial ecosystems. About 12 percent of the annual 

NPP was sequestered in biomass and soils. The amount of 

carbon removed by timber harvesting (only clearcut areas 

were considered) from the landscape was 11.7 TgC/yr, 

which was similar in magnitude to the carbon emissions 

from wildland fires (10.0 TgC/yr). The amount of carbon 

removed by harvesting grain from agricultural lands was 

18.9 TgC/yr, which is a large amount considering that 

agricultural land was not the dominant land-cover type in the 

Western United States. The amount of carbon removed by 

timber harvesting was largely underestimated compared with 

estimates in other studies (Hudiburg and others, 2011; D.P. 

Turner, Ritts, and others, 2011) and in the U.S. Department 

of Agriculture’s timber statistics reports (USDA, 2011a). The 

underestimation was likely caused by the omission of partial 

forest cutting in the assessment, which was due to the absence 

of geospatial data layers describing the location, extent, and 

intensity of partial forest cutting with adequate spatial and 

temporal resolution. 

Although carbon fluxes related to timber and grain 

harvesting were estimated, no life-cycle analysis was 

conducted to evaluate the long-term decomposition rates 

of the harvests. Also not included in this assessment were 

carbon fluxes related to forest thinning, forest defoliation and 

mortality from insects, and rangeland grazing. As documented 

in chapter 4 of this report, these land-management concerns 

and natural disturbances, which are highly relevant to the 

carbon cycle in the Western United States, were not supported 

with sufficient input data. As a result, their exclusion 

introduced uncertainty in the assessment.

Inland aquatic ecosystems in the Western United States 

represented only a small portion of the total area (1.5 percent), 

but they played an important role in determining the fate 

of a large portion of the total carbon flux in the region. The 

total flux (lateral and efflux) of inland aquatic ecosystems 

at 37.7 TgC/yr was previously unaccounted for and is 

regionally significant (such as in the Marine West Coast Forest 

ecoregion). Several processes related to the carbon cycle of 

the inland and coastal aquatic systems were not included in 

the study: the effluxes of carbon dioxide from the Pacific 

coastal waters, lateral transport of carbon by soil erosion and 

deposition, and the interactions of carbon between terrestrial 

and aquatic ecosystems. 

The export of carbon by riverine systems into the 

Pacific coastal waters was estimated to be 7.2 TgC/yr. Only 

a small amount of the carbon exported by riverine system 

was estimated to be stored in the Pacific coastal waters, but 

terrestrial processes (such as primary production by different 

terrestrial ecosystems) were directly involved in storing 

approximately 2.0 TgC/yr.

12.3.2. Comparing Baseline and Projected Future 

Estimates of Net Ecosystem Carbon Balance

The minimum and maximum estimates of the mean 

terrestrial net ecosystem carbon balance are listed in 

table 12.1 for both baseline (2001–2005) and projected future 

(2006–2050) conditions. The negative NECB values indicate 

carbon sequestration in terrestrial ecosystems, and positive 

values suggest carbon loss from ecosystems (partially by 

lateral transport of terrestrial ecosystems, such as grain and 

timber harvesting). 
162 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Table 12.1. Minimum and maximum estimates of mean net ecosystem carbon balance under baseline (2001–2005) and projected future 

(2006–2050) conditions for all major ecosystems for the Western United States. 

[Negative net ecosystem carbon balance (NECB) values indicate carbon sequestration in terrestrial ecosystems and positive values indicate carbon loss. 

Minimum mean and maximum mean represent the annual means of the minimum and maximum NECB among the 21 General Ensemble Modeling System 

(GEMS) simulations over the baseline and projection periods under various biogeochemical models, land-use- and land-cover-change scenarios, and climates 

projected by general circulation models (see chapters 5 and 9 of this report). For the column indicating the difference between the baseline and projected NECB, 

negative values indicate a decrease in NECB from baseline to future projections, and positive values indicate an increase. TgC/yr, teragrams of carbon per year]

Ecoregion Ecosystem

Baseline NECB

(TgC/yr)

Projected NECB

(TgC/yr)

Difference between

baseline and 

projected NECB

(TgC/yr)

Minimum

mean

Maximum

mean

Minimum

mean

Maximum

mean

Minimum

mean

Maximum

mean

Western 

Cordillera

Forests −70.3 −19.6 −52.3 −7.0 −18.0 −12.6

Grasslands/shrublands −14.6 0.2 −7.9 0.3 −6.7 −0.1

Agricultural lands −0.4 0.0 −1.0 0.0 0.6 0.0

Wetlands −0.7 −0.1 −0.4 0.0 −0.3 −0.1

Other lands −0.2 0.4 −0.2 0.0 0.0 0.4

Total −86.2 −19.1 −61.8 −6.7 −24.4 −12.4

Marine West 

Coast Forest

Forests −6.0 −1.3 −8.1 1.8 2.1 −3.1

Grasslands/shrublands −0.7 0.0 −0.4 0.0 −0.3 0.0

Agricultural lands 0.0 0.1 −0.5 0.2 0.5 −0.1

Wetlands 0.0 0.0 −0.1 0.0 0.1 0.0

Other lands −0.2 0.2 −0.5 −0.1 0.3 0.3

Total −6.9 −1.0 −9.6 1.9 2.7 −2.9

Cold Deserts Forests −7.8 1.5 −7.7 −0.8 −0.1 2.3

Grasslands/shrublands −20.9 3.8 −8.7 4.5 −12.2 −0.7

Agricultural lands −3.0 0.0 −4.7 0.0 1.7 0.0

Wetlands −0.6 0.0 −0.4 0.0 −0.2 0.0

Other lands −0.3 0.4 −0.2 0.1 −0.1 0.3

Total −32.6 5.7 −21.7 3.8 −10.9 1.9

Warm Deserts Forests −0.6 0.2 −0.5 0.0 −0.1 0.2

Grasslands/shrublands −16.1 2.7 −3.9 5.4 −12.2 −2.7

Agricultural lands −1.8 0.0 −1.3 0.0 −0.5 0.0

Wetlands 0.0 0.0 −0.1 0.0 0.1 0.0

Other lands −0.1 0.0 −0.1 0.0 0.0 0.0

Total −18.6 2.9 −5.9 5.4 −12.7 −2.5

Mediterranean 

California

Forests −6.1 −2.6 −5.8 −2.0 −0.3 −0.6

Grasslands/shrublands −6.4 0.3 −3.0 0.6 −3.4 −0.3

Agricultural lands −5.6 0.2 −5.0 0.1 −0.6 0.1

Wetlands −0.1 0.1 −0.3 0.0 0.2 0.1

Other lands −0.4 −0.1 −0.5 −0.2 0.1 0.1

Total −18.6 −2.1 −14.6 −1.5 −4.0 −0.6

Western United 

States (total)

Forests −90.8 −21.8 −74.4 −8.0 −16.4 −13.8

Grasslands/shrublands −58.7 7.0 −23.9 10.8 −34.8 −3.8

Agricultural lands −10.8 0.3 −12.5 0.3 1.7 0.0

Wetlands −1.4 0.0 −1.3 0.0 −0.1 0.0

Other lands −1.2 0.9 −1.5 −0.2 0.3 1.1

Total −162.9 −13.6 −113.6 2.9 −49.3 −16.5
Chapter 12 163

During the baseline period, the NECB of the terrestrial 

ecosystems in the Western United States was estimated to 

range from −162.9 to −13.6 TgC/yr, with a mean value of 

−86.6 TgC/yr. In comparison, the projected future range of the 

NECB was estimated to range from −113.6 to 2.9 TgC/yr. The 

comparison in table 12.1 indicates a projected decline in future 

potential sequestration ranging from 16.5 to 49.3 TgC/yr, 

which represents an estimated 30 to 121 percent decrease in 

the potential of those ecosystems to sequester carbon. 

The projected decline in the NECB was highly variable 

among ecoregions and ecosystems. Forests were estimated to 

be the largest carbon sink during the baseline period with a 

mean rate of −53.9 TgC/yr, which accounted for 62 percent 

of the total NECB in the Western United States; however, 

this sink was projected to decrease by 13.8 to 16.4 TgC/yr 

by 2050. This result correlates with previous studies which 

hypothesized that the aging of forest ecosystems in the 

United States may result in weakened carbon sequestration 

by forests over time (Hurtt and others, 2002; Pan, Chen, and 

others, 2011; D.P. Turner, Ritts, and others, 2011). Grasslands/

shrublands were estimated to be the second largest carbon 

sink during the baseline period because of their extensive 

coverage of part of the Western United States; however, this 

estimated sink was projected to have the largest decrease in 

the NECB, with losses ranging from 34.8 to 3.8 TgC/yr by 

2050. In general, the NECB in the rest of the ecosystems in 

the Western United States was projected to remain relatively 

stable between the baseline and projected time periods. 

Table 12.2 shows the differences between the baseline 

estimated mean annual NECB (table 5.4 of chapter 5) and 

the projected mean annual NECB by biogeochemical model, 

climate-change scenario, and general circulation model 

(table 9.2 of chapter 9) for each ecoregion and for the Western 

United States as a whole. Among the three biogeochemical 

models, the CENTURY model projected the largest decrease 

for the Western United States as a whole, followed by the 

spreadsheet model and the Erosion-Deposition-Carbon 

Model (EDCM). The EDCM projected an increase in the 

NECB in the Cold and Warm Deserts ecoregions, whereas the 

CENTURY model projected a decrease of about 20 percent 

and the spreadsheet model projected a similar trend. All three 

biogeochemical models projected that the NECB for the 

Marine West Coast Forest would remain relatively flat. 

Table 12.2. Differences between the baseline and projected net ecosystem carbon balance for each ecoregion, 

categorized by biogeochemical model, land-use- and land-cover-change scenario, and general circulation model.

[CCCma CGCM3.1, Canadian Centre for Climate Modelling and Analysis’s Coupled Global Climate Model version 3.1; CSIRO-Mk3.0, 

Commonwealth Scientific and Industrial Research Organization Mark 3.0; EDCM, Erosion-Deposition-Carbon Model; GCM, general circulation 

model; MIROC 3.2-medres, Model for Interdisciplinary Research on Climate (version 3.2, medium resolution); TgC/yr, teragrams of carbon per 

year]

Model or scenario

Western 

Cordillera 

(TgC/yr)

Marine West

Coast Forest

(TgC/yr)

Cold Deserts 

(TgC/yr)

Warm 

Deserts 

(TgC/yr)

Mediterranean 

California 

(TgC/yr)

Western 

United States 

(TgC/yr)

CENTURY

biogeochemical

model

−31.2 −0.2 −22.4 −18.7 −5.3 −77.7

EDCM

biogeochemical

model

−5.7 −0.3 7.3 2.3 −6.0 −2.4

Spreadsheet

biogeochemical 

model 

−10.0 −1.7 −0.4 −0.1 −0.5 −12.7

A1B scenario −19.3 −1.6 −6.6 −7.2 −5.1 −39.8

A2 scenario −17.6 −1.3 −6.8 −7.2 −4.8 −37.6

B1 scenario −14.8 1.6 −6.3 −6.7 −4.7 −30.9

CCCma

CGCM3.1 

GCM

−18.2 −0.1 −7.8 −8.7 −5.6 −40.3

CSIRO–

Mk3.0 GCM

−18.1 −0.4 −4.3 −6.0 −5.5 −34.4

MIROC 3.2–

medres GCM

−19.0 −0.2 −10.5 −9.9 −5.8 −45.3
164 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

The differences between the baseline and projected 

carbon fluxes under the three scenarios chosen from the 

Intergovernmental Panel on Climate Change’s Special 

Report on Emissions Scenarios (IPCC–SRES; Nakicenovic 

and others, 2000) were relatively consistent, varying from 

−39.8 TgC/yr (A1B scenario) to −30.9 TgC/yr (B1 scenario) 

for the entire Western United States, and this consistency 

can also be seen across all the ecoregions. The climate 

projections affected the magnitude of carbon-flux change 

as well. The most significant decline of −45.3 TgC/yr was 

projected under the Model for Interdisciplinary Research 

on Climate (version 3.2, medium resolution; MIROC 

3.2-medres), and the smallest decline (−34.4 TgC/yr) was 

projected under the Commonwealth Scientific and Industrial 

Research Organization Mark 3.0 (CSIRO–Mk3.0) model. 

The largest differences in carbon flux under the different 

GCMs were manifested in the Cold and Warm Deserts, which 

were the most climate-sensitive ecoregions in the Western 

United States.

12.3.3. Preliminary Observations of Land-Use 

and Land-Cover Change, Disturbances, and 

Climate Change

12.3.3.1. Land-Use and Land-Cover Change

The effects of estimated LULC change on carbon 

sequestration were observed by examining the net change 

in area and the net change in the amount of carbon stored 

(NECB) within three major ecosystems in the Western United 

States (forests, grasslands/shrublands, and agricultural lands). 

Each 5-year time period was plotted for each of the three 

scenarios (fig. 12.2). Although figure 12.2 may be useful for 

examining some effects of LULC change, interpretations 

should be made with these caveats:

• The changes in carbon storage depicted in figure 12.2

were all-inclusive and represented not only the effects 

of net LULC change, but also the effects of other 

driving forces such as climate change and locationspecific LULC transitions. 

• Gross LULC change (LULC transitions both to and 

from a given LULC class) may have led to a change in 

carbon storage, even if there was no net change in area, 

because of the geographic differences in carbon storage 

within the same land cover. The effects of gross LULC 

change on carbon could be investigated in the future. 

• Changes in carbon storage in each LULC category 

did not necessarily indicate carbon sequestration 

from or release to the atmosphere. The changes may 

have simply indicated the reassignment of carbon 

storage from one LULC type to another following a 

LULC transition. For example, if an area of marginal 

agricultural land (with an assumed amount of carbon 

storage of 3,000 gC/m2) transitions to grassland 

(with an assumed amount of carbon storage of 

3,030 gC/m2), it could incur a net carbon gain of 

30 gC/m2/yr. The change in carbon storage would be 

indicated as a loss of 3,000 gC/m2 for the agricultural 

land and a gain of 3,030 gC/m2 for the grassland one 

year after the transition. 

Among the three scenarios, the rate of carbon 

sequestration was projected to decline precipitously over time 

under the A1B and A2 scenarios, while remaining relatively 

stable under the B1 scenario after an initial drop (fig. 12.2). An 

exploration of the exact causes and their relative contributions 

to the trends was not conducted for this report; however, the 

following observations were made: 

• Despite either positive or negative changes in 

individual ecosystems, carbon storage in all 

ecosystems increased consistently in the Western 

United States throughout the projected time period, 

but the rate of increase declined under the A1B and A2 

scenario (fig. 12.2). This result suggested a complex 

relation between LULC change and the net change 

in carbon storage that likely involved the effects of 

other factors. For example, the large amount of carbon 

sequestered in some forests may have been dictated 

by their relatively young age (Pan, Chen, and others, 

2011), which was the result of forest-management 

policies that were created in the first half of the 20th 

century (Houghton and others, 1999; D.P. Turner, 

Ritts, and others, 2011). As the forests matured and 

aged, their sequestration capacity may have been in an 

overall decline. 

• The projected increase in carbon storage in agricultural 

lands may have been largely driven by the modeled 

increase in biomass production capacity over time 

on the basis of assumptions made in the model about 

improvements in genetic engineering, cultivation, 

and management practices (S. Liu and others, 2003). 

On the other hand, changes in carbon storage and 

sequestration by grasslands/shrublands were projected 

to follow changes in the ecosystem’s land area with a 

time lag.
Chapter 12 165

 Scenario A1B

Figure 12–2.

Change in area, in square kilometers –40,000

–60,000

–20,000

0

20,000

40,000

Net ecosystem carbon balance,

in teragrams of carbon

0

100

200

300

400

2001–20052006–20102011–2015

2016–20202021–2025

2026–20302031–20352036–20402041–2045

2046–20502001–20052006–20102011–20152016–20202021–2025

2026–20302031–2035

2036–2040

2041–2045

2046–2050

2001–20052006–2010

2011–20152016–20202021–2025

2026–20302031–20352036–20402041–2045

2046–2050

 Scenario A2 Scenario B1

Forest

Grassland/shrubland

Agriculture

EXPLANATION

Figure 12.2. Charts showing comparisons of net change in the area of major land-use and land-cover classes and 

net ecosystem carbon balance (NECB), by 5-year intervals in the Western United States from the baseline (2001–2005) 

through the projected (2006–2050) time periods. 

12.3.3.2. Land Management and Disturbances

Across the Western United States, forest cutting was 

projected to increase from the baseline under the A1B and A2 

scenarios, but was projected to decline from the baseline under 

the B1 scenario (chapter 6 of this report). These projections 

were used to simulate the amount of timber harvested 

(fig. 12.3). The projections of reduced forest cutting under the 

B1 scenario, which effectively increased the rotation length 

of harvesting, largely explained the differences in carbon 

sequestration between the B1 scenario and the other two 

IPCC–SRES scenarios (fig. 12.3). For example, under the 

B1 scenario, the projected increase in carbon by forests was 

more pronounced and sustained than under the other scenarios 

in the Marine West Coast Forest and Western Cordillera 

ecoregions, where most forest cutting was expected to take 

place. The annual differences in carbon sequestration by 

forest cutting among all three IPCC scenarios were as great as 

3 TgC/yr in the Marine West Coast Forest and 7.5 TgC/yr 

in the Western Cordillera. The results agreed well with past 

observations that changes in forest harvesting regimes have 

a large effect on carbon sequestration (Cohen and others, 

1996; Houghton and others, 1999; D.P. Turner, Ritts, and 

others, 2011). 
166 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

Across the Western United States, the median area 

burned annually by wildland fires was 12,136 km2 during 

the baseline time period (2001–2008), but the interannual 

variability in burned area was large; specifically, 23,261 km2

burned during extreme years, defined as the 95th percentile 

of the area burned annually. Wildland fires emitted a median 

of 41.0 TgCO2-eq/yr and emitted 65.0 TgCO2-eq/yr in 

extreme years. Median and extreme wildfire emissions were 

approximately 0.07 percent and 0.13 percent, respectively, 

of the total carbon stock (14,182 TgC) in the Western United 

States from 2001 to 2008.

Both the area burned by wildland fires and GHG 

emissions were projected to increase in the Western United 

States under all three of the climate-change scenarios 

considered in this assessment (chapter 8 of this report). 

The projected median of the area burned annually increased 

31 to 66 percent relative to the baseline conditions (average 

of 2001 to 2008, which was 12,136 km2) and the projected 

median annual emissions increased 28 to 56 percent from a 

baseline median of 41.0 TgCO2-eq/yr. These increases resulted 

in the median of the area burned annually ranging between 

15,900 and 20,100 km2 and emissions ranging between 

52.5 and 64.0 TgCO2-eq in the decade between 2041 and 

2050. Thus, a typical (median) fire year in the future could be 

rather similar to an extreme (95th percentile) fire year in the 

baseline period. Extreme fire years were projected to become 

even more extreme; the 95th percentile of the area burned 

annually increased 79 to 95 percent from baseline conditions 

(2001–2008), from 23,261 km2/yr to between 41,600 and 

45,400 km2/yr. The emissions in extreme fire years increased 

73 to 150 percent to between 112 and 163 TgCO2-eq/yr relative 

to the 65.0 TgCO2-eq/yr during the baseline period.

The relative amount of carbon stocks lost in each 

ecosystem for each year through wildland-fire emissions 

was projected to increase. The future potential carbon stocks 

in the decade between 2041 and 2050 were projected to be 

16,492 TgC across the Western United States. Carbon losses 

through emissions in a typical fire year in the same decade 

were projected to range between 0.08 and 0.09 percent of 

the potential carbon stock, which is a 0.01 to 0.02 percent 

increase from the baseline time period; in an extreme fire year 

during the same decade, carbon losses were projected to range 

between 0.19 and 0.27 percent of the potential carbon stock

(table 12.3). The patterns of change in carbon stocks across 

the Western United States were generally consistent within the 

ecoregions, except for the Marine West Coast Forest, where 

little change in wildland-fire occurrences and emissions was 

projected, and in Cold Deserts, where the projected changes in 

emissions relative to carbon stocks were small. Over the same 

time period, the rate of carbon sequestration was projected to 

decrease by 45 to 58 percent across the Western United States. 

Even though carbon stocks were projected to increase over 

time, carbon sequestration rates were projected to ultimately 

decrease, partially because of the projected increase in 

wildland-fire emissions.

2000 2010 2020 2030 2040 2050

0

5

10

15

20

Western Cordillera

Year Year

Carbon removal due to timber harvest,

in teragrams of carbon per year 

2000 2010 2020 2030 2040 2050

0

2

4

6

8

10

Marine West Coast Forest

EDCM and Scenario A1B

EDCM and Scenario A2

EDCM and Scenario B1

CENTURY and Scenario A1B

CENTURY and Scenario A2

CENTURY and Scenario B1

Scenario A1B mean

Scenario A2 mean

Scenario B1 mean

All mean

EXPLANATION

Figure 12–3.

Standard deviation of 

 model runs

Figure 12.3. Graphs showing carbon removal from the Western 

Cordillera and Marine West Coast Forest ecoregions during the 

baseline (2001–2005) and projected (2006–2050) time periods 

as the result of forest harvesting activities, simulated under 

the three selected climate-change scenarios and two of the 

biogeochemical models. The other ecoregions studied in the 

assessment were estimated to have smaller amounts of carbon 

removal because they had limited forest coverage; the results 

from those ecoregions are not presented here. Scenarios are from 

the Intergovernmental Panel on Climate Change’s Special Report 

on Emissions Scenarios (Nakicenovic and others, 2000). EDCM, 

Erosion-Deposition-Carbon Model; TgC/yr, teragrams of carbon 

per year.
Chapter 12 167

Table 12.3. Estimated wildland-fire emissions relative to total ecosystem carbon stocks during typical and extreme fire years 

for the baseline (2001–2008) and future (2041–2050) time periods.

Ecoregion

Typical fire years

(in percent)

Extreme fire years

(in percent)

Baseline

Future 

projected 

low

Future 

projected

high

Baseline

Future 

projected

low

Future 

projected

high

Western Cordillera 0.100 0.090 0.130 0.180 0.200 0.440

Marine West Coast Forest 0.010 0.010 0.010 0.010 0.000 0.010

Cold Deserts 0.040 0.050 0.070 0.070 0.120 0.150

Warm Deserts 0.090 0.100 0.160 0.230 0.200 0.460

Mediterranean California 0.060 0.050 0.070 0.110 0.110 0.120

Western United States 0.070 0.080 0.090 0.130 0.190 0.270

12.3.3.3. Effects of Climate Change

Globally, increased carbon dioxide and climate change 

may cause change in the terrestrial ecosystem carbon cycle 

(Birdsey and others, 1993). Levy and others (2004) noted 

that the global carbon sink for 1990 through 2100 may range 

between 2 and 6 PgC/yr because of different fossil-fuelemissions scenarios (Levy and others, 2004). According 

to Fung and others (2005), the terrestrial carbon sink may 

decrease globally in the coming decades and the amount could 

vary, depending on emissions scenarios. In the United States, 

the carbon sink could continue but could weaken over the 21st 

century (Hurtt and others, 2002). The following observations 

were made on the potential effects of climate change:

• The grasslands/shrublands ecosystem in the Western 

United States was sensitive to climate change and 

variability. The temporal variability of carbon stock 

change (sources or sinks) in the Cold Deserts and 

Warm Deserts ecoregions, as examples, were high and 

did not follow the corresponding temporal variability 

of the change in the extent of the grasslands/shrublands 

ecosystem (fig. 12.2). Flux-tower observations at the 

site-specific and regional scales have shown strong 

interannual variability in carbon-storage changes in the 

grasslands/shrublands ecosystem in this region (Scott 

and others, 2011; Xiao and others, 2011). 

• All of the GCMs consistently projected future warming 

trends in all ecoregions, but the degree of warming 

varied by GCM and ecoregion (chapter 7 of this 

report). The projected changes in precipitation were 

highly variable. Figure 12.4 compares the density 

functions of relative change of precipitation during 

two time periods: 2001 to 2010 and 2041 to 2050. All 

of the GCMs projected extensive changes at the pixel 

level as indicated by the spread and shift of the density 

functions from x=0 (which indicates no change). As 

an example, in the Cold Deserts ecoregion, where the 

carbon balance in the grasslands/shrublands ecosystem 

changed from a sink to a source under the A1B and 

A2 IPCC–SRES scenarios, two out of three GCMs 

suggested a 5 to 20 percent decrease in precipitation 

under all three IPCC–SRES scenarios (fig. 12.4). 

• The GCMs projected a high degree of spatial 

variability in climate change even within ecoregions, 

as indicated by the spreading of the density curves 

of temperature and precipitation changes. In order 

to understand the effects of climate change at the 

ecoregion level, the spatial variability of climate 

change needed to be considered. For example, for the 

Marine West Coast Forest ecoregion, all of the GCMs 

projected, on average, small increases in precipitation 

under the A1B and A2 scenarios and small decreases 

under the B1 scenario; however, the patterns of 

carbon-storage change across scenarios in forests did 

not correlate to projected precipitation increases or 

decreases in the ecoregion. Future efforts to analyze 

the effects of climate may be aided by considering the 

spatial variability of those effects.
168 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

0

0.10

0.20

0

0.10

0.20

–40 –20 0 20 40

0

0.10

0.20

–40 –20 0 20 40 –40 –20 0 20 40 –40 –20 0 20 40 –40 –20 0 20 40

Scenario B1 Scenario A2 Scenario A1B

NORMALIZED FREQUENCY

 Western Cordillera Marine West Coast Forest Cold Deserts Warm Deserts Mediterranean California

Annual average precipitation differences between two time periods (2001–2010 and 2041–2050), in millimeters per year

EXPLANATION

Figure 12–4.

CSIRO–Mk3.0 MIROC 3.2–medres CCCma CGCM3.1

Figure 12.4. Graphs showing the distribution of annual average 

precipitation differences between the two time periods: 2001 to 

2010 and 2041 to 2050. These averages were derived from the 

three general circulation models (CCCma CGCM3.1, CSIRO–Mk3.0, 

MIROC 3.2 medres) under three IPCC–SRES scenarios (A1B, A2, 

B1) for five ecoregions in the Western United States. The vertical 

axis shows the relative frequency and the integral (or area 

under each curve) equals 1. CCCma CGCM3.1, Canadian Centre 

for Climate Modelling and Analysis’s Coupled Global Climate 

Model version 3.1; CSIRO–Mk3.0, Commonwealth Scientific and 

Industrial Research Organisation Mark 3.0 model; IPCC–SRES, 

Intergovernmental Panel of Climate Change’s Special Report on 

Emissions Scenarios (Nakicenovic and others, 2000); MIROC 3.2–

medres, Model for Interdisciplinary Research on Climate version 

3.2, medium resolution.
Chapter 12 169

12.4. Gaps, Uncertainties, and 

Limitations

This report covered broad and comprehensive 

topics designed to fulfill the requirements of the Energy 

Independence and Security Act of 2007 (described in 

chapter 1 of this report; U.S. Congress, 2007). The results, 

data products, and publications (including this report) were 

designed to assist the scientific community, land managers, 

and policy stakeholders in a variety of applications. Gaps in 

the assessment remain, however. There were both natural and 

anthropogenic ecosystem processes that were not explored 

and critical relations and feedback loops not yet analyzed 

and reported. The following gaps contributed to uncertainties 

in the results of this assessment and could be considered for 

future investigations.

• Major land-management activities in the Western 

United States (see chapter 4 of this report for more 

information) were not fully addressed. Two of the most 

important land-management activities in the Western 

United States, forest thinning and rangeland grazing, 

were not included in the assessment and their effects 

on carbon and GHG fluxes were not analyzed.

• Although emissions from wildland-fire combustions 

and effects on carbon dynamics over time were 

estimated using the best available data and models, 

an analysis of the long-term effects on net ecosystem 

production, including decomposition and regeneration 

of forests, was not included in the report.

• The estimated mean baseline carbon stock of 

13,921 TgC (ranging from 12,418 to 15,460 TgC) for 

the Western United States reflected only terrestrial 

ecosystems. Baseline and projected estimates of carbon 

stocks were not made for the aquatic ecosystems. The 

estimates for the aquatic ecosystems focused only on 

carbon fluxes.

• Carbon sequestration estimates for both the baseline 

and the projected time periods were based on three 

future scenarios, which reflected the combined 

effects of LULC change, available land-management 

activities, wildland fires, and climate change (for future 

projections only). An understanding of the specific 

contributions by each of these controlling processes 

would require model runs using experimental designs. 

Instead, for this report, only preliminary analyses of 

possible individual effects were provided. 

For all of the major technical processes in this 

assessment, practical efforts were made to validate baseline 

estimates and evaluate uncertainties in both the baseline and 

projected results. The validation steps and uncertainty in the 

results have been documented in this report. Uncertainties 

were quantified based on traditional statistical methods to 

account for the spread of multiple model runs. The actual 

spread of uncertainties in the results, as well as contributions 

from specific sources (including input data, model structure 

and parameterization, shortfalls in land-management activities 

and natural disturbances (as noted above), and connections 

or coupling between technical components of the assessment 

methodology) were not statistically quantified. Additional 

observations concerning uncertainties were made:

• The LULC changes and wildland-fire disturbances 

were modeled and estimates were made separately. 

The estimates were calculated for each pixel, but 

these estimates were not integrated; therefore, it is 

possible that a forest pixel that was modeled to be 

burned would still have a chance of being harvested at 

the same time or within a few years of the wildlandfire occurrence. Nevertheless, over the scale of an 

ecoregion, the integration of LULC with wildland-fire 

models and estimates is unlikely to be a major source 

of uncertainty.

• Aquatic and terrestrial methods were not coupled 

such that the aquatic methods used direct input 

from terrestrial models (for example, erosion and 

deposition) in order to estimate the effects and fate of 

terrestrial exports. Thus, it is uncertain how much of 

the aquatic carbon fluxes came from terrestrial sources. 

In addition, the possibility of overlaps in counting 

the surface areas between aquatic features (such as 

streams and rivers) and terrestrial ecosystems (such as 

wetlands) could lead a small portion of carbon fluxes 

to be counted twice.

• Ultimately, for projected future potential carbon storage 

and fluxes, it is the use of various input data layers 

(including the LULC-change and climate-change 

scenarios within the three IPCC–SRES storylines) 

and biogeochemical models that dictated the overall 

spread of the uncertainties in the assessment results. 

Uncertainties from these models and data layers were 

undoubtedly large, and future effort should emphasize 

the quantification and attribution of uncertainty in 

estimating carbon sequestration over large areas.

In using this report, as well as publications and data 

products generated for the assessment, caution should be 

exercised by considering the above-noted constraints and 

uncertainties together with the major findings and unique 

aspects of the assessment. In addition, this assessment was 

conducted in the framework of the five ecoregions, which 

were used to parameterize the assessment models. The 

results were therefore presented at the ecoregional scale. 

Therefore, although this assessment’s spatial-data products 

were delivered at a 250-m-pixel resolution, the scale of the 

ecoregions is the most appropriate scale for applying the 

results of this assessment to further activities. 
170 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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192 Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States

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Zhu and Reed, eds.— Baseline and Projected Future Carbon Storage and Greenhouse-Gas Fluxes in Ecosystems of the Western United States—Professional Paper 1797