United States*
Environmental Protection
Agency
Policy, Planning,
And Evaluation
(2122)
EPA 230-R-95-002
June 1995
Climate Change Mitigation
Strategies In The Forest
And Agriculture Sectors
!l
'I
r z. -
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CLIMATE CHANGE MITIGATION STRATEGIES
IN THE FOREST AND AGRICULTURE SECTORS
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF POLICY, PLANNING, AND EVALUATION
CLIMATE CHANGE DIVISION
WASHINGTON, D.C., U.S.A.
JUNE 1995
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ACKNOWLEDGEMENTS
This report is the result of an extensive collaborative effort by a number of organizations and
individuals. The work was sponsored and coordinated by the EPA Office of Policy, Planning,
and Evaluation (OPPE), in Washington, DC. Richard Morgenstern, Maryann Froehlich, Dennis
Tirpak, and Jane Leggett-Emil provided important guidance and support for the project.
Kenneth Andrasko, William Hohenstein, and Steven Winnett provided technical guidance,
coordination, and review throughout the project.
A number of individuals contributed to the design and coordination of the research,
including: Thomas Murphy, Peter Beedlow, and Robert Dixon at the EPA Environmental
Research Laboratory in Corvallis, OR; Rosemarie Russo, Lee Mulkey, and Tom Barnwell at
the EPA Environmental Research Laboratory in Athens, GA; Courtney Riordan at the EPA
Office of Research and Development; Andy Manale at the Water and Agricultural Policy
Division of OPPE; Thomas Hamilton, Fred Kaiser, William Sommers and David Darr at the
USDA Forest Service Research Office; Richard Haynes, John Mills, Judy Mikowski, and Del
Thompson at the USDA Forest Service Pacific Northwest Research Station; Peter Ince and
Ken Skog at the USDA Forest Service Forest Products Laboratory, Madison, Wl; Carol
Whitman and Gary Evans at the USDA Global Change Office; and Kate Heaton at the Bruce
Company.
Studies for this analysis were conducted by: David Turner, Jeffrey Lee, Greg Koerper, and
Jerry Barker at the EPA Environmental Research Laboratory in Corvallis, OR; Richard
Haynes, Ralph Alig, and Eric Moore at the USDA Forest Service Pacific Northwest Research
Station in Portland, OR; Richard Birdsey and Linda Heath at the USDA Forest Service in
Washington DC; John Perez-Garcia at the Center for International Trade in Forest Products,
University of Washington, Seattle, WA; Aziz Bouzaher, Derald Holtkamp, Randall Reese, and
Jason Shogren at the Center for Agricultural and Rural Development, Iowa State University,
Ames, IA; Anthony Donigian, Avinash Patwardhan, and Radha Chinnaswamy at AQUA
TERRA Consultants, Mountain View, CA; Tom Barnwell and Robert Jackson at the EPA
Environmental Research Laboratory in Athens, GA; Kevin Weinrich and Allen Rowell at
Computer Sciences Corporation, Athens, GA; Vern Cole at the Natural Resources Ecology
Laboratory, Fort Collins, CO; Bruce McCarl at Texas A&M University, College Station, TX;
John (Mac) Callaway at RCG/Hagler Bailly, Boulder, CO; and Alice Cialella and Changsheng
Li at the Bruce Company, Washington, DC.
Assistance in preparing this report synthesizing the study results was provided by Frances
Sussman, David Reiner, Jeff Fiedler, Doug Keinath, Susan Barvenik, and Roger Schwabacher
at ICF Incorporated, Washington, DC.
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TABLE OF CONTENTS
Executive Summary ES-1
1. Introduction "I
2. Background: The Carbon Cycle, Historic Land Use Change, and Mitigation
Strategies 3
2.1 The Global Carbon Cycle and Carbon Sector Budgets 4
2.2 Historic Land Use Change: U.S. Forests 6
2.3 Historic Land Use Change: Agriculture 8
2.4 Overview of Scenarios 8
3. Methodology 8
3.1 Forest Sector Models 12
3.2 Agriculture Sector Models 13
4. Tree Planting Scenarios 15
4.1 Tree Planting on Marginal Cropland and Pastureland 16
4.2 Conservation Reserve and Wetlands Reserve Programs 23
4.3 The Agriculture Sector: Implications for Federally Funded Tree Planting 29
5. Other Forest Policy Scenarios 35
5.1 Increased Rates of Recycled Paper Utilization 35
5.2 Reduced National Forest Harvests 38
5.3 Increased Use of Biomass Energy 41
5.4 Effectiveness of Combined Scenarios 46
6. Modified Agricultural Practices 51
6.1 Modified Tillage Practices 52
6.2 Winter Cover Crops 58
7. Conclusions: Directions for Future Research 60
References
61
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LIST OF FIGURES
2. Background: The Carbon Cycle, Historic Land Use Change, and Mitigation Strategies
Figure 2-1 The Global Carbon Cycle , 4
Figure 2-2 The Forest Sector Carbon Budget 5
Figure 2-3 Carbon Storage on U.S. Timberland, by Region 7
3. Methodology
Figure 3-1 Forest Sector Models 11
Figure 3-2 Agriculture Sector Models 11
4. Tree Planting Scenarios
Figure 4-1 Carbon Storage in U.S. Forest Ecosystems by Forest Ecosystem Component 15
Figure 4-2 Geographical Regions Corresponding to Enrollment Scenarios 18
Figure 4-3 Total Carbon Storage on U.S. Public and Private Timberland: Range of Model
Results for Base Case Scenario 19
Figure 4-4 Total Carbon Storage on U.S. Public and Private Timberland: Increases
Relative to Base Case for Tree Planting Scenarios 20
Figure 4-5 U.S. Softwood Inventory Projections for Privately Owned Timberland: Base
Case and Tree Planting Scenarios 22
Figure 4-6 Annual Acreage Under CRP Scenarios 25
Figure 4-7 Composition of Reserve Scenarios 26
Figure 4-8 Carbon Storage Under Reseive Program Scenarios: Increases Relative
to Base Case 27
Figure 4-9 Impacts on Agriculture for CRP and WRP Scenarios, Change from Base Case 30
Figure 4-10 Average Annual Net Carbon Accumulation: Tree Planting On Three Land Types 32
5.
Other Forest Policy Scenarios
Figure 5-1 Total Carbon Storage on U.S. Public and Private Timberland: Increases
Relative to Base Case for the Increased Recycling Scenario
Figure 5-2 U.S. Softwood and Hardwood Inventory Projections for Privately Owned
Timberland: Base Case and Increased Recycling Scenario
36
38
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Figure 5-3 U.S. Private Timber Inventory: Changes Relative to Base Case for National
Forest Harvest Scenario 41
Figure 5-4 Projected Global Production Increases in Response to Habitat Preservation,
by Region: 1995 42
Figure 5-5 Total Carbon Storage on U.S. Public and Private Timberland: Changes
Relative to Base Case for Increasing Biomass Energy Scenario 44
Figure 5-6 U.S. Private Timber Inventory: Changes Relative to Base Case for Increasing
Biomass Energy Scenario 45
Figure 5-7 Total Carbon Storage on U.S. Public and Private Timberland: Changes Relative
to Base Case for Combined Scenarios 48
Figure 5-8 U.S. Private Softwood Timber Inventory: Changes Relative to Base Case
for Combined Scenarios 49
Figure 5-9 U.S. Private Hardwood Timber Inventory: Changes Relative to Base Case
for Combined Scenarios 49
6. Modified Agricultural Practices
Figure 6-1 RAMS Study Region 53
Figure 6-2 Tillage Distributions for Alternative Scenarios 54
Figure 6-3 Major Rotations: Base Case and Targeted Levels of Winter Cover Crops 58
in
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LIST OF TABLES
Executive Summary
Table ES-1 Annual Carbon Accumulation for the Forest and Agriculture Sector Scenarios,
Decadal Intervals
ES-5
4. Tree Planting Scenarios
Table 4-1 Average Storage of Carbon in Forest Ecosystems by U.S. Region 16
Table 4-2 Regional Distribution of New Forest Under Alternative Enrollment Schedules . . . 18
Table 4-3 Annual Carbon Accumulation on U.S. Public and Private Timberland Relative
to Base Case for Three Tree Planting Scenarios, Decadal Intervals 21
Table 4-4 U.S. Softwood Harvests for Tree Planting Scenarios: All Owners 22
Table 4-5 Stumpage Prices in the Base Case .23
Table 4-6 Stumpage Prices in the Tree Planting Scenarios 24
Table 4-7 Annual Carbon Accumulation for CRP and WRP Scenarios Relative to Base Case,
Decadal Intervals 27
Table 4-8 Impacts of Reserve Program Scenarios on Agricultural Production and Producer
Prices: Percent Change Relative to Base Case, Decadal Intervals 28
Table 4-9 Impacts of Tree Planting on Different Land Bases 32
Table 4-10 Impacts of Tree Planting on Cropland with Varying Enrollment Strategies 33
Table 4-11 Economic Welfare Effects of Federal Subsidies for Tree Planting on Cropland 34
Table 4-12 Price Effects of Federal Subsidies for Tree Planting on Cropland:
Fisher Price Indices 34
5.
Other Forest Policy Scenarios
Table 5-1 Annual Carbon Accumulation on U.S. Public and Private Timberland Relative
to Base Case for Increased Recycling Scenario, Decadal Intervals 37
Table 5-2 Changes in Harvest Levels for the Increased Recycling Scenario,
Relative to the Base Case 37
Table 5-3 Stumpage Prices in the Increased Recycling Scenario 39
Table 5-4 National Forest Harvest Under Base Case and Reduced National Forest
Harvest Scenario 39
Table 5-5 Base Case Harvest Projections by Region: Public and Private Timberland Owners 40
iv
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Table 5-6 Stumpage Prices in the Reduced National Forest Harvest Scenario 42
Table 5-7 Biomass Fuelwood Consumption: Assumptions for Base Case and Biofuel Scenario,
Decadal Intervals 43
Table 5-8 Annual Carbon Accumulation on U.S. Public and Private Timberland Relative
to Base Case for Increased Use of Biomass Energy, Decadal Intervals 46
Table 5-9 Stumpage Prices in the Increased Biomass Energy Scenario 46
Table 5-10 Combination Scenarios 47
Table 5-11 Annual Carbon Accumulation on U.S. Public and Private Timberland Relative
to Base Case for Combined Scenarios, Decadal Intervals 50
Table 5-12 Stumpage Prices in the Combination Scenarios 51
6. Modified Agricultural Practices
Table 6-1 Soil Organic Carbon Accumulation for the Conservation Tillage Scenarios
in the RAMS Study Region 54
Table 6-2 Impact of Short Term Yield Assumptions on the Introduction of Conservation Tillage ... 56
Table 6-3 Impact of Short Term Yield Assumptions on Major Crop Rotations 56
Table 6-4 Regional Variation in Soil Carbon Accumulation 57
Table 6-5 Soil Organic Carbon Accumulation for the Winter Cover Crop Scenario 59
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LIST OF BOXES
1. Introduction
Box 1-1 Actions to Mitigate Climate Change 1
Box 1 -2 Studies Conducted for this Assessment 3
2. Background: The Carbon Cycle, Historic Land Use Change, and Mitigation Strategies
Box 2-1 Definition of Timberland and Woodland 6
Box 2-2 Summary of Scenarios 9
3. Methodology
Box 3-1 Summary of Key Models Used for this Assessment 10
Box 3-2 Estimating Forest Carbon: FCM and FORCARB 13
4. Tree Planting Scenarios
Box 4-1 Investment Behavior in TAMM/ATLAS 17
5. Other Forest Policy Scenarios
Box 5-1 Paper Recycling in the U.S 35
6. Modified Agricultural Practices
Box 6-1 The Effects of Crop Rotation, Tillage Practice, and Climate on Soil Carbon
for Two Neighboring Climate Divisions 55
VI
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EXECUTIVE SUMMARY
Human activities, particularly the use of fossil
fuels for energy, increase atmospheric levels of
greenhouse gases, which may induce changes
in the earth's climate over the coming
decades. While there remains considerable
uncertainty about the rate and magnitude of
possible climatic changes, the Intergovern-
mental Panel on Climate Change, under the
auspices of the World Meteorological
Organization and the United Nations
Environmental Program, estimates that rising
concentrations of greenhouse gases are likely
to increase global temperatures by between
1.5°C and 4.5°C (2.7°F and 8.1°F) over the next
century (IPCC 1992).
Together with temperature rise, related climatic
changes, including rising sea level and altered
storm patterns, are likely to have adverse
impacts, such as loss of wetlands and coastal
property, changes in water supply, and
reductions in agricultural productivity in some
areas. The U.S. Government is examining
policies that may help reduce atmospheric
concentrations of greenhouse gases, the most
important of which is carbon dioxide (CO2).
Because vegetation and soil contain about
three times as much carbon as the
atmosphere, terrestrial ecosystems offer an
opportunity to absorb and store (sequester) a
significant additional amount of CO2 from the
atmosphere. One possible approach for
slowing the increase in greenhouse gases
concentrations in the atmosphere is to manage
terrestrial ecosystems to conserve or sequester
additional carbon.
Forest ecosystems represent an important
opportunity for conserving and sequestering
carbon because of their large accumulations of
woody biomass. Creating new forests or
restoring degraded ones can significantly
increase carbon sequestration. Similarly,
agricultural systems, which cover vast
acreages, can be managed on a yearly basis
to augment the large store of carbon in their
soils.
The Office of Policy, Planning, and Evaluation
at the U.S. Environmental Protection Agency, in
collaboration with the U.S. Forest Service, is
conducting an assessment of land use
management policies that can contribute to
stabilizing U.S. greenhouse gas emissions.
This assessment analyzes potential
greenhouse gas, economic, and other impacts
of land use management policies. The
assessment uses a number of different sectoral
models, which have been, where feasible,
linked to provide a comprehensive evaluation
of the forest and agricultural sectors. Scenarios
that represent the implementation of a number
of policies are being analyzed using the
assembled models. While much of this work is
still ongoing, this study presents preliminary
results of the following scenario analyses:
Tree Planting on Marginal Crop and
Pasture Land
Conservation Reserve and Wetlands
Reserve Programs
Increased Use of Recycled Paper
Reduced Harvest on National Forest Land
Increased Use of Biomass Energy
Modified Agricultural Tillage Practices
Increased Use of Winter Cover Crops
TREE PLANTING ON MARGINAL CROP AND PASTURE
LAND
Forestation policies that plant trees on
marginal crop and pasture land increase the
acreage devoted to forests in the U.S. These
policies also increase the amount of carbon
stored in U.S. forests.
Carbon Impacts. A large-scale tree
planting program of 12 million acres,
costing $220 million annually for 10 years,
would sequester an additional 6.8 million
metric tons of carbon annually in 2000, and
16.7 million metric tons in 2010 (see Table
ES-1). This accumulation would increase
the size of the U.S. forest carbon pool by
between almost 500 and 800 million metric
tons of carbon by 2040, relative to the
baseline, with approximately one-fourth of
the total achieved by 2010.
Economic Impacts. Since planting trees
increases the wood available for harvest
when the timber reaches maturity, future
prices for timber are lower than in the
ES-1
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absence of the tree planting program.
Stumpage prices fall most in the South,
creating benefits for consumers and losses
for owners of timber. Lower prices for U.S.
timber result in a significant decrease in
imports of Canadian lumber by the year
2040.
Other Impacts. Tree planting on marginal
lands can reduce soil erosion, protect
watersheds, and conserve biodiversity.
CONSERVATION RESERVE AND WETLANDS RESERVE
PROGRAMS
One policy option using existing programs to
sequester carbon is to extend current and
planned contracts under the Conservation
Reserve Program (CRP), thereby preventing
the loss of forested land that would otherwise
revert to cropland. Other options would expand
both the CRP and the Wetlands Reserve
Program (WRP) with tree-planted areas.
Carbon Impacts:
Enrolling 40 million acres under the CRP
and maintaining this acreage would result
in an annual carbon accumulation of 11.6
million metric tons in 2000, and 7.9 million
metric tons in 2010. This would increase
the size of the U.S forest carbon pool by
almost 200 million metric tons in 2015 and
nearly 350 million metric tons by 2035,
compared to the likely reversion of CRP
lands after 1995.
Expanding the CRP to 50 million acres
by planting an additional 10 million acres
with trees would result in an annual carbon
accumulation of 31.5 million metric tons in
2000, and 15.9 million metric tons in 2010
(see Table ES-1), and would more than
double the incremental carbon stored
relative to the base case. The total carbon
pool on these lands would increase by
over 1,100 million metric tons by 2035.
Expanding the WRP to five million acres
would result in an annual carbon
accumulation of 2.2 million metric tons in
2000, and 4.4 million metric tons in 2010.
The forest carbon pool would increase by
almost 200 million metric tons by 2035.
Economic Impacts. Net economic returns
increase for crop producers, but decrease
significantly for livestock producers. The
net result of changes in income and in
government payments is a decline in
combined agriculture and livestock industry
returns of about $350 million to $450
million per year. Under the CRP scenarios,
consumers are generally worse off with
slightly lower consumption and higher retail
prices, resulting in about a 2 percent
increase in total consumer expenditures.
INCREASED USE OF RECYCLED PAPER
By decreasing the demand for harvested
wood, increased paper recycling has the
potential to increase standing biomass and,
thus, enlarge the forest carbon pool. In this
scenario, the utilization rate for recycled
wastepaper increases to 45% by 2000 and
remains constant through 2040.
Carbon Impacts. Increased use of
recycled paper would result in an annual
carbon accumulation of 13.5 million metric
tons in 2000, and 15.6 million metric tons
in 2010 (see Table ES-1). The forest
carbon pool would increase by an
additional 400 to 600 million metric tons by
2040, an amount comparable to that of
large scale tree planting programs.
Economic Impacts. Because additional
recycling reduces the demand for
pulpwood, stumpage prices and revenues
for producers decline over time under this
scenario. Declining revenues occur
predominantly in the softwood markets in
the South, which produce the bulk of the
paper pulp for markets that switch to
recycled fiber. Lower U.S. timber prices
reduce softwood lumber imports from
Canada, which drop roughly to 36 percent
below base case levels by 2040.
REDUCED HARVEST ON NATIONAL FOREST LAND
Harvest reductions in this scenario result from
eliminating harvest of old growth volumes in
the Pacific Northwest, protecting spotted owl
habitat in Washington, Oregon and California,
protecting the red cockaded woodpecker in
the South, eliminating below cost timber sales,
ES-2
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and eliminating harvesting in existing roadless
areas.
Carbon Impacts. Decreases in National
Forest harvest would be mostly offset by
increased harvests by other landowners, or
in other regions. Overall there is little
change in the total timber inventory and,
hence, in the total carbon stored on U.S.
timberland. Offsetting harvests in other
countries could, however, increase carbon
storage in U.S. forests over base case
levels. Carbon losses in those other
countries might be greater than the carbon
savings realized in the U.S.
Economic Impacts. Because timber
inventories are reduced, softwood lumber
prices increase, prompting a slight
decrease in consumption of 16% and an
increase in Canadian imports of 10% by
2040. Higher prices also increase the use
of more energy-intensive, non-wood
substitute products. Analysis of
international trade linkages suggests that
higher prices increase harvests in countries
other than the U.S. This result could lead
to economic surplus gains of $1.4 billion to
timber producers worldwide and a net
welfare loss of almost $100 million for U.S.
producers.
INCREASED USE OF BIOMASS ENERGY
Under this scenario, energy supplied by
fuelwood from existing forests increases from
3.1 Quads in 2000 to 5.4 Quads in 2030, to
meet levels of bioenergy supply contained in
the National Energy Strategy (NES).
Carbon Impacts. Increasing the production
of energy from biomass has three distinct
effects on CO2 emissions: (1) CO2 is
released when the wood is combusted to
produce energy; (2) carbon is sequestered
during the growth or regrowth of forests
harvested for biofuels; and (3) carbon
emissions are "avoided" when fossil fuel
combustion is displaced by bioenergy.
Removing wood for biofuels initially has the
effect of reducing the carbon inventory on
the forest base. Over time, however,
regrowth on harvested lands replaces the
biomass carbon. Increased use of biomass
energy results in an annual forest carbon
accumulation of -7.3 million metric tons in
2000, and -17.8 million metric tons in 2010
(see Table ES-1). The real benefit to the
atmosphere occurs as wood displaces
fossil fuels. Avoided fossil fuel emissions
are 2.6 million metric tons in 2000, and 7.5
million metric tons in 2010. Combined net
carbon impacts equal -4.7 million metric
tons in 2000, and -10.3 million metric tons
in 2010.
COMBINED FOREST POLICY SCENARIOS
Because policies can have offsetting economic
impacts, there are benefits to jointly
implementing forest sector policies. Combining
scenarios presents an opportunity to evaluate
the carbon, timber, and economic
consequences of a coordinated forest sector
strategy to sequester carbon. The combined
scenarios are:
Reduced Harvest and Increased
Wastepaper Recycling (Combination 1)
Combination 1 with Increased Production
of Energy from Biomass (Combination 2)
Combination 2 with Large-scale Tree
Planting (Combination 3)
The combined scenarios are projected to have
the following effects.
Carbon Impacts. The carbon impact of the
combination 1 scenario is similar to that of
the increased paper recycling scenario;
10.6 million metric tons of carbon are
accumulated annually in 2000 and 13.0
million metric tons are accumulated
annually in 2010. In addition:
Adding the biomass energy scenario
(combination 2) reduces carbon
significantly, even when avoided fossil fuel
emissions are taken into account. Net
annual carbon accumulation equals 6.8
million metric tons in 2000, and 3.7 million
metric tons in 2010.
Adding large-scale tree planting to this
scenario (combination 3) illustrates the
benefits of combining a bioenergy strategy
with plantations established to grow biofuel
stocks. Net annual carbon accumulation for
combination 3 rises to 12.7 million metric
ES-3
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tons in 2000 and 18.5 million metric tons in
2010.
Economic Impacts. Combining increased
recycling with reduced harvests on public
lands creates offsetting impacts on timber
prices. Stumpage prices for combination 1
are higher than for the recycled fiber
scenario and lower than the harvest
reduction scenario. Because of the strong
influence of additional recycling, prices are
lower than in the base case. In addition:
Adding a large biomass energy program
that draws on existing resources in the
forest sector increases prices over the first
scenario, creating economic gains for
stumpage suppliers in the combination 2
scenario.
Introducing large-scale tree planting
reduces prices, relative to combination 2.
Because combination 3 includes the
reduced harvest scenario and biomass
energy scenario, however, which draw
down the timber inventory, prices are
above those for the tree planting scenario
alone.
Thus, the presence of multiple activities in
the combined scenarios reduces the
adverse economic impacts of individual
scenarios.
MODIFIED AGRICULTURAL TILLAGE PRACTICES
It is estimated that agricultural soils store 1.5
trillion metric tons of carbon, or roughly twice
the amount of carbon in the atmosphere.
Under this scenario, tillage practices on highly
erodible lands were changed to reduced-till
and no-till practices in order to meet soil
conservation targets.
Carbon Impacts. Changing agricultural
practices, that continue the trend towards
conservation tillage, would result in
average annual soil organic carbon
accumulations of up to 2.5 million metric
tons above base case levels (see table
ES-1). Estimated soil carbon accumulation
rates are very sensitive to projected crop
yields. Soil carbon impacts on individual
areas of the U.S. can differ significantly
from national averages due to variation in
dominant crop rotations, other production
practices, climate, and soil conditions.
Economic Impacts. Economic impacts
depend primarily on assumptions about
short term crop yield decreases due to
unfamiliarity with the new tillage practices.
Without yield adjustments, net returns
(gross revenues less variable costs) under
the low conservation scenario increase by
$0.67 per acre, or 0.8 percent. Net returns
under the more aggressive high
conservation scenario increase by $4.06
per acre, or 5.4 percent. With yield
adjustments for implementing conservation
tillage practices, net returns decrease by
$3.02 per acre or (3.4 percent) for the low
conservation scenario, and decrease by
$2.93 per acre or (3.3 percent) for the high
conservation scenario.
Other Impacts. As an additional benefit,
soil erosion decreases by 20 to 30 percent
with increased use conservation tillage
practices.
INCREASED USE OF WINTER COVER CROPS
This scenario introduces winter cover crops to
areas with favorable conditions (areas with
proper climate, crop rotations, and length of
growing season), thereby increasing total
biomass production and associated soil
carbon accumulation on agricultural lands over
the course of the year.
Carbon Impacts. Although lands targeted
for winter cover crops account for only 5 to
10 percent of the total land area in the
study region, there are significant
increases in the level of soil organic
carbon. Increased planting of winter cover
crops results in an average annual soil
organic carbon accumulations of up to 3.5
million metric tons above base case levels
(see Table ES-1).
Economic Impacts. Average net economic
returns to farms decreased by slightly over
1 percent as a result of these cover crop
policies.
Other Impacts. Some cover crops, such as
hairy vetch, have the additional benefit of
fixing nitrogen in the soil.
ES-4
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Table ES-1
Annual Carbon Accumulation for the Forest and Agriculture Sector Scenarios,
Decadal Intervals (million metric tons)
Tree Planting on Marginal Crop and
12 million acres,
optimal distribution
6 million acres,
optimal distribution
4 million acres,
historic distribution
Conservation and Wetlands Reserve
40 million acres in CRP
50 million acres in CRP
5 million acres of Wetlands Forest
Increased Use of Recycled Paper
Increased Energy from Biomass
Forest Carbon
Avoided Fossil
Fuel Emissions
Net Carbon Flux
Combined Forest Policy Scenarios
Combination 1:
NF harvest reduction and recycling
Combination 2:
Combination 1 and biomass energy
Forest Carbon
Avoided Fossil
Fuel Emissions
Net Carbon Flux
Combination 3:
Combination 2 and tree planting
Forest Carbon
Avoided Fossil
Fuel Emissions
Net Carbon Flux
Modified Tillage Practices
Winter Cover Crops
2000
Pasture Land
6.8
4.1
3.5
Programs
11.6
31.5
2.2
13.5
-7.3
2.6
-4.7
10.6
4.2
2.6
6.8
10.1
2.6
12.7
2.5
3.5
2010
16.7
9.6
6.5
7.9
15.9
4.4
15.6
-77.8
7.5
-10.3
13.0
-3.8
7.5
3.7
11.0
7.5
18.5
2.5
3.5
2020
19.4
10.8
7.5
7.7
34.5
7.0
10.0
-29.6
73.2
-16.4
8.8
-23.8
73.2
-10.6
-6.6
73.2
6.6
2.5
3.5
2030
13.0
6.2
5.5
7.2
31.6
4.6
4.4
-27.7
27.5
6.4
3.7
-24.2
27.5
3.3
-72.7
27.5
14.8
2.5
3.5
ES-5
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1. INTRODUCTION
Rising atmospheric levels of greenhouse gases, which are the result of anthropogenic sources of
emissions, are likely to induce changes in the earth's climate over the coming decades. Greenhouse
gas-induced climate change, which is projected to result in rising global averagejemperatures and
rising sea levels, may have associated impacts on energy demand, water resource quality, coastal
property and ecosystems, and the commercial forestry and agriculture sectors. There remains
considerable uncertainty about the rate and magnitude of possible climate change, as well as about
the physical impacts associated with such change. There is, however, an emerging consensus that
policies to stabilize or reduce emissions of greenhouse gases which include carbon dioxide (CO2)
and other radiatively important trace gases, such as methane (CH^, nitrous oxide (N2O),
hydrofluorocarbons (HFCs), and perfluorocarbons (PFCs) should be explored (see Box 1-1).
The vegetation and soil in terrestrial
ecosystems contain about three times as much
carbon as is in the atmosphere, and play a
major role in the movement of CO2 and other
greenhouse gases into and out of the
atmosphere. For example, carbon may be
released to the atmosphere as CO2 or CH4
when trees or other vegetation are harvested or
decay, or when soils are tilled. Thus, increasing
the amount of standing biomass, or changing
cultivation practices, can increase the size of the
carbon sink and decrease concentrations of
greenhouse gases in the atmosphere. One
proposed approach, therefore, for slowing the
increase in atmospheric CO2 is to manage
terrestrial ecosystems to conserve or sequester
(remove and store) carbon.
Forest ecosystems present particularly
significant opportunities for carbon conservation
and sequestration because of their large accu-
mulations of woody biomass. In 1990, U.S.
forests recaptured approximately 9 percent of
the CO2 emitted in the U.S. from the combustion
of fossil fuels (USEPA 1994). Strategies in the
forest and agriculture sectors have the technical
potential to recapture a significantly greater
portion of U.S. CO2 emissions in the future.
The Office of Policy, Planning, and
Evaluation at the U.S. Environmental Protection
Agency, in collaboration with the U.S. Forest
Service, is conducting an assessment of land
use management policies that can contribute to
stabilizing U.S. greenhouse gas emissions. A
broad set of policies in the agriculture and forest
sectors that could potentially increase the
capacity of terrestrial carbon storage include:
£ox 1-1
Actions to Mitigate Climate Change
tn 1992, the United Nations conference on
Environment and Development (UNCED) formu-
lated the Framework Convention on Climate
Change, which has since been signed by the U.S.
and at least 160 other countries. On Earth Day
1993, President Clinton announced that the U,&
woufd participate Tn climate change mitigation
efforts and, in October 1993, released the U,&
Climate Change Action Plan (CGAP), which has as
Its goaf returning U,S. emissions of greenhouse
gases to 1990 levels by the year 2000.
Emissions of greenhouse gases are generally
measured in million metric tons of carbon
equivalent (MMTCE)* MMTCE provides a
consistent measure to compare emissions of
different greenhouse gases that accounts for the
relative global warming input of each gas. In 1990,
U,S, net greenhouse gas emissions equalled 1,444
MMTCE, Of this total, 1,233 MMTGE (85 percent)
were net carbon released as C02 emissions, 162
MMTGE (11 percent) were methane (CHA 30
MMTCE (2 percent) were N2O, and 19 MMTCE
(1 percent) were HFCs or PFCs,
tn the absence of the CCAP, the
Administration projects that net greenhouse gas
emissions would grow to 1,568 MMTCE by 2090,
Under the CCAP, which Includes measures to
reduce various sources of emissions as well as
increase carbon sequestration by forests, the
Administration estimates net greenhouse gas
emissions of 1,459 MMTCE* This estimate reflects
reductions by the year 2000 of 109 MMTCE, or 7
percent of estimated emissions tn the year 20DO,
Sources: USEPA 1994; USDOS 1994
enlarging the acreage of trees by
encouraging rural and urban tree planting and adopting long term fire management strategies;
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increasing the rate of tree growth on existing forest land by improving timber management
practices or using improved seedling stock;
using biomass-based fuels, which reduce carbon emissions from fossil fuels, and do not
themselves have a net impact on long-term atmospheric carbon;
increasing utilization rates for recycled paper, thereby reducing demand for pulpwood and
maintaining and increasing timber inventories;
conserving standing primary and old-growth forests as stocks of biomass by restricting harvesting
or setting aside land;
reducing soil disturbances by modifying tillage practices and thereby increasing soil organic
carbon; and
planting winter cover crops to increase biomass on agricultural lands.
This document summarizes the results of a number of studies conducted over the last three years
to examine forestry and agricultural policies, including many of those described above, and their
implications for carbon storage and emissions of greenhouse gases (see Box 1-2). Understanding not
only the greenhouse gas implications but also the socioeconomic effects of these policies requires
answering a series of key questions:
To what extent can the policy or program sequester or offset greenhouse gas emissions?
How much will the policy or program cost the government?
What are the economic and social impacts on the forest and agriculture sectors nationally and
regionally?
How effective are the policies or programs when combined?
What are the impacts of these domestic policies on global trade, and of global trade on these
policies?
The results of the studies reported in this document build on a body of literature, both scientific
and policy-analytic. Past analyses of the potential impacts of domestic forest and agriculture
management practices have concentrated on one or two of a multitude of factors an individual
policy, effects on soil carbon, or program cost. This study evaluates the full range of economic
implications and quantifies the likely physical effects for a variety of potential strategies. Together with
the past literature, the studies reported here represent an initial step towards building the volume of
information necessary to comprehensively assess viable policy options in the forest and agriculture
sectors for reducing/offsetting greenhouse gas emissions.
This study has assembled a set of models which, collectively, evaluate the impacts of various
forest and agriculture sector strategies designed to reduce or sequester carbon emissions. Following
a brief description (in Section 2) of carbon processes, land use change, and the scenarios examined,
Section 3 presents the models used in the study. Sections 4, 5, and 6 present the results of the
scenario analyses. Section 7 concludes with a brief discussion of research directions.
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Box 1*2
Studies Conducted for this Assessment
The Forest Sector Carbon Budget of the United States: Carbon Pools and Flux Under Alternative
Policy Option*. May 199& Edited by D>P. Tomer, J*J, Lee, G.4> Koerper, and J>R Barker, US. EPA
Environmental Research Laboratory at CorvalliS, Oregon. EPA report EPA/600/3-93/093. Supplemented by
additional scenario analyses.
Alternative Simulations M, Perest-Garcia, Center for
International Trade in Forest Products at the University of Washington."
Economic and Resource Impacts of PoUcles to Increase Organic Carbon tn Agricultural Soils. May
1993, Report prepared by A Bouzaher, OJ, Holtfcamp, ft. Reese, and J. Shogren, Center for Agricultural and
Rural Development at lowa Slate University,
Long Term Economic Consequences of Alternative Carbon Reducing Conservation and Wetlands
Reserve Programs: A BLS Analysis. May 1993. Report prepared by R. Reese, A. Bouzaher, and J.
Shogren, Center for Agricultural and Rural Development af Iowa State; University,
Assessment oitAjterjtatlva Management Practices and Policies Affecting Soft Carbon In
Agroecosystems of the Central United States. April 1994. Report prepared by AS. Oonigian, A.S.
Patwardhan, and R. Chinnaswamy, AQUA TERRA Consultants; T.O, Bacnwelt, Jr. and R.B, Jackson, IV, O:S.
EPA Environmental Research. Laboraiory at Athens, Georgia; K.B, Wejnrich and A,L, Rowett, computer
Sciences Corporation; and C.V. Cole, Natural Resources Ecology Laboratory. EPA/60G/R-94/067.
Planting Trees on Agricultural Lands; The Costs and Economic Impacts of GRP Reversion. December
' 14, 1994, Report prepared by JM Catlaway, RCG/Hagler Batlty and 6.F, McCar), Texas A&M University,
Carbon Sequestrat/on and N20 Emissions from Soils: A Model Simulation Study for Seven Agricultural
Sites In the Central V.S, Ustoff the DNDC model. October 7,1993> Draft report prepared by C< Li and A.
Cialella, The Bruce Company.
2. BACKGROUND: THE CARBON CYCLE, HISTORIC LAND USE CHANGE, AND
MITIGATION STRATEGIES
Rising levels of atmospheric CO2 may increase global temperatures through the "greenhouse"
effect, which in turn may raise sea level and have serious domestic and international implications for
human health, ecosystems, productive resources, and coastal areas. The atmospheric concentration
of CO2 has risen from approximately 275 parts-per-million (ppm) in pre-industrial times to 350 ppm
today, and is currently increasing at a rate of approximately 1.5 ppm per year. Projections suggest
that the global average temperature will warm by 1.5 °C to 4.5 °C (2.7 °F to 8.1 °F) by the first half of
the next century (IPCC 1992).
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The potential consequences of increasing atmospheric carbon levels are serious enough that
governments are considering programs to stabilize or reduce anthropogenic emissions. Increasing
forest carbon sequestration can play an important role in these efforts. To develop effective policy
options, an understanding of the global carbon cycle, and how anthropogenic carbon emissions may
affect it, is necessary. This section presents background information on the role of terrestrial
ecosystems in the global carbon cycle, describes how historic land-use changes have determined the
current status of U.S. forests, and presents the policy scenarios that are evaluated in this report.
2.1 THE GLOBAL CARBON CYCLE AND CARBON SECTOR BUDGETS
The global carbon cycle is the movement of carbon among the atmosphere, terrestrial biosphere,
and ocean. Current estimates suggest that the oceans store by far the largest amount of carbon
roughly 40,000 billion metric tons of carbon (see Figure 2-1). Soil is the next largest reservoir, or pool,
followed by the vegetation and the atmospheric carbon reservoirs, which are about equal in
magnitude. Although the terrestrial biosphere (vegetation and soils) stores much less carbon than do
the oceans, the amount of carbon that cycles annually between the terrestrial biosphere and the
atmosphere is similar to that which cycles between the oceans and the atmosphere. Together, the
combined annual flux between these two pools and the atmosphere is about 20 percent of the total
atmospheric carbon pool.
Figure 2-1. The Global Carbon Cycle
Atmosphere
750 Pg
* 3 Pg per year
92 Pg
Biological
and
Chemical Processes
60 Pg
Respiration,
Decomposition
Chemical Processes
Sources: IPCC 1994; IPCC 1992; Schneider 1989
From the perspective of possible global climate change, the concern is that more carbon, primarily
in the form of CO2, is accumulating in the atmosphere than is being removed through plant
photosynthesis and other biological processes. It is estimated that the atmosphere is gaining about 3
billion metric tons of carbon annually. The two principal sources of atmospheric CO2 increases are
fossil fuel combustion and deforestation, which contribute 5.5 billion and 1.1 billion metric tons of
carbon, respectively, worldwide. Further, trends suggest that rates of anthropogenic emissions of CO2
from these two sources are rising. Terrestrial vegetation is an important component of the carbon
-------
cycle, and policies designed to enhance its capacity as a carbon pool, or reduce its emissions of
greenhouse gases, can potentially have a significant impact on atmospheric levels of CO2.
FOREST SECTOR CARBON BUDGET*
A carbon budget is a bookkeeping system for tracking the amount of carbon in various reservoirs
("pools") and the amount of carbon transferred among the reservoirs and the atmosphere ("fluxes").
The forest sector carbon budget has three major pools: the organic matter of forest ecosystems, the
products derived from forests, and products that are landfilled, incinerated, or otherwise discarded
(see Figure 2-2). The main uptake of carbon into forests is through photosynthesis, the fixation of
atmospheric CO2 by green plants. Carbon loss from forests occurs primarily from burning and from
the harvest of wood by humans. The net flux of carbon from the atmosphere to the forest is the
difference between carbon uptake from photosynthesis and carbon release from respiration by all
forest organisms, including decomposers. The "net accumulation" of carbon by forest ecosystems is
the net flux minus carbon removed by harvest and burning. Detailed forest sector inventories
developed periodically by the U.S. Forest Service provide an accurate basis for estimating forest
carbon storage. The analyses conducted for this report model the impacts of various policies on forest
inventories over time and estimate the associated changes in carbon storage.
Figure 2-2. The Forest Sector Carbon Budget
CO2
CO2
{Photosynthesis * Burning,
1 Decomposition
Forest
Ecosystem
Harvest
CO2
# Incineration
Products
{Respiration. I
Burning V
COj
Landfills
Decomposition
Source: Turner, etal. 1993
Unlike the forests, there are no systematic inventories of the product and disposal pools, or of the
net annual transfer of material into or out of these pools. Some products, such as furniture and lumber
for housing, are a relatively long-lived store for carbon. Once these and other products, such as
newspaper and paper packaging, enter disposal pools, much of the material decays and the carbon is
emitted to the atmosphere in the form of greenhouse gases. The length of time over which material
decays depends on the type of material and on factors specific to the landfill. In some cases, a
portion of the carbon may effectively be permanently stored in the landfill. Transfers of harvested
1
This section is based primarily on Turner, et al. 1993.
5
-------
forest biomass into product and disposal pools can, therefore, have a significant impact on the timing
and magnitude of carbon accumulation in the entire forest sector.
AGRICULTURE
Vegetation and soil in the agricultural sector also store carbon. Soil organic matter, in the form of
live crops in the ground, crop residues, and other dead and decaying plant material and soil micro-
fauna, account for the carbon found in agricultural soils. Soil carbon accumulation is determined by
the balance of biomass inputs from primary production (e.g., crop residue) and carbon loss from
decomposition and erosion (Donigian, et al. 1994). Thus, agricultural management practices such as
crop selection, crop residue treatment (e.g., burning, removal), and tillage, have a large impact on soil
carbon accumulation. For example, tilling soil during the planting season disturbs some of the soil
organic matter and promotes decomposition, releasing CO2 into the atmosphere. Management
practices that increase production, such as introducing winter cover crops into an annual crop
rotation, can also increase soil carbon accumulation.
2.2 HISTORIC LAND USE CHANGE: U.S. FORESTS*
The history of the conversion of original
forest to its current state is important for a
complete understanding of trends and modelling
projections of carbon flux and storage. In 1630,
the continental U.S. had about 822 million acres
of forest land, characterized by a high
proportion of very large trees and in
approximate equilibrium with respect to growth
and mortality. With the exception of pockets in
the western U.S., most of the pre-settlement
forest has now been cleared and developed, or
replaced with agricultural land or successional
forest. Productive forest land (see Box 2-1) is
estimated at 537 million acres, with another 200
million acres of urban and marginal forest land
(now called other forest) (Haynes, et al. 1994). A
division of the continental U.S. into three regions
North, South, and West broadly captures
differences in the use and management of the
pre-settlement forest lands. Current and historic
carbon storage on these lands reflects the
different land use patterns in each region (see
Figure 2-3) .3
NORTHERN REGION
By the end of the 19th century, virtually all
northern forests had been cleared for
agricultural use or heavily logged for timber
products, with the exception of extreme northern
Box 2-1
Definition of Timberland and Woodland
Forest land in the US. Is differentiated between
timberland> reserved timbertancif and other forest.
Timberland is forest (and that is producing at is
capable of producing crops of Industrial wood and
that is not withdrawn from timber utilization by
statute or administrative regulation. (Mote; areas
Qualifying as tlmberland are capable of producing
in excess of 20 cubic feet per acre per year of
Industrial wood in natural stands. Currently
inaccessible and inoperable areas are included.}
Reserved timberiand refers to land having the
productive capacity of timberiand but which Is
withdrawn from timber utilization by statute or
administrative regulation,
Other forest land f woodland") includes fofeSt land
other than timberiand ana reserved timberiand* if
includes available and reserved unproductive forest
land, which Is incapable of producing 20 cubic feet
per acre per year of industrial wood under natural
conditions because of adverse site conditions such
as sterile soils> dry climate, poor drainage, high
elevation, steepness, OF cockiness.
Source: Turner, etaL 1993
This section is based primarily on Birdsey and Heath 1993.
3 In terms of the regions identified subsequently in Figure 4-2, the West is composed of the Pacific Northwest
and Southwest and the Rocky Mountains; the North combines the Northeast and the North Central; and the South
contains the Southeast and South Central.
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Figure 2-3. Carbon Storage on U.S. Timberland, by Region
40 -
35 -
J 30 -
o
° 25 -
g
in
g 20 -
3| 15 -
c
_o
S 10 -
5 -
0
195
f * *
f -
~
-
O 1960 1970 1980
f Total U.S. _--.- ""
-North
r South
I
West
t 1 1 1 r
1990 2000 2010 2020 2030 2040
Year
Historic-
-Projected-
Source: Birdsey and Heath 1993
areas of Maine and the Great Lakes States and some inaccessible areas in the Appalachian
mountains. Beginning in the mid-nineteenth century and accelerating in the 20th century, marginal
agricultural land reverted to forest and produced a dense stocking of trees, with much of the area now
covered by trees in the 25 to 65 year age classes. These forest lands of mixed species are in the
middle of a period of rapid growth that can be sustained for several more decades before reaching a
period of declining growth. In the near future, therefore, forest biomass is expected to continue to
increase.
SOUTHERN REGION
As in the North, only scattered fragments of pre-settlement forest remain. The current forest has
been regenerated either naturally or artificially on marginal cropland, pasture, or cutover forest land,
and many areas are being cut for the third time and regenerated to a fourth timber stand. The
intensively managed southern forests have the youngest age class distribution in the U.S., with a large
proportion in the 25 to 45 year age classes. Because of intensive management and a continuing shift
of industrial timber supply to the South, most of these forests are not expected to reach biological
maturity before further harvest and regeneration. Forest biomass is expected to remain constant or
decline slightly over time.
WESTERN REGION
Although the West has not experienced the major land use shifts characteristic of other regions,
forest disturbance has dominated the landscape as the original forests have been logged and
converted to second-growth forests. The remaining old-growth in the West comprises less than 2
-------
percent of the pre-settlement forest. Both private and public western forests have a relatively flat age-
class distribution, but with a large component of older forest classes. It is expected that western public
forest lands will be increasingly reserved from timber cutting, producing a long-term net gain in forest
biomass on public lands. As harvesting shifts from public to private lands, forest biomass on private
lands will correspondingly decline.
2.3 HISTORIC LAND USE CHANGE: AGRICULTURE
The extensive conversion of land to agriculture, which began just after the turn of the century,
resulted in substantial decreases in soil organic carbon relative to native ecosystems. Traditional
agricultural practices involved increased disturbance of soil, reduced plant cover during fallow periods,
and the removal or burning of crop residues, which minimized carbon inputs and promoted organic
matter decomposition (Donigian, et al. 1994). These practices led to an estimated 47% decrease in
soil organic carbon between 1907 and 1950. This release represents the second largest
anthropogenic source contributing to historical increases in CO2, after fossil fuel combustion (Post, et
al. 1990).
Following this period of decline, soil organic carbon remained fairly constant for the next two
decades as modern crop management practices were developed. These management practices have
decreased the level and intensity of tillage, and have increased the amount of crop residues that are
returned to the soil. Soil carbon models that reflect changes in agricultural practices indicate that soil
organic carbon levels have been steadily increasing since 1970, although this trend has yet to be
confirmed at a national or regional level (Donigian, et al. 1994).
2.4 OVERVIEW OF SCENARIOS
There are a number of trends in the forest and agriculture sectors, as well as potential new
programs, that could increase the next accumulation of carbon in forest and agricultural ecosystems.
The scenarios considered in this report, which are summarized in Box 2-2, represent a range of
plausible trends, new programs, or expanded existing programs. Three of these scenarios (large-scale
tree planting, and tree planting on conservation or wetlands reserve program lands) increase the
amount of carbon stored on U.S. forest land by increasing the acreage of standing trees.4 Two
additional scenarios expand the forest carbon pool by reducing harvesting on existing stands
(reduced National Forest harvest and increased wastepaper recycling). A sixth scenario increases the
use of wood for biofuels, and additional scenarios combine policies.
In the agriculture sector, modifying existing agricultural practices can increase soil organic carbon
levels. Employing tillage practices that do not disturb the soil as much as conventional tillage, and
planting winter cover crops, can in some cases increase carbon sequestration in agricultural soils, and
provide other benefits such as reduced erosion or increased nitrogen fixation.
3. METHODOLOGY
This report analyzes potential economic, greenhouse gas, and other impacts of land use
management policies. The assessment uses a number of different sectoral models, which have been|
where feasible, linked to provide a comprehensive evaluation of the forest and agricultural sectors (see
Box 3-1). The relationships among these models are illustrated in Figures 3-1 and 3-2.
The Conservation Reserve Program provides incentives to remove highly erodible land from agricultural
production by paying for conversion costs, and providing rental payments over 10 year contracts. The WRP
provides incentives to restore and protect wetlands that have been fully or partially converted to agricultural
production, by paying for conversion costs and compensating owners for the land value.
8
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, , -; BOX2-2
Summary of Scenarios
Increasing Forest Carbon Storage
Afforestation > Tree planting on marginal crop and pasture land Two alternative funding levefs for tree
planting programs are analyzed ($11D mlion and $220 rnlion annually lor to years, or about 6 to 12
million acres).
Conservation Reserve Program (CRP) Branding and maintaining the current CRP plans, thereby
Increasing fbrestland acreage above the current program. Two alternative proposals are analyzed {a 40
million acre CRP and a 50 million acre CRP}<
Wetland Reserve Program (WRP) introducing a 5 million acre reserve of wetlands targeted to re-
establish bottomland hardwood forest stands on suitable agricultural lands,
Increased Recycling The utilization rate for recycled paper increases to 45 percent of total fiber
production In tie year 2000 and remains constant through 204a
Reduced National forest Harvest Harvest on National Forests declines relative to the base case to
reflect additional reserved timberiand and set-astdes,
Wood Energy fj>/0f«efej Fuelwood consumption for bjofueis increases as described in the National
Energy Strategy.
Combination Scenario 1 Combines reduced National Forest harvest with recycling.
Combination Scenario 2 Combines reduced National Forest harvest, recycling,, and biofuels.
Combination Scenario 3 Combines reduced National Forest harvest, recycling, biofuels, with $220
million tn annual funding over 10 years for tree planting programs.
* *
Strategies in the Agriculture Sector
Modified Tillage Practices Increased use of Reduced'Till and No-Till practices on agricultural land,
Winter Cover Crofts Introduce winter cover crops where climate, crop rotations, and length of growing
season allow.
For the forest sector, changes in forest inventory on private timberlands are estimated by linking
an economic model (TAMM), which estimates tree harvest volume by region, to a forest inventory
model (ATLAS), which tracks forest age class distribution by forest type and productivity class. TAMM
ensures that the economic consequences of implementing the various policy options are allowed to
affect the carbon budget. The resulting forest inventory at any point in time is run through two
alternative carbon models (FCM and FORCARB), to estimate total forest carbon. The model
HARVCARB is used to estimate changes in the amount of carbon in forest products and in disposal
pools from material harvested from 1990 to 2040.
The basic forest sector analyses using TAMM/ATLAS and the carbon models are supplemented in
several ways. First, because tree planting on marginal crop and pasture land may affect prices and
production in the agriculture sector, additional results from two models of the U.S. agricultural sector,
ASM and BLS, provide insights into the potential impacts of tree planting policies. Second, because
the U.S. exports and imports raw timber and forest products, policies to expand the U.S. timber
inventory can affect world markets. The CINTRAFOR global trade model is used to evaluate these
-------
BOX 3-1
Summary of Key Models Used for this Assessment
Forest Sector Models
Tlmberland Assessment Market Model (TAMM) economic model of the U,S. forest sector, developed
by the U.S. Forest Service.
Aggregate Tlmhertand Atse&ment System (ATLAS) forest inventory change modal for private
timberland in the U.S,, developed1 by the U.S, Forest Service and finked to TAMM,
North American Put ft and Paper (NAPAP} mode/ sectoral moctel of demand, supply and
technology for the pulp and paper sector of U.S, and Canada, developed by the U.S. Forest
Service.
Forest Carbon Modet9 (FCM and FOHGARty models of the carbon contained in forest
ecosystems, developed &y the U.S, Environmental Protection Agency and the U.S. Forest Service,
respectively,
HARVCARB -~ model of post-harvest carbon, tracing the flows of carbon through processing, use,
and disposal, developed at the institute for Forest Analysis, Planning, and Policy.
CINTRAFOR Global Trade Model (G&THII) global forest sector model, developed by the
International Institute for Applied Systems Analysis (IIASA) and the University of Washington's Center
for International Trade fn Forest Products (CiNTRAPOR).
Agriculture Sector Models
Basic Unked Systems (BUS) model linking 34 national and regional models to simulate world
agricultural production and trade, developed by Iowa State University's Center for Agricultural and
Rural Development (CARD).
Resource Adjustment Modeling System (RAMS) model of regional agricultural production,
developed by Iowa State University's Center for Agricultural and Rural Development (CARD),
Denltrlflcatlon and Decomposition (DNDC) Model model of carbon and nitrogen dynamics In
agricultural soils, developed by the Bruce company and the university of New Hampshire,
CENTURY - modei of the dynamics of soil organic matter in agricultural lands and grasslands,
developed by Colorado State University in collaboration with Michigan State University.
Agriculture Sector Model (ASM) model of the U.S. agriculture sector, developed at the
Agricultural Economics Department of Texas A&M University.
impacts. Last, to analyze the impacts of increased waste paper recycling, the NAPAP model provides
detail on the North American pulp and paper sector.
To evaluate the economic and carbon impacts of change in agricultural practices, the analysis
combines models of agricultural production, agricultural markets, and physical processes (such as the
dynamics of carbon and nitrogen in soils). A detailed regional model (RAMS) of agricultural production
methods is used to evaluate the impacts on production of alternative crops, tillage practices, and
rotations. This regional production model is linked to two models (DNDC and CENTURY) of the
physical processes in agricultural soils to capture soil dynamics, fluctuations in the levels of soil
organic carbon, and changes in nitrous oxide emissions. Finally, the impacts of these policies on
10
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Figure 3-1. Forest Sector Models
Policy Triggers
CGTM
Global Economic
Trade Model
I
TAMM
Forest Sector
Economic Model
ATLAS
Forest Inventory
Model
I
FCM
FORCARB
Forest Carbon Models
Fuelwood
Model
NAPAP
Pulp & Paper
Sector Model
HARVCARB
Model of Post-
Harvest Carbon
Figure 3-2. Agriculture Sector Models
Policy Triggers
I
Land Use
Changes
ASM
Agriculture Sector
Economic Model
BLS
Agriculture Sector
Economic Model
FCM
Forest Carbon Model
RAMS
Agriculture Sector
Economic Model
1
CENTURY
Soil Carbon Model
DNDC
CENTURY Validation
11
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agricultural markets are evaluated using a general equilibrium model (BLS) which accounts for the
linkages between agricultural markets and the non-agricultural markets, regional and international
feedbacks related to trade, and impacts on different commodities, including the major cash crops and
livestock.
3.1 FOREST SECTOR MODELS
The Timber Assessment Market Model (TAMM) is a model of the U.S. forest sector developed by
the U.S. Forest Service, which provides an integrated structure for examining the behavior of regional
prices, consumption, and production in stumpage and product markets (Adams and Haynes 1980;
Haynes and Adams 1985). It is designed to provide long-term projections of price, consumption, and
production trends and to simulate the effects of alternative forest policies and programs. TAMM
includes six lumber and plywood demand regions and eight product and stumpage supply regions
within the contiguous U.S. Projections under TAMM are dependent on exogenous inputs from other
models: pulp fiber requirements (from the NAPAP model described below), and trade and fuelwood
projections. The background assumptions for any TAMM model run include projections of future forest
products markets (based on forecasts of the major determinants of product demand, and of timber
and product supply). On the demand side, the major determinants are future growth in aggregate
economic activity, as measured by gross national product (GNP), and in certain key end-uses for
forest products, such as new residential construction and the repair or alteration of existing dwellings.
It is important to note that TAMM does not account for changes in managerial behavior in response to
price signals and likely overestimates any adverse economic impacts due to tree planting or reduced
harvests (Winnett, et al. 1993). TAMM also does not account for forests that are managed for non-
commodity values.
The Aggregate TimberLand Assessment System (ATLAS) projects inventories for all private
timberland in the U.S. (Mills and Kincaid 1992). Developed by the U.S. Forest Service, ATLAS is an
age-based, yield table model that projects acres by detailed strata for time intervals consistent with the
inventory stand-age classes. In the model, the inventory is represented by acreage cells classified by
region, ownership, management type, management intensity, and age class. Inputs to the model
include estimates of harvest, acreage shifts, management alternatives, and growth parameters. A
major attribute of the model is that it can simulate shifts in management intensities and the
consequent changes in yields. It can also account for both partial harvests and thinning.
The North American Pulp and Paper (NAPAP) sector model uses linear programming to solve for
market equilibrium in spatially specific markets. NAPAP represents technological options as economic
choices via activity analysis, with production capacity modeled for many competing production
processes. The pulp and paper sector is modeled as eight demand regions for 14 categories of final
products and five supply regions, which together provide sufficient detail to capture market equilibria
for all principal commodities of the pulp and paper sector in North America (U.S. and Canada). The
model includes estimates of regional supply functions for manufacturing inputs; regional demand
functions for commodity outputs; technological coefficients describing production possibilities in terms
of inputs per unit of product output in various production processes for each commodity; other
manufacturing costs by process; transportation costs for various commodities and regions; regional
production capacities for the various processes; regional constraints on recovery of paper for
recycling; import and export ad valorem taxes; and monetary exchange rates (between U.S. and
Canada).
The CINTRAFOR Global Trade Model (CGTM) is a global forest sector model developed by the
International Institute for Applied Systems Analysis (NASA) and the University of Washington's Center
for International Trade in Forest Products (CINTRAFOR). CGTM provides forecasts of production,
consumption, prices, and trade for eight different forest product commodities, in 43 timber supply
regions and 33 demand regions (Perez-Garcia 1993, Cardellichio et al. 1989). Forecasts of market
behavior are subject to regional constraints including resource availability and production capacity.
12
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CGTM searches for a spatial (or global) equilibrium, which is the point where the amount supplied by
several log and commodity markets equals the amount demanded by all consumers.
The Forest Carbon Model (FCM), developed by the U.S. Environmental Protection Agency, is
used to generate estimates of forest carbon from the inventories generated by the TAMM/ATLAS
analyses (Turner, et al. 1993). The yield tables in ATLAS are used as the basis for constructing stand-
level carbon budgets. Carbon pool size per unit area per age class is estimated for living tree
biomass, woody debris, understory vegetation, forest floor, and soil components of the forest.
Separate stand-level carbon budgets are prepared for each of 422 yield tables supplied by the USDA
Forest Service. Carbon storage at the regional and national level is then determined by coupling these
stand-level carbon budgets to forest inventory data on the areal extent and stocking volume of each
age class within each inventory type. The set of stand-level carbon budgets provides the foundation
for the FCM (see Box 3-2).
A separate forest carbon model, FORCARB,
developed by the U.S. Forest Service, is
alternatively linked to TAMM/ATLAS for some of
the analyses (Birdsey 1992a, 1992b). Growing
stock inventories by age class and area are
derived from the ATLAS model and grouped into
248 "management units," defined by region,
owner, species, and site quality. The growing
stock inventories are treated as "snapshots" of
the forest at particular times and converted to
tree (living tree and standing dead trees), soil,
forest floor, and understory carbon. Removals of
growing stock for each management unit are
converted to estimates of harvested carbon.
The model HARVCARB is used to examine
the distribution and transfer of post-harvest
carbon quantities predicted by the
TAMM/ATLAS analyses of policy alternatives
(Row and Phelps 1990). The model traces the
flow of forest harvest carbon through five
phases of processing, use, and disposal: from
trees to roundwood logs; through processing
into forest products; into uses in construction,
manufacturing, and paper products; to
discarded products; and finally, to landfills,
incinerators, and back to the atmosphere.
HARVCARB reports emissions on both a carbon
(i.e., mass) basis and carbon-equivalent (i.e.,
climate impact) basis. The latter result, which
accounts for the generation and release of
methane from landfilled forest products, and the
greater climate impact of methane relative to
carbon dioxide, is used in this report.
HARVCARB was developed at the Institute for
Forest Analysis, Planning, and Policy.
3.2 AGRICULTURE SECTOR MODELS
Iowa State University's Center for Agricultural and Rural Development (CARD) has constructed the
Basic Linked System (BLS) of applied general equilibrium models to simulate the world agricultural
BOX 3-2
Estimating Forest Carbon; FCM and FORCARB
Both the FCM and FORCARB models use the
volume of merchantable wood (trees that are-farge
enough to contain salable products} as a basis 1or
calculating carbon \n the whole stand. Thus, neither
model calculates the existence of fciomass before
the stands are old enough to have trees at least B
inches in diameter in them* Consequently, the
models show no biomass {or carbon) In stands for
the ffrst 5 to 15 years after regeneration (depending
on stand type and region). As a result, biomass
and carbon are underestimated in the base case
and scenarios.
Although this limitation of the model affects the
calculation of faiomass and carbon in both the
base case and scenarios, the impacts are likely to
be important only for some scenarios. As forests
are managed1 overtime, stands are constantly
being harvested and regenerated. In the years
following harvest, or in ihe first few years of new
stands, non-merchantable volume may become a
more significant portion of the forest condition, and
so the carbon models might miss a significant
amount of carbon. Such situations can arise in the
first few years following a significant increase In
harvested acreage, of In the first few years
following large amounts of new afforestation or
reforestation* Thust the net carbon accumulation
for some scenarios, such as afforestation or
increased biomass energy production, may be
understated relative to the base case.
13
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economy. The BLS consists of 20 national models of the major agricultural producers and 14 regional
models, which account for the remainder of global production. At the international level, all countries
trade in a world market of 10 commodities, which may be aggregated from more extensive lists at the
national and regional level (the U.S. model, for example, contains 23 commodities). For the purposes
of this analysis, only the model of the United States was used to model the impacts of alternative
agricultural practices and the Conservation Reserve Program (CRP) and the Wetlands Reserve
Program (WRP). Because the BLS was not designed for projections, but rather for determining the
effects of different scenarios, model results are more valid for incremental changes of the scenarios
from the base case than for the absolute values generated in either individual scenario or base case
runs.
The Resource Adjustment Modeling System (RAMS), was developed by Iowa State University's
Center for Agricultural and Rural Development (CARD) in order to determine optimal agricultural
production levels for regional Producing Areas (PAs). A Producing Area is an aggregation of counties
(often across state boundaries) that has been defined by the U.S. Water Resources Council as being
a single hydrologicai area. Each PA is sufficiently small that it can also be assumed that production is
homogeneous across the PA. Because each PA acts as an independent decision-making entity, RAMS
allows for region-specific targeting of production practices.
RAMS is designed as a short term, static, profit-maximizing, linear programming model of
agricultural production. Profit-maximization is subject to a number of constraints including the
technology available, the resource base, and government policy. All activities are characterized by four
dimensions: crop rotation, tillage, contour management, and irrigation. RAMS is designed to
accommodate crop and geophysical process models such as DNDC and CENTURY in order to
provide a more comprehensive evaluation of policies designed to sequester carbon in agricultural
soils.
The Denitrification and Decomposition (DNDC) model, which was developed by the Bruce
Company and the University of New Hampshire, is used to examine carbon and nitrogen dynamics in
agricultural soils. Nitrous oxide (N2O), dinitrogen (molecular nitrogen) (N2), and carbon dioxide (CO2)
production in soils are evaluated as a function of agriculture practices, soil conditions, and climate
(both precipitation and temperature). Common agriculture practices that are modeled include: tillage
intensity; fertilizer application; seeding and harvest times; and crop rotations. Rainfall events, soil
moisture, and temperature (determined from the climatic data and soil properties) drive the fluctuating
physical processes. Between rain events, decomposition occurs, which results in CO2 production and
oxidation (including nitrification), while during the rainfall events themselves the denitrification process
dominates.
CENTURY was originally developed at Colorado State University, and has been supplemented by
more recent collaboration with Michigan State University. CENTURY simulates the dynamics of soil
organic matter (SOM) in both grassland and agricultural ecosystems. Specifically, the dynamics of
carbon, nitrogen, phosphorous, and sulphur in soils can be modeled in one month intervals for
periods as long as 100 to 10,000 years; scenarios can be modeled using monthly time steps. SOM in
CENTURY is divided into three categories based on the time scale required for turnover or
decomposition: 1.5 years (active), 50 years (slow), and 1000 years (passive). The decomposition rate
is a function of chemical composition of the soil, expressed in terms of lignin and nitrogen content,
climatic conditions and location of the organic matter.
In order to assess both the economic and the physical effects, including changes in carbon levels,
associated with different agricultural practices, RAMS, the agricultural economics model, is linked with
DNDC and CENTURY, the soil carbon models. As a refinement of the PAs used in RAMS, Production
Areas are subdivided into Climate Divisions which allow for a more precise representation of soil and
climate conditions. DNDC and CENTURY then use geographic information systems (GIS) data to
define land type and area with increased resolution.
14
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ASM, the Agriculture Sector Model of the United States, was developed at the Agricultural
Economics Department of Texas A&M University to determine changes in U.S. production, consumer
and producer surplus, prices, international trade, and food processing based on changes in resource
availability. Production is divided into 63 regions and 36 commodities with region-specific data for crop
yields and human and natural resource endowments. Each region uses a set of supply and demand
budgets, which incorporates prices, quantities, and elasticities. Supply budgets account for
transportation costs, while demand includes aggregate demand from foreign markets and domestic
demand in the form of food consumption, Commodity Credit Corporation stock, feed grains for
livestock, and food processing. ASM has been modified to include a stumpage supply sector (from
TAMM), which harvests the trees on both agricultural land and commercial timberland.
4. TREE PLANTING SCENARIOS
U.S. forests currently occupy almost 740 million acres, or about 5 percent of the world's forest
area, providing an important terrestrial "pool" for carbon (Haynes, et al. 1994; Birdsey and Heath
1993). Trees, which are relatively long-lived structures, sequester CO2 from the atmosphere as they
grow, storing it as carbon in trunks, limbs, foliage, and roots. Soil and vegetative cover also provide a
pool for carbon. In 1987, U.S. forest ecosystems stored about 53 billion metric tons of carbon, of
which over half was in the soil (Birdsey and Heath 1993). Standing (living and dead) trees store
almost one-third of the forest carbon, and the remainder is stored in the understory or on the forest
floor (see Figure 4-1). Thus, expanding the carbon pool by increasing the acreage devoted to
timberlands and other woodlands has the potential to sequester significant additional amounts of
carbon.
Figure 4-1. Carbon Storage in U.S. Forest Ecosystems by Forest
Ecosystem Component (in billion metric tons)
Understory O.9
(2%)
Soil 34.O
(59%) _
Forest Ecosystem
Forest Floor 5.3
(9%)
Foliage 0.4
'(3%)
Other Parts 5.4
(31%)
Roots 3.O
(17 %)
Trees
Source: Birdsey and Heath 1993
This portion of the report describes the results of the analyses of possible forestation programs.
Section 4.1 examines the timber, carbon and economic impacts of large scale tree planting programs
that are similar in scale to the originally proposed funding levels for the "America the Beautiful"
program. Next, Section 4.2 looks at the implications for both carbon and agricultural production of
expanding existing tree planting programs. Last, Section 4.3 links the forest and agriculture sections
together, in order to capture the interactions between tree planting on agricultural lands and land
prices. Each of the three sections describes the base case and scenarios evaluated, the models used
for the analysis, and presents the impacts on carbon and on the forest and agriculture sectors.
15
-------
4.1 TREE PLANTING ON MARGINAL CROPLAND AND PASTURELAND
Two key studies (Moulton and Richards 1990, and Parks and Hardie 1992) have identified land
areas in the U.S. that are suitable for establishing forest plantations. These lands are generally
marginal crop and pasture land, which are defined based on soil erosion rates, soil type, and U.S. Soil
Conservation Service land classifications. The carbon sequestration potential of these lands varies
considerably by region and land quality, reflecting different growth rates and wood densities for
various tree species and climate conditions (as Table 4-1 illustrates for each region). Planting on these
lands can generate benefits other than carbon sequestration, including reduced soil erosion,
watershed protection, conservation of biodiversity, and improved recreation and aesthetic
opportunities.
Table 4-1
Average Storage of Carbon In Forest
Ecosystems by U.S. Region
Region
South Central
Southeast
North Central
Northeast
Rocky Mountain
Pacific Coast
Total U.S.
Carbon Storage
(pounds per acre)
116,748
124,146
162,948
165,021
128,040
205,225
158,225
Source: Birdsey and Heath 1993
The current analysis examines the carbon, timber, and economic impacts of federally subsidized
tree planting programs, using several models (see Section 3). TAMM, an economic model focusing on
the forest sector and private timberland, is linked to ATLAS, a forest inventory model, which tracks
forest age-class distribution and productivity classes, and to NAPAP, which models the pulp and
paper sector. These models are combined with a similar inventory constructed for public lands. For
public lands, there are no stand-alone inventory models, and inventory assumptions are embedded in
a variety of harvest planning models. Estimated future forest inventories are derived using data from
planning efforts at the level of individual National Forests and other public agencies, such as the
Forest Planning Model (FORPLAN) used in the National Forests. Carbon data for the forest inventory
at any point in time are supplied by two alternative forest carbon models, FCM and FORCARB.
HARVCARB analyses of the flow of post-harvest carbon supplement the results of these two forest
carbon models. The CGTM, which models global timber markets, provides additional insights into the
impacts of tree planting on U.S. timber inventories, harvests, and imports and exports.
This combination of models captures a number of critical impacts and interactions. Together, the
models provide projections over the period 1990 to 2040 for carbon stored on forested land, carbon
stored in other pools (i.e., in products produced using harvested wood or in landfills), impacts on
timber inventory, harvest, and other effects. In the analyses, all trees planted and/or retained from
harvest under a tree planting program are available once they reach minimum harvest age. Thus,
5 Minimum harvest age is approximately 20 years in the South, 45 years in the Pacific Coast states, and 70
years elsewhere.
16
-------
near-term tree planting, by increasing the standing timber available in the future for harvesting, can
significantly affect the prices of both sawtimber and wood-containing products (such as lumber and
furniture) and may affect consumer and producer welfare.
These models do not, however, capture several important effects. The impacts of federally
subsidized tree planting on stumpage prices will affect not only future decisions about harvesting, but
also decisions made by forest landowners to plant or harvest today, made in response to expectations
about future prices and profits, an effect not captured by the TAMM/ATLAS models (see Box 4-1). In
addition, large-scale tree planting on agricultural
lands could potentially increase the prices of
crop land. This increase could affect farm
income and/or crop prices, as well as alter the
cost to the government of planting trees on any
given acreage. The analysis using the ASM
model, which is reported in Section 4.3, partially
captures this interaction. Ongoing work at the
U.S. EPA and U.S. Forest Service continues to
investigate these effects, and so the results
reported here are preliminary. However, they
illustrate the significant potential of expanding
forested land to sequester carbon.
SCENARIOS AND BASE CASE
The tree planting analyses examine the im-
pacts of two alternative funding levels and two
alternative land base/enrollment schedules. For
funding levels, alternative government
expenditures of $110 million and $220 million
annually for ten years are used. These funding
levels correspond to the originally proposed
level of funding for rural tree planting under the
"America the Beautiful" tree planting program,
and to a more aggressive program with double
that funding. The funding covers half the cost of
planting and establishing trees, and 10 years of
land rental costs, or payments made to owners
of the land where planting occurs.
Enrollment schedules are designed to forest
land in the most cost-effective manner, i.e., to
enroll first those lands on which carbon could
be sequestered most cheaply. Because
differences in the land base can affect the
pattern of cost-effective enrollment, two
alternative schedules of land area (described in
Table 4-2 and Figure 4-2) are used: a low
enrollment schedule and a high enrollment
schedule (derived from Moulton and Richards
1990, and Parks and Hardie 1992, respectively).
For both enrollment schedules, the majority of acres enrolled are marginal pasture land. These
scenarios assume that, at the end of the 10 year contract period, all acres revert gradually to
agricultural use (less than one-half percent annually) over the time-frame of the analysis. Table 4-2
also presents the enrollment schedule if $110 million in annual funding (for 10 years) is distributed
following the geographic enrollment pattern observed historically in the U.S. over the years 1981-1990.
Box 4-1
investment Behavior in TAMM/ATLAS
The TAMM/ATLAS models do not Include
price-sensitive land management decisions and,
consequently, do not capture the effects of future
prices on current planting decisions, Bather, the
models project behavior based on historically
observed investment responses, Since there are no
historic data on behavior under conditions explored
fn these scenarios (Len targe-scale tree planting),
the models may not project the most likely
responses (Winnett, et al. 1993), These models
would have a tendency to project little or no
divestment of timber (the observed pattern for
private non-industrial forest owners under
historically observed conditions) even under
conditions of very low prices brought about by
large increases in timber supplies. An analogous
situation would apply to new timber investment
under conditions of very high prices and timber
scarcity.
In contrast, a model that included responses
to expected prices in management tehavior would
show very different behavioral responses to a large
scale federal tree planting program, in a world of
perfect foresight, owners, in anticipation of lower
future prices when the trees planted today become
available for harvest, may choose to plant less or
accelerate current harvest plans, thus mediating the
impacts of the program on future prices, Simitartyt
higher anticipated; future prices would lead prof tf-
maximTzing owners to delay harvest decisions and
undertake additional near-term planting.
The true response is bounded by these two
models of behavior, and probably lies somewhere
in between. Results, particularly those for pricesv
could therefore be less extreme than some of
those presented here.
17
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Table 4-2
Regional Distribution of New Forest Under
Alternative Enrollment Schedules (million acres)
Region
South Central
Southeast
North Central
Northeast
Rocky Mountain
Pacific Southwest
Pacific Northwest
Total U.S.
$110
low
enrollment
5.8
0
0
0
0
0
0
5.8
Million Annually
(1 0 years)
high
enrollment
6.4
0
0
0.1
0
0
0.5
7.0
historic
enrollment
2.0
1.5
0.3
0.1
0
0
0.3
4.2
$220
Million Annually
(10 years)
low high
enrollment enrollment
8.0
0
0
0
1.8
0
0
9.8
8.5
0.4
2.5
0.2
0
0.1
0.6
12.3
Source: Birdsey and Heath 1993
Figure 4-2. Geographical Regions Corresponding to Enrollment Scenarios
PACIFIC NORTHWEST
NORTH CENTRAL
NORTHEAST
SOUTHEAST
PACIFIC
SOUTHWEST
SOUTH CENTRAL
Source: Turner, et al. 1993
18
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The Forest and Rangeland Renewable Resources Planning Act (RPA) of 1974 requires that the
U.S. Forest Service (USFS) of the U.S. Department of Agriculture assess the timber situation and
examine possible future trends in cost and ^availability. USFS performed an assessment in 1989 that
examined the period 1989-2040 (USFS 1990). The base case for the forestation analyses in this report
is a modified version of the 1989 RPA generated by the TAMM/ATLAS system, and reflects knowledge,
as of 1992, about future timber supply, demand, and harvest on private and public lands. The base
case projects a growth in GNP of 2 to 3 percent over the 50 year period, increasing energy costs, and
an increase in U.S. population to 333 million by 2040. Demand for forest products rises following
population projections, but reflects a slowing of per capita demand. The base case for the analysis
presented here differs from the 1989 RPA primarily in reducing National Forest timber harvest
projections by approximately 0.5 billion cubic feet per year to reflect revised National Forest
management plans, additional restrictions on log exports, and harvest set-asides attributable to legal
actions under the Endangered Species Act.
Figure 4-3 presents the range of forest carbon projected by FCM and FORCARB for the
TAMM/ATLAS base case, against which subsequent scenario analyses are compared. The two carbon
models use slightly different assumptions about changes in carbon in the various ecosystem
components (especially soils), reflecting uncertainty in the supporting literature. In particular,
FORCARB assumes that soil carbon levels undergo significant change in response to forest
management activities, with carbon levels decreasing after harvest and increasing during regrowth. In
contrast, the FCM model assumes that soil carbon levels are relatively insensitive to management
activity and there is little per acre change in carbon due to harvest and regrowth. Consequently, the
FCM results show a slow but steady increase in carbon levels, while the FORCARB results show steep
increases in carbon inventories, which are then slowed by the harvest of trees as they reach financial
maturity.
Figure 4-3. Total Carbon Storage on U.S. Public and Private Timberland:
Range of Model Results for Base Case Scenario
2010
2040
Year
Sources: Lee 1993c; Heath 1993
19
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CARBON IMPACTS
Growth rates change as trees age, so that carbon accumulation rates vary over time. Because
trees grow relatively slowly, the bulk of the carbon is accumulated some years after planting occurs.
Figure 4-4 illustrates the range of results for two of the scenarios the lower funding, lower acreage
enrollment schedule, and the higher funding, higher acreage enrollment schedule, which together
essentially bound the analysis. Results are also presented for the scenario in which $110 million in
annual funding (for 10 years) is used to plant trees on lands following the historic distribution of lands
planted over the years 1981-1990. The range of carbon accumulation reported for each of these
scenarios also results partly from differences between the two forest carbon models used, FCM and
FORCARB.
Figure 4-4. Total Carbon Storage on U.S. Public and Private Timberland:
Increases Relative to Base Case for Tree Planting Scenarios
1990
Sources: Turner, et al. 1993; Heath 1993
As illustrated in Figure 4-4, large scale tree planting has the potential to increase the size of the
forest carbon pool over base case projections by between about 500 million metric tons and 800
million metric tons by the year 2040, with approximately one-fourth of the total achieved by the year
2010. Table 4-3 presents annual carbon accumulation over the base case at decadal intervals. Carbon
results in Table 4-3 are the average of the FORCARB and FCM model results.
Harvested timber is an important component of the total forest sector carbon pool, because the
carbon can be stored not only in forest ecosystems, but also in products manufactured from
harvested trees, and in products discarded into landfills. The model HARVCARB examines the
distribution and transfer of harvested wood for the TAMM/ATLAS forestation scenarios. In the base
case analysis, HARVCARB allocates 81 percent of each year's harvest during the first decade to
storage in products or landfills. The balance of harvested carbon returns to the atmosphere
20
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Table 4-3
Annual Carbon Accumulation on U.S. Public and Private Timberland Relative to Base Case for
Three Tree Planting Scenarios, Decadal Intervals (million metric tons)
2000
2010
2020
2030
$220 million annually for 10
years, high enrollment
$110 million annually for 10
years, low enrollment
$110 million annually for 10
years, historic distribution
6.8
4.1
3.5
16.7
9.6
6.5
19.4
10.8
7.5
13.0
6.2
5.5
Note: Forest carbon estimates are presented as the average of FORCARB and FCM results.
Source: Turner, et al. 1993; Heath 1993
immediately, primarily as a result of energy production. In succeeding years, carbon from current
harvests continues to be allocated largely to products, and carbon moves from products to both
disposal pools and the atmosphere as older products are retired.
Because a large portion of the carbon contained in harvested timber remains in products for some
length of time, these products represent an additional store of carbon, over and above that stored on
forested lands. The forestation scenarios show an average annual carbon accumulation (post-harvest)
in products of 1.7 to 2.4 million metric tons over the 50 year period. However, the potential climate
impact of this carbon accumulation may be offset when it is adjusted to account for the effect of
methane emissions from landfilled forest products (Turner, et al. 1993).
TIMBER INVENTORY EFFECTS
The scenario analyses suggest that tree planting programs funded at $110 million to $220 million
per year for ten years would lead to large increases in U.S. timberland area. Results suggest that the
tree planting scenarios would have the largest impact on privately owned U.S. softwood growing stock
inventories and harvest. These effects are greatest in the South Central region where a majority of the
land enrollment is projected to occur under all scenarios. As Figure 4-5 illustrates, U.S. softwood
inventories on privately owned lands in the scenarios increase over the base case by about 2 percent
in the year 2010 and by between 6 and 10 percent in the year 2040.7 Table 4-4 illustrates softwood
harvest rates, for selected years and forestation scenarios.
ECONOMIC AND TRADE EFFECTS
Projected increases in timberland are likely to have substantial impacts on U.S. timber markets,
particularly in the South Central region where the largest increases occur. The analysis shows that
increases in timber supplies drive down stumpage prices relative to the base case, particularly
softwood stumpage prices in the South, where prices become low and steady toward the end of the
To the extent that it substitutes for energy from fossil fuel use, the use of forest products can be considered to
be a permanent carbon sink, or an energy offset.
Timber inventory as used here is the growing stock volume, defined as the cubic volume of all live trees of
commercial species, meeting specified standards of quality or vigor, which are at least 5.0 inches in diameter at
breast height.
21
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Figure 4-5. U.S. Softwood Inventory Projections For Privately Owned
Timberland: Base Case and Tree Planting Scenarios
250 -r
240 - -
230 --
220 --
210 --
200 - -
180
$110 M Hllon Low
E n rollm e nt
$220 M Hllon. riign
Enrollm ent
$110 Million Historic
D 'stributio n
1990
Source: Haynes. et al. 1994
Table 4-4
U.S. Softwood Harvests for Tree Planting Scenarios: All Owners
(billion cubic feet)
$110 Million Annually $220 Million Annually
(10 years) (10 years)
Year
1990
2000
2020
2040
Base Case
11.0
11.8
14.1
15.3
Historic
Distribution
11.0
11.8
14.1
15.6
Low
Enrollment
11.0
11.8
14.2
15.8
High
Enrollment
11.0
11.8
14.3
16.0
Source: Haynes, et al. 1994
time-frame examined.8 If private owners plant at the levels assumed under these scenarios,
reductions in stumpage prices are likely to be tempered by actions taken by other landowners to plant
less area to trees, an effect which is the subject of ongoing investigation by the U.S. EPA. To the
extent that prices decline, consumers would tend to benefit and owners of timber would lose.
8 Stumpage price is paid for standing timber in the forest, and is typically measured in dollars per thousand
board feet.
22
-------
Although softwood inventory and harvest projections increase under each tree planting scenario,
stumpage price projections fall relative to the base case (see Tables 4-5 and 4-6). The price decline is
greatest in the South, where the majority of marginal crop and pasture lands are situated, and, hence,
where planting occurs. Prices in the South become low and steady soon after the timber inventory
begins to increase, i.e., when the wood becomes merchantable (after 2 or 3 decades). Softwood
stumpage prices in the Rocky Mountains and Pacific Coast show slight declines, relative to the base
case, over the time frame of the analysis, while prices in the North are largely unaffected, as are
hardwood sawtimber stumpage prices. The declines are greatest for the largest tree planting program.
Table 4-5
Stumpage Prices in the Base Case
(dollars per thousand board feet)
2000
2010
2020
2030
2040
Softwood Stumpage Prices
North
South
Rocky Mountains
Pacific Coast
50
180
102
247
Hardwood Sawtimber Stumpage Prices
United States 463
66
260
236
311
559
88
306
287
365
665
101
306
259
367
784
111
297
279
358
903
Source: Haynes, et al. 1994
As U.S. stumpage prices decline, U.S. forest products become more competitive, and Canadian
lumber imports to northern U.S. markets decline after 2010, falling to between 7 and 9 billion board
feet in 2040, as compared to 13 billion board feet in the base case projection (Haynes, et al. 1994).
The CGTM analysis finds similar trade impacts. In addition, because there is no or little enrollment of
lands in these programs in the Pacific Northwest, exports from this region to Pacific Rim markets are
not affected (Perez-Garcia 1994).
4.2 CONSERVATION RESERVE AND WETLANDS RESERVE PROGRAMS
The analyses of the Conservation Reserve Program (CRP) and Wetlands Reserve Program (WRP)
provide another view of the impacts of government subsidized tree planting. CRP was established as
part of the Food Security Act of 1985 to foster the withdrawal from agricultural production of between
40 and 45 million acres of highly erodible grasslands and wetlands. To be eligible for inclusion in the
CRP, land must have an average erosion rate of at least 19.1 tons of soil per acre nearly three times
the national average. By this criterion, an estimated 24 percent of all U.S. cropland mostly in the
Corn Belt, northern and southern plains, and mountain regions is potentially eligible. Without special
dispensation, however, CRP signups are limited to 25 percent of a county's cropland, in an attempt to
spare local economies significant damage. This limitation reduces eligible land by almost one-third, to
just under 70 million acres (Trexler 1991). To encourage landowners to participate in the CRP, the
government shares the cost of converting the land into alternative uses (such as trees and other
cover) and provides rental payments throughout the 10-year CRP contracts. Currently, there are
approximately 36 million acres enrolled in the program, about 2.4 million of which are planted with
trees, and the remainder of which are in grasses.
23
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Table 4-6
Stumpage Prices In the Tree Planting Scenarios
(dollars per thousand board feet)
2000
$110 million annual funding for 10 years,
Softwood Stumpage Prices
North 50
South 178
Rocky Mountains 102
Pacific Coast 248
Hardwood Sawtlmber Stumpage Prices
United States 463
$220 million annual funding for 10 years,
Softwood Stumpage Prices
North 50
South 178
Rocky Mountains 102
Pacific Coast 248
Hardwood Sawtimber Stumpage Prices
United States 463
$110 million annual funding for 10 years,
Softwood Stumpage Prices
North 50
South 179
Rocky Mountains 102
Pacific Coast 244
Hardwood Sawtimber Stumpage Prices
United States 463
2010
low enrollment
66
237
239
310
559
high enrollment
64
228
239
309
558
2020
88
235
265
342
664
82
199
260
334
663
2030
101
33
230
314
782
84
*
210
293
779
2040
111
*
217
280
899
90
*
195
247
896
historic distribution
66
250
243
316
559
88
256
270
351
664
100
203
252
334
782
110
211
253
313
900
Note: "*" indicates prices outside the range of model results.
Source: Haynes, et al. 1994
The Wetlands Reserve Program was established as part of the 1990 Farm Bill to restore and
protect wetlands that have been partially or fully converted to agricultural use. The WRP places
accepted land areas under 30 year or permanent easements that prohibit the draining of wetlands.
The WRP encourages land owners to enter the program by paying compensation based on the type
of easement and the appraised land value, up to the full value of the land. The program also pays for
the cost of any restoration activities. The program goal was to have enrolled slightly less than 1 million
acres by 1995, although projected enrollment is a fraction of this amount.
24
-------
Because the reserve programs operate on agricultural land, the BLS model provides the results for
crop, income, and price effects in the agriculture sector. Carbon impacts are calculated from the BLS
results using the FCM. Together, these analyses provide results that encompass both carbon and
economic impacts. Although the impacts are based on specific policy options, they also illustrate the
impacts that other large scale tree planting programs, such as those described in Section 4.1, could
have on agriculture.
SCENARIOS AND BASE CASE
The analysis examines the carbon and economic impacts of tree planting for two alternative CRP
scenarios and a targeted WRP scenario. For the CRP analyses, the base case assumes that the
original CRP target enrollment of 40 million acres is achieved by 1995, then declines over time to 17.5
million acres, an outcome that is considered to be likely after current contracts expire. The CRP
scenarios reflect different assumptions about the size of future programs and alternative uses of CRP
land. Two alternative proposals 40 million acres and 50 million acres are compared to the base
case, as illustrated in Figure 4-6. Historical signups under the CRP guide enrollment patterns under
the base case and CRP scenarios. For both the base case and the 40 million acre CRP scenario, 3.7
million acres are planted with trees and the remainder is grassland. The incremental 10 million acres
in the second CRP scenario is planted with trees.
Figure 4-6. Annual Acreage Under CRP Scenarios
50 -
45 -
40 - -
35 - ;
30
25
20 -
15 -
10 -
5 --
0
1990
1995
2000
2005
2010
Year
2015
2020
2025
2030
Note: In the base case, the current program reaches 40 million acres in 1995 and
then contracts until 17.5 million acres remain in 2005. CRP-40 retains all 40 million
acres after 1995. CRP-50 expands the program to cover 50 million acres by 2005.
Source: Reese, et al. 1993
The third scenario, WRP, simulates the introduction of a 5 million acre reserve of wetlands
consisting predominantly of drained bottomland previously planted to agricultural crops. These acres
are targeted to establish hardwood tree stands for the potential carbon benefits of the trees, and to
provide wetlands benefits such as flood control, habitat preservation, and improved water quality. The
WRP also involves considerably different crops than the CRP, as displayed in Figure 4-7.
25
-------
Figure 4-7. Composition of Reserve Scenarios
Typical CRP
WRP
Other
24%
12%
Wheat
30%
Other
11%
Wheat
11%
Other Grains
18%
Corn
12%
Soybeans
42%
Other Grains
6%
Source: Reese, et al. 1993
CARBON IMPACTS
The FCM model suggests that expanding or extending the CRP program and using the WRP to
plant hardwood trees can sequester significant additional carbon dioxide. As Figure 4-8 illustrates,
maintaining the full 40 million acres results in an additional carbon accumulation of almost 200 million
metric tons in 2015 and nearly 350 million metric tons by 2035. This accumulation is relative to the
base case; full implementation of the current CRP plans (assuming that land begins to revert to
agricultural production after 1995). Carbon storage in the base case is approximately 1,050 million
metric tons in 1995, growing to 1,160 million metric tons in 2015 and 1,360 million metric tons in 2035.
Expanding the program to 50 million acres, by planting an incremental 10 million acres with trees,
more than doubles the carbon accumulated on CRP lands, relative to the base case. Under full imple-
mentation of the 50 million acre CRP program, the total carbon pool on CRP lands, including soil,
trees, understory and other forest ecosystem components, is estimated to reach almost 2,500 million
metric tons, a gain in excess of 1,100 million metric tons over the base case in the year 2035. The
smaller WRP program results in almost 200 additional million metric tons of carbon by the year 2035.
For the three scenarios, Table 4-7 presents annual carbon accumulation relative to the base case.
IMPACTS ON AGRICULTURE
Maintaining or expanding the reserve programs can affect agricultural output by removing
agricultural land from production and driving up commodity prices. The BLS model is used to estimate
the economic impacts of the CRP and WRP scenarios on the agriculture sector of the United States.
Crop acreages in both CRP scenarios are consistently lower over time than in the base case (see
Table 4-8). In percentage terms, soybean and rice acreages are the least affected of the major crops,
and planted acres of the "other grains" are reduced the most, with barley acres falling most
dramatically. For most crops the reductions in acreage are slightly offset by increases in yield on
planted acres, as producers farm their remaining acres more intensively in response to higher output
prices. On balance, production of all major crops is less under the CRP scenario than the base case,
and producer prices are concomitantly higher (see Table 4-8).
26
-------
Figure 4-8. Carbon Storage Under Reserve Program
Scenarios: Increases Relative to Base Case
b.
c 600
Note: CRP estimates are relative to CRP base case. WRP estimates are relative to carbon
storage in 1995 on WRP lands that will be planted with hardwood trees.
Sources: Lee 1993a; Lee 1993b
Table 4-7
Annual Carbon Accumulation for CRP and WRP
Scenarios Relative to Base Case,
Decadal Intervals (million metric tons)
2000
2010
2020
2030
CRP-40
CRP-50
WRP
11.6
31.5
2.2
7.9
15.9
4.4
7.7
34.5
7.0
7.2
31.6
4.6
Note: WRP estimates are relative to flux in 1995 on WRP lands that
will be planted with hardwood trees. Forest carbon estimates are
derived from the FCM model.
Source: Lee 1993a; Lee 1993b
Because the output of feed grains is significantly affected, feed prices are higher under the CRP
scenarios, and livestock production is generally lower under the scenarios, reflecting higher feed
costs. Beef production increases in both CRP scenarios relative to the base case (by 1 percent to 2
percent) and production of pork, milk, poultry, and eggs falls. Pork shows the largest decline over the
time period, on the order of 3 percent to 4 percent, while declines for milk, poultry, and eggs are
generally less than one percent (Reese, et al. 1993).
27
-------
Table 4-8
Impacts of Reserve Program Scenarios on Agricultural Production and Producer Prices:
Percent Change Relative to Base Case, Decadal Intervals
CRP - 40 MILLION ACRES PLANTED
Year
Acree Harvested
2000
2010
2020
3030
Producer Prices
2000
2010
2020
2030
Wheat
*7
-8
*$
-7
4
4
4
6
Rice
-2
-2
4
-2
2
1
1
3
Corn
*4
-4
-4
-5
5
6
§
5
Other Grain
""- **
-15
-if
-18
"+ . . V.W.
-
4+
'..
-
Soybean
»1
-2
«
1
4
3
$
4
Cotton
«e
-7
*7
-7
1
1
1,
0
CRP - 50 MILLION ACRES PLANTED
Year
Acres Harvested
2000
2010
2020
2030
Producer Prices
2000
2010
2020
2030
Wheat
-8
-10
-10
-9
$
5
5
7
Rice
-a
-2
-2
-2
2
1
1
3
Corn
;!
-6
-S
-7
7
8
$
6
Other Grain Soybean
1K -3
-20 -5
S.9 -5
-28 -1
a
6
^ S
8
Cotton
-7
-9
8 '
-10
2
1
2
-0.3
WRP - 5 MILLION ACRES PLANTED
Year
Acres Harvested
2000
2010
2020
2030
Producer Prices
2000
2010
20?0
2030
Wheat
0
0
6
0
1
1
1
1
Rice
Q
0
0
0
*
*
#
1
Corn
0
-2
-1
-2
1
1
1
1
Other Grain Soybean
0 -2
-1 -4
'-1 " " " -4
-1 -3
2
3
S
4
Cotton
*
*
*
*
*
*
*
*
Note: "*" indicates an increase or decrease of less than 0.5%.
Source: Reese, et al. 1993
28
-------
The WRP scenario has similar, but less dramatic, effects. The production of soybeans and corn is
most affected, with acreage reductions of about 4 percent and 2 percent, respectively. In contrast,
acreage falls by at most 1 percent for other crops. As a result, soybean producer prices increase by
about 3 percent and corn prices increase by about 1 percent (see Table 4-8). Correspondingly small
impacts occur in livestock; production of pork and of poultry falls by 1 to 2 percent, while production
of other livestock products is relatively unaffected (Reese, et al. 1993).
ECONOMIC IMPACTS AND GOVERNMENT COSTS
Under the CRP scenarios, per capita consumption of most commodities changes only slightly,
although consumption of grain products and most meat fall by 1 to 2.5 percent after the programs
have been fully implemented. As a result of these changes, producer net returns increase for crop
producers, but decline significantly for livestock producers. Government price support payments to
crop producers fall by more than the cost of the CRP programs.9 Combined returns in the agriculture
and livestock industries, i.e., the net result of changes in income and in government payments, are
about $350 million to $450 million per year lower under the CRP scenarios. By comparison, total net
U.S. farm income between 1989 and 1991 averaged $47 billion per year. Consumers are generally
worse off with slightly lower consumption and higher retail prices, resulting in about a 2 percent
increase in total consumer expenditures (Reese, et al. 1993). The effects of the WRP are similar;
results for all three scenarios are reported in Figure 4-9, for selected years.
4.3 THE AGRICULTURE SECTOR: IMPLICATIONS FOR FEDERALLY FUNDED TREE PLANTING
Large-scale tree planting affects not only the forest sector but also the agriculture sector.
Subsidized tree planting takes marginal land out of agricultural production and may raise crop prices,
with consequent welfare impacts for consumers and producers in the agriculture sector, as discussed
in Section 4.2. Taking land out of production may also increase land prices, which in turn increases
the subsidy that is necessary to induce landowners and others to plant trees. Thus, the cost to the
government of funding tree planting on a given number of acres can be higher when agricultural price
effects are considered. The cost per ton of carbon sequestered will also be higher. Agricultural price
effects may also lead to welfare changes for producers and consumers in both the agriculture and
forest sectors.
To assess the carbon and economic implications of land price increases for the agriculture sector,
the U.S. EPA initiated an additional series of tree planting analyses. The analyses reported in this
section complement the analyses reported in Section 4.1 and Section 4.2. These analyses use the
ASM, a U.S. Agriculture Sector Model (Adams, et al. 1993; and Chang and McCarl 1991). In the ASM
analyses, land currently enrolled in the CRP is released at the termination of the program and either
reverts to cropland or is available for tree planting. For the analyses, TAMM provides regional forest
sector supply and demand curves and other information about the demand for wood products.
Estimates of the cost of establishing trees are based on estimates in Moulton and Richards (1990),
and carbon yield data are taken from Richards (1992).
SCENARIOS
The ASM analysis evaluates the welfare and carbon impacts of tree planting programs under
several alternative assumptions. First, the analysis examines the implications of using alternative land
bases for planting trees: cropland, pastureland, and wetlands. These land types differ in carbon
sequestration potential, in distribution within the geographic United States, and in current agricultural
Program costs are not handled endogenously in the models; rather they are based on estimates by analysts
familiar with the Conservation Reserve Program. It Is estimated that additions to the CRP in the Great Plains states
would cost 40 to 50 percent of the current $49 to 50 per acre. Environmentally sensitive acres added to the CRP
are expected to cost $70 to 80 per acre.
29
-------
Figure 4-9. Impacts on Agriculture for CRP and WRP
Scenarios, Change from Base Case
CRP Maintained at 40 Million Acres
I
I
2010
2020
2030
CRP Expanded to 50 Million Acres
JRJ
1
2010 2020 2030
WRP Established on 5 Million Acres
-3000
-4000 J 2010
2020
2030
mi Change in net farm income
INI from crop production
D Change in government transfer
payments for program crops
Change in net farm income
from livestock production
rca Change in government payments
tia for reserve programs
Source: Reese, et al. 1993
30
-------
use. Using alternative land bases, therefore, produces different price impacts for land, crops, and
livestock, and different impacts on economic welfare and carbon sequestration. The three specific land
scenarios reported here involve planting 6.3 million acres on cropland, 7.5 million acres on
pastureland, or 4.6 million acres on wetlands. These programs are roughly similar in magnitude to the
smaller tree planting program in Section 4.1 (low enrollment and $110 million in funding) and the
wetlands program described in Section 4.2, although the land bases are not directly comparable.
Second, several different enrollment patterns are analyzed. Because land varies in productivity,
land price, and the cost of establishing trees, the cost of sequestering a ton of carbon varies within
each of the land types.10 A program that enrolls lands in order of carbon sequestration costs will
sequester a given amount of carbon at the lowest cost. For most analyses reported here, land is
enrolled on a least-cost basis: for a given land class, acres are planted to minimize the cost per ton of
sequestering carbon, so that lands that can sequester carbon most cheaply are enrolled first. For
cropland, however, an alternative pattern of enrollment is also analyzed, in which the regional
distribution of planted lands follows the pattern of lands enrolled in the current Conservation Reserve
Program.
Last, the analysis examines two alternative harvesting assumptions: optional harvests and no
harvests. In the optional harvest scenario, the ASM simulates the decision faced by farmers in each
region to plant or harvest trees based on economic considerations. While allowing harvesting reduces
the amount of carbon stored on planted lands, it provides an additional incentive for landowners to
plant trees, an effect that may offset the potential carbon loss from harvesting, as described more fully
below.
The ASM has several advantages. Because it is a detailed model of the agriculture sector, it
directly models impacts on land prices (previous analyses have assumed no impacts on these prices),
captures farm program effects, and reports welfare and other impacts in the farm sector. The ASM
analyses are, however, static; all planting essentially takes place in a single time period, and so the
model reports average carbon per acre per year, or average cost per ton per year, rather than time
paths of carbon, timber, acres, and costs. While this approach captures average carbon accumulation
over the rotation of the trees that are planted, it tends to overstate carbon accumulation that would
occur during the early years of a multiple year tree planting program and to understate accumulation
during later years.
IMPACTS ON CARBON, COSTS, AND WELFARE
Figure 4-10 presents average annual carbon accumulation for three land types, under alternative
assumptions about harvesting. In this figure, the highest average annual sequestration rate under the
no-harvest assumption occurs for cropland, followed closely by pastureland, and then by wetlands.
Although less cropland is enrolled than pastureland, higher annual carbon accumulation on cropland
reflects the higher productivity of these lands, at the assumed levels of planting.
The relative productivity of these lands also influences the costs of sequestering carbon, which are
reported in Table 4-9. In this table, average cost is calculated as the annual cost (to the government)
of the tree planting program divided by the amount of carbon sequestered annually. In turn,
government costs represent the subsidy that the government would have to pay landowners to induce
them to plant the additional trees. This subsidy, therefore, will be higher if land rents are higher. On a
per ton basis, the subsidy will be lower if the enrolled land is more productive. The cost per annual
10 Cost, in this analysis, is calculated as the full "opportunity cost" of planting trees, i.e., the amount farmers
must be paid to induce them to plant trees, taking into account land prices and profitability of the land in alternative
uses, the cost of establishing trees on the land, and revenues from harvesting mature trees. Cost is not, therefore,
fully comparable with costs reported in Section 4.1, where it was assumed that the government fully compensates
farmers for foregone land rent, and pays half of the cost of establishing trees, regardless of whether these sum to
more or less than the opportunity cost of the land.
31
-------
Figure 4-10. Average Annual Net Carbon Accumulation:
Tree Planting on Three Land Types
Crcpland Pastureland
Source: Callaway and McCarl 1994
ton of carbon, under the assumption of no harvests, is lowest for wetlands, followed closely by
cropland and more distantly by pastureland.
While the results for the restricted harvest scenario illustrate carbon and cost impacts most clearly,
a more realistic assumption is that harvesting occurs. Allowing harvesting will have several competing
effects. First, harvesting generates some income for those who plant; a lower subsidy, therefore, is
required to induce additional planting. In addition, harvesting forested land may lead to more land
Table 4-9
Impacts of Tree Planting on Different Land Bases
Cropland
Annual Government Cost
($ millions)
Annual Carbon
(million tons)
Annual Average Cost
($ per ton)
No
Harvest
100
14.1
6.90
Optional
Harvest
60
11.7
5.00
Pastureland
No
Harvest
220
13.9
15.70
Optional
Harvest
90
14.0
6.60
Wetlands
No
Harvest
70
11.1
6.30
Optional
Harvest
40
8.9
4.40
Source: Callaway and McCarl 1994
32
-------
returning to agricultural use, mitigating the impacts of tree planting on land prices and, thus, reducing
the costs to the government of subsidizing forestation. At the same time, harvesting a large amount of
timber would tend not only to depress stumpage prices significantly, but partially to reduce carbon
sequestration gains.
As displayed in Figure 4-10, allowing harvesting reduces the carbon stored on cropland and
wetlands, relative to a situation of no-harvest. Government costs drop substantially, however, as
illustrated in Table 4-9. On balance, the cost-per-ton of carbon sequestered drops significantly for all
three types of land when harvesting can occur.
Both the amount of carbon sequestered per acre, and the cost of sequestration per ton of carbon,
are highly sensitive to the pattern of enrollment. When lands are enrolled on a least-carbon-cost basis,
costs of sequestering a given amount of carbon will be lowest. Alternatively, 6.3 million acres of
cropland could be enrolled in a pattern reflecting the regional distribution of lands historically enrolled
in the CRP. As illustrated in Table 4-10, the two patterns of enrollment produce dramatically different
results. Although average annual carbon accumulation is slightly higher under the historic enrollment
pattern, costs more than double. When harvests are restricted, the costs of sequestering carbon using
the historic distribution are more than triple those using a least-cost enrollment pattern.
Table 4-10
Impacts of Tree Planting on Cropland with Varying Enrollment Strategies
Least-Cost Enrollment
No Harvest Optional Harvest
Historic Enrollment
No Harvest Optional Harvest
Annual Government Cost 100
($ millions)
Annual Carbon 14.1
(million tons)
Annual Average Cost 6.90
($ per ton)
60
11.7
5.00
340
15.7
21.60
150
12.6
11.61
Source: Callaway and McCarl 1994
Finally, the ASM provides measures of the change in economic welfare and prices in the
agriculture and forest sectors. The results for the agriculture sector, displayed in Tables 4-11 and 4-12,
are similar to those in Section 4.2. Crop prices (which do not include farm program payments) and
livestock prices tend to rise slightly as a result of tree planting on agricultural lands, which results in
declines in consumer surplus. These results are particularly pronounced for the historic enrollment
pattern, which plants more trees in regions that are important to crop production. Agricultural
producers show a decrease in welfare when land is enrolled in order of carbon cost, and an increase
in welfare under the historic enrollment scenario. As in the analysis in Section 4.2, impacts under
11 Table 4-11 reports Fisher price indices for agricultural crops (raw agricultural crop prices not including farm
program payments); livestock; and forest consumer prices for logs (which gives an index of prices to all forest
producers at the mill dock).
33
-------
either scenario, while apparently large in dollar terms, are relatively small as a percent of the base
case surplus for agricultural producers.12
Table 4-11
Economic Welfare Effects of Federal Subsidies for Tree Planting on Cropland
(million dollars, percent change)
Least-Cost Enrollment
Historic Enrollment
No Harvest
Optional
Harvest
No Harvest
Optional
Harvest
Forest Sector
Consumer Surplus
Producer Surplus
0
-10
(0%)
(-1%)
190 (2%)
-210 (-13%)
0 (0%)
0 (0%)
230 (2%)
-240 (-15%)
Agriculture Sector
Consumer Surplus
Producer Surplus
140
-100
(*)
(*)
-10
-10
(*)
(*)
-250
110
(*)
(*)
-610
330
(*)
(1%)
Notes: Surplus changes estimated relative to surplus in a base case with no planting subsidies.
"*' Indicates an increase or decrease of less than 0.5%.
Source: Callaway and McCarl 1994
Table 4-12
Price Effects of Federal Subsidies for Tree Planting on Cropland:
Fisher Price Indices
Least-Cost Enrollment
Baseline No Harvest Optional Harvest
Historic Enrollment
No Harvest Optional Harvest
Crops
Livestock
Logs
100
100
100
99.9
100
100
100.1
100
88.6
100.7
100.2
100.0
101.5
100.4
87.1
Source: Callaway and McCarl 1994
Economic impacts in the forest sector as a result of tree planting are significantly affected by
whether or not harvesting occurs. When harvests are restricted, trees that are planted do not
ultimately enter timber markets, and so there is no change in the log prices or in the welfare of
producers and consumers, as displayed in Tables 4-11 and 4-12. When harvests are allowed to occur,
tree planting reduces forest product prices significantly, resulting in benefits to consumers and
adverse impacts on producers.
12 Differences in the magnitude and direction of results between Sections 4.2 and 4.3 may reflect differences in
the number of acres enrolled, in enrollment patterns and the assumptions about the rates at which land enrolled in
the CRP reverts to alternative uses or become available for tree planting, in how the farm program is modelled, and
In interactions between the agriculture sector and the forest sector (which is absent in the CRP analysis) in the
ASM.
34
-------
5. OTHER FOREST POLICY SCENARIOS
Policies that increase the acreage of standing trees by reducing harvest can expand the amount
of carbon stored on forest land. Two scenarios, reduced harvest in National Forests and increased
rates of utilization of recycled fiber (which decreases the demand for virgin fiber), provide information
on the carbon, timber, and economic impacts of such forest policies. A third scenario, increased use
of wood fuels, which reduces carbon emissions by displacing fossil fuel generated energy, is also
examined. Finally, this part of the report examines the implications of combining policies to take
advantage of the potentially offsetting economic impacts.
5.1 INCREASED RATES OF RECYCLED PAPER UTILIZATION
Policies designed to increase the use of recycled paper and fiber in the paper and pulp making
process (see Box 5-1) increase the size of the forest carbon pool in three ways. First, manufacturers of
pulp and paper products that use greater amounts of recycled fiber use less virgin (freshly harvested)
fiber, reducing the harvest of pulpwood-sized trees. By decreasing demand for harvested wood,
increased use of recycled fiber can increase forest inventories and enlarge the forest carbon pool.
Second, trees left uncut grow larger over time, further increasing forest and carbon inventories. Last,
to the extent that the wastepaper in landfills eventually decays and returns greenhouse gases to the
atmosphere, increased utilization of recycled fiber can reduce emissions associated with the forest
products pool. Pulpwood-sized trees that grow into sawtimber sizes can be cut for long-lived solid
wood products, which sequester carbon for longer periods of time than do paper products.
Although increased recycling has the
potential to expand forest carbon, timber market
effects may mitigate the beneficial impacts of
recycling on forest carbon. If decreased demand
for harvested timber for paper production
reduces long-term prices in the forest sector,
then less near-term planting may occur, in
anticipation of lower returns in the long term. At
current rates of recycling, however, projections
for the U.S. suggest that serious supply
shortages will exist for sawtimber in the future,
resulting in rapidly rising stumpage prices.
Increased recycling, therefore, can extend fiber
supply and partially mitigate potential increases
in stumpage prices over time; the scenario
results presented below suggest that, with
increased recycling, real prices of softwood
remain relatively stable (rather than rise) through
the time period.
This analysis employs the same models
used for the analyses of large scale tree
planting presented in Section 4.1. The NAPAP
model provides the framework necessary to
analyze the impacts of policies designed to
increase recycling rates. This model (described
in Section 3) simulates the evolution of process
technology (for using recycled fiber and virgin
wood fiber) for all primary paper and paperboard products (such as newsprint, printing and writing
paper, and linerboard). The model combines regional information on supply and demand,
manufacturing processes, and transportation costs to project future technological changes,
production, capacity, imports and exports, and related market equilibria for the United States and
Box 5-1
Paper Recycling in the U,S.
The U.S. currently recycles severed types of
paper, including newspaper, and the rate at which
recyclable paper is being utilized has risen from
around 25 percent fn the late 1980s to almost 30
percent fn 1992, Continuing growth In recycling
rates is technically feasible, particularly for
newspaper, and a variety of policies are being
considered at both the federal and State levels to
increase the rate at which wastepaper Is used.
Reducing the pressure on landfills provides
much of the impetus for recycling programs; in
1990, paper and paperboard comprised
approximately 37.5 percent, by weight, of the
material deposited in landfills. Policies that have
been proposed to improve waste paper recycling
include minimum recycled content standards for
newspaper, per-unit disposal fees fortrasrt
removal, mandatory recycling rylesf and financial
incentives to use or recycle wastepaper, increased
recycling may also have added benefits for carbon
storage,
Source; Tnce 1994
35
-------
Canadian pulp and paper sector. Combining this model with TAMM/ATLAS provides the necessary
link for analyzing the implications of increased paper recycling on forest product markets and on
carbon storage. The CGTM model provides additional insight into the regional distribution of impacts
on pulpwood and sawtimber markets within the U.S., and the associated effects on international trade
in the forest products sector.
SCENARIOS AND BASE CASE
Increasing the use of recycled fiber in the manufacture of paper and board replaces a percentage
of the newly harvested (virgin) fiber in the production process. Using less virgin fiber reduces the
harvest of trees and leaves more of the forest, intact to grow longer and to sequester more carbon.
The increased recycling scenario differs from the base case both in how quickly higher levels of
recycled fiber use are attained, and in the magnitude of the final level of recycled fiber use. The
increased recycling scenario achieves 45 percent utilization by 2000 and maintains that level through
2040. This scenario, which was derived from suggestions by the American Paper Institute, assumes
that policies and programs are aimed at reducing volumes of waste (through more efficient product
use, public education, disposal fees, and other means).
Figure 5-1. Total Carbon Storage on U.S. Public and Private Timberland:
Increases Relative to Base Case for the Increased Recycling Scenario
1990
2000
2010
2020
2030
2040
Year
Sources: Turner, et al. 1993; Birdsey and Heath 1993
CARBON IMPACTS
Increasing the use of recycled fiber increases the supply of standing timber and the associated
carbon storage, as Figure 5-1 illustrates. Carbon storage above base case levels rises to between 400
and 600 million metric tons by the year 2040, a level that is comparable to that achieved by the large
scale tree planting programs discussed in Section 4.1 (the range reflects estimates from FORCARB
and from FCM). Because the gains in carbon storage under the increased recycling scenario depend
less on new growth than on conserving existing standing stock, increases in carbon occur more
rapidly than in the tree planting scenarios; more than half of the carbon accumulates by the year
36
-------
2010. Table 5-1 presents annual carbon accumulation at decadal intervals. The HARVCARB analysis
suggests additional average annual carbon accumulation in post-harvest pools of 1.9 million metric
tons of carbon per year, over the 50 years of the analysis. However, the potential climate impact
benefit of post-harvest carbon accumulation may be offset when the relative climate impact of
methane is taken into account (Turner, et al. 1993).
Table 5-1
Annual Carbon Accumulation on U.S. Public and Private Timberland Relative to Base Case
for Increased Recycling Scenario, Decadal Intervals (million metric tons)
2000
2010
2020
2030
Increased Recycling
13.5
15.6
10.0
4.4
Note: Forest carbon estimates are presented as an average of FORCARB and FCM results.
Source: Turner, et al. 1993; Heath 1993
TIMBER INVENTORY EFFECTS
As the demand for virgin fiber declines, fewer acres are harvested and timber inventories rise (see
Figure 5-2). Relative to the base case, softwood inventories in 2040 rise by about 5 percent, and
hardwood inventories rise by 7 percent. Overall harvest levels decline, as illustrated in Table 5-2. The
magnitude, as well as the pattern, of changes in harvests reflects the fact that some of the "savings" in
wood that would have been used as pulp for manufacturing paper and paperboard are being used for
the manufacture of other products, especially lumber, after the time lag needed for pulpwood-sized
trees to grow to sawtimber size.
Table 5-2
Changes in Harvest Levels for the Increased Recycling Scenario,
Relative to the Base Case (million cubic feet)
Region
North
South
Rockies
Pacific Coast
Total U.S.
2000
-154
-304
0
-14
-473
Hardwood
2020
-171
-285
0
-14
-470
2040
-123
-172
0
-8
-304
2000
-60
-580
-5
-160
-805
Softwood
2020
-60
11
-48
-187
-284
2040
-40
300
-17
-128
117
Note: Sum of regions may not equal totals because of rounding.
Source: Haynes, et al. 1994
37
-------
Figure 5-2. U.S. Softwood and Hardwood Inventory Projections for Privately Owned
Timberland: Base Case and Increased Recycling Scenario
I
-Base Case, Softwood
Base Case, Hardwood
Increased Recycling,
Softwood
-Increased Recycling,
Hardwood
Source: Haynes, et al. 1994
ECONOMIC AND TRADE EFFECTS
Because additional recycling reduces the demand for pulpwood, stumpage prices and revenues
to forest land owners decline over time under the increased recycling scenario relative to the base
case. Reduced harvest for pulpwood increases the future supply of sawtimber, thereby increasing
harvests of sawtimber and decreasing prices (see Table 5-3). Increases in the supply of sawtimber do
not happen immediately, but may lag more than 10 years behind the initial impacts of recycling on
pulpwood markets. Results are felt most strongly in the softwood and hardwood markets in the South,
which produces the bulk of the paper pulp consumed in markets that switch to recycled fiber.
Similarly to the tree planting scenarios, reduced sawtimber prices in the U.S result in decreased
imports from Canada. Softwood lumber imports from Canada drop significantly throughout the time
period and by over 4,600 million board feet in 2040, or 36 percent of base case imports in that year
(Haynes, et al. 1994).
5.2 REDUCED NATIONAL FOREST HARVESTS
The analysis of changing National Forest harvest levels examines the effects of harvest reductions.
These reductions result from elimination of harvest of old growth in the Pacific Northwest, protection of
spotted owl habitat in Washington, Oregon and California, protection of the red cockaded woodpecker
in the South, elimination of below cost timber sales, and elimination of harvesting in existing roadless
areas. As illustrated in Table 5-4, the overall level of National Forest harvest for the scenario is about
1.36 billion cubic feet in 2000 and 1.59 billion cubic feet in 2040, about 21 percent below harvest
levels in the base case. Harvest levels projected under the base case, for all public and private lands,
are presented by region in Table 5-5. Most of this analysis relies on the base case and models used
for the analyses of large scale tree planting presented in Section 4.1, and the CGTM provides
additional results.
38
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Table 5-3
Stumpage Prices In the Increased Recycling Scenario
(dollars per thousand board feet)
2000
Softwood Stumpage Prices
North 48
South 125
Rocky Mountains 99
Pacific Coast 241
2010
50
6
197
274
2020
63
29
190
274
2030
67
70
191
252
2040
75
165
202
236
Hardwood Sawtimber Stumpage Prices
United States 461 551
651
764
879
Source: Haynes, et al. 1994
Table 5-4
National Forest Harvest Under Base Case and
Reduced National Forest Harvest Scenario
(billion cubic feet)
Year
Base Case
Reduced Harvest
Scenario
1986
2000
2010
2020
2030
2040
2.07
1.54
1.64
1.70
1.74
1.78
2.07
1.05
1.08
1.09
1.11
1.11
Source: Haynes, et al. 1994
RESULTS; CARBON, TIMBER INVENTORY, ECONOMIC EFFECTS, AND TRADE
Timber inventory and carbon impacts for this scenario are modeled using the TAMM/ATLAS
system and the forest carbon models, FCM and FORCARB. The CGTM model provides additional
analysis of the impact of international trade linkages. Under this scenario, declines in timber
inventories result in intensified competition for the available timber and upward pressure on softwood
Stumpage prices. In regions where there are sufficient private timber supplies, however, decreases in
National Forest harvest are offset by increased timber harvests from private timberlands.
Overall, there is little change in the total timber inventory and, hence, in the total carbon stored on
U.S. timberland. Because of offsetting private harvests, total public and private harvest remain
relatively unchanged under this scenario, as does the carbon stored in the product and landfill pools.
It is important to note (as described in Box 4-1) that this analysis does not account for changes in
39
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management behavior in response to price signals, and likely overestimates the economic impacts of
these policies.
Table 5-5
Base Case Harvest Projections by Region:
Public and Private Timberland Owners
(billion cubic feet)
Region/Owner
North
Public
Private
South
Public
Private
Rockies
Public
Private
Pacific Coast
Public
Private
Total U.S.
Hardwood Harvest
2000 2020 2040
.2
1.8
.1
2.8
--
.1
.1
5.1
.3
3.8
.2
5.3
-
.3
g.g
.4
4.9
.3
5.3
--
.4
11.3
Softwood Harvest
2000 2020 2040
.1
.6
.4
5.3
.5
.3
1.8
2.1
11.2
.2
1.0
.4
5.6
.6
.5
1.3
2.3
11.8
.2
1.6
.5
7.5
.7
.6
1.3
2.9
15.4
Note: Hardwood harvest is reported for the West, i.e., Rockies and Pacific Coast combined.
Source: Haynes, et al. 1994
Private softwood inventory (which is illustrated in Figure 5-3) declines by about 1 to 2 percent over
the time period relative to the base case. This change in available timber supply affects the prices of
sawtimber and timber products. Softwood stumpage prices in all regions are significantly affected
through 2040, as a comparison of Tables 5-6 and 4-5 illustrates. Softwood stumpage prices on the
Pacific Coast, for example, are about 12 percent above the base case by the year 2040. Softwood
lumber prices, overall, are about 7 percent higher in 2040 than in the base case (Haynes, et al. 1994).
There are no significant impacts on hardwood timber inventories or hardwood saw timber stumpage
prices, illustrating the small role of National Forests in the hardwood sector.
Because of the lumber price increases, softwood lumber consumption declines slightly, by about
16 percent, and lumber imports from Canada rise by 10 percent by 2040 (Haynes, et al. 1994). The
increase in lumber imports comes progressively after 2010 because domestic production is reduced
as a consequence of the lower timber inventories and the associated higher prices.
The CGTM analysis provides slightly different results; higher Pacific Northwest log prices prompt
higher-cost producers to increase their production levels both internationally and domestically. Thus,
reduced harvests on U.S. public lands are replaced not only by large increases in supply from the
U.S. South, but also by increased production from Europe and possibly from mature softwood stands
in Siberia. In addition, CGTM projects non-wood product substitution to meet as much as one-third of
the supply reduction (Perez-Garcia 1993).
The CGTM results have several implications for the carbon and economic impacts of reducing
harvest levels in National Forests. The analysis using TAMM/ATLAS and FCM/FORCARB finds that
increased harvests on U.S. private timberland replace decreased harvests on public lands, resulting in
little net effect on total U.S. inventories or carbon flux from all U.S. timberland. The CGTM analysis
40
-------
Figure 5-3. U.S. Private Timber Inventory: Changes Relative
to Base Case for National Forest Harvest Scenario
1 -r
Softwood South
r
"
x
Softwood, All Regions
\
2000
Source: Haynes, et al. 1994
2010
2020
2030
2040
Year
finds, however, that a significant portion of the offsetting harvests occurs in countries other than the
U.S. (see Figure 5-4). Thus, carbon storage in U.S. forests could be higher in the reduced harvest
scenario than under the base case.13 The impacts on global carbon, however, are unclear and
depend on the relative productivity of the lands harvested in the U.S. and internationally, and on the
carbon impacts of substituting more energy-intensive products for forest products.
The CGTM analysis also shows economic surplus gains of $1.4 billion to timber producers
worldwide. U.S. producers experience a net welfare loss of almost $100 million. Economic losses to
lumber mills in the U.S. West are about $270 million, which are only partially offset by gains to mills in
the South and North of $56 million. Consumer surplus losses in the U.S., which total $971 million, are
evenly distributed among all regions (Perez-Garcia 1993).
5.3 INCREASED USE OF BIOMASS ENERGY
This analysis examines the implications of using existing forest resources in the U.S. to increase
the use of bioenergy for electricity generation. This analysis derives the wood energy (biofuel)
"1 *3
The CGTM analysis assumes that public harvests decline significantly in Western Canada, thereby reducing
potential timber supplies to the U.S.
41
-------
Table 5-6
Stumpage Prices In the Reduced National Forest Harvest Scenario
(dollars per thousand board feet)
2000
2010
2020
2030
2040
Softwood Stumpage Prices
North 53
South 208
Rocky Mountains 159
Pacific Coast 288
72
322
276
357
Hardwood Sawtlmber Stumpage Prices
United States 463 559
98
370
315
405
665
114
331
305
409
784
129
342
329
401
903
Source: Haynes, et al. 1994
Figure 5-4. Projected Global Production Increases in Response
to Habitat Preservation, by Region: 1995
38%
21%
20%
Q Europe
IBJapan
E3 Eastern Canada
E3 US North
0 US South
US West
D Product Substitution
12%
Note: Distribution reported as a percent of total production increase of
33.3 million cubic meters.
Source: Perez-Garcia 1993
scenario from the National Energy Strategy (NES) (USDOE 1991). The scenario assumes that wood
energy supply increases from 3.1 Quads in 2000 to 5.4 Quads in 2030, compared to the base case in
which wood energy supply increases from 1.8 Quads to 2.0 Quads over the same period (Colin and
Skog 1990). The scenario accounts for changes both in fuelwood consumption and in the proportion
of fuelwood that comes from the growing stock part of timber inventories (USDOE 1991). Harvest
projections for the base case and scenario are shown in Table 5-7.
42
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Table 5-7
Biomass Fuelwood Consumption: Assumptions
for Base Case and Biofuel Scenario, Decadal Intervals
Base Case Biofuel Scenarios
Year Softwood Hardwood Softwood Hardwood
Biomass Fuelwood Consumption (million cubic feet)
2000
2010
2020
2030
2040
883
1,207
1,312
1,271
1,219
3,377
4,395
4,420
4,113
3,875
1,030
1,650
2,160
3,040
3,200
3,940
6,020
7,200
9,890
10,070
Fuel from Non-growing Stock Sources (percent)
2000
2010
2020
2030
2040
85
85
86
85
86
75
76
77
77
77
73
82
70
61
67
73
82
70
61
67
Source: USDOE 1991, reported in Haynes, et al. 1994
The growing stock fraction is especially important in dealing with fuelwood demand on forest
resources. Of the approximately 737 million acres of forest land in the U.S., 47 million acres are
reserved from harvest, and 200 million acres are urban or low productivity forest land, leaving 490
million acres to support harvests for various products (Haynes, et al. 1994). Harvests for fuelwood
primarily come from urban forest land, low productivity forest land, or from residues left after logging.
There has, thus, been little actual harvest for fuelwood in some regions and, overall, the majority of
both hardwood and softwood fuelwood comes from non-growing stock, both currently and under the
base case and scenario projections. The percentage of fuelwood derived from growing stock (wood of
merchantable quality) is projected to increase in the NES scenario for both softwoods and hardwoods.
That increase, combined with the higher overall harvest level has dramatic effects on forest resources,
especially hardwoods.
TIMBER INVENTORY EFFECTS AND CARBON IMPACTS
Increasing the production of energy from biomass has three distinct effects on CO2 emissions:
(1) CO2 is released when the wood is combusted to produce energy; (2) carbon is sequestered
during the growth or regrowth of forests harvested for biofuels; and (3) carbon emissions are
"avoided" when fossil fuel combustion is displaced by bioenergy. Removing wood for biofuels initially
has the effect of reducing the carbon inventory on the forest base.14 Over time, however, regrowth
on harvested lands replaces the biomass carbon. The real benefit to the atmosphere occurs as wood
displaces fossil fuels, and the CO2 emissions from burning wood are absorbed by regrowing forest.
Strategies that plant dedicated energy crops will initially increase the carbon inventory prior to harvesting,
unlike strategies that harvest existing forests.
43
-------
Figure 5-5. Total Carbon Storage on U.S. Public and Private Timberland:
Changes Relative to Base Case for Increasing Biomass Energy Scenario
2010
2020
2030
2040
Year
2000
Sources: Lee 1993c; Heath 1993
The considerably greater harvest levels associated with increased biofuels utilization result (by
2040) in a large reduction in the U.S. timber inventory and, thus, the total carbon pool, relative to the
base case. Estimates of the changes in carbon storage and inventory are shown in Figures 5-5 and
5-6, respectively. The large declines in timber inventory and carbon displayed in these figures result
from several factors. First, the additional biofuel harvest levels under this scenario are large; in 2010,
additional biofuel harvest over the base case is about 37 percent over the base case, and as large as
the total harvest from National Forest lands in 1990. These increases in harvest leave gaps in the
inventory that cannot be filled until the forest regenerates. Because hardwoods, which in general
regenerate more slowly than softwoods, supply much of the harvested timber, regrowth lags
significantly behind harvest, and the inventory shows large declines throughout the time period.
Second, the volume of harvest rises almost uniformly throughout the time period of the scenario
analysis, relative to the base case. As more volume (and more acreage) is being harvested in each
succeeding decade than is being regenerated, the regeneration cannot keep pace with the size of the
harvest. This result is mirrored in the increasingly steeper downward trajectory of carbon storage
losses in the first four decades of Figure 5-5. As the size of the increase abates towards the end of
the simulation period, regeneration begins to catch up with the harvest, and carbon losses from
inventory level out in Figure 5-5. The depletion of inventory and the carbon pool could be mitigated to
some degree, but not prevented, by taking more of the harvest volumes from southern softwoods,
which grow and regenerate faster than hardwoods.
Last, as discussed in Section 3, the analysis does not take into account the carbon contained in
timber stands before they reach merchantable size (see Box 3-2). Accounting for biomass in stands in
the first few years after harvest might therefore reduce the size of the depletion in inventory. A rough
calculation of carbon in young stands suggests that the results of this scenario analysis are not
changed significantly by such inclusion (Birdsey 1995).
44
-------
Figure 5-6. U.S. Private Timber Inventory: Changes Relative to
Base Case for Increasing Biomass Energy Scenario
2040
Source: Haynes, et al. 1994
On balance, the results suggest that large increases in the rate of removal of standing inventory
immediately deplete forest inventories and carbon pools, and that depletion effect is maintained or
magnified when the size of the harvest increases over time. The carbon pool is likely to return to a
point of no net loss, compared with the baseline, when harvest volumes reach a steady state,
although the analysis was not carried out far enough to confirm this.
AVOIDED FOSSIL FUEL EMISSION: NET CARBON IMPACTS
Although the combined forest inventory and carbon models do not produce estimates of the
impact on CO2 emissions of displacing fossil fuels in the bioenergy scenario, projected harvest levels
can be used to estimate these carbon benefits. The magnitude of avoided emissions depends on a
number of factors, including the energy content of the biomass, the heat rate of the biomass-fired
energy technology, and the carbon intensity of the displaced fossil fuel. Cumulative emissions avoided
by the year 2040 could, however, under a reasonable set of assumptions, range between 470 and 840
million metric tons of carbon with a mean of about 650 million metric tons (ICF 1995).
Including avoided emissions does not completely offset the reduced carbon storage due to
increased harvest until the final decade reported here. Table 5-8 presents annual carbon accumulation
in forest ecosystems at decadal intervals, avoided carbon emissions from displaced fossil fuel use, as
well as total net accumulation under this scenario. Savings of fossil fuel emissions do not completely
offset forest carbon losses because fossil fuels (especially coal) are more efficient, or have a higher
energy content per ton of carbon, than wood. Consequently, more tons of wood must be burned to
create the same amount of energy produced by a given tonnage of fossil fuel.
This result makes an important point. Even when considering the contribution of an offset in the
use of fossil fuels, harvesting an additional portion of existing forest resources for bioenergy depletes
forest carbon pools, and will not fulfill greenhouse gas mitigation objectives in the short term, and
45
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Table 5-8
Annual Carbon Accumulation on U.S. Public and Private Tlmberland Relative to Base
Case for Increased Use of Blomass Energy, Decadal Intervals (million metric tons)
2000
2010
2020
2030
Forest Carbon
Avoided Fossil
Fuel Emissions
Net Carbon
Flux
-7.3
2.6
-4.7
-17.8
7.5
-10.3
-29.6
13.2
-16.4
-21.1
27.5
6.4
Note: Forest carbon estimates are derived as an average of FORCARB and FCM results. Avoided fossil
fuel omissions are an average of results assuming the displacement of coal and gas-fired generation.
Sources: Birdsey and Heath, 1993; Lee 1993; ICF 1995
possibly in the medium term. Once the forest returns to a steady state where removals and
regeneration balance, the fossil fuel offset would probably be a net contribution to greenhouse gas
abatement. The results suggest that a forest bioenergy strategy that uses wood from plantations
established in advance for growing biofuel stocks would mitigate the adverse impacts on forest
inventories and carbon pools of a significant biomass harvest. Combination scenario 3, below,
addresses that situation. Additional planting and regrowth would further mitigate the impacts of
harvest on carbon storage. Forestation can also mitigate increases in stumpage prices that occur in
the biomass energy scenario, presented in Table 5-9.
Table 5-9
Stumpage Prices in the Increased Biomass Energy Scenario
(dollars per thousand board feet)
2000
2010
2020
2030
2040
Softwood Stumpage Prices
North 52 76
South 183 278
Rooky Mountains 106 233
Pacific Coast 254 332
Hardwood Sawtimber Stumpage Prices
United States 465 565
103
345
291
392
685
125
341
342
420
827
150
358
339
425
947
Source: Haynes, et al. 1994
5.4 EFFECTIVENESS OF COMBINED SCENARIOS
In reality, climate change mitigation activities are unlikely to be implemented singly or in a policy
vacuum. The U.S. Climate Change Action Plan, for example, identifies some 44 climate change
46
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mitigation activities for simultaneous implementation (White House 1993). The analyses considered
thus far in this report as well as most analyses of climate change mitigation options examine the
carbon, timber, and economic impacts of isolated policies. The impacts of policies implemented jointly,
however, may differ from those suggested by inspecting the results for individual policies, because of
complementary, synergistic, or competing effects across the policies. To investigate the impacts of
broader forest sector strategies, this report analyzes several additional scenarios that combine policies
reported earlier in Sections 4 and 5.
Analyzing combined scenarios allows an evaluation of the relative success or failure of jointly
executed programs in achieving the competing goals of maximum carbon sequestration and minimum
economic disturbance. There are, thus, two key reasons to analyze the impacts of simultaneous
implementation of forest sector policies. First, combining policies can increase the aggregate carbon
sequestration that is achieved. Because most of the forest sector policies considered in this report act
to expand the forest carbon sink, combining policies is likely to have additive impacts on aggregate
net carbon sequestration. Whether these impacts are, indeed, additive (or less or more than additive),
can be a consideration in appropriately devising, and analyzing the cost-effectiveness of, policy
strategies to sequester carbon in the forest sector.
Second, many of the policies, taken in isolation, potentially have adverse economic impacts on at
least some groups in the forest sector, because of price and other market effects (such as changes in
trade flows). Combining policies that have opposite impacts, e.g., those that create upward pressure
on prices by reducing timber supply and those that create downward pressure on prices by reducing
timber demand, can result in less economic disruption than occurs under the individual policy
scenarios. Again, confirming this result and understanding the net impacts of these offsetting effects
solidifies the analytical underpinnings of the analysis of the economic impacts of forest sector carbon
sequestration actions.
Table 5-10
Combination Scenarios
Scenario
Reduced National
Forest Harvest
Increased Biofuels Low Enrollment
Recycling $220 million funding
Combination 1
Combination 2
Combination 3
Combining scenarios, thus, presents an opportunity to evaluate the carbon, timber, and economic
consequences of a coordinated forest sector strategy to sequester carbon. The three combination
scenarios analyzed are described in Table 5-10. Strategy 1 combines reduced National Forest harvest
with increased paper recycling. These two policies have positive or no (and, hence, complementary)
impacts on carbon accumulation and opposite (and, hence, offsetting) impacts on prices and
economic welfare. Strategy 2 combines the first strategy with the increased production of biomass
energy; this addition would tend to reduce the carbon stored on timberland (relative to Strategy 1)
and to aggravate the upward pressure on prices created by reduced harvest of National Forests. The
third strategy adds large-scale tree planting to the second strategy.15 The addition of this scenario
would tend to offset the declines in timber inventory and carbon storage associated with the biomass
energy scenario, and provide offsetting downward pressure on softwood stumpage prices.
15
' The afforestation program added to the Combination 3 analysis is the low enrollment distribution (Moulton
and Richards 1990) with an annual funding level of $220 million for 10 years.
47
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IMPACTS ON TIMBER INVENTORY AND CARBON ACCUMULATION
Figure 5-7 displays the impacts of the combined scenarios on total carbon storage, using the
results from the FCM carbon model. Figures 5-8 and 5-9 display the underlying changes in U.S.
private softwood and hardwood timber inventories over the period of the analysis. Because there is
little change in net carbon accumulated over the base case in the reduced harvest scenario, the
carbon impacts of the increased paper recycling scenario, reported earlier in Section 5, are similar to
those of combination 1 (illustrated in Figure 5-7). As would be expected, the incremental carbon
stored, relative to the base case, is lower for combination 2 than for combination 1, because of the
addition of the increased biomass energy scenario, which reduces the timber inventory substantially.
Adding an aggressive tree planting program (the third combination) further increases the carbon
benefits of forest sector policies. Table 5-11, which presents net annual carbon accumulation in
the forests at decadal intervals for the FCM model, displays analogous results.
Figure 5-7. Total Carbon Storage on U.S. Public and Private Timberland:
Changes Relative to Base Case for Combined Scenarios
Combination 1
2030
2040
Source: Lee 1993c
16 Using the high, rather than the low, enrollment assumptions for the $220 million afforestation program in
combination 3 would not change the overall results dramatically, although the net accumulation of carbon would
exceed that in Figure 5-7.
48
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Figure 5-8. U.S. Private Softwood Timber Inventory: Changes
Relative to Base Case for Combined Scenarios
20-r
Combination 3
Combination 2
2000
2010 2020
Year
2030
2040
Source: Haynes, et al. 1994
Figure 5-9. U.S. Private Hardwood Timber Inventory: Changes
Relative to Base Case for Combined Scenarios
20--
15-
10-
5--
0- -
-5--
-10
-15--
-20--
-25 J-
1990
Combination 1
Combination 2
Combination 3
2000
2010 2020
Year
2030
2040
Source: Haynes, et a!. 1994
49
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Table 5-11
Annual Carbon Accumulation on U.S. Public and Private Timberland Relative to Base Case
for Combined Scenarios, Decadal Intervals (million metric tons)
Combination 1
Combination 2
Forest Carbon
Avoided Fossil
Fuel Emissions
2000
10.6
4.2
2.6
2010
13.0
-3.8
7.5
2020
8.8
-23.8
13.2
2030
3.7
-24.2
27.5
Net Carbon Flux
Combination 3
Forest Carbon
Avoided Fossil
Fuel Emissions
Net Carbon Flux
6.8
10.1
2.6
12.7
3.7
11.0
7.5
18.5
-10.6
-6.6
13.2
6.6
3.3
-12.7
27.5
14.8
Noto: Forest carbon estimates are derived from the FCM model. Avoided fossil fuel emissions are an average of results
assuming the displacement of coal and gas-fired generation.
Sources: Lee 1993c; IGF 1995
ECONOMIC IMPACTS
In Table 5-12, stumpage prices over the time frame of the analysis are provided for each of the
combined scenarios. In combination 1, stumpage prices for softwood, are higher than for the recycled
fiber scenario and lower than the harvest reduction scenario. Prices do not, however, return back to
base case levels, demonstrating (in this case, at these levels of activity) that increased use of recycled
fiber utilization has more of an effect on prices than do the public harvest reductions. Similar trends
are evident for these scenarios in consumer and producer surplus, and stumpage producer
(landowner) surplus (Haynes, et al. 1994).
Adding a large biomass energy program based on existing wood resources from the forest sector
increases prices over the first combination, as the large draw on the forest resource for biofuel feed
stocks depletes timber supplies. The magnitude of the price change varies by region, with those
regions supplying the most additional biomass for energy experiencing the largest price increases.
Stumpage suppliers gain somewhat in economic welfare, but other economic players (consumers and
product producers) show almost no change in welfare compared to the base case (Haynes, et al.
1994).
Finally, the third combination scenario adds an aggressive tree planting program. Economic
impacts vary, with the most severe effects experienced in South for the latter decades of the analysis,
when the large increase in timber inventories from federally subsidized tree planting undermines the
stumpage market and drives prices down. This analysis suggests that a bioenergy program that
draws extensively on Southern timber markets could raise demand enough to partially offset the
negative impacts of a large tree planting program. The addition of a tree planting program mitigates
the price increases stimulated by the bioenergy program in the second combination, and prices in
some regions and years falls below those in the base case. Here again, the presence of other
activities in the combination reduces the adverse economic impacts of a tree planting program
implemented by itself.
50
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Table 5-12
Stumpage Prices in the Combination Scenarios
(dollars per thousand board feet)
2000
Combination 1
Softwood Stumpage Prices
North
South
Rocky Mountains
Pacific Coast
Hardwood Sawtimber Stumpage
United States
Combination 2
Softwood Stumpage Prices
North
South
Rocky Mountains
Pacific Coast
Hardwood Sawtimber Stumpage
United States
Combination 3
Softwood Stumpage Prices
North
South
Rocky Mountains
Pacific Coast
Hardwood Sawtimber Stumpage
United States
52
161
155
280
Prices
461
53
161
150
282
Prices
462
53
161
161
286
Prices
462
Note: "*" indicates prices outside the range of model
2010
56
67
224
314
551
71
102
241
326
557
71
78
220
327
557
results.
2020
73
111
238
317
651
100
134
261
339
671
100 .
30
245
324
668
2030
80
168
264
305
764
125
202
329
341
813
125
*
273
299
810
2040
94
253
232
287
879
157
261
333
337
935
157
*
232
280
931
Source: Haynes, et al. 1994
6. MODIFIED AGRICULTURAL PRACTICES
Agricultural soils store an estimated 1.5 trillion metric tons of carbon, which is about twice the
amount held in the atmosphere (Post, et al. 1990). Modifying current agricultural practices to increase
or maintain this carbon sink may have a significant effect on the flux of carbon between agricultural
soils and the atmosphere. Possible alternative management strategies include modifying tillage
practices, using winter cover crops, changing crop rotations, and altering the extent or composition of
51
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fertilizer use. Specifically, this section analyzes two types of scenarios: (1) increased use of
conservation tillage practices; and (2) increased planting of winter cover crops. Conservation tillage
can reduce the loss of soil organic carbon by decreasing the soil disturbance of conventional tillage;
using winter cover crops can increase the stored carbon in agricultural soils by expanding biomass
production on existing farm lands.
These practices can also affect the release of soil N2O. Although the magnitude of N2O emissions
is much smaller than that of CO2, because the global warming potential of N2O is 270 times that of
CO2 the potential impacts on global warming may be significant. While preliminary results indicate that
these policies may also reduce N2O emissions (Cialella and Li 1993), because of the complex
interactions between carbon and nitrogen emissions from agricultural soils no quantitative results are
presented.
The analysis of agricultural management practices was conducted by integrating the RAMS
economic model with the CENTURY soil carbon model, with the use of GIS analysis to combine
results and incorporate meteorologic and soils databases. As described in Section 3, the RAMS model
is a short-term, profit maximizing model, which is used in this analysis to determine detailed
production activities (e.g., crop rotations, tillage, and irrigation) under the constraints of the scenarios
chosen for this report. The production activities determined in the RAMS analysis for each area of the
study region are used by the CENTURY model to estimate the associated soil carbon impacts with a
high level of regional detail. The DNDC (Denitrification and Decomposition) model was used to validate
the results of the CENTURY model, and to assess potential impacts on N2O emissions.
The RAMS model focuses on the Midwestern and Central U.S. (see Figure 6-1), which comprises
about 216 million acres, or 60 to 70 percent of the agricultural cropland in the contiguous U.S.
(Donigian, et al. 1994). Because factors that influence soil carbon and economic impacts, such as soil
type, season length, and management practices (e.g., crop rotations), vary significantly from region to
region, the results presented below cannot be directly generalized to all regions in the U.S.
Nevertheless, given the magnitude of the RAMS study region, they indicate that modifying agricultural
management practices can significantly increase the accumulation of soil carbon.
6.1 MODIFIED TILLAGE PRACTICES
Modifying tillage practices can have significant impacts on the sequestration of carbon in
agricultural soils, soil erosion, and economic welfare. In this analysis, four types of tillage practices are
modelled: conventional spring and fall tillage, reduced tillage, and no-tillage. These four practices
differ in important physical aspects, such as the frequency and depth of plowing, as well as other
tillage operations, resulting in different transfers of carbon and nitrogen between various above and
below ground pools. Depending on a range of regional factors captured in the models, such as crop
rotation, soil type, climate, and management practices, the reduced disturbance of the soil using
conservation tillage practices (i.e., reduced tillage and no-tillage) may increase the retention of soil
organic carbon relative to conventional tillage.
The impacts of these tillage practices are assessed using four scenarios that represent
progressively greater acreages of farmland managed with conservation tillage practices. Figure 6-2
shows the degree to which each tillage practice is used in each scenario. These scenarios were
developed by targeting the application of conservation tillage practices on agricultural lands with the
highest erodibility indexes (El). By including land with progressively lower El ratings (i.e., implementing
conservation tillage on progressively less erodible land), more land is managed with these practices.
The low, medium, and high conservation scenarios shown in Figure 6-2 have minimum El limits of 8, 5,
and 2, resulting in the inclusion of 18, 27, and 53 percent of U.S. agricultural land, respectively. The
targeting of highly erodible lands in these policy scenarios has the additional benefit of reducing soil
erosion on agricultural lands.
52
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Figure 6-1. RAMS Study Region
Source: Donigian, et al. 1994
The base case (status quo) scenario, as defined by the RAMS model, is based on data for the
1990 growing season. The use of conservation tillage may, however, already exceed levels
comparable to the medium conservation scenario. If the actual "no-policy" base case has a higher use
of conservation tillage than the base case used in the current analysis, then aggressive policies (i.e.,
high conservation) will in fact be easier and less costly to implement, although carbon sequestration
benefits will also be reduced. Nevertheless, the results presented in the next section indicate the
potential importance of promoting conservation tillage.
CARBON IMPACTS: SOIL ORGANIC CARBON
In general, the modelssshow a net accumulation of carbon in agricultural soils within the RAMS
study region, resulting in an increase in soil organic carbon of 26 to 52 percent by 2030, depending
on tillage practices, crop yield increases, and other assumptions. The low conservation scenario
results in roughly a 1 percent increase in soil carbon levels relative to the base case by 2030, while
the medium and high scenarios result in 2 and 6 percent increases, respectively. These increases
correspond to average annual carbon accumulations above base case levels of 0.25, 0.5, and 2.5
million metric tons for the low, medium, and high conservation scenarios, respectively (see Table 6-1).
17 Soil organic carbon refers to carbon in the first 20 centimeters of the soil profile, including roots and surface
residues.
53
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Figure 6-2. Tillage Distributions for Alternative Scenarios
Status Quo/Base Case
Low Conservation
Medium Conservation
High Conservation
Source: Donigian, et al. 1994
Table 6-1
Soil Organic Carbon Accumulation for the Conservation Tillage Scenarios
in the RAMS Study Region (million metric tons)
Scenarios
Base Case
Low Conservation
Medium Conservation
High Conservation
Carbon
Accumulation
1990-2030
1,800
1,810
1,820
1,900
Percent
Increase from
1990 Value
49%
49%
50%
52%
Percent Increase
above Base
Case
--
1%
2%
6%
Average Annual
Carbon
Accumulation Above
Base Case
--
0.25
0.50
2.50
Noto: These results assume an annual crop yield increase of 1.5%,
Source: Donigian, et al. 1994
The potential of conservation tillage practices to increase carbon sequestration is greatly affected
by factors such as crop yield, crop rotation, and regional variations in soil type, geography, and
season length. As a result of these variations, the aggregate results presented here cannot be
generalized to specific land areas. The impacts of any policies to encourage conservation tillage will
54
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depend greatly on which agricultural lands, and associated production activities, are targeted. Box 6-1
provides an illustration of the regional variation of crop rotations and tillage practices, and their
importance for soil carbon results. The remainder of this section discusses how the analysis
addressed each of these factors, and their impact on soil carbon results.
Box 6-1
The Effects of Crop Rotation, Tillage practice, and
Climate on Soil Carbon for Two Neighboring Climate Divisions
As an example of how sail carbon varies wtth crop rotation, tillage practice, and Ottmate Division,
consider the example of two neighboring Climate Divisions. CD 312 is in the eastern-most part of the
stuoy region on the border of Ohio and West Virginia. This CD attains its highesl levels of soft carbon
for a rotation of corn Sitage-corn silage-Soybean, for which, by the year 2030, soil carbon levels reach
10fQ96 gC/m2 for Reduced Tilt and tO,400 gC/ra2 for Mo-Till. When this rotation is replaced by Com-
Corn*$0ybean* However, soil carbon Is only 6,925 gC/m2 under Deduced Tl and 7,221 gC/m2 under
NO-Til). , ,
Considering the exact same two crop rotations and tillage practices-in the neighboring Climate
Division 313 (same Production Area, different climates, on the Wesi Virginia-Kentucky border) produces
a significantly different story* For the Corn Silage-Corn Silage-Soybean rotation, by the year 2030, soil
carbon levels reach 8,413 gG/m2 for Reduced Till-and 8,526 gC/m2 for No-TiB. When this rotation is
replaced by eorn-com-soybean,. however* sol carbon is only 5,415 gc/mF under Reduced Till and
5,758 gG/m2 under No-Till.
It should be noted, however, that even the initial soil carbon levels were somewhat different for the
two CDs, in 1880, soil carbon was estimated at 3,543 gC/m2 irt OD.,312, white in OBu3i3f SOG.was
only 3,105 o,G/nr< Thus, although soil carbon increases in CO 312 were indeed higher in percentage
terms than in CD 312y they were not quite as high as the'absolute projections would otherwise indicate.
Source: Ooniglar), et aft. 1994 _, ,, , ^
Crop Yield. Crop yield can have several important effects on the soil carbon impacts of
conservation tillage policies. First, potential short term crop yield decreases following the introduction
of conservation tillage may deter individual producers from changing tillage practices, and also may
influence the choice of crop rotations. Second, assumptions about long term annual crop yield
increases have a large impact on total carbon accumulation.
Although implementing conservation tillage practices may not have a significant long term impact
on crop yield, lower yield may be expected during the initial adoption period as producers learn to use
the new tillage systems (Cruse 1992). The magnitude of such losses will affect the degree to which
conservation tillage practices are adopted. With small or negligible economic losses, gains realized
from reduced soil erosion may be sufficient to make conservation policies widely appealing, while
large initial losses may hinder implementation.
Two alternative assumptions are evaluated in order to assess the impact of short term crop yield
decreases. The first assumption keeps crop yields roughly the same for both conventional and
conservation tillage practices; the second assumes 5 and 10 percent yield reductions for reduced till
and no-till practices, respectively. As shown in Table 6-2, these assumptions affect the acreage of
farmland on which conservation tillage practices are employed, and thus reduce carbon accumulation
within the study region. Crop yield decreases also affect the type of crop rotations used, which, as
described below, have a large impact on carbon accumulation. Table 6-3 illustrates the variation in
major crop rotations under different conservation targets and short term yield assumptions.
55
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Table 6-2
Impact of Short Term Yield Assumptions on the Introduction of Conservation Tillage
(percent change in acreage of each tillage practice)
Conservation Tillage Targets
Low Conservation High Conservation
Reduced Yield No Yield Change Reduced Yield No Yield Change
Tillage Practice
Conventional Tillage/
Fall Plow
-7%
-2%
-46%
-44%
Conventional
Tillage/Spring Plow
Reduced Tillage
No-Tillage
-4%
9%
48%
-7%
7%
69%
-32%
56%
401%
-33%
8%
905%
Source: Bouzaher, et al. 1993
Table 6-3
Impact of Short Term Yield Assumptions on Major Crop Rotations
(percent change in acreage of each crop rotation)
Crop Rotation
Key: CRN Corn for grain
HLH = Legume hay
NLH = Non-Legume hay
Source: Bouzaher, et al. 1993
Base Case
Conservation Tillage Targets
Low Conservation High Conservation
Continuous CRN
CRN CRN SOY
CRN SOY WWT
Continuous HLH
Continuous NLH
8.36
7.11
23.87
8.43
8.34
Reduced
Yield
8.37
7.22
23.92
8.43
8.39
No Yield
Change
8.42
6.03
25.03
8.34
7.94
Reduced
Yield
7.96
7.13
24.23
7.63
6.96
No Yield
Change
8.71
6.39
24.82
8.45
6.65
SOY = Soybeans
WWT = Winter wheat
The second analysis examines the significance of annual increases in crop yield during the
simulation period. Higher crop yields will increase soil carbon accumulation because, for a given set of
production activities and conditions, more biomass is produced and subsequently returned to the soil.
A 1.5 percent annual increase in crop yield, based on historic data and projected future yields, was
used for the results presented in this section. For comparison, analyses were also conducted
assuming percentage increases of 1.0 and 0.5. Although total carbon accumulated on agricultural land
rises with the assumed yield level, the absolute amount of carbon accumulated in the scenario over
the base case is relatively insensitive to the yield level (Donigian, et al. 1994).
56
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Crop Rotation. Carbon sequestration depends on the specific crop rotation that is in production,
in large part because crop rotations return different quantities of biomass to the soil. For example,
crop rotations involving spring wheat sequestered 30 to 60 percent less carbon than continuous corn
planting, and crop rotations involving hay sequestered 60 percent less carbon than spring wheat
(Donigian, et al. 1994; Cialella and Li 1993). Thus, the targeting of specific production regimes, and
effects that alter crop rotations (i.e., short term yield decreases), can influence the soil carbon impacts
of conservation tillage policies.
Regional Variation. Variation in regional characteristics, such as soil type, geography, and season
length, also affects carbon accumulation in agricultural soils. To analyze this effect, the study region
was divided into 80 climate divisions (CDs). Table 6-4 provides an illustration of the regional
differences in soil organic carbon impacts by showing results for five different CDs with the same crop
rotation (corn - soybeans). Even for the two neighboring CDs (CD272 and CD321), percent increases
in soil carbon levels differ by 10 to 20 percent.
Table 6-4
Regional Variation In Soil Carbon Accumulation
(percent increase in soil carbon, 1990-2030)
Tillage Practice
CD272
(NW Ohio)
CD321
(W Ohio)
CD392
(S Minnesota)
CD413
(Iowa)
CD603
(W Missouri)
Conventional Till/
Spring Plow
45%
53%
37%
20%
64%
Reduced Till
No-Till
50%
61%
58%
68%
40%
52%
23%
36%
69%
78%
Note: Most CDs cross one or more state boundaries. The primary state is listed for each CD.
Source: Donigian, et al. 1994
AGRICULTURAL IMPACTS: SOIL EROSION AND NET RETURN PER ACRE
Soil erosion rates decrease under the more aggressive conservation tillage scenarios. For the low
conservation case, soil erosion rates are reduced by approximately 3 percent from base case levels.
In the high conservation case, erosion drops by 23 to 34 percent from erosion rates in the base case,
depending on the short term crop yield decreases and other assumptions (Bouzaher, et al. 1993).
Economic impacts in the agricultural sector depend primarily on assumptions about crop yield
changes. Without yield decreases, net returns increase relative to the base case by $0.67 per acre
(0.8 percent) under the low conservation scenario, and by $4.73 per acre (5.4 percent) under the high
conservation scenario. If lower yields are assumed with conservation tillage practices, then net returns
decrease by $3.07 per acre (3.4 percent) under the low conservation scenario, and by $2.93 per acre
(3.3 percent) under the high conservation scenario. These results reflect the change in both crop
revenues (which decline if yields fall) and production costs (which are lower with conservation tillage).
If yields are assumed to remain constant, then revenues also remain constant and the reduced
machinery costs associated with using conservation tillage practices result in increased net returns. If
yields are assumed to decrease, then the lower revenues associated with decreased yields are not
fully offset by reduced machinery costs. In either case (i.e., with or without yield adjustments), net
returns per acre are greater under the high conservation scenario than under the low conservation
scenario (Bouzaher et al. 1993).
57
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6.2 WINTER COVER CROPS
Winter cover crops can increase soil carbon, but are only appropriate for use on a fraction of U.S.
agricultural land due to restrictive crop rotations, growing season lengths, and climates. Based on
these factors, approximately 5 to 10 percent of the land in the RAMs mode! was targeted as being
suitable to establish winter cover crops. The desired sequence of crop rotation for winter cover crops
was small grains or silage followed by crops not seeded in the fall. Crops seeded in the fall (e.g.,
winter wheat and leguminous and non-leguminous hay) already provide for winter cover, while the
growing period for winter cover crops was greater following crops with early harvest dates.
Figure 6-3 provides a breakdown of how crop rotations would change if winter cover crops were
introduced on suitable land. In addition to timing issues (crop rotation, and harvest and planting
dates), the availability of water is a limiting factor. For example, some planting areas in the West do
not have enough water to support a winter cover crop, whereas the longer growing seasons in the
South allow substantial growth.
Figure 6-3. Major Rotations: Base Case and Targeted Levels of Winter Cover Crops
(percentage of total acres)
Base Case
Winter Cover Crops
Ccrtnuccs CRN
Rye Cover
CRN CRN SOY 4% Continuous CRN
7%
CBNSOV Other Rotations
35* 35%
CRN SOY WWT
0%
Continuous HLH
7%
___^___ SMF SWT
Continuous NLH VMch cr 5%
Source: Bouzaher, etal. 1993
Of the cover crops planted, 55 percent by acreage were rye and 45 percent were hairy vetch,
which is often used to fix nitrogen. In the scenarios evaluated, rye cover was used with corn-soy-winter
wheat, corn silage-soy-legume hay, and sorghum-winter wheat rotations. Hairy vetch cover was
planted with the corn-soybean-winter wheat rotation.
RESULTS: CARBON, ECONOMIC, AND AGRICULTURAL IMPACTS
Where appropriate, policies to promote cover crops have the potential to increase soil carbon
levels significantly. Although only a small fraction of the agricultural land would be included in such a
58
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scenario, there is a net soil carbon accumulation above the base case of roughly 140 million metric
tons of carbon into soil by 2030, or an average annual carbon accumulation of 3.5 million metric tons
(see Table 6-5).
Table 6-5
Soil Organic Carbon Accumulation for the Winter Cover Crop Scenario
(million metric tons)
Scenarios
Status Quo
Winter Cover Crops
Carbon Accumulation
1,800
1,940
Percent
Increase
from 1990
Value
49%
53%
Percent
Increase above
Base Case
--
8%
Average Annual
Carbon Accumulation
above Base Case
--
3.5
Note: These results assume an annual crop yield increase of 1.5%.
Source: Donigian, et al. 1994
Because carbon sequestration is sensitive to the rate at which crop yield is assumed to increase
over time, alternative assumptions of annual increases in crop yield of 0.5, 1.0, and 1.5 percent were
examined. As with the conservation tillage analysis, lower crop yield increases result in similar soil
carbon accumulation relative to the base case, despite lower absolute soil carbon levels by the end of
the study period (Donigian, et al. 1994).
Average net returns are reduced by 1.2 percent, or $1.05 per acre.18 Soil erosion is also
reduced by using winter cover crops in the model, with average soil erosion rates decreasing from
4.51 tons per acre to 4.39 tons per acre, a decline of almost 3 percent (Bouzaher, et al. 1993).
7. CONCLUSIONS: DIRECTIONS FOR FUTURE RESEARCH
The results of the preceding sections suggest that a variety of strategies, in both the forest and
the agriculture sectors, could reduce emissions of greenhouse gases or increase the carbon stored in
biomass and soil. Such policies could also have significant impacts (in some regions or nationally) on
product prices, forest and agricultural production, consumer and producer welfare, and trade. Thus,
research at the U.S. EPA and its collaborators in the U.S. Forest Service, at universities, and at private
research organizations, continues to address outstanding questions.
For the tree planting and other forest policy scenarios, which (with the exception of biofuels)
sequester carbon primarily by enlarging the acreage devoted to trees over time, both economic and
carbon impacts depend critically on how private forest land owners respond to changing inventories
and prices over time. Economic impacts also depend oh interactions between the forest and
agriculture sectors, which influence both the cost of land available for tree planting (and, hence, the
cost of government-subsidized planting) and also affect consumer and producer welfare in agricultural
and forest markets. Research continues to address these questions, and to investigate issues related
to other aspects of the forest-climate change link, such as the impacts of alternative management
strategies on public and private lands, improving the data on all portions of the forest sector carbon
budget, and continuing to evaluate the effects of climate change on forests.
18 This decrease includes the fact that cost is partially offset by using hairy vetch as a winter crop, since it fixes
nitrogen, thus resulting in nitrogen savings.
59
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The analyses of policy scenarios that change agricultural practices have focused on a few of the
agricultural areas located in the central United States. Estimating the implications for national GHG
emissions of changing agricultural practices requires understanding how these results can be
generalized to all regions, which may require additional data on selected crops (such as soybeans),
regions, and tillage practices. Other areas requiring further investigation include: improved estimates
of impacts of policies on crop yields; impacts of climate change on carbon sequestration; physical
impacts on the carbon and nitrogen balances of animal waste applications; a more thorough
investigation of the impact of No-Till practices on soil carbon levels; and better tracking of erosional
soil organic carbon losses.
60
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