The U.S. Department of Agriculture (USDA) prohibits discrimination in its programs and

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To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room

326-W, Whitten Building, 14th and Independence Ave., SW, Washington, DC 20250-

9410, or call (202) 720-5964 (voice and TDD). USDA is an equal opportunity provider

and employer.

Cover: Soil scientists Harry Pionke (left) and Ron Schnabel examine a switchgrass stand.

If switchgrass were to become a major crop, it could add up to $5 billion to farmers' income

and contribute to the reduction of the United States' dependence on oil imports.

Photo by Scott Bauer.

USDA ARS Photo Library Image Number K7956-15.
Daniel G. De La Torre Ugarte

Marie E. Walsh

Hosein Shapouri

Stephen P. Slinsky1

February 2003

1 Authors are Research Assistant Professor at the University of Tennessee Agricultural Policy Analysis Center (APAC), Economist at the Oak Ridge National Laboratory, (DOE-ORNL); Economist at the

Office of Energy Policy and New Uses (USDA-OEPNU); and Research Associate at APAC.

The Economic Impacts

of Bioenergy Crop Production

on U.S. Agriculture

i
 ii

This research is sponsored by USDA and DOE and performed in part at Oak Ridge National Laboratory. ORNL is

managed by UT-Battelle, LLC under US-DOE contract number DE-AC05-00OR22725.
The Economic Impacts of Bioenergy Crop Production on U.S. Agriculture.

By Daniel G. De La Torre Ugarte, Marie E. Walsh, Hosein Shapouri, and Stephen P. Slinsky. U.S. Department of

Agriculture, Office of the Chief Economist, Office of Energy Policy and New Uses. Agricultural Economic Report No. 816

Abstract

In response to energy security concerns, alternative energy programs such as biomass energy systems are being

developed to provide energy in the 21st century. For the biomass industry to expand, a variety of feedstocks will need

to be utilized. Large scale production of bioenergy crops could have significant impacts on the United States agricultural sector in terms of quantities, prices and production location of traditional crops as well as farm income. Though

a number of scenarios were examined to study the impact of bioenergy crop production on the agricultural sector, two

cropland scenarios are presented in this report. Under the wildlife management scenario, the analysis indicates that, at

$30/dry ton (dt) for switchgrass, $31.74/dt for willow and $32.90 for poplar, an estimated 19.4 million acres of

cropland (8.2 million from CRP) could be used to produce 96 million dry tons of bioenergy crops annually at a profit

greater than the profit created by existing uses for the land. In this scenario, traditional crop prices increase from 3

percent to 9 percent (depending on crop) and net farm income increases by $2.8 billion annually. At $40/dt of switchgrass, $42.32/dt for willow and $43.87/dt for poplar and assuming the production management scenario, an estimated

41.9 million acres (12.9 million from CRP) could be used to produce 188 million dry tons of biomass annually. Under

this scenario, traditional crop prices increase by 8 to 14 percent and net farm income increases by $6 billion annually.

Keywords: Alternative crops, bioenergy crops, biomass, Conservation Reserve Program, crop acreage shifts, crop

budgeting, economic feasibility, economic impact, hybrid poplars, hybrid willow, POLYSYS, switchgrass

About the Authors

Daniel G, De La Torre Ugarte is Research Associate Professor at the University of Tennessee Agricultural Policy

Analysis Center (APAC); Marie E. Walsh is an Economist at the Oak Ridge National laboratory (DOE-ORNL); Hosein

Shapouri is an Economist at the Office of Energy Policy and New Uses (USDA-OEPNU); and Stephen P. Slinsky is a

Research Associate at APAC.

Contributors

The contributors to this study include: Dr. Larry Abrahamson (State University of New York); Dr. Mike Anderson

(USDA-NRCS); Dr. Samuel Baldwin (Office of Science and Technology Policy); Dr. Alex Barbarika (USDA-FSA);

Dr. Dwayne Buxton (USDA-ARS-NPS); Dr. Liu-Hsiung Chuang (USDA-NRCS); Dr. Roger Conway (USDA-OEPNU);

Ms. Janet Cushman (DOE-ORNL); Mr. John Ferrell (DOE); Dr. Robin Graham (DOE-ORNL); Dr. Malcolm Henning

(USDA-NRCS); Dr. John Hom (USDA-FS); Dr. Jud Isebrands (USDA-FS); Dr. Sandy McLaughlin (DOE-ORNL);

Mr. Tien Nguyen (DOE); Mr. Rick Pierce (Champion International); Dr. Edward Rall (USDA-FSA); Dr. Daryll Ray

(APAC); Dr. Dan Robison (North Carolina State University); Dr. Mark Safley (USDA-NRCS); Mr. Harwood Schaffer

(APAC); Dr. John Stierna (USDA-NRCS); Mr. Mike Sullivan (Champion International); Dr. Keith Tamiguchi (DOIFWS); Mr. Alan Teel (Iowa State University); Dr. Keith Ticknor (USDA-NRCS); Dr. Kelly Tiller (APAC); Dr. Jerry

Tuskan (DOE-ORNL); Dr. Ken Vogel (USDA-ARS); and Ms. Lynn Wright (DOE-ORNL).

iii

Washington, DC February 2003
iv

Executive Summary

In response to energy security concerns, alternative energy programs such as biomass energy systems are being

developed to provide energy in the 21st century. For the biomass industry to expand, a variety of feedstocks will need

to be utilized. Producing bioenergy crops could significantly increase profits for the agricultural sector. Though this

analysis focuses on switchgrass, hybrid poplar and willow, numerous herbaceous and woody crop species could be

used as bioenergy crops. This report examines the potential for converting cropped, idle, and pasture acres, as well as

Conservation Reserve Program acres, to bioenergy crop production. Though a number of scenarios were examined to

study the impact of bioenergy crop production on the agricultural sector, just two cropland scenarios are presented in

this report.

On cropped, idle, and pasture acres and assuming a farmgate price of $30/dry ton (dt) for switchgrass ($31.74/dt

for willow and $32.90 for poplar) bioenergy crops offer a greater potential profit than existing uses on an estimated

11.2 million acres and produce 58 million dry tons of biomass. At a farmgate price of $40/dt of switchgrass ($42.32/

dt for willow and $43.87/dt for poplar) an estimated 28.95 million cropped, idle, and pasture acres could be converted

to bioenergy crop production producing 132 million dry tons.

Two bioenergy crop management practices were evaluated on Conservation Reserve Program Acres (CRP)ñone to

provide for high wildlife diversity, and the other to provide for high biomass production. Farmers forfeited 25 percent

of their annual rental payment in exchange for the right to harvest and sell bioenergy crops. Management practices

were designed to maintain the erosion and chemical runoff benefits of existing CRP acres included in the analysis.

CRP acres deemed too environmentally sensitive or outside the geographic production range used for bioenergy crops

in the analysis were excluded, leaving 16.9 million of the enrolled 29.8 million acres. Under the $30/dt switchgrass

price ($31.74/dt for willow and $32.90/dt for hybrid poplar) and the wildlife scenario, an estimated 8.2 million acres

producing 34 million dry tons of biomass could provide farmers with higher returns than the annual rental rate. Under

the $40/dt switchgrass price and assuming the production management scenario, an estimated 12.9 million CRP acres

producing 55.3 million dry tons of biomass could be converted to bioenergy production.

Under the $40/dt switchgrass price and the production scenario, nearly 42 million acres of cropped, idle, pasture,

and CRP acres could be converted to bioenergy crop production resulting in an annual production level of 188 million

dry tons. This number of acres is sufficient to make bioenergy crops the fourth largest crop produced by the United

States behind corn, wheat and soybeans. Net farm income is estimated to increase by $2.8 billion annually ($30/dt

switchgrass price; wildlife CRP management scenario; all cropped, idle, and pasture acres) to $6.0 billion annually

($40/dt switchgrass price; production CRP management scenario; all cropped, idle, and pasture acres). Conventional

crop prices increase from 3 to 9 percent (above USDA 1999 baseline prices) under the $30/dry ton and CRP wildlife

scenario and from 9 to 14 percent under the $40/dt and production scenario.

As a potential energy source, the 188 million dry tons of biomass produced under the $40/dt switchgrass price and

the production CRP scenario is sufficient to provide 2.92 quadrillion Btus (Quads) of primary energy and produce

16.7 billion gallons of ethanol (current production is about 1.93 billion, or 7.3 percent of the electricity currently

produced in the United States, assuming current conversion rates. Under the $30/dt switchgrass price and wildlife

CRP scenario, the biomass produced is equivalent to 1.54 Quads of primary energyñsufficient to produce 8.51 billion

gallons of ethanol or 3.8 percent of electricity use.

The analysis uses POLYSYS, an agricultural policy simulation model of the U.S. agricultural sector that includes

national demand, regional supply, livestock, and aggregate income modules (De La Torre Ugarte and Ray, 2000).

POLYSYS is anchored to published baseline projections for the agricultural sector and the model simulates deviations

from the baseline. Typically, POLYSYS uses the USDA, Food and Agricultural Policy Research Institute (FAPRI) or

Congressional Budget Office (CBO) baseline for U.S. agriculture.
Table of Contents

Abstract .........................................................................................................................................................................iii

Executive Summary ...................................................................................................................................................... iv

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

Methodology ...................................................................................................................................................................3

The POLYSYS Model .......................................................................................................................................3

Cropland Categories.........................................................................................................................................3

Crop Production Costs.....................................................................................................................................5

Production Decision Issues .............................................................................................................................8

Land Allocation Rules ......................................................................................................................................8

Price Expectations ............................................................................................................................................9

Modeling Implications .....................................................................................................................................9

Estimated Impacts of Bioenergy Crop Production ...................................................................................................... 10

Land Use Impacts........................................................................................................................................... 11

Price Impacts .................................................................................................................................................. 19

Net Farm Income Impacts ............................................................................................................................... 19

Energy Supply Implications ........................................................................................................................... 22

Summary and Conclusions .......................................................................................................................................... 23

References ................................................................................................................................................................... 24

Glossary ....................................................................................................................................................................... 26

Appendices: Table of Contents..................................................................................................................................... 27

List of Figures

Figure 1 Cropland categories ....................................................................................................................................4

Figure 2 ASDs in which production of switchgrass is assumed ..............................................................................5

Figure 3 ASDs in which production of hybrid poplar is assumed ............................................................................5

Figure 4 ASDs in which production of willow is assumed .......................................................................................5

Figure 5 Distribution of CRP acres assumed potentially available for bioenergy production ..................................5

Figure 6 Wildlife management scenario - Switchgrass plantings on all cropland, 2008 .......................................... 14

Figure 7 Wildlife management scenario - Switchgrass plantings on cropland enrolled in CRP, 2008 ..................... 15

Figure 8 Wildlife management scenario - Poplar plantings on cropland enrolled in CRP, 2008 .............................. 15

Figure 9 Production management scenario - Switchgrass plantings on all cropland, 2008 .................................... 16

Figure 10 Production management scenario - Switchgrass plantings on cropland enrolled in CRP, 2008 ............... 16

Figure 11 Wildlife management scenario - Production of biomass by ASD, 2008 .................................................... 17

Figure 12 Production management scenario - Production of biomass by ASD, 2008 ............................................... 17

Figure 13 Biomass production at selected prices by cropland type and assuming the production

management scenario on CRP acres (million dt) ..................................................................................... 19

List of Tables

Table 1 Summary of cropland in POLYSYS .......................................................................................................... 6

Table 2 Regional bioenergy crop production costs and yields, average and range ................................................ 7

Table 3 Comparison between wildlife management scenario and production management scenario ................. 10

Table 4 Plantings of bioenergy crops, 2008.......................................................................................................... 11

Table 5 Cropland changes due to introduction of bioenergy crops, 2008, wildlife management scenario ......... 12

Table 6 Cropland changes due to introduction of bioenergy crops, 2008, production management scenario .... 12

Table 7 Idle cropland brought back into crop production, 2008 .......................................................................... 13

v
vi

Table 8 Cropland in pasture brought back into crop production, 2008 ................................................................. 13

Table 9 Changes in traditional crop production in Iowa resulting from the national introduction of

bioenergy crops - production management scenario ............................................................................... 13

Table 10 CRP plantings, 2008................................................................................................................................. 14

Table 11 Production of switchgrass by State, 2008 - Comparison between wildlife management scenario and

production management scenario............................................................................................................. 18

Table 12 Price changes for major crops, 2008 ....................................................................................................... 20

Table 13 Changes in net farm income, 2008 ........................................................................................................... 20

Table 14 Changes in net farm income by State, 2008 - Comparison between wildlife management scenario and

production management scenario............................................................................................................. 21

Table 15 Annual energy production equivalents for bioenergy crops, 2008 .......................................................... 22
The Economic Impacts of Bioenergy

Crop Production on U.S. Agriculture

INTRODUCTION

The oil embargoes of the 1970s raised concerns about

energy security. In response, programs to develop alternative energy sources were begun. While energy security

still remains a concern, the potential threat of global climate change resulting from the use of fossil fuels has added

new immediacy to the development of alternative energy

systems. Biomass energy systems are among the alternatives being developed to provide energy into the 21st

century. Life cycle assessments indicate that biomass energy systems can be energy efficient, may significantly

reduce greenhouse gas emissions relative to fossil energy, and can provide other environmental benefits

(DeLucchi, M.A.; Wang, M., Saricks, C., and Santini, D.;

Mann, M.K., and Spath, P.L.).

Several biomass energy systems are nearing commercialization. Plans to build commercial cellulose to ethanol

facilities are underway, but none are in operation yet. Pilot

and demonstration facilities are operational, including a

24 mt/week facility in Canada. Advanced biomass gasification systems for electricity generation are being tested

at two sites and co-firing tests (i.e., mixing biomass with

coal in coal-fired electrical generation facilities) are being

conducted at numerous sites throughout the United

States. These early facilities will rely, predominantly, on

waste biomass materials, such as logging residues, wood

processing mill residues, urban wood wastes, and selected

agricultural residues such as sugarcane bagasse and rice

straw, as their biomass feedstock. However, these feedstocks are available in limited quantities. For the biomass

industry to expand to represent a significant portion of

the primary energy consumed in the United States, additional feedstocks will need to be utilized. Recognizing this

fact, in 1978 the U.S. Department of Energy (DOE) established the Bioenergy Feedstock Development Program

(BFDP) at the Oak Ridge National Laboratory (ORNL).

The BFDP is engaged in the development of new crops

and cropping systems that can be used as dedicated bioenergy feedstocks. The program has screened numerous

potential crop candidates to identify promising species.

Research activities frequently involve collaborative efforts

with university and United States Department of Agriculture (USDA) researchers. While numerous herbaceous and

woody crop species could be used as bioenergy crops,

this analysis focuses on switchgrass, hybrid poplar, and

willow. The rationale for this focus includes the facts that

these crops receive the greatest research funding and their

management practices are similar to several of the other

potential bioenergy crops being evaluated. Thus they can

serve as a general model for many other potential bioenergy crops.

Switchgrass (Panicum virgatum) is a perennial warmseason grass. Its native range includes the United States

east of the Rocky Mountains and extends into Mexico

and Canada. It is a dominant species of the remnant tall

grass prairies in the United States. Switchgrass is genetically diverse and includes both lowland and upland varieties. Currently, switchgrass is grown on limited acreage

in the Conservation Reserve Program (CRP) and as a forage crop. Existing research plots have produced yields as

high as 15 dry tons per acre per year (dt/ac/yr) and have

averaged over 10 dt/ac/yr for 6 years. The potential to

increase yields is viewed as high. Switchgrass can be

planted, managed, and harvested in a manner similar to

traditional hay crops using existing agricultural equipment.

Poplar (Populus spp.) is widely distributed throughout

the United States and includes both aspen and cottonwood

species. Many of the poplar varieties being developed for

commercial use are crosses between two or more Populus

species that provide hybrid vigor to the offspring. Currently, hybrid poplar is commercially produced on about

200,000 acres for use by the paper and pulp industry. In

commercial stands in the Pacific Northwest, hybrid poplar trees have reached harvestable size (8 inch diameter

breast height) in 6-7 years. At selected research sites, mean

annual incremental yields of as high as 15 dt/ac/yr for a

complete production cycle have been obtained using improved varieties. Hybrid poplar can be planted and managed with existing agricultural equipment and can be

harvested with existing forestry equipment.

Willow (Salix spp.) can be grown throughout the eastern United States. However, suitable varieties and appropriate management practices required for large-scale

commercial production in the Plains and Southern United

States regions have not yet been developed. The willow

plants used for energy production are hybrid shrubs, rather

than the trees often associated with the species. Willow

production is expected to involve a close-spaced, coppice

system developed predominantly in Europe, where willow is being commercially produced for energy. Yields as

high as 12 dt/ac/yr have been achieved in research plots

1
in the United States. Planting and harvesting of willow

utilize specially designed machinery that is commercially

available in Europe.

The production of switchgrass, hybrid poplar, and willow utilizes agricultural management practices that are

similar to those used in traditional crop agriculture and

forest plantations. In this study, production is assumed to

occur on agricultural croplands. Thus, bioenergy crops

must compete economically with traditional crops. As a

result, large-scale production of bioenergy crops could

have important implications for the agricultural sector in

terms of crop prices and farm income. To address these

issues, the DOE Office of Transportation Technologies

and USDA, in collaboration with the University of Tennessee Agricultural Policy Analysis Center (APAC) and

ORNL, have jointly evaluated the potential economic feasibility and ramifications of bioenergy crop production in

the United States. For the study, an agricultural sector

model (POLYSYS), which was developed and maintained

by APAC and used by USDAís Economic Research Service (USDA-ERS), has been modified to include switchgrass, hybrid poplar, and willow. The analysis seeks, at a

macroeconomic level, to:

ï Estimate the farmgate price needed to make bioenergy crops economically competitive with alternative agricultural uses for cropland,

ï Determine the regional distribution of bioenergy

crop production,

ï Estimate the potential impact of bioenergy crop production on traditional crop prices and quantities,

ï Estimate the potential impact of bioenergy crop production on net farm income, and

ï Evaluate the economic potential of a modified CRP

to serve as a land resource for bioenergy crop production.

The CRP program has been suggested as a means to

introduce bioenergy crops to the agricultural sector. The

CRP contract length roughly corresponds to the production cycle of bioenergy crops. Production of bioenergy

crops on CRP acres could potentially provide a stable supply of feedstocks to user facilities, and income to producers through continued receipt of partial rental payments

and the sale of bioenergy crops, while potentially lowering the cost of the CRP program to the Federal Government. The partial support of bioenergy crops could help

lower their price and improve their attractiveness to user

facilities.

However, the CRP program is an environmental program. If it is to be used as a source of bioenergy crops, the

production and harvest of these crops must be conducted

in a manner that maintains the environmental benefits of

the program. Criteria must be developed that identify acres

suitable for bioenergy crop production. Management practices must be developed that minimize the loss of environmental benefits while still providing an economic

incentive to producers. This study makes a first attempt at

addressing these issues. The study eliminates the most

environmentally sensitive CRP acres from consideration

for bioenergy crop production, and analyzes the economic

impacts of different bioenergy crop management strategies.

The following chapters describe the POLYSYS model,

the modifications made to the POLYSYS model to accommodate inclusion of bioenergy crops, and the results

of the analysis for two price and bioenergy crop management strategies. Appendices detail traditional crop management data sources and describe the management

practices and estimated production costs assumed for bioenergy crops.

2
The POLYSYS Model

The analysis uses POLYSYS, an agricultural policy

simulation model of the U.S. agricultural sector that includes national demand, regional supply, livestock, and

aggregate income modules (De La Torre Ugarte and Ray,

2000). POLYSYS is anchored to published baseline projections for the agricultural sector, and the model simulates deviations from the baseline. Typically POLYSYS

uses the USDA, Food and Agriculture Policy Research

Institute (FAPRI), or Congressional Budget Office (CBO)

baseline for U.S. agriculture.

The regional crop supply module consists of independent linear programming models for each of the 305 geographic regions contained in POLYSYS corresponding to

the 305 Agricultural Statistical Districts (ASD). Each ASD

is characterized by relatively homogeneous production.

The core POLYSYS model includes the eight major crops

(corn, grain sorghum, oats, barley, wheat, soybeans, cotton, and rice) as well as some minor crops (peanuts, sugarcane, sugar beets, dry beans) and it can be modified to

include additional crops or exclude some of the core commodities. As with all the other modules, the crop supply

module is anchored to a national baseline which is disaggregated to a regional level based on historical crop production and supply patterns. Once the total acreage

available for crop production in each ASD is determined

(baseline acres and short- and long-term land retirement

programs), the supply module allocates acres to competing crops using a linear programming model that maximizes expected returns using expected crop prices (to be

described later). Production from each of the 305 ASDs is

determined independently and aggregated to obtain national production. Allocation rules are utilized to limit the

acreage that can be switched from production of one crop

to another or removed from production in each ASD. These

allocation rules prevent corner solutions and simulate the

inelastic nature of agricultural supply.

The core POLYSYS model estimates expected returns

in one of two ways: a weighted average of prices for the

last 3 years or the previous yearís price. Expected returns

per acre for each crop include revenues, based on the

expected prices and the baseline or hypothesized yield,

and a range of expenditures, used to compute the variable

and cash costs. The core model uses enterprise budgets

for each crop in each ASD. Rotational budgets can be

incorporated into any given study.

The crop supply module solves for the optimal allocation of cropping activities in each region, given the allocation rules established. The estimated supply quantity

interacts with the crop demand module to estimate new

prices, demand quantities, and carryover stocks for the

current time period.

The livestock module is an econometric model that interacts with the crop supply and demand modules to estimate livestock production, feed use, and market prices.

Livestock production levels are a function of lagged livestock and feed own and cross prices, as well as the baseline levels and exogenously determined variables such as

livestock exports. The livestock sector is linked to the

supply and demand modules principally through the feed

grain component. Livestock quantities affect feed grain

demand and price, and feed grain prices and supply affect

livestock production decisions. Exports and imports of

livestock products are exogenous to the model.

The crop demand module estimates national-level demand quantities and prices using elasticities and changes

in baseline prices. Crop utilization is estimated for domestic demand (food, feed, and industrial uses), exports, and

stock carryovers. Derivative products such as soybean

oil and meal are also included. Demand quantities are estimated as a function of own and cross prices and selected

non-price variables such as livestock production. The crop

prices are estimated using price flexibilities, and stock

carryovers are estimated as the residual element.

The income module uses information from the crop

supply, crop demand, and livestock modules to estimate

cash receipts, production expenses, government outlays,

net returns, and net realized farm income.

To evaluate the economic potential of bioenergy crops,

several modifications to the core POLYSYS model are made.

Acres planted to alfalfa and other hay crops are incorporated into the model as are cropland acres currently enrolled in the CRP program and acres that are idled or in

pasture. Geographic areas suitable for the production of

bioenergy crops are identified, and production practices

and yields for these crops are incorporated into the model.

The land allocation rules in POLYSYS are modified to account for the potential production of bioenergy crops. In

order to allow producers to include in their decision framework any anticipated price changes that might result from

significant shifts of acres to bioenergy crops, a rational

expectations price formulation is incorporated.

Cropland Categories

According to the 1997 Census of Agriculture, 431.4

million acres are identified as cropland in the United States.

Seventy-three percent of these acres are currently in major crop production (including alfalfa and other hay). The

remaining cropland acres are idled (4 percent), in pasture

(14 percent), enrolled in the Conservation Reserve ProMETHODOLOGY

3
gram (7 percent), or in other uses such as in the production of fruits, vegetables, or other minor crops (2 percent)

(figure 1). According to the 1999 USDA baseline, 254.5

million cropland acres are planted to the eight major crops.

The 1999 FAPRI baseline estimates that 27.2 million cropland acres are planted to alfalfa and 33.2 million cropland

acres are planted to other hay crops. A total of 29.8 million

cropland acres are enrolled in the Conservation Reserve

Program (Farm Service Agency, October 1, 1998). The 1997

Census of Agriculture estimates that 19.0 million cropland

acres are idled with 60.3 million cropland acres planted to

pasture. The version of POLYSYS used to evaluate bioenergy crops includes all of these cropland acres. POLYSYS

does not include cropland acres allocated to fruits and

vegetables and minor crops such as dry beans, sugarcane

and sugar beets, tobacco, etc., which total 2 percent of all

U.S. cropland.

The acres included in POLYSYS represent the cropland

acres in the 48 contiguous States. Bioenergy crops can

grow in all regions of the United States. However, for the

purpose of this analysis, the geographic ranges where

production can occur are limited to areas where bioenergy

crops can be produced with high productivity under rainfed conditions and where sufficient research has been

conducted to make informed decisions regarding suitable

varieties, appropriate management practices, and expected

yields. The regions analyzed include those where sufficient knowledge of each bioenergy crop has been accumulated so one can reasonably expect that large-scale

commercial production could begin during the timeframe

considered in the analysis, 1999-2008. The production regions could be expanded in the future as research is conducted in other geographic regions. The switchgrass,

hybrid poplar, and willow production regions used in this

analysis are presented in figures 2 to 4.

With respect to the Conservation Reserve Program

acres, geographic limitations reduce the number of acres

from the enrolled 29.8 million acres (as of October 1, 1998)

to 24.1 million acres. These acres are further restricted to

remove from consideration for bioenergy production the

most environmentally sensitive areas: (1) acres enrolled in

buffer strips to protect water quality, (2) acres classified

as wetlands, (3) acres critical to watershed management,

and (4) critical habitat acres in Wildlife Conservation Priority Areas. These restrictions remove an additional 7.2

million CRP acres. Thus, for this analysis, 16.9 million CRP

acres are identified as being potentially available for bioenergy crop production (figure 5).

A summary of the cropland, by category, that is included in POLYSYS is presented in table 1. The production of at least one of the bioenergy crops included in this

analysis is assumed suitable on 368 million of the total 424

4

Figure 1. Cropland Categories

Cropland in CRP

Idle Cropland

Cropland in Pasture

Cropland in Major Crops

Cropland Not

Considered in

POLYSYS

73%

7% 4%

14%

2%

Cropland

Category

(Data Sources)

1999 USDA Baseline

Land Enrolled in CRP (through October 1998 - Farm Service Agency)

Idle Cropland (1997 Census of Agriculture)

Cropland in Pasture (1997 Census of Agriculture)

Difference between U.S. Census of Agriculture Cropland and Cropland Considered by

POLYSYS

Total United States Cropland = 431.4 million acres
million acres included in POLYSYS.

Crop Production Costs

The bioenergy crops analyzed in this study are not

currently produced as dedicated energy sources in the

United States. However, about 200,000 acres of hybrid

poplar are being commercially produced as a fiber source,

and switchgrass is grown on some CRP acres and on hay

acres as a forage crop. The lack of large-scale commercial

production necessitates the use of research data and expert opinion to determine yields and management practices. Before beginning the analysis, experts from the U.S.

Departments of Energy and Agriculture participated in a

workshop (Appendix 1) where recommendations were

made regarding:

ï Geographic regions assumed for bioenergy crop production;

ï Current and projected bioenergy crop yields by geographic region;

ï Management practices appropriate for bioenergy

crop production by land type and geographic region.

Geographic regions and yields are based chiefly on

those contained in the Oak Ridge Energy Crop County

Level Database (Graham, et al, 1996) and modified by the

recommendations of the workshop participants. Bioenergy crop yields, by ASD, range from 2 dt/ac/yr to 6.75 dt/

ac/yr depending on crop and location. Yields of bioenergy crops on idled and pasture acres are assumed to be

85 percent of those that can be obtained on acres in crop

production. Bioenergy crop yields on CRP acres are adjusted by an index of traditional crop yields obtained on

CRP acres prior to being enrolled in the CRP. Once planted,

the expected yields for bioenergy crops remain fixed for

the life of the production rotation. Research is ongoing to

Figure 4. ASDs in which production of

willow is assumed

Figure 5. Distribution of CRP acres

assumed potentially available for bioenergy

production as of October 31, 1998

5

Figure 2. ASDs in which production of

switchgrass is assumed

Figure 3. ASDs in which production of

hybrid poplar is assumed

Acres

469,000to1,430,00

235,000to 469,000

119,000to 235,000

54,000to 119,000

0 to 54,000
improve yields. As a result, acres planted in later years

could be assumed to have higher yields than those planted

in earlier years.

Production costs for all crops considered in the analysis (i.e., traditional and bioenergy) are estimated using

enterprise budgets. All production costs, except willow

and hybrid poplar harvesting costs, are estimated using

the APAC Budgeting System (ABS) (Slinsky and Tiller,

1999). ABS generates consistent enterprise and rotation

budgets for each of the 305 ASDs contained in POLYSYS.

Use of this budgeting system to estimate the costs of

producing bioenergy crops as well as traditional crops

ensures consistency across all crops in the analysis. ABS

generates cost-of-production data based on operations

schedules (i.e., field-level activities). The schedule of operations used for each traditional crop for each region is

based on Agricultural Extension Service publications whenever possible. The resolution of information (State or

substate level) provided in each budget varies according

to the level at which particular information is available.

Appendix 2 contains information regarding traditional crop

management data sources.

Crop management practices for bioenergy crops produced on cropped, idle, and pasture acres are based on

recommendations from the expert panel. These practices

are presented in Appendices 3.1 and 3.2. Bioenergy crop

management practices used on CRP acres were determined

in subsequent discussions with USDA (Natural Resources

Conservation Service and Farm Service Agency). Two CRP

management practices were selected for use in the analysis: one to achieve high levels of biomass production (production management scenario), and one to achieve high

levels of wildlife diversity (wildlife management scenario).

These management practices are described in Appendix

3.3. Generally, the wildlife management scenario utilizes

fewer fertilizer and chemical inputs than does the production management scenario. It also places significantly

greater constraints on the harvest of switchgrass by restricting harvest to alternating halves of a field each year

in contrast to the annual harvesting of the whole field in

the production management scenario.

Estimated production costs for all crops include variable cash input costs (chemicals, fertilizers, seeds, cuttings, fuel and lubrication, machinery repair, hired labor,

loan interest payments, etc.), producerís own labor, and

machinery-related costs (such as depreciation, insurance,

and non-land capital costs). Machinery-related costs are

estimated by first defining all equipment needed to complete each field operation as specified by the management

practices for each crop. Labor costs are estimated as a

function of machinery hours. Machine costs per hour of

operation are estimated using standard methodology

(USDA, American Society of Agricultural Engineers) and

multiplied by the hours per acre required to complete each

operation to obtain the cost of the machinery per acre.

Machinery prices and engineering performance parameters

were obtained from the USDA (McBride) for all equipment

except that used for harvesting hybrid poplar and willow.

Those costs were estimated using BIOCOST, a budget

generator model developed by Oak Ridge National Laboratory to estimate the cost of producing bioenergy crops

(Walsh and Becker, 1996). BIOCOST is used to estimate

hybrid poplar and willow harvesting costs because neither the USDA database nor ABS includes data on forestharvesting equipment. The methodologies, input prices,

and the cost categories used in BIOCOST are consistent

with ABS.

The management practices used to estimate production costs are those that are typical for that ASD. They are

not necessarily those used on every individual farm or

soil type within a farm. Thus, the production costs used in

the analysis are representative average costs for each

ASD. Variation in production practices, yields, and labor

and equipment constraints at an individual farm or field

level within an ASD may occur which could alter the estimated costs of production for that site. These variations

are not captured in the analysis.

Based on the assumed yield, management practices,

Table 1. Summary of Cropland in POLYSYS

POLYSYS Acreage Acres Assumed Suitable for Bioenergy Crop Production

(Mil. Acres) (Mil. Acres) (% of Total Acres)

Major Crops* 314.9 282.5 89.7%

CRP 29.8 16.9 56.7%

Idle 19.0 14.7 77.4%

Pasture 60.3 53.8 89.2%

TOTAL** 424.0 367.9 86.8%

* Includes corn, soybeans, sorghum, oats, barley, wheat, cotton, rice, alfalfa, and other hays.

** Excludes 7.4 million acres in other uses such as fruits, vegetables and other minor crops.

6
and input costs used in the analysis, switchgrass is relatively the least expensive bioenergy crop to produce per

dry ton yield for most ASDs. Hybrid poplar is next and

willow is generally the most expensive. Table 2 contains

the estimated regional average and range of production

costs and yields for bioenergy crops.

The production costs are the present value cost (assuming a real discount rate of 6.5 percent) of producing

the bioenergy crop (in dollars per acre and dollars per dry

ton) for its entire production rotation. Production rotations are 10 years for switchgrass, 6 to 10 years for poplar,

and 22 years for willow. The net present value framework

is discussed in more detail in the following section. Production costs are those estimated for cropland acres currently planted to crops. Production costs for idle, pasture,

and CRP acres are generally higher for each bioenergy crop.

Given that the estimated average per ton production

costs for switchgrass are generally lower than for the tree

crops in most ASDs, at similar market prices ($/dt) for the

three bioenergy crops, switchgrass will be relatively more

profitable than poplar and willow. As a result, POLYSYS

allocates most of the bioenergy crop acres to switchgrass.

Poplar and willow are generally more expensive to produce due to the higher establishment costs and the long

period of time before returns from harvest are sufficient to

pay for establishment. Those conditions require that interest payments be carried for several years. In a present

value framework, costs incurred in the first few years are

weighted more heavily than those incurred in later years.

Appendix 4 contains a more detailed breakdown of the

regional average bioenergy crop production costs.

NE APP CB LS SE SP NP PNW

Switchgrass

Yield (dt/ac/yr) 4.87 5.84 5.98 4.80 5.49 4.30 3.47 -

Yield Range (dt/ac/yr) 3.50-5.50 4.36-6.62 4.95-6.73 3.50-6.00 3.40-6.45 2.55-5.98 2.00-5.49 -

Avg. Prod. Cost ($/ac) 983.14 969.50 975.75 863.10 929.73 847.37 714.25 -

Avg. Prod. Cost ($/dt) 22.53 18.53 18.21 20.07 18.90 21.99 22.97 -

Prod. Cost Range ($/dt) 21.38-25.10 17.21-20.89 17.63-18.76 18.91-23.32 17.87-23.70 16.87-29.44 18.73-36.20 -

Hybrid Poplar

Yield (dt/ac/yr) 3.99 3.56 4.63 4.41 4.50 3.75 3.83 5.73

Yield Range (dt/ac/yr) 3.43-4.50 4.00-5.21 3.75-5.20 3.50-5.25 3.82-5.21 3.25-4.00 3.25 -4.31 5.50-6.00

Avg. Prod. Cost ($/ac) 920.38 967.56 917.26 892.82 967.57 928.78 900.74 1051.08

Avg. Prod. Cost ($/dt) 23.07 27.18 19.81 20.25 26.88 30.96 23.52 30.57

Prod. Cost Range ($/dt) 20.87-29.21 24.03-29.59 23.18-18.74 17.72-24.40 23.95-30.13 29.49-34.57 22.25-26.67 29.56-31.59

Willow

Yield (dt/ac/yr) 4.90 4.50 4.70 4.60 - - - -

Yield Range (dt/ac/yr) 3.15-5.77 4.50-4.50 4.50-5.08 4.05-5.25 ----

Avg. Prod. Cost ($/ac) 2206.33 2163.74 2161.30 2154.30 ----

Avg. Prod. Cost ($/dt) 20.47 21.86 20.90 21.29 ----

Prod Cost Range ($/dt) 17.77-30.46 21.86-21.86 19.51-21.71 18.95-23.88 ---

Table 2: Regional Bioenergy Crop Production Costs and Yields, Average and Range

NE = CT, NH, NJ, NY, MA, ME, PA, RI, VT APP = DE, KY, MD, NC, TN, VA, WV

CB = IA, IL, IN, MO, OH LS = MI, MN, WI

SE = AL, AR, FL, GA, LA, MS, SC SP = CO, KS, NE, OK, TX

NP = MT, ND, SD, WY PNW = OR, WA

Yield = Mature Yield

Production Costs ($/ac & $/dt) = Present value cost over entire rotation

7
Production Decision Issues

As annuals, traditional agricultural crops are planted

and harvested each year. The bioenergy crops examined

in this study are perennials that are planted in one year

and remain in production for several years after planting.

Harvest can occur annually during the production cycle

(e.g., switchgrass), multiple times at defined intervals during a production cycle (e.g., willow), or once at the end of

a production cycle (e.g., hybrid poplar). Due to the multiyear characteristics of bioenergy crops, a net present value

(NPV) approach is used to decide which crop to produce.

This differs from the original mechanism embodied in

POLYSYS, which utilizes annual net returns to allocate

acres among the traditional crops.

To evaluate whether a bioenergy crop should be

planted in a particular region, its expected net present

value profit is calculated and compared with the corresponding expected net present value profit for each of the

traditional crops. Acreage is allocated to each crop (traditional as well as bioenergy crops) based on relative NPV

profits subject to flexibility constraints described in the

next section. Given that the three bioenergy crops examined in this study have production cycles of different time

lengths, a common planning horizon is used to ensure

comparability of discounted revenue streams. A total planning horizon of 40 years is set because, although not a

minimum common denominator, it spans a long enough

time period to consider insignificant the stream of net returns beyond this period. A real discount rate of 6.5 percent is assumed.

Production decisions on CRP, idle, and pasture acres

require additional considerations to those made on cropland planted to traditional crops. On CRP acres, it is assumed either that existing contracts, upon expiration, can

be renewed under the same conditions that were in effect

upon initial enrollment in the program, or that the acres

can be planted to bioenergy crops under a modified contract. This assumption greatly simplifies the analysis by

not requiring development of a model to determine reenrollment or initial enrollment requirements. In exchange

for being allowed to produce and harvest bioenergy crops

on CRP acres, 25 percent of the current rental rate on the

acres is forfeited. Thus, the decision to allocate CRP acres

to bioenergy crop production is reduced to a comparison

of the net present value of producing bioenergy crops

with the net present value of the foregone CRP rental payments.

Cropland acres that are idle or in pasture are assumed

to be idled or in pasture for economic reasonsóthat is,

given prices, costs of production, and yields, the most

economic use of the land is either to not plant a crop or to

dedicate it to pasture. To return these acres to production

of the major crops or to plant bioenergy crops, the net

present value returns of these crops must be higher than

the most profitable crop under the baseline assumptions.

Furthermore, to account for possible inertia to keep the

land in its current use and/or the value of pasture land in

livestock operations, the model assumes a premium of 10

percent above the baseline net present returns for idled

acres and 15 percent for pasture acres is required.

Land Allocation Rules

To avoid corner solutions in the regional linear programming models, POLYSYS contains embedded flexibility constraints that limit the acreage that a given crop can

lose or gain each year. To accommodate the addition of

bioenergy crops, these allocation rules were modified to

the following:

ï If the net present value in years t, t-1, and t-2 is

positive, the acreage of a crop can increase/decrease

by up to 10 percent of the baseline acreage in year t,

depending on its net present value relative to that

of competing crops.

ï If the net present value in years t and t-1 is negative

and positive in year t-2, the acreage of a crop can

increase/decrease by up to 30 percent of the baseline acreage in year t, depending on its net present

value relative to that of competing crops.

ï If the net present value in years t, t-1, and t-2 is

negative, the acreage of a crop can increase/decrease

by up to 50 percent of the baseline acreage in year t,

depending on its net present value relative to that

of competing crops.

ï For crops comprising more than 20 percent of the

total planted acres for all crops in an ASD, acres

that can be gained or lost are limited to 20 percent of

the baseline acreage of the crop.

ï Idled and pasture acres that can be reallocated to agricultural production are limited to 40 percent and 25

percent, respectively, of the baseline acres in each ASD.

ï Bioenergy crops can gain as much acreage as is

available from other crops, given the above constraints.

ï Once acreage is allocated to bioenergy crops, the

acreage remains allocated to the bioenergy crop for

the duration of its productive life cycle.

It is assumed that some type of contractual arrangement between farmers and bioenergy crop users exists

which limits, for the duration of the bioenergy crop production cycle, the conversion of acres back to traditional

crop production once they are allocated to bioenergy

crops. Since the period of analysis for bioenergy crops is

the years 2000-2008, which is less than the production

cycle of the three bioenergy crops considered, land allocated to bioenergy crops remains in bioenergy crop production until the end period of the analysis.

8
Price Expectations

When dealing with traditional crops under a scenario

of relative equilibrium, POLYSYS has historically calculated expected future prices using a naive price expectation hypothesis that utilizes a weighted average of prices

in the previous three years. However, the introduction of

bioenergy crops offers the possibility of significant shifts

in the way agricultural cropland is allocated, which could

potentially result in significant impacts on the prices of

traditional agricultural crops. Thus POLYSYS has been

modified to estimate future expected crop prices using a

rational expectations approach.

Rational expectations are premised on the hypothesis

that, in a given year, farmers will anticipate price changes

resulting from significant shifts of acreage from traditional

crops to bioenergy crops and will incorporate these price

changes into their planting decisions. These changes in

expected prices are estimated in POLYSYS through an iterative process. In the first step of the iteration, the supply module in POLYSYS allocates acres to traditional and

bioenergy crops using naive price expectations for traditional crops (i.e., a weighted average of past prices) and

assumed market prices for bioenergy crops. The supply

of traditional crops resulting from the allocation interacts

with the demand module in POLYSYS to estimate the

changes in prices for traditional crops. These ìnewî prices

for traditional crops are now used as the prices farmers

expect to receive for these crops in the second step of the

iteration process. Assuming the ìnewî market prices for

traditional crops and the same prices for bioenergy crops

assumed in the first step, the supply module in POLYSYS

then reestimates the acres allocated to traditional and bioenergy crops. These new supply quantities interact with

the demand module to once again estimate the ìnewî market prices for traditional crops. The two-step iteration is

repeated until the changes in prices for traditional crops

between the two iterations are less than a predetermined

convergence factor.

Since there are no well-developed markets for the bioenergy crops, their prices are determined exogenously. To

keep bioenergy crop prices consistent with each other,

the price of switchgrass is used as the numeraire, and the

prices of hybrid poplar and willow are adjusted based on

their energy content (in Btu per dry ton).

Modeling Implications

The production and land allocation rules can be summarized in the following mathematical formulation, which

indicates that for each time period (t) in each POLYSYS

region (r), acres (x) are allocated based on the net present

value for each crop (k), subject to land availability (X) in

each land category (l) (cropland in major crops, cropland

in CRP, cropland idle, and cropland in pasture), and subject to the upper (U) and lower limits (L) on the acreage

planted to each crop.

The NPV includes any government payments on a per

acre basis, such as the CRP rental rate, and is estimated

using the price expectation formulation described previously.

9
ESTIMATED IMPACTS OF

BIOENERGY CROP PRODUCTION

A number of alternative scenarios were constructed and

estimated.The results of just two scenarios are presented

here, however, to keep the discussion focused on the economic feasibility and potential economic impacts of bioenergy crop production on the agricultural sector. These

two scenarios, summarized in Table 3, were chosen because they serve to place boundaries around the discussion.

The wildlife diversity scenario assumes a bioenergy

farmgate price (i.e., no transportation costs included) of

$30/dry ton for switchgrass, $31.74/dt for willow, and

$32.90/dt for hybrid poplar. (Because the energy density

of the three bioenergy crops differs slightly, an equivalent

energy price in $/MBtu results in slightly different $/dry

ton prices. The $/MBtu value assumed for all three crops

is $1.94). This scenario also assumes that wildlife management practices are employed on CRP acres and that

farmers receive 75 percent of their rental rate in exchange

for the right to harvest and sell bioenergy crops.

The production management scenario assumes a bioenergy farmgate price of $2.58/MBtu for each energy crop,

which is equivalent to $40/dry ton for switchgrass,

$42.32/dt for willow, and $43.87/dt for hybrid poplar. This

scenario assumes that production management practices

are employed on CRP acres and that farmers receive 75

percent of their current rental rate in exchange for the right

to harvest and sell bioenergy crops.

Both scenarios use the 1999 USDA baseline for the

eight major crops in the analysis (corn, grain sorghum,

oats, barley, wheat, soybeans, cotton, and rice) and the

1999 FAPRI baseline for alfalfa and other hay, which are

not included in the USDA baseline. CRP baseline acres

and location are those prevailing on October 1, 1998. Idle

and pasture baseline acres and location are obtained from

the 1997 Census of Agriculture and are assumed to be

representative of, and consistent with, the baseline information for the major crops.

Bioenergy crop production is assumed to begin in the

year 2000, and the largest shift in land is estimated to occur in that year. Annual impacts for the period 2000-2008

are available for each scenario, but to facilitate the presentation of the results, only the results from the year 2008

are given. It is assumed that most of the initial shock resulting from the allocation of land to bioenergy crop production will have occurred by 2008 and that the agricultural

production sector will have settled into a new long-run

equilibrium.

Bioenergy crops compete not only with traditional crops

for land, but with each other as well. Land is allocated to

those bioenergy crops with the greatest average net returns. As discussed in previous sections, switchgrass is

relatively the least expensive bioenergy crop to produce,

and at similar market prices, switchgrass is relatively more

profitable than poplar or willow. As a result, in most ASDs,

switchgrass has higher average net returns for each price

scenario examined in the analysis, and bioenergy crop

acres are generally allocated to switchgrass production

(see Appendix 4 for a detailed description of regional average costs and returns of bioenergy crops).

That observation does not imply that for any given field

or soil type within an ASD, willow or poplar could not be

produced more profitably than switchgrass or traditional

crops. Rather, the analysis considers only average net

present value returns for the entire ASD, given the assumed

average yields and typical management practices for each

bioenergy crop in each ASD. Variations in average returns

Wildlife Management Scenario* Production Management Scenario*

Farmgate Crop Price $1.94/MBtu Farmgate Crop Price $2.58/MBtu

ï Switchgrass $30.00/dt ï Switchgrass $40.00/dt

ï Willow $31.74/dt ï Willow $42.32/dt

ï Hybrid Poplar $32.90/dt ï Hybrid Poplar $43.87/dt

Wildlife Management Practices on CRP land Production Management Practices on CRP land

ï Fewer fertilizer and chemical inputs ï Standard fertilizer and chemical inputs

ï Annual switchgrass harvest is limited to ï Annual switchgrass harvest of whole field

ïalternating halves each year

Retain 75% CRP rental rate Retain 75% CRP rental rate

*For complete details on the two management practices see Appendix 3

Table 3. Comparison between wildlife management scenario and production management scenario

10
between ASDs is accounted for in the model, but sitespecific variations in returns within an ASD are not accounted for in the analysis.

At prices that are 20 percent higher than switchgrass

(in $/MBtu), and keeping production costs and yields

fixed, willow achieves a net present value return greater

than switchgrass in many ASDs where both can be produced. Similarly, at a $/MBtu price that is 15 percent higher

than switchgrass, poplar is relatively more profitable. Thus,

combinations of yields, production costs, and market prices

that provide a 15 percent to 20 percent differential in net

present value returns between short-rotation woody crops

and switchgrass would result in more acres being allocated to poplar and willow, over switchgrass (on acres for

which the relative profitability of bioenergy crops exceeds

those of traditional crops). A situation like this happens

on CRP acres under the wildlife management scenario.

The restrictions placed on the production and harvest of

switchgrass relative to that of short-rotation woody crops,

alter the relative profitability enough that significant acres

of bioenergy crop production shift from switchgrass production (in the production management scenario) to hybrid poplar production. Willow, having the least average

profitability, still does not enter the solution set in the

analysis.

Thus, under the conditions and assumptions used in

the analysis, switchgrass dominates the other two bioenergy crops under most scenarios considered. Under selected conditions, acres are also allocated to poplar but

not to willow. The remaining discussion of the impacts of

bioenergy crops production on the agricultural sector reflects these results.

Land Use Impacts

Estimated total national acres allocated to bioenergy

crops under the two scenarios are presented in Table 4.

Under the wildlife management scenario, 19.4 million

acres of cropland are planted to bioenergy crops, with 10.4

million of those acres (54 percent) coming from land previously planted to traditional crops. An estimated 8.2 million CRP acres, 0.2 million idled acres, and 0.5 million

pasture acres are converted to bioenergy crop production.

For the production management scenario, an estimated

41.9 million acres are planted to bioenergy crops, with

23.4 million of those acres coming from land planted to

traditional crops and 12.9 million acres coming from converted CRP acres. An estimated 2.1 million idled acres

and 3.5 million pasture acres are also converted to bioenergy crop production.

Tables 5 and 6 present the shifts in acres from the major crops and cropland categories that result from the introduction of bioenergy crops. Total cropland area planted

increases from the baseline 325.4 million acres to 335.9

million acres under the wildlife management scenario and

to 346.8 million acres under the production management

scenario. The additional acreage comes almost exclusively

from CRP land in the wildlife management scenario and

from CRP, idled, and pasture land in the production management scenario. Many traditional crops lose acres as a

result of bioenergy crop production, but gain acres from

production on idled and pasture acres. This effect occurs

because the shift in acres resulting from the introduction

of bioenergy crops results in lower production of traditional crops and thus higher traditional crop prices. The

11

Units in Million Acres Wildlife Management Scenario

All Cropland Major Crops CRP Idle Pasture

Switchgrass 12.32 10.44 1.1 0.23 0.55

Hybrid Poplar 7.10 0 7.1 0 0

Willows 0.00 0.00 0.0000 0

All Bioenergy 19.42 10.44 8.20 0.23 0.55

Units in Million Acres Production Management Scenario

All Cropland Major Crops CRP Idle Pasture

Switchgrass 41.87 23.37 12.91 2.09 3.49

Hybrid Poplar 0 000 0

Willows 0.00 0.00 0.0000 0

All Bioenergy 41.87 23.37 12.91 2.09 3.49

Table 4. Plantings of bioenergy crops, 2008
USDA

baseline WILDLIFE MANAGEMENT SCENARIO

Million Acres (Feb. 1999)

1999 Effect on Acreage gained Net 2008

Acres cropland in from idle Change Acres

major crops & pasture

Corn 82.0 -2.2 0.8 -1.4 80.6

Sorghum 10.6 0.0 0.0 0.0 10.6

Oats 4.7 -0.1 0.0 -0.1 4.6

Barley 7.0 0.0 0.0 0.0 7.0

Wheat 73.1 -1.8 0.4 -1.4 71.7

Soybeans 71.8 -2.0 0.1 -1.9 69.9

Cotton 12.8 -0.8 0.3 -0.5 12.3

Rice 3.2 -0.1 0.0 -0.1 3.1

Alfalfa 27.1 -1.0 0.0 -1.0 26.1

Other Hay 33.1 -2.5 0.0 -2.5 30.6

Bioenergy 0.0 18.6 0.8 19.4 19.4

Total CRP 29.8 -8.2 0.0 -8.2 21.6

Total Planted 325.4 8.2 2.3 10.5 335.9

Idle and Pasture 79.3 -2.3 0.0 -2.3 77.0

Table 5. Cropland changes due to introduction of bioenergy crops, 2008

Wildlife management scenario

USDA

baseline PRODUCTION MANAGEMENT SCENARIO

Million Acres (Feb. 1999)

1999 Effect on Acreage gained Net 2008

Acres cropland in from idle Change Acres

major crops & pasture

Corn 82.0 -4.7 1.0 -3.7 78.3

Sorghum 10.6 -0.4 0.0 -0.4 10.2

Oats 4.7 -0.2 0.1 -0.1 4.6

Barley 7.0 0.0 0.0 0.0 7.0

Wheat 73.1 -7.4 1.2 -6.2 66.9

Soybeans 71.8 -3.5 0.1 -3.4 68.4

Cotton 12.8 -1.2 0.5 -0.7 12.1

Rice 3.2 -0.1 0.0 -0.1 3.1

Alfalfa 27.1 -2.2 0.0 -2.2 24.9

Other Hay 33.1 -3.7 0.0 -3.7 29.4

Bioenergy 0.0 41.2 0.7 41.9 41.9

Total CRP 29.8 -12.9 0.0 -12.9 16.9

Total Planted 325.4 17.8 3.6 21.4 346.8

Idle or Pasture 79.3 -8.5 0.0 -8.5 70.8

Table 6. Cropland changes due to introduction of bioenergy crops, 2008

Production management scenario

12
Crop Million Acres

Bioenergy Crop Management Scenario

Wildlife Production

Corn 0.237 0.277

Sorghum 0.003 0.000

Oats 0.005 0.000

Wheat 0.129 0.301

Soybeans 0.034 0.031

Cotton 0.249 0.454

Bioenergy 0.228 2.093

Total all crops 0.877 3.156

Table 7. Idle cropland brought back into

crop production, 2008

Crop Million Acres

Bioenergy Crop Management Scenario

Wildlife Production33

Corn 0.595 0.712

Wheat 0.217 0.921

Soybeans 0.081 0.065

Bioenergy 0.548 3.485

Total all crops 1.441 5.183

Table 8. Cropland in pasture brought back

into crop production, 2008

higher prices provide sufficient incentive to return some

idled and pasture acres to traditional crop production. For

example, under the production management scenario, corn

loses 4.7 million acres as a result of bioenergy crop production but higher corn prices result in the conversion of

1 million idled and pasture acres to corn production, resulting in a net loss of 3.7 million corn acres.

Crop Acres

Corn -965,908

Oats +058,569

Soybeans +904,671

Bioenergy +002,667

Table 9. Changes in traditional crop production in Iowa resulting from the national introduction of bioenergy crops - production

management scenario.

Tables 7 and 8 detail the acres shifted to traditional

crops and to bioenergy crops from idle and pasture acres

under the two scenarios. In addition to changes in total

crop acres allocated to each traditional crop on a national

level, shifts of acres among traditional crops at a regional

level may also occur. As an example, Iowa loses nearly 1

million acres of corn production (Table 9) under the production management scenario. However, fewer than 3,000

of these acres are shifted to bioenergy crop production.

Rather, the changes in relative prices of traditional crops

induce farmers to replace som of their corn acres with

soybeans and, to a lesser extent, oats. Similar shifts in the

allocation of traditional crop acres occur in other States

as well, due to changes in the relative prices of traditional

crops caused by the introduction of bioenergy crops.

As discussed previously, bioenergy crops compete for

acreage not only with traditional crops, but with each other

as well. Acreage from each ASD is allocated to each crop

based on average NPV profit given the assumed yields,

production costs, and land allocation rules described previously. In nearly every ASD, switchgrass is relatively

more profitable than hybrid poplar, which is in turn relatively more profitable than willow. As a result, switchgrass dominates the other two bioenergy crops. Nearly 99

percent of the acres in traditional crops, idled, or in pasture that are shifted to bioenergy crop production are

shifted to switchgrass production under both scenarios.

In a few ASDs, hybrid poplar is the most profitable bioenergy crop and acres are allocated to it in these ASDs.

Willow, being the least profitable of the three bioenergy

crops, cannot compete for acres with the other two bioenergy crops and no acres are allocated to willow in the analysis.

The bioenergy crop produced on CRP acres depends

on the scenario assumed (Table 10). The wildlife management scenario places substantial penalties on switchgrass in terms of yields and production costs relative to

those of hybrid poplar and willow. As a result, for any

given bioenergy crop price, the relative profitability of

hybrid poplar exceeds that of switchgrass and willow on a

substantial portion of the CRP acres allocated to bioenergy crops. On the remaining CRP acres allocated to bioenergy crops under the wildlife scenario, switchgrass is

relatively more profitable than willow, and the acres are

allocated to switchgrass. Under the production management scenario, switchgrass is the relatively more profitable crop, and the CRP acres are allocated to it. The results

suggest that the interaction between environmental and

economic benefits will require further delineation of management practices that provide a high level of both benefits.

Figures 6-12 present the regional distribution of bioenergy crop production by cropland type for the two scenarios. Figure 6 presents the location and range of acreage

13
of switchgrass production on all cropland acres (combined

acres in crops, idled, in pasture, and in CRP). Figures 7

and 8 present the acres and location of switchgrass and

hybrid poplar respectively on CRP acres under the wildlife management scenario. Under this scenario, switchgrass

production on CRP acres occurs primarily in the southeastern United States. Hybrid poplar production on CRP acres

occurs predominantly in the Midwest and Lake States. Figure 9 presents the location (in acres) of switchgrass production on all cropland acres. Figure 10 presents the location of

switchgrass production on CRP acres under the production

management scenario. Under this scenario, switchgrass production occurs throughout the United States in nearly every

ASD where production is permitted in the analysis. The highest concentration of acres occurs in the Northern and Southern Plains regions.

Figures 11 and 12 present the location of bioenergy

crop production (in dry tons) under the two scenarios.

Table 11 contains the quantities (in dry tons) of bioenergy

crops available by State under the two scenarios. Total

Crop Million Acres

Wildlife Management Scenario Production Management Scenario

Switchgrass 1.099 12.913

Poplar 7.097 0

All bioenergy 8.196 12.913

Bioenergy potential 16.925 16.925

Available CRP for bioenergy 22.608 22.608

All CRP through October 1998 29.788 29.788

Table 10. CRP plantings, 2008

14

WILDLIFE MANAGEMENT SCENARIO

Figure 6. Switchgrass plantings on all cropland, 2008

Acres

469,000 to 1,430,000

235,000 to 469,000

119,000 to 235,000

54,000 to 119,000

0 to 54,000
Figure 7. Switchgrass plantings on cropland enrolled in CRP, 2008

WILDLIFE MANAGEMENT SCENARIO

Figure 8. Poplar plantings on cropland enrolled in CRP, 2008

WILDLIFE MANAGEMENT SCENARIO

15

Acres

469,000 to 1,430,000

235,000 to 469,000

119,000 to 235,000

54,000 to 119,000

0 to 54,000

Acres

469,000 to 1,430,000

235,000 to 469,000

119,000 to 235,000

54,000 to 119,000

0 to 54,000
Figure 9. Switchgrass plantings on all cropland, 2008

PRODUCTION MANAGEMENT SCENARIO

Figure 10. Switchgrass plantings on cropland enrolled in CRP

PRODUCTION MANAGEMENT SCENARIO

16

Acres

469,000 to 1,430,000

235,000 to 469,000

119,000 to 235,000

54,000 to 119,000

0 to 54,000

Acres

469,000 to 1,430,000

235,000 to 469,000

119,000 to 235,000

54,000 to 119,000

0 to 54,000
Figure 11. Production of biomass by ASD, 2008

WILDLIFE MANAGEMENT SCENARIO

Figure 12. Production of biomass by ASD, 2008

PRODUCTION MANAGEMENT SCENARIO

17

Dry Tons

1,300,000 to 3,420,000

730,000 to 1,300,000

450,000 to 730,000

220,000 to 450,000

0 to 220,000

Dry Tons

1,300,000 to 3,420,000

730,000 to 1,300,000

450,000 to 730,000

220,000 to 450,000

0 to 220,000
Table 11. Production of switchgrass by State, 2008

Comparison between the wildlife management scenario and

the production management scenario

Wildlife Management Production Management

Scenario Scenario

State Production in million dry tons

Alabama 3.1 6.6

Arkansas 2.2 5.5

Connecticut 0.0 0.2

Delaware 0.0 0.0*

Florida 0.0 1.3

Georgia 1.3 4.0

Illinois 0.8 7.7

Indiana 0.0 5.0

Iowa 0.0 8.3

Kansas 2.9 11.4

Kentucky 3.0 5.1

Louisiana 3.7 5.8

Maryland 0.0 0.3

Massachusetts 0.0 0.2

Michigan 1.2 4.2

Minnesota 0.4 5.8

Mississippi 4.3 9.3

Missouri 2.5 12.8

Montana 0.0 2.8

Nebraska 1.9 5.2

New Hampshire 0.0 0.2

New Jersey 0.0 0.1

New York 0.0 3.4

North Carolina 0.6 1.6

North Dakota 1.9 16.8

Ohio 3.8 9.7

Oklahoma 3.6 8.1

Pennsylvania 0.0 2.3

Rhode Island 0.0 0.0*

South Carolina 1.3 2.4

South Dakota 5.6 12.8

Tennessee 6.5 9.4

Texas 4.5 9.1

Vermont 0.0 0.3

Virginia 1.3 2.6

West Virginia 0.3 1.2

Wisconsin 3.6 6.1

Wyoming 0.0 0.5

Total 60.5 188.1

Note: The production of bioenergy crops is not assumed in Arizona, California, Idaho, Nevada, New Mexico, and Utah. Although production occurs in Oregon

and Washington, harvest has not yet occurred by 2008. Addition of annualized production of poplar under Scenario 1 adds an additional 35.5 million dry tons

with production occurring in Oregon and Washington.

* Delaware 0.03; Rhode Island 0.005

18
Figure 13. Biomass production at selected prices by cropland type and assuming the

 production management scenario on CRP acres (million dt)

national production in the year 2008 under the wildlife

management scenario is an estimated 60.5 million dry tons

annually. While most of the poplar is not harvested until

after 2008, its contribution can be annualized to provide

an equivalent annual amount of 35.5 million dry tons, for

a total of 96 million tons of feedstock. Under the production management scenario, an estimated 188 million dry

tons could be produced annually, exclusively from switchgrass.

For convenience, we present detailed results of the

analysis for two price scenarios only. It is useful, however, to elucidate the potential national supply by cropland type (cropland in traditional crops, idle, pasture and

CRP) for different price scenarios. Figure 13 presents these

estimates for selected bioenergy crop prices assuming the

production management scenario for bioenergy crops on

CRP acres.

Price Impacts

The shift of cropland from traditional crops to bioenergy crops results in higher prices for traditional crops.

The impact on traditional crop prices is a function of the

acreage shifted to bioenergy crops, as well as the elasticity of supply and demand parameters for each crop. Price

impacts for the two scenarios are presented in Table 12.

Traditional crop prices increase by an estimated 4 percent

to 9 percent under the wildlife management scenario, depending on crop, and by an estimated 9 percent to 14 percent under the production management scenario. Cotton

and rice experience the largest price increases under the

wildlife management scenario, while cotton and sorghum

show the largest increases under the production management scenario. It should be noted that the higher estimated

prices for the major crops, except wheat, are within the

range of historical market prices experienced by these

crops over the last 5 years. For example, corn prices have

ranged between $1.95/bu and $3.24/bu. Because POLYSYS calculates the price as changes from the baseline

price, the level of the final prices is highly influenced by

the price level assumed in the baseline. It should also be

noted that POLYSYS is not able to estimate price changes

for alfalfa and other hay crops that are generally determined locally rather than at the national level.

Net Farm Income Impacts

The overall impact of bioenergy crop production on

agriculture is summarized by changes in net farm income.

To account for the contribution of bioenergy crops to net

19

0

50

100

150

200

250

27.5 32.5 37.5 42.5 47.5

Price ($/dry ton)

Quantity (dry tons)

Millions

Crop Acres CRP Acres Idle Acres Pasture Acres
Billion $

USDA Wildlife Production

Baseline management management

(Feb. 1999) scenario scenario

Crops & Livestock 50.5 52.6 54.2

Bioenergy Crops 0 0.7 2.3

Total Net Farm Income 50.5 53.3 56.5

Table 13. Changes in net farm income, 2008

Crop Baseline Price Bioenergy Crop Management Scenario

Value Difference

Wildlife Production Wildlife Production

Corn/bu. $2.55 2.65 2.79 $0.10 4% $0.24 9%

Sorghum/bu. 2.44 2.57 2.77 0.13 5% 0.33 14%

Oats/bu. 1.50 1.58 1.67 0.08 5% 0.17 11%

Barley/bu. 2.35 2.43 2.55 0.08 3% 0.20 9%

Wheat/bu. 4.25 4.40 4.74 0.15 4% 0.49 12%

Soybeans/bu. 6.10 6.42 6.71 0.32 5% 0.61 10%

Cotton/cwt. 0.68 0.74 0.77 0.06 9% 0.09 13%

Rice/cwt. 10.37 11.23 11.37 0.86 8% 1.00 10%

Table 12. Price changes for major crops in 2008

farm income, the net present value resulting from the

production of biomass is expressed in terms of an annuity and added to the farm income measures used for the

major crops and livestock sector. Again, POLYSYS is

not able to estimate changes in alfalfa and other hay prices

,which are generally determined locally rather than nationally. Alfalfa and other hay prices are likely to increase, generating extra income for producers and,

consequently, to cause losses for livestock producers who

feed hay and alfalfa to their cattle. The net effects, which

could be negative, neutral, or positive, have not been

accounted for in the income estimates.

The changes in the annual net farm income generated

in the year 2008 under the two scenarios are shown in

Table 13. Under the wildlife management scenario, a gain

of $2.8 billion is projected, with bioenergy crops accounting for $700 million of that total and the rest resulting

from higher traditional crop prices. Under the production management scenario, a gain of $6.0 billion is projected, with bioenergy crops accounting for $2.3 billion

of that total and the rest resulting from higher traditional

crop prices.

Table 14 presents the change in estimated net farm

income resulting directly from the introduction of bioenergy crop production by State for the two scenarios.

Under the wildlife management scenario, the gains in

income generated by the production of bioenergy crops

are highest in the Midwest, Northern Plains, Southeast,

and Delta regions, although gains are also experienced

in the Southern Plains and New England. Under the

higher price scenario, North and South Dakota experience significant income gains from bioenergy crop production. Bioenergy crops could potentially provide an

effective alternative for these wheat-dependent States.

States with a relatively larger agricultural base also benefit the most from the price increase experienced by the

major crops.

20
Wildlife Production

management management

scenario scenario

State Million dollars

Alabama 22 89

Arkansas 10 63

Connecticut 0 1

Delaware 0 0

Florida 0 11

Georgia 3 40

Illinois 53 128

Indiana 19 76

Iowa 112 184

Kansas 26 127

Kentucky 27 75

Louisiana 20 76

Maryland 1 3

Massachusetts 0 2

Michigan 17 55

Minnesota 16 58

Mississippi 36 131

Missouri 88 214

Montana 0 19

Nebraska 32 83

New Hampshire 0 1

New Jersey 0 1

New York 1 25

North Carolina 4 21

North Dakota 1 137

Ohio 32 128

Oklahoma 7 55

Oregon 9 0

Pennsylvania 0 22

Rhode Island 0 0

South Carolina 7 32

South Dakota 20 137

Tennessee 37 129

Texas 16 75

Vermont 0 2

Virginia 2 27

Washington 6 0

West Virginia 1 12

Wisconsin 41 87

Wyoming 0 5

Total 666 2,331

Note: The production of bioenergy crops is not assumed in Arizona, California, Idaho, Nevada, New Mexico, and Utah.

Table 14. Changes in net farm income by State, 2008

Comparison between the wildlife management scenario and

the production management scenario

21
Wildlife Production

management management

scenario scenario

Switchgrass SRWC* Switchgrass SRWC*

Million Acres 12.3 7.1 41.9 0

Million Dry tons 60.5 35.5 188.1 0

Quads 0.94 0.60 2.92 0

Billion Gallons of ethanol 5.36 3.15 16.67 0

Million Barrels of oil displaced 81.2 47.7 252.4 0

MW electricity capacity 14,119 9.086 43,897 0

Percent of electricity capacity 1.51 0.97 4.67 0

Billion kWh electricity (gasifier combined cycle) 98.9 63.7 307.6 0

Percent of electricity supplied 2.3 1.5 7.3 0

* SWRC - Short Rotation Woody Crop (poplar and willow)

Notes: Energy content of energy crops assumes 15.5 MBtu/dt for switchgrass and 17 MBtu/dt for hybrid poplar.

Ethanol conversion rate is assumed to be 88.8 gallons/dt.

Oil displaced does not subtract fuel used in crop production and conversion.

Electricity estimates assume gasifier combined cycle with 36% conversion efficiency and 80% operating rate.

Electricity capacity and supply taken from DOE energy Information Administration, Annual Energy Outlook ë99

reference case for the year 2008.

Table 15. Annual energy production equivalents for bioenergy crops, 2008

Energy Supply Implications

Bioenergy crops are being developed as feedstocksfor

energy or biobased products. Table 15 presents the energy equivalents that could be obtained from bioenergy

crop production under the two scenarios. Under the wildlife management scenario, the 96 million dry tons of biomass (60.5 million tons of switchgrass and an additional

35.5 millions tons from the annualized production of poplar that are harvested starting in 2009) produced is equivalent to 1.54 Quads (1015Btu) of primary energy. Given

current conversion efficiencies, this quantity could be used

to produce 8.5 billion gallons of ethanol and displace 129

million barrels of oil annually if used as a transportation

fuel in place of gasoline. Current annual fuel ethanol production from corn is about 1.4 billion gallons. Alternatively, this quantity of biomass could be used to produce

163 billion kilowatthours of electricity (assuming a gasifier combined cycle technology), which is equivalent to

about 3.8 percent of the electricity currently produced in

the United States.

Under the production management scenario, annual bioenergy crop production of 188.1 million tons is equivalent to 2.92 Quads of primary energy. Given current

conversion efficiencies, it could be used to produce 16.7

billion gallons of ethanol and displace 252 million barrels

of oil each year. Alternatively, that quantity of biomass

could be used to produce 308 billion kilowatthours of electricity which is equivalent to about 7.3 percent of the electricity currently produced in the United States.

22
The widespread introduction of bioenergy crops to

agriculture could have significant impacts for the agricultural sector. Substantial cropland acres (up to 42 million acres at a switchgrass price of $40/dt) could be

profitably shifted to the production of bioenergy crops

under the price and management scenarios analyzed in

this study. This level of production would make bioenergy crops the fourth largest crop produced in the United

States, in terms of total acres, behind corn, wheat, and

soybeans.

Net farm income is estimated to increase in the year

2008 by $2.8 wildlife management scenario and $6.0

billion under the production management scenario. In

recent years, prices for traditional crops have been low.

To maintain farm income, the Federal Government has

made direct payments to farmers. These direct payments

equaled $12.3 billion in 1998, $21.5 billion in 1999, and

$22.9 billion in 2000. Bioenergy crops offer a potential

new production activity that could have a positive impact on farm income.

Increased farm income is a result of the value of the

bioenergy crop production itself, as well as an increase

over projected baseline prices for traditional crops. Prices

for traditional crops are estimated to increase from 3

percent to 14 percent depending on the traditional crop

and the bioenergy crop scenario analyzed. Estimated

prices are well within the range of the historic variability of traditional crop prices. For example, under the production management scenario ($40/dt for switchgrass),

the corn price is projected to increase from a baseline

price of $2.55/bu to $2.79/bu, a 9 percent increase. Over

the past 5 years, market prices for corn have ranged from

$1.95/bu to $3.24/bu (USDA, April 1999). During this

same time, food prices have remained stable, generally

averaging less than a 3 percent increase per year (Elitzak).

The analysis also indicates that CRP acres could become a significant source of biomass crops. Clearly, criteria to determine suitable CRP acres and appropriate

bioenergy crop management practices must be developed

before CRP acres can be used for bioenergy crop production. However, the analysis of the two management

practices examined suggests substantial economic potential to use CRP program acreage for bioenergy crop

production. The environmental ramifications of various

management practices must be examined to ensure that

there is not a substantial loss of environmental benefits

resulting from the production of bioenergy crops on CRP

acres. Research is ongoing to determine the implications

of bioenergy crop production on environmental parameters such as biodiversity and soil and water quality (see,

for example, the 1998 edition of Biomass and BioenSUMMARY AND CONCLUSIONS

ergy, volume 14, number 4, for several articles. Also see

Tolbert and Wright, 1998; Christian et al, 1997; Christian, 1997; Hanowski et al, 1997; Schiller et al, 2000;

Ma et al, 2000, Tolbert et al, 1999; and Perry et al, 2000

among other studies).

Currently, about 2.6 Quads of the primary energy used

in the industrial sector in the United States comes from

biomass resources (USDOE, 1999). President Clinton,

in an Executive Order signed August 12, 1999, called

for a threefold increase in the use of bioenergy and biobased products. Bioenergy crops could play a significant role in achieving that goal. Under the production

management scenario, an estimated 188 million dry tons

of biomass could be produced. This quantity is equivalent to 2.92 Quads of primary energy. If used to produce

ethanol, production would increase nearly 1,100 percent

over the current ethanol production level. Alternatively,

188 million dry tons of biomass could be used to produce nearly 7.3 percent of the electricity currently produced in the United States.

Interpretation of the results should consider the limitations to the analysis. For example, in the analysis, acres

are allocated based on relative average profitability for

an entire ASD. Variations within an ASD are not considered. Thus, while the average profitability of switchgrass

may be greater than the average profitability of hybrid

poplar and willow in most ASDs, there may be some

acres within any given ASD for which hybrid poplar or

willow are relatively more profitable than switchgrass.

These situations are not captured by the analysis. As a

result, nearly all of the acres allocated to bioenergy crop

production are allocated to switchgrass. Additionally, the

analysis considers only the timeframe of 1999-2008. Improvements in yields and production technologies are

occurring for both bioenergy crops and traditional crops.

The analysis is also limited by the inability of the

model to estimate price changes for alfalfa and hay. Thus,

there may be some income losses in the livestock sector

not accounted for in the analysis as well as corresponding gains in the production of hay and alfalfa.

Additionally, the analysis is a supply-side analysis

only. It is beyond the scope of this project to analyze the

infrastructure and prices needed to make bioenergy a

reality. Farmgate prices of $40/dt are higher than mid1999 market prices for fossil fuels. In addition, it should

be noted that fossil fuel market prices do not fully reflect many of the environmental and social externalities

associated with their use. This point is particularly significant in light of growing concerns over global climate

change.

23
REFERENCES

Christian, D.P., P.T. Collins, J.M. Hanowski, G.J. Niemi. 1997. ìBird and small mammal use of short-rotation hybrid

poplar plantations.î Journal of Wildlife Management. 61(1):171-182.

Christian, D.P. 1997. ìWintertime use of hybrid poplar plantations by deer and medium-sized mammals in the Midwestern U.S.î Biomass and Bioenergy 12(1):35-40.

De La Torre Ugarte, Daniel G., and Daryll E. Ray 2000. Biomass and bioenergy applications of the POLYSYS modeling framework. Biomass and Bioenergy. 18(4):291-308.

DeLucchi, M.A. 1991. Emissions of Greenhouse Gases from the Use of Transportation Fuels and Electricity, Argonne

National Laboratory, ANL/ESD/TM-22.

Elitzak, Howard, Food Cost Review, 1950-1997, U.S. Department of Agriculture, Economic Research Service, AER780.

Food and Agricultural Policy Research Institute. 1999. The Rainbow Book: A Summary of the November 1998 FAPRI

Baseline. University of Missouri, January 1999.

Graham, Robin L., L.J. Allison, and D.A. Becker. 1996. ORECCL - Oak Ridge energy crop county level database.

Proceedings of Bioenergy í96, Nashville, Tennessee, Sept. 15-19th, 1996. pp. 522 to 529.

Hanowski, J.M., G.J. Niemi, D.P. Christian. 1997. ìInfluence of Within-Plantation Heterogeneity and Surrounding

Landscape Composition on Avian Communities in Hybrid Poplar Plantations.î Conservation Biology 11(4):936-944.

Ma, Z., C.W. Wood, D.I. Bransby. 2000. ìCarbon Dynamics Subsequent to Establishment of Switchgrass.î Biomass

and Bioenergy 18:93-104.

Mann, K., and P.L. Spath 1999.î The Net CO2

 Emissions and Energy Balances of Biomass and Coal-Fired Power

systems.î Proceedings of the Fourth Biomass Conference of the Americas, R.P. Overend and E. Chornet (eds.), Elsevier Science, Ltd., United Kingdom, pp. 379-385.

McBride, William. 1996. Datasets on Machinery Complements and Machinery Prices. Economic Research Service,

USDA.

Perry, C.H., R.C. Miller, and K.N. Brooks. 2000. (Accepted for publication.) ìImpacts of Short-Rotation Woody

Crops on Regional Water Yield.î Forest Ecology and Management.

Schiller, A., W.A. Cresko, J.E. Lindberg, V.R. Tolbert. 2000. ìBird Communities on Intensively Managed Forests

from Planting to Harvest in the Southeastern United States.î Submitted to Ecological Applications.

Slinsky, Stephen P., and Kelly H. Tiller 1999. ìApplication of an Alternative Methodological Approach for Budget

Generators for Research.î Selected paper, published abstract. Journal of Agricultural and Applied Economics.

31(2):401.

Tolbert, V. R., and L. L. Wright. 1998. ìEnvironmental Enhancement of U.S. Biomass Crop Technologies: Research

Results to Date.î Biomass and Bioenergy 15(1):93-100.

Tolbert, V. R., J. D. Joslin, F. C. Thornton, B. R. Bock, D. E. Pettry, W. Bandaranayake, D. Tyler, A. Houston, and S.

Schoenholtz. 1999. ìBiomass Crop Production: Benefits for Soil Quality and Carbon Sequestration.î Proceedings of

the Fourth Biomass Conference of the Americas, R.P. Overend and E. Chornet (eds.), Elsevier Science, Ltd., United

Kingdom, pp. 127-132.

24
U.S. Department of Agriculture, National Agricultural Statistics Service, 1997 Census of Agriculture. March 1999.

U.S. Department of Agriculture,World Agricultural Outlook Board, Office of the Chief Economist. 1997. Agricultural

Baseline Projections to 2008. Prepared by the Interagency Agricultural Projections Committee. Staff Report No.

WAOB-99-1.

U.S. Department of Agriculture, Economic Research Service, 1999. Feed Yearbook, FDS-1999.

U.S. Department of Agriculture, Economic Resource Service, 2000. Agricultural Outlook, AGO-268.

U.S. Department of Energy, Energy Information Administration, Annual Energy Review-1998, July 1999.

U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 1999.

Walsh, Marie E., and D.A. Becker. BIOCOST: A Software Program to Estimate the Cost of Producing Bioenergy

Crops.î Proceedings of Bioenergy í96, Nashville, Tennessee, September 15-19, 1996. pp. 480 to 486.

Wang, M., C. Saricks, and D. Santini 1999. Effects of Fuel Ethanol Use on Fuel-Cycle Energy and Greenhouse Gas

Emissions, Argonne National Laboratory, ANL/ESD-38.

25
26

Alternative crops ñ Crops other than the eight major U.S.

crops (corn, wheat, soybeans, cotton, rice, grain sorghum, barley, and oats), alfalfa and other hay.

Bioenergy crops ñ Crops grown for industrial use (i.e.,

bioethanol, biodiesel, electricity, other bioproducts such

as chemicals, plastics) rather than food and feed uses.

Biomass ñ Any product of a biological process that can

be used to produce energy or bioproducts. This includes

bioenergy crops as well as food processing wastes,

agricultural residues such as corn stover and grain straw,

other agricultural processing wastes such as cotton gin,

forest and mill residues, animal wastes, and urban wood

wastes.

Conservation Reserve Program ñ A land retirement program authorized by U.S. law to take environmentally

sensitive agricultural land out of production in exchange

for direct rental payments and cost-sharing.

Crop acreage shifts ñ A change in acreage dedicated to a

given crop in response to changes in economic and/or

production considerations.

Cropland - Agricultural land used for crops, pasture, or

grazing. This category includes land from which crops

were harvested or hay was cut, land in orchards, citrus

groves, vineyards, nurseries, and greenhouses; cropland used only for pasture or grazing; land in covered

crops, legumes, and soil-improvement grasses; land on

which all crops failed; land in cultivated summer fallow; and idle cropland.

Crop budgeting ñ A detailed listing of prices, yields, practices, input and machinery use, and costs, associated

with a specific crop or crop rotation.

Filter strips ñ Narrow bands of crop acreage, generally

planted to grass, used to filter runoff from cultivated

fields before the water enters a lake or a stream.

GLOSSARY

Fossil fuel ñ Fuel derived from plants that grew in past

geologic ages (e.g. coal, natural gas, crude oil)

Hybrid poplars ñ Any one of a variety of poplars (genus

Populus) bred for high productivity and short production cycles and used for fiber, energy or bioproducts.

Hybrid willow ñ Any one of a variety of willows (genus

Salix) bred for high productivity and short production

cycles and used for fiber, energy or bioproducts.

POLYSYS ñ A computerized economic simulation model

of the U.S. agricultural sector in which planting decisions are made at the regional level (305 Agricultural

Statistics District), while crop and livestock demands

and market prices are solved at the national level.

Riparian buffers ñ Usually grass strips and/or trees and

shrubs that are grown along the banks of water courses

to protect the waterway from pollution caused by surrounding crop or pasture land. (See filter strips.)

Switchgrass- A warm season, native perennial grass (Panicum virgatum) that can be grown as a dedicated bioenergy crop.

Wetlands ñ an ecosystem that depends on constant or recurrent, shallow inundation or saturation at or near the

surface of the substrate and displays the physical,

chemical, and biological features reflective of a recurrent or sustained inundation. Common diagnostic features of wetlands are hydric soils, and hydrophytic

vegetation.

Windbreaks ñ plantings of trees or brush for the purpose

of sheltering an area from the direct impact of wind or

to control snow drifting.
APPENDICES

Table of Contents

Appendix 1: List of Participants in POLYSYS Data Review Workshop, Knoxville, TN, November 19, 1997 28

Appendix 2: Sources Used in Developing Biomass Budgets .................................................................................. 29

Primary data source ...................................................................................................................................... 29

Personal communications ............................................................................................................................. 30

Extension Service .......................................................................................................................................... 30

U.S. Department of Agriculture .................................................................................................................... 35

The University of Tennessee ......................................................................................................................... 35

Experiment Stations ...................................................................................................................................... 35

NC214 Regional Project Group.................................................................................................................... 35

Appendix 3: Bioenergy Crops Management Practices........................................................................................... 36

Appendix Table 3.1: Management Practices for Bioenergy Crops on Cropland

Currently Planted to Traditional Crops.................................................................................................... 36

Appendix Table 3.2: Management Practices for Bioenergy Crops on Cropland

Currently Idled or Planted to Pasture....................................................................................................... 37

Appendix 3.3: Management practices of bioenergy crops on Conservation Reserve Program acres ......... 37

Appendix 4: Regional NPV Production Costs and Returns for Bioenergy Crops .............................................. 40

27
Dr. Larry Abrahamson

State University of New York

College of Environmental Science and Forestry

Dr. Dwayne Buxton

USDA-ARS-NPS

Ms. Janet Cushman

Oak Ridge National Laboratory

Dr. Robin Graham

Oak Ridge National Laboratory

Dr. John Hom

USDA-FS

Dr. Jud Isebrands

North Central Forestry Experiment Station

Forestry Sciences Laboratory

Dr. Sandy McLaughlin

Oak Ridge National Laboratory

Mr. Tien Nguyen

U.S. Department of Energy

Mr. Rick Pierce

Champion International

Dr. Daryll Ray

The University of Tennessee Knoxville

Agricultural Policy Analysis Center

Dr. Dan Robison

Department of Forestry

North Carolina State University

Dr. Hosein Shapouri

Office of Energy Policy and New Uses

USDA

Mr. Steve Slinsky

The University of Tennessee Knoxville

Agricultural Policy Analysis Center

Mr. Mike Sullivan

Champion International

Mr. Alan Teel

Iowa State University

Dr. Kelly Tiller

The University of Tennessee Knoxville

Agricultural Policy Analysis Center

Dr. Jerry Tuskan

Oak Ridge National Laboratory

Dr. Daniel De La Torre Ugarte

The University of Tennessee Knoxville

Agricultural Policy Analysis Center

Dr. Ken Vogel

USDA-ARS

Dr. Marie Walsh

Oak Ridge National Laboratory

Ms. Lynn Wright

Oak Ridge National Laboratory

Appendix 1. List of Participants in

POLYSYS Data Review Workshop

Knoxville, TN

November 19, 1997

28
Appendix 2. Sources used in developing biomass budgets

Primary Data Source

State Level of Resolution Source

of Information

Alabama Substate USDA (Benson), The University of Tennessee (De La Torre Ugarte)

Arizona Substate Experiment Station

Arkansas Substate Extension Service

California Substate USDA (Benson), Extension Service

Colorado Substate Extension Service

Connecticut State Neighboring State (NY)

Delaware State Extension Service

Florida State Extension Service, The University of Tennessee (De La Torre Ugarte)

Georgia State USDA (Benson), The University of Tennessee (De La Torre Ugarte)

Idaho Substate Extension Service

Illinois State USDA (Benson)

Indiana Substate Neighboring State (IL and OH)

Iowa State USDA (Benson)

Kansas State USDA (Benson), Experiment Station (Kansas State University)

Kentucky State Neighboring State (TN), Extension Service

Louisiana Substate Extension Service

Maine State Extension Service

Maryland State Extension Service

Massachusetts State Neighboring State (NY)

Michigan State USDA (Benson), Neighboring State (MN and IL)

Minnesota Substate The University of Tennessee (English)

Mississippi Substate Extension Service, The University of Tennessee (De La Torre Ugarte)

Missouri Substate USDA, NC214 Regional Project

Montana Substate Extension Service and Personal Communication (Zidack)

Nebraska Substate Extension Service, NC214 (Baker), Personal Communication (Bernhardt)

Nevada State Neighboring State (UT)

New Hampshire State Neighboring State (NY)

New Jersey State Neighboring State (PA)

New Mexico State USDA (Benson), Extension Service

New York State Extension Service

North Carolina State USDA, The University of Tennessee (De La Torre Ugarte)

North Dakota Substate Neighboring States (MT, SD, and MN)

Ohio Substate Personal Communication (Batte)

Oklahoma State USDA (Benson)

Oregon Substate Extension Service

Pennsylvania State Extension Service

Rhode Island State Neighboring State (NY)

South Carolina State USDA, The University of Tennessee (De La Torre Ugarte)

South Dakota Substate Extension Service and NC214 (Janssen)

Tennessee State Extension Service, The University of Tennessee (De La Torre Ugarte)

Texas Substate USDA (Benson)

Utah State USDA (Benson)

Vermont State Neighboring State (Maine)

Virginia State USDA

Washington Substate Extension Service and Personal Communication

West Virginia State Neighboring State (VA)

Wisconsin Substate Neighboring States (MN and IL)

Wyoming State Extension Service

Bold face type used in listing to improve readability of appendix

29
Personal Communications

Kentucky Isaacs, Steve. Personal Communication. University of Kentucky, Extension Economics. August 1995.

Montana Zidack, Walt. Personal Communication. Montana State University, Extension Economics. March

1996.

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30
Stuart, Clyde A., and T.E. Windham. Estimating 1994 Production Costs in Arkansas ñ Grain Sorghum: Clay Soils. University of Arkansas Cooperative Extension Service. Extension Technical

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Stuart, Clyde A., T.E. Windham, and R.L. Rainey. Estimating 1994 Production Costs in Arkansas ñ

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Stuart, Clyde A., T.E. Windham, and R.L. Rainey. Estimating 1994 Production Costs in Arkansas ñ

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Windham, Tony E., C.A. Stuart, and M.P. Mason. Estimating 1994 Production Costs in Arkansas ñ

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31
Windham, Tony E., C.A. Stuart, and M.P. Mason. Estimating 1994 Production Costs in Arkansas ñ

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Arkansas Cooperative Extension Service. Extension Technical Bulletin No. 234. 1994.

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December 1994.

35
Appendix Table 3.1: Management Practices for Bioenergy Crops on Cropland Acres

Currently Planted to Traditional Crops

(SE = Southeast; App = Appalachia; CB = Corn Belt; LS = Lake States; NP = Northern Plains; SP = Southern Plains;

PNW = Pacific Northwest; NE = Northeast)

I. Switchgrass

A. Establishment Year

1. 1x disk, 1.15x grain drill

2. 5.75 lb seed/acre (Alamo in SE, APP, SP; Cave-in-Rock in NP; Pathfinder in CB, LS)

3. 1x lime (1 ton/ac in LS, CB; 2 ton/ac in SE, APP; 0 elsewhere).

4. 1x P (15 lb/ac P in all regions) and N (20 lb/dry ton yield in SE; 25 lb/dt yield in SP; 0 elsewhere).

5. 1x 2,4-D (1 lb a.i./acre in all regions)

6. 1x Plateau (2 lb a.i./acre in all regions)

7. 1x harvest (mow, rake, 4x6 round bale, move to side of field and stack)

8. Yield is 30 percent of expected average annual yield

B. Maintenance Years (Years 2-10)

1. 1x K (25 lb/ac in years 3, 6, and 9 east of the Mississippi River; no K west of the Mississippi River) and

N (25 lb/dry yield ton annually in SP; 20 lb/dry ton yield annually elsewhere)

2. 1x harvest annually (mow, rake, 4x6 round bale, move to side of field and stack)

3. Yield is 67 percent of expected yield in year 2 and 100 percent in yrs. 3-10

4. In year 10 following harvest, 1x application glyphosate (2 lb a.i./acre)

II. Hybrid Poplar

A. Establishment Year

1. 2x disk

2. Manual planting of cuttings (8' x 10' spacing; 545 trees/acre; $0.24/cutting-planting)

3. 1x Fusilade (quart/acre) or Transline (pint/acre) in all regions

4. 1x Linuron (1.5 lb a.i./acre in LS) or 1x Oust (0.15 lb a.i./acre elsewhere)

5. 3x cultivations

B. Maintenance Years

1. 1x N (75 lb/ac in yr 3 in PNW; 75 lb/ac in yr 4 elsewhere)

2 1x lime in yr 3 (1 ton/ac in SE, APP; 1.5 ton/acre in NP, SP; none elsewhere)

3. 1x K in yr 3 (35 lb/ac in LS; 50 lb/ac in CB, APP; 40 lb/ac in SE; 15 lb/ac in NP, PNW; and 25 lb/ac SP)

and 1x P in yr 3 (20 lb/ac in LS, SE, PNW; 15 lb/ac in NP, SP; 25 lb/ac in APP; 50 lb/ac in CB)

4. 2x cultivation in yr 2 (all regions but PNW where it is 1x)

5. 1x cultivation in yr 3 (all regions but PNW where it is 0x)

6. 1x Seven in yr 2 (all regions but PNW where it is 0x)

7. 1x harvest (feller buncher, skid, chip, blow into truck) (yr 10 in LS, CB, NP, NE; yr 8 in SE, SP; yr 6 in

PNW)

8. Following harvest, 1x glyphosate (2 lb a.i./ac) - forestry disk

III. Willow

A. Establishment Year

1. 2x disk

2. Mechanical planting (6200 trees/acre; $0.10/cutting; $0.02/cutting to plant)

3. 1x glyphosate (2 lb a.i./acre)

4. 1x Goal (1 lb a.i./acre)

B. Maintenance Years (Years 2-22)

1. 1x N (100 lb/ac in yrs 2, 5, 8, 11, 14, 17, 20)

2. 1x harvest in yrs 4, 7, 10, 13, 16, 19, 22 (Claas-Jaguar; blow into trailer; load into chip van)

3. After final harvest, 1x glyphosate (2 lb a.i./ac), 2x heavy forestry disk, 1x harrow rake

4. Yield is 60 percent expected yield in yr 4 and 100 percent expected yield thereafter

Appendix 3: Bioenergy Crops Management Practices

36
Appendix Table 3.2: Management Practices for Bioenergy Crops on Cropland Acres

Currently Idled or Planted to Pasture

(SE = Southeast; App = Appalachia; CB = Corn Belt; LS = Lake States; NP = North Plains; SP = South Plains; PNW

= Pacific Northwest; NE = Northeast)

I. Switchgrass

A. Establishment Year

1. 1x glyphosate (2 lb a.i./ac)

2. 2x disk

3. 1.15 grain drill

4. 5.75 lb seed/acre (Alamo in SE, APP, SP; Cave-in-Rock in NP; Pathfinder in CB, LS)

5. 1x lime (1 ton/ac in LS, CB; 2 ton/ac in SE, APP; 0 elsewhere).

6. 1x P (15 lb/ac P in all regions) and N (20 lb/dry ton yield in SE; 25 lb/dt yield in SP; 0 elsewhere)

7. 1x Plateau (2 lb a.i./acre in all regions)

8. 1x harvest (mow, rake, 4x6 round bale, move to side of field and stack)

9. Yield is 30 percent of expected average annual yield

B. Maintenance Years (Years 2-10)

1. 1x K (25 lb/ac in years 3, 6, and 9 east of the Mississippi River; no K west of the Mississippi River) and

N (25 lb/dry yield ton annually in SP; 20 lb/dry ton yield annually elsewhere)

2. 1x harvest annually (mow, rake, 4x6 round bale, move to side of field and stack)

3. Yield is 67 percent of expected yield in year 2 and 100 percent in yrs. 3-10

4. In year 10 following harvest, 1x application glyphosate (2 lb a.i./acre)

II. Hybrid Poplar

A. Establishment Year

1. 1x glyphosate (2 lb a.i./ac)

2. Moldboard plow, 2x disk

3. Manual planting of cuttings (8' x 10' spacing; 545 trees/acre; $0.24/cutting)

4. 1x Fusilade (quart/acre) or Transline (pint/acre) in all regions

5. 3x cultivations

B. Maintenance Years

1. 1x N (75 lb/ac in yr 3 in PNW; 75 lb/ac in yr 4 elsewhere)

2. 1x lime in yr 3 (1 ton/ac in SE, APP; 1.5 ton/acre in NP, SP; none elsewhere)

3. 1x K in yr 3 (35 lb/ac in LS; 50 lb/ac in CB, APP; 40 lb/ac in SE; 15 lb/ac in NP, PNW; and 25 lb/ac SP)

and 1x P in yr 3 (20 lb/ac in LS, SE, PNW; 15 lb/ac in NP, SP; 25 lb/ac in APP; 50 lb/ac in CB)

4. 2x cultivation in yr 2 (all regions but PNW where it is 1x)

5. 1x cultivation in yr 3 (all regions but PNW where it is 0x)

6. 1x Seven in yr 2 (all regions but PNW where it is 0x)

7. 1x harvest (feller buncher, skid, chip, blow into truck) (yr 10 in LS, CB, NP, NE; yr 8 in SE, SP; yr 6 in

PNW)

8. Following harvest, 1x glyphosate (2 lb a.i./ac)

III. Willow

A. Establishment Year

1. 2x disk

2. Mechanical planting (6200 trees/acre; $0.02/cutting)(0.10/cutting; 0.02/cutting to plant)

3. 1x glyphosate (2 lb a.i./acre)

4. 1x Goal (1 lb a.i./acre)

B. Maintenance Years (Years 2-22)

1. 1x N (100 lb/ac in yrs 2, 5, 8, 11, 14, 17, 20)

2. 1x harvest in yrs 4, 7, 10, 13, 16, 19, 22 (Claas-Jaguar; blow into trailer; load into chip van)

3. After final harvest, 1x glyphosate (2 lb a.i./ac), 2x heavy forestry disk, 1x harrow rake

4. Yield is 60 percent expected yield in yr 4 and 100 percent expected yield thereafter

37
Appendix Table 3.3: Management Practices of Bioenergy Crops on Conservation Reserve

Program Acres

I. CRP Acres under the Production Management Scenario

A. This scenario assumes that upon expiration of current CRP contracts:

1. The same acres are reenrolled in a CRP program at 75 percent of the rental rate that they currently receive

2. The acres will be allowed to be replanted into switchgrass, poplar, or willow

3. Government sharing of establishment costs is not assumed

4. Annual harvest is allowed

5. Management practices to encourage high biomass yields are used

6. Early-out options with no penalty are allowed

B. CRP acres allowed to be harvested include all acres currently enrolled in CRP program in designated geographic

areas for biomass energy crop production except:

1. Acres in special-uses categories (riparian buffers, filter strips, windbreaks, wetlands, etc.)

2. Acres designated as essential to maintaining water quality in watersheds

3. Acres designated as essential to maintaining critical wildlife habitat in high-priority wildlife regions (i.e.,

Prairie Pothole region, etc.)

C. Management practices:

1. Acres replanted to high-yielding switchgrass or poplar or willow varieties suitable to region

2. Herbicide applications the same as for non-CRP biomass acres

3. Fertilizer applications applied in same years as for non-CRP biomass acres at the same rate for poplar and

willow. For switchgrass, P, K, and lime applied as for non-CRP acres and nitrogen applied at a rate of 10

lb/ton expected yield for switchgrass everywhere but in the South Plains where the rate is 15 lb/ton expected yield

D. Harvest practices:

1. For switchgrass, annual harvest of entire field is allowed, 4-6" height

2. For poplar and willow, harvest of entire field in same years as for non-CRP acres

E. Biomass yields on CRP acres are adjusted relative to yields on non-CRP acres using a crop efficiency index

provided by FSA

II. CRP Acres under the Wildlife Management Scenario

A. This scenario assumes that upon expiration of current CRP contracts:

1. The same acres are reenrolled in the CRP program at 75 percent of the rental rate that they currently

receive

2. The acres will be allowed to be replanted into switchgrass, poplar, or willow

3. No government sharing of establishment costs is assumed

4. Management practices to ensure high wildlife diversity are used

5. Early-out options with no penalties are allowed

B. CRP acres allowed to be harvested include all acres currently enrolled in CRP program in designated geographic

areas for biomass energy crop production except:

1. Acres in special-uses categories (riparian buffers, filter strips, windbreaks, wetlands, etc.)

2. Acres designated as essential to maintaining water quality in watersheds

3. Acres designated as essential to maintaining critical habitat in high-priority wildlife regions (i.e., Prairie

Pothole region, etc.)

C. Management practices:

1. Acres replanted to high-yielding switchgrass or poplar or willow varieties suitable to region. Planting will

use no-till operations. Poplar and willow will be planted with a cover crop

2. Glyphosate herbicide application of 2 lb a.i. in establishment year

3. Nitrogen fertilizer applied every 3 years beginning in year 2 to switchgrass at a rate of 10 lb/expected ton

in all regions but the South Plains where the rate is 15 lb/expected ton. Nitrogen applied to poplar and

willow as on non-CRP acres. Potassium and phosphorus added as on non-CRP acres for all biomass

crops. No lime added for any biomass crop

4. Cover crop of annual ryegrass planted with switchgrass and poplar and willow at a rate of 3 lb/ac and 5 lb/

ac respectively

38
D. Harvest Practices:

1. Harvest will be every 3 years for willow and after 10 years for poplar

2. For switchgrass, half of the field will be harvested in years 3, 5, 7, and 9 and the other half will be

harvested in years 4, 6, 8, and 10 at a height of 6-8"

E. Biomass yields are adjusted by an index of crops on CRP acres compared to non-CRP acres

39
Appendix 4. Regional Net Present Value production costs and returns for bioenergy crops

(per acre)(price=$2.58/MBtu)

Northeast Appalachia

Switchgrass Poplars Willows Switchgrass Poplars Willows

Mature Yield 4.87 39.87 16.23 5.84 35.77 15.00

Revenue $1,246.16 $976.69 $2,176.78 $1,494.37 $984.55 $2,011.82

Seed Cost $27.93 $123.40 $701.89 $27.93 $123.40 $701.89

Fertilizer N $240.39 $23.99 $158.20 $260.95 $21.73 $144.93

Fertilizer P $4.26 $6.33 $0.00 $4.02 $5.98 $0.00

Fertilizer K $6.82 $5.36 $0.00 $7.30 $5.73 $0.00

Fertilizer Lime $47.15 $20.98 $0.00 $45.33 $20.18 $0.00

PH* Chemical $13.09 $34.76 $88.11 $13.09 $34.76 $88.11

PH Labor $15.50 $15.92 $7.66 $13.01 $13.20 $6.45

PH Mach Var $24.16 $21.23 $7.98 $19.28 $18.94 $8.25

PH Mach Fixed $33.79 $27.72 $11.55 $27.31 $25.30 $11.88

Interest OPI $15.95 $166.15 $238.66 $16.54 $143.92 $235.80

Harvest Cost $523.02 $403.74 $956.27 $504.81 $481.57 $934.22

CU* Chemical $25.44 $25.44 $12.64 $25.44 $28.58 $12.64

CU Labor $0.94 $3.94 $2.24 $0.79 $3.67 $1.89

CU Mach Var $1.93 $14.91 $7.53 $1.43 $15.37 $6.79

CU Mach Fixed $2.78 $26.52 $13.59 $2.25 $25.24 $10.88

Total Cost $983.14 $920.38 $2,206.33 $969.50 $967.56 $2,163.76

Returns $263.02 $56.31 ($29.55) $524.86 $16.99 ($151.94)

Corn Belt Lake States

Switchgrass Poplars Willows Switchgrass Poplars Willows

Mature Yield 5.98 46.26 15.80 4.80 44.06 15.34

Revenue $1,530.19 $1,133.22 $2,119.11 $1,228.25 $1,079.33 $2,057.42

Seed Cost $10.85 $123.40 $701.89 $10.85 $123.40 $701.89

Fertilizer N $243.60 $19.79 $130.51 $195.66 $19.79 $130.51

Fertilizer P $3.92 $11.63 $0.00 $3.92 $4.65 $0.00

Fertilizer K $4.05 $5.31 $0.00 $4.50 $3.72 $0.00

Fertilizer Lime $12.04 $0.00 $0.00 $12.04 $0.00 $0.00

PH* Chemical $13.09 $34.76 $88.11 $13.09 $32.89 $88.11

PH Labor $14.82 $15.07 $7.22 $16.14 $16.43 $7.79

PH Mach Var $24.03 $20.56 $8.23 $24.80 $20.55 $7.96

PH Mach Fixed $35.48 $27.92 $12.16 $36.12 $27.02 $11.82

Interest OPI $13.69 $155.13 $233.04 $11.74 $147.80 $233.12

Harvest Cost $569.02 $435.20 $945.32 $502.85 $425.70 $937.70

CU* Chemical $25.44 $25.44 $12.64 $25.44 $25.44 $12.64

CU Labor $0.90 $3.73 $2.11 $0.98 $4.07 $2.28

CU Mach Var $1.90 $14.36 $7.29 $1.97 $14.96 $7.42

CU Mach Fixed $2.89 $24.98 $12.77 $2.95 $26.39 $13.07

Total Cost $975.75 $917.26 $2,161.30 $863.10 $892.82 $2,154.30

Returns $554.44 $215.96 ($42.19) $365.14 $186.51 ($96.88)

*PH - Pre Harvest

*CU - Post Harvest

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Southeast Southern Plains Northern Plains Pacific

Northwest

Switchgrass Poplars Switchgrass Poplars Switchgrass Poplars Poplars

Mature Yield 5.49 36.00 4.30 30.01 3.47 38.31 34.37

Revenue $1,404.81 $990.88 $1,100.30 $826.01 $887.92 $960.22 $1,062.95

Seed Cost $27.93 $123.40 $27.93 $123.40 $10.85 $123.40 $123.40

Fertilizer N $248.11 $21.02 $249.77 $19.61 $149.75 $18.67 $23.38

Fertilizer P $3.98 $4.72 $3.90 $3.47 $3.98 $3.54 $5.28

Fertilizer K $7.20 $4.52 $0.00 $2.61 $0.00 $1.65 $1.95

Fertilizer Lime $44.21 $19.68 $0.00 $29.87 $0.00 $22.04 $0.00

PH* Chemical $13.09 $34.76 $13.09 $34.76 $13.09 $34.76 $33.14

PH Labor $13.03 $13.24 $12.45 $12.73 $15.49 $15.73 $10.51

PH Mach Var $20.20 $19.44 $20.61 $19.49 $24.87 $20.88 $16.30

PH Mach Fixed $29.38 $26.33 $28.95 $27.01 $37.40 $28.93 $22.23

Interest OPI $15.96 $143.38 $14.11 $145.43 $9.69 $157.96 $93.09

Harvest Cost $476.44 $481.53 $445.97 $433.49 $405.86 $400.78 $624.69

CU* Chemical $25.44 $28.58 $25.44 $28.58 $25.44 $26.03 $32.12

CU Labor $0.79 $3.68 $0.76 $3.54 $0.94 $4.00 $4.85

CU Mach Var $1.50 $15.93 $1.75 $16.23 $1.97 $15.25 $20.84

CU Mach Fixed $2.43 $27.35 $2.65 $28.55 $3.09 $27.13 $39.30

Total Cost $929.73 $967.57 $847.37 $928.78 $714.25 $900.74 $1,051.08

Returns $475.08 $23.32 $252.93 ($102.76) $173.67 $59.48 $11.87

*PH - Pre Harvest

*CU - Post Harvest

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