Published March 6, 2014
Crop Economics, Production & Management
Profitability of Cellulosic Biomass Production in the Northern
Great Lakes Region
Bradley J. Kells and Scott M. Swinton*
ABSTRACT
Producing bioenergy feedstocks on non-crop land can largely avoid the food price feedbacks of energy biomass production on
cropland. The U.S. northern tier grassland-to-forest ecotone offers large areas of marginal land that is not currently cropped. In
this ecological transition zone, the relative profitability of grassy vs. woody sources of energy biomass is little studied. This paper
reports an exploratory investment analysis of cellulosic biomass production in the northern Great Lakes region. It compares two
short-rotation tree crops, willow (Salix sachalinensis F. Schmidt)and hybrid poplar (Populus nigra L. X P. maximowiczii A. Henry),
and switchgrass (Panicum virgatum L.) (a native prairie grass) to conventional mixed hay. Because biomass markets are not yet well
developed, this study calculates threshold prices and yields at which biomass crops become at least as profitable as mixed grass hay.
At 2010–2012 prices and available production technologies, none of the cellulosic crops is competitive with the hay baseline system.
The breakeven price of energy biomass ranges from $90–100 per oven-dry Mg–1 for all three energy crops. Breakeven yields are much
more variable, due to the high cost of harvesting woody biomass. At 2010–2012 prices, necessary biomass yield increases range from
3.5-fold for switchgrass and willow to over 25-fold for poplar. While the ratio of input costs to revenue remains relatively constant
between the northern and southern Great Lakes regions, the opportunity cost of active cropland in the southern zone is much
higher, implying an economic comparative advantage for marginal land of the northern tier of the Great Lakes region.
Public concerns about U.S. energy independence and
climate change risks associated with fossil fuel use have given rise
to public laws mandating bioenergy use both for liquid transportation fuel and for electricity generation. The U.S. Energy
Independence and Security Act of 2007 (EISA) (U.S. Congress, 2007) requires ambitious increases in the use of biofuels
for transportation use, while over a score of state-level laws set
targets for renewable portfolio standards (including biomass) to
produce electricity (USDOE-EERE, 2012).
Accompanying the scientific and engineering research
into cost-effective innovation in bioenergy production has
been a series of economic studies exploring the conditions for
commercial viability of a bioenergy industry, starting with the
production of energy biomass. As a corn grain ethanol industry
already exists, the literature has focused on cellulosic biomass for
conversion into ethanol or for direct combustion for electricity.
Research has focused chiefly on how current cropland could
shift to produce more energy biomass. Studies have ranged
from breakeven analysis of threshold biomass prices and yields
B.J. Kells, Dep. of Economics, George Mason Univ., Fairfax, VA 22030; S.M.
Swinton, Dep. of Agricultural, Food and Resource Economics, Michigan
State Univ., East Lansing, MI 48824. All authors are also affiliated with DOE
Great Lakes Bioenergy Research Center, Michigan State University. Received
17 Aug 2013. *Corresponding author (swintons@msu.edu).
Published in Agron. J. 106:397–406 (2014)
doi:10.2134/agronj2013.0397
Available freely online through the author-supported open access option.
Copyright © 2014 by the American Society of Agronomy, 5585 Guilford Road,
Madison, WI 53711. All rights reserved. No part of this periodical may be
reproduced or transmitted in any form or by any means, electronic or mechanical,
including photocopying, recording, or any information storage and retrieval
system, without permission in writing from the publisher.
required for profitable production (Mooney et al., 2009; James
et al., 2010) to regional and national supply analyses that capture
the relative opportunity costs of displacing alternative current
crops either at current prices (Egbendewe-Mondzozo et al., 2011,
2013) or by simulating price feedbacks triggered by biomass
expansion (Hertel et al., 2010; Khanna et al., 2011).
In particular, the EISA law and similar legislation in other
nations have increased demand for feedstocks to make liquid
biofuels, triggering cropland shifts and grain price rises (Baier et
al., 2009). The USDA estimates that more than 35% of the total
corn supply grown in the United States will be used for biofuel
during the next decade (USDA, ERS, 2012). This increased
demand caused at least a 25% increase in corn prices from 2006
to 2008 (Baier et al., 2009; Tyner, 2008). And price increases
in corn affect other goods: Crops that compete with corn for
land (soybean, wheat), grain-intensive products (beef, poultry),
and substitute goods all face increased prices (Baier et al., 2009;
Hayes et al., 2009; Tyner, 2008).
Higher grain prices have two pernicious effects. First, they
reduce food consumption, especially among the world’s poor
(Hertel et al., 2010). Second, higher food prices create a market
incentive to bring new lands under production, both in the
United States and the rest of the world (Chen and Khanna,
2012). More producing land helps mitigate food price rises, but
expanding the area of land under cultivation increases emission
of greenhouse gasses. This indirect land use change (ILUC)
effect of biofuel mandates that are met from current cropland
can lead to potentially large greenhouse gas releases along with
Abbreviations: NPV, net present value; PLS pure live seed.
A g ro n o my J o u r n a l • Vo l u m e 10 6 , I s s u e 2 • 2 014
397
global land degradation (Fargione et al., 2008; Hertel et al.,
2010; Khanna and Crago, 2012; Searchinger et al., 2008).
These findings have shifted the attention of scientists and
policymakers to the potential for non-crop marginal lands to
produce energy biomass (Hill et al., 2006; Keoleian and Volk,
2005; Swinton et al., 2011). Energy biomass production on
marginal land minimizes competition with cropland and thus
avoids putting pressure on crop and cropland prices (Campbell
et al., 2008; Hill et al., 2006; Lemus and Lal, 2005). It may
also decrease the environmental impact of expanded biofuel
production, as many non-crop cellulosic biomass crops are
perennial, and so have smaller environmental footprints than cropbased biofuels because of their greater efficiency at C sequestration
(Fargione et al., 2008; Lemus and Lal, 2005; Adler et al., 2007),
and greater N conversion efficiency (Crutzen et al., 2008).
Non-crop marginal land in the United States is largely
found where it gets dry enough to make crop production risky
in the Great Plains, where it gets cold enough for grain yields
to be risky, across the northern tier of the grain and dairy
belt, and where soils are relatively unproductive, as in parts of
the wooded Southeast (Swinton et al., 2011). In the wake of
the declining U.S. pulpwood industry (Ince, 2009), energy
biomass production from the wooded regions potentially
offers the attractions of low opportunity cost and local
economic development.
The northern tier of the Great Lakes, notably northern
Michigan, Minnesota, and Wisconsin, includes large areas of
poor quality, glacial till-based soils covered with scrub brush,
forest, and hay for dairy cows (Bos taurus). Land prices tend to
be low compared to more productive cropland. It remains an
empirical question whether dedicated energy crops are more
economically feasible in this setting than in areas of food, fiber,
and feed crops. Two types of energy crops are of particular
interest: perennial grasses and short-rotation woody biomass
crops like willow and poplar. Studies have shown perennial
grasses like switchgrass and Giant Miscanthus (Miscanthus ×
giganteus J.M. Greef & Deuter ex Hodkinson & Renvoize)can
give very high biomass yields on good quality cropland. On the
other hand, willow and poplar may be better adapted to the
poorer quality soils and short growing season of the northern
tier. Tree crops have the added advantage of storing their own
biomass until needed, as compared to grasses that must be
harvested annually and stored until use.
Emerging results from agronomic and forestry experimental
sites in the northern tier of Michigan and Wisconsin paired
with cost of production estimates create the opportunity to
compute biomass yield and price thresholds for these dedicated
biomass crops compared to current land-income opportunities
in the area. In analyzing returns to investments in dedicated
energy crops compared to alternative long-term investments in
forage crops, this paper develops improved, dynamic analyses of
breakeven comparative prices and yields.
OBJECTIVES
Assuming that land owners attempt to maximize the expected
profitability of their land, this study aims to estimate the relative
profitability of converting land from mixed hay (baseline system)
to produce switchgrass, hybrid poplar, or willow. The specific
research objectives of this study are as follows:
398
1. To estimate costs of production and potential returns of
each crop compared to a current baseline system.
2. To develop an appropriate method for comparative breakeven analysis in a dynamic setting where yields evolve over
time.
3. To compute the biomass price threshold necessary for each
biomass system to break even with the profitability of the
baseline system.
4. To compute the biomass yield threshold necessary for each
biomass system to break even with the profitability of the
baseline system.
5. To compare the profitability of energy biomass production in the northern Great Lakes to recent results from the
southern part of this region.
MATERIALS AND METHODS
This study examines the potential profitability of expanded
energy biomass production from switchgrass, willow, and hybrid
poplar in the northern Great Lakes region. The general approach
is to characterize likely commercial production systems and to
evaluate their profitability using capital budgeting (investment
analysis) over a 16-yr time horizon. None of these crops are
currently produced commercially for energy use, though all
are being researched for energy use and all have other current
uses (e.g., paper pulp and wood products, wildlife habitat).
Profitability is evaluated both individually (do likely revenues
cover likely costs?) and comparatively (can net revenues compete
with the best current alternative land use?). In Michigan’s Upper
Peninsula in particular and on marginal land in the northern
Great Lakes region in general, a common current land use is
mixed hay production. As a means to represent existing revenue
streams from marginal lands in the region, we chose a mixed
grass hay production system. This rotation serves as the baseline
land use against which energy biomass systems are compared.
Production Practices and Yield Levels
The basic production systems to be evaluated are synthetic
systems built up from the best available research data and
commercial production data to represent likely commercial
production systems for energy biomass. They are described
below, beginning with the mixed grass hay baseline system. A
complete agronomic management protocol was created for each
cropping system as it would be practiced under commercial
conditions (Table 1). These protocols were a mix of current
research findings and best practice guides based on commercial
production information for each individual crop. The associated
production costs are summarized in Table 2.
Mixed hay: The mixed hay production guide was based on
Michigan State University (MSU) crop production budgets
(Stein, 2011a). Because these budgets were created for central and
southern Michigan, the data was adjusted to fit northern Great
Lakes conditions (D. Min, Extension Forage Specialist; C. Kapp,
Research Technician, personal communication, Michigan State
University (MSU), Upper Peninsula Research Station (UPRS),
July 2012). In the northern Great Lakes region, many farmers
who use marginal land currently grow a cool weather mixed grass
hay (Corace et al., 2009) (D. Undersander, Professor, University
of Wisconsin-Madison, personal communication, January
2013) (C. Shaeffer, Professor, personal communication, Univ. of
Agronomy Journal • Volume 106, Issue 2 • 2014
Table 1. Agronomic protocol.
Crop
Mixed grass hay
Willow
Poplar
Switchgrass
Planting material per
hectare per planting
15
15,650
2,170
9
Unit
kg PLS† ha–1
cuttings ha–1
cuttings ha–1
N
0
0
0
P
0
0
0
K
0
0
0
kg PLS ha–1
120
0
0
Pest control
None
Oxyflourfen 2.5L ha–1, simazine 2.5L ha–1
Pendimethalin 5L ha–1
Glyphosate 5L ha–1, 2, 4-D 2.5L ha–1, imazetherapyr 283 g
ha–1, atrazine 2.5L ha–1, dicamba 1.25L ha–1
† PLS, pure live seed.
Minnesota, February 2013) (C. Kapp, personal communication,
January 2013). Our budgets used a grass mix consisting of tall
fescue (Festuca arundinacea Schreb.) and red clover (Trifolium
pratense L.), planted with a mechanized seed drill. There is
typically no replanting. Since most farmers in the northern Great
Lakes region aim to keep input costs low, fertilizer is applied in
small amounts, and thus we assume the application of 19–19–19
fertilizer four times over the 16-yr time horizon of these capital
budgets. Harvest is yearly. Pesticides are rarely applied to mixed
grasses, and therefore do not figure into our model.
Willow: Willow is a short-rotation woody biomass crop under
intensive research in the northern Great Lakes region. The
willow production system described here is based on the State
University of New York Environmental Science and Forestry
Willow Biomass Producer’s Handbook (Abrahamson et al.,
2010) for most basic data and for the management regime,
adjusted to northern Great Lakes conditions by regional
experts (R. Miller, Director; B. Bender, Operations Forester,
MSU, Forestry Biomass Innovation Center (FBIC), personal
communication, July 2012). Woody biomass in this region is
rarely produced with the application of N, so our willow budget
excludes fertilizer, but it includes weed control using glyphosate
(N-(phosphonomethyl)glycine), 2,4-D (2,4-dichlorophenoxy)
acetic acid), oxyflourfen (2-chloro-1-(3-ethoxy-4-nitrophenoxy)4-(trifluoromethyl)benzene), and simazine (6-chloro-N,N9diethyl-1,3,5-triazine-2,4-diamine) (Table 1). Current research
suggests that coppiced willow production is the most efficient
means of producing biomass from willow, with harvests
occurring every 4 yr to keep biomass growth at its most efficient
(R. Miller; Brad Bender, personal communication, August
2012). Variety trials are underway, and yields are consistently
improving, but SX-61, the varietal selected for this study, is a
current leader in biomass yield production at MSU’s Forest
Biomass Innovation Center (FBIC) in Escanaba, MI (Wang
and MacFarlane, 2012). As willow is harvested by coppicing, no
replanting is necessary. Land preparation includes mowing the
field, spraying with 2,4-D and glyphosate, and tilling, before
planting with a mechanical Egedal planter.
Hybrid poplar: Hybrid poplar, another short-rotation woody
biomass crop, follows a longer rotation and different harvest
regime than willow, because it is harvested by whole tree cutting
as opposed to coppicing. The poplar budgets are based on the
University of Minnesota’s hybrid poplar best management
practices (Zamora et al., 2011), modified by regional experts (R.
Miller; B. Bender, personal communication, July 2012). Poplar is
harvested after 8 yr and then replanted for a second harvest 8 yr
later, at the end of the 16-yr time horizon. The variety chosen for
our budgets, NM-6, is a popular poplar clone with good yields
(Wang and MacFarlane, 2012) and good disease resistance.
Poplar yields are lower than willow, but because they continue
increasing over a longer time period poplar can be harvested
less frequently. Fertilizer is not used in this region for wood
production. Herbicides applied to poplar include glyphosate;
2,4-D; and pendimethalin (N-(1-ethylpropyl)-3,4-dimethyl-2,6dinitrobenzenamine). Land preparation is the same as for willow,
and the poplar cuttings are planted with the same equipment.
Switchgrass: Switchgrass is the only non-woody biomass crop
being researched extensively for production in the northern
Great Lakes region. A perennial grass crop, switchgrass is
harvested annually, beginning the year after planting and
continuing for 10 yr, with a replant in Year 11 taking production
to the end of our 16-yr time horizon. The varietal Cave-In-Rock
can withstand the cold winters of the region while maintaining
high yields. Unlike the two woody crops, switchgrass requires
N fertilizer. To aid with seedling establishment, it is treated
after each planting with 2,4-D, imazetherapyr (2-[4,5-dihydro4-methyl-4-(1-methylethyl)-5-oxo-1H-imidazol-2-yl]-5-ethyl3-pyridinecarboxylic acid), atrazine (6-chloro-N-ethyl-N9(1-methylethyl)-1,3,5-triazine-2,4-diamine), and dicamba
(3,6-dichloro-2-methoxybenzoic acid) (Min, 2011)). Switchgrass
is assumed to be planted with a seed drill into a glyphosate-killed
and plowed field.
Yield data, summarized in Table 3, comes from the FBIC at
Escanaba, MI, the Upper Peninsula Research and Extension
Center at Chatham, MI, and the National Agricultural Statistics
Service. Non-alfalfa hay is produced at a rate of about 3.5 Mg ha–1
in the northeastern counties of Wisconsin (USDA, NASS, 2010–
2012), a number that matches average hay yield in Michigan’s
Upper Peninsula (K. Hillock-Vining, Chippewa County Farm
Service Agency Executive Director, Sault Ste Marie, MI, personal
communication, May 2012).
The willow yields reported in Table 3 are based on reported
yields at the Forest Biomass Innovation Center in Escanaba, MI,
where they use similar harvest methods to the protocol here. Yields
Table 2. Crop production input prices and data sources.
Input
Mixed grass seed (red clover/tall fescue)
Switchgrass seed
Willow
Poplar
Unit
kg PLS†
kg PLS
Cutting
Cutting
Price $
4.2/3.5
15.5
0.1725
0.16
Source
Deer Creek Seed, Ashland, WI; De Bruyn Seed, Zeeland, MI
Ernst Seed Co, Meadville, PN
Double A Willows, Fredonia, NY
Hramor Nursery, Manistee, MI
† PLS, pure live seed.
Agronomy Journal • Volume 106, Issue 2 • 2014
399
Table 3. Crop yields, prices, and data sources.
Output
Hay
Yield
Green Mg ha–1 yr–1
3.5
Price
$ Mg–1
115
Source of yield value
Source of price value
Chippewa County Farm Service Agency,
Phone Interview, May 2012.
Wang and MacFarlane, 2012
Willow
20
23
Poplar
16
23
Wang and MacFarlane, 2012; Netzer et
al., 2002
Switchgrass
10
38
Min, 2011; switchgrass for a bioenergy
crop and livestock feed
are reported in green Mg–1, equal to harvest weight. Because dry
weight varies from one species to another, yields elsewhere are
also reported in oven-dry Mg–1. Recent improvements in yield,
documented in Wang and MacFarlane (2012), demonstrate
willow’s potential to reach a mature yield of over 20 green (10
dry) Mg ha–1 per year. Though we calculate willow yields as only
reaching maximum yield after the first coppice, this still leads to
three harvests over 11 yr at full production capacity, with a total
yield of more than 130 dry Mg ha–1 over 16 yr.
Poplar yields of 16 green (8 dry) Mg ha–1 per year also come
from Wang and MacFarlane (2012), adjusted to an 8 yr harvest
cycle (R. Miller, B. Bender, personal communication, July
2012). The mature yield for poplar represents the total yield over
8 yr averaged out across the entire cycle. After this 8-yr period,
yields begin declining at such a rate that failure to harvest will
result in overall loss of profit (R. Miller, B. Bender, personal
communication, August 2012).
Switchgrass yields come from field trials conducted at the MSU
experiment station in Chatham, MI. There is no current regional
production of switchgrass by private individuals, but the yield
data from Chatham is representative of the potential achievable
in the northern Great Lakes region. Yields of 10 green Mg ha–1
have been achieved with the Cave-In-Rock varietal, the currently
recommended varietal for the region (Min, 2011).
Sensitivity analyses were conducted for each of the proposed
biomass production methods to account for a range of outcomes
in the northern Great Lakes region. For each biomass crop there
is an “optimistic” and a “pessimistic” scenario in addition to
the baseline. The optimistic scenarios assume a mix of yields,
planting and harvest regimes, and chemical and fertilizer costs
that favors profitability. The pessimistic scenarios entail higher
costs and lower yields than the baseline. Details are included
in Table 4. The optimistic willow scenario assumes that the
trees require no fertilization, and they can grow for 4 yr at
maximum productivity, requiring only four harvests during
the budgeted period. The pessimistic willow scenario assumes
that harvest is required every 3 yr instead of 4 to maintain its
most efficient growth rate, which leads to five harvests over 16
yr. Application of 100 kg ha–1 of N is assumed to be required
after each harvest in the pessimistic model (Abrahamson et
USDA NASS survey data, 2010–2012.
NRC 2011, modified to regional conditions. Price based on
$45 dry Mg–1 converted to wet weight.
NRC 2011, modified to regional conditions. Price based on
$45 dry Mg–1 converted to wet weight.
NRC 2011, modified to regional conditions. Price based on
$45 dry Mg–1 converted to wet weight.
al., 2010). The poplar optimistic and pessimistic scenarios also
differ by whether fertilizer is required (Zamora et al., 2011).
Poplar weed control costs also differ between scenarios, as the
optimistic poplar model assumes a lighter chemical regime
than the pessimistic poplar model (which, in addition to the
chemicals previously discussed, includes additional applications
of fluazifop {(±)-2-[4-[[5-(trifluoromethyl)-2-pyridinyl]oxy]
phenoxy]propanoic acid}, imazaquin {5-dihydro-4-methyl-4-(1methylethyl)-5-[oxo-1H-imidazol-2-yl]-3-quinolinecarboxylic
acid}, and oxyfluorfen). The optimistic model also assumes
hand-planting instead of machine planting (R. Miller, personal
communication, May 2013): due to the high fixed cost of
currently available machinery, producers can hand plant low
cutting-per-acre woody crops like poplar more cheaply than
by mechanized methods. The optimistic switchgrass scenario
assumes that switchgrass will survive the entire 16-yr time
horizon of the study, whereas the pessimistic scenario assumes
replanting every 6 yr to maintain high productivity, meaning
two replantings over the 16 yr. The two scenarios also differ in
weed control costs, as the pessimistic one requires herbicides and
fertilizers to be applied at every planting, with a heavier rate of N
used in the pessimistic scenario than in the optimistic one.
Input Costs
Whenever possible, the costs used in this study’s budgets
are drawn from local primary sources. The herbicide prices are
averages over the 2010–2012 period from Great Lakes Agri
Service, a local chemical dealer (J. Sergant, Great Lakes Agri
Service, Gladstone, MI, personal communication, July 2012).
Fertilizer prices are also derived from a regional company (Ray’s
Feed Mill, Bark River, MI, personal communication, August
2012) and adjusted to price per elemental pound. Seed and
propagule prices are more complicated, but also based on primary
data. Willow cutting and planting costs are derived from estimates
given by a leading producer in New York (Sue Rak, Double-A
Willow, Fredonia, NY, personal communication, July 2012).
Costs for poplar cuttings come from a major Michigan Nursery
(Hramor Nursery, Manistee, MI, www.hramornursery.com/
pricelist/hrab2012fall-2013spring.pdf, July 2013). Mixed grass hay
seed is an average of regional prices (Debruyn Seed Co, Zeeland,
Table 4. Sensitivity analysis differences by model.
Willow optimistic
Willow pessimistic
Poplar optimistic
Poplar pessimistic
Switchgrass optimistic
Switchgrass pessimistic
400
4 yr between harvests. No fertilizer applied.
3 yr between harvests. 100 kg ha–1 N applied after each coppice.
No fertilizer applied. Light chemical regime: Only 2,4-D, glyphosate, and pendimethalin applied.
50 kg ha–1 N applied every year. Assumes “light chemical regime” plus imazaquin, fluazifop, and oxyflourfen.
No replantings required. 65kg ha–1 N per growing year
Two replantings, every 6 yr. 150 kg ha–1 yr–1 N per growing year
Agronomy Journal • Volume 106, Issue 2 • 2014
MI, www.debruynseed.com/new_page_5.htm, February 2013)
(Deer Creek Seed, Ashland, WI, www.deercreekseed.com/forageseed/, February 2013). Cave-In-Rock switchgrass seed prices were
acquired from a regional dealer (Ernst Seed Co, Meadville, PA,
personal communication, July 2012).
Machine costs are charged as custom hire operations, instead
of separately accounting for all machinery ownership and
operating costs. This assumption recognizes that expensive
planting and harvest machinery for willow and poplar would
typically not be efficient for ownership by any farming operation
that does not function on a very large scale. For the more
common pieces of equipment, this study based its custom costs
on Michigan State University’s 2011 estimates for custom
machine costs (Stein, 2011b). Certain pieces of equipment are
too rare to have published custom hire costs, such as the Egedal
planter, a machine that plants woody biomass cuttings and is
used in our study for poplar and willow planting. In this case,
we calculated custom hire equivalent cost from ownership costs,
assuming a 5% rate of return to capital (Erickson et al., 2004),
plus skilled equipment operator labor at $17/hour (Stein, 2011b).
Poplar was assumed to be harvested on a whole tree system
where trees are harvested in a manner similar to logging
operations, so costs per acre were found for clean-cut-harvesting
softwood plantations, divided into felling, skidding, and
chipping costs. Felling, skidding, and chipping costs are based
on average costs of forestry equipment use (A. Srivastava, D.
Abbas, C. Saffron, and F. Pan. 2011. Economic analysis of
woody biomass supply chain logistics for biofuel production
in Michigan, Final report. Michigan State Univ., Dep. of
Biosystems and Agric. Eng., East Lansing), modified to include
the same custom harvesting profit rate assumed by Stein (2011b).
Willow harvest costs are based on the State University of
New York Environmental Science and Forestry Department’s
(SUNY-ESF) EcoWillow model (SUNY-ESF, Syracuse, NY,
www.esf.edu/willow/download.asp, June 2012), available
online, and include cutting, chipping, and in-field transport.
The EcoWillow model is built around specialized harvesting
equipment developed by SUNY and Case New Holland, but
due to the lack of willow harvesting data with conventional
machinery, it provides the best available data on potential willow
harvest costs. Transport costs, calculated at 20 miles of shipping,
differed between the woody and grassy biomass crops, and
separate costs for each, derived from Searcy et al. (2007), form
the basis for this study’s assumed transport costs.
Annualized costs for each production system are reported in
Table 5. All cost calculations for switchgrass, poplar, and willow
are calculated on a per green Mg–1 basis. Drying of the wood
occurs at the very end of the process, so all the other steps (harvest,
skidding, chipping) occur with raw green biomass. This means that
the extra weight of green material adds to the costs of production.
Storage costs are omitted, though Brechbill et al.’s (2011) literature
review reported a median weight loss of 8.8% over 6 mo storage for
plastic-wrapped round bales of switchgrass. While lower storage loss
values are likely for woody species, no data were available.
Output Prices
The mixed hay baseline price of $115 Mg–1 is the average
of prices paid in the 2010–2012 period for non-alfalfa hay
across Michigan (USDA, NASS, 2010–2012). While in most
of Michigan’s Upper Peninsula, hay is consumed on-farm and
not sold, this price represents the price that could be received if
farmers desired to sell their product.
Since switchgrass, poplar, and willow are being analyzed as
bioenergy sources, their value is based entirely on the amount
of dry biomass they produce per hectare per year. For willow
and poplar, the weight ratio of green to oven-dry biomass is
2:1 (50% dry matter). Switchgrass is 85% dry matter when
harvested after senescence (K. Thelen, Professor, MSU, personal
communication, September 2012). Woody biomass grown
has alternative uses as fuelwood and pulpwood, worth $35 to
$55 dry Mg–1 in the southern United States (National Research
Council, 2011). As a reference price received at the biorefinery,
we use the median of this range, $45 dry Mg–1 of biomass. As
noted above, storage losses are omitted from the analysis. In
sensitivity analysis, we also calculated the profitability of each
biomass crop at $30 and $60 per oven-dry Mg–1.
Capital Budgeting for Relative Profitability Analysis
This study develops capital budgets for each system over a
period of 16 yr, using them as the basis for calculating comparative
breakeven yields and prices relative to the benchmark production
method of mixed grass hay. The capital budgeting approach uses
discounted cash flows, following Boehlje and Eidman (1984),
based on revenues minus the costs that vary across production
systems (CIMMYT, 1988). Costs that are the same across systems,
such as land rental rates, are omitted because they do not affect
the relative profitability of the systems included. While they
would affect a simple breakeven price or yield calculation, they do
not affect the comparative breakeven values calculated here. The
capital budgets are based on 2010–2012 prices prevailing in the
northern Great Lakes region.
Comparative Breakeven Cellulosic Feedstock
Price Analysis for Changing Crops
The goal of this analysis is not simply to calculate the
minimum returns from raising a biomass crop that covers its
direct costs of production, but rather to calculate the level
of returns that would cover both those direct costs plus the
opportunity cost of giving up net income earned from the
traditional dominant crop regime in the region. Comparative
breakeven analysis calculates the biomass price or yield that
would be necessary for the producer to earn as much from the
energy biomass crop as from traditional crop production (mixed
grass hay, in this case). This study also estimates breakeven costs
Table 5. Present value of input costs by crop and by category, per hectare, over 16 yr.
Crop
Hay
Willow
Poplar
Switchgrass
Harvest
$1519
$2280
$3160
$2980
Machine
$80
$300
$510
$310
Pest control
$0
$110
$280
$150
Agronomy Journal • Volume 106, Issue 2 • 2014
Fertilizer
$680
$0
$0
$1860
Planting material
$50
$2570
$560
$210
Total
$2340
$5250
$4510
$5510
401
for both optimistic and pessimistic models, giving a range of
likely prices necessary for biomass crops to equal the economic
value of mixed hay production to a potential biomass farmer.
The discount rate applied is 5%, based on Erickson et al.
(2004), who found that to be a typical real rate of return to
capital on U.S. farms. Assuming constant real prices over the
16-yr period, results are reported in 2010–2012 dollars (present
value at time of study). To calculate annualized costs, revenue,
and net profit from present values, a standard financial annuity
formula was used over the 16 yr sum of net returns. The formula
used (Ross et al., 2008) is as follows:
æ r(1 + r )t ÷ö
÷
A = NPV çç
çè (1 + r )t -1÷÷ø
[1]
where A is annuity, NPV is net present value of production
system, r is the discount rate (5%), and t is time horizon (16 yr).
Due to the long time horizon used in this study, the year that
harvest occurs has a significant impact on the profitability of any
operation. While hay and switchgrass are harvested yearly, and
thus generate yearly revenue, willow and especially poplar are
harvested at much longer time intervals. Thus the present value
of revenue from these tree crops is reduced significantly when
calculated as a present value.
To calculate comparative breakeven prices and yields, this
study innovates on the comparative breakeven methodology
for energy biomass crops used in James et al. (2010). The
methodology used in that work calculated breakeven yield
as the annual average yield that would be required, assuming
a static biomass price and a 5% discount rate, to match the
annualized NPV of the status quo crop. The method is sound
if crop rotations are balanced over time, meaning that the
same area is planted each year, so that average yields represent
a weighted average over time. However, this approach tends to
underestimate the comparative breakeven yields of perennial
crops when plantings are not evenly spaced over time and
harvests are infrequent. The underestimation is slight for crops
that are harvested frequently, such as perennial grasses. The
distortion is much larger for woody crops with intermittent
harvests, when no biomass is harvested in many years but large
yields occur in a few years.
To correct for this time-dependent distortion when new
plantings are not evenly spaced over the entire time horizon,
this study develops a modified methodology to calculate
comparative breakeven price relative to a time-discounted yield,
and breakeven yield relative to a time-discounted biomass price.
We calculate breakeven price (P BE) as a function of the NPV
of a “defender” crop (NPV D) plus the cost (ct) of producing
the new biomass crop, divided by an assumed biomass yield
(y). Because P BE depends on the timing of when yields are
harvested, the biomass yield of the “defender” crop (yDt) must
discounted and subtracted from the discounted yield achieved
by the “challenger” biomass crop (yCt). This ensures that the
biomass yield numbers of both crops receive the same temporal
weighting. The resulting equation becomes:
402
PBE =
æ c ö
NPVD + å t çç t t ÷÷÷
èç (1 + r ) ø÷
æy -y ö
å t èççç (1Ct+ r )Dtt ø÷÷÷÷
[2]
Note that unlike the James et al. (2010) study, in which the
defender crop of corn for grain could also produce stover for
energy biomass as a byproduct, in the current study, the defender
rotation of mixed grass hay produces no additional energy
biomass, so yDt = 0.
The total breakeven yield (TY BE) is also calculated as a
function of the NPV of the “defender” crop (NPV D) plus
the cost of producing the new biomass crop (ct), divided by an
assumed biomass price (Pt) that is discounted. Calculations
are again made for both optimistic and pessimistic models.
To simplify calculation, yield dependent costs (ydct) per Mg–1
are subtracted from the assumed biomass price, while acreage
dependent costs (adct) are kept in the numerator. The resulting
equation becomes:
æ adct ÷ö
NPVD + å t çç
÷
çè (1 + r )t ÷÷ø
TYBE =
æ P - ydc ö
å t çççè (1t + r )t t ÷÷÷÷ø
[3]
This method gives a correctly discounted average total yield over
the entire time horizon. For ease of interpretation, we convert the
value to mature annual yield, by taking TY BE (total breakeven
yield) and dividing it by the sum of the ratios of current year yield
to mature yield for each year (Rt) (e.g., if yield in the first year is
half of mature yield, then R1 = 0.5), the breakeven mature annual
yield (YBE) can be calculated as follows.
YBE =
TYBE
å t ( Rt )
[4]
The breakeven mature annual yield is suitable target value for
researchers seeking to develop new varieties that can break even
with the “defender” cropping system at the assumed biomass price.
Fig. 1. Annualized net present value for energy biomass crops and
mixed grass hay ($ ha –1).
Agronomy Journal • Volume 106, Issue 2 • 2014
RESULTS
Investment Analysis: Relative Profitability
Using a biomass price of $45 dry Mg–1, relative profitability
was calculated for the mixed grass hay system and each of the
three dedicated biomass crop systems. We calculate the average
annual net revenue over selected costs of a mixed grass hay
rotation at $200 ha–1. In the comparative breakeven budgets,
this value is treated as the opportunity cost of giving up mixed
grass hay. The three energy biomass systems not only failed to
match the profitability of mixed grass hay, but they also failed to
cover their own direct variable costs. The annualized net present
values per hectare of each crop are illustrated in Fig. 1.
Comparative Breakeven Prices
for Replacing Mixed Grass Hay
Using the average measured yields collected for this study, the
comparative breakeven prices indicate that the farm-gate prices
of $45 dry Mg–1 that prevail for pulpwood (~$22.50 green Mg–1
for wood) would be insufficient to equal the net return from the
production of mixed grass hay. Willow has the highest breakeven
price, at $100 Mg–1, while poplar and switchgrass both have
breakeven prices around $92 Mg–1. Although switchgrass has
lower yields and higher costs than poplar or willow, it manages
to remain price competitive due to the frequency of its harvests,
causing its revenues to face less discounting over time. Poplar has
significantly lower costs than willow or poplar, as the higher costs
of N fertilization of switchgrass and planting of willow more than
offset the comparatively greater harvest costs of poplar.
Comparative Breakeven Yield for Replacing
the Mixed Grass Hay Baseline
Assuming a price of $45 dry Mg–1 of biomass, the estimated
mature yields necessary for biomass production to break even
with net returns from hay production are shown in Fig. 2.
Switchgrass and willow have significantly lower breakeven prices
than poplar, due to the much higher yield dependent costs of
poplar harvest. Since poplar has a longer growth period between
harvests than willow, the wood to be harvested is significantly
thicker than willow and thus requires more expensive
equipment. Harvesting poplar, therefore, is significantly more
expensive than harvesting willow or switchgrass, which results in
significant differences in breakeven yields, even when breakeven
prices are not extremely different.
Sensitivity Analysis
Breakeven prices differ by $30 to $40 dry Mg–1 per year
between the optimistic and pessimistic scenarios. Even in the
optimistic models, the breakeven prices are double the assumed
current biomass price dry Mg–1, while in the pessimistic
models, they are much higher. The problem is exacerbated in the
breakeven yield calculations, where even the optimistic willow
and switchgrass mature yields are about three times the current
yield. The poplar budgets, due to their much higher yielddependent costs, would require a nearly 25-fold yield increase,
even under the optimistic scenario (Tables 6 and 7).
In Table 8, we compare annualized NPV results at
optimistic and pessimistic biomass price forecasts. At a price
of $30 dry Mg–1, all three biomass crops face annualized NPV
losses of between $190 and $270 ha–1. At $60 dry Mg–1, poplar
covers with its own variable costs, but does not make enough
additional profit to compensate for the opportunity cost
associated with switching away from a current land use such as
mixed grass hay production. Willow and switchgrass both fall
short of covering their own variable costs. Even at the optimistic
biomass prices, all of the biomass crops fall more than $150
short of breaking even with the $200 ha–1 earning potential
(opportunity cost) of a traditional mixed grass hay rotation.
DISCUSSION
Breakeven Analysis
Harvest and planting costs play important roles in limiting
the potential profitability of biomass production in the northern
Great Lakes region. Harvest costs offset more than 65% of
the expected revenue from the three biomass crops (Fig. 3).
This stands in stark contrast to hay production, where <40%
of revenue is needed to cover harvest costs. Hence, although
breakeven prices only exceed the baseline biomass price by 100
to 150%, breakeven yields generally require an increase of more
than 300% from baseline yields. This problem is most extreme
Table 6. Sensitivity analysis of breakeven biomass prices under optimistic,
baseline, and pessimistic scenarios for three energy crops ($ dry Mg –1)
compared to mixed grass hay.†
Crop\Scenario:
Willow
Poplar
Switchgrass
Optimistic
95
84
79
Baseline
102
92
93
Pessimistic
116
123
108
† NB: For green weight values, divide by 2 for willow and poplar and by 1.18 for
switchgrass.
Table 7. Sensitivity analysis of breakeven biomass yields by optimistic, baseline, and pessimistic scenarios for three energy crops (dry Mg ha–1 yr–1).†
Crop\Scenario:
Willow
Poplar
Switchgrass
Optimistic
48
212
30
Baseline
48
225
36
Pessimistic
67
327
41
† NB: For green weight values, multiply by 2 for willow and poplar and by
1.18 for switchgrass.
Table 8. Sensitivity analysis of annualized net present value of three
biomass crops at low, baseline, and high prices ($ ha –1 yr –1).†
Fig. 2. Comparative breakeven mature yields of three biomass crops
compared to mixed grass hay (dry Mg ha –1 yr –1).
Crop
Willow
Poplar
Switchgrass
Agronomy Journal • Volume 106, Issue 2 • 2014
Low
$30 dry Mg–1
(261)
(193)
(255)
Baseline
$45 dry Mg–1
(180)
(113)
(163)
High
$60 dry Mg–1
(37)
29
(1)
403
Fig. 3. Harvest cost as percent of total revenue.
in poplar, where harvest costs account for more than 90% of
revenue at baseline prices.
The cost of planting willow is the other influential cost driving
profitability findings. With a planting rate of over 15,000 cuttings
per hectare at a cost of more than 17 cents per cutting, planting
materials account for almost 50% of total willow costs (see Table
5). In comparison, planting costs make up only 2% of total costs
for the hay baseline. Indeed, apart from the costs of planting
materials, the willow scenarios have total costs only $400 greater
than those of the hay rotation. But when planting material costs
are included, the willow cost per hectare is almost $3,000 dollars
greater than the total cost of a mixed grass hay rotation.
Comparing Productivity in the Northern
and Southern Great Lakes
Offsetting the potential advantages of producing biomass on
marginal lands—lower land cost and lack of food price feedbacks
with their associated indirect land use effects on climate—the
chief potential disadvantage is lower productivity. Mooney et
al. (2009) found that switchgrass grown on marginal land in
Tennessee had a higher simple breakeven price than switchgrass
grown on cropland, implying that marginal land may not be
a cost-effective means of increasing cellulosic biomass output.
To analyze the claim that biomass production on marginal
land in the northern tier of the Great Lakes region will have a
comparative advantage to production on higher quality land in
the southern tier, this study compared its northern tier budgets
to those produced by James et al. (2010) studying biomass
production on cropland in southern Michigan. To make a
reasonable comparison, the James et al. (2010) budgets were
adjusted to incorporate the price and cost parameters, the 16-yr
time horizon, and the same breakeven calculation method
(Eq. [2]–[4]) as in this paper.
A number of details were changed in the James et al. (2010)
numbers to fit the new situation. Poplar planting costs, instead
of using hand planting costs, use the costs of the Egedal planter.
Received biomass prices are standardized across the two studies,
both using the $45 Mg–1 biomass price. Switchgrass costs are
increased to account for the assumption that harvest will occur
while the material is not yet fully dry. For costs that do not vary
across regions (machine costs, imported seed, or cuttings), the
prices used in this paper were used across the board. For costs
that do differ (fertilizer, chemical application, transport) the
numbers from the James et al. (2010) budgets are used. Since the
procedure used for harvesting poplar and switchgrass does not
404
significantly differ from one area to another, most machine costs
remain constant across the two budgets.
In adjusting yields, one significant change that had to be
made was to adjust the James et al. (2010) poplar yields up from
the original values that came from the Forest Biomass Research
Center in Escanaba, MI, to more recent yield data from southern
Michigan. Yields currently being achieved at the Tree Research
Center in East Lansing are currently in the range of double those
at the FBIC (P. Bloese, Research Manager, Tree Research Center,
MSU, personal communication, August 2012). This makes a
significant difference in the relative profitability of poplar, and also
sets poplar apart from switchgrass, which has roughly comparable
yields in both the northern and southern Great Lakes region.
To calculate the opportunity cost in the James et al. (2010)
budgets, corn prices had to be increased to account for the recent
increased value per hectare of growing corn. The price of corn
has increased significantly, from $3.50 bu–1 in 2007–2009
(James et al., 2010) to $6.25 bu–1 in 2010–2012 (USDA, NASS,
2010–2012), resulting in a significant increase in land opportunity
cost for producing biomass. So, while the ratio of variable cost:
revenue is fairly constant across the northern and southern Great
Lakes regions (that is, costs and revenue change proportionately
with latitude), the opportunity cost of land decreases faster than
predicted profitability as production moves farther north. Thus,
while biomass production is not currently profitable in either
region, production of biomass in the northern Great Lakes region
has the advantage of being comparatively less unprofitable.
To show the comparative advantage of the northern Great
Lakes region for biomass production, a breakeven analysis was
run for both of the two regions, using the adjusted southern
Great Lakes budgets, for both poplar and switchgrass. At
2010–2012 prices the necessary breakeven price for the Lower
Peninsula was higher than that of the Upper Peninsula (about
$11 green Mg–1 ($22 dry Mg–1) higher for poplar, and about
$30 green Mg–1($35 dry Mg–1) higher for switchgrass).
The difference was even more stark in the breakeven yields:
Compared to baseline yields, poplar in the southern Great Lakes
region required a percentage increase that was 45% greater than
in the northern Great Lakes region; for switchgrass, the increase
relative to baseline was 66% greater. Results of the comparative
analysis of the northern to the southern Great Lakes region is
reported in Tables 9 and 10.
A key factor driving the comparative breakeven analyses
between the two regions is the land use assumed to be the
baseline “defender” case, corn for grain in the southern Great
Lakes region and mixed grass hay in the north. The reference
price corn nearly doubled from the 2007–2009 period used
in the James et al. (2010) to the 2010–2012 period used in
the comparative study reported here, rising proportionately
much more than the price of mixed hay. In fact, with corn at
its $3.50 bu–1 mean price of 2007–2009 but all other prices
at 2010–2012 levels, the southern Great Lakes region would
have lower biomass breakeven prices and yields than the north
(sensitivity analysis available from authors).
CONCLUSIONS
Production of energy biomass on marginal land in the
northern Great Lakes region is not currently competitive with
conventional mixed hay at current prices and yields. Even the
Agronomy Journal • Volume 106, Issue 2 • 2014
optimistic price of $60 dry Mg–1 is not enough for returns
from production of energy biomass to break even with returns
to alternative uses of land, as represented by mixed grass hay
production. However, biomass production on marginal lands in
the northern Great Lakes region is relatively more attractive than
it is on cropland in the southern Great Lakes. Although biomass
yields decline with the move to more marginal, northerly sites,
at recent prices of alternative crops (mixed grass hay in the
north; corn grain in the south), the decline in income flows from
alternative uses of these lands is proportionately greater, giving
the northerly marginal areas greater profit potential.
There are two cost bottlenecks where targeted research could
sharply trim production costs. The first involves automation
of harvest. The equipment needed to harvest short rotation
woody crops cost effectively is not yet in common usage.
While companies like John Deere and Case New Holland
are partnering with universities to work on producing
effective biomass harvesting equipment (Abrahamson et
al., 2008, Meadows et al., 2010), the resulting equipment is
still experimental. Using the poplar budget as an example,
if poplar harvest costs could be reduced from 95% of each
dollar of revenue to 70% (the percentage of each dollar revenue
from willow lost to harvest costs using specialized harvesting
equipment), the breakeven yield could be reduced from almost
225 dry Mg–1 to just over 25 dry Mg–1 (55 green Mg–1, or less
than a 250% increase over current yields), and breakeven price
can be reduced from more than $90 dry Mg–1 to <$80 Mg–1.
Such mechanical innovations have succeeded before. In 1960
professors at the University of California-Davis, working with
a local equipment manufacturer, released a commercial tomato
harvester that reduced tomato harvesting cost by nearly half.
When this invention was combined with a new tomato variety
that could withstand the force of mechanical processing, the
labor requirements and overall cost of producing tomatoes
decreased by 92%. This cost reduction was partially responsible
for the quadrupling of tomato production in California from
1960 to 1990 (Thompson and Blank, 2000). Similar discoveries
are possible in the woody and grassy biomass industries, and
could have similar effects on production costs.
The second bottleneck is the cost of willow cuttings as
propagules, made especially costly in high density plantings.
More efficient propagation methods and/or intensified price
competition among firms could reduce costs.
Technological innovation aside, another means to increase
the potential profitability of energy biomass from short rotation
Table 9. Northern vs. southern tier of Michigan: Comparative breakeven prices ($ dry Mg –1).†
Crop
Poplar
Switchgrass
North
$92
$93
South
$114
$128
† NB: For green weight values, divide by 2 for willow and poplar and by 1.18 for
switchgrass.
woody crops would be to develop production systems with
multiple products, rather than to expect them to turn a profit
on energy biomass alone. Drawing a lesson from the relative
profitability of biomass byproducts from grain crops like corn
stover and wheat straw (Egbendewe-Mondzozo et al., 2011), the
challenge would be to separate out higher value timber products.
Short rotation woody plantations might, over a growing cycle,
produce biomass for bioenergy, pulp for area paper mills, and
veneer bolts. This process has not yet been well studied, but a
three step thinning cycle, with the first thinning being harvested
for biomass, the second thinning harvested for pulpwood,
and the third and final harvest being used for veneer, has the
potential to generate more revenue than production exclusively
of energy biomass (B. Bender, personal communication, August
2012). More research needs to be done into the economics of
multi-product timber production.
The findings reported here are based on capital budgets,
which are point estimates of representative investment returns
over a designated time period. These budgets are designed to be
representative of potential costs and returns in the northern tier
of the Great Lakes region, as represented by the eastern Upper
Peninsula of Michigan during 2010–2012. But apart from the
baseline hay system, they are based on production systems that
do not currently exist on a commercial basis. Important changes
would have to occur in the costs and returns of these systems for
them to become commercialized.
Our findings indicate that although the production of energy
biomass on marginal lands in the northern Great Lakes region
is not currently profitable, the profitability potential is greater in
this zone than it is on cropland in the southern tier of the Great
Lakes. For that profitability potential to be realized, one of four
circumstances would have to obtain: The relative price of energy
biomass would have to rise sharply, yields of dedicated biomass
crops would have to rise dramatically, costs of production would
have to drop (notably via mechanical planting and harvest), or
an attractive multiple product production strategy would have
to develop (e.g., wood product sales for biomass, paper pulp,
and veneer). Should sufficient gains be accomplished in one or a
combination of these areas, dedicated energy biomass production
would become profitable in an agriculturally marginal area like
the northern Great Lakes, before it would successfully compete
for land that is already producing food and feed crops. In order
for such a transition to occur, further research is needed into
cost-reducing production methods and multi-product woody
crop production and marketing.
Acknowledgments
This work was funded by the US Department of Energy Great Lakes
Bioenergy Research Center (DOE Office of Science BER DE-FC0207ER64494) with additional support from MSU AgBioResearch
and the USDA National Institute of Food and Agriculture. For data
and information, the authors thank Brad Bender, Paul Bloese, Kaye
Table 10. Northern vs. southern tier of Michigan: Current yields, comparative breakeven yields, and percent change needed to break even (Mg ha –1 yr –1).
North
Crop
Poplar
Switchgrass
Current yield
8
8
Breakeven yield
225
36
South
Percent change
2713%
350%
Agronomy Journal • Volume 106, Issue 2 • 2014
Current yield
16
11
Breakeven yield
640
75
Percent
change
3900%
582%
405
Hillock-Vining, Christian Kapp, Raymond Miller, Doo-Hong Min,
Sue Rak, David Rothstein, Jay Sergeant, Craig Shaeffer, Kurt Thelen,
and Dan Undersander. For comments (but no responsibility for the
final product), we thank Christian Kapp, Raymond Miller, Daniel F.
Mooney, and David Rothstein.
References
Abrahamson, L.P., T.A. Volk, E. Priepke, J. Posselius, D.J. Aneshansley, and L.B.
Smart. 2008. Development of a willow biomass crop harvesting system in
New York. Powerpoint. Univ. of New York, College of Environmental Sci.
and Forestry. http://www.esf.edu/outreach/pd/2010/srwc/documents/
willowharvestingtalkSRWCOWG2010.pdf (accessed 17 Dec. 2013.
Abrahamson, L.P., T.A. Volk, L.B. Smart, and K.D. Cameron. 2010. Shrub
willow biomass producer’s handbook. State Univ. of New York, College
of Environmental Sci. and Forestry. www.esf.edu/willow/documents/ProducersHandbook.pdf (accessed 15 Aug. 2013).
Adler, P.R., S.J. Del Grosso, and W.J. Parton. 2007. Life-cycle assessment of net
greenhouse-gas flux for bioenergy cropping systems. Ecol. Appl. 17:675–
691. doi:10.1890/05-2018
Baier, S., M. Clemens, C. Griffiths, and J. Ihrig. 2009. Biofuels impact on crop
and food prices: Using an interactive spreadsheet. International Finance
Discussion Paper no. 967. Board of Governors of the Federal Reserve System, Washington, DC.
Boehlje, M.D., and V.R. Eidman. 1984. Farm management. Wiley, New York.
Brechbill, S.C., W.E. Tyner, and K.E. Ileleji. 2011. The economics of biomass
collection and transportation and its supply to Indiana cellulosic and electrical utility facilities. BioEnergy Research 4(2):141–152. doi:10.1007/
s12155-010-9108-0
Campbell, J.E., D.B. Lobell, R.C. Genova, and C.B. Field. 2008. The global
potential of bioenergy on abandoned agriculture lands. Environ. Sci. Technol. 42:5791–5794. doi:10.1021/es800052w
Chen, X., and M. Khanna. 2012. The market-mediated effects of low carbon fuel
policies. AgBioForum 15(1):1–17.
CIMMYT. 1988. From agronomic data to farmer recommendations: An economics training manual. Centro Internacional de Mejoramiento de Maíz
y Trigo (CIMMYT), Mexico. www.fao.org/sd/erp/toolkit/books/fromagronomic_manual.pdf (accessed 5 Oct. 2012.)
Corace, R.G., III, D.J. Flaspohler, and L.M. Shartell. 2009. Geographical patterns in openland cover and hayfield mowing in the Upper Great Lakes
region: Implications for grassland bird conservation. Landscape Ecol.
24:309–323. doi:10.1007/s10980-008-9306-8
Crutzen, P.J., A.R. Mosier, K.A. Smith, and W. Winiwarter. 2008. N2O
release from agro-biofuel production negates global warming reduction
by replacing fossil fuels. Atmos. Chem. Phys. 8:389–395. doi:10.5194/
acp-8-389-2008
Egbendewe-Mondzozo, A., S.M. Swinton, B.D. Bals, and B.E. Dale. 2013. Can
dispersed biomass processing protect the environment and cover the bottom line for biofuel? Environ. Sci. Technol. 47:1695–1703.
Egbendewe-Mondzozo, A., S.M. Swinton, C. Izzauralde, D.M. Manowitz, and
X. Zhang. 2011. Biomass supply from alternative cellulosic crops and crop
residues: A spatially explicit bioeconomic modeling approach. Biomass
Bioenergy 35:4636–4647. doi:10.1016/j.biombioe.2011.09.010
Erickson, K.W., C.B. Moss, and A.K. Mishra. 2004. Rates of return in the
farm and nonfarm sectors: How do they compare? J. Agric. Appl. Econ.
32:789–795.
Fargione, J., J. Hill, D. Tilman, S. Polasky, and P. Hawthorne. 2008. Land clearing and the biofuel carbon debt. Science (Washington, DC) 319:1235–
1238. doi:10.1126/science.1152747
Hayes, D.J., B.A. Babcock, J.F. Fabiosa, S. Tokgoz, A. Elobeid, T. Yu et al. 2009.
Biofuels: Potential production capacity, effects on grain and livestock sectors, and implications for food prices and consumers. J. Agric. Appl. Econ.
41(2):465–491.
Hertel, T.W., A.A. Golub, A.D. Jones, M. O’Hare, R.J. Plevin, and D.M. Kammen. 2010. Effects of US maize ethanol on global land use and greenhouse
gas emissions: Estimating market-mediated responses. Bioscience 60:223–
231. doi:10.1525/bio.2010.60.3.8
Hill, J., E. Nelson, D. Tilman, S. Polasky, and D. Tiffany. 2006. Environmental, economic, and energetic costs and benefits of biodiesel and ethanol
biofuels. Proc. Natl. Acad. Sci. USA 103:11206–11210. doi:10.1073/
pnas.0604600103
Ince, P.J. 2009. Status and trends of U.S. pulpwood market. Climate change and
its causes, effects, and prediction series. Nova Science Publ., New York. p.
101–117.
406
James, L.K., S.M. Swinton, and K.D. Thelen. 2010. Profitability analysis of
cellulosic energy crops compared with corn. Agron. J. 102:675–687.
doi:10.2134/agronj2009.0289
Keoleian, G.A., and T.A. Volk. 2005. Renewable energy from willow biomass
crops: Life cycle energy, environmental and economic performance. Crit.
Rev. Plant Sci. 24:385–406. doi:10.1080/07352680500316334
Khanna, M., X. Chen, H. Huang, and H. Onal. 2011. Supply of cellulosic biofuel feedstocks and regional production patterns. Am. J. Agric. Econ.
93(2):473–480.
Khanna, M., and C.L. Crago. 2012. Measuring indirect land use change with
biofuels: Implications for policy. Annual Review of Resource Economics
4:161–184. doi:10.1146/annurev-resource-110811-114523
Lemus, R., and R. Lal. 2005. Bioenergy crops and carbon sequestration. Crit.
Rev. Plant Sci. 24(1):1–21. doi:10.1080/07352680590910393
Meadows, S., T. Gallagher, and D. Mitchell. 2010. Project summary: Application
of a trailer-mounted slash bundler for southern logging. www.srs.fs.usda.
gov/pubs/37375 (accessed 19 June, 2012).
Min, D.H. 2011. Switchgrass for a bioenergy crop and livestock feed. Michigan
State Univ. Ext. http://msue.anr.msu.edu/news/switchgrass_for_a_bioenergy_crop_and_livestock_feed (accessed 13 Sept. 2013).
Mooney, D.F., R.K. Roberts, B.C. English, D.D. Tyler, and J.A. Larson. 2009.
Yield and breakeven price of ‘Alamo’ switchgrass for biofuels in Tennessee.
Agron. J. 101:1234–1242. doi:10.2134/agronj2009.0090
National Research Council. 2011. Renewable fuel standard: Potential economic
and environmental effects of U.S. biofuel policy. The National Academies
Press, Washington, DC.
Netzer, D.A., D.N. Tolsted, M.E. Ostry, J.G. Isebrands, D.E. Riemenschneider,
K.T. Ward. 2002. Growth, yield, and disease resistance of 7- to 12-year-old
poplar clones in the north central United States. Gen. Tech. Rep. NC-229.
USDA, Forest Serv., North Central Res. Stn., St. Paul, MN.
Ross, S.A., R.W. Westerfield, J. Jaffe, and B.D. Jordan. 2008. Modern financial
management. 8th ed. McGraw-Hill, Boston, MA.
Searchinger, T., R. Heimlich, R.A. Houghton, F.X. Dong, A. Elobeid, J. Fabiosa
et al. 2008. Use of US croplands for biofuels increases greenhouse gases
through emissions from land-use change. Science (Washington, DC)
319:1238–1240. doi:10.1126/science.1151861
Searcy, E., P. Flynn, E. Ghafoori, and A. Kumar. 2007. The relative cost of biomass
energy transport. Appl. Biochem. Biotechnol. 137:639–652. doi:10.1007/
s12010-007-9085-8
Stein, D. 2011a. Crop and livestock enterprise budgets. Michigan State Univ.
Ext. www.msu.edu/~steind/budgets_crop_production.html (accessed 16
Aug. 2013).
Stein, D. 2011b. Custom machine and work rate estimates. Michigan State Univ.
Ext.
www.msu.edu/user/steind/1_2012%20Cust_MachineWrk%20
10_31_11.pdf (accessed 15 June 2012).
Swinton, S.M., B.A. Babcock, L.K. James, and V. Bandaru. 2011. Higher US
crop prices trigger little area expansion so marginal land for biofuel crops
is limited. Energy Policy 39:5254–5258. doi:10.1016/j.enpol.2011.05.039
Thompson, J., and S. Blank. 2000. Harvest mechanization helps agriculture remain competitive. Calif. Agric. 54(3):51–56. doi:10.3733/
ca.v054n03p51
Tyner, W.E. 2008. The US ethanol and biofuels boom: Its origins, current status,
and future prospects. Bioscience 58(7):646–653. doi:10.1641/B580718
U.S. Congress. 2007. Public Law 110-140: Energy Independence and Security
Act of 2007. U.S. Gov. Print. Office, Washington, DC. www.gpo.gov/
fdsys/pkg/BILLS-110hr6enr/pdf/BILLS-110hr6enr.pdf (accessed 15 July
2012)
USDA, ERS. 2012. USDA Long-term Projections, February 2012. USDA,
Economic Res. Serv. www.ers.usda.gov/media/273331/oce121d_1_.pdf
(accessed 29 Aug. 2012)
USDA, NASS. 2010–2012. Survey of agriculture, 2010, 2011, 2012. USDA,
Natl. Agric. Statistics Serv., Washington, DC. Accessed via Quick Stats
2.0, 2013.
USDOE, EERE. 2012. State Laws and Incentives. U.S. Dep. of Energy, Office of
Energy Efficiency and Renewable Energy. www.afdc.energy.gov/laws/state
(accessed 21 Dec. 2012).
Wang, Z., and D.W. MacFarlane. 2012. Evaluating the biomass production of
coppiced willow and poplar clones in Michigan, USA, over multiple rotations and different growing conditions. Biomass Bioenergy 46:380–388.
doi:10.1016/j.biombioe.2012.08.003
Zamora, D., G. Wyatt, and J. Isebrands. 2011. Hybrid poplar best management
practices. Univ. of Minnesota Ext. www.extension.umn.edu/distribution/
naturalresources/M1313.html (accessed 15 July 2013).
Agronomy Journal • Volume 106, Issue 2 • 2014