indirect land use change for biofuels: testing predictions and improving analytical methodologies

6
Indirect land use change for biofuels: Testing predictions and improving analytical methodologies Seungdo Kim, Bruce E. Dale* Department of Chemical Engineering and Materials Science, DOE Great Lakes Bioenergy Research Center, Michigan State University, 3900 Collins Road, Lansing, MI 48910, USA article info Article history: Received 27 January 2011 Received in revised form 21 April 2011 Accepted 25 April 2011 Available online 13 May 2011 Keywords: Corn Biofuel Historical data Indirect land use change Renewable energy policy Soybean abstract Current practices for estimating indirect land use change (iLUC) due to United States bio- fuel production rely on assumption-heavy, global economic modeling approaches. Prior iLUC studies have failed to compare their predictions to past global historical data. An empirical approach is used to detect evidence for iLUC that might be catalyzed by United States biofuel production through a “bottom-up”, data-driven, statistical approach. Results show that biofuel production in the United States from 2002 to 2007 is not significantly correlated with changes in croplands for corn (coarse grain) plus soybean in regions of the world which are corn (coarse grain) and soybean trading partners of the United States. The results may be interpreted in at least two different ways: 1) biofuel production in the United States through 2007 (the last date for which information is available) probably has not induced any indirect land use change, and 2) this empirical approach may not be sensitive enough to detect indirect land use change from the historical data. It seems clear that additional effort may be required to develop methodologies to observe indirect land use change from the historical data. Such efforts might reduce uncertainties in indirect land use change estimates or perhaps form the basis for better policies or standards for biofuels. ª 2011 Elsevier Ltd. All rights reserved. 1. Introduction Indirect land use change (iLUC) due to biofuel production has become a key issue in the ongoing ‘Food-versus-Energy’ debates. The basic concept of iLUC is that natural ecosystems elsewhere might be converted to croplands to replace crops (either ‘animal feed’ or ‘food’) that are lost due to biofuel production. For example, changes in the United States (US) corn supply caused by ethanol fuel production could eventu- ally lead to increases in: 1) corn (coarse grain) areas in other countries due to decline in US corn export or 2) croplands for soybean in other countries due to a decline in US soybean exports, resulting from conversion of soybean fields to corn- fields in the United States. Several studies show that iLUC has the potential to be one of the primary potential greenhouse gas (GHG) sources in well- to-fuel GHG emissions of biofuels [1e5]. Crop management practices in newly converted croplands can also play an important role in GHG estimates due to iLUC [6]. Even though there is a general consensus within the biofuel community that the iLUC effects are potentially important, a major concern for iLUC is ‘uncertainty’, particularly due to the amount and type of forest and grassland converted. These are critical factors in determining GHG emissions associated with iLUC. For example, Searchinger et al. [1] shows that about 9.1 ha of natural ecosystems are converted to croplands (52% from forest, 46% from grassland and 2% from desert) due to one TJ of ethanol fuel production, while the United States * Corresponding author. Tel.: þ1 517 353 6777; fax: þ1 517 337 7904. E-mail addresses: [email protected] (S. Kim), [email protected] (B.E. Dale). Available at www.sciencedirect.com http://www.elsevier.com/locate/biombioe biomass and bioenergy 35 (2011) 3235 e3240 0961-9534/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.biombioe.2011.04.039

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Page 1: Indirect land use change for biofuels: Testing predictions and improving analytical methodologies

b i om a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 3 2 3 5e3 2 4 0

Avai lab le a t www.sc iencedi rec t .com

ht tp : / /www.e lsev ier . com/ loca te /b iombioe

Indirect land use change for biofuels: Testing predictions andimproving analytical methodologies

Seungdo Kim, Bruce E. Dale*

Department of Chemical Engineering and Materials Science, DOE Great Lakes Bioenergy Research Center, Michigan State University,

3900 Collins Road, Lansing, MI 48910, USA

a r t i c l e i n f o

Article history:

Received 27 January 2011

Received in revised form

21 April 2011

Accepted 25 April 2011

Available online 13 May 2011

Keywords:

Corn

Biofuel

Historical data

Indirect land use change

Renewable energy policy

Soybean

* Corresponding author. Tel.: þ1 517 353 677E-mail addresses: [email protected] (S.

0961-9534/$ e see front matter ª 2011 Elsevdoi:10.1016/j.biombioe.2011.04.039

a b s t r a c t

Current practices for estimating indirect land use change (iLUC) due to United States bio-

fuel production rely on assumption-heavy, global economic modeling approaches. Prior

iLUC studies have failed to compare their predictions to past global historical data. An

empirical approach is used to detect evidence for iLUC that might be catalyzed by United

States biofuel production through a “bottom-up”, data-driven, statistical approach. Results

show that biofuel production in the United States from 2002 to 2007 is not significantly

correlated with changes in croplands for corn (coarse grain) plus soybean in regions of the

world which are corn (coarse grain) and soybean trading partners of the United States. The

results may be interpreted in at least two different ways: 1) biofuel production in the United

States through 2007 (the last date for which information is available) probably has not

induced any indirect land use change, and 2) this empirical approach may not be sensitive

enough to detect indirect land use change from the historical data. It seems clear that

additional effort may be required to develop methodologies to observe indirect land use

change from the historical data. Such efforts might reduce uncertainties in indirect land

use change estimates or perhaps form the basis for better policies or standards for biofuels.

ª 2011 Elsevier Ltd. All rights reserved.

1. Introduction Several studies show that iLUC has the potential to be one

Indirect land use change (iLUC) due to biofuel production has

become a key issue in the ongoing ‘Food-versus-Energy’

debates. The basic concept of iLUC is that natural ecosystems

elsewhere might be converted to croplands to replace crops

(either ‘animal feed’ or ‘food’) that are lost due to biofuel

production. For example, changes in the United States (US)

corn supply caused by ethanol fuel production could eventu-

ally lead to increases in: 1) corn (coarse grain) areas in other

countries due to decline in US corn export or 2) croplands for

soybean in other countries due to a decline in US soybean

exports, resulting from conversion of soybean fields to corn-

fields in the United States.

7; fax: þ1 517 337 7904.Kim), [email protected] Ltd. All rights reserved

of the primary potential greenhouse gas (GHG) sources inwell-

to-fuel GHG emissions of biofuels [1e5]. Crop management

practices in newly converted croplands can also play an

important role in GHG estimates due to iLUC [6]. Even though

there is a general consensus within the biofuel community

that the iLUC effects are potentially important, a major

concern for iLUC is ‘uncertainty’, particularly due to the

amount and type of forest and grassland converted. These are

critical factors in determining GHG emissions associated with

iLUC. For example, Searchinger et al. [1] shows that about

9.1 ha of natural ecosystems are converted to croplands (52%

from forest, 46% from grassland and 2% from desert) due to

one TJ of ethanol fuel production, while the United States

(B.E. Dale)..

Page 2: Indirect land use change for biofuels: Testing predictions and improving analytical methodologies

b i om a s s an d b i o e n e r g y 3 5 ( 2 0 1 1 ) 3 2 3 5e3 2 4 03236

Environmental Protection Agency (US EPA) [2] estimates about

4.4 ha TJ�1 for land conversion as iLUC (66% from forest and

34% from grassland). The California Air Resources Board

(CARB) [3] and the GREETmodel [4,5] estimate the iLUC effects

due to corn based ethanol via the Global Trade Analysis

Project (GTAP) model to determine the sizes and the locations

of natural ecosystems converted due to biofuels. Results from

CARB show the conversion of 5.1 ha TJ�1 of natural ecosys-

tems to croplands (26% from forest and 74% from grassland),

while GREET shows the conversion of 1.6 ha TJ�1 of natural

ecosystems to croplands (33% from forest and 67% from

grassland). These results show that the sizes, the types and

the locations of the natural ecosystems converted differ

greatly between the economic models chosen and their

assumptions.

CARB [3] uses an ethanol production increase of 50 hm3 in

its economic modeling, while the US EPA [2] uses a 10 hm3

ethanol production increase. CARB’s assumption of

a 50 hm3 ethanol production increase in its analysis implies

that an ethanol production increase dating from 2002 would

begin to trigger iLUC.

If biofuel production in the United States has indeed trig-

gered land conversion elsewhere, evidence for iLUC effects

should be observed in the historical data. The historical data

would include changes in the area of forest lands, total arable

lands and croplands for animal feed and food associated with

biofuel production in the United States. Few studies have

attempted to find evidence for iLUC from the historical data.

This study attempts to detect evidence for iLUC from the

historical data through a set of tests for a better understanding

of iLUC in policy or standard developments. The tests devel-

oped in this study identify regions of the world in which iLUC

due to US biofuel production might be observed from the

historical data. This analysis uses 19 geographical regions as

in Tyner et al.’s study [5] e Brazil (BRA), Canada (CAN), China

and Hong Kong (CHK), India (IND), Japan (JAP), United States

(USA), Central and Caribbean Americas (CCA), East Asia (EAS),

European Union 27(EUN), Malaysia and Indonesia (MAI),

Middle Eastern and North Africa (MEA), Oceania countries

(OCC), Other East Europe and Rest of Former Soviet Union

(OES), Rest of European Countries (REC), Rest of South Asia

(RSA), Rest of South East Asia (SEA), Russia (RUS), South and

Other Americas (SOA), and Sub Saharan Africa (SSA). The

details of these regions are given elsewhere [5]. The historical

data, including land use patterns and commodity grain

imports, associated with those 19 regions are investigated to

determine regions where iLUC has occurred.

2. Material and methods

The analysis proposed in this study is an empirical approach

to detect indirect land use change due to US biofuel produc-

tion, particularly corn based ethanol and soybean biodiesel.

This is a “bottom-up”, data-driven, statistical approach based

on individual regions’ land use patterns and commodity grain

imports. This approach relies on very few assumptions and

tries neither to quantify nor to predict iLUC effects. According

to iLUC predictions [1e3], production of corn ethanol or

soybean biodiesel in the United States will lead to reduced

exports which will increase crop commodity prices which in

turn will catalyze land use change with potentially large

accompanying GHG releases. Thus biofuel production leads to

reduced exports which in turn lead to land use change. It is

this mechanism that we test here.

Predictions of iLUC are empirically tested using historical

data on the United States croplands, commodity grain exports

to specific regions and land use trends in those geographical

regions. We use the 1990s as a baseline when the United

States biofuel industry was very small and measure changes

against that baseline. In order for iLUC to occur in a specific

geographical region, it is postulated that the following five

conditions must be met simultaneously.

1. For a specific region, average areas of croplands used for

corn plus soybean production in the 2000s must increase

compared to the 1990s.

2. For a specific region, average areas of arable lands in the

2000smust also increase compared to the 1990s. Otherwise,

corn plus soybean areas are probably converted from other

cropland areas in that region. Biofuel production in the

United States is unlikely to be involved in those inter-

cropland conversion processes. Economic or other factors

such as domestic agricultural policies are more likely to be

responsible for those inter-cropland conversions than is US

biofuel production [7]. Since there is always some cost

associated with bringing new lands into agricultural

production, we assume that there would be no conversion

of natural ecosystems in regions where average areas of

arable lands in the 2000s are less than those in the 1990s.

3. For a particular geographical region, average areas of

natural ecosystem lands in the 2000s decline compared to

the 1990s. The natural ecosystem lands include forest, and

permanent meadows and pastures. Otherwise, no natural

ecosystems are converted to croplands to produce animal

feed or food that is lost due to US biofuel production.

4. For a particular region, average corn plus soybean imports

from United States in the 2000s decline significantly

compared to imports during the 1990s. Annual changes

that occur within average annual variation are taken to

mean ‘no significant decline’. iLUC due to biofuel produc-

tion is not likely to occur in regions within which mean

corn plus soybean imports from United States increase.

Up to this point, conditions 1e4 seem to be straightfor-

ward. Indirect land use changes due to US biofuel production

would not happen in regions that do not meet conditions 1e4.

The last condition (condition 5) determines whether iLUC

would be observed in the regions that meet conditions 1e4

using correlation tests. Changes in harvested areas for corn

and soybean for US biofuel productionwill lead to increases or

decreases in croplands for corn plus soybean in a specific

region if US biofuel production influences land use changes.

The correlation test between biofuel production and land use

changes can provide some clues about the relationships

between these factors.

5. Annual percentage changes in croplands for corn plus

soybean in a specific region are positively correlated with

Page 3: Indirect land use change for biofuels: Testing predictions and improving analytical methodologies

b i om a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 3 2 3 5e3 2 4 0 3237

annual percentage changes in harvested areas for corn and

soybean for biofuel production (corn ethanol and soybean

biodiesel) in the United States. A negative correlation

suggests that annual percentage changes in croplands for

corn plus soybean decline with annual percentage changes

in harvested areas for corn and soybean for biofuel

production in the United States. Even though ‘correlation’

does not mean ‘causation’, ‘no correlation’ strongly

suggests ‘not related to each other’.

Year 2007 biofuel production in the United States is tested

using the above conditions to determine regions within which

iLUC effects are detected in the historical data. The 1990

baseline values are average values from 1992 to 1999. Average

values in the 2000s are taken from 2000 to 2008. Global infor-

mation on country-level croplands and natural ecosystems is

available at the Food and Agriculture Organization of the

United Nations e FAOSTAT [8]. The United States corn and

soybean trade data are obtained from the United States

Foreign Agricultural Service [9].

Even though crop price is a primary factor driving iLUC

effects in the global economicmodels, the amount of cropland

involved is used in the correlation tests. The historical data

show that annual percentage changes in corn prices in the

United States are moderately correlated with annual

percentage changes in croplands for US biofuel production.

This is illustrated in Fig. 1. Due to moderate correlations,

cropland would be more appropriate for the correlation tests

than crop price. Furthermore, corn price is also influenced by

fossil energy costs (crude oil price), weather conditions and

other factors [10,11].

Annual percentage change is defined as (Ai�Ai�1)/(Ai�1) %,

where Ai is area at year i. The reasons for using the annual

percentage changes instead of total cropland areas in this

analysis are that a) biofuel production accounts for only 1.5%

of global croplands for grain and oil seeds [12], b) the biofuel

industry is relatively young, and c) many other factors rather

than biofuel production (e.g., population pressure, food

consumption, economics, crop yields, commodity specula-

tion, etc.) are involved in the system. Therefore, correlation

tests with the total cropland areas would not be appropriate.

The annual change in croplands, not just percentage change,

is another feasible parameter for the correlation tests. Both

Fig. 1 e Annual percentage changes in corn price versus

annual percentage changes in croplands for biofuel

production in the United States (from 1997 to 2009).

parameters (i.e., annual percentage changes and annual

changes) are investigated in our correlation tests.

For the correlation tests, corn area used for corn based

ethanol production is estimated by Eq. (1).

EtOHi$

�Di

YDiþ ð1� DiÞ

YWi

Ci�1$bþ

EtOHi$

�Di

YDiþ ð1� DiÞ

YWi

Ci$ð100� bÞ

(1)

Where EtOHi is corn based ethanol production at year i. Di is

the dry milling share of total ethanol production. YDi is

ethanol yield in dry milling, while YWi is ethanol yield in wet

milling. Ci is corn yield at year i. b is a percentage of feedstock

harvested in the previous year involved in producing corn

based ethanol at year i. (100�b) is a percentage of feedstock

harvested at year i. Soybean area used for soybean diesel

follows the same algorithm. Biofuel yield (e.g., ethanol and

soybean diesel) and other data are obtained from literature

[4,13e15].

We assume that essentially 100% of US biofuel production

in a given year is derived from feedstock harvested in the

previous year (b ¼ 1). This implies that there is at least a two-

year lag between diversion of corn and soybean production to

biofuels and any possible iLUC effects. The time lag between

biofuel production and its possible iLUC effects is one year, in

order to account for planting and harvesting decisions. For

example, the iLUC effects due to corn and soybeans produced

in 2005 and converted to biofuels in the US would occur in

2007 in the regions of interest, while the iLUC effects due to

the 2006 diversion of corn and soybean production to the 2007

biofuel production increase in the United States would occur

in 2008. In a sensitivity analysis, we investigate the effect of

the fraction of feedstock harvested in the previous year

involved in biofuel production in a given year.

The possibility that coarse grains other than corn alone are

planted in the newly converted croplands is also investigated

in a sensitivity analysis (referred to as ‘coarse grain case’).

This coarse grain case in the sensitivity analysis affects

conditions 1, 4 and 5. Croplands for coarse grain plus soybean

production in condition 1 and coarse grain plus soybean

imports from United States in condition 4 are investigated. In

condition 5, the correlations between croplands for coarse

grain plus soybean in a specific region and harvested areas for

corn and soybean for biofuel production are tested.

3. Results

First, the correlations between domestic cropland and crop-

land used for biofuel production in the United States are

investigated to determine whether iLUC has occurred in the

United States e annual percentage changes in planted areas

for crops versus annual percentage change in croplands for

biofuel production. Results show that the annual percentage

change in planted areas for cotton, corn plus soybean and oats

are significantly correlated with the annual percentage

change in croplands for biofuel production in the United

States at p< 0.05. However, negative correlations are observed

only for cotton, which is not a major food source. This implies

that US biofuel production can reduce croplands for cotton,

Page 4: Indirect land use change for biofuels: Testing predictions and improving analytical methodologies

Table 1 e Results from testing conditions 1e4 [O:satisfying, X: not satisfying, n.a.: not applicable].

Condition1

Condition2

Condition3

Condition4

Brazil O (O) O O O (O)

Canada O (X) X O X (X)

China and

Hong Kong

O (X) X X X (X)

India O (O) X X O (O)

Japan O (X) X O X (O)

United States O (X) X X n.a.

Central and

Caribbean

Americas

X (X) O O X (X)

East Asia X (X) X O O (O)

European

Union 27

X (X) X X O (O)

Malaysia and

Indonesia

X (X) O O X (X)

Middle Eastern

and North

Africa

X (X) O X X (X)

Oceania

Countries

O (O) O O O (O)

Other East

Europe and

Rest of

Former

Soviet Union

O (X) X X X (X)

Rest of

European

Countries

X (X) X X O (O)

Rest of South

Asia

O (O) X O X (X)

Rest of South

East Asia

O (O) O O X (X)

Russia O (X) X X O (O)

South and

Other

Americas

O (O) O O X (X)

Sub Saharan

Africa

O (O) O O O (X)

b i om a s s an d b i o e n e r g y 3 5 ( 2 0 1 1 ) 3 2 3 5e3 2 4 03238

which is consistent with findings in the United States

Government Accountability Office’s report [11]. This result

also intensifies the rationale for condition 5. Pearson product-

moment correlation coefficients for individual crops up to

year 2009 are summarized in the supplementary material.

Even though year 2007 US biofuel production is tested for

conditions in other regions, the data availability in the United

States allows investigating year 2009 biofuel production to

determine the iLUC effects in the United States. No arable land

increases from the 1990s are observed in the United States.

Furthermore, no declines in natural ecosystem lands in the

United States have been observed since 1998. Therefore, the

US historical data do not indicate that iLUC occurred within

the 48 contiguous states as a result of US biofuel production.

The regional information on 18 regions (except for the USA)

is tested for conditions 1e4 first to identify any regions that

meet all four conditions. Results show that only three regions

satisfy conditions 1e4: Brazil, Oceania countries, and Sub

Saharan Africa (Brazil and Oceania countries in the coarse

grain case). These three regions (two regions in the coarse

grain case) would thus have potential for iLUC due to US

biofuel production and are tested through the correlation

analysis. Results from testing conditions 1e4 are listed in

Table 1. Results in parentheses reflect the coarse grain case.

The MAI region (Malaysia and Indonesia) is eliminated

from consideration because it shows no increases in crop-

lands for corn (coarse grain) plus soybean despite satisfying

conditions 2e4. About 44% of natural ecosystems converted in

the MAI region from 1992 to 2008 become croplands, while the

rest of the natural ecosystems converted (about 56%) become

urban or other lands. Palm oil, but not corn (coarse grain) or

soybeans, is the major crop planted in the converted natural

ecosystem followed by coffee, coca bean and natural rubber

from 1992 to 2008. On the contrary, average croplands for

soybean in the 2000s in the MAI region were reduced by 55%

compared to those in the 1990s. It is thus obvious that US

biofuel production does not play a great role in land use

changes in the MAI region.

Although the SEA (Rest of South East Asia) and the SOA

regions (South and Other Americas) meet conditions 1e3,

these two regions do not meet condition 4. The average corn

(coarse grain) plus soybean imports from United States in the

2000s in the SEA and the SOA region increased by 22% (20%)

and 30% (29%) compared to corn (coarse grain) plus soybean

imports during the 1990s, respectively. Rice and beans are the

major crops grown on increased arable lands in the SEA

region, while soybean is the major crop grown on increased

arable lands in the SOA region, particularly in Argentina. Large

increases in soybean areas in Argentina occurred from 2001 to

2005 because of its floating currency policy, biotechnology and

double cropping [7]. Therefore, US biofuel production does not

play a role in increasing soybean area in the SOA regions.

If the correlation is significant, three regions (two regions

in the coarse grain case) identified from conditions 1e4 (i.e.,

BRA, OCC and SSA) might potentially have converted natural

ecosystems to croplands to produce corn (coarse grain) and

soybean that were once imported from the United States. Both

Pearson product-moment and Spearman’s rank correlation

coefficients are used to determine whether the correlation

between the percentage changes of croplands for corn (coarse

grain) plus soybean in those regions and the percentage

changes in corn and soybean production dedicated to US

biofuel production is significant at p < 0.05. Results show that

there are no regions that have a significant correlation

(at p < 0.05), implying that the percentage change in cropland

for corn (coarse grain) plus soybean in regions which are corn

(coarse grain) and soybean trading partners of the United

States may not be significantly correlated with the percentage

change in croplands for biofuel production in the United

States up to the 2007 biofuel production increase. These

results provide strong evidence that either: 1) no iLUC has

occurred due to US biofuel production up through the end of

2007 or 2) that the empirical data cannot detect iLUC due to US

biofuel production.

Increased soybean production plays a major role in

increased croplands in Brazil. Policies, biotechnology and

growing soybean demand from China expanded soybean area

in Brazil [16,17]. Wheat accounts for about 57% of the arable

land increases from the 1990s in the OCC region (Oceania

Countries), followed by barley and rapeseed accounting for

Page 5: Indirect land use change for biofuels: Testing predictions and improving analytical methodologies

b i om a s s a n d b i o e n e r g y 3 5 ( 2 0 1 1 ) 3 2 3 5e3 2 4 0 3239

27% and 14%, respectively. It is possible that declines in

soybean imports from the United States would lead to

increases in croplands for rapeseed in the OCC region,

particularly Australia. However, rapeseed production in

Australia began to increase in early 1990s. Better varieties,

improved agronomy, crop monitoring program (Canola

Check) and good prices are the primary reasons for the

expansion of croplands for rapeseed in Australia [18]. Most

increases in croplands for rapeseed in Australia occurred

during 1998 and 1999 [19]. Therefore, the expansion of rape-

seed production in the OCC region is not related to US biofuel

production. Population pressure is a major driver for agricul-

tural expansion in the SSA region (Sub Saharan Africa) [20,21],

where extensification is a dominant trend [22].

Results for the correlation tests are summarized in the

supplementary material. Even though the RSA region (Rest of

South Asia) has a significant correlation with the annual

percentage change in croplands for US biofuel production at

p < 0.05, the RSA region fails to meet other conditions 1e4.

Sensitivity analyses also show that using the annual changes

as parameters (instead of the annual percentage changes)

does not affect the findings. The coarse grain case also shows

the similar results, which are summarized in the supple-

mentary material.

4. Discussion and conclusions

Results from these empirical tests are likely to be controver-

sial. Our results can be interpreted in two different ways:

1. Biofuel production in the United States up through the end

of 2007 in all probability has not induced indirect land use

change.

There are two feasible dependent conclusions to that

might be drawn from this interpretation: 1) crop intensifica-

tion may have absorbed the effects of expanding US biofuel

production or 2) the effects of US biofuel production expan-

sion may be simply negligible, and not resolvable within the

accuracy of the data. Note that these results do not apply to

increased biofuels production after 2008. Data do not yet exist

to make comparable tests after 2008. It therefore appears that

not every unit of biofuel production implemented to date has

triggered indirect land use change. For example, the 1999

biofuel production increase (biofuel produced in a biofuel

production facility built in 1999) has apparently not triggered

indirect land use change, while we do not have information to

say one way or the other whether the 2010 biofuel production

increase triggered iLUC. In other words, the characteristics of

indirect land use changes due to 2010 biofuel production

increases may be quite different from those due to a 2015

biofuel production increase. This conclusion also suggests

that ongoing agricultural intensification can continue to

absorb the effects of biofuel production expansion without

inducing indirect land use change, at least up to some level.

2. A contrary interpretation is that this empirical test simply

fails to detect ongoing indirect land use change from the

historical data.

This interpretation implies that iLUC has occurred, but that

our analysis may not be adequate to detect it from the

historical data. Thus more sophisticated empirical

approaches should be developed to detect indirect land use

change from the historical data.

Another concern with our conclusions is based on the

completeness of the FAO statistics. Unfortunately, there are

no global data currently available that are as complete as the

FAO statistics. In fact, some global economic models used to

estimate iLUC also use the data from the FAO statistics. Thus,

this concern does not appear to be relevant. Either these data

are adequate for analysis or they are not, and if they are not,

then iLUC estimates based on them are invalid also, and the

discussion cannot proceed further.

Very few previous studies have attempted to find empirical

evidence for or against indirect land use change from the

historical data. Most previous studies [1e5] have relied on

global economic simulations. Therefore, we encourage addi-

tional effort to determine a potential threshold point for

indirect land use change, to developmethodologies to observe

indirect land use change in the historical data, or to determine

that no measurable iLUC is taking place in the United States.

Such efforts might reduce uncertainties in indirect land use

change estimates or form the basis for better policies or

standards for biofuels.

Acknowledgments

This work was funded by DOE Great Lakes Bioenergy

Research Center (www.greatlakesbioenergy.org) supported by

the US Department of Energy, Office of Science, Office of

Biological and Environmental Research, through Cooperative

Agreement DEFC02-07ER64494. Support was also provided by

the Michigan Agricultural Experiment Station.

Appendix. Supplementary data

Supplementary data associated with this article can be found,

in the online version, at doi:10.1016/j.biombioe.2011.04.039.

r e f e r e n c e s

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