supporting information for ” by thomas kastner,...
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Supporting information for “Rapid growth in agricultural trade: effects on global area-efficiency and the 1
role of management” by Thomas Kastner, Karl-Heinz Erb and Helmut Haberl 2
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Method and data 5 Table S1 lists the specific webpage links to the used FAOSTAT datasets along with the dates of last 6
access. The following section gives a short overview on these data and their handling. 7
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Production data 9
We use data on crop production for 157 primary crops along with data on crop yields [1], excluding 10
planted fodder crops (see below for details). Additionally, we use production data for six primary animal 11
products from the same database. Table S3 list the included primary products. 12
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Trade data 14
Detailed trade data from the FAO database form the cornerstone of our calculations [1]. These give 15
information on bilateral trade linkages for 574 agricultural commodities and are based on the UN’s 16
COMTRADE database [2]. We use data in physical units (tons) on import and export connections. For a 17
variety of reasons, it is not uncommon that reported import flows into country A from country B, are 18
different from export flows from country B into country A [3]. For our calculations, we give priority to 19
import data. In the case that export data are reported for a product, while import data are not, we use 20
export data. From the total available data for 574 items, our calculations cover about 450 items or about 21
97% of the total global trade volume expressed in tons of dry matter biomass (for the remaining products, 22
no unambiguous link to a primary crop could be established). The used trade statistics do not include food 23
aid shipments. In 2008 (3 year average) such shipments amounted to about 5 million tons dry matter 24
biomass [1], or 0.7% of the total global production for export we find in Table S2. 25
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Animal feed data 27
To arrive at a consistent assessment of feed products from cropland linked to traded animal products we 28
utilize data from FAOSTAT’s commodity balances on feed use at the national level [1]. These data 29
provide information on the amount of about 70 crop products used as animal feed. 30
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Table S1. FAOSTAT data sets used for the calculations, along with and links to the respective webpages 32
and dates of last access. 33
Data set Link Date last accessed
Crop production and yield data http://faostat.fao.org/site/567/default.aspx November 29, 2013
Livestock production data http://faostat.fao.org/site/569/default.aspx November 29, 2013
Feed use data http://faostat.fao.org/site/614/default.aspx November 30, 2013
Bilateral trade data http://faostat.fao.org/site/537/default.aspx March 13, 2012
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Calculations 35 Figure S1 presents a detailed flowchart of the calculation necessary to arrive accounts conceptualized in 36
Figure 1 and presented in Figures S2 and 2. The main principles of the approach are described in the main 37
text and in [4]. Accounting for cropland feed needed to generate animal products poses an additional 38
challenge. To arrive at results consistent with reported national level feed use [1], in a first step we apply 39
the described procedure to trade and production data for the six primary animal products (and the included 40
processed animal products derived from those). In a next step, country specific weighting factors of feed 41
demand per unit of animal product are applied (based on [5,6]. This yields 40 matrices for cropland feed 42
products in primary equivalents (e.g. maize, soybeans) which are added to the respective trade matrices of 43
traded plant based products. This way, feed products can be traced to the place of cultivation: for instance, 44
if country A imports meat produced in country B with feed from country C, this flow will show up as 45
consumption of country A supplied by cropland from country C. 46
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47 Figure S1. Flow chart of calculation steps to arrive at consumption-perspective accounts of crop product and cropland demand at the national level. 48
Input data in normal font, intermediate results in italics, final result in bold font. The numbers above the boxes refer to the dimensions of the 49
respective data sets, (dimensions are: number of nations x (number of nations) x number of items x number years). The regional totals of the colored 50
boxes correspond to the lines displayed in Figure S2, and, conceptually, to the height of the bars in Figure 1.51
Bilateral Trade data (plant products)
Production data (primary crops)
Feed use data(crop products)
Bilateral Trade data (crops in
animal products)
Production data (animal
products)Origin of animal
products (primary
equivalents)Bilateral Trade data (animal
products)
Bilateral Trade data (primary
crop equivalents)
Bilateral Trade data (primary
animal products equivalents)
Consumption-perspective
account of crop products
Crop yield data
Consumption-perspective account of cropland demand
Conversionfactors
Feed use data (primary crop equivalents)
Conversion factors
Conversionfactors
Feed requirements
key
255 x 255 x 78 x 24
Calculations following
Kastner et. al 2011
Calculations following
Kastner et. al 2011
255 x 157 x 24
255 x 157 x 24
255 x 255 x 157 x 24
255 x 255 x 157 x 24255 x 255 x 157 x 24
255 x 255 x 400 x 24
255 x 255 x 6 x 24
255 x 6 x 24
255 x 255 x 6 x 24
255 x 73 x 24 255 x 38 x 24
255 x 255 x 38 x 24
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Results 52
53 Figure S2. Regional trends in crop production and crop products associated with consumption and 54
import and export flows for the years 1986 - 2009, following the accounting scheme in Figure 1. Values in 55
million tons dry matter crop biomass per year, trade flows reflect interregional trade only. Note the 56
different scales of the y-axes. 57
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North America Central America and the Caribbean South America
EU 15+ FSU and other Europe Sub-Saharan Africa
- 2 4 6 8
10 12 14
1986 1989 1992 1995 1998 2001 2004 2007
production consumption
for exports from imports
Northern Africa and Western Asia Eastern Asia Southern Asia
Southeast Asia Oceania
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59 Figure S3. Crop products associated with interregional trade; the color of the regions shows rates of self-60
sufficiency (production / consumption). Values in million tons dry matter crop biomass per year; flows 61
larger than 10 million tons are shown. The flows shown account for 51% (1987) respectively 63% (2008) 62
of the total crop products related to interregional trade. Values are 3-year means around the respective 63
year. 64
2008
1987
11
22
20
18 45
14
10
2038
2223
2114
30
61
27
1.0
self-sufficiency ratio (production / consumption)
1.1 1.2 1.3 1.4 1.5 1.60.90.80.70.6
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Table S2. Composition of the 11 world regions; our region grouping follows largely the UN geographical 65
region and composition (http://unstats.un.org/unsd/methods/m49/m49regin.htm), with the exception of the 66
regions European Union 15+ (EU 15+) and Former Soviet Union and other Europe (FSU and other 67
Europe). These changes were made to enable for constant region groups throughout time and to account 68
for common recent economic history. 69
North America Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of
America
Central America
and Caribbean
Belize, Costa Rica, El Salvador, Guatemala, Honduras, Mexico, Nicaragua,
Panama, Antigua and Barbuda, Bahamas, Barbados, Aruba, Cayman Islands,
Cuba, Dominica, Dominican Republic, Grenada, Guadeloupe, Haiti, Jamaica,
Martinique, Montserrat, Netherlands Antilles, Puerto Rico, Saint Kitts and Nevis,
Saint Lucia, Saint Vincent and the Grenadines, Trinidad and Tobago, Turks and
Caicos Islands, British Virgin Islands, United States Virgin Islands, Anguilla
South America
Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Ecuador,
Falkland Islands (Malvinas), French Guiana, Guyana, Paraguay, Peru, Suriname,
Uruguay, Venezuela (Bolivarian Republic of)
EU 15+
Denmark, Faroe Islands, Finland, Iceland, Ireland, Norway, Sweden, United
Kingdom, Channel Islands, Svalbard and Jan Mayen Islands, Isle of Man,
Andorra, Gibraltar, Greece, Holy See, Italy, Malta, Portugal, San Marino, Spain,
Austria, Belgium-Luxembourg, France, Germany, Liechtenstein, Monaco,
Netherlands, Switzerland, Belgium, Luxembourg
FSU and other
Europe
Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan, Bulgaria,
Czechoslovakia, Belarus, Hungary, Republic of Moldova, Czech Republic,
Poland, Romania, Russian Federation, Slovakia, USSR, Ukraine, Estonia, Latvia,
Lithuania, Albania, Bosnia and Herzegovina, Croatia, The former Yugoslav
Republic of Macedonia, Serbia and Montenegro, Slovenia, Yugoslav SFR, Serbia,
Montenegro
Sub-Saharan Africa
British Indian Ocean Territory, Burundi, Comoros, Ethiopia PDR, Djibouti,
Kenya, Madagascar, Malawi, Mauritius, Mozambique, Eritrea, Zimbabwe,
Réunion, Rwanda, Seychelles, Somalia, United Republic of Tanzania, Uganda,
Ethiopia, Zambia, Mayotte, Angola, Cameroon, Central African Republic, Chad,
Congo, Equatorial Guinea, Gabon, Sao Tome and Principe, Democratic Republic
of the Congo, Botswana, Lesotho, Namibia, South Africa, Swaziland, Cape Verde,
Benin, Gambia, Ghana, Guinea, Côte d'Ivoire, Liberia, Mali, Mauritania, Niger,
Nigeria, Guinea-Bissau, Saint Helena, Senegal, Sierra Leone, Togo, Burkina Faso
Northern Africa
and Western Asia
Algeria, Egypt, Libya, Morocco, Western Sahara, Sudan, Tunisia, Armenia,
Bahrain, Cyprus, Azerbaijan, Georgia, Iraq, Israel, Jordan, Kuwait, Lebanon,
Qatar, Saudi Arabia, Syrian Arab Republic, Oman, Turkey, United Arab Emirates,
Yemen, Occupied Palestinian Territory
Eastern Asia Japan, Democratic People's Republic of Korea, Republic of Korea, Mongolia,
China
Southern Asia Afghanistan, Bangladesh, Bhutan, Sri Lanka, India, Iran (Islamic Republic of),
Maldives, Nepal, Pakistan
Southeast Asia Brunei Darussalam, Myanmar, Indonesia, Cambodia, Lao People's Democratic
Republic, Malaysia, Philippines, Timor-Leste, Singapore, Thailand, Viet Nam
Oceania
American Samoa, Australia, Solomon Islands, Christmas Island, Cocos (Keeling)
Islands, Cook Islands, Fiji, French Polynesia, Kiribati, Guam, Marshall Islands,
Micronesia (Federated States of), Nauru, New Caledonia, Vanuatu, New Zealand,
Niue, Norfolk Island, Northern Mariana Islands, Pacific Islands Trust Territory,
Papua New Guinea, Pitcairn Islands, Palau, Tokelau, Tonga, Tuvalu, Wake Island,
Wallis and Futuna Islands, Samoa
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Table S3. Primary crops and primary animal products covered in the presented data 70
Crops Agave Fibres Nes; Almonds, with shell; Anise, badian, fennel, corian.; Apples; Apricots;
Arecanuts; Artichokes; Asparagus; Avocados; Bambara beans; Bananas; Barley; Beans,
dry; Beans, green; Berries Nes; Blueberries; Brazil nuts, with shell; Broad beans, horse
beans, dry; Buckwheat; Cabbages and other brassicas; Canary seed; Carobs; Carrots and
turnips; Cashew nuts, with shell; Cashewapple; Cassava; Castor oil seed; Cauliflowers
and broccoli; Cereals, nes; Cherries; Chestnuts; Chick peas; Chicory roots; Chillies and
peppers, dry; Chillies and peppers, green; Cinnamon (canella); Citrus fruit, nes; Cloves;
Cocoa beans; Coconuts; Coffee, green; Coir; Cottonseed; Cow peas, dry; Cranberries;
Cucumbers and gherkins; Currants; Dates; Eggplants (aubergines); Fibre Crops Nes;
Figs; Fonio; Fruit Fresh Nes; Fruit, tropical fresh nes; Garlic; Ginger; Gooseberries;
Grapefruit (inc. pomelos); Grapes; Groundnuts, with shell; Gums Natural; Hazelnuts,
with shell; Hempseed; Hops; Jute; Kapok Fibre; Kapokseed in Shell; Karite Nuts
(Sheanuts); Kiwi fruit; Kolanuts; Leguminous vegetables, nes; Lemons and limes;
Lentils; Lettuce and chicory; Linseed; Lupins; Maize; Maize, green; Mangoes,
mangosteens, guavas; Manila Fibre (Abaca); Maté; Millet; Mixed grain; Mushrooms and
truffles; Mustard seed; Natural rubber; Nutmeg, mace and cardamoms; Nuts, nes; Oats;
Oilseeds, Nes; Okra; Olives; Onions (inc. shallots), green; Onions, dry; Oranges; Other
Bastfibres; Other melons (inc.cantaloupes); Oil Palm Fruit; Papayas; Peaches and
nestarines; Pears; Peas, dry; Peas, green; Pepper (Piper spp.); Peppermint; Persimmons;
Pigeon peas; Pineapples; Pistachios; Plantains; Plums and sloes; Popcorn; Poppy seed;
Potatoes; Pulses, nes; Pumpkins, squash and gourds; Pyrethrum,Dried; Quinces; Quinoa;
Ramie; Rapeseed; Raspberries; Rice, paddy; Roots and Tubers, nes; Rye; Safflower seed;
Sesame seed; Sisal; Sorghum; Sour cherries; Soybeans; Spices, nes; Spinach; Stone fruit,
nes; Strawberries; String beans; Sugar beet; Sugar cane; Sugar crops, nes; Sugar Refined;
Sunflower seed; Sweet potatoes; Tangerines, mandarins, clem.; Taro (cocoyam); Tea;
Tobacco, unmanufactured; Tomatoes; Triticale; Tung Nuts; Vanilla; Vegetables fresh
nes; Vetches; Walnuts, with shell; Watermelons; Wheat; Yams; Yautia (cocoyam);
Animal
products
Pig meat; Beef and Buffalo Meat; Eggs Primary; Milk,Total; Poultry Meat; Sheep and
Goat Meat
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7
Table S4. Primary crops and countries included in calculations on global land savings and attainable 72
yields (Figure 4). 73
Crops Cotton, Groundnut, Maize, Millet, Oil palm, Potato, Rapeseed, Rice, Rye, Sorghum,
Soybean, Sunflower, Wheat
Countries Afghanistan, Angola, Albania, United Arab Emirates, Argentina, Armenia, Australia,
Austria, Azerbaijan , Barbados, Burundi, Benin, Burkina Faso, Bangladesh, Bulgaria,
Bahrain, Bosnia and Herzegovina, Belarus, Bhutan, Bolivia (Plurinational State of),
Brazil, Brunei Darussalam, Belize, Canada, Switzerland, Chile, China, Côte d'Ivoire,
Cameroon, Congo, Colombia, Costa Rica, Cuba, Cyprus, Czech Republic, Germany,
Dominica, Denmark, Algeria, Ecuador, Egypt, El Salvador, Eritrea, Spain, Estonia,
Ethiopia, Finland, Fiji, France, Gabon, United Kingdom, Georgia, Ghana, Guinea,
Gambia, Greece, Grenada, Guatemala, Guyana, Honduras, Croatia, Hungary, Indonesia,
India, Ireland, Iran (Islamic Republic of), Iraq, Iceland, Israel, Italy, Jamaica, Jordan,
Japan, Kazakhstan, Kenya, Kyrgyzstan, Cambodia, Saint Kitts and Nevis, Republic of
Korea, Kuwait, Lebanon, Libya, Sri Lanka, Lithuania, Luxembourg, Latvia, Morocco,
Republic of Moldova, Madagascar, Maldives, Mexico, Marshall Islands, The former
Yugoslav Republic of Macedonia, Mali, Malta, Myanmar, Mongolia, Mozambique,
Mauritius, Malawi, Malaysia, Namibia, New Caledonia, Niger, Nigeria, Nicaragua,
Netherlands, Norway, Nepal, New Zealand, Oman, Pakistan, Panama, Peru, Philippines,
Papua New Guinea, Poland, Portugal, Paraguay, French Polynesia, Qatar, Romania,
Russian Federation, Rwanda, Saudi Arabia, Sudan, Senegal, Singapore, Serbia and
Montenegro, Suriname, Slovakia, Slovenia, Sweden, Seychelles, Syrian Arab Republic,
Togo, Thailand, Tajikistan, Tonga, Trinidad and Tobago, Tunisia, Turkey, United
Republic of Tanzania, Uganda, Ukraine, Uruguay, United States of America, Venezuela
(Bolivarian Republic of), Viet Nam, Samoa, Yemen, South Africa, Democratic Republic
of the Congo, Zambia, Zimbabwe
74
8
Table S5. Global trends in crop production and the amounts of crop products associated with 75
international, inter- and intraregional trade. Values are 3-year means around the respective year. Note 76
that crop products related to trade are given in primary equivalents to establish a consistent account. 77 Crop Products annual changes rates
1987 1997 2008 ‘87 – ‘97 ‘97 – ‘08 ‘87 - ‘08
Global crop production [Mt dm/y] 2492 2992 3737 1.8% 2.0% 1.9%
for domestic use 2113 2495 3013 1.7% 1.7% 1.7%
for export 379 498 724 2.8% 3.5% 3.1%
Interregional trade1 312 371 571 1.7% 4.0% 2.9%
Intraregional trade1 66 127 153 6.7% 1.7% 4.0%
Global population [Mio capita] 5030 5887 6740 1.6% 1.2% 1.4%
1 discerning 11 world regions (see method section) 78
9
Availability of land suitable for cropping vs. land demand in the counterfactuals 79
Figure S4 replicates the results presented in Figure 4, splitting up the total cropland demand in each of the 80
four cases into areas that are considered suitable for agriculture and areas outside the respective suitability 81
definition. We compared national level area demand in the respective case to national level estimates of 82
land suitable for cropping. Figure S4a uses data from the most recent Global Agro-Ecological Zones 83
assessment [7], Figure S4b data from Ramankutty et al. [8]. This calculation indicates that maintaining 84
consumption levels based on domestically available croplands without trade may be difficult or at least 85
costly by requiring the use of a considerably larger fraction of land deemed less suitable for cropping than 86
under current trade patterns. These results stress the hypothetical nature of the assumption of the same 87
consumption levels in the no-trade counterfactuals. 88
89
90 Figure S4. cropland area exceeding (dark segments) and within (light segments) estimates on national 91
level availability of lands suitable for cropping. Suitable lands defined as (a) classes good, high and very 92
high for cereals cultivation with high inputs according to the Global Agro-Ecological Zones assessment 93
[7] and (b) lands where the index of land suitable for cultivation from Ramankutty et al. [8] exceeds 0.5. 94
0
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current situation(2000)
attainable yieldsno trade
attainable yieldswith trade
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current situation(2000)
attainable yieldsno trade
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Limitations, uncertainties and comparison to similar studies 95
The calculations are based on the most complete dataset available offering a consistent account of 96
agricultural production and trade flows [1]. We assess national consumption levels through these data, 97
considering detailed bilateral trade linkages in biophysical units. Our results account for the annual 98
cropland area harvested. The actual cropland requirement will differ depending on prevailing cropping 99
frequencies: it will be lower in systems where multi-cropping practices prevail and higher where fallows 100
from an integral part of the cropping system. This could be accounted for by linking our results to 101
consistent, country and crop specific data on cropping frequencies. Such a dataset is, however, currently 102
not available at the global level [9]. 103
104
In our assessment we focus on global cropland areas and the importance of international trade for this land 105
use category. Grazing lands / pastures cover considerably larger land areas at the global level [1,10]. Our 106
sole focus on cropland was motivated by their central position for food supply (see introduction section of 107
the main text). Additionally, linking grazing lands to consumed products requires fundamentally different 108
considerations and assumptions because, among others, this land use type includes lands of greatly 109
varying quality, productivity and levels of human interference. For instance, the link between productivity 110
and harvests is much weaker than on croplands [11]. 111
112
Our account also excludes areas planted to fodder crops such as alfalfa or clover, as FAOSTAT data for 113
these crops are sketchy and inconsistent. According to FAOSTAT data these lands made up 10% of the 114
total harvested cropland area in 2007, with more than half of this area made by the crop “pumpkins for 115
fodder” (which further questions the reliability of these data). Additionally, it is not clear if some of these 116
lands should be considered grasslands (see http://www.fao.org/es/faodef/fdef11e.htm). With regards to the 117
considered cropland products embodied as feed in traded animal products we find that their share in 118
overall export production increased from 16% in 1986 to 23% in 2007 in terms of dry matter crop 119
products. This share is considerably lower than the share of cropland linked to the production of animal 120
products which was more than one third of total area harvested throughout the study period [12], 121
indicating that trade in animal products is comparably less relevant than trade in vegetable products in this 122
respect. However, according to these figures this relevance increased considerably in just two decades. 123
Additionally, traded vegetal products are often used as livestock feed in receiving countries. Separating 124
food from feed based on the presented dataset would require additional analyses and assumptions. 125
126
Our results on croplands related to international trade are very consistent with the results of a study using 127
a similar methodology [13]. A comparison of the results for the 12 nations covered in that study provided 128
a very good match. The overall share of global cropland area associated with international trade (Table 1) 129
is in the same range as the corresponding value in a recent study that places it at 22% in 2004 [14]; our 130
value for this year is 19%. Another recent [15] study places this share at 29% in 2007, compared to our 131
value of 22% for that year. The fact that our values are lower than the ones in those studies was expected, 132
due to different definitions of consumption (see e.g. [16]). However, the results of these studies are not 133
directly comparable to ours due to different underlying methods: one study [14] does not account for yield 134
differences between sending and receiving regions, both [14,15] use very different crop aggregation levels 135
compared to our study and present results based on a multiregional input–output model relying on 136
monetary trade data. Our results (see SI dataset) are in line with recent studies (e.g., [17,18]) showing that 137
a large number of importing countries depends a relatively small number of large exporters. Another study 138
[19] quantified to what extent trade in agricultural products lowers global crop demand. Their result is in 139
line with ours (41 Mha vs. 72 Mha average for the period 1998 to 2002, respectively). However, 140
differences in underlying methodology (for instance, use of modelled crop yields vs. the use of reported 141
crop yields) and coverage ([19] include “only” 53% of the global cropland area and “only” primary crop 142
products) hamper more detailed comparisons. 143
144
Comparing our time series results to similar work on different resources shows the following picture with 145
regard to the importance of international trade at the global level: Peters et al. [20] show that CO2 146
11
emissions associated with the production of internationally traded goods grew from 20% of global total 147
emissions in 1990 to 26% by 2007. Our values, 14% and 22% for the respective years, reveal that the level 148
of cropland associated with international trade was lower but the growth in the relevance of trade was 149
faster than for CO2 emissions. The growth rates of the absolute values were very similar, with “traded” 150
CO2 emissions growing from 4.3 Gt CO2 in 1990 to 7.6 Gt CO2 by 2007 (growth by 76% of the 1990 151
value) and “traded” cropland areas growing from 158 Mha in 1990 to 276 Mha by 2007 (growth by 74% 152
of the 1990 value). These numbers also show that net growth in CO2 emissions directly linked to domestic 153
demand were considerable steeper than the almost stable value we found for croplands (Table 2 in the 154
main text). 155
156
With regards to studies on virtual water trade, to our knowledge, no comparable time series results exist at 157
the global level. A recent study [21], shows that interregional trade in virtual water grew from 1986 to 158
2007 by 119% of the 1986 level. For our result on cropland area, the corresponding value was 68%. 159
However, the results are not directly comparable as Dalin et al. [21] consider trade of 58 commodities, 160
compared to over 450 in our study. Additionally, they distinguish 6 world regions for their assessment of 161
interregional trade, compared to the 11 world regions discerned in our study. Another recent study [22] 162
provides a comprehensive static assessment of virtual water trade: this study places the value of water 163
footprint for export production at 19% of the global total (average value for the period 1996 to 2005). This 164
corresponds very well with the value of 18% average that we find for cropland for the same period. 165
166
References 167 [1] FAO 2013 FAOSTAT statistical database 168
[2] UN Statistics Division 2010 UN Comtrade, http://comtrade.un.org/ 169
[3] Gehlhar M 1996 Reconciling bilateral trade data for use in GTAP GTAP Tech. Pap. 10 170
[4] Kastner T, Kastner M and Nonhebel S 2011 Tracing distant environmental impacts of agricultural 171
products from a consumer perspective Ecol. Econ. 70 1032–40 172
[5] Bouwman A F, Van der Hoek K W, Eickhout B and Soenario I 2005 Exploring changes in world 173
ruminant production systems Agric. Syst. 84 121–53 174
[6] Smil V 2002 Worldwide transformation of diets, burdens of meat production and opportunities for 175
novel food proteins Enzyme Microb. Technol. 30 305–11 176
[7] FAO/IIASA 2010 Global Agro-ecological Zones (GAEZ v3.0) (Rome, Italy and Laxenburg, 177
Austria: FAO and IIASA) 178
[8] Ramankutty N, Foley J A, Norman J and McSweeney K 2002 The global distribution of cultivable 179
lands: current patterns and sensitivity to possible climate change Glob. Ecol. Biogeogr. 11 377–92 180
[9] Ray D K and Foley J A 2013 Increasing global crop harvest frequency: recent trends and future 181
directions Environ. Res. Lett. 8 044041 182
[10] Erb K-H, Gaube V, Krausmann F, Plutzar C, Bondeau A and Haberl H 2007 A comprehensive 183
global 5 min resolution land-use data set for the year 2000 consistent with national census data J. 184
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