1

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

3

4

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

8

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

13

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

26

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

31

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

34

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

2

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

3

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

58

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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

4

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

38

11

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5

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

6

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

71

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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1000

current yieldsno trade

current situation(2000)

attainable yieldsno trade

attainable yieldswith trade

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1000

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current situation(2000)

attainable yieldsno trade

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10

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

Land Use Sci. 2 191–224 185

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