Urbanization and food systems

vorgelegt von
Dipl.-Kfm., M.Sc.
Christopher Bren d ’A mour
geb. in Bonn

von der Fakultä t VI – Plane n Bauen U mwelt
der Technisch en Universitä t Berlin
zu Erlang ung des akade mischen Grades

Doktor der Na turwissensch aften
- Dr . rer. n at . –

genehmigte Di ssertation

Promotionsau sschuss :
Vorsitzende: Prof. Dr. Eva Paton
Gutachter: Prof. Dr. Felix Cr eutzig
Gutachter: Prof. Dr. Ott mar Edenh ofer
Gutachter: Prof. Dr. Jan Minx
Gutachter: PD Dr. Daniel Müller

Tag der wissenschaf tlichen Ausspr ache: 14.03. 2018

Berlin 2018

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Abstr act
Food systems a re shaped by global change. Clima te c hange adversely affects yields and alread y strained
resources necessar y for food producti on. Economic and demographic developm ent influence consum er
pr eferences and create unprecedent ed demands, trans forming the entire food value chain. Understandin g
how gl obal chang e d rivers are in fluencing food syste ms is essential in finding solutions for sustainabl y
providing f ood for nine billion pe ople.
Urbanization is one of these defining drivers of fo od system transitions. Yet, its effec ts have not been
sufficiently explored. This dissertati o n contributes to a bette r understanding of the role of urb anizati o n by
investigating the implications o f two dimensions o f ur baniz ation on two di mensions of the food system :
the spatial dimension and urban living on the o ne hand, and the food production and food consumpti on
activities on the other hand. Specificall y, it address es tw o overarching r esearch qu estions in two separ ate
parts: (i) How is urban area expansi on affecting food producti on activities? (ii) How is urbanization and
associated urban living affecting food consump tio n pa tterns?
The first part o f this dissertation addresses the first question and analyzes the imp lications o f the spatial
dimension o f urbanization on food producti o n activities. Chapter 2 sets the s tage with a compreh ensive
assessment of the extent and density of multiple drivers and impacts of land use change . It reveals
significant co-occurrenc es of expanding human activities and pervasive pressure on biodiversity. Further,
it highlights the need for a m ore detailed understan di ng of competin g land use dynamic s driv en b y human
activities. Chapter 3 ex ami nes the implica tions of urban areas expansion o n croplands at the global lev el.
It shows that while global cro pland losses a re margin al, they are very relevant in some of the rapidly
urbaniz ing regions o f Afric a and Asia. It also finds that the croplands surrounding urban areas are almost
twice as producti ve as the remaining croplands. The implications at the lo cal level are fa r-reaching ,
affecting liveliho o ds and ul timately food secur ity . In this context, some coun tries are likely to lose their
food self-suffi ciency. Chapter 4 supplements the earlier f inding s and explores the risks associa ted with
high import depend encies o n key staple crops for developing countries. It investigates how high
dependency on food imp o rts c o uld potential ly affec t the calori e supply in developing countries.
The second part of the diss ertation investigat es the second question and explores how urbanizatio n and
associated urban living is affecting food co nsu mption patterns. Chapter 5 analyzes the empirica l
relationships b etwe en urba n develop ment and pa ckaged food, processed food, a nd food away from home
consumption at different spatial scales . The analysis reveals that the level o f urban development affects
the consu m ption o f packaged foods at the country level. Further, it shows variations in processed food
and foo d away from h ome consumption at differen t levels of urban development within India. While
income is still the most important driver for chan gin g food consumpti o n, the findin gs also identify a
significant urb an effect on diets.
The conclud ing chapter 6 discusses the broader implications and significance o f the findin gs o f thi s
dissertation. In particular, it is discussed how the finding s affect f oo d system o utcom es, namely food
security and liv elihoods. Chapter 6 also highlig hts potential av enues for futur e research.

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Zu sammen fassung
Das Ernährung ssystem wird fundamental vo n den Veränderung spro z essen des globalen Wandels
beeinflusst. Der Klimawandel etwa hat negative Folgen für die weltweiten Ernteerträge und wirkt sich
bereits jetzt auf dringend b enö tigte R essourcen zur Na hrungsmittelpr o dukti o n aus. Die wirtschaftlich e und
demographisch e Entwicklu ng beeinflusst das Konsumverhalt en der Menschen und sorgt f ür eine rasant
steigende Nachfrag e nach L ebens mitteln. Es ist essentiell zu verstehen, wie die Treiber der globale n
Veränderung das Ernährungssystem be einflussen, um Lö sungen für eine nac hhaltige Versorgung mit
Lebensmitteln für neun Milli arden Menschen zu finde n.
Einer der wichtigsten Treib er hinter d em gl obal en Wa ndel ist d ie Urban isierung. Bisher sind deren Effekte
auf Ernährungssysteme noch nicht hin reichend erforscht. D iese Dissertation leistet einen Bei trag zu m
besseren Verständ nis der Rolle der Urbanisierun g, indem sie die Auswirkungen vo n zw ei Aspekten der
Urbanisierun g auf zwei Aspekte des Ernährungssyste m s untersucht: die räumliche Dimensi on und das
urbane Leben au f der ein en und die Nahrun gsmittelp roduktion und d er Nahru ng smittelverbr auch auf der
anderen Seite. Zwei umfassend e Forschungsfrag en werden in jeweils eine m Teil der Dissertati on
bearbeitet. Die erste Frage lautet, wie die räu mliche Expansion der urbanen Gebiete die
Nahrun gsmittelprodukti on beeinflu sst. Die zweit e Frag e ist, wie sich die Urbanisi erung und das dami t
verbundene urban e Leb en auf die Essge wohnheiten auswirken .
Der erste Teil der D isserta tion befasst sich mit der ersten Frage. Mit einer umfangreich en räumlichen
Analyse der Intensitäten versch iedener L andnu tzungsdyna miken schafft Kapitel z wei die Vorauss etzungen
dafür. Es zeigt insbes ondere Zusa m menhänge zwisch en dem sich ausdehnend en mensc hlich en Handeln
und dem allgegenwärtigen D ruck auf die Biodiversität. D es Weiteren unterstreich t es die Notwendig ke i t
eines besseren Verständ nisses der konkurrierend en Landnutzun gsdynamiken, die aus menschliche m
Handeln resultieren. Kapitel drei untersucht die Auswirkun gen der Expansi o n urbaner Gebiete auf
Ackerflächen in einem globalen Zusammenh ang. Es wird deutlich, dass die Verlus te an Ackerfl ächen zw ar
global ges ehen m arginal sind. Gleichzeitig sind sie aber sehr pr oduktiv und b eso nd ers rele vant in R egionen
mit schnell expandierenden urbanen Gebieten in Asien und Afrika. Die Auswir kungen sind auf lo kaler
Ebene weitreichend und betreff en die Lebensgrundlag e und letztlich die Nahr ungsmittelsi cherheit. In
diesem Zusam m enhang ist es wahrscheinlich, dass einige Länder sich in Zukunft nicht mehr ausr eichend
selber m it Lebensmitteln versorgen können. Kapit el vier ergänzt die bisherigen Erkenn tnisse und
beleuchtet die Ri siken von Impor tabhängigkeiten f ür Entwicklu ngsländer. Es wird geprüft, wie hohe
Abh ängigkeiten von Nahru ngsmittelimp orten im Falle von Angebotssch o cks m öglicher weise die
Kalorienvers orgung in d iesen Ländern be einflussen könnte.
Der zweite Teil der Dissertation untersucht die zweite Frage – wie sich die Urbanisierun g und damit
verbunden das urbane Leben auf die Gewohnheit en d es Nahrungsmit te lkonsu ms auswirken. Kapitel f ünf
analysiert die empirisch en Zusammenhänge zwisch en urbaner Entwicklun g und verpackten
Lebensmitteln , verarbeitet en Lebensmitteln und dem Ko nsu m von Lebens m ittel n außerhalb der eige nen
vier Wände auf verschie denen räumlichen Skalen. Die Analyse zeigt, dass das L evel der urbanen
Entwicklung den Konsum von verpackten Lebensmitteln auf dem L and beeinflu sst. Außerdem wird
deutlich, dass es auf versch iedenen Ebenen der urba nen Entwicklung in Indien Variationen des Konsu m s
von verarbeit eten Lebensmitteln und des Ko nsu m s von Lebens mitteln außer Haus gibt. Während das
Einkommen immer noch d er wichtig ste Treiber fü r veränderte Essgewohnh eiten ist, zeigen die Ergebnisse
auch einen signifi kanten urb anen Einfluss auf di e Ernä hrung.

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Das abschl ie ßende Kapitel sechs disku tiert die breiteren Auswirkun gen und die Sig nifikanz der
vorliegenden Di sserta tio n. Besonderes Augenmerk lieg t dabei auf der D iskussi on, wie die Ergebnisse die
Literatur zu Nahru ngsmittelsystem en unter dem Einfluss des globalen Wandels komplementiert. Kapitel
sechs beleuch tet außerde m mögliche Wege für weitere F orschungsv orhaben.

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Contents

Abstract ............................................................................................................................................. ii
Zusammenfa ssung ............................................................................................................................. iv
1. Introduc tion ................................................................................................................................... 1
1.1. Background: food systems, food s ecurity, and urbaniz ation ............................................................. 2
1.1.1. Food syste m tran sitions .............................................................................................................. 2
1.1.2. Food syste m s an d food security un der gl obal chan ge ............................................................... 4
1.2. Linkages b et ween f ood sy ste m s and urban ization ............................................................................ 6
1.3 Thesis objec tives and outlin e ................................................................ .............................................. 8
PART I .............................................................................................................................................. 14
2. Assessing hu man and en v ironmen tal pressures of global lan d-use change 2000-2010 .................... 15
2.1. Introducti o n ..................................................................................................................................... 18
2.2. Results .............................................................................................................................................. 19
2.3. Discussi on and conclu sion ............................................................................................................... 34
2.4. Methods ........................................................................................................................................... 35
2.4.1. Data and data pr ocessin g ......................................................................................................... 35
2.4.2. Intensit y cur ves ................................ ......................................................................................... 38
2.4.3. Intensit y change ........................................................................................................................ 38
2.4.4. Principle Component Analysis .................................................................................................. 38
2.4.5. Land e mbodied in cr o p trade ................................................................................................... 39
2.5 Supple mentary Inf o rmation .............................................................................................................. 48
2.5.1. Figures ....................................................................................................................................... 50
2.5.2. Tables ........................................................................................................................................ 54
2.5.3. Supple mentary Inf o rmati o n text .............................................................................................. 67
3. Future urba n land expansion and implications for global croplan ds ............................................... 89
3.1. Statement o f sign ificance ................................................................................................................. 92
3.2. Introducti o n ..................................................................................................................................... 92
3.3. Results .............................................................................................................................................. 93
3.4. Discussi on ......................................................................................................................................... 98
3.4.1. Compensa ting Cropland Loss ................................................................................................... 98
3.4.2. Food Sys tem Transition ............................................................................................................ 99
3.4.3. Liveliho o ds and F o od Security .................................................................................................. 99
3.4.4. Governanc e ............................................................................................................................. 10 0
3.5. Conclusion ...................................................................................................................................... 100
3.6. Materials an d Methods .................................................................................................................. 10 1
3.7. Supple mentary Infor mation ........................................................................................................... 106
4. Telecon nected foo d supply sho c ks .............................................................................................. 117
4.1. Introducti o n ................................................................................................................................... 12 0
4.2. Methods ......................................................................................................................................... 121

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4.3. Results ............................................................................................................................................ 123
4.3.1. Countri es vulnerable due t o large caloric trad e deficits ........................................................ 123
4.3.2. Trade d ep endencies ............................................................................................................... 125
4.3.3. Continu o us vuln erability mapp ing for specifi c tr ade shock scenarios ................................... 12 6
4.4. Discussi on ....................................................................................................................................... 128
4.5 Conclusi o n ....................................................................................................................................... 131
4.6. Supple mentary Infor mation ........................................................................................................... 136
PART II ........................................................................................................................................... 145
5. Urban tran sitions and diets ................................................................................................ ......... 147
5.1. Introducti o n ................................................................................................................................... 14 9
5.2. Urbanizati o n and pack aged food c onsumption ............................................................................. 1 50
5.3. Lessons fr om India ................................................................ ......................................................... 1 52
5.4. Discussi on ....................................................................................................................................... 157
5.5. Conclusion ...................................................................................................................................... 159
5.6. Supple mentary Infor mation ........................................................................................................... 163
6. Synthesi s and o utlook ................................................................................................................. 167
6.1. The spatial dime nsi on of urbaniz atio n ........................................................................................... 167
6.2. Urban li ving .................................................................................................................................... 16 9
6.3. Discussi on ....................................................................................................................................... 170
6.4. Policy r elevance and implicati o ns ................................................................................................ .. 174
6.5. Outlook and fu ture research .......................................................................................................... 176
Acknowledgemen ts ........................................................................................................................ 183
Statemen t of contribu tion .............................................................................................................. 185
Tools and re sources ................................ ........................................................................................ 186
List of pub lications ......................................................................................................................... 187

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Chapter 1

1. Intr oduction
Food syste ms are responsi ble fo r achieving food and nutrition securi ty across the developing world in a
sustainable way. By 2050, world food supply will need to increase by 60% compar ed to 2005 level s
(Alexandrat os and Bruins m a, 201 2). The increasing de mand from a rapidly g ro wing population wi th
changing preferences is only one aspect that makes providing enough food a major challenge. Climat e
change, for example, will have vast impac ts on food produ ction capabilities (Port er et al., 2014). Average
yields w ill decreas e with risin g mean t emperatures (Lob ell et al., 2013; L o bell and Field, 2 007); heat waves
will lead to mo re variability in yields and hence o utp ut. These effects will not be distributed equally :
emerging and de veloping r egions will be m ore e xposed to thes e devel o p ments (Lobell et al., 2008; Porter
et al., 2014 ) .
Providing en ough calories t o tackle undernutriti o n and hu nger is only one part of the solu tion. Malnutriti on
in general is becoming an issue of great concern (Global Panel o n Agriculture and Fo od Syst ems fo r
Nutrition, 2017). While malnutrition is often associated with undernutriti on, it mostly means poor
nutrition (Ingram, 2017), or lack of proper and health y nutrition. Food and nutriti on security are inherentl y
connected. Both are important components o f the sustainable develop m ent agenda. Specificall y, the
Sustainable Developmen t Goal (SD G) number 2 explicitly aims at eradi cating hunger and all for ms o f
malnutriti on by 2030 (United Nations, 2015). It will require tremendous efforts and a more detaile d
understandin g o f how gl o b al change dyna m ics are aff ecting food syste m s.
The influence of urbaniza tion is still no t we ll understood (Seto and Raman kutty, 2016). Cities are
predominan t engines of wealth creation (Bettencou rt et al., 20 07; Grubler et al., 2 012) and, more
importantly, hot spots of consumption (Creutzig et al. , 2015; Set o et al., 2014). The mul tiple dimensi o ns of
urbaniz ation – including the share of people livin g in urban areas, the expansi on o f built environ m ents,
and the associated urban way of living – are driving environmen tal change (Grimm et al., 2008) . In this
context, urbanizati o n is also fundamentally affecting food systems (FAO, 2011). Rapid urbaniz ation is
forecast to take pla ce in devel oping regions of Sub-Sah aran Africa and Asia (Unite d Nations, 2014), regions
that are prone to food and nutrition insecurit y (FAO, IFAD and WFP, 2016). Understanding how
urbaniz ation influences food production activities and how urbanization and associated urban living is
affecting food consumpti on patterns would all o w for mo re inf ormed and targete d policies.
The remainder of this chapter provides background inform ation on the curr ent stat us o f research on
transforming food systems, and details the structure of this dissertati o n. Part 1 describes the nature of i)
food syste ms activi ties and ii) food syste ms o utco mes. Part 2 establish es how urba nization is affectin g
food system activities, and discusses the need for a m ore detail ed understandin g of the implications of
urban area expansion and urban food co nsu m pti on patterns. Part 3 introduc es the guiding rese arch
questions and outlines the structure of the diss ertatio n.

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1.1. Backgroun d: food sys tems, food secur ity , and ur banization
This section provides a brief overview over concepts used in this dissertati o n and the status quo of
research o n food systems under global change. It uses a framework to describe the concepts o f food
systems and fo o d s ecurity and the in teractions with global cha nge driv ers, pro vidin g an o verview over the
literature and approach es to analyz e food securi ty.

1.1.1. Food system tr ansition s
Food systems can be de fined as “ the chain of activities connecting food production, processing ,
distribution, consumption , and waste management, as well as all the associated regulatory institution s an d
activities ” (Pothukuchi and Kaufman, 2000). All these activities are shap ed by g lobal change dynamics.
Economic growth and rising incomes, for example, are changing co nsu m er preferences towards a
“ weste rnization of diets ” in the dev elopin g world, away fro m basic staples toward s more proc esse d foods
and animal based pr oducts (Pingali, 2007). This has impor tant implications for reso urce use (Erb et al.,
2016; Kastner et al., 2012; Tilman and Clark, 2014) an d public health (Po pkin, 2001, 1994). In parallel, a
rapid proliferation of modern food retail outlets is observed, transfor m i ng the retail sector of developing
economies (Reard on et al., 2012, 2003). These transf ormations ha v e far-reaching consequences be yond
the immedia te food systems activities, for exampl e for social welfare in terms of income generation and
employment , health, and ultimately food security. They are generally interlinked and o ccur as the overall
structure of the f oo d sys tem of an economy moderniz es (Reardon and Tim mer, 2014).
To facili tate the understandin g of food systems an d the comple x interacti ons with global chang e, Ericksen
(2008) devel oped a food sy stems frame work for envir onmental change research, which includes feedbacks
and interacti ons with drive rs, and considers multiple outcomes. Central to this framewor k is the noti on
that the primary outc o me of any generi c food syste m is food security. It further builds upon the idea that
within co m plex systems, it is possible to identif y key processes as we ll as determinants that affect the
outcomes. Here, I use a slightly adjusted versi on o f this Global Enviro nmental Chan ge and Food Syste ms
framework (GECAFS, based on Ingram (2011), Figure 1) to describe the co nc ept of food syst ems activi ties
and outcomes, and the interactions wi th global change drive rs.
In this framework, food systems activities are grouped i nto four components : produci ng food , processing
& packaging , distribution & retail , and consuming (Figure 1 ). The produci ng activities include all activi ties
involved in the producti o n o f raw food materials, and include inputs such as natural resources. Factors
such as climate change determine the se activities. Pr oce ssing & packaging includes all activities that
process the ra w materials and ad d valu e in the econo mic s ense. D eter m inants in clude, for example, trade
organizations that set stand ards. D istribution & retailing includes all activi ties that move the product s from
one place to another , as well as getting the products to the consumer. In frastruc ture is a key determinant
in this co ntex t. Consumi ng includes everything fr om deciding what to eat to the preparing and
consumption of meals. Ad vertising is an ex a mple of a determinant of consump tion.

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Figure 1 – Food system acti vities, outcomes, and drivers. Adju sted G lobal Environ mental Change and Food Systems
(GECAFS) frame work, based o n Ericksen (2008) an d Ingram (2011).
These acti vities will have different o utco mes, grouped into three components: social , food security , and
environmental (Figure 1). Social outcomes relate to how th ese activities are affecting emplo yment and
income of p eople that wor k along the food value chain . Food security outcomes are the pri mary outcomes
of food systems. They will be discussed in detail in the next section. Environm ental outcomes includ e
natural capital and ecosystem services that are i mpacted, for example by f arming activities. It is important
to note that social and environmental outcomes are both o utcomes of food system activities, but a ls o
determinants of food security. For example, a higher income of a household as outcome of employ ment
in food pr o cessing will al so determine its food securi ty by increa sing the accessib il ity of f o od. At the same
time, marginaliz ation of small shop owners due to the super market revolution might have a negativ e
outcome in t erms of li v elih o ods, which will also affect the acc essibility of food.
Global change dynamics drive these fo od syst ems acti vities and subsequently outcomes. The i mpacts o f
these dri v ers can be expl ored in isolation or interac tin g with other driver s and determinants. To reduce
the complexit y, they can a lso be further broken dow n. For example, r esearchi ng the i mpacts of climat e
change on producti o n activi ties could be don e o nly con sidering the effects o f incre asing m ean temperatur e
on yields, without accoun ting for increasing climati c variability. A more holistic approach wo uld also
consider the CO 2 -fertilizer- effect tha t arises with incr easing CO 2 -levels in the atmosph ere and can have a
po sitive effect o n yields (Smith et al., 2014). Since ag ricultural activities contrib ute significantl y to GHG -

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emissions (Smith et al., 2 0 14), largel y due to the emission of meth ane v ia enteric fermentati o n, this would
also constitute an environmental feedbac k fr om food system acti v ities t o the glob al change drive rs.
This v ersion of the frame work regards both f ood syst em activiti es and outcomes as part of th e ‘overall’
food syst em (grey box, Figure 1), a slight abstraction from the definition introdu ced earli er in this section
that only in cludes the activi ties. Further, it groups different global change drivers that were put separately
in the original framework (e.g. socio-economic drivers & global envir o nmental chang e drivers) in one box
under the heading global change driver s . Additionall y, the po tential feedbacks are grouped together. All
of this is d one to reduce the complexity for the pur pose of this diss ertation. The overall validity of the
framework is unaff ected.

1.1.2. Food system s and f ood security und er glo b al change
Food s ecurity is c o nsider ed as the p rincipal outcome of food syste ms (Ericksen, 2008). It is achieved when
“ all people, at all times, have physica l and economic access to sufficient, safe and nutritious food to meet
their dietary needs and food preferences for an active and healthy life ” (FAO, 1996). Generally, food
security has three dimensi o ns: availability, accessibil ity, and utilization. Follo wing the GE CAFS framework
presented in Figure 1, availab ility refers to elements su ch as the production (how much is availab le through
local production?), and exchang e (how much is obtained via trade rather than local producti on?).
Accessibilit y conc erns the monetary aff o rdability and allocation o f food items ( where and h ow can food
be access ed by consumers?). Utilization contains nutritional value o f the food as well as food safety
concerns. By definition, nutrition security is hence a comp o nent o f food security. Ach ieving food securi ty
requires a de tailed unders tanding of all of these co mponents.
A range of approaches for achieving food security exists, each focusing on different aspects (Burchi and
De Muro, 2016). However, m uch of the debate about food security and correspondin g research has been
centered on aspects of fo od production (Burchi and D e Muro, 2016; Ingram, 2017, 2011) . The basic
concept of increasing production to meet increasin g demand, the ‘ productionis t approach ’, has been the
reference approach for the internati onal community . For much of the twentie th century, food securit y
was seen as a matter of aggregate per capita food supply. This changed with the World Food Summit 1996
and the subsequent introduction of the commonly used definition of food security intr o duced earlier in
this section. The notion o f accessibilit y was pu t at the center stage, acknowled ging that the inabilit y to
access food was and is to this day the main reason for food insecurity (Ingram, 2011). The emphasis
changed from increasing production to increasing accessibility. The definiti on also encompassed t h e
notions of availability in a broader sense (not just production but also exchange and distribution) and
utilization.
Much of the research o n food securit y under glob al change still centers on issues rela te d to food
production (Garnett, 2016). Central in this context is the lim it ed av ailabilit y of key resource inputs, most
notably land, which is becoming increasin gly scarce (Creutzig , 20 1 7; Lambin and Meyfr o idt, 2011; S m ith
et al., 2010), but also wate r (Jackson et al., 2007). L a ndmark papers such as Godfray et al (2010) on the
challenge of feeding nine billion people or Foley et al (2011) o n solutions for a cultivated planet, for
example, focus on addressing the unprecedented demands on agricultur e and natural resources. In an
important contribution o n potential lever age p oints to improve food securit y , West et al (2014) explicitly

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focus on how to provide enough calori es to meet the a dditional de mand. Other studies (L icker et al., 2010;
Mueller et al., 2012; van Ittersum et al., 2013) focus o n closing yield gaps, i.e. the gaps between actual
yields and potentially attainab le yields, which wo uld promise additional potential in regions such as Sub -
Saharan Africa (SSA). These contributions analyze how to produce enough food in light o f a range of global
change drivers. While some draw inferences regardin g general food security, they mostly only add ress th e
availability dim ension.
Climate change pos es argu ably the biggest challenge to the p roducti on side of food syste m s. Many studies
are concerned with i m plica tions of climate change on foo d producti on activitie s, discussing how climate
change is affecting yields and yield variability (Asseng et al., 2011; Lobell, 2011 ; Lobell and Field, 2 007;
Parry et al., 2004). According to the IPCC WGII report, the implicatio ns “ are expec ted to be widespread,
complex, geographic ally and tem porally variable ” (Porter et al., 20 14) . The effects will not be distribut ed
equally, with the Souther n hemisphere being more exposed to climate hazards than the Norther n
hemisphere (Lobell et al., 2008; Schlenker and Lobell, 2 010). Since m uch of the po pulati o n growth is
forecast to come from the Southern regions (United Nations, 2012), this raises concerns about
distributional effects. Countries m ight lose their food self-sufficiency. Due to the complex nature of food
system ac tivities and food system outcomes, however, the implications of climate change for food sec urit y
are m uch less clear. The IPCC states that quant ifying the effect of climate change o n food security is “ an
extremely difficult task ”, conclud ing that “ there is [… ] limited direct evidenc e that unambiguously links
climate chang e to impa cts on food security ” ( Porter et al., 2014).
Providing eno ugh food has lo ng been an imp o rtant s trategy t o alle viate food secu rity concerns, and still is
today. H owever, as alread y ind icated, it do es no t suffi ciently capture the comple xity o f fo od securi ty for a
number of reasons. First, it does not address the multidimensionality of t he issue. The availability
dimension is over- emphasiz ed. Successfully assessing food security will require con sidering all dimensi o ns,
as the exa mple of trade highlig hts. In order to mitigate the distribu tional effects, trade will become
increasingly imp ortant as c ountries have t o resort to imports to feed their populations (Erb et al., 2016;
Kastner et al., 2012). Imports will increase the domestic food availability in a co untry, but it will also
increase the co untr y ’s ex p osure to global food shocks, which is concernin g in a “ global food system […]
vulnerable to systemic dis r u ptions ” ( Puma et al., 2015). Sup ply shocks, for exampl e due to severe droughts
in exporting countries, would mostly be mediated by price effects. In such a scenario, assess ing the
implications for fo od security becomes a question of accessibilit y, specifically of “ how do inte rnational
prices transmit to domest ic prices and what does this mean for the most vuln erable parts of the
popula tion ?” (Kalkuhl, 201 4; Ko rnher and Kalkuhl, 2013). Hence, any food security assessment for food
import-depend ent countri es requires a detail ed analysis of issues related to fo od accessibilit y.
Second, pr oviding enough calories does not necess arily achie v e food sec urit y per definition, even if
accessibilit y is not an issue. Malnutrition is becoming a matter of grave co ncern (Global Panel on
Agriculture and Food Syst ems fo r Nutriti o n, 2017; Ingram, 2017). More than two billion people consume
excess calories, and, parad oxically, many of those do no t get enough nutrients (Ng et al., 2014) . This in
turn has important implications fo r public health, raising concerns about obesity and other diet -related
noncommunicab le diseas es (Garnett, 2016; Mendez and Popkin, 2004). To tackle these issues, nutrition
and nutrition security ha ve been put at the center stag e. In 2016, the Unit ed Na tions General Assembly
proclaimed the ‘ Decade of Nutrition ’ as part of the UN Sustainable Develop ment Goals initiati ve (FAO,
2016). The same year, the Global Panel on Agricul ture and Food Systems for Nutrition, comprised of

6

international experts, many of which from rele v ant UN agencies, states that “ food sys tems need to be
repositioned : from feeding people to nourishing people well ” (Gl o bal Panel on Agriculture and Food
Systems for Nutrition, 20 17) . This is also reflected in the 2017 ‘ State of Food Security and Nutrition in the
World ‘ report (FAO, IFAD, UNICEF, WFP and WH O, 2017), published by a consor tium consisting of
numerous UN agencies, includ ing the Fo od and Agriculture Organization of the United Nations (FAO) and
the World Health Organiza tion (WHO). This report is specifically designed to monitor progress toward s
both endin g hunger and all fo rms of malnutrition. To tackle the nutriti on probl em, Ingram ( 2017) propose s
a fo od syste ms appr o ach, which includes “ identifying problems at the consumer end of the supply chain,
and working b ackwards to the producer from there ”. He argu es that this bot tom up approach would allow
for more targ eted policy interv entio n. How ever, thi s wo uld als o require a more detailed understand ing of
what is drivin g consum er preferenc es.

1.2. Lin kages betwe en food systems an d urbaniz ation
Figure 1 shows how gl o bal change dynamics ar e drivin g transitions in food system acti vities and how that
in turn is affecting food system outcomes. This d issert atio n is based o n the hyp o th esis that urban ization is
one of the defining global change drivers shaping food systems. This secti on describ es potential linkag es
between urban ization and food syste m s, and high lights pot ential challeng es.
Urbanization involves chan ges in multiple dimensions . First, a growing percenta ge of people is living in
urban area s (United Nations, 2014): by 2050, 6 . 5 billion peo ple will li ve in cities, equali ng two thirds of the
population. Second, there is a rapid expansion of urban areas (Seto et al., 2011). Urban areas are expect ed
to triple fr om 2000 to 2030 (Seto et al., 2 012), making it the fastest growing land use form . Third, there
are changes in norms and ways of living that are uniq ue to urban areas (Bet te nc ourt and West, 2010). All
of these have implications for food systems. The la tter, for example, affect foo d consumpt ion patterns
towards more resource intensive diets (Popkin, 1999). As Seto and Raman kutty (2016) highligh t,
urbaniz ation is affecting the activities of the food systems in a multitude of ways. Table 1 lists some
examples of how urbaniz ation is tr ansformin g food syste m activiti es.

Table 1 – Imp lications o f ur banization on food system activities. This tab le pro vides a selection of poten tial
implications and is n on- exhaustive.

Global Change
Driver

Producing fo od

Processin g &
packaging of food

Distribut ing &
retailing of foo d

Consuming fo od

Urbanization

Competition f o r
resources (land
and water)
(Bagan and
Yamagata, 2014;
Chen, 2007)

Transformati on of
agro-processing
chain:
marginalization o f
small scale a ctors
(Reardon et al. ,
2014; Reard on
an d Timmer,
2014)

Proliferati o n of
modern retail &
fast-food
restaurants
(Reardon et al. ,
2012; Reard on
and Berdegue,
2002)

Higher
op portunit y cost
of cooking – more
food away fr o m
home
consumption
(Gaiha et al.,
2009; Ma e t al.,
2006)

7

Urbanization and associat ed urban area expansion convert valuable croplands, as confir m ed by case
studies ar ound the world (Ah mad e t al., 2016; Bag an and Yamagata, 2 014; Chen, 2 007). Gi ven that 60% of
the world ’s irrig ated cropla nds lie in the vicini ty of urban areas (Thebo et al., 2014), this is likely to continue
to be a proble m for m an y countries. In arid regions such as Egypt, the c ompetiti on for reso urces is n ot only
limited to land: urban area s and croplands also compete for scarce water res o urces. Th is competition for
biophysical resourc es affects the food producing activities of countries. Howe ver, while there are case
studies highlighting the importance of the issue, ther e are no global estimates of the magnitude of the
effects.
The preference o f urban consum ers for processed fo ods and the different retai l structure in cities ha ve
important impli cations for the processing an d p ackagi ng of f o od. In Indian cities, for e xample, only 17% of
the food co nsu med d oes not underg o any kind of processing (Morisset and Kumar, 2008). These d ynamics
are transforming the food value chains, providing ample non-farm empl o yment along the way (Reardon,
2015).
Urbaniz ation also has major implications for the d istri bution an d retailing of food. Cities pla y an imp o rtant
role in the prolif eration of s upermarkets, other m odern retail options, an d fas t fo od restau rants (Reardon
et al., 2003; Reardon and Berdegue, 2002). Again, this is providing new service sector employment.
However, it might h ave unintended co ns equences , su ch as the marginali zation of sm allh o lder agriculture,
as supermarke ts tend t o so urce from larg er, com m ercial farms.
The transfor mation of the retail sector is inherentl y lin ke d with the urban food consumpti o n patterns.
Different emplo yment stru ctures and an incr easing participation of wome n in the work force lead to higher
opportunity costs of cooking at h ome. This in turn leads to more meals consu med away from home (Gaiha
et al., 2009 ; Ma et al., 2 00 6).
While the effects o n food system activities are comparatively clear, the implications for food sy ste m
outcomes are more complex to assess. Important qu estio ns arise. Fo r example, will the people that are
displaced as urban areas expand fin d access to urban lab or mar kets? Will th ese h ouseholds manage to be
food secure ? Displaced subsistence farmers might los e the ability to feed thems elves, thus becoming net
buyers of food. F o r these h o useh olds, and the urban poor in general, f ood security is much more an issu e
of financial accessib ility than availability (Cohen and Garrett, 20 10) . In this context, househ old’s access t o
labor marke ts is ess ential.
Many of these questi ons on the linkages betwe en urban ization and food syste m s remain to be explored
(Seto and Ramankut ty , 2016). Most studies that spe cifically analyze the implic atio ns of urbaniz ation are
case studie s at the city o r regional level, specificall y on the spatial dimension of urbanization. Global
estimates of the magnitud e o f these effects are lacking. Studies on, for example, changin g food
consumption pa tt erns gen erally conflate urb anization and income effects (Seto a nd Ramankut ty, 201 6) .
It was o nly relati v ely r ecently that the internati onal c ommunity focused mo re explicitly on urbaniz ation
(FAO, 2011). However, its importan ce is in creasingly acknowledged. The U nited States Agenc y for
International Development (USAID), f or exa mple, held a strategic expert meeting on ‘ Cities and the future
of agriculture and food security: a policy and programmatic roundtable ’ in 2016 (Richards et al., 2016) ,
essentially highligh ting the need for a better understandin g of urbanization in rapidly changing food
systems, making it a priority for future research and funding. The 20 17 Global Foo d Policy Report by the
International Food Policy Research Institute (IFPRI, 2017) also focuses explici tly on the impact s of

8

urbaniz ation on food securi ty and nutrition, recognizing the need fo r a bett er understan ding of the role o f
urbaniz ation in order t o res hape food s ystems to bene fit both urban and rural population s.

1.3 Thesis objec t ive s and outline
This dissertation contributes to the understandin g of how urbanization as gl obal change driver is shaping
food systems b y investigat i ng the implicati o ns of two dimensi ons of urbanizati on on two dim ensions of
the food system: the spatial dimension and urban living on the one hand, and the food produc tion and
food consumption activitie s on the o ther hand. In particular, this thesis contributes by addressing tw o
main research qu estions :
• How is urban area expansi on affecting food pr o ducti on activi ties?
• How is urbanization and associated urban living affecting food consumption patterns? What are the
potential implica tio ns for broader f ood sy stems and publi c health?
This dissertation addresse s the two research questions in four manuscripts, correspondin g to journal
publications. They are rep roduced as chapters 2 -5, as detailed in the followin g sections. Chapters 2- 4
address the first r esearch question, chapter 5 the sec ond.

Chapter 2 comprehensivel y assesses the extent and density o f multiple drivers and im pac ts of land -use
change. It se eks to answ er the foll owing resea rch questions:
• How are c ompeting land uses driv en by human activiti es affecting the fo od production land scap e?
• What are the geo graphical hotspots of land c o nversi on?
• What is the dir ect and ind ir ect impact of human activit y?
The study c ombines and reanalyzes spa tially explici t data of g lobal land use change 2000 -20 10 f or
population, li vestock, cropland, terrestrial carb on, and biodiversi ty. This is supplemented by a detailed
region-specific literature review. It reveals signifi cant co-occurrences of expanding human activi ties and
pervasive pressure on biodiversit y. Patterns of land use change vary, with the biggest changes observ ed in
developing regions. This art icle highlig hts the need for a more detailed and spatiall y e xplicit understandin g
of competing lan d use dyn amics driven by hum an acti vities, thus s etting th e stage for th e next chapter.
Chapter 3 ex amines the implications of urb an areas e xpan sion o n croplands at th e global level, addressing
the following research qu estions :
• Where are cr o plands most vulnerable to con v ersion d ue to future urban expan sion?
• What is the magnitude of croplan d loss, especiall y of pri me cr opland, due to futur e urban expansion ?
• How will the loss of crop lands affect total croplan d area and relative economic imp o rtance of
agriculture fo r differen t cou ntries?
This article provides the first global estimate of the urbanization of croplan ds. It uses a probabilistic map
of future urban area ex pa nsion and combines it with spatial datasets on croplan d area and cro pland
productivity. It sh ows that while cr o pland losses are marginal at the g lobal l evel and c an likel y be
compensated by the global foo d system, they are very relevant in some of the rapidly urbanizing regions
of Africa and Asia. The implications are potentially far-reaching , affecting liveli hoods and dimensions o f

9

food security. In this cont ext, some countries are likel y to lose their food self-sufficiency and will have to
resort increa singly t o imports.
Chapter 4 builds on s ome of the findings from the previous chapter and explor es the risks associated with
high im port d ependencies o n key staple crops for developing countries. It seeks to a nswer the followin g
set of questions :
• Which countri es ha ve a strong dietary relian ce on specific cr ops that the y also need to imp ort?
• What happens in the case of supply shocks, for example if exporting count ries introduce restricti ve
trade policies ?
• What would be the effect on the calorie supply of the p oorest people in these countries?
It analyzes how high depend ency on imports of staple crops could potentiall y affect the calorie supply in
developing co untri es. The analysis re veals that high impor t dependency expose s the poorest part of the
population to telec onnecte d fo od supp ly sh o cks, threatening the calorie supply of up to 200 million peo ple
below the poverty line, 90% o f which live in Sub -Saharan Africa. This article shows that while trade is
undoubtedly an importan t factor in providing eno ugh food in the future , it will be essential to mitigate the
risks associa ted with i m port depend ence.
Chapter 5 provides a change in perspective and focuses on the impl ications of urbanizati on on food
consumption. It addresses the fo llo wing questi o ns:
• What is dri ving urban food consump tio n pa tterns?
• Is there an ur ban effect o n d iets that is n o t inco me rel ated?
• What are the co nsequ ences of an urban effe ct on diets?
This chapter explores the empirical relationship s between urban devel opmen t and packaged food,
processed food, and food away fro m home consumption at different spatial scales, using country level
data for a global analysis and household level data for India. T his analysis reveals that the level of urban
development affects the c onsumption of packaged food s at the co untr y level. Further, it shows variation s
in processed f ood and food away from home consu mption at different levels o f urb an develop ment within
India. These urban effects vary significantl y betwee n metropolitan cities and non-metropolitan urban
areas. While income is still the most important driver for changing food consumption, the findings of this
chapter underlin e the i mportance of urbanization.
Ch apter 6 sum marizes the results of the previ ous chapters, discusses the rele v a nce o f the findings of this
thesis, and la ys out ques tions for furth er research.
In thi s diss ertation, I ap ply methods fro m different disciplines. Chapters 2 and 3 r ely mostly on geograph ic
information sy ste m s (GIS). In these chapters, I use Ar cGIS to process and analyze spatial data. In chapter
4, I use empirical and analytical methods to model the pote nti al implications of food supply sh ocks. In
chapter 5, I empiricall y analyze c ountry level and household-survey data, also employing econometric
concepts.

10

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14

P AR T I

15

Chapter 2

2. Assessing hu man and en vir o nmental pr e ssu r es of global
land-use c hange 2000 - 2010

*

Felix Creutzig
Christopher Bren d ’A mour
Ulf Weddige
Sabine Fuss
Tim Beringer
Anne Glaeser
Matthias Kalkuhl
Jan C. Steckel
Alexander Rad ebach
Ottmar Ed enhofer

*

Currently un der review as F. Creutz ig, C. Bren d’Amour, U. Weddige , S. Fuss, T. Bering er, A. Glaeser, M. Kalkuh l,
J.C. Steckel, A. Radebach , O. E denh ofer: Assessing human a nd environmental pressur es of global lan d -use chan ge
2000 - 2010.

16

17

Assessing hu man and environ mental pres sures of globa l land-use chan ge 2000-20 10

Felix Creutzig 1, 2, *, Christopher Bren d’Am o ur 1,2 , Ulf Weddig e 1 , Sabin e Fuss 1 , Tim Beringer 1 , Ann e Glaeser 1 ,
Matthias Kalkuhl 1 ,3 , Jan Steckel 1,2 , Alexander Rad ebach 1 ,2 , Ottmar Edenhof er 1,2,4

Abstract

Global land turns into an increasin gly s carce resource. Here we present a comp rehensive assessment of
the extent and intensit y of multiple drivers and impa cts of land use change. We combine and reanalyze
data of global land use change 2000 -201 0 for popu lation, livestoc k, cropland, terrestrial carbon, and
biodiversity. We find pervasive pressure on biodi versit y but differentiated types of gross land-use changes
across world regi ons. The ‘ consumers’ type, display ed in Europe, and North America, features high land
footprints, reduced direct h uman pressure s, corresponding to in tensification o f agriculture, and increased
reliance on imported goods, enabling a partial recovery o f terrestrial carbon and biodiversity. In the
‘producer’ type, most clea rly epitomized by Latin America, te lecoupled land-use links drive biodiversity
and carbon loss. In the ‘mover’ ty pe, we find strong direct domesti c pressures but with wide variety of
outcomes, ranging from a c oncurrent expansion of population, livestoc k, and croplands in Sub -Saharan
Africa at costs o f natural habitats to strong pressure on cropland by urbanization in Eastern Asia. In
addition, anthr o pogenic climate change already leav es a distinct footprint in global land use change. Our
data- and literature-based assessment rev eals region-sp ecific o pp o rtunities for managing global land-use
change.

1 Mercator Resear ch Institute on Gl o bal Com mons and Clim ate Chan ge, 10829 Be rlin, Ger m any
2 Department Econ omics of Climate Chan ge, Technisch e Universität Berlin, 10623 Berlin, Ger many
3 Faculty of Ec onomic and S ocial Sciences, University of Potsda m , D-14482 P otsdam, Ger m any
4 Potsdam Insti tute for Cli mate I mpact Res earch, D-1441 2 Potsdam, German y
* Author to who m any c orrespondence should be addressed.

18

2.1. Introduction
Demand for land is conti nuously rising globally (Foley et al., 2005). This is characterized by both
intensificati o n and extensif icatio n of food pr oduction (FAO, 2014), by urbanizati on (Seto et al., 2012), by
the onset o f modern bioen ergy (Chum et al., 2011; Cr eutzig et al., 2014), by preserva tion of nature and
biodiversity (Newbold e t al., 2015) , and, more recently, by afforestati on to sequ ester CO 2 on land (Canadell
and Raupach, 2008). Projected additi onal land dema nd could exceed available land by a factor o f 3 -7 by
2050 (C anadell and Schulze, 2014). Even when accounting fo r plausible multi-purpose allocati on, this
future demand is unlikel y to be matched by available land reso urces (D a vis et al., 2016). I mperativel y, as
global land emerges as a scarce resourc e, the imp ortance of land for various and interconnected aspects
of human well-being is emerging , raising normative and ethical questions (Creutzig , 2017; Risse, 2008) . A
few studies have investiga te d total area demands for v a rious purposes and have provided long -term
outlooks (Hurtt et al., 2011 ; Lambin and Me yfroidt, 2011; Smi th et al., 20 10). But a holistic unders tanding
of geograp hical patterns of the most recen t land system dynamics that investi gates both location and
intensity of land use changes for human needs (food, shelter), and biophysical stability (biodiversity,
climate stabili zation) across scal es is missing . This paper investigat es global land -use change across
different purposes and perspectiv es betw een 2000 and 2010 with harmonize d m etrics. It investigates
effects of dire ct and telecoup led land demand ( de fined as socioecon omic and environmental interaction
over long distances, includi ng trade and climate change (J. Liu et al., 2013) presenting a compreh ensive,
but spatially and r egionally diff erentiated pi cture of global de mand for land.
Land-use change has been asso ciated with human activitie s for millennia and, prior to industrializati on,
was dominated by d eforestation induced by po pulati on pressure and c orrespondi ng demand for cr o pland,
closely following the ascen t and descent of civilizati ons (Kaplan et al., 2009). With the industrialization,
fossil fuel substitut ed for wood fuel, and the nexus between population press ure and defo r estation was
broken, at least regionall y (Krau smann et al., 2008). However, current trends indicate that a re-transition
to more land-use intensi ve eco n omies may exce ed glo bal biophysical limits (Rockström et al., 2009 ; Steffen
et al., 2 015). First, at the current rate o f technol o gica l change, croplands will most likely need to increase
by 10-25% until 2050 to feed a growing and more affl uent populati on demandin g more land -intensiv e
nutrition (Schmitz et al., 2014). Sec ond, human s ettlements expand, demanding an unprecedented area
of land that is o n averag e about twice a s agricult urally productive as world average cropland (Bren
d’Amour et al., 2017) . Third, energy producti o n has started to shift back fro m fossi l - to land-in tensive fuels,
a develop m en t p otentially desirable to reduce counterfactual greenhous e gas emission s ( Creutzig et al.,
2014), or to even gen erate so -called negative e m issions (Fuss et al., 2014; S mith e t al., 2016). Four th, land
could pro v ide the space f or an enh anced terrestrial carbon sin k, e.g. by af fo r estation, thus co ntributin g to
the mitigation of cli mate ch ange. Fifth, ec o syst em s need to be stabilized acr oss the glob e to avoid
unprecedented human-m ad e biodiversity loss. As decisi on-makers bec o me aware of climate change and
biodiversity concerns , previously low-value residual land increases in value, limiting the availability for
other purposes. At the same ti me, anthrop ogenic climat e change itself affects the ‘supply side’ of land -
use, e.g. by changing temperatur e and precipitati o n patterns or CO 2 -fertiliz ation, in part reducing
counterfactual crop yields (Lo bell, 2011). In short, developing human land pressures encounter global
biophysical constrain ts and threaten global common goods, such as biodiversit y and climate. The o verall
spatial patterns o f t hese ch anges requires an up dated an alysis and as sess ment.

19

Clearly, it does not simply m a tter how land is allocated, but also how well it is utilized for different
purposes and objecti v es. For example, land all ocated to crop produc tion could b e used to varying degre es
of efficienc y, dependin g on manage m ent techniq ues and technolog y (West et al., 2014). It is hence equally
important to m easure the quality of land use, using intensity metrics normalized per unit area (Erb et al.,
2013; Kuemmerle et al., 2013), as also realized from a different perspecti ve in ecological and land footprint
analysis (Galli et al., 2014; Wack ern agel et al., 2002; Weinzettel et al., 2013) . To use common language
across di mensions, we also refer to population density and species richness as intensities if used per unit
of area.
In this assessment and review, we co mprehensi vely evaluate regional variation of global land use change
patterns, add ressing the following questions : 1) which kind of spatially distin ct land -use transiti o ns
coincide? 2 ) At what intens ity of use do land -use trans itions occur and where are the hotspots of rapidly
changing land-use dyna mics located ? 3 ) What kind of types of land us e transiti ons can be distinguished
across world regions? To an swer these questions, we comprehensively reanalyze existing dat a on land u se
change in the specifi c categ ories of populati on, pasture, cropland , biodiver sity an d terrestrial carb on for
2000 and 2010. Compiling av ailable data from differ ent sources, we 1) evaluate the change dynamics
between 2000 and 2010; 2) calculate global and regionally varying co-occurrenc e dyna m ics; 3 ) compute
land-use intensity cur v es f or population, pasture and croplan d, b iodiversit y , an d terrestrial carbon; and 4)
identify underl ying drivers drawing fr om the region-specific li teratur e. We und erstand our paper as an
assessment of recent lan d- us e change dynami cs (2000 – 2010). With the goal of comprehensivel y
understandin g land use dynam ics in this limited, but important time range, we combine and reanalyze
published data an d review region-specific literatur e. This assessment is rele vant in that th ere is an
emerging class of global land assessmen ts, including the Global Land Outlook , and the IPCC’s special report
on climate change, deserti fication , land degradation, sustainable land manage ment, food securi ty, and
greenhouse gas fluxes in terrestrial ecosystems (SR2). It is our intenti o n to provid e input and background
to these asses sment r eports.
The data analysis make s use of the best data available for 2000 -2010. Nonethel ess, the data analysis part
is limited by the spatial resolution, and a ccuracy of availab le datasets; data on vegetati o n and soil carbo n
stocks, and cropland suitab ility are m odeled, and the biodiversity data are downscaled proxy data. In
addition, there might be disagree m ents between different da ta sets of the sa me dimension, exemplified
by considerable differences between differ ent cropland extent datasets (Anderso n et al., 201 5; Fr itz et al. ,
2015). The resolution (approximatel y 50x50 km 2 ) is insuffici ent for reporting shifts in land use change o n
identical patches of land. To handle the resulting uncertainty, we cross -validate our results - co -occurrin g
land use changes patterns in particular regions and cross effects - by a detailed review o f region-specific
relevant lite rature.

2.2. Results
We first inves tigate the chang e in intensity of land u se for human pressures from population growth,
expanding pastures and croplands, as well as their imp acts on the biophysical metrics carbon density and
biodiversity (Fig . 1 , Table1). We rely on intensit y metri cs, here al ways und erstood as units (population, tC,

20

livestock unit, cro pland area fractio n, carbon storage by using tones of terrestria l carbon stored/km 2 and
biodiversity intactness weighted by species richness/km 2 ) per area (km 2 ), see Methods. Intensit y hotspo t
analysis (top 10%) corresponds to the t op decile of all grid cells with an intensity change between 2000
and 2010 (rank ed by absol ute density delta). O verall l and-use change an alysis f ocuses on 80% of grid cells
with the highest absolute density change, notable cha nge pixels , filtering o ut land-use change of low
magnitudes. We designat e hotspots as areas where 10% of the highest absolute ch anges in int ensity occur
and notable change areas where 8 0% o f the highest absolute c hanges in intensity occur. When not
explicitly described as hotspots, land-use dynamics are represented by notable change areas. Populatio n
density is increa sing on 76% of lan d (within notable chan ge areas), and on 91% of the h o tspot areas (Table
1). Population growth is most s ubstantial on the India n subcontinent, Northern Africa and Western Asia,
West Africa , the Lake Victo ria region, and around the Sao Paolo mega -urban regions. Population densit y
is decreasing in parts of Eastern Europe, and rural China. The croplan d area fracti on is increasing in hotspot
areas (on 61% o f hotsp o t area), but overall, cropland area fraction is decreasing in a slight majority of
places (53% Table 1). Cro pland is expanding most prominen tly in Mato Gros so , Brazil, the Guinean
Savannah zone and Sumatra (So uth East Asia), but is declining across large parts o f the Northern
hemisphere. Sub -Saharan Africa is the region showing greatest human pressur es as population density
increased o n averag e by 27%, and cropland expanded by 18%, bet ween 200 0 and 2010 (cf. Table S5). Af te r
population, the greatest increase is in livestock (o n 62% of land). The mo st nota ble increases in livestoc k
density appear in Ch ina, Br azil and parts of Sub-Sa haran Africa, but there are dec reases in parts o f Europe ,
too. W orldwide, a small majority of places demonstrat e an increase in land carb on sto ck (55%), notably in
the Northern hemisphere and in tropical rain fo rest s (parts o f the Amazon, Congo and Indonesia). In
contrast, decreases occur in m ost of S outh America, Sub-Saharan Africa, Sumatra, and some North-
American regions (e.g., Alberta). Notably, 57% of global net terrestrial carbon loss took place in Sub-
Saharan Africa and Latin America, together with 68% of global net cropland expan sion (T abl e S5). With
rare excepti o ns, bi odiversity is de creasing worldwide ( 90%, and 98% of ho tspots).
Notably, biofuel pr oduction was resp onsible for ab o ut half the global cropland e xpansion of about 44Mha
between 2000 and 2010; it increased more than 4 -fold between 2000 and 2010 and, by 2 010, biofuels
required about 30Mha of lan d (Bruinsma, 2009; L am bin and M eyfroidt, 2011) . This expansion has mostly
taken place on low-intensiv ely used pastur e land in Bra zil, but als o involves about 2.3Mha biodiversi ty -ric h
prairie land in t h e US (Lark et al., 2 0 15) , and, in total, >8Mha o f palm oil (o nl y partial ly used as fuel) in
Sumatra, Borne o and Mala ysia (Koh et al., 2 011).

21

Table 1. Ga in/loss per land use dimension with dens ity change above t hreshold between 2000 and 2010 (2000 a nd 2005 for
livestock). De nsity u nits: 1) Popul ation: population/km 2 ; 2) Lives tock: livestock units/km 2 ; 3) Cropland: c ropland area fraction
(here defined as percentage of cropland in a grid cell); 4) Carbon: tC/ha; 5) Bio divers ity: Intactness/km 2 (weighted with species
richness). Intactness measures the degree to which the original biodiversity of a terrestri al site remains unimpaired in the face of
human land use and related pressures. Threshold refers to changes in intensity b etween 2010 (2005 for livesto ck) and 2000: Top
10% = hotspots areas of intensity c hange s, Top 80% = areas with notable changes.

Dimension

Threshold
(onl y cells
with
absolute
changes
above
threshold
considered)

Share of area
with gain

Share of area
with loss

Average
density 2000

Average
density
change for
areas with
gain

Average
density
change for
areas with
loss

Average
density 2010
(and change
compared to
2000)

Population

Top 10%

91%

9%

311.2

55.3 (+18%)

-29.2 (-9%)

357.2 (+15%)

Top 80%

76%

24%

64.6

12.0 (+19%)

-2.7 (-4%)

72.1 (+12%)

Livestock

Top 10%

86%

14%

45.0

7.2 (+16%)

-5.7 (-13%)

49.8 (+11%)

Top 80%

62%

38%

12.5

1.8 (+14%)

-0.8 (-6%)

13.2 (+5%)

Cropland

Top 10%

61%

39%

0.46

0.1 (+21%)

-0.09 (-19%)

0.47 (+4%)

Top 80%

47%

53%

0.21

0.03 (+13%)

-0.02 (-10%)

0.21 (-0.1%)

Carbon

Top 10%

55%

45%

257.1

11.1 (+4%)

-12.9 (-5%)

259.0 (+1%)

Top 80%

56%

44%

262.3

4.0 (+2%)

-3.8 (-1%)

263.3
(+0.4%)

Biodiversity

Top 10%

2%

98%

0.14

0.004 (+3%)

-0.0065 (-5%)

0.13 (-4%)

Top 80%

10%

90%

0.11

0.0005
(+0.4%)

-0.0016 (-1%)

0.11 (-1%)

22

Figure 1. Chan ge in intensity of land use between 2000 and 2010. A) Population density. B) Livestock density (for 2000 and 2005).
C) Cro pland ar ea fraction D) Te rrestrial carbon density E) Biodiversity i ntactness (proxy for biodiversity) F) Hotspot wi t h mul tiple
co -occurren ces where human pressures (p opulation, cropland, livestock) are aggreg ated to reduce complexity; r ectangular areas
denote hotspots o f deforestation as identified by Harris et al., (2017a) . All data are process ed an d mapped into 30 arc-minute (0.5

23

degree) gri d (63879 data points), c orrespond i ng to ≈50x50km at equator, and finer resolu tion at higher latitudes. Data source s
are summarized in Table S1.

Figure 2. Co-occurrences of land use changes between 2000 and 2 010 (population, cropland, carbon, biodiversity) and 2000 an d
2005 (livestock), respectively, within g rid cells for (A) h otspots, and (B) notable c hange regions. Solid ci rcle filling represents
the area that experienced i ntensity increases o r decreases within each type of land use . Links bet ween types o f land use depict
pair-wise c o-occurrences. Un directed red ( blue) links r epresent mutual increase ( decrease) in intensity. Reported a re gross
changes . For example, in some parts of the w orld, both cropland and livestock decrease simu ltaneo usly. In others , it increases
simultaneousl y. This results in both red and b lue lines between c ropland land livestock in pa nel B. Di rected ye llow li nks re p resent
an intensity increase in source land use, and decrease in target la nd use. Co-o ccurrences measured at 0.5° grid resolution. Width
of the links show the respective total area o f pair-wise co-occurren ce. Links smaller than 2% of total co -occurrence area are
omitted. The hotsp ot analysis (top 10%) corre sponds to the top de cile of all grid cells with an inten sity change be tween 2000 and
2010 (ranked by absolute density delta). O verall land -use change analysis focuses o n 80% of grid cells wit h the highest absolute
density change, notable change pixels , filtering out land-use change of low magnitu de s.

24

Next, we analyze the spatial co -occurrence of land-u se changes by aggregating the area of grid cells on
which land-use changes co-occur (Fig. 2). We find that human activities (population, livest ock, cropland )
tend to grow together. This is confirmed by a Principal Component Analysis (PCA), in which the first
eigenvect or clearly distinguish es between increasin g human direct pressures and negative impact on
biophysical dimensi o ns (Fig. S1-S2, Table S2). The seco nd eigenvector describes t hat, a fter accounting for
the first eigenvector that explains the largest share of data variation, increase s in population density and
terrestrial carbon tend to co -occur with lo sses in cropland area, biodiversity, and, to a low er extent,
livestock. This reflects on the one hand cropland and biodiversity reduction due to urban expansi o n (c.f.
Bren d’Amour et al., 2017 ) an d population gro wth (Ind ia), and on the other hand increased carbon stocks
in Europe, the US and in remote areas of the boreal and tropical biomes due to re duced agricultural activity
(US, Europe) and C O 2 -fertilization, re spectivel y .
Biodiversity reducti on co-occurs pervasively with inten sity increases for all o ther land uses (Fig. 2). The
land carbon stock is partial ly reduced where human activities expand; there is an increase in land carbon
stock in o ther areas most likely related to CO 2 -fertiliz atio n, longer growing periods, or increased
precipitati on. In hotspots, population and livestoc k increase, but carbon stock and especially biodiversit y
is reduced (Fig. 2A). P opul ation exerts a dominant pressure over all land use changes (Fig. 2B). Increases
in population where d ensities are high (urbanization) l ead to cropland losses m easur able on a global scal e.
In other instances , cropland expansion and biodiversit y loss often co incid e.
Changes of land use are concentrated in specific intensity bands (Fig. 3). An analysis of the magnitude of
intensity shift fo r all lan d areas reveals that mo re than 90% o f the shifts have an absolute value of <10 %
of their respec tive scales as presented in Fig. 3; popu lation and livestock shifts tend to be positive, while
biodiversity shifts are strongly negative (Fig. S2). We cross-validated results with a wo rld-regi on specifi c
literature (Tab. 2). Pristine land becomes p opulated, reflecting human land take in Sub-Sah aran Africa, the
Arabian Peninsula, and in a few scarcely p o pulated areas of the Americas (Fig. 3A, Fig. S3a, Tab. 2). Th e
area of high po pulati o n concentra tion (>900 pop/km 2 ) increases, reflecting urbanization in the Bengal
delta, coastal China, the Nile delta, and Java (Fig. 3A, Fig . S3b, Tab. 2). Livest ock lan d use follows a negati v e
exponential function with large areas of land being used for very low -intensi v e husbandry (Fig. 3 B).
Livestock is increasin g in areas of very low density, i.e. mostly in Brazil, Northern China, and the Guinean
Savannah, but there is less husbandry in Eastern Europe (Fig, 3B, Fig. S3c, Tab. 2). Livestock is also
increasing in areas of higher density, reflecting industrial livestock breedin g in Shandong, Hebei, and
Henan provinces in China and around Sao Paulo, Brazil (Fig. 1 , Fig. 3B, Fig. S3d, Tab. 2). There is an
expansion o f cropland of medium suitability in the Guinean Savannah and South Ame rica, but there is a
loss of cropland in the USA and Easte rn Europe (Fig. 3, Fig. S3e, Tab. 2 ). Land of very high suitability was
utilized less for agricul ture in the US Mid-West in 2010, while cr opland has expanded in the hig hly suitable
Chaco r egio n of Argentina producing soybean for exports (Fig. 3C, Fig . S3f , Tab. 2), while s ome land of l ow
suitability has been abandoned (Fig. 3 C). Most land has less than 50 tC/ha carbon stock, which is low
compared to the peak value of 1,850tC/ha (Keith et al. , 2009) (Fig. 3D). The chang e in intensity of t errestrial
carbon is complex, but there is a distinct increase in carbon stored b y land at <1 00tC /ha, par ticularly cl ose
to the Arctic Circle (Fig. 3D, S3g ). Ther e is also an increase of terr est rial c arb o n stored at aro und 4 00tC /ha
in boreal areas and in the tropics (Fig. 3D, Fig. S3h, Tab. 1). Areas of medium -hig h species intactne ss are

25

lost, particularl y in South Asia (India and Pakistan) and the Chaco region, Argentina (Fig. 3E, Fig. S3i, Tab.
2).

Figure 3. Distribu tion of changes in the intensity of land u se betw een 2000 and 2010 for population (A ), livestock (B), cropland
(C), carbon (D), and bi odiversity (E). Bin sizes are 0.01. Lines re present 5-bin weighted mean average. T he blue lines represent
frequency of land ( total area) within each bin; the red lin es changes i n frequency. Red boxes i ndicate intensity bins of s pecial
interest and are s ubstantiated with maps i n Fig. S 3 in the SI fo r analysis of sp atial patterns, and by the world-region specific review
(Table 1 and SI).

A wo rld-regi o n specific analysis of co-occurring land-use changes (Fig. 4), substantiated by literature
review (Tab. 2, Supplemen tary Informa tio n f or detailed discussion), and an analysis of the increasin gl y

26

important r ole of internati o nal trade (T ab. S3) reveals that regions can be a ssoci ate d with at least one o f
three types o f land -use dynamics (Fig. 5). Archetype A is charac te rized by a large land footprint but at most
moderate po pulati o n growth (‘Consum ers’). Europe fits best into this arch etype, with stagnating
population, intensificati on of agriculture, and increa sed reliance on imp orted foods. Europe outsourced
land-in tensive f ood production at a scale corr espondin g to up - to -half of their domestic cropland use (Fig.
5, Table S3). On its own territory, these factors enabled a part ial recovery o f te rrestrial carbon and
biodiversity. North Americ a and Oceania also have hig h footprints, but also have modera te po pulati o n
growth and high biocapa city enabling exports of its agricultural surplus. Human pressure and losses of
ecosyste m services have decoupled only in few instances: land carbon stock and biodiversit y are partially
co -improvin g in Europe and Oceania. A possib le explanation for the improvem ent in Europe and Oceania
is the emergence o f new institutions and policies, as for example, in EU-accession co untrie s from Eastern
Europe.

Archetype B is d efined by high export shares (>5% of land is used fo r export) as enabled by high capacity
relative to overall populati on (‘P roducer s’). Notably, this involves Latin America that increasin gly serves
the consumer needs of Euro pe and Eastern A sia. Specifically, South America and Russia increased their
cropland embedded in net exports by 24 and 16 percentag e points, respec tively (Table S3). But also
Eastern Europe and Central Asia, witnessing decreasin g population, sees an increasin g share of land used
for exports. The consumer world-regions of North America and Oce ania belong simultaneously to the
producers, exporting high margins to other world re gions. Importantl y , telecou pled and trade -induced
land-use links drive bi odiversity and carbon loss, epitomiz ed by Latin America, notably in parts o f Brazil
and the Argentian Chaco region (Tab. 2 & S3). In addition, export of palm oil from Indonesia is a major
driver for b iodiver sity l o ss and deforestation in South-East Asia (Tab. 2 & S 3). Overall, exp o rts are
responsible for 17% of spec ies loss, with highest i m pact e mbodied in ex p orts from Indonesia to the US and
China (Chaud hary and Kas tner, 2 016).

Archetype C is characterized by high population growth (>5%) and limited land used for export (expor t
sh are o f land <5% and incr eased imports in 2009 compared to 2000). We den o te this type as ‘movers’
reflecting their dynamic po pulation and economic growth, and their expected future global influence on
global land use change. Lan d use change is domin ated by direct regi o nal de mands , feeding a gr o wing and
more affluen t population . 8 3% of species loss is attributed to agriculture devoted for domestic
consumption ( Chaudhary a nd Kastner, 2016), and demand is increasingly dri ven by growing affl uence and
dietary change rath er than po pulation growth (Kastner et al., 2012). Most of Asia and Africa belongs t o
this archetype. But the variety of ‘mo ver’ wo rld r egions is considerable, ra nging from a concurrent
expansion o f population, livestoc k, and croplands in Sub-Saharan Africa at costs of natural habitats to
strong pressure on cr opland by u rbanization in Eastern Asia (Fig. 2&4). In fact, a detailed co mpanion study
finds that urbaniz ation c onsumes ar o und 2-3% of gl obal agricu ltural land be tween 2000 and 20 3 0, m ostly
in East Asia; this is pri me ag ricultural land and is near ly twice as producti v e as average agricultural land,
implying a productivity loss of 4 -5% (Bren d’Amour et al., 2017) . Eastern Asia an d the Middle East and
North Africa import a high proportion of land -based products fro m elsewher e, similar to Europe. The

27

Middle East and North Af rica are in the most precariou s situation with h igh population growth and stro ng
reliance on i m ported f o od and other lan d produce (Fig . 5).

Anthropogenic climate chan ge is associated with r egion-specific dynamics that have a total ef fect
comparable to that of dir ect human pressures. Carbon fertilizati on has especially affected carbon stocks
in the intac t tr opical rainforests, such as in Congo, and the b oreal zone, including Siberi a (Zhu et al. , 2016) .
Increased precipitati on in the Sahel zone (P a rk et al., 2016) and Central Africa enabled higher carbon
stocks, while prolong ed drought conditions contribut ed to salinization (Gallant et al., 2012) and reduced
cropland densit y in Oceani a by 11% (cf. Table S 5).

The analysis o f drivers fr om the lit erature re veals the importanc e of instit utional drivers, inclu ding
agricultural policies in Europe and North America, afforestation programs in China, conservati on in India,
forest protec tio n in the A mazon, and the legal underpi nning s of international trad e (Tab. 2).

28

Figure 4. Co-occu rrenc e of notable land use ch anges within regions. See caption of Fig. 2 for explanation of co -
occurrence figur es. Th e map shows th e z -scores f rom th e product of th e first eigenv ector from th e P CA with the
standardized data of in tensity ch anges. Blue colors ind icate th at increases in carbon stocks and biodiversity are

29

relatively stron g whil e red colors indica te th at p opulation, cropland and livestock gain s dominate (relative to the
mean change).

Figure 5. Land use change across world r eg ions belong to different archetypes. Type A (Co nsume rs): High la nd footprint,
moderate population growth ( Europe, North America, Oceania). Type B (Producers): High biocapacity and institutional capacity
that enables a s hare of cropland >5% being e xported (Eastern Europe and Central Asia, Latin America, North America, Oceania,
South-East Asia). Type C ( Movers): Population gr owth>5% and e xport share <5%: (North Africa and Western Asia, Southern Asia,
Eastern Asia, Sub-Saharan Afri ca, South-E astern Asia). Data from (Kastner et al., 2014; Weinzettel et al., 2013).

30

World
region

Key observations

Explanations

Europe
(without
Eastern
Europe)

Low population pressures go alo ng with an
aband onment of cropland and co-occur with
increases in land carbo n stock (84% o f area), and
declines in biodivers ity (albeit increases in
biodiversity occur in s ome places such as
Germany) (Fi g. 4). Li vestock d ensity i s decreas ing
by 94% in h otspots and 76% i n areas with nota ble
changes (cf. Tabl e S4&S5 ).

Aging popu lations, and established u rbanization p atterns
point to low populat ion pressures. Technological an d
institutional drivers un derlie l ocation- specific
agricultural intensification in Eu rope; economi c factor s,
including u rbaniza tion, and changes in th e E uropean
Common Agricultural Policy explain location- specific
reductions in intensity ( van Vliet et al., 201 5) . Both
agricultural in tensification of the most p roductive lan ds
(e.g. in Denmark) and farmland ab andonment in
marginal, less co mpetitive regions are dri ven by th e
globalization of agricultural markets ( Kuemmerle et al.,
2016; van Vlie t et al., 2015). E urope is strongly
outsourcing land-intensive crop p roduction through
international trade; the shar e of ‘imported’ cro pland,
driven by dietary change (Gall i et al., 2017), grew by 20%
from 2000 to 2009 an d by then corresponded to more
than half of the crop land u nder domestic production ( cf:
Table S3).

Eastern
Europe
and
Central
Asia

The stock of terre strial carbon increa ses in many
areas (with th e exception of Sou th -East Sib eria)
(Fig. 1D), includ ing, at lo w int ensities, c lose to t he
Arctic Circl e (Fig. 3D, S3g). At th e top decile,
carbon stock gains ou tweigh l osses by 517Mt CO 2
in Eastern Europe and Central Asia (cf. Table S4).
Those effects co -occur with crop land, pastu res
and livestock declin es (Fig. 4 ). Crop land inten sity
in Eastern Europ e an d Central Asia dro pped by
18% in h otspots (cf. Tab le S4), despite the region
having become an effectiv e exp orter o f crops (cf.
Table S3)

The increase of forest s on abandoned farmlan d after the
collapse of the Sovie t Union (>30Mha) contrib uted
substantially to carbon stock gains. In former socialis t
countries restitutio n, low c ompetitivene ss, an d rural
emigration led to the abandon ment of farms
(Kuemmerle et al., 2016) . There is, h owever, sub stantial
variation between the countries, attributed to stron g
differences in market reform (Alcantara et al., 2013) . In
European Russia the gain amou n ts to mor e than
44tCO 2 /ha du ring our ob servation period, which makes it
outstandin g as a sink in the boreal region an d
comparable to sinks in the temperate biom e (Pan et al.,
2011). After land is ab andoned, soil lo ses carbon before
reforestation dynamics eme rge, in creasing terrestrial
carbon. Hence, vari ed pattern s exist in carbon stock
changes, par tially depend ing on the ord er of land
aband onment (cf Schi erhorn et al., 2013). South -East
Siberia displays carbon loss, lin ked to deforestation an d
timber exports to China, an d demand for p roducts sold
globally (Lian g et al., 2016). In large parts of Siberia,
global warming enable s longer period s o f p lant growth
and photosynthesis (increased lan d carbon stock) (Zhu et
al., 2016), while wild fires red uce the land carbon stock
in some other parts (see SI).

South Asia

Strong concurrent increases in population,
cropland, and livestock are combin ed with a loss
in biodiversity at hotspots (Fig. 4). Pop ulation
increases by 18% (In dia, N orth -east Paki stan),
cropland expand s b y 17% (Pakistan Afghanistan)
and livestock by 3 % (No rth -east Pakistan ) at

Strong p opulation growth (250 million from 2000 to
2010) do minates lan d us e chan ges. In Ind ia, agricultu ral
land loss du e to urba niza tion led to a reduction of th e
harvested ar ea o f ric e by 4%, while yi elds increased b y
15% betw een 2000 and 2010 (SI). Urban ization also
emerged as a key press ure af fecting biodiversity loss, but

31

hotspots (Fig. 1, Table S4). Croplan d decreases
with urb anization, but in creases in wider urban
regions (SI, cf Bren d ’Amour et al., 20 17).
Biodiversity d ensity los s a mounts to 8% at
hotspots and 3% at n otable c hanges all over India
and East Pakistan . Global share in b iodiversity
intensity loss is 13 %.

conservation program s an d a switch away fro m
traditional fuels ameliorated the loss o f biodiversity
(Nagendra et al., 2013; Reddy et al., 2015).

South -East
Asia

Strong co-occurring in tensity in creases in h uman
settlements (14%), croplan d (18%), livestock
(14%), and, les s so, carb on stock (2%), abu ndant
losses of biodiv ersity ( -2%) (F ig. 4, Table S5). The
region acco mmodates 19% of glob al croplan d
expansion, with h igh contrib utions from Su matra,
Vietnam an d centra l Myan mar (Table S5, Fig. 1).
Human activities have trigg ered increasing
pressure on biodive rsity (Fig. 4). 97% of all land
with biodiversity change sho w loss, concentra ted
in Sumatra, the North of Thailand, Cambodia and
Vietnam (Table S4, F ig. 1).

The s evere lo ss of biodiv ersity is mostly driven by
deforestation for commercial agriculture (Ho son uma et
al., 2012), par ticularly for palm oil (more th an 30% for
international markets (W ilcov e et al., 2013 )) and forest
plantatio ns (explainin g th e m ore mod est effect on lan d
carbon stock, cf. Stibig et al., 2014) , somet imes related to
large-scale land acquisitions (Davis et al., 2015). Draining
and bu rning of peatland constitute a m ajor source of
carbon release in South East Asia, especially in Sumatra,
and to lesser degree in Borneo (Wilcove et al., 2013).
Peak emission rates e xceedin g th ose of the Euro p ean
Union f ossil fuel burnin g occu rred in 2015 (Huijnen et al.,
2016). Growth in po pulation in cities (by > 31%) as well
as urban land (by 22 %) h as been significant, with th e
highest ra tes o bserved in Mal aysia, Vietnam, Cambod ia,
the Philippin es and Laos (Schn eider et al., 20 15). Growth
in incomes has resulted in an increasing consu mption of
meat across the entir e region (Thorn ton, 2010).

East Asia

Population an d livestock expan d, partially co -
occurring, while crop land a nd biodiversity losses
are massive; terrestria l carbon dynamics are
mixed (Fi g 4). E ast Asia shows 15% of pop ulation
and 30% of livestock growt h as global shares
(Table S5, Fig 3B, S3d). Ongo ing u rbanization in
East Asia lead s to high population decreases in
rural are as (44 % of global tota l negative , Tab le S5)
mainly. Los s of croplan d is 19 % of global cropland
loss; loss of biodiversity is 9% of global biodiversity
loss, (Table S5, F ig. 1).

Rapid urb anization an d population growth arou nd big
metropolitan and urban centers b etween 2000 and 2010
led to pres sures on other land use types, e.g., consuming
productive croplan ds ( Bren d’ Amour et al., 2017; Ch en,
2007; Galli et al., 2015). Urbaniza tion has also b een th e
most i mportant driv er o f bio diversity losses; e.g., in th e
Pearl River delta, 26% of natural habitat and 42% of loca l
wetlands ha ve been prey to i ncreasing urban land (H e et
al., 2014). In the biod ivers ity-rich Chinese Yunn an
province ca sh crop plan tations, notab ly rubber, cause
biodiversity loss (X. Liu et al., 2013). Net changes o f
te rrestrial carb on have been negative in th e region, with
a h ighly d iversified regional p attern (Calle et al., 2016).
Afforestation and restor ed grassland on d egraded
agricultural land in ru ral areas (e.g., Tibet, Inner
Mongolia) increased terrestrial carbon stock (De ng et al.,
2014), whil e croplan d exten sification, e.g. in th e Sichuan
basin an d Heilon gjiang, incre ased emi ssions fro m land
use chang e (Zhang et al., 20 15). Rap idly incr easing meat
demand in East Asia is mostly satisfied by industrializ ed

32

livestock breedin g, particular in urb an areas (Bai et al.,
2014). Inc reasing fodder imports, particularly maize an d
soybean, for liv estock pro duction h ave raised land -use
pressures el sewhere as th e pro portion of i nd irect
cropland imports grew (Table S3).

Middle
East and
North
Africa

Increasing population (Fig. 3 & S3b) is a ssociated
with growing livestock densities at the expense of
biodiversity (Fig. 4). The r egion records high
relative population density growth (20 %), and
accounts for 9% of total global positive changes in
populat ion, and 6% of glob al positive livestock
changes, mainly concentra ted at Nile river delta
and South -wes t Yem en. The region depicts
cropland loss (7% of global total) in Morocco, East
Iraq, T urkey, as well as cropland gain (4% of glob a l
total) in th e N ile ri ver d elta, North of Syria an d
Mediterranean Alg eria (Table S4&S5, Fig. 1).

Human and economic acti vities congr egate arou nd the
available, but scarce water resources, mo stly rivers,
deltas, and oases, b ut also coa stal zones; th e competition
between land uses is particularly fierce, best exemplified
by the N ile river in Egyp t, where urb an ar ea expan sion is
forecasted to engulf more than a qu arter of v aluable
croplands (Bren d’Amou r et a l., 2017). In Ma rocco, food
demand multiplied driven by population growth (160% in
1961 -2009) and per cap ita d emand (>50% in 1961 - 2009,
c.f. Galli, 201 5). The region outsou rces land -intensiv e
productio n by imports, which h ave increased
substantially between 2000 and 2010 ( cf. Galli et al., 2017
and Table S 3), increasing the risk for telecoupled food
supply shocks (Br en d ’Amour et al., 2016). In Turkey,
biodiversity los s appears where i mportant wetlands,
grasslands, an d even ri vers are disapp earing due to
human activities ( Şekercioğlu et al., 2011). Pri stine land
take on the Arabian peninsula is closely related to
populat ion growth, and agricultural expansion, fostered
by unsustainab le reliance on fossil water r eserves
(Odhiambo, 2016).

Sub-
Saharan
Africa

Strong concurrent human press ures dominate (Fig
1,3A&4, Fig S3a). Populat ion is in creasing mostly
in the La ke Victoria region and West Afri ca,
cropland expansion is p ervasive acro ss the entire
Guinean Savann ah, and livestock expan sion is
concentrated in East Africa (E thiop ia, Lake Victoria
region), repre senting 3 9% of global croplan d
expansion (Table S5). Biod iversity is decreasing
pervasively (Fig. 1&4). Fertil e savannahs, o ffering
a large unta pped potentia l for agricultu re, display
increased crop production r epresenting 25% of
the world’s fa stest chan ging crop lands (hotspots,
Table S4), co -occurring w ith rural population
growth and carbon loss (Fig. 4 ).

Population dynamics are cha racterized by h igh fertility
rates an d rural-urb an migration (Buhau g and Urdal,
2013), driven by popu lation growth in resource
constrained rural areas rather than urban
agglomerations (Hold en and Otsuka , 2014). Local
cropland losses (South Africa) are related to the
concurrent expansion of horticu lture (Liebenber g and
Pardey, 2010). The co-occur rent p opulation an d crop
yield growth in the Guinean Savannah is in line with
existing e vidence on Boserupi an inten sification in Africa
(Jayne et al., 2014). Cropland expan sion, ho wever, also
results in to a reduction in land carbon stock (cf.
Searchinger et al., 2015). La nd -use emissions for
savannah burning e xceed those of fos sil fuels in Sub -
Saharan Af rica (Ciais et al., 2011). In contrast, carbon
fertilization an d increased p recipitation generated an
increase in land carb on stock in forest areas (Ciai s et al.,
2011). Most Sub -Sahara African coun tries have been
poorly integrated into to the world agricultu ral market

33

because of a lack of infrastru cture and low investment
rates resulting from poor instit utional quality (Barrett,
2008; Kalkuh l, 2016). Henc e, cropland d ynamics have so
far largely b een driven by lo cal factors rather than by
international trade (cf. Table S3). Pristine lan d take and
biodiversity loss is most strongly asso ciated with
populat ion pressure, b ut al so with crop land expan sion
(cf. Searchinger et al., 2015).

Oceania

Cropland and livestock redu ction appears more
pervasively than biod ivers ity or carbon loss (Fig.
4). Crop land intensity decre ased by 11% (Table
S5).

Salinization and droughts, partially attributed to
anthrop ogenic climate ch an ge (Gal lant et al., 2012),
compromised more th an half of th e farmland and crop
productio n in Australia (MSEI C, 2010). Local biodi versity
loss in Australia has mo stly been attribu ted to
agricultural p ressures (Steffen et al., 2009).

Latin and
Central
America

Population growth is pronou nced mostly in
Central America and in coa stal parts of South
America (Fig. 1A). Crop and livestock d ensities
rose by 16% and 24%, respectively, in Latin
American h otspot areas betw een 2000 and 2010
(Table S4), includ ing th e Cha co region, Arg entina
(Fig. 3E, Fig. S3i). 28% o f gl obal lan d area with
notable reduction in biodiversity is loca ted in La tin
America (Table S5). Carbon losse s are
concentrated in th e mo st carb on -rich region s (in
hotspots, Table S4). This expla ins the ob served co-
occurrences (Fig. 4): a dominance of h uman
pressures in C entral America and part of Latin
America (mainly Brazil), an d a recovery of carb on
and b iodiversity in the North .

Direct hu man pres sures are less dominant as th e
continent had alread y been mostly urban ized b efore
2000. In South America, c attle ranch ing intensified,
especially in the Brazilian su btropics, an d is n o long er
only associated with d eforestation (Lapo la et al., 2014);
the combination of the availability of fertil e land and low
product ion costs has le d to defore station through
export-orient ed industrial ag riculture, esp ecially in the
peripheral A mazon b asin (cf. Fig 1 and Grau and Aide,
2008) , even as deforestation rates in Brazil declined after
2005 (Nep stad et al., 2014). Declinin g de forestation
arose from better monito ring and more rigorous
enforcement. Soy and maize was increa singly p roduced,
and exported to Euro pe and East Asia (cf. Table S5; cf.
Kastner et al., 2 014). Notab le, th e Argentinian Chaco
region experienc ed an acceler ation of dry forest clearing
for soybean pro duction for internation al markets
(Gasparri and Grau, 2009). A combinat ion of agricultu ral
modernization and rural -urban migration caused land to
be aband oned, enabling ecos ystem r ecovery, especially
in parts of the Caribbean and Central America (Grau and
Aide, 2008).

North
America

North America records population growth (9%)
accompanied by u rbanization , par tly at the
expense of liv e stock and cropland area (Fig. 4,
Table S5). It shows cropland depletion of 10% an d
31 % total global share (T ab le S4). On cropland
biodiversity is r educed. Nort h America is a large
land-exporting region , with 34% (2000) and 31%
(2009) n et expo rt as share of croplan d under
domestic production (Table S3). Share of the total

Cropland loss occurred wi th the i ntensification of
agriculture and the expans ion of u rban areas ( Sleeter et
al., 2013). High commodity prices driv en by th e rising
demand for bio fuel feedsto cks since th e late 200 0s
provided new incenti ves to expan d crop prod uction
(Wright and Wimberly, 201 3). Consequently , wide-
spread con version of gras slands, shrublan ds, and
wetlands to agricultu ral uses reapp eared across th e
United State s with h ot-spot s of change located in the

34

Table 2. Land-use change dynamic s in world regions 2000 -2010. See SI and associated on line information f or more bac kground.
Table S7 separately li st key refe rences for each worl d region.

2.3. Discussion and conclusion
Our data and literatur e -bas ed assessment reveals that the regionally d ivergin g p atterns of g l obal lan d use
change, grounded in direct human pressures, telecoup led land demand by interna tional trade, and v aryin g
climate change i mpacts. We identify t hr ee crude type s o f world regi o ns: A) ‘cons umers’, charact erized by
high per capita lan d footpri nt; B) ‘producers ’, characteriz ed by high exp ort share of land; and C) ‘ movers’,
characterized by high population growth, and increasi ng demand fo r land o u ts id e their o wn regions. Due
to its popula tio n and dynamic change, the ‘movers’ will have the most i mport role in future global land
use change.
Managing global land use change requires an explicit co nsid eration of the differences between world
regions. Our an alysis and resulting typology de monstrates that a successful manag em ent of global lan d
use is clos ely linked to SDG 2 (Zero Hunger), S D G 12 (Responsible Co nsu mption a nd Pro duc tion), and SDG
15 (Life o n L and), and atta ched to SDG 13 (Climate Action) both on the mitigation and i m pac t side. Th e
strong telec o upling , both by international trade and climat e change, substantiate the need for
international cooperati on to manage gl obal lan d (Creutzig, 2 017; Magalhã es et al., 201 6). Plausible gl obal
cooperation o n la nd -use managemen t includes measures particularly suited for different typ es of world
regions. In consumer regi ons, such as Europe, sustain ability certificates and dietary change could foster a
shift to sustainable land use on the demand side (Gall i et a l., 2017; Tayleur et al., 2016). In producer
regions, in particular those with rich biodiversity, harmonizati o n of ecosystem protection m easur es and
financing of nature conver satio n (Waroux et al., 2016), and an upscaling of international paym ent for
ecosyste m services schemes (Rands et al., 2010) would be a crucial compon ent of protecting intact
ecosyste ms. As carbon stock movements are not always related to biodiversit y, it is crucial for the design
of environ m ental policies, such as REDD+, to differentia te between land carbon stock and bi odiversity
(Phelps et al., 2012). Our da ta reveals that in Sub-Saharan Africa and Latin America rural population growth
is accompanied by an increase in cropland, and a re duction in biodiversity (Fig. 5), pointing to pot e ntial
efficiency gains in agricultu re due to populati on press ure (cf. Boserup, 2005 ). Specific measures to fu rther
improve efficient land use involv e int ensification that complies with the protection o f i mportant

global positi ve carb on stock density increa se by
20% in vast parts of Alaska, Canada, and th e Mid -
West USA (Tab le S5, Fi g. 1 ). Carb on increase
coincides with cropland abando nment,
afforestation, an d cropland intensification (Fig.
1&4).

Corn Belt an d th e Lake Sta tes. Corn cau sed mo st of
recent land u se change th rough its displacement of oth er
crops (Lark et al., 2015; Mladenoff et al., 2016). Between
2006 and 2008 th e area harvested for corn an d soybean
in the United States increase d by 3.2Mha (Wallander et
al., 2011) with anoth er 5Mh a increase occurr ing b etween
20 08 and 2012 mostly at the expense of grassland s
(Faber et al., 2012; Lark et al., 2015). This new wave of
expanding corn and soy p roduction occurred most
rapidly o n land less suitable for agriculture, charact erized
by high erosion ri sk, shallow s oils, an d drought
vulnerability (Lark et al., 2015).

35

ecosyste ms, soil carbon, an d water resourc e s (Garnett et al., 201 3); multi-purpos e sy ste m s that integra te
several land uses , an approach called land shari ng (Fis cher et al., 2014; Lambin an d Meyfroidt, 2011); and
compact urbanizati on that preserves cropland (Bren d’Amour et al., 2017) . Prioritizing a small set of
leverage points co uld greatly increase the sustainabil ity and efficiency of food production (West et al.,
2014) .
Our synthesis of the litera ture on the driver s of land-use cha nge in dicates also th at institutions ar e crucial
for pr eserving biodiver sity-rich land, for example in Europe and in par ticular inst ances in South Asia. The
current land-use chang e observed in o ur analysis sugg ests that econo mic pressur es of direct human ne eds
trump sustainabilit y concerns, or, in other words , that institutions are poorly suite d to preserve biophysica l
assets, and in particular, biodiver sity. The fact that the highest pressures on land can be found in the
developing wo rld where in stitutional qu ality is very h eterogeneous needs to be take n as a strong wa rni ng
signal that, at least in the near futur e, increasing human activities will continu e to put high pressure on
natural systems. Improving institutional capacity will be a key factor in realizing nature conservation and
efficient land use. Especial ly in mov er regions, highly efficient land uses could be further fostered by
technological transfer and institutional capacity building.
Our emerging view differs from both Malthus (popula tio n rises until limited by resourc e availability) and
Condorcet (the human race is c apable of unlimited pr ogress), who b oth see hu man-nature intera ctio ns in
terms of natural laws. Instead, human actions, particularly in te rms of institu tio nal design, including
markets, cultures, and reg ulations, will decide wheth er direct human needs and sustainability objectives
can be simultaneously achi ev ed. The global dimensio n of land use is not only founded in transboundary
externalities of emission reductions and biodiversit y p rotection; it is also that underlying drivers such as
rural-urb an migration, trade in land-intensive goods, and more indire ctly, pov erty redu ction eff orts and
education impr ovements, go beyond the immediate jurisdictions of the nati on state and require some
form of internati o nal co operation. Local land use chang es are therefor e p art of a mu ltilayered bi ophysical-
socioeconomic system. This perspective of globally integrated land use could more effectively translate
into local and globally c o ordinated action to make the best use of land for direct human needs and fos te r
biophysical stabi lity.

2.4. Methods
2.4.1. Data and data processing
This study combines gridded datasets of different land use dimensions and their respecti v e intensities
(Table S1). D ata selecti o n is based on quality and availabil ity fo r the year 2000 and 2010. All data are
processed and mapped into 30 arc- minute (0.5 degree) grid, corresp onding to ≈50x50 km at equator, and
finer resolution at higher latitudes. The sample size ensures statistical relevan t measurements of co -
occurrences of land use cha nge an d stat isti cal analysis o n world regi on scale. The resolution is insuffici ently
high fo r reporting shifts in land use change o n identical patches o f land. Instead, the analysis reveals co -
occurring land use changes in p articular regi ons, and by this, statistical inferen ce of cr o ss effects. Spatially
explicit reported data are used for all dimensions in the y ear 2000. Data are only partially availably fo r

36

2010. Specifically, est ablis hed datasets on li vestock (Robinson et al., 2014) only go as far as 200 5. Som e
data (e.g. po pulati o n, livestoc k) are based on censu s data. Not all countries provide frequently updat ed
censuses, therefore are some of the est i mates base d o n a single census year, while others have had
adjustments applied to normalize the data fro m diffe rent census years to a co mmon se t of boundari es.
Data should be taken with care in in ter-annual comparison as changes can be ma tter from adjustments or
reflections of nati o nal o r re gional growth rates rather than e.g. ne t migration or po pulation growth. Henc e,
differences between the observed points in time, 20 0 0 and 2010 should be taken with care and seen as
indicators rather than fixed values. Nevertheless thes e were the best availab le data, on global level, at this
time. This study combine s gridded datasets of different land use dimensi o ns and their respectiv e
intensities (Table S1). It focuses exclusiv ely o n land-use dynamics and does not cover water as additi o nal
component, which is beyond the sc ope of this stud y.
Cropland data is based o n HYDE 3.1 (K lein Goldewijk et al., 2011) and the GAEZ product (IIASA, 2 01 2, see
also Table S1). Other croplan d maps, e.g. (Fritz et al., 2015), offer higher resoluti on, but are not available
for 2010.
All data were read in, r e-sampled (if applicab le), and c ompiled into a single dataset for subsequen t analy sis,
using zonal statistics in ArcGIS. Additional processing steps were required for the d ata used in livestock
and biodiversi ty dimensi o n s:
Livestock datasets of the most important livest ock types (poultr y, pigs, goats, sheep, and cattle) wer e read
in as layer s and re- sampled to 2.5’ Arc Minute. Th e aggrega te Li vestock Unit (LU ) Layer was gen e rated with
the raster calculat or tool using the L ivest ock Layers an d Livestock Unit Conv ersion Factors (poultry: 0 . 01,
pigs: 0.225, goats: 0.1, sheep: 0.1, and cattle: 0.7; derived from
http://www.lrrd .org/lrrd 18/8 /chil181 17.htm).
Biodiversity is defined as the stock of plants (including tree s) and animals (including fi sh), fungi and
bacteria (e.g. for food, fuels , fi ber and medicine, geneti c resources f or developing new crops or medicines,
or as a tourism asset etc.) following the o fficial SEEA (Syste m of Environment al Economic Accounting)
definition (Un ited Na tions, 2014 ). The focus is on terre strial biodiversi ty , thus includin g fish (in rivers, la kes
etc.), but no t o ffsh ore m ari ne life. The m ap of species richness by UNEP/WCMC is used which covers the
taxonomic gr o ups o f birds, m a mmals and amphibians, based on the Predicts m odel (Ne wbo ld et al., 2014).
Species richn ess can be interpreted as the potential number o f different species in one grid cell, thus
measuring actual diversity and not absolute numbers. F rom species richness, we compute ‘inta ctness’ as
proxy for the biodiver sity dimensi o n. The intactness o f a grid cell is an index o f how much of the initial
species richness of a grid ce ll (unto uch ed, i.e. in 100% ‘primary’ vegetation) is impacted by o th er land uses.
The intactness f or a given year is computed by fact oring in gridded land use data (for both 200 0 and 2010).
Every land use t y pe in a grid cell (in fractions of a grid cell) gets assigned a differen t i m pact o n th e original ,
initial species richness in that cell, m ethod olo gicall y following Newbold et al. (201 5). Newbold et al.
differentiat e betw ee n different intensities of land use types (minimal, light, intense use) and, in the case
of se co ndar y vegeta tio n, different maturities (young, intermediate, mature). These will have an impact on
the effect of the land us e type on the species richnes s. In the calculations, the in tensity of th e land use
type is assumed to be light (not mini mal o r intense). The light intensity allows for relatively high specie s

37

richness, in dependent of the lan d use type it is asso ciated w ith. The resulting est i mate can be r egarded as
relatively cons erv ative since it would be in the lower range of the potential effects o n species richness.
Using these inputs, the intactness of e ach grid cell is computed. The resulting in tactness is weighted with
the species richn ess of the cell and divided by the corresponding area of the cell. In o ther words, if
intactness is consid erabl y impacted in a regi on with ve ry low species richness, the intactness densit y metric
will be compara tively low. The resulting biodiversit y density metric is: intactn ess weighted by species
richness/km 2 .
We use the proc ess-based dynamic global vegetation mo d el LPJmL (Bondeau et al., 2007; Gerten et al.,
2004; Sitch et al., 2003) to estima te land carbon s tocks in vegetation and soils. LPJmL is a gl o bal, grid-based
biogeography – biogeoch emistry model, simula tes terrestrial carbon pools and fluxes and the
biogeographical distributi on of natural vegetation. The representation of agricultural land driven by land
use data all ows for the quantification of the impacts of land u se on water and carbon cycles. Here we used
observation-b ased monthly temperature and cloud cover time series provided by the Climatic Resea rch
Unit (CRU TS version 3.21; see CRU et al., 2 013; Harris et al. , 2014) and monthly gridded precipitation dat a
based o n the Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis Version 6.0 (Becker et
al., 2013; Schneider et al., 2 011). In this study, we calcul ate terrestrial carbon storage as the sum of all
above- and bel o wgroun d carb on stocks in vegeta tion and soil.
LPJmL uses a land us e da ta set based o n the HYDE 3 . 1 that provides gridded cr opland and pasture land use
from 10000 B.C. to 2005 A.D. (K lein Goldewijk et al., 2 011). Detailed informatio n o n the distr ibution of
crop types is taken from Mo nfr eda et al. (Monfreda et al., 2008). In order to run the model until 2010
LPJmL applies linear extrap olation of recent land change dynamics for the years 2006-2010. Updating the
LPJmL land use data with HYDE 3.2 (Klein Goldewijk et al., 2016) or other more recent data sets was not
possible within the scope o f this study. W e were aware that the reduced tempor al coverage may li m it o ur
ability to c apture the most recent and emergin g patterns of d eforestation and other no n-linear changes in
land use. In order to evaluate possible shortcoming s of our analysis due to data used we compared
patterns of expanding hum an land use in the L PJmL da ta with a recent analysis of emerging deforest ation
hot spots (Harris e t al., 2017b).
Figure S4 shows areas with decreasing sha res o f natur al vegetati o n in the LPJmL data colored in shades of
blue. Countries and regi o ns with em erging hot spots of fore st loss sinc e the year 2000 acc o rding to Harri s
et al. (2017b) are highlig hted with a red border. In B razil, both data sets show forest cover l oss in the
Cerrado and the M ata Atla ntica biomes, but LPJmL misses hot spots in the most southern parts of Brazil.
Forest loss in Kalimantan and Sumatra is prevalent in both d ata sets, but the spatial pat terns are differ ent.
This is also caus ed by the diff erent spatial resolution of the two data sets. While Harris et al. (2017b) use
satellite data with 30m resolution, LP J mL uses land use inform ation at a res olution of 0.5° equivalent to
about 5 5k m at the e quat or. Spatial patterns of land u se change will therefore be much more detailed in
Harris et al. (2017b ). In the case of the Dem o cratic Rep ublic of Congo, LPJmL completely misses emerging
patterns of forest loss. While LPJmL assumes slight losses o f natur al vegeta tion in the south, the h ot spo t
analysis of Harris et al. shows new f o rest los s in the n o rthern par t of the country.

38

However, it is also not possible to directl y apply the Global Forest Watch data used by Harris et al. to
improve the L PJmL si m ul at ions, b ecause this d ata does not discriminate between clear cuts, forest
thinning s, and changes in management. Once this inform ation becomes availa ble, it will be possible to
improve the estimates o f carbon st ock changes with LPJmL.

2.4.2. Intensity curves
Intensity curves are constr ucted t o depict the d istribu tio n o f the land use dimens io ns in te r ms of area and
intensity (Fig. 3 o f the m a nuscript). To this end, are a s (in km 2 ) of grid cells that fall into the re spective
intensity bins were aggregated. To m easure the spatial concentrati on o f land use we comput ed the Gini
coefficient of the five dimensions.

2.4.3. Intensity change
Intensity chang e refers to the respecti v e land-use dimensi o n (Table S1) in a grid cell between 2000 and
2010, e.g. the change in population density (populatio n/ km² ) in a grid cell. First, we calculate the intensit y
for each lan d use dimension. Second, we compute th e change for each grid cell between 2000 and 2010.
We calculate bo th relative and absolute int ensity change to identify where and to what extent specific
changes occurred, r espectively ho w much area was af fect ed an d at which magnit ude.

2.4.4. Pr inciple Component Analysis
Principle Component Analysis (PCA) w as performed us ing STATA 14 to identify major underlying patterns
of land-use changes. The PCA is a statistical techniqu e to reduce the dimensions of large datasets by
orthogonal transf ormati ons to a lower-dimensi onal space (Jolliffe, 200 2). Particul arly, we ar e interested in
the first principal componen t which accounts for the largest variance in the data with considering only one
dimension. The first component is the eigenvector of the correlation matrix, which corresponds to the
largest eig envalue. We perform the PCA with STATA 14. The results are shown in Table S2.
The first component Fig. S1a) indicates that the variables can be grouped into those with po sitive signs
(population d ensity, cr op area and liv estock density) a nd with negati v e signs (carbon, biodiversit y). These
two groups have a clear interpretation as the y corres po nd to dir ect human pressures (positi v e sign) and
the nature-related residual (negativ e sign) which mean s that categorizin g dynamics among thi s dimension
allows to explain the l argest share of the variabilit y in the data. Adding additional ort hogonal components
(e.g. component 2, Fig. S1b) would increase explana tory power; the second component is, however,
difficult to int erpret. We therefore restrict only to the first co mponent, which has high statistical power as
well as a cl ear interpr etatio n.
In order to visuali ze o verall lan d- use dynamics ac cordin g to the first principal co m ponent (th e ‘human - vs -
nature’ di m ension), th e corresponding eig envec tor is m ultiplied with the nor malized data. The

39

normalization to zero mean and o ne standard deviation v arianc e is necessary to convert the different
variables and dimensi ons to one comparable m etric. The resulting scores indica te whether overall land-
use changes are related to human drivers (high positive scor e) or to the nature residual (large negative
score). As the s cores result from the normaliz ed data, they m ust be interpreted rel ative to the overal l land -
use dyna mics. Hence, a neg ativ e score doe s no t m ean that nature-related land-use chan ges are ‘str onger’
than human-r elated land-use changes. Rather, large positive and negative values indicate regions where
human or natural force s are particular l y strong.
For interpretati o n and in-depth understanding of observed co-occurring global land us e change between
2000 and 2010, we perform an in -depth literatur e research on regional driver s of land-use dynamics,
explaining hotspots and their regi onal and global rele vance (se e SI and ass ociated online mat erial).

2.4.5. Land embodied in cr op trade
Our detailed spatial analysis focuses o n local dyna mics. For discussing the results, referring to spatial
linkages particularly throug h trade is useful because trade in agricultural products links local land-use
decisions to far-distant or g lobal demand chang es. Trade in agricultural p roducts involves im plici t trade o f
the produc tio n factors that are used t o produc e th e trad ed go od. The concept of fa ctors embodied in tr ade
is particularly used for analyzin g virtual water trade (Dalin et al., 2012; Hoek stra and Hung, 2005), carbon
emissions embodied in trade (Peters and Hertwich, 2008) and, m ore recently, also for quantifying crop
land that is associated to trade (Kastn er et al. , 2 014). B ased on bilat eral virtual land trade data (Kastner et
al., 2014), we cal culate in Table S3 th e share of the cro pland in our w o rld regi o ns that is associated t o net
exports in the yea rs 2000 a nd 2009. The Oc eana regi on is, for example, a large lan d expo rter as roug hly 70
% of the cropland is asso cia ted to net export s of crops. Hence, local land-use dynamics can b e expected to
be strongly influenced by international m arkets. Contrary, Sub-Saharan Africa, South-Eastern Asia and
Southern Asia are largely lan d self-sufficient. Note that this can be consisten t with large food trade flows
(as we look only on exp orts net of imports) and trade deficits or surpluses which are measured in monetar y
terms an d q uantities of par ticular food ite ms (and no t land ). Fin ally, Europe, Eastern Asia an d Mid dle Eas t
and North Africa rely on larg e land im ports. For these three regions, dependen cy on im p orted land ha s
substantially incr eased.

40

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48

2.5 Suppleme ntar y Infor mation

49

Supp lementary Infor mation Guide

This document s entails info rm ation regardin g
Figures S1-4
Tables S1-7
Supp lementary Infor mation text

50

2.5.1. Figure s

Figure S1 – Princ ipal Co mponent Analysis. This figure cont ains maps of th e Z -scores o f the PCA for a) component 1
b) component 2. Z -scores are calculated as the p roduct of th e eigenvectors from the PCA with the standardized data
of intensity chang es. They show the r eduction of th e und erlying data to th e lo wer -dim ensional space (h ere: two
dimensions as we consider only t h e first two components) while maintainin g highest explan a tory po wer.

51

Figure S2 – Shi ft d iagrams. The shift diagram s depict the frequency distribu tion in terms of area of the in tensity
changes bet ween 2000 an d 2 010 from negative (on the left) to posit ive (on the right) for a) population density; b)
livestock d ensity; c) crop land area fraction; d) carb on stock; e) Intactness. The gr ey b ar represent s the area without
notable chan ges.

52

53

Figure S3 – In tensity change maps. The following maps show th e spatial distribution of th e areas in intensity b ins of
interest (red boxes ) as identified in Fig. 3 o f the manuscri pt. a) Pristine land take: Change in pop ulation d ensit y
between 2000 and 2010 in low density areas (pop ulation d ensity <25 pop/km2); b) Urbanization: Cha nge in
populat ion density between 2000 and 2010 in high density area s (pop ulation density >900 po p/km2); c)
Intensification in peripher al are as: Cha nge in live stock d ensity b etween 2 000 an d 2010 in lower density are a s
(livestock den sity >25 and <30 LU/km2); d) Intense husbandry: Cha nge in livestock density between 20 00 an d 2010
in higher density area s (livest ock density >90 LU/km 2); e) Exp ansion in LAM, SSA and SEA: Chan ge in cropland area
fraction between 2000 and 2 010 in areas with m edium to good suitability (suitability index >50 and <7 5); f) Cropland
ab andon ment in OECD countr ies: Chan ge in croplan d area fraction between 2 000 an d 2 010 in ar eas with medium
to high suitability (suitability >80); g) Incre ase in ice -free a reas: Change in carbo n stock b etween 2000 and 2010 in
areas with low carbon stock (t C/ha <80); h) Incr ease in boreal areas: Change in carbon s tock between 2000 an d 2010
in areas with medium carbon stock (tC/ha >400 and <500); i) Human pressures: Cha nge in intactness density b etween
2000 an d 2010 in ar eas with medium intactne ss density (intac tness weighted with spec ies richn ess/km2 >0.05 and
<0.15).

Figure S4. Compar ison of L JP with defore station hotsp ots. Blue areas d enote a reducti on of v egetatio n betw een
2000 and 2010 a ccording to LPJ. Red ar eas denot e deforestation hotspots betw een 2 0 00 and 2014 accordin g to
Harris et al. ( 2017) , in cluding deforestation dy namics after 2010. LPJ likely underestimates d eforestation loss due to
deforestation, espe cially in Co ngo.

54

2.5.2. Tables

Table S1 – Over view over d atasets. Dat a selection i s based o n quality and availability for th e year 2 000 and 2010.
Modelled data is only used if alt ernatives were unavailabl e.

Name of
dataset

Reso
lution

Commen ts

Units

Poin
ts in
time

Source/ Link

Population

SEDAC’s
Gridded
Population of
the World
(GPW), v3
(Center for
Internation al
Earth Science
Information
Network -
CIESIN -
Columbia
University
and Centro
Internacional
de
Agricultura
Tropical -
CIAT, 2005)

50x5
0km
(5x5km
possibl
e)

The projected
grid for 201 0
was produced in
collaboration
with the United
Nation s Food
and Agricultu re
Program (FAO)
as Population
Count an d
Density Grid
Future
Estimates.

Total
populat ion,
Population
density
(pop/km 2 )

2000
and
2010
(projec
ted)

(Gridded Popul ation
of the World, Version
3 (GPWv3): Population
Count Grid. Palisades,
NY: NASA
Socioeconomic Data
and Applicati ons
Center (S EDAC).
http://dx.doi.org/10.7
927/H4639MPP .
Accessed, Jan 2016)
(We used Ver sion
v3 which got
recently updat ed to
v4 in June 2016.)

Livestock

Gridded
Livestock of
the World
(GLW)
(Robinson et
al., 2014;
Wint et al.,
2007)

5x5
arc-
minute

Aggregate
Livestock units
compromise
different
livestock types

Livestock
units, livestock
density (LU/k m 2 )

2000
and
2005

http://www.fao.org
/ag/againfo/resources
/en/glw/GLW_dens .ht
ml

Cropland

History
Database of
the Global
Environment
(HYDE) (Klein
Goldewijk et
al., 2011);

Global
Agro-
Ecological
Zones (GAEZ)
(IIASA, 2012)

0.5x
0.5
degree

HYDE data i s
based on FAO’s
categories
‘Arable land a nd
permanent
crops’

GAEZ
suitability for
cereals only,
high inpu t level

Crop area
fraction, i.e.
percentage of a
grid cell

Suitability
Index [from 0- 1]

2000
and
2010

2000
(for
suitabil
ity)

ftp://ftp.pbl.nl/hyde
/hyde3.2/

http://themasites.p
bl.nl/tridion/en/them
asites/hyde/

http://gaez.fao.org/
Main.htm l#

55

Carbon
Storage

Lund -
Potsdam-
Jena
managed
Land mod el
(LPJ)
(Bondeau et
al., 2007)

0.5x
0.5
degree

Modelled
data.

tC stored
(total, an d per
ha)

2000
and
2010

https://www.pik -
potsdam.de/r esearc
h/projects/acti vities
/biosphere-wat er-
modelling/lpjml

Biodiversity

Predicts
database
(Hudson et
al., 2014)

Newbold
et al.
(Newbold et
al., 2015) (SI)

LUHa_u2t1
Land Use
Harmoni-
zation (Hurtt
et al., 2011)

See SI text for
further
explanation on
data p rocessing.
Partially, p re-
processed data
by Newbold et
al.

Species
Richness

Intactness

Land Uses

n/a

n/a
2000
and
2010

http://www.predi ct
s.org.uk/

http://www.biodive
rsityin fo.org/spcdownl
oad/r5h8a1/

http://www.nature.
com/nature/journal/v
520/n7545/full/nature
14324.html

http://tntcat.iiasa.a
c.at/RcpDb/dsd?Acti o
n=htmlpage&page=ab
out

Land
embodied in
trade

Kastner et
al, 2014
(Kastner et
al., 2014)

Coun
try
level

Used to
account for
teleconnected
land u ses

Net share of
croplands u sed
for exports

2000
and
2009

Data (Kastner et
al, 2014(Kastner et
al., 2014)(SI)):
http://iopscienc e.io
p.org/1748-
9326/9/3/034015 /
media

Land
footprint

Weinzettel
et al, 2013
(Weinzettel
et al., 2013)

Coun
try
level

Used for Fig.
5

global
hectares (gha)
per capita

2004

http://www.scien
cedirect.com/sci enc
e/article/pii/S0 9593
78012001501

56

Table S2 - F irst two c omponents (eigenvecto rs) of the Principle Co mponen t Analysis. The eigen vector with the
highest eigenvector i s th e p rinciple co mponent which give s a one -dim ensional reductio n of the d ata that explain s
the highest share o f the varia tion . Addin g further eigenvectors allo ws to accou nt for more variability (b ut increases
also dimensionality ). The eige nvectors are used t o calculate the z -scores.

Variable

Compon ent 1

Compon ent 2

Unexplained

Population

0.2671

0.7195

0.3 801

Carbon

-0.276

0.68 49

0.4227

Crop area

0.5239

-0.0679

0.6218

Livestock

0.5666

-0.0232

0.5625

Biodiversity

-0.507

-0.0898

0.642

57

Table S3 - Cropland associated to trade (net exports) as a s hare of the cropland under domestic p roduction [in %].
(a ) relative to tota l regional cro pland in 2000. (b ) relative to total regional crop land in 2009. N umbers are calculated
using detailed cou ntry data from the Supp lementary Appendix in Kastner et al. (2014) which con tains land embedded
in crop trad e f lows. As d ata for 2009 is th e most rec ent a vailable, we use 200 9 data in stead of 201 0. Entrie s are
ordered according t o the largest change s between 2009 an d 2000 (last colu mn). Positive (negative) nu mbers for the
year 2000 and 2009 ind icate th at a country is a n et lan d exporter (importer), with the net export share of land on
total cropland represented by the respective e ntri es. The last column show s the change o f the lan d n et export share.

Region

2000

2009 (a)

2009 (b)

Change (2000 vs
2009 (a))

Latin an d Central
America

14.0

37.8

31.2

23.8

Eastern Eu rope &
Central Asia

2.3

17.9

16.7

15.7

Oceania

68.1

71.0

62.6

2.9

South-Eastern
Asia

4.1

3.6

3.0

-0.5

Sub-Saharan
Africa

3.6

2.9

2.4

-0.7

Southern Asia

-0.3

-3.4

-3.2

-3.0

North America

33.9

30.9

31.8

-3.1

Eastern Asia

-21.4

-31.7

-30.0

-10.3

Europe

-39.5

-50.3

-53.0

-10.8

Middle East an d
North Africa

-36.8

-53.9

-52.0

-17.1

58

Table S4 - R egional overview over gain/loss per land use dimen sion in hotspots (top 10%) between 2000 and 2010
(2000 and 2005 for livesto ck). Un its used are 1 ) Popu lation (Pop ): populat ion/km2 (density) an d million people
(total); 2) Livestock (Li vest): livestock u nits/km2 (density an d million livestock units (t otal); 3) Croplan d (C rop):
cropland ar ea fraction (% of crop land in a grid ce ll, density) an d ‘000 km2 (total); 4) Ca rbon: tC/ha (density) and
megatons Carbon (to tal); 5) Biodiversity: In tactness/km2 (weight ed with species richn ess, density) an d Intactn ess
weighted with spe cies richne ss (total).

Top
10%

Dime
nsion

Share
of area
wit h
gain

Avera
ge
density
2000

Avera
ge
density
2010

Densi
ty 2010
–
density
2000

Chan
ge in
intensit
y (%)

Avera
ge
density
change
for
areas
with
gain

Share
of
global
area
with
gain

Avera
ge
density
change
for
areas
with
loss

Share
of
global
area
with
loss

Eas ter
n Asia

Pop

59%

505.7

556.8

51.1

10%

117

14%

- 19

30%

Livest

98%

52.1

59.5

7.3

14%

32

26%

0

1%

Crop

0.6

0.5

-0.1

- 11%

0

0%

- 34

4%

Carbo
n

20%

280.7

274.4

-6.3

- 2%

238

1%

- 919

5%

Bio

0.109

0.103

0.0

- 5%

0

0%

-7

4%

Easter
n
Europe
&
Central
Asia

Po p

37%

256.1

245.8

-10.2

- 4%

7

1%

-9

14%

Livest

35%

22.5

20.9

-1.6

- 7%

2

2%

-4

13%

Crop

7%

0.5

0.4

-0.1

- 18%

2

0%

- 31

4%

Carbo
n

60%

294.5

298.0

3.5

1%

382

2%

- 240

1%

Bio

3%

0.117

0.111

0.0

- 5%

0

4%

-7

5%

Europ
e (exc l.
Eastern
Europe)

Pop

60%

463.2

470.3

7.1

2%

6

1%

-4

5%

Livest

6%

72.2

65.9

-6.3

- 9%

0

0%

-4

14%

Crop

1%

0.5

0.4

-0.1

- 17%

0

0%

- 25

3%

Carbo
n

89%

162.4

170.2

7.8

5%

241

1%

- 36

0%

Bio

10%

0.104

0.097

0.0

- 7%

0

6%

-5

3%

Latin
America

Pop

100%

294.8

342.5

47.7

16%

54

6%

0

0%

Live st

94%

40.8

47.5

6.7

16%

28

23%

-1

4%

Crop

96%

0.4

0.5

0.1

24%

146

16%

-4

0%

Carbo
n

54%

261.9

261.9

0.0

0%

2,905

12%

-
3,178

17%

Bio

0.171

0.165

0.0

- 3%

0

1%

- 28

19%

West
ern Asi a
and
Nort her
n Afri ca

Pop

99%

216.9

264.0

47.1

22%

56

7%

0

1%

Livest

9 6%

37.1

42.1

5.0

13%

4

3%

0

0%

Crop

46%

0.4

0.4

0.0

- 4%

15

2%

- 19

2%

Carbo
n

9%

131.2

122.0

-9.1

- 7%

9

0%

- 126

1%

Bio

11%

0.083

0.079

0.0

- 5%

0

3%

-1

1%

Nort h
America

Pop

100%

414.5

459.5

45.0

11%

18

2%

0

0%

Livest

99%

56.3

60.8

4.5

8%

1

1%

0

0%

Crop

1%

0.7

0.6

-0.1

- 14%

1

0%

- 158

20%

Carbo
n

92%

244.9

253.0

8.2

3%

1,327

6%

- 159

1%

Bio

0.105

0.099

0.0

- 6%

0

0%

-1

1%

Ocea
nia

Pop

100%

251.0

283.3

32.3

13%

2

0%

0

0%

Livest

28%

63.0

62.9

-0.1

0%

0

0%

0

1%

Crop

0%

0.5

0.4

-0.1

- 16%

0

0%

- 19

2%

Carbo
n

79%

311.6

321.2

9.7

3%

852

4%

- 178

1%

59

Bio

0.118

0.113

0.0

- 4%

0

0%

-1

0%

South
-Eastern
Asia

Pop

99%

322.8

370.9

48.2

15%

61

7%

-1

1%

Livest

97%

27.7

33.4

5.7

21%

5

4%

0

1%

Crop

100%

0.3

0.4

0.1

27%

111

12%

0

0%

Carbo
n

81%

302.6

311.2

8. 5

3%

1,537

7%

- 492

3%

Bio

0.181

0.175

0.0

- 3%

0

0%

-6

4%

South
ern Asi a

Pop

100%

357.4

420.6

63.2

18%

243

29%

0

0%

Livest

73%

71.8

74.0

2.3

3%

3

3%

-1

4%

Crop

99%

0.4

0.5

0.1

17%

13

1%

0

0%

Carbo
n

43%

189.3

188.4

-0.8

0%

74

0%

- 120

1%

Bio

2%

0.1 04

0.096

0.0

- 8%

0

4%

- 18

12%

Sub-
Saharan
Afric a

Pop

99%

131.5

170.4

39.0

30%

128

15%

-1

2%

Livest

99%

33.7

40.7

7.0

21%

13

11%

0

0%

Crop

93%

0.4

0.4

0.1

23%

232

26%

- 14

2%

Carbo
n

29%

208.0

201.8

-6.1

- 3%

932

4%

-
2,894

16%

Bio

4%

0.168

0.162

0.0

- 4%

0

6%

- 13

8%

60

Table S5 - Regional over view over gain/loss per land use dimension (top 80%) between 2000 and 2010 (2000 and
2005 for livestock). Unit s u sed are 1) Po pulation (Pop ): p opulation/km2 (density) and million people (total); 2)
Livestock (Li vest): livestock un its/km2 (density and million livestock units (to tal); 3) Cropland (Crop): croplan d area
fraction (% o f cropland in a grid cell, dens ity) and ‘ 000 km2 ( total); 4) Carbon: t C/ha (dens ity) and megaton s Carbon
(total); 5) Biodiversity: Intactness/km2 ( weighted with species richness, density) and Inta ctness weighted with
species richness (tota l).

Top
80%

Dime
nsion

Share
of area
with
gain

Avera
ge
density
2000

Avera
ge
density
2010

Densi
ty 2010
–
Density
2000

Chan
ge in
intensit
y (%)

Avera
ge
density
change
for
areas
with
gain

Share
of
global
area
with
gain

Avera
ge
density
change
for
areas
with
loss

Share
of
global
area
with
loss

Easter
n Asia

Pop

63%

154.2

164.4

10.3

7%

126

15%

- 29

44%

Livest

82%

22.5

25.4

2.9

13%

36

30%

-2

7%

Crop

2%

0.2

0. 2

0.0

- 10%

1

0%

- 152

19%

Carbo
n

38%

173.5

172.1

-1.4

- 1%

1,127

5%

-
2,520

14%

Bio

3%

0.095

0.094

0.0

- 2%

0

1%

- 13

9%

Easter
n
Europe
&
Central
Asia

Pop

17%

22.1

21.3

-0.8

- 4%

11

1%

- 21

32%

Livest

27%

4.3

4.0

-0.3

- 7%

4

4%

-9

29%

Crop

20%

0.3

0.3

0.0

- 5%

22

2%

- 128

16%

Carbo
n

69%

426.2

427.5

1.3

0%

3,804

16%

-
1,494

8%

Bio

5%

0.112

0.111

0.0

- 1%

1

16%

- 20

13%

Europ
e (excl.
Eastern
Europe)

Pop

34%

104.3

104.8

0.5

0%

10

1%

-8

13%

Livest

24%

24.8

23.4

-1.3

- 5%

1

1%

-6

21%

Crop

43%

0.2

0.2

0.0

- 3%

12

1%

- 40

5%

Carbo
n

84%

208.9

211.8

3.0

1%

1,286

5%

- 166

1%

Bio

48%

0.094

0.092

0.0

- 2%

1

17%

-6

4%

Latin
America

Pop

85%

35.9

40.8

5.0

14%

77

9%

-2

3%

Livest

80%

15.4

17.1

1.7

11%

36

30%

-3

10%

Crop

74%

0.1

0.1

0.0

13%

258

29%

- 38

5%

Carbo
n

52 %

192.8

193.0

0.2

0%

5,517

23%

-
5,438

29%

Bio

4%

0.164

0.162

0.0

- 1%

1

11%

- 42

28%

West
ern Asi a
and
Nort her
n Afri ca

Pop

98%

39.9

47.9

8.0

20%

76

9%

-1

2%

Livest

88%

9.4

10.1

0.7

7%

7

6%

-1

3%

Crop

39%

0.2

0.2

0.0

- 2%

39

4%

- 53

7%

Carbo
n

32%

47.2

46.4

-0.8

- 2%

214

1%

- 641

3%

Bio

3%

0.054

0.053

0.0

- 2%

0

4%

-6

4%

Nort h
America

Pop

88%

38.9

42.3

3.4

9%

28

3%

0

1%

Livest

54%

6.8

6.9

0.1

2%

3

2%

-1

4%

Crop

17%

0.3

0.2

0.0

- 10%

15

2%

- 248

31%

Carbo
n

72%

336.1

338.7

2.7

1%

4,598

20%

-
1,005

5%

B io

9%

0.105

0.105

0.0

0%

0

2%

-5

3%

Ocea
nia

Pop

92%

17.7

19.9

2.2

12%

4

0%

0

0%

Livest

28%

7.7

7.4

-0.3

- 4%

0

0%

-2

6%

Crop

16%

0.2

0.2

0.0

- 11%

2

0%

- 56

7%

Carbo
n

44%

97.4

98.7

1.3

1%

1,413

6%

- 853

5%

61

Bio

46%

0.074

0.074

0.0

- 1%

0

7%

-4

2%

South
-Eastern
Asia

Pop

94%

134.9

153.7

18.8

14%

72

9%

-1

1%

Livest

90%

10.3

11.7

1.4

14%

9

7%

0

2%

Crop

93%

0.2

0.3

0.0

18%

168

19%

-4

0%

Carbo
n

73%

271.5

276.3

4.8

2%

2,282

10%

- 749

4%

Bio

2%

0.149

0.147

0.0

- 2%

0

1%

- 10

7%

South
ern Asi a

Pop

100%

221. 0

259.7

38.8

18%

254

30%

0

0%

Livest

51%

37.1

37.2

0.1

0%

5

5%

-4

15%

Crop

30%

0.4

0.4

0.0

0%

33

4%

- 37

5%

Carbo
n

60%

70.1

70.7

0.6

1%

638

3%

- 417

2%

Bio

31%

0.092

0.089

0.0

- 3%

1

28%

- 20

13%

Sub-
Saharan
Afric a

Pop

94%

34.9

44.5

9.5

27%

173

21%

-3

4%

Livest

71%

10.0

11.1

1.1

11%

20

16%

-1

4%

Crop

82%

0.1

0.2

0.0

18%

354

39%

- 31

4%

Carbo
n

42%

144.0

142.6

-1.5

- 1%

2,570

11%

-
5,092

28%

Bio

1%

0.121

0.119

0.0

- 1%

0

9%

- 25

17%

62

Table S6 – Supporting data for Figure 5 of the manuscript. N umbers on the share o f croplands used for exports ar e
calculated using detailed country data f rom th e Sup plementary Appendix in Kastner et al. (2014) whi ch contains land
embedded in crop trade flows. As data for 2009 is the mo st recent available, we use 2 009 d ata instead o f 2010.
Entries are ord ered according to ta ble S3. Positive (negativ e) numbers for the year 2000 an d 2009 ind icate that a
country is a n et lan d exporter (importer), with the n et expo rt share o f land on total cropland represented by the
re spective entrie s. Population d ensity growth is comp uted from GPW data (Center for Internation al Earth Science
Information Network - CIE SIN - Columbia University an d Centro Internacional de Agricultura Tropical - CIAT, 2005) .
The land us e footprint is ba sed on dat a from Weinzett el et al. (2013) . South-Eastern A sia and Eastern Asia a further
supplemented with d isaggregated co untry level data o n Indonesia, China, a nd Japan.

Region

Share of cropland s
used for ex ports (net)

Share of cropland s
used for exports ( net)

Population de ns ity
growth

land use footp r int

2000

2009

in %

(global h ectar e s per
capit a)

Latin and Centr al
America

14

38

14

1.7

Eastern Europe &
Central Asia

2

18

-4

1.4

Oceani a

68

71

12

3.4

South-Easter n Asia

4

4

14

0.8

Indonesi a

5

16

12

0.8

Sub-Saharan Afric a

4

3

27

1.2

Souther n Asia

0

-3

18

0.5

Nort h America

34

31

9

3.6

Eastern Asia

- 21

- 32

7

0.9

China

-6

- 19

7

0.8

Japan

- 554

- 486

1

2.0

Europe

- 40

- 50

0

2.7

Nort h Africa and
Wester n Asia

- 37

- 54

20

1.1

63

Table S7 – Overv iew over refe ren ces from Table 2 of the man uscript. The list is non exhaustive an d on ly lists the
references fro m Table 2 of th e manuscript. Add itional references can be foun d in the Supplementary Information
Text, which pro vides a more d etailed overview over the diffe rent world re gions.

World region

Key referenc es from tabl e 2

Multi ple regions

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land r equirements for food. Proc. N atl. Acad. Sci. 109, 68 68 – 6872 ( 2012).
Chaudhary , A. & Kastne r, T. Land use biodi versity impacts embodi e d in internat ional food trade. G lob.
Environ. Chan ge 38, 195 – 204 ( 2016) .
West, P. C. e t al. Le verage p oint s for improving global food securit y and the envi ronment. Science 345,
325 – 328 (201 4).
Weinze ttel , J., Hert wich, E. G., Pete rs, G. P., Steen-Olsen, K. & Galli, A. Affl uence drives t he globa l
displ acement o f land use . Glob. Environ. Change 23 , 433 – 438 (2 013).
Bren d’Amour, C., Re itsma, F., Bai occhi , G., Bart hel, S., Gün eralp, B ., Erb, K. - H. , Haber l, H., Cre utzi g, F.,
Seto, K.C., 2017. Future urban land expansio n and impl ications for globa l croplan ds. Proc. N atl.
Acad. Sci. 114, 8 939 – 8944.

Europe w/o East ern
Europe

van Vli et, J., de Groot, H., Ri etve ld, P. & Verbur g, P. H. Manif estations a nd under lying dr iv ers of
agricul tural land use c hange in Europe. Landsc. Urb an Pl an. 133, 24 – 36 (2015).
Kuemmerl e, T. et al. Ho tspot s of L and Use Change in Europe. Enviro n. Res. Let t. 11, (2016).
Galli , A. et al . Mediter ranean countries’ food consumpt ion an d sourci ng patterns : An Ecologic al
Footpr int viewpo int. Sc i. Total Environ. 578, 38 3 – 391 (201 7).

Eastern Europe a nd
Central Asia

Kuemmerl e, T. et al. Ho tspot s of L and Use Change in Europe. Enviro n. Res. Let t. 11, (2016).
Alcantar a et al. Mapping the extent of aband oned f armland i n Central a nd Eastern Eur ope usi ng MODIS
time se ries satellite d ata. Environ. R es. Lett. 8, (2013).
Pan, Y. et al . A Large and Persist ent C arbon Sink i n the Worl d’s Forest s. Science 333, 988 – 99 3 (2011).
Schier horn, F. et a l. Post-Sovi et cropland ab andonment and car bon se questrat ion in Euro pean R ussia,
Ukrai ne, and B elarus. Glo b. Biog eochem. Cycles 27, 1175 – 1185 ( 2013).
Liang, S. et al. G lobal Driv ers of Russian Timber Harvest. J. Ind. Ecol. 20, 515 – 525 (2016).
Zhu, Z. et a l. Greening of the Ear th and its drivers. Nat. Cl im. Cha nge 6, 791 – 795 (2016).

Souther n Asia

Reddy , C. S. et al. Quant ifi cation and monit oring o f defor estatio n in India over eight d ecades (1930 –
2013). Bio divers. Con serv. 25, 93 – 116 (2015).
Nagendra, H. , Sudhir a, H. S., Katti, M . & Sche wenius , M. in Urban ization, Biodiversit y and Ecosystem
Services: Cha lleng es and Opportuni ties (eds. Elmqvist , T . et a l.) 65 – 74 (Spr inger Ne ther lands,
2013).

South-East Asia

Hosonuma, N. et a l. An asse ssment o f def orestat ion and fo rest degradat ion driv ers in de veloping
count ries. Environ . Res. Lett . 7, 044009 (2012).
Wilcov e, D. S., Giam, X., Edwards , D. P., Fishe r, B. & Koh , L. P. Navjot’s nigh tmare revisit ed: logging,
agricul ture, a nd bio diversity in Sout heast Asia. Trends Ecol. Evol. 28, 531 – 540 ( 2013).

64

Stibig, H.- J., Achar d, F., Carbo ni, S., R aši , R. & Mi etti nen, J. Change in tropi c al for est cov er of Sout heast
Asia fr om 1990 to 2010. Bi ogeo sciences 11, 247 – 258 (20 14).
Davis, K. F., Yu, K., Rul li, M. C., Pichd ar a, L. & D’Odor ico, P. Acceler ated deforest at ion dr iven by l a rge-
scale land ac quisitions i n Cambodia. Na t. Geosci . 8, 772 – 775 (2015).
Huijnen, V. et a l. Fire carbo n emissions ove r marit ime sout heast Asia i n 2015 largest sinc e 1997. Sci.
Rep. 6, 26886 ( 2016).
Schneide r, A. et al . A new ur ban lan dscape in East – Southe ast Asia, 2000 – 2010. Environ . Res. Lett. 10,
034002 (2015) .
Thornto n, P. K. Livest ock p roducti on: recent trends, f uture pr ospects. Philos. Trans. R. So c. B B iol. S ci.
365, 2853 – 28 67 (2010).

East Asia

Chen, J. Rap id urban ization in China : A real chal lenge t o soil prot e ctio n and food security . CAT ENA 69,
1 – 15 (2007).
He, C., Liu, Z ., Tian, J. & Ma, Q. Urban expansion dynamics and nat ural habitat l oss in China : a
multisc ale l andscape pe rspecti ve. Glob. Chan ge Biol . 20, 2886 – 2902 (2014) .
Liu, X. et al . Rubbe r plantat ion and it s relations hip wit h topograp hical fac tors in the border region of
China, Laos and Myan mar. J. Geog r. Sci. 23, 1019 – 104 0 (2013).
Calle, L. et a l. Regional carbon fluxes from l and use a nd land cover c hange in Asia, 1980 – 2009. Envi ron.
Res. Lett . 11, 074011 (201 6).
Deng, L., Liu, G. & Shangguan, Z. La nd - use conve rsio n and changing so il carbon stoc ks in China’s ‘Grain -
for- Gre en’ Program: a sy nthesi s. Glob. Change B i ol. 20, 3544 – 3556 ( 2014).
Zhang, M. et al . Impact o f land use t ype conve rsion on carbon st orage in terr estrial ecosyst ems of
China: A spat ial-tempor al perspectiv e. Sci. Rep. 5, 10233 (2015).
Bai, Z. H. et a l. Changes in Pig Product ion in China a nd Their Effects on Ni t rogen and Phospho rus Us e
and Lo sses. Environ. S ci. Techno l. 48, 12742 – 127 49 (2014).

Nort h Africa and Wester n
Asia

Bren d’Amour , C., Wenz, L., Kalkuhl, M., Stec kel, J . C. & Creutz ig, F. Teleconn ecte d food su pply shock s.
Environ. R es. Lett . 11, 035007 (201 6).
Şekerc ioğlu, Ç. H. et al . T urke y’s global ly impor tant biodiversity i n crisis. Biol. Con serv. 144, 2752 – 27 69
(2011).
Odhiambo, G. O . Water s carci ty in the Arab ian Peni nsula and socio-economic i mplicat ions. App l. Water
Sci. 1 – 14 (2016). doi:10.10 07/s13201- 016 -0440- 1.
Galli , A. et al . Mediterr anean count ries’ food co nsumpti on and sour cing patter ns: An Ecol ogical
Footpr int viewpo int. Sci . T otal Envir on. 578, 383 – 391 (201 7).
Galli , A., Halle, M. & Gr unewald, N . Physi cal limits to reso urc e acc ess and utilisatio n and thei r economic
implicat ions in Mediterr anean economies. Env iron. Sc i. Polic y 51, 125 – 136 ( 2015).
Galli , A. On the rational e and policy usef ulness of Ecologic al Footpri nt Accounting: The c ase of
Moroc co. Envi ron. Sci . Policy 48, 210 – 224 (2015).

Sub-Saharan Afric a

Buhaug, H. & Urdal, H. An urbani zati on bomb? Populat ion gro wth and so ci al di sorder i n citie s. G lob .
Environ. Ch ang e 23, 1 – 10 ( 2013).

65

Holden, S. T. & Otsu ka, K. The ro les o f land te nure ref orms and land markets in the cont ext of
populat ion growth and land us e intensification in Africa. Food Policy 48, 88 – 97 (2014).
Liebe nberg, F. & Pardey, P . G. in The Sh ifting Patterns o f Agricult ural Producti on and Productivit y
Worldwid e. (The Mi dwest Agri business Tr ade Re search and Informati on Center, Io wa State
Univer sity, 2010).
Jayne, T., Cha m berl in, J. & Heade y, D. D. Land pr essures, the evo lution of farming sy stems, and
devel opment s trategies in Afric a: A synthesi s. Food Policy 48, 1 – 17 (2014).
Searchi nger, T. D. et al . High carbo n and bi odiv ersity cost s from conv er ting Afr ica/ ’s wet s avannahs to
cropl and. Nat . Cl im. Chan ge 5, 481 – 486 (2015).
Ciais, P. et al . The carbo n balance of Africa: s ynthe sis of rece nt research studies. Phil os. Trans. R . Soc.
Lond . Math. Phys. Eng . Sci. 369, 2038 – 2057 (2011).
Barre tt, C. B. Smallhol der marke t par ticipation: Concept s and e vidence from east ern and southe r n
Afric a. Food Pol icy 33, 299 – 317 (2008).
Kalkuhl , M. in Foo d Price Vol atilit y and Its Impl ication s for Food Securit y and Policy 269 – 301 (Springer,
2016).

Oceani a

Gallan t, A., Kiem, A., Ver d on -Kidd, D., Stone, R . & Karoly , D. Underst anding hydroc limate p rocesses in
the M urray-Dar ling Basin f or natural resources management. Hydrol. Eart h Syst . Sci. 16,
2049 – 2068 (2 012).
MSEIC. Austral ia and Food S ecurit y in a Changin g World . (The Pr ime Mini s te r’s Science , Engineeri ng
and Innov ation Council, 2010).
Steff en, W. et al. Aus tral ia’s biodiv ersity and c limate change: a strat eg ic a ssessment of the vulne rab ili ty
of Aust rali a’s biodiversi ty to climate change. (2009).

South and Central
America

Lapola, D. M . et al . Pervasi ve transiti on of the Brazilian l and- use syste m. Nat. Cli m. Chang e 4, 27 – 35
(2014).
Grau, H. R. & Aide , M. Gl obali zatio n and land-use tr ansitio ns in Latin America. Ecol. Soc. 13, 16 (2008).
Nepst ad, D. et al . Slowing Amazon defo restatio n through publ ic poli cy and interv entions in be ef and
soy sup ply c hains. Science 344, 1118 – 1123 (2014).
Kastner , T., Erb, K.-H. & Habe rl, H. Ra pid growth i n agricul tu ral trad e: effects o n global area efficiency
and the role of management. Enviro n. Res. Let t. 9, 034015 (201 4).
Gasparr i, N. I. & Grau , H. R. Defo rest ation and fragmentatio n of Chac o dry forest in NW Argentina
(1972 – 2007). For . Ecol. Manag . 258, 913 – 921 (200 9).

Nort h America

Sleete r, B. M. et al. Land -cover c hang e in the c onter minous Un ited States from 1973 to 2000. Gl ob.
Environ. Ch ange 23, 733 – 748 (2013).
Wright, C. K. & Wimberl y, M. C. Rece nt land use c hange in the Wester n Corn Bel t threatens grasslan ds
and wetl ands. Proc. Natl. Acad . Sci. 110, 4134 – 413 9 (2013).
Lark, T. J., Salmon , J. M. & Gibbs, H. K . C ropl and expansion o utpaces agri cultural and biofuel policie s in
the Uni ted States. Environ. R es. Lett . 10, 044003 (2015) .
Mladeno ff, D. J., Sahajpal, R., Jo hnson, C. P. & Rot hste in, D. E. Rec ent L and Use Change to Agri cult ure i n
the U.S. Lak e State s: Impacts on Cell ulosic Bio mass Potent ial and Natural Lands. PLOS ON E
11, e0148566 (2 016).

66

Wallande r, S., Claassen, R . & Nick erson, C. The eth anol decad e: an expansion of US corn production ,
2000 - 09 . (201 1).
Faber, S., Rundq uist, S. & Male , T. Plo wed under: how c rop su bsidies c ontribute t o massive habitat loss .
(Enviro nmental Worki ng Group, 2012) .

67

2.5.3. Suppleme ntary In formation te xt
Here we pr o vide an in-d epth overvi ew over region-specifi c land-use dyna m ics as s umm ariz ed in Table 2
of the manu script. This inf ormati on can also b e found on the website.

Region-specifi c analys i s
The following includes a descrip tion of obser v ed land- use dynamics in the 10 world regions anal y sed. If
not indicated o therwise, da ta reported refer to Table S 5.

Sub-Saharan Afr i ca
Description of key dynam ics
Sub -Saharan Africa experiences large changes over all land-use dimensions and could therefore be
considered as a m ajor hotspot region. Generall y , pop ulation density shows increasing trends, in particu la r
in co astal areas in West Africa as well as large parts of Nigeria, Ghana and Burkina Faso and East -Africa n
countries like Ethiopia, Uganda and Rwand a. Livestock density increased particular ly in East Africa
(Ethiopia, Uganda, Kenya and Rwanda) as well as Burkina Faso in West Africa. Cropland grew strongly in
the Guinean Savannah regions o f West Africa, East Africa as well as Southea st Africa and decreased
particularly in South Africa. 38% o f the world’s cropla nd ex tensific ation happene d in Sub-Saharan Africa.
Carbon density shows mixed and dispersed dynamics with mostly decreases in th e Guin ean Savannah and
increases in tropical forest areas. 28% of the global net reduc tion in terr estrial carbon happened in Sub -
Saharan Africa. Biodi versity decreases in most areas except some c oastal areas in Nigeria as well as parts
of Togo, Uganda, R wanda and Buru ndi, which experi enced major increas es.

Main Driver s
Populatio n d ynamics are characterized b y high fertility rat es as w ell as migration from spars ely p o pulate d
rural areas to urban areas (Buhaug and Urdal, 2013). Urbanization in SSA is driven by population growth
in reso urc e constrained rural areas rather than economic growth in cities that attract labour for higher
wa ges (H olden and Otsuka, 2014) .
Land ref orms which giv e private property rights to individuals at the expens e of communal lan d in duced a
structural change in the livestock sector from nomadic pastoralism to more intense agricultural and
livestock syste ms (Andela and van der Werf, 2014). L ike other devel oping countries, Africa also
experiences stronger dem and increases for m eat produ cts than d eveloped countries where demand
saturated (Tho rn ton, 2010). Beyond its role f o r income generation and food production , livestock is
considered as asset and insurance in many traditional societies, reflec ting also we alth and social status
(Thornton, 2010).
Regarding the agr icultural land dynamics in S o uth Af rica, the hor ticulture sec tor in creased strongly at the
expense of con ventional staple food production and large commercial farms replaced small-scale and
subsistence farming by in tensified and farming process es (Liebenberg and Pardey, 2010). Th ese processes

68

may explain the redu ction o f cr o pland vi sible, which corr espon ds to nati o nal statistics on croplan d
dynamics (FAOSTAT, 2015). Contrary to South Africa, cropland expanded strongly i n the Guinean Savanna h
regions that are considered as potential breadbasket of Africa (Morris et al., 2009). Roughly two thirds of
the Savannah region coul d be used for agricultur e while only 10% is currently used f o r agricultural
production (Morris et al. , 2009). The in crease in cropland expansion in this area therefore mirr ors not only
the biophysical feasibil ity but also the e conomic attrac tiveness of using the Sa vanna lands for agricultural
production. This attractiven ess is, in turn, als o influe nced by international dem and (high crop prices in
2007/08), changing political and institutional environments (e.g. facilitating foreign land inv estments ,
(Deininger and Byerlee, 2011; Kuusela and Amacher, 2015)) and im pr oved access and infrastructure to
remote areas(Cha mberlin et al., 2014). Recent cross-coun try and household sur v ey evid ence sugg ests tha t
rural population growth is also a driver o f higher cropping intensities (s o- called ‘ Boserupian intensificatio n,
see Jayne e t al., 2014 ).
Above-ground carbon changes are very heterogene o us. Large carbon release s occur in the Savannah
regions which si multaneou sly experienc e cropland expansion. Simul ated conver sion fr om Savannah wet
lands to maize or soyb ean crop la nd indicate major carbon releases (Searchinger et al., 2015). Fires have
been a common tool to convert bushlan d into croplan d as well as grazing land practiced by small -holde r
farmers (Andela and v an der Werf, 2014). Changes in fire incidenc e are, however, also associated to
precipitati on dynamics, in particular the ENSO phen omenon (Andela and v an der W erf, 2014). Globall y,
40% o f fire-rela ted CO2 em issions are linked to Sa v ann ah burnin g and land-use emissi o ns are in SSA hig her
than em i ssions from burning f ossil fuels (Ciais et al., 2011) . Contrary to Savann ah regions, tropical forest
areas sho w increas es in car bon stocks (despite large heter o geneit y). Th e main factors f or increas ed carbon
in SSA forest area s are carbon fer tilization and incr eased precipitation trend s (Ciais et al., 2011) .
Drivers of biod iversi ty cha nges are diffi cult to assess. Reductio ns in intac tness ar e correlated to incr eases
in cropland. As the Savan nah regions are rich in species, cropland expansion may reduce biodiversity
substantiall y (Searchinger et al., 2015). The few and very small hotspots of increasin g biodiversit y are
difficult to explain and we could not find studies provi ding ex planations for these dynamics. On e possible
reason for increa sed biodiversity is the establish ment and improved enforce ment of protec ted areas and
national parks in East Afric an countries that m ay attra ct further wildlife as a ‘ save haven’.

South-East As i a
Description of key dynam ics
South-East Asia has experienced major changes in all land-use dimensions and can generally be describe d
as a hotspot region in terms o f land-use change and competition. Severe losses in biodiversit y o ccurred in
Sumatra, the Malaysian peninsula, parts of Borneo, N orth Western Thailand, Cambodia and Vi etnam (98 %
of all land with notable biodiversity changes displays loss). At the same time, those regions (with the
exception of the Malaysian Peninsula) ha v e als o experi enced a large ext ension of c roplands (altogether in
93% o f all ar eas with notabl e changes). In population centres, particular Java and the Mekong Delta region,
livestock density has increased, while it h as remained relatively constant in the rest of the region
(altogether 90% o f land areas with notable changes). Population has increased largely around urban
centres, including Kuala Lumpur (Malay sia), the dens ely populated island of Java (Indonesia), Bangkok
(Thailand), Saigon (Vietnam), P hnom Penh (Cambodia) and Manila (The Philippin es), a nd in the Southern

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and Eastern parts o f Suma tra (Indonesia), altog et her in 94 % o f land areas. For carbon i ntensity a rath er
mixed picture e volves. While it increases in Bo rneo, Ja v a and P apua N ew Guinea (both p arts), i t de creases
in Sumatra and the Malaysian Peninsul a.
Main drivers
The scientifi c literature has highlighted the prom in ent role of deforestation in So uth East Asia. The most
important driver fo r defor estation in South East Asia is commercial ag riculture (Ho sonuma et al., 201 2) ,
particularly driv en by increasin g production of cash crops (palm-oil), l ogging and transformation of natural
forests to forest plantation s (Stibig et al., 2014). The former is satisfying an international m arket, with
>30% of palm o il produced for the world market no w stem ming from South East Asia , while the latter i s
also driv en by an incre asing pulp-and pap er in dustry in the region ( Wilcove et al., 2013). Da v is e t al. (201 5
for the case o f Cambodia) fin d that increasing lan d ac quisitions are a maj o r drive r o f defor estation.
Transformati on of primar y fo rest has severe impli cations for biodiversit y (Ph alan et al., 2013), with
different impacts of new plan tat ions o n v ari ous speci es. Palm oil plantations are in particular damaging
for biodiversit y, while logg ing (in particular selected loggin g as practiced, inter alia, in Myanmar) has less
consequences f o r m ost species in the regi on (Wilcove et al., 2 013) .
Draining and burning of peatlands has been the largest source of carbo n in the region, corresp o nding to
nearly twice the carbon that has been releas ed by forest conversi o n to shifting cultivation an d cropland,
respectivel y (Hought o n, 2012). Carbon-in tensive peat swam ps in particular have experienced a higher rate
of defore station than lowl and or forests o r montane forests. Highest rates (-5 . 2% yr - 1 ) are reported in
Sumatra, followed b y Borneo (Wilcove et al., 2013). Deforestati on o f peatland forest is found to increas e
the likelihood o f for est fire s, again holdin g impli cations for hu man health (Turets ky et al., 2 01 4) .
Between 2000 and 2010 po pulation gro w th in South E ast Asia has been mainly dr ive n by gro wt h of urban
agglomerati o ns. While the urban population climbed by > 31%, urban land area increased by 22% in the
East-South-East-Asi an region. Populati on growth has been in particular strong (with citi es gr o wing at an
average rate between 3 and 7.8% ) in Malaysia, Vietna m, Cambodia and La o s, while urb an land has grown
particular str o ng (higher th an 2% per year) in the P hili ppines, Cambodia and L aos(Schneider et al., 2 015) .
Increasing urbaniz ation and income is generally related to dietary shifts towards more demand for meat,
a pattern that can also be observed in South East Asia (Thornton, 2010). Lipoeto et al. (20 13) find that
traditional food still plays a major ro le within the re gion, with a rapid transitio n to wards Western-style
food predominan tly in urban areas.

Eastern Euro p e and Ce ntra l Asia (R ussia)
Description of key dynam ics
Moving from 2000 to 2010 , the Russian Federa tion has been characteriz ed by a stagnatin g – if not declining
- po pulation with increas es o nly in the major cities (83 % of l and has redu ction in population densi ty). This
is also the general trend observed for livestock dens ity (73% o f land area has reduced liv estoc k density).
There is also a significant decline in cropland (80% of all land area has less croplan d), specifically in the
Central, Volga and South Federal Districts (b etween the Black and Caspian Sea) and in Southern Siberia
and Southern Ural (bo rd erin g Kazakhstan and part of Mong o lia).

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However, this decline has not translated int o a recovery of nature in Southern Siberia and Southern Ural,
as both carbon stock s and species intactness have been developing negativ ely in these regions. On the
other hand, large parts of Northern and Central Russi a have e xperienced impr o vements in carbon d ensit y
during the observati on period. Altoge ther 69% of land displays an inc rease in terrestrial carbon.
Biodiversit y ha s seen a dec line in the Far-Eastern Russ ia (around the Yakutsk region).
Main drivers
The lack of population growth and slow urbaniz ation during the observati on period c an be attributed to,
inter alia, lo w fertili ty in urban areas (about 1 c ompared to 1.55 in rural areas in 2000) and th e fact that by
2009 life expectancy at birth for males was still more than a decade less than in Europe, the US, Japan or
Korea. In addition, urbanization rates were already above 70% in 2000 (Becker et al., 2012). Russia o ften
serves as the prime example of a region where birth rates have fallen behind death rates (Bongaar ts,
2009).
The large overall increase in carbon density bet ween 20 00 and 2010 is consisten t with the fin dings by Pa n
et al. (2011a) f or forest carbon in European Russi a, which the authors attribu te to se veral factors:
increased areas of forests after agricultural abandonment (31.3 million ha), reduced harvesting, and
changes o f for est age struc ture to mo re productive stag es, particularl y for decid uous forest. In Europea n
Russia the carbon gain amounts to mo re than 44 tons of CO 2 per hectare during our observa tio n period,
which makes it o utstand ing as a sink in the boreal regio n and comparable to sinks i n the temperate bio me.
However, Pan et al. (2011a) find a stable sink over the same time period for Asian Russia, which is not
matched by our data, which show an increas e. This could be due to the increas ed carbon s tock in dead
wood and on-ground litter (Dolman et al., 2012) that could have at least balanc ed reductions in carbo n
stocks from disturb ances that can be connected to cli mate change, e.g. large wild fires in Siberia and Far -
Eastern Russia (Kukavskaya et al., 2012; Shvidenko et al., 2011; van der Werf et al., 2 01 0) , which are not
captured in the model providing o ur carbon data. The damage from these disturbances could, however be
limited, by an improvemen t in institutions and policie s, not o nly for pr evention and increase d response
times, but also for better management on the hitherto unused incre ment (Petrov and Lob o vikov, 2012) .
What the model does capture, however, is the beneficial increase o f CO 2 fertilization on biomass in the
region, not inclu ded in other publi cations that repor t NPP (Dolman et al., 2012) .
Finally, carbon density loss es in the South East borderi ng China are also increasingly driven by consu mption
of wood pr oducts abroad (see e.g. Liang et al., 2016, on timber demand) and might, to a larg e extent , be
associated with illegal defores tation for timber expo rts to China, fo r which there is anecdo tal ev idence.
Our o bserv atio n peri o d is characterized by the large Russian roundwood footpr ints of China, the Unit ed
States, Japan , Finland, and German y, where China is not only the most important Russian timber imp o rter,
but also the larg est f oreign final consumer driving Russian timber har vest (Liang et al., 2016). This indicates
the strong role that institutions and policies can play in this context. Consumpti on -side measures in
importing co untri es could lead t o substantial impr o vements, e.g. by “taking shared responsibility and
improving the pro ducti o n efficiency o f ke y sectors in c onsuming nati ons” (Liang e t al., 2016).
The apparen t contradiction between the cropland abandonment in Southern Sib eria and Southern Ural
and decrease in carbon density m ight be ex plained by the lag in the sequestrati o n response (Schierhorn
et al., 2 013). A sim ilarl y slo w recovery might be the case for biodivers ity . Again, o ne has to kee p in mind
that the map shows an abs olute change from 200 0 to 2010 and that thos e areas s howing a negativ e change

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actually do not im pl y that intactness has crossed a cri tical level (e.g. the extinction o f a species). In fact,
the boreal area and tundra have been least affected by land use pressures in 2005 and are still within
planetary bound aries, whe reas many tropical, subtr opical and temperate biom es have already declined
beyond planetary bo undar y lim i ts (Newb old et al., 2 016).

Oceania
Description of key dynam ics
Oceania experiences little (population, biodiversit y, livestock) to m oderate (cro pland, carbon) changes.
Generally, popu lation hotsp ots ar e located where major cities are and indicate continued urbanizatio n
rates. Livestock densit y i s redu ced in 72% of all ar eas. Cropla nd redu ces in the So uth West and S outh East
of Australia as we ll as in N ew Zealan d. Altogether 84% of all areas experien ce cropland loss, with overall
11% les s cropland. Carbon density shows mixed an d d ispersed dyna mics with increases in the North West
of Australia and reduction s in the costal South East Australia. In comparis on to other world regions,
biodiversit y is less affected with o nly 54% of all area s with n otable changes dis playing biodi v ersity loss,
which remains als o relatively s mall.
Main Driver s
Cropland in Australi a is subject to strong salinizati o n which affects roughly 50% of the farmlan d in Western
Australia and even 85% of the farmland related to grain production (ABS [Australi an Bureau of Statistics] ,
2003). Hence, productive land shows di m inishin g trends due to continuing land de gradation which is partly
irreversible (MSEIC, 2010). Additionally, changed precipitation patterns and conti nued d rought conditions
between 1995 and 2007 h ad strong i mpacts on crop producti on in the entir e Oceania region (Gallant et
al., 2012; MSEIC, 2010). Hence, l ocal en vironmental changes can be c onsidered as main dri v er f o r cropland
reduction, which may be p artly also related to anthropogenic cli mate change (Gallant et al. , 2012).
Populatio n hotspots are cl early l ocated where major cities are and indica te continued ur banization rat es.
Livestock density shows no major chang es.
Carbon: mi xed dynam ics. Changes in biomass (and thus, carbon) are highly driven by heter o gene ous
rainfall trends with norther n Australia g etting wetter and southeast Australia dryer (L iu et al. , 2015). Apar t
from the impact on natura l vegetation, growth of f orest plantations may also contribute to changes in
carbon stocks. Carbon sequ estration in forest plantatio ns responds to rainfall variability (Paul et al., 2008) .
Forest plantations almost do ubled in Australia (1.54% o f total forest area in 20 10) while total fores t area
declined by 4.4% and tot al carbon in fo rests ab ove gr ound remained constant. In New Zealand, forest area
remained constant but carbon above gr ound increased by 4% (FAO, 2015). Fores t plantations in Australia
are l ocated in coastal areas in S outhwest and Southeast and correspond partly to increases in carb on in
our ho t spot map (ASFB, 2013). The inclusi on o f forestry into carb on mar kets led to ad ditional increases in
forest plantations (‘carbon forestry’) of about 65,000 ha in Australia (equal to 3.4% o f the area of total
forest planta tio ns, see Mitc hell et al., 2012). New Zealand introduced an emissions trading sche me in 2009
and included the forestry sector, leadi ng to a do ubli ng in forest planta tions in 2011 compared to the
previous year (Rh o des and Steph ens, 2014) .

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Biodiversit y : Majo r reasons for decrease in bi odivers ity related to agricultural issues: Land clearing for
agriculture, changes in wat er av ailabilit y due to agricultural land uses; application o f fertilizers ;
introducti on of new specie s (mammals but also weeds) to the sensitive ecosystem that evolved largely
isolated from o ther c o ntin ental systems (Steffen et al ., 2009).

North Ameri ca
Description of key dynam ics
The population of the United States grew from 283 Million to 310 Million betwe en 2000 and 2 010 (FAO,
2016). Urbaniz ation trends co ntinued as reflec te d by rising population densit ies in urban areas along the
coasts and some interior metrop olitan areas. Spatial patterns of urbanization are also the main driver o f
biodiversit y loss in the United States during our study period. Livestock densit ies remained constant
during this period while total cropland area declined especially in the northeast and increased in the
southeast – overall cropland was lost in 83% of areas. Persistent carbon sinks in the Wo rld’s fores ts (Pan
et al., 2011b) explain the spatial pattern of growing in carbon stocks concentrated in the large forest areas
of the eastern Uni ted Sta tes (72% of all areas gain terr estrial carb on in North A merica).
Main Driver s
The United States went through three distinct phases of land use change. Large-scale deforesta tion fo r
agricultural lands and cultivation of prairie soils accompanied the expansion of European settle ment s
across the continent with a peak in total cro pland area around 1940 (Houghton et al., 1999; Waisanen and
Bliss, 2002). Farm abandon ment in the second half of t he 20 th century resulte d in sev eral decades of
cropland area decline, reforestation, and the rapid expansion of developed lands (L ar k et al., 2015; Sleeter
et al., 2013). Increasin g forest area and recovering forests contribu te to the widespread increas e in carbon
density that was also driven by enhanced plant gr owth due to CO 2 fertiliz ation and nitrogen depositi on.
Average carbon gains in for ests of the Unit ed States amo unt to 38 tons of CO 2 pe r hectare in recent yea rs
(Pan et al., 2011b). At the same time , dr ought stress, pest infestations and fire events affected forests in
the western United Sta te s o ver the past few decades and reduced their capacity to s equester carbo n o r
even result ed in carb o n losses fr om vegeta tion and so ils.
High commodity prices driven b y the rising demand for biofuel feedst ocks since the late 2000s provide d
new incentiv es to expand crop produc tion (Lark et al., 2015; Wright and Wimberl y, 2013) . Consequently ,
wide-spread conversion o f grasslands, shrublands, and wetlands to agricult ural uses reappeared across
the United States with hot-spots of change located in the Corn Belt and the Lake States. In addition,
federally subsidized crop insurance mitigated th e risk of farming even in less productive areas
characterized b y high er o sion risk, shallow s oils, and d rought vulner ability (Feng et al., 2013).
Corn was the most co mmon crop cultivated on n ew ag ricultural land followed by soy an d wheat. Corn was
also responsible for the majority of recent land use chan ge through its displacem ent o f other crops (Lark
et al., 2015; Mladenoff et al., 2016). Between 2006 an d 2008 the area harvested for corn and soybean in
the United States increa sed by 3.2 Mha (Wallande r et al., 2011) and anoth er 5 Mha betwe en 2008 and
2012 mostly at the expense of grasslands (Faber et al., 2 012; Lark et al., 2015). This new wave o f ex pandin g
corn and soy production occurred most rapidly on land less suitable for agriculture character ized by high
erosion risk, shallow soils, and drought vulnerabilit y (Lark et al., 2015). The con centration of grassland

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conversion in th e Corn Bel t ar ound wetlands threatens wildlife habit ats and may also increase flood ri sk
(Wright and Wimberly, 2013). In some regions of th e Western Corn B elt ra tes of grassland conversion were
comparable to defor est a tion rates in Brazil, Malaysia, and Indonesia ( Wright an d Wimberly, 2013) and the
ongoing loss of grassland is expected to create ad v erse effects on native bi odiversity (Meehan et al., 2010).
Increased market demand for bi ofuels feedstocks also t riggered crop switching, especially from wheat to
corn and soybean, which f orces wheat pr oduction to expan d onto other land. Cascadin g land replacements
occurred in s ome areas wh ere land cover chang e from agricultural lan d to devel oped land was offset b y a
conversion of open lands to agricultural lands. In o ther areas o pen lands were converted to developed
lands to offs et the c onversion of devel o ped lands t o agricultu ral lands (Mladenof f e t al., 2 016).
Overall, recent pat terns of land use chang e l ead t o fu rther simplificati o n and homogenizati o n of m ixed-
use landscapes to large-scale cultivati o n of annual crops displaces the former crop to other locati ons
(Meehan and Grat to n, 2 0 15; Wrig ht, 2015) .
These most recent land use dynamics are not visible in our analy sis due to two facto rs. First, switching
from o ne crop to another does n ot chang e croplan d area. Seco nd, total cropland continued to d ecrease in
the United States in r ecent years (US DA, 2016) and this trend may outweigh and hence hide grassland
expansion under t he coars e resoluti o n of the l and use data we analy sed here.

North Africa a nd Wester n Asia
Description of key dynam ics
Populatio n density gr owth has been concentrated alo ng the c oastlines of the Mediterranean, and the river
valleys and delta s. The livestock density r emained more or less stable in most of the regi on but increase d
along the Nile River, in Syria and to s ome extent in North -Western Iran as well as in Yemen. Sligh t increas es
were o bser ved in Turkey. Ov erall livestock density in creased by 7%. Along the M editerran ean coastline,
the cropland ar ea fraction has largely increas ed. Morocco’s cropland area fraction has decreased. The
biggest changes, however, took place in Iraq and Ir an. The cr o pland area fracti on decrease substantially in
Iraq’s east, in the f ertile reg ion along the Euphrates and Tig ris vall ey s, while it increased in Iran ’s we st and
north. Croplands decreas ed in the semiarid mo un tainous regions of Turkey and its Mediterranea n
coastline. The region’s c ar bon intensity has be en largely constant with the exception of Turkey, Algeria ,
Morocco and Tunisia, with different, heterogeneous dynamics displayed. Despite consid erable human
activity in the MENA region, biodiversity was not impacted significantl y, the only exception being the
str etch of land in Algeria’s Northern Sahara as well as Turkeys coastlin es with the Black Sea and the
Mediterranean.
Main drivers
The M ENA region is charact erized by arid to semi- arid climate and is one of th e w orld’s most water -scarc e
regions. Human and economic activities are concentr ated around the few water so urc es, mostly rivers,
deltas, oases, but als o co astal zones, and th e com petition between land uses is particularly fierce.
Wherever there is access to fresh water, there is a high competition due to t he accumula tion of
anthropogeni c activities, best exemplified by the river Nile and the Nile delta in Egypt, where urban area
expansion is forecast to convert v aluable croplands (Bren d’Amour et al., 2017) . The MENA region is also

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expected to be among the most adversel y affected by Climate Chang e: heat extre mes ar e likel y to incr ease
across the entire region (Lelieveld et al., 2016), while precipitation is forecast to decrease in the Western
Asian part (Evans, 2009), potentiall y leading to increasin g levels of desertificatio n. Sea-level rise and the
sinking of deltas will further increase the risk for the flood-prone urban coastal zones (Bohannon, 2010) .
Attempts to res ettle are u nderway, but ha v e yet to prove to b e efficient (Bohan non, 201 0). Bio di v ersity
remains largely unchanged with the exception of Turkey, where important wetlands, grasslands, even
rivers are disappearin g due to human activi ties (Şekercioğlu et al., 2011) .
Regardless of any biophysi cal constraints , the p opu lation grew by 19% to a total of more than 2 00 milli on
in Northern Africa compared to 2000 levels, and by 25% in We stern Asia, totalling 230 million in 2010
(“World P op ulation Prospects - Population D i vision - United Nations, ” n.d.) . The population has
quadrup led in the second half of the last century. Fertility rates have slowed but the populati o n is s till
expected to reach almost 700 million by 2050 (Roudi-Fah imi and Kent, 2007). More than 50% of the
population lived in urban areas in Northern Africa in 2010, and more than 68% in Weste rn Asia. Both
urbaniz ation rates ar e expe cte d t o in crease further. Pop ulation in creases mos tly take place in an d ar ound
major cities as well as larger villages in the more rural areas. The MENA regi on still co ntains a significan t
number of pastoralists and the pastoral farming system can be found across al most a quarter of the land
area (Dix on et al., 2001). Seasonal migration, also across borders, plays an importan t role fo r the often
small herds of goats and sh eep, depending on the avai lability of grass and wat er.
We o bserv e co-occurrenc es o f significant population and livestock increas es ac ross the region, and o f
population and croplan ds in Northern Africa. In West ern Asia, population growth mostly takes place at the
expense of croplands, and we can exp ect similar dyna mics f or N o rthern Afri ca, as u rban areas c o ntinue to
increase (Bren d’Amour et al., 2017) . In the second half of the cent ur y, Clima te Change impacts are likely
to have reduced the littl e lands viable f or rain-fed agriculture by over 17 0 .000 km 2 across the region (Evans,
2009). Croplands can be v ery produc tive, especiall y in Northern Africa, but rely larg ely on comple x
irrigation syste ms (Fetzel et al., 2016). While the magnitud e of the competition in areas with competin g
land uses in the MENA regi on can be very strong, it is also co ntain ed t o a r elativ ely small fracti o n of the
total area. Large expanses are still not impac ted by human activity, mos tly bec ause they are uninh abitable.
The ab o ve-ground carbon stored in the MENA region will decrease, alb eit for different r easons. In
Northern Africa, this dynamic is driven by population growth whereas in Western Asia, it is driv en by
cropland ex pansi o n. Bi odi versity will also be affected by the increase in anthr opogenic land us es, mostly
by population and livest o ck intensification (in Wester n Asia). For Northern Afric a, we see an increase in
biodiversity which is mostly driv en by Egyp t which showed an almost country wide transition fro m
plantation to s econdary vegetati on. This development would substantiall y aff ect the intactness factor bu t
might be an arte fact.

Latin Ameri ca and t h e Caribbe a n
Description of key dynam ics
Populatio n growth in Latin America and the Carib bean between 2000 and 2 010 has been less pronoun ced
than in Sub-Saharan Africa and large parts o f Asia (population growth in 85% of all areas). It has been
mostly concentrat ed in Central (Guatemala, H onduras, El Salvador, Nicaragua and parts of Costa Rica and

75

Panama) and South ern A merica (main ly the coasta l areas in the North Wes t V enezuela, Col o mbia,
Ecuador, Peru and large parts of Eastern Brazil), and some hotspots where urban areas had already
expanded before (e.g. Buenos Aires in Argentina or São Paulo in Brazil, which is also apparent in the
dynamic described in the main text, cf. Fig. 1A).
Areas dedica ted to gr owing crops h ave increas ed in Br azil, parts of Chi le, Urug uay, Hond uras, El Salvad or,
Nicaragu a, North ern Col ombia and Venezuela. Interest ingly, m uch of Central A mer ica, Northern Colombia,
Ecuador and central Chile featu re the o pposite pictu re, i.e., a decrease in cropl and intensity. Livestock
intensity generall y increas ed in the same period (80% o f all area). We also observe an ex pansion o f
livestock density for Brazil, Uruguay, Argentina, P arag uay, Bolivia and Peru. Eve n though the Caribbean
islands are less pr ominent i n terms of absolute nu mbers, th ere seems to b e a shif t from cropland to larg er
areas dedicated t o lives tock on some islan ds.
This pressure from human demands (shelter /infrastru cture, livestock, cropland) h as come at the cost of
biodiversit y l osses across the whole o f Latin America and the Caribb ean, as is apparent from the Latin
American panel in Fig. 4 (ind icating a co -occurrenc e of increases in the three human demands with
decreases in biodi versity). In 96% o f all areas biodiversi ty is lost, representing 28% of the global biodi versit y
loss. The density of carbon , on the other hand, has been evolving in a much mo re dispersed way, with
gains in Mexico, Pana m a, Costa Rica, but also Colo mbia, Peru, Gu yana, Suriname, French Guiana and Brazil.
Much of the carbon increa ses in Brazil coincide with the A mazon Basin, where we als o partially ob serve
lower than expected biodiversity losses co mpared to other parts. This is also reflected in the mor e m i xed
pattern for carbon in Fig. 4. Nonetheless 29% of the global n et loss in terrestri al carbon is attributed t o
Latin America.
The latter regions (Mexi co and El Salvador, parts of Costa Rica and Panama, parts o f the Amazon Basin,
Ecuador and Colombia, No rthern Gu yana, Suriname and French Guiana, small parts of Peru, Bolivia an d
Argentina and larg e parts of Chile) are charac te rized by an improvem ent in nature (cf. Princip al Componen t
Analysis in main text), while most of middle and Southern Brazil, Uruguay, coastal Peru, Vene zuela, mid-
Central America and Caribbean are d ominated by the influ ence of human pr essures.
Main Driver s
The observed population dynamics can mainly be explain ed by reference to thre e drivers: L a tin America
has – in contrast to Sub-Sah aran Africa – seen a decline in fertilit y rates (Cohen, 2006). P artiall y
counteracting this trend is the fact that Latin America has been a front-runner in ca tching up with Northern
mortality rates. Indeed, the projections for our period of investiga tion (mad e in 1 990) indicat ed that in
2015, Latin A merica would have a rat e of around 29 deaths of children under 1 f o r e very 1,000 born ali ve,
whereas new estimates show that this rate has dropped to 19 deaths o n a regional average in 2015
(Observat orio Demográfic o de A mérica Latin a y el Caribe, 2014). Regional variations are larg e and range
from 5 . 4 in Cuba to 41.3 in Haiti. With a high level of urba nization in Southern A merica, which has matched
Northern levels already at the beginning of our o bs ervation period, it is no surprise that the rate of
(further) urbanizati on is relativel y low compared to other regions (Cohen, 2006) and growth is no longer
predominantly driven by rural-urb an m igrati o n for economic motives, but also by natural po pulati on
growth in the cities and migration between cities (Cerru tti and Bertoncello, 2003). These larger urban
populations in turn can be associated with increas ed demand fo r food and especially meat (Thornt o n,
2010) and more inefficient agricultural practices (Grau and Aide, 2008) , ex plaini ng parts o f the o bs erve d

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increases in cropland and livestock density . In Central America, rural-urban m igr atio n still plays a bigger
role in urbanizati o n, but the effects are more heter o geneous here. For example, Mexico and El Salvador
see lower losses of biodi versity and partially gains in carbo n d ensity , which some au thors hav e explain ed
by the positive correlation between remittanc es and forest recovery (e.g. Hech t and Saatchi 2008). In
Southern Ameri ca, the roots o f deforesta tio n are no longer only associat ed with the traditional
development pattern shifting agriculture and catt l e ranchi ng. Instead, the combi nation of the availabilit y
of fertile land and low production costs has l ed to deforestation through export-orien ted industrial
agricultu re (Grau and Aide, 2008). Both in te r ms of sp ecies inta ctness and carbon density, the hotspots o f
the past can still be single d o ut for the period 2000 -2010 (the Amazon Basin in Ecuador, Columbia and
Venezuela, Southern Guya na/Rio Negro, Acre, the Peruvian Amazon and Mato Gro sso, cf. Grau and Aide,
2008). Still, the change from 2000 to 201 0 appears to be less pr onounced in part s of Brazil, which can be
attributed to a substantial d ecrease in deforestation rates during the time (Gibbs et al., 2015; Nepstad et
al., 2014).
In addition, it has been observed that the comb ina tion o f agricultural m oder nization and rural-urban
migration has led t o aband o nment of marginal cropland and pastures, enab ling ecosystem recov ery (Grau
and Aide, 2008) . Grau and Aide (2008) provide an overview of the literature on the recovery of degra ded
forests in Puerto Rico and the Dominican Republic in the Caribbean, in Mexic o , El Salvador, Hondu ras,
Costa Rica and P ana ma in Central A merica and in par ts of South A merica.
This p oints to an i mpo rtan t ro l e for in stitutions and policy, where the La tin Ameri can e xperience has been
two -sided: on the o ne hand, our o bser vation period has seen a decrease in defores tation rates due to
enhanced monitoring and enforcement in Brazil (Nepstad et al., 2009). On the other hand, most of the
current deforestation in Latin America is related to meat production, either by planting pastures for
livestock or by planting soybean to supply feed for animals (Aide et al., 2013), which confronts decision-
makers with new institutional challeng es and points towards the need for transboun dary governanc e
concepts.

Southern Asi a
Description of key dynam ics
The world m ap demonstr ates that the world’s highest populat ion growth takes places in the India n
subcontinent (India, Pakistan, Bangladesh, Nepal), with highest change along the Southern Himalaya n
range (100% o f areas with notable changes display population gro wth). Suitable cro pland is slightl y
decreasing across South Asia (at 7 0% of area), and it the most frequent co -occur rence is with increase in
population. H owever, at h o tspots (i.e. where absolute cr opland intensit y changes bel o ng to the hig hest
10% globall y ), there i s stro ng co-occurrence o f cropla nd increase and population gro wth.
Livestock increase s togeth er with population, but also is reduced with populati on increase in other places.
Livestock has a m ostly balan ced interacti o n with other land-uses, co-occurring bo th with positi ve and
negative chang es, and appr o ximately incr easing in as many areas a s it is decreasi ng. Hotspots of livestock
increase co-occur with population. The land carbon stock is both increasing (60% of all area with notable
changes) and decreasing (40%), with both dynamics co-o ccur ring with population growth. Biodivers ity is

77

reduced across the subcont inent (6 9% o f all ar eas), mostly where there is also rele v ant population growth
but not along the Himalaya ranges.
Main drivers
India’s land use challenge is dominated by a rap idly growing popula tion and ensuing land use change.
Population is expected t o grow from 1.3 billion in 2 01 6 t o 1.7 billion in 20 50; In di a is expected to overtak e
China as the world’s most po pulous countr y in 2022 (US Census Bureau, n.d.). The total urban popu lation
is ex pected to nearl y doubl e fro m 420 million in 2 015 to about 81 4 million in 2050 (United Nations, 2 014) .
This urbanization translates into lar g e urban land expansion, which is mostly driven by populati o n growth,
and less by economic growth (Seto et al., 2 011). W hile the total urban land expansion is uncertain, it i s
estimated that in 2030 m ore than 1 00.000 km2 will be urbanized with likelih ood h igher than 75% (in 20 00
30.000 km2 were urbaniz ed, see Seto et al., 2012). There is lower probability o f urbaniz ation but for m uch
larger area al ong the Himal ayan rang e, reflecting the rap id po pulation growth of mostly rural populati ons.
Growing population will increase demand for food; it is ex pected that likel y rice y ield increas es o f about
1%/year would be suffici ent t o maintain per capita c onsumption rates (Ray et al., 2 013) .
FAO data demonstra te the total area harvested for key crops like rice and sugarcan e decreased by 4.1%
and 1.1% respectively. A case study of Delhi high lights that urban and infrastru cture land take
predominan tly correlates with agricultures land loss, and to l esser degree with dense forest loss (Jain et
al., 2016). This area loss was compensa ted by yield incr eases p er ha of 15% for rice, but yields for sugarcan e
kept constant (FAOSTAT, 2015). Differing land pr operty rights origin ating from colonial times lead to very
different o utco mes in agricu ltural produc tivity and well -being in the long run (B anerjee and Iyer, 2005) .
Crucially, the data us ed in our analysis (cropland suitabi lity) display the re duced area, bu t not the
increasing yields.
Deforestati o n due to huma n pressures has been the leadin g cause for biodivers ity but deforestati o n has
significantly decelerat ed due to effective conversation programs (Reddy et al., 2015). In so me areas of the
Doda region in the Weste rn Himalaya, anthr opogenic pressures on forest systems compro mise plant
biodiversity (Rashid et al., 2013). Urbanization em erges as a key treat to biodiversity; however, the shift
from traditional fuels (w ood) to mo dern fuels accompanying urbanization let to reduced pressure on peri-
urban forests and mangroves (Nagendra et al., 2013). The transition from subsistence farming to cash -
crop s ystems leads t o loss in agro -biodiv ersity (Pande et al., 2016). Howev er, c onservati on with a high le vel
of community involve m ent is proving to be an effective way to co nserve forests, especially if motivation
for conversati o n is coupled with social and ec onomic benefits (All endorf et al., 2013).

Europe
Description of key dynam ics
The P CA map shows a clear dominance of the “nature” dime nsion, alb eit with important exceptions such
as in Spain, along the M edi terranean and around the Baltic Sea and the Gulf o f Bothnia, where “ na ture”
recedes.
Biodiversit y decline dominates, most prominently in Spain , Italy and Belaru s. Biodiversity has in creased in
Poland and Germany. Strong declines in a gricultural area can be observed in Poland, Lithuania, Italy and

78

Portugal. D ecline in cropla nd tends to coincide with increasing carbon and decreasing population and
livestock. Agricultural area increased in Denmark, the Netherlands and Latvia. With regard to livestock , a
decrease in int ensity dominates in Europe, most strongly in th e U K, the Netherland s, Belgiu m and Ukraine ,
while pocket s of substanti al intensification exist in Denmark and Poland. Lookin g at Europe withou t the
Eastern European countrie s, 76% of the area in which sign ificant changes occur, manifes t a decrease in
livestock densit y. 21% of the global livestock decrea se occurs in this region (Europe excl. Eastern Europe).
Populatio n tre nds are mix ed with a tend ency for decreasin g densities in th e East and increasing d ensities
towards the Wes t. Overall, increasing densities in maj o r urban agg lomerations (Istanbul, London etc.) ar e
visible. C arbon increases d ominate the region, coinci ding with biodiversity loss in Easte rn and Souther n
Europe and biodiversit y gai ns in Northern and We ster n Europe. 84% of the ar ea in Euro pe (excl. Eastern
Europe) where significant carbon changes o ccur, show a gain in land carbon sto cks (see Region brief
Eastern Europe / Russia f o r more de tails concerning that regi o n).
Main drivers
Land-use change in Eur ope is characteris ed by increasing specialisation and polarisation. Key trends
involve agricultu ral intensification on the most productive lands (e.g. in Denmark) and farmlan d
aban donment in margina l, less competitive regions (e.g. in some former Soviet co untri es). Both
developments are driven by the globalization o f agricu ltural markets resulting in increased competiti o n
and (agricultural) land use displacement outside Europe (Cosor, 2014; Kuemmerle et al., 2016; van Vliet e t
al., 2015). Drivers of farm land ab andonmen t in particular include socie tal change in the form of incr easing
urbaniz ation and dem ograp hic chan ge resul ting in rur al depopu lati on (Cosor, 2014; van Vl iet et al., 2 015) .
Farmland aband onment and a strong decline in cap ital-intensive far m ing practic es have been particularl y
significant in the former s ocialist countries where the process of resti tution, low comp etitivene ss and rural
outmigration were imp o rtan t drivers ( Kuemmerle e t al., 2016; van Vliet et al., 2015). After the Soviet Union
collapsed prices for inputs and outputs were liberalis ed, fo rmer markets disappeared and internationa l
competition increased. Moreover, land ownership changed, o ften leading to tenure insecurity (Baumann
et al., 2011). The gr eat heterogen eity in the extent o f abandonment within Eas tern and Central Europe
results fro m strong differe nces in agricultural sector reforms ranging from full -scale market liberalisation
in P oland and Romania to gradual refo rms in Belarus and Ukraine; stark differences in state support;
different approaches conc erning land reforms (rangi ng from restituti on to cont inuing stat e ownership);
and EU accession of some co untries (Alcantara et al., 2013). On the o ther hand, in some former socialis t
countries, e.g. Poland, a lo wer baseline level of inten sification compar ed to other regions, technol ogical
change enabling increasin g me chanization and rising labour c o sts r esulted in intensification in the f o rm of
increasing liv estock densities (Kuem merle et al., 2016) .
In some EU countri es such as the Netherlan ds and Belgium, P and N applicati on standards and manure
fees led many holdings to decreas e their livestock concentra tions (European Com m ission, D G Agriculture,
2004; Kue mmerle et al., 2016) . The 2003 refor m of the E U's Co mmon Ag ricultura l Policy which d ecoupled
farm subsidies fro m output contributed to declinin g agricultural in te nsificati o n (WWF, 2010). According to
a systematic review of case studies co nc erning Europe by van Vliet et al. (2 015), technological and
institutional drivers (incl. subsidies and land-use pl anning ) dominate when it comes to agricultural
intensificati o n, while econ o mic (incl. gl o balization and urbaniz ation) and institutional dr ivers as well as
location factors (incl. topograp hy and soil) dominate with respect to agricultura l dis -intensification (van
Vliet et al., 2 015).

79

Biodiversit y loss due to poll ution, habitat loss and fragmentation, invasive species and climate change is
widespread throughou t th e regi on. B oth agricultural intensification and aband onment contribute to the
observed decline (European Environmen t Agency, 2015) . In Belarus in particu lar, biodiversity decline
associated with farmland abandonment could be observed (visible in our maps). Expansion of tourism an d
associated infra structure dev elopm ent is a strong driver o f biodiversi ty loss along the M editerran ean
coast. Underlying causes includ e governance and market failures (European C ommission, D G Environ m ent
2009). Notable excepti o ns are Poland and Germ an y where conservation pr ograms were imple m ented and
secondary v egetation established itself after agricult ural monoculture and former industrial sites wer e
abandoned (K olecka et al., 2 015) .
The o bserv ed urban i zation patterns refl ect rural- to -ur ban migration, t he attraction of larg e urban centres
and rural depopu lation dri ven by socie tal and de mographic chang e.
Carbon stock i ncrea ses have resulted from forest regrowth on abandoned farmland and afforesta tion
(Cosor, 2014; European Environ ment Agency, 2015; Kuemmerle et al., 2016). This dynamic is largely
responsible for the “nature ” dominan ce in the principal component anal ysis, which prevails in most of th e
region.

East Asia
Description of key dynam ics
East Asia has expe rienced l and use changes between 2000 and 201 0 to various extents. Ver y promin ently,
popu lation has grown in big metropolitan and urba n areas, e.g., in Guangzh ou, Chengdu, Shanghai or
Beijing in China, as well as in Seoul and Pusan in South Korea. At the same time , the hinterland regions of
large metr opolitan areas have experienced decreas es in population density indic ating a rural exodus and
inner regional migration in particular in China, and in South Korea. Cities in remo te areas, e.g. in Xinjiang
province in China and in Mongolia have also grown significantly. The overall net effect on average
population densities has been positive, as the rural exodus is more than o ffset by increases in the high
density regions a ro und e xisting urban areas. 15% of gl o bal populati o n gr o wth took plac e in Ea st Asia.
Population growth has gon e hand- in -hand with larg e increases in livestock . 30% of all growth in livestock
density took plac e in East Asia. Cr oplan d has decreas ed in the entire region – 98% o f all notable change s
in cropland are negative. Carbon intensity sh ows a rat her mixed picture, with increases in Eastern China,
the Tibetan Plateau, as well as Yunnan. D ecreas es o f carbon intensity can mainly be found in Taiwan,
Sichuan and the Southern Chinese provinces as well as in the Northern par t of the region, including
Mongolia, the Northern Chinese provinces (Heilongj iang, Jilin and Inner Mong olia) and N o rth Korea.
Biodiversit y has decreased mainly in the South of Chi na (across the border to South East Asian countries
Myanmar, Laos and Vietna m ), as well as in a co rrid o r reachin g approxi mately from Chengdu to the greater
Beijing area, covering the provinces of Hubei, Henan Shanxi and Hebei. Altoge ther 97% of all notabl e
changes in biodi versity are negative.
Main drivers
The literature identifies pop ulation dynamics to be largely driven by urbaniza tio n. In fact, East Asia is
among the w o rld regions w ith the strongest urbanization dynamics, both in terms o f scale and pace. From

80

2000 to 2010, urban populati on in China grew by 3.3% per annum on average (World Bank, 2015), whereas
the gro wth ra te of th e total po pulation averaged 0.5% (“World Population Prospects - Po pulati o n D ivisi on
- United Nati ons,” n.d.) . In the sam e decade, urban areas expanded by 3.1% p. a. Accordin gly, urban
population densities mostly increased, moderately re mained stable, or even dec reased ( e.g., in Shanghai).
In China, 87% of urban expa nsion occurred on arabl e land which had imp ortant impli cations for agricul tural
production (World Bank, 2015). There is evidence tha t the rapid urban area expan sion poses substantial
threats to China’s most pr oductive cropland s (Chen, 2007). By 2030, China is expected to have urbanized
more than 5% of its prime croplands which were use d to produce 9% of crop produ ction in 2000 (Bren
d’Amour et al., 2017) . How ever, observed decreases in cropland are partly also due to efforts to fight soil
erosion (Deng e t al., 2014) .
Livestock densi ties increas ed in much of East Asia, mostly driven by surges in demand for pig meat and
poultry (Thornt o n, 2010). I ncreasingly, confined li vestock produc tion syste ms are established to mee t this
demand; m etrop o litan areas like Shanghai, Beijing, and G uangdong increasingly rely o n industrial pig
production (Bai et al., 2014) This v ery intensive form of livestock production has allowed fo r significan t
simultaneous incr eases in both populati on and livest o ck.
Terrestrial carbon Strange is decreasing in 62% of Land in East Asia (Table S5, cf. Calle et al., 2016) .
However, decomposing those changes, significant differences can be identified, both related to land use
types as well as ac ross regions. Decreases in Norther n China and Mongolia are predominantly r ooted in
deforestati on. Increa ses i n cropland ha v e led to high decreas es in terrestrial carb o n in Sichuan and
Heilongjiang (Zhang et al., 2015) . Afforesta tio n and an increase o f grassland areas ha ve contribut ed to
increases in stored te rrestr ial carbon, pa rticul arly in Tibet. Parts of that can be attrib uted to China’s fight
against soil er osion (“green -for- grain” progra m), aiming to restor e degraded agric ultural land by grasslands
or afforestati on (Deng et al., 2014). However, affor estation does not always l ead to increased te rrestrial
carbon storage; in Inner M ongolia, for example, increasing carbon intensity by afforestation has been
compensated by l o sses in g rasslands (Zhang et al., 2015) .
Biodiversit y l osse s can to a large extent be attributed to land i ncreasin gly being consumed b y urban ar eas,
particular in China (He et al., 2014). For example, in the Pearl River delta, 26% of natural habitat and 42%
of local wetlan ds have been prey to urbanization. In particular in Yunnan the loss o f primary forest an d
biodiversity i s due to l oggin g and cash crop plantati o ns , particularly rubber (Liu et al. , 2013).

81

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Chapter 3

3. F ut ur e urban land e x pansion and im plications for global
cr o plands

*

Christopher Bren d ’A mour
Femke Reits m a
Giovanni Baioc chi
Stephan Barthel
Burak Güneralp
Karl-Heinz Erb
Helmut Hab erl
Felix Creutzig
Karen C. Seto

*

Published in t he journal Proceedings o f the National Ac ademy of Sciences o f the Unit ed State s of America as C.
Bren d’Amour, F. Reit sma, G. Baiocchi, S. Barthel, B. Gün eralp, K.H . Erb, H . Haberl, F. Creutzig, .K. C. Seto: Future
urban la nd expan sion and implications for global crop lands , PNAS 2017 114 (34) 8939-89 44; published ahead o f
pr int December 27, 2016, https://doi.org/ 10.1073/pn as.16060361 14

90

91

Future urba n l and expan sion and implications fo r glo bal cropland s

Christopher Bren d ’A mour 1,2 , Femke Reitsma 3 , Gi ovanni Baiocchi 4 , St ephan Barthel 5, 6 , Burak Güneralp 7 ,
Karl-Heinz Erb 8 , Helmut Ha berl 8 , Felix Creutzig 1,2 ,* , Karen C. Seto 9

Abstract

Urban expansion often occurs o n croplands. However , there is li ttle scientific understanding of how g lobal
patterns of future urban expansion will affect th e world’s culti v ated areas. He re, we co mbine spatiall y
explicit projections of urban expansion with datasets on global cropland s and crop yields. Our results show
that urban expansion will result in a 1.8 – 2.4% loss o f global croplands by 2030, with substantial regional
disparities. About 80% of global cropland loss from urban ex pansion will take place in Asia and Africa. In
both Asia and Africa , much of the cropland that will be l ost is more than twice as producti ve as natio nal
averages. Asia will e xperience the highest ab solute loss in cr o pland, whereas African countries will
exp erienc e the highest per centage loss of cropland. G lobally, the croplan ds that are likely to be lost were
responsible for 3 – 4% of wo rldwide crop p roducti o n in 2000. Urban e xpansion is expected to take place on
cropland that is 1.77 times more productive than the global average. The loss of cropland is likely to be
accompanied by other sustain ability risks and threatens liveliho o ds, with diverg ing characteristics for
different megaurban regions. Governance o f urban area expansion thus emerge s as a key area for se curing
livelihoods in the agrarian eco no mies of the Gl o bal S outh.

Keywords: u rbanizati on, global lan d use chang e, li velihoods, agri cultural product ivity, megaurb an regi o ns

1 Mercator Resear ch Institute on Gl o bal Com mons and Climate Change, 10829 Berlin, Ger m any
2 Department Econ omics of Climate Chan ge, Technisch e Universität Berlin, 10623 Berlin, Ger many
3 Department of Geograph y, Canterbury Univ ersity, Ch ristchurch 8140, New Z ealand
4 Department of Geographi cal Sciences, University o f Maryland, C o llege P ark, M D 2074 2, USA
5 University of Gävle, SE- 80176, Gä vle, Swed en
6 Stockholm Resilien ce C entre, Stockholm Uni versit y, SE-10691, St ockholm, S weden
7 Department of Geograph y, Texas A&M Uni versity, College Stati on, TX 77840, US A
8 Institute of Social Ecolo g y Vienn a, Alpen-Adria Uni ver sitaet Klagenfu rt, 1 070 Vien na, Austria
9 Yale School of Forestry an d Environmental Studies, Yale University, Ne w Ha v en, CT 065 1 1, USA
* Author to who m any c orrespondenc e should be add ressed.

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3.1. Statemen t of si gnificance
Urb anization’s contributi on to land use change emerg es as an important sustain ability concern. Here, we
demonstrate that projected urb an area expansion will take plac e o n some of the world’s most productiv e
croplands, in particular in m egaurban regions in Asia and Africa. This dynamic ad ds pressur e to poten tially
strained future foo d syste ms and threat ens livelihood s in vulnerable re gions.

3.2. Introduction
Urban land expansion — the process of creating the built env ironment to house urban populations and
their activities — is o n e of the fundamen tal aspects of urbanization. Urban land ex pansi o n modifies
habitats, biogeochemistry, hydrolog y, land cover, and surface energ y balance (Grim m et al., 2008). In most
parts of the world, urban land is expanding faster than urban populations (Seto et al., 2 010). Whereas
urban populations are expected to almost double from 2.6 billion in 2000 to 5 billion in 20 30 (United
Nations, 2014), urban areas are forecast to triple bet ween 2000 and 2030 (Seto et al., 2012). A defining
ch aracteris tic of contemp o rary urbanization is the rise of megaurban regions (MURs): the m erging of
multiple urban areas into a contiguous and continuous urban fabric. These MURs differ from megacities
with populations o f 10 million o r more in two important and fundamental ways: ad ministrativel y , they
consist of multiple contigu o us entities with discrete governance structures; biophysically, they are a single
continuous urban area whose absolute spatial size creates challenges for urb an, land, and transport
governance. The rate and magnitude o f urban land ex pansion are influenced by many macro factors,
includin g income, economic developm ent, and pop ulation grow th, as well as a nu mber o f local and
regional factors such as land use policies, the informal eco nom y , capital flows, and transportati on cost s
(Seto et al., 20 1 1).

More than 60% of the world’s irrigated croplands are located near urban areas (Thebo et al., 2014) ,
hi ghligh ting the p otential competition for land between agricultural and urban uses. Individual cas e
studies show that high rates of urban expansion over the last three decades have resulted in the loss of
cropland all around the world, with ex amples from Ch ina, the United States, Egypt, Turkey, India, and
other countries (Ah mad et al., 2016; Bagan and Yama gata, 2014; Chen, 2007 ). Although cropland loss has
become a significan t conc ern in terms of food production and livelihoods for many co untri es (Bro ok and
Dávila, 2000), there is very little scientific understandin g of how future urban expansion and especially
growth of MURs w ill aff ect cropland s. However, this kn owledge is k ey given th e potential l arge-scale land
conflicts bet ween agricu ltu re and urban uses in an era of rapid megaurb anizati o n.

Most of the future urban population and urban area expansion are forecas t to take place in Asia and Africa
(Seto et al., 20 12), oft en in places with high pover ty rates and po te ntiall y pr one t o syste mic disr uptions in
the f o od syste m (Bren d’Amour et al., 2016; Puma et al., 2015) . F or many of th ese countries, agricu lture i s
a crucial economic sector in terms o f income generation, percentag e of total national gross domestic
product (GD P), and e mployment source. Thus, there is a ne ed to assess the i m plicati ons of urban
expansion on croplands on global, national, and subn ational scales to identif y potential areas o f conflic t
as well as s trategi es for sha ping more sustain able for m s of urban expansion.

This pap er fills thes e knowledg e gap s by addressin g the f o llowing qu estions : (i) W here ar e croplands most
vulnerable to conversion due to future urban expan sion? (ii) What is the magnitud e of cropland lo ss,
especially of prime croplan d, due to future urban expa nsion? (iii) How will th e loss of cro plands affect total
cropland area and relative economic importance of agricultu re for different countries? Sustainability in

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the era of megaurbanizati on will require understandin g the “hidden linkages” between urbanization and
food s yst ems (Seto and Ramankutty, 2016), in cluding where and how to maintain croplands to grow food,
the mos t basic o f all human necessities. Here, we defin e food syste ms as “ the chain o f ac tivities connecting
food production, processi ng, distribution, consump tion , and waste management, as well as all the
associated r egulator y instit utions and ac tiviti es” (Pothu kuchi and Kaufman, 200 0).

This study provides a g lobal estim ate of the loss o f cr oplands to urban area expansion and its implicati o ns
for crop producti o n. We limit our discussi on to croplands, which cover 12% o f Earth’s i ce -free land area
(Ramankutty et al., 2 0 08), but ex clude pastures. We compar e spatiall y explicit datasets on cro plands (Fritz
et al., 2015; Ramankutty et al., 2008) and cropland productivity (Monfreda et al., 2008) for the year 2000
to gridded urban area proj ections for the year 2030 (Seto et al., 2012). P roce ssin g the cropland datasets,
we gen erate a cr o pland map and intersect it with g ridd ed data on the aggregated productivi ty of 16 m ajor
nutritional crops. We supplement this with a disaggregated analysis of four staple crops (m aize, rice ,
soybean, wheat) and three cash crops (cacao, o il palm, sugarcane). We then calculate the croplan d and
crop production lo ss acc o rd ing to three differ ent urbanization sc enarios (low, medi um, and high).

3.3. Results
Future urban expansion is highly likely to occur in areas currently under cultivati on (Fig. 1). Globally, 46
Mha (medium scenario; range from low to high scenario: 43 – 55 Mha) o f croplan ds in 2000 are loca ted in
areas that are expected to be urbaniz ed by 2030, corresponding to 3.2% (3.0 – 3.8%) o f existing cultivate d
land. However, urban agriculture is known to be significant in many cities. Hence, we acc ount for urban
agriculture by o verlaying maps of urban areas and cr oplands for the year 2000, a nd find that, on a verage,
36% of all urban areas are used for crop production. We assume this p ercentag e of urban agriculture to
prevail when urban area ex pands but account for regional variation (for example , 41% in Asia and 32% in
Africa; see Supp orting Information for details). Accounting for these prevailin g cropland fractions, total
cropland loss a mounts to 2.0% (1.8 – 2.4%) o f the global total — around 30 Mha (27 – 35 Mha), with countries
such as China, Vie tnam, and Pakis tan rangin g betwee n 5 and 10% (Table 1).
Although the aggregat e impact of urban expansion on global cropland is modest, regional impac ts will be
acute and differentiat ed. In the medium urbaniz ation scenario, Asia and Africa will experience around 8 0%,
or roughly 24 M ha, o f the total global cropland loss. The most affected regions i n Africa include Egypt,
Nigeria, and the regi on surround ing Lake Victoria Basin in Eastern Afri ca (Fig. 1). In Asia, the hot spots of
cropland loss ar e river vall eys and coastlines, many of which are in the v icin ity o f M URs, such as the Bohai
Economic Ri m and the Yan gtze River Delta in Ch ina, or Ja va Island in Indon esia (Fig. 2).

94

Figure 1 – Maps show where projected urb an expansion until 2030 is expected to result in crop land loss. Competing
areas (red) hold croplands but have a high probab ility (>75%; mediu m scenario) of becomin g urbanized by 2030. (A –
E) Close-ups of urb an area ex pansion hot spots. Dat a on urban expansion are from Seto et al. (2012), an d data o n
cropland a re from Fritz et al. ( 2015).

One-fourth o f t otal gl o bal croplan d los s will occur in Ch ina. Urban expansi on in C hina is taking place in the
country’s mo st productive farmland and over larg e ar eas. Therefore, urban expa nsion c ould p ose a threat
to domestic crop producti o n. In contrast, India, the United States, and Brazil will also experie n ce high
losses in absolu te te r ms, but here urban expansion leaves l arge expanses of croplan ds untouched, and is
therefore l ess likely to threaten do mestic crop produc tio n (Tabl e 1).
Future urban land expansion will continue to take pl ace on prim e agricultural lands. We obser ve a total
loss of crop producti on of 3.7% (3.4 – 4.2 %) due to urban expansion. On averag e, the cropland lost t o urban
expansion is 1 . 77 times as productive as the average global croplands. Our r esults hence co nfir m evidence
from local case studies (Ahmad et al., 2016 ; Bagan and Yam aga ta, 2014; Chen, 2007), indicating that urban
agglomerati o ns are surr ound ed by cropland s with above a v erage productivit y .
Our an alysis shows tha t 84% of gl obal production l o sses ar e expected to occur in Africa an d A sia (Tabl e 1 ).
The 3% cropland loss in Asi a translates into a 6 % production loss (T able 1). In Afri ca, the effects are tripled :
a 3% cropland loss transla tes into a 9% crop producti on reduction, most of which will take plac e in Egypt
and Nigeria. Only a few countries display urbanized cropland with below national averag e agricultural
productivity, the United States being the most prominent example. China and India will co n tinue to

95

urbaniz e rapidly, but with different spatial patterns and development d ynamics. China’s croplands are
concentrated along the coastal areas and in the east o f th e c ountry (Fig. 1). By 2030, most of the urba n
land cover expansion is e xpect ed to occur in that re gi on.
Table 1 - Region al and national imp lications of ur ban area exp ansion on c roplands and crop pro duction.

Expected
cropland loss

Relative
cropland loss

Production loss

Production loss

Productivity in
conflicting ce ll s

Mha

% of cropland

Tera Cal yr-1

% of total cr op
production

relative to
domestic/reg ional
average

World

30 (27- 35)

2.0 (1.8-2.4)

333 (308 - 378)

3.7 (3.4-4.2)

1.77

Asia

18 (16- 21)

3.2 (2.9-3.7)

231 (214 - 264)

5.6 (5.1-6.3)

1.59

Africa

6 (5- 6)

2.6 (2.4- 3)

49 (45- 52)

8.9 (8.3-9.4)

3.32

Europe

2 (2- 3)

0.5 (0.5-0.9)

17 (16- 23)

1.2 (1.1-1.5)

2.18

Americas

5 (4 - 5)

1.2 (1.1-1.4)

35 (32- 40)

1.3 (1.2-1.5)

1.09

Australasia

0.1 (0-0.1)

0.2 (0.1-0.3)

0.3 (0.1-0.3)

0.2 (0.1-0.3)

0.94

Top 10

China

7.6 (7.1-8.6)

5.4 (5-6.1)

137 (128 - 153)

8.7 (8.2-9.8)

1.53

India

3.4 (3.3-3.7)

2.0 (1.9-2.2)

34 (32- 38)

3.9 (3.7-4.3)

1.61

Nigeria

2.1 (1.8-2.5)

5.7 (5-6.9)

16 (15- 17)

11.7 (10.7-12 .6)

1.82

Pakistan

1.8 (1.7- 2)

7.6 (7.2-8.6)

9 (9- 10)

8.8 (8.4-9.9)

1.22

United State s

1.5 (1.4-1.6)

0.8 (0.8-0.9)

11 (11- 12)

0.7 (0.7-0.8)

0.90

Brazil

1.0 (0.9-1.2)

2.0 (1.7-2.4)

10 (9- 12)

2.4 (2.1-2.8)

1.22

Egypt

0.8 (0.7-0.8)

34.1 (31.6-35 .8)

25 (23- 26)

36.5 (34- 38)

1.07

Viet Na m

0.8 (0.7-0.8)

10.3 (9.3-11.2)

15 (15- 17)

15.9 (15.2-17 .2)

1.41

Mex ico

0.7 (0.6-0.8)

1.9 (1.7-2.3)

4 (4- 5)

3.7 (3.2-4.4)

1.91

Indonesia

0.6 (0.5-0.7)

1.1 (0.9-1.3)

10 (8- 11)

2.3 (2-2.7)

2.03

Cropland and produ ction losses are generated u sing data from refs. 4, 15, and 17. We differentiate between d ifferent
urbaniza tion p robability th resholds (50, 75, an d 87.5 %). Depending on the correspon ding threshold, w e defin e
cropland loss s cenarios as fol lows: low (>87.5%), medium (>75 %), and high (>50%). Me dium -scenario re sults ar e
reported, an d ranges indicate low- to high- scenario resu lts. The 10 cou ntries with th e highest absolute crop
productio n losses are present ed in d escending order.
The analysis reveals relative cropland losses of 5 – 6% (8 – 9 Mha) and pr o ducti vity l osses of 8 – 10% ( 128 –
153 P cal) b etween 20 00 an d 20 30 (Tab le 1). Results for In dia are m arkedl y differen t. Total urb an e xtent in
2000 is an order of ma gnit ude smaller than in China (3 Mha compared with 8 Mha), and absolute urban
area expansion until 2030 is expected to cover one-half as much area as in China (3 – 4 Mha compared with
7 – 8 Mha). This difference in urban expansion is in large part explained by very dif ferent urbanizati on and
urban expansion trends (United Nations, 2014) . Whereas China’s urban population exceeded its rural
population in 201 2 and is expected to be 75% of the total populati o n by 2050, In d ia’s urban population is
currently less than one-thir d of the total populati on and by 2050 will just be over o ne -half. Furthermore,
as of 2011, 7 9% of India’s total population resided in settle ments o f 100,000 o r fewer, and 52% o f the
country lived in towns and villages with populations fewer than 5,000 (Mitra et al., 2016). This is in star k
contrast to China. Althoug h cro pland loss is currently not an issue in Ind ia (about 2% by 2030; Table 1),

96

other studies corrobora te that it is likely to become mo re sig nificant in the future when the countr y’s
urban expansion begi ns to accelera te (P ande y and Set o , 2015).

Figure 2 – Competition between cropland s an d urban expansion in select MUR s. Th e maps show wh ere projected
urbaniza tion until 2030 is exp ected to re s ult in croplan d loss. Competing areas (red) hold crop lands b ut have a h igh
probab ility (>75%; medium sc enario) of becoming u rbanized by 2030. MURs d isplayed ar e (A ) Pearl Ri ver Delta, (B)
Yangtze River Delta, (C) Bohai Economic Rim, ( D) Tokaido Corrid or, ( E ) Delhi N ational Cap ital Region an d Jaipur , (F)
Ganges-Brah maputra Delta (Kolkata , Dhaka, and Chittagong Region), ( G) Ja va, (H) North east Megalop olis, (I)
Expan ded Metrop olitan Complex of São Pa ulo, (J) Gr eater Ib adan Lagos Accra Corrid or ( GILA), and (K) Greater Cairo
Region. See Supp orting Infor mation for more details.

In African c o untrie s, there will b e signifi cant variati on in the ge ographic distrib uti on and rate s of croplan d
loss. Cro plands in less arid zones are expected to be relatively less affecte d by urbanization. Nigeria,
Africa’s most p opulous country, will experience high rates of urban expansi on and 5 – 7% cropland loss
(Table 1). Urban expansion will b e conc entrated along the c ontinent’s c o astlines, whereas the majorit y of
cropland lies inland (Fig. 1). The region around Lake Victoria w ill experience the highest rates of urban
expansion. In particular, for Burundi and Rwanda, the high rates of expected cropla nd co nversion to urban
( ∼ 28 and 34%) reflec t the l imited availabilit y of land i n those countries.
Our disag gregated anal y sis for individual stapl e crops sh ows their relative importa nce in urb anizing areas.
In 2000, 4% of m aiz e, 9% of rice, 2% of soybean, and 7% of global wheat production were grown in areas
that are forecast to be urbanized ( Table S1). Although the r esults fo r Europe (r ange between 2 and 3%),

97

the A m eri cas (1 – 2%), an d A ustralasia (all <1%) indicate low compe tition f or these key staples, the findings
for Asia and Africa suggest significant losses of specific cro ps. In Asia, 10% o f maize, 9% of rice, 7% o f
soybean, and 13% of wheat production were produced in areas that will be urba nized by 2 030. In Africa,
these shares range from 11% of s oybean production to 26% of the continent’s wheat producti on (14%
maize, 19% ric e).
We further analyzed cropland loss fo r a selection of MURs, defin ed as continuous urban regions with
multiple urban centers and a co mbined population greater than 20 million, often expanding over 10,000
km2. P ri me agricultural land s are especially vulnera ble to conv ersion in MURs with estimated cropland
losses b etween 0.1 and 1.2 Mha for the 11 cas e studies (Fig. 2 an d Table S2). With the e xception of the US
Northeast, th e produc tiv ity o f the cr opland c onverted in MUR is higher than national averages ( Table S2).
Notably, in MURs of India, Ban gladesh, and Indonesia, the relative productivity is >2 (Fig. 2 E – G). In Chines e
MURs, the r elative pr o ductivity is 1.05 – 2 . 05 (Fig. 2 A – C).
To understand agricultural production patterns aroun d these ev olving MURs, we analyzed the harvested
area fraction (HAF) — the ratio o f harvested area of a specific crop over the total harvested area — in
competing areas of the ab ovementioned staple crops an d a selection of cash crop s specific to some of the
MURs (cacao, o il pal m, sugarcane; Table S2). The aggregated HAF for these crops is high in most of the
MURs. In the Yangtze Rive r Delta around Shanghai, f or example, the combined HAF o f rice and wheat
accounts for 50% of total area harvested in competing areas. In contrast, the comb ined HAF is very low for
the United States, Brazil, and Japan, indicating that these areas are used to grow other crops such as
vegetables. HAF is also low for the Great er Ibadan L ag os Accra (GILA) corrido r in Western Africa, wher e
these cr ops only contribut e marginally to diets. The prevalence of the cash cro ps analyzed is c omparatively
low (the exc eption is sug arcan e around Delhi with HA F of 18%).
The spatial pattern of urban expansion plays an important role in croplan d lo ss. MURs are o ften
characterized by multiple urban cente rs, with productive cropland dis tribute d throughout the urban
fabric. Although the aggreg ate amount of cropland in these regions may be high, each patch o f cropland
is relatively small and thus vulnerable to urban envel opment (Pearl River Delta, Fig. 2A). In regi ons with a
single dominant urban center, such as Greater D elh i (Fig. 2E), urban envelopment of cropland is still
contained around the urban co re, with little evidence o f large-scale c ontinuous urb an fabric develop m ent.
Cropland in these r egi ons will continue to be conver ted (Pandey and Seto, 2015), but not at the same
magnitude as in multin odal urb an regions.
As urban areas expand, the remaining croplands and farmers at the periurban interface experien ce greater
competition for water and increased exposure to clim ate hazards. The u rban expan sion into the Ganges-
Brahmaputra Delta, for example, has resulted in the loss of wetlands and water b odies tha t serve a s flood
protection (Dewan et al., 2012) . In addition, croplan d conversion led to a sinking o f the delta due to a
combination of sedi ment loading , compaction, ground water extracti on, and reduced aggradation. This
makes the delta increasing ly vulnerable to hazards associated with climate chang e, such as sea level rise
(Higgin s et al., 2014), and threatens not only urban areas but a lso the remaini ng croplands that were
largely used to feed the reg ional populati on with rice ( HAF of rice >83%; Tabl e S2) .
Sea level rise and subsiden ce are also significant con cerns for Greater Cairo, because a considerab le
fraction of the Nile D elta i s already near or below sea level and expected to sin k further (Syvitski et al.,
2009). Diminishin g sedi m ent discharge due to da m s in the south will incr ease the pressure on the delta,

98

which will eventually decrease in size (Redeker and Kantoush, 2 01 4). Our results show that urbaniz ation
converts precarious cropla nds at hig h rates al ong the Nile even though they are i mportant for maintaining
food supply of the urban centers [combined HAF for wheat and maize, 49% (Table 1 and Table S2)]. Efforts
to divert urbanization away from the fertile lan ds into the deserts are underway but have been less
effective than hoped (R edeker and K anto ush, 2014).

3.4. Discussion
Our study sh o ws that futur e urban expansi on is expected to convert 27 – 35 Mha of cr oplands (1.8 – 2.4% of
global cropland and 3.4 – 4.2% o f the yearly production) globally between 2000 and 2030, adding an
additional c omponent t o the emergi ng global co nseq uences of land us e (T urner et al., 2007). On averag e,
this amounts to an annual land consumption of 1 Mha, wh ich is almost a third of the annual agricultural
expansion between 1 961 and 2009 o f 3.38 M ha ⋅ y − 1 (FAOSTAT, 2015). Our study is limited by the spati al
resolution of the analysis; although higher-resolution data w ould generate more detailed insights, these
results provide a global assessmen t of the patt erns of likely cropland loss due to urban expansion.

3.4.1. Compensating Cropland Loss
On agg regate, the l oss of cr o pland can be c ompensated by the gl o bal food s ystem, bu t the effects will n ot
be distributed equ ally. Many less develop ed and e mergin g countries will face acu te losses, both in abs o lute
and relative terms (Table 1 and Table S3). In princip le, cro pland loss c o uld be co mpensated by in te nsif ying
existing production or e xpanding cro pland. However , th e domestic adaptation potential varies
substantially by country and m ay be limited. For example, many sub-Saharan countries have ampl e
potential for extensifica tion and could additi o nally ai m to close their yield gap by impr oving agricultural
management and te chn o logy (West et al., 2 014). The opti on to expand croplan d is constrain ed in other
regions, such as Southern Asia, where much o f the suitable land is already under intense, multicropping
cultivation. Expansi on in these regions is likel y to occur in less suitable areas, thus requiring
disproportionat ely more la nd (Wirsenius et al., 2010). Other countries in arid regi ons, especial ly N o rthern
Africa and the Middle East, have nearly reached their maxi m um poten tial (Fetzel et al., 2016 ). The option
to expand is likely to be constrained further as clim ate change is expect ed to decrease the amount o f
suitable croplands throughout A frica, and Southern and Southeast Asia (Fisch er et al., 2002). Climate
change is also expect ed to adversely affe ct yields (Chall inor et al., 2014), ma king it harder for c ountries in
the tropical r egio ns of Asia and Africa to c ompensate for croplan d losses via int ensifi cation.
The loss of cr oplands and associated food productio n could also be offset by gl obal agricu ltural market s
and trade. Regardless of cropland loss t o u rbanization , the total volume of gl obal trade is likel y to rise, and
many developing re gi ons will see a decrease in foo d self -sufficiency (Erb et al., 2016). Many African
countries as well as China have experien ced a decline in the production- to -consumption ratio of f ood in
the last d ecade, indica ting rising imports (Fukas e and Martin, 2016). Countries with limited extensification
and intensification potential, such as Egypt, are likely to resort to trade to compensate fo r cropland loss ,
which c ould make the m more susceptibl e to in ternati o nal food sup ply sh ocks (Bren d’Am o ur et al., 2016) .

99

3.4.2. Food System Transition
Beyond the direct l oss of cropland, the growth of MUR s has other impor tant impli catio ns for food systems ,
especially for smallhold er farmers (Masters et al., 2013). Worldwide, there are about 500 million small
farms and an estimated 2 – 2.5 billion smallholder farmers who cultivat e farms of 2 ha o r smaller. Large
urban areas have seen a growth in super markets replacin g locally o wned or small-scale food retail stores
(Hu et al., 2004; Reardon and Berdegue, 2002). This trend is occu rring through out the developing world,
particularly in Eas t Asia, where the gro wth o f large cities and rising h ousehold in comes conve rg e to create
new demands for “mo der n” food retail supply chai ns. Additionally, super markets have gained greater
market shares over traditional stores in big cities (Nev en and Reardon, 2004). Thus, as MURs continue t o
grow in nu mber and size, fo od retail i s likely to bec o me increasin gly dominated by large supermarke t
chains. This has important implications fo r tradition al reta ilers, small-scale producers, traditional fo od
brokers, and the entire supply chain. In larg er cities, de centralized systems of food procure ment (individu al
stores and their buyers work directly with producers or food brokers) shift to a m ore centraliz ed system
focused o n large distribution cente r s. To protect small -scale produc ers and traditional retailers,
governments may interve ne. I ndia, for exampl e, has strictly regulated foreign direct invest ment into
multibrand retail (the Indian equivalent to large supermarkets ). Still, there is evidence of an “emerging
supermarket revoluti o n in In dia” (Re ard on and Mint en, 2 011), driven by d omestic capital. The l o ss of l ocal
food chains might compromise food a ccessibilit y in markets as local food chains historically have shown
to build resilience against price spikes (Mukherjee, 2015). Local producer s typically keep pric es low, to
maintain cus tomers, a m echanism supportin g resilient food securi ty (Keck and Etz old, 2013).

3.4.3. Livelihoods and Food Security
The dynami cs of agricultur al livelihood tran sformatio n are complex and involv e dispossessi on of pe asants
by agrobusinesses (Ross, 2 003). Urban land expansion also coincides with the loss of income and
displacement of periurba n livelihoods (Simon, 2008). However, econ omic develop ment and the
accompanying structural change are likely to provid e sufficient j ob opportunitie s. The transf o rmati o n of
food supply chains around evolving cities, for exampl e, offers ample nonfarm employment opportunities
along the food chain — in processing, logistics, and wholesal e (Reard on, 2015). A study from Ghana sho ws
that more than 50% o f households that lost access t o agricultural land engage in trading and o ther
activities, such as c onstruction, whereas 28% become une mployed (Kasanga, 19 98). As only 11% o f
households try to replace the land they had lost, the overwhelming majority wo uld aim to enter the
nonfarm lab o r market. Livelihood and food insecurity could become an issue for the househo lds that do
not find em pl oyment. Generally, urban food securit y depends not only on the availability o f foods in the
markets, but ultimately on the ability o f households to access food on their income (Cohen and Garrett,
2010). Hence, poor urban or periurban househ o lds, entaili ng the displaced farmers that are unemployed,
are at risk o f b ecoming f o od insecure (Crush et al., 2012). There is a myriad of other factors to ac count fo r
to assess whether h o useholds wo uld be bet te r or worse off. H o wever , such investigations ar e beyond th e
scope of this stud y.

100

3.4.4. Governance
To m eet the twin goals o f u rban devel opment t o h o us e the gro wing urban population an d preserve prime
cropland, it will be impera tiv e to guide and shape future urban expansion to m ore sustainable forms.
Different approa ches to safeguard agricultural land have been tried around the world, with different
outcomes. F or example, d espite numer ous edicts fro m the central government to protec t agricultural land
from conversion, agricultu ral land in China continues to be converted (Jiang et al., 2012). Regardless of
approach, good governan ce is a necessary condition for sustainable urbanization and critical for
successfully shaping urban expansion (Koroso et al., 2013) . The quality of governance in countries with
important cropland losses, however, tends to be mediu m to low in emerging economies and low fo r
developing co untri es (Kauf mann et al., 2011, and t able S4). A fact or specific to MURs is that the y often
consist of multiple contigu ous entities with discr ete governance structure s. More comprehensive
governance regi mes c o uld be helpful to mitigat e pr essures fr om urb anizati o n on food syst ems an d
ecosyste ms in urban hinter lands (Barthel et al., 2 013).
Urban policy makers and p lanners play a crucial r ole in managing urban area expansion. Containin g the
expansion of u rban areas is a well-estab lish ed planning approach to encourage compa ct, public transport-
oriented urban for ms, crucial for securing long-term climate mi tigation goals (Creutz ig et al., 2016). The
same approa ch also pres erv es agricultural lands in periurban area s (Daniels, 199 9 ). Howe v er, the
effectiven ess of urban c ontain ment strategies around the world is mixed, and its success depends on m an y
factors, including the willp ower of policy makers, and geographic and instituti o nal contexts (Dawkins and
Nelson, 2002). An alternative approach involves selective protection o f open space fro m urban
encroachmen t (Ang el et al., 2011). One policy instrument to use in this resp ect m ay be transfer of
development rights that effectively redirects new growth from areas to be protected (e .g., prim e
agricultural fields) to areas where more develop ment is desired (J ohnston and Madison, 1997). Howev er,
national policy makers a re also impor tant by designin g crucial econ omic incentives. In particular , fuel tax es
have al so both e mpirically and theoreticall y been shown to indu ce more compact urban fo rm and pr eserve
open space (Cr eutzig, 201 4; Creutzig et al., 2015).

3.5. Conclusion
As Seitzinger et al. (20 12) argue, “Urban regions m us t take an increased responsi bility for motivating and
implementing solutions tha t take into ac count their pr o found connections with and impa cts on the rest of
the planet.” Nowhere is this mo re evident than a t the interface of urban areas and croplands. The nex t
few decades will be a perio d o f large-scale urb an expa nsion, and in many parts o f the w orld, this will t ake
place on prime cropland. Our fin dings show that, for a few countries, the loss of croplan d will significantl y
reduce the total share of national cropland . As most of the cropland expected to be convert ed is more
productive than th e global average, eff o rts will ne ed to compensate for that loss, whether by intensif yin g
remaining cropland or by expanding agricultural production into new areas. The results sugges t that
strategies and policies to effectively steer patterns o f urban ex pansi o n will be critical for preserving
cropland. In an in creasingly interconnected world, the sustainab ility of urban areas cannot be considered
in isolation fr o m the sustai nability of res ources and liv elihoo ds els ewhere.

101

3.6. Materials and Methods
We base our study on a spatially expl icit urban area expansion probability datase t (Seto et al., 2012) and
two gridded datasets on global croplands in 2000 ( Ramankutt y et al., 2008) and 2005 (Fritz et al., 2015) .
We use a dataset on gridde d global crop yields in 200 0 (Monfreda et al., 2008) to calculate the productivity
of the displaced land. Yie lds of the 16 most i mportant crops (listed in Supporting Informati o n) are
converted to calories and aggregated in a single dataset, weight ed with area harvest ed. We supplement
this with a disaggregated analysis of fo ur stap l e crops (maize, rice, soybean, and wheat) and three cash
crops ( cacao, oil pal m , and sugarcane). W e ass ess the impact of urban ar ea expan sio n by inters ect ing three
distinct urbanization projections for the year 2030 with the cropland dataset for the y ear 2000. The
resulting cr o pland and prod uction lo ss sc enarios ar e “low ” (with a restricti v e threshold inclu ding o nly g rid
cells exceeding 87.5% urbaniz ation probability), “med ium” (>7 5% urbanizati on probability), and “ high”
(>50% urbanization probability). As a “best guess,” we as sume that all grid cells with >75% probabil ity of
becoming urbanized (medi um scenar io) will be affected b y urb anization until 2030. Pleas e see Su pportin g
Information f or a detail ed description.

Acknowledgemen ts
We acknowledg e the contrib ution of Ulf Weddige from the Mercator Resea rch Institute on Global
Commons and Climate Chang e, Graham Furniss from t he University of Canterbu ry, an d Sung Bae from the
BlueFern Superco m puting Services. We thank the EarthS tat team for support in data - re lated inquiries.
Thanks to Stockhol m Resilience Centre, University of Gävle, and Formas for funding S.B.; Stiftung der
Deutschen Wirtschaft for funding C.B.d.; ERC-2010-stg -263522 LUISE fo r fundin g K.-H.E.; and NASA Grants
NNX15AD4 3G and NNX 1 1AE88G for supporting B.G. and K.C.S.

102

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