on February 6, 2017http://rstb.royalsocietypublishing.org/Downloaded from rstb.royalsocietypublishing.orgResearch
Cite this article: Drescher J et al. 2016
Ecological and socio-economic functions across
tropical land use systems after rainforest
conversion. Phil. Trans. R. Soc. B 371:
20150275.
http://dx.doi.org/10.1098/rstb.2015.0275
Accepted: 27 January 2016
One contribution of 17 to a theme issue
‘Biodiversity and ecosystem functioning
in dynamic landscapes’.
Subject Areas:
ecology, environmental science, plant science,
taxonomy and systematics
Keywords:
agroforestry, biodiversity and ecosystem
function, deforestation, EFForTS, oil palm,
jungle rubber
Author for correspondence:
Jochen Drescher
e-mail: jdresch@gwdg.de& 2016 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.†Equally contributing first authors.
‡Equally contributing senior authors.
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rstb.2015.0275 or
via http://rstb.royalsocietypublishing.org.Ecological and socio-economic functions
across tropical land use systems after
rainforest conversion
Jochen Drescher1,†, Katja Rembold2,†, Kara Allen4, Philip Beckscha¨fer5,
Damayanti Buchori6, Yann Clough10,11, Heiko Faust12, Anas M. Fauzi7,
Dodo Gunawan13, Dietrich Hertel14, Bambang Irawan15, I. Nengah S. Jaya8,
Bernhard Klarner1, Christoph Kleinn5, Alexander Knohl3,
Martyna M. Kotowska14, Valentyna Krashevska1, Vijesh Krishna16,
Christoph Leuschner14, Wolfram Lorenz1, Ana Meijide3, Dian Melati5,
Miki Nomura17, Ce´sar Pe´rez-Cruzado5, Matin Qaim16, Iskandar Z. Siregar9,
Stefanie Steinebach18, Aiyen Tjoa19, Teja Tscharntke10, Barbara Wick1,
Kerstin Wiegand20, Holger Kreft2,‡ and Stefan Scheu1,‡
1Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, University of Go¨ttingen,
Berliner Strasse 28, 37073 Go¨ttingen, Germany
2Biodiversity, Macroecology and Conservation Biogeography, University of Go¨ttingen, Bu¨sgenweg 1,
37077 Go¨ttingen, Germany 3Bioclimatology, and 4Soil Science of Tropical and Subtropical Ecosystems, Bu¨sgen
Institute, University of Go¨ttingen, Bu¨sgenweg 2, 37077 Go¨ttingen, Germany
5Chair of Forest Inventory and Remote Sensing, University of Go¨ttingen, Bu¨sgenweg 5, 37077 Go¨ttingen, Germany
6Department of Plant Protection, 7Department of Agroindustrial Technology, 8Forest Resources Inventory and
Remote Sensing, and 9Department of Silviculture, Bogor Agricultural University, Kampus IPB Darmaga,
Bogor 16680, Indonesia
10Agroecology, Department of Crop Sciences, University of Go¨ttingen, Grisebachstrasse 6, 37077 Go¨ttingen,
Germany
11Centre for Environmental and Climate Research, Lund University, So¨lvegatan 37, 22362 Lund, Sweden
12Department of Human Geography, University of Go¨ttingen, Goldschmidtstrasse 5, 37077 Go¨ttingen, Germany
13Centre for Climate Change and Air Quality, Agency for Meteorology, Climatology and Geophysics (BMKG),
Jln Angkasa I No. 2, Jakarta 10720, Indonesia
14Department of Plant Ecology and Ecosystem Research, Albrecht-von-Haller Institute for Plant Sciences,
University of Go¨ttingen, Untere Karspu¨le 2, 37073 Go¨ttingen, Germany
15Faculty of Forestry, University of Jambi, Jln Raya Jambi-Muara Bulian km 15, Mendalo Darat, Jambi 36361,
Indonesia
16Department of Agricultural Economics and Rural Development, University of Go¨ttingen, Platz der Go¨ttinger
Sieben 5, 37073 Go¨ttingen, Germany
17Graduate School of Life Sciences, Tokohu University, Aroba 6-3, Aramaki, Aoba-ku, Sendai 980-85478, Japan
18Institute of Social and Cultural Anthropology, University of Go¨ttingen, Theaterplatz 15, 37073 Go¨ttingen,
Germany
19Agriculture Faculty of Tadulako University, Jln Soekarno Hatta km 09, Tondo, Palu 94118, Indonesia
20Ecosystem Modelling, University of Go¨ttingen, Bu¨sgenweg 4, 37077 Go¨ttingen, Germany
JD, 0000-0002-5162-9779
Tropical lowland rainforests are increasingly threatened by the expansion
of agriculture and the extraction of natural resources. In Jambi Province,
Indonesia, the interdisciplinary EFForTS project focuses on the ecological
and socio-economic dimensions of rainforest conversion to jungle rubber agro-
forests and monoculture plantations of rubber and oil palm. Our data confirm
that rainforest transformation and land use intensification lead to substantial
losses in biodiversity and related ecosystem functions, such as decreased
above- and below-ground carbon stocks. Owing to rapid step-wise transform-
ation from forests to agroforests to monoculture plantations and renewal of
each plantation type every few decades, the converted land use systems are
rstb.royalsocietypublishing.org
Phil.Trans.R.So
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of animal and plant communities. On the other hand,
agricultural rainforest transformation systems provide
increased income and access to education, especially
for migrant smallholders. Jungle rubber and rubber
monocultures are associated with higher financial land
productivity but lower financial labour productivity
compared to oil palm, which influences crop choice: small-
holders that are labour-scarce would prefer oil palm while
land-scarce smallholders would prefer rubber. Collecting
long-term data in an interdisciplinary context enables
us to provide decision-makers and stakeholders with
scientific insights to facilitate the reconciliation between
economic interests and ecological sustainability in tropical
agricultural landscapes.c.B
371:201502751. Introduction
Growing human population and rising per capita consump-
tion lead to ecosystem degradation and biodiversity decline
worldwide [1–5]. Agricultural expansion for the production
of food, feed, fibre and fuel has generated fundamental
benefits for human welfare (e.g. [6]) but comes with a variety
of costs [7,8]. These costs may compromise human well-being
in the long term [9], as they are linked to greenhouse gas
emissions [10], declining biodiversity [11,12] and degradation
of a variety of regulatory ecosystem services that affect air
quality, purification of water, carbon storage or soil erosion
[13–15]. It is commonly assumed that the conversion of natu-
ral to agricultural systems leads to major losses of important
ecosystem services [16]. However, the degree to which agri-
cultural systems still provide certain ecosystem services
strongly depends on the converted ecosystem, the type of
planted crop, the spatial dimensions of plantations, and the
management practices in place [17]. With the exception of
small-scale experiments, the mechanisms governing the
relationship between biodiversity and ecosystem functions
(BEF, [3]) remain poorly understood [18], especially in tropical
rainforest ecosystems, which experience massive transform-
ations and varying land use intensities [19]. In order to
understand BEF relationships in rainforest transformation sys-
tems as well as to facilitate the reconciliation of economic
interests and ecological sustainability therein, detailed ecologi-
cal and socio-economic evaluations of these systems are
needed, both at different spatial and temporal scales as well
as under different institutional conditions [20,21].
In tropical Asia, a rapidly growing population [22,23] and
agricultural expansion coincides with one of the highest levels
of biodiversity and endemism worldwide [24,25]. Rainforests
in Southeast Asia have been logged on a large scale since
themid 20th century, usually followed by subsequent transform-
ation of logged-over rainforests into cash crop monocultures
[26,27], such as acacia, rubber and oil palm. In Indonesia, this
process has accelerated during the past decades, where annual
loss in rainforest cover was estimated at 0.84 million hectares
for the year 2012, the highest worldwide [28]. Large-scale con-
version of rainforest for agricultural use is particularly evident
on the island of Sumatra, which experiences the highest primary
rainforest cover loss in all of Indonesia [16,28,29].
In the Ecological and Socio-economic Functions of Tropi-
cal Lowland Rainforest Transformation Systems project(EFForTS project, http://www.uni-goettingen.de/crc990),
we comprehensively study the environmental processes as
well as the ecological and socio-economic dimensions of the
current agricultural transformation processes in Jambi Pro-
vince (figure 1). Four research foci serve as a basis for the
synthesis of this interdisciplinary project:
(1) Assessing the ecological and socio-economic functions
across rainforest transformation systems;
(2) Quantifying the effects of spatial and temporal variability
on ecological and socio-economic functions;
(3) Scaling-up of ecological and socio-economic functions
from local to landscape and regional scales and
(4) Contributing to approaches towards more sustainable
land use in tropical regions.
This long-term research project aims at an in-depth under-
standing of the drivers and consequences of rainforest
transformation into agricultural landscapes for biodiversity,
ecosystem functions and human well-being.
2. Study area
EFForTS conducts research in Jambi Province in Sumatra
(Indonesia, figure 2). Jambi Province covers a land area of
50 160 km2 [30] and stretches from the Barisan mountain
range in the west across extensive lowlands towards the
southern Malacca Strait in the east. The climate in Jambi’s low-
lands is tropical humid with two peak rainy seasons around
March and December, and a dryer period during July–
August (figure 3). Jambi’s rainforests have a long history of
exploitation, including traditional agroforestry systems and
the extraction of timber and non-timber products [31,32]. The
first large commercial logging concessions were issued in the
1970s [33]. Since then, governmental land and resource use pol-
icies have been combined with population migration schemes
to foster economic development [34,35]: rainforests, often pre-
viously logged, have been converted into intensively managed
agro-industrial production zones to grow cash crop trees of
rubber (Hevea brasiliensis) and oil palm (Elaeis guineensis) or
fast-growing tree species such as Acacia mangium for pulp
production. From 1967 to 2007, roughly 400 000 people
were resettled in a governmental transmigration programme
from densely populated regions like Java to Jambi Province
[36], who then mainly engaged in cash crop production.
As of 2014, more than 650 000 ha of rubber and more than
590 000 ha of oil palm are being cultivated in Jambi Province
[30]. Increasing population and agricultural activity led to
rapid land-cover changes in Jambi resulting in a continuous
decrease of rainforest cover. In 2013, only 30% of Jambi Pro-
vince was covered with rainforest (mainly located in
mountainous areas), while 55% was already converted into
agricultural land, and 10% of the land was degraded/fallow
(mainly comprising land awaiting conversion into
monocultures; figure 4).3. Study design
Rainforest conversion entails a variety of abiotic, biotic and
socio-economic changes [20]. EFForTS is thus based on three
major lines of research: (i) environmental processes, (ii) biota
and ecosystem services, and (iii) human dimensions
(figure 1). The data for environmental processes and biota
global
markets
policy-
making
ecosystem
services biological
diversity
climate
regulation
water balance
environmental processes biota and ecosystems human dimensions
species/habitat loss
ecosystem services
biological invasions
economic progress
demography, culture
land use conflicts
rainforest conversion
research, policy recommendations
soil degradation
climate change
economic
strategies
population
dynamics
Figure 1. Conceptual approach of the EFForTS project. EFForTS combines research on environmental processes, biota and ecosystems, and human dimensions
to understand the drivers and consequences of current agricultural development in Jambi Province (Indonesia).
0 5 10 20 km
Bukit Duabelas
National Park
Harapan
RainforestLubuk Kepayang
Dusun Baru
Bungku
Singkawang
Sungkai
PTPN VI
Pompa air
PT Humusindo
Pematang Kabau
Pauh
Sarolangun
Sumatra,
Indonesia
Jambi Province
Jambi City
Jambi City
Muara Bulian
(b)(a) (c)
(d )
core plot village
Legend
research village
household survey data
meteostation
climate measurement tower
biodiversity enrichment
experiment
core plots
roads
river
Jambi City
Jambi City
Figure 2. Location of EFForTS study sites in Sumatra (a,b) and Jambi Province (c,d). Socio-economic surveys are carried out all over Jambi Province (c), while the core
plot design is located in two landscapes near to Bukit Duabelas National Park and Harapan Rainforest (d ).
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‘core plot design’, while data on human dimensions were col-
lected in the ‘socio-economic survey design’.For the core plot design, we established research core plots
in four different land use systems (lowland rainforest, jungle
rubber, rubber monoculture and oil palm monoculture) in
50
°
C
40
30
20
10
0
300
100
80
60
40
20
0
m
m
Sulthan Thaha
1991–2011
average temp. 26.7 ± 0.2°C
annual precip. 2235 ± 381 mm
J F M A M J J A S O N D
Figure 3. Average monthly temperature and rainfall at Sulthan Thaha
Airport, Jambi City, from 1991 to 2011 (Sulthan Thaha Airport station).
The relation of average monthly rainfall (solid and striped blue) to average
monthly temperature (red line) illustrates Jambi’s humid climate, with
mean monthly rainfall above 100 mm throughout the year.
100
80
60
40
20
0
degraded land
agriculture and tree crops
forest
year
la
nd
 c
ov
er
 (%
)
1990 1995 2000 2005 2010 2013
Figure 4. Land cover in Jambi Province from 1990 to 2013. Data were
obtained by a series of Landsat imageries with spatial resolution of 30 
30 m. The entire area of Jambi Province was used as reference. Degraded
land (brown): shrubs, bare land, burnt areas; others (black): settlements,
water bodies, fishpond.
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apan landscape’ (figure 2). Rainforest core plots represent
‘primary degraded forest’ as classified by Margono et al. [28]
and show signs of selective logging and extraction of non-
timber rainforest products. Jungle rubber represents a small-
holder rubber agroforest system which is established by
planting rubber trees into (often previously logged) rainforests
[37]. All rubber and oil palm core plots have been established in
smallholder monoculture plantations, which varied in age
between 7 and 16 years for rubber and between 8 and 15
years for oil palm at the time of plot selection in 2012. All
core plots were established on Acrisol soils. While soils in the
Harapan landscape contain more even fractions of sand, silt
and clay (loam Acrisols), soils in the Bukit Duabelas landscapeare clay Acrisols, characterized by higher proportions of clay
[38]. In each landscape, we established four core plots in each
of the four land use systems, resulting in a total of 32 plots (elec-
tronic supplementary material, table S1). Each core plot
measures 50  50 m and contains five 5  5 m subplots at
fixed positions that were randomly assigned (electronic sup-
plementary material, figure S1). Each core plot is equipped
with a meteorological station which measures air temperature,
relative air humidity, soil temperature and soil moisture. The
core plot design is extended by a biodiversity enrichment
experiment and a meteorological monitoring network (see
the electronic supplementary material, text S2).
The ‘socio-economic survey design’ follows a complemen-
tary approach ranging from household (micro) and village
(meso) to national and international (macro) level using a
joint sampling framework (for details see [39], electronic sup-
plementary material, figure S2). This study mainly uses data
from village and household surveys, conducted during
August–December 2012. The socio-economic village survey
covers 93 randomly selected and five purposively selected vil-
lages. The latter come from the two core plot landscapes to
allow linking of ecological, environmental and socio-economic
data and integratedmodelling. The household survey includes
700 farmer households, of which 600 reside in the randomly
selected villages and 100 in the purposively selected ones.
Within the core plot and socio-economic design, a variety
of data were collected covering soil, water, atmosphere,
biogeochemical cycles, biomass, carbon stocks, above- and
below-ground biodiversities, community structure, food web
dynamics, energy and nutrient fluxes as well as economic (e.g.
profit, income, employment), social (e.g. income distribution,
risk, poverty, food security, culture, gender) and institutional
(e.g. sharecropping, property rights) factors. In the following,
we present key results and respective methods used to analyse
ecosystem functions, biodiversity of plants, above- and below-
ground invertebrates and key socio-economic characteristics.4. Material and methods
(a) Temperature and humidity
Below-canopy air temperature and relative humidity were
measured hourly by meteorological stations within each core
plot and stored using a UIT LogTrans 16-GPRS data logger.
The meteorological stations were equipped with thermohygrom-
eters (Galltec Melaw) placed at a height of 2 m to record air
temperature (8C) and humidity (%), and additional soil sensors
(IMKO TRIME-PICO) at 0.3 m depth to monitor soil temperature
(8C) and moisture (vol %).
(b) Canopy openness
Canopy openness was derived from hemispherical photographs
taken at 1.2 m above the ground from 32 positions within each
core plot (Canon EOS 700D SLR camera and SIGMA 4.5 mm
F2.8 EX DC circular fisheye lens). A bubble level slotted into
the flash socket, vertically levelled the camera and aligned it to
the magnetic north. Exposure was determined by following a
histogram-exposure protocol [40] and photographs were pro-
cessed by applying the ‘Minimum’ thresholding algorithm’ [41]
using ‘ImageJ’ [42].
(c) Leaf litterfall
Leaf litterfall was measured monthly from March 2013 to April
2014 by placing 16 litter traps (75  75 cm) in each core plot.
rstb.royalsocietypublishing.org
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palm fronds are pruned with each harvest as a standard manage-
ment procedure. We measured the dry weight of 16 fully grown
palm fronds (two per core plot in oil palm plantation) and counted
all pruned palm fronds during harvest, thus allowing to calculate
average ‘litterfall’ in oil palm plantations per area and time.
(d) Litter carbon
To determine the amount of litter in the litter layer, five cores of a
diameter of 5 cm were taken from each plot and pooled, resulting
in 32 samples. The material was dried at 658C for 72 h and
weighed. Aliquots of the material were milled and analysed for
total C concentrations using an elemental analyser (Carlo Erba,
Milan, Italy). From these data, the total amount of C per area
was calculated.
(e) Tree biomass
Height anddiameterat breast height (DBH) of all trees andpalms in
the core plots were recorded. Wood density was determined for
cores of 208 trees (10 each in rainforest and jungle rubber plots,
five each in rubber plantations). Interpolated values were applied
for the remaining trees basedonacalibration equationwithpinpen-
etration depth. Rainforest understorey trees with a diameter of
2–10 cm were inventoried in the same way on two subplots in
each plot. Above-ground biomass, coarse-root and root stock bio-
mass were modelled using standard allometric equations [43–47].
Fine-root biomass was assessed separately using 10 vertical soil
cores (3.5 cm in diameter) down to 50 cm soil depth including the
organic layer on each plot, from which all fine-root segments
longer than 1 cm were extracted. The C concentration of all com-
ponents (stem wood, fine roots and leaf litter) was analysed with
a CN Analyser (Vario EL III, Hanau, Germany).
( f ) Plant species richness
Plant species numbers include all treeswith aDBH  10 cmwithin
the entire core plot, plus all vascular plant species foundwithin the
five subplots nested within each core plot.
(g) Ant species richness
Arboreal arthropods were sampled from three locations in each of
the 32 core plots by canopy fogging. We used DECIS 25 (Bayer
CropScience) mixed with petroleum-based white oil in a 9 : 1
ratio (white oil : DECIS25) forming a visible fog which allows
directing the fog towards the target canopies. Target canopies con-
sisted of mixed tree canopies in rainforest and jungle rubber, two
trees in rubber plantations, and one palm in oil palm plantations.
Paralysed and dead arthropods were collected in 16 funnels of
1 m2 per replicate; each funnel was fitted with a plastic bottle con-
taining 96% EtOH. Immediately after sampling, the specimens
were cleaned of debris, washed, EtOH exchanged, and stored at
2208C.
(h) Oribatid mite species richness
Oribatid mites (Oribatida, Acari) were extracted from soil cores
of 16  16 cm taken from each core plot with a spade. Litter
and top soil layers (to a depth of 5 cm) of each sample were
extracted separately using the high-gradient canister method in
modified Kempson extractors [48].
(i) Labour and gross margin
Labour intensity (’00 h ha21 yr21), gross margin per land unit
(million IDR ha21 yr21) and gross margin per work hour (‘0000
IDR h21) are based on the socio-economic survey of 700 farmer
households [39]. These data are available for all threetransformation systems except rainforest, i.e. jungle rubber,
rubber plantations and oil palm plantations.5. Results and discussion
Data from the core plots and socio-economic surveys after 3
years of measurement reveal marked differences in key factors
and processes between the four land use systems (figure 5).
Stand microclimate, vegetation structure, biodiversity and
carbon fluxes differ significantly between rainforest andmono-
cultures of rubber and oil palm, while jungle rubber often takes
an intermediate position. Rainforest was characterized by
lower mean air temperature and higher humidity compared
with the other land use systems (figure 5a,b), corresponding
to a denser canopy (figure 5c). Litterfall was significantly
lower in rubbermonoculture than in the other land use systems
(figure 5d ) and carbon stored in the litter layer was highest in
rainforest (figure 5e). It is important to note that litterfall in
oil palm plantations does not occur naturally, but leaves are
cut during fruit harvest and piled up in rows between oil
palms. Heterogeneous litter distribution in oil palm may lead
to the apparent discrepancy between high leaf litter input
(figure 5d) but low litter carbon stock (figure 5e) in oil palm,
as the latter was not measured in piles of palm fronds. The
decrease of leaf litter from rainforest to jungle rubber, rubber
plantation and oil palm plantations may explain the significant
decrease in species richness, density and biomass of leaf litter
invertebrates, reducing energy fluxes from rainforest to oil
palm communities by up to 51% [49]. Rainforests contained
more than twice as much above- and below-ground tree bio-
mass carbon as jungle rubber, and more than four times as
much as the monoculture plantations (figure 5f, see also [50]).
Species richness in the agricultural land use systems was
significantly lower than in rainforests. This is particularly
apparent in vascular plants, where rainforest had almost six
times as many species as the monocultures (figure 5g). Pre-
vious research suggests that plant diversity is a reliable
predictor of arthropod diversity in the tropics [51]. This is con-
firmed by our data, where above-ground consumer species
richness (here: canopy ants) was about twice as high in rainfor-
est as in the converted ecosystems (figure 5h). For both vascular
plants and canopy ants, there is a clear shift from communities
dominated by native species in rainforest and jungle rubber
towards communities dominated by introduced species in
rubber and oil palm plantations (J. Drescher & K. Rembold,
personal observation 2015). Species richness of below-ground
consumers (here: oribatid mites) shows a similar but less pro-
nounced decline from rainforest towards the other land use
systems.
The three agricultural land use systems, jungle rubber,
rubber plantation and oil palm plantation, differ markedly
in key socio-economic properties. Comparing the plantation
crops, oil palm required significantly less labour per hectare
than jungle rubber and rubber monocultures (figure 5j ),
but generated relatively lower gross margin per unit area
(figure 5k). However, the gross margin per unit of labour
was highest in oil palm (figure 5l ). Hence, when labour is
limited, farmers have an incentive to grow oil palm; farmers
for whom land is the scarcest factor in turn have an incentive
to grow rubber. Interestingly, jungle rubber has a similar
gross margin as rubber monoculture per unit of labour
(lower than oil palm), but is not competitive with rubber
m
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(b)(a) (c)
(d ) (e) ( f )
(g) (h) (i)
( j) (k) (l)
Figure 5. Environmental (blue), ecological (green) and socio-economic (yellow) differences among rainforest (F), jungle rubber (J), rubber (R), and oil palm (O) planta-
tions. Three outliners are not shown: (k) 7100 rubber labour hours, (l) –52.2 and –25.6 oil palm gross margin/labour. Letters indicate significant differences between land
use systems ((a– i) ANOVA, Tukey’s HSD test, p, 0.05; ( j– l) Kruskal–Wallis/Kruskalmc test, p, 0.05) (for details, see the electronic supplementary material).
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tion of jungle rubber into rubber plantations. In 2012, about
50% of the land in the surveyed villages was rubber, includ-
ing both jungle rubber and monoculture plantations, while
12% was cultivated with oil palm (an increase from 5.0% 10
years earlier, with an increase of 8.5% for the entire study
area during the same period). Most of the remaining village
land was covered by rainforest (17%) at various stages of
degradation or by fallow land (15%). Fallow land often rep-
resents degraded land dominated by shrubs after clear-
cutting in preparation for agricultural use. While most of
the plantations and fallow lands in the villages are held
and managed by individual smallholder households, the
rainforest land within village boundaries is usually managed
by the state and only occasionally by the community. Small-
holders in Jambi Province grow hardly any food crops, except
for certain villages near urban centres. The socio-economic
surveys revealed that the recent and ongoing transformation
of land use systems other than oil palm started among the
migrant population in the late 1980s, whereas the local popu-
lation has engaged in oil palm cultivation only since the mid1990s. Case study interviews revealed that land use change in
Jambi is largely founded on different layers of past and pre-
sent land rights which provoke the present controversy of
land use, resource exploitation and the socio-economic conse-
quences of these. The core drivers of land use change in Jambi
are private and public investment, federal development
schemes (i.e. for migrants) and the national Indonesian
policy of resource exploitation, all of which are fuelled by
the international demand for agrarian commodities such as
rubber and palm oil.
Together, these first results from this extensive research pro-
ject demonstrate that the conversion of rainforest into rubber
and oil palm monocultures leads to substantial losses in plant
and animal diversities, reduces above- and below-ground
carbon stocks to a fraction of their original state, and signifi-
cantly alters microclimatic conditions (figure 5). In-depth
studies further showed that this conversion process also
reduces energy fluxes, decreases soil fertility and increases
soil erosion [38,49,52]. While rainforest conversion into mono-
cultures has clearly negative effects on the environment, biota
and ecosystems, many smallholders benefit substantially from
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Phil.Trans.R.Soc.B
371:20150275
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[53,54]. Therefore, it is not surprising that rural population
growth has a strong impact on the ongoing deforestation [55].
The economic benefits of this transformation process, however,
are mainly experienced by landowners, while people without
land experience various disadvantages from land use intensifi-
cation towards monoculture cash crops, e.g. due to increasing
food prices [26].
This study delivered vital baseline data for the long-term
monitoring of BEF dynamics after rainforest conversion into
rubber and oil palm plantations. In order to be able to provide
evidence-based policy recommendations, however, comp-
lementary studies are necessary which go beyond recording
the status quo. Specifically, experimental studies targeting
land-sparing and land-sharing approaches [56,57] might pro-
vide realistic solutions which could then be presented to
policy-makers. While the running biodiversity enrichment
experiment (electronic supplementary material, Text S2) tests
a land-sharing approach in oil palm, future EFForTS data col-
lection will—among others—focus on rainforest conversion
and rubber/oil palm agriculture on waterlogged soils of
low productivity [58,59], thus analysing potentials for land
sparing in arable landscapes. Together, running long-term
data collections and experimental approaches will provide us
with a detailed understanding of the interactions and feedback
loops between humans, nature and environment in growing oil
palm- and rubber-dominated landscapes, and hold the key tothe reconciliation of conservation needs and socio-economic
development in Southeast Asia.Data accessibility. The datasets supporting this article have been
uploaded as part of the electronic supplementary material.
Authors’ contributions. J.D. and K.R. equally contributed to designing and
writing the manuscript with equal support from H.K. and S.Sc. as
senior authors. Data were provided by the following authors: climate:
A.M., D.G., A.K., soil: K.A., A.T., land use change: C.P.-C., D.N.M.,
I.N.S.J., C.K., canopy openness: M.N., P.B., K.R., H.K., leaf litterfall
and tree biomass: M.M.K., D.H., C.L. litter carbon: V.Kra., S.Sc., veg-
etation: K.R., H.K., tree heterogeneity: K.W., K.R., H.K., arboreal ants:
J.D., D.B., S.Sc., oribatid mites: B.K., S.Sc., labour and gross margin:
V.Kri., M.Q., migration background Jambi: S.St., socio-economic case
study: H.F. The EFForTS project was designed and realized by Y.C.,
H.F., A.M.F., B.I., A.K., H.K., W.L., M.Q., I.Z.S., S.Sc., S.St., A.T., T.T.,
B.W., K.W. All authors reviewed and approved the manuscript.
Competing interests. We have no competing interests.
Funding. EFForTS is financed by the German Research Foundation
(DFG) in the framework of the Collaborative Research Centre 990
(http://www.uni-goettingen.de/crc990).
Acknowledgements. We thank the Ministry of Research, Technology and
Higher Education (RISTEKDIKTI) for research permission in Indone-
sia. Sincere thanks to the staff of Harapan Rainforest/PT Restorasi
Ekosistem Indonesia, Bukit Duabelas National Park, PT Humusindo
and PTPN VI. We also thank our colleagues from the Indonesian
Institute of Sciences (LIPI) and the smallholders and families partici-
pating in the village/household surveys and core plot design. We
also thank two reviewers for constructive criticism which consider-
ably improved an earlier version of this manuscript.References1. Zhang X, Zwiers FW, Hegerl GC, Lambert H, Gillet
NP, Solomon S, Stott PA, Nozawa T. 2007 Detection
of human influence on twentieth-century
precipitation trends. Nature 448, 461–465.
(doi:10.1038/nature06025)
2. Gibbs HK, Ruesch AS, Achard F, Clayton MK, Holmgren
P, Ramankutty N, Foley JA. 2010 Tropical forests were
the primary source of new agricultural land in the
1980s and 1990s. Proc. Natl Acad. Sci. USA 107,
16 732–16 737. (doi:10.1073/pnas.0910275107)
3. Brose U, Hillebrand H. 2016 Biodiversity and ecosystem
functioning in dynamic landscapes. Phil. Trans. R. Soc. B
371, 20150267. (doi:10.1098/rstb.2015.0267)
4. Foley JA et al. 2005 Global consequences of land
use. Science 309, 570–574. (doi:10.1126/science.
1111772)
5. Dirzo R, Raven PH. 2003 Global state of
biodiversity and loss. Annu. Rev. Environ. Resour.
28, 137–167. (doi:10.1146/annurev.ebergy.28.
050302.105532)
6. Godfray HCJ et al. 2010 Food security: the challenge
of feeding 9 billion people. Science 327, 812–818.
(doi:10.1126/science.1185383)
7. Millenium Ecosystem Assessment. 2005 Ecosystems
and human well-being: synthesis. Washington, DC:
Island Press.
8. Newbold T et al. 2015 Global effects of land use on
local terrestrial biodiversity. Nature 520, 45–50.
(doi:10.1038/nature14324)
9. Dı´az S, Fargione J, Chapin III FS, Tilman D. 2006
Biodiversity loss threatens human well-being. PLoSBiol. 4, e0040277. (doi:10.1371/journal.pbio.
0040277)
10. Smith P et al. 2008 Greenhouse gas mitigation in
agriculture. Phil. Trans. R. Soc. B 363, 789–813.
(doi:10.1098/rstb.2007.2184)
11. Gibson L et al. 2011 Primary forests are
irreplaceable for sustaining tropical biodiversity.
Nature 478, 378–381. (doi:10.1038/nature10425)
12. Stork NE, Coddington JA, Colwell RK, Chazdon RL,
Dick CW, Peres CA, Sloan S, Willis K. 2009
Vulnerability and resilience of tropical forest species
to land-use change. Conserv. Biol. 23, 1438–1447.
(doi:10.1111/j.1523-1739.2009.01335.x)
13. Obidzinski K, Andriani R, Komarudin H, Andrianto H.
2012 Environmental and social impacts of oil palm
plantations and their implications for biofuel
production in Indonesia. Ecol Soc. 17, 25. (doi:10.
5751/ES-04775-170125)
14. van Straaten O, Corre MD, Wolf K, Tchienkoua M,
Cuellar E, Matthews RB, Veldkamp E. 2015
Conversion of lowland tropical forests to tree cash
crop plantations loses up to one-half of stored soil
organic carbon. Proc. Natl Acad. Sci. USA 112,
9956–9960. (doi:10.1073/pnas.1504628112)
15. Ro¨ll A, Niu F, Meijide A, Hardanto A, Knohl A,
Ho¨lscher D. 2015 Transpiration in an oil palm
landscape: effects of palm age. Biogeosciences 12,
5619–5633. (doi:10.5194/bg-12-5619-2015)
16. Laumonier Y, Uryu Y, Stu¨we M, Budiman A,
Setiabudi B, Hadian O. 2010 Eco-floristic sectors
and deforestation threats in Sumatra: identifyingnew conservation area network priorities for
ecosystem-based land use planning. Biodivers.
Conserv. 19, 1153–1174. (doi:10.1007/s10531-010-
9784-2)
17. Power AG. 2010 Ecosystem services and agriculture:
tradeoffs and synergies. Phil. Trans. R. Soc. B 365,
2959–2971. (doi:10.1098/rstb.2010.0143)
18. Balvanera P, Pfisterer AB, Buchmann N, He J-S,
Nakashizuka T, Raffaelli D, Schmid B. 2006
Quantifying the evidence for biodiversity effects on
ecosystem functioning and services. Ecol. Lett. 9,
1146–1156. (doi:10.1111/j.1461-0248.2006.
00963.x)
19. Scherer-Lorenzen M, Schulze E-D, Don A,
Schumacher J, Weller E. 2007 Exploring the
functional significance of forest diversity: a new
long-term experiment with temperate tree species
(BIOTREE). Perspect. Plant Ecol. 9, 53–70. (doi:10.
1016/j.ppees.2007.08.002)
20. Sodhi NS, Koh LP, Brook BW, Ng PKL. 2004
Southeast Asian biodiversity: an impending disaster.
Trends Ecol. Evol. 19, 654–660. (doi:10.1016/j.tree.
2004.09.006)
21. Steffan-Dewenter I et al. 2007 Tradeoffs between
income, biodiversity, and ecosystem functioning
during tropical rainforest conversion and
agroforestry intensification. Proc. Natl Acad. Sci. USA
104, 4973–4978. (doi:10.1073/pnas.0608409104)
22. Jones GW. 2013 The Population of Southeast Asia,
ARI Working Paper, No. 196, January 2013 Asia
Research Institute, Singapore.
rstb.royalsocietypublishing.org
Phil.Trans.R.Soc.B
371:20150275
8
 on February 6, 2017http://rstb.royalsocietypublishing.org/Downloaded from 23. United Nations Statistics Division. 2014 Demographic
Yearbook 2014. New York, NY. See http://unstats.un.
org/unsd/demographic/products/dyb/dyb2014.htm.
24. Sodhi NS, Posa MRC, Lee TM, Blickfprd D, Koh LP,
Brook BW. 2010 The state and conservation of
Southeast Asian biodiversity. Biodivers. Conserv. 19,
317–328. (doi:10.1007/s10531-009-9607-5)
25. Myers N, Mittermeier RA, Mitterleier CG, Da Fonseca
GAB, Kent J. 2000 Biodiversity hotspots for
conservation priorities. Nature 403, 853–858.
(doi:10.1038/35002501)
26. Koh LP, Ghazoul J. 2008 Biofuels, biodiversity, and
people: Understanding the conflicts and finding
opportunities. Biol. Conserv. 141, 2450–2460.
(doi:10.1016/j.biocon.2008.08.005)
27. Wilcove DS, Koh LP. 2010 Addressing the threats to
biodiversity from oil-palm agriculture. Biodivers.
Conserv. 19, 999–1007. (doi:10.1007/s10531-009-
9760-x)
28. Margono BA, Potapov PV, Turubanova S, Stolle F,
Hansen MC. 2014 Primary forest cover loss in
Indonesia over 2000–2012. Nat. Clim. Change 4,
730–735. (doi:10.1038/nclimate2277)
29. Miettinen J, Shi C, Liew SC. 2011 Deforestation rates
in insular Southeast Asia between 2000 and 2010.
Glob. Change Biol. 17, 2261–2270. (doi:10.1111/j.
1365-2486.2011.02398.x)
30. Badan Pusat Statistik. 2014 Jambi Dalam Angka
2014. Jambi, Indonesia. See http://jambiprov.go.id.
31. Andaya BW. 1993 To live as brothers: Southeast
Sumatra in the seventeenth and eighteenth centuries,
344. Honolulu, HI: University of Hawaii Press.
32. Kathirithamby-Wells J. 1993 Hulu-hilir unity and
conflict: Malay statecraft in East Sumatra before the
mid-nineteenth century. Archipel 45, 77–96.
(doi:10.3406/arch.1993.2894)
33. Suyanto S, Ruchiat Y, Stolle F, Applegate G. 2000
The Underlying Causes and Impacts of Fires in
South-East Asia: Site 3. Tanah Tumbuh, Jambi
Province, Indonesia. Site Report. Bogor, Indonesia.
CIFOR, ICRAF, USAID and USFS. See http://pdf.usaid.
gov/pdf_docs/Pnact619.pdf.
34. Elmhirst R. 2011 Migrant pathways to resource
access in Lampung’s political forest: gender,
citizenship and creative conjugality. Geoforum 42,
173–183. (doi:10.1016/j.geoforum.2010.12.004)
35. Gatto M, Wollni M, Qaim M. 2015 Oil palm boom
and land-use dynamics in Indonesia: the role of
policies and socioeconomic factors. Land Use
Policy 46, 292–303. (doi:10.1016/j.landusepol.
2015.03.001)36. Pemerintah Provinsi Jambi. 2008 Bangun Daerah
Tertinggal Melalui Program Transmigrasi. Jambi,
Indonesia.
37. Gouyon A, de Foresta H, Levang P. 1993 Does
‘jungle rubber’ deserve its name? An analysis of
rubber agroforestry systems in southeast Sumatra.
Agrofor. Syst. 22, 181–206. (doi:10.1007/
BF00705233)
38. Allen K, Corre MD, Tjoa A, Veldkamp E. 2015 Soil
nitrogen cycling responses to conversion of lowland
forests to oil palm and rubber plantations in
Sumatra, Indonesia. PLoS ONE 10, e0133325.
(doi:10.1371/journal.pone.0133325)
39. Faust H et al. 2013 Assessment of socio-economic
functions of tropical lowland transformation systems
in Indonesia: sampling framework and
methodological approach. EFForTS discussion
paper series.
40. Beckscha¨fer P, Seidel D, Kleinn C, Xu J. 2013 On the
exposure of hemipherical photographs in forests.
iForest 6, 228–237. (doi:10.3832/ifor0957-006)
41. Glatthorn J, Beckscha¨fer P. 2014 Standardizing the
protocol for hemispherical photographs: accuracy
assessment of binarization algorithms. PLoS ONE 9,
e111924. (doi:10.1371/journal.pone.0111924)
42. Rasband WS. 1997–2015 ImageJ. Bethesda, MD:
U.S. National Institutes of Health.
43. Chave J et al. 2005 Tree allometry and improved
estimation of carbon stocks and balance in tropical
forests. Oecologia 145, 87–99. (doi:10.1007/
s00442-005-0100-x)
44. Wauters JB, Coudert S, Grallien E, Jonard M, Ponette
Q. 2008 Carbon stock in rubber tree plantations in
Western Ghana and Mato Grosso (Brazil). For. Ecol.
Manag. 225, 2347–2361. (doi:10.1016/j.foreco.
2007.12.038)
45. Asari N, Suratman MN, Jaafar J. 2013 Estimation of
aboveground biomass for oil palm plantations using
allometric equations. In 4th Int. Conf. on Biology,
Environment and Chemistry. Singapore: IPCBEE,
IACSIT Press.
46. Niiyama K et al. 2010 Estimation of root biomass
based on excavation of individual root systems in a
primary dipterocarp forest in Pasoh Forest Reserve,
Peninsular Malaysia. J. Trop. Ecol. 26, 271–284.
(doi:10.1017/S0266467410000040)
47. Syahrinudin. 2005 The potential of oil palm and
forest plantations for carbon sequestration on
degraded land in Indonesia. Cuvillier.
48. Kempson D, Lloyd M, Ghelardi R. 1963 A new
extractor for woodland litter. Pedobiologia 3, 1–21.49. Barnes AD et al. 2014 Consequences of tropical land
use for multitrophic biodiversity and ecosystem
functioning. Nat. Commun. 5, 5351. (doi:10.1038/
ncomms6351)
50. Kotowska MM, Leuschner C, Triadiati T, Meriem S,
Hertel D. 2015 Quantifying above-and belowground
biomass carbon loss with forest conversion in
tropical lowlands of Sumatra (Indonesia). Glob.
Change Biol. 21, 3620–3634. (doi:10.1111/gcb.
12979)
51. Basset Y et al. 2012 Arthropod diversity in a tropical
forest. Science 338, 1481–1484. (doi:10.1126/
science.1226727)
52. Guillaume T, Damris M, Kuzyakov Y. 2015 Losses of
soil carbon by converting tropical forest to
plantations: erosion and decomposition estimated
by d13C. Glob. Change Biol. 21, 3548–3560.
(doi:10.1111/gcb.12907)
53. Rist L, Feintrenie L, Levang P. 2010 The livelihood
impacts of oil palm: smallholders in Indonesia.
Biodivers. Conserv. 19, 1009–1024. (doi:10.1007/
s10531-010-9815-z)
54. Murdiyarso D, Van Noordwijk M, Wasrin UR, Tomich
TP, Gillison AN. 2002 Environmental benefits and
sustainable land-use options in the Jambi transect,
Sumatra. J. Veg. Sci. 13, 429–438. (doi:10.1111/j.
1654-1103.2002.tb02067.x)
55. Miyamoto M. 2006 Forest conversion to rubber
around Sumatran villages in Indonesia: Comparing
the impacts of road construction, transmigration
projects and population. For. Policy Econ. 9, 1–12.
(doi:10.1016/j.forpol.2005.01.003)
56. Phalan B, Onial M, Balmford A, Green RE. 2011
Reconciling food production and biodiversity
conservation: land sharing and land sparing
compared. Science 333, 1289–1291. (doi:10.1126/
science.1208742)
57. Fischer J et al. 2011 Conservation: limits of land
sparing. Science 334, 593. (doi:10.1126/science.334.
6056.593-a)
58. Datta KK, Jong CD. 2002 Adverse effect of
waterlogging and soil salinity on crop and land
productivity in northwest region of Haryana, India.
Agric. Water Manag. 57, 223–238. (doi:10.1016/
S0378-3774(02)00058-6)
59. Ferry B, Morneau F, Bontemps J-D, Blanc L, Freycon
V. 2010 Higher treefall rates on slopes and
waterlogged soils result in lower stand biomass
and productivity in a tropical rain forest. J. Ecol.
98, 106–116. (doi:10.1111/j.1365-2745.2009.
01604.x)