Int J Primatol
DOI 10.1007/s10764-013-9671-2
Determining Sensitive Parameters
for the Population Viability of Reintroduced
Sumatran Orangutans (Pongo abelii)
Doris Kelle & Dominik Fechter & Alexander Singer &
Peter Pratje & Ilse Storch
Received: 30 June 2012 / Accepted: 14 February 2013
# Springer Science+Business Media New York 2013
Abstract Although reintroduction has been a widely implemented conservation tool,
in many cases it is unclear whether the released animals can successfully establish a
viable and self-sustaining population. We constructed a population model for
reintroduced Sumatran orangutans (Pongo abelii) and conducted a population viability analysis to evaluate the probability of persistence. We based our study on a
reintroduced orangutan population at Bukit Tigapuluh, Jambi, Central Sumatra,
Indonesia. We used various scenarios to assess the effects of adaptation time, number
of released individuals, duration of release period, variation in infant survival, and
carrying capacity on population extinction probability over time. We found that
behavioral adaptation of individuals to living in the wild within <6 yrs after release
enhanced population persistence, and that initial losses may be compensated by
additional releases. Our analyses indicated that a lack of information about released
orangutans prevented accurate evaluation of the effectiveness of reintroduction procedures. Consequently, we recommend that reintroduction projects improve data
quality on the fates of released individuals in order to provide a reliable basis for a
population viability analysis. The use of population viability analyses would allow
proactive management and a better evaluation of reintroduction progress.
Keywords Overview–Design concepts–Details (ODD) . Pongo abelii .
Population viability analysis . Reintroduction
D. Kelle (*) : D. Fechter : I. Storch
Chair of Wildlife Ecology and Management, Freiburg University, 79106 Freiburg, Germany
e-mail: [email protected]
A. Singer
Department of Ecological Modelling, Helmholtz Centre for Environmental Research,
04318 Leipzig, Germany
P. Pratje
Frankfurt Zoological Society, Jambi, Sumatra, Indonesia
D. Kelle et al.
Introduction
Reintroduction projects have been criticized for their lack of a priori defined goals and
management plans for population viability, and for their retrospective, rather than goaloriented, approach to reviewing project success (Sarrazin and Barbault 1996; Seddon
1999; Seddon et al. 2007). Population viability analysis (PVA) can help to evaluate
success and enhance management strategies. By simulating the dynamics of a released
population based on varying conditions of demographic and environmental data
(Meretsky et al. 2000; Reed et al. 2002; Schaub et al. 2008; Slotta-Bachmayr et al.
2004) a PVA can identify challenges that might threaten the accomplishment of the overall
goal, the establishment of a viable and self-sustaining population. An a posteriori PVA,
i.e., conducted after release, can include release-specific data that cannot be anticipated
beforehand, such as the age, sex, survival, and reproductive rates of the released individuals (Russon 2009).
Reintroducing orangutans into areas where they once occurred has been widely
used to establish new populations and to provide confiscated ex-pet orangutans with a
place to live. Despite the official protection status awarded by the Indonesian
government in 1924 (Rijksen and Meijaard 1999), numbers of Sumatran orangutans
(Pongo abelii) have declined to an estimated 3500–7000 individuals in the wild
(Wich et al. 2003). The main causes of decline are habitat loss from deforestation,
habitat degradation, and illegal pet trade (Ellis et al. 2006; Rijksen and Meijaard
1999). Rehabilitation centers with the aim of releasing confiscated orangutans into
the wild have existed since 1961 (Rijksen and Meijaard 1999). However, the success
of reintroductions, and predictions concerning the viability status of the resulting
populations, remain vague (Russon 2009; Yeager 1997), because data concerning the
fate of most of the released orangutans are lacking owing to insufficient post-release
monitoring (Russon 2009). Once released, an orangutan is rarely seen again.
Here, we present the first PVA specifically modeled for a reintroduced population
of ex-captive orangutans. The aim of our analysis was to identify those parameters
that are most sensitive for the persistence of reintroduced populations of orangutans.
First, we determined demographic growth rates based on pessimistic to optimistic
assumptions on post-release survival and investigated effects of post-release adaptation and further releases on population persistence. Second, we assessed how infant
survival affects population persistence. Third, we addressed habitat degradation by
simulating population persistence under various scenarios of reduced carrying
capacity.
Methods
Study Area and Data Origins
The Bukit Tigapuluh (BT) ecosystem in Jambi, Central Sumatra, Indonesia, covers an
area of roughly 3200 km2 (Pratje 2000). The core area is the Bukit Tigapuluh
National Park (BTNP), which comprises an area of 1440 km2 mixed dipterocarp
rain forest in the provinces of Jambi and Riau. The area is characterized by a steep
mountain range in the southern part of the park. Bukit Huluh Supin is the highest
Viability of Reintroduced Sumatran Orangutans
elevation at 843 m. Unprotected forest outside the boundaries of the national park is
categorized by Indonesian authorities as production forest and thus may be
transformed into plantations (Riedler et al. 2010). The BT ecosystem is inhabited
by many rare and endangered species, such as Sumatran tigers (Panthera tigris
sumatrae), Sumatran elephants (Elephas maximus sumatranus), and rafflesia
(Rafflesia hasseltii) (Sitompul and Pratje 2009). Wild orangutans have been extinct
from Central Sumatra since the end of the 19th century (Rijksen and Meijaard 1999).
In collaboration with the Sumatran Orangutan Conservation Programme (SOCP), the
Frankfurt Zoological Society (FZS) has released 142 ex-captive orangutans into
BTNP from 2003 to 2012 (Cocks and Bullo 2008; Pratje 2000; Riedler et al. 2010;
Zweifel 2009), following IUCN guidelines (Beck et al. 2007; IUCN 1998). However,
the project is challenged by habitat destruction and unknown fates of released individuals. It therefore may serve as a test case for the suitability of PVA to evaluate
orangutan reintroduction success.
FZS provided daily activity data and medical files for 111 individuals released
from 2003 to 2009. Daily activity was recorded via instantaneous sampling of one
focal individual every 2 min from dawn to dusk (Geissmann 2002). The amount of
daily activity data of each individual ranged from many months to just a few weeks
depending on how long the individual was being followed. Records included independent food acquisition, arboreal locomotion, nest building, and supplemental
feeding. Medical files reported on each individual’s pre- and post-release health
history, recorded by the project’s veterinary staff.
Modeling Approach
Ellis et al. (2006) have presented a PVA for wild orangutan populations using Vortex.
We constructed an individual-based model for PVA that loosely followed this approach, but differed from the model of Ellis et al. (2006) in three ways: 1) We used
intervals of 6 yrs between births (interbirth interval [IBI]). 2) We assumed that newly
released individuals need time to adapt to the wild. We therefore introduced an
adaptation time into our model, defined as the period after release during which
released individuals had survival rates and reproductive rates lower than reported for
wild orangutans (Kuze et al. 2012; Wich et al. 2004). 3) We modeled mother–infant
interdependence by assigning every infant to its mother, and excluded the mother
from further reproduction for the duration of the IBI. We developed our model in Java
1.6 because the Vortex framework was not sufficiently flexible to implement these
additional processes. In the following, we describe our model according to the ODD
(Overview–Design concepts–Details) protocol (Grimm et al. 2006, 2010), a standard for
describing individual-based models.
Overview
Entities, State Variables, and Scales The entities of our model were individual
orangutans characterized by age, sex, mother–infant interdependencies, whether they
had been released or wild born, and how much time had elapsed since their release.
These factors influenced individual survival rates. The model referred to the BTNP,
covering 1440 km2.
D. Kelle et al.
Process Overview and Scheduling Each time step of the model represented 1 yr. We
simulated population dynamics for a period of 1000 yrs. Submodels were executed at
each time step (Fig. 1).
Design Concept
Basic Principles We considered the specifics of reintroductions by including timediscrete and predefined animal release schedules, uncertainties about individual fates
due to information gaps in monitoring, effects of learning and social interactions, and
stochasticity.
Learning Numerous studies have described the learning abilities of rehabilitant
orangutans (Cocks and Bullo 2008; Grundmann 2006; Grundmann et al. 2001;
Riedler et al. 2010; Russon 2009), supporting the assumption that survival
skills improve with time. We assumed that newly released orangutans would
show reduced survival compared to wild orangutans until they were fully
adapted. Thus, a 10-yr-old recently released orangutan might have poorer
chances of survival compared to a 10-yr-old orangutan released 6 yrs previously. We simulated the process of adaptation considering adaptation times of
2, 6, 10, and 20 yrs after release, during which an individual’s probability of
survival was lower than that of wild orangutans as reported from Ketambe,
North Sumatra (Wich et al. 2004).
Social Interactions Our model took into account the semisolitary nature of orangutans, with social interactions restricted to reproduction and mother–offspring care
(Delgado and van Schaik 2000; Mitra Setia et al. 2009; Rijksen 1978; Singleton and
van Schaik 2001; van Noordwijk et al. 2009).
Stochasticity We set the following processes as stochastic: release subsequent to
2009 (before 2009, releases followed the known schedule of the release project;
Appendix A), sex of newborns, survival, mating, environmental variability, and
catastrophes.
Details
Initialization We initialized simulations with zero orangutans. A total of 111 orangutans were released in the first 7 yrs. We based the age, sex, reproduction, and year of
release on orangutans released at BTNP (Appendix A). We numbered each individual
released or born chronologically in the order of their appearance.
Input Data We took general life history parameters from literature on both
Bornean (Pongo pygmaeus spp.) and Sumatran orangutans (Ellis et al. 2006;
Grundmann 2006; Kuze et al. 2008, 2012; Riedler et al. 2010; Rijksen 1978;
Russon 2009; Singleton et al. 2004, 2009; van Noordwijk et al. 2009; Wich et
al. 2004), but focused on information about Sumatran orangutans whenever
Viability of Reintroduced Sumatran Orangutans
Fig. 1 Path diagram illustrating a submodel and the modeling process for a PVA of reintroduced Sumatran
orangutans (Pongo abelii) at the Bukit Tigapuluh reintroduction project, Jambi, Sumatra.
D. Kelle et al.
available. A main shortcoming in previous reintroduction projects has been the
large number of orangutans with unknown fates. Hence, it is difficult to
calculate a specific survival rate per sex–age class and to approximate a
population growth rate. We took this uncertainty into account by distinguishing
five groups of individuals (a–e) according to their likely fates, as based on
documented survival competencies. We used daily activity data from 2003–2009
for information on independent food acquisition and natural, arboreal behavior
(arboreal locomotion and nest building) (Zweifel 2009) and we used medical
records for information on body condition and medical treatment histories.
Recorded data on sightings enabled us to find proof for surviving orangutans.
We used the following criteria for assigning individuals to one of the five fate
categories:
a) Confirmed alive (observed and identified reliably in 2008): All release
individuals observed and reliably identified in 2008 were classified as alive
(N=45).
b) Probably alive (unknown fate but data indicate all necessary survival
competencies): Vanished individuals for which independent food acquisition
and natural arboreal behavior (arboreal locomotion and nest building) were
recorded within the last two documented months before vanishing. Further,
body condition and health status at the time of last contact were documented as good and there was no history of reoccurring health issues.
These orangutans were considered to have full survival competencies and
classified as probably alive (N=35).
c) Unknown (no post-release monitoring data available): If no post-release monitoring data were available the fate of the vanished ape was classified as unknown
(N=13).
d) Probably dead (unknown fates; data indicate a lack of survival competence): If the recorded daily activity included continuous supplemental
feeding and no nest building competence or nests built only on the ground,
the vanished ape was classified as likely to be dead. Nest building skills
but no independent food acquisition as well as no nest building skills but
independent food acquisition also led to the assumption of the vanished ape
being dead. Health issues recorded at the last time being seen and a history
of repeated illness led to the assumption of an individual being dead, even
if behavioral skills appeared positive (N=11).
e) Confirmed dead (corpse found and identified reliably): If the corpse was found
and identified reliably the ape was classified as dead (N=7).
Survival Rates and Population Growth Rates The fact that the fates of many of
the released individuals remained unknown was a challenge for modeling
population viability. We therefore calculated different survival rates ranging
from optimistic to pessimistic based on the fate categories defined in the
preceding text. We created a life-table matrix by plotting all released orangutans
against age and sex. We included each individual from the year of release until
2009, from the year of release until it vanished, or from the year of release
Viability of Reintroduced Sumatran Orangutans
until it died. The outcome was a matrix of apes surviving, dying, or vanishing
at a specific age. After summarizing the age classes to life stages (Ellis
P et al.
2006), we calculated four different survival rates (SR) with 1 P alive
dead
follows:
as
e
SR1 ¼ 1 aþbþcþd
dþe
SR2 ¼ 1 aþbþc
SR3 ¼ 1 cþdþe
aþb
SR4 ¼ 1 bþcþdþe
e
To calculate the deterministic population growth rate (det. r) for each set of
survival rates (SR1–SR4 and SRwild, Table I), we constructed a deterministic
age-class model based on a Leslie matrix. We assumed constant birth and death
rates without any stochastic variation in survival and litter size. We assumed no
density dependency, no limitation of mates, no catastrophes, no inbreeding, and
a stable age distribution.
Table I Survival rates (SR) (%) and deterministic population growth rates (det. r) (%) of reintroduced
Sumatran orangutans in Bukit Tigapuluh, based on their assumed fates (SR1–4) and survival rates for wild
Sumatran orangutans
Sex
Females
Age
det. r
a
SR2 b
SR3
c
SR4
d
SRwilde
0–1
(0.999)
(0.999)
(0.999)
(0.999)
0.95
1–2
(0.999)
(0.999)
(0.999)
(0.999)
0.94
2–8
0.999
0.99
0.96
0.86
0.995
8–11
0.98
0.9
0.88
0.74
0.94
11–15
0.999
0.999
0.85
0.75
0.995
15+
0.999
0.999
0.999
0.67
0.9825
4.16 %
2.8 %
–0.07 %
–17.44 %
1.33 %
0–1
(0.999)
(0.999)
(0.999)
(0.999)
0.95
1–2
(0.999)
(0.999)
(0.999)
(0.999)
0.95
2–8
0.95
0.93
0.92
0.8
0.97
8–11
0.97
0.97
0.91
0.77
0.945
11–15
0.999
0.88
0.85
0.79
0.995
15+
0.999
0.75
0.5
0.25
0.9875
4.16 %
2.75 %
–17.42 %
1.32 %
det. r
Males
SR1
–0.06 %
a
SR1: Orangutans confirmed alive, probably alive, unknown (no data), and probably dead all included as
alive.
b
SR2: Orangutans confirmed alive, probably alive, unknown (no data) included as alive.
c
SR3: Only orangutans confirmed alive, probably alive included as alive.
d
SR4: Only orangutans confirmed alive included as alive.
e
SRwild: Modified after Ellis et al. (2006) as 1-mortality.
D. Kelle et al.
Submodels The following sequence describes the modeling process (Fig. 1):
1) Check for catastrophes and for logging affecting carrying capacity (K): We drew
a random number between 0 and 1 for catastrophes (fire and landslides), based
on probabilities of occurrence taken from Ellis et al. (2006): fires occurred with
an annual probability of 0.2 % and reduced K by 10 %. Landslides occurred with
an annual probability of 2.5 % and reduced K by 0.75 %. We considered logging
by decreasing K by a given percentage (see Scenarios).
2) Check whether number of living orangutans ≤ K and determine K: We defined K
as the maximum number of individuals able to persist in the area. Despite the fact
that orangutans do not distinguish between protected and unprotected areas, we
restricted the model to the protected part of the ecosystem. The unprotected
forest outside of BTNP is at risk of being transformed into plantations (Riedler et
al. 2010), and its persistence as orangutan habitat is not secured. Including this
area into calculation of K would lead to unrealistic long-term perspectives. A
viable population of orangutans (250–500 individuals) has been estimated to
need 80–300 km2 of suitable habitat (Russon 2009). Thus, with 1440 km2 of
protected forest, BTNP might offer habitat for at least 1000 orangutans (Russon
2009). We thus assumed K=1000 as the maximum capacity, unless reduced by
logging and catastrophes (Fig. 1; see Scenarios for specifics). We modeled K
using a ceiling approach, allowing us to simulate population development under
optimum conditions. At K, reproduction was suppressed. We chose this approach
because the Bukit Tigapuluh ecosystem is surrounded by intensively used
landscapes including farms, plantations, and urban areas. The population is
isolated and emigration inevitably leads to death because there is no suitable
habitat in neighboring areas.
3) Check for further release: At each time step after 2009, if a scenario implied
further releases, individuals were added randomly based on the age–sex distribution of the released orangutans from 2003–2009 (Appendix A).
4) Check for adaptation: If time since release is greater than or equal to adaptation
time, we assigned the corresponding ape a natural survival rate (SRwild) and a
natural age at first birth (AFB).
5) Determine reproductive ability: AFB is earlier in released (11.6 yrs; Kuze et al.
2008) than in wild (15.4 yrs; Wich et al. 2004) orangutans, possibly due to food
provisioning (Kuze et al. 2008, 2012). We used AFB=11 yrs for reintroduced
females, reflecting AFB data from the BT population (AFB=10, 10, and 14 yrs;
2003–2009). After adaptation time, we used AFB=15 yrs, as reported for wild
orangutans (Ellis et al. 2006). For released male orangutans, we used 15 yrs as
the age of first reproduction, based on the only released male from BT known to
sire offspring. We used 25 yrs as age at first reproduction in wild males, based on
data from Ketambe, North Sumatra (Ellis et al. 2006). However, age estimates
for male orangutans must be treated with caution because of bimaturism among
males (Russon 2009; Utami-Atmoko et al. 2009). The maximum age of reproduction remains unknown in the BTNP project. Long-term observations in
Ketambe indicate 50 yrs as a maximum age at reproduction for both sexes,
which has been generally accepted (Wich et al. 2004). We considered females
able to reproduce if they had reached AFB and had no offspring to take care of,
Viability of Reintroduced Sumatran Orangutans
i.e., she was primiparous, previous offspring older than 6 yrs, or offspring had
died. We considered males able to reproduce if they had reached age at first
reproduction.
6) Calculate reproduction: IBIs for wild Sumatran orangutans range from 6 to
9.3 yrs (Ellis et al. 2006; van Noordwijk et al. 2009; Wich et al. 2009). IBIs
for reintroduced orangutans tend to be shorter (5.5–6 yrs), possibly owing to
supplementary feeding (Kuze et al. 2008, 2012). We used an IBI of 6 yrs
throughout the modeling process, making the simulation conservative. We
calculated parturition events individually for each female, based on her
reproductive status, the fate of her infant, and IBI. We excluded each female
that gave birth from further reproduction until the IBI of 6 yrs had elapsed, or
her infant had died. To allow consideration of mother–infant relationships, we
assigned each orangutan an individual identification number and linked the
mother to her offspring. If an infant died within the first 6 yrs of age the
mother was able to reproduce again.
Dominant flanged male orangutans have greater chances of siring offspring
than other flanged and unflanged males (Utami-Atmoko et al. 2009); we therefore assumed that 50 % of all males of reproductive age could sire offspring.
Because field data were lacking, we conservatively assumed that each male was
able to sire no more than one young per year. Because of the polygynandrous
mating system, mates were randomly assigned at every reproduction.
We assigned all newborn infants the survival rate for wild-borns (0.95 %;
Table I).We determined the sex of the infant by drawing random numbers
between 0 and 1, with a sex ratio of 55 % male based on the finding of Ellis
et al. (2006) and Kuze et al. (2008) that there are no significant differences in
birth sex ratio between populations of reintroduced and wild orangutans. We set
the maximum litter size to one as orangutans rarely give birth to twins, and if so,
commonly only one survives (Ellis et al. 2006; Goossens et al. 2012).
7) Check for catastrophe affecting survival: We modeled disease epidemics to occur
a mean of once every 50 yrs (2 % of all years), and survival probabilities during
that year were reduced by 20 % (Ellis et al. 2006).
8) Determine survival probability: Based on the literature (Kuze et al. 2012; van
Noordwijk et al. 2009), we assumed reduced offspring survival if the mother
died while the infant was <7 yrs old (yr 1–3: 0 % survival; yr 4: survival reduced
by 50 %, yr 5–6: survival reduced by 25 %).
For every year, we generated a random value between 0 and 1 for environmental variation (EnvRand). We assumed that the survival probability for each
age and sex class was affected equally by environmental variation (environmental stochasticity). We calculated survival probability from a truncated, cumulative, inverse normal distribution provided by Apache Software Foundation with a
survival rate according to Table I as the mean, EnvRand as the probability of
1Survival ratex
yz
occurrence, and
as the standard deviation. Index x denotes
2
survival scenarios (SR1–SR4 or SRwild), y denotes sex class (male, female), and z
denotes age class. Note that the survival rate as the mean of the normal distribution
could be modified due to mother–infant interdependence. Finally, for each individual, we drew a random number between 0 and 1. If the number was greater than
D. Kelle et al.
the calculated survival probability, the ape died; if it was less than the calculated
survival probability the ape survived.
9) Check for extinction: We defined the population as extinct if only individuals of
one sex remained. As long as releases continued, the population could not go
extinct.
Scenarios
We simulated 267 scenarios based on different combinations of adaptation time,
release regime, infant survival, and K.
Adaptation Time We investigated the impact of the time to full adaptation on
population persistence by simulating 2, 6, 10, and 20 yrs until survival rates equaled
those of wild orangutans (natural survival rate). We based a further scenario on the
assumption that released individuals would never achieve a natural survival rate.
Release Regime Most orangutans at BTNP were released between the ages of 4 and
10 yrs resulting in an age bias toward juveniles, adolescents, and subadults (Rijksen
1978). Based on animals released between 2003 and 2009 (Appendix A), we
calculated a weighted age–sex distribution and generated the age and sex of future
released individuals randomly from this distribution. To simulate the impact of
various release regimes on population persistence we simulated all possible combinations of the number of orangutans released annually and the number of consecutive
years in which orangutans are released from 5×5 to 20×20 in steps of 5 each
(Appendix B). We used 20 annually released individuals each year for 20 yrs as a
maximum because this figure was well within the release capacities of the Bukit
Tigapuluh project.
Infant Survival Reintroduction projects in general do not release orangutan infants <3 yrs of age (Russon 2009). However, in rare cases, an orangutan
mother is released with a dependent offspring. Therefore, we included calculations of infant survival rates for released infants for age classes 0–3 yrs in our
model. For those infants born in the wild we used figures adopted from Kuze
et al. (2012) to simulate poor mothering skills in released orangutans. We used
the inverse of infant mortality rate to match our definition of survival rate.
Infant mortality rates reported by Kuze et al. (2012) include a variety of figures
based on other reintroduction projects as well as from zoos and studies on wild
orangutans (Table III). Our use of high infant mortality rates made our simulations rather conservative.
Carrying Capacity (K) We assumed that K was constant in all simulations, and
modeled scenarios of K=1000, 750, 500, and 250 orangutans. We determined the
minimum K necessary to enable population persistence by interpolating results across
scenarios. We simulated habitat loss by reducing the initial K. We used a negative
initial growth rate (SR3 see Table I) and adaptation after 6 yrs.
Viability of Reintroduced Sumatran Orangutans
Sensitivity Analysis
In step 1, we changed one parameter at a time and compared the scenarios to
investigate the influence of each parameter on persistence. In step 2, we
combined two parameters to investigate the effect on population establishment
and population persistence, and to detect favorable combinations of parameters.
To depict population establishment and population persistence we used scenarios based on intermediate sets of survival rates, i.e., those closest to±0 %
population growth rate: SR2 and SR3; Table I) as they seemed most realistic.
We assessed population viability as the cumulative probability of extinction by
a given time (P0(t); Grimm and Wissel 2004). We calculated P0(t) at 50, 100,
200, 500, and 1000 yrs to assess population establishment and persistence.
Following Shaffer (1981), we defined a population as persistent if the risk of
extinction over 1000 yrs was ≤5 %.
Results
Survival Rates and Population Growth Rates
The deterministic growth rates for the reintroduced population varied from –
17.44 % to +4.16 %, depending on assumed fates of released orangutans. The
deterministic growth rate was positive in only two (SR1 and SR2) of the four
survival rate sets (Table I). Scenarios based on the intermediate survival rate
sets SR2 and SR3 were more sensitive to changes in parameters than were the
extremely optimistic (SR1) or pessimistic (SR4) ones (Table I).
Figure 2A illustrates the effect of different deterministic growth rates resulting
from assumptions on orangutan fates on population development, modeled without
adaptation and without further releases. Survival rates SR1 and SR2 and the natural
survival rate of wild orangutans represent a very stable population with low risk of
extinction (Fig. 2A).
Effects of Further Releases
To assess the effects of further releases on population development, we used the
intermediate, yet slightly negative, survival rate SR3 (Table I; compare Fig. 2A)
and assumed no adaptation of released apes. Our model implied a high risk of
extinction regardless of the release regime (Fig. 2B). Not even the most intense
release regime prevented extinction, because the deterministic growth rate
remained negative. However, the more intense the release regime, the longer
the population survived.
Effects of Post-release Adaptation
In a population with a negative growth rate (SR3) but with an adaptation time
set as the natural survival rate (SRwild) extinction risk decreased to 8–28 %
within 1000 yrs, depending on adaptation time (Fig. 2C). The longer adaptation
D. Kelle et al.
A
B
Survival
1.0
Release
1.0
SR1
no release
20 × 5
5 × 20
20 × 20
SR2
SR3
0.8
0.8
SR4
0.6
0.6
P0(t)
P0(t)
SRwild
0.4
0.2
0.2
0.0
0.0
C
Adaptation
0.30
20 years
10 years
6 years
2 years
0.25
0.20
0.30
Adaptation+Release
6 years + no release
6 years + 20 × 5
6 years + 5 × 20
6 years + 20 × 20
0.25
0.20
0.15
0.15
0.10
0.10
0.05
0.05
0.00
0
D
P0(t)
P0(t)
0.4
100 200 300 400 500 600 700 800 900 1000
0.00
0
100 200 300 400 500 600 700 800 900 1000
Time to extinction t [ yrs]
Time to extinction t [ yrs]
Fig. 2 Cumulative probability of extinction by time t, P0(t) of a reintroduced population of Sumatran orangutans
(Pongo ablii) in Jambi, Sumatra. (A) Populations based on different survival rates (SR 1, 2, 3, 4, wild), no further
releases after 2009 and no adaptation. (B) populations based on SR3, different release regimes and no adaptation.
(C) Populations based on SR3, no further release and with adaptation after 2, 6, 10, and 20 yrs. (D) Populations
based on SR3 with adaptation after 6 yrs and releases. Releases are number of annually releases×number of
consecutive years of releases.
time, the greater was the risk of extinction. However, the threshold of P0(1000)<1 %
was not met for any of the adaptation time scenarios without further releases (Appendix
C; see Fig. 2D).
Combined Effects of Adaptation and Release Regime
Scenarios that combined assumptions of post-release adaptation with further releases
greatly improved the population’s performance (Fig. 2D). Of the 16 release regime
scenarios possible (5–20 orangutans released annually and 5–20 consecutive years
with adaptation after 6 yrs), 13 suggested long-term viability with P0(1000)≤5 %
(Appendix B, bold). However, even the most optimistic scenarios of adaptation and
release regime did not ensure a population persistence of P0(1000)<1 %.
Many scenarios without adaptation shown in Fig. 2B became extinct initially but
reached the threshold of P0(1000)≤5 % when adaptation and future releases were
added to the simulation (Fig. 2D). Only three scenarios with only a few additional
releases (<50 orangutans) did not achieve population persistence with P0(1000)≤5 %
(Table IIa). We therefore simulated these three scenarios (5 × 5, 5 × 10, 10 × 5)
Viability of Reintroduced Sumatran Orangutans
Table II Cumulative probability of extinction (%) at time steps 50–1000 for reintroduced Sumatran
orangutans (Pongo abelii) at Bukit Tigapuluh, Jambi, Sumatra with a scenario based on SR3 with
adaptation after a) 6 and b) 2 yrs, K=1000 and further releases
Cumulative probability of extinction at time t (P0(t)) (%)
5×5a
5×10a
10×5a
50
0
0
0
100
0.1
0
0
200
1
0.3
0.4
500
5
3
4
1000
8
6
6
50
0
0
0
100
0
0
0
200
0.3
0.1
0.1
500
2
2
2
1000
5
3
3
a) 6 yrs
t (yr)
b) 2 yrs
t (yr)
a
Number of annual releases × number of consecutive years of releases.
assuming adaptation after 2 yrs to assess the effect of a shorter adaptation period. This
reduced P0(1000) by almost 50 % (Table IIb).
Population establishment (P0(50)=0 %, P0(100)=0 %) was achieved in all release
regimes if the apes achieved a natural survival rate and thus a positive population
growth rate within any of the tested timeframes (2–20 yrs).
Effects of Infant Survival
When we assumed that lower maternal skills led to lower infant survival, we found that
population persistence was not achieved in any scenario, based neither on an initially
positive survival rate (SR2) nor on an initially negative survival rate (SR3) (Table III).
Even populations with an infant survival rate of at least 88 % showed a high probability
of extinction (Fig. 3). Low infant survival rates consistently led to negative deterministic
population growth rates (Table IIIc) and eventually to extinction. The two scenarios
showed only minor differences in probability of extinction (Table IIIa, b).
Changes in Carrying Capacity and Population Viability
Four scenarios with adaptation after 6 yrs and further releases based on SR3 reached
persistence with P0(1000)≤1 % (Appendix B); in all, release regimes were intensive
with 200–400 further individuals. Those populations remained persistent while decreasing K to a minimum of 750–500 (Table IV). Below the threshold of K=500–750
individuals no simulation reached population persistence with P0(1000)≤1 %.
D. Kelle et al.
Fig. 3 Effect of variation in infant survival on the cumulative probability of extinction (%) at time t (P0(t)).
Simulations are based on a population of reintroduced Sumatran orangutans (Pongo abelii) at the Bukit
Tigapuluh reintroduction project, Jambi, Sumatra with a negative initial growth rate (SR3) and 6 yrs until
adaptation.
Discussion
Although some parameters like genetic factors could not be analyzed in this PVA, the
results have clearly pointed out that reintroduction specific parameters such as
adaptation after release, release intensity and fates of the released orangutans need
to be considered carefully when establishing a new population of reintroduced
orangutans. Our simulations indicated great variation in the risk of extinction
depending on the assumptions we made about the fates of released orangutans.
Despite the long duration of the BT project, the available data were insufficient to
enable reliable predictions of population growth rates. The fates of released individuals need to be identified to reduce uncertainty of PVA results. We interpret our
findings based on the assumption that intermediate scenarios are most realistic and
survival rates SR2 and SR3 represent an optimistic and pessimistic view of the BT
population, respectively, implying that population survival would be possible only if
some of the unmonitored or less competent orangutans survive.
Population establishment and population persistence were influenced by two parameters: adaptation time and the specifics of the release regime. Our results indicated that
adaptation time has a larger influence on population persistence than release regimes.
Although our results indicated that further releases had only a temporary effect on
population development, further releases decreased extinction risk along with adaptation
time. The time schedule of release was less important. For example, there were only minor
differences in population development if 20 individuals were released annually for 5
consecutive years or if 5 individuals were released annually for 20 consecutive years.
Thus, the total number of released individuals and each individual’s survival appeared to
be more important than the number of release years. This might be explained by the fact
that further releases contribute to the overall population size and substitute for mortalities.
With slower adaptation of >6 yrs, further releases do have an effect on extinction risk,
suggesting that intense release regimes can decrease the risk of extinction temporarily.
Viability of Reintroduced Sumatran Orangutans
Table III Effects of variation of orangutan infant survival rate for ages 0–3 yrs of wild-born offspring on
extinction probability (P0(t)) under a) SR2 and b) SR3
Infant survival (%)
a) SR2
b) SR3
P0(t) %
t=50
t=100
P0(t)=
100 %
P0(t) %
t
t=50
c) New det. r wild
P0(t)=
100 %
t=100
t
39a
2,5
99
137
6
97
142
–9.33
61b
<1
41
274
<1
25
237
–4.64
371c
<1
11
357
<1
4
370
–2.85
79d
<1
3
819
<1
0.5
697
–1.51
82e
0
2
895
<1
0.5
814
–1.02
88f
0
1
—
<1
0.08
—
–0.36
The simulation used K=1000 and adaptation after 6 yrs and no further release. The new deterministic
growth rate as a consequence of the variation in infant survival rate is presented in c).
Infant survival figures from Kuze et al. 2012.
a
Bukit Lawang, rehabilitant, Dellatore et al. (in prep.).
b
Rehabilitant overall, Kuze et al. 2012.
c
Kaja Island, rehabilitant, Russon (unpublished).
d
Camp Leaky, rehabilitant, Banes and Russon (unpublished).
e
Zoo overall.
f
Wild overall.
Thus, further releases can help prevent extinction during the period before adaptation is
achieved (Fig. 2A, D).
Every released orangutan potentially contributed to reproduction once it matured. Once
released orangutans adapted behaviorally so they achieved survived rates equivalent to
those reported for their wild-born relatives (Ellis et al. 2006), they appeared to establish
viable populations. To lower the risk of extinction, it is highly advisable to ensure fast
adaptation to the wild by developing the survival skills of ex-captive orangutans, i.e.,
climbing, nest building, and food finding skills (Russon 2002). This information is
valuable, as management decisions can now take into account parameters that enhance
population persistence.
Table IV Minimum K for which the probability of extinction ≤1 % within the next 1000 yrs with
adaptation after 6 yrs and SR3 with different release scenarios
Release×yearsa
Minimum K with P0(1000)≤1 %
10×20
700–750
15×20
550–600
20×15
500–550
20×20
500–550
a
Number of annual releases × number of consecutive years of releases.
D. Kelle et al.
The simulations in this PVA suggested that infant survival rates reported by other
orangutan reintroduction projects (Ellis et al. 2006; Kuze et al. 2012) are too low to
support viable populations. Infact, Ellis et al. (2006) stated that at Bukit Lawang, infants of
ex-captive orangutans rarely live longer than 5 yrs. The large variability in reported infant
survival ranging from 39 % to 88 % may be due to insufficient skills of released females
and diseases, which may or may not be affected by project management practices, but may
also result from small sample sizes. Our results indicate that enhancing infant survival is
imperative for successful orangutan reintroduction. Project managers should consider
post-release care to compensate for poor mothering skills (Seddon 1999), yet avoid risks
involved (Kuze et al. 2008; Muehlenbein et al. 2010).
Suitable habitat such as dipterocarp lowland forest is decreasing rapidly in Sumatra.
The simulation of habitat loss by decreasing carrying capacity showed that reintroduction
projects should provide habitat for at least 500–750 orangutans if the population shall
persist. Considering the increasing extinction probabilities for small isolated orangutan
populations (Bruford et al. 2010) and effects of habitat destruction on carrying capacity
and high densities of orangutans, i.e., “compression effect” (Marshall et al. 2009), in areas
close to logging operations (Marshall et al. 2006), our results underline the necessity of
focusing conservation actions on the protection of remaining habitat.
Conclusions
Post-release PVAs are a necessary tool to evaluate project success. Better documentation
of survival and reproductive success of released individuals is needed to reduce uncertainty in population viability assessments. Released individuals must adapt to living in the
wild, i.e., showing behaviors and demographic performance comparable to those of wild
conspecifics in order to establish a viable self-sustaining population. Further releases can
support population establishment by adding to the number of reproductive individuals.
Releasing many apes within a short period of time or releasing few apes over a long period
of time did not substantially influence viability in this simulation study. Behavioral
adaptation progress, mothering skills, and infant survival in released orangutans, including
the second generation, should be documented consistently (Sarrazin and Barbault 1996).
Documenting age class–specific survival rates would allow management actions to focus
on critical aspects such as infant mortality. We strongly recommend intensifying postrelease observation efforts by radio-tagging individuals and checking them more regularly
after release to assess reproductive status and offspring survival. Regular assessments of
population viability via PVA are recommended to adjust the need for potential interventions and keep them to an effective minimum.
Acknowledgments We thank the Indonesian State Ministry of Research and Technology (RISTEK), the
Indonesian Institute of Sciences (LIPI), the Indonesian State Ministry of Forestry (PHKA), and the
Frankfurt Zoological Society (FZS) for making this research possible; Elizabeth Riemer and John
Bissonette for proofreading; and Robert Mattmueller for assistance in Python Programming. We thank
two anonymous reviewers for their helpful comments. We thank Felix Knauer for support in the initial
model setup and the fnet-team of the faculty of environment and natural resources, University of Freiburg,
for providing computing capacities. This project was supported by scholarships from the Rosa-Luxemburg
Foundation (to D. Kelle) and the Evangelisches Studienwerk Villigst e.V. (to D. Fechter). DK expresses her
sincere thanks to the employees of the FZS for their help and support in the field and in Jambi.
Viability of Reintroduced Sumatran Orangutans
Appendix A
Table V Number of orangutans
released at Bukit Tigapuluh National Park from 2003 to 2009 per
year/age class, sex class
Sex/age at release Year
2003 2004 2005 2006 2007 2008 2009
F0
1
F1
F2
1
F3
1
1
1
F4
1
1
1
F5
2
1
2
2
2
2
3
3
1
F6
2
F7
F8
F9
2
2
3
2
1
1
1
1
1
1
4
F10
1
F11
F12
1
F13
F14
1
1
1
1
M0
1
1
1
M1
M2
M3
M4
1
M5
1
M6
1
3
4
3
1
2
1
1
1
2
2
M7
M8
2
M9
3
1
1
1
1
1
1
M10
1
M11
1
2
1
1
2
1
1
1
1
1
M12
1
M13
M14
1
M15
1
2
1
1
M16
M17
M18
Sum
1
11
24
19
23
11
10
13
D. Kelle et al.
Appendix B
Table VI Cumulative probability
of extinction (%) after 1000 yrs
(P0(1000)) for scenario SR3 with
adaptation after 6, 10, and 20 yrs,
K=1000 and further releases
a
Number of annual releases ×
number of consecutive years of
releases.
Releasea
Adaptation (%)
6
10
20
20×20
0.4
0.5
0.6
15×20
0.6
0.8
0.9
20×15
0.8
0.9
1
10×20
0.8
1.7
1.8
15×15
1
1.5
1.7
20×10
1.2
1.8
2
15×10
1.5
2.7
3.1
10×15
1.7
2.5
2.6
5×20
2.5
4.1
4.5
20×5
2.8
4.9
7
10×10
3.1
4.7
5
15×5
3.9
5.7
8.8
5×15
4.1
5.6
6.6
Appendix C
Table VII Adaptation, no release: Cumulative probability of
extinction (%) at time steps 50–
1000 for scenario SR3 with adaptation after 2, 6, 10, and 20 yrs, K=
1000 and no further releases
t (yr)
Adaptation
2
6
10
20
50
0
0
0
1
100
0.03
0.2
0.5
3
200
0.4
2
5
10
500
4
8
15
23
1000
8
13
21
28
References
Beck, B., Walkup, K., Rodrigues, M., Unwin, S., Travis, D., & Stoinski, T. (2007). Best practice guidelines
for the re-introduction of Great Apes. Gland, Switzerland: SSC Primate Specialist Group of the World
Conservation Union.
Bruford, M. W., Ancrenaz, M., Chikhi, L., Lackman-Ancrenaz, I., Andau, M., Ambu, L., et al. (2010).
Projecting genetic diversity and population viability for the fragmented orang-utan population in the
Kinabatangan floodplain, Sabah, Malaysia. Endangered Species Research, 12, 249–261.
Cocks, L., & Bullo, K. (2008). The progress for releasing a zoo-bred Sumatran orang-utan (Pongo abelii) at
Bukit Tigapuluh National Park, Jambi, Sumatra. International Zoo Yearbook, 42, 1–7.
Viability of Reintroduced Sumatran Orangutans
Delgado, R. A., Jr., & van Schaik, C. P. (2000). The behavioural ecology and conservation of the orangutan
(Pongo pygmaeus): a tale of two islands. Evolutionary Anthropology, 9, 201–218.
Ellis, S., Singleton, I., Andayani, N., Traylor-Holzer, K., & Supriatna, J. (Eds.). (2006). Sumatran orangutan
conservation action plan. Washington, DC and Jakarta, Indonesia: Conservation International.
Geissmann, T. (2002). Verhaltensbiologische Forschungsmethoden: Eine Einführung. Münster: Schüling
Verlag.
Goossens, B., Kapar, M. D., Kahar, S., & Ancrenaz, M. (2012). First sighting of Bornean orang-utan twins
in the wild. Asian Primates Journal, 2(1), 12–14.
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., et al. (2006). A standard protocol
for describing individual-based and agent-based models. Ecological Modelling, 198, 115–126.
Grimm, V., Berger, U., DeAngelis, D. L., Polhill, J. G., Giske, J., & Railsback, S. F. (2010). The ODD
protocol: a review and first update. Ecological Modelling, 221, 2760–2768.
Grimm, V., & Wissel, C. (2004). The intrinsic mean time to extinction: a unifying approach to analysing
persistence and viability of populations. Oikos, 105, 501–511.
Grundmann, E. (2006). Back to the wild: will re-introduction and rehabilitation help the long-term
conservation of orangutans in Indonesia? Social Sciences Information, 45(2), 265–284.
Grundmann, E., Lestel, D., Boestani, A. N., & Bomsel, M. C. (2001). Learning to survive in the forest:
What every orangutan should know. The apes: Challenges for the 21st century (pp. 300–304).
Chicago: Brookfield Zoo.
IUCN (1998). Guidelines for re-introductions. IUCN/SSC Re-introduction Specialist Group. Gland,
Switzerland and Cambridge, UK: IUCN.
Kuze, N., Dellatore, D., Banes, G. L., Pratje, P., Tajima, T., & Russon, A. E. (2012). Factors affecting
reproduction in rehabilitated female orangutans: young age at first birth and short inter-birth interval.
Primates, 53, 181–192.
Kuze, N., Sipangkui, S., Malim, T. P., Bernard, H., Ambu, L. N., & Kohsima, S. (2008). Reproductive
parameters over a 37-year period of free-ranging female Borneo orangutans at Sepilok Orangutan
Rehabilitation Centre. Primates, 49, 126–134.
Marshall, A. J., Lacy, R., Ancrenaz, M., Byers, O., Husson, S. J., Leighton, M., et al. (2009). Orangutan
population biology, life history, and conservation. In S. A. Wich, S. S. Utami Atmoko, T. Mitra Setia,
& C. P. van Schaik (Eds.), Orangutans: Geographic variation in behavioral ecology and conservation
(pp. 311–326). Oxford: Oxford University Press.
Marshall, A. J., Nardiyono, Engström, L. M., Pamungkas, B., Palapa, J., Meijaard, E., et al. (2006). The
blowgun is mightier than the chainsaw in determining population density of Bornean orangutans
(Pongo pygmaeus morio) in the forest of East Kalimantan. Biological Conservation, 129, 566–578.
Meretsky, V. J., Snyder, N. F. R., Beissinger, S. R., Clendenen, D. A., & Wiley, J. W. (2000). Demography
of the California Condor: implications for reestablishment. Conservation Biology, 14, 957–967.
Mitra Setia, T., Delgado, R. A., Utami Atmoko, S. S., Singleton, I., & van Schaik, C. P. (2009). Social
organization and male-female relationships. In S. A. Wich, S. S. Utami Atmoko, T. Mitra Setia, & C. P.
van Schaik (Eds.), Orangutans: Geographic variation in behavioral ecology and conservation (pp.
245–253). Oxford: Oxford University Press.
Muehlenbein, M. P., Martinez, L. A., Lemke, A. A., Ambu, L., Nathan, S., Alsisto, S., et al. (2010).
Unhealthy travelers present challenges to sustainable primate ecotourism. Travel Medicine and Infectious Disease, 8, 169–175.
Pratje, P. H. (2000). Fruit tree availability in Bukit Tigapuluh National Park as an estimator of Orang-Utan
carrying capacity. In Orang-Utan Project-Bukit Tigapuluh Survey of the Frankfurt Zoological Society.
Unpublished report. Frankfurt: Frankfurt Zoological Society.
Reed, J. M., Mills, L. S., Dunning, J. B., Jr., Menges, E. S., McKelvey, K. S., Frye, R., et al. (2002).
Emerging issues in population viability analysis. Conservation Biology, 16, 7–19.
Riedler, B., Millesi, E., & Pratje, P. H. (2010). Adaptation to forest life during the reintroduction process of
immature Pongo abelii. International Journal of Primatology, 31, 647–663.
Rijksen, H. D. (1978). A field study on Sumatran orang-utans (Pongo pygmaeus abelii Lesson, 1827):
Ecology, behavior and conservation. Waageningen, The Netherlands: H. Veenman & Zonen.
Rijksen, H. D., & Meijaard, E. (1999). Our vanishing relative: The status of wild orang-utans at the close
of the twentieth century. Dordrecht: Kluwer Academic.
Russon, A. E. (2002). Return of the native: cognition and site-specific expertise in orangutan rehabilitation.
International Journal of Primatology, 23, 461–478.
Russon, A. (2009). Orangutan rehabilitation and reintroduction. In S. A. Wich, S. S. Utami Atmoko, T.
Mitra Setia, & C. P. van Schaik (Eds.), Orangutans: Geographic variation in behavioral ecology and
conservation (pp. 327–350). Oxford: Oxford University Press.
D. Kelle et al.
Sarrazin, F., & Barbault, R. (1996). Reintroduction: challenges and lessons for basic ecology. Trends in
Ecology & Evolution, 11, 474–478.
Schaub, M., Zink, R., Beissmann, H., Sarrazin, F., & Arlettaz, R. (2008). When to end releases in
reintroduction progammes: demographic rates and population viability analysis of bearded vultures
in the Alps. Journal of Applied Ecology, 46, 92–100.
Seddon, P. J. (1999). Persistence without intervention: assessing success in wildlife reintroductions. Trends
in Ecology & Evolution, 14, 503.
Seddon, P. J., Armstrong, D. P., & Maloney, R. F. (2007). Developing the science of reintroduction biology.
Conservation Biology, 21, 303–312.
Shaffer, M. L. (1981). Minimum population sizes for species conservation. BioScience, 31, 131–134.
Singleton, I., Knott, C. D., Morrrogh-Bernard, H. C., Wich, S. A., & van Schaik, C. P. (2009). Ranging
behavior of orangutan females and social organization. In S. A. Wich, S. S. Utami Atmoko, T. Mitra
Setia, & C. P. van Schaik (Eds.), Orangutans: Geographic variation in behavioral ecology and
conservation (pp. 205–212). Oxford: Oxford University Press.
Singleton, I., & van Schaik, C. P. (2001). Orangutan home range size and its determinants in a Sumatran
swamp forest. International Journal of Primatology, 22, 877–911.
Singleton, I., Wich, S. A., Husson, S., Stephens, S., Utami-Atmoko, S. S., Leighton, M., et al. (2004).
Orangutan population and habitat assessment : Final report. Apple Valley, MN: IUCN/SSC Conservation Breeding Specialist Group.
Sitompul, A., & Pratje, P. H. (2009). Resource base inventory: Implementation of conservation in Bukit
Tigapuluh Ecosystem. Unpublished report.
Slotta-Bachmayr, L., Boegel, R., Kaczensky, P., Stauffer, C., & Walzer, C. (2004). Use of population
viability analysis to identify management priorities and success in reintroducing Przewalski´s horses to
southwestern Mongolia. The Journal of Wildlife Management, 68, 790–798.
Utami Atmoko, S. S., Mitra Setia, T., Goossens, B., James, S. S., Knott, C. D., Morrogh-Bernard, H. C., et
al. (2009). Orangutan mating behavior and strategies. In S. A. Wich, S. S. Utami Atmoko, T. Mitra
Setia, & C. P. van Schaik (Eds.), Orangutans: Geographic variation in behavioral ecology and
conservation (pp. 235–244). Oxford: Oxford University Press.
Van Noordwijk, M. A., Sauren, S. E. B., Nuzuar, Abulani, A., Morrogh-Bernard, H. C., Utami Atmoko, S.
S., et al. (2009). Development of independence. In S. A. Wich, S. S. Utami Atmoko, T. Mitra Setia, &
C. P. van Schaik (Eds.), Orangutans: Geographic variation in behavioral ecology and conservation
(pp. 189–203). Oxford: Oxford University Press.
Wich, S. A., de Vries, H., Ancrenaz, M., Perkins, L., Shumaker, R. W., Suzuki, A., et al. (2009). Orangutan
life history variation. In S. A. Wich, S. S. Utami Atmoko, T. Mitra Setia, & C. P. van Schaik (Eds.),
Orangutans: Geographic variation in behavioral ecology and conservation (pp. 65–75). Oxford:
Oxford University Press.
Wich, S. A., Singleton, I., Utami-Atmoko, S. S., Geurts, M. L., Rijksen, H. D., & van Schaik, C. P. (2003).
The status of the Sumatran orang-utan Pongo abelii: an update. Oryx, 37, 49–54.
Wich, S. A., Utami-Atmoko, S. S., Mitra Setia, T., Rijksen, H. D., Schürmann, C., van Hooff, J. A. R. A.
M., et al. (2004). Life history of wild Sumatran orangutans (Pongo abelii). Journal of Human
Evolution, 47, 385–398.
Yeager, C. P. (1997). Orangutan rehabilitation in Tanjung Putting National Park, Indonesia. Conservation
Biology, 11, 802–805.
Zweifel, N. (2009). Evaluation of orangutan re-introduction project Bukit Tigapuluh National Park.
Unpublished report. Frankfurt: Frankfurt Zoological Society.