ORANGUTAN(DENSITYANDNESTING … · Orangutan nests have the potential to reflect important aspects...
Transcript of ORANGUTAN(DENSITYANDNESTING … · Orangutan nests have the potential to reflect important aspects...
ORANGUTAN DENSITY AND NESTING PREFERENCE IN CENTRAL KALIMANTAN,
INDONESIAN BORNEO
By: Cynthia Malone
Advisor: Dr. Karen B. Strier
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The extinction of orangutans has been predicted to occur by 2025 without a reversal of the extensive deforestation of Indonesia’s rainforests. Conservation efforts have begun to focus on measuring orangutan population densities and responses to change so that remaining habitat is adequately protected. Population densities are estimated using indirect surveys of orangutan nests, but our knowledge of nest construction is limited. I conducted a six-week study of orangutan density and nesting preferences in collaboration with the ‘Orang-utan Tropical Peatland Research Project’ (OuTrop). OuTrop is based in the Sabangau peat-swamp forest, home to the largest remaining population of orangutans in the world, Pongo pygmaeus wurmbii. Two sites of different disturbance levels, one a relic primary forest and the other a heavily degraded and fragmented forest, were compared in order to enhance our knowledge of how this subspecies copes with disturbance. In the degraded forest, density estimates were nearly twice that of those of the protected forest, potentially indicative of an over-crowding of individuals as the population is pushed into a smaller habitat patch fragmented by forest fires. Analysis of the environmental components of nest construction revealed preferences for particular tree species, which has been demonstrated previously in the protected forest, and a significant relationship between nest height and tree-tying, the use of multiple trees to build one nest. These results warrant further assessment of the degraded forest ecosystem and potential fire effects to better ascertain whether this population can persist without strong management efforts.
Introduction The archipelago of Indonesia is considered a global hotspot for biodiversity (Brooks et al
2002), representing a richness in ecosystems and endemic plant, insect, bird, and mammal species
that is arguably unparalleled anywhere else in the world. For primates in particular, Indonesia is a
stronghold; nearly half of the over 40 species present are endemic (Gursky-Doyen and Supriatna
2010). Perhaps the most recognized of all of Indonesia’s primates is Asia’s only great ape and the
world’s largest arboreal mammal, the orangutan. This charismatic species serves as a vital catalyst to
protect Indonesia’s biodiverse tropical forests that are currently being severely degraded at rapid
rates. Extensive deforestation and the consequential destruction of massive expanses of carbon-
storing peat have earned Indonesia the title of the third largest contributor to global carbon emissions
(Schwarz 2010). The government has recently made efforts to curtail emissions by partnering with
the United Nation’s REDD (Reducing Emissions from Deforestation and Forest Degradation in
Developing Countries) Program, and also declaring a two year moratorium on logging all pristine
forests. However, a lack of legal enforcement allows for the continued establishment of plantations
in pristine forest and illegal logging (Nantha and Tisdell 2009), furthering the fragmentation of
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forests on the islands of Borneo and Sumatra, the only remaining habitat of the orangutan.
Orangutans were once widespread throughout continental Southeast Asia and mainland Asia,
including areas between Vietnam, northern India, and Southern China, until the late Pleistocene, or
40,000 years ago. Climatic changes combined with human expansion and selective hunting to limit
orangutans to their present day range of two Sunda-shelf islands in Southeast Asia, Borneo and
Sumatra (Rijkson and Meijaard 1999). Although all members of the genus Pongidae were once
considered members of the same species, Pongo pygmaeus, as they can successfully interbreed and
have fertile offspring, recognizing the extent of morphological and ecological variation across all
orangutan populations is vital to addressing their immediate and long-term threats. Bornean and
Sumatran populations are now formally classified into two distinct species. Pongo abelli refers to all
Sumatran populations, while Pongo pygmaeus refers to Bornean populations. The Bornean
orangutan, Pongo pygmaeus, is further classified into three subspecies (Warren et al 2001): P.
pygmaeus pygmaeus inhabit West Kalimantan, P. pygmaeus wurmbii inhabit Central Kalimantan,
and P. pygmaeus morio, inhabit East Kalimantan and Malaysian Borneo (Figure 1, Taylor 2006).
Figure 1. Current distribution of the genus Pongidae. Pongo abelli is endemic to the island of Sumatra (a) and Pongo pygmaeus is endemic to the island of Borneo (b). (Source: Taylor 2006)
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While the historical and current distribution of orangutans within tropical rainforests subject
to climatic variations and increasing anthropogenic pressure is enough to suggest vulnerability, they
are not the only primate species endemic to Southeast Asia and yet have suffered greater losses to
their populations. The biology of the genus Pongidae is one of extremes, allowing for intrinsic
sensitivity to disturbance. They are predominantly frugivorous and will subsist on fruit whenever it is
available. While orangutans have adapted to seasonal fluctuations in fruit availability, namely by
minimizing energetic social interactions and relying on fallback foods such as pith, bark and leaves
(Marshall 2009), their dependence on an unreliable resource is paired with a long inter-birth interval
and high parental investment. Females give birth once every seven to nine years and parents spend at
least six years with one offspring, as they must become equipped with a mental map of the location
of over 250 different tree species used for food (Delgado and van Schaik 2000). Orangutan
dependence on fruit in a habitat where fruit is not always reliable combined with their delayed
reproduction and long inter-birth intervals make recovery from population losses difficult.
Current Status
As of 2009, the IUCN lists Pongo pygmaeus, the Bornean species, as endangered and Pongo
abelli, the Sumatran species, as critically endangered. The population growth trend is decreasing, as
over 50% have been lost over the past 60 years. From a total remaining population of 60,000, an
estimated 5,000 are lost each year. In Sumatra, there are less than 7,300 individuals remaining while
in Borneo, there are an estimated 50,000 individuals separated by extensive fragmentation (Wich et
al 2008). Unfortunately, the prospect of population numbers increasing does not look promising.
With Indonesia’s economic development so tied to palm oil production and logging concessions, and
lack of sufficient government enforcement to prevent illegal logging even in protected forest, the
future of orangutan populations depends on effectively managing protected areas and preventing
more destruction in unprotected areas by establishing official protected status. Baseline
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quantification of how populations are impacted by destruction at multiple habitat scales is needed to
mitigate anthropogenic pressures.
The majority of research regarding the effects of disturbance on orangutan populations
pertains to the alteration of their density and distribution, as conservation efforts attempt to discover
how many remain in the wild, why some populations seem to be more successful than others, and
how perturbations can be mitigated. While orangutan distribution across Borneo and Sumatra is
fairly well known, the same cannot be said for orangutan density. Because orangutans are a semi-
solitary and arboreal species that naturally occur in low densities with clumped spatial distribution
(Galdikas 1988), obtaining direct counts of orangutan individuals is notoriously challenging and
expensive, requiring intense tracking of an elusive arboreal species on difficult terrain. As a result,
accurate density estimates are difficult to obtain (Spehar et al 2010).
Recent efforts have relied almost exclusively on indirect measurements. The most widely
used non-encounter survey method utilizes the nests orangutans construct daily. Orangutans, the
other great apes, and prosimians are unique among the Primate order in their construction of nests
(Frothman and Hughman 1996). Unlike prosimian nests that are built instinctively and for a variety
of purposes, such as concealing young or breeding, the nests of great apes are flat platforms used for
sleeping. As nests are typically built daily, rarely re-used, and can remain visible for weeks or
sometimes years, they can act as reliable indirect markers of individuals within a given space.
Counting nests using line-transect techniques and a variety of habitat and population-specific
parameters is a method that is widely used for the estimations of chimpanzees, gorillas, and
orangutan densities (Husson et al 2009). For orangutans, the nest count method is less sensitive to
changes in densities over the short-term that tend to be associated with direct observations. It is an
efficient and cost-effective method to rapidly capture orangutan density at the population level.
Because of the parameters involved in calculating nest density, such as the time it takes a nest
to degrade, numbers cannot accurately be extrapolated over different habitat types and are restricted
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to the population level. This is ideal for conservation, as management efforts considering orangutan
density can be effectively tailored to a given area. However, orangutan density surveys utilizing the
nest count method have in the past concentrated on areas that are already protected, and only recently
have degraded areas become a topic of research and recognized as having conservation value
(Meijaard et al 2012).
Husson and colleagues (2009) shed light on the effects of disturbance on density across sites
in Borneo and Sumatra. Their analyses demonstrate that in heavily to moderately logged forests,
orangutans are present at lower densities than they are in unlogged forests of similar habitat, largely
due to the reduction in fruit availability. However, they also noted that disturbance can shift the
distribution of a population from a site of high disturbance to more suitable habitat if accessible,
which can lead to an overcrowding of individuals. Such overcrowding has been reported in sites
across Borneo, namely in West Kalimantan where nest densities were moderately high in sub-
optimal, previously logged forest adjacent to an area undergoing active disturbance (Russon et al
2001).
In Borneo, an estimated 75% of orangutans live outside of protected areas in plantations and
former logging concessions. Meijaard and colleagues (2010) demonstrated that an acacia plantation
in East Kalimantan with a history of illegal logging and forest fires contains as high as 3-4% of the
total Bornean orangutan population. Currently, there are no laws in place to prevent degraded areas
from undergoing further logging and anthropogenic disturbance. Density estimates can act as
justification for mitigating destruction of degraded forests, while knowledge of how orangutans cope
in such areas can serve to inform management decisions. .
Orangutan nests have the potential to reflect important aspects of orangutan behavior that can
inform conservation. As nests are currently widely used as the standard method for on-going density
surveys, and likely will continue to in the future, considering other aspects of nest construction in
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greater detail will enhance our understanding of orangutan habitat preferences and ecological
responses to disturbance in a cost-effective manner.
Nest Construction and Habitat Preferences
A variety of explanations have been proposed for the demonstrated time and effort
orangutans devote to nest construction. These include avoidance of predators, reducing heat loss, and
guarding against parasites (those that would either disturb apes on the ground or potentially be
transmitted if nests were reused often) and comfort while sleeping (Prasetyo et al 2009). Given that
all of these factors may play a role, it is unsurprising that orangutans start practicing before they are
one year old, and often build a number of nests in a day to hone their skills. At three years old, they
are able to build suitable nests (van Schaik et al 2005).
Nest construction has been recognized as a process that requires an advanced level of
cognitive ability comparable to tool use (van Casteren et al 2012). Observations of nest construction
in the wild demonstrate the significant effort and time an orangutan takes to construct a nest; the
process can sometimes take up to 30 minutes. In order to construct a nest, orangutans situate
themselves on a solid base, typically a single, strong lateral branch, and build a sturdy platform by
bending and weaving branches inward. A lining is created by breaking surrounding, typically leafy,
branches and placing these on top of the structure. Embellishments such as pillows, made from leafy
twigs, or blankets, in the form of detached leafy branches placed atop of a reclined individual, are
often added. Although materials are typically taken from the tree in which the nest was built, “leaf-
carrying,” where an orangutan will select branches from one or a few species to be used in
constructing a nest at a different site (Russon et al 2007).
The demonstrated effort and selectivity involved in nest construction is indicative of its
importance to the habitat preferences of orangutans. Analyzing the placement and structure of
orangutan nests within trees promises to reveal important factors involved in selection. A study in
Tuanan revealed that a tree’s structural characteristics, including the type of branching, were
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important to choice. Nests are typically built close to the tip of a tree in one of recognized four basic
patterns that reflect variations in the positioning of the platform at a particular height (Prasetyo et al
2009). While the first three patterns utilize one to two branches from a single tree as a base, the
fourth pattern is distinguished in its utilization of multiple trees to build a sleeping platform.
Orangutans bend and lock the branches of these trees together in a variety of ways to make the base
for their nest, a process referred to as tree-tying.
Tree-tying was once thought to be restricted to chimpanzees (Marchant 1996), but studies of
nest-building in orangutans document nests that employ over six trees for one nest. Patterns one to
three, those using just one tree, are most common in sites across Borneo and Sumatra, while the
fourth pattern is rare and most common in Central Kalimantan. Prasetyo et al (2009) suggest this
may be a result of selective logging and the absence of larger trees, since those that employ tree-
tying tend to be smaller, although it may also represent a subspecies preference related more to
geography than habitat loss.
Prasetyo and colleagues (2009) demonstrated that in study sites across Borneo and Sumatra,
tree species were not nested in proportion to their availability, or abundance, in the forest. Although
a wide variety of tree species are used, orangutans do not typically build their sleeping platforms in
active fruiting trees, where they are subject to disturbance by sympatric primate species or predators.
For those species that are commonly used within a population and across sites, further research is
required to determine what factors result in these apparent preferences.
To explore whether nests reflect important ecological responses to particular habitat types
across all orangutan populations, a comparative framework of the ecological components of
orangutan nesting and its relation to habitat viability is needed. This study was undertaken to explore
the effects of habitat disturbance on orangutan density and the potential of nest construction as an
indicator of important habitat preferences. Density and nesting preferences are compared between a
protected, secondary growth forest and an unprotected, degraded forest within a shared peatland
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ecosystem as part of ongoing research of the southern Bornean orangutan, P.p. wurmbii by the
Orangutan Tropical Peatland Research Project (OuTrop). Density in the protected area was expected
to remain similar to previous estimates, as the area has not undergone recent environmental or
anthropogenic disturbance. Orangutan density in the degraded forest was expected to be higher than
in the protected site as a result of overcrowding of individuals seeking refuge from degradation at the
forest edge as a result of periodic fires.
OuTrop’s research in the protected site demonstrates that orangutans prefer particular tree
species and locations for nests. Tree species preferences are also expected for the degraded site, but
the tree species and variables that explain their preference may be different as a result of the
ecological effects of disturbance. Alternatively, the unprotected site may not support nesting
preferences, as orangutans may not have the flexibility of choosing particular tree species if overall
the diversity and abundance of trees is low.
Study Site and Methods
OuTrop is a non-governmental organization and research camp based in the lowland peat-
swamp forest of the Sabangau basin in Central Kalimantan, Borneo. Along with being the largest
remaining lowland forest in Borneo, the Sabangau basin is home to the largest remaining continuous
population of Bornean orangutans, an estimated 6,900 individuals (Singleton et al 2004). The
distribution of P. p. wurmbii, is extensively fragmented (Husson et al 2009) and areas outside of the
protected national park are still subject to the threats of deforestation. OuTrop has conducted
extensive research on the population status, distribution, and behavioral ecology of P.p. wurmbii, and
the peatland ecosystem in which they inhabit.
Bisected by the Sabangau River, the study area of OuTrop is divided into two regions, the
Sebangau National Park and the National Laboratory of Peat-swamp Forest (NLPSF) and to the west
of the river and the unprotected Block C of the former Mega-Rice Project to the east (Figure 2). This
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study will compare parts of both these catchments, as they historically represent the same peatland
ecosystem supported by the Sabangau basin but have been altered to different degrees by disturbance.
Sabangau
Sabangau – National Laboratory of Peat-swamp Forest
The Sebangau National Forest is a 5780 km2 protected area situated between the Sabangau
River and the Katingan River. Although legal logging concessions ceased in 1996 upon its official
designation as a national park and research site, the area subsequently suffered from intense illegal
logging. The result is a habitat mosaic in different successional stages with patches of varied habitat
quality and secondary growth. The NLPSF is categorized into three main habitat sub-types: the
Figure 2: Map of the Sabangau basin, Central Kalimantan. OuTrop is based at the NLPSF, located in the Sabangau forest, the western catchment. Block C of the Mega-Rice Project is located in the eastern catchment, east of the Sabangau River,
Source: The Orangutan Tropical Peatland Research Project
Block C of the Mega Rice Project
NLPSF
Block C
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mixed-swamp forest, low pole interior forest, and the tall interior forest. This study is based within
the mixed-swamp forest, an area that stretches from the edge of the forest to six kilometers into the
interior characterized by a diversity of tree species up to 35 meters in height. The last reported
orangutan density estimate from this forest was 1.93 individuals/km2. There is minimal
anthropogenic disturbance in this portion of the forest and fires are infrequent.
Research of the orangutan nests in Sabangau provides interesting insights into nesting
behavior. A study of nest construction (Rowland 2008) identified 23% of the total tree species used
for nests as significantly preferred for nesting and 8% of tree species as avoided, making a total of
31% of nest trees used at numbers disproportionate to their abundance in the forest. Rowland
measured variables potentially related to the comfort and stability of a nest, such as the size and
number of leaves and branch strength, to determine which most explained the preference of these
particular tree species. Sap volume, viscosity, and stickiness were found to be the most important
factors in explaining the level of selection for a particular tree species.
Gibson (2005) revealed that overall, orangutans prefer to nest in tall trees with complete
canopy coverage and actively avoided patches of shorter trees with incomplete canopy. However,
significant differences between age-sex classes were reported. Flanged males nested in trees that
were significantly shorter in height and smaller in DBH (diameter at breast height) than sub-adult
males, females, and all adolescents. Adolescents nested in trees that were often twice the height of all
other age classes, and generally larger in DBH. Flanged males employed tree-tying in 58% of all
observations. Considering that flanged males were also shown to build the largest nests and
adolescents the smallest, there is a clear relationship between nest size and tree size, height, and the
number utilized in construction. This is suggestive of an age-sex class relationship to tree-tying.
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Block C - Kalampangan
The smaller and fragmented eastern catchment of the Sabangau basin is situated between the
Sabangau River and the Kahayan River. This area is Block C, one of five formerly forested blocks of
Indonesia’s former Mega-Rice Project, a failed attempt to alleviate a national food shortage in 1996
by converting one million hectares of peatland into rice padi. Aside from deforesting much of the
region by fire clearance, over 4000 km of drainage and irrigation channels were constructed (Boehm
and Siegert 1999). The combination of these canals and the severe drought imposed by the 1997 El
Nino Southern Oscillation has resulted in extensive destruction of the peat’s hydrology. Logging has
exacerbated the problem and 83% of forest cover has been lost since the initiation of the project in
1996. The region is prone to extensive fires annually during Indonesia’s dry season. From 2000 to
2007, 45% of Block C’s peatland had been lost, in addition to substantial vegetation loss and soil
drying from remaining forested areas (Cattau 2010).
Within Block C, OuTrop has conducted research from a small base camp in the Kalampangan
site, the northwestern portion of the segment. LANDSAT images reveal that it is isolated from other
forested areas within Block C and fragmentation has increased since 2000. Research of the
orangutans here is limited; this analysis of nesting preferences is the first study of this unhabituated
population’s ecology. In 2004, researchers (OuTrop, personal communication) observed orangutans
travelling on the ground along the banks of a 10 km long canal that runs 100 m from the base camp.
As orangutans are primarily arboreal, this is unusual and potentially indicative of overcrowding
pushing individuals out of the forest, and also may suggest habitat in the interior is unsuitable. The
last survey of orangutans reported a density of 1.6 individuals/km2 (Cattau 2009). Forest fires have
occurred at Kalampangan since this survey, though the extent of their effects has yet to be measured
(OuTrop, personal communication).
Field Methods
In order to estimate orangutan density in both study sites, previously established transects
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were surveyed for orangutan nests. For each nest encountered, the following variables were recorded
in accordance with standard protocol: distance and position (left or right) along transect,
perpendicular distance to nest, nest size in 0.5 meter increments, and the nest decay stage. Nest decay
stage was identified to one of the following categories: A: New, leaves still green, B: Older, nest still
in original shape, with brown leaves attached, C: Old, holes in the nest, or D: Very old, nest no
longer in original shape, but some twigs and branches still present (Morrogh-Bernard et al 2003).
While not employed in this study, nest decay is important in estimating the nest degradation rate of a
site and may potentially aid in future studies.
Nest Tree Species Preference in Kalampangan
The variables that may affect the preference of a tree species in nest construction were
recorded from the same transects surveyed for nest density. For every nest encountered along a
transect, the tree species was identified with the help of experienced OuTrop field assistants. In order
to determine whether orangutans are selecting specific tree species as nest sites, only data from nests
constructed in just one tree species were considered in this part of the analysis to avoid potential
confounding effects.
To investigate whether orangutans are using tree species at a level not predicted by the
presence of that species in the study area as a whole, vegetation data collected from six 100 x 5 meter
plots, a combined area of 0.3 hectares, in Kalampangan was used to calculate the proportions of each
nest tree species in the forest as represented by the plots. If a nest tree species was present in this
sample but not in the plots, it was assigned an observation of 0.5 stems/ha, as the minimum number of
stems in the forest is one, but the true abundance per hectare can be expected to be much less than this.
It is important that those tree species that are not represented in the plots but present in the sample are
included in the analysis, as they potentially represent species that are highly preferred for nests. These
species are present in the forest, but at such low abundance they were not observed in the vegetation
plots.
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In order to assess what factors may determine the selection of a tree species in Kalampangan,
the variables investigated in a previous study of nest construction at the Sabangau site (Rowland 2008)
thought to be associated with stability and comfort were considered here. Leaf, branch, and sap data
were considered to be intrinsic properties of each tree species, and data collected from the Sabangau
study that utilizes the vegetation plot data from this forest was used here in addition to data obtained
from this study of tree species in Kalampangan.
Sap measurements were taken by cutting into a section of the tree at breast height. Sap
viscosity was determined by the distance the sap traveled alongside a metric ruler. Measurements
were distributed into 5 class estimates, 0 representing no sap emitted, and 4 representing sap that
traveled the farthest distance. Sap stickiness was also estimated into 5 class estimates: 0 representing
no sap emitted and 4 representing a very sticky sap. Two branches thought to be typical of the kind an
orangutan might use for a nest were cut with the help of an OuTrop field assistant. For each branch,
the length was measured in meters and the number of secondary branches, branches perpendicular to
the main branch line, counted. The total number of leaves was recorded and the length and width of
the first 50 recorded. The area of a leaf was calculated utilizing the formula:
. As 50 leaves were not recorded in all cases, the average total leaf area
was weighted by the number of leaves recorded.
Tree-tying and Habitat Quality Surrounding Nests
In addition to variables affecting the selection of a tree species, the following variables were
collected to assess habitat quality surrounding a nest and their potential effects on tree-tying. For
each tree encountered with a nest, both tree height and nest height were measured in meters with a
clinometer. Circumference at breast height (CBH) was recorded 1.3 meters above the base of the
tree with measuring tape in centimeters, then converted to diameter at breast height (DBH) by
dividing this value by Π. Basal diameter was measured directly above the roots of tree in
centimeters.
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Variables related to habitat quality were only measured in the Kalampangan site. To maintain
consistency and avoid inter-observer bias, the following data were always recorded by me. Canopy
cover was measured using a hand-constructed “density-ometer”. The top of a bottle was cut and
plastic film with a 6 x 6 one inch square drawn grid was placed over the broadest part on the opposite
end of the mouthpiece, which acted as an eye piece. Canopy health was determined utilizing an index
developed by OuTrop, which includes five categories of health based on percentage of leaf cover.
Trees that have full coverage of leaves were assigned a score of 0 and those with little to no leaf
coverage were assigned a score of 5 (Figure 3).
Figure 3. Canopy health, based on an index developed by OuTrop (Gibson 2005). There are 5 class estimates: 0 represents 80-100% leaf cover, 1 represents 60-80% and 5 represents 0-20% leaf cover.
Interconnectivity, the level of connectedness between the tree observed with a nest and the
rest of a canopy, was also estimated into five classes. A score of 0 was given when a tree was not
connected to the rest of the canopy and a score of 5 was given when a tree was 100% connected to
the canopy on all sides.
Statistical Analysis
The program DISTANCE (Thomas et al 2009) is a statistical distance-sampling software that
utilizes the length of a transect (meters), the numbers of nests along a transect, and the perpendicular
distance of each of these nests to the transect to estimate nest density for a given survey area. It
employs robust semi-parametric models to determine the probability of detection as a function of the
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distance of the observed nest from transect, and uses this detection function to estimate an effective
strip width. The effective strip width of the area is accepted from the model that provides the lowest
Akaikes Information Criterion (AIC) and input into the following formula to estimate nest density: N
=n / L * 2w, in which N is nest density, n is the total number of nests observed subtracted by nests
beyond the effective strip width; L is the sum of transect lengths in km; and w is the effective
transect width in km.
Nest density was then used to estimate orangutan densities with following formula: D = N
/ (p * r * t), in which D is orangutan density (individuals/km2), N is nest density, p is the proportion
of nest builders in the population, r is the rate at which nests are produced (n/day/individual), and t is
the decay rate of nests, or time during which a nest remains viable (Morrogh-Bernard et al 2003).
The values of p, r, and t are parameters subject to variability across field sites, but require intensive
surveys if measured directly for each study. This study uses values previously obtained in Sabangau,
(Husson et al 2009), where p = 1.17, r = 0.89, and t=365. The final estimates were then multiplied by
correction factors to account for variability in experimental design (Husson et al 2009). A correction
factor of 1.25 accounts for the line-transect survey design employed, which typically produces lower
estimates than density surveys based on a plot design. A correction factor of 1.18 accounts for single
transect surveys such as this, where transects are only walked once.
A chi-squared test was performed to determine which of the tree species observed with nests
varied significantly from the vegetation plot abundance of each respective species, with the null
hypothesis that there is no difference between the nest sample proportion and the control, plot sample
proportion. An electivity index, “Chesson’s α,”was employed to measure the degree of preference
for tree species within this sample that differed significantly from vegetation plot proportions.
“Chesson’s α” index (Chesson, 1978) is a measurement of the selectivity of a given item that is
robust to changes in relative abundances, which allows for comparability across studies. The
expected value for random nest tree species selection (i.e. use is directly proportional to abundance
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in the environment) within this index is a function of number of nest tree species: 1/n where n is the
number of nest tree species in the sample. The value alpha, α, was calculated for each tree species
with the formula: α i = W i = ( ri / pi )/∑I (ri / pi), where r = the proportion of the tree species
encountered with nests and p = the proportion of tree species in the forest as measured by the
vegetation plots. Alpha values above 1/n indicate preference and those below 1/n indicate avoidance.
Values that are equal to 1/n indicate that the tree species is neither preferred nor avoided and the
proportions of these species would not vary significantly from the plot proportions.
A principal components analysis test, a multivariate statistical technique for analyzing the
source of variation within a data set, was used to determine which variables contribute to the
selection of a tree species. For tree-tying, a generalized linear model, in the form of a probit analysis,
was used to assess the contributions of each relevant variable and functional relationship to the
binary response of whether more than one tree was utilized or not.
Results
Orangutan Density
In Sabangau, a total of 124 nests was recorded over 11.63 kilometers divided into six transects.
The hazard + polynomial model provided the lowest AIC and best histogram fit, and an effective strip
width of 19.42 meters was used to calculate nest density. The orangutan density was estimated to be
0.88 individuals/km2 before the correction factor. The final estimate with the correction factor is 0.944
individuals/km2. In Kalampangan, a total of 158 nests were recorded over 10.63 kilometers surveyed
divided into 5 transects to the interior and 5 transects towards the forest edge. The uniform + cosine
model provided the lowest AIC and best histogram fit. An effective strip width of 12.14 meters was
used to estimate nest density. The orangutan density of Kalampangan was estimated to be 1.2
individuals/km2 before the correction factor. The final estimate with the correction factor is 1.77
individuals/km2.
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Nest Tree Species Preference
A total of 33 tree species were recorded for all nests that were constructed with branches from one
tree (Table S1). When comparing the proportions of each tree species observed with a nest from transect
surveys with the proportion of these tree species observed in the vegetation plots, seven tree species, or 21
% of the total tree species encountered were determined to be significantly preferred by orangutans for
nesting and five species, or 15 % of the total tree species encountered, were determined to be significantly
avoided (Figure 4).
The tree species variables relating to the sap, leaves, and branch characteristics of these 13 tree
species were used in the Principal Components Analysis. The model was first run to determine the
number of important components as visually displayed in a scree plot. The first three principal
Figure 4: Chesson’s α Index Values for significantly preferred and avoided tree species (critical value = 3.85, df=1, p < 0.05). The horizontal line marks the value expected if there were no preference, 1/n, calculated for this study as 0.03 (1/33 tree species). Tree species with Chesson’s values below this are considered avoided and tree species with values above are preferred.
18
components provided Eigen-values over one and contributed the most to the variation in the data.
Principal Component 1 accounts for 46% of the variation in the data, while Principal Component 2
accounts for 20% of this variation. The loadings scores and plot (Figure S1) show that variables
relating to tree security and comfort, as represented by average total leaf area and leaf area to branch
ratio, explain the majority of the variation between species that are preferred and avoided. Secondary
branches may explain around 20% of the variation.
In Kalampangan, 109 observations, or 69% of the total, were single tree nests and 49 observations,
or 31% of the total were built using multiple trees. Before analysis, six rows with missing values were
removed. Each measured variable was first compared between the two forms of nest construction
independently of all other variables with two sample t-tests. There was no significant difference in nest
size between single nest trees and those constructed with tree-tying (p = 0.118). Tree size (Figures 5)
measured by DBH (DBH for single tree nests: mean = 21.14 cm, SD = 8.80; DBH for tree tied nests:
mean = 12.81, SD = 6.37, two sample t test t: 5.74, df=150, p <0.05) and basal area (basal area for
single tree nests: mean = 24.34, SD = 9.62; basal area for tree tied nests: mean = 15.06, SD =7.29, two
sample t test t – 5.80 , p<0.05) were both significantly greater for single tree nests. Nest height (Figure
6) and tree height were also significantly greater for single tree nests (nest height for single tree nests:
mean = 16.33, SD = 6.66; nest height for tree tied nests: mean = 8.97, SD = 3.98, two sample t test t:
6.71, df=150, p<0.05).
For variables thought to be related to habitat quality, canopy coverage did not vary significantly
(p=0.946) between the two forms of nest construction, while canopy health and interconnectivity did.
Canopy health scores were significantly higher for trees constructed with tree-tying (which according
to the scale denotes less leave coverage and poor health (Mann-Whitney U Test, p-value = 0.0009).
Canopy connectivity scores were significantly lower for single nest trees than for those constructed
with tree-tying (Mann-Whitney U Test, p-value = 0.0014).
19
Trees TiedSingle Tree
50
40
30
20
10
0
size
in c
m
Diameter at Breast Height (DBH) in Kalampangan
Figure 5. Box plot comparison of DBH for single tree nests and those constructed with tree-tying in Kalampangan
Trees TiedSingle Tree
40
30
20
10
0
Met
ers
Nest Height
Figure 6. Boxplot comparison of nest heights for single tree nests and those constructed with tree-tying.
20
In order to fully examine the interactions and relative contributions of these variables to tree-
tying, a general linear model incorporating all variables was conducted, with tree-tying treated as a
binary response (0 denoting single nest trees and 1 denoting tree-tying). The full, initial model only
showed nest height to be a significant factor in tree-tying. The negative point estimate demonstrates
that the probability of tree-tying decreases with increasing nest height. As many of these variables
were thought to be related and potentially confounding, a stepwise AIC model reduction was formed
to reduce the Akaikes Information Criterion and increase the predictive power of the model. Table 1
displays the final model, with nest size and tree height as significant factors in tree-tying and nest
height as highly significant. The reduced AIC model was a better fit than the initial model and was
further determined to be a good fit by comparing model predicted verses actual values of tree-tying
for each composite point estimate.
Table 1. Reduced general linear model for tree-tying analysis. The probability that a variable was greater than or equal to z represents a significant relationship to tree-tying.
Estimate Std. Error z value Pr ( > I z I ) Intercept 0.20452 0.54255 0.377 0.7062 Nest Size 0.78450 0.39348 1.994 0.0462 Nest Height -0.27469 0.06341 -4.332 1.48 e -05 Tree Height 0.08700 0.04158 2.092 0.0364 Canopy Health 0.22320 0.12482 1.788 0.0737
Nest height and tree height explain a large proportion of the data and seem to co-vary with all
other measured variables. Basal diameter was the last variable to be removed in the step AIC process,
and is likely captured by the predictive power of nest height and tree height. Figure 7 demonstrates
how nests placed high in tall trees with large basal diameters were more often built in just one tree
and did not employ tree-tying, while tree-tying was more often seen in shorter trees with smaller
basal diameters.
21
In Sabangau, 67 nests, or 54% of the total, were single tree nests and 57 nests, or 46% of the
total, were constructed with tree-tying. CBH (CBH for single tree nests: mean =20.36 cm, SD = 7.83;
CBH for tree tied nests: mean = 12.68 cm, SD = 3.71, two sample t test t: 6.69, df=120, p <0.05;
Figure 8), nest height (nest height for single tree nests: mean = 16.12, SD = 4.90; nest height for tree
tied nests: mean = 12.97, SD = 4.41, two sample t test t: 3.68, df=119, p<0.05), and tree height (tree
height for single tree nests: mean = 18.95, SD = 5.07; tree height for tree tied nests: mean = 15.31,
SD = 3.41, two sample t test t: 4.51, df=119, p<0.05) were all significantly greater in single tree nests
than in those with trees tied. Nest size did not vary between single tree nests and those with trees tied
(p-value = 0.79).
Figure 7: Nest height and tree height as a function of tree-tying, where 0, represented by circles, denotes single tree nests and 1, represented by squares, denotes tree-tying. Each point reflects basal diameter with size.
22
Trees TiedSingle Tree
40
30
20
10
0
size
in c
m
Diameter at Breast Height (DBH) in Sabangau
Figure 8. Box plot comparison of DBH for single tree nests and those constructed with tree-tying in Sabangau.
Nest height, tree height, and CBH did not vary significantly between Sabangau and Kalampangan (in
two sample t-tests performed with all trees, single nest trees alone, and nests constructed with tree-
tying).
Discussion
Contrary to our prediction for Sabangau, the density estimate, 0.94 individuals/km2, has
decreased from the last reported estimate in 2009 of 1.93 individuals/km2. As there have been no
major environmental perturbations or anthropogenic disturbances within the national park, it is
possible that these numbers are a reflection of either sampling error or the natural fluctuation known
to occur in orangutan density over a period of time (Galdikas 1988). Additional analysis of these
estimates and potential explanations are in progress.
In Kalampangan, the density estimate of 1.77 individuals/km2 is similar to the last reported
23
estimate of 1.6 individuals/km2 in 2009. While it was assumed that the density would have decreased
as a result of fires diminishing fruit availability and survival, these numbers may reflect a time lag in
the effects of disturbance. Such a time lag has been reported in a study in Sabangau, (Husson,
unpublished) where orangutan distribution was altered following logging activities, but a substantial
change in orangutan density was not seen until four years after the disturbance, when a 30% decline
was measured over just one year (Husson et al 2009).
The estimates obtained from this study suggest that the number of orangutans in
Kalampangan is currently almost twice that of a similar measurable area in Sabangau. This provides
support for our prediction of overcrowding, as individuals are pushed into the interior of a shrinking
habitat patch that is becoming more fragmented due to forest fires. In addition to the aforementioned
evidence for Bornean orangutans, this has been documented in other primate species. In West
Malaysia, Johns (1986) noted significant changes to the ranging and activity patterns of several
primate species prior to logging events. Gibbons (Hylobates lar) either restricted their activity to
areas not yet logged or moved beyond the core areas of disturbance. As they have no means of
dispersal to other forested patches, orangutans in Kalampangan may be altering their distribution to
the forest interior, where fruit availability and the structural integrity of the canopy is less disturbed
by fire. Additional research of the typical ranging patterns of P.p. wurmbii is warranted to better
assess if and how distributions are modified in Kalampangan.
It is also important to consider that orangutans naturally occur at different densities across
sites (Galdikas 1988), and as we do not have density estimates for Kalampangan prior to its
extensive fragmentation, we cannot rule out the possibility that these estimates are merely a
reflection of an intrinsic difference in densities between Sabangau and Kalampangan. While it may
not be possible to ascertain whether such an intrinsic difference exists, an assessment of habitat
characteristics known to impact the demography, health, and density of orangutan populations, such
as fruit availability and canopy structure, should be conducted to determine whether Kalampangan
24
can continue to support orangutans at this density if fires and the resulting loss of vegetation and
expanses of peatland in Block C continues at its current rate.
This study has demonstrated that orangutans prefer particular tree species for nest
construction in Kalampangan. While none of the variables measured here are significantly associated
with such preferences, the Principal Components Analysis revealed that tree characteristics relating
to the security of a nest, such as branch strength and the leaf area to branch ratio may play an
important role in tree species preference. Considering habitat quality between the two study sites
could shed light on these results. More tree species are avoided for nesting in Kalampangan than in
Sabangau. What would explain the higher proportion of avoided species? If comparing the usage of
tree species for nests with their abundance in the forest is an accurate way to measure preference,
there are two possible explanations.
First, due to time restrictions, only one measurement of each tree species characteristic was
considered. Such a small sample size may not be entirely reflective of the typical sap, branch, and
leaf characteristics of these tree species. The second explanation is related to this study’s assumption
that selected tree species characteristics did not vary between Sabangau and Kalampangan.
Measurements were analyzed interchangeably, which would not account for potential differences in
tree species and their characteristics between each site. A study in East Kalimantan (van Nieuwstadt
and Sheil 2004) demonstrated the severe effects of fire and associated water-deficient soils on trees,
which ultimately lead to an exhaustion of stem energy reserves, loss of leaves, and potential
mortality for many tree species. Given the diminished soil hydrology documented within Block C
(Cattau 2010), it is possible that sap quantity, branch lengths, and leaf number and size have been
affected by fire events, and therefore the same tree species would not be comparable between sites.
The Principal Components Analysis of the measured variables could only explain a
maximum of 46% of the variation between tree species that were preferred and avoided for nesting at
Kalampangan. One possible explanation for this result aside from small sample size is that
25
orangutans prefer tree species for characteristics different to the ones measured in this study. Habitat
disturbance is known to affect the distribution of tree species within the forest – from dispersal of
their seeds to regrowth prior to fire (van Nieuwstadt and Sheil 2004). The tree species orangutans
prefer may be ones that occur in areas of the forest that have more complete canopy coverage or tend
to occur in the interior of the forest rather than the edge. Future research of nest tree species
preference should aim for larger sample sizes and incorporate an understanding of tree species
phenology and any potential effects of disturbance on the distribution of trees and measured
characteristics.
Analysis of variables related to tree-tying allow for a deeper understanding of nest
construction and reveal more than tree species preferences can alone, especially when comparing
between sites. There is likely something more than merely an association between nest size and age-
sex class at work. These results demonstrate a relationship between tree height and habitat quality, as
canopy health is significantly lower for nests constructed with tree-tying in Kalampangan. The lower
canopy interconnectivity for single tree nests may be related to the canopy structure of this forest.
Incomplete canopy coverage and frequent gaps within the canopy of Kalampangan may leave tall
trees disconnected from the rest of the forest. There may be a compromise between the stability of
using one, large tree for a nest that may not have complete coverage, to trees that are smaller in size,
shorter in height, but more connected to the rest of the canopy.
In Sabangau, the patterns observed for tree-tying were similar to those in Kalampangan.
Nests constructed with just one tree were on average greater in DBH, nest height, and tree height. As
single tree nests are seen more often in both sites, the structural stability given by larger, healthier
trees seems to be an important factor in nest construction for P.p. wurmbii. Tree DBH distributions
from vegetation plots in Sabangau and Kalampangan demonstrate that the majority of trees fall
between 0 and 10 cm in DBH in both sites. This is indicative of a potential preference for larger trees
than are available - in both sites the average DBH for single tree nests was around 20 cm, and even
26
for tree-tying is around 12 cm. Given that tree-tying is rare outside of Central Kalimantan, these
results suggest that tree-tying may be a compromise when better quality nest sites (with increased
structural stability in tree height and size, and greater canopy health) are not available.
Conclusions
This study has shown that orangutans in the degraded forest of Kalampangan can occur in
higher numbers than the protected forest of Sabangau. While further research is needed to establish
whether this is a result of overcrowding, the presence of orangutans is enough to warrant this site’s
protection from further logging and subsequent management efforts. If the habitat is deemed
unsuitable and numbers continue to increase, corridors should be established to facilitate the
dispersal of orangutans within the Kalampangan site to another forest patch.
Orangutans at both of these sites in the Sabangau basin of Central Kalimantan have
demonstrated preferences for specific tree species in nest construction. While further research is
required to provide more robust conclusions for which tree species attributes underlie the
demonstrated tree species preferences, forest characteristics such as tree size and height play an
important role in the nest construction process. Management efforts may want to ensure that trees of
a certain size and height remain in the forest for use in nesting. A comparative framework of nest
construction should be established from sites across Borneo and Sumatra to examine how the
preferences observed for P. p. wurmbii compare with other populations.
Acknowledgements
I would like to give a special thanks to my advisor, Dr. Karen B. Strier for her unrelenting
assistance and guidance from the beginnings of this project. Funding was crucial in allowing me to
have this great opportunity to conduct research abroad, and I am thankful to the Holstrom
Environmental Scholarship committee for their generous recognition of this project. I appreciate the
University of Wisconsin-Madison, particularly the Letters and Science Honors Program and Dr.
27
Chuck Snowdon, for their encouragement of undergraduate research. Thanks to Benjamin Stenhaug
for his help with multivariate statistics.
This project would not have been possible without the wonderful opportunity the Orangutan
Tropical Peatland Project has given me to participate in their research. I would like to thank all of the
OuTrop researchers for their inspiring work in the Sabangau forest and help with this project, in
particular Dr. Mark Harrison, for his continued assistance in the field and with data analysis. Thanks
also to Karen Jeffers for her persistence in getting me the necessary permits to work in Indonesia. I
am so grateful for all of OuTrop’s field assistants, in particular, Ari Purwanto and Franciscus
Harsanto - their expertise in nest spotting and intimate knowledge of the Sabangau forest made every
day in the field an amazing learning experience. Thanks to Joana Aragay, Lilia Kapsali, Nick Boyd,
Victoria Hatton, Cassie Freund and Megan Cattau for their assistance with data collection and great
companionship in the field.
References
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Boehm, H. D. V., and Siegert, F. (1999) Application of Remote Sensing and GIS to survey and evaluate tropical peat. Kalteng Consultants. International Conference and Workshop on Tropical Peat Swamps, Safeguarding a Global Natural Resource. 27-29 July 1999. Penang, Malaysia.
Cattau (2010) Land cover change in Sabangau, Central Kalimantan from 2000-2007: Implications for the Bornean orangutan (Pongo pygmaeus). MSc Project, Duke University.
Galdikas, B. M. F. (1988). Orang-utan diet, range and activity at Tanjung Puting, Central Borneo. International Journal of Primatology, 9:1-35. Husson, S.; Wich, S.A.; Marshall, A.J.; Dennis, R.D.; Ancrenaz, M.; Brassey, R.; Gumal, M.; Hearn, A.J.; Meijaard, E.; Simorangkir,T.; and Singleton,S. (2009) Chapter 6 – Orang-utan distribution, density, abundance and impacts of disturbance. In: Wich, S.; Atmoko, S.; Setia, T.M; and van Schaik, C.P. Orang-utans: Geographic Variation in Behavioral Ecology and Conservation. Oxford University Press, USA. Johns, A. (1986) Effects of Selective Logging on the Behavioral Ecology of West Malaysian Primates. Ecology, 67 (3): 684-694.
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Marshall, A. J., Boyko, C. M., Feilen, K. L., Boyko, R. H. and Leighton, M. (2009), Defining fallback foods and assessing their importance in primate ecology and evolution. Am. J. Phys. Anthropol., 140: 603–614. Meijaard, E, Guillaume A, Nardiyono, Rayadin Y, Ancrenaz M, and Spehar S. (2010) Unexpected ecological resilience in Bornean orangutans and implications for pulp and paper management. PLoS ONE, 5 (9): 1-7. Meijaard, E., Wich, S., Ancrenaz, M. and Marshall, A. J. (2012), Not by science alone: why orangutan conservationists must think outside the box. Annals of the New York Academy of Sciences, 1249: 29–44. Morrogh-Bernard, H; Husson, S; Page, S.E; and Rieley, J.O. (2003) Population status of the Bornean orang-utan (Pongo pygmaeus) in the Sebangau peat swamp forest, Central Kalimantan, Indonesia. Biological Conservation, 110:141-152. Nantha and Tinsdall (2009) The orang-utan–oil palm conflict: economic constraints and opportunities for conservation. Biodivers Conserv, 18: 487-502.
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Supplementary Material
Table S1 – All Tree Species Encountered with a Nest
Tree Species Local Indonesian Name Shorea belangeran Belangaran/Kahui
BintanTristaniopsis sp.4 Blawan punai
Palaquium leiocarpum HangkangSyzygium sp./sp. 1 cf garcinifolia Jambu burung
Xylopia fusca Jangkang kuningCalophylum hosei JinjitCalophylum sp. Kapurnaga laut
Koompasia malaccensis KempasBlumeodendron elateriospermum/tokbrai Kenari
cf. Anisoptera (Dipterocarp) Keruing sambunNephellium maingayi Kelumun bohis
Eugenia spictata Kayu Lalas Diospyros bantamensis Malam malamElaeocarpus mastersii Mangkinang/Blueberi
Gymnacranthera farquhariania Mendarahan daun kecilShorea teysmanniana Meranti semut/Meranti
Dactylocladus stenostachys MertibuPalaquium ridleyii/cf. xanthochymum Nyatoh burung
Palaquium cochlearifolium Nyatoh gagasLithocarpus rassa Pampaning
Lithocarpus conocarpus Pampaning bayangLithocarpus sp.1 cf. dasystachys Pampaning bitik
Sandoricum beccanarium PapongMezzetia leptopoda/parviflora Pisang pisang besar
Tetramerista glabra Ponak Neoscortechinia kingii Pupu palandukTetractomia tetrandra Rambangun
Nephellium lappaceum RambutanGonoystylus bancanus Ramin
Stemonorus cf. scorpiodes Tabaras yang tdk punya akar tinggi Mesua sp. 1 Tabaras akar tinggi
Campnosperma coriaceum Terontang
31
0.500.250.00-0.25-0.50
0.50
0.25
0.00
-0.25
-0.50
-0.75
First Component
Seco
nd C
ompo
nent
No. Secondary Branches
Total Leaves
Leaf Area:Branch
Avg Leaf Area
Strength
Sap Stickiness
Sap Viscosity
Loading Plot of Tree Variables
Figure S1. Loadings plot of variables relating to tree species attributes from Principal Components Analysis.