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Tigers and Their Prey in Bukit Rimbang Bukit Baling: Abundance Baseline for Effective Wildlife Reserve Management

Authors:
  • World Wide Fund For Nature Indonesia

Abstract

Managing the critically endangered Sumatran tiger (Panthera tigris sumatrae) needs accurate information on its abundance and availability of prey at the landscape level. Bukit Rimbang Bukit Baling Wildlife Reserve in central Sumatra represents an important area for tigers at local, regional and global levels. The area has been recognized as a long-term priority Tiger Conservation Landscape. Solid baseline information on tigers and prey is fundamentally needed for the management. The objective of this study was to produce robust estimate of tiger density and prey a vailability in the reserve. We used camera traps to systematically collecting photographic samples of tigers and prey using Spatial Capture Recapture (SCR) framework. We estimated density for tigers and calculated trap success rate (TSR; independent pictures/100 trap nights) for main prey species. Three blocks in the reserve were sampled from 2012 to 2015 accumulating a total of 8,125 effective trap nights. We captured 14 tiger individuals including three cubs. We documented the highest density of tigers (individuals/100 km 2) in southern sampling block (based on traditional capture recapture (TCR) : 1.52 ± SE 0.55; based on Maximum Likelihood (ML) SCR:0.51 ± SE 0.22) and the lowest in northeastern sampling block (TCR: 0.77 ±SE 0.39; ML SCR: 0.19 ± SE 0.16). The highest TSR of main prey (large ungulates and primates) was in northeastern block (35.01 ± SD 8.67) and the lowest was in southern block (12.42 ± SD 2.91). The highest level of disturbance, as indicated by TSR of people, was in northeastern sampling block (5.45 ± SD 5.64) and the lowest in southern (1.26 ± SD 2.41). The results suggested that human disturbance strongly determine the density of tigers in the area, more than prey availability. To recover tigers, suggested strategies include controlling human disturbance and poaching to the lowest possible level in addition to maintaining main prey availability.
118
Tigers and Their Prey in Bukit Rimbang Bukit Baling: Abundance
Baseline for Effective Wildlife Reserve Management
Harimau dan Mangsanya di Bukit Rimbang Bukit Baling: Basis Informasi Kelimpahan untuk
Pengelolaan Suaka Margasatwa yang Efektif
Febri Anggriawan Widodo1*, Stephanus Hanny2, Eko Hery Satriyo Utomo2, Zulfahmi1, Kusdianto1,
Eka Septayuda1, Tugio1, Effendy Panjaitan1, Leonardo Subali1, Agung Suprianto1, Karmila Parakkasi1,
Nurchalis Fadhli1, Wishnu Sukmantoro1, Ika Budianti2, & Sunarto1
1WWF – Indonesia Central Sumatra Program, Perum Pemda Arengka Jalan Cemara Kipas No. 33, Pekanbaru
*Email: anggri_widodo@yahoo.co.id
2Balai Besar Konservasi Sumber Daya Alam (BBKSDA) Riau, Jl. HR. Soebrantas Km. 8.5, Pekanbaru
Jurnal Ilmu Kehutanan
Journal of Forest Science
https://jurnal.ugm.ac.id/jikfkt
HASIL PENELITIAN
Riwayat naskah:
Naskah masuk (received): 4 November 2016
Diterima (accepted): 26 Februari 2017
KEYWORDS
Capture-Mark-Recapture
closed population
habitat management
population viability
tiger recovery
ABSTRACT
Managing the critically endangered Sumatran tiger (Panthera tigris
sumatrae) needs accurate information on its abundance and availability of
prey at the landscape level. Bukit Rimbang Bukit Baling Wildlife Reserve in
central Sumatra represents an important area for tigers at local, regional
and global levels. The area has been recognized as a long-term priority Tiger
Conservation Landscape. Solid baseline information on tigers and prey is
fundamentally needed for the management. The objective of this study was
to produce robust estimate of tiger density and prey a vailability in the
reserve. We used camera traps to systematically collecting photographic
samples of tigers and prey using Spatial Capture Recapture (SCR)
framework. We estimated density for tigers and calculated trap success rate
(TSR; independent pictures/100 trap nights) for main prey species. Three
blocks in the reserve were sampled from 2012 to 2015 accumulating a total of
8,125 effective trap nights. We captured 14 tiger individuals including three
cubs. We documented the highest density of tigers (individuals/100 km2) in
southern sampling block (based on traditional capture recapture (TCR) : 1.52
± SE 0.55; based on Maximum Likelihood (ML) SCR:0.51 ± SE 0.22) and the
lowest in northeastern sampling block (TCR: 0.77 ±SE 0.39; ML SCR: 0.19 ±
SE 0.16). The highest TSR of main prey (large ungulates and primates) was in
northeastern block (35.01 ± SD 8.67) and the lowest was in southern block
(12.42 ± SD 2.91). The highest level of disturbance, as indicated by TSR of
people, was in northeastern sampling block (5.45 ± SD 5.64) and the lowest in
southern (1.26 ± SD 2.41). The results suggested that human disturbance
strongly determine the density of tigers in the area, more than prey
availability. To recover tigers, suggested strategies include controlling
human disturbance and poaching to the lowest possible level in addition to
maintaining main prey availability.
Introduction
Managing the critically endangered Sumatran
tiger (Panthera tigris sumatrae) requires solid
baseline and up to date information on the population
at a landscape or forest management unit level (Linkie
et al. 2006). Around 10% of the 3890 global tiger
population lives on the island of Sumatra (Goodrich et
al. 2015; WWF - Tigers Alive Initiative 2016). The
population of this only remaining island tigers is still
believed to be decreasing, mainly due to hunting
pressure (poaching for domestic and international
markets as well as prey depletion due to hunting and
trapping) and habitat loss because of small to
large-scale logging (both legal and illegal),
development of commercial crops (primarily rubber,
oil palm and pulpwood plantations), conversion to
agriculture, and forest fires (Linkie et al. 2003;
Kinnaird et al. 2003; Indonesian Ministry of Forestry
2007; Uryu et al. 2010; Wilting et al. 2015).
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Jurnal Ilmu Kehutanan
Volume 10 No. 2 - Juli-September 2016
INTISARI
Mengelola spesies kunci seperti harimau Sumatera (Panthera tigris
sumatrae) yang dalam kondisi kritis, memerlukan informasi terkait
populasi satwa tersebut dan ketersediaan satwa mangsanya pada tingkat
lanskap. Suaka Margasatwa Bukit Rimbang Bukit Baling di Sumatera
bagian tengah merupakan sebuah kawasan penting untuk harimau baik
pada tingkat lokal, regional, maupun global. Kawasan ini telah diakui
sebagai sebuah kawasan prioritas jangka panjang Tiger Conservation
Landascapes (TCL). Informasi dasar yang sahih mengenai populasi
harimau dan mangsanya sangat dibutuhkan untuk pengelolaan efektif
satwa tersebut dan kawasan habitatnya. Tujuan dari studi ini adalah untuk
menghasilkan perkiraan kepadatan populasi harimau dan ketersediaan
mangsanya di kawasan suaka margasatwa tersebut. Kami menggunakan
perangkap kamera untuk mengumpulkan sampel gambar harimau dan
mangsanya secara sistematis menggunakan kerangka kerja Spatial Capture
Recapture (SCR). Kami memperkirakan kepadatan harimau dan
menghitung angka keberhasilan perangkap atau trap success rate (TSR:
gambar independen/100 hari aktif kamera) untuk satwa mangsa utama.
Tiga blok di dalam suaka margasatwa telah disurvei dari tahun 2012 hingga
2015 mengakumulasikan keseluruhan 8,125 hari kamera aktif. Kami
merekam 14 individu harimau termasuk tiga anak. Kami mendokumen-
tasikan kepadatan tertinggi harimau (individu/100 km2) di blok sampling
selatan (berdasarkan pendekatan analisa capture recapture tradisional
(TCR) 1.52 ± SE 0.55; berdasarkan Maximum Likelihood (ML) SCR 0.51 ± SE
0.22) dan terendah di utara-timur (TCR: 0.77 ±SE 0.39; ML SCR: 0.19 ± SE
0.16). TSR tertinggi dari mangsa utama (ungulate besar dan primata)
adalah di blok sampling utara-timur (35.01 ± SD 8.67) dan terendah adalah
di blok sampling selatan (12.42 ± SD 2.91). Tingkat gangguan tertinggi,
sebagaimana diindikasikan oleh TSR manusia, adalah di blok sampling
utara-timur (5.45 ± SD 5.64) dan terendahnya di blok sampling selatan
(1.26 ± SD 2.41). Hasil studi ini mengindikasikan bahwa gangguan manusia
yang sangat tinggi sangat menentukan kepadatan harimau di kawasan ini,
melebihi pengaruh dari ketersediaan satwa mangsa. Untuk memulihkan
populasi harimau, disarankan beberapa strategi termasuk mengendalikan
gangguan manusia dan perburuan hingga ke tingkat terendah, selain tetap
memastikan ketersediaan satwa mangsa utama yang memadai.
KATA KUNCI
Capture-Mark-Recapture
populasi tertutup
pengelolaan habitat
kesintasan populasi
pemulihan harimau
© Jurnal Ilmu Kehutanan-All rights reserved
Tiger experts have classified global tiger habitats
into several categories of Tiger Conservation
Landscapes (TCL). Sumatra has 12 TCLs with total
area of around 88,000 km² that falls into several
categories based on priority scales related to tiger
viability and action needed to conserve (Dinerstein et
al. 2006). While some TCLs are already widely
recognized and relatively more intensively managed
such as Kerinci Seblat and Bukit Barisan Selatan, there
are some that have only received minor attention
despite their high potential for global tiger
conservation such as Rimbang Baling, Batanghari, and
Bukit Balai Rejang Selatan. Among the TCLs that have
been overlooked from the management perspective
include the long-term priority Rimbang Baling Tiger
Landscape. The core of this tiger landscape is the
Bukit Rimbang Bukit Baling Wildlife Reserve
(BRBBWR). Due to its potentially strategic role for
tiger recovery and relatively low level of hitherto
management attention, WWF Tigers Alive Initiative
has appointed this area as one of their Tx2 (where the
network plan to recover tiger population by
implementing strategic conservation interventions)
sites (WWF - Tigers Alive Initiative 2012). The premise
is that conservation resources invested in such a site
can potentially make higher return in terms of tiger
recovery, compared to same amount of investments
allocated to areas that are already relatively well
managed.
Managing and recovering tigers in BRBBWR
needs accurate knowledge of species’ ecological and
geographic requirements, that is fundamental for
conservation planning and effective management
(Elith et al. 2006). Monitoring tigers and promoting
the effectiveness of conservation management involve
the establishment of robust baseline information and
closely monitoring subsequent trends. Human as a
key factor to influence and affect tiger presence,
needed to be considered, understood, and managed to
ensure effectiveness of the conservation of tigers and
forest as their main habitat (Linkie et al. 2008;
Wibisono & Pusparini 2010; Imron et al. 2011). The
objective of this study was to provide robust
estimation of tiger density and prey availability
including human disturbance level in Bukit Rimbang
Bukit Baling Wildlife Reserve as a baseline for
effective wildlife reserve management especially for
its contribution to national species conservation
target and global tiger recovery program.
Materials and Methods
Study Area
This study was conducted in Bukit Rimbang
Bukit Baling Wildlife Reserve (BRBBWR), central
Sumatra. Established in 1984, the reserve measured
around 136.000 ha and is managed by BBKSDA Riau
(Nature Resource Conservation Agency of Riau),
Indonesia Ministry of Environment and Forestry
(MoEF). Based on Forestry Minister Decree No.
SK.3977/Menhut-VII/KUH/2014 year 2014, the reserve
is now measured 141,226.25 ha. The area plays
important role for tiger conservation as a breeding
site, and as a connectivity among the otherwise
isolated neighboring tiger landscapes such as
Batanghari, Kerinci Seblat, Bukit Tigapuluh, and
Rimbo Panti landscapes. Previous tiger study in the
reserve was conducted in 2006 where only 2
individuals of tigers were identified from 1,574 total
effective trap nights of camera traps deployed in 20
camera stations, covering a relatively small portion of
the reserve (Sunarto et al. 2013).
The reserve borders with acacia plantations, palm
oil plantations, coal mining, and community lands.
Bukit Rimbang Bukit Baling is dominated by hills with
slopes mainly ranging from 25% to 100%. The highest
elevation measured ±1070 masl. The area serves as a
major water catchment area in central Sumatra. To
ensure the ecosystem function and better manage-
ment of the area, in 2016, the Ministry of Environment
and Forestry has recently inaugurated Bukit Rimbang
Bukit Baling as a Conservation Forest Management
Unit (CFMU, based on Environment and Forestry
Minister Decision Letter No. SK.468/Menlhk/
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Setjen/PLA.0/6/2016). The Forest Management Unit,
measured ± 142,156 ha, is located in two districts of
Riau Province: Kampar and Kuantan Singingi. The
designation as an FMU indicates an improvement in
the management of the conservation area, allowing
the area to be managed by a special management body
with specially allocated budget and facilities from the
government.
Methods
This study applied capture-mark-recapture
(CMR) approach that was developed to tackle the
difficulties associated with the estimation of
population size in highly mobile animals (Petit &
Valiere 2006). Noninvasive CMR in this study was
implemented using remotely-triggered camera traps
that allow researchers to collect reliable evidence of
animal presence and associated data such as time,
location, and other relevant variables (Sunarto et al.
2013).
We superimposed the study area with 2x2-km
grid system, and divided it into three sampling blocks.
To ensure that every tiger in the study area has a
non-zero probability of being captured, we installed
camera station in every other 2x2-km grid cell. With
this and assuming that smallest tiger homerange in
Sumatra is 49 km2 (Franklin et al. 1999), we believe
that every tiger homerange would have around 3
camera stations (Sunarto et al. 2013). We set the
camera to take both of videos and photos which is
useful for individual description and identification.
We followed closed-population CMR framework.
During the sampling period in every block, we can
assume that there is no migration (outward and
inward), mortality or birth. We used 3 months in each
sampling period to meet closure assumption, as tigers’
gestation period take around the same period
(Sunarto et al. 2013). We used stripe patterns to
distinguish the uniqueness between tiger individuals.
The differences in stripe patterns were sufficiently
distinct allowing unambiguous identification of
individual tigers (Karanth et al. 2006).
Population and Density Estimation
We used two different methods to estimate tiger
density: traditional capture-recapture (TCR) and
spatial capture recapture (SCR). The first allows
comparison of results to previous studies conducted
in other places; while the second allows application of
the latest advanced technique that presumably more
likely produce results with better accuracy.
We implement the TCR framework in Program
CAPTURE (Rexstad & Burnham 1992). Detection
history used in this approach was developed by
collapsing every 10-day period into one sampling
occasion. So, for the three-month sampling, we have
approximately 9 to 10 sampling occasions in the
detection history. We selected models based on
Akaike Information Criteria (AIC; Akaike 1973).
However, when the only competing model is M0
(model assuming equal capture probability for all
animals) we used the heterogeneity model (Mh) with
Jackknife estimator, which allows each individual to
have different and unique detection probabilities
(Otis et al. 1978; Sunarto et al. 2013). To produce tiger
density estimates, we calculated tiger density using
TCR and by using ½ Mean Maximum Distance Moved
(MMDM). Also, ½ MMDM plus a buffer (to calculate
‘the minimum convex polygon’of the effective camera
trapping site) were used to calculate effective trapping
area (ETA) based on tiger individual movements
(Karanth & Nichols 1998; Sunarto et al. 2013). Mean
Maximum Distance Moved (MMDM) was calculated
based on the movement of all the tigers that were
trapped more than once; it is used to compute
boundaries of buffer strips within capture – recapture
framework to estimate the density when home range
information is not available in the area sampled
(Soisalo & Cavalcanti 2006). Spatial Capture
Recapture (SCR) to estimate population size and
density was implemented using Maximum Likelihood
approach and run in Program DENSITY (Otis et al.
1978; Efford 2004; Petit & Valiere 2006; Efford et al.
2016). Detection history for this approach was
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developed based on an occasion that represents a
24-hour period of camera trapping. For every occasion
we marked each camera station as either active (1)
when at least one camera was operational, or inactive
(0) when no camera was working. This enabled us to
use incomplete trap layout in the input option in
Program DENSITY. We selected the best model based
on the Akaike Information Criteria (AIC; Akaike 1973),
or that corrected version adjusted for small sample
sizes, and their Akaike weights (wi) (Linkie et al.2008;
Sunarto et al. 2013). However, we followed Efford
(2004) and used half normal model for the best
density model with probability of capture (P) as a
function of distance (d) from home range centre to
trap, in the absence of competition that is suitable to
tiger density study. For better accuracy of possible
areas available for tigers, we used forest cover map
2011 available from WWF-Indonesia (Setiabudi 2015);
published at ) as habitat mask in program DENSITY.
Trap Success Rate
We used the trap success rate (TSR) or commonly
known as Relative Abundance Index (RAI) to indicate
abundance of prey species which mostly are difficult
to identify individually for capture-recapture analysis.
TSR represents the number of independent pictures
for each species per 100 trap nights. We followed the
definition of independent pictures as (1) consecutive
photographs of different individuals of the same or
different species, (2) consecutive photographs of
individuals of the same species taken more than 0.5
hours apart, (3) nonconsecutive photos of individuals
of the same species (O’Brien et al. 2003). While we
recognize some of the drawbacks, the use of
photographic rate (photographs per sampling time) as
an index of abundance potentially applies to the
majority of terrestrial mammals where individual
recognition, and hence capture–recapture analysis,
are unfeasible (Rovero & Marshall 2009).
We compared trap success rates of tigers, main
prey species, and people. In this topic we use large
ungulates because tigers are the largest of the fields
and prey almost exclusively on large ungulates
(Karanth et al. 2004). We defined main prey species to
include barking deer (Muntia cusmuntjac), bearded
pig (Susbar batus), sambar deer (Rusa unicolor),
serow (Capricornis sumatraensis), and wild pig (Sus
scrofa); and primate sincluding pig-tailed macaque
(Macacane mestrina) (Table 2). We did not include
Malayan sun bear (Helarcto smalayanus) and Malayan
tapir (Tapirus indicus) as main prey species because
they are unlikely become main tiger prey species
(Sriyanto 2003).
We also assessed the level of human activity in
each sampling block using the photographic rate of
humans, excluding the monitoring team, and level of
vandalism to the cameras by camera lost numbers
(Sunarto et al. 2013). The trap success rate of people
was used to indicate the level of human disturbance in
the study area.
Results and Discussion
The total 8,125 effective trap nights in 83 camera
station resulting in 227 tiger photographs from 30
locations (Table 1). Tiger images were identified into
14 unique individuals including three cubs. The three
sampling blocks, measured 498 km2, covers secondary
and primary forest areas in the reserve (Fig. 1).
Elevation of the camera trap station range between 102
and 1,247 m.asl (Table 1).
We used minimum convex polygon (MCP) of
camera trap stations with buffer of ½ mean maximum
distance moved (MMDM) to calculate effective
trapping area (ETA) for each sampling block. The
largest ETA was in northwestern sampling block (645
km2) and the lowest ETA was in northeastern
sampling block (267 km2) (Table 1).
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Tiger Density
Two approaches of tiger density estimation
produced different results. Traditional Capture
Recapture (TCR) approach generally resulted in
higher estimate than the newer technique of
Maximum Likelihood Spatial Capture Recapture
(MLSCR). This apparently consistent with previous
and other studies implementing the two approaches
(Sunarto et al. 2013).
We documented the highest tiger density in
southern sampling block (1.52 ± SE 0.55
individuals/100 km2 based on TCR), followed by 0.77±
SE 0.39 individuals/100 km2 in northeastern sampling
block, and 0.46± SE 0.17 individuals/100 km2 in
northwestern sampling block (Table 1). Compared to
result from previous study by Sunarto et al. (2013) in
northeastern sampling block (with density estimation
was 0.86 ± SE 0.50 individuals/100 km2), the density
estimate from this study in the same sampling block
was lower. But, compared to the other sampling
blocks, especially in southern, the estimated density
from this study was higher.
Compared to other studies in Sumatra using the
same approach namely in Way Kambas National Park
4.3 individuals/100 km2 (Franklin et al. 1999), Bukit
Barisan Selatan National Park 1.6 individuals/100 km2
(O’Brien et al. 2003) and Bungo and Ipuh at Kerinci
Seblat National Park (2.95 ± 0.56 adult individuals/100
km2 and 1.55 ± SE 0.34 adult individuals/100 km2)
(Linkie et al. 2008), generally the estimated density
from this study was lower.
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Northeastern SouthernNorthwestern
16 November 2011
- 25 February 2012
12
- 10 June 2014
February 28 August
- 19 December 2015
Survey period
ETA (km )
Trap polygon size (km )
Station altitude range (m)
Number of stations
No. of camera lost
No. of trap nights
Detection probability (P)
Unique individual (Mt+1)
Population estimate (N)
½ MMDM (km )
D with ½ MMDM (km )
D MLSCR
2 a 267
95
102-830
20
0
1,688
0.3889
2
2 (SE 0.04)
3.520
0.77 (SE 0.39)
0.19 (SE 0.16)
654
195
378-1,247
31
4
3,169
0.3704
3
3 (SE 0.23)
6.187
0.46 (SE 0.17)
0.23 (SE 0.14)
525
208
291-886
32
0
3,268
0.4074
6
6 (SE 0.73)
4.573
1.52 (SE 0.55)
0.51 (SE 0.22)
b
c
d
2 b
e
2
f
2
g
Table 1. Summary of the survey efforts and tiger density estimates in three different sampling blocks of Bukit Rimbang
Bukit Baling Wildlife Reserve
Tabel 1. Ringkasan usaha survei dan perkiraan kepadatan harimau di tiga blok sampling berbeda di Suaka Margasatwa
Bukit Rimbang Bukit Baling
Compared to other studies outside of Sumatra
such as in Malaysia namely Merapoh 1.98 ± SE 0.54
individual/100 km2, Kuala Terengan 1.10 ± SE 0.52
individuals/100 km2, and Kuala Koh 1.89 ± SE 0.77
individuals/100 km2 (Kawanishi & Sunquist 2004) and
Gunung Basor Forest Reserve, Peninsular Malaysia
2.59 ± SE 0.71 individuals/100 km2 (Rayan & Mohamad
2009), in India (Bhadra 3.42 ± SE 0.84 individuals/100
km2, Kanha 11.70 ± SE 1.93 individuals/100 km2,
Nagarahole 11.92 ± SE 1.71 individuals/100 km2 and
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Figure 1. Three sampling blocks in the study areas of Bukit Rimbang Bukit Baling Wildlife Reserve with
trap polygon and effective trapping area (ETA)
Gambar 1. Tiga blok sampling di kawasan studi Suaka Margasatwa Bukit Rimbang Bukit Baling dengan
ukuran poligon sampling and ukuran sampling efektif (effective trapping area/ETA)
Figure 2. Trap success rates (TSR) of tigers, main prey species and human in three different
sampling blocks of Bukit Rimbang Bukit Baling Wildlife Reserve
Gambar 2. Angka keberhasilan perangkap (TSR) dari harimau, jenis mangsa utama, dan manusia
di tiga blok sampling berbeda di Suaka Margasatwa Bukit Rimbang Bukit Baling.
TSR species
Northeastern Northwestern Southern
Sampling block
0
5
10
15
20
25
30
35
40
Tiger
Main prey
People
Kaziranga 16.76 ± SE 2.96 individuals/100 km2), the
estimated density of tigers from this study was
generally lower. However, the estimated density from
this study was higher than the estimated density in
Terengan, Malaysia.
We believe that the lower density of tiger in this
study area compared to other places was attributed to
human disturbance, poaching, and prey availability as
the highest influence to tigers. We found that tiger
density was highest in southern block where the
lowest human activities were documented (Fig. 2).
TSR of prey and people
We use TSR to get insight into prey availability
and human disturbance for each sampling block. The
highest TSR of main prey was documented in
northeastern sampling block, followed by north-
western sampling block and southern sampling block.
The highest TSR of people was documented in
northeastern sampling block, followed by north-
western sampling block and southern sampling block
(Table 2, 3, and Fig. 2).
Sambar deer as the largest potential prey species
of tigers, were only documented in two sampling
blocks: northeastern with TSR was 0.14 ± SD 0.44 and
northwestern with TSR was 0.09 ± SD 0.37. However,
TSRs of sambar deer were the lowest compared to
other main prey species. Wild pig’s TSR was the
highest among other main prey species in north-
eastern sampling block (22.28 ± SD 26.82). Bearded
pig, another species of pigs, was only captured in
northwestern and had higher TSR (13.80 ± SD 12.76)
than wild pig (0.49 ± SD 1.61) and other main prey
species in the same sampling block. TSRs of barking
deer, as the main target of hunting by local people,
were almost similar in all sampling block (north-
eastern 4.36 ± SD 5.00, northwestern 3.56 ± SD 5.68
and southern 5.53 ± SD 6.31).
Some studies have suggested that prey
availability is the most if not the single most
important determinant for tiger density (Karanth &
Stith 1999; Karanth et al. 2004; Wibisono & Pusparini
2010; Sunarto et al. 2013). However, this study showed
that, tiger densities do not seem to directly
correspond to the abundance of main prey as
indicated by TSR. Sampling block where the highest
tiger density was documented (the southern block)
had the lowest TSR of main prey, but also the lowest
human activity as indicated by their TSR. On the
contrary, sampling block with the highest TSR of main
prey (northeastern) but also had the highest TSR of
human, had the lowest density of tigers. Tiger
Protection Units of WWF and BBKSDA Riau
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Object Trap Success Rate (TSR) SD*
±
Northeastern Northwestern Southern
Barking deer
Bearded pig
Sambar deer
Sumatran serow
Wild pig
Pig-tailed macaque
People
Sumatran tiger
4.36 SD 5.00
0.00
0.14 SD 0.44
0.17 SD 0.78
22.28 SD 26,82
8.06 SD 9.56
5.45 SD 5.64
0.57 SD 0.87
±
±
±
±
±
±
±
3.56 SD 5.68
13.80 SD 12.76
0.09 SD 0.37
0.49 SD 1.07
0.49 SD 1.61
2.70 SD 1.61
2.70 SD 3.27
2.59 SD 3.39
±
±
±
±
±
±
±
±
5.53 SD 6.31
0.00
0.00
0.06 SD 0.40
0.73 SD 1.19
6.08 SD 6.90
1.26 SD 2.41
0.89 SD 1.85
±
±
±
±
±
±
Table 2. Trap success rates of tigers, each main prey and people in three sampling blocks of Bukit Rimbang Bukit Baling
Wildlife Reserve
Tabel 2. Angka keberhasilan perangkap (TSR) dari harimau, jenis mangsa utama dan manusia di tiga blok sampling di
Suaka Margasatwa Bukit Rimbang Bukit Baling
Remark : Total trap success rates of main prey species in each sampling block: northeastern sampling block was 35.01 ± SD 8.67, northwestern
sampling block was 21.14 ± SD 5.22 and southern sampling block was 12.42 ± SD 2.91, *Standard Deviation
Keterangan : Jumlah keseluruhan angka keberhasilan perangkap dari mangsa utama di setiap blok sampling: blok sampling utara – timur 35,01 ±
SD 8,67, blok sampling utara – barat 21,14 ± SD 5,22, dan blok sampling selatan 12,42 ± SD 2,91, *Standar Deviasi
documented high level of hunting in some areas of the
reserve, especially near human settlements. In 2015,
for example, the team collected more than 100 tiger
snares from the reserve. Meanwhile, Wildlife Crime
Team of WWF Indonesia and Ministry of the
Environment and Forestry have identified many
poachers and traders tigers operating around the
reserve.
We believe that prey availability in all areas is
already above the threshold needed to sustain the
highest recorded density of tigers (such as in southern
sampling block) that overall living under high
poaching pressure. Considering the prey availability,
the density of tigers in northeastern sampling block,
we believe, could be higher that what we documented,
but the human disturbance and poaching should be
minimized. The role of human disturbance in
suppressing large mammal population has been
documented, especially in Sumatra (Griffiths & Schaik
1993; Kinnaird et al. 2003; Wibisono & Pusparini 2010).
While TSR has been relatively commonly used as
an indicator of animal activity or abundance, we
recognize that there are drawbacks potentially
involved in the used of TSR for such a purpose. For
example, trap shyness or trap happiness might affect
the result of TSR calculation (Wegge et al. 2004). In
this study, however, we deem that using TSR to
indicate availability of main prey and level of human
activity in each sampling block is still appropriate.
Possible existence of trap shyness or trap happiness of
one species can likely be compensated by other
species as we calculated the TSR not just for single but
for an assemblage of species as the potential main
tiger prey. Interestingly, for tigers where absolute
density and TSR were also calculated in this study, we
found consistency of both results. In this case, for
example, southern sampling block with the highest
tiger density was also the highest TSR of tigers.
Conclusions
This study captured 14 tigers including three cubs
in three sampling blocks of Bukit Rimbang Bukit
Baling Wildlife Reserve. The result proofed that
BRBBWR provides habitat allowing tigers to breed.
The study also showed that tiger densities in three
different sampling blocks vary. Different approaches
used to estimate tiger density resulting in different
126
Jurnal Ilmu Kehutanan
Volume 10 No. 2 - Juli-September 2016
Detection function K AIC AICc
Northeastern, 2012 (N capture = 9, N animal = 2, N recapture = 7)
Half normal
Negative exponential
Hazard rate
Northwestern, 2014 (N capture = 17, N animal = 3, N recapture = 14)
Negative exponential
Hazard rate
Half normal
Southtern, 2015 (N capture = 32, N animal = 6, N recapture = 26)
Hazard rate
Negative exponential
Half normal
2
2
3
2
3
2
3
2
2
131.50
131.53
131.86
253.26
254.95
256.79
436.13
445.75
454.43
NA
NA
NA
NA
NA
NA
476.13
457.75
466.43
0
0.03
0.33
0
1.69
1.84
0
9.62
8.68
0.19 0.16
0.19 0.16
0.21 0.17
0.23 0.14
0.23 0.14
0.23 0.14
0.55 0.25
0.59 0.27
0.51 0.22
±
±
±
±
±
±
±
±
±
0.00409 0.00824
0.00305 0.00867
0.00406 0.00168
0.00387 0.00507
0.00218 0.00099
0.00281 0.00194
0.07635 0.08053
0.02173 0.00895
0.00853 0.00345
±
±
±
±
±
±
±
±
±
14623.60 473803.60
101746.33 NA
14597.74 NA
18762.14 106648.16
21154.09 11381.42
16737.05 17379.77
781.73 890.72
3613.29 788.86
7027.30 1156.70
±
±
±
±
±
±
±
±
±
2
Tiger density (individual/100 km ) model selection with AIC (from the lowest AIC to the highest AIC) of spatial
capture–recapture with conditional maximum likelihood estimators in Program DENSITY. We have chosen half
normal model following Effort (2004) half-normal model for probability of capture (P) as a function of distance (d)
from home range centre to trap, in the absence of competition that is suitable to tiger density study.
2
Model seleksi kepadatan harimau (individu/100 km ) dengan AIC (dari AIC terendah ke AIC tertinggi) spatial capture
– recapture dengan estimator kemungkinan maksimal kondisional di Program DENSITY. Kami memilih model half
normal mengikuti Effort (2004) model half normal untuk kemungkinan tangkapan (P) sebagai sebuah fungsi jarak (d)
dari pusat wilayah jelajah ke jebakan pada kehadiran – ketidakhadiran yang cocok untuk studi kepadatan harimau.
Table 3.
Tabel 3.
estimates. The highest tiger density were documented
in southern sampling block that has the longest
distance to villages, the lowest level of human
disturbance, albeit also the lowest TCR of main tiger
prey species. The result showed that tiger density does
not correspond directly to the indication of prey
availability which suggests that prey might still be
adequate to sustain higher density of tigers if human
disturbance and poaching can be controlled. For tiger
recovery, therefore, some strategies need to be
implemented in BRBBWR especially to control human
disturbance and poaching to the lowest possible level,
while maintaining prey availability to sustain the tiger
population at an increased number. To ensure
long-term viability of tigers, continuing monitoring of
tigers and habitat, active management, and stronger
protection of the key wildlife are fundamentally
needed. Furthermore, as a follow up from this, we
suggest to conduct tiger’s population viability to
assess the best options for management interventions
to recover tigers and increase their long-term viability
(Moßbrucker et al. 2016).
Southern forest block of BRBBWR currently has
the highest density of tigers and likely can be
maintained as the core area of the tiger landscape.
This area should be more strictly protected to prevent
poaching. Other forest block should be managed by
accommodating sustainable use in some areas
without compromising the security of key wildlife
from poaching. An integrated protection that focus
not only on law enforcement but also other
approaches, and intensive management through
multi-stakeholder partnerships can help reduce the
level of human disturbance and facilitate the recovery
of the habitat and prey, and thus tigers. Also,
maintaining a primary forest refuge for tigers is
important (Linkie et al. 2008). As additional to
support a primary forest refuge for tigers, forest
production, and plantation areas in surrounding of
the reserve should also be well managed (Maddox et
al. 2011). Suggested approach to reduce threats and
control human disturbance include a combination of
protection/law enforcement, awareness and alterna-
tive livelihood. Through the newly inaugurated
Rimbang Baling Conservation Forest Management
Unit, the management of the area can be improved
through an integrated approach of wildlife conserva-
tion and sustainable livelihood through full
engagement of local communities and other key
stakeholders.
Acknowledgements
We are grateful to WWF – Indonesia and the
networks especially WWF – United State of America,
WWF – Sweden, WWF – Germany and WWF – Tigers
Alive Initiative in providing funds for this monitoring
works. Also, we thanks other donors such as KfW and
IUCN’s ITHCP for their support. We also thank the
field team (Hermanto Gebok, Amrizal, Wirda, Jerri,
Atan, Dani and everyone) in making this study
possible, and Ministry of Environment and Forestry
especially the local authority, Balai Besar Konservasi
Sumber Daya Alam (BBKSDA) Riau or Nature
Resource Conservation Agency of Riau for the
collaborations and permits. Special thanks are due to
people living in and around Rimbang Baling Wildlife
Reserve to support this study. We also thank editors
and reviewers of Jurnal Ilmu Kehutanan for their
inputs and comments that helped improved this
paper.
References
Dinerstein E, et al. 2006. Setting priorities for the
conservation and recovery of wild tigers: 2005 - 2015.
Hlm 1-50. A user’s guide. WWF, WCS, Smithsonian, dan
NFWF-STF.Washington, D.C - New York.
Efford M. 2004. Density estimation in live-trapping studies.
Oikos 106: 598-610.
Efford MG, Dawson DK, Jhala YV, Qureshi Q. 2016.
Density-depent home range soze revealed by spatially
explicit capture-recapture. Ecography 39: 676-688.
Elith J, et al. 2006. Novel methods improve prediction of
species’ distributions from occurrence data. Ecography
29: 129-151.
Franklin N, Bastoni, Sriyanto, Siswomartono D, Manansang
J, Tilson R. 1999. Last of the Indonesian tigers: a cause for
optimism. Hlm. 130 - 147, dalam Seidensticker J, Christie
S, Jackson P, editor. Riding the tiger: Tiger conservation
127
Jurnal Ilmu Kehutanan
Volume 10 No. 2 - Juli-September 2016
in human-dominated landscapes. Cambridge University
Press.
Goodrich JM. 2010. Human–tiger conflict: A review and call
for comprehensive plans. Integrative Zoology 5(4): 300 -
312.
Goodrich J, et al. 2015. Panthera tigris. The IUCN Red List of
Threatened Species 2015: e.T15955A50659951.
http://dx.doi.org/10.2305/IUCN.UK.2015-2.RLTS.T15955
A50659951.en. IUCN Red List.
Griffiths M, Schaik CP. 1993. The impact of human traffic on
the abundance and activity periods of Sumatran rain
forest wildlife. Conservation Biology 7:623 - 626.
Imron MA, Herzog S, Berger U. 2011. The influence of
agroforestry and other land-use types on the persistence
of a sumatran tiger (Panthera tigris sumatrae)
population: an individual-based model approach.
Environmental Management 48(2): 276–88.
http://doi.org/10.1007/s00267-010-9577-0.
Indonesian Ministry of Forestry. 2007. Strategy and action
plan for the Sumatran tiger (Panthera tigris sumatrae)
2007 - 2017. Indonesian Ministry of Forestry, Jakarta,
Indonesia.
Karanth KU, Nichols JD. 1998. Estimation of tiger densities
in India using photographic captures and recaptures.
Ecology 79: 2852-2862.
Karanth KU, Stith BM. 1999. Prey depletion as a critical
determinant of tiger population viability. Hlm. 100 - 113,
dalam Seidensticker J, Christie S, Jackson P, editor.
Riding the tiger: Tiger conservation in
human-dominated landscapes. Cambridge University
Press.
Karanth KU, Nichols JD, Kumar S. 2006. Assessing tiger
population dynamics using photographic
capture–recapture sampling. Ecology 87(11): 2925–2937.
Karanth KU, Nichols JD, Kumar S, Link WA, Hines JE. 2004.
Tigers and their prey: Predicting carnivore densities
from prey abundance. PNAS 101(14):4854-4858.
Kawanishi K, Sunquist ME. 2004. Conservation status of
tigers in a primary rainforest of Peninsular Malaysia.
Biological Conservation 120: 329 – 344.
Kinnaird MF, Sanderson EW, O’Brien TG, Wibisono HT,
Woolmer G. 2003. Deforestation trends in a tropical
landscape and implications for endangered large
mammals. Conservation Biology 17:245-257.
Linkie M, Chapron G, Martyr DJ, Holden J, Leader-Williams
N. 2006. Assessing the viability of tiger subpopulations
in a fragmented landscape. Journal of Applied Ecology
43:576–586.
Linkie M, Haidir IA, Nugroho A, Dinata Y. 2008. Conserving
tigers Panthera tigris in selectively logged Sumatran
forests. Biological Conservation 141:2410 - 2415.
Linkie M, et al. 2003. Habitat destruction and poaching
threaten the Sumatran tiger in Kerinci Seblat National
Park, Sumatra. Oryx 37(1):41–48. DOI:
10.1017/S0030605303000103.
Linkie M, Wibisono HT, Martyr DJ, Sunarto S. 2008.
Panthera tigris spp. sumatrae. The IUCN Red List of
Threatened Species. Version 2014.3.
www.iucnredlist.org. (diakses Februari 2015).
Maddox T, Priatna D, Gemita E, Salampessy A. 2007. The
conservation of tigers and other wildlife in oil palm
plantations. Jambi Province, Sumatra, Indonesia
(October 2007). ZSL Conservation Report No. 7 The
Zoological Society of London, London.
Moßbrucker AM, Imron MA, Pudyatmoko S, Pratje P,
Sumardi. 2016. Modeling the fate of Sumatran elephants
in Bukit Tigapuluh, Indonesia: Research needs and
implications for population management. Jurnal Ilmu
Kehutanan 10(1):5-18.
Nyhus P, Tilson R. 2004. Agroforestry, elephants, and tigers:
balancing conservation theory and practice in
human-dominated landscapes of Southeast Asia.
Agriculture, Ecosystems and Environment 104: 87 – 97.
O’Brien TG, Kinnaird MF, Wibisono HT. 2003. Crouching
tigers, hidden prey: Sumatran tiger and prey populations
in a tropical forest landscape. Animal Conservation 6:
131-139.
Otis DL, Burnham KP, White GC, Anderson DR. 1978.
Statistical inference from capture data on closed animal
populations. Wildlife Monographs 62.
Petit E, Valiere N. 2006. Estimating population size with
noninvasive capture-mark-recapture data. Conservation
Biology 20(4): 1062–1073.
Rayan DM, Mohamad SW. 2009. The importance of
selectively logged forests for tiger Panthera tigris
conservation: a population density estimae in Peninsular
Malaysia. Oryx 43(1):48–51.
doi:10.1017/S0030605308001890.
Rexstad E, Burnham K. 1992. User’s guide for interactive
Program CAPTURE. Colorado State University, Fort
Collins, USA.
Rovero F, Marshall AR. 2009. Camera trapping
photographic rate as an index of density in forest
ungulates. Journal of Applied Ecology 46:1011–1017. doi:
10.1111/j.1365-2664.2009.01705.x.
Soisalo MK, Cavalcanti SC. 2006. Estimating the density of a
jaguar population in the Brazilian Pantanal using
camera-traps and capture–recapture sampling in
combination with GPS radio-telemetry. Biological
Conservation 129:487-496.
Sriyanto. 2003. Kajian mangsa harimau Sumatera (Panthera
tigris sumatrae, Pocock 1929) di Taman Nasional Way
Kambas, Lampung. Tesis (Tidak dipuplikasikan).
Institut Pertanian Bogor, Bogor.
Sunarto, et al. 2013. Threatened predator on the equator:
multi-point abundance estimates of the tiger Panthera
tigris in central Sumatra. Oryx 47(2):
211–220.doi:10.1017/S0030605311001530.
Sunarto S, Kelly MJ, Parakkasi K, Hutajulu MB. 2015. Cat
coexistence in central Sumatra: Ecological
characteristics, spatial and temporal overlap, and
implications for management. Journal of Zoology
296:104-115.doi:10.111/jzo.12218.
Sunarto S, et al. 2012. Tigers need cover: Multi-scale
occupancy study of the big cat in Sumatran forest and
plantation landscapes. PLoS One 7(1).
doi:10.1371/journal.pone.0030859.
Sunarto S, Sollmann R, Mohamed A, Kelly MJ. 2013. Camera
trapping for the study and conservation of tropical
carnivores. The Raffles Bulletin of Zoology 28:21-42.
Sunquist ME. 1981. The social organization of tigers
Panthera tigris in Royal Chitwan National Park, Nepal.
Smithsonian Contribution to Zoology 336: 1-98.
128
Jurnal Ilmu Kehutanan
Volume 10 No. 2 - Juli-September 2016
Uryu Y, et al. 2010. Sumatra’s forests, their wildlife and the
climate windows in time: 1985, 1990, 2000 and 2009.
WWF - Indonesia Technical Report, Jakarta, Indonesia.
Wegge P, Pokheral CP, Jnawali SR. 2004. Effects of trapping
effort and trap shyness on estimates of tiger abundance
from camera trap studies. Animal Conservation
7:251–256.doi:10.1017/S1367943004001441.
Wibisono HT, Pusparini W. 2010. Sumatran tiger (Panthera
tigris sumatrae): A review of conservation status.
Integrative Zoology 5: 313-323. doi:
10.1111/j.1749-4877.2010.00219.x.
Wibisono HT, et al. 2011. Population status of a cryptic top
predator: An island-wide assessment of tigers in
Sumatran rainforest. PLoS ONE 6(11): e25931.
doi:10.1371/journal.pone.0025931.
Widodo FA, Mazzolli M, Hammer M. 2016. Sumatran tiger
conservation - Forest flagship: researching & conserving
critically endangered Sumatran tigers in Rimbang Baling
Wildlife Sanctuary, Sumatra, Indonesia. Biosphere
expeditions report.Norwich, UK. www.biosphere-
expeditions.org/reports.
Wilting A, et al. 2015. Planning tiger recovery:
Understanding intraspecific variation for effective
conservation. Science Advanves 1(5):e1400175.
WWF - Tigers Alive Initiative. 2012. Tiger Alive Initiative’s 12
Tiger Landscapes.
WWF - Tigers Alive Initiative’. 2016. Report of global tiger
status.
http://tigers.panda.org/news/wild-tigers-numbers-incr
ease-to-3890/.
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Volume 10 No. 2 - Juli-September 2016
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Abstract Biosphere Expeditions and WWF Indonesia ran their third joint expedition with citizen scientists in and around Bukit Rimbang Bukit Baling Wildlife Reserve (BRBBWR), Riau Province, Sumatra, Indonesia, from 30 July to 1 September 2017. The expedition study was a follow-up of the two previous studies in 2015 and 2016, with the tiger and its habitat as the focal point, including prey species and species that contribute to information on tiger habitat quality, or human disturbance of these. In an effort to support tiger conservation in BRBBWR, the objectives of this activity continued to be (1) to conduct long-term tiger and habitat monitoring in locations of high human disturbance along the Subayang river and (2) to involve and engage with local communities in order to raise their awareness of and support for tiger and habitat conservation. 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We found 25 incidences of tiger threat, including two prey species snares in two cells. Illegal logging was very common (10 cells, 71%) and we also encountered people with firearms. The majority of threats occurred in the buffer zone of the reserve. Finally, we visited four elementary schools in three villages, involving 68 pupils in presentations as well as talks about tiger and general conservation. Abstrak Biosphere Expeditions dan WWF Indonesia atas izin BBKSDA Riau kembali melakukan ekspedisi gabungan untuk ketiga kalinya bersama dengan sukarelawan global di Suaka Margasatwa Bukit Rimbang Bukit Baling (SMBRBB) dan sekitarnya, Provinsi Riau, Sumatera, Indonesia, dari 30 Juli hingga 1 September 2017. Studi ekspedisi ini merupakan tindak lanjut dari dua studi sebelumnya pada tahun 2015 dan 2016, dengan harimau dan habitatnya sebagai focal point, termasuk satwa mangsa dan spesies lain yang berkontribusi pada informasi kualitas habitat harimau, atau gangguan manusia terhadap hal tersebut. Kegiatan ini dilakukan dalam upaya mendukung pelestarian harimau di SMBRBB dengan melanjutkan tujuan kegiatan sebelumnya yaitu (1) melakukan pemantauan harimau dan habitat jangka panjang di lokasi-lokasi yang memiliki tingkat gangguan manusia tinggi di sepanjang sungai Subayang dan (2) melibatkan dan melibatkan masyarakat lokal dalam rangka untuk meningkatkan kesadaran dan dukungan mereka terhadap konservasi harimau dan habitatnya. Survei deteksi-non-deteksi untuk harimau dan spesies mangsa dilakukan dengan berjalan kaki atau dengan perahu, meliputi kawasan SMBRBB utamanya di sepanjang sungai Subayang, yang berfungsi sebagai jalur perjalanan dan titik akses yang nyaman bagi tim survei. Metode yang digunakan untuk mencatat spesies (mamalia dan burung besar) melalui pencatatan keberadaan-ketiadaan spesies dan frekuensi individu dalam sel pengamatan berukuran 2x2 km dengan mencatat temuan seperti tanda, penampakan dan suara satwa. Tujuh belas kamera penjebak juga digunakan untuk merekam keberadaan spesies. Penelitian ini dirancang untuk membandingkan keberadaan spesies dalam sel dengan dan tanpa keberadaan desa (selanjutnya dikodekan sebagai sel desa dan non desa) untuk mengetahui apakah kedekatan dengan desa berpengaruh terhadap distribusi spesies di hutan. Untuk tujuan ini, tim tersebut mensurvei sel target menggunakan lembar data standar untuk survei kamera penjebak dan deteksi tanda. Selain itu, kami juga mewawancarai penduduk desa tentang keberadaan dan interaksi harimau dan spesies satwa liar utama lainnya. Kami mensurvei empat belas sel (tiga desa dan sebelas non-desa), mencatat empat belas spesies mamalia yang berbeda (termasuk kerbau Bubalus bubalis) dalam empat genera mamalia, ditambah dua spesies burung besar. Kecuali babi hutan Sus scrofa, beruang madu Helarctos malayanus dan kerbau, semua spesies jarang ditemukan (≤ 5 keberadaan dalam sel), sehingga menghambat analisis lebih lanjut. Kerbau dan babi hutan ditemukan tersebar merata di sel desa dan non desa. Tidak ada tanda-tanda harimau yang dijumpai. Kami mencatat tiga spesies utama mangsa harimau: kijang Muntiacus muntjak, kera ekor babi Macaca nemestrina dan babi hutan. Jumlah RAI (indeks kelimpahan relatif) kamera penjebak tertinggi adalah babi hutan (15,70) diikuti oleh monyet ekor babi (8,26) dan kera ekor panjang Macaca fascicularis (3,31), yang tidak termasuk jenis mangsa harimau. Kijang sebagai spesies mangsa harimau besar memiliki RAI adalah 1,65. Jenis owa yang terancam punah (EN) Hylobates agilis dan siamang Symphalangus syndactylus dijumpai di masing-masing empat dan delapan sel, tetapi kami tidak merekam salah satu spesies tersebut di kamera penjebak karena mereka adalah satwa arboreal. Kami juga mencatat spesies mangsa sekunder seperti landak umum Hystrix brachyura, burung kuau raja Argusianus argus, keduanya memiliki kelimpahan rendah (RAI 0 dan 2,48 masing-masing). Keberadaan semua spesies tersebut menjadi ciri khas bahwa habitat harimau masih baik, meskipun tidak ada tanda-tanda harimau yang tercatat. Kami mewawancarai 14 penduduk desa, 8 di antaranya melaporkan pernah melihat harimau dan jejak harimau. Sebagian besar penduduk desa (n = 12, 86%) mengatakan bahwa mereka takut pada harimau, sembilan di antaranya merasa keberadaan harimau berdampak buruk bagi kawasan tersebut. Namun, semua kecuali satu orang yang diwawancarai memahami bahwa harimau dilindungi di Indonesia dan sebelas orang yang diwawancarai (79%) setuju bahwa seharusnya demikian. Kami menemukan 25 keberadaan ancaman harimau, termasuk dua jerat mangsa harimau dalam dua sel berbeda. Penebangan liar sangat umum (10 sel, 71%). Mayoritas ancaman terjadi di zona penyangga suaka margasatwa tersebut. Terakhir, kami mengunjungi empat sekolah dasar di tiga desa, melibatkan 68 siswa dalam presentasi serta berdiskusi tentang harimau dan konservasi secara umum.
Research
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Abstract Biosphere Expeditions and WWF Indonesia ran their second joint expedition with volunteers in and around Bukit Rimbang Bukit Baling Wildlife Reserve (BRBBWR), Riau Province, Sumatra, Indonesia, from 17 July to 12 August 2016. The expedition study was a follow-up of the previous study in 2015, with the tiger and its habitat as the focal point, including prey species and species that contribute to information on tiger habitat quality, or human disturbance of these. In an effort to support tiger conservation in BRBBWR, the objectives of this activity were (1) to conduct long-term tiger and habitat monitoring in locations of high human disturbance along the Subayang river and (2) to involve and engage with local communities in order to raise their awareness of and support for tiger and habitat conservation. Surveys were conducted on foot or by boat, covering BRBBWR along the Subayang river, which served as a convenient travel route and access point for survey teams. The methods employed to record species (mammals and large birds) involved recording species presence-absence and frequency of individuals in a grid of 2x2 km cells by means such as signs, sightings and calls. Camera traps were also employed to record species presence. The study was designed to compare the presence of species in cells with and without villages in order to investigate whether village presence had any influence on species distribution in the forest. Sixteen cells were surveyed, seven were non-village cells and nine were village cells. In total, thirteen wildlife species (including water buffalo) in four mammal genera were recorded, plus two large bird species. Except for the wild boar Sus scrofa, the sun bear Helarctos malayanus and the water buffalo, all species had very low scores (≤ 5 of presence in cells). This hampered any further analysis. The water buffalo and wild boar were found to be evenly distributed in village and non-village cells. The sun bear, considered Vulnerable (VU) by the IUCN (International Union for the Conservation of Nature), was the only species that displayed a noticeably higher presence value in non-village cells, suggesting a certain degree of avoidance of human presence. The number of independent pictures recorded by camera traps was ≥ 5 for humans (n=23), mouse deer Tragulus sp. (n=7), wild boars (n=6), pig-tailed macaque Macaca nemestrina (n=11) and common porcupine Hystrix brachyura (n=9). The pig-tailed macaque, listed as Vulnerable (VU) by the IUCN, was camera-trapped more often in village cells (n=8), than in non-village cells (n=3). The Endangered (EN) gibbon Hylobates agilis and the siamang Symphalangus syndactylus were present, but infrequently recorded. The presence of these species suggests that villagers have a relatively high tolerance towards them and also towards other species such as the crop-rading wild boars and sun bears. Four recognised mammalian prey species for tiger were recorded during the expedition, namely the barking deer Muntiacus muntjak, the sambar deer Rusa unicolor, pig-tailed macaque and wild boar. The common porcupine and two birds, the crested partridge Rollulus rouloul and the great argus pheasant Argusianus argus, may occasionally be taken by tigers, and all of them were recorded at low rates. The presence of all these species, including known tiger prey, is thought to be beneficial to tiger presence, although none were recorded by the expedition. However, a large proportion of villagers interviewed (n=16) have reportedly seen tigers (25%) and tiger tracks (38%) during their lifetimes. Most villagers were scared (72%) or slightly scared (14%) of tigers and as a result a majority (69%) had a negative opinion of tiger presence. However, most interviewees recognised the importance of tigers for the country (61%) and for tourism (81%), and understood that they should be protected (>80%). During the survey, snares installed for tiger prey were found in 14% of 16 grid cells sampled and shotguns were heard. Four schools (three elementary schools and one junior high school) were visited, involving 158 pupils in presentations as well as talks about tiger and general conservation. Abstrak Biosphere Expeditions dan WWF Indonesia menyelenggarakan ekspedisi kedua mereka bersama para sukarelawan di Suaka Margasatwa Bukit Rimbang Bukit Baling (SMBRBB), Provinsi Riau, Sumatra, Indonesia, dari tanggal 17 Juli hingga 12 Agustus 2016. Studi ekspedisi ini adalah sebagai sebuah tindak lanjut dari studi sebelumnya di tahun 2015 dengan harimau dan habitatnya sebagai poin utama termasuk satwa mangsa dan satwa lain yang berkontribusi pada kualitas habitat harimau atau gangguan manusia. Dalam sebuah usaha untuk mendukung upaya konservasi harimau di SMBRBB, tujuan dari studi ini adalah (1) melakukan pemantauan jangka panjang untuk harimau dan habitatnya di lokasi – lokasi dengan gangguan manusia tinggi sepanjang sungai Subayang dan (2) melibatkan masyarakat lokal untuk meningkatkan kesadartahuan mereka dan mendukung untuk upaya konservasi harimau dan habitatnya. Beberapa survai dilakukan dengan berjalan kaki atau berperahu, mencakup sepanjang sungai Subayang yang dapat diakses secara mudah oleh tim – tim survai. Metode ini digunakan untuk merekam spesies (mamalia dan burung – burung besar) termasuk merekam kehadiran-ketidakhadiran (presence-absence) spesies dan frekuensi individu – individu spesies dalam grid sel pemantauan 2x2 km melalui perjumpaan langsung maupun tanda keberadaan seperti jejak, suara, dsb. Kamera penjebak juga digunakan untuk merekam keberadaan satwaliar. Studi ini didesain untuk membandingkan keberadaan spesies di grid – grid dengan dan tanpa keberadaan desa untuk mengetahui apakah keberadaan desa memiliki pengaruh terhadap persebaran satwaliar. Enam belas grid sel tersurvai, tujuh dimana tanpa desa dan sembilan berdesa. Keseluruhan, tiga belas spesies satwaliar (termasuk kerbau) dalam empat genus mamalia dan aves terekam, ditambah dua spesies burung besar. Kecuali babi hutan Sus scrofa, beruang madu Helarctos malayanus dan kerbau, seluruh spesies memiliki skor kehadiran rendah (≤ 5 grid sel) pada grid sel tersurvei. Dengan data yang minim, menghambat analisis data. Kerbau dan babi hutan terekam pada seluruh sel baik berdesa maupun tanpa desa. Beruang madu dengan status Vulnerable (VU) berdasarkan IUCN, adalah spesies yang dapat terlihat jelas kehadirannya lebih tinggi di grid sel tanpa desa, kemungkinan menghindari keberadaan manusia. Jumlah dari gambar independen terekam kamera penjebak dengan jumlah ≥ 5 gambar independen untuk manusia (n=23), kancil Trangulus sp. (n=7), babi hutan (n=6), monyet beruk Macaca nemestrina (n=11) dan landak Hystrix brachyura (n=9). Monyet beruk, terdaftar sebagai Vurnerable (VU) di IUCN terekam kamera penjebak lebih sering di grid sel berdesa (n=8) daripada tanpa desa (n=3). Owa ungko Hylobates agilis terdaftar Endangered (EN) atau terancam oleh IUCN dan siamang Symphalangus syndactylus juga hadir selama survai, namun sangat jarang terekam. Kehadiran dari spesies – spesies memberikan kesan bahwa keberadaan desa – desa secara relatif bertoleransi tinggi terhadap mereka dan juga terhadap spesies lain seperti babi hutan dan beruang madu. Empat satwa dikenal sebagai mangsa harimau terekam selama ekspedisi ini yaitu kijang Muntiacus muntjak, rusa sambar Rusa unicolor, monyet beruk, dan babi hutan. Landak dan dua spesies burung besar, burungpuyuh sengayan Rollulus rouloul dan burung kuau Argusianus argus mungking secara terkadang termangsa oleh harimau dan semua spesies yang terekam dengan nilai rendah. Kehadiran dari spesies – spesies tersebut, termasuk satwa mangsa harimau, diperkirakan memberikan dampak baik pada kehadiran harimau meskipun beberapa diantara mereka tidak terekam selama ekspedisi ini. Selain itu, dari jumlah masyarakat lolal terwawancara (n=16) memiliki laporan pernah melihat harimau (25%) dan jejak harimau (38%) seumur hidup mereka. Umumnya masyarakat mengalami ketakutan (72%) or sedikit takut (14%) dan sebagai hasil, mayoritas (69%) memiliki pendapat negatif terhadap keberadaan harimau. Akantetapi, umumnya, masyarakat lokal terwawancara mengetahui pentingnya keberadaan harimau untuk negara (61%) dan untuk kunjungan wisata (81%), dan seharusnya harimau dilindungi (>80%). Selama survai, jerat mangsa harimau ditemukan di 14% dari 16 grid tersurvei dan suara tembakan kemungkinan perburuan didengar. Empat sekolah (tiga sekolah tingkat dasar dan satu sekolah tingkat menengah pertama) dikunjungi dengan melibatkan 158 murid keseluruhan dalam presentasi – presentasi dan pengajaran tentang harimau dan konservasi secara umum.
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