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Popul Ecol (2009) 51:115–121 DOI 10.1007/s10144-008-0093-5

ORIGINAL ARTICLE

Estimating abundance with sparse data: tigers in northern Myanmar Antony J. Lynam Æ Alan Rabinowitz Æ Than Myint Æ Myint Maung Æ Kyaw T. Latt Æ Saw Htoo T. Po

Received: 10 October 2007 / Accepted: 12 May 2008 / Published online: 18 June 2008 Ó The Society of Population Ecology and Springer 2008

Abstract As part of a national strategy for recovering tiger populations, the Myanmar Government recently proposed its first and the world’s largest tiger reserve in the Hukaung Valley, Kachin State. During November 2002–June 2004, camera-traps were used to record tigers, identify individuals, and, using capture–recapture approaches, estimate density in the reserve. Despite extensive (203 trap locations, 275–558 km2 sample plots) and intensive ([4,500 trap nights, 9 months of sampling) survey efforts, only 12 independent detections of six individual tigers were made across three study sites. Due to the sparse data, estimates of tiger abundance generated by Program CAPTURE could not be made for all survey sites. Other approaches to estimating density, based on numbers of tigers caught, or derived from borrowed estimates of detection probability, offer an alternative to capture–recapture analysis. Tiger densities fall in the range of 0.2–2.2 tigers/100 km2, with 7– 71 tigers inside a 3,250 km2 area of prime tiger habitat, where efforts to protect tigers are currently focused. Tiger

A. J. Lynam (&) Wildlife Conservation Society, International Programs, 2300 Southern Blvd, New York 10460, USA e-mail: [email protected] A. Rabinowitz Panthera, 8 W 40th Street, 18th Floor, New York 10019, USA T. Myint  K. T. Latt  S. H. T. Po Wildlife Conservation Society, Myanmar Program, Yangon, Myanmar M. Maung Division of Wildlife and Nature Conservation, Forest Department, Ministry of Forestry, West Gyogone, Insein, Yangon, Myanmar

numbers might be stabilized if strict measures are taken to protect tigers and their prey from seasonal hunting and to suppress illegal trade in wildlife. Efforts to monitor abundance trends in the tiger population will be expensive given the difficulty with which tiger data can be obtained and the lack of available surrogate indices of tiger density. Monitoring occupancy patterns, the subject of a separate ongoing study, may be more efficient. Keywords Camera-traps  Capture–recapture  Myanmar  Population density  Tigers

Introduction Information on abundance and variation in abundance forms one basis for the effective management of tropical large carnivore populations. However, due to the rarity of some species, particularly those subject to direct hunting or hunting of prey, precise estimates of population size are usually difficult to obtain, while changes in populations potentially go unnoticed. Camera-traps generate verifiable photographic evidence for tropical large carnivores that is useful not only for confirming their presence (Silveira et al. 2003; Srbek-Araujo and Chiarello 2005), but can potentially be used to generate sample estimates of density (Karanth and Nichols 1998; O’Brien et al. 2003; Maffei et al. 2004; Silver et al. 2004) and assess spatial trends in populations (Johnson et al. 2006). However, the utility of camera-traps for estimating abundance may be constrained when a target species is difficult to detect due to cryptic behavior or very low density. All of these are traits of the Tiger Panthera tigris. The objective of this study was to estimate the abundance of tigers in the proposed Hukaung Tiger Reserve, northern Myanmar. A second question for

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Potential trap locations, places where tiger or prey signs had been detected, were selected at each of the three sites during short 1–3-day reconnaissance surveys on foot and on elephant-back. The potential locations were recorded using GPS devices and logged onto topographic base-maps TM using MapSource software and a laptop computer. Camera-traps (CamtrakkerTM, Camtrak South Inc., Watkinsville, GA), each consisting of an autofocus 35-mm camera with a built-in flash attached to a passive infrared monitor, were placed to maximize the probability of detecting tigers (Karanth and Nichols 2002).

managers concerns the occupancy of habitats by tigers. A follow-up study, currently in progress but employing different methods, will address the question of occupancy of habitats. These studies are being undertaken as part of an effort to guide management efforts for tigers in this reserve and in other important tiger areas in the country (Lynam et al. 2006a).

Materials and methods Study area

Survey design 0

0

The Hukaung Tiger Reserve (HTR) (25°23 –27°23 N and 95°330 –97°180 E) offers great potential for tiger conservation given its size (21,802 km2) and because it forms part of a contiguous forest block (ca. 50,000 km2) that links Myanmar, north-eastern India, and Nepal, across which there are relatively low impacts from humans (Sanderson et al. 2002). The HTR protects the entire watershed of the Upper Chindwin River Basin with an elevational range from 94 to 3,440 m. Vegetation in lowland areas is a mosaic of tropical broadleaf forest and grasslands with some areas cleared for crop farming or plantation. Broadleaf forest covers hill slopes where shifting cultivation is done by indigenous people, although the practice is geographically restricted. Temperate broadleaf and conifer forests or shrubs cover high ridges and peaks. The HTR is bounded to the north, east, and west by mid-elevation peaks. This study was conducted in the core area of the reserve, a roughly 3,250 km2 area that covers lowlands and hill slopes containing prime habitats for tigers and that is the focus of management efforts (M. Maung and S. Htun, personal communication).

Camera-trapping for density estimation needs to balance the competing desires of reducing the possibility that a tiger walking through the array of traps is not detected (Karanth and Nichols 2002), which is achieved by reducing inter-trap distance (Wegge et al. 2004), and increasing numbers of tiger individuals encountered, which is achieved by increasing areal coverage of the camera-trap array (to sample more tiger ranges) and increasing numbers of trap nights (Wegge et al. 2004). In the Hukaung Tiger Reserve, the lack of roads means that frequent movement of traps is not possible, and the number of available camera-traps was limited. We followed the suggestion of Karanth and Nichols (2002) to achieve the spacing objectives. At each site, 48–50 locations were selected from the potential locations for camera-trap sampling (Table 1). The final camera-trap locations were on average 2.9 km apart (range 0.6–10.7 km) so that the arrays of camera-trap locations covered several hundred square kilometers (see also ‘‘Results’’). At each location, a pair of traps were established facing each other on opposite sides of trails or streambeds, approximately 0.4 m above the ground. Pairs of traps were used to record both sides of a tiger, to validate the two unique stripe patterns on each individual. For the purpose of sampling, trap locations were divided into traplines. There were four or five traplines at each site with an average 10–12 locations along each trapline (Table 1). Traplines were established one at a time with camera-traps set to operate 24 h a day for an average of 18 days (range

Methods Because tiger density may vary across continuous habitat, and it was desirable to quantify this variation, sample estimates of density were attempted at three sites in the core area of the reserve where previous surveys (Lynam 2003) and reliable local reports confirmed use by tigers.

Table 1 Survey efforts for tigers using camera-traps in the Hukaung Tiger Reserve, Myanmar (October 2002–June 2004) Study site

Dates

Tawang River

1 Dec 2002–22 Jan 2003

53

Taron River

26 Nov 2003–11 Feb 2004

77

Naga Hills

28 Mar 2004–28 May 2004

123

Days

Total camera-trap locations

No. traplines (average locations per trapline)

Trap days

48

5 (10)

1,328

50

4 (12)

1,062

60

49

4 (12)

190

147

1,069 3,459

Popul Ecol (2009) 51:115–121

12–26 days), after which time the trapline was closed down, films sent for developing, and a new trapline opened. This procedure was done until all traplines had been run once. Karanth and Nichols (1998, 2000) used 3-month samples to ensure demographic closure, an assumption of the capture–recapture method, for tiger surveys in India. They suggested that sampling periods of 8–12 weeks were acceptably short relative to tiger population turnover (Karanth and Nichols 2002). In this study, demographic closure of the population was ensured by completing each of the three site-surveys within 53–77 days (Table 1). Analysis Tiger individuals were identified from developed films using unique striping patterns on the flanks, shoulders, and hind quarters (Franklin et al. 1999). Capture histories for individual tigers were developed, and a capture–recapture approach (White et al. 1982) using a web-based version of Program CAPTURE (Otis et al. 1978; Rexstad and Burnham 1991; White et al. 1982) was employed to estimate numbers of tigers N^ present at each site following the recommendations of Karanth and Nichols (2002). Program CAPTURE estimates a null population model (Mo), which assumes equal probabilities of capture for individuals, or a jackknife population model (Mh), which allows for heterogeneous probability of capture of individuals (White et al. 1982). Since tigers in different age classes may have different probabilities of capture (Karanth and Nichols 2002) due to heterogeneity of dispersal patterns (Smith 1993) or other behaviors that affect detectability, this latter model best reflects the biological reality of trapping tigers (Karanth and Nichols 1998). Program CAPTURE approx^ imates the standard error (SE) for an estimate of N: However, at small samples sizes, it is difficult to compute the 95% confidence interval (95% CI) for a CAPTURE estimator, the CI is not always symmetric, and the coverage of the CI is often less than 95% (T. O’Brien, personal communication). Therefore, following the recommendation of White et al. (1982) we estimated a 95% CI as N^  1:96ðSEÞ; then rounded up to the nearest integer to get the upper limit, and rounded down to the nearest integer to get the lower limit. If the lower limit was less than the number of individuals caught Mtþ1 we then used Mtþ1 as the lower 95% CI (White et al. 1982). Because tigers are declining across their range, surveys have often revealed low numbers of individuals or recaptures (O’Brien et al. 2003; Kawanishi and Sunquist 2004; Johnson et al. 2006). In some cases, numbers may be too small to reliably estimate abundance via Program CAPTURE. Two alternatives exist for estimating tiger abundance where direct estimation is not possible. The first alternative is simply the number of tiger individuals caught

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(Mtþ1 ), in the survey. The second alternative is derived from the daily detection probability p^ an empirically derived maximum likelihood estimate, and the number of occasions in the sampling period T, by estimating p^1 ; the probability of detecting an individual at least once during the sampling period. For example, if p^ ¼ 0:15 then the probability of not detecting a tiger on a given day is 1  p^ ¼ 0:85: The probability of never detecting a tiger over a ten-occasion sampling period is ð1  p^Þ10 ¼ 0:197: The probability p^1 of detecting an individual at least once during the sampling period is 1 - 0.197 = 0.803. If two tigers are observed in the survey, the number of tigers is then estimated as N^1 ¼ Mtþ1=^ p1 ¼ 2:5 tigers. The variance ^ of N1 can be calculated as  Var ðCÞ=C2 þ Varð^ p1 Þ=^ p21    N^12 or N^1  p^1  ð1  p^1 Þ =C 2 þ p^1  ð1  p^1 Þ = N^1 = p^21 g  N^12 ; where C is the sum of positive detections (1s) and failures to detect (0s). Tiger density was estimated by assuming a sampling effective area equivalent to the combined area of cameratrap locations each buffered by a distance equivalent to either the mean maximum distance (MMDM) between recaptures of individual tigers (Parmenter et al. 2003) or half the mean maximum distance (‘MMDM) between recaptures of individual tigers (Wilson and Anderson 1985). Translation of the abundance estimate into density was done by: D^0 ¼

N^ ; ^ AðWÞ

^ where AðWÞ is the estimated sampling effective area (Karanth and Nichols 1998). Lower and upper ranges around individual density estimates were calculated by substituting values for the 95% CIs for D^ in the density equation.

Results A total of 21 photographs of tigers were recorded across the three intensive sampling plots from 3,459 trap days, 147 trapstations, and 190 days of survey effort (Table 1). Twelve of these photographs were of six individually identifiable tigers and were used in subsequent analyses. Other photographs were partial or blurred shots of tigers, and individuals could not be identified. The probability that a tiger was captured on a single sampling occasion varied from 0.11 to 0.32 between study sites (Table 2). Capture–recapture results were interpretable from the Program CAPTURE analysis for two study sites (Tawang River and Taron River). At Taron River the results violated the closed population assumption (Closure test, P \ 0.05; Table 2). However, failure of the closure test may be due to behavioral changes in capture

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118 Table 2 Statistical parameters from capture-recapture analysis and sample abundance estimates using three statistical models for tigers at three sites in the proposed Hukuang Tiger Reserve, Myanmar

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Parameter

Tawang River

Taron River

Naga Hills –

Probability of capture under Mh

p^

0.111

0.318

Closure test

P

0.632

0.015



Selection criteria

Mo

1.00

1.00



Selection criteria

Mh

0.86

0.95



No. occasions

T

9

11

11

No. individuals caught

Mtþ1

2

2

2

Total captures-recaptures

3

7

2

Est. no. tigers by Mo

n p^1 ^ (95% CI) N^ ± SE(N)

2.0 ± 0.92

2.0 ± 0.18

(2–4)

(2–2)

Est. no. tigers by Mh

^ (95% CI) N^ ± SE(N)

Probability of at least 1 detection

Est. no. tigers by borrowed p^1

N^1 ± SE(N^1 ) (95% CI)

0.985

3.0 ± 1.35

2.0 ± 0.05

(2–6)

(2–2)

– – 2.0 ± 1.54 (2–5)

probability (White et al. 1982), and our surveys were done well within the timeframe considered sufficient to assume population closure (Karanth and Nichols (1998, 2000). Also, the closure test has low power at small sample sizes. For these reasons, we decided that the failure of the closure test was in this case not sufficient grounds for discarding the result of the capture–recapture analysis. At a third site (Naga Hills), there were only single captures of two individual tigers, so the capture–recapture analysis did ^ not permit reliable interpretation of tiger abundance (N). ^ The Instead, we considered alternative estimates for N: first alternative, the number of tiger individuals caught (Mtþ1 ), was two. The second alternative, derived from borrowing daily detection probability p^ from the adjacent Taron River survey (0.318), and the number of occasions in the sampling period T(11), was 2.0 with SE 1.54 (Table 2). Assuming a ‘MMDM buffer radius, the total effective sampling area of the three plots was 1,369 km2, or 22% of the core area, or 6.3% of the total reserve area (Fig. 1; Table 3). In the case of Naga Hills where no recaptures were made, the buffer from the Taron River survey was assumed to estimate the sampling effective area. Using abundance N^ estimated from Program CAPTURE, tiger density was 0.36 and 1.09 tigers/100 km2 assuming a ‘MMDM buffer or 0.21 and 0.66 tigers/100 km2 using a MMDM buffer, at Taron River and Tawang River, respectively (Table 3). Using the borrowed p^ method for Naga Hills, density was 0.37 tigers/100 km2 using a ‘MMDM buffer, or 0.22 tigers/100 km2 using a MMDM buffer. Substituting Mtþ1 for N^ gave estimates of naı¨ve density in the range 0.36–0.73 tigers/100 km2 using a ‘MMDM buffer, or 0.21–0.44 tigers/100 km2 using a MMDM buffer method across the three sites.

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Discussion Knowing the number of tigers in HTR would provide one baseline for monitoring management efforts to recover the species (Lynam et al. 2006a). Rarity makes difficult the task of accurately estimating populations using capture– recapture models because sample sizes, i.e., the numbers of individual tigers caught and numbers of recaptures (Otis et al. 1978; White et al. 1982), are low. However, rarity is the typical situation for the Tiger over most of its global range because populations have been decimated (Sanderson et al. 2006). For example, in protected areas in northern and central Thailand with habitats similar to HTR, a sign survey (Rabinowitz 1989), and two camera-trap surveys (Lynam et al. 2001, 2006b) across areas 75–300 km2 in size, each found evidence of only one tiger individual. At Namdapha, a reserve in northeast India that lies adjacent to HTR, camera-traps failed to detect tigers although they were present (Karanth and Nichols 2000). Because population surveys had not previously been attempted in HTR, a relatively large effort was expended to detect tigers and maximize sample sizes. Despite, this effort and reports indicating the widespread distribution of tigers in the reserve (WCS, unpublished data), estimating the tiger population at our sites was potentially problematic due to the small numbers of individuals detected and low numbers of recaptures from surveys. Numbers of individual tigers might have been increased had surveys been done over wider areas. However, since the largest sampling area (Taron River) was almost the size of the island state of Singapore (645 km2), increasing it would require an enormous investment of resources. That tiger recapture rates were low may be explained in part by behavioral avoidance of humans along shared travel routes, i.e., dry

Popul Ecol (2009) 51:115–121

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Fig. 1 Locations of three camera-trap sampling areas in the Hukaung Tiger Reserve, Kachin State, Myanmar. From west to east, Naga Hills, Taron River, and Tawang River

Table 3 Spatial parameters and tiger density estimates at three sites in the Hukaung Tiger Reserve, Myanmar Site

Buffer radius

Buffer distance (km)

Sample area (km2)

Naı¨ve density (tigers/100 km2)

Tawang River

‘MMDM

2.37

275

0.73

Taron River

‘MMDM

3.96

558

0.36

Naga Hills

‘MMDM

3.96

536

0.37

Tawang River Taron River

MMDM MMDM

4.74 7.92

456 968

0.44 0.21

Naga Hills

MMDM

7.92

931

0.22

Densitya [tigers/100 km2 (95% CI)]

1.09 (0.72–2.18) 0.36 (0.36–0.36) 0.37 (0.37–0.93)

– 0.66 (0.44–1.31) 0.21 (0.21–0.21)

0.22 (0.22–0.54)

a

Based on estimate of number of tigers by borrowed p^

b

Based on the jackknife population model (Mh) from capture-recapture analysis and using Program CAPTURE

stream beds, during the dry season. An estimated 100,000 itinerant hill tribe people (R. Tizard, personal communication) hunt wildlife and collect forest products in the

Densityb [tigers/100 km2 (95% CI)]



Hukaung Valley during this period. Judging from tracks followed by survey teams when camera-traps were collected, individual tigers sometimes moved off these

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preferred travel routes, perhaps to avoid encounters with humans. While this would have the effect of lowering the frequency of photographic detections, it is unlikely any individual tiger was completely missed by camera-trapping due to such behavior. Although sample sizes were small, we were able to directly estimate abundance using Program CAPTURE at two sites (Tawang River and Taron River) and to arrive at estimates for all three sites using alternative methods. Using a ‘MMDM buffer, which tends to overestimate true density (Parmenter et al. 2003), the different methods led to density estimates in the range 0.36–1.09 tigers/100 km2 with a minimum value of 0.36 and a maximum of 2.18 tigers/100 km2. Using a MMDM buffer, which tends to underestimate at low density (Parmenter et al. 2003), the different methods gave estimates in the range 0.21–0.66 tigers/100 km2 with a minimum value of 0.21 and a maximum of 1.31 tiger/100 km2. Therefore, true density of tigers is bracketed by the minimum of the underestimates and the maximum of the overestimates, or 0.21–2.18 tigers/ 100 km2. This capture-recapture derived density estimate range compares with that reported from a study in Lao PDR (0.2–0.4 tigers/100 km2; Johnson et al. 2006), and is lower than estimates reported or inferred from studies in Sumatra (1.2–3.2 tigers/100 km2; O’Brien et al. 2003), Peninsular Malaysia (1.1–6.62 tigers/100 km2; Kawanishi and Sunquist 2004), Thailand (2.38–8.65 tigers/100 km2; Simcharoen et al. 2007), and Badhra, India (1.98–7.31 tigers/100 km2; Karanth and Nichols 2000). Tiger densities at HTR fall at the low end of the scale for tropical Asia. Tiger numbers at HTR are likely depressed due to intense hunting both of prey and of tigers, but populations might be recovered with appropriate management to reduce these threats (Madhusudan and Karanth 2002; Lynam et al. 2006a) and given the otherwise highly suitable grassland/ forest mosaic habitats. In the short-term, efforts to manage the tiger population of HTR will be concentrated in a 3,250 km2 core area that includes the three survey sites in this study. In this area, despite obvious signs of human presence, we detected tigers with camera-traps, encountered tiger signs, and obtained credible reports of tigers that indicate the species’ presence in all major watersheds (WCS, unpublished data). If it is assumed that tiger density varies due to local conditions (prey abundance, hunting, availability of permanent water, and habitat) and that tiger densities estimated in this study (0.21–2.18 tigers/100 km2; Table 3) are indicative of this variation, we estimate 7–71 tigers in this core area. These numbers represent the subpopulation of adult and subadult individuals because the lower age classes (cubs and juveniles), which make up 20– 25% of wild populations (Smith 1993), are not reliably detected using camera-traps (Karanth and Nichols 2002).

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In isolation a subpopulation of tigers of this size might have a relatively low probability of survival in the longterm (Reed et al. 2003; but see Pacheco 2004). However, HTR is part of a network of connected subpopulations across a conservation landscape spanning Myanmar, India, Nepal, and Bhutan (Sanderson et al. 2006). Taken together, these areas potentially support one of the largest contiguous tiger populations across the species’ global range. In future, it will be desirable to monitor trends in HTR’s tiger population. Camera-traps will be of use in this endeavour, but given short-staffing, the large size of the reserve, and the complexity of management issues needing urgent progress, indicators of tiger abundance that can be measured incidentally to management-oriented work would be extremely useful. Knowing the functional relationships among prey levels and tigers (O’Brien et al. 2003; Karanth et al. 2004), as well as having information on prey levels from line transect or reconnaissance surveys (Karanth and Nichols 2002), may help managers predict tiger occurrence/abundance in areas where camera-trap surveys are logistically difficult. Monitoring trends in tiger occurrence or surrogate indicators of tigers, such as prey levels, may facilitate assessments of the success of management interventions. However, obtaining information on prey densities via a line transect methods will be time consuming due to the needs for staff training, calibration of observation methods, and the establishment and maintenance of transects. It may also be possible to repeat capture–recapture sampling for estimating density at periodic intervals. Alternatively, occupancy surveys may provide a basis for monitoring tiger populations (MacKenzie and Nichols 2004). However, at very low densities, efforts to detect population trends may detract from action needed to save a species from extinction (Taylor and Gerrodette 1993). Therefore, efforts to monitor tiger and prey populations will be balanced with the needs for proactive law enforcement and protection measures (M. Maung and S. Htun, personal communication). Acknowledgments The field program was overseen by Khin Maung Zaw, Director of Nature and Wildlife Conservation Division, Myanmar Forest Department, Saw Tun Khaing, Wildlife Conservation Society (WCS). Eight staff of the Forest Department and two WCS staff members participated in the tiger survey: Saw Htoo Tha Po, Myint Maung, Zaw Naing Tun, Zaw Win Khaing, Nyunt Hlaing, Hla Naing, Khin Maung Htay, Tun Kyal, Aung Maung, and Maung Shwe. Soe Than and Win Naing provided logistical assistance to field teams. Local guides and porters and work elephants were hired to help locate survey areas and participate in tiger monitoring. We thank Tim O’Brien, Jim Nichols, Marcella Kelly, Andrew Noss, and Scott Silver for suggesting various statistical treatments for sparse data. The final analysis reflects a balance between varying viewpoints over how to deal with such data. Comments and suggestions by Will Duckworth, Tim O’Brien, and two anonymous reviewers helped improve the manuscript.

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