Muthamizh Selvan, Salvador Lyngdoh, Govindan Veeraswami Gopi * and Bilal Habib

DOI 10.1515/mammalia-2013-0084 Mammalia 2014; aop Short Note Muthamizh Selvan, Salvador Lyngdoh, Govindan Veeraswami Gopi * and Bilal Habib Density estimation of leopard cat Prionailurus bengalensis using capture recaptures sampling in lowland forest of Pakke Tiger Reserve, Arunachal Pradesh, India Abstract: In this study, we estimated leopard cat abundance and density using photographic capture-recapture methods. The leopard cat, Prionailurus bengalensis, is a common spread small cat in Asia, which is mainly nocturnal and solitary in nature. It occurs in across a range of habitat types. The study was conducted in Pakke Tiger Reserve (PTR) 26 54 27 16 N, 92 36 93 09 E), which lies in the eastern Himalayan state of Arunachal Pradesh (27 29 29 23 N 94 02 95 15 E) and covers an area of 862 km 2. Population status and abundance estimates were made through individual identification using camera trapping combined with mark-recapture methods. A total of 900 trap nights yielded seven leopard cat individuals, with 16 left flank and nine right flanks. The population abundance was 7 ± 1.0 and the density was 3.2 individuals/100 km 2. Estimated probability of capture, p-hat = 0.15. Program closure test indicates that closure assumption was not violated in the study. Our density estimates (3.21) seems to be low as the leopard cat shares resources with five other small cats in the area. Keywords: Arunachal Pradesh; camera trap; India; leopard cat; population estimation. *Corresponding author: Govindan Veeraswami Gopi, Wildlife Institute of India, Chandrabani, Dehradun 248 001, India, e-mail: gopigv@wii.gov.in Muthamizh Selvan, Salvador Lyngdoh and Bilal Habib: Wildlife Institute of India, Chandrabani, Dehradun, India The estimation of abundance and density for cryptic and secretive species is extremely difficult in the field ( Trolle and Kerry 2003 ). Recently, camera trapping associated with capture recapture studies has proved effective for elusive and nocturnal species ( Karanth 1995, Trolle and Kerry 2003 ). It has successfully been used for individually identifiable larger carnivores, such as tigers, leopards, hyenas, and jaguars but there are comparatively few studies that have been carried out on smaller carnivores. In this paper, leopard cat abundance and density was estimated using photographic capture-recapture. The leopard cat, Prionailurus bengalensis, is a widespread common small cat in Asia, across the range of habitats from tropical rainforest to temperate broadleaf and, marginally, coniferous forest, as well as shrub forest and successional grasslands ( Sanderson et al. 2008 ). This species is considered as least concern (LC) by IUCN and CITES listed in appendix I. A radio collard study in Thailand revealed that the home range size of the leopard cat was 12.4 km 2, with daily movements of 1298 m ( Grassman et al. 2005 ). The small Asian felids are poorly represented in field studies ( Grassman et al. 2005 ) and information on leopard cats was surprisingly absent in India. The general ecology of leopard cats ( Grassman 2000, Austin 2002 ) and their diet and movement patterns was studied ( Grassman et al. 2005 ) in Thailand. The main objective of this study was to estimate the abundance of leopard cats in a humandominated landscape where hunting is common among indigenous communities. This information will help in the future monitoring and conservation of this unnoticed species in the eastern Himalayan landscape. The study was conducted from 2010 to 2011 in Pakke Tiger Reserve (PTR) between the months of October and February ( Figure 1 ; 26 54 27 16 N, 92 36 93 09 E), which lies in the eastern Himalayan state of Arunachal Pradesh (27 29 29 23 N 94 02 95 15 E) and covers an area of 862 km 2 (Figure 1). Contiguous forest and perennial rivers surround the park. This tropical climate area has cooler weather in November to February. The vegetation of the park is classified as Assam valley tropical evergreen forest ( Champion and Seth 1968 ). The terrain is undulating with elevation ranges from 150 2000 m. This park is one among the best protected areas in the state

2 M. Selvan et al.: Leopard cat density estimation 92 40 E 92 50 E 93 0 E 27 10 N 0 20 40 27 0 N 27 10 N 27 0 N km 92 40 E 92 50 E 93 0 E Figure 1 Study area and camera trap locations. of Arunachal Pradesh. Apart from tigers, leopards and dholes, Himalayan black bears and clouded leopards also occur in the study area. More than 20 villages are located in the northern and southeastern boundary of the park. The people around the park belong to the indigenous Nyshi community, who are involved in hunting, fishing, and collection of non-timber forest products ( Datta et al. 2008 ). Population status and abundance estimates were made through individual identification using camera trapping with mark-recapture methods ( Karanth 1995, Carbone et al. 2001 ). Camera traps have been successfully used for estimating densities ( Karanth et al. 2004, Harihar et al. 2007, 2010 ). Sampling was done in part of the 160 km 2 of 300 km intensive study area (ISA). The study area was divided into 2 2 km grid, and each grid had at least one pair of Moultrie digital cameras (Figure 1). A total of 40 cameras were operated in 20 locations for 45 days in possible grids. The cameras were placed under wooden logs, and faced each other, to get both right and left flanks of the individuals. We maintained the inter camera distance 1.5 km and cameras were active 24 h a day and the camera delay time was 60 s. Each leopard cat photo record was examined for rosette patterns and pelagic patterns ( Figure 2 ). We assumed that the sampled population was geographically and demographically closed for conventional methods (Stanley and Burnham 1999). We defined three trap nights (a trap night = 24 h) as a sampling occasion and we considered each day photographs taken by a camera as independent photographs. A capture-recapture model with lowest AIC value was considered best for parameter estimates in the program MARK ( Burnham and Anderson 1998 ). To estimate the population density of the leopard cat program DENSITY 4.4 ( Efford 2011 ) was used and density ( ± SE)/100 km2 using 1/2MMDM and MMDM and maximum likelihood methods were estimated. Density was estimated by the population size (N) divided by the effective sampled area (A) (Karanth 1998, Harihar et al. 2007 ). A total of 900 trap nights of sampling efforts yielded seven individuals of leopard cat, with recordings of 16 left flanks and nine right flanks. Out of seven, three individuals were not recaptured, three individuals were recaptured more than once, and a single recapture took place for the

M. Selvan et al.: Leopard cat density estimation 3 Figure 2 Example of individual identification of leopard cat from a camera trap picture. remaining one. The selected Mo (null), which allows difference in capture probabilities between the captures, gave the best fit to the data set. The population size N-hat ± SE (95% confidence interval) was 7 ± 1.0 (7.0 2.0) and the density was 3.4 individuals/100 km 2 (Table 1 ). Program closure test indicates that closure assumption was not violated in the study ( Table 2 ). Mean distance moved by individual leopard cat was 3.5 ± 0.7 km. Model scores and different method for estimating leopard cat density is given in Tables 1 and 2. Our density estimates (3.2/100 km 2 ) seem to be low, however, the available recourses was shared by five other smaller cats in the area, which could be the reason for a low density of leopard cats. A study in Malaysia commercial forest revealed that density was higher in disturbed forest than managed forest ( Azlan et al. 2013 ) and it prefers the habitat with a higher prey catchability area than higher prey density ( Rajaratnam et al. 2007 ). Capture recapture statistics show acceptance of the Mo (null model) model and supporting rejection of the Mh model, due to lack of explanation and imprecision. The Mo model was selected as none of the other models showed meaningful differences with respect to time, behavior or heterogeneity (p = 0.1). The camera placement that was along Table 1 Density estimates for leopard cat using different methods in Pakke Tiger Reserve. Model Mt +1 n SE p-hat Method ETA Density/100 km 2 SE Mo 7 7 1.0 0.1 1/2MMDM 215.2 km 2 3.2 0.9 MMDM 405.7 km 2 1.7 0.6 MLSECR 2.9 0.2 Mt+1, number of individuals caught; n, abundance; SE, standard error; p-hat, probability of capture; ETA, effective trapping area.

4 M. Selvan et al.: Leopard cat density estimation Table 2 Model selection procedure, model scores from Program Mark and closure test for leopard cat from program Close Test. Closure test Model selection z p-value Mo Mh Mb Mbh Mt Mth Mtb Mtbh 7.35 0.51 1 0.84 0.34 0.6 0 0.36 0.32 0.66 the road yielded more captures than trails, streams, and the river. Individual identification of each leopard cat was possible when animals were captured approximately < 5 m away, and if animals were captured more than 5 m away they could not be identified with certainty, thus, we have excluded those photographs from the analysis. Conservation of large felids is a major focus of many wildlife programs. However, lesser cats have received limited academic, as well as conservation, attention. The current study establishes baseline information on leopard cat in the region. Similar studies have shown a low abundance, suggesting that good tree cover and small prey greatly influences the presence of the leopard cat in tropical regions (Bashir et al. 2013). In the present study area, a diverse assemblage sympatric species, such a marbled cat, jungle cat, golden cat, and fishing cat ( Lyngdoh et al. 2011, Gopi et al. 2012 ) have been reported to occur. Such habitats, thus, need to be preserved, as they are a refuge to a diverse family of lesser cats. Hence, in the long-term, conservation efforts and future monitoring programs based on similar methodology may be a good strategy to check their population status and adhere to timely management interventions if necessary. Acknowledgments: We thank Mr P. R. Sinha, Director of WII and Dr V. B. Mathur, Dean FWS of WII for providing the Institutional support. In particular, GVG would like to thank Drs. A.J.T. Johnsingh, S.K. Dutta, Bhaskar Acharya, Claudio Sillero-Zubiri for their support. 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