Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Density and occupancy of leopard cats across different forest types in Cambodia

Density and occupancy of leopard cats across different forest types in Cambodia The leopard cat (Prionailurus bengalensis) is the most common wild felid in Southeast Asia, yet little is known about the factors that affect their population density and occupancy in natural habitats. Although leopard cats are highly adaptable and reportedly can attain high densities in human-modified habitats, it is not clear which natural habitat is optimal for the spe- cies. Also, this felid has been preyed upon by large carnivores in Southeast Asia, yet the intra-guild effects of large carnivore presence on leopard cats are almost unknown. To shed light on these fundamental questions, we used data from camera trap surveys for felids to determine the leopard cat densities in three different forest types within Cambodia: continuous ever - green, mosaic dominated by evergreen (hereafter evergreen mosaic), and mosaic dominated by open dry deciduous forests (hereafter DDF mosaic). We also conducted occupancy analyses to evaluate the interactions of the leopard cats with three large carnivores: leopards (Panthera pardus), dholes (Cuon alpinus), and domestic dogs (Canis familiaris). The estimated density (individuals/100 km ± SE) was highest in the continuous evergreen (27.83 ± 7.68), followed by evergreen mosaic (22.06 ± 5.35) and DDF mosaic (13.53 ± 3.23). Densities in all three forest types were relatively high compared to previous studies. Domestic dogs were detected on all 3 sites, and leopards and dholes had sufficient records on only one site each. The occupancy probability of leopard cats was not affected by the presence or absence of any large carnivore, indicating that large carnivores and leopard cats occurred independently of each other. Our findings support the claim that leopard cats are habitat generalists, but we show that evergreen forest is the optimum natural habitat for this species in the region. The DDF mosaic appears to sustain lower densities of leopard cats, probably due to the harsh dry season and wildfires that led to reduced prey base, although this generalist felid was still able to occupy DDF in relatively moderate numbers. Overall, the adaptability of leopard cats to various forest types, and lack of negative interaction with large carnivores, helps to explain why this species is the most common and widespread felid in Southeast Asia. Keywords Cambodia · Co-occurrence · Dry deciduous forest · Evergreen forest · Prionailurus bengalensis · Spatial capture-recapture Communicated by: Krzysztof Schmidt * Chanratana Pin World Wild Fund for Nature Cambodia, House #54, Street chanratana.pin@gmail.com 352, Boeung Keng Kang I, Phnom Penh, Cambodia Victoria University of Wellington, Wellington, New Zealand Ministry of Environment, Morodok Techo Building (Lot 503), Tonle Bassac, Chamkarmorn, Phnom Penh, Cambodia Saïd Business School, University of Oxford, Park End Street, Oxford OX1 1HP, UK Wildlife Conservation Research Unit, The Recanati-Kaplan Centre, Department of Zoology, University of Oxford, Tubney House, Abingdon Road, Tubney OX13 5QL, Abingdon, UK Vol.:(0123456789) 1 3 288 Mammal Research (2022) 67:287–298 leopard cat density in natural habitats, and it is not clear Introduction which natural habitat is optimal for this species. Southeast Asia is dominated by evergreen and semi-ever- Southeast Asia is rich in biodiversity and has a high concen- green forests, although open dry deciduous forests (DDF) tration of endemic fauna and flora species that comprise 18% cover about 15–20% of Southeast Asia (Wohlfart et al. 2014). of the global endemic plant and animal species (Myers et al. Previous studies gave conflicting results about the effects of 2000; Sodhi et al. 2010). The biodiversity of Southeast Asia these forest types on leopard cat abundance. In northeastern has dramatically declined as a result of human-related activi- Thailand, leopard cats were found to be most abundant in ever- ties, including habitat destruction, over-hunting, pollution, and green forests, moderately abundant in degraded forests, and climate change (Sodhi et al. 2004; Sodhi and Brook 2006; Koh almost non-existent in DDF (Petersen et al. 2019). However, in and Sodhi 2010). Habitat loss and deforestation in Southeast eastern Cambodia, leopard cats were found to be habitat gen- Asia are among the highest in the world (Sodhi et al. 2010), and eralists that regularly used DDF (Rostro-García et al. 2021). forest cover continues to decline (Kim et al. 2015; Miettinen Evergreen forests would seemingly be better habitat for leopard et al. 2011), even inside protected areas (Heino et al. 2015). cats because this habitat has a higher number and biomass of Wild felids are among the most threatened groups of ter- small rodents compared to DDF (Walker and Rabinowitz 1992; restrial mammalian carnivores, with 25 of the 38 known spe- Petersen et al. 2019; Rostro-García et al. 2021). In contrast to cies listed as globally threatened (Macdonald et al. 2010; evergreen forests, DDF forests in Southeast Asia typically have Sunquist and Sunquist 2017). At least nine species of wild annual dry season fires which burn most of the grassy under - cats occur in mainland Southeast Asia, making it one of story (Baker and Bunyavejchewin 2009; McShea et al. 2011; the most felid-diverse regions in the world (Burnham et al. Pin et al. 2018) which can significantly decrease the seasonal 2012; Macdonald et al. 2012). The leopard cat (Prionailurus biomass of small mammals (Walker and Rabinowitz 1992). bengalensis) is the smallest felid (3–5 kg; Francis 2019) in However, there might be some benefits of DDF compared to Southeast Asia, and it is a generalist that occupies a broad evergreen forests for leopard cats, such as reduced numbers of range of habitats in both protected and non-protected areas predators such as leopards, which were previously shown to (Ross et al. 2015; Sunquist and Sunquist 2017). Leopard cats consume this small felid in eastern Cambodia (Rostro-García that occur on Indonesian and Philippine islands recently have et al. 2018). Comparing leopard cat densities between ever- been classified as a different species, the Sunda leopard cat green forests and DDF would help determine which forest type (P. javanensis; Kitchener et al. 2017), although it is similar is optimal for this species in Southeast Asia. in size and presumably has a similar ecology to mainland Leopard cats are preyed upon by larger carnivores, includ- leopard cats. The diet of both species of leopard cats consists ing leopards (Panthera pardus; Rostro-García et al. 2018) mostly of small (< 500 g) mammals, mainly Muridae, but and dholes (Cuon alpinus; Kamler et al. 2020b), but little also Sciuridae, and Tupaiidae (Rabinowitz 1990; Grassman is known about the negative impacts of large carnivores on 2000; Kamler et al. 2020a), and they occasionally feed on this small felid. Previous research gave conflicting results small carnivores (i.e., Mustelidae), lizards, birds, insects, because some studies found high spatial overlap between amphibians, and plants (Rajaratnam et al. 2007; Xiong et al. both leopard cat species and large felids (Sunarto et al. 2015; 2016; Sunquist and Sunquist 2017). Because leopard cats Kyaw et al. 2021), whereas another study found that leop- have not declined dramatically across their range despite ard cats avoided large felids (Vitekere et al. 2020); no stud- human-caused habitat changes, they are classified as Least ies have investigated the interactions of dholes and leopard Concern by the IUCN (Ross et al. 2015). In fact, densities cats. Also, domestic dogs (Canis familiaris) are sometimes of this small felid might be higher in human-modified land- abundant within protected areas of Southeast Asia, and they scape compared to natural landscapes. For example, densities can have severe negative impacts on wildlife (Hughes and of both leopard cat species were 2–21 individuals/100 km Macdonald 2013; Doherty et  al. 2017; Gompper 2021). across protected areas (Table 1). However, they can attain Therefore, domestic dogs probably also prey on leopard cats unusually high densities (89 individuals/100 km ) in human- and they might have negative impacts on their populations. modified habitats, such as palm tree plantations (Chua et al. Understanding the relationships between leopard cats and 2016), and they can prefer palm plantations over nearby large carnivores might help explain differences in their den- natural forest, reportedly because of the greater abundance sities in both natural and human-modified habitats. of small murid species in palm plantations (Rajaratnam We used camera trap data to determine leopard cat densities et al. 2007). Higher abundances of leopard cats in human- in three sites in Cambodia that contained different forest types: dominated areas also have been reported in India (Srivathsa continuous evergreen, evergreen mosaic, and DDF mosaic. We et  al. 2015), and high tolerance for degraded habitat was also conducted occupancy analyses to evaluate the interaction confirmed for the Sunda leopard cat in Borneo (Wearn et al. of leopard cats with three large carnivores: leopards, dholes, 2013). However, little is known about the factors that affect 1 3 Mammal Research (2022) 67:287–298 289 Table 1 Summary of leopard cat (Prionailurus bengalensis) and tially explicit capture-recapture (SCR) methods in South and South- Sunda leopard cat (P. javanensis; marked with *) densities (from east Asian countries. Ind, individual; MLH, maximum likelihood highest to lowest) determined from camera trap studies that used spa- method Site, country Density Ind./100 km 95% confidence interval SCR method Dominant habitat Reference Central Cardamom 27.83 ± 7.67 15.33–43.55 Bayesian Continuous evergreen This study National Park, Cambodia forest Phnom Prich Wildlife 22.06 ± 5.35 12.79–32.94 Bayesian Forest mosaic dominated This study Sanctuary, Cambodia by evergreen/semi-ever- green forest Sakaerat Biosphere 21.2 ± 5.3 11.5–27.2 MLH Evergreen/semi-evergreen (Petersen et al. 2019) Reserve, Thailand forest Sakaerat Biosphere 17.70 ± 3.90 11.50–27.20 MLH Reforested area and ever- (Petersen et al. 2019) Reserve, Thailand green/semi-evergreen forest Khangchendzonga Bio- 17.52 ± 5.52 8.80–26.80 Bayesian Temperate broadleaf forest (Bashir et al. 2013) sphere Reserve, India Segaliud Lokan Forest 16.5 ± 2.00 12.99–16.37 Bayesian Mixed dry deciduous (Mohamed et al. 2013) Reserve, Sabah, Malay- forest-evergreen forest sia* Srepok Wildlife Sanctuary, 13.53 ± 3.23 8.09–19.49 Bayesian Forest mosaic dominated This study Cambodia by dry deciduous forest Tang Kulap-Pinangah 12.40 ± 1.60 9.49–15.73 Bayesian Mixed dry deciduous (Mohamed et al. 2013) Forest Reserve, Sabah, forest-evergreen forest Malaysia* Bhadra Tiger Reserve, 10.45 ± 3.03 5.14–16.50 Bayesian Mixed dry deciduous (Srivathsa et al. 2015) India forest-evergreen forest Deramakot Forest Reserve, 9.60 ± 1.70 6.69–12.98 Bayesian Mixed dry deciduous (Mohamed et al. 2013) Sabah, Malaysia* forest-evergreen forest Sakaerat Biosphere 7.9 ± 2.7 4.1–15.0 MLH Reforested area (Petersen et al. 2019) Reserve, Thailand Biligiri Rangaswamy Tem- 4.48 ± 1.31 2.17–7.08 Bayesian Mixed dry deciduous (Srivathsa et al. 2015) ple Tiger Reserve, India forest-evergreen forest Nam Et—Phou Louey 1.50 ± 0.30 1.00–2.00 Bayesian Evergreen forests (Rasphone et al. 2021) National Protected Area, Laos and domestic dogs. Based on previous studies, we predicted Sanctuary (PPWS, 12° 46ʹ N, 106° 52ʹ E), and Srepok Wildlife that the density of this small felid would be highest in continu- Sanctuary (SWS, 12° 50′ N, 107° 50′ E; Fig. 1). The CCNP ous evergreen and lowest in DDF mosaic, owing to presumed (4013 km ) is dominated by evergreen and semi-evergreen for- differences in small rodent abundance (Walker and Rabinowitz ests in hilly terrain that forms part of the Cardamom Rainfor- 1992; Petersen et al. 2019; Rostro-García et al. 2021). We also est Landscape, situated in southwestern Cambodia; elevation predicted that all three large carnivores would have a negative ranges from 20 to 1540 m. The PPWS (2225 k m ) consists impact on leopard cat occupancy because of their potential of large patches of evergreen and semi-evergreen forests in predation on this species (Rostro-García et al. 2018; Kamler hilly terrain and ridge lines, interspersed with DDF habitat et al. 2020b). Our study will help determine the effects of for - on flat terrain; elevation ranges from 80 to 640 m. The SWS est types and large carnivores on the density and occupancy of (3729 km ) is dominated by DDF habitat with small patches leopard cats in relatively natural habitats. of evergreen and semi-evergreen forests in hilly terrain; eleva- tion ranges from 100 to 400 m. Both PPWS and SWS are part of the Cambodia’s Eastern Plains Landscape that forms the Study areas largest extant of lowland dry forest in Southeast Asia. Camera- trapping grids in all study sites were located in natural for- Camera trap surveys were conducted in the core zones of three ests, without villages, agricultural fields, plantations, or cattle protected areas in Cambodia: Central Cardamom National grazing, and these sites are considered potential areas for tiger Park (CCNP, 11° 56′ N, 103° 29′ E), Phnom Prich Wildlife reintroduction in Cambodia (Gray et al. 2020). 1 3 290 Mammal Research (2022) 67:287–298 Fig. 1 The camera-trapping grids and forest types within three protected areas in Cambodia: Central Cardamom National Park (CCNP), Phnom Prich Wildlife Sanctuary (PPWS), and Srepok Wildlife Sanctuary (SWS) the trail, and fastened to trees approx. 30–50 cm above the Methods ground, and approx. 2–3 m from the center of the trails. In CCNP and PPWS, the focal animal of the camera trap Camera‑trapping survey was clouded leopards (Neofelis nebulosa), and the mean spacing between camera traps was 479 m and 725 m, All camera trap surveys were conducted during the dry respectively. In SWS, the focal animal of the camera trap season (December to May). In CCNP, from December survey was leopard, and the mean spacing between camera 2013 to March 2014 cameras were placed in 81 locations traps was 2516 m (Rostro-García et al. 2018). within continuous evergreen forests in hilly terrain; this site was classified as continuous evergreen forest (Fig.  1; Density estimation Table 2). In PPWS, from December 2012 to March 2013 camera traps were placed in 77 locations within evergreen Leopard cats were independently identified by three of the and semi-evergreen forests in hilly terrain that were sur- authors based on unique body-markings, and any discrep- rounded by DDF habitat; this site was classified as ever - ancies were jointly reviewed to reach a final agreement on green mosaic (Fig. 1; Table 2). In SWS, from December identification (Rostro-García et al.  2018).We separated the 2015 to February 2016 cameras were placed in 46 loca- pictures into left and right flanks and discarded those pictures tions primarily within DDF habitat (87% of locations) that could not be identified. We also identified the sex of indi- in relatively flat terrain; this site was classified as DDF viduals when there were clear photographs of the rear end; an mosaic (Fig. 1; Table 2). Camera traps were placed along individual was defined as a male if its scrotum was visible, dirt roads, animal trails, abandoned logging roads, dry riv- or as female if no scrotum was visible or if it was accompa- erbeds, and ridge lines in the core zones of all sites. In all nied by young or appeared to be pregnant (Webb et al. 2020 sites, paired camera traps were placed on opposite sides of 1 3 Mammal Research (2022) 67:287–298 291 Table 2 Summary of the camera trap surveys conducted for leopard nights and the number of sampling periods for SCR analyses are cats in Cambodia. Effective survey area (state space) is defined as shown in parentheses. For number of identified individuals, the total the suitable habitat that was set to five times the movement param- number of independent records is given in parentheses. M, male; F, eter buffer around the camera trap polygon. The total number of trap female; Unk, unknown Study site Habitat type Effective survey No. of No. of trap days No. of identified individuals area (state space) camera trap (total events); sex of indi- (km ) stations viduals Central Cardamom National Continuous evergreen forest 163 81 7244 (94) 16 (56); M = 4, F = 7, Park Unk = 5 Phnom Prich Wildlife Mosaic dominated by ever- 260 77 5313 (78) 19 (50); M = 5, F = 8, Sanctuary green forest Unk = 6 Srepok Wildlife Sanctuary Mosaic dominated by dry 754 46 2935 (78) 31 (79); M = 12, F = 13, deciduous forest Unk = 6 ). On each site, we included in the analysis adult individuals burn-in and 10,000 during adaptation per chain, and thinned in which both flanks were identified (Fig.  S1 ), as well as by 10, which yielded 27,000 total posterior samples. The those in which only one side was identified (we used the side model convergence was assessed based on the Gelman- that had the most individuals) to get a minimum number of Rubin statistic (Rhat): the potential scale reduction factor individuals per site. We used 1-day occasions as a sampling and MCMC diagnostic trace plots (Gelman et al. 2013; Pen- period yielding a total of 78–94 occasions per study site jor et al. 2018). To assess model fit, we calculated Freeman- (Table 2 ) and constructed a capture history that consisted of Tukey discrepancy between real and simulated data and all identified mature individuals, camera trap station number, calculated Bayesian p value where values between 0.05 and occasion ID, and sex (Royle et al. 2014 ). 0.95 indicate adequate fit. Densities were estimated using spatially explicit capture- recapture (SCR) models under the Bayesian framework Occupancy modeling (Royle et al. 2014; Meredith 2020a). The R packages secr (Efford 2020), rgdal (Bivand et al. 2016), raster (Bivand We conducted single-season two-species occupancy analyses et al. 2016), and makeJAGSmask (Meredith 2020b) were (Waddle et al. 2010) to investigate the interaction between used for importing and formatting capture histories and cre- the leopard cat and three large carnivores: dholes, leopards, ating the state space. We ran two models: (1) a spatial model and domestic dogs (Table 3), which we considered domi- with elevation as a covariate assuming that their densities nant. To avoid zero inflation in the data (i.e., too many non- would vary across the elevational gradient, and (2) capture detections) and increase detection frequency, multiple days probability (p) and scale parameter (σ) as a function of sex were pooled (Bischof et al. 2014; Penjor et al. 2019). We (Sollmann et al. 2011; Webb et al. 2020). The capture prob- pooled the detection/non-detection data into 7-day occasions ability and the movement scale parameter for both sexes yielding a total of 12–14 sampling occasions per study site. were estimated for each site. The elevation covariate was The hierarchical single-season two-species occupancy standardized by subtracting the values by its mean, and analysis allowed us to estimate the occupancy and detection dividing by the standard deviation. probability of both dominant (i.e., large carnivores) and subor- An effective survey area (state space) was created using dinate species (i.e., leopard cats) simultaneously (Waddle et al. QGIS 3.14 (QGIS Delopment Team 2020) by setting a buffer 2010). We adopted the previous code (Meredith 2020a, c) to (4 times the movement scale parameter σ) around each cam- model one-way interaction between a dominant species and era-trap grid (Efford 2004). Unsuitable habitats, such as a subordinate species, where occupancy of subordinate spe- permanent rivers, were excluded from the effective survey cies is affected by the presence/absence of the dominant spe- area (Royle et al. 2014; Webb et al. 2020). We set data aug- cies, but not vice versa. We fitted the model using a Bayesian mentation to 5 times the number of total identified individu- approach implemented with JAGS (Plummer 2003) via pro- als (Efford and Fewster 2013; Royle et al. 2014). We report gram R (R Core Team 2020) using R packages jagsUI (Kellner posterior mean density with standard deviations and the 95% et al. 2018) and wiqid (Meredith 2020c). We used uninforma- posterior highest density intervals (Penjor et al. 2018). tive uniform priors for all the parameters (i.e., dbeta[1, 1]). We fitted the model using a Bayesian approach imple- We ran three chains of Marko Chain Monte Carlo (MCMC) mented with JAGS (Plummer 2003) via program R (R Core with 500,000 iterations, discarded 10,000 during initial burn- Team 2020) by using R package jagsUI (Kellner et al. 2018). in and 10,000 during adaptation per chain, and thinned by 10, We ran three chains of Marko Chain Monte Carlo (MCMC) which yielded 147,000 total posterior samples. The model con- of 100,000 iterations each, discarded 10,000 during initial vergence was based on the Gelman-Rubin statistic for each 1 3 292 Mammal Research (2022) 67:287–298 Table 3 Number of detections of leopard cat and large carnivores, and the number of sampling occasions (7-day periods) from three camera trap surveys in Cambodia. Asterisks indicate that the sample size was too low to be included in the analysis Study site Leopard cat Domestic dog Leopard Dhole No. of sampling occasions Central Cardamom NP 47 23 - 34 14 Phnom Prich WS 47 19 10* - 12 Srepok WS 56 120 21 3* 12 WS, wildlife sanctuary; NP, national park parameter, where models were successfully converged with The Bayesian p values suggested that models including the Rhat value < 1.1 (Gelman et al. 2013; Bischof et al. 2014; elevation as a spatial covariate and sex as a covariate fit Penjor et al. 2019). We report posterior means with standard our data better than the null model (Fig. S4). The models deviations and 95% highest density credible intervals (Pen- indicated adequate fit with p values ranging from 0.30 to jor et al. 2018, 2019). For each parameter, n.eff was a crude 0.50 (Fig. S4). The SCR spatial covariate model tested the measure of effective sample size. We checked if 0 falls in the effect of elevation on leopard cat density in each study site parameter’s 95% Bayesian Credible Interval (CI), and consid- and showed that elevation did not have a significant effect ered that it has a strong support if the 95% BIC did not overlap on density in any site because all the credible intervals over- 0. For each model, the species interaction factor (SIF) was lapped zero (Table S1). calculated between the leopard cats and the dominant species (SIF < 1 suggests species avoidance, SIF > 1 suggests species Occupancy modeling co-occur more frequently, and SIF = 1 suggests species occur independently; MacKenzie et al. 2004). Domestic dogs were detected in sufficient numbers for analysis in all sites (Table 3). However, leopards were only recorded in sufficient numbers for analysis in SWS, whereas Results dholes were only recorded in sufficient numbers for analysis in CCNP (Table 3). Leopard cat density The estimated occupancy probability of dholes was 0.58 ± 0.11 (mean ± SD) in CCNP (Table 5; Fig. S5). The We identified a total of 66 individual leopard cats from 15,492 occupancy of leopard cats was higher for the sites where trap days across all three sites (Table 2). Photos from all sites dholes were present (0.74 ± 0.13) compared to the sites could be identified to an individual, except for 1 photo from where dholes were absent (0.16 ± 0.12; Table 5), and SIF CCNP, 1 photo from SWS, and 2 photos from PPWS that for the two species was 1.50. The detection probability of were discarded because of blurriness. The estimated popula- both species was relatively low (< 0.1; Table 5; Fig. S5). tion sizes (N ± SD) in the effective area were 45.36 ± 12.51 in The estimated occupancy probability of leopards was CCNP, 56.93 ± 13.81 in PPWS, and 102.01 ± 24.37 in SWS. 0.46 ± 0.14 in SWS (Table 5; Fig. S6). The occupancy of The model with capture probability and the movement scale leopard cats was similar for the sites where leopards were parameter as a function of sex covariate estimated the den- present (0.84 ± 11) compared to the sites where leopards sity (no. individuals/100 km ± SD) as 27.82 ± 7.67 in CCNP, were absent (0.74 ± 0.15; Table 5), and the SIF for the two 22.06 ± 5.35 in PPWS, and 13 ± 3.23 in SWS (Fig. S2). We species was 1.06. The detection probabilities of both species also estimated the expected number of individuals/100 km at were similar (Table 5; Fig. S6). each activity center within the study areas (Fig. S3). In SWS The estimated occupancy probability of domestic and PPWS, the capture probability of males was lower com- dogs was 0.17 ± 0.05 in CCNP, 0.70 ± 0.18 in PPWS, and pared to that of females (Table 4). Overall, the capture prob- 0.79 ± 0.06 in SWS (Figs. S7, S8, and S9). In CCNP, the ability was highest for females in SWS, and highest for males occupancy of leopard cats was about twice as high for the in CCNP (Table 4). In SWS and PPWS, the movement scale sites where dogs were present (0.78 ± 0.14) compared to parameters (sigma) for males were 1–2 times higher than for the sites where dogs were absent (0.41 ± 0.09; Table  5), females (Table 3). In contrast, in CCNP the movement scale and the SIF was 1.67. In PPWS, the probability of occu- parameter (sigma) for females was higher than for males pancy of leopard cats was similar for the sites where dogs (Table 4). The sex ratio of females to males in the population were present (0.65 ± 0.16) compared to the sites where within the effective area was 1.2:1 in CCNP, 1.9:1 in PPWS, dogs were absent (0.63 ± 0.24; Table 5), and the SIF was and 1.7:1 in SWS (Table 4; Fig. S2). 0.98. Similarly, in SWS the probability of occupancy of 1 3 Mammal Research (2022) 67:287–298 293 Table 4 The SCR sex covariate Mean SD Median l95 u95 Rhat MCEpc model estimated density (D), capture probability for male Central Cardamom National Park (p[1]) and female (p[2]) leopard   D 27.83 7.68 26.38 15.34 43.56 - - cats, the movement parameter   p[1] 0.08 0.15 0.03 0.002 0.39 1.00 3.06 for male (sigma[1]) and female   p[2] 0.01 0.003 0.01 0.004 0.02 1.00 0.71 (sigma[2]) leopard cats, the population size (N) in the state   sigma[1] 0.32 0.12 0.30 0.13 0.56 1.00 1.63 space, and the sex ratio in the   sigma[2] 0.67 0.10 0.66 0.48 0.88 1.00 0.73 population (pi)   N 45.36 12.51 43 24 70 1.00 1.12   pi 0.55 0.152 0.554 0.26 0.836 1.001 1.148 Phnom Prich Wildlife Sanctuary   D 22.06 5.35 21.32 12.79 32.94 - -   p[1] 0.01 0.004 0.01 0.001 0.01 1.00 0.77   p[2] 0.01 0.005 0.01 0.003 0.02 1.00 0.78   sigma[1] 1.11 0.35 1.04 0.57 1.82 1.00 1.14   sigma[2] 0.69 0.13 0.67 0.47 0.95 1.00 0.78   N 56.93 13.81 55 32 84 1.01 1.03   pi 0.66 0.14 0.67 0.38 0.90 1.00 0.94 Srepok Wildlife Sanctuary   D 13.53 3.23 13.39 8.09 19.50 - -   p[1] 0.02 0.02 0.02 0.01 0.04 1.00 4.68   p[2] 0.11 0.07 0.09 0.04 0.22 1.00 1.71   sigma[1] 1.39 0.24 1.36 0.95 1.89 1.00 1.14   sigma[2] 0.52 0.13 0.50 0.30 0.78 1.00 1.66   N 102.02 24.37 10 61 147 1.00 1.66   pi 0.63 0.12 0.64 0.39 0.84 1.00 1.45 SD, standard deviation; l95 and u95, the limits of a 95% Highest Density Credible Interval; Rhat, the potential scale reduction factor (at convergence, Rhat = 1); MCEpc, the Monte Carlo standard error as a percentage of the posterior SD leopard cats was similar for the sites where dogs were pre- Similarly, Rabinowitz (1990) found that leopard cats used sent (0.83 ± 0.09) compared to the sites where leopards were DDF less often than other habitats in western Thailand, absent (0.72 ± 0.16; Table 5), and SIF was 1.03. In CCNP, owing to lower numbers of their preferred prey. Our results the detection probabilities of domestic dogs and leopard cats also suggest DDF is a suboptimal habitat for leopard cats, were similar (Table 5; Fig. S7). In PPWS, the detection prob- and we speculate that this was because of the harsh con- ability of leopard cats was about twice as high as domestic ditions within the DDF during the dry season, and the dogs (Table 5; Fig. S8), whereas in SWS the detection prob- effects this has on the prey availability. Frequent annual ability of domestic dogs was about twice as high as leopard dry season fires, both natural and human-caused (e.g., to cats (Table 5; Fig. S9). enhance regrowth in the rainy season), occur in DDF after the dipterocarp trees loss their leaves, burning most of the grassy understory (McShea et al. 2011). The DDF is well Discussion adapted to dry season fires, which seem to have occurred in this habitat since the late Pleistocene (McShea et al. The leopard cat density was highest in CCNP and lowest in 2011), in contrast to evergreen forests which typically do SWS, which supported our prediction that evergreen for- not experience dry season fires. Previous research showed ests support higher densities of leopard cats compared to that evergreen forests and nearby DDF forests in South- DDF. However, our results should be viewed with caution east Asia have similar biomass of small rodents during the because the 95% credible intervals of the densities over- rainy season, but after the dry season fires the biomass of lapped among all three sites. Nonetheless, our results were small rodents becomes 5 times higher in evergreen forests similar to Peterson et al. (2019), who found that leopard compared to DDF (Walker and Rabinowitz 1992). Over- cat density in northeastern Thailand was higher in the ever- all, the biomass of small rodents decreases about 76% in green and semi-evergreen forest compared to DDF, likely DDF forests from the rainy season until after the dry sea- because the latter is a suboptimal habitat for this species. son fires (Walker and Rabinowitz 1992). Because leopard 1 3 294 Mammal Research (2022) 67:287–298 Table 5 Estimated occupancy Mean SD Median l95 u95 Rhat MCEpc probability (psiA) for large carnivores (leopards, dholes, CCNP: dholes vs leopard cats and domestic dogs), occupancy   pA 0.05 0.01 0.05 0.03 0.08 1 0.29 probability for leopard cats   pB 0.09 0.02 0.08 0.05 0.12 1 0.29 when large carnivores were   psiA 0.58 0.11 0.57 0.37 0.79 1 0.31 absent (psiB[1]), occupancy probability for leopard cats   psiB[1] 0.16 0.12 0.14 0 0.39 1 0.30 when large carnivores were   psiB[2] 0.73 0.13 0.74 0.51 1 1 0.334 present (psiB[2]), detection   Na 47.26 7.64 46 33 62 1 0.331 probability of large carnivores   Nb 39.99 5.47 39 30 50 1.02 0.30 (pA), and the detection probability of leopard cats (pB).   Nboth 34.88 6.08 35 23 46 1 0.30 The “Na” is the number of sites SWS: leopards vs leopard cats used by dhole/leopard/domestic   pA 0.11 0.03 0.11 0.05 0.18 1 0.34 dog, “Nb” is the number of   pB 0.15 0.022 0.15 0.11 0.195 1 0.29 sites used by leopard cat, and “Nboth” is the number of sites   psiA 0.46 0.14 0.44 0.22 0.77 1 0.40 used by both species   psiB[1] 0.74 0.15 0.76 0.48 1 1 0.32   psiB[2] 0.84 0.11 0.85 0.62 1 1 0.31   Na 21.35 5.98 20 13 34 1 0.40   Nb 37.71 3.10 38 32 43 1 0.30   Nboth 18.58 5.54 17 10 30 1 0.40 CCNP: domestic dog vs leopard cats   pA 0.13 0.03 0.13 0.07 0.2 1 0.25   pB 0.09 0.02 0.09 0.06 0.12 1 0.28   psiA 0.17 0.05 0.17 0.08 0.27 1 0.27   psiB[1] 0.41 0.09 0.41 0.24 0.59 1 0.27   psiB[2] 0.78 0.14 0.80 0.51 1 1 0.25   Na 13.36 2.28 13 11 18 1 0.27   Nb 38.79 5.08 38 29 48 0.97 0.28   Nboth 10.99 2.44 11 7 15 1 0.27 PPWS: domestic dog vs leopard cats   pA 0.04 0.01 0.03 0.02 0.06 1 0.43   pB 0.09 0.02 0.09 0.05 0.12 1 0.31   psiA 0.70 0.18 0.71 0.40 1 1 0.53   psiB[1] 0.63 0.25 0.66 0.14 1 1 0.37   psiB[2] 0.65 0.16 0.65 0.36 0.97 1 0.39   Na 54.52 13.48 55 32 77 0.98 0.53   Nb 51.47 7.92 51 36 66 0.98 0.35   Nboth 36.198 12.954 36 13 60 1 0.528 SWS: domestic dog vs leopard cats   pA 0.33 0.03 0.33 0.28 0.39 1 0.26   pB 0.15 0.02 0.15 0.11 0.19 1 0.27   psiA 0.79 0.06 0.79 0.67 0.90 1 0.25   psiB[1] 0.72 0.16 0.74 0.43 1 1 0.27   psiB[2] 0.83 0.09 0.84 0.67 1 1 0.27   Na 36.78 0.88 37 36 38 1 0.25   Nb 38.40 3.21 38 33 44 1 0.28   Nboth 31.29 2.97 31 25 36 1 0.27 SD, standard deviation; l95 and u95, the limits of a 95% Highest Density Credible Interval; Rhat, the potential scale reduction factor (at convergence, Rhat = 1); MCEpc, the Monte Carlo standard error as a percentage of the posterior SD 1 3 Mammal Research (2022) 67:287–298 295 cats feed mostly on small rodents < 500 g (Kamler et al. density and similar sex ratio in CCNP; thus, males might 2020a; Rostro-García et al. 2021), the higher prey avail- have had smaller home ranges because they did not need to ability throughout the year in evergreen forests likely sup- travel as far to encompass several female home ranges. ports higher densities of this small felid compared to DDF. The two-species occupancy analyses suggested that Although leopard cats can attain unusually high densities domestic dogs did not have a negative impact on leopard in human-modified habitats, owing to superabundant small cat presence on any of the sites, which did not support our rodent numbers (Chua et al. 2016), their densities in natural prediction. Nonetheless, leopard cats likely avoided domes- habitats typically range from 2 to 18 individuals/100 km tic dogs temporally, because the former are almost strictly (Table 1). The only previous study to report a density > 18 nocturnal (Lynam et al. 2013; Gray et al. 2014; Kamler et al. individuals/km was Petersen et al. (2019), who found a den- 2020a; Rostro-García et al. 2021) whereas domestic dogs are sity of 21.2 individuals/100 km in semi-evergreen forests mostly diurnal in accordance with human activity (Kamler in northeastern Thailand. Therefore, our study found two of et al. 2012; Bianchi et al. 2020). We observed that domestic the highest densities of leopard cats ever reported in natu- dogs were brought into all three sites by local people for the ral habitat. When compared to previous studies, continuous purposes of illegally hunting wildlife, including red muntjac evergreen or large patches of evergreen forests appear to (Muntiacus vaginalis), wild pig (Sus scrofa), and reptiles. be an optimal natural habitat for leopard cats in South and Thus, domestic dogs likely negatively impact numerous Southeast Asia (Table 1), probably due to relatively high other species inside the protected areas, especially in SWS numbers of small rodents in these forests. Although we where dogs were detected at high frequencies. Domestic found their density in DDF mosaic to be half of that found dogs pose a threat to nearly 200 globally threatened species in a continuous evergreen forest, the density in DDF mosaic worldwide, and they have contributed to the extinctions of was still moderate compared to that reported in previous 11 vertebrates via depredations, disease transmission, com- studies across various habitats (Table 1). We conclude that petition, and hybridization (Doherty et al. 2017). Given the DDF appears to be a suboptimal habitat for leopard cats high rates of dog detections on our study sites, we recom- compared to evergreen forests; however, DDF can still sus- mend further research on domestic dogs and their impacts tain a modest population of this species, which is similar to on wildlife within protected areas in Cambodia (Hughes and that reported by Rostro-García et al. (2021). Macdonald 2013; Hughes et al. 2017). We also recommend The elevation did not significantly affect the density of that the management of all three protected areas makes a leopard cats in any of the study sites, probably because there greater effort to enforce the laws and prevent domestic dogs was not much variation in elevation across the study sites. and humans from illegally entering the core zones because Leopard cat densities might be affected by other factors not such efforts are likely to have a positive impact on the overall included in our study, such as local small rodent abundance, biodiversity in the protected areas. microhabitats, and possibly anthropogenic disturbances, The occupancy probability of leopard cats was similar including roads. We recommend that future studies investi- when leopards were present or absent in SWS, which did not gate other factors that might influence densities of leopard support our prediction. This suggests that leopard cats were cats in natural habitat, to gain a more complete understand- able to coexist with leopards in SWS. Although a previous ing of the factors that influence their densities. study in SWS found that leopards consumed leopard cats, In SWS and PPWS, the capture probability of male the latter only accounted for < 1% of the biomass consumed leopard cats was lower than that of females, which likely by leopards, and overall the leopard density was extremely corresponds to differences in movement patterns between low (1 leopard/100 km ; Rostro-García et al. 2018). This the sexes. Males moved twice as far as females from their suggests that leopards rarely prey on leopard cats, at least not activity center, which likely resulted in low capture prob- enough for this small felid to spatially avoid leopards, and ability of males compared to females, especially if camera that the low leopard density may have affected their interac- spacing was far relative to leopard cat home range sizes. tion with leopard cats. Regardless, leopard and leopard cats Larger home ranges and greater distanced traveled by males have vastly different diets (Rostro-García et al.  2018, 2021; compared to females are common in solitary felid species Kamler et al. 2020a); thus, they do not compete for the same (Kamler and Gipson 2000; Goodrich et al. 2010; Simchar- food resources. Both felids were nocturnal in SWS (Rostro- oen et al. 2014; Sarkar et al. 2016), and result from males García et al. 2018); thus; leopard cats did not appear to avoid establishing home ranges to encompass several female home leopards temporally. We conclude that due to large differ - ranges, whereas females establish their home ranges based ences in body size and diets, leopard cats do not spatially or on food resources and cover for their young (Sandell 1989). temporally avoid leopards, despite the occasional predation However, in CCNP males appeared to have higher capture on this small felid by leopards, at least in areas were leopard probability, and had shorter distance movements compared densities are low such as SWS. to females. This result might have been because of the higher 1 3 296 Mammal Research (2022) 67:287–298 In CCNP, the occupancy probability of leopard cats was 2021), indicating this small felid might not be preyed upon similar when dholes were present or absent, which did not frequently by these mesocarnivores. Regardless, we recom- support our prediction. This indicates that leopard cats were mend that future studies examine in more detail if meso- not spatially avoiding dholes, despite that dholes sometimes carnivores affect the density or occupancy of leopard cats. prey upon this small felid (Kamler et al. 2020b). Similar to Additionally, we recommend that future researches consider the leopard, the diet of dholes contained < 1% biomass con- multi-scale analyses when investigating the interactions of sumed of leopard cats, indicating they are rarely preyed upon leopard cats and both large and mesocarnivores. Only by by dholes. Also, dholes and leopard cats have vastly different studying leopard cats within different carnivore communities diets (Kamler et al. 2020a, b), indicating that they do not com- can we gain a more complete understanding of coexistence pete for the same food resources. However, dholes are diurnal mechanisms, and the important factors that affect the density in Southeast Asia (Kamler et al. 2012), so leopard cats might and occupancy of Southeast Asia’s smallest felid. avoid dholes temporally. We conclude that due to large differ - Supplementary Information The online version contains supplemen- ences in body size and diets, leopard cats do not spatially avoid tary material available at https://doi. or g/10. 1007/ s13364- 022- 00634-6 . dholes, despite the occasional predation on this small felid by dholes, although leopard cats might avoid dholes temporally. Acknowledgements These research projects were conducted under the Overall, the adaptability of leopard cats to various forest permission granted by the General Department of Administration for types, and lack of strong negative impacts caused by large Nature Conservation and Protection, Ministry of Environment (MoE), and Forestry Administration, Ministry of Agriculture, Forestry and carnivores, helps to explain why this species is the most Fishery (MAFF). We thank the field teams who helped collect the data, common and widespread felid in Southeast Asia. Nonethe- including MoE rangers, WWF Cambodia staff, and local porters. We less, our camera-trapping surveys focused on larger felid also thank WWF Cambodia for coordination, logistical, and fieldwork species had different spacing between camera stations, support in SWS and PPWS, and Mike Meredith for providing statisti- cal advice. and occurred in different habitats, all of which could have affected our results. However, we feel that potential differ - Funding The camera trap studies in PPWS and CCNP were funded ences in leopard cat detectability due to different method- by the Robertson Foundation through Wildlife Conservation Research ologies were minimal given the relatively large number of Unit (WildCRU), Department of Zoology, University of Oxford, with support provided by WWF Cambodia, FFI Cambodia, and the Minis- detections at each site. Also, home ranges of leopard cats 2 2 try of Environment. The camera trap studies in SWS were funded by in Thailand averaged 12 km for 14 males and 14 km for Panthera with support provided by WWF Cambodia and the Forestry 6 females (Grassman et al. 2005); thus, even the relatively Administration. large camera spacing of about 2.5 km in SWS theoretically would have missed few, if any, leopard cats. Another caveat Data availability Data are available upon request. is that our investigation was limited to broad scale analysis of habitat and occupancy. Thus, leopard cats might have Declarations avoided large carnivores using mechanisms at finer scales. Ethics approval Our research was carried out following the legal For example, time-to-encounter analysis might have detected standards of Cambodia’s Natural Protected Area law, the Ministry leopard cat avoidance of large carnivores. Additionally, leop- of Environment, and Forestry Law, Ministry of Agriculture, Forestry ard cats might have avoided large carnivores at the level of and Fishery, and the guidelines provided by the University of Oxford, the home range, feeding site, or resting site (Rostro-Garía Biomedical Sciences, Animal Welfare and Ethical Review Body (AWERB). et al. 2015). Furthermore, in our study sites the small- and medium-sized felids and canids, such as clouded leopards, Consent for publication The manuscript has been approved by all co- Asian golden cats (Catopuma temminckii), jungle cats (Felis authors. chaus), marbled cats (Pardofelis marmorata), and golden jackals (Canis aureus), were absent or occurred in such low Conflict of interest The authors declare no competing interests. numbers that they could not be included in the analyses. Leopard cats might compete more with small and meso- Open Access This article is licensed under a Creative Commons Attri- felids, which are known to feed more on small rodents com- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long pared to large carnivores (Kamler et al. 2020a). Nonethe- as you give appropriate credit to the original author(s) and the source, less, previous studies showed that the occupancy of leopard provide a link to the Creative Commons licence, and indicate if changes cats was not affected by the presence of Asian golden cats were made. The images or other third party material in this article are (Kamler et al. 2020a) or jungle cats (Rostro-García et al. included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in 2021), indicating leopard cats might not spatially avoid the article's Creative Commons licence and your intended use is not meso-felids. Furthermore, leopard cats were not found in permitted by statutory regulation or exceeds the permitted use, you will the scats of Asian golden cats (Kamler et al. 2020a), jungle need to obtain permission directly from the copyright holder. To view a cats (Rostro-García et al. 2021), and jackals (Kamler et al. copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . 1 3 Mammal Research (2022) 67:287–298 297 Hughes J, MacDonald DW, Boitani L (2017) Roaming free in the References rural idyll: dogs and their connections with wildlife. In: Serpell J (ed) The domestic dog: its evolution, behaviour and interac- Baker PJ, Bunyavejchewin S (2009) Fire behavior and r fi e ee ff cts across tions with people. Cambridge University Press, Cambridge, pp the forest landscape of continental Southeast Asia. In: Cochrane 369–384 MA (ed) Tropical fire ecology. Springer, Chichester, pp 311–334 Kamler JF, Gipson PS (2000) Home range, habitat selection, and sur- Bashir T, Bhattacharya T, Poudyal K, Sathyakumar S, Qureshi Q vival of bobcats, Lynx rufus, in a prairie ecosystem in Kansas. (2013) Estimating leopard cat Prionailurus bengalensis densi- Can Field-Naturalist 114:388–394 ties using photographic captures and recaptures. Wildl Biol Kamler JF, Johnson A, Vongkhamheng C, Bousa A (2012) The diet, 19:462–472 prey selection, and activity of dholes (Cuon alpinus) in northern Bianchi RdC, Olifiers N, Riski LL, Gouvea JA, Cesário CS, Fornitano Laos. J Mammal 93:627–633 L, Zanirato GL, Yan de Oliveira M, de Morais KD, Ribeiro RL, Kamler JF, Inthapanya X, Rasphone A, Bousa A, Vongkhamheng C, D’Andrea PS (2020) Dog activity in protected areas: behavioral Johnson A, Macdonald DW (2020a) Diet, prey selection, and effects on mesocarnivores and the impacts of a top predator. Eur activity of Asian golden cats and leopard cats in northern Laos. J Wildl Res 66:36 J Mammal 101:1267–1278 Bischof R, Ali H, Kabir M, Hameed S, Nawaz MA (2014) Being the Kamler JF, Thatdokkham K, Rostro‐García S, Bousa A, Caragiulo underdog: an elusive small carnivore uses space with prey and A, Crouthers R, In V, Pay C, Pin C, Prum S, Vongkhamheng time without enemies. J Zool 293:40–48 C (2020b) Diet and prey selection of dholes in evergreen Bivand R, Keitt T, Rowlingson B, Pebesma E, Sumner M, Hijmans and deciduous forests of Southeast Asia. J Wildl Manag R, Rouault E, Warmerdam F, Ooms J, Rundel C (2016) Rgdal: 84:1396–1405 bindings for the geospatial data abstraction library. R package Kamler JF, Minge C, Rostro-García S, Gharajehdaghipour T, Burnham D, Hinks AE, Macdonald DW (2012) Life and dinner under Crouthers R, In V, Pay C, Pin C, Sovanna P, Macdonald the shared umbrella: patterns in felid and primate communities. DW (2021) Home range, habitat selection, density, and diet of Folia Primatol 83:148–170 golden jackals in the Eastern Plains Landscape, Cambodia. J Chua MA, Sivasothi N, Meier R (2016) Population density, spatiotem- Mammal 102:636–650 poral use and diet of the leopard cat (Prionailurus bengalensis) Kellner K, Kellner MK, SystemRequirements J (2018) Package ‘jag- in a human-modified succession forest landscape of Singapore. sUI’ A wrapper around ‘rjags’ to streamline ‘JAGS’ analyses Mammal Res 61:99–108 Kim DH, Sexton JO, Townshend JR (2015) Accelerated deforestation Doherty TS, Dickman CR, Glen AS, Newsome TM, Nimmo DG, in the humid tropics from the 1990s to the 2000s. Geophys Res Ritchie EG, Vanak AT, Wirsing AJ (2017) The global impacts of Lett 42:3495–3501 domestic dogs on threatened vertebrates. Biol Cons 210:56–59 Kitchener AC, Breitenmoser-Würsten C, Eizirik E, Gentry A, Werde- Efford M (2004) Density estimation in live-trapping studies. Oikos lin L, Wilting A, Yamaguchi N, Abramov AV, Christiansen P, 106:598–610 Driscoll C, Duckworth JW (2017) A revised taxonomy of the Efford M (2020) secr: spatially explicit capture-recapture models. 4.3.1 Felidae. The final report of the Cat Classification Task Force Efford MG, Fewster RM (2013) Estimating population size by spatially of the IUCN/SSC Cat Specialist Group. Cat News S11:1–80 explicit capture-recapture. Oikos 122:918–928 Koh LP, Sodhi NS (2010) Conserving Southeast Asia’s imperiled Francis C (2019) Field guide to the mammals of South-east Asia, 2nd biodiversity: scientific, management, and policy challenges. edn. Bloomsbury Publishing, New York Biodivers Conserv 19:913–917 Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB Kyaw PP, Macdonald DW, Penjor U, Htun S, Naing H, Burnham D, (2013) Bayesian data analysis. CRC Press, New York Kaszta Ż, Cushman SA (2021) Investigating carnivore guild Gompper ME (2021) Adding nuance to our understanding of dog– structures: spatial and temporal relationships amongst threat- wildlife interactions and the need for management. Integr Comp ened felids in Myanmar. ISPRS Int J Geo Inf 10:808 Biol 61:93–102 Lynam AJ, Jenks KE, Tantipisanuh N, Chutipong W, Ngoprasert Goodrich JM, Miquelle DG, Smirnov EN, Kerley LL, Quigley HB, D, Gale GA, Steinmetz R, Sukmasuang R, Bhumpakphan N, Hornocker MG (2010) Spatial structure of Amur (Siberian) tigers Grassman Jr LI, Cutter P (2013) Terrestrial activity patterns of (Panthera tigris altaica) on Sikhote-Alin Biosphere Zapovednik, wild cats from camera-trapping. Raffles Bull Zool 61:407–415 Russia. J Mammal 91:737–748 Macdonald DW, Loveridge AJ, Nowell K (2010) Dramatis personae: Grassman LI (2000) Movements and diet of the leopard cat Prionai- an introduction to the wild felids. In: Macdonad DW, Loveridge lurus bengalensis in a seasonal evergreen forest in south-central AJ (eds) Biology and conservation of wild felids. Oxford Uni- Thailand. Acta Theriol 45:421–426 versity Press, Oxford, pp 3–58 Grassman LI, Tewes ME, Silvy NJ, Kreetiyutanout K (2005) Spatial Macdonald DW, Burnham D, Hinks AE, Wrangham R (2012) A organization and diet of the leopard cat (Prionailurus bengalensis) problem shared is a problem reduced: seeking efficiency in the in north-central Thailand. J Zool 266:45–54 conservation of felids and primates. Folia Primatol 83:171–215 Gray T, Channa P, Chanrattanak P, Sovanna P (2014) The status of MacKenzie DI, Bailey LL, Nichols JD (2004) Investigating species jungle cat and sympatric small cats in Cambodia’s Eastern Plains. co-occurrence patterns when species are detected imperfectly. Cat News 8:19–23 J Anim Ecol 73:546–555 Gray TN, Grainger MJ, Grosu R (2020) Conservation decision-making McShea WJ, Davies SJ, Bhumpakphan N (2011) The ecology and under uncertainty: identifying when to reintroduce tiger Panthera conservation of seasonally dry forests in Asia. Smithsonian tigris to Cambodia. Conserv Sci Pract 2:e187 Institution Scholarly Press, Washington, D.C. Heino M, Kummu M, Makkonen M, Mulligan M, Verburg PH, Jalava Meredith M (2020a) Bayes with JAGS – a tutorial for wildlife M, Räsänen TA (2015) Forest loss in protected areas and intact researchers. https:// bcss. or g. m y/ tut/ ba y es- wit h- jags-a- tut or forest landscapes: a global analysis. PLoS ONE 10:e0138918 ial- f or - wildl ife- r esea r c hers/ occup ancy - model ling/ tw o- speci Hughes J, Macdonald DW (2013) A review of the interactions es- occup ancy- models/. Accessed Sept 2020 between free-roaming domestic dogs and wildlife. Biol Con- Meredith M (2020b) makeJAGSmask. Habitat matrices for use with serv 157:341–351 SECR analysis in JAGS or BUGS. https:// mmere dith. net/R/. Accessed Sept 2020 1 3 298 Mammal Research (2022) 67:287–298 Meredith M (2020c) wiqid: quick and dirty estimates for wildlife Sandell M (1989) The mating tactics and spacing patterns of solitary populations. R package, version 0.3.0. https:// CRAN.R- proje carnivores. In: Gittleman JL (ed) Carnivore behavior, ecology, ct. org/ packa ge= wiqid . Accessed Sept 2020 and evolution, vol 1. Cornell University Press, Ithaca, pp 164–182 Miettinen J, Shi C, Liew SC (2011) Deforestation rates in insu- Sarkar MS, Ramesh K, Johnson JA, Sen S, Nigam P, Gupta SK, Murthy lar Southeast Asia between 2000 and 2010. Glob Change Biol RS, Saha GK (2016) Movement and home range characteristics 17:2261–2270 of reintroduced tiger (Panthera tigris) population in Panna Tiger Mohamed A, Sollmann R, Bernard H, Ambu LN, Lagan P, Mannan S, Reserve, central India. Eur J Wildl Res 62:537–547 Hofer H, Wilting A (2013) Density and habitat use of the leopard Simcharoen A, Savini T, Gale GA, Simcharoen S, Duangchantrasiri cat (Prionailurus bengalensis) in three commercial forest reserves S, Pakpien S, Smith JL (2014) Female tiger Panthera tigris home in Sabah, Malaysian Borneo. J Mammal 94:82–89 range size and prey abundance: important metrics for manage- Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GA, Kent J ment. Oryx 48:370–377 (2000) Biodiversity hotspots for conservation priorities. Nature Sodhi NS, Brook BW (2006) Southeast Asian biodiversity in crisis. 403:853 Cambridge University Press, Cambridge Penjor U, Macdonald DW, Wangchuk S, Tandin T, Tan CKW (2018) Sodhi NS, Koh LP, Brook BW, Ng PK (2004) Southeast Asian bio- Identifying important conservation areas for the clouded leopard diversity: an impending disaster. Trends Ecol Evol 19:654–660 Neofelis nebulosa in a mountainous landscape: inference from Sodhi NS, Posa MRC, Lee TM, Bickford D, Koh LP, Brook BW (2010) spatial modeling techniques. Ecol Evol 8:4278–4291 The state and conservation of Southeast Asian biodiversity. Bio- Penjor U, Tan CKW, Wangdi S, Macdonald DW (2019) Understanding divers Conserv 19:317–328 the environmental and anthropogenic correlates of tiger presence Sollmann R, Furtado MM, Gardner B, Hofer H, Jácomo AT, Tôrres in a montane conservation landscape. Biol Conserv 238:108196 NM, Silveira L (2011) Improving density estimates for elusive Petersen WJ, Savini T, Steinmetz R, Ngoprasert D (2019) Estimating carnivores: accounting for sex-specific detection and movements leopard cat Prionailurus bengalensis Kerr, 1792 (Carnivora: Feli- using spatial capture–recapture models for jaguars in central Bra- dae) density in a degraded tropical forest fragment in northeastern zil. Biol Conserv 144:1017–1024 Thailand. J Threat Taxa 11:13448–13458 Srivathsa A, Parameshwaran R, Sharma S, Karanth KU (2015) Estimat- Pin C, Ngoprasert D, Gray TN, Savini T, Crouthers R, Gale GA (2018) ing population sizes of leopard cats in the Western Ghats using Utilization of waterholes by globally threatened species in decidu- camera surveys. J Mammal 96:742–750 ous dipterocarp forest of the Eastern Plains Landscape of Cambo- Sunarto S, Kelly MJ, Parakkasi K, Hutajulu MB (2015) Cat coexistence dia. Oryx 54:572–582 in central Sumatra: ecological characteristics, spatial and temporal Plummer M (2003) JAGS: a program for analysis of Bayesian graphi- overlap, and implications for management. J Zool 296:104–115 cal models using Gibbs sampling. DSC 2003 Working Papers, Sunquist M, Sunquist F (2017) Wild cats of the world. University of Vienna, Austria Chicago Press, Chicago QGIS Delopment Team (2020) QGIS geographic information system. Vitekere K, Wang J, Karanja H, Consolée KT, Jiang G, Hua Y (2020) Open Source Geospatial Foundation Project Dynamic in species estimates of carnivores (leopard cat, red fox, R Core Team (2020) R: A Language and Environment for Statistical and north Chinese leopard): a multi-year assessment of occupancy Computing. R Foundation for Statistical Computing, Vienna, Aus- and coexistence in the Tieqiaoshan Nature Reserve, Shanxi Prov- tria. https:// www.R- proje ct. org/. Accessed Sept 2020 ince, China. Animals 10:1333 Rabinowitz A (1990) Notes on the behavior and movements of leopard Waddle JH, Dorazio RM, Walls SC, Rice KG, Beauchamp J, Schuman cats, Felis bengalensis, in a dry tropical forest mosaic in Thailand. MJ, Mazzotti FJ (2010) A new parameterization for estimating Biotropica:397–403 co-occurrence of interacting species. Ecol Appl 20:1467–1475 Rajaratnam R, Sunquist M, Rajaratnam L, Ambu L (2007) Diet and Walker S, Rabinowitz A (1992) The small-mammal community of a habitat selection of the leopard cat (Prionailurus bengalensis dry-tropical forest in central Thailand. J Trop Ecol:57–71 borneoensis) in an agricultural landscape in Sabah, Malaysian Wearn OR, Rowcliffe JM, Carbone C, Bernard H, Ewers RM (2013) Borneo. J Trop Ecol 23:209–217 Assessing the status of wild felids in a highly-disturbed commer- Rasphone A, Kamler JF, Tobler M, Macdonald DW (2021) Den- cial forest reserve in Borneo and the implications for camera trap sity trends of wild felids in northern Laos. Biodivers Conserv survey design. PLoS One 8:e77598 30:1881–1897 Webb EL, Choo YR, Kudavidanage EP, Amarasinghe TR, Bandara Ross J, Brodie J, Cheyne S, Hearn A, Izawa M, Loken B, Lynam A, UG, Wanninayaka WA, Ravindrakumar P, Nimalrathna TS, Liang McCarthy J, Mukherjee S, Phan C, Rasphone A, Wilting A (2015) SH, Chua MA (2020) Leopard activity patterns in a small mon- Prionailurus bengalensis. The IUCN Red List of Threatened Spe- tane protected area highlight the need for integrated, collaborative cies 2015: e.T18146A50661611. https:// doi. org/ 10. 2305/ IUCN. landscape conservation. Glob Ecol Conserv 23:e01182 UK. 2015-4. RL T S. T1814 6A506 61611. en. Downloaded on 12 Wohlfart C, Wegmann M, Leimgruber P (2014) Mapping threatened June 2020 dry deciduous dipterocarp forest in South-east Asia for conserva- Rostro-García S, Kamler JF, Hunter LTB (2015) To kill, stay or flee: tion management. Trop Conserv Sci 7:597–613 the effects of lions and landscape factors on habitat and kill site Xiong M, Shao X, Long Y, Bu H, Zhang D, Wang D, Li S, Wang R, selection of cheetahs in South Africa. PLoS ONE 10:e0117743 Yao M (2016) Molecular analysis of vertebrates and plants in scats Rostro-García S et al (2018) An adaptable but threatened big cat: den- of leopard cats (Prionailurus bengalensis) in southwest China. J sity, diet and prey selection of the Indochinese leopard (Panthera Mammal 97:1054–1064 pardus delacouri) in eastern Cambodia. R Soc Open Sci 5:171187 Rostro‐García S, Kamler JF, Minge C, Caragiulo A, Crouthers R, Publisher's note Springer Nature remains neutral with regard to Groenenberg M, Gray TN, In V, Pin C, Sovanna P, Kéry M (2021) jurisdictional claims in published maps and institutional affiliations. Small cats in big trouble? Diet, activity, habitat use, and occu- pancy of jungle cats and leopard cats in threatened dry deciduous forests, Cambodia. Ecol Evol 11:4205–4217 Royle JA, Chandler RB, Sollmann R, Gardner B (2014) Spatial cap- ture-recapture. Academic Press, Boston 1 3 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mammal Research Springer Journals

Density and occupancy of leopard cats across different forest types in Cambodia

Download PDF
12 pages

Loading next page...
 
/lp/springer-journals/density-and-occupancy-of-leopard-cats-across-different-forest-types-in-UhpCmsH1yR

References (74)

Publisher
Springer Journals
Copyright
Copyright © The Author(s) 2022
ISSN
2199-2401
eISSN
2199-241X
DOI
10.1007/s13364-022-00634-6
Publisher site
See Article on Publisher Site

Abstract

The leopard cat (Prionailurus bengalensis) is the most common wild felid in Southeast Asia, yet little is known about the factors that affect their population density and occupancy in natural habitats. Although leopard cats are highly adaptable and reportedly can attain high densities in human-modified habitats, it is not clear which natural habitat is optimal for the spe- cies. Also, this felid has been preyed upon by large carnivores in Southeast Asia, yet the intra-guild effects of large carnivore presence on leopard cats are almost unknown. To shed light on these fundamental questions, we used data from camera trap surveys for felids to determine the leopard cat densities in three different forest types within Cambodia: continuous ever - green, mosaic dominated by evergreen (hereafter evergreen mosaic), and mosaic dominated by open dry deciduous forests (hereafter DDF mosaic). We also conducted occupancy analyses to evaluate the interactions of the leopard cats with three large carnivores: leopards (Panthera pardus), dholes (Cuon alpinus), and domestic dogs (Canis familiaris). The estimated density (individuals/100 km ± SE) was highest in the continuous evergreen (27.83 ± 7.68), followed by evergreen mosaic (22.06 ± 5.35) and DDF mosaic (13.53 ± 3.23). Densities in all three forest types were relatively high compared to previous studies. Domestic dogs were detected on all 3 sites, and leopards and dholes had sufficient records on only one site each. The occupancy probability of leopard cats was not affected by the presence or absence of any large carnivore, indicating that large carnivores and leopard cats occurred independently of each other. Our findings support the claim that leopard cats are habitat generalists, but we show that evergreen forest is the optimum natural habitat for this species in the region. The DDF mosaic appears to sustain lower densities of leopard cats, probably due to the harsh dry season and wildfires that led to reduced prey base, although this generalist felid was still able to occupy DDF in relatively moderate numbers. Overall, the adaptability of leopard cats to various forest types, and lack of negative interaction with large carnivores, helps to explain why this species is the most common and widespread felid in Southeast Asia. Keywords Cambodia · Co-occurrence · Dry deciduous forest · Evergreen forest · Prionailurus bengalensis · Spatial capture-recapture Communicated by: Krzysztof Schmidt * Chanratana Pin World Wild Fund for Nature Cambodia, House #54, Street chanratana.pin@gmail.com 352, Boeung Keng Kang I, Phnom Penh, Cambodia Victoria University of Wellington, Wellington, New Zealand Ministry of Environment, Morodok Techo Building (Lot 503), Tonle Bassac, Chamkarmorn, Phnom Penh, Cambodia Saïd Business School, University of Oxford, Park End Street, Oxford OX1 1HP, UK Wildlife Conservation Research Unit, The Recanati-Kaplan Centre, Department of Zoology, University of Oxford, Tubney House, Abingdon Road, Tubney OX13 5QL, Abingdon, UK Vol.:(0123456789) 1 3 288 Mammal Research (2022) 67:287–298 leopard cat density in natural habitats, and it is not clear Introduction which natural habitat is optimal for this species. Southeast Asia is dominated by evergreen and semi-ever- Southeast Asia is rich in biodiversity and has a high concen- green forests, although open dry deciduous forests (DDF) tration of endemic fauna and flora species that comprise 18% cover about 15–20% of Southeast Asia (Wohlfart et al. 2014). of the global endemic plant and animal species (Myers et al. Previous studies gave conflicting results about the effects of 2000; Sodhi et al. 2010). The biodiversity of Southeast Asia these forest types on leopard cat abundance. In northeastern has dramatically declined as a result of human-related activi- Thailand, leopard cats were found to be most abundant in ever- ties, including habitat destruction, over-hunting, pollution, and green forests, moderately abundant in degraded forests, and climate change (Sodhi et al. 2004; Sodhi and Brook 2006; Koh almost non-existent in DDF (Petersen et al. 2019). However, in and Sodhi 2010). Habitat loss and deforestation in Southeast eastern Cambodia, leopard cats were found to be habitat gen- Asia are among the highest in the world (Sodhi et al. 2010), and eralists that regularly used DDF (Rostro-García et al. 2021). forest cover continues to decline (Kim et al. 2015; Miettinen Evergreen forests would seemingly be better habitat for leopard et al. 2011), even inside protected areas (Heino et al. 2015). cats because this habitat has a higher number and biomass of Wild felids are among the most threatened groups of ter- small rodents compared to DDF (Walker and Rabinowitz 1992; restrial mammalian carnivores, with 25 of the 38 known spe- Petersen et al. 2019; Rostro-García et al. 2021). In contrast to cies listed as globally threatened (Macdonald et al. 2010; evergreen forests, DDF forests in Southeast Asia typically have Sunquist and Sunquist 2017). At least nine species of wild annual dry season fires which burn most of the grassy under - cats occur in mainland Southeast Asia, making it one of story (Baker and Bunyavejchewin 2009; McShea et al. 2011; the most felid-diverse regions in the world (Burnham et al. Pin et al. 2018) which can significantly decrease the seasonal 2012; Macdonald et al. 2012). The leopard cat (Prionailurus biomass of small mammals (Walker and Rabinowitz 1992). bengalensis) is the smallest felid (3–5 kg; Francis 2019) in However, there might be some benefits of DDF compared to Southeast Asia, and it is a generalist that occupies a broad evergreen forests for leopard cats, such as reduced numbers of range of habitats in both protected and non-protected areas predators such as leopards, which were previously shown to (Ross et al. 2015; Sunquist and Sunquist 2017). Leopard cats consume this small felid in eastern Cambodia (Rostro-García that occur on Indonesian and Philippine islands recently have et al. 2018). Comparing leopard cat densities between ever- been classified as a different species, the Sunda leopard cat green forests and DDF would help determine which forest type (P. javanensis; Kitchener et al. 2017), although it is similar is optimal for this species in Southeast Asia. in size and presumably has a similar ecology to mainland Leopard cats are preyed upon by larger carnivores, includ- leopard cats. The diet of both species of leopard cats consists ing leopards (Panthera pardus; Rostro-García et al. 2018) mostly of small (< 500 g) mammals, mainly Muridae, but and dholes (Cuon alpinus; Kamler et al. 2020b), but little also Sciuridae, and Tupaiidae (Rabinowitz 1990; Grassman is known about the negative impacts of large carnivores on 2000; Kamler et al. 2020a), and they occasionally feed on this small felid. Previous research gave conflicting results small carnivores (i.e., Mustelidae), lizards, birds, insects, because some studies found high spatial overlap between amphibians, and plants (Rajaratnam et al. 2007; Xiong et al. both leopard cat species and large felids (Sunarto et al. 2015; 2016; Sunquist and Sunquist 2017). Because leopard cats Kyaw et al. 2021), whereas another study found that leop- have not declined dramatically across their range despite ard cats avoided large felids (Vitekere et al. 2020); no stud- human-caused habitat changes, they are classified as Least ies have investigated the interactions of dholes and leopard Concern by the IUCN (Ross et al. 2015). In fact, densities cats. Also, domestic dogs (Canis familiaris) are sometimes of this small felid might be higher in human-modified land- abundant within protected areas of Southeast Asia, and they scape compared to natural landscapes. For example, densities can have severe negative impacts on wildlife (Hughes and of both leopard cat species were 2–21 individuals/100 km Macdonald 2013; Doherty et  al. 2017; Gompper 2021). across protected areas (Table 1). However, they can attain Therefore, domestic dogs probably also prey on leopard cats unusually high densities (89 individuals/100 km ) in human- and they might have negative impacts on their populations. modified habitats, such as palm tree plantations (Chua et al. Understanding the relationships between leopard cats and 2016), and they can prefer palm plantations over nearby large carnivores might help explain differences in their den- natural forest, reportedly because of the greater abundance sities in both natural and human-modified habitats. of small murid species in palm plantations (Rajaratnam We used camera trap data to determine leopard cat densities et al. 2007). Higher abundances of leopard cats in human- in three sites in Cambodia that contained different forest types: dominated areas also have been reported in India (Srivathsa continuous evergreen, evergreen mosaic, and DDF mosaic. We et  al. 2015), and high tolerance for degraded habitat was also conducted occupancy analyses to evaluate the interaction confirmed for the Sunda leopard cat in Borneo (Wearn et al. of leopard cats with three large carnivores: leopards, dholes, 2013). However, little is known about the factors that affect 1 3 Mammal Research (2022) 67:287–298 289 Table 1 Summary of leopard cat (Prionailurus bengalensis) and tially explicit capture-recapture (SCR) methods in South and South- Sunda leopard cat (P. javanensis; marked with *) densities (from east Asian countries. Ind, individual; MLH, maximum likelihood highest to lowest) determined from camera trap studies that used spa- method Site, country Density Ind./100 km 95% confidence interval SCR method Dominant habitat Reference Central Cardamom 27.83 ± 7.67 15.33–43.55 Bayesian Continuous evergreen This study National Park, Cambodia forest Phnom Prich Wildlife 22.06 ± 5.35 12.79–32.94 Bayesian Forest mosaic dominated This study Sanctuary, Cambodia by evergreen/semi-ever- green forest Sakaerat Biosphere 21.2 ± 5.3 11.5–27.2 MLH Evergreen/semi-evergreen (Petersen et al. 2019) Reserve, Thailand forest Sakaerat Biosphere 17.70 ± 3.90 11.50–27.20 MLH Reforested area and ever- (Petersen et al. 2019) Reserve, Thailand green/semi-evergreen forest Khangchendzonga Bio- 17.52 ± 5.52 8.80–26.80 Bayesian Temperate broadleaf forest (Bashir et al. 2013) sphere Reserve, India Segaliud Lokan Forest 16.5 ± 2.00 12.99–16.37 Bayesian Mixed dry deciduous (Mohamed et al. 2013) Reserve, Sabah, Malay- forest-evergreen forest sia* Srepok Wildlife Sanctuary, 13.53 ± 3.23 8.09–19.49 Bayesian Forest mosaic dominated This study Cambodia by dry deciduous forest Tang Kulap-Pinangah 12.40 ± 1.60 9.49–15.73 Bayesian Mixed dry deciduous (Mohamed et al. 2013) Forest Reserve, Sabah, forest-evergreen forest Malaysia* Bhadra Tiger Reserve, 10.45 ± 3.03 5.14–16.50 Bayesian Mixed dry deciduous (Srivathsa et al. 2015) India forest-evergreen forest Deramakot Forest Reserve, 9.60 ± 1.70 6.69–12.98 Bayesian Mixed dry deciduous (Mohamed et al. 2013) Sabah, Malaysia* forest-evergreen forest Sakaerat Biosphere 7.9 ± 2.7 4.1–15.0 MLH Reforested area (Petersen et al. 2019) Reserve, Thailand Biligiri Rangaswamy Tem- 4.48 ± 1.31 2.17–7.08 Bayesian Mixed dry deciduous (Srivathsa et al. 2015) ple Tiger Reserve, India forest-evergreen forest Nam Et—Phou Louey 1.50 ± 0.30 1.00–2.00 Bayesian Evergreen forests (Rasphone et al. 2021) National Protected Area, Laos and domestic dogs. Based on previous studies, we predicted Sanctuary (PPWS, 12° 46ʹ N, 106° 52ʹ E), and Srepok Wildlife that the density of this small felid would be highest in continu- Sanctuary (SWS, 12° 50′ N, 107° 50′ E; Fig. 1). The CCNP ous evergreen and lowest in DDF mosaic, owing to presumed (4013 km ) is dominated by evergreen and semi-evergreen for- differences in small rodent abundance (Walker and Rabinowitz ests in hilly terrain that forms part of the Cardamom Rainfor- 1992; Petersen et al. 2019; Rostro-García et al. 2021). We also est Landscape, situated in southwestern Cambodia; elevation predicted that all three large carnivores would have a negative ranges from 20 to 1540 m. The PPWS (2225 k m ) consists impact on leopard cat occupancy because of their potential of large patches of evergreen and semi-evergreen forests in predation on this species (Rostro-García et al. 2018; Kamler hilly terrain and ridge lines, interspersed with DDF habitat et al. 2020b). Our study will help determine the effects of for - on flat terrain; elevation ranges from 80 to 640 m. The SWS est types and large carnivores on the density and occupancy of (3729 km ) is dominated by DDF habitat with small patches leopard cats in relatively natural habitats. of evergreen and semi-evergreen forests in hilly terrain; eleva- tion ranges from 100 to 400 m. Both PPWS and SWS are part of the Cambodia’s Eastern Plains Landscape that forms the Study areas largest extant of lowland dry forest in Southeast Asia. Camera- trapping grids in all study sites were located in natural for- Camera trap surveys were conducted in the core zones of three ests, without villages, agricultural fields, plantations, or cattle protected areas in Cambodia: Central Cardamom National grazing, and these sites are considered potential areas for tiger Park (CCNP, 11° 56′ N, 103° 29′ E), Phnom Prich Wildlife reintroduction in Cambodia (Gray et al. 2020). 1 3 290 Mammal Research (2022) 67:287–298 Fig. 1 The camera-trapping grids and forest types within three protected areas in Cambodia: Central Cardamom National Park (CCNP), Phnom Prich Wildlife Sanctuary (PPWS), and Srepok Wildlife Sanctuary (SWS) the trail, and fastened to trees approx. 30–50 cm above the Methods ground, and approx. 2–3 m from the center of the trails. In CCNP and PPWS, the focal animal of the camera trap Camera‑trapping survey was clouded leopards (Neofelis nebulosa), and the mean spacing between camera traps was 479 m and 725 m, All camera trap surveys were conducted during the dry respectively. In SWS, the focal animal of the camera trap season (December to May). In CCNP, from December survey was leopard, and the mean spacing between camera 2013 to March 2014 cameras were placed in 81 locations traps was 2516 m (Rostro-García et al. 2018). within continuous evergreen forests in hilly terrain; this site was classified as continuous evergreen forest (Fig.  1; Density estimation Table 2). In PPWS, from December 2012 to March 2013 camera traps were placed in 77 locations within evergreen Leopard cats were independently identified by three of the and semi-evergreen forests in hilly terrain that were sur- authors based on unique body-markings, and any discrep- rounded by DDF habitat; this site was classified as ever - ancies were jointly reviewed to reach a final agreement on green mosaic (Fig. 1; Table 2). In SWS, from December identification (Rostro-García et al.  2018).We separated the 2015 to February 2016 cameras were placed in 46 loca- pictures into left and right flanks and discarded those pictures tions primarily within DDF habitat (87% of locations) that could not be identified. We also identified the sex of indi- in relatively flat terrain; this site was classified as DDF viduals when there were clear photographs of the rear end; an mosaic (Fig. 1; Table 2). Camera traps were placed along individual was defined as a male if its scrotum was visible, dirt roads, animal trails, abandoned logging roads, dry riv- or as female if no scrotum was visible or if it was accompa- erbeds, and ridge lines in the core zones of all sites. In all nied by young or appeared to be pregnant (Webb et al. 2020 sites, paired camera traps were placed on opposite sides of 1 3 Mammal Research (2022) 67:287–298 291 Table 2 Summary of the camera trap surveys conducted for leopard nights and the number of sampling periods for SCR analyses are cats in Cambodia. Effective survey area (state space) is defined as shown in parentheses. For number of identified individuals, the total the suitable habitat that was set to five times the movement param- number of independent records is given in parentheses. M, male; F, eter buffer around the camera trap polygon. The total number of trap female; Unk, unknown Study site Habitat type Effective survey No. of No. of trap days No. of identified individuals area (state space) camera trap (total events); sex of indi- (km ) stations viduals Central Cardamom National Continuous evergreen forest 163 81 7244 (94) 16 (56); M = 4, F = 7, Park Unk = 5 Phnom Prich Wildlife Mosaic dominated by ever- 260 77 5313 (78) 19 (50); M = 5, F = 8, Sanctuary green forest Unk = 6 Srepok Wildlife Sanctuary Mosaic dominated by dry 754 46 2935 (78) 31 (79); M = 12, F = 13, deciduous forest Unk = 6 ). On each site, we included in the analysis adult individuals burn-in and 10,000 during adaptation per chain, and thinned in which both flanks were identified (Fig.  S1 ), as well as by 10, which yielded 27,000 total posterior samples. The those in which only one side was identified (we used the side model convergence was assessed based on the Gelman- that had the most individuals) to get a minimum number of Rubin statistic (Rhat): the potential scale reduction factor individuals per site. We used 1-day occasions as a sampling and MCMC diagnostic trace plots (Gelman et al. 2013; Pen- period yielding a total of 78–94 occasions per study site jor et al. 2018). To assess model fit, we calculated Freeman- (Table 2 ) and constructed a capture history that consisted of Tukey discrepancy between real and simulated data and all identified mature individuals, camera trap station number, calculated Bayesian p value where values between 0.05 and occasion ID, and sex (Royle et al. 2014 ). 0.95 indicate adequate fit. Densities were estimated using spatially explicit capture- recapture (SCR) models under the Bayesian framework Occupancy modeling (Royle et al. 2014; Meredith 2020a). The R packages secr (Efford 2020), rgdal (Bivand et al. 2016), raster (Bivand We conducted single-season two-species occupancy analyses et al. 2016), and makeJAGSmask (Meredith 2020b) were (Waddle et al. 2010) to investigate the interaction between used for importing and formatting capture histories and cre- the leopard cat and three large carnivores: dholes, leopards, ating the state space. We ran two models: (1) a spatial model and domestic dogs (Table 3), which we considered domi- with elevation as a covariate assuming that their densities nant. To avoid zero inflation in the data (i.e., too many non- would vary across the elevational gradient, and (2) capture detections) and increase detection frequency, multiple days probability (p) and scale parameter (σ) as a function of sex were pooled (Bischof et al. 2014; Penjor et al. 2019). We (Sollmann et al. 2011; Webb et al. 2020). The capture prob- pooled the detection/non-detection data into 7-day occasions ability and the movement scale parameter for both sexes yielding a total of 12–14 sampling occasions per study site. were estimated for each site. The elevation covariate was The hierarchical single-season two-species occupancy standardized by subtracting the values by its mean, and analysis allowed us to estimate the occupancy and detection dividing by the standard deviation. probability of both dominant (i.e., large carnivores) and subor- An effective survey area (state space) was created using dinate species (i.e., leopard cats) simultaneously (Waddle et al. QGIS 3.14 (QGIS Delopment Team 2020) by setting a buffer 2010). We adopted the previous code (Meredith 2020a, c) to (4 times the movement scale parameter σ) around each cam- model one-way interaction between a dominant species and era-trap grid (Efford 2004). Unsuitable habitats, such as a subordinate species, where occupancy of subordinate spe- permanent rivers, were excluded from the effective survey cies is affected by the presence/absence of the dominant spe- area (Royle et al. 2014; Webb et al. 2020). We set data aug- cies, but not vice versa. We fitted the model using a Bayesian mentation to 5 times the number of total identified individu- approach implemented with JAGS (Plummer 2003) via pro- als (Efford and Fewster 2013; Royle et al. 2014). We report gram R (R Core Team 2020) using R packages jagsUI (Kellner posterior mean density with standard deviations and the 95% et al. 2018) and wiqid (Meredith 2020c). We used uninforma- posterior highest density intervals (Penjor et al. 2018). tive uniform priors for all the parameters (i.e., dbeta[1, 1]). We fitted the model using a Bayesian approach imple- We ran three chains of Marko Chain Monte Carlo (MCMC) mented with JAGS (Plummer 2003) via program R (R Core with 500,000 iterations, discarded 10,000 during initial burn- Team 2020) by using R package jagsUI (Kellner et al. 2018). in and 10,000 during adaptation per chain, and thinned by 10, We ran three chains of Marko Chain Monte Carlo (MCMC) which yielded 147,000 total posterior samples. The model con- of 100,000 iterations each, discarded 10,000 during initial vergence was based on the Gelman-Rubin statistic for each 1 3 292 Mammal Research (2022) 67:287–298 Table 3 Number of detections of leopard cat and large carnivores, and the number of sampling occasions (7-day periods) from three camera trap surveys in Cambodia. Asterisks indicate that the sample size was too low to be included in the analysis Study site Leopard cat Domestic dog Leopard Dhole No. of sampling occasions Central Cardamom NP 47 23 - 34 14 Phnom Prich WS 47 19 10* - 12 Srepok WS 56 120 21 3* 12 WS, wildlife sanctuary; NP, national park parameter, where models were successfully converged with The Bayesian p values suggested that models including the Rhat value < 1.1 (Gelman et al. 2013; Bischof et al. 2014; elevation as a spatial covariate and sex as a covariate fit Penjor et al. 2019). We report posterior means with standard our data better than the null model (Fig. S4). The models deviations and 95% highest density credible intervals (Pen- indicated adequate fit with p values ranging from 0.30 to jor et al. 2018, 2019). For each parameter, n.eff was a crude 0.50 (Fig. S4). The SCR spatial covariate model tested the measure of effective sample size. We checked if 0 falls in the effect of elevation on leopard cat density in each study site parameter’s 95% Bayesian Credible Interval (CI), and consid- and showed that elevation did not have a significant effect ered that it has a strong support if the 95% BIC did not overlap on density in any site because all the credible intervals over- 0. For each model, the species interaction factor (SIF) was lapped zero (Table S1). calculated between the leopard cats and the dominant species (SIF < 1 suggests species avoidance, SIF > 1 suggests species Occupancy modeling co-occur more frequently, and SIF = 1 suggests species occur independently; MacKenzie et al. 2004). Domestic dogs were detected in sufficient numbers for analysis in all sites (Table 3). However, leopards were only recorded in sufficient numbers for analysis in SWS, whereas Results dholes were only recorded in sufficient numbers for analysis in CCNP (Table 3). Leopard cat density The estimated occupancy probability of dholes was 0.58 ± 0.11 (mean ± SD) in CCNP (Table 5; Fig. S5). The We identified a total of 66 individual leopard cats from 15,492 occupancy of leopard cats was higher for the sites where trap days across all three sites (Table 2). Photos from all sites dholes were present (0.74 ± 0.13) compared to the sites could be identified to an individual, except for 1 photo from where dholes were absent (0.16 ± 0.12; Table 5), and SIF CCNP, 1 photo from SWS, and 2 photos from PPWS that for the two species was 1.50. The detection probability of were discarded because of blurriness. The estimated popula- both species was relatively low (< 0.1; Table 5; Fig. S5). tion sizes (N ± SD) in the effective area were 45.36 ± 12.51 in The estimated occupancy probability of leopards was CCNP, 56.93 ± 13.81 in PPWS, and 102.01 ± 24.37 in SWS. 0.46 ± 0.14 in SWS (Table 5; Fig. S6). The occupancy of The model with capture probability and the movement scale leopard cats was similar for the sites where leopards were parameter as a function of sex covariate estimated the den- present (0.84 ± 11) compared to the sites where leopards sity (no. individuals/100 km ± SD) as 27.82 ± 7.67 in CCNP, were absent (0.74 ± 0.15; Table 5), and the SIF for the two 22.06 ± 5.35 in PPWS, and 13 ± 3.23 in SWS (Fig. S2). We species was 1.06. The detection probabilities of both species also estimated the expected number of individuals/100 km at were similar (Table 5; Fig. S6). each activity center within the study areas (Fig. S3). In SWS The estimated occupancy probability of domestic and PPWS, the capture probability of males was lower com- dogs was 0.17 ± 0.05 in CCNP, 0.70 ± 0.18 in PPWS, and pared to that of females (Table 4). Overall, the capture prob- 0.79 ± 0.06 in SWS (Figs. S7, S8, and S9). In CCNP, the ability was highest for females in SWS, and highest for males occupancy of leopard cats was about twice as high for the in CCNP (Table 4). In SWS and PPWS, the movement scale sites where dogs were present (0.78 ± 0.14) compared to parameters (sigma) for males were 1–2 times higher than for the sites where dogs were absent (0.41 ± 0.09; Table  5), females (Table 3). In contrast, in CCNP the movement scale and the SIF was 1.67. In PPWS, the probability of occu- parameter (sigma) for females was higher than for males pancy of leopard cats was similar for the sites where dogs (Table 4). The sex ratio of females to males in the population were present (0.65 ± 0.16) compared to the sites where within the effective area was 1.2:1 in CCNP, 1.9:1 in PPWS, dogs were absent (0.63 ± 0.24; Table 5), and the SIF was and 1.7:1 in SWS (Table 4; Fig. S2). 0.98. Similarly, in SWS the probability of occupancy of 1 3 Mammal Research (2022) 67:287–298 293 Table 4 The SCR sex covariate Mean SD Median l95 u95 Rhat MCEpc model estimated density (D), capture probability for male Central Cardamom National Park (p[1]) and female (p[2]) leopard   D 27.83 7.68 26.38 15.34 43.56 - - cats, the movement parameter   p[1] 0.08 0.15 0.03 0.002 0.39 1.00 3.06 for male (sigma[1]) and female   p[2] 0.01 0.003 0.01 0.004 0.02 1.00 0.71 (sigma[2]) leopard cats, the population size (N) in the state   sigma[1] 0.32 0.12 0.30 0.13 0.56 1.00 1.63 space, and the sex ratio in the   sigma[2] 0.67 0.10 0.66 0.48 0.88 1.00 0.73 population (pi)   N 45.36 12.51 43 24 70 1.00 1.12   pi 0.55 0.152 0.554 0.26 0.836 1.001 1.148 Phnom Prich Wildlife Sanctuary   D 22.06 5.35 21.32 12.79 32.94 - -   p[1] 0.01 0.004 0.01 0.001 0.01 1.00 0.77   p[2] 0.01 0.005 0.01 0.003 0.02 1.00 0.78   sigma[1] 1.11 0.35 1.04 0.57 1.82 1.00 1.14   sigma[2] 0.69 0.13 0.67 0.47 0.95 1.00 0.78   N 56.93 13.81 55 32 84 1.01 1.03   pi 0.66 0.14 0.67 0.38 0.90 1.00 0.94 Srepok Wildlife Sanctuary   D 13.53 3.23 13.39 8.09 19.50 - -   p[1] 0.02 0.02 0.02 0.01 0.04 1.00 4.68   p[2] 0.11 0.07 0.09 0.04 0.22 1.00 1.71   sigma[1] 1.39 0.24 1.36 0.95 1.89 1.00 1.14   sigma[2] 0.52 0.13 0.50 0.30 0.78 1.00 1.66   N 102.02 24.37 10 61 147 1.00 1.66   pi 0.63 0.12 0.64 0.39 0.84 1.00 1.45 SD, standard deviation; l95 and u95, the limits of a 95% Highest Density Credible Interval; Rhat, the potential scale reduction factor (at convergence, Rhat = 1); MCEpc, the Monte Carlo standard error as a percentage of the posterior SD leopard cats was similar for the sites where dogs were pre- Similarly, Rabinowitz (1990) found that leopard cats used sent (0.83 ± 0.09) compared to the sites where leopards were DDF less often than other habitats in western Thailand, absent (0.72 ± 0.16; Table 5), and SIF was 1.03. In CCNP, owing to lower numbers of their preferred prey. Our results the detection probabilities of domestic dogs and leopard cats also suggest DDF is a suboptimal habitat for leopard cats, were similar (Table 5; Fig. S7). In PPWS, the detection prob- and we speculate that this was because of the harsh con- ability of leopard cats was about twice as high as domestic ditions within the DDF during the dry season, and the dogs (Table 5; Fig. S8), whereas in SWS the detection prob- effects this has on the prey availability. Frequent annual ability of domestic dogs was about twice as high as leopard dry season fires, both natural and human-caused (e.g., to cats (Table 5; Fig. S9). enhance regrowth in the rainy season), occur in DDF after the dipterocarp trees loss their leaves, burning most of the grassy understory (McShea et al. 2011). The DDF is well Discussion adapted to dry season fires, which seem to have occurred in this habitat since the late Pleistocene (McShea et al. The leopard cat density was highest in CCNP and lowest in 2011), in contrast to evergreen forests which typically do SWS, which supported our prediction that evergreen for- not experience dry season fires. Previous research showed ests support higher densities of leopard cats compared to that evergreen forests and nearby DDF forests in South- DDF. However, our results should be viewed with caution east Asia have similar biomass of small rodents during the because the 95% credible intervals of the densities over- rainy season, but after the dry season fires the biomass of lapped among all three sites. Nonetheless, our results were small rodents becomes 5 times higher in evergreen forests similar to Peterson et al. (2019), who found that leopard compared to DDF (Walker and Rabinowitz 1992). Over- cat density in northeastern Thailand was higher in the ever- all, the biomass of small rodents decreases about 76% in green and semi-evergreen forest compared to DDF, likely DDF forests from the rainy season until after the dry sea- because the latter is a suboptimal habitat for this species. son fires (Walker and Rabinowitz 1992). Because leopard 1 3 294 Mammal Research (2022) 67:287–298 Table 5 Estimated occupancy Mean SD Median l95 u95 Rhat MCEpc probability (psiA) for large carnivores (leopards, dholes, CCNP: dholes vs leopard cats and domestic dogs), occupancy   pA 0.05 0.01 0.05 0.03 0.08 1 0.29 probability for leopard cats   pB 0.09 0.02 0.08 0.05 0.12 1 0.29 when large carnivores were   psiA 0.58 0.11 0.57 0.37 0.79 1 0.31 absent (psiB[1]), occupancy probability for leopard cats   psiB[1] 0.16 0.12 0.14 0 0.39 1 0.30 when large carnivores were   psiB[2] 0.73 0.13 0.74 0.51 1 1 0.334 present (psiB[2]), detection   Na 47.26 7.64 46 33 62 1 0.331 probability of large carnivores   Nb 39.99 5.47 39 30 50 1.02 0.30 (pA), and the detection probability of leopard cats (pB).   Nboth 34.88 6.08 35 23 46 1 0.30 The “Na” is the number of sites SWS: leopards vs leopard cats used by dhole/leopard/domestic   pA 0.11 0.03 0.11 0.05 0.18 1 0.34 dog, “Nb” is the number of   pB 0.15 0.022 0.15 0.11 0.195 1 0.29 sites used by leopard cat, and “Nboth” is the number of sites   psiA 0.46 0.14 0.44 0.22 0.77 1 0.40 used by both species   psiB[1] 0.74 0.15 0.76 0.48 1 1 0.32   psiB[2] 0.84 0.11 0.85 0.62 1 1 0.31   Na 21.35 5.98 20 13 34 1 0.40   Nb 37.71 3.10 38 32 43 1 0.30   Nboth 18.58 5.54 17 10 30 1 0.40 CCNP: domestic dog vs leopard cats   pA 0.13 0.03 0.13 0.07 0.2 1 0.25   pB 0.09 0.02 0.09 0.06 0.12 1 0.28   psiA 0.17 0.05 0.17 0.08 0.27 1 0.27   psiB[1] 0.41 0.09 0.41 0.24 0.59 1 0.27   psiB[2] 0.78 0.14 0.80 0.51 1 1 0.25   Na 13.36 2.28 13 11 18 1 0.27   Nb 38.79 5.08 38 29 48 0.97 0.28   Nboth 10.99 2.44 11 7 15 1 0.27 PPWS: domestic dog vs leopard cats   pA 0.04 0.01 0.03 0.02 0.06 1 0.43   pB 0.09 0.02 0.09 0.05 0.12 1 0.31   psiA 0.70 0.18 0.71 0.40 1 1 0.53   psiB[1] 0.63 0.25 0.66 0.14 1 1 0.37   psiB[2] 0.65 0.16 0.65 0.36 0.97 1 0.39   Na 54.52 13.48 55 32 77 0.98 0.53   Nb 51.47 7.92 51 36 66 0.98 0.35   Nboth 36.198 12.954 36 13 60 1 0.528 SWS: domestic dog vs leopard cats   pA 0.33 0.03 0.33 0.28 0.39 1 0.26   pB 0.15 0.02 0.15 0.11 0.19 1 0.27   psiA 0.79 0.06 0.79 0.67 0.90 1 0.25   psiB[1] 0.72 0.16 0.74 0.43 1 1 0.27   psiB[2] 0.83 0.09 0.84 0.67 1 1 0.27   Na 36.78 0.88 37 36 38 1 0.25   Nb 38.40 3.21 38 33 44 1 0.28   Nboth 31.29 2.97 31 25 36 1 0.27 SD, standard deviation; l95 and u95, the limits of a 95% Highest Density Credible Interval; Rhat, the potential scale reduction factor (at convergence, Rhat = 1); MCEpc, the Monte Carlo standard error as a percentage of the posterior SD 1 3 Mammal Research (2022) 67:287–298 295 cats feed mostly on small rodents < 500 g (Kamler et al. density and similar sex ratio in CCNP; thus, males might 2020a; Rostro-García et al. 2021), the higher prey avail- have had smaller home ranges because they did not need to ability throughout the year in evergreen forests likely sup- travel as far to encompass several female home ranges. ports higher densities of this small felid compared to DDF. The two-species occupancy analyses suggested that Although leopard cats can attain unusually high densities domestic dogs did not have a negative impact on leopard in human-modified habitats, owing to superabundant small cat presence on any of the sites, which did not support our rodent numbers (Chua et al. 2016), their densities in natural prediction. Nonetheless, leopard cats likely avoided domes- habitats typically range from 2 to 18 individuals/100 km tic dogs temporally, because the former are almost strictly (Table 1). The only previous study to report a density > 18 nocturnal (Lynam et al. 2013; Gray et al. 2014; Kamler et al. individuals/km was Petersen et al. (2019), who found a den- 2020a; Rostro-García et al. 2021) whereas domestic dogs are sity of 21.2 individuals/100 km in semi-evergreen forests mostly diurnal in accordance with human activity (Kamler in northeastern Thailand. Therefore, our study found two of et al. 2012; Bianchi et al. 2020). We observed that domestic the highest densities of leopard cats ever reported in natu- dogs were brought into all three sites by local people for the ral habitat. When compared to previous studies, continuous purposes of illegally hunting wildlife, including red muntjac evergreen or large patches of evergreen forests appear to (Muntiacus vaginalis), wild pig (Sus scrofa), and reptiles. be an optimal natural habitat for leopard cats in South and Thus, domestic dogs likely negatively impact numerous Southeast Asia (Table 1), probably due to relatively high other species inside the protected areas, especially in SWS numbers of small rodents in these forests. Although we where dogs were detected at high frequencies. Domestic found their density in DDF mosaic to be half of that found dogs pose a threat to nearly 200 globally threatened species in a continuous evergreen forest, the density in DDF mosaic worldwide, and they have contributed to the extinctions of was still moderate compared to that reported in previous 11 vertebrates via depredations, disease transmission, com- studies across various habitats (Table 1). We conclude that petition, and hybridization (Doherty et al. 2017). Given the DDF appears to be a suboptimal habitat for leopard cats high rates of dog detections on our study sites, we recom- compared to evergreen forests; however, DDF can still sus- mend further research on domestic dogs and their impacts tain a modest population of this species, which is similar to on wildlife within protected areas in Cambodia (Hughes and that reported by Rostro-García et al. (2021). Macdonald 2013; Hughes et al. 2017). We also recommend The elevation did not significantly affect the density of that the management of all three protected areas makes a leopard cats in any of the study sites, probably because there greater effort to enforce the laws and prevent domestic dogs was not much variation in elevation across the study sites. and humans from illegally entering the core zones because Leopard cat densities might be affected by other factors not such efforts are likely to have a positive impact on the overall included in our study, such as local small rodent abundance, biodiversity in the protected areas. microhabitats, and possibly anthropogenic disturbances, The occupancy probability of leopard cats was similar including roads. We recommend that future studies investi- when leopards were present or absent in SWS, which did not gate other factors that might influence densities of leopard support our prediction. This suggests that leopard cats were cats in natural habitat, to gain a more complete understand- able to coexist with leopards in SWS. Although a previous ing of the factors that influence their densities. study in SWS found that leopards consumed leopard cats, In SWS and PPWS, the capture probability of male the latter only accounted for < 1% of the biomass consumed leopard cats was lower than that of females, which likely by leopards, and overall the leopard density was extremely corresponds to differences in movement patterns between low (1 leopard/100 km ; Rostro-García et al. 2018). This the sexes. Males moved twice as far as females from their suggests that leopards rarely prey on leopard cats, at least not activity center, which likely resulted in low capture prob- enough for this small felid to spatially avoid leopards, and ability of males compared to females, especially if camera that the low leopard density may have affected their interac- spacing was far relative to leopard cat home range sizes. tion with leopard cats. Regardless, leopard and leopard cats Larger home ranges and greater distanced traveled by males have vastly different diets (Rostro-García et al.  2018, 2021; compared to females are common in solitary felid species Kamler et al. 2020a); thus, they do not compete for the same (Kamler and Gipson 2000; Goodrich et al. 2010; Simchar- food resources. Both felids were nocturnal in SWS (Rostro- oen et al. 2014; Sarkar et al. 2016), and result from males García et al. 2018); thus; leopard cats did not appear to avoid establishing home ranges to encompass several female home leopards temporally. We conclude that due to large differ - ranges, whereas females establish their home ranges based ences in body size and diets, leopard cats do not spatially or on food resources and cover for their young (Sandell 1989). temporally avoid leopards, despite the occasional predation However, in CCNP males appeared to have higher capture on this small felid by leopards, at least in areas were leopard probability, and had shorter distance movements compared densities are low such as SWS. to females. This result might have been because of the higher 1 3 296 Mammal Research (2022) 67:287–298 In CCNP, the occupancy probability of leopard cats was 2021), indicating this small felid might not be preyed upon similar when dholes were present or absent, which did not frequently by these mesocarnivores. Regardless, we recom- support our prediction. This indicates that leopard cats were mend that future studies examine in more detail if meso- not spatially avoiding dholes, despite that dholes sometimes carnivores affect the density or occupancy of leopard cats. prey upon this small felid (Kamler et al. 2020b). Similar to Additionally, we recommend that future researches consider the leopard, the diet of dholes contained < 1% biomass con- multi-scale analyses when investigating the interactions of sumed of leopard cats, indicating they are rarely preyed upon leopard cats and both large and mesocarnivores. Only by by dholes. Also, dholes and leopard cats have vastly different studying leopard cats within different carnivore communities diets (Kamler et al. 2020a, b), indicating that they do not com- can we gain a more complete understanding of coexistence pete for the same food resources. However, dholes are diurnal mechanisms, and the important factors that affect the density in Southeast Asia (Kamler et al. 2012), so leopard cats might and occupancy of Southeast Asia’s smallest felid. avoid dholes temporally. We conclude that due to large differ - Supplementary Information The online version contains supplemen- ences in body size and diets, leopard cats do not spatially avoid tary material available at https://doi. or g/10. 1007/ s13364- 022- 00634-6 . dholes, despite the occasional predation on this small felid by dholes, although leopard cats might avoid dholes temporally. Acknowledgements These research projects were conducted under the Overall, the adaptability of leopard cats to various forest permission granted by the General Department of Administration for types, and lack of strong negative impacts caused by large Nature Conservation and Protection, Ministry of Environment (MoE), and Forestry Administration, Ministry of Agriculture, Forestry and carnivores, helps to explain why this species is the most Fishery (MAFF). We thank the field teams who helped collect the data, common and widespread felid in Southeast Asia. Nonethe- including MoE rangers, WWF Cambodia staff, and local porters. We less, our camera-trapping surveys focused on larger felid also thank WWF Cambodia for coordination, logistical, and fieldwork species had different spacing between camera stations, support in SWS and PPWS, and Mike Meredith for providing statisti- cal advice. and occurred in different habitats, all of which could have affected our results. However, we feel that potential differ - Funding The camera trap studies in PPWS and CCNP were funded ences in leopard cat detectability due to different method- by the Robertson Foundation through Wildlife Conservation Research ologies were minimal given the relatively large number of Unit (WildCRU), Department of Zoology, University of Oxford, with support provided by WWF Cambodia, FFI Cambodia, and the Minis- detections at each site. Also, home ranges of leopard cats 2 2 try of Environment. The camera trap studies in SWS were funded by in Thailand averaged 12 km for 14 males and 14 km for Panthera with support provided by WWF Cambodia and the Forestry 6 females (Grassman et al. 2005); thus, even the relatively Administration. large camera spacing of about 2.5 km in SWS theoretically would have missed few, if any, leopard cats. Another caveat Data availability Data are available upon request. is that our investigation was limited to broad scale analysis of habitat and occupancy. Thus, leopard cats might have Declarations avoided large carnivores using mechanisms at finer scales. Ethics approval Our research was carried out following the legal For example, time-to-encounter analysis might have detected standards of Cambodia’s Natural Protected Area law, the Ministry leopard cat avoidance of large carnivores. Additionally, leop- of Environment, and Forestry Law, Ministry of Agriculture, Forestry ard cats might have avoided large carnivores at the level of and Fishery, and the guidelines provided by the University of Oxford, the home range, feeding site, or resting site (Rostro-Garía Biomedical Sciences, Animal Welfare and Ethical Review Body (AWERB). et al. 2015). Furthermore, in our study sites the small- and medium-sized felids and canids, such as clouded leopards, Consent for publication The manuscript has been approved by all co- Asian golden cats (Catopuma temminckii), jungle cats (Felis authors. chaus), marbled cats (Pardofelis marmorata), and golden jackals (Canis aureus), were absent or occurred in such low Conflict of interest The authors declare no competing interests. numbers that they could not be included in the analyses. Leopard cats might compete more with small and meso- Open Access This article is licensed under a Creative Commons Attri- felids, which are known to feed more on small rodents com- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long pared to large carnivores (Kamler et al. 2020a). Nonethe- as you give appropriate credit to the original author(s) and the source, less, previous studies showed that the occupancy of leopard provide a link to the Creative Commons licence, and indicate if changes cats was not affected by the presence of Asian golden cats were made. The images or other third party material in this article are (Kamler et al. 2020a) or jungle cats (Rostro-García et al. included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in 2021), indicating leopard cats might not spatially avoid the article's Creative Commons licence and your intended use is not meso-felids. Furthermore, leopard cats were not found in permitted by statutory regulation or exceeds the permitted use, you will the scats of Asian golden cats (Kamler et al. 2020a), jungle need to obtain permission directly from the copyright holder. To view a cats (Rostro-García et al. 2021), and jackals (Kamler et al. copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . 1 3 Mammal Research (2022) 67:287–298 297 Hughes J, MacDonald DW, Boitani L (2017) Roaming free in the References rural idyll: dogs and their connections with wildlife. In: Serpell J (ed) The domestic dog: its evolution, behaviour and interac- Baker PJ, Bunyavejchewin S (2009) Fire behavior and r fi e ee ff cts across tions with people. Cambridge University Press, Cambridge, pp the forest landscape of continental Southeast Asia. In: Cochrane 369–384 MA (ed) Tropical fire ecology. Springer, Chichester, pp 311–334 Kamler JF, Gipson PS (2000) Home range, habitat selection, and sur- Bashir T, Bhattacharya T, Poudyal K, Sathyakumar S, Qureshi Q vival of bobcats, Lynx rufus, in a prairie ecosystem in Kansas. (2013) Estimating leopard cat Prionailurus bengalensis densi- Can Field-Naturalist 114:388–394 ties using photographic captures and recaptures. Wildl Biol Kamler JF, Johnson A, Vongkhamheng C, Bousa A (2012) The diet, 19:462–472 prey selection, and activity of dholes (Cuon alpinus) in northern Bianchi RdC, Olifiers N, Riski LL, Gouvea JA, Cesário CS, Fornitano Laos. J Mammal 93:627–633 L, Zanirato GL, Yan de Oliveira M, de Morais KD, Ribeiro RL, Kamler JF, Inthapanya X, Rasphone A, Bousa A, Vongkhamheng C, D’Andrea PS (2020) Dog activity in protected areas: behavioral Johnson A, Macdonald DW (2020a) Diet, prey selection, and effects on mesocarnivores and the impacts of a top predator. Eur activity of Asian golden cats and leopard cats in northern Laos. J Wildl Res 66:36 J Mammal 101:1267–1278 Bischof R, Ali H, Kabir M, Hameed S, Nawaz MA (2014) Being the Kamler JF, Thatdokkham K, Rostro‐García S, Bousa A, Caragiulo underdog: an elusive small carnivore uses space with prey and A, Crouthers R, In V, Pay C, Pin C, Prum S, Vongkhamheng time without enemies. J Zool 293:40–48 C (2020b) Diet and prey selection of dholes in evergreen Bivand R, Keitt T, Rowlingson B, Pebesma E, Sumner M, Hijmans and deciduous forests of Southeast Asia. J Wildl Manag R, Rouault E, Warmerdam F, Ooms J, Rundel C (2016) Rgdal: 84:1396–1405 bindings for the geospatial data abstraction library. R package Kamler JF, Minge C, Rostro-García S, Gharajehdaghipour T, Burnham D, Hinks AE, Macdonald DW (2012) Life and dinner under Crouthers R, In V, Pay C, Pin C, Sovanna P, Macdonald the shared umbrella: patterns in felid and primate communities. DW (2021) Home range, habitat selection, density, and diet of Folia Primatol 83:148–170 golden jackals in the Eastern Plains Landscape, Cambodia. J Chua MA, Sivasothi N, Meier R (2016) Population density, spatiotem- Mammal 102:636–650 poral use and diet of the leopard cat (Prionailurus bengalensis) Kellner K, Kellner MK, SystemRequirements J (2018) Package ‘jag- in a human-modified succession forest landscape of Singapore. sUI’ A wrapper around ‘rjags’ to streamline ‘JAGS’ analyses Mammal Res 61:99–108 Kim DH, Sexton JO, Townshend JR (2015) Accelerated deforestation Doherty TS, Dickman CR, Glen AS, Newsome TM, Nimmo DG, in the humid tropics from the 1990s to the 2000s. Geophys Res Ritchie EG, Vanak AT, Wirsing AJ (2017) The global impacts of Lett 42:3495–3501 domestic dogs on threatened vertebrates. Biol Cons 210:56–59 Kitchener AC, Breitenmoser-Würsten C, Eizirik E, Gentry A, Werde- Efford M (2004) Density estimation in live-trapping studies. Oikos lin L, Wilting A, Yamaguchi N, Abramov AV, Christiansen P, 106:598–610 Driscoll C, Duckworth JW (2017) A revised taxonomy of the Efford M (2020) secr: spatially explicit capture-recapture models. 4.3.1 Felidae. The final report of the Cat Classification Task Force Efford MG, Fewster RM (2013) Estimating population size by spatially of the IUCN/SSC Cat Specialist Group. Cat News S11:1–80 explicit capture-recapture. Oikos 122:918–928 Koh LP, Sodhi NS (2010) Conserving Southeast Asia’s imperiled Francis C (2019) Field guide to the mammals of South-east Asia, 2nd biodiversity: scientific, management, and policy challenges. edn. Bloomsbury Publishing, New York Biodivers Conserv 19:913–917 Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB Kyaw PP, Macdonald DW, Penjor U, Htun S, Naing H, Burnham D, (2013) Bayesian data analysis. CRC Press, New York Kaszta Ż, Cushman SA (2021) Investigating carnivore guild Gompper ME (2021) Adding nuance to our understanding of dog– structures: spatial and temporal relationships amongst threat- wildlife interactions and the need for management. Integr Comp ened felids in Myanmar. ISPRS Int J Geo Inf 10:808 Biol 61:93–102 Lynam AJ, Jenks KE, Tantipisanuh N, Chutipong W, Ngoprasert Goodrich JM, Miquelle DG, Smirnov EN, Kerley LL, Quigley HB, D, Gale GA, Steinmetz R, Sukmasuang R, Bhumpakphan N, Hornocker MG (2010) Spatial structure of Amur (Siberian) tigers Grassman Jr LI, Cutter P (2013) Terrestrial activity patterns of (Panthera tigris altaica) on Sikhote-Alin Biosphere Zapovednik, wild cats from camera-trapping. Raffles Bull Zool 61:407–415 Russia. J Mammal 91:737–748 Macdonald DW, Loveridge AJ, Nowell K (2010) Dramatis personae: Grassman LI (2000) Movements and diet of the leopard cat Prionai- an introduction to the wild felids. In: Macdonad DW, Loveridge lurus bengalensis in a seasonal evergreen forest in south-central AJ (eds) Biology and conservation of wild felids. Oxford Uni- Thailand. Acta Theriol 45:421–426 versity Press, Oxford, pp 3–58 Grassman LI, Tewes ME, Silvy NJ, Kreetiyutanout K (2005) Spatial Macdonald DW, Burnham D, Hinks AE, Wrangham R (2012) A organization and diet of the leopard cat (Prionailurus bengalensis) problem shared is a problem reduced: seeking efficiency in the in north-central Thailand. J Zool 266:45–54 conservation of felids and primates. Folia Primatol 83:171–215 Gray T, Channa P, Chanrattanak P, Sovanna P (2014) The status of MacKenzie DI, Bailey LL, Nichols JD (2004) Investigating species jungle cat and sympatric small cats in Cambodia’s Eastern Plains. co-occurrence patterns when species are detected imperfectly. Cat News 8:19–23 J Anim Ecol 73:546–555 Gray TN, Grainger MJ, Grosu R (2020) Conservation decision-making McShea WJ, Davies SJ, Bhumpakphan N (2011) The ecology and under uncertainty: identifying when to reintroduce tiger Panthera conservation of seasonally dry forests in Asia. Smithsonian tigris to Cambodia. Conserv Sci Pract 2:e187 Institution Scholarly Press, Washington, D.C. Heino M, Kummu M, Makkonen M, Mulligan M, Verburg PH, Jalava Meredith M (2020a) Bayes with JAGS – a tutorial for wildlife M, Räsänen TA (2015) Forest loss in protected areas and intact researchers. https:// bcss. or g. m y/ tut/ ba y es- wit h- jags-a- tut or forest landscapes: a global analysis. PLoS ONE 10:e0138918 ial- f or - wildl ife- r esea r c hers/ occup ancy - model ling/ tw o- speci Hughes J, Macdonald DW (2013) A review of the interactions es- occup ancy- models/. Accessed Sept 2020 between free-roaming domestic dogs and wildlife. Biol Con- Meredith M (2020b) makeJAGSmask. Habitat matrices for use with serv 157:341–351 SECR analysis in JAGS or BUGS. https:// mmere dith. net/R/. Accessed Sept 2020 1 3 298 Mammal Research (2022) 67:287–298 Meredith M (2020c) wiqid: quick and dirty estimates for wildlife Sandell M (1989) The mating tactics and spacing patterns of solitary populations. R package, version 0.3.0. https:// CRAN.R- proje carnivores. In: Gittleman JL (ed) Carnivore behavior, ecology, ct. org/ packa ge= wiqid . Accessed Sept 2020 and evolution, vol 1. Cornell University Press, Ithaca, pp 164–182 Miettinen J, Shi C, Liew SC (2011) Deforestation rates in insu- Sarkar MS, Ramesh K, Johnson JA, Sen S, Nigam P, Gupta SK, Murthy lar Southeast Asia between 2000 and 2010. Glob Change Biol RS, Saha GK (2016) Movement and home range characteristics 17:2261–2270 of reintroduced tiger (Panthera tigris) population in Panna Tiger Mohamed A, Sollmann R, Bernard H, Ambu LN, Lagan P, Mannan S, Reserve, central India. Eur J Wildl Res 62:537–547 Hofer H, Wilting A (2013) Density and habitat use of the leopard Simcharoen A, Savini T, Gale GA, Simcharoen S, Duangchantrasiri cat (Prionailurus bengalensis) in three commercial forest reserves S, Pakpien S, Smith JL (2014) Female tiger Panthera tigris home in Sabah, Malaysian Borneo. J Mammal 94:82–89 range size and prey abundance: important metrics for manage- Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GA, Kent J ment. Oryx 48:370–377 (2000) Biodiversity hotspots for conservation priorities. Nature Sodhi NS, Brook BW (2006) Southeast Asian biodiversity in crisis. 403:853 Cambridge University Press, Cambridge Penjor U, Macdonald DW, Wangchuk S, Tandin T, Tan CKW (2018) Sodhi NS, Koh LP, Brook BW, Ng PK (2004) Southeast Asian bio- Identifying important conservation areas for the clouded leopard diversity: an impending disaster. Trends Ecol Evol 19:654–660 Neofelis nebulosa in a mountainous landscape: inference from Sodhi NS, Posa MRC, Lee TM, Bickford D, Koh LP, Brook BW (2010) spatial modeling techniques. Ecol Evol 8:4278–4291 The state and conservation of Southeast Asian biodiversity. Bio- Penjor U, Tan CKW, Wangdi S, Macdonald DW (2019) Understanding divers Conserv 19:317–328 the environmental and anthropogenic correlates of tiger presence Sollmann R, Furtado MM, Gardner B, Hofer H, Jácomo AT, Tôrres in a montane conservation landscape. Biol Conserv 238:108196 NM, Silveira L (2011) Improving density estimates for elusive Petersen WJ, Savini T, Steinmetz R, Ngoprasert D (2019) Estimating carnivores: accounting for sex-specific detection and movements leopard cat Prionailurus bengalensis Kerr, 1792 (Carnivora: Feli- using spatial capture–recapture models for jaguars in central Bra- dae) density in a degraded tropical forest fragment in northeastern zil. Biol Conserv 144:1017–1024 Thailand. J Threat Taxa 11:13448–13458 Srivathsa A, Parameshwaran R, Sharma S, Karanth KU (2015) Estimat- Pin C, Ngoprasert D, Gray TN, Savini T, Crouthers R, Gale GA (2018) ing population sizes of leopard cats in the Western Ghats using Utilization of waterholes by globally threatened species in decidu- camera surveys. J Mammal 96:742–750 ous dipterocarp forest of the Eastern Plains Landscape of Cambo- Sunarto S, Kelly MJ, Parakkasi K, Hutajulu MB (2015) Cat coexistence dia. Oryx 54:572–582 in central Sumatra: ecological characteristics, spatial and temporal Plummer M (2003) JAGS: a program for analysis of Bayesian graphi- overlap, and implications for management. J Zool 296:104–115 cal models using Gibbs sampling. DSC 2003 Working Papers, Sunquist M, Sunquist F (2017) Wild cats of the world. University of Vienna, Austria Chicago Press, Chicago QGIS Delopment Team (2020) QGIS geographic information system. Vitekere K, Wang J, Karanja H, Consolée KT, Jiang G, Hua Y (2020) Open Source Geospatial Foundation Project Dynamic in species estimates of carnivores (leopard cat, red fox, R Core Team (2020) R: A Language and Environment for Statistical and north Chinese leopard): a multi-year assessment of occupancy Computing. R Foundation for Statistical Computing, Vienna, Aus- and coexistence in the Tieqiaoshan Nature Reserve, Shanxi Prov- tria. https:// www.R- proje ct. org/. Accessed Sept 2020 ince, China. Animals 10:1333 Rabinowitz A (1990) Notes on the behavior and movements of leopard Waddle JH, Dorazio RM, Walls SC, Rice KG, Beauchamp J, Schuman cats, Felis bengalensis, in a dry tropical forest mosaic in Thailand. MJ, Mazzotti FJ (2010) A new parameterization for estimating Biotropica:397–403 co-occurrence of interacting species. Ecol Appl 20:1467–1475 Rajaratnam R, Sunquist M, Rajaratnam L, Ambu L (2007) Diet and Walker S, Rabinowitz A (1992) The small-mammal community of a habitat selection of the leopard cat (Prionailurus bengalensis dry-tropical forest in central Thailand. J Trop Ecol:57–71 borneoensis) in an agricultural landscape in Sabah, Malaysian Wearn OR, Rowcliffe JM, Carbone C, Bernard H, Ewers RM (2013) Borneo. J Trop Ecol 23:209–217 Assessing the status of wild felids in a highly-disturbed commer- Rasphone A, Kamler JF, Tobler M, Macdonald DW (2021) Den- cial forest reserve in Borneo and the implications for camera trap sity trends of wild felids in northern Laos. Biodivers Conserv survey design. PLoS One 8:e77598 30:1881–1897 Webb EL, Choo YR, Kudavidanage EP, Amarasinghe TR, Bandara Ross J, Brodie J, Cheyne S, Hearn A, Izawa M, Loken B, Lynam A, UG, Wanninayaka WA, Ravindrakumar P, Nimalrathna TS, Liang McCarthy J, Mukherjee S, Phan C, Rasphone A, Wilting A (2015) SH, Chua MA (2020) Leopard activity patterns in a small mon- Prionailurus bengalensis. The IUCN Red List of Threatened Spe- tane protected area highlight the need for integrated, collaborative cies 2015: e.T18146A50661611. https:// doi. org/ 10. 2305/ IUCN. landscape conservation. Glob Ecol Conserv 23:e01182 UK. 2015-4. RL T S. T1814 6A506 61611. en. Downloaded on 12 Wohlfart C, Wegmann M, Leimgruber P (2014) Mapping threatened June 2020 dry deciduous dipterocarp forest in South-east Asia for conserva- Rostro-García S, Kamler JF, Hunter LTB (2015) To kill, stay or flee: tion management. Trop Conserv Sci 7:597–613 the effects of lions and landscape factors on habitat and kill site Xiong M, Shao X, Long Y, Bu H, Zhang D, Wang D, Li S, Wang R, selection of cheetahs in South Africa. PLoS ONE 10:e0117743 Yao M (2016) Molecular analysis of vertebrates and plants in scats Rostro-García S et al (2018) An adaptable but threatened big cat: den- of leopard cats (Prionailurus bengalensis) in southwest China. J sity, diet and prey selection of the Indochinese leopard (Panthera Mammal 97:1054–1064 pardus delacouri) in eastern Cambodia. R Soc Open Sci 5:171187 Rostro‐García S, Kamler JF, Minge C, Caragiulo A, Crouthers R, Publisher's note Springer Nature remains neutral with regard to Groenenberg M, Gray TN, In V, Pin C, Sovanna P, Kéry M (2021) jurisdictional claims in published maps and institutional affiliations. Small cats in big trouble? Diet, activity, habitat use, and occu- pancy of jungle cats and leopard cats in threatened dry deciduous forests, Cambodia. Ecol Evol 11:4205–4217 Royle JA, Chandler RB, Sollmann R, Gardner B (2014) Spatial cap- ture-recapture. Academic Press, Boston 1 3

Journal

Mammal Research – Springer Journals

Published: Jul 1, 2022

Keywords: Cambodia; Co-occurrence; Dry deciduous forest; Evergreen forest; Prionailurus bengalensis; Spatial capture-recapture

There are no references for this article.