The peri-urban leopards of Kathmandu: assessing determinants of presence and predation on domestic animals
A SHISH B ISTA,PRANAV C HANCHANI N ARESH S UBEDI and S IDDHARTHA B. BAJRACHARYA
Abstract The conservation of large carnivores in human- Introduction dominated landscapes needs to be reconciled with the safety of humans and domestic animals. This is especially true for umans and large carnivores co-occur extensively where the leopard Panthera pardus, which occurs extensively in Hurban areas expand into or surround wildlife habitats agricultural landscapes and remnant forest tracts embedded (Zérah, ). Although large mammals do not always persist within peri-urban areas such as Kathmandu district in in areas with high anthropogenic pressure (Woodroffe, ; Nepal. We carried out interviews in households in this Ripple et al., ), they sometimes adapt to human-modified district to determine the extent of leopard habitat use and habitats including the edges of populous towns and farm- predation on domestic animals (dogs and goats) during lands, often sheltering, feeding and breeding in such areas October –April . We used multi-state occupancy (Gehrt, ; Beckmann & Lackey, ; Bateman & models, and estimated probabilities of leopard habitat use Fleming, ; Athreya et al., ; Odden et al., ). The conservation of large carnivores presents a conundrum (Ψ) and predation on domestic animals (Ψ) as a function of covariates, while accounting for imperfect detection. Our for wildlife managers and local administrators who are findings indicate that the rapidly urbanizing outskirts of tasked with protecting wildlife and ensuring the safety of Kathmandu city are used extensively by leopards. The esti- local communities (Allendorf, ). This task is especially mated probability of fine-scale habitat use in km sample challenging when carnivores occur on privately owned land units was . ± SE . and the probability of predation (Enserink & Vogel, ), where there is an elevated risk of on domestic animals was . ± SE .. Leopard attacks negative interactions with people (Nyhus & Tilson, ). occurred in areas with high vegetation cover and abundant The leopard Panthera pardus commonly occurs in close goats. Addressing the problem of leopard attacks on domes- proximity to human settlements (Odden & Wegge, ; tic animals will require developing a comprehensive mit- Odden et al., ). There are many drivers for leopard igation plan that includes educational activities to raise occurrence in human-dominated landscapes, including habi- awareness, measures to address grievances of affected local tat fragmentation, wild prey depletion, attraction to domestic communities, interventions to prevent attacks on livestock, animals as easy prey and competitive displacement as a compensation programmes, and rapid response teams to result of inter- or intra-species interactions (Seidensticker, ensure human and animal welfare in conflict-prone areas. ; Odden et al., ; Ripple et al., ). Several studies Land-use planning in these peri-urban landscapes needs show that home ranges of leopards sometimes overlap to facilitate the safe sharing of space between people and partially or completely with human-use areas (e.g. Odden ’ leopards. et al., , ), which is facilitated by the species dietary plasticity. Leopards readily adapt to prey on domestic ani- Keywords Carnivore conservation, habitat use, human– mals, particularly dogs, which may comprise as much as leopard conflict, Kathmandu, leopard, occupancy models, % of their diet (Karanth & Sunquist, ; Edgaonkar Panthera pardus, urban wildlife & Chellam, ; Dickman & Marker, ; Athreya et al., ; Kumbhojkar et al., ). Predation of domestic animals by leopards is common across many Asian and African range countries (Kissui, ; Dar et al., ; Khorozyan et al., ; Kshettry
ASHISH BISTA* (Corresponding author) and PRANAV CHANCHANI World Wide et al., ). Such predation, especially on livestock, causes Fund for Nature, 172-B Lodhi Estate, New Delhi, 110003, India economic losses (Dar et al., ), can affect the livelihoods E-mail [email protected] and social well-being of people (Barua et al., ; Kshettry NARESH SUBEDI and SIDDHARTHA B. BAJRACHARYA National Trust for Nature Conservation, Khumaltar, Lalitpur, Nepal et al., ), engenders negative attitudes of people towards carnivores (Megaze et al., ) and may catalyse retaliatory *Previously at: National Trust for Nature Conservation, Khumaltar, Lalitpur, Nepal killing by poisoning or other means (Ogada et al., ). – Received January . Revision requested March . In Nepal, human leopard conflict is a serious issue Accepted May . (Acharya et al., ). Adverse interactions with humans
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are more likely when leopards occur in densely populated Here, we assessed the extent and determinants of leopard peri-urban areas (Soulsbury & White, ), such as habitat use and predation on domestic animals in peri- Kathmandu district. Inclusive of Kathmandu, the country’s urban areas within Kathmandu district, with the aim of capital city, this district has a population of . . million assisting the Government of Nepal in devising strategies people, with a population density of , people/km ( to mitigate future human–leopard conflict. times higher than the national average; CBS, ). The city and its suburbs are surrounded by montane forests, Study area most notably the Shivapuri-Nagarjun National Park and National Forest, which supports a leopard population We conducted this study in of municipalities in (Pokharel, ). Leopards sometimes enter human settle- Kathmandu district, Nepal ( km ; Fig. ). Kathmandu ments, including the fringes of Kathmandu city, and are district is one amongst three districts located within the subsequently captured and translocated to zoos or released Kathmandu valley, and is home to . , households back into the wild. Although leopards are routinely captured (CBS, ). The predominant land-use types are forest in the Kathmandu valley, the extent of their occurrence and (%), farmland (%) and built-up areas (%; Wang predation on domestic animals has hitherto not been thor- et al., ). Along with a rapid increase in the human oughly investigated (Pokharel, ). population, urban areas expanded by % in the
FIG. 1 Study area showing Kathmandu district, Kathmandu city and survey locations within -km grid cells. The inset map shows the location of the study area within Nepal.
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Kathmandu valley since , with conversion of %of et al. (), each household was treated as a discrete sam- farmlands (Ishtiaque et al., ). Most communities in pling occasion. Adult residents in each household were Kathmandu district outside the city are agrarian, with rice, asked whether they had detected leopard presence or wheat, maize, potato and mustard being the main crops. knew of leopard predation on domestic animals in the im- The forested hills around Kathmandu district (Fig. )are mediate neighbourhood (within c. m of their home) managed by the administration of Shivapuri-Nagarjun over the past year. We only considered the immediate National Park ( km ) and the Kathmandu District neighbourhood so that we could reliably assign reported Forest Office as National Forest, Community Forest and predation events to individual grid cells. To avoid ambiguity others ( km ). These forests support diverse mammalian regarding the identity of the predator, respondents were and avian communities. The vegetation is sub-tropical/tem- asked to provide clear descriptions of the species and its perate forest dominated by Pinus spp., Quercus spp. and signs, or distinguish these from images of various carnivores Castanopsis spp. (Shrestha, ). These forests contribute and their pugmarks. We only recorded leopard presence to the provision of drinking water and clean air for the . and/or predation when respondents provided an accurate million inhabitants of Kathmandu district, and are valuable description of the species. In the case of reported depreda- for religious and cultural reasons (SSNP, ). tion of domestic animals, the interviewers recorded infor- mation on the species of domestic animal, count of events and their locations. All interviews were carried out in Methods Nepali.
Interview surveys
Covariates and hypotheses We divided the study area into -km grid cells (Fig. ) and carried out interview surveys in of these cells (sites), to We collated data for a total of five covariates (Table ). We collect information on leopard occurrence and predation determined the relative abundance of dogs and goats (co- on domestic animals. A two-member survey team was variates dog and goat, respectively) during field surveys trained to undertake the interview surveys. The team inter- and derived the other three covariates from remotely sensed viewed – households in each grid cell during October data: normalized difference vegetation index (NDVI; covari- –April . Following Athreya et al. () and Zeller ate ndvi), Euclidean distance from the centre of the grid cell
TABLE 1 List of covariates used to model probabilities of leopard Panthera pardus habitat use (Ψ) and predation on domestic animals (Ψ) in Kathmandu district, Nepal.
Expected influence on Covariates associated with occur- detecting use when true rence of leopards and predation Expected influence on habitat Expected influence on the occupancy state is Ψ Ψ on domestic animals (range) use 1 occurrence of predation 2 1(p1)&2(p2) Distance to forest (0–3.1 km) Leopards are more likely to use Higher predation of domestic Sites close to forest are sites close to forest, which is their animals is expected closer to expected to be associated primary habitat forests with higher detection of leopard presence & predation (p1)(p2) Normalized difference vegetation Grids with greater vegetation Sites with higher vegetation Detection probability of index (including forest & cover will be associated with cover will have higher leopards likely to be higher cultivated land) in human- higher leopard presence predation in grid cells with more dominated landscape vegetation (0.01–0.95) Dog abundance (0–2.5) Leopard use is expected to be Sites with more dogs will have higher in sites with higher relative higher rates of predation abundance of dogs Goat abundance (0–18.6) Habitat use is expected to be Sites with more goats will have higher in sites with higher relative higher rates of predation abundance of goats River length (0–5.0 km) Leopards will extensively use Higher rates of predation are rivers & drainage features, expected in grid cells with which provide cover, & access to greater cumulative length of food sources around rivers because of higher leopard human settlements presence
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to the nearest forest patch (covariate distoforest), and estimated proportion of habitat use and parameter Ψ as the cumulative length of rivers in each grid cell (covariate probability of depredation in sites with habitat use, rather river). We used ArcGIS . (Esri, Redlands, USA) for spa- than occupancy, because the size of the sample unit is tial analyses. small relative to the home range of leopards (MacKenzie We hypothesized that dogs were likely to attract leopards et al., ; Zeller et al., ). We defined three discrete to settlements (Table ), as they are important in the leo- habitat-use and predation states in our detection matrix: un- pard’s diet (Edgaonkar & Chellam, ; Athreya et al., occupied (state ), occupied with no predation on domestic ). However, in grid cells with high dog numbers (be- animals (state ) and occupied with predation on domestic yond a certain threshold) we speculated that leopard pre- animals (state ). For each interview survey, we recorded ‘’ dation on dogs may decline as packs of dogs are known to when no leopard presence was reported, and ‘’ when one chase off leopards and alert people to the felids’ presence or more events of predation on domestic animals were re- (Young et al., ; Potgieter et al., ). We counted all ported. We recorded ‘’ when leopard presence was reported dogs within m of surveyed homes and calculated an without mention of depredation. State carries a level of un- encounter rate following Krishna et al. (): certainty: it could either be a correct assignment (leopards present but not preying on domestic animals), or an incor- No. of dogs Index = rect assignment (actual situation is state , but respondent is No. of households surveyed in grid cell unaware of depredation event). Leopards prefer medium-sized prey (Karanth & Sunquist, Our multi-state occupancy model included five para- Ψ ; Hayward et al., ). During interviews, we therefore meters (following Nichols et al., ). is the probability recorded the number of goats kept by respondents. We then of site use by leopards, regardless of whether or not preda- Ψ calculated a goat abundance index as described above for dog tion on domestic animals occurs. is the probability that abundance. We expected high probabilities of leopard pres- depredation occurs, in the event that the site is used by leo- ence and predation on domestic animals in grid cells with pards. The parameter p is the probability of leopard pres- higher goat abundance (Hayward et al., ;Sangay& ence being reported in cases where the true state is , and Vernes, ; Table ). In addition, we predicted that prob- p is the probability of leopard presence being reported abilities of leopard occurrence and predation on domestic an- where the true state is . The parameters p and p address imals would both decline as a function of distance to forest state uncertainty because depredation events may or may edge, because urban and built-up areas provide less suitable not be reported in sites where leopards are present. We also δ cover for leopards (Table ). The NDVI is an indicator of estimated , which is the probability of finding evidence green vegetation (Krishna et al., ), which we used as a for leopard predation on domestic animals in cells where proxy for cover. We predicted that areas with dense vegetation the true state is (leopards are present and predating on cover would be more likely to harbour leopards (Kshettry livestock). et al., ). We also predicted that cells with more vegetation cover would have higher rates of predation on goats and dogs, Data analysis because leopards can remain concealed while stalking or feeding on prey (Table ). Carnivores commonly use water Prior to model-building, we tested for collinearity among the , courses as movement routes (Smith, ), and we thus ex- covariates, and found they were not correlated (r . ). We pected the cumulative length of rivers in a grid cell to posi- adopted a two-step process to model the effects of covariates tively influence habitat use by leopards and predation. We to estimate model parameters (Athreya et al., ). Firstly, we expected higher detection probabilities near forests because sought to explain variation in the detection process by mod- people residing there were more likely to encounter and re- elling distance to forest and NDVI, by building alternate port leopards. We also expected that detectability would be models (covariates modelled singly, additively and a null higher in cells with high vegetation cover as leopard presence model; Table ). In this step, we used a global model for the Ψ would be reported more frequently in such grid cells, because parameters habitat use ( ndvi+dog+goat+river+distoforest)andpre- Ψ we expected greater leopard occurrence in cells with higher dation on domestic animals ( ndvi+dog+goat+river+distoforest). We NDVI (Table ). compared models using the Akaike information criterion adjusted for small sample size (AICc), to determine the optimal detection parameterization, which was retained in Habitat use states and model parameters the next modelling step (Table ). In the second step, we tested our hypotheses about the We used multi-state occupancy models to concurrently test spatial variation in leopard habitat use and predation on do- our hypotheses about the predictors of leopard habitat use mestic animals. For this, we retained the covariate combi- and predation on domestic animals (Nichols et al., ; nation for detection parameters from the best supported Athreya et al., ). We interpret the parameter Ψ as model from the previous step, and tested our hypotheses
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TABLE 2 Model results for detection parameters, p (leopard detection probability) and p (detection probability of predation on domestic animals). Two covariates ndvi and distoforest were modelled with global model Ψ(dog+goat+ndvi+river+distoforest), Ψ(dog+goat+ndvi +river+distoforest).
Model1 AICc2 ΔAICc3 Akaike weight Model likelihood No. of parameters Deviance δ p1(.), p2(distoforest), (.) 516.39 0.00 0.25 1.00 16 476.94 δ p1(.), p2(ndvi+distoforest), (.) 517.37 0.98 0.15 0.61 17 474.87 δ p1(distoforest), p2(.), (.) 517.38 0.99 0.15 0.60 10 494.60 δ p1(distoforest), p2(distoforest), (.) 517.62 1.22 0.13 0.54 17 475.86 δ p1(disstoforest), p2(ndvi+distoforest), (.) 518.24 1.85 0.10 0.39 18 472.61 δ p1(ndvi), p2(distoforest), (.) 518.36 1.97 0.09 0.37 17 475.86 δ p1(ndvi+distoforest), p2(distoforest), (.) 520.61 4.21 0.03 0.12 18 474.97 δ p1(ndvi+distoforest), p2(ndvi+distoforest), (.) 521.31 4.92 0.02 0.08 19 472.45 δ p1(.), p2(ndvi), (.) 521.34 4.94 0.02 0.08 16 481.89 δ p1(ndvi), p2(ndvi), (.) 532.27 5.26 0.01 0.07 17 479.15 δ p1(.), p2(.), (.) 532.27 15.88 0.00 0.00 15 495.79 δ p1(ndvi), p2(.), (.) 532.32 15.92 0.00 0.00 16 492.86 δ p1(distoforest), p2(ndvi), (.) 535.10 18.71 0.00 0.00 17 492.60 δ p1(ndvi+distforest), p2(.), (.) 535.20 18.80 0.00 0.00 17 492.70 δ p1(ndvi+distoforest), p2(ndvi), (.) 536.91 20.52 0.00 0.00 18 491.28
Covariates: distoforest, distance to nearest forest patch; dog, relative abundance of dogs; goat, relative abundance of goats; ndvi, normalized difference vegetation index; river, cumulative length of rivers in a grid cell. Akaike information criterion adjusted for small sample size. Difference in AICc to best performing model.
about factors influencing spatial variation on Ψ and Ψ.We We included covariates for Ψ and Ψ singly, or in additive used a logit link function to assess model parameters as a combinations (see Table for a complete list of models). function of covariates (Mackenzie et al., ). Nineteen Again we evaluated model support using AICc. Analysis alternate models were implemented to test our hypothesis. was carried out in MARK . (White, ).
TABLE 3 Model results for probabilities of leopard habitat use (Ψ) and predation on domestic animals (Ψ), based on a priori hypotheses. For all models, covariates ndvi and distoforest were used to explain variation in detection probability.
Akaike Model No. of Model1 AICc2 ΔAICc3 weight likelihood parameters Deviance Ψ Ψ 1(dog+ndvi), 2(goat+river) 513.68 0.00 0.19 1.00 13 482.89 Ψ Ψ 1(dog+ndvi), 2(goat+dog) 513.96 0.27 0.17 0.87 13 483.17 Ψ Ψ 1(dog+ndvi), 2(goat+ndvi) 514.29 0.60 0.14 0.74 13 483.50 Ψ Ψ 1(dog+goat+ndvi), 2(goat+ndvi) 514.87 1.18 0.10 0.55 14 481.27 Ψ Ψ 1(dog+ndvi), 2(dog+goat+ndvi) 515.50 1.81 0.08 0.40 14 481.90 Ψ Ψ 1(dog+ndvi), 2(dog+goat+river) 515.62 1.93 0.07 0.37 14 482.02 Ψ Ψ 1(distoforest+river+ndvi), 2(goat+ndvi) 516.06 2.37 0.06 0.30 14 482.46 Ψ Ψ 1(dog+dog × dog+ndvi), 2(goat+ndvi) 516.81 3.12 0.04 0.20 14 483.21 Ψ Ψ 1(dog+goat+ndvi), 2(dog+goat+ndvi) 517.20 3.51 0.03 0.17 15 480.72 Ψ Ψ 1(distoforest+river+ndvi), 2(goat+river+ndvi) 517.58 3.89 0.02 0.14 15 481.09 Ψ Ψ 1(dog+goat), 2(dog+goat) 517.67 3.98 0.02 0.13 13 486.88 Ψ Ψ 1(distoforest+river+ndvi+dog), 2(goat+river) 519.83 6.14 0.00 0.04 15 483.34 Ψ 1(distoforest+river+ndvi+dog+goat), 521.31 7.62 0.00 0.02 19 472.45 Ψ 2(distoforest+river+ndvi+dog+goat) Intercept only 521.56 7.87 0.00 0.01 9 501.31 Ψ Ψ 1(distoforest+river+ndvi+dog), 2(dog+goat+ndvi) 521.59 7.90 0.00 0.01 15 485.10 Ψ Ψ 1(distoforest+ndvi), 2(distoforest+ndvi) 523.57 9.88 0.00 0.00 13 492.78 Ψ Ψ 1(river+ndvi), 2(river+ndvi) 523.83 10.14 0.00 0.00 13 493.04 Ψ Ψ 1(distoforest+river), 2(distoforest+ndvi) 524.41 10.72 0.00 0.00 13 493.62 Ψ Ψ 1(distoforest+river+ndvi), 2(distoforest+river+ndvi) 525.38 11.69 0.00 0.00 15 488.89
Covariates: distoforest, distance to nearest forest patch; dog, relative abundance of dogs; goat, relative abundance of goats; ndvi, normalized difference vegetation index; river, cumulative length of rivers in a grid cell. Akaike information criterion adjusted for small sample size. Difference in AICc to best performing model.
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Results parameter Ψ was positively associated with goat abundance ̂ β = . ± SE .. Probability of habitat use with predation We conducted interviews in households in grid cells, increased when the goat encounter rate was . , and fell away covering municipalities within Kathmandu district. Sixty steeply at lower values of this covariate (Fig. ). Relative per cent of the respondents were farmers primarily depen- abundance of dogs and normalized difference vegetation dent on agriculture, and others were engaged in livelihoods index were positively associated with probability of livestock ̂ such as business and service in government institutions or depredation in cells with leopard site use β = . ± SE .; ̂ private enterprises. Mean land holding size of respondents β = . ± SE ., although there was considerable uncer- – . ha (range . ha), and % of respondents identified tainty in these estimates. River length and distance to forest themselves as middle class, with a monthly income of USD did not have any discernible effect on the parameters Ψ and – – . Interviewees were aged years, with a mean Ψ based on these data. age of years. Seventy-eight per cent of interviewees were men and % women. The naïve probability of leopard habitat use was % and Discussion predation on domestic animals was recorded in % of the surveyed cells. Respondents reported leopard predation on Our finding that leopards occur extensively in areas with goats (% of respondents) and dogs (%), but no human high human densities in Kathmandu district is of signifi- deaths or injuries. The reported losses resulting from depre- cance for a number of reasons. Firstly, it establishes that dation of goats were valued at a total of USD ,. this leopard population is well adapted to exploiting farm- Amongst candidate models to assess the influence of lands and human settlements in a densely populated land- covariates on detection probabilities associated with p (leo- scape, with near-ubiquitous occurrence over the study area. pard detection probability when true state is )andp (detec- Our findings corroborate those of Athreya et al. () from tion probability when true state is ), eight models (with Maharashtra state in India, where leopards move extensively combination of covariates distance to forest and NDVI) within an agricultural landscape. We note, however, that the accumulated . % Akaike weight (Table ). Because both Kathmandu valley is more densely populated than areas distance to forest and NDVI covariates appeared in the such as rural Maharashtra. Secondly, we ascertained that eight best supported models, the model carried forward c. % of the area around Kathmandu city is subject to vary- into the next step of analysis included these covariates ing levels of leopard predation on domestic animals (Fig. ). (additively) to address heterogeneity in p and p.Nosingle Remarkably, despite the widespread distribution of leo- model was particularly well supported (Table ). The model pards, attacks on people are infrequent. Our findings, how- averaged estimate of p was . ± SE . and p was . ± ever, do suggest that leopards may use both adjacent forests SE ..Themodelaveragedestimateforδ (probability of and peri-urban habitats, where they prey upon domestic finding evidence of leopard predation on domestic animals) animals and gain access to additional food resources. This was . ± SE .. leads us to conjecture that leopards have a predilection to Of candidate models run to estimate leopard habitat spend longer periods in these peri-urban areas. use with and without predation on domestic animals (Ψ We found that the relationship between leopard habitat and Ψ), no single model was particularly well supported. use and relative abundance of dogs is variable. Although The best model, Ψ(dog+ndvi), Ψ(goat+river), had %of dogs attract leopards (Athreya et al., ), they may also the overall model weight. The additive covariates relative repel leopards. Dogs in Kathmandu occur in a density of abundance of dogs and NDVI were associated with Ψ animals/ha (Kakati, ) and our observations indicate that in the six best supported models (which cumulatively ac- they generally form packs and live in clusters. An expla- counted for . % of the overall support). For the param- nation for the possible ambiguity in the relationship between eter Ψ, the relative abundance of goats was associated leopard habitat use and relative abundance of dogs could be with these top six models, in combination with one or that dog packs may detect and repel leopards away from more of the other covariates (dog abundance, river length human settlements. In addition, reporting of predation on and NDVI; Table ). The model averaged estimate (across stray dogs may be incomplete. More research is required to all models) of Ψ was . +SE ., indicating near- obtain robust, spatially explicit estimates of dog and leopard ubiquitous leopard presence across the study area. The cor- populations in the study area, and examine the interactions of responding estimate for Ψ was . +SE ., indicating these species in peri-urban areas. that depredation on domestic animals occurs in many Our research raises an important question: if leopards are cells with leopard use. widely distributed and frequently predate on dogs and goats, Given extensive leopard occurrence, none of the covari- why are encounters between people and leopards rare in the ates in our models had statistically significant influence on Kathmandu valley? This is in contrast to some other areas of the parameter Ψ (MacKenzie et al., ; Table ). The the Himalayas (Naha et al., ), where people have
Oryx, Page 6 of 10 © The Author(s), 2021. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605320000423 Downloaded from https://www.cambridge.org/core. IP address: 170.106.35.93, on 26 Sep 2021 at 14:32:03, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0030605320000423 https://www.cambridge.org/core/terms Downloaded from Oryx ae7o 10 of 7 Page , https://www.cambridge.org/core © h uhrs,22.Pbihdb abig nvriyPeso eafo an lr nentoa doi:10.1017/S0030605320000423 International Flora & Fauna of behalf on Press University Cambridge by Published 2021. Author(s), The . https://doi.org/10.1017/S0030605320000423 TABLE 4 Estimates of β-coefficient values (with standard errors) for individual covariates associated with probabilities of leopard presence (Ψ) and predation on domestic animals (Ψ) for models. For all models, covariates ndvi and distoforest were fixed with detection probabilities p and p. . IPaddress: Ψ1 Ψ1 Ψ1 Ψ1 Ψ1 distoforest 1 Model Ψ1 (.) ± SE dog ± SE goat ± SE ndvi ± SE river ± SE ± SE Ψ2 (.) ± SE Ψ2 dog ± SE Ψ2 goat ± SE Ψ2 ndvi ± SE Ψ2 river ± SE 170.106.35.93 Ψ1(dog+ndvi), 3.45 ± 1.65 −1.02 ± 0.69 2.31 ± 1.34 0.78 ± 0.56 2.28 ± 0.92 −0.67 ± 0.48 Ψ2 (goat+river) Ψ1(dog+ndvi), 3.18 ± 1.27 −1.02 ± 0.63 2.19 ± 1.08 1.09 ± 0.59 0.70 ± 0.57 2.32 ± 0.93
, on Ψ2(goat+dog) Ψ ± − ± ± ± ± ± 26 Sep2021 at14:32:03 1(dog+ndvi), 3.75 2.05 1.09 0.79 2.36 1.51 0.84 0.59 2.29 0.97 0.54 0.49 Ψ2(goat+ndvi) Ψ1(dog+goat+ndvi), 4.05 ± 2.03 1.51 ± 1.21 0.90 ± 0.90 −1.33 ± 0.99 2.38 ± 1.41 4.47 ± 2.06 1.99 ± 0.91 Ψ2(goat+ndvi) Ψ1(dog+ndvi), 3.34 ± 1.47 −1.04 ± 0.67 2.25 ± 1.19 0.93 ± 0.59 0.69 ± 0.56 2.21 ± 0.93 0.53 ± 0.48 Ψ2(dog+goat+ndvi) Ψ ± − ± ± ± ± ± − ± , subjectto theCambridgeCore termsofuse,available at 1(dog+ndvi), 3.31 1.45 1.01 0.65 2.27 1.20 0.83 0.56 0.49 0.53 2.24 0.89 0.54 0.51 Ψ2(dog+goat+river) Ψ1(distoforest+river+ndvi), 3.41 ± 1.98 0.53 ± 0.65 −0.04 ± 0.72 2.67 ± 2.69 4.13 ± 3.36 6.75 ± 4.76 2.47 ± 1.45 Ψ2(goat+ndvi) Ψ1(dog+dog × dog+ndvi), 3.43 ± 1.75 −1.36 ± 1.05 2.29 ± 1.30 0.86 ± 0.59 2.26 ± 0.98 0.52 ± 0.49 Ψ2(goat+ndvi) Ψ1(dog+goat+ndvi), 3.36 ± 1.37 −0.99 ± 0.65 1.29 ± 1.28 1.87 ± 1.07 0.94 ± 0.59 0.74 ± 0.57 2.07 ± 0.91 0.49 ± 0.47
Ψ2(dog+goat+ndvi) peri The Ψ1(distoforest+river+ndvi), 3.16 ± 1.88 0.58 ± 0.62 −0.02 ± 0.66 2.44 ± 2.60 3.90 ± 2.95 6.62 ± 4.39 2.23 ± 1.42 −0.97 ± 0.79 Ψ2(goat+river+ndvi) ‐ Ψ1(dog+goat), 2.41 ± 0.97 −0.53 ± 0.60 1.75 ± 1.16 1.21 ± 0.74 0.72 ± 0.71 2.06 ± 1.05 7 Kathmandu of leopards urban Ψ2(dog+goat) Covariates: distoforest, distance to nearest forest patch; dog, relative abundance of dogs; goat, relative abundance of goats; ndvi, normalized difference vegetation index; river, cumulative length of rivers in a grid cell. 8 A. Bista et al.
FIG. 2 Relationship between occurrence of predation (Ψ) and relative abundance of goats. The black dots and line show the mean value and the grey area represents the % CI.
frequently been injured or killed by leopards. We posit that
most settlements within our study area have amenities such FIG. 3 (a) Probability of habitat use of leopard in peri-urban as street lights and toilets within homes, which reduce close Kathmandu within km survey grid cells, and (b) probability of interaction between humans and leopards, even in shared occurrence of predation on domestic animals. These estimates spaces. Odden et al. () reported that leopards adapt are from the best-ranked model Ψ (dog+ndvi), Ψ (goat+river). their behaviour to avoid humans, and predominantly use areas within settlements at night. Leopard habitat use and predation on domestic animals areas where the true state was or ). This is because we in Kathmandu district also needs to be understood in the do not have independent data sources (e.g. from camera context of the ecology of predators and prey in the forests traps or sign surveys) or information to differentiate be- around the city. Forests in the mid-hills of Nepal generally tween more and less reliable observers. False positives in support sparse populations of wild prey (Acharya et al., the data can introduce bias in the parameter estimates ), which may push leopards into human-dominated (Royle & Link, ; Petracca et al., ). We note that habitats where they can predate upon domestic animals our results are therefore preliminary, although it is com- with relative ease (Kabir et al., ). There is no information mon for occupancy surveys using interview data to not on the distribution and abundance of wild prey species of account for false positives, particularly when these are leopards in the Shivapuri-Nagarjun National Park and rapid surveys or studies carried out using modest budgets Kathmandu Forest Division. Carrying out a baseline assess- (Ghoshal et al., ; Srivathsa et al., ). Future studies ment of prey and predator populations in this forest is thus a should build on our initial work by combining sign sur- priority area for future research, to examine the proximate veys or camera trapping with interview data, to account drivers of predation on domestic animals in the Kathmandu for potential false positives. Robust estimates of dog valley. Moreover, expansion of human settlements into wilder- abundance may be derived by rigorous sampling coupled – ness areas increases spatial overlap between people and car- with mark resight models (Punjabi et al., ), in lieu nivores, and the risk of negative interactions (Woodroffe, of encounter rates. ). Our research calls for urban planners to consider these factors when delineating plans for urban development Management and policy recommendations in the Kathmandu valley, to limit encroachment of human settlements into natural habitats. Negative human–leopard interactions in Kathmandu dis- A key limitation of our study is that it does not account trict are an increasing problem. During our study period, for false positives in responses (leopard presence and pre- leopards were captured and removed from three locations dation on domestic animals may have been reported in within urban areas. We anticipate that conflict may be
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exacerbated by increasing human and livestock popula- human-dominated landscapes of India. Conservation Biology, tions and progressive urbanization that may create ecolo- , –. gical traps as the landscape is further fragmented. Thus ATHREYA, V., ODDEN, M., LINNELL, J.D., KRISHNASWAMY,J.& KARANTH, K.U. () Big cats in our backyards: persistence of comprehensive strategies are needed to mitigate conflict. large carnivores in a human dominated landscape in India. We propose a two-pronged approach. Firstly, a framework PLOS ONE, ,e. is required for the systematic monitoring of leopards in the ATHREYA, V., ODDEN, M., LINNELL, J.D., KRISHNASWAMY,J.& area, for which our study can serve as a template. Secondly, KARANTH, K.U. () A cat among the dogs: leopard Panthera a comprehensive conflict mitigation plan should be cre- pardus diet in a human-dominated landscape in western Maharashtra, India. Oryx, , –. ated, including education and awareness programmes, ATHREYA, V., SRIVATHSA, A., PURI, M., KARANTH, K.K., KUMAR, N.S. control of free-ranging dogs (with monitoring to assess &KARANTH, K.U. () Spotted in the news: using media reports any potential unintended adverseeffectssuchasincreased to examine leopard distribution, depredation, and management predation on livestock), measures to prevent attacks on practices outside protected areas in Southern India. PLOS ONE, livestock (e.g. predator-proof corrals), compensation pro- ,e . BARUA, M., BHAGWAT, S.A. & JADHAV,S.() The hidden grammes and rapid response teams to ensure human and dimensions of human–wildlife conflict: health impacts, opportunity animal welfare in conflict-prone areas. These teams must and transaction costs. Biological Conservation, , –. include personnel trained in animal capture and crowd BATEMAN,P.W.&FLEMING, P.A. () Big city life: carnivores in control. Careful deliberation is needed on whether and urban environments. Journal of Zoology, , –. where captured leopards should be translocated (Athreya BECKMANN, J.P. & LACKEY, C.W. ( ) Carnivores, urban landscapes, and longitudinal studies: a case history of black bears. et al., ). Effective conflict mitigation planning and Human–Wildlife Conflicts, , –. implementation of plans will require the collaboration of CBS (CENTRAL BUREAU OF STATISTICS)() National Population various stakeholders including government departments, and Housing Census . Central Bureau of Statistics, Kathmandu, veterinarians, ecologists and community representatives. Nepal. cbs.gov.np [accessed October ]. Ultimately, plans will need to recognize that a strict sepa- DAR, N.I., MINHAS, R.A., ZAMAN,Q.&LINKIE,M.() Predicting – ration of people and leopards may not be feasible in the the patterns, perceptions and causes of human carnivore conflict in and around Machiara National Park, Pakistan. Biological Kathmandu valley, and they must therefore also include Conservation, , –. measures that enable coexistence in shared spaces. DICKMAN, A.J. & MARKER, L.L. () Factors affecting leopard (Panthera pardus) spatial ecology, with particular reference to Acknowledgements We thank the Department of National Parks Namibian farmlands. South African Journal of Wildlife Research, – and Wildlife Conservation of the Government of Nepal for permission , . to carry out this study. We acknowledge the financial support provided EDGAONKAR,A.&CHELLAM,R.( ) Food habit of the leopard, by National Trust for Nature Conservation under IDA project no. Panthera pardus, in the Sanjay Gandhi National Park, Maharashtra, – H6660. We acknowledge the contribution of Sujhav Pun and Mr India. Mammalia, , . Bishwanath for their support in coordination; and Nirmal Magar, ENSERINK,E.&VOGEL,G.( ) The carnivore comeback. Science, – Surendar Magar and Sagar Bhattarai for assistance in field data , . collection. 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