Habitat occupancy of sloth bear Melursus ursinus in Chitwan National Park, Nepal

Factors affecting the occupancy of sloth bear and its detection probability in Parsa-Koshi Complex, Nepal

Understanding factors associated with coexistence of human and wildlife in human-dominated landscapes is crucial for effective species conservation. Among the wildlife species, the sloth bears Melursus ursinus are found both inside and outside the protected areas of Nepal, and with increasing cases of human and bear conflicts in both areas. This highlights the necessity for a comprehensive understanding of anthropogenic and ecological factors that affect the occurrence of sloth bear. The understanding of these factors is important for its coexistence and conservation in human-dominated areas through establishing management and conservation action plan. We studied the sloth bear's occupancy and their coexistence in human-dominated environments with other large predators in the Parsa-Koshi Complex of Nepal using camera traps from December 2022 to March 2023. We identified the occupancy and detection probability of the sloth bear as 0.12 and 0.31, respectively. Our analysis reveals a positive relationship between sloth bear occurrence and the presence of large predators (βpredators = 3.104 ± 0.968), such as tigers (Panthera tigris) and leopards (Panthera pardus), as well as the number of humans detected (βhuman = 1.428 ± 1.216) and canopy cover percentage (βcc = 1.002 ± 0.737). However, the number of livestock detected shows a negative interaction with the occurrence of sloth bears (βlivestock = -2.240 ± 1.467). There was insignificant interaction between sloth bear occupancy and distance to human settlements, roads, and water bodies. These findings underscore the complex dynamics between sloth bears, humans, large predators, and livestock in human-dominated landscapes. To ensure the long-term survival of sloth bear populations and promote species conservation, comprehensive conservation strategies that account for both ecological and socio-economic factors are essential.

N-mixture model-based estimate of relative abundance of sloth bear (Melursus ursinus) in response to biotic and abiotic factors in a human-dominated landscape of central India

Reliable estimation of abundance is a prerequisite for a species' conservation planning in human-dominated landscapes, especially if the species is elusive and involved in conflicts. As a means of population estimation, the importance of camera traps has been recognized globally, although estimating the abundance of unmarked, cryptic species has always been a challenge to conservation biologists. This study explores the use of the N-mixture model with three probability distributions, i.e., Poisson, negative binomial (NB) and zero-inflated Poisson (ZIP), to estimate the relative abundance of sloth bears (Melursus ursinus) based on a camera trapping exercise in Sanjay Tiger Reserve, Madhya Pradesh from December 2016 to April 2017. We used environmental and anthropogenic covariates to model the variation in the abundance of sloth bears. We also compared null model estimates (mean site abundance) obtained from the N-mixture model to those of the Royle-Nichols abundance-induced heterogeneity model (RN model) to assess the application of similar site-structured models. Models with Poisson distributions produced ecologically realistic and more precise estimates of mean site abundance (λ = 2.60 ± 0.64) compared with other distributions, despite the relatively high Akaike Information Criterion value. Area of mixed and sal forest, the photographic capture rate of humans and distance to the nearest village predicted a higher relative abundance of sloth bears. Mean site abundance estimates of sloth bears obtained from the N-mixture model (Poisson distribution) and the RN model were comparable, indicating the overall utility of these models in this field. However, density estimates of sloth bears based on spatially explicit methods are essential for evaluating the efficacy of the relatively more cost-effective N-mixture model. Compared to commonly used index/encounter-based methods, the N-mixture model equipped with knowledge on governing biotic and abiotic factors provides better relative abundance estimates for a species like the sloth bear. In the absence of absolute abundance estimates, the present study could be insightful for the long-term conservation and management of sloth bears.

Spatio-Temporal Patterns and Source-Dispersion Modeling Towards Sloth Bear–Human Conflict Management in Central India

The impact of humans on biodiversity, in the form of the spatially extensive occurrence of humans and subsequent habitat degradation, leads to negative interactions between humans and native wildlife. However, knowledge of the spatial and temporal interface between humans and wildlife is necessary to understand the root cause of such negative interactions, yet considerably understudied in the context of human-dominated landscapes in south and south-eastern Asia. We took this opportunity, gaining insights on seasonal spatial interaction and spatio-temporal overlap between sloth bears (Melursus ursinus) and humans, and subsequently predicted the conflict source sites and dispersion (i.e., hotspots) based on the robust geographic profiling (GP) method in the Sanjay Tiger Reserve (STR), a human-dominated landscape of central India. Detection data of sloth bear and human were obtained from camera trap survey conducted for two years (2017–2018) and records of conflict incidents (2009–2019) were collected from forest department. We found that sloth bears can co-occur with humans independently of seasons, based on occupancy models. However, during summer, higher temporal overlap (Δ4 = 0.46) and lower spatial overlap (0.31) were observed between sloth bears and humans. Contrastingly, lower temporal overlap (Δ4 = 0.29) and higher spatial overlap (0.44) were observed between the same two during winter. The activity patterns of sloth bears and humans differed significantly across seasons and within the same species in different seasons. Our findings indicated that significant changes in human activity, especially during summer, increased the likelihood of sloth bear-human interaction and subsequent conflict incidents. The mapping of conflict source and dispersion (with high accuracy) also predicted a greater probability of conflict during summer, compared to winter, and thus showed the successful application of GP models in this field. Also, camera trap data alone were able to predict the occurrence of hotspots, demonstrating the use of camera trap records in the successful prediction of source-dispersion of conflict. This study would be useful for decision-makers to alleviate sloth bear–human conflict based on insights on seasonal variation of spatio-temporal overlap between the two and direct conservation efforts accordingly.