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

Abstract

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.

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

“…We were interested in this relationship between human occurrence and sloth bear abundance as a matter of concern regarding the possible negative interactions between humans and sloth bears. However, to cope with extensive human pressure in STR, sloth bears have shown a fine-scale seasonal spatio-temporal segregation ( Chaudhuri et al, 2022 ). On the other hand, sloth bears avoided areas close to villages in STR, which is in agreement with previous studies ( Santhanakrishnan et al, 2015 ; Puri et al, 2015 ; Paudel et al, 2022 ; Pokharel et al, 2022 ).…”

Investigation of Air Quality in Medical Centers in Different Places in Basra Province, South of Iraq

“…Numerous indoor VOCs may worsen IAQ by causing sensory reactions such as odor discomfort and eye and airway irritation (Berglund andLindvall, 1990, WHO, 1989) A wide range of different emission sources, such as building-related materials including furniture and equipment (Levin, 1992), consumer and domestic products, and other items, is the source of VOCs. Depending on spatial and temporal patterns, some sources, including human activities (Hernandez et al, 2020;Chaudhuri et al, 2022). Particles (PM) are classified as PM10 (respirable particles with a diameter of 10 µg.…”