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HABITAT PREFERENCE OF THE SRI LANKAN SLOTH BEAR (Melursus ursinus inornatus) IN RAINY SEASON USING OCCUPANCY MODELING IN WILPATTU NATIONAL PARK, SRI LANKA

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dc.contributor.author Hippala, H. M. U. K.
dc.contributor.author Tharinduni, W. A. L.
dc.contributor.author Anawarathna, M. A. D. C. K.
dc.contributor.author Jayasekara, E. G. D. P.
dc.contributor.author Mahaulpatha, W. A. D.
dc.date.accessioned 2025-12-03T06:49:24Z
dc.date.available 2025-12-03T06:49:24Z
dc.date.issued 2025
dc.identifier.uri http://repository.ou.ac.lk/handle/94ousl/3809
dc.description.abstract The study focused on the endangered Sri Lankan sloth bear (Melursus ursinus inornatus), assessing its habitat preferences through occupancy modeling to improve target conservation efforts in protected areas. The study was conducted in Wilpattu National Park from September 2024 to April 2025 during the wet season. Twelve passive infrared camera traps were installed using a systematic-random sampling method and relocated every 1.5 months. Data on sloth bear presence/absence and habitat variables, including vegetation, physical, and food abundance covariates, were collected. Occupancy was analyzed using a likelihood-based method, with detection histories recorded as binary values ('1' for presence, '0' for absence), assuming camera trap station independence and no animal movement between stations. Logistic regression identified significant covariates, and highly collinear ones (r > 2) were excluded to avoid overfitting. Data analysis was performed using the PRESENCE software, where detection histories were combined into single species models. Multiple models incorporating various covariates were developed to assess their impact on occupancy. Model selection was based on delta AIC (dAIC), with model-averaged parameters used to estimate occupancy and detection probabilities. Occupancy probabilities for different habitat types were calculated and visualized using R Studio 4.5.0. The occupancy probability of sloth bears was highest in dry mixed evergreen forests (0.93) and tropical thorn forests (0.68), with grasslands showing the lowest probability (0.30). The best-fitting model for occupancy had an AIC weight of 0.11, with a model-averaged occupancy probability of 0.79, compared to a naïve estimate of 0.49. Main factors influencing sloth bear occupancy include stem density>10cm, litter depth, termite mound density, and fruiting tree density, all of which positively impact occupancy. The negative impact of distance to water bodies highlights the importance of key habitat features for conservation. Focusing on areas with essential resources, such as water and food, can improve habitat management and ensure the long-term survival of sloth bears. en_US
dc.language.iso en en_US
dc.publisher The Open University of Sri Lanka en_US
dc.subject camera trapping en_US
dc.subject occupancy modeling en_US
dc.title HABITAT PREFERENCE OF THE SRI LANKAN SLOTH BEAR (Melursus ursinus inornatus) IN RAINY SEASON USING OCCUPANCY MODELING IN WILPATTU NATIONAL PARK, SRI LANKA en_US
dc.type Article en_US


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