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Predictive Modeling and Mapping of Malayan Sun Bear (Helarctos malayanus) Distribution Using Maximum Entropy
Authors:Mona Nazeri  Kamaruzaman Jusoff  Nima Madani  Ahmad Rodzi Mahmud  Abdul Rani Bahman  Lalit Kumar
Institution:1. Faculty of Forestry, Univesiti Putra Malaysia (UPM), Selangor, Malaysia.; 2. Faculty of Engineering, Universiti Putra Malaysia (UPM), Selangor, Malaysia.; 3. Faculty of Veterinary Medicine, Universiti Putra Malaysia (UPM), Selangor, Malaysia.; 4. Ecosystem Management, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.; California State University Fullerton, United States of America,
Abstract:One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt) is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus) in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear’s population.
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