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Predictive Modeling and Mapping of Malayan Sun Bear ('Helarctos malayanus') Distribution Using Maximum Entropy

  • M Nazeri
  • , K Jusoff
  • , N Madani
  • , A R Mahmud
  • , A R Bahman
  • , Lalit Kumar

Research output: Contribution to journal › Article › peer-review

85 Citations (Scopus)

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.
Original languageEnglish
Article numbere48104
Pages (from-to)1-9
JournalPLoS One
Volume7
Issue number10
DOIs
Publication statusPublished - 2012

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Wildlife and Habitat Management

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