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

Title
Predictive Modeling and Mapping of Malayan Sun Bear ('Helarctos malayanus') Distribution Using Maximum Entropy
Publication Date
2012
Author(s)
Nazeri, M
Jusoff, K
Madani, N
Mahmud, A R
Bahman, A R
Kumar, Lalit
( author )
OrcID: https://orcid.org/0000-0002-9205-756X
Email: lkumar@une.edu.au
UNE Id une-id:lkumar
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Public Library of Science
Place of publication
United States of America
DOI
10.1371/journal.pone.0048104
UNE publication id
une:11770
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.
Link
Citation
PLoS One, 7(10), p. 1-9
ISSN
1932-6203
Start page
1
End page
9

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