Predictive modeling and mapping of Malayan Sun Bear (Helarctos malayanus) distribution using maximum entropy.

Area of Science:

• Ecology and Conservation Biology
• Biodiversity Informatics
• Geographic Information Systems (GIS)

Background:

• Species distribution models (SDMs) are crucial for mapping habitats, especially for poorly documented species in undersampled regions like the tropics.
• The Malayan Sun Bear (Helarctos malayanus) is a vulnerable species with limited distribution data in Peninsular Malaysia.
• Maximum Entropy (MaxEnt) is an effective SDM that requires minimal occurrence data for calibration.

Purpose of the Study:

• To utilize the MaxEnt model to delineate the potential distribution of the Malayan Sun Bear in Peninsular Malaysia.
• To identify critical environmental and bioclimatic variables influencing the sun bear's habitat suitability.
• To assess the adequacy of current protected areas in conserving potential sun bear habitats.

Main Methods:

• Application of the Maximum Entropy (MaxEnt) modeling technique.
• Analysis of bioclimatic variables and habitat characteristics relevant to sun bear distribution.
• Spatial analysis of predicted suitable habitats against existing protected area networks.

Main Results:

• MaxEnt modeling revealed that Malayan Sun Bear distribution is associated with tropical evergreen forests but exists at the marginal limits of bioclimatic variables.
• A significant portion of the predicted suitable habitat for sun bears is currently outside protected areas in Peninsular Malaysia.
• The study highlights the sensitivity of sun bear habitats to bioclimatic thresholds.

Conclusions:

• Current protected area networks are insufficient to encompass the majority of potential Malayan Sun Bear habitats.
• Future threats including climate change, forest degradation, and illegal hunting pose severe risks to the Malayan Sun Bear population.
• Urgent conservation strategies are needed to address habitat protection and mitigate anthropogenic threats.