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

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.

Predicting Suitable Distribution for an Endemic, Rare and Threatened Species (Grey-Shanked Douc Langur, Pygathrix Cinerea Nadler, 1997) Using Maxent Model

“…By now, many species are threatened with extinction and face habitat loss. Habitat loss and a number of the individuals remaining are two greatest concerns for species conservation (Nazeri et al, 2012). In the case of rare primate species like GSDL, the greatest threats are habitat loss and hunting (Vu et al, 2008;Nguyen et al, 2012).…”

“…Lacking species distributional data has caused many difficulties in management and conservation of wildlife (Nazeri et al, 2012), especially rare species. Understanding the most basic requirements of living habitats and distribution of each species is a top priority for conservation programs and action plans.…”

“…Understanding the most basic requirements of living habitats and distribution of each species is a top priority for conservation programs and action plans. Species distribution modelling using an ecological niche model is an instrument that can be used to help us understand more about the distribution of species Nazeri et al, 2012). However, modelling the potential distribution or suitable habitat of a species requires a wide variety of complex data coming from environmental studies, natural resources studies, biodiversity assessment and detailed studies of species (Franklin and Miller, 2009;Sarma et al, 2015).…”

Should species distribution models use only native or exotic records of existence or both?

“…The level of suitability of each cell of the grid is expressed by the environmental variables' functions of the specific cell (Phillips et al, 2006). Absence data is not a requirement, and conversely the model incorporates background environmental variables of the complete study area, with a regularization function preventing predictions from over-fitting of data (Nazeri et al, 2012;Peterson et al, 2007;Phillips et al, 2006). MaxEnt allows the incorporation of continuous and categorical variables, estimating a resource's selection probability, by establishing the distribution of maximum entropy, with a proviso that the anticipated value of every feature equates with its empirical average (Phillips, 2005).…”

Expansion of Protected Areas under Climate Change: An Example of Mountainous Tree Species in Taiwan

“…SDMs are essential tools for both predicting the impacts of climatic change on biodiversity, and designing conservation plans and policies which best mitigate the effects of climate change [26]. Recent notable examples are by [19,20,[27][28][29][30][31][32][33]. However, it is recognized that there are significant limitations in projecting future species distribution using SDMs [34,35].…”