A lemur’s guide to biophysical modelling

Date & time

4–5pm 5 December 2018


Eucalyptus Seminar Room (S2.05), Level 2, RN Robertson Building (46), ANU


Eleanor Stalenberg, Foley Group, RSB, ANU


 Audra Johnstone
 6125 2866


Mapping species vulnerability to climate change

Forecasting how a changing climate will affect wildlife is a major goal in scientific research and policy.

Ecologists have traditionally used correlative modelling techniques to predict future species distributions. Biophysical ecology is an alternative approach for forecasting species response to environmental change. Biophysical models apply fundamental laws of physics and chemistry to predict animals’ energetic requirements in the environment. The models can be integrated with spatial environmental data to predict ecological outcomes such as species distribution.

In this presentation, I will discuss the development, validation and ecological application of a biophysical model of my study species, the white-footed sportive lemur (Lepilemur leucopus) of southern Madagascar, that I developed as part of my PhD research. Madagascar supports 23% of the world’s primate diversity and more than 93% of these species are listed on the ICUN red list of threatened species. Habitat loss is the primary driver of population decline, however anthropogenic climate change has emerged as a major additional threat arising from the increased risk of heat stress and dehydration, and the potential for reduced nutritional quality of browse for herbivorous species.

Biophysical models explore the mechanisms driving potential distribution change and species decline and can provide insights into the capacity of species to cope. I developed the model of L. leucopus in an interactive framework that simulates the physiological response of the species to environmental stressors or to changes in biology. I use the model to map the predicted habitat suitability for the species and develop spatial predictions of the risks of extinction in the face of future climatic change. Insights from the model can be used to inform targeted conservation management of the species, such as to identify habitat resources that are critical for survival and highlight areas of conservation priority.

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