Mechanistically simulating the effects of climate change to identify conservation hotspots and reproduction potential for an endangered species

Abstract

Mechanistic approaches have advantages over correlative models for predicting climate change impacts on species currently residing in suboptimal habitat, where anthropogenic induced range contraction reduces the performance of correlative models and results limit contribution to conservation. Here, we combined physiological, behavioral, morphological, ecological and environmental data to simulate the climate change effects on the distribution and reproduction potential (RP) of one of the world's rarest primates, the Hainan gibbon (Nomascus hainanus). Our simulations showed that the only remnant population of this species is currently located outside its stable suitable area with 3 months of cold stress in Hainan Tropical Rainforest National Park, China. The RP of the current home ranges will increase, while the stable suitable area of the Hainan gibbon may increase first and then decline as climate warms due to reduction in cold stress followed by an increase in heat stress. The sharp population decline in 1983–1984 was associated with a period of predicted elevated cold stress, although their causal relationship is unclear. Our novel approach explores climate impacts on the populations' persistence rather than just individual survival, and we recommend the areas with RP > maximum RP × 30 % and without heat stress could be characterized as conservation hotspots. This study showed the feasibility of using biophysical modeling to generate useful information for endangered species, when empirical data are lacking and correlative models may be insufficient.