Predicting giant panda habitat with climate data and calculated habitat suitability index (HSI) map

Citations Over TimeTop 11% of 2013 papers

Abstract

Climate data are particularly important in Species Distribution Models (SDMs) that are used for predicting global warming consequences on plant and animal distributions. A number of the plants and animals, especially the endangered species such as the giant panda (Ailuropoda melanolecua), are limited in their scope of distribution due to climate changes. Thus, predicting the habitat quality distribution under climate change is important for protecting these species. In this paper the existing and potential habitats of the giant pandas are used as the study area, the calculated Habitat Suitability Index (HSI) maps in 1989 and 2002, and climate change data in 1989, 2002, 2050 and 2099 from the IPCC are used as the data sources. A multivariable linear regression model for mapping HSI is created with the regressive results in 2002 and 1989. The HSIs of the study area in 2050 and 2099 were then mapped with the model. These maps indicate that, from 2002 to 2050, about 2.64% of the unsuitable habitat in the study area will become suitable, while about 1.5% of the suitable habitat will turn into unsuitable habitat. This leads to an increase of the suitable habitat area on the whole from 2050 to 2099: about 3.43% of the unsuitable habitat will become suitable, while about 6.59% of the suitable habitat will turn into unsuitable habitat, which leads to a decrease of the suitable habitat area on the whole. From the suitable habitat distribution, it can be seen that the suitable habitat of giant pandas gradually moves north under projected global climate change. Copyright © 2013 Royal Meteorological Society

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