• Xinping Ye, Xiaoping Yu, Changqing Yu, Aletai Tayibazhaer, Fujun Xu, Andrew K Skidmore, and Tiejun Wang.
• College of Life Sciences, Shaanxi Normal University, Xi'an 710119, China; Research Center for UAV Remote Sensing, Shaanxi Normal University, Xi'an 710119, China. Electronic address: yexinping@snnu.edu.cn.
• Sci. Total Environ. 2018 Jan 15; 612: 775-787.

AbstractDryland biodiversity plays important roles in the fight against desertification and poverty, but is highly vulnerable to the impacts of environmental change. However, little research has been conducted on dual pressure from climate and land cover changes on biodiversity in arid and semi-arid environments. Concequntly, it is crutial to understand the potential impacts of future climate and land cover changes on dryland biodiversity. Here, using the Chinese Altai Mountains as a case study area, we predicted the future spatial distributions and local assemblages of nine threatened mammal species under projected climate and land cover change scenarios for the period 2010-2050. The results show that remarkable declines in mammal species richness as well as high rates of species turnover are seen to occur across large areas in the Chinese Altai Mountains, highlighting an urgent need for developing protection strategies for areas outside of current nature reserve network. The selected mammals are predicted to lose more than 50% of their current ranges on average, which is much higher than species' range gains (around 15%) under future climate and land cover changes. Most of the species are predicted to contract their ranges while moving eastwards and to higher altitudes, raising the need for establishing cross-border migration pathways for species. Furthermore, the inclusion of land cover changes had notable effects on projected range shifts of individual species under climate changes, demonstrating that land cover changes should be incorporated into the assessment of future climate impacts to facilitate biodiversity conservation in arid and semi-arid environments.Copyright © 2017 Elsevier B.V. All rights reserved.

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