Spatial conservation prioritization for dominant tree species of Chinese forest communities under climate change
Climate change is likely to threaten forests in future. Because dominant tree species (DTS) play central roles in stabilizing forest ecosystems, to effectively protect forests, we need to pay more attention to the protection of DTS. Furthermore, we need to integrate potential impacts of climate change into conservation efforts of DTS for improving forest protection. We utilized species distribution modeling, coupled with conservation planning, to establish climate-informed conservation prioritization for 136 taxa of DTS in three forest types (broad-leaved forests, mixed broadleaf-conifer forests, and coniferous forests) in China. We considered both current and future distributions and assessed the ability of existing nature reserves in China to protect forests based on these DTS. Regions with the highest climate-informed conservation prioritization were distributed in the southern, southwestern, and northeastern regions of China. There was a small gap between existing nature reserves and predicted conservation prioritization areas for conserving forests: the proportions of overlap between existing reserves and areas prioritized under climate change scenarios were 87.8, 95.7, and 80.4% for broad-leaved forests, mixed broadleaf-conifer forests, and coniferous forests, respectively. Even so, we need to increase the number and/or area of nature reserves to protect coniferous forests in Tibet, Sichuan, and Yunnan, and broad-leaved forests in Guizhou, Guangxi, Hu’nan, Yunnan, and Sichuan. Our results demonstrate the importance of conservation planning under climate change, taking both current and future distributions of plant species into consideration. Nature reserves should develop different management strategies for different forest types.
We thank three anonymous reviewers for their valuable comments on an earlier version of this manuscript. This research was supported by National Key R & D Program of China (2016YFC1201100), Fundamental Research Funds for the Central Non-profit Research Institution of CAF (CAFYBB2014ZD001) and NSFC (31570413).
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