A New Tool for Exploring Climate Change Induced Range Shifts of Conifer Species in ChinaReportar como inadecuado




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It is inevitable that tree species will undergo considerable range shifts in response to anthropogenic induced climate change, even in the near future. Species Distribution Models SDMs are valuable tools in exploring general temporal trends and spatial patterns of potential range shifts. Understanding projections to future climate for tree species will facilitate policy making in forestry. Comparative studies for a large number of tree species require the availability of suitable and standardized indices. A crucial limitation when deriving such indices is the threshold problem in defining ranges, which has made interspecies comparison problematic until now. Here we propose a set of threshold-free indices, which measure range explosion I, overlapping O, and range center movement in three dimensions Dx, Dy, Dz, based on fuzzy set theory Fuzzy Set based Potential Range Shift Index, F-PRS Index. A graphical tool PRS Chart was developed to visualize these indices. This technique was then applied to 46 Pinaceae species that are widely distributed and partly common in China. The spatial patterns of the modeling results were then statistically tested for significance. Results showed that range overlap was generally low; no trends in range size changes and longitudinal movements could be found, but northward and poleward movement trends were highly significant. Although range shifts seemed to exhibit huge interspecies variation, they were very consistent for certain climate change scenarios. Comparing the IPCC scenarios, we found that scenario A1B would lead to a larger extent of range shifts less overlapping and more latitudinal movement than the A2 and the B1 scenarios. It is expected that the newly developed standardized indices and the respective graphical tool will facilitate studies on PRS-s for other tree species groups that are important in forestry as well, and thus support climate adaptive forest management.



Autor: Xiaojun Kou, Qin Li, Carl Beierkuhnlein, Yiheng Zhao, Shirong Liu

Fuente: http://plos.srce.hr/



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