文献类型：期刊文献

英文题名：Modelling the spatial pattern of biodiversity utilizing the high-resolution tree cover data at large scale: Case study in Yunnan province, Southwest China

作者：Liu, Shiliang[1] Dong, Yuhong[2] Sun, Yongxiu[1] Li, Junran[3] An, Yi[1] Shi, Fangning[1]

第一作者：Liu, Shiliang

通信作者：Liu, SL[1]

机构：[1]Beijing Normal Univ, Sch Environm, State Key Lab Water Environm Simulat, Beijing 100875, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry, Key Lab Tree Breeding & Cultivat State Forestry A, Beijing 100091, Peoples R China;[3]Univ Tulsa, Dept Geosci, 441 South Gary, Tulsa, OK 74104 USA

年份：2019

卷号：134

起止页码：1-8

外文期刊名：ECOLOGICAL ENGINEERING

收录：;EI(收录号：20191906903499);Scopus(收录号：2-s2.0-85065248655);WOS:【SSCI(收录号:WOS:000468733400001)，SCI-EXPANDED(收录号:WOS:000468733400001)】；

基金：This study was funded by the National Natural Sciences Foundation of China (Grant No. 41571173) and National Key Research and Development Project (Grant No. 2016YFC0502103).

语种：英文

外文关键词：Biodiversity; Influencing factors; Linear regression analysis; Geographically Weighted Regression (GWR); Yunnan province

摘要：Explicit biodiversity level at large spatial scale is often indicated by species richness. The spatial variability of species richness has been postulated to be related with influencing factors such as climate, habitat and human activities using many geostastical methods. Understanding the relationship between species richness and its influencing factors is of critical importance for its conservation. As tree cover data with high resolution can reflect the terrestrial habitat with environment, its efficiency for modelling spatial pattern of biodiversity was investigated in this study. The spatial distribution of tree cover and its influencing factors in Yunnan province, and the relationship between tree cover and species richness of mammals and birds were analyzed by linear regression method and Geographically Weighted Regression (GWR) model. The results showed that tree cover in this study region exhibited a substantially spatial heterogeneity, which was affected by human activities, topography and climate. Linear regression analysis showed that tree cover was significantly correlated with the species richness of mammals and birds. The explanatory power (local R-2) of GWR model between tree cover and species richness of mammals and birds showed great spatial variability. The predicted spatial distribution of species richness of mammals and birds was consistent with the actual observed values. Our study revealed that the GWR model provides local details of spatial variation in species richness of mammals and birds. These results will be helpful to understand the impact of tree cover on variation of species richness of mammals and birds under global change and will be of theoretical significance for better conservation and management of biodiversity.