文献类型：期刊文献

英文题名：Modelling the effects of topographic heterogeneity on distribution of Nitraria tangutorum Bobr. species in deserts using LiDAR-data

作者：Zhou, Huoyan[1,2] Feng, Linyan[3] Fu, Liyong[3] Sharma, Ram P.[4] Zhou, Xiao[5] Zhao, Xiaodi[2,6]

第一作者：Zhou, Huoyan

通信作者：Zhao, XD[1];Zhao, XD[2]

机构：[1]Yunnan Univ, Sch Ecol & Environm Sci, Kunming 650031, Yunnan Province, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry Policy & Informat, Beijing 100091, Peoples R China;[3]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[4]Tribhuvan Univ, Inst Forestry, Kathmandu 44600, Nepal;[5]Int Ctr Bamboo & Rattan, Key Lab Natl Forestry & Grassland Adm, Beijing 100091, Peoples R China;[6]Univ British Columbia, Fac Forestry, Vancouver, BC V6T 1Z4, Canada

年份：2023

卷号：13

期号：1

外文期刊名：SCIENTIFIC REPORTS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001052937600063)】；

基金：AcknowledgementsWe thank the 14th Five-Year Plan Pioneering Project of High Technology Plan of the National Department of Technology under Grant(Grant No. 2021YFD2200405), and the National Natural Science Foundation of China (Grant Nos. 31470641, 31300534, and 31570628) for financial support.

语种：英文

摘要：Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.