北京林业大学学报2017，Vol.39Issue(8)：33-41,9.DOI:10.13332/j.1000--1522.20170002
基于MaxEnt模型的紫椿适生区预测
Distributional change in suitable areas for Toona sureni based on MaxEnt model
摘要
Abstract
Climate change influences biodiversity by altering the habitat of species in ecosystem. Toona sureni is a timber plant with high ecological, economic and medicinal value. It is called"Chinese mahogany" in China with other species in Toona. Understanding the habitat requirements, evaluating habitat quality and predicting the species ' potential habitat are significant for protecting T. sureni, as well as for its protection introduction and plantation. Because of the advantages of using presence-only data and performing well with small sample sizes, incomplete data and gaps, MaxEnt model was employed to simulate the habitat suitability distribution, and the area under the receive operating characteristic curve ( AUC) was used to examine the model ' s accuracy, the larger the AUC is, the more accurate the prediction is. So, based on the distribution of T. sureni in Yunnan Province of southwestern China, the MaxEnt model was used to set up its distributional model of potential habitat. The results showed that the mean training AUC and mean test AUC were 0. 959 and 0. 818, respectively. It is illustrated that the prediction of T. sureni ' s suitable habitats was reliable. Five variables, namely standard deviation of temperature seasonal change, minimum temperature of the coldest month(℃) , mean temperature of the driest quarter (℃) , precipitation of the coldest quarter ( mm ) , range of annual temperature were significant factors determining T. sureni ' s suitable habitat. Habitat suitability for current and future climate warming(2050s,2070s) under scenario RCP2. 6 in Yunnan Province and China was calculated.The study reports the intuitive and quantitative predictions of climate change on T. sureni species ' suitable habitats. The habitat suitability of T. sureni in Yunnan Province and China is predicted to deteriorate with global warming.关键词
紫椿/MaxEnt/全球变暖/适生区变迁Key words
Toona sureni/MaxEnt/global warming/distributional area change分类
农业科技引用本文复制引用
张春华,和菊,孙永玉,李昆..基于MaxEnt模型的紫椿适生区预测[J].北京林业大学学报,2017,39(8):33-41,9.基金项目
林业公益性行业科研专项(201304202). （201304202）
