基于MaxEnt模型的干巴菌云南适生区预测

Prediction of Suitable Habitat of Thelephora ganbajun in Yunnan Based on MaxEnt Model

【目的】明确干巴菌在云南的适生区,并探讨未来气候变化对其分布及生境适宜性的影响。【方法】采用主成分分析法对气候因子、土壤因子进行降维处理,将筛选后的生态因子输入最大熵(maximum entropy,MaxEnt)模型,对干巴菌适生区进行预测,使用刀切法(Jackknife)和响应曲线确定影响物种分布的关键生态因子和适宜阈值范围;采用ArcGIS对预测结果进行空间统计分析和适生等级划分,研究未来气候条件下干巴菌分布范围的变化趋势。【结果】MaxEnt模型训练集和测试集的受试者工作特征曲线下面积分别为0.884和0.911,表明模型预测结果可靠。刀切分析结果显示:年降水量、等温性和坡度是影响干巴菌分布最为关键的因子。未来气候变化将影响干巴菌的分布,与当前相比,在SSP126情景下,21世纪末(2090s)的干巴菌云南适宜生境丧失和新增面积分别为1.09×10^(4)和2.60×10^(3)km^(2);在SSP370情景下,丧失和新增面积分别为1.21×10^(4)和5.20×10^(3)km^(2)。【结论】未来气候变化将导致云南境内的干巴菌适生区面积减小,其中滇中地区受气候变化的影响最为严重。

[Purpose]To clarify the suitable habitat of Thelephora ganbajun in Yunnan,and to explore the effects of future climate change on the distribution and habitat suitability of this species.[Methods]The dimension of soil and climate components was reduced using principal component analysis,and the selected ecological factors were input into the maximum entropy(MaxEnt)model to predict suitable habitat of T.ganbajun.Knife cutting method(Jackknife)and response curve were used to identify the key ecological factors and suitable threshold range influencing species distribution.ArcGIS was used to carry out spatial statistical analysis and fitness classification,and to study the changing trend of species distribution range under future climatic conditions.[Results]The area under curve(AUC)of the training set and test set of the MaxEnt model was 0.884 and 0.911,respectively.Jackknife analysis showed that annual precipitation,isothermality and slope were the key factors affecting the species distribution of T.ganbajun.The distribution of the species would be affected by climate change in the future.Compared to the present,by the 21st century(2090s),under the SSP126 scenario,the suitable habitat loss and the new area of T.ganbajun in Yunnan was 1.09×10^(4)and 2.60×10^(3)km^(2),respectively;under the SSP370 scenario,the loss and the new area of suitable habitats for T.ganbajun was 1.21×10^(4)km^(2)and 5.20×10^(3)km^(2),respectively.[Conclusion]Future climate change will result in a reduction of the suitable area for T.ganbajun in Yunnan,with the central Yunnan region being the most severely affected by climate change.