基于MaxEnt模型的中国欧洲山杨林潜在分布预测

Prediction of Potential Distribution of Populus tremula Forests in China Based on the MaxEnt Model

摘要: 为明确影响欧洲山杨林分布的主导环境因子，量化不同时期的潜在适生区，本研究借助MaxEnt模型与ArcGIS空间分析技术，融合我国境内910个欧洲山杨林点位及生物气候数据，对其在当前及4个未来时期的潜在适生区进行预测分析。结果表面，MaxEnt模型受试者工作特征曲线下面积(Area under the curve, AUC)值为0.889，预测结果有较好可靠性。欧洲山杨林的分布主要受年降水量(bio12)、最冷季度的降水量(bio19)、最冷季度的平均温度(bio11)、年平均温度(bio1)、最干燥季度的平均温度(bio9)、最热月份的最高温度(bio5)影响。与当前适生区相比，四种气候情境下，未来四个年代的适生区均有扩张趋势。

Abstract: To identify the dominant environmental factors affecting the distribution of Populus tremula forests, and quantify their potential suitable habitats in different periods, this study used the MaxEnt model and ArcGIS spatial analysis technology, integrated 910 distribution sites of European aspen forests in China and bioclimatic data, to predict and analyze their potential suitable habitats in the current period and four future periods. The results showed that the Area Under the Curve (AUC) value of the MaxEnt model was 0.889, indicating that the prediction results had good reliability. The distribution of European aspen forests was mainly affected by annual precipitation (bio12), precipitation of the coldest quarter (bio19), mean temperature of the coldest quarter (bio11), annual mean temperature (bio1), mean temperature of the driest quarter (bio9), and maximum temperature of the warmest month (bio5). Compared with the current suitable habitats, the suitable habitats in the four future decades showed an expansion trend under the four climate scenarios.