摘要:采用1：100万的中国植被类型图以及19个气候环境变量数据，基于最大熵（MaxEnt）算法和ArcGIS空间分析模块构建西南地区高山植被地理分布的气候适宜性预测模型，模拟其在基准期（1960-2000年）和不同气候情景下（A2、A1B和B1）的气候适宜性分布格局，并评价其对气候变化的适应性。结果表明：MaxEnt模型分析研究区高山植被地理分布气候适宜性的适用性非常高（AUC=0.93）；最暖月均温、最湿季均温、最冷月均温等温度变量是限制其地理分布的主要气候因子；研究区高山植被地理分布的气候适宜区主要集中在西藏自治区、青海省、四川省西部及云南省西北部的部分地区；完全适宜、中度适宜、轻度适宜、不适宜的面积所占总面积比例约为1：1：2：5；1960-2050年研究区高山植被潜在地理分布的气候适宜性面积有不同定程度的减少；未来3种气候变化情景下高山植被地理分布对气候变化的适应性分布格局基本一致，均为不适应区所占总面积比例较大；伴随气候变化，研究区高山植被的适应性减弱，体现在其潜在地理分布对气候变化的适应区分布范围减少；海拔5000-5500m适应性较强，适应区所占面积比例最大（53%左右）；3500-4500m适应性最弱，适应区所占面积比例最小（5%左右）。



Abstract:Using the maximum entropy (MaxEnt) algorithm and the spatial analysis module of ArcGIS, a suitable habitat prediction model for the potential geographical distribution of alpine mean in southwestern China is constructed based on the mean type map and 19 climate variables. The geographical distribution patterns of alpine mean during 1960-2000 and 2020-2050 in southwestern China are simulated. The adaptability characteristics under the future climatic change scenarios (A1B, A2 and B1) are evaluated. The results show that the applicability of the MaxEnt model for geographical distribution prediction of alpine mean in Southwest China is very high (AUC=0.93). The mean temperature in the warmest month, the mean temperature in the wettest season, and the mean temperature in the coldest month are main climatic factors limiting the distribution of alpine mean in Southwest China. The climate suitable areas for the geographical distribution of alpine mean are mainly concentrated in Tibet, Qinghai, the western part of Sichuan, and the northwest part of Yunnan, with an altitude between 4500-5500m. The proportion of totally suitable, moderately suitable, mildly suitable, and unsuitable areas in the total area is about 1:1:2:5. Under three climate change scenarios in the future, the adaptation pattern of alpine mean geographical distribution to climate change is consistent. The adaptation of alpine mean is weakened companying climate change, which is reflected by the reduction of the suitable areas of potentially geographical distribution to climate change. The altitude 5000-5500m has a strong adaptability, and the proportion of the adaptive area is the highest (about 53%). The adaptability of 3500-4500m is the weakest, and the proportion of adaptive area is the lowest (about 5%).





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