摘要
中华小熊猫(Ailurus styani)为我国II级重点保护野生动物,目前对其研究较少。该研究使用最大熵模型(Maximum entropy model)对邛崃山系中华小熊猫适宜栖息地进行了预测分析,同时采用Jackknife检验对生态因子的重要性进行分析。结果表明:中华小熊猫适宜栖息地预测模型的训练集和测试集的受试者工作特征曲线下面积(AUC)值分别是0.945和0.886,均大于0.8,模型精度可靠。模型预测结果表明,影响中华小熊猫适宜栖息地分布的主要生态因子为年均温(25.7%)、海拔(24.9%)和降水量变异系数(21.5%),这3个变量的累计贡献率达到了72.1%;其次是公路(6.6%)、最湿季降水量(5.1%)、坡度(3.9%)等生态因子。邛崃山系中华小熊猫适宜栖息地主要分布于山系中段,栖息地连贯但破碎化。
Chinese red panda(Ailurus styani)as China's II key protected wild animal,at present,is few studied.In this study,the Maximum Entropy Model was used to predict and analyze the suitable habitat of Chinese red pandas in Qionglai Mountains,and the importance of ecological factors was analyzed by Jackknife test.The results showed that the area values of the training set and the test set of the Chinese red panda suitable habitat prediction model under the receiver operating characteristic curve(AUC)were 0.945 and 0.886,respectively,both greater than 0.8,and the model accuracy was reliable.The results showed that the main ecological factors affecting the suitable habitat distribution of Chinese red panda were average annual temperature(25.7%),altitude(24.9%)and precipitation variation coefficient(21.5%),and the cumulative contribution rate of these three variables reached 72.1%.Ecological factors such as highway(6.6%),precipitation in the wettest season(5.1%)and slope(3.9%)were the next factors.The suitable habitats for Chinese red pandas in Qionglai mountain system were mainly distributed in the middle part of the mountain system,and the habitats were coherent but fragmented.
作者
李行
黄尤优
阮涛
韦伟
LI Hang;HUANG Youyou;RUAN Tao;WEI Wei(Key Laboratory of Southwest China Wildlife Resources Conservation of Ministry of Education,China West Normal University,Nanchong,Sichuan 637009,China;Institute of Rare Animals and Plants,China West Normal University,Nanchong,Sichuan 637009,China)
出处
《贵州师范大学学报(自然科学版)》
CAS
2022年第2期34-39,共6页
Journal of Guizhou Normal University:Natural Sciences
基金
国家自然科学基金(31801996,32070524,41901224)。
关键词
中华小熊猫
邛崃山系
最大熵模型
栖息地适宜性
Chinese red panda
Qionglai mountains
maximum entropy model
habitat suitability