• 研究报告 •

### 使用大熊猫数据评估Biomod2和MaxEnt分布预测模型的表现

1. (1复旦大学生命科学学院, 上海 200433;  2北京大学生命科学学院自然保护与社会发展研究中心, 北京 100871)
• 出版日期:2018-05-18

### Evaluating the performance of species distribution models Biomod2 and MaxEnt using the giant panda distribution data.

LUO Mei1,2, WANG Hao2*, LYU Zhi2#br#

1. (1School of Life Sciences, Fudan University, Shanghai 200433, China; 2School of Life Sciences, Peking University, Beijing 100871, China).
• Online:2018-05-18

Abstract: Species distribution models (SDMs) are widely used by researchers and conservationists. Results of prediction from different models vary significantly, which makes users feel difficult in selecting models. In this study, we evaluated the performance of two commonly used SDMs, the Biomod2 and Maximum Entropy (MaxEnt), with real presence/absence data of giant panda, and used three indicators,i.e, area under the ROC curve (AUC), true skill statistics (TSS), and Cohen’s Kappa, to evaluate the accuracy of the two model predictions. The results showed that both models could produce accurate predictions with adequate occurrence inputs and simulation repeats. Compared to MaxEnt, Biomod2 made more accurate prediction, especially when occurrence inputs were few. However, Biomod2 was more difficult to be applied, required longer running time, and had less data processing capability. To choose the right models, users should refer to the error requirements of their objectives. MaxEnt should be considered if the error requirement was clear and both models could achieve, otherwise, we recommend the use of Biomod2 as much as possible.