ROC曲线分析在评价入侵物种分布模型中的应用

Application of ROC curve analysis in evaluating the performance of alien species' potential distribution models

生态位模型(ecological niche models,ENMs)已广泛应用于物种潜在分布区预测,ENMs的应用也为外来入侵物种的风险分析提供了重要的定量化分析工具,但如何评价不同模型之间的预测效果成了当今研究的热点问题。本文介绍了受试者工作特征(ROC)曲线分析在评价不同生态位模型预测效果中的应用原理和分析方法,并以一种植物病原线虫-相似穿孔线虫(Radopholus similis)为例,应用ROC曲线分析法对其5种模型(BIOCLIM,CLIMEX,DOMAIN,GARP,MAXENT)的预测结果进行了比较分析。5种模型的ROC曲线下面积AUC(Area Under Curve)值分别为0.810,0.758,0.921,0.903和0.950,以MAXENT模型的AUC值最大,表明其预测效果最好;方差分析结果表明,除GARP与DOMAIN模型之间AUC值差异不显著外,其余各模型之间差异显著。

Ecological niche models （ENMs）, which are widely employed to predict the potential geographic distribution of species, provide an important tool to quantify the risks imposed by invasive alien species. The problem of how to evaluate the performance of different models has attracted more and more attention. In the present paper, we introduced the principle of the method of Receiver Operating Characteristic （ROC） curve analysis in assessing the accuracy of different ENMs. We predicted the suitable distribution area of Radopholus similis, an important banana toppling disease nematode, with five widely used ENMs and evaluated the performance of different models by ROC curve analysis. The area under ROC curve （AUC） for BIOCLIM, CLIMEX, DOMAIN, GARP, and MAXENT models was 0.810, 0.758, 0.921, 0.903, and 0.950, respectively. Among these, the biggest value of AUC was assigned to MAXENT, indicating that the result gained by MAXENT should be better than the other four models. According to the results of analysis of variance （ANOVA）, there was a remarkable difference in AUC between each model except for DOMAIN and GARP.