Abstract
The use of ecological niche models (ENM) to generate potential geographic distributions of species has rapidly increased in ecology, conservation and evolutionary biology. Many methods are available and the most used are Maximum Entropy Method (MAXENT) and the Genetic Algorithm for Rule Set Production (GARP). Recent studies have shown that MAXENT perform better than GARP. Here we used the statistics methods of ROC - AUC (area under the Receiver Operating Characteristics curve) and bootstrap to evaluate the performance of GARP and MAXENT in generate potential distribution models for 39 species of New World coral snakes. We found that values of AUC for GARP ranged from 0.923 to 0.999, whereas those for MAXENT ranged from 0.877 to 0.999. On the whole, the differences in AUC were very small, but for 10 species GARP outperformed MAXENT. Means and standard deviations for 100 bootstrapped samples with sample sizes ranging from 3 to 30 species did not show any trends towards deviations from a zero difference in AUC values of GARP minus AUC values of MAXENT. Ours results suggest that further studies are still necessary to establish under which circumstances the statistical performance of the methods vary. However, it is also important to consider the possibility that this empirical inductive reasoning may fail in the end, because we almost certainly could not establish all potential scenarios generating variation in the relative performance of models.
Highlights
Niche‐based species distribution models, or ecological niche models (ENM), today play a central role in many areas of ecology, conservation and evolutionary biology, both because they can fill gaps in knowledge and allow a better estimate of multiple components of species diversity (Guisan and Zimmermann, 2000; Araújo and Guisan, 2006; Phillips et al, 2006)
Taking into account the AUC values, we found that Genetic Algorithm for Rule Set Production (GARP) does not work always worse than MAXENT, on the contrary that would be expected by considering the ‘performance axis’ suggested by Elith et al (2006)
What can we claim based on these results? The first and obvious issue to discuss is that the analysis of this particular dataset is not in agreement with Elith et al (2006), regarding the performance of GARP and MAXENT
Summary
Niche‐based species distribution models, or ecological niche models (ENM), today play a central role in many areas of ecology, conservation and evolutionary biology, both because they can fill gaps in knowledge and allow a better estimate of multiple components of species diversity (Guisan and Zimmermann, 2000; Araújo and Guisan, 2006; Phillips et al, 2006). They can be used, under certain assumptions, to predict the fate of biodiversity under ongoing climate change processes (Guisan and Thuiller, 2005; Araújo and New, 2007). Elith et al (2006) recently did a broad and general evaluation of ENM and showed that one of the most widely used methods, GARP (Genetic Algorithm for Rule Set Production) (Stockwell and Noble, 1992) performed poorly, whereas the recently developed MAXENT (Maximum Entropy Method) (Phillips et al, 2006) ranked among the best methods (together with novel methods like boosted regression trees [BRT], and regression‐ based methods [GAM, GLM and MARS], which were previously suggested as high‐performance methods in most studies; see Segurado and Araújo, 2004). Pearson et al (2007) recently compared MAXENT and GARP to predict species distribution from small numbers of occurrence records and found that MAXENT was better than GARP when sample sizes were experimentally reduced to less than 10 presence‐records
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