How many studies are necessary to compare niche-based models for geographic distributions? Inductive reasoning may fail at the end

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 Producti...

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Bibliographic Details
Published in:Brazilian journal of biology 2010-05, Vol.70 (2), p.263-269
Main Authors: Terribile, L C, Diniz-Filho, J A F, De Marco, Jr, P
Format: Article
Language:English
Subjects:
Algorithms
Animals
BIOLOGY
cobras corais
Demography
Elapidae
Elapidae - classification
GARP
Geography
MAXENT
modelos de distribuição potencial
Models, Biological
ROC Curve
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Summary: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.
ISSN:1519-6984
1678-4375
1678-4375
1519-6984
DOI:10.1590/s1519-69842010000200005