We tested the utility of the modelling program Genetic Algorithm for Rule-set Prediction (GARP) for modelling ecological niches to make accurate predictions of geographical distributions for 25 bird species across Mexico. Specimen-based point-occurrence data were entered into the algorithm in the form of geographical coordinates, and related to digitized maps of environmental variables, including mean annual precipitation, elevation, mean annual temperature, and potential vegetation. Two Mexican states were used as test areas by withholding their points from model construction; these points were later overlaid on predictions to measure model performance. Statistically, most models (7890%) were significantly more powerful than random models in predicting occurrences in test states; model failures were most often due to low sample size for testing, rather than an inability to model distributions of particular species. The success of this test indicates that ecological niche modelling approaches such as GARP provide a promising tool for exploring a broad range of questions in ecology, biogeography and conservation.
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