An RWizard application for identifying the most likely causal factors in controlling species richness

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Authors Cástor Guisande, Juergen Heine, Emilio García-Roselló, Jacinto González-Dacosta, Baltasar J. García Perez-Schofield, Luis González-Vilas, Antonio Vaamonde, Jorge M. Lobo
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Paper Abstract We herein present FactorsR, an RWizard application which provides tools for the identification of the most likely causal factors significantly correlated with species richness, and for depicting on a map the species richness predicted by a Support Vector Machine (SVM) model. As a demonstration of FactorsR, we used an assessment using a database incorporating all species of terrestrial carnivores, a total of 249 species, distributed across 12 families. The model performed with SVM explained 91.9% of the variance observed in the species richness of terrestrial carnivores. Species richness was higher in areas with both higher vegetation index and patch index, i.e., containing higher numbers of species whose range distribution is less fragmented. Lower species richness than expected was observed in Chile, Madagascar, Sumatra, Taiwan, and Sulawesi.
Date of publication 2015
Code Programming Language R
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