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dc.contributor.authorGuisande, Cástores_ES
dc.contributor.authorHeine, Juergenes_ES
dc.contributor.authorGarcía-Roselló, Emilioes_ES
dc.contributor.authorGonzález-Dacosta, Jacintoes_ES
dc.contributor.authorGarcía Pérez-Schofield, Baltasar J.es_ES
dc.contributor.authorGonzález-Vilas, Luises_ES
dc.contributor.authorVaamonde, Antonioes_ES
dc.contributor.authorLobo, Jorge M.es_ES
dc.date.accessioned2016-01-19T12:55:50Z-
dc.date.available2016-01-19T12:55:50Z-
dc.date.issued2015-11-16-
dc.identifier.citationDiversity 7(4) 385-396 (2015)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/127799-
dc.description.abstractWe 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.es_ES
dc.description.sponsorshipWe acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)-
dc.description.sponsorshipWe thank Empresa Nacional de Electricidad (ENDESA) for technical and financial support.-
dc.language.isoenges_ES
dc.publisherMultidisciplinary Digital Publishing Institutees_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsopenAccess-
dc.subjectSpecies richnesses_ES
dc.subjectPatch distributiones_ES
dc.subjectTerrestrial carnivoreses_ES
dc.titleFactorsR: An RWizard application for identifying the most likely causal factors in controlling specieses_ES
dc.typeartículo-
dc.identifier.doi10.3390/d7040385-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.3390/d7040385es_ES
dc.identifier.e-issn1424-2818-
dc.rights.licensehttp://creativecommons.org/licenses/by/4.0/es_ES
dc.contributor.funderConsejo Superior de Investigaciones Científicas (España)-
dc.relation.csices_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003339es_ES
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