Description Modelled pine species richness in Mexico based on the ‘maximum training sensitivity and specificity threshold’ according to (a) climatic S‐SDMs (CLIMATE) and (b) a hierarchical combination of...
Article Title: Remote sensing data can improve predictions of species richness by stacked species distribution models: a case study for Mexican pines
Publication Title: Journal of Biogeography

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Description Relative difference of modelled and observed species numbers according to climatic S‐SDMs (CLIMATE) or a hierarchical combination of climate and remote sensing‐based S‐SDMs (CLIMATE_RS) based on...
Article Title: Remote sensing data can improve predictions of species richness by stacked species distribution models: a case study for Mexican pines
Publication Title: Journal of Biogeography

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Description Examples of study species. (a) Pinus jeffreyi, Baja California, (b) P. culminicola, Coahuila, (c) P. californiarum, California, (d) P. quadrifolia, Baja California, and (e) P. hartwegii, State of...
Article Title: Remote sensing data can improve predictions of species richness by stacked species distribution models: a case study for Mexican pines
Publication Title: Journal of Biogeography

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Description Percentage contributions of (a) climatic data and (b) remote sensing variables to the species distribution models. Species were grouped according to their preferred climatic conditions (see Table )...
Article Title: Remote sensing data can improve predictions of species richness by stacked species distribution models: a case study for Mexican pines
Publication Title: Journal of Biogeography

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