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Do stacked species distribution models reflect altitudinal diversity patterns?

Abstract:

The objective of this study was to evaluate the performance of stacked species distribution models in pbkp_redicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the pbkp_redictions for the same species in ensemble models based on two different criteria: the average of the rescaled pbkp_redictions by all techniques and the average of the best techniques. The rescaled pbkp_redictions were then reclassified into binary pbkp_redictions (presence/absence). By stacking either the original pbkp_redictions or binary pbkp_redictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the pbkp_rediction abilities for the four pbkp_redictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble pbkp_rediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpbkp_redict species richness. The use of the ensemble pbkp_redictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-pbkp_rediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed. © 2012 Mateo et al.