Do stacked species distribution models reflect altitudinal diversity patterns?

Détails

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Etat: Public
Version: de l'auteur
ID Serval
serval:BIB_E08665619B4C
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Do stacked species distribution models reflect altitudinal diversity patterns?
Périodique
PLoS One
Auteur(s)
Mateo R.G., Felicísimo Á.M., Pottier J., Guisan A., Muñoz J.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Statut éditorial
Publié
Date de publication
2012
Peer-reviewed
Oui
Volume
7
Numéro
3
Pages
e32586
Langue
anglais
Résumé
The objective of this study was to evaluate the performance of stacked species distribution models in predicting 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 predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions 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 prediction abilities for the four predictions 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 prediction 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 overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, 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.
Mots-clé
ADAPTIVE REGRESSION SPLINES, CLIMATE-CHANGE, ELEVATIONAL GRADIENT, RICHNESS PATTERNS, SPATIAL PREDICTION, ECOLOGICAL THEORY, COMMUNITY-LEVEL, BIODIVERSITY, UNCERTAINTY, ABSENCES
Pubmed
Web of science
Open Access
Oui
Création de la notice
01/02/2012 15:09
Dernière modification de la notice
20/08/2019 17:04
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