SSDM : An R package to predict distribution of species richness and composition based on stacked species distribution models

Schmitt Sylvain, Pouteau Robin, Justeau-Allaire Dimitri, De Boissieu Florian, Birnbaum Philippe. 2017. SSDM : An R package to predict distribution of species richness and composition based on stacked species distribution models. Methods in Ecology and Evolution, 8 (12) : 1795-1803.

https://doi.org/10.1111/2041-210X.12841

Article de revue ; Article de revue à facteur d'impact

Version publiée - Anglais
Accès réservé aux personnels Cirad
Utilisation soumise à autorisation de l'auteur ou du Cirad.
597712.pdf
Télécharger (957kB) | Demander une copie

Url - jeu de données - Entrepôt autre : https://doi.org/10.15468/dl.2mvxxk / Url - jeu de données - Entrepôt autre : https://www.worldclim.org/

Quartile : Q1, Sujet : ECOLOGY

Résumé : There is growing interest among conservationists in biodiversity mapping based on stacked species distribution models (SSDMs), a method that combines multiple individual species distribution models to produce a community-level model. However, no user-friendly interface specifically designed to provide the basic tools needed to fit such models was available until now. The “ssdm” package is a computer platform implemented in r providing a range of methodological approaches and parameterisation at each step in building the SSDM: e.g. pseudo-absence selection, variable contribution and model accuracy assessment, inter-model consensus forecasting, species assembly design, and calculation of weighted endemism. The object-oriented design of the package is such that: users can modify existing methods, extend the framework by implementing new methods, and share them to be reproduced by others. The package includes a graphical user interface to extend the use of SSDMs to a wide range of conservation scientists and practitioners.

Mots-clés Agrovoc : distribution des populations, modélisation, biodiversité, bioinformatique, logiciel, écologie animale, phytoécologie, écologie des populations

Mots-clés libres : Bioinformatics, Community ecology, Conservation, Habitats, Modelling, Software

Classification Agris : P01 - Conservation de la nature et ressources foncières
U10 - Informatique, mathématiques et statistiques
F70 - Taxonomie végétale et phytogéographie

Champ stratégique Cirad : Axe 2 (2014-2018) - Valorisation de la biomasse

Auteurs et affiliations