Titre
Land use improves spatial predictions of mountain plant abundance but not presence-absence
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Auteur(s)
Randin, C.F.
Co-première auteure/Co-premier auteur
Jaccard, H.
Co-première auteure/Co-premier auteur
Vittoz, P.
Co-dernière auteure/Co-dernier auteur
Yoccoz, N.G.
Co-dernière auteure/Co-dernier auteur
Guisan, A.
Co-dernière auteure/Co-dernier auteur
Liens vers les personnes
Liens vers les unités
ISSN
1100-9233
Statut éditorial
Publié
Date de publication
2009
Volume
20
Numéro
6
Première page
996
Dernière page/numéro d’article
1008
Peer-reviewed
Oui
Langue
anglais
Résumé
Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.
PID Serval
serval:BIB_461AF2146366
Date de création
2009-01-18T21:27:47.292Z
Date de création dans IRIS
2025-05-20T14:07:41Z