Equilibrium modeling of alpine plant distribution: how far can we go?

Détails

ID Serval
serval:BIB_51333BBB8726
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Equilibrium modeling of alpine plant distribution: how far can we go?
Périodique
Phytocoenologia
Auteur(s)
Guisan A., Theurillat J. P.
ISSN
0340-269X
Statut éditorial
Publié
Date de publication
2000
Peer-reviewed
Oui
Volume
30
Numéro
3-4
Pages
353-384
Langue
anglais
Notes
42nd Symposium of the International-Association-of-Vegetation-Science, BILBAO, SPAIN, JUL 26-30, 1999, Int Assoc Vegetat Sci
Résumé
Predictive distribution modeling of species and communities has gained much importance in recent years. In this paper, generalized linear models (GLM) are implemented in a Geographical Information System to mimic the spatial distribution of alpine and subalpine species habitat and diversity in the study area of Belalp (Aletsch region, Wallis, Swiss Alps). Quantitative predictors used to quantify environmental requirements of species are: annual mean temperature, slope angle, topographic position, solar radiation, snow cover indices and the three spectral bands of a color infrared aerial photograph, as well as disjunctive classes of qualitative substrate-related predictors. Presence-absence logistic GLM are adjusted for 63 species. Percent ground cover measured on an ordinal scale is additionally modeled using a special case of GLM for 26 species with significant variation of abundance in the field. Both ordinal abundance and presence/absence at each spatial location are successfully modeled for some species, as shown by quantitative evaluation using an independent data set. Finally, species richness (SR) is modeled by (i) using a Poisson GLM and (ii) summing up single species predictions by presence/absence models. Successful models are finally used to mimic potential impact of climatic change on plant distribution and diversity. Results from these scenarios suggest (i) an overall trend toward a reduction of suitable habitat for alpine species and (ii) two different responses for the distribution of SR, namely: (a) a serious shift of the optimal SR elevation belt upward in elevation or (b) the SR optimal belt shifting only slightly upward in elevation, accompanied by a parallel spatial spread out of high SR patches at, these elevations. Limitations of both species and diversity models are discussed and some suggestions for future research are proposed.
Mots-clé
species distribution, generalized linear model, logistic regression, ordinal abundance, species richness, remote sensing, geographical information system, climate change, impact scenarios, Swiss Alps
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Création de la notice
24/01/2008 20:06
Dernière modification de la notice
03/03/2018 17:10
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