Abstract. The relationships between the distribution of alpine species and selected environmental variables are investigated by using two types of generalized linear models (GLMs) in a limited study area in the Valais region (Switzerland). The empirical relationships are used in a predictive sense to mimic the potential abundances of alpine species over a regular grid. Here, we present the results for the alpine sedge Carex curvula ssp. curvula. The modelling approach consists of (1) a binomial GLM, including only the mean annual temperature as explanatory variable, which is adjusted to species presence/absence data in the entire study area; (2) a logistic model restricted to stands occurring within the a priori defined temperature range for the species ‐ which allows ordinal abundance data to be adjusted; (3) the two species‐response functions combined in a GIS to generate a map of the species' potential abundance in the study area; (4) model predictions filtered by the classes of the qualitative variables under which the species never occur. Such a stratified approach used to better fit the variability within the optimal altitudinal zone for the species. Removing stand descriptions from altitudes too high or too low, where the species is unlikely to occur, enhances the global modelling performance by allowing the identification of important environmental variables only retained in the second model. The model evaluation is finally carried out with the γ‐measure of association in an ordinal contingency table. It shows that abundance is satisfactorily predicted for C. curvula.
Journal of Vegetation Science – Wiley
Published: Feb 1, 1998
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