Equilibrium modeling of alpine plant distribution: how far can we go?
Guisan, Antoine; Theurillat, Jean-Paul
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.
species distribution • generalized linear model • logistic regression • ordinal abundance • species richness • remote sensing • geographical information system • climate change • impact scenarios • Swiss Alps