What are the most crucial soil variables for predicting the distribution of mountain plant species? a comprehensive study in the Swiss Alps

Aim: To investigate the potential of a large range of soil variables to
improve topo-climatic models of plant species distributions in a temperate
mountain region encompassing complex relief. Location: The western Swiss
Alps. Methods: Fitting topo-climatic models for >60 plant species
across >250 sites with and without added soil predictor variables
(>30). Testing included: (i) which soil variables improve plant
species distribution models; (ii) whether an optimal subset of soil
variables can improve models for the majority of species and habitat
types; and (iii) how much variation in plant species distributions soil
variables alone explain. Results: Geochemical variables (i.e., CaO, pH and
inorganic carbon) and a drainage indicator (i.e., bulk soil water content)
improved the predictive abilities of the models across the large majority
of alpine plant species. The improvement of the models after the addition
of soil information varied strongly between plant species and habitat
types, but a trade-off was found between the number of soil variables and
the associated gain in model performance. Finally, across all species, one
specific combination of soil variables–bulk soil water content + total
phosphorus + δ13C–outperformed the commonly used topo-climatic variables.
Main conclusions: Several soil variables significantly increased the
predictive power of plant species distribution models in the temperate
mountain region. Geochemical and drainage variables proved most important.