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What are the most crucial soil variables for predicting the distribution of mountain plant species? A comprehensive study in the Swiss Alps
Author(s) -
Buri Aline,
Grand Stéphanie,
Yashiro Erika,
Adatte Thierry,
Spangenberg Jorge E.,
PintoFigueroa Eric,
Verrecchia Eric,
Guisan Antoine
Publication year - 2020
Publication title -
journal of biogeography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.7
H-Index - 158
eISSN - 1365-2699
pISSN - 0305-0270
DOI - 10.1111/jbi.13803
Subject(s) - range (aeronautics) , temperate climate , environmental science , habitat , species distribution , ecology , drainage , soil science , hydrology (agriculture) , biology , geology , materials science , composite material , geotechnical engineering
Abstract 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 the following: (a) which soil variables improve plant species distribution models; (b) whether an optimal subset of soil variables can improve models for the majority of species and habitat types and (c) 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 + δ 13 C – 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.