Biotic interactions boost spatial models of species richness

• Published in: Ecography
• Main Authors: Mod, Heidi K., Le Roux, Peter Christiaan, Guisan, Antoine, Luoto, Miska
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2016
• Subjects: Biotic interactions; Enhanced predictions; Impact biodiversity; Species richness; Arctic
• Online Access: http://hdl.handle.net/2263/52812; https://doi.org/10.1111/ecog.01129

Biotic interactions are known to aff ect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter-specifi c interactions. Here, we test whether incorporating biotic interactions into high-resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic-alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant – plant interactions consistently and signifi cantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. Th e global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially aff ect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts. Academy of Finland (Project Number 1140873) and Research Foundation of the University of Helsinki. http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1600-0587 2016-09-30 hb2016 Plant Science