Combining food web and species distribution models for improved community projections

• Published in: Ecology and evolution Vol. 3; no. 13; pp. 4572 - 4583
• Main Authors: Pellissier, Loïc, Rohr, Rudolf P., Ndiribe, Charlotte, Pradervand, Jean‐Nicolas, Salamin, Nicolas, Guisan, Antoine, Wisz, Mary
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.11.2013; Blackwell Publishing Ltd
• Subjects: Accounting; Accuracy; Biodiversity; Biotic interactions; Butterflies & moths; Climate change; Communities; Constraint modelling; Datasets; ecological niche modeling; Ecology; Environmental gradient; Flowers & plants; Food; Food chains; Food webs; Herbivores; Host plants; Larvae; Links; Original Research; Phylogeny; plant–herbivore interactions; Species; trophic network; Trophic relationships; Switzerland, Alps Mts; ecological niche modeling; plant–herbivore interactions; phylogeny; Biotic interactions; trophic network
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.843

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant–herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks. We combine a predictive food web model that can infer the potential interaction links between species, with species distribution models. Using a plant–herbivore (butterfly) interaction, dataset collected in the Swiss Alps and dissected in previous studies, we demonstrate for the first time that this combined approach is able to improve both species distribution and community forecasts. Our combined approach points a promising direction forward to model the spatial variation in entire species interaction networks.