Data from: Trait-matching and phylogeny as predictors of predator-prey interactions involving ground beetles
Brousseau, Pierre-Marc; Gravel, Dominique; Tanya Handa, I. (2018), Data from: Trait-matching and phylogeny as predictors of predator-prey interactions involving ground beetles, Dryad, Dataset, https://doi.org/10.5061/dryad.7tn01
With global change modifying species assemblages, our success in predicting ecosystem level consequences of these new communities will depend, in part, on our ability to understand biotic interactions. Current food web theory considers interactions between numerous species simultaneously, but descriptive models are unable to predict interactions between newly co-occurring species. Incorporating proxies such as functional traits and phylogeny into models could help infer predator/ prey interactions. Here we used trait-matching between predator feeding traits and prey vulnerability traits, along with phylogeny (used as a proxy for chemical defence and other traits difficult to document), to infer predatory interactions using ground beetles as model organisms. A feeding experiment was conducted involving 20 ground beetle and 115 prey species to determine which pair of species did or did not interact. Eight predator and four prey functional traits were measured directly on specimens. Then, using a modeling approach based on the matching-centrality formalism, we evaluated 511 predictive ecological models that tested different combinations of all predator and prey functional traits, and phylogenetic information. The most parsimonious model accurately predicted 81 % of the observed realized and unrealized interactions, using phylogenetic information and the trait-matches predator biting force/ prey cuticular toughness and predator/ prey body size ratio. The best trait-based models predicted correctly >80 % which species interact (realized interactions), but predict <58 % of which species did not interact (unrealized interactions). Adding a phylogenetic term representing the evolutionary distance within each trophic level increased the ability to predict which species did not interact to >75 %. The matching of predator biting force and prey cuticular toughness demonstrated a better predictive power than the commonly used predator/ prey body size ratio. Our novel model combining both functional traits and phylogeny extends beyond existing descriptive approaches and could represent a valuable tool to predict consumer/ resource interactions of newly introduced species and to resolve cryptic food webs.