Incorporating host-parasite biotic factors in species distribution models: Modelling the distribution of the castor bean tick, Ixodes ricinus.
Keywords:biotic interactions, host species, parasitism, species distribution modelling, ticks
Understanding where ticks are found, and the drivers of their geographic distributions is imperative for successful epidemiological precautions. Predictive models of tick distributions are often projected using solely abiotic (e.g. climate) variables, despite the strong biotic interaction that host species undoubtedly have with parasitic species. We used species distribution modelling to project the distribution of Ixodes ricinus in Ireland and the United Kingdom using different combinations of abiotic, biotic, and abiotic-biotic variables. We found that models parameterised solely on abiotic variables generally reported lower accuracy and ecological realism than models that incorporated biotic factors alongside climate. We also investigated representation of host distribution in models, testing four different methods (habitat suitability of individual hosts, presence-absence of individual hosts, ensembled habitat suitability, and ensembled presence-absence). Biotic representations of ensembles host distributions alongside abiotic variables reported the highest accuracy, with the variable representing host diversity (e.g. number of host species) the most important variable when measured using a jackknife test. Moreover, our results suggested how host distributions are represented (i.e. presence-absence, habitat suitability) greatly impacted results, with differences reported among habitat specialists and generalists. Results suggest that it is now imperative for projections of parasitic species to include a representation of biotic factors with host species. This research has improved our understanding of the drivers of tick distributions in a national context, and the investigation of biotic representation should foster discussion among researchers working in species distribution modelling and the wider biogeography discipline.