The importance of parasite geography and spillover effects for global patterns of host-parasite associations in two invasive species

AimGeographic spread and range expansion of species into novel environments may merge originally separated species assemblages, yet the possible drivers of geographic heterogeneity in host-parasite associations remain poorly understood. Here, we examine global patterns in the parasite assemblages of two rat species and explore the role of parasite acquisition from local pools of host species. LocationGlobal. MethodsWe compiled a global data set of helminth parasites (n=241 species) from two rat species (Rattus rattus species complex, R.norvegicus) and, concomitantly, from all other mammal species known to be infected by the same parasites. We used an inverse Bayesian modelling approach to explicitly link species-level to community-level infestation probabilities at different geographic scales and alleviate the shortcoming of sampling bias. ResultsPatterns of species richness and turnover of parasites in the two focal rat species revealed clear biogeographic structure with lowest species richness and most distinct assemblages in Madagascar and highest species richness and least distinct assemblages in the Palaearctic region. Parasite species richness and turnover across regions were correlated for the two focal hosts, although they were associated with distinct assemblages within regions. Infection probability of a focal host with any given parasite was clearly related to infection probability of the local species pool of wildlife hosts with that same parasite. Infection probability of other mammal species infected with these parasite species, in turn, decreased with their taxonomic distance to the genus Rattus. Main conclusionsOur study demonstrates the importance of spillover of parasites from local wildlife hosts to invasive rats on global patterns of host-parasite associations. Considering both changes in local pools of host species and the global distributions of parasite and pathogen diversity in consistent model frameworks may therefore advance the forecasting of species-level infestation patterns and the possible risk of disease emergence from local to global scale.