LAUSR

Abstract Species distribution models (SDMs) have conventionally been used for evaluating the distribution of individual species, but they can also be used, through comparing different SDMs, to evaluate the geographic similarity between taxa. In this study, we used a parasite and host system to infer the geographic overlaps between species with tight biological interaction, for example, parasites and their obligate host. Specifically, we used the horsehair worm Chordodes formosanus and its three mantis hosts to study the extent of niche overlap. We retrieved presence points for the host species and the parasite, and then we built SDMs with MaxEnt implemented in ENMeval using selected bioclim variables (based on variance inflation factor values) at 30s scale. The models showed that the hosts and parasite do not occur in the high elevation areas in Taiwan, which is expected based on their biology. Interestingly, the predicted parasite distribution included areas without collection records, implying local extinction or sampling bias. We subsequently evaluated niche overlap between hosts and the parasite according to five similarity indices (Schoener's D, I statistic, relative rank, Pearson correlation coefficient, and the rank correlation coefficient rho). Our models showed a high similarity of SDM predictions between hosts and the parasite. There were differences among metrics for which host shared the highest similarity with the parasite, but the majority of the results indicated that the Japanese boxing mantis had the highest niche similarity with the horsehair worm. The choice of the niche overlap metric to use can uncover information on the parasite's ecology, which can be important for endangered species. SDMs are reliable tools for host and parasite conservation management and could help improve our understanding of parasite biology and ecology.