Predicting host range expansion in parasitic mites using a global mammalian-acarine dataset.

Multi-host parasites pose greater health risks to wildlife, livestock, and humans than single-host parasites, yet our understanding of how ecological and biological factors influence a parasite's host range remains limited. Here, we assemble the largest and most complete dataset on permanently parasitic mammalian mites and build a predictive model assessing the probability of single-host parasites to become multi-hosts, while accounting for potentially unobserved host-parasite links and class imbalance. This model identifies statistically significant predictors related to parasites, hosts, climate, and habitat disturbance. The most important predictors include the parasite's contact level with the host immune system and two variables characterizing host phylogenetic similarity and spatial co-distribution. Our model reveals an overrepresentation of mites associated with Rodentia (rodents), Chiroptera (bats), and Carnivora in the multi-host risk group. This highlights both the potential vulnerability of these hosts to parasitic infestations and the risk of serving as reservoirs of parasites for new hosts. In addition, we find independent macroevolutionary evidence that supports our prediction of several single-host species of Notoedres, the bat skin parasites, to be in the multi-host risk group, demonstrating the forecasting potential of our model. Some mite species infect only one mammal host, while other typically more dangerous species, infect multiple hosts. This study developed a model using parasite, host, climate, and habitat data to predict potential host range expansions in single-host mites and the probability of single-host parasites to become multi-hosts. [ABSTRACT FROM AUTHOR]