Disentangling the drivers of parasite occurrence in a native and a non-native small mammal across a land-use gradient

Matan Markfeld, Toky Maheriniaina Randriamoria, Voahangy Soarimalala, Steven M. Goodman, Charles L. Nunn, Georgia Titcomb, Shai Pilosof 

Land-use change can reorganize host--parasite systems by altering environmental conditions, host communities, and transmission pathways. Yet parasite occurrence remains difficult to predict as it is shaped simultaneously by the environment, host identity, individual host attributes, the within-host microbiome, and parasite biology. We integrated these components within a single framework for two coexisting small mammals along a land-use gradient in northeastern Madagascar: the native, Malagasy-endemic shrew tenrec, Microgale brevicaudata (Tenrecidae), and the non-native, invasive black rat, Rattus rattus (Muridae). We characterized gut protozoan and nematode parasites in 505 hosts and used Hierarchical Modeling of Species Communities (HMSC) to quantify the relative contributions of environmental, host, microbiome, and parasite-level factors to parasite occurrence. Host species was the dominant driver overall, accounting for approximately half of the weighted explained variance, followed by environmental conditions, but their relative importance varied substantially among parasites. Parasite taxonomic group explained part of this variation, indicating that parasite biology also shaped responses to the same environmental and host-level drivers. Land-use responses differed sharply between hosts: parasite richness in M. brevicaudata was highest in the primary forest, whereas richness in R. rattus was highest in disturbed habitats. Thus, land-use change did not generate a common increase or decline in parasitism, but redistributed parasite richness between coexisting native and non-native hosts. Together, these results show that responses of host--parasite systems to land-use change emerge from the interaction of host identity, environmental conditions, and parasite biology, and cannot be understood from any single level alone. This multi-level perspective can improve predictions of infection risk as global change expands the interface between native and non-native hosts.