The ecology of pathogen amplification in communities of hosts
The tick-borne diseases Lyme disease, babesiosis, and anaplasmosis are rapidly emerging and expanding worldwide. Ticks acquire these pathogens from vertebrate hosts and may then transmit them to humans, causing disease. Within endemic zones, almost all species of terrestrial mammals and birds are exposed to these pathogens, but only a few are able to maintain and transmit infections to feeding ticks. Our research shows that three small mammal species – the white-footed mouse, Eastern chipmunk, and short-tailed shrew – are the most competent reservoirs for all three pathogens. Life history traits associated with a fast pace of life, as well as high average population density, correlate positively with reservoir competence. Ticks that bite a mouse, chipmunk, or shrew are likely to acquire multiple tick-borne pathogens; therefore these host species are responsible for most co-infections. These three small mammals are also highly resilient to forest fragmentation, persisting in small fragments that have lost most of their vertebrate diversity.
Several meso-mammals are predators on small mammals, poor reservoirs for tick-borne pathogens, and poor hosts for ticks. All three of these traits would reduce the prevalence of tick-borne pathogens. We find that sites lacking mesopredators have higher abundance of ticks infected with all three pathogens. Our long-term monitoring provides strong evidence that pulsed resources (acorns) for amplification hosts (rodents) can also affect risk through bottom-up effects. We think that these results for tick-borne pathogens apply generally to multi-host pathogen systems in the following ways: (1) host species vary dramatically in reservoir competence; (2) the best reservoirs are often basal members of nested communities; (3) the loss of species able to regulate the abundance or effect of reservoir hosts can increase disease risk; and (4) reservoir abundances can be driven by resource pulses. Taken together, these results suggest that land-use changes that are likely to increase zoonotic disease risk can be predicted and potentially avoided.