This project will investigate how the way that groups are connected through the movement of individuals affects the spread of disease by studying viruses, bacteria, and other disease-causing parasites that infect desert bighorn sheep in southeastern California deserts. Many animals live in habitat patches, forming a network of populations that are linked by occasional movements. Understanding how changes in population connectivity affect disease transmission is important, as landscapes are changing rapidly in many regions around the globe. Desert bighorn sheep that live on mountain tops in the deserts of the American West. The study will measure how many of the sheep have been infected, and the rate at which they move among populations. They will ask whether more isolated populations have less genetic diversity and are more likely to be infected. This research will train of undergraduate students, graduate students, and postdoctoral fellows, and will engage the public through collaborations with K-12 teachers, wildlife management agencies, and natural history museums.
The researchers will use observational data, experiments, and mathematical models to investigate how the spatial relationships between interconnected host populations shape infection risks in different locales, setting the stage for genetic adaptation of immune defenses in the hosts. Differences in immune responses among host populations are likely to affect the populations' vulnerability to infectious diseases. The investigators hypothesize that network topology will constrain parasite species distributions across host populations, and parasite interactions will structure parasite communities within individual hosts. They expect that differences in parasite communities across populations mediate differential selection on genes involved in immune function, resulting in variation in immune responses and local immunogenetic adaptation. They hypothesize that feedbacks between these ecological and evolutionary processes drive the dynamics of parasite communities in host population networks, resulting in differential vulnerability to emerging infections across populations. Metagenomic data from fecal samples will be used to discover landscape-level parasite community patterns across three metapopulations. In a Mojave Desert metapopulation, they will combine longitudinal observational data and experimental approaches to assess the role of parasite interactions in structuring within-host parasite communities. Immune responses and survey immunogenetic profiles of sheep will be used to estimate the selective pressure underlying immunogenetic differences across fourteen bighorn populations. The empirical data will be used to parameterize and test mathematical network models exploring how ecological and host evolutionary processes shape disease dynamics in bighorn in particular, and across population networks in general.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
