PROJECT SUMMARY My research program has the goal of identifying predictive rules of cross-species viral transmission (or ‘spillover’) from wild mammals to humans. To do so, we study processes at both global and local scales. This work comes at a pivotal time for human health globally, with recent outbreaks of Ebola, monkeypox, MERS, and SARS- related CoVs all originating in wild mammals. Societal decisions increasingly hinge upon the ability to identify and mitigate risks of spillover. However, which types of species interactions carry the greatest zoonotic risks? The answer is not straightforward. Not only are complex ecological dynamics involved, but also the complex histories of biologists studying the involved species. Taxonomic classifications of wild mammals and their viruses are at center stage, not least because the flood of genomes is changing views of evolutionary relationships. Quelling the unfolding drama of emerging wildlife viruses will require attention to both the quality of public data that informs global models and the quantity of data available for local models of mammal-virus dynamics. Over the next five years, my research group will develop projects to address gaps in mammal-virus knowledge in the following areas. (1) Decay in the quality of public genetic and phylogenetic data through time requires systems to update the taxonomy of species names used to label and aggregate data. With 45% more mammal and 500% more virus species now recognized than 30 years ago, global mammal phylogenies and spillover risk models are quickly becoming outdated. In response, we will build automated tools for curating mammal and virus genetic data, including a pipeline for regularly re-inferring the Mammalia species-level molecular phylogeny from curated data. (2) Most models of spillover risk offer coarse-grain predictions due to data imprecision. But categories of all bats or all rodents hide the tremendous eco-physiological and immune variation among species. In response, we will apply the taxonomically updated data curated by our tools to test the sensitivity of species-level spillover risk models globally. (3) Lack of local knowledge of how viruses are shared among hosts requires a renaissance of field-based surveys coupled with genomic tools. We will sample forest-dwelling rodents in isolated montane habitats of Arizona’s Madrean sky islands to investigate the extent to which rates of gene flow predict viral sharing. If gene flow can proxy viral sharing, at least for certain taxa, then public DNA data can be leveraged to predict viral interactions without needing to describe the entire mammal virome, of which only ~3% is globally known. My research program will generate mechanistic models of viral spillover risk while contextualizing those results within mammal-virus evolutionary history. By unifying perspectives across scales, this research advances hypothesis-driven ecological studies of how and why viral spillover occurs while building tools for the global- scale curation of biomedically relevant data. Jointly, these synergistic projects will spur nonlinear outcomes.

PROJECT NARRATIVE Recent outbreaks of Ebola, monkeypox, and SARS-related CoVs all originated in wild mammals, increasing the societal need to identify predictive rules of cross-species viral transmission (or ‘spillover’). To address gaps in mammal-virus knowledge, my research program will build automated tools for curating public genetic and phylogenetic data, including a pipeline for re-inferring global mammal phylogeny; apply the taxonomically updated data from our tools to test the sensitivity of species-level spillover risk models globally; and investigate the extent to which rates of gene flow predict viral sharing among wild rodent populations in Arizona. By unifying perspectives across scales, this research advances understandings of how and why viral spillover occurs.