BEE: Eco-evolutionary dynamics of disease-induced apex predator declines

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This project will study how the spread of an infectious disease can affect the co-evolution of the pathogen and the host, and who those changes can create changes in the rest of the animal community. Emerging infectious diseases and the global loss of biodiversity are two leading challenges for the life sciences in the 21st century. Declines of the iconic Tasmanian devil in Australia represent an example of these two threats acting together to endanger a species. Additionally, as such large predators decline, the role of other species shifts in the food chain, which can lead to loss of biodiversity via secondary declines and extinctions of other species. These community changes can then feed back on the predator themselves, resulting in changes in developmental timing and reproduction. Thus, it is critical to study how losses of top predators lead to changes in food webs, population densities, and evolution of species with which they interact. Through outreach to the general public, this study will increase understanding of how infectious diseases affect biological communities and influence biodiversity. It will also provide training opportunities for US graduate students and post-doctoral scholars in an international setting.Tasmanian devils and their fatal transmissible cancer, devil facial tumor disease (DFTD), represents an ideal study system to elucidate the impacts of top predator losses on community dynamics. The east to west spread of DFTD provides a rare, natural experiment to test how temporal variation in extent of devil declines across Tasmania affects community dynamics. Devils are indeed community architects, the declines of which cause the direct effects of mesopredator release that then cascades through the food web to indirect secondary declines of native species. The research will bridge ecological and evolutionary theory to predict how co-evolutionary interactions of devils and DFTD will affect current and future devil population densities. These predictions will then be plugged into (structural equation) models that incorporate field studies of ecological interactions within the Tasmanian devil food web across the decline gradient. Feedbacks of these community-level changes on Tasmanian devil life history evolution will be evaluated with genomic study of the basis of a rapid developmental trajectory and precocial breeding in female devils. Evolutionary feedbacks on mesopredators and prey will be assessed using landscape genomics studies to test the influence of variation in devil density on gene flow and adaptive potential across multiple generations.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.