We are developing genomic approaches aimed at assisting with conservation efforts of endangered species. Many threatened populations are extensively fragmented relative to their natural state, which impacts the population genetics and genomics. We are studying how we can infer eco-evolutionary processes from these genomic signatures, and how we can better manage populations to maximize their evolutionary potential and increase their long-term viability.



We are addressing fundamental questions in ecology & evolution using mathematical and computational models. For example, we are interested in studying the impact of population structure on the distribution of variation across populations and along the genome, and modeling how fragmentation impacts the evolution of traits such as dispersal . We are also interested in modeling the interaction between disease transmission and immune-related gene flow, with application to the dynamics between Neanderthals and modern humans or invasive and native species.

Disease model.png


Gene drive is a very exciting merging population-editing technology, but one that also raises many concerns. One of the main limitation of gene drive is that they could potentially spillover to other populations or to other species. We use mathematical models to study the eco-evolutionary dynamics of gene drives in order to better understand the consequences of deploying this technology into wild populations.


Greenbaum Lab