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Evolutionary Rescue (ER) is the process by which a declining population in a stressful environment can avoid extinction via genetic adaptation, e.g. during the invasion of new habitats or the emergence of resistance to treatments. This project mixes fitness-landscape models and stochastic demographic dynamics to predict the likelihood and genetic basis of ER from measurable parameters. A predictive analytical/numerical modelling framework will be developed, based on complex and non-standard mathematical objects, such as nonlocal-nonlinear partial differential equations and multi-type branching processes. It will be quantitatively tested on (i) high-throughput kinetic measurements of ER in vitro for E.coli facing chemical stress (e.g. antibiotics), predation, infection or competition; and (ii) an experiment in the field (host shift in plant virus ENMV). The project gathers skills in eco-evolutionary modelling, mathematical/numerical analysis, experimental evolution and statistics.

Contacts: Guillaume Martin (PI), Lionel Roques (co-PI) and Loïc Houde (administrator of the website)