Evolutionary Rescue over a Fitness Landscape

Yoann Anciaux (1) , Luis-Miguel Chevin (2) , Ophélie Ronce (1) , Guillaume Martin (1)

1 UMR ISEM - Institut des Sciences de l'Evolution de Montpellier
2 CEFE - Centre d’Ecologie Fonctionnelle et Evolutive

Evolutionary rescue describes a situation where adaptive evolution prevents the extinction of a population facing a stressing environment. Models of evolutionary rescue could in principle be used to predict the level of stress beyond which extinction becomes likely for species of conservation concern, or, conversely, the treatment levels most likely to limit the emergence of resistant pests or pathogens. Stress levels are known to affect both the rate of population decline (demographic effect) and the speed of adaptation (evolutionary effect), but the latter aspect has received less attention. Here, we address this issue using Fisher's geometric model of adaptation. In this model, the fitness effects of mutations depend both on the genotype and the environment in which they arise. In particular, the model introduces a dependence between the level of stress, the proportion of rescue mutants, and their costs before the onset of stress. We obtain analytic results under a strong-selection-weak-mutation regime, which we compare to simulations. We show that the effect of the environment on evolutionary rescue can be summarized into a single composite parameter quantifying the effective stress level, which is amenable to empirical measurement. We describe a narrow characteristic stress window over which the rescue probability drops from very likely to very unlikely as the level of stress increases. This drop is sharper than in previous models, as a result of the decreasing proportion of stress-resistant mutations as stress increases. We discuss how to test these predictions with rescue experiments across gradients of stress.

Mots clés: antibiotic resistance; evolutionary rescue; Fisher's geometric model; fitness landscape; mutation

Domaines: Evolution [q-bio.PE]

Yoann Anciaux, Luis-Miguel Chevin, Ophélie Ronce, Guillaume Martin. Evolutionary Rescue over a Fitness Landscape. Genetics, 2018, 209 (1), pp.265-279. ⟨10.1534/genetics.118.300908⟩. ⟨hal-02360786⟩