Adapt or Perish: Evolutionary Rescue in a Gradually Deteriorating Environment

Abstract

We investigate the evolutionary rescue of a microbial population in a gradually deteriorating environment, through a combination of analytical calculations and stochastic simulations. We consider a population destined for extinction in the absence of mutants, which can only survive if mutants sufficiently adapted to the new environment arise and fix. We show that mutants that appear later during the environment deterioration have a higher probability to fix. The rescue probability of the population increases with a sigmoidal shape when the product of the carrying capacity and of the mutation probability increases. Furthermore, we find that rescue becomes more likely for smaller population sizes and/or mutation probabilities if the environment degradation is slower, which illustrates the key impact of the rapidity of environment degradation on the fate of a population. We also show that our main conclusions are robust across various types of adaptive mutants, including specialist and generalist ones, as well as mutants modeling antimicrobial resistance evolution. We further express the average time of appearance of the mutants that do rescue the population and the average extinction time of those that do not. Our methods can be applied to other situations with continuously variable fitnesses and population sizes, and our analytical predictions are valid in the weak-to-moderate mutation regime.

Predicting population genetic change in an autocorrelated random environment: Insights from a large automated experiment

“…Only recently has predictability in the dynamics (rather than outcome) of evolutionary change gained more prominence [8][9][10][11]. This question is indeed of crucial importance for many applications of evolution where the rate of change matters more than the end result, including evolutionary rescue, pest control, antibiotic resistance, and all contexts where strong eco-evolutionary dynamics involve a race between adaptation and population growth or decline [12][13][14][15][16].…”

A Branching Process Model of Evolutionary Rescue

“…The influence of these assumptions on the probability, tempo, and mode of evolutionary rescue is an active area of research. Different studies have incorporated, for example, a deteriorating environment [22], recombination [36], and density-dependent population regulation [22, 35].…”

“…The results of Orr and Unckless [24, 25] have been extended in multiple ways through studies of different kinds of models (e.g., birth-death processes [22], time-inhomogeneous branching processes [35], Feller diffusion processes [23], population genetic models [1, 36]), making a variety of assumptions (e.g., density-dependent population regulation [22, 35], population structure [35], rescue by multiple mutations [23, 26], variable mutational effects [1, 23, 26], epistasis [1, 26], recombination [36], environmental deterioration [22]).…”

Predicting population genetic change in an experimental stochastic environment

“…Only recently has predictability in the dynamics (rather than outcome) of evolutionary change gained more prominence (Doebeli & Ispolatov, 2014;Nosil et al, 2018Nosil et al, , 2020Rego-Costa et al, 2018). This question is of crucial importance for many applications of evolution where the rate of change matters more than the end result, including evolutionary rescue, pest control, antibiotic resistance, and all contexts with strong eco-evolutionary dynamics involving a race between adaptation and population growth (Anciaux et al, 2018;Gomulkiewicz & Holt, 1995;Kingsolver & Gomulkiewicz, 2003;Marrec & Bitbol, 2020;Orr & Unckless, 2014).…”