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Evolutionary rescue under demographic and environmental stochasticity

Kuangyi Xu,T. Vision,M. Servedio

Published 2023 in bioRxiv

ABSTRACT

Wild populations suffer two types of stochasticity: demographic stochasticity, from sampling error in offspring number, and environmental stochasticity, from temporal variation of the growth rate. By modeling evolution through phenotypic selection following an abrupt environmental change, we investigate how genetic and demographic dynamics, as well as effects of selection intensity after the environmental change and genetic variance on population survival, differ under demographic and environmental stochasticity. We find that the survival probability declines sharply with stronger selection under demographic stochasticity, but declines more continuously under environmental stochasticity. However, the genetic variance that confers the highest survival probability differs little under demographic and environmental stochasticity. Since the influence of demographic stochasticity is stronger when population size is smaller, a slow initial decline of genetic variance which allows quicker evolution and increase of fitness, is important for persistence. In contrast, the influence of environmental stochasticity is density-independent, so higher initial fitness becomes important for survival under strong environmental stochasticity. Combining both types of stochasticity shows that adding even weak environmental stochasticity can exaggerate the effects of different levels of demographic stochasticity on survival probabilities. Our work suggests the importance of explicitly distinguishing and measuring the forms of stochasticity for evolutionary rescue studies.

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