Predicting evolutionary potential: A numerical test of evolvability measures

Evolution; International Journal of Organic Evolution
Thomas F HansenMihaela Pavlicev

Abstract

Despite sophisticated mathematical models, the theory of microevolution is mostly treated as a qualitative rather than a quantitative tool. Numerical measures of selection, constraints, and evolutionary potential are often too loosely connected to theory to provide operational predictions of the response to selection. In this paper, we study the ability of a set of operational measures of evolvability and constraint to predict short-term selection responses generated by individual-based simulations. We focus on the effects of selective constraints under which the response in one trait is impeded by stabilizing selection on other traits. The conditional evolvability is a measure of evolutionary potential explicitly developed for this situation. We show that the conditional evolvability successfully predicts rates of evolution in an equilibrium situation, and further that these equilibria are reached with characteristic times that are inversely proportional to the fitness load generated by the constraining characters. Overall, we find that evolvabilities and conditional evolvabilities bracket responses to selection, and that they together can be used to quantify evolutionary potential on time scales where the G-matrix remains rel...Continue Reading

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Citations

Jun 18, 2019·Evolution; International Journal of Organic Evolution·Josselin CloJoëlle Ronfort
Aug 11, 2020·Evolution Letters·Amanda K PettersenDustin J Marshall
Jun 14, 2019·Brain Structure & Function·Emiliano BrunerDiego Rasskin-Gutman
Jun 18, 2021·Evolution; International Journal of Organic Evolution·Christophe PélabonThomas F Hansen
Oct 23, 2021·Evolution; International Journal of Organic Evolution·Junya Watanabe

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