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On the effect of phenotypic dimensionality on adaptation and optimality
Author(s) -
BrunUsan M.,
MarinRiera M.,
SalazarCiudad I.
Publication year - 2014
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1111/jeb.12516
Subject(s) - biology , natural selection , selection (genetic algorithm) , trait , phenotypic trait , evolutionary biology , population , multiplicative function , genetic load , phenotype , stabilizing selection , genetics , pleiotropy , statistics , genetic variation , mathematics , inbreeding , gene , demography , machine learning , computer science , mathematical analysis , sociology , programming language
What proportion of the traits of individuals has been optimally shaped by natural selection and what has not? Here, we estimate the maximal number of those traits using a mathematical model for natural selection in multitrait organisms. The model represents the most ideal conditions for natural selection: a simple genotype–phenotype map and independent variation between traits. The model is also used to disentangle the influence of fitness functions and the number of traits, n , per se on the efficiency of natural selection. We also allow n to evolve. Our simulations show that, for all fitness functions and even in the best conditions optimal phenotypes are rarely encountered, only for n = 1, and that a large proportion of traits are always far from their optimum, specially for large n . This happens to different degrees depending on the fitness functions (additive linear, additive nonlinear, Gaussian and multiplicative). The traits that arise earlier in evolution account for a larger proportion of the absolute fitness of individuals. Thus, complex phenotypes have, in proportion, more traits that are far from optimal and the closeness to the optimum correlates with the age of the trait. Based on estimated population sizes, mutation rates and selection coefficients, we provide an upper estimation of the number of traits that can become and remain adapted by direct natural selection.