Dissemin is shutting down on January 1st, 2025

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Public Library of Science, PLoS Computational Biology, 4(10), p. e1003550, 2014

DOI: 10.1371/journal.pcbi.1003550

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The Evolution of Multivariate Maternal Effects

Journal article published in 2014 by Bram Kuijper ORCID, Rufus A. Johnstone, Stuart Townley
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Published online ; Journal Article ; Research Support, Non-U.S. Gov't ; There is a growing interest in predicting the social and ecological contexts that favor the evolution of maternal effects. Most predictions focus, however, on maternal effects that affect only a single character, whereas the evolution of maternal effects is poorly understood in the presence of suites of interacting traits. To overcome this, we simulate the evolution of multivariate maternal effects (captured by the matrix M) in a fluctuating environment. We find that the rate of environmental fluctuations has a substantial effect on the properties of M: in slowly changing environments, offspring are selected to have a multivariate phenotype roughly similar to the maternal phenotype, so that M is characterized by positive dominant eigenvalues; by contrast, rapidly changing environments favor Ms with dominant eigenvalues that are negative, as offspring favor a phenotype which substantially differs from the maternal phenotype. Moreover, when fluctuating selection on one maternal character is temporally delayed relative to selection on other traits, we find a striking pattern of cross-trait maternal effects in which maternal characters influence not only the same character in offspring, but also other offspring characters. Additionally, when selection on one character contains more stochastic noise relative to selection on other traits, large cross-trait maternal effects evolve from those maternal traits that experience the smallest amounts of noise. The presence of these cross-trait maternal effects shows that individual maternal effects cannot be studied in isolation, and that their study in a multivariate context may provide important insights about the nature of past selection. Our results call for more studies that measure multivariate maternal effects in wild populations. ; This work was supported by EPSRC grant EP/H031928/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript