The evolution of multivariate maternal effects.

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 suite...

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Main Authors: Bram Kuijper, Rufus A Johnstone, Stuart Townley
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-04-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC3983079?pdf=render
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spelling doaj-26e58f5e431847aba2439242b04d11e02020-11-25T01:13:29ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582014-04-01104e100355010.1371/journal.pcbi.1003550The evolution of multivariate maternal effects.Bram KuijperRufus A JohnstoneStuart TownleyThere 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.http://europepmc.org/articles/PMC3983079?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Bram Kuijper
Rufus A Johnstone
Stuart Townley
spellingShingle Bram Kuijper
Rufus A Johnstone
Stuart Townley
The evolution of multivariate maternal effects.
PLoS Computational Biology
author_facet Bram Kuijper
Rufus A Johnstone
Stuart Townley
author_sort Bram Kuijper
title The evolution of multivariate maternal effects.
title_short The evolution of multivariate maternal effects.
title_full The evolution of multivariate maternal effects.
title_fullStr The evolution of multivariate maternal effects.
title_full_unstemmed The evolution of multivariate maternal effects.
title_sort evolution of multivariate maternal effects.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2014-04-01
description 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.
url http://europepmc.org/articles/PMC3983079?pdf=render
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