Advanced

Assessing Multivariate Constraints to Evolution across Ten Long-Term Avian Studies.

Teplitsky, Celine; Tarka, Maja LU ; Møller, Anders P; Nakagawa, Shinichi; Balbontín, Javier; Burke, Terry A; Doutrelant, Claire; Gregoire, Arnaud; Hansson, Bengt LU and Hasselquist, Dennis LU , et al. (2014) In PLoS ONE 9(3).
Abstract
In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate... (More)
In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate selection coefficients to predict evolutionary responses to selection. Using Bayesian methods that facilitate the propagation of errors in estimates, we compare (1) the rate of adaptation based on predicted response to selection when including genetic correlations with predictions from models where these genetic correlations were set to zero and (2) the multivariate evolvability in the direction of current selection to the average evolvability in random directions of the phenotypic space. We show that genetic correlations on average decrease the predicted rate of adaptation by 28%. Multivariate evolvability in the direction of current selection was systematically lower than average evolvability in random directions of space. These significant reductions in the rate of adaptation and reduced evolvability were due to a general nonalignment of selection and genetic variance, notably orthogonality of directional selection with the size axis along which most (60%) of the genetic variance is found. These results suggest that genetic correlations can impose significant constraints on the evolution of avian morphology in wild populations. This could have important impacts on evolutionary dynamics and hence population persistence in the face of rapid environmental change. (Less)
Please use this url to cite or link to this publication:
author
, et al. (More)
(Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
PLoS ONE
volume
9
issue
3
publisher
Public Library of Science
external identifiers
  • pmid:24608111
  • wos:000332485800026
  • scopus:84897480891
ISSN
1932-6203
DOI
10.1371/journal.pone.0090444
project
BECC
CAnMove
language
English
LU publication?
yes
id
eec218b9-1ec7-4eca-a05f-69f1f1168c5a (old id 4383675)
date added to LUP
2014-04-25 09:36:01
date last changed
2017-11-19 03:54:38
@article{eec218b9-1ec7-4eca-a05f-69f1f1168c5a,
  abstract     = {In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate selection coefficients to predict evolutionary responses to selection. Using Bayesian methods that facilitate the propagation of errors in estimates, we compare (1) the rate of adaptation based on predicted response to selection when including genetic correlations with predictions from models where these genetic correlations were set to zero and (2) the multivariate evolvability in the direction of current selection to the average evolvability in random directions of the phenotypic space. We show that genetic correlations on average decrease the predicted rate of adaptation by 28%. Multivariate evolvability in the direction of current selection was systematically lower than average evolvability in random directions of space. These significant reductions in the rate of adaptation and reduced evolvability were due to a general nonalignment of selection and genetic variance, notably orthogonality of directional selection with the size axis along which most (60%) of the genetic variance is found. These results suggest that genetic correlations can impose significant constraints on the evolution of avian morphology in wild populations. This could have important impacts on evolutionary dynamics and hence population persistence in the face of rapid environmental change.},
  articleno    = {e90444},
  author       = {Teplitsky, Celine and Tarka, Maja and Møller, Anders P and Nakagawa, Shinichi and Balbontín, Javier and Burke, Terry A and Doutrelant, Claire and Gregoire, Arnaud and Hansson, Bengt and Hasselquist, Dennis and Gustafsson, Lars and de Lope, Florentino and Marzal, Alfonso and Mills, James A and Wheelwright, Nathaniel T and Yarrall, John W and Charmantier, Anne},
  issn         = {1932-6203},
  language     = {eng},
  number       = {3},
  publisher    = {Public Library of Science},
  series       = {PLoS ONE},
  title        = {Assessing Multivariate Constraints to Evolution across Ten Long-Term Avian Studies.},
  url          = {http://dx.doi.org/10.1371/journal.pone.0090444},
  volume       = {9},
  year         = {2014},
}