Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species

The phenotypic variance–covariance matrix (P) describes the multivariate distribution of a population in phenotypic space, providing direct insight into the appropriateness of measured traits within the context of multicollinearity (i.e., do they describe any significant variance that is independent...

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Main Authors: Bertram, Susan M, Fitzsimmons, Lauren P, McAuley, Emily M, Rundle, Howard D, Gorelick, Root
Format: Online
Language:English
Published: Blackwell Publishing Ltd 2012
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297187/
id pubmed-3297187
recordtype oai_dc
spelling pubmed-32971872012-03-09 Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species Bertram, Susan M Fitzsimmons, Lauren P McAuley, Emily M Rundle, Howard D Gorelick, Root Original Research The phenotypic variance–covariance matrix (P) describes the multivariate distribution of a population in phenotypic space, providing direct insight into the appropriateness of measured traits within the context of multicollinearity (i.e., do they describe any significant variance that is independent of other traits), and whether trait covariances restrict the combinations of phenotypes available to selection. Given the importance of P, it is therefore surprising that phenotypic covariances are seldom jointly analyzed and that the dimensionality of P has rarely been investigated in a rigorous statistical framework. Here, we used a repeated measures approach to quantify P separately for populations of four cricket species using seven acoustic signaling traits thought to enhance mate attraction. P was of full or almost full dimensionality in all four species, indicating that all traits conveyed some information that was independent of the other traits, and that phenotypic trait covariances do not constrain the combinations of signaling traits available to selection. P also differed significantly among species, although the dominant axis of phenotypic variation (pmax) was largely shared among three of the species (Acheta domesticus, Gryllus assimilis, G. texensis), but different in the fourth (G. veletis). In G. veletis and A. domesticus, but not G. assimilis and G. texensis, pmax was correlated with body size, while pmax was not correlated with residual mass (a condition measure) in any of the species. This study reveals the importance of jointly analyzing phenotypic traits. Blackwell Publishing Ltd 2012-01 /pmc/articles/PMC3297187/ /pubmed/22408735 http://dx.doi.org/10.1002/ece3.76 Text en © 2011 The Authors. Published by Blackwell Publishing Ltd. http://creativecommons.org/licenses/by/2.5/ This is an open access article under the terms of the Creative Commons Attribution Non Commercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Bertram, Susan M
Fitzsimmons, Lauren P
McAuley, Emily M
Rundle, Howard D
Gorelick, Root
spellingShingle Bertram, Susan M
Fitzsimmons, Lauren P
McAuley, Emily M
Rundle, Howard D
Gorelick, Root
Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
author_facet Bertram, Susan M
Fitzsimmons, Lauren P
McAuley, Emily M
Rundle, Howard D
Gorelick, Root
author_sort Bertram, Susan M
title Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
title_short Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
title_full Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
title_fullStr Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
title_full_unstemmed Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
title_sort phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species
description The phenotypic variance–covariance matrix (P) describes the multivariate distribution of a population in phenotypic space, providing direct insight into the appropriateness of measured traits within the context of multicollinearity (i.e., do they describe any significant variance that is independent of other traits), and whether trait covariances restrict the combinations of phenotypes available to selection. Given the importance of P, it is therefore surprising that phenotypic covariances are seldom jointly analyzed and that the dimensionality of P has rarely been investigated in a rigorous statistical framework. Here, we used a repeated measures approach to quantify P separately for populations of four cricket species using seven acoustic signaling traits thought to enhance mate attraction. P was of full or almost full dimensionality in all four species, indicating that all traits conveyed some information that was independent of the other traits, and that phenotypic trait covariances do not constrain the combinations of signaling traits available to selection. P also differed significantly among species, although the dominant axis of phenotypic variation (pmax) was largely shared among three of the species (Acheta domesticus, Gryllus assimilis, G. texensis), but different in the fourth (G. veletis). In G. veletis and A. domesticus, but not G. assimilis and G. texensis, pmax was correlated with body size, while pmax was not correlated with residual mass (a condition measure) in any of the species. This study reveals the importance of jointly analyzing phenotypic traits.
publisher Blackwell Publishing Ltd
publishDate 2012
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297187/
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