title: Phenotypic covariance structure and its divergence for acoustic mate attraction signals among four cricket species.
abstract: 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 (p(max)) 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, p(max) was correlated with body size, while p(max) was not correlated with residual mass (a condition measure) in any of the species. This study reveals the importance of jointly analyzing phenotypic traits.
authors.forename: Susan M
authors.initials: SM
authors.lastname: Bertram
authors.forename: Lauren P
authors.initials: LP
authors.lastname: Fitzsimmons
authors.forename: Emily M
authors.initials: EM
authors.lastname: McAuley
authors.forename: Howard D
authors.initials: HD
authors.lastname: Rundle
authors.forename: Root
authors.initials: R
authors.lastname: Gorelick