This study attempts to quantify the multivariate genetic constraint, considering both within- and between-sex genetic (co variation, in a wild population experiencing a natural environment.
Thus the components of selection operating directly on ornamental traits are largely opposed by indirect selection on correlated traits, and multivariate genetic constraint on male ornamentation is a plausible explanation for the lack of response in attractiveness itself.
Although rare, other estimates of multivariate genetic constraint in the literature have provided stronger evidence of constraint (Blows et al. 2004; Hine and Blows 2006; Smith and Rausher 2008; Lewis et al. 2011; Simonsen and Stinchcombe 2011; Gosden et al. 2012; Williams et al. 2012; Teplitsky et al. 2014).
Explaining the maintenance of genetic variance for quantitative traits is a core area of research in evolutionary biology and a number of potential explanations, other than multivariate genetic constraint, have been proposed (Via and Lande 1985; Gillespie and Turelli 1989; Charlesworth and Hughes 2000; Johnson and Barton 2005).
We use factor analytic modeling of the genetic variance covariance matrix (G) to reduce the dimensionality of the problem and take a multivariate approach to estimating genetic constraints.
Here we extend the multivariate analysis of genetic constraint in the Rum red deer population to include both males and females and to study the effect of both genetic variances and within- and between-sex genetic covariances in generating constraint.
In the multivariate case, an additional source of genetic constraints may arise from genetic correlations.
Its multiple cuticular hydrocarbons, which serve as contact pheromones, have been extensively studied in the development of multivariate quantitative genetic approaches for exploring genetic constraints on adaptation (Blows et al. 2004; Chenoweth et al. 2010; McGuigan et al. 2011).
Our aim in this study was to use multivariate techniques to assess the potential for genetic constraints to the evolution of four life history traits in a wild population of red deer (C. elaphus) on the Isle of Rum, Scotland.
Commonly applied univariate and bivariate approaches to detecting genetic constraints can underestimate their prevalence, with important aspects potentially tractable only within a multivariate framework.
