Dimensionality of mate choice, sexual isolation, and speciation

Abstract

Multiple cues, across multiple sensory modalities, are involved in mate choice in a wide range of animal taxa. This multiplicity leads to the prediction that, in adaptive radiations, sexual isolation results from divergence in multiple dimensions. However, difficulties in directly measuring preferences and detecting multiple effects limit our ability to empirically assess the number of independent traits contributing to mate choice and sexual isolation. We present an approach to estimate the dimensionality of sexual isolation using mating trials across groups of related populations. We analyze nine radiations: seven in fruit flies (Drosophila) and one each in salamanders (Desmognathus) and cichlid fishes (Pseudotropheus). We find strong evidence that multiple latent traits-linear combinations of phenotypic traits and preferences-are responsible for the patterns of sexual isolation in all nine radiations but that dimensionality has a strong upper limit. Just two latent traits are implicated in the majority of cases. Mapping along latent trait axes tests predictions of sexual-selection models and allows correlation with specific phenotypic traits and functional components of mate choice. We find support for the role of stabilizing natural selection on the sexually selected (male) traits. In the cichlids, latent-trait axes incorporate male-coloration patterns and exhibit convergence as well as divergence among populations. In the salamanders, temporal patterning in sensory modalities and male vs. female preferences are reflected in different latent-trait axes.behavioral isolation | female preference | multidimensional scaling | prezygotic isolation | sexual selection

Computational mate choice: Theory and empirical evidence

“…However, when females assess several cues and signals across multiple sensory modalities, the internal representation of male attractiveness may be multidimensional, involving multiple preference functions (Fawcett and Johnstone, 2003b;Hohenlohe and Arnold, 2010). In these cases (see also Section 3), there may be a single DV that integrates information from multiple preference functions or there may be as many DVs as the number of preference functions.…”

Trait dimensionality explains widespread variation in local adaptation

“…In order to test our central theoretical prediction that local adaptation increases with dimensionality, we extended a method for estimating dimensionality originally designed for mate choice and behavioural isolation [31]. Here we apply this method to previously published reciprocal transplant data in which individuals from a set of source populations are tested in the corresponding sites, and fitness is measured for each pairwise test in the form of viability, fecundity or some composite fitness measure.…”

“…This model-based approach allows us, for any dataset of fitness in a reciprocal transplant experiment, to calculate a likelihood given any particular arrangement of phenotypic means and selective optima in a d-dimensional space. We thus use maximum likelihood techniques to find the best-fit arrangement of points given each value of d, and the likelihood of this arrangement is treated as the likelihood of that value of d. The dimensionality of selection inferred from the dataset is then estimated in two ways: first using corrected Akaike Information Criterion (AICc) and related statistics to identify the most supported value of d; and second using the effective dimensionality (n D ; [32]) of the points when fit in a high-dimensional space [31]. This second metric reflects the amount of variation among phenotypic means and selective optima that is concentrated along a primary axis; for instance, a value of n D ¼ 3.0 means that one-third of the variation among phenotypic means and selective optima lies along a single primary axis.…”

Multivariate sexual selection in a rapidly evolving speciation phenotype

“…Alternatively, particular song characters might be more or less constrained by genetic correlations with other traits, though at least among song characters, phenotypic correlations in this population are evidently weak [21]. It is also possible that divergence has been influenced by neutral genetic drift, which is expected to occur primarily in the direction concordant with additive genetic variation [37,38].…”