Sex-specific responses of phenotypic diversity to environmental variationTools Algar, Adam C. and López-Darias, Marta (2016) Sex-specific responses of phenotypic diversity to environmental variation. Ecography, 39 (8). pp. 715-725. ISSN 1600-0587 Full text not available from this repository.AbstractIdentifying the factors generating ecomorphological diversity within species can provide a window into the nascent stages of ecological radiation. Sexual dimorphism is an obvious axis of intraspecific morphological diversity that could affect how environmental variation leads to ecological divergence among populations. In this paper we test for sex-specific responses in how environmental variation generates phenotypic diversity within species, using the generalist lizard Gallotia galloti on Tenerife (Canary Islands). We evaluate two hypotheses: the first proposes that different environments have different phenotypic optima, leading to shifts in the positions of populations in morphospace between environments; the second posits that the strength of trait-filtering differs between environments, predicting changes in the volume of morphospace occupied by populations in different environments. We found that intraspecific morphological diversity, provided it is adaptive, arises from both shifts in populations’ position in morphospace and differences in the strength of environmental filtering among environments, especially at high elevations. However, effects were found only in males; morphological diversity of females responded little to environmental variation. These results within G. galloti suggest natural selection is not the sole source of phenotypic diversity across environments, but rather that variation in the strength of, or response to, sexual selection may play an important role in generating morphological diversity in environmentally diverse settings. More generally, disparities in trait–environment relationships among males and females also suggest that ignoring sex differences in studies of trait dispersion and clustering may produce misleading inferences.
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