Scale dependence of sex ratio in wild plant populations: implications for social selection

Article
Authors:Sanderson, Brian , Department of BiologyUniversity of Virginia Augat, Malcolm, Department of BiologyUniversity of Virginia Taylor, Douglas, Department of BiologyUniversity of Virginia Brodie, Edmund, Department of BiologyUniversity of Virginia
Abstract:

Social context refers to the composition of an individual’s social interactants, including potential mates. In spatially structured populations, social context can vary among individuals within populations, generating the opportunity for social selection to drive differences in fitness functions among individuals at a fine spatial scale. In sexually polymorphic plants, the local sex ratio varies at a fine scale and thus has the potential to generate this opportunity. We measured the spatial distribution of two wild populations of the gynodioecious plant Silene vulgaris and show that there is fine-scale heterogeneity in the local distribution of the sexes within these populations. We demonstrate that the largest variance in sex ratio is among nearest neighbors. This variance is greatly reduced as the spatial scale of social interactions increases. These patterns suggest the sex of neighbors has the potential to generate fine-scale differences in selection differentials among individuals. One of the most important determinants of social interactions in plants is the behavior of pollinators. These results suggest that the potential for selection arising from sex ratio will be greatest when pollen is shared among nearest neighbors. Future studies incorporating the movement of pollinators may reveal whether and how this fine-scale variance in sex ratio affects the fitness of individuals in these populations.   

Keywords:
Context-dependence, gynodioecy, local mate competition, multilevel selection, population structure, Silene vulgaris
Publisher:
John Wiley & Sons Ltd.
Published Date:
December 18, 2015
Sponsoring Agency:
National Science FoundationUniversity of Virginia Open Access Fund