title: The evolution of gynodioecy on a lattice.
abstract: Gynodioecy is a breeding system in plants where populations consist of hermaphrodites and females. The females result from a genetic mutation which impairs pollen production in hermaphrodite plants. Most previous models for the evolution of gynodioecy do not take into account any spatial detail, which might be expected to play an important role in populations with short range interactions caused by poor or no locomotion. In this article we present a generalised mean-field analysis (which ignores any spatial detail), together with stochastic spatial simulations, to investigate the spatial effect on the evolution of gynodioecy. We show that, in a population of hermaphrodites where male sterility is caused by a dominant allele in a nuclear gene, mean-field calculations greatly underestimate the reproductive advantage females require to become viable under spatial constraints. This suggests that gynodioecy is less likely to evolve in plants with more localised pollination and seed setting. This may have implications for the evolution of dioecy, a breeding system in plants where the population consists of males and females, as gynodioecy is thought to be a route to dioecy. Our results also demonstrate that a lower frequency of females should be expected for gynodioecious populations when interactions are local. This is relevant when comparing the results of breeding experiments with observations of female frequency in the wild.
authors.affiliation: School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK. ppxtp@nottingham.ac.uk
authors.forename: T
authors.initials: T
authors.lastname: Preece
authors.forename: Y
authors.initials: Y
authors.lastname: Mao
mesh_terms: D005075:Biological Evolution; D003198:Computer Simulation; D057850:Hermaphroditic Organisms / Q000502:physiology; D008954:Models, Biological; D018521:Plant Physiological Phenomena / Q000502:physiology*; D012098:Reproduction / Q000502:physiology*; D012737:Sex Factors