Trade-offs and coexistence: A lottery model applied to fig wasp communities

Citation

Duthie AB, Abbott K & Nason J (2014) Trade-offs and coexistence: A lottery model applied to fig wasp communities. American Naturalist, 183 (6), pp. 826-841. https://doi.org/10.1086/675897

Abstract
Ecological communities in which organisms complete their life cycles on discrete ephemeral patches are common and often support an unusually large number of species. Explaining this diversity is challenging for communities of ecologically similar species undergoing preemptive competition, where classic coexistence mechanisms may not readily apply. We use nonpollinating fig wasps as a model community characterized by high diversity and preemptive competition to show how subadditive population growth and a trade-off between competitor fecundity and dispersal ability can lead to coexistence. Because nonpollinator species are often closely related, have similar life histories, and compete for the same discrete resources, understanding their coexistence is challenging given competitive exclusion is expected. Empirical observations suggest that nonpollinating fig wasp species may face a trade-off between egg loads and dispersal abilities. We model a lottery in which a species’ competitive ability is determined by a trade-off between fecundity and dispersal ability. Variation in interpatch distance between figs generates temporal variability in the relative benefit of fecundity versus dispersal. We show that the temporal storage effect leads to coexistence for a range of biologically realistic parameter values. We further use individual-based modeling to show that when species’ traits evolve, coexistence is less likely but trait divergence can result. We discuss the implications of this coexistence mechanism for ephemeral patch systems wherein competition is strongly preemptive.

Keywords
storage effect; coexistence; competition; fig wasp; trade-offs

Journal
American Naturalist: Volume 183, Issue 6

People

Dr Brad Duthie

Lecturer in Environmental Modelling, Biological and Environmental Sciences