Wednesday, August 6, 2008 - 8:30 AM

SYMP 10-2: Evolution of specialization in (meta)communities

Nicolas Loeuille, Universite Paris 6, Priyanga Amarasekare, University of California, Los Angeles, and Claire De mazancourt, McGill University.

Background/Question/Methods
We develop a set of models to understand how specialization evolves in a guild of competitors embedded in a community. We show that the likelihood of specialisation depends on the nature of their interaction with another guild. We thus considered the evolution of specialisation of two guilds when they interact in an trophic (as in a herbivore-plant or predator-prey) or mutualistic (as in a pollinator-plant) interaction.

Results/Conclusions
We consider both obligate interactions where species are completely inter-dependent and facultative interactions where plants or pollinators can survive in the absence of their mutualistic partners and the predator can survive in the absence of their prey.
Evolution of specialization is modeled using an adaptive dynamics approach in which one of the two interacting guild is allowed to evolve, while the other guild is maintained at two coexisting species. We then extend the approach to include coevolution of the two partners. Empirical datasets seem to suggest that such coevolution of specialization may produce nestedness in mutualistic networks (based on pollinator-plant interactions, Bascompte et al. 2006). It is unclear if such nestedness would also appear in networks of trophic interactions such as food webs. By including coevolution, we want to test if the adaptive dynamics indeed produce such nestedness in networks and if so, how the appearance of nestedness depends on the nature and the exclusivity of the interaction. Once we have identified the role of local adaptation in the evolution of specialization, we extend the model to include dispersal, to know how dispersal between contrasting local communities may change the evolution of specialization, hence the structure of the metacommunity, at the local and regional scales.