PS 87-227 - Coevolution by trait matching and exploitation barriers shape the structure of antagonistic and mutualistic networks in different ways

Friday, August 11, 2017
Exhibit Hall, Oregon Convention Center
Cecilia S. Andreazzi, Fundação Oswaldo Cruz, Brazil, Julia Astegiano, Universidad Nacional de Córdoba-CONICET, Argentina and Paulo R. Guimarães Jr., Departamento de Ecologia, Universidade de São Paulo, Brazil

Ecological interactions shape and are shaped by the evolution of interacting species. Interactions between antagonistic and mutualistic partners, such as predators and prey and pollinators and plants, are usually embedded in networks of species interactions that show non-random structural patterns. Since network structure modulates network dynamics, establishing the eco-evolutionary processes that shape species interaction patterns and thus that may modulate the response of species assemblages to biodiversity changes is a fundamental issue. Species traits, such as size and color, can modulate the likelihood of an interaction and thereby influence network structure and coevolutionary dynamics. Here, we explore if coevolution driven by two distinct functional relationships between traits and fitness, (i) trait matching and (ii) exploitation barriers, differently shape the structure of antagonistic and mutualistic networks. We used an adaptive network approach combining the evolution of species traits in a network context and the effects of trait evolution on the dynamics of the network itself. We parameterized these coevolutionary models with data on the structure of 122 antagonistic and 122 mutualistic networks.


Coevolution by trait matching better reproduced the structure of antagonistic networks, predicting the nestedness and the modularity of 72% and 69% of the empirical networks, respectively. The coevolutionary models poorly reproduced the structure of mutualistic networks. Coevolution by exploitation barriers reproduced the structure of the highest number of mutualistic networks, predicting the nestedness and the modularity of 20% and 22% of the empirical networks, respectively. For the remaining antagonistic and mutualistic networks, the two coevolutionary models underestimated nestedness and overestimated modularity. Interaction rewiring was determined by network connectance and varied from 0-50% of the interactions per time step (mean = 28%). Interaction rewiring was drastically reduced when differences in species traits had a strong effect on the probabilities of interactions. Coevolution by trait matching reduced interaction rewiring in antagonistic interactions, while coevolution by exploitation barriers reduced interaction rewiring in mutualistic interactions. In summary, the structure of antagonistic networks was better predicted by coevolution than mutualistic networks. Neutral processes and additional mechanisms may be relevant predictors for mutualistic networks than for antagonistic ones. Our results highlight the relevance of combining eco-evolutionary models with network studies to understand the eco-evolutionary dynamics of species traits in species-rich communities.