IADIZA   20886
INSTITUTO ARGENTINO DE INVESTIGACIONES DE LAS ZONAS ARIDAS
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Revisiting the link between network structure and stability of mutualistic communities
Autor/es:
PERALTA G.; VÁZQUEZ D.; BRINGA E.; STOUFFER D.
Lugar:
Hunter Valley
Reunión:
Congreso; EcoTas; 2017
Resumen:
The structure of species interaction networks is usually associated with community stability. In mutualistic communities, network modularity (i.e. the extent to which subsets of species interact more frequently among themselves) has been reported to diminish species persistence. If this were the case, however, we would not expect empirical mutualistic networks to be modular, and yet this pattern is pervasive in nature. One possible explanation for this difference could be that mutualistic interactions are usually modelled as mutually beneficial for the interacting partners, even though there are both positive and negative effects associated with the consumption and supply of resources (e.g. damage to floral structures made by visitors). As such, the incorporation of the cost of mutualistic interactions into dynamic models could have a strong influence on the dynamics of the populations that interact within a community. Furthermore, these changes in the dynamics could alter the relationship between interaction network modularity and species persistence, as modularity should make it take longer for changes in species abundance to spread across the entire community, favouring species persistence. Here, we compared species persistence of mutualistic communities with different levels of modularity, using population dynamic models that included the cost of these interactions. We found that the negative effect modularity has on species persistence decreases as the cost of the mutualistic interaction increases (providing the cost never exceeds the benefit). Using more realistic models for mutualistic communities, including the cost of interactions, allow us to better understand the relationship between network structure and community stability.