How the structure of interactions in biological communities affects their stability is a key question in ecology. In mutualistic networks in particular, empirical studies have found a number of consistent structural patterns, but how these link to mutualistic network stability remains controversial. In particular, nestedness is a nearly ubiquitous structure of empirical mutualistic networks, which is puzzling because on the one hand it appears to both reduce local stability and increase resource sharing (i.e. reduce resource complementarity). On the other hand, nestedness increases structural stability of networks. One element that could contribute to resolving these inconsistencies is better understanding how the topological structure (presence-absence of edges among nodes) of such networks interacts with their quantitative structure (the weighting of interaction strength). To investigate this topic, we used a community-matrix approach, to assess local stability, resilience, and reactivity in networks varying in topological and quantitative structure. We specifically explored the roles of quantitative complementarity and topological nestedness in conferring stability. We also gathered field data on plant pollinator networks with independent assessment of pollinator and plant abundances and interactions to assess whether the topological and quantitative patterns supported by our models are found in nature.
Results/Conclusions
While we continue to run simulations and analyze model outcomes, preliminary results indicate that topological nestedness on its own is destabilizing, but quantitative complementarity can interact with topological nestedness to dramatically increase local stability, relative to other structural configurations. Thus, seemingly opposing quantitative and topological structures can interact to enhance stability in ecological networks. At the time of abstract submission, we are unable to tie these results to field data as specimen identification was incomplete. We discuss interactions between topological and quantitative structures in the context of both mutualisms and other kinds of ecological interactions, and in the context of prediction in ecological systems.