PS 18-250 - Contrasting Topological and Quantitative Structures Drive Stability in Mutualistic Networks

Abstract: How do complex communities of interacting organisms persist? Ecologists have long been interested in how the structure, or patterns of interactions, in communities impact dynamical stability and long-term community persistence. Mutualistic networks, such as plant-pollinator communities, almost always exhibit a nested interaction pattern in nature. Such ubiquity in this structure is puzzling given the fact it seems to both reduce local stability and increase resource sharing (i.e. reduce resource complementarity). At the same time however, nestedness can increase community robustness to coextinction. One potential key to resolving this tension is by considering the strength of interactions in addition to the topological structure (presence or absence interactions). By adopting a community-matrix approach, we simulated networks of varying nestedness and assessed local stability. We predict that complementarity in interaction strengths can confer local stability to nested networks, ultimately resulting in networks that are both more locally stable and robust to coextinction perturbation. Such complementarity in interaction strengths has been predicted from adaptive foraging theory and has analytical justification for enhancing stability in networks with nested interaction patterns.

While we continue to run simulations and analyze model outcomes, preliminary results indicate that complementarity in interaction strengths can dramatically increase local stability in topologically nested networks relative to random, null-networks. The interplay of interaction strengths and topological structures can influence stability across several measures in ecological networks, thereby resulting in new and unexpected dynamics.