The persistence of natural communities and ecosystems depends strongly on the maintenance of the structure of interactions among the many species that form part of them. Network ecology addresses this topic through the analysis of the structure and dynamics of complex, realistic ecological systems.
In spite of the remarkable advances of network ecology during the last decade, we are in a good position to move a step further and consider abandoning some simplistic assumptions about the dynamics of natural communities, whose use in modeling network dynamics limits our ability to understand, predict and manage the functioning of ecosystems in the context of the current biodiversity crisis. Two of these (wrong) assumptions are that interactions occur uninterruptedly through time and that, when they occur, their per capita strength is static. In this proposed research we expect to advance our understanding of the dynamics of ecological networks threatened by environmental perturbations, with special attention to the role of phenological features and adaptive dynamics of the constituent species.
Our research goals are (1) to analyze empirical relationships between phenological traits and topological centrality attributes of the species that compose complex ecological networks, (2) to evaluate the importance of phenological traits of the species for the robustness of complex ecological networks to species loss, (3) to evaluate the effects of phenological mismatch between interacting species on the long-term dynamics of complex ecological networks, under a set of realistic scenarios, (4) to analyze the effects of adaptive dynamics on the long-term dynamics of ecological networks subjected to environmental perturbation and (5) to analyze critically the approaches commonly used for modeling trophic behavior and adaptive dynamics in the context of complex ecological networks.
To accomplish this, for goals 1-3 we will use empirical datasets with accurate records of the topology of complex plant-pollination networks and the phenology of each component species. For goals 2-4 we will use somewhat sophisticated differential equation models for the phenological and long-term dynamics of the interacting species within complex ecological networks, pollutant dynamics and adaptive dynamics (goal 4) and analyze the models with numerical methods developed and tuned for them. For goal 5, we will perform a theoretical analysis of the current vs proper use of replicator equations in ecological networks. Our procedures involve major programming and computational challenges derived from the intricacy and high dimensionality of the model systems and the huge number of runs needed for experimental and sensitivity analyses. As results, we expect to find (a) an association between phenological and topological features of the species embedded in ecological networks, (b) sensitivity of networks to the loss of species according to their phenological traits, (c) effects of phenological mismatch being dependent on the quantity and properties of the species affected, (d) adaptive trophic behavior to weaken the harmful effects of pollutants on community stability and (e) an improved form for modeling the dynamics of trophic interactions in ecological networks.
Overall, as a continuation of our present research line, this study will allow understanding better how phenological features and adaptive behavior of the species shape the long-term dynamics of ecological networks as well as their responses to current biodiversity threats.
Lab website: www.ramos-jiliberto.cl