Understanding community dynamics is challenging because species respond differently to environmental conditions while interacting within networks of interactions with other species. Most food web models portray species populations or guilds as aggregate units, and thus have no capability to capture important interactions of organisms with their abiotic and biotic environments. This is a major shortcoming, because organism functional traits are known to have strong influences on population dynamics and population interactions. Building on previous research on individual-based modeling, we constructed a model that simulates fish population and food web dynamics for the last major un-dammed reach of the Upper Paraná River in Brazil. This model uses topographic information and hydrologic data to create a spatially explicit environment for food web dynamics. The model incorporates general functions for biological processes and functional traits of species to simulate organism performance and population dynamics and interactions. The model simulates environmental conditions in each landscape cell on a daily time step in response to hydrology, which is input as a regime.
Results/Conclusions
We set the rules for individual fish feeding, growth, reproduction and mortality based on conditions in its local environment. After validation of model components, we simulated contrasting scenarios of extreme wet years and extreme dry years in order to demonstrate the potential of the simulation model. Different hydrological regimes yielded fish assemblages with different structures. This was mostly because, during relatively dry years, fish spawning and recruitment decreased due to reduction in habitat availability, and predatory-prey interactions and competition for food resources intensified. Such outcomes match general predictions based on literature reports for tropical river-floodplain ecosystems. We conclude that spatially explicit individual-based models to have good potential for simulating ecosystem dynamics in support of natural resource management and policy.