The ecology of estuaries is shaped significantly by the extent of freshwater discharge which regulates abiotic processes and influences overall biological productivity. The Suwannee River Estuary of Florida’s Big Bend Coastline has historically been a productive and diverse estuarine ecosystem supported by significant freshwater inputs from the Suwannee River. In recent years, significant changes in land use and climatic conditions have resulted in lower discharges from the Suwannee. Our objectives were to explore the impact of freshwater inputs from the Suwannee River on the estuarine forage fish and sportfish communities downstream. We built a trophic-dynamic food web model in Ecopath with Ecosim to simulate different levels of discharge and evaluate how changes in discharge (drought and floods) would influence the trophic structure of the food web. Using the fitted model, we applied a series of different short-term and long-term flow projections under different climatic scenarios to evaluate impacts on fish functional groups and sportfish biomass. Simulations suggested that ecological production was more influenced by drought conditions than flood conditions. In our short-term scenarios, the drought simulations produced biomass changes that were approximately twice as substantial as the flood scenarios. When making comparisons to other published EwE models, we generally observed smaller changes in biomass production. Although this model focused on the influence of bottom-up effects, we observed strong top-down control of snook (Centropomus undecimalis) on the system. Several functional groups were particularly sensitive to changes in snook abundance which included spotted seatrout (Cynoscion nebulosus), sand seatrout (C. arenarius), and other members of the family Sciaenidae. Because snook have recently colonized the estuary, likely as a result of warmer winter temperatures, this finding has implications for climate change and natural resource management.

Detecting strong species interactions in food webs is often challenging due to difficulties related to adequate experimentation and the prevalence of generalist diets throughout nature. A promising new mathematical technique, empirical dynamic modeling (EDM), has demonstrated the potential to identify trophic interactions between populations by assessing time lags between associated time series. We attempted to analyze trophic linkages both within a subtropical estuary, as well as a simulated, theoretical ecosystem, to determine how energy moves through these systems. Additionally, we intended to evaluate the technique’s ability to detect biological relationships in ecosystems of different complexity. In both datasets, we were able to clearly identify strong consumer—resource interactions, which were generally related to bottom-up drivers. Overall, trophic connections at lower trophic levels were more easily detected than linkages higher in the food web. The ability of EDM to detect food web interactions appeared to be strongly influenced by the degree of observation error exhibited in the data. In the empirical dataset, several examples of bottom-up processes were clearly evident including effects of discharge, nutrients, and/or chlorophyll-a concentrations on anchovies (Anchoa spp.), Gulf flounder (Paralichthys albiguttata), and red drum (Sciaenops ocellatus). We also observed instances where lengths of time lags decreased as trophic level distances between consumers and resources decreased (for example, Anchovies, Gulf flounder, young-of-the-year seatrout). This analysis demonstrates the promising application of EDM to detect energetic pathways in systems of varying complexity.