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Cyanobacteria, prokaryotic photoautrophs referred to as “blue-green algae,” form harmful algal blooms in freshwater and estuarine systems that are capable of producing toxins, shading out submerged aquatic vegetation, prompting hypoxic/anoxic conditions, and restricting recreational activity. Several cyanobacteria genera are also capable of tapping into nutrient pools that are typically inaccessible to eukaryotic phytoplankton, such as through N2-fixation. N2-fixation results in the introduction of “new” nitrogen to the system. Such cyanobacteria-nutrient feedbacks complicate the development of water quality targets for systems affected by blooms, but are necessary to understand for the purpose of creating effective management plans. Thus, we seek to explore cyanobacteria-nitrogen feedbacks and identify environmental controls on N2-fixation. Important management questions we aim to address include: how can TMDLs be adjusted to prevent cyanobacteria blooms and N2-fixation? Which environmental variables correspond to high bloom and N2-fixation conditions? To tackle these questions, we evaluate a unique long-term (17.5 years) dataset composed of time series (monthly step) of the abundances of several phytoplankton and zooplankton phyla, water quality constituents, and hydrologic variables from Lake George, a flow-through lake located along the St. Johns River, Florida, USA. Using Granger causality analysis, a time series analysis approach, cyanobacteria and nutrient data were evaluated under both additive and interactive/non-additive assumptions to identify biological and physical drivers of cyanobacteria-nitrogen feedbacks. Causal effects and interactions, and associated magnitudes of influence, were compiled using network diagrams to map influential environmental factors across cyanobacteria taxa. These maps depict webs of interacting species and physicochemical drivers, which are then presented in the context of questions related to water management. |