Planning for the future, algae bloom dynamics in water management and ecosystem restoration efforts

Paul Julian^1*Bill W Walker²Donatto Surratt³Stephen E Davis¹

• ¹Everglades Foundation, Palmetto Bay, United States
• ²Environmental Engineer, Concord, MA, United States
• ³National Park Service, Boynton Beach, Florida, United States

Eutrophication and chronic harmful algal blooms (HABs) are a challenge for ecosystem managers and restoration planners. Drivers of HABs include nutrient availability, temperature patterns, atmospheric conditions, rainfall-runoff relationships, and lake hydrodynamics. In South Florida, water is managed by water control plans that leverage restoration and water management infrastructure to control water levels in Lake Okeechobee and downstream systems. This study evaluated factors that contribute to algal blooms within Lake Okeechobee, assessed the long-term trends in algal biomass, and developed a modeling tool to evaluate lake algal bloom risk in the context of restoration and water management planning. For this study, Lake Okeechobee was divided into five distinct ecological zones based on physical (i.e., bathymetric), chemical (i.e., nutrient concentrations), and ecological (i.e., littoral, shallow, and open water zones) characteristics. Long-term changes in chlorophyll-a concentrations were interrelated with lake stage, volume, residence time, nitrogen, phosphorus, and temperature. Algal biomass, as indicated by concentrations of chlorophyll-a and phycocyanin, was significantly influenced by stage elevation, season, and location within the lake. Given the spatially unique characteristics of the lake and the potential drivers of algal blooms, two separate models were developed to evaluate scenarios. The first was an updated and expanded stage-based algal bloom indicator model used in prior restoration planning efforts. This model demonstrated the sensitivity of average summer chlorophyll-a concentration and bloom frequency across the lake, with littoral south, littoral west, and nearshore zones being the most responsive to changes in stage. The second model was a hierarchical model that used hydrodynamic and biogeochemical variables to predict chlorophyll-a concentrations across the lake. This model enhanced the understanding of summer chlorophyll-a concentrations across ecological zones. Moreover, these models both demonstrated how changes in water management regimes and restoration infrastructure can improve ecological conditions and significantly shift algal bloom potential for the lake. These models are valuable tools for understanding algal bloom potential and can be incorporated as a performance measure to evaluate future restoration planning efforts.