FCE LTER Journal Articles


Water quality implications of hydrologic restoration alternatives in the Florida Everglades, United States


The use of models to generate future scenarios is an important tool for restoration planning. We used a scenario modeling approach to examine water quality implications of five options for Everglades hydrologic restoration. In oligotrophic Everglades wetlands, phosphorus (P) inputs exceeding 10 µg/L cause P accumulation in soils and a shift to cattail marsh. Everglades restoration seeks to improve wetland hydrology while ensuring that delivered water contains no more than 10 µg P/L (long-term average). Outputs from a landscape-scale ecological model, the Everglades Landscape Model (ELM), showed that P concentrations in new water inputs will be controlled by P uptake by constructed treatment wetlands and by the movement of legacy P. Benthic periphyton responds quickly to changes in P, initiating a eutrophication response cascade, so we used ELM output to drive periphyton response models that predicted abundance, quality, and composition. All five restoration scenarios had similar effects on these three attributes in Everglades National Park, but variable responses across the other wetland units depended on water delivery and legacy P mobilization. Periphyton biomass was considerably reduced in scenarios that maximized freshwater delivery, but predicted values for periphyton total P were below the legal P concentration maximum in most of the Everglades. Benthic algal edibility increased more than 4-fold, with the greatest increases in the deeper water areas. To meet water quality standards for the five restoration scenarios, we estimated that Everglades restoration should include an additional 105–156 km2 of treatment marshes upstream of surface water inflows to the landscape.


This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DEB-1237517, #DBI-0620409, and #DEB-9910514. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.



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