Climate change (via sea-level rise [SLR] and changing weather patterns) is expected to significantly alter low-lying coastal and intertidal areas, which provide seasonal habitat for a variety of shoreline-dependent organisms. Many coastal military installations in Florida have coastal habitats with shoreline-dependent bird data that strongly illustrates their seasonal importance for birds. The objectives of this project were to: (1) assess current vulnerability scenarios and information on selected Florida military installations; (2) develop a set of habitat- and species-based models for the coastal threatened, endangered, and at-risk species (TER-S) Snowy Plover (Charadrius nivosus), Piping Plover (C. melodus), and Red Knot (Calidris canutus); (3) assess the current prediction level and assumptions of selected categories of TER-S models for use in benchmarking model performance and uncertainty levels; and (4) integrate the scientific data, modeling, and uncertainty results into a risk-informed, multi-criteria decision analysis (MCDA) system to allow systematic analysis of potential management options.

The technical approach utilized the Sea Level Affecting Marshes Model (SLAMM), MaxEnt species distribution model, and RAMAS-GIS metapopulation model to explore current and future habitat/spatial distribution/population states, as well as the spatial and temporal patterns of these uncertain results with global sensitivity and uncertainty analysis. Joint simulations of SLR at 0.2, 0.5, 1.0, 1.5, and 2.0 m were conducted at 30 m horizontal grid resolution for the Eglin Air Force Base (AFB)/Santa Rosa Island areas and for the entire Florida Gulf Coast (Pensacola to Naples) at 120 m grid resolution. MCDA was then used to rank alternative management solutions under potential future scenarios. The results from JSMAA and Logical Decisions software were compared. A spatial portfolio decision model was developed for selecting the optimal set of restoration alternatives in space and in time; this optimal portfolio set maximizes the balance between the habitat that supports TER-S, land requirements for training, and restoration costs.

Although uncertainty levels are high, consistent simulation results show key results in two areas: potential habitat losses and Snowy Plover population dynamics. Overall, projected habitat types at Eglin AFB are more stable over time than Tyndall AFB or the whole Gulf Coast of Florida, manifesting the least changes between 2010 and 2100 at SLR = 2.0 m in all land cover categories except tidal flats. The Gulf Coast simulations show that the Snowy Plover population size will decline faster than the area of habitat or carrying capacity, demonstrating the necessity of incorporating population dynamics when assessing the impacts of SLR on coastal species, particularly the resident Snowy Plover, wintering Piping Plover, and the migratory Red Knot. MCDA returned variable results in ranking preferred management alternatives because of the uncertainty in the system. Beach nourishment and exclosures were the preferred management tools and no action was the least preferred. MCDA also showed that a better understanding of species reproductive strategies will provide a more definitive alternative ranking.

The benefits of this research were: (1) integration of models that are generally applicable to any coastal ecosystem; (2) quantification of the drivers and uncertainty of ecogeomorphological processes; and (3) formulation of environmental management recommendations for the sustainability of Florida coastal ecosystems.