Extensive salt marsh restoration is expected in the northern Gulf of Mexico over the next several decades, funded in part by settlements from the 2010 Deepwater Horizon oil spill. Understanding the ecological benefits of restored marshes over time is integral to setting appropriate restoration targets and performance criteria and in determining the restoration area needed to achieve desired restoration goals and offset quantified natural resource injuries. We present a method for quantifying anticipated ecological benefits associated with marsh restoration projects, particularly marsh creation or enhancement through the placement of dredged material, in the northern Gulf of Mexico. Using salt marsh vegetation (percent cover, aboveground biomass, and belowground biomass) and indicator faunal species (periwinkle snails and amphipods) as representative marsh community components, we used resource equivalency analysis (REA) to model projected ecological benefits over time and quantified total net project benefits for a hypothetical marsh creation project in Barataria Bay, Louisiana. Sensitivity analysis of the resulting model suggests that the recovery trajectories for each marsh component were the most important drivers of modeled restoration benefits and that model uncertainty was greatest for marsh fauna, which has limited data availability compared to marsh vegetation and high natural variability. Longer-term monitoring at restored restoration sites and/or targeted monitoring of older restoration projects would reduce variability in the recovery trajectories for the marsh community components examined in this case study and improve the reliability of the REA model for projecting benefits associated with salt marsh restoration.
CITATION STYLE
Fricano, G. F., Baumann, M. S., Fedeli, K., Schlemme, C. E., Carle, M. V., & Landry, M. (2020). Modeling Coastal Marsh Restoration Benefits in the Northern Gulf of Mexico. Estuaries and Coasts, 43(7), 1804–1820. https://doi.org/10.1007/s12237-020-00706-3
Mendeley helps you to discover research relevant for your work.