Seagrass habitat suitability modeling for the Alabama Barrier Island restoration assessment at Dauphin Island
Dates
Publication Date
2020-02-26
Time Period
2019
Citation
Wang, H., Enwright, N.M., Darnell, K.M., La Peyre, M.K., Cebrian, J., Kim, S.-C., Bunch, B., Stelly, S.J., Couvillion, B.R., Dalyander, P.S., Mickey, R.C., and Segura, M., 2020, Seagrass habitat suitability modeling for the Alabama Barrier Island restoration assessment at Dauphin Island: U.S. Geological Survey data release, https://doi.org/10.5066/P9B32VTE.
Summary
A barrier island seagrass habitat suitability index (HSI) model was developed for the Alabama barrier island restoration assessment at Dauphin Island. Shoal grass (Halodule wrightii) was selected as the representative species for seagrass community near Dauphin Island waters since H. wrightii is the dominant species (>62%) of seagrass communities in this area due to its rapid growth and tolerance to a wide range of salinity. Five water quality and morphological variables were selected and their relationships with habitat suitability were developed and incorporated into the seagrass HSI model for Dauphin Island restoration assessment: 1) mean salinity during the summer growing season, 2) mean temperature during the growing season, 3) [...]
Summary
A barrier island seagrass habitat suitability index (HSI) model was developed for the Alabama barrier island restoration assessment at Dauphin Island. Shoal grass (Halodule wrightii) was selected as the representative species for seagrass community near Dauphin Island waters since H. wrightii is the dominant species (>62%) of seagrass communities in this area due to its rapid growth and tolerance to a wide range of salinity. Five water quality and morphological variables were selected and their relationships with habitat suitability were developed and incorporated into the seagrass HSI model for Dauphin Island restoration assessment: 1) mean salinity during the summer growing season, 2) mean temperature during the growing season, 3) annual mean water depth, 4) mean total suspended solid/turbidity during the growing season, and 5) relative wave exposure index (REI). The final HSI score was calculated using the weighted geometric mean of the suitability scores of these individual variables. The seagrass HSI model was calibrated and validated using field data from National Park Service (NPS) Gulf Coast Inventory and Monitoring Network (GULN). Then, the seagrass HSI model was used to assess seagrass habitat suitability changes with and without restoration under future storminess and sea level (SL) conditions. The barrier island restoration actions being assessed include beach and dune restoration, marsh restoration, and placement of sand in the littoral zone. The storminess bins included realizations with a "medium" storminess, which included 1 to 3 storms over a 10-year period (that is, ST2) and a "high" storminess, which included 4 to 5 storms over an equal period (that is, ST3). The two future sea levels included a SL of 0.3 m (that is, SL1) and a SL of 1.0 m(that is, SL3) above the contemporary SL. Specifically, the medium storminess was paired with the 0.3 m above the contemporary SL (that is, ST2SL1) and the "high" storminess bin was paired with the 1.0 m above the contemporary SL (that is, ST3SL3). To account for intertidal marsh vertical accretion as a component of marsh morphology evolution, two scenarios were included in modeling: the U.S. Army Corps of Engineers (USACE) high and intermediate SLR curves in which marsh kept pace with SLR through accretion (1 cm/yr) through 2022 under high SLR curve whereas marsh kept pace with SLR by accretion for the entirety of the USACE intermediate curve. Inputs of water quality conditions under future storminess and sea level conditions were provided by the CE-QUAL-ICM model that was coupled with a geomorphology model and a hydrodynamic model. The relative wave exposure index (REI) for each scenario was estimated from wind climatology data and fetch and USGS Coastal National Elevation Database (CoNED) topography and bathymetry digital elevation model (TBDEM) that was updated by the landscape-position habitat model. This data release includes simulation results and metadata of seagrass habitat suitability scores at each spatial unit (grid cell) across the study domain: estuarine waters near Dauphin Island.
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Related External Resources
Type: Related Primary Publication
Enwright, N.M., Wang, H., Dalyander, S.P., and Godsey, E., eds., 2020, Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama: U.S. Geological Survey Open-File Report 2020–1003, 99 p.
This data release provides the details on the calculations of seagrass habitat suitability index values across the model domain and final model outputs. The HSI model simulations include eight scenarios for each of the six restoration actions and the future-without action: ST2SL1 under USACE high SLR curve and intermediate curve for initial year (Yr = 0) and a period after 10 years (Yr = 10), and ST3SL3 under USACE high SLR curve and intermediate curve for initial year (Yr = 0) and a period after 10 years (Yr = 10). There is a total of 60 simulation runs. Values of each habitat suitability variable from water quality model monthly output and the relative wave exposure index (REI) for the cells were calculated using the Esri ArcMap 10.7.1 for each simulation run. Landscape position-based habitat model outputs were used to calculate the mean water depth. A Python script (Python 2.7) was developed to read in the value of each habitat suitability parameter in spatial layers of the habitat suitability variables, calculate the individual suitability index based on the habitat suitability curves and determine the total habitat suitability index using the weighted geometric mean method, classify the suitability scores (0 to 1) into groups, and generate spatial a distribution map of seagrass habitat suitability designations (that is, unsuitable, marginally suitable, suitable, and highly suitable).
