Habitat Suitability Modeling for Oyster Reefs in Mobile Bay
Team Location: Marshall Space Flight Center
Authors: Danielle Bolte, Corey Manberg, Kristin Cooksey, Steve Padgett-Vasquez
Science Advisors/Mentors: Dr. Jeff Luvall, Maurice Estes, Dr. Mohammad Alhamdan
Abstract: Oyster reefs in Mobile Bay, Alabama, are both ecologically and economically important, yet they are diminishing in both health and extent. This decline has led to many attempts to restore the oyster reefs in Mobile Bay, with only limited success. The goal of this project was to create a mathematical habitat suitability model for oyster reefs in Mobile Bay, Alabama, to guide future restoration efforts and help them target areas of the bay most likely to support oyster reefs. The model was developed based on outputs from two hydrologic models: The LSPC watershed model and the EFDC hydrodynamic model. The EFDC model outputs were analyzed for salinity, temperature, depth, and TSS values for our study area in the southern portion of Mobile Bay and Mississippi Sound. The outputs were analyzed on a seasonal basis and a mathematical habitat classification performed based on the habitat requirements of the eastern oyster. The data from the seasonal analysis was then used to create the habitat suitability model using multiple regression techniques. Attempts were made to validate the model using aerial photography, Landsat imagery, HICO imagery, GIS data, nautical maps, and other means of determining the location of current oyster reefs. Efforts to use remote sensing were largely unsuccessful due to the turbidity of the water in the bay and the subtidal nature of the reefs. A 2003 nautical chart obtained from the NOAA website was the most recent available data on the location of oyster reefs and was used along with a pre-existing shapefile of 1968 oyster reefs to validate the habitat suitability model data. At the completion of the project, the model was transferred to groups in Mobile Bay attempting to restore the oyster reefs for further validation and use.
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