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The Oyster Habitat Suitability (HSI) layers were created to illustrate current conditions for oyster habitat suitability and how water quality conditions resulting from a 1/2 meter rise in sea level may change the extent and quality of suitable oyster habitat within the eastern Mississippi Sound and Mobile Bay.

 

The Oyster HSI utilizes important water quality parameters (Salinity, Temperature, Dissolved Oxygen, Depth and Total Suspended Solids) generated from an existing coupled hydrodynamic and water quality model as documented in (Bunch and others, 2018) to classify an area along a suitability spectrum from potentially High Suitability to potentially Low Suitability. 

The Oyster HSI was developed by the United States Geological Survey (USGS) for the National Fish and Wildlife Foundation (NFWF) Alabama Barrier Island Restoration Assessment Study.  As salinity, temperature, turbidity (or total suspended solids), dissolved oxygen and depth were found to be key factors regulating oyster growth and survive and often used to develop habitat suitability models for oyster restoration (Pollack and others, 2012; Soniat and others, 2013; Patterson and others, 2014; Linhoss and others, 2016),these water quality parameters were included in the HSI.  Additional details regarding the Oyster HSI can be found in (Enwright and others 2019).  

The Oyster HSI focuses on key water quality parameters and does not include all factors such as substrate suitability. In addition, simulated habitat suitability may be overestimated due to the underestimated total suspended sediment and spatial distribution of sediment oxygen demand from the water quality model due to 1) the organic portion not being entirely incorporated and 2) wind waves not being incorporated in the coupled hydrodynamic and water quality model (Kim and others, 2013 and Bunch and others, 2018).  The purpose of the HSI is intended to inform resource managers on potential locations where the water quality is best suited for the continued presence and/or recruitment of oysters. As additional data becomes available for other parameters (substrate type/condition) the model could be adapted to include additional variables.