Date of Award

Fall 12-2015

Degree Type

Masters Thesis

Degree Name

Master of Science (MS)


Marine Science

Committee Chair

Scott P. Milroy

Committee Chair Department

Marine Science

Committee Member 2

Donald G. Redalje

Committee Member 2 Department

Marine Science

Committee Member 3

Stephan D. Howden

Committee Member 3 Department

Marine Science


Hypoxia events occur when dissolved oxygen concentrations fall below the minimum threshold (dissolved oxygen concentrations < 2 mg O2 L-1) necessary to avoid respiratory distress among aquatic organisms. In the Mississippi Sound and Bight, hypoxia is most prevalent from late-spring through late summer. Since hypoxia events can have dramatic effects on coastal fisheries, the spatial and temporal magnitude of hypoxia presents a clear threat to the productive fisheries in the northern Gulf of Mexico. Long-term hydrographic data were collected from eight sampling stations on a monthly basis from January 2009 to December 2011 along a cross-shelf transect from the mouth of Bay of St. Louis to the 20-meter isobath in the Mississippi Bight. These data were then used to develop statistical models to predict the geographic extent and intensity of hypoxia, informed by variables generally indicative of three main drivers of hypoxia: 1) water column stability/stratification; 2) eutrophication; and 3) water quality/clarity. Results from comparative analyses of river discharge, nutrient loading, and climatology data indicated statistically significant differences (p < 0.05) from year-to-year within self-similar months (e.g. June 2009 ≠ June 2010 ≠ June 2011); therefore there was insufficient evidence to justify pooling monthly data across multiple years in pursuit of a “typical” monthly condition. Month-to-month regression equations were derived from multiple regression analyses of dissolved oxygen resulting in (Adjusted) R2 values ranging from 0.718–0.979. Despite statistical differences between self-similar months, multi-year datasets were combined to develop “cumulative” monthly regressions which yielded (Adjusted) R2 values ranging from 0.531–0.900. These regression products can be used as statistical models to explore the impact of a particular variable on the development of hypoxia.