PS 23-59
Differential impact of oil-induced stress on Barataria Bay, East Bird’s Foot and Chandeleur Islands in the Gulf of Mexico due to the BP Deep Water Horizon oil spill

Tuesday, August 12, 2014
Exhibit Hall, Sacramento Convention Center
Kristen D. Shapiro, Land, Air, and Water Resources, University of California, Davis, Davis, CA
Shruti Khanna, Land, Air and Water Resources, University of California, Davis, Davis, CA
Susan L. Ustin, Land, Air & Water Resources, University of California Davis, Davis, CA
Background/Question/Methods

Oil spills have both short-term and long-term detrimental effects on coastal ecosystems. Coastal wetlands in the Gulf of Mexico comprise highly productive and richly diverse ecosystems including saline, brackish, intermediate and freshwater marshes as well as mangroves, which provide critically important habitat for both aquatic and terrestrial organisms. These ecosystems have varying sensitivity to oil contamination. We analyzed AVIRIS hyperspectral data flown over Bay Jimmy in Barataria Bay (BB), East Bird’s Foot (EBF) and Chandeleur Islands (CI) during September 2010 to assess the impact of the BP Deepwater Horizon (BP-DWH) Oil Spill on the health of the BB saltmarshes, EBF mixed marshes and CI mangroves.  We used four plant stress indexes (NDVI, mNDVI, ANIR, ARed) and three water content indices (NDII, WA980, WA1240) to compare the impact of oil on plant stress in the first five pixels along the heavily oiled shore to oilfree shore using t-tests and effect sizes.

Results/Conclusions

Each index consistently showed that plant stress was significantly higher along oiled shoreline compared to oilfree shoreline in BB and CI. In EBF, the results were weak and the NDII and ARed indices did not show a significant impact. A comparison of effect sizes showed that in each study site, different indices were the most sensitive to oil or showed the maximum effect. The effect of oil was strongest in CI (average Cohen’s d: 0.90), medium in BB (average Cohen’s d: 0.48) and weak in EBF (average Cohen’s d: 0.19).  This study illustrates the contribution of hyperspectral remote sensing in comparing impact of oil and recovery across different ecosystems after an oil spill.