Case Study: Using a Combined Laboratory, Field, and Modeling Approach to Assess Oil Spill Impacts
The Deepwater Horizon (DWH) spill was the largest oil spill in US history, requiring an assessment of injuries to nearshore habitats and estuarine organisms. Developing a model of appropriate complexity is critical in an environmental assessment; models should be complex enough to adequately address the assessment objectives without being more complex than is needed. We present an approach that starts with a sensitivity analysis of an initial assumption-based model to prioritize model parameters and focus research efforts to reduce model uncertainty. We then develop a targeted research strategy that utilized laboratory, field, and intermediate modeling efforts to parameterize a final set of models of varying complexity to evaluate risk. We demonstrate this process in a case study of the small estuarine fish, the sheepshead minnow (Cyprinodon variegatus), exposed to weathered oil in Barataria Bay, LA, following the DWH oil spill.
KeywordsPopulation-level risk assessment Model complexity Uncertainty Spatially explicit
We thank Alex Almario, George Craven, Geraldine Cripe, Adam Glahn, Becky Hemmer, Julie Krzywka, Crystal Lilivois, Bob Quarles, Hannah Rutter, and Deborah Vivian for their support during the research described here. The views expressed in this chapter are those of the authors and do not necessarily reflect the views or policies of the US Environmental Protection Agency.
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