Avian injury quantification using the Shoreline Deposition Model and model sensitivities.

Deposition models, such as the Shoreline Deposition Model (SDM) used to quantify nearshore avian injuries resulting from the 2010 Deepwater Horizon (DWH) oil spill, were developed to improve the estimates of nearshore avian mortality resulting from the release of oil into coastal and marine environments. Unlike earlier approaches to injury quantification, such as simple counts of carcasses on the shoreline, a modeling approach allows trustees to evaluate the precision of their estimate (i.e., to develop a confidence interval) and can inform decision-making and the likely utility of additional primary data collection activities through sensitivity analyses. In this paper, we rely on published literature, actual DWH data, and a deposition model simulation to evaluate how different model inputs and assumptions can affect the accuracy and precision of model results. We find that the precision of deposition models is strongly affected by the length of time between subsequent shoreline searches, the underlying magnitude of carcass deposition, carcass persistence probabilities, and carcass detection probabilities. In addition, the accuracy of deposition model results may be affected by natural fluctuations in deposition rates. Given these findings, we recommend that natural resource trustees include an evaluation of future model uncertainty as part of their initial data collection efforts. This will allow them to deploy resources in a way that maximizes the utility of future deposition model results. We also identify several factors that do not need to be assessed immediately following a spill event, thereby potentially freeing resources for more time critical data collection efforts.