This project was funded by the Gulf of Mexico Research Initiative (GoMRI).
The impacts of the Deepwater Horizon (DWH) oil spill on marine fish populations of the northern Gulf of Mexico are largely unknown. Of particular concern in the wake of the DWH event was the fate of pelagic fish eggs and larvae that were present in the water column at the time, as these are the most vulnerable life stages. Variability in the recruitment of marine fishes to adult populations is largely related to the variability encountered in vital rates (e.g., growth) during the larval stages, therefore DWH-related impacts on ichthyoplankton may have profound effects on future recruitment and fishery yields. In order to detangle DWH impacts from the highly variable “background noise” in the marine environment, a time series that covers a wide range of environmental conditions, as well as ‘baseline’, impact’, and ‘recovery’ periods is critical. Preliminary analysis of plankton samples collected during a long-term (2004-2011) survey has identified changes in both zooplankton and ichthyoplankton assemblage structures off the coast of Alabama during the DWH oil spill.

IMG_3612©S_HuynhThe overall goal of this study is to examine how the documented shifts in zooplankton community structure during the DWH event affected larval fish feeding, growth and condition (critical factors related to survivorship and recruitment success). Relative to fisheries oceanography and recruitment theory, the overarching question is, “Did the DWH event create a ‘mismatch’ scenario in the planktonic food web?” At the core of this study is access to data collected as part of a unique plankton survey that is the only source of pre-DWH zooplankton and ichthyoplankton data for the northern Gulf of Mexico region collected at high temporal (monthly sampling throughout; twice monthly during the DWH event) and spatial resolutions (three cross-shelf stations, each with vertically-discrete sampling).

The objectives of this study are to examine larval fish feeding, growth and condition (using established methodologies) and compare these parameters among ‘baseline’, ‘impact’, and ‘recovery’ periods.