Journal Article
A Multidisciplinary Approach to Investigate Deep-Pelagic Ecosystem Dynamics in the Gulf of Mexico Following Deepwater Horizon
April B. Cook; Andrea M. Bernard; Kevin M. Boswell; Heather Bracken-Grissom; Marta D’Elia; Sergio deRada; Cole G. Easson; David English; Ron I. Eytan; Tamara Frank; Chuanmin Hu; Matthew W. Johnston; Heather Judkins; Chad Lembke; Jose V. Lopez; Rosanna J. Milligan; Jon A. Moore; Bradley Penta; Nina M. Pruzinsky; John A. Quinlan; Travis M. Richards; Isabel C. Romero; Mahmood S. Shivji; Michael Vecchione; Max D. Weber; R. J. David Wells; Tracey T. Sutton
Frontiers in Marine Science · Vol. 7 · 2020
Abstract
The pelagic Gulf of Mexico (GoM) is a complex system of dynamic physical oceanography (western boundary current, mesoscale eddies), high biological diversity, and community integration via diel vertical migration and lateral advection. Humans also heavily utilize this system, including its deep-sea components, for resource extraction, shipping, tourism, and other commercial activity. This utilization has had impacts, some with disastrous consequences. The Deepwater Horizon oil spill (DWHOS) occurred at a depth of ∼1500 m (Macondo wellhead), creating a persistent and toxic mixture of hydrocarbons and dispersant in the deep-pelagic (water column below 200 m depth) habitat. In order to assess the impacts of the DWHOS on this habitat, two large-scale research programs, described herein, were designed and executed. These programs, ONSAP and DEEPEND, aimed to quantitatively characterize the oceanic ecosystem of the northern GoM and to establish a time-series with which natural and anthropogenic changes could be detected. The approach was multi-disciplinary in nature and included in situ sampling, acoustic sensing, water column profiling and sampling, satellite remote sensing, AUV sensing, numerical modeling, genetic sequencing, and biogeochemical analyses. The synergy of these methodologies has provided new and unprecedented perspectives of an oceanic ecosystem with respect to composition, connectivity, drivers, and variability.