Doctor of Philosophy (PhD)
Oceanography and Coastal Sciences
Soft-sediment benthic environments are amongst the largest marine ecosystems in the world and play important roles in many ecosystem functions. In recent years, exploitation of resources and unintentional impacts on deep-sea benthic environments has increased. The Deepwater Horizon oil spill of 2010 in the northern Gulf of Mexico (GoM) represented a prime example of this. The oil spill not only highlighted deficiencies of data and information on baseline conditions, but also represented an opportunity to learn more and develop better methods for the future. Deep-sea imaging platforms such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) have been growing in popularity as a minimally invasive means of exploring the deep-sea; and the use of industrial resources has increased due to availability of these technologies in the GoM region. This dissertation explores the use of industrial-based AUVs and ROVs as a means of studying benthic megafauna in the vicinity of the Deepwater Horizon Macondo well, and outlines a methodology that can be applied to current and future environmental monitoring efforts. Industrial ROVs were found to be generally superior to AUVs for specifically studying benthic megafauna. Simulations comparing different radial survey designs found that designs featuring longer transects with smaller transect spacing were more effective at estimating animal populations. In particular, the 15°, 250 m long transect radial survey design employed by the ROVs in this study was found to perform well for surveying benthic megafauna. To improve collection and analysis of the wealth of data extracted from the imagery, a customized database system was developed for use in this study and for similar future studies. Data collected via ROV one year after the oil spill was used to characterize benthic megafaunal communities and evaluate potential influences on them. It was found that community composition was primarily related to depth and, to a lesser degree, location in the northern GoM and anthropogenic disturbance to the seafloor. Overall, the methodology and results explored here represent an opportunity to standardize and improve future environmental monitoring efforts of this kind in the GoM and beyond.
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Secure the entire work for patent and/or proprietary purposes for a period of one year. Student has submitted appropriate documentation which states: During this period the copyright owner also agrees not to exercise her/his ownership rights, including public use in works, without prior authorization from LSU. At the end of the one year period, either we or LSU may request an automatic extension for one additional year. At the end of the one year secure period (or its extension, if such is requested), the work will be released for access worldwide.
Sharuga, Stephanie Marie, "Methods for the Characterization of Deep-Sea Benthic Megafauna in the Vicinity of the Deepwater Horizon Macondo Well" (2014). LSU Doctoral Dissertations. 1581.