Offshore oil and gas platforms have a finite life of production operations. Once production ceases, decommissioning options for the platform are assessed. The role that a platform's jacket plays as fish habitat can inform the decommissioning decision. In this study, conducted along the crossbeams of a California platform jacket and using an ROV, we compared estimates of fish diversity and densities determined from a targeted "biological" survey with those from a replicated "structural" survey. We found that the water column fish species assemblages characterized by the two methods were similar. By contrast, the two survey methods yielded different species assemblages inhabiting the crossbeam at the platform jacket base. This difference occurred because, at least off California, the platform jacket base species diversity tends to be highest where the bottom crossbeam is undercut, creating sheltering sites for many species. Because the structural method inadequately imaged the seafloor-crossbeam interface, particularly where a gap occurred between crossbeam and seafloor, substantial numbers of fishes were not visible. While we cannot extrapolate from this study to all platforms' worldwide, it is clear that routine platform structural integrity surveys may be a valuable source for opportunistic marine community surveys. Intentional planning of the structural survey to incorporate relatively minor variations (e.g., maintaining fixed ROV distance from the infrastructure and consistent 90° camera angle) coupled with a deliberate consideration of the platform ecology (e.g., positioning the ROV to capture the seafloor-crossbeam interface) can substantially improve the effects on fish assemblage assessments from routine structural surveys without compromising the integrity assessment. We suggest that these biases should be both acknowledged and, understood when using routine structural surveys to inform platform ecology assessment. Additional consideration may be given to structural surveys that incorporate incremental adjustments to provide better data applicability to biological assessments.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654814PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242017PLOS

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