A cross-taxa study using environmental DNA/RNA metabarcoding to measure biological impacts of offshore oil and gas drilling and production operations

Standardized ecosystem-based monitoring surveys are critical for providing information on marine ecosystem health. Environmental DNA/RNA (eDNA/eRNA) metabarcoding may facilitate such surveys by quickly and effectively characterizing multi-trophic levels. In this study, we assessed the suitability of eDNA/eRNA metabarcoding to evaluate changes in benthic assemblages of bacteria, Foraminifera and other eukaryotes along transects at three offshore oil and gas (O&G) drilling and production sites, and compared these to morphologically characterized macro-faunal assemblages. Bacterial communities were the most responsive to O&G activities, followed by Foraminifera, and macro-fauna (the latter assessed by morphology). The molecular approach enabled detection of hydrocarbon degrading taxa such as the bacteria Alcanivorax and Microbulbifer at petroleum impacted stations. Most identified indicator taxa, notably among macro-fauna, were highly specific to site conditions. Based on our results we suggest that eDNA/eRNA metabarcoding can be used as a stand-alone method for biodiversity assessment or as a complement to morphology-based monitoring approaches.

Citation

Laroche O, Wood SA, Tremblay LA, Ellis JI, Lear G, et al. (2018) A cross-taxa study using environmental DNA/RNA metabarcoding to measure biological impacts of offshore oil and gas drilling and production operations. Marine Pollution Bulletin 127: 97–107. Available: http://dx.doi.org/10.1016/j.marpolbul.2017.11.042.

Sponsors

The authors thank Olivia Johnston (Cawthron), Deanna Elvines (Cawthron) and Resource and Environmental Management Ltd. (REM; Nelson, New Zealand) for collection of samples and physico-chemical data, and taxonomist groups at Cawthron Institute (Fiona Gower) and REM for providing the macro infauna data. We express our gratitude to Simon Knapman (AWE Ltd) and Matiu Park (OMV NZ Ltd) for providing access to samples, valuable discussions and in-kind support. This research was co-funded by the Cawthron Institute Internal Investment Fund (IIF #15955) and the “Fonds de Recherche du Québec - Natures et Technologies” as part of a doctoral research scholarship (grant ID#184395).