A cross-taxa study using environmental DNA/RNA metabarcoding to measure biological impacts of offshore oil and gas drilling and production operations. (February 2018)

• Record Type: Journal Article
• Authors: Laroche, Olivier; Wood, Susanna A.; Tremblay, Louis A.; Ellis, Joanne I.; Lear, Gavin; Pochon, Xavier
• Is Part Of: Marine pollution bulletin. Volume 127(2018)
• Page Start: 97
• Page End: 107
• Publication Date: 2018-02
• Subjects: Biomonitoring -- Benthic ecology -- High-throughput sequencing -- Bacteria 16S -- Eukaryotes 18S -- Foraminifera 18S; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2017.11.042
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: 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. Highlights: Bacterial (16S) communities are most responsive to O&G activities. Abundant hydrocarbonoclastic taxa were detected at petroleum impacted stations. Most indicator taxa, notably among macro-fauna, were highly specific to site conditions. eDNA metabarcoding was at least as efficient as traditional monitoring.