Abstract

Apart from its contribution to climate change, offshore oil and gas extraction is also a potential threat to the diversity and function of marine ecosystems. Routine monitoring of the environmental status of affected areas is therefore critical for effective management. While current morphology-based monitoring is relatively time consuming, costly and prone to identification bias, environmental DNA metabarcoding offers an attractive alternative for assessing the impacts of oil drilling, extraction or spills. However, to be ready for routine monitoring, its performance needs to be demonstrated through agreement with assessments based on physicochemical measurements and current bioindicators. To this end, we applied metabarcoding to sequence the metazoan (COI) and total eukaryotic (18S) benthic components. We targeted a range of sites, with a gradient of low to high level of impact, located near active production installations and reference sites, in the North and Barents Seas. Alpha diversity and community structure of both datasets correlated strongly with a physicochemical pressure index (PI) based on total hydrocarbons (THC), PAH16, Ba and Cu. Calculations of the macroinvertebrate-based Norwegian Sensitivity Index (NSI) based on COI metabarcoding data agreed well with corresponding morpho-taxonomy values and with the PI. Further, we identified a set of bioindicator taxa from both metabarcoding datasets, to develop novel biotic indices and demonstrate their predictive performance using cross-validation. Finally, we compared co-occurrence networks from impacted vs. non-impacted sites, to improve the understanding of the ecological consequences of impacts. Our study demonstrates that metabarcoding can act as a meaningful and relatively accurate complement to the current morpho-taxonomic approach.

Highlights

  • In order to ensure a balance between environmental impact and socioeconomic benefits, Norwegian legislation regulates the extent of offshore oil exploitation, and requires that extraction activities are routinely monitored according to a system that divides the Norwegian continental shelf into monitoring regions that are surveyed on a rotating basis (Norwegian Environment Agency, 2020)

  • Our results show that sediment eDNA metabarcoding can be used to directly and accurately infer impacts from offshore oil extraction, by utilising biotic indices such as the Norwegian Sensitivity Index (NSI), given sufficient spatial replication, even though the accuracy obtained did not reach the same accuracy as values inferred using morphotaxo­ nomic data

  • We verify that inferred NSI values based on cytochrome oxidase subunit I gene (COI) metabarcoding correlated and strongly agreed with morpho-taxonomic data and with a custom pressure index (PI) devel­ oped to take into account the main impacts caused by oil drilling and extraction in the studied habitats

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Summary

Introduction

In order to ensure a balance between environmental impact and socioeconomic benefits, Norwegian legislation regulates the extent of offshore oil exploitation, and requires that extraction activities are routinely monitored according to a system that divides the Norwegian continental shelf into monitoring regions that are surveyed on a rotating basis (Norwegian Environment Agency, 2020). In addition to physico­ chemical parameters, this monitoring regime includes sampling of benthic sediment macrofaunal communities for a subset of sampling stations based on perceived risk of anthropogenic impact. This “morphotaxonomic” monitoring component has been successful This, in turn, limits the spatial and temporal resolution possible, as sampling stations are typically surveyed only every three years (Bakke et al, 2011; Norwegian Environment Agency 2020) It causes a significant time lag, typically more than one year, between surveys and final monitoring reports, which may slow down environmental management due to failure to identify warning signs at an early stage. Morphological species identifications can be subject to human error and bias by individual taxonomists, and are limited by a shortage of taxonomic expertise and by cryptic species complexes

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