AI Article Synopsis

  • Deep-sea biodiversity is crucial for ecological functions but faces threats from various human activities, including deep-seabed mining, which has raised concerns about monitoring biodiversity changes.
  • The paper compares two methods for biodiversity assessment—morphology-based taxonomy and metabarcoding—focusing on their trade-offs in terms of cost-effectiveness and the types of data they provide.
  • The findings suggest that while morphology-based taxonomy is less cost-effective than metabarcoding, it has unique advantages, and combining both methods could improve monitoring and assessment during deep-seabed mining activities.

Article Abstract

Deep-sea biodiversity, a source of critical ecological functions and ecosystem services, is increasingly subject to the threat of disturbance from existing practices (e.g., fishing, waste disposal, oil and gas extraction) as well as emerging industries such as deep-seabed mining. Current scientific tools may not be adequate for monitoring and assessing subsequent changes to biodiversity. In this paper, we evaluate the scientific and budgetary trade-offs associated with morphology-based taxonomy and metabarcoding approaches to biodiversity surveys in the context of nascent deep-seabed mining for polymetallic nodules in the Clarion-Clipperton Zone, the area of most intense interest. For the dominant taxa of benthic meiofauna, we discuss the types of information produced by these methods and use cost-effectiveness analysis to compare their abilities to yield biological and ecological data for use in environmental assessment and management. On the basis of our evaluation, morphology-based taxonomy is less cost-effective than metabarcoding but offers scientific advantages, such as the generation of density, biomass, and size structure data. Approaches that combine the two methods during the environmental assessment phase of commercial activities may facilitate future biodiversity monitoring and assessment for deep-seabed mining and for other activities in remote deep-sea habitats, for which taxonomic data and expertise are limited. Integr Environ Assess Manag 2022;18:655-663. © 2021 SETAC.

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http://dx.doi.org/10.1002/ieam.4466DOI Listing

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