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Scientific and budgetary trade‐offs between morphological and molecular methods for deep‐sea biodiversity assessment

Le, Jennifer T.; Levin, Lisa A.; Lejzerowicz, Franck; Cordier, Tristan; Gooday, Andrew J. ORCID: https://orcid.org/0000-0002-5661-7371; Pawlowski, Jan. 2021 Scientific and budgetary trade‐offs between morphological and molecular methods for deep‐sea biodiversity assessment. Integrated Environmental Assessment and Management. https://doi.org/10.1002/ieam.4466

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Abstract/Summary

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 2021;00:1–9. © 2021 SETAC

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1002/ieam.4466
ISSN: 1551-3777
Date made live: 20 Jul 2021 18:57 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/530711

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