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Bendima: A database for marine macro-invertebrate bycatch data designed to improve reproducibility in benthic ecology

  • Alexis Martin
  • , Jonathan Blettery
  • , Agnes Dettal
  • , Nicolas Rosset
  • , Yann Gousseau
  • Université Pierre et Marie Curie
  • Institut de Systématique, Evolution, Biodiversité (ISEB), UMR 7205 CNRS/Muséum National d'Histoire Naturelle
  • CNRS LTCI

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

2 Citations (Scopus)

Résumé

The difficulty of identifying marine macro-invertebrates and the lack of experts, added to the growing use of complex modeling approaches based on massive datasets, has led to a reproducibility crisis in benthic ecology. Improving the reliability of identification remains a key factor to increase the quality of raw data. We developed the Bendima database to manage benthic macro-invertebrate bycatch data from the scientific survey of the French Southern Ocean and Indian Ocean fisheries. This database is structured to store observations of macro-invertebrates in the form of images of the caught organisms associated with sampling effort data and molecular data, which allows for ongoing amendments to identifications and crossreferencing with barcode data. Once uploaded and stored as digital images, the Bendima observations data underpinning models can be fully assessed, criticized and compared. Here, we describe the Bendima system and provide an overview of the contents for teams involved in biodiversity database development, benthic ecology or fisheries monitoring.

langue originaleAnglais
Pages (de - à)325-334
Nombre de pages10
journalCybium
Volume47
Numéro de publication3
Les DOIs
étatPublié - 1 juil. 2023
Modification externeOui

SDG des Nations Unies

Ce résultat contribue à ou aux Objectifs de développement durable suivants

  1. SDG 14 - Vie sous l’eau
    SDG 14 Vie sous l’eau

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