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Chelidonichthys lucerna (Linnaeus, 1758) Population Structure in the Northeast Atlantic Inferred from Landmark-Based Body Morphometry

  • Inês Ferreira
  • , Rafael Schroeder
  • , Estanis Mugerza
  • , Iñaki Oyarzabal
  • , Ian D. McCarthy
  • , Alberto T. Correia
  • Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR/CIMAR)
  • AZTI Fundazioa

Research output: Contribution to journalArticlepeer-review

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Abstract

The study of geometric morphometrics among stocks has proven to be a valuable tool in delineating fish spatial distributions and discriminating distinct population units. Variations in fish body morphology can be linked to genetic factors or to phenotypic adaptability in response to environmental variables. The tub gurnard (Chelidonichthys lucerna) is a demersal species that usually lives in the bottom of the continental shelf, being widely distributed along the northeast Atlantic, Mediterranean and Black seas. Worldwide interest in the species has increased since 2006, when ICES recognized its potential for commercial exploitation. However, despite its broad geographic occurrence, to date, research on C. lucerna population structure at large spatial scales is still lacking. In this paper, body geometric morphometrics, using a landmark-based truss network, was applied in order to discriminate C. lucerna populations caught in three different fishery grounds areas along the northeast Atlantic: Conwy Bay (United Kingdom), Biscay Bay (Spain) and Matosinhos (Portugal). The results obtained in this study revealed a high overall relocation success (95%) of samples to their original locations, thus demonstrating the existence of significant regional differences and indicating that we are dealing with different fish population units. Moreover, the data revealed a partial overlap between individuals from Spain and United Kingdom, suggesting that in geographically distant areas these populations may inhabit similar environments. However, to corroborate these findings, future works using a holistic approach with alternative and complimentary stock assessment tools (e.g., genetic and phenotypic natural tags) are highly recommended.
Original languageEnglish
Article number17
JournalBiology
Volume13
Issue number1
DOIs
Publication statusPublished - 27 Dec 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water

Keywords

  • General Agricultural and Biological Sciences
  • General Immunology and Microbiology
  • General Biochemistry, Genetics and Molecular Biology

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