Atlantic Bluefin Tuna (Thunnus thynnus) Biometrics and Condition.

The compiled data for this study represents the first Atlantic and Mediterranean-wide effort to pool all available biometric data for Atlantic bluefin tuna (Thunnus thynnus) with the collaboration of many countries and scientific groups. Biometric relationships were based on an extensive sampling (o...

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Bibliographic Details
Published in:PLOS ONE
Main Authors: Enrique Rodriguez-Marin, Mauricio Ortiz, José María Ortiz de Urbina, Pablo Quelle, John Walter, Noureddine Abid, Piero Addis, Enrique Alot, Irene Andrushchenko, Simeon Deguara, Antonio Di Natale, Mark Gatt, Walter Golet, Saadet Karakulak, Ai Kimoto, David Macias, Samar Saber, Miguel Neves Santos, Rafik Zarrad
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2015
Subjects:
R
Q
Online Access:https://doi.org/10.1371/journal.pone.0141478
https://doaj.org/article/a236444848bc4e1ea84ddaed1d61b1e7
Description
Summary:The compiled data for this study represents the first Atlantic and Mediterranean-wide effort to pool all available biometric data for Atlantic bluefin tuna (Thunnus thynnus) with the collaboration of many countries and scientific groups. Biometric relationships were based on an extensive sampling (over 140,000 fish sampled), covering most of the fishing areas for this species in the North Atlantic Ocean and Mediterranean Sea. Sensitivity analyses were carried out to evaluate the representativeness of sampling and explore the most adequate procedure to fit the weight-length relationship (WLR). The selected model for the WLRs by stock included standardized data series (common measurement types) weighted by the inverse variability. There was little difference between annual stock-specific round weight-straight fork length relationships, with an overall difference of 6% in weight. The predicted weight by month was estimated as an additional component in the exponent of the weight-length function. The analyses of monthly variations of fish condition by stock, maturity state and geographic area reflect annual cycles of spawning and feeding behavior. We update and improve upon the biometric relationships for bluefin currently used by the International Commission for the Conservation of Atlantic Tunas, by incorporating substantially larger datasets than ever previously compiled, providing complete documentation of sources and employing robust statistical fitting. WLRs and other conversion factors estimated in this study differ from the ones used in previous bluefin stock assessments.