A life cycle model to assess the abundance of black scabbardfish a widely distributed fish with cryptic migrations

Type Article
Acceptance Date 2022-06-28 IN PRESS
Language English
Author(s) Ribeiro Figueiredo Ivone1, Natário Isabel2, Lorance PascalORCID3, Carvalho M. Lucília4
Affiliation(s) 1 : IPMA, 131673, Sea and Marine resources Department, Lisboa, Lisboa, Portugal
2 : Universidade Nova de Lisboa, 50106, Department of Mathematics, Lisboa, Lisboa, Portugal
3 : Ifremer Centre Atlantique, 70611, Laboratoire Ecologie et Modèles pour l'Halieutique, Halieutique Grand Ouest (HALGO) UMR DECOD (Dynamique et Durabilité des Ecosystèmes), Nantes, Nantes, France
4 : Universidade de Lisboa, 37809, Lisboa, Lisboa, Portugal
Source Canadian Journal of Fisheries and Aquatic Sciences (0706-652X) (Canadian Science Publishing) In Press
DOI 10.1139/cjfas-2021-0272
Keyword(s) Deep sea, Abundance, Bayesian Statistics, Fishery Management, Spatial Statistics.

The spatio-temporal dynamics of the black scabbardfish abundance in the northeast Atlantic is modeled using two linked Bayesian state-space models fitted to fishery dependent data from trawlers operating to the west and north off the British Isles and longliners off the west coast of Portugal. The stage structured life cycle models include species vital processes, fishing and are linked by the migration flow between the two areas. Although data on spawners abundance and recruitment are missing, the hierarchical nature of state-space models allows to conveniently represent black scabbardfish dynamics using reliable data from the two studied areas, which correspond to two of the three main fishing grounds for the species. The approach presented is somehow comparable to the few models developed for other species, like European eel, where spawning and recruitment occur at restricted and distant regions. This approach is likely to remain the only option for black scabbardfish stock assessment and fisheries monitoring, as it is unlikely that data about the unobserved spawning and early life stages become available in the near future.

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