Fisheries-dependent and -independent data used to model the distribution of diadromous fish at-sea

Type Article
Date 2023-06
Language English
Author(s) Elliott Sophie A.M.ORCID1, 5, 7, Deleys NoémieORCID1, 2, Beaulaton LaurentORCID1, 6, Rivot EtienneORCID1, 5, Réveillac Elodie4, Acou AnthonyORCID1, 3
Affiliation(s) 1 : Management of Diadromous Fish in their Environment OFB, INRAE, Institut Agro, UPPA, 35042 Rennes, France
2 : French Research Institute for the Exploration of the Sea (IFREMER) Vigies, 44311, Nantes, France
3 : Centre d'expertise et de données sur le patrimoine naturel, Patrinat OFB-MNHN-CNRS-IRD, Station marine du Museum National d'Histoire Naturelle, 35800 Dinard, France
4 : Littoral, Environnement et Sociétés (LIENSs), UMR 7266, La Rochelle Université-CNRS, 17000 La Rochelle, France
5 : DECOD (Ecosystem Dynamics and Sustainability), Institut Agro, Ifremer, INRAE, Rennes, France
6 : Service Conservation et Gestion Durable des Espèces Exploitées, DRAS, OFB, U3E, 35042 Rennes, France
7 : Game & Wildlife Conservation Trust, Salmon & Trout Research Centre, East Stoke, Wareham BH20 6BB, UK
Source Data In Brief (2352-3409) (Elsevier BV), 2023-06 , Vol. 48 , P. 109107 (6p.)
DOI 10.1016/j.dib.2023.109107
Keyword(s) Commercial fisheries data, Scientific survey data, Presence-absence data, Fishing gear, Bycatch, Anadromous and catadromous fish, Distribution modelling

A database of 168 904 hauls covering the period from 1965 to 2019, from 46 surveys containing both fisheries-dependent (fishing vessels) and -independent data (scientific surveys) were collated from across the eastern Atlantic (Greater North Sea, Celtic Sea, Bay of Biscay and Iberian coast) and Metropolitan French Mediterranean waters. Data on diadromous fish (the European sturgeon (Acipenser sturio), allis shad (Alosa alosa), twait shad (Alosa fallax), Mediterranean twaite shad (Alosa agone), European eel (Anguilla anguilla), thinlip mullet (Chelon ramada), river lamprey (Lampetra fluviatilis), sea lamprey (Petromyzon marinus), smelt (Osmerus eperlanus), European flounder (Platichthys flesus), Atlantic salmon (Salmo salar) and the sea trout (Salmo trutta)) presence-absence was extracted and cleaned. The gear type and gear category which caught these species, their spatial location, and the date of capture (year and month), were also cleaned and standardised. Very little is known about diadromous fish at-sea and modelling data-poor and poorly detectable species such as diadromous fish is challenging for species conservation. Furthermore, databases which contain both scientific surveys and fisheries-dependent data on data-poor species at the temporal and geographical scale of this database are uncommon. This data could therefore be used to improve knowledge of diadromous fish spatial and temporal trends, and modelling techniques for data-poor species.

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