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

• Published in: Data in Brief
• Main Authors: Elliott, Sophie A.m., Deleys, Noémie, Beaulaton, Laurent, Rivot, Etienne, Réveillac, Elodie, Acou, Anthony
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier BV 2023
• Subjects: Commercial fisheries data; Scientific survey data; Presence-absence data; Fishing gear; Bycatch; Anadromous and catadromous fish; Distribution modelling; Anguilla anguilla; Atlantic salmon; European eel; Salmo salar
• Online Access: https://archimer.ifremer.fr/doc/00831/94262/101667.pdf; https://archimer.ifremer.fr/doc/00831/94262/101668.docx; https://doi.org/10.1016/j.dib.2023.109107; https://archimer.ifremer.fr/doc/00831/94262/

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.