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

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.

Landscape effects on demersal fish revealed by field observations and predictive seabed modelling.

Nature conservation and fisheries management often focus on particular seabed features that are considered vulnerable or important to commercial species. As a result, individual seabed types are protected in isolation, without any understanding of what effect the mixture of seabed types within the landscape has on ecosystem functions. Here we undertook predictive seabed modelling within a coastal marine protected area using observations from underwater stereo-video camera deployments and environmental information (depth, wave fetch, maximum tidal speeds, distance from coast and underlying geology). The effect of the predicted substratum type, extent and heterogeneity or the diversity of substrata, within a radius of 1500 m around each camera deployment of juvenile gadoid relative abundance was analysed. The predicted substratum model performed well with wave fetch and depth being the most influential predictor variables. Gadus morhua (Atlantic cod) were associated with relatively more rugose substrata (Algal-gravel-pebble and seagrass) and heterogeneous landscapes, than Melanogrammus aeglefinus (haddock) or Merlangius merlangus (whiting) (sand and mud). An increase in M. merlangus relative abundance was observed with increasing substratum extent. These results reveal that landscape effects should be considered when protecting the seabed for fish and not just individual seabed types. The landscape approach used in this study therefore has important implications for marine protected area, fisheries management and monitoring advice concerning demersal fish populations.