3D habitat suitability maps of the 30 main commercial fish species from the Atlantic Ocean

• Main Authors: Valle, Mireia, Ramírez-Romero, Eduardo, Ibaibarriaga, Leire, Citores, Leire, Fernandes-Salvador, Jose A., Chust, Guillem
• Other Authors: Valle, Mireia [e-mail]
• Format: Dataset
• Language: English
• Published: VLIZ 2024
• Subjects: Marine/Coastal; 3D modelling; Biota; Data not evaluated; Ecological niches; Metadata conformant; NetCDF (Network Common Data Form); No limitations to public access; Species distribution; WGS84 (EPSG:4326); A; Atlantic; Clupea harengus Linnaeus; 1758; Conger conger (Linnaeus; 1758); Coryphaena hippurus Linnaeus; Engraulis encrasicolus (Linnaeus; Gadus morhua Linnaeus; Katsuwonus pelamis (Linnaeus; Lophius piscatorius Linnaeus; Mallotus villosus (Müller; 1776); Melanogrammus aeglefinus (Linnaeus; Merluccius merluccius (Linnaeus; Merlangius merlangus (Linnaeus; Micromesistius poutassou (Risso; 1827); Molva molva (Linnaeus; Pisces; Platichthys flesus (Linnaeus; Pleuronectes platessa Linnaeus; Pollachius virens (Linnaeus; Reinhardtius hippoglossoides (Walbaum; 1792); Scomber scombrus Linnaeus; Sebastes mentella Travin; Gadus morhua; Sebastes mentella
• Online Access: http://hdl.handle.net/10261/355862; https://marineinfo.org/id/dataset/8057

3-D habitat suitability maps (HSM) or probability of occurrence maps, built using Shape-Constrained Generalized Additive Models (SC-GAMs) for the 30 main commercial species of the Atlantic region. Predictor variables for each species were selected from: sea water temperature, salinity, nitrate, net primary productivity, distance to seafloor, distance to coast, and relative position to mixed layer depth. Each species HSM contains 47 maps, one per depth level from 0 to 1000 m. Probability values of each map range from 0 (unsuitable habitat) to 1 (optimal habitat). For depth levels below the 0.99 quantile of the depth values found on the species occurrence data, NA values were assigned. Maps have been masked to species native range regions. See Valle et al. (2024) in Ecological Modelling 490:110632 (https://doi.org/10.1016/j.ecolmodel.2024.110632), for more details. Peer reviewed