<p>Environmental Niche Model (ENM) outputs for 49 commercial fish species under climate change until the decade of 2060 around northwestern Europe. A model ensemble of 5 ENMs was used (MaxEnt, Generalised Linear Models, Support Vector Machine, Random Forest and BIOCLIM ), and projections were made under three different emission scenarios: A1B, RCP4.5 and RCP 8.5. The data shows model agreement (normalised to 1) for presence/absence decadal projections from 2020 to 2060. Additionally we provide data on model performance, with the Area Under the Curve (AUC) scores of the Receiver Operator Characteristic (ROC) curve for each of the 5 ENMs trained for each combination of fish species and emission scenario. Only ENMs with an AUC score of at least 0.7 were considered.</p>

<p>These data are Bayesian Additive Regression Tree model annual predictions for habitat suitability of marine fish species across a range of body sizes and belonging to different feeding guilds from 2010 to 2095 in 5 year intervals in the northeast Atlantic shelf seas. Feeding guilds were allocated based on classifications following Thompson <i>et al</i>. (2020).</p>

<p>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.</p><p>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.</p>