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  • 1
    Publication Date: 2024-03-11
    Description: We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to forecast changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean (from 18°N to 76°N and 36°E to 98°W). The VME indicator taxa included Lophelia pertusa , Madrepora oculata, Desmophyllum dianthus, Acanela arbuscula, Acanthogorgia armata, and Paragorgia arborea. The six deep-sea fish species selected were: Coryphaenoides rupestris, Gadus morhua, blackbelly Helicolenus dactylopterus, Hippoglossoides platessoides, Reinhardtius hippoglossoides, and Sebastes mentella. We used an ensemble modelling approach employing three widely-used modelling methods: the Maxent maximum entropy model, Generalized Additive Models, and Random Forest. This dataset contains: 1) Predicted habitat suitability index under present-day (1951-2000) and future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean, using an ensemble modelling approach.  2) Climate-induced changes in the suitable habitat of twelve deep-sea species in the North Atlantic Ocean, as determined by binary maps built with an ensemble modelling approach and the 10-percentile training presence logistic (10th percentile) threshold. 3) Forecasted present-day suitable habitat loss (value=-1), gain (value=1), and acting as climate refugia (value=2) areas under future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modelling approach and two thresholds: 10-percentile training presence logistic threshold (10th percentile) and maximum sensitivity and specificity (MSS). Refugia areas are those areas predicted as suitable both under present-day and future conditions. All predictions were projected with the Albers equal-area conical projection centred in the middle of the study area. The grid cell resolution is of 3x3 km.
    Keywords: ATLAS; A Trans-Atlantic assessment and deep-water ecosystem-based spatial management plan for Europe; Climate change; cold-water corals; Deep-sea; File format; File name; File size; fisheries; fishes; habitat suitability modelling; octocorals; scleractinians; species distribution models; Uniform resource locator/link to file; vulnerable marine ecosystems
    Type: Dataset
    Format: text/tab-separated-values, 384 data points
    Location Call Number Expected Availability
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  • 2
    Publication Date: 2024-04-20
    Description: In order to better describe both ancient and contemporary migratory flows associated with the North Atlantic abyssal fauna as part of the EC H2020 iAtlantic project, this dataset provides a collection of connectivity maps for several engineer species from hydrothermal springs on the Mid-Atlantic Ridge, from mussels of cold seeps on both sides of the Atlantic and, from deep-water corals in the NE Atlantic. These maps and the associated migrant flow matrices are derived from several demogenetic model analyses (dadi, moments and divmigrate) using multi-locus genotype data derived from a sub-sampling of the genomes of these target species. For each species, the dataset includes a series of shapefiles with a pdf map, the file of the geographic coordinates of the studied localities with a flow matrix, as well as the file of the multi-locus genotypes used to carry out the genetic analysis of the populations and establish the migratory flows.
    Keywords: Binary Object; Binary Object (File Size); Binary Object (Media Type); connectivity maps; deep corals; File content; genomic data; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; Model; North Atlantic; population genetics; seep mussels; vent fauna
    Type: Dataset
    Format: text/tab-separated-values, 4 data points
    Location Call Number Expected Availability
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